Hydrology, Water Scarcity and Market Economics

Science.gov (United States)

Narayanan, M.

2008-12-01

Research scientists claim to have documented a six-fold increase in water use in the United States during the last century. It is interesting to note that the population of the United States has hardly doubled during the last century. While this indicates higher living standards, it also emphasizes an urgent need for establishing a strong, sound, sensible and sustainable management program for utilizing the available water supplies efficiently. Dr. Sandra Postel directs the independent Global Water Policy Project, as well as the Center for the Environment at Mount Holyoke College in South Hadley, Massachusetts. Author of the 1998 book, Last Oasis: Facing Water Scarcity, Dr. Postel predicts big water availability problems as populations of so-called "water-stressed" countries jump perhaps six fold over the next 30 years. The United Nations declared the years 2005 - 2015 as the "Water for Life" decade. It is also interesting and important to observe that the Oil - Rich Middle - East suffers from water scarcity to the maximum extent. It is also recognized that almost three-quarters of the globe is covered with water. Regardless, this is salt-water and there is very limited supply of freshwater to meet the needs of exploding global population. In excess of 10,000 desalination plants operate around the world in more than a hundred countries, but such a process is expensive and may seem prohibitive for developing countries with limited resources. Farmers can cut water usage by adopting the method known as drip irrigation which is known to be highly efficient. Drip Irrigation was pioneered by Israel and the Israeli farmers documented their efficiency by reducing the water used for irrigation by more than 30 percent. Unfortunately the rest of the world has failed to follow the lead set by this Great Jewish Nation. Worldwide, hardly 1percent of irrigated land utilizes efficient drip irrigation techniques. The problem lies in the fact that water is considered to be a free

Feminist Refiguring of La Malinche in Sandra Cisneros’ Never Marry A Mexican

Directory of Open Access Journals (Sweden)

Dian Natalia Sutanto

2016-12-01

Full Text Available La Malinche, the mistress of Spanish conquistador Hernán Cortés, has evolved from a historical figure into Mexican national myth that connotes all the negative aspects of woman’s sexuality in Mexican and Mexican-American Culture. Sandra Cisneros in her Never Marry A Mexican reinterpretsLa Malinchein a more positive light and points out how women sexuality can be the site for women empowerment.By drawing on insights from feminist theories on motherhood, marriage, and incest taboo, this study identifies the way Cisneros revises the negative image of La Malinche as a dupe, passive and submissive mistress. This study identifies that Cisneros has created a strong protagonist character named Clemencia, who exerts her subjectivity and claims for her sexual agency totransgress patriarchal construction of woman passive sexuality, imposition of maternal identity as asexual mother and taboo on incestuous relationship. Cisneros’s La Malinche is no longer depicted as the victim duped by the patriarchy, but as the survivor who is able to preserve her sense of herself in the dominating patriarchal world.   DOI: https://doi.org/10.24071/llt.2015.180103

Is Storage a Solution to End Water Shortage?

Science.gov (United States)

Narayanan, M.

2009-12-01

Water shortage is a problem of supply and demand. Some authors refer to it as Water Scarcity. The author has discussed this in his previous presentation at the 2008 AGU International Conference. Part of it is reproduced here for purposes of clarification. It is important to recognize that water is essential for the survival of all life on earth. Many water-rich states have thought of water conservation as an art that is practiced mainly in the arid states. But one has to recite the famous quote: “You will never miss water till the well runs dry.” Researchers have also concluded that quantity deficiency experienced by groundwater supplies are affecting many communities around the world. Furthermore federal regulations pertaining to the quality of potable or drinking water have become more stringent (Narayanan, 2008). One must observe that water conservation schemes and efficient utilization practices also benefit the environment to a large extent. These water conservation practicies indeed have a short payback period althought it may seem that there is a heavy initial investment is required. Research scientists have studied MARR (Mean Annual River Runoff) pattern over the years and have arrived at some significant conclusions. Vörsömarty and other scientists have indicated that water scarcity exists when the demand to supply ratio exceeds the number 0.4. (Vörsömarty, 2005). Furthermore other researchers claim to have documented a six-fold increase in water use in the United States during the last century. It is interesting to note that the population of the United States has hardly doubled during the last century. This obviously, is indicative of higher living standards. Nevertheless, it also emphasizes an urgent need for establishing a strong, sound, sensible and sustainable management program for utilizing the available water supplies efficiently (Narayanan, 2008). Author of the 1998 book, Last Oasis: Facing Water Scarcity, Dr. Sandra Postel predicts big

Cleófilas and La Llorona: Latin Heroines Against Patriarchal Marginalisation in ‘El arroyo de la Llorona’, a Short Story by Sandra Cisneros

OpenAIRE

Luis fernando Gómez R

2012-01-01

This paper discusses the short story ‘El arroyo de la Llorona’ by female Mexican-American writer Sandra Cisneros. In it the main character, Cleófilas, is subject to social, emotional and economic dependence on her husband, according to the cultural constructs on female identity that are still relevant in Latin-American patriarchal societies. Due to her circumstances of complete marginalisation and domestic violence, Cleófilas chooses to avoid reality, and this avoidance not only costs her men...

The analysis of Sandra Cisneros' House on Mango Steet based on social criticism of Gloria Anzaldúa's Borderlands: La Frontera

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Špela Grum

2015-12-01

Full Text Available The article deals with the main female characters that appear in Sandra Cisneros' collection of vignettes, House on Mango Street (1991. It sheds light on their lives and motives for their actions, through social criticism of Gloria Anzaldúa and the main points she establishes in her semi-autobiographical collection of essays Borderlands: La Frontera (1999. The topics Anzaldúa addresses give an insight into the Chicano identity, and the struggle of Chicano women in particular. Through her vantage point, I discuss gender roles, the immigrants' search for identity and their quest for a more dignified life, by trying to reconcile the antagonizing forces of the different parts of their identity.

In Pompeii and Volterra the Earth Really Trembles: De-Territorialisation, European Art-Cinema, and the Fate of Neorealism in Roberto Rossellini's Journey to ltaly and Luchino Visconti's Sandra

Directory of Open Access Journals (Sweden)

Stefano Ciammaroni

2007-06-01

Full Text Available Este trabalho se utiliza de dois estudos de caso - Viagem to Italy (1953, de Roberto Rossellini e Sandra (1965, de Luchino Visconti para discutir questões políticas, historiográficas e estéticas [que interferem] no relacionamento entre o neo-realismo como cinema da nação italiana e o "cinema de arte europeu" como uma instituição desnacionalizada.

Reescribir la historia desde la frontera: reparación de la memoria en Engel des Vergessens de Maja Haderlap y Caramelo o puro cuento de Sandra Cisneros

Directory of Open Access Journals (Sweden)

Ana Gimenez Calpe

2016-04-01

Full Text Available A parir del análisis comparativo de dos novelas recientes, Engel des Vergessens, de Maja Haderlap, y Caramelo o Puro cuento, de Sandra Cisneros, el artículo examina los mecanismos empleados en los textos para  reescribir la historia nacional, recuperando y reorganizando para ello los recuerdos familiares de las narradoras protagonistas. Este proceso se produce en un contexto transnacional, en el que los límites entre países vecinos quedan cada vez más difusos. En este sentido, el artículo examina la reescritura de la memoria nacional desde la perspectiva de unos actantes determinados, esto es, de unos personajes en continuo tránsito entre fronteras.  

Cleófilas and La Llorona: Latin Heroines Against Patriarchal Marginalisation in ‘El arroyo de la Llorona’, a Short Story by Sandra Cisneros

Directory of Open Access Journals (Sweden)

Luis fernando Gómez R

2012-08-01

Full Text Available This paper discusses the short story ‘El arroyo de la Llorona’ by female Mexican-American writer Sandra Cisneros. In it the main character, Cleófilas, is subject to social, emotional and economic dependence on her husband, according to the cultural constructs on female identity that are still relevant in Latin-American patriarchal societies. Due to her circumstances of complete marginalisation and domestic violence, Cleófilas chooses to avoid reality, and this avoidance not only costs her mental well-being,but also annuls her will to make changes to her suffocating life. Oppressed by a patriarchal system,Cleófilas develops an unusual interest in the Llorona legend and, through the remembrance of this myth, these two female figures become symbols of resistance and liberation. In the story, the Llorona ceases to be the denigrated woman tradition has always made her out to be, and becomes the image of a contemporary heroine capable of challenging radical patriarchal norms.

Sandra Cisneros’s The House on Mango Street: (Collective Memory Resonating from “the Barrio”

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Jelena Nikodinoska

2014-11-01

Full Text Available  “The people I wrote about were real, for the most part, from here and there, now and then, but sometimes three real people would be braided together into one made-up person… I cut apart and stitched together events to tailor the story, gave it shape so it had a beginning, middle, and end, because real life stories rarely come to us complete. Emotions, though, can’t be invented, can’t be borrowed. All the emotions my characters feel, good or bad are mine.” (xxiii Although Sandra Cisneros draws on autobiographical elements in The House on Mango Street (1984, her novella does not stand for an autobiography, but it rather represents a collage of events, characters, and places that independently from one another constitute vignettes. These vignettes are not necessarily chronologically related, yet they make up a whole of voices, stories, colors, and movements that once reverberated along Mango Street. Through her (Cisneros’s stories, Esperanza Cordero’s stories, and Esperanza’s neighbors’ stories, Cisneros conveys the Southwestern Latino experience of the big city and the streets, of the barrios that is. Taking my cue from Cisneros’s “The House on Mango Street,” I will try to examine how personal experiences become memories and those memories transcend into stories. Is what comes from experience and memory that makes writing strong, powerful, persuasive, and to a certain extent relatable? Have Cisneros’s memories, reflected in Esperanza’s living experience and language contributed to the Latino’s collective memory of the life in the barrios coupled with racism, poverty and shame? On that note, I shall see how Maurice Halbwachs’s concept of collective memory applies to Cisneros’ story and the Latino experience, where Latinos’ memory is dependent upon the life in the barrio within which the majority were/are situated.

LA PSICOLOGIA PARAGUAYA REPRESENTADA EN LA PSICOLOGIA DE JAMES O. WHITTAKER Y SANDRA J. WHITTAKER

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José E. García

2014-01-01

Full Text Available En 1987 los psicólogos estadounidenses James O. Whittaker y Sandra J. Whittaker publicaron la cuarta edición de su famoso libro Psicología. Este fue uno de los textos de introducción más conocidos y utilizados en América Latina y a través de él muchos miles de estudiantes aprendieron sus primeros conceptos sobre la psicología. Esta edición estaba preparada especialmente para su utilización con los alumnos de habla castellana e introducía numerosos tópicos relacionados a la psicología latinoamericana. Además incluía menciones específicas a algunos psicólogos de la región y sus contribuciones a la psicología. Uno de ellos era José de Jesús Aguirre, psicólogo y sacerdote jesuita y uno de los pioneros de la psicología profesional en el Paraguay. Aguirre aplicó la teoría del filósofo holandés Gerard Heymans y su colaborador el psiquiatra Enno Dirk Wiersma con las modificaciones que unos años más tarde introdujo el psicólogo francés René Le Senne. El propósito de la investigación era el análisis de los rasgos tipológicos característicos en la población paraguaya. Con ello, Aguirre iniciaba el estudio científico de la personalidad en el Paraguay. Este artículo estudia la importancia que corresponde asignar a la investigación de Aguirre como parte del texto introductorio de Whittaker y Whittaker. Se analizan los fundamentos teóricos de la tipología de Heymans-Wiersma-Le Senne y las adaptaciones realizadas por Aguirre, además de su aplicación a una muestra superior a las setecientas personas. Esta provenía de diversos niveles educativos, tanto secundarios como universitarios. En la parte concluyente se analiza la relevancia de Aguirre y su trabajo en el contexto de la psicología paraguaya y latinoamericana.

Genetics Home Reference: age-related macular degeneration

Science.gov (United States)

... Li Y, Augustaitis KJ, Karoukis AJ, Scott WK, Agarwal A, Kovach JL, Schwartz SG, Postel EA, Brooks ... Guymer RH, Merriam JE, Francis PJ, Hannum G, Agarwal A, Armbrecht AM, Audo I, Aung T, Barile ...

"Loomakari" kui uue ühiskonnakorralduse näide / Ernest Truely ; tõlkinud Ulla Juske

Index Scriptorium Estoniae

Truely, Ernest

2009-01-01

Sandra Jõgeva kuraatoriprojektist "Loomakari" Tallinna Kunstihoones, avatud 12. aprillini. Kujundaja Tanel Saar. Sandra Jõgeva, Tanel Saare, Anthony Faroux' (Inglismaa), Jenni Juulia Wallinheimo (Soome) ja Kjetil Kauslandi (Norra) töödest

124---14 Dec 2009.indd [FINAL VERSION].indd

African Journals Online (AJOL)

2009-12-14

Dec 14, 2009 ... convinced as Danny Postel (2006:15) was three years ago, during the most .... Every forty days, the masses re-appeared to mourn, as Shi'ite. Muslims do, the ...... the modernising of Islamic countries in a European fashion.

Amet kohustab / Sandra Peetso

Index Scriptorium Estoniae

Peetso, Sandra

2008-01-01

18.-22. okt. Pärnu teatris Endla toimunud rahvusvahelisest laste- ja noorteteatrite festivalist "NB festival 2008". Pikemalt lavastustest "Võimaluste aed" (Prantsuse teatritrupp Association 16 rue de Plaisance), "Sailor & Pekka" (Rootsi teater TRE), "Misantroop" (VAT-teater), "Maria Bonita" (Taani teater Batida), "Avatud ring" (Leedu teatrilabor Open Circle)

Leningradi aktsioonid / Sandra Jõgeva

Index Scriptorium Estoniae

Jõgeva, Sandra, 1976-

2006-01-01

Eesti kunstnike väljapanekust "Empty Spaces and their Occupants" 12.-24. augustini 2006 a. toimuval Peterburi Maneezhi 6. rahvusvahelisel eksperimentaalkunsti festivalil, kuraator Maksim Surin. Osalevad Kaido Ole, Merike Estna, Meeland Sepp jt

Spatially and temporally explicit water footprint accounting

NARCIS (Netherlands)

Mekonnen, Mesfin

2011-01-01

The earth’s freshwater resources are subject to increasing pressure in the form of consumptive water use and pollution (Postel, 2000; WWAP, 2003, 2006, 2009). Quantitative assessment of the green, blue and grey water footprint of global production and consumption can be regarded as a key in

Anmeldelse af: Bruner og de små børns læring

DEFF Research Database (Denmark)

Christensen, Bodil

2013-01-01

Anmeldelse af: Bruner og de små børns læring - en introduktion af Sandra Smidt, Hans Reitzels Forlag, 2013.......Anmeldelse af: Bruner og de små børns læring - en introduktion af Sandra Smidt, Hans Reitzels Forlag, 2013....

Kuues "Diverse. Universe" / Sandra Jõgeva

Index Scriptorium Estoniae

Jõgeva, Sandra, 1976-

2010-01-01

Non Grata korraldatud rahvusvaheline performance'i-kunsti festival "Diverse Universe 2010" Pärnu Kunstihallis ja Pärnu Kunstnike Majas 23. ja 24. aprillil. Rühmituste Juurikasvu (Soome), Cnopt (Eesti), Rubensid (Eesti), Ornicart (Prantsusmaa), Zane Matule ja Gatis Vectirānsi (Läti) jt. performance'itest

1409-IJBCS-Article-Sandra Farias+

African Journals Online (AJOL)

hp

reduction, promoting greater social contact, and represent a ... Uberlândia-Brazil (CEP/UFU), receiving the .... Table 4: Profile of research subjects. .... Improvement of Higher Education Personnel ... Biominerals Company and to the teacher.

Positive predictive value of the infant respiratory distress syndrome diagnosis in the Danish National Patient Registry

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Thygesen SK

2013-08-01

Full Text Available Sandra Kruchov Thygesen, Morten Olsen, Christian Fynbo ChristiansenDepartment of Clinical Epidemiology, Aarhus University Hospital, Aarhus, DenmarkBackground: Infant respiratory distress syndrome (IRDS is the most common respiratory disease in preterm infants, and is associated with considerable morbidity and mortality. Valid data on IRDS are important in clinical epidemiological research.Objectives: The objective of this study was to estimate the positive predictive value (PPV of the IRDS diagnosis registered in the population-based Danish National Patient Registry according to the International Classification of Diseases, 8th and 10th revisions.Methods: Between January 1, 1977 and December 31, 2008, we randomly selected three patients per year, 96 in total, who were registered with an IRDS diagnosis in the Danish National Patient Registry and living in the northern part of Denmark. Data on the infants included information on the presence of predefined clinical symptoms. We defined IRDS as the presence of at least two of four clinical symptoms (tachypnea, retractions or nasal flaring, grunting, and central cyanosis, which had to be present for more than 30 minutes. Using medical record review as the reference standard, we computed the positive predictive value of the registered IRDS diagnosis including 95% confidence intervals (CIs.Results: We located the medical record for 90 of the 96 patients (94%, and found an overall PPV of the IRDS diagnosis of 81% (95% CI 72%–88%. This did not vary substantially between primary and secondary diagnoses. The PPV was higher, at 89% (95% CI 80%–95%, for preterm infants born before 37 weeks of gestation.Conclusion: The PPV of the IRDS diagnosis in the Danish National Patient Registry is reasonable when compared with symptoms described in the corresponding medical records. The Danish National Patient Registry is a useful data source for studies of IRDS, particularly if restricted to preterm infants

Labral Reattachment in Femoroacetabular Impingement Surgery Results in Increased 10-year Survivorship Compared With Resection.

Science.gov (United States)

Anwander, Helen; Siebenrock, Klaus A; Tannast, Moritz; Steppacher, Simon D

2017-04-01

Since the importance of an intact labrum for normal hip function has been shown, labral reattachment has become the standard method for open or arthroscopic treatment of hips with femoroacetabular impingement (FAI). However, no long-term clinical results exist evaluating the effect of labral reattachment. A 2-year followup comparing open surgical treatment of FAI with labral resection versus reattachment was previously performed at our clinic. The goal of this study was to report a concise followup of these patients at a minimum of 10 years. We asked if patients undergoing surgical hip dislocation for the treatment of mixed-type FAI with labral reattachment compared with labral resection had (1) improved hip pain and function based on the Merle d'Aubigné-Postel score; and (2) improved survival at 10-year followup. Between June 1999 and July 2002, we performed surgical hip dislocation with femoral neck osteoplasty and acetabular rim trimming in 52 patients (60 hips) with mixed-type FAI. In the first 20 patients (25 hips) until June 2001, a torn labrum or a detached labrum in the area of acetabular rim resection was resected. In the next 32 patients (35 hips), reattachment of the labrum was performed. The same indications were used to perform both procedures during the periods in question. Of the 20 patients (25 hips) in the first group, 19 patients (95%) (24 hips [96%]) were available for clinical and/or radiographic followup at a minimum of 10 years (mean, 13 years; range, 12-14 years). Of the 32 patients (35 hips) in the second group, 29 patients (91%) (32 hips [91%]) were available for clinical and/or radiographic followup at a minimum of 10 years (mean, 12 years; range, 10-13 years). We used the anterior impingement test to assess pain. Function was assessed using the Merle d'Aubigné- Postel score and ROM. Survivorship calculation was performed using the method of Kaplan-Meier with failure defined as conversion to THA, progression of osteoarthritis (of one

Measuring Cooperative Biological Engagement Program (CBEP) Performance: Capacities, Capabilities, and Sustainability Enablers for Biorisk Management and Biosurveillance

Science.gov (United States)

2014-01-01

Monica, Calif.: RAND Corporation, MG-662-OSD, 2008. As of May 21, 2014: http://www.rand.org/pubs/monographs/MG662.html de Sa, Joia , Sandra Mounier...Hanvoravongchai, Piya, Wiku Adisasmito, Pham Ngoc Chau, Alexandra Conseil, Joia de Sa, Ralf Krumkamp, Sandra Mounier-Jack, Bounlay Phommasack...This work should be of interest to CBEP and CTR leadership as they seek to improve program design , budget allocation, and execution and to

Radiologic contribution to the extracorporeal lithotripsy treatment of calyceal diverticular calculi

International Nuclear Information System (INIS)

Papanicolaou, N.; Pfister, R.C.; Stafford, S.A.

1987-01-01

The authors reviewed the radiologic studies in 19 patients with calyceal diverticular calculi treated with extracorporeal lithotripsy (EL) in order to establish criteria predicting successful outcome. Pre-EL imaging was performed to evaluate the size of calculus in relation to the diverticular cavity, and the width of the connection of the diverticulum to the adjacent calyx. Post-EL studies were performed to assess fragmentation and passage of fragments. EL fragmented calculi in 15 diverticula with cavities larger than stone volume. Complete passage of fragments was shown in five patients and partial passage in two, all with wide diverticular necks. No passage was seen in eight diverticular with fragmented calculi, five of which had narrow or nondemonstrable necks. The radiologic demonstration of large diverticular correlates well with effective EL fragmentation, and a wide neck results in satisfactory fragment passage. Calculi in tight, narrowly communicating diverticula are unlikely to respond to EL

Cyber Practices: What Can the U.S. Air Force Learn from the Commercial Sector?

Science.gov (United States)

2015-01-01

dam/lockheed/data/isgs/documents/LMCSA%20Ov erview%20Fact%20Sheet_Final%20%282%29. pdf Lunt, Barry, Joseph J. Ekstrom, Sandra Gorka, Gregory Hislop ...Electronics Engineers, 2006, p. 33. 21 Barry Lunt, Joseph J. Ekstrom, Sandra Gorka, Gregory Hislop , Reza Kamali, Eydie Lawson, Richard LeBlanc, Jacob Miller...1 (January 1980 ). 106 Daft, 2008, p. 17. 107 Gerald D. Bell, “Determinants of Span of Control,” American Journal of Sociology 73, no. 1 (1967

International Space Station Systems Engineering. Case Study

Science.gov (United States)

2010-01-01

negotiators to move beyond an impasse.108  Don’t be so ready to chase revolutionary designs over evolutionary designs. A key lesson from Russian...112 2002 Oct. 7 2002 Oct. 18 9A S1 truss delivery Jeffrey S. Ashby, Pamela A. Melroy, David A. Wolf, Piers J. Sellers, Sandra H. Magnus , Fyodor...2002 Oct. 18 9A S1 truss delivery Jeffrey S. Ashby, Pamela A. Melroy, David A. Wolf, Piers J. Sellers, Sandra H. Magnus , Fyodor N. Yurchikhin

Nooremas keskeas klassikute nukuteater / Sandra Jõgeva

Index Scriptorium Estoniae

Jõgeva, Sandra, 1976-

2010-01-01

Silja Saarepuu ja Villu Plingi näitus "Aknal" Pärnu Kunstihallis 28. veebruarini 2010. Suure osa eksponeeritud loomingust hõlmab nn väikeste inimeste teema. Jasper Zoova ruumiliste maalide näitus "Jass tuli koju" Jazz Cafés Pärnus 3. märtsini 2010

Mitmekülgne universum / Sandra Jõgeva

Index Scriptorium Estoniae

Jõgeva, Sandra, 1976-

2008-01-01

26. V toimunud tegevuskunstifestivali "Diverse Universe 2008" performance''i-konverentsist Pärnus Academia Non Grata majas. Tutvustati kollektiive HorseCow (California, Sacramento), GoGoTrash (Kesselberg), Berliini kunstnikerühmitust Open Space, 500 korea performance'i-kunstnikku koondavat isetekkelist organisatsiooni KOPAS - Korea Performance Art Spirit, ettekandega esines Brightoni kunstnik Orion Maxted

Smells Like Teen Spirit / Sandra Jõgeva

Index Scriptorium Estoniae

Jõgeva, Sandra, 1976-

2009-01-01

Kuigi on majanduslik langus, tekib praegu juurde loomelinnakuid ja kultuuriruume (Rotermanni loovala, Baltika loomeinkubaator, Telliskivi loomelinnak jne.). Riia kesklinnas olid septembris projekti Survival Kit raames avatud ajutised kunstigaleriid südalinna äripindadel. Autori sõnul on õhus üheksakümnendate hõngu, vanad jõuvahekorrad enam ei kehti, tekib uusi võimalusi

Paraproletariaat ja vilets Valgre / Sandra Jõgeva

Index Scriptorium Estoniae

Jõgeva, Sandra, 1976-

2008-01-01

Eesti Kunstiakadeemia interdistsiplinaarsete kunstide osakonna ning Pärnu filmi- ja videofestivali alternatiivkino "Le Cinema Extraordinaire" (kuraatorid Erik Alalooga ja Ville-Karel Viirelaid) Tallinnas Nongrata Kunstikonteineris kultuuritehases Polymer 1.-22. II. Minna Hindi autoriõhtu (filmid "Kolm pilti elust ja ajast" ning "Sees või väljas") ja Jaan-Jürgen Klausi filmid "Sinitäheke" (peategelane Erkki Hüva) ning "Erakpoeet Marko Kompus"

Los géneros efímeros: el caso del programa de mano

OpenAIRE

Sánchez, Sandra

2014-01-01

Fil: Di Stéfano, Mariana. Universidad Nacional de las Artes. Área Transdepartamental de Crítica de Artes. Instituto de Investigación y Experimentación en Arte y Crítica; Argentina Fil: Sánchez, Sandra. Universidad Nacional de las Artes. Área Transdepartamental de Crítica de Artes. Instituto de Investigación y Experimentación en Arte y Crítica; Argentina Fil: Sánchez, Sandra. Universidad de Ciencias Empresariales y Sociales; Facultad de Ciencias de la Comunicación; Argentina. Fil: Di ...

MFIRE-2: A Multi Agent System for Flow-Based Intrusion Detection Using Stochastic Search

Science.gov (United States)

2012-03-01

Algorithms to pattern recognition comes from Radtke et al. [72]. The authors apply Multi- Objective Genetic Algorithms (MOGAs) to two parts of a handwritten...Postel, J.B. “User Datagram Protocol. RFC 768”, 1980. [72] Radtke , Paulo V. W., Robert Sabourin, and Tony Wong. “Classification system optimization...Rennes 1, Suvisoft, La Baule (France), 10 2006. URL http://hal.inria.fr/inria-00104200/en/. [73] Radtke , P.V.W., T. Wong, and R. Sabourin. “A multi

Spatially and temporally explicit water footprint accounting

OpenAIRE

Mekonnen, Mesfin

2011-01-01

The earth’s freshwater resources are subject to increasing pressure in the form of consumptive water use and pollution (Postel, 2000; WWAP, 2003, 2006, 2009). Quantitative assessment of the green, blue and grey water footprint of global production and consumption can be regarded as a key in understanding the pressure put on the global freshwater resources. The overall objective of this thesis is, therefore, to analyse the spatial and temporal pattern of the water footprint of humans from both...

A contemplation in negation and emphasizes of outstanding philosophers of Tehran philosophy school in immortality of subject in substantial movement.

Directory of Open Access Journals (Sweden)

mohamad khosravi farsani

2015-03-01

Full Text Available Agha Ali and Jelveh ,two of outstanding of Tehran philosophy school, have reconsidered Sandra's opinions in two opposite sides. Agha Ali is the claimant of negation and ambiguity in most of Sandra's opinions while emphasizing on transcendent theosophy foundations ,and he tries to make these ambiguities clear .However , Jelveh follows Avicenna's way and has the idea of criticizing Sandra .This article has chosen the problem Of immortality of subject in substantial movement between all debates of these two philosophers of the same age.in this essay we are going to survey Agha Ali's claims in his new explantation in one hand ,and survey and criticize the new explanation of Jelveh in negation Of substantial movement .One of the consequences of surveying and criticizing these two philosophers is that we recognize Agha Ali has succeeded in making Sadra's opinions clear by presenting a new explanation of substantial movement subject. However ,Jelveh has merged Sadra's opinions with Avicenna's instead of debilitating Sadra's opinions and stabilizing Avicenna's opinions.

Pärnu kunstnikud tagasi kodus / Sandra Jõgeva

Index Scriptorium Estoniae

Jõgeva, Sandra, 1976-

2011-01-01

Pärnust pärit kunstnike näitus "Tagasi koju" Pärnu Linnagaleriis 13. augustini 2011. Kuraator Mari Kartau, kunstnikud Kaarel Kurismaa, Mari Kurismaa, Malle Leis, Marco Laimre, Maiu Rõõmus, Flo Kasearu, Elin Kard

Kaasaegne kunst kui ekstreemne meelelahutus / Sandra Jõgeva

Index Scriptorium Estoniae

Jõgeva, Sandra, 1976-

2005-01-01

Tutvustatakse kümmet kaasaegset kunstirühmitust ja -projekti: USA anonüümne kollektiiv The Yes Men, rahvusvaheline rühmitus The Biotic Pie Bacing Brigade, Hispaania rühmitus Yomango, taani disainerite rühmitus N55, poolaka Krzystof Wodiczko projekt, USA rühmitus Basekamp, Austraalia tegevuskunstniku Stelarc' projekt, USA rühmitus Pink Bloque ja Inglismaa rühmitus My Dads Strip Club

Lagunenud valitsusega Pakistan vaevleb kriisis / Sandra Maasalu

Index Scriptorium Estoniae

Maasalu, Sandra

2008-01-01

Ilmunud ka: Postimees : na russkom jazõke 27. aug. 2008, lk. 7. Pakistani valitsuse lagunemisest, kui endine peaminister Navaz Sharif oma parteiga koalitsioonist lahkus. Vt. samas: Pakistani ahistavad separatistid ja majanduse allakäik. Kaart: Pakistan

Homme kell 13 algab Von Krahli teatris...

Index Scriptorium Estoniae

2005-01-01

III rahvusvaheline video ja performance'i festival "Inport 2005", mille on kokku pannud Gert Hatsukov. Loetletud aktsioonide autorid (Eesti: Sandra Jõgeva, Yellow Wolfman [Andrus Joonas], Andres Tenusaar)

Vetshera estonskogo iskusstva / Ruta Pels

Index Scriptorium Estoniae

Pels, Ruta, 1960-

2001-01-01

Eesti kunsti õhtutest Suurbritannia saadiku residentsis Tallinnnas, partneriks La Galerie Passage. Iga kuu muutuvas kunstikollektsioonis olevatest eesti kunstnike töödest (Rein Tammik, Malle Leis, Sandra Jõgeva jt.)

77 FR 16249 - Notice of Cancellation of Customs Broker Licenses

Science.gov (United States)

2012-03-20

... Dependable International Services 12574 New Orleans. and Transport, Inc.. Professional Customs Brokers, Inc.... Horizon Logistics, LLC 28432 Dallas. Sandra L. Smith 15266 Dallas. Barry E. Booth 09627 San Francisco...

Kolmapäeval kroonitakse Raekoja platsil Lucia

Index Scriptorium Estoniae

2006-01-01

Püha Lucia ehk luutsinapäeval kroonitakse heade jõulude kehastaja ja soojuse ning valguse tooja Lucia. Krooni valmistas Rootsi suursaatkonna algatatud konkursi võitja Sandra Savelli Eesti Kunstiakdeemiast

76 FR 8739 - Granting of Request for Early Termination of the Waiting Period Under the Premerger Notification...

Science.gov (United States)

2011-02-15

... Equity Investors V, L.P. 20110468 G New Generations Trust; Thomas and Dafna Kaplan; New Generations Trust... Corporation; Exxon Mobil Corporation; TSRC Corporation. FOR FURTHER INFORMATION CONTACT: Sandra M. Peay...

Plaadid / Immo Mihkelson

Index Scriptorium Estoniae

Mihkelson, Immo, 1959-

2002-01-01

Uutest plaatidest Mike Oldfield "Collection", Compay Segundo "Duets", Sandra "Wheel Of Time", "Spirit Of Africa", Paddy's "Irish Folk", Edwin Collins "Doctor Syntax", Doors "Live in Hollywood", Sonic Youth "Murray Street"

Pink Pungi näitusel valgub veri linale / Raimu Hanson

Index Scriptorium Estoniae

Hanson, Raimu, 1957-

2006-01-01

Kunstirühmituse Pink Punk (Sandra Jõgeva, Kristin Kalamees, Aino Ingrid Sepp, Kaarel Sammet) näitusest Y-galeriis. Lähemalt videoinstallatsioonist "Must turg" ja ruumiinstallatsioonist "Elulähedane kogemus"

Animaalne antimagnetism / Mari Laaniste

Index Scriptorium Estoniae

Laaniste, Mari, 1977-

2009-01-01

Rahvusvaheline grupinäitus "Loomakari" Tallinna Kunstihoones kuni 12. aprillini. Kuraator Sandra Jõgeva, kujundaja Tanel Saar. Lühidalt Jenni Juulia Wallinheimo, Kjetil Kauslandi ja Loore Emilie Raavi töödest

76 FR 76411 - Ocean Transportation Intermediary License; Reissuance

Science.gov (United States)

2011-12-07

... Customs October 28, 2011. Brokers, 1386 Salford, Houston, TX 77032. 017582F Trans Global Logistics, Inc., 1 Conan Drive, Midland City, AL 36350. Sandra L. Kusumoto, Director, Bureau of Certification and...

Romance With America: Americanization in the Bluest Eye and The House on Mango Street

National Research Council Canada - National Science Library

Bronson, Niko

2000-01-01

.... Reading Toni Morrison's The Bluest Eye and Sandra Cisneros' The House on Mango Street in a comparative context allows an investigation of parallel identity issues that are represented through cultural specificity.

Noortenäidend kulgeb teismeliste tempos / Sandra Sillaots

Index Scriptorium Estoniae

Sillaots, Sandra

2009-01-01

Pärnu Endla teatris etendunud lavastusest "Oma elu superstaarid". Autorid Triinu ja Laura-Marie Ojalo, lavastaja Enn Keerd, kunstnik Tuulikki Ojalo. Ka peategelase Eliis Vaiksaare (Lenna) osatäitmisest

Eesti koomiks ja I Eesti koomiksibiennaal / Toomas Verrev

Index Scriptorium Estoniae

Verrev, Toomas, 1979-

2010-01-01

I Eesti Koomiksibiennaal Kultuuritehase Polymer Kunstikonteineris Tallinnas 16. aprillist 23. maini. Kuraatorid Elisabeth Salmin ja Sandra Jõgeva. Esitleti Ed Labetski ja Ago Visaki koomiksit "Kalevipoeg" ning Elisabeth Salmini koomiksikogumikku "Simulant ja teised"

African Safety Promotion: A Journal of Injury and Violence ...

African Journals Online (AJOL)

. Richard Matzopoulos, Ashley van Niekerk, Sandra Marais, Hilton Donson. A Qualitative Evaluation of Medico-Legal Services in Gauteng, South Africa: Service Accessibility and Quality of Care to Rape Survivors. Shahnaaz Suffla, Mohamed ...

Veri, glamuur ja jänesed kirstus / Ave Randviir

Index Scriptorium Estoniae

Randviir, Ave, 1981-

2006-01-01

Näitus "Leave like a Lady" Draakoni galeriis, autorid Sandra Jõgeva & Kristin Kalamees, "Paradiis" Hobusepea galeriis, autor Marianne Männi ja "Väikeloomade surnuaed" HOP galeriis, autorid Ester Faiman ja Argo Männik

Под сенью комиксов в цвету /Николай Караев

Index Scriptorium Estoniae

Караев, Николай, 1978-

2010-01-01

Eesti I Koomiksibiennaal Kultuuritehase Polymer Kunstikonteineris Tallinnas alates 16. aprillist. Kuraatorid on Elisabeth Salmin ja Sandra Jõgeva. Esitletakse kollektiivselt loodud kunstnikuraamatut "Comic Magazine", toimub kirjanduslike kohtumiste seeria "Üks hullem kui teine" koomiksieri

76 FR 34972 - USG Pipeline Company; Notice of Application

Science.gov (United States)

2011-06-15

.... Forshay or Sandra E. Safro, Sutherland Ashbill & Brennan LLP, 1275 Pennsylvania Avenue, Washington [email protected]sutherland.com , [email protected]sutherland.com or [email protected]sutherland.com . There are two ways...

75 FR 12749 - Ocean Transportation Intermediary License Reissuances

Science.gov (United States)

2010-03-17

... Logistics, Inc., February 13, 2010. One Cross Island Plaza, Suite 203-G, Rosedale, NY 11422. 018250F.... 021870N AKM International, LLC, 301 February 19, 2010. Varick Street, Jersey City, NJ 07302. Sandra L...

Kinship and Beyond: The Genealogical Model Reconsidered

Directory of Open Access Journals (Sweden)

Ryan Schram

2010-08-01

Full Text Available Review of Kinship and Beyond: The Genealogical Model Reconsidered. Sandra Bamford and James Leach, eds. 2009. Berghahn Books, New York. 292 pp., 21 illustrations, bibliography, index. $95.00 (hardback. ISBN 9781845454227.

Etenduskunsti eetikast / Mari Saat

Index Scriptorium Estoniae

Saat, Mari, 1947-

2007-01-01

Pärnu nüüdiskunsti festivalil toimunud performance'i ja seal esinenud Eesti rahvusmeeskoori konfliktist. Näituse "Kehaturg" avamisel toimunud performance'ist "Kadalipp". Kommenteerivad Andrus Kallastu, Al paldrok, Ville-Karel Viirelaiu ja Sandra Jõgeva

PUBLICATIONS and PRESENTATIONS | ITSC

Science.gov (United States)

Ranganath, Heggere S Ranganathan, J. Rao, S Raskin, Rob Raven, P H Redman, Sandra Reed, D Reed, Daniel Months Blakeslee RJ, Stewart MF, Hawkins DL, Mach DM, Wharton NA, Ranganathan J, He Y, Flynn SE, Garrett

Десятка самых прибыльных актеров / Кая Коовит

Index Scriptorium Estoniae

Коовит, Кая, 1968-

2010-01-01

10 kõige enam teenivat Hollywoodi näitlejat (Quigley Publishing' andmeil) on Denzel Washington, Shia LaBeouf, Brad Pitt, Meryl Streep, Tom Hanks, Robert Downey jr., George Clooney, Matt Damon, Johnny Depp ja Sandra Bullock

Tudengite hea esinemine Willem C. Vis'i nimelisel harjutuskohtuvõistlusel

Index Scriptorium Estoniae

2013-01-01

XX Willem C. Vis’i nimelise rahvusvahelise kaubandusõiguse harjutuskohtuvõistlusel Viinis saavutas Tartu Ülikooli õigusteaduskonna võistkond (Kristina Promet, Jaana Lints, Edgar-Kaj Velbri ja Sandra-Kristin Noot) 290 ülikooli seast 84. koha

Celiac Family Health Education Video Series

Medline Plus

Full Text Available ... you, Boston Children's is a place where we can write the greatest children's stories ever told. Sandra ... and CEO Connect with Boston Children's Hospital How can we help? Close How can we help? Request ...

Fiftieth Anniversary at the summit : neither fear of heights nor the cold succeeded in cooling the ardour of four brave climbers from CERN who celebrated CERN's 50th Anniversary at the summit of Mount Kilimanjaro (5,895 metres).

CERN Multimedia

2005-01-01

On the way back from the summit, Miguel Cerqueira Bastos (AB/PO), David Collados Polidura (IT/GM), Sandra Sequeira Tavares (PH/CMI) and Daniel Cano Ott (n_TOF) raised the official CERN Jubilee flag at 4750 metres altitude.

Kolga koolis andsid tunde hiinlased / Ülle Tamm

Index Scriptorium Estoniae

Tamm, Ülle

2016-01-01

Tallinna Ülikooli Konfutsiuse Instituudi neli õppejõudu - Zhuoya Wu, Xiuping Huang, Sandra Sainio ja Kristiina Kraft viisid Kolga koolis toimunud Hiina päeval läbi töötubasid ja loenguid hiina keelest ja kultuurist

Nuestra experiencia con el minivástago femoral de disco a compresión y el cotilo Hedrocel (tantalio)

OpenAIRE

Acosta Fle, José María; Alonso Barrio, José Antonio; Mencía Barrio, Ricardo; Fernández Hernández, O.; González Fernández, J.J.; Sánchez Herráez, S.

2005-01-01

Durante los años 2000 a 2002 intervinimos 18 pacientes de artrosis o necrosis sintomática de cadera, con minivástago de fijación metafisiaria de Disco a Compresión (Sulzer) y cotilo monobloque de tantalio Hedrocel (Zimmer), con par de fricción alúmina-polietileno. La edad media de los pacientes fue de 46,7 años (rango 35-61), y el seguimiento medio de 42 meses. La valoración clínica se realizó con la escala de Merle D'Augbigné Postel obteniendo 38,8% de resultados excelentes, 22,2 de resultad...

Sphaerococcus coronopifolius (Rhodophyta, Gigartinales): a Mediterranean red alga with potential and applications in restoration.

Science.gov (United States)

Fratini, Filippo; Rivière, Catherine; Santamaria, Ulderico

2016-04-25

Experimental studies conducted on some species of Mediterranean red algae allowed to identify Sphaerococcus coronopifolius Stackhouse as a valid alternative to the Pacific alga Gloiopeltis furcata (Postels & Ruprecht) J. Agardh, for the extraction of a material usable as natural consolidant and adhesive in the field of restoration. Promising results have been observed by comparing the extracts obtained from these two algae after the same extraction procedure. Chemical analysis (FTIR) revealed that S. coronopifolius has qualities similar to G. furcata. Even more promising results for S. coronopifolius compared to G. furcata were observed after the analysis of pH and conductivity, and the adhesion tests carried out on both extracts.

77 FR 61571 - Membership of the Departmental Performance Review Board

Science.gov (United States)

2012-10-10

... Geovette E. Washington, Deputy General Counsel Office of the Chief Financial Officer and Assistant..., Chief Financial Officer and Director for Administration Economics and Development Administration Thomas Guevara, Deputy Assistant Secretary for Regional Affairs Sandra Walters, Chief Financial Officer and...

CONTOURS OF BIBLICAL SPIRITUALITY AS A DISCIPLINE

African Journals Online (AJOL)

Three approaches are used for coming towards a definition of Biblical spirituality. The ..... Donahue is that he shows how the ideas of Sandra Schneiders are rooted in the .... The central part of the book of Kees Waaijman about spirituality.

77 FR 43410 - Data Collection Available for Public Comments and Recommendations

Science.gov (United States)

2012-07-24

... the collections, to Sandra Johnston, Program Analyst, Office of Financial Assistance, Small Business... Premier Certified Lenders Program (PCLP) transfers considerable authority and autonomy to Premier...) that are held in account at financial institutions and about SBIC borrowings from financial...

76 FR 54196 - Membership of the Departmental Performance Review Board

Science.gov (United States)

2011-08-31

.... Chief Financial Officer and Assistant Secretary for Administration, William J. Fleming, Director for... Assistant Secretary for Regional Affairs, Sandra Walters, Chief Financial Officer and Director of..., Robert J. Byrd, Chief Financial Officer/Chief Administrative Officer, NWS, Joseph, F. Klimavicz, Chief...

Microbial ecology at the International Space Station : the use of rapid and easy molecular methods for the quantitative detection of bacteria

NARCIS (Netherlands)

van Tongeren, Sandra P.

2011-01-01

Bij lange, bemande ruimtemissies, bijvoorbeeld naar Mars, kan gevaar schuilen in de kleinste hoekjes. Dat blijkt uit het promotieonderzoek van Sandra van Tongeren. Zij stelt onder meer vast dat al bij kortdurende ruimtemissies opmerkelijke veranderingen optreden in de hoeveelheden en soorten

75 FR 22689 - Fiscal Service

Science.gov (United States)

2010-04-29

... the U.S. Department of the Treasury, Financial Management Service, Financial Accounting and Services..., 2010. Sandra Paylor-Sanders, Acting Director, Financial Accounting and Services Division. [FR Doc. 2010... Bonding Company AGENCY: Financial Management Service, Fiscal Service, Department of the Treasury. ACTION...

Eesti harrastusfilm võitis esikoha

Index Scriptorium Estoniae

2007-01-01

Tallinna V rahvusvahelise amatöörfilmide festivali peaauhind jagunes nelja filmi vahel, millest üks oli Eesti "Elevanti nägema" (tegijad Sandra Dürdorth, Maureen Apel, Kalev Saar, Leon Shamis). Teised võitjad olid Austria (2 filmi) ja Soome

EU citizenship and social solidarity / Sandra Mantu, Paul Minderhoud

Index Scriptorium Estoniae

Mantu, Sandra

2017-01-01

Majanduslikult inaktiivsete ja mobiilsete Euroopa Liidu kodanike sotsiaalsetest õigustest Brexiti valguses. Euroopa Liidu kodanike liikumisvabadusest ja heaolu turismist. Sisaldab asjakohast kohtupraktikat

Sinimustvalge junn... no mis kunst see ka on?! / Janno Zõbin ; interv. Janno Zõbin

Index Scriptorium Estoniae

Zõbin, Janno

2003-01-01

Kunstnikud Krista Rambak (24), Sandra Jõgeva (26) ja Kristin Kalamees (24) avasid moodsa kunsti seletamiseks kunstitelefoni, millele helistades on 24 tundi ööpäevas võimalik küsida nõu kunstiküsimustes. Projekti kaasosaline ja flaieri kujundaja Margus Tamm

Exhibition

CERN Multimedia

Staff Association

2016-01-01

COLORATION Sandra Duchêne From September 5 to 16, 2016 CERN Meyrin, Main Building La recherche de l’Universel. Après tout ! C’est de l’Amour ! What else to say ? …La couleur, l’ENERGIE de la vie…

The Brave Black Regiment: The Fifty-Fourth Massachusetts Infantry Volunteers (Colored) January 1863 - September 1864.

Science.gov (United States)

1996-01-01

additional references.. The material contained in this thesis was compiled from numerous books, magazines, official military records, pamphlets...Reedy Creek Road Raleigh, NC 27607-6410 13. Cynthia E. Williams 318 Petunia Path Chesapeake, VA 2332 5 14. Sandra K. Alston 17409 Park Lane

Research for global challenges: IDRC's ninth annual public meeting ...

International Development Research Centre (IDRC) Digital Library (Canada)

2018-01-02

Jan 2, 2018 ... ... that are going to improve the lives of people in the developing world.” ... and in particular the brain power, can have the biggest impact.” ... IDRC Speakers, from left to right: Robert Hofstede, Sandra Gagnon, Jean Lebel ...

Uued filmid sarjast "Eesti lood"

Index Scriptorium Estoniae

2008-01-01

Novembris ja detsembris on ETV ekraanil uued dokumentaalfilmid sarjast "Eesti lood" - "Professionaalne amatöör" (I. Kangro film Jaan-Jürgen Klausist), "Sõjamäng" (M. Arjukese film Ilmar Raagi osalemisest Erna retkel), "Ars longa" (M. Lillaku film kunstnik Sandra Jõgevast)

Globaalne konteiner, järjekorranumbriga 8 / Maarin Mürk

Index Scriptorium Estoniae

Mürk, Maarin

2009-01-01

Kunstikonteineri rahvusvaheline kunsti- ja performance'iüritus "Global Container 8" 27. augustil kultuuritehases Polymer. Justin Tyler Tate'i, Auseklis/Usinsi ja Sandra Jõgeva esinemisest. Tom Russotti ja Ernest Truely ürituse kohta valminud dokumentaalist. Simon B. Haefele vestlusringist teemal "Kunsti võim"

Arts@CERN | ACCELERATE Austria | 19 May | IdeaSquare

CERN Multimedia

2016-01-01

​Arts@CERN welcomes you to a talk by architects Sandra Manninger and Matias Del Campo, at IdeaSquare (Point 1) on May 19 at 6:00 p.m.   Sensible Bodies - architecture, data, and desire. Sandra and Matias are the winning architects for ACCELERATE Austria. Focusing on the notion of geometry, they are at CERN during the month of May, as artists in residence. Their research highlights how to go beyond beautiful data to discover something that could be defined voluptuous data. This coagulation of numbers, algorithms, procedures and programs uses the forces of thriving nature and, passing through the calculation of a multi-core processor, knits them with human desire. Read more. ACCELERATE Austria is supported by The Department of Arts of the Federal Chancellery of Austria. Thursday, May 19 at 6:00 p.m. at IdeaSquare.  See event on Indico. 

BOOK REVIEW

Directory of Open Access Journals (Sweden)

Nadiia BUREIKO

2016-06-01

Full Text Available Tina Freyburg, Sandra Lavenex, Frank Schimmelfennig, Tatiana Skripka and Anne Wetzel. 2015. Democracy Promotion by Functional Cooperation. The European Union and its Neighbourhood. Challenges to Democracy in the 21st Century. Palgrave Macmillan, UK, 291 pages, ISBN: 978-1-137-48934-0

Early home-based intervention for children at familial risk of dyslexia

NARCIS (Netherlands)

van Otterloo, S.G.

2011-01-01

Veel ouders zijn in staat hun kleuters thuis deelvaardigheden van lezen en spellen aan te leren. Ook bij kinderen met een erfelijk risico op dyslexie. Sandra van Otterloo onderzocht de effectiviteit van een thuistraining die speciaal ontwikkeld is voor deze doelgroep. Een steekproef uit deze

27. XI esitles Kanuti gildi saalis Mooste avatud ateljee MOKS video-, heli- ja tegevuskunstiprogrammi "Põhi silmab kagu"...

Index Scriptorium Estoniae

2003-01-01

Esinesid MOKSiga seotud kunstnikud ja rühmitused: John Grzinich, OPA: Slobodanka Stevceska, Denis Saraginovski (Obsessive Possessive Aggression, Makedoonia), Kaarel Vulla, Irene Roos, Jane Remm, OMP: maalikunstnikud Maris Palgi, Eva Orav ja ajakirjanik Maia Möller, Pink Punk: Kristin Kalamees, Margus Tamm, Sandra Jõgeva

"Woman Hollering Creek" a Traves de la Musica: Articulating Mexicanidad to Pochismo

Science.gov (United States)

French, Lydia A.

2011-01-01

This essay intervenes in contemporary scholarship on Sandra Cisneros's "Woman Hollering Creek" (1991) by examining the canciones she uses as epigraphs and their relationship to the multiple nationalisms that Chicana/os actively negotiate. I argue that Cisneros's decision to include powerfully nationalist Mexican cancion traditions…

Incorporating Feminist Standpoint Theory

DEFF Research Database (Denmark)

Ahlström, Kristoffer

2005-01-01

As has been noted by Alvin Goldman, there are some very interesting similarities between his Veritistic Social Epistemology (VSE) and Sandra Harding’s Feminist Standpoint Theory (FST). In the present paper, it is argued that these similarities are so significant as to motivate an incorporation...

Poliitiline sõnum ja igapäevaelu / Grete Nootre

Index Scriptorium Estoniae

Nootre, Grete

2006-01-01

56. Berliini filmifestivali auhinnasaajad - Jasmila Zhbavici film "Grbavica", Michael Winterbottom ja Mat Whitecross filmi eest "Teekond Guatanamosse" ("The Road to Guantanamo"), Pernille Fischer Christensen filmi "Seep" eest ja Jafar Panahi filmi "Suluseis" eest. Parimad näitlejad olid Sandra Hüller ja Moritz Bleibtreu

Hotelli Radisson SAS mantra : jah, ma saan! / Kai Vare

Index Scriptorium Estoniae

Vare, Kai, 1968-

2004-01-01

Radisson SAS hotell Tallinnas on kliendirahulolu-uuringute järgi keti hotellide seas esimeste hulgas. Hotelli direktor Kaido Ojaperv ja müügijuht Ann-Kai Tõrs Radisson SAS-i standarditest, kliendi sajaprotsendilise rahulolu tagamise põhimõtetest, personali valikust, koolitusest. Kommenteerib Sandra Dimitrovich

Kunst viib saunakultuuri maakera kuklapoolele

Index Scriptorium Estoniae

2010-01-01

Kultuuritehases Polymer tegutsev Art Container tutvustab Austraalias Brisbane'i festivalil eesti saunakultuuri. Eksponeeritakse arhitektuurilist installatsiooni (kasutatud akendest ehitatud läbipaistev saun) ja esitatakse interaktiivset performance'it "Kümblejad". Töö autorid on Erik Alalooga, Tanel Saar, Sandra Jõgeva, Janno Bergmann, Hans-Gunter Lock

Aftercare Guidelines for Drug and Alcohol Program Advisors

Science.gov (United States)

1991-10-21

Relationships Relaxing Resentment Respect Responsibility Rigidity Risks Secrets Self-acceptance Self-esteem Serenity Shame Sharing Silence Slips Slippery ...Bit You (1967) 22041 A Time For Decision (1968) 22138 The Summer We Moved To Elm Street (1972) 22144 The Secret Love of Sandra Blain (1971) 22154

Hamartia: Foucault and Iran 1978–1979 (2: Scholarship and significance

Directory of Open Access Journals (Sweden)

Johann Beukes

2009-07-01

Full Text Available Against the backdrop of the introduction and analysis of Foucault’s Iran writings in the first of two articles, this second article attempts to contribute to an understanding of Foucault’s involvement in the revolution in Iran (1978–1979 by 1 employing the concluding suggestions in the first article as premises for 2 an analysis of three explicit contributions (Janet Afary and Kevin Anderson, Ian Almond, and Danny Postel that have been made recently on this traditionally neglected issue in Foucault scholarship, 3 and, via the notion of an ‘ethics of Self-discomfort’, arguing for an acknowledgement of the philosophical significance of Foucault’s involvement in Iran and his writings from that period.

Multi-stage type replacing method of iodine filter

International Nuclear Information System (INIS)

Kitamura, Masao; Kamiya, Kunio.

1976-01-01

Object: To effectively replace a filter into a removing device of radioactive impurities used in ventilation and air conditioning system or the like in an atomic power plant. Structure: A plurality of elements of a filter are arranged in series relative to fluid. In the first replacement, an ante-filter-element on inlet side of fluid is removed, and a post-filter-element is repositioned to that position of the ante-element. Then, a fresh element is newly mounted on that position of the post-element. Replacement after the second time may be effected by repeating the operation noted above. With this arrangement, the minimal value of collection efficiency at replacement of filter may be increased. (Ikeda, J.)

Guide biogas. From production to utilization. 5. compl. rev. ed.; Leitfaden Biogas. Von der Gewinnung zur Nutzung

Energy Technology Data Exchange (ETDEWEB)

NONE

2010-07-01

The book under consideration is a guide for biogas and consists of the following contributions: (a) Targets of the guide (M. Kaltschmitt); (b) Fundamentals of anaerobic fermentation (J. Friehe); (c) Systems engineering for supplying biogas (J. Postel); (d) Description of selected substrates (J. Friehe); (e) Operation of biogas plants (J. Liebetrau); (f) Gas processing and possibilities of utilization (M. Wetthaeuser); (g) Legal and administrative framework conditions (H. von Bredow); (g) Economy (S. Hartmann); (h) Company organisation (G. Reinhold); (i) Quality and utilization of fermentation residues (H. Doehler); (j) Implementation of a project (E. Fischer); (k) Position and significance of biogas as a renewable energy resource in Germany (M. Kaltschmitt); (l) Project examples (J. Friehe).

Making detailed predictions makes (some) predictions worse

Science.gov (United States)

Kelly, Theresa F.

In this paper, we investigate whether making detailed predictions about an event makes other predictions worse. Across 19 experiments, 10,895 participants, and 415,960 predictions about 724 professional sports games, we find that people who made detailed predictions about sporting events (e.g., how many hits each baseball team would get) made worse predictions about more general outcomes (e.g., which team would win). We rule out that this effect is caused by inattention or fatigue, thinking too hard, or a differential reliance on holistic information about the teams. Instead, we find that thinking about game-relevant details before predicting winning teams causes people to give less weight to predictive information, presumably because predicting details makes information that is relatively useless for predicting the winning team more readily accessible in memory and therefore incorporated into forecasts. Furthermore, we show that this differential use of information can be used to predict what kinds of games will and will not be susceptible to the negative effect of making detailed predictions.

El tamaño del daño

OpenAIRE

José Eduardo Rueda Enciso

2000-01-01

Chajeradó, el río de la caña flecha partida. Luz Marcela Duque, Iván Darío Espinosa, Afda Cecilia Gálvez, Diego Herrera y Sandra María Turbay. Premios Nacionales Colcultura 1996, Colcultura, Bogotá, 1997, 477 págs.

75 FR 57906 - Membership of the Defense Contract Audit Agency Senior Executive Service Performance Review Boards

Science.gov (United States)

2010-09-23

... publication of this notice. FOR FURTHER INFORMATION CONTACT: Sandra L. Burrell, Chief, Human Resources Management Division, Defense Contract Audit Agency, 8725 John J. Kingman Road, Suite 2133, Fort Belvoir... following are the names and titles of DCAA career executives appointed to serve as members of the DCAA...

76 FR 59664 - Membership of the Defense Contract Audit Agency Senior Executive Service Performance Review Boards

Science.gov (United States)

2011-09-27

... Date: Upon publication of this notice. FOR FURTHER INFORMATION CONTACT: Sandra L. Burrell, Chief, Human Resources Management Division, Defense Contract Audit Agency, 8725 John J. Kingman Road, Suite 2133, Fort...(c)(4), the following are the names and titles of DCAA career executives appointed to serve as...

Editorial: Multicultural Education--Solution or Problem for American Schools?

Science.gov (United States)

Cochran-Smith, Marilyn

2001-01-01

Discusses the role of multicultural education in American education, examining Geneva Gay's book on culturally responsive teaching (which argues for culturally responsive teaching, with teaching having the moral courage to help make education more multiculturally responsive) and Sandra Stotsky's book (which argues that multicultural education is a…

Measuring Institutional Performance in Higher Education.

Science.gov (United States)

Meyerson, Joel W., Ed.; Massy, William F., Ed.

This collection of seven essays from the Stanford Forum for Higher Education Futures focuses on how downsizing, quality management, and reengineering have are affecting higher education. An introductory paper, "Introduction: Change in Higher Education: Its Effect on Institutional Performance," (Joel W. Meyerson and Sandra L. Johnson)…

Tartu ja Tallinna boheemkond ning lotovõitjad : Valitud palu dokumentaalfilmide sarjast "Eesti lood" / Olev Remsu

Index Scriptorium Estoniae

Remsu, Olev, 1947-

2009-01-01

ETVs näidatud dokumentaalfilmidest sarjas "Eesti lood" - Indrek Kangro film Jaan-Jürgen Klausist "Professionaalne amatöör" (eetris 3. XII 2008), Margit Lillaku film kunstnik Sandra Jõgevast "Ars longa" (eetris 29. X 2008), Eva-Katariina Taimre "Jackpot" lotovõitjatest (eetris 19. XI 2008)

Valgussähvatused saalipimedusest / Katrin Rajasaare

Index Scriptorium Estoniae

Rajasaare, Katrin

2002-01-01

6. Pimedate Ööde Festivali filmidest : "Puur" ("La Cage"), režissöör Alain Raoust : Prantsusmaa 2002, "Kuuvalgel" ("Kuutamolla"), režissöör Aku Louhimies : Soome 2001, "Kaunis Martha" ("Bella Martha"), režissöör Sandra Nettelbeck : Saksamaa 2001

Paul Dirac lectures at CERN

CERN Multimedia

CERN Bulletin

2010-01-01

When a group of physicists entered the Main Auditorium, during the evening of 29 June, they felt they had opened a time portal.   Paul Dirac in front of a blackboard showing his formula. ©Sandra Hoogeboom An attentive audience, dressed in early 1900 costumes, were watching a lecture by the elusive Paul Dirac, presenting for the first time his famous formula on the blackboard. Paul Adrien Maurice Dirac (1902-1984) was a British mathematical physicist at Cambridge, and one of the "fathers" of quantum mechanics. When he first wrote it, in 1928, Dirac was not sure what his formula really meant. As demonstrated by Andersson four year later, what Dirac had written on the blackboard was the first definition of a positron, hence he is credited with having anticipated the existence of antimatter. The actor John Kohl performs as Paul Dirac. ©Sandra Hoogeboom What the group of puzzled physicists were really observing when they entered the CERN Auditorium was the shoo...

Bootstrap prediction and Bayesian prediction under misspecified models

OpenAIRE

Fushiki, Tadayoshi

2005-01-01

We consider a statistical prediction problem under misspecified models. In a sense, Bayesian prediction is an optimal prediction method when an assumed model is true. Bootstrap prediction is obtained by applying Breiman's `bagging' method to a plug-in prediction. Bootstrap prediction can be considered to be an approximation to the Bayesian prediction under the assumption that the model is true. However, in applications, there are frequently deviations from the assumed model. In this paper, bo...

Language universals without universal categories

NARCIS (Netherlands)

Croft, W.; van Lier, E.

2012-01-01

In this article, the authors present their views on an article by author Sandra Chung related to lexical categories. According to them, Chung's article critiques an analysis of word classes in Chamorro by author Donald M. Topping. They discuss the restatements made by Chung on Topping's criteria for

75 FR 51167 - Bank of Ruston, Ruston, Louisiana; Approval of Conversion Application

Science.gov (United States)

2010-08-18

... DEPARTMENT OF THE TREASURY Office of Thrift Supervision [AC-48 OTS Nos. 03912 and H4739] Bank of..., 2010, the Office of Thrift Supervision approved the application of Bank of Ruston, Ruston, Louisiana.... Dated: August 11, 2010. By the Office of Thrift Supervision. Sandra E. Evans, Federal Register Liaison...

75 FR 31511 - Oneida Financial Corp., Oneida, NY; Approval of Conversion Application

Science.gov (United States)

2010-06-03

... Office of Thrift Supervision approved the application of Oneida Financial, MHC and Oneida Savings Bank... DEPARTMENT OF THE TREASURY Office of Thrift Supervision [AC-44: OTS No. H-4704] Oneida Financial... of Thrift Supervision. Sandra E. Evans, Federal Register Liaison. [FR Doc. 2010-13209 Filed 6-2-10; 8...

Kaitstud magistritööd, 1. juuni 2012

Index Scriptorium Estoniae

2013-01-01

Oma töid kaitsesid Claudio Julio Rodriguez Higuera, Davi William Ferreira Gomes, Karlina Vaivade, Mohamed Gamal Abdelmeged Elmaayergy, Sigita Tamošauskaite, Eduardo Chávez Herrera, Tyler James Bennett, Felipe Cuervo Restrepo, Julia Popova, Anastasiia Sidielnik, Thomas Mark Boyle, Mirjam Männik, Sandra Preiman, Tamara Stojanovic

77 FR 35384 - Ocean Transportation Intermediary License; Applicants

Science.gov (United States)

2012-06-13

... Logistics LLC (NVO), 9814 Goldenglade Drive, Houston, TX 77064, Officer: Sandra Lesage, Member/Manager... telephone at (202) 523-5843 or by email at [email protected] . ABC Trucking and Logistics L.L.C. (OFF), 3080...), Lawrence R. Lammers, President/CEO, Application Type: License Transfer Atlantic Cargo Logistics LLC (NVO...

Litsid ja kunstnikud näitusesaalis / Teet Veispak

Index Scriptorium Estoniae

Veispak, Teet, 1955-

2007-01-01

Näitusest "Kehaturg" Tallinna Kunstihoones, kuraator Reet Varblane. Liina Siibi videost "Vastumeelne keha", soome kunstniku Teemu Mäki väljapanekust "Prostitutsioonist", malaisia fotograafi Diana Lui fotoseeriast, rootsi-eesti fotograafi Bie Erenurme väljapanekust "Mu ema on lits", Sandra Jõgeva näitusel eksponeeritud šokolaadiümbristest

Muusika / Aimar Ventsel

Index Scriptorium Estoniae

Ventsel, Aimar, 1970-

2005-01-01

Uutest heliplaatidest "Sandra Sillamaa", "The Concretes", The Juan Maclean "Less Than Human", Joni Mitchell "Songs Of A Prairie Girl", Pedegree "Growing Apart", Shelton San "EP", The Five Corners Quintet "Chasin' The Jazz Gone By", "The Story of Popular Black Music", Foo Fighters "In Your Honor", A "Teen Dance Ordinance"

Say No to Excess Salt (A Cup of Health with CDC)

Centers for Disease Control (CDC) Podcasts

Hypertension is a leading cause of heart disease and stroke and occurs in nearly one in three U.S. adults. Reducing salt intake can lower blood pressure, helping to prevent and treat hypertension. In this podcast, Dr. Sandra Jackson discusses the importance of consuming a diet low in sodium.

Advocacy for School Leaders: Becoming a Strong Voice for Education

Science.gov (United States)

Whitaker, Sandra

2007-01-01

In today's political and global world, it's not enough to remain a solid educational leader; leaders must become advocates for education--on Capitol Hill, in state legislatures, and within communities. In this book, Sandra Whitaker examines key issues facing education, demonstrates methods for unpacking the issues, and discusses strategies to…

Fungal treatment of lignocellulosic biomass

NARCIS (Netherlands)

Kuijk, van S.J.A.

2016-01-01

Summary PhD thesis Sandra J.A. van Kuijk

Carbohydrates in plant cell walls are highly fermentable and could be used as a source for ruminant nutrition or biofuel production. The presence of lignin in cell walls hampers the utilization of these carbohydrates and should thus

Laboratory-scale simulations with hydrated lime and organic ...

African Journals Online (AJOL)

+27 (18) 299-2508; e-mail: sandra.barnard@nwu.ac.za .... After 5 min exposure, an inverted light microscope was used to ..... Light microscopy images of C. hirundinella cells in source water (a) and the effects of chlorine concentrations after exposure to chlorine .... trations of organic carbon compounds measured during dif-.

27. V kell 16 avatakse Niguliste kirikus...

Index Scriptorium Estoniae

2002-01-01

EKA interdistsiplinaarsete kunstide eriala magistritööde näitus "Nagu aamen kirikus". Eksponeeritud Kristin Kalamehe lühimängufilm "Igavene tuli", Mirja-Mari Smidti video ja maaliseeria "Kaaluta olek", Allan Tõnissoo videoskulptuur "Kristus", Avangardi (Sandra Jõgeva, Margus Tamm) fotoseeria ja video "Sõda ja rahu". Avamisel Avangardi performance

Rainbow Nation's "Ubuntu": Discovering Distinctness as a Spectrum through South African Literature

Science.gov (United States)

Smith, Colin Bridges

2007-01-01

Apartheid created more than physical distances between color groups; South Africa is made up of people with often separated minds. Leaders of the democratic government draw from and modify the ancient African tribal value called "ubuntu" as the philosophic basis for their cultural strategy of unification. Sandra Chait has pointed out…

Tiit Land: Anname panuse Alzheimeri tõve võimalikuks raviks / Kristel Toom

Index Scriptorium Estoniae

Toom, Kristel

2008-01-01

Tallinna Ülikooli Matemaatika ja Loodusteaduste Instituudis töötab uurimisrühm, kelle huvi on seotud organismis toimuva raua ainevahetuse ning selle häirete tagajärjel ilmnevate haiguslike protsessidega, mille hulka kuulub ka Alzheimeri tõbi. Teadusprojekte juhivad Tiit Land ja Sandra Zetterström Fernaeus

The Puerto Ricans: Their History, Culture, and Society.

Science.gov (United States)

Lopez, Adalberto, Ed.

Articles in this book cover Puerto Rican history from the Spanish colonization to the present day experience of Puerto Ricans in the United States. Political, social, economic, cultural, and historical issues are addresed by the following authors: Edna Acosta-Belen, Frank Bonilla, Juan Manuel Carrion, Diana Christopulos, Sandra Messinger Cypess,…

76 FR 70711 - Senior Executive Service; Performance Review Board

Science.gov (United States)

2011-11-15

... L BEKKEDAHL, LARRY N BELL, MELODY C BIENIAWSKI, ANDREW J BIERBOWER, WILLIAM J BISHOP, CLARENCE T... BROWN, FRED L BROWN, STEPHANIE H BRUCE, SANDRA D BRYAN, PAUL F BRYAN, WILLIAM N BURROWS, CHARLES W BUTTRESS, LARRY D BUZZARD, CHRISTINE M CADIEUX, GENA E CALBOS, PHILIP T CALLAHAN, SAMUEL N CAMPAGNONE, MARI...

the effect of cooking time on the vitamin c, dietary fiber and mineral

African Journals Online (AJOL)

Administrator

(Sandra, 1995). Several methods of processing the vegetables are being use without considering the effect on the vitamin C, dietary fiber and minerals components. This study is designed to determine the effect of cooking time on the Vitamin C, dietary fiber. & mineral constituents of T. occidentalis (FP), V. amygdalina (BL),.

75 FR 76466 - Ocean Transportation Intermediary License Reissuance

Science.gov (United States)

2010-12-08

... Hollins Ferry Road, Halethorpe, MD 21227. 020253NF Concord October 22, 2010. International Transport, Inc... Logistics, Inc. October 30, 2010. dba LTH Express, 837 East Sandhill Avenue Carson, CA 90746. 021890F Empire Global October 31, 2010. Logistics, LLC, 160- 51 Rockaway Blvd., Suite 206, Jamaica, NY 11434. Sandra L...

Protein docking prediction using predicted protein-protein interface

Directory of Open Access Journals (Sweden)

Li Bin

2012-01-01

Full Text Available Abstract Background Many important cellular processes are carried out by protein complexes. To provide physical pictures of interacting proteins, many computational protein-protein prediction methods have been developed in the past. However, it is still difficult to identify the correct docking complex structure within top ranks among alternative conformations. Results We present a novel protein docking algorithm that utilizes imperfect protein-protein binding interface prediction for guiding protein docking. Since the accuracy of protein binding site prediction varies depending on cases, the challenge is to develop a method which does not deteriorate but improves docking results by using a binding site prediction which may not be 100% accurate. The algorithm, named PI-LZerD (using Predicted Interface with Local 3D Zernike descriptor-based Docking algorithm, is based on a pair wise protein docking prediction algorithm, LZerD, which we have developed earlier. PI-LZerD starts from performing docking prediction using the provided protein-protein binding interface prediction as constraints, which is followed by the second round of docking with updated docking interface information to further improve docking conformation. Benchmark results on bound and unbound cases show that PI-LZerD consistently improves the docking prediction accuracy as compared with docking without using binding site prediction or using the binding site prediction as post-filtering. Conclusion We have developed PI-LZerD, a pairwise docking algorithm, which uses imperfect protein-protein binding interface prediction to improve docking accuracy. PI-LZerD consistently showed better prediction accuracy over alternative methods in the series of benchmark experiments including docking using actual docking interface site predictions as well as unbound docking cases.

Protein docking prediction using predicted protein-protein interface.

Science.gov (United States)

Li, Bin; Kihara, Daisuke

2012-01-10

Many important cellular processes are carried out by protein complexes. To provide physical pictures of interacting proteins, many computational protein-protein prediction methods have been developed in the past. However, it is still difficult to identify the correct docking complex structure within top ranks among alternative conformations. We present a novel protein docking algorithm that utilizes imperfect protein-protein binding interface prediction for guiding protein docking. Since the accuracy of protein binding site prediction varies depending on cases, the challenge is to develop a method which does not deteriorate but improves docking results by using a binding site prediction which may not be 100% accurate. The algorithm, named PI-LZerD (using Predicted Interface with Local 3D Zernike descriptor-based Docking algorithm), is based on a pair wise protein docking prediction algorithm, LZerD, which we have developed earlier. PI-LZerD starts from performing docking prediction using the provided protein-protein binding interface prediction as constraints, which is followed by the second round of docking with updated docking interface information to further improve docking conformation. Benchmark results on bound and unbound cases show that PI-LZerD consistently improves the docking prediction accuracy as compared with docking without using binding site prediction or using the binding site prediction as post-filtering. We have developed PI-LZerD, a pairwise docking algorithm, which uses imperfect protein-protein binding interface prediction to improve docking accuracy. PI-LZerD consistently showed better prediction accuracy over alternative methods in the series of benchmark experiments including docking using actual docking interface site predictions as well as unbound docking cases.

WALS Prediction

NARCIS (Netherlands)

Magnus, J.R.; Wang, W.; Zhang, Xinyu

2012-01-01

Abstract: Prediction under model uncertainty is an important and difficult issue. Traditional prediction methods (such as pretesting) are based on model selection followed by prediction in the selected model, but the reported prediction and the reported prediction variance ignore the uncertainty

Informe científico de investigador: Fuselli, Sandra Rosa (2015)

OpenAIRE

Fuselli, Sandra Rosa

2015-01-01

El Grupo Microbiología Aplicada (GIMA), perteneciente al Centro de Investigación en Abejas Sociales (CIAS) de la FCEyN-UNMdP, bajo la dirección de Dra. SR Fuselli, desarrolla dos líneas de investigación: Sanidad apícola: Productos naturales bioactivos, y Calidad y trazabilidad de productos agroalimentarios. En este contexto, se están llevando a cabo estudios sobre la actividad antimicrobiana y antipatogénica de PRODUCTOS NATURALES, concr...

The Average Expectable Environment Is Not Good Enough: A Response to Scarr.

Science.gov (United States)

Baumrind, Diana

1993-01-01

Takes the position, contrary to that of Sandra Scarr, that the details of socialization patterns are crucial to an understanding of normal and deviant development. Research is cited to support the argument that better than adequate parenting optimizes the development of both normal and vulnerable children and that parents' belief in their own…

Diversity in the Workplace.

Science.gov (United States)

1996

This document contains three papers presented at a symposium on diversity in the workplace moderated by Sandra Johnson at the 1996 conference of the Academy of Human Resource Development (AHRD). "Diversity and Development: An Assessment of Equal Opportunities and the Role of HRD in the Police Service" (Rashmi Biswas, Penny Dick) examines…

Homme kell 13 avatakse Y-galerii hoovis linnafestivali "Eclectica" raames...

Index Scriptorium Estoniae

2004-01-01

Performance'ikunsti ja kunstipärase rokkmuusika ühisfestival "In/Out". Esinevad Tartu Popi & Roki Instituut, Maris Palgi, Eva Orav, Kaie Luik, Maia Möller, Trikotaaž, Enn Tegova, Ruumi Trummid, Fashist Lendas Üle ja Avangard (Sandra Jõgeva & Margus Tamm). Festival päädib Erkki Hüva LP "Varjust rambini" esitlusega

78 FR 14808 - Notice of Regulatory Waiver Requests Granted for the Fourth Quarter of Calendar Year 2012

Science.gov (United States)

2013-03-07

..., 2012, awarded a new contract to Hayes and Associates. On June 20, 2012, HUD began a forensic audit and... accordance with the Single Audit Act and OMB Circular A-133. Granted By: Sandra B. Henriquez, Assistant..., a contract to perform the Omaha Housing Authority (OHA) audit was awarded to the Reznick Group...

Children as Consumers: Advertising and Marketing

Science.gov (United States)

Calvert, Sandra L.

2008-01-01

Marketing and advertising support the U.S. economy by promoting the sale of goods and services to consumers, both adults and children. Sandra Calvert addresses product marketing to children and shows that although marketers have targeted children for decades, two recent trends have increased their interest in child consumers. First, both the…

Diversity in the Workplace [in HRD].

Science.gov (United States)

1995

These four papers are from a symposium that was facilitated by Laura Bierema at the 1995 conference of the Academy of Human Resource Development (HRD). "The Status of Valuing and Managing Diversity in Fortune 500 Manufacturing and Fortune 500 Service Organizations: Perceptions of Top Human Resource Professionals" (Sandra J. Johnson) reports a…

Walking the Lines of Indian Leadership: Using Goals and Visions for Balance.

Science.gov (United States)

Evans, Lara

1995-01-01

Sandra Begay-Campbell, newly elected Chair of the Board of Directors for the American Indian Science and Engineering Society discusses difficulties she has faced, including almost failing college, struggling to find her place in a male-dominated field, and dealing with leadership issues as an American Indian woman. Begay-Campbell stresses the…

Viin! / Karen Jagodin

Index Scriptorium Estoniae

Jagodin, Karen, 1982-

2006-01-01

Näitused austria kaasaegsest arhitektuurist Eesti Arhitektuurimuuseumis kuni 21. V: "Viin: linnaehitus ja uusim arhitektuur" suures saalis (kuraator Leopold Dungl), kaasneb kataloog; "Elamuehitus Viinis: arhitektuur igaühele" galeriil (näituse idee: Wolfgang Förster, Dietmar Steiner, Alexandra Viehhauser, kuraator A. Viehhauser, kujundus - Span-Arhitektid: Matias del Campo, Sandra Manninger, Sebastian Michalski)

Data-Based Predictive Control with Multirate Prediction Step

Science.gov (United States)

Barlow, Jonathan S.

2010-01-01

Data-based predictive control is an emerging control method that stems from Model Predictive Control (MPC). MPC computes current control action based on a prediction of the system output a number of time steps into the future and is generally derived from a known model of the system. Data-based predictive control has the advantage of deriving predictive models and controller gains from input-output data. Thus, a controller can be designed from the outputs of complex simulation code or a physical system where no explicit model exists. If the output data happens to be corrupted by periodic disturbances, the designed controller will also have the built-in ability to reject these disturbances without the need to know them. When data-based predictive control is implemented online, it becomes a version of adaptive control. One challenge of MPC is computational requirements increasing with prediction horizon length. This paper develops a closed-loop dynamic output feedback controller that minimizes a multi-step-ahead receding-horizon cost function with multirate prediction step. One result is a reduced influence of prediction horizon and the number of system outputs on the computational requirements of the controller. Another result is an emphasis on portions of the prediction window that are sampled more frequently. A third result is the ability to include more outputs in the feedback path than in the cost function.

Heidegger and the source of meaning | Knowles | South African ...

African Journals Online (AJOL)

Sandra Lee Bartky criticises the account of meaning contained in Heidegger's ontology in Being and Time. In her view, Heidegger must choose between the claim that meaning is received and the claim that it is created, but is unable to do so. This paper argues that Bartky's criticism is misconceived, by showing that ...

Human Factors and Safety Considerations of Night Vision Systems Flight Using Thermal Imaging Systems

Science.gov (United States)

1990-04-01

Duke) Fort Sam Houston, TX 78234-6200 26 Director of Professional Services U.S. Air Force School AFMSC/GSP of Aerospace Medicina Brooks Air Force Base...Force Base, CA 93523-5000 Commander Ms. Sandra G. Hart Code 3431 Ames Research Center Naval Weapons Center MS 229-S China Lake, CA 93555 Moffett Field, CA

Influence of vermicompost humic acid on chlorophyll content and ...

African Journals Online (AJOL)

Influence of vermicompost humic acid on chlorophyll content and acclimatization in banana clone, Enano Guantanamero. Marcia Beatriz Moya Fernández, Esteban Sánchez Chávez, Daniel Cabezas Montero, Andrés Calderín García, Dany Marrero López, Eduardo F. Héctor Ardisana, Sandra Pérez Álvarez ...

78 FR 56912 - Notice of Regulatory Waiver Requests Granted for the Second Quarter of Calendar Year 2013

Science.gov (United States)

2013-09-16

... fraud and misuse of city funds, which resulted in a forensic audit investigation, the audited financial...) fiscal year end (FYE), in accordance with the Single Audit Act and OMB Circular A-133. Granted By: Sandra... Waived: The VHA requested a waiver of the audit due date as a result of the State of California...

Schools as Sanctuaries

Science.gov (United States)

Stanwood, H. Mark; Doolittle, Gini

2004-01-01

The concept of sanctuary developed by psychiatrist Sandra Bloom is applied to building safe school cultures. In April 1999, when a group of superintendents in southern New Jersey first assembled to discuss the ramifications of Columbine, the authors had no vision of safe schools, little understanding of the complexities of change, and certainly no…

Counterinsurgency in the Philippines. Problems and Prospects

Science.gov (United States)

1989-10-01

funds and the farmer-producers in the rural areas are practically begging for start-up funds with which to finance a backyard poultry farm, a cottage...257-70. Burton, Sandra. "Aquino’s Philippines: The Center Holds." Foreign Affairs 65:3 (America and the World 1986): 524-37. Butcher , Scott. U.S

Saving Mango Street

Science.gov (United States)

Van Winkle, Katie

2012-01-01

The author first learned about cultural diversity and racial justice in Mr. Sanderson's middle school English class. They read a book called "The House on Mango Street" by Sandra Cisneros and learned about a different culture, but also about a community with striking similarities to their own. The main character in the novel, Esperanza,…

Computer program for modelling the history of the in-service bending of fast power reactor fuel assemblies

International Nuclear Information System (INIS)

Dienstbier, J.

1979-04-01

The studies into stresses and deformations in the core are mainly focused on the fuel rod and the fuel assembly can. In high neutron doses austenitic steel swells and this is associated with a considerable increase in the volume of material. The SANDRA computer program is used for solving the problems of can deformations and stress during long-term reactor operation. The block for the mechanical interaction of cans is the key part of the program. The program input data include temperature distribution, fast neutron flux distribution and coolant overpressure inside the cans. Reactor operation is modelled using operating modes A, B, C which may arbitrarily be combined. Mode A computes bending deformations and the deformations of the can cross-section due to temperature dilatation in the change in temperature fields in the reactor; mode B computes deformations due to swelling and creep in long-term operation; mode C computes thermal deformations in reactor shut-down. A flowsheet is shown of program SANDRA as are examples of computed deformations. (M.S.)

Generalized Predictive Control and Neural Generalized Predictive Control

Directory of Open Access Journals (Sweden)

Sadhana CHIDRAWAR

2008-12-01

Full Text Available As Model Predictive Control (MPC relies on the predictive Control using a multilayer feed forward network as the plants linear model is presented. In using Newton-Raphson as the optimization algorithm, the number of iterations needed for convergence is significantly reduced from other techniques. This paper presents a detailed derivation of the Generalized Predictive Control and Neural Generalized Predictive Control with Newton-Raphson as minimization algorithm. Taking three separate systems, performances of the system has been tested. Simulation results show the effect of neural network on Generalized Predictive Control. The performance comparison of this three system configurations has been given in terms of ISE and IAE.

NG Kunstikonteiner alustab kirjandusega

Index Scriptorium Estoniae

2008-01-01

Kunstnik Sandra Jõgeva korraldab Tallinnas kultuuritehases Polymer alternatiivgaleriis Non Grata Kunstikonteiner kirjanduslike kohtumiste seeria "Üks hullem kui teine". Kirjandusüritused ei ole mõeldud ainult oma ala insider'itele. 17. juulil esinevad Armin Kõomägi teemal "Kirjandus ja äri", Andrus Elbing "Vangla sinus eneses" jt. Vt. ka Looming, 2008, nr. 8, lk. 1271

Mineralogical and chemical characteristics of newer dolerite dyke ...

Indian Academy of Sciences (India)

Dunn and Dey 1942; Saha 1948, 1952; Saha et al. 1972, 1973). ... nuclei of the Indian landmass (Basu et al. 1981;. Goswami ... Geochemistry. In order to get an idea about petrogenetic process ...... Greenough John D, Fryer Brian J and Robinson Paul T ... 643–660. Mc Mullin David W A, Barr Sandra M and Raeside Robert.

Putting the "Her" in Science Hero

Science.gov (United States)

Wentworth, Sandra

2014-01-01

In this article, Sandra Wentworth invites science teachers to ask a group of students to write the names of three famous scientists on a piece of paper within one minute. Chances are that most students will mention Einstein and be unable to name another scientist, specifically a woman, except for an occasional Marie Curie response. This article…

Introducing Bruner: A Guide for Practitioners and Students in Early Years Education

Science.gov (United States)

Smidt, Sandra

2011-01-01

Sandra Smidt takes the reader on a journey through the key concepts of Jerome Bruner, a significant figure in the field of early education whose work has spanned almost a century. His wide-ranging and innovative principles of early learning and teaching are unpicked here using everyday language and the links between his ideas and those of other…

Science.gov (United States)

2005-09-01

Screen break: nursing students Jackie Walsh, Laura Robinson and Liz Midgley join 'matron' Sandra McQuat, a ward manager at Beatson Oncology Centre, the Western Infirmary, Glasgow, as they try out nurse training 1950s style for a new BBC series to be televised this autumn. The series, Thoroughly Modern Matron, was filmed at Belvoir Park Hospital, Belfast.

Loitsumees ja salapärane autojuht / Mare Müürsepp

Index Scriptorium Estoniae

Müürsepp, Mare, 1958-

2014-01-01

Artikkel on kirjutatud Sandra Rannastiku magistritöö põhjal (Tallinna Ülikool, kasvatusteaduste instituut, algõpetuse osakond, 2014). Magistritöö põhineb uuringul, mille jaoks valiti välja kümme raamatut, et uurida milliseid ootusi üks või teine raamat lastes tekitab ja viidi läbi 72 neljanda klassi õpilase hulgas

author's correction 1..1

Indian Academy of Sciences (India)

J. Genet. 89, e25Ye29 (http://www.ias.ac.in/jgenet/OnlineResources/90/e25.pdf). In table 1, for locus Aaz1, the core motif should be (ACAT)8 ATAAA(TG)6 and not (ACAT)8. Genetic polymorphism of serotonin transporter 5-HTTLPR: involvement in smoking behaviour. Maria Angelica Ehara Watanabe, Sandra Odebrechet ...

Welcome to the Fun House: When Is a Children's Room Not a Children's Room? When It's The Trove

Science.gov (United States)

Kenney, Brian

2006-01-01

In this article, the author talks about The Trove, a children's space--library doesn't quite cut it--located in the White Plains Public Library, New York. Sandra Miranda, the library's director, came up with the idea for The Trove, although it took the work of many--from her staff to the architects to theatrical designers and fabrications--to…

Leaving Mango Street: Speech, Action and the Construction of Narrative in Britton's Spectator Stance

Science.gov (United States)

Crawford-Garrett, Katherine

2009-01-01

This paper attempts to unite "The House on Mango Street" by Sandra Cisneros with the participant and spectator theories of James Britton and D. W. Harding in the hopes that such a union will provide new insights into each. In particular, this article explores how the speech acts of Esperanza, the novel's protagonist, are indicative of a shifting…

The Use of Nontreated Mosquito‑Net Mesh Cloth for a Tension Free ...

African Journals Online (AJOL)

Wideochir Inne Tech Malo. Inwazyjne 2013;8:36‑42. 15. Taylor EW, Duffy K, Lee K, Hill R, Noone A, Macintyre I, et al. Surgical site infection after groin hernia repair. Br J Surg. 2004;91:105‑11. 16. Tongaonkar RR, Sandra DL, Kingsnorth AN. Ten year personal experience of using Low Density Polyethylene (LDPE) mesh for.

The use of a tripolar articulation in revision total hip arthroplasty: a minimum of 24 months' follow-up.

Science.gov (United States)

Levine, Brett R; Della Valle, Craig J; Deirmengian, Carl A; Breien, Kristoffer M; Weeden, Steven H; Sporer, Scott M; Paprosky, Wayne G

2008-12-01

A retrospective cohort study of 31 hips revised with a tripolar articular construct was performed. Patient demographics and preoperative and postoperative information were recorded. Indications for a tripolar construct were recurrent dislocation and the inability to attain intraoperative stability during hip revision. Nine patients (29%) were revised to the tripolar construct after failure of a constrained liner. Twenty patients (65%) had at least one episode of instability before the most recent revision. At a mean follow-up of 38 months, modified Postel scores improved from a mean of 5.28 to 9.64 (P tripolar construct was effective in eliminating or preventing instability in 93% of the complex cases treated. These early results support the use of a tripolar construct in treating recurrent instability or instability encountered at the time of revision hip arthroplasty.

Zolotopia: A New Classic for Design

Science.gov (United States)

Payne, Janet

2007-01-01

While working on a graphic design job at FAO Schwartz, entrepreneurs Sandra Higashi and Byron Glaser recognized a need for something new in toys. The result was the birth of Zolo, an innovative, interactive toy, designed and produced by Higashi and Glaser and distributed by the Museum of Modern Art (MoMA) in New York. The initial idea for Zolo…

Tallinna XIII graafikatriennaali grand prix' pälvis leedu graafik Egle Kuckaite

Index Scriptorium Estoniae

2004-01-01

Kolm võrdset preemiat: Sang-gon Chung Lõuna-Koreast, Krishs Salmanis Lätist ja Joanne Soroka Shotimaalt. Diplomid: Anonymous Boh ja Eve Kiiler Eestist, Pete Nevin Inglismaalt, Hanna Oinonen Soomest ja venetsueela-soome kunstnik Sandra Vina de Karila. Tallinna linna preemia: John Smith (Marko Mäetamm & Kaido Ole) Eestist. Eesti Kunstimuuseumi preemia: Markus Lampinen Soomest. Eesti Panga preemia: Leonards Laganovskis Lätist

Feminist Groupwork Feminist Groupwork Groupwork Butler S Wintram Sage SAGE £10.95 , 0-8039-8210-0 [Formula: see text].

Science.gov (United States)

1991-11-27

Feminist Groupworkis a very thought-provoking book, although the thoughts and speculations stimulated aren't necessarily those intended. I wish that Sandra Butler and Claire Wintram had sorted out their research results with their tabula rasa in tact. When describing the effects on the female psyche of oppression, imbalance of power and exploitation, they accept continually that these stresses are confined to females.

The Quest for Diversity in Library Staffing: From Awareness to Action

Directory of Open Access Journals (Sweden)

Jennifer Vinopal

2016-01-01

Full Text Available The work of diversity in libraries begins at the crossroad where superiority, inaction, and denial become intolerable. – Sandra Ríos Balderrama, “This Trend Called Diversity” In Brief: Despite our ongoing quest for diversity and a growing number of initiatives to increase it, the demographics of the professional librarian population haven’t changed in any significant way. […

Predicting outdoor sound

CERN Document Server

Attenborough, Keith; Horoshenkov, Kirill

2014-01-01

1. Introduction  2. The Propagation of Sound Near Ground Surfaces in a Homogeneous Medium  3. Predicting the Acoustical Properties of Outdoor Ground Surfaces  4. Measurements of the Acoustical Properties of Ground Surfaces and Comparisons with Models  5. Predicting Effects of Source Characteristics on Outdoor Sound  6. Predictions, Approximations and Empirical Results for Ground Effect Excluding Meteorological Effects  7. Influence of Source Motion on Ground Effect and Diffraction  8. Predicting Effects of Mixed Impedance Ground  9. Predicting the Performance of Outdoor Noise Barriers  10. Predicting Effects of Vegetation, Trees and Turbulence  11. Analytical Approximations including Ground Effect, Refraction and Turbulence  12. Prediction Schemes  13. Predicting Sound in an Urban Environment.

Prediction-error of Prediction Error (PPE)-based Reversible Data Hiding

OpenAIRE

Wu, Han-Zhou; Wang, Hong-Xia; Shi, Yun-Qing

2016-01-01

This paper presents a novel reversible data hiding (RDH) algorithm for gray-scaled images, in which the prediction-error of prediction error (PPE) of a pixel is used to carry the secret data. In the proposed method, the pixels to be embedded are firstly predicted with their neighboring pixels to obtain the corresponding prediction errors (PEs). Then, by exploiting the PEs of the neighboring pixels, the prediction of the PEs of the pixels can be determined. And, a sorting technique based on th...

Janez Jansha. Euroopa oivik tõrjub solgiämbreid / Sandra Maasalu

Index Scriptorium Estoniae

Maasalu, Sandra

2008-01-01

2004. a. paremtsentristliku Demokraatliku Partei juhina valimistel võitnud Janez Jansha on populaarsust kaotamas ning peatsed valimised ei tõota ennustuste põhjal erilist edu. Dissidendist kõvakäemeheks. Korruptsioonisüüdistused seoses Soome relvafirma tehinguga

Vikergallup : eesti kirjandus 2010 / Peeter Helme, Sandra Jõgeva, Mihkel Kaevats ... [jt.

Index Scriptorium Estoniae

2011-01-01

24 arvustaja vastus küsimusele, milline oli 2010. aasta parim uudisteos ja debüüt. Parima uudisteosena nimetati enim Kalju Kruusa luulekogu "Tühhja", Ene Mihkelsoni luulekogu "Torn" ning Lauri Sommeri proosaraamatut "Kolm yksiklast". Parimaks debüüdiks peeti Siim Nurkliku näidendit "Kas ma olen nüüd elus".

Sõrve 2008 / Nicholas Wurm, Steven Buchert, Mai Buchert, Sandra Buchert...[jt.

Index Scriptorium Estoniae

2008-01-01

lapsed ja lapsevanemad Austraaliast meenutavad oma viibimist Sõrve lastelaagris: This is a story of a family from Sõrve; Nicholas Wurm - Age 9 (Adelaide); Alan and Debbie Mikkor (Melbourne); Jesse Mikkor's point of view: Age 8; Lauren Mikkor's point of view: Age 13

Haiglavoodisse sattunud patsiendid küsivad internetti / Nils Niitra, Sandra Maasalu

Index Scriptorium Estoniae

Niitra, Nils, 1975-

2006-01-01

Vt. ka Tartu Postimees 16. juuni, lk. 1 ; Postimees : na russkom jazõke 19. juuni, lk. 9. Pärnu haiglas saavad kõik patsiendid, kel tervis lubab, palatis sülearvutiga traadita internetti kasutada. Tartu ja Tallinna haiglates levib WiFi esialgu tagasihoidlikumalt - kui üldse, siis ainult osas ruumidest

Predictability and Prediction for an Experimental Cultural Market

Science.gov (United States)

Colbaugh, Richard; Glass, Kristin; Ormerod, Paul

Individuals are often influenced by the behavior of others, for instance because they wish to obtain the benefits of coordinated actions or infer otherwise inaccessible information. In such situations this social influence decreases the ex ante predictability of the ensuing social dynamics. We claim that, interestingly, these same social forces can increase the extent to which the outcome of a social process can be predicted very early in the process. This paper explores this claim through a theoretical and empirical analysis of the experimental music market described and analyzed in [1]. We propose a very simple model for this music market, assess the predictability of market outcomes through formal analysis of the model, and use insights derived through this analysis to develop algorithms for predicting market share winners, and their ultimate market shares, in the very early stages of the market. The utility of these predictive algorithms is illustrated through analysis of the experimental music market data sets [2].

Earthquake prediction

International Nuclear Information System (INIS)

Ward, P.L.

1978-01-01

The state of the art of earthquake prediction is summarized, the possible responses to such prediction are examined, and some needs in the present prediction program and in research related to use of this new technology are reviewed. Three basic aspects of earthquake prediction are discussed: location of the areas where large earthquakes are most likely to occur, observation within these areas of measurable changes (earthquake precursors) and determination of the area and time over which the earthquake will occur, and development of models of the earthquake source in order to interpret the precursors reliably. 6 figures

Similarities and Differences Between Warped Linear Prediction and Laguerre Linear Prediction

NARCIS (Netherlands)

Brinker, Albertus C. den; Krishnamoorthi, Harish; Verbitskiy, Evgeny A.

2011-01-01

Linear prediction has been successfully applied in many speech and audio processing systems. This paper presents the similarities and differences between two classes of linear prediction schemes, namely, Warped Linear Prediction (WLP) and Laguerre Linear Prediction (LLP). It is shown that both

Predictive Manufacturing: A Classification Strategy to Predict Product Failures

DEFF Research Database (Denmark)

Khan, Abdul Rauf; Schiøler, Henrik; Kulahci, Murat

2018-01-01

manufacturing analytics model that employs a big data approach to predicting product failures; third, we illustrate the issue of high dimensionality, along with statistically redundant information; and, finally, our proposed method will be compared against the well-known classification methods (SVM, K......-nearest neighbor, artificial neural networks). The results from real data show that our predictive manufacturing analytics approach, using genetic algorithms and Voronoi tessellations, is capable of predicting product failure with reasonable accuracy. The potential application of this method contributes...... to accurately predicting product failures, which would enable manufacturers to reduce production costs without compromising product quality....

Kunst aitab klisheesid lõhkuda : prostitutsioon / Reet Varblane

Index Scriptorium Estoniae

Varblane, Reet, 1952-

2007-01-01

Prostitutsiooniteemast kunstis, praeguste prostitutsiooni käsitlevate näituste ("Sex Work. Kunst. Mythos. Realität" Berliinis, Ann-Sofi Sideni projekt "Warte mal! Prostitutsion after the Velvet Revolution" jt.) rollist. Pikemalt näitusest "Kehaturg / Sex market" Tallinna Kunstihoones. Anu Juuraku, Foxy Haze'i, Teemu Mäki, Tatjana Antoshina, Kari Bie Erenurme, Sandra Jõgeva, Shula Kesheti, Deimantas Narkeviciuse ja Pal Hollenderi töödest

Kuidas edasi, "Berlinale"? / Endel Link

Index Scriptorium Estoniae

Link, Endel

2006-01-01

56. Berliini filmifestivali auhinnasaajatest- Kuldkaru saaja bosnialanna Jasmila Zhbavic filmi "Grbavica" eest, režii Hõbekaru saajad britid Michael Winterbottom ja Mat Whitecross filmi eest "Teekond Guatanamosse" ("The Road to Guantanamo"), parima filmi Hõbekaru ja debüüdiauhinna saanud taanlanna Pernille Fischer Christensen filmi "Seep" eest ja iraanlane Jafar Panahi filmi "Suluseis" eest. Parimad näitlejad olid Sandra Hüller ja Moritz Bleibtreu

Berlinale : snõ o Sarajeve

Index Scriptorium Estoniae

2006-01-01

56. Berliini filmifestivali auhinnasaajatest- Kuldkaru saaja bosnialanna Jasmila Zhbavic filmi "Grbavica" eest, režii Hõbekaru saajad britid Michael Winterbottom ja Mat Whitecross filmi eest "Teekond Guatanamosse" ("The Road to Guantanamo"), parima filmi Hõbekaru ja debüüdiauhinna saanud taanlanna Pernille Fischer Christensen filmi "Seep" eest ja iraanlane Jafar Panahi filmi "Suluseis" eest. Parimad näitlejad olid Sandra Hüller ja Moritz Bleibtreu.

Cybertherapy 2005: A Decade of VR

Science.gov (United States)

2005-07-01

Theo & Seth: 1. Precalculus Test quences orally, to order numbers, to decom- (by Neva Milicic and Sandra Schmidt) that pose numbers through audio... Precalculus Test 81 7911 80 6975 -109 1 109 70 •100 91 e60 55 582:t5 30 •46 4 37 20 28 - 10 L _ _19- 10 3 7 - O Pre Test casos 0 Post Test Figure 6-7

Say No to Excess Salt (A Cup of Health with CDC)

Centers for Disease Control (CDC) Podcasts

2016-01-14

Hypertension is a leading cause of heart disease and stroke and occurs in nearly one in three U.S. adults. Reducing salt intake can lower blood pressure, helping to prevent and treat hypertension. In this podcast, Dr. Sandra Jackson discusses the importance of consuming a diet low in sodium.  Created: 1/14/2016 by MMWR.   Date Released: 1/14/2016.

Сандра Баллок поблагодарила Алара Кивило / Тийт Туумалу

Index Scriptorium Estoniae

Туумалу, Тийт, 1971-

2010-01-01

Näitleja Sandra Bullock tänas oma Filminäitlejate Gildi Auhindade (American Screen Actors Guild Awards) tseremoonia tänukõnes ka operaator Alar Kivilod. Artiklis Kanadas sündinud ja Los Angeleses töötavast eesti päritolu filmioperaatorist ning lähemalt tema ühest südamelähedasemast tööst, filmist "Taking Chance" (USA 2009)

Applied predictive control

CERN Document Server

Sunan, Huang; Heng, Lee Tong

2002-01-01

The presence of considerable time delays in the dynamics of many industrial processes, leading to difficult problems in the associated closed-loop control systems, is a well-recognized phenomenon. The performance achievable in conventional feedback control systems can be significantly degraded if an industrial process has a relatively large time delay compared with the dominant time constant. Under these circumstances, advanced predictive control is necessary to improve the performance of the control system significantly. The book is a focused treatment of the subject matter, including the fundamentals and some state-of-the-art developments in the field of predictive control. Three main schemes for advanced predictive control are addressed in this book: • Smith Predictive Control; • Generalised Predictive Control; • a form of predictive control based on Finite Spectrum Assignment. A substantial part of the book addresses application issues in predictive control, providing several interesting case studie...

Development of a regional ensemble prediction method for probabilistic weather prediction

International Nuclear Information System (INIS)

Nohara, Daisuke; Tamura, Hidetoshi; Hirakuchi, Hiromaru

2015-01-01

A regional ensemble prediction method has been developed to provide probabilistic weather prediction using a numerical weather prediction model. To obtain consistent perturbations with the synoptic weather pattern, both of initial and lateral boundary perturbations were given by differences between control and ensemble member of the Japan Meteorological Agency (JMA)'s operational one-week ensemble forecast. The method provides a multiple ensemble member with a horizontal resolution of 15 km for 48-hour based on a downscaling of the JMA's operational global forecast accompanied with the perturbations. The ensemble prediction was examined in the case of heavy snow fall event in Kanto area on January 14, 2013. The results showed that the predictions represent different features of high-resolution spatiotemporal distribution of precipitation affected by intensity and location of extra-tropical cyclone in each ensemble member. Although the ensemble prediction has model bias of mean values and variances in some variables such as wind speed and solar radiation, the ensemble prediction has a potential to append a probabilistic information to a deterministic prediction. (author)

Reliability of windstorm predictions in the ECMWF ensemble prediction system

Science.gov (United States)

Becker, Nico; Ulbrich, Uwe

2016-04-01

Windstorms caused by extratropical cyclones are one of the most dangerous natural hazards in the European region. Therefore, reliable predictions of such storm events are needed. Case studies have shown that ensemble prediction systems (EPS) are able to provide useful information about windstorms between two and five days prior to the event. In this work, ensemble predictions with the European Centre for Medium-Range Weather Forecasts (ECMWF) EPS are evaluated in a four year period. Within the 50 ensemble members, which are initialized every 12 hours and are run for 10 days, windstorms are identified and tracked in time and space. By using a clustering approach, different predictions of the same storm are identified in the different ensemble members and compared to reanalysis data. The occurrence probability of the predicted storms is estimated by fitting a bivariate normal distribution to the storm track positions. Our results show, for example, that predicted storm clusters with occurrence probabilities of more than 50% have a matching observed storm in 80% of all cases at a lead time of two days. The predicted occurrence probabilities are reliable up to 3 days lead time. At longer lead times the occurrence probabilities are overestimated by the EPS.

Accurate and dynamic predictive model for better prediction in medicine and healthcare.

Science.gov (United States)

Alanazi, H O; Abdullah, A H; Qureshi, K N; Ismail, A S

2018-05-01

Information and communication technologies (ICTs) have changed the trend into new integrated operations and methods in all fields of life. The health sector has also adopted new technologies to improve the systems and provide better services to customers. Predictive models in health care are also influenced from new technologies to predict the different disease outcomes. However, still, existing predictive models have suffered from some limitations in terms of predictive outcomes performance. In order to improve predictive model performance, this paper proposed a predictive model by classifying the disease predictions into different categories. To achieve this model performance, this paper uses traumatic brain injury (TBI) datasets. TBI is one of the serious diseases worldwide and needs more attention due to its seriousness and serious impacts on human life. The proposed predictive model improves the predictive performance of TBI. The TBI data set is developed and approved by neurologists to set its features. The experiment results show that the proposed model has achieved significant results including accuracy, sensitivity, and specificity.

Computational prediction of protein-protein interactions in Leishmania predicted proteomes.

Directory of Open Access Journals (Sweden)

Antonio M Rezende

Full Text Available The Trypanosomatids parasites Leishmania braziliensis, Leishmania major and Leishmania infantum are important human pathogens. Despite of years of study and genome availability, effective vaccine has not been developed yet, and the chemotherapy is highly toxic. Therefore, it is clear just interdisciplinary integrated studies will have success in trying to search new targets for developing of vaccines and drugs. An essential part of this rationale is related to protein-protein interaction network (PPI study which can provide a better understanding of complex protein interactions in biological system. Thus, we modeled PPIs for Trypanosomatids through computational methods using sequence comparison against public database of protein or domain interaction for interaction prediction (Interolog Mapping and developed a dedicated combined system score to address the predictions robustness. The confidence evaluation of network prediction approach was addressed using gold standard positive and negative datasets and the AUC value obtained was 0.94. As result, 39,420, 43,531 and 45,235 interactions were predicted for L. braziliensis, L. major and L. infantum respectively. For each predicted network the top 20 proteins were ranked by MCC topological index. In addition, information related with immunological potential, degree of protein sequence conservation among orthologs and degree of identity compared to proteins of potential parasite hosts was integrated. This information integration provides a better understanding and usefulness of the predicted networks that can be valuable to select new potential biological targets for drug and vaccine development. Network modularity which is a key when one is interested in destabilizing the PPIs for drug or vaccine purposes along with multiple alignments of the predicted PPIs were performed revealing patterns associated with protein turnover. In addition, around 50% of hypothetical protein present in the networks

Kuldkaru sai Bosnia naisrežissöör / Grete Nootre

Index Scriptorium Estoniae

Nootre, Grete

2006-01-01

56. Berliini filmifestivali auhinnasaajatest- Kuldkaru saaja bosnialanna Jasmila Zhbavic filmi "Grbavica" eest, režii Hõbekaru saajad britid Michael Winterbottom ja Mat Whitecross filmi eest "Teekond Guatanamosse" ("The Road to Guantanamo"), parima filmi Hõbekaru ja debüüdiauhinna saanud taanlanna Pernille Fischer Christensen filmi "Seep" eest ja iraanlane Jafar Panahi filmi "Suluseis" eest. Parimad näitlejad olid Sandra Hüller ja Moritz Bleibtreu. Lisatud nimekiri "Võitjad"

Surm kevadises Tallinnas ehk Kunstnike valuline reaktsioon meie ajale / Reet Varblane

Index Scriptorium Estoniae

Varblane, Reet, 1952-

2006-01-01

Mark Soosaare näitus "Aeg" Tallinna Kunstihoone galeriis kuni 23. IV, Jaan Paavle maalinäitus "1 minut" 3.-15. IV Draakoni galeriis, Sandra Jõgeva ja Kristin Kalamehe "Leave like a Lady" Draakoni galerii keldrisaalis 4.-15. IV, Marianne Männi näitus "Paradiis" Hobusepea galeriis 5.-17. IV. Maailma positiivsemale poolusele osutab 20. IV Tallinna Linnagaleriis avatud Mari ja Kaarel Kurismaa ruumiinstallatsioon "Teine süütus"

The Role of IDO in Muc1 Targeted Immunotherapy

Science.gov (United States)

2013-01-01

Besmer*, Teresa L. Tinder , Lopamudra Das Roy, Joseph Lustgarten, Sandra J. Gendler, Pinku Mukherjee Intratumoral Delivery of CpG-Conjugated Anti...3073-87. Epub 2012 Jan 11. PMID: 22238308 3. Mahnaz Sahraei , Lopamudra Das Roy , Jennifer Curry , Teresa Tinder , Sritama Nath , Dahlia M...10.1038/onc.2011.651 4. Dahlia M. Besmer , Dr. Jennifer M. Curry , Dr. Lopamudra D. Roy , Ms. Teresa L. Tinder , Ms. Mahnaz M. Sahraei , Dr

Pathophysiology, risk factors, and screening methods for prediabetes in women with polycystic ovary syndrome

OpenAIRE

Gourgari, Evgenia; Spanakis,Elias; Dobs,Adrian

2016-01-01

Evgenia Gourgari,1 Elias Spanakis,2 Adrian Sandra Dobs3 1Division of Pediatric Endocrinology, Georgetown University School of Medicine, Washington, DC, 2Division of Endocrinology, University of Maryland School of Medicine, 3Department of Endocrinology, Johns Hopkins University School of Medicine, Baltimore, MD, USA Abstract: Polycystic ovary syndrome (PCOS) is a syndrome associated with insulin resistance (IR), obesity, infertility, and increased cardiometabolic risk. This is a des...

Eripalgeline universum Polymeri kultuuritehases / Marian Kivila

Index Scriptorium Estoniae

Kivila, Marian

2008-01-01

23. V toimunud rahvusvahelise tegevuskunstifestivali "Diverse Universe IV" performance''i-programmist Non Grata Kunstikonteineris Kultuuritehases Polymer. Sandra Jõgeva ja rühmituse Cnopt, rühmituse Non Grata, korealase Kim Baek-Ki ning sakslaste Micha Stegeri ja Andreas Stadleri, poolakate Marta Zioleki ja Agata Siniarska, ameeriklase Travis McCoy Fulleri, Russ Butleri (Bermuda), rühmituse HorseCow (Sacramento) performance'itest. Lühidalt Non Grata videonäitusest

Predictive systems ecology.

Science.gov (United States)

Evans, Matthew R; Bithell, Mike; Cornell, Stephen J; Dall, Sasha R X; Díaz, Sandra; Emmott, Stephen; Ernande, Bruno; Grimm, Volker; Hodgson, David J; Lewis, Simon L; Mace, Georgina M; Morecroft, Michael; Moustakas, Aristides; Murphy, Eugene; Newbold, Tim; Norris, K J; Petchey, Owen; Smith, Matthew; Travis, Justin M J; Benton, Tim G

2013-11-22

Human societies, and their well-being, depend to a significant extent on the state of the ecosystems that surround them. These ecosystems are changing rapidly usually in response to anthropogenic changes in the environment. To determine the likely impact of environmental change on ecosystems and the best ways to manage them, it would be desirable to be able to predict their future states. We present a proposal to develop the paradigm of predictive systems ecology, explicitly to understand and predict the properties and behaviour of ecological systems. We discuss the necessary and desirable features of predictive systems ecology models. There are places where predictive systems ecology is already being practised and we summarize a range of terrestrial and marine examples. Significant challenges remain but we suggest that ecology would benefit both as a scientific discipline and increase its impact in society if it were to embrace the need to become more predictive.

Predictable or not predictable? The MOV question

International Nuclear Information System (INIS)

Thibault, C.L.; Matzkiw, J.N.; Anderson, J.W.; Kessler, D.W.

1994-01-01

Over the past 8 years, the nuclear industry has struggled to understand the dynamic phenomena experienced during motor-operated valve (MOV) operation under differing flow conditions. For some valves and designs, their operational functionality has been found to be predictable; for others, unpredictable. Although much has been accomplished over this period of time, especially on modeling valve dynamics, the unpredictability of many valves and designs still exists. A few valve manufacturers are focusing on improving design and fabrication techniques to enhance product reliability and predictability. However, this approach does not address these issues for installed and inpredictable valves. This paper presents some of the more promising techniques that Wyle Laboratories has explored with potential for transforming unpredictable valves to predictable valves and for retrofitting installed MOVs. These techniques include optimized valve tolerancing, surrogated material evaluation, and enhanced surface treatments

Neural Fuzzy Inference System-Based Weather Prediction Model and Its Precipitation Predicting Experiment

Directory of Open Access Journals (Sweden)

Jing Lu

2014-11-01

Full Text Available We propose a weather prediction model in this article based on neural network and fuzzy inference system (NFIS-WPM, and then apply it to predict daily fuzzy precipitation given meteorological premises for testing. The model consists of two parts: the first part is the “fuzzy rule-based neural network”, which simulates sequential relations among fuzzy sets using artificial neural network; and the second part is the “neural fuzzy inference system”, which is based on the first part, but could learn new fuzzy rules from the previous ones according to the algorithm we proposed. NFIS-WPM (High Pro and NFIS-WPM (Ave are improved versions of this model. It is well known that the need for accurate weather prediction is apparent when considering the benefits. However, the excessive pursuit of accuracy in weather prediction makes some of the “accurate” prediction results meaningless and the numerical prediction model is often complex and time-consuming. By adapting this novel model to a precipitation prediction problem, we make the predicted outcomes of precipitation more accurate and the prediction methods simpler than by using the complex numerical forecasting model that would occupy large computation resources, be time-consuming and which has a low predictive accuracy rate. Accordingly, we achieve more accurate predictive precipitation results than by using traditional artificial neural networks that have low predictive accuracy.

Prediction of residential radon exposure of the whole Swiss population: comparison of model-based predictions with measurement-based predictions.

Science.gov (United States)

Hauri, D D; Huss, A; Zimmermann, F; Kuehni, C E; Röösli, M

2013-10-01

Radon plays an important role for human exposure to natural sources of ionizing radiation. The aim of this article is to compare two approaches to estimate mean radon exposure in the Swiss population: model-based predictions at individual level and measurement-based predictions based on measurements aggregated at municipality level. A nationwide model was used to predict radon levels in each household and for each individual based on the corresponding tectonic unit, building age, building type, soil texture, degree of urbanization, and floor. Measurement-based predictions were carried out within a health impact assessment on residential radon and lung cancer. Mean measured radon levels were corrected for the average floor distribution and weighted with population size of each municipality. Model-based predictions yielded a mean radon exposure of the Swiss population of 84.1 Bq/m(3) . Measurement-based predictions yielded an average exposure of 78 Bq/m(3) . This study demonstrates that the model- and the measurement-based predictions provided similar results. The advantage of the measurement-based approach is its simplicity, which is sufficient for assessing exposure distribution in a population. The model-based approach allows predicting radon levels at specific sites, which is needed in an epidemiological study, and the results do not depend on how the measurement sites have been selected. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Predictive modeling of complications.

Science.gov (United States)

Osorio, Joseph A; Scheer, Justin K; Ames, Christopher P

2016-09-01

Predictive analytic algorithms are designed to identify patterns in the data that allow for accurate predictions without the need for a hypothesis. Therefore, predictive modeling can provide detailed and patient-specific information that can be readily applied when discussing the risks of surgery with a patient. There are few studies using predictive modeling techniques in the adult spine surgery literature. These types of studies represent the beginning of the use of predictive analytics in spine surgery outcomes. We will discuss the advancements in the field of spine surgery with respect to predictive analytics, the controversies surrounding the technique, and the future directions.

Predictive medicine

NARCIS (Netherlands)

Boenink, Marianne; ten Have, Henk

2015-01-01

In the last part of the twentieth century, predictive medicine has gained currency as an important ideal in biomedical research and health care. Research in the genetic and molecular basis of disease suggested that the insights gained might be used to develop tests that predict the future health

Predictability of Conversation Partners

Science.gov (United States)

Takaguchi, Taro; Nakamura, Mitsuhiro; Sato, Nobuo; Yano, Kazuo; Masuda, Naoki

2011-08-01

Recent developments in sensing technologies have enabled us to examine the nature of human social behavior in greater detail. By applying an information-theoretic method to the spatiotemporal data of cell-phone locations, [C. Song , ScienceSCIEAS0036-8075 327, 1018 (2010)] found that human mobility patterns are remarkably predictable. Inspired by their work, we address a similar predictability question in a different kind of human social activity: conversation events. The predictability in the sequence of one’s conversation partners is defined as the degree to which one’s next conversation partner can be predicted given the current partner. We quantify this predictability by using the mutual information. We examine the predictability of conversation events for each individual using the longitudinal data of face-to-face interactions collected from two company offices in Japan. Each subject wears a name tag equipped with an infrared sensor node, and conversation events are marked when signals are exchanged between sensor nodes in close proximity. We find that the conversation events are predictable to a certain extent; knowing the current partner decreases the uncertainty about the next partner by 28.4% on average. Much of the predictability is explained by long-tailed distributions of interevent intervals. However, a predictability also exists in the data, apart from the contribution of their long-tailed nature. In addition, an individual’s predictability is correlated with the position of the individual in the static social network derived from the data. Individuals confined in a community—in the sense of an abundance of surrounding triangles—tend to have low predictability, and those bridging different communities tend to have high predictability.

Predictability of Conversation Partners

Directory of Open Access Journals (Sweden)

Taro Takaguchi

2011-09-01

Full Text Available Recent developments in sensing technologies have enabled us to examine the nature of human social behavior in greater detail. By applying an information-theoretic method to the spatiotemporal data of cell-phone locations, [C. Song et al., Science 327, 1018 (2010SCIEAS0036-8075] found that human mobility patterns are remarkably predictable. Inspired by their work, we address a similar predictability question in a different kind of human social activity: conversation events. The predictability in the sequence of one’s conversation partners is defined as the degree to which one’s next conversation partner can be predicted given the current partner. We quantify this predictability by using the mutual information. We examine the predictability of conversation events for each individual using the longitudinal data of face-to-face interactions collected from two company offices in Japan. Each subject wears a name tag equipped with an infrared sensor node, and conversation events are marked when signals are exchanged between sensor nodes in close proximity. We find that the conversation events are predictable to a certain extent; knowing the current partner decreases the uncertainty about the next partner by 28.4% on average. Much of the predictability is explained by long-tailed distributions of interevent intervals. However, a predictability also exists in the data, apart from the contribution of their long-tailed nature. In addition, an individual’s predictability is correlated with the position of the individual in the static social network derived from the data. Individuals confined in a community—in the sense of an abundance of surrounding triangles—tend to have low predictability, and those bridging different communities tend to have high predictability.

21st Century Water Conservation Principles

Science.gov (United States)

Narayanan, M.

2013-12-01

report details key priorities for the Agency: Many researchers are of the opinion that applying the principles of free market enterprise to water conservation ideas would result in a more efficient utilization of water supply and distribution everywhere. References: EPA's June 2011 Strategic Sustainability Performance Plan (SSPP) (PDF) (74 pp, 1MB) June 2010 EPA Strategic Sustainability Performance Plan (PDF) (67 pp, 3.8MB) U.S. EPA Policy Statement on Climate-Change Adaptation (PDF) (3pp, 55KB) Narayanan, Mysore. (2008). Hydrology, Water Scarcity and Market Economics. 68th AGU International Conference. Eos Transactions: American Geophysical Union, Vol. 89, No. 53, Fall Meeting Supplement, 2009. H11E - 0801. Postel, Sandra L. The Last Oasis: Facing Water Scarcity. New York: W. W. Norton and Company. 1997. Falkenmark, M.J. and Rockström, J. (2004). Balancing Water For Humans and Nature. Sterling, VA. Earthscan. Giordano, M. (2006) Agricultural Groundwater Use and Rural Livelihoods Journal of Hydrogeology. 14, 310 - 318. Allan, J.A. (2003). Virtual Water. Useful Concept or Misleading Metaphor? Water International. 28, 4-11. Vörsömarty, C.J., Douglas, E.M., Green, P.A. and Revenga, C. 2005. Geospatial Indicators of Energing Water Stress. Ambio, 34. 230-236.

The Importance of Water Conservation in the 21st Century

Science.gov (United States)

Narayanan, M.

2012-12-01

Performance Plan. The report details key priorities for the Agency: 1. GHG emissions inventories and reduction through energy efficiency, renewable energy, and transportation management. 2. High-performance sustainable buildings. 3. Regional and local planning. 4. Water conservation. 5. Recycling and pollution prevention. 6. Sustainable acquisition. 7. Electronics stewardship. Many researchers are of the opinion that applying the principles of free market enterprise to water conservation ideas would result in a more efficient utilization of water supply and distribution everywhere. References: EPA's June 2011 Strategic Sustainability Performance Plan (SSPP) (PDF) (74 pp, 1MB) June 2010 EPA Strategic Sustainability Performance Plan (PDF) (67 pp, 3.8MB) U.S. EPA Policy Statement on Climate-Change Adaptation (PDF) (3pp, 55KB) Narayanan, Mysore. (2008). Hydrology, Water Scarcity and Market Economics. 68th AGU International Conference. Eos Transactions: American Geophysical Union, Vol. 89, No. 53, Fall Meeting Supplement, 2009. H11E - 0801. Postel, Sandra L. The Last Oasis: Facing Water Scarcity. New York: W. W. Norton and Company. 1997.

Structural prediction in aphasia

Directory of Open Access Journals (Sweden)

Tessa Warren

2015-05-01

Full Text Available There is considerable evidence that young healthy comprehenders predict the structure of upcoming material, and that their processing is facilitated when they encounter material matching those predictions (e.g., Staub & Clifton, 2006; Yoshida, Dickey & Sturt, 2013. However, less is known about structural prediction in aphasia. There is evidence that lexical prediction may be spared in aphasia (Dickey et al., 2014; Love & Webb, 1977; cf. Mack et al, 2013. However, predictive mechanisms supporting facilitated lexical access may not necessarily support structural facilitation. Given that many people with aphasia (PWA exhibit syntactic deficits (e.g. Goodglass, 1993, PWA with such impairments may not engage in structural prediction. However, recent evidence suggests that some PWA may indeed predict upcoming structure (Hanne, Burchert, De Bleser, & Vashishth, 2015. Hanne et al. tracked the eyes of PWA (n=8 with sentence-comprehension deficits while they listened to reversible subject-verb-object (SVO and object-verb-subject (OVS sentences in German, in a sentence-picture matching task. Hanne et al. manipulated case and number marking to disambiguate the sentences’ structure. Gazes to an OVS or SVO picture during the unfolding of a sentence were assumed to indicate prediction of the structure congruent with that picture. According to this measure, the PWA’s structural prediction was impaired compared to controls, but they did successfully predict upcoming structure when morphosyntactic cues were strong and unambiguous. Hanne et al.’s visual-world evidence is suggestive, but their forced-choice sentence-picture matching task places tight constraints on possible structural predictions. Clearer evidence of structural prediction would come from paradigms where the content of upcoming material is not as constrained. The current study used self-paced reading study to examine structural prediction among PWA in less constrained contexts. PWA (n=17 who

Uus kaasaegse kunsti näitusepaik Riias / Inga Lace ; interv. Sandra Jõgeva

Index Scriptorium Estoniae

Lace, Inga

2008-01-01

Riia Kunstiruumi (Riga Art Space) turundusjuht Inga Lace Raekoja platsi all asuvast uuest näitusepaigast, selle tööpõhimõtetest ning eesti kunstnike - Jaan Tooniku ja Andrus Joonase näitus suures saalis, Kaido Ole ja Tõnis Saadoja näitus väikses saalis- vastuvõtust Lätis. Septembris avatakse Johannes Saare kureeritud rahvusvaheline projekt "Halb nali"

Ground motion predictions

Energy Technology Data Exchange (ETDEWEB)

Loux, P C [Environmental Research Corporation, Alexandria, VA (United States)

1969-07-01

Nuclear generated ground motion is defined and then related to the physical parameters that cause it. Techniques employed for prediction of ground motion peak amplitude, frequency spectra and response spectra are explored, with initial emphasis on the analysis of data collected at the Nevada Test Site (NTS). NTS postshot measurements are compared with pre-shot predictions. Applicability of these techniques to new areas, for example, Plowshare sites, must be questioned. Fortunately, the Atomic Energy Commission is sponsoring complementary studies to improve prediction capabilities primarily in new locations outside the NTS region. Some of these are discussed in the light of anomalous seismic behavior, and comparisons are given showing theoretical versus experimental results. In conclusion, current ground motion prediction techniques are applied to events off the NTS. Predictions are compared with measurements for the event Faultless and for the Plowshare events, Gasbuggy, Cabriolet, and Buggy I. (author)

Evaluating prediction uncertainty

International Nuclear Information System (INIS)

McKay, M.D.

1995-03-01

The probability distribution of a model prediction is presented as a proper basis for evaluating the uncertainty in a model prediction that arises from uncertainty in input values. Determination of important model inputs and subsets of inputs is made through comparison of the prediction distribution with conditional prediction probability distributions. Replicated Latin hypercube sampling and variance ratios are used in estimation of the distributions and in construction of importance indicators. The assumption of a linear relation between model output and inputs is not necessary for the indicators to be effective. A sequential methodology which includes an independent validation step is applied in two analysis applications to select subsets of input variables which are the dominant causes of uncertainty in the model predictions. Comparison with results from methods which assume linearity shows how those methods may fail. Finally, suggestions for treating structural uncertainty for submodels are presented

Ground motion predictions

International Nuclear Information System (INIS)

Loux, P.C.

1969-01-01

Nuclear generated ground motion is defined and then related to the physical parameters that cause it. Techniques employed for prediction of ground motion peak amplitude, frequency spectra and response spectra are explored, with initial emphasis on the analysis of data collected at the Nevada Test Site (NTS). NTS postshot measurements are compared with pre-shot predictions. Applicability of these techniques to new areas, for example, Plowshare sites, must be questioned. Fortunately, the Atomic Energy Commission is sponsoring complementary studies to improve prediction capabilities primarily in new locations outside the NTS region. Some of these are discussed in the light of anomalous seismic behavior, and comparisons are given showing theoretical versus experimental results. In conclusion, current ground motion prediction techniques are applied to events off the NTS. Predictions are compared with measurements for the event Faultless and for the Plowshare events, Gasbuggy, Cabriolet, and Buggy I. (author)

Andrographolide potentiates the antitumor effect of topotecan in acute myeloid leukemia cells through an intrinsic apoptotic pathway

OpenAIRE

Hodroj,Mohammad Hassan; Jardaly,Achraf; abi Raad,Sarah; Zouein,Annalise; Rizk,Sandra

2018-01-01

Mohammad Hassan Hodroj, Achraf Jardaly, Sarah Abi Raad, Annalise Zouein, Sandra Rizk Department of Natural Sciences, Lebanese American University, Beirut, Lebanon Background: Topotecan (TP) is an anticancer drug acting as topoisomerase I inhibitor that is used in the treatment of many types of cancers including leukemia, but it has significant side effects. Andrographolide, a compound extracted from Andrographis paniculata, was recently proven to inhibit the growth of cancer cells and can ind...

Microbial ecology at the International Space Station: the use of rapid and easy molecular methods for the quantitative detection of bacteria

OpenAIRE

van Tongeren, Sandra P.

2011-01-01

Bij lange, bemande ruimtemissies, bijvoorbeeld naar Mars, kan gevaar schuilen in de kleinste hoekjes. Dat blijkt uit het promotieonderzoek van Sandra van Tongeren. Zij stelt onder meer vast dat al bij kortdurende ruimtemissies opmerkelijke veranderingen optreden in de hoeveelheden en soorten micro-organismen in en op het lichaam van de ruimtevaarder. Van Tongeren analyseerde monsters die werden genomen tijdens korte ruimtemissies naar de Russische Zvezda-module van het ISS, van 2004 tot 2007....

La pelle del selfie

Directory of Open Access Journals (Sweden)

Theresa Senft

2015-12-01

Full Text Available This is an essay about power and faces. Specifically, it about the faces that manifest in the global self-imaging practice referred to as “selfie culture.” More specifically still, it is about circulation of selfies featuring the face of Sandra Bland, an African American activist with the group Black Lives Matter, who police claim hung herself in a cell after being imprisoned after a routine traffic stop.

Gateway. Volume 13

Science.gov (United States)

2003-01-01

Unclassified 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Hart, Sandra G ; Drury , Colin G ; Hancock, Peter A ; Szalma, James...interventions, thereby improving threat inspection and, ultimately, homeland security. n For more information please contact: Colin G. Drury , Ph.D. University...at Buffalo, SUNY Department of Industrial Engineering 342 Bell Hell Hall Buffalo, NY 14260 A Unified Model of Security Inspection Colin G. Drury

Celiac Family Health Education Video Series

Medline Plus

Full Text Available ... condition. We are grateful to have been ranked #1 on U.S. News & World Report's list of the best children's hospitals in the nation for the fourth ... families who inspire us to do our very best for them. Thanks to you, Boston Children's is a place where we can write the greatest children's stories ever told. Sandra L. Fenwick, ... Boston Children's Hospital #1 Ranked Children's Hospital by U. S. News & World Report ...

Poor physical function in elderly women in low-level aged care is related to muscle strength rather than to measures of sarcopenia

OpenAIRE

Walker, Karen; Woods,; Iuliano-Burns,Sandra; King,Susannah; Strauss,Boyd

2011-01-01

Julie L Woods1, Sandra Iuliano-Burns2, Susannah J King1, Boyd J Strauss1, Karen Z Walker11Nutrition and Dietetics Department, Monash University, Victoria, Australia; 2Endocrine Centre of Excellence, Department of Medicine, Austin Health, University of Melbourne, West Heidelberg, AustraliaPurpose: To determine the prevalence of sarcopenia and investigate relationships among body composition, muscle strength, and physical function in elderly women in low-level aged care.Subjects and methods: Si...

Effect of Multiple Simultaneous Vaccines on Polio Seroresponse and Associated Health Outcomes

Science.gov (United States)

2015-01-01

Broderick M. Steven Oberste Deborah Moore Sandra Romero-Steiner Christian J. Hansen Dennis J. Faix Report No. 13-53 The views expressed in...michael.broderick@med.navy.mil (M.P. Broderick ). 1 Current address: Office of Public Health Preparedness and Response, CDC, tlanta, GA 30333, USA. ttp...titers examined were those of polio, not of other vaccines givenM.P. Broderick et al. / V utcomes were associated with receipt of the same vaccinations

Intelligence Operations In Small Wars: A Comparison Of The Malayan Emergency And Vietnam War

Science.gov (United States)

2013-04-01

Effect, 18. 41 Spencer C. Tucker, David Coffey, Nguyen Cong Luan, Nike Nichols, and Sandra Wittman, eds, Encyclopedia of the Vietnam War Volume One: A...War: The Unexamined Victories and Final Tragedy of America’s Last Years in Vietnam, (Orlando, FL :Harcourt, Inc ., 1999), 72-73. 91 Sorley, A Better...Victories and Final Tragedy of America’s Last Years in Vietnam. Orlando, FL: Harcourt, Inc ., 1999. Stubbs, Richard. Hearts and Minds in

Swarming Mechanisms in the Yellow Fever Mosquito: Aggregation Pheromones are Involved in the Mating Behavior of Aedes aegypti

Science.gov (United States)

2014-12-01

behavior of Aedes aegypti Emadeldin Y. Fawaz1, Sandra A. Allan2, Ulrich R. Bernier2, Peter J. Obenauer3, and Joseph W. Diclaro II1 1Vector Biology... Aedes aegypti swarming behavior and identified associated chemical cues. Novel evidence is provided that Ae. aegypti females aggregate by means of...the isolated aggregation pheromones in controlling Ae. aegypti. Journal of Vector Ecology 39 (2): 347-354. 2014. Keyword Index: Aedes aegypti, swarm

Lipid-lowering therapy: who can benefit?

OpenAIRE

Lewis, Sandra J

2011-01-01

Sandra J LewisNorthwest Cardiovascular Institute, Portland, OR, USAAbstract: Cardiovascular disease (CVD) is the leading cause of death in the US. Despite the decline in CVD-associated mortality rates in recent years, coronary heart disease (CHD) still causes one in every six deaths in this country. Because most CHD risk factors are modifiable (eg, smoking, hypertension, obesity, onset of type 2 diabetes, and dyslipidemia), cardiovascular risk can be reduced by timely and appropriate interven...

Maailm Berlinale filmipeeglis. Kus oleme meie? / Annika Koppel

Index Scriptorium Estoniae

Koppel, Annika

2006-01-01

56. Berliini filmifestivali auhinnasaajatest- Kuldkaru saaja bosnialanna Jasmila Zhbavic filmi "Grbavica" eest, režii Hõbekaru saajad britid Michael Winterbottom ja Mat Whitecross filmi eest "Teekond Guatanamosse" ("The Road to Guantanamo"), parima filmi Hõbekaru ja debüüdiauhinna saanud taanlanna Pernille Fischer Christensen filmi "Seep" eest ja iraanlane Jafar Panahi filmi "Suluseis" eest. Parimad näitlejad olid Sandra Hüller ja Moritz Bleibtreu. Eestlased filmiturul. Lisatud nimekiri "56. Berliini rahvusvahelise filmifestivali auhinnad"

Cloud prediction of protein structure and function with PredictProtein for Debian.

Science.gov (United States)

Kaján, László; Yachdav, Guy; Vicedo, Esmeralda; Steinegger, Martin; Mirdita, Milot; Angermüller, Christof; Böhm, Ariane; Domke, Simon; Ertl, Julia; Mertes, Christian; Reisinger, Eva; Staniewski, Cedric; Rost, Burkhard

2013-01-01

We report the release of PredictProtein for the Debian operating system and derivatives, such as Ubuntu, Bio-Linux, and Cloud BioLinux. The PredictProtein suite is available as a standard set of open source Debian packages. The release covers the most popular prediction methods from the Rost Lab, including methods for the prediction of secondary structure and solvent accessibility (profphd), nuclear localization signals (predictnls), and intrinsically disordered regions (norsnet). We also present two case studies that successfully utilize PredictProtein packages for high performance computing in the cloud: the first analyzes protein disorder for whole organisms, and the second analyzes the effect of all possible single sequence variants in protein coding regions of the human genome.

Ljubav koja prihvaća i paradoksi (političke) umjetnosti u Sjevernoj Irskoj: Sandra Johnston = Accepting Love and the Paradoxes of (Political) Art in Northern Ireland: Sandra Johnston

NARCIS (Netherlands)

Lerm-Hayes, C.M.

2017-01-01

City branding of contested cities with violent histories has taken hold of hearts, but what kind of love is conducive to establishing and furthering democratic communities - and how can artists approach this subject matter in a credible way? In Belfast, Northern Ireland, o cials decided to demolish

MJO prediction skill of the subseasonal-to-seasonal (S2S) prediction models

Science.gov (United States)

Son, S. W.; Lim, Y.; Kim, D.

2017-12-01

The Madden-Julian Oscillation (MJO), the dominant mode of tropical intraseasonal variability, provides the primary source of tropical and extratropical predictability on subseasonal to seasonal timescales. To better understand its predictability, this study conducts quantitative evaluation of MJO prediction skill in the state-of-the-art operational models participating in the subseasonal-to-seasonal (S2S) prediction project. Based on bivariate correlation coefficient of 0.5, the S2S models exhibit MJO prediction skill ranging from 12 to 36 days. These prediction skills are affected by both the MJO amplitude and phase errors, the latter becoming more important with forecast lead times. Consistent with previous studies, the MJO events with stronger initial amplitude are typically better predicted. However, essentially no sensitivity to the initial MJO phase is observed. Overall MJO prediction skill and its inter-model spread are further related with the model mean biases in moisture fields and longwave cloud-radiation feedbacks. In most models, a dry bias quickly builds up in the deep tropics, especially across the Maritime Continent, weakening horizontal moisture gradient. This likely dampens the organization and propagation of MJO. Most S2S models also underestimate the longwave cloud-radiation feedbacks in the tropics, which may affect the maintenance of the MJO convective envelop. In general, the models with a smaller bias in horizontal moisture gradient and longwave cloud-radiation feedbacks show a higher MJO prediction skill, suggesting that improving those processes would enhance MJO prediction skill.

Weighted-Average Least Squares Prediction

NARCIS (Netherlands)

Magnus, Jan R.; Wang, Wendun; Zhang, Xinyu

2016-01-01

Prediction under model uncertainty is an important and difficult issue. Traditional prediction methods (such as pretesting) are based on model selection followed by prediction in the selected model, but the reported prediction and the reported prediction variance ignore the uncertainty from the

Dopamine reward prediction error coding.

Science.gov (United States)

Schultz, Wolfram

2016-03-01

Reward prediction errors consist of the differences between received and predicted rewards. They are crucial for basic forms of learning about rewards and make us strive for more rewards-an evolutionary beneficial trait. Most dopamine neurons in the midbrain of humans, monkeys, and rodents signal a reward prediction error; they are activated by more reward than predicted (positive prediction error), remain at baseline activity for fully predicted rewards, and show depressed activity with less reward than predicted (negative prediction error). The dopamine signal increases nonlinearly with reward value and codes formal economic utility. Drugs of addiction generate, hijack, and amplify the dopamine reward signal and induce exaggerated, uncontrolled dopamine effects on neuronal plasticity. The striatum, amygdala, and frontal cortex also show reward prediction error coding, but only in subpopulations of neurons. Thus, the important concept of reward prediction errors is implemented in neuronal hardware.

"When does making detailed predictions make predictions worse?": Correction to Kelly and Simmons (2016).

Science.gov (United States)

2016-10-01

Reports an error in "When Does Making Detailed Predictions Make Predictions Worse" by Theresa F. Kelly and Joseph P. Simmons ( Journal of Experimental Psychology: General , Advanced Online Publication, Aug 8, 2016, np). In the article, the symbols in Figure 2 were inadvertently altered in production. All versions of this article have been corrected. (The following abstract of the original article appeared in record 2016-37952-001.) In this article, we investigate whether making detailed predictions about an event worsens other predictions of the event. Across 19 experiments, 10,896 participants, and 407,045 predictions about 724 professional sports games, we find that people who made detailed predictions about sporting events (e.g., how many hits each baseball team would get) made worse predictions about more general outcomes (e.g., which team would win). We rule out that this effect is caused by inattention or fatigue, thinking too hard, or a differential reliance on holistic information about the teams. Instead, we find that thinking about game-relevant details before predicting winning teams causes people to give less weight to predictive information, presumably because predicting details makes useless or redundant information more accessible and thus more likely to be incorporated into forecasts. Furthermore, we show that this differential use of information can be used to predict what kinds of events will and will not be susceptible to the negative effect of making detailed predictions. PsycINFO Database Record (c) 2016 APA, all rights reserved

Automatically explaining machine learning prediction results: a demonstration on type 2 diabetes risk prediction.

Science.gov (United States)

Luo, Gang

2016-01-01

Predictive modeling is a key component of solutions to many healthcare problems. Among all predictive modeling approaches, machine learning methods often achieve the highest prediction accuracy, but suffer from a long-standing open problem precluding their widespread use in healthcare. Most machine learning models give no explanation for their prediction results, whereas interpretability is essential for a predictive model to be adopted in typical healthcare settings. This paper presents the first complete method for automatically explaining results for any machine learning predictive model without degrading accuracy. We did a computer coding implementation of the method. Using the electronic medical record data set from the Practice Fusion diabetes classification competition containing patient records from all 50 states in the United States, we demonstrated the method on predicting type 2 diabetes diagnosis within the next year. For the champion machine learning model of the competition, our method explained prediction results for 87.4 % of patients who were correctly predicted by the model to have type 2 diabetes diagnosis within the next year. Our demonstration showed the feasibility of automatically explaining results for any machine learning predictive model without degrading accuracy.

Predictive Modelling and Time: An Experiment in Temporal Archaeological Predictive Models

OpenAIRE

David Ebert

2006-01-01

One of the most common criticisms of archaeological predictive modelling is that it fails to account for temporal or functional differences in sites. However, a practical solution to temporal or functional predictive modelling has proven to be elusive. This article discusses temporal predictive modelling, focusing on the difficulties of employing temporal variables, then introduces and tests a simple methodology for the implementation of temporal modelling. The temporal models thus created ar...

NOAA's National Air Quality Predictions and Development of Aerosol and Atmospheric Composition Prediction Components for the Next Generation Global Prediction System

Science.gov (United States)

Stajner, I.; Hou, Y. T.; McQueen, J.; Lee, P.; Stein, A. F.; Tong, D.; Pan, L.; Huang, J.; Huang, H. C.; Upadhayay, S.

2016-12-01

NOAA provides operational air quality predictions using the National Air Quality Forecast Capability (NAQFC): ozone and wildfire smoke for the United States and airborne dust for the contiguous 48 states at http://airquality.weather.gov. NOAA's predictions of fine particulate matter (PM2.5) became publicly available in February 2016. Ozone and PM2.5 predictions are produced using a system that operationally links the Community Multiscale Air Quality (CMAQ) model with meteorological inputs from the North American mesoscale forecast Model (NAM). Smoke and dust predictions are provided using the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model. Current NAQFC focus is on updating CMAQ to version 5.0.2, improving PM2.5 predictions, and updating emissions estimates, especially for NOx using recently observed trends. Wildfire smoke emissions from a newer version of the USFS BlueSky system are being included in a new configuration of the NAQFC NAM-CMAQ system, which is re-run for the previous 24 hours when the wildfires were observed from satellites, to better represent wildfire emissions prior to initiating predictions for the next 48 hours. In addition, NOAA is developing the Next Generation Global Prediction System (NGGPS) to represent the earth system for extended weather prediction. NGGPS will include a representation of atmospheric dynamics, physics, aerosols and atmospheric composition as well as coupling with ocean, wave, ice and land components. NGGPS is being developed with a broad community involvement, including community developed components and academic research to develop and test potential improvements for potentially inclusion in NGGPS. Several investigators at NOAA's research laboratories and in academia are working to improve the aerosol and gaseous chemistry representation for NGGPS, to develop and evaluate the representation of atmospheric composition, and to establish and improve the coupling with radiation and microphysics

Reward positivity: Reward prediction error or salience prediction error?

Science.gov (United States)

Heydari, Sepideh; Holroyd, Clay B

2016-08-01

The reward positivity is a component of the human ERP elicited by feedback stimuli in trial-and-error learning and guessing tasks. A prominent theory holds that the reward positivity reflects a reward prediction error signal that is sensitive to outcome valence, being larger for unexpected positive events relative to unexpected negative events (Holroyd & Coles, 2002). Although the theory has found substantial empirical support, most of these studies have utilized either monetary or performance feedback to test the hypothesis. However, in apparent contradiction to the theory, a recent study found that unexpected physical punishments also elicit the reward positivity (Talmi, Atkinson, & El-Deredy, 2013). The authors of this report argued that the reward positivity reflects a salience prediction error rather than a reward prediction error. To investigate this finding further, in the present study participants navigated a virtual T maze and received feedback on each trial under two conditions. In a reward condition, the feedback indicated that they would either receive a monetary reward or not and in a punishment condition the feedback indicated that they would receive a small shock or not. We found that the feedback stimuli elicited a typical reward positivity in the reward condition and an apparently delayed reward positivity in the punishment condition. Importantly, this signal was more positive to the stimuli that predicted the omission of a possible punishment relative to stimuli that predicted a forthcoming punishment, which is inconsistent with the salience hypothesis. © 2016 Society for Psychophysiological Research.

Dopamine reward prediction error coding

OpenAIRE

Schultz, Wolfram

2016-01-01

Reward prediction errors consist of the differences between received and predicted rewards. They are crucial for basic forms of learning about rewards and make us strive for more rewards?an evolutionary beneficial trait. Most dopamine neurons in the midbrain of humans, monkeys, and rodents signal a reward prediction error; they are activated by more reward than predicted (positive prediction error), remain at baseline activity for fully predicted rewards, and show depressed activity with less...

Model Prediction Control For Water Management Using Adaptive Prediction Accuracy

NARCIS (Netherlands)

Tian, X.; Negenborn, R.R.; Van Overloop, P.J.A.T.M.; Mostert, E.

2014-01-01

In the field of operational water management, Model Predictive Control (MPC) has gained popularity owing to its versatility and flexibility. The MPC controller, which takes predictions, time delay and uncertainties into account, can be designed for multi-objective management problems and for

Transionospheric propagation predictions

Science.gov (United States)

Klobucher, J. A.; Basu, S.; Basu, S.; Bernhardt, P. A.; Davies, K.; Donatelli, D. E.; Fremouw, E. J.; Goodman, J. M.; Hartmann, G. K.; Leitinger, R.

1979-01-01

The current status and future prospects of the capability to make transionospheric propagation predictions are addressed, highlighting the effects of the ionized media, which dominate for frequencies below 1 to 3 GHz, depending upon the state of the ionosphere and the elevation angle through the Earth-space path. The primary concerns are the predictions of time delay of signal modulation (group path delay) and of radio wave scintillation. Progress in these areas is strongly tied to knowledge of variable structures in the ionosphere ranging from the large scale (thousands of kilometers in horizontal extent) to the fine scale (kilometer size). Ionospheric variability and the relative importance of various mechanisms responsible for the time histories observed in total electron content (TEC), proportional to signal group delay, and in irregularity formation are discussed in terms of capability to make both short and long term predictions. The data base upon which predictions are made is examined for its adequacy, and the prospects for prediction improvements by more theoretical studies as well as by increasing the available statistical data base are examined.

Predictable grammatical constructions

DEFF Research Database (Denmark)

Lucas, Sandra

2015-01-01

My aim in this paper is to provide evidence from diachronic linguistics for the view that some predictable units are entrenched in grammar and consequently in human cognition, in a way that makes them functionally and structurally equal to nonpredictable grammatical units, suggesting that these p......My aim in this paper is to provide evidence from diachronic linguistics for the view that some predictable units are entrenched in grammar and consequently in human cognition, in a way that makes them functionally and structurally equal to nonpredictable grammatical units, suggesting...... that these predictable units should be considered grammatical constructions on a par with the nonpredictable constructions. Frequency has usually been seen as the only possible argument speaking in favor of viewing some formally and semantically fully predictable units as grammatical constructions. However, this paper...... semantically and formally predictable. Despite this difference, [méllo INF], like the other future periphrases, seems to be highly entrenched in the cognition (and grammar) of Early Medieval Greek language users, and consequently a grammatical construction. The syntactic evidence speaking in favor of [méllo...

Candidate Prediction Models and Methods

DEFF Research Database (Denmark)

Nielsen, Henrik Aalborg; Nielsen, Torben Skov; Madsen, Henrik

2005-01-01

This document lists candidate prediction models for Work Package 3 (WP3) of the PSO-project called ``Intelligent wind power prediction systems'' (FU4101). The main focus is on the models transforming numerical weather predictions into predictions of power production. The document also outlines...... the possibilities w.r.t. different numerical weather predictions actually available to the project....

Prediction Markets

DEFF Research Database (Denmark)

Horn, Christian Franz; Ivens, Bjørn Sven; Ohneberg, Michael

2014-01-01

In recent years, Prediction Markets gained growing interest as a forecasting tool among researchers as well as practitioners, which resulted in an increasing number of publications. In order to track the latest development of research, comprising the extent and focus of research, this article...... provides a comprehensive review and classification of the literature related to the topic of Prediction Markets. Overall, 316 relevant articles, published in the timeframe from 2007 through 2013, were identified and assigned to a herein presented classification scheme, differentiating between descriptive...... works, articles of theoretical nature, application-oriented studies and articles dealing with the topic of law and policy. The analysis of the research results reveals that more than half of the literature pool deals with the application and actual function tests of Prediction Markets. The results...

Adding propensity scores to pure prediction models fails to improve predictive performance

Directory of Open Access Journals (Sweden)

Amy S. Nowacki

2013-08-01

Full Text Available Background. Propensity score usage seems to be growing in popularity leading researchers to question the possible role of propensity scores in prediction modeling, despite the lack of a theoretical rationale. It is suspected that such requests are due to the lack of differentiation regarding the goals of predictive modeling versus causal inference modeling. Therefore, the purpose of this study is to formally examine the effect of propensity scores on predictive performance. Our hypothesis is that a multivariable regression model that adjusts for all covariates will perform as well as or better than those models utilizing propensity scores with respect to model discrimination and calibration.Methods. The most commonly encountered statistical scenarios for medical prediction (logistic and proportional hazards regression were used to investigate this research question. Random cross-validation was performed 500 times to correct for optimism. The multivariable regression models adjusting for all covariates were compared with models that included adjustment for or weighting with the propensity scores. The methods were compared based on three predictive performance measures: (1 concordance indices; (2 Brier scores; and (3 calibration curves.Results. Multivariable models adjusting for all covariates had the highest average concordance index, the lowest average Brier score, and the best calibration. Propensity score adjustment and inverse probability weighting models without adjustment for all covariates performed worse than full models and failed to improve predictive performance with full covariate adjustment.Conclusion. Propensity score techniques did not improve prediction performance measures beyond multivariable adjustment. Propensity scores are not recommended if the analytical goal is pure prediction modeling.

Relationships Between the Bulk-Skin Sea Surface Temperature Difference, Wind, and Net Air-Sea Heat Flux

Science.gov (United States)

Emery, William J.; Castro, Sandra L.; Lindstrom, Eric (Technical Monitor)

2002-01-01

The primary purpose of this project was to evaluate and improve models for the bulk-skin temperature difference to the point where they could accurately and reliably apply under a wide variety of environmental conditions. To accomplish this goal, work was conducted in three primary areas. These included production of an archive of available data sets containing measurements of the skin and bulk temperatures and associated environmental conditions, evaluation of existing skin layer models using the compiled data archive, and additional theoretical work on the development of an improved model using the data collected under diverse environmental conditions. In this work we set the basis for a new physical model of renewal type, and propose a parameterization for the temperature difference across the cool skin of the ocean in which the effects of thermal buoyancy, wind stress, and microscale breaking are all integrated by means of the appropriate renewal time scales. Ideally, we seek to obtain a model that will accurately apply under a wide variety of environmental conditions. A summary of the work in each of these areas is included in this report. A large amount of work was accomplished under the support of this grant. The grant supported the graduate studies of Sandra Castro and the preparation of her thesis which will be completed later this year. This work led to poster presentations at the 1999 American Geophysical Union Fall Meeting and 2000 IGARSS meeting. Additional work will be presented in a talk at this year's American Meteorological Society Air-Sea Interaction Meeting this May. The grant also supported Sandra Castro during a two week experiment aboard the R/P Flip (led by Dr. Andrew Jessup of the Applied Physics Laboratory) to help obtain additional shared data sets and to provide Sandra with a fundamental understanding of the physical processes needed in the models. In a related area, the funding also partially supported Dr. William Emery and Daniel

Development and validation of a risk model for prediction of hazardous alcohol consumption in general practice attendees: the predictAL study.

Science.gov (United States)

King, Michael; Marston, Louise; Švab, Igor; Maaroos, Heidi-Ingrid; Geerlings, Mirjam I; Xavier, Miguel; Benjamin, Vicente; Torres-Gonzalez, Francisco; Bellon-Saameno, Juan Angel; Rotar, Danica; Aluoja, Anu; Saldivia, Sandra; Correa, Bernardo; Nazareth, Irwin

2011-01-01

Little is known about the risk of progression to hazardous alcohol use in people currently drinking at safe limits. We aimed to develop a prediction model (predictAL) for the development of hazardous drinking in safe drinkers. A prospective cohort study of adult general practice attendees in six European countries and Chile followed up over 6 months. We recruited 10,045 attendees between April 2003 to February 2005. 6193 European and 2462 Chilean attendees recorded AUDIT scores below 8 in men and 5 in women at recruitment and were used in modelling risk. 38 risk factors were measured to construct a risk model for the development of hazardous drinking using stepwise logistic regression. The model was corrected for over fitting and tested in an external population. The main outcome was hazardous drinking defined by an AUDIT score ≥8 in men and ≥5 in women. 69.0% of attendees were recruited, of whom 89.5% participated again after six months. The risk factors in the final predictAL model were sex, age, country, baseline AUDIT score, panic syndrome and lifetime alcohol problem. The predictAL model's average c-index across all six European countries was 0.839 (95% CI 0.805, 0.873). The Hedge's g effect size for the difference in log odds of predicted probability between safe drinkers in Europe who subsequently developed hazardous alcohol use and those who did not was 1.38 (95% CI 1.25, 1.51). External validation of the algorithm in Chilean safe drinkers resulted in a c-index of 0.781 (95% CI 0.717, 0.846) and Hedge's g of 0.68 (95% CI 0.57, 0.78). The predictAL risk model for development of hazardous consumption in safe drinkers compares favourably with risk algorithms for disorders in other medical settings and can be a useful first step in prevention of alcohol misuse.

Development and validation of a risk model for prediction of hazardous alcohol consumption in general practice attendees: the predictAL study.

Directory of Open Access Journals (Sweden)

Michael King

Full Text Available Little is known about the risk of progression to hazardous alcohol use in people currently drinking at safe limits. We aimed to develop a prediction model (predictAL for the development of hazardous drinking in safe drinkers.A prospective cohort study of adult general practice attendees in six European countries and Chile followed up over 6 months. We recruited 10,045 attendees between April 2003 to February 2005. 6193 European and 2462 Chilean attendees recorded AUDIT scores below 8 in men and 5 in women at recruitment and were used in modelling risk. 38 risk factors were measured to construct a risk model for the development of hazardous drinking using stepwise logistic regression. The model was corrected for over fitting and tested in an external population. The main outcome was hazardous drinking defined by an AUDIT score ≥8 in men and ≥5 in women.69.0% of attendees were recruited, of whom 89.5% participated again after six months. The risk factors in the final predictAL model were sex, age, country, baseline AUDIT score, panic syndrome and lifetime alcohol problem. The predictAL model's average c-index across all six European countries was 0.839 (95% CI 0.805, 0.873. The Hedge's g effect size for the difference in log odds of predicted probability between safe drinkers in Europe who subsequently developed hazardous alcohol use and those who did not was 1.38 (95% CI 1.25, 1.51. External validation of the algorithm in Chilean safe drinkers resulted in a c-index of 0.781 (95% CI 0.717, 0.846 and Hedge's g of 0.68 (95% CI 0.57, 0.78.The predictAL risk model for development of hazardous consumption in safe drinkers compares favourably with risk algorithms for disorders in other medical settings and can be a useful first step in prevention of alcohol misuse.

Partnering with diabetes educators to improve patient outcomes

OpenAIRE

Burke SD; Sherr D; Lipman RD

2014-01-01

Sandra D Burke,1,2 Dawn Sherr,3 Ruth D Lipman3 1American Association of Diabetes Educators, Chicago, IL, USA; 2University of Illinois at Chicago College of Nursing, Urbana, IL, USA; 3Science and Practice, American Association of Diabetes Educators, Chicago, IL, USA Abstract: Diabetes is a chronic, progressive disease that affects millions worldwide. The paradigm of diabetes management has shifted to focus on empowering the person with diabetes to manage the disease successfully and to improv...

Creativity in Transitions

Directory of Open Access Journals (Sweden)

Molly Bathje MS, OTR/L

2014-01-01

Full Text Available Professor Sandra Edwards, MA, OTR/L, FOATA, and professor emerita at Western Michigan University (WMU, provided the cover art for the winter 2014 issue of The Open Journal of Occupational Therapy. The oil painting, “Silent Witness, Cross Creek” was created over a period of two years. Professor Edwards has participated in many creative and artistic activities throughout her life, which have shaped her practice as an occupational therapist and her experience in life.

Arsenic in your food: potential health hazards from arsenic found in rice

OpenAIRE

Carbonell-Barrachina, Ángel; Munera-Picazo,Sandra; Cano-Lamadrid,Marina; Burló,Francisco; Castaño-Iglesias,María Concepción

2015-01-01

Sandra Munera-Picazo,1 Marina Cano-Lamadrid,1 María Concepción Castaño-Iglesias,2 Francisco Burló,1 Ángel A Carbonell-Barrachina11Food Quality and Safety Group, Department of Agro-Food Technology, Universidad Miguel Hernández, Orihuela, 2Servicio de Pediatría, Hospital Universitario San Juan de Alicante, Alicante, SpainAbstract: Rice is a staple food for over half of the world population, but there is some concern ab...

Interviewing Francis Bacon

OpenAIRE

Kisters, Sandra

2012-01-01

British painter Francis Bacon (1909-1992) was known for the eloquence with which he talked about his art. He was easy to talk to, and was interviewed countless times by numerous critics. However, when studying Bacon's paintings one soon comes across the published interviews with art critic and curator David Sylvester (1924-2001), who interviewed him as many as 18 times between 1962 and 1986. Art historian Sandra Kisters argues that Sylvester's interviews with Bacon are carefully constructed a...

Assessing the carcinogenic potential of low-dose exposures to chemical mixtures in the environment: the challenge ahead

OpenAIRE

Goodson, William H.; Lowe, Leroy; Carpenter, David O.; Gilbertson, Michael; Manaf Ali, Abdul; Lopez de Cerain Salsamendi, Adela; Lasfar, Ahmed; Carnero, Amancio; Azqueta, Amaya; Amedei, Amedeo; Charles, Amelia K.; Collins, Andrew R.; Ward, Andrew; Salzberg, Anna C.; Colacci, Anna Maria

2015-01-01

John Pierce Wise Sr. and Sandra S.Wise were supported by National Institute of Environmental Health Sciences (ES016893 to J.P.W.) and the Maine Center for Toxicology and Environmental Health; Jonathan Whitfield acknowledges support from the FERO Foundation in Barcelona, Spain; Joseph Christopher is funded by Cancer Research UK and the International Journal of Experimental Pathology; Julia Kravchenko is supported by a philanthropic donation by Fred and Alice Stanback; Jun Sun is supported by a...

Development, characterization, and skin delivery studies of related ultradeformable vesicles: transfersomes, ethosomes, and transethosomes

OpenAIRE

Ascenso, Andreia; Raposo, Sara; Batista, Cátia; Cardoso, Pedro; Mendes, Tiago; Praça, Fabíola Garcia; Bentley, Maria Vitória Lopes Badra; Simões, Sandra

2015-01-01

Andreia Ascenso,1 Sara Raposo,1 Cátia Batista,2 Pedro Cardoso,2 Tiago Mendes,2 Fabíola Garcia Praça,3 Maria Vitória Lopes Badra Bentley,3 Sandra Simões1 1Instituto de Investigação do Medicamento (iMed.ULisboa), 2Faculdade de Farmácia, Universidade de Lisboa, Lisboa, Portugal; 3Faculdade de Ciências Farmacêuticas de Ribeirão Preto, Universidade de São Paulo, Monte ...

Genomic prediction of complex human traits: relatedness, trait architecture and predictive meta-models

Science.gov (United States)

Spiliopoulou, Athina; Nagy, Reka; Bermingham, Mairead L.; Huffman, Jennifer E.; Hayward, Caroline; Vitart, Veronique; Rudan, Igor; Campbell, Harry; Wright, Alan F.; Wilson, James F.; Pong-Wong, Ricardo; Agakov, Felix; Navarro, Pau; Haley, Chris S.

2015-01-01

We explore the prediction of individuals' phenotypes for complex traits using genomic data. We compare several widely used prediction models, including Ridge Regression, LASSO and Elastic Nets estimated from cohort data, and polygenic risk scores constructed using published summary statistics from genome-wide association meta-analyses (GWAMA). We evaluate the interplay between relatedness, trait architecture and optimal marker density, by predicting height, body mass index (BMI) and high-density lipoprotein level (HDL) in two data cohorts, originating from Croatia and Scotland. We empirically demonstrate that dense models are better when all genetic effects are small (height and BMI) and target individuals are related to the training samples, while sparse models predict better in unrelated individuals and when some effects have moderate size (HDL). For HDL sparse models achieved good across-cohort prediction, performing similarly to the GWAMA risk score and to models trained within the same cohort, which indicates that, for predicting traits with moderately sized effects, large sample sizes and familial structure become less important, though still potentially useful. Finally, we propose a novel ensemble of whole-genome predictors with GWAMA risk scores and demonstrate that the resulting meta-model achieves higher prediction accuracy than either model on its own. We conclude that although current genomic predictors are not accurate enough for diagnostic purposes, performance can be improved without requiring access to large-scale individual-level data. Our methodologically simple meta-model is a means of performing predictive meta-analysis for optimizing genomic predictions and can be easily extended to incorporate multiple population-level summary statistics or other domain knowledge. PMID:25918167

Predicting scholars' scientific impact.

Directory of Open Access Journals (Sweden)

Amin Mazloumian

Full Text Available We tested the underlying assumption that citation counts are reliable predictors of future success, analyzing complete citation data on the careers of ~150,000 scientists. Our results show that i among all citation indicators, the annual citations at the time of prediction is the best predictor of future citations, ii future citations of a scientist's published papers can be predicted accurately (r(2 = 0.80 for a 1-year prediction, P<0.001 but iii future citations of future work are hardly predictable.

Protein Sorting Prediction

DEFF Research Database (Denmark)

Nielsen, Henrik

2017-01-01

and drawbacks of each of these approaches is described through many examples of methods that predict secretion, integration into membranes, or subcellular locations in general. The aim of this chapter is to provide a user-level introduction to the field with a minimum of computational theory.......Many computational methods are available for predicting protein sorting in bacteria. When comparing them, it is important to know that they can be grouped into three fundamentally different approaches: signal-based, global-property-based and homology-based prediction. In this chapter, the strengths...

'Red Flag' Predictions

DEFF Research Database (Denmark)

Hallin, Carina Antonia; Andersen, Torben Juul; Tveterås, Sigbjørn

-generation prediction markets and outline its unique features as a third-generation prediction market. It is argued that frontline employees gain deep insights when they execute operational activities on an ongoing basis in the organization. The experiential learning from close interaction with internal and external......This conceptual article introduces a new way to predict firm performance based on aggregation of sensing among frontline employees about changes in operational capabilities to update strategic action plans and generate innovations. We frame the approach in the context of first- and second...

Predictive value of diminutive colonic adenoma trial: the PREDICT trial.

Science.gov (United States)

Schoenfeld, Philip; Shad, Javaid; Ormseth, Eric; Coyle, Walter; Cash, Brooks; Butler, James; Schindler, William; Kikendall, Walter J; Furlong, Christopher; Sobin, Leslie H; Hobbs, Christine M; Cruess, David; Rex, Douglas

2003-05-01

Diminutive adenomas (1-9 mm in diameter) are frequently found during colon cancer screening with flexible sigmoidoscopy (FS). This trial assessed the predictive value of these diminutive adenomas for advanced adenomas in the proximal colon. In a multicenter, prospective cohort trial, we matched 200 patients with normal FS and 200 patients with diminutive adenomas on FS for age and gender. All patients underwent colonoscopy. The presence of advanced adenomas (adenoma >or= 10 mm in diameter, villous adenoma, adenoma with high grade dysplasia, and colon cancer) and adenomas (any size) was recorded. Before colonoscopy, patients completed questionnaires about risk factors for adenomas. The prevalence of advanced adenomas in the proximal colon was similar in patients with diminutive adenomas and patients with normal FS (6% vs. 5.5%, respectively) (relative risk, 1.1; 95% confidence interval [CI], 0.5-2.6). Diminutive adenomas on FS did not accurately predict advanced adenomas in the proximal colon: sensitivity, 52% (95% CI, 32%-72%); specificity, 50% (95% CI, 49%-51%); positive predictive value, 6% (95% CI, 4%-8%); and negative predictive value, 95% (95% CI, 92%-97%). Male gender (odds ratio, 1.63; 95% CI, 1.01-2.61) was associated with an increased risk of proximal colon adenomas. Diminutive adenomas on sigmoidoscopy may not accurately predict advanced adenomas in the proximal colon.

Review of Nearshore Morphologic Prediction

Science.gov (United States)

Plant, N. G.; Dalyander, S.; Long, J.

2014-12-01

The evolution of the world's erodible coastlines will determine the balance between the benefits and costs associated with human and ecological utilization of shores, beaches, dunes, barrier islands, wetlands, and estuaries. So, we would like to predict coastal evolution to guide management and planning of human and ecological response to coastal changes. After decades of research investment in data collection, theoretical and statistical analysis, and model development we have a number of empirical, statistical, and deterministic models that can predict the evolution of the shoreline, beaches, dunes, and wetlands over time scales of hours to decades, and even predict the evolution of geologic strata over the course of millennia. Comparisons of predictions to data have demonstrated that these models can have meaningful predictive skill. But these comparisons also highlight the deficiencies in fundamental understanding, formulations, or data that are responsible for prediction errors and uncertainty. Here, we review a subset of predictive models of the nearshore to illustrate tradeoffs in complexity, predictive skill, and sensitivity to input data and parameterization errors. We identify where future improvement in prediction skill will result from improved theoretical understanding, and data collection, and model-data assimilation.

The Prediction Value

NARCIS (Netherlands)

Koster, M.; Kurz, S.; Lindner, I.; Napel, S.

2013-01-01

We introduce the prediction value (PV) as a measure of players’ informational importance in probabilistic TU games. The latter combine a standard TU game and a probability distribution over the set of coalitions. Player i’s prediction value equals the difference between the conditional expectations

Predicting Energy Consumption for Potential Effective Use in Hybrid Vehicle Powertrain Management Using Driver Prediction

Science.gov (United States)

Magnuson, Brian

A proof-of-concept software-in-the-loop study is performed to assess the accuracy of predicted net and charge-gaining energy consumption for potential effective use in optimizing powertrain management of hybrid vehicles. With promising results of improving fuel efficiency of a thermostatic control strategy for a series, plug-ing, hybrid-electric vehicle by 8.24%, the route and speed prediction machine learning algorithms are redesigned and implemented for real- world testing in a stand-alone C++ code-base to ingest map data, learn and predict driver habits, and store driver data for fast startup and shutdown of the controller or computer used to execute the compiled algorithm. Speed prediction is performed using a multi-layer, multi-input, multi- output neural network using feed-forward prediction and gradient descent through back- propagation training. Route prediction utilizes a Hidden Markov Model with a recurrent forward algorithm for prediction and multi-dimensional hash maps to store state and state distribution constraining associations between atomic road segments and end destinations. Predicted energy is calculated using the predicted time-series speed and elevation profile over the predicted route and the road-load equation. Testing of the code-base is performed over a known road network spanning 24x35 blocks on the south hill of Spokane, Washington. A large set of training routes are traversed once to add randomness to the route prediction algorithm, and a subset of the training routes, testing routes, are traversed to assess the accuracy of the net and charge-gaining predicted energy consumption. Each test route is traveled a random number of times with varying speed conditions from traffic and pedestrians to add randomness to speed prediction. Prediction data is stored and analyzed in a post process Matlab script. The aggregated results and analysis of all traversals of all test routes reflect the performance of the Driver Prediction algorithm. The

Is Time Predictability Quantifiable?

DEFF Research Database (Denmark)

Schoeberl, Martin

2012-01-01

Computer architects and researchers in the realtime domain start to investigate processors and architectures optimized for real-time systems. Optimized for real-time systems means time predictable, i.e., architectures where it is possible to statically derive a tight bound of the worst......-case execution time. To compare different approaches we would like to quantify time predictability. That means we need to measure time predictability. In this paper we discuss the different approaches for these measurements and conclude that time predictability is practically not quantifiable. We can only...... compare the worst-case execution time bounds of different architectures....

Predicting AD conversion

DEFF Research Database (Denmark)

Liu, Yawu; Mattila, Jussi; Ruiz, Miguel �ngel Mu�oz

2013-01-01

To compare the accuracies of predicting AD conversion by using a decision support system (PredictAD tool) and current research criteria of prodromal AD as identified by combinations of episodic memory impairment of hippocampal type and visual assessment of medial temporal lobe atrophy (MTA) on MRI...

Filtering and prediction

CERN Document Server

Fristedt, B; Krylov, N

2007-01-01

Filtering and prediction is about observing moving objects when the observations are corrupted by random errors. The main focus is then on filtering out the errors and extracting from the observations the most precise information about the object, which itself may or may not be moving in a somewhat random fashion. Next comes the prediction step where, using information about the past behavior of the object, one tries to predict its future path. The first three chapters of the book deal with discrete probability spaces, random variables, conditioning, Markov chains, and filtering of discrete Markov chains. The next three chapters deal with the more sophisticated notions of conditioning in nondiscrete situations, filtering of continuous-space Markov chains, and of Wiener process. Filtering and prediction of stationary sequences is discussed in the last two chapters. The authors believe that they have succeeded in presenting necessary ideas in an elementary manner without sacrificing the rigor too much. Such rig...

PredictSNP: robust and accurate consensus classifier for prediction of disease-related mutations.

Directory of Open Access Journals (Sweden)

Jaroslav Bendl

2014-01-01

Full Text Available Single nucleotide variants represent a prevalent form of genetic variation. Mutations in the coding regions are frequently associated with the development of various genetic diseases. Computational tools for the prediction of the effects of mutations on protein function are very important for analysis of single nucleotide variants and their prioritization for experimental characterization. Many computational tools are already widely employed for this purpose. Unfortunately, their comparison and further improvement is hindered by large overlaps between the training datasets and benchmark datasets, which lead to biased and overly optimistic reported performances. In this study, we have constructed three independent datasets by removing all duplicities, inconsistencies and mutations previously used in the training of evaluated tools. The benchmark dataset containing over 43,000 mutations was employed for the unbiased evaluation of eight established prediction tools: MAPP, nsSNPAnalyzer, PANTHER, PhD-SNP, PolyPhen-1, PolyPhen-2, SIFT and SNAP. The six best performing tools were combined into a consensus classifier PredictSNP, resulting into significantly improved prediction performance, and at the same time returned results for all mutations, confirming that consensus prediction represents an accurate and robust alternative to the predictions delivered by individual tools. A user-friendly web interface enables easy access to all eight prediction tools, the consensus classifier PredictSNP and annotations from the Protein Mutant Database and the UniProt database. The web server and the datasets are freely available to the academic community at http://loschmidt.chemi.muni.cz/predictsnp.

Predictive maintenance primer

International Nuclear Information System (INIS)

Flude, J.W.; Nicholas, J.R.

1991-04-01

This Predictive Maintenance Primer provides utility plant personnel with a single-source reference to predictive maintenance analysis methods and technologies used successfully by utilities and other industries. It is intended to be a ready reference to personnel considering starting, expanding or improving a predictive maintenance program. This Primer includes a discussion of various analysis methods and how they overlap and interrelate. Additionally, eighteen predictive maintenance technologies are discussed in sufficient detail for the user to evaluate the potential of each technology for specific applications. This document is designed to allow inclusion of additional technologies in the future. To gather the information necessary to create this initial Primer the Nuclear Maintenance Applications Center (NMAC) collected experience data from eighteen utilities plus other industry and government sources. NMAC also contacted equipment manufacturers for information pertaining to equipment utilization, maintenance, and technical specifications. The Primer includes a discussion of six methods used by analysts to study predictive maintenance data. These are: trend analysis; pattern recognition; correlation; test against limits or ranges; relative comparison data; and statistical process analysis. Following the analysis methods discussions are detailed descriptions for eighteen technologies analysts have found useful for predictive maintenance programs at power plants and other industrial facilities. Each technology subchapter has a description of the operating principles involved in the technology, a listing of plant equipment where the technology can be applied, and a general description of the monitoring equipment. Additionally, these descriptions include a discussion of results obtained from actual equipment users and preferred analysis techniques to be used on data obtained from the technology. 5 refs., 30 figs

Genomic prediction using subsampling.

Science.gov (United States)

Xavier, Alencar; Xu, Shizhong; Muir, William; Rainey, Katy Martin

2017-03-24

Genome-wide assisted selection is a critical tool for the genetic improvement of plants and animals. Whole-genome regression models in Bayesian framework represent the main family of prediction methods. Fitting such models with a large number of observations involves a prohibitive computational burden. We propose the use of subsampling bootstrap Markov chain in genomic prediction. Such method consists of fitting whole-genome regression models by subsampling observations in each round of a Markov Chain Monte Carlo. We evaluated the effect of subsampling bootstrap on prediction and computational parameters. Across datasets, we observed an optimal subsampling proportion of observations around 50% with replacement, and around 33% without replacement. Subsampling provided a substantial decrease in computation time, reducing the time to fit the model by half. On average, losses on predictive properties imposed by subsampling were negligible, usually below 1%. For each dataset, an optimal subsampling point that improves prediction properties was observed, but the improvements were also negligible. Combining subsampling with Gibbs sampling is an interesting ensemble algorithm. The investigation indicates that the subsampling bootstrap Markov chain algorithm substantially reduces computational burden associated with model fitting, and it may slightly enhance prediction properties.

Emerging approaches in predictive toxicology.

Science.gov (United States)

Zhang, Luoping; McHale, Cliona M; Greene, Nigel; Snyder, Ronald D; Rich, Ivan N; Aardema, Marilyn J; Roy, Shambhu; Pfuhler, Stefan; Venkatactahalam, Sundaresan

2014-12-01

Predictive toxicology plays an important role in the assessment of toxicity of chemicals and the drug development process. While there are several well-established in vitro and in vivo assays that are suitable for predictive toxicology, recent advances in high-throughput analytical technologies and model systems are expected to have a major impact on the field of predictive toxicology. This commentary provides an overview of the state of the current science and a brief discussion on future perspectives for the field of predictive toxicology for human toxicity. Computational models for predictive toxicology, needs for further refinement and obstacles to expand computational models to include additional classes of chemical compounds are highlighted. Functional and comparative genomics approaches in predictive toxicology are discussed with an emphasis on successful utilization of recently developed model systems for high-throughput analysis. The advantages of three-dimensional model systems and stem cells and their use in predictive toxicology testing are also described. © 2014 Wiley Periodicals, Inc.

Earthquake prediction with electromagnetic phenomena

Energy Technology Data Exchange (ETDEWEB)

Hayakawa, Masashi, E-mail: hayakawa@hi-seismo-em.jp [Hayakawa Institute of Seismo Electomagnetics, Co. Ltd., University of Electro-Communications (UEC) Incubation Center, 1-5-1 Chofugaoka, Chofu Tokyo, 182-8585 (Japan); Advanced Wireless & Communications Research Center, UEC, Chofu Tokyo (Japan); Earthquake Analysis Laboratory, Information Systems Inc., 4-8-15, Minami-aoyama, Minato-ku, Tokyo, 107-0062 (Japan); Fuji Security Systems. Co. Ltd., Iwato-cho 1, Shinjyuku-ku, Tokyo (Japan)

2016-02-01

Short-term earthquake (EQ) prediction is defined as prospective prediction with the time scale of about one week, which is considered to be one of the most important and urgent topics for the human beings. If this short-term prediction is realized, casualty will be drastically reduced. Unlike the conventional seismic measurement, we proposed the use of electromagnetic phenomena as precursors to EQs in the prediction, and an extensive amount of progress has been achieved in the field of seismo-electromagnetics during the last two decades. This paper deals with the review on this short-term EQ prediction, including the impossibility myth of EQs prediction by seismometers, the reason why we are interested in electromagnetics, the history of seismo-electromagnetics, the ionospheric perturbation as the most promising candidate of EQ prediction, then the future of EQ predictology from two standpoints of a practical science and a pure science, and finally a brief summary.

Eesti-Leedu sõpruskohtumised / Maarin Ektermann

Index Scriptorium Estoniae

Ektermann, Maarin

2007-01-01

Noorte maalikunstnike ühisnäitused "Shoot or Shout - No Escape" Vilniuse Art's Printing House'is 19. X-3. XI 2006 (lisaks kodus maalitud töödele maalisid Aivar Reisner, Sirli Hein ja Rait Rosin remake'e leedu kunstnike töödest) ja "Fresh Paint" Vaal-galeriis 29. III-17. IV. Paaride Triinu Lill ja Agne Jonkute, Sirli Hein ja Sandra Lukoshevichiute, Agne Kulbyte ja Merike Estna ning Rait Rosina, Konstantinas Gaitanzhi ja Elis Saarevälja töödest

Políticas e poéticas feministas : imagens em movimento sob a ótica de mulheres latino-americanas

OpenAIRE

Maria Célia Orlato Selem

2013-01-01

Resumo: A presente pesquisa busca identificar poéticas feministas no cinema de mulheres latino-americanas neste século XXI. Nesse intuito, foram selecionados os seguintes filmes: La teta asustada, de Claudia Llosa (Peru - 2009); Que tan lejos, de Tania Hermida (Equador - 2006); Rompecabezas, Natalia Smirnoff (Argentina, 2009); Entre nós, de Paola Mendoza e Gloria La Morte (Colômbia, 2009); Sonhos Roubados, de Sandra Werneck (Brasil, 2009); En la puta vida, de Beatriz Flores Silva (Uruguai, 20...

Minskad miljöpåverkan av kapslar för kaffe, te och choklad : med avseende på materialval och utformning

OpenAIRE

Hollsten, Petra

2012-01-01

During the spring semester of 2012 did Petra Hollsten independently a thesis on reducing the environmental impact of capsule for coffee, tea and chocolate. The work was performed at Karlstad University, Faculty of Technology and Science under the Bachelor of Science program in innovation, technology and design. The project's scope is at 22.5 points. The employment for this project is the company Löfbergs Lila AB in Karlstad. Supervisor at the Principal has been Maria Herou Wallner and Sandra ...

PR-konsulter och bloggare; en win-win situation? : En studie om PR-konsulters förändrade arbetssätt i och med modebloggarnas framväxt

OpenAIRE

Girell, Cecilia; Kjellström, Sandra

2014-01-01

Abstract Title: PR consultants and bloggers; a win-win situation? -  A study of PR consultants’ new adaptations in the labour market due to the emergence of fashion bloggers.  Authors: Cecilia Girell, Sandra Kjellström Tutor: Ylva Ekström Purpose: With the expansion of the Internet, fashion bloggers have gotten more power. A few companies have understood this powerful and reasonable cheap marketing channel. Despite this, most companies still feel powerless, but what has happened to the wor...

Prediction of bull fertility.

Science.gov (United States)

Utt, Matthew D

2016-06-01

Prediction of male fertility is an often sought-after endeavor for many species of domestic animals. This review will primarily focus on providing some examples of dependent and independent variables to stimulate thought about the approach and methodology of identifying the most appropriate of those variables to predict bull (bovine) fertility. Although the list of variables will continue to grow with advancements in science, the principles behind making predictions will likely not change significantly. The basic principle of prediction requires identifying a dependent variable that is an estimate of fertility and an independent variable or variables that may be useful in predicting the fertility estimate. Fertility estimates vary in which parts of the process leading to conception that they infer about and the amount of variation that influences the estimate and the uncertainty thereof. The list of potential independent variables can be divided into competence of sperm based on their performance in bioassays or direct measurement of sperm attributes. A good prediction will use a sample population of bulls that is representative of the population to which an inference will be made. Both dependent and independent variables should have a dynamic range in their values. Careful selection of independent variables includes reasonable measurement repeatability and minimal correlation among variables. Proper estimation and having an appreciation of the degree of uncertainty of dependent and independent variables are crucial for using predictions to make decisions regarding bull fertility. Copyright © 2016 Elsevier B.V. All rights reserved.

Climate Prediction - NOAA's National Weather Service

Science.gov (United States)

Statistical Models... MOS Prod GFS-LAMP Prod Climate Past Weather Predictions Weather Safety Weather Radio National Weather Service on FaceBook NWS on Facebook NWS Director Home > Climate > Predictions Climate Prediction Long range forecasts across the U.S. Climate Prediction Web Sites Climate Prediction

Tide Predictions, California, 2014, NOAA

Data.gov (United States)

U.S. Environmental Protection Agency — The predictions from the web based NOAA Tide Predictions are based upon the latest information available as of the date of the user's request. Tide predictions...

Decadal climate prediction (project GCEP).

Science.gov (United States)

Haines, Keith; Hermanson, Leon; Liu, Chunlei; Putt, Debbie; Sutton, Rowan; Iwi, Alan; Smith, Doug

2009-03-13

Decadal prediction uses climate models forced by changing greenhouse gases, as in the International Panel for Climate Change, but unlike longer range predictions they also require initialization with observations of the current climate. In particular, the upper-ocean heat content and circulation have a critical influence. Decadal prediction is still in its infancy and there is an urgent need to understand the important processes that determine predictability on these timescales. We have taken the first Hadley Centre Decadal Prediction System (DePreSys) and implemented it on several NERC institute compute clusters in order to study a wider range of initial condition impacts on decadal forecasting, eventually including the state of the land and cryosphere. The eScience methods are used to manage submission and output from the many ensemble model runs required to assess predictive skill. Early results suggest initial condition skill may extend for several years, even over land areas, but this depends sensitively on the definition used to measure skill, and alternatives are presented. The Grid for Coupled Ensemble Prediction (GCEP) system will allow the UK academic community to contribute to international experiments being planned to explore decadal climate predictability.

Potential Predictability and Prediction Skill for Southern Peru Summertime Rainfall

Science.gov (United States)

WU, S.; Notaro, M.; Vavrus, S. J.; Mortensen, E.; Block, P. J.; Montgomery, R. J.; De Pierola, J. N.; Sanchez, C.

2016-12-01

The central Andes receive over 50% of annual climatological rainfall during the short period of January-March. This summertime rainfall exhibits strong interannual and decadal variability, including severe drought events that incur devastating societal impacts and cause agricultural communities and mining facilities to compete for limited water resources. An improved seasonal prediction skill of summertime rainfall would aid in water resource planning and allocation across the water-limited southern Peru. While various underlying mechanisms have been proposed by past studies for the drivers of interannual variability in summertime rainfall across southern Peru, such as the El Niño-Southern Oscillation (ENSO), Madden Julian Oscillation (MJO), and extratropical forcings, operational forecasts continue to be largely based on rudimentary ENSO-based indices, such as NINO3.4, justifying further exploration of predictive skill. In order to bridge this gap between the understanding of driving mechanisms and the operational forecast, we performed systematic studies on the predictability and prediction skill of southern Peru summertime rainfall by constructing statistical forecast models using best available weather station and reanalysis datasets. At first, by assuming the first two empirical orthogonal functions (EOFs) of summertime rainfall are predictable, the potential predictability skill was evaluated for southern Peru. Then, we constructed a simple regression model, based on the time series of tropical Pacific sea-surface temperatures (SSTs), and a more advanced Linear Inverse Model (LIM), based on the EOFs of tropical ocean SSTs and large-scale atmosphere variables from reanalysis. Our results show that the LIM model consistently outperforms the more rudimentary regression models on the forecast skill of domain averaged precipitation index and individual station indices. The improvement of forecast correlation skill ranges from 10% to over 200% for different

Predicting epileptic seizures in advance.

Directory of Open Access Journals (Sweden)

Negin Moghim

Full Text Available Epilepsy is the second most common neurological disorder, affecting 0.6-0.8% of the world's population. In this neurological disorder, abnormal activity of the brain causes seizures, the nature of which tend to be sudden. Antiepileptic Drugs (AEDs are used as long-term therapeutic solutions that control the condition. Of those treated with AEDs, 35% become resistant to medication. The unpredictable nature of seizures poses risks for the individual with epilepsy. It is clearly desirable to find more effective ways of preventing seizures for such patients. The automatic detection of oncoming seizures, before their actual onset, can facilitate timely intervention and hence minimize these risks. In addition, advance prediction of seizures can enrich our understanding of the epileptic brain. In this study, drawing on the body of work behind automatic seizure detection and prediction from digitised Invasive Electroencephalography (EEG data, a prediction algorithm, ASPPR (Advance Seizure Prediction via Pre-ictal Relabeling, is described. ASPPR facilitates the learning of predictive models targeted at recognizing patterns in EEG activity that are in a specific time window in advance of a seizure. It then exploits advanced machine learning coupled with the design and selection of appropriate features from EEG signals. Results, from evaluating ASPPR independently on 21 different patients, suggest that seizures for many patients can be predicted up to 20 minutes in advance of their onset. Compared to benchmark performance represented by a mean S1-Score (harmonic mean of Sensitivity and Specificity of 90.6% for predicting seizure onset between 0 and 5 minutes in advance, ASPPR achieves mean S1-Scores of: 96.30% for prediction between 1 and 6 minutes in advance, 96.13% for prediction between 8 and 13 minutes in advance, 94.5% for prediction between 14 and 19 minutes in advance, and 94.2% for prediction between 20 and 25 minutes in advance.

Are abrupt climate changes predictable?

Science.gov (United States)

Ditlevsen, Peter

2013-04-01

It is taken for granted that the limited predictability in the initial value problem, the weather prediction, and the predictability of the statistics are two distinct problems. Lorenz (1975) dubbed this predictability of the first and the second kind respectively. Predictability of the first kind in a chaotic dynamical system is limited due to the well-known critical dependence on initial conditions. Predictability of the second kind is possible in an ergodic system, where either the dynamics is known and the phase space attractor can be characterized by simulation or the system can be observed for such long times that the statistics can be obtained from temporal averaging, assuming that the attractor does not change in time. For the climate system the distinction between predictability of the first and the second kind is fuzzy. This difficulty in distinction between predictability of the first and of the second kind is related to the lack of scale separation between fast and slow components of the climate system. The non-linear nature of the problem furthermore opens the possibility of multiple attractors, or multiple quasi-steady states. As the ice-core records show, the climate has been jumping between different quasi-stationary climates, stadials and interstadials through the Dansgaard-Oechger events. Such a jump happens very fast when a critical tipping point has been reached. The question is: Can such a tipping point be predicted? This is a new kind of predictability: the third kind. If the tipping point is reached through a bifurcation, where the stability of the system is governed by some control parameter, changing in a predictable way to a critical value, the tipping is predictable. If the sudden jump occurs because internal chaotic fluctuations, noise, push the system across a barrier, the tipping is as unpredictable as the triggering noise. In order to hint at an answer to this question, a careful analysis of the high temporal resolution NGRIP isotope

Predicting Free Recalls

Science.gov (United States)

Laming, Donald

2006-01-01

This article reports some calculations on free-recall data from B. Murdock and J. Metcalfe (1978), with vocal rehearsal during the presentation of a list. Given the sequence of vocalizations, with the stimuli inserted in their proper places, it is possible to predict the subsequent sequence of recalls--the predictions taking the form of a…

Deep Visual Attention Prediction

Science.gov (United States)

Wang, Wenguan; Shen, Jianbing

2018-05-01

In this work, we aim to predict human eye fixation with view-free scenes based on an end-to-end deep learning architecture. Although Convolutional Neural Networks (CNNs) have made substantial improvement on human attention prediction, it is still needed to improve CNN based attention models by efficiently leveraging multi-scale features. Our visual attention network is proposed to capture hierarchical saliency information from deep, coarse layers with global saliency information to shallow, fine layers with local saliency response. Our model is based on a skip-layer network structure, which predicts human attention from multiple convolutional layers with various reception fields. Final saliency prediction is achieved via the cooperation of those global and local predictions. Our model is learned in a deep supervision manner, where supervision is directly fed into multi-level layers, instead of previous approaches of providing supervision only at the output layer and propagating this supervision back to earlier layers. Our model thus incorporates multi-level saliency predictions within a single network, which significantly decreases the redundancy of previous approaches of learning multiple network streams with different input scales. Extensive experimental analysis on various challenging benchmark datasets demonstrate our method yields state-of-the-art performance with competitive inference time.

A grey NGM(1,1, k) self-memory coupling prediction model for energy consumption prediction.

Science.gov (United States)

Guo, Xiaojun; Liu, Sifeng; Wu, Lifeng; Tang, Lingling

2014-01-01

Energy consumption prediction is an important issue for governments, energy sector investors, and other related corporations. Although there are several prediction techniques, selection of the most appropriate technique is of vital importance. As for the approximate nonhomogeneous exponential data sequence often emerging in the energy system, a novel grey NGM(1,1, k) self-memory coupling prediction model is put forward in order to promote the predictive performance. It achieves organic integration of the self-memory principle of dynamic system and grey NGM(1,1, k) model. The traditional grey model's weakness as being sensitive to initial value can be overcome by the self-memory principle. In this study, total energy, coal, and electricity consumption of China is adopted for demonstration by using the proposed coupling prediction technique. The results show the superiority of NGM(1,1, k) self-memory coupling prediction model when compared with the results from the literature. Its excellent prediction performance lies in that the proposed coupling model can take full advantage of the systematic multitime historical data and catch the stochastic fluctuation tendency. This work also makes a significant contribution to the enrichment of grey prediction theory and the extension of its application span.

The IntFOLD server: an integrated web resource for protein fold recognition, 3D model quality assessment, intrinsic disorder prediction, domain prediction and ligand binding site prediction.

Science.gov (United States)

Roche, Daniel B; Buenavista, Maria T; Tetchner, Stuart J; McGuffin, Liam J

2011-07-01

The IntFOLD server is a novel independent server that integrates several cutting edge methods for the prediction of structure and function from sequence. Our guiding principles behind the server development were as follows: (i) to provide a simple unified resource that makes our prediction software accessible to all and (ii) to produce integrated output for predictions that can be easily interpreted. The output for predictions is presented as a simple table that summarizes all results graphically via plots and annotated 3D models. The raw machine readable data files for each set of predictions are also provided for developers, which comply with the Critical Assessment of Methods for Protein Structure Prediction (CASP) data standards. The server comprises an integrated suite of five novel methods: nFOLD4, for tertiary structure prediction; ModFOLD 3.0, for model quality assessment; DISOclust 2.0, for disorder prediction; DomFOLD 2.0 for domain prediction; and FunFOLD 1.0, for ligand binding site prediction. Predictions from the IntFOLD server were found to be competitive in several categories in the recent CASP9 experiment. The IntFOLD server is available at the following web site: http://www.reading.ac.uk/bioinf/IntFOLD/.

Dynamics beetween 'old' and 'new' ethnicities and multiple identities in Sandra Cisneros' Caramelo

Directory of Open Access Journals (Sweden)

Branka Kalogjera

2007-12-01

Full Text Available The paper takes Candra Cisneros'  epic semi-biographical novel Caramelo asa literary insight into dynamics  between generations  within  a single ethnic (Chicano  community,  and compares  it against classics  of the genre in its shifting  definition  of one's  ethnic identity;  here the postmodern approach of entwining fiction and fact and awarding them equallegitimacy mirrors the possibility of embracing multiple identities, as exemplified by the novel's protagonist.

Andres Elbingu gängstaräpp avas Polymeris ajutise alternatiivkino / Sandra Jõgeva

Index Scriptorium Estoniae

Jõgeva, Sandra, 1976-

2008-01-01

1.-22. veebruarini 2008 toimub Tallinnas Nongrata Kunstikonteineris Kultuuritehases Polymer Eesti Kunstiakadeemia interdistsiplinaarsete kunstide kateedri ja Pärnu filmi- ja videofestivali korraldatav alternatiivkino "La Cinema Extraordinaire"

Prediction skill of rainstorm events over India in the TIGGE weather prediction models

Science.gov (United States)

Karuna Sagar, S.; Rajeevan, M.; Vijaya Bhaskara Rao, S.; Mitra, A. K.

2017-12-01

Extreme rainfall events pose a serious threat of leading to severe floods in many countries worldwide. Therefore, advance prediction of its occurrence and spatial distribution is very essential. In this paper, an analysis has been made to assess the skill of numerical weather prediction models in predicting rainstorms over India. Using gridded daily rainfall data set and objective criteria, 15 rainstorms were identified during the monsoon season (June to September). The analysis was made using three TIGGE (THe Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble) models. The models considered are the European Centre for Medium-Range Weather Forecasts (ECMWF), National Centre for Environmental Prediction (NCEP) and the UK Met Office (UKMO). Verification of the TIGGE models for 43 observed rainstorm days from 15 rainstorm events has been made for the period 2007-2015. The comparison reveals that rainstorm events are predictable up to 5 days in advance, however with a bias in spatial distribution and intensity. The statistical parameters like mean error (ME) or Bias, root mean square error (RMSE) and correlation coefficient (CC) have been computed over the rainstorm region using the multi-model ensemble (MME) mean. The study reveals that the spread is large in ECMWF and UKMO followed by the NCEP model. Though the ensemble spread is quite small in NCEP, the ensemble member averages are not well predicted. The rank histograms suggest that the forecasts are under prediction. The modified Contiguous Rain Area (CRA) technique was used to verify the spatial as well as the quantitative skill of the TIGGE models. Overall, the contribution from the displacement and pattern errors to the total RMSE is found to be more in magnitude. The volume error increases from 24 hr forecast to 48 hr forecast in all the three models.

Predicting Well-Being in Europe?

DEFF Research Database (Denmark)

Hussain, M. Azhar

2015-01-01

Has the worst financial and economic crisis since the 1930s reduced the subjective wellbeing function's predictive power? Regression models for happiness are estimated for the three first rounds of the European Social Survey (ESS); 2002, 2004 and 2006. Several explanatory variables are significant...... happiness. Nevertheless, 73% of the predictions in 2008 and 57% of predictions in 2010 were within the margin of error. These correct prediction percentages are not unusually low - rather they are slightly higher than before the crisis. It is surprising that happiness predictions are not adversely affected...... by the crisis. On the other hand, results are consistent with the adaption hypothesis. The same exercise is conducted applying life satisfaction instead of happiness, but we reject, against expectation, that (more transient) happiness is harder to predict than life satisfaction. Fifteen ESS countries surveyed...

Prediction of postoperative pain: a systematic review of predictive experimental pain studies

DEFF Research Database (Denmark)

Werner, Mads Utke; Mjöbo, Helena N; Nielsen, Per R

2010-01-01

Quantitative testing of a patient's basal pain perception before surgery has the potential to be of clinical value if it can accurately predict the magnitude of pain and requirement of analgesics after surgery. This review includes 14 studies that have investigated the correlation between...... preoperative responses to experimental pain stimuli and clinical postoperative pain and demonstrates that the preoperative pain tests may predict 4-54% of the variance in postoperative pain experience depending on the stimulation methods and the test paradigm used. The predictive strength is much higher than...

When predictions take control: The effect of task predictions on task switching performance

Directory of Open Access Journals (Sweden)

Wout eDuthoo

2012-08-01

Full Text Available In this paper, we aimed to investigate the role of self-generated predictions in the flexible control of behaviour. Therefore, we ran a task switching experiment in which participants were asked to try to predict the upcoming task in three conditions varying in switch rate (30%, 50% and 70%. Irrespective of their predictions, the colour of the target indicated which task participants had to perform. In line with previous studies (Mayr, 2006; Monsell & Mizon, 2006, the switch cost was attenuated as the switch rate increased. Importantly, a clear task repetition bias was found in all conditions, yet the task repetition prediction rate dropped from 78% over 66% to 49% with increasing switch probability in the three conditions. Irrespective of condition, the switch cost was strongly reduced in expectation of a task alternation compared to the cost of an unexpected task alternation following repetition predictions. Hence, our data suggest that the reduction in the switch cost with increasing switch probability is caused by a diminished expectancy for the task to repeat. Taken together, this paper highlights the importance of predictions in the flexible control of behaviour, and suggests a crucial role for task repetition expectancy in the context-sensitive adjusting of task switching performance.

An Overview of Practical Applications of Protein Disorder Prediction and Drive for Faster, More Accurate Predictions.

Science.gov (United States)

Deng, Xin; Gumm, Jordan; Karki, Suman; Eickholt, Jesse; Cheng, Jianlin

2015-07-07

Protein disordered regions are segments of a protein chain that do not adopt a stable structure. Thus far, a variety of protein disorder prediction methods have been developed and have been widely used, not only in traditional bioinformatics domains, including protein structure prediction, protein structure determination and function annotation, but also in many other biomedical fields. The relationship between intrinsically-disordered proteins and some human diseases has played a significant role in disorder prediction in disease identification and epidemiological investigations. Disordered proteins can also serve as potential targets for drug discovery with an emphasis on the disordered-to-ordered transition in the disordered binding regions, and this has led to substantial research in drug discovery or design based on protein disordered region prediction. Furthermore, protein disorder prediction has also been applied to healthcare by predicting the disease risk of mutations in patients and studying the mechanistic basis of diseases. As the applications of disorder prediction increase, so too does the need to make quick and accurate predictions. To fill this need, we also present a new approach to predict protein residue disorder using wide sequence windows that is applicable on the genomic scale.

An Overview of Practical Applications of Protein Disorder Prediction and Drive for Faster, More Accurate Predictions

Directory of Open Access Journals (Sweden)

Xin Deng

2015-07-01

Full Text Available Protein disordered regions are segments of a protein chain that do not adopt a stable structure. Thus far, a variety of protein disorder prediction methods have been developed and have been widely used, not only in traditional bioinformatics domains, including protein structure prediction, protein structure determination and function annotation, but also in many other biomedical fields. The relationship between intrinsically-disordered proteins and some human diseases has played a significant role in disorder prediction in disease identification and epidemiological investigations. Disordered proteins can also serve as potential targets for drug discovery with an emphasis on the disordered-to-ordered transition in the disordered binding regions, and this has led to substantial research in drug discovery or design based on protein disordered region prediction. Furthermore, protein disorder prediction has also been applied to healthcare by predicting the disease risk of mutations in patients and studying the mechanistic basis of diseases. As the applications of disorder prediction increase, so too does the need to make quick and accurate predictions. To fill this need, we also present a new approach to predict protein residue disorder using wide sequence windows that is applicable on the genomic scale.

Confidence scores for prediction models

DEFF Research Database (Denmark)

Gerds, Thomas Alexander; van de Wiel, MA

2011-01-01

In medical statistics, many alternative strategies are available for building a prediction model based on training data. Prediction models are routinely compared by means of their prediction performance in independent validation data. If only one data set is available for training and validation,...

Predicting beta-turns and their types using predicted backbone dihedral angles and secondary structures.

Science.gov (United States)

Kountouris, Petros; Hirst, Jonathan D

2010-07-31

Beta-turns are secondary structure elements usually classified as coil. Their prediction is important, because of their role in protein folding and their frequent occurrence in protein chains. We have developed a novel method that predicts beta-turns and their types using information from multiple sequence alignments, predicted secondary structures and, for the first time, predicted dihedral angles. Our method uses support vector machines, a supervised classification technique, and is trained and tested on three established datasets of 426, 547 and 823 protein chains. We achieve a Matthews correlation coefficient of up to 0.49, when predicting the location of beta-turns, the highest reported value to date. Moreover, the additional dihedral information improves the prediction of beta-turn types I, II, IV, VIII and "non-specific", achieving correlation coefficients up to 0.39, 0.33, 0.27, 0.14 and 0.38, respectively. Our results are more accurate than other methods. We have created an accurate predictor of beta-turns and their types. Our method, called DEBT, is available online at http://comp.chem.nottingham.ac.uk/debt/.

A Grey NGM(1,1, k) Self-Memory Coupling Prediction Model for Energy Consumption Prediction

Science.gov (United States)

Guo, Xiaojun; Liu, Sifeng; Wu, Lifeng; Tang, Lingling

2014-01-01

Energy consumption prediction is an important issue for governments, energy sector investors, and other related corporations. Although there are several prediction techniques, selection of the most appropriate technique is of vital importance. As for the approximate nonhomogeneous exponential data sequence often emerging in the energy system, a novel grey NGM(1,1, k) self-memory coupling prediction model is put forward in order to promote the predictive performance. It achieves organic integration of the self-memory principle of dynamic system and grey NGM(1,1, k) model. The traditional grey model's weakness as being sensitive to initial value can be overcome by the self-memory principle. In this study, total energy, coal, and electricity consumption of China is adopted for demonstration by using the proposed coupling prediction technique. The results show the superiority of NGM(1,1, k) self-memory coupling prediction model when compared with the results from the literature. Its excellent prediction performance lies in that the proposed coupling model can take full advantage of the systematic multitime historical data and catch the stochastic fluctuation tendency. This work also makes a significant contribution to the enrichment of grey prediction theory and the extension of its application span. PMID:25054174

A Grey NGM(1,1,k Self-Memory Coupling Prediction Model for Energy Consumption Prediction

Directory of Open Access Journals (Sweden)

Xiaojun Guo

2014-01-01

Full Text Available Energy consumption prediction is an important issue for governments, energy sector investors, and other related corporations. Although there are several prediction techniques, selection of the most appropriate technique is of vital importance. As for the approximate nonhomogeneous exponential data sequence often emerging in the energy system, a novel grey NGM(1,1,k self-memory coupling prediction model is put forward in order to promote the predictive performance. It achieves organic integration of the self-memory principle of dynamic system and grey NGM(1,1,k model. The traditional grey model’s weakness as being sensitive to initial value can be overcome by the self-memory principle. In this study, total energy, coal, and electricity consumption of China is adopted for demonstration by using the proposed coupling prediction technique. The results show the superiority of NGM(1,1,k self-memory coupling prediction model when compared with the results from the literature. Its excellent prediction performance lies in that the proposed coupling model can take full advantage of the systematic multitime historical data and catch the stochastic fluctuation tendency. This work also makes a significant contribution to the enrichment of grey prediction theory and the extension of its application span.

Viral IRES prediction system - a web server for prediction of the IRES secondary structure in silico.

Directory of Open Access Journals (Sweden)

Jun-Jie Hong

Full Text Available The internal ribosomal entry site (IRES functions as cap-independent translation initiation sites in eukaryotic cells. IRES elements have been applied as useful tools for bi-cistronic expression vectors. Current RNA structure prediction programs are unable to predict precisely the potential IRES element. We have designed a viral IRES prediction system (VIPS to perform the IRES secondary structure prediction. In order to obtain better results for the IRES prediction, the VIPS can evaluate and predict for all four different groups of IRESs with a higher accuracy. RNA secondary structure prediction, comparison, and pseudoknot prediction programs were implemented to form the three-stage procedure for the VIPS. The backbone of VIPS includes: the RNAL fold program, aimed to predict local RNA secondary structures by minimum free energy method; the RNA Align program, intended to compare predicted structures; and pknotsRG program, used to calculate the pseudoknot structure. VIPS was evaluated by using UTR database, IRES database and Virus database, and the accuracy rate of VIPS was assessed as 98.53%, 90.80%, 82.36% and 80.41% for IRES groups 1, 2, 3, and 4, respectively. This advance useful search approach for IRES structures will facilitate IRES related studies. The VIPS on-line website service is available at http://140.135.61.250/vips/.

Numerical prediction of rose growth

NARCIS (Netherlands)

Bernsen, E.; Bokhove, Onno; van der Sar, D.M.

2006-01-01

A new mathematical model is presented for the prediction of rose growth in a greenhouse. Given the measured ambient environmental conditions, the model consists of a local photosynthesis model, predicting the photosynthesis per unit leaf area, coupled to a global greenhouse model, which predicts the

Seismology for rockburst prediction.

CSIR Research Space (South Africa)

De Beer, W

2000-02-01

Full Text Available project GAP409 presents a method (SOOTHSAY) for predicting larger mining induced seismic events in gold mines, as well as a pattern recognition algorithm (INDICATOR) for characterising the seismic response of rock to mining and inferring future... State. Defining the time series of a specific function on a catalogue as a prediction strategy, the algorithm currently has a success rate of 53% and 65%, respectively, of large events claimed as being predicted in these two cases, with uncertainties...

Collective motion of predictive swarms.

Directory of Open Access Journals (Sweden)

Nathaniel Rupprecht

Full Text Available Theoretical models of populations and swarms typically start with the assumption that the motion of agents is governed by the local stimuli. However, an intelligent agent, with some understanding of the laws that govern its habitat, can anticipate the future, and make predictions to gather resources more efficiently. Here we study a specific model of this kind, where agents aim to maximize their consumption of a diffusing resource, by attempting to predict the future of a resource field and the actions of other agents. Once the agents make a prediction, they are attracted to move towards regions that have, and will have, denser resources. We find that the further the agents attempt to see into the future, the more their attempts at prediction fail, and the less resources they consume. We also study the case where predictive agents compete against non-predictive agents and find the predictors perform better than the non-predictors only when their relative numbers are very small. We conclude that predictivity pays off either when the predictors do not see too far into the future or the number of predictors is small.

Neural Networks for protein Structure Prediction

DEFF Research Database (Denmark)

Bohr, Henrik

1998-01-01

This is a review about neural network applications in bioinformatics. Especially the applications to protein structure prediction, e.g. prediction of secondary structures, prediction of surface structure, fold class recognition and prediction of the 3-dimensional structure of protein backbones...

Prediction of resource volumes at untested locations using simple local prediction models

Science.gov (United States)

Attanasi, E.D.; Coburn, T.C.; Freeman, P.A.

2006-01-01

This paper shows how local spatial nonparametric prediction models can be applied to estimate volumes of recoverable gas resources at individual undrilled sites, at multiple sites on a regional scale, and to compute confidence bounds for regional volumes based on the distribution of those estimates. An approach that combines cross-validation, the jackknife, and bootstrap procedures is used to accomplish this task. Simulation experiments show that cross-validation can be applied beneficially to select an appropriate prediction model. The cross-validation procedure worked well for a wide range of different states of nature and levels of information. Jackknife procedures are used to compute individual prediction estimation errors at undrilled locations. The jackknife replicates also are used with a bootstrap resampling procedure to compute confidence bounds for the total volume. The method was applied to data (partitioned into a training set and target set) from the Devonian Antrim Shale continuous-type gas play in the Michigan Basin in Otsego County, Michigan. The analysis showed that the model estimate of total recoverable volumes at prediction sites is within 4 percent of the total observed volume. The model predictions also provide frequency distributions of the cell volumes at the production unit scale. Such distributions are the basis for subsequent economic analyses. ?? Springer Science+Business Media, LLC 2007.

Adaptive Outlier-tolerant Exponential Smoothing Prediction Algorithms with Applications to Predict the Temperature in Spacecraft

OpenAIRE

Hu Shaolin; Zhang Wei; Li Ye; Fan Shunxi

2011-01-01

The exponential smoothing prediction algorithm is widely used in spaceflight control and in process monitoring as well as in economical prediction. There are two key conundrums which are open: one is about the selective rule of the parameter in the exponential smoothing prediction, and the other is how to improve the bad influence of outliers on prediction. In this paper a new practical outlier-tolerant algorithm is built to select adaptively proper parameter, and the exponential smoothing pr...

Prediction of interannual climate variations

International Nuclear Information System (INIS)

Shukla, J.

1993-01-01

It has been known for some time that the behavior of the short-term fluctuations of the earth's atmosphere resembles that of a chaotic non-linear dynamical system, and that the day-to-day weather cannot be predicted beyond a few weeks. However, it has also been found that the interactions of the atmosphere with the underlying oceans and the land surfaces can produce fluctuations whose time scales are much longer than the limits of deterministic prediction of weather. It is, therefore, natural to ask whether it is possible that the seasonal and longer time averages of climate fluctuations can be predicted with sufficient skill to be beneficial for social and economic applications, even though the details of day-to-day weather cannot be predicted beyond a few weeks. The main objective of the workshop was to address this question by assessing the current state of knowledge on predictability of seasonal and interannual climate variability and to investigate various possibilities for its prediction. (orig./KW)

Dynamical Predictability of Monthly Means.

Science.gov (United States)

Shukla, J.

1981-12-01

We have attempted to determine the theoretical upper limit of dynamical predictability of monthly means for prescribed nonfluctuating external forcings. We have extended the concept of `classical' predictability, which primarily refers to the lack of predictability due mainly to the instabilities of synoptic-scale disturbances, to the predictability of time averages, which are determined by the predictability of low-frequency planetary waves. We have carded out 60-day integrations of a global general circulation model with nine different initial conditions but identical boundary conditions of sea surface temperature, snow, sea ice and soil moisture. Three of these initial conditions are the observed atmospheric conditions on 1 January of 1975, 1976 and 1977. The other six initial conditions are obtained by superimposing over the observed initial conditions a random perturbation comparable to the errors of observation. The root-mean-square (rms) error of random perturbations at all the grid points and all the model levels is 3 m s1 in u and v components of wind. The rms vector wind error between the observed initial conditions is >15 m s1.It is hypothesized that for a given averaging period, if the rms error among the time averages predicted from largely different initial conditions becomes comparable to the rms error among the time averages predicted from randomly perturbed initial conditions, the time averages are dynamically unpredictable. We have carried out the analysis of variance to compare the variability, among the three groups, due to largely different initial conditions, and within each group due to random perturbations.It is found that the variances among the first 30-day means, predicted from largely different initial conditions, are significantly different from the variances due to random perturbations in the initial conditions, whereas the variances among 30-day means for days 31-60 are not distinguishable from the variances due to random initial

Predictive Analytics in Information Systems Research

OpenAIRE

Shmueli, Galit; Koppius, Otto

2011-01-01

textabstractThis research essay highlights the need to integrate predictive analytics into information systems research and shows several concrete ways in which this goal can be accomplished. Predictive analytics include empirical methods (statistical and other) that generate data predictions as well as methods for assessing predictive power. Predictive analytics not only assist in creating practically useful models, they also play an important role alongside explanatory modeling in theory bu...

Prediction of intermetallic compounds

International Nuclear Information System (INIS)

Burkhanov, Gennady S; Kiselyova, N N

2009-01-01

The problems of predicting not yet synthesized intermetallic compounds are discussed. It is noted that the use of classical physicochemical analysis in the study of multicomponent metallic systems is faced with the complexity of presenting multidimensional phase diagrams. One way of predicting new intermetallics with specified properties is the use of modern processing technology with application of teaching of image recognition by the computer. The algorithms used most often in these methods are briefly considered and the efficiency of their use for predicting new compounds is demonstrated.

Learned predictiveness and outcome predictability effects are not simply two sides of the same coin.

Science.gov (United States)

Thorwart, Anna; Livesey, Evan J; Wilhelm, Francisco; Liu, Wei; Lachnit, Harald

2017-10-01

The Learned Predictiveness effect refers to the observation that learning about the relationship between a cue and an outcome is influenced by the predictive relevance of the cue for other outcomes. Similarly, the Outcome Predictability effect refers to a recent observation that the previous predictability of an outcome affects learning about this outcome in new situations, too. We hypothesize that both effects may be two manifestations of the same phenomenon and stimuli that have been involved in highly predictive relationships may be learned about faster when they are involved in new relationships regardless of their functional role in predictive learning as cues and outcomes. Four experiments manipulated both the relationships and the function of the stimuli. While we were able to replicate the standard effects, they did not survive a transfer to situations where the functional role of the stimuli changed, that is the outcome of the first phase becomes a cue in the second learning phase or the cue of the first phase becomes the outcome of the second phase. Furthermore, unlike learned predictiveness, there was little indication that the distribution of overt attention in the second phase was influenced by previous predictability. The results suggest that these 2 very similar effects are not manifestations of a more general phenomenon but rather independent from each other. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Estimating Model Prediction Error: Should You Treat Predictions as Fixed or Random?

Science.gov (United States)

Wallach, Daniel; Thorburn, Peter; Asseng, Senthold; Challinor, Andrew J.; Ewert, Frank; Jones, James W.; Rotter, Reimund; Ruane, Alexander

2016-01-01

Crop models are important tools for impact assessment of climate change, as well as for exploring management options under current climate. It is essential to evaluate the uncertainty associated with predictions of these models. We compare two criteria of prediction error; MSEP fixed, which evaluates mean squared error of prediction for a model with fixed structure, parameters and inputs, and MSEP uncertain( X), which evaluates mean squared error averaged over the distributions of model structure, inputs and parameters. Comparison of model outputs with data can be used to estimate the former. The latter has a squared bias term, which can be estimated using hindcasts, and a model variance term, which can be estimated from a simulation experiment. The separate contributions to MSEP uncertain (X) can be estimated using a random effects ANOVA. It is argued that MSEP uncertain (X) is the more informative uncertainty criterion, because it is specific to each prediction situation.

Peak-summer East Asian rainfall predictability and prediction part II: extratropical East Asia

Science.gov (United States)

Yim, So-Young; Wang, Bin; Xing, Wen

2016-07-01

The part II of the present study focuses on northern East Asia (NEA: 26°N-50°N, 100°-140°E), exploring the source and limit of the predictability of the peak summer (July-August) rainfall. Prediction of NEA peak summer rainfall is extremely challenging because of the exposure of the NEA to midlatitude influence. By examining four coupled climate models' multi-model ensemble (MME) hindcast during 1979-2010, we found that the domain-averaged MME temporal correlation coefficient (TCC) skill is only 0.13. It is unclear whether the dynamical models' poor skills are due to limited predictability of the peak-summer NEA rainfall. In the present study we attempted to address this issue by applying predictable mode analysis method using 35-year observations (1979-2013). Four empirical orthogonal modes of variability and associated major potential sources of variability are identified: (a) an equatorial western Pacific (EWP)-NEA teleconnection driven by EWP sea surface temperature (SST) anomalies, (b) a western Pacific subtropical high and Indo-Pacific dipole SST feedback mode, (c) a central Pacific-El Nino-Southern Oscillation mode, and (d) a Eurasian wave train pattern. Physically meaningful predictors for each principal component (PC) were selected based on analysis of the lead-lag correlations with the persistent and tendency fields of SST and sea-level pressure from March to June. A suite of physical-empirical (P-E) models is established to predict the four leading PCs. The peak summer rainfall anomaly pattern is then objectively predicted by using the predicted PCs and the corresponding observed spatial patterns. A 35-year cross-validated hindcast over the NEA yields a domain-averaged TCC skill of 0.36, which is significantly higher than the MME dynamical hindcast (0.13). The estimated maximum potential attainable TCC skill averaged over the entire domain is around 0.61, suggesting that the current dynamical prediction models may have large rooms to improve

Kunstnike Liit

Index Scriptorium Estoniae

2004-01-01

EKLi volikogu töökoosolek 5. IV. SA ERF alllfondina loodud Olev Soansi mälestusfondi toetamisest, EKLi 2005. a. aastanäituse korraldamisest Tallinna Kunstihoones, vajalikest täiendustest ja muudatustest põhikirjas, mis puudutavad tehinguid Tallinna Kunstihoone ja selle galeriiga. Võeti vastu tööjuhised SA Tallinna Kunstihoone Fondi nõukogule. EKLi uued liikmed: Kaarel Eelma, Piret Hirv, Sandra Jõgeva, Irene Jürna, Kristin Kalamees, Kristiina Laurits, Eve Margus-Villems, Villu Plink, Lembe Ruben, Katrin Sipelgas, Margus Tamm, Tanel Veenre

Enhancing Human-Machine System Performance by Introducing Artificial Cognition in Vehicle Guidance Work Systems

Science.gov (United States)

2009-10-01

evaluated after each mission using the NASA - TLX method [21]. Moreover, they were interviewed to be able to state problems and suggest system...France, 3 rd -4 th September 2008. [21] Sandra G. Hart & Lowell E. Staveland (1988). Development of NASA - TLX (Task Load Index): Results of...o b s e rv a b le b e h a v io u r o f C P = A C U b e h a v io u r Interpretation Figure 11: The Cognitive Process for generating knowledge

APF-The Lick Observatory Automated Planet Finder

Science.gov (United States)

2014-04-01

WILLIAM DEICH,1 BRIAN DUPRAW,1 WAYNE EARTHMAN,1 HARLAND EPPS,1 SANDRA FABER,1 DEBRA FISCHER ,3 ELINOR GATES,1 DAVID HILYARD,1 BRAD HOLDEN,1 KEN JOHNSTON,4...SANDY KEISER,2 DICK KANTO,1 MYRA KATSUKI,1 LEE LAITERMAN,1 KYLE LANCLOS,1 GREG LAUGHLIN,1 JEFF LEWIS,1 CHRIS LOCKWOOD,1,5 PAUL LYNAM,1 GEOFFREY MARCY,6...with S. Vogt as principal investigator, G. Marcy and D. Fischer as coinvestgators, and M. Radovan as project manager and principal engineer. A large

Polémica em torno da liberdade da sexualidade: «liberdade de importunar» versus violências sexuais

OpenAIRE

Cova, Anne

2018-01-01

Na sequência do escândalo que explodiu nos EUA em Outubro de 2017 envolvendo o produtor americano de cinema Harvey Weinstein, nasceram os hashtags #Balancetonporc e #MeToo que levaram dezenas de milhares de mulheres a testemunhar sobre as violências sexuais. No Twitter, #Balancetonporc foi lançado no dia 13 de Outubro por uma jornalista francesa, Sandra Muller, e dois dias depois a atriz americana, Alyssa Milano, tomou uma iniciativa semelhante com #MeToo. O efeito bola de neve das redes soci...

Globalization and FARC

Science.gov (United States)

2013-03-01

through the National Security Doctrine, the ALCA (Area de Libre Comercio de las Americas, The Free Trade Area of the Americas) is, the Plan Colombia...of books such as El Mossad and Las Armas Secretas de la Cía). Other sources like El Universal of Mexico (30-OCT- 03), have stated that Al Qaeda has...María Edith Bordón”, Sandra Quiñónez, prosecutor of the Counter Kidnapping Unit said in El Tiempo newspaper. Bordón was kidnapped on September 21

Fiftieth Anniversary at the summit

CERN Multimedia

2005-01-01

Neither fear of heights nor the cold succeeded in cooling the ardour of four brave climbers from CERN who celebrated CERN's 50th Anniversary at the summit of Mount Kilimanjaro (5,895 metres). On the way back from the summit, Miguel Cerqueira Bastos (AB/PO), David Collados Polidura (IT/GM), Sandra Sequeira Tavares (PH/CMI) and Daniel Cano Ott (n_TOF) raised the official CERN Jubilee flag at 4750 metres altitude. How long will it be before a CERN flag is planted on the moon?

Predicting child maltreatment: A meta-analysis of the predictive validity of risk assessment instruments.

Science.gov (United States)

van der Put, Claudia E; Assink, Mark; Boekhout van Solinge, Noëlle F

2017-11-01

Risk assessment is crucial in preventing child maltreatment since it can identify high-risk cases in need of child protection intervention. Despite widespread use of risk assessment instruments in child welfare, it is unknown how well these instruments predict maltreatment and what instrument characteristics are associated with higher levels of predictive validity. Therefore, a multilevel meta-analysis was conducted to examine the predictive accuracy of (characteristics of) risk assessment instruments. A literature search yielded 30 independent studies (N=87,329) examining the predictive validity of 27 different risk assessment instruments. From these studies, 67 effect sizes could be extracted. Overall, a medium significant effect was found (AUC=0.681), indicating a moderate predictive accuracy. Moderator analyses revealed that onset of maltreatment can be better predicted than recurrence of maltreatment, which is a promising finding for early detection and prevention of child maltreatment. In addition, actuarial instruments were found to outperform clinical instruments. To bring risk and needs assessment in child welfare to a higher level, actuarial instruments should be further developed and strengthened by distinguishing risk assessment from needs assessment and by integrating risk assessment with case management. Copyright © 2017 Elsevier Ltd. All rights reserved.

Integrating geophysics and hydrology for reducing the uncertainty of groundwater model predictions and improved prediction performance

DEFF Research Database (Denmark)

Christensen, Nikolaj Kruse; Christensen, Steen; Ferre, Ty

the integration of geophysical data in the construction of a groundwater model increases the prediction performance. We suggest that modelers should perform a hydrogeophysical “test-bench” analysis of the likely value of geophysics data for improving groundwater model prediction performance before actually...... and the resulting predictions can be compared with predictions from the ‘true’ model. By performing this analysis we expect to give the modeler insight into how the uncertainty of model-based prediction can be reduced.......A major purpose of groundwater modeling is to help decision-makers in efforts to manage the natural environment. Increasingly, it is recognized that both the predictions of interest and their associated uncertainties should be quantified to support robust decision making. In particular, decision...

Aircraft noise prediction program theoretical manual: Rotorcraft System Noise Prediction System (ROTONET), part 4

Science.gov (United States)

Weir, Donald S.; Jumper, Stephen J.; Burley, Casey L.; Golub, Robert A.

1995-01-01

This document describes the theoretical methods used in the rotorcraft noise prediction system (ROTONET), which is a part of the NASA Aircraft Noise Prediction Program (ANOPP). The ANOPP code consists of an executive, database manager, and prediction modules for jet engine, propeller, and rotor noise. The ROTONET subsystem contains modules for the prediction of rotor airloads and performance with momentum theory and prescribed wake aerodynamics, rotor tone noise with compact chordwise and full-surface solutions to the Ffowcs-Williams-Hawkings equations, semiempirical airfoil broadband noise, and turbulence ingestion broadband noise. Flight dynamics, atmosphere propagation, and noise metric calculations are covered in NASA TM-83199, Parts 1, 2, and 3.

Time-predictable Stack Caching

DEFF Research Database (Denmark)

Abbaspourseyedi, Sahar

completely. Thus, in systems with hard deadlines the worst-case execution time (WCET) of the real-time software running on them needs to be bounded. Modern architectures use features such as pipelining and caches for improving the average performance. These features, however, make the WCET analysis more...... addresses, provides an opportunity to predict and tighten the WCET of accesses to data in caches. In this thesis, we introduce the time-predictable stack cache design and implementation within a time-predictable processor. We introduce several optimizations to our design for tightening the WCET while...... keeping the timepredictability of the design intact. Moreover, we provide a solution for reducing the cost of context switching in a system using the stack cache. In design of these caches, we use custom hardware and compiler support for delivering time-predictable stack data accesses. Furthermore...

Implementation of short-term prediction

Energy Technology Data Exchange (ETDEWEB)

Landberg, L; Joensen, A; Giebel, G [and others

1999-03-01

This paper will giver a general overview of the results from a EU JOULE funded project (`Implementing short-term prediction at utilities`, JOR3-CT95-0008). Reference will be given to specialised papers where applicable. The goal of the project was to implement wind farm power output prediction systems in operational environments at a number of utilities in Europe. Two models were developed, one by Risoe and one by the Technical University of Denmark (DTU). Both prediction models used HIRLAM predictions from the Danish Meteorological Institute (DMI). (au) EFP-94; EU-JOULE. 11 refs.

Earthquake prediction by Kina Method

International Nuclear Information System (INIS)

Kianoosh, H.; Keypour, H.; Naderzadeh, A.; Motlagh, H.F.

2005-01-01

Earthquake prediction has been one of the earliest desires of the man. Scientists have worked hard to predict earthquakes for a long time. The results of these efforts can generally be divided into two methods of prediction: 1) Statistical Method, and 2) Empirical Method. In the first method, earthquakes are predicted using statistics and probabilities, while the second method utilizes variety of precursors for earthquake prediction. The latter method is time consuming and more costly. However, the result of neither method has fully satisfied the man up to now. In this paper a new method entitled 'Kiana Method' is introduced for earthquake prediction. This method offers more accurate results yet lower cost comparing to other conventional methods. In Kiana method the electrical and magnetic precursors are measured in an area. Then, the time and the magnitude of an earthquake in the future is calculated using electrical, and in particular, electrical capacitors formulas. In this method, by daily measurement of electrical resistance in an area we make clear that the area is capable of earthquake occurrence in the future or not. If the result shows a positive sign, then the occurrence time and the magnitude can be estimated by the measured quantities. This paper explains the procedure and details of this prediction method. (authors)

Audiovisual biofeedback improves motion prediction accuracy.

Science.gov (United States)

Pollock, Sean; Lee, Danny; Keall, Paul; Kim, Taeho

2013-04-01

The accuracy of motion prediction, utilized to overcome the system latency of motion management radiotherapy systems, is hampered by irregularities present in the patients' respiratory pattern. Audiovisual (AV) biofeedback has been shown to reduce respiratory irregularities. The aim of this study was to test the hypothesis that AV biofeedback improves the accuracy of motion prediction. An AV biofeedback system combined with real-time respiratory data acquisition and MR images were implemented in this project. One-dimensional respiratory data from (1) the abdominal wall (30 Hz) and (2) the thoracic diaphragm (5 Hz) were obtained from 15 healthy human subjects across 30 studies. The subjects were required to breathe with and without the guidance of AV biofeedback during each study. The obtained respiratory signals were then implemented in a kernel density estimation prediction algorithm. For each of the 30 studies, five different prediction times ranging from 50 to 1400 ms were tested (150 predictions performed). Prediction error was quantified as the root mean square error (RMSE); the RMSE was calculated from the difference between the real and predicted respiratory data. The statistical significance of the prediction results was determined by the Student's t-test. Prediction accuracy was considerably improved by the implementation of AV biofeedback. Of the 150 respiratory predictions performed, prediction accuracy was improved 69% (103/150) of the time for abdominal wall data, and 78% (117/150) of the time for diaphragm data. The average reduction in RMSE due to AV biofeedback over unguided respiration was 26% (p biofeedback improves prediction accuracy. This would result in increased efficiency of motion management techniques affected by system latencies used in radiotherapy.

The trickle-down effect of predictability: Secondary task performance benefits from predictability in the primary task.

Directory of Open Access Journals (Sweden)

Magdalena Ewa Król

Full Text Available Predictions optimize processing by reducing attentional resources allocation to expected or predictable sensory data. Our study demonstrates that these saved processing resources can be then used on concurrent stimuli, and in consequence improve their processing and encoding. We illustrate this "trickle-down" effect with a dual task, where the primary task varied in terms of predictability. The primary task involved detection of a pre-specified symbol that appeared at some point of a short video of a dot moving along a random, semi-predictable or predictable trajectory. The concurrent secondary task involved memorization of photographs representing either emotionally neutral or non-neutral (social or threatening content. Performance in the secondary task was measured by a memory test. We found that participants allocated more attention to unpredictable (random and semi-predictable stimuli than to predictable stimuli. Additionally, when the stimuli in the primary task were more predictable, participants performed better in the secondary task, as evidenced by higher sensitivity in the memory test. Finally, social or threatening stimuli were allocated more "looking time" and a larger number of saccades than neutral stimuli. This effect was stronger for the threatening stimuli than social stimuli. Thus, predictability of environmental input is used in optimizing the allocation of attentional resources, which trickles-down and benefits the processing of concurrent stimuli.

The trickle-down effect of predictability: Secondary task performance benefits from predictability in the primary task.

Science.gov (United States)

Król, Magdalena Ewa; Król, Michał

2017-01-01

Predictions optimize processing by reducing attentional resources allocation to expected or predictable sensory data. Our study demonstrates that these saved processing resources can be then used on concurrent stimuli, and in consequence improve their processing and encoding. We illustrate this "trickle-down" effect with a dual task, where the primary task varied in terms of predictability. The primary task involved detection of a pre-specified symbol that appeared at some point of a short video of a dot moving along a random, semi-predictable or predictable trajectory. The concurrent secondary task involved memorization of photographs representing either emotionally neutral or non-neutral (social or threatening) content. Performance in the secondary task was measured by a memory test. We found that participants allocated more attention to unpredictable (random and semi-predictable) stimuli than to predictable stimuli. Additionally, when the stimuli in the primary task were more predictable, participants performed better in the secondary task, as evidenced by higher sensitivity in the memory test. Finally, social or threatening stimuli were allocated more "looking time" and a larger number of saccades than neutral stimuli. This effect was stronger for the threatening stimuli than social stimuli. Thus, predictability of environmental input is used in optimizing the allocation of attentional resources, which trickles-down and benefits the processing of concurrent stimuli.

NOAA's National Air Quality Prediction and Development of Aerosol and Atmospheric Composition Prediction Components for NGGPS

Science.gov (United States)

Stajner, I.; McQueen, J.; Lee, P.; Stein, A. F.; Wilczak, J. M.; Upadhayay, S.; daSilva, A.; Lu, C. H.; Grell, G. A.; Pierce, R. B.

2017-12-01

NOAA's operational air quality predictions of ozone, fine particulate matter (PM2.5) and wildfire smoke over the United States and airborne dust over the contiguous 48 states are distributed at http://airquality.weather.gov. The National Air Quality Forecast Capability (NAQFC) providing these predictions was updated in June 2017. Ozone and PM2.5 predictions are now produced using the system linking the Community Multiscale Air Quality model (CMAQ) version 5.0.2 with meteorological inputs from the North American Mesoscale Forecast System (NAM) version 4. Predictions of PM2.5 include intermittent dust emissions and wildfire emissions from an updated version of BlueSky system. For the latter, the CMAQ system is initialized by rerunning it over the previous 24 hours to include wildfire emissions at the time when they were observed from the satellites. Post processing to reduce the bias in PM2.5 prediction was updated using the Kalman filter analog (KFAN) technique. Dust related aerosol species at the CMAQ domain lateral boundaries now come from the NEMS Global Aerosol Component (NGAC) v2 predictions. Further development of NAQFC includes testing of CMAQ predictions to 72 hours, Canadian fire emissions data from Environment and Climate Change Canada (ECCC) and the KFAN technique to reduce bias in ozone predictions. NOAA is developing the Next Generation Global Predictions System (NGGPS) with an aerosol and gaseous atmospheric composition component to improve and integrate aerosol and ozone predictions and evaluate their impacts on physics, data assimilation and weather prediction. Efforts are underway to improve cloud microphysics, investigate aerosol effects and include representations of atmospheric composition of varying complexity into NGGPS: from the operational ozone parameterization, GOCART aerosols, with simplified ozone chemistry, to CMAQ chemistry with aerosol modules. We will present progress on community building, planning and development of NGGPS.

Archaeological predictive model set.

Science.gov (United States)

2015-03-01

This report is the documentation for Task 7 of the Statewide Archaeological Predictive Model Set. The goal of this project is to : develop a set of statewide predictive models to assist the planning of transportation projects. PennDOT is developing t...

Branch prediction in the pentium family

DEFF Research Database (Denmark)

Fog, Agner

1998-01-01

How the branch prediction mechanism in the Pentium has been uncovered with all its quirks, and the incredibly more effective branch prediction in the later versions.......How the branch prediction mechanism in the Pentium has been uncovered with all its quirks, and the incredibly more effective branch prediction in the later versions....

Prediction during sentence comprehension in aphasia

Directory of Open Access Journals (Sweden)

Michael Walsh Dickey

2014-04-01

Full Text Available Much recent psycholinguistic work has focused on prediction in language comprehension (Altmann & Kamide, 1999; Federmeier, 2007; Levy, 2008. Unimpaired adults predict upcoming words and phrases based on material in the preceding context, like verbs (Altmann & Kamide, 1999 or constraining sentence contexts (Federmeier, 2007. Several models have tied rapid prediction to the language production system (Federmeier, 2007; Pickering & Garrod, 2013; Dell & Chang, 2014. Evidence for this link comes from that fact that older adults with lower verbal fluency show less predictive behavior (Federmeier, et al., 2010; DeLong, et al., 2012. Prediction in aphasic language comprehension has not been widely investigated, even though constraining sentence contexts are strongly facilitative for naming in aphasia (e.g., Love & Webb, 1977. Mack, et al. (2013 found in a visual-world task that people with aphasia (PWA do not predict upcoming objects based on verbs (cf. Altmann & Kamide, 1999. This finding suggests that prediction may be reduced in aphasia. However, it is unclear whether reduced prediction was caused by language-production impairments: all the PWA in their study had non-fluent aphasia. The current study examined whether PWA show evidence of prediction based on constraining sentence contexts (e.g., Federmeier, 2007. Specifically, it tested whether they exhibited facilitation for highly predictable words in reading, using materials that have previously demonstrated strong predictability effects for unimpaired adults (Rayner, et al., 2004. In addition, it tested whether differences in language-production ability among PWA accounted for differences in predictive behavior (viz. Pickering & Garrod, 2013; Dell & Chang, 2014. Eight PWA read sentences adapted from Rayner, et al. (2004 in a self-paced reading task. The materials crossed word frequency with predictability: high- vs. low-frequency words (bottle/diaper were preceded by contexts which made them

Stuck pipe prediction

KAUST Repository

Alzahrani, Majed; Alsolami, Fawaz; Chikalov, Igor; Algharbi, Salem; Aboudi, Faisal; Khudiri, Musab

2016-01-01

Disclosed are various embodiments for a prediction application to predict a stuck pipe. A linear regression model is generated from hook load readings at corresponding bit depths. A current hook load reading at a current bit depth is compared with a normal hook load reading from the linear regression model. A current hook load greater than a normal hook load for a given bit depth indicates the likelihood of a stuck pipe.

Stuck pipe prediction

KAUST Repository

Alzahrani, Majed

2016-03-10

Disclosed are various embodiments for a prediction application to predict a stuck pipe. A linear regression model is generated from hook load readings at corresponding bit depths. A current hook load reading at a current bit depth is compared with a normal hook load reading from the linear regression model. A current hook load greater than a normal hook load for a given bit depth indicates the likelihood of a stuck pipe.

Earthquake predictions using seismic velocity ratios

Science.gov (United States)

Sherburne, R. W.

1979-01-01

Since the beginning of modern seismology, seismologists have contemplated predicting earthquakes. The usefulness of earthquake predictions to the reduction of human and economic losses and the value of long-range earthquake prediction to planning is obvious. Not as clear are the long-range economic and social impacts of earthquake prediction to a speicifc area. The general consensus of opinion among scientists and government officials, however, is that the quest of earthquake prediction is a worthwhile goal and should be prusued with a sense of urgency. 

Predictive Biomarkers for Asthma Therapy.

Science.gov (United States)

Medrek, Sarah K; Parulekar, Amit D; Hanania, Nicola A

2017-09-19

Asthma is a heterogeneous disease characterized by multiple phenotypes. Treatment of patients with severe disease can be challenging. Predictive biomarkers are measurable characteristics that reflect the underlying pathophysiology of asthma and can identify patients that are likely to respond to a given therapy. This review discusses current knowledge regarding predictive biomarkers in asthma. Recent trials evaluating biologic therapies targeting IgE, IL-5, IL-13, and IL-4 have utilized predictive biomarkers to identify patients who might benefit from treatment. Other work has suggested that using composite biomarkers may offer enhanced predictive capabilities in tailoring asthma therapy. Multiple biomarkers including sputum eosinophil count, blood eosinophil count, fractional concentration of nitric oxide in exhaled breath (FeNO), and serum periostin have been used to identify which patients will respond to targeted asthma medications. Further work is needed to integrate predictive biomarkers into clinical practice.

Towards Predictive Association Theories

DEFF Research Database (Denmark)

Kontogeorgis, Georgios; Tsivintzelis, Ioannis; Michelsen, Michael Locht

2011-01-01

Association equations of state like SAFT, CPA and NRHB have been previously applied to many complex mixtures. In this work we focus on two of these models, the CPA and the NRHB equations of state and the emphasis is on the analysis of their predictive capabilities for a wide range of applications....... We use the term predictive in two situations: (i) with no use of binary interaction parameters, and (ii) multicomponent calculations using binary interaction parameters based solely on binary data. It is shown that the CPA equation of state can satisfactorily predict CO2–water–glycols–alkanes VLE...

Selecting Optimal Random Forest Predictive Models: A Case Study on Predicting the Spatial Distribution of Seabed Hardness

Science.gov (United States)

Li, Jin; Tran, Maggie; Siwabessy, Justy

2016-01-01

Spatially continuous predictions of seabed hardness are important baseline environmental information for sustainable management of Australia’s marine jurisdiction. Seabed hardness is often inferred from multibeam backscatter data with unknown accuracy and can be inferred from underwater video footage at limited locations. In this study, we classified the seabed into four classes based on two new seabed hardness classification schemes (i.e., hard90 and hard70). We developed optimal predictive models to predict seabed hardness using random forest (RF) based on the point data of hardness classes and spatially continuous multibeam data. Five feature selection (FS) methods that are variable importance (VI), averaged variable importance (AVI), knowledge informed AVI (KIAVI), Boruta and regularized RF (RRF) were tested based on predictive accuracy. Effects of highly correlated, important and unimportant predictors on the accuracy of RF predictive models were examined. Finally, spatial predictions generated using the most accurate models were visually examined and analysed. This study confirmed that: 1) hard90 and hard70 are effective seabed hardness classification schemes; 2) seabed hardness of four classes can be predicted with a high degree of accuracy; 3) the typical approach used to pre-select predictive variables by excluding highly correlated variables needs to be re-examined; 4) the identification of the important and unimportant predictors provides useful guidelines for further improving predictive models; 5) FS methods select the most accurate predictive model(s) instead of the most parsimonious ones, and AVI and Boruta are recommended for future studies; and 6) RF is an effective modelling method with high predictive accuracy for multi-level categorical data and can be applied to ‘small p and large n’ problems in environmental sciences. Additionally, automated computational programs for AVI need to be developed to increase its computational efficiency and

Predicting Ideological Prejudice.

Science.gov (United States)

Brandt, Mark J

2017-06-01

A major shortcoming of current models of ideological prejudice is that although they can anticipate the direction of the association between participants' ideology and their prejudice against a range of target groups, they cannot predict the size of this association. I developed and tested models that can make specific size predictions for this association. A quantitative model that used the perceived ideology of the target group as the primary predictor of the ideology-prejudice relationship was developed with a representative sample of Americans ( N = 4,940) and tested against models using the perceived status of and choice to belong to the target group as predictors. In four studies (total N = 2,093), ideology-prejudice associations were estimated, and these observed estimates were compared with the models' predictions. The model that was based only on perceived ideology was the most parsimonious with the smallest errors.

Predicting visibility of aircraft.

Directory of Open Access Journals (Sweden)

Andrew Watson

Full Text Available Visual detection of aircraft by human observers is an important element of aviation safety. To assess and ensure safety, it would be useful to be able to be able to predict the visibility, to a human observer, of an aircraft of specified size, shape, distance, and coloration. Examples include assuring safe separation among aircraft and between aircraft and unmanned vehicles, design of airport control towers, and efforts to enhance or suppress the visibility of military and rescue vehicles. We have recently developed a simple metric of pattern visibility, the Spatial Standard Observer (SSO. In this report we examine whether the SSO can predict visibility of simulated aircraft images. We constructed a set of aircraft images from three-dimensional computer graphic models, and measured the luminance contrast threshold for each image from three human observers. The data were well predicted by the SSO. Finally, we show how to use the SSO to predict visibility range for aircraft of arbitrary size, shape, distance, and coloration.

Psychometric prediction of penitentiary recidivism.

Science.gov (United States)

Medina García, Pedro M; Baños Rivera, Rosa M

2016-05-01

Attempts to predict prison recidivism based on the personality have not been very successful. This study aims to provide data on recidivism prediction based on the scores on a personality questionnaire. For this purpose, a predictive model combining the actuarial procedure with a posteriori probability was developed, consisting of the probabilistic calculation of the effective verification of the event once it has already occurred. Cuestionario de Personalidad Situacional (CPS; Fernández, Seisdedos, & Mielgo, 1998) was applied to 978 male inmates classified as recidivists or non-recidivists. High predictive power was achieved, with the area under the curve (AUC) of 0.85 (p <.001; Se = 0.012; 95% CI [0.826, 0.873]. The answers to the CPS items made it possible to properly discriminate 77.3% of the participants. These data indicate the important role of the personality as a key factor in understanding delinquency and predicting recidivism.

Univariate Time Series Prediction of Solar Power Using a Hybrid Wavelet-ARMA-NARX Prediction Method

Energy Technology Data Exchange (ETDEWEB)

Nazaripouya, Hamidreza; Wang, Yubo; Chu, Chi-Cheng; Pota, Hemanshu; Gadh, Rajit

2016-05-02

This paper proposes a new hybrid method for super short-term solar power prediction. Solar output power usually has a complex, nonstationary, and nonlinear characteristic due to intermittent and time varying behavior of solar radiance. In addition, solar power dynamics is fast and is inertia less. An accurate super short-time prediction is required to compensate for the fluctuations and reduce the impact of solar power penetration on the power system. The objective is to predict one step-ahead solar power generation based only on historical solar power time series data. The proposed method incorporates discrete wavelet transform (DWT), Auto-Regressive Moving Average (ARMA) models, and Recurrent Neural Networks (RNN), while the RNN architecture is based on Nonlinear Auto-Regressive models with eXogenous inputs (NARX). The wavelet transform is utilized to decompose the solar power time series into a set of richer-behaved forming series for prediction. ARMA model is employed as a linear predictor while NARX is used as a nonlinear pattern recognition tool to estimate and compensate the error of wavelet-ARMA prediction. The proposed method is applied to the data captured from UCLA solar PV panels and the results are compared with some of the common and most recent solar power prediction methods. The results validate the effectiveness of the proposed approach and show a considerable improvement in the prediction precision.

Verification, validation, and reliability of predictions

International Nuclear Information System (INIS)

Pigford, T.H.; Chambre, P.L.

1987-04-01

The objective of predicting long-term performance should be to make reliable determinations of whether the prediction falls within the criteria for acceptable performance. Establishing reliable predictions of long-term performance of a waste repository requires emphasis on valid theories to predict performance. The validation process must establish the validity of the theory, the parameters used in applying the theory, the arithmetic of calculations, and the interpretation of results; but validation of such performance predictions is not possible unless there are clear criteria for acceptable performance. Validation programs should emphasize identification of the substantive issues of prediction that need to be resolved. Examples relevant to waste package performance are predicting the life of waste containers and the time distribution of container failures, establishing the criteria for defining container failure, validating theories for time-dependent waste dissolution that depend on details of the repository environment, and determining the extent of congruent dissolution of radionuclides in the UO 2 matrix of spent fuel. Prediction and validation should go hand in hand and should be done and reviewed frequently, as essential tools for the programs to design and develop repositories. 29 refs

Predicting DNA-binding proteins and binding residues by complex structure prediction and application to human proteome.

Directory of Open Access Journals (Sweden)

Huiying Zhao

Full Text Available As more and more protein sequences are uncovered from increasingly inexpensive sequencing techniques, an urgent task is to find their functions. This work presents a highly reliable computational technique for predicting DNA-binding function at the level of protein-DNA complex structures, rather than low-resolution two-state prediction of DNA-binding as most existing techniques do. The method first predicts protein-DNA complex structure by utilizing the template-based structure prediction technique HHblits, followed by binding affinity prediction based on a knowledge-based energy function (Distance-scaled finite ideal-gas reference state for protein-DNA interactions. A leave-one-out cross validation of the method based on 179 DNA-binding and 3797 non-binding protein domains achieves a Matthews correlation coefficient (MCC of 0.77 with high precision (94% and high sensitivity (65%. We further found 51% sensitivity for 82 newly determined structures of DNA-binding proteins and 56% sensitivity for the human proteome. In addition, the method provides a reasonably accurate prediction of DNA-binding residues in proteins based on predicted DNA-binding complex structures. Its application to human proteome leads to more than 300 novel DNA-binding proteins; some of these predicted structures were validated by known structures of homologous proteins in APO forms. The method [SPOT-Seq (DNA] is available as an on-line server at http://sparks-lab.org.

Potential for western US seasonal snowpack prediction

Science.gov (United States)

Kapnick, Sarah B.; Yang, Xiaosong; Vecchi, Gabriel A.; Delworth, Thomas L.; Gudgel, Rich; Malyshev, Sergey; Milly, Paul C. D.; Shevliakova, Elena; Underwood, Seth; Margulis, Steven A.

2018-01-01

Western US snowpack—snow that accumulates on the ground in the mountains—plays a critical role in regional hydroclimate and water supply, with 80% of snowmelt runoff being used for agriculture. While climate projections provide estimates of snowpack loss by the end of th ecentury and weather forecasts provide predictions of weather conditions out to 2 weeks, less progress has been made for snow predictions at seasonal timescales (months to 2 years), crucial for regional agricultural decisions (e.g., plant choice and quantity). Seasonal predictions with climate models first took the form of El Niño predictions 3 decades ago, with hydroclimate predictions emerging more recently. While the field has been focused on single-season predictions (3 months or less), we are now poised to advance our predictions beyond this timeframe. Utilizing observations, climate indices, and a suite of global climate models, we demonstrate the feasibility of seasonal snowpack predictions and quantify the limits of predictive skill 8 month sin advance. This physically based dynamic system outperforms observation-based statistical predictions made on July 1 for March snowpack everywhere except the southern Sierra Nevada, a region where prediction skill is nonexistent for every predictor presently tested. Additionally, in the absence of externally forced negative trends in snowpack, narrow maritime mountain ranges with high hydroclimate variability pose a challenge for seasonal prediction in our present system; natural snowpack variability may inherently be unpredictable at this timescale. This work highlights present prediction system successes and gives cause for optimism for developing seasonal predictions for societal needs.

Right Lateral Cerebellum Represents Linguistic Predictability.

Science.gov (United States)

Lesage, Elise; Hansen, Peter C; Miall, R Chris

2017-06-28

Mounting evidence indicates that posterolateral portions of the cerebellum (right Crus I/II) contribute to language processing, but the nature of this role remains unclear. Based on a well-supported theory of cerebellar motor function, which ascribes to the cerebellum a role in short-term prediction through internal modeling, we hypothesize that right cerebellar Crus I/II supports prediction of upcoming sentence content. We tested this hypothesis using event-related fMRI in male and female human subjects by manipulating the predictability of written sentences. Our design controlled for motor planning and execution, as well as for linguistic features and working memory load; it also allowed separation of the prediction interval from the presentation of the final sentence item. In addition, three further fMRI tasks captured semantic, phonological, and orthographic processing to shed light on the nature of the information processed. As hypothesized, activity in right posterolateral cerebellum correlated with the predictability of the upcoming target word. This cerebellar region also responded to prediction error during the outcome of the trial. Further, this region was engaged in phonological, but not semantic or orthographic, processing. This is the first imaging study to demonstrate a right cerebellar contribution in language comprehension independently from motor, cognitive, and linguistic confounds. These results complement our work using other methodologies showing cerebellar engagement in linguistic prediction and suggest that internal modeling of phonological representations aids language production and comprehension. SIGNIFICANCE STATEMENT The cerebellum is traditionally seen as a motor structure that allows for smooth movement by predicting upcoming signals. However, the cerebellum is also consistently implicated in nonmotor functions such as language and working memory. Using fMRI, we identify a cerebellar area that is active when words are predicted and

Controlled test for predictive power of Lyapunov exponents: their inability to predict epileptic seizures.

Science.gov (United States)

Lai, Ying-Cheng; Harrison, Mary Ann F; Frei, Mark G; Osorio, Ivan

2004-09-01

Lyapunov exponents are a set of fundamental dynamical invariants characterizing a system's sensitive dependence on initial conditions. For more than a decade, it has been claimed that the exponents computed from electroencephalogram (EEG) or electrocorticogram (ECoG) signals can be used for prediction of epileptic seizures minutes or even tens of minutes in advance. The purpose of this paper is to examine the predictive power of Lyapunov exponents. Three approaches are employed. (1) We present qualitative arguments suggesting that the Lyapunov exponents generally are not useful for seizure prediction. (2) We construct a two-dimensional, nonstationary chaotic map with a parameter slowly varying in a range containing a crisis, and test whether this critical event can be predicted by monitoring the evolution of finite-time Lyapunov exponents. This can thus be regarded as a "control test" for the claimed predictive power of the exponents for seizure. We find that two major obstacles arise in this application: statistical fluctuations of the Lyapunov exponents due to finite time computation and noise from the time series. We show that increasing the amount of data in a moving window will not improve the exponents' detective power for characteristic system changes, and that the presence of small noise can ruin completely the predictive power of the exponents. (3) We report negative results obtained from ECoG signals recorded from patients with epilepsy. All these indicate firmly that, the use of Lyapunov exponents for seizure prediction is practically impossible as the brain dynamical system generating the ECoG signals is more complicated than low-dimensional chaotic systems, and is noisy. Copyright 2004 American Institute of Physics

Wind power prediction models

Science.gov (United States)

Levy, R.; Mcginness, H.

1976-01-01

Investigations were performed to predict the power available from the wind at the Goldstone, California, antenna site complex. The background for power prediction was derived from a statistical evaluation of available wind speed data records at this location and at nearby locations similarly situated within the Mojave desert. In addition to a model for power prediction over relatively long periods of time, an interim simulation model that produces sample wind speeds is described. The interim model furnishes uncorrelated sample speeds at hourly intervals that reproduce the statistical wind distribution at Goldstone. A stochastic simulation model to provide speed samples representative of both the statistical speed distributions and correlations is also discussed.

Prediction ranges. Annual review

Energy Technology Data Exchange (ETDEWEB)

Parker, J.C.; Tharp, W.H.; Spiro, P.S.; Keng, K.; Angastiniotis, M.; Hachey, L.T.

1988-01-01

Prediction ranges equip the planner with one more tool for improved assessment of the outcome of a course of action. One of their major uses is in financial evaluations, where corporate policy requires the performance of uncertainty analysis for large projects. This report gives an overview of the uses of prediction ranges, with examples; and risks and uncertainties in growth, inflation, and interest and exchange rates. Prediction ranges and standard deviations of 80% and 50% probability are given for various economic indicators in Ontario, Canada, and the USA, as well as for foreign exchange rates and Ontario Hydro interest rates. An explanatory note on probability is also included. 23 tabs.

El riesgo contable

OpenAIRE

Pérez, Haydée J.; Carboni, Sandra

2005-01-01

Se propone incluir el riesgo contable como una nueva categoría dentro del riesgo asistemático, conceptualizando dicho riesgo y analizando los factores que lo determinan, para incluir su estimación como una etapa dentro de la metodología del análisis económico-financiero basado en información contable. Fil: Pérez, Haydée J. Universidad Nacional de Mar del Plata. Facultad de Ciencias Económicas y Sociales; Argentina. Fil: Carboni, Sandra. Universidad Nacional de Mar del Plata. Facultad de...

Fatores que influenciam o sobrepeso de crianças menores de quatro anos usuárias do SUS e Centros de Ensino Infantil do Município de Curitiba

OpenAIRE

Baltazar, Daniele Ferreira Barbosa dos Santos

2015-01-01

Orientadora : Profª. Drª. Sandra M. W. Barreira Co-orientadora : Profª. Drª. Grace M. F. C. Wile Dissertação (mestrado) - Universidade Federal do Paraná, Setor de Ciências da Saúde, Programa de Pós-Graduação em Ciências Farmacêuticas. Defesa: Curitiba, 27/03/2015 Inclui referências Área de concentração: Insumos, medicamentos e correlatos Resumo: A obesidade infantil se caracteriza como uma epidemia, sendo um dos principais desafios da saúde pública no momento. Seu combate pode ...

Editorial

Directory of Open Access Journals (Sweden)

Fábio Vergara Cerqueira

2012-09-01

Full Text Available O quarto número dos Cadernos procura trazer estudos concernentes às três temáticas centrais da publicação, Patrimônio, Antropologia e Arqueologia. Composto por seis artigos e uma resenha, a composição autoral deste volume mescla, intencionalmente, autores consagrados em suas áreas de  pesquisa, como os historiadores Sandra Pesavento e Francisco Marshall, com jovens pesquisadores, formados na própria UFPEL, como Rafael Guedes Milheira, Welcsoner Silva da Cunha e Luiz Carlos da Silva Júnior.

If it doesn’t spread it’s dead  : En kvalitativ studie över hur unga entreprenörer positionerar sig på marknaden och med hjälp av sociala medier sprider sitt varumärke

OpenAIRE

Hoffman, Anna; Ahlinder, Sandra

2013-01-01

Abstract Title: If it doesn’t spread it’s dead - a qualitative study on how young entrepreneurs are positioning themselves in the marketplace and with the help of social media spreading their brand. (If it doesn’t spread it’s dead ­- en kvalitativ studie om hur unga entreprenörer positionerar sig på marknaden, med hjälp av sociala medier sprider sitt varumärke).   Number of pages: 48   Author: Sandra Ahlinder, Anna Hoffman   Tutor: Peder Hård af Segerstad Course: Media and Communications Stud...

Long Range Aircraft Trajectory Prediction

OpenAIRE

Magister, Tone

2009-01-01

The subject of the paper is the improvement of the aircraft future trajectory prediction accuracy for long-range airborne separation assurance. The strategic planning of safe aircraft flights and effective conflict avoidance tactics demand timely and accurate conflict detection based upon future four–dimensional airborne traffic situation prediction which is as accurate as each aircraft flight trajectory prediction. The improved kinematics model of aircraft relative flight considering flight ...

Prediction of molecular crystal structures

International Nuclear Information System (INIS)

Beyer, Theresa

2001-01-01

The ab initio prediction of molecular crystal structures is a scientific challenge. Reliability of first-principle prediction calculations would show a fundamental understanding of crystallisation. Crystal structure prediction is also of considerable practical importance as different crystalline arrangements of the same molecule in the solid state (polymorphs)are likely to have different physical properties. A method of crystal structure prediction based on lattice energy minimisation has been developed in this work. The choice of the intermolecular potential and of the molecular model is crucial for the results of such studies and both of these criteria have been investigated. An empirical atom-atom repulsion-dispersion potential for carboxylic acids has been derived and applied in a crystal structure prediction study of formic, benzoic and the polymorphic system of tetrolic acid. As many experimental crystal structure determinations at different temperatures are available for the polymorphic system of paracetamol (acetaminophen), the influence of the variations of the molecular model on the crystal structure lattice energy minima, has also been studied. The general problem of prediction methods based on the assumption that the experimental thermodynamically stable polymorph corresponds to the global lattice energy minimum, is that more hypothetical low lattice energy structures are found within a few kJ mol -1 of the global minimum than are likely to be experimentally observed polymorphs. This is illustrated by the results for molecule I, 3-oxabicyclo(3.2.0)hepta-1,4-diene, studied for the first international blindtest for small organic crystal structures organised by the Cambridge Crystallographic Data Centre (CCDC) in May 1999. To reduce the number of predicted polymorphs, additional factors to thermodynamic criteria have to be considered. Therefore the elastic constants and vapour growth morphologies have been calculated for the lowest lattice energy

Prediction of molecular crystal structures

Energy Technology Data Exchange (ETDEWEB)

Beyer, Theresa

2001-07-01

The ab initio prediction of molecular crystal structures is a scientific challenge. Reliability of first-principle prediction calculations would show a fundamental understanding of crystallisation. Crystal structure prediction is also of considerable practical importance as different crystalline arrangements of the same molecule in the solid state (polymorphs)are likely to have different physical properties. A method of crystal structure prediction based on lattice energy minimisation has been developed in this work. The choice of the intermolecular potential and of the molecular model is crucial for the results of such studies and both of these criteria have been investigated. An empirical atom-atom repulsion-dispersion potential for carboxylic acids has been derived and applied in a crystal structure prediction study of formic, benzoic and the polymorphic system of tetrolic acid. As many experimental crystal structure determinations at different temperatures are available for the polymorphic system of paracetamol (acetaminophen), the influence of the variations of the molecular model on the crystal structure lattice energy minima, has also been studied. The general problem of prediction methods based on the assumption that the experimental thermodynamically stable polymorph corresponds to the global lattice energy minimum, is that more hypothetical low lattice energy structures are found within a few kJ mol{sup -1} of the global minimum than are likely to be experimentally observed polymorphs. This is illustrated by the results for molecule I, 3-oxabicyclo(3.2.0)hepta-1,4-diene, studied for the first international blindtest for small organic crystal structures organised by the Cambridge Crystallographic Data Centre (CCDC) in May 1999. To reduce the number of predicted polymorphs, additional factors to thermodynamic criteria have to be considered. Therefore the elastic constants and vapour growth morphologies have been calculated for the lowest lattice energy

Multi-Objective Predictive Balancing Control of Battery Packs Based on Predictive Current

Directory of Open Access Journals (Sweden)

Wenbiao Li

2016-04-01

Full Text Available Various balancing topology and control methods have been proposed for the inconsistency problem of battery packs. However, these strategies only focus on a single objective, ignore the mutual interaction among various factors and are only based on the external performance of the battery pack inconsistency, such as voltage balancing and state of charge (SOC balancing. To solve these problems, multi-objective predictive balancing control (MOPBC based on predictive current is proposed in this paper, namely, in the driving process of an electric vehicle, using predictive control to predict the battery pack output current the next time. Based on this information, the impact of the battery pack temperature caused by the output current can be obtained. Then, the influence is added to the battery pack balancing control, which makes the present degradation, temperature, and SOC imbalance achieve balance automatically due to the change of the output current the next moment. According to MOPBC, the simulation model of the balancing circuit is built with four cells in Matlab/Simulink. The simulation results show that MOPBC is not only better than the other traditional balancing control strategies but also reduces the energy loss in the balancing process.

Genomic Prediction of Barley Hybrid Performance

Directory of Open Access Journals (Sweden)

Norman Philipp

2016-07-01

Full Text Available Hybrid breeding in barley ( L. offers great opportunities to accelerate the rate of genetic improvement and to boost yield stability. A crucial requirement consists of the efficient selection of superior hybrid combinations. We used comprehensive phenotypic and genomic data from a commercial breeding program with the goal of examining the potential to predict the hybrid performances. The phenotypic data were comprised of replicated grain yield trials for 385 two-way and 408 three-way hybrids evaluated in up to 47 environments. The parental lines were genotyped using a 3k single nucleotide polymorphism (SNP array based on an Illumina Infinium assay. We implemented ridge regression best linear unbiased prediction modeling for additive and dominance effects and evaluated the prediction ability using five-fold cross validations. The prediction ability of hybrid performances based on general combining ability (GCA effects was moderate, amounting to 0.56 and 0.48 for two- and three-way hybrids, respectively. The potential of GCA-based hybrid prediction requires that both parental components have been evaluated in a hybrid background. This is not necessary for genomic prediction for which we also observed moderate cross-validated prediction abilities of 0.51 and 0.58 for two- and three-way hybrids, respectively. This exemplifies the potential of genomic prediction in hybrid barley. Interestingly, prediction ability using the two-way hybrids as training population and the three-way hybrids as test population or vice versa was low, presumably, because of the different genetic makeup of the parental source populations. Consequently, further research is needed to optimize genomic prediction approaches combining different source populations in barley.

Decadel climate prediction: challenges and opportunities

International Nuclear Information System (INIS)

Hurrell, J W

2008-01-01

The scientific understanding of climate change is now sufficiently clear to show that climate change from global warming is already upon us, and the rate of change as projected exceeds anything seen in nature in the past 10,000 years. Uncertainties remain, however, especially regarding how climate will change at regional and local scales where the signal of natural variability is large. Addressing many of these uncertainties will require a movement toward high resolution climate system predictions, with a blurring of the distinction between shorter-term predictions and longer-term climate projections. The key is the realization that climate system predictions, regardless of timescale, will require initialization of coupled general circulation models with best estimates of the current observed state of the atmosphere, oceans, cryosphere, and land surface. Formidable challenges exist: for instance, what is the best method of initialization given imperfect observations and systematic errors in models? What effect does initialization have on climate predictions? What predictions should be attempted, and how would they be verified? Despite such challenges, the unrealized predictability that resides in slowly evolving phenomena, such as ocean current systems, is of paramount importance for society to plan and adapt for the next few decades. Moreover, initialized climate predictions will require stronger collaboration with shared knowledge, infrastructure and technical capabilities among those in the weather and climate prediction communities. The potential benefits include improved understanding and predictions on all time scales

A highly accurate predictive-adaptive method for lithium-ion battery remaining discharge energy prediction in electric vehicle applications

International Nuclear Information System (INIS)

Liu, Guangming; Ouyang, Minggao; Lu, Languang; Li, Jianqiu; Hua, Jianfeng

2015-01-01

Highlights: • An energy prediction (EP) method is introduced for battery E RDE determination. • EP determines E RDE through coupled prediction of future states, parameters, and output. • The PAEP combines parameter adaptation and prediction to update model parameters. • The PAEP provides improved E RDE accuracy compared with DC and other EP methods. - Abstract: In order to estimate the remaining driving range (RDR) in electric vehicles, the remaining discharge energy (E RDE ) of the applied battery system needs to be precisely predicted. Strongly affected by the load profiles, the available E RDE varies largely in real-world applications and requires specific determination. However, the commonly-used direct calculation (DC) method might result in certain energy prediction errors by relating the E RDE directly to the current state of charge (SOC). To enhance the E RDE accuracy, this paper presents a battery energy prediction (EP) method based on the predictive control theory, in which a coupled prediction of future battery state variation, battery model parameter change, and voltage response, is implemented on the E RDE prediction horizon, and the E RDE is subsequently accumulated and real-timely optimized. Three EP approaches with different model parameter updating routes are introduced, and the predictive-adaptive energy prediction (PAEP) method combining the real-time parameter identification and the future parameter prediction offers the best potential. Based on a large-format lithium-ion battery, the performance of different E RDE calculation methods is compared under various dynamic profiles. Results imply that the EP methods provide much better accuracy than the traditional DC method, and the PAEP could reduce the E RDE error by more than 90% and guarantee the relative energy prediction error under 2%, proving as a proper choice in online E RDE prediction. The correlation of SOC estimation and E RDE calculation is then discussed to illustrate the

Spatial Economics Model Predicting Transport Volume

Directory of Open Access Journals (Sweden)

Lu Bo

2016-10-01

Full Text Available It is extremely important to predict the logistics requirements in a scientific and rational way. However, in recent years, the improvement effect on the prediction method is not very significant and the traditional statistical prediction method has the defects of low precision and poor interpretation of the prediction model, which cannot only guarantee the generalization ability of the prediction model theoretically, but also cannot explain the models effectively. Therefore, in combination with the theories of the spatial economics, industrial economics, and neo-classical economics, taking city of Zhuanghe as the research object, the study identifies the leading industry that can produce a large number of cargoes, and further predicts the static logistics generation of the Zhuanghe and hinterlands. By integrating various factors that can affect the regional logistics requirements, this study established a logistics requirements potential model from the aspect of spatial economic principles, and expanded the way of logistics requirements prediction from the single statistical principles to an new area of special and regional economics.

Prediction-based dynamic load-sharing heuristics

Science.gov (United States)

Goswami, Kumar K.; Devarakonda, Murthy; Iyer, Ravishankar K.

1993-01-01

The authors present dynamic load-sharing heuristics that use predicted resource requirements of processes to manage workloads in a distributed system. A previously developed statistical pattern-recognition method is employed for resource prediction. While nonprediction-based heuristics depend on a rapidly changing system status, the new heuristics depend on slowly changing program resource usage patterns. Furthermore, prediction-based heuristics can be more effective since they use future requirements rather than just the current system state. Four prediction-based heuristics, two centralized and two distributed, are presented. Using trace driven simulations, they are compared against random scheduling and two effective nonprediction based heuristics. Results show that the prediction-based centralized heuristics achieve up to 30 percent better response times than the nonprediction centralized heuristic, and that the prediction-based distributed heuristics achieve up to 50 percent improvements relative to their nonprediction counterpart.

Sports Tournament Predictions Using Direct Manipulation.

Science.gov (United States)

Vuillemot, Romain; Perin, Charles

2016-01-01

An advanced interface for sports tournament predictions uses direct manipulation to allow users to make nonlinear predictions. Unlike previous interface designs, the interface helps users focus on their prediction tasks by enabling them to first choose a winner and then fill out the rest of the bracket. In real-world tests of the proposed interface (for the 2014 FIFA World Cup tournament and 2015/2016 UEFA Champions League), the authors validated the use of direct manipulation as an alternative to widgets. Using visitor interaction logs, they were able to determine the strategies people use to perform predictions and identify potential areas of improvement for further prediction interfaces.

Collaboratory for the Study of Earthquake Predictability

Science.gov (United States)

Schorlemmer, D.; Jordan, T. H.; Zechar, J. D.; Gerstenberger, M. C.; Wiemer, S.; Maechling, P. J.

2006-12-01

Earthquake prediction is one of the most difficult problems in physical science and, owing to its societal implications, one of the most controversial. The study of earthquake predictability has been impeded by the lack of an adequate experimental infrastructure---the capability to conduct scientific prediction experiments under rigorous, controlled conditions and evaluate them using accepted criteria specified in advance. To remedy this deficiency, the Southern California Earthquake Center (SCEC) is working with its international partners, which include the European Union (through the Swiss Seismological Service) and New Zealand (through GNS Science), to develop a virtual, distributed laboratory with a cyberinfrastructure adequate to support a global program of research on earthquake predictability. This Collaboratory for the Study of Earthquake Predictability (CSEP) will extend the testing activities of SCEC's Working Group on Regional Earthquake Likelihood Models, from which we will present first results. CSEP will support rigorous procedures for registering prediction experiments on regional and global scales, community-endorsed standards for assessing probability-based and alarm-based predictions, access to authorized data sets and monitoring products from designated natural laboratories, and software to allow researchers to participate in prediction experiments. CSEP will encourage research on earthquake predictability by supporting an environment for scientific prediction experiments that allows the predictive skill of proposed algorithms to be rigorously compared with standardized reference methods and data sets. It will thereby reduce the controversies surrounding earthquake prediction, and it will allow the results of prediction experiments to be communicated to the scientific community, governmental agencies, and the general public in an appropriate research context.

Predictive Analytics in Information Systems Research

NARCIS (Netherlands)

G. Shmueli (Galit); O.R. Koppius (Otto)

2011-01-01

textabstractThis research essay highlights the need to integrate predictive analytics into information systems research and shows several concrete ways in which this goal can be accomplished. Predictive analytics include empirical methods (statistical and other) that generate data predictions as

Bitter or not? BitterPredict, a tool for predicting taste from chemical structure.

Science.gov (United States)

Dagan-Wiener, Ayana; Nissim, Ido; Ben Abu, Natalie; Borgonovo, Gigliola; Bassoli, Angela; Niv, Masha Y

2017-09-21

Bitter taste is an innately aversive taste modality that is considered to protect animals from consuming toxic compounds. Yet, bitterness is not always noxious and some bitter compounds have beneficial effects on health. Hundreds of bitter compounds were reported (and are accessible via the BitterDB http://bitterdb.agri.huji.ac.il/dbbitter.php ), but numerous additional bitter molecules are still unknown. The dramatic chemical diversity of bitterants makes bitterness prediction a difficult task. Here we present a machine learning classifier, BitterPredict, which predicts whether a compound is bitter or not, based on its chemical structure. BitterDB was used as the positive set, and non-bitter molecules were gathered from literature to create the negative set. Adaptive Boosting (AdaBoost), based on decision trees machine-learning algorithm was applied to molecules that were represented using physicochemical and ADME/Tox descriptors. BitterPredict correctly classifies over 80% of the compounds in the hold-out test set, and 70-90% of the compounds in three independent external sets and in sensory test validation, providing a quick and reliable tool for classifying large sets of compounds into bitter and non-bitter groups. BitterPredict suggests that about 40% of random molecules, and a large portion (66%) of clinical and experimental drugs, and of natural products (77%) are bitter.

Evaluating predictions of critical oxygen desaturation events

International Nuclear Information System (INIS)

ElMoaqet, Hisham; Tilbury, Dawn M; Ramachandran, Satya Krishna

2014-01-01

This paper presents a new approach for evaluating predictions of oxygen saturation levels in blood ( SpO 2 ). A performance metric based on a threshold is proposed to evaluate  SpO 2 predictions based on whether or not they are able to capture critical desaturations in the  SpO 2 time series of patients. We use linear auto-regressive models built using historical  SpO 2 data to predict critical desaturation events with the proposed metric. In 20 s prediction intervals, 88%–94% of the critical events were captured with positive predictive values (PPVs) between 90% and 99%. Increasing the prediction horizon to 60 s, 46%–71% of the critical events were detected with PPVs between 81% and 97%. In both prediction horizons, more than 97% of the non-critical events were correctly classified. The overall classification capabilities for the developed predictive models were also investigated. The area under ROC curves for 60 s predictions from the developed models are between 0.86 and 0.98. Furthermore, we investigate the effect of including pulse rate (PR) dynamics in the models and predictions. We show no improvement in the percentage of the predicted critical desaturations if PR dynamics are incorporated into the  SpO 2 predictive models (p-value = 0.814). We also show that including the PR dynamics does not improve the earliest time at which critical  SpO 2 levels are predicted (p-value = 0.986). Our results indicate oxygen in blood is an effective input to the PR rather than vice versa. We demonstrate that the combination of predictive models with frequent pulse oximetry measurements can be used as a warning of critical oxygen desaturations that may have adverse effects on the health of patients. (paper)

Neural Elements for Predictive Coding

Directory of Open Access Journals (Sweden)

Stewart SHIPP

2016-11-01

Full Text Available Predictive coding theories of sensory brain function interpret the hierarchical construction of the cerebral cortex as a Bayesian, generative model capable of predicting the sensory data consistent with any given percept. Predictions are fed backwards in the hierarchy and reciprocated by prediction error in the forward direction, acting to modify the representation of the outside world at increasing levels of abstraction, and so to optimize the nature of perception over a series of iterations. This accounts for many ‘illusory’ instances of perception where what is seen (heard, etc is unduly influenced by what is expected, based on past experience. This simple conception, the hierarchical exchange of prediction and prediction error, confronts a rich cortical microcircuitry that is yet to be fully documented. This article presents the view that, in the current state of theory and practice, it is profitable to begin a two-way exchange: that predictive coding theory can support an understanding of cortical microcircuit function, and prompt particular aspects of future investigation, whilst existing knowledge of microcircuitry can, in return, influence theoretical development. As an example, a neural inference arising from the earliest formulations of predictive coding is that the source populations of forwards and backwards pathways should be completely separate, given their functional distinction; this aspect of circuitry – that neurons with extrinsically bifurcating axons do not project in both directions – has only recently been confirmed. Here, the computational architecture prescribed by a generalized (free-energy formulation of predictive coding is combined with the classic ‘canonical microcircuit’ and the laminar architecture of hierarchical extrinsic connectivity to produce a template schematic, that is further examined in the light of (a updates in the microcircuitry of primate visual cortex, and (b rapid technical advances made

Neural Elements for Predictive Coding.

Science.gov (United States)

Shipp, Stewart

2016-01-01

Predictive coding theories of sensory brain function interpret the hierarchical construction of the cerebral cortex as a Bayesian, generative model capable of predicting the sensory data consistent with any given percept. Predictions are fed backward in the hierarchy and reciprocated by prediction error in the forward direction, acting to modify the representation of the outside world at increasing levels of abstraction, and so to optimize the nature of perception over a series of iterations. This accounts for many 'illusory' instances of perception where what is seen (heard, etc.) is unduly influenced by what is expected, based on past experience. This simple conception, the hierarchical exchange of prediction and prediction error, confronts a rich cortical microcircuitry that is yet to be fully documented. This article presents the view that, in the current state of theory and practice, it is profitable to begin a two-way exchange: that predictive coding theory can support an understanding of cortical microcircuit function, and prompt particular aspects of future investigation, whilst existing knowledge of microcircuitry can, in return, influence theoretical development. As an example, a neural inference arising from the earliest formulations of predictive coding is that the source populations of forward and backward pathways should be completely separate, given their functional distinction; this aspect of circuitry - that neurons with extrinsically bifurcating axons do not project in both directions - has only recently been confirmed. Here, the computational architecture prescribed by a generalized (free-energy) formulation of predictive coding is combined with the classic 'canonical microcircuit' and the laminar architecture of hierarchical extrinsic connectivity to produce a template schematic, that is further examined in the light of (a) updates in the microcircuitry of primate visual cortex, and (b) rapid technical advances made possible by transgenic neural

Predicting Anthracycline Benefit

DEFF Research Database (Denmark)

Bartlett, John M S; McConkey, Christopher C; Munro, Alison F

2015-01-01

PURPOSE: Evidence supporting the clinical utility of predictive biomarkers of anthracycline activity is weak, with a recent meta-analysis failing to provide strong evidence for either HER2 or TOP2A. Having previously shown that duplication of chromosome 17 pericentromeric alpha satellite as measu......PURPOSE: Evidence supporting the clinical utility of predictive biomarkers of anthracycline activity is weak, with a recent meta-analysis failing to provide strong evidence for either HER2 or TOP2A. Having previously shown that duplication of chromosome 17 pericentromeric alpha satellite...

Linguistic Structure Prediction

CERN Document Server

Smith, Noah A

2011-01-01

A major part of natural language processing now depends on the use of text data to build linguistic analyzers. We consider statistical, computational approaches to modeling linguistic structure. We seek to unify across many approaches and many kinds of linguistic structures. Assuming a basic understanding of natural language processing and/or machine learning, we seek to bridge the gap between the two fields. Approaches to decoding (i.e., carrying out linguistic structure prediction) and supervised and unsupervised learning of models that predict discrete structures as outputs are the focus. W

Unification predictions

International Nuclear Information System (INIS)

Ghilencea, D.; Ross, G.G.; Lanzagorta, M.

1997-07-01

The unification of gauge couplings suggests that there is an underlying (supersymmetric) unification of the strong, electromagnetic and weak interactions. The prediction of the unification scale may be the first quantitative indication that this unification may extend to unification with gravity. We make a precise determination of these predictions for a class of models which extend the multiplet structure of the Minimal Supersymmetric Standard Model to include the heavy states expected in many Grand Unified and/or superstring theories. We show that there is a strong cancellation between the 2-loop and threshold effects. As a result the net effect is smaller than previously thought, giving a small increase in both the unification scale and the value of the strong coupling at low energies. (author). 15 refs, 5 figs

Predicting community composition from pairwise interactions

Science.gov (United States)

Friedman, Jonathan; Higgins, Logan; Gore, Jeff

The ability to predict the structure of complex, multispecies communities is crucial for understanding the impact of species extinction and invasion on natural communities, as well as for engineering novel, synthetic communities. Communities are often modeled using phenomenological models, such as the classical generalized Lotka-Volterra (gLV) model. While a lot of our intuition comes from such models, their predictive power has rarely been tested experimentally. To directly assess the predictive power of this approach, we constructed synthetic communities comprised of up to 8 soil bacteria. We measured the outcome of competition between all species pairs, and used these measurements to predict the composition of communities composed of more than 2 species. The pairwise competitions resulted in a diverse set of outcomes, including coexistence, exclusion, and bistability, and displayed evidence for both interference and facilitation. Most pair outcomes could be captured by the gLV framework, and the composition of multispecies communities could be predicted for communities composed solely of such pairs. Our results demonstrate the predictive ability and utility of simple phenomenology, which enables accurate predictions in the absence of mechanistic details.

Prediction of GNSS satellite clocks

International Nuclear Information System (INIS)

Broederbauer, V.

2010-01-01

This thesis deals with the characterisation and prediction of GNSS-satellite-clocks. A prerequisite to develop powerful algorithms for the prediction of clock-corrections is the thorough study of the behaviour of the different clock-types of the satellites. In this context the predicted part of the IGU-clock-corrections provided by the Analysis Centers (ACs) of the IGS was compared to the IGS-Rapid-clock solutions to determine reasonable estimates of the quality of already existing well performing predictions. For the shortest investigated interval (three hours) all ACs obtain almost the same accuracy of 0,1 to 0,4 ns. For longer intervals the individual predictions results start to diverge. Thus, for a 12-hours- interval the differences range from nearly 10 ns (GFZ, CODE) until up to some 'tens of ns'. Based on the estimated clock corrections provided via the IGS Rapid products a simple quadratic polynomial turns out to be sufficient to describe the time series of Rubidium-clocks. On the other hand Cesium-clocks show a periodical behaviour (revolution period) with an amplitude of up to 6 ns. A clear correlation between these amplitudes and the Sun elevation angle above the orbital planes can be demonstrated. The variability of the amplitudes is supposed to be caused by temperature-variations affecting the oscillator. To account for this periodical behaviour a quadratic polynomial with an additional sinus-term was finally chosen as prediction model both for the Cesium as well as for the Rubidium clocks. The three polynomial-parameters as well as amplitude and phase shift of the periodic term are estimated within a least-square-adjustment by means of program GNSS-VC/static. Input-data are time series of the observed part of the IGU clock corrections. With the estimated parameters clock-corrections are predicted for various durations. The mean error of the prediction of Rubidium-clock-corrections for an interval of six hours reaches up to 1,5 ns. For the 12-hours

Comparison of Prediction-Error-Modelling Criteria

DEFF Research Database (Denmark)

Jørgensen, John Bagterp; Jørgensen, Sten Bay

2007-01-01

Single and multi-step prediction-error-methods based on the maximum likelihood and least squares criteria are compared. The prediction-error methods studied are based on predictions using the Kalman filter and Kalman predictors for a linear discrete-time stochastic state space model, which is a r...

Semen analysis and prediction of natural conception

NARCIS (Netherlands)

Leushuis, Esther; van der Steeg, Jan Willem; Steures, Pieternel; Repping, Sjoerd; Bossuyt, Patrick M. M.; Mol, Ben Willem J.; Hompes, Peter G. A.; van der Veen, Fulco

2014-01-01

Do two semen analyses predict natural conception better than a single semen analysis and will adding the results of repeated semen analyses to a prediction model for natural pregnancy improve predictions? A second semen analysis does not add helpful information for predicting natural conception

Evaluating the Predictive Value of Growth Prediction Models

Science.gov (United States)

Murphy, Daniel L.; Gaertner, Matthew N.

2014-01-01

This study evaluates four growth prediction models--projection, student growth percentile, trajectory, and transition table--commonly used to forecast (and give schools credit for) middle school students' future proficiency. Analyses focused on vertically scaled summative mathematics assessments, and two performance standards conditions (high…

Comprehensive update of the atomic mass predictions

International Nuclear Information System (INIS)

Haustein, P.E.

1987-01-01

A project has been completed recently for a comprehensive update of atomic mass predictions. This last occurred in 1976. Over the last 10 years the reliability of these earlier predictions (and others published later) has been analyzed by comparisons of the predictions with new masses from isotopes that were not in the experimental data base when the predictions were prepared. This analysis has highlighted distinct systematic features in various models which frequently result in poor predictions for nuclei that lie far from stability. An overview of the new predictions from models with different theoretical approaches will be presented

Efficient predictive algorithms for image compression

CERN Document Server

Rosário Lucas, Luís Filipe; Maciel de Faria, Sérgio Manuel; Morais Rodrigues, Nuno Miguel; Liberal Pagliari, Carla

2017-01-01

This book discusses efficient prediction techniques for the current state-of-the-art High Efficiency Video Coding (HEVC) standard, focusing on the compression of a wide range of video signals, such as 3D video, Light Fields and natural images. The authors begin with a review of the state-of-the-art predictive coding methods and compression technologies for both 2D and 3D multimedia contents, which provides a good starting point for new researchers in the field of image and video compression. New prediction techniques that go beyond the standardized compression technologies are then presented and discussed. In the context of 3D video, the authors describe a new predictive algorithm for the compression of depth maps, which combines intra-directional prediction, with flexible block partitioning and linear residue fitting. New approaches are described for the compression of Light Field and still images, which enforce sparsity constraints on linear models. The Locally Linear Embedding-based prediction method is in...

Prediction of Protein Configurational Entropy (Popcoen).

Science.gov (United States)

Goethe, Martin; Gleixner, Jan; Fita, Ignacio; Rubi, J Miguel

2018-03-13

A knowledge-based method for configurational entropy prediction of proteins is presented; this methodology is extremely fast, compared to previous approaches, because it does not involve any type of configurational sampling. Instead, the configurational entropy of a query fold is estimated by evaluating an artificial neural network, which was trained on molecular-dynamics simulations of ∼1000 proteins. The predicted entropy can be incorporated into a large class of protein software based on cost-function minimization/evaluation, in which configurational entropy is currently neglected for performance reasons. Software of this type is used for all major protein tasks such as structure predictions, proteins design, NMR and X-ray refinement, docking, and mutation effect predictions. Integrating the predicted entropy can yield a significant accuracy increase as we show exemplarily for native-state identification with the prominent protein software FoldX. The method has been termed Popcoen for Prediction of Protein Configurational Entropy. An implementation is freely available at http://fmc.ub.edu/popcoen/ .

Host specificity and growth of kelp gametophytes symbiotic with filamentous red algae (Ceramiales, Rhodophyta)

Science.gov (United States)

Hubbard, Charlene B.; Garbary, David J.; Kim, Kwang Young; Chiasson, David M.

2004-02-01

Kelp gametophytes were previously observed in nature living endophytically in red algal cell walls. Here we examine the interactions of two kelp species and six red algae in culture. Gametophytes of Nereocystis luetkeana (Mertens) Postels et Ruprecht became endophytic in the cell walls of Griffithsia pacifica Kylin and Antithamnion defectum Kylin, and grew epiphytically in high abundance on G. japonica Okamura and Aglaothamnion oosumiense Itono. Alaria esculenta (Linnaeus) Greville from the Atlantic coast of Nova Scotia became endophytic in Aglaothamnion oosumiense, Antithamnion defectum, Callithamnion sp., G. japonica, G. pacifica, and Pleonosporium abysicola Gardner, all from the Pacific Ocean. Some cultures were treated with phloroglucinol before infection to thicken the cell walls. The endophytic gametophytes were smaller and grew more slowly than gametophytes epiphytic on the same host. N. luetkeana failed to become endophytic in some of the potential hosts, and this may reflect host specificity, or culture artifacts. This work improves our understanding of the process of infection of red algae by kelp gametophytes, and broadens our knowledge of host specificity in endophytic symbioses.

Acetabular reconstruction with human and bovine freeze-dried bone grafts and a reinforcement device

Directory of Open Access Journals (Sweden)

Ricardo Rosito

2008-01-01

Full Text Available BACKGROUND: This is a cohort trial (1997-2005 of 49 patients submitted to an acetabular component revision of a total hip arthroplasty, using impacted human and bovine freeze-dried cancellous bone grafts (H&FDBG and a reinforcement device. OBJECTIVE: To compare clinical/radiographic graft incorporation capability between cancellous bone grafts. PATIENTS/METHODS: There were two groups: I (n=26 receiving human grafts and II (n=25 receiving bovine grafts. The average follow-up times were 55 and 49 months, respectively. Clinical analysis was based on the Merle d'Aubigné and Postel score, and the radiographic analysis involved an established score based on Conn's et al. criteria for radiographic bone incorporation. RESULTS: No clinical/radiographic differences were found between the groups and both showed an overall rate of 88.5% and 76% of graft incorporation (p=0.424. CONCLUSION: The results presented here are comparable to those in the literature with the use of deep-FG. Therefore, cancellous bone grafts can be safely and adequately used in acetabular component revision in total hip arthroplasty.

House Price Prediction Using LSTM

OpenAIRE

Chen, Xiaochen; Wei, Lai; Xu, Jiaxin

2017-01-01

In this paper, we use the house price data ranging from January 2004 to October 2016 to predict the average house price of November and December in 2016 for each district in Beijing, Shanghai, Guangzhou and Shenzhen. We apply Autoregressive Integrated Moving Average model to generate the baseline while LSTM networks to build prediction model. These algorithms are compared in terms of Mean Squared Error. The result shows that the LSTM model has excellent properties with respect to predict time...

Predictability of Stock Returns

Directory of Open Access Journals (Sweden)

Ahmet Sekreter

2017-06-01

Full Text Available Predictability of stock returns has been shown by empirical studies over time. This article collects the most important theories on forecasting stock returns and investigates the factors that affecting behavior of the stocks’ prices and the market as a whole. Estimation of the factors and the way of estimation are the key issues of predictability of stock returns.

Prediction of beta-turns at over 80% accuracy based on an ensemble of predicted secondary structures and multiple alignments.

Science.gov (United States)

Zheng, Ce; Kurgan, Lukasz

2008-10-10

beta-turn is a secondary protein structure type that plays significant role in protein folding, stability, and molecular recognition. To date, several methods for prediction of beta-turns from protein sequences were developed, but they are characterized by relatively poor prediction quality. The novelty of the proposed sequence-based beta-turn predictor stems from the usage of a window based information extracted from four predicted three-state secondary structures, which together with a selected set of position specific scoring matrix (PSSM) values serve as an input to the support vector machine (SVM) predictor. We show that (1) all four predicted secondary structures are useful; (2) the most useful information extracted from the predicted secondary structure includes the structure of the predicted residue, secondary structure content in a window around the predicted residue, and features that indicate whether the predicted residue is inside a secondary structure segment; (3) the PSSM values of Asn, Asp, Gly, Ile, Leu, Met, Pro, and Val were among the top ranked features, which corroborates with recent studies. The Asn, Asp, Gly, and Pro indicate potential beta-turns, while the remaining four amino acids are useful to predict non-beta-turns. Empirical evaluation using three nonredundant datasets shows favorable Q total, Q predicted and MCC values when compared with over a dozen of modern competing methods. Our method is the first to break the 80% Q total barrier and achieves Q total = 80.9%, MCC = 0.47, and Q predicted higher by over 6% when compared with the second best method. We use feature selection to reduce the dimensionality of the feature vector used as the input for the proposed prediction method. The applied feature set is smaller by 86, 62 and 37% when compared with the second and two third-best (with respect to MCC) competing methods, respectively. Experiments show that the proposed method constitutes an improvement over the competing prediction

Predictive coding in Agency Detection

DEFF Research Database (Denmark)

Andersen, Marc Malmdorf

2017-01-01

Agency detection is a central concept in the cognitive science of religion (CSR). Experimental studies, however, have so far failed to lend support to some of the most common predictions that follow from current theories on agency detection. In this article, I argue that predictive coding, a highly...... promising new framework for understanding perception and action, may solve pending theoretical inconsistencies in agency detection research, account for the puzzling experimental findings mentioned above, and provide hypotheses for future experimental testing. Predictive coding explains how the brain......, unbeknownst to consciousness, engages in sophisticated Bayesian statistics in an effort to constantly predict the hidden causes of sensory input. My fundamental argument is that most false positives in agency detection can be seen as the result of top-down interference in a Bayesian system generating high...

Predictions of High Energy Experimental Results

Directory of Open Access Journals (Sweden)

Comay E.

2010-10-01

Full Text Available Eight predictions of high energy experimental results are presented. The predictions contain the $Sigma ^+$ charge radius and results of two kinds of experiments using energetic pionic beams. In addition, predictions of the failure to find the following objects are presented: glueballs, pentaquarks, Strange Quark Matter, magnetic monopoles searched by their direct interaction with charges and the Higgs boson. The first seven predictions rely on the Regular Charge-Monopole Theory and the last one relies on mathematical inconsistencies of the Higgs Lagrangian density.

Predicting Consumer Effort in Finding and Paying for Health Care: Expert Interviews and Claims Data Analysis.

Science.gov (United States)

Long, Sandra; Monsen, Karen A; Pieczkiewicz, David; Wolfson, Julian; Khairat, Saif

2017-10-12

For consumers to accept and use a health care information system, it must be easy to use, and the consumer must perceive it as being free from effort. Finding health care providers and paying for care are tasks that must be done to access treatment. These tasks require effort on the part of the consumer and can be frustrating when the goal of the consumer is primarily to receive treatments for better health. The aim of this study was to determine the factors that result in consumer effort when finding accessible health care. Having an understanding of these factors will help define requirements when designing health information systems. A panel of 12 subject matter experts was consulted and the data from 60 million medical claims were used to determine the factors contributing to effort. Approximately 60 million claims were processed by the health care insurance organization in a 12-month duration with the population defined. Over 292 million diagnoses from claims were used to validate the panel input. The results of the study showed that the number of people in the consumer's household, number of visits to providers outside the consumer's insurance network, number of adjusted and denied medical claims, and number of consumer inquiries are a proxy for the level of effort in finding and paying for care. The effort level, so measured and weighted per expert panel recommendations, differed by diagnosis. This study provides an understanding of how consumers must put forth effort when engaging with a health care system to access care. For higher satisfaction and acceptance results, health care payers ideally will design and develop systems that facilitate an understanding of how to avoid denied claims, educate on the payment of claims to avoid adjustments, and quickly find providers of affordable care. ©Sandra Long, Karen A. Monsen, David Pieczkiewicz, Julian Wolfson, Saif Khairat. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 12.10.2017.

Adaptive filtering prediction and control

CERN Document Server

Goodwin, Graham C

2009-01-01

Preface1. Introduction to Adaptive TechniquesPart 1. Deterministic Systems2. Models for Deterministic Dynamical Systems3. Parameter Estimation for Deterministic Systems4. Deterministic Adaptive Prediction5. Control of Linear Deterministic Systems6. Adaptive Control of Linear Deterministic SystemsPart 2. Stochastic Systems7. Optimal Filtering and Prediction8. Parameter Estimation for Stochastic Dynamic Systems9. Adaptive Filtering and Prediction10. Control of Stochastic Systems11. Adaptive Control of Stochastic SystemsAppendicesA. A Brief Review of Some Results from Systems TheoryB. A Summary o

Prediction Models for Dynamic Demand Response

Energy Technology Data Exchange (ETDEWEB)

Aman, Saima; Frincu, Marc; Chelmis, Charalampos; Noor, Muhammad; Simmhan, Yogesh; Prasanna, Viktor K.

2015-11-02

As Smart Grids move closer to dynamic curtailment programs, Demand Response (DR) events will become necessary not only on fixed time intervals and weekdays predetermined by static policies, but also during changing decision periods and weekends to react to real-time demand signals. Unique challenges arise in this context vis-a-vis demand prediction and curtailment estimation and the transformation of such tasks into an automated, efficient dynamic demand response (D²R) process. While existing work has concentrated on increasing the accuracy of prediction models for DR, there is a lack of studies for prediction models for D²R, which we address in this paper. Our first contribution is the formal definition of D²R, and the description of its challenges and requirements. Our second contribution is a feasibility analysis of very-short-term prediction of electricity consumption for D²R over a diverse, large-scale dataset that includes both small residential customers and large buildings. Our third, and major contribution is a set of insights into the predictability of electricity consumption in the context of D²R. Specifically, we focus on prediction models that can operate at a very small data granularity (here 15-min intervals), for both weekdays and weekends - all conditions that characterize scenarios for D²R. We find that short-term time series and simple averaging models used by Independent Service Operators and utilities achieve superior prediction accuracy. We also observe that workdays are more predictable than weekends and holiday. Also, smaller customers have large variation in consumption and are less predictable than larger buildings. Key implications of our findings are that better models are required for small customers and for non-workdays, both of which are critical for D²R. Also, prediction models require just few days’ worth of data indicating that small amounts of

Seasonal climate prediction for North Eurasia

International Nuclear Information System (INIS)

Kryjov, Vladimir N

2012-01-01

An overview of the current status of the operational seasonal climate prediction for North Eurasia is presented. It is shown that the performance of existing climate models is rather poor in seasonal prediction for North Eurasia. Multi-model ensemble forecasts are more reliable than single-model ones; however, for North Eurasia they tend to be close to climatological ones. Application of downscaling methods may improve predictions for some locations (or regions). However, general improvement of the reliability of seasonal forecasts for North Eurasia requires improvement of the climate prediction models. (letter)

Entropy and the Predictability of Online Life

Directory of Open Access Journals (Sweden)

Roberta Sinatra

2014-01-01

Full Text Available Using mobile phone records and information theory measures, our daily lives have been recently shown to follow strict statistical regularities, and our movement patterns are, to a large extent, predictable. Here, we apply entropy and predictability measures to two datasets of the behavioral actions and the mobility of a large number of players in the virtual universe of a massive multiplayer online game. We find that movements in virtual human lives follow the same high levels of predictability as offline mobility, where future movements can, to some extent, be predicted well if the temporal correlations of visited places are accounted for. Time series of behavioral actions show similar high levels of predictability, even when temporal correlations are neglected. Entropy conditional on specific behavioral actions reveals that in terms of predictability, negative behavior has a wider variety than positive actions. The actions that contain the information to best predict an individual’s subsequent action are negative, such as attacks or enemy markings, while the positive actions of friendship marking, trade and communication contain the least amount of predictive information. These observations show that predicting behavioral actions requires less information than predicting the mobility patterns of humans for which the additional knowledge of past visited locations is crucial and that the type and sign of a social relation has an essential impact on the ability to determine future behavior.

Phenology prediction component of GypsES

Science.gov (United States)

Jesse A. Logan; Lukas P. Schaub; F. William Ravlin

1991-01-01

Prediction of phenology is an important component of most pest management programs, and considerable research effort has been expended toward development of predictive tools for gypsy moth phenology. Although phenological prediction is potentially valuable for timing of spray applications (e.g. Bt, or Gypcheck) and other management activities (e.g. placement and...

A Game Theoretic Approach to Cyber Attack Prediction

Energy Technology Data Exchange (ETDEWEB)

Peng Liu

2005-11-28

The area investigated by this project is cyber attack prediction. With a focus on correlation-based prediction, current attack prediction methodologies overlook the strategic nature of cyber attack-defense scenarios. As a result, current cyber attack prediction methodologies are very limited in predicting strategic behaviors of attackers in enforcing nontrivial cyber attacks such as DDoS attacks, and may result in low accuracy in correlation-based predictions. This project develops a game theoretic framework for cyber attack prediction, where an automatic game-theory-based attack prediction method is proposed. Being able to quantitatively predict the likelihood of (sequences of) attack actions, our attack prediction methodology can predict fine-grained strategic behaviors of attackers and may greatly improve the accuracy of correlation-based prediction. To our best knowledge, this project develops the first comprehensive framework for incentive-based modeling and inference of attack intent, objectives, and strategies; and this project develops the first method that can predict fine-grained strategic behaviors of attackers. The significance of this research and the benefit to the public can be demonstrated to certain extent by (a) the severe threat of cyber attacks to the critical infrastructures of the nation, including many infrastructures overseen by the Department of Energy, (b) the importance of cyber security to critical infrastructure protection, and (c) the importance of cyber attack prediction to achieving cyber security.

Postprocessing for Air Quality Predictions

Science.gov (United States)

Delle Monache, L.

2017-12-01

In recent year, air quality (AQ) forecasting has made significant progress towards better predictions with the goal of protecting the public from harmful pollutants. This progress is the results of improvements in weather and chemical transport models, their coupling, and more accurate emission inventories (e.g., with the development of new algorithms to account in near real-time for fires). Nevertheless, AQ predictions are still affected at times by significant biases which stem from limitations in both weather and chemistry transport models. Those are the result of numerical approximations and the poor representation (and understanding) of important physical and chemical process. Moreover, although the quality of emission inventories has been significantly improved, they are still one of the main sources of uncertainties in AQ predictions. For operational real-time AQ forecasting, a significant portion of these biases can be reduced with the implementation of postprocessing methods. We will review some of the techniques that have been proposed to reduce both systematic and random errors of AQ predictions, and improve the correlation between predictions and observations of ground-level ozone and surface particulate matter less than 2.5 µm in diameter (PM2.5). These methods, which can be applied to both deterministic and probabilistic predictions, include simple bias-correction techniques, corrections inspired by the Kalman filter, regression methods, and the more recently developed analog-based algorithms. These approaches will be compared and contrasted, and strength and weaknesses of each will be discussed.

Lightning prediction using radiosonde data

Energy Technology Data Exchange (ETDEWEB)

Weng, L.Y.; Bin Omar, J.; Siah, Y.K.; Bin Zainal Abidin, I.; Ahmad, S.K. [Univ. Tenaga, Darul Ehsan (Malaysia). College of Engineering

2008-07-01

Lightning is a natural phenomenon in tropical regions. Malaysia experiences very high cloud-to-ground lightning density, posing both health and economic concerns to individuals and industries. In the commercial sector, power lines, telecommunication towers and buildings are most frequently hit by lightning. In the event that a power line is hit and the protection system fails, industries which rely on that power line would cease operations temporarily, resulting in significant monetary loss. Current technology is unable to prevent lightning occurrences. However, the ability to predict lightning would significantly reduce damages from direct and indirect lightning strikes. For that reason, this study focused on developing a method to predict lightning with radiosonde data using only a simple back propagation neural network model written in C code. The study was performed at the Kuala Lumpur International Airport (KLIA). In this model, the parameters related to wind were disregarded. Preliminary results indicate that this method shows some positive results in predicting lighting. However, a larger dataset is needed in order to obtain more accurate predictions. It was concluded that future work should include wind parameters to fully capture all properties for lightning formation, subsequently its prediction. 8 refs., 5 figs.

In silico prediction of genotoxicity.

Science.gov (United States)

Wichard, Jörg D

2017-08-01

The in silico prediction of genotoxicity has made considerable progress during the last years. The main driver for the pharmaceutical industry is the ICH M7 guideline about the assessment of DNA reactive impurities. An important component of this guideline is the use of in silico models as an alternative approach to experimental testing. The in silico prediction of genotoxicity provides an established and accepted method that defines the first step in the assessment of DNA reactive impurities. This was made possible by the growing amount of reliable Ames screening data, the attempts to understand the activity pathways and the subsequent development of computer-based prediction systems. This paper gives an overview of how the in silico prediction of genotoxicity is performed under the ICH M7 guideline. Copyright © 2016 Elsevier Ltd. All rights reserved.

Prediction based on mean subset

DEFF Research Database (Denmark)

Øjelund, Henrik; Brown, P. J.; Madsen, Henrik

2002-01-01

, it is found that the proposed mean subset method has superior prediction performance than prediction based on the best subset method, and in some settings also better than the ridge regression and lasso methods. The conclusions drawn from the Monte Carlo study is corroborated in an example in which prediction......Shrinkage methods have traditionally been applied in prediction problems. In this article we develop a shrinkage method (mean subset) that forms an average of regression coefficients from individual subsets of the explanatory variables. A Bayesian approach is taken to derive an expression of how...... the coefficient vectors from each subset should be weighted. It is not computationally feasible to calculate the mean subset coefficient vector for larger problems, and thus we suggest an algorithm to find an approximation to the mean subset coefficient vector. In a comprehensive Monte Carlo simulation study...

Global skin colour prediction from DNA.

Science.gov (United States)

Walsh, Susan; Chaitanya, Lakshmi; Breslin, Krystal; Muralidharan, Charanya; Bronikowska, Agnieszka; Pospiech, Ewelina; Koller, Julia; Kovatsi, Leda; Wollstein, Andreas; Branicki, Wojciech; Liu, Fan; Kayser, Manfred

2017-07-01

Human skin colour is highly heritable and externally visible with relevance in medical, forensic, and anthropological genetics. Although eye and hair colour can already be predicted with high accuracies from small sets of carefully selected DNA markers, knowledge about the genetic predictability of skin colour is limited. Here, we investigate the skin colour predictive value of 77 single-nucleotide polymorphisms (SNPs) from 37 genetic loci previously associated with human pigmentation using 2025 individuals from 31 global populations. We identified a minimal set of 36 highly informative skin colour predictive SNPs and developed a statistical prediction model capable of skin colour prediction on a global scale. Average cross-validated prediction accuracies expressed as area under the receiver-operating characteristic curve (AUC) ± standard deviation were 0.97 ± 0.02 for Light, 0.83 ± 0.11 for Dark, and 0.96 ± 0.03 for Dark-Black. When using a 5-category, this resulted in 0.74 ± 0.05 for Very Pale, 0.72 ± 0.03 for Pale, 0.73 ± 0.03 for Intermediate, 0.87±0.1 for Dark, and 0.97 ± 0.03 for Dark-Black. A comparative analysis in 194 independent samples from 17 populations demonstrated that our model outperformed a previously proposed 10-SNP-classifier approach with AUCs rising from 0.79 to 0.82 for White, comparable at the intermediate level of 0.63 and 0.62, respectively, and a large increase from 0.64 to 0.92 for Black. Overall, this study demonstrates that the chosen DNA markers and prediction model, particularly the 5-category level; allow skin colour predictions within and between continental regions for the first time, which will serve as a valuable resource for future applications in forensic and anthropologic genetics.

Climate Prediction Center - The ENSO Cycle

Science.gov (United States)

Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Home Site Map News Web resources and services. HOME > El Niño/La Niña > The ENSO Cycle ENSO Cycle Banner Climate for Weather and Climate Prediction Climate Prediction Center 5830 University Research Court College

Sentence-Level Attachment Prediction

Science.gov (United States)

Albakour, M.-Dyaa; Kruschwitz, Udo; Lucas, Simon

Attachment prediction is the task of automatically identifying email messages that should contain an attachment. This can be useful to tackle the problem of sending out emails but forgetting to include the relevant attachment (something that happens all too often). A common Information Retrieval (IR) approach in analyzing documents such as emails is to treat the entire document as a bag of words. Here we propose a finer-grained analysis to address the problem. We aim at identifying individual sentences within an email that refer to an attachment. If we detect any such sentence, we predict that the email should have an attachment. Using part of the Enron corpus for evaluation we find that our finer-grained approach outperforms previously reported document-level attachment prediction in similar evaluation settings.

Essays on Earnings Predictability

DEFF Research Database (Denmark)

Bruun, Mark

This dissertation addresses the prediction of corporate earnings. The thesis aims to examine whether the degree of precision in earnings forecasts can be increased by basing them on historical financial ratios. Furthermore, the intent of the dissertation is to analyze whether accounting standards...... forecasts are not more accurate than the simpler forecasts based on a historical timeseries of earnings. Secondly, the dissertation shows how accounting standards affect analysts’ earnings predictions. Accounting conservatism contributes to a more volatile earnings process, which lowers the accuracy...... of analysts’ earnings forecasts. Furthermore, the dissertation shows how the stock market’s reaction to the disclosure of information about corporate earnings depends on how well corporate earnings can be predicted. The dissertation indicates that the stock market’s reaction to the disclosure of earnings...

Inverse and Predictive Modeling

Energy Technology Data Exchange (ETDEWEB)

Syracuse, Ellen Marie [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2017-09-27

The LANL Seismo-Acoustic team has a strong capability in developing data-driven models that accurately predict a variety of observations. These models range from the simple – one-dimensional models that are constrained by a single dataset and can be used for quick and efficient predictions – to the complex – multidimensional models that are constrained by several types of data and result in more accurate predictions. Team members typically build models of geophysical characteristics of Earth and source distributions at scales of 1 to 1000s of km, the techniques used are applicable for other types of physical characteristics at an even greater range of scales. The following cases provide a snapshot of some of the modeling work done by the Seismo- Acoustic team at LANL.

Trust-based collective view prediction

CERN Document Server

Luo, Tiejian; Xu, Guandong; Zhou, Jia

2013-01-01

Collective view prediction is to judge the opinions of an active web user based on unknown elements by referring to the collective mind of the whole community. Content-based recommendation and collaborative filtering are two mainstream collective view prediction techniques. They generate predictions by analyzing the text features of the target object or the similarity of users' past behaviors. Still, these techniques are vulnerable to the artificially-injected noise data, because they are not able to judge the reliability and credibility of the information sources. Trust-based Collective View

Dividend Predictability Around the World

DEFF Research Database (Denmark)

Rangvid, Jesper; Schrimpf, Andreas

The common perception in the literature, mainly based on U.S. data, is that current dividend yields are uninformative about future dividends. We show that this nding changes substantially when looking at a broad international panel of countries, as aggregate dividend growth rates are found...... that in countries where the quality of institutions is high, dividend predictability is weaker. These ndings indicate that the apparent lack of dividend predictability in the U.S. does not, in general, extend to other countries. Rather, dividend predictability is driven by cross-country dierences in rm...

Short-term wind power prediction

DEFF Research Database (Denmark)

Joensen, Alfred K.

2003-01-01

, and to implement these models and methods in an on-line software application. The economical value of having predictions available is also briefly considered. The summary report outlines the background and motivation for developing wind power prediction models. The meteorological theory which is relevant......The present thesis consists of 10 research papers published during the period 1997-2002 together with a summary report. The objective of the work described in the thesis is to develop models and methods for calculation of high accuracy predictions of wind power generated electricity...

Predictive ability of machine learning methods for massive crop yield prediction

Directory of Open Access Journals (Sweden)

Alberto Gonzalez-Sanchez

2014-04-01

Full Text Available An important issue for agricultural planning purposes is the accurate yield estimation for the numerous crops involved in the planning. Machine learning (ML is an essential approach for achieving practical and effective solutions for this problem. Many comparisons of ML methods for yield prediction have been made, seeking for the most accurate technique. Generally, the number of evaluated crops and techniques is too low and does not provide enough information for agricultural planning purposes. This paper compares the predictive accuracy of ML and linear regression techniques for crop yield prediction in ten crop datasets. Multiple linear regression, M5-Prime regression trees, perceptron multilayer neural networks, support vector regression and k-nearest neighbor methods were ranked. Four accuracy metrics were used to validate the models: the root mean square error (RMS, root relative square error (RRSE, normalized mean absolute error (MAE, and correlation factor (R. Real data of an irrigation zone of Mexico were used for building the models. Models were tested with samples of two consecutive years. The results show that M5-Prime and k-nearest neighbor techniques obtain the lowest average RMSE errors (5.14 and 4.91, the lowest RRSE errors (79.46% and 79.78%, the lowest average MAE errors (18.12% and 19.42%, and the highest average correlation factors (0.41 and 0.42. Since M5-Prime achieves the largest number of crop yield models with the lowest errors, it is a very suitable tool for massive crop yield prediction in agricultural planning.

Psoriasis prediction from genome-wide SNP profiles

Directory of Open Access Journals (Sweden)

Fang Xiangzhong

2011-01-01

Full Text Available Abstract Background With the availability of large-scale genome-wide association study (GWAS data, choosing an optimal set of SNPs for disease susceptibility prediction is a challenging task. This study aimed to use single nucleotide polymorphisms (SNPs to predict psoriasis from searching GWAS data. Methods Totally we had 2,798 samples and 451,724 SNPs. Process for searching a set of SNPs to predict susceptibility for psoriasis consisted of two steps. The first one was to search top 1,000 SNPs with high accuracy for prediction of psoriasis from GWAS dataset. The second one was to search for an optimal SNP subset for predicting psoriasis. The sequential information bottleneck (sIB method was compared with classical linear discriminant analysis(LDA for classification performance. Results The best test harmonic mean of sensitivity and specificity for predicting psoriasis by sIB was 0.674(95% CI: 0.650-0.698, while only 0.520(95% CI: 0.472-0.524 was reported for predicting disease by LDA. Our results indicate that the new classifier sIB performs better than LDA in the study. Conclusions The fact that a small set of SNPs can predict disease status with average accuracy of 68% makes it possible to use SNP data for psoriasis prediction.

Ensemble-based prediction of RNA secondary structures.

Science.gov (United States)

Aghaeepour, Nima; Hoos, Holger H

2013-04-24

Accurate structure prediction methods play an important role for the understanding of RNA function. Energy-based, pseudoknot-free secondary structure prediction is one of the most widely used and versatile approaches, and improved methods for this task have received much attention over the past five years. Despite the impressive progress that as been achieved in this area, existing evaluations of the prediction accuracy achieved by various algorithms do not provide a comprehensive, statistically sound assessment. Furthermore, while there is increasing evidence that no prediction algorithm consistently outperforms all others, no work has been done to exploit the complementary strengths of multiple approaches. In this work, we present two contributions to the area of RNA secondary structure prediction. Firstly, we use state-of-the-art, resampling-based statistical methods together with a previously published and increasingly widely used dataset of high-quality RNA structures to conduct a comprehensive evaluation of existing RNA secondary structure prediction procedures. The results from this evaluation clarify the performance relationship between ten well-known existing energy-based pseudoknot-free RNA secondary structure prediction methods and clearly demonstrate the progress that has been achieved in recent years. Secondly, we introduce AveRNA, a generic and powerful method for combining a set of existing secondary structure prediction procedures into an ensemble-based method that achieves significantly higher prediction accuracies than obtained from any of its component procedures. Our new, ensemble-based method, AveRNA, improves the state of the art for energy-based, pseudoknot-free RNA secondary structure prediction by exploiting the complementary strengths of multiple existing prediction procedures, as demonstrated using a state-of-the-art statistical resampling approach. In addition, AveRNA allows an intuitive and effective control of the trade-off between

For how long can we predict the weather? - Insights into atmospheric predictability from global convection-allowing simulations

Science.gov (United States)

Judt, Falko

2017-04-01

A tremendous increase in computing power has facilitated the advent of global convection-resolving numerical weather prediction (NWP) models. Although this technological breakthrough allows for the seamless prediction of weather from local to global scales, the predictability of multiscale weather phenomena in these models is not very well known. To address this issue, we conducted a global high-resolution (4-km) predictability experiment using the Model for Prediction Across Scales (MPAS), a state-of-the-art global NWP model developed at the National Center for Atmospheric Research. The goals of this experiment are to investigate error growth from convective to planetary scales and to quantify the intrinsic, scale-dependent predictability limits of atmospheric motions. The globally uniform resolution of 4 km allows for the explicit treatment of organized deep moist convection, alleviating grave limitations of previous predictability studies that either used high-resolution limited-area models or global simulations with coarser grids and cumulus parameterization. Error growth is analyzed within the context of an "identical twin" experiment setup: the error is defined as the difference between a 20-day long "nature run" and a simulation that was perturbed with small-amplitude noise, but is otherwise identical. It is found that in convectively active regions, errors grow by several orders of magnitude within the first 24 h ("super-exponential growth"). The errors then spread to larger scales and begin a phase of exponential growth after 2-3 days when contaminating the baroclinic zones. After 16 days, the globally averaged error saturates—suggesting that the intrinsic limit of atmospheric predictability (in a general sense) is about two weeks, which is in line with earlier estimates. However, error growth rates differ between the tropics and mid-latitudes as well as between the troposphere and stratosphere, highlighting that atmospheric predictability is a complex

Does the sensorimotor system minimize prediction error or select the most likely prediction during object lifting?

Science.gov (United States)

McGregor, Heather R.; Pun, Henry C. H.; Buckingham, Gavin; Gribble, Paul L.

2016-01-01

The human sensorimotor system is routinely capable of making accurate predictions about an object's weight, which allows for energetically efficient lifts and prevents objects from being dropped. Often, however, poor predictions arise when the weight of an object can vary and sensory cues about object weight are sparse (e.g., picking up an opaque water bottle). The question arises, what strategies does the sensorimotor system use to make weight predictions when one is dealing with an object whose weight may vary? For example, does the sensorimotor system use a strategy that minimizes prediction error (minimal squared error) or one that selects the weight that is most likely to be correct (maximum a posteriori)? In this study we dissociated the predictions of these two strategies by having participants lift an object whose weight varied according to a skewed probability distribution. We found, using a small range of weight uncertainty, that four indexes of sensorimotor prediction (grip force rate, grip force, load force rate, and load force) were consistent with a feedforward strategy that minimizes the square of prediction errors. These findings match research in the visuomotor system, suggesting parallels in underlying processes. We interpret our findings within a Bayesian framework and discuss the potential benefits of using a minimal squared error strategy. NEW & NOTEWORTHY Using a novel experimental model of object lifting, we tested whether the sensorimotor system models the weight of objects by minimizing lifting errors or by selecting the statistically most likely weight. We found that the sensorimotor system minimizes the square of prediction errors for object lifting. This parallels the results of studies that investigated visually guided reaching, suggesting an overlap in the underlying mechanisms between tasks that involve different sensory systems. PMID:27760821

Predicting volume of distribution with decision tree-based regression methods using predicted tissue:plasma partition coefficients.

Science.gov (United States)

Freitas, Alex A; Limbu, Kriti; Ghafourian, Taravat

2015-01-01

Volume of distribution is an important pharmacokinetic property that indicates the extent of a drug's distribution in the body tissues. This paper addresses the problem of how to estimate the apparent volume of distribution at steady state (Vss) of chemical compounds in the human body using decision tree-based regression methods from the area of data mining (or machine learning). Hence, the pros and cons of several different types of decision tree-based regression methods have been discussed. The regression methods predict Vss using, as predictive features, both the compounds' molecular descriptors and the compounds' tissue:plasma partition coefficients (Kt:p) - often used in physiologically-based pharmacokinetics. Therefore, this work has assessed whether the data mining-based prediction of Vss can be made more accurate by using as input not only the compounds' molecular descriptors but also (a subset of) their predicted Kt:p values. Comparison of the models that used only molecular descriptors, in particular, the Bagging decision tree (mean fold error of 2.33), with those employing predicted Kt:p values in addition to the molecular descriptors, such as the Bagging decision tree using adipose Kt:p (mean fold error of 2.29), indicated that the use of predicted Kt:p values as descriptors may be beneficial for accurate prediction of Vss using decision trees if prior feature selection is applied. Decision tree based models presented in this work have an accuracy that is reasonable and similar to the accuracy of reported Vss inter-species extrapolations in the literature. The estimation of Vss for new compounds in drug discovery will benefit from methods that are able to integrate large and varied sources of data and flexible non-linear data mining methods such as decision trees, which can produce interpretable models. Graphical AbstractDecision trees for the prediction of tissue partition coefficient and volume of distribution of drugs.

The function and failure of sensory predictions.

Science.gov (United States)

Bansal, Sonia; Ford, Judith M; Spering, Miriam

2018-04-23

Humans and other primates are equipped with neural mechanisms that allow them to automatically make predictions about future events, facilitating processing of expected sensations and actions. Prediction-driven control and monitoring of perceptual and motor acts are vital to normal cognitive functioning. This review provides an overview of corollary discharge mechanisms involved in predictions across sensory modalities and discusses consequences of predictive coding for cognition and behavior. Converging evidence now links impairments in corollary discharge mechanisms to neuropsychiatric symptoms such as hallucinations and delusions. We review studies supporting a prediction-failure hypothesis of perceptual and cognitive disturbances. We also outline neural correlates underlying prediction function and failure, highlighting similarities across the visual, auditory, and somatosensory systems. In linking basic psychophysical and psychophysiological evidence of visual, auditory, and somatosensory prediction failures to neuropsychiatric symptoms, our review furthers our understanding of disease mechanisms. © 2018 New York Academy of Sciences.

Recent Advances in Predictive (Machine) Learning

Energy Technology Data Exchange (ETDEWEB)

Friedman, J

2004-01-24

Prediction involves estimating the unknown value of an attribute of a system under study given the values of other measured attributes. In prediction (machine) learning the prediction rule is derived from data consisting of previously solved cases. Most methods for predictive learning were originated many years ago at the dawn of the computer age. Recently two new techniques have emerged that have revitalized the field. These are support vector machines and boosted decision trees. This paper provides an introduction to these two new methods tracing their respective ancestral roots to standard kernel methods and ordinary decision trees.

Tail Risk Premia and Return Predictability

DEFF Research Database (Denmark)

Bollerslev, Tim; Todorov, Viktor; Xu, Lai

The variance risk premium, defined as the difference between actual and risk-neutralized expectations of the forward aggregate market variation, helps predict future market returns. Relying on new essentially model-free estimation procedure, we show that much of this predictability may be attribu......The variance risk premium, defined as the difference between actual and risk-neutralized expectations of the forward aggregate market variation, helps predict future market returns. Relying on new essentially model-free estimation procedure, we show that much of this predictability may......-varying economic uncertainty and changes in risk aversion, or market fears, respectively....

Final Technical Report: Increasing Prediction Accuracy.

Energy Technology Data Exchange (ETDEWEB)

King, Bruce Hardison [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Hansen, Clifford [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Stein, Joshua [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2015-12-01

PV performance models are used to quantify the value of PV plants in a given location. They combine the performance characteristics of the system, the measured or predicted irradiance and weather at a site, and the system configuration and design into a prediction of the amount of energy that will be produced by a PV system. These predictions must be as accurate as possible in order for finance charges to be minimized. Higher accuracy equals lower project risk. The Increasing Prediction Accuracy project at Sandia focuses on quantifying and reducing uncertainties in PV system performance models.

Prediction Methods for Blood Glucose Concentration

DEFF Research Database (Denmark)

“Recent Results on Glucose–Insulin Predictions by Means of a State Observer for Time-Delay Systems” by Pasquale Palumbo et al. introduces a prediction model which in real time predicts the insulin concentration in blood which in turn is used in a control system. The method is tested in simulation...... EEG signals to predict upcoming hypoglycemic situations in real-time by employing artificial neural networks. The results of a 30-day long clinical study with the implanted device and the developed algorithm are presented. The chapter “Meta-Learning Based Blood Glucose Predictor for Diabetic......, but the insulin amount is chosen using factors that account for this expectation. The increasing availability of more accurate continuous blood glucose measurement (CGM) systems is attracting much interest to the possibilities of explicit prediction of future BG values. Against this background, in 2014 a two...

Novel Approach for the Recognition and Prediction of Multi-Function Radar Behaviours Based on Predictive State Representations.

Science.gov (United States)

Ou, Jian; Chen, Yongguang; Zhao, Feng; Liu, Jin; Xiao, Shunping

2017-03-19

The extensive applications of multi-function radars (MFRs) have presented a great challenge to the technologies of radar countermeasures (RCMs) and electronic intelligence (ELINT). The recently proposed cognitive electronic warfare (CEW) provides a good solution, whose crux is to perceive present and future MFR behaviours, including the operating modes, waveform parameters, scheduling schemes, etc. Due to the variety and complexity of MFR waveforms, the existing approaches have the drawbacks of inefficiency and weak practicability in prediction. A novel method for MFR behaviour recognition and prediction is proposed based on predictive state representation (PSR). With the proposed approach, operating modes of MFR are recognized by accumulating the predictive states, instead of using fixed transition probabilities that are unavailable in the battlefield. It helps to reduce the dependence of MFR on prior information. And MFR signals can be quickly predicted by iteratively using the predicted observation, avoiding the very large computation brought by the uncertainty of future observations. Simulations with a hypothetical MFR signal sequence in a typical scenario are presented, showing that the proposed methods perform well and efficiently, which attests to their validity.

Prediction during natural language comprehension

NARCIS (Netherlands)

Willems, R.M.; Frank, S.L.; Nijhof, A.D.; Hagoort, P.; Bosch, A.P.J. van den

2016-01-01

The notion of prediction is studied in cognitive neuroscience with increasing intensity. We investigated the neural basis of 2 distinct aspects of word prediction, derived from information theory, during story comprehension. We assessed the effect of entropy of next-word probability distributions as

Predictive Systems Toxicology

KAUST Repository

Kiani, Narsis A.; Shang, Ming-Mei; Zenil, Hector; Tegner, Jesper

2018-01-01

In this review we address to what extent computational techniques can augment our ability to predict toxicity. The first section provides a brief history of empirical observations on toxicity dating back to the dawn of Sumerian civilization. Interestingly, the concept of dose emerged very early on, leading up to the modern emphasis on kinetic properties, which in turn encodes the insight that toxicity is not solely a property of a compound but instead depends on the interaction with the host organism. The next logical step is the current conception of evaluating drugs from a personalized medicine point-of-view. We review recent work on integrating what could be referred to as classical pharmacokinetic analysis with emerging systems biology approaches incorporating multiple omics data. These systems approaches employ advanced statistical analytical data processing complemented with machine learning techniques and use both pharmacokinetic and omics data. We find that such integrated approaches not only provide improved predictions of toxicity but also enable mechanistic interpretations of the molecular mechanisms underpinning toxicity and drug resistance. We conclude the chapter by discussing some of the main challenges, such as how to balance the inherent tension between the predictive capacity of models, which in practice amounts to constraining the number of features in the models versus allowing for rich mechanistic interpretability, i.e. equipping models with numerous molecular features. This challenge also requires patient-specific predictions on toxicity, which in turn requires proper stratification of patients as regards how they respond, with or without adverse toxic effects. In summary, the transformation of the ancient concept of dose is currently successfully operationalized using rich integrative data encoded in patient-specific models.

Predictive Systems Toxicology

KAUST Repository

Kiani, Narsis A.

2018-01-15

In this review we address to what extent computational techniques can augment our ability to predict toxicity. The first section provides a brief history of empirical observations on toxicity dating back to the dawn of Sumerian civilization. Interestingly, the concept of dose emerged very early on, leading up to the modern emphasis on kinetic properties, which in turn encodes the insight that toxicity is not solely a property of a compound but instead depends on the interaction with the host organism. The next logical step is the current conception of evaluating drugs from a personalized medicine point-of-view. We review recent work on integrating what could be referred to as classical pharmacokinetic analysis with emerging systems biology approaches incorporating multiple omics data. These systems approaches employ advanced statistical analytical data processing complemented with machine learning techniques and use both pharmacokinetic and omics data. We find that such integrated approaches not only provide improved predictions of toxicity but also enable mechanistic interpretations of the molecular mechanisms underpinning toxicity and drug resistance. We conclude the chapter by discussing some of the main challenges, such as how to balance the inherent tension between the predictive capacity of models, which in practice amounts to constraining the number of features in the models versus allowing for rich mechanistic interpretability, i.e. equipping models with numerous molecular features. This challenge also requires patient-specific predictions on toxicity, which in turn requires proper stratification of patients as regards how they respond, with or without adverse toxic effects. In summary, the transformation of the ancient concept of dose is currently successfully operationalized using rich integrative data encoded in patient-specific models.

Trading network predicts stock price.

Science.gov (United States)

Sun, Xiao-Qian; Shen, Hua-Wei; Cheng, Xue-Qi

2014-01-16

Stock price prediction is an important and challenging problem for studying financial markets. Existing studies are mainly based on the time series of stock price or the operation performance of listed company. In this paper, we propose to predict stock price based on investors' trading behavior. For each stock, we characterize the daily trading relationship among its investors using a trading network. We then classify the nodes of trading network into three roles according to their connectivity pattern. Strong Granger causality is found between stock price and trading relationship indices, i.e., the fraction of trading relationship among nodes with different roles. We further predict stock price by incorporating these trading relationship indices into a neural network based on time series of stock price. Experimental results on 51 stocks in two Chinese Stock Exchanges demonstrate the accuracy of stock price prediction is significantly improved by the inclusion of trading relationship indices.

Prediction of beta-turns at over 80% accuracy based on an ensemble of predicted secondary structures and multiple alignments

Directory of Open Access Journals (Sweden)

Kurgan Lukasz

2008-10-01

Full Text Available Abstract Background β-turn is a secondary protein structure type that plays significant role in protein folding, stability, and molecular recognition. To date, several methods for prediction of β-turns from protein sequences were developed, but they are characterized by relatively poor prediction quality. The novelty of the proposed sequence-based β-turn predictor stems from the usage of a window based information extracted from four predicted three-state secondary structures, which together with a selected set of position specific scoring matrix (PSSM values serve as an input to the support vector machine (SVM predictor. Results We show that (1 all four predicted secondary structures are useful; (2 the most useful information extracted from the predicted secondary structure includes the structure of the predicted residue, secondary structure content in a window around the predicted residue, and features that indicate whether the predicted residue is inside a secondary structure segment; (3 the PSSM values of Asn, Asp, Gly, Ile, Leu, Met, Pro, and Val were among the top ranked features, which corroborates with recent studies. The Asn, Asp, Gly, and Pro indicate potential β-turns, while the remaining four amino acids are useful to predict non-β-turns. Empirical evaluation using three nonredundant datasets shows favorable Qtotal, Qpredicted and MCC values when compared with over a dozen of modern competing methods. Our method is the first to break the 80% Qtotal barrier and achieves Qtotal = 80.9%, MCC = 0.47, and Qpredicted higher by over 6% when compared with the second best method. We use feature selection to reduce the dimensionality of the feature vector used as the input for the proposed prediction method. The applied feature set is smaller by 86, 62 and 37% when compared with the second and two third-best (with respect to MCC competing methods, respectively. Conclusion Experiments show that the proposed method constitutes an

NEURAL METHODS FOR THE FINANCIAL PREDICTION

OpenAIRE

Jerzy Balicki; Piotr Dryja; Waldemar Korłub; Piotr Przybyłek; Maciej Tyszka; Marcin Zadroga; Marcin Zakidalski

2016-01-01

Artificial neural networks can be used to predict share investment on the stock market, assess the reliability of credit client or predicting banking crises. Moreover, this paper discusses the principles of cooperation neural network algorithms with evolutionary method, and support vector machines. In addition, a reference is made to other methods of artificial intelligence, which are used in finance prediction.

NEURAL METHODS FOR THE FINANCIAL PREDICTION

Directory of Open Access Journals (Sweden)

Jerzy Balicki

2016-06-01

Full Text Available Artificial neural networks can be used to predict share investment on the stock market, assess the reliability of credit client or predicting banking crises. Moreover, this paper discusses the principles of cooperation neural network algorithms with evolutionary method, and support vector machines. In addition, a reference is made to other methods of artificial intelligence, which are used in finance prediction.

Predictive genomics: A cancer hallmark network framework for predicting tumor clinical phenotypes using genome sequencing data

OpenAIRE

Wang, Edwin; Zaman, Naif; Mcgee, Shauna; Milanese, Jean-Sébastien; Masoudi-Nejad, Ali; O'Connor, Maureen

2014-01-01

We discuss a cancer hallmark network framework for modelling genome-sequencing data to predict cancer clonal evolution and associated clinical phenotypes. Strategies of using this framework in conjunction with genome sequencing data in an attempt to predict personalized drug targets, drug resistance, and metastasis for a cancer patient, as well as cancer risks for a healthy individual are discussed. Accurate prediction of cancer clonal evolution and clinical phenotypes will have substantial i...

Comparison of predictive performance of data mining algorithms in predicting body weight in Mengali rams of Pakistan

Directory of Open Access Journals (Sweden)

Senol Celik

Full Text Available ABSTRACT The present study aimed at comparing predictive performance of some data mining algorithms (CART, CHAID, Exhaustive CHAID, MARS, MLP, and RBF in biometrical data of Mengali rams. To compare the predictive capability of the algorithms, the biometrical data regarding body (body length, withers height, and heart girth and testicular (testicular length, scrotal length, and scrotal circumference measurements of Mengali rams in predicting live body weight were evaluated by most goodness of fit criteria. In addition, age was considered as a continuous independent variable. In this context, MARS data mining algorithm was used for the first time to predict body weight in two forms, without (MARS_1 and with interaction (MARS_2 terms. The superiority order in the predictive accuracy of the algorithms was found as CART > CHAID ≈ Exhaustive CHAID > MARS_2 > MARS_1 > RBF > MLP. Moreover, all tested algorithms provided a strong predictive accuracy for estimating body weight. However, MARS is the only algorithm that generated a prediction equation for body weight. Therefore, it is hoped that the available results might present a valuable contribution in terms of predicting body weight and describing the relationship between the body weight and body and testicular measurements in revealing breed standards and the conservation of indigenous gene sources for Mengali sheep breeding. Therefore, it will be possible to perform more profitable and productive sheep production. Use of data mining algorithms is useful for revealing the relationship between body weight and testicular traits in describing breed standards of Mengali sheep.

Gate valve performance prediction

International Nuclear Information System (INIS)

Harrison, D.H.; Damerell, P.S.; Wang, J.K.; Kalsi, M.S.; Wolfe, K.J.

1994-01-01

The Electric Power Research Institute is carrying out a program to improve the performance prediction methods for motor-operated valves. As part of this program, an analytical method to predict the stem thrust required to stroke a gate valve has been developed and has been assessed against data from gate valve tests. The method accounts for the loads applied to the disc by fluid flow and for the detailed mechanical interaction of the stem, disc, guides, and seats. To support development of the method, two separate-effects test programs were carried out. One test program determined friction coefficients for contacts between gate valve parts by using material specimens in controlled environments. The other test program investigated the interaction of the stem, disc, guides, and seat using a special fixture with full-sized gate valve parts. The method has been assessed against flow-loop and in-plant test data. These tests include valve sizes from 3 to 18 in. and cover a considerable range of flow, temperature, and differential pressure. Stem thrust predictions for the method bound measured results. In some cases, the bounding predictions are substantially higher than the stem loads required for valve operation, as a result of the bounding nature of the friction coefficients in the method

The prediction of surface temperature in the new seasonal prediction system based on the MPI-ESM coupled climate model

Science.gov (United States)

Baehr, J.; Fröhlich, K.; Botzet, M.; Domeisen, D. I. V.; Kornblueh, L.; Notz, D.; Piontek, R.; Pohlmann, H.; Tietsche, S.; Müller, W. A.

2015-05-01

A seasonal forecast system is presented, based on the global coupled climate model MPI-ESM as used for CMIP5 simulations. We describe the initialisation of the system and analyse its predictive skill for surface temperature. The presented system is initialised in the atmospheric, oceanic, and sea ice component of the model from reanalysis/observations with full field nudging in all three components. For the initialisation of the ensemble, bred vectors with a vertically varying norm are implemented in the ocean component to generate initial perturbations. In a set of ensemble hindcast simulations, starting each May and November between 1982 and 2010, we analyse the predictive skill. Bias-corrected ensemble forecasts for each start date reproduce the observed surface temperature anomalies at 2-4 months lead time, particularly in the tropics. Niño3.4 sea surface temperature anomalies show a small root-mean-square error and predictive skill up to 6 months. Away from the tropics, predictive skill is mostly limited to the ocean, and to regions which are strongly influenced by ENSO teleconnections. In summary, the presented seasonal prediction system based on a coupled climate model shows predictive skill for surface temperature at seasonal time scales comparable to other seasonal prediction systems using different underlying models and initialisation strategies. As the same model underlying our seasonal prediction system—with a different initialisation—is presently also used for decadal predictions, this is an important step towards seamless seasonal-to-decadal climate predictions.

Pulverized coal devolatilization prediction

International Nuclear Information System (INIS)

Rojas, Andres F; Barraza, Juan M

2008-01-01

The aim of this study was to predict the two bituminous coals devolatilization at low rate of heating (50 Celsius degrade/min), with program FG-DVC (functional group Depolymerization. Vaporization and crosslinking), and to compare the devolatilization profiles predicted by program FG-DVC, which are obtained in the thermogravimetric analyzer. It was also study the volatile liberation at (10 4 k/s) in a drop-tube furnace. The tar, methane, carbon monoxide, and carbon dioxide, formation rate profiles, and the hydrogen, oxygen, nitrogen and sulphur, elemental distribution in the devolatilization products by FG-DVC program at low rate of heating was obtained; and the liberation volatile and R factor at high rate of heating was calculated. it was found that the program predicts the bituminous coals devolatilization at low rate heating, at high rate heating, a volatile liberation around 30% was obtained

Fixed recurrence and slip models better predict earthquake behavior than the time- and slip-predictable models 1: repeating earthquakes

Science.gov (United States)

Rubinstein, Justin L.; Ellsworth, William L.; Chen, Kate Huihsuan; Uchida, Naoki

2012-01-01

The behavior of individual events in repeating earthquake sequences in California, Taiwan and Japan is better predicted by a model with fixed inter-event time or fixed slip than it is by the time- and slip-predictable models for earthquake occurrence. Given that repeating earthquakes are highly regular in both inter-event time and seismic moment, the time- and slip-predictable models seem ideally suited to explain their behavior. Taken together with evidence from the companion manuscript that shows similar results for laboratory experiments we conclude that the short-term predictions of the time- and slip-predictable models should be rejected in favor of earthquake models that assume either fixed slip or fixed recurrence interval. This implies that the elastic rebound model underlying the time- and slip-predictable models offers no additional value in describing earthquake behavior in an event-to-event sense, but its value in a long-term sense cannot be determined. These models likely fail because they rely on assumptions that oversimplify the earthquake cycle. We note that the time and slip of these events is predicted quite well by fixed slip and fixed recurrence models, so in some sense they are time- and slip-predictable. While fixed recurrence and slip models better predict repeating earthquake behavior than the time- and slip-predictable models, we observe a correlation between slip and the preceding recurrence time for many repeating earthquake sequences in Parkfield, California. This correlation is not found in other regions, and the sequences with the correlative slip-predictable behavior are not distinguishable from nearby earthquake sequences that do not exhibit this behavior.

The Theory of Linear Prediction

CERN Document Server

Vaidyanathan, PP

2007-01-01

Linear prediction theory has had a profound impact in the field of digital signal processing. Although the theory dates back to the early 1940s, its influence can still be seen in applications today. The theory is based on very elegant mathematics and leads to many beautiful insights into statistical signal processing. Although prediction is only a part of the more general topics of linear estimation, filtering, and smoothing, this book focuses on linear prediction. This has enabled detailed discussion of a number of issues that are normally not found in texts. For example, the theory of vecto

Predicting emergency diesel starting performance

International Nuclear Information System (INIS)

DeBey, T.M.

1989-01-01

The US Department of Energy effort to extend the operational lives of commercial nuclear power plants has examined methods for predicting the performance of specific equipment. This effort focuses on performance prediction as a means for reducing equipment surveillance, maintenance, and outages. Realizing these goals will result in nuclear plants that are more reliable, have lower maintenance costs, and have longer lives. This paper describes a monitoring system that has been developed to predict starting performance in emergency diesels. A prototype system has been built and tested on an engine at Sandia National Laboratories. 2 refs

Multi-model analysis in hydrological prediction

Science.gov (United States)

Lanthier, M.; Arsenault, R.; Brissette, F.

2017-12-01

Hydrologic modelling, by nature, is a simplification of the real-world hydrologic system. Therefore ensemble hydrological predictions thus obtained do not present the full range of possible streamflow outcomes, thereby producing ensembles which demonstrate errors in variance such as under-dispersion. Past studies show that lumped models used in prediction mode can return satisfactory results, especially when there is not enough information available on the watershed to run a distributed model. But all lumped models greatly simplify the complex processes of the hydrologic cycle. To generate more spread in the hydrologic ensemble predictions, multi-model ensembles have been considered. In this study, the aim is to propose and analyse a method that gives an ensemble streamflow prediction that properly represents the forecast probabilities and reduced ensemble bias. To achieve this, three simple lumped models are used to generate an ensemble. These will also be combined using multi-model averaging techniques, which generally generate a more accurate hydrogram than the best of the individual models in simulation mode. This new predictive combined hydrogram is added to the ensemble, thus creating a large ensemble which may improve the variability while also improving the ensemble mean bias. The quality of the predictions is then assessed on different periods: 2 weeks, 1 month, 3 months and 6 months using a PIT Histogram of the percentiles of the real observation volumes with respect to the volumes of the ensemble members. Initially, the models were run using historical weather data to generate synthetic flows. This worked for individual models, but not for the multi-model and for the large ensemble. Consequently, by performing data assimilation at each prediction period and thus adjusting the initial states of the models, the PIT Histogram could be constructed using the observed flows while allowing the use of the multi-model predictions. The under-dispersion has been

Genomic prediction using subsampling

OpenAIRE

Xavier, Alencar; Xu, Shizhong; Muir, William; Rainey, Katy Martin

2017-01-01

Background Genome-wide assisted selection is a critical tool for the?genetic improvement of plants and animals. Whole-genome regression models in Bayesian framework represent the main family of prediction methods. Fitting such models with a large number of observations involves a prohibitive computational burden. We propose the use of subsampling bootstrap Markov chain in genomic prediction. Such method consists of fitting whole-genome regression models by subsampling observations in each rou...

Empirical Flutter Prediction Method.

Science.gov (United States)

1988-03-05

been used in this way to discover species or subspecies of animals, and to discover different types of voter or comsumer requiring different persuasions...respect to behavior or performance or response variables. Once this were done, corresponding clusters might be sought among descriptive or predictive or...jump in a response. The first sort of usage does not apply to the flutter prediction problem. Here the types of behavior are the different kinds of

Geophysical Anomalies and Earthquake Prediction

Science.gov (United States)

Jackson, D. D.

2008-12-01

Finding anomalies is easy. Predicting earthquakes convincingly from such anomalies is far from easy. Why? Why have so many beautiful geophysical abnormalities not led to successful prediction strategies? What is earthquake prediction? By my definition it is convincing information that an earthquake of specified size is temporarily much more likely than usual in a specific region for a specified time interval. We know a lot about normal earthquake behavior, including locations where earthquake rates are higher than elsewhere, with estimable rates and size distributions. We know that earthquakes have power law size distributions over large areas, that they cluster in time and space, and that aftershocks follow with power-law dependence on time. These relationships justify prudent protective measures and scientific investigation. Earthquake prediction would justify exceptional temporary measures well beyond those normal prudent actions. Convincing earthquake prediction would result from methods that have demonstrated many successes with few false alarms. Predicting earthquakes convincingly is difficult for several profound reasons. First, earthquakes start in tiny volumes at inaccessible depth. The power law size dependence means that tiny unobservable ones are frequent almost everywhere and occasionally grow to larger size. Thus prediction of important earthquakes is not about nucleation, but about identifying the conditions for growth. Second, earthquakes are complex. They derive their energy from stress, which is perniciously hard to estimate or model because it is nearly singular at the margins of cracks and faults. Physical properties vary from place to place, so the preparatory processes certainly vary as well. Thus establishing the needed track record for validation is very difficult, especially for large events with immense interval times in any one location. Third, the anomalies are generally complex as well. Electromagnetic anomalies in particular require

Applications of contact predictions to structural biology

Directory of Open Access Journals (Sweden)

Felix Simkovic

2017-05-01

Full Text Available Evolutionary pressure on residue interactions, intramolecular or intermolecular, that are important for protein structure or function can lead to covariance between the two positions. Recent methodological advances allow much more accurate contact predictions to be derived from this evolutionary covariance signal. The practical application of contact predictions has largely been confined to structural bioinformatics, yet, as this work seeks to demonstrate, the data can be of enormous value to the structural biologist working in X-ray crystallography, cryo-EM or NMR. Integrative structural bioinformatics packages such as Rosetta can already exploit contact predictions in a variety of ways. The contribution of contact predictions begins at construct design, where structural domains may need to be expressed separately and contact predictions can help to predict domain limits. Structure solution by molecular replacement (MR benefits from contact predictions in diverse ways: in difficult cases, more accurate search models can be constructed using ab initio modelling when predictions are available, while intermolecular contact predictions can allow the construction of larger, oligomeric search models. Furthermore, MR using supersecondary motifs or large-scale screens against the PDB can exploit information, such as the parallel or antiparallel nature of any β-strand pairing in the target, that can be inferred from contact predictions. Contact information will be particularly valuable in the determination of lower resolution structures by helping to assign sequence register. In large complexes, contact information may allow the identity of a protein responsible for a certain region of density to be determined and then assist in the orientation of an available model within that density. In NMR, predicted contacts can provide long-range information to extend the upper size limit of the technique in a manner analogous but complementary to experimental

In-Hospital Risk Prediction for Post-stroke Depression. Development and Validation of the Post-stroke Depression Prediction Scale

NARCIS (Netherlands)

Thóra Hafsteinsdóttir; Roelof G.A. Ettema; Diederick Grobbee; Prof. Dr. Marieke J. Schuurmans; Janneke van Man-van Ginkel; Eline Lindeman

2013-01-01

Background and Purpose—The timely detection of post-stroke depression is complicated by a decreasing length of hospital stay. Therefore, the Post-stroke Depression Prediction Scale was developed and validated. The Post-stroke Depression Prediction Scale is a clinical prediction model for the early

Ônibus 174: um olhar sobre a violência urbana e a exclusão social

Directory of Open Access Journals (Sweden)

Joana Maria Eleutério

2011-01-01

Full Text Available This article aims to analyze the film Ônibus Linha 174 (José Padilha, 2002 as another interpretation of the episode narrated and commented based on a variety of texts. The film is a documentary, which was produced by Jose Padilha (also director and Marcos Prado, photography by Cesar Morales and Marcelo Guru and editing by Felipe Lacerda. The film focuses on urban violence, but this article discusses other issues, avoiding the repetition of what has already been said by great experts and even ordinary citizens. This film, the foundation of my research, is the guideline to the reflection that I propose, since the focus of my analysis the main character of two parallel stories narrated in the film: the young Sandro Rosa do Nascimento, who becomes an archetypal figure in the social context of stories, scenarios and the testimonies shown by Padilha. As the discussion progresses, another important character for the analysis emerges: Sandra Mara Herzer (1962-1982, a young woman whose life trajectory allows me to compare the two aiming to understand how these two characters who report a serious context that causes the multiplication of a series of other stories similar to theirs. It is unquestionable that, although both have achieved international visibility, there is a multitude of invisible Sandros and Sandras, living in the streets and "caregivens" institutions for children, going through the same stages of this monstrous metamorphosis that led them desperation in the final scene of their short lives.

La Violencia del Lugar Violence of Site

Directory of Open Access Journals (Sweden)

Zulema Moret

2010-12-01

Full Text Available Este ensayo presenta personajes nómades, huérfanos, habitantes de la noche, sin hogar y sin ley. Estos personajes nos permiten analizar las relaciones entre violencia y lugar, en la cultura argentina durante los noventa y el inicio del 2000. Las películas elegidas son Un día de suerte (2002 de Sandra Gugliotta, Vagón Fumador (2001 de Verónica Chen y Hoy y Mañana (2003 de Alejandro Chomski. Las tres películas, filmadas a principios del 2000, tienen como escenario la ciudad de Buenos Aires, las historias siguen los desplazamientos de los jóvenes protagonistas por la ciudad, estableciendo nuevas fronteras entre el centro y la periferia, y la noción de no-lugar en la cartografía de la ciudad de Buenos Aires.This essay introduces nomadic characters, orphans, night crawlers, jobless and lawless people. These characters will allow us to analyze the bonds between violence and site in Argentine culture during the nineties and at the beginning of our century. The chosen films are Un día de suerte (A Lucky Day, 2002 by Sandra Gugliotta, Vagón Fumador (Smoking Car, 2001 by Verónica Chen, and Hoy y Mañana ( Today and Tomorrow, 2003 by Alejandro Chomski. These three movies, filmed at the beginning of the year 2000, are set in the city of Buenos Aires; the stories follow the wanderings of their young protagonists, showing new displacements between center and periphery in Buenos Aires' cartography.

Model Predictive Control for Smart Energy Systems

DEFF Research Database (Denmark)

Halvgaard, Rasmus

pumps, heat tanks, electrical vehicle battery charging/discharging, wind farms, power plants). 2.Embed forecasting methodologies for the weather (e.g. temperature, solar radiation), the electricity consumption, and the electricity price in a predictive control system. 3.Develop optimization algorithms....... Chapter 3 introduces Model Predictive Control (MPC) including state estimation, filtering and prediction for linear models. Chapter 4 simulates the models from Chapter 2 with the certainty equivalent MPC from Chapter 3. An economic MPC minimizes the costs of consumption based on real electricity prices...... that determined the flexibility of the units. A predictive control system easily handles constraints, e.g. limitations in power consumption, and predicts the future behavior of a unit by integrating predictions of electricity prices, consumption, and weather variables. The simulations demonstrate the expected...

Prediction of Commuter’s Daily Time Allocation

Directory of Open Access Journals (Sweden)

Fang Zong

2013-10-01

Full Text Available This paper presents a model system to predict the time allocation in commuters’ daily activity-travel pattern. The departure time and the arrival time are estimated with Ordered Probit model and Support Vector Regression is introduced for travel time and activity duration prediction. Applied in a real-world time allocation prediction experiment, the model system shows a satisfactory level of prediction accuracy. This study provides useful insights into commuters’ activity-travel time allocation decision by identifying the important influences, and the results are readily applied to a wide range of transportation practice, such as travel information system, by providing reliable forecast for variations in travel demand over time. By introducing the Support Vector Regression, it also makes a methodological contribution in enhancing prediction accuracy of travel time and activity duration prediction.

EFFICIENT PREDICTIVE MODELLING FOR ARCHAEOLOGICAL RESEARCH

OpenAIRE

Balla, A.; Pavlogeorgatos, G.; Tsiafakis, D.; Pavlidis, G.

2014-01-01

The study presents a general methodology for designing, developing and implementing predictive modelling for identifying areas of archaeological interest. The methodology is based on documented archaeological data and geographical factors, geospatial analysis and predictive modelling, and has been applied to the identification of possible Macedonian tombs’ locations in Northern Greece. The model was tested extensively and the results were validated using a commonly used predictive gain, which...

Dividend Predictability Around the World

DEFF Research Database (Denmark)

Rangvid, Jesper; Schmeling, Maik; Schrimpf, Andreas

2014-01-01

We show that dividend-growth predictability by the dividend yield is the rule rather than the exception in global equity markets. Dividend predictability is weaker, however, in large and developed markets where dividends are smoothed more, the typical firm is large, and volatility is lower. Our f...

Dividend Predictability Around the World

DEFF Research Database (Denmark)

Rangvid, Jesper; Schmeling, Maik; Schrimpf, Andreas

We show that dividend growth predictability by the dividend yield is the rule rather than the exception in global equity markets. Dividend predictability is weaker, however, in large and developed markets where dividends are smoothed more, the typical firm is large, and volatility is lower. Our f...

Using Predictability for Lexical Segmentation.

Science.gov (United States)

Çöltekin, Çağrı

2017-09-01

This study investigates a strategy based on predictability of consecutive sub-lexical units in learning to segment a continuous speech stream into lexical units using computational modeling and simulations. Lexical segmentation is one of the early challenges during language acquisition, and it has been studied extensively through psycholinguistic experiments as well as computational methods. However, despite strong empirical evidence, the explicit use of predictability of basic sub-lexical units in models of segmentation is underexplored. This paper presents an incremental computational model of lexical segmentation for exploring the usefulness of predictability for lexical segmentation. We show that the predictability cue is a strong cue for segmentation. Contrary to earlier reports in the literature, the strategy yields state-of-the-art segmentation performance with an incremental computational model that uses only this particular cue in a cognitively plausible setting. The paper also reports an in-depth analysis of the model, investigating the conditions affecting the usefulness of the strategy. Copyright © 2016 Cognitive Science Society, Inc.

EPRI MOV performance prediction program

International Nuclear Information System (INIS)

Hosler, J.F.; Damerell, P.S.; Eidson, M.G.; Estep, N.E.

1994-01-01

An overview of the EPRI Motor-Operated Valve (MOV) Performance Prediction Program is presented. The objectives of this Program are to better understand the factors affecting the performance of MOVs and to develop and validate methodologies to predict MOV performance. The Program involves valve analytical modeling, separate-effects testing to refine the models, and flow-loop and in-plant MOV testing to provide a basis for model validation. The ultimate product of the Program is an MOV Performance Prediction Methodology applicable to common gate, globe, and butterfly valves. The methodology predicts thrust and torque requirements at design-basis flow and differential pressure conditions, assesses the potential for gate valve internal damage, and provides test methods to quantify potential for gate valve internal damage, and provides test methods to quantify potential variations in actuator output thrust with loading condition. Key findings and their potential impact on MOV design and engineering application are summarized

Predictability of Mobile Phone Associations

DEFF Research Database (Denmark)

Jensen, Bjørn Sand; Larsen, Jan; Hansen, Lars Kai

2010-01-01

Prediction and understanding of human behavior is of high importance in many modern applications and research areas ranging from context-aware services, wireless resource allocation to social sciences. In this study we collect a novel dataset using standard mobile phones and analyze how the predi...... representation, and general behavior. This is of vital interest in the development of context-aware services which rely on forecasting based on mobile phone sensors.......Prediction and understanding of human behavior is of high importance in many modern applications and research areas ranging from context-aware services, wireless resource allocation to social sciences. In this study we collect a novel dataset using standard mobile phones and analyze how...... the predictability of mobile sensors, acting as proxies for humans, change with time scale and sensor type such as GSM and WLAN. Applying recent information theoretic methods, it is demonstrated that an upper bound on predictability is relatively high for all sensors given the complete history (typically above 90...

Predictable and Predictive Emotions:Explaining Cheap Signals and Trust Re-Extension

Directory of Open Access Journals (Sweden)

Eric eSchniter

2014-11-01

Full Text Available Despite normative predictions from economics and biology, unrelated strangers will often develop the trust necessary to reap gains from one-shot economic exchange opportunities. This appears to be especially true when declared intentions and emotions can be cheaply communicated. Perhaps even more puzzling to economists and biologists is the observation that anonymous and unrelated individuals, known to have breached trust, often make effective use of cheap signals, such as promises and apologies, to encourage trust re-extension. We used a pair of trust games with one-way communication and emotion surveys to investigate the role of emotions in regulating the propensity to message, apologize, re-extend trust, and demonstrate trustworthiness. This design allowed us to observe the endogenous emergence and natural distribution of trust-relevant behaviors, remedial strategies used by promise-breakers, their effects on behavior, and subsequent outcomes. We found that emotions triggered by interaction outcomes are predictable and also predict subsequent apology and trust re-extension. The role of emotions in behavioral regulation helps explain why messages are produced, when they can be trusted, and when trust will be re-extended.

Predictable and predictive emotions: explaining cheap signals and trust re-extension.

Science.gov (United States)

Schniter, Eric; Sheremeta, Roman M

2014-01-01

Despite normative predictions from economics and biology, unrelated strangers will often develop the trust necessary to reap gains from one-shot economic exchange opportunities. This appears to be especially true when declared intentions and emotions can be cheaply communicated. Perhaps even more puzzling to economists and biologists is the observation that anonymous and unrelated individuals, known to have breached trust, often make effective use of cheap signals, such as promises and apologies, to encourage trust re-extension. We used a pair of trust games with one-way communication and an emotion survey to investigate the role of emotions in regulating the propensity to message, apologize, re-extend trust, and demonstrate trustworthiness. This design allowed us to observe the endogenous emergence and natural distribution of trust-relevant behaviors, remedial strategies used by promise-breakers, their effects on behavior, and subsequent outcomes. We found that emotions triggered by interaction outcomes are predictable and also predict subsequent apology and trust re-extension. The role of emotions in behavioral regulation helps explain why messages are produced, when they can be trusted, and when trust will be re-extended.

Prediction Model for Predicting Powdery Mildew using ANN for Medicinal Plant— Picrorhiza kurrooa

Science.gov (United States)

Shivling, V. D.; Ghanshyam, C.; Kumar, Rakesh; Kumar, Sanjay; Sharma, Radhika; Kumar, Dinesh; Sharma, Atul; Sharma, Sudhir Kumar

2017-02-01

Plant disease fore casting system is an important system as it can be used for prediction of disease, further it can be used as an alert system to warn the farmers in advance so as to protect their crop from being getting infected. Fore casting system will predict the risk of infection for crop by using the environmental factors that favor in germination of disease. In this study an artificial neural network based system for predicting the risk of powdery mildew in Picrorhiza kurrooa was developed. For development, Levenberg-Marquardt backpropagation algorithm was used having a single hidden layer of ten nodes. Temperature and duration of wetness are the major environmental factors that favor infection. Experimental data was used as a training set and some percentage of data was used for testing and validation. The performance of the system was measured in the form of the coefficient of correlation (R), coefficient of determination (R2), mean square error and root mean square error. For simulating the network an inter face was developed. Using this interface the network was simulated by putting temperature and wetness duration so as to predict the level of risk at that particular value of the input data.

Does the Risk Assessment and Prediction Tool Predict Discharge Disposition After Joint Replacement?

DEFF Research Database (Denmark)

Hansen, Viktor J.; Gromov, Kirill; Lebrun, Lauren M

2015-01-01

BACKGROUND: Payers of health services and policymakers place a major focus on cost containment in health care. Studies have shown that early planning of discharge is essential in reducing length of stay and achieving financial benefit; tools that can help predict discharge disposition would...... populations is unknown. A low RAPT score is reported to indicate a high risk of needing any form of inpatient rehabilitation after TJA, including short-term nursing facilities. QUESTIONS/PURPOSES: This study attempts (1) to assess predictive accuracy of the RAPT on US patients undergoing total hip and knee....... Based on our findings, the risk categories in our populations should be high risk intermediate risk 7 to 10, and low risk > 10. CONCLUSIONS: The RAPT accurately predicted discharge disposition for high- and low-risk patients in our cohort. Based on our data, intermediate-risk patients should...

Development of a Climate Prediction Market

Science.gov (United States)

Roulston, M. S.

2017-12-01

Winton, a global investment firm, is planning to establish a prediction market for climate. This prediction market will allow participants to place bets on global climate up to several decades in the future. Winton is pursuing this endeavour as part of its philanthropy that funds scientific research and the communication of scientific ideas. The Winton Climate Prediction Market will be based in the U.K. It will be structured as an online gambling site subject to the regulation of the Gambling Commission. Unlike existing betting sites, the Climate Prediction Market will be subsidized: a central market maker will inject money into the market. This is in contrast to traditional bookmakers or betting exchanges who set odds in their favour or charge commissions to make a profit. The philosophy of a subsidized prediction market is that the party seeking information should fund the market, rather than the participants who provide the information. The initial market will allow bets to be placed on the atmospheric concentration of carbon dioxide and the global mean temperature anomaly. It will thus produce implied forecasts of carbon dioxide concentration as well as global temperatures. If the initial market is successful, additional markets could be added which target other climate variables, such as regional temperatures or sea-level rise. These markets could be sponsored by organizations that are interested in predictions of the specific climate variables. An online platform for the Climate Prediction Market has been developed and has been tested internally at Winton.

Profit Driven Decision Trees for Churn Prediction

OpenAIRE

Höppner, Sebastiaan; Stripling, Eugen; Baesens, Bart; Broucke, Seppe vanden; Verdonck, Tim

2017-01-01

Customer retention campaigns increasingly rely on predictive models to detect potential churners in a vast customer base. From the perspective of machine learning, the task of predicting customer churn can be presented as a binary classification problem. Using data on historic behavior, classification algorithms are built with the purpose of accurately predicting the probability of a customer defecting. The predictive churn models are then commonly selected based on accuracy related performan...

Seasonal Drought Prediction: Advances, Challenges, and Future Prospects

Science.gov (United States)

Hao, Zengchao; Singh, Vijay P.; Xia, Youlong

2018-03-01

Drought prediction is of critical importance to early warning for drought managements. This review provides a synthesis of drought prediction based on statistical, dynamical, and hybrid methods. Statistical drought prediction is achieved by modeling the relationship between drought indices of interest and a suite of potential predictors, including large-scale climate indices, local climate variables, and land initial conditions. Dynamical meteorological drought prediction relies on seasonal climate forecast from general circulation models (GCMs), which can be employed to drive hydrological models for agricultural and hydrological drought prediction with the predictability determined by both climate forcings and initial conditions. Challenges still exist in drought prediction at long lead time and under a changing environment resulting from natural and anthropogenic factors. Future research prospects to improve drought prediction include, but are not limited to, high-quality data assimilation, improved model development with key processes related to drought occurrence, optimal ensemble forecast to select or weight ensembles, and hybrid drought prediction to merge statistical and dynamical forecasts.

Predicting unpredictability

Science.gov (United States)

Davis, Steven J.

2018-04-01

Analysts and markets have struggled to predict a number of phenomena, such as the rise of natural gas, in US energy markets over the past decade or so. Research shows the challenge may grow because the industry — and consequently the market — is becoming increasingly volatile.

EMD-Based Predictive Deep Belief Network for Time Series Prediction: An Application to Drought Forecasting

Directory of Open Access Journals (Sweden)

Norbert A. Agana

2018-02-01

Full Text Available Drought is a stochastic natural feature that arises due to intense and persistent shortage of precipitation. Its impact is mostly manifested as agricultural and hydrological droughts following an initial meteorological phenomenon. Drought prediction is essential because it can aid in the preparedness and impact-related management of its effects. This study considers the drought forecasting problem by developing a hybrid predictive model using a denoised empirical mode decomposition (EMD and a deep belief network (DBN. The proposed method first decomposes the data into several intrinsic mode functions (IMFs using EMD, and a reconstruction of the original data is obtained by considering only relevant IMFs. Detrended fluctuation analysis (DFA was applied to each IMF to determine the threshold for robust denoising performance. Based on their scaling exponents, irrelevant intrinsic mode functions are identified and suppressed. The proposed method was applied to predict different time scale drought indices across the Colorado River basin using a standardized streamflow index (SSI as the drought index. The results obtained using the proposed method was compared with standard methods such as multilayer perceptron (MLP and support vector regression (SVR. The proposed hybrid model showed improvement in prediction accuracy, especially for multi-step ahead predictions.

Novel Approach for the Recognition and Prediction of Multi-Function Radar Behaviours Based on Predictive State Representations

Directory of Open Access Journals (Sweden)

Jian Ou

2017-03-01

Full Text Available The extensive applications of multi-function radars (MFRs have presented a great challenge to the technologies of radar countermeasures (RCMs and electronic intelligence (ELINT. The recently proposed cognitive electronic warfare (CEW provides a good solution, whose crux is to perceive present and future MFR behaviours, including the operating modes, waveform parameters, scheduling schemes, etc. Due to the variety and complexity of MFR waveforms, the existing approaches have the drawbacks of inefficiency and weak practicability in prediction. A novel method for MFR behaviour recognition and prediction is proposed based on predictive state representation (PSR. With the proposed approach, operating modes of MFR are recognized by accumulating the predictive states, instead of using fixed transition probabilities that are unavailable in the battlefield. It helps to reduce the dependence of MFR on prior information. And MFR signals can be quickly predicted by iteratively using the predicted observation, avoiding the very large computation brought by the uncertainty of future observations. Simulations with a hypothetical MFR signal sequence in a typical scenario are presented, showing that the proposed methods perform well and efficiently, which attests to their validity.

Climate Prediction Center - Seasonal Outlook

Science.gov (United States)

Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Site Map News Forecast Discussion PROGNOSTIC DISCUSSION FOR MONTHLY OUTLOOK NWS CLIMATE PREDICTION CENTER COLLEGE PARK MD INFLUENCE ON THE MONTHLY-AVERAGED CLIMATE. OUR MID-MONTH ASSESSMENT OF LOW-FREQUENCY CLIMATE VARIABILITY IS

Quadratic prediction of factor scores

NARCIS (Netherlands)

Wansbeek, T

1999-01-01

Factor scores are naturally predicted by means of their conditional expectation given the indicators y. Under normality this expectation is linear in y but in general it is an unknown function of y. II is discussed that under nonnormality factor scores can be more precisely predicted by a quadratic

Predicting Online Purchasing Behavior

OpenAIRE

W.R BUCKINX; D. VAN DEN POEL

2003-01-01

This empirical study investigates the contribution of different types of predictors to the purchasing behaviour at an online store. We use logit modelling to predict whether or not a purchase is made during the next visit to the website using both forward and backward variable-selection techniques, as well as Furnival and Wilson’s global score search algorithm to find the best subset of predictors. We contribute to the literature by using variables from four different categories in predicting...

NASA/MSFC prediction techniques

International Nuclear Information System (INIS)

Smith, R.E.

1987-01-01

The NASA/MSFC method of forecasting is more formal than NOAA's. The data are smoothed by the Lagrangian method and linear regression prediction techniques are used. The solar activity period is fixed at 11 years--the mean period of all previous cycles. Interestingly, the present prediction for the time of the next solar minimum is February or March of 1987, which, within the uncertainties of two methods, can be taken to be the same as the NOAA result

Ensemble-based Regional Climate Prediction: Political Impacts

Science.gov (United States)

Miguel, E.; Dykema, J.; Satyanath, S.; Anderson, J. G.

2008-12-01

Accurate forecasts of regional climate, including temperature and precipitation, have significant implications for human activities, not just economically but socially. Sub Saharan Africa is a region that has displayed an exceptional propensity for devastating civil wars. Recent research in political economy has revealed a strong statistical relationship between year to year fluctuations in precipitation and civil conflict in this region in the 1980s and 1990s. To investigate how climate change may modify the regional risk of civil conflict in the future requires a probabilistic regional forecast that explicitly accounts for the community's uncertainty in the evolution of rainfall under anthropogenic forcing. We approach the regional climate prediction aspect of this question through the application of a recently demonstrated method called generalized scalar prediction (Leroy et al. 2009), which predicts arbitrary scalar quantities of the climate system. This prediction method can predict change in any variable or linear combination of variables of the climate system averaged over a wide range spatial scales, from regional to hemispheric to global. Generalized scalar prediction utilizes an ensemble of model predictions to represent the community's uncertainty range in climate modeling in combination with a timeseries of any type of observational data that exhibits sensitivity to the scalar of interest. It is not necessary to prioritize models in deriving with the final prediction. We present the results of the application of generalized scalar prediction for regional forecasts of temperature and precipitation and Sub Saharan Africa. We utilize the climate predictions along with the established statistical relationship between year-to-year rainfall variability in Sub Saharan Africa to investigate the potential impact of climate change on civil conflict within that region.

Deterministic prediction of surface wind speed variations

Directory of Open Access Journals (Sweden)

G. V. Drisya

2014-11-01

Full Text Available Accurate prediction of wind speed is an important aspect of various tasks related to wind energy management such as wind turbine predictive control and wind power scheduling. The most typical characteristic of wind speed data is its persistent temporal variations. Most of the techniques reported in the literature for prediction of wind speed and power are based on statistical methods or probabilistic distribution of wind speed data. In this paper we demonstrate that deterministic forecasting methods can make accurate short-term predictions of wind speed using past data, at locations where the wind dynamics exhibit chaotic behaviour. The predictions are remarkably accurate up to 1 h with a normalised RMSE (root mean square error of less than 0.02 and reasonably accurate up to 3 h with an error of less than 0.06. Repeated application of these methods at 234 different geographical locations for predicting wind speeds at 30-day intervals for 3 years reveals that the accuracy of prediction is more or less the same across all locations and time periods. Comparison of the results with f-ARIMA model predictions shows that the deterministic models with suitable parameters are capable of returning improved prediction accuracy and capturing the dynamical variations of the actual time series more faithfully. These methods are simple and computationally efficient and require only records of past data for making short-term wind speed forecasts within practically tolerable margin of errors.

CONSTRUCTION COST PREDICTION USING NEURAL NETWORKS

Directory of Open Access Journals (Sweden)

Smita K Magdum

2017-10-01

Full Text Available Construction cost prediction is important for construction firms to compete and grow in the industry. Accurate construction cost prediction in the early stage of project is important for project feasibility studies and successful completion. There are many factors that affect the cost prediction. This paper presents construction cost prediction as multiple regression model with cost of six materials as independent variables. The objective of this paper is to develop neural networks and multilayer perceptron based model for construction cost prediction. Different models of NN and MLP are developed with varying hidden layer size and hidden nodes. Four artificial neural network models and twelve multilayer perceptron models are compared. MLP and NN give better results than statistical regression method. As compared to NN, MLP works better on training dataset but fails on testing dataset. Five activation functions are tested to identify suitable function for the problem. ‘elu' transfer function gives better results than other transfer function.

Physiognomy: Personality Traits Prediction by Learning

Institute of Scientific and Technical Information of China (English)

Ting Zhang; Ri-Zhen Qin; Qiu-Lei Dong; Wei Gao; Hua-Rong Xu; Zhan-Yi Hu

2017-01-01

Evaluating individuals' personality traits and intelligence from their faces plays a crucial role in interpersonal relationship and important social events such as elections and court sentences.To assess the possible correlations between personality traits (also measured intelligence) and face images,we first construct a dataset consisting of face photographs,personality measurements,and intelligence measurements.Then,we build an end-to-end convolutional neural network for prediction of personality traits and intelligence to investigate whether self-reported personality traits and intelligence can be predicted reliably from a face image.To our knowledge,it is the first work where deep learning is applied to this problem.Experimental results show the following three points:1)"Rule-consciousness" and "Tension" can be reliably predicted from face images.2) It is difficult,if not impossible,to predict intelligence from face images,a finding in accord with previous studies.3) Convolutional neural network (CNN) features outperform traditional handcrafted features in predicting traits.

Compressor Part II: Volute Flow Predictions

Directory of Open Access Journals (Sweden)

Yu-Tai Lee

1999-01-01

Full Text Available A numerical method that solves the Reynolds-averaged Navier-Stokes equations is used to study an inefficient component of a shipboard air-conditioning HCFC-124 compressor system. This high-loss component of the centrifugal compressor was identified as the volute through a series of measurements given in Part I of the paper. The predictions were made using three grid topologies. The first grid closes the connection between the cutwater and the discharge diffuser. The other two grids connect the cutwater area with the discharge diffuser. Experiments were performed to simulate both the cutwater conditions used in the predictions. Surface pressures along the outer wall and near the inlet of the volute were surveyed for comparisons with the predictions. Good agreements between the predicted results and the measurements validate the calculations. Total pressure distributions and flow stream traces from the prediction results support the loss distribution through the volute. A modified volute configuration is examined numerically for further loss comparison.

RNA-SSPT: RNA Secondary Structure Prediction Tools.

Science.gov (United States)

Ahmad, Freed; Mahboob, Shahid; Gulzar, Tahsin; Din, Salah U; Hanif, Tanzeela; Ahmad, Hifza; Afzal, Muhammad

2013-01-01

The prediction of RNA structure is useful for understanding evolution for both in silico and in vitro studies. Physical methods like NMR studies to predict RNA secondary structure are expensive and difficult. Computational RNA secondary structure prediction is easier. Comparative sequence analysis provides the best solution. But secondary structure prediction of a single RNA sequence is challenging. RNA-SSPT is a tool that computationally predicts secondary structure of a single RNA sequence. Most of the RNA secondary structure prediction tools do not allow pseudoknots in the structure or are unable to locate them. Nussinov dynamic programming algorithm has been implemented in RNA-SSPT. The current studies shows only energetically most favorable secondary structure is required and the algorithm modification is also available that produces base pairs to lower the total free energy of the secondary structure. For visualization of RNA secondary structure, NAVIEW in C language is used and modified in C# for tool requirement. RNA-SSPT is built in C# using Dot Net 2.0 in Microsoft Visual Studio 2005 Professional edition. The accuracy of RNA-SSPT is tested in terms of Sensitivity and Positive Predicted Value. It is a tool which serves both secondary structure prediction and secondary structure visualization purposes.

Conditional prediction intervals of wind power generation

DEFF Research Database (Denmark)

Pinson, Pierre; Kariniotakis, Georges

2010-01-01

A generic method for the providing of prediction intervals of wind power generation is described. Prediction intervals complement the more common wind power point forecasts, by giving a range of potential outcomes for a given probability, their so-called nominal coverage rate. Ideally they inform...... on the characteristics of prediction errors for providing conditional interval forecasts. By simultaneously generating prediction intervals with various nominal coverage rates, one obtains full predictive distributions of wind generation. Adapted resampling is applied here to the case of an onshore Danish wind farm...... to the case of a large number of wind farms in Europe and Australia among others is finally discussed....

Practical aspects of geological prediction

International Nuclear Information System (INIS)

Mallio, W.J.; Peck, J.H.

1981-01-01

Nuclear waste disposal requires that geology be a predictive science. The prediction of future events rests on (1) recognizing the periodicity of geologic events; (2) defining a critical dimension of effect, such as the area of a drainage basin, the length of a fault trace, etc; and (3) using our understanding of active processes the project the frequency and magnitude of future events in the light of geological principles. Of importance to nuclear waste disposal are longer term processes such as continental denudation and removal of materials by glacial erosion. Constant testing of projections will allow the practical limits of predicting geological events to be defined. 11 refs

Predictions for Excited Strange Baryons

Energy Technology Data Exchange (ETDEWEB)

Fernando, Ishara P.; Goity, Jose L. [Thomas Jefferson National Accelerator Facility (TJNAF), Newport News, VA (United States)

2016-04-01

An assessment is made of predictions for excited hyperon masses which follow from flavor symmetry and consistency with a 1/N c expansion of QCD. Such predictions are based on presently established baryonic resonances. Low lying hyperon resonances which do not seem to fit into the proposed scheme are discussed.

Model predictive control using fuzzy decision functions

NARCIS (Netherlands)

Kaymak, U.; Costa Sousa, da J.M.

2001-01-01

Fuzzy predictive control integrates conventional model predictive control with techniques from fuzzy multicriteria decision making, translating the goals and the constraints to predictive control in a transparent way. The information regarding the (fuzzy) goals and the (fuzzy) constraints of the

Extending Theory-Based Quantitative Predictions to New Health Behaviors.

Science.gov (United States)

Brick, Leslie Ann D; Velicer, Wayne F; Redding, Colleen A; Rossi, Joseph S; Prochaska, James O

2016-04-01

Traditional null hypothesis significance testing suffers many limitations and is poorly adapted to theory testing. A proposed alternative approach, called Testing Theory-based Quantitative Predictions, uses effect size estimates and confidence intervals to directly test predictions based on theory. This paper replicates findings from previous smoking studies and extends the approach to diet and sun protection behaviors using baseline data from a Transtheoretical Model behavioral intervention (N = 5407). Effect size predictions were developed using two methods: (1) applying refined effect size estimates from previous smoking research or (2) using predictions developed by an expert panel. Thirteen of 15 predictions were confirmed for smoking. For diet, 7 of 14 predictions were confirmed using smoking predictions and 6 of 16 using expert panel predictions. For sun protection, 3 of 11 predictions were confirmed using smoking predictions and 5 of 19 using expert panel predictions. Expert panel predictions and smoking-based predictions poorly predicted effect sizes for diet and sun protection constructs. Future studies should aim to use previous empirical data to generate predictions whenever possible. The best results occur when there have been several iterations of predictions for a behavior, such as with smoking, demonstrating that expected values begin to converge on the population effect size. Overall, the study supports necessity in strengthening and revising theory with empirical data.

Can We Predict Patient Wait Time?

Science.gov (United States)

Pianykh, Oleg S; Rosenthal, Daniel I

2015-10-01

The importance of patient wait-time management and predictability can hardly be overestimated: For most hospitals, it is the patient queues that drive and define every bit of clinical workflow. The objective of this work was to study the predictability of patient wait time and identify its most influential predictors. To solve this problem, we developed a comprehensive list of 25 wait-related parameters, suggested in earlier work and observed in our own experiments. All parameters were chosen as derivable from a typical Hospital Information System dataset. The parameters were fed into several time-predicting models, and the best parameter subsets, discovered through exhaustive model search, were applied to a large sample of actual patient wait data. We were able to discover the most efficient wait-time prediction factors and models, such as the line-size models introduced in this work. Moreover, these models proved to be equally accurate and computationally efficient. Finally, the selected models were implemented in our patient waiting areas, displaying predicted wait times on the monitors located at the front desks. The limitations of these models are also discussed. Optimal regression models based on wait-line sizes can provide accurate and efficient predictions for patient wait time. Copyright © 2015 American College of Radiology. Published by Elsevier Inc. All rights reserved.

PREDICTING DEMAND FOR COTTON YARNS

Directory of Open Access Journals (Sweden)

SALAS-MOLINA Francisco

2017-05-01

Full Text Available Predicting demand for fashion products is crucial for textile manufacturers. In an attempt to both avoid out-of-stocks and minimize holding costs, different forecasting techniques are used by production managers. Both linear and non-linear time-series analysis techniques are suitable options for forecasting purposes. However, demand for fashion products presents a number of particular characteristics such as short life-cycles, short selling seasons, high impulse purchasing, high volatility, low predictability, tremendous product variety and a high number of stock-keeping-units. In this paper, we focus on predicting demand for cotton yarns using a non-linear forecasting technique that has been fruitfully used in many areas, namely, random forests. To this end, we first identify a number of explanatory variables to be used as a key input to forecasting using random forests. We consider explanatory variables usually labeled either as causal variables, when some correlation is expected between them and the forecasted variable, or as time-series features, when extracted from time-related attributes such as seasonality. Next, we evaluate the predictive power of each variable by means of out-of-sample accuracy measurement. We experiment on a real data set from a textile company in Spain. The numerical results show that simple time-series features present more predictive ability than other more sophisticated explanatory variables.

Les voix de l’éthique : justice et care .

Directory of Open Access Journals (Sweden)

Nathalie Zaccaï-Reyners

2010-05-01

Full Text Available Le célèbre essai de Carol Gilligan paraît aujourd’hui dans une traduction revue et sous son titre original, redonnant toute sa place à la voix . Publié en 1982 aux États-Unis et disponible en français dès 1986 sous le titre Une si grande différence , les enjeux qui accompagnent cette nouvelle édition sont explicités dans la présentation , sous les plumes de Sandra Laugier et de Patricia Paperman. L’occasion de revenir sur les arguments centraux de cet essai et sur son ...

The North American Multi-Model Ensemble (NMME): Phase-1 Seasonal to Interannual Prediction, Phase-2 Toward Developing Intra-Seasonal Prediction

Science.gov (United States)

Kirtman, Ben P.; Min, Dughong; Infanti, Johnna M.; Kinter, James L., III; Paolino, Daniel A.; Zhang, Qin; vandenDool, Huug; Saha, Suranjana; Mendez, Malaquias Pena; Becker, Emily;

Does predictability matter? Effects of cue predictability on neurocognitive mechanisms underlying prospective memory

OpenAIRE

Cona, Giorgia; Arcara, Giorgio; Tarantino, Vincenza; Bisiacchi, Patrizia S.

2015-01-01

Prospective memory (PM) represents the ability to successfully realize intentions when the appropriate moment or cue occurs. In this study, we used event-related potentials (ERPs) to explore the impact of cue predictability on the cognitive and neural mechanisms supporting PM. Participants performed an ongoing task and, simultaneously, had to remember to execute a pre-specified action when they encountered the PM cues. The occurrence of the PM cues was predictable (being signaled by a warning...

Relationship between water temperature predictability and aquatic ...

African Journals Online (AJOL)

Macroinvertebrate taxonomic turnover across seasons was higher for sites having lower water temperature predictability values than for sites with higher predictability, while temporal partitioning was greater at sites with greater temperature variability. Macroinvertebrate taxa responded in a predictable manner to changes in ...

Genomic Prediction of Gene Bank Wheat Landraces

Directory of Open Access Journals (Sweden)

José Crossa

2016-07-01

Full Text Available This study examines genomic prediction within 8416 Mexican landrace accessions and 2403 Iranian landrace accessions stored in gene banks. The Mexican and Iranian collections were evaluated in separate field trials, including an optimum environment for several traits, and in two separate environments (drought, D and heat, H for the highly heritable traits, days to heading (DTH, and days to maturity (DTM. Analyses accounting and not accounting for population structure were performed. Genomic prediction models include genotype × environment interaction (G × E. Two alternative prediction strategies were studied: (1 random cross-validation of the data in 20% training (TRN and 80% testing (TST (TRN20-TST80 sets, and (2 two types of core sets, “diversity” and “prediction”, including 10% and 20%, respectively, of the total collections. Accounting for population structure decreased prediction accuracy by 15–20% as compared to prediction accuracy obtained when not accounting for population structure. Accounting for population structure gave prediction accuracies for traits evaluated in one environment for TRN20-TST80 that ranged from 0.407 to 0.677 for Mexican landraces, and from 0.166 to 0.662 for Iranian landraces. Prediction accuracy of the 20% diversity core set was similar to accuracies obtained for TRN20-TST80, ranging from 0.412 to 0.654 for Mexican landraces, and from 0.182 to 0.647 for Iranian landraces. The predictive core set gave similar prediction accuracy as the diversity core set for Mexican collections, but slightly lower for Iranian collections. Prediction accuracy when incorporating G × E for DTH and DTM for Mexican landraces for TRN20-TST80 was around 0.60, which is greater than without the G × E term. For Iranian landraces, accuracies were 0.55 for the G × E model with TRN20-TST80. Results show promising prediction accuracies for potential use in germplasm enhancement and rapid introgression of exotic germplasm

Influences of misprediction costs on solar flare prediction

Science.gov (United States)

Huang, Xin; Wang, HuaNing; Dai, XingHua

2012-10-01

The mispredictive costs of flaring and non-flaring samples are different for different applications of solar flare prediction. Hence, solar flare prediction is considered a cost sensitive problem. A cost sensitive solar flare prediction model is built by modifying the basic decision tree algorithm. Inconsistency rate with the exhaustive search strategy is used to determine the optimal combination of magnetic field parameters in an active region. These selected parameters are applied as the inputs of the solar flare prediction model. The performance of the cost sensitive solar flare prediction model is evaluated for the different thresholds of solar flares. It is found that more flaring samples are correctly predicted and more non-flaring samples are wrongly predicted with the increase of the cost for wrongly predicting flaring samples as non-flaring samples, and the larger cost of wrongly predicting flaring samples as non-flaring samples is required for the higher threshold of solar flares. This can be considered as the guide line for choosing proper cost to meet the requirements in different applications.

Machine learning methods for metabolic pathway prediction

Directory of Open Access Journals (Sweden)

Karp Peter D

2010-01-01

Full Text Available Abstract Background A key challenge in systems biology is the reconstruction of an organism's metabolic network from its genome sequence. One strategy for addressing this problem is to predict which metabolic pathways, from a reference database of known pathways, are present in the organism, based on the annotated genome of the organism. Results To quantitatively validate methods for pathway prediction, we developed a large "gold standard" dataset of 5,610 pathway instances known to be present or absent in curated metabolic pathway databases for six organisms. We defined a collection of 123 pathway features, whose information content we evaluated with respect to the gold standard. Feature data were used as input to an extensive collection of machine learning (ML methods, including naïve Bayes, decision trees, and logistic regression, together with feature selection and ensemble methods. We compared the ML methods to the previous PathoLogic algorithm for pathway prediction using the gold standard dataset. We found that ML-based prediction methods can match the performance of the PathoLogic algorithm. PathoLogic achieved an accuracy of 91% and an F-measure of 0.786. The ML-based prediction methods achieved accuracy as high as 91.2% and F-measure as high as 0.787. The ML-based methods output a probability for each predicted pathway, whereas PathoLogic does not, which provides more information to the user and facilitates filtering of predicted pathways. Conclusions ML methods for pathway prediction perform as well as existing methods, and have qualitative advantages in terms of extensibility, tunability, and explainability. More advanced prediction methods and/or more sophisticated input features may improve the performance of ML methods. However, pathway prediction performance appears to be limited largely by the ability to correctly match enzymes to the reactions they catalyze based on genome annotations.

Machine learning methods for metabolic pathway prediction

Science.gov (United States)

2010-01-01

Background A key challenge in systems biology is the reconstruction of an organism's metabolic network from its genome sequence. One strategy for addressing this problem is to predict which metabolic pathways, from a reference database of known pathways, are present in the organism, based on the annotated genome of the organism. Results To quantitatively validate methods for pathway prediction, we developed a large "gold standard" dataset of 5,610 pathway instances known to be present or absent in curated metabolic pathway databases for six organisms. We defined a collection of 123 pathway features, whose information content we evaluated with respect to the gold standard. Feature data were used as input to an extensive collection of machine learning (ML) methods, including naïve Bayes, decision trees, and logistic regression, together with feature selection and ensemble methods. We compared the ML methods to the previous PathoLogic algorithm for pathway prediction using the gold standard dataset. We found that ML-based prediction methods can match the performance of the PathoLogic algorithm. PathoLogic achieved an accuracy of 91% and an F-measure of 0.786. The ML-based prediction methods achieved accuracy as high as 91.2% and F-measure as high as 0.787. The ML-based methods output a probability for each predicted pathway, whereas PathoLogic does not, which provides more information to the user and facilitates filtering of predicted pathways. Conclusions ML methods for pathway prediction perform as well as existing methods, and have qualitative advantages in terms of extensibility, tunability, and explainability. More advanced prediction methods and/or more sophisticated input features may improve the performance of ML methods. However, pathway prediction performance appears to be limited largely by the ability to correctly match enzymes to the reactions they catalyze based on genome annotations. PMID:20064214

Reduce manual curation by combining gene predictions from multiple annotation engines, a case study of start codon prediction.

Directory of Open Access Journals (Sweden)

Thomas H A Ederveen

Full Text Available Nowadays, prokaryotic genomes are sequenced faster than the capacity to manually curate gene annotations. Automated genome annotation engines provide users a straight-forward and complete solution for predicting ORF coordinates and function. For many labs, the use of AGEs is therefore essential to decrease the time necessary for annotating a given prokaryotic genome. However, it is not uncommon for AGEs to provide different and sometimes conflicting predictions. Combining multiple AGEs might allow for more accurate predictions. Here we analyzed the ab initio open reading frame (ORF calling performance of different AGEs based on curated genome annotations of eight strains from different bacterial species with GC% ranging from 35-52%. We present a case study which demonstrates a novel way of comparative genome annotation, using combinations of AGEs in a pre-defined order (or path to predict ORF start codons. The order of AGE combinations is from high to low specificity, where the specificity is based on the eight genome annotations. For each AGE combination we are able to derive a so-called projected confidence value, which is the average specificity of ORF start codon prediction based on the eight genomes. The projected confidence enables estimating likeliness of a correct prediction for a particular ORF start codon by a particular AGE combination, pinpointing ORFs notoriously difficult to predict start codons. We correctly predict start codons for 90.5±4.8% of the genes in a genome (based on the eight genomes with an accuracy of 81.1±7.6%. Our consensus-path methodology allows a marked improvement over majority voting (9.7±4.4% and with an optimal path ORF start prediction sensitivity is gained while maintaining a high specificity.

Predicting birth weight with conditionally linear transformation models.

Science.gov (United States)

Möst, Lisa; Schmid, Matthias; Faschingbauer, Florian; Hothorn, Torsten

2016-12-01

Low and high birth weight (BW) are important risk factors for neonatal morbidity and mortality. Gynecologists must therefore accurately predict BW before delivery. Most prediction formulas for BW are based on prenatal ultrasound measurements carried out within one week prior to birth. Although successfully used in clinical practice, these formulas focus on point predictions of BW but do not systematically quantify uncertainty of the predictions, i.e. they result in estimates of the conditional mean of BW but do not deliver prediction intervals. To overcome this problem, we introduce conditionally linear transformation models (CLTMs) to predict BW. Instead of focusing only on the conditional mean, CLTMs model the whole conditional distribution function of BW given prenatal ultrasound parameters. Consequently, the CLTM approach delivers both point predictions of BW and fetus-specific prediction intervals. Prediction intervals constitute an easy-to-interpret measure of prediction accuracy and allow identification of fetuses subject to high prediction uncertainty. Using a data set of 8712 deliveries at the Perinatal Centre at the University Clinic Erlangen (Germany), we analyzed variants of CLTMs and compared them to standard linear regression estimation techniques used in the past and to quantile regression approaches. The best-performing CLTM variant was competitive with quantile regression and linear regression approaches in terms of conditional coverage and average length of the prediction intervals. We propose that CLTMs be used because they are able to account for possible heteroscedasticity, kurtosis, and skewness of the distribution of BWs. © The Author(s) 2014.

Nonlinear chaotic model for predicting storm surges

Directory of Open Access Journals (Sweden)

M. Siek

2010-09-01

Full Text Available This paper addresses the use of the methods of nonlinear dynamics and chaos theory for building a predictive chaotic model from time series. The chaotic model predictions are made by the adaptive local models based on the dynamical neighbors found in the reconstructed phase space of the observables. We implemented the univariate and multivariate chaotic models with direct and multi-steps prediction techniques and optimized these models using an exhaustive search method. The built models were tested for predicting storm surge dynamics for different stormy conditions in the North Sea, and are compared to neural network models. The results show that the chaotic models can generally provide reliable and accurate short-term storm surge predictions.

Cast iron - a predictable material

Directory of Open Access Journals (Sweden)

Jorg C. Sturm

2011-02-01

Full Text Available High strength compacted graphite iron (CGI or alloyed cast iron components are substituting previously used non-ferrous castings in automotive power train applications. The mechanical engineering industry has recognized the value in substituting forged or welded structures with stiff and light-weight cast iron castings. New products such as wind turbines have opened new markets for an entire suite of highly reliable ductile iron cast components. During the last 20 years, casting process simulation has developed from predicting hot spots and solidification to an integral assessment tool for foundries for the entire manufacturing route of castings. The support of the feeding related layout of the casting is still one of the most important duties for casting process simulation. Depending on the alloy poured, different feeding behaviors and self-feeding capabilities need to be considered to provide a defect free casting. Therefore, it is not enough to base the prediction of shrinkage defects solely on hot spots derived from temperature fields. To be able to quantitatively predict these defects, solidification simulation had to be combined with density and mass transport calculations, in order to evaluate the impact of the solidification morphology on the feeding behavior as well as to consider alloy dependent feeding ranges. For cast iron foundries, the use of casting process simulation has become an important instrument to predict the robustness and reliability of their processes, especially since the influence of alloying elements, melting practice and metallurgy need to be considered to quantify the special shrinkage and solidification behavior of cast iron. This allows the prediction of local structures, phases and ultimately the local mechanical properties of cast irons, to asses casting quality in the foundry but also to make use of this quantitative information during design of the casting. Casting quality issues related to thermally driven

Individualized prediction of perineural invasion in colorectal cancer: development and validation of a radiomics prediction model.

Science.gov (United States)

Huang, Yanqi; He, Lan; Dong, Di; Yang, Caiyun; Liang, Cuishan; Chen, Xin; Ma, Zelan; Huang, Xiaomei; Yao, Su; Liang, Changhong; Tian, Jie; Liu, Zaiyi

2018-02-01

To develop and validate a radiomics prediction model for individualized prediction of perineural invasion (PNI) in colorectal cancer (CRC). After computed tomography (CT) radiomics features extraction, a radiomics signature was constructed in derivation cohort (346 CRC patients). A prediction model was developed to integrate the radiomics signature and clinical candidate predictors [age, sex, tumor location, and carcinoembryonic antigen (CEA) level]. Apparent prediction performance was assessed. After internal validation, independent temporal validation (separate from the cohort used to build the model) was then conducted in 217 CRC patients. The final model was converted to an easy-to-use nomogram. The developed radiomics nomogram that integrated the radiomics signature and CEA level showed good calibration and discrimination performance [Harrell's concordance index (c-index): 0.817; 95% confidence interval (95% CI): 0.811-0.823]. Application of the nomogram in validation cohort gave a comparable calibration and discrimination (c-index: 0.803; 95% CI: 0.794-0.812). Integrating the radiomics signature and CEA level into a radiomics prediction model enables easy and effective risk assessment of PNI in CRC. This stratification of patients according to their PNI status may provide a basis for individualized auxiliary treatment.

Development of predictive weather scenarios for early prediction of rice yield in South Korea

Science.gov (United States)

Shin, Y.; Cho, J.; Jung, I.

2017-12-01

International grain prices are becoming unstable due to frequent occurrence of abnormal weather phenomena caused by climate change. Early prediction of grain yield using weather forecast data is important for stabilization of international grain prices. The APEC Climate Center (APCC) is providing seasonal forecast data based on monthly climate prediction models for global seasonal forecasting services. The 3-month and 6-month seasonal forecast data using the multi-model ensemble (MME) technique are provided in their own website, ADSS (APCC Data Service System, http://adss.apcc21.org/). The spatial resolution of seasonal forecast data for each individual model is 2.5°×2.5°(about 250km) and the time scale is created as monthly. In this study, we developed customized weather forecast scenarios that are combined seasonal forecast data and observational data apply to early rice yield prediction model. Statistical downscale method was applied to produce meteorological input data of crop model because field scale crop model (ORYZA2000) requires daily weather data. In order to determine whether the forecasting data is suitable for the crop model, we produced spatio-temporal downscaled weather scenarios and evaluated the predictability by comparison with observed weather data at 57 ASOS stations in South Korea. The customized weather forecast scenarios can be applied to various application fields not only early rice yield prediction. Acknowledgement This work was carried out with the support of "Cooperative Research Program for Agriculture Science and Technology Development (Project No: PJ012855022017)" Rural Development Administration, Republic of Korea.

Ensemble method for dengue prediction.

Science.gov (United States)

Buczak, Anna L; Baugher, Benjamin; Moniz, Linda J; Bagley, Thomas; Babin, Steven M; Guven, Erhan

2018-01-01

In the 2015 NOAA Dengue Challenge, participants made three dengue target predictions for two locations (Iquitos, Peru, and San Juan, Puerto Rico) during four dengue seasons: 1) peak height (i.e., maximum weekly number of cases during a transmission season; 2) peak week (i.e., week in which the maximum weekly number of cases occurred); and 3) total number of cases reported during a transmission season. A dengue transmission season is the 12-month period commencing with the location-specific, historical week with the lowest number of cases. At the beginning of the Dengue Challenge, participants were provided with the same input data for developing the models, with the prediction testing data provided at a later date. Our approach used ensemble models created by combining three disparate types of component models: 1) two-dimensional Method of Analogues models incorporating both dengue and climate data; 2) additive seasonal Holt-Winters models with and without wavelet smoothing; and 3) simple historical models. Of the individual component models created, those with the best performance on the prior four years of data were incorporated into the ensemble models. There were separate ensembles for predicting each of the three targets at each of the two locations. Our ensemble models scored higher for peak height and total dengue case counts reported in a transmission season for Iquitos than all other models submitted to the Dengue Challenge. However, the ensemble models did not do nearly as well when predicting the peak week. The Dengue Challenge organizers scored the dengue predictions of the Challenge participant groups. Our ensemble approach was the best in predicting the total number of dengue cases reported for transmission season and peak height for Iquitos, Peru.

Evoked emotions predict food choice.

Science.gov (United States)

Dalenberg, Jelle R; Gutjar, Swetlana; Ter Horst, Gert J; de Graaf, Kees; Renken, Remco J; Jager, Gerry

2014-01-01

In the current study we show that non-verbal food-evoked emotion scores significantly improve food choice prediction over merely liking scores. Previous research has shown that liking measures correlate with choice. However, liking is no strong predictor for food choice in real life environments. Therefore, the focus within recent studies shifted towards using emotion-profiling methods that successfully can discriminate between products that are equally liked. However, it is unclear how well scores from emotion-profiling methods predict actual food choice and/or consumption. To test this, we proposed to decompose emotion scores into valence and arousal scores using Principal Component Analysis (PCA) and apply Multinomial Logit Models (MLM) to estimate food choice using liking, valence, and arousal as possible predictors. For this analysis, we used an existing data set comprised of liking and food-evoked emotions scores from 123 participants, who rated 7 unlabeled breakfast drinks. Liking scores were measured using a 100-mm visual analogue scale, while food-evoked emotions were measured using 2 existing emotion-profiling methods: a verbal and a non-verbal method (EsSense Profile and PrEmo, respectively). After 7 days, participants were asked to choose 1 breakfast drink from the experiment to consume during breakfast in a simulated restaurant environment. Cross validation showed that we were able to correctly predict individualized food choice (1 out of 7 products) for over 50% of the participants. This number increased to nearly 80% when looking at the top 2 candidates. Model comparisons showed that evoked emotions better predict food choice than perceived liking alone. However, the strongest predictive strength was achieved by the combination of evoked emotions and liking. Furthermore we showed that non-verbal food-evoked emotion scores more accurately predict food choice than verbal food-evoked emotions scores.

Ensemble method for dengue prediction.

Directory of Open Access Journals (Sweden)

Anna L Buczak

Full Text Available In the 2015 NOAA Dengue Challenge, participants made three dengue target predictions for two locations (Iquitos, Peru, and San Juan, Puerto Rico during four dengue seasons: 1 peak height (i.e., maximum weekly number of cases during a transmission season; 2 peak week (i.e., week in which the maximum weekly number of cases occurred; and 3 total number of cases reported during a transmission season. A dengue transmission season is the 12-month period commencing with the location-specific, historical week with the lowest number of cases. At the beginning of the Dengue Challenge, participants were provided with the same input data for developing the models, with the prediction testing data provided at a later date.Our approach used ensemble models created by combining three disparate types of component models: 1 two-dimensional Method of Analogues models incorporating both dengue and climate data; 2 additive seasonal Holt-Winters models with and without wavelet smoothing; and 3 simple historical models. Of the individual component models created, those with the best performance on the prior four years of data were incorporated into the ensemble models. There were separate ensembles for predicting each of the three targets at each of the two locations.Our ensemble models scored higher for peak height and total dengue case counts reported in a transmission season for Iquitos than all other models submitted to the Dengue Challenge. However, the ensemble models did not do nearly as well when predicting the peak week.The Dengue Challenge organizers scored the dengue predictions of the Challenge participant groups. Our ensemble approach was the best in predicting the total number of dengue cases reported for transmission season and peak height for Iquitos, Peru.

Does predictability matter? Effects of cue predictability on neurocognitive mechanisms underlying prospective memory.

Science.gov (United States)

Cona, Giorgia; Arcara, Giorgio; Tarantino, Vincenza; Bisiacchi, Patrizia S

2015-01-01

Prospective memory (PM) represents the ability to successfully realize intentions when the appropriate moment or cue occurs. In this study, we used event-related potentials (ERPs) to explore the impact of cue predictability on the cognitive and neural mechanisms supporting PM. Participants performed an ongoing task and, simultaneously, had to remember to execute a pre-specified action when they encountered the PM cues. The occurrence of the PM cues was predictable (being signaled by a warning cue) for some participants and was completely unpredictable for others. In the predictable cue condition, the behavioral and ERP correlates of strategic monitoring were observed mainly in the ongoing trials wherein the PM cue was expected. In the unpredictable cue condition they were instead shown throughout the whole PM block. This pattern of results suggests that, in the predictable cue condition, participants engaged monitoring only when subjected to a context wherein the PM cue was expected, and disengaged monitoring when the PM cue was not expected. Conversely, participants in the unpredictable cue condition distributed their resources for strategic monitoring in more continuous manner. The findings of this study support the most recent views-the "Dynamic Multiprocess Framework" and the "Attention to Delayed Intention" (AtoDI) model-confirming that strategic monitoring is a flexible mechanism that is recruited mainly when a PM cue is expected and that may interact with bottom-up spontaneous processes.

Modeling Seizure Self-Prediction: An E-Diary Study

Science.gov (United States)

Haut, Sheryl R.; Hall, Charles B.; Borkowski, Thomas; Tennen, Howard; Lipton, Richard B.

2013-01-01

Purpose A subset of patients with epilepsy successfully self-predicted seizures in a paper diary study. We conducted an e-diary study to ensure that prediction precedes seizures, and to characterize the prodromal features and time windows that underlie self-prediction. Methods Subjects 18 or older with LRE and ≥3 seizures/month maintained an e-diary, reporting AM/PM data daily, including mood, premonitory symptoms, and all seizures. Self-prediction was rated by, “How likely are you to experience a seizure [time frame]”? Five choices ranged from almost certain (>95% chance) to very unlikely. Relative odds of seizure (OR) within time frames was examined using Poisson models with log normal random effects to adjust for multiple observations. Key Findings Nineteen subjects reported 244 eligible seizures. OR for prediction choices within 6hrs was as high as 9.31 (1.92,45.23) for “almost certain”. Prediction was most robust within 6hrs of diary entry, and remained significant up to 12hrs. For 9 best predictors, average sensitivity was 50%. Older age contributed to successful self-prediction, and self-prediction appeared to be driven by mood and premonitory symptoms. In multivariate modeling of seizure occurrence, self-prediction (2.84; 1.68,4.81), favorable change in mood (0.82; 0.67,0.99) and number of premonitory symptoms (1,11; 1.00,1.24) were significant. Significance Some persons with epilepsy can self-predict seizures. In these individuals, the odds of a seizure following a positive prediction are high. Predictions were robust, not attributable to recall bias, and were related to self awareness of mood and premonitory features. The 6-hour prediction window is suitable for the development of pre-emptive therapy. PMID:24111898

Evaluation of environmental impact predictions

International Nuclear Information System (INIS)

Cunningham, P.A.; Adams, S.M.; Kumar, K.D.

1977-01-01

An analysis and evaluation of the ecological monitoring program at the Surry Nuclear Power Plant showed that predictions of potential environmental impact made in the Final Environmental Statement (FES), which were based on generally accepted ecological principles, were not completely substantiated by environmental monitoring data. The Surry Nuclear Power Plant (Units 1 and 2) was chosen for study because of the facility's relatively continuous operating history and the availability of environmental data adequate for analysis. Preoperational and operational fish monitoring data were used to assess the validity of the FES prediction that fish would congregate in the thermal plume during winter months and would avoid the plume during summer months. Analysis of monitoring data showed that fish catch per unit effort (CPE) was generally high in the thermal plume during winter months; however, the highest fish catches occurred in the plume during the summer. Possible explanations for differences between the FES prediction and results observed in analysis of monitoring data are discussed, and general recommendations are outlined for improving impact assessment predictions

Prediction of natural gas consumption

International Nuclear Information System (INIS)

Zhang, R.L.; Walton, D.J.; Hoskins, W.D.

1993-01-01

Distributors of natural gas need to predict future consumption in order to purchase a sufficient supply on contract. Distributors that offer their customers equal payment plans need to predict the consumption of each customer 12 months in advance. Estimates of previous consumption are often used for months when meters are inaccessible, or bimonthly-read meters. Existing methods of predicting natural gas consumption, and a proposed new method for each local region are discussed. The proposed model distinguishes the consumption load factors from summer to other seasons by attempting to adjust them by introducing two parameters. The problem is then reduced to a quadratic programming problem. However, since it is not necessary to use both parameters simultaneously, the problem can be solved with a simple iterative procedure. Results show that the new model can improve the two-equation model to a certain scale. The adjustment to heat load factor can reduce the error of prediction markedly while that to base load factor influences the error marginally. 3 refs., 11 figs., 2 tabs

NetTurnP--neural network prediction of beta-turns by use of evolutionary information and predicted protein sequence features.

Directory of Open Access Journals (Sweden)

Bent Petersen

Full Text Available UNLABELLED: β-turns are the most common type of non-repetitive structures, and constitute on average 25% of the amino acids in proteins. The formation of β-turns plays an important role in protein folding, protein stability and molecular recognition processes. In this work we present the neural network method NetTurnP, for prediction of two-class β-turns and prediction of the individual β-turn types, by use of evolutionary information and predicted protein sequence features. It has been evaluated against a commonly used dataset BT426, and achieves a Matthews correlation coefficient of 0.50, which is the highest reported performance on a two-class prediction of β-turn and not-β-turn. Furthermore NetTurnP shows improved performance on some of the specific β-turn types. In the present work, neural network methods have been trained to predict β-turn or not and individual β-turn types from the primary amino acid sequence. The individual β-turn types I, I', II, II', VIII, VIa1, VIa2, VIba and IV have been predicted based on classifications by PROMOTIF, and the two-class prediction of β-turn or not is a superset comprised of all β-turn types. The performance is evaluated using a golden set of non-homologous sequences known as BT426. Our two-class prediction method achieves a performance of: MCC=0.50, Qtotal=82.1%, sensitivity=75.6%, PPV=68.8% and AUC=0.864. We have compared our performance to eleven other prediction methods that obtain Matthews correlation coefficients in the range of 0.17-0.47. For the type specific β-turn predictions, only type I and II can be predicted with reasonable Matthews correlation coefficients, where we obtain performance values of 0.36 and 0.31, respectively. CONCLUSION: The NetTurnP method has been implemented as a webserver, which is freely available at http://www.cbs.dtu.dk/services/NetTurnP/. NetTurnP is the only available webserver that allows submission of multiple sequences.

NetTurnP--neural network prediction of beta-turns by use of evolutionary information and predicted protein sequence features.

Science.gov (United States)

Petersen, Bent; Lundegaard, Claus; Petersen, Thomas Nordahl

2010-11-30

β-turns are the most common type of non-repetitive structures, and constitute on average 25% of the amino acids in proteins. The formation of β-turns plays an important role in protein folding, protein stability and molecular recognition processes. In this work we present the neural network method NetTurnP, for prediction of two-class β-turns and prediction of the individual β-turn types, by use of evolutionary information and predicted protein sequence features. It has been evaluated against a commonly used dataset BT426, and achieves a Matthews correlation coefficient of 0.50, which is the highest reported performance on a two-class prediction of β-turn and not-β-turn. Furthermore NetTurnP shows improved performance on some of the specific β-turn types. In the present work, neural network methods have been trained to predict β-turn or not and individual β-turn types from the primary amino acid sequence. The individual β-turn types I, I', II, II', VIII, VIa1, VIa2, VIba and IV have been predicted based on classifications by PROMOTIF, and the two-class prediction of β-turn or not is a superset comprised of all β-turn types. The performance is evaluated using a golden set of non-homologous sequences known as BT426. Our two-class prediction method achieves a performance of: MCC=0.50, Qtotal=82.1%, sensitivity=75.6%, PPV=68.8% and AUC=0.864. We have compared our performance to eleven other prediction methods that obtain Matthews correlation coefficients in the range of 0.17-0.47. For the type specific β-turn predictions, only type I and II can be predicted with reasonable Matthews correlation coefficients, where we obtain performance values of 0.36 and 0.31, respectively. The NetTurnP method has been implemented as a webserver, which is freely available at http://www.cbs.dtu.dk/services/NetTurnP/. NetTurnP is the only available webserver that allows submission of multiple sequences.

SEIZURE PREDICTION: THE FOURTH INTERNATIONAL WORKSHOP

Science.gov (United States)

Zaveri, Hitten P.; Frei, Mark G.; Arthurs, Susan; Osorio, Ivan

2010-01-01

The recently convened Fourth International Workshop on Seizure Prediction (IWSP4) brought together a diverse international group of investigators, from academia and industry, including epileptologists, neurosurgeons, neuroscientists, computer scientists, engineers, physicists, and mathematicians who are conducting interdisciplinary research on the prediction and control of seizures. IWSP4 allowed the presentation and discussion of results, an exchange of ideas, an assessment of the status of seizure prediction, control and related fields and the fostering of collaborative projects. PMID:20674508

Predicting Process Behaviour using Deep Learning

OpenAIRE

Evermann, Joerg; Rehse, Jana-Rebecca; Fettke, Peter

2016-01-01

Predicting business process behaviour is an important aspect of business process management. Motivated by research in natural language processing, this paper describes an application of deep learning with recurrent neural networks to the problem of predicting the next event in a business process. This is both a novel method in process prediction, which has largely relied on explicit process models, and also a novel application of deep learning methods. The approach is evaluated on two real da...

Sports Tournament Predictions Using Direct Manipulation

OpenAIRE

Vuillemot , Romain; Perin , Charles

2016-01-01

An advanced interface for sports tournament predictions uses direct manipulation to allow users to make nonlinear predictions. Unlike previous interface designs, the interface helps users focus on their prediction tasks by enabling them to first choose a winner and then fill out the rest of the bracket. In real-world tests of the proposed interface (for the 2014 FIFA World Cup tournament and 2015/2016 UEFA Champions League), the authors validated the use of direct manipulation as an alternati...

Applications for predictive microbiology to food packaging

Science.gov (United States)

Predictive microbiology has been used for several years in the food industry to predict microbial growth, inactivation and survival. Predictive models provide a useful tool in risk assessment, HACCP set-up and GMP for the food industry to enhance microbial food safety. This report introduces the c...