Miracle-dz/UniFAR-FTUs huggingface dataset:
The psychological effects of political and domestic violence on Central American and Mexican immigrant mothers and children

The goal of this study was to compare the psychosocial adjustment of 70 immigrant mothers and their children from Mexico and countries in Central America. In particular, we traced the effects of political violence on Central American refugee families and domestic violence on resettled Mexican women and children. Mothers and children were interviewed about political and domestic violence they had witnessed and experienced, and their current mental health, including symptoms of post-traumatic stress disorder. Central American refugee children appeared indistinguishable on mental health indices from Mexican children residing in violent homes. Both groups of children had elevated psychological symptoms when compared to Mexican immigrant children from nonviolent backgrounds. Central American mothers were most likely to meet the clinical criteria of post-traumatic stress disorder. We examined whether the mothers' post-traumatic stress symptoms, fathers' demise, or general stressors mediated the effects of violence on the children's mental health. The overall effects of war on children are mediated by maternal mental health and the specific associated risk of having lost a father to violent death. Mexican immigrant children were additionally affected by their mothers' employment. Our findings show similar effects on children of growing up with different forms of violence.
The role of self-regulation strategies and self-efficacy perceptions in successful weight loss maintenance

Abstract The purpose of this study was to identify the self-regulatory strategies which people use to lose, maintain, or manage their weight, and to assess their self-efficacy perceptions to implement these strategies. Thirty-three (N = 33) undergraduate college students were divided into three groups based on their past weight loss experience and confirmed by their current Body Mass Index: (a) overweight participants who tried but failed to lose weight, (b) participants who used to be overweight but lost significant weight and kept it off for at least six months, and (c) participants with an optimal weight. All participants were interviewed using a structured questionnaire. Data were analyzed using a one-way ANOVA and correlation analyses. Participants who used self-regulatory strategies such as goal-setting, self-monitoring, self-evaluation, environmental structuring, time management, social assistance and information seeking were better able to maintain or lose weight. Overweight participants reported significantly less strategy use than participants who had lost weight or who had a healthy weight. In addition, overweight participants had lower self-efficacy perceptions about implementing strategies than did healthy weight participants or participants who had successfully lost weight. Finally, a path analysis revealed that participants who reported high self-efficacy perceptions and applied their strategies persistently in the face of difficulties were more likely to successfully manage their weight.
No evidence for a central IMBH in M 15

Intermediate mass black holes (IMBHs) with expected masses M• ≈ 10 4 Mare thought to bridge the gap between stellar mass black holes (M• ≈ 3−100 M� ) and supermassive black holes found at the centre of galaxies (M• > 10 6 M� ). Until today, no IMBH has been confirmed observationally. The most promising objects to host an IMBH as their central mass are globular clusters. Here, we present high sensitivity multi-epoch 1.6 GHz very long baseline interferometry observations of the globular cluster M 15 that has been suggested to host an IMBH. Assuming the IMBH to be accreting matter from its surrounding we expect to detect it as a point source moving with the global motion of the cluster. However, we do not detect any such object within a radius of 6000 AU of the cluster centre in any of the five observations spread over more than one year. This rules out any variability of the putative IMBH on the time scale of one to two months. To get the most stringent upper limit for the flux density of the putative IMBH we concatenate the data of all five epochs. In this data we measure a 3σ upper flux limit of 10 μJy for a central source. We employ the fundamental plane of black hole activity to estimate the mass of the central IMBH candidate. Based on previous X-ray observations of M 15 our measurements indicate a 3σ upper mass limit of ≈500 M� .
Unified Clustering Locality Preserving Matrix Factorization for Student Performance Prediction

—Matrix factorization (MF), known as the most effective recommendation approach, has recently been used in educational contexts for predicting student performance. However, most applications neither take into account the nonnegative nature of the factor matrices nor explore the intrinsic geometric structure of the data. In this study, we propose a novel regularization framework that imposes the locality preserving constraints into the weighted regularized nonnegative MF for predicting student performance. To reduce the complexity of neighborhood evaluation, we employ the k-means clustering technique to identify groups of similar students and tasks based on the corresponding skill profiles. We also provide formal analysis for the theoretical convergence guarantees and the correctness of the iterative multiplicative updating algorithm. Experiments on two benchmark data sets demonstrate that the proposed method outperforms traditional NMF approaches and some baselines.
Stability of backpropagation-decorrelation efficient O(N) recurrent learning

We provide a stability analysis based on nonlinear feedback theory for the recently introduced backpropagation-decorrelation (BPDC) recurrent learning algorithm. For one output neuron BPDC adapts only the output weights of a possibly large network and therefore can learn in O(N). We derive a simple sufficient stability inequality which can easily be evaluated and monitored online to assure that the recurrent network remains stable while adapting. As byproduct we show that BPDC is highly competitive on the recently introduced CATS benchmark data (1).
A Framework for Computing on Large Dynamic Graphs

This proposal presents a graph computing framework intending to support both online and offline computing on large dynamic graphs efficiently. The framework proposes a new data model to support rich evolving vertex and edge data types. It employs a replica-coherence protocol to improve data locality thus can adapt to data access patterns of different algorithms. A new computing model called protocol dataflow is proposed to implement and integrate various programming models for both online and offline computing on large dynamic graphs. A central topic of the proposal is also the analysis of large real dynamic graphs using our proposed framework. Our goal is to calculate the temporal patterns and properties which emerge when the large graphs keep evolving. Thus we can evaluate the capability of the proposed framework. Key words: Large dynamic graph, programming model, distributed computing.
Procedural semantics for autonomous robots - a case study in locative spatial language

This paper discusses the application of a procedural semantics framework to autonomous robots. We model insights from decades of research in cognitive linguistics and empirical research to develop a system capable of autonomously producing and interpreting German locative utterances. The system is tested in the real world using a population of robots that talk to each other via natural language.
Prodorshok I: A bengali isolated speech dataset for voice-based assistive technologies: A comparative analysis of the effects of data augmentation on HMM-GMM and DNN classifiers

Prodorshok I is a Bengali isolated word dataset tailored to help create speaker-independent, voice-command driven automated speech recognition (ASR) based assistive technologies to help improve human-computer interaction (HCI). This paper presents the results of an objective analysis that was undertaken using a subset of words from Prodorshok I to assess its reliability in ASR systems that utilize Hidden Markov Models (HMM) with Gaussian emissions and Deep Neural Networks (DNN). The results show that simple data augmentation involving a small pitch shift can make surprisingly tangible improvements to accuracy levels in speech recognition.
A Two-Level Predictive Event-Related Potential-Based Brain–Computer Interface

Increasing the freedom of communication using conventional row/column (RC) P300 paradigm by naive way (increasing matrix size) may deteriorate inherent distraction effect and interaction speed. In this paper, we propose a two-level predictive (TLP) paradigm by integrating a 3×3 two-level matrix paradigm with a statistical language model. The TLP paradigm is evaluated using offline and online data from ten healthy subjects. Significantly larger event-related potentials (ERPs) are evoked by the TLP paradigm compared with the classical 6×6 RC. During an online task (correctly spell an English sentence with 57 characters), accuracy and information transfer rate for the TLP are increased by 14.45% and 29.29%, respectively, when compared with the 6×6 RC. Time to complete the task is also decreased by 24.61% using TLP. In sharp contrast, an 8×8 RC (naive extension of the 6×6 RC) consumed 19.18% more time than the classical 6×6 RC. Furthermore, the statistical language model is also exploited to improve classification accuracy in a Bayesian approach. The proposed Bayesian fusion method is tested offline on data from the online spelling tasks. The results show its potential improvement on single-trial ERP classification.
The Kill Date as a Management Tool for Cover Cropping Success

Integrating cover crops (CC) in rotations provides multiple ecological services, but it must be ensured that management does not increase pre-emptive competition with the subsequent crop. This experiment was conducted to study the effect of kill date on: (i) CC growth and N content; (ii) the chemical composition of residues; (iii) soil inorganic N and potentially mineralizable N; and (iv) soil water content. Treatments were fallow and a CC mixture of barley (Hordeum vulgare L.) and vetch (Vicia sativa L.) sown in October and killed on two different dates in spring. Above-ground biomass and chemical composition of CC were determined at harvest, and ground cover was monitored based on digital image analysis. Soil mineral N was determined before sowing and after killing the CC, and potentially mineralizable N was measured by aerobic incubation at the end of the experiment. Soil water content was monitored daily to a depth of 1.1 m using capacitance sensors. Under the present conditions of high N availability, delaying kill date increased barley above-ground biomass and N uptake from deep soil layers; little differences were observed in vetch. Postponing kill date increased the C/N ratio and the fiber content of plant residues. Ground cover reached >80% by the first kill date (∼1250°C days). Kill date was a means to control soil inorganic N by balancing the N retained in the residue and soil, and showed promise for mitigating N losses. The early kill date decreased the risk of water and N pre-emptive competition by reducing soil depletion, preserving rain harvested between kill dates and allowing more time for N release in spring. The soil potentially mineralizable N was enhanced by the CC and kill date delay. Therefore kill date is a crucial management variable for maximizing the CC benefits in agricultural systems.
PreSEIS: A Neural Network-Based Approach to Earthquake Early Warning for Finite Faults

The major challenge in the development of earthquake early warning (EEW) systems is the achievement of a robust performance at largest possible warning time. We have developed a new method for EEW—called PreSEIS (Pre-SEISmic)—that is as quick as methods that are based on single station observations and, at the same time, shows a higher robustness than most other approaches. At regular timesteps after the triggering of the first EEW sensor, PreSEIS estimates the most likely source parameters of an earthquake using the available information on ground motions at different sensors in a seismic network. The approach is based on two-layer feed-forward neural networks to estimate the earthquake hypocenter location, its moment magnitude, and the expansion of the evolving seismic rupture. When applied to the Istanbul Earthquake Rapid Response and Early Warning System (IERREWS), PreSEIS estimates the moment magnitudes of 280 simulated finite faults scenarios (4.5≤M≤7.5) with errors of less than ±0.8 units after 0.5 sec, ±0.5 units after 7.5 sec, and ±0.3 units after 15.0 sec. In the same time intervals, the mean location errors can be reduced from 10 km over 6 km to less than 5 km, respectively. Our analyses show that the uncertainties of the estimated parameters (and thus of the warnings) decrease with time. This reveals a trade-off between the reliability of the warning on the one hand, and the remaining warning time on the other hand. Moreover, the ongoing update of predictions with time allows PreSEIS to handle complex ruptures, in which the largest fault slips do not occur close to the point of rupture initiation. The estimated expansions of the seismic ruptures lead to a clear enhancement of alert maps, which visualize the level and distribution of likely ground shaking in the affected region seconds before seismic waves will arrive.
Zaïre: the Shattered Illusion of the Integral State

Zaïre, by the early 1990s, by some accounts had all but vanished. One senior American diplomat described it as nothing more than the presidential vessel ‘Kamanyola’ anchored safely offshore in the Zaïre River, an élite praetorian guard compensated in hard currency, the remote marble city of Gbadolite, a shrivelled state superstructure nourished by diamond smuggling. Its perennial President, Mobutu Sese Seko, was characterised contemptuously by a French official as ‘a walking bank account in a leopard-skin cap’. More than a decade ago, a former publicist for the central régime had relegated the once-powerful state to a zone of non-existence: ‘The state does not exist or no longer exists in Za’. The 1992 National Conference resolved to expunge Zaire from history by restoring its earlier colonial and post-colonial nomenclature of ‘Congo’.
The Effect of Education on Adult Health and Mortality: Evidence from Britain

There is a strong, positive and well-documented correlation between education and health outcomes. There is much less evidence on the extent to which this correlation reflects the causal effect of education on health - the parameter of interest for policy. In this paper we attempt to overcome the difficulties associated with estimating the causal effect of education on health. Our approach exploits two changes to British compulsory schooling laws that generated sharp differences in educational attainment among individuals born just months apart. Using regression discontinuity methods, we confirm that the cohorts just affected by these changes completed significantly more education than slightly older cohorts subject to the old laws. However, we find little evidence that this additional education improved health outcomes or changed health behaviors. We argue that it is hard to attribute these findings to the content of the additional education or the wider circumstances that the affected cohorts faced (e.g., universal health insurance). As such, our results suggest caution as to the likely health returns to educational interventions focused on increasing educational attainment among those at risk of dropping out of high school, a target of recent health policy efforts.
Dynamics of a Mobile RNA of Potato Involved in a Long-Distance Signaling Pathway[W][OA]

BEL1-like transcription factors interact with Knotted1 types to regulate numerous developmental processes. In potato (Solanum tuberosum), the BEL1 transcription factor St BEL5 and its protein partner POTH1 regulate tuber formation by mediating hormone levels in the stolon tip. The accumulation of St BEL5 RNA increases in response to short-day photoperiods, inductive for tuber formation. RNA detection methods and heterografting experiments demonstrate that BEL5 transcripts are present in phloem cells and move across a graft union to localize in stolon tips, the site of tuber induction. This movement of RNA to stolon tips is correlated with enhanced tuber production. Overexpression of BEL5 transcripts that include the untranslated sequences of the BEL5 transcript endows transgenic lines with the capacity to overcome the inhibitory effects of long days on tuber formation. Addition of the untranslated regions leads to preferential accumulation of the BEL5 RNA in stolon tips under short-day conditions. Using a leaf-specific promoter, the movement of BEL5 RNA to stolon tips was facilitated by a short-day photoperiod, and this movement was correlated with enhanced tuber production. These results implicate the transcripts of St BEL5 in a long-distance signaling pathway that are delivered to the target organ via the phloem stream.
Robust Gene Expression Signature from Formalin-Fixed Paraffin-Embedded Samples Predicts Prognosis of Non–Small-Cell Lung Cancer Patients

Purpose: The requirement of frozen tissues for microarray experiments limits the clinical usage of genome-wide expression profiling by using microarray technology. The goal of this study is to test the feasibility of developing lung cancer prognosis gene signatures by using genome-wide expression profiling of formalin-fixed paraffin-embedded (FFPE) samples, which are widely available and provide a valuable rich source for studying the association of molecular changes in cancer and associated clinical outcomes. Experimental Design: We randomly selected 100 Non–Small-Cell lung cancer (NSCLC) FFPE samples with annotated clinical information from the UT-Lung SPORE Tissue Bank. We microdissected tumor area from FFPE specimens and used Affymetrix U133 plus 2.0 arrays to attain gene expression data. After strict quality control and analysis procedures, a supervised principal component analysis was used to develop a robust prognosis signature for NSCLC. Three independent published microarray datasets were used to validate the prognosis model. Results: This study showed that the robust gene signature derived from genome-wide expression profiling of FFPE samples is strongly associated with lung cancer clinical outcomes and can be used to refine the prognosis for stage I lung cancer patients, and the prognostic signature is independent of clinical variables. This signature was validated in several independent studies and was refined to a 59-gene lung cancer prognosis signature. Conclusions: We conclude that genome-wide profiling of FFPE lung cancer samples can identify a set of genes whose expression level provides prognostic information across different platforms and studies, which will allow its application in clinical settings. Clin Cancer Res; 17(17); 5705–14. ©2011 AACR.
Managerial sex role stereotyping: a New Zealand perspective

The relationship between sex role stereotypes and the characteristics perceived necessary for managerial success was examined among 153 male and 165 female commerce students in New Zealand using the 92‐item Schein Descriptive Index. The results were compared with those from similar studies conducted in the USA, Great Britain, Canada, Germany, Japan, and the People’s Republic of China. Both male and female commerce students in New Zealand perceive successful middle managers as possessing the characteristics, attitudes and temperaments commonly ascribed to men in general and, to a lesser degree, women in general. Discriminant analysis was used to identify the specific attributes used by respondents to distinguish the stereotypes.
Transient Frequency-Domain Thermal Measurements With Applications to Electronic Packaging

Non-uniform power distribution, increased die-size, and multiple-chip modules present new challenges for the thermal management of modern integrated circuit (IC) packages. Thermal characterization techniques capable of resolving partial thermal resistances at the component level have received increased emphasis in development of advanced packaging technologies. This paper aims to develop a practical method for thermal characterization of IC packages using the frequency-domain measurement technique as a complementary technique to the widely used time-domain thermal transient measurement technique. This paper discusses practical implementation of the technique and demonstrates both thermal modeling and experimental results. Thermal impedances measured in frequency-domain yield the structure function, which describes the dynamic thermal response of the device based on thermal RC network analysis. Various applications of this technique in thermal characterization of the IC packages subjected to field conditions are also discussed.
The effects of curvature on fluid flow fields in pulmonary artery models: flow visualization studies.

In vitro pulsatile flow visualization studies were conducted to assess the effects of varying radii of curvature of the right ventricular outflow tract (RVOT) and main pulmonary artery (MPA) on the flow fields in the main, right, and left pulmonary arteries of a one month lamb pulmonary artery model. Three glass flow-through models were studied; one with no curvature, one with the correct anatomic curvature, and one with an overaccentuated curvature on the RVOT and MPA. All other geometric parameters were held constant. Pulsatile flow visualization studies were conducted at nine flow conditions; heart rates of 70, 100, and 140 bpm, and cardiac outputs of 1.5, 2.5 and 3.5 l/min with corresponding mean pulmonary pressures of 10, 20, and 30 mmHg. Changes were observed in the pulmonary flow fields as the curvature of the outflow tract, heart rate and mean pulmonary pressure were varied. An increase in vessel curvature led to an increase in the overall radial nature of the flow field as well as flow separation regions which formed faster, originated further downstream, and occupied more of the vessel area. At higher heart rates, the maximum size of the separation regions decreased, while flow separation regions appeared earlier in the cardiac cycle and grew more quickly. Heart rate also affected the initiation of flow reversal; flow reversal occurred later in the cardiac cycle at lower heart rates. Both heart rate and mean pulmonary pressure influenced the stability of the pulmonary flow field and the appearance of coherent structures. In addition, an increase in mean pulmonary pressure increased the magnitude of reverse flow. (ABSTRACT TRUNCATED AT 250 WORDS)
Accuracy of teachers' judgments of students' academic achievement: A meta-analysis

This meta-analysis summarizes empirical results on the correspondence between teachers' judgments of students' academic achievement and students' actual academic achievement. The article further investigates theoretically and methodologically relevant moderators of the correlation between the two measures. Overall, 75 studies reporting correlational data on the relationship between teachers' judgments of students' academic achievement and students' performance on a standardized achievement test were analyzed, including studies focusing on different school types, grade levels, and subject areas. The overall mean effect size was found to be . 63. The effect sizes were moderated by use of informed versus uninformed teacher judgments, with use of informed judgments leading to a higher correspondence between teachers' judgments and students' academic achievement. A comprehensive model of teacher-based judgments of students' academic achievement is provided in the Discussion. Supplemental materials: http://dx.doi. org/10.1037/a0027627.supp