Miracle-dz/UniFAR-FTUs huggingface dataset:
Perceived benefits from non-formal digital training sessions in later life: views of older adult learners, peer tutors, and teachers

ABSTRACT Rapid development of digital technologies affects the lives of all people and often leads to people being in unequal positions regarding digital skills training opportunities. Older adults’ motivations for learning digital skills vary, but they are generally connected with expectations of upcoming benefits. This study investigates the self-perceived benefits of older adults, information and communications technology (ICT) teachers and peer tutors who have participated in digital training sessions in older-adult organisations or adult education centres. The data included 226 respondents (136 women, 90 men; older adults 53–90 years old, mean age 71 years, SD 6.74; ICT teachers 30–68 years old) from Finland. According to the results, participation in digital training events supported development of digital literacy and wellbeing of the participants. Most older adult peer tutors described an increase in their wellbeing. The findings of the study indicate that participation in digital training sessions in later life is beneficial, as it supports the growth of independence and positive interdependence in new types of learning communities that strengthen older adults’ learning and wellbeing.
What determines political trust during the COVID-19 crisis? The role of sociotropic and egotropic crisis impact

ABSTRACT The pandemic caused by the novel coronavirus has led to changes in all areas of public and private life. This study explores if it has also affected trust in political institutions. As early research suggests that trust is associated with governments’ responses to the pandemic, citizens’ health behaviours, public compliance with regulations, and overall levels of COVID-19 mortality, it is important to understand what drives citizens’ trust during the crisis. Using high-quality data from the German GESIS Covid-19 Special Survey, we analyse predictors of institutional trust at the onset of the pandemic in March 2020. We pay specific attention to the effect of sociotropic and egotropic impact of the crisis. We find that on the societal level, the intensity of the health threat, but not policy responses, are linked to trust, while on the individual level, employment in a “critical occupation” and individual family situations matter. We argue that in the ongoing management of the crisis, consequences for specific groups of citizens, such as families, need to be considered.
A New Notion of Individually Fair Clustering: α-Equitable k-Center

Clustering is a fundamental problem in unsupervised machine learning, and fair variants of it have recently received significant attention due to its societal implications. In this work we introduce a novel definition of individual fairness for clustering problems. Specifically, in our model, each point $j$ has a set of other points $\mathcal{S}_j$ that it perceives as similar to itself, and it feels that it is fairly treated if the quality of service it receives in the solution is $\alpha$-close (in a multiplicative sense, for a given $\alpha \geq 1$) to that of the points in $\mathcal{S}_j$. We begin our study by answering questions regarding the structure of the problem, namely for what values of $\alpha$ the problem is well-defined, and what the behavior of the \emph{Price of Fairness (PoF)} for it is. For the well-defined region of $\alpha$, we provide efficient and easily-implementable approximation algorithms for the $k$-center objective, which in certain cases enjoy bounded-PoF guarantees. We finally complement our analysis by an extensive suite of experiments that validates the effectiveness of our theoretical results.
Effects of High Soil Water Content and Temperature on Soil Respiration

The aim of this study was to quantify the effects of high soil water content and soil temperature on soil respiration. With an automatic system, soil respiration, soil water content, and soil temperature at 5-cm depth were measured at 10-min intervals for 22 days. The measurements were carried out at three locations with high soil water content and soil temperature. Results showed that soil respiration and soil water content were negatively correlated (P < 0.01); rainfall did not stimulate any obvious pulse of soil respiration. There was an obvious hysteresis effect between soil respiration and soil temperature. Without considering the hysteresis effect, the temperature dependence parameter (q10) of soil respiration on soil temperature was underestimated. With the consideration of the hysteresis effect between soil temperature and soil respiration, the estimated q10 values were in the range of 1.2 to 2.1, and the estimated basal respiration values were in the range of 0.5 to 2.5 &mgr;mol m−2 sec−1 for the three measurement points. Based on more than 2,200 data points, reasonable relationships in the diurnal scale were established between soil respiration and soil water content, as well as soil temperature. The relationships should be useful to estimate soil respiration based on soil temperature and moisture data.
Genetic differentiation and restricted gene flow in rice landraces from Yunnan, China: effects of isolation-by-distance and isolation-by-environment

Background Understanding and identifying the factors responsible for genetic differentiation is of fundamental importance for efficient utilization and conservation of traditional rice landraces. In this study, we examined the spatial genetic differentiation of 594 individuals sampled from 28 locations in Yunnan Province, China, covering a wide geographic distribution and diverse growing conditions. All 594 accessions were studied using ten unlinked target genes and 48 microsatellite loci, and the representative 108 accessions from the whole collection were sampled for resequencing. Results The genetic diversity of rice landraces was quite different geographically and exhibited a geographical decline from south to north in Yunnan, China. Population structure revealed that the rice landraces could be clearly differentiated into japonica and indica groups, respectively. In each group, the rice accessions could be further differentiated corresponded to their geographic locations, including three subgroups from northern, southern and middle locations. We found more obvious internal geographic structure in the japonica group than in the indica group. In the japonica group, we found that genetic and phenotypic differentiation were strongly related to geographical distance, suggesting a pattern of isolation by distance (IBD); this relationship remained highly significant when we controlled for environmental effects, where the likelihood of gene flow is inversely proportional to the distance between locations. Moreover, the gene flow also followed patterns of isolation by environment (IBE) whereby gene flow rates are higher in similar environments. We detected 314 and 216 regions had been differentially selected between Jap-N and Jap-S, Ind-N and Ind-S, respectively, and thus referred to as selection signatures for different geographic subgroups. We also observed a number of significant and interesting associations between loci and environmental factors, which implies adaptation to local environment. Conclusions Our findings highlight the influence of geographical isolation and environmental heterogeneity on the pattern of the gene flow, and demonstrate that both geographical isolation and environment drives adaptive divergence play dominant roles in the genetic differentiation of the rice landraces in Yunnan, China as a result of limited dispersal.
Potential Role of Natriuretic Response to Furosemide Stress Test During Acute Heart Failure

Supplemental Digital Content is available in the text. Background: Poor natriuresis has been associated with a poorer response to diuretic treatment and worse prognosis in acute heart failure. Recommendations on how and when to measure urinary sodium (UNa) are lacking. We aim to evaluate UNa quantification after a furosemide stress test (FST) capacity to predict appropriate decongestion during acute heart failure hospitalization. Methods: Patients underwent an FST on day-1 of admission, and UNa was measured 2 hours after, dividing patients into low or high UNa based on the sample median value. A semiquantitative composite congestive score (CCS; 0–9) and NT pro-BNP (N-terminal pro-B-type natriuretic peptide) quantification were assessed before the FST and at day 5 after the FST. Results: Median UNa after FST in the 65 patients included was 113 (97–122) mmol/L. At day 5, a lower proportion of patients with a low UNa reached a 30% decrease in NT-proBNP levels (21 [66%] for low UNa versus 31 [94%] for high UNa; P=0.005) and an appropriate grade of decongestion (CCS<3) (20 [62%] for low UNa versus 32 [97%] for high UNa; P<0.001). A UNa>83 mmol/L 2 hours after FST had a 96% sensitivity to predict an NT-proBNP reduction ≥30% and 95% to predict a CCS<3 at day 5. Low UNa patients presented a lower cumulative diuresis and weight loss and presented more often with prolonged hospitalization, worsening heart failure, and readmission because of acute heart failure or death at 6 months. Conclusions: Low natriuresis after an FST identified patients at a higher risk of an inadequate diuretic response and an inappropriate decongestion. FST-guided diuretic treatment might help to improve decongestion, shorten hospitalizations, and to reduce adverse outcomes.
The Hidden Heterogeneity of Inflation and Interest Rate Expectations: The Role of Preferences

Using a new consumer survey dataset, we study the role of macroeconomic preferences for expectations and economic decisions. While household expectations are inversely related to preferences, households with the same inﬂation expectations can diﬀerently assess whether the level of expected inﬂation and of nominal interest rates is appropriate or too high/too low. This ‘hidden heterogeneity’ in expectations is correlated with sociodemographic characteristics and aﬀects current and planned spending via the intertemporal elasticity of substitution. We also show that the variation in preferences can be explained with risk preferences. Overall, this adds a new dimension to the deﬁnition of anchored expectations.
Symptom and Age Homophilies in SARS-CoV-2 Transmission Networks during the First and Second Waves of the Pandemic in Japan

Background Hokkaido is the northernmost, least populous, and coldest of the Japanese islands. It was the first prefecture to be affected by COVID-19, while Kanagawa is home to one of the most populous areas of Japan, namely the Tokyo metro area. The Japanese government responded early during the pandemic by identifying infected patients, contact tracing, and performing PCR analysis on anyone who was suspected of having been exposed to SARS-CoV-2. The government has also been publishing information about each individual who tested positive for the virus. Both Hokkaido and Kanagawa started recording COVID-19 cases in the winter of 2020 and have detailed records of thousands of patients, thus providing an invaluable resource for the transmission and behavior of the virus. Methods The current study analyzed the COVID-19 registry data from the Hokkaido and Kanagawa prefectures. The Hokkaido registry contained 1,269 cases (674 (53%) females and 595 (47%) males) recorded between February 14 and July 22, 2020. The Kanagawa registry had 3,123 cases (1,346 (43%) females and 1,777 (57%) males. The final data contained a total of 4,392 cases (2,020 (46%) females and 2,372 (54%) males). By leveraging the information on viral transmission paths available in the registry data, we performed exponential random graph model (ERGM) network analysis to examine demographic and symptomological homophilies of the SARS-CoV-2 viral transmission networks. Results We observed age, symptomatic, and asymptomatic homophilies in both prefectures. Furthermore, those patients who contracted the virus through secondary or tertiary contacts were more likely to be asymptomatic than those who contracted it from primary infection cases. The transmission networks showed that transmission occurred significantly in healthcare settings, as well as in families, although the size of the networks was small in the latter. Most of the transmissions stopped at the primary and secondary levels and no transmission beyond quaternary was observed. We also observed a higher level of asymptomatic transmission in Kanagawa than in Hokkaido. Conclusions Symptom homophilies are an important component of COVID-19 and suggest that nuanced genetic differences in the virus may affect its epithelial cell type range and can thus result in the diversity of symptoms seen in individuals infected by SARS-CoV-2. Moreover, environmental variables such as temperature and humidity may also be playing an important role in the overall pathogenesis of the virus.
Scalable Training with Information Bottleneck Objectives

The Information Bottleneck principle offers both a mechanism to explain how deep neural networks train and generalize, as well as a regularized objective with which to train models, with multiple competing objectives proposed in the literature. Moreover, the information-theoretic quantities used in these objectives are difficult to compute for large deep neural networks, often relying on density estimation using generative models. This, in turn, limits their use as a training objective. In this work, we review these quantities, compare and unify previously proposed objectives and relate them to surrogate objectives more friendly to optimization without relying on cumbersome tools such as density estimation. We find that these surrogate objectives allow us to apply the information bottleneck to modern neural network architectures with stochastic latent representations. We demonstrate our insights on MNIST and CIFAR10 with modern neural network architectures.
Death Clustering of Neonates & its Determinants in India

The increased reach of health programs in India, during the past few decades, has significantly contributed to decline in postnatal mortality including infant, child & other mortality. However, reduction in neonatal mortality remained negligible. About 70% neonatal deaths take place within a week after birth. The prime objective of this study is to explore the death clustering of the neonates and its determinants in India. 3 rd round of National Family Health Survey (NFHS-3), India, 2005-06 data was used for this study. Bivariate analysis followed by multivariate analysis (Binary logistic regression) was performed to identify the determinants of neonatal mortality. Moran’s I & Univariate LISA cluster map was used to explore the spatial clusters of neonatal deaths in India. Univariate Moran’s I (Moran’s I=0.215) was significant i.e. spatial dependence exists for neonatal deaths in Indian states. The Univariate LISA cluster map explored significant hotspots of neonatal deaths which were Bihar, Chhattisgarh, Jharkhand, MP, Odisha, Rajasthan, UP and WB. The estimated odds of neonatal death was 2.75 times higher (OR=2.75; 95% CI: 2.21-3.43) among smaller size neonates than the average & larger size neonates. The odds of neonatal death was found 2.39 times, 2.73 times & 1.84 times higher among those mothers who had an illiterate, primary & secondary level of education as compared to mothers who had higher education. The risk of neonatal death among 1 st (OR=1.43) and more than 4 th (OR=1.35) order births was positively higher than 2 nd to 3 rd order births. Based on the findings, the study proposes various approaches to address the increasing contribution of neonatal deaths in India. The findings suggest that raising mother education & providing a healthy diet to pregnant women, can bring a quick substantial reduction of neonatal mortality and the target fixed can be achieved. So, it is necessary to encourage & support women for higher education. This study proposes to provide the combination of the continuum care for maternal, neonatal, and child health by integrating a family-community based service delivery approach with the existing health care system specially to the death clusters in India. © 2017 Elixir All rights reserved. Elixir Statistics 103 (2017) 45699-45704 Statistics Available online at www.elixirpublishers. com (Elixir International Journal)
Retention of employees in pharmaceutical industries of Bangalore

Introduction Employee turnover is a much studied phenomenon. There is a vast literature on the causes of voluntary employee turnover dating back to the 1950s. By developing multivariate models that combine a number of factors contributing to turnover and empirically testing the models researchers have sought to predict why individuals leave organization. Many studies are based on only a small number of variables which often only explain a small amount of variability in turnover. Another criticism of turnover studies is that they do not adequately capture the complex psychological processes involved in individual turnover decisions. A recent study of turnover by Boxall et al (2003) in New Zealand confirmed the view that motivation for job change is multidimensional and that no one factor will explain it. However, over time there have been a number of factors that appear to be consistently linked to turnover. An early review article of studies on turnover by Mobley et al (1979) revealed that age, tenure, overall satisfaction, job content, intentions to remain on the job, and commitment were all negatively related
Volatile Constituents of Aerial Parts of Capsella rubella Reut.

: Three different isolates from unexplored wild-growing Brassicaceae plant Capsella rubella were investigated in order to provide more complete insight of the composition and content of volatile constituents. The analy sis of volatile compounds was performed by GC-FID/MS. C. rubella essential oil, that is isolate obtained by hydrodistillation, was characterized by a high percentage of 3,4 - epithiobutanenitrile (67.8 %). The main volatile compounds in autolysate, i.e. isol ate obtained by solvent extraction upon endogenous enzymatic hydrolysis, were 3,4 - epithiobutanenitrile (44.1 %) and ethyl isothiocyanate (29.4 %). Same as in autolysate, the main volatile constituents of hyd rolysate, i.e. isolate obtained by solvent extrac tion upon exogenous enzymatic hydrolysis, were 3,4 -epithiobutanenitrile and ethyl isothiocyanate, but with ethyl isothiocyanate as the dominating compound (57.8 %) followed by 3,4 - epithiobutanenitrile (15.6 %). The results showed that qualitative and quant itative composition of C. rubella volatile constituents depends on the isolation method. But, regardless of the isolation method sulfur - and nitrogen-containing volatile compounds were quantitatively dominating constituents in all isolates
The secret life of predictive brains: what’s spontaneous activity for?

Brains at rest generate dynamical activity that is highly structured in space and time. We suggest that spontaneous activity, as in rest or dreaming, underlies top-down dynamics of generative models. During active tasks, generative models provide top-down predictive signals for perception, cognition, and action. When the brain is at rest and stimuli are weak or absent, top-down dynamics optimize the generative models for future interactions by maximizing the entropy of explanations and minimizing model complexity. Spontaneous fluctuations of correlated activity within and across brain regions may reflect transitions between 'generic priors' of the generative model: low dimensional latent variables and connectivity patterns of the most common perceptual, motor, cognitive, and interoceptive states. Even at rest, brains are proactive and predictive.
CLASSIFICATION OF TURKISH TWEETS BY DOCUMENT VECTORS AND INVESTIGATION OF THE EFFECTS OF PARAMETER CHANGES ON CLASSIFICATION SUCCESS

Natural language processing is an artificial intelligence field which is gaining in popularity in recent years. To make an emotional deduction from texts related to an issue, or classify documents are of great importance considering the increasing data size in today's world. Understanding and interpreting written texts is a feature that pertains to people. But, it is possible to deduce from texts or classify texts using natural language processing which is a sub-branch of machine learning and artificial intelligence. In this study, both text classification was made on Turkish tweets, and text classification success of method parameter changes was investigated using two different methods of the algorithm mentioned as document vectors in the literature. It was found in the study that as well as higher accuracy values were obtained by the DBoW (Distributed Bag of Words) method than DM (Distributed Memory) method; higher accuracy values were also obtained by DBoW-NS (Negative Sampling) architecture than others.
Modelling andFiltering forNon-MarkovianQuantum Systems ?

This paper presents an augmented Markovian system model for non-Markovian quantum systems. In this augmented system model, ancillary systems are introduced to play the role of internal modes of the non-Markovian environment converting white noise to colored noise. Consequently, non-Markovian dynamics are represented as resulting from direct interaction of the principal system with the ancillary system. To demonstrate the utility of the proposed augmented system model, it is applied to design whitening quantum filters for non-Markovian quantum systems. Examples are presented to illustrate how whitening quantum filters can be utilized for estimating non-Markovian linear quantum systems and qubit systems. In particular, we showed that the augmented Markovian formulation can be used to theoretically model the environment for an observed nonMarkovian behavior in a recent experiment on quantum dots [10].
Use of the Barthel Index to Assess Activities of Daily Living before and after SARS-COVID 19 Infection of Institutionalized Nursing Home Patients

The objective of the present study was to evaluate the activities of daily living (ADLs) using the Barthel Index before and after infection with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and also to determine whether or not the results varied according to gender. The ADLs of 68 cohabiting geriatric patients, 34 men and 34 women, in two nursing homes were measured before and after SARS-CoV-2 (Coronavirus 2019 (COVID-19)) infection. COVID-19 infection was found to affect the performance of ADLs in institutionalized elderly in nursing homes, especially in the more elderly subjects, regardless of sex. The COVID-19 pandemic, in addition to having claimed many victims, especially in the elderly population, has led to a reduction in the abilities of these people to perform their ADLs and caused considerable worsening of their quality of life even after recovering from the disease.