1,791 research outputs found

    The contribution of injury severity, executive and implicit functions to awareness of defi cits after traumatic brain injury (TBI)

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    Deficits in self-awareness are commonly seen after Traumatic Brain Injury (TBI) and adversely affect rehabilitative efforts, independence and quality of life (Ponsford, 2004). Awareness models predict that executive and implicit functions are important cognitive components of awareness though the putative relationship between implicit and awareness processes has not been subject to empirical investigation (Crosson et al., 1989; Ownsworth, Clare, & Morris, 2006; Toglia & Kirk, 2000). Severity of injury, also thought to be a crucial determinant of awareness outcome post-insult, is under-explored in awareness studies (Sherer, Boake, Levin, Silver, Ringholz, & Walter, 1998 ). The present study measured the contribution of injury severity, IQ, mood state, executive and implicit functions to awareness in head-injured patients assigned to moderate/severe head-injured groups using several awareness, executive, and implicit measures. Severe injuries resulted in greater impairments across most awareness, executive and implicit measures compared with moderate injuries, although deficits were still seen in the moderate group. Hierarchical regression results showed that severity of injury, IQ, mood state, executive and implicit functions made signifi cant unique contributions to selective aspects of awareness. Future models of awareness should account for both implicit and executive contributions to awareness and the possibility that both are vulnerable to disruption after neuropathology. ( JINS , 2010, 16 , 1– 10 .

    Investigating the 'latent' deficit hypothesis : age at time of head injury, executive and implicit functions and behavioral insight

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    This study investigated the 'latent deficit' hypothesis in two groups of frontotemporal headinjured patients, those injured prior to steep morphological and corresponding functional maturational periods for frontotemporal networks (≀ age 25), and those injured >28 years. The latent deficit hypothesis proposes that early injuries produce enduring cognitive deficits manifest later in the lifespan with graver consequences for behavior than adult injuries, particularly after frontal pathology (Eslinger, Grattan, Damasio & Damasio, 1992). Implicit and executive deficits both contribute to behavioral insight after frontotemporal head injury (Barker, Andrade, Romanowski, Morton & Wasti, 2006). On the basis of morphological and behavioral data, we hypothesised that early injury would confer greater vulnerability to impairment on tasks associated with frontotemporal regions than later injury. Patients completed experimental tasks of implicit cognition, executive function measures and the DEX measure of behavioural insight (Behavioral Assessment of the Dysexecutive Syndrome: Wilson, Alderman, Burgess, Emslie, & Evans, 1996). The Early Injury group were more impaired on implicit cognition tasks compared to controls that Late Injury patients. There were no marked group differences on most executive function measures. Executive ability only contributed to behavioral awareness in the Early Injury Group. Findings showed that age at injury moderates the relationship between executive and implicit cognition and behavioral insight and that early injuries result in longstanding deficits to functions associated with frontotemporal regions partially supporting the latent deficit hypothesis

    Editorial: Executive function(s): Conductor, orchestra or symphony? Towards a trans-disciplinary unification of theory and practice across development, in normal and atypical groups.

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    There are several theories of executive function(s) that tend to share some theoretical overlap yet are also conceptually distinct, each bolstered by empirical data (Norman and Shallice, 1986; Shallice & Burgess, 1991; Stuss and Alexander, 2007; Burgess, Gilbert, & Dumentheil, 2007; Burgess & Shallice, 1996; Miyake et al., 2000). The notion that executive processes are supervisory, and most in demand in novel situations was an early conceptualization of executive function that has been adapted and refined over time (Norman & Shallice, 1986; Shallice, 2001; Burgess, Gilbert & Dumentheil, 2007). Presently there is general consensus that executive functions are multi-componential (Shallice, 2001), and are supervisory only in the sense that attention in one form or another is key to the co-ordination of other hierarchically organized ‘lower’ cognitive processes. Attention in this sense is defined as (i) independent but interrelated attentional control processes (Stuss & Alexander, 2007); (ii) automatic orientation towards stimuli in the environment or internally–driven thought (Burgess, Gilbert & Dumontheil, 2007); (iii) the automatically generated interface between tacit processes and strategic conscious thought (Barker, Andrade, Romanowski, Morton and Wasti, 2006; Morton and Barker, 2010); and (iv) distinct but interrelated executive processes that maintain, update and switch across different sources of information (Miyake et al., 2000). One problem is that executive dysfunction or dysexecutive syndrome (Baddeley & Wilson, 1988) after brain injury typically produces a constellation of deficits across social, cognate, emotional and motivational domains that rarely map neatly onto theoretical frameworks (Barker, Andrade & Romanowski, 2004). As a consequence there is debate that conceptual theories of executive function do not always correspond well to the clinical picture (Manchester, Priestley & Jackson, 2004). Several studies have reported cases of individuals with frontal lobe pathology and impaired daily functioning despite having little detectable impairment on traditional tests of executive function (Shallice & Burgess, 1991; Eslinger & Damasio, 1985; Barker, Andrade & Romanowski, 2004; AndrĂ©s & Van der Linden, 2002; Chevignard et al., 2000; Cripe, 1998; Fortin, Godbout & Braun, 2003). There is also some suggestion that weak ecological validity limits predictive and clinical utility of many traditional measures of executive function (Burgess et al, 2006; Lamberts, Evans & Spikman, 2010; Barker, Morton, Morrison, McGuire, 2011). Complete elimination of environmental confounds runs the risk of generating results that cannot be generalized beyond constrained circumstances of the test environment (Barker, Andrade & Romanowski, 2004). Several researchers have concluded that a new approach is needed that is mindful of the needs of the clinician yet also informed by the academic debate and progress within the discipline (McFarquhar & Barker, 2012; Burgess et al., 2006). Finally, translational issues also confound executive function research across different disciplines (psychiatry, cognitive science, and developmental psychology) and across typically developing and clinical populations (including Autism Spectrum Disorders, Head Injury and Schizophrenia – Blakemore & Choudhury, 2006; Taylor, Barker, Heavey & McHale, 2013). Consequently, there is a need for unification of executive function approaches across disciplines and populations and narrowing of the conceptual gap between theoretical positions, clinical symptoms and measurement

    Chrono: A System for Normalizing Temporal Expressions

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    The Chrono System: Chrono is a hybrid rule-based and machine learning system written in Python and built from the ground up to identify temporal expressions in text and normalizes them into the SCATE schema. Input text is preprocessed using Python’s NLTK package, and is run through each of the four primary modules highlighted here. Note that Chrono does not remove stopwords because they add temporal information and context, and Chrono does not tokenize sentences. Output is an Anafora XML file with annotated SCATE entities. After minor parsing logic adjustments, Chrono has emerged as the top performing system for SemEval 2018 Task 6. Chrono is available on GitHub at https://github.com/AmyOlex/Chrono. Future Work: Chrono is still under development. Future improvements will include: additional entity parsing, like “event”; evaluating the impact of sentence tokenization; implement an ensemble ML module that utilizes all four ML methods for disambiguation; extract temporal phrase parsing algorithm to be stand-alone and compare to similar systems; evaluate performance on THYME medical corpus; migrate to UIMA framework and implement Ruta Rules for portability and easier customization

    Need A Boost? A Comparison of Traditional Commuting Models with the XGBoost Model for Predicting Commuting Flows (Short Paper)

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    Commuting models estimate the number of commuting trips from home to work locations in a given area. Since their infancy, they have been increasingly used in a variety of fields to reduce traffic and pollution, drive infrastructure choices, and solve a variety of other problems. Traditional commuting models, such as gravity and radiation models, typically have a strict structural form and limited number of input variables, which may limit their ability to predict commuting flows as well as machine learning models that might better capture the complex dynamics of the commuting process. To determine whether machine learning models might add value to the field of commuter flow prediction, we compare and discuss the performance of two standard traditional models with the XGBoost machine learning algorithm for predicting home to work commuter flows from a well-known United States commuting dataset. We find that the XGBoost model outperforms the traditional models on three commonly used metrics, indicating that machine learning models may add value to the field of commuter flow prediction

    Alex Mallett, Popular Muslim Reactions to the Franks in the Levant, 1097-1291

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    Au cours des derniĂšres dĂ©cennies, l’histoire des croisades a Ă©tĂ© le sujet d’un grand nombre d’études, couvrant une grande variĂ©tĂ© de thĂ©matiques. Ce sont gĂ©nĂ©ralement les croisĂ©s colons francs qui ont obtenu la part du lion dans les recherches, alors qu’un nombre beaucoup plus faible de monographies et d’articles se sont penchĂ©s sur les politiques musulmanes de l’Est. Cette disparitĂ© s’explique principalement par l’incapacitĂ© gĂ©nĂ©ralisĂ©e des chercheurs europĂ©ens et amĂ©ricains Ă  lire l’arabe, ..

    New Villagers

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    It was a gorgeous day in Dubrovnik, Croatia. Brooke Barker, senior in management and international business, kayaked to the Island of Lokrum, the wind blew through her hair as she paddled to keep up with the group. Upon reaching the island, she began the trek to the top, where she ran into some local daredevils preparing to jump into the deep blue water of the Adriatic Sea 35 feet below. Intrigued, Brooke decided to join them

    Quenching Limits and Materials Degradation of Hydrogen Diffusion Flames

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    This study examines the types of hydrogen leaks that can support combustion and the effects on various materials of long term hydrogen flame exposure. Experimental and analytical work is presented. Measurements included limits of quenching, blowoff, and pilted ignition for burners with diameters of 0.36 to 1.78 mm. Flow rates of 0.019 to 40 mg/s for hydrogen, 0.12 to 64 mg/s for methane, and 0.03 to 220 mg/s for propane were studied. Materials degradation experiments were conducted on carbon steel, stainless steel, aluminum alloy, and carbon fiber. Noticeable corrosion is present on 304 and 316 stainless steel, galvanized 1006 - 1008 carbon steel. Silicon carbide fibers perform relatively similarly for hydrogen and methane flame exposure
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