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Relevant bibliographies by topics / Models of disorder

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Academic literature on the topic 'Models of disorder'

Author: Grafiati

Published: 4 June 2021

Last updated: 13 February 2022

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Journal articles on the topic "Models of disorder"

1

Csahok, Z., and T. Vicsek. "Traffic models with disorder." Journal of Physics A: Mathematical and General 27, no. 16 (August 21, 1994): L591—L596. http://dx.doi.org/10.1088/0305-4470/27/16/005.

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Mack, Avram H. "Models for Mental Disorder." Journal of Nervous and Mental Disease 203, no. 12 (December 2015): 977. http://dx.doi.org/10.1097/nmd.0000000000000403.

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Haslam, Nick. "Categorical Versus Dimensional Models of Mental Disorder: The Taxometric Evidence." Australian & New Zealand Journal of Psychiatry 37, no. 6 (December 2003): 696–704. http://dx.doi.org/10.1080/j.1440-1614.2003.01258.x.

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Objective: To review studies of the categorical versus dimensional status of mental disorders that employ taxometric methodology. Method: A comprehensive qualitative review of all published taxometric studies of psychopathology. Results: Categorical and dimensional models each receive well-replicated support for some groups of mental disorders. Studies favour categorical models for melancholia, eating disorders, pathological dissociation, and schizotypal and antisocial personality disorders. Dimensional models tend to be favoured for the broad neurotic spectrum – general depression, generalized anxiety, posttraumatic stress disorder – and for borderline personality disorder. Conclusions: Taxometric research clarifies the latent structure of psychopathology in ways that have implications for the classification, assessment, explanation and conceptualization of mental disorder

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Jenkins, Rachel. "Models for Mental Disorder, Conceptual Models in Psychiatry." International Clinical Psychopharmacology 3, no. 1 (January 1988): 91–92. http://dx.doi.org/10.1097/00004850-198801000-00014.

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Olivier, B. "Animal models of panic disorder." Behavioural Pharmacology 8, no. 6 (November 1997): 661. http://dx.doi.org/10.1097/00008877-199711000-00066.

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Kato, Tadafumi, Mie Kubota, and Takaoki Kasahara. "Animal models of bipolar disorder." Neuroscience & Biobehavioral Reviews 31, no. 6 (January 2007): 832–42. http://dx.doi.org/10.1016/j.neubiorev.2007.03.003.

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Silva, Rhayra Xavier do Carmo, Sueslene Prado Rocha, Anderson Manoel Herculano, Monica Gomes Lima-Maximino, and Caio Maximino. "Animal models for panic disorder." Psychology & Neuroscience 13, no. 1 (March 2020): 1–18. http://dx.doi.org/10.1037/pne0000177.

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Galvez, Juan F., Ives C. Passos, Flavio P. Kapczinski, and Jair C. Soares. "Staging Models in Bipolar Disorder." FOCUS 13, no. 1 (January 2015): 19–24. http://dx.doi.org/10.1176/appi.focus.130110.

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Trull, Timothy J. "Dimensional models of personality disorder." Current Opinion in Psychiatry 13, no. 2 (March 2000): 179–84. http://dx.doi.org/10.1097/00001504-200003000-00007.

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D’Agostino, Alessandra, Mario Rossi Monti, and Vladan Starcevic. "Models of borderline personality disorder." Current Opinion in Psychiatry 31, no. 1 (January 2018): 57–62. http://dx.doi.org/10.1097/yco.0000000000000374.

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Dissertations / Theses on the topic "Models of disorder"

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Harris, Rosemary J. "Disorder in non-equilibrium models." Thesis, University of Oxford, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.408687.

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Samuel, Douglas B. "COMPARING PERSONALITY DISORDER MODELS: FFM AND DSM-IV-TR." Lexington, Ky. : [University of Kentucky Libraries], 2008. http://hdl.handle.net/10225/884.

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Thesis (Ph. D.)--University of Kentucky, 2008.
Title from document title page (viewed on October 30, 2008). Document formatted into pages; contains: vi, 43 p. Includes abstract and vita. Includes bibliographical references (p. 33-39).

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Giblin, Kathryn Anne. "Is epilepsy a preventable disorder? New evidence from animal models." Yale University, 2010. http://ymtdl.med.yale.edu/theses/available/etd-03052010-144943/.

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Epilepsy accounts for 0.5% of the global burden of disease, and primary prevention of epilepsy represents one of the three 2007 NINDS Epilepsy Research Benchmarks. Efforts to understand and intervene in the process of epileptogenesis have yielded fruitful preventative strategies in animal models. This article reviews the current understanding of epileptogenesis, introduces the concept of a "critical period" for epileptogenesis, and examines strategies for epilepsy prevention in animal models of both acquired and genetic epilepsies. As proof of principle, we investigated whether early preventative treatment during epileptogenesis in the WAG/Rij rat model of primary generalized epilepsy would persistently suppress the epilepsy phenotype in adulthood. Oral ethosuximide was given from age p21 to 5 months, covering the established period for epileptogenesis in this model. We then assessed the epilepsy phenotype by performing electroencephpalogram (EEG) recordings at serial time points after treatment cessation and by immunocytochemically measuring the cortical expression of ion channels Nav1.1, Nav1.6, and HCN1, which are dysregulated in epileptic WAG/Rij rats. Treatment both persistently suppressed seizures, even up to 3 months after treatment cessation, and blocked ion channel dysregulation. These findings indicated that treatment during epileptogenesis prevented the development of the epileptic phenotype. Subsequently, we investigated the C3H/HeJ mouse model of genetic epilepsy as a candidate for future studies in preventative treatment during epileptogenesis. Serial EEG recordings were performed from p5 to 3 months of age. We found that C3H/HeJ mice underwent three distinct, stereotyped phases of seizure development, which suggests that this model would be an appropriate candidate for future research on prevention of epileptogenesis.

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Jeans, Aruna. "The peripheral immune system of glycosphingolipid storage disorder mouse models." Thesis, University of Oxford, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.432342.

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Arnold, Wolfram Till. "Theory of electron localization in disordered systems /." view abstract or download file of text, 2000. http://wwwlib.umi.com/cr/uoregon/fullcit?p9986736.

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Thesis (Ph. D.)--University of Oregon, 2000.
Typescript. Includes vita and abstract. Includes bibliographical references (leaves 199-204). Also available for download via the World Wide Web; free to UO users.

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Bower, Peter John. "Attitudes, models and the detection of psychiatric disorder in general practice." Thesis, St George's, University of London, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.307454.

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Guida, Domenico. "Localization and mobility-edges in non-interacting fermionic models with disorder." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2016. http://amslaurea.unibo.it/10453/.

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Nel corso degli ultimi decenni la fisica sperimentale ha raggiunto notevoli traguardi nel campo della manipolazione di sistemi di atomi freddi, riaccendendo l'interesse della ricerca su sistemi a lungo studiati teoricamente, ma fino a poco tempo fa impossibili da realizzare sperimentalmente. Questa riaccesa attenzione ha permesso di sfruttare le moderne capacità di calcolo per studiare sistemi quantistici che ancora risultano di difficile realizzazione. In questo contesto si inserisce il rinnovato interesse per i sistemi quantistici monodimensionali caratterizzati dalla presenza di potenziale disordinato. Questi presentano proprietà di trasporto particolari e sotto particolari condizioni sono oggetto di una transizione di localizzazione. La maggior parte degli studi in questo campo rivolgono la loro attenzione a sistemi di particelle fermioniche interagenti. In questo lavoro di tesi analizziamo, invece, sistemi quantistici fermionici non interagenti, mettendo in luce quanto già noto e proponendo strumenti di analisi derivati dallo studio dei sistemi interagenti. In particolare, proponiamo un'analisi statistica dei livelli energetici e poniamo le basi per futuri studi a riguardo.

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Perondi, Leonel Fernando. "Theoretical studies of diffusion in disordered systems." Thesis, University of Oxford, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.334896.

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Okello, Elialilia Sarikiaeli. "Cultural explanatory models of depression in Uganda /." Stockholm, 2006. http://diss.kib.ki.se/2006/91-7140-823-1/.

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Loureiro, Bruno. "Disorder in holographic field theories : inhomogeneous geometries, momentum relaxation and SYK models." Thesis, University of Cambridge, 2018. https://www.repository.cam.ac.uk/handle/1810/277911.

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Holographic dualities are now an established tool in the study of universal properties of strongly coupled field theories. Yet, theories without translational symmetry are still poorly understood in this context. In this dissertation, we investigate three new approaches to this challenging problem. The first part of the dissertation concerns a class of phenomenological holographic models in which momentum relaxation can be achieved without breaking translational symmetry in the dual geometry. In particular, we focus on an example in which the dual geometry is similar to anti-de Sitter (AdS) Brans-Dicke theory. We study the thermodynamic and transport properties of the model and show that for strong momentum relaxation and low temperatures the model has insulator-like behaviour. In the second part, we go beyond the effective description and consider holographic theories which explicitly break translational symmetry. From the perspective of gravity, these theories translate to geometries that vary explicitly in the boundary space-like coordinates. We refer to these geometries as 'inhomogeneous' and investigate two approaches to study them. The first is motivated by the question: "what happens to a homogeneous geometry when coupled with a field varying randomly in space?". Starting from an AdS geometry at zero or finite temperature, we show that a spatially varying random Maxwell potential drives the dual field theory to a non-trivial infra-red fixed point characterised by an emerging scale invariance. Thermodynamic and transport properties of this disordered ground state are also discussed. The second is motivated by the complementary question: "how does a random geometry affect a probe field?". In the weak disorder limit, we show that disorder induces an additional power-law decay in the dual correlation functions. For certain choices of geometry profile, this contribution becomes dominant in the infra-red, indicating the breaking of perturbation theory and the possible existence of a phase transition induced by disorder. The third and last part of this dissertation switches from the gravity to the field theoretical side of the duality. We discuss the Sachdev-Ye-Kitaev (SYK) model, a disordered many-body model with distinctive black hole-like properties. We provide analytical and numerical evidence that these holographic properties are robust against a natural one-body deformation for a finite range of parameters. Outside this interval, this system undergoes a chaotic-integrable transition.

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Books on the topic "Models of disorder"

1

Tyrer, Peter J. Models for Mental Disorder. New York: John Wiley & Sons, Ltd., 2006.

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Tyrer, Peter J. Models for mental disorder: Conceptual models in psychiatry. Chichester: Wiley, 1987.

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Tyrer, Peter J. Models for mental disorder: Conceptual models in psychiatry. 3rd ed. Chichester: John Wiley, 1998.

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Tyrer, Peter J. Models for mental disorder: Conceptual models in psychiatry. 2nd ed. Chichester: J. Wiley, 1993.

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Derek, Steinberg, ed. Models for mental disorder: Conceptual models in psychiatry. 4th ed. Chichester, England: John Wiley & Sons, 2005.

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Tyrer, Peter J. Models for mental disorder: Conceptual models in psychiatry. Chichester, West Sussex: John Wiley & Sons, 2014.

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A, Salinas Silvio R., ed. Disorder and competition in soluble lattice models. Singapore: World Scientific, 1993.

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Romanczyk, Raymond G., and John McEachin, eds. Comprehensive Models of Autism Spectrum Disorder Treatment. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-40904-7.

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9

C, Charmet J., Roux Stéphane, and Guyon Etienne, eds. Disorder and fracture. New York: Plenum Press, 1990.

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Hicks, Trevor J. Magnetism in disorder. Oxford: Clarendon Press, 1995.

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Book chapters on the topic "Models of disorder"

1

Cocker, Paul J., and Catharine A. Winstanley. "Animal Models of Gambling-Related Behaviour." In Gambling Disorder, 101–25. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-03060-5_6.

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Davey, Graham, Suzanne Dash, and Frances Meeten. "Biological Models of OCD." In Obsessive Compulsive Disorder, 96–118. London: Macmillan Education UK, 2014. http://dx.doi.org/10.1007/978-1-137-30869-6_6.

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Le Moal, Michel. "Addictive Disorder: Animal Models." In Encyclopedia of Psychopharmacology, 1–10. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-27772-6_137-2.

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Scherrmann, Jean-Michel, Kim Wolff, Christine A. Franco, Marc N. Potenza, Tayfun Uzbay, Lisiane Bizarro, David C. S. Roberts, et al. "Addictive Disorder: Animal Models." In Encyclopedia of Psychopharmacology, 20–28. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-540-68706-1_137.

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Le Moal, Michel. "Addictive Disorder: Animal Models." In Encyclopedia of Psychopharmacology, 26–34. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-642-36172-2_137.

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Stollmann, Peter. "Analysis of Anderson-type Models." In Caught by Disorder, 37–67. Boston, MA: Birkhäuser Boston, 2001. http://dx.doi.org/10.1007/978-1-4612-0169-4_2.

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Portman, Michael E. "Conceptual Models." In Generalized Anxiety Disorder Across the Lifespan, 31–39. New York, NY: Springer New York, 2009. http://dx.doi.org/10.1007/978-0-387-89243-6_3.

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Meakin, Paul, Gang Li, Leonard M. Sander, Hong Yan, Francisco Guinea, Oscar Pla, and Enrique Louis. "Simple Stochastic Models for Material Failure." In Disorder and Fracture, 119–40. Boston, MA: Springer US, 1990. http://dx.doi.org/10.1007/978-1-4615-6864-3_8.

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Singh, Shamsher, Onkar Bedi, Ganesh Singh Bhakuni, and Puneet Kumar Bansal. "Animal Models of Sleep Disorder." In Animal Models of Neurological Disorders, 181–94. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-5981-0_12.

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Gottfredson, Gary D., and Denise C. Gottfredson. "Alternative Models of School Disorder." In Victimization in Schools, 137–69. Boston, MA: Springer US, 1985. http://dx.doi.org/10.1007/978-1-4684-4985-3_11.

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Conference papers on the topic "Models of disorder"

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Biscari, P., and G. Capriz. "Temperance for order/disorder transition in nematics." In Mathematical Models and Methods for Smart Materials. WORLD SCIENTIFIC, 2002. http://dx.doi.org/10.1142/9789812776273_0001.

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"Bayesian Prognostic Model for Genomic Discovery in Bipolar Disorder." In International Conference on Bioinformatics Models, Methods and Algorithms. SCITEPRESS - Science and and Technology Publications, 2014. http://dx.doi.org/10.5220/0004642100910098.

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Szczepaniak, Adam. "Schwinger-Dyson equations in models with disorder." In International Workshop on QCD Green's Functions, Confinement and Phenomenology. Trieste, Italy: Sissa Medialab, 2012. http://dx.doi.org/10.22323/1.136.0045.

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TONINELLI, FABIO L. "DISORDER RELEVANCE FOR PINNING/WETTING MODELS: A REVIEW." In XVIth International Congress on Mathematical Physics. WORLD SCIENTIFIC, 2010. http://dx.doi.org/10.1142/9789814304634_0025.

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Tsvelik, Alexei. "Critical models of disorder in 2 spatial dimensions." In Non-perturbative Quantum Effects 2000. Trieste, Italy: Sissa Medialab, 2000. http://dx.doi.org/10.22323/1.006.0045.

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Guhr, Thomas, and Thomas Wilke. "Disorder and Quantum Chromodynamics — Non-Linear σ Models." In Proceedings of Nobel Symposium 116. WORLD SCIENTIFIC, 2001. http://dx.doi.org/10.1142/9789812811004_0017.

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Deng, Tingyan. "Classifying Autism Spectrum Disorder using Machine Learning Models." In 7th International Conference on Advances in Computer Science and Information Technology (ACSTY 2021). AIRCC Publishing Corporation, 2021. http://dx.doi.org/10.5121/csit.2021.110306.

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Autistic Spectrum Disorder (ASD) is a developmental disability, which can affect communication and behavior, causing significant social, communication, and behavior challenge. From a rare childhood disorder, ASD has evolved into a disorder that is found, according to the National Institute of Health, in 1% to 2% of the population in high income countries. A potential early and accurate diagnosis can not only help doctors to find the disease early, leading to a more on time treatment to the patient, but also can save significant healthcare costs for the patients. With the rapid growth of ASD cases, many open-source ASD related datasets were created for scientists and doctors to investigate this disease. Autistic Spectrum Disorder Screening Data for Adult is a well-known dataset, which contains 20 features to be utilized for further analysis on the potential cause and prediction of ASD. In this paper, we developed an Autism classification algorithm based on logistic regression model. Our model starts with featuring engineering to extract deep information from the dataset and then applied a modified logistic regression classifier to the data. The model can predict the ASD in an average F1 score of 0.97, which displays the superiority and feasibility of the proposed model. Besides, the data visualization technique was used to displays several feature distributions images for people to better understand the data and related feature engineering.

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Baranwal, Astha, and M. Vanitha. "Autistic Spectrum Disorder Screening: Prediction with Machine Learning Models." In 2020 International Conference on Emerging Trends in Information Technology and Engineering (ic-ETITE). IEEE, 2020. http://dx.doi.org/10.1109/ic-etite47903.2020.186.

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Constantinides, Marios, Jonas Busk, Aleksandar Matic, Maria Faurholt-Jepsen, Lars Vedel Kessing, and Jakob E. Bardram. "Personalized versus Generic Mood Prediction Models in Bipolar Disorder." In UbiComp '18: The 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3267305.3267536.

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Alexander-Uribe, Jonny, Julián D. Arias-Londoño, and Alexandre Perera-Lluna. "Protein Disorder Prediction using Jumping Motifs from Torsion Angles Dynamics in Ramachandran Plots." In 9th International Conference on Bioinformatics Models, Methods and Algorithms. SCITEPRESS - Science and Technology Publications, 2018. http://dx.doi.org/10.5220/0006647900380048.

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Reports on the topic "Models of disorder"

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Gupta, Shweta. The Disorder That Makes One Age 7 Times Faster. Science Repository OÜ, November 2020. http://dx.doi.org/10.31487/sr.blog.13.

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In addition to the implications for the diagnosis and conceivable treatment of progeria, the revelation of this model’s underlying genetics of premature aging may assist in revealing new insight into people s normal aging process

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Browne, Susan E. Bioenergetic Defects and Oxidative Damage in Transgenic Mouse Models of Neurodegenerative Disorders. Fort Belvoir, VA: Defense Technical Information Center, June 2005. http://dx.doi.org/10.21236/ada460659.

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Browne, Susan E. Bioenergetic Defects and Oxidative Damage in Transgenic Mouse Models of Neurodegenerative Disorders. Fort Belvoir, VA: Defense Technical Information Center, May 2003. http://dx.doi.org/10.21236/ada419306.

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Browne, Susan E. Bioenergetic Defects and Oxidative Damage in Transgenic Mouse Models of Neurodegenerative Disorders. Fort Belvoir, VA: Defense Technical Information Center, May 2004. http://dx.doi.org/10.21236/ada430585.

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Green, Jessica. A Paradigm Shift: From a Categorical to Dimensional Diagnostic Model of Personality Disorder. Portland State University Library, January 2015. http://dx.doi.org/10.15760/honors.178.

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MOSKALENKO, OLGA, and ROMAN YASKEVICH. ANXIETY-DEPRESSIVE DISORDERS IN PATIENTS WITH ARTERIAL HYPERTENSION. Science and Innovation Center Publishing House, March 2021. http://dx.doi.org/10.12731/2658-4034-2021-12-1-2-185-190.

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Our article presents a review of the literature and considers the most pressing problem of modern medicine - a combination of anxiety-depressive states in patients with cardiovascular diseases, which are more common in people of working age, having a negative impact on the quality of life of patients, contributing to the deterioration of physical, mental and social adaptation, which further leads to negative socio-economic consequences.

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Yang, Ruoting, Jr Daigle, Muhie Bernie J., Hammamieh Seid Y., Jett Rasha, Petzold Marti, Doyle Linda, and Francis J. III. Core Modular Blood and Brain Biomarkers in Social Defeat Mouse Model for Post Traumatic Stress Disorder. Fort Belvoir, VA: Defense Technical Information Center, August 2013. http://dx.doi.org/10.21236/ada596945.

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Lavrova, Galina, Natalia Tulupova, and Julia Zabolotneva. Model adapted core preschool education program for early and preschool children with autism spectrum disorders. ChIPPKRO, 2020. http://dx.doi.org/10.12731/educationprogram.

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Dutra, Lauren M., Matthew C. Farrelly, Brian Bradfield, Jamie Ridenhour, and Jamie Guillory. Modeling the Probability of Fraud in Social Media in a National Cannabis Survey. RTI Press, September 2021. http://dx.doi.org/10.3768/rtipress.2021.mr.0046.2109.

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Cannabis legalization has spread rapidly in the United States. Although national surveys provide robust information on the prevalence of cannabis use, cannabis disorders, and related outcomes, information on knowledge, attitudes, and beliefs (KABs) about cannabis is lacking. To inform the relationship between cannabis legalization and cannabis-related KABs, RTI International launched the National Cannabis Climate Survey (NCCS) in 2016. The survey sampled US residents 18 years or older via mail (n = 2,102), mail-to-web (n = 1,046), and two social media data collections (n = 11,957). This report outlines two techniques that we used to problem-solve several challenges with the resulting data: (1) developing a model for detecting fraudulent cases in social media completes after standard fraud detection measures were insufficient and (2) designing a weighting scheme to pool multiple probability and nonprobability samples. We also describe our approach for validating the pooled dataset. The fraud prevention and detection processes, predictive model of fraud, and the methods used to weight the probability and nonprobability samples can be applied to current and future complex data collections and analysis of existing datasets.

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How can we model the brain when it goes awry? How Reinforcement Learning Models can shed light on Psychiatric Disorders that emerge during Development. ACAMH, January 2021. http://dx.doi.org/10.13056/acamh.14458.

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