Miracle-dz/UniFAR-FTUs huggingface dataset:
Network Connections and Salivary Testosterone Among Older U.S. Women: Social Modulation or Hormonal Causation?

Objectives This study examined potentially bidirectional connections of older U.S. women's salivary testosterone with their social network connections. Methods Data were from the 2005-2006 and 2010-2011 waves of the National Social Life, Health and Aging Project (NSHAP), a national probability sample of older U.S. adults. Autoregressive cross-lagged panel models tested linkages of women's testosterone with their social networks. Results Consistent with recent biological theory suggesting social modulation of hormones, a higher kin proportion in one's egocentric (person-centered) network, arguably a stable compositional feature, negatively predicted women's testosterone levels. In contrast, findings for tie strength were consistent with hormonal regulation of women's sociality-with both perceived support from friends and family, and closeness to network members, negatively influenced by testosterone. Discussion Rather than being a static and exogenous biological factor, older women's testosterone levels seem partly an outcome of their social context. Implications for sexual health and hormone therapy are discussed. However, this androgen also influences dimensions of their intimate networks critical to successful aging. Findings suggest the need for social scientists to engage with the neuroendocrine literature, which offers suggestions on linkages of hormones with specific network patterns.
Nanomaterial-Based Sensing and Biosensing of Phenolic Compounds and Related Antioxidant Capacity in Food

Polyphenolic compounds (PCs) have received exceptional attention at the end of the past millennium and as much at the beginning of the new one. Undoubtedly, these compounds in foodstuffs provide added value for their well-known health benefits, for their technological role and also marketing. Many efforts have been made to provide simple, effective and user friendly analytical methods for the determination and antioxidant capacity (AOC) evaluation of food polyphenols. In a parallel track, over the last twenty years, nanomaterials (NMs) have made their entry in the analytical chemistry domain; NMs have, in fact, opened new paths for the development of analytical methods with the common aim to improve analytical performance and sustainability, becoming new tools in quality assurance of food and beverages. The aim of this review is to provide information on the most recent developments of new NMs-based tools and strategies for total polyphenols (TP) determination and AOC evaluation in food. In this review optical, electrochemical and bioelectrochemical approaches have been reviewed. The use of nanoparticles, quantum dots, carbon nanomaterials and hybrid materials for the detection of polyphenols is the main subject of the works reported. However, particular attention has been paid to the success of the application in real samples, in addition to the NMs. In particular, the discussion has been focused on methods/devices presenting, in the opinion of the authors, clear advancement in the fields, in terms of simplicity, rapidity and usability. This review aims to demonstrate how the NM-based approaches represent valid alternatives to classical methods for polyphenols analysis, and are mature to be integrated for the rapid quality assessment of food quality in lab or directly in the field.
Subjective perceptions of unmet need for health care in Europe among social groups: Findings from the European social survey (2014) special module on the social determinants of health

Background: Unmet need can be defined as the individually perceived subjective differences between services judged necessary to deal with health problems and the services actually received. This study examines what factors are associated with unmet need, as well as how reasons for unmet need are distributed across socioeconomic and demographic groups in Europe. Methods: Multilevel logistic regression models were employed using data from the 7th round of the European Social Survey, on people aged 25–75. Self‐reported unmet need measured whether respondents had been unable to get medical consultation or treatment in the last 12 months. Reasons for unmet need were grouped into three categories: availability, accessibility and acceptability. Health status was measured by self‐reported health, non‐communicable diseases and depressive symptoms. Results: Two‐thirds of all unmet need were due waiting lists and appointment availability. Females and young age groups reported more unmet need. We found no educational inequalities, while financial strain was found to be an important factor for all types of unmet need for health care in Europe. All types of health care use and poor health were associated with unmet need. Low physician density and high out‐of‐pocket payments were found to be associated with unmet need due to availability. Conclusion: Even though health care coverage is universal in many European welfare states, financial strain appeared as a major determinant for European citizens' access to health care. This may suggest that higher income groups are able to bypass waiting lists. European welfare states should, therefore, intensify their efforts in reducing barriers for receiving care.
Receiving Post-Conflict Affiliation from the Enemy's Friend Reconciles Former Opponents

The adaptive function of bystander initiated post-conflict affiliation (also: consolation & appeasement) has been debated for 30 years. Three influential hypotheses compete for the most likely explanation but have not previously been tested with a single data set. The consolation hypothesis argues that bystander affiliation calms the victim and reduces their stress levels. The self-protection hypothesis proposes that a bystander offers affiliation to either opponent to protect himself from redirected aggression by this individual. The relationship-repair hypothesis suggests a bystander can substitute for a friend to reconcile the friend with the friend's former opponent. Here, we contrast all three hypotheses and tested their predictions with data on wild chimpanzees (Pan troglodytes verus) of the Taï National Park, Côte d'Ivoire. We examined the first and second post-conflict interactions with respect to both the dyadic and triadic relationships between the bystander and the two opponents. Results showed that female bystanders offered affiliation to their aggressor friends and the victims of their friends, while male bystanders offered affiliation to their victim friends and the aggressors of their friends. For both sexes, bystander affiliation resulted in a subsequent interaction pattern that is expected for direct reconciliation. Bystander affiliation offered to the opponent's friend was more likely to lead to affiliation among opponents in their subsequent interaction. Also, tolerance levels among former opponents were reset to normal levels. In conclusion, this study provides strong evidence for the relationship-repair hypothesis, moderate evidence for the consolation hypothesis and no evidence for the self-protection hypothesis. Furthermore, that bystanders can repair a relationship on behalf of their friend indicates that recipient chimpanzees are aware of the relationships between others, even when they are not kin. This presents a mechanism through which chimpanzees may gain benefits from social knowledge.
Exploration in structured space of robot movements for autonomous augmentation of action knowledge

Imitation learning has been proposed as the basis for fast and efficient acquisition of new sensorimotor behaviors. Movement representations such as dynamic movement primitives were designed to enable the reproduction of the demonstrated behaviors and their modulation with respect to unexpected external perturbations. Various statistical methods were developed to generalize the acquired sensorimotor knowledge to new configurations of the robot's workspace. However, statistical methods can only be successful if enough training data are available. If this is not the case, usually the teacher must provide additional demonstrations to augment the database, thereby improving the performance of generalization. In this paper we propose an approach that enables robots to expand their knowledge database autonomously. Efficient exploration becomes possible by exploiting the structure of the search space defined by the previously acquired example movements. We show in real-world experiments that this way the robot can expand its database and improve the performance of generalization without the help of the teacher.
Multi-Pixel Simultaneous Classification of PolSAR Image Using Convolutional Neural Networks

Convolutional neural networks (CNN) have achieved great success in the optical image processing field. Because of the excellent performance of CNN, more and more methods based on CNN are applied to polarimetric synthetic aperture radar (PolSAR) image classification. Most CNN-based PolSAR image classification methods can only classify one pixel each time. Because all the pixels of a PolSAR image are classified independently, the inherent interrelation of different land covers is ignored. We use a fixed-feature-size CNN (FFS-CNN) to classify all pixels in a patch simultaneously. The proposed method has several advantages. First, FFS-CNN can classify all the pixels in a small patch simultaneously. When classifying a whole PolSAR image, it is faster than common CNNs. Second, FFS-CNN is trained to learn the interrelation of different land covers in a patch, so it can use the interrelation of land covers to improve the classification results. The experiments of FFS-CNN are evaluated on a Chinese Gaofen-3 PolSAR image and other two real PolSAR images. Experiment results show that FFS-CNN is comparable with the state-of-the-art PolSAR image classification methods.
Bridgehead Effect in the Worldwide Invasion of the Biocontrol Harlequin Ladybird

Recent studies of the routes of worldwide introductions of alien organisms suggest that many widespread invasions could have stemmed not from the native range, but from a particularly successful invasive population, which serves as the source of colonists for remote new territories. We call here this phenomenon the invasive bridgehead effect. Evaluating the likelihood of such a scenario is heuristically challenging. We solved this problem by using approximate Bayesian computation methods to quantitatively compare complex invasion scenarios based on the analysis of population genetics (microsatellite variation) and historical (first observation dates) data. We applied this approach to the Harlequin ladybird Harmonia axyridis (HA), a coccinellid native to Asia that was repeatedly introduced as a biocontrol agent without becoming established for decades. We show that the recent burst of worldwide invasions of HA followed a bridgehead scenario, in which an invasive population in eastern North America acted as the source of the colonists that invaded the European, South American and African continents, with some admixture with a biocontrol strain in Europe. This demonstration of a mechanism of invasion via a bridgehead has important implications both for invasion theory (i.e., a single evolutionary shift in the bridgehead population versus multiple changes in case of introduced populations becoming invasive independently) and for ongoing efforts to manage invasions by alien organisms (i.e., heightened vigilance against invasive bridgeheads).
Effect of Eicosapentaenoic Acid and Docosahexaenoic Acid on Myogenesis and Mitochondrial Biosynthesis during Murine Skeletal Muscle Cell Differentiation

Polyunsaturated fatty acids are important nutrients for human health, especially omega-3 fatty acids such as eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), which have been found to play positive roles in the prevention of various diseases. However, previous studies have reported that excessive omega-3 fatty acids supplement during pregnancy caused side effects such as slower neural transmission times and postnatal growth restriction. In this study, we investigated the effect of EPA and DHA on mitochondrial function and gene expression in C2C12 myoblasts during skeletal muscle differentiation. C2C12 myoblasts were cultured to confluency and then treated with differentiation medium that contained fatty acids (50-µM EPA and DHA). After 72 h of myogenic differentiation, mRNA was collected, and gene expression was analyzed by real-time PCR. Microscopy was used to examine cell morphology following treatment with fatty acids. The effect of EPA and DHA on cellular oxygen consumption was measured using a Seahorse XF24 Analyzer. Cells treated with fatty acids had fewer myotubes formed (P ≤ 0.05) compared with control cells. The expression of the genes related to myogenesis was significantly lower (P ≤ 0.05) in cells treated with fatty acids, compared with control cells. Genes associated with adipogenesis had higher (P ≤ 0.05) expression after treatment with fatty acids. Also, the mitochondrial biogenesis decreased with lower (P ≤ 0.05) gene expression and lower (P ≤ 0.05) mtDNA/nDNA ratio in cells treated with fatty acids compared with control cells. However, the expression of genes related to peroxisome biosynthesis was higher (P ≤ 0.05) in cells treated with fatty acids. Moreover, fatty-acid treatment reduced (P ≤ 0.05) oxygen consumption rate under oligomycin-inhibited (reflecting proton leak) and uncoupled conditions. Our data imply that fatty acids might reduce myogenesis and increase adipogenesis in myotube formation. Fatty acids may also decrease cell metabolism by reducing mitochondrial biogenesis as well as respiration rate. This study suggests that the maternal overdosage of EPA and DHA may influence fetal muscle development, increase intramuscular adipose tissue deposition in offspring, and have a long-term effect on the development of metabolic diseases such as obesity and diabetes in adult offspring.
A theoretical approach for a weighted assessment of the mutagenic potential of nanomaterials

Abstract Several approaches have recently been proposed for predicting the potential hazard and risk to human health of engineered nanomaterials (NMs). Here, we present a theoretical approach to assess the mutagenic potential of NMs, which could be incorporated into risk assessment tools. Following the weight of evidence approach recommended for chemicals, we describe criteria for evaluating and weighting existing literature information, based on current knowledge on the relevance and limitations of genotoxicity and mutagenicity assays used in testing NMs. The relevant assays are then categorized according to the genotoxic events detected in three categories: DNA damage, gene mutations and chromosomal damage – the former weighing lower than the two latter ones, since unrepairable alterations have more weight than those depicting primary DNA damage that can still be repaired. Besides, evidence from in vivo tests are given a higher weight than data coming from in vitro tests, because animal studies can more accurately predict secondary genotoxicity. Although studies conducted according to validated protocols have greater weight, studies that do not comply with conventional test guidelines are also considered, trying to make use of all available information for each NM. A threshold of agreement among studies belonging to the same category is required to consider this category positive or negative for mutagenicity. The final outcome is a statement on the mutagenic potential of the nanoform and the uncertainty of this evaluation. Finally, we discuss new methods and possible improvements in current assays that could be incorporated in future guidelines.
He Says Potato, She Says Potahto: Young Infants Track Talker-Specific Accents

ABSTRACT One of the most fundamental aspects of learning a language is determining the mappings between words and referents. An often-overlooked complication is that infants interact with multiple individuals who may not produce words in the same way. In the present study, we explored whether 10- to 12-month-olds can use talker-specific knowledge to infer the intended referents of novel labels. During exposure, infants heard two talkers whose front vowels differed; one talker trained them on a word-referent mapping. At test, infants saw the trained object and a novel object; they heard a single novel label from both talkers. When the label had a front vowel (Experiment 1), infants responded differently as a function of talker, but when it had a back vowel (Experiment 2), they did not, mapping the novel label to the novel object for both talkers. These results suggest that infants can track the phonetic properties of two simultaneously presented talkers and use information about each talker’s previous productions to guide their referential interpretations.
1 CRYPTOGRAPHIC HASH FUNCTIONS

Hash functions were introduced in cryptology in the late seventies as a tool to protect the authenticity of information. Soon it became clear that they were a very useful building block to solve other security problems in telecommunication and computer networks. This paper sketches the history of the concept, discusses the applications of hash functions, and presents the approaches which have been followed to construct hash functions. In addition, it tries to provide the information which is necessary to choose a practical hash function. An overview of practical constructions and their performance is given and some attacks are discussed. Special attention is paid to standards dealing with hash functions.
Attitudes of Crohn’s Disease Patients: Infodemiology Case Study and Sentiment Analysis of Facebook and Twitter Posts

Background Data concerning patients originates from a variety of sources on social media. Objective The aim of this study was to show how methodologies borrowed from different areas including computer science, econometrics, statistics, data mining, and sociology may be used to analyze Facebook data to investigate the patients’ perspectives on a given medical prescription. Methods To shed light on patients’ behavior and concerns, we focused on Crohn’s disease, a chronic inflammatory bowel disease, and the specific therapy with the biological drug Infliximab. To gain information from the basin of big data, we analyzed Facebook posts in the time frame from October 2011 to August 2015. We selected posts from patients affected by Crohn’s disease who were experiencing or had previously been treated with the monoclonal antibody drug Infliximab. The selected posts underwent further characterization and sentiment analysis. Finally, an ethnographic review was carried out by experts from different scientific research fields (eg, computer science vs gastroenterology) and by a software system running a sentiment analysis tool. The patient feeling toward the Infliximab treatment was classified as positive, neutral, or negative, and the results from computer science, gastroenterologist, and software tool were compared using the square weighted Cohen’s kappa coefficient method. Results The first automatic selection process returned 56,000 Facebook posts, 261 of which exhibited a patient opinion concerning Infliximab. The ethnographic analysis of these 261 selected posts gave similar results, with an interrater agreement between the computer science and gastroenterology experts amounting to 87.3% (228/261), a substantial agreement according to the square weighted Cohen’s kappa coefficient method (w2K=0.6470). A positive, neutral, and negative feeling was attributed to 36%, 27%, and 37% of posts by the computer science expert and 38%, 30%, and 32% by the gastroenterologist, respectively. Only a slight agreement was found between the experts’ opinion and the software tool. Conclusions We show how data posted on Facebook by Crohn’s disease patients are a useful dataset to understand the patient’s perspective on the specific treatment with Infliximab. The genuine, nonmedically influenced patients’ opinion obtained from Facebook pages can be easily reviewed by experts from different research backgrounds, with a substantial agreement on the classification of patients’ sentiment. The described method allows a fast collection of big amounts of data, which can be easily analyzed to gain insight into the patients’ perspective on a specific medical therapy.
Implementation and Evaluation of Zero-Knowledge Proofs of Knowledge Boran Car

Zero-Knowledge Proofs of Knowledge are protocols that allow one to prove possession or knowing of a secret without actually revealing it. Goals of current ZeroKnowledge Proofs of Knowledge compiler frameworks are to make the implementation of these protocols easy for those outside the field of cryptography while at the same time making it easy for those inside the field to prototype such protocols. We acknowledge that such frameworks have made it easy to develop the protocols but we note that they have not made it easy or general to those implementing the protocols on the end devices. Such frameworks either target C/C++ code generation or an interpreted language. They also use high-level multi-precision arithmetic libraries which are too resource demanding for small embedded devices. These limitations as well as hidden pitfalls of C/C++ have motivated us to extend one of those frameworks and build our own framework from it. This framework is targeted specifically at HW-SW co-design exploration while not losing any generality of the framework it extends. We hope that this will ease the work for those outside the field and allow for a more widespread usage of these protocols.
Chaotic Adaptive Synchronization Control and Application in Chaotic Secure Communication for Industrial Internet of Things

In this paper, a Lyapunov stability theorem is used to design a model system with adaptive control synchronization. The system uses the pseudo-randomness of chaotic signals to hide the signals that need to be transmitted in seemingly messy chaotic signals. The small input signals are superimposed on the chaotic signals, and the receiving end demodulates the useful information with a synchronized chaotic signal. The system can dynamically adjust the value of the controller according to the initial value of the neuron model so that the two coupling Hindmarsh–Rose neural system can be in a better synchronous state, with good stability and self-adaptability. In this paper, the controller is applied to chaotic secure communication. The simulation results verify the feasibility and effectiveness of the designed controller, and the capability of realizing the transmission of confidential information.