Miracle-dz/UniFAR-FTUs huggingface dataset:
Evolutionary Psychopathology and Life History: A Clinician's Perspective

Life history theory is one of the major approaches within evolutionary theory, combining the adaptationist approach with developmental constraints and including how organisms must invest resources strategically (Kaplan & Gangestad, 2005). Del Giudice has offered a truly biological approach to evolutionary psychology through his previous work on life history theory (e.g., Del Giudice, 2009) and is one of the rising stars of the field. It is therefore most welcome when Del Giudice in his current article considers evolutionary psychopathology from this perspective, something I suggested might be fruitful and necessary a decade ago (Kennair, 2003). Del Giudice offers a veritable tour de force, spanning an enormous amount of literature and developing an original approach by considering all mental disorders from a life history perspective, or more precisely from a fast versus slow life history perspective. There is an impressive amount of work behind this article, and although I cannot do justice to all points he raises, I do attempt to provide a clinician’s perspective to some of the conditions that I am most familiar with. It is true; the field of psychopathology lacks theoretical integration (Kennair, 2011, 2012; Nesse & Stein, 2012). There is little consensus on what constitutes mental disorder, and despite work from an evolutionary approach (e.g., Wakefield, 1999), we will probably need research from an evolutionary modular and functional approach for such approaches to fulfill their potential. A comprehensive life history perspective might have the explanatory power to aid such integration, at least as part of the process of expanding the developmental and individual differences level of analysis to an evolutionary psychology approach to psychopathology (Kennair, 2003, 2011, 2012). Although I am very fond of Del Giudice’s work, and welcome his interest in evolutionary psychopathology, I have two points I would like to raise: (a) the possible limitations of reducing life history theory to a fast versus slow approach, and (b) the possible consequences of some of the disorders’ treatability for a life history approach. I take the clinician’s perspective in the current commentary. As both an evolutionary psychologist and a clinician, I believe it is the latter that may contribute the most interesting perspective for further development of the proposed taxonomy.
Application of Intent Inference for Air Defense and Conformance Monitoring

The human brain has remarkable capabilities in perception and reasoning. However, the amount of complex data/information that can be processed by the human brain is constrained by the limited memory capacity. Hence, computational tools are necessary to provide cognitive aid to the human brain in attaining better performance in intellectual tasks, such as decision making. Intent inference is about analyzing the actions and activities of an opponent or a target of interest to obtain a conclusion (prediction) on its purpose [3, 10, 18, 24]. Generally, data (collectively called observables) concerning the opponent are first collected from available sources. Next, the data are fused to obtain useful information. Finally, the fused information is utilized to derive the inferred intent of the opponent. It is desirable that intent inference be able to provide three kinds of hypotheses about an opponent’s objective [3, 18]:
Propensity Score Methods for Causal Inference: On the Relative Importance of Covariate Selection, Reliable Measurement, and Choice of Propensity Score Technique

The popularity of propensity score (PS) methods for estimating causal treatment effects from observational studies has increased during the past decades. However, the success of these methods in removing selection bias mainly rests on strong assumptions, like the strong ignorability assumption, and the competent implementation of a specific propensity score technique. After giving a brief introduction to the Rubin Causal Model and different types of propensity score techniques, the paper assess the relative importance of three factors in removing selection bias in practice: (i) The availability of covariates that are related to both the selection process and the outcome under investigation; (ii) The reliability of the covariates’ measurements; And (iii) the choice of a specific analytic method for estimating the treatment effect—either a specific propensity score technique (PS matching, PS stratification, inverse-propensity weighting, and PS regression adjustment) or standard regression approaches. The importance of these three factors is investigated by reviewing different within-study comparisons and meta-analyses. Within-study comparisons enable an empirical assessment of PS methods’ performance in removing selection bias since they contrast the estimated treatment effect from an observational study with an estimate from a corresponding randomized experiment. The empirical evidence indicates that the selection of covariates counts most in reducing selection bias, their reliable measurement next most, and the mode of data analysis—either a specific propensity score technique or standard regression—is of least importance. Additional evidence suggests that the crucial strong ignorability assumption is most likely met if pretest measures of the outcome or constructs that directly determine the selection process are available and reliably measured.
General Educators' Attitudes Toward Students with Mild Disabilities and Their Use of Instructional Strategies

In today's schools the demands of general educators to meet the diverse needs of their students have greatly increased. General educators need to have an increasingly large repertoire of instructional strategies to effectively meet their students' needs. In this study the frequency of several instructional strategies used by general educators at the middle school level (Grades 6, 7, and 8) was investigated. The frequency of the use of these instructional strategies by middle school teachers was compared to the amount of time they spent collaborating with special educators and also to the number of courses taken related to specialized techniques. This study also examined the attitudes general educators have toward the inclusion of students with mild disabilities. Findings indicated that the number of instructional strategies general educators use increases with the number of special education courses taken and the number of hours spent with special educators. In addition, some general educators may not have a positive attitude toward including students with disabilities in their classrooms. Discussion of these findings and implications for training are provided.
Attentional Modulation of Alpha Oscillations in Macaque Inferotemporal Cortex

Recent work reported the observation of alpha frequency oscillations (8–12 Hz) in several regions of macaque visual cortex, including V2, V4, and inferotemporal cortex (IT). While alpha-related physiology in V2 and V4 appears consistent with a role in attention-related suppression, in IT, alpha reactivity appears conflicted with such a role. We addressed this issue directly by analyzing laminar profiles of local field potentials and multiunit activities from the IT of macaque monkeys during performance of an intermodal selective attention task (visual versus auditory). We found that (1) before visual stimulus onset (−200 to 0 ms), attention to visual input increased ongoing alpha power in IT relative to attention to auditory input, and (2) in contrast to the prevailing view of alpha inhibition, the increased ongoing alpha activity is accompanied by increased concurrent multiunit firing and facilitates visual stimulus processing. These results suggest that ongoing alpha oscillations in IT play a different functional role than that in the occipital cortex and may be part of the neuronal mechanism representing task-relevant information.
The Acquaintanceship Process:

The present study examined the relationship between uncertainty (reduction), information seeking, and liking during unstructured initial interaction. Participants' uncertainty and liking were measured before and after observing their partner, and again after they had interacted with the partner. The preobservation measure of uncertainty dealt with persons' uncertainty about acquaintanceship in general (i.e., their global uncertainty). The conversations, which were tape-recorded, were transcribed and coded to generate measures of question asking and self-disclosure. Analyses showed significant linear and quadratic trends in the uncertainty scores; global uncertainty was also significantly related to uncertainty about the specific partner after interaction and the amount of uncertainty reduction that participants achieved. Uncertainty and liking were inversely correlated both before and after persons talked to each other although the analysis provided little evidence of causal conjunction. Further, whereas global uncertainty was predictive of amount of information seeking, target-specific uncertainty was unrelated to the frequency of both question asking and disclosure. These findings are discussed in the context of uncertainty reduction theory.
FORMULATION OF COTTON MIX : DEVELOPMENT FROM INDECISIVE TO DECISION SUPPORT SYSTEMS

Consistency and optimization of Quality and Economy of the product yarn are the basic aspects; spinner should always need to be conscious about it. Formulation of the mix is the outcome of these constraints. But the selection of right components and their proportion in mix to reach the above mentioned target demands lot of brainstorming exercise, statistics and the human skills involved in this course. Drastic changes took place in the conventional practices used for the formulation of the mix to that of present practices going on. The limitations of conventional methods have been identified. The present method with the adoption of ANN, HVI and EFS has overcome these limitations to a greater extent. This paper explores in brief limitations of conventional approach; present method used along with the expected future trends.
Fast and Scalable Feature Selection for Gene Expression Data Using Hilbert-Schmidt Independence Criterion

Goal: In computational biology, selecting a small subset of informative genes from microarray data continues to be a challenge due to the presence of thousands of genes. This paper aims at quantifying the dependence between gene expression data and the response variables and to identifying a subset of the most informative genes using a fast and scalable multivariate algorithm. Methods: A novel algorithm for feature selection from gene expression data was developed. The algorithm was based on the Hilbert-Schmidt independence criterion (HSIC), and was partly motivated by singular value decomposition (SVD). Results: The algorithm is computationally fast and scalable to large datasets. Moreover, it can be applied to problems with any type of response variables including, biclass, multiclass, and continuous response variables. The performance of the proposed algorithm in terms of accuracy, stability of the selected genes, speed, and scalability was evaluated using both synthetic and real-world datasets. The simulation results demonstrated that the proposed algorithm effectively and efficiently extracted stable genes with high predictive capability, in particular for datasets with multiclass response variables. Conclusion/Significance: The proposed method does not require the whole microarray dataset to be stored in memory, and thus can easily be scaled to large datasets. This capability is an important attribute in big data analytics, where data can be large and massively distributed.
Perchlorate formation on Mars through surface radiolysis‐initiated atmospheric chemistry: A potential mechanism

Recent observations of the Martian surface by the Phoenix lander and the Sample Analysis at Mars indicate the presence of perchlorate (ClO4–). The abundance and isotopic composition of these perchlorates suggest that the mechanisms responsible for their formation in the Martian environment may be unique in our solar system. With this in mind, we propose a potential mechanism for the production of Martian perchlorate: the radiolysis of the Martian surface by galactic cosmic rays, followed by the sublimation of chlorine oxides into the atmosphere and their subsequent synthesis to form perchloric acid (HClO4) in the atmosphere, and the surface deposition and subsequent mineralization of HClO4 in the regolith to form surface perchlorates. To evaluate the viability of this mechanism, we employ a one‐dimensional chemical model, examining chlorine chemistry in the context of Martian atmospheric chemistry. Considering the chlorine oxide, OClO, we find that an OClO flux as low as 3.2 × 107 molecules cm–2 s–1 sublimated into the atmosphere from the surface could produce sufficient HClO4 to explain the perchlorate concentration on Mars, assuming an accumulation depth of 30 cm and integrated over the Amazonian period. Radiolysis provides an efficient pathway for the oxidation of chlorine, bypassing the efficient Cl/HCl recycling mechanism that characterizes HClO4 formation mechanisms proposed for the Earth but not Mars.
Modeling and Multi-Objective Optimization of NO x Conversion Efficiency and NH 3 Slip for a Diesel Engine

The objective of the study is to present the modeling and multi-objective optimization of NO x conversion efficiency and NH 3 slip in the Selective Catalytic Reduction (SCR) catalytic converter for a diesel engine. A novel ensemble method based on a support vector machine (SVM) and genetic algorithm (GA) is proposed to establish the models for the prediction of upstream and downstream NO x emissions and NH 3 slip. The data for modeling were collected from a steady-state diesel engine bench calibration test. After obtaining the two conflicting objective functions concerned in this study, the non-dominated sorting genetic algorithm (NSGA-II) was implemented to solve the multi-objective optimization problem of maximizing NO x conversion efficiency while minimizing NH 3 slip under certain operating points. The optimized SVM models showed great accuracy for the estimation of actual outputs with the Root Mean Squared Error (RMSE) of upstream and downstream NO x emissions and NH 3 slip being 44.01 × 10 −6 , 21.87 × 10 −6 and 2.22 × 10 −6 , respectively. The multi-objective optimization and subsequent decisions for optimal performance have also been presented.
Mirroring in the Human Brain: Deciphering the Spatial-Temporal Patterns of the Human Mirror Neuron System

Embodied theories of cognition emphasize the central role of sensorimotor transformations in the representation of others' actions. Support for these theories is derived from the discovery of the mirror neuron system (MNS) in primates, from noninvasive techniques in humans, and from a limited number of intracranial studies. To understand the neural dynamics of the human MNS, more studies with precise spatial and temporal resolutions are essential. We used electrocorticography to define activation patterns in sensorimotor, parietal and/or frontal neuronal populations, during a viewing and grasping task. Our results show robust high gamma activation for both conditions in classic MNS sites. Furthermore, we provide novel evidence for 2 different populations of neurons: sites that were only active for viewing and grasping ("pure mirroring") and sites that were also active between viewing and grasping, and perhaps serve a more general attentional role. Lastly, a subgroup of parietal electrodes showed earlier peaks than all other regions. These results highlight the complexity of spatial-temporal patterns within the MNS and provide a critical link between single-unit research in monkeys and noninvasive techniques in human.
Automatic Image Forgery Exposure using Illuminant Measure of Face Region and Random Object Detection Method

For decades, photographs have often served as evidence in courts. One of the most common forms of photographic manipulation, known as image composition or splicing is analysed in this paper. The goal of blind image forensics is to distinguish original and manipulated images. We propose illumination color as a new indicator for the assessment of image authenticity. Many images exhibit a combination of multiple illuminants (ash photography, mixture of indoor and outdoor lighting, etc.). In the proposed method, the user selects illuminated areas for further investigation. The illuminant colors are locally estimated, effectively decomposing the scene in a map of differently illuminated regions. Inconsistencies in such a map suggest possible image tampering.The information from the physics and statistical-based illuminant estimators on image regions are incorporated to achieve this. From these illuminant estimates, texture and edge-based features are extracted and then provided to a machine-learning approach for decision-making. The classification performance is done by using a Random forest classifier. Automatic face detection is used in order to improve the accuracy of the result.
Gaussian mixture classification for moving object detection in video surveillance environment

The paper deals with detection of moving objects by modelling pixel grey level distribution along the time. The detection of moving objects is based on learning and update of background pixel distributions. The choice of appropriate mixture's component for a given pixel is performed by likelihood maximization. An original Markov regularization is proposed to smooth detection. The method performs in real time on CIF resolution video and low cost commercial hardware.
Doing Multiculturalism: An Interactionist Analysis of the Practices of a Multicultural Sorority

Despite the many references to multiculturalism in academic works and media accounts, we know little about what it is like in practice. Drawing on data from interviews, ethnographic observations, and archival materials from a multicultural sorority chapter, this article highlights three main ways its members do multiculturalism: (1) recognizing and valuing differences, (2) teaching and learning about differences, and (3) bridging differences via personal friendships and organizational alliances. Broad racial ideologies and the culture of the university and the Greek system, however, created the conditions under which sorority members do multiculturalism, including their focus on some differences (e.g., race, ethnicity, and sexual identity) and neglect of others (i.e., class and gender). While the multicultural sorority sought to lessen racial divisions on campus and their approach opposed colorblind ideology, they presented little challenge to the hegemony of the campus Greek system. This study has implications for understanding Greek Letter Organizations, multiculturalism as a collective practice, and how countering colorblind ideology can reproduce other inequality-legitimating ideologies.
Long-term outcome of psychopathology in childhood and adolescence : a clinical epidemiological study

textabstractVery different populations were used in these studies, two populations consisting of adolescents only (Otto and Otto, 1978 and Rey et al., 1995, 1997), one population existing of males only (Steinhausen, Meier, and Angst, 1998), and all studies differing on in- and exclusion criteria. This leads to difficulties in comparing results. Excluding the all male sample (Steinhausen, Meier, and Angst, 1998), populations consisted of an average of 64.5% males and 35.5% females. Response rates were on average 90.4% for studies using records or registers only, and 65.9% for studies using direct assessment. Only one study used standardized measures with well-validated, empirical syndromes at both times of assessment (Stanger, et al., 1996). This was also the only study in which multiple informants were used, but unfortunately at follow-up only. Analytic strategies were very different across studies, so comparison at result level is extremely difficult. Still, some general conclusions can be drawn. Among others, these studies seem to confirm the stability and continuity of psychopathology found in general population samples, especially for externalizing problems. Unfortunately no average figures can be given, because different analytic strategies resulted in incomparable measures (e.g., percentages and stability coefficients). Furthermore, most authors agree that other domains of functioning are likely to be hampered as well, e.g., family relations, educational and professional achievements, and social functioning, and that other indices of poor functioning are increased, e.g., mental health service use and judicial contacts. Results indicate that prognosis can to some extent be predicted from factors known at initial assessment, such as age at intake, gender, length of follow-up period, socio-economic status, or initial type of problem. However, the inconsistency of results across studies on these related factors hampers drawing firm conclusions on their influence. Results led us to expect considerable stability of psychopathology, and to expect the type of problems to remain mostly the same across time, and at follow-up to be predicted by comparable problems at intake.
Top-down Data Analysis with Treemaps

Statistics Netherlands produces statistics about the economic activity in The Netherlands. These statistics are based on survey data and administrative sources, such as value added tax (VAT). A recent trend in the production of official statistics is to use a top-down analysis, which means that analysts first analyze high level aggregated data, and then zoom in on a more detailed level when necessary. In this paper, we discuss how treemap visualizations can be used for this top-down approach. We use comparison treemaps and density treemaps. Finally, we introduce a method to visualize confidence intervals in treemaps.
Duplication of Coding Segments in Genetic Programming

Research into the utility of non-eoding segments, or introns, in genetic-based encodings has shown that they expedite the evolution of solutions in domains by protecting building blocks against destructive crossover. We consider a genetic programming system where non-coding segments can be removed, and the resultant chromosomes returned into the population. This parsimonious repair leads to premature convergence, since as we remove the naturally occurring non-coding segments, we strip away their protective backup feature. We then duplicate the coding segments in the repaired chromosomes, and place the modified chromosomes into the population. The duplication method significantly improves the learning rate in the domain we have considered. We also show that this method can be applied to other domains.