Miracle-dz/UniFAR-FTUs huggingface dataset:
Sodium production in asymptotic giant branch stars

A new scenario is presented for the production of 23 Na in asymptotic giant branch (AGB) stars. The scenario takes advantage of the periodic third dredge-up episodes characteriz- ing those stars, which mix primary 12 C from their intershell layers to their surface. Two successive interpulse/pulse/dredge- up sequences are then required to produce 23 Na. During the first sequence carbon and oxygen are converted into 14 N by the hy- drogen burning shell, and subsequently transformed into 22 Ne by the helium burning shell. During the second sequence, 22 Ne is converted into 23 Na by the hydrogen burning shell, which is brought to the surface by the subsequent dredge-up episode. The 23 Na produced by this scenario is thus primary. The efficiency of this scenario is analyzed through standard evolutionary AGB model predictions combined with synthetic calculations for the surface chemical evolution. It is shown that primary 23 Na can efficiently be produced as soon as the sur- face C+N+O abundance enhancement reaches a certain level de- pending on the stellar metallicity. The required surface C+N+O abundance enhancement amounts to 0.4 dex in solar metal- licity stars, and to 0.8 dex at a metallicity five times less than solar.
Sector-Specific Training and Mobility in Germany

This article studies mobility patterns of German workers in light of a model of sector-specific human capital. Furthermore, I employ and describe little-used data on continuous on-the-job training occuring after apprenticeships. Results are presented describing the incidence and duration of continuous training. Continuous training is quite common, depite the high incidence of apprenticeships which precedes this part of a worker's career. Most previous studies have only distinguished between firm-specific and general human capital, generally concluding that training was general. Inconsistent with those conclusions, I show that German men are more likely to find a job within the same sector if they have received continuous training in that sector. These results are similar to results obtained for young U.S. workers, and suggest that sector-specific capital is an important feature of very different labor markets. Furthermore, the results suggest that the observed effect of training on mobility is sensitive to the state of the business cycle, indicating a more complex interaction between supply and demand that most theoretical models allow for. Cet article etudie la mobilite des travailleurs allemands a la lumiere d'un modele de capital humain dont la specificite est sectorielle. En outre, j'utilise et decris des donnees peu utilisees sur la formation formelle ayant lieu apres la fin d'un apprentissage. Comparativement aux Etats-Unis, un plus grand nombre de travailleurs suit une formation annuellement, et ce en depit d'une incidence elevee d'apprentissage precedent. Tandis que plusieurs autres etudes font uniquement une distinction entre capital humain specifique a une seule firme et capital humain general, je montre que les travailleurs allemands ont une plus grande probabilite de trouver un emploi dans un secteur s'ils ont suivi une formation formelle dans ce secteur. Ce resultat n'est coherent ni avec la presence de capital humain specifique a une seule firme, ni avec du capital humain completement general. Conjointement avec des resultats semblables pour des travailleurs americains, il suggere l'importance du capital humain specifique a l'industrie. Par ailleurs, l'effet de la formation sur la mobilite semble sensible a l'etat de la conjoncture, suggerant une relation entre offre et demande plus complexe que celle decrite par la plupart des modeles theoriques.
Principles of scientific research team formation and evolution

Significance Science is an activity with far-reaching implications for modern society. Understanding how the social organization of science and its fundamental unit, the research team, forms and evolves is therefore of critical significance. Previous studies uncovered important properties of the internal structure of teams, but little attention has been paid to their most basic property: size. This study fills this gap by presenting a model that successfully explains how team sizes in various fields have evolved over the past half century. This model is based on two principles: (i) smaller (core) teams form according to a Poisson process, and (ii) larger (extended) teams begin as core teams but consequently accumulate new members through the process of cumulative advantage based on productivity. Research teams are the fundamental social unit of science, and yet there is currently no model that describes their basic property: size. In most fields, teams have grown significantly in recent decades. We show that this is partly due to the change in the character of team size distribution. We explain these changes with a comprehensive yet straightforward model of how teams of different sizes emerge and grow. This model accurately reproduces the evolution of empirical team size distribution over the period of 50 y. The modeling reveals that there are two modes of knowledge production. The first and more fundamental mode employs relatively small, “core” teams. Core teams form by a Poisson process and produce a Poisson distribution of team sizes in which larger teams are exceedingly rare. The second mode employs “extended” teams, which started as core teams, but subsequently accumulated new members proportional to the past productivity of their members. Given time, this mode gives rise to a power-law tail of large teams (10–1,000 members), which features in many fields today. Based on this model, we construct an analytical functional form that allows the contribution of different modes of authorship to be determined directly from the data and is applicable to any field. The model also offers a solid foundation for studying other social aspects of science, such as productivity and collaboration.
Development and Characterization of Simple Sequence Repeat Markers Providing Genome-Wide Coverage and High Resolution in Maize

Simple sequence repeats (SSRs) have been widely used in maize genetics and breeding, because they are co-dominant, easy to score, and highly abundant. In this study, we used whole-genome sequences from 16 maize inbreds and 1 wild relative to determine SSR abundance and to develop a set of high-density polymorphic SSR markers. A total of 264 658 SSRs were identified across the 17 genomes, with an average of 135 693 SSRs per genome. Marker density was one SSR every of 15.48 kb. (C/G)n, (AT)n, (CAG/CTG)n, and (AAAT/ATTT)n were the most frequent motifs for mono, di-, tri-, and tetra-nucleotide SSRs, respectively. SSRs were most abundant in intergenic region and least frequent in untranslated regions, as revealed by comparing SSR distributions of three representative resequenced genomes. Comparing SSR sequences and e-polymerase chain reaction analysis among the 17 tested genomes created a new database, including 111 887 SSRs, that could be develop as polymorphic markers in silico. Among these markers, 58.00, 26.09, 7.20, 3.00, 3.93, and 1.78% of them had mono, di-, tri-, tetra-, penta-, and hexa-nucleotide motifs, respectively. Polymorphic information content for 35 573 polymorphic SSRs out of 111 887 loci varied from 0.05 to 0.83, with an average of 0.31 in the 17 tested genomes. Experimental validation of polymorphic SSR markers showed that over 70% of the primer pairs could generate the target bands with length polymorphism, and these markers would be very powerful when they are used for genetic populations derived from various types of maize germplasms that were sampled for this study.
Factors Controlling Multiple Tropical Cyclone Events in the Western North Pacific

Abstract The statistical feature of occurrence of multiple tropical cyclone (MTC) events in the western North Pacific (WNP) is examined during summer (June–September) for the period of 1979–2006. The number of MTC events ranged from one to eight per year, experiencing a marked interannual variation. The spatial distance between the TCs associated with MTC events is mostly less than 3000 km, which accounts for 73% of total samples. The longest active phase of an MTC event lasts for nine days, and about 80% of the MTC events last for five days or less. A composite analysis of active and inactive MTC phases reveals that positive low-level (negative upper-level) vorticity anomalies and enhanced convection and midtropospheric relative humidity are the favorable large-scale conditions for MTC genesis. About 77% of the MTC events occurred in the region where either the atmospheric intraseasonal (25–70 day) oscillation (ISO) or biweekly (10–20 day) oscillation (BWO) is in a wet phase. The overall occurrence of th.
Wearable robotics as a behavioral interface - the study of the Parasitic Humanoid

The Parasitic Humanoid (PH) is a wearable robot for modeling nonverbal human behavior. This anthropomorphic robot senses the behavior of the wearer and has the internal models to learn the process of human sensory motor integration, thereafter it begins to predict the next behavior of the wearer using the learned models. When the reliability of the prediction is sufficient, the PH outputs the errors from the actual behavior as a request for motion to the wearer. Through symbiotic interaction, the internal model and the process of human sensory motor integration approximate each other asymptotically.
The Effect of Nurses’ Self-Efficacy, Work Stress and Coping Type on Mental Health

This is a descriptive research to identify the relationship and influential factors between nurses’ mental health, self-efficacy, work stress and coping types. The subjects of this research were 210 nurses. For data collection, a structured questionnaire was used from September 10 to 20, 2014. The results are as follows: There were a negative correlation between mental health and self-efficacy and a positive correlation between mental health(r=-.493, р =<.001), and work stress, a negative correlation(r=.384, р =<.001) with the problem-based(r=-.356, р =<.001), searching for social support(r=-.232, р =.001) and positive perspectives among the coping types(r=-.342, р =<.001), and a positive correlation with hopeful expectations(r=.180, р =.009).
Experimental Tuberculosis in the Wistar Rat: A Model for Protective Immunity and Control of Infection

Background Despite the availability of many animal models for tuberculosis (TB) research, there still exists a need for better understanding of the quiescent stage of disease observed in many humans. Here, we explored the use of the Wistar rat model for the study of protective immunity and control of Mycobacterium tuberculosis (Mtb) infection. Methodology/Principal Findings The kinetics of bacillary growth, evaluated by the colony stimulating assay (CFU) and the extent of lung pathology in Mtb infected Wistar rats were dependent on the virulence of the strains and the size of the infecting inoculums. Bacillary growth control was associated with induction of T helper type 1 (Th1) activation, the magnitude of which was also Mtb strain and dose dependent. Histopathology analysis of the infected lungs demonstrated the formation of well organized granulomas comprising epithelioid cells, multinucleated giant cells and foamy macrophages surrounded by large numbers of lymphocytes. The late stage subclinical form of disease was reactivated by immunosuppression leading to increased lung CFU. Conclusion The Wistar rat is a valuable model for better understanding host-pathogen interactions that result in control of Mtb infection and potentially establishment of latent TB. These properties together with the ease of manipulation, relatively low cost and well established use of rats in toxicology and pharmacokinetic analyses make the rat a good animal model for TB drug discovery.
Plant Responses to High Frequency Electromagnetic Fields

High frequency nonionizing electromagnetic fields (HF-EMF) that are increasingly present in the environment constitute a genuine environmental stimulus able to evoke specific responses in plants that share many similarities with those observed after a stressful treatment. Plants constitute an outstanding model to study such interactions since their architecture (high surface area to volume ratio) optimizes their interaction with the environment. In the present review, after identifying the main exposure devices (transverse and gigahertz electromagnetic cells, wave guide, and mode stirred reverberating chamber) and general physics laws that govern EMF interactions with plants, we illustrate some of the observed responses after exposure to HF-EMF at the cellular, molecular, and whole plant scale. Indeed, numerous metabolic activities (reactive oxygen species metabolism, α- and β-amylase, Krebs cycle, pentose phosphate pathway, chlorophyll content, terpene emission, etc.) are modified, gene expression altered (calmodulin, calcium-dependent protein kinase, and proteinase inhibitor), and growth reduced (stem elongation and dry weight) after low power (i.e., nonthermal) HF-EMF exposure. These changes occur not only in the tissues directly exposed but also systemically in distant tissues. While the long-term impact of these metabolic changes remains largely unknown, we propose to consider nonionizing HF-EMF radiation as a noninjurious, genuine environmental factor that readily evokes changes in plant metabolism.
Study of Dataset Feature Filtering of OpCode for Malware Detection Using SVM Training Phase

Malware can be defined as any type of malicious code that has the potential to harm a computer or network. To detect unknown malware families, the frequency of the appearance of Opcode (Operation Code) sequences are used through dynamic analysis. Opcode n-gram analysis used to extract features from the inspected files. Opcode n-grams are used as features during the classification process with the aim of identifying unknown malicious code. A support vector machine (SVM) is used to create a reference model, which is used to evaluate two methods of feature reduction, which are “area of intersect” and “subspace analysis using eigenvectors. ” The SVM is configured to traverse through the dataset searching for Opcodes that have a positive impact on the classification of benign and malicious software. The dataset is constructed by representing each executable file as a set of Opcode density histograms. Classification tasks involve separating dataset into training and test data. The training sets are classified into benign and malicious software. In area of interest the characteristics of benign and malicious Opcodes are plotted as normal distributions. They are grouped into density curves of a single Opcode. The key feature to note is the overlapping area of the two density curves. In Subspace analysis the importance of individual OpCodes, are investigated by the eigenvalues and eigenvectors in subspace.PCA is used for data compression and mapping. The eigenvector filter Opcodes coincides with the SVM classify the malware Opcodes feature.
Review of reliability issues in high-k/metal gate stacks

This paper reviews some of the recent learning at IMEC in reliability research on high-k gate stacks. We show how measurement, characterization techniques and physical degradation models can be transferred from SiO2 (or SiON) single layers to SiO2(SiON)/high-k stacks. In a first part, negative bias temperature instability (NBTI) is discussed. We show how interface states created at the SiO2 (or SiON)/substrate interface determine to a large extend the NBTI. Nitridation has a strong negative impact on NBTI, while thickness or composition of the high-k layer have nearly no influence. In a second part, we discuss the effect of bulk traps in the high-k layer. These traps cause fast Vt-instability and hysteresis, as well as significant positive bias temperature instability (PBTI). Additional bulk traps are created under electrical stress and form percolating paths of two or more traps causing soft breakdown (SBD). At low voltage and with metal gates, the SBD-leakage path develops into a hard breakdown (HBD) after some further wear-out time. We summarize the methodology to come to a complete reliability prediction that includes multiple SBDs and HBD. In high-k stacks, the leakage current increase due to multiple SBDs can be a reliability threat for some applications.
A Heuristic Search Algorithm for Re-routing of On-Chip Networks in The Presence of Faulty Links and Switches

The decreasing manufacturing yield of integrated circuits, as a result of rising complexity and decreased feature size, and the emergence of NoC-based design techniques, has necessitated the search for network reconfiguration techniques for reusing NoCs with faulty components. In this paper, we propose a new method to cope with the problem of faulty components in mesh-based on-chip networks. The method is based on using programmable routing tables in network switches. We propose a heuristic algorithm to search for a valid configuration for these routing tables when several physical faults occur in communication links, switch ports, routing tables and routing logics. The algorithm considerably reduces the required search effort as compared to the exhaustive search method.
The Long-Term Effects of Type 1 Diabetes Treatment and Complications on Health-Related Quality of Life

OBJECTIVE To examine the long-term effects of type 1 diabetes treatment, metabolic control, and complications on health-related quality of life (HRQOL). RESEARCH DESIGN AND METHODS A total of 1,441 participants, initially 13–39 years of age, were followed for an average of 23.5 years as part of the Diabetes Control and Complications Trial (DCCT) and the Epidemiology of Diabetes Interventions and Complications (EDIC) follow-up study. The Diabetes Quality-of-Life questionnaire (DQOL) was administered annually during DCCT and every other year during EDIC. Biomedical data, including HbA1c levels, exposure to severe hypoglycemia, intercurrent psychiatric events, and development of diabetes complications were collected at regular intervals throughout the follow-up. RESULTS Mean total DQOL scores were not significantly different between the former DCCT intensive and conventional treatment groups (DCCT baseline, 78 ± 8 vs. 78 ± 9; EDIC year 17, 75 ± 11 vs. 74 ± 11). Over the course of the study, a drop of ≥5 points in DQOL score from DCCT baseline maintained on two successive visits occurred in 755 individuals and was associated with increased HbA1c, albumin excretion rate, mean blood pressure, BMI, and occurrence of hypoglycemic events requiring assistance. Lower DQOL scores after 23.5 years of follow-up were associated with prior development of retinopathy (P = 0.0196), nephropathy (P = 0.0019), and neuropathy (P < 0.0001) as well as self-reported chest pain (P = 0.0004), decreased vision in both eyes (P = 0.0005), painful paresthesias (P < 0.0001), recurrent urinary incontinence (P = 0.0001), erectile dysfunction (P < 0.0001), and history of psychiatric events (P < 0.0001). CONCLUSIONS Among DCCT/EDIC participants, worsening metabolic control, serious diabetes complications and their associated symptoms, and development of psychiatric conditions led to decreased HRQOL.
Measurement of camera response function based on polarizer

Measurement of camera response function (CRF) has become an important technique in the field of computer graphics and radiance measurement. It can be used to achieve accurate modeling and high dynamic range imaging. A method was developed in this paper by using a polariscope to provide accurate radiance for direct measurement of the CRF. The experimental results show that the accuracy of the estimated CRF obtained by the new approach is about 5% better than that of the previous method.
Bayesian identification of protein differential expression in multi-group isobaric labelled mass spectrometry data

Abstract In this paper we develop a Bayesian statistical inference approach to the unified analysis of isobaric labelled MS/MS proteomic data across multiple experiments. An explicit probabilistic model of the log-intensity of the isobaric labels’ reporter ions across multiple pre-defined groups and experiments is developed. This is then used to develop a full Bayesian statistical methodology for the identification of differentially expressed proteins, with respect to a control group, across multiple groups and experiments. This methodology is implemented and then evaluated on simulated data and on two model experimental datasets (for which the differentially expressed proteins are known) that use a TMT labelling protocol.
Graph-Based Hyperspectral Image Classification Using Outliers Detection Based on Spatial Information and Estimating of the Number of GMM Mixtures

In this article is tried to improve the hyper spectral image classification by expectation maximization (EM) algorithm with proposed approaches for estimate the number of the mixture for image classes, covariance matrix correction and outlier detection. by decrease the number of the mixtures of an hyper spectral image, the time of the algorithm has decreased and by covariance matrix correction the accuracy and the validation of the classification could increased for the classes that have a few training sample. Because the EM algorithm is an iterative algorithm, if in one of the step occur an error in classification, this error inter in the next steps and decrease the accuracy and the validation of the classification. In this article this problem has addressed by outliers identification in each step and remove them for parameter estimation in the next step. Therefore, it is prevented from error propagation and increases the accuracy and the credit of the classification.
Self-Conscious or Self-Confident? A Diary Study Conceptualizing the Social Accessibility of Assistive Technology

With the recent influx of smartphones, tablets, and wearables such as watches and glasses, personal interactive device use is increasingly visible and commonplace in public and social spaces. Assistive Technologies (ATs) used by people with disabilities are observable to others and, as a result, can affect how AT users are perceived. This raises the possibility that what we call “social accessibility” may be as important as “functional accessibility” when considering ATs. But, to date, ATs have almost exclusively been regarded as functional aids. For example, ATs are defined by the Technical Assistance to the States Act as technologies that are “used to increase, maintain or improve functional capabilities of individuals with disabilities. ” To investigate perceptions and self-perceptions of AT users, we conducted a diary study of two groups of participants: people with disabilities and people without disabilities. Our goal was to explore the types of interactions and perceptions that arise around AT use in social and public spaces. During our 4-week study, participants with sensory disabilities wrote about feeling either self-conscious or self-confident when using an assistive device in a social or public situation. Meanwhile, participants without disabilities were prompted to record their reactions and feelings whenever they saw ATs used in social or public situations. We found that AT form and function does influence social interactions by impacting self-efficacy and self-confidence. When the design of form or function is poor, or when inequality between technological accessibility exists, social inclusion is negatively affected, as are perceptions of ability. We contribute a definition for the “social accessibility” of ATs and subsequently offer Design for Social Accessibility (DSA) as a holistic design stance focused on balancing an AT user's sociotechnical identity with functional requirements.