Miracle-dz/UniFAR-FTUs huggingface dataset:
Wintertime CO2 Emission from Soils of Northeastern Siberia

The emission of CO2 from northeastern Siberian soil was estimated for the period December 1989 to February 1990. Concentrations of air CO2 near the ground and 1 m above the snow cover were measured by an infrared gas analyzer. Fluxes of CO2 across the snow cover were calculated from the differences of these two values and the predetermined CO2 transfer coefficients at various flux rates through a layer of snow. Temperature and moisture content of the soil profiles were also observed simultaneously. The average transfer coefficient of CO2 for packed snow measured in the winter of 1989/90 was about 0.28 cm2*s-1. This value was used to estimate the average CO2 flux from soil: 0.26 g Cm-2.day-1 in December 1989, 0.13 g Cm-2.day-1 in January 1990 and 0.07 g C*m-2*day-1 in February 1990. Thus a minimal total of about 13.8 g Cm-2 had been released from the tundra soil during the 90 days from December 1989 to February 1990. Using the study by Kelley et al. (1968) and assuming that the minimal CO2 transfer coefficient is also applicable for the entire tundra and Northern Taiga zones between September and June, the total emission from this region would amount to 0.23 X loL5 g of carbon. The main source of this CO2 probably originated from microbial oxidation of soil organic matter. This assertion is supported by the existence of a relatively warm layer in the frozen soil at 40-120 cm depth. This warm layer was about 10-40°C higher than the ambient air, or about 5-10°C higher than the soil surface, and its moisture content was also higher than the surrounding layers.
Overcompleteness of coherent frames for unimodular amenable groups

This paper concerns the overcompleteness of coherent frames for amenable unimodular groups. It is shown that for coherent frames associated with an integrable vector a set of positive Beurling density can be removed yet still leave a frame. The obtained results extend various theorems of [J. Fourier Anal. Appl. , 12(3):307-344, 2006] to frames with non-Abelian index sets.
ISSC: Interactive Semantic Shared Control for Haptic Teleoperation

We propose a novel interactive semantic shared control framework that exploits an active high-level communication loop between the human operator and the robot for time-efficient teleoperation. In shared control approaches, accurate prediction of the operator’s intention is crucial to enable the robot to provide meaningful assistance. Incorrect intention prediction (e.g., target objects to be interacted with) increases the task duration due to conflicts between human behaviors and robot guidance. Unlike existing methods, our approach not only passively observes and predicts the human operator’s input in the haptic control loop, but also actively communicates with the human operator in an additional semantic loop in the form of a speech user interface to optimize the effectiveness of assistance. We evaluate our ISSC framework for a pegin-hole teleoperation task. The experimental results show that the proposed framework significantly outperforms teleoperation without assistance and conventional shared control paradigms regarding task execution efficiency and user control quality, and reduces task completion time by up to 26.68% and 39.00%, respectively.
Policymakers’ Uncertainty

Uncertainty is a ubiquitous concern emphasized by policy-makers. We study how uncertainty affects decision-making by the Federal Open Market Committee (FOMC). We distinguish between the notion of the Fed-driven uncertainty that is induced by the policy choice and the classic notion of uncertainty that emanates from within the economy and which the Fed takes as given. A simple theoretical framework illustrates how the Fed-driven uncertainty introduces a wedge between the standard Taylor-type rule and the optimal decision. Using internal Fed deliberations, we provide the first quantification of the types of uncertainty that the Fed perceives and their effects on the policy stance. The FOMC members’ uncertainty about inflation strongly predicts a more hawkish policy stance that is not explained either by the internal Fed’s forecasts or by the measures of public uncertainty. In contrast, policymakers’ uncertainty about growth has no impact on policy decisions beyond these standard controls. Consistent with a model of inflation scares, policymakers’ inflation uncertainty reflects their constant worries about losing the nominal anchor. We argue that the desire to maintain inflation credibility is an important driver of the FOMC’s decisions and provide evidence from the FOMC transcripts consistent with this channel.
Calibrated Human-Robot Teaching: What People Do When Teaching Norms to Robots*

Robots deployed in social communities must act according to the communities’ social and moral norms. To acquire the large number of nuanced norms, robots can rely on human teaching. While humans tend to naturally use more than one teaching method when training a novice, current human-in-the-loop teaching frameworks have typically relied on single teaching methods (e.g., instruction or reward). To gain insight into how humans would teach robots to master social and moral norms, we present a novel paradigm in which participants interactively teach a simulated robot to behave appropriately in a healthcare setting, choosing to either instruct the robot or evaluate its proposed actions. We demonstrate that 89.5% of human teachers naturally use both teaching methods. Importantly, they adapt their teaching method as they observe the robot’s task performance, responding dynamically to the task’s difficulty, the robot’s most recent action, and the accumulated evidence of the robot’s learning progress.
Benchmark for Personalized Federated Learning

Federated learning is a distributed machine learning approach that allows a single server to collaboratively build machine learning models with multiple clients without sharing datasets. Since data distributions may differ across clients, data heterogeneity is a challenging issue in federated learning. To address this issue, numerous federated learning methods have been proposed to build personalized models for clients, referred to as personalized federated learning. Nevertheless, no studies comprehensively investigate the performance of personalized federated learning methods in various experimental settings such as datasets and client settings. Therefore, in this article, we aim to benchmark the performance of existing personalized federated learning methods in various settings. We first survey the experimental settings in existing studies. We then benchmark the performance of existing methods through comprehensive experiments to reveal their characteristics in computer vision and natural language processing tasks which are the most popular tasks based on our survey. Our experimental study shows that (i) large data heterogeneity often leads to highly accurate predictions and (ii) standard federated learning methods (e.g. FedAvg) with fine-tuning often outperform personalized federated learning methods.
Effects of air pollution on morphological and anatomical characteristics of Pinus Eldarica Wood

Air pollution, including automobile exhaust pollution, can affect anatomical and morphological characteristics of wood. In order to evaluate this subject, the Pinus eldarica trees of Chitgar Park in Tehran, which extends from a crowded highway in the south (polluted site) to the semi polluted midsection and to Alborz Mountain in the north (unpolluted site) were sampled with an increment borer and cores were collected. After cross dating, the tree rings of the last five years were separated from the rest of the core. Anatomical characteristics of the cross sections, including the transition between early wood and latewood, the tangential thickness of the last-formed latewood tracheids, the frequency of rays and resin ducts and the morphological characteristics of tracheids in rings formed in the same year were studied. The results indicated that the ring widths of P. eldarica in the three zones are not significantly different. Rays and false rings were more frequent in the polluted and semi polluted sites than in the reference area, and wall thickness was significantly different in some years. Other morphological properties did not differ significantly except for tracheid diameted. In conclusion air pollution does not alter P. eldarica ring width significantly but changes some anatomical and morphological properties of its wood. Therefore trees growing on polluted sites are not suitable for Dendrochronological studies.
A comparative assessment of meteorological drought in the Tafna basin, Northwestern Algeria

: The drought ranked first in terms the natural hazard characteristics and impacts followed by tropical cyclones, regional floods, earthquakes, and volcanoes. Drought monitoring is an important aspect of drought risk management and the assessment of drought is usually done through using various drought indices. The western region in Algeria is the most affected by the drought since the middle of the 70s.The current research focuses on the analysis and comparison of four meteorological drought indices (standardized precipitation index – SPI , percent of normal index – PN , decile index – DI , and rainfall anomaly index – RAI ) in the Tafna basin for different time scales (annual, seasonal, and monthly) during 1979–2011. The results showed that the SPI and DI have similar frequencies for dry and wet categories. The RAI and PN were able to detect more drought categories. Meanwhile, all indices have strong positive correlations between each other, especially with Spearman correlation tests (0.99; 1.0), the meteorological drought indices almost showed consistent and similar results in the study area. It was determined in 1982 as the driest year and 2008 as the wettest year in the period of the study. The analysis of the trend was based on the test of Mann– Kendall (MK), a positive trend of the indices were detected on a monthly scale, this increasing of indices trend represent the increasing of the wet categories which explains the increasing trend of the rainfall in the last 2000s. These results overview of the understanding of drought trends in the region is crucial for making strategies and assist in decision making for water resources management and reducing vulnerability to drought.
Regeneration of the molluscan fauna of a small lowland river after dredging

Dredging of the river to remove macrophytic vegetation and bottom sediment is a common anthropogenic disturbance in the river ecosystem that directly and indirectly influences benthic invertebrates, including molluscs. We assessed the effect of dredging on malacofauna during the year following such an intervention on the river Krąpiel (NW Poland) and describe the process of gradual recolonization of the dredged parts by gastropods and bivalves as well as its possible sources. Molluscs were adversely impacted immediately after the dredging: relative abundance of rheophilic and species typical of stagnant water or slow-flowing rivers changed and the overall species richness decreased. The fauna recovered to its pre-management state within a year. The BACI analysis showed no long-term effect of the intervention on the total abundance and diversity of the molluscs. As many as 17 mollusc species, among them Unio crassus, were present in the river before and after the dredging.
Impact of green HRM practices on bank employee service behaviors

This study aims to examine the influence of green human resource management (HRM) practices on the service behaviors of bank employees operating in the banking sector of Bangladesh. The study endeavors to offer valuable insights into the effectiveness of green HRM practices in enhancing practices and employee service behaviors in the banking sector. The results indicate that green human resource management practices have a beneficial influence on employee service behaviors by green knowledge sharing, green training and development, green performance appraisal, green reward system. This study also emphasizes how green HRM practices affect banks in terms of organizational sustainability, employee motivation, talent acquisition and retention, and the necessity of ongoing evaluation and improvement. Moreover, the current study used convenience sampling techniques to collect data from 258 workers of several commercial banks in Bangladesh using a self-reported questionnaire that had been modified from other studies. 95% confidence interval was used to accept the hypotheses during regression analysis. The results show that each and every hypothesis is supported, whereas hypothesis tests were analyzed using SPSS version 26.0. The results show that employees’ knowledge sharing tendency, training facility, performance appraisal and reward system have a significant and positive impact on bank employees’ service behavior. This study may contribute to the growing subject of sustainable HRM and offers useful advice for banks looking to include environmental sustainability into their HRM plans to spur progress and enhance service.
Examining The Relationship Between Economic, Demographic, Legal And Institutional Variables Towards Tax Evasion : A Case Study In West Kalimantan

Tax evasion, one of the most common crimes in the world. There are so many cases of tax evasion that are not known by the public, in fact there are many cases of tax evasion that are closed and only revealed a few years later. This is also happened in Indonesia. Without exception, Indonesia is also one of the countries with the most tax evasion practices. To examine which factor, affect the tax evasion practice the most, this problem needs to be studied further. This research aims to examine and reveals how the economic variable, demographic variable, and legal and institutional variable affect tax evasion practice with West Kalimantan, Indonesia as the studied area. This research uses the multiple regression analysis as its research method. Questionnaire was used for the data collection where the questionnaire succeeded to obtain 120 respondents as research population, then 100 sample gained after screening process . The result of this research is that the economic variable and the legal and institutional variable has a positive effect on tax evasion practice and the demographic variable has a negative effect on tax evasion practice.
Bisphenol AF Induces Prostatic Dorsal Lobe Hyperplasia in Rats through Activation of the NF-κB Signaling Pathway

Bisphenol AF (BPAF) represents a common environmental estrogenic compound renowned for its capacity to induce endocrine disruptions. Notably, BPAF exhibits an enhanced binding affinity to estrogen receptors, which may have more potent estrogenic activity compared with its precursor bisphenol A (BPA). Notwithstanding, the existing studies on BPAF-induced prostate toxicity remain limited, with related toxicological research residing in the preliminary stage. Our previous studies have confirmed the role of BPAF in the induction of ventral prostatic hyperplasia, but its role in the dorsal lobe is not clear. In this study, BPAF (10, 90 μg/kg) and the inhibitor of nuclear transcription factor-κB (NF-κB), pyrrolidinedithiocarbamate (PDTC, 100 mg/kg), were administered intragastrically in rats for four weeks. Through comprehensive anatomical and pathological observations, as well as the assessment of PCNA over-expression, we asserted that BPAF at lower doses may foster dorsal prostatic hyperplasia in rats. The results of IHC and ELISA indicated that BPAF induced hyperplastic responses in the dorsal lobe of the prostate by interfering with a series of biomarkers in NF-κB signaling pathways, containing NF-κB p65, COX-2, TNF-α, and EGFR. These findings confirm the toxic effect of BPAF on prostate health and emphasize the potential corresponding mechanisms.
Adolescent Perspectives in Eastern Indonesia on Social Motivation in Alcohol Consumption: A Qualitative Study

Introduction: Alcohol consumption among teenagers is a significant public health issue on a global scale. However, the levels of alcohol consumption among teenagers and their understanding of its impact on human health are still relatively poorly documented in various regions of Indonesia, especially among teenagers in the eastern regions of Indonesia. Objective: This research aims to comprehend the social motivations driving alcohol consumption among teenagers in Eastern Indonesia, identify contributing motivations, and investigate their implications in clinical nursing practice. Method: This study employs a qualitative approach with a descriptive design. The study population consists of teenagers aged 16–17 in the eastern region of Indonesia. Sampling was conducted using the snowball sampling method based on predefined inclusion criteria. The data were gathered through in-depth interviews, recorded using audio recording devices, and supplemented with field notes. Data analysis was carried out using the Colaizzi method, continuing until data saturation was achieved. Result: The research findings reveal a variety of perspectives among East Indonesian teenagers regarding alcohol consumption, including cultural normalization of drinking and youth parties, factors associated with adolescent alcohol consumption, conflicting feelings about alcohol consumption, and alcohol consumption as a symbol of masculinity. Conclusion: This study underscores the importance of a more holistic approach to understanding and addressing alcohol consumption issues among teenagers in Eastern Indonesia. Clinical nursing practice implications involve intensifying health education efforts for adolescents and developing more effective interventions to reduce the risks associated with alcohol consumption among teenagers, particularly in Eastern Indonesia
Optimal collective reputation

ABSTRACT Collective reputation, such as watches “made in Switzerland”, affects the whole industry all over the world. This article highlights the relationship between competition and collective reputation. First, collective quality level depends on firms objectives. Second, the collectively determined quality of profit incentive firms reaches social optimal level. Finally, quality restriction is more efficient than subsidies to promote collective quality. The policy implication is that antitrust policy should not care about jointly determined quality for profit incentive firms. Further, cooperative innovation is encouraged to promote the collective reputation or cooperative innovation promotes the values of patents by collective reputation.
Effectiveness and impact of community-based health insurance on health service utilization in northwest Ethiopia: a quasi-experimental evaluation

Background Addressing the health challenges of lower socioeconomic groups in Ethiopia is still a huge problem. In that regard, the government piloted the community-based health insurance (CBHI) in 2011 in a few districts and subsequently scaled up. However, the effectiveness of the program on the utilization of health services and its impact was not well explored. Thus, we aimed to evaluate the effectiveness of CBHI toward health services’ utilization and its impact in northwest Ethiopia. Methods A quasi-experimental matched comparison group evaluation design with sequential explanatory mixed methods was employed. To evaluate the CBHI program, the effectiveness and impact dimensions from the Organization for Economic Cooperation and Development framework were used. A multistage sampling technique was used to select a total of 332 households enrolled in the CBHI program; 341 comparison households who did not enroll in the program were also randomly selected. A structured interviewer-administrated questionnaire was used to evaluate the effectiveness and impact of CBHI on health service utilization. The Propensity score matching model was employed for the estimation of the effect of the CBHI program on health service utilization. Challenges for program achievement toward health service utilization were explained through qualitative data and these were then analyzed thematically. Results The evaluation showed 1.3 visits per capita per year of health service utilization among CBHI members. Households enrolled in CBHI increased health service utilization by 6.9 percentage points (ATT = 0.069; 95% CI: 0.034, 0.114). There was an improvement in health service utilization after the introduction of CBHI, however, there are challenges: (i) shortage of human resources, (ii) out-of-stock of drugs and medical supplies, and (iii) long waiting times for service and reimbursement claims. These issues limit the success of the program toward health service utilization. Conclusion The CBHI program contributed to health service utilization improvement among CBHI members. However, the utilization rate of health services among CBHI members is still less than the target stated for the program and also the WHO recommendation. Therefore, the findings of this evaluation can be used by program implementers, policy makers, and other stakeholders to overcome the identified challenges and to increase the success of the program.
An explainable multi-class decision support framework to predict COVID-19 prognosis utilizing biomarkers

Abstract Millions of lives have been impacted by COVID-19, which has spread rapidly. Several vaccines have been developed to curb the severe prognosis induced by the virus. However, a part of the population (elderly and patients with coexisting conditions) is still at risk. It is crucial to identify these patients early since appropriate treatments can be provided to them to prevent the onset of severe symptoms such as breathlessness and hypoxia. Hence, this study utilizes machine learning and explainable artificial intelligence (XAI) to predict COVID-19 severity using biochemical, haematological and inflammatory markers. The patients are grouped into three classes: mild, moderate and severe. Four nature-inspired techniques have been utilized to select the best markers. The final stacked model obtained a maximum accuracy of 84. Demystifying the models has been done using four XAI techniques, including Shapley additive values (SHAP) and Local Interpretable Model-Agnostic Explanations (LIME). Lactate dehydrogenase (LDH), albumin, D-Dimer, c-reactive protein (CRP) and lymphocytes were considered important, according to them. The classifiers can be utilized as a prognostic decision support framework to aid the medical personnel in classifying COVID-19 patients.
Determination of the Boundaries of the Non-Magnetic Phase of the Dual-Phase Magnetic Material of the Starter-Generator Rotor

Dual-phase magnetic material - a magnetic material in which, by processing, localized non-magnetic areas can be obtained to control the direction of the magnetic flux. Such properties can significantly improve the output characteristics of a number of topologies of electrical machines, as well as neutralize a number of the main disadvantages inherent in traditional designs of electrical machines. This paper presents a numerical study of the strength characteristics of the rotor of an electric starter-generator with permanent magnets with a dual-phase magnetic material. The optimal boundaries of racks for processing in the non-magnetic phase are determined.