Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of COVID-19 restrictions on newly occurring loneliness in older people – a prospective study in a memory clinic population

The COVID-19 pandemic was associated with high burden and numerous negative consequences for older people. Social isolation and loneliness are major and prevalent health problems impacting well-being and quality of life and may have increased due to pandemic-related restrictions. The present study investigate the impact of the COVID-19 pandemic on loneliness in people visiting a memory clinic between March 2020 and September 2022. We conducted a prospective, single-center, questionnaire-based observational follow-up study to assess potential predictors of newly occurring, pandemic-related loneliness. Next to a newly developed COVID-19 questionnaire, a comprehensive neuropsychological test battery, the Neuropsychiatric Inventory and the Geriatric Depression Scale were used. In total 426 people (mean age: 76.48 years, 12.9% cognitively intact, 33.1% diagnosed with Mild Cognitive Impairment, 49.8% diagnosed with dementia, and 4.2% diagnosed with depression) completed the COVID-19 questionnaire at baseline and 166 at follow-up. Newly occurring loneliness was indicated by 22.3% of baseline participants and by 24.1% of follow-up participants. Results of logistic regression analysis showed that living alone (OR 5.452) and having less contact with friends (OR 2.771) were most predictive of the occurrence of loneliness. The use of digital communication media as an alternative strategy for social interaction was lowest in dementia patients (6–13%). In conclusion, personal contacts and a close friendship network appear to be more decisive to prevent loneliness in older people than does the use of digital communication media. However, promoting an intensi�ed use of digital communication media may be useful to counteract loneliness, especially in dementia patients.
Clustering Mutual Funds Using Unsupervised Learning With Imbalanced Classes

This study utilizes K Means clustering-an unsupervised machine learning to first classify the mutual fund into rating groups or classes and validate if the machine generated ratings match with the given ratings. This study is a way to compare between machine generated ratings vs human analyst ratings [2]and plays a vital role in finance domain where human biasedness towards an entity can cause huge loss to investors. The study is focused to know if the given mutual fund analyst ratings are correct or not, using unsupervised machine learning and measure the misclassification rate. Also, for this data on mutual funds, our data has imbalanced classes, and the K means clustering underperforms due to imbalanced data, hence we propose a new hybrid class balancing algorithm to balance the data, which uses Expectation Maximization (EM) algorithm for Under sampling and Gaussian Distribution and K means (GK-means) for oversampling the data, resulting in a balanced dataset. After balancing the data set using proposed class balancing technique, from clustering results ,we find that almost 16% of the funds are rated wrongly or do not have similarities with other funds in the same category. These 16% funds are insignificantly different from others in terms of their financial characteristics and are wrongly rated. We also compare the clustering accuracy of imbalanced classes, SCUT and EM+GK Means.
Energy-Efficient CNN inferencing on GPUs with Dynamic Frequency Scaling

To ensure that emerging technologies such as autonomous driving and application-specific Internet of Things devices work correctly, fast and accurate calculations must be performed by algorithms like Machine Learning (ML). One essential algorithm in these systems is Convolutional Neural Network (CNN), which requires a lot of computational resources. De-signers often use ML accelerators like General Purpose Graphic Processing Units (GPGPUs) to keep up with design requirements, but choosing the right accelerator and accelerator configuration can be time-consuming and difficult. Our research analyzes the power consumption and execution time of CNNs on GPGPUs with different frequency settings. We found that changing the frequency significantly impacted power consumption but only had a marginal effect on computation time. Furthermore, increasing the frequency beyond 1200 MHz shows no improvement in computation time anymore. Therefore, a lower frequency can help create an energy-efficient CNN inference system without sacrificing performance.
Laboratory geometric calibration simulation analysis of push-broom satellite imaging sensor

Linear array imaging sensors are widely used in remote sensing satellites. The final products of an imaging sensor can only be used when they are geometrically, radiometrically, and spectrally calibrated. Therefore, at the first stages of sensor design, a detailed calibration procedure must be carefully planned based on the accuracy requirements. In this paper, focusing on inherent optical distortion, a step-by-step procedure for laboratory geometric calibration of a typical push-broom satellite imaging sensor is simulated. The basis of this work is the simulation of a laboratory procedure in which a linear imager mounted on a rotary table captures images of a pin-hole pattern at different angles. By these images and their corresponding pinhole approximation, the correction function is extracted and applied to the raw images to give the corrected ones. The simulation results illustrate that using this approach, the nonlinear effects of distortion can be minimized and therefore the accuracy of the geometric position of this method on the image screen can be improved to better than the order of sub-pixel. On the other hand, the analyses can be used to proper laboratory facility selection based on the imaging sensor specifications and the accuracy.
The Enigma Of Low Production In Agricultural Sector: The Solution Through Trajectory Of Women’s Empowerment

Among many others, the enigma of low production per acre is also a persistent common phenomenon of developing economies. The present study is a guide towards solving this problem by assessing the impact of women’s empowerment on agricultural production. The convenient sample of 160 women farmers aged between 21-55 year was recruited from district Khanewal, Pakistan. The Composite Women’s Empowerment Index (CWEI: Batool & Batool, 2018) was used to measure the empowerment variable. The outcomes of the stepwise regression model showed a positive significant impact of women’s empowerment, in particular, and use of technology, agricultural information, farm ownership, paid job, and agricultural training on agricultural production, produced by sample women farmers, in general. The recommendations to the government are also discussed.
Trends in Psychiatry and Psychotherapy

Objective: To present the process of cross-cultural adaptation of the Sport Anxiety Scale-2 (SAS-2) for the Brazilian context. Method: The following stages were used: translation into Brazilian Portuguese by independent translators, elaboration of a synthesis version, back-translation, evaluation by experts and pretest with target population. Results: All the stages of cross-cultural adaptation were completed, and in the majority of items evaluated, good concordance between experts was obtained (≥ 80%). Suggested adjustments were compiled into the consensus version by the two authors, with the resulting material being considered adequate in the pretest (and thus no further changes were needed). Termed as “Escala de Ansiedade Esportiva-2,” the final version was considered by the main author of the original scale as an official version in Brazilian Portuguese. Conclusions: In view of the fulfilment of all steps suggested for the cross-cultural adaptation process, the SAS-2 is now available in Brazilian Portuguese to be tested for its psychometric qualities.
Diabetes and obesity are significant risk factors for morning hypertension : From Ibaraki Hypertension Assessment Trial ( I-HAT ) 著者

Aims: Morning hypertension (HT) has been identified as a major cardiovascular risk factor, but the population susceptible to morning HT is unknown. This study aimed to clarify the relationship between morning HT and diabetes or obesity in a large-scale population. Main methods: Clinic blood pressure (BP) and the BP upon awakening of 2554 outpatients with HT who attended 101 clinics or hospitals, were recorded for two weeks. Hypertension was defined as mean clinic BP > 140/90 mmHg or awakening BP >135/85 mmHg. The patients were assigned to 4 groups (normal BP, white coat HT, masked HT, and sustained HT) based on values of clinic and home BPs. Key findings: Morning BP (mmHg) was significantly elevated and progressed in the order of
Involuntary coping mechanisms: a psychodynamic perspective

Coping responses to stress can be divided into three broad categories. The first coping category involves voluntarily mobilizing social supports. The second category involves voluntary coping strategies like rehearsing responses to danger. The third coping category, like fever and leukocytosis, is involuntary. It entails deploying unconscious homeostatic mechanisms that reduce the disorganizing effects of sudden stress, DSM-5 offers a tentative hierarchy of defenses, from psychotic to immature to mature. The 70-year prospective Study of Development at Harvard provides a clinical validation of this hierarchy Maturity of coping predicted psychosocial adjustment to aging 25 years later, and was associated with not developing symptoms of post-traumatic stress disorder after very severe WWII combat.
Calculation of Cause-specific Mortality Impacts of Fine Particulate Matter in GAINS

In the early 2000s, the GAINS (Greenhouse gas - Air pollution Interactions and Synergies) model used emerging epidemiological evidence to estimate premature mortality of the European population that can be attributed to the exposure to fine particulate matter and to identify cost-effective emission control strategies that reduce health impacts at least cost (Amann et al., 2011, p.accepted for publication). Based on the review of available studies on the health effects of PM conducted by the UNECE Task Force on Health (UNECE/WHO, 2003), the GAINS impact assessment employed the associations between population exposure to PM2.5 and all-cause mortality of the American Cancer Society study (Pope et al., 2002). In the meantime, a wealth of new epidemiological studies have sharpened the evidence about health effects of particulate matter and revealed more specific associations between ambient concentrations of PM2.5 and health impacts (e.g., Pope et al., 2009). In particular, new studies establish robust relationships between exposure to fine particles and specific causes of deaths. These new insights should facilitate a more specific estimate of the role of particular death causes that are associated with bad air quality, and a more precise estimate of the total mortality impacts in different countries as baseline death rates from different diseases vary over countries. This background paper describes a revised approach of the health impact assessment in GAINS that employs cause-specific concentration-response relationships for lung cancer, cardio-vascular and respiratory diseases for the European countries. Data on cause-specific deaths in the European countries have been extracted from the 2010 version of the World Health Organization database on mortality indicators by 67 causes of death, age and sex (HFA-MDB) for the latest available year. As a result, the cause-specific approach results in higher impact estimates than the former calculation for all-cause mortality. The difference depends on the relative shares of death causes in the various countries; for the EU-27, cause-specific calculations for the year 2000 result in 16% higher health effects, keeping all other factors constant (i.e., PM exposure, population, etc.). In the non-EU countries, the difference amounts to 54%, essentially due to the higher share of cardio-vascular deaths.
Edinburgh Research Explorer MERS-CoV recombination

Recombination is a process that unlinks neighboring loci allowing for independent evolutionary trajectories within genomes of many organisms. If not properly accounted for, recombination can compromise many evolutionary analyses. In addition, when dealing with organisms that are not obligately sexually reproducing, recombination gives insight into the rate at which distinct genetic lineages come into contact. Since June 2012, Middle East respiratory syndrome coronavirus (MERS-CoV) has caused 1,106 laboratory-conﬁrmed infections, with 421 MERS-CoV-associated deaths as of 16 April 2015. Although bats are considered as the likely ultimate source of zoonotic betacoronaviruses, dromedary camels have been consistently implicated as the source of current human infections in the Middle East. In this article, we use phylogenetic meth-ods and simulations to show that MERS-CoV genome has likely undergone numerous recombinations recently. Recombination in MERS-CoV implies frequent co-infection with distinct lineages of MERS-CoV, probably in camels given the current understanding of MERS-CoV epidemiology.
Temporal Trends in Cardiovascular Health Status Among Chinese School-Aged Children From 1989 to 2018: Multiwave Cross-Sectional Analysis

Background Despite the release of updated metrics for Life’s Essential 8 (LE8), key indicators for assessing cardiovascular health (CVH) status, there is currently no report on their distribution among Chinese children. Objective This study aimed to assess the nationwide distribution of CVH in Chinese school-aged children using LE8 scores and analyze temporal changes in these scores over time. Methods Participants aged 7 to 19 years from 11 waves (between 1989 and 2018) of the China Health and Nutrition Survey were included in this study. LE8 components were grouped into 2 domains of health behaviors (diet, physical activity, nicotine exposure, sleep) and health factors (BMI, blood lipids, blood glucose, blood pressure). Scores of overall CVH and each LE8 metric were calculated individually. Temporal changes were assessed with joint point regression models by rural and urban living residence. The causal relationships between health behaviors and health factors that changed the most over time were built with cross-lagged panel models. Results A total of 21,921 participants, 52.6% (n=11,537) of whom were male, who had data for at least 4 CVH components were included in the analysis. The mean age was 13 (SD 3.6) years. The overall CVH score remained stable in most regions, with the lowest found in Shandong from East China, which had a mean between 67 (SD 10.9) and 67.2 (SD 12.4). In contrast, the highest score was found in Guizhou from Southwest China, with a mean between 71.4 (SD 10.8) and 74.3 (SD 10.3). In rural areas, the diet score decreased significantly from 1997 onward with a speed of 0.18 (95% CI: 0.15-0.21; P<.001) per year, and the BMI score decreased significantly from 2005 onward with a speed of 0.56 (95% CI 0.44-0.68; P<.001) per year. In urban areas, the diet score decreased from 1994 onward with a speed of 0.03 (95% CI: 0.001-0.07; P=.04) per year, and the BMI score decreased from 2002 onward with a speed of 0.63 (95% CI 0.47-0.79; P<.001) per year. The sleep score dropped constantly in both urban and rural areas, with a speed of 0.69 (95% CI 0.58-0.80; P<.001) and 0.69 (95% CI: 0.52-0.86; P<.001) per year, respectively. A decline in the diet score led to a decline in the BMI score with a coefficient of 0.190 (95% CI 0.030-0.351; P=.02), while a decline in the BMI score led to a decline in sleep health with a coefficient of 0.089 (95% CI 0.010-0.168; P=.03). Conclusions Chinese school-aged children and adolescents were generally of moderate CVH status, but mutual influences existed between CVH metrics. Dietary interventions should be prioritized for promoting overall CVH in the future.
Digital Platform Ecosystem Performance: Antecedents and Digital Platform Ecosystem Performance: Antecedents and Interrelations Interrelations

The success of many of the world’s most valuable companies is based on digital platform ecosystems (DPEs). Their performance depends on integrating autonomous, individually incentivized but highly entangled actors using digital platforms to cocreate values. Extant research uses numerous dependent variables to measure the performance of different actors in isolation. These variables are often limited to the (economic) gains of single actors, where an interconnected perspective on the performance of the whole DPE is lacking. This study extracts all variables and causal links from 132 empirical articles in top information system, management, and economic outlets and aggregates them into ten interconnected antecedents of DPE performance, namely: Heterogeneity, Competition, Engagement, Governance, Quality, Network Size, Generativity, Architecture, Cost, and Motivation/Satisfaction. Based on a nomological network, we contribute an understanding of DPE performance as an interrelated, sociotechnical, and dynamic construct. Our findings aim to support practitioners in effectively navigating and steering their DPEs.
Holocene environmental and climate evolution of Central West Patagonia as reconstructed from lacustrine sediments of Meseta Chile Chico

Holocene environmental changes in Patagonia were mostly shaped by unsteady ice-cover recession. Consequently, environmental reconstructions are largely based on discontinuous moraine chronologies from valley deposits. Here, we present a 3 m-long continuous sediment record recovered from Laguna Meseta (LME), a lake located on Meseta Chile Chico. Its 15 altitude and location relative to the North Patagonian Icefield provide a unique opportunity to reconstruct the glacial history and the related environmental dynamics. Our radiocarbon chronology constrains sedimentation to the last ~10,000 years and provides a minimum age for postglacial ice-free lacustrine conditions due to a westward retreat of the ice cap. Lacustrine productivity reached its maximum at the start of sedimentation and decreased afterwards. Between 5,500 and 4,600 cal yr BP, a major shift towards allochthonous sediment 20 accumulation occurred, caused by an abrupt increase in clastic deposition from basaltic lithologies of the Meseta Chile Chico. This episode correlates with the precipitation-driven mid-Holocene glacier advance of Patagonian glaciers and suggests that conditions were colder/wetter on the Meseta Chile Chico at that time. After 4,600 cal yr BP these conditions continued to supply LME with clastic sediments until a stepped decrease around 900 cal yr BP. Thereupon, lacustrine productivity distinctly increased and stabilized around 300 cal yr BP. Our findings indicate that environmental conditions on Meseta Chile Chico 25 were mainly controlled by precipitation variability during regional oscillations of the Southern Hemisphere Westerly Winds over the last 10 ka.
Classifying Death Causes with Hierarchical Clustering: The Colombian Case

: Hierarchical clustering is a clustering technique used primarily in natural and social sciences. Unlike the technique of k-means clustering, this allows us to understand the data at different levels of granularity, making it possible the recursively partition of n data points in 2, 3, 4 or n clusters. This can be represented by a tree rooted where all the sheets correspond to the data points given. Each internal node represents a cluster that consists of the data points corresponding to its leaves descendants. The objective of this paper was to present an application case of hierarchical clustering algorithm for classifying the leading death causes in the Colombian departments. Thanks to this classification, we identified some similarity patterns in the appearance of diseases in the north and west center regions of the country, which facilitates the identification of strategies and measures that contribute to the drop in the appearance of the same.
Interplay Of Financial Knowledge And Psychological Factors On Financial Behavior: Evidence From Urban India

The spread and efficacy of financial knowledge in making fruitful financial decisions and in exhibiting rational financial behaviour are widely discussed among policymakers and academicians. Based on the previous literature, the researchers hypothesize that financial behaviour pertaining to savings, borrowing, and investments is influenced by individuals’ financial knowledge along with self -reported financial control, financial self-efficacy and perceived financial satisfaction. This paper employs data from Financial Inclusion Insights India survey 2017 with particular focus on urban populace working in the private sector to understand the interaction of financial knowledge and the said psychological factors on their financial behaviour. A crosssectional data of 1195 respondents across India were analysed for the above-mentioned relevant variables. Significant differences in variable groups were identified using ANOVA. Bivariate relationships and multivariate relationships were explored using correlation and hierarchical regression analysis respectively. The results indicate that financial knowledge, financial satisfaction, and financial self-efficacy have a significant influence on financial behaviour. Also, the channel of knowledge to behaviour is stronger for more educated individuals particularly men.
Uniformity of spheroids-on-a-chip by surface treatment of PDMS microfluidic platforms

Spheroids have emerged as a reliable model in preclinical oncology research. Uniformity of spheroids is the key parameter in the reproducibility and precision of drug test results. Microfluidic-based biochips have many advantages over other spheroid formation methods, including better control over the size of spheroids. Decreasing the cell adhesion to the surface is one of the most important challenges in microfluidic platforms, which could be controlled by appropriate surface engineering methods. We have studied the effect of surface modification of PMDS microfluidic biochips with two commonly used anti-fouling coating materials, BSA and Pluronic F-68, on the uniformity of spheroids produced on-chip. The optimized PDMS surfaces effectively inhibited cell adhesion into the surfaces and promoted cell self-aggregation to produce homogenous and uniform spheroids on-chip. This work highlights the importance of surface modification on the quality and quantity of spheroid formation on microfluidic-based biochips.
Road vehicles – Safety Of The Intended Functionality Using STPA

Unlike the traditional hazard analysis methods, STPA can be started in early concept analysis to assist in identifying safety requirements and constraints. These can then be used to design safety into the system architecture and design, eliminating the costly rework involved when design flaws are identified late in development or during operations. As the design is refined and more detailed design decisions are made, the STPA analysis is also refined to help make more and more detailed design decisions. Complete traceability from requirements to all system artifacts can be easily maintained, enhancing system maintainability and evolution. STPA found all the causal scenarios found by the more traditional analyses but it also identified many more, often performance-related and operator misuse, scenarios that the traditional methods did not find. Finally, feasibility of SOTIF using STPA will be illustrated with an example in the presentation.