Miracle-dz/UniFAR-FTUs huggingface dataset:
Risks of suicide among family members of suicide victims: A nationwide sample of South Korea

Objective Identifying the risks of completed suicide in suicide survivors is essential for policies supporting family members of suicide victims. We aimed to determine the suicide risk of suicide survivors and identify the number of suicides per 100,000 population of suicide survivors, bereaved families of traffic accident victims, and bereaved families with non-suicide deaths. Methods This was a nationwide population-based cohort study in South Korea. The data were taken from the Korean National Health Insurance and Korea National Statistical Office between January 2008 and December 2017. The relationship between the decedent and the bereaved family was identified using the family database of the National Health Insurance Data. Age and gender were randomly matched 1:1 among 133,386 suicide deaths and non-suicide deaths. A proportional hazard model regression analysis was conducted after confirming the cumulative hazard using Kaplan–Meier curves to obtain the hazard ratio (HR) of completed suicide in suicide survivors. Results Using 423,331 bereaved families of suicide victims and 420,978 bereaved families of non-suicide deaths as the control group, HR of completed suicide in suicidal survivors was found to be 2.755 [95% confidence limit (CL): 2.550–2.977]. HR for wives committing suicide after husbands' suicide was 5.096 (95% CL: 3.982–6.522), which was the highest HR among all relationships with suicide decedents. The average duration from suicide death to suicide of family members was 25.4 months. Among suicide survivors, the number of suicides per 100,000 people was 586, thrice that of people in bereaved families of traffic accident victims and in bereaved families of non-suicide deaths. Conclusion The risk of completed suicide was three times higher in suicide survivors than in bereaved families with non-suicide deaths, and it was highest in wives of suicide decedents. Thus, socio-environmental interventions for suicidal survivors must be expanded.
Larval Development in Tropical Gar (Atractosteus tropicus) Is Dependent on the Embryonic Thermal Regime: Ecological Implications under a Climate Change Context

In ectotherm species, environmental temperature plays a key role in development, growth, and survival. Thus, determining how temperature affects fish populations is of utmost importance to accurately predict the risk of climate change over fisheries and aquaculture, critical to warrant nutrition and food security in the coming years. Here, the potential effects of abnormal thermal regimes (24, 28 and 32 °C; TR24, TR28, and TR32, respectively) exclusively applied during embryogenesis in tropical gar (Atractosteus tropicus) has been explored to decipher the potential consequences on hatching and growth from fertilization to 16 days post-fertilization (dpf), while effects on skeletal development and body morphology were explored at fertilization and 16 dpf. Egg incubation at higher temperatures induced an early hatching and mouth opening. A higher hatching rate was obtained in eggs incubated at 28 °C when compared to those at 24 °C. No differences were found in fish survival at 16 dpf, with values ranging from 84.89 to 88.86%, but increased wet body weight and standard length were found in larvae from TR24 and TR32 groups. Thermal regime during embryogenesis also altered the rate at which the skeletal development occurs. Larvae from the TR32 group showed an advanced skeletal development, with a higher development of cartilaginous structures at hatching but reduced at 16 dpf when compared with the TR24 and TR28 groups. Furthermore, this advanced skeletal development seemed to determine the fish body morphology. Based on biometric measures, a principal component analysis showed how along development, larvae from each thermal regime were clustered together, but with each population remaining clearly separated from each other. The current study shows how changes in temperature may induce craniofacial and morphological alterations in fish during early stages and contribute to understanding the possible effects of global warming in early development of fish and its ecological implications.
Distinct sub-second dopamine signaling in dorsolateral striatum measured by a genetically-encoded fluorescent sensor

Dopamine produces neuromodulation throughout the basal ganglia, cortex and other brain regions, and is implicated in movement control, neural mechanisms of reward and actions of misused substances. The efferent projections of dopaminergic neurons with somata in the substantia nigra pars compacta and ventral tegmental area strongly innervate different striatal subregions. While much is known about the function of these neurons, there is a relative deficiency of information about in vivo dopamine dynamics in the nigrostriatal projections, especially those to the dorsolateral striatum (DLS). In past studies, subsecond dopamine changes were measured predominantly with fast-scan cyclic voltammetry (FSCV) both in brain slices and in vivo. However, traditional FSCV has limitations in discriminating among catecholamines, and cannot be used for simultaneous measurement of both slow and fast/phasic dopamine changes. In addition, FSCV has been most useful for measuring dopamine in the ventral striatum in vivo with less utility for measurement in dorsolateral striatum. The development of genetically encoded dopamine sensors has provided a new approach to measuring slow and fast dopamine dynamics both in brain slices and in vivo, raising the hope of more facile measurement of in vivo dopamine measurements, including in areas where measurement was previously difficult with FSCV. To this end, we first evaluated dLight photometry in brain slices with simultaneous FSCV. We found that both techniques yielded comparable findings. However, differences were noted in responses to dopamine transporter inhibitors, including cocaine. We then used in vivo fiber photometry with dLight to examine responses to cocaine in DLS and compared responses during Pavlovian conditioning in DLS to two other striatal subregions. These experiments show that dopamine increases are readily detectable in DLS and provide new information about dopamine transient kinetics and slowly developing signaling during conditioning. Overall, our findings indicate that dLight photometry is well suited to measuring dopamine dynamics in a striatal region of great interest where such measurements were difficult previously.
SMART CIRCUIT BREAKER: A UNIQUE AND OPTIMIZED SOLUTION FOR DIFFERENT APPLICATIONS

The present paper describes a new generation of medium voltage apparatus where the tailored integration of both embedded control electronics and IoT sensors allow to implement different sets of behaviours in terms of timing performance, actuator controls and used sensors interface extending the capability of the apparatus. The increased performance can be easily tailored and combined with the selection of different operational and logic profiles enabling easy matching with the application requirements and special integration needs.
Deploying an Artificial Intelligence-Based Defect Finder for Manufacturing Quality Management

This paper describes how the Big Data Research Center of Kyung Hee University and Benple Inc. developed and deployed an artificial intelligence system to automate the quality management process for Frontec, an SME company that manufactures automobile parts. Various constraints, such as response time requirements and the limited computing resources available, needed to be considered in this project. Defect finders using large-scale images are expected to classify weld nuts within 0.2 s with an accuracy rate of over 95%. Our system uses Circular Hough Transform for preprocessing as well as an adjusted VGG (Visual Geometry Group) model. Our convolutional neural network (CNN) system shows an accuracy of over 99% and a response time of about 0.14 s. To embed the CNN model into the factory, we reimplemented the preprocessing modules using LabVIEW and had the classification model server communicate with an existing vision inspector. We share our lessons from this experience by explain-ing the procedure and real-world issues developing and embedding a deep learn-ing framework in an existing manufacturing environment without implementing any hardware changes.
Job forecasting based on the patent information: A word embedding-based approach

The rapid change in technology makes it challenging to forecast the future of jobs. Previous studies have analyzed economics and employment data or employed expert-based methods to forecast the future of jobs, but these approaches were not able to reflect the latest technology trends in an objective way. To overcome the issue, this study matches jobs with patents and forecasts the future of jobs based on changes in the number of patents with time. A word embedding model is trained by patent classification code and job description data and used to find similar patent classification codes of jobs. For an illustration purpose, we identify information technology-related jobs listed in O*NET and discover similar patent classification codes of the jobs. Based on the change in the number of patents, we find promising jobs presenting high technical demands. Several implications of our approach are also discussed.
Determining Factors of the Use of E-learning during COVID-19 Lockdown among the college students of Nepal: A Cross-Sectional Study

COVID-19 Pandemic had affected all sectors of human life around the globe. Education is one of them where traditional method of teaching had to be shift to virtual learning all of sudden in both developed and developing countries. Therefore, the article reflects that associated factors of E-learning among college students of Nepal during emergency shift of teaching paradigm due to COVID-19. Convenient sampling method through social media and Google form was used to collect 385 data from college students of Nepal during COVID-19 Pandemic lockdown. The article only 30% of the Nepalese students had all the required resources all the time for the use of E-learning however, 85% of the student had engaged in in E-learning during COVID-19 pandemic lockdown. The study found that gender, marital status, training on the use of E-learning, experience of E-learning prior to pandemic were statistically significant with the future use of E-learning. In conclusion, educational institutions need be responsive towards the challenges faced by students during E-learning, so that learning needs of the students will be fulfilled even in pandemic situation.
BAYESIAN INFERENCE BY INFORMATIVE GAUSSIAN FEATURES OF THE DATA

Sebastian Springer Bayesian inference by informative Gaussian features of the data Lappeenranta 2021 62 pages Acta Universitatis Lappeenrantaensis 950 Diss. Lappeenranta-Lahti University of Technology LUT ISBN 978-952-335-627-6, ISBN 978-952-335-628-3 (PDF), ISSN-L 1456-4491, ISSN 1456-4491 Given a set of measurements, a model can be calibrated to data by minimising a cost function that captures the model-data difference. The standard cost function for deterministic models is the residual sum of squares between the model output and the reference data. Sequential data assimilation methods can be used for stochastic models whenever it is possible to estimate the next state of the system from the current values. Chaotic dynamical systems are a specific type of models for which the classic approaches are often not available. Especially so, if the time gap between consecutive observations is higher than the predictable time interval. There is, therefore, a need for new methods for such problems, defined even as insolvable in the literature. In recent years, Haario et al. presented a solution to estimate the model parameters of chaotic systems by the so-called Correlation integral likelihood (CIL). The idea behind it is to use a generalisation of the correlation integral sum as a feature vector and build a Gaussian likelihood by estimating the variability from the repetitions of the experiment. In this work, we will further develop those ideas. We will first see how to generalise the CIL approach to use statistics that best fit the specific problem studied. Furthermore, we will see how it is possible to create different feature vectors from one or several data sets concerning the same phenomenon and combine them in a single likelihood to improve the estimation of the parameters. It will be shown how by using this method it is possible to estimate the parameters of chaotic systems when only the state vector is observed, or only a part of it, and when the measurements are arbitrarily sparse and scattered. We emphasise that the original distance-based CIL is by no means the only way to construct provably Gaussian feature vectors. Indeed, the selection of features to produce normally distributed empirical cumulative distribution function (eCDF) vectors should be carefully done case by case. Moreover, we will present tools to diagnose goodness-of-fit or a possible lack of fit after the posterior distribution has been obtained. To make our approach available also for cases with expensive forward models, we studied the combination with the Local Approximation MCMC (LA-MCMC) algorithms. The idea behind these types of sampling methods is to construct local polynomial approximations of the likelihood by regression over a set of neighbouring evaluations of the expensive likelihood, and make it more and more precise as the sampling proceeds. By this method, the number of expensive likelihood evaluations could be reduced by orders of magnitude without significantly impacting the precision of the resulting posterior distribution.
Statistical Behavior of Large‐Scale Ionospheric Disturbances From High Latitudes to Mid‐Latitudes During Geomagnetic Storms Using 20‐yr GNSS‐TEC Data: Dependence on Season and Storm Intensity

To establish the statistical behavior of ionospheric TEC variations from high latitudes to mid‐latitudes during the main and recovery phases of geomagnetic storms, we conducted a superposed epoch analysis of interplanetary magnetic field, solar wind, geomagnetic indices (AE and SYM‐H), and global navigation satellite system (GNSS)‐total electron content (TEC) data for 20 yr (2000–2019). In this study, we identify 663 geomagnetic storm events with the minimum SYM‐H value of less than −40 nT and investigate the characteristics of the TEC variations for the weak (−60 ≤ SYM‐Hmin < −40 nT), moderate (−100 ≤ SYM‐Hmin < −60 nT), and strong (−150 ≤ SYM‐Hmin < −100 nT) geomagnetic storms. The main results obtained from the present study are as follows: (a) The TEC enhancements related to the tongue of ionization (TOI), auroral oval, and storm‐enhanced density (SED) plume are more dominant in winter than in summer during the main phase of geomagnetic storms. (b) The structure of the mid‐latitude trough in the nighttime sector becomes unclear in winter. (c) The TEC depletion at auroral and mid‐latitudes (40°–70° GMLAT: geomagnetic latitude) starts to appear in the morning sector (8–10 hr GMLT: geomagnetic local time) during the main phase of geomagnetic storms and the decreased region extends in the lower latitude and GMLT directions with time. The negative storm activity tends to be enhanced significantly as the storm intensity becomes larger. The activity of the TEC depletion is dominant in summer than in winter, which is agreement with the classical ionospheric storm scenario.
Access to healthcare during COVID-19 among ageing population in Latvia

Medical staff has worked tirelessly throughout the COVID-19 pandemic to test and treat coronavirus patients. However, the focus on the virus has caused huge disruption to healthcare services, resulting in delayed treatment for patients with other serious conditions. Additionally, the reasons for forgoing or abstaining healthcare could also relate to individual decisions. We used data from the Survey of Health, Ageing and Retirement in Europe (SHARE), where the respondents aged 50 and older of the Wave 8, version 0, were asked to answer, among other, questions on delayed, postponed or denied healthcare services during the first wave of COVID-19 pandemic in Latvia. For comparative reasons also Estonian and Lithuanian data were included in the study with 2 473 627 valid weighted cases in total. Due to the large sample size, in order to evaluate statistically significant result for Pearson’s chi-square test, strength of association (f) was provided. The results show that 12.7% of the respondents forwent and 14% postponed medical treatment in Latvia. Appointment was denied to 5.5% of the respondents. Generally, older people in Latvia had better access to health care services compared to the average in the Baltic countries. We found significant age and gender differences, but they varied depending on the type of treatment and reason for not receiving it. However, further studies are necessary to analyse how limited access to the healthcare for other reasons has affected health of the ageing population. Also, more knowledge is needed about how to maintain public health and wellbeing for the growing part of the ageing society.
Retrofittable Solutions Capability for Gas Turbine Compressors

The increasing introduction of renewable energy capacity has changed the perspective on the operation of conventional power plants, introducing the necessity of reaching extreme off-design conditions. There is a strong interest in the development and optimization of technologies that can be retrofitted to an existing power plant to enhance flexibility as well as increase performance and lower emissions. Under the framework of the European project TURBO-REFLEX, a typical F-class gas turbine compressor designed and manufactured by Ansaldo Energia has been studied. Numerical analyses were performed using the TRAF code, which is a state-of-the-art 3D CFD RANS/URANS flow solver. In order to assess the feasibility of lower minimum environmental load operation, by utilizing a reduction in the compressor outlet mass-flow rate, with a safe stability margin, two different solutions have been analyzed: blow-off extractions and extra-closure of Variable Inlet Guide Vanes. The numerical steady-state results are compared and discussed in relation to an experimental campaign, which was performed by Ansaldo Energia. The purpose is to identify the feasibility of the technologies and implementation opportunity in the existing thermal power plant fleet.
unc-37/Groucho and lsy-22/AES repress Wnt target genes in C. elegans asymmetric cell divisions

Asymmetric cell division (ACD) is a fundamental mechanism of cell fate specification and adult tissue homeostasis. In C. elegans, the Wnt/β-catenin asymmetry (WβA) pathway regulates ACDs throughout embryonic and larval development. Under control of Wnt ligand-induced polarity, the transcription factor POP-1/TCF functions with the coactivator SYS-1/β-catenin to activate gene expression in the signaled cell or, in absence of the coactivator, to repress Wnt target genes in the unsignaled daughter cell. To date, investigation of Groucho function in WβA is lacking, and the function of LSY-22/AES has only been evaluated in C. elegans neurons. Further, conflicting evidence shows TCF utilizing Groucho-mediated repression may be either aided or repressed by AES addition. Here we demonstrate a genetic interaction between Groucho corepressors and POP-1/TCF in the distal tip cells (DTCs), seam cells (SCs) and embryonic endoderm development. In the DTCs, signaled cell fate increases after individual and double Groucho loss of function, representing the first demonstration of Groucho function in wildtype WβA ACDs. Further, WβA target gene misexpression occurs more frequently than DTC fate changes, suggesting derepression generates an intermediate cell fate. In the SCs, loss of UNC-37/Groucho or LSY-22/AES in a POP-1/TCF hypomorphic background enhances SC expansion and target gene misregulation. Moreover, while POP-1/TCF depletion in lsy-22/AES nulls yielded an expected increase in SCs we observed a surprising SC decrease in unc-37/Groucho nulls subjected to POP-1/TCF depletion. This phenotype correlates with UNC-37/Groucho regulation of pop-1/tcf expression since POP-1/TCF levels are increased in unc-37/Groucho null SCs. Lastly, Groucho functions in embryonic endoderm development since we observe ectopic endoderm transgene expression in unc-37/Groucho and lsy-22/AES knockdown in a HDA-1 background. Together, these data indicate Groucho-mediated modulation of cell fate via regulation of POP-1/TCF repression is widespread in WβA ACDs and suggests a novel role of LSY-22/AES as a bona fide TCF repressor.
Function Computation under Privacy, Secrecy, Distortion, and Communication Constraints

The problem of reliable function computation is extended by imposing privacy, secrecy, and storage constraints on a remote source whose noisy measurements are observed by multiple parties. The main additions to the classic function computation problem include (1) privacy leakage to an eavesdropper is measured with respect to the remote source rather than the transmitting terminals’ observed sequences; (2) the information leakage to a fusion center with respect to the remote source is considered a new privacy leakage metric; (3) the function computed is allowed to be a distorted version of the target function, which allows the storage rate to be reduced compared to a reliable function computation scenario, in addition to reducing secrecy and privacy leakages; (4) two transmitting node observations are used to compute a function. Inner and outer bounds on the rate regions are derived for lossless and lossy single-function computation with two transmitting nodes, which recover previous results in the literature. For special cases, including invertible and partially invertible functions, and degraded measurement channels, simplified lossless and lossy rate regions are characterized, and one achievable region is evaluated as an example scenario.
A Framework for Describing Theoretical Perspectives: Overview and Application to the Work System Perspective

This paper summarizes a framework for describing theoretical perspectives (an FDTP) and uses it to describe the work system perspective (WSP) in a way that integrates ideas that often had been discussed in isolation from each other. It also illustrates how the FDTP can support application of the WSP to the idea of digital transformation (DT). It discusses the general value of the FDTP along with potential applications.
Synthesis and Characterization of Novel Uracil-Modified Chitosan as a Promising Adsorbent for Efficient Removal of Congo Red Dye

Novel Uracil-modified chitosan (UCs) adsorbent has successfully been synthesized through a four-step method during which the amino groups of chitosan have been protected, then epoxy nuclei have been incorporated, afterwards the latter have been opened using 6-amino-1,3-dimethyl uracil, and finally the amino groups have been regained via removing the protection. Its structure was checked using FTIR, XRD and SEM techniques. The adsorption capacity of UCs for anionic Congo Red (CR) dye was studied under various conditions. It decreased significantly with increasing the solution pH value and dye concentration, while increased with increasing temperature. The adsorption of UCs for CR dye at different temperatures, solution pH and dye concentrations fitted to the kinetic model of pseudo-second order and Elovich model. The intraparticle diffusion model showed that the adsorption process involves multi-step process. The isotherm of CR dye adsorption by UCs conforms to the Langmuir isotherm model indicating the monolayer nature of adsorption. The maximum monolayer coverage capacity, qmax, was 434.78 mg g−1. Studying the thermodynamic showed that the adsorption of CR dye onto UCs was endothermic as illustrated from the positive value of enthalpy (21.37 kJ mol−1). According to the values of ΔG°, the adsorption process was spontaneous at all selected temperatures. The value of ΔS° showed an increase in randomness for the adsorption of CR dye by UCs. The value of activation energy was 18.40 kJ mol−1.