Miracle-dz/UniFAR-FTUs huggingface dataset:
Influence of Profit Sharing Funds and Regional Financial Performance in the Previous Year on the Allocation of Capital Expenditures in Provincial Governments in Indonesia in 2016 – 2020

This research is aimed at testing the influence of revenue sharing funds, the previous year's ratio of local independence, the previous year's effectiveness, the previous year's expenditure harmony toward capital expenditure allocation in the provincial government in Indonesia in 2016-2020. The data used in this research is secondary data which is obtained from access to financial reports from the website www.djpk. depkeu.go. id. Analysis of the data in this research using a quantitative approach with statistical descriptive tests, classic assumption tests, multiple regression analysis and hypothesis testing was helped by SPSS 22. The results of this research indicate that the revenue sharing fund variable has no effect on capital expenditure with a significant value of 0.055> 0.05. An independent variable independence ratio from the previous year affects capital expenditure allocation in a negative direction with a significant value of 0.017<0.05. The higher the independence ratio, the lower the capital expenditure allocation. The previous year's effectiveness variable did not affect the allocation of capital expenditure with a significant value of 0.224> 0.05. An independent variable expenditure harmony ratio from previous year affects capital expenditure allocation in a negative direction with a significant value of 0.000<0.05. And simultaneously revenue sharing fund, financial independence of the previous year, the effectiveness of the previous year.
Securing Retirement Through Intra-European Migration: Older Romanian Women’s Transnational Struggle for Formal Social Protection

This article explores through qualitative methods how structural inequalities and weak welfare states push women to migrate in their old age to piece together their pension across different countries. Based on in-depth interviews, observations, and ethnographic conversations conducted with Romanian women in Spain, it explores how they navigate the European Union’s (UE) law on Social Security to aggregate social insurance periods from the work performed in different member states and therefore get entitled to a state pension. We analyze how the accumulation of vulnerabilities (related to class, gender, age, and ethnicity) shape the trajectories of these aging women in a context of structurally unequal welfare systems. The paper thus contributes to the transnational social protection field with a timely focus on old age formal arrangements within the EU and use of life-course approach to understand the reasons of related with social protection older migrant’s im/mobilities.
Attitudes of Anesthesiology Postgraduate Residents Toward the Influential Factors in Their Success in the Iranian National Board Exam

Background One of the prominent indicators of academic success in postgraduate medical education is the “Residents’ Pass Rate” in the “National Board Exam. ” Objectives This study was designed and implemented to assess the attitudes of the anesthesiology residents toward factors affecting their success in the National Board Exam. Methods After the Institutional Review Board (IRB) approval, in an attitude assessment study, 20 of the 21 recently graduated anesthesiology residents were asked about the factors affecting their success quantitatively and qualitatively. A self-administered questionnaire with 19 closed questions and a personal virtual WhatsApp Messenger® interview were used for the study. Results The respondents’ viewpoints demonstrated that a step-by-step multifaceted integrative program in combination with psychological support (both from the family and the department) and individual motivation positively affected their success and their endurance to overcome the high load of the mandatory texts. In contrast, unplanned stressors leading to program shifts (mainly due to COVID-19) had adverse effects on their success. Conclusions Anesthesiology residents believed that a well-designed and appropriately implemented study plan with psychological support and personal motivating factors could facilitate passing the National Board Exam, and unplanned external stressors could hinder it.
Effect of ownership structure on dividend payments: Evidence from public companies in Nordic and Baltic Countries

Abstract We investigate whether ownership structure influences the likelihood and amount of dividend payments in two groups of European Union’s public companies: Nordic and Baltic. Nordic and Baltic capital markets have become increasingly integrated through Nasdaq OMX stock exchanges and harmonized by the EU corporate governance directives. However, some differences in the corporate governance system, legislation, practice, and ownership structure still exist. The study covers Nordic and Baltic companies listed on the Nasdaq OMX for the period 2013–2020. Logit and Tobit panel regressions are applied to disclose the effect of ownership structure on the likelihood and amount of dividend payments accordingly. We find that ownership concentration positively influences the likelihood and amount of dividend payments in Nordic public companies. Managerial ownership does not influence the likelihood of dividend payments but positively influences their amount. Institutional ownership does not influence the likelihood of dividend payments but negatively influences their amount. Our findings revealed that ownership structure does not have any effect either on the likelihood of dividend payments or on their amount in Baltic public companies. We disclosed that the effect of ownership structure on dividend payments is influenced by the context behind ownership structure. The results of our research will improve understanding and predict the decision-making on dividend payments and will help investors manage their portfolios, choosing between current and future consumption.
Methods for solving regularized inverse problems : from non-Euclidean fidelities to computational imaging applications

Many branches of science and engineering are concerned with the problem of recording signals from physical phenomena. However, an acquisition system does not always directly provide the high-quality signal representations that a given application may require. Signal processing and the study of inverse problems offer a set of powerful tools to recover a good signal quality from altered raw measurements. After a preliminary overview of the field, this thesis presents three main contributions. They involve, in various degrees, the interconnected constituents of a regularized inverse problem: the forward model, the prior or regularization, the data fidelity, and the recovery method. The first and most theoretical contribution focuses on recovering a key structural property of a sparse signal, its support. It discusses guarantees associated to a convex optimization method with atypical fidelity, e.g., using a non-Euclidean norm. The second part introduces a method for learning a convoluti. Document type : Thèse (Dissertation) Référence bibliographique Degraux, Kévin. Methods for solving regularized inverse problems : from non-Euclidean fidelities to computational imaging applications. Prom. : Jacques, Laurent METHODS FOR SOLVING REGULARIZED INVERSE PROBLEMS: FROM NON-EUCLIDEAN FIDELITIES TO COMPUTATIONAL IMAGING APPLICATIONS
Identifying Critical Test Scenarios for Lane Keeping Assistance System Using Analytic Hierarchy Process and Hierarchical Clustering

Lane keeping assistance system (LKAS) is critical components of autonomous driving technologies, and their reliable operation is crucial to ensure passenger safety and maintain traffic flow. The validation of LKAS's safety and performance requires extensive testing using diverse and representative test scenarios. However, identifying the most critical test scenarios from a large data is a significant challenge. Inspired by Scenarios Engineering, the present study introduces a novel approach that includes being the first to combine analytic hierarchy process (AHP) and hierarchical clustering (HC) to identify critical test scenarios for the comprehensive evaluation of LKAS. The proposed approach first utilizes the AHP to rank the key factors that contribute to the failure of the LKAS. Then, by taking the key factors as clustering parameters, the HC method is employed to cluster LKAS failure scenarios with similar characteristics. The experimental results suggest that our method is capable of effectively clustering 200 LKAS failure scenarios into 9 categories of critical, reasonable, and reliable LKAS test scenarios. Furthermore, these 9 categories of critical test scenarios can provide guidance for the development and testing of autonomous driving and serve as a foundation for establishing a testing and evaluation system for LKAS in China and around the world.
Statistica Sinica Preprint No : SS-2015-0392 . R 2 Title Optimal Model Averaging Estimation for Partially Linear Models

This article studies optimal model averaging for partially linear models with heteroscedasticity. A Mallows-type criterion is proposed to choose the weight. The resulting model averaging estimator is proved to be asymptotically optimal under some regularity conditions. Simulation experiments show that the proposed model averaging method is superior to other commonly used model selection and averaging methods. The proposed procedure is further applied to study Japan’s sovereign credit default swap spreads.
Machine learning-accelerated aerodynamic inverse design

The computational cost of iterative design methods has been a challenge in aerodynamics. In this research, the data-driven acceleration of an iterative inverse design method was implemented to reduce its computational cost. Although iterative design methods are robust, a lot of unwanted data is generated during their intermediate stages. Inverse design methods rely on correcting an initial geometry based on a given target parameter distribution. The generated data during the early iterations of the inverse design was incorporated into two deep-learning models to accelerate target geometry attainment. The deep learning models were used to recognize the correlation between the pressure distribution and corresponding geometry as well as the meaningful changes of geometry and pressure distribution toward their targets. The deep learning models were validated in viscous and inviscid compressible flows for various benchmark aerodynamics problems. In conclusion, between 70 to 80% computational cost decrease was observed for online uses of the machine learning module with the inverse design algorithm. This approach suggests incorporating machine learning techniques into design algorithms by exploiting the intermediate data for further improvement of them. We draw a new interpretation of learning dynamic changes through consecutive iterations instead of typical time-dependent problems in the use of LSTM network.
q-Difference equations for the generalized Cigler’s polynomials

Abstract In this paper, we show how to prove several types of generating functions for Cigler’s polynomials involving four variables by the method of homogeneous q-difference equations. We utilize some methods and results of Liu’s [Ramanujan Math. Soc. 20 (2013), pp. 213–250. ] and Fang’s [Appl. Math. Comput. 248 (2014), pp. 550–561. ] continue to study Cigler’s results [J. Differ. Equ. Appl. 22 (2016), pp. 1880–1892. ]. In addition, we deduce type generation functions for Cigler’s polynomials. More over, we build relations between transformation formulas and homogeneous q-difference equations. And then, we gain multilinear and multiple generating functions for Cigler’s polynomials as application. Finally, we generalize Andrews–Askey integrals, moment integrals and Askey–Roy integrals by the method of homogeneous q-difference equations.
Intranasal immunization with a Bucl8-based vaccine ameliorates bacterial burden and pathological inflammation, and promotes an IgG2a/b dominant response in an outbred mouse model of Burkholderia infection

Burkholderia pseudomallei is a gram-negative bacterium that is the etiological agent of the tropical disease melioidosis. Currently, there is no licensed vaccine for melioidosis, but numerous candidates are being tested for protective efficacy and characterization of the elicited immune response. Our lab has previously reported the immunogenicity of a Bucl8-protein-based peptide antigen, designated L1-CRM197 (Cross-reacting material 197). When given subcutaneously, this vaccine formulation promoted a strong Th2 (IgG1) antibody response, however immunization did not protect from death. In this study, we hypothesized that an intranasally administered L1-CRM197 vaccine would induce protective mucosal immunity. To evaluate vaccine efficacy, we developed a surrogate Burkholderia infection model that employs outbred CD-1 mice which imitates the immunogenetic diversity of humans. Mice were immunized with either L1-CRM197 adjuvanted with fluorinated cyclic diguanosine monophosphate (FCDG) or with FCDG-only control. These mice were then challenged intranasally with an infectious dose of a luminescent strain of B. thailandensis E264 two weeks post-immunization, and correlates of protection were assessed in euthanized mice on days 1, 2, 3, and 7 post-infection. Overall, intranasal vaccination, compared to subcutaneous administration, induced a stronger Th1 (IgG2a/2b) to Th2 (IgG1) antibody response and promoted anti-L1 nasal, pulmonary, and systemic IgA. Additionally, sera IgG from L1-CRM197-vaccinated mice recognized whole-cell B. thailandensis and B. pseudomallei, a select agent exempt strain Bp82. Vaccination ameliorated disease indicators, including luminescent signal and bacterial cell counts, weight and temperature loss, and organ weight, which negatively correlated with IgG2a antibody levels and mucosa-stimulating cytokines IL-13 and IL-9. L1-CRM197-vaccinated mice also had earlier resolution of inflammatory and tissue-damaging cytokines compared to the FCDG-only controls. These results suggest a balanced humoral and cell-mediated response, along with mucosa-based immunity are beneficial for protection. Future efforts should further assess mucosal cellular and humoral mechanisms of protection and test such protection, using aerosolized B. pseudomallei select agent strain(s).
Propagating Sentinel-2 Top-of-Atmosphere Radiometric Uncertainty Into Land Surface Phenology Metrics Using a Monte Carlo Framework

Time series of optical imagery allow one to derive land surface phenology metrics. These metrics are only complete with a statement about their uncertainty. A source of uncertainty is the radiometry of the sensor. We propagated radiometric uncertainties within a Monte Carlo framework into phenological metrics using the TIMESAT approach based on time series of the normalized difference vegetation index (NDVI), three-band enhanced vegetation index (EVI), and green leaf area index (GLAI) derived from radiative transfer modeling. In addition, we studied the effect of propagated uncertainties on scene preclassification. We focused on Sentinel-2 multispectral imager top-of-atmosphere data since quantitative estimates of radiometric uncertainties are available. Propagation was carried out for a growing season over an agricultural region in Switzerland. Propagated uncertainties had little impact on the classification except for spectrally mixed pixels. Effects on the spectral indices and GLAI were more pronounced. In detail, the GLAI was more uncertain due to the ill-posedness of radiative transfer model inversion (median relative uncertainty for all crop pixels and Sentinel-2 scenes: 4.4%) than EVI (2.7%) and NDVI (1.1%). Regarding phenology, metrics exhibited largest uncertainties in the case of GLAI. The magnitude of uncertainty in the metrics depends on the interscene error correlation, which we assumed to be either zero (uncorrelated) or one (fully correlated) since the actual correlation is unknown. If uncertainties are fully correlated, uncertainties in metrics are small (two to three days) but take values up to greater ten days under the uncorrelated assumption. Thus, our work provides guidance for the interpretation of phenological metrics.
They have taken out my spinal cord: an interpretative phenomenological analysis of self-boundary in psychotic experience within a sociocentric culture

Introduction In the tradition of phenomenological psychiatry, schizophrenia is described as a disturbance of the minimal self, i.e. the most basic form of self-awareness. This disturbance of the minimal self at the individual level is assumed to precede the intersubjective disturbances such as boundary weakening. However, the role of intersubjective disturbances in the emergence and recovery of schizophrenic experience still remains an open question. This phenomenological study focuses on how encounters with others shape self-experience during from psychosis by analyzing this process from the perspective of cultural differences, which in current research is especially under-researched. While most phenomenological accounts are based on first person-accounts from Western, individualist cultures where the self is conceived and experienced as separate to others, the present study qualitatively investigates psychotic experiences of patients from Jaffna, Sri Lanka. Method Semi-structured interviews were conducted with three participants with a diagnosis of schizophrenia or first episode psychosis. The interviews were transcribed and analyzed using interpretative phenomenological analysis (IPA). Eight group experiential themes were identified across interviews. Results The data suggest that intersubjective processes of boundary weakening such as invasiveness and hyperattunement may shape minimal self-experience and more specifically contribute to a mistrust of the own senses and to hyper-reflexivity. Interestingly, boundary weakening yields pervasive emotions and can be experienced as a threat to the whole social unit. On the one hand, the strengthening of self-other-boundary was achieved through opposition, closedness and withdrawal from others. On the other hand, this study suggests that the re-opening of self-other-boundaries in response to the crisis may help establish connectedness and may lead to recovery.
Calpain Regulation and Dysregulation—Its Effects on the Intercalated Disk

The intercalated disk is a cardiac specific structure composed of three main protein complexes—adherens junctions, desmosomes, and gap junctions—that work in concert to provide mechanical stability and electrical synchronization to the heart. Each substructure is regulated through a variety of mechanisms including proteolysis. Calpain proteases, a class of cysteine proteases dependent on calcium for activation, have recently emerged as important regulators of individual intercalated disk components. In this review, we will examine how calcium homeostasis regulates normal calpain function. We will also explore how calpains modulate gap junctions, desmosomes, and adherens junctions activity by targeting specific proteins, and describe the molecular mechanisms of how calpain dysregulation leads to structural and signaling defects within the heart. We will then examine how changes in calpain activity affects cardiomyocytes, and how such changes underlie various heart diseases.
Eye-tracking paradigms for the assessment of mild cognitive impairment: a systematic review

Mild cognitive impairment (MCI), representing the ‘transitional zone’ between normal cognition and dementia, has become a novel topic in clinical research. Although early detection is crucial, it remains logistically challenging at the same time. While traditional pen-and-paper tests require in-depth training to ensure standardized administration and accurate interpretation of findings, significant technological advancements are leading to the development of procedures for the early detection of Alzheimer’s disease (AD) and facilitating the diagnostic process. Some of the diagnostic protocols, however, show significant limitations that hamper their widespread adoption. Concerns about the social and economic implications of the increasing incidence of AD underline the need for reliable, non-invasive, cost-effective, and timely cognitive scoring methodologies. For instance, modern clinical studies report significant oculomotor impairments among patients with MCI, who perform poorly in visual paired-comparison tasks by ascribing less attentional resources to novel stimuli. To accelerate the Global Action Plan on the Public Health Response to Dementia 2017–2025, this work provides an overview of research on saccadic and exploratory eye-movement deficits among older adults with MCI. The review protocol was drafted based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Electronic databases were systematically searched to identify peer-reviewed articles published between 2017 and 2022 that examined visual processing in older adults with MCI and reported gaze parameters as potential biomarkers. Moreover, following the contemporary trend for remote healthcare technologies, we reviewed studies that implemented non-commercial eye-tracking instrumentation in order to detect information processing impairments among the MCI population. Based on the gathered literature, eye-tracking-based paradigms may ameliorate the screening limitations of traditional cognitive assessments and contribute to early AD detection. However, in order to translate the findings pertaining to abnormal gaze behavior into clinical applications, it is imperative to conduct longitudinal investigations in both laboratory-based and ecologically valid settings.
Pituitary Diseases and COVID-19 Outcomes in South Korea: A Nationwide Cohort Study

The pituitary gland is either directly or indirectly impacted by SARS-CoV-2 infection. As a consequence of SARS-CoV-2 infection, hypothalamic–pituitary dysfunction or pituitary apoplexy can occur. This study aimed to investigate severe COVID-19 outcomes and COVID-19-related mortality in patients with underlying pituitary disease in Korea using a nationwide cohort database. The data required for this study were obtained from the Health Insurance Review and Assessment Service of Korea. Patients with SARS-CoV-2 infection between January 2020 and December 2021 were divided into the following three groups and analyzed: Group A, those who were hospitalized for SARS-CoV-2 infection without underlying pituitary disease (n = 725,170); Group B, those who were hospitalized for SARS-CoV-2 infection with underlying pituitary disease without exposure to systemic steroids (n = 1509); and Group C, patients with underlying pituitary disease and exposure to systemic steroids (n = 365). Differences in severe COVID-19, requirement for oxygen therapy, intensive care unit admission, application of invasive ventilation or use of extracorporeal membrane oxygenation, and COVID-19-related deaths between groups were then analyzed. Group C had the highest rates of hospitalization after COVID-19 infection (82.2%) and mortality within 30 days of infection (6.8%). Group B had a 1.3-fold increase in severe COVID-19 outcomes compared to Group A. Group C had 1.8-fold and 1.3-fold increases in severe COVID-19 outcomes compared to Group A and Group B, respectively. Group C also had 2.34 and 3.24 times higher mortality rates within 30 days of COVID-19 infection than Group A and Group B, respectively. In conclusion, patients with pituitary disease who are receiving systemic steroids have poorer outcomes and higher mortality associated with COVID-19. Therefore, thorough COVID-19 infection control is required in these patients.