Miracle-dz/UniFAR-FTUs huggingface dataset:
Modeling Reveals Bistability and Low-Pass Filtering in the Network Module Determining Blood Stem Cell Fate

Combinatorial regulation of gene expression is ubiquitous in eukaryotes with multiple inputs converging on regulatory control elements. The dynamic properties of these elements determine the functionality of genetic networks regulating differentiation and development. Here we propose a method to quantitatively characterize the regulatory output of distant enhancers with a biophysical approach that recursively determines free energies of protein-protein and protein-DNA interactions from experimental analysis of transcriptional reporter libraries. We apply this method to model the Scl-Gata2-Fli1 triad—a network module important for cell fate specification of hematopoietic stem cells. We show that this triad module is inherently bistable with irreversible transitions in response to physiologically relevant signals such as Notch, Bmp4 and Gata1 and we use the model to predict the sensitivity of the network to mutations. We also show that the triad acts as a low-pass filter by switching between steady states only in response to signals that persist for longer than a minimum duration threshold. We have found that the auto-regulation loops connecting the slow-degrading Scl to Gata2 and Fli1 are crucial for this low-pass filtering property. Taken together our analysis not only reveals new insights into hematopoietic stem cell regulatory network functionality but also provides a novel and widely applicable strategy to incorporate experimental measurements into dynamical network models.
Negative affectivity and workplace deviance: the moderating role of ethical climate

This study investigates (1) the relationship between employees’ trait of negative affectivity (NA) and workplace deviance and (2) the moderating role of ethical climate in the above relationship. Data was collected from 310 employees in 40 Taiwanese companies, and hierarchical linear modeling was used to test the hypotheses. Results show that NA was positively related to workplace deviance. In addition, the rules climate weakened the relationship between NA and workplace deviance, and both the instrumental climate and the caring climate strengthened the relationship between NA and workplace deviance. Managerial implications and future research directions are also discussed.
Comparison of bleomycin-detectable iron and labile plasma iron assays.

To the Editor: Non–transferrin-bound iron (NTBI)1 is detected in the plasma of patients with diseases in which the transferrin-binding capacity for iron is exceeded by a massive iron overload, such as in certain forms of thalassemia and hemochromatosis, repeated blood transfusions, or bone marrow failure. NTBI may occur in plasma as insoluble polynuclear ferrihydrate species, as Fe(III) citrate or acetate complexes, or bound to certain flavonoids, amino acids, albumin, or modified albumin. Excess iron is harmful because it causes oxidative stress, accumulates in and damages tissues, and enhances the growth of pathogens. Therefore, the measurement of NTBI is of clinical importance, because NTBI may be used as an indicator of systemic iron overload and iron toxicity (1, 2). We compared 2 NTBI assays: a labile plasma iron (LPI) assay that uses desferrioxamine as the iron chelator (3) and a microwell modification of a bleomycin-detectable iron (BDI) assay (2). The BDI assay is an indirect method based on the formation redox-active complexes between NTBI in the sample and the bleomycin reagent. …
On the linear convergence of descent methods for convex essentially smooth minimization

Consider the problem of minimizing, over a polyhedral set, the composition of an affine mapping with a strictly convex essentially smooth function. A general result on the linear convergence of descent methods for solving this problem is presented. By applying this result, the linear convergence of both the gradient projection algorithm of Goldstein and Levitin and Polyak, and a matrix splitting algorithm using regular splitting, is established. The results do not require that the cost function be strongly convex or that the optimal solution set be bounded. The key to the analysis lies in a new error bound for estimating the distance from a feasible point to the optimal solution set.
On the potential of hybrid route/relay schemes

The objective of increasing capacity in mobile ad-hoc networks (MANETs) by exploiting the mobility of nodes has produced interesting but rather unrealistic results. The throughput improvement is not followed by reasonable delay performance, and in realistic settings there is a need to compensate for the potentially low mobility of all, or parts of, the network. We explore the throughput/delay tradeoff by attempting to utilize all possible service (transmission) opportunities that may exist. To this end, a measure of redundancy is introduced and its impact characterized. The definition of redundancy admits both the replication of data items as well as the traversal of paths. We study three schemes, where the third is a new proposal for a hybrid scheme that balances off a limited form of routing with relayed packet propagation. We find that the hybrid is resilient to the impact of mobility, providing good performance even at low mobility settings.
Free English and Czech telephone speech corpus shared under the CC-BY-SA 3.0 license

We present a dataset of telephone conversations in English and Czech, developed for training acoustic models for automatic speech recognition (ASR) in spoken dialogue systems (SDSs). The data comprise 45 hours of speech in English and over 18 hours in Czech. Large part of the data, both audio and transcriptions, was collected using crowdsourcing, the rest are transcriptions by hired transcribers. We release the data together with scripts for data pre-processing and building acoustic models using the HTK and Kaldi ASR toolkits. We publish also the trained models described in this paper. The data are released under the CC-BY-SA~3.0 license, the scripts are licensed under Apache~2.0. In the paper, we report on the methodology of collecting the data, on the size and properties of the data, and on the scripts and their use. We verify the usability of the datasets by training and evaluating acoustic models using the presented data and scripts.
The Influence of Anxiety Level, Eye-Movement and Type of Information on an Eyewitness’ Memory of a Crime.

Eyewitness testimony is widely used as evidence in court (Weber and Brewer, 2008) However, many factors that influence a witness’ memory of a crime means that the credibility is questionable, which can have huge repercussions on the conviction of criminals (Albright, 2017). Examples of those factors include a person’s level of anxiety (Easterbrook, 1959) and eye movement (van den Hout and Engelhard, 2012) at the crime scene. This study aims to look at level of anxiety, eye movement and the type of information and their influence on eyewitness memory, by investigating the number of correctly answered central and peripheral questions in high and low anxiety level groups, and horizontal, vertical and none eye movement groups. The study used an opportunity sample of 30 people between the ages of 18 – 50. Two mixed ANOVA’s revealed a non-significant interaction between the level of anxiety and the correctly answered central and peripheral questions relating to the crime. Subsequently, there was a non-significant interaction between the type of eye movement and the correctly answered central and peripheral questions. The findings are discussed with relation to future research.
The Influence of Professional Competence and Working Environment to The Teachers Performance of The Economic Teachers in Senior High School At Pemalang Regency Through Their Working Motivation

This study aims to analyze the influence of professional competence on the performance of economic teachers, professional competence on the performance of economic teachers through work motivation, work environment on teacher economic performance, work environment on teacher economic performance through work motivation, and work motivation on teacher economic performance. Analytical techniques used descriptive analysis and path analysis. The results showed that there is a positive and significant influence of professional competence on teacher economic performance of 17.8%. Professional competence on teacher economy performance through work motivation is 28%. Working environment on teacher economics performance amounted to 41.2%. Work environment on teacher economy performance through work motivation of 77.7%. Motivation of work on teacher economic performance equal to 48,2%. The conclusion of this study is the teacher performance is getting better when the professional competence of a teacher is better, the total value is greater than the direct influence of professional competence to the economic teachers performance, the better working environment makes the better teacher economic performance, the total value is greater than the direct influence of the work environment to the economic teacher performance, and the more economic teachers have a high work motivation, the better their performance.
A Quantitative and Qualitative Study of Facebook Privacy using the Antecedent-Privacy Concern-Outcome Macro Model

Information privacy is a complex and important phenomenon to understand. Because of this, several recent review articles have integrated findings across various studies and contexts. In this study we investigate information privacy in the online social networking context using the Antecedent-Privacy Concern-Outcome (APCO) Macro Model as the theoretical lens. We use both quantitative and qualitative data collected in a survey of Facebook users. Online social networking provides a rich window into privacy concerns and the resulting behavioral reactions. By analyzing both types of data, we are able to show additional support and insights for our hypotheses tests. These results provide future research opportunities that include modifying the APCO model and refining its constructs to be more context and risk-specific.
How Much Metadata Do We Need in Music Recommendation? A Subjective Evaluation Using Preference Sets

In this work we consider distance-based approaches to music recommendation, relying on an explicit set of music tracks provided by the user as evidence of his/her music preferences. Firstly, we propose a purely content-based approach, working on low-level (timbral, temporal, and tonal) and inferred high-level semantic descriptions of music. Secondly, we consider its simple refinement by adding a minimum amount of genre metadata. We compare the proposed approaches with one content-based and three metadata-based baselines. As such, we consider content-based approach working on inferred semantic descriptors, a tag-based recommender exploiting artist tags, a commercial black-box recommender partially employing collaborative filtering information, and a simple genre-based random recommender. We conduct a listening experiment with 19 participants. The obtained results reveal that although the low-level/semantic content-based approach does not achieve the performance of the baseline working exclusively on the inferred semantic descriptors, the proposed refinement provides significant improvement in the listeners’ satisfaction comparable with metadata-based approaches, and surpasses these approaches by the number of novel relevant recommendations. We conclude that the proposed content-based approach refined by simple genre metadata is suited for music discovery not only in the long-tail but also within popular music items.
Reduced osmolarity oral rehydration solution for treating dehydration due to diarrhoea in children: systematic review

Abstract Objectives: To compare reduced osmolarity oral rehydration solution with standard World Health Organization oral rehydration solution in children with acute diarrhoea. Design: Systematic review of randomised controlled trials. Studies: 15 randomised controlled trials including 2397 randomised patients. Outcomes: The primary outcome was unscheduled intravenous infusion; secondary outcomes were stool output, vomiting, and hyponatraemia. Results: In a meta-analysis of nine trials for the primary outcome, reduced osmolarity rehydration solution was associated with fewer unscheduled intravenous infusions compared with standard WHO rehydration solution (odds ratio 0.61, 95% confidence interval 0.47 to 0.81). Three trials reported that no patients required unscheduled intravenous infusion. Trials reporting secondary outcomes suggested that in the reduced osmolarity rehydration solution group, stool output was lower (standardised mean difference in the log scale −0.214 (95% confidence interval −0.305 to −0.123; 13 trials) and vomiting was less frequent (odds ratio 0.71, 0.55 to 0.92; six trials). Six trials sought presence of hyponatraemia, with events in three studies, but no significant difference between the two arms. Conclusion: In children admitted to hospital with dehydration associated with diarrhoea, reduced osmolarity rehydration solution is associated with reduced need for unscheduled intravenous infusions, lower stool volume, and less vomiting compared with standard WHO rehydration solution. What is already known on this topic Oral rehydration solution prevents death from diarrhoea in many developing countries What this study adds Children receiving a reduced osmolarity rehydration solution were less likely to need intravenous infusion than those receiving WHO rehydration solution Reduced osmolarity rehydration solution also reduced stool output and vomiting No difference was found in rates of hyponatraemia
Arabic Text Categorization using Rocchio Model

Automatic text categorization is considered an important application in natural language processing. It is the process of assigning a document to predefined categories based on its content. In this research, some well-known techniques developed for classifying English text are considered to be applied on Arabic. This work focuses on applying the well-known Rocchio (Centroid-based) technique on Arabic documents. This technique uses centroids to define good class boundaries. The centroid of a class c is computed as center of mass of its members. Arabic language is highly inflectional and derivational which makes text processing a complex task. In the proposed work, first Arabic text is preprocessed using tokenization and stemming techniques. Then, the Rocchio Algorithm is adopted and adapted to be applied to classify Arabic documents. The implemented algorithm is evaluated using a corpus containing a set of actual documents. The results show that the adapted Rocchio algorithm is applicable to categorize Arabic text. Ratios of 92.2%, 92.7%, and 92.1% of Micro-averaging recall, precision, and F-measure respectively are achieved, against a data set of 500 Arabic text documents covering five distinct categories.
The Opposing Mediational Effects of Apprehensive Threat and Motivational Threat When Inoculating Against Reactance to Health Promotion

ABSTRACT This investigation assessed how a threatening inoculation forewarning about psychological reactance affected message targets’ derogation of a subsequent health appeal. A two-mediator model showed that apprehensive threat—the traditional operationalization of inoculation’s psychological function based on fear arousal—and motivational threat—an alternative operationalization of inoculation’s psychological function based on the activation of thoughtful counterargumention—both significantly intervened between the experimental inoculation treatment and message derogation, with motivation leading to less and apprehension leading to more derogation of the health appeal. The inconsistent mediational effects were of equal magnitude, which masked the significant indirect effects of inoculation as a null total effect. Theoretical and methodological implications of these results are discussed.
Understanding Image and Text Simultaneously: a Dual Vision-Language Machine Comprehension Task

We introduce a new multi-modal task for computer systems, posed as a combined vision-language comprehension challenge: identifying the most suitable text describing a scene, given several similar options. Accomplishing the task entails demonstrating comprehension beyond just recognizing "keywords" (or key-phrases) and their corresponding visual concepts. Instead, it requires an alignment between the representations of the two modalities that achieves a visually-grounded "understanding" of various linguistic elements and their dependencies. This new task also admits an easy-to-compute and well-studied metric: the accuracy in detecting the true target among the decoys. The paper makes several contributions: an effective and extensible mechanism for generating decoys from (human-created) image captions; an instance of applying this mechanism, yielding a large-scale machine comprehension dataset (based on the COCO images and captions) that we make publicly available; human evaluation results on this dataset, informing a performance upper-bound; and several baseline and competitive learning approaches that illustrate the utility of the proposed task and dataset in advancing both image and language comprehension. We also show that, in a multi-task learning setting, the performance on the proposed task is positively correlated with the end-to-end task of image captioning.
Influencia de los hábitos de sueño en los alumnos de primer ciclo de Educación Secundaria = Influence of sleep habits in students of the first cycle of Secondary Education

ResumenEn los últimos años, ha habido una gran controversia sobre cuál es la cantidad óptima que deben dormir los estudiantes para afrontar con éxito la jornada escolar. Así, por un lado, se ha realizado una revisión del marco teórico basado en las investigaciones y estudios de diferentes autores sobre qué es el sueño, cuáles son las características del sueño en la adolescencia y cómo afecta el sueño a la capacidad de aprendizaje en los adolescentes. Por otro lado, también se ha realizado un estudio sobre los hábitos de sueño a un grupo de adolescentes de entre 12 y 13 años de tres centros escolares de la Comunidad de Madrid, con una muestra de 420 estudiantes de 1º y 2º de E.S. O, comparando los resultados obtenidos con las investigaciones referenciadas en el marco teórico, para contrastar la validez de las mismas. Además, se han consultado los expedientes académicos de los alumnos, a fin de comprobar si la cantidad de horas de sueño es un factor decisivo a la hora de obtener mejores o peores calificaciones. En conclusión, los resultados muestran una relación entre las horas de sueño y el rendimiento académico, donde se aconseja dormir un mínimo de 7.5 horas en la etapa de primer ciclo de secundaria y deja entre ver que quizá sea necesario un reajuste de los horarios escolares debido a los hábitos de los estudiantes.AbstractIn recent years, there has been a great controversy over which is the optimum amount of sleep a student should get to face successfully a school day. Thus, on one side, there has been a review of a theoretical framework based on investigation and researches of different authors about what sleep is, which the characteristics of sleep in the adolescence are, and how sleep affects the capacity of learning in adolescences. On the other side, the research of sleep habits was carried out with a group of adolescences between 12 and 13 years old from tree educational centers of Madrid Community, with a sample of 420 students of the first and the second cycle of Compulsory Secondary Education, comparing obtained results with the researches referenced in the theoretical framework, in order to contrast the validity of these researches. Moreover, the school records of the students were consulted with an aim to check whether the amount of sleeping hours is a decisive factor to obtain better or worse scores. In conclusion, the results show a relation between sleeping hours and academic performance, recommending sleeping minimum 7.5 hours during the stage of the first cycle of secondary education and rising the possible necessity to readjust school timetable according to the habits of the students.
Information technology and supply chain collaboration: moderating effects of existing relationships between partners

Previous studies suggest that information technology (IT) is critical to the development of collaboration between supply chain partners. Our study posits that the effect of IT is not predetermined by its technological capabilities. Rather, its effect on interorganizational collaboration is the emergent properties of the interplay between IT and existing relationships between partners. Based on the literature, we selected four dimensions of supplier-retailer relationship (trust, interdependence, long-term orientation, and information sharing) to investigate the moderating effect of existing relationships on the efficacy of IT. Using case research that involved direct observation and systematic interviews with five pairs of suppliers and retailers, we verified that existing formative contexts between partners both enable and constrain the effect of IT on interorganizational collaboration. In addition, IT reinforces and stabilizes the already existing interorganizational structures and arrangements. Overall, the results suggest that cooperative formative contexts between partners should precede the IT-based interorganizational linkage effort.
Debiasing the Mind Through Meditation

In the research reported here, we investigated the debiasing effect of mindfulness meditation on the sunk-cost bias. We conducted four studies (one correlational and three experimental); the results suggest that increased mindfulness reduces the tendency to allow unrecoverable prior costs to influence current decisions. Study 1 served as an initial correlational demonstration of the positive relationship between trait mindfulness and resistance to the sunk-cost bias. Studies 2a and 2b were laboratory experiments examining the effect of a mindfulness-meditation induction on increased resistance to the sunk-cost bias. In Study 3, we examined the mediating mechanisms of temporal focus and negative affect, and we found that the sunk-cost bias was attenuated by drawing one’s temporal focus away from the future and past and by reducing state negative affect, both of which were accomplished through mindfulness meditation.
SEU effects in registers and in a dual-ported static RAM designed in a 0.25 $\mu$m CMOS technology for applications in the LHC

A dedicated high-speed 18 Kbit static memory featuring synchronous mode, parity and dual port access has been designed and fabricated in a quarter micron 3 metals commercial CMOS technology. This SRAM has been designed to be a test vehicle to measure Single Event Upset (SEU) effects on a real circuit. The measurements have been performed at the cyclotron of Louvain-la-Neuve, Belgium, with a proton and heavy ion beam. We present the experimental cross-section curve for the RAM chip, together with a detailed study of the SEU phenomenon on dedicated test structures (shift registers) integrated in the same technology. Finally, we give an estimate for the upset rate the memory chip will experience in LHC.