Miracle-dz/UniFAR-FTUs huggingface dataset:
Public investment criteria under optimal nonlinear income taxation without commitment

It is well known that the production efficiency theorem fails under the optimal nonlinear income tax model with endogenous wages. Thus, production efficiency is thought to hold when wages are exogenous. However, we show that the desirability of production efficiency depends on the credibility of the government’s commitment. If the government cannot commit to its tax policies and the types of taxpayers are separated completely, then the production efficiency theorem should be violated in an optimal solution, and this result holds even if wages are exogenous.
The Impact of an Epidemic: Experimental Evidence on Preference Stability from Wuhan

We examine how the outbreak of the COVID-19 virus in the Hubei province of China impacted pro-social behavior and attitudes toward risk and uncertainty. The study repeatedly applies a panel of financially incentivized individual and strategic decision tasks via the WeChat social media platform to a population of preregistered Wuhan University students. We find that the initial outbreak coupled with the lock-down of Wuhan City led to an uptick in altruism, trust, and ambiguity aversion and a downtick in risk aversion. Over the remaining samples, we observed that all measurements return to baseline levels except for risk aversion.
The Influence of Policy Implementation of Integrated Activity Monitoring Information System (SIMKET) Apllication Through the Characteristic of Information On Organizational Performance in the Central Bureau of Statistic of South Sumatera

The purpose of this study was to determined the influence of policy implementation of integrated activity monitoring information system (SIMKET) application through the characteristic of information on organizational performance in the central bureau of statistics of South Sumatera. The population was respondents with the criteria of civil servants in the central bureau of statistics of the South Sumatera Province. The sampling method used was proportionate stratified random sampling. The method used in analyzing data is Structural Equation Modeling (SEM). The result of the study found that the implementation of integrated activities monitoring information system (SIMKET) application had an effect on the characteristic of information, characteristic of information had an effect on the organizational performance and the implementation of integrated activities monitoring information system (SIMKET) application had an unsignificant effect on organizational performance.
Contributions of polyelectrolyte complexes and ionic bonding to performance of barrier films for packaging: A review

Barrier films that are used on packages play an important role, especially in the protection of food products. Research is being carried out at an accelerating pace to replace petroleum-based plastic films, which do not biodegrade and are difficult to recycle. This review article considers publications related to the use of polyelectrolyte complexes (PECs) in barrier films as a strategy to decrease the permeation of oxygen and other substances into and out from packages. Research progress has been achieved in using combinations of positively and negatively charged polymers, sometimes together with platy mineral particles, as a way to restrict diffusion through packaging materials. In principle, the ionic bonds within PECs contribute to a relatively high cohesive energy density within such a barrier film, which can resist diffusion of various gases and greasy substances. Resistance to water vapor, as well as aqueous substances, represent important challenges for barrier concepts that depend on ionic bond contributions. Factors affecting barrier performance of PEC-based films are discussed in light of research findings.
On Estimating Personality Traits of US Supreme Court Justices

Psychological scholarship on personality is uniting with political science to redefine existing theories. This is clearly the case with research on judicial behavior and the US Supreme Court. But if this new approach is to survive and thrive, it must employ measures equal to the task. We show that Supreme Court Individual Personality Estimates, which seek to estimate justices’ personalities by examining their concurring opinions, suffer from a number of important methodological deficits that critically limit their usefulness. We briefly discuss what kinds of improved personality measures scholars should use instead and offer an improved set of estimates for one trait with an application that demonstrates our cautionary tale.
SPECIES IDENTIFICATION FOR AQUATIC BIOMONITORING USING DEEP RESIDUAL CNN AND TRANSFER LEARNING

Aquatic insects and other benthic macroinvertebrates are mostly used as bioindicators of the ecological status of freshwaters. However, an expensive and time-consuming process of species identification represents one of the key obstacles for reliable biomonitoring of aquatic ecosystems. In this paper, we proposed a deep learning (DL) based method for species identification that we evaluated on several available public datasets (FIN-Benthic, STONEFLY9, and EPT29) along with our Chironomidae dataset (CHIRO10). The proposed method relies on three DL techniques used to improve robustness when training is done on a relatively small dataset: transfer learning, data augmentation, and feature dropout. We applied transfer learning by employing ResNet-50 deep convolutional neural network (CNN) pretrained on ImageNet 2012 dataset. The results show significant improvement compared to original contributions and confirms that there is a considerable gain when there are multiple images per specimen.
Improved robust H∞ stability analysis and stabilization of uncertain systems with stochastic input time‐varying delays

This article focus on the robust H∞ stability analysis and controller design for a class of uncertain and disturbed continuous‐time systems with input time‐varying delays characterized by stochastic Bernoulli distributions. First, robust H∞ stability conditions for linear continuous systems with interval input time‐varying delays is investigated. A delay‐distribution‐approach is considered to reduce the conservatism of the stability conditions from the convenient selection of a Lyapunov–Krasovskii functional (LKF), which considers both the lower and upper bounds of the stochastic time‐varying delay to derive new delay‐dependent H∞ stability conditions in terms of linear matrix inequalities (LMIs). Then, derived from the proposed stability conditions, LMI‐based conditions for the design of stabilizing robust H∞ delayed state feedback controller are proposed. Finally, five numerical examples are considered to show the effectiveness of the proposed stability analysis and controller design conditions, in comparison to previous related results.
The Differences in The Effectiveness of Indonesian Bay Leaves and Cucumbers in Elderly with Hypertension

During the last 10 years, it is estimated that there has been a significant increase in hypertension patients, which has contributed to the death of approximately 8 million people annually worldwide. The purpose of this study was to analyze the differences in the effectiveness of Indonesian bay leaves solution and cucumbers in elderly with hypertension at Puskesmas Moncobalang, Gowa Regency in 2019. The research method was quantitative with Quasi Experimental design and NonEquivalent Control Group Design. The results of the Wilcoxon statistical test on Indonesian bay leaves solution with a value of Pvalue 0,005 <0,05, this means that Ho has been rejected and Ha has been accepted. The average pretest score of 3,80 is smaller than the average posttest score of 1,80. Thus, there is the effectiveness of boiled Indonesian bay leaves solution in elderly with hypertension. Likewise, the Wilcoxon statistical test results on cucumbers showed a value of Pvalue 0,004 <0,05, this means that Ho has been rejected and Ha has been accepted. The means of blood pressure pretest is 3.80 which is smaller than the posttest average value of 2,50. This research inferred that the juiced cucumber is effective in treating elderly with hypertension. In conclusion, there is no difference in effectiveness between boiled Indonesian bay leaves solution and juiced cucumber in treating elderly with hypertension at Moncobalang Health Center, Gowa Regency.
A Seroprevalence Study for HBV in Pregnant Women in Greece: High Risk Migrant Groups and Opportunities for Intervention

Background: Perinatal transmission of HBV leads to chronic infection in up to 90% of neonates. Focused prenatal screening and appropriate treatment of pregnant women and neonates is necessary for the elimination of hepatitis B, as was stated in the 2017 WHO Action Plan for HBV. Information on seroprevalence of HBV in Greece, especially in pregnant women, is scarce and rather outdated. Seroprevalence data specifically for high-risk groups, such as immigrants, is necessary for proper public health planning and elimination of vertical transmission and this study will struggle to fill the gap that exists in Greece. Methods: HBsAg status of pregnant women delivering during 2017 in Crete was studied. Seroprevalence was estimated for the whole population and each ethnic group separately. Results: The mean age of the participants was 30.38 (±6) years. Their origin was Greek (76.76 %), Albanian (10.18%), Bulgarian (3.79%), Roma population (2.44%), Russia and Former Republics of Russia (2.06%), Romanian (1.95%), Central Europe (0.70%) refugees from Syria, Morocco, Egypt (0.55%), and East Asian (0.43%). The HBsAg (+) seroprevalence was 1.5%. The seroprevalence of Greeks was 0.5%, while Albanians, Bulgarians, Romanians and Roma had 4.3%, 5.7%, 2.8%, and 11.1% respectively (p<0.001). Conclusions: Defining specific at-risk groups in each country is fundamental, since MTCT is the principal mode of transmission in high prevalence settings. Our study revealed high seroprevalence in certain migrant groups and Roma women. This information is essential for proper planning of perinatal care in Greece, especially taking into account that these underprivileged groups often lack quality health care.
Exploring the role of peer-assisted learning for professional preparation in recreation

ABSTRACT In the recreation sector there is concern for ensuring that students and practitioners have adequate knowledge and skills to contribute to its growth and sustainability. While other researchers have identified the importance of personal attributes (i.e., ‘soft’ skills) for entry-level practitioners, there has been limited exploration of how peer assisted learning might contribute to preparing recreation students for their future professional practice. Recreation students from three different courses who were involved in a leisure education-based peer learning project participated in the study. Three themes were constructed to reflect students’ perceptions: (1) benefits of peer learning for preparing for future practice, 2) practice for real life, and (3) factors impacting abilities to facilitate peer learning. The results are discussed in relation to the role of peer learning or mentoring in cultivating personal and professional growth and development in and for the recreation sector.
A METHOD FOR SYNTHESIZING THERMAL IMAGES USING GAN MULTI-LAYERED APPROACH

Abstract. The active development of neural network technologies and optoelectronic systems has led to the introduction of computer vision technologies in various fields of science and technology. Deep learning made it possible to solve complex problems that a person had not been able to solve before. The use of multi-spectral optical systems has significantly expanded the field of application of video systems. Tasks such as image recognition, object re-identification, video surveillance require high accuracy, speed and reliability. These qualities are provided by algorithms based on deep convolutional neural networks. However, they require to have large databases of multi-spectral images of various objects to achieve state-of-the-art results. While large and various databases of color images of different objects are widely available in public domain, then similar databases of thermal images are either not available, or they represent a small number of types of objects. The quality of three-dimensional modeling for the thermal imaging spectral range remains at an insufficient level for solving a number of important tasks, which require high precision and reliability. The realistic synthesis of thermal images is especially important due to the complexity and high cost of obtaining real data. This paper is focused on the development of a method for synthesizing thermal imaging images based on generative adversarial neural networks. We developed an algorithm for a multi-spectral image-to-image translation. We have changed to the original GAN architecture and converted the loss function. We presented a new learning approach. For this, we prepared a special training dataset including about 2000 image tensors. The evaluation of the results obtained showed that the proposed method can be used to expand the available databases of thermal images.
The application of ceramic membranes for treating effluent water from closed-circuit fish farming

Abstract The aim of the study was to analyze and assess the possibility of using a two-stage filtration system with ceramic membranes: a 3-tube module with 1.0 kDa cut-off (1st stage) and a one-tube module with 0.45 kDa cut-off (2nd stage) for treating effluent water from a juvenile African catfish aquaculture. The study revealed that during the 1st filtration stage of the effluent water, the highest degrees of retention were obtained with respect to: suspended solids SS (rejection coefficient RI=100%), turbidity (RI=99.40%), total iron (RI=89.20%), BOD5 (RI=76.0%), nitrite nitrogen (RI=62.30%), and CODCr (RI=41.74%). The 2nd filtration stage resulted in a lower reduction degree of the tested indicators in comparison to the 1st filtration stage. At the 2nd stage, the highest values of the rejection coefficient were noted in for the total iron content (RIV=100%), CODCr (RIV=59.52%; RV=64.28%, RVI=63.49%) and turbidity (RIV and RV = 45.0%, RVI=50.0%). The obtained results indicate that ceramic membranes (with 1.0 and 0.45 kDa cut-offs) may be used in recirculation aquaculture systems as one of the stages of effluent water treatment.
Objective Assessment of Porcine Voice Acoustics for Laryngeal Surgical Modeling

Pigs have become important animal models in voice research. Several objective parameters exist to characterize the pig voice, but it is not clear which of them are sensitive to the impaired voice quality after laryngeal injury or surgery. In order to conduct meaningful voice research in pigs, it is critical to have standard functional voice outcome measures that can distinguish between normal and impaired voices. For this reason, we investigated 17 acoustic parameters before and early after surgery in three Yucatan mini pigs. Four parameters showed consistent changes between pre- and post-surgery recordings, mostly related to decreased spectral energy in higher frequencies after surgery. We recommend two of these, 50% spectral energy quartile (Q50) and Flux, for objective functional voice assessment of pigs undergoing laryngeal surgery. The long-term goal of this process is to enable quantitative voice outcome tracking of laryngeal surgical interventions in porcine models.
Corbiculate Bees (Hymenoptera: Apidae): Exploring the Limits of Morphological Data to Solve a Hard Phylogenetic Problem

Abstract Corbiculate bees comprise a distinctive radiation of animals including many familiar species, such as honey bees and bumble bees. The group exhibits a broad variety of morphologies and behaviors, including solitary, social, and cleptoparasitic lifestyles. Since corbiculate bees play a critical role for the interpretation of eusocial behaviors, understanding their phylogeny is crucial to explain patterns and mechanisms of social evolution. Despite advances to unveil corbiculate relationships employing genomic data, the drivers of conflict between molecular and morphological hypotheses are still not fully understood. Morphological datasets favor a single origin for highly eusocial behaviors (i.e., Apini + Meliponini) whereas molecular datasets favor other scenarios (e.g., Bombini + Meliponini). Explanations for this incongruence have been suggested, including quality, quantity, and source of data or methodological issues. In this work we tackled this problem by generating the most extensive morphological dataset for the corbiculate bee species by exploring characters from all body regions, including external and internal adult skeletal anatomy. We produced a matrix with 289 characters for 53 taxa of Apidae, including 24 corbiculate bees. We explored different analyses and optimality criteria including extended implied weights parsimony and two partitioning schemes for Bayesian inferences. We contrasted hypotheses with Bayesian topological tests and conducted analyses to investigate if characters were prone to concerted convergence. Our results are congruent with the conclusions of previous studies based on morphology, recovering Apini sister to Meliponini and both of them together sister to Bombini. Finally, we provide our interpretations on the corbiculate controversy and provide a conciliatory scenario about this issue.
Cryogenic Materials Conference in 2014 , ICEC 25 – ICMC 2014 Helium contamination through polymeric walls

The concentration of impurities in helium gas is an important parameter for a recovery and liquefaction plant. A low level of impurities is necessary to maintain an optimum liquefaction rate in any kind of liquefier. The main origin of the impurities is the air contamination that enters into the helium mainstream at some point in the recovery cycle. In this work we have: i) identified the main sources for impurities in an experimental helium recovery plant, ii) quantified the contamination rate and iii) proposed a mitigation strategy. An analysis of the He impurities composition reveals a nitrogen/oxygen ratio different to the one existing in air. This observation is in accordance with the permeability values for nitrogen and oxygen through the polymer materials used in the plant. Experimental on line measurements for oxygen content in the He mainstream with sensitivity below 1 ppm, have been performed after recirculation through metal and polymeric pipelines, respectively, to validate our hypothesis. In addition, the dependence of the impurities concentration with the He retention time in the recovery gas bag has been evaluated. Finally some operational recommendations are given for practical applications. © 2014 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the organizing committee of ICEC 25-ICMC 2014.
A Two-Stage Approach to the Estimation of High-Resolution Soil Organic Carbon Storage with Good Extension Capability

Soil organic carbon storage (SOCS) estimation is a crucial branch of the atmospheric–vegetation–soil carbon cycle study under the background of global climate change. SOCS research has increased worldwide. The objective of this study is to develop a two-stage approach with good extension capability to estimate SOCS. In the first stage, an artificial neural network (ANN) model is adopted to estimate SOCS based on 255 soil samples with five soil layers (20 cm increments to 100 cm) in Luoding, Guangdong Province, China. This method is compared with three common methods: The soil type method (STM), ordinary kriging (OK), and radial basis function (RBF) interpolation. In the second stage, a linear model is introduced to capture the regional differences and further improve the estimation accuracy of the Luoding-based ANN model when extending it to Xinxing, Guangdong Province. This is done after assessing the generalizability of the above four methods with 120 soil samples from Xinxing. The results for the first stage show that the ANN model has much better estimation accuracy than STM, OK, and RBF, with the average root mean square error (RMSE) of the five soil layers decreasing by 0.62–0.90 kg·m−2, R2 increasing from 0.54 to 0.65, and the mean absolute error decreasing from 0.32 to 0.42. Moreover, the spatial distribution maps produced by the ANN model are more accurate than those of other methods for describing the overall and local SOCS in detail. The results of the second stage indicate that STM, OK, and RBF have poor generalizability (R2 < 0.1), and the R2 value obtained with ANN method is also 43–56% lower for the five soil layers compared with the estimation accuracy achieved in Luoding. However, the R2 of the linear models built with the 20% soil samples from Xinxing are 0.23–0.29 higher for the five soil layers. Thus, the ANN model is an effective method for accurately estimating SOCS on a regional scale with a small number of field samples. The linear model could easily extend the ANN model to outside areas where the ANN model was originally developed with a better level of accuracy.
Fiscal Decentralization, Accountability and Corruption Indication: Evidence from Indonesia

In the Corruption Perception Index 2019, Indonesia ranks 90th among 180 countries (Transparency International, 2020). Indonesia still among the lowest rank in the corruption index. This index shows that corruption is an important issue for Indonesia. Therefore, the study aims at examining the determinants of corruption in Indonesia. This study focuses on two important aspects: fiscal decentralization and accountability. Since the enactment of Law Number 22 of 1999, which was then revised by Law Number 32 of 2004, the local government can manage fiscal. It is expected that local governments can use resources for the improvement of the wealth of the citizens. Further, the local government has a responsibility for using the resources. However, there are cases regarding corruption in local government in Indonesia. This study uses secondary data from local government financial statements to search the corruption indication, level of fiscal decentralization, and accountability. The study’s sample consists of 94 districts/cities on Java during the 2013-2015 period. The dependent variable in this study is an indication of corruption. Furthermore, the study divided corruption into three aspects: regional losses, potential regional losses, and revenue deficiency. The independent variables in this study were fiscal decentralization and accountability. This study uses multiple linear regression models to test the effect of fiscal decentralization and accountability on Indonesia’s corruption indicator. The result of the study shows that fiscal decentralization has a negative impact on corruption indication. The higher degree of fiscal decentralization minimizes the corruption indication in Java island. Meanwhile, fiscal decentralization has a negative effect on regional losses and revenue deficiency. Accountability has no significant on corruption indication. However, accountability has a negative impact on regional losses. In conclusion, both fiscal decentralization and accountability have curb corruption indication in the regional losses aspect.