Miracle-dz/UniFAR-FTUs huggingface dataset:
Social connectedness as resource of resilience: Italian validation of the Social Connectedness Scale – Revised

Summary Objectves Considering social variables influencing psychological well-being and protecting from development of mental disease, social support received great attention. In recent years the focus shifted toward more general constructs that can account for stability and coherence of the scheme that each person applies to relate to the social word as a whole. The construct of social connectedness seems to be closest to this aim. In this study, we present the validation of the Social Connectedness Scale - Revised (SCS-R) developed by Lee et al. on a sample of Italian general population. Methods We collected data from 197 subjects heterogeneous for gender and age. We then investigated the validity of the scale through an exploratory factor analysis and its reliability by calculating Cronbach’s Alpha. Differences in the mean scores of SCS-R due to gender, age and education were investigated. To test the criterion validity of the scale, we analyzed the correlations between the SCS-R and a multidimensional measure of resiliency and with some symptoms of psychological suffering. Finally, we analyzed the relations between SCS-R and a self-rated measure of perceived physical health. Results The analyses confirmed the uni-dimensional factor structure of the scale and the good reliability of SCS-R on this sample of Italian population. No differences due to demographics emerged. The correlations between SCS-R and the six resiliency dimensions measured by the Resiliency Scale for Adults (RSA) were all positive and statistically significant (but with Structured Style), and the highest correlations emerged with the social and individual competence resiliency dimensions. In contrast, the correlations between SCS-R and the psychopathology dimensions were all negative and significant, and the highest correlation was with depression, confirming previous results. It is interesting to underline the positive correlation between SCS-R and participants’ satisfaction with their physical health. Discussion The SCS-R confirmed good psychometrics in an Italian sample. Validity and reliability indexes were good. Investigating the criterion validity, we found evidence that confirms previous results about the protective role of social connectedness on psychopathology, and the negative correlations with depression, hostility and anxiety corroborated previous results. It should be underlined that the SCS-R correlated with a multidimensional measure of resiliency, and particularly with the resiliency dimensions that address personal and social competence dimensions in coping with negative events. Further studies are needed to clarify the relations of causality among these constructs.
The effect of size on the strength of FCC metals at elevated temperatures: annealed copper

Abstract As the length scale of sample dimensions is reduced to the micron and sub-micron scales, the strength of various materials has been observed to increase with decreasing size, a fact commonly referred to as the ‘sample size effect’. In this work, the influence of temperature on the sample size effect in copper is investigated using in situ microcompression testing at 25, 200 and 400 °C in the SEM on vacuum-annealed copper structures, and the resulting deformed structures were analysed using X-ray μLaue diffraction and scanning electron microscopy. For pillars with sizes between 0.4 and 4 μm, the size effect was measured to be constant with temperature, within the measurement precision, up to half of the melting point of copper. It is expected that the size effect will remain constant with temperature until diffusion-controlled dislocation motion becomes significant at higher temperatures and/or lower strain rates. Furthermore, the annealing treatment of the copper micropillars produced structures which yielded at stresses three times greater than their un-annealed, FIB-machined counterparts.
Greedy Layer-Wise Training of Deep Networks

Complexity theory of circuits strongly suggests that deep architectures can be much more efficient (sometimes exponentially) than shallow architectures, in terms of computational elements required to represent some functions. Deep multi-layer neural networks have many levels of non-linearities allowing them to compactly represent highly non-linear and highly-varying functions. However, until recently it was not clear how to train such deep networks, since gradient-based optimization starting from random initialization appears to often get stuck in poor solutions. Hinton et al. recently introduced a greedy layer-wise unsupervised learning algorithm for Deep Belief Networks (DBN), a generative model with many layers of hidden causal variables. In the context of the above optimization problem, we study this algorithm empirically and explore variants to better understand its success and extend it to cases where the inputs are continuous or where the structure of the input distribution is not revealing enough about the variable to be predicted in a supervised task. Our experiments also confirm the hypothesis that the greedy layer-wise unsupervised training strategy mostly helps the optimization, by initializing weights in a region near a good local minimum, giving rise to internal distributed representations that are high-level abstractions of the input, bringing better generalization.
Practice of Epidemiology Chicago Healthy Aging Study: Objectives and Design

Investigators in the Chicago Healthy Aging Study (CHAS) reexamined 1,395 surviving participants aged 65 – 84 years (28% women) from the Chicago Heart Association Detection Project in Industry (CHA) 1967 – 1973 cohort whose cardiovascular disease (CVD) risk profiles were originally ascertained at ages 25 – 44 years. CHAS investigators reexamined 421 participants who were low-risk (LR) at baseline and 974 participants who were non-LR at baseline. LR was defined as having favorable levels of 4 major CVD risk factors: serum total cholesterol level <200 mg/dL and no use of cholesterol-lowering medication; blood pressure <120/ ≤ 80 mm Hg and no use of antihypertensive medication; no current smoking; and no history of diabetes or heart attack. While the potential of LR status in overcoming the CVD epidemic is being recognized, the long-term association of LR with objectively measured health in older age has not been examined. It is hypothesized that persons who were LR in 1967 – 1973 and have survived to older age will have less clinical and subclinical CVD, lower levels of inflammatory markers, and better physical performance/functioning and sleep quality. Here we describe the rationale, objectives, design, and implementation of this longitudinal epidemiologic study, compare baseline and follow-up characteristics of participants and nonparticipants, and highlight the feasibility of reexamining study participants after an extended period postbaseline with minimal interim contact.
Upregulation of Mir-21 Levels in the Vitreous Humor Is Associated with Development of Proliferative Vitreoretinal Disease

MicroRNAs (miRNAs) are small noncoding RNAs that regulate gene expression by post-transcriptional inhibition of mRNA translation. Dysregulation of miRNAs, including circulating miRNAs, has been reported to play an important role in the development of various diseases, including fibrotic diseases. Aberrant expression of miRNAs in the vitreous humor of vitreoretinal diseased eyes has been reported. However, the expression pattern of miRNAs present in the vitreous humor of proliferative vitreoretinal disease (PVD) patients, including proliferative diabetic retinopathy (PDR), and proliferative vitreoretinopathy (PVR), remains unknown. To investigate the factors important for the development of PVD, we characterized the miRNAs present in the vitreous humor of PVD patients and analyzed the expression profiles of 377 miRNAs using quantitative polymerase chain reaction-based miRNA arrays. The expression of a specific subset of miRNAs, previously reported to be associated with the development of angiogenesis and fibrosis, was significantly altered in the vitreous of PVD patients. Among these miRNAs, we identified miR-21 as a candidate fibrotic miRNA with an important role in the pathogenesis of PVD. Increased miR-21 levels in the vitreous were associated with retinal fibrosis, including PVR and PDR. Because epithelial-mesenchymal transition (EMT) of retinal pigment epithelial cells (RPECs) plays a critical role in retinal fibrosis, the expression of miR-21 in human RPECs was determined. Its expression in RPECs was induced by transforming growth factor-β, a key growth factor involved in fibrogenesis, and was enhanced by high glucose culture conditions, suggesting that miR-21 expression positively correlates with disease progression. Gain- and loss-of-function studies revealed that miR-21 promoted cell proliferation and migration of ARPE-19 cells without affecting EMT-related gene expression. Together, our studies have identified miR-21 as a potential disease-modifying miRNA in the vitreous humor that is involved in the development of retinal fibrosis and may be a novel marker of PVD.
Towards a global journalism ethics model: an Islamic perspective†

ABSTRACT There seems to be an internationally shared consensus that search for a universal journalism ethic has often ended with the attempt to import traditional and underlying Western free-press values, such as objectivity and an adversarial platform forged in Enlightenment philosophy. There is also a universally shared consensus on the dilemma of how to invent a universal journalism ethical framework that sustains the universal solidarity of human being and recognises cultural, religious and ideological differences. The central argument of this article is that the Islamic worldview offers a modern journalism ethical model that both protects and limits universal pluralism in a multi-cultural society. It favours pluralism to the extent that it does not threaten unity of the universe or create the state of anarchy. It, therefore, establishes universal values that human beings share without transcending local cultures. The suggested model is based on four guiding principles: respecting pluralism and cultural diversity, freedom of expression, justice and moderation.
We Know Where You Are: Home Location Identification in Location-Based Social Networks

The rapid spread of smartphones has led to the increasing popularity of Location-Based Social Networks(LBSNs) like Foursquare, Gowalla, Facebook Places and so on where users can publish information about their current location. In LBSNs, identifying home locations of users is very important for various applications like effective location-based advertisement and recommendation. However, this problem is rather challenging because the location information in LBSNs is sparse and noisy: Only a small percentage of users share their home location information due to privacy concerns; users may check in at diverse places far from their home and make friends far away; many users even do not have any check-in information. In this paper, we propose a trust-based influence model, named as TSU to solve the problem. To be specific, TSU is a Trust-based unified probabilistic model that models edges in LBSNs based on signals from Social relationship data(social friendship, social trust) and User-centric data(check-in data) in LBSN. We proposed a Home Location Identification method based on TSU model and evaluate it on a large real-world LBSNs dataset. Extensive experiments demonstrate that our method significantly outperforms state-of-the-art methods.
The largest eigenvalues of finite rank deformation of large Wigner matrices: Convergence and nonuniversality of the fluctuations.

We investigate the asymptotic spectrum of complex or real Deformed Wigner matrices when the entries of the Hermitian (resp., symmetric) Wigner matrix have a symmetric law satisfying a Poincare inequality. The perturbation is Hermitian (resp., symmetric) and deterministic with all but finitely many eigenvalues equal to zero. We first show that, as soon as the first largest or last smallest eigenvalues of the perturbation are sufficiently far from zero, the corresponding eigenvalues of the deformed Wigner matrix almost surely exit the limiting semicircle compact sup- port as the size becomes large. The corresponding limits are universal in the sense that they only involve the variance of the entries of the Wigner matrix. On the other hand, when the perturbation is diagonal with a sole simple nonnull eigenvalue large enough, we prove that the fluctuations of the largest eigenvalue are not universal and vary with the particular distribution of the entries of the Wigner matrix.
Indole Alkaloids from Plants as Potential Leads for Antidepressant Drugs: A Mini Review

Depression is the most common illness observed in the elderly, adults, and children. Antidepressants prescribed are usually synthetic drugs and these can sometimes cause a wide range of unpleasant side effects. Current research is focussed on natural products from plants as they are a rich source of potent new drug leads. Besides Hypericum perforatum (St. John’s wort), the plants studied include Passiflora incarnata L. (passion flower), Mitragyna speciosa (kratom), Piper methysticum G. Forst (kava) and Valeriana officinalis L. Harman, harmol, harmine, harmalol and harmaline are indole alkaloids isolated from P. incarnata, while mitragynine is isolated from M. speciosa. The structure of isolated compounds from P. methysticum G. Forst and V. officinalis L. contains an indole moiety. The indole moiety is related to the neurotransmitter serotonin which is widely implicated for brain function and cognition as the endogenous receptor agonist. An imbalance in serotonin levels may influence mood in a way that leads to depression. The moiety is present in a number of antidepressants already on the market. Hence, the objective of this review is to discuss bioactive compounds containing the indole moiety from plants that can serve as potent antidepressants.
Rosenthal operator spaces

In 1969 Lindenstrauss and Rosenthal showed that if a Banach space is isomorphic to a complemented subspace of an Lp-space, then it is either an Lp-space or isomorphic to a Hilbert space. This is the motivation of this paper where we study non- Hilbertian complemented operator subspaces of non-commutative Lp-spaces and show that this class is much richer than in the commutative case. We investigate the local properties of some new classes of operator spaces for every 2 < p < 1 which can be considered as operator space analogues of the Rosenthal sequence spaces from Banach space theory, constructed in 1970. Under the usual conditions on the defining sequence we prove that most of these spaces are operator Lp-spaces, not completely isomorphic to previously known such spaces. However, it turns out that some column and row versions of our spaces are not operator Lp-spaces and have a rather complicated local structure which implies that the Lindenstrauss-Rosenthal alternative does not carry over to the non-commutative case.
Rotavirus vaccination and intussusception – Science, surveillance, and safety: A review of evidence and recommendations for future research priorities in low and middle income countries

ABSTRACT As of January 2016, 80 countries have introduced rotavirus vaccines into their national immunization programs. Many have documented significant declines in rotavirus-specific and all-cause diarrheal illnesses following vaccine introduction. Two globally licensed rotavirus vaccines have been associated with a low risk of intussusception in several studies. In July 2014, the Rotavirus Organization of Technical Allies Council convened a meeting of research and advocacy organizations, public health experts, funders, and vaccine manufacturers to discuss post-marketing intussusception surveillance and rotavirus vaccine impact data. Meeting objectives were to evaluate updated data, identify and prioritize research gaps, discuss best practices for intussusception monitoring in lower-income settings and risk communication, and provide insight to country-level stakeholders on best practices for intussusception monitoring and communication. Meeting participants agreed with statements from expert bodies that the benefits of vaccination with currently available rotavirus vaccines outweigh the low risk of vaccination-associated intussusception. However, further research is needed to better understand the relationship of intussusception to wild-type rotavirus and rotavirus vaccines and delineate potential etiologies and mechanisms of intussusception. Additionally, evidence from research and post-licensure evaluations should be presented with evidence of the benefits of vaccination to best inform policymakers deciding on vaccine introduction or vaccination program sustainability.
Improving Comprehension of Capital Sentencing Instructions

Previous research has demonstrated that judicial instructions on the law are not well understood by jurors tasked with applying the law to the facts of a case. The past research has also shown that jurors are often confused by the instructions used in the sentencing phase of a capital trial. The current research tested the effectiveness of a “debunking” approach to improving juror misunderstanding associated with capital sentencing instructions. Participants were randomly assigned to hear either Florida's pattern instructions used in the penalty phase of a capital trial or the same instructions with additional statements that mentioned and refuted misconceptions thought to be associated with established areas of miscomprehension. After participants heard the judicial instructions, their understanding of the law on capital punishment decision making was assessed. The results revealed that comprehension was higher for participants exposed to the bias-refutation statements than for participants who were exposed to only the pattern instructions.
Pretreatment hepatoprotective effect of regular aerobic training against hepatic toxicity induced by Doxorubicin in rats.

BACKGROUND Doxorubicin is an anthracycline antibiotic commonly used to treat a variety of cancers as a most effective antitumor. However, its clinical use is associated with the toxic effects in numerous healthy tissues. Here we investigated the pretreatment effect of regular aerobic exercise on oxidative stress in rats acutely exposed to DOX-induced hepatotoxicity. MATERIALS AND METHODS Forty-eight Wistar male rats were randomly divided into 2 groups: control and training. The training protocol included treadmill running between 25 to 54 min/day and 15 to 20 m/min, 5 days/week for 6 weeks. At the end of the exercise training protocol, rats from the control and trained groups were again randomly separated into 3 subgroups: DOX 10 mg/kg, DOX 20 mg/kg and saline. All treatments were carried 24 h after the last exercise bout and animals were sacrificed 24 h after DOX and saline injections. RESULTS Administration of DOX (10 and 20 mg.kg-1) resulted in imbalance in biomarkers related to oxidants and antioxidants in liver tissue, as compared to control groups. Six weeks of pretreatment training led to a significant increase in nitric oxide (NO), superoxide dismutase (SOD) and glutathione peroxidase (GPX) as compared to the control+DOX 10 mg/kg group. Training before DOX 20 mg/kg administration also led to a significant increase in NO and SOD, and a significant decrease in malondialdehyde (MDA). In addition, there was a significant difference between DOX 10 mg/kg and DOX 20 mg/kg treatments in MDA levels, only. CONCLUSIONS The results of the present study indicate that pretreatment with aerobic exercise induces positive adaptations and has a potential protective effect against doxorubicin (DOX)-induced hepatotoxicity with doses of 10 and 20 mg.kg.
Evaluating iterative optimization across 1000 datasets

While iterative optimization has become a popular compiler optimization approach, it is based on a premise which has never been truly evaluated: that it is possible to learn the best compiler optimizations across data sets. Up to now, most iterative optimization studies find the best optimizations through repeated runs on the same data set. Only a handful of studies have attempted to exercise iterative optimization on a few tens of data sets. In this paper, we truly put iterative compilation to the test for the first time by evaluating its effectiveness across a large number of data sets. We therefore compose KDataSets, a data set suite with 1000 data sets for 32 programs, which we release to the public. We characterize the diversity of KDataSets, and subsequently use it to evaluate iterative optimization.We demonstrate that it is possible to derive a robust iterative optimization strategy across data sets: for all 32 programs, we find that there exists at least one combination of compiler optimizations that achieves 86% or more of the best possible speedup across all data sets using Intel's ICC (83% for GNU's GCC). This optimal combination is program-specific and yields speedups up to 1.71 on ICC and 2.23 on GCC over the highest optimization level (-fast and -O3, respectively). This finding makes the task of optimizing programs across data sets much easier than previously anticipated, and it paves the way for the practical and reliable usage of iterative optimization. Finally, we derive pre-shipping and post-shipping optimization strategies for software vendors.
METHOD FOR ASR PERFORMANCE PREDICTION BASED ON TEMPORAL PROPERTIES OF SPEECH SIGNAL

Extending previous work on prediction of phoneme recognition error from unlabelled data, corrupted by unpredictable factors, the current work investigates a simple but effective method of estimating ASR performance by computing Mean Temporal Distance (MTD), which is the mean distance between speech feature vectors, determined as a function of temporal distance between the vectors. It is shown that MTD is a function of the signal-to-noise ratio of the speech signal. Comparing MTD curves, derived on data used for training of the classifier, and on test utterances, allows for predicting error on the test data. Another interesting observation from the proposed technique is that the Mean Temporal Distance remains approximately constant, as temporal separation exceeds certain critical interval (about 200 ms), corresponding to the extent of coarticulation in speech sounds. This lends further support to the notion that speech message is coded in overlapping speech sound units, lasting approximately 200 ms.
What do we know about the financial behaviour of the Spanish SME?: an empirical analysis

The main objective of this work is to analyze the capital structure of Spanish small and medium-sized enterprises from the point of view of the "pecking order theory". The Data base employed to test our hypotheses comes from the SABI (Sistema de Analisis de Balances Ibericos). The contribution of this paper are basically: i) the database used in the empirical analysis of the Spanish financial companies behaviour and ii) the panel data allow us to control the possible existence of fixed effects associated to each company as well as the endogeneity problems through the use of instrumental variables models. By means of the so-called, "pecking-order-theory" we make a test of the capital structure againsts the size, age and activities within the sector.