Weight maintenance through behaviour modification with a cooking course or neurolinguistic programming.

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Sørensen, Lone Brinkmann; Greve, Tine; Kreutzer, Martin; Pedersen, Ulla; Nielsen, Claus Meyer; Toubro, Søren; Astrup, Arne

2011-01-01

We compared the effect on weight regain of behaviour modification consisting of either a gourmet cooking course or neurolinguistic programming (NLP) therapy. Fifty-six overweight and obese subjects participated. The first step was a 12-week weight loss program. Participants achieving at least 8% weight loss were randomized to five months of either NLP therapy or a course in gourmet cooking. Follow-up occurred after two and three years. Forty-nine participants lost at least 8% of their initial body weight and were randomized to the next step. The NLP group lost an additional 1.8 kg and the cooking group lost 0.2 kg during the five months of weight maintenance (NS). The dropout rate in the cooking group was 4%, compared with 26% in the NLP group (p=0.04). There was no difference in weight maintenance after two and three years of follow-up. In conclusion, weight loss in overweight and obese participants was maintained equally efficiently with a healthy cooking course or NLP therapy, but the dropout rate was lower during the active cooking treatment.

[Neurolinguistic programming in physician-patient communication. Basic principles of the procedure--examples for application in surgery].

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Graf, U

1995-09-20

Neurolinguistic programming (NLP) is a means of improving physician-patient communication that can be learned by any doctor. The present article first describes some of the fundamentals of NLP and then provides examples taken from the field of surgery-in the first instance dealing with the treatment of painful conditions by means of trance or dissociation and, secondly, on the influencing of expectations and the restructuring (reframing) of doctrines in a patient with malignant disease.

Neurolinguistic programming: a systematic review of the effects on health outcomes.

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Sturt, Jackie; Ali, Saima; Robertson, Wendy; Metcalfe, David; Grove, Amy; Bourne, Claire; Bridle, Chris

2012-11-01

Neurolinguistic programming (NLP) in health care has captured the interest of doctors, healthcare professionals, and managers. To evaluate the effects of NLP on health-related outcomes. Systematic review of experimental studies. The following data sources were searched: MEDLINE, PsycINFO, ASSIA, AMED, CINAHL, Web of Knowledge, CENTRAL, NLP specialist databases, reference lists, review articles, and NLP professional associations, training providers, and research groups. Searches revealed 1459 titles from which 10 experimental studies were included. Five studies were randomised controlled trials (RCTs) and five were pre-post studies. Targeted health conditions were anxiety disorders, weight maintenance, morning sickness, substance misuse, and claustrophobia during MRI scanning. NLP interventions were mainly delivered across 4-20 sessions although three were single session. Eighteen outcomes were reported and the RCT sample sizes ranged from 22 to 106. Four RCTs reported no significant between group differences with the fifth finding in favour of the NLP arm (F = 8.114, P<0.001). Three RCTs and five pre-post studies reported within group improvements. Risk of bias across all studies was high or uncertain. There is little evidence that NLP interventions improve health-related outcomes. This conclusion reflects the limited quantity and quality of NLP research, rather than robust evidence of no effect. There is currently insufficient evidence to support the allocation of NHS resources to NLP activities outside of research purposes.

Predicate Matching in NLP: A Review of Research on the Preferred Representational System.

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Sharpley, Christopher F.

1984-01-01

Reviews 15 studies that have investigated the use of the Preferred Representational System (PRS) in Neurolinguistic Programming (NLP). Aspects of design, methodology, population and dependent measures are evaluated, with comments on the outcomes obtained. Results suggested that there is little supportive evidence for the use of PRS in the NLP.…

The eyes don't have it: lie detection and Neuro-Linguistic Programming.

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Richard Wiseman

Full Text Available Proponents of Neuro-Linguistic Programming (NLP claim that certain eye-movements are reliable indicators of lying. According to this notion, a person looking up to their right suggests a lie whereas looking up to their left is indicative of truth telling. Despite widespread belief in this claim, no previous research has examined its validity. In Study 1 the eye movements of participants who were lying or telling the truth were coded, but did not match the NLP patterning. In Study 2 one group of participants were told about the NLP eye-movement hypothesis whilst a second control group were not. Both groups then undertook a lie detection test. No significant differences emerged between the two groups. Study 3 involved coding the eye movements of both liars and truth tellers taking part in high profile press conferences. Once again, no significant differences were discovered. Taken together the results of the three studies fail to support the claims of NLP. The theoretical and practical implications of these findings are discussed.

The relationship between hypnotizability, internal imagery, and efficiency of neurolinguistic programming.

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Kirenskaya, Anna V; Novototsky-Vlasov, Vladimir Y; Chistyakov, Andrey N; Zvonikov, Vyacheslav M

2011-04-01

Subjective scoring and autonomic variables (heart rate, skin conduction span) were used to verify the reality of inner experience during recollection of emotionally neutral, positive, and negative past events in 19 high (HH) and 12 low (LH) hypnotizable subjects in hypnotic and nonhypnotic experimental sessions. Also, the influence of hypnotizability on the effectiveness of an imagery-based neurolinguistic programming (NLP) technique was evaluated. Results demonstrated that subjective scores of image vividness and emotional intensity were significantly higher in the HH subjects compared to LH in both sessions. The past-events recollection was followed by increased autonomic activity only in the HH subjects. The NLP procedure was followed by decreased negative emotional intensity in both groups, but autonomic activity decline was observed in the HH subjects and not in the LH.

An NLP-Based Programme for Developing EFL Student-Teachers ...

African Journals Online (AJOL)

An NLP-Based Programme for Developing EFL Student-Teachers' Motivational Language. ... teaching of motivational language by using influential hypnotic language patterns should be integrated into EFL pre-service teacher training curricula. Keywords: Motivational language, Neuro-linguistic Programming, Milton Model ...

Sensory submodalities testing in neurolinguistic programming, part of mental training

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Vlad Teodor GROSU

2017-03-01

Full Text Available Introduction: this study is part of a larger work, which involves increasing sporting performance by applying mental training techniques – special techniques of neurolinguistic programming. In this case we will discuss some aspects of the test application Jacobson S. (2011. Purpose of study and hypothesis: In neurolinguistic programming (NLP we have studied the relationship between sensory submodalities, in accordance with the Jacobson test (2011. We wanted to check the degree of significance of the mean difference parameters studied and if the materiality result falls within the objective parameters. If ideomotor representations of athletes are completed with multiple sensations of all sensory submodalities such as visual, auditory, kinesthetic, olfactory and gustatory, the possibility of applying the techniques of NLP (neurolinguistic programming will have more effective results. Methods and material: two records were made by using two tests, test1 and test2 on master students of the University “Babes-Bolyai” Cluj-Napoca, from FEFS from APS department (training and sports performance. The statistical indicators were calculated on elements of descriptive statistics and the data is presented using indicators of centrality, location and distribution. Statistical analysis of non-parametric Wilcoxon test was used for sample pairs (data uneven distribution/rank. Materiality tests used was α=0.05 (5%, α=0.01 (1% or α=0.001. Results and deliberations: to detect the correlation between the two variables we used the Spearman rank correlation coefficient (ρ. Statistical analysis was performed using the correlation coefficients Colton’s rule. It was found that no statistically significant differences were observed (p>0.05 in the statistical analysis of sample pairs Jacobson test values (times T1-T2. This is a result of the short timeframe – just one month – for objectives reasons. However, many of them appear in a good and a very good

Neuro-Linguistic Programming and Learning: Teacher Case Studies on the Impact of NLP in Education

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Carey, John; Churches, Richard; Hutchinson, Geraldine; Jones, Jeff; Tosey, Paul

2010-01-01

This research paper reports on evidence from 24 teacher-led action research case studies and builds on the 2008 CfBT Education Trust published paper by Richard Churches and John West-Burnham "Leading learning through relationships: the implications of Neurolinguistic programming for personalisation and the children's agenda in England".…

Visual displays and Neuro-Linguistic Programming

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Brown-VanHoozer, S.A. [Argonne National Lab., Idaho Falls, ID (United States); VanHoozer, W.R. [Tranceformations Unlimited, Rigby, ID (United States)

1994-10-01

Advancement of computer technology is forthcoming at such a rapid pace that the research concerning the interplay of humans and computer technology is lagging far behind. One area of particular concern is the design of visual displays that are pragmatic, ``user friendly,`` and ``user assisting.`` When engineers design visual displays, they generally do so methodically and logically, but only from within their own individual perspective or ``model of the world.`` They select the human aspects which make sense to them and not necessarily to non-engineers, operators, and others. The model design is what the engineer chooses to relate, based on his or her perspective of reality. These choices limit the model design thereby excluding the users` perspective. A set of techniques which can be used to assist the designers in expanding their choices and include the users` model is Neuro-Linguistic Programming (NLP).

The Old Brain, the New Mirror: Matching Teaching and Learning Styles in Foreign Language Class (Based on Neuro-Linguistic Programming).

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Knowles, John K.

The process of matching teaching materials and methods to the student's learning style and ability level in foreign language classes is explored. The Neuro-Linguistic Programming (NLP) model offers a diagnostic process for the identification of style. This process can be applied to the language learning setting as a way of presenting material to…

Using an imaginary scrapbook for neurolinguistic programming in the aftermath of a clinical depression: a case history.

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Hossack, A; Standidge, K

1993-04-01

We employed neurolinguistic programming (NLP) principles to develop a positive self-identity in an elderly male patient in England recovering from clinical depression. This novel technique encouraged recall of intrinsically rewarding past experiences. Each experience was conceptualized in an image and compiled chronologically in an imaginary book, providing continuity to what were chaotic and fragmented recollections during the immediate postdepressive stage. The patient's anxiety and depression were alleviated and his own functional goals largely realized.

Efficacy of neurolinguistic programming training on mental health in nursing and midwifery students

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Sahebalzamani, Mohammad

2014-01-01

Background: Neurolinguistic programming (NLP) refers to the science and art of reaching success and perfection. It is a collection of the skills based on human beings’ psychological characteristics through which the individuals obtain the ability to use their personal capabilities as much as possible. This study aimed to investigate the efficacy of NLP training on mental health in nursing and midwifery students in Islamic Azad University Tehran Medical Sciences branch. Materials and Methods: In this quasi-experimental study, the study population comprised all nursing and midwifery students in Islamic Azad University, Tehran Medical branch, of whom 52 were selected and assigned to two groups through random sampling. Data collection tool was Goldberg General Health Questionnaire (28-item version). After primary evaluation, NLP training was given in five 120-min sessions and the groups were re-evaluated. The obtained data were analyzed. Results: In the nursing group, paired t-test showed a significant difference in the scores of mental health (with 39 points decrease), physical signs (with 7.96 scores decrease), anxiety (with 10.75 scores decrease), social function (with 7.05 scores decrease) and depression (with 9.38 scores decrease). In the midwifery group, it showed a significant difference in mental health (with 22.63 scores decrease), physical signs (with 6.54 scores decrease), anxiety (with nine scores decrease), and depression (with 8.38 scores decrease). Conclusions: This study showed that NLP strategies are effective in the improvement of general health and its various dimensions. Therefore, it is essential to conduct structured and executive programs concerning NLP among the students. PMID:25400679

Efficacy of neurolinguistic programming training on mental health in nursing and midwifery students.

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Sahebalzamani, Mohammad

2014-09-01

Neurolinguistic programming (NLP) refers to the science and art of reaching success and perfection. It is a collection of the skills based on human beings' psychological characteristics through which the individuals obtain the ability to use their personal capabilities as much as possible. This study aimed to investigate the efficacy of NLP training on mental health in nursing and midwifery students in Islamic Azad University Tehran Medical Sciences branch. In this quasi-experimental study, the study population comprised all nursing and midwifery students in Islamic Azad University, Tehran Medical branch, of whom 52 were selected and assigned to two groups through random sampling. Data collection tool was Goldberg General Health Questionnaire (28-item version). After primary evaluation, NLP training was given in five 120-min sessions and the groups were re-evaluated. The obtained data were analyzed. In the nursing group, paired t-test showed a significant difference in the scores of mental health (with 39 points decrease), physical signs (with 7.96 scores decrease), anxiety (with 10.75 scores decrease), social function (with 7.05 scores decrease) and depression (with 9.38 scores decrease). In the midwifery group, it showed a significant difference in mental health (with 22.63 scores decrease), physical signs (with 6.54 scores decrease), anxiety (with nine scores decrease), and depression (with 8.38 scores decrease). This study showed that NLP strategies are effective in the improvement of general health and its various dimensions. Therefore, it is essential to conduct structured and executive programs concerning NLP among the students.

Training in Influencing Skills from Neuro-Linguistic Programming (Modelled from Hypnosis and Family Therapy), in Combination with Innovative Maths Pedagogy, Raises Maths Attainment in Adult Numeracy Learners

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Allan, F.; Bourne, J.; Bouch, D.; Churches, R.; Dennison, J.; Evans, J.; Fowler, J.; Jeffers, A.; Prior, E.; Rhodes, L.

2012-01-01

Case study research suggests that NLP [neuro-linguistic programming] influencing strategies benefit teacher effectiveness. Maths pedagogy involving higher-order questioning, challenge, problem solving and collaborative working may be a way of improving attainment in adult numeracy learning, however, such strategies may be less effective if the…

Neurolinguistic programming as an adjunct to other psychotherapeutic/hypnotherapeutic interventions.

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Field, E S

1990-01-01

The therapeutic dissociative techniques of "anchoring" and "three-part dissociation," neurolinguistic programming (NLP) treatment paradigms incorporating the idea of division into ego states, are effective in crisis intervention and as a stimulus for catharsis. Using the anchoring technique in the first session, a patient with severe anxiety, manifested by episodes of hyperactivity, was able to superimpose inner resources upon the situations which led to the episodes. Utilizing three-part dissociation, the patient experienced the hyperactive episodes "for the very last time" and terminated them permanently. Hypnotic exploration and ideomotor signaling were used with a patient presenting with uncomfortable feelings associated with intense anger. After the origin of the anger was determined, a three-part dissociation produced an abreaction and catharsis. Interaction at a cognitive level integrated the feelings and knowledge into personal consciousness.

Bibliography of Literature on Neuro-Linguistic Programming.

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McCormick, Donald W.

Two bibliographies on neurolinguistic programming are updates of an earlier literature review by the same compiler. The two lists contain citations of over 160 books, research reports, dissertations, journal articles, audio and video recordings, and research projects in progress on aspects of neurolinguistic programming. Appended notes suggest…

Applying "What Works" in Psychology to Enhancing Examination Success in Schools: The Potential Contribution of NLP

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Kudliskis, Voldis; Burden, Robert

2009-01-01

The strengths and weaknesses of Neuro-Linguistic Programming (NLP) are described with reference to its origins, previous research and comments from critics and supporters. A case is made for this allegedly theoretical approach to provide the kind of outcomes focused intervention that psychology and psychologists can offer to schools. In…

Neuro-Linguistic Programming: Eye Movements as Indicators of Representational Systems.

Science.gov (United States)

1984-09-01

Elizabeth A. Beck, "Test of the Eye Movement Hypothesis of Neurolinguistic Programing : A Rebuttal of Conclu- sions," Perceptual and Motor Skills, 58: 175...Meta Publications, 1980. 64 .. .] .! S ~ ~ ~ ~ 1 - ----. 14. Maron, Davida, " Neurolinguistic Programming : The Answer to Change? Training and Development... Neurolinguistic Programming ," Perceptual and Motor Skills, 51: 230 (April 1980). 65 VITA Captain William H. Moore was born on 22 October 1949. He

Neuro-Linguistic Programming: Human Technology for Today’s Air Force.

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1986-04-01

Part III, pp. 4-5. ’ 26. Ibid, p. 6. 27. Donald W. McCormick, " Neurolinguistic Programming : A Resource Guide and Review of the Research, The 1984...Carol Johnson, " Neurolinguistic Programming --Mystique or Mistake?" Army Organizational Effectiveness Journal, No. 1, 1985, pp. 74-80. 29. Dilts...AD-RI67 836 NEURO-LINGUISTIC PROGRAMMING : HUHAN TECHNOLOGY FOR / TODAY’S AIR FORCEMU AIR COMMAND ANM STAFF COLL NAXHELL AFB AL J B CAULFIELD APR 86

Neurolinguistic programming used to reduce the need for anaesthesia in claustrophobic patients undergoing MRI.

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Bigley, J; Griffiths, P D; Prydderch, A; Romanowski, C A J; Miles, L; Lidiard, H; Hoggard, N

2010-02-01

The purpose of this study was to assess the success of neurolinguistic programming in reducing the need for general anaesthesia in claustrophobic patients who require MRI and to consider the financial implications for health providers. This was a prospective study performed in 2006 and 2007 at a teaching hospital in England and comprised 50 adults who had unsuccessful MR examinations because of claustrophobia. The main outcome measures were the ability to tolerate a successful MR examination after neurolinguistic programming, the reduction of median anxiety scores produced by neurolinguistic programming, and models of costs for various imaging pathways. Neurolinguistic programming allowed 38/50 people (76%) to complete the MR examination successfully. Overall, the median anxiety score was significantly reduced following the session of neurolinguistic programming. In conclusion, neurolinguistic programming reduced anxiety and subsequently allowed MRI to be performed without resorting to general anaesthesia in a high proportion of claustrophobic adults. If these results are reproducible, there will be major advantages in terms of patient safety and costs.

NLP as a communication strategy tool in libraries

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Koulouris, Alexandros; Sakas, Damianos P.; Giannakopoulos, Georgios

2015-02-01

The role of communication is a catalyst for the proper function of an organization. This paper focuses on libraries, where the communication is crucial for their success. In our opinion, libraries in Greece are suffering from the lack of communication and marketing strategy. Communication has many forms and manifestations. A key aspect of communication is body language, which has a dominant communication tool the neuro-linguistic programming (NLP). The body language is a system that expresses and transfers messages, thoughts and emotions. More and more organizations in the public sector and companies in the private sector base their success on the communication skills of their personnel. The NLP suggests several methods to obtain excellent relations in the workplace and to develop ideal communication. The NLP theory is mainly based on the development of standards (communication model) that guarantees the expected results. This research was conducted and analyzed in two parts, the qualitative and the quantitative. The findings mainly confirm the need for proper communication within libraries. In the qualitative research, the interviewees were aware of communication issues, although some gaps in that knowledge were observed. Even this slightly lack of knowledge, highlights the need for constant information through educational programs. This is particularly necessary for senior executives of libraries, who should attend relevant seminars and refresh their knowledge on communication related issues.

Impact of the application of neurolinguistic programming to mothers of children enrolled in a day care center of a shantytown.

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de Miranda, C T; de Paula, C S; Palma, D; da Silva, E M; Martin, D; de Nóbrega, F J

1999-03-04

Of the members of a family, the mother is without doubt the most important one, which provides justification for including an evaluation of her mental health as one of the variables to be considered as determining factors in each child's level of development. To assess the impact of the application of Neurolinguistic Programming (NLP) on child development, home environment and maternal mental health. Randomised controlled trial. The study included children enrolled in the municipal day care center of a shantytown in the City of São Paulo. 45 pairs of mothers and respective children between 18 and 36 months of age. Children's development (Bayley scales); home environment variation (HOME); and maternal mental health (SRQ). Comparison between before and after the intervention was made in terms of children's psychomotor development, home environment and maternal mental health. Application of the NLP technique to the experimental group and comparison with a control group. 1--Experimental (EG), consisting of 23 children submitted to intervention by NLP; and 2--Control (CG), with 22 children with no intervention. Length of intervention: 15 sessions of NLP. 37 children remained in the study (EG = 10, CG = 27). Variations in mental development (OR 1.21, IC 95% 0.0 to 23.08) in their home environment (Wilcoxon): p = 0.96 (before) and p = 0.09 (after); in maternal mental health: p = 0.26, 2 df. There was a trend that indicated positive effects on the home environment from the intervention.

Neurolinguistic Programming in Orientation and Mobility.

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Williams, M. F.; Jacobson, W. H.

1989-01-01

The article describes the neurolinguistic programing model and applies it to teaching orientation and mobility skills to congenitally blind students, who have access to only the auditory and kinesthetic primary systems. Understanding the effects on thought of limited representational systems can help trainers teach more effective cane or dog guide…

Neuro-Linguistic Programming: Enhancing Teacher-Student Communications.

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Childers, John H., Jr.

1985-01-01

Defines Neurolinguistic Programming (NCP) and discusses specific dimensions of the model that have applications for classroom teaching. Describes five representational systems individuals use to process information and gives examples of effective and ineffective teacher-student communication for each system. (MCF)

Impact of the application of neurolinguistic programming to mothers of children enrolled in a day care center of a shantytown

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Cláudio Torres de Miranda

1999-03-01

Full Text Available CONTEXT: Of the members of a family, the mother is without doubt the most important one, which provides justification for including an evaluation of her mental health as one of the variables to be considered as determining factors in each child’s level of development. OBJECTIVE: To assess the impact of the application of Neurolinguistic Programming (NLP on child development, home environment and maternal mental health. DESIGN: Randomised controlled trial. SETTING: The study included children enrolled in the municipal day care center of a shantytown in the City of São Paulo. PARTICIPANTS: 45 pairs of mothers and respective children between 18 and 36 months of age. MAIN MEASUREMENTS: Children’s development (Bayley scales; home environment variation (HOME; and maternal mental health (SRQ. Comparison between before and after the intervention was made in terms of children’s psychomotor development, home environment and maternal mental health. INTERVENTION: Application of the NLP technique to the experimental group and comparison with a control group. 1 - Experimental (EG, consisting of 23 children submitted to intervention by NLP; and 2 - Control (CG, with 22 children with no intervention. Length of intervention: 15 sessions of NLP. RESULTS: 37 children remained in the study (EG = 10, CG = 27. Variations in mental development (OR 1.21, IC 95% 0.0 to 23.08 in their home environment (Wilcoxon: p = 0.96 (before and p = 0.09 (after; in maternal mental health: p = 0.26, 2 df. CONCLUSIONS: There was a trend that indicated positive effects on the home environment from the intervention.

Using Neurolinguistic Programming: Some Suggestions for the Remedial Teacher.

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Burton, Grace M.

1986-01-01

The use of neurolinguistic programming techniques is suggested as a means of enhancing rapport with students. Mirroring, digital mirroring, analog mirroring, metaphors, knowing persons, and how these aid in presenting content are each discussed. (MNS)

Neuro-Linguistics Programming: Developing Effective Communication in the Classroom.

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Torres, Cresencio; Katz, Judy H.

1983-01-01

Students and teachers experience the world primarily through visual, kinesthetic, or auditory representational systems. If teachers are aware of their own favored system and those of their students, classroom communication will improve. Neurolinguistic programing can help teachers become more effective communicators. (PP)

LEARNING CREATIVE WRITING MODEL BASED ON NEUROLINGUISTIC PROGRAMMING

OpenAIRE

Rustan, Edhy

2017-01-01

The objectives of the study are to determine: (1) condition on learning creative writing at high school students in Makassar, (2) requirement of learning model in creative writing, (3) program planning and design model in ideal creative writing, (4) feasibility of model study based on creative writing in neurolinguistic programming, and (5) the effectiveness of the learning model based on creative writing in neurolinguisticprogramming.The method of this research uses research development of L...

The Effects of Clinical Hypnosis versus Neurolinguistic Programming (NLP before External Cephalic Version (ECV: A Prospective Off-Centre Randomised, Double-Blind, Controlled Trial

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Joscha Reinhard

2012-01-01

Full Text Available Objective. To examine the effects of clinical hypnosis versus NLP intervention on the success rate of ECV procedures in comparison to a control group. Methods. A prospective off-centre randomised trial of a clinical hypnosis intervention against NLP of women with a singleton breech fetus at or after 370/7 (259 days weeks of gestation and normal amniotic fluid index. All 80 participants heard a 20-minute recorded intervention via head phones. Main outcome assessed was success rate of ECV. The intervention groups were compared with a control group with standard medical care alone (=122. Results. A total of 42 women, who received a hypnosis intervention prior to ECV, had a 40.5% (=17, successful ECV, whereas 38 women, who received NLP, had a 44.7% (=17 successful ECV (>0.05. The control group had similar patient characteristics compared to the intervention groups (>0.05. In the control group (=122 27.3% (=33 had a statistically significant lower successful ECV procedure than NLP (=0.05 and hypnosis and NLP (=0.03. Conclusions. These findings suggest that prior clinical hypnosis and NLP have similar success rates of ECV procedures and are both superior to standard medical care alone.

The Effects of Clinical Hypnosis versus Neurolinguistic Programming (NLP) before External Cephalic Version (ECV): A Prospective Off-Centre Randomised, Double-Blind, Controlled Trial.

Science.gov (United States)

Reinhard, Joscha; Peiffer, Swati; Sänger, Nicole; Herrmann, Eva; Yuan, Juping; Louwen, Frank

2012-01-01

Objective. To examine the effects of clinical hypnosis versus NLP intervention on the success rate of ECV procedures in comparison to a control group. Methods. A prospective off-centre randomised trial of a clinical hypnosis intervention against NLP of women with a singleton breech fetus at or after 37(0/7) (259 days) weeks of gestation and normal amniotic fluid index. All 80 participants heard a 20-minute recorded intervention via head phones. Main outcome assessed was success rate of ECV. The intervention groups were compared with a control group with standard medical care alone (n = 122). Results. A total of 42 women, who received a hypnosis intervention prior to ECV, had a 40.5% (n = 17), successful ECV, whereas 38 women, who received NLP, had a 44.7% (n = 17) successful ECV (P > 0.05). The control group had similar patient characteristics compared to the intervention groups (P > 0.05). In the control group (n = 122) 27.3% (n = 33) had a statistically significant lower successful ECV procedure than NLP (P = 0.05) and hypnosis and NLP (P = 0.03). Conclusions. These findings suggest that prior clinical hypnosis and NLP have similar success rates of ECV procedures and are both superior to standard medical care alone.

Speaker recognition through NLP and CWT modeling.

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Brown-VanHoozer, A.; Kercel, S. W.; Tucker, R. W.

1999-06-23

The objective of this research is to develop a system capable of identifying speakers on wiretaps from a large database (>500 speakers) with a short search time duration (<30 seconds), and with better than 90% accuracy. Much previous research in speaker recognition has led to algorithms that produced encouraging preliminary results, but were overwhelmed when applied to populations of more than a dozen or so different speakers. The authors are investigating a solution to the ''huge population'' problem by seeking two completely different kinds of characterizing features. These features are extracted using the techniques of Neuro-Linguistic Programming (NLP) and the continuous wavelet transform (CWT). NLP extracts precise neurological, verbal and non-verbal information, and assimilates the information into useful patterns. These patterns are based on specific cues demonstrated by each individual, and provide ways of determining congruency between verbal and non-verbal cues. The primary NLP modalities are characterized through word spotting (or verbal predicates cues, e.g., see, sound, feel, etc.) while the secondary modalities would be characterized through the speech transcription used by the individual. This has the practical effect of reducing the size of the search space, and greatly speeding up the process of identifying an unknown speaker. The wavelet-based line of investigation concentrates on using vowel phonemes and non-verbal cues, such as tempo. The rationale for concentrating on vowels is there are a limited number of vowels phonemes, and at least one of them usually appears in even the shortest of speech segments. Using the fast, CWT algorithm, the details of both the formant frequency and the glottal excitation characteristics can be easily extracted from voice waveforms. The differences in the glottal excitation waveforms as well as the formant frequency are evident in the CWT output. More significantly, the CWT reveals significant

Neurolinguistic Programming: Add It To Your Tool Chest of Interpretive Techniques.

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Parratt, Smitty

1997-01-01

Highlights the importance of using verbal and nonverbal neurolinguistic programming to maximize the potential of interactions between interpreters and the general public and to improve long-term interactions. Discusses the power of mirroring and representational systems. Contains 29 references. (JRH)

Effect of neurolinguistic programming training on self-actualization as measured by the Personal Orientation Inventory.

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Duncan, R C; Konefal, J; Spechler, M M

1990-06-01

Neurolinguistic programming training is based on principles that should enable the trainee to be more "present"-oriented, inner-directed, flexible, self-aware, and responsive to others, that is, more self-actualized. This study reports within-person changes on self-actualization measures of the Personal Orientation Inventory following a 24-day residential training in neurolinguistic programming. Significant positive mean changes were found for 18 master practitioners on nine of the 12 scales and for 36 practitioners on 10 of the 12 scales. Findings are consistent with the hypothesis that training increases individual self-actualization scores.

PENERAPAN HIPNOTEACHING MELALUI NEURO-LINGUISTIC PROGRAMMING DALAM PEMBELAJARAN KIMIA

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S. Ismuzaroh

2013-10-01

Full Text Available Tujuan penerapan hypnoteaching melalui neuro linguistic programming (NLP dalam proses pembelajaran kimia adalah untuk menghilangkan pikiran negatif siswa terhadap pembelajaran kimia, yang selanjutnya meningkatkan minat, motivasi dan keaktifan belajar kimia siswa. Hasil penelitian menunjukkan siswa lebih terbuka, berani mengemukakan pendapat terhadap permasalahan kimia yang pelajari, siswa merasa fresh, dan nyaman. Hypnoteaching goals through the application of neuro linguistic programming (NLP is a chemical in the learning process to eliminate the negative thoughts of students towards learning chemistry, which further increase the interest, motivation and active learning chemistry students. Results showed students were more open, daring to express opinions on issues studied chemistry, students feel fresh, and comfortable.

Neurolinguistic programming training, trait anxiety, and locus of control.

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Konefal, J; Duncan, R C; Reese, M A

1992-06-01

Training in the neurolinguistic programming techniques of shifting perceptual position, visual-kinesthetic dissociation, timelines, and change-history, all based on experiential cognitive processing of remembered events, leads to an increased awareness of behavioral contingencies and a more sensitive recognition of environmental cues which could serve to lower trait anxiety and increase the sense of internal control. This study reports on within-person and between-group changes in trait anxiety and locus of control as measured on the Spielberger State-Trait Anxiety Inventory and Wallston, Wallston, and DeVallis' Multiple Health Locus of Control immediately following a 21-day residential training in neurolinguistic programming. Significant with-in-person decreases in trait-anxiety scores and increases in internal locus of control scores were observed as predicted. Chance and powerful other locus of control scores were unchanged. Significant differences were noted on trait anxiety and locus of control scores between European and U.S. participants, although change scores were similar for the two groups. These findings are consistent with the hypothesis that this training may lower trait-anxiety scores and increase internal locus of control scores. A matched control group was not available, and follow-up was unfortunately not possible.

THE PROGRAMMING NEURO-LINGUISTICS AND THEIR APPLICABILITY IN THE PROCESS OF RECRUITMENT AND SELECTION

Directory of Open Access Journals (Sweden)

Gilma Álamo Sánchez

2008-04-01

Full Text Available He/she is carried out a study referred to tools of Programming Neuro-linguistics (PNL for the Selection, Employment and Training that allow choosing the appropriate personnel taking the language and the behavior as a result. For their development theories were revised referred to the PNL and the recruitment process and selection sustained in the process of the interview. The summations are oriented to the importance and convenience for the Management of Human resources of applying the Programming Neuro-linguistics as selection tool of personal. Finally it is recommended to apply the proposal inside the mark of adaptability according to the necessities and demands of each organization.

Teaching Assistants, Neuro-Linguistic Programming (NLP) and Special Educational Needs: "Reframing" the Learning Experience for Students with Mild SEN

Science.gov (United States)

Kudliskis, Voldis

2014-01-01

This study examines how an understanding of two NLP concepts, the meta-model of language and the implementation of reframing, could be used to help teaching assistants enhance class-based interactions with students with mild SEN. Participants (students) completed a pre-intervention and a post-intervention "Beliefs About my Learning…

Assessment of Primary Representational Systems with Neurolinguistic Programming: Examination of Preliminary Literature.

Science.gov (United States)

Dorn, Fred J.; And Others

1983-01-01

Reviews the inconsistent findings of studies on neurolinguistic programing and recommends some areas that should be examined to verify various claims. Discusses methods of assessing client's primary representational systems, including predicate usage and eye movements, and suggests that more reliable methods of assessing PRS must be found. (JAC)

Sales Training for Army Recruiter Success: Modeling the Sales Strategies and Skills of Excellent Recruiters

Science.gov (United States)

1987-11-01

strategies used by excellent Army recruiters. Neurolinguistic programming (NLP) was used as the protocol for modeling performance and acquiring...Behavioral and Social Sciences 3001 Eisenhower Avenue, Alexandria, VA 22333-5600 10. PROGRAM ELEMENT. PROJECT. TASK ARE* 4 WORK UNIT...Modeling ’Expert knowledge,, Neurolinguistics Knowledge engineering; Recruiting Sales, &’ Sales cycle Sales skills Sales strategies 20

Hypothesized eye movements of neurolinguistic programming: a statistical artifact.

Science.gov (United States)

Farmer, A; Rooney, R; Cunningham, J R

1985-12-01

Neurolinguistic programming's hypothesized eye-movements were measured independently from videotapes of 30 subjects, aged 15 to 76 yr., who were asked to recall visual pictures, recorded audio sounds, and textural objects. chi 2 indicated that subjects' responses were significantly different from those predicted. When chi 2 comparisons were weighted by number of eye positions assigned to each modality (3 visual, 3 auditory, 1 kinesthetic), subjects' responses did not differ significantly from the expected pattern. These data indicate that the eye-movement hypothesis may represent randomly occurring rather than sensory-modality-related positions.

An exploratory study of neuro linguistic programming and communication anxiety

Science.gov (United States)

Brunner, Lois M.

1993-12-01

This thesis is an exploratory study of Neuro-Linguistic Programming (NLP), and its capabilities to provide a technique or a composite technique that will reduce the anxiety associated with making an oral brief or presentation before a group, sometimes referred to as Communication Apprehension. The composite technique comes from NLP and Time Line Therapy, which is an extension to NLP. Student volunteers (17) from a Communications course given by the Administrative Sciences Department were taught this technique. For each volunteer, an informational oral presentation was made and videotaped before the training and another informational oral presentation made and videotaped following the training. The before and after training presentations for each individual volunteer were evaluated against criteria for communications anxiety and analyzed to determine if there was a noticeable reduction of anxiety after the training. Anxiety was reduced in all of the volunteers in this study.

Neuro-linguistic programming as a communication tool for management

OpenAIRE

2014-01-01

M.Com. (Business Management) The outcome of the study was to explore the use of neuro linguistic programming as a communication tool that enhances communication in the workplace, and the results revealed that NLP business communications differ from the usual workplace communications. They involve communications that identify explicit and achievable outcomes, use sensory awareness to notice responses and flexibly alter behaviour to achieve outcomes. Participants were noticing and discoverin...

Comparison for aphasic and control subjects of eye movements hypothesized in neurolinguistic programming.

Science.gov (United States)

Dooley, K O; Farmer, A

1988-08-01

Neurolinguistic programming's hypothesized eye movements were measured independently using videotapes of 10 nonfluent aphasic and 10 control subjects matched for age and sex. Chi-squared analysis indicated that eye-position responses were significantly different for the groups. Although earlier research has not supported the hypothesized eye positions for normal subjects, the present findings support the contention that eye-position responses may differ between neurologically normal and aphasic individuals.

MODEL PEMBELAJARAN NEUROLINGUISTIC PROGRAMMING BERORIENTASI KARAKTER BAGI PENINGKATAN KEMAMPUAN MENULIS SISWA SMP

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Wikanengsih -

2014-06-01

Abstrak: Model Pembelajaran Neurolinguistic Programming Berorientasi Karakter untuk Mening­katkan Kemampuan Menulis Siswa. Penelitian ini bertujuan untuk mengetahui keefektifan model pem­belajaran neurolinguistik programming berorientasi karakter (MPNLPBK terhadap kemampuan menulis siswa. Metode penelitian yang digunakan metode penelitian kombinasi (mixed method jenis sequential exploratory strategy. Hasil penelitian tahap pertama (penelitian kualitatif menghasilkan model pembelajaran hipotetik. Penelitian tahap kedua merupakan uji coba penerapan model hipotetik (penelitian kuantitatif. Hasil pengujian menunjukkan bahwa pembelajaran menulis dengan menggunakan MPNLPBK dapat meningkatkan kemampuan menulis siswa kelompok eksperimen. Selain itu, berdasarkan hasil pengamatan terhadap aspek karakter komunikatif, toleran, tanggungjawab dan kreatif siswa, terdapat perkembangan pada diri siswa untuk setiap aspek tersebut.

Sales Training for Army Recruiter Success: Sales Strategies and Skills Used by Excellent U. S. Army Recruiters

Science.gov (United States)

1987-11-01

Army recruiters. Neurolinguistic programming (NLP) was used as the protocol for modeling performance and acquiring information on the communication...kills -Linguistic pattern~ Sales cycle, Communica tion s trategies Mode-H.R-g. Sales skills, {:( ~Expert kn0\\vlc dge1 ’ Neurolinguist ic~ Sales...describe s a program of r esearch on the communicat ion st rate - gies a nd skills use d by excellen t Army r ecrui t e rs. Information to be used to

NLP

DEFF Research Database (Denmark)

Krogsdal, Iben

2007-01-01

Artiklen søger at problematisere forståelsen af terapiformen NLP (Neuro Linguistisk Programmering) som fremelsker af selvstyrende individer. Den viser, hvordan NLP - gennem sin underliggende fortælling om det autentiske menneske som ideal - fordrer et fortsat selvudviklingarbejde via terapeutisk ...

Neurolinguistic programming used to reduce the need for anaesthesia in claustrophobic patients undergoing MRI

OpenAIRE

Bigley, J; Griffiths, P D; Prydderch, A; Romanowski, C A J; Miles, L; Lidiard, H; Hoggard, N

2010-01-01

The purpose of this study was to assess the success of neurolinguistic programming in reducing the need for general anaesthesia in claustrophobic patients who require MRI and to consider the financial implications for health providers. This was a prospective study performed in 2006 and 2007 at a teaching hospital in England and comprised 50 adults who had unsuccessful MR examinations because of claustrophobia. The main outcome measures were the ability to tolerate a successful MR examination ...

Mõisteid ja meetodeid kaasaegsetes pedagoogilistes süsteemides

Index Scriptorium Estoniae

1999-01-01

Mõistete multiintelligentsus ja NLP - Neuro-Linguistic Programming tähendusest]; emotsionaalne intelligentsus : [mõiste emotsionaalne intelligentsus tähendusest]; konvergentne ja divergentne mõtlemine - inimese mõtlemisprotsessi 2 külge : [mõistete konvergentne ja divergentne mõtlemine tähendusest

DE and NLP Based QPLS Algorithm

Science.gov (United States)

Yu, Xiaodong; Huang, Dexian; Wang, Xiong; Liu, Bo

As a novel evolutionary computing technique, Differential Evolution (DE) has been considered to be an effective optimization method for complex optimization problems, and achieved many successful applications in engineering. In this paper, a new algorithm of Quadratic Partial Least Squares (QPLS) based on Nonlinear Programming (NLP) is presented. And DE is used to solve the NLP so as to calculate the optimal input weights and the parameters of inner relationship. The simulation results based on the soft measurement of diesel oil solidifying point on a real crude distillation unit demonstrate that the superiority of the proposed algorithm to linear PLS and QPLS which is based on Sequential Quadratic Programming (SQP) in terms of fitting accuracy and computational costs.

Do HCI and NLP Interact?

NARCIS (Netherlands)

Karamanis, N.; Schneider, A.; van der Sluis, Ielka; Schlogl, S.; Doherty, G.; Luz, S.

2009-01-01

We examine the relationship between HCI and Natural Language Processing (NLP) by performing a bibliometric analysis and looking at the specific example of BioNLP. We identify opportunities for HCI to fertilise current NLP research and suggest that HCI will benefit from looking at advances in NLP

Visual imagery and the user model applied to fuel handling at EBR-II

International Nuclear Information System (INIS)

Brown-VanHoozer, S.A.

1995-01-01

The material presented in this paper is based on two studies involving visual display designs and the user's perspective model of a system. The studies involved a methodology known as Neuro-Linguistic Programming (NLP), and its use in expanding design choices which included the ''comfort parameters'' and ''perspective reality'' of the user's model of the world. (author)

A different approach to designing visual displays and workstations

Energy Technology Data Exchange (ETDEWEB)

Brown-VanHoozer, S.A.

1995-06-01

The material presented in this paper is based on two studies involving the design of visual displays based on the user`s perspective model of a system. The studies involve a methodology known as Neuro-Linguistic Programming (NLP), and its use in expanding design choices from the user`s ``model of the world,`` and the use of virtual reality.

GENERAL ASPECTS OF NLP IN TEACHING LANGUAGES

Directory of Open Access Journals (Sweden)

Clementina Niţă

2011-11-01

Full Text Available This article is focus on NLP as a tool helping to improve personal excellence in teaching languages. NLP states that learning begins in the students’ frame of reference and thus, it is important for teachers to increase their interpersonal skills and ability to recognize it. A map of how language operates is drawn by the Meta Model - a tool for a fuller understanding of what people say -, which deals with the concepts of surface structure and deep structure. The meta programs deal with deletions, distortions and generalisations which appear in language during communication. Establish rapport is a helpful method to create favourable teaching atmosphere and humanising teaching is a way to improve students’ performance.

Sales Training for Army Recruiter Success: Interviews with Excellent Recruiters

Science.gov (United States)

1987-11-01

merit of an expert modeling system of the skills and strategies used by excel- lent Army recruiters. Neurolinguistic programming (NLP) was used as the...7. AUTHOR(&) 8. CONTRACT OR GRANT NUMBER(s) Steven R. Frieman 9. PERFORMING ORGANIZATION NAME AND ADDRESS 10. PROGRAM ELEMENT. PROJECT, TASK U.S...Recruiting 2M AUSTIRACT (rcnttm ame r orw am nssry i Identify by block number) s-This report describes a program of research on communication strategies and

Optimization of a gas turbine in the methanol process, using the NLP model

International Nuclear Information System (INIS)

Kralj, Anita Kovac; Glavic, Peter

2007-01-01

Heat and power integration can reduce fuel usage, CO 2 and SO 2 emissions and, thereby, pollution. In the simultaneous heat and power integration approach and including additional production, the optimization problem is formulated using a simplified process superstructure. Nonlinear programming (NLP) contains equations which enable structural heat and power integration and parametric optimization. In the present work, the NLP model is formulated as an optimum energy target of process integration and electricity generation using a gas turbine with a separator. The reactor acts as a combustion chamber of the gas turbine plant, producing high temperature. The simultaneous NLP approach can account for capital cost, integration of combined heat and power, process modification, and additional production trade-offs accurately, and can thus yield a better solution. It gives better results than non-simultaneous methods. The NLP model does not guarantee a global cost optimum, but it does lead to good, perhaps near optimum designs. This approach is illustrated by an existing, complex methanol production process. The objective function generates a possible increase in annual profit of 1.7 MEUR/a

Neuro-Linguistic Programming: Improving Rapport between Track/Cross Country Coaches and Significant Others

Science.gov (United States)

Helm, David Jay

2017-01-01

This study examines the background information and the components of N.L.P., being eye movements, use of predicates, and posturing, as they apply to improving rapport and empathy between track/cross country coaches and their significant others in the arena of competition to help alleviate the inherent stressors.

Robo-Sensei's NLP-Based Error Detection and Feedback Generation

Science.gov (United States)

Nagata, Noriko

2009-01-01

This paper presents a new version of Robo-Sensei's NLP (Natural Language Processing) system which updates the version currently available as the software package "ROBO-SENSEI: Personal Japanese Tutor" (Nagata, 2004). Robo-Sensei's NLP system includes a lexicon, a morphological generator, a word segmentor, a morphological parser, a syntactic…

Contribution of NLP to the Content Indexing of Multimedia Documents

NARCIS (Netherlands)

Declerck, T.; Enser, P.; Saggion, H.; Kompatsiaris, Y.; Kuper, Jan; O' Connor, N.E.; Samiotou, A.; Wittenburg, P.; Contreras, J.

2004-01-01

This paper describes the role natural language processing (NLP) can play for multimedia applications. As an example of such an application, we present an approach dealing with the conceptual indexing of soccer videos which the help of structured information automatically extracted by NLP tools from

Developing safer systems in a NPP environment using the operator`s comfort parameters and virtual reality

Energy Technology Data Exchange (ETDEWEB)

Brown-VanHoozer, S.A.

1995-07-01

The contents of this paper is based on two studies involving the design of visual displays from the operator`s point of view, and the utilization of virtual reality for operations, training and maintenance repairs. The studies involve a methodology known as Neuro-Linguistic Programming (NLP), and its use in strengthening design choices from the user`s perspective model of the environment. The contents of this paper focuses on the results which may be implemented in nuclear power plants for the purpose of providing systems which are less inherently error prone.

The method of global learning in teaching foreign languages

Directory of Open Access Journals (Sweden)

Tatjana Dragovič

2001-12-01

Full Text Available The authors describe the method of global learning of foreign languages, which is based on the principles of neurolinguistic programming (NLP. According to this theory, the educator should use the method of the so-called periphery learning, where students learn relaxation techniques and at the same time they »incidentally « or subconsciously learn a foreign language. The method of global learning imitates successful strategies of learning in early childhood and therefore creates a relaxed attitude towards learning. Global learning is also compared with standard methods.

NLP model and stochastic multi-start optimization approach for heat exchanger networks

International Nuclear Information System (INIS)

Núñez-Serna, Rosa I.; Zamora, Juan M.

2016-01-01

Highlights: • An NLP model for the optimal design of heat exchanger networks is proposed. • The NLP model is developed from a stage-wise grid diagram representation. • A two-phase stochastic multi-start optimization methodology is utilized. • Improved network designs are obtained with different heat load distributions. • Structural changes and reductions in the number of heat exchangers are produced. - Abstract: Heat exchanger network synthesis methodologies frequently identify good network structures, which nevertheless, might be accompanied by suboptimal values of design variables. The objective of this work is to develop a nonlinear programming (NLP) model and an optimization approach that aim at identifying the best values for intermediate temperatures, sub-stream flow rate fractions, heat loads and areas for a given heat exchanger network topology. The NLP model that minimizes the total annual cost of the network is constructed based on a stage-wise grid diagram representation. To improve the possibilities of obtaining global optimal designs, a two-phase stochastic multi-start optimization algorithm is utilized for the solution of the developed model. The effectiveness of the proposed optimization approach is illustrated with the optimization of two network designs proposed in the literature for two well-known benchmark problems. Results show that from the addressed base network topologies it is possible to achieve improved network designs, with redistributions in exchanger heat loads that lead to reductions in total annual costs. The results also show that the optimization of a given network design sometimes leads to structural simplifications and reductions in the total number of heat exchangers of the network, thereby exposing alternative viable network topologies initially not anticipated.

Expression of Caenorhabditis elegans antimicrobial peptide NLP-31 in Escherichia coli

Science.gov (United States)

Lim, Mei-Perng; Nathan, Sheila

2014-09-01

Burkholderia pseudomallei is the causative agent of melioidosis, a fulminant disease endemic in Southeast Asia and Northern Australia. The standardized form of therapy is antibiotics treatment; however, the bacterium has become increasingly resistant to these antibiotics. This has spurred the need to search for alternative therapeutic agents. Antimicrobial peptides (AMPs) are small proteins that possess broad-spectrum antimicrobial activity. In a previous study, the nematode Caenorhabditis elegans was infected by B. pseudomallei and a whole animal transcriptome analysis identified a number of AMP-encoded genes which were induced significantly in the infected worms. One of the AMPs identified is NLP-31 and to date, there are no reports of anti-B. pseudomallei activity demonstrated by NLP-31. To produce NLP-31 protein for future studies, the gene encoding for NLP-31 was cloned into the pET32b expression vector and transformed into Escherichia coli BL21(DE3). Protein expression was induced with 1 mM IPTG for 20 hours at 20°C and recombinant NLP-31 was detected in the soluble fraction. Taken together, a simple optimized heterologous production of AMPs in an E. coli expression system has been successfully developed.

Cultural neurolinguistics.

Science.gov (United States)

Chen, Chuansheng; Xue, Gui; Mei, Leilei; Chen, Chunhui; Dong, Qi

2009-01-01

As the only species that evolved to possess a language faculty, humans have been surprisingly generative in creating a diverse array of language systems. These systems vary in phonology, morphology, syntax, and written forms. Before the advent of modern brain-imaging techniques, little was known about how differences across languages are reflected in the brain. This chapter aims to provide an overview of an emerging area of research - cultural neurolinguistics - that examines systematic cross-cultural/crosslinguistic variations in the neural networks of languages. We first briefly describe general brain networks for written and spoken languages. We then discuss language-specific brain regions by highlighting differences in neural bases of different scripts (logographic vs. alphabetic scripts), orthographies (transparent vs. nontransparent orthographies), and tonality (tonal vs. atonal languages). We also discuss neural basis of second language and the role of native language experience in second-language acquisition. In the last section, we outline a general model that integrates culture and neural bases of language and discuss future directions of research in this area.

Parallelization of Neural Network Training for NLP with Hogwild!

Directory of Open Access Journals (Sweden)

Deyringer Valentin

2017-10-01

Full Text Available Neural Networks are prevalent in todays NLP research. Despite their success for different tasks, training time is relatively long. We use Hogwild! to counteract this phenomenon and show that it is a suitable method to speed up training Neural Networks of different architectures and complexity. For POS tagging and translation we report considerable speedups of training, especially for the latter. We show that Hogwild! can be an important tool for training complex NLP architectures.

Discovery of nitrate-CPK-NLP signalling in central nutrient-growth networks

Science.gov (United States)

Liu, Kun-hsiang; Niu, Yajie; Konishi, Mineko; Wu, Yue; Du, Hao; Sun Chung, Hoo; Li, Lei; Boudsocq, Marie; McCormack, Matthew; Maekawa, Shugo; Ishida, Tetsuya; Zhang, Chao; Shokat, Kevan; Yanagisawa, Shuichi; Sheen, Jen

2018-01-01

Nutrient signalling integrates and coordinates gene expression, metabolism and growth. However, its primary molecular mechanisms remain incompletely understood in plants and animals. Here we report novel Ca2+ signalling triggered by nitrate with live imaging of an ultrasensitive biosensor in Arabidopsis leaves and roots. A nitrate-sensitized and targeted functional genomic screen identifies subgroup III Ca2+-sensor protein kinases (CPKs) as master regulators orchestrating primary nitrate responses. A chemical switch with the engineered CPK10(M141G) kinase enables conditional analyses of cpk10,30,32 to define comprehensive nitrate-associated regulatory and developmental programs, circumventing embryo lethality. Nitrate-CPK signalling phosphorylates conserved NIN-LIKE PROTEIN (NLP) transcription factors (TFs) to specify reprogramming of gene sets for downstream TFs, transporters, N-assimilation, C/N-metabolism, redox, signalling, hormones, and proliferation. Conditional cpk10,30,32 and nlp7 similarly impair nitrate-stimulated system-wide shoot growth and root establishment. The nutrient-coupled Ca2+ signalling network integrates transcriptome and cellular metabolism with shoot-root coordination and developmental plasticity in shaping organ biomass and architecture. PMID:28489820

Assessing Primary Representational System (PRS) Preference for Neurolinguistic Programming (NLP) Using Three Methods.

Science.gov (United States)

Dorn, Fred J.

1983-01-01

Considered three methods of identifying Primary Representational System (PRS)--an interview, a word list, and a self-report--in a study of 120 college students. Results suggested the three methods offer little to counselors either collectively or individually. Results did not validate the PRS construct, suggesting the need for further research.…

Evidence-based Neuro Linguistic Psychotherapy: a meta-analysis.

Science.gov (United States)

Zaharia, Cătălin; Reiner, Melita; Schütz, Peter

2015-12-01

Neuro Linguistic Programming (NLP) Framework has enjoyed enormous popularity in the field of applied psychology. NLP has been used in business, education, law, medicine and psychotherapy to identify people's patterns and alter their responses to stimuli, so they are better able to regulate their environment and themselves. NLP looks at achieving goals, creating stable relationships, eliminating barriers such as fears and phobias, building self-confidence, and self-esteem, and achieving peak performance. Neuro Linguistic Psychotherapy (NLPt) encompasses NLP as framework and set of interventions in the treatment of individuals with different psychological and/or social problems. We aimed systematically to analyse the available data regarding the effectiveness of Neuro Linguistic Psychotherapy (NLPt). The present work is a meta-analysis of studies, observational or randomized controlled trials, for evaluating the efficacy of Neuro Linguistic Programming in individuals with different psychological and/or social problems. The databases searched to identify studies in English and German language: CENTRAL in the Cochrane Library; PubMed; ISI Web of Knowledge (include results also from Medline and the Web of Science); PsycINFO (including PsycARTICLES); Psyndex; Deutschsprachige Diplomarbeiten der Psychologie (database of theses in Psychology in German language), Social SciSearch; National library of health and two NLP-specific research databases: one from the NLP Community (http://www.nlp.de/cgi-bin/research/nlprdb.cgi?action=res_entries) and one from the NLP Group (http://www.nlpgrup.com/bilimselarastirmalar/bilimsel-arastirmalar-4.html#Zweig154). From a total number of 425 studies, 350 were removed and considered not relevant based on the title and abstract. Included, in the final analysis, are 12 studies with numbers of participants ranging between 12 and 115 subjects. The vast majority of studies were prospective observational. The actual paper represents the first

Comment Dire: a Neurolinguistic Approach to Beckett's Bilingual Writings

Science.gov (United States)

Kager, Maria

2015-01-01

Recent studies from the field of neurolinguistics and psycholinguistics suggest that bilinguals and multilinguals are in many ways fundamentally different from monolinguals, a difference that starts with a different cerebral structure for language. This difference will constitute the point of departure for my paper: If multilingual people are…

The NlpD lipoprotein is a novel Yersinia pestis virulence factor essential for the development of plague.

Directory of Open Access Journals (Sweden)

Avital Tidhar

Full Text Available Yersinia pestis is the causative agent of plague. Previously we have isolated an attenuated Y. pestis transposon insertion mutant in which the pcm gene was disrupted. In the present study, we investigated the expression and the role of pcm locus genes in Y. pestis pathogenesis using a set of isogenic surE, pcm, nlpD and rpoS mutants of the fully virulent Kimberley53 strain. We show that in Y. pestis, nlpD expression is controlled from elements residing within the upstream genes surE and pcm. The NlpD lipoprotein is the only factor encoded from the pcm locus that is essential for Y. pestis virulence. A chromosomal deletion of the nlpD gene sequence resulted in a drastic reduction in virulence to an LD(50 of at least 10(7 cfu for subcutaneous and airway routes of infection. The mutant was unable to colonize mouse organs following infection. The filamented morphology of the nlpD mutant indicates that NlpD is involved in cell separation; however, deletion of nlpD did not affect in vitro growth rate. Trans-complementation experiments with the Y. pestis nlpD gene restored virulence and all other phenotypic defects. Finally, we demonstrated that subcutaneous administration of the nlpD mutant could protect animals against bubonic and primary pneumonic plague. Taken together, these results demonstrate that Y. pestis NlpD is a novel virulence factor essential for the development of bubonic and pneumonic plague. Further, the nlpD mutant is superior to the EV76 prototype live vaccine strain in immunogenicity and in conferring effective protective immunity. Thus it could serve as a basis for a very potent live vaccine against bubonic and pneumonic plague.

Non Linear Programming (NLP) formulation for quantitative modeling of protein signal transduction pathways.

Science.gov (United States)

Mitsos, Alexander; Melas, Ioannis N; Morris, Melody K; Saez-Rodriguez, Julio; Lauffenburger, Douglas A; Alexopoulos, Leonidas G

2012-01-01

Modeling of signal transduction pathways plays a major role in understanding cells' function and predicting cellular response. Mathematical formalisms based on a logic formalism are relatively simple but can describe how signals propagate from one protein to the next and have led to the construction of models that simulate the cells response to environmental or other perturbations. Constrained fuzzy logic was recently introduced to train models to cell specific data to result in quantitative pathway models of the specific cellular behavior. There are two major issues in this pathway optimization: i) excessive CPU time requirements and ii) loosely constrained optimization problem due to lack of data with respect to large signaling pathways. Herein, we address both issues: the former by reformulating the pathway optimization as a regular nonlinear optimization problem; and the latter by enhanced algorithms to pre/post-process the signaling network to remove parts that cannot be identified given the experimental conditions. As a case study, we tackle the construction of cell type specific pathways in normal and transformed hepatocytes using medium and large-scale functional phosphoproteomic datasets. The proposed Non Linear Programming (NLP) formulation allows for fast optimization of signaling topologies by combining the versatile nature of logic modeling with state of the art optimization algorithms.

Non Linear Programming (NLP formulation for quantitative modeling of protein signal transduction pathways.

Directory of Open Access Journals (Sweden)

Alexander Mitsos

Full Text Available Modeling of signal transduction pathways plays a major role in understanding cells' function and predicting cellular response. Mathematical formalisms based on a logic formalism are relatively simple but can describe how signals propagate from one protein to the next and have led to the construction of models that simulate the cells response to environmental or other perturbations. Constrained fuzzy logic was recently introduced to train models to cell specific data to result in quantitative pathway models of the specific cellular behavior. There are two major issues in this pathway optimization: i excessive CPU time requirements and ii loosely constrained optimization problem due to lack of data with respect to large signaling pathways. Herein, we address both issues: the former by reformulating the pathway optimization as a regular nonlinear optimization problem; and the latter by enhanced algorithms to pre/post-process the signaling network to remove parts that cannot be identified given the experimental conditions. As a case study, we tackle the construction of cell type specific pathways in normal and transformed hepatocytes using medium and large-scale functional phosphoproteomic datasets. The proposed Non Linear Programming (NLP formulation allows for fast optimization of signaling topologies by combining the versatile nature of logic modeling with state of the art optimization algorithms.

Visual imagery and the user model applied to fuel handling at EBR-II

International Nuclear Information System (INIS)

Brown-VanHoozer, S.A.

1995-01-01

The material presented in this paper is based on two studies involving visual display designs and the user's perspective model of a system. The studies involved a methodology known as Neuro-Linguistic Programming (NLP), and its use in expanding design choices which included the ''comfort parameters'' and ''perspective reality'' of the user's model of the world. In developing visual displays for the EBR-II fuel handling system, the focus would be to incorporate the comfort parameters that overlap from each of the representation systems: visual, auditory and kinesthetic then incorporate the comfort parameters of the most prominent group of the population, and last, blend in the other two representational system comfort parameters. The focus of this informal study was to use the techniques of meta-modeling and synesthesia to develop a virtual environment that closely resembled the operator's perspective of the fuel handling system of Argonne's Experimental Breeder Reactor - II. An informal study was conducted using NLP as the behavioral model in a v reality (VR) setting

NLP pielietošana angļu valodas mācīšanā

OpenAIRE

Gorohova, Diāna

2011-01-01

Neirolingvistiskās programmēšana (NLP) praktiķu aprindās tiek uzskatīta par ļoti efektīvu instrumentu visdažādākajās dzīves sfēras. Šī pieeja ļauj cilvēkiem ticēt saviem spēkiem padarīt viņu dzīves labākas. Tieši tāpēc NLP piekritēji uzskata, ka, NLP pieeju izmantošana angļu valodas mācīšanā, var uzlabot skolēnu angļu valodas zināšanas, kā arī paaugstināt viņu pašapziņu. Šī bakalaura darba autore piedāvā ieskatu NLP vēsturiskajā attīstībā un apskata tās pamatprincipus. Autore analizē NLP t...

Finding 'Evidence of Absence' in Medical Notes: Using NLP for Clinical Inferencing.

Science.gov (United States)

Carter, Marjorie E; Divita, Guy; Redd, Andrew; Rubin, Michael A; Samore, Matthew H; Gupta, Kalpana; Trautner, Barbara W; Gundlapalli, Adi V

2016-01-01

Extracting evidence of the absence of a target of interest from medical text can be useful in clinical inferencing. The purpose of our study was to develop a natural language processing (NLP) pipelineto identify the presence of indwelling urinary catheters from electronic medical notes to aid in detection of catheter-associated urinary tract infections (CAUTI). Finding clear evidence that a patient does not have an indwelling urinary catheter is useful in making a determination regarding CAUTI. We developed a lexicon of seven core concepts to infer the absence of a urinary catheter. Of the 990,391 concepts extractedby NLP from a large corpus of 744,285 electronic medical notes from 5589 hospitalized patients, 63,516 were labeled as evidence of absence.Human review revealed three primary causes for false negatives. The lexicon and NLP pipeline were refined using this information, resulting in outputs with an acceptable false positive rate of 11%.

Visual imagery and the user model applied to fuel handling at EBR-II

Energy Technology Data Exchange (ETDEWEB)

Brown-VanHoozer, S.A.

1995-06-01

The material presented in this paper is based on two studies involving visual display designs and the user`s perspective model of a system. The studies involved a methodology known as Neuro-Linguistic Programming (NLP), and its use in expanding design choices which included the ``comfort parameters`` and ``perspective reality`` of the user`s model of the world. In developing visual displays for the EBR-II fuel handling system, the focus would be to incorporate the comfort parameters that overlap from each of the representation systems: visual, auditory and kinesthetic then incorporate the comfort parameters of the most prominent group of the population, and last, blend in the other two representational system comfort parameters. The focus of this informal study was to use the techniques of meta-modeling and synesthesia to develop a virtual environment that closely resembled the operator`s perspective of the fuel handling system of Argonne`s Experimental Breeder Reactor - II. An informal study was conducted using NLP as the behavioral model in a v reality (VR) setting.

Investigating the Effects of Repeated Reading and NLP : Language Patterns on Reading Rate

OpenAIRE

Ben, Backwell; Brian, Cullen

2018-01-01

This paper investigates EFL student reading speed and describes a quasi-experimental study that attempted to quantify the effects of repeated reading and the use of NLP language patterns in the instructions. An experimental group (n=30) and a control group (n=30) carried out the same timed reading activity three times each lesson for five lessons. The instructions for the experimental group included NLP language patterns designed to promote faster reading. It was shown that the repeated readi...

Language and human nature: Kurt Goldstein's neurolinguistic foundation of a holistic philosophy.

Science.gov (United States)

Ludwig, David

2012-01-01

Holism in interwar Germany provides an excellent example for social and political influences on scientific developments. Deeply impressed by the ubiquitous invocation of a cultural crisis, biologists, physicians, and psychologists presented holistic accounts as an alternative to the "mechanistic worldview" of the nineteenth century. Although the ideological background of these accounts is often blatantly obvious, many holistic scientists did not content themselves with a general opposition to a mechanistic worldview but aimed at a rational foundation of their holistic projects. This article will discuss the work of Kurt Goldstein, who is known for both his groundbreaking contributions to neuropsychology and his holistic philosophy of human nature. By focusing on Goldstein's neurolinguistic research, I want to reconstruct the empirical foundations of his holistic program without ignoring its cultural background. In this sense, Goldstein's work provides a case study for the formation of a scientific theory through the complex interplay between specific empirical evidences and the general cultural developments of the Weimar Republic. © 2012 Wiley Periodicals, Inc.

Neurolinguistics Aspects of Second Language Acquisition

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Laleh Fakhraee Faruji

2011-12-01

Full Text Available   Fundamental breakthroughs in the neurosciences, combined with technical innovations for measuring brain activity, are shedding new light on the neural basis of second language (L2
processing, and on its relationship to native language processing (L1 (Perani & Abutalebi, 2005.  Over the past two decades, a large body of neuroimaging studies has been devoted to the study of the neural organization of language (De´monet, Thierry, & Cardebat, 2005; Indefrey & Levelt, 2004; Price, 2000 as cited in Abutalebi, 2008. The value that functional neuroimaging adds to language research is to improve the perspective on the distributed anatomy of language. Thus, it can be used with considerable precision to identify the neural networks underlying the different domains of language processing. In this paper some main issues related to neurolinguistics and second language acquisition with a focus on bilingualism will be discussed.

A natural language processing program effectively extracts key pathologic findings from radical prostatectomy reports.

Science.gov (United States)

Kim, Brian J; Merchant, Madhur; Zheng, Chengyi; Thomas, Anil A; Contreras, Richard; Jacobsen, Steven J; Chien, Gary W

2014-12-01

Natural language processing (NLP) software programs have been widely developed to transform complex free text into simplified organized data. Potential applications in the field of medicine include automated report summaries, physician alerts, patient repositories, electronic medical record (EMR) billing, and quality metric reports. Despite these prospects and the recent widespread adoption of EMR, NLP has been relatively underutilized. The objective of this study was to evaluate the performance of an internally developed NLP program in extracting select pathologic findings from radical prostatectomy specimen reports in the EMR. An NLP program was generated by a software engineer to extract key variables from prostatectomy reports in the EMR within our healthcare system, which included the TNM stage, Gleason grade, presence of a tertiary Gleason pattern, histologic subtype, size of dominant tumor nodule, seminal vesicle invasion (SVI), perineural invasion (PNI), angiolymphatic invasion (ALI), extracapsular extension (ECE), and surgical margin status (SMS). The program was validated by comparing NLP results to a gold standard compiled by two blinded manual reviewers for 100 random pathology reports. NLP demonstrated 100% accuracy for identifying the Gleason grade, presence of a tertiary Gleason pattern, SVI, ALI, and ECE. It also demonstrated near-perfect accuracy for extracting histologic subtype (99.0%), PNI (98.9%), TNM stage (98.0%), SMS (97.0%), and dominant tumor size (95.7%). The overall accuracy of NLP was 98.7%. NLP generated a result in report. This novel program demonstrated high accuracy and efficiency identifying key pathologic details from the prostatectomy report within an EMR system. NLP has the potential to assist urologists by summarizing and highlighting relevant information from verbose pathology reports. It may also facilitate future urologic research through the rapid and automated creation of large databases.

Neurolinguistics and psycholinguistics as a basis for computer acquisition of natural language

Energy Technology Data Exchange (ETDEWEB)

Powers, D.M.W.

1983-04-01

Research into natural language understanding systems for computers has concentrated on implementing particular grammars and grammatical models of the language concerned. This paper presents a rationale for research into natural language understanding systems based on neurological and psychological principles. Important features of the approach are that it seeks to place the onus of learning the language on the computer, and that it seeks to make use of the vast wealth of relevant psycholinguistic and neurolinguistic theory. 22 references.

Lithium NLP: A System for Rich Information Extraction from Noisy User Generated Text on Social Media

OpenAIRE

Bhargava, Preeti; Spasojevic, Nemanja; Hu, Guoning

2017-01-01

In this paper, we describe the Lithium Natural Language Processing (NLP) system - a resource-constrained, high- throughput and language-agnostic system for information extraction from noisy user generated text on social media. Lithium NLP extracts a rich set of information including entities, topics, hashtags and sentiment from text. We discuss several real world applications of the system currently incorporated in Lithium products. We also compare our system with existing commercial and acad...

NLP and the Humanities: The Revival of an Old Liaison

NARCIS (Netherlands)

de Jong, Franciska M.G.

This paper presents an overview of some emerging trends in the application of NLP in the domain of the so-called Digital Humanities and discusses the role and nature of metadata, the annotation layer that is so characteristic of documents that play a role in the scholarly practises of the

NLP model of a LiBr–H2O absorption refrigeration system for the minimization of the annual operating cost

International Nuclear Information System (INIS)

Rubio-Maya, Carlos; Pacheco-Ibarra, J. Jesús; Belman-Flores, Juan M.; Galván-González, Sergio R.; Mendoza-Covarrubias, Crisanto

2012-01-01

In this paper the optimization of a LiBr–H 2 O absorption refrigeration system with the annual operating cost as the objective function to be minimized is presented. The optimization problem is established as a Non-Linear Programming (NLP) model allowing a formulation of the problem in a simple and structured way, and reducing the typical complexity of the thermal systems. The model is composed of three main parts: the thermodynamic model based on the exergy concept including also the proper formulation for the thermodynamic properties of the LiBr–H 2 O mixture, the second is the economic model and the third part composed by inequality constraints. The solution of the model is obtained using the CONOPT solver suitable for NLP problems (code is available on request). The results show the values of the decision variables that minimize the annual cost under the set of assumptions considered in the model and agree well with those reported in other works using different optimization approaches. - Highlights: ► The optimization of an ARS is presented using the annual operating cost as the objective function. ► The problem is established as an NLP model allowing a formulation in a simple and structured way. ► Several formulations for the thermodynamic properties were tested to implement the simpler ones. ► The results obtained agree well with those reported in the work being in comparison.

Mapping Partners Master Drug Dictionary to RxNorm using an NLP-based approach.

Science.gov (United States)

Zhou, Li; Plasek, Joseph M; Mahoney, Lisa M; Chang, Frank Y; DiMaggio, Dana; Rocha, Roberto A

2012-08-01

To develop an automated method based on natural language processing (NLP) to facilitate the creation and maintenance of a mapping between RxNorm and a local medication terminology for interoperability and meaningful use purposes. We mapped 5961 terms from Partners Master Drug Dictionary (MDD) and 99 of the top prescribed medications to RxNorm. The mapping was conducted at both term and concept levels using an NLP tool, called MTERMS, followed by a manual review conducted by domain experts who created a gold standard mapping. The gold standard was used to assess the overall mapping between MDD and RxNorm and evaluate the performance of MTERMS. Overall, 74.7% of MDD terms and 82.8% of the top 99 terms had an exact semantic match to RxNorm. Compared to the gold standard, MTERMS achieved a precision of 99.8% and a recall of 73.9% when mapping all MDD terms, and a precision of 100% and a recall of 72.6% when mapping the top prescribed medications. The challenges and gaps in mapping MDD to RxNorm are mainly due to unique user or application requirements for representing drug concepts and the different modeling approaches inherent in the two terminologies. An automated approach based on NLP followed by human expert review is an efficient and feasible way for conducting dynamic mapping. Copyright © 2011 Elsevier Inc. All rights reserved.

Insights into Substrate Specificity of NlpC/P60 Cell Wall Hydrolases Containing Bacterial SH3 Domains

Energy Technology Data Exchange (ETDEWEB)

Xu, Qingping; Mengin-Lecreulx, Dominique; Liu, Xueqian W.; Patin, Delphine; Farr, Carol L.; Grant, Joanna C.; Chiu, Hsiu-Ju; Jaroszewski, Lukasz; Knuth, Mark W.; Godzik, Adam; Lesley, Scott A.; Elsliger, Marc-André; Deacon, Ashley M.; Wilson, Ian A.

2015-09-15

Bacterial SH3 (SH3b) domains are commonly fused with papain-like Nlp/P60 cell wall hydrolase domains. To understand how the modular architecture of SH3b and NlpC/P60 affects the activity of the catalytic domain, three putative NlpC/P60 cell wall hydrolases were biochemically and structurally characterized. These enzymes all have γ-d-Glu-A₂pm (A₂pm is diaminopimelic acid) cysteine amidase (ordl-endopeptidase) activities but with different substrate specificities. One enzyme is a cell wall lysin that cleaves peptidoglycan (PG), while the other two are cell wall recycling enzymes that only cleave stem peptides with an N-terminall-Ala. Their crystal structures revealed a highly conserved structure consisting of two SH3b domains and a C-terminal NlpC/P60 catalytic domain, despite very low sequence identity. Interestingly, loops from the first SH3b domain dock into the ends of the active site groove of the catalytic domain, remodel the substrate binding site, and modulate substrate specificity. Two amino acid differences at the domain interface alter the substrate binding specificity in favor of stem peptides in recycling enzymes, whereas the SH3b domain may extend the peptidoglycan binding surface in the cell wall lysins. Remarkably, the cell wall lysin can be converted into a recycling enzyme with a single mutation.

IMPORTANCEPeptidoglycan is a meshlike polymer that envelops the bacterial plasma membrane and bestows structural integrity. Cell wall lysins and recycling enzymes are part of a set of lytic enzymes that target covalent bonds connecting the amino acid and amino sugar building blocks of the PG network. These hydrolases are involved in processes such as cell growth and division, autolysis, invasion, and PG turnover and recycling. To avoid cleavage of unintended substrates, these enzymes have very selective substrate specificities. Our biochemical and structural

Canary: An NLP Platform for Clinicians and Researchers.

Science.gov (United States)

Malmasi, Shervin; Sandor, Nicolae L; Hosomura, Naoshi; Goldberg, Matt; Skentzos, Stephen; Turchin, Alexander

2017-05-03

Information Extraction methods can help discover critical knowledge buried in the vast repositories of unstructured clinical data. However, these methods are underutilized in clinical research, potentially due to the absence of free software geared towards clinicians with little technical expertise. The skills required for developing/using such software constitute a major barrier for medical researchers wishing to employ these methods. To address this, we have developed Canary, a free and open-source solution designed for users without natural language processing (NLP) or software engineering experience. It was designed to be fast and work out of the box via a user-friendly graphical interface.

Neurolinguistic Relativity: How Language Flexes Human Perception and Cognition.

Science.gov (United States)

Thierry, Guillaume

2016-09-01

The time has come, perhaps, to go beyond merely acknowledging that language is a core manifestation of the workings of the human mind and that it relates interactively to all aspects of thinking. The issue, thus, is not to decide whether language and human thought may be ineluctably linked (they just are), but rather to determine what the characteristics of this relationship may be and to understand how language influences-and may be influenced by-nonverbal information processing. In an attempt to demystify linguistic relativity, I review neurolinguistic studies from our research group showing a link between linguistic distinctions and perceptual or conceptual processing. On the basis of empirical evidence showing effects of terminology on perception, language-idiosyncratic relationships in semantic memory, grammatical skewing of event conceptualization, and unconscious modulation of executive functioning by verbal input, I advocate a neurofunctional approach through which we can systematically explore how languages shape human thought.

Novel Use of Natural Language Processing (NLP to Predict Suicidal Ideation and Psychiatric Symptoms in a Text-Based Mental Health Intervention in Madrid

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Benjamin L. Cook

2016-01-01

Full Text Available Natural language processing (NLP and machine learning were used to predict suicidal ideation and heightened psychiatric symptoms among adults recently discharged from psychiatric inpatient or emergency room settings in Madrid, Spain. Participants responded to structured mental and physical health instruments at multiple follow-up points. Outcome variables of interest were suicidal ideation and psychiatric symptoms (GHQ-12. Predictor variables included structured items (e.g., relating to sleep and well-being and responses to one unstructured question, “how do you feel today?” We compared NLP-based models using the unstructured question with logistic regression prediction models using structured data. The PPV, sensitivity, and specificity for NLP-based models of suicidal ideation were 0.61, 0.56, and 0.57, respectively, compared to 0.73, 0.76, and 0.62 of structured data-based models. The PPV, sensitivity, and specificity for NLP-based models of heightened psychiatric symptoms (GHQ-12 ≥ 4 were 0.56, 0.59, and 0.60, respectively, compared to 0.79, 0.79, and 0.85 in structured models. NLP-based models were able to generate relatively high predictive values based solely on responses to a simple general mood question. These models have promise for rapidly identifying persons at risk of suicide or psychological distress and could provide a low-cost screening alternative in settings where lengthy structured item surveys are not feasible.

Novel Use of Natural Language Processing (NLP) to Predict Suicidal Ideation and Psychiatric Symptoms in a Text-Based Mental Health Intervention in Madrid.

Science.gov (United States)

Cook, Benjamin L; Progovac, Ana M; Chen, Pei; Mullin, Brian; Hou, Sherry; Baca-Garcia, Enrique

2016-01-01

Natural language processing (NLP) and machine learning were used to predict suicidal ideation and heightened psychiatric symptoms among adults recently discharged from psychiatric inpatient or emergency room settings in Madrid, Spain. Participants responded to structured mental and physical health instruments at multiple follow-up points. Outcome variables of interest were suicidal ideation and psychiatric symptoms (GHQ-12). Predictor variables included structured items (e.g., relating to sleep and well-being) and responses to one unstructured question, "how do you feel today?" We compared NLP-based models using the unstructured question with logistic regression prediction models using structured data. The PPV, sensitivity, and specificity for NLP-based models of suicidal ideation were 0.61, 0.56, and 0.57, respectively, compared to 0.73, 0.76, and 0.62 of structured data-based models. The PPV, sensitivity, and specificity for NLP-based models of heightened psychiatric symptoms (GHQ-12 ≥ 4) were 0.56, 0.59, and 0.60, respectively, compared to 0.79, 0.79, and 0.85 in structured models. NLP-based models were able to generate relatively high predictive values based solely on responses to a simple general mood question. These models have promise for rapidly identifying persons at risk of suicide or psychological distress and could provide a low-cost screening alternative in settings where lengthy structured item surveys are not feasible.

Equitably Distributing Quality of Marine Security Guards Using Integer Programming

Science.gov (United States)

2013-03-01

ARB BALMOD COM DoD DoS E HAF HQ 10 IP IQ LP MOS MCESG MSG MSGAT NLP NMC OSAB PCS PP&O Q RSO SAl SD SE SNCO T-ODP LIST OF...and Eurasia 2 Abu Dhabi, United Arab Emirates India and the Middle East 3 Bangkok, Thailand East Asia and Pacific 4 Fort Lauderdale, Florida South...integer, goal, and quadratic programming. LP models and nonlinear programming ( NLP ) models are very similar in model development for both maximizing

Direct transcriptional activation of BT genes by NLP transcription factors is a key component of the nitrate response in Arabidopsis.

Science.gov (United States)

Sato, Takeo; Maekawa, Shugo; Konishi, Mineko; Yoshioka, Nozomi; Sasaki, Yuki; Maeda, Haruna; Ishida, Tetsuya; Kato, Yuki; Yamaguchi, Junji; Yanagisawa, Shuichi

2017-01-29

Nitrate modulates growth and development, functioning as a nutrient signal in plants. Although many changes in physiological processes in response to nitrate have been well characterized as nitrate responses, the molecular mechanisms underlying the nitrate response are not yet fully understood. Here, we show that NLP transcription factors, which are key regulators of the nitrate response, directly activate the nitrate-inducible expression of BT1 and BT2 encoding putative scaffold proteins with a plant-specific domain structure in Arabidopsis. Interestingly, the 35S promoter-driven expression of BT2 partially rescued growth inhibition caused by reductions in NLP activity in Arabidopsis. Furthermore, simultaneous disruption of BT1 and BT2 affected nitrate-dependent lateral root development. These results suggest that direct activation of BT1 and BT2 by NLP transcriptional activators is a key component of the molecular mechanism underlying the nitrate response in Arabidopsis. Copyright © 2016 Elsevier Inc. All rights reserved.

FIRST AND SECOND LANGUAGE DEVELOPMENT IN YOUNG CHILDREN AND BILINGUALISM IN LIGHT OF LINGUISTICS, NEUROLINGUISTICS AND FINDINGS FROM BRAIN RESEARCH

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Yunus PINAR

2015-10-01

Full Text Available The present review shows that infants begin picking up elements of what will be their first language in the womb, and certainly long before their first coo according to the current guidelines and it presents a descriptive approach to bilingualism and multilingualism. This article is the outcome of a thorough survey of literature and primarily it aims to present the similarities and differences between the L1 and L2 acquisition in light of linguistics, neurolinguistics and findings from brain research. This Review will illustrate various thought and new hypotheses on first and second language development, bilingualism and multilingualism derived from studies in linguistics, neurolinguistics and brain research. In the context of our paper we shall try to describe aspects and stages of first language acquisition from even before birth especially the 20th week of the fetal development of the baby to 60th week of life, as well as the second language acquisition process, which is divided into three types: simultaneous, consecutive and adult. In particular, we will present and discuss some of the main results of the brain researchers like Franceschini and De Bleser and we shall interpret them.

Measuring the readability of sustainability reports: : A corpus-based analysis through standard formulae and NLP

NARCIS (Netherlands)

Smeuninx, N.; De Clerck, B.; Aerts, Walter

2016-01-01

This study characterises and problematises the language of corporate reporting along region, industry, genre, and content lines by applying readability formulae and more advanced natural language processing (NLP)–based analysis to a manually assembled 2.75-million-word corpus. Readability formulae

Applications of NLP Techniques to Computer-Assisted Authoring of Test Items for Elementary Chinese

Science.gov (United States)

Liu, Chao-Lin; Lin, Jen-Hsiang; Wang, Yu-Chun

2010-01-01

The authors report an implemented environment for computer-assisted authoring of test items and provide a brief discussion about the applications of NLP techniques for computer assisted language learning. Test items can serve as a tool for language learners to examine their competence in the target language. The authors apply techniques for…

Toward a Learning Health-care System - Knowledge Delivery at the Point of Care Empowered by Big Data and NLP.

Science.gov (United States)

Kaggal, Vinod C; Elayavilli, Ravikumar Komandur; Mehrabi, Saeed; Pankratz, Joshua J; Sohn, Sunghwan; Wang, Yanshan; Li, Dingcheng; Rastegar, Majid Mojarad; Murphy, Sean P; Ross, Jason L; Chaudhry, Rajeev; Buntrock, James D; Liu, Hongfang

2016-01-01

The concept of optimizing health care by understanding and generating knowledge from previous evidence, ie, the Learning Health-care System (LHS), has gained momentum and now has national prominence. Meanwhile, the rapid adoption of electronic health records (EHRs) enables the data collection required to form the basis for facilitating LHS. A prerequisite for using EHR data within the LHS is an infrastructure that enables access to EHR data longitudinally for health-care analytics and real time for knowledge delivery. Additionally, significant clinical information is embedded in the free text, making natural language processing (NLP) an essential component in implementing an LHS. Herein, we share our institutional implementation of a big data-empowered clinical NLP infrastructure, which not only enables health-care analytics but also has real-time NLP processing capability. The infrastructure has been utilized for multiple institutional projects including the MayoExpertAdvisor, an individualized care recommendation solution for clinical care. We compared the advantages of big data over two other environments. Big data infrastructure significantly outperformed other infrastructure in terms of computing speed, demonstrating its value in making the LHS a possibility in the near future.

A Description Of Space Relations In An NLP Model: The ABBYY Compreno Approach

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Aleksey Leontyev

2015-12-01

Full Text Available The current paper is devoted to a formal analysis of the space category and, especially, to questions bound with the presentation of space relations in a formal NLP model. The aim is to demonstrate how linguistic and cognitive problems relating to spatial categorization, definition of spatial entities, and the expression of different locative senses in natural languages can be solved in an artificial intelligence system. We offer a description of the locative groups in the ABBYY Compreno formalism – an integral NLP framework applied for machine translation, semantic search, fact extraction, and other tasks based on the semantic analysis of texts. The model is based on a universal semantic hierarchy of the thesaurus type and includes a description of all possible semantic and syntactic links every word can attach. In this work we define the set of semantic locative relations between words, suggest different tools for their syntactic presentation, give formal restrictions for the word classes that can denote spaces, and show different strategies of dealing with locative prepositions, especially as far as the problem of their machine translation is concerned.

Toward a Learning Health-care System – Knowledge Delivery at the Point of Care Empowered by Big Data and NLP

Science.gov (United States)

Kaggal, Vinod C.; Elayavilli, Ravikumar Komandur; Mehrabi, Saeed; Pankratz, Joshua J.; Sohn, Sunghwan; Wang, Yanshan; Li, Dingcheng; Rastegar, Majid Mojarad; Murphy, Sean P.; Ross, Jason L.; Chaudhry, Rajeev; Buntrock, James D.; Liu, Hongfang

2016-01-01

The concept of optimizing health care by understanding and generating knowledge from previous evidence, ie, the Learning Health-care System (LHS), has gained momentum and now has national prominence. Meanwhile, the rapid adoption of electronic health records (EHRs) enables the data collection required to form the basis for facilitating LHS. A prerequisite for using EHR data within the LHS is an infrastructure that enables access to EHR data longitudinally for health-care analytics and real time for knowledge delivery. Additionally, significant clinical information is embedded in the free text, making natural language processing (NLP) an essential component in implementing an LHS. Herein, we share our institutional implementation of a big data-empowered clinical NLP infrastructure, which not only enables health-care analytics but also has real-time NLP processing capability. The infrastructure has been utilized for multiple institutional projects including the MayoExpertAdvisor, an individualized care recommendation solution for clinical care. We compared the advantages of big data over two other environments. Big data infrastructure significantly outperformed other infrastructure in terms of computing speed, demonstrating its value in making the LHS a possibility in the near future. PMID:27385912

Infusing Counseling Skills in Test Interpretation.

Science.gov (United States)

Rawlins, Melanie E.; And Others

1991-01-01

Presents an instructional model based on Neurolinguistic Programming that links counseling student course work in measurement and test interpretation with counseling techniques and theory. A process incorporating Neurolinguistic Programming patterns is outlined for teaching graduate students the counseling skills helpful in test interpretation.…

The neurolinguistic approach to awake surgery reviewed.

Science.gov (United States)

De Witte, Elke; Mariën, Peter

2013-02-01

Intraoperative direct electrical stimulation (DES) is increasingly used in patients operated on for tumours in critical language areas. Although a positive impact of DES on postoperative linguistic outcome is generally advocated, the literature is only scantily documented with information about the linguistic methods applied in awake surgery. This article critically reviews the neurolinguistic procedures currently used in awake studies. Based on an extensive review of the literature, an overview is given of the language mapping techniques applied in brain tumour surgery. Studies investigating linguistic testing and outcome in awake surgery were analysed. Information about the timing of the assessment(s), the linguistic tasks, the linguistic stimuli and the indication for awake surgery was also discussed. Intraoperative DES remains the 'gold standard' for language mapping, but pre- and postoperative non-invasive mapping methods are important adjuncts. In the pre- and postoperative phase, standardised linguistic test batteries are generally used to assess language function. In the intraoperative phase, only naming and number counting are commonly applied. Most often no detailed information about the linguistic stimuli is provided and no standardised protocols measuring different linguistic levels have been described. Awake surgery with DES is a useful tool for preserving linguistic functions in patients undergoing surgery in critical brain regions. However, no studies exist that apply a well-balanced and standardised linguistic protocol to reliably identify the critical language zones. The availability of a standardised linguistic protocol might substantially increase intraoperative comfort and might improve outcome and quality of life. Copyright © 2012 Elsevier B.V. All rights reserved.

Dysarthric Bengali speech: A neurolinguistic study

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Chakraborty N

2008-01-01

Full Text Available Background and Aims: Dysarthria affects linguistic domains such as respiration, phonation, articulation, resonance and prosody due to upper motor neuron, lower motor neuron, cerebellar or extrapyramidal tract lesions. Although Bengali is one of the major languages globally, dysarthric Bengali speech has not been subjected to neurolinguistic analysis. We attempted such an analysis with the goal of identifying the speech defects in native Bengali speakers in various types of dysarthria encountered in neurological disorders. Settings and Design: A cross-sectional observational study was conducted with 66 dysarthric subjects, predominantly middle-aged males, attending the Neuromedicine OPD of a tertiary care teaching hospital in Kolkata. Materials and Methods: After neurological examination, an instrument comprising commonly used Bengali words and a text block covering all Bengali vowels and consonants were used to carry out perceptual analysis of dysarthric speech. From recorded speech, 24 parameters pertaining to five linguistic domains were assessed. The Kruskal-Wallis analysis of variance, Chi-square test and Fisher′s exact test were used for analysis. Results: The dysarthria types were spastic (15 subjects, flaccid (10, mixed (12, hypokinetic (12, hyperkinetic (9 and ataxic (8. Of the 24 parameters assessed, 15 were found to occur in one or more types with a prevalence of at least 25%. Imprecise consonant was the most frequently occurring defect in most dysarthrias. The spectrum of defects in each type was identified. Some parameters were capable of distinguishing between types. Conclusions: This perceptual analysis has defined linguistic defects likely to be encountered in dysarthric Bengali speech in neurological disorders. The speech distortion can be described and distinguished by a limited number of parameters. This may be of importance to the speech therapist and neurologist in planning rehabilitation and further management.

THE MODEL OF MANAGEMENT OF THE INTERNAL MARKETING OF HIGHER EDUCATION INSTITUTE

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Yuliya Viktorovna Naurazbaeva

2015-12-01

Full Text Available The main purpose of the research is the development of methods and models of management of the internal marketing of a higher education institute based on complex approach that includes strategic management methods and staff marketing and also technologies of Neuro-Linguistic Programming (NLP.Method or methodology of the research. Adapted models and methods of Neuro-Linguistic Programming, strategic management and marketing to management of marketing of the university which are presented as a complex of models that are reveling through the interrelation «external labor-market – higher education institute – internal labor-market».Results:1. The mechanism of management of the internal marketing of higher education institute based on the interrelation «external labor – market – higher education institute – internal labor-market» is offered that assumes solving problem of miscomparison between market conditions, university’s opportunities and demands of an employee of this educational institute.2. Methodical bases of formation of NLP-model that coordinates the requirements of labor collective as internal consumers of the educational service and needs of higher education institute in order to provide high quality services at all stages of creation and realization of an educational service are developed.3. The infological model of construction and choosing the strategy of the internal marketing of educational institute is presented.Practical implications. The received results can be used in practical management of higher education institute when forming the strategy of the internal marketing taking into account the specific features of concrete university.

Structural analysis of papain-like NlpC/P60 superfamily enzymes with a circularly permuted topology reveals potential lipid binding sites.

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Qingping Xu

Full Text Available NlpC/P60 superfamily papain-like enzymes play important roles in all kingdoms of life. Two members of this superfamily, LRAT-like and YaeF/YiiX-like families, were predicted to contain a catalytic domain that is circularly permuted such that the catalytic cysteine is located near the C-terminus, instead of at the N-terminus. These permuted enzymes are widespread in virus, pathogenic bacteria, and eukaryotes. We determined the crystal structure of a member of the YaeF/YiiX-like family from Bacillus cereus in complex with lysine. The structure, which adopts a ligand-induced, "closed" conformation, confirms the circular permutation of catalytic residues. A comparative analysis of other related protein structures within the NlpC/P60 superfamily is presented. Permutated NlpC/P60 enzymes contain a similar conserved core and arrangement of catalytic residues, including a Cys/His-containing triad and an additional conserved tyrosine. More surprisingly, permuted enzymes have a hydrophobic S1 binding pocket that is distinct from previously characterized enzymes in the family, indicative of novel substrate specificity. Further analysis of a structural homolog, YiiX (PDB 2if6 identified a fatty acid in the conserved hydrophobic pocket, thus providing additional insights into possible function of these novel enzymes.

Russian and Chinese Information Warfare: Theory and Practice

Science.gov (United States)

2004-06-01

Integral neurolinguistic programming •Placing essential programs into the conscious or sub- conscious mind •Subconscious suggestions that modify human...Generators of special rays •Optical systems • Neurolinguistic programming •Computer psychotechnology •The mass media •Audiovisual effects •Special effects...Information Warfare: Theory and Practice 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e

Comparison of linear and nonlinear programming approaches for "worst case dose" and "minmax" robust optimization of intensity-modulated proton therapy dose distributions.

Science.gov (United States)

Zaghian, Maryam; Cao, Wenhua; Liu, Wei; Kardar, Laleh; Randeniya, Sharmalee; Mohan, Radhe; Lim, Gino

2017-03-01

Robust optimization of intensity-modulated proton therapy (IMPT) takes uncertainties into account during spot weight optimization and leads to dose distributions that are resilient to uncertainties. Previous studies demonstrated benefits of linear programming (LP) for IMPT in terms of delivery efficiency by considerably reducing the number of spots required for the same quality of plans. However, a reduction in the number of spots may lead to loss of robustness. The purpose of this study was to evaluate and compare the performance in terms of plan quality and robustness of two robust optimization approaches using LP and nonlinear programming (NLP) models. The so-called "worst case dose" and "minmax" robust optimization approaches and conventional planning target volume (PTV)-based optimization approach were applied to designing IMPT plans for five patients: two with prostate cancer, one with skull-based cancer, and two with head and neck cancer. For each approach, both LP and NLP models were used. Thus, for each case, six sets of IMPT plans were generated and assessed: LP-PTV-based, NLP-PTV-based, LP-worst case dose, NLP-worst case dose, LP-minmax, and NLP-minmax. The four robust optimization methods behaved differently from patient to patient, and no method emerged as superior to the others in terms of nominal plan quality and robustness against uncertainties. The plans generated using LP-based robust optimization were more robust regarding patient setup and range uncertainties than were those generated using NLP-based robust optimization for the prostate cancer patients. However, the robustness of plans generated using NLP-based methods was superior for the skull-based and head and neck cancer patients. Overall, LP-based methods were suitable for the less challenging cancer cases in which all uncertainty scenarios were able to satisfy tight dose constraints, while NLP performed better in more difficult cases in which most uncertainty scenarios were hard to meet

Mathematical programs with complementarity constraints in traffic and telecommunications networks.

Science.gov (United States)

Ralph, Daniel

2008-06-13

Given a suitably parametrized family of equilibrium models and a higher level criterion by which to measure an equilibrium state, mathematical programs with equilibrium constraints (MPECs) provide a framework for improving or optimizing the equilibrium state. An example is toll design in traffic networks, which attempts to reduce total travel time by choosing which arcs to toll and what toll levels to impose. Here, a Wardrop equilibrium describes the traffic response to each toll design. Communication networks also have a deep literature on equilibrium flows that suggest some MPECs. We focus on mathematical programs with complementarity constraints (MPCCs), a subclass of MPECs for which the lower level equilibrium system can be formulated as a complementarity problem and therefore, importantly, as a nonlinear program (NLP). Although MPECs and MPCCs are typically non-convex, which is a consequence of the upper level objective clashing with the users' objectives in the lower level equilibrium program, the last decade of research has paved the way for finding local solutions of MPCCs via standard NLP techniques.

Effect of escitalopram combined neuro-linguistic programming treatment on cognitive function in patients with somatoform disorders%艾司西酞普兰合并身心语法程序治疗对躯体形式障碍患者认知功能的影响

Institute of Scientific and Technical Information of China (English)

谢国军; 徐彩霞; 李晓玲; 罗伟森; 赵长江; 黎雪松

2013-01-01

Objective To investigate the effect of escitalopram combined neuro-linguistic programming treatment(NLP) on cognitive function in patients with somatoform disorders.Methods 120 cases with somatoform disorders were randomly divided into the escitalopram monotherapy group and escitalopram with NLP combined group,with 60 cases in each group for six weeks.At baseline and after six weeks for treatment,it was respectively assessed that the efficacy using Symptom Checklist 90 and Global Assessment Function,and cognitive function using the Raven Standard Progressive Matrices Test,digit span and digit symbol tests in Adult Wechsler Intelligence Test,while event related potentials P300 were detected.60 cases normal healthy adults as controls.Results Compared with the control group,the Raven scores,digit span,digit symbol scores were lower (P ＜0.01),N1,P3 latent periods were longer (P ＜ 0.01 or ＜ 0.05),N1N2,N2P2,P2P3 amplitudes were less(P =0.00) in patients with somatoform disorders.After treatment,Raven scores(91.25 ± 14.87,95.60 ± 19.95),digit span scores (11.98 ± 1.89,10.90 ± 2.76),digit symbol scores (11.71 ± 2.89,11.92 ± 2.90),N2P2 amplitudes ((11.32 ± 6.67) μV,(13.39 ± 9.31) μV),P2P3 amplitudes ((9.04 ± 6.14) μV,(9.51 ± 7.17) μV) increased,N2 latent periods ((240.60 ± 41.41) ms,(238.31 ± 41.47) ms) prolonged,N1 latent periods shortened (P ＜ 0.05 or 0.01) in the monotherapy group and the combined group.The digit span,P2 latent periods,N1N2,N2P2,P2P3 amplitudes had statistically significant differences between monotherapy group and combined group after treatment(P ＜ 0.05 or 0.01).Conclusion Both escitalopram monotherapy and escitalopram combined NLP have improved cognitive function in patients with somatoform disorders,but combined therapy has more prominent advantage.%目的 探讨艾司西酞普兰合并身心语法程序(NLP)治疗对躯体形式障碍患者认知功能的影响.方法 120�

Knowledge representation and management: benefits and challenges of the semantic web for the fields of KRM and NLP.

Science.gov (United States)

Rassinoux, A-M

2011-01-01

To summarize excellent current research in the field of knowledge representation and management (KRM). A synopsis of the articles selected for the IMIA Yearbook 2011 is provided and an attempt to highlight the current trends in the field is sketched. This last decade, with the extension of the text-based web towards a semantic-structured web, NLP techniques have experienced a renewed interest in knowledge extraction. This trend is corroborated through the five papers selected for the KRM section of the Yearbook 2011. They all depict outstanding studies that exploit NLP technologies whenever possible in order to accurately extract meaningful information from various biomedical textual sources. Bringing semantic structure to the meaningful content of textual web pages affords the user with cooperative sharing and intelligent finding of electronic data. As exemplified by the best paper selection, more and more advanced biomedical applications aim at exploiting the meaningful richness of free-text documents in order to generate semantic metadata and recently to learn and populate domain ontologies. These later are becoming a key piece as they allow portraying the semantics of the Semantic Web content. Maintaining their consistency with documents and semantic annotations that refer to them is a crucial challenge of the Semantic Web for the coming years.

HYPNOTEACHING IN HISTORY LESSON

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Agus Budianto

2017-07-01

Full Text Available Abstract: Hypnoteaching in History Lesson. Historical learning is a science that can’t be separated in educating the younger generation. Through this lesson, teachers in secondary schools can provide the foundation of nationality through important events in the study of the social sciences. Many of the problems that occur in learning history, such as the boring and make sleepy. Everyone must have heard the term hypnosis, hypnotism, or hypnotherapy. Each person must also have a different view or understanding when hearing these terms. Hypnoteaching is one of the learning methods by using the art of communicating to influence learners. Hypnoteaching is a combination of five teaching-learning methods such as quantum learning, accelerate learning, power teaching, neuro-linguistic programming (NLP and hypnosis. Hypnoteaching can be done using informal hypnosis as well as formal hypnosis. Informal hypnosis is also called indirect hypnosis ie teachers can naturally make the Critical Area learners become no longer critical, through a very persuasive communication pattern. Here's what the teacher can do in Informal hypnosis: (1 get attention; (2 establishing Themes; (3 presenting the structure and regulations; (4 building relationships. If the learners are already comfortable and interested, the next step is to do a formal hypnosis before the lesson begins. Here are the steps that must be done: (1 Induction; (2 Deepening; (3 Deep level test; (4 Suggestion, and; (5 Termination.   Keywords: Historical learning, hypnoteaching, hypnosis, hypnotism, hypnotherapy, history Abstrak: Hipnoteaching dalam Pembelajaran Sejarah. Pelajaran sejarah tidak bisa dihilangkan dalam mendidik para generasi muda. Melalui pembelajaran ini, guru pada sekolah menengah pertama dapat memberikan pondasi rasa nasionalisme melalui peristiwa peristiwa penting dalam pelajaran ilmu pengetahuan social. Masalah yang sering muncul pada pembelajaran ini adalah kebosanan siswa dan

Eye-movements and ongoing task processing.

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Burke, David T; Meleger, Alec; Schneider, Jeffrey C; Snyder, Jim; Dorvlo, Atsu S S; Al-Adawi, Samir

2003-06-01

This study tests the relation between eye-movements and thought processing. Subjects were given specific modality tasks (visual, gustatory, kinesthetic) and assessed on whether they responded with distinct eye-movements. Some subjects' eye-movements reflected ongoing thought processing. Instead of a universal pattern, as suggested by the neurolinguistic programming hypothesis, this study yielded subject-specific idiosyncratic eye-movements across all modalities. Included is a discussion of the neurolinguistic programming hypothesis regarding eye-movements and its implications for the eye-movement desensitization and reprocessing theory.

Optimization Research of Generation Investment Based on Linear Programming Model

Science.gov (United States)

Wu, Juan; Ge, Xueqian

Linear programming is an important branch of operational research and it is a mathematical method to assist the people to carry out scientific management. GAMS is an advanced simulation and optimization modeling language and it will combine a large number of complex mathematical programming, such as linear programming LP, nonlinear programming NLP, MIP and other mixed-integer programming with the system simulation. In this paper, based on the linear programming model, the optimized investment decision-making of generation is simulated and analyzed. At last, the optimal installed capacity of power plants and the final total cost are got, which provides the rational decision-making basis for optimized investments.

NLP model based thermoeconomic optimization of vapor compression–absorption cascaded refrigeration system

International Nuclear Information System (INIS)

Jain, Vaibhav; Sachdeva, Gulshan; Kachhwaha, S.S.

2015-01-01

Highlights: • It addresses the size and cost estimation of cascaded refrigeration system. • Cascaded system is a promising decarburizing and energy efficient technology. • Second law analysis is carried out with modified Gouy-Stodola equation. • The total annual cost of plant operation is optimized in present work. - Abstract: This paper addresses the size and cost estimation of vapor compression–absorption cascaded refrigeration system (VCACRS) for water chilling application taking R410a and water–LiBr as refrigerants in compression and absorption section respectively which can help the design engineers in manufacturing and experimenting on such kind of systems. The main limitation in the practical implementation of VCACRS is its size and cost which are optimized in the present work by implementing Direct Search Method in non-linear programming (NLP) mathematical model of VCACRS. The main objective of optimization is to minimize the total annual cost of system which comprises of costs of exergy input and capital costs in monetary units. The appropriate set of decision variables (temperature of evaporator, condenser, generator, absorber, cascade condenser, degree of overlap and effectiveness of solution heat exchanger) minimizes the total annual cost of VCACRS by 11.9% with 22.4% reduction in investment cost at the base case whereas the same is reduced by 7.5% with 11.7% reduction in investment cost with reduced rate of interest and increased life span and period of operation. Optimization results show that the more investment cost in later case is well compensated through the performance and operational cost of the system. In the present analysis, optimum cascade condensing temperature is a strong function of period of operation and capital recovery factor. The cascading of compression and absorption systems becomes attractive for lower rate of interest and increase life span and operational period

TRIANGULATION OF METHODS OF CAREER EDUCATION

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Marija Turnsek Mikacic

2015-09-01

Full Text Available This paper is an overview of the current research in the field of career education and career planning. Presented results constitute a model based on the insight into different theories and empirical studies about career planning as a building block of personal excellence. We defined credibility, transferability and reliability of the research by means of triangulation. As sources of data of triangulation we included essays of participants of education and questionnaires. Qualitative analysis represented the framework for the construction of the paradigmatic model and the formulation of the final theory. We formulated a questionnaire on the basis of our own experiences in the area of the education of individuals. The quantitative analysis, based on the results of the interviews, confirms the following three hypotheses: The individuals who elaborated a personal career plan and acted accordingly, changed their attitudes towards their careers and took control over their lives; in addition, they achieved a high level of self-esteem and self-confidence, in tandem with the perception of personal excellence, in contrast to the individuals who did not participate in career education and did not elaborate a career plan. We used the tools of NLP (neurolinguistic programming as an additional technique at learning.

Neurolinguistics Programming: Method or Myth?

Science.gov (United States)

Gumm, W. B.; And Others

1982-01-01

The preferred modality by which 50 right-handed female college students encoded experience was assessed by recordings of conjugate eye movements, content analysis of the subject's verbal report, and the subject's self-report. Kappa analyses failed to reveal any agreement of the three assessment methods. (Author)

BioNLP Shared Task--The Bacteria Track.

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Bossy, Robert; Jourde, Julien; Manine, Alain-Pierre; Veber, Philippe; Alphonse, Erick; van de Guchte, Maarten; Bessières, Philippe; Nédellec, Claire

2012-06-26

We present the BioNLP 2011 Shared Task Bacteria Track, the first Information Extraction challenge entirely dedicated to bacteria. It includes three tasks that cover different levels of biological knowledge. The Bacteria Gene Renaming supporting task is aimed at extracting gene renaming and gene name synonymy in PubMed abstracts. The Bacteria Gene Interaction is a gene/protein interaction extraction task from individual sentences. The interactions have been categorized into ten different sub-types, thus giving a detailed account of genetic regulations at the molecular level. Finally, the Bacteria Biotopes task focuses on the localization and environment of bacteria mentioned in textbook articles. We describe the process of creation for the three corpora, including document acquisition and manual annotation, as well as the metrics used to evaluate the participants' submissions. Three teams submitted to the Bacteria Gene Renaming task; the best team achieved an F-score of 87%. For the Bacteria Gene Interaction task, the only participant's score had reached a global F-score of 77%, although the system efficiency varies significantly from one sub-type to another. Three teams submitted to the Bacteria Biotopes task with very different approaches; the best team achieved an F-score of 45%. However, the detailed study of the participating systems efficiency reveals the strengths and weaknesses of each participating system. The three tasks of the Bacteria Track offer participants a chance to address a wide range of issues in Information Extraction, including entity recognition, semantic typing and coreference resolution. We found common trends in the most efficient systems: the systematic use of syntactic dependencies and machine learning. Nevertheless, the originality of the Bacteria Biotopes task encouraged the use of interesting novel methods and techniques, such as term compositionality, scopes wider than the sentence.

Theoretical and algorithmic advances in multi-parametric programming and control

KAUST Repository

Pistikopoulos, Efstratios N.; Dominguez, Luis; Panos, Christos; Kouramas, Konstantinos; Chinchuluun, Altannar

2012-01-01

This paper presents an overview of recent theoretical and algorithmic advances, and applications in the areas of multi-parametric programming and explicit/multi-parametric model predictive control (mp-MPC). In multi-parametric programming, advances include areas such as nonlinear multi-parametric programming (mp-NLP), bi-level programming, dynamic programming and global optimization for multi-parametric mixed-integer linear programming problems (mp-MILPs). In multi-parametric/explicit MPC (mp-MPC), advances include areas such as robust multi-parametric control, multi-parametric nonlinear MPC (mp-NMPC) and model reduction in mp-MPC. A comprehensive framework for multi-parametric programming and control is also presented. Recent applications include a hydrogen storage device, a fuel cell power generation system, an unmanned autonomous vehicle (UAV) and a hybrid pressure swing adsorption (PSA) system. © 2012 Springer-Verlag.

Theoretical and algorithmic advances in multi-parametric programming and control

KAUST Repository

Pistikopoulos, Efstratios N.

2012-04-21

This paper presents an overview of recent theoretical and algorithmic advances, and applications in the areas of multi-parametric programming and explicit/multi-parametric model predictive control (mp-MPC). In multi-parametric programming, advances include areas such as nonlinear multi-parametric programming (mp-NLP), bi-level programming, dynamic programming and global optimization for multi-parametric mixed-integer linear programming problems (mp-MILPs). In multi-parametric/explicit MPC (mp-MPC), advances include areas such as robust multi-parametric control, multi-parametric nonlinear MPC (mp-NMPC) and model reduction in mp-MPC. A comprehensive framework for multi-parametric programming and control is also presented. Recent applications include a hydrogen storage device, a fuel cell power generation system, an unmanned autonomous vehicle (UAV) and a hybrid pressure swing adsorption (PSA) system. © 2012 Springer-Verlag.

Automated Classification of Phonological Errors in Aphasic Language

Science.gov (United States)

Ahuja, Sanjeev B.; Reggia, James A.; Berndt, Rita S.

1984-01-01

Using heuristically-guided state space search, a prototype program has been developed to simulate and classify phonemic errors occurring in the speech of neurologically-impaired patients. Simulations are based on an interchangeable rule/operator set of elementary errors which represent a theory of phonemic processing faults. This work introduces and evaluates a novel approach to error simulation and classification, it provides a prototype simulation tool for neurolinguistic research, and it forms the initial phase of a larger research effort involving computer modelling of neurolinguistic processes.

Klik-suri sa Online Community ng mga Lesbiyana sa Facebook Gamit ang Critical Discourse Analysis (CDA at Natural Language Processing (NLP (Click-analysis of a Lesbian Online Community in Facebook Using the CDA and NLP

Directory of Open Access Journals (Sweden)

Alona Jumaquio-Ardales

2017-12-01

Full Text Available This study aims to describe the discourse on the online community of lesbians in the Philippines. The organization of Lesbian Community or LESCOM was chosen as subject of the study based on high number of ‘likes’ they received in Facebook. The texts were automatically gathered, filtered, shortlisted, and harvested from their Facebook page using the Natural Language Processing (NLP. The theoretical framework of Critical Discourse Analysis (CDA was used in analysing the data in order to describe online discourses that reflect the identity and community of lesbians based in the Philippines. The result of analysis were the following: [1] the emotions projected by exclamatory mark displayed their identity; [2] some plural words served as their voice for being group-oriented; [3] frequent usage of personal names manifested their inclusive community; and [4] social consciousness was part of their organizational agenda.

Hybrid Differential Dynamic Programming with Stochastic Search

Science.gov (United States)

Aziz, Jonathan; Parker, Jeffrey; Englander, Jacob

2016-01-01

Differential dynamic programming (DDP) has been demonstrated as a viable approach to low-thrust trajectory optimization, namely with the recent success of NASAs Dawn mission. The Dawn trajectory was designed with the DDP-based Static Dynamic Optimal Control algorithm used in the Mystic software. Another recently developed method, Hybrid Differential Dynamic Programming (HDDP) is a variant of the standard DDP formulation that leverages both first-order and second-order state transition matrices in addition to nonlinear programming (NLP) techniques. Areas of improvement over standard DDP include constraint handling, convergence properties, continuous dynamics, and multi-phase capability. DDP is a gradient based method and will converge to a solution nearby an initial guess. In this study, monotonic basin hopping (MBH) is employed as a stochastic search method to overcome this limitation, by augmenting the HDDP algorithm for a wider search of the solution space.

Overview of the ID, EPI and REL tasks of BioNLP Shared Task 2011

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Pyysalo Sampo

2012-06-01

Full Text Available Abstract We present the preparation, resources, results and analysis of three tasks of the BioNLP Shared Task 2011: the main tasks on Infectious Diseases (ID and Epigenetics and Post-translational Modifications (EPI, and the supporting task on Entity Relations (REL. The two main tasks represent extensions of the event extraction model introduced in the BioNLP Shared Task 2009 (ST'09 to two new areas of biomedical scientific literature, each motivated by the needs of specific biocuration tasks. The ID task concerns the molecular mechanisms of infection, virulence and resistance, focusing in particular on the functions of a class of signaling systems that are ubiquitous in bacteria. The EPI task is dedicated to the extraction of statements regarding chemical modifications of DNA and proteins, with particular emphasis on changes relating to the epigenetic control of gene expression. By contrast to these two application-oriented main tasks, the REL task seeks to support extraction in general by separating challenges relating to part-of relations into a subproblem that can be addressed by independent systems. Seven groups participated in each of the two main tasks and four groups in the supporting task. The participating systems indicated advances in the capability of event extraction methods and demonstrated generalization in many aspects: from abstracts to full texts, from previously considered subdomains to new ones, and from the ST'09 extraction targets to other entities and events. The highest performance achieved in the supporting task REL, 58% F-score, is broadly comparable with levels reported for other relation extraction tasks. For the ID task, the highest-performing system achieved 56% F-score, comparable to the state-of-the-art performance at the established ST'09 task. In the EPI task, the best result was 53% F-score for the full set of extraction targets and 69% F-score for a reduced set of core extraction targets, approaching a level

Is a lone right hemisphere enough? Neurolinguistic architecture in a case with a very early left hemispherectomy.

Science.gov (United States)

Danelli, Laura; Cossu, Giuseppe; Berlingeri, Manuela; Bottini, Gabriella; Sberna, Maurizio; Paulesu, Eraldo

2013-01-01

We studied the linguistic profile and neurolinguistic organization of a 14-year-old adolescent (EB) who underwent a left hemispherectomy at the age of 2.5 years. After initial aphasia, his language skills recovered within 2 years, with the exception of some word finding problems. Over the years, the neuropsychological assessments showed that EB's language was near-to-normal, with the exception of lexical competence, which lagged slightly behind for both auditory and written language. Moreover, EB's accuracy and speed in both reading and writing words and non-words were within the normal range, whereas difficulties emerged in reading loan words and in tasks with homophones. EB's functional magnetic resonance imaging (fMRI) patterns for several linguistic and metalinguistic tasks were similar to those observed in the dominant hemisphere of controls, suggesting that his language network conforms to a left-like linguistic neural blueprint. However, a stronger frontal recruitment suggests that linguistic tasks are more demanding for him. Finally, no specific reading activation was found in EB's occipitotemporal region, a finding consistent with the surface dyslexia-like behavioral pattern of the patient. While a lone right hemisphere may not be sufficient to guarantee full blown linguistic competences after early hemispherectomy, EB's behavioral and fMRI patterns suggest that his lone right hemisphere followed a left-like blueprint of the linguistic network.

Modeling Documents with Event Model

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Longhui Wang

2015-08-01

Full Text Available Currently deep learning has made great breakthroughs in visual and speech processing, mainly because it draws lessons from the hierarchical mode that brain deals with images and speech. In the field of NLP, a topic model is one of the important ways for modeling documents. Topic models are built on a generative model that clearly does not match the way humans write. In this paper, we propose Event Model, which is unsupervised and based on the language processing mechanism of neurolinguistics, to model documents. In Event Model, documents are descriptions of concrete or abstract events seen, heard, or sensed by people and words are objects in the events. Event Model has two stages: word learning and dimensionality reduction. Word learning is to learn semantics of words based on deep learning. Dimensionality reduction is the process that representing a document as a low dimensional vector by a linear mode that is completely different from topic models. Event Model achieves state-of-the-art results on document retrieval tasks.

How Did an Antismoking Campaign with a Neuro Linguistic Program Work out? A Case Study of Secondary School Students' Experiences in One Finnish School

Science.gov (United States)

Sahi, Salme; Maatta, Kaarina

2013-01-01

This article describes the use of a Neuro Linguistic Program (NLP) in an antismoking campaign and studies how successful this campaign was according to secondary school students. This campaign was carried out in a small town in northern Finland as an intensive three-day-long campaign. The data consisted of the essays and interviews of those…

Optimization-Based Selection of Influential Agents in a Rural Afghan Social Network

Science.gov (United States)

2010-06-01

nonlethal targeting model, a nonlinear programming ( NLP ) optimization formulation that identifies the k US agent assignment strategy producing the greatest...leader social network, and 3) the nonlethal targeting model, a nonlinear programming ( NLP ) optimization formulation that identifies the k US agent...NATO Coalition in Afghanistan. 55 for Afghanistan ( [54], [31], [48], [55], [30]). While Arab tribes tend to be more hierarchical, Pashtun tribes are

PROPOSAL FOR NEURAL-LINGUISTIC PROGRAMMING (N.L.P. INTHE ADMINISTRATIVE DEVELOPMENT OF LEADERSHIP SPORTS

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Khalil Samira

2010-08-01

Full Text Available Neural-linguistic programming is an organised method to know the human self construction and dealing with it in fixed means and styles so as to decesisively affect the processes of perception, thinking, imaging, ideas,feeling and also in behavior, skills and the human body and mental performance (1 Neural-linguistic programming has a private nature because it is a group of mechanisms and practicaltechniques far from likeliness, so it enters in the circle of application and employment of the human abilities and possibilities. (9 Al Fiky (2001 points out that neural linguistic programming created the favourable environment to help individuals to get rid of their diseased fears and controlling in their negative reactions and thus improving communication with themselves and with others. He shows it took its way into the human life fields because itsways and strategies are used in the sectors of health, education, marketing and administration(2. The modern administration embarks on the human element that represents the most valuable elementsof administration and is the most effective on the productivity and with the increasing the effect of the human element in the efficacy of the administrative organizations, the need increased to consider the management of the human resources as an independent function of administrative functions that cancers the human element and onwhose efficiency, abilities, experience and zeal for work, the administration efficacy depends.

Neuro-Linguistic Programming for Leaders and Managers

OpenAIRE

Tosey, Paul

2010-01-01

On few occasions in the history of modern management have leadership skills been in such sharp focus as they are now. The ability to direct often very large and diverse organizations; to make sense of the complex and turbulent markets and environments in which you operate; and to adapt and learn seems at an all time premium. The premise behind the fifth edition of this influential Handbook is that leadership, management and organizational development are all parts of the same process; enhanci...

Social anxiety and training in neurolinguistic programming.

Science.gov (United States)

Konefal, J; Duncan, R C

1998-12-01

The Liebowitz Social Phobia Scale measured the effect of training on social anxiety responses of 28 adults prior to and following a 21-day residential training, and at 6 mo. follow-up. Significant reductions posttraining and at follow-up were evident in the mean self-reported global scale scores on fear and avoidance behavior in social situations. The item scores, aggregated to reflect the situational domains of formal and informal speaking, being observed by others, and assertion, showed significant and continuing reduction from posttraining through follow-up. These findings are consistent with the hypothesis that this training may be associated with reduced responses to social anxiety, but as there was no formal control group, pretest scores from another study were used. Interpretation is limited.

Extraction of Static and Dynamic Reservoir Operation Rules by Genetic Programming

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Habib Akbari Alashti

2014-11-01

Full Text Available Considering the necessity of desirable operation of limited water resources and assuming the significant role of dams in controlling and consuming the surface waters, highlights the advantageous of suitable operation rules for optimal and sustainable operation of dams. This study investigates the hydroelectric supply of a one-reservoir system of Karoon3 using nonlinear programming (NLP, genetic algorithm (GA, genetic programming (GP and fixed length gen GP (FLGGP in real-time operation of dam considering two approaches of static and dynamic operation rules. In static operation rule, only one rule curve is extracted for all months in a year whereas in dynamic operation rule, monthly rule curves (12 rules are extracted for each month of a year. In addition, nonlinear decision rule (NLDR curves are considered, and the total deficiency function as the target (objective function have been used for evaluating the performance of each method and approach. Results show appropriate efficiency of GP and FLGGP methods in extracting operation rules in both approaches. Superiority of these methods to operation methods yielded by GA and NLP is 5%. Moreover, according to the results, it can be remarked that, FLGGP method is an alternative for GP method, whereas the GP method cannot be used due to its limitations. Comparison of two approaches of static and dynamic operation rules demonstrated the superiority of dynamic operation rule to static operation rule (about 10% and therefore this method has more capabilities in real-time operation of the reservoirs systems.

Selected Alternative Training Techniques in HRD. [and] Invited Reaction. [and] Final Word: A Rejoinder.

Science.gov (United States)

Von Bergen, C. W.; Soper, Barlow; Rosenthal, Gary T.; Wilkinson, Lamar V.; Watkins, Karen E.

1997-01-01

Von Bergen, Soper, Rosenthal, and Wilkinson examine four alternative training methods (subliminal self-help, meditation, mental imagery/practice, and neurolinguistic programming), concluding that only mental practice is supported by scientific evidence. Watkins takes issue with their dismissal of qualitative evidence. Their rejoinder asserts the…

Delivery mode and neonatal outcome after a trial of external cephalic version (ECV): a prospective trial of vaginal breech versus cephalic delivery.

Science.gov (United States)

Reinhard, Joscha; Sänger, Nicole; Hanker, Lars; Reichenbach, Lena; Yuan, Juping; Herrmann, Eva; Louwen, Frank

2013-04-01

To examine the delivery mode and neonatal outcome after a trial of external cephalic version (ECV) procedures. This is an interim analysis of an ongoing larger prospective off-centre randomised trial, which compares a clinical hypnosis intervention against neuro-linguistic programming (NLP) of women with a singleton breech foetus at or after 37(0/7) (259 days) weeks of gestation and normal amniotic fluid index. Main outcome measures were delivery mode and neonatal outcome. On the same day after the ECV procedure two patients (2 %), who had unsuccessful ECVs, had Caesarean sections (one due to vaginal bleeding and one due to pathological CTG). After the ECV procedure 40.4 % of women had cephalic presentation (n = 38) and 58.5 % (n = 55) remained breech presentation. One patient remained transverse presentation (n = 1; 1.1 %). Vaginal delivery was observed by 73.7 % of cephalic presentation (n = 28), whereas 26.3 % (n = 10) had in-labour Caesarean sections. Of those, who selected a trial of vaginal breech delivery, 42.4 % (n = 14) delivered vaginally and 57.6 % (n = 19) delivered via Caesarean section. There is a statistically significant difference between the rate of vaginal birth between cephalic presentation and trial of vaginal breech delivery (p = 0.009), however, no difference in neonatal outcome was observed. ECV is a safe procedure and can reduce not only the rate of elective Caesarean sections due to breech presentation but also the rate of in-labour Caesarean sections even if a trial of vaginal breech delivery is attempted.

Pattern Recognition and Natural Language Processing: State of the Art

Directory of Open Access Journals (Sweden)

Mirjana Kocaleva

2016-05-01

Full Text Available Development of information technologies is growing steadily. With the latest software technologies development and application of the methods of artificial intelligence and machine learning intelligence embededs in computers, the expectations are that in near future computers will be able to solve problems themselves like people do. Artificial intelligence emulates human behavior on computers. Rather than executing instructions one by one, as theyare programmed, machine learning employs prior experience/data that is used in the process of system’s training. In this state of the art paper, common methods in AI, such as machine learning, pattern recognition and the natural language processing (NLP are discussed. Also are given standard architecture of NLP processing system and the level thatisneeded for understanding NLP. Lastly the statistical NLP processing and multi-word expressions are described.

Report on ONR Conference on ’Dolphin Behavior and Cognition: Comparative and Ecological Aspects’, Hubbs-Sea World Research Institute, San Diego, California, 92109, July 6-9, 1983.

Science.gov (United States)

1983-11-01

Brookfield Zoo Brookfield, IL 60513 Robert Buhr Animal communication and cognition; Department of Linguistics neurolinguistics and neuropsychology Brown...Rockefeller University 1230 York Avenue New York, NY 10021 Henry Halff (observer) Personnel and Training Research Program .,,; Code 442 PT Arlington, VA 22212...observer) Physiology and Neurobiology Research Program Code 441 NP e., Office of Naval Research Arlington, VA 22217 Bernd Wursig Cetacean behavior

Representational System Predicate Use and Convergence in Counseling: Gloria Revisited.

Science.gov (United States)

Mercier, Mary Ann; Johnson, Marilyn

1984-01-01

Analayzed transcripts of Three Approaches to Psychotherapy (Shostrom, 1966) for counselor and client representational system predicate use. Although different patterns of predicate use emerged, only limited support for Neurolinguistic Programming theory was found. The findings of different patterns of predicate use were related to convergence and…

Development of Intelligent Method for Differential Diagnosis of Specific Language Impairment

Science.gov (United States)

2001-10-25

Grant Number Program Element Number Author(s) Project Number Task Number Work Unit Number Performing Organization Name(s) and Address(es) Dept...Development in a Grammatical SLI boy: Modularity and Innateness, Journal of Neurolinguistics 10, (1997) 75-107. [8] J.P. Craiger, D.F. Goodman, R.J

Structure-guided functional characterization of DUF1460 reveals a highly specific NlpC/P60 amidase family.

Science.gov (United States)

Xu, Qingping; Mengin-Lecreulx, Dominique; Patin, Delphine; Grant, Joanna C; Chiu, Hsiu-Ju; Jaroszewski, Lukasz; Knuth, Mark W; Godzik, Adam; Lesley, Scott A; Elsliger, Marc-André; Deacon, Ashley M; Wilson, Ian A

2014-12-02

GlcNAc-1,6-anhydro-MurNAc-tetrapeptide is a major peptidoglycan degradation intermediate and a cytotoxin. It is generated by lytic transglycosylases and further degraded and recycled by various enzymes. We have identified and characterized a highly specific N-acetylmuramoyl-L-alanine amidase (AmiA) from Bacteroides uniformis, a member of the DUF1460 protein family, that hydrolyzes GlcNAc-1,6-anhydro-MurNAc-peptide into disaccharide and stem peptide. The high-resolution apo structure at 1.15 Å resolution shows that AmiA is related to NlpC/P60 γ-D-Glu-meso-diaminopimelic acid amidases and shares a common catalytic core and cysteine peptidase-like active site. AmiA has evolved structural adaptations that reconfigure the substrate recognition site. The preferred substrates for AmiA were predicted in silico based on structural and bioinformatics data, and subsequently were characterized experimentally. Further crystal structures of AmiA in complexes with GlcNAc-1,6-anhydro-MurNAc and GlcNAc have enabled us to elucidate substrate recognition and specificity. DUF1460 is highly conserved in structure and defines another amidase family. Copyright © 2014 Elsevier Ltd. All rights reserved.

GAME--Gym Activities for Mind's Efficiency

Science.gov (United States)

Rocha Ferreira, Cristina

2016-01-01

GAME results from the exhaustion of doing the same activities, dealing with unmotivated students and not getting the desired results academically. Thus, I initiated a process of research and training in areas such as Positive Psychology, Neurosciences and Neurolinguistic Programming, which allowed to design an Evidence-Based Intervention. Students…

A Computational Model of Spatial Visualization Capacity

Science.gov (United States)

2008-03-07

GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 61102F 6. AUTHOR(S) Don Lyon; Glenn Gunzelmann; Kevin Gluck 5d. PROJECT NUMBER 2313 5e. TASK NUMBER AS...specialization in prefrontal cortex: Effects of verbalizability, imageability and meaning. Journal of Neurolinguistics , 16, 361–382. Diwadkar, V. A

Natural Language Processing (NLP), Machine Learning (ML), and Semantics in Polar Science

Science.gov (United States)

Duerr, R.; Ramdeen, S.

2017-12-01

One of the interesting features of Polar Science is that it historically has been extremely interdisciplinary, encompassing all of the physical and social sciences. Given the ubiquity of specialized terminology in each field, enabling researchers to find, understand, and use all of the heterogeneous data needed for polar research continues to be a bottleneck. Within the informatics community, semantics has broadly accepted as a solution to these problems, yet progress in developing reusable semantic resources has been slow. The NSF-funded ClearEarth project has been adapting the methods and tools from other communities such as Biomedicine to the Earth sciences with the goal of enhancing progress and the rate at which the needed semantic resources can be created. One of the outcomes of the project has been a better understanding of the differences in the way linguists and physical scientists understand disciplinary text. One example of these differences is the tendency for each discipline and often disciplinary subfields to expend effort in creating discipline specific glossaries where individual terms often are comprised of more than one word (e.g., first-year sea ice). Often each term in a glossary is imbued with substantial contextual or physical meaning - meanings which are rarely explicitly called out within disciplinary texts; meaning which are therefore not immediately accessible to those outside that discipline or subfield; meanings which can often be represented semantically. Here we show how recognition of these difference and the use of glossaries can be used to speed up the annotation processes endemic to NLP, enable inter-community recognition and possible reconciliation of terminology differences. A number of processes and tools will be described, as will progress towards semi-automated generation of ontology structures.

Feasibility Study for Design of a Biocybernetic Communication System

Science.gov (United States)

1975-08-01

VIRGINIA 22209 ^LtVAHU Attention: DR. GEORGE LAWRENCE, PROGRAM MANAGER Ä^Se^o.2^ C0NTRACT DpAHC-15-72-C-0167 Contractor: Stanford...cussed on page 77. Various portions of this research program have been presented orally in several scientific forums. The participants made critical...The San Francisco Bay Area Neurolinguistics Society meeting, Stanford University, Dr. Karl Pribram, Chairman. • The Department of Linguistics

Recent Advances in Explicit Multiparametric Nonlinear Model Predictive Control

KAUST Repository

Domínguez, Luis F.

2011-01-19

In this paper we present recent advances in multiparametric nonlinear programming (mp-NLP) algorithms for explicit nonlinear model predictive control (mp-NMPC). Three mp-NLP algorithms for NMPC are discussed, based on which novel mp-NMPC controllers are derived. The performance of the explicit controllers are then tested and compared in a simulation example involving the operation of a continuous stirred-tank reactor (CSTR). © 2010 American Chemical Society.

Rochester Connectionist Papers. 1979-1985

Science.gov (United States)

1985-12-01

updated and improved version of the thesis account of recent neurolinguistic data. Fanty, M., "Context-free parsing in connectionist networks." TR 174...April 1982. Our first large program in the connectionist paradigm. It simulates a multi- layer network for recognizing line drawings of Origami figures...The program successfully deals with noise and simple occlusion and the thesis incorporates many key ideas on designing and running large models. Small

Cognition in the Brain: Investigations Using Positron Emission Tomography

Science.gov (United States)

1992-07-16

0029 DDIRESS (City. State and ZIP Code) 10. SOURCE Of FUNDING NOS. _____________ .dg. 410 PROGRAM PROJECT TASKC WORK .,%r illing Air Force Base, DC...Bethesda, MD 20892 20. Daniel Bubb, M.D. Department of Neurolinguistics Montreal Neurological Institute 15. Sung-cheng tHuang, Ph.D. 3801 University...Chief of Pediatric Neu- rology Service Director, Center for Morphomet- 24. Terry Allard, Ph.D. ric Analysis Cognitive Science Programs Kennedy 9 Office

Comparison of linear, mixed integer and non-linear programming methods in energy system dispatch modelling

DEFF Research Database (Denmark)

Ommen, Torben Schmidt; Markussen, Wiebke Brix; Elmegaard, Brian

2014-01-01

In the paper, three frequently used operation optimisation methods are examined with respect to their impact on operation management of the combined utility technologies for electric power and DH (district heating) of eastern Denmark. The investigation focusses on individual plant operation...... differences and differences between the solution found by each optimisation method. One of the investigated approaches utilises LP (linear programming) for optimisation, one uses LP with binary operation constraints, while the third approach uses NLP (non-linear programming). The LP model is used...... as a benchmark, as this type is frequently used, and has the lowest amount of constraints of the three. A comparison of the optimised operation of a number of units shows significant differences between the three methods. Compared to the reference, the use of binary integer variables, increases operation...

[Psychotherapy impact on effectiveness of in-hospital physical rehabilitation in patients with acute coronary syndrome].

Science.gov (United States)

Sumin, A N; Khaĭredinova, O P; Sumina, L Iu; Variushkina, E V; Doronin, D V; Galimzianov, D M; Masin, A N; Gol'dberg, G A

2000-01-01

Of 103 patients with acute coronary syndrome (mean age 51.6 +/- 0.9 years) 47 patients participated in 5 group psychotherapeutic sessions added to conversional rehabilitation program. Psychotherapy included progressive muscular relaxation, neurolinguistic programming, eriksonian hypnosis, therapeutic metaphora. Psychotherapy decreased the hear rate, number of ventricular extrasystoles, stimulated tonicity of the parasympathetic nervous system. Compared to the controls, the test patients developed higher exercise tolerance and lower reactivity of the central hemodynamics in all the exercise tests.

Rationale for a ’Many Maps’ Phonology Machine

Science.gov (United States)

1990-03-01

City, State, and ZIP Code) 10 SOURCE OF FUNDING NUMBERS 40005ub201/7-4-86 PROGRAM PROJECT TASK ~ WORK UNIT ELEMENT NO NO.I NO. ACCESSION NO NIA N/A NIA...seek to verify or refute. Some day, neurolinguistics may provide the decisive answer to the rationalist/empiricist debate. If so, we are confident that...linguistics program , Carnegie Mellon University. [7] Touretzky, D. S. (1989) Toward a connectionist phonology: the "many maps" ap- proach to sequencc

The effect of career planning education

Directory of Open Access Journals (Sweden)

Marija Turnšek Mikačič

2015-09-01

Full Text Available Research Question (RQ: We employed a qualitative approach to study the effects of career planning education, perceiving it as an effective way to gain a deeper understanding of introductorily-organised career education. Purpose: We researched important areas to formulate a questionnaire for quantitative analysis. Method: We used a qualitative research approach in order to develop a theoretical framework for the exploration, interpretation and identification of the impact of education on career plans, on the changing attitudes towards careers, the raising of self-esteem and perception of personal growth. We used Neuro-linguistic programming as a tool to develop and achieve personal excellence within the career planning. Results: We constructed a paradigmatic model and developed the final theory. By means of qualitative analysis, we identified the elements of design criteria for the construction of the questionnaire; we measured the effects of education on career plans. Organization: The findings of the research will prove useful in personal management and career management in the process of planning and organizing the promotion of individuals within the organizations in accordance with the needs of those organizations. Originality: A career plan as a building block of personal growth, based on the model of career education with the in-built elements and tools of NLP, has been confirmed by the most recent studies in neuroscience. This represents a novelty, and, therefore, this study offers a genuine contribution, and is an indicator of contemporary knowledge, based on the results of the research. Limitations/Future Research: The model of career education and the results of this study open new directions for further research of the influence of career planning on the organisation of companies and their success, which is the phase of the study which was not carried out.

Designing visual displays and system models for safe reactor operations

International Nuclear Information System (INIS)

Brown-VanHoozer, S.A.

1995-01-01

The material presented in this paper is based on two studies involving the design of visual displays and the user's prospective model of a system. The studies involve a methodology known as Neuro-Linguistic Programming and its use in expanding design choices from the operator's perspective image. The contents of this paper focuses on the studies and how they are applicable to the safety of operating reactors

Parallel Nonlinear Optimization for Astrodynamic Navigation, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — CU Aerospace proposes the development of a new parallel nonlinear program (NLP) solver software package. NLPs allow the solution of complex optimization problems,...

Natural language processing: an introduction.

Science.gov (United States)

Nadkarni, Prakash M; Ohno-Machado, Lucila; Chapman, Wendy W

2011-01-01

To provide an overview and tutorial of natural language processing (NLP) and modern NLP-system design. This tutorial targets the medical informatics generalist who has limited acquaintance with the principles behind NLP and/or limited knowledge of the current state of the art. We describe the historical evolution of NLP, and summarize common NLP sub-problems in this extensive field. We then provide a synopsis of selected highlights of medical NLP efforts. After providing a brief description of common machine-learning approaches that are being used for diverse NLP sub-problems, we discuss how modern NLP architectures are designed, with a summary of the Apache Foundation's Unstructured Information Management Architecture. We finally consider possible future directions for NLP, and reflect on the possible impact of IBM Watson on the medical field.

Exploiting Speech for Automatic TV Delinearization: From Streams to Cross-Media Semantic Navigation

Directory of Open Access Journals (Sweden)

Guinaudeau Camille

2011-01-01

Full Text Available The gradual migration of television from broadcast diffusion to Internet diffusion offers countless possibilities for the generation of rich navigable contents. However, it also raises numerous scientific issues regarding delinearization of TV streams and content enrichment. In this paper, we study how speech can be used at different levels of the delinearization process, using automatic speech transcription and natural language processing (NLP for the segmentation and characterization of TV programs and for the generation of semantic hyperlinks in videos. Transcript-based video delinearization requires natural language processing techniques robust to transcription peculiarities, such as transcription errors, and to domain and genre differences. We therefore propose to modify classical NLP techniques, initially designed for regular texts, to improve their robustness in the context of TV delinearization. We demonstrate that the modified NLP techniques can efficiently handle various types of TV material and be exploited for program description, for topic segmentation, and for the generation of semantic hyperlinks between multimedia contents. We illustrate the concept of cross-media semantic navigation with a description of our news navigation demonstrator presented during the NEM Summit 2009.

Designing visual displays and system models for safe reactor operations

Energy Technology Data Exchange (ETDEWEB)

Brown-VanHoozer, S.A.

1995-12-31

The material presented in this paper is based on two studies involving the design of visual displays and the user`s prospective model of a system. The studies involve a methodology known as Neuro-Linguistic Programming and its use in expanding design choices from the operator`s perspective image. The contents of this paper focuses on the studies and how they are applicable to the safety of operating reactors.

A quasi-sequential parameter estimation for nonlinear dynamic systems based on multiple data profiles

Energy Technology Data Exchange (ETDEWEB)

Zhao, Chao [FuZhou University, FuZhou (China); Vu, Quoc Dong; Li, Pu [Ilmenau University of Technology, Ilmenau (Germany)

2013-02-15

A three-stage computation framework for solving parameter estimation problems for dynamic systems with multiple data profiles is developed. The dynamic parameter estimation problem is transformed into a nonlinear programming (NLP) problem by using collocation on finite elements. The model parameters to be estimated are treated in the upper stage by solving an NLP problem. The middle stage consists of multiple NLP problems nested in the upper stage, representing the data reconciliation step for each data profile. We use the quasi-sequential dynamic optimization approach to solve these problems. In the lower stage, the state variables and their gradients are evaluated through ntegrating the model equations. Since the second-order derivatives are not required in the computation framework this proposed method will be efficient for solving nonlinear dynamic parameter estimation problems. The computational results obtained on a parameter estimation problem for two CSTR models demonstrate the effectiveness of the proposed approach.

A quasi-sequential parameter estimation for nonlinear dynamic systems based on multiple data profiles

International Nuclear Information System (INIS)

Zhao, Chao; Vu, Quoc Dong; Li, Pu

2013-01-01

A three-stage computation framework for solving parameter estimation problems for dynamic systems with multiple data profiles is developed. The dynamic parameter estimation problem is transformed into a nonlinear programming (NLP) problem by using collocation on finite elements. The model parameters to be estimated are treated in the upper stage by solving an NLP problem. The middle stage consists of multiple NLP problems nested in the upper stage, representing the data reconciliation step for each data profile. We use the quasi-sequential dynamic optimization approach to solve these problems. In the lower stage, the state variables and their gradients are evaluated through ntegrating the model equations. Since the second-order derivatives are not required in the computation framework this proposed method will be efficient for solving nonlinear dynamic parameter estimation problems. The computational results obtained on a parameter estimation problem for two CSTR models demonstrate the effectiveness of the proposed approach

Extraction of Protein Interaction Data: A Comparative Analysis of Methods in Use

Directory of Open Access Journals (Sweden)

Jose Hena

2007-01-01

Full Text Available Several natural language processing tools, both commercial and freely available, are used to extract protein interactions from publications. Methods used by these tools include pattern matching to dynamic programming with individual recall and precision rates. A methodical survey of these tools, keeping in mind the minimum interaction information a researcher would need, in comparison to manual analysis has not been carried out. We compared data generated using some of the selected NLP tools with manually curated protein interaction data (PathArt and IMaps to comparatively determine the recall and precision rate. The rates were found to be lower than the published scores when a normalized definition for interaction is considered. Each data point captured wrongly or not picked up by the tool was analyzed. Our evaluation brings forth critical failures of NLP tools and provides pointers for the development of an ideal NLP tool.

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.

Natural Language Processing in Serious Games: A state of the art.

Directory of Open Access Journals (Sweden)

Davide Picca

2015-09-01

Full Text Available In the last decades, Natural Language Processing (NLP has obtained a high level of success. Interactions between NLP and Serious Games have started and some of them already include NLP techniques. The objectives of this paper are twofold: on the one hand, providing a simple framework to enable analysis of potential uses of NLP in Serious Games and, on the other hand, applying the NLP framework to existing Serious Games and giving an overview of the use of NLP in pedagogical Serious Games. In this paper we present 11 serious games exploiting NLP techniques. We present them systematically, according to the following structure:  first, we highlight possible uses of NLP techniques in Serious Games, second, we describe the type of NLP implemented in the each specific Serious Game and, third, we provide a link to possible purposes of use for the different actors interacting in the Serious Game.

The Use of Neuro-Linguistic Programming Model for Learning Success.

Science.gov (United States)

Woerner, Janet J.; Stonehouse, Harold B.

1988-01-01

This model is useful in identifying specific learning problems and in providing techniques for the teacher to motivate and teach students at all levels. What it is and how it can be used are discussed, illustrated by specific strategies for geometry and science. (MNS)

Basic quantitative assessment of visual performance in patients with very low vision.

Science.gov (United States)

Bach, Michael; Wilke, Michaela; Wilhelm, Barbara; Zrenner, Eberhart; Wilke, Robert

2010-02-01

A variety of approaches to developing visual prostheses are being pursued: subretinal, epiretinal, via the optic nerve, or via the visual cortex. This report presents a method of comparing their efficacy at genuinely improving visual function, starting at no light perception (NLP). A test battery (a computer program, Basic Assessment of Light and Motion [BaLM]) was developed in four basic visual dimensions: (1) light perception (light/no light), with an unstructured large-field stimulus; (2) temporal resolution, with single versus double flash discrimination; (3) localization of light, where a wedge extends from the center into four possible directions; and (4) motion, with a coarse pattern moving in one of four directions. Two- or four-alternative, forced-choice paradigms were used. The participants' responses were self-paced and delivered with a keypad. The feasibility of the BaLM was tested in 73 eyes of 51 patients with low vision. The light and time test modules discriminated between NLP and light perception (LP). The localization and motion modules showed no significant response for NLP but discriminated between LP and hand movement (HM). All four modules reached their ceilings in the acuity categories higher than HM. BaLM results systematically differed between the very-low-acuity categories NLP, LP, and HM. Light and time yielded similar results, as did localization and motion; still, for assessing the visual prostheses with differing temporal characteristics, they are not redundant. The results suggest that this simple test battery provides a quantitative assessment of visual function in the very-low-vision range from NLP to HM.

Natural Language Processing Technologies in Radiology Research and Clinical Applications

Science.gov (United States)

Cai, Tianrun; Giannopoulos, Andreas A.; Yu, Sheng; Kelil, Tatiana; Ripley, Beth; Kumamaru, Kanako K.; Rybicki, Frank J.

2016-01-01

The migration of imaging reports to electronic medical record systems holds great potential in terms of advancing radiology research and practice by leveraging the large volume of data continuously being updated, integrated, and shared. However, there are significant challenges as well, largely due to the heterogeneity of how these data are formatted. Indeed, although there is movement toward structured reporting in radiology (ie, hierarchically itemized reporting with use of standardized terminology), the majority of radiology reports remain unstructured and use free-form language. To effectively “mine” these large datasets for hypothesis testing, a robust strategy for extracting the necessary information is needed. Manual extraction of information is a time-consuming and often unmanageable task. “Intelligent” search engines that instead rely on natural language processing (NLP), a computer-based approach to analyzing free-form text or speech, can be used to automate this data mining task. The overall goal of NLP is to translate natural human language into a structured format (ie, a fixed collection of elements), each with a standardized set of choices for its value, that is easily manipulated by computer programs to (among other things) order into subcategories or query for the presence or absence of a finding. The authors review the fundamentals of NLP and describe various techniques that constitute NLP in radiology, along with some key applications. ©RSNA, 2016 PMID:26761536

Natural Language Processing Technologies in Radiology Research and Clinical Applications.

Science.gov (United States)

Cai, Tianrun; Giannopoulos, Andreas A; Yu, Sheng; Kelil, Tatiana; Ripley, Beth; Kumamaru, Kanako K; Rybicki, Frank J; Mitsouras, Dimitrios

2016-01-01

The migration of imaging reports to electronic medical record systems holds great potential in terms of advancing radiology research and practice by leveraging the large volume of data continuously being updated, integrated, and shared. However, there are significant challenges as well, largely due to the heterogeneity of how these data are formatted. Indeed, although there is movement toward structured reporting in radiology (ie, hierarchically itemized reporting with use of standardized terminology), the majority of radiology reports remain unstructured and use free-form language. To effectively "mine" these large datasets for hypothesis testing, a robust strategy for extracting the necessary information is needed. Manual extraction of information is a time-consuming and often unmanageable task. "Intelligent" search engines that instead rely on natural language processing (NLP), a computer-based approach to analyzing free-form text or speech, can be used to automate this data mining task. The overall goal of NLP is to translate natural human language into a structured format (ie, a fixed collection of elements), each with a standardized set of choices for its value, that is easily manipulated by computer programs to (among other things) order into subcategories or query for the presence or absence of a finding. The authors review the fundamentals of NLP and describe various techniques that constitute NLP in radiology, along with some key applications. ©RSNA, 2016.

Use of Radcube for extraction of finding trends in a large radiology practice.

Science.gov (United States)

Dang, Pragya A; Kalra, Mannudeep K; Blake, Michael A; Schultz, Thomas J; Stout, Markus; Halpern, Elkan F; Dreyer, Keith J

2009-12-01

The purpose of our study was to demonstrate the use of Natural Language Processing (Leximer), along with Online Analytic Processing, (NLP-OLAP), for extraction of finding trends in a large radiology practice. Prior studies have validated the Natural Language Processing (NLP) program, Leximer for classifying unstructured radiology reports based on the presence of positive radiology findings (F (POS)) and negative radiology findings (F (NEG)). The F (POS) included new relevant radiology findings and any change in status from prior imaging. Electronic radiology reports from 1995-2002 and data from analysis of these reports with NLP-Leximer were saved in a data warehouse and exported to a multidimensional structure called the Radcube. Various relational queries on the data in the Radcube were performed using OLAP technique. Thus, NLP-OLAP was applied to determine trends of F (POS) in different radiology exams for different patient and examination attributes. Pivot tables were exported from NLP-OLAP interface to Microsoft Excel for statistical analysis. Radcube allowed rapid and comprehensive analysis of F (POS) and F (NEG) trends in a large radiology report database. Trends of F (POS) were extracted for different patient attributes such as age groups, gender, clinical indications, diseases with ICD codes, patient types (inpatient, ambulatory), imaging characteristics such as imaging modalities, referring physicians, radiology subspecialties, and body regions. Data analysis showed substantial differences between F (POS) rates for different imaging modalities ranging from 23.1% (mammography, 49,163/212,906) to 85.8% (nuclear medicine, 93,852/109,374; p OLAP can help in analysis of yield of different radiology exams from a large radiology report database.

Creation of lung-targeted dexamethasone immunoliposome and its therapeutic effect on bleomycin-induced lung injury in rats.

Directory of Open Access Journals (Sweden)

Xue-Yuan Chen

Full Text Available OBJECTIVE: Acute lung injury (ALI, is a major cause of morbidity and mortality, which is routinely treated with the administration of systemic glucocorticoids. The current study investigated the distribution and therapeutic effect of a dexamethasone(DXM-loaded immunoliposome (NLP functionalized with pulmonary surfactant protein A (SP-A antibody (SPA-DXM-NLP in an animal model. METHODS: DXM-NLP was prepared using film dispersion combined with extrusion techniques. SP-A antibody was used as the lung targeting agent. Tissue distribution of SPA-DXM-NLP was investigated in liver, spleen, kidney and lung tissue. The efficacy of SPA-DXM-NLP against lung injury was assessed in a rat model of bleomycin-induced acute lung injury. RESULTS: The SPA-DXM-NLP complex was successfully synthesized and the particles were stable at 4°C. Pulmonary dexamethasone levels were 40 times higher with SPA-DXM-NLP than conventional dexamethasone injection. Administration of SPA-DXM-NLP significantly attenuated lung injury and inflammation, decreased incidence of infection, and increased survival in animal models. CONCLUSIONS: The administration of SPA-DXM-NLP to animal models resulted in increased levels of DXM in the lungs, indicating active targeting. The efficacy against ALI of the immunoliposomes was shown to be superior to conventional dexamethasone administration. These results demonstrate the potential of actively targeted glucocorticoid therapy in the treatment of lung disease in clinical practice.

Neurolinguistic Programming: The Impact of Imagery Tasks on Sensory Predicate Usage.

Science.gov (United States)

Graunke, Bruce; Roberts, T. Kevin

1985-01-01

Investigated the impact of varied imagining tasks on individuals' use of sensory predicates. Results demonstrated that subjects were able to vary their type of sensory predicates according to the task demands or situational context. Findings are incongruent with Bandler and Grinder's (1979) conceptualization of representational systems.…

Arabic Natural Language Processing System Code Library

Science.gov (United States)

2014-06-01

Adelphi, MD 20783-1197 This technical note provides a brief description of a Java library for Arabic natural language processing ( NLP ) containing code...for training and applying the Arabic NLP system described in the paper "A Cross-Task Flexible Transition Model for Arabic Tokenization, Affix...and also English) natural language processing ( NLP ), containing code for training and applying the Arabic NLP system described in Stephen Tratz’s

Clinical Natural Language Processing in languages other than English: opportunities and challenges.

Science.gov (United States)

Névéol, Aurélie; Dalianis, Hercules; Velupillai, Sumithra; Savova, Guergana; Zweigenbaum, Pierre

2018-03-30

Natural language processing applied to clinical text or aimed at a clinical outcome has been thriving in recent years. This paper offers the first broad overview of clinical Natural Language Processing (NLP) for languages other than English. Recent studies are summarized to offer insights and outline opportunities in this area. We envision three groups of intended readers: (1) NLP researchers leveraging experience gained in other languages, (2) NLP researchers faced with establishing clinical text processing in a language other than English, and (3) clinical informatics researchers and practitioners looking for resources in their languages in order to apply NLP techniques and tools to clinical practice and/or investigation. We review work in clinical NLP in languages other than English. We classify these studies into three groups: (i) studies describing the development of new NLP systems or components de novo, (ii) studies describing the adaptation of NLP architectures developed for English to another language, and (iii) studies focusing on a particular clinical application. We show the advantages and drawbacks of each method, and highlight the appropriate application context. Finally, we identify major challenges and opportunities that will affect the impact of NLP on clinical practice and public health studies in a context that encompasses English as well as other languages.

Benefits, Costs, and Harms of Osteoporosis Screening in Male Veterans

Science.gov (United States)

2013-10-01

obtaining text files due to new requirement for real SSN access. However, NLP programming is completed, validated, and ready to run on the dataset...the diagnosis and management of osteoporosis in Canada : summary. CMAJ Canadian Medical Association Journal 2010, 182(17):1864-1873. 13. Qaseem A

Looking at Yourself through Loving Eyes.

Science.gov (United States)

Childers, John H., Jr.

1989-01-01

Introduces and discusses Neuro-Linquistic Programming (NLP) using "Looking at Yourself through Loving Eyes" technique. Presents the seven steps necessary in implementing this technique, and provides guidelines. Presents results suggesting that this technique is useful when working with elementary school students, and is a useful tool for…

A corpus-based approach to generalising a chatbot system

OpenAIRE

Abu Shawar, Bayan; Atwell, Eric

2003-01-01

International research in NLP is dominated by work on English. NLP techniques and systems can be ported to other natural languages, but this is generally a labour-intensive task, requiring scarce computational and linguistic expertise; hence minority languages are poorly represented in NLP technology. We present an automated approach to porting an NLP technology, the AIML-based chatbot, to new languages, by using a corpus in the target language to retrain the chatbot. We have s...

Programac ión neurolinguistica . ¿Realidad o mito en Psicología

Directory of Open Access Journals (Sweden)

Arlinthon David Jaruffe Romero

2013-10-01

Full Text Available Resumen La aplicabilidad de la Programación Neuro-Lingüística es para muchos, cuestión de mito, pseudociencia o incompatibilidad metodológica entre ella y la Psicología. Sin embargo, en el proceso de aprendizaje se evidencia que tiene un alto sentido, puesto que es una herramienta eficaz y sencilla que permite un cambio significativo en el rendimiento académico de los estudiantes y la productividad en términos organizacionales. Con este modelo se aprende a sintonizar de manera efectiva las relaciones sociales, con el propósito de darle un sentido más estimulante y significativo a los procesos implícitos donde se manifieste el ser humano. De esta forma, en el presente artículo, bajo un método de investigación teórica, se planteó el objetivo de: determinar la relación conceptual y práctica de la Programación Neurolinguística con la Psicología y la Neurociencia; al tiempo que se concluyó que la misma tiene relación con las otras en la medida que busca el desarrollo cognitivo y mental de los sujetos. (DUAZARY 2011 No. 2, 243 - 250Abstract: The applicability of the Programming Neuro-linguistics is for many, myth question, pseudosciences or methodological incompatibility between her and the Psychology. However, in the learning process it is evidenced that he/she makes a high sense, since it is an effective and simple tool that allows a significant change in the academic yield of the students and the productivity in organizational terms. With this model he/she learns how to syntonize in an effective way the social relationships, with the purpose of giving a more stimulating and more significant sense to the implicit processes where the human being is manifested. This way, presently article, under a method of theoretical investigation, thought about the objective of: to determine the conceptual relationship and he/she practices of the Programming Neuro-linguistics with the Psychology and the Neuro-science; at the time that you

Comparative and functional analysis of the widely occurring family of Nep1-like proteins

NARCIS (Netherlands)

Oome, Stan; van den Ackerveken, Guido

2014-01-01

Nep1-like proteins (NLP) are best known for their cytotoxic activity in dicot plants. NLP are taxonomically widespread among microbes with very different lifestyles. To learn more about this enigmatic protein family, we analyzed more than 500 available NLP protein sequences from fungi, oomycetes,

What Makes a Good Educator? The Relevance of Meta Programmes

Science.gov (United States)

Brown, Nigel

2004-01-01

This paper reports the results of a qualitative study which explores the relevance of meta programmes to students' perceptions of teaching quality. Meta programmes are a model of personality preferences from the discipline of Neuro Linguistic Programming (NLP). Research into teaching effectiveness indicates that students rate as important "hygiene…

CLAMP - a toolkit for efficiently building customized clinical natural language processing pipelines.

Science.gov (United States)

Soysal, Ergin; Wang, Jingqi; Jiang, Min; Wu, Yonghui; Pakhomov, Serguei; Liu, Hongfang; Xu, Hua

2017-11-24

Existing general clinical natural language processing (NLP) systems such as MetaMap and Clinical Text Analysis and Knowledge Extraction System have been successfully applied to information extraction from clinical text. However, end users often have to customize existing systems for their individual tasks, which can require substantial NLP skills. Here we present CLAMP (Clinical Language Annotation, Modeling, and Processing), a newly developed clinical NLP toolkit that provides not only state-of-the-art NLP components, but also a user-friendly graphic user interface that can help users quickly build customized NLP pipelines for their individual applications. Our evaluation shows that the CLAMP default pipeline achieved good performance on named entity recognition and concept encoding. We also demonstrate the efficiency of the CLAMP graphic user interface in building customized, high-performance NLP pipelines with 2 use cases, extracting smoking status and lab test values. CLAMP is publicly available for research use, and we believe it is a unique asset for the clinical NLP community. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Using information from the electronic health record to improve measurement of unemployment in service members and veterans with mTBI and post-deployment stress.

Directory of Open Access Journals (Sweden)

Christina Dillahunt-Aspillaga

Full Text Available The purpose of this pilot study is 1 to develop an annotation schema and a training set of annotated notes to support the future development of a natural language processing (NLP system to automatically extract employment information, and 2 to determine if information about employment status, goals and work-related challenges reported by service members and Veterans with mild traumatic brain injury (mTBI and post-deployment stress can be identified in the Electronic Health Record (EHR.Retrospective cohort study using data from selected progress notes stored in the EHR.Post-deployment Rehabilitation and Evaluation Program (PREP, an in-patient rehabilitation program for Veterans with TBI at the James A. Haley Veterans' Hospital in Tampa, Florida.Service members and Veterans with TBI who participated in the PREP program (N = 60.Documentation of employment status, goals, and work-related challenges reported by service members and recorded in the EHR.Two hundred notes were examined and unique vocational information was found indicating a variety of self-reported employment challenges. Current employment status and future vocational goals along with information about cognitive, physical, and behavioral symptoms that may affect return-to-work were extracted from the EHR. The annotation schema developed for this study provides an excellent tool upon which NLP studies can be developed.Information related to employment status and vocational history is stored in text notes in the EHR system. Information stored in text does not lend itself to easy extraction or summarization for research and rehabilitation planning purposes. Development of NLP systems to automatically extract text-based employment information provides data that may improve the understanding and measurement of employment in this important cohort.

Book review

Directory of Open Access Journals (Sweden)

Ripan Hermawan

2011-07-01

Full Text Available Natural Language Processing (NLP is a 'theoretically motivated range of computational techniques for analyzing and representing naturally occurring texts at one or more levels of linguistic analysis for the purpose of achieving human-like language processing for a range of tasks or applications' (Liddy, 2001, p.1. NLP is an increasingly popular field of study nowadays. The applications of NLP are widespread. There are many applications made possible by NLP such as translation tools, speech recognition and transcription softwares, speech to text and text to speech applications, corpus tools, predictive text applications, and many more. These in return have contributed to the increase in the popularity of NLP itself, not only among academics but also among wider audiences who have benefited from it.

African languages — is the writing on the screen? | Bosch | Southern ...

African Journals Online (AJOL)

The trends emerging in the natural language processing (NLP) of African languages spoken in South Africa, are explored in order to determine whether research in and development of such NLP is keeping abreast of international developments. This is done by investigating the past, present and future of NLP of African ...

Building a Natural Language Processing Tool to Identify Patients With High Clinical Suspicion for Kawasaki Disease from Emergency Department Notes.

Science.gov (United States)

Doan, Son; Maehara, Cleo K; Chaparro, Juan D; Lu, Sisi; Liu, Ruiling; Graham, Amanda; Berry, Erika; Hsu, Chun-Nan; Kanegaye, John T; Lloyd, David D; Ohno-Machado, Lucila; Burns, Jane C; Tremoulet, Adriana H

2016-05-01

Delayed diagnosis of Kawasaki disease (KD) may lead to serious cardiac complications. We sought to create and test the performance of a natural language processing (NLP) tool, the KD-NLP, in the identification of emergency department (ED) patients for whom the diagnosis of KD should be considered. We developed an NLP tool that recognizes the KD diagnostic criteria based on standard clinical terms and medical word usage using 22 pediatric ED notes augmented by Unified Medical Language System vocabulary. With high suspicion for KD defined as fever and three or more KD clinical signs, KD-NLP was applied to 253 ED notes from children ultimately diagnosed with either KD or another febrile illness. We evaluated KD-NLP performance against ED notes manually reviewed by clinicians and compared the results to a simple keyword search. KD-NLP identified high-suspicion patients with a sensitivity of 93.6% and specificity of 77.5% compared to notes manually reviewed by clinicians. The tool outperformed a simple keyword search (sensitivity = 41.0%; specificity = 76.3%). KD-NLP showed comparable performance to clinician manual chart review for identification of pediatric ED patients with a high suspicion for KD. This tool could be incorporated into the ED electronic health record system to alert providers to consider the diagnosis of KD. KD-NLP could serve as a model for decision support for other conditions in the ED. © 2016 by the Society for Academic Emergency Medicine.

A common type system for clinical natural language processing.

Science.gov (United States)

Wu, Stephen T; Kaggal, Vinod C; Dligach, Dmitriy; Masanz, James J; Chen, Pei; Becker, Lee; Chapman, Wendy W; Savova, Guergana K; Liu, Hongfang; Chute, Christopher G

2013-01-03

One challenge in reusing clinical data stored in electronic medical records is that these data are heterogenous. Clinical Natural Language Processing (NLP) plays an important role in transforming information in clinical text to a standard representation that is comparable and interoperable. Information may be processed and shared when a type system specifies the allowable data structures. Therefore, we aim to define a common type system for clinical NLP that enables interoperability between structured and unstructured data generated in different clinical settings. We describe a common type system for clinical NLP that has an end target of deep semantics based on Clinical Element Models (CEMs), thus interoperating with structured data and accommodating diverse NLP approaches. The type system has been implemented in UIMA (Unstructured Information Management Architecture) and is fully functional in a popular open-source clinical NLP system, cTAKES (clinical Text Analysis and Knowledge Extraction System) versions 2.0 and later. We have created a type system that targets deep semantics, thereby allowing for NLP systems to encapsulate knowledge from text and share it alongside heterogenous clinical data sources. Rather than surface semantics that are typically the end product of NLP algorithms, CEM-based semantics explicitly build in deep clinical semantics as the point of interoperability with more structured data types.

Community challenges in biomedical text mining over 10 years: success, failure and the future.

Science.gov (United States)

Huang, Chung-Chi; Lu, Zhiyong

2016-01-01

One effective way to improve the state of the art is through competitions. Following the success of the Critical Assessment of protein Structure Prediction (CASP) in bioinformatics research, a number of challenge evaluations have been organized by the text-mining research community to assess and advance natural language processing (NLP) research for biomedicine. In this article, we review the different community challenge evaluations held from 2002 to 2014 and their respective tasks. Furthermore, we examine these challenge tasks through their targeted problems in NLP research and biomedical applications, respectively. Next, we describe the general workflow of organizing a Biomedical NLP (BioNLP) challenge and involved stakeholders (task organizers, task data producers, task participants and end users). Finally, we summarize the impact and contributions by taking into account different BioNLP challenges as a whole, followed by a discussion of their limitations and difficulties. We conclude with future trends in BioNLP challenge evaluations. Published by Oxford University Press 2015. This work is written by US Government employees and is in the public domain in the US.

PLENATITUDE Teacher Education for Effectiveness and Well-Being with Neuro-Linguistic Programming

Science.gov (United States)

Vieira, Cristina Rocha; Gaspar, Maria Filomena

2013-01-01

The role and functioning of schools are changing as well as what is expected of teachers (who face growing and diversified challenges); consequentially, well-being at the schools is endangered. As teachers and teachers' educators concern is: How to improve schools' and teachers' effectiveness and promote well-being. Believing that the path to…

Application of Neurolinguistic Programming for Treatment and Relapse Prevention of Addictive Behaviors.

Science.gov (United States)

Sandhu, Daya Singh

The dilemma of relapse exists for a number of addictive behaviors, and mental health authorities agree that keeping addictive behaviors off permanently is much more difficult than treating the behaviors initially. Several relapse prevention models have been posited and environmental, physiological, behavioral, cognitive, and affective factors have…

The use of natural language processing on pediatric diagnostic radiology reports in the electronic health record to identify deep venous thrombosis in children.

Science.gov (United States)

Gálvez, Jorge A; Pappas, Janine M; Ahumada, Luis; Martin, John N; Simpao, Allan F; Rehman, Mohamed A; Witmer, Char

2017-10-01

Venous thromboembolism (VTE) is a potentially life-threatening condition that includes both deep vein thrombosis (DVT) and pulmonary embolism. We sought to improve detection and reporting of children with a new diagnosis of VTE by applying natural language processing (NLP) tools to radiologists' reports. We validated an NLP tool, Reveal NLP (Health Fidelity Inc, San Mateo, CA) and inference rules engine's performance in identifying reports with deep venous thrombosis using a curated set of ultrasound reports. We then configured the NLP tool to scan all available radiology reports on a daily basis for studies that met criteria for VTE between July 1, 2015, and March 31, 2016. The NLP tool and inference rules engine correctly identified 140 out of 144 reports with positive DVT findings and 98 out of 106 negative reports in the validation set. The tool's sensitivity was 97.2% (95% CI 93-99.2%), specificity was 92.5% (95% CI 85.7-96.7%). Subsequently, the NLP tool and inference rules engine processed 6373 radiology reports from 3371 hospital encounters. The NLP tool and inference rules engine identified 178 positive reports and 3193 negative reports with a sensitivity of 82.9% (95% CI 74.8-89.2) and specificity of 97.5% (95% CI 96.9-98). The system functions well as a safety net to screen patients for HA-VTE on a daily basis and offers value as an automated, redundant system. To our knowledge, this is the first pediatric study to apply NLP technology in a prospective manner for HA-VTE identification.

Non-abelian factorisation for next-to-leading-power threshold logarithms

International Nuclear Information System (INIS)

Bonocore, D.; Laenen, E.; Magnea, L.; Vernazza, L.; White, C.D.

2016-01-01

Soft and collinear radiation is responsible for large corrections to many hadronic cross sections, near thresholds for the production of heavy final states. There is much interest in extending our understanding of this radiation to next-to-leading power (NLP) in the threshold expansion. In this paper, we generalise a previously proposed all-order NLP factorisation formula to include non-abelian corrections. We define a non-abelian radiative jet function, organising collinear enhancements at NLP, and compute it for quark jets at one loop. We discuss in detail the issue of double counting between soft and collinear regions. Finally, we verify our prescription by reproducing all NLP logarithms in Drell-Yan production up to NNLO, including those associated with double real emission. Our results constitute an important step in the development of a fully general resummation formalism for NLP threshold effects.

Non-abelian factorisation for next-to-leading-power threshold logarithms

Energy Technology Data Exchange (ETDEWEB)

Bonocore, D. [Nikhef, Science Park 105, NL-1098 XG Amsterdam (Netherlands); Institute for Theoretical Particle Physics and Cosmology, RWTH Aachen University, Sommerfeldstr. 16, 52074 Aachen (Germany); Laenen, E. [Nikhef, Science Park 105, NL-1098 XG Amsterdam (Netherlands); ITFA, University of Amsterdam, Science Park 904, Amsterdam (Netherlands); ITF, Utrecht University, Leuvenlaan 4, Utrecht (Netherlands); Kavli Institute for Theoretical Physics, University of California, Santa Barbara, CA 93106-4030 (United States); Magnea, L. [Dipartimento di Fisica, Università di Torino and INFN, Sezione di Torino, Via P. Giuria 1, I-10125 Torino (Italy); Vernazza, L. [Higgs Centre for Theoretical Physics, School of Physics and Astronomy, The University of Edinburgh, Edinburgh EH9 3JZ, Scotland (United Kingdom); White, C.D. [Centre for Research in String Theory, School of Physics and Astronomy, Queen Mary University of London, 327 Mile End Road, London E1 4NS (United Kingdom)

2016-12-22

Soft and collinear radiation is responsible for large corrections to many hadronic cross sections, near thresholds for the production of heavy final states. There is much interest in extending our understanding of this radiation to next-to-leading power (NLP) in the threshold expansion. In this paper, we generalise a previously proposed all-order NLP factorisation formula to include non-abelian corrections. We define a non-abelian radiative jet function, organising collinear enhancements at NLP, and compute it for quark jets at one loop. We discuss in detail the issue of double counting between soft and collinear regions. Finally, we verify our prescription by reproducing all NLP logarithms in Drell-Yan production up to NNLO, including those associated with double real emission. Our results constitute an important step in the development of a fully general resummation formalism for NLP threshold effects.

A common type system for clinical natural language processing

Directory of Open Access Journals (Sweden)

Wu Stephen T

2013-01-01

Full Text Available Abstract Background One challenge in reusing clinical data stored in electronic medical records is that these data are heterogenous. Clinical Natural Language Processing (NLP plays an important role in transforming information in clinical text to a standard representation that is comparable and interoperable. Information may be processed and shared when a type system specifies the allowable data structures. Therefore, we aim to define a common type system for clinical NLP that enables interoperability between structured and unstructured data generated in different clinical settings. Results We describe a common type system for clinical NLP that has an end target of deep semantics based on Clinical Element Models (CEMs, thus interoperating with structured data and accommodating diverse NLP approaches. The type system has been implemented in UIMA (Unstructured Information Management Architecture and is fully functional in a popular open-source clinical NLP system, cTAKES (clinical Text Analysis and Knowledge Extraction System versions 2.0 and later. Conclusions We have created a type system that targets deep semantics, thereby allowing for NLP systems to encapsulate knowledge from text and share it alongside heterogenous clinical data sources. Rather than surface semantics that are typically the end product of NLP algorithms, CEM-based semantics explicitly build in deep clinical semantics as the point of interoperability with more structured data types.

Heavy quarkonium production at collider energies: Factorization and evolution

Science.gov (United States)

Kang, Zhong-Bo; Ma, Yan-Qing; Qiu, Jian-Wei; Sterman, George

2014-08-01

We present a perturbative QCD factorization formalism for inclusive production of heavy quarkonia of large transverse momentum, pT at collider energies, including both leading power (LP) and next-to-leading power (NLP) behavior in pT. We demonstrate that both LP and NLP contributions can be factorized in terms of perturbatively calculable short-distance partonic coefficient functions and universal nonperturbative fragmentation functions, and derive the evolution equations that are implied by the factorization. We identify projection operators for all channels of the factorized LP and NLP infrared safe short-distance partonic hard parts, and corresponding operator definitions of fragmentation functions. For the NLP, we focus on the contributions involving the production of a heavy quark pair, a necessary condition for producing a heavy quarkonium. We evaluate the first nontrivial order of evolution kernels for all relevant fragmentation functions, and discuss the role of NLP contributions.

Neurophysiology of speech differences in childhood apraxia of speech.

Science.gov (United States)

Preston, Jonathan L; Molfese, Peter J; Gumkowski, Nina; Sorcinelli, Andrea; Harwood, Vanessa; Irwin, Julia R; Landi, Nicole

2014-01-01

Event-related potentials (ERPs) were recorded during a picture naming task of simple and complex words in children with typical speech and with childhood apraxia of speech (CAS). Results reveal reduced amplitude prior to speaking complex (multisyllabic) words relative to simple (monosyllabic) words for the CAS group over the right hemisphere during a time window thought to reflect phonological encoding of word forms. Group differences were also observed prior to production of spoken tokens regardless of word complexity during a time window just prior to speech onset (thought to reflect motor planning/programming). Results suggest differences in pre-speech neurolinguistic processes.

Predictive factors for final outcome of severely traumatized eyes with no light perception

Directory of Open Access Journals (Sweden)

Agrawal Rupesh

2012-06-01

Full Text Available Abstract Background An eye injury that causes no light perception (NLP typically carries an unfavorable prognosis, and NLP because of trauma is a common indication for enucleation. With advances in vitreoretinal surgical techniques, however, the indication for enucleation is no longer determined by posttrauma NLP vision alone. There are limited studies in the literature to analyse the outcome of NLP eyes following open globe injury. The current study was aimed to evaluate the outcome of surgical repair of severely traumatized eyes with no light perception vision as preoperative visual acuity. Secondary objective was to possibly predict the factors affecting the final vision outcome in this eyes. Methods Retrospective case analysis of patients with surgical repair of open globe injury over last ten years at a tertiary referral eye care centre in Singapore. Results Out of one hundred and seventy two eyes with open globe injury 27 (15.7% eyes had no light perception (NLP. After surgical repair, final visual acuity remained NLP in 18 (66.7% eyes. Final vision improved to Light perception/ Hand movement (LP/HM in 2(7.4% eyes, 1/200 to 19/200(11.1% in 3 eyes and 20/50-20/200(14.8% in 4 eyes. The median follow up was 18.9 months (range: 4–60 months. The factors contributing to poor postoperative outcome were presence of RAPD (p = 0.014, wound extending into zone III (p = 0.023 and associated vitreoretinal trauma (p = 0.008. Conclusions One third of eyes had ambulatory vision or better though two third of eyes still remained NLP. Pre-operative visual acuity of NLP should not be an indication for primary enucleation or evisceration for severely traumatized eyes. Presence of afferent papillary defect, wound extending posterior to rectus insertion and associated vitreoretinal trauma can adversely affect the outcome in severely traumatized eyes with NLP. Timely intervention and state of art surgery may restore useful vision in severely

Process integration: Cooling water systems design

CSIR Research Space (South Africa)

Gololo, KV

2010-10-01

Full Text Available stream_source_info Gololo2_2010.pdf.txt stream_content_type text/plain stream_size 17891 Content-Encoding UTF-8 stream_name Gololo2_2010.pdf.txt Content-Type text/plain; charset=UTF-8 The 13th Asia Pacific Confederation... results in a nonlinear program (NLP) formulation and the second case yields mixed integer nonlinear program (MINLP). In both cases the cooling towers operating capacity were debottlenecked without compromising the heat duties. The 13th Asia...

The social impact of natural language processing

DEFF Research Database (Denmark)

Hovy, Dirk; Spruit, Shannon

Research in natural language processing (NLP) used to be mostly performed on anonymous corpora, with the goal of enriching linguistic analysis. Authors were either largely unknown or public figures. As we increasingly use more data from social media, this situation has changed: users are now...... individually identifiable, and the outcome of NLP experiments and applications can have a direct effect on their lives. This change should spawn a debate about the ethical implications of NLP, but until now, the internal discourse in the field has not followed the technological development. This position paper...... identifies a number of social implications that NLP research may have, and discusses their ethical significance, as well as ways to address them....

Natural language processing systems for capturing and standardizing unstructured clinical information: A systematic review.

Science.gov (United States)

Kreimeyer, Kory; Foster, Matthew; Pandey, Abhishek; Arya, Nina; Halford, Gwendolyn; Jones, Sandra F; Forshee, Richard; Walderhaug, Mark; Botsis, Taxiarchis

2017-09-01

We followed a systematic approach based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses to identify existing clinical natural language processing (NLP) systems that generate structured information from unstructured free text. Seven literature databases were searched with a query combining the concepts of natural language processing and structured data capture. Two reviewers screened all records for relevance during two screening phases, and information about clinical NLP systems was collected from the final set of papers. A total of 7149 records (after removing duplicates) were retrieved and screened, and 86 were determined to fit the review criteria. These papers contained information about 71 different clinical NLP systems, which were then analyzed. The NLP systems address a wide variety of important clinical and research tasks. Certain tasks are well addressed by the existing systems, while others remain as open challenges that only a small number of systems attempt, such as extraction of temporal information or normalization of concepts to standard terminologies. This review has identified many NLP systems capable of processing clinical free text and generating structured output, and the information collected and evaluated here will be important for prioritizing development of new approaches for clinical NLP. Copyright © 2017 Elsevier Inc. All rights reserved.

Natural Language Processing in Radiology: A Systematic Review.

Science.gov (United States)

Pons, Ewoud; Braun, Loes M M; Hunink, M G Myriam; Kors, Jan A

2016-05-01

Radiological reporting has generated large quantities of digital content within the electronic health record, which is potentially a valuable source of information for improving clinical care and supporting research. Although radiology reports are stored for communication and documentation of diagnostic imaging, harnessing their potential requires efficient and automated information extraction: they exist mainly as free-text clinical narrative, from which it is a major challenge to obtain structured data. Natural language processing (NLP) provides techniques that aid the conversion of text into a structured representation, and thus enables computers to derive meaning from human (ie, natural language) input. Used on radiology reports, NLP techniques enable automatic identification and extraction of information. By exploring the various purposes for their use, this review examines how radiology benefits from NLP. A systematic literature search identified 67 relevant publications describing NLP methods that support practical applications in radiology. This review takes a close look at the individual studies in terms of tasks (ie, the extracted information), the NLP methodology and tools used, and their application purpose and performance results. Additionally, limitations, future challenges, and requirements for advancing NLP in radiology will be discussed. (©) RSNA, 2016 Online supplemental material is available for this article.

Differentiation of ileostomy from colostomy procedures: assessing the accuracy of current procedural terminology codes and the utility of natural language processing.

Science.gov (United States)

Vo, Elaine; Davila, Jessica A; Hou, Jason; Hodge, Krystle; Li, Linda T; Suliburk, James W; Kao, Lillian S; Berger, David H; Liang, Mike K

2013-08-01

Large databases provide a wealth of information for researchers, but identifying patient cohorts often relies on the use of current procedural terminology (CPT) codes. In particular, studies of stoma surgery have been limited by the accuracy of CPT codes in identifying and differentiating ileostomy procedures from colostomy procedures. It is important to make this distinction because the prevalence of complications associated with stoma formation and reversal differ dramatically between types of stoma. Natural language processing (NLP) is a process that allows text-based searching. The Automated Retrieval Console is an NLP-based software that allows investigators to design and perform NLP-assisted document classification. In this study, we evaluated the role of CPT codes and NLP in differentiating ileostomy from colostomy procedures. Using CPT codes, we conducted a retrospective study that identified all patients undergoing a stoma-related procedure at a single institution between January 2005 and December 2011. All operative reports during this time were reviewed manually to abstract the following variables: formation or reversal and ileostomy or colostomy. Sensitivity and specificity for validation of the CPT codes against the mastery surgery schedule were calculated. Operative reports were evaluated by use of NLP to differentiate ileostomy- from colostomy-related procedures. Sensitivity and specificity for identifying patients with ileostomy or colostomy procedures were calculated for CPT codes and NLP for the entire cohort. CPT codes performed well in identifying stoma procedures (sensitivity 87.4%, specificity 97.5%). A total of 664 stoma procedures were identified by CPT codes between 2005 and 2011. The CPT codes were adequate in identifying stoma formation (sensitivity 97.7%, specificity 72.4%) and stoma reversal (sensitivity 74.1%, specificity 98.7%), but they were inadequate in identifying ileostomy (sensitivity 35.0%, specificity 88.1%) and colostomy (75

Controller design for interval plants

International Nuclear Information System (INIS)

Al-Sunni, F.M.

2003-01-01

We make use of celebrated Kharitoniv theorem to come up with a design procedure for the stabilization of uncertain systems in the parameters using low order controllers. The proposed design is based on classical design methods. A Non-linear programming (NLP) approach for the design of higher order controllers is also presented. We present our results and give illustrating examples. (author)

On Dataless Hierarchical Text Classification (Author’s Manuscript)

Science.gov (United States)

2014-07-27

compound talk.politics.mideast politics mideast israel arab jews jewish muslim talk.politics.misc politics gay homosexual sexual alt.atheism atheism...tion in NLP tasks; it was further used in several NLP works, such as by Liang (2005), to measure words’ distributional similarity. This method...embedding trained by neural networks has been used widely in the NLP community and has become a hot trend recently. In this pa- per, we test the suitability

Development of a Natural Language Processing Engine to Generate Bladder Cancer Pathology Data for Health Services Research.

Science.gov (United States)

Schroeck, Florian R; Patterson, Olga V; Alba, Patrick R; Pattison, Erik A; Seigne, John D; DuVall, Scott L; Robertson, Douglas J; Sirovich, Brenda; Goodney, Philip P

2017-12-01

To take the first step toward assembling population-based cohorts of patients with bladder cancer with longitudinal pathology data, we developed and validated a natural language processing (NLP) engine that abstracts pathology data from full-text pathology reports. Using 600 bladder pathology reports randomly selected from the Department of Veterans Affairs, we developed and validated an NLP engine to abstract data on histology, invasion (presence vs absence and depth), grade, the presence of muscularis propria, and the presence of carcinoma in situ. Our gold standard was based on an independent review of reports by 2 urologists, followed by adjudication. We assessed the NLP performance by calculating the accuracy, the positive predictive value, and the sensitivity. We subsequently applied the NLP engine to pathology reports from 10,725 patients with bladder cancer. When comparing the NLP output to the gold standard, NLP achieved the highest accuracy (0.98) for the presence vs the absence of carcinoma in situ. Accuracy for histology, invasion (presence vs absence), grade, and the presence of muscularis propria ranged from 0.83 to 0.96. The most challenging variable was depth of invasion (accuracy 0.68), with an acceptable positive predictive value for lamina propria (0.82) and for muscularis propria (0.87) invasion. The validated engine was capable of abstracting pathologic characteristics for 99% of the patients with bladder cancer. NLP had high accuracy for 5 of 6 variables and abstracted data for the vast majority of the patients. This now allows for the assembly of population-based cohorts with longitudinal pathology data. Published by Elsevier Inc.

Test of the neurolinguistic programming hypothesis that eye-movements relate to processing imagery.

Science.gov (United States)

Wertheim, E H; Habib, C; Cumming, G

1986-04-01

Bandler and Grinder's hypothesis that eye-movements reflect sensory processing was examined. 28 volunteers first memorized and then recalled visual, auditory, and kinesthetic stimuli. Changes in eye-positions during recall were videotaped and categorized by two raters into positions hypothesized by Bandler and Grinder's model to represent visual, auditory, and kinesthetic recall. Planned contrast analyses suggested that visual stimulus items, when recalled, elicited significantly more upward eye-positions and stares than auditory and kinesthetic items. Auditory and kinesthetic items, however, did not elicit more changes in eye-position hypothesized by the model to represent auditory and kinesthetic recall, respectively.

Designing visual displays and system models for safe reactor operations based on the user's perspective of the system

International Nuclear Information System (INIS)

Brown-VanHoozer, S.A.

1995-01-01

Most designers are not schooled in the area of human-interaction psychology and therefore tend to rely on the traditional ergonomic aspects of human factors when designing complex human-interactive workstations related to reactor operations. They do not take into account the differences in user information processing behavior and how these behaviors may affect individual and team performance when accessing visual displays or utilizing system models in process and control room areas. Unfortunately, by ignoring the importance of the integration of the user interface at the information process level, the result can be sub-optimization and inherently error- and failure-prone systems. Therefore, to minimize or eliminate failures in human-interactive systems, it is essential that the designers understand how each user's processing characteristics affects how the user gathers information, and how the user communicates the information to the designer and other users. A different type of approach in achieving this understanding is Neuro Linguistic Programming (NLP). The material presented in this paper is based on two studies involving the design of visual displays, NLP, and the user's perspective model of a reactor system. The studies involve the methodology known as NLP, and its use in expanding design choices from the user's ''model of the world,'' in the areas of virtual reality, workstation design, team structure, decision and learning style patterns, safety operations, pattern recognition, and much, much more

Optimization of Multipurpose Reservoir Operation with Application Particle Swarm Optimization Algorithm

Directory of Open Access Journals (Sweden)

Elahe Fallah Mehdipour

2012-12-01

Full Text Available Optimal operation of multipurpose reservoirs is one of the complex and sometimes nonlinear problems in the field of multi-objective optimization. Evolutionary algorithms are optimization tools that search decision space using simulation of natural biological evolution and present a set of points as the optimum solutions of problem. In this research, application of multi-objective particle swarm optimization (MOPSO in optimal operation of Bazoft reservoir with different objectives, including generating hydropower energy, supplying downstream demands (drinking, industry and agriculture, recreation and flood control have been considered. In this regard, solution sets of the MOPSO algorithm in bi-combination of objectives and compromise programming (CP using different weighting and power coefficients have been first compared that the MOPSO algorithm in all combinations of objectives is more capable than the CP to find solution with appropriate distribution and these solutions have dominated the CP solutions. Then, ending points of solution set from the MOPSO algorithm and nonlinear programming (NLP results have been compared. Results showed that the MOPSO algorithm with 0.3 percent difference from the NLP results has more capability to present optimum solutions in the ending points of solution set.

Synthesizing optimal waste blends

International Nuclear Information System (INIS)

Narayan, V.; Diwekar, W.M.; Hoza, M.

1996-01-01

Vitrification of tank wastes to form glass is a technique that will be used for the disposal of high-level waste at Hanford. Process and storage economics show that minimizing the total number of glass logs produced is the key to keeping cost as low as possible. The amount of glass produced can be reduced by blending of the wastes. The optimal way to combine the tanks to minimize the vole of glass can be determined from a discrete blend calculation. However, this problem results in a combinatorial explosion as the number of tanks increases. Moreover, the property constraints make this problem highly nonconvex where many algorithms get trapped in local minima. In this paper the authors examine the use of different combinatorial optimization approaches to solve this problem. A two-stage approach using a combination of simulated annealing and nonlinear programming (NLP) is developed. The results of different methods such as the heuristics approach based on human knowledge and judgment, the mixed integer nonlinear programming (MINLP) approach with GAMS, and branch and bound with lower bound derived from the structure of the given blending problem are compared with this coupled simulated annealing and NLP approach

An MPCC Formulation and Its Smooth Solution Algorithm for Continuous Network Design Problem

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Guangmin Wang

2017-12-01

Full Text Available Continuous network design problem (CNDP is searching for a transportation network configuration to minimize the sum of the total system travel time and the investment cost of link capacity expansions by considering that the travellers follow a traditional Wardrop user equilibrium (UE to choose their routes. In this paper, the CNDP model can be formulated as mathematical programs with complementarity constraints (MPCC by describing UE as a non-linear complementarity problem (NCP. To address the difficulty resulting from complementarity constraints in MPCC, they are substituted by the Fischer-Burmeister (FB function, which can be smoothed by the introduction of the smoothing parameter. Therefore, the MPCC can be transformed into a well-behaved non-linear program (NLP by replacing the complementarity constraints with a smooth equation. Consequently, the solver such as LINDOGLOBAL in GAMS can be used to solve the smooth approximate NLP to obtain the solution to MPCC for modelling CNDP. The numerical experiments on the example from the literature demonstrate that the proposed algorithm is feasible.

Pt supported self-assembled nest-like-porous WO3 hierarchical microspheres as electrocatalyst for methanol oxidation

International Nuclear Information System (INIS)

Zhang, Jun; Tu, Jiang-ping; Du, Gao-hui; Dong, Zi-min; Su, Qing-mei; Xie, Dong; Wang, Xiu-li

2013-01-01

Highlights: ► Nest-like-porous (NLP) WO 3 microspheres are assembled by a hydrothermal method. ► The NLP-WO 3 microspheres have a hexagonal structure and high porous surface. ► Great enhancement of electrochemical property is achieved for Pt/NLP-WO 3 microspheres. -- Abstract: Hexagonal tungsten trioxide (hex-WO 3 ) hierarchical microspheres with nest-like pores are synthesized by a facile hydrothermal method. The nest-like-porous (NLP) WO 3 hierarchical microspheres with 5–6 μm in diameters are self-assembled of single-crystal nanowires. The nanowires have lengths of several hundred nanometers and diameters of 5–30 nm; the long axis of nanowire is oriented toward 〈0 0 1〉 direction. The specific surface area of hex-WO 3 microspheres is 62 m 2 g −1 . 20 wt.% Pt nanoparticles with ∼7 nm are loaded onto the WO 3 microspheres using a conventional microwave-assisted ethylene glycol (EG) method. The electrocatalytic activity for methanol oxidation of Pt/NLP-WO 3 microspheres is investigated by cyclic voltammetry and chronoamperometry. Due to the large tunnels of hexagonal structure and high porous surface morphology, great enhancement of electrochemical performance is achieved. The Pt/NLP-WO 3 microspheres are demonstrated to be a promising anode material for direct methanol fuel cells (DMFC)

PVCM, PVCD, EPL, and irritable larynx syndrome: what are we talking about and how do we treat it?

Science.gov (United States)

Andrianopoulos, M V; Gallivan, G J; Gallivan, K H

2000-12-01

Paroxysmal vocal cord movement/motion (PVCM), paroxysmal vocal cord dysfunction (PVCD), episodic paroxysmal laryngospasm (EPL), and irritable larynx syndrome (ILS) are terms used to describe laryngeal dysfunction masquerading as asthma, upper airway obstruction, or functional and organic voice disorders. The differential diagnosis of PVCM, PVCD, EPL, and ILS is critical to successful medical and behavioral management of the patient. During the past 10 years, 27 subjects, ages 15-79 years, were identified to have paroxysms of inspiratory stridor, acute respiratory distress, associated aphonia and dysphonia, resulting in misdiagnosis and unnecessary emergency treatments, including endotracheal intubation, cardiopulmonary resuscitation, massive pharmacotherapy, or tracheostomy. A multifactorial management program is proposed utilizing principles of motor learning, neurolinguistic programming model, respiratory and phonatory synchronization, relaxation techniques, concurrent monitoring of behavioral adjustments, and formal psychological counseling.

Validation of natural language processing to extract breast cancer pathology procedures and results

Directory of Open Access Journals (Sweden)

Arika E Wieneke

2015-01-01

Full Text Available Background: Pathology reports typically require manual review to abstract research data. We developed a natural language processing (NLP system to automatically interpret free-text breast pathology reports with limited assistance from manual abstraction. Methods: We used an iterative approach of machine learning algorithms and constructed groups of related findings to identify breast-related procedures and results from free-text pathology reports. We evaluated the NLP system using an all-or-nothing approach to determine which reports could be processed entirely using NLP and which reports needed manual review beyond NLP. We divided 3234 reports for development (2910, 90%, and evaluation (324, 10% purposes using manually reviewed pathology data as our gold standard. Results: NLP correctly coded 12.7% of the evaluation set, flagged 49.1% of reports for manual review, incorrectly coded 30.8%, and correctly omitted 7.4% from the evaluation set due to irrelevancy (i.e. not breast-related. Common procedures and results were identified correctly (e.g. invasive ductal with 95.5% precision and 94.0% sensitivity, but entire reports were flagged for manual review because of rare findings and substantial variation in pathology report text. Conclusions: The NLP system we developed did not perform sufficiently for abstracting entire breast pathology reports. The all-or-nothing approach resulted in too broad of a scope of work and limited our flexibility to identify breast pathology procedures and results. Our NLP system was also limited by the lack of the gold standard data on rare findings and wide variation in pathology text. Focusing on individual, common elements and improving pathology text report standardization may improve performance.

TEACHING GEOGRAPHY TO CHILDREN WITH LEARNING DIFFICULTIES, IN THE EUROPEAN SCHOOLS

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IULIA ŞCHIOPU

2016-01-01

Full Text Available European Schools offer the opportunity to observe the differences between students and how attention towards the individual is needed. Backed up by a set of frameworks, such as Gestion Mentale, Neuro-linguistic Programming and thinkers such as Paulo Freire, the work of empowering the individual when a challenge is present is exemplified in the context of Geography. What makes a student succeed when the default method is proven challenging. There is no limit as to what methods could be applied as long as they are all guided by the lines of placing the student in a powerful spot: the spot where a challenge becomes a learning opportunity.

Deterministic global optimization algorithm based on outer approximation for the parameter estimation of nonlinear dynamic biological systems.

Science.gov (United States)

Miró, Anton; Pozo, Carlos; Guillén-Gosálbez, Gonzalo; Egea, Jose A; Jiménez, Laureano

2012-05-10

The estimation of parameter values for mathematical models of biological systems is an optimization problem that is particularly challenging due to the nonlinearities involved. One major difficulty is the existence of multiple minima in which standard optimization methods may fall during the search. Deterministic global optimization methods overcome this limitation, ensuring convergence to the global optimum within a desired tolerance. Global optimization techniques are usually classified into stochastic and deterministic. The former typically lead to lower CPU times but offer no guarantee of convergence to the global minimum in a finite number of iterations. In contrast, deterministic methods provide solutions of a given quality (i.e., optimality gap), but tend to lead to large computational burdens. This work presents a deterministic outer approximation-based algorithm for the global optimization of dynamic problems arising in the parameter estimation of models of biological systems. Our approach, which offers a theoretical guarantee of convergence to global minimum, is based on reformulating the set of ordinary differential equations into an equivalent set of algebraic equations through the use of orthogonal collocation methods, giving rise to a nonconvex nonlinear programming (NLP) problem. This nonconvex NLP is decomposed into two hierarchical levels: a master mixed-integer linear programming problem (MILP) that provides a rigorous lower bound on the optimal solution, and a reduced-space slave NLP that yields an upper bound. The algorithm iterates between these two levels until a termination criterion is satisfied. The capabilities of our approach were tested in two benchmark problems, in which the performance of our algorithm was compared with that of the commercial global optimization package BARON. The proposed strategy produced near optimal solutions (i.e., within a desired tolerance) in a fraction of the CPU time required by BARON.

Caracterização anestésica da nanoemulsão não lipídica de propofol Caracterización anestésica de la nanoemulsión no lipídica de propofol Anesthetic profile of a non-lipid propofol nanoemulsion

Directory of Open Access Journals (Sweden)

Roberto Takashi Sudo

2010-10-01

Full Text Available JUSTIFICATIVA E OBJETIVOS: Uso clínico de formulação lipídica de propofol causa dor durante injeção, reação alérgica e crescimento microbiano. Propofol tem sido reformulado em diferentes apresentações não lipídicas para reduzir os efeitos adversos, mas essas mudanças podem modificar sua farmacocinética e farmacodinâmica. Neste trabalho, investigamos a farmacologia e a toxicologia do propofol lipídico (CLP e da nanoemulsão não lipídica (NLP. MÉTODO: CLP and NLP foram infundidos na veia jugular de ratos sob medida da pressão arterial (PA, frequência cardíaca (FC e frequência respiratória (FR. Ambas as formulações (1% foram infundidas (40 µL.min-1 durante 1 hora. Doses hipnóticas e anestésicas, assim como recuperações, foram determinadas. A dor induzida pelo veículo do CLP e NLP foi comparada por meio da contagem do número de contorções abdominais ("writhing test" após injeção intraperitonial (i.p. em camundongos. Ácido acético (0,6% foi usado como controle positivo. RESULTADOS: As doses hipnóticas e anestésicas com 1% CLP (6,0 ± 1,3 e 17,8 ± 2,6 mg.kg-1, respectivamente e 1% NLP (5,4 ± 1,0 e 16,0 ± 1,4 mg.kg-1, respectivamente não foram significativamente diferentes. A recuperação da hipnose e da anestesia foi mais rápida com NLP do que com CLP. As alterações de FC, PA e FR causadas pelo NLP não foram significativamente diferentes das do CLP. Ácido acético e veículo do CLP provocaram 46,0 ± 2,0 e 12,5 ± 0,6 contorções em 20 min após injeção i.p., respectivamente. Observou-se ausência de contorções abdominais com veículo de NLP. Nenhuma resposta inflamatória abdominal foi notada com a injeção i.p. de ambos os veículos de propofol. CONCLUSÕES: O NLP pode representar melhor alternativa do que o CLP para anestesia venosa com menores efeitos adversosJUSTIFICATIVA Y OBJETIVOS: El uso clínico de la formulación lipídica del propofol, causa dolor durante la inyección, reacci

Effect of garlic and neem leaf powder supplementation on growth performance and carcass traits in broilers

Directory of Open Access Journals (Sweden)

Karan Rajendra Kharde

2014-10-01

Full Text Available Aim: Present experiment was designed to study the effect of supplementation of garlic and neem leaf powder (NLP on growth performance and carcass yields in broilers. Materials and Methods: A total of 210-day-old commercial male broiler chicks (Ven Cobb were procured and randomly distributed in to seven treatments, each treatment had six replicates with five chicks per each replicate. Growth trial was conducted in a randomized block design comprising seven dietary treatments. T1 was served as control. T2 and T3 were fed with garlic powder (GP 0.5, 1 g/kg feed respectively. T4 and T5 were given with NLP 1, 2 g/kg feed respectively. T6 was fed with 0.5 g/kg GP and 1.0 g/kg NLP. T7 was treated with 1.0 g/kg GP and 2.0 g/kg NLP. The body weight, feed consumption of individual bird was recorded at weekly interval and the body weight gain, feed conversion ratio (FCR were calculated. At the end of 42 day, six birds from each dietary group were sacrificed to estimate the dressing yield and relative weights of giblet (liver, heart and gizzard. Results: Supplementation of garlic and NLP alone and their combination significantly (p0.05 influence was observed in carcass parameters like dressing yield and giblet yield (heart, gizzard and liver in all treatment groups. Conclusions: Supplementation of GP alone showed poor performance, but when it was supplemented in combination with NLP there was improvement in performance parameters. These results indicated that the combination of GP and NLP can be used as alternates to coccidiostats for improving the performance. Such meat can be used as a designer meat as fetch higher price if marketed as branded item.

INTEGRATING CORPUS-BASED RESOURCES AND NATURAL LANGUAGE PROCESSING TOOLS INTO CALL

Directory of Open Access Journals (Sweden)

Pascual Cantos Gomez

2002-06-01

Full Text Available This paper ainis at presenting a survey of computational linguistic tools presently available but whose potential has been neither fully considered not exploited to its full in modern CALL. It starts with a discussion on the rationale of DDL to language learning, presenting typical DDL-activities. DDL-software and potential extensions of non-typical DDL-software (electronic dictionaries and electronic dictionary facilities to DDL . An extended section is devoted to describe NLP-technology and how it can be integrated into CALL, within already existing software or as stand alone resources. A range of NLP-tools is presentcd (MT programs, taggers, lemn~atizersp, arsers and speech technologies with special emphasis on tagged concordancing. The paper finishes with a number of reflections and ideas on how language technologies can be used efficiently within the language learning context and how extensive exploration and integration of these technologies might change and extend both modern CAI,I, and the present language learning paradigiii..

Trajectory optimization for lunar rover performing vertical takeoff vertical landing maneuvers in the presence of terrain

Science.gov (United States)

Ma, Lin; Wang, Kexin; Xu, Zuhua; Shao, Zhijiang; Song, Zhengyu; Biegler, Lorenz T.

2018-05-01

This study presents a trajectory optimization framework for lunar rover performing vertical takeoff vertical landing (VTVL) maneuvers in the presence of terrain using variable-thrust propulsion. First, a VTVL trajectory optimization problem with three-dimensional kinematics and dynamics model, boundary conditions, and path constraints is formulated. Then, a finite-element approach transcribes the formulated trajectory optimization problem into a nonlinear programming (NLP) problem solved by a highly efficient NLP solver. A homotopy-based backtracking strategy is applied to enhance the convergence in solving the formulated VTVL trajectory optimization problem. The optimal thrust solution typically has a "bang-bang" profile considering that bounds are imposed on the magnitude of engine thrust. An adaptive mesh refinement strategy based on a constant Hamiltonian profile is designed to address the difficulty in locating the breakpoints in the thrust profile. Four scenarios are simulated. Simulation results indicate that the proposed trajectory optimization framework has sufficient adaptability to handle VTVL missions efficiently.

Evaluation of Nanolipoprotein Particles (NLPs) as an In Vivo Delivery Platform

Energy Technology Data Exchange (ETDEWEB)

Fischer, Nicholas O. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States). Biosciences and Biotechnology Division; Weilhammer, Dina R. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States). Biosciences and Biotechnology Division; Dunkle, Alexis [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States). Biosciences and Biotechnology Division; Thomas, Cynthia [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States). Biosciences and Biotechnology Division; Hwang, Mona [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States). Biosciences and Biotechnology Division; Corzett, Michele [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States). Biosciences and Biotechnology Division; Lychak, Cheri [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States). Biosciences and Biotechnology Division; Mayer, Wasima [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States). Biosciences and Biotechnology Division; Urbin, Salustra [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States). Biosciences and Biotechnology Division; Collette, Nicole [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States). Biosciences and Biotechnology Division; Chiun Chang, Jiun [Univ. of California, Merced, CA (United States). School of Natural Sciences; Loots, Gabriela G. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States). Biosciences and Biotechnology Division; Univ. of California, Merced, CA (United States). School of Natural Sciences; Rasley, Amy [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States). Biosciences and Biotechnology Division; Blanchette, Craig D. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States). Biosciences and Biotechnology Division; Ceña, Valentin [Univ. of Castilla-La Mancha, Real (Spain)

2014-03-27

Nanoparticles hold great promise for the delivery of therapeutics, yet limitations remain with regards to the use of these nanosystems for efficient long-lasting targeted delivery of therapeutics, including imparting functionality to the platform, in vivo stability, drug entrapment efficiency and toxicity. In order to begin to address these limitations, we evaluated the functionality, stability, cytotoxicity, toxicity, immunogenicity and in vivo biodistribution of nanolipoprotein particles (NLPs), which are mimetics of naturally occurring high-density lipoproteins (HDLs). We also found that a wide range of molecules could be reliably conjugated to the NLP, including proteins, single-stranded DNA, and small molecules. The NLP was also found to be relatively stable in complex biological fluids and displayed no cytotoxicity in vitro at doses as high as 320 µg/ml. In addition, we observed that in vivo administration of the NLP daily for 14 consecutive days did not induce significant weight loss or result in lesions on excised organs. Furthermore, the NLPs did not display overt immunogenicity with respect to antibody generation. Finally, the biodistribution of the NLP in vivo was found to be highly dependent on the route of administration, where intranasal administration resulted in prolonged retention in the lung tissue. Though only a select number of NLP compositions were evaluated, the findings of this study suggest that the NLP platform holds promise for use as both a targeted and non-targeted in vivo delivery vehicle for a range of therapeutics.

Performance and carcass characteristics of guinea fowl fed on dietary Neem (Azadirachta indica) leaf powder as a growth promoter.

Science.gov (United States)

Singh, M K; Singh, S K; Sharma, R K; Singh, B; Kumar, Sh; Joshi, S K; Kumar, S; Sathapathy, S

2015-01-01

The present work aimed at studying growth pattern and carcass traits in pearl grey guinea fowl fed on dietary Neem (Azadirachta indica) leaf powder (NLP) over a period of 12 weeks. Day old guinea fowl keets (n=120) were randomly assigned to four treatment groups, each with 3 replicates. The first treatment was designated as control (T0) in which no supplement was added to the feed, while in treatments T1, T2 and T3, NLP was provided as 1, 2 and 3 g per kg of feed, respectively. The results revealed a significant increase in body weight at 12 weeks; 1229.7 for T1, 1249.8 for T2, and 1266.2 g T3 compared to 1220.0 g for the control group (Pratio (FCR) of the treated groups over the control, showing that feeding NLP to the treated groups has lowered their residual feed efficiency. The results of the study demonstrate the beneficial effects of supplementing NLP on body weight gain and dressed yield in the treated groups in guinea fowl. NLP is, therefore, suggested to be used as a feed supplement in guinea fowl for higher profitability.

The social impact of natural language processing

DEFF Research Database (Denmark)

Hovy, Dirk; Spruit, Shannon

Research in natural language processing (NLP) used to be mostly performed on anonymous corpora, with the goal of enriching linguistic analysis. Authors were either largely unknown or public figures. As we increasingly use more data from social media, this situation has changed: users are now...... individually identifiable, and the outcome of NLP experiments and applications can have a direct effect on their lives. This change should spawn a debate about the ethical implications of NLP, but until now, the internal discourse in the field has not followed the technological development. This position paper...

Semi-supervised learning and domain adaptation in natural language processing

CERN Document Server

Søgaard, Anders

2013-01-01

This book introduces basic supervised learning algorithms applicable to natural language processing (NLP) and shows how the performance of these algorithms can often be improved by exploiting the marginal distribution of large amounts of unlabeled data. One reason for that is data sparsity, i.e., the limited amounts of data we have available in NLP. However, in most real-world NLP applications our labeled data is also heavily biased. This book introduces extensions of supervised learning algorithms to cope with data sparsity and different kinds of sampling bias.This book is intended to be both

Designing visual displays and system models for safe reactor operations based on the user`s perspective of the system

Energy Technology Data Exchange (ETDEWEB)

Brown-VanHoozer, S.A.

1995-12-31

Most designers are not schooled in the area of human-interaction psychology and therefore tend to rely on the traditional ergonomic aspects of human factors when designing complex human-interactive workstations related to reactor operations. They do not take into account the differences in user information processing behavior and how these behaviors may affect individual and team performance when accessing visual displays or utilizing system models in process and control room areas. Unfortunately, by ignoring the importance of the integration of the user interface at the information process level, the result can be sub-optimization and inherently error- and failure-prone systems. Therefore, to minimize or eliminate failures in human-interactive systems, it is essential that the designers understand how each user`s processing characteristics affects how the user gathers information, and how the user communicates the information to the designer and other users. A different type of approach in achieving this understanding is Neuro Linguistic Programming (NLP). The material presented in this paper is based on two studies involving the design of visual displays, NLP, and the user`s perspective model of a reactor system. The studies involve the methodology known as NLP, and its use in expanding design choices from the user`s ``model of the world,`` in the areas of virtual reality, workstation design, team structure, decision and learning style patterns, safety operations, pattern recognition, and much, much more.

Real-time process optimization based on grey-box neural models

Directory of Open Access Journals (Sweden)

F. A. Cubillos

2007-09-01

Full Text Available This paper investigates the feasibility of using grey-box neural models (GNM in Real Time Optimization (RTO. These models are based on a suitable combination of fundamental conservation laws and neural networks, being used in at least two different ways: to complement available phenomenological knowledge with empirical information, or to reduce dimensionality of complex rigorous physical models. We have observed that the benefits of using these simple adaptable models are counteracted by some difficulties associated with the solution of the optimization problem. Nonlinear Programming (NLP algorithms failed in finding the global optimum due to the fact that neural networks can introduce multimodal objective functions. One alternative considered to solve this problem was the use of some kind of evolutionary algorithms, like Genetic Algorithms (GA. Although these algorithms produced better results in terms of finding the appropriate region, they took long periods of time to reach the global optimum. It was found that a combination of genetic and nonlinear programming algorithms can be use to fast obtain the optimum solution. The proposed approach was applied to the Williams-Otto reactor, considering three different GNM models of increasing complexity. Results demonstrated that the use of GNM models and mixed GA/NLP optimization algorithms is a promissory approach for solving dynamic RTO problems.

Identifying beneficial task relations for multi-task learning in deep neural networks

DEFF Research Database (Denmark)

Bingel, Joachim; Søgaard, Anders

2017-01-01

Multi-task learning (MTL) in deep neural networks for NLP has recently received increasing interest due to some compelling benefits, including its potential to efficiently regularize models and to reduce the need for labeled data. While it has brought significant improvements in a number of NLP...

Human Capital Management Through the Use of a Standard Integrated Personnel System in Royal Saudi Naval Forces

Science.gov (United States)

2013-03-01

Management System MHC Costal Mine Hunter MOD Ministry Of Defense MSC Coastal Mine Sweeper NLP Natural Language Programming NSIPS Navy Standard...seas, the Red Sea on the west and the Arabian Gulf on the east. It borders Kuwait, Iraq, and Jordan in the north and Qatar and the United Arab ...Persians from trying to invade the Arabian Peninsula. The Arabs repelled the Persian Army and defeated it in 609, causing a scandal for the ancient

An Overview of Computer-Based Natural Language Processing.

Science.gov (United States)

Gevarter, William B.

Computer-based Natural Language Processing (NLP) is the key to enabling humans and their computer-based creations to interact with machines using natural languages (English, Japanese, German, etc.) rather than formal computer languages. NLP is a major research area in the fields of artificial intelligence and computational linguistics. Commercial…

Common data model for natural language processing based on two existing standard information models: CDA+GrAF.

Science.gov (United States)

Meystre, Stéphane M; Lee, Sanghoon; Jung, Chai Young; Chevrier, Raphaël D

2012-08-01

An increasing need for collaboration and resources sharing in the Natural Language Processing (NLP) research and development community motivates efforts to create and share a common data model and a common terminology for all information annotated and extracted from clinical text. We have combined two existing standards: the HL7 Clinical Document Architecture (CDA), and the ISO Graph Annotation Format (GrAF; in development), to develop such a data model entitled "CDA+GrAF". We experimented with several methods to combine these existing standards, and eventually selected a method wrapping separate CDA and GrAF parts in a common standoff annotation (i.e., separate from the annotated text) XML document. Two use cases, clinical document sections, and the 2010 i2b2/VA NLP Challenge (i.e., problems, tests, and treatments, with their assertions and relations), were used to create examples of such standoff annotation documents, and were successfully validated with the XML schemata provided with both standards. We developed a tool to automatically translate annotation documents from the 2010 i2b2/VA NLP Challenge format to GrAF, and automatically generated 50 annotation documents using this tool, all successfully validated. Finally, we adapted the XSL stylesheet provided with HL7 CDA to allow viewing annotation XML documents in a web browser, and plan to adapt existing tools for translating annotation documents between CDA+GrAF and the UIMA and GATE frameworks. This common data model may ease directly comparing NLP tools and applications, combining their output, transforming and "translating" annotations between different NLP applications, and eventually "plug-and-play" of different modules in NLP applications. Copyright © 2011 Elsevier Inc. All rights reserved.

Det senmoderne menneske mellem magt og afmagt

DEFF Research Database (Denmark)

Krogsdal, Iben Egekvist

Afhandlingen bygger på intensivt feltarbejde i et dansk NLP-miljø. Den beskriver de grundlæggende menneske-og verdenssyn, der ligger bag ved både NLP-metoden og store dele af senmoderne terapiformer. Derefter beskriver og diskuterer den, hvordan religion (kristendom) i en senmoderne og psykologis...

Cognition-Based Approaches for High-Precision Text Mining

Science.gov (United States)

Shannon, George John

2017-01-01

This research improves the precision of information extraction from free-form text via the use of cognitive-based approaches to natural language processing (NLP). Cognitive-based approaches are an important, and relatively new, area of research in NLP and search, as well as linguistics. Cognitive approaches enable significant improvements in both…

Automated processing of electronic medical records is a reliable method of determining aspirin use in populations at risk for cardiovascular events.

Science.gov (United States)

Pakhomov, Serguei Vs; Shah, Nilay D; Hanson, Penny; Balasubramaniam, Saranya C; Smith, Steven A

2010-01-01

Low-dose aspirin reduces cardiovascular risk; however, monitoring over-the-counter medication use relies on the time-consuming and costly manual review of medical records. Our objective is to validate natural language processing (NLP) of the electronic medical record (EMR) for extracting medication exposure and contraindication information. The text of EMRs for 499 patients with type 2 diabetes was searched using NLP for evidence of aspirin use and its contraindications. The results were compared to a standardised manual records review. Of the 499 patients, 351 (70%) were using aspirin and 148 (30%) were not, according to manual review. NLP correctly identified 346 of the 351 aspirin-positive and 134 of the 148 aspirin-negative patients, indicating a sensitivity of 99% (95% CI 97-100) and specificity of 91% (95% CI 88-97). Of the 148 aspirin-negative patients, 66 (45%) had contraindications and 82 (55%) did not, according to manual review. NLP search for contraindications correctly identified 61 of the 66 patients with contraindications and 58 of the 82 patients without, yielding a sensitivity of 92% (95% CI 84-97) and a specificity of 71% (95% CI 60-80). NLP of the EMR is accurate in ascertaining documented aspirin use and could potentially be used for epidemiological research as a source of cardiovascular risk factor information.

A missense mutation in the agouti signaling protein gene (ASIP) is associated with the no light points coat phenotype in donkeys.

Science.gov (United States)

Abitbol, Marie; Legrand, Romain; Tiret, Laurent

2015-04-08

Seven donkey breeds are recognized by the French studbook and are characterized by a black, bay or grey coat colour including light cream-to-white points (LP). Occasionally, Normand bay donkeys give birth to dark foals that lack LP and display the no light points (NLP) pattern. This pattern is more frequent and officially recognized in American miniature donkeys. The LP (or pangare) phenotype resembles that of the light bellied agouti pattern in mouse, while the NLP pattern resembles that of the mammalian recessive black phenotype; both phenotypes are associated with the agouti signaling protein gene (ASIP). We used a panel of 127 donkeys to identify a recessive missense c.349 T > C variant in ASIP that was shown to be in complete association with the NLP phenotype. This variant results in a cysteine to arginine substitution at position 117 in the ASIP protein. This cysteine is highly-conserved among vertebrate ASIP proteins and was previously shown by mutagenesis experiments to lie within a functional site. Altogether, our results strongly support that the identified mutation is causative of the NLP phenotype. Thus, we propose to name the c.[349 T > C] allele in donkeys, the a(nlp) allele, which enlarges the panel of coat colour alleles in donkeys and ASIP recessive loss-of-function alleles in animals.

Integrating natural language processing expertise with patient safety event review committees to improve the analysis of medication events.

Science.gov (United States)

Fong, Allan; Harriott, Nicole; Walters, Donna M; Foley, Hanan; Morrissey, Richard; Ratwani, Raj R

2017-08-01

Many healthcare providers have implemented patient safety event reporting systems to better understand and improve patient safety. Reviewing and analyzing these reports is often time consuming and resource intensive because of both the quantity of reports and length of free-text descriptions in the reports. Natural language processing (NLP) experts collaborated with clinical experts on a patient safety committee to assist in the identification and analysis of medication related patient safety events. Different NLP algorithmic approaches were developed to identify four types of medication related patient safety events and the models were compared. Well performing NLP models were generated to categorize medication related events into pharmacy delivery delays, dispensing errors, Pyxis discrepancies, and prescriber errors with receiver operating characteristic areas under the curve of 0.96, 0.87, 0.96, and 0.81 respectively. We also found that modeling the brief without the resolution text generally improved model performance. These models were integrated into a dashboard visualization to support the patient safety committee review process. We demonstrate the capabilities of various NLP models and the use of two text inclusion strategies at categorizing medication related patient safety events. The NLP models and visualization could be used to improve the efficiency of patient safety event data review and analysis. Copyright © 2017 Elsevier B.V. All rights reserved.

Hierarchical Load Tracking Control of a Grid-Connected Solid Oxide Fuel Cell for Maximum Electrical Efficiency Operation

Directory of Open Access Journals (Sweden)

Yonghui Li

2015-03-01

Full Text Available Based on the benchmark solid oxide fuel cell (SOFC dynamic model for power system studies and the analysis of the SOFC operating conditions, the nonlinear programming (NLP optimization method was used to determine the maximum electrical efficiency of the grid-connected SOFC subject to the constraints of fuel utilization factor, stack temperature and output active power. The optimal operating conditions of the grid-connected SOFC were obtained by solving the NLP problem considering the power consumed by the air compressor. With the optimal operating conditions of the SOFC for the maximum efficiency operation obtained at different active power output levels, a hierarchical load tracking control scheme for the grid-connected SOFC was proposed to realize the maximum electrical efficiency operation with the stack temperature bounded. The hierarchical control scheme consists of a fast active power control and a slower stack temperature control. The active power control was developed by using a decentralized control method. The efficiency of the proposed hierarchical control scheme was demonstrated by case studies using the benchmark SOFC dynamic model.

Advancing Research in Second Language Writing through Computational Tools and Machine Learning Techniques: A Research Agenda

Science.gov (United States)

Crossley, Scott A.

2013-01-01

This paper provides an agenda for replication studies focusing on second language (L2) writing and the use of natural language processing (NLP) tools and machine learning algorithms. Specifically, it introduces a range of the available NLP tools and machine learning algorithms and demonstrates how these could be used to replicate seminal studies…

A Morphological Analyzer for Vocalized or Not Vocalized Arabic Language

Science.gov (United States)

El Amine Abderrahim, Med; Breksi Reguig, Fethi

This research has been to show the realization of a morphological analyzer of the Arabic language (vocalized or not vocalized). This analyzer is based upon our object model for the Arabic Natural Language Processing (NLP) and can be exploited by NLP applications such as translation machine, orthographical correction and the search for information.

Data science from scratch

CERN Document Server

Grus, Joel

2015-01-01

This is a first-principles-based, practical introduction to the fundamentals of data science aimed at the mathematically-comfortable reader with some programming skills. The book covers: * The important parts of Python to know * The important parts of Math / Probability / Statistics to know * The basics of data science * How commonly-used data science techniques work (learning by implementing them) * What is Map-Reduce and how to do it in Python * Other applications such as NLP, Network Analysis, and more

Recurrent Artificial Neural Networks and Finite State Natural Language Processing.

Science.gov (United States)

Moisl, Hermann

It is argued that pessimistic assessments of the adequacy of artificial neural networks (ANNs) for natural language processing (NLP) on the grounds that they have a finite state architecture are unjustified, and that their adequacy in this regard is an empirical issue. First, arguments that counter standard objections to finite state NLP on the…

De nye myter

DEFF Research Database (Denmark)

Krogsdal, Iben Egekvist

Selvudvikling og selvrealisering i en psykologiseret tidsalder. Bogen er en omskrivning af min ph.d.-afhandling og behandler psykologiseringen af det moderne samfund ud fra terapiformen NLP.......Selvudvikling og selvrealisering i en psykologiseret tidsalder. Bogen er en omskrivning af min ph.d.-afhandling og behandler psykologiseringen af det moderne samfund ud fra terapiformen NLP....

Building an Evaluation Scale using Item Response Theory.

Science.gov (United States)

Lalor, John P; Wu, Hao; Yu, Hong

2016-11-01

Evaluation of NLP methods requires testing against a previously vetted gold-standard test set and reporting standard metrics (accuracy/precision/recall/F1). The current assumption is that all items in a given test set are equal with regards to difficulty and discriminating power. We propose Item Response Theory (IRT) from psychometrics as an alternative means for gold-standard test-set generation and NLP system evaluation. IRT is able to describe characteristics of individual items - their difficulty and discriminating power - and can account for these characteristics in its estimation of human intelligence or ability for an NLP task. In this paper, we demonstrate IRT by generating a gold-standard test set for Recognizing Textual Entailment. By collecting a large number of human responses and fitting our IRT model, we show that our IRT model compares NLP systems with the performance in a human population and is able to provide more insight into system performance than standard evaluation metrics. We show that a high accuracy score does not always imply a high IRT score, which depends on the item characteristics and the response pattern.

Matching therapists' predicates: an in vivo test of effectiveness.

Science.gov (United States)

Dowd, E T; Hingst, A G

1983-08-01

The theory of neurolinguistic programming predicts that a therapist's matching of a client's primary representational system, as expressed in the client's predicates, should result in increased therapist's rapport and social influence. This hypothesis was tested in an actual interview situation. Six relatively inexperienced therapists, two each in predicate matching, predicate mismatching, and predicate no-matching conditions, conducted a 30-min. interview with nine undergraduate student volunteers each, for a total of 54 subjects. After the appropriate interview condition was completed, subjects rated ther therapists on the Counselor Rating Form and the Counseling Evaluation Inventory. No significant differences among the three conditions on any of the measures were found. Results are compared with those of previous research on assessment and primary representational matching in analogue situations.

The application of natural language processing to augmentative and alternative communication.

Science.gov (United States)

Higginbotham, D Jeffery; Lesher, Gregory W; Moulton, Bryan J; Roark, Brian

2011-01-01

Significant progress has been made in the application of natural language processing (NLP) to augmentative and alternative communication (AAC), particularly in the areas of interface design and word prediction. This article will survey the current state-of-the-science of NLP in AAC and discuss its future applications for the development of next generation of AAC technology.

Using NLP meta, Milton, metaphor models, for improving the activity of the organization

Directory of Open Access Journals (Sweden)

Cornel Marian IOSIF

2010-12-01

Full Text Available The objective of this paper is the improving of the three methods from the neuro- linguistic programming – metaphor, Milton model and the meta-model, so by using this in daily activities by an organization to improve the activities witch, are performed and to have a more efficient allocation of the available resources.

Online constrained model-based reinforcement learning

CSIR Research Space (South Africa)

Van Niekerk, B

2017-08-01

Full Text Available Constrained Model-based Reinforcement Learning Benjamin van Niekerk School of Computer Science University of the Witwatersrand South Africa Andreas Damianou∗ Amazon.com Cambridge, UK Benjamin Rosman Council for Scientific and Industrial Research, and School... MULTIPLE SHOOTING Using direct multiple shooting (Bock and Plitt, 1984), problem (1) can be transformed into a structured non- linear program (NLP). First, the time horizon [t0, t0 + T ] is partitioned into N equal subintervals [tk, tk+1] for k = 0...

Analyze the optimal solutions of optimization problems by means of fractional gradient based system using VIM

Directory of Open Access Journals (Sweden)

Firat Evirgen

2016-04-01

Full Text Available In this paper, a class of Nonlinear Programming problem is modeled with gradient based system of fractional order differential equations in Caputo's sense. To see the overlap between the equilibrium point of the fractional order dynamic system and theoptimal solution of the NLP problem in a longer timespan the Multistage Variational İteration Method isapplied. The comparisons among the multistage variational iteration method, the variationaliteration method and the fourth order Runge-Kutta method in fractional and integer order showthat fractional order model and techniques can be seen as an effective and reliable tool for finding optimal solutions of Nonlinear Programming problems.

The Islamic State Battle Plan: Press Release Natural Language Processing

Science.gov (United States)

2016-06-01

Institute for the Study of Violent Groups NATO North Atlantic Treaty Organization NLP Natural Language Processing PCorpus Permanent Corpus PDF...approaches, we apply Natural Language Processing ( NLP ) tools to a unique database of text documents collected by Whiteside (2014). His collection...from Arabic to English. Compared to other terrorism databases, Whiteside’s collection methodology limits the scope of the database and avoids coding

Planetary Pledge Pyramid, Facebook Application

DEFF Research Database (Denmark)

2009-01-01

Create an Advert X Alt skal væk NU Macbook Air solgt til 370,- kr. Acer Ferrari ONE 200 solgt til 374,- kr. på Ziinga.dk. - Klik her – Like Unlike You like this. X Mindstep | Useful Training® Interesseret i NLP og i at forbedre din bundlinie markant? Nyt NLP Business Practitioner hold i Århus, 19...

Mental Imagery as Revealed by Eye Movements and Spoken Predicates: A Test of Neurolinguistic Programming.

Science.gov (United States)

Elich, Matthew; And Others

1985-01-01

Tested Bandler and Grinder's proposal that eye movement direction and spoken predicates are indicative of sensory modality of imagery. Subjects reported images in the three modes, but no relation between imagery and eye movements or predicates was found. Visual images were most vivid and often reported. Most subjects rated themselves as visual,…

Contributions to the Functional Neuroanatomy of Morphosyntactic Processing in L2

Science.gov (United States)

De Diego-Balaguer, Ruth; Rodriguez-Fornells, Antoni

2010-01-01

Studies about bilingualism and second language acquisition (SLA) have a long tradition within linguistic and psycholinguistic research. The contributions from psycholinguistic research are crucial to the improvement of neurolinguistic models. This importance stems from the fact that psycholinguistic research is posing more specific questions than…

An annotated corpus with nanomedicine and pharmacokinetic parameters.

Science.gov (United States)

Lewinski, Nastassja A; Jimenez, Ivan; McInnes, Bridget T

2017-01-01

A vast amount of data on nanomedicines is being generated and published, and natural language processing (NLP) approaches can automate the extraction of unstructured text-based data. Annotated corpora are a key resource for NLP and information extraction methods which employ machine learning. Although corpora are available for pharmaceuticals, resources for nanomedicines and nanotechnology are still limited. To foster nanotechnology text mining (NanoNLP) efforts, we have constructed a corpus of annotated drug product inserts taken from the US Food and Drug Administration's Drugs@FDA online database. In this work, we present the development of the Engineered Nanomedicine Database corpus to support the evaluation of nanomedicine entity extraction. The data were manually annotated for 21 entity mentions consisting of nanomedicine physicochemical characterization, exposure, and biologic response information of 41 Food and Drug Administration-approved nanomedicines. We evaluate the reliability of the manual annotations and demonstrate the use of the corpus by evaluating two state-of-the-art named entity extraction systems, OpenNLP and Stanford NER. The annotated corpus is available open source and, based on these results, guidelines and suggestions for future development of additional nanomedicine corpora are provided.

Enhancing Comparative Effectiveness Research With Automated Pediatric Pneumonia Detection in a Multi-Institutional Clinical Repository: A PHIS+ Pilot Study.

Science.gov (United States)

Meystre, Stephane; Gouripeddi, Ramkiran; Tieder, Joel; Simmons, Jeffrey; Srivastava, Rajendu; Shah, Samir

2017-05-15

Community-acquired pneumonia is a leading cause of pediatric morbidity. Administrative data are often used to conduct comparative effectiveness research (CER) with sufficient sample sizes to enhance detection of important outcomes. However, such studies are prone to misclassification errors because of the variable accuracy of discharge diagnosis codes. The aim of this study was to develop an automated, scalable, and accurate method to determine the presence or absence of pneumonia in children using chest imaging reports. The multi-institutional PHIS+ clinical repository was developed to support pediatric CER by expanding an administrative database of children's hospitals with detailed clinical data. To develop a scalable approach to find patients with bacterial pneumonia more accurately, we developed a Natural Language Processing (NLP) application to extract relevant information from chest diagnostic imaging reports. Domain experts established a reference standard by manually annotating 282 reports to train and then test the NLP application. Findings of pleural effusion, pulmonary infiltrate, and pneumonia were automatically extracted from the reports and then used to automatically classify whether a report was consistent with bacterial pneumonia. Compared with the annotated diagnostic imaging reports reference standard, the most accurate implementation of machine learning algorithms in our NLP application allowed extracting relevant findings with a sensitivity of .939 and a positive predictive value of .925. It allowed classifying reports with a sensitivity of .71, a positive predictive value of .86, and a specificity of .962. When compared with each of the domain experts manually annotating these reports, the NLP application allowed for significantly higher sensitivity (.71 vs .527) and similar positive predictive value and specificity . NLP-based pneumonia information extraction of pediatric diagnostic imaging reports performed better than domain experts in this

NLP modeling for the optimization of LiBr-H_2O absorption refrigeration systems with exergy loss rate, heat transfer area, and cost as single objective functions

International Nuclear Information System (INIS)

Mussati, Sergio F.; Gernaey, Krist V.; Morosuk, Tatiana; Mussati, Miguel C.

2016-01-01

Highlights: • A NLP model is used for simultaneous optimization of sizes and operating conditions. • Total exergy loss rate and transfer area are optimized as single objective functions. • Theoretical and practical bounds for cost optimization problems are computed. • A systematic solution strategy is proposed for total annual cost optimization. • Relevance of components is ranked by heat transfer area, exergy loss rate, and cost. - Abstract: Based on a nonlinear mathematical programming model, the sizes and operating conditions of the process units of single-effect absorption refrigeration systems operating with a LiBr–H_2O solution are optimized for a specified cooling capacity by minimizing three single objective functions: the total exergy loss rate, the total heat transfer area, and the total annual cost of the system. It was found that the optimal solution obtained by minimization of the total exergy loss rate provides “theoretical” upper bounds not only for the total heat transfer area of the system but also for each process unit and all stream temperatures, while the optimal solution obtained by minimization of the total heat transfer area provides the lower bounds for these model variables, to solve a cost optimization problem. The minimization of the total exergy loss rate by varying parametrically the available total heat transfer area between these bounds was also performed, allowing to see how the optimal distribution of the available total heat transfer area among the system components, as well as the operating conditions (stream temperature, pressure, composition, and mass flow rate) and heat loads, vary qualitatively and quantitatively with increasing available total heat transfer area. These optimization results allowed to find a “practical” value of the total heat transfer area, i.e. no benefits can be obtained by increasing the available total heat transfer area above this value since the minimal total exergy loss value cannot

Neurology of foreign language aptitude

Directory of Open Access Journals (Sweden)

Adriana Biedroń

2015-01-01

Full Text Available This state-of-the art paper focuses on the poorly explored issue of foreign language aptitude, attempting to present the latest developments in this field and reconceptualizations of the construct from the perspective of neuroscience. In accordance with this goal, it first discusses general directions in neurolinguistic research on foreign language aptitude, starting with the earliest attempts to define the neurological substrate for talent, sources of difficulties in the neurolinguistic research on foreign language aptitude and modern research methods. This is followed by the discussion of the research on the phonology of foreign language aptitude with emphasis on functional and structural studies as well as their consequences for the knowledge of the concept. The subsequent section presents the studies which focus on lexical and morphosyntactic aspects of foreign language aptitude. The paper ends with a discussion of the limitations of contemporary research, the future directions of such research and selec ed methodological issues.

Causal knowledge extraction by natural language processing in material science: a case study in chemical vapor deposition

Directory of Open Access Journals (Sweden)

Yuya Kajikawa

2006-11-01

Full Text Available Scientific publications written in natural language still play a central role as our knowledge source. However, due to the flood of publications, the literature survey process has become a highly time-consuming and tangled process, especially for novices of the discipline. Therefore, tools supporting the literature-survey process may help the individual scientist to explore new useful domains. Natural language processing (NLP is expected as one of the promising techniques to retrieve, abstract, and extract knowledge. In this contribution, NLP is firstly applied to the literature of chemical vapor deposition (CVD, which is a sub-discipline of materials science and is a complex and interdisciplinary field of research involving chemists, physicists, engineers, and materials scientists. Causal knowledge extraction from the literature is demonstrated using NLP.

Die meting van neurolinguistiese programmering se verteenwoordigende stelsels: 'n Eksploratiewe studie

Directory of Open Access Journals (Sweden)

P. C. Bester

2000-06-01

Opsomming 'n Oorsig van die Sielkunde-literatuur wys daarop dat verskeie outeurs saamstem oor die bestaan van Neurolinguistiese Programmering (NLP se verteenwoordigende stelsels. Tot onlangs toe is geen studie oor die bestaan van n omvattende meetinstrument vir NLP se verteenwoordigende stelsels in die literatuur gerapporteer nie. Die hoofdoel van die onderhawige studie was om vas te stel of dit wenslik is om NLP se verteenwoordigende stelsels met 'n omvattende normatiewe vraelys te meet. Drie konstrukte is voorveronderstel en 'n "Vraelys oor Sensoriese Modaliteite", bestaande uit 84 items, is gekonstrueer. Hierdie vraelys is afgeneem op studente (N=338 van drie verskillende tersiere instellings. hTweede faktorontleding op die 18 subtellings van n eerste faktorontleding, het twee faktore opgelewer wat nie die drie verteenwoordigende stelsels suiwer weergee nie. Die implikasies van hierdie bevindinge word bespreek.

Integrating UIMA annotators in a web-based text processing framework.

Science.gov (United States)

Chen, Xiang; Arnold, Corey W

2013-01-01

The Unstructured Information Management Architecture (UIMA) [1] framework is a growing platform for natural language processing (NLP) applications. However, such applications may be difficult for non-technical users deploy. This project presents a web-based framework that wraps UIMA-based annotator systems into a graphical user interface for researchers and clinicians, and a web service for developers. An annotator that extracts data elements from lung cancer radiology reports is presented to illustrate the use of the system. Annotation results from the web system can be exported to multiple formats for users to utilize in other aspects of their research and workflow. This project demonstrates the benefits of a lay-user interface for complex NLP applications. Efforts such as this can lead to increased interest and support for NLP work in the clinical domain.

Psycholinguistic and motor theories of apraxia of speech.

Science.gov (United States)

Ziegler, Wolfram

2002-11-01

This article sketches the relationships between modern conceptions of apraxia of speech (AOS) and current models of neuromotor and neurolinguistic disorders. The first section is devoted to neurophysiological perspectives of AOS, and its relation to dysarthrias and to limb apraxia is discussed. The second section introduces the logogen model and considers AOS in relation to supramodal aspects of aphasia. In the third section, AOS with the background of psycholinguistic models of spoken language production, including the Levelt model and connectionist models, is discussed. In the fourth section, the view of AOS as a disorder of speech motor programming is discussed against the background of theories from experimental psychology. The final section considers two models of speech motor control and their relation to AOS. The article discusses the strengths and weaknesses of these approaches.

Mathematical Modeling and Simulation of SWRO Process Based on Simultaneous Method

Directory of Open Access Journals (Sweden)

Aipeng Jiang

2014-01-01

Full Text Available Reverse osmosis (RO technique is one of the most efficient ways for seawater desalination to solve the shortage of freshwater. For prediction and analysis of the performance of seawater reverse osmosis (SWRO process, an accurate and detailed model based on the solution-diffusion and mass transfer theory is established. Since the accurate formulation of the model includes many differential equations and strong nonlinear equations (differential and algebraic equations, DAEs, to solve the problem efficiently, the simultaneous method through orthogonal collocation on finite elements and large scale solver were used to obtain the solutions. The model was fully discretized into NLP (nonlinear programming with large scale variables and equations, and then the NLP was solved by large scale solver of IPOPT. Validation of the formulated model and solution method is verified by case study on a SWRO plant. Then simulation and analysis are carried out to demonstrate the performance of reverse osmosis process; operational conditions such as feed pressure and feed flow rate as well as feed temperature are also analyzed. This work is of significant meaning for the detailed understanding of RO process and future energy saving through operational optimization.

Volume I: Select Papers

Science.gov (United States)

2010-08-01

Abstract A domain-specific term base may be useful not only as a resource for written and oral translation, but also for Natural Language Processing ( NLP ...Processing ( NLP ) applications, text retrieval (1), document indexing, and other knowledge management tasks. The National Virtual Translation Center (NVTC...8953 terms with their translations was published by M. Green for the NVTC, under the title Iraqi Military English- Arabic Arabic -English Dictionary

Instance-Based Question Answering

Science.gov (United States)

2006-12-01

cluster-based query expan- sion, learning answering strategies, machine learning in NLP To my wife Monica Abstract During recent years, question...process is typically tedious and involves expertise in crafting and implement- ing these models (e.g. rule-based), utilizing NLP resources, and...questions. For languages that use capitalization (e.g. not Chinese or Arabic ) for named entities, IBQA can make use of NE classing (e.g. “Bob Marley

Quick Pad Tagger : An Efficient Graphical User Interface for Building Annotated Corpora with Multiple Annotation Layers

OpenAIRE

Marc Schreiber; Kai Barkschat; Bodo Kraft; Albert Zundorf

2015-01-01

More and more domain specific applications in the internet make use of Natural Language Processing (NLP) tools (e. g. Information Extraction systems). The output quality of these applications relies on the output quality of the used NLP tools. Often, the quality can be increased by annotating a domain specific corpus. However, annotating a corpus is a time consuming and exhaustive task. To reduce the annota tion time we present...

Using natural language processing and machine learning to identify gout flares from electronic clinical notes.

Science.gov (United States)

Zheng, Chengyi; Rashid, Nazia; Wu, Yi-Lin; Koblick, River; Lin, Antony T; Levy, Gerald D; Cheetham, T Craig

2014-11-01

Gout flares are not well documented by diagnosis codes, making it difficult to conduct accurate database studies. We implemented a computer-based method to automatically identify gout flares using natural language processing (NLP) and machine learning (ML) from electronic clinical notes. Of 16,519 patients, 1,264 and 1,192 clinical notes from 2 separate sets of 100 patients were selected as the training and evaluation data sets, respectively, which were reviewed by rheumatologists. We created separate NLP searches to capture different aspects of gout flares. For each note, the NLP search outputs became the ML system inputs, which provided the final classification decisions. The note-level classifications were grouped into patient-level gout flares. Our NLP+ML results were validated using a gold standard data set and compared with the claims-based method used by prior literatures. For 16,519 patients with a diagnosis of gout and a prescription for a urate-lowering therapy, we identified 18,869 clinical notes as gout flare positive (sensitivity 82.1%, specificity 91.5%): 1,402 patients with ≥3 flares (sensitivity 93.5%, specificity 84.6%), 5,954 with 1 or 2 flares, and 9,163 with no flare (sensitivity 98.5%, specificity 96.4%). Our method identified more flare cases (18,869 versus 7,861) and patients with ≥3 flares (1,402 versus 516) when compared to the claims-based method. We developed a computer-based method (NLP and ML) to identify gout flares from the clinical notes. Our method was validated as an accurate tool for identifying gout flares with higher sensitivity and specificity compared to previous studies. Copyright © 2014 by the American College of Rheumatology.

Benchmarking of the 2010 BioCreative Challenge III text-mining competition by the BioGRID and MINT interaction databases

Directory of Open Access Journals (Sweden)

Cesareni Gianni

2011-10-01

Full Text Available Abstract Background The vast amount of data published in the primary biomedical literature represents a challenge for the automated extraction and codification of individual data elements. Biological databases that rely solely on manual extraction by expert curators are unable to comprehensively annotate the information dispersed across the entire biomedical literature. The development of efficient tools based on natural language processing (NLP systems is essential for the selection of relevant publications, identification of data attributes and partially automated annotation. One of the tasks of the Biocreative 2010 Challenge III was devoted to the evaluation of NLP systems developed to identify articles for curation and extraction of protein-protein interaction (PPI data. Results The Biocreative 2010 competition addressed three tasks: gene normalization, article classification and interaction method identification. The BioGRID and MINT protein interaction databases both participated in the generation of the test publication set for gene normalization, annotated the development and test sets for article classification, and curated the test set for interaction method classification. These test datasets served as a gold standard for the evaluation of data extraction algorithms. Conclusion The development of efficient tools for extraction of PPI data is a necessary step to achieve full curation of the biomedical literature. NLP systems can in the first instance facilitate expert curation by refining the list of candidate publications that contain PPI data; more ambitiously, NLP approaches may be able to directly extract relevant information from full-text articles for rapid inspection by expert curators. Close collaboration between biological databases and NLP systems developers will continue to facilitate the long-term objectives of both disciplines.

NONLINEAR MODEL PREDICTIVE CONTROL OF CHEMICAL PROCESSES

Directory of Open Access Journals (Sweden)

SILVA R. G.

1999-01-01

Full Text Available A new algorithm for model predictive control is presented. The algorithm utilizes a simultaneous solution and optimization strategy to solve the model's differential equations. The equations are discretized by equidistant collocation, and along with the algebraic model equations are included as constraints in a nonlinear programming (NLP problem. This algorithm is compared with the algorithm that uses orthogonal collocation on finite elements. The equidistant collocation algorithm results in simpler equations, providing a decrease in computation time for the control moves. Simulation results are presented and show a satisfactory performance of this algorithm.

Multiphase Return Trajectory Optimization Based on Hybrid Algorithm

Directory of Open Access Journals (Sweden)

Yi Yang

2016-01-01

Full Text Available A hybrid trajectory optimization method consisting of Gauss pseudospectral method (GPM and natural computation algorithm has been developed and utilized to solve multiphase return trajectory optimization problem, where a phase is defined as a subinterval in which the right-hand side of the differential equation is continuous. GPM converts the optimal control problem to a nonlinear programming problem (NLP, which helps to improve calculation accuracy and speed of natural computation algorithm. Through numerical simulations, it is found that the multiphase optimal control problem could be solved perfectly.

GATECloud.net: a platform for large-scale, open-source text processing on the cloud.

Science.gov (United States)

Tablan, Valentin; Roberts, Ian; Cunningham, Hamish; Bontcheva, Kalina

2013-01-28

Cloud computing is increasingly being regarded as a key enabler of the 'democratization of science', because on-demand, highly scalable cloud computing facilities enable researchers anywhere to carry out data-intensive experiments. In the context of natural language processing (NLP), algorithms tend to be complex, which makes their parallelization and deployment on cloud platforms a non-trivial task. This study presents a new, unique, cloud-based platform for large-scale NLP research--GATECloud. net. It enables researchers to carry out data-intensive NLP experiments by harnessing the vast, on-demand compute power of the Amazon cloud. Important infrastructural issues are dealt with by the platform, completely transparently for the researcher: load balancing, efficient data upload and storage, deployment on the virtual machines, security and fault tolerance. We also include a cost-benefit analysis and usage evaluation.

Using NLP Reframing, Metaprograme Methods for Improving the Activity of the Organization

Directory of Open Access Journals (Sweden)

Iosif Cornel Marian

2011-12-01

Full Text Available The new method by increasing the adaptation speed to a context, through a slight transformation of the contextual meaning of words and by the optimization of the phases in which the actual process of reframing provides a closer connection between the person and context, a better adaptation to the language contextual requirements, but also to reduce the steps in which the process of reframing is done, which is a higher efficiency of it and a lower consumption of resources. By improving the programs and filters that are serving to metaprograms, the environmental information will be obtained at a high quality, the redundancy will decrease, and the consumption of resources needed to perform the filtering of information will also be reduced.Keywords: optimization, efficient, reduce, improve, communication

A Human Mirror Neuron System for Language: Perspectives from Signed Languages of the Deaf

Science.gov (United States)

Knapp, Heather Patterson; Corina, David P.

2010-01-01

Language is proposed to have developed atop the human analog of the macaque mirror neuron system for action perception and production [Arbib M.A. 2005. From monkey-like action recognition to human language: An evolutionary framework for neurolinguistics (with commentaries and author's response). "Behavioral and Brain Sciences, 28", 105-167; Arbib…

Neurology of Foreign Language Aptitude

Science.gov (United States)

Biedron, Adriana

2015-01-01

This state-of-the art paper focuses on the poorly explored issue of foreign language aptitude, attempting to present the latest developments in this field and reconceptualizations of the construct from the perspective of neuroscience. In accordance with this goal, it first discusses general directions in neurolinguistic research on foreign…

An integrated architecture for shallow and deep processing

OpenAIRE

Crysmann, Berthold; Frank, Anette; Kiefer, Bernd; Müller, Stefan; Neumann, Günter; Piskorski, Jakub; Schäfer, Ulrich; Siegel, Melanie; Uszkoreit, Hans; Xu, Feiyu; Becker, Markus; Krieger, Hans-Ulrich

2011-01-01

We present an architecture for the integration of shallow and deep NLP components which is aimed at flexible combination of different language technologies for a range of practical current and future applications. In particular, we describe the integration of a high-level HPSG parsing system with different high-performance shallow components, ranging from named entity recognition to chunk parsing and shallow clause recognition. The NLP components enrich a representation of natural language te...

LDC Arabic Treebanks and Associated Corpora: Data Divisions Manual

OpenAIRE

Diab, Mona; Habash, Nizar; Rambow, Owen; Roth, Ryan

2013-01-01

The Linguistic Data Consortium (LDC) has developed hundreds of data corpora for natural language processing (NLP) research. Among these are a number of annotated treebank corpora for Arabic. Typically, these corpora consist of a single collection of annotated documents. NLP research, however, usually requires multiple data sets for the purposes of training models, developing techniques, and final evaluation. Therefore it becomes necessary to divide the corpora used into the required data sets...

Role-Play in Foreign Language Acquisition: A Causal-Comparative Study

Science.gov (United States)

Allen, Elena A.

2013-01-01

Foreign language educators have been striving to improve practices that support language teaching for adults for many years. Common knowledge insists that children are better language learners than adults. Creation of the new field of neurolinguistics at the end of the 20th century brought about new opportunities for both teachers of foreign…

Domain Adaptation of Translation Models for Multilingual Applications

Science.gov (United States)

2009-04-01

employed. In the past two years, domain adaptation for NLP tasks has become an active research area [3, 38, 25, 23]. New domain adaptation tasks have...and unlabeled data in the target domain and learn a mixture model to adapt from the source domain. Other NLP tasks where domain adaptation has been...evaluation forum, http://www.clef-campaign.org. [13] K. Darwish and D. Oard, CLIR experiments at maryland for TREC-2002: Evidence combination for arabic

DALILA: The Dialectal Arabic Linguistic Learning Assistant

OpenAIRE

Khalifa , Salam; Bouamor , Houda; Habash , Nizar

2016-01-01

International audience; Dialectal Arabic (DA) poses serious challenges for Natural Language Processing (NLP). The number and sophistication of tools and datasets in DA are very limited in comparison to Modern Standard Arabic (MSA) and other languages. MSA tools do not effectively model DA which makes the direct use of MSA NLP tools for handling dialects impractical. This is particularly a challenge for the creation of tools to support learning Arabic as a living language on the web, where aut...

Fístula arteriovenosa pós-nefrolitotripsia percutânea Arteriovenous fistula after percutaneous nephrolithotomy

Directory of Open Access Journals (Sweden)

Luis Alberto Batista Peres

2009-09-01

Full Text Available Fístula arteriovenosa (FAV é uma rara complicação pós-nefrolitotripsia percutânea (NLP. Apresentamos o caso de um paciente de 70 anos, sexo masculino, que apresentou sangramento maciço após NLP, tratado por angioembolização renal superseletiva com implante de stent. Após a embolização, houve resolução do sangramento. FAV é uma complicação incomum da NLP, que pode ser tratada com sucesso com angioembolização.Arteriovenous fistula (AVF is a rare complication of percutaneous nephrolithotomy (PNL. We report the case of a 70-year-old man, who had massive bleeding after PNL and underwent treatment with superselective renal angiographic embolization and stent implantation. Bleeding resolved after embolization. Arteriovenous fistula is an uncommon complication of PNL, which may be successfully treated with angiographic embolization.

Workshop on using natural language processing applications for enhancing clinical decision making: an executive summary.

Science.gov (United States)

Pai, Vinay M; Rodgers, Mary; Conroy, Richard; Luo, James; Zhou, Ruixia; Seto, Belinda

2014-02-01

In April 2012, the National Institutes of Health organized a two-day workshop entitled 'Natural Language Processing: State of the Art, Future Directions and Applications for Enhancing Clinical Decision-Making' (NLP-CDS). This report is a summary of the discussions during the second day of the workshop. Collectively, the workshop presenters and participants emphasized the need for unstructured clinical notes to be included in the decision making workflow and the need for individualized longitudinal data tracking. The workshop also discussed the need to: (1) combine evidence-based literature and patient records with machine-learning and prediction models; (2) provide trusted and reproducible clinical advice; (3) prioritize evidence and test results; and (4) engage healthcare professionals, caregivers, and patients. The overall consensus of the NLP-CDS workshop was that there are promising opportunities for NLP and CDS to deliver cognitive support for healthcare professionals, caregivers, and patients.

Harmonization and development of resources and tools for Italian natural language processing within the PARLI project

CERN Document Server

Bosco, Cristina; Delmonte, Rodolfo; Moschitti, Alessandro; Simi, Maria

2015-01-01

The papers collected in this volume are selected as a sample of the progress in Natural Language Processing (NLP) performed within the Italian NLP community and especially attested by the PARLI project. PARLI (Portale per l’Accesso alle Risorse in Lingua Italiana) is a project partially funded by the Ministero Italiano per l’Università e la Ricerca (PRIN 2008) from 2008 to 2012 for monitoring and fostering the harmonic growth and coordination of the activities of Italian NLP. It was proposed by various teams of researchers working in Italian universities and research institutions. According to the spirit of the PARLI project, most of the resources and tools created within the project and here described are freely distributed and they did not terminate their life at the end of the project itself, hoping they could be a key factor in future development of computational linguistics.

NOBLE - Flexible concept recognition for large-scale biomedical natural language processing.

Science.gov (United States)

Tseytlin, Eugene; Mitchell, Kevin; Legowski, Elizabeth; Corrigan, Julia; Chavan, Girish; Jacobson, Rebecca S

2016-01-14

Natural language processing (NLP) applications are increasingly important in biomedical data analysis, knowledge engineering, and decision support. Concept recognition is an important component task for NLP pipelines, and can be either general-purpose or domain-specific. We describe a novel, flexible, and general-purpose concept recognition component for NLP pipelines, and compare its speed and accuracy against five commonly used alternatives on both a biological and clinical corpus. NOBLE Coder implements a general algorithm for matching terms to concepts from an arbitrary vocabulary set. The system's matching options can be configured individually or in combination to yield specific system behavior for a variety of NLP tasks. The software is open source, freely available, and easily integrated into UIMA or GATE. We benchmarked speed and accuracy of the system against the CRAFT and ShARe corpora as reference standards and compared it to MMTx, MGrep, Concept Mapper, cTAKES Dictionary Lookup Annotator, and cTAKES Fast Dictionary Lookup Annotator. We describe key advantages of the NOBLE Coder system and associated tools, including its greedy algorithm, configurable matching strategies, and multiple terminology input formats. These features provide unique functionality when compared with existing alternatives, including state-of-the-art systems. On two benchmarking tasks, NOBLE's performance exceeded commonly used alternatives, performing almost as well as the most advanced systems. Error analysis revealed differences in error profiles among systems. NOBLE Coder is comparable to other widely used concept recognition systems in terms of accuracy and speed. Advantages of NOBLE Coder include its interactive terminology builder tool, ease of configuration, and adaptability to various domains and tasks. NOBLE provides a term-to-concept matching system suitable for general concept recognition in biomedical NLP pipelines.

New spectrophotometric/chemometric assisted methods for the simultaneous determination of imatinib, gemifloxacin, nalbuphine and naproxen in pharmaceutical formulations and human urine

Science.gov (United States)

Belal, F.; Ibrahim, F.; Sheribah, Z. A.; Alaa, H.

2018-06-01

In this paper, novel univariate and multivariate regression methods along with model-updating technique were developed and validated for the simultaneous determination of quaternary mixture of imatinib (IMB), gemifloxacin (GMI), nalbuphine (NLP) and naproxen (NAP). The univariate method is extended derivative ratio (EDR) which depends on measuring every drug in the quaternary mixture by using a ternary mixture of the other three drugs as divisor. Peak amplitudes were measured at 294 nm, 250 nm, 283 nm and 239 nm within linear concentration ranges of 4.0-17.0, 3.0-15.0, 4.0-80.0 and 1.0-6.0 μg mL-1 for IMB, GMI, NLP and NAB, respectively. Multivariate methods adopted are partial least squares (PLS) in original and derivative mode. These models were constructed for simultaneous determination of the studied drugs in the ranges of 4.0-8.0, 3.0-11.0, 10.0-18.0 and 1.0-3.0 μg mL-1 for IMB, GMI, NLP and NAB, respectively, by using eighteen mixtures as a calibration set and seven mixtures as a validation set. The root mean square error of predication (RMSEP) were 0.09 and 0.06 for IMB, 0.14 and 0.13 for GMI, 0.07 and 0.02 for NLP and 0.64 and 0.27 for NAP by PLS in original and derivative mode, respectively. Both models were successfully applied for analysis of IMB, GMI, NLP and NAP in their dosage forms. Updated PLS in derivative mode and EDR were applied for determination of the studied drugs in spiked human urine. The obtained results were statistically compared with those obtained by the reported methods giving a conclusion that there is no significant difference regarding accuracy and precision.

A simple and versatile system for the ATP-dependent assembly of chromatin.

Science.gov (United States)

Khuong, Mai T; Fei, Jia; Cruz-Becerra, Grisel; Kadonaga, James T

2017-11-24

Chromatin is the natural form of DNA in the eukaryotic nucleus and is the substrate for diverse biological phenomena. The functional analysis of these processes ideally would be carried out with nucleosomal templates that are assembled with customized core histones, DNA sequences, and chromosomal proteins. Here we report a simple, reliable, and versatile method for the ATP-dependent assembly of evenly spaced nucleosome arrays. This minimal chromatin assembly system comprises the Drosophila nucleoplasmin-like protein (dNLP) histone chaperone, the imitation switch (ISWI) ATP-driven motor protein, core histones, template DNA, and ATP. The dNLP and ISWI components were synthesized in bacteria, and each protein could be purified in a single step by affinity chromatography. We show that the dNLP-ISWI system can be used with different DNA sequences, linear or circular DNA, bulk genomic DNA, recombinant or native Drosophila core histones, native human histones, the linker histone H1, the non-histone chromosomal protein HMGN2, and the core histone variants H3.3 and H2A.V. The dNLP-ISWI system should be accessible to a wide range of researchers and enable the assembly of customized chromatin with specifically desired DNA sequences, core histones, and other chromosomal proteins. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

The missing link in the embodiment of syntax: prosody.

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Kreiner, Hamutal; Eviatar, Zohar

2014-10-01

Neurolinguistic theories are challenged by the amodal abstract representations assumed by linguists. Embodied linguistics offers a conceptualization of the relationship between linguistic representation, experience, and the brain. Findings correlating brain activation patterns with referential features of words (e.g., body parts), suggest that the mechanism underlying linguistic embodiment is an "action-perception simulation". This mechanism accounts for embodied representation of words, but is harder to adapt to syntactic abstractions. We suggest that prosody is the missing link. Prosody is a sensory-motor phenomenon that can evoke an "action-perception simulation" that underpins the syntax-experience-brain association. Our review discusses different embodiment models and then integrates psycholinguistic and neurocognitive studies into a new approach to linguistic embodiment. We propose a novel implementation of the syntax-experience-brain relationship via the mapping between the temporo-spectral aspects of speech prosody and temporo-spectral patterns of synchronized behavior of neural populations. We discuss the potential implications for psycho- and neuro-linguistic research. Copyright © 2014 Elsevier Inc. All rights reserved.

Natural language processing using online analytic processing for assessing recommendations in radiology reports.

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Dang, Pragya A; Kalra, Mannudeep K; Blake, Michael A; Schultz, Thomas J; Stout, Markus; Lemay, Paul R; Freshman, David J; Halpern, Elkan F; Dreyer, Keith J

2008-03-01

The study purpose was to describe the use of natural language processing (NLP) and online analytic processing (OLAP) for assessing patterns in recommendations in unstructured radiology reports on the basis of patient and imaging characteristics, such as age, gender, referring physicians, radiology subspecialty, modality, indications, diseases, and patient status (inpatient vs outpatient). A database of 4,279,179 radiology reports from a single tertiary health care center during a 10-year period (1995-2004) was created. The database includes reports of computed tomography, magnetic resonance imaging, fluoroscopy, nuclear medicine, ultrasound, radiography, mammography, angiography, special procedures, and unclassified imaging tests with patient demographics. A clinical data mining and analysis NLP program (Leximer, Nuance Inc, Burlington, Massachusetts) in conjunction with OLAP was used for classifying reports into those with recommendations (I(REC)) and without recommendations (N(REC)) for imaging and determining I(REC) rates for different patient age groups, gender, imaging modalities, indications, diseases, subspecialties, and referring physicians. In addition, temporal trends for I(REC) were also determined. There was a significant difference in the I(REC) rates in different age groups, varying between 4.8% (10-19 years) and 9.5% (>70 years) (P OLAP revealed considerable differences between recommendation trends for different imaging modalities and other patient and imaging characteristics.

Scholarly Information Extraction Is Going to Make a Quantum Leap with PubMed Central (PMC).

Science.gov (United States)

Matthies, Franz; Hahn, Udo

2017-01-01

With the increasing availability of complete full texts (journal articles), rather than their surrogates (titles, abstracts), as resources for text analytics, entirely new opportunities arise for information extraction and text mining from scholarly publications. Yet, we gathered evidence that a range of problems are encountered for full-text processing when biomedical text analytics simply reuse existing NLP pipelines which were developed on the basis of abstracts (rather than full texts). We conducted experiments with four different relation extraction engines all of which were top performers in previous BioNLP Event Extraction Challenges. We found that abstract-trained engines loose up to 6.6% F-score points when run on full-text data. Hence, the reuse of existing abstract-based NLP software in a full-text scenario is considered harmful because of heavy performance losses. Given the current lack of annotated full-text resources to train on, our study quantifies the price paid for this short cut.

Deep Neural Network-Based Chinese Semantic Role Labeling

Institute of Scientific and Technical Information of China (English)

ZHENG Xiaoqing; CHEN Jun; SHANG Guoqiang

2017-01-01

A recent trend in machine learning is to use deep architec-tures to discover multiple levels of features from data, which has achieved impressive results on various natural language processing (NLP) tasks. We propose a deep neural network-based solution to Chinese semantic role labeling (SRL) with its application on message analysis. The solution adopts a six-step strategy: text normalization, named entity recognition (NER), Chinese word segmentation and part-of-speech (POS) tagging, theme classification, SRL, and slot filling. For each step, a novel deep neural network - based model is designed and optimized, particularly for smart phone applications. Ex-periment results on all the NLP sub - tasks of the solution show that the proposed neural networks achieve state-of-the-art performance with the minimal computational cost. The speed advantage of deep neural networks makes them more competitive for large-scale applications or applications requir-ing real-time response, highlighting the potential of the pro-posed solution for practical NLP systems.

Natural language processing: state of the art and prospects for significant progress, a workshop sponsored by the National Library of Medicine.

Science.gov (United States)

Friedman, Carol; Rindflesch, Thomas C; Corn, Milton

2013-10-01

Natural language processing (NLP) is crucial for advancing healthcare because it is needed to transform relevant information locked in text into structured data that can be used by computer processes aimed at improving patient care and advancing medicine. In light of the importance of NLP to health, the National Library of Medicine (NLM) recently sponsored a workshop to review the state of the art in NLP focusing on text in English, both in biomedicine and in the general language domain. Specific goals of the NLM-sponsored workshop were to identify the current state of the art, grand challenges and specific roadblocks, and to identify effective use and best practices. This paper reports on the main outcomes of the workshop, including an overview of the state of the art, strategies for advancing the field, and obstacles that need to be addressed, resulting in recommendations for a research agenda intended to advance the field. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

Automated Extraction of Substance Use Information from Clinical Texts.

Science.gov (United States)

Wang, Yan; Chen, Elizabeth S; Pakhomov, Serguei; Arsoniadis, Elliot; Carter, Elizabeth W; Lindemann, Elizabeth; Sarkar, Indra Neil; Melton, Genevieve B

2015-01-01

Within clinical discourse, social history (SH) includes important information about substance use (alcohol, drug, and nicotine use) as key risk factors for disease, disability, and mortality. In this study, we developed and evaluated a natural language processing (NLP) system for automated detection of substance use statements and extraction of substance use attributes (e.g., temporal and status) based on Stanford Typed Dependencies. The developed NLP system leveraged linguistic resources and domain knowledge from a multi-site social history study, Propbank and the MiPACQ corpus. The system attained F-scores of 89.8, 84.6 and 89.4 respectively for alcohol, drug, and nicotine use statement detection, as well as average F-scores of 82.1, 90.3, 80.8, 88.7, 96.6, and 74.5 respectively for extraction of attributes. Our results suggest that NLP systems can achieve good performance when augmented with linguistic resources and domain knowledge when applied to a wide breadth of substance use free text clinical notes.

A study of the transferability of influenza case detection systems between two large healthcare systems.

Science.gov (United States)

Ye, Ye; Wagner, Michael M; Cooper, Gregory F; Ferraro, Jeffrey P; Su, Howard; Gesteland, Per H; Haug, Peter J; Millett, Nicholas E; Aronis, John M; Nowalk, Andrew J; Ruiz, Victor M; López Pineda, Arturo; Shi, Lingyun; Van Bree, Rudy; Ginter, Thomas; Tsui, Fuchiang

2017-01-01

This study evaluates the accuracy and transferability of Bayesian case detection systems (BCD) that use clinical notes from emergency department (ED) to detect influenza cases. A BCD uses natural language processing (NLP) to infer the presence or absence of clinical findings from ED notes, which are fed into a Bayesain network classifier (BN) to infer patients' diagnoses. We developed BCDs at the University of Pittsburgh Medical Center (BCDUPMC) and Intermountain Healthcare in Utah (BCDIH). At each site, we manually built a rule-based NLP and trained a Bayesain network classifier from over 40,000 ED encounters between Jan. 2008 and May. 2010 using feature selection, machine learning, and expert debiasing approach. Transferability of a BCD in this study may be impacted by seven factors: development (source) institution, development parser, application (target) institution, application parser, NLP transfer, BN transfer, and classification task. We employed an ANOVA analysis to study their impacts on BCD performance. Both BCDs discriminated well between influenza and non-influenza on local test cases (AUCs > 0.92). When tested for transferability using the other institution's cases, BCDUPMC discriminations declined minimally (AUC decreased from 0.95 to 0.94, pdetection performance in two large healthcare systems in two geographically separated regions, providing evidentiary support for the use of automated case detection from routinely collected electronic clinical notes in national influenza surveillance. The transferability could be improved by training Bayesian network classifier locally and increasing the accuracy of the NLP parser.

Exploring subdomain variation in biomedical language

Directory of Open Access Journals (Sweden)

Séaghdha Diarmuid Ó

2011-05-01

Full Text Available Abstract Background Applications of Natural Language Processing (NLP technology to biomedical texts have generated significant interest in recent years. In this paper we identify and investigate the phenomenon of linguistic subdomain variation within the biomedical domain, i.e., the extent to which different subject areas of biomedicine are characterised by different linguistic behaviour. While variation at a coarser domain level such as between newswire and biomedical text is well-studied and known to affect the portability of NLP systems, we are the first to conduct an extensive investigation into more fine-grained levels of variation. Results Using the large OpenPMC text corpus, which spans the many subdomains of biomedicine, we investigate variation across a number of lexical, syntactic, semantic and discourse-related dimensions. These dimensions are chosen for their relevance to the performance of NLP systems. We use clustering techniques to analyse commonalities and distinctions among the subdomains. Conclusions We find that while patterns of inter-subdomain variation differ somewhat from one feature set to another, robust clusters can be identified that correspond to intuitive distinctions such as that between clinical and laboratory subjects. In particular, subdomains relating to genetics and molecular biology, which are the most common sources of material for training and evaluating biomedical NLP tools, are not representative of all biomedical subdomains. We conclude that an awareness of subdomain variation is important when considering the practical use of language processing applications by biomedical researchers.

An annotated corpus with nanomedicine and pharmacokinetic parameters

Directory of Open Access Journals (Sweden)

Lewinski NA

2017-10-01

Full Text Available Nastassja A Lewinski,1 Ivan Jimenez,1 Bridget T McInnes2 1Department of Chemical and Life Science Engineering, Virginia Commonwealth University, Richmond, VA, 2Department of Computer Science, Virginia Commonwealth University, Richmond, VA, USA Abstract: A vast amount of data on nanomedicines is being generated and published, and natural language processing (NLP approaches can automate the extraction of unstructured text-based data. Annotated corpora are a key resource for NLP and information extraction methods which employ machine learning. Although corpora are available for pharmaceuticals, resources for nanomedicines and nanotechnology are still limited. To foster nanotechnology text mining (NanoNLP efforts, we have constructed a corpus of annotated drug product inserts taken from the US Food and Drug Administration’s Drugs@FDA online database. In this work, we present the development of the Engineered Nanomedicine Database corpus to support the evaluation of nanomedicine entity extraction. The data were manually annotated for 21 entity mentions consisting of nanomedicine physicochemical characterization, exposure, and biologic response information of 41 Food and Drug Administration-approved nanomedicines. We evaluate the reliability of the manual annotations and demonstrate the use of the corpus by evaluating two state-of-the-art named entity extraction systems, OpenNLP and Stanford NER. The annotated corpus is available open source and, based on these results, guidelines and suggestions for future development of additional nanomedicine corpora are provided. Keywords: nanotechnology, informatics, natural language processing, text mining, corpora

Engineering the growth pattern and cell morphology for enhanced PHB production by Escherichia coli.

Science.gov (United States)

Wu, Hong; Chen, Jinchun; Chen, Guo-Qiang

2016-12-01

E. coli JM109∆envC∆nlpD deleted with genes envC and nlpD responsible for degrading peptidoglycan (PG) led to long filamentous cell shapes. When cell fission ring location genes minC and minD of Escherichia coli were deleted, E. coli JM109∆minCD changed the cell growth pattern from binary division to multiple fissions. Bacterial morphology can be further engineered by overexpressing sulA gene resulting in inhibition on FtsZ, thus generating very long cellular filaments. By overexpressing sulA in E. coli JM109∆envC∆nlpD and E. coli JM109∆minCD harboring poly(3-hydroxybutyrate) (PHB) synthesis operon phbCAB encoded in plasmid pBHR68, respectively, both engineered cells became long filaments and accumulated more PHB compared with the wild-type. Under same shake flask growth conditions, E. coli JM109∆minCD (pBHR68) overexpressing sulA grown in multiple fission pattern accumulated approximately 70 % PHB in 9 g/L cell dry mass (CDM), which was significantly higher than E. coli JM109∆envC∆nlpD and the wild type, that produced 7.6 g/L and 8 g/L CDM containing 64 % and 51 % PHB, respectively. Results demonstrated that a combination of the new division pattern with elongated shape of E. coli improved PHB production. This provided a new vision on the enhanced production of inclusion bodies.

PSYCHOLOGICAL AND PEDAGOGICAL BASES FOR THE CREATION OF AN AUTOMATED SYSTEM FOR THE DIAGNOSIS OF LEVELS OF PERCEPTION CHANNELS DEVELOPMENT (PERCEPTION.GUIDE

Directory of Open Access Journals (Sweden)

Petro P. Vorobiyenko

2017-12-01

Full Text Available The article describes the results of research on the process of human perception of information, the definitions of the main channels of perception of the external world, and the diagnoses of the prevailing channel. The experience and practical achievements of scientists are analyzed in the context of psychology, pedagogy, socionics, neurolinguistic programming. Certain methods for diagnosing the dominant channel of human perception of information using electronic resources and software complexes are considered. An extended model of the process of human information perception is presented based on the three-element classification of personality types: visual, audial, kinesthetic. The main stages of the creation of an automated "perception.guide" system for diagnosing the leading channel of information perception with the purpose of choosing the most effective teaching methods using information and communication technologies are revealed. The advantages of using the system for educational purposes are determined.

On the Possibility of ESP Data Use in Natural Language Processing

OpenAIRE

Knopp, Tomáš

2011-01-01

The aim of this bachelor thesis is to explore this image label database coming from the ESP game from the natural language processing (NLP) point of view. ESP game is an online game, in which human players do useful work - they label images. The output of the ESP game is then a database of images and their labels. What interests us is whether the data collected in the process of labeling images will be of any use in NLP tasks. Specifically, we are interested in the tasks of automatic corefere...

Recognizing textual entailment models and applications

CERN Document Server

Dagan, Ido; Sammons, Mark

2013-01-01

In the last few years, a number of NLP researchers have developed and participated in the task of Recognizing Textual Entailment (RTE). This task encapsulates Natural Language Understanding capabilities within a very simple interface: recognizing when the meaning of a text snippet is contained in the meaning of a second piece of text. This simple abstraction of an exceedingly complex problem has broad appeal partly because it can be conceived also as a component in other NLP applications, from Machine Translation to Semantic Search to Information Extraction. It also avoids commitment to any sp

Bullying in Virtual Learning Communities.

Science.gov (United States)

Nikiforos, Stefanos; Tzanavaris, Spyros; Kermanidis, Katia Lida

2017-01-01

Bullying through the internet has been investigated and analyzed mainly in the field of social media. In this paper, it is attempted to analyze bullying in the Virtual Learning Communities using Natural Language Processing (NLP) techniques, mainly in the context of sociocultural learning theories. Therefore four case studies took place. We aim to apply NLP techniques to speech analysis on communication data of online communities. Emphasis is given on qualitative data, taking into account the subjectivity of the collaborative activity. Finally, this is the first time such type of analysis is attempted on Greek data.

Nanolipoprotein Particles (NLPs) as Versatile Vaccine Platforms for Co-delivery of Multiple Adjuvants with Subunit Antigens from Burkholderia spp. and F. tularensis - Technical Report

Energy Technology Data Exchange (ETDEWEB)

Fischer, N. O. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2015-01-06

The goal of this proposal is to demonstrate that colocalization of protein subunit antigens and adjuvants on nanolipoprotein particles (NLPs) can increase the protective efficacy of subunit antigens from Burkholderia spp. and Francisella tularensis against an aerosol challenge. In the second quarter of the third year, LLNL finalized all immunological assessments of NLP vaccine formulations in the F344 model. Battelle has immunized rats with three unique NLP formulations by either intramuscular or intranasal administration. All inoculations have been completed, and protective efficacy against an aerosolized challenge will begin at the end of October, 2014.

Identification of Long Bone Fractures in Radiology Reports Using Natural Language Processing to support Healthcare Quality Improvement.

Science.gov (United States)

Grundmeier, Robert W; Masino, Aaron J; Casper, T Charles; Dean, Jonathan M; Bell, Jamie; Enriquez, Rene; Deakyne, Sara; Chamberlain, James M; Alpern, Elizabeth R

2016-11-09

Important information to support healthcare quality improvement is often recorded in free text documents such as radiology reports. Natural language processing (NLP) methods may help extract this information, but these methods have rarely been applied outside the research laboratories where they were developed. To implement and validate NLP tools to identify long bone fractures for pediatric emergency medicine quality improvement. Using freely available statistical software packages, we implemented NLP methods to identify long bone fractures from radiology reports. A sample of 1,000 radiology reports was used to construct three candidate classification models. A test set of 500 reports was used to validate the model performance. Blinded manual review of radiology reports by two independent physicians provided the reference standard. Each radiology report was segmented and word stem and bigram features were constructed. Common English "stop words" and rare features were excluded. We used 10-fold cross-validation to select optimal configuration parameters for each model. Accuracy, recall, precision and the F1 score were calculated. The final model was compared to the use of diagnosis codes for the identification of patients with long bone fractures. There were 329 unique word stems and 344 bigrams in the training documents. A support vector machine classifier with Gaussian kernel performed best on the test set with accuracy=0.958, recall=0.969, precision=0.940, and F1 score=0.954. Optimal parameters for this model were cost=4 and gamma=0.005. The three classification models that we tested all performed better than diagnosis codes in terms of accuracy, precision, and F1 score (diagnosis code accuracy=0.932, recall=0.960, precision=0.896, and F1 score=0.927). NLP methods using a corpus of 1,000 training documents accurately identified acute long bone fractures from radiology reports. Strategic use of straightforward NLP methods, implemented with freely available

Enhancing clinical communication in dermatologists: a personalized educational intervention.

Science.gov (United States)

Tsimtsiou, Zoi; Stavropoulou, Charitini; Papastefanou, Noni; Lionis, Christos

2017-11-01

Effective communication is a vital component of patient-centered consultations with favorable treatment outcomes. This study aimed in testing the effectiveness of a personalized, communication training program for dermatologists in their practices. Fifteen dermatologists were offered the educational intervention NO.TE.S. (Non-Technical Skills). Depending on the dermatologists' needs, seven to nine sessions with a 60-min duration were performed, focusing on: patient-centered care, principles of Neurolinguistic Programming, a guide to the medical interview, principles of motivational interviewing and self-care. After the program's completion, participants completed anonymously an 18-item evaluation questionnaire. All 14 participants would suggest NO.TE.S to a colleague. According to the main themes identified, their participation led to (i) re-consideration of the physician-patient relationship, (ii) more conscious application of the patient-centered model, (iii) improvement in communication skills, (iv) awareness of medical interview guides, (v) increase in self-confidence, and (vi) techniques of self-care. Eleven physicians (78.6%) declared improvement in patients' satisfaction, 14 (100%) in their own satisfaction, seven (50%) in adherence to therapeutic plan and seven (50%) in treatment outcomes. The one-to-one coaching is a convenient and well-received personalized means of enhancing clinical communication in dermatologists, leading to more patient-centered medical encounters with better treatment outcomes.

Determination of the Cascade Reservoir Operation for Optimal Firm-Energy Using Genetic Algorithms

Directory of Open Access Journals (Sweden)

Azmeri

2013-08-01

Full Text Available Indonesia today face a new paradigm in water management where aim to apply integrated water resources management has become unavoidable task in purpose of achieving greater level of effectiveness and efficiency. On of most interesting case study is the case of Citarum river, one of the most potential river for water supply in West Java, Indonesia. Alongside the river, Saguling, Cirata and Djuanda Reservoirs had been constructed in series/cascade. Saguling and Cirata reservoirs are particularly operated for hydroelectric power and Djuanda is multipurpose reservoir mainly operated for irrigation and contribute domestic water supply for Jakarta (capital city of Indonesia. Basically all reservoirs are relying on same resources, therefore this condition has considered addressing management and operational problem. Therefore, an approach toward new management and operation system are urgently required in order to achieve the effective and efficient output and to avoid conflicts of water used. This study aims to obtain energy production from Citarum Cascade Reservoir System using Genetic Algorithms optimization with the objective function to maximize firm-energy. Firm-energy is the minimum energy requirements must be available in a certain time period. Then, the result obtained by using the energy produced by GA is compared to the conventional searching technique of Non-Linier Programming (NLP. The GA derived operating curves reveal the higher energy and firm-energy than NLP model

Automatic Lung-RADS™ classification with a natural language processing system.

Science.gov (United States)

Beyer, Sebastian E; McKee, Brady J; Regis, Shawn M; McKee, Andrea B; Flacke, Sebastian; El Saadawi, Gilan; Wald, Christoph

2017-09-01

Our aim was to train a natural language processing (NLP) algorithm to capture imaging characteristics of lung nodules reported in a structured CT report and suggest the applicable Lung-RADS™ (LR) category. Our study included structured, clinical reports of consecutive CT lung screening (CTLS) exams performed from 08/2014 to 08/2015 at an ACR accredited Lung Cancer Screening Center. All patients screened were at high-risk for lung cancer according to the NCCN Guidelines ® . All exams were interpreted by one of three radiologists credentialed to read CTLS exams using LR using a standard reporting template. Training and test sets consisted of consecutive exams. Lung screening exams were divided into two groups: three training sets (500, 120, and 383 reports each) and one final evaluation set (498 reports). NLP algorithm results were compared with the gold standard of LR category assigned by the radiologist. The sensitivity/specificity of the NLP algorithm to correctly assign LR categories for suspicious nodules (LR 4) and positive nodules (LR 3/4) were 74.1%/98.6% and 75.0%/98.8% respectively. The majority of mismatches occurred in cases where pulmonary findings were present not currently addressed by LR. Misclassifications also resulted from the failure to identify exams as follow-up and the failure to completely characterize part-solid nodules. In a sub-group analysis among structured reports with standardized language, the sensitivity and specificity to detect LR 4 nodules were 87.0% and 99.5%, respectively. An NLP system can accurately suggest the appropriate LR category from CTLS exam findings when standardized reporting is used.

Building and using comparable corpora

CERN Document Server

Sharoff, Serge; Zweigenbaum, Pierre; Fung, Pascale

2013-01-01

The 1990s saw a paradigm change in the use of corpus-driven methods in NLP. In the field of multilingual NLP (such as machine translation and terminology mining) this implied the use of parallel corpora. However, parallel resources are relatively scarce: many more texts are produced daily by native speakers of any given language than translated. This situation resulted in a natural drive towards the use of comparable corpora, i.e. non-parallel texts in the same domain or genre. Nevertheless, this research direction has not produced a single authoritative source suitable for researchers and stu

An XML Approach of Coding a Morphological Database for Arabic Language

Directory of Open Access Journals (Sweden)

Mourad Gridach

2011-01-01

Full Text Available We present an XML approach for the production of an Arabic morphological database for Arabic language that will be used in morphological analysis for modern standard Arabic (MSA. Optimizing the production, maintenance, and extension of morphological database is one of the crucial aspects impacting natural language processing (NLP. For Arabic language, producing a morphological database is not an easy task, because this it has some particularities such as the phenomena of agglutination and a lot of morphological ambiguity phenomenon. The method presented can be exploited by NLP applications such as syntactic analysis, semantic analysis, information retrieval, and orthographical correction.

Linguistic fundamentals for natural language processing 100 essentials from morphology and syntax

CERN Document Server

Bender, Emily M

2013-01-01

Many NLP tasks have at their core a subtask of extracting the dependencies-who did what to whom-from natural language sentences. This task can be understood as the inverse of the problem solved in different ways by diverse human languages, namely, how to indicate the relationship between different parts of a sentence. Understanding how languages solve the problem can be extremely useful in both feature design and error analysis in the application of machine learning to NLP. Likewise, understanding cross-linguistic variation can be important for the design of MT systems and other multilingual a

Nematode Peptides with host-directed anti-inflammatory activity rescue Caenorhabditis elegans from a Burkholderia pseudomallei infection

Directory of Open Access Journals (Sweden)

Mei-Perng Lim

2016-09-01

Full Text Available Burkholderia pseudomallei, the causative agent of melioidosis, is among a growing number of bacterial pathogens that are increasingly antibiotic resistant. Antimicrobial peptides (AMPs have been investigated as an alternative approach to treat microbial infections, as generally, there is a lower likelihood that a pathogen will develop resistance to AMPs. In this study, 36 candidate Caenorhabditis elegans genes that encode secreted peptides of <150 amino acids and previously shown to be overexpressed during infection by B. pseudomallei were identified from the expression profile of infected nematodes. RNA interference (RNAi-based knockdown of 12/34 peptide-encoding genes resulted in enhanced nematode susceptibility to B. pseudomallei without affecting worm fitness. A microdilution test demonstrated that two peptides, NLP-31 and Y43C5A.3, exhibited anti-B. pseudomallei activity in a dose dependent manner on different pathogens. Time kill analysis proposed that these peptides were bacteriostatic against B. pseudomallei at concentrations up to 8× MIC90. The SYTOX green assay demonstrated that NLP-31 and Y43C5A.3 did not disrupt the B. pseudomallei membrane. Instead, gel retardation assays revealed that both peptides were able to bind to DNA and interfere with bacterial viability. In parallel, microscopic examination showed induction of cellular filamentation, a hallmark of DNA synthesis inhibition, of NLP-31 and Y43C5A.3 treated cells. In addition, the peptides also regulated the expression of inflammatory cytokines in B. pseudomallei infected macrophage cells. Collectively, these findings demonstrate the potential of NLP-31 and Y43C5A.3 as anti-B. pseudomallei peptides based on their function as immune modulators.

Afázie u dospělých a starších lidí

OpenAIRE

VALVODOVÁ, Olga

2015-01-01

The Bachelor thesis pay attention to the aphasia as a communication disorder. The thesis is divided into the theoretical and the practical part. In the theoretical part themes of the neurolinguistics, the speech, tha brain and the aphasia are analysed. The longest chapter focuses on causes of the aphasia, types of aphasia, the diagnosis and therapy of aphasia. The practical part includes single casuistry of three patients and the analysis.

An Introduction to Natural Language Processing: How You Can Get More From Those Electronic Notes You Are Generating.

Science.gov (United States)

Kimia, Amir A; Savova, Guergana; Landschaft, Assaf; Harper, Marvin B

2015-07-01

Electronically stored clinical documents may contain both structured data and unstructured data. The use of structured clinical data varies by facility, but clinicians are familiar with coded data such as International Classification of Diseases, Ninth Revision, Systematized Nomenclature of Medicine-Clinical Terms codes, and commonly other data including patient chief complaints or laboratory results. Most electronic health records have much more clinical information stored as unstructured data, for example, clinical narrative such as history of present illness, procedure notes, and clinical decision making are stored as unstructured data. Despite the importance of this information, electronic capture or retrieval of unstructured clinical data has been challenging. The field of natural language processing (NLP) is undergoing rapid development, and existing tools can be successfully used for quality improvement, research, healthcare coding, and even billing compliance. In this brief review, we provide examples of successful uses of NLP using emergency medicine physician visit notes for various projects and the challenges of retrieving specific data and finally present practical methods that can run on a standard personal computer as well as high-end state-of-the-art funded processes run by leading NLP informatics researchers.

Feature generation and representations for protein-protein interaction classification.

Science.gov (United States)

Lan, Man; Tan, Chew Lim; Su, Jian

2009-10-01

Automatic detecting protein-protein interaction (PPI) relevant articles is a crucial step for large-scale biological database curation. The previous work adopted POS tagging, shallow parsing and sentence splitting techniques, but they achieved worse performance than the simple bag-of-words representation. In this paper, we generated and investigated multiple types of feature representations in order to further improve the performance of PPI text classification task. Besides the traditional domain-independent bag-of-words approach and the term weighting methods, we also explored other domain-dependent features, i.e. protein-protein interaction trigger keywords, protein named entities and the advanced ways of incorporating Natural Language Processing (NLP) output. The integration of these multiple features has been evaluated on the BioCreAtIvE II corpus. The experimental results showed that both the advanced way of using NLP output and the integration of bag-of-words and NLP output improved the performance of text classification. Specifically, in comparison with the best performance achieved in the BioCreAtIvE II IAS, the feature-level and classifier-level integration of multiple features improved the performance of classification 2.71% and 3.95%, respectively.

Web 2.0-based crowdsourcing for high-quality gold standard development in clinical natural language processing.

Science.gov (United States)

Zhai, Haijun; Lingren, Todd; Deleger, Louise; Li, Qi; Kaiser, Megan; Stoutenborough, Laura; Solti, Imre

2013-04-02

A high-quality gold standard is vital for supervised, machine learning-based, clinical natural language processing (NLP) systems. In clinical NLP projects, expert annotators traditionally create the gold standard. However, traditional annotation is expensive and time-consuming. To reduce the cost of annotation, general NLP projects have turned to crowdsourcing based on Web 2.0 technology, which involves submitting smaller subtasks to a coordinated marketplace of workers on the Internet. Many studies have been conducted in the area of crowdsourcing, but only a few have focused on tasks in the general NLP field and only a handful in the biomedical domain, usually based upon very small pilot sample sizes. In addition, the quality of the crowdsourced biomedical NLP corpora were never exceptional when compared to traditionally-developed gold standards. The previously reported results on medical named entity annotation task showed a 0.68 F-measure based agreement between crowdsourced and traditionally-developed corpora. Building upon previous work from the general crowdsourcing research, this study investigated the usability of crowdsourcing in the clinical NLP domain with special emphasis on achieving high agreement between crowdsourced and traditionally-developed corpora. To build the gold standard for evaluating the crowdsourcing workers' performance, 1042 clinical trial announcements (CTAs) from the ClinicalTrials.gov website were randomly selected and double annotated for medication names, medication types, and linked attributes. For the experiments, we used CrowdFlower, an Amazon Mechanical Turk-based crowdsourcing platform. We calculated sensitivity, precision, and F-measure to evaluate the quality of the crowd's work and tested the statistical significance (Pcrowdsourced and traditionally-developed annotations. The agreement between the crowd's annotations and the traditionally-generated corpora was high for: (1) annotations (0.87, F-measure for medication names

solveME: fast and reliable solution of nonlinear ME models

DEFF Research Database (Denmark)

Yang, Laurence; Ma, Ding; Ebrahim, Ali

2016-01-01

Background: Genome-scale models of metabolism and macromolecular expression (ME) significantly expand the scope and predictive capabilities of constraint-based modeling. ME models present considerable computational challenges: they are much (>30 times) larger than corresponding metabolic reconstr......Background: Genome-scale models of metabolism and macromolecular expression (ME) significantly expand the scope and predictive capabilities of constraint-based modeling. ME models present considerable computational challenges: they are much (>30 times) larger than corresponding metabolic...... reconstructions (M models), are multiscale, and growth maximization is a nonlinear programming (NLP) problem, mainly due to macromolecule dilution constraints. Results: Here, we address these computational challenges. We develop a fast and numerically reliable solution method for growth maximization in ME models...

Nonlinear model predictive control of a wave energy converter based on differential flatness parameterisation

Science.gov (United States)

Li, Guang

2017-01-01

This paper presents a fast constrained optimization approach, which is tailored for nonlinear model predictive control of wave energy converters (WEC). The advantage of this approach relies on its exploitation of the differential flatness of the WEC model. This can reduce the dimension of the resulting nonlinear programming problem (NLP) derived from the continuous constrained optimal control of WEC using pseudospectral method. The alleviation of computational burden using this approach helps to promote an economic implementation of nonlinear model predictive control strategy for WEC control problems. The method is applicable to nonlinear WEC models, nonconvex objective functions and nonlinear constraints, which are commonly encountered in WEC control problems. Numerical simulations demonstrate the efficacy of this approach.

Die kortikale Verarbeitung semantischer Domänen : eine ERP-Studie

OpenAIRE

Wengenroth, Alexandra

2005-01-01

From a semantic point of view concrete nouns can be divided into different categories or domains such as living - non-living as well as into different lexical hierarchies (e.g. dog - beagle). Psycholinguistic and aphasiological case studies as well as neurophysiological investigations have shown that distinct semantic categories can be selectively damaged or show advantages in processing. However, these mental lexicon structures are still sketchy with regard to psycho- and neurolinguistics. I...

A study of the transferability of influenza case detection systems between two large healthcare systems.

Directory of Open Access Journals (Sweden)

Ye Ye

Full Text Available This study evaluates the accuracy and transferability of Bayesian case detection systems (BCD that use clinical notes from emergency department (ED to detect influenza cases.A BCD uses natural language processing (NLP to infer the presence or absence of clinical findings from ED notes, which are fed into a Bayesain network classifier (BN to infer patients' diagnoses. We developed BCDs at the University of Pittsburgh Medical Center (BCDUPMC and Intermountain Healthcare in Utah (BCDIH. At each site, we manually built a rule-based NLP and trained a Bayesain network classifier from over 40,000 ED encounters between Jan. 2008 and May. 2010 using feature selection, machine learning, and expert debiasing approach. Transferability of a BCD in this study may be impacted by seven factors: development (source institution, development parser, application (target institution, application parser, NLP transfer, BN transfer, and classification task. We employed an ANOVA analysis to study their impacts on BCD performance.Both BCDs discriminated well between influenza and non-influenza on local test cases (AUCs > 0.92. When tested for transferability using the other institution's cases, BCDUPMC discriminations declined minimally (AUC decreased from 0.95 to 0.94, p<0.01, and BCDIH discriminations declined more (from 0.93 to 0.87, p<0.0001. We attributed the BCDIH decline to the lower recall of the IH parser on UPMC notes. The ANOVA analysis showed five significant factors: development parser, application institution, application parser, BN transfer, and classification task.We demonstrated high influenza case detection performance in two large healthcare systems in two geographically separated regions, providing evidentiary support for the use of automated case detection from routinely collected electronic clinical notes in national influenza surveillance. The transferability could be improved by training Bayesian network classifier locally and increasing the

Performance of a Machine Learning Classifier of Knee MRI Reports in Two Large Academic Radiology Practices: A Tool to Estimate Diagnostic Yield.

Science.gov (United States)

Hassanpour, Saeed; Langlotz, Curtis P; Amrhein, Timothy J; Befera, Nicholas T; Lungren, Matthew P

2017-04-01

The purpose of this study is to evaluate the performance of a natural language processing (NLP) system in classifying a database of free-text knee MRI reports at two separate academic radiology practices. An NLP system that uses terms and patterns in manually classified narrative knee MRI reports was constructed. The NLP system was trained and tested on expert-classified knee MRI reports from two major health care organizations. Radiology reports were modeled in the training set as vectors, and a support vector machine framework was used to train the classifier. A separate test set from each organization was used to evaluate the performance of the system. We evaluated the performance of the system both within and across organizations. Standard evaluation metrics, such as accuracy, precision, recall, and F1 score (i.e., the weighted average of the precision and recall), and their respective 95% CIs were used to measure the efficacy of our classification system. The accuracy for radiology reports that belonged to the model's clinically significant concept classes after training data from the same institution was good, yielding an F1 score greater than 90% (95% CI, 84.6-97.3%). Performance of the classifier on cross-institutional application without institution-specific training data yielded F1 scores of 77.6% (95% CI, 69.5-85.7%) and 90.2% (95% CI, 84.5-95.9%) at the two organizations studied. The results show excellent accuracy by the NLP machine learning classifier in classifying free-text knee MRI reports, supporting the institution-independent reproducibility of knee MRI report classification. Furthermore, the machine learning classifier performed well on free-text knee MRI reports from another institution. These data support the feasibility of multiinstitutional classification of radiologic imaging text reports with a single machine learning classifier without requiring institution-specific training data.

Dictionaries of Mexican Sexual Slang for NLP

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Roberto Villarejo-Martínez

2018-04-01

Full Text Available Abstract: In this paper the creation of two relevant resources for the double entendre and humour recognition problem in Mexican Spanish is described: a morphological dictionary and a semantic dictionary. These were created from two sources: a corpus of albures (drawn from “Antología del albur” book and a Mexican slang dictionary (“El chilangonario”. The morphological dictionary consists of 410 forms of words that corresponds to 350 lemmas. The semantic dictionary consists of 27 synsets that are associated to lemmas of morphological dictionary. Since both resources are based on Freeling library, they are easy to implement for tasks in Natural Language Processing. The motivation for this work comes from the need to address problems such as double entendre and computational humour. The usefulness of these disciplines has been discussed many times and it has been shown that they have a direct impact on user interfaces and, mainly, in human-computer interaction. This work aims to promote that the scientific community generates more resources about informal language in Spanish and other languages.  Spanish Abstract: En este artículo se describe la creación de dos recursos relevantes para el reconocimiento del doble sentido y el humor en el español mexicano: un diccionario morfológico y un diccionario semántico. Éstos fueron creados a partir de dos fuentes: un corpus de albures (extraídos del libro "Antología del albur" y un diccionario de argot mexicano ("El chilangonario". El diccionario morfológico consiste en 410 formas de palabras que corresponden a 350 lemas. El diccionario semántico consiste en 27 synsets que están asociados a lemas del diccionario morfológico. Puesto que ambos recursos están basados en la biblioteca Freeling, son fáciles de implementar en tareas de Procesamiento del Lenguaje Natural. La motivación de este trabajo proviene de la necesidad de abordar problemas como el doble sentido y el humor computacional. La utilidad de estas disciplinas han sido discutidas muchas veces y se ha mostrado que tienen un impacto directo en las interfaces de usuario y, principalmente, en la interacción humano-computadora. Este trabajo tiene como objetivo promover que la comunidad científica genere más recursos sobre el lenguaje informal en español y otros lenguajes.

Creation of a simple natural language processing tool to support an imaging utilization quality dashboard.

Science.gov (United States)

Swartz, Jordan; Koziatek, Christian; Theobald, Jason; Smith, Silas; Iturrate, Eduardo

2017-05-01

Testing for venous thromboembolism (VTE) is associated with cost and risk to patients (e.g. radiation). To assess the appropriateness of imaging utilization at the provider level, it is important to know that provider's diagnostic yield (percentage of tests positive for the diagnostic entity of interest). However, determining diagnostic yield typically requires either time-consuming, manual review of radiology reports or the use of complex and/or proprietary natural language processing software. The objectives of this study were twofold: 1) to develop and implement a simple, user-configurable, and open-source natural language processing tool to classify radiology reports with high accuracy and 2) to use the results of the tool to design a provider-specific VTE imaging dashboard, consisting of both utilization rate and diagnostic yield. Two physicians reviewed a training set of 400 lower extremity ultrasound (UTZ) and computed tomography pulmonary angiogram (CTPA) reports to understand the language used in VTE-positive and VTE-negative reports. The insights from this review informed the arguments to the five modifiable parameters of the NLP tool. A validation set of 2,000 studies was then independently classified by the reviewers and by the tool; the classifications were compared and the performance of the tool was calculated. The tool was highly accurate in classifying the presence and absence of VTE for both the UTZ (sensitivity 95.7%; 95% CI 91.5-99.8, specificity 100%; 95% CI 100-100) and CTPA reports (sensitivity 97.1%; 95% CI 94.3-99.9, specificity 98.6%; 95% CI 97.8-99.4). The diagnostic yield was then calculated at the individual provider level and the imaging dashboard was created. We have created a novel NLP tool designed for users without a background in computer programming, which has been used to classify venous thromboembolism reports with a high degree of accuracy. The tool is open-source and available for download at http://iturrate.com/simpleNLP

Capturing and Modeling Domain Knowledge Using Natural Language Processing Techniques

National Research Council Canada - National Science Library

Auger, Alain

2005-01-01

.... Initiated in 2004 at Defense Research and Development Canada (DRDC), the SACOT knowledge engineering research project is currently investigating, developing and validating innovative natural language processing (NLP...

C. elegans Stress-Induced Sleep Emerges from the Collective Action of Multiple Neuropeptides.

Science.gov (United States)

Nath, Ravi D; Chow, Elly S; Wang, Han; Schwarz, Erich M; Sternberg, Paul W

2016-09-26

The genetic basis of sleep regulation remains poorly understood. In C. elegans, cellular stress induces sleep through epidermal growth factor (EGF)-dependent activation of the EGF receptor in the ALA neuron. The downstream mechanism by which this neuron promotes sleep is unknown. Single-cell RNA sequencing of ALA reveals that the most highly expressed, ALA-enriched genes encode neuropeptides. Here we have systematically investigated the four most highly enriched neuropeptides: flp-7, nlp-8, flp-24, and flp-13. When individually removed by null mutation, these peptides had little or no effect on stress-induced sleep. However, stress-induced sleep was abolished in nlp-8; flp-24; flp-13 triple-mutant animals, indicating that these neuropeptides work collectively in controlling stress-induced sleep. We tested the effect of overexpression of these neuropeptide genes on five behaviors modulated during sleep-pharyngeal pumping, defecation, locomotion, head movement, and avoidance response to an aversive stimulus-and we found that, if individually overexpressed, each of three neuropeptides (nlp-8, flp-24, or flp-13) induced a different suite of sleep-associated behaviors. These overexpression results raise the possibility that individual components of sleep might be specified by individual neuropeptides or combinations of neuropeptides. Copyright © 2016 Elsevier Ltd. All rights reserved.

A factorization approach to next-to-leading-power threshold logarithms

Energy Technology Data Exchange (ETDEWEB)

Bonocore, D. [Nikhef,Science Park 105, NL-1098 XG Amsterdam (Netherlands); Laenen, E. [Nikhef,Science Park 105, NL-1098 XG Amsterdam (Netherlands); ITFA, University of Amsterdam,Science Park 904, Amsterdam (Netherlands); ITF, Utrecht University,Leuvenlaan 4, Utrecht (Netherlands); Magnea, L. [Dipartimento di Fisica, Università di Torino and INFN, Sezione di Torino,Via P. Giuria 1, I-10125, Torino (Italy); Melville, S. [School of Physics and Astronomy, University of Glasgow,Glasgow, G12 8QQ (United Kingdom); Vernazza, L. [Higgs Centre for Theoretical Physics, School of Physics and Astronomy, University of Edinburgh,Edinburgh, EH9 3JZ, Scotland (United Kingdom); White, C.D. [School of Physics and Astronomy, University of Glasgow,Glasgow, G12 8QQ (United Kingdom)

2015-06-03

Threshold logarithms become dominant in partonic cross sections when the selected final state forces gluon radiation to be soft or collinear. Such radiation factorizes at the level of scattering amplitudes, and this leads to the resummation of threshold logarithms which appear at leading power in the threshold variable. In this paper, we consider the extension of this factorization to include effects suppressed by a single power of the threshold variable. Building upon the Low-Burnett-Kroll-Del Duca (LBKD) theorem, we propose a decomposition of radiative amplitudes into universal building blocks, which contain all effects ultimately responsible for next-to-leading-power (NLP) threshold logarithms in hadronic cross sections for electroweak annihilation processes. In particular, we provide a NLO evaluation of the radiative jet function, responsible for the interference of next-to-soft and collinear effects in these cross sections. As a test, using our expression for the amplitude, we reproduce all abelian-like NLP threshold logarithms in the NNLO Drell-Yan cross section, including the interplay of real and virtual emissions. Our results are a significant step towards developing a generally applicable resummation formalism for NLP threshold effects, and illustrate the breakdown of next-to-soft theorems for gauge theory amplitudes at loop level.

Characterization and Purification of Polydisperse Reconstituted Lipoproteins and Nanolipoprotein Particles

Directory of Open Access Journals (Sweden)

Paul D. Hoeprich

2009-07-01

Full Text Available Heterogeneity is a fact that plagues the characterization and application of many self-assembled biological constructs. The importance of obtaining particle homogeneity in biological assemblies is a critical goal, as bulk analysis tools often require identical species for reliable interpretation of the results—indeed, important tools of analysis such as x-ray diffraction typically require over 90% purity for effectiveness. This issue bears particular importance in the case of lipoproteins. Lipid-binding proteins known as apolipoproteins can self assemble with liposomes to form reconstituted high density lipoproteins (rHDLs or nanolipoprotein particles (NLPs when used for biotechnology applications such as the solubilization of membrane proteins. Typically, the apolipoprotein and phospholipids reactants are self assembled and even with careful assembly protocols the product often contains heterogeneous particles. In fact, size polydispersity in rHDLs and NLPs published in the literature are frequently observed, which may confound the accurate use of analytical methods. In this article, we demonstrate a procedure for producing a pure, monodisperse NLP subpopulation from a polydisperse self-assembly using size exclusion chromatography (SEC coupled with high resolution particle imaging by atomic force microscopy (AFM. In addition, NLPs have been shown to self assemble both in the presence and absence of detergents such as cholate, yet the effects of cholate on NLP polydispersity and separation has not been systematically examined. Therefore, we examined the separation properties of NLPs assembled in both the absence and presence of cholate using SEC and native gel electrophoresis. From this analysis, NLPs prepared with and without cholate showed particles with well defined diameters spanning a similar size range. However, cholate was shown to have a dramatic affect on NLP separation by SEC and native gel electrophoresis. Furthermore, under

Neuro-Linguistic Programming and Altered States: Encouraging Preparation for Learning in the Classroom for Students with Special Educational Needs

Science.gov (United States)

Kudliskis, Voldis

2013-01-01

In seeking to identify the processes associated with the immediate engagement of learning for students with mild special educational needs, this study examined the responses of an extraction group (n = 7) of 11- to 13-year-old students who participated in a number of lessons in which the opening episode involved the use of visualisation techniques…

Hierarchical Load Tracking Control of a Grid-connected Solid Oxide Fuel Cell for Maximum Electrical Efficiency Operation

DEFF Research Database (Denmark)

Li, Yonghui; Wu, Qiuwei; Zhu, Haiyu

2015-01-01

efficiency operation obtained at different active power output levels, a hierarchical load tracking control scheme for the grid-connected SOFC was proposed to realize the maximum electrical efficiency operation with the stack temperature bounded. The hierarchical control scheme consists of a fast active...... power control and a slower stack temperature control. The active power control was developed by using a decentralized control method. The efficiency of the proposed hierarchical control scheme was demonstrated by case studies using the benchmark SOFC dynamic model......Based on the benchmark solid oxide fuel cell (SOFC) dynamic model for power system studies and the analysis of the SOFC operating conditions, the nonlinear programming (NLP) optimization method was used to determine the maximum electrical efficiency of the grid-connected SOFC subject...

English semantic word-pair norms and a searchable Web portal for experimental stimulus creation.

Science.gov (United States)

Buchanan, Erin M; Holmes, Jessica L; Teasley, Marilee L; Hutchison, Keith A

2013-09-01

As researchers explore the complexity of memory and language hierarchies, the need to expand normed stimulus databases is growing. Therefore, we present 1,808 words, paired with their features and concept-concept information, that were collected using previously established norming methods (McRae, Cree, Seidenberg, & McNorgan Behavior Research Methods 37:547-559, 2005). This database supplements existing stimuli and complements the Semantic Priming Project (Hutchison, Balota, Cortese, Neely, Niemeyer, Bengson, & Cohen-Shikora 2010). The data set includes many types of words (including nouns, verbs, adjectives, etc.), expanding on previous collections of nouns and verbs (Vinson & Vigliocco Journal of Neurolinguistics 15:317-351, 2008). We describe the relation between our and other semantic norms, as well as giving a short review of word-pair norms. The stimuli are provided in conjunction with a searchable Web portal that allows researchers to create a set of experimental stimuli without prior programming knowledge. When researchers use this new database in tandem with previous norming efforts, precise stimuli sets can be created for future research endeavors.

Dystypia: isolated typing impairment without aphasia, apraxia or visuospatial impairment.

Science.gov (United States)

Otsuki, Mika; Soma, Yoshiaki; Arihiro, Shoji; Watanabe, Yoshimasa; Moriwaki, Hiroshi; Naritomi, Hiroaki

2002-01-01

We report a 60-year-old right-handed Japanese man who showed an isolated persistent typing impairment without aphasia, agraphia, apraxia or any other neuropsychological deficit. We coined the term 'dystypia' for this peculiar neuropsychological manifestation. The symptom was caused by an infarction in the left frontal lobe involving the foot of the second frontal convolution and the frontal operculum. The patient's typing impairment was not attributable to a disturbance of the linguistic process, since he had no aphasia or agraphia. The impairment was not attributable to the impairment of the motor execution process either, since he had no apraxia. Thus, his typing impairment was deduced to be based on a disturbance of the intermediate process where the linguistic phonological information is converted into the corresponding performance. We hypothesized that there is a specific process for typing which branches from the motor programming process presented in neurolinguistic models. The foot of the left second frontal convolution and the operculum may play an important role in the manifestation of 'dystypia'. Copyright 2002 S. Karger AG, Basel

Building gold standard corpora for medical natural language processing tasks.

Science.gov (United States)

Deleger, Louise; Li, Qi; Lingren, Todd; Kaiser, Megan; Molnar, Katalin; Stoutenborough, Laura; Kouril, Michal; Marsolo, Keith; Solti, Imre

2012-01-01

We present the construction of three annotated corpora to serve as gold standards for medical natural language processing (NLP) tasks. Clinical notes from the medical record, clinical trial announcements, and FDA drug labels are annotated. We report high inter-annotator agreements (overall F-measures between 0.8467 and 0.9176) for the annotation of Personal Health Information (PHI) elements for a de-identification task and of medications, diseases/disorders, and signs/symptoms for information extraction (IE) task. The annotated corpora of clinical trials and FDA labels will be publicly released and to facilitate translational NLP tasks that require cross-corpora interoperability (e.g. clinical trial eligibility screening) their annotation schemas are aligned with a large scale, NIH-funded clinical text annotation project.

Combined Noncyclic Scheduling and Advanced Control for Continuous Chemical Processes

Directory of Open Access Journals (Sweden)

Damon Petersen

2017-12-01

Full Text Available A novel formulation for combined scheduling and control of multi-product, continuous chemical processes is introduced in which nonlinear model predictive control (NMPC and noncyclic continuous-time scheduling are efficiently combined. A decomposition into nonlinear programming (NLP dynamic optimization problems and mixed-integer linear programming (MILP problems, without iterative alternation, allows for computationally light solution. An iterative method is introduced to determine the number of production slots for a noncyclic schedule during a prediction horizon. A filter method is introduced to reduce the number of MILP problems required. The formulation’s closed-loop performance with both process disturbances and updated market conditions is demonstrated through multiple scenarios on a benchmark continuously stirred tank reactor (CSTR application with fluctuations in market demand and price for multiple products. Economic performance surpasses cyclic scheduling in all scenarios presented. Computational performance is sufficiently light to enable online operation in a dual-loop feedback structure.

Humanities data in R exploring networks, geospatial data, images, and text

CERN Document Server

Arnold, Taylor

2015-01-01

This pioneering book teaches readers to use R within four core analytical areas applicable to the Humanities: networks, text, geospatial data, and images. This book is also designed to be a bridge: between quantitative and qualitative methods, individual and collaborative work, and the humanities and social scientists. Exploring Humanities Data Types with R does not presuppose background programming experience. Early chapters take readers from R set-up to exploratory data analysis (continuous and categorical data, multivariate analysis, and advanced graphics with emphasis on aesthetics and facility). Everything is hands-on: networks are explained using U.S. Supreme Court opinions, and low-level NLP methods are applied to short stories by Sir Arthur Conan Doyle. The book’s data, code, appendix with 100 basic programming exercises and solutions, and dedicated website are valuable resources for readers. The methodology will have wide application in classrooms and self-study for the humanities, but also for use...

Content-rich biological network constructed by mining PubMed abstracts

Directory of Open Access Journals (Sweden)

Sharp Burt M

2004-10-01

Full Text Available Abstract Background The integration of the rapidly expanding corpus of information about the genome, transcriptome, and proteome, engendered by powerful technological advances, such as microarrays, and the availability of genomic sequence from multiple species, challenges the grasp and comprehension of the scientific community. Despite the existence of text-mining methods that identify biological relationships based on the textual co-occurrence of gene/protein terms or similarities in abstract texts, knowledge of the underlying molecular connections on a large scale, which is prerequisite to understanding novel biological processes, lags far behind the accumulation of data. While computationally efficient, the co-occurrence-based approaches fail to characterize (e.g., inhibition or stimulation, directionality biological interactions. Programs with natural language processing (NLP capability have been created to address these limitations, however, they are in general not readily accessible to the public. Results We present a NLP-based text-mining approach, Chilibot, which constructs content-rich relationship networks among biological concepts, genes, proteins, or drugs. Amongst its features, suggestions for new hypotheses can be generated. Lastly, we provide evidence that the connectivity of molecular networks extracted from the biological literature follows the power-law distribution, indicating scale-free topologies consistent with the results of previous experimental analyses. Conclusions Chilibot distills scientific relationships from knowledge available throughout a wide range of biological domains and presents these in a content-rich graphical format, thus integrating general biomedical knowledge with the specialized knowledge and interests of the user. Chilibot http://www.chilibot.net can be accessed free of charge to academic users.

Multi-Objective Trajectory Optimization of a Hypersonic Reconnaissance Vehicle with Temperature Constraints

Science.gov (United States)

Masternak, Tadeusz J.

This research determines temperature-constrained optimal trajectories for a scramjet-based hypersonic reconnaissance vehicle by developing an optimal control formulation and solving it using a variable order Gauss-Radau quadrature collocation method with a Non-Linear Programming (NLP) solver. The vehicle is assumed to be an air-breathing reconnaissance aircraft that has specified takeoff/landing locations, airborne refueling constraints, specified no-fly zones, and specified targets for sensor data collections. A three degree of freedom scramjet aircraft model is adapted from previous work and includes flight dynamics, aerodynamics, and thermal constraints. Vehicle control is accomplished by controlling angle of attack, roll angle, and propellant mass flow rate. This model is incorporated into an optimal control formulation that includes constraints on both the vehicle and mission parameters, such as avoidance of no-fly zones and coverage of high-value targets. To solve the optimal control formulation, a MATLAB-based package called General Pseudospectral Optimal Control Software (GPOPS-II) is used, which transcribes continuous time optimal control problems into an NLP problem. In addition, since a mission profile can have varying vehicle dynamics and en-route imposed constraints, the optimal control problem formulation can be broken up into several "phases" with differing dynamics and/or varying initial/final constraints. Optimal trajectories are developed using several different performance costs in the optimal control formulation: minimum time, minimum time with control penalties, and maximum range. The resulting analysis demonstrates that optimal trajectories that meet specified mission parameters and constraints can be quickly determined and used for larger-scale operational and campaign planning and execution.

Novel 6xHis tagged foot-and-mouth disease virus vaccine bound to nanolipoprotein adjuvant via metal ions provides antigenic distinction and effective protective immunity

Energy Technology Data Exchange (ETDEWEB)

Rai, Devendra K.; Segundo, Fayna Diaz-San [Foreign Animal Disease Research Unit, United States Department of Agriculture, Agricultural Research Service, Plum Island Animal Disease Center, Greenport, NY 11944 (United States); Department of Pathobiology and Veterinary Science, CANR, University of Connecticut, Storrs, CT 06269 (United States); Schafer, Elizabeth [Foreign Animal Disease Research Unit, United States Department of Agriculture, Agricultural Research Service, Plum Island Animal Disease Center, Greenport, NY 11944 (United States); Burrage, Thomas G. [Department of Homeland Security, S & T, Targeted Advance Development, Virus, Cellular and Molecular Imaging Agriculture, Agricultural Research Service, Plum Island Animal Disease Center, Greenport, NY 11944 (United States); Rodriguez, Luis L.; Santos, Teresa de los [Foreign Animal Disease Research Unit, United States Department of Agriculture, Agricultural Research Service, Plum Island Animal Disease Center, Greenport, NY 11944 (United States); Hoeprich, Paul D. [Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, CA (United States); Rieder, Elizabeth, E-mail: Elizabeth.Rieder@ars.usda.gov [Foreign Animal Disease Research Unit, United States Department of Agriculture, Agricultural Research Service, Plum Island Animal Disease Center, Greenport, NY 11944 (United States)

2016-08-15

Here, we engineered two FMD viruses with histidine residues inserted into or fused to the FMDV capsid. Both 6xHis viruses exhibited growth kinetics, plaque morphologies and antigenic characteristics similar to wild-type virus. The 6xHis tag allowed one-step purification of the mutant virions by Co{sup 2+} affinity columns. Electron microscopy and biochemical assays showed that the 6xHis FMDVs readily assembled into antigen: adjuvant complexes in solution, by conjugating with Ni{sup 2+}-chelated nanolipoprotein and monophosphoryl lipid A adjuvant (MPLA:NiNLP). Animals Immunized with the inactivated 6xHis-FMDV:MPLA:NiNLP vaccine acquired enhanced protective immunity against FMDV challenge compared to virions alone. Induction of anti-6xHis and anti-FMDV neutralizing antibodies in the immunized animals could be exploited in the differentiation of vaccinated from infected animals needed for the improvement of FMD control measures. The novel marker vaccine/nanolipid technology described here has broad applications for the development of distinctive and effective immune responses to other pathogens of importance. - Highlights: • 6xHis-tags in A{sub 24} FMDV enable purification and biding to adjuvants via metal ions. • 6xHis A{sub 24} FMDV:MPLA:NiNLP vaccine enhanced protective immunity against FMDV. • Surface exposed capsid tags allow distinction of infected from vaccinated animals.

Novel 6xHis tagged foot-and-mouth disease virus vaccine bound to nanolipoprotein adjuvant via metal ions provides antigenic distinction and effective protective immunity

International Nuclear Information System (INIS)

Rai, Devendra K.; Segundo, Fayna Diaz-San; Schafer, Elizabeth; Burrage, Thomas G.; Rodriguez, Luis L.; Santos, Teresa de los; Hoeprich, Paul D.; Rieder, Elizabeth

2016-01-01

Here, we engineered two FMD viruses with histidine residues inserted into or fused to the FMDV capsid. Both 6xHis viruses exhibited growth kinetics, plaque morphologies and antigenic characteristics similar to wild-type virus. The 6xHis tag allowed one-step purification of the mutant virions by Co"2"+ affinity columns. Electron microscopy and biochemical assays showed that the 6xHis FMDVs readily assembled into antigen: adjuvant complexes in solution, by conjugating with Ni"2"+-chelated nanolipoprotein and monophosphoryl lipid A adjuvant (MPLA:NiNLP). Animals Immunized with the inactivated 6xHis-FMDV:MPLA:NiNLP vaccine acquired enhanced protective immunity against FMDV challenge compared to virions alone. Induction of anti-6xHis and anti-FMDV neutralizing antibodies in the immunized animals could be exploited in the differentiation of vaccinated from infected animals needed for the improvement of FMD control measures. The novel marker vaccine/nanolipid technology described here has broad applications for the development of distinctive and effective immune responses to other pathogens of importance. - Highlights: • 6xHis-tags in A_2_4 FMDV enable purification and biding to adjuvants via metal ions. • 6xHis A_2_4 FMDV:MPLA:NiNLP vaccine enhanced protective immunity against FMDV. • Surface exposed capsid tags allow distinction of infected from vaccinated animals.

De-identification of psychiatric intake records: Overview of 2016 CEGS N-GRID shared tasks Track 1.

Science.gov (United States)

Stubbs, Amber; Filannino, Michele; Uzuner, Özlem

2017-11-01

The 2016 CEGS N-GRID shared tasks for clinical records contained three tracks. Track 1 focused on de-identification of a new corpus of 1000 psychiatric intake records. This track tackled de-identification in two sub-tracks: Track 1.A was a "sight unseen" task, where nine teams ran existing de-identification systems, without any modifications or training, on 600 new records in order to gauge how well systems generalize to new data. The best-performing system for this track scored an F1 of 0.799. Track 1.B was a traditional Natural Language Processing (NLP) shared task on de-identification, where 15 teams had two months to train their systems on the new data, then test it on an unannotated test set. The best-performing system from this track scored an F1 of 0.914. The scores for Track 1.A show that unmodified existing systems do not generalize well to new data without the benefit of training data. The scores for Track 1.B are slightly lower than the 2014 de-identification shared task (which was almost identical to 2016 Track 1.B), indicating that these new psychiatric records pose a more difficult challenge to NLP systems. Overall, de-identification is still not a solved problem, though it is important to the future of clinical NLP. Copyright © 2017 Elsevier Inc. All rights reserved.

Azadirachta indica (Neem) leaf powder as a biosorbent for removal of Cd(II) from aqueous medium

Energy Technology Data Exchange (ETDEWEB)

Sharma, Arunima [Department of chemistry, Gauhati University, Guwahati 781014, Assam (India); Bhattacharyya, Krishna G. [Department of chemistry, Gauhati University, Guwahati 781014, Assam (India)]. E-mail: krishna2604@sify.com

2005-10-17

A biosorbent, Neem leaf powder (NLP), was prepared from the mature leaves of the Azadirachta indica (Neem) tree by initial cleaning, drying, grinding, washing to remove pigments and redrying. The powder was characterized with respect to specific surface area (21.45 m{sup 2} g{sup -1}), surface topography and surface functional groups and the material was used as an adsorbent in a batch process to remove Cd(II) from aqueous medium under conditions of different concentrations, NLP loadings, pH, agitation time and temperature. Adsorption increased from 8.8% at pH 4.0 to 70.0% at pH 7.0 and 93.6% at pH 9.5, the higher values in alkaline medium being due to removal by precipitation. The adsorption was very fast initially and maximum adsorption was observed within 300 min of agitation. The kinetics of the interactions was tested with pseudo first order Lagergren equation (mean k {sub 1} = 1.2 x 10{sup -2} min{sup -1}), simple second order kinetics (mean k {sub 2} = 1.34 x 10{sup -3} g mg{sup -1} min{sup -1}), Elovich equation, liquid film diffusion model (mean k = 1.39 x 10{sup -2} min{sup -1}) and intra-particle diffusion mechanism. The adsorption data gave good fits with Langmuir and Freundlich isotherms and yielded Langmuir monolayer capacity of 158 mg g{sup -1} for the NLP and Freundlich adsorption capacity of 18.7 L g{sup -1}. A 2.0 g of NLP could remove 86% of Cd(II) at 293 K from a solution containing 158.8 mg Cd(II) per litre. The mean values of the thermodynamic parameters, {delta}H, {delta}S and {delta}G, at 293 K were -73.7 kJ mol{sup -1}, -0.24 J mol{sup -1} K{sup -1} and -3.63 kJ mol{sup -1}, respectively, showing the adsorption process to be thermodynamically favourable. The results have established good potentiality for the Neem leaf powder to be used as a biosorbent for Cd(II)

Identification and characterization of proteins involved in nuclear organization using Drosophila GFP protein trap lines.

Directory of Open Access Journals (Sweden)

Margaret Rohrbaugh

Full Text Available Strains from a collection of Drosophila GFP protein trap lines express GFP in the normal tissues where the endogenous protein is present. This collection can be used to screen for proteins distributed in the nucleus in a non-uniform pattern.We analyzed four lines that show peripheral or punctate nuclear staining. One of these lines affects an uncharacterized gene named CG11138. The CG11138 protein shows a punctate distribution in the nuclear periphery similar to that of Drosophila insulator proteins but does not co-localize with known insulators. Interestingly, mutations in Lamin proteins result in alterations in CG11138 localization, suggesting that this protein may be a novel component of the nuclear lamina. A second line affects the Decondensation factor 31 (Df31 gene, which encodes a protein with a unique nuclear distribution that appears to segment the nucleus into four different compartments. The X-chromosome of males is confined to one of these compartments. We also find that Drosophila Nucleoplasmin (dNlp is present in regions of active transcription. Heat shock leads to loss of dNlp from previously transcribed regions of polytene chromosome without redistribution to the heat shock genes. Analysis of Stonewall (Stwl, a protein previously found to be necessary for the maintenance of germline stem cells, shows that Stwl is present in a punctate pattern in the nucleus that partially overlaps with that of known insulator proteins. Finally we show that Stwl, dNlp, and Df31 form part of a highly interactive network. The properties of other components of this network may help understand the role of these proteins in nuclear biology.These results establish screening of GFP protein trap alleles as a strategy to identify factors with novel cellular functions. Information gained from the analysis of CG11138 Stwl, dNlp, and Df31 sets the stage for future studies of these proteins.

Evaluation of the performance of Moses statistical engine adapted to ...

African Journals Online (AJOL)

... of Moses statistical engine adapted to English-Arabic language combination. ... of Artificial Intelligence (AI) dedicated to Natural Language Processing (NLP). ... and focuses on SMT, then introducing the features of the open source Moses ...

LEARNING SEMANTICS-ENHANCED LANGUAGE MODELS APPLIED TO UNSUEPRVISED WSD

Energy Technology Data Exchange (ETDEWEB)

VERSPOOR, KARIN [Los Alamos National Laboratory; LIN, SHOU-DE [Los Alamos National Laboratory

2007-01-29

An N-gram language model aims at capturing statistical syntactic word order information from corpora. Although the concept of language models has been applied extensively to handle a variety of NLP problems with reasonable success, the standard model does not incorporate semantic information, and consequently limits its applicability to semantic problems such as word sense disambiguation. We propose a framework that integrates semantic information into the language model schema, allowing a system to exploit both syntactic and semantic information to address NLP problems. Furthermore, acknowledging the limited availability of semantically annotated data, we discuss how the proposed model can be learned without annotated training examples. Finally, we report on a case study showing how the semantics-enhanced language model can be applied to unsupervised word sense disambiguation with promising results.

Applications of Natural Language Processing in Biodiversity Science

Directory of Open Access Journals (Sweden)

Anne E. Thessen

2012-01-01

A computer can handle the volume but cannot make sense of the language. This paper reviews and discusses the use of natural language processing (NLP and machine-learning algorithms to extract information from systematic literature. NLP algorithms have been used for decades, but require special development for application in the biological realm due to the special nature of the language. Many tools exist for biological information extraction (cellular processes, taxonomic names, and morphological characters, but none have been applied life wide and most still require testing and development. Progress has been made in developing algorithms for automated annotation of taxonomic text, identification of taxonomic names in text, and extraction of morphological character information from taxonomic descriptions. This manuscript will briefly discuss the key steps in applying information extraction tools to enhance biodiversity science.

Available Methods in Farsi-English Cross Language Information Retrieval Using Machine-readable, Bilingual Glossary

Directory of Open Access Journals (Sweden)

Hamid Alizadeh

2009-12-01

Full Text Available In this paper the impact scope of Natural Language Processing (NLP on translating search statements was determined by testing out research hypotheses. The NLP techniques employed for search statement processing included text parsing, linguistic forms identification, stopword removal, morphological analysis, and tokenization. Examination of the hypotheses indicated that using the method of translating the first equivalent term selected versus the method of selecting all equivalent terms, would contribute to increased efficiency of the review that while morphological analysis of the terms not translated by the glossary, would increase the retrieval precision cutoff, there would be no significant difference established by the lack of such analysis thereof that sentence translation as opposed to term by term translation, would increase the efficiency of Farsi-English proofreading. Other findings are also represented.

Nanolipoprotein Particles (NLPs) as Versatile Vaccine Platforms for Co-delivery of Multiple Adjuvants with Subunit Antigens from Burkholderia spp. and F. tularensis - Technical Report

Energy Technology Data Exchange (ETDEWEB)

Fischer, N. O. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2015-01-13

The goal of this proposal is to demonstrate that colocalization of protein subunit antigens and adjuvants on nanolipoprotein particles (NLPs) can increase the protective efficacy of subunit antigens from Burkholderia spp. and Francisella tularensis against an aerosol challenge. In the third quarter of the third year, F344 rats vaccinated with adjuvanted NLP formulations were challenged with F. tularensis SCHU S4 at Battelle. Preliminary data indicate that up to 65% of females vaccinated intranasally with an NLP-based formulation survived this challenge, compared to only 20% survival of naïve animals. In addition, NLPs were successfully formulated with Burkholderia protein antigens. IACUC approval for immunological assessments in BALB/c mice was received and we anticipate that these assessments will begin by March 2015, pending ACURO approval.

Fulltext PDF

Indian Academy of Sciences (India)

user

study language the way it is used to achieve certain ends. ... increasingly complex levels of language mo- dality. ... guage processing (NLP) and machine transla- ... Memory-based or example-based approaches ... It presents a framework in.

Optimal groundwater remediation using artificial neural networks and the genetic algorithm

Energy Technology Data Exchange (ETDEWEB)

Rogers, Leah L. [Stanford Univ., CA (United States)

1992-08-01

An innovative computational approach for the optimization of groundwater remediation is presented which uses artificial neural networks (ANNs) and the genetic algorithm (GA). In this approach, the ANN is trained to predict an aspect of the outcome of a flow and transport simulation. Then the GA searches through realizations or patterns of pumping and uses the trained network to predict the outcome of the realizations. This approach has advantages of parallel processing of the groundwater simulations and the ability to ``recycle`` or reuse the base of knowledge formed by these simulations. These advantages offer reduction of computational burden of the groundwater simulations relative to a more conventional approach which uses nonlinear programming (NLP) with a quasi-newtonian search. Also the modular nature of this approach facilitates substitution of different groundwater simulation models.

Optimal groundwater remediation using artificial neural networks and the genetic algorithm

International Nuclear Information System (INIS)

Rogers, L.L.

1992-08-01

An innovative computational approach for the optimization of groundwater remediation is presented which uses artificial neural networks (ANNs) and the genetic algorithm (GA). In this approach, the ANN is trained to predict an aspect of the outcome of a flow and transport simulation. Then the GA searches through realizations or patterns of pumping and uses the trained network to predict the outcome of the realizations. This approach has advantages of parallel processing of the groundwater simulations and the ability to ''recycle'' or reuse the base of knowledge formed by these simulations. These advantages offer reduction of computational burden of the groundwater simulations relative to a more conventional approach which uses nonlinear programming (NLP) with a quasi-newtonian search. Also the modular nature of this approach facilitates substitution of different groundwater simulation models

Efficient Encoding of Inflection Rules in NLP Systems

Directory of Open Access Journals (Sweden)

Péter BARABÁSS

2012-12-01

Full Text Available The grammatical parsing unit is a core module in natural language processing engines. This unit determines the grammatical roles of the incoming words and it converts the sentences into semantic models. A special grammar rule in agglutinative languages is the inflection rule. The traditional, automata-based parsers are usually not very effective in the parsing of inflection transformations. The paper presents implementation alternatives and compares them from the viewpoint of time efficiency and accuracy. The prototype system was tested with examples from Hungarian.

Cost Optimization of Industrial Enterprises of Building Materials Оптимизация расходов предприятий промышленности строительных материалов

Directory of Open Access Journals (Sweden)

Belovodskaya Alena A.

2012-04-01

Full Text Available The paper has proved that one of the directions of increasing profitability of construction materials industry enterprises’ activity can be optimizing costs dealing with sales. Tools of neuro-linguistic programming (NLP or so called sensor marketing have been proposed for use to choose the most effective technology of market promoting construction materials. Use of method of solving optimization tasks in mathematical programming has allowed getting a ranked series of NLP measures for decreasing efficiency as follows: sound design of trade zones, conducting trainings for staff, design of shop windows and interior, use of merchandising principles.В работе доказано, что одним из направлений повышения прибыльности деятельности предприятий промышленности строительных материалов может быть оптимизация расходов, связанных с реализацией продукции. Для выбора наиболее эффективной технологии продвижения строительных материалов на рынок было предложено использовать инструменты нейролингвистического программирования (НЛП или так называемый сенсорный маркетинг. Использование метода решения оптимизационных задач в математическом программировании позволило получить проранжированный ряд мероприятий НЛП по уменьшению эффективности следующего вида: звуковое оформление торгового помещения, проведение тренингов для персонала, оформление витрин и �

Scenario Customization for Information Extraction

National Research Council Canada - National Science Library

Yangarber, Roman

2001-01-01

Information Extraction (IE) is an emerging NLP technology, whose function is to process unstructured, natural language text, to locate specific pieces of information, or facts, in the text, and to use these facts to fill a database...

Co-occurrence rate networks: towards separate training for undirected graphical models

NARCIS (Netherlands)

Zhu, Zhemin

2015-01-01

Dependence is a universal phenomenon which can be observed everywhere. In machine learning, probabilistic graphical models (PGMs) represent dependence relations with graphs. PGMs find wide applications in natural language processing (NLP), speech processing, computer vision, biomedicine, information

Querying and Serving N-gram Language Models with Python

Directory of Open Access Journals (Sweden)

2009-06-01

Full Text Available Statistical n-gram language modeling is a very important technique in Natural Language Processing (NLP and Computational Linguistics used to assess the fluency of an utterance in any given language. It is widely employed in several important NLP applications such as Machine Translation and Automatic Speech Recognition. However, the most commonly used toolkit (SRILM to build such language models on a large scale is written entirely in C++ which presents a challenge to an NLP developer or researcher whose primary language of choice is Python. This article first provides a gentle introduction to statistical language modeling. It then describes how to build a native and efficient Python interface (using SWIG to the SRILM toolkit such that language models can be queried and used directly in Python code. Finally, it also demonstrates an effective use case of this interface by showing how to leverage it to build a Python language model server. Such a server can prove to be extremely useful when the language model needs to be queried by multiple clients over a network: the language model must only be loaded into memory once by the server and can then satisfy multiple requests. This article includes only those listings of source code that are most salient. To conserve space, some are only presented in excerpted form. The complete set of full source code listings may be found in Volume 1 of The Python Papers Source Codes Journal.

Representing Information in Patient Reports Using Natural Language Processing and the Extensible Markup Language

Science.gov (United States)

Friedman, Carol; Hripcsak, George; Shagina, Lyuda; Liu, Hongfang

1999-01-01

Objective: To design a document model that provides reliable and efficient access to clinical information in patient reports for a broad range of clinical applications, and to implement an automated method using natural language processing that maps textual reports to a form consistent with the model. Methods: A document model that encodes structured clinical information in patient reports while retaining the original contents was designed using the extensible markup language (XML), and a document type definition (DTD) was created. An existing natural language processor (NLP) was modified to generate output consistent with the model. Two hundred reports were processed using the modified NLP system, and the XML output that was generated was validated using an XML validating parser. Results: The modified NLP system successfully processed all 200 reports. The output of one report was invalid, and 199 reports were valid XML forms consistent with the DTD. Conclusions: Natural language processing can be used to automatically create an enriched document that contains a structured component whose elements are linked to portions of the original textual report. This integrated document model provides a representation where documents containing specific information can be accurately and efficiently retrieved by querying the structured components. If manual review of the documents is desired, the salient information in the original reports can also be identified and highlighted. Using an XML model of tagging provides an additional benefit in that software tools that manipulate XML documents are readily available. PMID:9925230

Slavic Forest, Norwegian Wood (models)

OpenAIRE

Rosa, Rudolf; Žabokrtský, Zdeněk; Zeman, Daniel; Mareček, David

2017-01-01

Trained models for UDPipe used to produce our final submission to VarDial 2017 shared task (https://bitbucket.org/hy-crossNLP/vardial2017) and described in a paper by the same authors titled Slavic Forest, Norwegian Wood.

Tune Your Brown Clustering, Please

DEFF Research Database (Denmark)

Derczynski, Leon; Chester, Sean; Bøgh, Kenneth Sejdenfaden

2015-01-01

Brown clustering, an unsupervised hierarchical clustering technique based on ngram mutual information, has proven useful in many NLP applications. However, most uses of Brown clustering employ the same default configuration; the appropriateness of this configuration has gone predominantly...

NLTK essentials

CERN Document Server

Hardeniya, Nitin

2015-01-01

If you are an NLP or machine learning enthusiast with some or no experience in text processing, then this book is for you. This book is also ideal for expert Python programmers who want to learn NLTK quickly.

Using natural language processing techniques to inform research on nanotechnology

Directory of Open Access Journals (Sweden)

Nastassja A. Lewinski

2015-07-01

Full Text Available Literature in the field of nanotechnology is exponentially increasing with more and more engineered nanomaterials being created, characterized, and tested for performance and safety. With the deluge of published data, there is a need for natural language processing approaches to semi-automate the cataloguing of engineered nanomaterials and their associated physico-chemical properties, performance, exposure scenarios, and biological effects. In this paper, we review the different informatics methods that have been applied to patent mining, nanomaterial/device characterization, nanomedicine, and environmental risk assessment. Nine natural language processing (NLP-based tools were identified: NanoPort, NanoMapper, TechPerceptor, a Text Mining Framework, a Nanodevice Analyzer, a Clinical Trial Document Classifier, Nanotoxicity Searcher, NanoSifter, and NEIMiner. We conclude with recommendations for sharing NLP-related tools through online repositories to broaden participation in nanoinformatics.

Endoparasites of American marten (Martes americana: Review of the literature and parasite survey of reintroduced American marten in Michigan

Directory of Open Access Journals (Sweden)

Maria C. Spriggs

2016-12-01

Full Text Available The American marten (Martes americana was reintroduced to both the Upper (UP and northern Lower Peninsula (NLP of Michigan during the 20th century. This is the first report of endoparasites of American marten from the NLP. Faeces from live-trapped American marten were examined for the presence of parasitic ova, and blood samples were obtained for haematocrit evaluation. The most prevalent parasites were Capillaria and Alaria species. Helminth parasites reported in American marten for the first time include Eucoleus boehmi, hookworm, and Hymenolepis and Strongyloides species. This is the first report of shedding of Sarcocystis species sporocysts in an American marten and identification of 2 coccidian parasites, Cystoisospora and Eimeria species. The pathologic and zoonotic potential of each parasite species is discussed, and previous reports of endoparasites of the American marten in North America are reviewed.

Behind the scenes: A medical natural language processing project.

Science.gov (United States)

Wu, Joy T; Dernoncourt, Franck; Gehrmann, Sebastian; Tyler, Patrick D; Moseley, Edward T; Carlson, Eric T; Grant, David W; Li, Yeran; Welt, Jonathan; Celi, Leo Anthony

2018-04-01

Advancement of Artificial Intelligence (AI) capabilities in medicine can help address many pressing problems in healthcare. However, AI research endeavors in healthcare may not be clinically relevant, may have unrealistic expectations, or may not be explicit enough about their limitations. A diverse and well-functioning multidisciplinary team (MDT) can help identify appropriate and achievable AI research agendas in healthcare, and advance medical AI technologies by developing AI algorithms as well as addressing the shortage of appropriately labeled datasets for machine learning. In this paper, our team of engineers, clinicians and machine learning experts share their experience and lessons learned from their two-year-long collaboration on a natural language processing (NLP) research project. We highlight specific challenges encountered in cross-disciplinary teamwork, dataset creation for NLP research, and expectation setting for current medical AI technologies. Copyright © 2017. Published by Elsevier B.V.

Feasibility and Utility of Lexical Analysis for Occupational Health Text.

Science.gov (United States)

Harber, Philip; Leroy, Gondy

2017-06-01

Assess feasibility and potential utility of natural language processing (NLP) for storing and analyzing occupational health data. Basic NLP lexical analysis methods were applied to 89,000 Mine Safety and Health Administration (MSHA) free text records. Steps included tokenization, term and co-occurrence counts, term annotation, and identifying exposure-health effect relationships. Presence of terms in the Unified Medical Language System (UMLS) was assessed. The methods efficiently demonstrated common exposures, health effects, and exposure-injury relationships. Many workplace terms are not present in UMLS or map inaccurately. Use of free text rather than narrowly defined numerically coded fields is feasible, flexible, and efficient. It has potential to encourage workers and clinicians to provide more data and to support automated knowledge creation. The lexical method used is easily generalizable to other areas. The UMLS vocabularies should be enhanced to be relevant to occupational health.

Lexicografia i intel·ligència artificial

Directory of Open Access Journals (Sweden)

Ramon Cerdà Massó

2015-10-01

Full Text Available Unlike most of traditional approaches to grammar, today's formal and computational models make use of the lexicon as an essential part of the whole system. Differences between current theoretical and computational models are more and more insignificant albeit the latter are perhaps still characterized by yielding full priority to minimalist solutions over more abstract considerations such as exhaustivity or formal elegance. The paper introduces some strategies in linguistic computation for natural language processing (NLP according to a typology based on functional complexity and describing in every case the scope and the role performed by the dictionary: pattern matching, semàntic grammars, syntactic parsers, augmented transition networks, unification formalisms, case frame grammars, etc. It ends with an exploration into lexicographically oriented procedures of conceptual dependency, which are found beyond the NLP, deeply within the domain of artificial intelligence.

Drug-Drug Interaction Extraction via Convolutional Neural Networks

Directory of Open Access Journals (Sweden)

Shengyu Liu

2016-01-01

Full Text Available Drug-drug interaction (DDI extraction as a typical relation extraction task in natural language processing (NLP has always attracted great attention. Most state-of-the-art DDI extraction systems are based on support vector machines (SVM with a large number of manually defined features. Recently, convolutional neural networks (CNN, a robust machine learning method which almost does not need manually defined features, has exhibited great potential for many NLP tasks. It is worth employing CNN for DDI extraction, which has never been investigated. We proposed a CNN-based method for DDI extraction. Experiments conducted on the 2013 DDIExtraction challenge corpus demonstrate that CNN is a good choice for DDI extraction. The CNN-based DDI extraction method achieves an F-score of 69.75%, which outperforms the existing best performing method by 2.75%.

A System for Extracting Study Design Parameters from Nutritional Genomics Abstracts

Directory of Open Access Journals (Sweden)

Kelly Cassidy

2013-06-01

Full Text Available The extraction of study design parameters from biomedical journal articles is an important problem in natural language processing (NLP. Such parameters define the characteristics of a study, such as the duration, the number of subjects, and their profile. Here we present a system for extracting study design parameters from sentences in article abstracts. This system will be used as a component of a larger system for creating nutrigenomics networks from articles in the nutritional genomics domain. The algorithms presented consist of manually designed rules expressed either as regular expressions or in terms of sentence parse structure. A number of filters and NLP tools are also utilized within a pipelined algorithmic framework. Using this novel approach, our system performs extraction at a finer level of granularity than comparable systems, while generating results that surpass the current state of the art.

Brid Hendron: 'People talk about stress when what we need to be doing is eliminating it'.

Science.gov (United States)

Hendron, Brid; Doherty, Ruth

2014-06-01

Brid Hendron is a GDP and has a special interest in relaxing nervous, anxious and phobic patients. She holds an NLP trainer qualification and is also qualified in hypnosis. Brid provides training for healthcare professionals in advanced communication skills.

Sadhana | Indian Academy of Sciences

Indian Academy of Sciences (India)

2018-06-07

Jun 7, 2018 ... Science Education Programmes · Women in Science · Committee on ... Transliteration; informal information; natural language processing (NLP); information retrieval. ... Department of Computer Science and Engineering, Indian Institute of Technology (Indian School of Mines), Dhanbad 826004, India ...

Yoga club

CERN Multimedia

Yoga club

2012-01-01

Learn at lunchtime Workshop on sophrology by Dorna Revie, Master Sophrologist & NLP Trainer, on Tuesday 29th January - 12.30 to 14.00, Council Chamber (503/1-001) Conférence de Chantal Roy & Dorna Revie, Maîtres Sophrologues

Responses of broiler chickens under hot humid tropical climate as ...

African Journals Online (AJOL)

NLP) on the growth, haematology and serum biochemistry parameters of broiler chicks. Two hundred and forty day-old broiler chicks were randomly assigned to four treatments which contained 0, 5, 10 and 15g/Kg diets in a Completely ...

A comparison of rule-based and machine learning approaches for classifying patient portal messages.

Science.gov (United States)

Cronin, Robert M; Fabbri, Daniel; Denny, Joshua C; Rosenbloom, S Trent; Jackson, Gretchen Purcell

2017-09-01

Secure messaging through patient portals is an increasingly popular way that consumers interact with healthcare providers. The increasing burden of secure messaging can affect clinic staffing and workflows. Manual management of portal messages is costly and time consuming. Automated classification of portal messages could potentially expedite message triage and delivery of care. We developed automated patient portal message classifiers with rule-based and machine learning techniques using bag of words and natural language processing (NLP) approaches. To evaluate classifier performance, we used a gold standard of 3253 portal messages manually categorized using a taxonomy of communication types (i.e., main categories of informational, medical, logistical, social, and other communications, and subcategories including prescriptions, appointments, problems, tests, follow-up, contact information, and acknowledgement). We evaluated our classifiers' accuracies in identifying individual communication types within portal messages with area under the receiver-operator curve (AUC). Portal messages often contain more than one type of communication. To predict all communication types within single messages, we used the Jaccard Index. We extracted the variables of importance for the random forest classifiers. The best performing approaches to classification for the major communication types were: logistic regression for medical communications (AUC: 0.899); basic (rule-based) for informational communications (AUC: 0.842); and random forests for social communications and logistical communications (AUCs: 0.875 and 0.925, respectively). The best performing classification approach of classifiers for individual communication subtypes was random forests for Logistical-Contact Information (AUC: 0.963). The Jaccard Indices by approach were: basic classifier, Jaccard Index: 0.674; Naïve Bayes, Jaccard Index: 0.799; random forests, Jaccard Index: 0.859; and logistic regression, Jaccard

Intraoperative mapping of language functions: a longitudinal neurolinguistic analysis.

Science.gov (United States)

Ilmberger, Josef; Ruge, Maximilian; Kreth, Friedrich-Wilhelm; Briegel, Josef; Reulen, Hans-Juergen; Tonn, Joerg-Christian

2008-10-01

This prospective longitudinally designed study was conducted to evaluate language functions pre- and postoperatively in patients who underwent microsurgical treatment of tumors in close proximity to or within language areas and to detect those patients at risk for a postoperative aphasic disturbance. Between 1991 and 2005, 153 awake craniotomies with subsequent cortical mapping of language functions were performed in 149 patients. Language functions were assessed using a standardized test battery. Risk factors were obtained from multivariate logistic regression models. Language mapping was able to be performed in all patients, and complete tumor resection was achieved in 48.4%. Within 21 days after surgery a new language deficit (aphasic disturbance) was observed in 41 (32%) of the 128 cases without preoperative deficits. There were a total of 60 cases involving postoperative aphasic disturbances, including cases both with and without preoperative disturbances. Risk factors for postoperative aphasic disturbance were preoperative aphasia (planguage-positive sites within the tumor (planguage disturbances. A total of 17.6% of all cases demonstrated new postoperative language disturbances after 7 months. Risk factors for persistent aphasic disturbance were increased age (>40 years, planguage-relevant areas intraoperatively, even when they are located within the tumor. New postoperative deficits resolve in the majority of patients, which may be a result of cortical mapping as well as functional reorganization.

[Tributes to Macdonald Critchley and his achievements in neurolinguistics].

Science.gov (United States)

Hung, Tsu-Pei

2008-06-01

Macdonald Critchley, a world renowned neurologist, is best remembered as the person who challenged to solve the mystery and enigma of higher cerebral functions. He was the author of over 200 published articles and 20 books on neurology including his pioneer work on developmental dyslexia, the parietal lobe, cerebral hemisphere dominance and aphasiology. He also published articles on migraine, epilepsy, dementia, visual perseveration, anterior cerebral artery syndromes, indifference to pain, sleep disorders, movement disorders, and myotonia. He was very erudite and talented in linguistics; his interests were broad and eclectic. He wrote extensively on non-medical topics, such as plays, horror stories, mythology, and biographies of distinguished neuroscientists, philosophers or artists. His articles were written in the elegant prose style with thorough reference citations and extensive reviews of the literature worldwide. He was born in Bristol in 1900. From an early age, he was fascinated with the functioning brain and retained a life-long interest in languages. He was appointed to the Consultant staff of the National Hospital, Queen Square, and to King's College Hospital at the age of 27, and was elected to become FRCP at 30. He was Dean of the Institute of Neurology from 1948 to 1953. When I was studying advanced neurology at Queen Square in 1960-1961, I was fascinated by his outstanding lectures on Huntington's Disease and Non-verbal Communication. Although he did not read the manuscripts and used only a few slides for illustrations in his lectures, he could describe the details of historical accounts and relevant figures. He was an altruistic, instructive teacher with keen attention to responses from the audience. His clinical demonstrations, teaching rounds and tutorials were hugely popular among postgraduate students from all over the world. He emphasized the importance of shrewd observation and careful history taking in neurological practice. Macdonald Critchley was President of the World Federation of Neurology (1965-1973) and Editor of Journal of the Neurological Sciences. I met him at the 2nd Asian and Oceanian Congress of Neurology held in Melbourne in 1967. He was interested to know more about aphasia and dyslexia among people speaking and reading Chinese. He kindly invited me to speak on 'Linguistic Implications of Chinese Characters' at the meeting of the Research Group on Developmental Dyslexia in Dallas. Critchley's prominent achievements in teaching, writings and research on neurology derived from his creative thinking, powers of shrewd observation, wide knowledge of literature, and indefatigable assiduity in scientific pursuits. He died peacefully at home at the age of 97 and entered the pantheon of distinguished neuroscientists of the 20th century.

Progressive apraxia of speech as a window into the study of speech planning processes.

Science.gov (United States)

Laganaro, Marina; Croisier, Michèle; Bagou, Odile; Assal, Frédéric

2012-09-01

We present a 3-year follow-up study of a patient with progressive apraxia of speech (PAoS), aimed at investigating whether the theoretical organization of phonetic encoding is reflected in the progressive disruption of speech. As decreased speech rate was the most striking pattern of disruption during the first 2 years, durational analyses were carried out longitudinally on syllables excised from spontaneous, repetition and reading speech samples. The crucial result of the present study is the demonstration of an effect of syllable frequency on duration: the progressive disruption of articulation rate did not affect all syllables in the same way, but followed a gradient that was function of the frequency of use of syllable-sized motor programs. The combination of data from this case of PAoS with previous psycholinguistic and neurolinguistic data, points to a frequency organization of syllable-sized speech-motor plans. In this study we also illustrate how studying PAoS can be exploited in theoretical and clinical investigations of phonetic encoding as it represents a unique opportunity to investigate speech while it progressively disrupts. Copyright © 2011 Elsevier Srl. All rights reserved.

Using Nonexperts for Annotating Pharmacokinetic Drug-Drug Interaction Mentions in Product Labeling: A Feasibility Study.

Science.gov (United States)

Hochheiser, Harry; Ning, Yifan; Hernandez, Andres; Horn, John R; Jacobson, Rebecca; Boyce, Richard D

2016-04-11

Because vital details of potential pharmacokinetic drug-drug interactions are often described in free-text structured product labels, manual curation is a necessary but expensive step in the development of electronic drug-drug interaction information resources. The use of nonexperts to annotate potential drug-drug interaction (PDDI) mentions in drug product label annotation may be a means of lessening the burden of manual curation. Our goal was to explore the practicality of using nonexpert participants to annotate drug-drug interaction descriptions from structured product labels. By presenting annotation tasks to both pharmacy experts and relatively naïve participants, we hoped to demonstrate the feasibility of using nonexpert annotators for drug-drug information annotation. We were also interested in exploring whether and to what extent natural language processing (NLP) preannotation helped improve task completion time, accuracy, and subjective satisfaction. Two experts and 4 nonexperts were asked to annotate 208 structured product label sections under 4 conditions completed sequentially: (1) no NLP assistance, (2) preannotation of drug mentions, (3) preannotation of drug mentions and PDDIs, and (4) a repeat of the no-annotation condition. Results were evaluated within the 2 groups and relative to an existing gold standard. Participants were asked to provide reports on the time required to complete tasks and their perceptions of task difficulty. One of the experts and 3 of the nonexperts completed all tasks. Annotation results from the nonexpert group were relatively strong in every scenario and better than the performance of the NLP pipeline. The expert and 2 of the nonexperts were able to complete most tasks in less than 3 hours. Usability perceptions were generally positive (3.67 for expert, mean of 3.33 for nonexperts). The results suggest that nonexpert annotation might be a feasible option for comprehensive labeling of annotated PDDIs across a broader

Empirical Methods in Natural Language Generation

NARCIS (Netherlands)

Krahmer, Emiel; Theune, Mariet

Natural language generation (NLG) is a subfield of natural language processing (NLP) that is often characterized as the study of automatically converting non-linguistic representations (e.g., from databases or other knowledge sources) into coherent natural language text. In recent years the field

Elementary? Question Answering, IBM's Watson, and the Jeopardy ...

Indian Academy of Sciences (India)

IAS Admin

One of the most readable accounts of early AI systems, including. NLP systems, may be .... tions of these questions to annotations of information segments in ..... Watson as a decision-aide rather than as a decision-maker will be a safe step ...

MINLP solution for an optimal isotope separation system

International Nuclear Information System (INIS)

Boisset-Baticle, L.; Latge, C.; Joulia, X.

1994-01-01

This paper deals with designing of cryogenic distillation systems for the separation of hydrogen isotopes in a thermonuclear fusion process. The design must minimize the tritium inventory in the distillation columns and satisfy the separation requirements. This induces the optimization of both the structure and the operating conditions of the columns. Such a problem is solved by use of a Mixed-Integer NonLinear Programming (MINLP) tool coupled to a process simulator. The MINLP procedure is based on the iterative and alternative treatment of two subproblems: a NLP problem which is solved by a reduced-gradient method, and a MILP problem, solved with a Branch and Bound method coupled to a simplexe. The formulation of the problem and the choice of an appropriate superstructure are here detailed, and results are finally presented, concerning the optimal design of a specific isotope separation system. (author)

Families of optimal thermodynamic solutions for combined cycle gas turbine (CCGT) power plants

International Nuclear Information System (INIS)

Godoy, E.; Scenna, N.J.; Benz, S.J.

2010-01-01

Optimal designs of a CCGT power plant characterized by maximum second law efficiency values are determined for a wide range of power demands and different values of the available heat transfer area. These thermodynamic optimal solutions are found within a feasible operation region by means of a non-linear mathematical programming (NLP) model, where decision variables (i.e. transfer areas, power production, mass flow rates, temperatures and pressures) can vary freely. Technical relationships among them are used to systematize optimal values of design and operative variables of a CCGT power plant into optimal solution sets, named here as optimal solution families. From an operative and design point of view, the families of optimal solutions let knowing in advance optimal values of the CCGT variables when facing changes of power demand or adjusting the design to an available heat transfer area.

The 1st reveal of Gen-V nuclear energy. Prospecting investigation of nuclear power 2050 (A2050) for energy innovation in the nuclear industry

International Nuclear Information System (INIS)

Woo, Tae Ho; Lee, Soon Ho

2012-01-01

The proposed strategy for the future nuclear energy is analyzed. The conventional nuclear power plants (NPPs) are investigated by the 21 st style interdisciplinary research as the information technology (IT), nanotechnology (NT), and biological technology (BT). New kinds of energy production methods as spherical isotropic power reactor (SIPR) and nano lattice power (NLP) are introduced. In addition, the problems of Gen-IV technologies are challenged to be solved, which is the matters of the mechanical and thermal controls of several coolants cases. The simulation result shows the increasing for the usefulness of the business. The core and vessel are very tractable due to moving core vessel (SIPR). The concept of safety system is changed to be submerged into coolant instead of injection concept (SIPR). The commercial fusion energy is realized for mass energy productions (NLP). Eventually, the safety as well as economical status is increased comparing to previous NPPs. (orig.)

The 1{sup st} reveal of Gen-V nuclear energy. Prospecting investigation of nuclear power 2050 (A2050) for energy innovation in the nuclear industry

Energy Technology Data Exchange (ETDEWEB)

Woo, Tae Ho [Seoul National Univ. (Korea, Republic of). Dept. of Nuclear Engineering; Lee, Seok Jong [POSCO Engineering and Construction Co., Ltd., Incheon (Korea, Republic of); Lee, Soon Ho [SK Engineering and Construction Co., Ltd., Seoul (Korea, Republic of)

2012-11-15

The proposed strategy for the future nuclear energy is analyzed. The conventional nuclear power plants (NPPs) are investigated by the 21{sup st} style interdisciplinary research as the information technology (IT), nanotechnology (NT), and biological technology (BT). New kinds of energy production methods as spherical isotropic power reactor (SIPR) and nano lattice power (NLP) are introduced. In addition, the problems of Gen-IV technologies are challenged to be solved, which is the matters of the mechanical and thermal controls of several coolants cases. The simulation result shows the increasing for the usefulness of the business. The core and vessel are very tractable due to moving core vessel (SIPR). The concept of safety system is changed to be submerged into coolant instead of injection concept (SIPR). The commercial fusion energy is realized for mass energy productions (NLP). Eventually, the safety as well as economical status is increased comparing to previous NPPs. (orig.)

Annotating Logical Forms for EHR Questions.

Science.gov (United States)

Roberts, Kirk; Demner-Fushman, Dina

2016-05-01

This paper discusses the creation of a semantically annotated corpus of questions about patient data in electronic health records (EHRs). The goal is to provide the training data necessary for semantic parsers to automatically convert EHR questions into a structured query. A layered annotation strategy is used which mirrors a typical natural language processing (NLP) pipeline. First, questions are syntactically analyzed to identify multi-part questions. Second, medical concepts are recognized and normalized to a clinical ontology. Finally, logical forms are created using a lambda calculus representation. We use a corpus of 446 questions asking for patient-specific information. From these, 468 specific questions are found containing 259 unique medical concepts and requiring 53 unique predicates to represent the logical forms. We further present detailed characteristics of the corpus, including inter-annotator agreement results, and describe the challenges automatic NLP systems will face on this task.

Improving performance of natural language processing part-of-speech tagging on clinical narratives through domain adaptation.

Science.gov (United States)

Ferraro, Jeffrey P; Daumé, Hal; Duvall, Scott L; Chapman, Wendy W; Harkema, Henk; Haug, Peter J

2013-01-01

Natural language processing (NLP) tasks are commonly decomposed into subtasks, chained together to form processing pipelines. The residual error produced in these subtasks propagates, adversely affecting the end objectives. Limited availability of annotated clinical data remains a barrier to reaching state-of-the-art operating characteristics using statistically based NLP tools in the clinical domain. Here we explore the unique linguistic constructions of clinical texts and demonstrate the loss in operating characteristics when out-of-the-box part-of-speech (POS) tagging tools are applied to the clinical domain. We test a domain adaptation approach integrating a novel lexical-generation probability rule used in a transformation-based learner to boost POS performance on clinical narratives. Two target corpora from independent healthcare institutions were constructed from high frequency clinical narratives. Four leading POS taggers with their out-of-the-box models trained from general English and biomedical abstracts were evaluated against these clinical corpora. A high performing domain adaptation method, Easy Adapt, was compared to our newly proposed method ClinAdapt. The evaluated POS taggers drop in accuracy by 8.5-15% when tested on clinical narratives. The highest performing tagger reports an accuracy of 88.6%. Domain adaptation with Easy Adapt reports accuracies of 88.3-91.0% on clinical texts. ClinAdapt reports 93.2-93.9%. ClinAdapt successfully boosts POS tagging performance through domain adaptation requiring a modest amount of annotated clinical data. Improving the performance of critical NLP subtasks is expected to reduce pipeline error propagation leading to better overall results on complex processing tasks.

Applying Active Learning to Assertion Classification of Concepts in Clinical Text

Science.gov (United States)

Chen, Yukun; Mani, Subramani; Xu, Hua

2012-01-01

Supervised machine learning methods for clinical natural language processing (NLP) research require a large number of annotated samples, which are very expensive to build because of the involvement of physicians. Active learning, an approach that actively samples from a large pool, provides an alternative solution. Its major goal in classification is to reduce the annotation effort while maintaining the quality of the predictive model. However, few studies have investigated its uses in clinical NLP. This paper reports an application of active learning to a clinical text classification task: to determine the assertion status of clinical concepts. The annotated corpus for the assertion classification task in the 2010 i2b2/VA Clinical NLP Challenge was used in this study. We implemented several existing and newly developed active learning algorithms and assessed their uses. The outcome is reported in the global ALC score, based on the Area under the average Learning Curve of the AUC (Area Under the Curve) score. Results showed that when the same number of annotated samples was used, active learning strategies could generate better classification models (best ALC – 0.7715) than the passive learning method (random sampling) (ALC – 0.7411). Moreover, to achieve the same classification performance, active learning strategies required fewer samples than the random sampling method. For example, to achieve an AUC of 0.79, the random sampling method used 32 samples, while our best active learning algorithm required only 12 samples, a reduction of 62.5% in manual annotation effort. PMID:22127105

Reusable Lexical Representations for Idioms

NARCIS (Netherlands)

Odijk, J.E.J.M.

2004-01-01

In this paper I introduce (1) a technically simple and highly theory-independent way for lexically representing flexible idiomatic expressions, and (2) a procedure to incorporate these lexical representations in a wide variety of NLP systems. The method is based on Structural EQuivalence Classes

Part-of-speech effects on text-to-speech synthesis

CSIR Research Space (South Africa)

Schlunz, GI

2010-11-01

Full Text Available One of the goals of text-to-speech (TTS) systems is to produce natural-sounding synthesised speech. Towards this end various natural language processing (NLP) tasks are performed to model the prosodic aspects of the TTS voice. One of the fundamental...

Introduction to special issue on machine learning approaches to shallow parsing

NARCIS (Netherlands)

Hammerton, J; Osborne, M; Armstrong, S; Daelemans, W

2002-01-01

This article introduces the problem of partial or shallow parsing (assigning partial syntactic structure to sentences) and explains why it is an important natural language processing (NLP) task. The complexity of the task makes Machine Learning an attractive option in comparison to the handcrafting

DKIE: Open Source Information Extraction for Danish

DEFF Research Database (Denmark)

Derczynski, Leon; Field, Camilla Vilhelmsen; Bøgh, Kenneth Sejdenfaden

2014-01-01

Danish is a major Scandinavian language spoken daily by around six million people. However, it lacks a unified, open set of NLP tools. This demonstration will introduce DKIE, an extensible open-source toolkit for processing Danish text. We implement an information extraction architecture for Danish...

Kenya: Current Conditions and the Challenges Ahead

Science.gov (United States)

2010-12-09

Tree 1 PPK Peoples Party of Kenya Trumpet 1 NLP National Labour Party Bull (Ndume) 1 KADDU Kenya African Democratic Development Union Fruit Basket...15%, Asian, European, and Arab 1% Religions: Protestant 45%, Roman Catholic 33%, indigenous beliefs 10%, Muslim 10%, other 2% Languages: English

Named Entity Extraction and Linking Challenge: University of Twente at #Microposts2014

NARCIS (Netherlands)

Habib, Mena Badieh; van Keulen, Maurice; Zhu, Zhemin; Rowe, Matthew; Stankovic, Milan; Dadzie, Aba-Sah

Twitter is a potentially rich source of continuously and instantly updated information. Shortness and informality of tweets are challenges for Natural Language Processing (NLP) tasks. In this paper, we present a hybrid approach for Named Entity Extraction (NEE)and Linking (NEL) for tweets. Although

GLIMPSED

DEFF Research Database (Denmark)

Klerke, Sigrid

This thesis addresses the problem of detecting complex text by exploring whether recordings of readers’ eye movements can be leveraged for learning what parts of texts obstruct readers, and investigates how this information can help improve NLP applications. The problem of detecting and handling...

Machine transliteration and transliterated text retrieval: a survey

Indian Academy of Sciences (India)

Dinesh Kumar Prabhakar

2018-06-07

Jun 7, 2018 ... Transliteration; informal information; natural language processing (NLP); information retrieval. 1. Introduction ... information is growing rapidly, making IR more challenging [1]. This .... Although Karimi et al [48] give a good account of pioneering ..... Decision Tree and Memory-Based Learning) were used for.

Developmental Foreign Accent Syndrome: report of a new case

Directory of Open Access Journals (Sweden)

Stefanie eKeulen

2016-03-01

Full Text Available This paper presents the case of a 17-year-old right-handed Belgian boy with developmental FAS and comorbid developmental apraxia of speech (DAS. Extensive neuropsychological and neurolinguistic investigations demonstrated a normal IQ but impaired planning (visuo-constructional dyspraxia. A Tc-99m-ECD SPECT revealed a significant hypoperfusion in the prefrontal and medial frontal regions, as well as in the lateral temporal regions. Hypoperfusion in the right cerebellum almost reached significance. It is hypothesized that these clinical findings support the view that FAS and DAS are related phenomena following impairment of the cerebro-cerebellar network.

A Review on Stuttering and Social Anxiety Disorder in Children: Possible Causes and Therapies/Treatments

Directory of Open Access Journals (Sweden)

Nadia Nathania

2016-12-01

Full Text Available In the past two decades, stuttering and its relation to social anxiety disorder have been researched using different approaches in study fields such as neurolinguistics and neuropsychology. This paper presents a review of research publications about social anxiety disorder in children who stutter. It takes into account studies of stuttering, social anxiety disorders, the possible causes as well as atti-tudes and beliefs towards stuttering. Also, therapies or treatments that have been conducted on both English-speaking children who stutter in the Western context and Mandarin-speaking children stut-terers in Asia, Taiwan in particular; will be looked at

A Novel Interactive MINLP Solver for CAPE Applications

DEFF Research Database (Denmark)

Henriksen, Jens Peter; Støy, S.; Russel, Boris Mariboe

2000-01-01

This paper presents an interactive MINLP solver that is particularly suitable for solution of process synthesis, design and analysis problems. The interactive MINLP solver is based on the decomposition based MINLP algorithms, where a NLP sub-problem is solved in the innerloop and a MILP master pr...

Neural Ranking Models with Weak Supervision

NARCIS (Netherlands)

Dehghani, M.; Zamani, H.; Severyn, A.; Kamps, J.; Croft, W.B.

2017-01-01

Despite the impressive improvements achieved by unsupervised deep neural networks in computer vision and NLP tasks, such improvements have not yet been observed in ranking for information retrieval. The reason may be the complexity of the ranking problem, as it is not obvious how to learn from

NudtMDP at TREC 2015 LiveQA Track

Science.gov (United States)

2015-11-20

Language Processing(NLP) method to choose the best answer, because there are many user behaviors can be used. We employed the users behavioral analysis to...and adaptive clustering algorithms for ttg. Technical report, DTIC Document, 2014. 4. George A Miller. Wordnet: a lexical database for english

Assessing lexical, syntactic, and conceptual turn-by-turn alignment in conversations involving conflict and deception

DEFF Research Database (Denmark)

Duran, Nicholas; Fusaroli, Riccardo; Paxton, Alexandra

2015-01-01

-based NLP tools, the procedure begins by taking conversational partners' turns and converting each into a lemmatized sequence of words, assigning part-of-speech tags and computing high-dimensional semantic vectors per each utterance. Words and part-of-speech tags are further sequenced into n-g! rams...

Combining Machine Learning and Natural Language Processing to Assess Literary Text Comprehension

Science.gov (United States)

Balyan, Renu; McCarthy, Kathryn S.; McNamara, Danielle S.

2017-01-01

This study examined how machine learning and natural language processing (NLP) techniques can be leveraged to assess the interpretive behavior that is required for successful literary text comprehension. We compared the accuracy of seven different machine learning classification algorithms in predicting human ratings of student essays about…

Tackling Error Propagation through Reinforcement Learning: A Case of Greedy Dependency Parsing

NARCIS (Netherlands)

Le, M.N.; Fokkens, A.S.

Error propagation is a common problem in NLP. Reinforcement learning explores erroneous states during training and can therefore be more robust when mistakes are made early in a process. In this paper, we apply reinforcement learning to greedy dependency parsing which is known to suffer from error

Non-abelian factorisation for next-to-leading-power threshold logarithms

NARCIS (Netherlands)

Bonocore, D.; Laenen, E.; Magnea, L.; Vernazza, L.; White, C.D.

2016-01-01

Soft and collinear radiation is responsible for large corrections to many hadronic cross sections, near thresholds for the production of heavy final states. There is much interest in extending our understanding of this radiation to next-to-leading power (NLP) in the threshold expansion. In this

Development, prevention, and treatment of feeding tube dependency.

Science.gov (United States)

Krom, Hilde; de Winter, J Peter; Kindermann, Angelika

2017-06-01

Enteral nutrition is effective in ensuring nutritional requirements and growth. However, when tube feeding lasts for a longer period, it can lead to tube dependency in the absence of medical reasons for continuation of tube feeding. Tube-dependent children are unable or refuse to start oral activities and they lack oral skills. Tube dependency has health-, psychosocial-, and economy-related consequences. Therefore, the transition to oral feeding is of great importance. However, this transition can be very difficult and needs a multidisciplinary approach. Most studies for treatment of tube dependency are based on behavioral interventions, such as family therapy, individual behavior therapy, neuro-linguistic programming, and parental anxiety reduction. Furthermore, oral motor therapy and nutritional adjustments can be helpful in tube weaning. The use of medication has been described in the literature. Although mostly chosen as the last resort, hunger-inducing methods, such as the Graz-model and the Dutch clinical hunger provocation program, are also successful in weaning children off tube feeding. The transition from tube to oral feeding is important in tube-dependent children but can be difficult. We present an overview for the prevention and treatment of tube dependency. What is known: • Longer periods of tube feeding can lead to tube dependency. • Tube weaning can be very difficult. What is new: • Weaning as soon as possible and therefore referral to a multidisciplinary team are recommended. • An overview of treatment options for tube dependency is presented in this article.

Radiosensitizing and cytotoxic properties of DNA targeted phenanthridine-linked nitroheterocycles of varying electron affinities

International Nuclear Information System (INIS)

Cowan, D.S.M.; Rauth, A.M.; Toronto Univ., ON; Matejovic, J.F.; McClelland, R.A.; Wardman, P.

1994-01-01

2-Nitroimidazoles targeted to DNA via intercalation have previously been shown to be as much as 10-100 times more efficient on a molar basis than the untargeted nitroimidazole, misonidazole, in vitro as hypoxic cell selective radiosensitizers and cytotoxins based on extracellular concentrations. In this work the effect of varying the nitroaromatic group has been examined through the preparation of a DNA-targeted 4-nitroimidazole (4-MeNLP-3), a 5-nitroimidazole (5-NLP-3) and a 5-nitrofuran (FEP-2) linked to phenanthridinium ions. With the previously synthesized 2-nitroimidazoles, this provides a series of DNA targeted compounds of varying electron affinity as well as structure at the nitroaromatic position. The present series of compounds was tested for partition coefficient, DNA binding ability, reduction potentials and in vitro radiosensitizing and cytotoxic abilities. The results obtained indicate that targeting such compounds to DNA diminishes the dependency of radiosensitizing and cytotoxic properties on reduction potential and may allow significant uncoupling of toxicity from radiosensitizing ability. (author)

Automated Assessment of Medical Students' Clinical Exposures according to AAMC Geriatric Competencies.

Science.gov (United States)

Chen, Yukun; Wrenn, Jesse; Xu, Hua; Spickard, Anderson; Habermann, Ralf; Powers, James; Denny, Joshua C

2014-01-01

Competence is essential for health care professionals. Current methods to assess competency, however, do not efficiently capture medical students' experience. In this preliminary study, we used machine learning and natural language processing (NLP) to identify geriatric competency exposures from students' clinical notes. The system applied NLP to generate the concepts and related features from notes. We extracted a refined list of concepts associated with corresponding competencies. This system was evaluated through 10-fold cross validation for six geriatric competency domains: "medication management (MedMgmt)", "cognitive and behavioral disorders (CBD)", "falls, balance, gait disorders (Falls)", "self-care capacity (SCC)", "palliative care (PC)", "hospital care for elders (HCE)" - each an American Association of Medical Colleges competency for medical students. The systems could accurately assess MedMgmt, SCC, HCE, and Falls competencies with F-measures of 0.94, 0.86, 0.85, and 0.84, respectively, but did not attain good performance for PC and CBD (0.69 and 0.62 in F-measure, respectively).

Payload charging events in the mesosphere and their impact on Langmuir type electric probes

Directory of Open Access Journals (Sweden)

T. A. Bekkeng

2013-02-01

Full Text Available Three sounding rockets were launched from Andøya Rocket Range in the ECOMA campaign in December 2010. The aim was to study the evolution of meteoric smoke particles during a major meteor shower. Of the various instruments onboard the rocket payload, this paper presents the data from a multi-Needle Langmuir Probe (m-NLP and a charged dust detector. The payload floating potential, as observed using the m-NLP instrument, shows charging events on two of the three flights. These charging events cannot be explained using a simple charging model, and have implications towards the use of fixed bias Langmuir probes on sounding rockets investigating mesospheric altitudes. We show that for a reliable use of a single fixed bias Langmuir probe as a high spatial resolution relative density measurement, each payload should also carry an additional instrument to measure payload floating potential, and an instrument that is immune to spacecraft charging and measures absolute plasma density.

Study on the nonlocality effects for generalized optical potentials

International Nuclear Information System (INIS)

Gurbanovich, I.S.; Zelenskaya, N.S.

1981-01-01

In previous studies the authors have ihown that the generalized optic potential (GOP) of particles interaction is a superposition of local and non local potentials (LP, NLP). On the example of α- particles scattering on the 8 Be nucleus at about 10-15 MeV the GOP nonlocal part is considered. For obtaining NLP the spectral decomposition of the Green function taking into account only contribution of relative motion of two α-particles in S-state is used. The locally-equivalent addition to central potential of α-particles scattering at 8 Be previously calculated is obtained. In a graphical form a total locally-equivalent potential and local GOP part are presented. It is shown that taking into account the nonlocallity effect in a locally energy approximation for precise wave function in S-state widen a potential hole without changing its depth. Such widening corresponds to the general character of behaviour of non local potentials calculated in the microscopic approach [ru

Text mining with R a tidy approach

CERN Document Server

Silge, Julia

2017-01-01

Much of the data available today is unstructured and text-heavy, making it challenging for analysts to apply their usual data wrangling and visualization tools. With this practical book, you'll explore text-mining techniques with tidytext, a package that authors Julia Silge and David Robinson developed using the tidy principles behind R packages like ggraph and dplyr. You'll learn how tidytext and other tidy tools in R can make text analysis easier and more effective. The authors demonstrate how treating text as data frames enables you to manipulate, summarize, and visualize characteristics of text. You'll also learn how to integrate natural language processing (NLP) into effective workflows. Practical code examples and data explorations will help you generate real insights from literature, news, and social media. Learn how to apply the tidy text format to NLP Use sentiment analysis to mine the emotional content of text Identify a document's most important terms with frequency measurements E...

Language-agnostic processing of microblog data with text embeddings

NARCIS (Netherlands)

Chrupala, Grzegorz

2014-01-01

A raw stream of posts from a microblogging platform such as Twitter contains text written in a large variety of languages and writing systems, in registers ranging from formal to internet slang. A significant amount has been expended in recent years to adapt standard NLP processing pipelines to be

Identification and characterization of serovar-independent immunogens in Actinobacillus pleuropneumoniae

DEFF Research Database (Denmark)

Antenucci, Fabio; Fougeroux, Cyrielle; Bosse, Janine T.

2017-01-01

and further characterized, both in silico and in vitro. Additionally, we analysed outer membrane vesicles (OMVs) of A. pleuropneumoniae MIDG2331 as potential immunogens, and compared deletions in degS and nlpI for increasing yields of OMVs compared to the parental strain. Our results indicated that Apf...

Intermediate Term (3-6 Years Post Surgery) Outcome of ...

African Journals Online (AJOL)

Post-operatively, the 5 eyes had VA ranging from 6/60 to NLP, after a variable follow-up period of 3-6 years. Complications included development of tough vascularized retroprosthetic membrane (4 eyes) and infective endophthalmitis in one eye. Conclusion: The intermediate-term outcome of keratoprosthesis surgery in ...

Lexical Link Analysis Application: Improving Web Service to Acquisition Visibility Portal

Science.gov (United States)

2013-09-30

during the Empire Challenge 2008 and 2009 (EC08/09) field experiments and for numerous other field experiments of new technologies during Trident Warrior...Empirical Methods in Natural Language Processing and Very Large Corpora (EMNLP/ VLC -2000) (pp. 63–70). Retrieved from http://nlp.stanford.edu/manning

Behavioral program synthesis with genetic programming

CERN Document Server

Krawiec, Krzysztof

2016-01-01

Genetic programming (GP) is a popular heuristic methodology of program synthesis with origins in evolutionary computation. In this generate-and-test approach, candidate programs are iteratively produced and evaluated. The latter involves running programs on tests, where they exhibit complex behaviors reflected in changes of variables, registers, or memory. That behavior not only ultimately determines program output, but may also reveal its `hidden qualities' and important characteristics of the considered synthesis problem. However, the conventional GP is oblivious to most of that information and usually cares only about the number of tests passed by a program. This `evaluation bottleneck' leaves search algorithm underinformed about the actual and potential qualities of candidate programs. This book proposes behavioral program synthesis, a conceptual framework that opens GP to detailed information on program behavior in order to make program synthesis more efficient. Several existing and novel mechanisms subs...

VISUAL: a software package for plotting data in the RADHEAT-V4 code system

International Nuclear Information System (INIS)

Sasaki, Toshihiko; Yamano, Naoki

1984-03-01

In this report, the features, the capabilities and the constitution of the VISUAL Software Package are presented. The one of the features is that the VISUAL provides a versatile graphic display tool to plot a wide variety of data of the RADHEAT-V4 code system. And the other is to enable a user to handle easily the executing data in the Conversational Management Mode named ''CMM''. The program adopts the adjustable dimension system to increase its flexibility. VISUAL generates two-dimensional drawing, contour line map and three dimensional drawing on TSS (Time Sharing System) digital graphic equipment, NLP (Nihongo Laser Printer) or COM(Computer Output Microfilm). It is easily possible to display the calculated and experimental data in a DATA-POOL by using these functions. The purpose of this report is to describe sufficient information to enable a user to use VISUAL profitabily. (author)

Trajectory Optimization Based on Multi-Interval Mesh Refinement Method

Directory of Open Access Journals (Sweden)

Ningbo Li

2017-01-01

Full Text Available In order to improve the optimization accuracy and convergence rate for trajectory optimization of the air-to-air missile, a multi-interval mesh refinement Radau pseudospectral method was introduced. This method made the mesh endpoints converge to the practical nonsmooth points and decreased the overall collocation points to improve convergence rate and computational efficiency. The trajectory was divided into four phases according to the working time of engine and handover of midcourse and terminal guidance, and then the optimization model was built. The multi-interval mesh refinement Radau pseudospectral method with different collocation points in each mesh interval was used to solve the trajectory optimization model. Moreover, this method was compared with traditional h method. Simulation results show that this method can decrease the dimensionality of nonlinear programming (NLP problem and therefore improve the efficiency of pseudospectral methods for solving trajectory optimization problems.

Explicit Nonlinear Model Predictive Control Theory and Applications

CERN Document Server

Grancharova, Alexandra

2012-01-01

Nonlinear Model Predictive Control (NMPC) has become the accepted methodology to solve complex control problems related to process industries. The main motivation behind explicit NMPC is that an explicit state feedback law avoids the need for executing a numerical optimization algorithm in real time. The benefits of an explicit solution, in addition to the efficient on-line computations, include also verifiability of the implementation and the possibility to design embedded control systems with low software and hardware complexity. This book considers the multi-parametric Nonlinear Programming (mp-NLP) approaches to explicit approximate NMPC of constrained nonlinear systems, developed by the authors, as well as their applications to various NMPC problem formulations and several case studies. The following types of nonlinear systems are considered, resulting in different NMPC problem formulations: Ø  Nonlinear systems described by first-principles models and nonlinear systems described by black-box models; �...

Building a comprehensive syntactic and semantic corpus of Chinese clinical texts.

Science.gov (United States)

He, Bin; Dong, Bin; Guan, Yi; Yang, Jinfeng; Jiang, Zhipeng; Yu, Qiubin; Cheng, Jianyi; Qu, Chunyan

2017-05-01

To build a comprehensive corpus covering syntactic and semantic annotations of Chinese clinical texts with corresponding annotation guidelines and methods as well as to develop tools trained on the annotated corpus, which supplies baselines for research on Chinese texts in the clinical domain. An iterative annotation method was proposed to train annotators and to develop annotation guidelines. Then, by using annotation quality assurance measures, a comprehensive corpus was built, containing annotations of part-of-speech (POS) tags, syntactic tags, entities, assertions, and relations. Inter-annotator agreement (IAA) was calculated to evaluate the annotation quality and a Chinese clinical text processing and information extraction system (CCTPIES) was developed based on our annotated corpus. The syntactic corpus consists of 138 Chinese clinical documents with 47,426 tokens and 2612 full parsing trees, while the semantic corpus includes 992 documents that annotated 39,511 entities with their assertions and 7693 relations. IAA evaluation shows that this comprehensive corpus is of good quality, and the system modules are effective. The annotated corpus makes a considerable contribution to natural language processing (NLP) research into Chinese texts in the clinical domain. However, this corpus has a number of limitations. Some additional types of clinical text should be introduced to improve corpus coverage and active learning methods should be utilized to promote annotation efficiency. In this study, several annotation guidelines and an annotation method for Chinese clinical texts were proposed, and a comprehensive corpus with its NLP modules were constructed, providing a foundation for further study of applying NLP techniques to Chinese texts in the clinical domain. Copyright © 2017. Published by Elsevier Inc.

Assessing the similarity of surface linguistic features related to epilepsy across pediatric hospitals.

Science.gov (United States)

Connolly, Brian; Matykiewicz, Pawel; Bretonnel Cohen, K; Standridge, Shannon M; Glauser, Tracy A; Dlugos, Dennis J; Koh, Susan; Tham, Eric; Pestian, John

2014-01-01

The constant progress in computational linguistic methods provides amazing opportunities for discovering information in clinical text and enables the clinical scientist to explore novel approaches to care. However, these new approaches need evaluation. We describe an automated system to compare descriptions of epilepsy patients at three different organizations: Cincinnati Children's Hospital, the Children's Hospital Colorado, and the Children's Hospital of Philadelphia. To our knowledge, there have been no similar previous studies. In this work, a support vector machine (SVM)-based natural language processing (NLP) algorithm is trained to classify epilepsy progress notes as belonging to a patient with a specific type of epilepsy from a particular hospital. The same SVM is then used to classify notes from another hospital. Our null hypothesis is that an NLP algorithm cannot be trained using epilepsy-specific notes from one hospital and subsequently used to classify notes from another hospital better than a random baseline classifier. The hypothesis is tested using epilepsy progress notes from the three hospitals. We are able to reject the null hypothesis at the 95% level. It is also found that classification was improved by including notes from a second hospital in the SVM training sample. With a reasonably uniform epilepsy vocabulary and an NLP-based algorithm able to use this uniformity to classify epilepsy progress notes across different hospitals, we can pursue automated comparisons of patient conditions, treatments, and diagnoses across different healthcare settings. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Predictive value of ocular trauma score in open globe combat eye injuries

International Nuclear Information System (INIS)

Islam, Q.

2016-01-01

Prediction of final visual outcome in ocular injuries is of paramount importance and various prognostic models have been proposed to predict final visual outcome. The objective of this study was to validate the predictive value of ocular trauma score (OTS) in patients with combat related open globe injuries and to evaluate the factors affecting the final visual outcome. Methods: Data of 93 patients admitted in AFIO Rawalpindi between Jan 2010 to June 2014 with combat related open globe ocular injuries was analysed. Initial and final best corrected visual acuity (BCVA) was categorized as No Light Perception (NLP), Light Perception (LP) to Hand Movement (HM), 1/200-19/200, 20/200-20/50, and =20/40. OTS was calculated for each eye by assigning numerical raw points to six variables and then scores were stratified into five OTS categories. Results: Mean age of study population was 28.77 ± 8.37 years. Presenting visual acuity was <20/200 (6/60) in 103 (96.23%) eyes. However, final BCVA of =20/40 (6/12) was achieved in 18 (16.82%) eyes, while 72 (67.28%) eyes had final BCVA of <20/200 (6/60). Final visual outcome in our study were similar to those in OTS study, except for NLP in category 1 (81% vs. 74%) and =20/40 in category 3 (30% vs. 41%). The OTS model predicted visual survival (LP or better) with a sensitivity of 94.80% and predicted no vision (NLP) with a specificity of 100%. Conclusion: OTS is a reliable tool for assessment of ocular injuries and predicting final visual outcome at the outset. (author)

Hyoid bone position and head posture comparison in skeletal Class I and Class II subjects: A retrospective cephalometric study

Directory of Open Access Journals (Sweden)

Pawankumar Dnyandeo Tekale

2014-01-01

Full Text Available Objective: The aim of the study was to investigate the hyoid bone position and the head posture using lateral cephalograms in subjects with skeletal Class I and skeletal Class II pattern and to investigate the gender differences. Materials and Methods: The study used lateral cephalograms of 40 subjects (20 skeletal Class I pattern; 20 skeletal Class II pattern. Lateral cephalograms were traced and analyzed for evaluation of the hyoid bone position and the head posture using 34 parameters. Independent sample t-test was performed to compare the differences between the two groups and between genders in each group. Statistical tests were performed using NCSS 2007 software (NCSST, Kaysville, Utah, USA. Results: The linear measurements between the hyoid bone (H and cervical spine (CV2ia, the nasion-sella line, palatal line nasion line, the anterior nasal spine (ANS to perpendicular projection of H on the NLP (NLP- Nasal Linear Projection (H-NLP/ANS as well as the posterior cranial points (Bo, Ar and S points were found to be less in skeletal Class II subjects. The measurement H-CV2ia was found to be less in males with skeletal Class I pattern and H-CV4ia was found to be less in males with skeletal Class II pattern. The natural head posture showed no significant gender differences. Conclusion: The position of hyoid bone was closer to the cervical vertebra horizontally in skeletal Class II subjects when compared with skeletal Class I subjects. In males, the hyoid bone position was closer to the cervical vertebra horizontally both in skeletal Class I and skeletal Class II subjects.

Computing Accurate Grammatical Feedback in a Virtual Writing Conference for German-Speaking Elementary-School Children: An Approach Based on Natural Language Generation

Science.gov (United States)

Harbusch, Karin; Itsova, Gergana; Koch, Ulrich; Kuhner, Christine

2009-01-01

We built a natural language processing (NLP) system implementing a "virtual writing conference" for elementary-school children, with German as the target language. Currently, state-of-the-art computer support for writing tasks is restricted to multiple-choice questions or quizzes because automatic parsing of the often ambiguous and fragmentary…

The Sentence Fairy: A Natural-Language Generation System to Support Children's Essay Writing

Science.gov (United States)

Harbusch, Karin; Itsova, Gergana; Koch, Ulrich; Kuhner, Christine

2008-01-01

We built an NLP system implementing a "virtual writing conference" for elementary-school children, with German as the target language. Currently, state-of-the-art computer support for writing tasks is restricted to multiple-choice questions or quizzes because automatic parsing of the often ambiguous and fragmentary texts produced by pupils…

Instructor-Aided Asynchronous Question Answering System for Online Education and Distance Learning

Science.gov (United States)

Wen, Dunwei; Cuzzola, John; Brown, Lorna; Kinshuk

2012-01-01

Question answering systems have frequently been explored for educational use. However, their value was somewhat limited due to the quality of the answers returned to the student. Recent question answering (QA) research has started to incorporate deep natural language processing (NLP) in order to improve these answers. However, current NLP…

Combining Natural Language Processing and Statistical Text Mining: A Study of Specialized versus Common Languages

Science.gov (United States)

Jarman, Jay

2011-01-01

This dissertation focuses on developing and evaluating hybrid approaches for analyzing free-form text in the medical domain. This research draws on natural language processing (NLP) techniques that are used to parse and extract concepts based on a controlled vocabulary. Once important concepts are extracted, additional machine learning algorithms,…

The Military Language Tutor (MILT)

Science.gov (United States)

1998-11-01

interactive tutor in a Pentium based laptop computer. The first version of MILT with keyboard input was designed for Spanish and Arabic and can recognize... NLP ). The goal of the MILT design team was an authoring system which would require no formal external training and which could be learned within four

Multilingual Techniques for Low Resource Automatic Speech Recognition

Science.gov (United States)

2016-05-20

linguistic and ASR expertise, and Regina, bringing in another point of view from the NLP side, really help shape the direction of some of the work in...improved keyword spotting. In Proc. ASRU, 2013. 41 [43] K. Kirchhoff and D. Vergyri. Cross-dialectal data sharing for acoustic modeling in Arabic speech

Use of Modality and Negation in Semantically-Informed Syntactic MT

Science.gov (United States)

2012-06-01

for computational linguistics. When an annotation scheme is consistent and well devel- oped, its subsequent application to NLP systems is most...example, to an Arabic –English system that has more than 100 times the amount of training data. The output in Figure 2 was produced using Moses (Koehn et

Universality of next-to-leading power threshold effects for colourless final states in hadronic collisions

NARCIS (Netherlands)

Duca, Vittorio del; Laenen, E.; Magnea, L.; Vernazza, L.; White, C.D.

2017-01-01

We consider the production of an arbitrary number of colour-singlet particles near partonic threshold, and show that next-to-leading order cross sections for this class of processes have a simple universal form at next-to-leading power (NLP) in the energy of the emitted gluon radiation. Our analysis

An intermolecular binding mechanism involving multiple LysM domains mediates carbohydrate recognition by an endopeptidase

DEFF Research Database (Denmark)

Wong, Mei Mei Jaslyn Elizabeth; Midtgaard, Søren Roi; Gysel, Kira

2015-01-01

of multiple LysM domains in substrate binding has so far lacked support from high-resolution structures of ligand-bound complexes. Here, a structural study of the Thermus thermophilus NlpC/P60 endopeptidase containing two LysM domains is presented. The crystal structure and small-angle X-ray scattering...

Generating a Spanish Affective Dictionary with Supervised Learning Techniques

Science.gov (United States)

Bermudez-Gonzalez, Daniel; Miranda-Jiménez, Sabino; García-Moreno, Raúl-Ulises; Calderón-Nepamuceno, Dora

2016-01-01

Nowadays, machine learning techniques are being used in several Natural Language Processing (NLP) tasks such as Opinion Mining (OM). OM is used to analyse and determine the affective orientation of texts. Usually, OM approaches use affective dictionaries in order to conduct sentiment analysis. These lexicons are labeled manually with affective…

A Neuro-Linguistic Model for Speech Recognition in Tone Language

African Journals Online (AJOL)

The primary aim for this work is to develop a speech recognition system that exploits the computational paradigm with learning ability and the inherent robustness and parallelism in ANN coupled with the capability of fuzzy logic to model vagueness, handling uncertainness and support for human reasoning. This research ...

About the neurolinguistics of the implicatures: abstract of a study

Directory of Open Access Journals (Sweden)

Juliano Luís Fontanari

1989-06-01

Full Text Available Taking into account recent data on linguistics of production and comprehension in aphasia, a protocol was executed including the several types of implicatures. The protocol was applied to 90 subjects classified according to the localization of cerebral lesions, as shown by CT. Results are discussed in report to clinical manifestations of brain lesions, as aphasia, apraxia, agnosia, and intelligence and pragmatics disturbances. Discussion supports the impression that there is a mechanism that correlates extra-linguistics contexts with the 'said' at the right hemisphere.

Neurolinguistics and Second Language Teaching: A View from the Crossroads

Science.gov (United States)

Rastelli, Stefano

2018-01-01

The topic of this article is the link between research on the neurocognition of the teaching--acquisition interface and research on second language teaching. This recent scientific enterprise investigates whether and how different aspects of second language instruction may change both the anatomy and the functioning of an adult learner's brain…

Recognizing speech in a novel accent: the motor theory of speech perception reframed.

Science.gov (United States)

Moulin-Frier, Clément; Arbib, Michael A

2013-08-01

The motor theory of speech perception holds that we perceive the speech of another in terms of a motor representation of that speech. However, when we have learned to recognize a foreign accent, it seems plausible that recognition of a word rarely involves reconstruction of the speech gestures of the speaker rather than the listener. To better assess the motor theory and this observation, we proceed in three stages. Part 1 places the motor theory of speech perception in a larger framework based on our earlier models of the adaptive formation of mirror neurons for grasping, and for viewing extensions of that mirror system as part of a larger system for neuro-linguistic processing, augmented by the present consideration of recognizing speech in a novel accent. Part 2 then offers a novel computational model of how a listener comes to understand the speech of someone speaking the listener's native language with a foreign accent. The core tenet of the model is that the listener uses hypotheses about the word the speaker is currently uttering to update probabilities linking the sound produced by the speaker to phonemes in the native language repertoire of the listener. This, on average, improves the recognition of later words. This model is neutral regarding the nature of the representations it uses (motor vs. auditory). It serve as a reference point for the discussion in Part 3, which proposes a dual-stream neuro-linguistic architecture to revisits claims for and against the motor theory of speech perception and the relevance of mirror neurons, and extracts some implications for the reframing of the motor theory.

The benefits of a product-independent lexical database with formal word features

NARCIS (Netherlands)

Froon, Johanna; Froon, Janneke; de Jong, Franciska M.G.

Dictionaries can be used as a basis for lexicon development for NLP applications. However, it often takes a lot of pre-processing before they are usable. In the last 5 years a product-independent database of formal word features has been developed on the basis of the Van Dale dictionaries for Dutch.

An Intelligent Computer Assisted Language Learning System for Arabic Learners

Science.gov (United States)

Shaalan, Khaled F.

2005-01-01

This paper describes the development of an intelligent computer-assisted language learning (ICALL) system for learning Arabic. This system could be used for learning Arabic by students at primary schools or by learners of Arabic as a second or foreign language. It explores the use of Natural Language Processing (NLP) techniques for learning…

Construct Validity in TOEFL iBT Speaking Tasks: Insights from Natural Language Processing

Science.gov (United States)

Kyle, Kristopher; Crossley, Scott A.; McNamara, Danielle S.

2016-01-01

This study explores the construct validity of speaking tasks included in the TOEFL iBT (e.g., integrated and independent speaking tasks). Specifically, advanced natural language processing (NLP) tools, MANOVA difference statistics, and discriminant function analyses (DFA) are used to assess the degree to which and in what ways responses to these…

Data-Driven Approaches for Paraphrasing across Language Variations

Science.gov (United States)

Xu, Wei

2014-01-01

Our language changes very rapidly, accompanying political, social and cultural trends, as well as the evolution of science and technology. The Internet, especially the social media, has accelerated this process of change. This poses a severe challenge for both human beings and natural language processing (NLP) systems, which usually only model a…

How many people constitute a crowd and what do they do ...

African Journals Online (AJOL)

Wiktionary is increasingly gaining influence in a wide variety of linguistic fields such as NLP and lexicography, and has great potential to become a serious competitor for publisher-based and academic dictionaries. However, little is known about the "crowd" that is responsible for the content of Wiktionary. In this article, we ...

Memory, Mind and Language

DEFF Research Database (Denmark)

up a number of topics in the field, among them the question of synchrony vs. diachrony in the language sciences, and issues of how to investigate the relationship between language, brain and mind. The book proposes some preliminary solutions to that problem, and, most significantly, it touches...... on both general and specific issues in theory and analysis, e.g. ‘adverbs in English and Norwegian,’ ‘verb semantics,’ ‘pronouns in Estonian,’ ‘morphology and neurolinguistics,’ ‘word order and morphology,’ ‘the nature and use of prepotions’ and ‘speech acts.’ The contributing scholars come from a variety...

Oxidative Stability and Physico-chemical Properties of Meat from Broilers Fed with Dietary Neem Leaf Powder, Spirulina and their Combination

Directory of Open Access Journals (Sweden)

Ravi KILLI

2015-12-01

Full Text Available This 6 week study was conducted to evaluate the antioxidant potential, maintaining quality and sensory properties of broiler meat from birds fed on dietary neem leaf powder (NLP. A total of 90 Vencobb broiler chicks were randomly allotted to 6 groups of 15 birds in each. Dietary treatments consisted of normal diet (control Group I, feed containing terramycin-200 (TM-200* at the concentration of 0.05% (Group II, feed containing NLP of 0.2% (Group III, feed containing NLP of 0.2% and spirulina of 1% (Group IV, feed containing TM-200 at 0.05% and spirulina of 1% (Group V and feed containing spirulina of 1% (Group VI. At the end of the experiment liver, kidney and muscle samples were collected to evaluate the tissue peroxidation (TBARS and protein carbonyls and antioxidant markers (SOD. Physico-chemical quality determinants of both fresh and preserved meat viz. extract release volume (ERV, water holding capacity (WHC and pH were also studied. TBARS protein carbonyls indicated a significant (P < 0.05 decrease in all the treated groups when compared to control. Superoxide dismutase levels were found to be significantly increased in all the treated groups, in all the tissues collected. Compared to control group, favorable physico-chemical quality determinants were recorded in all the treated groups. The sensory attributes did not show significant (P < 0.05 differences for color, flavor, juiciness, tenderness and overall acceptability. This study indicates enhanced stress tolerance levels, improved meat quality with unaffected consumer acceptance levels of the meat observed in the study, from broilers fed with neem and spirulina either alone or in combinationsș this points out that neem at 0.2% level can be used in poultry diets instead of antibiotic growth promoters (AGP.

Healthcare costs and resource utilization of patients with binge-eating disorder and eating disorder not otherwise specified in the Department of Veterans Affairs.

Science.gov (United States)

Bellows, Brandon K; DuVall, Scott L; Kamauu, Aaron W C; Supina, Dylan; Babcock, Thomas; LaFleur, Joanne

2015-12-01

The objective of this study was to compare the one-year healthcare costs and utilization of patients with binge-eating disorder (BED) to patients with eating disorder not otherwise specified without BED (EDNOS-only) and to matched patients without an eating disorder (NED). A natural language processing (NLP) algorithm identified adults with BED from clinical notes in the Department of Veterans Affairs (VA) electronic health record database from 2000 to 2011. Patients with EDNOS-only were identified using ICD-9 code (307.50) and those with NLP-identified BED were excluded. First diagnosis date defined the index date for both groups. Patients with NED were randomly matched 4:1, as available, to patients with BED on age, sex, BMI, depression diagnosis, and index month. Patients with cost data (2005-2011) were included. Total healthcare, inpatient, outpatient, and pharmacy costs were examined. Generalized linear models were used to compare total one-year healthcare costs while adjusting for baseline patient characteristics. There were 257 BED, 743 EDNOS-only, and 823 matched NED patients identified. The mean (SD) total unadjusted one-year costs, in 2011 US dollars, were $33,716 ($38,928) for BED, $37,052 ($40,719) for EDNOS-only, and $19,548 ($35,780) for NED patients. When adjusting for patient characteristics, BED patients had one-year total healthcare costs $5,589 higher than EDNOS-only (p = 0.06) and $18,152 higher than matched NED patients (p < 0.001). This study is the first to use NLP to identify BED patients and quantify their healthcare costs and utilization. Patients with BED had similar one-year total healthcare costs to EDNOS-only patients, but significantly higher costs than patients with NED. © 2015 Wiley Periodicals, Inc.

Comparing deep learning and concept extraction based methods for patient phenotyping from clinical narratives.

Science.gov (United States)

Gehrmann, Sebastian; Dernoncourt, Franck; Li, Yeran; Carlson, Eric T; Wu, Joy T; Welt, Jonathan; Foote, John; Moseley, Edward T; Grant, David W; Tyler, Patrick D; Celi, Leo A

2018-01-01

In secondary analysis of electronic health records, a crucial task consists in correctly identifying the patient cohort under investigation. In many cases, the most valuable and relevant information for an accurate classification of medical conditions exist only in clinical narratives. Therefore, it is necessary to use natural language processing (NLP) techniques to extract and evaluate these narratives. The most commonly used approach to this problem relies on extracting a number of clinician-defined medical concepts from text and using machine learning techniques to identify whether a particular patient has a certain condition. However, recent advances in deep learning and NLP enable models to learn a rich representation of (medical) language. Convolutional neural networks (CNN) for text classification can augment the existing techniques by leveraging the representation of language to learn which phrases in a text are relevant for a given medical condition. In this work, we compare concept extraction based methods with CNNs and other commonly used models in NLP in ten phenotyping tasks using 1,610 discharge summaries from the MIMIC-III database. We show that CNNs outperform concept extraction based methods in almost all of the tasks, with an improvement in F1-score of up to 26 and up to 7 percentage points in area under the ROC curve (AUC). We additionally assess the interpretability of both approaches by presenting and evaluating methods that calculate and extract the most salient phrases for a prediction. The results indicate that CNNs are a valid alternative to existing approaches in patient phenotyping and cohort identification, and should be further investigated. Moreover, the deep learning approach presented in this paper can be used to assist clinicians during chart review or support the extraction of billing codes from text by identifying and highlighting relevant phrases for various medical conditions.

Comparison of Natural Language Processing Rules-based and Machine-learning Systems to Identify Lumbar Spine Imaging Findings Related to Low Back Pain.

Science.gov (United States)

Tan, W Katherine; Hassanpour, Saeed; Heagerty, Patrick J; Rundell, Sean D; Suri, Pradeep; Huhdanpaa, Hannu T; James, Kathryn; Carrell, David S; Langlotz, Curtis P; Organ, Nancy L; Meier, Eric N; Sherman, Karen J; Kallmes, David F; Luetmer, Patrick H; Griffith, Brent; Nerenz, David R; Jarvik, Jeffrey G

2018-03-28

To evaluate a natural language processing (NLP) system built with open-source tools for identification of lumbar spine imaging findings related to low back pain on magnetic resonance and x-ray radiology reports from four health systems. We used a limited data set (de-identified except for dates) sampled from lumbar spine imaging reports of a prospectively assembled cohort of adults. From N = 178,333 reports, we randomly selected N = 871 to form a reference-standard dataset, consisting of N = 413 x-ray reports and N = 458 MR reports. Using standardized criteria, four spine experts annotated the presence of 26 findings, where 71 reports were annotated by all four experts and 800 were each annotated by two experts. We calculated inter-rater agreement and finding prevalence from annotated data. We randomly split the annotated data into development (80%) and testing (20%) sets. We developed an NLP system from both rule-based and machine-learned models. We validated the system using accuracy metrics such as sensitivity, specificity, and area under the receiver operating characteristic curve (AUC). The multirater annotated dataset achieved inter-rater agreement of Cohen's kappa > 0.60 (substantial agreement) for 25 of 26 findings, with finding prevalence ranging from 3% to 89%. In the testing sample, rule-based and machine-learned predictions both had comparable average specificity (0.97 and 0.95, respectively). The machine-learned approach had a higher average sensitivity (0.94, compared to 0.83 for rules-based), and a higher overall AUC (0.98, compared to 0.90 for rules-based). Our NLP system performed well in identifying the 26 lumbar spine findings, as benchmarked by reference-standard annotation by medical experts. Machine-learned models provided substantial gains in model sensitivity with slight loss of specificity, and overall higher AUC. Copyright © 2018 The Association of University Radiologists. All rights reserved.

De-identification of clinical notes via recurrent neural network and conditional random field.

Science.gov (United States)

Liu, Zengjian; Tang, Buzhou; Wang, Xiaolong; Chen, Qingcai

2017-11-01

De-identification, identifying information from data, such as protected health information (PHI) present in clinical data, is a critical step to enable data to be shared or published. The 2016 Centers of Excellence in Genomic Science (CEGS) Neuropsychiatric Genome-scale and RDOC Individualized Domains (N-GRID) clinical natural language processing (NLP) challenge contains a de-identification track in de-identifying electronic medical records (EMRs) (i.e., track 1). The challenge organizers provide 1000 annotated mental health records for this track, 600 out of which are used as a training set and 400 as a test set. We develop a hybrid system for the de-identification task on the training set. Firstly, four individual subsystems, that is, a subsystem based on bidirectional LSTM (long-short term memory, a variant of recurrent neural network), a subsystem-based on bidirectional LSTM with features, a subsystem based on conditional random field (CRF) and a rule-based subsystem, are used to identify PHI instances. Then, an ensemble learning-based classifiers is deployed to combine all PHI instances predicted by above three machine learning-based subsystems. Finally, the results of the ensemble learning-based classifier and the rule-based subsystem are merged together. Experiments conducted on the official test set show that our system achieves the highest micro F1-scores of 93.07%, 91.43% and 95.23% under the "token", "strict" and "binary token" criteria respectively, ranking first in the 2016 CEGS N-GRID NLP challenge. In addition, on the dataset of 2014 i2b2 NLP challenge, our system achieves the highest micro F1-scores of 96.98%, 95.11% and 98.28% under the "token", "strict" and "binary token" criteria respectively, outperforming other state-of-the-art systems. All these experiments prove the effectiveness of our proposed method. Copyright © 2017. Published by Elsevier Inc.

development of dual purpose sorghum: correlation and path

African Journals Online (AJOL)

ACSS

(Table 3). Grain yield and stem sugar traits. The correlation coefficients between grain yield and. T. ABLE 2. Correlation coefficients between grain yield and stem sugar content with selected agronomic traits in sorghum. SBX. GY. SBW. DT50F. HDL. SJS. NLP. PHT. Stem brix (SBX). 1.000. Grain yield (GY). 0.071**. 1.000.

Functional Programming

OpenAIRE

Chitil, Olaf

2009-01-01

Functional programming is a programming paradigm like object-oriented programming and logic programming. Functional programming comprises both a specific programming style and a class of programming languages that encourage and support this programming style. Functional programming enables the programmer to describe an algorithm on a high-level, in terms of the problem domain, without having to deal with machine-related details. A program is constructed from functions that only map inputs to ...

Electronic Health Record Phenotypes for Precision Medicine: Perspectives and Caveats From Treatment of Breast Cancer at a Single Institution

Science.gov (United States)

Liu, Hongfang; Maxwell, Kara N.; Pathak, Jyotishman; Zhang, Rui

2018-01-01

Abstract Precision medicine is at the forefront of biomedical research. Cancer registries provide rich perspectives and electronic health records (EHRs) are commonly utilized to gather additional clinical data elements needed for translational research. However, manual annotation is resource‐intense and not readily scalable. Informatics‐based phenotyping presents an ideal solution, but perspectives obtained can be impacted by both data source and algorithm selection. We derived breast cancer (BC) receptor status phenotypes from structured and unstructured EHR data using rule‐based algorithms, including natural language processing (NLP). Overall, the use of NLP increased BC receptor status coverage by 39.2% from 69.1% with structured medication information alone. Using all available EHR data, estrogen receptor‐positive BC cases were ascertained with high precision (P = 0.976) and recall (R = 0.987) compared with gold standard chart‐reviewed patients. However, status negation (R = 0.591) decreased 40.2% when relying on structured medications alone. Using multiple EHR data types (and thorough understanding of the perspectives offered) are necessary to derive robust EHR‐based precision medicine phenotypes. PMID:29084368

Natural language processing tools for computer assisted language learning

Directory of Open Access Journals (Sweden)

Vandeventer Faltin, Anne

2003-01-01

Full Text Available This paper illustrates the usefulness of natural language processing (NLP tools for computer assisted language learning (CALL through the presentation of three NLP tools integrated within a CALL software for French. These tools are (i a sentence structure viewer; (ii an error diagnosis system; and (iii a conjugation tool. The sentence structure viewer helps language learners grasp the structure of a sentence, by providing lexical and grammatical information. This information is derived from a deep syntactic analysis. Two different outputs are presented. The error diagnosis system is composed of a spell checker, a grammar checker, and a coherence checker. The spell checker makes use of alpha-codes, phonological reinterpretation, and some ad hoc rules to provide correction proposals. The grammar checker employs constraint relaxation and phonological reinterpretation as diagnosis techniques. The coherence checker compares the underlying "semantic" structures of a stored answer and of the learners' input to detect semantic discrepancies. The conjugation tool is a resource with enhanced capabilities when put on an electronic format, enabling searches from inflected and ambiguous verb forms.

Natural language processing and advanced information management

Science.gov (United States)

Hoard, James E.

1989-01-01

Integrating diverse information sources and application software in a principled and general manner will require a very capable advanced information management (AIM) system. In particular, such a system will need a comprehensive addressing scheme to locate the material in its docuverse. It will also need a natural language processing (NLP) system of great sophistication. It seems that the NLP system must serve three functions. First, it provides an natural language interface (NLI) for the users. Second, it serves as the core component that understands and makes use of the real-world interpretations (RWIs) contained in the docuverse. Third, it enables the reasoning specialists (RSs) to arrive at conclusions that can be transformed into procedures that will satisfy the users' requests. The best candidate for an intelligent agent that can satisfactorily make use of RSs and transform documents (TDs) appears to be an object oriented data base (OODB). OODBs have, apparently, an inherent capacity to use the large numbers of RSs and TDs that will be required by an AIM system and an inherent capacity to use them in an effective way.

Arabic text preprocessing for the natural language processing applications

International Nuclear Information System (INIS)

Awajan, A.

2007-01-01

A new approach for processing vowelized and unvowelized Arabic texts in order to prepare them for Natural Language Processing (NLP) purposes is described. The developed approach is rule-based and made up of four phases: text tokenization, word light stemming, word's morphological analysis and text annotation. The first phase preprocesses the input text in order to isolate the words and represent them in a formal way. The second phase applies a light stemmer in order to extract the stem of each word by eliminating the prefixes and suffixes. The third phase is a rule-based morphological analyzer that determines the root and the morphological pattern for each extracted stem. The last phase produces an annotated text where each word is tagged with its morphological attributes. The preprocessor presented in this paper is capable of dealing with vowelized and unvowelized words, and provides the input words along with relevant linguistics information needed by different applications. It is designed to be used with different NLP applications such as machine translation text summarization, text correction, information retrieval and automatic vowelization of Arabic Text. (author)

Integration of Neuroimaging and Microarray Datasets  through Mapping and Model-Theoretic Semantic Decomposition of Unstructured Phenotypes

Directory of Open Access Journals (Sweden)

Spiro P. Pantazatos

2009-06-01

Full Text Available An approach towards heterogeneous neuroscience dataset integration is proposed that uses Natural Language Processing (NLP and a knowledge-based phenotype organizer system (PhenOS to link ontology-anchored terms to underlying data from each database, and then maps these terms based on a computable model of disease (SNOMED CT®. The approach was implemented using sample datasets from fMRIDC, GEO, The Whole Brain Atlas and Neuronames, and allowed for complex queries such as “List all disorders with a finding site of brain region X, and then find the semantically related references in all participating databases based on the ontological model of the disease or its anatomical and morphological attributes”. Precision of the NLP-derived coding of the unstructured phenotypes in each dataset was 88% (n = 50, and precision of the semantic mapping between these terms across datasets was 98% (n = 100. To our knowledge, this is the first example of the use of both semantic decomposition of disease relationships and hierarchical information found in ontologies to integrate heterogeneous phenotypes across clinical and molecular datasets.

Extracting Various Classes of Data From Biological Text Using the Concept of Existence Dependency.

Science.gov (United States)

Taha, Kamal

2015-11-01

One of the key goals of biological natural language processing (NLP) is the automatic information extraction from biomedical publications. Most current constituency and dependency parsers overlook the semantic relationships between the constituents comprising a sentence and may not be well suited for capturing complex long-distance dependences. We propose in this paper a hybrid constituency-dependency parser for biological NLP information extraction called EDCC. EDCC aims at enhancing the state of the art of biological text mining by applying novel linguistic computational techniques that overcome the limitations of current constituency and dependency parsers outlined earlier, as follows: 1) it determines the semantic relationship between each pair of constituents in a sentence using novel semantic rules; and 2) it applies a semantic relationship extraction model that extracts information from different structural forms of constituents in sentences. EDCC can be used to extract different types of data from biological texts for purposes such as protein function prediction, genetic network construction, and protein-protein interaction detection. We evaluated the quality of EDCC by comparing it experimentally with six systems. Results showed marked improvement.

Bengali-English Relevant Cross Lingual Information Access Using Finite Automata

Science.gov (United States)

Banerjee, Avishek; Bhattacharyya, Swapan; Hazra, Simanta; Mondal, Shatabdi

2010-10-01

CLIR techniques searches unrestricted texts and typically extract term and relationships from bilingual electronic dictionaries or bilingual text collections and use them to translate query and/or document representations into a compatible set of representations with a common feature set. In this paper, we focus on dictionary-based approach by using a bilingual data dictionary with a combination to statistics-based methods to avoid the problem of ambiguity also the development of human computer interface aspects of NLP (Natural Language processing) is the approach of this paper. The intelligent web search with regional language like Bengali is depending upon two major aspect that is CLIA (Cross language information access) and NLP. In our previous work with IIT, KGP we already developed content based CLIA where content based searching in trained on Bengali Corpora with the help of Bengali data dictionary. Here we want to introduce intelligent search because to recognize the sense of meaning of a sentence and it has a better real life approach towards human computer interactions.

Post processing system for multi-dimensional thermal-hydraulic analyses

International Nuclear Information System (INIS)

Miyake, Yasuhiro; Nakane, Shigeru; Nishimura, Motohiko; Kimura, Nobuyuki

1999-12-01

In the conventional visualization system for the computational results, only Japanese (Nihongo) Line Printer (NLP) was available to print two dimensional cross sectional plots of vector and scalar fields. To evaluate the phenomena, an analyst had to print many plots on the NLP. This task makes difficult to check the computational results immediately after the calculation. Recently, as the visualization tools, we introduced Micro AVS and Field View which are utilized widely in the scientific and the industrial fields. In order to show the numerical results on the visualization software, we constructed a post processing system which convert the results of the numerical code to 'intermediate files' which can be read by the visualization tools. As using this system, the examination of the numerical results can be executed on the display of the personal computer. Furthermore, the persuasive report and paper with high quality can be produced due to the color printing. As for the transient calculation, the change of the phenomena can be visually evaluated by using the animation function. (author)

Post processing system for multi-dimensional thermal-hydraulic analyses

Energy Technology Data Exchange (ETDEWEB)

Miyake, Yasuhiro [NDD Corporation, Tokyo (Japan); Nakane, Shigeru [Nuclear Energy System Inc., Tokyo (Japan); Nishimura, Motohiko; Kimura, Nobuyuki [Japan Nuclear Cycle Development Inst., Oarai, Ibaraki (Japan). Oarai Engineering Center

1999-12-01

In the conventional visualization system for the computational results, only Japanese (Nihongo) Line Printer (NLP) was available to print two dimensional cross sectional plots of vector and scalar fields. To evaluate the phenomena, an analyst had to print many plots on the NLP. This task makes difficult to check the computational results immediately after the calculation. Recently, as the visualization tools, we introduced Micro AVS and Field View which are utilized widely in the scientific and the industrial fields. In order to show the numerical results on the visualization software, we constructed a post processing system which convert the results of the numerical code to 'intermediate files' which can be read by the visualization tools. As using this system, the examination of the numerical results can be executed on the display of the personal computer. Furthermore, the persuasive report and paper with high quality can be produced due to the color printing. As for the transient calculation, the change of the phenomena can be visually evaluated by using the animation function. (author)

Programming language for computations in the Interkosmos program

Science.gov (United States)

Schmidt, K.

1975-01-01

The programming system for Intercosmos data processing, based on the structural programming theory, which considers a program as an ordered set of standardized elementary parts, from which the user programs are automatically generated, is described. The programs are comprised of several modules, which are briefly summarized. The general structure of the programming system is presented in a block diagram. A programming control language developed to formulate the problem quickly and completely is presented along with basic symbols which are characteristic of the Intercosmos programming system.

Costate Estimation of PMP-Based Control Strategy for PHEV Using Legendre Pseudospectral Method

Directory of Open Access Journals (Sweden)

Hanbing Wei

2016-01-01

Full Text Available Costate value plays a significant role in the application of PMP-based control strategy for PHEV. It is critical for terminal SOC of battery at destination and corresponding equivalent fuel consumption. However, it is not convenient to choose the approximate costate in real driving condition. In the paper, the optimal control problem of PHEV based on PMP has been converted to nonlinear programming problem. By means of KKT condition costate can be approximated as KKT multipliers of NLP divided by the LGL weights. A kind of general costate estimation approach is proposed for predefined driving condition in this way. Dynamic model has been established in Matlab/Simulink in order to prove the effectiveness of the method. Simulation results demonstrate that the method presented in the paper can deduce the closer value of global optimal value than constant initial costate value. This approach can be used for initial costate and jump condition estimation of PMP-based control strategy for PHEV.

OPF-Based Optimal Location of Two Systems Two Terminal HVDC to Power System Optimal Operation

Directory of Open Access Journals (Sweden)

Mehdi Abolfazli

2013-04-01

Full Text Available In this paper a suitable mathematical model of the two terminal HVDC system is provided for optimal power flow (OPF and optimal location based on OPF such power injection model. The ability of voltage source converter (VSC-based HVDC to independently control active and reactive power is well represented by the model. The model is used to develop an OPF-based optimal location algorithm of two systems two terminal HVDC to minimize the total fuel cost and active power losses as objective function. The optimization framework is modeled as non-linear programming (NLP and solved by Matlab and GAMS softwares. The proposed algorithm is implemented on the IEEE 14- and 30-bus test systems. The simulation results show ability of two systems two terminal HVDC in improving the power system operation. Furthermore, two systems two terminal HVDC is compared by PST and OUPFC in the power system operation from economical and technical aspects.

Commander’s Decision Aid for Predictive Battlespace Awareness (CDA4PBA)

Science.gov (United States)

2006-12-01

plans include enhancing Natural Language Processing (NLP) capabilities, improved knowledge acquisition techniques, and meta - rule formation to capture...Reality to Understand Complex Metabolic Networks. Atlantic Symposium on Computational Biology, Genomic Information Systems & Technology, September...Based on the availability of airborne and ground-based weapon systems, data link architectures, and tactical C2 relationships, the primary outputs

Natural language processing with Java

CERN Document Server

Reese, Richard M

2015-01-01

If you are a Java programmer who wants to learn about the fundamental tasks underlying natural language processing, this book is for you. You will be able to identify and use NLP tasks for many common problems, and integrate them in your applications to solve more difficult problems. Readers should be familiar/experienced with Java software development.

Data-Driven RDF Property Semantic-Equivalence Detection Using NLP Techniques

OpenAIRE

Rico, Mariano; Mihindukulasooriya, Nandana; Gómez-Pérez, A.

2016-01-01

DBpedia extracts most of its data from Wikipedia’s infoboxes. Manually-created “mappings” link infobox attributes to DBpedia ontology properties (dbo properties) producing most used DBpedia triples. However, infoxbox attributes without a mapping produce triples with properties in a different namespace (dbp properties). In this position paper we point out that (a) the number of triples containing dbp properties is significant compared to triples containing dbo properties for the DBpedia instan...

Maine Migrant Program: 1997-1998 Program Evaluation.

Science.gov (United States)

Bazinet, Suzanne C., Ed.

The Maine Department of Education contracts with local educational agencies to administer the Maine Migrant Education Program. The program's overall mission is to provide the support necessary for migrant children to achieve Maine's academic standards. In 1997-98, 73 local migrant programs served 9,838 students, and 63 summer programs served 1,769…

Program Leadership from a Nordic Perspective - Program Leaders' Power to Influence Their Program

DEFF Research Database (Denmark)

Högfeldt, Anna-Karin; Strömberg, Emma; Jerbrant, Anna

2013-01-01

research demonstrated that program leaders have quite different positions, strategies and methods when it comes to monitoring and developing their programs. In this paper, a deeper investigation is carried out of the (im-) possibilities to make real influence on the study courses that constitutes...... the respective Engineering study programs. Eight program leaders from the five N5T universities have been interviewed, and the analysis of these studies, has culminated in a model for the analysis of program leadership for Engineering education development....

Multi-Year Program Plan - Building Regulatory Programs

Energy Technology Data Exchange (ETDEWEB)

none,

2010-10-01

This document presents DOE’s multi-year plan for the three components of the Buildings Regulatory Program: Appliance and Equipment Efficiency Standards, ENERGY STAR, and the Building Energy Codes Program. This document summarizes the history of these programs, the mission and goals of the programs, pertinent statutory requirements, and DOE’s 5-year plan for moving forward.

Program summary for the Civilian Reactor Development Program

International Nuclear Information System (INIS)

1982-07-01

This Civilian Reactor Development Program document has the prime purpose of summarizing the technical programs supported by the FY 1983 budget request. This section provides a statement of the overall program objectives and a general program overview. Section II presents the technical programs in a format intended to show logical technical interrelationships, and does not necessarily follow the structure of the formal budget presentation. Section III presents the technical organization and management structure of the program

Geothermal Technologies Program Overview - Peer Review Program

Energy Technology Data Exchange (ETDEWEB)

Milliken, JoAnn [Office of Energy Efficiency and Renewable Energy (EERE), Washington, DC (United States)

2011-06-06

This Geothermal Technologies Program presentation was delivered on June 6, 2011 at a Program Peer Review meeting. It contains annual budget, Recovery Act, funding opportunities, upcoming program activities, and more.

A Program Transformation for Backwards Analysis of Logic Programs

DEFF Research Database (Denmark)

Gallagher, John Patrick

2003-01-01

The input to backwards analysis is a program together with properties that are required to hold at given program points. The purpose of the analysis is to derive initial goals or pre-conditions that guarantee that, when the program is executed, the given properties hold. The solution for logic...... programs presented here is based on a transformation of the input program, which makes explicit the dependencies of the given program points on the initial goals. The transformation is derived from the resultants semantics of logic programs. The transformed program is then analysed using a standard...

Object-Oriented Programming in the Beta Programming Language

DEFF Research Database (Denmark)

Madsen, Ole Lehrmann; Møller-Pedersen, Birger; Nygaard, Kristen

This is a book on object-oriented programming and the BETA programming language. Object-oriented programming originated with the Simula languages developed at the Norwegian Computing Center, Oslo, in the 1960s. The first Simula language, Simula I, was intended for writing simulation programs....... Simula I was later used as a basis for defining a general purpose programming language, Simula 67. In addition to being a programming language, Simula1 was also designed as a language for describing and communicating about systems in general. Simula has been used by a relatively small community for many...... years, although it has had a major impact on research in computer science. The real breakthrough for object-oriented programming came with the development of Smalltalk. Since then, a large number of programming languages based on Simula concepts have appeared. C++ is the language that has had...

Repository-Based Software Engineering Program: Working Program Management Plan

Science.gov (United States)

1993-01-01

Repository-Based Software Engineering Program (RBSE) is a National Aeronautics and Space Administration (NASA) sponsored program dedicated to introducing and supporting common, effective approaches to software engineering practices. The process of conceiving, designing, building, and maintaining software systems by using existing software assets that are stored in a specialized operational reuse library or repository, accessible to system designers, is the foundation of the program. In addition to operating a software repository, RBSE promotes (1) software engineering technology transfer, (2) academic and instructional support of reuse programs, (3) the use of common software engineering standards and practices, (4) software reuse technology research, and (5) interoperability between reuse libraries. This Program Management Plan (PMP) is intended to communicate program goals and objectives, describe major work areas, and define a management report and control process. This process will assist the Program Manager, University of Houston at Clear Lake (UHCL) in tracking work progress and describing major program activities to NASA management. The goal of this PMP is to make managing the RBSE program a relatively easy process that improves the work of all team members. The PMP describes work areas addressed and work efforts being accomplished by the program; however, it is not intended as a complete description of the program. Its focus is on providing management tools and management processes for monitoring, evaluating, and administering the program; and it includes schedules for charting milestones and deliveries of program products. The PMP was developed by soliciting and obtaining guidance from appropriate program participants, analyzing program management guidance, and reviewing related program management documents.

Application of artifical intelligence principles to the analysis of "crazy" speech.

Science.gov (United States)

Garfield, D A; Rapp, C

1994-04-01

Artificial intelligence computer simulation methods can be used to investigate psychotic or "crazy" speech. Here, symbolic reasoning algorithms establish semantic networks that schematize speech. These semantic networks consist of two main structures: case frames and object taxonomies. Node-based reasoning rules apply to object taxonomies and pathway-based reasoning rules apply to case frames. Normal listeners may recognize speech as "crazy talk" based on violations of node- and pathway-based reasoning rules. In this article, three separate segments of schizophrenic speech illustrate violations of these rules. This artificial intelligence approach is compared and contrasted with other neurolinguistic approaches and is discussed as a conceptual link between neurobiological and psychodynamic understandings of psychopathology.

Program auto

International Nuclear Information System (INIS)

Rawool-Sullivan, M.W.; Plagnol, E.

1990-01-01

The program AUTO was developed to be used in the analysis of dE vs E type spectra. This program is written in FORTRAN and calculates dE vs E lines in MeV. The provision is also made in the program to convert these lines from MeV to ADC channel numbers to facilitate the comparison with the raw data from the experiments. Currently the output of this program can be plotted with the display program, called VISU, but it can also be used independent of the program VISU, with little or no modification in the actual fortran code. The program AUTO has many useful applications. In this article the program AUTO is described along with its applications

An introduction to artificial intelligence and its potential use in space systems.

OpenAIRE

McDonald, Gary Wayne

1986-01-01

Approved for public release; distribution is unlimited This thesis provides an introduction to Artificial Intelligence and Space Systems, with comments regarding their integration. The survey of Artificial Intelligence (AI) is based upon a review of its history, its philosophical development, and subcategories of its current technologies. These subcategories are Expert Systems (ES), Natural Language Processing (NLP), Computer Vision and Pattern Recognition, and Robotic...

Open-Source Data Collection Techniques for Weapons Transfer Information

Science.gov (United States)

2012-03-01

IR Infrared ISO International Organization for Standardization ITAR International Traffic in Arms Regulations NER Named Entity Recognition NLP ...Control Protocol UAE United Arab Emirates URI Uniform Resource Identifier URL Uniform Resource Locator USSR Union of Soviet Socialist Republics UTF...KOREA, DEMOCRATIC PEOPLE’S REPUBLIC OF North Korea KOREA, REPUBLIC OF South Korea LIBYAN ARAB JAMAHIRIYA Libya RUSSIAN FEDERATION Russia Table 3

A Playful Programming Products Vs. Programming Concepts Matrix

DEFF Research Database (Denmark)

Allsopp, Benjamin Brink

2017-01-01

to computer program: playful programming. This research also describes a project to bring together different stakeholders (developers, educators, parents and researchers) with a common vocabulary for describing, developing, teaching with and comparing these playful programming products and develops a model......A number of Danish primary schools are involved in pilot studies where 1st to 9th grade students work with Scratch and Lego MindStorms in STEM subjects. These games may become part of the curriculum at these schools. Recent research identifies a category of games and toys that support learning...... to provide educators and researchers involved in pilot studies with an overview of which programming concepts various playful programming products exercise (a playful programming products vs. programming concepts matrix). We also add additional concept specializations and expand on the descriptions...

Programming by Numbers -- A Programming Method for Complete Novices

NARCIS (Netherlands)

Glaser, Hugh; Hartel, Pieter H.

2000-01-01

Students often have difficulty with the minutiae of program construction. We introduce the idea of `Programming by Numbers', which breaks some of the programming process down into smaller steps, giving such students a way into the process of Programming in the Small. Programming by Numbers does not

Clean Coal Technology Demonstration Program: Program Update 1998

Energy Technology Data Exchange (ETDEWEB)

Assistant Secretary for Fossil Energy

1999-03-01

Annual report on the Clean Coal Technology Demonstration Program (CCT Program). The report address the role of the CCT Program, implementation, funding and costs, accomplishments, project descriptions, legislative history, program history, environmental aspects, and project contacts. The project descriptions describe the technology and provides a brief summary of the demonstration results.

Program specialization

CERN Document Server

Marlet, Renaud

2013-01-01

This book presents the principles and techniques of program specialization - a general method to make programs faster (and possibly smaller) when some inputs can be known in advance. As an illustration, it describes the architecture of Tempo, an offline program specializer for C that can also specialize code at runtime, and provides figures for concrete applications in various domains. Technical details address issues related to program analysis precision, value reification, incomplete program specialization, strategies to exploit specialized program, incremental specialization, and data speci

UNDERSTANDING THE RELATIONSHIPS OF PROGRAM SATISFACTION, PROGRAM LOYALTY AND STORE LOYALTY AMONG CARDHOLDERS OF LOYALTY PROGRAMS

Directory of Open Access Journals (Sweden)

Nor Asiah Omar

2011-01-01

Full Text Available Loyalty programs have increasingly attracted interest in both academic marketing research and practice. One major factor that has been increasingly discussed is loyalty. In this study we examine the influence of cardholders' satisfaction on loyalty (program loyalty and store loyalty in a retail context, namely, in department stores and superstores. Data were collected from 400 cardholders of a retail loyalty program in Klang Valley, Malaysia via the drop-off-and-collect technique. Structural modelling techniques were applied to analyze the data. The results indicated that program satisfaction is not related to store loyalty (share-of-wallet, share-of-visit and store preference. However, loyalty to the program (program loyalty plays a crucial intervening role in the relationship between program satisfaction and store loyalty. The study underscores the principal importance of program loyalty in the retail loyalty program.

Cerebellar induced differential polyglot aphasia: A neurolinguistic and fMRI study.

Science.gov (United States)

Mariën, Peter; van Dun, Kim; Van Dormael, Johanna; Vandenborre, Dorien; Keulen, Stefanie; Manto, Mario; Verhoeven, Jo; Abutalebi, Jubin

2017-12-01

Research has shown that linguistic functions in the bilingual brain are subserved by similar neural circuits as in monolinguals, but with extra-activity associated with cognitive and attentional control. Although a role for the right cerebellum in multilingual language processing has recently been acknowledged, a potential role of the left cerebellum remains largely unexplored. This paper reports the clinical and fMRI findings in a strongly right-handed (late) multilingual patient who developed differential polyglot aphasia, ataxic dysarthria and a selective decrease in executive function due to an ischemic stroke in the left cerebellum. fMRI revealed that lexical-semantic retrieval in the unaffected L1 was predominantly associated with activations in the left cortical areas (left prefrontal area and left postcentral gyrus), while naming in two affected non-native languages recruited a significantly larger bilateral functional network, including the cerebellum. It is hypothesized that the left cerebellar insult resulted in decreased right prefrontal hemisphere functioning due to a loss of cerebellar impulses through the cerebello-cerebral pathways. Copyright © 2017 Elsevier Inc. All rights reserved.

Collectively loading programs in a multiple program multiple data environment

Science.gov (United States)

Aho, Michael E.; Attinella, John E.; Gooding, Thomas M.; Gooding, Thomas M.; Miller, Samuel J.

2016-11-08

Techniques are disclosed for loading programs efficiently in a parallel computing system. In one embodiment, nodes of the parallel computing system receive a load description file which indicates, for each program of a multiple program multiple data (MPMD) job, nodes which are to load the program. The nodes determine, using collective operations, a total number of programs to load and a number of programs to load in parallel. The nodes further generate a class route for each program to be loaded in parallel, where the class route generated for a particular program includes only those nodes on which the program needs to be loaded. For each class route, a node is selected using a collective operation to be a load leader which accesses a file system to load the program associated with a class route and broadcasts the program via the class route to other nodes which require the program.

Clean Coal Technology Demonstration Program: Program Update 2001

Energy Technology Data Exchange (ETDEWEB)

Assistant Secretary for Fossil Energy

2002-07-30

Annual report on the Clean Coal Technology Demonstration Program (CCT Program). The report address the role of the CCT Program, implementation, funding and costs, accomplishments, project descriptions, legislative history, program history, environmental aspects, and project contacts. The project descriptions describe the technology and provides a brief summary of the demonstration results. Also includes Power Plant Improvement Initiative Projects.

An Analysis of Programming Beginners' Source Programs

Science.gov (United States)

Matsuyama, Chieko; Nakashima, Toyoshiro; Ishii, Naohiro

The production of animations was made the subject of a university programming course in order to make students understand the process of program creation, and so that students could tackle programming with interest. In this paper, the formats and composition of the programs which students produced were investigated. As a result, it was found that there were a lot of problems related to such matters as how to use indent, how to apply comments and functions etc. for the format and the composition of the source codes.

Learners Programming Language a Helping System for Introductory Programming Courses

Directory of Open Access Journals (Sweden)

MUHAMMAD SHUMAIL NAVEED

2016-07-01

Full Text Available Programming is the core of computer science and due to this momentousness a special care is taken in designing the curriculum of programming courses. A substantial work has been conducted on the definition of programming courses, yet the introductory programming courses are still facing high attrition, low retention and lack of motivation. This paper introduced a tiny pre-programming language called LPL (Learners Programming Language as a ZPL (Zeroth Programming Language to illuminate novice students about elementary concepts of introductory programming before introducing the first imperative programming course. The overall objective and design philosophy of LPL is based on a hypothesis that the soft introduction of a simple and paradigm specific textual programming can increase the motivation level of novice students and reduce the congenital complexities and hardness of the first programming course and eventually improve the retention rate and may be fruitful in reducing the dropout/failure level. LPL also generates the equivalent high level programs from user source program and eventually very fruitful in understanding the syntax of introductory programming languages. To overcome the inherent complexities of unusual and rigid syntax of introductory programming languages, the LPL provide elementary programming concepts in the form of algorithmic and plain natural language based computational statements. The initial results obtained after the introduction of LPL are very encouraging in motivating novice students and improving the retention rate.

ARABIC LIGHT STEMMER (ARS

Directory of Open Access Journals (Sweden)

ASMA AL-OMARI

2014-12-01

Full Text Available Stemming is a main step used to process textual data. It is usually used in several types of applications such as: text mining, information retrieval (IR, and natural language processing (NLP. A major task in stemming is to standardize words; which can be achieved by reducing each word to its base (root or stem. Arabic stemming is not an easy task. Unlike other languages, Arabic language is a highly inflected language, since it uses many inflectional forms. Researchers are divided on the benefit of using stemming in fields of IR, NLP...etc., since in Arabic the morphological variants of a certain word are not always semantically related. The aim of this paper is to design and implement a new Arabic light stemmer (ARS which is not based on Arabic root patterns. Instead, it depends on well defined mathematical rules and several relations between letters. A series of tests were conducted on ARS stemmer to compare its effectiveness with the effectiveness of two other Arabic stemmers. Test shows clearly the effectiveness superiority of ARS compared to effectiveness of these two Arabic stemmers.

Selected Topics on Systems Modeling and Natural Language Processing: Editorial Introduction to the Issue 7 of CSIMQ

Directory of Open Access Journals (Sweden)

Witold Andrzejewski

2016-07-01

Full Text Available The seventh issue of Complex Systems Informatics and Modeling Quarterly presents five papers devoted to two distinct research topics: systems modeling and natural language processing (NLP. Both of these subjects are very important in computer science. Through modeling we can simplify the studied problem by concentrating on only one aspect at a time. Moreover, a properly constructed model allows the modeler to work on higher levels of abstraction and not having to concentrate on details. Since the size and complexity of information systems grows rapidly, creating good models of such systems is crucial. The analysis of natural language is slowly becoming a widely used tool in commerce and day to day life. Opinion mining allows recommender systems to provide accurate recommendations based on user-generated reviews. Speech recognition and NLP are the basis for such widely used personal assistants as Apple’s Siri, Microsoft’s Cortana, and Google Now. While a lot of work has already been done on natural language processing, the research usually concerns widely used languages, such as English. Consequently, natural language processing in languages other than English is very relevant subject and is addressed in this issue.

Isolation, characterization, and stability of discretely-sized nanolipoprotein particles assembled with apolipophorin-III.

Directory of Open Access Journals (Sweden)

Nicholas O Fischer

Full Text Available BACKGROUND: Nanolipoprotein particles (NLPs are discoidal, nanometer-sized particles comprised of self-assembled phospholipid membranes and apolipoproteins. NLPs assembled with human apolipoproteins have been used for myriad biotechnology applications, including membrane protein solubilization, drug delivery, and diagnostic imaging. To expand the repertoire of lipoproteins for these applications, insect apolipophorin-III (apoLp-III was evaluated for the ability to form discretely-sized, homogeneous, and stable NLPs. METHODOLOGY: Four NLP populations distinct with regards to particle diameters (ranging in size from 10 nm to >25 nm and lipid-to-apoLp-III ratios were readily isolated to high purity by size exclusion chromatography. Remodeling of the purified NLP species over time at 4 degrees C was monitored by native gel electrophoresis, size exclusion chromatography, and atomic force microscopy. Purified 20 nm NLPs displayed no remodeling and remained stable for over 1 year. Purified NLPs with 10 nm and 15 nm diameters ultimately remodeled into 20 nm NLPs over a period of months. Intra-particle chemical cross-linking of apoLp-III stabilized NLPs of all sizes. CONCLUSIONS: ApoLp-III-based NLPs can be readily prepared, purified, characterized, and stabilized, suggesting their utility for biotechnological applications.

Analyzing Array Manipulating Programs by Program Transformation

Science.gov (United States)

Cornish, J. Robert M.; Gange, Graeme; Navas, Jorge A.; Schachte, Peter; Sondergaard, Harald; Stuckey, Peter J.

2014-01-01

We explore a transformational approach to the problem of verifying simple array-manipulating programs. Traditionally, verification of such programs requires intricate analysis machinery to reason with universally quantified statements about symbolic array segments, such as "every data item stored in the segment A[i] to A[j] is equal to the corresponding item stored in the segment B[i] to B[j]." We define a simple abstract machine which allows for set-valued variables and we show how to translate programs with array operations to array-free code for this machine. For the purpose of program analysis, the translated program remains faithful to the semantics of array manipulation. Based on our implementation in LLVM, we evaluate the approach with respect to its ability to extract useful invariants and the cost in terms of code size.

Subseabed-disposal program: systems-analysis program plan

International Nuclear Information System (INIS)

Klett, R.D.

1981-03-01

This report contains an overview of the Subseabed Nuclear Waste Disposal Program systems analysis program plan, and includes sensitivity, safety, optimization, and cost/benefit analyses. Details of the primary barrier sensitivity analysis and the data acquisition and modeling cost/benefit studies are given, as well as the schedule through the technical, environmental, and engineering feasibility phases of the program

Federal Wind Energy Program. Program summary. [USA

Energy Technology Data Exchange (ETDEWEB)

None

1978-01-01

The objective of the Federal Wind Energy Program is to accelerate the development of reliable and economically viable wind energy systems and enable the earliest possible commercialization of wind power. To achieve this objective for small and large wind systems requires advancing the technology, developing a sound industrial technology base, and addressing the non-technological issues which could deter the use of wind energy. This summary report outlines the projects being supported by the program through FY 1977 toward the achievement of these goals. It also outlines the program's general organization and specific program elements.

Automatic Construction of Java Programs from Functional Program Specifications

OpenAIRE

Md. Humayun Kabir

2015-01-01

This paper presents a novel approach to construct Java programs automatically from the input functional program specifications on natural numbers from the constructive proofs of the input specifications using an inductive theorem prover called Poiti'n. The construction of a Java program from the input functional program specification involves two phases. The theorem prover is used to construct a higher order functional (HOF) program from the input specification expressed as an existential the...

Environmental radioactive intercomparison program and radioactive standards program

Energy Technology Data Exchange (ETDEWEB)

Dilbeck, G. [Environmental Monitoring Systems Laboratory, Las Vegas, NV (United States)

1993-12-31

The Environmental Radioactivity Intercomparison Program described herein provides quality assurance support for laboratories involved in analyzing public drinking water under the Safe Drinking Water Act (SDWA) Regulations, and to the environmental radiation monitoring activities of various agencies. More than 300 federal and state nuclear facilities and private laboratories participate in some phase of the program. This presentation describes the Intercomparison Program studies and matrices involved, summarizes the precision and accuracy requirements of various radioactive analytes, and describes the traceability determinations involved with radioactive calibration standards distributed to the participants. A summary of program participants, sample and report distributions, and additional responsibilities of this program are discussed.

Medical subdomain classification of clinical notes using a machine learning-based natural language processing approach

OpenAIRE

Weng, Wei-Hung; Wagholikar, Kavishwar B.; McCray, Alexa T.; Szolovits, Peter; Chueh, Henry C.

2017-01-01

Background The medical subdomain of a clinical note, such as cardiology or neurology, is useful content-derived metadata for developing machine learning downstream applications. To classify the medical subdomain of a note accurately, we have constructed a machine learning-based natural language processing (NLP) pipeline and developed medical subdomain classifiers based on the content of the note. Methods We constructed the pipeline using the clinical ...

Empirical Studies On Machine Learning Based Text Classification Algorithms

OpenAIRE

Shweta C. Dharmadhikari; Maya Ingle; Parag Kulkarni

2011-01-01

Automatic classification of text documents has become an important research issue now days. Properclassification of text documents requires information retrieval, machine learning and Natural languageprocessing (NLP) techniques. Our aim is to focus on important approaches to automatic textclassification based on machine learning techniques viz. supervised, unsupervised and semi supervised.In this paper we present a review of various text classification approaches under machine learningparadig...

Optimization of the energy production for the Baghdara hydropower plant in Afghanistan using simulated annealing; Optimierung der Energieerzeugung fuer das Wasserkraftwerk Baghdara in Afghanistan mit simulated annealing

Energy Technology Data Exchange (ETDEWEB)

Ayros, E.; Hildebrandt, H.; Peissner, K. [Fichtner GmbH und Co. KG, Stuttgart (Germany). Wasserbau und Wasserkraftwerke; Bardossy, A. [Stuttgart Univ. (Germany). Inst. fuer Wasserbau

2008-07-01

Simulated Annealing (SA) is an optimization method analogous to the thermodynamic method and is a new alternative for optimising the energy production of hydropower systems with storage capabilities. The SA-Algorithm is presented here and it was applied for the maximization of the energy production of the Baghdara hydropower plant in Afghanistan. The results were also compared with a non-linear optimization method NLP. (orig.)

Context and Domain Knowledge Enhanced Entity Spotting in Informal Text

Science.gov (United States)

Gruhl, Daniel; Nagarajan, Meena; Pieper, Jan; Robson, Christine; Sheth, Amit

This paper explores the application of restricted relationship graphs (RDF) and statistical NLP techniques to improve named entity annotation in challenging Informal English domains. We validate our approach using on-line forums discussing popular music. Named entity annotation is particularly difficult in this domain because it is characterized by a large number of ambiguous entities, such as the Madonna album "Music" or Lilly Allen's pop hit "Smile".

Advocate: A Distributed Architecture for Speech-to-Speech Translation

Science.gov (United States)

2009-01-01

tecture, are either wrapped natural-language processing ( NLP ) components or objects developed from scratch using the architecture’s API. GATE is...framework, we put together a demonstration Arabic -to- English speech translation system using both internally developed ( Arabic speech recognition and MT...conditions of our Arabic S2S demonstration system described earlier. Once again, the data size was varied and eighty identical requests were

Adaptive control of nonlinear in parameters chaotic system via Lyapunov exponents placement

Energy Technology Data Exchange (ETDEWEB)

Ayati, Moosa [Department of Electrical Engineering, K.N. Toosi University of Technology, Sayyed Khandan Bridge, Shariati Street, Tehran (Iran, Islamic Republic of)], E-mail: Ayati@dena.kntu.ac.ir; Khaki-Sedigh, Ali [Department of Electrical Engineering, K.N. Toosi University of Technology, Sayyed Khandan Bridge, Shariati Street, Tehran (Iran, Islamic Republic of)], E-mail: sedigh@kntu.ac.ir

2009-08-30

This paper proposes a new method for the adaptive control of nonlinear in parameters (NLP) chaotic systems. A method based on Lagrangian of a cost function is used to identify the parameters of the system. Estimation results are used to calculate the Lyapunov exponents adaptively. Finally, the Lyapunov exponents placement method is used to assign the desired Lyapunov exponents of the closed loop system.

Adaptive control of nonlinear in parameters chaotic system via Lyapunov exponents placement

International Nuclear Information System (INIS)

Ayati, Moosa; Khaki-Sedigh, Ali

2009-01-01

This paper proposes a new method for the adaptive control of nonlinear in parameters (NLP) chaotic systems. A method based on Lagrangian of a cost function is used to identify the parameters of the system. Estimation results are used to calculate the Lyapunov exponents adaptively. Finally, the Lyapunov exponents placement method is used to assign the desired Lyapunov exponents of the closed loop system.