Miracle-dz/UniFAR-FTUs huggingface dataset:
Self-Efficacy in Disrupted Environments: COVID-19 as a Natural Experiment

In two studies, we investigate whether the link between entrepreneurial self-efficacy and entrepreneurial intentions depends on outcome expectations. In Study 1, we exploit the COVID-19-induced lockdown as a natural experiment in a two-wave student sample. We compare the efficacy–intention link in survey responses submitted right before and right after the lockdown. In Study 2, we conceptually replicate and extend the findings via an online vignette experiment. Together, these studies show that a disruption of stable institutionalized outcome expectations implying increasing risk and uncertainty makes self-efficacy a weaker predictor of entrepreneurial intentions, particularly among those with pessimistic perceptions.
Do Free Food and Beverages Bring People to the Political Meeting? The Survey Experiment of Attendance-Buying

In this article, we explore a phenomenon we call attendance-buying. Specifically, we investigate the case of buying the attendance of voters at political rallies. Politicians and political parties promise voters certain rewards if they come to listen to them at political meetings. Often, these rewards can be food or valuable prizes. We conducted a survey experiment to discover what effect this form of attendance-buying has in Czech municipalities with up to 1000 inhabitants. We focused on small municipalities, where such a strategy can be effective because of the small number of candidates compared to large towns. We found that the effect of promising free food and drinks for attending a rally surprisingly did not manifest. With this finding, we contribute to and extend upon the theme of vote-buying. Our research also has practical implications, as local-level candidates do not have to make these food and drink expenditures because interested citizens will attend political rallies regardless of these offers.
Fine‐scale population fragmentation of a grassland butterfly Plebejus argyrognomon inhabiting agricultural field margin and riverbank in rural landscapes

Evaluating the spatial genetic structure of rare species is important because it could provide information on the degree of habitat fragmentation and effective population size that are necessary for conservation planning. We examined the genetic structure of the grassland butterfly Plebejus argyrognomon that has severely declined in recent decades using single nucleotide polymorphisms obtained by the MIG‐seq method. The study region was in the southern Ina Basin located in central Japan, where P. argyrognomon inhabits grasslands in agricultural field margin as well as in riverbank. We found a positive association between genetic and geographic distances, but the pattern was nonlinear, with little change in genetic distance above 12 km. The genetic differentiation was considerable, as demonstrated by FST and Structure. Moreover, genetic diversity was positively associated with habitat connectivity index, suggesting severe genetic drift in isolated populations. Comparing two habitat types, the genetic structure tended to be similar among agricultural field margin populations while dissimilar among riverbank populations, suggesting frequent gene flow in the former. Coupled with the presence of many habitat patches in agricultural field margin, we consider that agricultural field margin populations in the northern part of the study sites appear valuable to ensure long‐term persistence of the regional P. argyrognomon population.
Contribuições para o uso de células estromais mesenquimais no reparo de feridas cutâneas e no transplante de pele em coelhos

Tese de Doutorado Programa de Pós-Graduação em Medicina Veterinária Universidade Federal de Santa Maria, RS, Brasil CONTRIBUTIONS TO THE USE OF MESENCHYMAL STROMAL CELLS IN SKIN WOUND AND SKIN TRANSPLANTATION REPAIR IN RABBITS AUTHOR: TIAGO LUIS EILERS TREICHEL ADVISOR: DR. NEY LUIS PIPPI Defense Date and Local: Santa Maria, March 14, 2014. This thesis was carried out in three distinct stages; the first being intended to analyzing the cell therapy of skin wound healing in rabbits. The aim of this work was to evaluate the healing potential of the stromal vascular fraction (SVF) and mesenchymal stromal cells (MSC) and to compare which one presents better efficiency and ease of use. For this study we used 15 rabbits divided into three groups. A skin wound of 4 cm was created in all rabbits. The animals of group A did not receive any kind of treatment, whereas in group B they were treated with SVF from adipose tissue, and in group C they were treated with MSC. Histological analysis demonstrated that the healing stages occurred more satisfactorily in the treated groups. In the statistical analysis, the two treated groups showed no significant difference between them, but when compared with the control group there was a significant difference. It was found that both the use of SVF as well as MSC are viable and showed better results that the control, even making the resulting scar of the process aesthetically acceptable. In the second step we determined the degree of oxidative stress in the cultured MSC. The goal of this study was to evaluate the isolation and culture of MSC from adipose tissue samples from three rabbits, processed immediately after harvest and within 12 or 24 hours intervals, keeping them in culture until the ninth pass. The samples from each animal were divided into three new samples, the first of which was processed immediately after harvest, and the others within 12 and 24-hour intervals. The dichlorofluorescein diacetate (DCFH-DA) assay demonstrated that immediate cultures had an increased overall rate of reactive oxygen species (ROS) from the fourth passing, cultured cells after 12 hours, from the third passage and after 24 hours, after the third pass, but with another episode during the ninth passage. The PicoGreen test demonstrated that the immediate cultures obtained a greater release of DNA
Bots vs. humans: how schema congruity, contingency-based interactivity, and sympathy influence consumer perceptions and patronage intentions

Abstract Artificial intelligence (AI) is rapidly reconstructing consumer experiences with brands in recent years. However, there have been the unsettled debates on whether humans react to robots (e.g., chatbots) in the same way as they do to other humans, and how the intrinsic strength of AI (i.e., autonomous processing and synthetization of information) and humans (i.e., emotional intelligence) factor in the human-AI interactions in brand communication settings. Hence, this study investigates the conditions under which a service entity of a brand can optimize their potential. To this end, the current study conceptualizes and operationalizes two dimensions that define chatbots’ capabilities – message contingency (i.e., contingency-based interactivity) and emotional intelligence (i.e., sympathy). Based on two experiments, we found that, regarding the same online customer service of an apparel brand, participants rated the human employee to be more competent and warmer than a chatbot. When a human employee who expresses sympathy to the afflicted customer during the conversation, participants considered the employee to be more competent when he/she also exhibits contingency (vs. no contingency) during the conversation, which in turn, elicited higher patronage intentions among participants.
Links between Faith and Some Strengths of Character: Religious Commitment Manifestations as a Moderators

Religious commitment is a significant factor for the development of strengths of character. Previous studies have confirmed that for religious people, it is not religious affiliation but religious orientation that has influenced positive outcomes. The purpose of the research was to verify whether religious commitment moderates the relationship between faith and strengths of character in a sample of religious students from Poland. A cross-sectional investigation of 393 Polish students was performed with using following measures: the Santa Clara Strength of Religious Faith Questionnaire (SCSORFQ), the Transgression-Related Interpersonal Motivations (TRIM) scale, the Gratitude Questionnaire (GQ-6), the Purpose in Life Test (PIL) test, the Herth Hope Index (HHI), the Brief Religious Coping Scale (Brief RCOPE), and two one-item tools measuring religious practices such as frequency of prayer and attendance at Mass. The obtained results confirmed the moderating role of prayer, mass attendance, and positive religious coping on faith and meaning in life as well as hope. Additionally, positive religious coping moderated the relationships between faith and gratitude as well as between faith and motivation to avoid transgressors. The research has proven that faith without religious commitment is not a strong enough factor to improve strengths of character, and being a believer but not practicing religion is not sufficient to lead a person to finding meaning in life, having enhanced hope, or being able to forgive.
Ubiquinol ameliorates endothelial dysfunction and increases expression of miRNA-34a in a rat model of pulmonary hypertension

Introduction: In this research, we evaluate the effect of intravenously administrated solubilized ubiquinol on 4-week monocrotalin-induced pulmonary hypertension (PH) in rats. Materials and methods: To reproduce the model, some male Wistar rats were subcutaneously injected with alcohol solution of monocrotaline 60 mg/kg and the rest – with alcohol solution (Control). Those with monocrotaline (MCT) were divided into 3 groups. They underwent intravenous administration of 1% ubiquinol solution 30 mg/kg (MCT-Ubiquinol), the vehicle (MCT-Vehicle) and saline (MCT-saline) three times on days 7, 14 and 21, depending on the group. The hemodynamic parameters were measured in anesthetized rats on day 29. Right ventricle hypertrophy, pulmonary arteries reactivity and expression of miRNA-21 and miRNA-34a were estimated after euthanasia. Results and discussion: All MCT-groups demonstrated an increase in right ventricle systolic pressure and hypertrophy in comparison with the control group. An increase in lung weight was shown in MCT-Vehicle and MCT-Saline; however, the MCT-Ubiquinol indicators did not differ from those of the Control. There was an increased vasodilatation response to acetylcholine at concentrations of 1*10-6M and 1*10-5M in MCT-Ubiquinol in contrast to the other two MCT-groups. A significantly lower level of expression of miRNA-34a was observed in MCT-Ubiquinol. Conclusion: Our findings suggest that a triple ubiquinol injection influences pulmonary changes and endothelium-depended vasodilatation, which contributes to pulmonary vascular tone and reactivity. A decrease in miRNA-34a expression in MCT-Ubiquinol group demonstrates the ubiquinol anti-inflammatory properties.
Combinatorial Optimization by Graph Pointer Networks and Hierarchical Reinforcement Learning

In this work, we introduce Graph Pointer Networks (GPNs) trained using reinforcement learning (RL) for tackling the traveling salesman problem (TSP). GPNs build upon Pointer Networks by introducing a graph embedding layer on the input, which captures relationships between nodes. Furthermore, to approximate solutions to constrained combinatorial optimization problems such as the TSP with time windows, we train hierarchical GPNs (HGPNs) using RL, which learns a hierarchical policy to find an optimal city permutation under constraints. Each layer of the hierarchy is designed with a separate reward function, resulting in stable training. Our results demonstrate that GPNs trained on small-scale TSP50/100 problems generalize well to larger-scale TSP500/1000 problems, with shorter tour lengths and faster computational times. We verify that for constrained TSP problems such as the TSP with time windows, the feasible solutions found via hierarchical RL training outperform previous baselines. In the spirit of reproducible research we make our data, models, and code publicly available.
Nonsmooth Optimization over Stiefel Manifold: Riemannian Subgradient Methods

Nonsmooth Riemannian optimization is a still under explored subfield of manifold optimization. In this paper, we study optimization problems over the Stiefel manifold with nonsmooth objective function. This type of problems appears widely in the engineering field. We propose to address these problems with Riemannian subgradient type methods including: Riemannian full, incremental, and stochastic subgradient methods. When the objective function is weakly convex, we show iteration complexity ${\cal O}(\varepsilon^{-4})$ for these algorithms to achieve an $\varepsilon$-small surrogate stationary measure. Moreover, local linear convergence can be achieved for Riemannian full and incremental subgradient methods if the optimization problem further satisfies the sharpness regularity property. The fundamental ingredient for establishing the aforementioned convergence results is that any locally Lipschitz continuous weakly convex function in the Euclidean space admits a Riemannian subgradient inequality uniformly over the Stiefel manifold, which is of independent interest. We then extend our convergence results to a broader class of compact Riemannian manifolds embedded in Euclidean space. Finally, as a demonstration of applications, we discuss the sharpness property for robust subspace recovery and orthogonal dictionary learning and conduct experiments on the two problems to illustrate the performance of our algorithms.
Performance of Polytomous IRT Models With Rating Scale Data: An Investigation Over Sample Size, Instrument Length, and Missing Data

The implementation of polytomous item response theory (IRT) models such as the graded response model (GRM) and the generalized partial credit model (GPCM) to inform instrument design and validation has been increasing across social and educational contexts where rating scales are usually used. The performance of such models has not been fully investigated and compared across conditions with common survey-specific characteristics such as short test length, small sample size, and data missingness. The purpose of the current simulation study is to inform the literature and guide the implementation of GRM and GPCM under these conditions. For item parameter estimations, results suggest a sample size of at least 300 and/or an instrument length of at least five items for both models. The performance of GPCM is stable across instrument lengths while that of GRM improves notably as the instrument length increases. For person parameters, GRM reveals more accurate estimates when the proportion of missing data is small, whereas GPCM is favored in the presence of a large amount of missingness. Further, it is not recommended to compare GRM and GPCM based on test information. Relative model fit indices (AIC, BIC, LL) might not be powerful when the sample size is less than 300 and the length is less than 5. Synthesis of the patterns of the results, as well as recommendations for the implementation of polytomous IRT models, are presented and discussed.
Biculturalism and Self-Esteem: Differential Associations Based on Cultural Domain

Acculturation is multidimensional in that it encompasses both heritage and dominant cultural orientations, and it can take place across multiple domains; therefore, biculturalism, an acculturation strategy involving strong orientations to both heritage and dominant cultures, can also occur for the domains of behaviors and practices, values and beliefs, and cultural identity. The current study is the first to compare the relations between biculturalism and self-esteem across these three cultural domains. Mexican American undergraduate students (N = 219; Mage = 18.82 years, SD = 1.09), who were primarily women (72.15%) and born in the US (81.74%), responded to an in-person survey. We found that biculturalism is differentially associated with personal and collective self-esteem depending on the domain, with stronger associations for bicultural behaviors and weaker associations for bicultural values. Our findings highlight the importance of recognizing the multidimensionality of biculturalism in theory, research, and practice.
The Correlation of Free and Bound Phenolic Acid with Antioxidant Activity Accelerated by Germination Period and Temperature

Abstract Investigation of the free and bound phenolic acid profile in malted hulled rice and the correlation to antioxidant activity were elucidated in this study. Three of free and bound hydroxycinnamic acid (FHCAs and BHCA); p-coumaric acid (CA), ferulic acid (FA), sinapic acid (SA), and one of hydroxybenzoic acid (HBA); vanillic acid (VA) in three rice (Oryza sativa L.) cultivars (with white, red-brown, and dark-purple kernel) were germinated under warm conditions of temperature (30 °C, 35 °C and 40 °C) for 5 days and analyzed for their potential antioxidant activity. The relationship of rice cultivar, malting condition, and antioxidant activity was established by PCA bi-plot analysis. The dark-purple rice malt expressed the highest phenolic acid content and antioxidant activity. The amount of FHCA and FHBA increased with germination time, which was related to the feruloyl esterase activity assayed. Among BHCAs, BCA was the most abundant compound and correlated positively to the antioxidant activity of the bound phenolic extract of the three rice cultivars. The FVA in the dark-purple rice malt was 3 to 4 times higher than that found in white and red-brown grain and led to a strong antioxidant activity of the free form extract. This research suggests that a germination temperature of 30 °C to 35 °C improved the BCA and FVA content in the malted hulled rice cultivars and conveyed a functional property for the finished product.
Histological description of fresh, cooked and frozen cassava flesh

— The aim of this study was to describe the histological feature of cassava flesh at harvest, after cooking and after freezing. A light optical microscopy was used to analyze the relevant aspects of cassava flesh at these statuses. The non-uniform aspect of cooked cassava is associated with the partial dissolution of the middle lamella and the large amount of non-collapsed cells, while the formation of numerous spaces between
Damage Function of a Quasi-Brittle Material, Damage Rate, Acceleration and Jerk during Uniaxial Compression: Model and Application to Analysis of Trabecular Bone Tissue Destruction

A diversity of quasi-brittle materials can be observed in various engineering structures and natural objects (rocks, frozen soil, concrete, ceramics, bones, etc.). In order to predict the condition and safety of these objects, a large number of studies aimed at analyzing the strength of quasi-brittle materials has been conducted and presented in publications. However, at the modeling level, the problem of estimating the rate and acceleration of destruction of a quasi-brittle material under loading remains relevant. The purpose of the study was to substantiate the function of damage to a quasi-brittle material under uniaxial compression, determine the rate, acceleration and jerk of the damage process, and also to apply the results obtained to predicting the destruction of trabecular bone tissue. In accordance with the purpose of the study, the basic concepts of fracture mechanics and standard methods of mathematical modeling were used. The proposed model is based on the application of the previously obtained differentiable damage function without parameters. The results of the study are presented in the form of plots and analytical relations for computing the rate, acceleration and jerk of the damage process. Examples are given. The predicted peak of the combined effect of rate, acceleration and jerk of the damage process are found to be of practical interest as an additional criterion for destruction. The simulation results agree with the experimental data known from the available literature.
Macroprudential capital buffers in heterogeneous banking networks: insights from an ABM with liquidity crises

ABSTRACT We study how the effectiveness of macroprudential capital buffers conditional to the systemic-risk assessment of banks responds to the degree of heterogeneity of the financial system. A multi-agent model is employed to build an artificial economy with households, firms, and banks where occasional liquidity crises emerge. The systemic importance of banks is captured by a score-based mechanism reflecting banks' characteristics in terms of size or interconnectedness. We compare three degrees of heterogeneity in the configuration of financial networks related to different banking concentrations in the loan market. The main findings suggest that: (i) reducing the heterogeneity of the banking network stabilizes the economy by itself; (ii) the identification criteria of systemic-important institutions are affected by the heterogeneity of networks; it is preferable applying systemic capital surcharges to the largest banks under high heterogeneity and targeting those most interconnected under low heterogeneity; (iii) the effectiveness of systemic capital buffers is preserved under high heterogeneity when a common asset holding contagion channel is added. However, simple measures based on risk-weighted assets capital ratios appear to be more effective in low heterogeneous systems. Thus, we argue that prudential regulation should account for the characteristics of the banking networks and tune macroprudential tools accordingly.
SimpleShot: Revisiting Nearest-Neighbor Classification for Few-Shot Learning

Few-shot learners aim to recognize new object classes based on a small number of labeled training examples. To prevent overfitting, state-of-the-art few-shot learners use meta-learning on convolutional-network features and perform classification using a nearest-neighbor classifier. This paper studies the accuracy of nearest-neighbor baselines without meta-learning. Surprisingly, we find simple feature transformations suffice to obtain competitive few-shot learning accuracies. For example, we find that a nearest-neighbor classifier used in combination with mean-subtraction and L2-normalization outperforms prior results in three out of five settings on the miniImageNet dataset.
Preparation of activated carbon from mixed peels of fruits with chemical activation (K2CO3) - application in adsorptive removal of methylene blue from aqueous solution

This work explores the feasibility of mixed peels of fruits as a precursor for the preparation of activated carbon by carbonisation process with chemical activation by K2CO3. The process variables of carbonisation such as carbonisation temperature, time and chemical impregnation ratio on the carbon yield and adsorption capacity were optimised. The morphological structure and textural characteristics of produced activated carbon were examined by scanning electron microscopy. The optimum conditions for preparation of activated carbon were as follows: At carbonisation temperature of 525°C and 75 min of carbonisation time, yield of carbon was 40.83%. In addition, prepared activated carbon was used as adsorbent for the removal of methylene blue from aqueous solutions under various initial concentrations and carbon dosage. The maximum adsorption capacity of activated carbon was identified to be 59.5 mg/g in a 500 ppm solution.