Miracle-dz/UniFAR-FTUs huggingface dataset:
Study of microwave plasma discharge assisted by electron cyclotron resonance for hydrogenation of polycrystalline silicon thin film solar cells

In this work we have investigated the microwave plasma discharge assisted by electron cyclotron resonance for hydrogenation of thin film polycrystalline npp silicon solar cells in terms of defects passivation and surface etching. The polycrystalline silicon films were formed by high temperature chemical vapor deposition. Influence of various process parameters such as microwave plasma power, hydrogenation time and substrate temperature on the sheet resistance of the n emitter region and on the open-circuit voltage (Voc) of the n pp structure were investigated. The n emitter region was obtained by phosphorus diffusion using a spin-on dopant P507 solution from filmtronics. After 75 min of hydrogenation, Voc is greatly improved by a factor of 2.5 and reaches values up to 440 mV at 500°C and microwave power of 650 W. This enhancement in Voc after plasma hydrogenation is originating from a reducing recombination velocity at the grain boundaries due to the passivation of dangling bonds by hydrogen atoms, leading to an important increasing of the diffusion length. Above our hydrogenation parameters values, degradation is observed, especially an etching of the emitter region. Reasons for such behavior will thoroughly discuss. Keywords-polycristalline silicon; grain boundary; plasma hydrogenation; defects passivation; solar cells
Telomeres as integrative markers of exposure to stress and adversity: a systematic review and meta-analysis

Telomeres have been proposed as a biomarker that integrates the impacts of different kinds of stress and adversity into a common currency. There has as yet been no overall comparison of how different classes of exposure associate with telomeres. We present a meta-analysis of the literature relating telomere measures to stresses and adversities in humans. The analysed dataset contained 543 associations from 138 studies involving 402,116 people. Overall, there was a weak association between telomere variables and exposures (greater adversity, shorter telomeres: r = −0.15, 95% CI - 0.18 to −0.11). This was not driven by any one type of exposure, since significant associations were found separately for physical diseases, environmental hazards, nutrition, psychiatric illness, smoking, physical activity, psychosocial and socioeconomic exposures. Methodological features of the studies did not explain any substantial proportion of the heterogeneity in association strength. There was, however, evidence consistent with publication bias, with unexpectedly strong negative associations reported by studies with small samples. Restricting analysis to sample sizes greater than 100 attenuated the overall association substantially (r = −0.09, 95% CI −0.13 to −0.05). Most studies were underpowered to detect the typical association magnitude. The literature is dominated by cross-sectional and correlational studies which makes causal interpretation problematic.
The Expression of ICER Under the Control of the Ovarian CYP19A1 Promoter in Zebrafish Ovaries Danio rerio

Infertility, according to the World Health Organization, is defined as the failure to conceive after twelve months of regular unprotected sexual intercourse. A recent study measuring the prevalence of female infertility estimated that 48.5 million women were affected globally (World Health Organization). To even begin to understand infertility is a colossal undertaking. Before we can hope to cure this disorder in humans we must first understand its pathogenesis in animal models. For this purpose, a study will be undertaken in zebrafish, Danio rerio, a popular model organism for reproductive studies (Segner, 2009). Based on a previous study in mouse models the ICER (inducible cAMP early repressor) protein has been identified as a potentiator of hyperovulation in mice (Muñiz). The ICER protein is an inducible early repressor of the cAMP second messenger system and a dominant negative autoregulator of its own expression (Molina, 1993). Based on the results of the Muñiz study, the present research will focus on the expression of ICER in zebrafish ovaries. First, it was proven via protein and RNA expression analysis that ICER is expressed in a stage-dependent manner in the zebrafish ovary during folliculogenesis. Next, based on this expression profiling, an ICER plasmid vector was designed with ICER under the control of the cyp19a1 ovarian-specific promoter. Cyp19a1 is a gonadotropin and estrogen inducible promoter predominantly expressed in the zebrafish ovary (Kazeto, 2001). This plasmid vector can be utilized in the future, in conjunction with the Tol2 transposase system in zebrafish, to study the effects of ICER overexpression in the ovary and hopefully elucidate some further understanding of the causes and pathology of infertility as well as possible treatment scenarios
Does Fear of New Car Technologies Influence Brand Loyalty Relationship

The increasing importance of technology in our daily lives has led companies to implement the latest technology on their products before marketing them to their customers. In this era of technology, fuel efficient vehicles have attracted a great deal attention with a rapidly increasing customer base in the automotive industry. Automobile companies use this as a means of increasing customers’ level of loyalty, due to the anxiety about the system installed in their cars. The purpose of this study is to investigate the indirect effects of brand service quality and brand value towards brand loyalty moderated by technology anxiety. Since moderator variables are rarely tested in the context of PLS model, the author will analyze the data by utilizing Partial Least Square (PLS) in measuring the moderating effect of technology anxiety in brand loyalty relationships. The results illustrate that technology anxiety, one of factors of Car Technology Acceptance Model (CTAM), moderates the relationship between brand service quality, brand value and brand loyalty.
An Analysis of Multilevel Checkpoint Performance Models

Periodic application checkpointing to a parallel file system has for years been the standard strategy for providing high performance computing (HPC) systems with resilience to system failures. The traditional checkpoint/restart protocol has until recently proved sufficient for mitigating the impact of these failures on application performance. However, as system sizes approach exascale levels, the frequency of failures and the time required to checkpoint/restart an exascale-size application increases and the efficiency of traditional checkpointing decreases substantially, making it no longer a viable option for providing resilience to future HPC systems. The most frequently proposed solution for providing future systems with resilience has been to design multilevel checkpointing protocols. However, the relationship between system failure rates, checkpoint/restart overhead, and duration of time between successive checkpoints is complex and finding the optimal duration of time between successive checkpoints is an open and challenging problem. This work presents a novel execution time prediction model we have developed that takes into consideration execution events that have not been considered by previous multilevel checkpointing models. We show how this model can be used to select checkpoint intervals and demonstrate why consideration of these execution events is important. We validate our work through simulation and provide a comparison to several optimization strategies proposed in other work to demonstrate the advantage gained by considering these execution events.
A Text Messaging Intervention (Txt4HappyKids) to Promote Fruit and Vegetable Intake Among Families With Young Children: Pilot Study

Background Increasing fruit and vegetable intake among low-income populations, especially children, is a priority for United States federal food assistance programs. With over 49 million federal food assistance program recipients, cost-effective and efficient methods are needed to effectively deliver nutrition education to such a large population. Objective The objective of our study was to examine the preliminary efficacy and acceptability of a text messaging intervention, Txt4HappyKids, to promote fruit and vegetable intake among families with young children. Methods The intervention was evaluated using a pre-post study design. Parents (N=72) in Alaska were recruited from venues that serve a predominantly low-income population to participate in an 11-week intervention based on social cognitive theory. Parents received two texts per week promoting child fruit and vegetable intake. Behaviors, self-efficacy, and attitudes related to fruit and vegetable intake were measured at baseline and postintervention. Perceived changes in behaviors and open-ended feedback were also collected postintervention. Results Of all participants, 67.3% (72/107) completed the intervention. We found no changes in behavior (P=.26), self-efficacy (P=.43), or attitudes (P=.35) related to fruit and vegetable intake from pre- to postintervention. Completers reported that since their participation in Txt4HappyKids, 92% (66/72) served more fruits and vegetables to their child because they thought fruits and vegetables were beneficial, 86% (62/72) tried to follow a healthier diet, 85% (61/72) tried different ways of preparing fruits and vegetables, and 81% (58/72) were more aware of the foods their child consumes. Additionally, 79% (57/72) of completers thought that Txt4HappyKids was credible, 71% (51/72) found texts useful, and 82% (59/72) would recommend it to a friend. Conclusions A text messaging intervention was not sufficient to increase fruit and vegetable intake among families with young children. However, parents felt positively impacted by Txt4HappyKids and were receptive to nutrition information, despite the absence of face-to-face contact. High satisfaction among completers indicates that text messaging may be an acceptable complement to budget-constrained nutrition programs. These findings are an important first step in developing larger multi-level interventions utilizing mobile technology; however, a more rigorous evaluation of the Txt4HappyKids intervention is warranted.
Statistics of Finite Scale Local Lyapunov Exponents in Fully Developed Homogeneous Isotropic Turbulence

The present work analyzes the statistics of finite scale local Lyapunov exponents of pairs of fluid particles trajectories in fully developed incompressible homogeneous isotropic turbulence. According to the hypothesis of fully developed chaos, this statistics is here analyzed assuming that the entropy associated with the fluid kinematic state is maximum. The distribution of the local Lyapunov exponents results in an unsymmetrical uniform function in a proper interval of variation. From this PDF, we determine the relationship between average and maximum Lyapunov exponents and the longitudinal velocity correlation function. This link, which in turn leads to the closure of von Kármán–Howarth and Corrsin equations, agrees with results of previous works, supporting the proposed PDF calculation, at least for the purposes of the energy cascade main effect estimation. Furthermore, through the property that the Lyapunov vectors tend to align the direction of the maximum growth rate of trajectories distance, we obtain the link between maximum and average Lyapunov exponents in line with the previous results. To validate the proposed theoretical results, we present different numerical simulations whose results justify the hypotheses of the present analysis.
Pronominal Anaphora Resolution Using XML TaggedDocuments

Pronominal Anaphora Resolution Using XML Tagged Documents Anaphora resolution has become a major issue in natural language processing systems; in this work we propose a resolution approach in which texts are parsed by a definite clause grammar and then converted into an XML-tagged representation, where sentence elements are marked with discourse, syntactic, and semantic attributes. This extension was made primarily to test the viability of using XML tagged documents for anaphora resolution. The XML representation allows valuable text’s enrichment with anaphoric information in an elegant and easy way. The system’s performance arises primarily from the integration of multiple knowledge sources in a modular architecture and uses constraints and preferences to select the antecedent. The developed system proposes to resolve pronominal anaphora, namely personal pronouns for French language texts.
Maximum power point tracking using neural networks for stand-alone photovoltaic system

the optimization of the photovoltaic (PV) system performance is done through the energy management stage. The first step of the optimization consists in extracting the maximum power available from the PV generator. This is done by the Maximum Power Point Tracking (MPPT) of the PV generator which varies with the irradiance, the temperature and the load. Several techniques as the ‘Perturbation and observation’ (P&O), the ‘Incremental conductance’ (INC), the ‘Power feed-back method’, the ‘Hill climbing’ are used for this tracking. In this article, we present a new MPPT algorithm, based on neural network controller (NNC), whose structure configuration is of three layer; an input layer, an output layer and a hidden layer. In order to show the functionality of the developed neural controller algorithm, we have applied it to a standalone PV system for several conditions of irradiance and temperature. The tests conducted on this NNC show that it allows the system to reach quickly the optimal performance with a stable pattern for all the cases considered. KeywordsPV system; Maximum Power Point Tracking (MPPT); Neural Network; Neural Network Controller
zeolite membranes for CO 2 / H 2 separation

Membranes are considered one of the most promising technologies for CO2 separation from industrially important gas mixtures like synthesis gas or natural gas. In order for the membrane separation process to be efficient, membranes, in addition to being cost-effective, should be durable and possess high flux and sufficient selectivity. Current CO2-selective membranes are low flux polymeric membranes with limited chemical and thermal stability. In the present work, robust and high flux ceramic MFI zeolite membranes were prepared and evaluated for separation of CO2 from H2, a process of great importance to synthesis gas processing, in a broad temperature range of 235–310 K and at an industrially relevant feed pressure of 9 bar. The observed membrane separation performance in terms of both selectivity and flux was superior to that previously reported for the state-of-the-art CO2-selective zeolite and polymeric membranes. Our initial cost estimate of the membrane modules showed that the present membranes were economically viable. We also showed that the ceramic zeolite membrane separation system would be much more compact than a system relying on polymeric membranes. Our findings therefore suggest that the developed high flux ceramic zeolite membranes have great potential for selective, cost-effective and sustainable removal of CO2 from synthesis gas.
Study on vorticity structures in late flow transition

Vorticity and vortex are two different but related concepts. This paper focuses on the investigation of vorticity generation and development, and vorticity structure inside/ outside the vortex. Vortex is a region where the vorticity overtakes deformation. Vortex cannot be directly represented by the vorticity. Except for those vorticity lines which come from and end at side boundaries, another type of vorticity, self-closed vorticity lines named vorticity rings, is numerously generated inside the domain during flow transition. These new vorticity rings are found around the hairpin vortex heads and legs. The generation and growth of vorticity rings are produced by the buildup of the vortices according to the vorticity transport equation. On the other hand, vortex buildup is a consequence of vorticity line stretching, tilting and twisting. Both new vorticity and new vortices are generated during the flow transition. According to the Helmholtz vorticity flux conservation law, vorticity line cannot be interrupted, started, or ended inside the flow field, the newly produced vorticity has only one form which is the vorticity rings. In addition, an interesting finding is that a single hairpin vortex consists of several types of vorticity lines which could come from the side boundaries, whole vorticity rings and part of vorticity rings.
Leading-edge tubercles delay stall on humpback whale (Megaptera novaeangliae) flippers

The humpback whale (Megaptera novaeangliae) is exceptional among the baleen whales in its ability to undertake acrobatic underwater maneuvers to catch prey. In order to execute these banking and turning maneuvers, humpback whales utilize extremely mobile flippers. The humpback whale flipper is unique because of the presence of large protuberances or tubercles located on the leading edge which gives this surface a scalloped appearance. We show, through wind tunnel measurements, that the addition of leading-edge tubercles to a scale model of an idealized humpback whale flipper delays the stall angle by approximately 40%, while increasing lift and decreasing drag.
NetHide: Secure and Practical Network Topology Obfuscation

Simple path tracing tools such as traceroute allow malicious users to infer network topologies remotely and use that knowledge to craft advanced denial-of-service (DoS) attacks such as Link-Flooding Attacks (LFAs). Yet, despite the risk, most network operators still allow path tracing as it is an essential network debugging tool. In this paper, we present NetHide, a network topology obfuscation framework that mitigates LFAs while preserving the practicality of path tracing tools. The key idea behind NetHide is to formulate network obfuscation as a multi-objective optimization problem that allows for a flexible tradeoff between security (encoded as hard constraints) and usability (encoded as soft constraints). While solving this problem exactly is hard, we show that NetHide can obfuscate topologies at scale by only considering a subset of the candidate solutions and without reducing obfuscation quality. In practice, NetHide obfuscates the topology by intercepting and modifying path tracing probes directly in the data plane. We show that this process can be done at line-rate, in a stateless fashion, by leveraging the latest generation of programmable network devices. We fully implemented NetHide and evaluated it on realistic topologies. Our results show that NetHide is able to obfuscate large topologies (> 150 nodes) while preserving near-perfect debugging capabilities. In particular, we show that operators can still precisely trace back > 90% of link failures despite obfuscation.
Circadian variations in blood pressure in health and disease: implications for patient management

Traditionally, blood pressure measurements have been performed in office settings and have provided the basis for all diagnostic and therapeutic decisions. However, the develop- ment of a clinically relevant 24-hour blood pressure monitoring system has added greatly to the ability of blood pressure values to confer additional clinical information, including prognostic value. Mechanistically, the circadian rhythm of blood pressure is mediated by a complex pro- cess as a part of the neurohormonal cascade. Pattern recognition of blood pressure peaks and troughs over a 24-hour period has led to categorization into specific subsets namely, ie, dip- pers, nondippers, extreme dippers, and reverse dippers. Cardiovascular risk is associated with certain pattern types, as has been demonstrated in large observational and prospective studies. The development of therapies for the purpose of restoring more pathological patterns to normal ones continues to grow. These include both pharmaceutical and device therapy. This article describes the development of 24-hour blood pressure monitoring systems, the identification of circadian blood pressure patterns, and the treatment strategies studied thus far which affect these newer blood pressure parameters.
Comparison on Effect of Eye Gaze Activities between Human-human and Human-robot Conversations in Second-Language

This paper examines how eye gaze activities are different in between human-human and human-robot conversations in second language (L2). The results show that the mainly-gazed-at listener gazes more at the speaker and he/she takes more often a ﬂoor in L2 conversations than in L1 conversations, whereas the speaker’s eye gaze activity is almost the same in both conversations. The result shows that there is a signiﬁcant positive correlation be-tween the mainly-gazed-at listener’s gazing ratio and the ratios of mainly-gazed-at listener taking a ﬂoor. Comparative analyses of eye gaze activities between human-human and human-robot conversations are also conducted. The results show that the listener gazes more at the speaker in human-robot conversations than in human-human conversations, whereas the robots do not provide the nonverbal information related to the contents of the utterances. These results may show that listeners gaze more at the speaker to show their intention to take a ﬂoor in both human-human and human-robot conversations.
Differential Sensitivities of various growth modes of Candida albicans to sixteen molecules of plant origin

Candida albicans is opportunistic fungal human pathogen. Candida infections are becoming serious concern in immuno-comprised patients. Targeting of virulence factor can be an effective strategy to combat against C. albicans infections. Invasive growth is considered as crucial factor involved in virulence of C. albicans. Studies regarding drug sensitivity of invasive mode of growth are lacking. Sixteen molecules of plant origin were analyzed to test their efficacy against invasive, peripheral filamentous and total growth of C. albicans. Out of sixteen molecules, only four molecules i.e. Carvacrol, Geraniol, Eugenol and Geranyl acetate were specific inhibitors of invasive growth and their MIC values are presented in this communication. Fourteen molecules showed inhibitory activity against peripheral filamentous growth. Toxicity studies were done using human erythrocytes. These molecules showed negligible hemolytic activity at their MIC values. In addition, these molecules inhibited cell cycle division cycle. These molecules may be of use in developing novel drugs against candidiasis.
Multi-Class Breast Cancer Classification using Deep Learning Convolutional Neural Network

Breast cancer continues to be among the leading causes of death for women and much effort has been expended in the form of screening programs for prevention. Given the exponential growth in the number of mammograms collected by these programs, computer-assisted diagnosis has become a necessity. Computer-assisted detection techniques developed to date to improve diagnosis without multiple systematic readings have not resulted in a significant improvement in performance measures. In this context, the use of automatic image processing techniques resulting from deep learning represents a promising avenue for assisting in the diagnosis of breast cancer. In this paper, we present a deep learning approach based on a Convolutional Neural Network (CNN) model for multi-class breast cancer classification. The proposed approach aims to classify the breast tumors in non-just benign or malignant but we predict the subclass of the tumors like Fibroadenoma, Lobular carcinoma, etc. Experimental results on histopathological images using the BreakHis dataset show that the DenseNet CNN model achieved high processing performances with 95.4% of accuracy in the multi-class breast cancer classification task when compared with state-of-the-art models.