Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards an Information-Theoretic Approach to Population Structure

This paper uses an information-theoretic perspective to propose multi-locus informativeness measures for ancestry inference. These measures describe the potential for correct classification of unknown individuals to their source populations, given genetic data on population structure. Motivated by Shannon‟s axiomatic approach in deriving a unique information measure for communication (Shannon 1948), we first identify a set of intuitively justifiable criteria that any such quantitative information measure should satisfy, and then select measures that comply with these criteria. It is shown that standard information-theoretic measures such as multidimensional mutual information cannot completely account for informativeness when source populations differ in size, necessitating a decision-theoretic approach.
To establish online shoppers' markets and rules for dynamic CRM systems: an empirical case study in Taiwan

Purpose – The purpose of this paper is to establish customers’ markets and rules of dynamic customer relationship management (CRM) systems for online retailers.Design/methodology/approach – This research proposes a procedure to discover customers’ markets and rules, which adopts the recency, frequency, monetary value (RFM) variables, transaction records, and socioeconomic data of the online shoppers to be the research variables. The research methods aim at the supervised apriori algorithm, C5.0 decision tree algorithm, and RFM model.Findings – This research discovered eight RFM markets and six rules of online retailers.Practical implications – The proposed framework and research results can help retailer managers to retain and expand high value markets via their dynamic CRM and POS systems.Originality/value – This research uses data mining technologies to extract high value markets and rules for marketing plans. The research variables are easy to obtain via retailers’ systems. The found customer values, R.
Reconstructing a 3D Line from a Single Catadioptric Image

This paper demonstrates that, for axial non-central optical systems, the equation of a 3D line can be estimated using only four points extracted from a single image of the line. This result, which is a direct consequence of the lack of vantage point, follows from a classic result in enumerative geometry: there are exactly two lines in 3-space which intersect four given lines in general position. We present a simple algorithm to reconstruct the equation of a 3D line from four image points. This algorithm is based on computing the Singular Value Decomposition (SVD) of the matrix of Plucker coordinates of the four corresponding rays. We evaluate the conditions for which the reconstruction fails, such as when the four rays are nearly coplanar. Preliminary experimental results using a spherical catadioptric camera are presented. We conclude by discussing the limitations imposed by poor calibration and numerical errors on the proposed reconstruction algorithm.
Capping protein is essential for cell migration in vivo and for filopodial morphology and dynamics

This study shows that capping protein (CP) is essential for mammalian cell migration in vitro and in vivo. The authors also show that CP is present in filopodia of multiple cell types and that it regulates filopodial structure and function. Thus CP function in both lamellipodia and filopodia may contribute to efficient migration.
A brief Addiction Recovery Questionnaire derived from the views of service users and concerned others

Abstract Aims: (i) To quantify support across five stakeholder groups for 20 recovery indicators previously generated from focus groups of service users and concerned others and (ii) To create a brief recovery questionnaire. Methods: Indicators were rated by stakeholders for their overall importance and the three most important ranked. The factor structure was determined by principal component analysis. Findings: The initial 20 recovery indicators covered the spectrum of substance misuse, social and psychological domains. Positive endorsement of each indicator by stakeholder group ranged from 53% to 74% of the maximum support possible with stronger support from service users and concerned others than from practitioners and commissioners. The greatest number of individuals in each stakeholder group, from 86% of combined problem drinkers and drug takers to 36% of specialist practitioners, rated abstinence as the single most important aspect of recovery and well-being was rated second most important. The indicators were refined to create a 12-item Addiction Recovery Questionnaire – the items have good independent evidence of importance to outcome to support their inclusion. Originality: The questionnaire is derived solely from the views of service users and concerned others – it is a brief tool with high face validity and suitable for routine use.
FastLSM: fast lattice shape matching for robust real-time deformation

We introduce a simple technique that enables robust approximation of volumetric, large-deformation dynamics for real-time or large-scale offline simulations. We propose Lattice Shape Matching, an extension of deformable shape matching to regular lattices with embedded geometry; lattice vertices are smoothed by convolution of rigid shape matching operators on local lattice regions, with the effective mechanical stiffness specified by the amount of smoothing via region width. Since the naïve method can be very slow for stiff models - per-vertex costs scale cubically with region width - we provide a fast summation algorithm, Fast Lattice Shape Matching (FastLSM), that exploits the inherent summation redundancy of shape matching and can provide large-region matching at constant per-vertex cost. With this approach, large lattices can be simulated in linear time. We present several examples and benchmarks of an efficient CPU implementation, including many dozens of soft bodies simulated at real-time rates on a typical desktop machine.
Unified flow of custom processor design and FPGA implementation

The automation of custom hardware design often focuses on hardware optimizations for smaller portions of code that dominate the design execution. The same presumption can be stated for custom processor design. The data path of the processor can be well optimized for particular blocks of code that are formed during control flow extraction. However, larger source codes can have tens of blocks that result from Control Flow Graph (CFG). We implemented a global semi-automated flow that hierarchically forms the set of blocks which contributions are modeled into processor architecture. Resulting processor model is translated to RTL description and implemented inside FPGA logic.
Sex bias in studies selected for clinical guidelines.

OBJECTIVE To determine the proportions of female participants in research studies selected to inform the development of national clinical guidelines and to assess these against the proportions of women affected by the conditions. METHODS We assessed 392 published articles, involving a total of 5.2 million participants, cited as references in five influential clinical guidelines addressing the use of antiarrhythmics, chronic fatigue, depression, diabetes, and colorectal cancer. For each article, we extracted the number of female participants to determine any discrepancies in the sex of participants and if the proportion of female participants as research subjects reflected the sex distribution of patients affected by the condition. RESULTS The overall and median percentages (per study) of females per guideline were: use of antiarrhythmics (35%, median 38%), chronic fatigue (70%, median 73%), colorectal cancer (67%, median 46%), depression (66%, median 66%), and diabetes (63%, median 50%). The baseline prevalence rates used for comparison purposes were (percentage female): antiarrhythmics (60% of patients 75(+) years); chronic fatigue (66%), colorectal cancer (46%), depression (66%), and diabetes (46%). CONCLUSIONS The colorectal cancer, depression, and chronic fatigue guidelines were based on research populations that accurately reflected the sex distribution of the condition in the general population. Women were slightly overrepresented in the research studies supporting the diabetes guidelines and were significantly underrepresented in the research studies supporting the guidelines on the use of antiarrhythmics. Guideline developers should be aware of and comment on the potential impact of sex. Where the evidence base is lacking, guideline developers should highlight this and, where necessary, limit their specific conclusions to populations on whom the research was performed.
A Novel Hybrid Dual-PM Machine Excited by AC With DC Bias for Electric Vehicle Propulsion

This paper proposes a novel hybrid-excited dual-PM machine for electric vehicle propulsion. The key is to use an integrated stator winding to replace the armature winding and the field winding in the conventional hybrid-excited machine. The stator winding is excited by ac current with dc bias, in which the ac component is used to produce the rotating armature field, while the dc bias current is used for the flux regulation. Therefore, the function of the ac and dc windings can be incorporated and realized by using just one set of winding. The torque density and flux regulating capability can be improved, and the winding configuration is also simplified. In addition, dual-PM excitation structure combines the advantage of stator-PM doubly salient machine and rotor-PM magnetic-geared machine, which can further enhance the torque capability. The operating principle and control strategy of the proposed machine are discussed. The electromagnetic performances are studied using the time-stepping finite-element method. A machine prototype is manufactured and experimental tests are conducted to verify the effectiveness of the machine design.
Simple and efficient compression of animation sequences

We present a new geometry compression method for animations, which is based on the clustered principal component analysis (CPCA). Instead of analyzing the set of vertices for each frame, our method analyzes the set of paths for all vertices for a certain animation length. Thus, using a data-driven approach, it can identify mesh parts, that are "coherent" over time. This usually leads to a very efficient and robust segmentation of the mesh into meaningful clusters, e.g. the wings of a chicken. These parts are then compressed separately using standard principal component analysis (PCA). Each of this clusters can be compressed more efficiently with lesser PCA components compared to previous approaches. Results show, that the new method outperforms other compression schemes like pure PCA based compression or combinations with linear prediction coding, while maintaining a better reconstruction error. This is true, even if the components and weights are quantized before transmission. The reconstruction process is very simple and can be performed directly on the GPU.
Machine learning techniques in Hadoop environment: A survey

A plenty of informative data is produced on social sites. Twitter is a widely used social site to express opinion and feelings related to any domain. Tweets can be used to extract relevant and reliable information. Data analysis is an important task for mining these types of large data. The classification of these tweets can be useful to human beings. However, storage and processing of plenty of tweets is a challenging problem. Hadoop Distributed File System (HDFS) can be used to store this data. To extract information and to classify tweets, various data mining techniques can be utilized. The well-known data mining techniques include Clustering and Classification. Traditionally, these algorithms run in the sequential environment. For improving computational performance and address scalability issue, these methods should run in distributed environment. However, distributed environment introduces issues like synchronization, communication overhead, appropriate division of tasks/data, and load imbalance. The problem of synchronization can be handled using Hadoop Map-reduce programming model. This paper aims to discuss parallelism of various data mining algorithms in Hadoop environment.
Responses of preschool children with and without ADHD to sensory events in daily life.

OBJECTIVE The purpose of this study was to compare parents' perceptions of the responses of their preschool children, with and without attention deficit hyperactivity disorder (ADHD), to sensory events in daily life in Israel. In addition, the relationship between levels of hyperactivity and sensory deficits was examined. METHOD The Sensory Profile Questionnaire (SP) was completed by mothers of forty-eight 4- to 6-year-old children with ADHD, and mothers of 46 children without disabilities. A matched group comparison design was used to identify possible differences in sensory processing. RESULTS Based on the measure of mothers' perceptions, children with ADHD demonstrated statistically significant differences from children without ADHD in their sensory responsiveness as reflected in 6 out of 9 factor scores (p < .001-.05), and on their sensory processing, modulation, and behavioral and emotional responses, as reflected in 11 out of 14 section scores (p < .001-.05). Scores on the SP yielded statistically significant low to moderate correlations with scores on the hyperactive scale of the Preschool Behavior Questionnaire (r = .28-.66). CONCLUSION The findings of the present study suggest that young children with ADHD may be at increased risk of deficits in various sensory processing abilities, over and above the core symptoms of ADHD. Early identification and treatment of sensory processing deficits from a young age may extend our ability to support the successful performance of children with ADHD in meaningful and productive occupations.
Integral motives and special values of zeta functions

For each field k, we define an abelian category of rationally decomposed mixed motives with integer coefficients. When k is finite, we show that the category is Tannakian, and we prove formulas relating the behaviour of zeta functions near integers to certain Ext groups. This is the submitted version, with minor corrections and additions from the first version.
High performance torque and flux control for multilevel inverter fed induction motors

This paper presents a high performance torque and flux control strategy for high power induction motor drives. The control method uses the torque error to control the load angle, obtaining the appropriate flux vector trajectory from which the voltage vector is directly derived based on DTC principles. The voltage vector is then generated by an asymmetric cascaded multilevel inverter without need of modulation. Due to the high output quality of the inverter, the torque response presents nearly no ripple. In addition, switching losses are greatly reduced since 80% of the power is delivered by the high power cell of the asymmetric inverter, which commutates only a few times per cycle. Simulation and experimental results for a 81-level inverter are presented
Multiobjective Optimization of Cement-bonded Sand Mould System with Differential Evolution

Currently, most optimization cases in engineering and other heavy industries present themselves in a multi-objective (MO) setting. Thus, it would greatly aid the decision maker (DM) if a series of multiple solutions were at hand prior to selecting the suitable solution. In this work, the weighted sum scalarization approach is used in conjunction with the differential evolution (DE) algorithm. The DE approach was then applied to the cement-bonded sand mould system to construct the approximate Pareto frontier as well as to identify the best solution option. Some analysis was then performed on the produced computational results. Examination on the performance and the quality of the solutions obtained by the DE algorithm is presented here.
A roles approach to conflict strategy: Modeling the effects of self- and other -role enactment on conflict strategies through goals and emotion

Title of Dissertation: A ROLES APPROACH TO CONFLICT STRATEGIES: MODELING THE EFFECTS OF SELFAND OTHER-ROLE ENACTMENT ON CONFLICT STRATEGIES THROUGH GOALS AND EMOTION Xiaoying Xie, Doctor of Philosophy, 2009 Dissertation Directed by: Professor Deborah A. Cai Department of Communication This dissertation addresses how, in a conflict situation, individuals enact different roles and how their responses to the other party’s role enactment affect the strategies they choose to handle the conflict. A model is proposed to delineate the cognitive and emotional process through which the focal individual and the other party’s role enactment affect the focal individual’s conflict strategies. The model was first examined using the data based on participants’ recall of a past conflict and their answers to questions that assessed behaviors (N = 265). Next, a laboratory experiment was used to test a model in which a conflict was induced and each participant interacted with a confederate to complete a decision making task (N = 261). The focal person’s obligation to his or her general role and the other party’s expectation violations were manipulated. Participants’ embracement of their situated roles, perceived goal importance, emotion, and the use of four types of conflict strategies were measured. Results indicated that obligation predicted the use of relational-protective strategies through the mediating effect of relational goal importance. Embracement of the situated role was found to directly predict the use of a relational-protective confronting strategy but indirectly predict the use of a relational-disruptive confronting strategy through situated goal importance. The other’s expectation violation changed the perceived goal importance and the emotion of the focal individual, which predicted the use of relational-disruptive strategies. However, the main reason for the effect of expectation violation on relational-disruptive strategies was individuals’ direct reaction to the other’s behavior rather than anger. Interpretations and implications of the results, the limitations of the study, theoretical and methodological contributions of the study, and future directions were discussed. A ROLES APPROACH TO CONFLICT STRATEGY: MODELING THE EFFECTS OF SELF-AND OTHER-ROLE ENACTMENT ON CONFLICT STRATEGIES THROUGH GOALS AND EMOTION
RE: net risk reclassification P Values: valid or misleading?

Biomedical research of the last few decades has been characterized by an overreliance on statistical testing. Researchers like many zeros in their P values to convince their audience on the validity of their claims from empirical observations. The area of predictive modeling has been no exception. When the focus shifted from association, eg, expressed by hazard ratios, to the added predictive ability of new biomarkers, P values remained at the forefront in reporting. A contributing factor is the difficult
Large object support in POSTGRES

Four implementations that support large objects in the POSTGRES database system are presented. The four implementations offer varying levels of support for security, transactions, compression, and time travel. All are implemented using the POSTGRES abstract data type paradigm, support user-defined operators and functions, and allow file-oriented access to large objects in the database. The support for user-defined storage managers available in POSTGRES is also detailed. The performance of all four large object implementations on two different storage devices is described. <<ETX>>
Cooperative Shared Spectrum Sensing for Dynamic Cognitive Radio Networks

Cooperative spectrum sensing for cognitive radio networks is recently being studied to simultaneously minimize uncertainty in primary user detection and solve hidden terminal problem. Sensing wideband spectrum is another challenging task for a single cognitive radio due to large sensing time required. In this paper, we introduce a technique to tackle both wideband and cooperative spectrum sensing tasks. We divide the wideband spectrum into several subbands. Then a group of cognitive radios is assigned for sensing of a particular narrow subband. A cognitive base station is used for collecting the results and making the final decision over the full spectrum. Our proposed algorithm minimizes time and amount of energy spent for wideband spectrum scanning by a cognitive radio, and effectively detects the primary users in the wideband spectrum thanks to cooperative shared spectrum sensing.
FAM: Ein Fragebogen zur Erfassung aktuller Motivation in Lern- und Leistungssituationen

Zusammenfassung.Vorgestellt wird ein Fragebogen (FAM), der mit 18 Items vier Komponenten der aktuellen Motivation in (experimentellen) Lern- und Leistungssituationen erfasst, namlich Misserfolgsbefurchtung, Erfolgswahrscheinlichkeit, Interesse und Herausforderung. Die deutsche sowie eine amerikanische Version weisen zufriedenstellende Konsistenzen auf (6 Stichproben, N = 944). Aus verschiedenen Experimenten liegen bereits Validitatshinweise dazu vor, dass die vorweg erfassten Motivationskomponenten mit dem nachfolgenden Lernverhalten und der Lernleistung im Zusammenhang stehen. Im jetzigen Artikel werden zwei Experimente berichtet, die zeigen, dass die Leistungsprognosen von Herausforderung und Interesse auch von der Lernaufgabe sowie von der Zahl der Lerndurchgange abhangen. Beide FAM-Faktoren erlauben Leistungsvorhersagen beim selbstgesteuerten Verstandnislernen (vs. fragengefuhrten Faktenlernen) und bei Probanden, die viele (vs. wenige) Durchgange benotigen, um ein akzeptables Leistungsniveau zu erreic.
Do women who succeed in male‐dominated domains help other women? The moderating role of gender identification

It is often expected that the first women to advance in male-dominated fields will promote other women who follow them. Two studies test the hypothesis that some women show this expected pattern of promoting women but that others show the opposite pattern, favoring men over women. In two studies, women's gender identification moderated the extent to which they favored men over women when they advanced in a male-dominated field. Specifically, the weaker women's gender identification, the more favoritism they showed for a male relative to a female subordinate. Gender identification did not moderate women's behavior in a context in which women were not underrepresented, pointing to the power of the situation in eliciting this relationship. Implications for the advancement of women in male-dominated fields are discussed.
Establishing specificity in psychotherapy: a meta-analysis of structural equivalence of placebo controls.

Placebo treatments in psychotherapy cannot adequately control for all common factors, which thereby attenuates their effects vis-a-vis active treatments. In this study, the authors used meta-analytic procedures to test one possible factor contributing to the attenuation of effects: structural inequalities between placebo and active treatments. Structural aspects of the placebo included number and duration of sessions, training of therapist, format of therapy, and restriction of topics. Results indicate that comparisons between active treatments and structurally inequivalent placebos produced larger effects than comparisons between active treatments and structurally equivalent placebos: moreover, the latter comparison produced negligible effects, indicating that active treatments were not demonstrably superior to well-designed placebos.
Marginal Structural Models and Causal Inference in Epidemiology

In observational studies with exposures or treatments that vary over time, standard approaches for adjustment of confounding are biased when there exist time-dependent confounders that are also affected by previous treatment. This paper introduces marginal structural models, a new class of causal models that allow for improved adjustment of confounding in those situations. The parameters of a marginal structural model can be consistently estimated using a new class of estimators, the inverse-probability-of-treatment weighted estimators.