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Sample records for model selection treatment

  1. Augmented Self-Modeling as a Treatment for Children with Selective Mutism.

    Science.gov (United States)

    Kehle, Thomas J.; Madaus, Melissa R.; Baratta, Victoria S.; Bray, Melissa A.

    1998-01-01

    Describes the treatment of three children experiencing selective mutism. The procedure utilized incorporated self-modeling, mystery motivators, self-reinforcement, stimulus fading, spacing, and antidepressant medication. All three children evidenced a complete cessation of selective mutism and maintained their treatment gains at follow-up.…

  2. [Treatment of selective mutism].

    Science.gov (United States)

    Melfsen, Siebke; Warnke, Andreas

    2007-11-01

    Selective mutism is a communication disorder of childhood in which the child does not speak in specific social situations despite the ability to speak in other situations. A literature review was completed in order to provide practical guidelines for the assessment and treatment of children with selective mutism. There are many different behavioral approaches in the treatment of this disorder, e.g. contingency management, shaping, stimulus fading, escape-avoidance, self-modeling, learning theory approaches. A clearer diagnostic understanding of the disorder as part of anxiety or oppositional disorders needs to be realized prior to generalize an effective treatment for this disorder.

  3. Treatment Selection in Depression.

    Science.gov (United States)

    Cohen, Zachary D; DeRubeis, Robert J

    2018-03-01

    Mental health researchers and clinicians have long sought answers to the question "What works for whom?" The goal of precision medicine is to provide evidence-based answers to this question. Treatment selection in depression aims to help each individual receive the treatment, among the available options, that is most likely to lead to a positive outcome for them. Although patient variables that are predictive of response to treatment have been identified, this knowledge has not yet translated into real-world treatment recommendations. The Personalized Advantage Index (PAI) and related approaches combine information obtained prior to the initiation of treatment into multivariable prediction models that can generate individualized predictions to help clinicians and patients select the right treatment. With increasing availability of advanced statistical modeling approaches, as well as novel predictive variables and big data, treatment selection models promise to contribute to improved outcomes in depression. Expected final online publication date for the Annual Review of Clinical Psychology Volume 14 is May 7, 2018. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

  4. Coupled variable selection for regression modeling of complex treatment patterns in a clinical cancer registry.

    Science.gov (United States)

    Schmidtmann, I; Elsäßer, A; Weinmann, A; Binder, H

    2014-12-30

    For determining a manageable set of covariates potentially influential with respect to a time-to-event endpoint, Cox proportional hazards models can be combined with variable selection techniques, such as stepwise forward selection or backward elimination based on p-values, or regularized regression techniques such as component-wise boosting. Cox regression models have also been adapted for dealing with more complex event patterns, for example, for competing risks settings with separate, cause-specific hazard models for each event type, or for determining the prognostic effect pattern of a variable over different landmark times, with one conditional survival model for each landmark. Motivated by a clinical cancer registry application, where complex event patterns have to be dealt with and variable selection is needed at the same time, we propose a general approach for linking variable selection between several Cox models. Specifically, we combine score statistics for each covariate across models by Fisher's method as a basis for variable selection. This principle is implemented for a stepwise forward selection approach as well as for a regularized regression technique. In an application to data from hepatocellular carcinoma patients, the coupled stepwise approach is seen to facilitate joint interpretation of the different cause-specific Cox models. In conditional survival models at landmark times, which address updates of prediction as time progresses and both treatment and other potential explanatory variables may change, the coupled regularized regression approach identifies potentially important, stably selected covariates together with their effect time pattern, despite having only a small number of events. These results highlight the promise of the proposed approach for coupling variable selection between Cox models, which is particularly relevant for modeling for clinical cancer registries with their complex event patterns. Copyright © 2014 John Wiley & Sons

  5. Selection of resistant Streptococcus pneumoniae during penicillin treatment in vitro and in three animal models

    DEFF Research Database (Denmark)

    Knudsen, Jenny Dahl; Odenholt, Inga; Erlendsdottir, Helga

    2003-01-01

    Pharmacokinetic (PK) and pharmacodynamic (PD) properties for the selection of resistant pneumococci were studied by using three strains of the same serotype (6B) for mixed-culture infection in time-kill experiments in vitro and in three different animal models, the mouse peritonitis, the mouse....../ml was used in the rabbit tissue cage model. During the different treatment regimens, the differences in numbers of CFU between treated and control animals were calculated to measure the efficacies of the regimens. Selective media with erythromycin or different penicillin concentrations were used to quantify...

  6. Selection of resistant Streptococcus pneumoniae during penicillin treatment in vitro and in three animal models

    DEFF Research Database (Denmark)

    Knudsen, Jenny Dahl; Odenholt, Inga; Erlendsdottir, Helga

    2003-01-01

    thigh, and the rabbit tissue cage models. Treatment regimens with penicillin were designed to give a wide range of T(>MIC)s, the amounts of time for which the drug concentrations in serum were above the MIC. The mixed culture of the three pneumococcal strains, 10(7) CFU of strain A (MIC of penicillin, 0....../ml was used in the rabbit tissue cage model. During the different treatment regimens, the differences in numbers of CFU between treated and control animals were calculated to measure the efficacies of the regimens. Selective media with erythromycin or different penicillin concentrations were used to quantify...... and PD rules for treatment with beta-lactams: a maximum efficacy was seen when the T(>MIC) was >40 to 50% of the observation time and the ratio of the maximum concentration of the drug in serum to the MIC was >10. It was possible in all three models to select for the less-susceptible strains by using...

  7. A data mining based model for selecting type of treatment for kidney stone patients

    Directory of Open Access Journals (Sweden)

    Sepehri MM

    2009-09-01

    Full Text Available "n Normal 0 false false false EN-US X-NONE AR-SA MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:Arial; mso-bidi-theme-font:minor-bidi;} Background: Data mining as a multidisciplinary field is rooted in the fields such as statistics, mathematics, computer science and artificial intelligence and has been gaining momentum in scientific, managerial, and executive applications in health care. Data mining can be defined as the automated extraction of valuable, practical and hidden knowledge and information from large data. Applying data mining in medical records and data is of utmost importance for health care givers and providers and brings vital and valuable outcomes. Data mining can help doctors come up with better recommendations and plans for treatment which actually in many respects have significant impact on patients' life and satisfaction In this paper we have proposed and utilized data mining methods to extract hidden information in medical records of pelvis stone patients with ureteral stone. We have tried to design a decision support system model to be applicable for selecting type of treatment for these groups of patients."n"nMethods: We gathered needed information from Shahid Hashemi Nejad hospital. In this research we have used decision tree as a data mining tool, for selecting suitable treatment for patients with ureteral stone. This

  8. Development of effluent removal prediction model efficiency in septic sludge treatment plant through clonal selection algorithm.

    Science.gov (United States)

    Ting, Sie Chun; Ismail, A R; Malek, M A

    2013-11-15

    This study aims at developing a novel effluent removal management tool for septic sludge treatment plants (SSTP) using a clonal selection algorithm (CSA). The proposed CSA articulates the idea of utilizing an artificial immune system (AIS) to identify the behaviour of the SSTP, that is, using a sequence batch reactor (SBR) technology for treatment processes. The novelty of this study is the development of a predictive SSTP model for effluent discharge adopting the human immune system. Septic sludge from the individual septic tanks and package plants will be desuldged and treated in SSTP before discharging the wastewater into a waterway. The Borneo Island of Sarawak is selected as the case study. Currently, there are only two SSTPs in Sarawak, namely the Matang SSTP and the Sibu SSTP, and they are both using SBR technology. Monthly effluent discharges from 2007 to 2011 in the Matang SSTP are used in this study. Cross-validation is performed using data from the Sibu SSTP from April 2011 to July 2012. Both chemical oxygen demand (COD) and total suspended solids (TSS) in the effluent were analysed in this study. The model was validated and tested before forecasting the future effluent performance. The CSA-based SSTP model was simulated using MATLAB 7.10. The root mean square error (RMSE), mean absolute percentage error (MAPE), and correction coefficient (R) were used as performance indexes. In this study, it was found that the proposed prediction model was successful up to 84 months for the COD and 109 months for the TSS. In conclusion, the proposed CSA-based SSTP prediction model is indeed beneficial as an engineering tool to forecast the long-run performance of the SSTP and in turn, prevents infringement of future environmental balance in other towns in Sarawak. Copyright © 2013 Elsevier Ltd. All rights reserved.

  9. Using Peer Modeling and Differential Reinforcement in the Treatment of Food Selectivity

    Science.gov (United States)

    Sira, Bipon K.; Fryling, Mitch J.

    2012-01-01

    Behavior analysts have evaluated a wide range of assessment and treatment strategies in the area of feeding disorders. However, little is known about the effects of interventions employing peer modeling. This study extends upon the existing research on peer modeling and differential reinforcement with a 9-year-old boy diagnosed with autism who…

  10. A Review and Treatment Selection Model for Individuals with Developmental Disabilities Who Engage in Inappropriate Sexual Behavior.

    Science.gov (United States)

    Davis, Tonya N; Machalicek, Wendy; Scalzo, Rachel; Kobylecky, Alicia; Campbell, Vincent; Pinkelman, Sarah; Chan, Jeffrey Michael; Sigafoos, Jeff

    2016-12-01

    Some individuals with developmental disabilities develop inappropriate sexual behaviors such as public masturbation, disrobing, and touching others in an unwanted sexual manner. Such acts are problematic given the taboo nature of the behaviors and the potential for significant negative consequences, such as restricted community access, injury, and legal ramifications. Therefore, it is necessary to equip caregivers and practitioners with effective treatment options. The purpose of this paper is to review studies that have evaluated behavioral treatments to reduce inappropriate sexual behavior in persons with developmental disabilities. The strengths and weaknesses of each treatment are reviewed, and a model for treatment selection is provided.

  11. The effects of modeling contingencies in the treatment of food selectivity in children with autism.

    Science.gov (United States)

    Fu, Sherrene B; Penrod, Becky; Fernand, Jonathan K; Whelan, Colleen M; Griffith, Kristin; Medved, Shannon

    2015-11-01

    The current study investigated the effectiveness of stating and modeling contingencies in increasing food consumption for two children with food selectivity. Results suggested that stating and modeling a differential reinforcement (DR) contingency for food consumption was effective in increasing consumption of two target foods for one child, and stating and modeling a DR plus nonremoval of the spoon contingency was effective in increasing consumption of the remaining food for the first child and all target foods for the second child. © The Author(s) 2015.

  12. Modelling the consequences of targeted selective treatment strategies on performance and emergence of anthelmintic resistance amongst grazing calves

    Directory of Open Access Journals (Sweden)

    Zoe Berk

    2016-12-01

    Full Text Available The development of anthelmintic resistance by helminths can be slowed by maintaining refugia on pasture or in untreated hosts. Targeted selective treatments (TST may achieve this through the treatment only of individuals that would benefit most from anthelmintic, according to certain criteria. However TST consequences on cattle are uncertain, mainly due to difficulties of comparison between alternative strategies. We developed a mathematical model to compare: 1 the most ‘beneficial’ indicator for treatment selection and 2 the method of selection of calves exposed to Ostertagia ostertagi, i.e. treating a fixed percentage of the population with the lowest (or highest indicator values versus treating individuals who exceed (or are below a given indicator threshold. The indicators evaluated were average daily gain (ADG, faecal egg counts (FEC, plasma pepsinogen, combined FEC and plasma pepsinogen, versus random selection of individuals. Treatment success was assessed in terms of benefit per R (BPR, the ratio of average benefit in weight gain to change in frequency of resistance alleles R (relative to an untreated population. The optimal indicator in terms of BPR for fixed percentages of calves treated was plasma pepsinogen and the worst ADG; in the latter case treatment was applied to some individuals who were not in need of treatment. The reverse was found when calves were treated according to threshold criteria, with ADG being the best target indicator for treatment. This was also the most beneficial strategy overall, with a significantly higher BPR value than any other strategy, but its degree of success depended on the chosen threshold of the indicator. The study shows strong support for TST, with all strategies showing improvements on calves treated selectively, compared with whole-herd treatment at 3, 8, 13 weeks post-turnout. The developed model appeared capable of assessing the consequences of other TST strategies on calf populations.

  13. A Proposed Model for Selecting Measurement Procedures for the Assessment and Treatment of Problem Behavior.

    Science.gov (United States)

    LeBlanc, Linda A; Raetz, Paige B; Sellers, Tyra P; Carr, James E

    2016-03-01

    Practicing behavior analysts frequently assess and treat problem behavior as part of their ongoing job responsibilities. Effective measurement of problem behavior is critical to success in these activities because some measures of problem behavior provide more accurate and complete information about the behavior than others. However, not every measurement procedure is appropriate for every problem behavior and therapeutic circumstance. We summarize the most commonly used measurement procedures, describe the contexts for which they are most appropriate, and propose a clinical decision-making model for selecting measurement produces given certain features of the behavior and constraints of the therapeutic environment.

  14. Harnessing cognitive neuroscience to develop new treatments for improving cognition in schizophrenia: CNTRICS selected cognitive paradigms for animal models.

    Science.gov (United States)

    Moore, Holly; Geyer, Mark A; Carter, Cameron S; Barch, Deanna M

    2013-11-01

    Over the past two decades, the awareness of the disabling and treatment-refractory effects of impaired cognition in schizophrenia has increased dramatically. In response to this still unmet need in the treatment of schizophrenia, the Cognitive Neuroscience Treatment Research to Improve Cognition in Schizophrenia (CNTRICS) initiative was developed. The goal of CNTRICS is to harness cognitive neuroscience to develop a brain-based set of tools for measuring cognition in schizophrenia and to test new treatments. CNTRICS meetings focused on development of tasks with cognitive construct validity for use in both human and animal model studies. This special issue presents papers discussing the cognitive testing paradigms selected by CNTRICS for animal model systems. These paradigms are designed to measure cognitive constructs within the domains of perception, attention, executive function, working memory, object/relational long-term memory, and social/affective processes. Copyright © 2013. Published by Elsevier Ltd.

  15. Application of a body condition score index for targeted selective treatment in adult Merino sheep--A modelling study.

    Science.gov (United States)

    Cornelius, M P; Jacobson, C; Besier, R B

    2015-11-30

    This study aimed to establish whether sheep flock production losses due to nematode (worm) infections are typically greater in mature sheep selected for anthelmintic treatment at random compared to sheep selected for treatment based on low (poorer) body condition score (BCS). The study also examined the proportion of sheep in flocks that could be left untreated before production losses became evident, and projected worm egg pasture contamination. Sheep were monitored at two experimental sites in Western Australia (Mediterranean climate). Sheep were stratified for BCS, liveweight and faecal worm egg count (WEC) and allocated into treatment groups (treated or untreated), with equal numbers for each. Liveweight, BCS and WEC measurements were taken on 6 occasions at Farm A and 10 occasions at Farm B. Comparisons of sheep production (liveweight and BCS change) and pasture contamination potential (WEC) were conducted by generating "virtual flocks" of varying proportions sheep untreated (10%, 20%, 30%, 40%, and 50% untreated). For the comparison of the selection mode of sheep for treatment, the untreated sheep were either selected at random, or as the highest BCS animals at the commencement of observations. Univariate general linear models with least square difference post-hoc tests were used to examine differences between flocks for liveweight, BCS and WEC, and regression analysis was used to examine relationships between BCS and WEC, and liveweight and WEC. No difference in body weights was observed between flocks with varying proportions of ewes notionally left untreated at Farm B, and until more than 30% were left untreated at Farm A. There was no difference in BCS between flocks with varying proportions of ewes left untreated at either site. At no point were there differences in cumulative liveweight change or BCS between selection methods (BCS versus random) where the same proportion of sheep in virtual flocks were left untreated, suggesting that effort committed to

  16. Socio-economic determinants in selecting childhood diarrhoea treatment options in Sub-Saharan Africa: A multilevel model

    Directory of Open Access Journals (Sweden)

    Lawoko Stephen

    2011-03-01

    Full Text Available Abstract Background Diarrhoea disease which has been attributed to poverty constitutes a major cause of morbidity and mortality in children aged five and below in most low-and-middle income countries. This study sought to examine the contribution of individual and neighbourhood socio-economic characteristics to caregiver's treatment choices for managing childhood diarrhoea at household level in sub-Saharan Africa. Methods Multilevel multinomial logistic regression analysis was applied to Demographic and Health Survey data conducted in 11 countries in sub-Saharan Africa. The unit of analysis were the 12,988 caregivers of children who were reported to have had diarrhoea two weeks prior to the survey period. Results There were variability in selecting treatment options based on several socioeconomic characteristics. Multilevel-multinomial regression analysis indicated that higher level of education of both the caregiver and that of the partner, as well as caregivers occupation were associated with selection of medical centre, pharmacies and home care as compared to no treatment. In contrast, caregiver's partners' occupation was negatively associated with selection medical centre and home care for managing diarrhoea. In addition, a low-level of neighbourhood socio-economic disadvantage was significantly associated with selection of both medical centre and pharmacy stores and medicine vendors. Conclusion In the light of the findings from this study, intervention aimed at improving on care seeking for managing diarrhoea episode and other childhood infectious disease should jointly consider the influence of both individual SEP and the level of economic development of the communities in which caregivers of these children resides.

  17. Selective hydrolysis of wastewater sludge. Part 1. Model calculations and cost benefit analysis for Esbjerg West waste water treatment plant, Denmark

    Energy Technology Data Exchange (ETDEWEB)

    OEstergaard, N. (Eurotec West A/S (DK)); Thomsen, Anne Belinda; Thygesen, Anders; Bangsoe Nielsen, H. (Risoe National Laboratory, DTU (DK)); Rasmussen, Soeren (SamRas (DK))

    2007-09-15

    The project 'Selective hydrolysis of wastewater sludge' investigates the possibilities of utilizing selective hydrolysis of sludge at waste water treatment plants to increase the production of biogas based power and heat, and at the same time reduce power consumption for handling and treatment of nitrogen and sludge as well as for disposal of the sludge. The selective hydrolysis system is based on the fact that an anaerobic digestion before a hydrolysis treatment increases the hydrolysis efficiency, as the production of volatile organic components, which might inhibit the hydrolysis efficiency, are not produced to the same extent as may be the case for a hydrolysis made on un-digested material. Furthermore it is possible to separate ammonia from the sludge without using chemicals; it has, however, proven difficult to treat wastewater sludge, as the sludge seems to be difficult to treat in the laboratory using simple equipment. Esbjerg Wastewater Treatment Plant West, Denmark, is used as model plant for the calculations of the benefits using selective hydrolysis of sludge as if established at the existing sludge digester system. The plant is a traditional build plant based on the activated sludge concept in addition to traditional digester technology. The plant treats combined household and factory wastewater with a considerable amount of the wastewater received from the industries. During the project period Esbjerg Treatment Plant West went through considerable process changes, thus the results presented in this report are based on historical plant characteristics and may be viewed as conservative relative to what actually may be obtainable. (BA)

  18. Phenomenology and treatment of selective mutism.

    Science.gov (United States)

    Kumpulainen, Kirsti

    2002-01-01

    Selective mutism is a multidimensional childhood disorder in which, according to the most recent studies, biologically mediated temperament and anxiety components seem to play a major role. Several psychotherapy methods have been reported in case studies to be useful, but the disorder is commonly seen to be resistant to change, particularly in cases of long duration. Currently, behaviour modification and other cognitive methods, together with cooperation with the family and the school personnel, are recommended in the treatment of selective mutism. Selective serotonin reuptake inhibitors and selective monoamine oxidase inhibitors have also been reported to be helpful when treating children with selective mutism. At the moment, pharmacotherapy cannot be recommended as the treatment of first choice but if other methods of treatment are not helpful, medication can be included in the treatment scheme. Comprehensive evaluation and treatment of possible primary and comorbid problems that require treatment are also essential.

  19. Models selection and fitting

    International Nuclear Information System (INIS)

    Martin Llorente, F.

    1990-01-01

    The models of atmospheric pollutants dispersion are based in mathematic algorithms that describe the transport, diffusion, elimination and chemical reactions of atmospheric contaminants. These models operate with data of contaminants emission and make an estimation of quality air in the area. This model can be applied to several aspects of atmospheric contamination

  20. Modeling Natural Selection

    Science.gov (United States)

    Bogiages, Christopher A.; Lotter, Christine

    2011-01-01

    In their research, scientists generate, test, and modify scientific models. These models can be shared with others and demonstrate a scientist's understanding of how the natural world works. Similarly, students can generate and modify models to gain a better understanding of the content, process, and nature of science (Kenyon, Schwarz, and Hug…

  1. Selective plasma filtration for treatment of fulminant hepatic failure induced by d-galactosamine in a pig model

    OpenAIRE

    Ho, D W Y; Fan, S T; To, J; Woo, Y H; Zhang, Z; Lau, C; Wong, J

    2002-01-01

    Background: Plasma exchange may be useful for treating patients with fulminant hepatic failure but during the procedure growth factors that are important for hepatic regeneration are discarded. Addition of a selective plasma filter to the plasmapheresis circuit could eliminate protein bound toxic substances and retain growth factors for hepatic regeneration. This process is called selective plasma filtration.

  2. Selected System Models

    Science.gov (United States)

    Schmidt-Eisenlohr, F.; Puñal, O.; Klagges, K.; Kirsche, M.

    Apart from the general issue of modeling the channel, the PHY and the MAC of wireless networks, there are specific modeling assumptions that are considered for different systems. In this chapter we consider three specific wireless standards and highlight modeling options for them. These are IEEE 802.11 (as example for wireless local area networks), IEEE 802.16 (as example for wireless metropolitan networks) and IEEE 802.15 (as example for body area networks). Each section on these three systems discusses also at the end a set of model implementations that are available today.

  3. Selective Serotonin Reuptake Inhibitors for Treatment of Selective Mutism

    Directory of Open Access Journals (Sweden)

    Mazlum Çöpür

    2012-03-01

    Full Text Available Some authors suggest that selective mutism should be considered as a variant of social phobia or a disorder in the obsessive-compulsive spectrum. Recent studies indicate that pharmacological treatments may be effective in the treatment of selective mutism. In this article, four cases who were treated with citalopram and escitalopram are presented. The results indicate that the drugs were well tolerated, and the level of social and verbal interactions improved significantly. These findings have shown that citalopram and escitalopram can be considered in medication of selective mutism; nevertheless, it is essential that research be done with more cases than previous ones, in order to prove their accuracy

  4. Dynamic treatment selection and modification for personalised blood pressure therapy using a Markov decision process model: a cost-effectiveness analysis.

    Science.gov (United States)

    Choi, Sung Eun; Brandeau, Margaret L; Basu, Sanjay

    2017-11-15

    Personalised medicine seeks to select and modify treatments based on individual patient characteristics and preferences. We sought to develop an automated strategy to select and modify blood pressure treatments, incorporating the likelihood that patients with different characteristics would benefit from different types of medications and dosages and the potential severity and impact of different side effects among patients with different characteristics. We developed a Markov decision process (MDP) model to incorporate meta-analytic data and estimate the optimal treatment for maximising discounted lifetime quality-adjusted life-years (QALYs) based on individual patient characteristics, incorporating medication adjustment choices when a patient incurs side effects. We compared the MDP to current US blood pressure treatment guidelines (the Eighth Joint National Committee, JNC8) and a variant of current guidelines that incorporates results of a major recent trial of intensive treatment (Intensive JNC8). We used a microsimulation model of patient demographics, cardiovascular disease risk factors and side effect probabilities, sampling from the National Health and Nutrition Examination Survey (2003-2014), to compare the expected population outcomes from adopting the MDP versus guideline-based strategies. Costs and QALYs for the MDP-based treatment (MDPT), JNC8 and Intensive JNC8 strategies. Compared with the JNC8 guideline, the MDPT strategy would be cost-saving from a societal perspective with discounted savings of US$1187 per capita (95% CI 1178 to 1209) and an estimated discounted gain of 0.06 QALYs per capita (95% CI 0.04 to 0.08) among the US adult population. QALY gains would largely accrue from reductions in severe side effects associated with higher treatment doses later in life. The Intensive JNC8 strategy was dominated by the MDPT strategy. An MDP-based approach can aid decision-making by incorporating meta-analytic evidence to personalise blood pressure

  5. A Heckman Selection- t Model

    KAUST Repository

    Marchenko, Yulia V.

    2012-03-01

    Sample selection arises often in practice as a result of the partial observability of the outcome of interest in a study. In the presence of sample selection, the observed data do not represent a random sample from the population, even after controlling for explanatory variables. That is, data are missing not at random. Thus, standard analysis using only complete cases will lead to biased results. Heckman introduced a sample selection model to analyze such data and proposed a full maximum likelihood estimation method under the assumption of normality. The method was criticized in the literature because of its sensitivity to the normality assumption. In practice, data, such as income or expenditure data, often violate the normality assumption because of heavier tails. We first establish a new link between sample selection models and recently studied families of extended skew-elliptical distributions. Then, this allows us to introduce a selection-t (SLt) model, which models the error distribution using a Student\\'s t distribution. We study its properties and investigate the finite-sample performance of the maximum likelihood estimators for this model. We compare the performance of the SLt model to the conventional Heckman selection-normal (SLN) model and apply it to analyze ambulatory expenditures. Unlike the SLNmodel, our analysis using the SLt model provides statistical evidence for the existence of sample selection bias in these data. We also investigate the performance of the test for sample selection bias based on the SLt model and compare it with the performances of several tests used with the SLN model. Our findings indicate that the latter tests can be misleading in the presence of heavy-tailed data. © 2012 American Statistical Association.

  6. Wastewater treatment models

    DEFF Research Database (Denmark)

    Gernaey, Krist; Sin, Gürkan

    2011-01-01

    The state-of-the-art level reached in modeling wastewater treatment plants (WWTPs) is reported. For suspended growth systems, WWTP models have evolved from simple description of biological removal of organic carbon and nitrogen in aeration tanks (ASM1 in 1987) to more advanced levels including...... of WWTP modeling by linking the wastewater treatment line with the sludge handling line in one modeling platform. Application of WWTP models is currently rather time consuming and thus expensive due to the high model complexity, and requires a great deal of process knowledge and modeling expertise...

  7. Wastewater Treatment Models

    DEFF Research Database (Denmark)

    Gernaey, Krist; Sin, Gürkan

    2008-01-01

    The state-of-the-art level reached in modeling wastewater treatment plants (WWTPs) is reported. For suspended growth systems, WWTP models have evolved from simple description of biological removal of organic carbon and nitrogen in aeration tanks (ASM1 in 1987) to more advanced levels including...... the practice of WWTP modeling by linking the wastewater treatment line with the sludge handling line in one modeling platform. Application of WWTP models is currently rather time consuming and thus expensive due to the high model complexity, and requires a great deal of process knowledge and modeling expertise...

  8. Treatment of selective mutism: focus on selective serotonin reuptake inhibitors.

    Science.gov (United States)

    Kaakeh, Yaman; Stumpf, Janice L

    2008-02-01

    Abstract Selective mutism is a pediatric psychiatric disorder that occurs when a child consistently fails to speak in specific situations in which speaking is expected, such as at school and social gatherings, but speaks appropriately in other settings. Selective mutism often is diagnosed when a child starts school and does not talk to teachers or peers, but talks to family members at home; the condition is frequently accompanied by anxiety and shyness. Although the underlying etiology of the condition remains unclear, psychotherapy is the preferred initial treatment, with the support of parents and teachers. If the child does not respond to psychotherapy, addition of pharmacologic treatment should be considered, depending on the severity of symptoms and presence of other illnesses. Although data are limited to case reports and trials with small patient populations and short follow-up periods, some patients with selective mutism respond to therapy with selective serotonin reuptake inhibitors (SSRIs). Fluoxetine is the most studied SSRI as treatment for the condition, although further investigation is required to determine the optimal dosage and duration of therapy.

  9. Treatment selection for tonsillar squamous cell carcinoma

    Directory of Open Access Journals (Sweden)

    Yao-Yuan Kuo

    2013-04-01

    Conclusion: Both primary surgery and RT/CRT organ preservation are effective treatments for tonsillar SCC. Single modality treatment, either surgery or RT/CRT, can typically be provided for stage I–II diseases. Although RT/CRT organ preservation is used more frequently for stage III–IV tonsillar SCC in recent years, primary surgery combined with adjuvant therapy still achieves equivalent outcomes. Multidisciplinary pretreatment counseling and the facilities and personnel available are therefore important for decision-making. In addition, if RT/CRT organ preservation is selected as the primary treatment, tumor tonsillectomy is not indicated.

  10. Endovascular treatment of diabetic foot in a selected population of patients with below-the-knee disease: is the angiosome model effective?

    Science.gov (United States)

    Fossaceca, Rita; Guzzardi, Giuseppe; Cerini, Paolo; Cusaro, Claudio; Stecco, Alessandro; Parziale, Giuseppe; Perchinunno, Marco; De Bonis, Marco; Carriero, Alessandro

    2013-06-01

    To evaluate the efficacy of percutaneous transluminal angioplasty (PTA) in a selected population of diabetic patients with below-the-knee (BTK) disease and to analyze the reliability of the angiosome model. We made a retrospective analysis of the results of PTA performed in 201 diabetic patients with BTK-only disease treated at our institute from January 2005 to December 2011. We evaluated the postoperative technical success, and at 1, 6, and 12 months' follow-up, we assessed the rates and values of partial and complete ulcer healing, restenosis, major and minor amputation, limb salvage, and percutaneous oximetry (TcPO2) (Student's t test). We used the angiosome model to compare different clinicolaboratory outcomes in patients treated by direct revascularization (DR) from patients treated with indirect revascularization (IR) technique by Student's t test and the χ(2) test. At a mean ± standard deviation follow-up of 17.5 ± 12 months, we observed a mortality rate of 3.5 %, a major amputation rate of 9.4 %, and a limb salvage rate of 87 % with a statistically significant increase of TcPO2 values at follow-up compared to baseline (p < 0.05). In 34 patients, treatment was performed with the IR technique and in 167 by DR; in both groups, there was a statistically significant increase of TcPO2 values at follow-up compared to baseline (p < 0.05), without statistically significant differences in therapeutic efficacy. PTA of the BTK-only disease is a safe and effective option. The DR technique is the first treatment option; we believe, however, that IR is similarly effective, with good results over time.

  11. Endovascular Treatment of Diabetic Foot in a Selected Population of Patients with Below-the-Knee Disease: Is the Angiosome Model Effective?

    Energy Technology Data Exchange (ETDEWEB)

    Fossaceca, Rita, E-mail: rfossaceca@hotmail.com; Guzzardi, Giuseppe, E-mail: guz@libero.it; Cerini, Paolo, E-mail: cerini84@hotmail.it [' Maggiore della Carita' Hospital, University of Eastern Piedmont ' Amedeo Avogadro' , Department of Diagnostic and Interventional Radiology (Italy); Cusaro, Claudio, E-mail: claudio.cusaro@libero.it [' Maggiore della Carita' Hospital, Department of Diabetic Complications (Italy); Stecco, Alessandro, E-mail: a.stecco@libero.it; Parziale, Giuseppe, E-mail: giuseppeparziale@gmail.com; Perchinunno, Marco, E-mail: marcoperchinunno@gmail.com; Bonis, Marco De, E-mail: marco_deb@hotmail.it; Carriero, Alessandro, E-mail: profcarriero@virgilio.it [' Maggiore della Carita' Hospital, University of Eastern Piedmont ' Amedeo Avogadro' , Department of Diagnostic and Interventional Radiology (Italy)

    2013-06-15

    Purpose. To evaluate the efficacy of percutaneous transluminal angioplasty (PTA) in a selected population of diabetic patients with below-the-knee (BTK) disease and to analyze the reliability of the angiosome model. Methods. We made a retrospective analysis of the results of PTA performed in 201 diabetic patients with BTK-only disease treated at our institute from January 2005 to December 2011. We evaluated the postoperative technical success, and at 1, 6, and 12 months' follow-up, we assessed the rates and values of partial and complete ulcer healing, restenosis, major and minor amputation, limb salvage, and percutaneous oximetry (TcPO{sub 2}) (Student's t test). We used the angiosome model to compare different clinicolaboratory outcomes in patients treated by direct revascularization (DR) from patients treated with indirect revascularization (IR) technique by Student's t test and the {chi}{sup 2} test. Results. At a mean {+-} standard deviation follow-up of 17.5 {+-} 12 months, we observed a mortality rate of 3.5 %, a major amputation rate of 9.4 %, and a limb salvage rate of 87 % with a statistically significant increase of TcPO{sub 2} values at follow-up compared to baseline (p < 0.05). In 34 patients, treatment was performed with the IR technique and in 167 by DR; in both groups, there was a statistically significant increase of TcPO{sub 2} values at follow-up compared to baseline (p < 0.05), without statistically significant differences in therapeutic efficacy. Conclusion. PTA of the BTK-only disease is a safe and effective option. The DR technique is the first treatment option; we believe, however, that IR is similarly effective, with good results over time.

  12. Voter models with heterozygosity selection

    Czech Academy of Sciences Publication Activity Database

    Sturm, A.; Swart, Jan M.

    2008-01-01

    Roč. 18, č. 1 (2008), s. 59-99 ISSN 1050-5164 R&D Projects: GA ČR GA201/06/1323; GA ČR GA201/07/0237 Institutional research plan: CEZ:AV0Z10750506 Keywords : Heterozygosity selection * rebellious voter model * branching * annihilation * survival * coexistence Subject RIV: BA - General Mathematics Impact factor: 1.285, year: 2008

  13. Selection of technologies for municipal wastewater treatment

    Directory of Open Access Journals (Sweden)

    Juan Pablo Rodríguez Miranda

    2015-11-01

    Full Text Available In water environmental planning in watersheds should contain aspects for the decontamination of receiving water body, therefore the selection of the treatment plants municipal wastewater in developing countries, you should consider aspects of the typical composition raw wastewater pollutant removal efficiency by technology, performance indicators for technology, environmental aspects of localization and spatial localization strategy. This methodology is built on the basis of technical, economic and environmental attributes, such as a tool for decision making future investments in treatment plants municipal wastewater with multidisciplinary elements.

  14. Constrained treatment planning using sequential beam selection

    International Nuclear Information System (INIS)

    Woudstra, E.; Storchi, P.R.M.

    2000-01-01

    In this paper an algorithm is described for automated treatment plan generation. The algorithm aims at delivery of the prescribed dose to the target volume without violation of constraints for target, organs at risk and the surrounding normal tissue. Pre-calculated dose distributions for all candidate orientations are used as input. Treatment beams are selected in a sequential way. A score function designed for beam selection is used for the simultaneous selection of beam orientations and weights. In order to determine the optimum choice for the orientation and the corresponding weight of each new beam, the score function is first redefined to account for the dose distribution of the previously selected beams. Addition of more beams to the plan is stopped when the target dose is reached or when no additional dose can be delivered without violating a constraint. In the latter case the score function is modified by importance factor changes to enforce better sparing of the organ with the limiting constraint and the algorithm is run again. (author)

  15. When to Intervene in Selective Mutism: The Multimodal Treatment of a Case of Persistent Selective Mutism.

    Science.gov (United States)

    Powell, Shawn; Dalley, Mahlono

    1995-01-01

    An identification and treatment model differentiating transient mutism from persistent selective mutism is proposed. The case study of a six-year-old girl is presented, who was treated with a multimodal approach combining behavioral techniques with play therapy and family involvement. At posttreatment and follow-up, she was talking in a manner…

  16. A framework for selecting performance measures for opioid treatment programs.

    Science.gov (United States)

    Pelletier, Luc R; Hoffman, Jeffrey A

    2002-01-01

    As a result of new federal regulations released in early 2001 that move the monitoring and evaluation of opioid treatment programs from a government regulation to an accreditation model, program staff members are now being challenged to develop performance measurement systems that improve care and service. Using measurement selection criteria is the first step in developing a performance measurement system as a component of an overall quality management (QM) strategy. Opioid treatment programs can "leapfrog" the development of such systems by using lessons learned from the healthcare quality industry. This article reviews performance measurement definitions, proposes performance measurement selection criteria, and makes a business case for Internet automation and accessibility. Performance measurement sets that are appropriate for opioid treatment programs are proposed, followed by a discussion on how performance measurement can be used within a comprehensive QM program. It is hoped that through development, adoption, and implementation of such a performance measurement program, treatment for clients and their families will continuously improve.

  17. Evaluation of the impact of explanatory variables on the accuracy of prediction of daily inflow to the sewage treatment plant by selected models nonlinear

    Directory of Open Access Journals (Sweden)

    Szeląg Bartosz

    2017-09-01

    Full Text Available The aim of the study was to evaluate the possibility of applying different methods of data mining to model the inflow of sewage into the municipal sewage treatment plant. Prediction models were elaborated using methods of support vector machines (SVM, random forests (RF, k-nearest neighbour (k-NN and of Kernel regression (K. Data consisted of the time series of daily rainfalls, water level measurements in the clarified sewage recipient and the wastewater inflow into the Rzeszow city plant. Results indicate that the best models with one input delayed by 1 day were obtained using the k-NN method while the worst with the K method. For the models with two input variables and one explanatory one the smallest errors were obtained if model inputs were sewage inflow and rainfall data delayed by 1 day and the best fit is provided using RF method while the worst with the K method. In the case of models with three inputs and two explanatory variables, the best results were reported for the SVM and the worst for the K method. In the most of the modelling runs the smallest prediction errors are obtained using the SVM method and the biggest ones with the K method. In the case of the simplest model with one input delayed by 1 day the best results are provided using k-NN method and by the models with two inputs in two modelling runs the RF method appeared as the best.

  18. Treatment of Selective Mutism: A Best-Evidence Synthesis.

    Science.gov (United States)

    Stone, Beth Pionek; Kratochwill, Thomas R.; Sladezcek, Ingrid; Serlin, Ronald C.

    2002-01-01

    Presents systematic analysis of the major treatment approaches used for selective mutism. Based on nonparametric statistical tests of effect sizes, major findings include the following: treatment of selective mutism is more effective than no treatment; behaviorally oriented treatment approaches are more effective than no treatment; and no…

  19. Model selection for univariable fractional polynomials.

    Science.gov (United States)

    Royston, Patrick

    2017-07-01

    Since Royston and Altman's 1994 publication ( Journal of the Royal Statistical Society, Series C 43: 429-467), fractional polynomials have steadily gained popularity as a tool for flexible parametric modeling of regression relationships. In this article, I present fp_select, a postestimation tool for fp that allows the user to select a parsimonious fractional polynomial model according to a closed test procedure called the fractional polynomial selection procedure or function selection procedure. I also give a brief introduction to fractional polynomial models and provide examples of using fp and fp_select to select such models with real data.

  20. Waste treatment by selective mineral ion exchanger

    International Nuclear Information System (INIS)

    Polito, Aurelie

    2007-01-01

    STMI, subsidiary company of the AREVA Group with over 40 years in the D and D business, has been continuously innovating and developing new decontamination techniques, with the objectives of achieving more efficient decontaminations on a growing spectrum of media. In the field of liquid waste treatment, STMI manufactures uses and commercialises selective inorganic ion exchangers (RAN). These are hydrated synthetic inorganic compounds prepared from very pure raw materials. Different types of RANs (POLYAN, OXTAIN, Fe-Cu, Fe-CoK, Si-Fe-CoK) can be used to trap a large number of radioactive elements in contaminated effluents. Different implementations could be applied depending on technical conditions. STMI's offers consist in building global solution and preliminary design of installation either in dispersed form (batch) or in column (cartridge filtration). Those products are used all over the world not only in the nuclear business (Canada, US, Belgium, France...) but also in other fields. Indeed, it provides competitive solutions to many domains of application especially water pollution control, liquid waste treatment in the nuclear business by decreasing the activity level of waste. The following paper will focus on the theoretical principle of the mineral exchanger, its implementation and the feed back collected by STMI. (author)

  1. Custom-made titanium devices as membranes for bone augmentation in implant treatment: Modeling accuracy of titanium products constructed with selective laser melting.

    Science.gov (United States)

    Otawa, Naruto; Sumida, Tomoki; Kitagaki, Hisashi; Sasaki, Kiyoyuki; Fujibayashi, Shunsuke; Takemoto, Mitsuru; Nakamura, Takashi; Yamada, Tomohiro; Mori, Yoshihide; Matsushita, Tomiharu

    2015-09-01

    The purpose of this study was to verify the modeling accuracy of various products, and to produce custom-made devices for bone augmentation in individual patients requiring implantation. Two-(2D) and three-dimensional (3D) specimens and custom-made devices that were designed as membranes for guided bone regeneration (GBR) were produced using a computer-aided design (CAD) and rapid prototyping (RP) method. The CAD design was produced using a 3D printing machine and selective laser melting (SLM) with pure titanium (Ti) powder. The modeling accuracy was evaluated with regard to: the dimensional accuracy of the 2D and 3D specimens; the accuracy of pore structure of the 2D specimens; the accuracy of porosity of the 3D specimens; and the error between CAD design and the scanned real product by overlapped images. The accuracy of the 2D and 3D specimens indicated precise results in various parameters, which were tolerant in ISO 2768-1. The error of overlapped images between the CAD and scanned data indicated that accuracy was sufficient for GBR. In integrating area of all devices, the maximum and average error were 292 and 139 μm, respectively. High modeling accuracy can be achieved in various products using the CAD/RP-SLM method. These results suggest the possibility of clinical applications. Copyright © 2015 European Association for Cranio-Maxillo-Facial Surgery. Published by Elsevier Ltd. All rights reserved.

  2. Augmented Self-Modeling as an Intervention for Selective Mutism

    Science.gov (United States)

    Kehle, Thomas J.; Bray, Melissa A.; Byer-Alcorace, Gabriel F.; Theodore, Lea A.; Kovac, Lisa M.

    2012-01-01

    Selective mutism is a rare disorder that is difficult to treat. It is often associated with oppositional defiant behavior, particularly in the home setting, social phobia, and, at times, autism spectrum disorder characteristics. The augmented self-modeling treatment has been relatively successful in promoting rapid diminishment of selective mutism…

  3. Selected sports talent development models

    OpenAIRE

    Michal Vičar

    2017-01-01

    Background: Sports talent in the Czech Republic is generally viewed as a static, stable phenomena. It stands in contrast with widespread praxis carried out in Anglo-Saxon countries that emphasise its fluctuant nature. This is reflected in the current models describing its development. Objectives: The aim is to introduce current models of talent development in sport. Methods: Comparison and analysing of the following models: Balyi - Long term athlete development model, Côté - Developmen...

  4. Anti-fibrotic effects of chronic treatment with the selective FXR agonist obeticholic acid in the bleomycin-induced rat model of pulmonary fibrosis.

    Science.gov (United States)

    Comeglio, Paolo; Filippi, Sandra; Sarchielli, Erica; Morelli, Annamaria; Cellai, Ilaria; Corcetto, Francesca; Corno, Chiara; Maneschi, Elena; Pini, Alessandro; Adorini, Luciano; Vannelli, Gabriella Barbara; Maggi, Mario; Vignozzi, Linda

    2017-04-01

    Farnesoid X receptor (FXR) activation by obeticholic acid (OCA) has been demonstrated to inhibit inflammation and fibrosis development in liver, kidney and intestine in multiple disease models. FXR activation has also been demonstrated to suppress the inflammatory response and to promote lung repair after lung injury. This study investigated the protective effects of OCA treatment (3 or 10mg/kg/day) on inflammation, tissue remodeling and fibrosis in the bleomycin-induced pulmonary fibrosis rat model. Effects of OCA treatment on morphological and molecular alterations of the lung, as well as remodeling of the alveoli and the right ventricle were also evaluated. Lung function was assessed by measuring airway resistance to inflation. In the acute phase (7days), bleomycin promoted an initial thickening and fibrosis of the lung interstitium, with upregulation of genes related to epithelial proliferation, tissue remodeling and hypoxia. At 28days, an evident increase in the deposition of collagen in the lungs was observed. This excessive deposition was accompanied by an upregulation of transcripts related to the extracellular matrix (TGFβ1, SNAI1 and SNAI2), indicating lung fibrosis. Administration of OCA protected against bleomycin-induced lung damage by suppressing molecular mechanisms related to epithelial-to-mesenchymal transition (EMT), inflammation and collagen deposition, with a dose-dependent reduction of proinflammatory cytokines such as IL-1β and IL-6, as well as TGF-β1 and SNAI1 expression. Pirfenidone, a recently approved treatment for idiopathic pulmonary fibrosis (IPF), significantly counteracted bleomycin-induced pro-fibrotic genes expression, but did not exert significant effects on IL-1β and IL-6. OCA treatment in bleomycin-challenged rats also improved pulmonary function, by effectively normalizing airway resistance to inflation and lung stiffness in vivo. Results with OCA were similar, or even superior, to those obtained with pirfenidone. In

  5. MODEL SELECTION FOR SPECTROPOLARIMETRIC INVERSIONS

    International Nuclear Information System (INIS)

    Asensio Ramos, A.; Manso Sainz, R.; Martínez González, M. J.; Socas-Navarro, H.; Viticchié, B.; Orozco Suárez, D.

    2012-01-01

    Inferring magnetic and thermodynamic information from spectropolarimetric observations relies on the assumption of a parameterized model atmosphere whose parameters are tuned by comparison with observations. Often, the choice of the underlying atmospheric model is based on subjective reasons. In other cases, complex models are chosen based on objective reasons (for instance, the necessity to explain asymmetries in the Stokes profiles) but it is not clear what degree of complexity is needed. The lack of an objective way of comparing models has, sometimes, led to opposing views of the solar magnetism because the inferred physical scenarios are essentially different. We present the first quantitative model comparison based on the computation of the Bayesian evidence ratios for spectropolarimetric observations. Our results show that there is not a single model appropriate for all profiles simultaneously. Data with moderate signal-to-noise ratios (S/Ns) favor models without gradients along the line of sight. If the observations show clear circular and linear polarization signals above the noise level, models with gradients along the line are preferred. As a general rule, observations with large S/Ns favor more complex models. We demonstrate that the evidence ratios correlate well with simple proxies. Therefore, we propose to calculate these proxies when carrying out standard least-squares inversions to allow for model comparison in the future.

  6. VEMAP 1: Selected Model Results

    Data.gov (United States)

    National Aeronautics and Space Administration — The Vegetation/Ecosystem Modeling and Analysis Project (VEMAP) was a multi-institutional, international effort addressing the response of biogeography and...

  7. The linear utility model for optimal selection

    NARCIS (Netherlands)

    Mellenbergh, Gideon J.; van der Linden, Willem J.

    A linear utility model is introduced for optimal selection when several subpopulations of applicants are to be distinguished. Using this model, procedures are described for obtaining optimal cutting scores in subpopulations in quota-free as well as quota-restricted selection situations. The cutting

  8. VEMAP 1: Selected Model Results

    Data.gov (United States)

    National Aeronautics and Space Administration — ABSTRACT: The Vegetation/Ecosystem Modeling and Analysis Project (VEMAP) was a multi-institutional, international effort addressing the response of biogeography and...

  9. Exploring Several Methods of Groundwater Model Selection

    Science.gov (United States)

    Samani, Saeideh; Ye, Ming; Asghari Moghaddam, Asghar

    2017-04-01

    Selecting reliable models for simulating groundwater flow and solute transport is essential to groundwater resources management and protection. This work is to explore several model selection methods for avoiding over-complex and/or over-parameterized groundwater models. We consider six groundwater flow models with different numbers (6, 10, 10, 13, 13 and 15) of model parameters. These models represent alternative geological interpretations, recharge estimates, and boundary conditions at a study site in Iran. The models were developed with Model Muse, and calibrated against observations of hydraulic head using UCODE. Model selection was conducted by using the following four approaches: (1) Rank the models using their root mean square error (RMSE) obtained after UCODE-based model calibration, (2) Calculate model probability using GLUE method, (3) Evaluate model probability using model selection criteria (AIC, AICc, BIC, and KIC), and (4) Evaluate model weights using the Fuzzy Multi-Criteria-Decision-Making (MCDM) approach. MCDM is based on the fuzzy analytical hierarchy process (AHP) and fuzzy technique for order performance, which is to identify the ideal solution by a gradual expansion from the local to the global scale of model parameters. The KIC and MCDM methods are superior to other methods, as they consider not only the fit between observed and simulated data and the number of parameter, but also uncertainty in model parameters. Considering these factors can prevent from occurring over-complexity and over-parameterization, when selecting the appropriate groundwater flow models. These methods selected, as the best model, one with average complexity (10 parameters) and the best parameter estimation (model 3).

  10. Selective primary angioplasty following an angiosome model of reperfusion in the treatment of Wagner 1-4 diabetic foot lesions: practice in a multidisciplinary diabetic limb service.

    Science.gov (United States)

    Alexandrescu, Vlad-Adrian; Hubermont, Gerard; Philips, Yvan; Guillaumie, Benoit; Ngongang, Christian; Vandenbossche, Pierre; Azdad, Khalid; Ledent, Gilles; Horion, Jacques

    2008-10-01

    To evaluate the technical and clinical outcomes of primary subintimal (SA) and endoluminal angioplasty (EA) guided by an angiosome model of revascularization in diabetic patients with critical limb ischemia (CLI) and Wagner grade 1-4 foot ulcers. A retrospective review was undertaken of 98 diabetic CLI patients (68 men; mean age 72.8 years, range 46-94) who presented to our institution from January 2005 to January 2008 for treatment of Wagner grade 1-4 foot ulcers involving 124 limbs. Following the angiosome model of perfusion in the foot and ankle, the target arterial lesions in the 124 limbs were treated with 80 (64%) associated SA and EA procedures, 21 (17%) multilevel EAs, and 23 (18%) single SA techniques. Initial technical success was achieved in 102 (82%) interventions: 82/103 SAs and 20/21 of the EAs. The 30-day survival rate was 98% (1 fatal myocardial infarction). The cumulative rates of primary and secondary patency, limb salvage, and clinical success were: 57%+/-4%, 71%+/-4%, 91%+/-3%, and 85%+/-3% at 12 months and 48%+/-5%, 61%+/-4%, 84%+/-6%, and 73%+/-6% at 32 months, respectively. Limb salvage appeared to be negatively affected at 3 years by the presence of Wagner grade 3-4 lesions (pfoot lesions healed in the first 1 to 3 months after revascularization. Targeted primary angioplasty following the angiosome model could be an effective therapeutic method in the ulcer healing process. However, beyond appropriate revascularization, aggressive control of concurrent risk factors in diabetic wound healing probably plays an equally relevant role.

  11. Selection of efficient etchants for nondestructive treatment of semiconductors

    International Nuclear Information System (INIS)

    Tomashik, V.N.; Fomin, A.V.; Tomashik, Z.F.

    1996-01-01

    The scheme for studying etching processes of semiconductor materials and developing new etchants for different semiconductors is proposed. The scheme includes the experiment mathematical planning, computerized physicochemical modeling, kinetic studies, investigation of surface layers, formed by etching. Such on approach makes it possible to optimize the etchant composition in every concrete cage. The scheme is tested in the course of developing optimal methodologies of preepitaxial treatment and selection of etchants composition for semiconductor compounds of the A 1 B 6 and A 3 B 5 type. 13 refs., 4 figs

  12. Selective dry cow treatment in dairy cows

    NARCIS (Netherlands)

    Scherpenzeel, C.G.M.

    2017-01-01

    In the dairy industry, udder health is associated with mastitis management, of which blanket dry cow treatment has been an important part for decades. To prevent the udder from new intramammary infections during the dry period, the use of blanket dry cow treatment has been advocated for more than 50

  13. Bayesian Model Selection in Geophysics: The evidence

    Science.gov (United States)

    Vrugt, J. A.

    2016-12-01

    Bayesian inference has found widespread application and use in science and engineering to reconcile Earth system models with data, including prediction in space (interpolation), prediction in time (forecasting), assimilation of observations and deterministic/stochastic model output, and inference of the model parameters. Per Bayes theorem, the posterior probability, , P(H|D), of a hypothesis, H, given the data D, is equivalent to the product of its prior probability, P(H), and likelihood, L(H|D), divided by a normalization constant, P(D). In geophysics, the hypothesis, H, often constitutes a description (parameterization) of the subsurface for some entity of interest (e.g. porosity, moisture content). The normalization constant, P(D), is not required for inference of the subsurface structure, yet of great value for model selection. Unfortunately, it is not particularly easy to estimate P(D) in practice. Here, I will introduce the various building blocks of a general purpose method which provides robust and unbiased estimates of the evidence, P(D). This method uses multi-dimensional numerical integration of the posterior (parameter) distribution. I will then illustrate this new estimator by application to three competing subsurface models (hypothesis) using GPR travel time data from the South Oyster Bacterial Transport Site, in Virginia, USA. The three subsurface models differ in their treatment of the porosity distribution and use (a) horizontal layering with fixed layer thicknesses, (b) vertical layering with fixed layer thicknesses and (c) a multi-Gaussian field. The results of the new estimator are compared against the brute force Monte Carlo method, and the Laplace-Metropolis method.

  14. Selection of classification models from repository of model for water ...

    African Journals Online (AJOL)

    This paper proposes a new technique, Model Selection Technique (MST) for selection and ranking of models from the repository of models by combining three performance measures (Acc, TPR and TNR). This technique provides weightage to each performance measure to find the most suitable model from the repository of ...

  15. Selective Mutism: Definition, Issues, and Treatment.

    Science.gov (United States)

    Brigham, Frederick J.; Cole, Jane E.

    This paper reviews definitions and issues in selective mutism in children and summarizes results of interventions conducted and published since 1982. Definitions and diagnostic criteria of the American Psychiatric Association's "Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) (1994)" and the World Health Organization's…

  16. Behavior Observations for Linking Assessment to Treatment for Selective Mutism

    Science.gov (United States)

    Shriver, Mark D.; Segool, Natasha; Gortmaker, Valerie

    2011-01-01

    Selective mutism is a childhood disorder that most school psychologists and educational providers will come across at least once in their careers. Selective mutism is associated with significant impairment in educational settings where speaking is necessary for academic and social skill development. Effective treatments for selective mutism…

  17. A Dynamic Model for Limb Selection

    NARCIS (Netherlands)

    Cox, R.F.A; Smitsman, A.W.

    2008-01-01

    Two experiments and a model on limb selection are reported. In Experiment 1 left-handed and right-handed participants (N = 36) repeatedly used one hand for grasping a small cube. After a clear switch in the cube’s location, perseverative limb selection was revealed in both handedness groups. In

  18. [Selection of treatment modalities in patients with spasticity].

    Science.gov (United States)

    Ota, Tetsuo

    2014-09-01

    Spasticity is the most common abnormality of muscle tone. Typically, oral antispastic drugs, phenol blocks, motor-point blocks, selective dorsal rhizotomies, and selective peripheral neurotomies are used to reduce muscle tone and/or improve ranges of motion. Recently, botulinum toxin injections and intrathecal baclofen have been used as treatment modalities. The selection of the most appropriate treatment modality by doctors treating patients with spasticity is critical. Furthermore, rehabilitation techniques, such as physiotherapy, occupational therapy, therapeutic electrical nerve stimulation, and orthosis, are useful as combination therapy for the treatment of spasticity. The purpose of this study was to outline the various modalities that are currently used for the treatment of spasticity. Regardless of the modality selected, it is imperative that treatment goals are carefully identified. The reduction of spasticity is not an appropriate treatment goal. Appropriate goals include improving gait, activities of daily living, and the quality of life.

  19. Review and selection of unsaturated flow models

    Energy Technology Data Exchange (ETDEWEB)

    Reeves, M.; Baker, N.A.; Duguid, J.O. [INTERA, Inc., Las Vegas, NV (United States)

    1994-04-04

    Since the 1960`s, ground-water flow models have been used for analysis of water resources problems. In the 1970`s, emphasis began to shift to analysis of waste management problems. This shift in emphasis was largely brought about by site selection activities for geologic repositories for disposal of high-level radioactive wastes. Model development during the 1970`s and well into the 1980`s focused primarily on saturated ground-water flow because geologic repositories in salt, basalt, granite, shale, and tuff were envisioned to be below the water table. Selection of the unsaturated zone at Yucca Mountain, Nevada, for potential disposal of waste began to shift model development toward unsaturated flow models. Under the US Department of Energy (DOE), the Civilian Radioactive Waste Management System Management and Operating Contractor (CRWMS M&O) has the responsibility to review, evaluate, and document existing computer models; to conduct performance assessments; and to develop performance assessment models, where necessary. This document describes the CRWMS M&O approach to model review and evaluation (Chapter 2), and the requirements for unsaturated flow models which are the bases for selection from among the current models (Chapter 3). Chapter 4 identifies existing models, and their characteristics. Through a detailed examination of characteristics, Chapter 5 presents the selection of models for testing. Chapter 6 discusses the testing and verification of selected models. Chapters 7 and 8 give conclusions and make recommendations, respectively. Chapter 9 records the major references for each of the models reviewed. Appendix A, a collection of technical reviews for each model, contains a more complete list of references. Finally, Appendix B characterizes the problems used for model testing.

  20. Review and selection of unsaturated flow models

    International Nuclear Information System (INIS)

    Reeves, M.; Baker, N.A.; Duguid, J.O.

    1994-01-01

    Since the 1960's, ground-water flow models have been used for analysis of water resources problems. In the 1970's, emphasis began to shift to analysis of waste management problems. This shift in emphasis was largely brought about by site selection activities for geologic repositories for disposal of high-level radioactive wastes. Model development during the 1970's and well into the 1980's focused primarily on saturated ground-water flow because geologic repositories in salt, basalt, granite, shale, and tuff were envisioned to be below the water table. Selection of the unsaturated zone at Yucca Mountain, Nevada, for potential disposal of waste began to shift model development toward unsaturated flow models. Under the US Department of Energy (DOE), the Civilian Radioactive Waste Management System Management and Operating Contractor (CRWMS M ampersand O) has the responsibility to review, evaluate, and document existing computer models; to conduct performance assessments; and to develop performance assessment models, where necessary. This document describes the CRWMS M ampersand O approach to model review and evaluation (Chapter 2), and the requirements for unsaturated flow models which are the bases for selection from among the current models (Chapter 3). Chapter 4 identifies existing models, and their characteristics. Through a detailed examination of characteristics, Chapter 5 presents the selection of models for testing. Chapter 6 discusses the testing and verification of selected models. Chapters 7 and 8 give conclusions and make recommendations, respectively. Chapter 9 records the major references for each of the models reviewed. Appendix A, a collection of technical reviews for each model, contains a more complete list of references. Finally, Appendix B characterizes the problems used for model testing

  1. Graphical tools for model selection in generalized linear models.

    Science.gov (United States)

    Murray, K; Heritier, S; Müller, S

    2013-11-10

    Model selection techniques have existed for many years; however, to date, simple, clear and effective methods of visualising the model building process are sparse. This article describes graphical methods that assist in the selection of models and comparison of many different selection criteria. Specifically, we describe for logistic regression, how to visualize measures of description loss and of model complexity to facilitate the model selection dilemma. We advocate the use of the bootstrap to assess the stability of selected models and to enhance our graphical tools. We demonstrate which variables are important using variable inclusion plots and show that these can be invaluable plots for the model building process. We show with two case studies how these proposed tools are useful to learn more about important variables in the data and how these tools can assist the understanding of the model building process. Copyright © 2013 John Wiley & Sons, Ltd.

  2. Selection of water treatment processes special study

    International Nuclear Information System (INIS)

    1991-11-01

    Characterization of the level and extent of groundwater contamination in the vicinity of Title I mill sites began during the surface remedial action stage (Phase 1) of the Uranium Mill Tailings Remedial Action (UMTRA) Project. Some of the contamination in the aquifer(s) at the abandoned sites is attributable to milling activities during the years the mills were in operation. The restoration of contaminated aquifers is to be undertaken in Phase II of the UMTRA Project. To begin implementation of Phase II, DOE requested that groundwater restoration methods and technologies be investigated by the Technical Assistance Contractor (TAC). and that the results of the TAC investigations be documented in special study reports. Many active and passive methods are available to clean up contaminated groundwater. Passive groundwater treatment includes natural flushing, geochemical barriers, and gradient manipulation by stream diversion or slurry walls. Active groundwater.cleanup techniques include gradient manipulation by well extraction or injection. in-situ biological or chemical reclamation, and extraction and treatment. Although some or all of the methods listed above may play a role in the groundwater cleanup phase of the UMTRA Project, the extraction and treatment (pump and treat) option is the only restoration alternative discussed in this report. Hence, all sections of this report relate either directly or indirectly to the technical discipline of process engineering

  3. The selective external carotid arterial embolization treatment of uncontrollable epistaxis

    International Nuclear Information System (INIS)

    Yao Qunli; Liu Yizhi; Ni Caifang

    2004-01-01

    Objective: To evaluate the selective external carotid arterial embolization of uncontrollable epistaxis. Methods: 27 procedures of super-selective external carotid arterial embolization were performed with absorbable gelfoam by using Seldinger's method in 26 cases with uncontrollable epistaxis. Results: 27 procedures of super-selective intra-arterial embolization of uncontrollable epistaxis were all successful without any serious complication. Conclusions: Selective external carotid arterial embolization is safe, effective and successful in the treatment of severe epistaxis. (authors)

  4. Mixed waste treatment model: Basis and analysis

    International Nuclear Information System (INIS)

    Palmer, B.A.

    1995-09-01

    The Department of Energy's Programmatic Environmental Impact Statement (PEIS) required treatment system capacities for risk and cost calculation. Los Alamos was tasked with providing these capacities to the PEIS team. This involved understanding the Department of Energy (DOE) Complex waste, making the necessary changes to correct for problems, categorizing the waste for treatment, and determining the treatment system requirements. The treatment system requirements depended on the incoming waste, which varied for each PEIS case. The treatment system requirements also depended on the type of treatment that was desired. Because different groups contributing to the PEIS needed specific types of results, we provided the treatment system requirements in a variety of forms. In total, some 40 data files were created for the TRU cases, and for the MLLW case, there were 105 separate data files. Each data file represents one treatment case consisting of the selected waste from various sites, a selected treatment system, and the reporting requirements for such a case. The treatment system requirements in their most basic form are the treatment process rates for unit operations in the desired treatment system, based on a 10-year working life and 20-year accumulation of the waste. These results were reported in cubic meters and for the MLLW case, in kilograms as well. The treatment system model consisted of unit operations that are linked together. Each unit operation's function depended on the input waste streams, waste matrix, and contaminants. Each unit operation outputs one or more waste streams whose matrix, contaminants, and volume/mass may have changed as a result of the treatment. These output streams are then routed to the appropriate unit operation for additional treatment until the output waste stream meets the treatment requirements for disposal. The total waste for each unit operation was calculated as well as the waste for each matrix treated by the unit

  5. Genetic search feature selection for affective modeling

    DEFF Research Database (Denmark)

    Martínez, Héctor P.; Yannakakis, Georgios N.

    2010-01-01

    Automatic feature selection is a critical step towards the generation of successful computational models of affect. This paper presents a genetic search-based feature selection method which is developed as a global-search algorithm for improving the accuracy of the affective models built....... The method is tested and compared against sequential forward feature selection and random search in a dataset derived from a game survey experiment which contains bimodal input features (physiological and gameplay) and expressed pairwise preferences of affect. Results suggest that the proposed method...

  6. Intensive treatment models and coercion

    DEFF Research Database (Denmark)

    Ohlenschlaeger, Johan; Thorup, Anne; Petersen, Lone

    2007-01-01

    Little evidence exists concerning the optimal treatment for patients with first-episode schizophrenia-spectrum disorders and the effect on traditional outcomes. The aim was to investigate whether optimal treatment models have an effect on the level of use of coercion and on traditional outcomes...... and on client satisfaction. Integrated Treatment had fewer bed-days, more patients living in non-supervised accommodation, and better score on quality of life. No differences were found as to the use of coercion. This study adds to the evidence that intensified treatment models are superior to standard...

  7. Chronic Treatment with a Promnesiant GABA-A α5-Selective Inverse Agonist Increases Immediate Early Genes Expression during Memory Processing in Mice and Rectifies Their Expression Levels in a Down Syndrome Mouse Model

    Science.gov (United States)

    Braudeau, J.; Dauphinot, L.; Duchon, A.; Loistron, A.; Dodd, R. H.; Hérault, Y.; Delatour, B.; Potier, M. C.

    2011-01-01

    Decrease of GABAergic transmission has been proposed to improve memory functions. Indeed, inverse agonists selective for α5 GABA-A-benzodiazepine receptors (α5IA) have promnesiant activity. Interestingly, we have recently shown that α5IA can rescue cognitive deficits in Ts65Dn mice, a Down syndrome mouse model with altered GABAergic transmission. Here, we studied the impact of chronic treatment with α5IA on gene expression in the hippocampus of Ts65Dn and control euploid mice after being trained in the Morris water maze task. In euploid mice, chronic treatment with α5IA increased IEGs expression, particularly of c-Fos and Arc genes. In Ts65Dn mice, deficits of IEGs activation were completely rescued after treatment with α5IA. In addition, normalization of Sod1 overexpression in Ts65Dn mice after α5IA treatment was observed. IEG expression regulation after α5IA treatment following behavioral stimulation could be a contributing factor for both the general promnesiant activity of α5IA and its rescuing effect in Ts65Dn mice alongside signaling cascades that are critical for memory consolidation and cognition. PMID:22028705

  8. Economic optimization of selective dry cow treatment

    NARCIS (Netherlands)

    Scherpenzeel, C G M; Hogeveen, H; Maas, L; Lam, T J G M

    2018-01-01

    The objective of this study was to develop a mathematical model to identify a scenario with the lowest costs for mastitis associated with the dry period while restricting the percentage of cows to be dried off with dry cow antimicrobials. Costs of clinical and subclinical mastitis as well as

  9. Modeling Hepatitis C treatment policy.

    Energy Technology Data Exchange (ETDEWEB)

    Kuypers, Marshall A.; Lambert, Gregory Joseph; Moore, Thomas W.; Glass, Robert John,; Finley, Patrick D.; Ross, David; Chartier, Maggie

    2013-09-01

    Chronic infection with Hepatitis C virus (HCV) results in cirrhosis, liver cancer and death. As the nations largest provider of care for HCV, US Veterans Health Administration (VHA) invests extensive resources in the diagnosis and treatment of the disease. This report documents modeling and analysis of HCV treatment dynamics performed for the VHA aimed at improving service delivery efficiency. System dynamics modeling of disease treatment demonstrated the benefits of early detection and the role of comorbidities in disease progress and patient mortality. Preliminary modeling showed that adherence to rigorous treatment protocols is a primary determinant of treatment success. In depth meta-analysis revealed correlations of adherence and various psycho-social factors. This initial meta-analysis indicates areas where substantial improvement in patient outcomes can potentially result from VA programs which incorporate these factors into their design.

  10. Selecting model complexity in learning problems

    Energy Technology Data Exchange (ETDEWEB)

    Buescher, K.L. [Los Alamos National Lab., NM (United States); Kumar, P.R. [Illinois Univ., Urbana, IL (United States). Coordinated Science Lab.

    1993-10-01

    To learn (or generalize) from noisy data, one must resist the temptation to pick a model for the underlying process that overfits the data. Many existing techniques solve this problem at the expense of requiring the evaluation of an absolute, a priori measure of each model`s complexity. We present a method that does not. Instead, it uses a natural, relative measure of each model`s complexity. This method first creates a pool of ``simple`` candidate models using part of the data and then selects from among these by using the rest of the data.

  11. Model selection for Gaussian kernel PCA denoising

    DEFF Research Database (Denmark)

    Jørgensen, Kasper Winther; Hansen, Lars Kai

    2012-01-01

    We propose kernel Parallel Analysis (kPA) for automatic kernel scale and model order selection in Gaussian kernel PCA. Parallel Analysis [1] is based on a permutation test for covariance and has previously been applied for model order selection in linear PCA, we here augment the procedure to also...... tune the Gaussian kernel scale of radial basis function based kernel PCA.We evaluate kPA for denoising of simulated data and the US Postal data set of handwritten digits. We find that kPA outperforms other heuristics to choose the model order and kernel scale in terms of signal-to-noise ratio (SNR...

  12. Melody Track Selection Using Discriminative Language Model

    Science.gov (United States)

    Wu, Xiao; Li, Ming; Suo, Hongbin; Yan, Yonghong

    In this letter we focus on the task of selecting the melody track from a polyphonic MIDI file. Based on the intuition that music and language are similar in many aspects, we solve the selection problem by introducing an n-gram language model to learn the melody co-occurrence patterns in a statistical manner and determine the melodic degree of a given MIDI track. Furthermore, we propose the idea of using background model and posterior probability criteria to make modeling more discriminative. In the evaluation, the achieved 81.6% correct rate indicates the feasibility of our approach.

  13. Pro and cons of targeted selective treatment against digestive-tract strongyles of ruminants

    Directory of Open Access Journals (Sweden)

    Cabaret J.

    2008-09-01

    Full Text Available The increasing prevalence of resistance to anthelmintics among gastrointestinal nematodes and the desire for lower input agriculture have promoted the idea that targeted selective treatment (treating the animals in need of such a treatment and only them could be a sustainable solution for controlling internal parasites of ruminants. The pros are the slowing of resistance prevalence, lower residues of anthelmintics in meat and milk, and lower cost; the cons are the difficulty and time spent on selecting animals in need of treatment and the possibility of lower production. Using actual experiments and modelling we show that targeted selective treatment can be used to sustainably control gastrointestinal nematode infections in flock.

  14. Intensive treatment models and coercion

    DEFF Research Database (Denmark)

    Ohlenschlaeger, Johan; Thorup, Anne; Petersen, Lone

    2007-01-01

    Little evidence exists concerning the optimal treatment for patients with first-episode schizophrenia-spectrum disorders and the effect on traditional outcomes. The aim was to investigate whether optimal treatment models have an effect on the level of use of coercion and on traditional outcomes. ...

  15. Model structure selection in convolutive mixtures

    DEFF Research Database (Denmark)

    Dyrholm, Mads; Makeig, Scott; Hansen, Lars Kai

    2006-01-01

    The CICAAR algorithm (convolutive independent component analysis with an auto-regressive inverse model) allows separation of white (i.i.d) source signals from convolutive mixtures. We introduce a source color model as a simple extension to the CICAAR which allows for a more parsimoneous...... representation in many practical mixtures. The new filter-CICAAR allows Bayesian model selection and can help answer questions like: 'Are we actually dealing with a convolutive mixture?'. We try to answer this question for EEG data....

  16. On spatial mutation-selection models

    Energy Technology Data Exchange (ETDEWEB)

    Kondratiev, Yuri, E-mail: kondrat@math.uni-bielefeld.de [Fakultät für Mathematik, Universität Bielefeld, Postfach 100131, 33501 Bielefeld (Germany); Kutoviy, Oleksandr, E-mail: kutoviy@math.uni-bielefeld.de, E-mail: kutovyi@mit.edu [Fakultät für Mathematik, Universität Bielefeld, Postfach 100131, 33501 Bielefeld (Germany); Department of Mathematics, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139 (United States); Minlos, Robert, E-mail: minl@iitp.ru; Pirogov, Sergey, E-mail: pirogov@proc.ru [IITP, RAS, Bolshoi Karetnyi 19, Moscow (Russian Federation)

    2013-11-15

    We discuss the selection procedure in the framework of mutation models. We study the regulation for stochastically developing systems based on a transformation of the initial Markov process which includes a cost functional. The transformation of initial Markov process by cost functional has an analytic realization in terms of a Kimura-Maruyama type equation for the time evolution of states or in terms of the corresponding Feynman-Kac formula on the path space. The state evolution of the system including the limiting behavior is studied for two types of mutation-selection models.

  17. Sparse model selection via integral terms

    Science.gov (United States)

    Schaeffer, Hayden; McCalla, Scott G.

    2017-08-01

    Model selection and parameter estimation are important for the effective integration of experimental data, scientific theory, and precise simulations. In this work, we develop a learning approach for the selection and identification of a dynamical system directly from noisy data. The learning is performed by extracting a small subset of important features from an overdetermined set of possible features using a nonconvex sparse regression model. The sparse regression model is constructed to fit the noisy data to the trajectory of the dynamical system while using the smallest number of active terms. Computational experiments detail the model's stability, robustness to noise, and recovery accuracy. Examples include nonlinear equations, population dynamics, chaotic systems, and fast-slow systems.

  18. Adverse selection model regarding tobacco consumption

    Directory of Open Access Journals (Sweden)

    Dumitru MARIN

    2006-01-01

    Full Text Available The impact of introducing a tax on tobacco consumption can be studied trough an adverse selection model. The objective of the model presented in the following is to characterize the optimal contractual relationship between the governmental authorities and the two type employees: smokers and non-smokers, taking into account that the consumers’ decision to smoke or not represents an element of risk and uncertainty. Two scenarios are run using the General Algebraic Modeling Systems software: one without taxes set on tobacco consumption and another one with taxes set on tobacco consumption, based on an adverse selection model described previously. The results of the two scenarios are compared in the end of the paper: the wage earnings levels and the social welfare in case of a smoking agent and in case of a non-smoking agent.

  19. Modeling and Selection of Software Service Variants

    OpenAIRE

    Wittern, John Erik

    2015-01-01

    Providers and consumers have to deal with variants, meaning alternative instances of a service?s design, implementation, deployment, or operation, when developing or delivering software services. This work presents service feature modeling to deal with associated challenges, comprising a language to represent software service variants and a set of methods for modeling and subsequent variant selection. This work?s evaluation includes a POC implementation and two real-life use cases.

  20. Model Selection in Data Analysis Competitions

    DEFF Research Database (Denmark)

    Wind, David Kofoed; Winther, Ole

    2014-01-01

    The use of data analysis competitions for selecting the most appropriate model for a problem is a recent innovation in the field of predictive machine learning. Two of the most well-known examples of this trend was the Netflix Competition and recently the competitions hosted on the online platfor...

  1. Efficiently adapting graphical models for selectivity estimation

    DEFF Research Database (Denmark)

    Tzoumas, Kostas; Deshpande, Amol; Jensen, Christian S.

    2013-01-01

    in estimation accuracy. We show how to efficiently construct such a graphical model from the database using only two-way join queries, and we show how to perform selectivity estimation in a highly efficient manner. We integrate our algorithms into the PostgreSQL DBMS. Experimental results indicate...

  2. A guide to Bayesian model selection for ecologists

    Science.gov (United States)

    Hooten, Mevin B.; Hobbs, N.T.

    2015-01-01

    The steady upward trend in the use of model selection and Bayesian methods in ecological research has made it clear that both approaches to inference are important for modern analysis of models and data. However, in teaching Bayesian methods and in working with our research colleagues, we have noticed a general dissatisfaction with the available literature on Bayesian model selection and multimodel inference. Students and researchers new to Bayesian methods quickly find that the published advice on model selection is often preferential in its treatment of options for analysis, frequently advocating one particular method above others. The recent appearance of many articles and textbooks on Bayesian modeling has provided welcome background on relevant approaches to model selection in the Bayesian framework, but most of these are either very narrowly focused in scope or inaccessible to ecologists. Moreover, the methodological details of Bayesian model selection approaches are spread thinly throughout the literature, appearing in journals from many different fields. Our aim with this guide is to condense the large body of literature on Bayesian approaches to model selection and multimodel inference and present it specifically for quantitative ecologists as neutrally as possible. We also bring to light a few important and fundamental concepts relating directly to model selection that seem to have gone unnoticed in the ecological literature. Throughout, we provide only a minimal discussion of philosophy, preferring instead to examine the breadth of approaches as well as their practical advantages and disadvantages. This guide serves as a reference for ecologists using Bayesian methods, so that they can better understand their options and can make an informed choice that is best aligned with their goals for inference.

  3. Model selection criterion in survival analysis

    Science.gov (United States)

    Karabey, Uǧur; Tutkun, Nihal Ata

    2017-07-01

    Survival analysis deals with time until occurrence of an event of interest such as death, recurrence of an illness, the failure of an equipment or divorce. There are various survival models with semi-parametric or parametric approaches used in medical, natural or social sciences. The decision on the most appropriate model for the data is an important point of the analysis. In literature Akaike information criteria or Bayesian information criteria are used to select among nested models. In this study,the behavior of these information criterion is discussed for a real data set.

  4. Testing exclusion restrictions and additive separability in sample selection models

    DEFF Research Database (Denmark)

    Huber, Martin; Mellace, Giovanni

    2014-01-01

    Standard sample selection models with non-randomly censored outcomes assume (i) an exclusion restriction (i.e., a variable affecting selection, but not the outcome) and (ii) additive separability of the errors in the selection process. This paper proposes tests for the joint satisfaction of these......Standard sample selection models with non-randomly censored outcomes assume (i) an exclusion restriction (i.e., a variable affecting selection, but not the outcome) and (ii) additive separability of the errors in the selection process. This paper proposes tests for the joint satisfaction...... of these assumptions by applying the approach of Huber and Mellace (Testing instrument validity for LATE identification based on inequality moment constraints, 2011) (for testing instrument validity under treatment endogeneity) to the sample selection framework. We show that the exclusion restriction and additive...... separability imply two testable inequality constraints that come from both point identifying and bounding the outcome distribution of the subpopulation that is always selected/observed. We apply the tests to two variables for which the exclusion restriction is frequently invoked in female wage regressions: non...

  5. On Using Selection Procedures with Binomial Models.

    Science.gov (United States)

    1983-10-01

    eds.), Shinko Tsusho Co. Ltd., Tokyo, Japan , pp. 501-533. Gupta, S. S. and Sobel, M. (1960). Selecting a subset containing the best of several...IA_____3_6r__I____ *TITLE food A$ieweI L TYPE of 09PORT 6 PERIOD COVERED ON USING SELECTION PROCEDURES WITH BINOMIAL MODELS Technical 6. PeSPRFeauS1 ONG. REPORT...ontoedis stoc toeSI. to Ei.,..,t&* toemR.,. 14. SUPPOLEMENTARY MOCTES 19. Rey WORDS (Coatiou. 40 ow.oa* edo if Necesary and #do""&a by block number

  6. Aerosol model selection and uncertainty modelling by adaptive MCMC technique

    Directory of Open Access Journals (Sweden)

    M. Laine

    2008-12-01

    Full Text Available We present a new technique for model selection problem in atmospheric remote sensing. The technique is based on Monte Carlo sampling and it allows model selection, calculation of model posterior probabilities and model averaging in Bayesian way.

    The algorithm developed here is called Adaptive Automatic Reversible Jump Markov chain Monte Carlo method (AARJ. It uses Markov chain Monte Carlo (MCMC technique and its extension called Reversible Jump MCMC. Both of these techniques have been used extensively in statistical parameter estimation problems in wide area of applications since late 1990's. The novel feature in our algorithm is the fact that it is fully automatic and easy to use.

    We show how the AARJ algorithm can be implemented and used for model selection and averaging, and to directly incorporate the model uncertainty. We demonstrate the technique by applying it to the statistical inversion problem of gas profile retrieval of GOMOS instrument on board the ENVISAT satellite. Four simple models are used simultaneously to describe the dependence of the aerosol cross-sections on wavelength. During the AARJ estimation all the models are used and we obtain a probability distribution characterizing how probable each model is. By using model averaging, the uncertainty related to selecting the aerosol model can be taken into account in assessing the uncertainty of the estimates.

  7. Review and selection of unsaturated flow models

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1993-09-10

    Under the US Department of Energy (DOE), the Civilian Radioactive Waste Management System Management and Operating Contractor (CRWMS M&O) has the responsibility to review, evaluate, and document existing computer ground-water flow models; to conduct performance assessments; and to develop performance assessment models, where necessary. In the area of scientific modeling, the M&O CRWMS has the following responsibilities: To provide overall management and integration of modeling activities. To provide a framework for focusing modeling and model development. To identify areas that require increased or decreased emphasis. To ensure that the tools necessary to conduct performance assessment are available. These responsibilities are being initiated through a three-step process. It consists of a thorough review of existing models, testing of models which best fit the established requirements, and making recommendations for future development that should be conducted. Future model enhancement will then focus on the models selected during this activity. Furthermore, in order to manage future model development, particularly in those areas requiring substantial enhancement, the three-step process will be updated and reported periodically in the future.

  8. Psychotherapy treatment decisions supported by SelectCare

    NARCIS (Netherlands)

    Witteman, C.L.M.

    1999-01-01

    SelectCare is a computerized decision support system for psychotherapists who decide how to treat their depressed patients. This paper descibes the decision making model that is implemented in SelectCare and the decision elements it uses to give advice to its users. The system itself is then

  9. Post-model selection inference and model averaging

    Directory of Open Access Journals (Sweden)

    Georges Nguefack-Tsague

    2011-07-01

    Full Text Available Although model selection is routinely used in practice nowadays, little is known about its precise effects on any subsequent inference that is carried out. The same goes for the effects induced by the closely related technique of model averaging. This paper is concerned with the use of the same data first to select a model and then to carry out inference, in particular point estimation and point prediction. The properties of the resulting estimator, called a post-model-selection estimator (PMSE, are hard to derive. Using selection criteria such as hypothesis testing, AIC, BIC, HQ and Cp, we illustrate that, in terms of risk function, no single PMSE dominates the others. The same conclusion holds more generally for any penalised likelihood information criterion. We also compare various model averaging schemes and show that no single one dominates the others in terms of risk function. Since PMSEs can be regarded as a special case of model averaging, with 0-1 random-weights, we propose a connection between the two theories, in the frequentist approach, by taking account of the selection procedure when performing model averaging. We illustrate the point by simulating a simple linear regression model.

  10. Selective mutism: a review of etiology, comorbidities, and treatment.

    Science.gov (United States)

    Wong, Priscilla

    2010-03-01

    Selective mutism is a rare and multidimensional childhood disorder that typically affects children entering school age. It is characterized by the persistent failure to speak in select social settings despite possessing the ability to speak and speak comfortably in more familiar settings. Many theories attempt to explain the etiology of selective mutism.Comorbidities and treatment. Selective mutism can present a variety of comorbidities including enuresis, encopresis, obsessive-compulsive disorder, depression, premorbid speech and language abnormalities, developmental delay, and Asperger's disorders. The specific manifestations and severity of these comorbidities vary based on the individual. Given the multidimensional manifestations of selective mutism, treatment options are similarly diverse. They include individual behavioral therapy, family therapy, and psychotherapy with antidepressants and anti-anxiety medications.Future directions. While studies have helped to elucidate the phenomenology of selective mutism, limitations and gaps in knowledge still persist. In particular, the literature on selective mutism consists primarily of small sample populations and case reports. Future research aims to develop an increasingly integrated, multidimensional framework for evaluating and treating children with selective mutism.

  11. Model structure selection in convolutive mixtures

    DEFF Research Database (Denmark)

    Dyrholm, Mads; Makeig, S.; Hansen, Lars Kai

    2006-01-01

    The CICAAR algorithm (convolutive independent component analysis with an auto-regressive inverse model) allows separation of white (i.i.d) source signals from convolutive mixtures. We introduce a source color model as a simple extension to the CICAAR which allows for a more parsimonious represent......The CICAAR algorithm (convolutive independent component analysis with an auto-regressive inverse model) allows separation of white (i.i.d) source signals from convolutive mixtures. We introduce a source color model as a simple extension to the CICAAR which allows for a more parsimonious...... representation in many practical mixtures. The new filter-CICAAR allows Bayesian model selection and can help answer questions like: ’Are we actually dealing with a convolutive mixture?’. We try to answer this question for EEG data....

  12. Skewed factor models using selection mechanisms

    KAUST Repository

    Kim, Hyoung-Moon

    2015-12-21

    Traditional factor models explicitly or implicitly assume that the factors follow a multivariate normal distribution; that is, only moments up to order two are involved. However, it may happen in real data problems that the first two moments cannot explain the factors. Based on this motivation, here we devise three new skewed factor models, the skew-normal, the skew-tt, and the generalized skew-normal factor models depending on a selection mechanism on the factors. The ECME algorithms are adopted to estimate related parameters for statistical inference. Monte Carlo simulations validate our new models and we demonstrate the need for skewed factor models using the classic open/closed book exam scores dataset.

  13. Selection of medical treatment in stable angina pectoris

    DEFF Research Database (Denmark)

    Ardissino, D; Savonitto, S; Egstrup, K

    1995-01-01

    pectoris. BACKGROUND: The characteristics of anginal symptoms and the results of exercise testing are considered of great importance for selecting medical treatment in patients with chronic stable angina pectoris. However, little information is available on how this first evaluation may be used to select......, the patients were randomly allocated to double-blind treatment for 6 weeks with either metoprolol (Controlled Release, 200 mg once daily) or nifedipine (Retard, 20 mg twice daily) according to a parallel group design. At the end of this period, exercise tests were repeated 1 to 4 h after drug intake. RESULTS....... CONCLUSIONS: The results of a baseline exercise test, but not the characteristics of anginal symptoms, may offer useful information for selecting medical treatment in stable angina pectoris....

  14. Chemical identification using Bayesian model selection

    Energy Technology Data Exchange (ETDEWEB)

    Burr, Tom; Fry, H. A. (Herbert A.); McVey, B. D. (Brian D.); Sander, E. (Eric)

    2002-01-01

    Remote detection and identification of chemicals in a scene is a challenging problem. We introduce an approach that uses some of the image's pixels to establish the background characteristics while other pixels represent the target for which we seek to identify all chemical species present. This leads to a generalized least squares problem in which we focus on 'subset selection' to identify the chemicals thought to be present. Bayesian model selection allows us to approximate the posterior probability that each chemical in the library is present by adding the posterior probabilities of all the subsets which include the chemical. We present results using realistic simulated data for the case with 1 to 5 chemicals present in each target and compare performance to a hybrid of forward and backward stepwise selection procedure using the F statistic.

  15. Expatriates Selection: An Essay of Model Analysis

    Directory of Open Access Journals (Sweden)

    Rui Bártolo-Ribeiro

    2015-03-01

    Full Text Available The business expansion to other geographical areas with different cultures from which organizations were created and developed leads to the expatriation of employees to these destinations. Recruitment and selection procedures of expatriates do not always have the intended success leading to an early return of these professionals with the consequent organizational disorders. In this study, several articles published in the last five years were analyzed in order to identify the most frequently mentioned dimensions in the selection of expatriates in terms of success and failure. The characteristics in the selection process that may increase prediction of adaptation of expatriates to new cultural contexts of the some organization were studied according to the KSAOs model. Few references were found concerning Knowledge, Skills and Abilities dimensions in the analyzed papers. There was a strong predominance on the evaluation of Other Characteristics, and was given more importance to dispositional factors than situational factors for promoting the integration of the expatriates.

  16. Reserve selection using nonlinear species distribution models.

    Science.gov (United States)

    Moilanen, Atte

    2005-06-01

    Reserve design is concerned with optimal selection of sites for new conservation areas. Spatial reserve design explicitly considers the spatial pattern of the proposed reserve network and the effects of that pattern on reserve cost and/or ability to maintain species there. The vast majority of reserve selection formulations have assumed a linear problem structure, which effectively means that the biological value of a potential reserve site does not depend on the pattern of selected cells. However, spatial population dynamics and autocorrelation cause the biological values of neighboring sites to be interdependent. Habitat degradation may have indirect negative effects on biodiversity in areas neighboring the degraded site as a result of, for example, negative edge effects or lower permeability for animal movement. In this study, I present a formulation and a spatial optimization algorithm for nonlinear reserve selection problems in grid-based landscapes that accounts for interdependent site values. The method is demonstrated using habitat maps and nonlinear habitat models for threatened birds in the Netherlands, and it is shown that near-optimal solutions are found for regions consisting of up to hundreds of thousands grid cells, a landscape size much larger than those commonly attempted even with linear reserve selection formulations.

  17. Behavioral optimization models for multicriteria portfolio selection

    Directory of Open Access Journals (Sweden)

    Mehlawat Mukesh Kumar

    2013-01-01

    Full Text Available In this paper, behavioral construct of suitability is used to develop a multicriteria decision making framework for portfolio selection. To achieve this purpose, we rely on multiple methodologies. Analytical hierarchy process technique is used to model the suitability considerations with a view to obtaining the suitability performance score in respect of each asset. A fuzzy multiple criteria decision making method is used to obtain the financial quality score of each asset based upon investor's rating on the financial criteria. Two optimization models are developed for optimal asset allocation considering simultaneously financial and suitability criteria. An empirical study is conducted on randomly selected assets from National Stock Exchange, Mumbai, India to demonstrate the effectiveness of the proposed methodology.

  18. Multi-dimensional model order selection

    Directory of Open Access Journals (Sweden)

    Roemer Florian

    2011-01-01

    Full Text Available Abstract Multi-dimensional model order selection (MOS techniques achieve an improved accuracy, reliability, and robustness, since they consider all dimensions jointly during the estimation of parameters. Additionally, from fundamental identifiability results of multi-dimensional decompositions, it is known that the number of main components can be larger when compared to matrix-based decompositions. In this article, we show how to use tensor calculus to extend matrix-based MOS schemes and we also present our proposed multi-dimensional model order selection scheme based on the closed-form PARAFAC algorithm, which is only applicable to multi-dimensional data. In general, as shown by means of simulations, the Probability of correct Detection (PoD of our proposed multi-dimensional MOS schemes is much better than the PoD of matrix-based schemes.

  19. A simple parametric model selection test

    OpenAIRE

    Susanne M. Schennach; Daniel Wilhelm

    2014-01-01

    We propose a simple model selection test for choosing among two parametric likelihoods which can be applied in the most general setting without any assumptions on the relation between the candidate models and the true distribution. That is, both, one or neither is allowed to be correctly speci fied or misspeci fied, they may be nested, non-nested, strictly non-nested or overlapping. Unlike in previous testing approaches, no pre-testing is needed, since in each case, the same test statistic to...

  20. Robust inference in sample selection models

    KAUST Repository

    Zhelonkin, Mikhail

    2015-11-20

    The problem of non-random sample selectivity often occurs in practice in many fields. The classical estimators introduced by Heckman are the backbone of the standard statistical analysis of these models. However, these estimators are very sensitive to small deviations from the distributional assumptions which are often not satisfied in practice. We develop a general framework to study the robustness properties of estimators and tests in sample selection models. We derive the influence function and the change-of-variance function of Heckman\\'s two-stage estimator, and we demonstrate the non-robustness of this estimator and its estimated variance to small deviations from the model assumed. We propose a procedure for robustifying the estimator, prove its asymptotic normality and give its asymptotic variance. Both cases with and without an exclusion restriction are covered. This allows us to construct a simple robust alternative to the sample selection bias test. We illustrate the use of our new methodology in an analysis of ambulatory expenditures and we compare the performance of the classical and robust methods in a Monte Carlo simulation study.

  1. Novel metrics for growth model selection.

    Science.gov (United States)

    Grigsby, Matthew R; Di, Junrui; Leroux, Andrew; Zipunnikov, Vadim; Xiao, Luo; Crainiceanu, Ciprian; Checkley, William

    2018-01-01

    Literature surrounding the statistical modeling of childhood growth data involves a diverse set of potential models from which investigators can choose. However, the lack of a comprehensive framework for comparing non-nested models leads to difficulty in assessing model performance. This paper proposes a framework for comparing non-nested growth models using novel metrics of predictive accuracy based on modifications of the mean squared error criteria. Three metrics were created: normalized, age-adjusted, and weighted mean squared error (MSE). Predictive performance metrics were used to compare linear mixed effects models and functional regression models. Prediction accuracy was assessed by partitioning the observed data into training and test datasets. This partitioning was constructed to assess prediction accuracy for backward (i.e., early growth), forward (i.e., late growth), in-range, and on new-individuals. Analyses were done with height measurements from 215 Peruvian children with data spanning from near birth to 2 years of age. Functional models outperformed linear mixed effects models in all scenarios tested. In particular, prediction errors for functional concurrent regression (FCR) and functional principal component analysis models were approximately 6% lower when compared to linear mixed effects models. When we weighted subject-specific MSEs according to subject-specific growth rates during infancy, we found that FCR was the best performer in all scenarios. With this novel approach, we can quantitatively compare non-nested models and weight subgroups of interest to select the best performing growth model for a particular application or problem at hand.

  2. Multimethod Behavioral Treatment of Long-Term Selective Mutism.

    Science.gov (United States)

    Watson, T. Steuart; Kramer, Jack J.

    1992-01-01

    Conducted single-subject, experimental research to examine efficacy of treating severe, long-term selective mutism in nine-year-old male using shaping, multiple reinforcers, natural consequences, stimulus fading, and mild aversives. Implemented different treatment regimens in home and school environments. Home intervention resulted in increase in…

  3. Assessment and Treatment of Selective Mutism with English Language Learners

    Science.gov (United States)

    Mayworm, Ashley M.; Dowdy, Erin; Knights, Kezia; Rebelez, Jennica

    2015-01-01

    Selective mutism (SM) is a type of anxiety disorder that involves the persistent failure to speak in contexts where speech is typically expected (e.g., school), despite speaking in other contexts (e.g., home). Research on the etiology and treatment of SM is limited, as it is a rare disorder and few clinical trials evaluating SM interventions have…

  4. Trends in pharmacotherapy selection for the treatment of alcohol ...

    African Journals Online (AJOL)

    Background. The selection of pharmacotherapy for the treatment of alcohol withdrawal remains a clinical challenge. Research continues into the underlying pathophysiology of dependence and withdrawal. A spectrum of clinical presentations of alcohol dependence is emerging, yet recommendations and guidelines have ...

  5. [Selective serotonine reuptake inhibitors (SSRI) in the treatment of paraphilia].

    Science.gov (United States)

    Kraus, C; Strohm, K; Hill, A; Habermann, N; Berner, W; Briken, P

    2007-06-01

    For about 15 years selective serotonine reuptake inhibitors (SSRI) have been used in the treatment of paraphilias. In an open, uncontrolled, retrospective study, which was the first in the German speaking countries we investigated 16 male outpatients, who have been treated for different paraphilias with SSRI and psychotherapy. There was a marked reduction in paraphilic symptoms. Despite high rates of sexual side effects most patients reported a high overall treatment satisfaction. SSRI are an important addition in pharmacological treatment of paraphilic patients, especially with a risk of so called "hands-off" delinquency.

  6. Appropriate selection for omalizumab treatment in patients with severe asthma?

    DEFF Research Database (Denmark)

    Nygaard, Leo; Henriksen, Daniel Pilsgaard; Madsen, Hanne

    2017-01-01

    Background: Omalizumab improves asthma control in patients with uncontrolled severe allergic asthma; however, appropriate patient selection is crucial. Information in this field is sparse. Objective: We aimed to estimate whether potential omalizumab candidates were appropriately selected according...... to guidelines, and the clinical effect of omalizumab treatment over time. Design: We performed a retrospective observational study on adult patients with asthma treated with omalizumab during 2006-2015 at the Department of Respiratory Medicine at Odense University Hospital (OUH), Denmark. Data were obtained...... from the Electronic Patient Journal of OUH and Odense Pharmaco-Epidemiological Database. Guideline criteria for omalizumab treatment were used to evaluate the appropriateness of omalizumab candidate selection, and the Asthma Control Test (ACT) to assess the clinical effects of omalizumab at weeks 16...

  7. Selective embolization in the treatment of intractable epistaxis

    DEFF Research Database (Denmark)

    Andersen, Pia Juul; Kjeldsen, Anette Drøhse; Nepper-Rasmussen, Jørgen

    2005-01-01

    the bleeding may present difficulties. Several methods are used to control posterior epistaxis, one of the latest treatment strategies being selective embolization of the nasal arteries. The aim of this study was to describe the effect of selective embolization in 22 patients treated with a total of 30...... of epistaxis other than HHT. RESULTS: In Group A, 15 procedures were performed, 12 of which were beneficial as the duration and number of episodes of epistaxis were reduced. In Group B, 15 procedures were performed and the success rate was 87%. One patient suffered from skin necrosis at the tip of the nose...

  8. Model selection and comparison for independents sinusoids

    DEFF Research Database (Denmark)

    Nielsen, Jesper Kjær; Christensen, Mads Græsbøll; Jensen, Søren Holdt

    2014-01-01

    In the signal processing literature, many methods have been proposed for estimating the number of sinusoidal basis functions from a noisy data set. The most popular method is the asymptotic MAP criterion, which is sometimes also referred to as the BIC. In this paper, we extend and improve this me....... Through simulations, we demonstrate that the lp-BIC outperforms the asymptotic MAP criterion and other state of the art methods in terms of model selection, de-noising and prediction performance. The simulation code is available online.......In the signal processing literature, many methods have been proposed for estimating the number of sinusoidal basis functions from a noisy data set. The most popular method is the asymptotic MAP criterion, which is sometimes also referred to as the BIC. In this paper, we extend and improve...... this method by considering the problem in a full Bayesian framework instead of the approximate formulation, on which the asymptotic MAP criterion is based. This leads to a new model selection and comparison method, the lp-BIC, whose computational complexity is of the same order as the asymptotic MAP criterion...

  9. SELECTION OF CHEMICAL TREATMENT PROGRAM FOR OILY WASTEWATER

    Directory of Open Access Journals (Sweden)

    Miguel Díaz

    2017-04-01

    Full Text Available When selecting a chemical treatment program for wastewater to achieve an effective flocculation and coagulation is crucial to understand how individual colloids interact. The coagulation process requires a rapid mixing while flocculation process needs a slow mixing. The behavior of colloids in water is strongly influenced by the electrokinetic charge, where each colloidal particle carries its own charge, which in its nature is usually negative. Polymers, which are long chains of high molecular weight and high charge, when added to water begin to form longer chains, allowing removing numerous particles of suspended matter. A study of physico-chemical treatment by addition of coagulant and flocculant was carried out in order to determine a chemical program for oily wastewater coming from the gravity separation process in a crude oil refinery. The tests were carried out in a Jar Test equipment, where commercial products: aluminum polychloride (PAC, aluminum sulfate and Sintec D50 were evaluated with five different flocculants. The selected chemical program was evaluated with fluids at three temperatures to know its sensitivity to this parameter and the mixing energy in the coagulation and flocculation. The chemical program and operational characteristics for physico-chemical treatment with PAC were determined, obtaining a removal of more than 93% for suspended matter and 96% for total hydrocarbons for the selected coagulant / flocculant combination.

  10. High-dimensional model estimation and model selection

    CERN Multimedia

    CERN. Geneva

    2015-01-01

    I will review concepts and algorithms from high-dimensional statistics for linear model estimation and model selection. I will particularly focus on the so-called p>>n setting where the number of variables p is much larger than the number of samples n. I will focus mostly on regularized statistical estimators that produce sparse models. Important examples include the LASSO and its matrix extension, the Graphical LASSO, and more recent non-convex methods such as the TREX. I will show the applicability of these estimators in a diverse range of scientific applications, such as sparse interaction graph recovery and high-dimensional classification and regression problems in genomics.

  11. Generalized Selectivity Description for Polymeric Ion-Selective Electrodes Based on the Phase Boundary Potential Model.

    Science.gov (United States)

    Bakker, Eric

    2010-02-15

    A generalized description of the response behavior of potentiometric polymer membrane ion-selective electrodes is presented on the basis of ion-exchange equilibrium considerations at the sample-membrane interface. This paper includes and extends on previously reported theoretical advances in a more compact yet more comprehensive form. Specifically, the phase boundary potential model is used to derive the origin of the Nernstian response behavior in a single expression, which is valid for a membrane containing any charge type and complex stoichiometry of ionophore and ion-exchanger. This forms the basis for a generalized expression of the selectivity coefficient, which may be used for the selectivity optimization of ion-selective membranes containing electrically charged and neutral ionophores of any desired stoichiometry. It is shown to reduce to expressions published previously for specialized cases, and may be effectively applied to problems relevant in modern potentiometry. The treatment is extended to mixed ion solutions, offering a comprehensive yet formally compact derivation of the response behavior of ion-selective electrodes to a mixture of ions of any desired charge. It is compared to predictions by the less accurate Nicolsky-Eisenman equation. The influence of ion fluxes or any form of electrochemical excitation is not considered here, but may be readily incorporated if an ion-exchange equilibrium at the interface may be assumed in these cases.

  12. Selecting a model of supersymmetry breaking mediation

    International Nuclear Information System (INIS)

    AbdusSalam, S. S.; Allanach, B. C.; Dolan, M. J.; Feroz, F.; Hobson, M. P.

    2009-01-01

    We study the problem of selecting between different mechanisms of supersymmetry breaking in the minimal supersymmetric standard model using current data. We evaluate the Bayesian evidence of four supersymmetry breaking scenarios: mSUGRA, mGMSB, mAMSB, and moduli mediation. The results show a strong dependence on the dark matter assumption. Using the inferred cosmological relic density as an upper bound, minimal anomaly mediation is at least moderately favored over the CMSSM. Our fits also indicate that evidence for a positive sign of the μ parameter is moderate at best. We present constraints on the anomaly and gauge mediated parameter spaces and some previously unexplored aspects of the dark matter phenomenology of the moduli mediation scenario. We use sparticle searches, indirect observables and dark matter observables in the global fit and quantify robustness with respect to prior choice. We quantify how much information is contained within each constraint.

  13. Hidden Markov Model for Stock Selection

    Directory of Open Access Journals (Sweden)

    Nguyet Nguyen

    2015-10-01

    Full Text Available The hidden Markov model (HMM is typically used to predict the hidden regimes of observation data. Therefore, this model finds applications in many different areas, such as speech recognition systems, computational molecular biology and financial market predictions. In this paper, we use HMM for stock selection. We first use HMM to make monthly regime predictions for the four macroeconomic variables: inflation (consumer price index (CPI, industrial production index (INDPRO, stock market index (S&P 500 and market volatility (VIX. At the end of each month, we calibrate HMM’s parameters for each of these economic variables and predict its regimes for the next month. We then look back into historical data to find the time periods for which the four variables had similar regimes with the forecasted regimes. Within those similar periods, we analyze all of the S&P 500 stocks to identify which stock characteristics have been well rewarded during the time periods and assign scores and corresponding weights for each of the stock characteristics. A composite score of each stock is calculated based on the scores and weights of its features. Based on this algorithm, we choose the 50 top ranking stocks to buy. We compare the performances of the portfolio with the benchmark index, S&P 500. With an initial investment of $100 in December 1999, over 15 years, in December 2014, our portfolio had an average gain per annum of 14.9% versus 2.3% for the S&P 500.

  14. Psyche Mission: Scientific Models and Instrument Selection

    Science.gov (United States)

    Polanskey, C. A.; Elkins-Tanton, L. T.; Bell, J. F., III; Lawrence, D. J.; Marchi, S.; Park, R. S.; Russell, C. T.; Weiss, B. P.

    2017-12-01

    NASA has chosen to explore (16) Psyche with their 14th Discovery-class mission. Psyche is a 226-km diameter metallic asteroid hypothesized to be the exposed core of a planetesimal that was stripped of its rocky mantle by multiple hit and run collisions in the early solar system. The spacecraft launch is planned for 2022 with arrival at the asteroid in 2026 for 21 months of operations. The Psyche investigation has five primary scientific objectives: A. Determine whether Psyche is a core, or if it is unmelted material. B. Determine the relative ages of regions of Psyche's surface. C. Determine whether small metal bodies incorporate the same light elements as are expected in the Earth's high-pressure core. D. Determine whether Psyche was formed under conditions more oxidizing or more reducing than Earth's core. E. Characterize Psyche's topography. The mission's task was to select the appropriate instruments to meet these objectives. However, exploring a metal world, rather than one made of ice, rock, or gas, requires development of new scientific models for Psyche to support the selection of the appropriate instruments for the payload. If Psyche is indeed a planetary core, we expect that it should have a detectable magnetic field. However, the strength of the magnetic field can vary by orders of magnitude depending on the formational history of Psyche. The implications of both the extreme low-end and the high-end predictions impact the magnetometer and mission design. For the imaging experiment, what can the team expect for the morphology of a heavily impacted metal body? Efforts are underway to further investigate the differences in crater morphology between high velocity impacts into metal and rock to be prepared to interpret the images of Psyche when they are returned. Finally, elemental composition measurements at Psyche using nuclear spectroscopy encompass a new and unexplored phase space of gamma-ray and neutron measurements. We will present some end

  15. Selected Physical Therapy Modalities for the treatment of Diabetic Polyneuropathy

    International Nuclear Information System (INIS)

    Sawan, S.; Sayed, N.; Al-Gazzar, S.

    2006-01-01

    The purpose of this study was to examine the effect of using selected physical therapy modalities for the treatment of diabetic polyneuropathy. Thirty patients participated in this study. Patients were randomly divided into study group (ten males and five females) and control group (six males and nine females). The study group received interferential current on the lumbosacral region, followed by repeated contraction as specific technique of proprioceptive neuromuscular facilitation (PNF) to the anterior tibial group muscles. The control group did not receive physical therapy treatment. The treatment for the study group was conducted three times per week, for a period of six weeks. The patients were assessed for intensity of pain, manual muscle testing of the anterior tibial group muscles, and the level of superficial sensation on their feet. Patients were assessed the beginning of the treatment session and after the last session. The result of this study showed a significant decrease in the pain intensity, increase anterior tibial group muscles strength and increase level of superficial sensation in patients of study group in comparison to the control group at the end of the treatment. The control group did not show significant changes. It can be concluded that the combination of interferential current and repeated contraction (specific technique of PNF to the anterior tibial group muscles) is effective in decreasing the pain, increasing anterior tibial group muscles strength and the level of superficial sensation in patients suffering from diabetic polyneuropathy. (author)

  16. Endoscopic bronchial valve treatment: patient selection and special considerations

    Directory of Open Access Journals (Sweden)

    Eberhardt R

    2015-10-01

    Full Text Available Ralf Eberhardt,1,2 Daniela Gompelmann,1,2 Felix JF Herth,1,2 Maren Schuhmann1 1Pneumology and Critical Care Medicine, Thoraxklinik at the University of Heidelberg, 2Translational Lung Research Center, Member of the German Center for Lung Research, Heidelberg, Germany Abstract: As well as lung volume reduction surgery, different minimally invasive endoscopic techniques are available to achieve lung volume reduction in patients with severe emphysema and significant hyperinflation. Lung function parameters and comorbidities of the patient, as well as the extent and distribution of the emphysema are factors to be considered when choosing the patient and the intervention. Endoscopic bronchial valve placement with complete occlusion of one lobe in patients with heterogeneous emphysema is the preferred technique because of its reversibility. The presence of high interlobar collateral ventilation will hinder successful treatment; therefore, endoscopic coil placement, polymeric lung volume reduction, or bronchoscopic thermal vapor ablation as well as lung volume reduction surgery can be used for treating patients with incomplete fissures. The effect of endoscopic lung volume reduction in patients with a homogeneous distribution of emphysema is still unclear and this subgroup should be treated only in clinical trials. Precise patient selection is necessary for interventions and to improve the outcome and reduce the risk and possible complications. Therefore, the patients should be discussed in a multidisciplinary approach prior to determining the most appropriate treatment for lung volume reduction. Keywords: lung emphysema, valve treatment, collateral ventilation, patient selection, outcome

  17. [Evaluation and selection of VOCs treatment technologies in packaging and printing industry].

    Science.gov (United States)

    Wang, Hai-Lin; Wang, Jun-Hui; Zhu, Chun-Lei; Nie, Lei; Hao, Zheng-Ping

    2014-07-01

    Volatile organic compounds (VOCs) play an important role in urban air pollution. Activities of industries including the packaging and printing industries are regarded as the major sources. How to select the suitable treating techniques is the major problem for emission control. In this article, based on the VOCs emission characteristics of the packaging and printing industry and the existing treatment technologies, using the analytic hierarchy process (AHP) model, an evaluation system for VOCs selection was established and all the technologies used for treatment were assessed. It showed that the priority selection was in the following order: Carbon Fiber Adsorption-Desorption > Granular Carbon Adsorption-Desorption > Thermal Combustion > Regenerative Combustion > Catalytic combustion > Rotary adsorption-concentration and combustion > Granular Carbon adsorption-concentration and combustion. Carbon Fiber Adsorption-Desorption was selected as the best available technology due to its highest weight among those technologies.

  18. On model selections for repeated measurement data in clinical studies.

    Science.gov (United States)

    Zou, Baiming; Jin, Bo; Koch, Gary G; Zhou, Haibo; Borst, Stephen E; Menon, Sandeep; Shuster, Jonathan J

    2015-05-10

    Repeated measurement designs have been widely used in various randomized controlled trials for evaluating long-term intervention efficacies. For some clinical trials, the primary research question is how to compare two treatments at a fixed time, using a t-test. Although simple, robust, and convenient, this type of analysis fails to utilize a large amount of collected information. Alternatively, the mixed-effects model is commonly used for repeated measurement data. It models all available data jointly and allows explicit assessment of the overall treatment effects across the entire time spectrum. In this paper, we propose an analytic strategy for longitudinal clinical trial data where the mixed-effects model is coupled with a model selection scheme. The proposed test statistics not only make full use of all available data but also utilize the information from the optimal model deemed for the data. The performance of the proposed method under various setups, including different data missing mechanisms, is evaluated via extensive Monte Carlo simulations. Our numerical results demonstrate that the proposed analytic procedure is more powerful than the t-test when the primary interest is to test for the treatment effect at the last time point. Simulations also reveal that the proposed method outperforms the usual mixed-effects model for testing the overall treatment effects across time. In addition, the proposed framework is more robust and flexible in dealing with missing data compared with several competing methods. The utility of the proposed method is demonstrated by analyzing a clinical trial on the cognitive effect of testosterone in geriatric men with low baseline testosterone levels. Copyright © 2015 John Wiley & Sons, Ltd.

  19. Using AHP for Selecting the Best Wastewater Treatment Process

    Directory of Open Access Journals (Sweden)

    AbdolReza Karimi

    2011-01-01

    Full Text Available In this paper, Analytical Hierarchy Process (AHP method that is based on expert knowledge is used for the selection of the optimal anaerobic wastewater treatment process in industrial estates. This method can be applied for complicated multi-criteria decision making to obtain reasonable results. The different anaerobic processes employed in Iranian industrial estates consist of UASB, UAFB, ABR, Contact process, and Anaerobic Lagoons. Based on the general conditions in wastewater treatment plants in industrial estates and on expert judgments and using technical, economic, environmental, and administrative criteria, the processes are weighted and the results obtained are assessed using the Expert Choice Software. Finally, the five processes investigated are ranked as 1 to 5 in a descending order of UAFB, ABR, UASB, Anaerobic Lagoon, and Contact Process. Sensitivity analysis showing the effects of input parameters on changes in the results was applied for technical, economic, environmental, and administrative criteria.

  20. Characterization of selectively etched halloysite nanotubes by acid treatment

    Science.gov (United States)

    Garcia-Garcia, Daniel; Ferri, Jose M.; Ripoll, Laura; Hidalgo, Montserrat; Lopez-Martinez, Juan; Balart, Rafael

    2017-11-01

    Halloysite nanotubes (HNTs) are a type of naturally occurring inorganic nanotubes that are characterized by a different composition between their external and internal walls. The internal walls are mainly composed of alumina whilst external walls are composed of silica. This particular structure offers a dual surface chemistry that allows different selective surface treatments which can be focused on increasing the lumen, increasing porosity, etc. In this work, HNTs were chemically treated with different acids (sulphuric, acetic and acrylic acid), for 72 h at a constant temperature of 50 °C. As per the obtained results, the treatment with sulphuric acid is highly aggressive and the particular shape of HNTs is almost lost, with a remarkable increase in porosity. The BET surface area increases from 52.9 (untreated HNTs) up to 132.4 m2 g-1 with sulphuric acid treatment, thus showing an interesting potential in the field of catalysis. On the other hand, the treatment with acetic acid led to milder effects with a noticeable increase in the lumen diameter that changed from 13.8 nm (untreated HNTs) up to 18.4 nm which the subsequent increase in the loading capacity by 77.8%. The aluminium content was measured by X-ray fluorescence (XRF) and laser induced breakdown spectroscopy (LIBS). The final results using two systems, suggest a good correlation between the acid strength and the aluminium reduction. Consequently, is possible to conclude that new applications for HNTs can be derived from selective etching with acids. Sulphuric acid widens the potential of HNTs in the field of catalysis while weak acids such as acetic and acrylic acids give a controlled and homogeneous lumen increase with the corresponding increase in the loading capacity.

  1. Models Predicting Success of Infertility Treatment: A Systematic Review

    Science.gov (United States)

    Zarinara, Alireza; Zeraati, Hojjat; Kamali, Koorosh; Mohammad, Kazem; Shahnazari, Parisa; Akhondi, Mohammad Mehdi

    2016-01-01

    Background: Infertile couples are faced with problems that affect their marital life. Infertility treatment is expensive and time consuming and occasionally isn’t simply possible. Prediction models for infertility treatment have been proposed and prediction of treatment success is a new field in infertility treatment. Because prediction of treatment success is a new need for infertile couples, this paper reviewed previous studies for catching a general concept in applicability of the models. Methods: This study was conducted as a systematic review at Avicenna Research Institute in 2015. Six data bases were searched based on WHO definitions and MESH key words. Papers about prediction models in infertility were evaluated. Results: Eighty one papers were eligible for the study. Papers covered years after 1986 and studies were designed retrospectively and prospectively. IVF prediction models have more shares in papers. Most common predictors were age, duration of infertility, ovarian and tubal problems. Conclusion: Prediction model can be clinically applied if the model can be statistically evaluated and has a good validation for treatment success. To achieve better results, the physician and the couples’ needs estimation for treatment success rate were based on history, the examination and clinical tests. Models must be checked for theoretical approach and appropriate validation. The privileges for applying the prediction models are the decrease in the cost and time, avoiding painful treatment of patients, assessment of treatment approach for physicians and decision making for health managers. The selection of the approach for designing and using these models is inevitable. PMID:27141461

  2. The Trimeric Model: A New Model of Periodontal Treatment Planning

    Science.gov (United States)

    Tarakji, Bassel

    2014-01-01

    Treatment of periodontal disease is a complex and multidisciplinary procedure, requiring periodontal, surgical, restorative, and orthodontic treatment modalities. Several authors attempted to formulate models for periodontal treatment that orders the treatment steps in a logical and easy to remember manner. In this article, we discuss two models of periodontal treatment planning from two of the most well-known textbook in the specialty of periodontics internationally. Then modify them to arrive at a new model of periodontal treatment planning, The Trimeric Model. Adding restorative and orthodontic interrelationships with periodontal treatment allows us to expand this model into the Extended Trimeric Model of periodontal treatment planning. These models will provide a logical framework and a clear order of the treatment of periodontal disease for general practitioners and periodontists alike. PMID:25177662

  3. Treatment selection and experience in multiple sclerosis: survey of neurologists

    Directory of Open Access Journals (Sweden)

    Hanson KA

    2014-04-01

    Full Text Available Kristin A Hanson,1 Neetu Agashivala,2 Kathleen W Wyrwich,3 Karina Raimundo,2 Edward Kim,2 David W Brandes4 1UBC: An Express Scripts Company, Dorval, QC, Canada; 2Novartis Pharmaceuticals Corporation, East Hanover, NJ, USA; 3Evidera, Bethesda, MD, USA; 4Hope MS Center, Knoxville, TN, USA Background: Multiple sclerosis (MS is a complex disease with many therapeutic options. Little is known about how neurologists select particular disease-modifying therapies (DMTs for their patients. Objective: To understand how neurologists make decisions regarding the prescription of DMTs for patients with MS, and to explore neurologists' experiences with individual DMTs. Methods: From December 2012 to January 2013, members of a nationwide physician market research panel were sent an online study invitation with a link to a survey website. Eligible neurologists were included if they currently practice medicine in the United States, and if they treat ≥20 patients with MS. Results: A total of 102 neurologists (n=63 general neurologists; n=39 MS specialists; 81.4% male completed the survey. The mean (standard deviation number of years in practice since completing medical training was 16.4 (8.6 years. Overall, the most commonly prescribed DMTs were subcutaneous interferon (IFN β -1a and glatiramer acetate; approximately 5.5% of patients were untreated. The most important attributes of DMT medication selection were (in order of importance efficacy, safety, tolerability, patient preference, and convenience. The DMT with the highest neurologist-reported percentage of patients who were “Very/Extremely Satisfied” with their therapy was fingolimod (31.0%, followed by glatiramer acetate (13.9%; P=0.017. Compared with fingolimod (94.0%, significantly fewer (P<0.05 neurologists reported that “All/Most” of their patients were adherent to treatment with glatiramer acetate (78.0%, subcutaneous IFN ß-1a (84.0%, and IFN β-1b (75.0%; no significant differences were

  4. Treatment Options for Liquid Radioactive Waste. Factors Important for Selecting of Treatment Methods

    Energy Technology Data Exchange (ETDEWEB)

    Dziewinski, J.J.

    1998-09-28

    The cleanup of liquid streams contaminated with radionuclides is obtained by the selection or a combination of a number of physical and chemical separations, processes or unit operations. Among those are: Chemical treatment; Evaporation; Ion exchange and sorption; Physical separation; Electrodialysis; Osmosis; Electrocoagulation/electroflotation; Biotechnological processes; and Solvent extraction.

  5. Treatment Options for Liquid Radioactive Waste. Factors Important for Selecting of Treatment Methods

    International Nuclear Information System (INIS)

    Dziewinski, J.J.

    1998-01-01

    The cleanup of liquid streams contaminated with radionuclides is obtained by the selection or a combination of a number of physical and chemical separations, processes or unit operations. Among those are: Chemical treatment; Evaporation; Ion exchange and sorption; Physical separation; Electrodialysis; Osmosis; Electrocoagulation/electroflotation; Biotechnological processes; and Solvent extraction

  6. A new Russell model for selecting suppliers

    NARCIS (Netherlands)

    Azadi, Majid; Shabani, Amir; Farzipoor Saen, Reza

    2014-01-01

    Recently, supply chain management (SCM) has been considered by many researchers. Supplier evaluation and selection plays a significant role in establishing an effective SCM. One of the techniques that can be used for selecting suppliers is data envelopment analysis (DEA). In some situations, to

  7. Selective experimental review of the Standard Model

    International Nuclear Information System (INIS)

    Bloom, E.D.

    1985-02-01

    Before disussing experimental comparisons with the Standard Model, (S-M) it is probably wise to define more completely what is commonly meant by this popular term. This model is a gauge theory of SU(3)/sub f/ x SU(2)/sub L/ x U(1) with 18 parameters. The parameters are α/sub s/, α/sub qed/, theta/sub W/, M/sub W/ (M/sub Z/ = M/sub W//cos theta/sub W/, and thus is not an independent parameter), M/sub Higgs/; the lepton masses, M/sub e/, Mμ, M/sub r/; the quark masses, M/sub d/, M/sub s/, M/sub b/, and M/sub u/, M/sub c/, M/sub t/; and finally, the quark mixing angles, theta 1 , theta 2 , theta 3 , and the CP violating phase delta. The latter four parameters appear in the quark mixing matrix for the Kobayashi-Maskawa and Maiani forms. Clearly, the present S-M covers an enormous range of physics topics, and the author can only lightly cover a few such topics in this report. The measurement of R/sub hadron/ is fundamental as a test of the running coupling constant α/sub s/ in QCD. The author will discuss a selection of recent precision measurements of R/sub hadron/, as well as some other techniques for measuring α/sub s/. QCD also requires the self interaction of gluons. The search for the three gluon vertex may be practically realized in the clear identification of gluonic mesons. The author will present a limited review of recent progress in the attempt to untangle such mesons from the plethora q anti q states of the same quantum numbers which exist in the same mass range. The electroweak interactions provide some of the strongest evidence supporting the S-M that exists. Given the recent progress in this subfield, and particularly with the discovery of the W and Z bosons at CERN, many recent reviews obviate the need for further discussion in this report. In attempting to validate a theory, one frequently searches for new phenomena which would clearly invalidate it. 49 references, 28 figures

  8. A Bayesian random effects discrete-choice model for resource selection: Population-level selection inference

    Science.gov (United States)

    Thomas, D.L.; Johnson, D.; Griffith, B.

    2006-01-01

    Modeling the probability of use of land units characterized by discrete and continuous measures, we present a Bayesian random-effects model to assess resource selection. This model provides simultaneous estimation of both individual- and population-level selection. Deviance information criterion (DIC), a Bayesian alternative to AIC that is sample-size specific, is used for model selection. Aerial radiolocation data from 76 adult female caribou (Rangifer tarandus) and calf pairs during 1 year on an Arctic coastal plain calving ground were used to illustrate models and assess population-level selection of landscape attributes, as well as individual heterogeneity of selection. Landscape attributes included elevation, NDVI (a measure of forage greenness), and land cover-type classification. Results from the first of a 2-stage model-selection procedure indicated that there is substantial heterogeneity among cow-calf pairs with respect to selection of the landscape attributes. In the second stage, selection of models with heterogeneity included indicated that at the population-level, NDVI and land cover class were significant attributes for selection of different landscapes by pairs on the calving ground. Population-level selection coefficients indicate that the pairs generally select landscapes with higher levels of NDVI, but the relationship is quadratic. The highest rate of selection occurs at values of NDVI less than the maximum observed. Results for land cover-class selections coefficients indicate that wet sedge, moist sedge, herbaceous tussock tundra, and shrub tussock tundra are selected at approximately the same rate, while alpine and sparsely vegetated landscapes are selected at a lower rate. Furthermore, the variability in selection by individual caribou for moist sedge and sparsely vegetated landscapes is large relative to the variability in selection of other land cover types. The example analysis illustrates that, while sometimes computationally intense, a

  9. Optimization model for the design of distributed wastewater treatment networks

    Directory of Open Access Journals (Sweden)

    Ibrić Nidret

    2012-01-01

    Full Text Available In this paper we address the synthesis problem of distributed wastewater networks using mathematical programming approach based on the superstructure optimization. We present a generalized superstructure and optimization model for the design of the distributed wastewater treatment networks. The superstructure includes splitters, treatment units, mixers, with all feasible interconnections including water recirculation. Based on the superstructure the optimization model is presented. The optimization model is given as a nonlinear programming (NLP problem where the objective function can be defined to minimize the total amount of wastewater treated in treatment operations or to minimize the total treatment costs. The NLP model is extended to a mixed integer nonlinear programming (MINLP problem where binary variables are used for the selection of the wastewater treatment technologies. The bounds for all flowrates and concentrations in the wastewater network are specified as general equations. The proposed models are solved using the global optimization solvers (BARON and LINDOGlobal. The application of the proposed models is illustrated on the two wastewater network problems of different complexity. First one is formulated as the NLP and the second one as the MINLP. For the second one the parametric and structural optimization is performed at the same time where optimal flowrates, concentrations as well as optimal technologies for the wastewater treatment are selected. Using the proposed model both problems are solved to global optimality.

  10. Threat-related selective attention predicts treatment success in childhood anxiety disorders

    NARCIS (Netherlands)

    Legerstee, Jeroen S.; Tulen, Joke H. M.; Kallen, Victor L.; Dieleman, Gwen C.; Treffers, Philip D. A.; Verhulst, Frank C.; Utens, Elisabeth M. W. J.

    2009-01-01

    The present study examined whether threat-related selective attention was predictive of treatment success in children with anxiety disorders and whether age moderated this association. Specific components of selective attention were examined in treatment responders and nonresponders. Participants

  11. Uncertainty associated with selected environmental transport models

    International Nuclear Information System (INIS)

    Little, C.A.; Miller, C.W.

    1979-11-01

    A description is given of the capabilities of several models to predict accurately either pollutant concentrations in environmental media or radiological dose to human organs. The models are discussed in three sections: aquatic or surface water transport models, atmospheric transport models, and terrestrial and aquatic food chain models. Using data published primarily by model users, model predictions are compared to observations. This procedure is infeasible for food chain models and, therefore, the uncertainty embodied in the models input parameters, rather than the model output, is estimated. Aquatic transport models are divided into one-dimensional, longitudinal-vertical, and longitudinal-horizontal models. Several conclusions were made about the ability of the Gaussian plume atmospheric dispersion model to predict accurately downwind air concentrations from releases under several sets of conditions. It is concluded that no validation study has been conducted to test the predictions of either aquatic or terrestrial food chain models. Using the aquatic pathway from water to fish to an adult for 137 Cs as an example, a 95% one-tailed confidence limit interval for the predicted exposure is calculated by examining the distributions of the input parameters. Such an interval is found to be 16 times the value of the median exposure. A similar one-tailed limit for the air-grass-cow-milk-thyroid for 131 I and infants was 5.6 times the median dose. Of the three model types discussed in this report,the aquatic transport models appear to do the best job of predicting observed concentrations. However, this conclusion is based on many fewer aquatic validation data than were availaable for atmospheric model validation

  12. Quality Quandaries- Time Series Model Selection and Parsimony

    DEFF Research Database (Denmark)

    Bisgaard, Søren; Kulahci, Murat

    2009-01-01

    Some of the issues involved in selecting adequate models for time series data are discussed using an example concerning the number of users of an Internet server. The process of selecting an appropriate model is subjective and requires experience and judgment. The authors believe an important...... consideration in model selection should be parameter parsimony. They favor the use of parsimonious mixed ARMA models, noting that research has shown that a model building strategy that considers only autoregressive representations will lead to non-parsimonious models and to loss of forecasting accuracy....

  13. Computational models as predictors of HIV treatment outcomes for ...

    African Journals Online (AJOL)

    Background: Selecting the optimal combination of HIV drugs for an individual in resourcelimited settings is challenging because of the limited availability of drugs and genotyping. Objective: The evaluation as a potential treatment support tool of computational models that predict response to therapy without a genotype, ...

  14. Computer modeling of lung cancer diagnosis-to-treatment process.

    Science.gov (United States)

    Ju, Feng; Lee, Hyo Kyung; Osarogiagbon, Raymond U; Yu, Xinhua; Faris, Nick; Li, Jingshan

    2015-08-01

    We introduce an example of a rigorous, quantitative method for quality improvement in lung cancer care-delivery. Computer process modeling methods are introduced for lung cancer diagnosis, staging and treatment selection process. Two types of process modeling techniques, discrete event simulation (DES) and analytical models, are briefly reviewed. Recent developments in DES are outlined and the necessary data and procedures to develop a DES model for lung cancer diagnosis, leading up to surgical treatment process are summarized. The analytical models include both Markov chain model and closed formulas. The Markov chain models with its application in healthcare are introduced and the approach to derive a lung cancer diagnosis process model is presented. Similarly, the procedure to derive closed formulas evaluating the diagnosis process performance is outlined. Finally, the pros and cons of these methods are discussed.

  15. HIV models for treatment interruption: Adaptation and comparison

    Science.gov (United States)

    Hillmann, Andreas; Crane, Martin; Ruskin, Heather J.

    2017-10-01

    In recent years, Antiretroviral Therapy (ART) has become commonplace for treating HIV infections, although a cure remains elusive, given reservoirs of replicating latently-infected cells, which are resistant to normal treatment regimes. Treatment interruptions, whether ad hoc or structured, are known to cause a rapid increase in viral production to detectable levels, but numerous clinical trials remain inconclusive on the dangers inherent in this resurgence. In consequence, interest in examining interruption strategies has recently been rekindled. This overview considers modelling approaches, which have been used to explore the issue of treatment interruption. We highlight their purpose and the formalisms employed and examine ways in which clinical data have been used. Implementation of selected models is demonstrated, illustrative examples provided and model performance compared for these cases. Possible extensions to bottom-up modelling techniques for treatment interruptions are briefly discussed.

  16. Application of Bayesian Model Selection for Metal Yield Models using ALEGRA and Dakota.

    Energy Technology Data Exchange (ETDEWEB)

    Portone, Teresa; Niederhaus, John Henry; Sanchez, Jason James; Swiler, Laura Painton

    2018-02-01

    This report introduces the concepts of Bayesian model selection, which provides a systematic means of calibrating and selecting an optimal model to represent a phenomenon. This has many potential applications, including for comparing constitutive models. The ideas described herein are applied to a model selection problem between different yield models for hardened steel under extreme loading conditions.

  17. Effect of different oral oxytetracycline treatment regimes on selection of antimicrobial resistant coliforms in nursery pigs.

    Science.gov (United States)

    Herrero-Fresno, Ana; Zachariasen, Camilla; Nørholm, Nanna; Holm, Anders; Christiansen, Lasse Engbo; Olsen, John Elmerdahl

    2017-09-01

    A major concern derived from using antimicrobials in pig production is the development of resistance. This study aimed to assess the impact of selected combinations of oral dose and duration of treatment with oxytetracycline (OTC) on selection of tetracycline resistant (TET-R) coliforms recovered from swine feces. The work encompassed two studies: 1) OTC 5mg/kg and 20mg/kg were administered to nursery pigs for 3 and 10days, respectively, under controlled experimental conditions, and 2) 10mg/kg, 20mg/kg and 30mg/kg OTC were given to a higher number of pigs for 6, 3 and 2days, respectively, under field conditions. Statistical modeling was applied to analyze trends in the proportion of TET-R coliforms. In the experimental study, no statistical difference in proportion of TET-R coliforms was observed between treatments at the end of the trial (day 18) and compared to day 0. In the field study, treatment had a significant effect on the proportion of TET-R bacteria two days after the end of treatment (2dAT) with the regimes "low dose-six days" and "medium dose-three days" yielding the highest and lowest proportions of TET-R strains, respectively. No indication of co-selection for ampicillin- and sulphonamide -R bacteria was observed for any treatment at 2dAT. By the end of the nursery period, the proportion of TET-R bacteria was not significantly different between treatments and compared to day 0. Our results suggest that similar resistance levels might be obtained by using different treatment regimes regardless of the combinations of oral dose-duration of treatment. Copyright © 2017 Elsevier B.V. All rights reserved.

  18. A Hybrid Multiple Criteria Decision Making Model for Supplier Selection

    OpenAIRE

    Wu, Chung-Min; Hsieh, Ching-Lin; Chang, Kuei-Lun

    2013-01-01

    The sustainable supplier selection would be the vital part in the management of a sustainable supply chain. In this study, a hybrid multiple criteria decision making (MCDM) model is applied to select optimal supplier. The fuzzy Delphi method, which can lead to better criteria selection, is used to modify criteria. Considering the interdependence among the selection criteria, analytic network process (ANP) is then used to obtain their weights. To avoid calculation and additional pairwise compa...

  19. Astrophysical Model Selection in Gravitational Wave Astronomy

    Science.gov (United States)

    Adams, Matthew R.; Cornish, Neil J.; Littenberg, Tyson B.

    2012-01-01

    Theoretical studies in gravitational wave astronomy have mostly focused on the information that can be extracted from individual detections, such as the mass of a binary system and its location in space. Here we consider how the information from multiple detections can be used to constrain astrophysical population models. This seemingly simple problem is made challenging by the high dimensionality and high degree of correlation in the parameter spaces that describe the signals, and by the complexity of the astrophysical models, which can also depend on a large number of parameters, some of which might not be directly constrained by the observations. We present a method for constraining population models using a hierarchical Bayesian modeling approach which simultaneously infers the source parameters and population model and provides the joint probability distributions for both. We illustrate this approach by considering the constraints that can be placed on population models for galactic white dwarf binaries using a future space-based gravitational wave detector. We find that a mission that is able to resolve approximately 5000 of the shortest period binaries will be able to constrain the population model parameters, including the chirp mass distribution and a characteristic galaxy disk radius to within a few percent. This compares favorably to existing bounds, where electromagnetic observations of stars in the galaxy constrain disk radii to within 20%.

  20. Modeling and Analysis of Supplier Selection Method Using ...

    African Journals Online (AJOL)

    However, in these parts of the world the application of tools and models for supplier selection problem is yet to surface and the banking and finance industry here in Ethiopia is no exception. Thus, the purpose of this research was to address supplier selection problem through modeling and application of analytical hierarchy ...

  1. Dealing with selection bias in educational transition models

    DEFF Research Database (Denmark)

    Holm, Anders; Jæger, Mads Meier

    2011-01-01

    This paper proposes the bivariate probit selection model (BPSM) as an alternative to the traditional Mare model for analyzing educational transitions. The BPSM accounts for selection on unobserved variables by allowing for unobserved variables which affect the probability of making educational tr...

  2. On Optimal Input Design and Model Selection for Communication Channels

    Energy Technology Data Exchange (ETDEWEB)

    Li, Yanyan [ORNL; Djouadi, Seddik M [ORNL; Olama, Mohammed M [ORNL

    2013-01-01

    In this paper, the optimal model (structure) selection and input design which minimize the worst case identification error for communication systems are provided. The problem is formulated using metric complexity theory in a Hilbert space setting. It is pointed out that model selection and input design can be handled independently. Kolmogorov n-width is used to characterize the representation error introduced by model selection, while Gel fand and Time n-widths are used to represent the inherent error introduced by input design. After the model is selected, an optimal input which minimizes the worst case identification error is shown to exist. In particular, it is proven that the optimal model for reducing the representation error is a Finite Impulse Response (FIR) model, and the optimal input is an impulse at the start of the observation interval. FIR models are widely popular in communication systems, such as, in Orthogonal Frequency Division Multiplexing (OFDM) systems.

  3. Health-Care Waste Treatment Technology Selection Using the Interval 2-Tuple Induced TOPSIS Method.

    Science.gov (United States)

    Lu, Chao; You, Jian-Xin; Liu, Hu-Chen; Li, Ping

    2016-06-04

    Health-care waste (HCW) management is a major challenge for municipalities, particularly in the cities of developing nations. Selecting the best treatment technology for HCW can be regarded as a complex multi-criteria decision making (MCDM) issue involving a number of alternatives and multiple evaluation criteria. In addition, decision makers tend to express their personal assessments via multi-granularity linguistic term sets because of different backgrounds and knowledge, some of which may be imprecise, uncertain and incomplete. Therefore, the main objective of this study is to propose a new hybrid decision making approach combining interval 2-tuple induced distance operators with the technique for order preference by similarity to an ideal solution (TOPSIS) for tackling HCW treatment technology selection problems with linguistic information. The proposed interval 2-tuple induced TOPSIS (ITI-TOPSIS) can not only model the uncertainty and diversity of the assessment information given by decision makers, but also reflect the complex attitudinal characters of decision makers and provide much more complete information for the selection of the optimum disposal alternative. Finally, an empirical example in Shanghai, China is provided to illustrate the proposed decision making method, and results show that the ITI-TOPSIS proposed in this paper can solve the problem of HCW treatment technology selection effectively.

  4. Python Program to Select HII Region Models

    Science.gov (United States)

    Miller, Clare; Lamarche, Cody; Vishwas, Amit; Stacey, Gordon J.

    2016-01-01

    HII regions are areas of singly ionized Hydrogen formed by the ionizing radiaiton of upper main sequence stars. The infrared fine-structure line emissions, particularly Oxygen, Nitrogen, and Neon, can give important information about HII regions including gas temperature and density, elemental abundances, and the effective temperature of the stars that form them. The processes involved in calculating this information from observational data are complex. Models, such as those provided in Rubin 1984 and those produced by Cloudy (Ferland et al, 2013) enable one to extract physical parameters from observational data. However, the multitude of search parameters can make sifting through models tedious. I digitized Rubin's models and wrote a Python program that is able to take observed line ratios and their uncertainties and find the Rubin or Cloudy model that best matches the observational data. By creating a Python script that is user friendly and able to quickly sort through models with a high level of accuracy, this work increases efficiency and reduces human error in matching HII region models to observational data.

  5. Ground-water transport model selection and evaluation guidelines

    International Nuclear Information System (INIS)

    Simmons, C.S.; Cole, C.R.

    1983-01-01

    Guidelines are being developed to assist potential users with selecting appropriate computer codes for ground-water contaminant transport modeling. The guidelines are meant to assist managers with selecting appropriate predictive models for evaluating either arid or humid low-level radioactive waste burial sites. Evaluation test cases in the form of analytical solutions to fundamental equations and experimental data sets have been identified and recommended to ensure adequate code selection, based on accurate simulation of relevant physical processes. The recommended evaluation procedures will consider certain technical issues related to the present limitations in transport modeling capabilities. A code-selection plan will depend on identifying problem objectives, determining the extent of collectible site-specific data, and developing a site-specific conceptual model for the involved hydrology. Code selection will be predicated on steps for developing an appropriate systems model. This paper will review the progress in developing those guidelines. 12 references

  6. Model and Variable Selection Procedures for Semiparametric Time Series Regression

    Directory of Open Access Journals (Sweden)

    Risa Kato

    2009-01-01

    Full Text Available Semiparametric regression models are very useful for time series analysis. They facilitate the detection of features resulting from external interventions. The complexity of semiparametric models poses new challenges for issues of nonparametric and parametric inference and model selection that frequently arise from time series data analysis. In this paper, we propose penalized least squares estimators which can simultaneously select significant variables and estimate unknown parameters. An innovative class of variable selection procedure is proposed to select significant variables and basis functions in a semiparametric model. The asymptotic normality of the resulting estimators is established. Information criteria for model selection are also proposed. We illustrate the effectiveness of the proposed procedures with numerical simulations.

  7. Selective Mutism: A Review of Etiology, Comorbidities, and Treatment

    OpenAIRE

    Wong, Priscilla

    2010-01-01

    Selective mutism is a rare and multidimensional childhood disorder that typically affects children entering school age. It is characterized by the persistent failure to speak in select social settings despite possessing the ability to speak and speak comfortably in more familiar settings. Many theories attempt to explain the etiology of selective mutism.

  8. Methods for model selection in applied science and engineering.

    Energy Technology Data Exchange (ETDEWEB)

    Field, Richard V., Jr.

    2004-10-01

    Mathematical models are developed and used to study the properties of complex systems and/or modify these systems to satisfy some performance requirements in just about every area of applied science and engineering. A particular reason for developing a model, e.g., performance assessment or design, is referred to as the model use. Our objective is the development of a methodology for selecting a model that is sufficiently accurate for an intended use. Information on the system being modeled is, in general, incomplete, so that there may be two or more models consistent with the available information. The collection of these models is called the class of candidate models. Methods are developed for selecting the optimal member from a class of candidate models for the system. The optimal model depends on the available information, the selected class of candidate models, and the model use. Classical methods for model selection, including the method of maximum likelihood and Bayesian methods, as well as a method employing a decision-theoretic approach, are formulated to select the optimal model for numerous applications. There is no requirement that the candidate models be random. Classical methods for model selection ignore model use and require data to be available. Examples are used to show that these methods can be unreliable when data is limited. The decision-theoretic approach to model selection does not have these limitations, and model use is included through an appropriate utility function. This is especially important when modeling high risk systems, where the consequences of using an inappropriate model for the system can be disastrous. The decision-theoretic method for model selection is developed and applied for a series of complex and diverse applications. These include the selection of the: (1) optimal order of the polynomial chaos approximation for non-Gaussian random variables and stationary stochastic processes, (2) optimal pressure load model to be

  9. Random effect selection in generalised linear models

    DEFF Research Database (Denmark)

    Denwood, Matt; Houe, Hans; Forkman, Björn

    We analysed abattoir recordings of meat inspection codes with possible relevance to onfarm animal welfare in cattle. Random effects logistic regression models were used to describe individual-level data obtained from 461,406 cattle slaughtered in Denmark. Our results demonstrate that the largest...

  10. Host population structure and treatment frequency maintain balancing selection on drug resistance

    Science.gov (United States)

    Baskerville, Edward B.; Colijn, Caroline; Hanage, William; Fraser, Christophe; Lipsitch, Marc

    2017-01-01

    It is a truism that antimicrobial drugs select for resistance, but explaining pathogen- and population-specific variation in patterns of resistance remains an open problem. Like other common commensals, Streptococcus pneumoniae has demonstrated persistent coexistence of drug-sensitive and drug-resistant strains. Theoretically, this outcome is unlikely. We modelled the dynamics of competing strains of S. pneumoniae to investigate the impact of transmission dynamics and treatment-induced selective pressures on the probability of stable coexistence. We find that the outcome of competition is extremely sensitive to structure in the host population, although coexistence can arise from age-assortative transmission models with age-varying rates of antibiotic use. Moreover, we find that the selective pressure from antibiotics arises not so much from the rate of antibiotic use per se but from the frequency of treatment: frequent antibiotic therapy disproportionately impacts the fitness of sensitive strains. This same phenomenon explains why serotypes with longer durations of carriage tend to be more resistant. These dynamics may apply to other potentially pathogenic, microbial commensals and highlight how population structure, which is often omitted from models, can have a large impact. PMID:28835542

  11. Bevacizumab in the treatment of NSCLC: patient selection and perspectives

    Directory of Open Access Journals (Sweden)

    Russo AE

    2017-12-01

    Full Text Available Alessia E Russo,1 Domenico Priolo,1 Giovanna Antonelli,1 Massimo Libra,2 James A McCubrey,3 Francesco Ferraù1 1Medical Oncology Department, San Vincenzo Hospital, Taormina (Messina, Italy; 2Laboratory of Translational Oncology & Functional Genomics, Department of Biomedical and Biotechnological Sciences, University of Catania, Catania, Italy; 3Department of Microbiology and Immunology, Brody School of Medicine at East Carolina University, Greenville, NC, USA Abstract: Non-small-cell lung cancer (NSCLC represents about 85% of all lung cancers, and more than half of NSCLCs are diagnosed at an advanced stage. Chemotherapy has reached a plateau in the overall survival curve of about 10 months. Therefore, in last decade novel targeted approaches have been developed to extend survival of these patients, including antiangiogenic treatment. Vascular endothelial growth factor (VEGF signaling pathway plays a dominant role in stimulating angiogenesis, which is the main process promoting tumor growth and metastasis. Bevacizumab (bev; Avastin® is a recombinant humanized monoclonal antibody that neutralizes VEGF’s biologic activity through a steric blocking of its binding with VEGF receptor. Currently, bev is the only antiangiogenic agent approved for the first-line treatment of advanced or recurrent nonsquamous NSCLC in “bev-eligible” patients. The ineligibility to receive bev is related to its toxicity. In the pivotal trials of bev in NSCLC, fatal bleeding events including pulmonary hemorrhage were observed with rates higher in the chemotherapy-plus-bev group. Therefore, in order to reduce the incidence of severe pulmonary hemorrhage, numerous exclusion criteria have been characteristically applied for bev such as central tumor localization or tumor cavitation, use of anticoagulant therapy, presence of brain metastases, age of patients (elderly. Subsequent studies designed to evaluate the safety of bev have demonstrated that this agent is safe and

  12. The genealogy of samples in models with selection.

    Science.gov (United States)

    Neuhauser, C; Krone, S M

    1997-02-01

    We introduce the genealogy of a random sample of genes taken from a large haploid population that evolves according to random reproduction with selection and mutation. Without selection, the genealogy is described by Kingman's well-known coalescent process. In the selective case, the genealogy of the sample is embedded in a graph with a coalescing and branching structure. We describe this graph, called the ancestral selection graph, and point out differences and similarities with Kingman's coalescent. We present simulations for a two-allele model with symmetric mutation in which one of the alleles has a selective advantage over the other. We find that when the allele frequencies in the population are already in equilibrium, then the genealogy does not differ much from the neutral case. This is supported by rigorous results. Furthermore, we describe the ancestral selection graph for other selective models with finitely many selection classes, such as the K-allele models, infinitely-many-alleles models. DNA sequence models, and infinitely-many-sites models, and briefly discuss the diploid case.

  13. Modeling shape selection of buckled dielectric elastomers

    Science.gov (United States)

    Langham, Jacob; Bense, Hadrien; Barkley, Dwight

    2018-02-01

    A dielectric elastomer whose edges are held fixed will buckle, given a sufficiently applied voltage, resulting in a nontrivial out-of-plane deformation. We study this situation numerically using a nonlinear elastic model which decouples two of the principal electrostatic stresses acting on an elastomer: normal pressure due to the mutual attraction of oppositely charged electrodes and tangential shear ("fringing") due to repulsion of like charges at the electrode edges. These enter via physically simplified boundary conditions that are applied in a fixed reference domain using a nondimensional approach. The method is valid for small to moderate strains and is straightforward to implement in a generic nonlinear elasticity code. We validate the model by directly comparing the simulated equilibrium shapes with the experiment. For circular electrodes which buckle axisymetrically, the shape of the deflection profile is captured. Annular electrodes of different widths produce azimuthal ripples with wavelengths that match our simulations. In this case, it is essential to compute multiple equilibria because the first model solution obtained by the nonlinear solver (Newton's method) is often not the energetically favored state. We address this using a numerical technique known as "deflation." Finally, we observe the large number of different solutions that may be obtained for the case of a long rectangular strip.

  14. Improving treatment outcome assessment in a mouse tuberculosis model.

    Science.gov (United States)

    Mourik, Bas C; Svensson, Robin J; de Knegt, Gerjo J; Bax, Hannelore I; Verbon, Annelies; Simonsson, Ulrika S H; de Steenwinkel, Jurriaan E M

    2018-04-09

    Preclinical treatment outcome evaluation of tuberculosis (TB) occurs primarily in mice. Current designs compare relapse rates of different regimens at selected time points, but lack information about the correlation between treatment length and treatment outcome, which is required to efficiently estimate a regimens' treatment-shortening potential. Therefore we developed a new approach. BALB/c mice were infected with a Mycobacterium tuberculosis Beijing genotype strain and were treated with rifapentine-pyrazinamide-isoniazid-ethambutol (R p ZHE), rifampicin-pyrazinamide-moxifloxacin-ethambutol (RZME) or rifampicin-pyrazinamide-moxifloxacin-isoniazid (RZMH). Treatment outcome was assessed in n = 3 mice after 9 different treatment lengths between 2-6 months. Next, we created a mathematical model that best fitted the observational data and used this for inter-regimen comparison. The observed data were best described by a sigmoidal E max model in favor over linear or conventional E max models. Estimating regimen-specific parameters showed significantly higher curative potentials for RZME and R p ZHE compared to RZMH. In conclusion, we provide a new design for treatment outcome evaluation in a mouse TB model, which (i) provides accurate tools for assessment of the relationship between treatment length and predicted cure, (ii) allows for efficient comparison between regimens and (iii) adheres to the reduction and refinement principles of laboratory animal use.

  15. Modeling HIV-1 drug resistance as episodic directional selection.

    Directory of Open Access Journals (Sweden)

    Ben Murrell

    Full Text Available The evolution of substitutions conferring drug resistance to HIV-1 is both episodic, occurring when patients are on antiretroviral therapy, and strongly directional, with site-specific resistant residues increasing in frequency over time. While methods exist to detect episodic diversifying selection and continuous directional selection, no evolutionary model combining these two properties has been proposed. We present two models of episodic directional selection (MEDS and EDEPS which allow the a priori specification of lineages expected to have undergone directional selection. The models infer the sites and target residues that were likely subject to directional selection, using either codon or protein sequences. Compared to its null model of episodic diversifying selection, MEDS provides a superior fit to most sites known to be involved in drug resistance, and neither one test for episodic diversifying selection nor another for constant directional selection are able to detect as many true positives as MEDS and EDEPS while maintaining acceptable levels of false positives. This suggests that episodic directional selection is a better description of the process driving the evolution of drug resistance.

  16. Wastewater treatment modelling: dealing with uncertainties

    DEFF Research Database (Denmark)

    Belia, E.; Amerlinck, Y.; Benedetti, L.

    2009-01-01

    This paper serves as a problem statement of the issues surrounding uncertainty in wastewater treatment modelling. The paper proposes a structure for identifying the sources of uncertainty introduced during each step of an engineering project concerned with model-based design or optimisation...... of a wastewater treatment system. It briefly references the methods currently used to evaluate prediction accuracy and uncertainty and discusses the relevance of uncertainty evaluations in model applications. The paper aims to raise awareness and initiate a comprehensive discussion among professionals on model...

  17. Statistical Model Selection for TID Hardness Assurance

    Science.gov (United States)

    Ladbury, R.; Gorelick, J. L.; McClure, S.

    2010-01-01

    Radiation Hardness Assurance (RHA) methodologies against Total Ionizing Dose (TID) degradation impose rigorous statistical treatments for data from a part's Radiation Lot Acceptance Test (RLAT) and/or its historical performance. However, no similar methods exist for using "similarity" data - that is, data for similar parts fabricated in the same process as the part under qualification. This is despite the greater difficulty and potential risk in interpreting of similarity data. In this work, we develop methods to disentangle part-to-part, lot-to-lot and part-type-to-part-type variation. The methods we develop apply not just for qualification decisions, but also for quality control and detection of process changes and other "out-of-family" behavior. We begin by discussing the data used in ·the study and the challenges of developing a statistic providing a meaningful measure of degradation across multiple part types, each with its own performance specifications. We then develop analysis techniques and apply them to the different data sets.

  18. Optimizing the selection of small-town wastewater treatment processes

    Science.gov (United States)

    Huang, Jianping; Zhang, Siqi

    2018-04-01

    Municipal wastewater treatment is energy-intensive. This high energy consumption causes high sewage treatment plant operating costs and increases the energy burden. To mitigate the adverse impacts of China’s development, sewage treatment plants should adopt effective energy-saving technologies. Artificial fortified natural water treatment and use of activated sludge and biofilm are all suitable technologies for small-town sewage treatment. This study features an analysis of the characteristics of small and medium-sized township sewage, an overview of current technologies, and a discussion of recent progress in sewage treatment. Based on this, an analysis of existing problems in municipal wastewater treatment is presented, and countermeasures to improve sewage treatment in small and medium-sized towns are proposed.

  19. Variable selection for mixture and promotion time cure rate models.

    Science.gov (United States)

    Masud, Abdullah; Tu, Wanzhu; Yu, Zhangsheng

    2016-11-16

    Failure-time data with cured patients are common in clinical studies. Data from these studies are typically analyzed with cure rate models. Variable selection methods have not been well developed for cure rate models. In this research, we propose two least absolute shrinkage and selection operators based methods, for variable selection in mixture and promotion time cure models with parametric or nonparametric baseline hazards. We conduct an extensive simulation study to assess the operating characteristics of the proposed methods. We illustrate the use of the methods using data from a study of childhood wheezing. © The Author(s) 2016.

  20. Partner Selection Optimization Model of Agricultural Enterprises in Supply Chain

    OpenAIRE

    Feipeng Guo; Qibei Lu

    2013-01-01

    With more and more importance of correctly selecting partners in supply chain of agricultural enterprises, a large number of partner evaluation techniques are widely used in the field of agricultural science research. This study established a partner selection model to optimize the issue of agricultural supply chain partner selection. Firstly, it constructed a comprehensive evaluation index system after analyzing the real characteristics of agricultural supply chain. Secondly, a heuristic met...

  1. Effect of Model Selection on Computed Water Balance Components

    NARCIS (Netherlands)

    Jhorar, R.K.; Smit, A.A.M.F.R.; Roest, C.W.J.

    2009-01-01

    Soil water flow modelling approaches as used in four selected on-farm water management models, namely CROPWAT. FAIDS, CERES and SWAP, are compared through numerical experiments. The soil water simulation approaches used in the first three models are reformulated to incorporate ail evapotranspiration

  2. Ensembling Variable Selectors by Stability Selection for the Cox Model

    Directory of Open Access Journals (Sweden)

    Qing-Yan Yin

    2017-01-01

    Full Text Available As a pivotal tool to build interpretive models, variable selection plays an increasingly important role in high-dimensional data analysis. In recent years, variable selection ensembles (VSEs have gained much interest due to their many advantages. Stability selection (Meinshausen and Bühlmann, 2010, a VSE technique based on subsampling in combination with a base algorithm like lasso, is an effective method to control false discovery rate (FDR and to improve selection accuracy in linear regression models. By adopting lasso as a base learner, we attempt to extend stability selection to handle variable selection problems in a Cox model. According to our experience, it is crucial to set the regularization region Λ in lasso and the parameter λmin properly so that stability selection can work well. To the best of our knowledge, however, there is no literature addressing this problem in an explicit way. Therefore, we first provide a detailed procedure to specify Λ and λmin. Then, some simulated and real-world data with various censoring rates are used to examine how well stability selection performs. It is also compared with several other variable selection approaches. Experimental results demonstrate that it achieves better or competitive performance in comparison with several other popular techniques.

  3. Elementary Teachers' Selection and Use of Visual Models

    Science.gov (United States)

    Lee, Tammy D.; Gail Jones, M.

    2018-02-01

    As science grows in complexity, science teachers face an increasing challenge of helping students interpret models that represent complex science systems. Little is known about how teachers select and use models when planning lessons. This mixed methods study investigated the pedagogical approaches and visual models used by elementary in-service and preservice teachers in the development of a science lesson about a complex system (e.g., water cycle). Sixty-seven elementary in-service and 69 elementary preservice teachers completed a card sort task designed to document the types of visual models (e.g., images) that teachers choose when planning science instruction. Quantitative and qualitative analyses were conducted to analyze the card sort task. Semistructured interviews were conducted with a subsample of teachers to elicit the rationale for image selection. Results from this study showed that both experienced in-service teachers and novice preservice teachers tended to select similar models and use similar rationales for images to be used in lessons. Teachers tended to select models that were aesthetically pleasing and simple in design and illustrated specific elements of the water cycle. The results also showed that teachers were not likely to select images that represented the less obvious dimensions of the water cycle. Furthermore, teachers selected visual models more as a pedagogical tool to illustrate specific elements of the water cycle and less often as a tool to promote student learning related to complex systems.

  4. Validation of elk resource selection models with spatially independent data

    Science.gov (United States)

    Priscilla K. Coe; Bruce K. Johnson; Michael J. Wisdom; John G. Cook; Marty Vavra; Ryan M. Nielson

    2011-01-01

    Knowledge of how landscape features affect wildlife resource use is essential for informed management. Resource selection functions often are used to make and validate predictions about landscape use; however, resource selection functions are rarely validated with data from landscapes independent of those from which the models were built. This problem has severely...

  5. A Working Model of Natural Selection Illustrated by Table Tennis

    Science.gov (United States)

    Dinc, Muhittin; Kilic, Selda; Aladag, Caner

    2013-01-01

    Natural selection is one of the most important topics in biology and it helps to clarify the variety and complexity of organisms. However, students in almost every stage of education find it difficult to understand the mechanism of natural selection and they can develop misconceptions about it. This article provides an active model of natural…

  6. Robust Decision-making Applied to Model Selection

    Energy Technology Data Exchange (ETDEWEB)

    Hemez, Francois M. [Los Alamos National Laboratory

    2012-08-06

    The scientific and engineering communities are relying more and more on numerical models to simulate ever-increasingly complex phenomena. Selecting a model, from among a family of models that meets the simulation requirements, presents a challenge to modern-day analysts. To address this concern, a framework is adopted anchored in info-gap decision theory. The framework proposes to select models by examining the trade-offs between prediction accuracy and sensitivity to epistemic uncertainty. The framework is demonstrated on two structural engineering applications by asking the following question: Which model, of several numerical models, approximates the behavior of a structure when parameters that define each of those models are unknown? One observation is that models that are nominally more accurate are not necessarily more robust, and their accuracy can deteriorate greatly depending upon the assumptions made. It is posited that, as reliance on numerical models increases, establishing robustness will become as important as demonstrating accuracy.

  7. Target Selection Models with Preference Variation Between Offenders

    NARCIS (Netherlands)

    Townsley, Michael; Birks, Daniel; Ruiter, Stijn; Bernasco, Wim; White, Gentry

    2016-01-01

    Objectives: This study explores preference variation in location choice strategies of residential burglars. Applying a model of offender target selection that is grounded in assertions of the routine activity approach, rational choice perspective, crime pattern and social disorganization theories,

  8. Akaike information criterion to select well-fit resist models

    Science.gov (United States)

    Burbine, Andrew; Fryer, David; Sturtevant, John

    2015-03-01

    In the field of model design and selection, there is always a risk that a model is over-fit to the data used to train the model. A model is well suited when it describes the physical system and not the stochastic behavior of the particular data collected. K-fold cross validation is a method to check this potential over-fitting to the data by calibrating with k-number of folds in the data, typically between 4 and 10. Model training is a computationally expensive operation, however, and given a wide choice of candidate models, calibrating each one repeatedly becomes prohibitively time consuming. Akaike information criterion (AIC) is an information-theoretic approach to model selection based on the maximized log-likelihood for a given model that only needs a single calibration per model. It is used in this study to demonstrate model ranking and selection among compact resist modelforms that have various numbers and types of terms to describe photoresist behavior. It is shown that there is a good correspondence of AIC to K-fold cross validation in selecting the best modelform, and it is further shown that over-fitting is, in most cases, not indicated. In modelforms with more than 40 fitting parameters, the size of the calibration data set benefits from additional parameters, statistically validating the model complexity.

  9. A risk assessment model for selecting cloud service providers

    OpenAIRE

    Cayirci, Erdal; Garaga, Alexandr; Santana de Oliveira, Anderson; Roudier, Yves

    2016-01-01

    The Cloud Adoption Risk Assessment Model is designed to help cloud customers in assessing the risks that they face by selecting a specific cloud service provider. It evaluates background information obtained from cloud customers and cloud service providers to analyze various risk scenarios. This facilitates decision making an selecting the cloud service provider with the most preferable risk profile based on aggregated risks to security, privacy, and service delivery. Based on this model we ...

  10. SELECTION MOMENTS AND GENERALIZED METHOD OF MOMENTS FOR HETEROSKEDASTIC MODELS

    Directory of Open Access Journals (Sweden)

    Constantin ANGHELACHE

    2016-06-01

    Full Text Available In this paper, the authors describe the selection methods for moments and the application of the generalized moments method for the heteroskedastic models. The utility of GMM estimators is found in the study of the financial market models. The selection criteria for moments are applied for the efficient estimation of GMM for univariate time series with martingale difference errors, similar to those studied so far by Kuersteiner.

  11. Model Selection in Continuous Test Norming With GAMLSS.

    Science.gov (United States)

    Voncken, Lieke; Albers, Casper J; Timmerman, Marieke E

    2017-06-01

    To compute norms from reference group test scores, continuous norming is preferred over traditional norming. A suitable continuous norming approach for continuous data is the use of the Box-Cox Power Exponential model, which is found in the generalized additive models for location, scale, and shape. Applying the Box-Cox Power Exponential model for test norming requires model selection, but it is unknown how well this can be done with an automatic selection procedure. In a simulation study, we compared the performance of two stepwise model selection procedures combined with four model-fit criteria (Akaike information criterion, Bayesian information criterion, generalized Akaike information criterion (3), cross-validation), varying data complexity, sampling design, and sample size in a fully crossed design. The new procedure combined with one of the generalized Akaike information criterion was the most efficient model selection procedure (i.e., required the smallest sample size). The advocated model selection procedure is illustrated with norming data of an intelligence test.

  12. Novel Selective Estrogen Mimics for the Treatment of Tamoxifen-Resistant Breast Cancer

    Science.gov (United States)

    Molloy, Mary Ellen; Perez White, Bethany E.; Gherezghiher, Teshome; Michalsen, Bradley T.; Xiong, Rui; Patel, Hitisha; Zhao, Huiping; Maximov, Philipp Y.; Jordan, V. Craig; Thatcher, Gregory R. J.; Tonetti, Debra A.

    2014-01-01

    Endocrine-resistant breast cancer is a major clinical obstacle. The use of 17β-estradiol (E2) has re-emerged as a potential treatment option following exhaustive use of tamoxifen (TAM) or aromatase inhibitors although side effects have hindered its clinical usage. Protein kinase C alpha (PKCα) expression was shown to be a predictor of disease outcome for patients receiving endocrine therapy and may predict a positive response to an estrogenic treatment. Here, we have investigated the use of novel benzothiophene selective estrogen mimics (SEMs) as an alternative to E2 for the treatment of TAM-resistant breast cancer. Following in vitro characterization of SEMs, a panel of clinically relevant PKCα-expressing, TAM-resistant models were used to investigate the antitumor effects of these compounds. SEM treatment resulted in growth inhibition and apoptosis of TAM-resistant cell lines in vitro. In vivo SEM treatment induced tumor regression of TAM-resistant T47D:A18/PKCα and T47D:A18-TAM1 tumor models. T47D:A18/PKCα tumor regression was accompanied by translocation of ERα to extranuclear sites, possibly defining a mechanism through which these SEMs initiate tumor regression. SEM treatment did not stimulate growth of E2-dependent T47D:A18/neo tumors. Additionally, unlike E2 or TAM, treatment with SEMs did not stimulate uterine weight gain. These findings suggest the further development of SEMs as a feasible therapeutic strategy for the treatment of endocrine-resistant breast cancer without the side effects associated with E2. PMID:25205655

  13. Selection Criteria in Regime Switching Conditional Volatility Models

    Directory of Open Access Journals (Sweden)

    Thomas Chuffart

    2015-05-01

    Full Text Available A large number of nonlinear conditional heteroskedastic models have been proposed in the literature. Model selection is crucial to any statistical data analysis. In this article, we investigate whether the most commonly used selection criteria lead to choice of the right specification in a regime switching framework. We focus on two types of models: the Logistic Smooth Transition GARCH and the Markov-Switching GARCH models. Simulation experiments reveal that information criteria and loss functions can lead to misspecification ; BIC sometimes indicates the wrong regime switching framework. Depending on the Data Generating Process used in the experiments, great care is needed when choosing a criterion.

  14. The Use of Evolution in a Central Action Selection Model

    Directory of Open Access Journals (Sweden)

    F. Montes-Gonzalez

    2007-01-01

    Full Text Available The use of effective central selection provides flexibility in design by offering modularity and extensibility. In earlier papers we have focused on the development of a simple centralized selection mechanism. Our current goal is to integrate evolutionary methods in the design of non-sequential behaviours and the tuning of specific parameters of the selection model. The foraging behaviour of an animal robot (animat has been modelled in order to integrate the sensory information from the robot to perform selection that is nearly optimized by the use of genetic algorithms. In this paper we present how selection through optimization finally arranges the pattern of presented behaviours for the foraging task. Hence, the execution of specific parts in a behavioural pattern may be ruled out by the tuning of these parameters. Furthermore, the intensive use of colour segmentation from a colour camera for locating a cylinder sets a burden on the calculations carried out by the genetic algorithm.

  15. A Hybrid Multiple Criteria Decision Making Model for Supplier Selection

    Directory of Open Access Journals (Sweden)

    Chung-Min Wu

    2013-01-01

    Full Text Available The sustainable supplier selection would be the vital part in the management of a sustainable supply chain. In this study, a hybrid multiple criteria decision making (MCDM model is applied to select optimal supplier. The fuzzy Delphi method, which can lead to better criteria selection, is used to modify criteria. Considering the interdependence among the selection criteria, analytic network process (ANP is then used to obtain their weights. To avoid calculation and additional pairwise comparisons of ANP, a technique for order preference by similarity to ideal solution (TOPSIS is used to rank the alternatives. The use of a combination of the fuzzy Delphi method, ANP, and TOPSIS, proposing an MCDM model for supplier selection, and applying these to a real case are the unique features of this study.

  16. Variable selection in Logistic regression model with genetic algorithm.

    Science.gov (United States)

    Zhang, Zhongheng; Trevino, Victor; Hoseini, Sayed Shahabuddin; Belciug, Smaranda; Boopathi, Arumugam Manivanna; Zhang, Ping; Gorunescu, Florin; Subha, Velappan; Dai, Songshi

    2018-02-01

    Variable or feature selection is one of the most important steps in model specification. Especially in the case of medical-decision making, the direct use of a medical database, without a previous analysis and preprocessing step, is often counterproductive. In this way, the variable selection represents the method of choosing the most relevant attributes from the database in order to build a robust learning models and, thus, to improve the performance of the models used in the decision process. In biomedical research, the purpose of variable selection is to select clinically important and statistically significant variables, while excluding unrelated or noise variables. A variety of methods exist for variable selection, but none of them is without limitations. For example, the stepwise approach, which is highly used, adds the best variable in each cycle generally producing an acceptable set of variables. Nevertheless, it is limited by the fact that it commonly trapped in local optima. The best subset approach can systematically search the entire covariate pattern space, but the solution pool can be extremely large with tens to hundreds of variables, which is the case in nowadays clinical data. Genetic algorithms (GA) are heuristic optimization approaches and can be used for variable selection in multivariable regression models. This tutorial paper aims to provide a step-by-step approach to the use of GA in variable selection. The R code provided in the text can be extended and adapted to other data analysis needs.

  17. Statistical model selection with “Big Data”

    Directory of Open Access Journals (Sweden)

    Jurgen A. Doornik

    2015-12-01

    Full Text Available Big Data offer potential benefits for statistical modelling, but confront problems including an excess of false positives, mistaking correlations for causes, ignoring sampling biases and selecting by inappropriate methods. We consider the many important requirements when searching for a data-based relationship using Big Data, and the possible role of Autometrics in that context. Paramount considerations include embedding relationships in general initial models, possibly restricting the number of variables to be selected over by non-statistical criteria (the formulation problem, using good quality data on all variables, analyzed with tight significance levels by a powerful selection procedure, retaining available theory insights (the selection problem while testing for relationships being well specified and invariant to shifts in explanatory variables (the evaluation problem, using a viable approach that resolves the computational problem of immense numbers of possible models.

  18. Multicriteria framework for selecting a process modelling language

    Science.gov (United States)

    Scanavachi Moreira Campos, Ana Carolina; Teixeira de Almeida, Adiel

    2016-01-01

    The choice of process modelling language can affect business process management (BPM) since each modelling language shows different features of a given process and may limit the ways in which a process can be described and analysed. However, choosing the appropriate modelling language for process modelling has become a difficult task because of the availability of a large number modelling languages and also due to the lack of guidelines on evaluating, and comparing languages so as to assist in selecting the most appropriate one. This paper proposes a framework for selecting a modelling language in accordance with the purposes of modelling. This framework is based on the semiotic quality framework (SEQUAL) for evaluating process modelling languages and a multicriteria decision aid (MCDA) approach in order to select the most appropriate language for BPM. This study does not attempt to set out new forms of assessment and evaluation criteria, but does attempt to demonstrate how two existing approaches can be combined so as to solve the problem of selection of modelling language. The framework is described in this paper and then demonstrated by means of an example. Finally, the advantages and disadvantages of using SEQUAL and MCDA in an integrated manner are discussed.

  19. The diagnosis and treatment of tubal pregnancy with selective salpingography

    International Nuclear Information System (INIS)

    Li Qunying

    2000-01-01

    Objective: To study feasibility of diagnosing and treating tubal pregnancy with selective salpingography. methods: 13 women diagnosed clinically as ectopic pregnancy without abdominal bleeding were studied and confirmed as tubal pregnancy with selective salpingography, MTX was then injected through fallopian tube. Urine hCG, blood β-hCG and US were studied during follow-up. Results: 12 cases tubal pregnancy were confirmed as well as 1 case of intra-uterine pregnancy. X-ray showed a localized dilation of fallopian tube, half-loop, ring-like or irregular shaped filling defect. In one case, cluster of grapes appearance of contrast medium could be seen at the umbrella end of fallopian tube. Of the 12 cases of tubal pregnancy, 10 were successfully treated, the successful rate was 83%. Conclusion: Selective salpingography is a simple safe and effective method of diagnosing and treating tubal pregnancy

  20. Anhedonia Predicts Poorer Recovery among Youth with Selective Serotonin Reuptake Inhibitor Treatment-Resistant Depression

    Science.gov (United States)

    McMakin, Dana L.; Olino, Thomas M.; Porta, Giovanna; Dietz, Laura J.; Emslie, Graham; Clarke, Gregory; Wagner, Karen Dineen; Asarnow, Joan R.; Ryan, Neal D.; Birmaher, Boris; Shamseddeen, Wael; Mayes, Taryn; Kennard, Betsy; Spirito, Anthony; Keller, Martin; Lynch, Frances L.; Dickerson, John F.; Brent, David A.

    2012-01-01

    Objective: To identify symptom dimensions of depression that predict recovery among selective serotonin reuptake inhibitor (SSRI) treatment-resistant adolescents undergoing second-step treatment. Method: The Treatment of Resistant Depression in Adolescents (TORDIA) trial included 334 SSRI treatment-resistant youth randomized to a medication…

  1. Morphea - selected local treatment methods and their effectiveness.

    Science.gov (United States)

    Narbutt, Joanna; Hołdrowicz, Agnieszka; Lesiak, Aleksandra

    2017-01-01

    Localised scleroderma is an uncommon connective tissue disease of multifactorial aetiology occurring in the paediatric and adult population. It is relatively difficult to conduct any research on the subject of this disease entity treatment due to the low number of patients suffering from morphea, a tendency of the disease to remit spontaneously, and not yet well recognised aetiology. Hence, there has been developed no causal treatment of well-proven effectiveness, and schedules of symptomatic therapy are not yet clearly determined. The paper depicts most widely used topical treatment methods in morphea therapy, which due to minor risk of systemic adverse effects seem to be a beneficial therapeutic alternative. The main aim of this article was to analyse different topical treatment options used in localised scleroderma therapy and to indicate the most appropriate, safe, and effective one.

  2. Trends in pharmacotherapy selection for the treatment of alcohol ...

    African Journals Online (AJOL)

    cycle of drinking, withdrawal, abstinence and relapse. The development of Lesch's typology[3] demonstrates how hereditary and environmental factors play out ... (model of anxiety) and Type 3 (model of depression) dependence may require more aggressive psychiatric and psychological intervention, while. Type 4 (model ...

  3. Optimal experiment design for model selection in biochemical networks.

    Science.gov (United States)

    Vanlier, Joep; Tiemann, Christian A; Hilbers, Peter A J; van Riel, Natal A W

    2014-02-20

    Mathematical modeling is often used to formalize hypotheses on how a biochemical network operates by discriminating between competing models. Bayesian model selection offers a way to determine the amount of evidence that data provides to support one model over the other while favoring simple models. In practice, the amount of experimental data is often insufficient to make a clear distinction between competing models. Often one would like to perform a new experiment which would discriminate between competing hypotheses. We developed a novel method to perform Optimal Experiment Design to predict which experiments would most effectively allow model selection. A Bayesian approach is applied to infer model parameter distributions. These distributions are sampled and used to simulate from multivariate predictive densities. The method is based on a k-Nearest Neighbor estimate of the Jensen Shannon divergence between the multivariate predictive densities of competing models. We show that the method successfully uses predictive differences to enable model selection by applying it to several test cases. Because the design criterion is based on predictive distributions, which can be computed for a wide range of model quantities, the approach is very flexible. The method reveals specific combinations of experiments which improve discriminability even in cases where data is scarce. The proposed approach can be used in conjunction with existing Bayesian methodologies where (approximate) posteriors have been determined, making use of relations that exist within the inferred posteriors.

  4. Quantile hydrologic model selection and model structure deficiency assessment : 1. Theory

    NARCIS (Netherlands)

    Pande, S.

    2013-01-01

    A theory for quantile based hydrologic model selection and model structure deficiency assessment is presented. The paper demonstrates that the degree to which a model selection problem is constrained by the model structure (measured by the Lagrange multipliers of the constraints) quantifies

  5. Fuzzy Investment Portfolio Selection Models Based on Interval Analysis Approach

    Directory of Open Access Journals (Sweden)

    Haifeng Guo

    2012-01-01

    Full Text Available This paper employs fuzzy set theory to solve the unintuitive problem of the Markowitz mean-variance (MV portfolio model and extend it to a fuzzy investment portfolio selection model. Our model establishes intervals for expected returns and risk preference, which can take into account investors' different investment appetite and thus can find the optimal resolution for each interval. In the empirical part, we test this model in Chinese stocks investment and find that this model can fulfill different kinds of investors’ objectives. Finally, investment risk can be decreased when we add investment limit to each stock in the portfolio, which indicates our model is useful in practice.

  6. Development of an Environment for Software Reliability Model Selection

    Science.gov (United States)

    1992-09-01

    now is directed to other related problems such as tools for model selection, multiversion programming, and software fault tolerance modeling... multiversion programming, 7. Hlardware can be repaired by spare modules, which is not. the case for software, 2-6 N. Preventive maintenance is very important

  7. Selection Bias in Educational Transition Models: Theory and Empirical Evidence

    DEFF Research Database (Denmark)

    Holm, Anders; Jæger, Mads

    Most studies using Mare’s (1980, 1981) seminal model of educational transitions find that the effect of family background decreases across transitions. Recently, Cameron and Heckman (1998, 2001) have argued that the “waning coefficients” in the Mare model are driven by selection on unobserved...... the United States, United Kingdom, Denmark, and the Netherlands shows that when we take selection into account the effect of family background variables on educational transitions is largely constant across transitions. We also discuss several difficulties in estimating educational transition models which...

  8. Novel web service selection model based on discrete group search.

    Science.gov (United States)

    Zhai, Jie; Shao, Zhiqing; Guo, Yi; Zhang, Haiteng

    2014-01-01

    In our earlier work, we present a novel formal method for the semiautomatic verification of specifications and for describing web service composition components by using abstract concepts. After verification, the instantiations of components were selected to satisfy the complex service performance constraints. However, selecting an optimal instantiation, which comprises different candidate services for each generic service, from a large number of instantiations is difficult. Therefore, we present a new evolutionary approach on the basis of the discrete group search service (D-GSS) model. With regard to obtaining the optimal multiconstraint instantiation of the complex component, the D-GSS model has competitive performance compared with other service selection models in terms of accuracy, efficiency, and ability to solve high-dimensional service composition component problems. We propose the cost function and the discrete group search optimizer (D-GSO) algorithm and study the convergence of the D-GSS model through verification and test cases.

  9. Methodology for the treatment of model uncertainty

    Science.gov (United States)

    Droguett, Enrique Lopez

    The development of a conceptual, unified, framework and methodology for treating model and parameter uncertainties is the subject of this work. Firstly, a discussion on the philosophical grounds of notions such as reality, modeling, models, and their relation is presented. On this, a characterization of the modeling process is presented. The concept of uncertainty, addressing controversial topics such as type and sources of uncertainty, are investigated arguing that uncertainty is fundamentally a characterization of lack of knowledge and as such all uncertainty are of the same type. A discussion about the roles of a model structure and model parameters is presented, in which it is argued that a distinction is for convenience and a function of the stage in the modeling process. From the foregoing discussion, a Bayesian framework for an integrated assessment of model and parameter uncertainties is developed. The methodology has as its central point the treatment of model as source of information regarding the unknown of interest. It allows for the assessment of the model characteristics affecting its performance, such as bias and precision. It also permits the assessment of possible dependencies among multiple models. Furthermore, the proposed framework makes possible the use of not only information from models (e.g., point estimates, qualitative assessments), but also evidence about the models themselves (performance data, confidence in the model, applicability of the model). The methodology is then applied in the context of fire risk models where several examples with real data are studied. These examples demonstrate how the framework and specific techniques developed in this study can address cases involving multiple models, use of performance data to update the predictive capabilities of a model, and the case where a model is applied in a context other than one for which it is designed.

  10. Selection of climate change scenario data for impact modelling

    DEFF Research Database (Denmark)

    Sloth Madsen, M; Fox Maule, C; MacKellar, N

    2012-01-01

    Impact models investigating climate change effects on food safety often need detailed climate data. The aim of this study was to select climate change projection data for selected crop phenology and mycotoxin impact models. Using the ENSEMBLES database of climate model output, this study...... illustrates how the projected climate change signal of important variables as temperature, precipitation and relative humidity depends on the choice of the climate model. Using climate change projections from at least two different climate models is recommended to account for model uncertainty. To make...... the climate projections suitable for impact analysis at the local scale a weather generator approach was adopted. As the weather generator did not treat all the necessary variables, an ad-hoc statistical method was developed to synthesise realistic values of missing variables. The method is presented...

  11. Maxillary Sinus Floor Augmentation: a Review of Selected Treatment Modalities

    Directory of Open Access Journals (Sweden)

    Thomas Starch-Jensen

    2017-09-01

    Full Text Available Objectives: The objective of the present study is to present the current best evidence for enhancement of the vertical alveolar bone height and oral rehabilitation of the atrophic posterior maxilla with dental implants and propose some evidence-based treatment guidelines. Material and Methods: A comprehensive review of the English literature including MEDLINE (PubMed, Embase and Cochrane Library search was conducted assessing the final implant treatment outcome after oral rehabilitation of the atrophic posterior maxilla with dental implants. No year of publication restriction was applied. The clinical, radiological and histomorphometric outcome as well as complications are presented after maxillary sinus floor augmentation applying the lateral window technique with a graft material, maxillary sinus membrane elevation without a graft material and osteotome-mediated sinus floor elevation with or without the use of a graft material. Results: High implant survival rate and new bone formation was reported with the three treatment modalities. Perforation of the Schneiderian membrane was the most common complication, but the final implant treatment outcome was not influenced by a Schneiderian membrane perforation. Conclusions: The different surgical techniques for enhancement of the vertical alveolar bone height in the posterior part of the maxilla revealed high implant survival with a low incidence of complications. However, the indication for the various surgical techniques is not strictly equivalent and the treatment choice should be based on a careful evaluation of the individual case. Moreover, further high evidence-based and well reported long-term studies are needed before one treatment modality might be considered superior to another.

  12. Adverse Selection Models with Three States of Nature

    Directory of Open Access Journals (Sweden)

    Daniela MARINESCU

    2011-02-01

    Full Text Available In the paper we analyze an adverse selection model with three states of nature, where both the Principal and the Agent are risk neutral. When solving the model, we use the informational rents and the efforts as variables. We derive the optimal contract in the situation of asymmetric information. The paper ends with the characteristics of the optimal contract and the main conclusions of the model.

  13. [Outpatient treatment of selective mutism: long-standing selective mutism in a 17-year-old male].

    Science.gov (United States)

    Herdener-Pinnekamp, Katharina; Gundelfinger, Ronnie; Steinhausen, Hans-Christoph

    2010-01-01

    The present case report describes the successful treatment of a 17 year old male adolescent suffering for 10 years from selective mutism. Following a summary review of recent publications on therapy approaches, the report describes the treatment concept in the present case, including detailed assessment of co-morbid disorders, motivation for change, behaviour therapy with supporting drug intervention, and intensive co-operation with parents and other caretakers.

  14. A SUPPLIER SELECTION MODEL FOR SOFTWARE DEVELOPMENT OUTSOURCING

    Directory of Open Access Journals (Sweden)

    Hancu Lucian-Viorel

    2010-12-01

    Full Text Available This paper presents a multi-criteria decision making model used for supplier selection for software development outsourcing on e-marketplaces. This model can be used in auctions. The supplier selection process becomes complex and difficult on last twenty years since the Internet plays an important role in business management. Companies have to concentrate their efforts on their core activities and the others activities should be realized by outsourcing. They can achieve significant cost reduction by using e-marketplaces in their purchase process and by using decision support systems on supplier selection. In the literature were proposed many approaches for supplier evaluation and selection process. The performance of potential suppliers is evaluated using multi criteria decision making methods rather than considering a single factor cost.

  15. Treatment with a selective histone deacetylase 6 inhibitor decreases lupus nephritis in NZB/W mice.

    Science.gov (United States)

    Vieson, Miranda D; Gojmerac, Alexander M; Khan, Deena; Dai, Rujuan; van Duzer, John H; Mazitschek, Ralph; Caudell, David L; Liao, Xiaofeng; Luo, Xin M; Reilly, Christopher M

    2017-12-01

    To date, there are 18 histone deacetylase (HDAC) enzymes, divided into four classes, which alter protein function by removing acetyl groups from lysine residues. Prior studies report that non-selective HDAC inhibitors decrease disease in lupus mouse models. Concern for adverse side effects of non-selective HDAC inhibition supports investigation of selective-HDAC inhibition. We hypothesized that a selective HDAC-6 inhibitor (HDAC6i) will alleviate disease in a mouse model of lupus by increasing acetylation of alpha-tubulin. Intraperitoneal injections of the selective HDAC6i ACY-1083 (0.3 mg/kg, 1 mg/kg, or 3 mg/kg), vehicle control, or dexamethasone were administered to 21-week-old, female NZB/W mice, 5 days a week, for 13 weeks. Disease progression was evaluated by proteinuria, serum levels of anti-dsDNA antibody, cytokines and immunoglobulins, and post mortem evaluation of nephritis and T cell populations in the spleen. HDAC6i treatment decreased proteinuria, glomerular histopathology, IgG, and C3 scores when compared to vehicle-treated mice. Within glomeruli of HDAC6i-treated mice, there was increased acetylation of alpha-tubulin and decreased NF-κB. Additionally, HDAC6i decreased serum IL-12/IL-23 and Th17 cells in the spleen. Taken together, these results suggest HDAC-6 inhibition may decrease lupus nephritis in NZB/W mice via mechanisms involving acetylation of alpha-tubulin and decreased NF-κB in glomeruli as well as inhibition of Th17 cells.

  16. Modeling quality attributes and metrics for web service selection

    Science.gov (United States)

    Oskooei, Meysam Ahmadi; Daud, Salwani binti Mohd; Chua, Fang-Fang

    2014-06-01

    Since the service-oriented architecture (SOA) has been designed to develop the system as a distributed application, the service selection has become a vital aspect of service-oriented computing (SOC). Selecting the appropriate web service with respect to quality of service (QoS) through using mathematical solution for optimization of problem turns the service selection problem into a common concern for service users. Nowadays, number of web services that provide the same functionality is increased and selection of services from a set of alternatives which differ in quality parameters can be difficult for service consumers. In this paper, a new model for QoS attributes and metrics is proposed to provide a suitable solution for optimizing web service selection and composition with low complexity.

  17. [On selection criteria in spatially distributed models of competition].

    Science.gov (United States)

    Il'ichev, V G; Il'icheva, O A

    2014-01-01

    Discrete models of competitors (initial population and mutants) are considered in which reproduction is set by increasing and concave function, and migration in the space consisting of a set of areas, is described by a Markov matrix. This allows the use of the theory of monotonous operators to study problems of selection, coexistence and stability. It is shown that the higher is the number of areas, more and more severe constraints of selective advantage to initial population are required.

  18. Comparing the staffing models of outsourcing in selected companies

    OpenAIRE

    Chaloupková, Věra

    2010-01-01

    This thesis deals with problems of takeover of employees in outsourcing. The capital purpose is to compare the staffing model of outsourcing in selected companies. To compare in selected companies I chose multi-criteria analysis. This thesis is dividend into six chapters. The first charter is devoted to the theoretical part. In this charter describes the basic concepts as outsourcing, personal aspects, phase of the outsourcing projects, communications and culture. The rest of thesis is devote...

  19. Selective electrothermolysis of the sebaceous glands: treatment of facial seborrhea.

    Science.gov (United States)

    Kobayashi, Toshio; Tamada, Shinji

    2007-02-01

    There are few publications on facial seborrhea treatment. A focused therapy is needed. Our aim was to evaluate the efficacy of electrothermolysis of the sebaceous glands. In the preliminary studies, histologic changes in the cheek skin by electrothermolysis were examined by light microscopy. In the clinical studies, 15 adult women subjects with facial seborrhea were treated four times by the same procedure. A 1.50-mm-long needle with a 0.45-mm base insulation was inserted into pores in the forehead and cheeks, and a high-frequency electrical current was applied for 0.25 to 0.50 seconds with an output of 40 W. Each treatment took 60 to 90 minutes. The subjects returned for 6-months follow-up after their fourth treatment. Histology 1 and 6 months later showed fewer sebaceous glands and the development of fibrosis. All 12 subjects who completed the 6-month follow-up gave a subjective assessment of continuous reduction of facial seborrhea. On a scale of 0.0 to 3.0, the mean improvement score was 1.67+/-0.75. The mean reduction rate of skin surface lipids was 31.5% by sebumeter (pfacial seborrhea treatment.

  20. Economic assessment model architecture for AGC/AVLIS selection

    International Nuclear Information System (INIS)

    Hoglund, R.L.

    1984-01-01

    The economic assessment model architecture described provides the flexibility and completeness in economic analysis that the selection between AGC and AVLIS demands. Process models which are technology-specific will provide the first-order responses of process performance and cost to variations in process parameters. The economics models can be used to test the impacts of alternative deployment scenarios for a technology. Enterprise models provide global figures of merit for evaluating the DOE perspective on the uranium enrichment enterprise, and business analysis models compute the financial parameters from the private investor's viewpoint

  1. Lightweight Graphical Models for Selectivity Estimation Without Independence Assumptions

    DEFF Research Database (Denmark)

    Tzoumas, Kostas; Deshpande, Amol; Jensen, Christian S.

    2011-01-01

    , propagated exponentially, can lead to severely sub-optimal plans. Modern optimizers typically maintain one-dimensional statistical summaries and make the attribute value independence and join uniformity assumptions for efficiently estimating selectivities. Therefore, selectivity estimation errors in today......’s optimizers are frequently caused by missed correlations between attributes. We present a selectivity estimation approach that does not make the independence assumptions. By carefully using concepts from the field of graphical models, we are able to factor the joint probability distribution of all...

  2. Genetic signatures of natural selection in a model invasive ascidian

    Science.gov (United States)

    Lin, Yaping; Chen, Yiyong; Yi, Changho; Fong, Jonathan J.; Kim, Won; Rius, Marc; Zhan, Aibin

    2017-03-01

    Invasive species represent promising models to study species’ responses to rapidly changing environments. Although local adaptation frequently occurs during contemporary range expansion, the associated genetic signatures at both population and genomic levels remain largely unknown. Here, we use genome-wide gene-associated microsatellites to investigate genetic signatures of natural selection in a model invasive ascidian, Ciona robusta. Population genetic analyses of 150 individuals sampled in Korea, New Zealand, South Africa and Spain showed significant genetic differentiation among populations. Based on outlier tests, we found high incidence of signatures of directional selection at 19 loci. Hitchhiking mapping analyses identified 12 directional selective sweep regions, and all selective sweep windows on chromosomes were narrow (~8.9 kb). Further analyses indentified 132 candidate genes under selection. When we compared our genetic data and six crucial environmental variables, 16 putatively selected loci showed significant correlation with these environmental variables. This suggests that the local environmental conditions have left significant signatures of selection at both population and genomic levels. Finally, we identified “plastic” genomic regions and genes that are promising regions to investigate evolutionary responses to rapid environmental change in C. robusta.

  3. Ecohydrological model parameter selection for stream health evaluation.

    Science.gov (United States)

    Woznicki, Sean A; Nejadhashemi, A Pouyan; Ross, Dennis M; Zhang, Zhen; Wang, Lizhu; Esfahanian, Abdol-Hossein

    2015-04-01

    Variable selection is a critical step in development of empirical stream health prediction models. This study develops a framework for selecting important in-stream variables to predict four measures of biological integrity: total number of Ephemeroptera, Plecoptera, and Trichoptera (EPT) taxa, family index of biotic integrity (FIBI), Hilsenhoff biotic integrity (HBI), and fish index of biotic integrity (IBI). Over 200 flow regime and water quality variables were calculated using the Hydrologic Index Tool (HIT) and Soil and Water Assessment Tool (SWAT). Streams of the River Raisin watershed in Michigan were grouped using the Strahler stream classification system (orders 1-3 and orders 4-6), k-means clustering technique (two clusters: C1 and C2), and all streams (one grouping). For each grouping, variable selection was performed using Bayesian variable selection, principal component analysis, and Spearman's rank correlation. Following selection of best variable sets, models were developed to predict the measures of biological integrity using adaptive-neuro fuzzy inference systems (ANFIS), a technique well-suited to complex, nonlinear ecological problems. Multiple unique variable sets were identified, all which differed by selection method and stream grouping. Final best models were mostly built using the Bayesian variable selection method. The most effective stream grouping method varied by health measure, although k-means clustering and grouping by stream order were always superior to models built without grouping. Commonly selected variables were related to streamflow magnitude, rate of change, and seasonal nitrate concentration. Each best model was effective in simulating stream health observations, with EPT taxa validation R2 ranging from 0.67 to 0.92, FIBI ranging from 0.49 to 0.85, HBI from 0.56 to 0.75, and fish IBI at 0.99 for all best models. The comprehensive variable selection and modeling process proposed here is a robust method that extends our

  4. Financial applications of a Tabu search variable selection model

    Directory of Open Access Journals (Sweden)

    Zvi Drezner

    2001-01-01

    Full Text Available We illustrate how a comparatively new technique, a Tabu search variable selection model [Drezner, Marcoulides and Salhi (1999], can be applied efficiently within finance when the researcher must select a subset of variables from among the whole set of explanatory variables under consideration. Several types of problems in finance, including corporate and personal bankruptcy prediction, mortgage and credit scoring, and the selection of variables for the Arbitrage Pricing Model, require the researcher to select a subset of variables from a larger set. In order to demonstrate the usefulness of the Tabu search variable selection model, we: (1 illustrate its efficiency in comparison to the main alternative search procedures, such as stepwise regression and the Maximum R2 procedure, and (2 show how a version of the Tabu search procedure may be implemented when attempting to predict corporate bankruptcy. We accomplish (2 by indicating that a Tabu Search procedure increases the predictability of corporate bankruptcy by up to 10 percentage points in comparison to Altman's (1968 Z-Score model.

  5. Selecting an appropriate genetic evaluation model for selection in a developing dairy sector

    NARCIS (Netherlands)

    McGill, D.M.; Mulder, H.A.; Thomson, P.C.; Lievaart, J.J.

    2014-01-01

    This study aimed to identify genetic evaluation models (GEM) to accurately select cattle for milk production when only limited data are available. It is based on a data set from the Pakistani Sahiwal progeny testing programme which includes records from five government herds, each consisting of 100

  6. New treatment models for compulsive disorders.

    Science.gov (United States)

    Grant, Jon E; Fineberg, Naomi; van Ameringen, Michael; Cath, Danielle; Visser, Henny; Carmi, Lior; Pallanti, Stefano; Hollander, Eric; van Balkom, Anton J L M

    2016-05-01

    Obsessive compulsive disorder (OCD) as well as related disorders such as body dysmorphic disorder, tic disorder, and trichotillomania are all common and often debilitating. Although treatments are available, more effective approaches to these problems are needed. Thus this review article presents what is currently known about OCD and related disorders and suggests that understanding OCD more broadly as a compulsive disorder may allow for more effective treatment options. Toward that goal, the review presents new models of psychopharmacology and psychotherapy, as well as new brain stimulation strategies. Treatment advances, grounded in the neuroscience, have promise in advancing treatment response for OCD as well as other disorders of compulsivity. Copyright © 2015 Elsevier B.V. and ECNP. All rights reserved.

  7. THE TOXICITY OF SEWAGE FROM SELECTED MUNICIPAL SEWAGE TREATMENT PLANTS

    Directory of Open Access Journals (Sweden)

    Andrzej Butarewicz

    2015-07-01

    Full Text Available This paper presents the results of the toxicity of crude and purified sewage from three municipal sewage treatment plants located in the Podlaskie Voivodeship. The bioindicative analysis, based on the use of the Microtox M500 analyzer and Vibrio fischeri bacteria, has shown high or significant toxicity in all the raw wastewater samples, according to Persoone classification. Classification by Sawicki differentiates more the results of acute toxicity tests of crude sewage, because only 66% of samples were toxic. All treated wastewater samples showed no toxicity. The obtained results of the study indicate the efficacy of removing toxic compounds in waste water treatment plants based on the classic activated sludge technology and sequential reactors (SBR and no risk at discharging the treated sewage into the water of receivers.

  8. Tiotropium for the Treatment of Asthma: Patient Selection and Perspectives

    Directory of Open Access Journals (Sweden)

    V. Madhu Chari

    2018-01-01

    Full Text Available Asthma is a chronic disease of airway inflammation with a large global burden. Despite established, guideline-based stepwise therapy, a significant proportion of patients remain symptomatic and poorly controlled. As such, there is a need for additional safe, effective, convenient, and cost-effective therapies that can be broadly applied across a range of asthma phenotypes. Tiotropium is a long-acting muscarinic antagonist (LAMA that leads to bronchodilation by blocking endogenous acetylcholine receptors in the airways. Tiotropium has long been approved for the treatment of chronic obstructive pulmonary disease, and it has recently been recognized for its safety and efficacy in improving lung function and controlling asthma. Evidence from several Phase III trials in the adult and paediatric population has shown that tiotropium is well tolerated and significantly improves a range of endpoints as an add-on treatment to ICS therapy, regardless of baseline characteristics and clinical phenotypes. Consequently, regulatory authorities worldwide have recently licensed tiotropium as the only LAMA approved for the treatment of asthma. This review provides an overview of safety and efficacy data and discusses the use of tiotropium in patients across the range of asthma severities, ages, and phenotypes.

  9. The Properties of Model Selection when Retaining Theory Variables

    DEFF Research Database (Denmark)

    Hendry, David F.; Johansen, Søren

    Economic theories are often fitted directly to data to avoid possible model selection biases. We show that embedding a theory model that specifies the correct set of m relevant exogenous variables, x{t}, within the larger set of m+k candidate variables, (x{t},w{t}), then selection over the second...... set by their statistical significance can be undertaken without affecting the estimator distribution of the theory parameters. This strategy returns the theory-parameter estimates when the theory is correct, yet protects against the theory being under-specified because some w{t} are relevant....

  10. Neoadjuvant endocrine therapy: Patient selection, treatment duration and surrogate endpoints.

    Science.gov (United States)

    Yeo, Belinda; Dowsett, Mitch

    2015-11-01

    Neoadjuvant endocrine treatment has become of increasing interest for downstaging primary ER+ breast cancers as it has become clear that the pathologic complete response rate of luminal tumours to chemotherapy is much lower than that of non-luminal and differs little from that to endocrine therapy. There is much more experience in postmenopausal than premenopausal women. Aromatase inhibitors are generally the agent of choice. Responses are lower in those with the low levels of ER. While duration of endocrine treatment in clinical trials has usually been standardized at around three to four months it is clear that volume reductions continue to occur beyond that time in a large proportion of cases and routine clinical practice is often to treat to maximum response. This relatively slow emergence of downstaging relates to the absence of any increase in apoptosis with endocrine therapy and dependence of responses on the antiproliferative effects of oestrogen withdrawal: apoptosis occurs but at a slightly lower rate such that cell loss is attritional. The dependence of responses on the reduced proliferation underpins the value of Ki67 as an intermediate end-point for treatment benefit with multiple studies having found that relative effects on proliferation by different drugs in neoadjuvant trials match their relative impact on recurrence. While change in Ki67 is now accepted as a validated endpoint for comparing endocrine agents in the neoadjuvant scenario, on-treatment levels of Ki67 are related to long-term prognosis more closely than pretreatment Ki67. The Preoperative Endocrine Prognostic Index (PEPI) that combines residual Ki67 score with measures of on-treatment ER and other clinicopathologic factors has also found application in clinical trials. The potential to make longitudinal assessments of both clinical and biomarker responses has encouraged the development of novel clinical trial designs for assessing the impact of agents that aim to enhance response

  11. Treatment of pathological gambling - integrative systemic model.

    Science.gov (United States)

    Mladenović, Ivica; Lažetić, Goran; Lečić-Toševski, Dušica; Dimitrijević, Ivan

    2015-03-01

    Pathological gambling was classified under impulse control disorders within the International Classification of Diseases (ICD-10) (WHO 1992), but the most recent Diagnostic and Statistical Manual, 5th edition (DSM-V), (APA 2013), has recognized pathological gambling as a first disorder within a new diagnostic category of behavioral addictions - Gambling disorder. Pathological gambling is a disorder in progression, and we hope that our experience in the treatment of pathological gambling in the Daily Hospital for Addictions at The Institute of Mental Health, through the original "Integrative - systemic model" would be of use to colleagues, dealing with this pathology. This model of treatment of pathological gambling is based on multi-systemic approach and it primarily represents an integration of family and cognitive-behavioral therapy, with traces of psychodynamic, existential and pharmacotherapy. The model is based on the book "Pathological gambling - with self-help manual" by Dr Mladenovic and Dr Lazetic, and has been designed in the form of a program that lasts 10 weeks in the intensive phase, and then continues for two years in the form of "extended treatment" ("After care"). The intensive phase is divided into three segments: educational, insight with initial changes and analysis of the achieved changes with the definition of plans and areas that need to be addressed in the extended treatment. "Extended treatment" lasts for two years in the form of group therapy, during which there is a second order change of the identified patient, but also of other family members. Pathological gambling has been treated in the form of systemic-family therapy for more than 10 years at the Institute of Mental Health (IMH), in Belgrade. For second year in a row the treatment is carried out by the modern "Integrative-systemic model". If abstinence from gambling witihin the period of one year after completion of the intensive phase of treatment is taken as the main criterion of

  12. IVF or IUI as first-line treatment in unexplained subfertility: the conundrum of treatment selection markers

    NARCIS (Netherlands)

    Tjon-Kon-Fat, R. I.; Tajik, P.; Zafarmand, M. H.; Bensdorp, A. J.; Bossuyt, P. M. M.; Oosterhuis, G. J. E.; van Golde, R.; Repping, S.; Lambers, M. D. A.; Slappendel, E.; Perquin, D.; Pelinck, M. J.; Gianotten, J.; Maas, J. W. M.; Eijkemans, M. J. C.; van der Veen, F.; Mol, B. W.; van Wely, M.

    2017-01-01

    Are there treatment selection markers that could aid in identifying couples, with unexplained or mild male subfertility, who would have better chances of a healthy child with IVF with single embryo transfer (IVF-SET) than with IUI with ovarian stimulation (IUI-OS)? We did not find any treatment

  13. Treatment of severe chronic hypotonic hyponatremia: a new treatment model

    Directory of Open Access Journals (Sweden)

    Antonio Burgio

    2013-03-01

    Full Text Available Recommended treatment of severe hypotonic hyponatremia is based on the infusion of 3% sodium chloride solution, with a daily correction rate below 10 mEq/L of sodium concentration, according to the Adrogué and Madias formula that includes the current desired change in sodium concentrations. However, such treatment needs close monitoring of the rate of infusion and does not take into account the body weight or age of the patient. This may result in hypercorrection and neurological damage. We made an inverse calculation using the same algorithms of the Adrogué and Madias formula to estimate the number of vials of sodium chloride needed to reach a correction rate of the serum sodium concentration below 0.4 mEq/h, taking into account the body weight and age of the patient. Three tables have been produced, each containing the number of vials to be infused, according to the patient’s age and body weight, the serum sodium concentration, and the rate of correction over 24 h to avoid the risk of brain damage. We propose a new practical model to calculate the need of sodium chloride infusate to safely correct the hyponatremia. The tables make treatment easier to manage in daily clinical practice in a wide range of patient ages and body weights.

  14. Fretting of AISI 9310 and selected fretting resistant surface treatments

    Science.gov (United States)

    Bill, R. C.

    1977-01-01

    Fretting wear experiments were conducted with uncoated AISI 9310 mating surfaces, and with combinations incorporating a selected coating to one of the mating surfaces. Wear measurements and SEM observations indicated that surface fatigue, as made evident by spallation and surface crack formation, is an important mechanism in promoting fretting wear to uncoated 9310. Increasing humidity resulted in accelerated fretting, and a very noticeable difference in nature of the fretting debris. Of the coatings evaluated, alumimum bronze with a polyester additive was most effective at reducing wear and minimizing fretting damage to the mating uncoated surface, by means of a self-lubricating film that developed on the fretting surfaces. Chromium plate performed as an effective protective coating, itself resisting fretting and not accelerating damage to the uncoated surface.

  15. Autism Treatment and Family Support Models Review

    Directory of Open Access Journals (Sweden)

    Mehrnoush Esbati

    2009-04-01

    Full Text Available Autism is a lifelong neurological disability of unknown etiology. The criteria for a diagnosis of autism are based on a triad of impairments in social interaction, communication and a lack of flexibility in thinking and behavior There are several factors which are likely to contribute to this variation including the definition of autism and variability in diagnosis amongst professionals, however anecdotally there appears to have been a steadily increasing demand for services. The purpose of this review of research literature relating to the management and treatment of children with autism is to identify the most effective models of best practice. The review includes Comparative evidence supporting a range of treatment and intervention models, across the range of individuals included within autism spectrum disorders, psychodynamic treatment/management which are based on the assumption that autism is the result of emotional damage to the child, usually because of failure to develop a close attachment to parents, especially the mother, biological treatments, educational and behavioral interventions, communication therapies, cost benefits and supporting families.The research is examined for evidence to support best practice models in supporting families at the time of diagnosis and assessment and an overview of the nature of comprehensive supports that help reduce stresses that may be experienced by families of a child with autism and promote inclusion in community activities.

  16. Selecting an optimal mixed products using grey relationship model

    Directory of Open Access Journals (Sweden)

    Farshad Faezy Razi

    2013-06-01

    Full Text Available This paper presents an integrated supplier selection and inventory management using grey relationship model (GRM as well as multi-objective decision making process. The proposed model of this paper first ranks different suppliers based on GRM technique and then determines the optimum level of inventory by considering different objectives. To show the implementation of the proposed model, we use some benchmark data presented by Talluri and Baker [Talluri, S., & Baker, R. C. (2002. A multi-phase mathematical programming approach for effective supply chain design. European Journal of Operational Research, 141(3, 544-558.]. The preliminary results indicate that the proposed model of this paper is capable of handling different criteria for supplier selection.

  17. Uniform design based SVM model selection for face recognition

    Science.gov (United States)

    Li, Weihong; Liu, Lijuan; Gong, Weiguo

    2010-02-01

    Support vector machine (SVM) has been proved to be a powerful tool for face recognition. The generalization capacity of SVM depends on the model with optimal hyperparameters. The computational cost of SVM model selection results in application difficulty in face recognition. In order to overcome the shortcoming, we utilize the advantage of uniform design--space filling designs and uniformly scattering theory to seek for optimal SVM hyperparameters. Then we propose a face recognition scheme based on SVM with optimal model which obtained by replacing the grid and gradient-based method with uniform design. The experimental results on Yale and PIE face databases show that the proposed method significantly improves the efficiency of SVM model selection.

  18. Sample selection and taste correlation in discrete choice transport modelling

    DEFF Research Database (Denmark)

    Mabit, Stefan Lindhard

    2008-01-01

    of taste correlation in willingness-to-pay estimation are presented. The first contribution addresses how to incorporate taste correlation in the estimation of the value of travel time for public transport. Given a limited dataset the approach taken is to use theory on the value of travel time as guidance...... many issues that deserve attention. This thesis investigates how sample selection can affect estimation of discrete choice models and how taste correlation should be incorporated into applied mixed logit estimation. Sampling in transport modelling is often based on an observed trip. This may cause...... a sample to be choice-based or governed by a self-selection mechanism. In both cases, there is a possibility that sampling affects the estimation of a population model. It was established in the seventies how choice-based sampling affects the estimation of multinomial logit models. The thesis examines...

  19. Spatial Fleming-Viot models with selection and mutation

    CERN Document Server

    Dawson, Donald A

    2014-01-01

    This book constructs a rigorous framework for analysing selected phenomena in evolutionary theory of populations arising due to the combined effects of migration, selection and mutation in a spatial stochastic population model, namely the evolution towards fitter and fitter types through punctuated equilibria. The discussion is based on a number of new methods, in particular multiple scale analysis, nonlinear Markov processes and their entrance laws, atomic measure-valued evolutions and new forms of duality (for state-dependent mutation and multitype selection) which are used to prove ergodic theorems in this context and are applicable for many other questions and renormalization analysis for a variety of phenomena (stasis, punctuated equilibrium, failure of naive branching approximations, biodiversity) which occur due to the combination of rare mutation, mutation, resampling, migration and selection and make it necessary to mathematically bridge the gap (in the limit) between time and space scales.

  20. Evidence accumulation as a model for lexical selection.

    Science.gov (United States)

    Anders, R; Riès, S; van Maanen, L; Alario, F X

    2015-11-01

    We propose and demonstrate evidence accumulation as a plausible theoretical and/or empirical model for the lexical selection process of lexical retrieval. A number of current psycholinguistic theories consider lexical selection as a process related to selecting a lexical target from a number of alternatives, which each have varying activations (or signal supports), that are largely resultant of an initial stimulus recognition. We thoroughly present a case for how such a process may be theoretically explained by the evidence accumulation paradigm, and we demonstrate how this paradigm can be directly related or combined with conventional psycholinguistic theory and their simulatory instantiations (generally, neural network models). Then with a demonstrative application on a large new real data set, we establish how the empirical evidence accumulation approach is able to provide parameter results that are informative to leading psycholinguistic theory, and that motivate future theoretical development. Copyright © 2015 Elsevier Inc. All rights reserved.

  1. Integrated model for supplier selection and performance evaluation

    Directory of Open Access Journals (Sweden)

    Borges de Araújo, Maria Creuza

    2015-08-01

    Full Text Available This paper puts forward a model for selecting suppliers and evaluating the performance of those already working with a company. A simulation was conducted in a food industry. This sector has high significance in the economy of Brazil. The model enables the phases of selecting and evaluating suppliers to be integrated. This is important so that a company can have partnerships with suppliers who are able to meet their needs. Additionally, a group method is used to enable managers who will be affected by this decision to take part in the selection stage. Finally, the classes resulting from the performance evaluation are shown to support the contractor in choosing the most appropriate relationship with its suppliers.

  2. Patient selection and treatment planning for implant restorations.

    Science.gov (United States)

    Bryington, Matthew; De Kok, Ingeborg J; Thalji, Ghadeer; Cooper, Lyndon F

    2014-01-01

    Dental implants are an indispensible tool for the restoration of missing teeth. Their use has elevated the practice of dentistry by improving both our technical ability to rehabilitate patients and general quality of life. To routinely achieve the associated high expectations, diligent attention to details must be observed and addressed from the outset. Of central concern is the attainment of osseointegration and the location of implants to ideally support the intended restoration. The pivotal point in treatment planning for dental implants occurs when the location of bone is viewed radiographically in the context of the planned prosthesis. This most often requires diagnostic waxing or tooth arrangement using mounted diagnostic casts. Copyright © 2014 Elsevier Inc. All rights reserved.

  3. Selective use of sorafenib in the treatment of thyroid cancer

    Directory of Open Access Journals (Sweden)

    Pitoia F

    2016-03-01

    Full Text Available Fabián Pitoia, Fernando Jerkovich Division of Endocrinology, Hospital de Clinicas – University of Buenos Aires, Buenos Aires, Argentina Abstract: Sorafenib is a multiple kinase inhibitor (MKI approved for the treatment of primary advanced renal cell carcinoma and advanced primary liver cancer. It was recently approved by several health agencies around the world as the first available MKI treatment for radioactive iodine-refractory advanced and progressive differentiated thyroid cancer. Sorafenib targets C-RAF, B-RAF, VEGF receptor-1, -2, -3, PDGF receptor-β, RET, c-kit, and Flt-3. As a multifunctional inhibitor, sorafenib has the potential of inhibiting tumor growth, progression, metastasis, and angiogenesis and downregulating mechanisms that protect tumors from apoptosis and has shown to increase the progression-free survival in several Phase II trials. This led to the Phase III trial (DECISION which showed that there was an improvement in progression-free survival of 5 months for patients on sorafenib when compared to those on placebo. Adverse events with this drug are common but usually manageable. The development of resistance after 1 or 2 years is almost a rule in most patients who showed partial response or stabilization of the disease while on sorafenib, which makes it necessary to think of a plan for subsequent therapies. These may include the use of another MKI, such as lenvatinib, the second approved MKI for advanced differentiated thyroid cancer, or include patients in clinical trials or the off-label use of other MKIs. Given sorafenib’s earlier approval, most centers now have access to its prescription. The goal of this review was to improve the care of these patients by describing key aspects that all prescribers will need to master in order to optimize outcomes. Keywords: multiple kinase inhibitor, differentiated thyroid cancer, progression-free survival, radioiodine

  4. The Selection of ARIMA Models with or without Regressors

    DEFF Research Database (Denmark)

    Johansen, Søren; Riani, Marco; Atkinson, Anthony C.

    We develop a $C_{p}$ statistic for the selection of regression models with stationary and nonstationary ARIMA error term. We derive the asymptotic theory of the maximum likelihood estimators and show they are consistent and asymptotically Gaussian. We also prove that the distribution of the sum o...

  5. Selecting candidate predictor variables for the modelling of post ...

    African Journals Online (AJOL)

    Selecting candidate predictor variables for the modelling of post-discharge mortality from sepsis: a protocol development project. Afri. Health Sci. .... Initial list of candidate predictor variables, N=17. Clinical. Laboratory. Social/Demographic. Vital signs (HR, RR, BP, T). Hemoglobin. Age. Oxygen saturation. Blood culture. Sex.

  6. Computationally efficient thermal-mechanical modelling of selective laser melting

    NARCIS (Netherlands)

    Yang, Y.; Ayas, C.; Brabazon, Dermot; Naher, Sumsun; Ul Ahad, Inam

    2017-01-01

    The Selective laser melting (SLM) is a powder based additive manufacturing (AM) method to produce high density metal parts with complex topology. However, part distortions and accompanying residual stresses deteriorates the mechanical reliability of SLM products. Modelling of the SLM process is

  7. Multivariate time series modeling of selected childhood diseases in ...

    African Journals Online (AJOL)

    This paper is focused on modeling the five most prevalent childhood diseases in Akwa Ibom State using a multivariate approach to time series. An aggregate of 78,839 reported cases of malaria, upper respiratory tract infection (URTI), Pneumonia, anaemia and tetanus were extracted from five randomly selected hospitals in ...

  8. Phototransformation of selected pharmaceuticals during UV treatment of drinking water.

    Science.gov (United States)

    Canonica, Silvio; Meunier, Laurence; von Gunten, Urs

    2008-01-01

    The kinetics of Ultraviolet C (UV-C)-induced direct phototransformation of four representative pharmaceuticals, i.e., 17alpha-ethinylestradiol (EE2), diclofenac, sulfamethoxazole, and iopromide, was investigated in dilute solutions of pure water buffered at various pH values using a low-pressure and a medium-pressure mercury arc lamp. Except for iopromide, pH-dependent rate constants were observed, which could be related to acid-base equilibria. Quantum yields for direct phototransformation were found to be largely wavelength-independent, except for EE2. This compound, which also had a rather inefficient direct phototransformation, mainly underwent indirect phototransformation in natural water samples, while the UV-induced depletion of the other pharmaceuticals appeared to be unaffected by the presence of natural water components. At the UV-C (254 nm) drinking-water disinfection fluence (dose) of 400 Jm(-2), the degree of depletion of the select pharmaceuticals at pH=7.0 in pure water was 0.4% for EE2, 27% for diclofenac, 15% for sulfamethoxazole, and 15% for iopromide, indicating that phototransformation should be seriously taken into account when evaluating the possibility of formation of UV transformation products from pharmaceuticals present as micropollutants.

  9. Model selection for the extraction of movement primitives

    Directory of Open Access Journals (Sweden)

    Dominik M Endres

    2013-12-01

    Full Text Available A wide range of blind source separation methods have been used in motor control research for the extraction of movement primitives from EMG and kinematic data. Popular examples are principal component analysis (PCA,independent component analysis (ICA, anechoic demixing, and the time-varying synergy model. However, choosing the parameters of these models, or indeed choosing the type of model, is often done in a heuristic fashion, driven by result expectations as much as by the data. We propose an objective criterion which allows to select the model type, number of primitives and the temporal smoothness prior. Our approach is based on a Laplace approximation to the posterior distribution of the parameters of a given blind source separation model, re-formulated as a Bayesian generative model.We first validate our criterion on ground truth data, showing that it performs at least as good as traditional model selection criteria (Bayesian information criterion, BIC and the Akaike Information Criterion (AIC. Then, we analyze human gait data, finding that an anechoic mixture model with a temporal smoothness constraint on the sources can best account for the data.

  10. Treatment selection for squamous cell carcinoma of oropharynx

    Energy Technology Data Exchange (ETDEWEB)

    Inakami, Ken-ichi; Sato, Takeo; Yoshino, Kunitoshi; Fujii, Takashi; Nagahara, Masamitu; Momohara, Chikahiro [Osaka Prefectural Center for Adult Diseases (Japan)

    1999-03-01

    Between 1979 and 1995, 153 patients were treated for squamous cell carcinoma of the oropharynx (except the posterior wall region). All patients had a minimum 2-year follow-up and no patient was lost to follow-up. The distribution according to primary site was as follows: base of tongue region, 41 lesions; tonsillar fossa region, 71 lesions; and anterior tonsillar pillar and soft palate region, 41 lesions. The T1 and T2 tumors treated with surgery or radiotherapy had control rates of 29/33 (88%) and 48/66 (73%), respectively. The base of the tongue and tonsillar fossa region had good local control rates in both surgery and radiotherapy. In the anterior tonsillar pillar and soft palate region, however, the initial control by radiotherapy and surgery was T1 and T2 of 8/ 21 (38%) and T1 and T2 of 8/9 (89%) respectively. The ultimate local control rate after surgical salvage was 25 (83%) of 30 patients. Surgical salvage was often successful for early lesions. Surgery is an effective form of treatment for carcinoma of the soft palate and tonsillar pillar. (author)

  11. On selection of optimal stochastic model for accelerated life testing

    International Nuclear Information System (INIS)

    Volf, P.; Timková, J.

    2014-01-01

    This paper deals with the problem of proper lifetime model selection in the context of statistical reliability analysis. Namely, we consider regression models describing the dependence of failure intensities on a covariate, for instance, a stressor. Testing the model fit is standardly based on the so-called martingale residuals. Their analysis has already been studied by many authors. Nevertheless, the Bayes approach to the problem, in spite of its advantages, is just developing. We shall present the Bayes procedure of estimation in several semi-parametric regression models of failure intensity. Then, our main concern is the Bayes construction of residual processes and goodness-of-fit tests based on them. The method is illustrated with both artificial and real-data examples. - Highlights: • Statistical survival and reliability analysis and Bayes approach. • Bayes semi-parametric regression modeling in Cox's and AFT models. • Bayes version of martingale residuals and goodness-of-fit test

  12. Model building strategy for logistic regression: purposeful selection.

    Science.gov (United States)

    Zhang, Zhongheng

    2016-03-01

    Logistic regression is one of the most commonly used models to account for confounders in medical literature. The article introduces how to perform purposeful selection model building strategy with R. I stress on the use of likelihood ratio test to see whether deleting a variable will have significant impact on model fit. A deleted variable should also be checked for whether it is an important adjustment of remaining covariates. Interaction should be checked to disentangle complex relationship between covariates and their synergistic effect on response variable. Model should be checked for the goodness-of-fit (GOF). In other words, how the fitted model reflects the real data. Hosmer-Lemeshow GOF test is the most widely used for logistic regression model.

  13. Statistical modelling in biostatistics and bioinformatics selected papers

    CERN Document Server

    Peng, Defen

    2014-01-01

    This book presents selected papers on statistical model development related mainly to the fields of Biostatistics and Bioinformatics. The coverage of the material falls squarely into the following categories: (a) Survival analysis and multivariate survival analysis, (b) Time series and longitudinal data analysis, (c) Statistical model development and (d) Applied statistical modelling. Innovations in statistical modelling are presented throughout each of the four areas, with some intriguing new ideas on hierarchical generalized non-linear models and on frailty models with structural dispersion, just to mention two examples. The contributors include distinguished international statisticians such as Philip Hougaard, John Hinde, Il Do Ha, Roger Payne and Alessandra Durio, among others, as well as promising newcomers. Some of the contributions have come from researchers working in the BIO-SI research programme on Biostatistics and Bioinformatics, centred on the Universities of Limerick and Galway in Ireland and fu...

  14. Bayesian Variable Selection on Model Spaces Constrained by Heredity Conditions.

    Science.gov (United States)

    Taylor-Rodriguez, Daniel; Womack, Andrew; Bliznyuk, Nikolay

    2016-01-01

    This paper investigates Bayesian variable selection when there is a hierarchical dependence structure on the inclusion of predictors in the model. In particular, we study the type of dependence found in polynomial response surfaces of orders two and higher, whose model spaces are required to satisfy weak or strong heredity conditions. These conditions restrict the inclusion of higher-order terms depending upon the inclusion of lower-order parent terms. We develop classes of priors on the model space, investigate their theoretical and finite sample properties, and provide a Metropolis-Hastings algorithm for searching the space of models. The tools proposed allow fast and thorough exploration of model spaces that account for hierarchical polynomial structure in the predictors and provide control of the inclusion of false positives in high posterior probability models.

  15. A model for the sustainable selection of building envelope assemblies

    International Nuclear Information System (INIS)

    Huedo, Patricia; Mulet, Elena; López-Mesa, Belinda

    2016-01-01

    The aim of this article is to define an evaluation model for the environmental impacts of building envelopes to support planners in the early phases of materials selection. The model is intended to estimate environmental impacts for different combinations of building envelope assemblies based on scientifically recognised sustainability indicators. These indicators will increase the amount of information that existing catalogues show to support planners in the selection of building assemblies. To define the model, first the environmental indicators were selected based on the specific aims of the intended sustainability assessment. Then, a simplified LCA methodology was developed to estimate the impacts applicable to three types of dwellings considering different envelope assemblies, building orientations and climate zones. This methodology takes into account the manufacturing, installation, maintenance and use phases of the building. Finally, the model was validated and a matrix in Excel was created as implementation of the model. - Highlights: • Method to assess the envelope impacts based on a simplified LCA • To be used at an earlier phase than the existing methods in a simple way. • It assigns a score by means of known sustainability indicators. • It estimates data about the embodied and operating environmental impacts. • It compares the investment costs with the costs of the consumed energy.

  16. PROPOSAL OF AN EMPIRICAL MODEL FOR SUPPLIERS SELECTION

    Directory of Open Access Journals (Sweden)

    Paulo Ávila

    2015-03-01

    Full Text Available The problem of selecting suppliers/partners is a crucial and important part in the process of decision making for companies that intend to perform competitively in their area of activity. The selection of supplier/partner is a time and resource-consuming task that involves data collection and a careful analysis of the factors that can positively or negatively influence the choice. Nevertheless it is a critical process that affects significantly the operational performance of each company. In this work, trough the literature review, there were identified five broad suppliers selection criteria: Quality, Financial, Synergies, Cost, and Production System. Within these criteria, it was also included five sub-criteria. Thereafter, a survey was elaborated and companies were contacted in order to answer which factors have more relevance in their decisions to choose the suppliers. Interpreted the results and processed the data, it was adopted a model of linear weighting to reflect the importance of each factor. The model has a hierarchical structure and can be applied with the Analytic Hierarchy Process (AHP method or Simple Multi-Attribute Rating Technique (SMART. The result of the research undertaken by the authors is a reference model that represents a decision making support for the suppliers/partners selection process.

  17. Modelling of Activated Sludge Wastewater Treatment

    Directory of Open Access Journals (Sweden)

    Kurtanjeka, Ž.

    2008-02-01

    Full Text Available Activated sludge wastewater treatment is a highly complex physical, chemical and biological process, and variations in wastewater flow rate and its composition, combined with time-varying reactions in a mixed culture of microorganisms, make this process non-linear and unsteady. The efficiency of the process is established by measuring the quantities that indicate quality of the treated wastewater, but they can only be determined at the end of the process, which is when the water has already been processed and is at the outlet of the plant and released into the environment.If the water quality is not acceptable, it is already too late for its improvement, which indicates the need for a feed forward process control based on a mathematical model. Since there is no possibility of retracing the process steps back, all the mistakes in the control of the process could induce an ecological disaster of a smaller or bigger extent. Therefore, models that describe this process well may be used as a basis for monitoring and optimal control of the process development. This work analyzes the process of biological treatment of wastewater in the Velika Gorica plant. Two empirical models for the description of the process were established, multiple linear regression model (MLR with 16 predictor variables and piecewise linear regression model (PLR with 17 predictor variables. These models were developed with the aim to predict COD value of the effluent wastewater at the outlet, after treatment. The development of the models is based on the statistical analysis of experimental data, which are used to determine the relations among individual variables. In this work are applied linear models based on multiple linear regression (MLR and partial least squares (PLR methods. The used data were obtained by everyday measurements of the quantities that indicate the quality of the input and output water, working conditions of the plant and the quality of the activated sludge

  18. [ProfessorWANG Fuchun's experience in the acupoint selection of clinical treatment with acupuncture and moxibustion].

    Science.gov (United States)

    Jiang, Hailin; Liu, Chengyu; Ha, Lijuan; Li, Tie

    2017-11-12

    Professor WANG Fuchun 's experience in the acupoint selection of clinical treatment with acupuncture and moxibustion was summarized. The main acupoints are selected by focusing on the chief symptoms of disease, the supplementary points are selected by differentiating the disorders. The acupoints are modified in terms of the changes of sickness. The effective acupoints are selected flexibly in accordance with the specific effects of points. The summary on the acupoint selection reflects professor WANG Fuchun 's academic thoughts and clinical experience and effectively instructs the clinical practice of acupuncture and moxibustion.

  19. Sequential Salinomycin Treatment Results in Resistance Formation through Clonal Selection of Epithelial-Like Tumor Cells

    Directory of Open Access Journals (Sweden)

    Florian Kopp

    2014-12-01

    Full Text Available Acquiring therapy resistance is one of the major obstacles in the treatment of patients with cancer. The discovery of the cancer stem cell (CSC–specific drug salinomycin raised hope for improved treatment options by targeting therapy-refractory CSCs and mesenchymal cancer cells. However, the occurrence of an acquired salinomycin resistance in tumor cells remains elusive. To study the formation of salinomycin resistance, mesenchymal breast cancer cells were sequentially treated with salinomycin in an in vitro cell culture assay, and the resulting differences in gene expression and salinomycin susceptibility were analyzed. We demonstrated that long-term salinomycin treatment of mesenchymal cancer cells resulted in salinomycin-resistant cells with elevated levels of epithelial markers, such as E-cadherin and miR-200c, a decreased migratory capability, and a higher susceptibility to the classic chemotherapeutic drug doxorubicin. The formation of salinomycin resistance through the acquisition of epithelial traits was further validated by inducing mesenchymal-epithelial transition through an overexpression of miR-200c. The transition from a mesenchymal to a more epithelial-like phenotype of salinomycin-treated tumor cells was moreover confirmed in vivo, using syngeneic and, for the first time, transgenic mouse tumor models. These results suggest that the acquisition of salinomycin resistance through the clonal selection of epithelial-like cancer cells could become exploited for improved cancer therapies by antagonizing the tumor-progressive effects of epithelial-mesenchymal transition.

  20. ASYMMETRIC PRICE TRANSMISSION MODELING: THE IMPORTANCE OF MODEL COMPLEXITY AND THE PERFORMANCE OF THE SELECTION CRITERIA

    Directory of Open Access Journals (Sweden)

    Henry de-Graft Acquah

    2013-01-01

    Full Text Available Information Criteria provides an attractive basis for selecting the best model from a set of competing asymmetric price transmission models or theories. However, little is understood about the sensitivity of the model selection methods to model complexity. This study therefore fits competing asymmetric price transmission models that differ in complexity to simulated data and evaluates the ability of the model selection methods to recover the true model. The results of Monte Carlo experimentation suggest that in general BIC, CAIC and DIC were superior to AIC when the true data generating process was the standard error correction model, whereas AIC was more successful when the true model was the complex error correction model. It is also shown that the model selection methods performed better in large samples for a complex asymmetric data generating process than with a standard asymmetric data generating process. Except for complex models, AIC's performance did not make substantial gains in recovery rates as sample size increased. The research findings demonstrate the influence of model complexity in asymmetric price transmission model comparison and selection.

  1. Broken selection rule in the quantum Rabi model.

    Science.gov (United States)

    Forn-Díaz, P; Romero, G; Harmans, C J P M; Solano, E; Mooij, J E

    2016-06-07

    Understanding the interaction between light and matter is very relevant for fundamental studies of quantum electrodynamics and for the development of quantum technologies. The quantum Rabi model captures the physics of a single atom interacting with a single photon at all regimes of coupling strength. We report the spectroscopic observation of a resonant transition that breaks a selection rule in the quantum Rabi model, implemented using an LC resonator and an artificial atom, a superconducting qubit. The eigenstates of the system consist of a superposition of bare qubit-resonator states with a relative sign. When the qubit-resonator coupling strength is negligible compared to their own frequencies, the matrix element between excited eigenstates of different sign is very small in presence of a resonator drive, establishing a sign-preserving selection rule. Here, our qubit-resonator system operates in the ultrastrong coupling regime, where the coupling strength is 10% of the resonator frequency, allowing sign-changing transitions to be activated and, therefore, detected. This work shows that sign-changing transitions are an unambiguous, distinctive signature of systems operating in the ultrastrong coupling regime of the quantum Rabi model. These results pave the way to further studies of sign-preserving selection rules in multiqubit and multiphoton models.

  2. Models of cultural niche construction with selection and assortative mating.

    Science.gov (United States)

    Creanza, Nicole; Fogarty, Laurel; Feldman, Marcus W

    2012-01-01

    Niche construction is a process through which organisms modify their environment and, as a result, alter the selection pressures on themselves and other species. In cultural niche construction, one or more cultural traits can influence the evolution of other cultural or biological traits by affecting the social environment in which the latter traits may evolve. Cultural niche construction may include either gene-culture or culture-culture interactions. Here we develop a model of this process and suggest some applications of this model. We examine the interactions between cultural transmission, selection, and assorting, paying particular attention to the complexities that arise when selection and assorting are both present, in which case stable polymorphisms of all cultural phenotypes are possible. We compare our model to a recent model for the joint evolution of religion and fertility and discuss other potential applications of cultural niche construction theory, including the evolution and maintenance of large-scale human conflict and the relationship between sex ratio bias and marriage customs. The evolutionary framework we introduce begins to address complexities that arise in the quantitative analysis of multiple interacting cultural traits.

  3. Models of cultural niche construction with selection and assortative mating.

    Directory of Open Access Journals (Sweden)

    Nicole Creanza

    Full Text Available Niche construction is a process through which organisms modify their environment and, as a result, alter the selection pressures on themselves and other species. In cultural niche construction, one or more cultural traits can influence the evolution of other cultural or biological traits by affecting the social environment in which the latter traits may evolve. Cultural niche construction may include either gene-culture or culture-culture interactions. Here we develop a model of this process and suggest some applications of this model. We examine the interactions between cultural transmission, selection, and assorting, paying particular attention to the complexities that arise when selection and assorting are both present, in which case stable polymorphisms of all cultural phenotypes are possible. We compare our model to a recent model for the joint evolution of religion and fertility and discuss other potential applications of cultural niche construction theory, including the evolution and maintenance of large-scale human conflict and the relationship between sex ratio bias and marriage customs. The evolutionary framework we introduce begins to address complexities that arise in the quantitative analysis of multiple interacting cultural traits.

  4. Selection of Models for Ingestion Pathway and Relocation Radii Determination

    International Nuclear Information System (INIS)

    Blanchard, A.

    1998-01-01

    The distance at which intermediate phase protective actions (such as food interdiction and relocation) may be needed following postulated accidents at three Savannah River Site nonreactor nuclear facilities will be determined by modeling. The criteria used to select dispersion/deposition models are presented. Several models were considered, including ARAC, MACCS, HOTSPOT, WINDS (coupled with PUFF-PLUME), and UFOTRI. Although ARAC and WINDS are expected to provide more accurate modeling of atmospheric transport following an actual release, analyses consistent with regulatory guidance for planning purposes may be accomplished with comparatively simple dispersion models such as HOTSPOT and UFOTRI. A recommendation is made to use HOTSPOT for non-tritium facilities and UFOTRI for tritium facilities

  5. Numerical Model based Reliability Estimation of Selective Laser Melting Process

    DEFF Research Database (Denmark)

    Mohanty, Sankhya; Hattel, Jesper Henri

    2014-01-01

    Selective laser melting is developing into a standard manufacturing technology with applications in various sectors. However, the process is still far from being at par with conventional processes such as welding and casting, the primary reason of which is the unreliability of the process. While...... of the selective laser melting process. A validated 3D finite-volume alternating-direction-implicit numerical technique is used to model the selective laser melting process, and is calibrated against results from single track formation experiments. Correlation coefficients are determined for process input...... parameters such as laser power, speed, beam profile, etc. Subsequently, uncertainties in the processing parameters are utilized to predict a range for the various outputs, using a Monte Carlo method based uncertainty analysis methodology, and the reliability of the process is established....

  6. Modelling Technical and Economic Parameters in Selection of Manufacturing Devices

    Directory of Open Access Journals (Sweden)

    Naqib Daneshjo

    2017-11-01

    Full Text Available Sustainable science and technology development is also conditioned by continuous development of means of production which have a key role in structure of each production system. Mechanical nature of the means of production is complemented by controlling and electronic devices in context of intelligent industry. A selection of production machines for a technological process or technological project has so far been practically resolved, often only intuitively. With regard to increasing intelligence, the number of variable parameters that have to be considered when choosing a production device is also increasing. It is necessary to use computing techniques and decision making methods according to heuristic methods and more precise methodological procedures during the selection. The authors present an innovative model for optimization of technical and economic parameters in the selection of manufacturing devices for industry 4.0.

  7. [AIT (Adolescent Identity Treatment) - an Integrative Treatment Model for the Treatment of Personality Disorders].

    Science.gov (United States)

    Schlüter-Müller, Susanne

    2017-07-01

    AIT (Adolescent Identity Treatment) - an Integrative Treatment Model for the Treatment of Personality Disorders Personality disorders are patterns of maladaptive personality traits that have an impact on the individual throughout the life span. Borderline Personality Disorder (BPD) is a very severe, but treatable mental disorder. Identity disturbance is seen as the central construct for detecting severe personality pathology - and, most notably, borderline personality disorder - in adults and adolescents. Crises in the development of identity usually resolve into a normal and consolidated identity with flexible and adaptive functioning whereas identity diffusion is viewed as a lack of integration of the concept of the self and significant others. It is seen as the basis for subsequent personality pathology, including that of borderline personality disorder. Although BPD has its onset in adolescence and emerging adulthood the diagnosis is often delayed. In most cases, specific treatment is only offered late in the course of the disorder and to relatively few individuals. Adolescent Identity Treatment (AIT) is a treatment model that focuses on identity pathology as the core characteristic of personality disorders. This model integrates specific techniques for the treatment of adolescent personality pathology on the background of object-relation theories and modified elements of Transference-Focused Psychotherapy. Moreover, psychoeducation, a behavior-oriented homeplan and intensive family work is part of AIT.

  8. The selection pressures induced non-smooth infectious disease model and bifurcation analysis

    International Nuclear Information System (INIS)

    Qin, Wenjie; Tang, Sanyi

    2014-01-01

    Highlights: • A non-smooth infectious disease model to describe selection pressure is developed. • The effect of selection pressure on infectious disease transmission is addressed. • The key factors which are related to the threshold value are determined. • The stabilities and bifurcations of model have been revealed in more detail. • Strategies for the prevention of emerging infectious disease are proposed. - Abstract: Mathematical models can assist in the design strategies to control emerging infectious disease. This paper deduces a non-smooth infectious disease model induced by selection pressures. Analysis of this model reveals rich dynamics including local, global stability of equilibria and local sliding bifurcations. Model solutions ultimately stabilize at either one real equilibrium or the pseudo-equilibrium on the switching surface of the present model, depending on the threshold value determined by some related parameters. Our main results show that reducing the threshold value to a appropriate level could contribute to the efficacy on prevention and treatment of emerging infectious disease, which indicates that the selection pressures can be beneficial to prevent the emerging infectious disease under medical resource limitation

  9. Forecasting house prices in the 50 states using Dynamic Model Averaging and Dynamic Model Selection

    DEFF Research Database (Denmark)

    Bork, Lasse; Møller, Stig Vinther

    2015-01-01

    We examine house price forecastability across the 50 states using Dynamic Model Averaging and Dynamic Model Selection, which allow for model change and parameter shifts. By allowing the entire forecasting model to change over time and across locations, the forecasting accuracy improves substantia...

  10. Quantitative modeling of selective lysosomal targeting for drug design

    DEFF Research Database (Denmark)

    Trapp, Stefan; Rosania, G.; Horobin, R.W.

    2008-01-01

    Lysosomes are acidic organelles and are involved in various diseases, the most prominent is malaria. Accumulation of molecules in the cell by diffusion from the external solution into cytosol, lysosome and mitochondrium was calculated with the Fick–Nernst–Planck equation. The cell model considers...... the diffusion of neutral and ionic molecules across biomembranes, protonation to mono- or bivalent ions, adsorption to lipids, and electrical attraction or repulsion. Based on simulation results, high and selective accumulation in lysosomes was found for weak mono- and bivalent bases with intermediate to high...... predicted by the model and three were close. Five of the antimalarial drugs were lipophilic weak dibasic compounds. The predicted optimum properties for a selective accumulation of weak bivalent bases in lysosomes are consistent with experimental values and are more accurate than any prior calculation...

  11. Genomic Selection in Plant Breeding: Methods, Models, and Perspectives.

    Science.gov (United States)

    Crossa, José; Pérez-Rodríguez, Paulino; Cuevas, Jaime; Montesinos-López, Osval; Jarquín, Diego; de Los Campos, Gustavo; Burgueño, Juan; González-Camacho, Juan M; Pérez-Elizalde, Sergio; Beyene, Yoseph; Dreisigacker, Susanne; Singh, Ravi; Zhang, Xuecai; Gowda, Manje; Roorkiwal, Manish; Rutkoski, Jessica; Varshney, Rajeev K

    2017-11-01

    Genomic selection (GS) facilitates the rapid selection of superior genotypes and accelerates the breeding cycle. In this review, we discuss the history, principles, and basis of GS and genomic-enabled prediction (GP) as well as the genetics and statistical complexities of GP models, including genomic genotype×environment (G×E) interactions. We also examine the accuracy of GP models and methods for two cereal crops and two legume crops based on random cross-validation. GS applied to maize breeding has shown tangible genetic gains. Based on GP results, we speculate how GS in germplasm enhancement (i.e., prebreeding) programs could accelerate the flow of genes from gene bank accessions to elite lines. Recent advances in hyperspectral image technology could be combined with GS and pedigree-assisted breeding. Copyright © 2017 Elsevier Ltd. All rights reserved.

  12. Generalized Degrees of Freedom and Adaptive Model Selection in Linear Mixed-Effects Models.

    Science.gov (United States)

    Zhang, Bo; Shen, Xiaotong; Mumford, Sunni L

    2012-03-01

    Linear mixed-effects models involve fixed effects, random effects and covariance structure, which require model selection to simplify a model and to enhance its interpretability and predictability. In this article, we develop, in the context of linear mixed-effects models, the generalized degrees of freedom and an adaptive model selection procedure defined by a data-driven model complexity penalty. Numerically, the procedure performs well against its competitors not only in selecting fixed effects but in selecting random effects and covariance structure as well. Theoretically, asymptotic optimality of the proposed methodology is established over a class of information criteria. The proposed methodology is applied to the BioCycle study, to determine predictors of hormone levels among premenopausal women and to assess variation in hormone levels both between and within women across the menstrual cycle.

  13. Parameter estimation and model selection in computational biology.

    Directory of Open Access Journals (Sweden)

    Gabriele Lillacci

    2010-03-01

    Full Text Available A central challenge in computational modeling of biological systems is the determination of the model parameters. Typically, only a fraction of the parameters (such as kinetic rate constants are experimentally measured, while the rest are often fitted. The fitting process is usually based on experimental time course measurements of observables, which are used to assign parameter values that minimize some measure of the error between these measurements and the corresponding model prediction. The measurements, which can come from immunoblotting assays, fluorescent markers, etc., tend to be very noisy and taken at a limited number of time points. In this work we present a new approach to the problem of parameter selection of biological models. We show how one can use a dynamic recursive estimator, known as extended Kalman filter, to arrive at estimates of the model parameters. The proposed method follows. First, we use a variation of the Kalman filter that is particularly well suited to biological applications to obtain a first guess for the unknown parameters. Secondly, we employ an a posteriori identifiability test to check the reliability of the estimates. Finally, we solve an optimization problem to refine the first guess in case it should not be accurate enough. The final estimates are guaranteed to be statistically consistent with the measurements. Furthermore, we show how the same tools can be used to discriminate among alternate models of the same biological process. We demonstrate these ideas by applying our methods to two examples, namely a model of the heat shock response in E. coli, and a model of a synthetic gene regulation system. The methods presented are quite general and may be applied to a wide class of biological systems where noisy measurements are used for parameter estimation or model selection.

  14. Pareto-Optimal Model Selection via SPRINT-Race.

    Science.gov (United States)

    Zhang, Tiantian; Georgiopoulos, Michael; Anagnostopoulos, Georgios C

    2018-02-01

    In machine learning, the notion of multi-objective model selection (MOMS) refers to the problem of identifying the set of Pareto-optimal models that optimize by compromising more than one predefined objectives simultaneously. This paper introduces SPRINT-Race, the first multi-objective racing algorithm in a fixed-confidence setting, which is based on the sequential probability ratio with indifference zone test. SPRINT-Race addresses the problem of MOMS with multiple stochastic optimization objectives in the proper Pareto-optimality sense. In SPRINT-Race, a pairwise dominance or non-dominance relationship is statistically inferred via a non-parametric, ternary-decision, dual-sequential probability ratio test. The overall probability of falsely eliminating any Pareto-optimal models or mistakenly returning any clearly dominated models is strictly controlled by a sequential Holm's step-down family-wise error rate control method. As a fixed-confidence model selection algorithm, the objective of SPRINT-Race is to minimize the computational effort required to achieve a prescribed confidence level about the quality of the returned models. The performance of SPRINT-Race is first examined via an artificially constructed MOMS problem with known ground truth. Subsequently, SPRINT-Race is applied on two real-world applications: 1) hybrid recommender system design and 2) multi-criteria stock selection. The experimental results verify that SPRINT-Race is an effective and efficient tool for such MOMS problems. code of SPRINT-Race is available at https://github.com/watera427/SPRINT-Race.

  15. Models of speciation by sexual selection on polygenic traits

    OpenAIRE

    Lande, Russell

    1981-01-01

    The joint evolution of female mating preferences and secondary sexual characters of males is modeled for polygamous species in which males provide only genetic material to the next generation and females have many potential mates to choose among. Despite stabilizing natural selection on males, various types of mating preferences may create a runaway process in which the outcome of phenotypic evolution depends critically on the genetic variation parameters and initial conditions of a populatio...

  16. A Model of Social Selection and Successful Altruism

    Science.gov (United States)

    1989-10-07

    D., The evolution of social behavior. Annual Reviews of Ecological Systems, 5:325-383 (1974). 2. Dawkins , R., The selfish gene . Oxford: Oxford...alive and well. it will be important to re- examine this striking historical experience,-not in terms o, oversimplified models of the " selfish gene ," but...Darwinian Analysis The acceptance by many modern geneticists of the axiom that the basic unit of selection Is the " selfish gene " quickly led to the

  17. A Bayesian Technique for Selecting a Linear Forecasting Model

    OpenAIRE

    Ramona L. Trader

    1983-01-01

    The specification of a forecasting model is considered in the context of linear multiple regression. Several potential predictor variables are available, but some of them convey little information about the dependent variable which is to be predicted. A technique for selecting the "best" set of predictors which takes into account the inherent uncertainty in prediction is detailed. In addition to current data, there is often substantial expert opinion available which is relevant to the forecas...

  18. Selection of representative emerging micropollutants for drinking water treatment studies: a systematic approach.

    Science.gov (United States)

    Jin, Xiaohui; Peldszus, Sigrid

    2012-01-01

    Micropollutants remain of concern in drinking water, and there is a broad interest in the ability of different treatment processes to remove these compounds. To gain a better understanding of treatment effectiveness for structurally diverse compounds and to be cost effective, it is necessary to select a small set of representative micropollutants for experimental studies. Unlike other approaches to-date, in this research micropollutants were systematically selected based solely on their physico-chemical and structural properties that are important in individual water treatment processes. This was accomplished by linking underlying principles of treatment processes such as coagulation/flocculation, oxidation, activated carbon adsorption, and membrane filtration to compound characteristics and corresponding molecular descriptors. A systematic statistical approach not commonly used in water treatment was then applied to a compound pool of 182 micropollutants (identified from the literature) and their relevant calculated molecular descriptors. Principal component analysis (PCA) was used to summarize the information residing in this large dataset. D-optimal onion design was then applied to the PCA results to select structurally representative compounds that could be used in experimental treatment studies. To demonstrate the applicability and flexibility of this selection approach, two sets of 22 representative micropollutants are presented. Compounds in the first set are representative when studying a range of water treatment processes (coagulation/flocculation, oxidation, activated carbon adsorption, and membrane filtration), whereas the second set shows representative compounds for ozonation and advanced oxidation studies. Overall, selected micropollutants in both lists are structurally diverse, have wide-ranging physico-chemical properties and cover a large spectrum of applications. The systematic compound selection approach presented here can also be adjusted to fit

  19. A decision model for energy resource selection in China

    International Nuclear Information System (INIS)

    Wang Bing; Kocaoglu, Dundar F.; Daim, Tugrul U.; Yang Jiting

    2010-01-01

    This paper evaluates coal, petroleum, natural gas, nuclear energy and renewable energy resources as energy alternatives for China through use of a hierarchical decision model. The results indicate that although coal is still the major preferred energy alternative, it is followed closely by renewable energy. The sensitivity analysis indicates that the most critical criterion for energy selection is the current energy infrastructure. A hierarchical decision model is used, and expert judgments are quantified, to evaluate the alternatives. Criteria used for the evaluations are availability, current energy infrastructure, price, safety, environmental impacts and social impacts.

  20. Selection of key terrain attributes for SOC model

    DEFF Research Database (Denmark)

    Greve, Mogens Humlekrog; Adhikari, Kabindra; Chellasamy, Menaka

    As an important component of the global carbon pool, soil organic carbon (SOC) plays an important role in the global carbon cycle. SOC pool is the basic information to carry out global warming research, and needs to sustainable use of land resources. Digital terrain attributes are often use...... was selected, total 2,514,820 data mining models were constructed by 71 differences grid from 12m to 2304m and 22 attributes, 21 attributes derived by DTM and the original elevation. Relative importance and usage of each attributes in every model were calculated. Comprehensive impact rates of each attribute...

  1. The Current State of Empirical Support for the Pharmacological Treatment of Selective Mutism

    Science.gov (United States)

    Carlson, John S.; Mitchell, Angela D.; Segool, Natasha

    2008-01-01

    This article reviews the current state of evidence for the psychopharmacological treatment of children diagnosed with selective mutism within the context of its link to social anxiety disorder. An increased focus on potential medication treatment for this disorder has resulted from significant monetary and resource limitations in typical practice,…

  2. Treatment of Selective Mutism: Applications in the Clinic and School through Conjoint Consultation

    Science.gov (United States)

    Mitchell, Angela D.; Kratochwill, Thomas R.

    2013-01-01

    The purpose of this study was to evaluate the effectiveness of a psychosocial approach to the treatment of Selective Mutism (SM). Four children with SM along with their parents and teachers participated in the study. A comprehensive assessment was completed; manualized treatment was implemented through a conjoint behavioral consultation approach,…

  3. Selecting, weeding, and weighting biased climate model ensembles

    Science.gov (United States)

    Jackson, C. S.; Picton, J.; Huerta, G.; Nosedal Sanchez, A.

    2012-12-01

    In the Bayesian formulation, the "log-likelihood" is a test statistic for selecting, weeding, or weighting climate model ensembles with observational data. This statistic has the potential to synthesize the physical and data constraints on quantities of interest. One of the thorny issues for formulating the log-likelihood is how one should account for biases. While in the past we have included a generic discrepancy term, not all biases affect predictions of quantities of interest. We make use of a 165-member ensemble CAM3.1/slab ocean climate models with different parameter settings to think through the issues that are involved with predicting each model's sensitivity to greenhouse gas forcing given what can be observed from the base state. In particular we use multivariate empirical orthogonal functions to decompose the differences that exist among this ensemble to discover what fields and regions matter to the model's sensitivity. We find that the differences that matter are a small fraction of the total discrepancy. Moreover, weighting members of the ensemble using this knowledge does a relatively poor job of adjusting the ensemble mean toward the known answer. This points out the shortcomings of using weights to correct for biases in climate model ensembles created by a selection process that does not emphasize the priorities of your log-likelihood.

  4. Optimal foraging in marine ecosystem models: selectivity, profitability and switching

    DEFF Research Database (Denmark)

    Visser, Andre W.; Fiksen, Ø.

    2013-01-01

    ecological mechanics and evolutionary logic as a solution to diet selection in ecosystem models. When a predator can consume a range of prey items it has to choose which foraging mode to use, which prey to ignore and which ones to pursue, and animals are known to be particularly skilled in adapting...... to the preference functions commonly used in models today. Indeed, depending on prey class resolution, optimal foraging can yield feeding rates that are considerably different from the ‘switching functions’ often applied in marine ecosystem models. Dietary inclusion is dictated by two optimality choices: 1...... by letting predators maximize energy intake or more properly, some measure of fitness where predation risk and cost are also included. An optimal foraging or fitness maximizing approach will give marine ecosystem models a sound principle to determine trophic interactions...

  5. Covariate selection for the semiparametric additive risk model

    DEFF Research Database (Denmark)

    Martinussen, Torben; Scheike, Thomas

    2009-01-01

    This paper considers covariate selection for the additive hazards model. This model is particularly simple to study theoretically and its practical implementation has several major advantages to the similar methodology for the proportional hazards model. One complication compared...... and study their large sample properties for the situation where the number of covariates p is smaller than the number of observations. We also show that the adaptive Lasso has the oracle property. In many practical situations, it is more relevant to tackle the situation with large p compared with the number...... of observations. We do this by studying the properties of the so-called Dantzig selector in the setting of the additive risk model. Specifically, we establish a bound on how close the solution is to a true sparse signal in the case where the number of covariates is large. In a simulation study, we also compare...

  6. Selection of productivity improvement techniques via mathematical modeling

    Directory of Open Access Journals (Sweden)

    Mahassan M. Khater

    2011-07-01

    Full Text Available This paper presents a new mathematical model to select an optimal combination of productivity improvement techniques. The proposed model of this paper considers four-stage cycle productivity and the productivity is assumed to be a linear function of fifty four improvement techniques. The proposed model of this paper is implemented for a real-world case study of manufacturing plant. The resulted problem is formulated as a mixed integer programming which can be solved for optimality using traditional methods. The preliminary results of the implementation of the proposed model of this paper indicate that the productivity can be improved through a change on equipments and it can be easily applied for both manufacturing and service industries.

  7. An Introduction to Model Selection: Tools and Algorithms

    Directory of Open Access Journals (Sweden)

    Sébastien Hélie

    2006-03-01

    Full Text Available Model selection is a complicated matter in science, and psychology is no exception. In particular, the high variance in the object of study (i.e., humans prevents the use of Popper’s falsification principle (which is the norm in other sciences. Therefore, the desirability of quantitative psychological models must be assessed by measuring the capacity of the model to fit empirical data. In the present paper, an error measure (likelihood, as well as five methods to compare model fits (the likelihood ratio test, Akaike’s information criterion, the Bayesian information criterion, bootstrapping and cross-validation, are presented. The use of each method is illustrated by an example, and the advantages and weaknesses of each method are also discussed.

  8. IVF or IUI as first-line treatment in unexplained subfertility : the conundrum of treatment selection markers

    NARCIS (Netherlands)

    Tjon-Kon-Fat, R I; Tajik, P; Zafarmand, M H; Bensdorp, A J; Bossuyt, P M M; Oosterhuis, G J E; van Golde, R; Repping, S; Lambers, M D A; Slappendel, E; Perquin, D; Pelinck, M J; Gianotten, J; Maas, J W M; Eijkemans, M J C|info:eu-repo/dai/nl/156353253; van der Veen, F; Mol, B W; van Wely, M

    STUDY QUESTION: Are there treatment selection markers that could aid in identifying couples, with unexplained or mild male subfertility, who would have better chances of a healthy child with IVF with single embryo transfer (IVF-SET) than with IUI with ovarian stimulation (IUI-OS)? SUMMARY ANSWER: We

  9. Treatment of Selective Serotonin Reuptake Inhibitor-Resistant Depression in Adolescents: Predictors and Moderators of Treatment Response

    Science.gov (United States)

    Asarnow, Joan Rosenbaum; Emslie, Graham; Clarke, Greg; Wagner, Karen Dineen; Spirito, Anthony; Vitiello, Benedetto; Iyengar, Satish; Shamseddeen, Wael; Ritz, Louise; Birmaher, Boris; Ryan, Neal; Kennard, Betsy; Mayes, Taryn; DeBar, Lynn; McCracken, James; Strober, Michael; Suddath, Robert; Leonard, Henrietta; Porta, Giovanna; Keller, Martin; Brent, David

    2009-01-01

    Adolescents who did not improve with Selective Serotonin Reuptake Inhibitor (SSRI) were provided an alternative SSRI plus cognitive-behavioral therapy (CBT). The superiority of the CBT/combined treatment as compared to medication alone is more evident in youths who had more comorbid disorders, no abuse history, and lower hopelessness.

  10. Body condition score as a selection tool for targeted selective treatment-based nematode control strategies in Merino ewes.

    Science.gov (United States)

    Cornelius, M P; Jacobson, C; Besier, R B

    2014-12-15

    Sheep nematode control utilising refugia-based strategies have been shown to delay anthelmintic resistance, but the optimal indices to select individuals to be left untreated under extensive sheep grazing conditions are not clear. This experiment tested the hypothesis that high body condition can indicate ability of mature sheep to better cope with worms and therefore remain untreated in a targeted treatment programme. Adult Merino ewes from flocks on two private farms located in south-west Western Australia (Farm A, n = 271, and Farm B, n = 258) were measured for body condition score (BCS), body weight and worm egg counts (WEC) on four occasions between May and December (pre-lambing, lamb marking, lamb weaning and post-weaning). Half of the ewes in each flock received anthelmintic treatments to suppress WEC over the experimental period and half remained untreated (unless critical limits were reached). Response to treatment was analysed in terms of BCS change and percentage live weight change. No effect of high or low initial WEC groups was shown for BCS response, and liveweight responses were inconsistent. A relatively greater BCS response to treatment was observed in ewes in low BCS pre-lambing compared to better-conditioned ewes on one farm where nutrition was sub-optimal and worm burdens were high. Sheep in low body condition pre-lambing were more than three times more likely to fall into a critically low BCS (<2.0) if left untreated. Recommendations can be made to treat ewes in lower BCS and leave a proportion of the higher body condition sheep untreated in a targeted selective treatment programme, to provide a population of non-resistant worms to delay the development of resistance. Copyright © 2014 Elsevier B.V. All rights reserved.

  11. Selection of Representative Models for Decision Analysis Under Uncertainty

    Science.gov (United States)

    Meira, Luis A. A.; Coelho, Guilherme P.; Santos, Antonio Alberto S.; Schiozer, Denis J.

    2016-03-01

    The decision-making process in oil fields includes a step of risk analysis associated with the uncertainties present in the variables of the problem. Such uncertainties lead to hundreds, even thousands, of possible scenarios that are supposed to be analyzed so an effective production strategy can be selected. Given this high number of scenarios, a technique to reduce this set to a smaller, feasible subset of representative scenarios is imperative. The selected scenarios must be representative of the original set and also free of optimistic and pessimistic bias. This paper is devoted to propose an assisted methodology to identify representative models in oil fields. To do so, first a mathematical function was developed to model the representativeness of a subset of models with respect to the full set that characterizes the problem. Then, an optimization tool was implemented to identify the representative models of any problem, considering not only the cross-plots of the main output variables, but also the risk curves and the probability distribution of the attribute-levels of the problem. The proposed technique was applied to two benchmark cases and the results, evaluated by experts in the field, indicate that the obtained solutions are richer than those identified by previously adopted manual approaches. The program bytecode is available under request.

  12. Framework for Construction of Multi-scale Models for Biological Wastewater Treatment Processes - Case Study: Autotrophic Nitrogen Conversion

    DEFF Research Database (Denmark)

    Vangsgaard, Anna Katrine; Mauricio Iglesias, Miguel; Gernaey, Krist

    2011-01-01

    In wastewater treatment technologies, employing biofilms or granular biomass, processes might occur at very different spatial and temporal scales. Model development for such systems is typically a tedious, complicated, and time consuming task, which involves selecting appropriate model equations...

  13. Selecting global climate models for regional climate change studies.

    Science.gov (United States)

    Pierce, David W; Barnett, Tim P; Santer, Benjamin D; Gleckler, Peter J

    2009-05-26

    Regional or local climate change modeling studies currently require starting with a global climate model, then downscaling to the region of interest. How should global models be chosen for such studies, and what effect do such choices have? This question is addressed in the context of a regional climate detection and attribution (D&A) study of January-February-March (JFM) temperature over the western U.S. Models are often selected for a regional D&A analysis based on the quality of the simulated regional climate. Accordingly, 42 performance metrics based on seasonal temperature and precipitation, the El Nino/Southern Oscillation (ENSO), and the Pacific Decadal Oscillation are constructed and applied to 21 global models. However, no strong relationship is found between the score of the models on the metrics and results of the D&A analysis. Instead, the importance of having ensembles of runs with enough realizations to reduce the effects of natural internal climate variability is emphasized. Also, the superiority of the multimodel ensemble average (MM) to any 1 individual model, already found in global studies examining the mean climate, is true in this regional study that includes measures of variability as well. Evidence is shown that this superiority is largely caused by the cancellation of offsetting errors in the individual global models. Results with both the MM and models picked randomly confirm the original D&A results of anthropogenically forced JFM temperature changes in the western U.S. Future projections of temperature do not depend on model performance until the 2080s, after which the better performing models show warmer temperatures.

  14. Selecting an Appropriate Upscaled Reservoir Model Based on Connectivity Analysis

    Directory of Open Access Journals (Sweden)

    Preux Christophe

    2016-09-01

    Full Text Available Reservoir engineers aim to build reservoir models to investigate fluid flows within hydrocarbon reservoirs. These models consist of three-dimensional grids populated by petrophysical properties. In this paper, we focus on permeability that is known to significantly influence fluid flow. Reservoir models usually encompass a very large number of fine grid blocks to better represent heterogeneities. However, performing fluid flow simulations for such fine models is extensively CPU-time consuming. A common practice consists in converting the fine models into coarse models with less grid blocks: this is the upscaling process. Many upscaling methods have been proposed in the literature that all lead to distinct coarse models. The problem is how to choose the appropriate upscaling method. Various criteria have been established to evaluate the information loss due to upscaling, but none of them investigate connectivity. In this paper, we propose to first perform a connectivity analysis for the fine and candidate coarse models. This makes it possible to identify shortest paths connecting wells. Then, we introduce two indicators to quantify the length and trajectory mismatch between the paths for the fine and the coarse models. The upscaling technique to be recommended is the one that provides the coarse model for which the shortest paths are the closest to the shortest paths determined for the fine model, both in terms of length and trajectory. Last, the potential of this methodology is investigated from two test cases. We show that the two indicators help select suitable upscaling techniques as long as gravity is not a prominent factor that drives fluid flows.

  15. Alternatives for OSAHS treatment: selection of patients for upper airway surgery and oral appliances

    Directory of Open Access Journals (Sweden)

    A. Boudewyns

    2007-12-01

    Full Text Available Although continuous positive airway pressure (CPAP is considered to represent the standard treatment for patients with moderate-to-severe obstructive sleep apnoea/hypopnoea syndrome (OSAHS, poor treatment compliance and/or refusal is an issue in 20–30% of these patients. As an alternative to life-long CPAP treatment, conservative procedures exist with dental appliances for mandibular advancement, as well as curative surgical techniques. Surgical treatment of OSAHS can be divided into the following two main groups: 1 upper airway surgery by soft tissue resection (uvulopalatopharyngoplasty, etc., and 2 skeletal procedures, such as maxillo-mandibular advancement. Proper selection of patients for the different treatment modalities is the key for full treatment success. Patient-related factors, such as the site of upper airway collapse, craniofacial characteristics, dental health, obesity, age, profession and positional dependence, as well as treatment-related factors, should be evaluated before a final proposal for these treatment alternatives is formulated.

  16. Bioeconomic model and selection indices in Aberdeen Angus cattle.

    Science.gov (United States)

    Campos, G S; Braccini Neto, J; Oaigen, R P; Cardoso, F F; Cobuci, J A; Kern, E L; Campos, L T; Bertoli, C D; McManus, C M

    2014-08-01

    A bioeconomic model was developed to calculate economic values for biological traits in full-cycle production systems and propose selection indices based on selection criteria used in the Brazilian Aberdeen Angus genetic breeding programme (PROMEBO). To assess the impact of changes in the performance of the traits on the profit of the production system, the initial values ​​of the traits were increased by 1%. The economic values for number of calves weaned (NCW) and slaughter weight (SW) were, respectively, R$ 6.65 and R$ 1.43/cow/year. The selection index at weaning showed a 44.77% emphasis on body weight, 14.24% for conformation, 30.36% for early maturing and 10.63% for muscle development. The eighteen-month index showed emphasis of 77.61% for body weight, 4.99% for conformation, 11.09% for early maturing, 6.10% for muscle development and 0.22% for scrotal circumference. NCW showed highest economic impact, and SW had important positive effect on the economics of the production system. The selection index proposed can be used by breeders and should contribute to greater profitability. © 2014 Blackwell Verlag GmbH.

  17. How Many Separable Sources? Model Selection In Independent Components Analysis

    DEFF Research Database (Denmark)

    Woods, Roger P.; Hansen, Lars Kai; Strother, Stephen

    2015-01-01

    Unlike mixtures consisting solely of non-Gaussian sources, mixtures including two or more Gaussian components cannot be separated using standard independent components analysis methods that are based on higher order statistics and independent observations. The mixed Independent Components Analysis....../Principal Components Analysis (mixed ICA/PCA) model described here accommodates one or more Gaussian components in the independent components analysis model and uses principal components analysis to characterize contributions from this inseparable Gaussian subspace. Information theory can then be used to select from...... among potential model categories with differing numbers of Gaussian components. Based on simulation studies, the assumptions and approximations underlying the Akaike Information Criterion do not hold in this setting, even with a very large number of observations. Cross-validation is a suitable, though...

  18. Auditory-model based robust feature selection for speech recognition.

    Science.gov (United States)

    Koniaris, Christos; Kuropatwinski, Marcin; Kleijn, W Bastiaan

    2010-02-01

    It is shown that robust dimension-reduction of a feature set for speech recognition can be based on a model of the human auditory system. Whereas conventional methods optimize classification performance, the proposed method exploits knowledge implicit in the auditory periphery, inheriting its robustness. Features are selected to maximize the similarity of the Euclidean geometry of the feature domain and the perceptual domain. Recognition experiments using mel-frequency cepstral coefficients (MFCCs) confirm the effectiveness of the approach, which does not require labeled training data. For noisy data the method outperforms commonly used discriminant-analysis based dimension-reduction methods that rely on labeling. The results indicate that selecting MFCCs in their natural order results in subsets with good performance.

  19. METHODS OF SELECTING THE EFFECTIVE MODELS OF BUILDINGS REPROFILING PROJECTS

    Directory of Open Access Journals (Sweden)

    Александр Иванович МЕНЕЙЛЮК

    2016-02-01

    Full Text Available The article highlights the important task of project management in reprofiling of buildings. It is expedient to pay attention to selecting effective engineering solutions to reduce the duration and cost reduction at the project management in the construction industry. This article presents a methodology for the selection of efficient organizational and technical solutions for the reconstruction of buildings reprofiling. The method is based on a compilation of project variants in the program Microsoft Project and experimental statistical analysis using the program COMPEX. The introduction of this technique in the realigning of buildings allows choosing efficient models of projects, depending on the given constraints. Also, this technique can be used for various construction projects.

  20. Applying a Hybrid MCDM Model for Six Sigma Project Selection

    Directory of Open Access Journals (Sweden)

    Fu-Kwun Wang

    2014-01-01

    Full Text Available Six Sigma is a project-driven methodology; the projects that provide the maximum financial benefits and other impacts to the organization must be prioritized. Project selection (PS is a type of multiple criteria decision making (MCDM problem. In this study, we present a hybrid MCDM model combining the decision-making trial and evaluation laboratory (DEMATEL technique, analytic network process (ANP, and the VIKOR method to evaluate and improve Six Sigma projects for reducing performance gaps in each criterion and dimension. We consider the film printing industry of Taiwan as an empirical case. The results show that our study not only can use the best project selection, but can also be used to analyze the gaps between existing performance values and aspiration levels for improving the gaps in each dimension and criterion based on the influential network relation map.

  1. Proposition of a multicriteria model to select logistics services providers

    Directory of Open Access Journals (Sweden)

    Miriam Catarina Soares Aharonovitz

    2014-06-01

    Full Text Available This study aims to propose a multicriteria model to select logistics service providers by the development of a decision tree. The methodology consists of a survey, which resulted in a sample of 181 responses. The sample was analyzed using statistic methods, descriptive statistics among them, multivariate analysis, variance analysis, and parametric tests to compare means. Based on these results, it was possible to obtain the decision tree and information to support the multicriteria analysis. The AHP (Analytic Hierarchy Process was applied to determine the data influence and thus ensure better consistency in the analysis. The decision tree categorizes the criteria according to the decision levels (strategic, tactical and operational. Furthermore, it allows to generically evaluate the importance of each criterion in the supplier selection process from the point of view of logistics services contractors.

  2. A Reliability Based Model for Wind Turbine Selection

    Directory of Open Access Journals (Sweden)

    A.K. Rajeevan

    2013-06-01

    Full Text Available A wind turbine generator output at a specific site depends on many factors, particularly cut- in, rated and cut-out wind speed parameters. Hence power output varies from turbine to turbine. The objective of this paper is to develop a mathematical relationship between reliability and wind power generation. The analytical computation of monthly wind power is obtained from weibull statistical model using cubic mean cube root of wind speed. Reliability calculation is based on failure probability analysis. There are many different types of wind turbinescommercially available in the market. From reliability point of view, to get optimum reliability in power generation, it is desirable to select a wind turbine generator which is best suited for a site. The mathematical relationship developed in this paper can be used for site-matching turbine selection in reliability point of view.

  3. Neuroimaging-based biomarkers for treatment selection in major depressive disorder.

    Science.gov (United States)

    Dunlop, Boadie W; Mayberg, Helen S

    2014-12-01

    The use of neuroimaging approaches to identify likely treatment outcomes in patients with major depressive disorder is developing rapidly. Emerging work suggests that resting state pretreatment metabolic activity in the fronto-insular cortex may distinguish between patients likely to respond to psychotherapy or medication and may function as a treatment-selection biomarker. In contrast, high metabolic activity in the subgenual anterior cingulate cortex may be predictive of poor outcomes to both medication and psychotherapy, suggesting that nonstandard treatments may be pursued earlier in the treatment course. Although these findings will require replication before clinical adoption, they provide preliminary support for the concept that brain states can be measured and applied to the selection of a specific treatment most likely to be beneficial for an individual patient.

  4. Gastrostomy Tube Weaning and Treatment of Severe Selective Eating in Childhood: Experience in Israel Using an Intensive Three Week Program.

    Science.gov (United States)

    Shalem, Tzippora; Fradkin, Akiva; Dunitz-Scheer, Marguerite; Sadeh-Kon, Tal; Goz-Gulik, Tali; Fishler, Yael; Weiss, Batia

    2016-06-01

    Children dependent on gastrostomy tube feeding and those with extremely selective eating comprise the most challenging groups of early childhood eating disorders. We established, for the first time in Israel, a 3 week intensive weaning and treatment program for these patients based on the "Graz model." To investigate the Graz model for tube weaning and for treating severe selective eating disorders in one center in Israel. Pre-program assessment of patients' suitability to participate was performed 3 months prior to the study, and a treatment goal was set for each patient. The program included a multidisciplinary outpatient or inpatient 3 week treatment course. The major outcome measures were achievement of the target goal of complete or partial tube weaning for those with tube dependency, and expansion of the child's nutritional diversity for those with selective eating. Thirty-four children, 28 with tube dependency and 6 with selective eating, participated in four programs conducted over 24 months. Their mean age was 4.3 ± 0.37 years. Of all patients, 29 (85%) achieved the target goal (24 who were tube-dependent and 5 selective eaters). One patient was excluded due to aspiration pneumonia. After 6 months follow-up, 24 of 26 available patients (92%) maintained their target or improved. This intensive 3 week program was highly effective in weaning children with gastrostomy tube dependency and ameliorating severe selective eating. Preliminary evaluation of the family is necessary for completion of the program and achieving the child's personal goal, as are an experienced multidisciplinary team and the appropriate hospital setup, i.e., inpatient or outpatient.

  5. Development of Solar Drying Model for Selected Cambodian Fish Species

    Directory of Open Access Journals (Sweden)

    Anna Hubackova

    2014-01-01

    Full Text Available A solar drying was investigated as one of perspective techniques for fish processing in Cambodia. The solar drying was compared to conventional drying in electric oven. Five typical Cambodian fish species were selected for this study. Mean solar drying temperature and drying air relative humidity were 55.6°C and 19.9%, respectively. The overall solar dryer efficiency was 12.37%, which is typical for natural convection solar dryers. An average evaporative capacity of solar dryer was 0.049 kg·h−1. Based on coefficient of determination (R2, chi-square (χ2 test, and root-mean-square error (RMSE, the most suitable models describing natural convection solar drying kinetics were Logarithmic model, Diffusion approximate model, and Two-term model for climbing perch and Nile tilapia, swamp eel and walking catfish and Channa fish, respectively. In case of electric oven drying, the Modified Page 1 model shows the best results for all investigated fish species except Channa fish where the two-term model is the best one. Sensory evaluation shows that most preferable fish is climbing perch, followed by Nile tilapia and walking catfish. This study brings new knowledge about drying kinetics of fresh water fish species in Cambodia and confirms the solar drying as acceptable technology for fish processing.

  6. Fuzzy Goal Programming Approach in Selective Maintenance Reliability Model

    Directory of Open Access Journals (Sweden)

    Neha Gupta

    2013-12-01

    Full Text Available 800x600 In the present paper, we have considered the allocation problem of repairable components for a parallel-series system as a multi-objective optimization problem and have discussed two different models. In first model the reliability of subsystems are considered as different objectives. In second model the cost and time spent on repairing the components are considered as two different objectives. These two models is formulated as multi-objective Nonlinear Programming Problem (MONLPP and a Fuzzy goal programming method is used to work out the compromise allocation in multi-objective selective maintenance reliability model in which we define the membership functions of each objective function and then transform membership functions into equivalent linear membership functions by first order Taylor series and finally by forming a fuzzy goal programming model obtain a desired compromise allocation of maintenance components. A numerical example is also worked out to illustrate the computational details of the method.  Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4

  7. Selection of candidate wells and optimization of conformance treatment design in the Barrancas Field using a 3D conformance simulator

    Energy Technology Data Exchange (ETDEWEB)

    Crosta, Dante; Elitseche, Luis [Repsol YPF (Argentina); Gutierrez, Mauricio; Ansah, Joe; Everett, Don [Halliburton Argentina S.A., Buenos Aires (Argentina)

    2004-07-01

    Minimizing the amount of unwanted water production is an important goal at the Barrancas field. This paper describes a selection process for candidate injection wells that is part of a pilot conformance project aimed at improving vertical injection profiles, reducing water cut in producing wells, and improving ultimate oil recovery from this field. The well selection process is based on a review of limited reservoir information available for this field to determine inter-well communications. The methodology focuses on the best use of available information, such as production and injection history, well intervention files, open hole logs and injectivity surveys. After the candidate wells were selected and potential water injection channels were identified, conformance treatment design and future performance of wells in the selected pilot area were evaluated using a new 3 -D conformance simulator, developed specifically for optimization of the design and placement of unwanted fluid shut-off treatments. Thus, when acceptable history match ing of the pilot area production was obtained, the 3 -D simulator was used to: evaluate the required volume of selected conformance treatment fluid; review expected pressures and rates during placement;. model temperature behavior; evaluate placement techniques, and forecast water cut reduction and incremental oil recovery from the producers in this simulated section of the pilot area. This paper outlines a methodology for selecting candidate wells for conformance treatments. The method involves application of several engineering tools, an integral component of which is a user-friendly conformance simulator. The use of the simulator has minimized data preparation time and allows the running of sensitivity cases quickly to explore different possible scenarios that best represent the reservoir. The proposed methodology provides an efficient means of identifying conformance problems and designing optimized solutions for these individual

  8. Modelling the Ozone-Based Treatments for Inactivation of Microorganisms.

    Science.gov (United States)

    Brodowska, Agnieszka Joanna; Nowak, Agnieszka; Kondratiuk-Janyska, Alina; Piątkowski, Marcin; Śmigielski, Krzysztof

    2017-10-09

    The paper presents the development of a model for ozone treatment in a dynamic bed of different microorganisms ( Bacillus subtilis , B. cereus , B. pumilus , Escherichia coli , Pseudomonas fluorescens , Aspergillus niger , Eupenicillium cinnamopurpureum ) on a heterogeneous matrix (juniper berries, cardamom seeds) initially treated with numerous ozone doses during various contact times was studied. Taking into account various microorganism susceptibility to ozone, it was of great importance to develop a sufficiently effective ozone dose to preserve food products using different strains based on the microbial model. For this purpose, we have chosen the Weibull model to describe the survival curves of different microorganisms. Based on the results of microorganism survival modelling after ozone treatment and considering the least susceptible strains to ozone, we selected the critical ones. Among tested strains, those from genus Bacillus were recognized as the most critical strains. In particular, B. subtilis and B. pumilus possessed the highest resistance to ozone treatment because the time needed to achieve the lowest level of its survival was the longest (up to 17.04 min and 16.89 min for B. pumilus reduction on juniper berry and cardamom seed matrix, respectively). Ozone treatment allow inactivate microorganisms to achieving lower survival rates by ozone dose (20.0 g O₃/m³ O₂, with a flow rate of 0.4 L/min) and contact time (up to 20 min). The results demonstrated that a linear correlation between parameters p and k in Weibull distribution, providing an opportunity to calculate a fitted equation of the process.

  9. Selective release of phosphorus and nitrogen from waste activated sludge with combined thermal and alkali treatment.

    Science.gov (United States)

    Kim, Minwook; Han, Dong-Woo; Kim, Dong-Jin

    2015-08-01

    Selective release characteristics of phosphorus and nitrogen from waste activated sludge (WAS) were investigated during combined thermal and alkali treatment. Alkali (0.001-1.0N NaOH) treatment and combined thermal-alkali treatment were applied to WAS for releasing total P(T-P) and total nitrogen(T-N). Combined thermal-alkali treatment released 94%, 76%, and 49% of T-P, T-N, and COD, respectively. Release rate was positively associated with NaOH concentration, while temperature gave insignificant effect. The ratio of T-N and COD to T-P that released with alkali treatment ranged 0.74-0.80 and 0.39-0.50, respectively, while combined thermal-alkali treatment gave 0.60-0.90 and 0.20-0.60, respectively. Selective release of T-P and T-N was negatively associated with NaOH. High NaOH concentration created cavities on the surface of WAS, and these cavities accelerated the release rate, but reduced selectivity. Selective release of P and N from sludge has a beneficial effect on nutrient recovery with crystallization processes and it can also enhance methane production. Copyright © 2015 Elsevier Ltd. All rights reserved.

  10. Selection Strategies for Social Influence in the Threshold Model

    Science.gov (United States)

    Karampourniotis, Panagiotis; Szymanski, Boleslaw; Korniss, Gyorgy

    The ubiquity of online social networks makes the study of social influence extremely significant for its applications to marketing, politics and security. Maximizing the spread of influence by strategically selecting nodes as initiators of a new opinion or trend is a challenging problem. We study the performance of various strategies for selection of large fractions of initiators on a classical social influence model, the Threshold model (TM). Under the TM, a node adopts a new opinion only when the fraction of its first neighbors possessing that opinion exceeds a pre-assigned threshold. The strategies we study are of two kinds: strategies based solely on the initial network structure (Degree-rank, Dominating Sets, PageRank etc.) and strategies that take into account the change of the states of the nodes during the evolution of the cascade, e.g. the greedy algorithm. We find that the performance of these strategies depends largely on both the network structure properties, e.g. the assortativity, and the distribution of the thresholds assigned to the nodes. We conclude that the optimal strategy needs to combine the network specifics and the model specific parameters to identify the most influential spreaders. Supported in part by ARL NS-CTA, ARO, and ONR.

  11. Continuum model for chiral induced spin selectivity in helical molecules

    Energy Technology Data Exchange (ETDEWEB)

    Medina, Ernesto [Centro de Física, Instituto Venezolano de Investigaciones Científicas, 21827, Caracas 1020 A (Venezuela, Bolivarian Republic of); Groupe de Physique Statistique, Institut Jean Lamour, Université de Lorraine, 54506 Vandoeuvre-les-Nancy Cedex (France); Department of Chemistry and Biochemistry, Arizona State University, Tempe, Arizona 85287 (United States); González-Arraga, Luis A. [IMDEA Nanoscience, Cantoblanco, 28049 Madrid (Spain); Finkelstein-Shapiro, Daniel; Mujica, Vladimiro [Department of Chemistry and Biochemistry, Arizona State University, Tempe, Arizona 85287 (United States); Berche, Bertrand [Centro de Física, Instituto Venezolano de Investigaciones Científicas, 21827, Caracas 1020 A (Venezuela, Bolivarian Republic of); Groupe de Physique Statistique, Institut Jean Lamour, Université de Lorraine, 54506 Vandoeuvre-les-Nancy Cedex (France)

    2015-05-21

    A minimal model is exactly solved for electron spin transport on a helix. Electron transport is assumed to be supported by well oriented p{sub z} type orbitals on base molecules forming a staircase of definite chirality. In a tight binding interpretation, the spin-orbit coupling (SOC) opens up an effective π{sub z} − π{sub z} coupling via interbase p{sub x,y} − p{sub z} hopping, introducing spin coupled transport. The resulting continuum model spectrum shows two Kramers doublet transport channels with a gap proportional to the SOC. Each doubly degenerate channel satisfies time reversal symmetry; nevertheless, a bias chooses a transport direction and thus selects for spin orientation. The model predicts (i) which spin orientation is selected depending on chirality and bias, (ii) changes in spin preference as a function of input Fermi level and (iii) back-scattering suppression protected by the SO gap. We compute the spin current with a definite helicity and find it to be proportional to the torsion of the chiral structure and the non-adiabatic Aharonov-Anandan phase. To describe room temperature transport, we assume that the total transmission is the result of a product of coherent steps.

  12. Selection of models to calculate the LLW source term

    International Nuclear Information System (INIS)

    Sullivan, T.M.

    1991-10-01

    Performance assessment of a LLW disposal facility begins with an estimation of the rate at which radionuclides migrate out of the facility (i.e., the source term). The focus of this work is to develop a methodology for calculating the source term. In general, the source term is influenced by the radionuclide inventory, the wasteforms and containers used to dispose of the inventory, and the physical processes that lead to release from the facility (fluid flow, container degradation, wasteform leaching, and radionuclide transport). In turn, many of these physical processes are influenced by the design of the disposal facility (e.g., infiltration of water). The complexity of the problem and the absence of appropriate data prevent development of an entirely mechanistic representation of radionuclide release from a disposal facility. Typically, a number of assumptions, based on knowledge of the disposal system, are used to simplify the problem. This document provides a brief overview of disposal practices and reviews existing source term models as background for selecting appropriate models for estimating the source term. The selection rationale and the mathematical details of the models are presented. Finally, guidance is presented for combining the inventory data with appropriate mechanisms describing release from the disposal facility. 44 refs., 6 figs., 1 tab

  13. Integrated modeling of ozonation for optimization of drinking water treatment

    NARCIS (Netherlands)

    van der Helm, A.W.C.

    2007-01-01

    Drinking water treatment plants automation becomes more sophisticated, more on-line monitoring systems become available and integration of modeling environments with control systems becomes easier. This gives possibilities for model-based optimization. In operation of drinking water treatment

  14. Variable Selection in Model-based Clustering: A General Variable Role Modeling

    OpenAIRE

    Maugis, Cathy; Celeux, Gilles; Martin-Magniette, Marie-Laure

    2008-01-01

    The currently available variable selection procedures in model-based clustering assume that the irrelevant clustering variables are all independent or are all linked with the relevant clustering variables. We propose a more versatile variable selection model which describes three possible roles for each variable: The relevant clustering variables, the irrelevant clustering variables dependent on a part of the relevant clustering variables and the irrelevant clustering variables totally indepe...

  15. A Dual-Stage Two-Phase Model of Selective Attention

    Science.gov (United States)

    Hubner, Ronald; Steinhauser, Marco; Lehle, Carola

    2010-01-01

    The dual-stage two-phase (DSTP) model is introduced as a formal and general model of selective attention that includes both an early and a late stage of stimulus selection. Whereas at the early stage information is selected by perceptual filters whose selectivity is relatively limited, at the late stage stimuli are selected more efficiently on a…

  16. Direction selectivity in a model of the starburst amacrine cell.

    Science.gov (United States)

    Tukker, John J; Taylor, W Rowland; Smith, Robert G

    2004-01-01

    The starburst amacrine cell (SBAC), found in all mammalian retinas, is thought to provide the directional inhibitory input recorded in On-Off direction-selective ganglion cells (DSGCs). While voltage recordings from the somas of SBACs have not shown robust direction selectivity (DS), the dendritic tips of these cells display direction-selective calcium signals, even when gamma-aminobutyric acid (GABAa,c) channels are blocked, implying that inhibition is not necessary to generate DS. This suggested that the distinctive morphology of the SBAC could generate a DS signal at the dendritic tips, where most of its synaptic output is located. To explore this possibility, we constructed a compartmental model incorporating realistic morphological structure, passive membrane properties, and excitatory inputs. We found robust DS at the dendritic tips but not at the soma. Two-spot apparent motion and annulus radial motion produced weak DS, but thin bars produced robust DS. For these stimuli, DS was caused by the interaction of a local synaptic input signal with a temporally delayed "global" signal, that is, an excitatory postsynaptic potential (EPSP) that spread from the activated inputs into the soma and throughout the dendritic tree. In the preferred direction the signals in the dendritic tips coincided, allowing summation, whereas in the null direction the local signal preceded the global signal, preventing summation. Sine-wave grating stimuli produced the greatest amount of DS, especially at high velocities and low spatial frequencies. The sine-wave DS responses could be accounted for by a simple mathematical model, which summed phase-shifted signals from soma and dendritic tip. By testing different artificial morphologies, we discovered DS was relatively independent of the morphological details, but depended on having a sufficient number of inputs at the distal tips and a limited electrotonic isolation. Adding voltage-gated calcium channels to the model showed that their

  17. Effect of tetracycline dose and treatment mode on selection of resistant coliform bacteria in nursery pigs

    DEFF Research Database (Denmark)

    Græsbøll, Kaare; Damborg, Peter; Mellerup, Anders

    2017-01-01

    This study describes the results of a randomized clinical trial investigating the effect of oxytetracycline treatment dose and mode of administration on the selection of antibiotic-resistant coliform bacteria in fecal samples from nursery pigs. Nursery pigs (pigs of 4 to 7 weeks of age) in five pig...... by the time that the pigs left the nursery unit. The counts and proportions of tetracyclineresistant coliforms did not vary significantly between treatment groups, except immediately after treatment, when the highest treatment dose resulted in the highest number of resistant coliforms. A control group treated...

  18. Parametric pattern selection in a reaction-diffusion model.

    Directory of Open Access Journals (Sweden)

    Michael Stich

    Full Text Available We compare spot patterns generated by Turing mechanisms with those generated by replication cascades, in a model one-dimensional reaction-diffusion system. We determine the stability region of spot solutions in parameter space as a function of a natural control parameter (feed-rate where degenerate patterns with different numbers of spots coexist for a fixed feed-rate. While it is possible to generate identical patterns via both mechanisms, we show that replication cascades lead to a wider choice of pattern profiles that can be selected through a tuning of the feed-rate, exploiting hysteresis and directionality effects of the different pattern pathways.

  19. Estimation and variable selection for generalized additive partial linear models

    KAUST Repository

    Wang, Li

    2011-08-01

    We study generalized additive partial linear models, proposing the use of polynomial spline smoothing for estimation of nonparametric functions, and deriving quasi-likelihood based estimators for the linear parameters. We establish asymptotic normality for the estimators of the parametric components. The procedure avoids solving large systems of equations as in kernel-based procedures and thus results in gains in computational simplicity. We further develop a class of variable selection procedures for the linear parameters by employing a nonconcave penalized quasi-likelihood, which is shown to have an asymptotic oracle property. Monte Carlo simulations and an empirical example are presented for illustration. © Institute of Mathematical Statistics, 2011.

  20. Group therapy for selective mutism - a parents' and children's treatment group.

    Science.gov (United States)

    Sharkey, Louise; Mc Nicholas, Fiona; Barry, Edwina; Begley, Maire; Ahern, Sinead

    2008-12-01

    To evaluate the feasibility and effectiveness of group therapy for children with selective mutism and their parents. Five children (mean age 6.1 years) with a diagnosis of selective mutism were administered group therapy over an 8-week period. Parents simultaneously attended a second group, aimed at providing education and advice on managing selective mutism in everyday situations, and in the school environment. At post-treatment, all children increased their level of confident speaking in school, clinic and community settings. Parents indicated a reduction in their own anxiety levels, from pre- to post-treatment on self-rating scales. Findings support the feasibility and effectiveness of group therapy for children with selective mutism and their parents.

  1. Modeling Knowledge Resource Selection in Expert Librarian Search

    Science.gov (United States)

    KAUFMAN, David R.; MEHRYAR, Maryam; CHASE, Herbert; HUNG, Peter; CHILOV, Marina; JOHNSON, Stephen B.; MENDONCA, Eneida

    2011-01-01

    Providing knowledge at the point of care offers the possibility for reducing error and improving patient outcomes. However, the vast majority of physician’s information needs are not met in a timely fashion. The research presented in this paper models an expert librarian’s search strategies as it pertains to the selection and use of various electronic information resources. The 10 searches conducted by the librarian to address physician’s information needs, varied in terms of complexity and question type. The librarian employed a total of 10 resources and used as many as 7 in a single search. The longer term objective is to model the sequential process in sufficient detail as to be able to contribute to the development of intelligent automated search agents. PMID:19380912

  2. An automation model of Effluent Treatment Plant

    Directory of Open Access Journals (Sweden)

    Luiz Alberto Oliveira Lima Roque

    2012-07-01

    on the conservation of water resources, this paper aims to propose an automation model of an Effluent Treatment Plant, using Ladder programming language and supervisory systems.

  3. Fuzzy Multicriteria Model for Selection of Vibration Technology

    Directory of Open Access Journals (Sweden)

    María Carmen Carnero

    2016-01-01

    Full Text Available The benefits of applying the vibration analysis program are well known and have been so for decades. A large number of contributions have been produced discussing new diagnostic, signal treatment, technical parameter analysis, and prognosis techniques. However, to obtain the expected benefits from a vibration analysis program, it is necessary to choose the instrumentation which guarantees the best results. Despite its importance, in the literature, there are no models to assist in taking this decision. This research describes an objective model using Fuzzy Analytic Hierarchy Process (FAHP to make a choice of the most suitable technology among portable vibration analysers. The aim is to create an easy-to-use model for processing, manufacturing, services, and research organizations, to guarantee adequate decision-making in the choice of vibration analysis technology. The model described recognises that judgements are often based on ambiguous, imprecise, or inadequate information that cannot provide precise values. The model incorporates judgements from several decision-makers who are experts in the field of vibration analysis, maintenance, and electronic devices. The model has been applied to a Health Care Organization.

  4. Microbial selectivity of UV treatment on antibiotic-resistant heterotrophic bacteria in secondary effluents of a municipal wastewater treatment plant.

    Science.gov (United States)

    Guo, Mei-Ting; Yuan, Qing-Bin; Yang, Jian

    2013-10-15

    Little is known about the microbial selectivity of UV treatment for antibiotic resistant bacteria, and the results of limited studies are conflicting. To understand the effect of UV disinfection on antibiotic resistant bacteria, both total heterotrophic bacteria and antibiotic resistant bacteria (including cephalexin-, ciprofloxacin-, erythromycin-, gentamicin-, vancomycin-, sulfadiazine-, rifampicin-, tetracycline- and chloramphenicol-resistant bacteria) were examined in secondary effluent samples from a municipal wastewater treatment plant. Bacteria resistant to both erythromycin and tetracycline were chosen as the representative of multiple-antibiotic-resistant bacteria and their characteristics after UV treatment were also investigated. UV disinfection results in effective inactivation for total heterotrophic bacteria, as well as all antibiotic resistant bacteria. After UV treatment at a fluence of 5 mJ/cm(2), the log reductions of nine types of antibiotic resistant bacteria varied from 1.0 ± 0.1 to 2.4 ± 0.1. Bacteria resistant to both erythromycin and tetracycline had a similar fluence response as did total heterotrophic bacteria. The findings suggest that UV disinfection could eliminate antibiotic resistance in wastewater treatment effluents and thus ensure public health security. Our experimental results indicated that UV disinfection led to enrichment of bacteria with resistance to sulfadiazine, vancomycin, rifampicin, tetracycline and chloramphenicol, while the proportions of cephalexin-, erythromycin-, gentamicin- and ciprofloxacin-resistant bacteria in the wastewater decreased. This reveals the microbial selectivity of UV disinfection for antibiotic resistant bacteria. Copyright © 2013 Elsevier Ltd. All rights reserved.

  5. Cliff-edge model of obstetric selection in humans.

    Science.gov (United States)

    Mitteroecker, Philipp; Huttegger, Simon M; Fischer, Barbara; Pavlicev, Mihaela

    2016-12-20

    The strikingly high incidence of obstructed labor due to the disproportion of fetal size and the mother's pelvic dimensions has puzzled evolutionary scientists for decades. Here we propose that these high rates are a direct consequence of the distinct characteristics of human obstetric selection. Neonatal size relative to the birth-relevant maternal dimensions is highly variable and positively associated with reproductive success until it reaches a critical value, beyond which natural delivery becomes impossible. As a consequence, the symmetric phenotype distribution cannot match the highly asymmetric, cliff-edged fitness distribution well: The optimal phenotype distribution that maximizes population mean fitness entails a fraction of individuals falling beyond the "fitness edge" (i.e., those with fetopelvic disproportion). Using a simple mathematical model, we show that weak directional selection for a large neonate, a narrow pelvic canal, or both is sufficient to account for the considerable incidence of fetopelvic disproportion. Based on this model, we predict that the regular use of Caesarean sections throughout the last decades has led to an evolutionary increase of fetopelvic disproportion rates by 10 to 20%.

  6. Developing a conceptual model for selecting and evaluating online markets

    Directory of Open Access Journals (Sweden)

    Sadegh Feizollahi

    2013-04-01

    Full Text Available There are many evidences, which emphasis on the benefits of using new technologies of information and communication in international business and many believe that E-Commerce can help satisfy customer explicit and implicit requirements. Internet shopping is a concept developed after the introduction of electronic commerce. Information technology (IT and its applications, specifically in the realm of the internet and e-mail promoted the development of e-commerce in terms of advertising, motivating and information. However, with the development of new technologies, credit and financial exchange on the internet websites were constructed so to facilitate e-commerce. The proposed study sends a total of 200 questionnaires to the target group (teachers - students - professionals - managers of commercial web sites and it manages to collect 130 questionnaires for final evaluation. Cronbach's alpha test is used for measuring reliability and to evaluate the validity of measurement instruments (questionnaires, and to assure construct validity, confirmatory factor analysis is employed. In addition, in order to analyze the research questions based on the path analysis method and to determine markets selection models, a regular technique is implemented. In the present study, after examining different aspects of e-commerce, we provide a conceptual model for selecting and evaluating online marketing in Iran. These findings provide a consistent, targeted and holistic framework for the development of the Internet market in the country.

  7. Ensemble Prediction Model with Expert Selection for Electricity Price Forecasting

    Directory of Open Access Journals (Sweden)

    Bijay Neupane

    2017-01-01

    Full Text Available Forecasting of electricity prices is important in deregulated electricity markets for all of the stakeholders: energy wholesalers, traders, retailers and consumers. Electricity price forecasting is an inherently difficult problem due to its special characteristic of dynamicity and non-stationarity. In this paper, we present a robust price forecasting mechanism that shows resilience towards the aggregate demand response effect and provides highly accurate forecasted electricity prices to the stakeholders in a dynamic environment. We employ an ensemble prediction model in which a group of different algorithms participates in forecasting 1-h ahead the price for each hour of a day. We propose two different strategies, namely, the Fixed Weight Method (FWM and the Varying Weight Method (VWM, for selecting each hour’s expert algorithm from the set of participating algorithms. In addition, we utilize a carefully engineered set of features selected from a pool of features extracted from the past electricity price data, weather data and calendar data. The proposed ensemble model offers better results than the Autoregressive Integrated Moving Average (ARIMA method, the Pattern Sequence-based Forecasting (PSF method and our previous work using Artificial Neural Networks (ANN alone on the datasets for New York, Australian and Spanish electricity markets.

  8. A Network Analysis Model for Selecting Sustainable Technology

    Directory of Open Access Journals (Sweden)

    Sangsung Park

    2015-09-01

    Full Text Available Most companies develop technologies to improve their competitiveness in the marketplace. Typically, they then patent these technologies around the world in order to protect their intellectual property. Other companies may use patented technologies to develop new products, but must pay royalties to the patent holders or owners. Should they fail to do so, this can result in legal disputes in the form of patent infringement actions between companies. To avoid such situations, companies attempt to research and develop necessary technologies before their competitors do so. An important part of this process is analyzing existing patent documents in order to identify emerging technologies. In such analyses, extracting sustainable technology from patent data is important, because sustainable technology drives technological competition among companies and, thus, the development of new technologies. In addition, selecting sustainable technologies makes it possible to plan their R&D (research and development efficiently. In this study, we propose a network model that can be used to select the sustainable technology from patent documents, based on the centrality and degree of a social network analysis. To verify the performance of the proposed model, we carry out a case study using actual patent data from patent databases.

  9. Mutation-selection models of codon substitution and their use to estimate selective strengths on codon usage

    DEFF Research Database (Denmark)

    Yang, Ziheng; Nielsen, Rasmus

    2008-01-01

    to examine the null hypothesis that codon usage is due to mutation bias alone, not influenced by natural selection. Application of the test to the mammalian data led to rejection of the null hypothesis in most genes, suggesting that natural selection may be a driving force in the evolution of synonymous......Current models of codon substitution are formulated at the levels of nucleotide substitution and do not explicitly consider the separate effects of mutation and selection. They are thus incapable of inferring whether mutation or selection is responsible for evolution at silent sites. Here we...... implement a few population genetics models of codon substitution that explicitly consider mutation bias and natural selection at the DNA level. Selection on codon usage is modeled by introducing codon-fitness parameters, which together with mutation-bias parameters, predict optimal codon frequencies...

  10. Bootstrap model selection had similar performance for selecting authentic and noise variables compared to backward variable elimination: a simulation study.

    Science.gov (United States)

    Austin, Peter C

    2008-10-01

    Researchers have proposed using bootstrap resampling in conjunction with automated variable selection methods to identify predictors of an outcome and to develop parsimonious regression models. Using this method, multiple bootstrap samples are drawn from the original data set. Traditional backward variable elimination is used in each bootstrap sample, and the proportion of bootstrap samples in which each candidate variable is identified as an independent predictor of the outcome is determined. The performance of this method for identifying predictor variables has not been examined. Monte Carlo simulation methods were used to determine the ability of bootstrap model selection methods to correctly identify predictors of an outcome when those variables that are selected for inclusion in at least 50% of the bootstrap samples are included in the final regression model. We compared the performance of the bootstrap model selection method to that of conventional backward variable elimination. Bootstrap model selection tended to result in an approximately equal proportion of selected models being equal to the true regression model compared with the use of conventional backward variable elimination. Bootstrap model selection performed comparatively to backward variable elimination for identifying the true predictors of a binary outcome.

  11. A CONCEPTUAL MODEL FOR IMPROVED PROJECT SELECTION AND PRIORITISATION

    Directory of Open Access Journals (Sweden)

    P. J. Viljoen

    2012-01-01

    Full Text Available

    ENGLISH ABSTRACT: Project portfolio management processes are often designed and operated as a series of stages (or project phases and gates. However, the flow of such a process is often slow, characterised by queues waiting for a gate decision and by repeated work from previous stages waiting for additional information or for re-processing. In this paper the authors propose a conceptual model that applies supply chain and constraint management principles to the project portfolio management process. An advantage of the proposed model is that it provides the ability to select and prioritise projects without undue changes to project schedules. This should result in faster flow through the system.

    AFRIKAANSE OPSOMMING: Prosesse om portefeuljes van projekte te bestuur word normaalweg ontwerp en bedryf as ’n reeks fases en hekke. Die vloei deur so ’n proses is dikwels stadig en word gekenmerk deur toue wat wag vir besluite by die hekke en ook deur herwerk van vorige fases wat wag vir verdere inligting of vir herprosessering. In hierdie artikel word ‘n konseptuele model voorgestel. Die model berus op die beginsels van voorsieningskettings sowel as van beperkingsbestuur, en bied die voordeel dat projekte geselekteer en geprioritiseer kan word sonder onnodige veranderinge aan projekskedules. Dit behoort te lei tot versnelde vloei deur die stelsel.

  12. Computationally efficient thermal-mechanical modelling of selective laser melting

    Science.gov (United States)

    Yang, Yabin; Ayas, Can

    2017-10-01

    The Selective laser melting (SLM) is a powder based additive manufacturing (AM) method to produce high density metal parts with complex topology. However, part distortions and accompanying residual stresses deteriorates the mechanical reliability of SLM products. Modelling of the SLM process is anticipated to be instrumental for understanding and predicting the development of residual stress field during the build process. However, SLM process modelling requires determination of the heat transients within the part being built which is coupled to a mechanical boundary value problem to calculate displacement and residual stress fields. Thermal models associated with SLM are typically complex and computationally demanding. In this paper, we present a simple semi-analytical thermal-mechanical model, developed for SLM that represents the effect of laser scanning vectors with line heat sources. The temperature field within the part being build is attained by superposition of temperature field associated with line heat sources in a semi-infinite medium and a complimentary temperature field which accounts for the actual boundary conditions. An analytical solution of a line heat source in a semi-infinite medium is first described followed by the numerical procedure used for finding the complimentary temperature field. This analytical description of the line heat sources is able to capture the steep temperature gradients in the vicinity of the laser spot which is typically tens of micrometers. In turn, semi-analytical thermal model allows for having a relatively coarse discretisation of the complimentary temperature field. The temperature history determined is used to calculate the thermal strain induced on the SLM part. Finally, a mechanical model governed by elastic-plastic constitutive rule having isotropic hardening is used to predict the residual stresses.

  13. Comprehensible knowledge model creation for cancer treatment decision making.

    Science.gov (United States)

    Afzal, Muhammad; Hussain, Maqbool; Ali Khan, Wajahat; Ali, Taqdir; Lee, Sungyoung; Huh, Eui-Nam; Farooq Ahmad, Hafiz; Jamshed, Arif; Iqbal, Hassan; Irfan, Muhammad; Abbas Hydari, Manzar

    2017-03-01

    A wealth of clinical data exists in clinical documents in the form of electronic health records (EHRs). This data can be used for developing knowledge-based recommendation systems that can assist clinicians in clinical decision making and education. One of the big hurdles in developing such systems is the lack of automated mechanisms for knowledge acquisition to enable and educate clinicians in informed decision making. An automated knowledge acquisition methodology with a comprehensible knowledge model for cancer treatment (CKM-CT) is proposed. With the CKM-CT, clinical data are acquired automatically from documents. Quality of data is ensured by correcting errors and transforming various formats into a standard data format. Data preprocessing involves dimensionality reduction and missing value imputation. Predictive algorithm selection is performed on the basis of the ranking score of the weighted sum model. The knowledge builder prepares knowledge for knowledge-based services: clinical decisions and education support. Data is acquired from 13,788 head and neck cancer (HNC) documents for 3447 patients, including 1526 patients of the oral cavity site. In the data quality task, 160 staging values are corrected. In the preprocessing task, 20 attributes and 106 records are eliminated from the dataset. The Classification and Regression Trees (CRT) algorithm is selected and provides 69.0% classification accuracy in predicting HNC treatment plans, consisting of 11 decision paths that yield 11 decision rules. Our proposed methodology, CKM-CT, is helpful to find hidden knowledge in clinical documents. In CKM-CT, the prediction models are developed to assist and educate clinicians for informed decision making. The proposed methodology is generalizable to apply to data of other domains such as breast cancer with a similar objective to assist clinicians in decision making and education. Copyright © 2017 Elsevier Ltd. All rights reserved.

  14. Effect of Tetracycline Dose and Treatment Mode on Selection of Resistant Coliform Bacteria in Nursery Pigs.

    Science.gov (United States)

    Græsbøll, Kaare; Damborg, Peter; Mellerup, Anders; Herrero-Fresno, Ana; Larsen, Inge; Holm, Anders; Nielsen, Jens Peter; Christiansen, Lasse Engbo; Angen, Øystein; Ahmed, Shahana; Folkesson, Anders; Olsen, John Elmerdahl

    2017-06-15

    This study describes the results of a randomized clinical trial investigating the effect of oxytetracycline treatment dose and mode of administration on the selection of antibiotic-resistant coliform bacteria in fecal samples from nursery pigs. Nursery pigs (pigs of 4 to 7 weeks of age) in five pig herds were treated with oxytetracycline for Lawsonia intracellularis -induced diarrhea. Each group was randomly allocated to one of five treatment groups: oral flock treatment with a (i) high (20 mg/kg of body weight), (ii) medium (10 mg/kg), or (iii) low (5 mg/kg) dose, (iv) oral pen-wise (small-group) treatment (10 mg/kg), and (v) individual intramuscular injection treatment (10 mg/kg). All groups were treated once a day for 5 days. In all groups, treatment caused a rise in the numbers and proportions of tetracycline-resistant coliform bacteria right after treatment, followed by a significant drop by the time that the pigs left the nursery unit. The counts and proportions of tetracycline-resistant coliforms did not vary significantly between treatment groups, except immediately after treatment, when the highest treatment dose resulted in the highest number of resistant coliforms. A control group treated with tiamulin did not show significant changes in the numbers or proportions of tetracycline-resistant coliforms. Selection for tetracycline-resistant coliforms was significantly correlated to selection for ampicillin- and sulfonamide-resistant strains but not to selection for cefotaxime-resistant strains. In conclusion, the difference in the dose of oxytetracycline and the way in which the drug was applied did not cause significantly different levels of selection of tetracycline-resistant coliform bacteria under the conditions tested. IMPORTANCE Antimicrobial resistance is a global threat to human health. Treatment of livestock with antimicrobials has a direct impact on this problem, and there is a need to improve the ways that we use antimicrobials in livestock

  15. Selecting treatment for patients with malignant epidural spinal cord compression-does age matter?: results from a randomized clinical trial.

    Science.gov (United States)

    Chi, John H; Gokaslan, Ziya; McCormick, Paul; Tibbs, Phillip A; Kryscio, Richard J; Patchell, Roy A

    2009-03-01

    Randomized clinical trial. OBJECTIVE.: To determine if age affects outcomes from differing treatments in patients with spinal metastases. Recently, class I data were published supporting surgery with radiation over radiation alone for patients with malignant epidural spinal cord compression (MESCC). However, the criteria to properly select candidates for surgery remains controversial and few independent variables which predict success after treatment have been identified. Data for this study was obtained in a randomized clinical trial comparing surgery versus radiation for MESCC. Hazard ratios were determined for the effect of age and the interaction between age and treatment. Age estimates at which prespecified relative risks could be expected were calculated with greater than 95% confidence to suggest possible age cut points for further stratification. Multivariate models and Kaplan-Meier curves were tested using stratified cohorts for both treatment groups in the randomized trial each divided into 2 age groups. Secondary data analysis with age stratification demonstrated a strong interaction between age and treatment (hazard ratio = 1.61, P = 0.01), such that as age increases, the chances of surgery being equal to radiation alone increases. The best estimate for the age at which surgery is no longer superior to radiation alone was calculated to be between 60 and 70 years of age (95% CI), using sequential prespecified relative risk ratios. Multivariate modeling and Kaplan-Meier curves for stratified treatment groups showed that there was no difference in outcome between treatments for patients >or=65 years of age. Ambulation preservation was significantly prolonged in patients variable in predicting preservation of ambulation and survival for patients being treated for spinal metastases. Our results provide compelling evidence for the first time that particular age cut points may help in selecting patients for surgical or nonsurgical intervention based on outcome.

  16. Model averaging in the presence of structural uncertainty about treatment effects: influence on treatment decision and expected value of information.

    Science.gov (United States)

    Price, Malcolm J; Welton, Nicky J; Briggs, Andrew H; Ades, A E

    2011-01-01

    Standard approaches to estimation of Markov models with data from randomized controlled trials tend either to make a judgment about which transition(s) treatments act on, or they assume that treatment has a separate effect on every transition. An alternative is to fit a series of models that assume that treatment acts on specific transitions. Investigators can then choose among alternative models using goodness-of-fit statistics. However, structural uncertainty about any chosen parameterization will remain and this may have implications for the resulting decision and the need for further research. We describe a Bayesian approach to model estimation, and model selection. Structural uncertainty about which parameterization to use is accounted for using model averaging and we developed a formula for calculating the expected value of perfect information (EVPI) in averaged models. Marginal posterior distributions are generated for each of the cost-effectiveness parameters using Markov Chain Monte Carlo simulation in WinBUGS, or Monte-Carlo simulation in Excel (Microsoft Corp., Redmond, WA). We illustrate the approach with an example of treatments for asthma using aggregate-level data from a connected network of four treatments compared in three pair-wise randomized controlled trials. The standard errors of incremental net benefit using structured models is reduced by up to eight- or ninefold compared to the unstructured models, and the expected loss attaching to decision uncertainty by factors of several hundreds. Model averaging had considerable influence on the EVPI. Alternative structural assumptions can alter the treatment decision and have an overwhelming effect on model uncertainty and expected value of information. Structural uncertainty can be accounted for by model averaging, and the EVPI can be calculated for averaged models. Copyright © 2011 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights

  17. Patch-based generative shape model and MDL model selection for statistical analysis of archipelagos

    DEFF Research Database (Denmark)

    Ganz, Melanie; Nielsen, Mads; Brandt, Sami

    2010-01-01

    as a probability distribution of a binary image where the model is intended to facilitate sequential simulation. Our results show that a relatively simple model is able to generate structures visually similar to calcifications. Furthermore, we used the shape model as a shape prior in the statistical segmentation......We propose a statistical generative shape model for archipelago-like structures. These kind of structures occur, for instance, in medical images, where our intention is to model the appearance and shapes of calcifications in x-ray radio graphs. The generative model is constructed by (1) learning...... a patch-based dictionary for possible shapes, (2) building up a time-homogeneous Markov model to model the neighbourhood correlations between the patches, and (3) automatic selection of the model complexity by the minimum description length principle. The generative shape model is proposed...

  18. Consistency in Estimation and Model Selection of Dynamic Panel Data Models with Fixed Effects

    Directory of Open Access Journals (Sweden)

    Guangjie Li

    2015-07-01

    Full Text Available We examine the relationship between consistent parameter estimation and model selection for autoregressive panel data models with fixed effects. We find that the transformation of fixed effects proposed by Lancaster (2002 does not necessarily lead to consistent estimation of common parameters when some true exogenous regressors are excluded. We propose a data dependent way to specify the prior of the autoregressive coefficient and argue for comparing different model specifications before parameter estimation. Model selection properties of Bayes factors and Bayesian information criterion (BIC are investigated. When model uncertainty is substantial, we recommend the use of Bayesian Model Averaging to obtain point estimators with lower root mean squared errors (RMSE. We also study the implications of different levels of inclusion probabilities by simulations.

  19. Multicriteria decision group model for the selection of suppliers

    Directory of Open Access Journals (Sweden)

    Luciana Hazin Alencar

    2008-08-01

    Full Text Available Several authors have been studying group decision making over the years, which indicates how relevant it is. This paper presents a multicriteria group decision model based on ELECTRE IV and VIP Analysis methods, to those cases where there is great divergence among the decision makers. This model includes two stages. In the first, the ELECTRE IV method is applied and a collective criteria ranking is obtained. In the second, using criteria ranking, VIP Analysis is applied and the alternatives are selected. To illustrate the model, a numerical application in the context of the selection of suppliers in project management is used. The suppliers that form part of the project team have a crucial role in project management. They are involved in a network of connected activities that can jeopardize the success of the project, if they are not undertaken in an appropriate way. The question tackled is how to select service suppliers for a project on behalf of an enterprise that assists the multiple objectives of the decision-makers.Vários autores têm estudado decisão em grupo nos últimos anos, o que indica a relevância do assunto. Esse artigo apresenta um modelo multicritério de decisão em grupo baseado nos métodos ELECTRE IV e VIP Analysis, adequado aos casos em que se tem uma grande divergência entre os decisores. Esse modelo é composto por dois estágios. No primeiro, o método ELECTRE IV é aplicado e uma ordenação dos critérios é obtida. No próximo estágio, com a ordenação dos critérios, o método VIP Analysis é aplicado e as alternativas são selecionadas. Para ilustrar o modelo, uma aplicação numérica no contexto da seleção de fornecedores em projetos é realizada. Os fornecedores que fazem parte da equipe do projeto têm um papel fundamental no gerenciamento de projetos. Eles estão envolvidos em uma rede de atividades conectadas que, caso não sejam executadas de forma apropriada, podem colocar em risco o sucesso do

  20. Improving permafrost distribution modelling using feature selection algorithms

    Science.gov (United States)

    Deluigi, Nicola; Lambiel, Christophe; Kanevski, Mikhail

    2016-04-01

    The availability of an increasing number of spatial data on the occurrence of mountain permafrost allows the employment of machine learning (ML) classification algorithms for modelling the distribution of the phenomenon. One of the major problems when dealing with high-dimensional dataset is the number of input features (variables) involved. Application of ML classification algorithms to this large number of variables leads to the risk of overfitting, with the consequence of a poor generalization/prediction. For this reason, applying feature selection (FS) techniques helps simplifying the amount of factors required and improves the knowledge on adopted features and their relation with the studied phenomenon. Moreover, taking away irrelevant or redundant variables from the dataset effectively improves the quality of the ML prediction. This research deals with a comparative analysis of permafrost distribution models supported by FS variable importance assessment. The input dataset (dimension = 20-25, 10 m spatial resolution) was constructed using landcover maps, climate data and DEM derived variables (altitude, aspect, slope, terrain curvature, solar radiation, etc.). It was completed with permafrost evidences (geophysical and thermal data and rock glacier inventories) that serve as training permafrost data. Used FS algorithms informed about variables that appeared less statistically important for permafrost presence/absence. Three different algorithms were compared: Information Gain (IG), Correlation-based Feature Selection (CFS) and Random Forest (RF). IG is a filter technique that evaluates the worth of a predictor by measuring the information gain with respect to the permafrost presence/absence. Conversely, CFS is a wrapper technique that evaluates the worth of a subset of predictors by considering the individual predictive ability of each variable along with the degree of redundancy between them. Finally, RF is a ML algorithm that performs FS as part of its

  1. Impact of periodic selective mebendazole treatment on soil-transmitted helminth infections in Cuban schoolchildren.

    NARCIS (Netherlands)

    van der Werff, S.D.; Vereecken, K.; van der Laan, K.; Campos Ponce, M.; Junco Diaz, R.; Nunez, F.A.; Rojas Rivero, L.; Bonet Gorbea, M.; Polman, K.

    2014-01-01

    Objective: To evaluate the impact of periodic selective treatment with 500 mg mebendazole on soil-transmitted helminth (STH) infections in Cuban schoolchildren. Methods: We followed up a cohort of 268 STH-positive schoolchildren, aged 5-14 years at baseline, at six-month intervals for two years and

  2. Mesquite removal and mulching treatment impacts on herbage production and selected soil chemical properties

    Science.gov (United States)

    Stacy Pease; Peter F. Ffolliott; Leonard F. DeBano; Gerald J. Gottfried

    2003-01-01

    Determining the effects of mesquite (Prosopis velutina) overstory removal, posttreatment control of sprouting, and mulching treatments on herbage production (standing biomass) and selected soil chemical properties on the Santa Rita Experimental Range were the objectives of this study. Mesquite control consisted of complete overstory removals with and without the...

  3. Xamoterol, a new selective beta-1-adrenoceptor partial agonist, in the treatment of postural hypotension

    DEFF Research Database (Denmark)

    Mehlsen, J; Trap-Jensen, J

    1986-01-01

    Three patients severely disabled from postural hypotension were treated with xamoterol, a selective beta-1-adrenoceptor antagonist with a high degree of partial agonist activity. Oral treatment (200 mg b.i.d.) was chosen on the basis of the effects of acute intravenous administration of xamoterol...

  4. [Selection of Suitable Microalgal Species for Sorption of Uranium in Radioactive Wastewater Treatment].

    Science.gov (United States)

    Li, Xin; Hu, Hong-ying; Yu, Jun-yi; Zhao, Wen-yu

    2016-05-15

    The amount of radioactive wastewater discharge was increasing year by year, with the quick development of nuclear industry. Therefore, the proper treatment and disposal of radioactive wastewater are essentially important for environmental safety and human health. Microalgal biosorption of nuclide has drawn much attention in the area of radioactive wastewater treatment recently, and the selection of a proper microalgal species for uranium biosorption is the basis for the research and application of this technology. The selection principle was set up from the view of practical application, and 11 species of microalgae were prepared for the selection work. Scenedesmus sp. LX1 has the highest biosorption capacity of 40.7 mg · g⁻¹ for uranium; and its biomass production in mBG11 medium (simulating the nitrogen and phosphorus limits in the first-class A discharge standard of pollutants for municipal wastewater treatment plant) was 0.32 g · L⁻¹, which was relatively high among the 11 microalgal species; when grown into stable phase it also showed a good precipitation capability with the precipitation ratio of 45.3%. Above all, in our selection range of the 11 microalgal species, Scenedesmus sp. LX1 could be considered as the suitable species for uranium biosorption in radioactive wastewater treatment.

  5. Threat Related Selective Attention Predicts Treatment Success in Childhood Anxiety Disorders

    Science.gov (United States)

    Legerstee, Jeroen S.; Tulen, Joke H. M.; Kallen, Victor L.; Dieleman, Gwen C.; Treffers, Philip D. A.; Verhulst, Frank C.; Utens, Elisabeth M. W. J.

    2009-01-01

    Threat-related selective attention was found to predict the success of the treatment of childhood anxiety disorders through administering a pictorial dot-probe task to 131 children with anxiety disorders prior to cognitive behavioral therapy. The diagnostic status of the subjects was evaluated with a semistructured clinical interview at both pre-…

  6. The discovery of potent and selective kynurenine 3-monooxygenase inhibitors for the treatment of acute pancreatitis.

    Science.gov (United States)

    Liddle, John; Beaufils, Benjamin; Binnie, Margaret; Bouillot, Anne; Denis, Alexis A; Hann, Michael M; Haslam, Carl P; Holmes, Duncan S; Hutchinson, Jon P; Kranz, Michael; McBride, Andrew; Mirguet, Olivier; Mole, Damian J; Mowat, Christopher G; Pal, Sandeep; Rowland, Paul; Trottet, Lionel; Uings, Iain J; Walker, Ann L; Webster, Scott P

    2017-05-01

    A series of potent, competitive and highly selective kynurenine monooxygenase inhibitors have been discovered via a substrate-based approach for the treatment of acute pancreatitis. The lead compound demonstrated good cellular potency and clear pharmacodynamic activity in vivo. Copyright © 2017 Elsevier Ltd. All rights reserved.

  7. Effects of Behavioral Skills Training on Parental Treatment of Children's Food Selectivity

    Science.gov (United States)

    Seiverling, Laura; Williams, Keith; Sturmey, Peter; Hart, Sadie

    2012-01-01

    We used behavioral skills training to teach parents of 3 children with autism spectrum disorder and food selectivity to conduct a home-based treatment package that consisted of taste exposure, escape extinction, and fading. Parent performance following training improved during both taste sessions and probe meals and was reflected in increases in…

  8. Selective Mutism: A Team Approach to Assessment and Treatment in the School Setting

    Science.gov (United States)

    Ponzurick, Joan M.

    2012-01-01

    The school nurse plays a pivotal role in the assessment and treatment of selective mutism (SM), a rare disorder found in elementary school children. Due to anxiety, children with SM do not speak in uncomfortable situations, primarily the school setting. Diagnosis of SM is often missed in the formative years because the child does speak at home.…

  9. Selection and utilization of assessment instruments in substance abuse treatment trials: the National Drug Abuse Treatment Clinical Trials Network experience

    Directory of Open Access Journals (Sweden)

    Rosa C

    2012-07-01

    Full Text Available Carmen Rosa, Udi Ghitza, Betty TaiCenter for the Clinical Trials Network, National Institute on Drug Abuse, Bethesda, MD, USAAbstract: Based on recommendations from a US Institute of Medicine report, the National Institute on Drug Abuse established the National Drug Abuse Treatment Clinical Trials Network (CTN in 1999, to accelerate the translation of science-based addiction treatment research into community-based practice, and to improve the quality of addiction treatment, using science as the vehicle. One of the CTN's primary tasks is to serve as a platform to forge bi-directional communications and collaborations between providers and scientists, to enhance the relevance of research, which generates empirical results that impact practice. Among many obstacles in moving research into real-world settings, this commentary mainly describes challenges and iterative experiences in regard to how the CTN develops its research protocols, with focus on how the CTN study teams select and utilize assessment instruments, which can reasonably balance the interests of both research scientists and practicing providers when applied in CTN trials. This commentary also discusses the process by which the CTN further selects a core set of common assessment instruments that may be applied across all trials, to allow easier cross-study analyses of comparable data.Keywords: addiction, assessment, drug abuse treatment, drug dependence, NIDA Clinical Trials Network, substance use disorder

  10. Surrogate formulations for thermal treatment of low-level mixed waste, Part II: Selected mixed waste treatment project waste streams

    International Nuclear Information System (INIS)

    Bostick, W.D.; Hoffmann, D.P.; Chiang, J.M.; Hermes, W.H.; Gibson, L.V. Jr.; Richmond, A.A.; Mayberry, J.; Frazier, G.

    1994-01-01

    This report summarizes the formulation of surrogate waste packages, representing the major bulk constituent compositions for 12 waste stream classifications selected by the US DOE Mixed Waste Treatment Program. These waste groupings include: neutral aqueous wastes; aqueous halogenated organic liquids; ash; high organic content sludges; adsorbed aqueous and organic liquids; cement sludges, ashes, and solids; chloride; sulfate, and nitrate salts; organic matrix solids; heterogeneous debris; bulk combustibles; lab packs; and lead shapes. Insofar as possible, formulation of surrogate waste packages are referenced to authentic wastes in inventory within the DOE; however, the surrogate waste packages are intended to represent generic treatability group compositions. The intent is to specify a nonradiological synthetic mixture, with a minimal number of readily available components, that can be used to represent the significant challenges anticipated for treatment of the specified waste class. Performance testing and evaluation with use of a consistent series of surrogate wastes will provide a means for the initial assessment (and intercomparability) of candidate treatment technology applicability and performance. Originally the surrogate wastes were intended for use with emerging thermal treatment systems, but use may be extended to select nonthermal systems as well

  11. Surrogate formulations for thermal treatment of low-level mixed waste, Part II: Selected mixed waste treatment project waste streams

    Energy Technology Data Exchange (ETDEWEB)

    Bostick, W.D.; Hoffmann, D.P.; Chiang, J.M.; Hermes, W.H.; Gibson, L.V. Jr.; Richmond, A.A. [Martin Marietta Energy Systems, Inc., Oak Ridge, TN (United States); Mayberry, J. [Science Applications International Corp., Idaho Falls, ID (United States); Frazier, G. [Univ. of Tennessee, Knoxville, TN (United States)

    1994-01-01

    This report summarizes the formulation of surrogate waste packages, representing the major bulk constituent compositions for 12 waste stream classifications selected by the US DOE Mixed Waste Treatment Program. These waste groupings include: neutral aqueous wastes; aqueous halogenated organic liquids; ash; high organic content sludges; adsorbed aqueous and organic liquids; cement sludges, ashes, and solids; chloride; sulfate, and nitrate salts; organic matrix solids; heterogeneous debris; bulk combustibles; lab packs; and lead shapes. Insofar as possible, formulation of surrogate waste packages are referenced to authentic wastes in inventory within the DOE; however, the surrogate waste packages are intended to represent generic treatability group compositions. The intent is to specify a nonradiological synthetic mixture, with a minimal number of readily available components, that can be used to represent the significant challenges anticipated for treatment of the specified waste class. Performance testing and evaluation with use of a consistent series of surrogate wastes will provide a means for the initial assessment (and intercomparability) of candidate treatment technology applicability and performance. Originally the surrogate wastes were intended for use with emerging thermal treatment systems, but use may be extended to select nonthermal systems as well.

  12. Multiphysics modeling of selective laser sintering/melting

    Science.gov (United States)

    Ganeriwala, Rishi Kumar

    A significant percentage of total global employment is due to the manufacturing industry. However, manufacturing also accounts for nearly 20% of total energy usage in the United States according to the EIA. In fact, manufacturing accounted for 90% of industrial energy consumption and 84% of industry carbon dioxide emissions in 2002. Clearly, advances in manufacturing technology and efficiency are necessary to curb emissions and help society as a whole. Additive manufacturing (AM) refers to a relatively recent group of manufacturing technologies whereby one can 3D print parts, which has the potential to significantly reduce waste, reconfigure the supply chain, and generally disrupt the whole manufacturing industry. Selective laser sintering/melting (SLS/SLM) is one type of AM technology with the distinct advantage of being able to 3D print metals and rapidly produce net shape parts with complicated geometries. In SLS/SLM parts are built up layer-by-layer out of powder particles, which are selectively sintered/melted via a laser. However, in order to produce defect-free parts of sufficient strength, the process parameters (laser power, scan speed, layer thickness, powder size, etc.) must be carefully optimized. Obviously, these process parameters will vary depending on material, part geometry, and desired final part characteristics. Running experiments to optimize these parameters is costly, energy intensive, and extremely material specific. Thus a computational model of this process would be highly valuable. In this work a three dimensional, reduced order, coupled discrete element - finite difference model is presented for simulating the deposition and subsequent laser heating of a layer of powder particles sitting on top of a substrate. Validation is provided and parameter studies are conducted showing the ability of this model to help determine appropriate process parameters and an optimal powder size distribution for a given material. Next, thermal stresses upon

  13. MAJOR PRINCIPLES OF EPILEPSY TREATMENT. ALGORITHM OF SELECTION OF ANTIEPILEPTIC DRUGS

    Directory of Open Access Journals (Sweden)

    K. Yu. Mukhin

    2014-01-01

    Full Text Available The authors reviewed general principles of epilepsy treatment in details as well as provided their proprietary algorithm of selection of antiepileptic drugs developed Svt. Luka's Institute of Child Neurology and Epilepsy. This algorithm is designed for general practitioners that deal with treatment of epilepsy. In the course of selection of the first antiepileptic drug, the doctor must take into consideration the age of the patient, assess their level of development, clinical manifestations of seizures, data of electroencephalography and magnetic resonance imaging. The data received allows determination of the type of seizures, supposing of the syndrome-related diagnosis, and selection of the most appropriate antiepileptic drug of first choice in each specific case. There are also recommendations for further examination of patients and monitoring of efficacy of therapy.

  14. Treatment of irregular word spelling in acquired dysgraphia: selective benefit from visual mnemonics.

    Science.gov (United States)

    Schmalzl, Laura; Nickels, Lyndsey

    2006-02-01

    In contrast to the numerous treatment studies of spoken language deficits, there have been relatively few studies concerned with the treatment of spelling disorders. Among these, there have been only a small number that have targeted specific components of the spelling process. We describe a successful single case treatment study for FME, a woman with acquired dysgraphia, which was conducted within a cognitive neuropsychological framework. Pre-treatment assessment revealed a semantic deficit, impaired access to output orthography and probable additional degradation of the actual representations within the orthographic output lexicon. The treatment study was therefore directed towards relearning spellings by strengthening, and facilitating access to, specific orthographic representations for writing. In order to maximise the functional outcome for FME, treatment was focused on high frequency, irregular words. The treatment programme was carried out in two phases, one without and one with the use of mnemonics, and the results showed a selective training effect with the mnemonics alone. Treatment benefits were item specific but long lasting, and a significant improvement in FME's spelling performance was still evident at 2 months post-treatment. The current study confirms how cognitive neuropsychological theories and methods can be successfully applied to the assessment of acquired spelling impairments, and exemplifies how treatment with carefully designed mnemonics is of benefit if the inability to retrieve orthographic representations for writing is aggravated by a semantic deficit.

  15. Hyperopt: a Python library for model selection and hyperparameter optimization

    Science.gov (United States)

    Bergstra, James; Komer, Brent; Eliasmith, Chris; Yamins, Dan; Cox, David D.

    2015-01-01

    Sequential model-based optimization (also known as Bayesian optimization) is one of the most efficient methods (per function evaluation) of function minimization. This efficiency makes it appropriate for optimizing the hyperparameters of machine learning algorithms that are slow to train. The Hyperopt library provides algorithms and parallelization infrastructure for performing hyperparameter optimization (model selection) in Python. This paper presents an introductory tutorial on the usage of the Hyperopt library, including the description of search spaces, minimization (in serial and parallel), and the analysis of the results collected in the course of minimization. This paper also gives an overview of Hyperopt-Sklearn, a software project that provides automatic algorithm configuration of the Scikit-learn machine learning library. Following Auto-Weka, we take the view that the choice of classifier and even the choice of preprocessing module can be taken together to represent a single large hyperparameter optimization problem. We use Hyperopt to define a search space that encompasses many standard components (e.g. SVM, RF, KNN, PCA, TFIDF) and common patterns of composing them together. We demonstrate, using search algorithms in Hyperopt and standard benchmarking data sets (MNIST, 20-newsgroups, convex shapes), that searching this space is practical and effective. In particular, we improve on best-known scores for the model space for both MNIST and convex shapes. The paper closes with some discussion of ongoing and future work.

  16. Estimating a dynamic model of sex selection in China.

    Science.gov (United States)

    Ebenstein, Avraham

    2011-05-01

    High ratios of males to females in China, which have historically concerned researchers (Sen 1990), have increased in the wake of China's one-child policy, which began in 1979. Chinese policymakers are currently attempting to correct the imbalance in the sex ratio through initiatives that provide financial compensation to parents with daughters. Other scholars have advocated a relaxation of the one-child policy to allow more parents to have a son without engaging in sex selection. In this article, I present a model of fertility choice when parents have access to a sex-selection technology and face a mandated fertility limit. By exploiting variation in fines levied in China for unsanctioned births, I estimate the relative price of a son and daughter for mothers observed in China's census data (1982-2000). I find that a couple's first son is worth 1.42 years of income more than a first daughter, and the premium is highest among less-educated mothers and families engaged in agriculture. Simulations indicate that a subsidy of 1 year of income to families without a son would reduce the number of "missing girls" by 67% but impose an annual cost of 1.8% of Chinese gross domestic product (GDP). Alternatively, a three-child policy would reduce the number of "missing girls" by 56% but increase the fertility rate by 35%.

  17. Model catalysis by size-selected cluster deposition

    Energy Technology Data Exchange (ETDEWEB)

    Anderson, Scott [Univ. of Utah, Salt Lake City, UT (United States)

    2015-11-20

    This report summarizes the accomplishments during the last four years of the subject grant. Results are presented for experiments in which size-selected model catalysts were studied under surface science and aqueous electrochemical conditions. Strong effects of cluster size were found, and by correlating the size effects with size-dependent physical properties of the samples measured by surface science methods, it was possible to deduce mechanistic insights, such as the factors that control the rate-limiting step in the reactions. Results are presented for CO oxidation, CO binding energetics and geometries, and electronic effects under surface science conditions, and for the electrochemical oxygen reduction reaction, ethanol oxidation reaction, and for oxidation of carbon by water.

  18. Analytical Modelling Of Milling For Tool Design And Selection

    Science.gov (United States)

    Fontaine, M.; Devillez, A.; Dudzinski, D.

    2007-05-01

    This paper presents an efficient analytical model which allows to simulate a large panel of milling operations. A geometrical description of common end mills and of their engagement in the workpiece material is proposed. The internal radius of the rounded part of the tool envelope is used to define the considered type of mill. The cutting edge position is described for a constant lead helix and for a constant local helix angle. A thermomechanical approach of oblique cutting is applied to predict forces acting on the tool and these results are compared with experimental data obtained from milling tests on a 42CrMo4 steel for three classical types of mills. The influence of some tool's geometrical parameters on predicted cutting forces is presented in order to propose optimisation criteria for design and selection of cutting tools.

  19. Analytical Modelling Of Milling For Tool Design And Selection

    International Nuclear Information System (INIS)

    Fontaine, M.; Devillez, A.; Dudzinski, D.

    2007-01-01

    This paper presents an efficient analytical model which allows to simulate a large panel of milling operations. A geometrical description of common end mills and of their engagement in the workpiece material is proposed. The internal radius of the rounded part of the tool envelope is used to define the considered type of mill. The cutting edge position is described for a constant lead helix and for a constant local helix angle. A thermomechanical approach of oblique cutting is applied to predict forces acting on the tool and these results are compared with experimental data obtained from milling tests on a 42CrMo4 steel for three classical types of mills. The influence of some tool's geometrical parameters on predicted cutting forces is presented in order to propose optimisation criteria for design and selection of cutting tools

  20. Evaluation of selected neutralizing agents for the treatment of uranium tailings leachates. Laboratory progress report

    International Nuclear Information System (INIS)

    Sherwood, D.R.; Serne, R.J.

    1983-02-01

    Laboratory experiments were conducted to evaluate the performance of selected neutralizing agents for the treatment of uranium tailings solutions. Highly acidic tailings solutions (pH 3 ) reagent grade; Calcium hydroxide [Ca(OH) 2 ] reagent grade; Magnesium oxide (MgO) reagent grade; Sodium carbonate (Na 2 CO 3 ) reagent grade; and Sodium hydroxide (NaOH) reagent grade. Evaluation of the effectiveness for the treatment of uranium tailings solutions for the selected neutralizing agents under controlled laboratory conditions was based on three criteria. The criteria are: (1) treated effluent water quality, (2) neutralized sludge handling and hydraulic properties, and (3) reagent costs and acid neutralizing efficiency. On the basis of these limited laboratory results calcium hydroxide or its dehydrated form CaO (lime) appears to be the most effective option for treatment of uranium tailings solutions

  1. An integrated knowledge-based and optimization tool for the sustainable selection of wastewater treatment process concepts

    DEFF Research Database (Denmark)

    Castillo, A.; Cheali, Peam; Gómez, V.

    2016-01-01

    The increasing demand on wastewater treatment plants (WWTPs) has involved an interest in improving the alternative treatment selection process. In this study, an integrated framework including an intelligent knowledge-based system and superstructure-based optimization has been developed and applied...... to a real case study. Hence, a multi-criteria analysis together with mathematical models is applied to generate a ranked short-list of feasible treatments for three different scenarios. Finally, the uncertainty analysis performed allows for increasing the quality and robustness of the decisions considering...... variation in influent concentrations. For the case study application, the expert system identifies 5 potential process technologies and, using this input, the superstructure identifies membrane bioreactors as the optimal and robust solution under influent uncertainties and tighter effluent limits. A mutual...

  2. Influence of selecting secondary settling tank sub-models on the calibration of WWTP models – A global sensitivity analysis using BSM2

    DEFF Research Database (Denmark)

    Ramin, Elham; Flores Alsina, Xavier; Sin, Gürkan

    2014-01-01

    This study investigates the sensitivity of wastewater treatment plant (WWTP) model performance to the selection of one-dimensional secondary settling tanks (1-D SST) models with first-order and second-order mathematical structures. We performed a global sensitivity analysis (GSA) on the benchmark......, the settling parameters were found to be as influential as the biokinetic parameters on the uncertainty of WWTP model predictions, particularly for biogas production and treated water quality. However, the sensitivity measures were found to be dependent on the 1-D SST models selected. Accordingly, we suggest...... a different optimum parameter selection for the calibration of WWTP models when either of the 1-D SST models is used. Using first-order models, the calibration should give equal importance to the adjustment of the hindered settling and slow settling parameter values. The adjusted hindered settling parameters...

  3. Selection of hydrologic modeling approaches for climate change assessment: A comparison of model scale and structures

    Science.gov (United States)

    Surfleet, Christopher G.; Tullos, Desirèe; Chang, Heejun; Jung, Il-Won

    2012-09-01

    SummaryA wide variety of approaches to hydrologic (rainfall-runoff) modeling of river basins confounds our ability to select, develop, and interpret models, particularly in the evaluation of prediction uncertainty associated with climate change assessment. To inform the model selection process, we characterized and compared three structurally-distinct approaches and spatial scales of parameterization to modeling catchment hydrology: a large-scale approach (using the VIC model; 671,000 km2 area), a basin-scale approach (using the PRMS model; 29,700 km2 area), and a site-specific approach (the GSFLOW model; 4700 km2 area) forced by the same future climate estimates. For each approach, we present measures of fit to historic observations and predictions of future response, as well as estimates of model parameter uncertainty, when available. While the site-specific approach generally had the best fit to historic measurements, the performance of the model approaches varied. The site-specific approach generated the best fit at unregulated sites, the large scale approach performed best just downstream of flood control projects, and model performance varied at the farthest downstream sites where streamflow regulation is mitigated to some extent by unregulated tributaries and water diversions. These results illustrate how selection of a modeling approach and interpretation of climate change projections require (a) appropriate parameterization of the models for climate and hydrologic processes governing runoff generation in the area under study, (b) understanding and justifying the assumptions and limitations of the model, and (c) estimates of uncertainty associated with the modeling approach.

  4. Evaluating experimental design for soil-plant model selection with Bayesian model averaging

    Science.gov (United States)

    Wöhling, Thomas; Geiges, Andreas; Nowak, Wolfgang; Gayler, Sebastian

    2013-04-01

    The objective selection of appropriate models for realistic simulations of coupled soil-plant processes is a challenging task since the processes are complex, not fully understood at larger scales, and highly non-linear. Also, comprehensive data sets are scarce, and measurements are uncertain. In the past decades, a variety of different models have been developed that exhibit a wide range of complexity regarding their approximation of processes in the coupled model compartments. We present a method for evaluating experimental design for maximum confidence in the model selection task. The method considers uncertainty in parameters, measurements and model structures. Advancing the ideas behind Bayesian Model Averaging (BMA), the model weights in BMA are perceived as uncertain quantities with assigned probability distributions that narrow down as more data are made available. This allows assessing the power of different data types, data densities and data locations in identifying the best model structure from among a suite of plausible models. The models considered in this study are the crop models CERES, SUCROS, GECROS and SPASS, which are coupled to identical routines for simulating soil processes within the modelling framework Expert-N. The four models considerably differ in the degree of detail at which crop growth and root water uptake are represented. Monte-Carlo simulations were conducted for each of these models considering their uncertainty in soil hydraulic properties and selected crop model parameters. The models were then conditioned on field measurements of soil moisture, leaf-area index (LAI), and evapotranspiration rates (from eddy-covariance measurements) during a vegetation period of winter wheat at the Nellingen site in Southwestern Germany. Following our new method, we derived the BMA model weights (and their distributions) when using all data or different subsets thereof. We discuss to which degree the posterior BMA mean outperformed the prior BMA

  5. MoDOT pavement preservation research program volume VI, pavement treatment trigger tables/decision trees and treatment candidate selection process.

    Science.gov (United States)

    2015-10-01

    The objective of Task 5 was the development of pavement treatment trigger tables and the treatment candidate selection process. : The input to the trigger tables entails such factors as an overall condition indicator, smoothness, individual distress ...

  6. Treatment of selective mutism based on cognitive behavioural therapy, psychopharmacology and combination therapy - a systematic review.

    Science.gov (United States)

    Østergaard, Kasper Rud

    2018-02-15

    Selective mutism (SM) is a debilitating childhood anxiety disorder characterized by a persistent lack of speech in certain social settings and is considered hard to treat. Cognitive behavioral therapy (CBT) and pharmacological treatments are the best described treatments in the literature. To test whether there is evidence on treatment based on CBT, medication or a combination of these. Systematic and critical review of the literature on CBT and/or pharmacological treatments of SM. Literature was sought on PubMed, Embase and Psycinfo in March 2017. Of the included studies, six examined CBT, seven pharmacologic treatment and two a combination of these. Using CBT 53/60 children improved symptomatically whilst respectively 55/67 and 6/7 improved using pharmacologic- and combination-treatment. Pharmacologic treatment and especially CBT showed promising results supported by some degree of evidence, which combination treatment lacks. Yet small numbers, few RCTs, heterogeneous study designs, lack of consistent measures, short treatment and follow-up periods, generally limits the evidence. This needs focus in future research.

  7. Hierarchical models in ecology: confidence intervals, hypothesis testing, and model selection using data cloning.

    Science.gov (United States)

    Ponciano, José Miguel; Taper, Mark L; Dennis, Brian; Lele, Subhash R

    2009-02-01

    Hierarchical statistical models are increasingly being used to describe complex ecological processes. The data cloning (DC) method is a new general technique that uses Markov chain Monte Carlo (MCMC) algorithms to compute maximum likelihood (ML) estimates along with their asymptotic variance estimates for hierarchical models. Despite its generality, the method has two inferential limitations. First, it only provides Wald-type confidence intervals, known to be inaccurate in small samples. Second, it only yields ML parameter estimates, but not the maximized likelihood values used for profile likelihood intervals, likelihood ratio hypothesis tests, and information-theoretic model selection. Here we describe how to overcome these inferential limitations with a computationally efficient method for calculating likelihood ratios via data cloning. The ability to calculate likelihood ratios allows one to do hypothesis tests, construct accurate confidence intervals and undertake information-based model selection with hierarchical models in a frequentist context. To demonstrate the use of these tools with complex ecological models, we reanalyze part of Gause's classic Paramecium data with state-space population models containing both environmental noise and sampling error. The analysis results include improved confidence intervals for parameters, a hypothesis test of laboratory replication, and a comparison of the Beverton-Holt and the Ricker growth forms based on a model selection index.

  8. Recurrence predictive models for patients with hepatocellular carcinoma after radiofrequency ablation using support vector machines with feature selection methods.

    Science.gov (United States)

    Liang, Ja-Der; Ping, Xiao-Ou; Tseng, Yi-Ju; Huang, Guan-Tarn; Lai, Feipei; Yang, Pei-Ming

    2014-12-01

    Recurrence of hepatocellular carcinoma (HCC) is an important issue despite effective treatments with tumor eradication. Identification of patients who are at high risk for recurrence may provide more efficacious screening and detection of tumor recurrence. The aim of this study was to develop recurrence predictive models for HCC patients who received radiofrequency ablation (RFA) treatment. From January 2007 to December 2009, 83 newly diagnosed HCC patients receiving RFA as their first treatment were enrolled. Five feature selection methods including genetic algorithm (GA), simulated annealing (SA) algorithm, random forests (RF) and hybrid methods (GA+RF and SA+RF) were utilized for selecting an important subset of features from a total of 16 clinical features. These feature selection methods were combined with support vector machine (SVM) for developing predictive models with better performance. Five-fold cross-validation was used to train and test SVM models. The developed SVM-based predictive models with hybrid feature selection methods and 5-fold cross-validation had averages of the sensitivity, specificity, accuracy, positive predictive value, negative predictive value, and area under the ROC curve as 67%, 86%, 82%, 69%, 90%, and 0.69, respectively. The SVM derived predictive model can provide suggestive high-risk recurrent patients, who should be closely followed up after complete RFA treatment. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  9. Modification of the Selectivity Properties of Tubular Ceramic Membranes after Alkaline Treatment

    Directory of Open Access Journals (Sweden)

    Patrick Dutournié

    2017-11-01

    Full Text Available This work focuses on the selectivity modification of ceramic membranes after a mild alkaline treatment. Filtration of pure salt-water solutions was carried out with commercial titania membranes before and after the treatment. After treatment, the rejection of NaF significantly decreased, while the rejection of NaCl and NaBr increased. Additionally, NaI and Na2SO4 remained close to zero. Pore size and electrical charge being almost unchanged, only significant modifications in the dielectric effects can explain this modification of selectivity. Therefore, the surface chemistry and the interaction (nature and magnitude with the solvent and with the species present in the solution appear to be modified by the alkaline treatment. This trend is also illustrated by discussing the electric and the dielectric properties that were numerically identified before and after treatment. The alkaline treatment significantly decreased the apparent dielectric constant of NaCl-water solution in the pore, highlighting the rejection of sodium chloride. Contrariwise, the modification of the surface chemistry increased the apparent dielectric constant of NaF-water solution by promoting fluoride transmission.

  10. Model Selection in the Analysis of Photoproduction Data

    Science.gov (United States)

    Landay, Justin

    2017-01-01

    Scattering experiments provide one of the most powerful and useful tools for probing matter to better understand its fundamental properties governed by the strong interaction. As the spectroscopy of the excited states of nucleons enters a new era of precision ushered in by improved experiments at Jefferson Lab and other facilities around the world, traditional partial-wave analysis methods must be adjusted accordingly. In this poster, we present a rigorous set of statistical tools and techniques that we implemented; most notably, the LASSO method, which serves for the selection of the simplest model, allowing us to avoid over fitting. In the case of establishing the spectrum of exited baryons, it avoids overpopulation of the spectrum and thus the occurrence of false-positives. This is a prerequisite to reliably compare theories like lattice QCD or quark models to experiments. Here, we demonstrate the principle by simultaneously fitting three observables in neutral pion photo-production, such as the differential cross section, beam asymmetry and target polarization across thousands of data points. Other authors include Michael Doring, Bin Hu, and Raquel Molina.

  11. Economic considerations and patients' preferences affect treatment selection for patients with rheumatoid arthritis: a discrete choice experiment among European rheumatologists.

    Science.gov (United States)

    Hifinger, M; Hiligsmann, M; Ramiro, S; Watson, V; Severens, J L; Fautrel, B; Uhlig, T; van Vollenhoven, R; Jacques, P; Detert, J; Canas da Silva, J; Scirè, C A; Berghea, F; Carmona, L; Péntek, M; Keat, A; Boonen, A

    2017-01-01

    To compare the value that rheumatologists across Europe attach to patients' preferences and economic aspects when choosing treatments for patients with rheumatoid arthritis. In a discrete choice experiment, European rheumatologists chose between two hypothetical drug treatments for a patient with moderate disease activity. Treatments differed in five attributes: efficacy (improvement and achieved state on disease activity), safety (probability of serious adverse events), patient's preference (level of agreement), medication costs and cost-effectiveness (incremental cost-effectiveness ratio (ICER)). A Bayesian efficient design defined 14 choice sets, and a random parameter logit model was used to estimate relative preferences for rheumatologists across countries. Cluster analyses and latent class models were applied to understand preference patterns across countries and among individual rheumatologists. Responses of 559 rheumatologists from 12 European countries were included in the analysis (49% females, mean age 48 years). In all countries, efficacy dominated treatment decisions followed by economic considerations and patients' preferences. Across countries, rheumatologists avoided selecting a treatment that patients disliked. Latent class models revealed four respondent profiles: one traded off all attributes except safety, and the remaining three classes disregarded ICER. Among individual rheumatologists, 57% disregarded ICER and these were more likely from Italy, Romania, Portugal or France, whereas 43% disregarded uncommon/rare side effects and were more likely from Belgium, Germany, Hungary, the Netherlands, Norway, Spain, Sweden or UK. Overall, European rheumatologists are willing to trade between treatment efficacy, patients' treatment preferences and economic considerations. However, the degree of trade-off differs between countries and among individuals. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted

  12. Estimating the Optimal Personalized Treatment Strategy Based on Selected Variables to Prolong Survival via Random Survival Forest with Weighted Bootstrap.

    Science.gov (United States)

    Shen, Jincheng; Wang, Lu; Daignault, Stephanie; Spratt, Daniel E; Morgan, Todd M; Taylor, Jeremy M G

    2018-01-01

    A personalized treatment policy requires defining the optimal treatment for each patient based on their clinical and other characteristics. Here we consider a commonly encountered situation in practice, when analyzing data from observational cohorts, that there are auxiliary variables which affect both the treatment and the outcome, yet these variables are not of primary interest to be included in a generalizable treatment strategy. Furthermore, there is not enough prior knowledge of the effect of the treatments or of the importance of the covariates for us to explicitly specify the dependency between the outcome and different covariates, thus we choose a model that is flexible enough to accommodate the possibly complex association of the outcome on the covariates. We consider observational studies with a survival outcome and propose to use Random Survival Forest with Weighted Bootstrap (RSFWB) to model the counterfactual outcomes while marginalizing over the auxiliary covariates. By maximizing the restricted mean survival time, we estimate the optimal regime for a target population based on a selected set of covariates. Simulation studies illustrate that the proposed method performs reliably across a range of different scenarios. We further apply RSFWB to a prostate cancer study.

  13. Verification Techniques for Parameter Selection and Bayesian Model Calibration Presented for an HIV Model

    Science.gov (United States)

    Wentworth, Mami Tonoe

    Uncertainty quantification plays an important role when making predictive estimates of model responses. In this context, uncertainty quantification is defined as quantifying and reducing uncertainties, and the objective is to quantify uncertainties in parameter, model and measurements, and propagate the uncertainties through the model, so that one can make a predictive estimate with quantified uncertainties. Two of the aspects of uncertainty quantification that must be performed prior to propagating uncertainties are model calibration and parameter selection. There are several efficient techniques for these processes; however, the accuracy of these methods are often not verified. This is the motivation for our work, and in this dissertation, we present and illustrate verification frameworks for model calibration and parameter selection in the context of biological and physical models. First, HIV models, developed and improved by [2, 3, 8], describe the viral infection dynamics of an HIV disease. These are also used to make predictive estimates of viral loads and T-cell counts and to construct an optimal control for drug therapy. Estimating input parameters is an essential step prior to uncertainty quantification. However, not all the parameters are identifiable, implying that they cannot be uniquely determined by the observations. These unidentifiable parameters can be partially removed by performing parameter selection, a process in which parameters that have minimal impacts on the model response are determined. We provide verification techniques for Bayesian model calibration and parameter selection for an HIV model. As an example of a physical model, we employ a heat model with experimental measurements presented in [10]. A steady-state heat model represents a prototypical behavior for heat conduction and diffusion process involved in a thermal-hydraulic model, which is a part of nuclear reactor models. We employ this simple heat model to illustrate verification

  14. Enhanced selection of high affinity DNA-reactive B cells following cyclophosphamide treatment in mice.

    Directory of Open Access Journals (Sweden)

    Daisuke Kawabata

    2010-01-01

    Full Text Available A major goal for the treatment of patients with systemic lupus erythematosus with cytotoxic therapies is the induction of long-term remission. There is, however, a paucity of information concerning the effects of these therapies on the reconstituting B cell repertoire. Since there is recent evidence suggesting that B cell lymphopenia might attenuate negative selection of autoreactive B cells, we elected to investigate the effects of cyclophosphamide on the selection of the re-emerging B cell repertoire in wild type mice and transgenic mice that express the H chain of an anti-DNA antibody. The reconstituting B cell repertoire in wild type mice contained an increased frequency of DNA-reactive B cells; in heavy chain transgenic mice, the reconstituting repertoire was characterized by an increased frequency of mature, high affinity DNA-reactive B cells and the mice expressed increased levels of serum anti-DNA antibodies. This coincided with a significant increase in serum levels of BAFF. Treatment of transgene-expressing mice with a BAFF blocking agent or with DNase to reduce exposure to autoantigen limited the expansion of high affinity DNA-reactive B cells during B cell reconstitution. These studies suggest that during B cell reconstitution, not only is negative selection of high affinity DNA-reactive B cells impaired by increased BAFF, but also that B cells escaping negative selection are positively selected by autoantigen. There are significant implications for therapy.

  15. Elucidating selection processes for antibiotic resistance in sewage treatment plants using metagenomics.

    Science.gov (United States)

    Bengtsson-Palme, Johan; Hammarén, Rickard; Pal, Chandan; Östman, Marcus; Björlenius, Berndt; Flach, Carl-Fredrik; Fick, Jerker; Kristiansson, Erik; Tysklind, Mats; Larsson, D G Joakim

    2016-12-01

    Sewage treatment plants (STPs) have repeatedly been suggested as "hotspots" for the emergence and dissemination of antibiotic-resistant bacteria. A critical question still unanswered is if selection pressures within STPs, caused by residual antibiotics or other co-selective agents, are sufficient to specifically promote resistance. To address this, we employed shotgun metagenomic sequencing of samples from different steps of the treatment process in three Swedish STPs. In parallel, concentrations of selected antibiotics, biocides and metals were analyzed. We found that concentrations of tetracycline and ciprofloxacin in the influent were above predicted concentrations for resistance selection, however, there was no consistent enrichment of resistance genes to any particular class of antibiotics in the STPs, neither for biocide and metal resistance genes. The most substantial change of the bacterial communities compared to human feces occurred already in the sewage pipes, manifested by a strong shift from obligate to facultative anaerobes. Through the treatment process, resistance genes against antibiotics, biocides and metals were not reduced to the same extent as fecal bacteria. The OXA-48 gene was consistently enriched in surplus and digested sludge. We find this worrying as OXA-48, still rare in Swedish clinical isolates, provides resistance to carbapenems, one of our most critically important classes of antibiotics. Taken together, metagenomics analyses did not provide clear support for specific antibiotic resistance selection. However, stronger selective forces affecting gross taxonomic composition, and with that resistance gene abundances, limit interpretability. Comprehensive analyses of resistant/non-resistant strains within relevant species are therefore warranted. Copyright © 2016 Elsevier B.V. All rights reserved.

  16. Flame treatment for the selective wetting and separation of PVC and PET

    International Nuclear Information System (INIS)

    Pascoe, R.D.; O'Connell, B.

    2003-01-01

    Flame treatment has been used for many years to modify the surface of plastics to allow coatings to be added. The effect of the treatment is to produce hydrophilic species on the surface of the plastic making it water-wettable. The production of hydrophilic plastic surfaces is also required in the selective separation of plastics by froth flotation. For the process to be selective one plastic must be rendered hydrophilic while another remains hydrophobic. In this study the potential for separation of PVC and PET has been investigated. Flame treatment was shown to be very effective in producing a hydrophilic surface on both plastics, although the process was not selective under the conditions investigated. Raising the temperature of the plastics above their softening point produced a hydrophobic recovery. As the softening point of PVC was significantly lower than for PET it was possible to produce a significant difference in hydrophobicity, as judged using contact angle measurement. When immersed in water the contact angle of the PVC was found to be strongly dependent on the pH. Good separation efficiency of the two plastics was achieved by froth flotation from pH 4 to 9. One particular advantage of the technique is that no chemical reagents may be required in the flotation stage. The practicalities of designing a flake treatment system however have to be addressed before considering it to be a viable industrial process

  17. A simple model of group selection that cannot be analyzed with inclusive fitness

    NARCIS (Netherlands)

    van Veelen, M.; Luo, S.; Simon, B.

    2014-01-01

    A widespread claim in evolutionary theory is that every group selection model can be recast in terms of inclusive fitness. Although there are interesting classes of group selection models for which this is possible, we show that it is not true in general. With a simple set of group selection models,

  18. Personalized neuromusculoskeletal modeling to improve treatment of mobility impairments: a perspective from European research sites

    Directory of Open Access Journals (Sweden)

    Fregly Benjamin J

    2012-03-01

    Full Text Available Abstract Mobility impairments due to injury or disease have a significant impact on quality of life. Consequently, development of effective treatments to restore or replace lost function is an important societal challenge. In current clinical practice, a treatment plan is often selected from a standard menu of options rather than customized to the unique characteristics of the patient. Furthermore, the treatment selection process is normally based on subjective clinical experience rather than objective prediction of post-treatment function. The net result is treatment methods that are less effective than desired at restoring lost function. This paper discusses the possible use of personalized neuromusculoskeletal computer models to improve customization, objectivity, and ultimately effectiveness of treatments for mobility impairments. The discussion is based on information gathered from academic and industrial research sites throughout Europe, and both clinical and technical aspects of personalized neuromusculoskeletal modeling are explored. On the clinical front, we discuss the purpose and process of personalized neuromusculoskeletal modeling, the application of personalized models to clinical problems, and gaps in clinical application. On the technical front, we discuss current capabilities of personalized neuromusculoskeletal models along with technical gaps that limit future clinical application. We conclude by summarizing recommendations for future research efforts that would allow personalized neuromusculoskeletal models to make the greatest impact possible on treatment design for mobility impairments.

  19. Acute and chronic effects of selective serotonin reuptake inhibitor treatment on fear conditioning: implications for underlying fear circuits.

    Science.gov (United States)

    Burghardt, N S; Bauer, E P

    2013-09-05

    Selective serotonin reuptake inhibitors (SSRIs) are widely used for the treatment of a spectrum of anxiety disorders, yet paradoxically they may increase symptoms of anxiety when treatment is first initiated. Despite extensive research over the past 30 years focused on SSRI treatment, the precise mechanisms by which SSRIs exert these opposing acute and chronic effects on anxiety remain unknown. By testing the behavioral effects of SSRI treatment on Pavlovian fear conditioning, a well characterized model of emotional learning, we have the opportunity to identify how SSRIs affect the functioning of specific brain regions, including the amygdala, bed nucleus of the stria terminalis (BNST) and hippocampus. In this review, we first define different stages of learning involved in cued and context fear conditioning and describe the neural circuits underlying these processes. We examine the results of numerous rodent studies investigating how acute SSRI treatment modulates fear learning and relate these effects to the known functions of serotonin in specific brain regions. With these findings, we propose a model by which acute SSRI administration, by altering neural activity in the extended amygdala and hippocampus, enhances both acquisition and expression of cued fear conditioning, but impairs the expression of contextual fear conditioning. Finally, we review the literature examining the effects of chronic SSRI treatment on fear conditioning in rodents and describe how downregulation of N-methyl-d-aspartate (NMDA) receptors in the amygdala and hippocampus may mediate the impairments in fear learning and memory that are reported. While long-term SSRI treatment effectively reduces symptoms of anxiety, their disruptive effects on fear learning should be kept in mind when combining chronic SSRI treatment and learning-based therapies, such as cognitive behavioral therapy. Copyright © 2013 IBRO. Published by Elsevier Ltd. All rights reserved.

  20. Selective HDAC inhibition by ACY-241 enhances the activity of paclitaxel in solid tumor models.

    Science.gov (United States)

    Huang, Pengyu; Almeciga-Pinto, Ingrid; Jarpe, Matthew; van Duzer, John H; Mazitschek, Ralph; Yang, Min; Jones, Simon S; Quayle, Steven N

    2017-01-10

    ACY-241 is a novel, orally available and selective histone deacetylase (HDAC) 6 inhibitor in Phase 1b clinical development in multiple myeloma (NCT 02400242). Like the structurally related drug ACY-1215 (ricolinostat), ACY-241 has the potential for a substantially reduced side effect profile versus current nonselective HDAC inhibitor drug candidates due to reduced potency against Class I HDACs while retaining the potential for anticancer effectiveness. We now show that combination treatment of xenograft models with paclitaxel and either ricolinostat or ACY-241 significantly suppresses solid tumor growth. In cell lines from multiple solid tumor lineages, combination treatment with ACY-241 and paclitaxel enhanced inhibition of proliferation and increased cell death relative to either single agent alone. Combination treatment with ACY-241 and paclitaxel also resulted in more frequent occurrence of mitotic cells with abnormal multipolar spindles and aberrant mitoses, consistent with the observed increase of aneuploid cells. At the molecular level, multipolar mitotic spindle formation was observed to be NuMA-dependent and γ-tubulin independent, suggesting that treatment-induced multipolar spindle formation does not depend on centrosomal amplification. The significantly enhanced efficacy of ACY-241 plus paclitaxel observed here, in addition to the anticipated superior safety profile of a selective HDAC6 inhibitor versus pan-HDAC inhibitors, provides a strong rationale for clinical development of this combination in patients with advanced solid tumors.

  1. The occurrence and removal of selected fluoroquinolones in urban drinking water treatment plants.

    Science.gov (United States)

    Xu, Yongpeng; Chen, Ting; Wang, Yuan; Tao, Hui; Liu, Shiyao; Shi, Wenxin

    2015-12-01

    Fluoroquinolones (FQs) are a widely prescribed group of antibiotics. They enter the aqueous environment, where they are frequently detected, and can lead to a threat to human health. Drinking water treatment plants (DWTPs) play a key role in removing FQs from potable water. This study investigated the occurrence and removal of four selected FQs (norfloxacin (NOR), ciprofloxacin (CIP), enrofloxacin (ENR), and ofloxacin (OFL)) in three urban DWTPs in China. The treatment efficacy for each system was simultaneously evaluated. Two of the examined DWTPs used conventional treatment processes. The third used conventional processes followed by additional treatment processes (ozonation-biologically activated carbon (ozonation-BAC) and membrane technology). The average concentrations of the four FQs in the source water and the finished water ranged from 51 to 248 ng/L and from residual concentrations, the conventional treatment system had a low removal of FQs. In contrast, the addition of advanced treatment processes such as the ozonation-BAC and membranes, substantially improved the removal of FQs. The finding of this study has important implications: even though coagulation-sedimentation and chlorination treatment processes can remove most target FQs, the typical practice of advanced treatment processes is necessary for the further removal.

  2. A proposal for a study on treatment selection and lifestyle recommendations in chronic inflammatory diseases

    DEFF Research Database (Denmark)

    Andersen, Vibeke; Holmskov, Uffe; Bek Sørensen, Signe

    2017-01-01

    to help tailor treatment decisions to an individual likely to initiate TNF inhibitor therapy, followed by (2) lifestyle factors that support achievement of optimised treatment outcome. This report describes the establishment of a cohort that aims to obtain this information. Clinical data including...... lifestyle and treatment response and biological specimens (blood, faeces, urine, and, in IBD patients, intestinal biopsies) are sampled prior to and while on TNF inhibitor therapy. Both hypothesis-driven and data-driven analyses will be performed according to pre-specified protocols including pathway...... analyses resulting from candidate gene expression analyses and global approaches (e.g., metabolomics, metagenomics, proteomics). The final purpose is to improve the lives of patients suffering from CIDs, by providing tools facilitating treatment selection and dietary recommendations likely to improve...

  3. Model selection on solid ground: Rigorous comparison of nine ways to evaluate Bayesian model evidence.

    Science.gov (United States)

    Schöniger, Anneli; Wöhling, Thomas; Samaniego, Luis; Nowak, Wolfgang

    2014-12-01

    Bayesian model selection or averaging objectively ranks a number of plausible, competing conceptual models based on Bayes' theorem. It implicitly performs an optimal trade-off between performance in fitting available data and minimum model complexity. The procedure requires determining Bayesian model evidence (BME), which is the likelihood of the observed data integrated over each model's parameter space. The computation of this integral is highly challenging because it is as high-dimensional as the number of model parameters. Three classes of techniques to compute BME are available, each with its own challenges and limitations: (1) Exact and fast analytical solutions are limited by strong assumptions. (2) Numerical evaluation quickly becomes unfeasible for expensive models. (3) Approximations known as information criteria (ICs) such as the AIC, BIC, or KIC (Akaike, Bayesian, or Kashyap information criterion, respectively) yield contradicting results with regard to model ranking. Our study features a theory-based intercomparison of these techniques. We further assess their accuracy in a simplistic synthetic example where for some scenarios an exact analytical solution exists. In more challenging scenarios, we use a brute-force Monte Carlo integration method as reference. We continue this analysis with a real-world application of hydrological model selection. This is a first-time benchmarking of the various methods for BME evaluation against true solutions. Results show that BME values from ICs are often heavily biased and that the choice of approximation method substantially influences the accuracy of model ranking. For reliable model selection, bias-free numerical methods should be preferred over ICs whenever computationally feasible.

  4. Selective Non-contact Field Radiofrequency Extended Treatment Protocol: Evaluation of Safety and Efficacy.

    Science.gov (United States)

    Moradi, Amir; Palm, Melanie

    2015-09-01

    Currently there are many non-invasive radiofrequency (RF) devices on the market that are utilized in the field of aesthetic medicine. At this time, there is only one FDA cleared device on the market that emits RF energy using a non-contact delivery system for circumferential reduction by means of adipocyte disruption. Innovation of treatment protocols is an integral part of aesthetic device development. However, when protocol modifications are made it is important to look at the safety as well as the potential for improved efficacy before initiating change. The purpose of this study was to evaluate the safety and efficacy of a newly designed extended treatment protocol using an operator independent selective non-contact RF device for the improvement in the contour and circumferential reduction of the abdomen and flanks (love handles). Twenty-five subjects enrolled in the IRB approved multi-center study to receive four weekly 45-minute RF treatments to the abdomen and love handles. Standardized digital photographs and circumference measurements were taken at baseline and at the 1- and 3-month follow-up visits. Biometric measurements including weight, hydration and body fat were obtained at baseline and each study visit. A subset of 4 subjects were randomly selected to undergo baseline serum lipid and liver-related blood tests with follow-up labs taken: 1 day post-treatment 1, 1 day post-treatment 4, and at the 1- and 3-month follow-up visits. Twenty-four subjects (22 female, 2 male), average age of 47.9 years (30-69 years), completed the study. The data of the twenty-four subjects revealed a statistically significant change in circumference P<.001 with an average decrease in circumference of 4.22cm at the 3-month follow-up visit. Lab values for the subset of 4 subjects remained relatively unchanged with only minor fluctuations noted in the serum lipid values in two of the subjects. Three independent evaluators viewed pre-treatment and 3-month post treatment

  5. A Selective Mutism Arising from First Language Attrition, Successfully Treated with Paroxetine-CBT Combination Treatment.

    Science.gov (United States)

    Serra, Agostino; Di Mauro, Paola; Andaloro, Claudio; Maiolino, Luigi; Pavone, Piero; Cocuzza, Salvatore

    2015-10-01

    After immersion in a foreign language, speakers often have difficulty retrieving native-language words and may experience a decrease in its proficiency, this phenomenon, in the non-pathological form, is known as first language attrition. Self-perception of this low native-language proficiency and apprehension occurring when speaking is expected and, may sometimes lead these people to a state of social anxiety and, in extreme forms, can involve the withholding of speech as a primitive tool for self-protection, linking them to selective mutism. We report an unusual case of selective mutism arising from first language attrition in an Italian girl after attending a two-year "German language school", who successfully responded to a paroxetine-cognitive behavioral treatment (CBT) combination treatment.

  6. Methodologies in the modeling of combined chemo-radiation treatments

    Science.gov (United States)

    Grassberger, C.; Paganetti, H.

    2016-11-01

    The variety of treatment options for cancer patients has increased significantly in recent years. Not only do we combine radiation with surgery and chemotherapy, new therapeutic approaches such as immunotherapy and targeted therapies are starting to play a bigger role. Physics has made significant contributions to radiation therapy treatment planning and delivery. In particular, treatment plan optimization using inverse planning techniques has improved dose conformity considerably. Furthermore, medical physics is often the driving force behind tumor control and normal tissue complication modeling. While treatment optimization and outcome modeling does focus mainly on the effects of radiation, treatment modalities such as chemotherapy are treated independently or are even neglected entirely. This review summarizes the published efforts to model combined modality treatments combining radiation and chemotherapy. These models will play an increasing role in optimizing cancer therapy not only from a radiation and drug dosage standpoint, but also in terms of spatial and temporal optimization of treatment schedules.

  7. Natalizumab treatment for multiple sclerosis: updated recommendations for patient selection and monitoring

    DEFF Research Database (Denmark)

    Kappos, Ludwig; Bates, David; Edan, Gilles

    2011-01-01

    Natalizumab, a highly specific a4-integrin antagonist, is approved for treatment of patients with active relapsing-remitting multiple sclerosis (RRMS). It is generally recommended for individuals who have not responded to a currently available first-line disease-modifying therapy or who have very......, based on additional long-term follow-up of clinical studies and post-marketing observations, including appropriate patient selection and management recommendations....

  8. Ball Milling Treatment of Black Dross for Selective Dissolution of Alumina in Sodium Hydroxide Leaching

    OpenAIRE

    Thi Thuy Nhi Nguyen; Man Seung Lee; Thi Hong Nguyen

    2018-01-01

    A process consisting of ball milling followed by NaOH leaching was developed to selectively dissolve alumina from black dross. From the ball milling treatment, it was found that milling speed greatly affected the leaching behavior of silica and the oxides of Ca, Fe, Mg, and Ti present in dross. The leaching behavior of the mechanically activated dross was investigated by varying NaOH concentration, leaching temperature and time, and pulp density. In most of the leaching conditions, only alumi...

  9. Natalizumab treatment for multiple sclerosis: updated recommendations for patient selection and monitoring

    DEFF Research Database (Denmark)

    Kappos, Ludwig; Bates, David; Edan, Gilles

    2011-01-01

    Natalizumab, a highly specific α4-integrin antagonist, is approved for treatment of patients with active relapsing-remitting multiple sclerosis (RRMS). It is generally recommended for individuals who have not responded to a currently available first-line disease-modifying therapy or who have very......, based on additional long-term follow-up of clinical studies and post-marketing observations, including appropriate patient selection and management recommendations....

  10. The selective angiographic diagnosis and endovascular embolization treatment of severe epistaxis

    International Nuclear Information System (INIS)

    Zhang Xiquan; Lu Yonghong; Sun Jinghua; Guo Deqiang; Li Yuzhen; Wei Aihua

    2002-01-01

    Objective: To evaluate selective angiographic diagnosis and embolization of severe epistaxis in 57 cases. Methods: 41 cases with spontaneous haemorrhage, 11 cases with traumatic haemorrhage, 3 cases with haemorrhage of nasopharyngeal fibroangioma, and 2 case with haemorrhage of nasopharyngeal carcinoma were included in the study. Selective angiographic diagnosis and embolization of epistaxis were performed with absorbable gelatin sponge or balloon or spring coil by using Seldinger's method. Results: 59 procedure of angiographic diagnosis and embolization were performed in 57 cases. Both maxillaris internal artery embolization was performed in 6 cases. After embolization, satisfactory results were achieved immediately in 55 cases. After 6 months to 2 years' follow-up, no haemorrhage recurred. In 4 cases with traumatic haemorrhage in the face, simple maxillaris internal artery embolization was performed in 2 cases. Conclusion: Selective angiographic diagnosis and embolization are safe, effective, and successful method of choices in the treatment of severe epistaxis

  11. Antibiotic selection of Escherichia coli sequence type 131 in a mouse intestinal colonization model

    DEFF Research Database (Denmark)

    Hertz, Frederik Boetius; Løbner-Olesen, Anders; Frimodt-Møller, Niels

    2014-01-01

    day, antibiotic treatment was initiated and given subcutaneously once a day for three consecutive days. CFU of E. coli ST131, Bacteroides, and Gram-positive aerobic bacteria in fecal samples were studied, with intervals, until day 8. Bacteroides was used as an indicator organism for impact on the Gram......-negative anaerobic population. For three antibiotics, prolonged colonization was investigated with additional fecal CFU counts determined on days 10 and 14 (cefotaxime, dicloxacillin, and clindamycin). Three antibiotics (cefotaxime, dicloxacillin, and clindamycin) promoted overgrowth of E. coli ST131 (P ...The ability of different antibiotics to select for extended-spectrum β-lactamase (ESBL)-producing Escherichia coli remains a topic of discussion. In a mouse intestinal colonization model, we evaluated the selective abilities of nine common antimicrobials (cefotaxime, cefuroxime, dicloxacillin...

  12. Heat transfer modelling and stability analysis of selective laser melting

    International Nuclear Information System (INIS)

    Gusarov, A.V.; Yadroitsev, I.; Bertrand, Ph.; Smurov, I.

    2007-01-01

    The process of direct manufacturing by selective laser melting basically consists of laser beam scanning over a thin powder layer deposited on a dense substrate. Complete remelting of the powder in the scanned zone and its good adhesion to the substrate ensure obtaining functional parts with improved mechanical properties. Experiments with single-line scanning indicate, that an interval of scanning velocities exists where the remelted tracks are uniform. The tracks become broken if the scanning velocity is outside this interval. This is extremely undesirable and referred to as the 'balling' effect. A numerical model of coupled radiation and heat transfer is proposed to analyse the observed instability. The 'balling' effect at high scanning velocities (above ∼20 cm/s for the present conditions) can be explained by the Plateau-Rayleigh capillary instability of the melt pool. Two factors stabilize the process with decreasing the scanning velocity: reducing the length-to-width ratio of the melt pool and increasing the width of its contact with the substrate

  13. Rules of meridians and acupoints selection in treatment of Parkinson's disease based on data mining techniques.

    Science.gov (United States)

    Li, Zhe; Hu, Ying-Yu; Zheng, Chun-Ye; Su, Qiao-Zhen; An, Chang; Luo, Xiao-Dong; Liu, Mao-Cai

    2018-01-15

    To help selecting appropriate meridians and acupoints in clinical practice and experimental study for Parkinson's disease (PD), the rules of meridians and acupoints selection of acupuncture and moxibustion were analyzed in domestic and foreign clinical treatment for PD based on data mining techniques. Literature about PD treated by acupuncture and moxibustion in China and abroad was searched and selected from China National Knowledge Infrastructure and MEDLINE. Then the data from all eligible articles were extracted to establish the database of acupuncture-moxibustion for PD. The association rules of data mining techniques were used to analyze the rules of meridians and acupoints selection. Totally, 168 eligible articles were included and 184 acupoints were applied. The total frequency of acupoints application was 1,090 times. Those acupoints were mainly distributed in head and neck and extremities. Among all, Taichong (LR 3), Baihui (DU 20), Fengchi (GB 20), Hegu (LI 4) and Chorea-tremor Controlled Zone were the top five acupoints that had been used. Superior-inferior acupoints matching was utilized the most. As to involved meridians, Du Meridian, Dan (Gallbladder) Meridian, Dachang (Large Intestine) Meridian, and Gan (Liver) Meridian were the most popular meridians. The application of meridians and acupoints for PD treatment lay emphasis on the acupoints on the head, attach importance to extinguishing Gan wind, tonifying qi and blood, and nourishing sinews, and make good use of superior-inferior acupoints matching.

  14. Isolation of cells for selective treatment and analysis using a magnetic microfluidic chip

    KAUST Repository

    Yassine, Omar

    2014-05-01

    This study describes the development and testing of a magnetic microfluidic chip (MMC) for trapping and isolating cells tagged with superparamagnetic beads (SPBs) in a microfluidic environment for selective treatment and analysis. The trapping and isolation are done in two separate steps; first, the trapping of the tagged cells in a main channel is achieved by soft ferromagnetic disks and second, the transportation of the cells into side chambers for isolation is executed by tapered conductive paths made of Gold (Au). Numerical simulations were performed to analyze the magnetic flux and force distributions of the disks and conducting paths, for trapping and transporting SPBs. The MMC was fabricated using standard microfabrication processes. Experiments were performed with E. coli (K12 strand) tagged with 2.8 μm SPBs. The results showed that E. coli can be separated from a sample solution by trapping them at the disk sites, and then isolated into chambers by transporting them along the tapered conducting paths. Once the E. coli was trapped inside the side chambers, two selective treatments were performed. In one chamber, a solution with minimal nutrition content was added and, in another chamber, a solution with essential nutrition was added. The results showed that the growth of bacteria cultured in the second chamber containing nutrient was significantly higher, demonstrating that the E. coli was not affected by the magnetically driven transportation and the feasibility of performing different treatments on selectively isolated cells on a single microfluidic platform.

  15. Effect of different oral oxytetracycline treatment regimes on selection of antimicrobial resistant coliforms in nursery pigs

    DEFF Research Database (Denmark)

    Fresno, Ana Herrero; Zachariasen, Camilla; Norholm, Nanna

    2017-01-01

    A major concern derived from using antimicrobials in pig production is the development of resistance. This study aimed to assess the impact of selected combinations of oral dose and duration of treatment with oxytetracycline (OTC) on selection of tetracycline resistant (TET-R) coliforms recovered...... from swine feces. The work encompassed two studies: 1) OTC 5 mg/kg and 20 mg/kg were administered to nursery pigs for 3 and 10 days, respectively, under controlled experimental conditions, and 2) 10 mg/kg, 20 mg/kg and 30 mg/kg OTC were given to a higher number of pigs for 6, 3 and 2 days, respectively......-selection for ampicillin- and sulphonamide-R bacteria was observed for any treatment at 2dAT. By the end of the nursery period, the proportion of TET-R bacteria was not significantly different between treatments and compared to day 0. Our results suggest that similar resistance levels might be obtained by using different...

  16. The use of mathematical models in teaching wastewater treatment engineering

    DEFF Research Database (Denmark)

    Morgenroth, Eberhard Friedrich; Arvin, Erik; Vanrolleghem, P.

    2002-01-01

    Mathematical modeling of wastewater treatment processes has become increasingly popular in recent years. To prepare students for their future careers, environmental engineering education should provide students with sufficient background and experiences to understand and apply mathematical models...

  17. Treatment efficacy, treatment failures and selection of macrolide resistance in patients with high load of Mycoplasma genitalium during treatment of male urethritis with josamycin.

    Science.gov (United States)

    Guschin, Alexander; Ryzhikh, Pavel; Rumyantseva, Tatiana; Gomberg, Mikhail; Unemo, Magnus

    2015-02-03

    Azithromycin has been widely used for Mycoplasma genitalium treatment internationally. However, the eradication efficacy has substantially declined recent decade. In Russia, josamycin (another macrolide) is the recommended first-line treatment for M. genitalium infections, however, no data regarding treatment efficacy with josamycin and resistance in M. genitalium infections have been internationally published. We examined the M. genitalium prevalence in males attending an STI clinic in Moscow, Russia from December 2006 to January 2008, investigated treatment efficacy with josamycin in male urethritis, and monitored the M. genitalium DNA eradication dynamics and selection of macrolide resistance in M. genitalium during this treatment. Microscopy and real-time PCRs were used to diagnose urethritis and non-viral STIs, respectively, in males (n = 320). M. genitalium positive patients were treated with recommended josamycin regimen and treatment efficacy was monitored using quantitative real-time PCR. Macrolide resistance mutations were identified using sequencing of the 23S rRNA gene. Forty-seven (14.7%) males were positive for M. genitalium only and most (85.1%) of these had symptoms and signs of urethritis. Forty-six (97.9%) males agreed to participate in the treatment efficacy monitoring. All the pre-treatment M. genitalium specimens had wild-type 23S rRNA. The elimination of M. genitalium DNA was substantially faster in patients with lower pre-treatment M. genitalium load, and the total eradication rate was 43/46 (93.5%). Of the six patients with high pre-treatment M. genitalium load, three (50%) remained positive post-treatment and these positive specimens contained macrolide resistance mutations in the 23S rRNA gene, i.e., A2059G (n = 2) and A2062G (n = 1). M. genitalium was a frequent cause of male urethritis in Moscow, Russia. The pre-treatment M. genitalium load might be an effective predictor of eradication efficacy with macrolides (and possibly

  18. Model Selection and Hypothesis Testing for Large-Scale Network Models with Overlapping Groups

    Directory of Open Access Journals (Sweden)

    Tiago P. Peixoto

    2015-03-01

    Full Text Available The effort to understand network systems in increasing detail has resulted in a diversity of methods designed to extract their large-scale structure from data. Unfortunately, many of these methods yield diverging descriptions of the same network, making both the comparison and understanding of their results a difficult challenge. A possible solution to this outstanding issue is to shift the focus away from ad hoc methods and move towards more principled approaches based on statistical inference of generative models. As a result, we face instead the more well-defined task of selecting between competing generative processes, which can be done under a unified probabilistic framework. Here, we consider the comparison between a variety of generative models including features such as degree correction, where nodes with arbitrary degrees can belong to the same group, and community overlap, where nodes are allowed to belong to more than one group. Because such model variants possess an increasing number of parameters, they become prone to overfitting. In this work, we present a method of model selection based on the minimum description length criterion and posterior odds ratios that is capable of fully accounting for the increased degrees of freedom of the larger models and selects the best one according to the statistical evidence available in the data. In applying this method to many empirical unweighted networks from different fields, we observe that community overlap is very often not supported by statistical evidence and is selected as a better model only for a minority of them. On the other hand, we find that degree correction tends to be almost universally favored by the available data, implying that intrinsic node proprieties (as opposed to group properties are often an essential ingredient of network formation.

  19. A Stochastic Programming Model for Fuel Treatment Management

    Directory of Open Access Journals (Sweden)

    Mohannad Kabli

    2015-06-01

    Full Text Available This work considers a two-stage stochastic integer programming (SIP approach for optimizing fuel treatment planning under uncertainty in weather and fire occurrence for rural forests. Given a set of areas for potentially performing fuel treatment, the problem is to decide the best treatment option for each area under uncertainty in future weather and fire occurrence. A two-stage SIP model is devised whose objective is to minimize the here-and-now cost of fuel treatment in the first-stage, plus the expected future costs due to uncertain impact from potential fires in the second-stage calculated as ecosystem services losses. The model considers four fuel treatment options: no treatment, mechanical thinning, prescribed fire, and grazing. Several constraints such as budgetary and labor constraints are included in the model and a standard fire behavior model is used to estimate some of the parameters of the model such as fuel levels at the beginning of the fire season. The SIP model was applied to data for a study area in East Texas with 15 treatment areas under different weather scenarios. The results of the study show, for example, that unless the expected ecosystem services values for an area outweigh fuel treatment costs, no treatment is the best choice for the area. Thus the valuation of the area together with the probability of fire occurrence and behavior strongly drive fuel treatment choices.

  20. Modelling uncertainty due to imperfect forward model and aerosol microphysical model selection in the satellite aerosol retrieval

    Science.gov (United States)

    Määttä, Anu; Laine, Marko; Tamminen, Johanna

    2015-04-01

    This study aims to characterize the uncertainty related to the aerosol microphysical model selection and the modelling error due to approximations in the forward modelling. Many satellite aerosol retrieval algorithms rely on pre-calculated look-up tables of model parameters representing various atmospheric conditions. In the retrieval we need to choose the most appropriate aerosol microphysical models from the pre-defined set of models by fitting them to the observations. The aerosol properties, e.g. AOD, are then determined from the best models. This choice of an appropriate aerosol model composes a notable part in the AOD retrieval uncertainty. The motivation in our study was to account these two sources in the total uncertainty budget: uncertainty in selecting the most appropriate model, and uncertainty resulting from the approximations in the pre-calculated aerosol microphysical model. The systematic model error was analysed by studying the behaviour of the model residuals, i.e. the differences between modelled and observed reflectances, by statistical methods. We utilised Gaussian processes to characterize the uncertainty related to approximations in aerosol microphysics modelling due to use of look-up tables and other non-modelled systematic features in the Level 1 data. The modelling error is described by a non-diagonal covariance matrix parameterised by correlation length, which is estimated from the residuals using computational tools from spatial statistics. In addition, we utilised Bayesian model selection and model averaging methods to account the uncertainty due to aerosol model selection. By acknowledging the modelling error as a source of uncertainty in the retrieval of AOD from observed spectral reflectance, we allow the observed values to deviate from the modelled values within limits determined by both the measurement and modelling errors. This results in a more realistic uncertainty level of the retrieved AOD. The method is illustrated by both

  1. The duration of orthodontic treatment with and without extractions: a pilot study of five selected practices.

    Science.gov (United States)

    Vig, P S; Weintraub, J A; Brown, C; Kowalski, C J

    1990-01-01

    Contemporary orthodontic practice is diverse, both in the variety of clinical problems treated and in the methods used. Practices differ with respect to their patient composition as well as in many variables relative to treatment protocols. Such heterogeneity makes it difficult to make valid generalizations concerning the characteristics of orthodontic treatment procedures or outcomes; yet data and methods are required for assessment of issues of efficacy and utility. The frequency of orthodontic extractions is an objective criterion that distinguishes practices and may also be related to differences in treatment outcome variables, such as duration. Following a telephone survey to estimate extraction rates in the practices of 238 Michigan orthodontists, five practices with very high or low reported rates were chosen for this pilot study. Our primary aim was to determine whether a systematic relationship existed between the relative frequency of extraction treatments and the duration of active appliance therapy. Records of 438 patients from these practices were examined. The extraction rates of the practices ranged from a low of 25% to a high of 84%. Treatment duration was affected by several variables, such as the number of arches treated, the number of treatment phases, and the practice selected. When the data for all five practices were pooled, and all of the extraction versus nonextraction treatments were compared, the mean durations of treatment were 31.2 and 31.3 months, respectively. Data from individual practices, however, indicated that extraction treatment in each of the practices was of longer duration than nonextraction therapy. These differences in duration were 3.0, 6.6, 2.4, 3.0, and 7.3 months in the five practices.(ABSTRACT TRUNCATED AT 250 WORDS)

  2. Water quality modelling and optimisation of wastewater treatment ...

    African Journals Online (AJOL)

    2016-10-04

    Oct 4, 2016 ... Using this model, it was demonstrated that water quality standards can be met at all monitoring points at a minimum cost by simultaneously optimising treatment levels at each treatment plant. Keywords: instream water quality, mixed integer optimisation, wastewater treatment levels, Streeter-Phelps.

  3. Computational models as predictors of HIV treatment outcomes for the Phidisa cohort in South Africa

    NARCIS (Netherlands)

    Revell, Andrew; Khabo, Paul; Ledwaba, Lotty; Emery, Sean; Wang, Dechao; Wood, Robin; Morrow, Carl; Tempelman, Hugo; Hamers, Raph L.; Reiss, Peter; van Sighem, Ard; Pozniak, Anton; Montaner, Julio; Lane, H. Clifford; Larder, Brendan

    2016-01-01

    Background: Selecting the optimal combination of HIV drugs for an individual in resourcelimited settings is challenging because of the limited availability of drugs and genotyping. Objective: The evaluation as a potential treatment support tool of computational models that predict response to

  4. Selective androgen receptor modulators for the treatment of late onset male hypogonadism

    Science.gov (United States)

    Coss, Christopher C; Jones, Amanda; Hancock, Michael L; Steiner, Mitchell S; Dalton, James T

    2014-01-01

    Several testosterone preparations are used in the treatment of hypogonadism in the ageing male. These therapies differ in their convenience, flexibility, regional availability and expense but share their pharmacokinetic basis of approval and dearth of long-term safety data. The brevity and relatively reduced cost of pharmacokinetic based registration trials provides little commercial incentive to develop improved novel therapies for the treatment of late onset male hypogonadism. Selective androgen receptor modulators (SARMs) have been shown to provide anabolic benefit in the absence of androgenic effects on prostate, hair and skin. Current clinical development for SARMs is focused on acute muscle wasting conditions with defined clinical endpoints of physical function and lean body mass. Similar regulatory clarity concerning clinical deficits in men with hypogonadism is required before the beneficial pharmacology and desirable pharmacokinetics of SARMs can be employed in the treatment of late onset male hypogonadism. PMID:24407183

  5. Cleanup and treatment of radioactively contaminated land including areas near nuclear facilities. A selected bibliography

    International Nuclear Information System (INIS)

    Fore, C.S.; Faust, R.A.; Brewster, R.H.

    1982-09-01

    This annotated bibliography of 337 references summarizes the literature published on the cleanup and treatment of radioactively contaminated land. Specifically, this bibliography focuses on literature concerned with the methods of cleanup and treatment being applied - chemical, physical, or vegetative stabilization; the types of equipment being used; and the influence of climatic conditions on the method selected for use. The emphasis in such literature is placed on hazardous site cleanup efforts that have been completed as well as those that are in progress and are being planned. Appendix A includes 135 additional references to literature identified but not included in the bibliography because of time and funding constraints. Appendix B consists of a table that identifies the cleanup and treatment research conducted at specific sites. All of the information included in this bibliography is stored in a computerized form that is readily available upon request

  6. Selective androgen receptor modulators for the treatment of late onset male hypogonadism.

    Science.gov (United States)

    Coss, Christopher C; Jones, Amanda; Hancock, Michael L; Steiner, Mitchell S; Dalton, James T

    2014-01-01

    Several testosterone preparations are used in the treatment of hypogonadism in the ageing male. These therapies differ in their convenience, flexibility, regional availability and expense but share their pharmacokinetic basis of approval and dearth of long-term safety data. The brevity and relatively reduced cost of pharmacokinetic based registration trials provides little commercial incentive to develop improved novel therapies for the treatment of late onset male hypogonadism. Selective androgen receptor modulators (SARMs) have been shown to provide anabolic benefit in the absence of androgenic effects on prostate, hair and skin. Current clinical development for SARMs is focused on acute muscle wasting conditions with defi ned clinical endpoints of physical function and lean body mass. Similar regulatory clarity concerning clinical deficits in men with hypogonadism is required before the beneficial pharmacology and desirable pharmacokinetics of SARMs can be employed in the treatment of late onset male hypogonadism.

  7. Selective androgen receptor modulators for the treatment of late onset male hypogonadism

    Directory of Open Access Journals (Sweden)

    Christopher C Coss

    2014-04-01

    Full Text Available Several testosterone preparations are used in the treatment of hypogonadism in the ageing male. These therapies differ in their convenience, flexibility, regional availability and expense but share their pharmacokinetic basis of approval and dearth of long-term safety data. The brevity and relatively reduced cost of pharmacokinetic based registration trials provides little commercial incentive to develop improved novel therapies for the treatment of late onset male hypogonadism. Selective androgen receptor modulators (SARMs have been shown to provide anabolic benefit in the absence of androgenic effects on prostate, hair and skin. Current clinical development for SARMs is focused on acute muscle wasting conditions with defi ned clinical endpoints of physical function and lean body mass. Similar regulatory clarity concerning clinical deficits in men with hypogonadism is required before the beneficial pharmacology and desirable pharmacokinetics of SARMs can be employed in the treatment of late onset male hypogonadism.

  8. Systematic Review and Meta-Analysis: Early Treatment Responses of Selective Serotonin Reuptake Inhibitors in Pediatric Major Depressive Disorder.

    Science.gov (United States)

    Varigonda, Anjali L; Jakubovski, Ewgeni; Taylor, Matthew J; Freemantle, Nick; Coughlin, Catherine; Bloch, Michael H

    2015-07-01

    Selective serotonin reuptake inhibitors (SSRIs) are the first-line pharmacological treatment for pediatric major depressive disorder (MDD). We conducted a meta-analysis to examine the following: the time-course of response to SSRIs in pediatric depression; whether higher doses of SSRIs are associated with an improved response in pediatric depression; differences in efficacy between SSRI agents; and whether the time-course and magnitude of response to SSRIs is different in pediatric and adult patients with MDD. We searched PubMed and CENTRAL for randomized controlled trials comparing SSRIs to placebo for the treatment of pediatric MDD. We extracted weekly symptom data from trials to characterize the trajectory of pharmacological response to SSRIs. Pooled estimates of treatment effect were calculated based on standardized mean differences between treatment and placebo groups. The meta-analysis included 13 pediatric MDD trials with a total of 3,004 patients. A logarithmic model indicating that the greatest benefits of SSRIs occurred early in treatment best fit the longitudinal data (log[week] = 0.10, 95% CI = 0.06-0.15, p power of early SSRI response (e.g., 2-4 weeks) to predict outcomes in short-term pharmacological trials. Copyright © 2015. Published by Elsevier Inc.

  9. General quality of life of patients with acne vulgaris before and after performing selected cosmetological treatments

    Science.gov (United States)

    Chilicka, Karolina; Maj, Joanna; Panaszek, Bernard

    2017-01-01

    Background Achieving a satisfying quality of life for a patient by applying individually matched therapy is, simultaneously, a great challenge and a priority for contemporary medicine. Patients with visible dermatological ailments are particularly susceptible to reduction in the general quality of life. Among the dermatological diseases, acne causes considerable reduction in the quality of life and changes in self-perception that lead to the worsening of a patient’s mental condition, including depression and suicidal thoughts. As a result, difficulties in contact with loved ones, as well as social and professional problems are observed, which show that acne is not a somatic problem alone. To a large extent, it becomes a part of psychodermatology, becoming an important topic of public health in social medicine practice. Pharmacological treatment of acne is a challenge for a dermatologist and often requires the necessity of cooperating with a cosmetologist. Cosmetological treatments are aimed at improving the condition of the skin and reduction or subsiding of acne skin changes. Aim The aim of this study was to assess the influence of selected cosmetological treatments on the general quality of life of patients with acne. Materials and methods The study group consisted of 101 women aged 19–29 years (x¯=22.5 years, SD =2.3 years). All subjects were diagnosed with acne vulgaris of the face. In the study group, the acne changes occurred over the course of 3–15 years (x¯=8.1 years, SD =2.7 years). Selected cosmetological treatments (intensive pulsing light, alpha-hydroxy acids, cavitation peeling, needle-free mesotherapy, diamond microdermabrasion and sonophoresis) were performed in series in the number depending on the particular patient’s chosen treatment, after excluding contraindications. General quality of life of the patients was estimated using the Skindex-29 and Dermatology Life Quality Index (DLQI) questionnaires, before and after the cosmetological

  10. Optimal treatment interruptions control of TB transmission model

    Science.gov (United States)

    Nainggolan, Jonner; Suparwati, Titik; Kawuwung, Westy B.

    2018-03-01

    A tuberculosis model which incorporates treatment interruptions of infectives is established. Optimal control of individuals infected with active TB is given in the model. It is obtained that the control reproduction numbers is smaller than the reproduction number, this means treatment controls could optimize the decrease in the spread of active TB. For this model, controls on treatment of infection individuals to reduce the actively infected individual populations, by application the Pontryagins Maximum Principle for optimal control. The result further emphasized the importance of controlling disease relapse in reducing the number of actively infected and treatment interruptions individuals with tuberculosis.

  11. New treatment models for compulsive disorders

    NARCIS (Netherlands)

    Grant, Jon E; Fineberg, Naomi; van Ameringen, Michael; Cath, Danielle; Visser, Henny; Carmi, Lior; Pallanti, Stefano; Hollander, Eric; van Balkom, Anton J L M

    Obsessive compulsive disorder (OCD) as well as related disorders such as body dysmorphic disorder, tic disorder, and trichotillomania are all common and often debilitating. Although treatments are available, more effective approaches to these problems are needed. Thus this review article presents

  12. Risk-adjusted treatment selection and outcome of patients with acute cholecystitis.

    Science.gov (United States)

    González-Muñoz, J I; Franch-Arcas, G; Angoso-Clavijo, M; Sánchez-Hernández, M; García-Plaza, A; Caraballo-Angeli, M; Muñoz-Bellvís, L

    2017-06-01

    Age and comorbidities increase the surgical risk for patients with acute cholecystitis and impact on the initial treatment selection. The aim of this article is the implementation of objective risk criteria that may be used to select the most appropriate treatment. We carried out a prospective cohort study of all patients who were admitted to the hospital with a diagnosis of acute cholecystitis during 2014. They were initially allocated to three different treatment groups according to cholecystitis grade, number of days from clinical onset, and surgical risk scores as follows: immediate surgery by sepsis (EmergS), early surgery (EarlyS), or medical treatment group (MedT). Differences in the outcomes between the treatment groups were evaluated using bivariate and logistic regression analyses. A total of 149 patients were admitted; 44 % were >80 years old and 40 % were American Society of Anesthesiologists (ASA) > II. The mortality rate of the series was 0 % in EarlyS, 17 % in MedT, and 19 % in EmergS. The mortality rate was significantly associated with a higher degree of cholecystitis, age, and worse score values in risk scales and Charlson index. Logistic regression identified that the only independent predictors of death at the time of admission were the degree of cholecystitis (OR 2.87, p = 0.018) and the Portsmouth Physiological and Operative Severity Score for the enumeration of Mortality and Morbidity (P-POSSUM) score (OR 1.14, p = 0.001). The evaluation for the initial treatment in acute cholecystitis should include a systematic determination of the degree of cholecystitis and a surgical risk assessment. Tokyo guideline recommendations should be reviewed.

  13. Structure and selection in an autocatalytic binary polymer model

    DEFF Research Database (Denmark)

    Tanaka, Shinpei; Fellermann, Harold; Rasmussen, Steen

    2014-01-01

    a pool of monomers, highly ordered populations with particular sequence patterns are dynamically selected out of a vast number of possible states. The interplay between the selected microscopic sequence patterns and the macroscopic cooperative structures is examined both analytically and in simulation...

  14. Performance Measurement Model for the Supplier Selection Based on AHP

    Directory of Open Access Journals (Sweden)

    Fabio De Felice

    2015-10-01

    Full Text Available The performance of the supplier is a crucial factor for the success or failure of any company. Rational and effective decision making in terms of the supplier selection process can help the organization to optimize cost and quality functions. The nature of supplier selection processes is generally complex, especially when the company has a large variety of products and vendors. Over the years, several solutions and methods have emerged for addressing the supplier selection problem (SSP. Experience and studies have shown that there is no best way for evaluating and selecting a specific supplier process, but that it varies from one organization to another. The aim of this research is to demonstrate how a multiple attribute decision making approach can be effectively applied for the supplier selection process.

  15. Voxel-based dose prediction with multi-patient atlas selection for automated radiotherapy treatment planning

    Science.gov (United States)

    McIntosh, Chris; Purdie, Thomas G.

    2017-01-01

    Automating the radiotherapy treatment planning process is a technically challenging problem. The majority of automated approaches have focused on customizing and inferring dose volume objectives to be used in plan optimization. In this work we outline a multi-patient atlas-based dose prediction approach that learns to predict the dose-per-voxel for a novel patient directly from the computed tomography planning scan without the requirement of specifying any objectives. Our method learns to automatically select the most effective atlases for a novel patient, and then map the dose from those atlases onto the novel patient. We extend our previous work to include a conditional random field for the optimization of a joint distribution prior that matches the complementary goals of an accurately spatially distributed dose distribution while still adhering to the desired dose volume histograms. The resulting distribution can then be used for inverse-planning with a new spatial dose objective, or to create typical dose volume objectives for the canonical optimization pipeline. We investigated six treatment sites (633 patients for training and 113 patients for testing) and evaluated the mean absolute difference in all DVHs for the clinical and predicted dose distribution. The results on average are favorable in comparison to our previous approach (1.91 versus 2.57). Comparing our method with and without atlas-selection further validates that atlas-selection improved dose prediction on average in whole breast (0.64 versus 1.59), prostate (2.13 versus 4.07), and rectum (1.46 versus 3.29) while it is less important in breast cavity (0.79 versus 0.92) and lung (1.33 versus 1.27) for which there is high conformity and minimal dose shaping. In CNS brain, atlas-selection has the potential to be impactful (3.65 versus 5.09), but selecting the ideal atlas is the most challenging.

  16. Process modeling for the Integrated Nonthermal Treatment System (INTS) study

    Energy Technology Data Exchange (ETDEWEB)

    Brown, B.W.

    1997-04-01

    This report describes the process modeling done in support of the Integrated Nonthermal Treatment System (INTS) study. This study was performed to supplement the Integrated Thermal Treatment System (ITTS) study and comprises five conceptual treatment systems that treat DOE contract-handled mixed low-level wastes (MLLW) at temperatures of less than 350{degrees}F. ASPEN PLUS, a chemical process simulator, was used to model the systems. Nonthermal treatment systems were developed as part of the INTS study and include sufficient processing steps to treat the entire inventory of MLLW. The final result of the modeling is a process flowsheet with a detailed mass and energy balance. In contrast to the ITTS study, which modeled only the main treatment system, the INTS study modeled each of the various processing steps with ASPEN PLUS, release 9.1-1. Trace constituents, such as radionuclides and minor pollutant species, were not included in the calculations.

  17. Comparison of multimedia system and conventional method in patients’ selecting prosthetic treatment

    Directory of Open Access Journals (Sweden)

    Baghai R

    2010-12-01

    Full Text Available "nBackground and Aims: Selecting an appropriate treatment plan is one of the most critical aspects of dental treatments. The purpose of this study was to compare multimedia system and conventional method in patients' selecting prosthetic treatment and the time consumed."nMaterials and Methods: Ninety patients were randomly divided into three groups. Patients in group A, once were instructed using the conventional method of dental office and once multimedia system and time was measured in seconds from the beginning of the instruction till the patient had came to decision. The patients were asked about the satisfaction of the method used for them. In group B, patients were only instructed using the conventional method, whereas they were only exposed to soft ware in group C. The data were analyzed with Paired-T-test"n(in group A and T-test and Mann-Whitney test (in groups B and C."nResult: There was a significant difference between multimedia system and conventional method in group A and also between groups B and C (P<0.001. In group A and between groups B and C, patient's satisfaction about multimedia system was better. However, in comparison between groups B and C, multimedia system did not have a significant effect in treatment selection score (P=0.08."nConclusion: Using multimedia system is recommended due to its high ability in giving answers to a large number of patient's questions as well as in terms of marketing.

  18. Genome-wide selection by mixed model ridge regression and extensions based on geostatistical models.

    Science.gov (United States)

    Schulz-Streeck, Torben; Piepho, Hans-Peter

    2010-03-31

    The success of genome-wide selection (GS) approaches will depend crucially on the availability of efficient and easy-to-use computational tools. Therefore, approaches that can be implemented using mixed models hold particular promise and deserve detailed study. A particular class of mixed models suitable for GS is given by geostatistical mixed models, when genetic distance is treated analogously to spatial distance in geostatistics. We consider various spatial mixed models for use in GS. The analyses presented for the QTL-MAS 2009 dataset pay particular attention to the modelling of residual errors as well as of polygenetic effects. It is shown that geostatistical models are viable alternatives to ridge regression, one of the common approaches to GS. Correlations between genome-wide estimated breeding values and true breeding values were between 0.879 and 0.889. In the example considered, we did not find a large effect of the residual error variance modelling, largely because error variances were very small. A variance components model reflecting the pedigree of the crosses did not provide an improved fit. We conclude that geostatistical models deserve further study as a tool to GS that is easily implemented in a mixed model package.

  19. Alemtuzumab in the treatment of multiple sclerosis: patient selection and special considerations

    Directory of Open Access Journals (Sweden)

    Dörr J

    2016-10-01

    the other are not yet available. Thus, the overall success of alemtuzumab treatment critically depends on the patient selection. The aim of this article is therefore, to characterize the significance of alemtuzumab in the treatment of MS with a focus on the selection of the optimal patient. Keywords: multiple sclerosis, treatment, safety, efficacy, selection, benefit risk relation

  20. Effective operator treatment of the Lipkin model

    International Nuclear Information System (INIS)

    Abraham, K.J.; Vary, J.P.

    2004-01-01

    We analyze the Lipkin model in the strong coupling limit using effective operator techniques. We present both analytical and numerical results for low energy effective Hamiltonians. We investigate the reliability of various approximations used to simplify the nuclear many body problem, such as the cluster approximation. We demonstrate, in explicit examples, certain limits to the validity of the cluster approximation but caution that these limits may be particular to this model where the interactions are of unlimited range

  1. Feature selection and classification model construction on type 2 diabetic patients' data.

    Science.gov (United States)

    Huang, Yue; McCullagh, Paul; Black, Norman; Harper, Roy

    2007-11-01

    Diabetes affects between 2% and 4% of the global population (up to 10% in the over 65 age group), and its avoidance and effective treatment are undoubtedly crucial public health and health economics issues in the 21st century. The aim of this research was to identify significant factors influencing diabetes control, by applying feature selection to a working patient management system to assist with ranking, classification and knowledge discovery. The classification models can be used to determine individuals in the population with poor diabetes control status based on physiological and examination factors. The diabetic patients' information was collected by Ulster Community and Hospitals Trust (UCHT) from year 2000 to 2004 as part of clinical management. In order to discover key predictors and latent knowledge, data mining techniques were applied. To improve computational efficiency, a feature selection technique, feature selection via supervised model construction (FSSMC), an optimisation of ReliefF, was used to rank the important attributes affecting diabetic control. After selecting suitable features, three complementary classification techniques (Naïve Bayes, IB1 and C4.5) were applied to the data to predict how well the patients' condition was controlled. FSSMC identified patients' 'age', 'diagnosis duration', the need for 'insulin treatment', 'random blood glucose' measurement and 'diet treatment' as the most important factors influencing blood glucose control. Using the reduced features, a best predictive accuracy of 95% and sensitivity of 98% was achieved. The influence of factors, such as 'type of care' delivered, the use of 'home monitoring', and the importance of 'smoking' on outcome can contribute to domain knowledge in diabetes control. In the care of patients with diabetes, the more important factors identified: patients' 'age', 'diagnosis duration' and 'family history', are beyond the control of physicians. Treatment methods such as 'insulin', 'diet

  2. KPI (KEY PERFORMANCE INDICATORS APPLICATION ON BALLAST WATER TREATMENT SYSTEM SELECTION

    Directory of Open Access Journals (Sweden)

    Gülçin Vural

    2017-01-01

    Full Text Available Every day, more than 7,000 different marine species are transferred to different ecosystems via ballast water in ships. The introduction of invasive species can cause problems for native species. After realizing the serious potential problems associated with the transport of organisms in ballast water, national and international regulations were developed. In 2004, the International Maritime Organization introduced the International Convention for the Control and Management of Ships' Ballast Water and Sediments. With these regulations, the problems caused by ballast water have attracted attention and many companies have started to research and develop technologies for the management of ballast water. Today, there are hundreds of different systems for ballast-water treatment, and the selection of the most suitable system for a specific vessel is an increasingly important issue as the Convention nears enforcement on September 8, 2017. The goal of this study is to demonstrate that the application of key performance indicators (KPIs to the selection of a ballast-water treatment system (BWTS leads to a very useful tool with which shipyards can compare BWTSs. This allows them to make better choices and to designate the most suitable system for each of their ships. In this study, we examine two types of vessel from a shipyard in Istanbul, Turkey. They have different ballast-water capacities and equipment, and the most suitable system for each is selected by using the KPI method.

  3. Treatment Strategies that Enhance the Efficacy and Selectivity of Mitochondria-Targeted Anticancer Agents

    Directory of Open Access Journals (Sweden)

    Josephine S. Modica-Napolitano

    2015-07-01

    Full Text Available Nearly a century has passed since Otto Warburg first observed high rates of aerobic glycolysis in a variety of tumor cell types and suggested that this phenomenon might be due to an impaired mitochondrial respiratory capacity in these cells. Subsequently, much has been written about the role of mitochondria in the initiation and/or progression of various forms of cancer, and the possibility of exploiting differences in mitochondrial structure and function between normal and malignant cells as targets for cancer chemotherapy. A number of mitochondria-targeted compounds have shown efficacy in selective cancer cell killing in pre-clinical and early clinical testing, including those that induce mitochondria permeability transition and apoptosis, metabolic inhibitors, and ROS regulators. To date, however, none has exhibited the standards for high selectivity and efficacy and low toxicity necessary to progress beyond phase III clinical trials and be used as a viable, single modality treatment option for human cancers. This review explores alternative treatment strategies that have been shown to enhance the efficacy and selectivity of mitochondria-targeted anticancer agents in vitro and in vivo, and may yet fulfill the clinical promise of exploiting the mitochondrion as a target for cancer chemotherapy.

  4. Mean field theory for a balanced hypercolumn model of orientation selectivity in primary visual cortex

    CERN Document Server

    Lerchner, A; Hertz, J; Ahmadi, M

    2004-01-01

    We present a complete mean field theory for a balanced state of a simple model of an orientation hypercolumn. The theory is complemented by a description of a numerical procedure for solving the mean-field equations quantitatively. With our treatment, we can determine self-consistently both the firing rates and the firing correlations, without being restricted to specific neuron models. Here, we solve the analytically derived mean-field equations numerically for integrate-and-fire neurons. Several known key properties of orientation selective cortical neurons emerge naturally from the description: Irregular firing with statistics close to -- but not restricted to -- Poisson statistics; an almost linear gain function (firing frequency as a function of stimulus contrast) of the neurons within the network; and a contrast-invariant tuning width of the neuronal firing. We find that the irregularity in firing depends sensitively on synaptic strengths. If Fano factors are bigger than 1, then they are so for all stim...

  5. Mean field theory for a balanced hypercolumn model of orientation selectivity in primary visual cortex

    DEFF Research Database (Denmark)

    Lerchner, Alexander; Sterner, G.; Hertz, J.

    2006-01-01

    We present a complete mean field theory for a balanced state of a simple model of an orientation hypercolumn, with a numerical procedure for solving the mean-field equations quantitatively. With our treatment, one can determine self-consistently both the firing rates and the firing correlations......, without being restricted to specific neuron models. Here, we solve the mean-field equations numerically for integrate-and-fire neurons. Several known key properties of orientation selective cortical neurons emerge naturally from the description: Irregular firing with statistics close...... to - but not restricted to Poisson statistics; an almost linear gain function (firing frequency as a function of stimulus contrast) of the neurons within the network; and a contrast-invariant tuning width of the neuronal firing. We find that the irregularity in firing depends sensitively on synaptic strengths...

  6. Helminths in horses : use of selective treatment for the control of strongyles

    Directory of Open Access Journals (Sweden)

    S. Matthee

    2004-06-01

    Full Text Available The current level of anthelmintic resistance in the horse-breeding industry is extremely high and therefore more emphasis is being placed on studies that focus on the judicious use of anthelmintic products. The aims of the study were to: 1 establish if there is variation in the egg excretion pattern of strongyles between the different age classes of Thoroughbred horses in the Western Cape Province (WCP, 2 test if a selective treatment approach successfully reduces the number of anthelmintic treatments and maintains acceptably low helminth burdens in adult Thoroughbred horses, and 3 evaluate the efficacy of subsampling large horse herds for faecal egg counts (FECs to monitor the strongyle burden. In 2001 the FECs of 4 adult mare, 5 yearling and 3 weanling herds from 8 different farms were compared in the WCP. Within the mare herds there were generally fewer eggexcreting individuals with lower mean FECs compared with the younger age classes. Individual faecal samples were collected every 3-4 weeks from 52 adult Thoroughbred mares from 1 farm in the WCP during a 12-month period (2002/2003. Animals with strongyle FECs > 100 eggs per gram (epg were treated with an ivermectin-praziquantel combination drug (Equimax oral paste, Virbac. The mean monthly strongyle FEC for the entire group was < 300 epg throughout the study and the number of treatments was reduced by 50 %. Resampling methods showed that an asymptote to mean FEC was reached at 55 animals for each of the pooled weanling, yearling and mare egg counts. Resampling within 4 different mare herds recorded asymptotes of between 24 and 28 animals. Subsampling entire herds for FECs therefore provided an effective approach to treatment management. This study demonstrates that selective treatment is both a practical and an effective approach to the management of anthelmintic resistance.

  7. Selection of response criteria affects the success rate of oral appliance treatment for obstructive sleep apnea.

    Science.gov (United States)

    Fukuda, Tatsuya; Tsuiki, Satoru; Kobayashi, Mina; Nakayama, Hideaki; Inoue, Yuichi

    2014-03-01

    In oral appliance therapy for obstructive sleep apnea (OSA), treatment success is arbitrarily defined. We investigated if the selection of response criteria affected the success rate of oral appliance treatment. The effects of an oral appliance on apnea-hypopnea index (AHI) and nadir percutaneous oxygen saturation (SpO2) were investigated in 224 OSA patients. Treatment success was defined as a reduction in AHI to 50% reduction in baseline AHI (criterion 1), a follow-up AHI of 50% reduction in baseline AHI (criterion 2), a >50% reduction in baseline AHI alone (criterion 3), or a >50% reduction in baseline AHI with the nadir SpO2 above 90% (criterion 4). The baseline AHI was reduced with an oral appliance in place compared with the follow-up value (23 ± 11-8.5 ± 8.7 events/h; Poral appliance treatment. To avoid adverse health outcomes, an adjunct definition of treatment success using SpO2 may be effective for patients who have more severe OSA. Copyright © 2014 Elsevier B.V. All rights reserved.

  8. Selection of odour removal technologies in wastewater treatment plants: a guideline based on Life Cycle Assessment.

    Science.gov (United States)

    Alfonsín, Carolina; Lebrero, Raquel; Estrada, José M; Muñoz, Raúl; Kraakman, N J R Bart; Feijoo, Gumersindo; Moreira, M Teresa

    2015-02-01

    This paper aims at analysing the environmental benefits and impacts associated with the treatment of malodorous emissions from wastewater treatment plants (WWTPs). The life cycle assessment (LCA) methodology was applied to two biological treatments, namely biofilter (BF) and biotrickling filter (BTF), two physical/chemical alternatives, namely activated carbon tower (AC) and chemical scrubber (CS), and a hybrid combination of BTF + AC. The assessment provided consistent guidelines for technology selection, not only based on removal efficiencies, but also on the environmental impact associated with the treatment of emissions. The results showed that biological alternatives entailed the lowest impacts. On the contrary, the use of chemicals led to the highest impacts for CS. Energy use was the main contributor to the impact related to BF and BTF, whereas the production of glass fibre used as infrastructure material played an important role in BTF impact. Production of NaClO entailed the highest burdens among the chemicals used in CS, representing ∼ 90% of the impact associated to chemicals. The frequent replacement of packing material in AC was responsible for the highest environmental impacts, granular activated carbon (GAC) production and its final disposal representing more than 50% of the impact in most categories. Finally, the assessment of BTF + AC showed that the hybrid technology is less recommendable than BF and BTF, but friendlier to the environment than physical/chemical treatments. Copyright © 2014 Elsevier Ltd. All rights reserved.

  9. Selecting representative climate models for climate change impact studies : An advanced envelope-based selection approach

    NARCIS (Netherlands)

    Lutz, Arthur F.; ter Maat, Herbert W.; Biemans, Hester; Shrestha, Arun B.; Wester, Philippus; Immerzeel, Walter W.

    2016-01-01

    Climate change impact studies depend on projections of future climate provided by climate models. The number of climate models is large and increasing, yet limitations in computational capacity make it necessary to compromise the number of climate models that can be included in a climate change

  10. Selecting representative climate models for climate change impact studies: an advanced envelope-based selection approach

    NARCIS (Netherlands)

    Lutz, Arthur F.; Maat, ter Herbert W.; Biemans, Hester; Shrestha, Arun B.; Wester, Philippus; Immerzeel, Walter W.

    2016-01-01

    Climate change impact studies depend on projections of future climate provided by climate models. The number of climate models is large and increasing, yet limitations in computational capacity make it necessary to compromise the number of climate models that can be included in a climate change

  11. Analysis of a tube-grid oscillatory contact: methodology for the selection of superficial treatments

    International Nuclear Information System (INIS)

    Voisin, J.M.; Vannes, A.B.; Vincent, L.; Daviot, J.; Giraud, B.

    1995-01-01

    To minimize the failure risks (metal loss, cracking) under continuous vibration loadings (fretting) at tube-grid contact of a tubular heat exchanger, a methodology for the identification and the estimation of the main damages was developed. Wear testing was based on a specific device devoted to fretting analyses. In the case studied a rapid and simple test has been set up to establish the so-called running condition fretting map. This methodology was applied to characterize the fretting behaviour of selected surface treated iron alloys as compared to the reference pair of the base material (SA 213 grade T91). Increment applied displacement (IAD) and constant normal load are used to determine the boundaries between the three fretting conditions which are stick, partial slip or gross slip. The IAD method is analyzed and validated by the means of a comparison with more sophisticated test techniques and surface analyses. From an Hertzian-like approach, several surface treatments and coatings were studied depending on the nature of the postulated damage (wear, cracking..). ''Surface treatment'' (nitriding..) or ''coatings'' (TiN, varnishes..) are described using required properties such as Young modulus, friction coefficient, residual stresses.. The simplified IAD method was used to enhance an a priori selection of surface treatments and to set guidelines for the development of coating well fitted with the industrial objectives. (orig.)

  12. The use of mathematical models in teaching wastewater treatment engineering

    DEFF Research Database (Denmark)

    Morgenroth, Eberhard Friedrich; Arvin, Erik; Vanrolleghem, P.

    2002-01-01

    Mathematical modeling of wastewater treatment processes has become increasingly popular in recent years. To prepare students for their future careers, environmental engineering education should provide students with sufficient background and experiences to understand and apply mathematical models...... efficiently and responsibly. Approaches for introducing mathematical modeling into courses on wastewater treatment engineering are discussed depending on the learning objectives, level of the course and the time available....

  13. Modeling and Solving the Liner Shipping Service Selection Problem

    DEFF Research Database (Denmark)

    Karsten, Christian Vad; Balakrishnan, Anant

    We address a tactical planning problem, the Liner Shipping Service Selection Problem (LSSSP), facing container shipping companies. Given estimated demand between various ports, the LSSSP entails selecting the best subset of non-simple cyclic sailing routes from a given pool of candidate routes...... requirements and the hop limits to reduce problem size, and describe techniques to accelerate the solution procedure. We present computational results for realistic problem instances from the benchmark suite LINER-LIB....

  14. An Integrated DEMATEL-QFD Model for Medical Supplier Selection

    OpenAIRE

    Mehtap Dursun; Zeynep Şener

    2014-01-01

    Supplier selection is considered as one of the most critical issues encountered by operations and purchasing managers to sharpen the company’s competitive advantage. In this paper, a novel fuzzy multi-criteria group decision making approach integrating quality function deployment (QFD) and decision making trial and evaluation laboratory (DEMATEL) method is proposed for supplier selection. The proposed methodology enables to consider the impacts of inner dependence among supplier assessment cr...

  15. Evaluation of uncertainties in selected environmental dispersion models

    International Nuclear Information System (INIS)

    Little, C.A.; Miller, C.W.

    1979-01-01

    Compliance with standards of radiation dose to the general public has necessitated the use of dispersion models to predict radionuclide concentrations in the environment due to releases from nuclear facilities. Because these models are only approximations of reality and because of inherent variations in the input parameters used in these models, their predictions are subject to uncertainty. Quantification of this uncertainty is necessary to assess the adequacy of these models for use in determining compliance with protection standards. This paper characterizes the capabilities of several dispersion models to predict accurately pollutant concentrations in environmental media. Three types of models are discussed: aquatic or surface water transport models, atmospheric transport models, and terrestrial and aquatic food chain models. Using data published primarily by model users, model predictions are compared to observations

  16. Model of Selective and Non-Selective Management of Badgers (Meles meles) to Control Bovine Tuberculosis in Badgers and Cattle.

    Science.gov (United States)

    Smith, Graham C; Delahay, Richard J; McDonald, Robbie A; Budgey, Richard

    2016-01-01

    Bovine tuberculosis (bTB) causes substantial economic losses to cattle farmers and taxpayers in the British Isles. Disease management in cattle is complicated by the role of the European badger (Meles meles) as a host of the infection. Proactive, non-selective culling of badgers can reduce the incidence of disease in cattle but may also have negative effects in the area surrounding culls that have been associated with social perturbation of badger populations. The selective removal of infected badgers would, in principle, reduce the number culled, but the effects of selective culling on social perturbation and disease outcomes are unclear. We used an established model to simulate non-selective badger culling, non-selective badger vaccination and a selective trap and vaccinate or remove (TVR) approach to badger management in two distinct areas: South West England and Northern Ireland. TVR was simulated with and without social perturbation in effect. The lower badger density in Northern Ireland caused no qualitative change in the effect of management strategies on badgers, although the absolute number of infected badgers was lower in all cases. However, probably due to differing herd density in Northern Ireland, the simulated badger management strategies caused greater variation in subsequent cattle bTB incidence. Selective culling in the model reduced the number of badgers killed by about 83% but this only led to an overall benefit for cattle TB incidence if there was no social perturbation of badgers. We conclude that the likely benefit of selective culling will be dependent on the social responses of badgers to intervention but that other population factors including badger and cattle density had little effect on the relative benefits of selective culling compared to other methods, and that this may also be the case for disease management in other wild host populations.

  17. Effects of selected operational parameters on efficacy and selectivity of electromembrane extraction. Chlorophenols as model analytes

    Czech Academy of Sciences Publication Activity Database

    Šlampová, Andrea; Kubáň, Pavel; Boček, Petr

    2014-01-01

    Roč. 35, č. 17 (2014), s. 2429-2437 ISSN 0173-0835 R&D Projects: GA ČR(CZ) GA13-05762S Institutional support: RVO:68081715 Keywords : electromembrane extraction * chlorophenols * extraction selectivity Subject RIV: CB - Analytical Chemistry, Separation Impact factor: 3.028, year: 2014

  18. National HIV prevalence estimates for sub-Saharan Africa: controlling selection bias with Heckman-type selection models

    Science.gov (United States)

    Hogan, Daniel R; Salomon, Joshua A; Canning, David; Hammitt, James K; Zaslavsky, Alan M; Bärnighausen, Till

    2012-01-01

    Objectives Population-based HIV testing surveys have become central to deriving estimates of national HIV prevalence in sub-Saharan Africa. However, limited participation in these surveys can lead to selection bias. We control for selection bias in national HIV prevalence estimates using a novel approach, which unlike conventional imputation can account for selection on unobserved factors. Methods For 12 Demographic and Health Surveys conducted from 2001 to 2009 (N=138 300), we predict HIV status among those missing a valid HIV test with Heckman-type selection models, which allow for correlation between infection status and participation in survey HIV testing. We compare these estimates with conventional ones and introduce a simulation procedure that incorporates regression model parameter uncertainty into confidence intervals. Results Selection model point estimates of national HIV prevalence were greater than unadjusted estimates for 10 of 12 surveys for men and 11 of 12 surveys for women, and were also greater than the majority of estimates obtained from conventional imputation, with significantly higher HIV prevalence estimates for men in Cote d'Ivoire 2005, Mali 2006 and Zambia 2007. Accounting for selective non-participation yielded 95% confidence intervals around HIV prevalence estimates that are wider than those obtained with conventional imputation by an average factor of 4.5. Conclusions Our analysis indicates that national HIV prevalence estimates for many countries in sub-Saharan African are more uncertain than previously thought, and may be underestimated in several cases, underscoring the need for increasing participation in HIV surveys. Heckman-type selection models should be included in the set of tools used for routine estimation of HIV prevalence. PMID:23172342

  19. Selection of a reference process for treatment of the West Valley alkaline waste

    International Nuclear Information System (INIS)

    Holton, L.K.; Wise, B.M.; Bray, L.A.; Pope, J.M.; Carl, D.E.

    1984-08-01

    As part of the West Valley Demonstration Project (WVDP) the alkaline PUREX supernatant stored in Tank 8D2 will be partially decontaminated by the removal of radiocesium. Four processes for removal of radiocesium from the alkaline supernatant were studied through experimentation and engineering analysis to identify a reference approach for the WVDP. These processes included the use of a zeolite inorganic ion-exchanger (Linde Ionsiv IE-95), an organic ion exchange resin (Duolite CS-100), and two precipitation processes; one using sodium tetraphenylboron (NaTPB) and the other using phosphotungstic acid (PTA). Based upon process performance, safety and environmental considerations, process and equipment complexity and impacts to the waste vitrification system, the zeolite ion-exchange process has been selected by West Valley Nuclear Services, Inc., as the reference supernatant treatment process for the WVDP. This paper will summarize the technical basis for the selection of the zeolite ion-exchange process. 4 figures, 2 tables

  20. [Sociological, legal and theological aspects of selection for treatment in myelomeningocele (author's transl)].

    Science.gov (United States)

    Holschneider, A M

    1977-06-24

    The arbitrary and arrogant presumption to be entitled to select cases for treatment amongst severely handicapped children cannot be justified at all, either from the legal or the theological point of view. The idea of selection can only be explained on the basis of the discrepancy in modern medicine between being forced, on the one hand, to continue in the tradition of the great biological and technical discoveries of the past decodes and, on the other hand, not being able to solve important current problems such as the determination of the time of death, the beginning of life or the inability to influence or prevent congenital malformations. The doctor, however, is charged against all exhortations of social Darwinism by society to help his patient to the best of his knowledge and skill.

  1. Reaction selectivity studies on nanolithographically-fabricated platinum model catalyst arrays

    Energy Technology Data Exchange (ETDEWEB)

    Grunes, Jeffrey Benjamin [Univ. of California, Berkeley, CA (United States)

    2004-05-01

    In an effort to understand the molecular ingredients of catalytic activity and selectivity toward the end of tuning a catalyst for 100% selectivity, advanced nanolithography techniques were developed and utilized to fabricate well-ordered two-dimensional model catalyst arrays of metal nanostructures on an oxide support for the investigation of reaction selectivity. In-situ and ex-situ surface science techniques were coupled with catalytic reaction data to characterize the molecular structure of the catalyst systems and gain insight into hydrocarbon conversion in heterogeneous catalysis. Through systematic variation of catalyst parameters (size, spacing, structure, and oxide support) and catalytic reaction conditions (hydrocarbon chain length, temperature, pressures, and gas composition), the data presented in this dissertation demonstrate the ability to direct a reaction by rationally adjusting, through precise control, the design of the catalyst system. Electron beam lithography (EBL) was employed to create platinum nanoparticles on an alumina (Al2O3) support. The Pt nanoparticle spacing (100-150-nm interparticle distance) was varied in these samples, and they were characterized using x-ray photoelectron spectroscopy (XPS), transmission electron microscopy (TEM), scanning electron microscopy (SEM), and atomic force microscopy (AFM), both before and after reactions. The TEM studies showed the 28-nm Pt nanoparticles with 100 and 150-nm interparticle spacing on alumina to be polycrystalline in nature, with crystalline sizes of 3-5 nm. The nanoparticle crystallites increased significantly after heat treatment. The nanoparticles were still mostly polycrystalline in nature, with 2-3 domains. The 28-nm Pt nanoparticles deposited on alumina were removed by the AFM tip in contact mode with a normal force of approximately 30 nN. After heat treatment at 500 C in vacuum for 3 hours, the AFM tip, even at 4000 nN, could not remove the platinum

  2. Effectiveness of Selected Stages of Wastewater Treatment in Elimination of Eggs of Intestinal Parasites

    Directory of Open Access Journals (Sweden)

    Zdybel Jolanta

    2015-04-01

    Full Text Available The objective of the study was to determine the degree of municipal wastewater contamination with intestinal parasite eggs of the genera Ascaris, Toxocara, and Trichuris at individual stages of treatment, and indication of potentially weak points in the hygienisation of sewage sludge. The study was conducted in 17 municipal mechanical-biological wastewater treatment plants which, to a slight degree, differed in the technological process of wastewater treatment and the method of hygienisation of sewage sludge. The selected treatment plants, located in seven regions, included five classified as large agglomerations (population equivalent - PE >100 000, ten as medium-size (PE 15 000-100 000, and two as smaller size with PE 10 000 - 5000. The largest number of viable eggs of Ascaris spp., Toxocara spp., and Trichuris spp. was found in the sewage sludge collected from the primary settling tank. A slightly lower number of the eggs were found in the samples of excess sludge, which indicates that the sedimentation process in the primary settling tank is not sufficiently long to effectively separate parasites’ eggs from the sewage treated. The number of eggs of Ascaris spp. and Toxocara spp. in the fermented sludge was nearly 3 times lower than that in the raw sludge. The effectiveness of hygienisation of dehydrated sewage sludge by means of quicklime was confirmed in two wastewater treatment plants, with respect to Ascaris spp. eggs, in three plants with respect to Toxocara spp. eggs, and in one plant with respect to Trichuris spp. eggs. The mean reduction of the number of eggs was 65%, 61%, and 100%, respectively. In one wastewater treatment plant, a reduction in the number of viable eggs of Ascaris and Trichuris species was also noted as a result of composting sludge by 85% and 75%, respectively. In the remaining treatment plants, no effect of hygienisation of sewage sludge was observed on the contents of viable eggs of these nematodes.

  3. Autotransplant tissue selection criteria with or without stereomicroscopy in parathyroidectomy for treatment of renal hyperparathyroidism

    Directory of Open Access Journals (Sweden)

    Monique Nakayama Ohe

    2014-07-01

    Full Text Available INTRODUCTION: Several methods have been proposed to improve operative success in renal hyperparathyroidism. OBJECTIVE: To evaluate stereomicroscopy in parathyroid tissue selection for total parathyroidectomy with autotransplantation in secondary (SHPT/tertiary (THPT hyperparathyroidism. METHODS: 118 renal patients underwent surgery from April of 2000 to October 2009. They were divided into two groups: G1, 66 patients operated from April of 2000 to May of 2005, with tissue selection based on macroscopic observation; G2, 52 patients operated from March of 2008 to October 2009 with stereomicroscopy for tissue selection searching for the presence of adipose cells. All surgeries were performed by the same surgeon. Patients presented SHPT (dialysis treatment or THPT (renal-grafted. Follow-up was 12-36 months. Intra-operative parathyroid hormone (PTH was measured in 100/118 (84.7% patients. RESULTS: Data are presented as means. G1 included 66 patients (38 SHPT, 24 females/14 males; 40.0 years of age; 28 THPT, 14 females/14 males; 44 years of age. G2 included 52 patients (29 SHPT, 11 females/18 males; 50.7 years of age; 23 THPT, 13 females/10 males, 44.4 years of age. SHPT patients from G2 presented preoperative serum calcium higher than those of SHPT patients in G1 (p < 0.05, suggesting a more severe disease. Definitive hypoparathyroidism was found in seven of 118 patients (5.9%. Graft-dependent recurrence occurred in four patients, two in each group. All occurred in dialysis patients. CONCLUSION: Stereomicroscopy in SHPT/THPT surgical treatment may be a useful tool to standardize parathyroid tissue selection.

  4. The role of magnetic resonance imaging to select patients for preoperative treatment in rectal cancer

    International Nuclear Information System (INIS)

    Roedel, Claus; Sauer, Rolf; Fietkau, Rainer

    2009-01-01

    Background: Traditionally, the decision to apply preoperative treatment for rectal cancer patients has been based on the T- and N-category. Recently, the radial distance of the tumor to the circumferential resection margin (CRM) has been identified as an important risk factor for local failure. By magnetic resonance imaging (MRI) this distance can be measured preoperatively with high reliability. Thus, selected groups have started to limit the indication for preoperative therapy to tumors extending to - or growing within 1 mm from - the mesorectal fascia (CRM+). Methods: Pros and cons of this selected approach for preoperative treatment and first clinical results are presented. Prerequisites are the availability of modern high-resolution thin-section MRI technology as well as strict quality control of MRI and surgical quality of total mesorectal excision (TME). Results: By selecting patients with CRM-positive tumors on MRI for preoperative therapy, only approximately 35% patients will require preoperative radiotherapy (RT) or radiochemotherapy (RCT). However, with histopathologic work-up of the resected specimen after primary surgery, the indication for postoperative RCT is given for a rather large percentage of patients, i.e., for pCRM+ (5-10%), intramesorectal or intramural excision (30-40%), pN+ (30-40%). Postoperative RCT, however, is significantly less effective and more toxic than preoperative RCT. A further point of concern is the assertion that patients, in whom a CRM-negative status is achieved by surgery alone, do not benefit from additional RT. Data of the Dutch TME trial and the British MRC (Medical Research Council) CR07 trial, however, suggest the reverse. Conclusion: To omit preoperative RT/RCT for CRM-negative tumors on MRI needs to be further investigated in prospective clinical trials. The German guidelines for the treatment of colorectal cancer 2008 continue to indicate preoperative RT/RCT based on the T- and N-category. (orig.)

  5. [The role of magnetic resonance imaging to select patients for preoperative treatment in rectal cancer].

    Science.gov (United States)

    Rödel, Claus; Sauer, Rolf; Fietkau, Rainer

    2009-08-01

    Traditionally, the decision to apply preoperative treatment for rectal cancer patients has been based on the T- and N-category. Recently, the radial distance of the tumor to the circumferential resection margin (CRM) has been identified as an important risk factor for local failure. By magnetic resonance imaging (MRI) this distance can be measured preoperatively with high reliability. Thus, selected groups have started to limit the indication for preoperative therapy to tumors extending to - or growing within 1 mm from - the mesorectal fascia (CRM+). Pros and cons of this selected approach for preoperative treatment and first clinical results are presented. Prerequisites are the availability of modern high-resolution thin-section MRI technology as well as strict quality control of MRI and surgical quality of total mesorectal excision (TME). By selecting patients with CRM-positive tumors on MRI for preoperative therapy, only approximately 35% patients will require preoperative radiotherapy (RT) or radiochemotherapy (RCT). However, with histopathologic work-up of the resected specimen after primary surgery, the indication for postoperative RCT is given for a rather large percentage of patients, i.e., for pCRM+ (5-10%), intramesorectal or intramural excision (30-40%), pN+ (30-40%). Postoperative RCT, however, is significantly less effective and more toxic than preoperative RCT. A further point of concern is the assertion that patients, in whom a CRM-negative status is achieved by surgery alone, do not benefit from additional RT. Data of the Dutch TME trial and the British MRC (Medical Research Council) CR07 trial, however, suggest the reverse. To omit preoperative RT/RCT for CRM-negative tumors on MRI needs to be further investigated in prospective clinical trials. The German guidelines for the treatment of colorectal cancer 2008 continue to indicate preoperative RT/RCT based on the T- and N-category.

  6. A selected controlled trial of supplementary vitamin E for treatment of muscle cramps in hemodialysis patients.

    Science.gov (United States)

    El-Hennawy, Adel S; Zaib, Salwat

    2010-01-01

    Muscle cramps are not uncommon complications of hemodialysis (HD) treatments and lead to early termination of HD sessions and are therefore a significant cause of under-dialysis. The etiology of cramps in dialysis patients remains a matter of debate. Many reports suggested that vitamin E (vit. E) may be effective for the prevention of HD-associated cramps. We decided to perform a selected controlled trial of supplementary vit. E for treatment of patients on HD who experience frequent attacks during and between HD sessions. The goal was to compare the number of attacks of muscle cramps with the patient's baseline over a specific period of time. In this study, 19 HD patients were randomly selected of different age groups and ethnicity. Patient must have had at least 60 attacks of muscle cramps during and between HD sessions over a 12-week period. All selected patients received vit. E at a dose of 400 international units daily for 12 weeks, and the number of attacks of muscle cramps was recorded. The frequency of muscle cramps decreased significantly during vit. E therapy, and, at the end of the trial, vit. E led to cramp reductions of 68.3%. The reduction in number of attacks of muscle cramps had no significant correlation with age, sex, etiology of end-stage renal disease, serum electrolytes, or HD duration, and it showed a statistically positive correlation (P = 0.0001) with vit. E therapy. No vit. E-related adverse effects were encountered during the trial. Short-term treatment with vit. E is safe and effective in reducing number of attacks of muscle cramps in HD patients, as shown in our study.

  7. 78 FR 20148 - Reporting Procedure for Mathematical Models Selected To Predict Heated Effluent Dispersion in...

    Science.gov (United States)

    2013-04-03

    ... mathematical modeling methods used in predicting the dispersion of heated effluent in natural water bodies. The... COMMISSION Reporting Procedure for Mathematical Models Selected To Predict Heated Effluent Dispersion in... Mathematical Models Selected to Predict Heated Effluent Dispersion in Natural Water Bodies.'' The guide is...

  8. Dasatinib for the treatment of chronic myeloid leukemia: patient selection and special considerations.

    Science.gov (United States)

    Keskin, Dilek; Sadri, Sevil; Eskazan, Ahmet Emre

    2016-01-01

    Dasatinib is one of the second-generation tyrosine kinase inhibitors used in imatinib resistance and/or intolerance, as well as in the frontline setting in patients with chronic myeloid leukemia-chronic phase, and also in patients with advanced disease. It is also utilized in Philadelphia chromosome-positive acute lymphocytic leukemia. While choosing the appropriate tyrosine kinase inhibitor (ie, dasatinib) for each individual patient, comorbidities and BCR-ABL1 kinase domain mutations should always be taken into consideration, among other things. This review mainly focuses on patient selection prior to dasatinib administration in the treatment of chronic myeloid leukemia.

  9. Bariatric surgery: the challenges with candidate selection, individualizing treatment and clinical outcomes

    Science.gov (United States)

    2013-01-01

    Obesity is recognized as a global health crisis. Bariatric surgery offers a treatment that can reduce weight, induce remission of obesity-related diseases, and improve the quality of life. In this article, we outline the different options in bariatric surgery and summarize the recommendations for selecting and assessing potential candidates before proceeding to surgery. We present current data on post-surgical outcomes and evaluate the psychosocial and economic effects of bariatric surgery. Finally, we evaluate the complication rates and present recommendations for post-operative care. PMID:23302153

  10. Selective serotonin-reuptake inhibitors for the treatment of hot flashes.

    Science.gov (United States)

    De Sloover Koch, Yvonne; Ernst, Michael E

    2004-01-01

    To review the literature evaluating the use of selective serotonin-reuptake inhibitors (SSRIs) for the treatment of hot flashes. Biomedical literature was accessed through MEDLINE (1966-June 2003), MD Consult, and references of reviewed articles. Key search terms used were hot flashes, vasomotor symptoms, antidepressants, and SSRIs. Recent evidence from the Women's Health Initiative precludes the use of traditional hormonal therapy in some women. Nonhormonal therapies are possible options, but conflicting evidence of efficacy exists. Although further studies are warranted, preliminary data suggest that SSRIs are generally modestly successful in reducing the frequency and severity of hot flashes.

  11. 3D Image Modelling and Specific Treatments in Orthodontics Domain

    Directory of Open Access Journals (Sweden)

    Dionysis Goularas

    2007-01-01

    Full Text Available In this article, we present a 3D specific dental plaster treatment system for orthodontics. From computer tomography scanner images, we propose first a 3D image modelling and reconstruction method of the Mandible and Maxillary based on an adaptive triangulation allowing management of contours meant for the complex topologies. Secondly, we present two specific treatment methods directly achieved on obtained 3D model allowing the automatic correction for the setting in occlusion of the Mandible and the Maxillary, and the teeth segmentation allowing more specific dental examinations. Finally, these specific treatments are presented via a client/server application with the aim of allowing a telediagnosis and treatment.

  12. Quantitative EEG Brain Mapping In Psychotropic Drug Development, Drug Treatment Selection, and Monitoring.

    Science.gov (United States)

    Itil, Turan M.; Itil, Kurt Z.

    1995-05-01

    Quantification of standard electroencephalogram (EEG) by digital computers [computer-analyzed EEG (CEEG)] has transformed the subjective analog EEG into an objective scientific method. Until a few years ago, CEEG was only used to assist in the development of psychotropic drugs by means of the quantitative pharmaco EEG. Thanks to the computer revolution and the accompanying reductions in cost of quantification, CEEG can now also be applied in psychiatric practice. CEEG can assist the physician in confirming clinical diagnoses, selecting psychotropic drugs for treatment, and drug treatment monitoring. Advancements in communications technology allow physicians and researchers to reduce the costs of acquiring a high-technology CEEG brain mapping system by utilizing the more economical telephonic services.

  13. Bioactive treatment promotes osteoblast differentiation on titanium materials fabricated by selective laser melting technology.

    Science.gov (United States)

    Tsukanaka, Masako; Fujibayashi, Shunsuke; Takemoto, Mitsuru; Matsushita, Tomiharu; Kokubo, Tadashi; Nakamura, Takashi; Sasaki, Kiyoyuki; Matsuda, Shuichi

    2016-01-01

    Selective laser melting (SLM) technology is useful for the fabrication of porous titanium implants with complex shapes and structures. The materials fabricated by SLM characteristically have a very rough surface (average surface roughness, Ra=24.58 µm). In this study, we evaluated morphologically and biochemically the specific effects of this very rough surface and the additional effects of a bioactive treatment on osteoblast proliferation and differentiation. Flat-rolled titanium materials (Ra=1.02 µm) were used as the controls. On the treated materials fabricated by SLM, we observed enhanced osteoblast differentiation compared with the flat-rolled materials and the untreated materials fabricated by SLM. No significant differences were observed between the flat-rolled materials and the untreated materials fabricated by SLM in their effects on osteoblast differentiation. We concluded that the very rough surface fabricated by SLM had to undergo a bioactive treatment to obtain a positive effect on osteoblast differentiation.

  14. Cancer treatment model with the Caputo-Fabrizio fractional derivative

    Science.gov (United States)

    Ali Dokuyucu, Mustafa; Celik, Ercan; Bulut, Hasan; Mehmet Baskonus, Haci

    2018-03-01

    In this article, a model for cancer treatment is examined. The model is integrated into the Caputo-Fabrizio fractional derivative first, to examine the existence of the solution. Then, the uniqueness of the solution is investigated and we identified under which conditions the model provides a unique solution.

  15. Impact of periodic selective mebendazole treatment on soil-transmitted helminth infections in Cuban schoolchildren.

    Science.gov (United States)

    van der Werff, Suzanne D; Vereecken, Kim; van der Laan, Kim; Campos Ponce, Maiza; Junco Díaz, Raquel; Núñez, Fidel A; Rojas Rivero, Lázara; Bonet Gorbea, Mariano; Polman, Katja

    2014-06-01

    To evaluate the impact of periodic selective treatment with 500 mg mebendazole on soil-transmitted helminth (STH) infections in Cuban schoolchildren. We followed up a cohort of 268 STH-positive schoolchildren, aged 5-14 years at baseline, at six-month intervals for two years and a final follow-up after three years. Kato-Katz stool examination was used to detect infections with Ascaris lumbricoides, Trichuris trichiura and hookworm. Common risk factors related to STHs were assessed by parental questionnaire. A significant reduction in the number of STH infections was obtained after three years with the highest reduction for T. trichiura (87.8%) and the lowest for hookworm (57.9%). After six months, cure rates (CRs) were 76.9% for A. lumbricoides, 67.4% for T. trichiura and 44.4% for hookworm. After two treatment rounds, more than 75% of all STH-positive children at baseline were cured, but with important differences between STH species (95.2% for A. lumbricoides, 80.5% for T. trichiura and 76.5% for hookworm). At the end of the study, these cumulative CRs were almost 100% for all three STHs. Risk factors for STHs were sex, sanitary disposal and habit of playing in the soil. Our results indicate that periodic selective treatment with 500 mg mebendazole is effective in reducing the number of STH infections in Cuban schoolchildren. Although important differences were found between helminth species, two rounds of treatment appeared sufficient to obtain substantial reductions. © 2014 John Wiley & Sons Ltd.

  16. Selective androgen receptor modulators for the prevention and treatment of muscle wasting associated with cancer.

    Science.gov (United States)

    Dalton, James T; Taylor, Ryan P; Mohler, Michael L; Steiner, Mitchell S

    2013-12-01

    This review highlights selective androgen receptor modulators (SARMs) as emerging agents in late-stage clinical development for the prevention and treatment of muscle wasting associated with cancer. Muscle wasting, including a loss of skeletal muscle, is a cancer-related symptom that begins early in the progression of cancer and affects a patient's quality of life, ability to tolerate chemotherapy, and survival. SARMs increase muscle mass and improve physical function in healthy and diseased individuals, and potentially may provide a new therapy for muscle wasting and cancer cachexia. SARMs modulate the same anabolic pathways targeted with classical steroidal androgens, but within the dose range in which expected effects on muscle mass and function are seen androgenic side-effects on prostate, skin, and hair have not been observed. Unlike testosterone, SARMs are orally active, nonaromatizable, nonvirilizing, and tissue-selective anabolic agents. Recent clinical efficacy data for LGD-4033, MK-0773, MK-3984, and enobosarm (GTx-024, ostarine, and S-22) are reviewed. Enobosarm, a nonsteroidal SARM, is the most well characterized clinically, and has consistently demonstrated increases in lean body mass and better physical function across several populations along with a lower hazard ratio for survival in cancer patients. Completed in May 2013, results for the Phase III clinical trials entitled Prevention and treatment Of muscle Wasting in patiEnts with Cancer1 (POWER1) and POWER2 evaluating enobosarm for the prevention and treatment of muscle wasting in patients with nonsmall cell lung cancer will be available soon, and will potentially establish a SARM, enobosarm, as the first drug for the prevention and treatment of muscle wasting in cancer patients.

  17. Selection of a bioassay battery to assess toxicity in the affluents and effluents of three water-treatment plants

    Directory of Open Access Journals (Sweden)

    Paola Bohórquez-Echeverry

    2012-08-01

    Full Text Available The assessment of water quality includes the analysis of both physical-chemical and microbiological parameters. However,none of these evaluates the biological effect that can be generated in ecosystems or humans. In order to define the most suitable organismsto evaluate the toxicity in the affluent and effluent of three drinking-water treatment plants, five acute toxicity bioassays were used,incorporating three taxonomic groups of the food chain. Materials and methods. The bioassays used were Daphnia magna and Hydraattenuata as animal models, Lactuca sativa and Pseudokirchneriella subcapitata as plant models, and Photobacterium leioghnathi asbacterial model. To meet this objective, selection criteria of the organisms evaluated and cluster analysis were used to identify the mostsensitive in the affluent and effluent of each plant. Results. All organisms are potentially useful in the assessment of water quality bymeeting four essential requirements and 17 desirable requirements equivalent to 100% acceptability, except P. leioghnathi which doesnot meet two essential requirements that are the IC50 for the toxic reference and the confidence interval. The animal, plant and bacterialmodels showed different levels of sensitivity at the entrance and exit of the water treatment systems. Conclusions. H. attenuata, P.subcapitata and P. leioghnathi were the most effective organisms in detecting toxicity levels in the affluents and D. magna, P. subcapitataand P. leioghnathi in the effluents.

  18. Selection of ESBL-Producing E. coli in a Mouse Intestinal Colonization Model.

    Science.gov (United States)

    Hertz, Frederik Boëtius; Nielsen, Karen Leth; Frimodt-Møller, Niels

    2018-01-01

    Asymptomatic human carriage of antimicrobially drug-resistant pathogens prior to infection is increasing worldwide. Further investigation into the role of this fecal reservoir is important for combatting the increasing antimicrobial resistance problems. Additionally, the damage on the intestinal microflora due to antimicrobial treatment is still not fully understood. Animal models are powerful tools to investigate bacterial colonization subsequent to antibiotic treatment. In this chapter we present a mouse-intestinal colonization model designed to investigate how antibiotics select for an ESBL-producing E. coli isolate. The model can be used to study how antibiotics with varying effect on the intestinal flora promote the establishment of the multidrug-resistant E. coli. Colonization is successfully investigated by sampling and culturing stool during the days following administration of antibiotics. Following culturing, a precise identification of the bacterial strain found in mice feces is applied to ensure that the isolate found is in fact identical to the strain used for inoculation. For this purpose random amplified of polymorphic DNA (RAPD) PCR specifically developed for E. coli is applied. This method allows us to distinguish E. coli with more than 99.95% genome similarity using a duplex PCR method.

  19. Natural Selection at Work: An Accelerated Evolutionary Computing Approach to Predictive Model Selection

    Science.gov (United States)

    Akman, Olcay; Hallam, Joshua W.

    2010-01-01

    We implement genetic algorithm based predictive model building as an alternative to the traditional stepwise regression. We then employ the Information Complexity Measure (ICOMP) as a measure of model fitness instead of the commonly used measure of R-square. Furthermore, we propose some modifications to the genetic algorithm to increase the overall efficiency. PMID:20661297

  20. Natural selection at work: an accelerated evolutionary computing approach to predictive model selection

    Directory of Open Access Journals (Sweden)

    Olcay Akman

    2010-07-01

    Full Text Available We implement genetic algorithm based predictive model building as an alternative to the traditional stepwise regression. We then employ the Information Complexity Measure (ICOMP as a measure of model fitness instead of the commonly used measure of R-square. Furthermore, we propose some modifications to the genetic algorithm to increase the overall efficiency.

  1. A rationale and model for addressing tobacco dependence in substance abuse treatment

    Directory of Open Access Journals (Sweden)

    Richter Kimber P

    2006-08-01

    Full Text Available Abstract Most persons in drug treatment smoke cigarettes. Until drug treatment facilities systematically treat their patients' tobacco use, millions will flow through the drug treatment system, overcome their primary drug of abuse, but die prematurely from tobacco-related illnesses. This paper reviews the literature on the health benefits of quitting smoking for drug treatment patients, whether smoking causes relapse to other drug or alcohol abuse, the treatment of tobacco dependence, and good and bad times for quitting smoking among drug treatment patients. It also presents a conceptual model and recommendations for treating tobacco in substance abuse treatment, and provides references to internet and paper-copy tools and information for treating tobacco dependence. At present, research on tobacco treatment in drug treatment is in its infancy. Although few drug treatment programs currently offer formal services, many more will likely begin to treat nicotine dependence as external forces and patient demand for these services increases. In the absence of clear guidelines and attention to quality of care, drug treatment programs may adopt smoking cessation services based on cost, convenience, or selection criteria other than efficacy. Because research in this field is relatively new, substance abuse treatment professionals should adhere to the standards of care for the general population, but be prepared to update their practices with emerging interventions that have proven to be effective for patients in drug treatment.

  2. Selection of the surface water treatment technology - a full-scale technological investigation.

    Science.gov (United States)

    Pruss, Alina

    2015-01-01

    A technological investigation was carried out over a period of 2 years to evaluate surface water treatment technology. The study was performed in Poland, in three stages. From November 2011 to July 2012, for the first stage, flow tests with a capacity of 0.1-1.5 m³/h were performed simultaneously in three types of technical installations differing by coagulation modules. The outcome of the first stage was the choice of the technology for further investigation. The second stage was performed between September 2012 and March 2013 on a full-scale water treatment plant. Three large technical installations, operated in parallel, were analysed: coagulation with sludge flotation, micro-sand ballasted coagulation with sedimentation, coagulation with sedimentation and sludge recirculation. The capacity of the installations ranged from 10 to 40 m³/h. The third stage was also performed in a full-scale water treatment plant and was aimed at optimising the selected technology. This article presents the results of the second stage of the full-scale investigation. The critical treatment process, for the analysed water, was the coagulation in an acidic environment (6.5 < pH < 7.0) carried out in a system with rapid mixing, a flocculation chamber, preliminary separation of coagulation products, and removal of residual suspended solids through filtration.

  3. Application of antioxidant indicators to select nicotine-degrading bacterium for bioaugmented treatment of tobacco wastewater

    International Nuclear Information System (INIS)

    Hongzhen, H.; Zheng, X.

    2013-01-01

    To select nicotine-degrading bacterium for bioaugmented treatment of tobacco wastewater, the activities of antioxidant indicators such as superoxide dismutase (SOD), catalase (CAT) and glutathione (GSH), and the ability to treat pollutants including nicotine degradation and chemical oxygen demand (COD) removal, were compared between Acinetobacter sp. TW and Sphingomonas sp. TY. When complicated toxins were present, the activities of SOD induced in strain TY were significantly higher than those in strain TW. However, the activities of CAT were inhibited in strain TY (CAT/CATLB 1). Additionally, the levels of GSH induced in strain TW were significantly higher than those in strain TY. These findings suggest that the antioxidant ability of strain TW was higher than that of strain TY, especially in tobacco wastewater. Moreover, when applied to the treatment of tobacco wastewater, the rate of nicotine degradation at 24 h was 99.50% for TW and 28.76% for TY, while the rate of COD removal at 48 h was 62.69% for TW and 45.80% for TY. Taken together, these findings indicate that the pollution treatment ability of strain TW was stronger than that of TY, and that the stronger the ability of the antioxidant, the higher the potential for treatment of tobacco wastewater. (author)

  4. Selection of hydrothermal pre-treatment conditions of waste sludge destruction using multicriteria decision-making.

    Science.gov (United States)

    Al-Shiekh Khalil, Wael; Shanableh, Abdullah; Rigby, Portia; Kokot, Serge

    2005-04-01

    The effectiveness of hydrothermal treatment for the destruction of the organic content of sludge waste was investigated. The sludge sampled in this study contained approximately 2% solids. The experimental program consisted of hydrothermal treatment experiments conducted in a batch reactor at temperatures between 100 and 250 degrees C, with the addition of an oxidant (hydrogen peroxide) in the range of 0-150% with reference to TCOD, and reaction times of up to 60 min. The results suggested that the availability of oxidant, reaction temperature and reaction time were the determining factors for COD removal. A significant fraction of the COD remaining after treatment consisted of the dissolved COD. The results confirmed that hydrothermal treatment proceeds through hydrolysis resulting in the production of dissolved organic products followed by COD removal through oxidation. Two MCDM chemometrics methods, PROMETHEE and GAIA, were applied to process the large data matrix so as to facilitate the selection of the most suitable hydrothermal conditions for sludge destruction. Two possible scenarios were produced from this analysis-one depended on the use of high temperatures and no oxidant, while the second offered a choice of compromise solutions at lower temperatures but with the use of at least some oxidant. Thus, for the final choice of operating conditions, the decision maker needs local knowledge of the costs and available infrastructure. In principle, such information could be added as further criteria to the data matrix and new rankings obtained.

  5. Variable selection for confounder control, flexible modeling and Collaborative Targeted Minimum Loss-based Estimation in causal inference

    Science.gov (United States)

    Schnitzer, Mireille E.; Lok, Judith J.; Gruber, Susan

    2015-01-01

    This paper investigates the appropriateness of the integration of flexible propensity score modeling (nonparametric or machine learning approaches) in semiparametric models for the estimation of a causal quantity, such as the mean outcome under treatment. We begin with an overview of some of the issues involved in knowledge-based and statistical variable selection in causal inference and the potential pitfalls of automated selection based on the fit of the propensity score. Using a simple example, we directly show the consequences of adjusting for pure causes of the exposure when using inverse probability of treatment weighting (IPTW). Such variables are likely to be selected when using a naive approach to model selection for the propensity score. We describe how the method of Collaborative Targeted minimum loss-based estimation (C-TMLE; van der Laan and Gruber, 2010) capitalizes on the collaborative double robustness property of semiparametric efficient estimators to select covariates for the propensity score based on the error in the conditional outcome model. Finally, we compare several approaches to automated variable selection in low-and high-dimensional settings through a simulation study. From this simulation study, we conclude that using IPTW with flexible prediction for the propensity score can result in inferior estimation, while Targeted minimum loss-based estimation and C-TMLE may benefit from flexible prediction and remain robust to the presence of variables that are highly correlated with treatment. However, in our study, standard influence function-based methods for the variance underestimated the standard errors, resulting in poor coverage under certain data-generating scenarios. PMID:26226129

  6. A bio-mathematical model for parallel organs and its use in ranking radiation treatment plans.

    Science.gov (United States)

    Wang, Li; Li, Wenhui; Bai, Han; Chang, Li; Qin, Jiyong; Hou, Yu

    2012-12-01

    To develop a new bio-mathematical model, named LQ-based parallel-organ model, that can overcome the limitation of interpreting the simple dose-volume information so as to rank the radio- toxicity of parallel organs in the same patient. A parallel organ consists of Function Subunits (FSUs), with each FSU being equal and representative in functional status. Based on the Linear-Quadratic model (LQ model), we had derived a bio-mathematical model to calculate the survival cell number for radiation dose response. We then compared the cell survival number for the ranking of treatment plans for the same patient. Ninety 3D plans from forty-five randomly selected lung cancer patients were generated using the ELEKTA precise 2.12 treatment planning system. The LQ-based parallel-organ model was tested against the widely used Lyman-Kutcher-Burman model (LKB model). There was no distinct statistical difference in plan ranking between using the LQ-based parallel-organ model and the LKB model (P = 0.475). Ranking plans by the V(x), Mean Lung Dose (MLD) and the LQ-based parallel-organ model shows that there was no distinct statistical difference between V(5), V(10), V(20), MLD and the LQ-based parallel-organ model, respectively (all Ps > 0.05). The proposed LQ-based parallel-organ model was found to be efficient and reliable for ranking treatment plans for the same patient.

  7. Selection bias in species distribution models: An econometric approach on forest trees based on structural modeling

    Science.gov (United States)

    Martin-StPaul, N. K.; Ay, J. S.; Guillemot, J.; Doyen, L.; Leadley, P.

    2014-12-01

    Species distribution models (SDMs) are widely used to study and predict the outcome of global changes on species. In human dominated ecosystems the presence of a given species is the result of both its ecological suitability and human footprint on nature such as land use choices. Land use choices may thus be responsible for a selection bias in the presence/absence data used in SDM calibration. We present a structural modelling approach (i.e. based on structural equation modelling) that accounts for this selection bias. The new structural species distribution model (SSDM) estimates simultaneously land use choices and species responses to bioclimatic variables. A land use equation based on an econometric model of landowner choices was joined to an equation of species response to bioclimatic variables. SSDM allows the residuals of both equations to be dependent, taking into account the possibility of shared omitted variables and measurement errors. We provide a general description of the statistical theory and a set of applications on forest trees over France using databases of climate and forest inventory at different spatial resolution (from 2km to 8km). We also compared the outputs of the SSDM with outputs of a classical SDM (i.e. Biomod ensemble modelling) in terms of bioclimatic response curves and potential distributions under current climate and climate change scenarios. The shapes of the bioclimatic response curves and the modelled species distribution maps differed markedly between SSDM and classical SDMs, with contrasted patterns according to species and spatial resolutions. The magnitude and directions of these differences were dependent on the correlations between the errors from both equations and were highest for higher spatial resolutions. A first conclusion is that the use of classical SDMs can potentially lead to strong miss-estimation of the actual and future probability of presence modelled. Beyond this selection bias, the SSDM we propose represents

  8. Model Selection and Risk Estimation with Applications to Nonlinear Ordinary Differential Equation Systems

    DEFF Research Database (Denmark)

    Mikkelsen, Frederik Vissing

    Broadly speaking, this thesis is devoted to model selection applied to ordinary dierential equations and risk estimation under model selection. A model selection framework was developed for modelling time course data by ordinary dierential equations. The framework is accompanied by the R software...... eective computational tools for estimating unknown structures in dynamical systems, such as gene regulatory networks, which may be used to predict downstream eects of interventions in the system. A recommended algorithm based on the computational tools is presented and thoroughly tested in various...... simulation studies and applications. The second part of the thesis also concerns model selection, but focuses on risk estimation, i.e., estimating the error of mean estimators involving model selection. An extension of Stein's unbiased risk estimate (SURE), which applies to a class of estimators with model...

  9. Model selection criteria : how to evaluate order restrictions

    NARCIS (Netherlands)

    Kuiper, R.M.

    2012-01-01

    Researchers often have ideas about the ordering of model parameters. They frequently have one or more theories about the ordering of the group means, in analysis of variance (ANOVA) models, or about the ordering of coefficients corresponding to the predictors, in regression models.A researcher might

  10. The Selection of Turbulence Models for Prediction of Room Airflow

    DEFF Research Database (Denmark)

    Nielsen, Peter V.

    This paper discusses the use of different turbulence models and their advantages in given situations. As an example, it is shown that a simple zero-equation model can be used for the prediction of special situations as flow with a low level of turbulence. A zero-equation model with compensation...

  11. New framework for standardized notation in wastewater treatment modelling

    DEFF Research Database (Denmark)

    Corominas, L.; Rieger, L.; Takacs, I.

    2010-01-01

    Many unit process models are available in the field of wastewater treatment. All of these models use their own notation, causing problems for documentation, implementation and connection of different models (using different sets of state variables). The main goal of this paper is to propose a new...... is a framework that can be used in whole plant modelling, which consists of different fields such as activated sludge, anaerobic digestion, sidestream treatment, membrane bioreactors, metabolic approaches, fate of micropollutants and biofilm processes. The main objective of this consensus building paper...... is to establish a consistent set of rules that can be applied to existing and most importantly, future models. Applying the proposed notation should make it easier for everyone active in the wastewater treatment field to read, write and review documents describing modelling projects....

  12. General quality of life of patients with acne vulgaris before and after performing selected cosmetological treatments

    Directory of Open Access Journals (Sweden)

    Chilicka K

    2017-08-01

    Full Text Available Karolina Chilicka,1 Joanna Maj,2 Bernard Panaszek3 1Department of Cosmetology, Opole Medical School, Opole, 2Department of Dermatology, Venereology and Allergology, 3Department of Internal Medicine and Allergy, Wroclaw Medical University, Wrocław, Poland Background: Achieving a satisfying quality of life for a patient by applying individually matched therapy is, simultaneously, a great challenge and a priority for contemporary medicine. Patients with visible dermatological ailments are particularly susceptible to reduction in the general quality of life. Among the dermatological diseases, acne causes considerable reduction in the quality of life and changes in self-perception that lead to the worsening of a patient’s mental condition, including depression and suicidal thoughts. As a result, difficulties in contact with loved ones, as well as social and professional problems are observed, which show that acne is not a somatic problem alone. To a large extent, it becomes a part of psychodermatology, becoming an important topic of public health in social medicine practice. Pharmacological treatment of acne is a challenge for a dermatologist and often requires the necessity of cooperating with a cosmetologist. Cosmetological treatments are aimed at improving the condition of the skin and reduction or subsiding of acne skin changes.Aim: The aim of this study was to assess the influence of selected cosmetological treatments on the general quality of life of patients with acne.Materials and methods: The study group consisted of 101 women aged 19–29 years (x̅  =22.5 years, SD =2.3 years. All subjects were diagnosed with acne vulgaris of the face. In the study group, the acne changes occurred over the course of 3–15 years (x̅ =8.1 years, SD =2.7 years. Selected cosmetological treatments (intensive pulsing light, alpha-hydroxy acids, cavitation peeling, needle-free mesotherapy, diamond microdermabrasion and sonophoresis were performed in

  13. Selective treatment of carious dentin using a mid-infrared tunable pulsed laser at 6 μm wavelength range

    Science.gov (United States)

    Saiki, Masayuki; Ishii, Katsunori; Yoshikawa, Kazushi; Yasuo, Kenzo; Yamamoto, Kazuyo; Awazu, Kunio

    2011-03-01

    Optical technologies have good potential for caries detection, prevention, excavation, and the realization of minimal intervention dentistry. This study aimed to develop a selective excavation technique of carious tissue using the specific absorption in 6 μm wavelength range. Bovine dentin demineralized with lactic acid solution was used as a carious dentin model. A mid-infrared tunable pulsed laser was obtained by difference-frequency generation technique. The wavelength was tuned to 6.02 and 6.42 μm which correspond to absorption bands called amide I and amide II, respectively. The laser delivers 5 ns pulse width at a repetition rate of 10 Hz. The morphological change after irradiation was observed with a scanning electron microscope, and the measurement of ablation depth was performed with a confocal laser microscope. At λ = 6.02 μm and the average power density of 15 W/cm2, demineralized dentin was removed selectively with less-invasive effect on sound dentin. The wavelength of 6.42 μm also showed the possibility of selective removal. High ablation efficiency and low thermal side effect were observed using the nanosecond pulsed laser with λ = 6.02 μm. In the near future, development of compact laser device will open the minimal invasive laser treatment to the dental clinic.

  14. Variable Selection for Nonparametric Gaussian Process Priors: Models and Computational Strategies.

    Science.gov (United States)

    Savitsky, Terrance; Vannucci, Marina; Sha, Naijun

    2011-02-01

    This paper presents a unified treatment of Gaussian process models that extends to data from the exponential dispersion family and to survival data. Our specific interest is in the analysis of data sets with predictors that have an a priori unknown form of possibly nonlinear associations to the response. The modeling approach we describe incorporates Gaussian processes in a generalized linear model framework to obtain a class of nonparametric regression models where the covariance matrix depends on the predictors. We consider, in particular, continuous, categorical and count responses. We also look into models that account for survival outcomes. We explore alternative covariance formulations for the Gaussian process prior and demonstrate the flexibility of the construction. Next, we focus on the important problem of selecting variables from the set of possible predictors and describe a general framework that employs mixture priors. We compare alternative MCMC strategies for posterior inference and achieve a computationally efficient and practical approach. We demonstrate performances on simulated and benchmark data sets.

  15. Mathematical model for HIV spreads control program with ART treatment

    Science.gov (United States)

    Maimunah; Aldila, Dipo

    2018-03-01

    In this article, using a deterministic approach in a seven-dimensional nonlinear ordinary differential equation, we establish a mathematical model for the spread of HIV with an ART treatment intervention. In a simplified model, when no ART treatment is implemented, disease-free and the endemic equilibrium points were established analytically along with the basic reproduction number. The local stability criteria of disease-free equilibrium and the existing criteria of endemic equilibrium were analyzed. We find that endemic equilibrium exists when the basic reproduction number is larger than one. From the sensitivity analysis of the basic reproduction number of the complete model (with ART treatment), we find that the increased number of infected humans who follow the ART treatment program will reduce the basic reproduction number. We simulate this result also in the numerical experiment of the autonomous system to show how treatment intervention impacts the reduction of the infected population during the intervention time period.

  16. Modelling the effects of treatment and quarantine on measles

    Science.gov (United States)

    Beay, Lazarus Kalvein

    2018-03-01

    Treatment and quarantine are efforts to cure as well as to overcome the spread of diseases including measles. The spread of measles can be expressed by mathematical modelling in the form of nonlinear dynamical systems. In this study was conducted on the spread of measles by considering the effect of treatment and quarantine on the infected individuals. By using the basic reproduction number of the model, can be analyzed the effects of treatment and quarantine to reduce the spread of measles. Basic reproduction number of models is monotonically descreasing as treatment and quarantine increasing. Numerical simulations conducted on the analysis of the results. The results showed that treatment and quarantine was given to infected individuals who were infectious has a major influence to eliminate measles from the system.

  17. Selection of Steady-State Process Simulation Software to Optimize Treatment of Radioactive and Hazardous Waste

    International Nuclear Information System (INIS)

    Nichols, T. T.; Barnes, C. M.; Lauerhass, L.; Taylor, D. D.

    2001-01-01

    The process used for selecting a steady-state process simulator under conditions of high uncertainty and limited time is described. Multiple waste forms, treatment ambiguity, and the uniqueness of both the waste chemistries and alternative treatment technologies result in a large set of potential technical requirements that no commercial simulator can totally satisfy. The aim of the selection process was two-fold. First, determine the steady-state simulation software that best, albeit not completely, satisfies the requirements envelope. And second, determine if the best is good enough to justify the cost. Twelve simulators were investigated with varying degrees of scrutiny. The candidate list was narrowed to three final contenders: ASPEN Plus 10.2, PRO/II 5.11, and CHEMCAD 5.1.0. It was concluded from ''road tests'' that ASPEN Plus appears to satisfy the project's technical requirements the best and is worth acquiring. The final software decisions provide flexibility: they involve annual rather than multi-year licensing, and they include periodic re-assessment

  18. Economic evaluation and efficacy of strategic-selective treatment of gastrointestinal parasites in dairy calves

    Directory of Open Access Journals (Sweden)

    Yuly Andrea Caicedo Blanco

    Full Text Available Abstract In the Experimental Farm of the Universidade Federal de Lavras (EF-UFLA, state of Minas Gerais, Brazil, on their day of birth, female Holstein calves were randomly selected and placed into two groups containing fifteen animals each: Strategic-Selective Treatment (S-ST or Conventional Treatment (CT. In the S-ST, calves were treated after coproparasitological examinations according to criteria established previously by the researchers. Calves in the CT were treated according to the opinion of the veterinarian of EF-UFLA. For statistical analysis, the frequency (% of fecal samples with count of eggs per gram of feces (EPG ≥300, count of oocysts per gram of feces (OoPG ≥500 and fecal samples with count of cysts of Giardia spp. ≥1 were conducted. The overall average frequency of fecal samples with EPG ≥300, OoPG ≥500 and Giardia spp. cysts ≥1, respectively, was similar (p >0.05 between S-ST (20.3%; 17.3%; and 31.5% and CT (26.4%; 23.9%; and 37.3%. The effective operational cost, per animal, in 12 months, was of R$ 784.58 (US$ 241.41 and R$ 83.90 (US$ 25.81 in S-ST and CT, respectively. The S-ST requires adjustments to be used as a technically efficient and economically viable alternative for the control of gastrointestinal parasitosis in female Holstein calves.

  19. Female infertility in India: Causes, treatment and impairment of fertility in selected districts with high prevalence

    Directory of Open Access Journals (Sweden)

    Shraboni Patra

    2017-01-01

    Full Text Available Although the ‘universal access to sexual and reproductive health care’ has received priority in the SDG‐3, the rural women experiencing infertility problem in India are unable to access and afford quality reproductive health care. The study investigates the present infertility situation, with a focus on risk factors, treatment seeking for infertility, and impact of infertility on fertility in India and its districts with high infertility prevalence. The DLHS‐3 data is used. Top fifteen districts with high infertility prevalence are selected for analysis. Simple bivariate and multivariate techniques are applied. In India, the prevalence of ever‐experienced primary, secondary, and current infertility is 6.6%, 2.1% and 4.6% respectively, whereas, in the selected districts, the estimates for the same indicators are 15%, 3.1%, and 5% respectively. A higher prevalence of reported symptoms of RTIs/STIs and menstrual problems is observed among women who ever had infertility. Treatment seeking for infertility is low in Korba and Koryia. The MCEB is less among women who ever had experienced infertility. The prevalence of ever‐experienced infertility and current infertility is considerably higher among women from socio‐economically disadvantaged sections. Awareness of RTIs, STIs, and menstrual problems, and preventive care can reduce infertility among rural women.

  20. A surrogate-based metaheuristic global search method for beam angle selection in radiation treatment planning.

    Science.gov (United States)

    Zhang, H H; Gao, S; Chen, W; Shi, L; D'Souza, W D; Meyer, R R

    2013-03-21

    An important element of radiation treatment planning for cancer therapy is the selection of beam angles (out of all possible coplanar and non-coplanar angles in relation to the patient) in order to maximize the delivery of radiation to the tumor site and minimize radiation damage to nearby organs-at-risk. This category of combinatorial optimization problem is particularly difficult because direct evaluation of the quality of treatment corresponding to any proposed selection of beams requires the solution of a large-scale dose optimization problem involving many thousands of variables that represent doses delivered to volume elements (voxels) in the patient. However, if the quality of angle sets can be accurately estimated without expensive computation, a large number of angle sets can be considered, increasing the likelihood of identifying a very high quality set. Using a computationally efficient surrogate beam set evaluation procedure based on single-beam data extracted from plans employing equallyspaced beams (eplans), we have developed a global search metaheuristic process based on the nested partitions framework for this combinatorial optimization problem. The surrogate scoring mechanism allows us to assess thousands of beam set samples within a clinically acceptable time frame. Tests on difficult clinical cases demonstrate that the beam sets obtained via our method are of superior quality.

  1. A surrogate-based metaheuristic global search method for beam angle selection in radiation treatment planning

    International Nuclear Information System (INIS)

    Zhang, H H; D’Souza, W D; Gao, S; Shi, L; Chen, W; Meyer, R R

    2013-01-01

    An important element of radiation treatment planning for cancer therapy is the selection of beam angles (out of all possible coplanar and non-coplanar angles in relation to the patient) in order to maximize the delivery of radiation to the tumor site and minimize radiation damage to nearby organs-at-risk. This category of combinatorial optimization problem is particularly difficult because direct evaluation of the quality of treatment corresponding to any proposed selection of beams requires the solution of a large-scale dose optimization problem involving many thousands of variables that represent doses delivered to volume elements (voxels) in the patient. However, if the quality of angle sets can be accurately estimated without expensive computation, a large number of angle sets can be considered, increasing the likelihood of identifying a very high quality set. Using a computationally efficient surrogate beam set evaluation procedure based on single-beam data extracted from plans employing equally-spaced beams (eplans), we have developed a global search metaheuristic process based on the nested partitions framework for this combinatorial optimization problem. The surrogate scoring mechanism allows us to assess thousands of beam set samples within a clinically acceptable time frame. Tests on difficult clinical cases demonstrate that the beam sets obtained via our method are of superior quality. (paper)

  2. Selection of Steady-State Process Simulation Software to Optimize Treatment of Radioactive and Hazardous Waste

    Energy Technology Data Exchange (ETDEWEB)

    Nichols, Todd Travis; Barnes, Charles Marshall; Lauerhass, Lance; Taylor, Dean Dalton

    2001-06-01

    The process used for selecting a steady-state process simulator under conditions of high uncertainty and limited time is described. Multiple waste forms, treatment ambiguity, and the uniqueness of both the waste chemistries and alternative treatment technologies result in a large set of potential technical requirements that no commercial simulator can totally satisfy. The aim of the selection process was two-fold. First, determine the steady-state simulation software that best, albeit not completely, satisfies the requirements envelope. And second, determine if the best is good enough to justify the cost. Twelve simulators were investigated with varying degrees of scrutiny. The candidate list was narrowed to three final contenders: ASPEN Plus 10.2, PRO/II 5.11, and CHEMCAD 5.1.0. It was concluded from "road tests" that ASPEN Plus appears to satisfy the project's technical requirements the best and is worth acquiring. The final software decisions provide flexibility: they involve annual rather than multi-year licensing, and they include periodic re-assessment.

  3. Selection of Steady-State Process Simulation Software to Optimize Treatment of Radioactive and Hazardous Waste

    Energy Technology Data Exchange (ETDEWEB)

    Nichols, T. T.; Barnes, C. M.; Lauerhass, L.; Taylor, D. D.

    2001-06-01

    The process used for selecting a steady-state process simulator under conditions of high uncertainty and limited time is described. Multiple waste forms, treatment ambiguity, and the uniqueness of both the waste chemistries and alternative treatment technologies result in a large set of potential technical requirements that no commercial simulator can totally satisfy. The aim of the selection process was two-fold. First, determine the steady-state simulation software that best, albeit not completely, satisfies the requirements envelope. And second, determine if the best is good enough to justify the cost. Twelve simulators were investigated with varying degrees of scrutiny. The candidate list was narrowed to three final contenders: ASPEN Plus 10.2, PRO/II 5.11, and CHEMCAD 5.1.0. It was concluded from ''road tests'' that ASPEN Plus appears to satisfy the project's technical requirements the best and is worth acquiring. The final software decisions provide flexibility: they involve annual rather than multi-year licensing, and they include periodic re-assessment.

  4. A Four-Step Model for Teaching Selection Interviewing Skills

    Science.gov (United States)

    Kleiman, Lawrence S.; Benek-Rivera, Joan

    2010-01-01

    The topic of selection interviewing lends itself well to experience-based teaching methods. Instructors often teach this topic by using a two-step process. The first step consists of lecturing students on the basic principles of effective interviewing. During the second step, students apply these principles by role-playing mock interviews with…

  5. Modelling the negative effects of landscape fragmentation on habitat selection

    NARCIS (Netherlands)

    Langevelde, van F.

    2015-01-01

    Landscape fragmentation constrains movement of animals between habitat patches. Fragmentation may, therefore, limit the possibilities to explore and select the best habitat patches, and some animals may have to cope with low-quality patches due to these movement constraints. If so, these individuals

  6. Selecting Human Error Types for Cognitive Modelling and Simulation

    NARCIS (Netherlands)

    Mioch, T.; Osterloh, J.P.; Javaux, D.

    2010-01-01

    This paper presents a method that has enabled us to make a selection of error types and error production mechanisms relevant to the HUMAN European project, and discusses the reasons underlying those choices. We claim that this method has the advantage that it is very exhaustive in determining the

  7. RUC at TREC 2014: Select Resources Using Topic Models

    Science.gov (United States)

    2014-11-01

    preprocess the data by parsing the pages ( html , txt, doc, xls, ppt, pdf, xml files) into tokens, removing the stopwords listed in the Indri’s...Gravano. Classification-Aware Hidden- Web Text Database Selection. ACM Trans. Inf. Syst. Vol. 26, No. 2, Article 6, April 2008. [8] J. Seo and B. W

  8. The Living Dead: Transformative Experiences in Modelling Natural Selection

    Science.gov (United States)

    Petersen, Morten Rask

    2017-01-01

    This study considers how students change their coherent conceptual understanding of natural selection through a hands-on simulation. The results show that most students change their understanding. In addition, some students also underwent a transformative experience and used their new knowledge in a leisure time activity. These transformative…

  9. Leukocyte Motility Models Assessed through Simulation and Multi-objective Optimization-Based Model Selection.

    Directory of Open Access Journals (Sweden)

    Mark N Read

    2016-09-01

    Full Text Available The advent of two-photon microscopy now reveals unprecedented, detailed spatio-temporal data on cellular motility and interactions in vivo. Understanding cellular motility patterns is key to gaining insight into the development and possible manipulation of the immune response. Computational simulation has become an established technique for understanding immune processes and evaluating hypotheses in the context of experimental data, and there is clear scope to integrate microscopy-informed motility dynamics. However, determining which motility model best reflects in vivo motility is non-trivial: 3D motility is an intricate process requiring several metrics to characterize. This complicates model selection and parameterization, which must be performed against several metrics simultaneously. Here we evaluate Brownian motion, Lévy walk and several correlated random walks (CRWs against the motility dynamics of neutrophils and lymph node T cells under inflammatory conditions by simultaneously considering cellular translational and turn speeds, and meandering indices. Heterogeneous cells exhibiting a continuum of inherent translational speeds and directionalities comprise both datasets, a feature significantly improving capture of in vivo motility when simulated as a CRW. Furthermore, translational and turn speeds are inversely correlated, and the corresponding CRW simulation again improves capture of our in vivo data, albeit to a lesser extent. In contrast, Brownian motion poorly reflects our data. Lévy walk is competitive in capturing some aspects of neutrophil motility, but T cell directional persistence only, therein highlighting the importance of evaluating models against several motility metrics simultaneously. This we achieve through novel application of multi-objective optimization, wherein each model is independently implemented and then parameterized to identify optimal trade-offs in performance against each metric. The resultant Pareto

  10. Soil biodiversity in artificial black pine stands one year after selective silvicultural treatments

    Science.gov (United States)

    Mocali, Stefano; Fabiani, Arturo; Landi, Silvia; Bianchetto, Elisa; Montini, Piergiuseppe; Samaden, Stefano; Cantiani, Paolo

    2017-04-01

    The decay of forest cover and soil erosion is a consequence of continual intensive forest exploitation, such as grazing and wild fires over the centuries. From the end of the eighteenth century up to the mid-1900s, black pine plantations were established throughout the Apennines' range in Italy, to improve forest soil quality. The main aim of this silvicultural treatment was to re-establish the pine as a first cover and pioneer species. A series of thinning activities were therefore planned by foresters when these plantations were designed. The project Selpibiolife (LIFE13 BIO/IT/000282) has the main objective to demonstrate the potential of an innovative silvicultural treatment to enhance soil and flora biodiversity and under black pine stands. The monitoring will be carried out by comparing selective and traditional thinning methods (selecting trees from below leaving well-spaced, highest-quality trees) to areas without any silvicultural treatments (e.g. weeding, cleaning, liberation cutting). The monitoring survey was carried out in Pratomagno and Amiata Val D'Orcia areas on the Appennines (Italy) and involved different biotic levels: microorganisms, mesofauna, nematodes and macrofauna (Coleoptera) and flora. The microbial (bacteria and fungi) diversity was assessed by both biochemical (microbial biomass, microbial respiration, metabolic quotient) and molecular (microbiota) approaches whereas QBS (Soil Biological Quality) index and diversity indexes were determined for mesofauna and other organisms, respectively, including flora. The overall results highlighted different a composition and activity of microbial communities within the two areas before thinning, and revealed a significant difference between the overall biodiversity of the two areas. Even though silvicultural treatments provided no significant differences at floristic level, microbial and mesofaunal parameters revealed to be differently affected by treatments. In particular, little but significant

  11. Model selection for integrated pest management with stochasticity.

    Science.gov (United States)

    Akman, Olcay; Comar, Timothy D; Hrozencik, Daniel

    2018-04-07

    In Song and Xiang (2006), an integrated pest management model with periodically varying climatic conditions was introduced. In order to address a wider range of environmental effects, the authors here have embarked upon a series of studies resulting in a more flexible modeling approach. In Akman et al. (2013), the impact of randomly changing environmental conditions is examined by incorporating stochasticity into the birth pulse of the prey species. In Akman et al. (2014), the authors introduce a class of models via a mixture of two birth-pulse terms and determined conditions for the global and local asymptotic stability of the pest eradication solution. With this work, the authors unify the stochastic and mixture model components to create further flexibility in modeling the impacts of random environmental changes on an integrated pest management system. In particular, we first determine the conditions under which solutions of our deterministic mixture model are permanent. We then analyze the stochastic model to find the optimal value of the mixing parameter that minimizes the variance in the efficacy of the pesticide. Additionally, we perform a sensitivity analysis to show that the corresponding pesticide efficacy determined by this optimization technique is indeed robust. Through numerical simulations we show that permanence can be preserved in our stochastic model. Our study of the stochastic version of the model indicates that our results on the deterministic model provide informative conclusions about the behavior of the stochastic model. Copyright © 2017 Elsevier Ltd. All rights reserved.

  12. Highly selective vagotomy and gastrojejunostomy in the treatment of peptic ulcer induced gastric outlet obstruction.

    Science.gov (United States)

    Radovanović, Nebojša; Simić, Aleksandar; Skrobić, Ognjan; Kotarac, Milutin; Ivanović, Nenad

    2014-11-01

    The incidence of peptic ulcer-induced gastric outlet obstruction is constantly declining. The aim of this study was to present our results in the treatment of gastric outlet obstruction with highly selective vagotomy and gastrojejunostomy. This retrospective clinical study included 13 patients with peptic ulcer-induced gastric outlet obstruction operated with higly selective vagotomy and gastrojejunostomy. A 3-year follow-up was conducted including clinical interview and upper gastrointestinal endoscopy on 1 and 3 years after the surgery. The most common preoperative symptom was vomiting (in 92.3% of patients). The mean preoperative body mass index was 16.3 +/- 3.1 kg/m2, with 9 patients classified preoperatively as underweight. There were no intraoperative complications, nor mortality. At a 3-year follow-up there was no ulcer recurrence. Delayed gastric emptying was present in 1, bile reflux in 2, and erosive gastritis in 1 patient. Two patients suffered from mild "dumping" syndrome. Higly selective vagotomy combined with gastrojejunostomy is a safe and easily feasible surgical solution of gastric outlet obstruction induced by peptic ulcer. Good functional results and low rate of complications can be expected at a long-term follow-up.

  13. Carbon induced selective regulation of cobalt-based Fischer-Tropsch catalysts by ethylene treatment.

    Science.gov (United States)

    Zhai, Peng; Chen, Pei-Pei; Xie, Jinglin; Liu, Jin-Xun; Zhao, Huabo; Lin, Lili; Zhao, Bo; Su, Hai-Yan; Zhu, Qingjun; Li, Wei-Xue; Ma, Ding

    2017-04-28

    Various carbonaceous species were controllably deposited on Co/Al 2 O 3 catalysts using ethylene as carbon source during the activation process for Fischer-Tropsch synthesis (FTS). Atomic, polymeric and graphitic carbon were distinguished by Raman spectroscopy, thermoanalysis and temperature programmed hydrogenation. Significant changes occurred in both the catalytic activity and selectivity toward hydrocarbon products after ethylene treatment. The activity decreased along with an increase in CH 4 selectivity, at the expense of a remarkable decrease of heavy hydrocarbon production, resulting in enhanced selectivity for the gasoline fraction. In situ XPS experiments show the possible electron transfer from cobalt to carbon and the blockage of metallic cobalt sites, which is responsible for the deactivation of the catalyst. DFT calculations reveal that the activation barrier (E a ) of methane formation decreases by 0.61 eV on the carbon-absorbed Co(111) surface, whereas the E a of the CH + CH coupling reaction changes unnoticeably. Hydrogenation of CH x to methane becomes the preferable route among the elementary reactions on the Co(111) surface, leading to dramatic changes in the product distribution. Detailed coke-induced deactivation mechanisms of Co-based catalysts during FTS are discussed.

  14. Highly selective vagotomy and gastrojejunostomy in the treatment of peptic ulcer induced gastric outlet obstruction

    Directory of Open Access Journals (Sweden)

    Radovanović Nebojša

    2014-01-01

    Full Text Available Background/Aim. The incidence of peptic ulcer-induced gastric outlet obstruction is constantly declining. The aim of this study was to present our results in the treatment of gastric outlet obstruction with highly selective vagotomy and gastrojejunostomy. Methods. This retrospective clinical study included 13 patients with peptic ulcer - induced gastric outlet obstruction operated with higly selective vagotomy and gastrojejunostomy. A 3-year follow-up was conducted including clinical interview and upper gastrointestinal endoscopy on 1 and 3 years after the surgery. Results. The most common preoperative symptom was vomiting (in 92.3% of patients. The mean preoperative body mass index was 16.3 ± 3.1 kg/m2, with 9 patients classified preoperatively as underweight. There were no intraoperative complications, nor mortality. At a 3-year follow-up there was no ulcer recurrence. Delayed gastric emptying was present in 1, bile reflux in 2, and erosive gastritis in 1 patient. Two patients suffered from mild “dumping” syndrome. Conclusion. Higly selective vagotomy combined with gastrojejunostomy is a safe and easily feasible surgical solution of gastric outlet obstruction induced by peptic ulcer. Good functional results and low rate of complications can be expected at a long-term follow-up.

  15. Prevention and treatment of complications of selective internal radiation therapy: Expert guidance and systematic review.

    Science.gov (United States)

    Sangro, Bruno; Martínez-Urbistondo, Diego; Bester, Lourens; Bilbao, Jose I; Coldwell, Douglas M; Flamen, Patrick; Kennedy, Andrew; Ricke, Jens; Sharma, Ricky A

    2017-09-01

    Selective internal radiation therapy (or radioembolization) by intra-arterial injection of radioactive yttrium-90-loaded microspheres is increasingly used for the treatment of patients with liver metastases or primary liver cancer. The high-dose beta-radiation penetrates an average of only 2.5 mm from the source, thus limiting its effects to the site of delivery. However, the off-target diversion of yttrium-90 microspheres to tissues other than the tumor may lead to complications. The most prominent of these complications include radiation gastritis and gastrointestinal ulcers, cholecystitis, radiation pneumonitis, and radioembolization-induced liver disease, which may occur despite careful pretreatment planning. Thus, selective internal radiation therapy demands an expert multidisciplinary team approach in order to provide comprehensive care for patients. This review provides recommendations to multidisciplinary teams on the optimal medical processes in order to ensure the safe delivery of selective internal radiation therapy. Based on the best available published evidence and expert opinion, we recommend the most appropriate strategies for the prevention, early diagnosis, and management of potential radiation injury to the liver and to other organs. (Hepatology 2017;66:969-982). © 2017 by the American Association for the Study of Liver Diseases.

  16. Current approach to male infertility treatment: sperm selection procedure based on hyaluronic acid binding ability

    Directory of Open Access Journals (Sweden)

    A. V. Zobova

    2015-01-01

    Full Text Available Intracytoplasmic sperm injection into an oocyte is widely used throughout the world in assisted reproductive technologies programs in the presence of male infertility factor. However, this approach can allow selection of a single sperm, which is carrying different types of pathologies. Minimizing of any potential risks, entailing the occurrence of abnormalities in the embryos development (apoptosis, fragmentation of embryos, alterations in gene expression, aneuploidies is a very important condition for reducing the potential negative consequences resulting the manipulation with gametes. Processes that could be influenced by the embryologist must be fulfilled in safe and physiological way as much as it is possible. Data of numerous publications reporting about the positive effects of using the technology of sperm selection by hyaluronic acid binding, let make a conclusion about the high prospects of this approach in the treatment of male infertility by methods of in vitro fertilization. The selection of sperm with improved characteristics, which determine the maturity and genetic integrity, provides an opportunity to improve the parameters of pre-implantation embryogenesis, having thus a positive effect on clinical outcomes of assisted reproductive technologies programs.

  17. Multistrain models predict sequential multidrug treatment strategies to result in less antimicrobial resistance than combination treatment

    DEFF Research Database (Denmark)

    Ahmad, Amais; Zachariasen, Camilla; Christiansen, Lasse Engbo

    2016-01-01

    frequency did not play a role in suppressing the growth of resistant strains, but the specific order of the two antimicrobials did. Predictions made from the study could be used to redesign multidrug treatment strategies not only for intramuscular treatment in pigs, but also for other dosing routes.......Background: Combination treatment is increasingly used to fight infections caused by bacteria resistant to two or more antimicrobials. While multiple studies have evaluated treatment strategies to minimize the emergence of resistant strains for single antimicrobial treatment, fewer studies have...... considered combination treatments. The current study modeled bacterial growth in the intestine of pigs after intramuscular combination treatment (i.e. using two antibiotics simultaneously) and sequential treatments (i.e. alternating between two antibiotics) in order to identify the factors that favor...

  18. The application of selective reaction monitoring confirms dysregulation of glycolysis in a preclinical model of schizophrenia

    Directory of Open Access Journals (Sweden)

    Martins-de-Souza Daniel

    2012-03-01

    Full Text Available Abstract Background Establishing preclinical models is essential for novel drug discovery in schizophrenia. Most existing models are characterized by abnormalities in behavioral readouts, which are informative, but do not necessarily translate to the symptoms of the human disease. Therefore, there is a necessity of characterizing the preclinical models from a molecular point of view. Selective reaction monitoring (SRM has already shown promise in preclinical and clinical studies for multiplex measurement of diagnostic, prognostic and treatment-related biomarkers. Methods We have established an SRM assay for multiplex analysis of 7 enzymes of the glycolysis pathway which is already known to be affected in human schizophrenia and in the widely-used acute PCP rat model of schizophrenia. The selected enzymes were hexokinase 1 (Hk1, aldolase C (Aldoc, triosephosphate isomerase (Tpi1, glyceraldehyde-3-phosphate dehydrogenase (Gapdh, phosphoglycerate mutase 1 (Pgam1, phosphoglycerate kinase 1 (Pgk1 and enolase 2 (Eno2. The levels of these enzymes were analyzed using SRM in frontal cortex from brain tissue of PCP treated rats. Results Univariate analyses showed statistically significant altered levels of Tpi1 and alteration of Hk1, Aldoc, Pgam1 and Gapdh with borderline significance in PCP rats compared to controls. Most interestingly, multivariate analysis which considered the levels of all 7 enzymes simultaneously resulted in generation of a bi-dimensional chart that can distinguish the PCP rats from the controls. Conclusions This study not only supports PCP treated rats as a useful preclinical model of schizophrenia, but it also establishes that SRM mass spectrometry could be used in the development of multiplex classification tools for complex psychiatric disorders such as schizophrenia.

  19. Global stability of two models with incomplete treatment for tuberculosis

    International Nuclear Information System (INIS)

    Yang Yali; Li Jianquan; Ma Zhien; Liu Luju

    2010-01-01

    Research highlights: → Two tuberculosis models with incomplete treatment. → Intuitive epidemiological interpretations for the basic reproduction numbers. → Global dynamics of the two models. → Strategies to control the spread of tuberculosis. - Abstract: Two tuberculosis (TB) models with incomplete treatment are investigated. It is assumed that the treated individuals may enter either the latent compartment due to the remainder of Mycobacterium tuberculosis or the infectious compartment due to the treatment failure. The first model is a simple one with treatment failure reflecting the current TB treatment fact in most countries with high tuberculosis incidence. The second model refines the simple one by dividing the latent compartment into slow and fast two kinds of progresses. This improvement can be used to describe the case that the latent TB individuals have been infected with some other chronic diseases (such as HIV and diabetes) which may weaken the immunity of infected individuals and shorten the latent period of TB. Both of the two models assume mass action incidence and exponential distributions of transfers between different compartments. The basic reproduction numbers of the two models are derived and their intuitive epidemiological interpretations are given. The global dynamics of two models are all proved by using Liapunov functions. At last, some strategies to control the spread of tuberculosis are discussed.

  20. Global stability of two models with incomplete treatment for tuberculosis

    Energy Technology Data Exchange (ETDEWEB)

    Yang Yali, E-mail: yylhgr@126.co [Department of Applied Mathematics, Xi' an Jiaotong University, Xi' an 710049 (China) and Department of Applied Mathematics and Physics, Air Force Engineering University, Xi' an 710051 (China); Li Jianquan, E-mail: jianq_li@263.ne [Department of Applied Mathematics and Physics, Air Force Engineering University, Xi' an 710051 (China); Ma Zhien, E-mail: zhma@mail.xjtu.edu.c [Department of Applied Mathematics, Xi' an Jiaotong University, Xi' an 710049 (China); Liu Luju, E-mail: dahai20401095@yahoo.com.c [Department of Mathematics, Henan University of Science and Technology, Luoyang 471003 (China)

    2010-12-15

    Research highlights: Two tuberculosis models with incomplete treatment. Intuitive epidemiological interpretations for the basic reproduction numbers. Global dynamics of the two models. Strategies to control the spread of tuberculosis. - Abstract: Two tuberculosis (TB) models with incomplete treatment are investigated. It is assumed that the treated individuals may enter either the latent compartment due to the remainder of Mycobacterium tuberculosis or the infectious compartment due to the treatment failure. The first model is a simple one with treatment failure reflecting the current TB treatment fact in most countries with high tuberculosis incidence. The second model refines the simple one by dividing the latent compartment into slow and fast two kinds of progresses. This improvement can be used to describe the case that the latent TB individuals have been infected with some other chronic diseases (such as HIV and diabetes) which may weaken the immunity of infected individuals and shorten the latent period of TB. Both of the two models assume mass action incidence and exponential distributions of transfers between different compartments. The basic reproduction numbers of the two models are derived and their intuitive epidemiological interpretations are given. The global dynamics of two models are all proved by using Liapunov functions. At last, some strategies to control the spread of tuberculosis are discussed.

  1. 3D Image Modelling and Specific Treatments in Orthodontics Domain

    OpenAIRE

    Goularas, Dionysis; Djemal, Khalifa; Mannoussakis, Yannis

    2007-01-01

    In this article, we present a 3D specific dental plaster treatment system for orthodontics. From computer tomography scanner images, we propose first a 3D image modelling and reconstruction method of the Mandible and Maxillary based on an adaptive triangulation allowing management of contours meant for the complex topologies. Secondly, we present two specific treatment methods directly achieved on obtained 3D model allowing the automatic correction for the setting in occlusion of the Mandible...

  2. Enhancing treatment effectiveness through social modelling: A pilot study.

    Science.gov (United States)

    Faasse, Kate; Perera, Anna; Loveys, Kate; Grey, Andrew; Petrie, Keith J

    2017-05-01

    Medical treatments take place in social contexts; however, little research has investigated how social modelling might influence treatment outcomes. This experimental pilot study investigated social modelling of treatment effectiveness and placebo treatment outcomes. Fifty-nine participants took part in the study, ostensibly examining the use of beta-blockers (actually placebos) for examination anxiety. Participants were randomly assigned to observe a female confederate report positive treatment effects (reduced heart rate, relaxed, calm) or feeling no different. Heart rate, anxiety and blood pressure were assessed, as were symptoms and attributed side effects. Heart rate decreased significantly more in the social modelling compared to control condition, p = .027 (d = .63), and there were trends towards effects in the same direction for both anxiety, p = .097 (d = .46), and systolic blood pressure, p = .077 (d = .51). Significant pre-post placebo differences in heart rate, anxiety and diastolic blood pressure were found in the social modelling group, ps  .28 (ds = .09-.59). Social observation of medication effectiveness enhanced placebo effectiveness in heart rate, and showed a trend towards enhancing treatment effectiveness in both anxiety and systolic blood pressure. Social modelling may have utility in enhancing the effectiveness of many active medical treatments.

  3. School-Based Intervention for Adolescent Obesity: Analysis of Treatment, Randomly Selected Control, and Self-Selected Control Subjects.

    Science.gov (United States)

    Lansky, David; Vance, Mary Ann

    1983-01-01

    Assigned children (N=114) from stratified blocks of percentage overweight to a comprehensive behavioral program or to a no-treatment condition. The average child in treatment declined to percentage overweight 5.71%; children in the control group gained 2.41%. Parental participation was correlated with weight change among children in the treatment…

  4. Onabotulinum toxin A in the treatment of chronic migraine: patient selection and special considerations

    Directory of Open Access Journals (Sweden)

    Barbanti P

    2017-09-01

    Full Text Available Piero Barbanti,1 Patrizia Ferroni2 1Headache and Pain Unit, Department of Neurological, Motor and Sensorial Sciences, 2Department of Human Sciences and Quality of Life Promotion, San Raffaele Roma Open University, IRCCS San Raffaele Pisana, Rome, Italy Abstract: Discovered by serendipity, onabotulinum toxin A (BoNT-A is the only US Food and Drug Administration-approved treatment for the prevention of chronic migraine (CM, one of the most disabling and burdensome human conditions. Its efficacy, safety and tolerability, proved by the largest and longest migraine therapeutic trial (the Phase III Research Evaluating Migraine Prophylaxis Therapy program [PREEMPT], have been replicated by various real-life studies also in the presence of medication overuse. The benefit of BoNT-A prophylaxis is likely due to its ability to counteract peripheral and central nociceptive sensitization through reversible chemical denervation of pericranial sensitive afferents. Its efficacy increases considerably over time during long-term treatments, significantly varying among patients. The present review focuses on the state-of-the art of current knowledge on putative instrumental, biochemical and clinical predictors of BoNT-A responsiveness, outlining the need for a thorough characterization of the full phenotypic migraine picture when trying to predict good responders. Available evidence suggests that disentangling the BoNT-A responsiveness puzzle requires 1 a reappraisal of easy-obtainable clinical details (eg, site and quality of pain, presence of cranial autonomic symptoms, 2 a proper stratification of patients with CM according to their headache frequency, 3 the evaluation of potential synergistic effects of concomitant prophylaxis/treatment and 4 a detailed assessment of modifiable risk factors evolution during treatment. Keywords: chronic migraine, onabotulinum toxin A, prophylaxis, treatment responder, patient selection, disability

  5. In-vitro evaluation of selected Egyptian traditional herbal medicines for treatment of Alzheimer disease.

    Science.gov (United States)

    Ali, Shereen K; Hamed, Ahmed R; Soltan, Maha M; Hegazy, Usama M; Elgorashi, Esameldin E; El-Garf, Ibrahim A; Hussein, Ahmed A

    2013-05-30

    Egyptians recognized the healing power of herbs and used them in their medicinal formulations. Nowadays, "Attarin" drug shops and the public use mainly the Unani medicinal system for treatment of their health problems including improvement of memory and old age related diseases. Numerous medicinal plants have been described in old literature of Arabic traditional medicine for treatment of Alzheimer's disease (AD) (or to strengthen memory). In this study, some of these plants were evaluated against three different preliminary bioassays related to AD to explore the possible way of their bio-interaction. Twenty three selected plants were extracted with methanol and screened in vitro against acetylcholinesterase (AChE) and cycloxygenase-1 (COX-1) enzymes. In addition, anti-oxidant activity using DPPH was determined. Of the tested plant extracts; Adhatoda vasica and Peganum harmala showed inhibitory effect on AChE at IC50 294 μg/ml and 68 μg/ml respectively. Moreover, A. vasica interacted reversibly with the enzyme while P. harmala showed irreversible inhibition. Ferula assafoetida (IC50 3.2 μg/ml), Syzygium aromaticum (34.9 μg/ml) and Zingiber officinalis (33.6 μg/ml) showed activity against COX-1 enzyme. Potent radical scavenging activity was demonstrated by three plant extracts Terminalia chebula (EC50 2.2 μg/ml), T. arjuna (3.1 μg/ml) and Emblica officinalis (6.3 μg/ml). Interestingly, differential results have been obtained which indicate the variability of the mode of actions for the selected plants. Additionally, the reversible interaction of A. vasica against AChE and the potent activity of F. assafoetida against COX-1 make them effective, new and promising agents for treatment of AD in the future, either as total extracts or their single bioactive constituents.

  6. Effects of a selective iNOS inhibitor versus norepinephrine in the treatment of septic shock.

    Science.gov (United States)

    Su, Fuhong; Huang, Hongchuan; Akieda, Kazuki; Occhipinti, Giovanna; Donadello, Katia; Piagnerelli, Michael; De Backer, Daniel; Vincent, Jean-Louis

    2010-09-01

    Inhibition of NOS is not beneficial in septic shock; selective inhibition of the inducible form (iNOS) may represent a better option. We compared the effects of the selective iNOS inhibitor BYK191023 with those of norepinephrine (NE) in a sheep model of septic shock. Twenty-four anesthetized, mechanically ventilated ewes received 1.5 g/kg body weight of feces into the abdominal cavity to induce sepsis. Animals were randomized into three groups (each n = 8): NE-only, BYK-only, and NE + BYK. The sublingual microcirculation was evaluated with sidestream dark-field videomicroscopy. MAP was higher in the NE + BYK group than in the other groups, but there were no significant differences in cardiac index or systemic vascular resistance. Mean pulmonary arterial pressure was lower in BYK-treated animals than in the NE-only group. PaO2/FiO2 was higher and lactate concentration lower in the BYK groups than in the NE-only group. Mesenteric blood flow was higher in BYK groups than in the NE-only group. Renal blood flow was higher in the NE + BYK group than in the other groups. Functional capillary density and proportion of perfused vessels were higher in the BYK groups than in the NE-only group 18 h after induction of peritonitis. Survival times were similar in the three groups. In this model of peritonitis, selective iNOS inhibition had more beneficial effects than NE on pulmonary artery pressures, gas exchange, mesenteric blood flow, microcirculation, and lactate concentration. Combination of this selective iNOS inhibitor with NE allowed a higher arterial pressure and renal blood flow to be maintained.

  7. Selected Aspects of Computer Modeling of Reinforced Concrete Structures

    Directory of Open Access Journals (Sweden)

    Szczecina M.

    2016-03-01

    Full Text Available The paper presents some important aspects concerning material constants of concrete and stages of modeling of reinforced concrete structures. The problems taken into account are: a choice of proper material model for concrete, establishing of compressive and tensile behavior of concrete and establishing the values of dilation angle, fracture energy and relaxation time for concrete. Proper values of material constants are fixed in simple compression and tension tests. The effectiveness and correctness of applied model is checked on the example of reinforced concrete frame corners under opening bending moment. Calculations are performed in Abaqus software using Concrete Damaged Plasticity model of concrete.

  8. Bronchodilatory and anti-inflammatory properties of inhaled selective phosphodiesterase inhibitors in a guinea pig model of allergic asthma

    NARCIS (Netherlands)

    Santing, R.E; de Boer, J; Rohof, A.A B; van der Zee, N.M; Zaagsma, Hans

    2001-01-01

    In a guinea pig model of allergic asthma, we investigated the effects of the selective phosphodiesterase inhibitors rolipram (phosphodiesterase 4-selective), Org 9935 (phosphodiesterase 3-selective) and Org 20241 (dual phosphodiesterase 4/phosphodiesterase 3-selective), administered by aerosol

  9. A model selection support system for numerical simulations of nuclear thermal-hydraulics

    International Nuclear Information System (INIS)

    Gofuku, Akio; Shimizu, Kenji; Sugano, Keiji; Yoshikawa, Hidekazu; Wakabayashi, Jiro

    1990-01-01

    In order to execute efficiently a dynamic simulation of a large-scaled engineering system such as a nuclear power plant, it is necessary to develop intelligent simulation support system for all phases of the simulation. This study is concerned with the intelligent support for the program development phase and is engaged in the adequate model selection support method by applying AI (Artificial Intelligence) techniques to execute a simulation consistent with its purpose and conditions. A proto-type expert system to support the model selection for numerical simulations of nuclear thermal-hydraulics in the case of cold leg small break loss-of-coolant accident of PWR plant is now under development on a personal computer. The steps to support the selection of both fluid model and constitutive equations for the drift flux model have been developed. Several cases of model selection were carried out and reasonable model selection results were obtained. (author)

  10. Individualized Selection of Beam Angles and Treatment Isocenter in Tangential Breast Intensity Modulated Radiation Therapy

    Energy Technology Data Exchange (ETDEWEB)

    Penninkhof, Joan, E-mail: j.penninkhof@erasmusmc.nl [Department of Radiation Oncology, Erasmus M.C. Cancer Institute, Rotterdam (Netherlands); Spadola, Sara [Department of Radiation Oncology, Erasmus M.C. Cancer Institute, Rotterdam (Netherlands); Department of Physics and Astronomy, Alma Mater Studiorum, University of Bologna, Bologna (Italy); Breedveld, Sebastiaan; Baaijens, Margreet [Department of Radiation Oncology, Erasmus M.C. Cancer Institute, Rotterdam (Netherlands); Lanconelli, Nico [Department of Physics and Astronomy, Alma Mater Studiorum, University of Bologna, Bologna (Italy); Heijmen, Ben [Department of Radiation Oncology, Erasmus M.C. Cancer Institute, Rotterdam (Netherlands)

    2017-06-01

    Purpose and Objective: Propose a novel method for individualized selection of beam angles and treatment isocenter in tangential breast intensity modulated radiation therapy (IMRT). Methods and Materials: For each patient, beam and isocenter selection starts with the fully automatic generation of a large database of IMRT plans (up to 847 in this study); each of these plans belongs to a unique combination of isocenter position, lateral beam angle, and medial beam angle. The imposed hard planning constraint on patient maximum dose may result in plans with unacceptable target dose delivery. Such plans are excluded from further analyses. Owing to differences in beam setup, database plans differ in mean doses to organs at risk (OARs). These mean doses are used to construct 2-dimensional graphs, showing relationships between: (1) contralateral breast dose and ipsilateral lung dose; and (2) contralateral breast dose and heart dose (analyzed only for left-sided). The graphs can be used for selection of the isocenter and beam angles with the optimal, patient-specific tradeoffs between the mean OAR doses. For 30 previously treated patients (15 left-sided and 15 right-sided tumors), graphs were generated considering only the clinically applied isocenter with 121 tangential beam angle pairs. For 20 of the 30 patients, 6 alternative isocenters were also investigated. Results: Computation time for automatic generation of 121 IMRT plans took on average 30 minutes. The generated graphs demonstrated large variations in tradeoffs between conflicting OAR objectives, depending on beam angles and patient anatomy. For patients with isocenter optimization, 847 IMRT plans were considered. Adding isocenter position optimization next to beam angle optimization had a small impact on the final plan quality. Conclusion: A method is proposed for individualized selection of beam angles in tangential breast IMRT. This may be especially important for patients with cardiac risk factors or an

  11. Optimal selection of Orbital Replacement Unit on-orbit spares - A Space Station system availability model

    Science.gov (United States)

    Schwaab, Douglas G.

    1991-01-01

    A mathematical programing model is presented to optimize the selection of Orbital Replacement Unit on-orbit spares for the Space Station. The model maximizes system availability under the constraints of logistics resupply-cargo weight and volume allocations.

  12. Assessing the accuracy and stability of variable selection methods for random forest modeling in ecology

    Science.gov (United States)

    Random forest (RF) modeling has emerged as an important statistical learning method in ecology due to its exceptional predictive performance. However, for large and complex ecological datasets there is limited guidance on variable selection methods for RF modeling. Typically, e...

  13. Optimizing warehouse logistics operations through site selection models : Istanbul, Turkey

    OpenAIRE

    Erdemir, Ugur

    2003-01-01

    Approved for public release; distribution is unlimited This thesis makes a cost benefit analysis of relocating the outdated and earthquake damaged supply distribution center of the Turkish Navy. Given the dynamic environment surrounding the military operations, logistic sustainability requirements, rapid information technology developments, and budget-constrained Turkish DoD acquisition environment, the site selection of a supply distribution center is critical to the future operations and...

  14. River water quality model no. 1 (RWQM1): III. Biochemical submodel selection

    DEFF Research Database (Denmark)

    Vanrolleghem, P.; Borchardt, D.; Henze, Mogens

    2001-01-01

    The new River Water Quality Model no.1 introduced in the two accompanying papers by Shanahan et al. and Reichert et al. is comprehensive. Shanahan et al. introduced a six-step decision procedure to select the necessary model features for a certain application. This paper specifically addresses one...... of these steps, i.e. the selection of submodels of the comprehensive biochemical conversion model introduced in Reichert et al. Specific conditions for inclusion of one or the other conversion process or model component are introduced, as are some general rules that can support the selection. Examples...... of simplified models are presented....

  15. In search of patient characteristics that may guide empirically based treatment selection for personality disorder patients - a concept map approach

    NARCIS (Netherlands)

    van Manen, J.G.; Kamphuis, J.H.; Goossensen, A.; Timman, R.; Busschbach, J.J.V.; Verheul, R.

    2012-01-01

    Using the concept map method, this study aimed to summarize and describe patient characteristics pertinent to treatment selection for patients with personality disorders (PDs). Initial patient characteristics were derived from the research literature and a survey among Dutch expert clinicians.

  16. Practical Study on Treatment of Selected Decorated Tapestry in Applied Art Museum, Cairo

    Directory of Open Access Journals (Sweden)

    Neven Kamal FAHIM

    2013-12-01

    Full Text Available The paper presents the method of treatment of tapestry textile, that considers the most common technique used in decoration of textile since the new kingdom until now, it is called Kabaty. The paper deals with selected piece of museum of Applied Art Faculty in Cairo. Treatment procedure was performed by several stages; firstly, Dating by comparing the decoration technique, the type of material and the decorative motifs existed in the object with another one known its date. Then samples taken from object were examined by optical microscope, scanning electron microscope to identify type of fibers and surface morphology .x-ray analysis was performed to identify mordant and dust. FTIR analysis to identify dyes in dyed samples. Then, the paper deal with the treatment of tapestry pieces by testing sensitive of fiber to water, mechanical cleaning and chemical cleaning to remove stain, washing stage using distilled water, and finally consolidation the object by fixed on support of natural linen which was stretched on wooden frame treated by anti-fungal substance.

  17. Selective Trapping of Volatile Fission Products with an Off-Gas Treatment System

    Energy Technology Data Exchange (ETDEWEB)

    B.R. Westphal; J.J. Park; J.M. Shin; G.I. Park; K.J. Bateman; D.L. Wahlquist

    2008-07-01

    A head-end processing step, termed DEOX for its emphasis on decladding via oxidation, is being developed for the treatment of spent oxide fuel by pyroprocessing techniques. The head-end step employs high temperatures to oxidize UO2 to U3O8 resulting in the separation of fuel from cladding and the removal of volatile fission products. Development of the head-end step is being performed in collaboration with the Korean Atomic Energy Research Institute (KAERI) through an International Nuclear Energy Research Initiative. Following the initial experimentation for the removal of volatile fission products, an off-gas treatment system was designed in conjunction with KAERI to collect specific fission gases. The primary volatile species targeted for trapping were iodine, technetium, and cesium. Each species is intended to be collected in distinct zones of the off-gas system and within those zones, on individual filters. Separation of the volatile off-gases is achieved thermally as well as chemically given the composition of the filter media. A description of the filter media and a basis for its selection will be given along with the collection mechanisms and design considerations. In addition, results from testing with the off-gas treatment system will be presented.

  18. Identifying Treatment Response of Sertraline in a Teenager with Selective Mutism using Electrophysiological Neuroimaging.

    Science.gov (United States)

    Eugene, Andy R; Masiak, Jolanta

    2016-06-01

    Selective Mutism is described as the inability to verbally express oneself in anxiety provoking social situations and may result in awkward social interactions in school-aged children. In this case-report we present the baseline electrophysiological neuroimaging results and after treatment with Sertraline for 6-weeks. A 20-channel EEG event-related potential recording was acquired during an internal voice task at baseline prior to the initiation of 50mg of Sertraline and then repeated 6-weeks after treatment with Sertraline. EEG signals were processed for movement, eye-blink, and muscle artifacts and ERP signal averaging was completed. ERPs were analyzed using Standard Low Resolution Brain Electromagnetic Tomography (sLORETA). At baseline, Sertraline increased the neuronal activation in the middle temporal gyrus and the anterior cingulate gyrus from baseline in the patient following 6-weeks of treatment. Our findings suggest that electrophysiological neuroimaging may provide a creative approach for personalizing medicine by providing insight to the pharmacodynamics of antidepressants.

  19. Default Bayes Factors for Model Selection in Regression

    Science.gov (United States)

    Rouder, Jeffrey N.; Morey, Richard D.

    2012-01-01

    In this article, we present a Bayes factor solution for inference in multiple regression. Bayes factors are principled measures of the relative evidence from data for various models or positions, including models that embed null hypotheses. In this regard, they may be used to state positive evidence for a lack of an effect, which is not possible…

  20. The analysis of the capacity of the selected measures of decision-making models in companies

    OpenAIRE

    Helena Kościelniak; Beata Skowron-Grabowska; Sylwia Łęgowik-Świącik; Małgorzata Łęgowik-Małolepsza

    2015-01-01

    The paper aims at the analysis of the information capacity of selected instruments of the assessment of decision-making models in the analyzed companies. In the paper there are presented the idea and concepts of decision-making models. There have been discussed the selected instruments of the assessment of decision-making models in enterprises. In the final part of the paper there has been held the quantification of decision- making models in the investigated cement industry companies. To mee...