Miracle-dz/UniFAR-FTUs huggingface dataset:
Impacts of Risk Perception and Environmental Regulation on Farmers’ Sustainable Behaviors of Agricultural Green Production in China

In China, the excessive application and improper disposal of chemical inputs have posed a great threat to the agricultural ecological environment and human health. The key to solve this problem is to promote the sustainable behaviors of farmers’ agricultural green production (AGP). Based on the micro-survey data of 652 farmers, this study adopts the binary probit model to investigate the impacts of risk perception and environmental regulation on the sustainable behaviors of farmers’ AGP. Results show that both risk perception and environmental regulation have significant effects on farmers’ willingness to engage in sustainable behaviors. Moreover, environmental regulation can positively adjust risk perception to improve farmers’ willingness to engage in sustainable behaviors. In terms of the two-dimensional variables, economic risks create the greatest negative impacts, and their marginal effect is 7.3%, while voluntary regulation creates the strongest positive impacts, and its marginal effect is 14.1%. However, both constrained and voluntary regulation have an enhanced moderating effect, where the effects of voluntary regulation are more remarkable. This is mainly because the environmental regulation policy signed by the government and farmers through the letter of commitment can inspire farmers to continue to implement green agricultural production from the deep heart. Therefore, government policies should constantly reduce farmers’ risk perception in terms of economic input, and adopt restrictive behaviors measures, such as regulatory punishment and voluntary contract, to promote their sustainable behaviors of AGP to the maximum extent.
COVID-19 Pandemic: Evidence from JII Stocks

The purpose of this study is to analyze the reaction of the Jakarta Islamic Index (JII) stocks to the announcement of COVID-19 as a national disaster in Indonesia. The sample used is 30 of JII stocks and an event study methodology applied. The results of the study found that there were in the second and the fourth day after the event date having significant on abnormal return at 1 % level. Additionally, there was the pretty strong impact of the event on Trading Volume Activity and Bid-Ask Spread of JII stocks. In addition, based on the regression test indicated that the event has a significant effect on JII stocks, so that the result remain robust. It indicated that the announcement of COVID-19 as a national disaster in Indonesia has affected market stock.
JPET #94656. Page 1 Neuronal nitric oxide synthase (nNOS) inhibition facilitates adrenergic neurotransmission in rat mesenteric resistance arteries

The effects of non-selective nitric oxide synthesis (NOS) inhibitors (L-NAME and L-NNA) and specific neuronal NOS (nNOS) inhibitor (L-VNIO) on adrenergic nerve-mediated vasoconstriction were studied in rat perfused mesenteric vascular beds without endothelium. Perfusion of L-NAME, L-NNA or L-VNIO markedly augmented vasoconstrictor responses to periarterial nerve stimulation (PNS: 2-8 Hz) without affecting vasoconstriction induced by exogenously injected norepinephrine (NE). Addition of L-arginine, a precursor for the synthesis of NO, reversed the augmentation of the PNS-response by L-NAME. The PNS (8 Hz)-evoked NE release in the perfusate was increased by L-NAME perfusion. In preparations treated with capsaicin (a depletor of calcitonin gene-related peptide (CGRP)-containing nerves), L-NAME did not augment vasoconstrictor responses to PNS or NE injection. Combined perfusion of CGRP(8-37) (a CGRP receptor antagonist) and L-NAME induced additive augmentation of the vasoconstrictor response to PNS, but did not affect the response to NE injection. In preparations with active tone produced by methoxamine and in the presence of guanethidine, L-NAME perfusion did not affect the vasodilator response induced by PNS. Immunostaining of the mesenteric artery showed the presence of nNOS-like immunopositive nerve fibers, which were absent in arteries pretreated with capsaicin. These findings suggest that NO, which is released from perivascular capsaicin-sensitive nerves, presynaptically inhibits neurogenic NE release to modulate adrenergic neurotransmission. This article has not been copyedited and formatted. The final version may differ from this version. JPET Fast Forward. Published on October 19, 2005 as DOI: 10.1124/jpet.105. 094656 at A PE T Jornals on Jne 9, 2022 jpet.asjournals. org D ow nladed from
MiR-222 inhibition alleviates Staphylococcal Enterotoxin B-induced inflammatory acute lung injury by targeting Foxo3

Acute lung injury (ALI) is a common acute and severe disease in clinical practice. Staphylococcal Enterotoxin B (SEB) is a superantigen that can cause inflammatory ALI. MiR-222 has been demonstrated to be upregulated in SEB-induced inflammatory ALI, but its exact roles and functions remain ill-defined. In this study, SEB exposure led to inflammatory ALI and high expression of miR-222 in model mice and lung infiltrating mononuclear cells, but the inflammatory response and high expression of miR-222 were restored in miR-222 mice. Moreover, we investigated the roles of miR-222 in vitro and observed that the concentrations of inflammatory cytokines and the expression of miR-222 were all elevated in SEB-activated splenocytes and miR-222 inhibition reversed the effects. Foxo3 was confirmed as a direct target of miR-222. Interestingly, SEB exposure led to a decrease of Foxo3 expression, and Foxo3 knockdown partially reversed the promotion of Foxo3 and the inhibition of inflammatory cytokines induced by miR-222 inhibitor in SEB-activated splenocytes. Our data indicated that miR-222 inhibition could alleviate SEB-induced inflammatory ALI by directly targeting Foxo3, shedding light on the potential therapeutic of miR-222 for SEB-induced inflammation in the lung.
Can traffic light labelling nudge heuristical decision processes?

This research investigates the effect of different front-of-pack nutritional labelling on individuals’ decision-making process and food choices. To do this, we combine a stated choice experiment, a preference elicitation technique, with an eye-tracking experiment to explore the tendency to make fast (or slow) decision-making processes. Our results show that when the tendency to make fast decisions decreases, the probability of ignoring an alternative decreases. We also find that the labelling format plays an important role in influencing visual fixation and the probability of considering a choice alternative. Most importantly, we find that these effects are more prominent for unhealthy products compared to healthy products. The results have important implications for the food industry and the policy-makers regarding the front-of-pack labels. The findings show that labels using traffic light colour coding are more likely to help consumers process information as compared to other formats, such as no-colour coded numeric labels. This gives insights into other areas where communication is delivered via labels to encourage people to make informed choices. JEL Classification: D12, D90, D91
Fundamental issues on kappa-distributions in space plasmas

Numerous in situ observations indicate clearly the presence of nonthermal electron and ion structures as ubiquitous and persistent feature in a variety of astrophysical plasma environments. In particular, the detected suprathermal particle populations are accurately represented by the family of κ-distributions, a power-law in particle speed. After clarifying the characteristics of high-energy tail distributions under various space plasma conditions, different generation mechanisms of energetic particles are introduced where numerical simulations of wave–particle interaction based on a Fokker–Planck approach demonstrate how Landau interaction ultimately leads to κ-like distributions. Because of lack of theoretical justification, the use of the analytical form of κ-functions was frequently criticized. It is shown that these distributions turn out as consequence of an entropy generalization favored by nonextensive thermo-statistics, thus providing the missing link for powerlaw models of suprathermal tails fr.
Hop-constrained expander decompositions, oblivious routing, and distributed universal optimality

This paper studies the fundamental task of establishing routing paths in distributed networks. We prove the existence of compact routing tables that store in each network-node few simple forwarding rules tracing out hop-constrained and oblivious routing paths for any pair of nodes. For any collection of pairs the congestion of these paths is almost-optimal, i.e., competitive with the globally optimal solution up to a sub-polynomial factor. The key to this result is the algorithmic theory of hop-constrained expanders and expander decompositions developed in this paper. Informally, we say a graph is an h-hop φ-expanders iff for any set of node-pairs, in which each node is paired to O(deg(v)) nodes at hop-distance O(h), there exists an (h)-hop path between each pair such that any edge is used at most (1/φ) often. An h-hop φ-expander is basically a regular (φ)-expander when h = Ω(logn/φ). For shorter path lengths h ≪ 1/φ, however, h-hop expanders become interesting, powerful, and fundamentally different. We prove that every graph can be decomposed into h-hop (boundary-linked) φ-expanders by cutting at most an O(φ logn)-fraction of its edges. We also provide efficient constructions for almost-optimal h-hop expander decompositions and our compact routing tables. These are parallel algorithms with almost-linear work and sub-polynomial depth that also have highly-efficient implementations in CONGEST, the standard model for distributed message-passing algorithms. As major implication this gives novel CONGEST algorithms for a large class of important optimization problems, including minimum-spanning tree, (1+є)-min-cut, (1+)-shortest paths. Our algorithms solve these problems in sub-polynomial rounds on any network, as long as a sub-polynomial-round distributed algorithm exists for this network. This strong optimality guarantee is closely related to the notion of universal optimality.
Randomized communication and implicit graph representations

The most basic lower-bound question in randomized communication complexity is: Does a given problem have constant cost, or non-constant cost? We observe that this question has a deep connection to implicit graph representations in structural graph theory. Specifically, constant-cost communication problems correspond to hereditary graph families that admit constant-size adjacency sketches, or equivalently constant-size probabilistic universal graphs (PUGs), and these graph families are a subset of families that admit adjacency labeling schemes of size O(logn), which are the subject of the well-studied implicit graph question (IGQ). We initiate the study of the hereditary graph families that admit constant-size PUGs, with the two (equivalent) goals of (1) giving a structural characterization of randomized constant-cost communication problems, and (2) resolving a probabilistic version of the IGQ. For each family F studied in this paper (including the monogenic bipartite families, product graphs, interval and permutation graphs, families of bounded twin-width, and others), it holds that the subfamilies H ⊆ F are either stable (in a sense relating to model theory), in which case they admit constant-size PUGs (i.e. adjacency sketches), or they are not stable, in which case they do not. The correspondence between communication problems and hereditary graph families allows for a probabilistic method of constructing adjacency labeling schemes. By this method, we show that the induced subgraphs of any Cartesian products Gd are positive examples to the IGQ, also giving a bound on the number of unique induced subgraphs of any graph product. We prove that this probabilistic construction cannot be ”naïvely derandomized” by using an Equality oracle, implying that the Equality oracle cannot simulate the k-Hamming Distance communication protocol. As a consequence of our results, we obtain constant-size sketches for deciding dist(x,y) ≤ k for vertices x,y in any stable graph family with bounded twin-width, answering an open question about planar graphs from earlier work. This generalizes to constant-size sketches for deciding first-order formulas over the same graphs.
Examining the predictors of firm performance: The role of transformational leadership, HRM digitalization, and organizational commitment

This study aims to understand the predictors of firm performance, namely by examining the direct influence of transformational leadership, HRM digitalization, and organizational commitment. The sample which becomes the respondents of this study is the owners or managers of creative MSMEs in Bandung, West Java, with the number of samples of 125 respondents. The data is collected using survey method, namely by giving the questionnaires to the respondents. The data is analyzed using multiple linear regression analysis with SPSS 25 software. The findings prove that transformational leadership, HRM digitalization, and organizational commitment are able to predict firm performance, both partially and simultaneously. © 2022 by the authors. Licensee SSBFNET, Istanbul, Turkey. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
The Influence of Investors’ Risk Attitude and Market Information on Cryptocurrency Investment: Evidence from an Experimental Study

The existing studies underline the relationship between individual behavior and market information on investment decisions. However, to our knowledge, few studies investigated this relationship in the field of cryptocurrencies. Cryptocurrencies are hybrid assets with high volatility. This paper explores the impact of investors’ risk attitude and market information on cryptocurrency investment using an experimental research design. We employed 185 Master students in our experiment. We tested our model through a probit regression, and results indicate that investors’ risk attitudes and market information positively impact investment in cryptocurrencies. Our study contributes to behavioral finance literature on risk attitude and market information related to cryptocurrencies.
ON ZERO DISTRIBUTIONS OF SOME SELF-RECIPROCAL POLYNOMIALS WITH REAL COEFFICIENTS

If q(z) is a polynomial of degree n with all zeros in the unit circle, then the self-reciprocal polynomial q(z) + xq(1/z) has all its zeros on the unit circle. One might naturally ask: where are the zeros of q(z) + xq(1/z) located if q(z) has different zero distribution from the unit circle? In this paper, we study this question when q(z) = (z− 1)n−k(z− 1− c1) · · · (z− 1− ck) + (z + 1)n−k(z + 1 + c1) · · · (z + 1 + ck), where cj > 0 for each j, and q(z) is a ‘zeros dragged’ polynomial from (z − 1) + (z + 1) whose all zeros lie on the imaginary axis.
Relationship between Personality Traits and Academic Achievement among NCE Students

The study was designed to investigate the relationship between personality traits and academic achievement among NCE students of Kashim Ibrahim College of Education Maiduguri. Eighty one (81) students consisting of forty five (45) male and thirty six (36) female students were purposively selected. Two instruments were used to gather information. A profoma and the Big Five Personality questionnaire were used in this study. The proforma was used to obtain the cumulative grade point average (CGPA) of the students and the questionnaire was used to measure the personality trait of the students. Data collected were analyzed using multiple regression analysis. Results of the study revealed that personality trait is a predictor of students’ academic performance. The result further revealed that consciousness and agreeableness are the best predictors of students’ academic achievement.
High-dimensional robust precision matrix estimation: Cellwise corruption under -contamination

We analyze the statistical consistency of robust estimators for precision matrices in high dimensions. We focus on a contamination mechanism acting cellwise on the data matrix. The estimators we analyze are formed by plugging appropriately chosen robust covariance matrix estimators into the graphical Lasso and CLIME. Such estimators were recently proposed in the robust statistics literature, but only analyzed mathematically from the point of view of the breakdown point. This paper provides complementary high-dimensional error bounds for the precision matrix estimators that reveal the interplay between the dimensionality of the problem and the degree of contamination permitted in the observed distribution. We also show that although the graphical Lasso and CLIME estimators perform equally well from the point of view of statistical consistency, the breakdown property of the graphical Lasso is superior to that of CLIME. We discuss implications of our work for problems involving graphical model estimation when the uncontaminated data follow a multivariate normal distribution, and the goal is to estimate the support of the population-level precision matrix. Our error bounds do not make any assumptions about the the contaminating distribution and allow for a nonvanishing fraction of cellwise contamination. MSC 2010 subject classifications: Primary 62F35; secondary 62G35.
Detection of Virulence-Associated Genes and in vitro Gene Transfer From Aeromonas sp. Isolated From Aquatic Environments of Sub-himalayan West Bengal

Aeromonas is omnipresent in aquatic environments and cause disease within a wide host range. A total of thirty-four isolates from water samples of small fish farms were identified as Aeromonas based on biochemical characteristics and 16S rRNA gene sequence. A total of six virulent factors were analyzed which indicated 100% of isolates as beta-haemolytic and proteolytic, whereas 44.1, 38.2, and 70.6% of isolates produced DNAse, siderophore, and amylase, respectively. Studies on the occurrence of four genetic determinants of virulence factors revealed that aer/haem (haemolytic toxin) and flaA (polar flagella) genes were present in 44.1% of strains whereas ascV (type 3 secretion system) and aspA (serine protease) genes were detected in 21.5 and 8.82% of strains, respectively. Fish (Anabas testudineus) challenge studies showed that the isolate GP3 (Aeromonas veronii) bearing five virulent factors with the combination of aer/haem+/ascV+/fla+ genes induced severe lesions leading to 100% of mortality. In contrast, RB7 possessing four virulence factors and three genes (aer/haem+/ascV+/aspA+) could not produce severe lesions and any mortality indicating the absence of correlation between the virulence factors, its genes, and the pathogenicity in fishes. GP3 was cytotoxic to human liver cell line (WRL-68) in trypan blue dye exclusion assay. The 431 bp aer/haem gene of GP3 was transferable to E. coli Dh5α with a conjugational efficiency of 0.394 × 10–4 transconjugants per recipient cell. The transfer was confirmed by PCR and by the presence of 23-kb plasmids in both donor and transconjugants. Therefore, the occurrence of mobile genetic elements bearing virulence-associated genes in Aeromonas indicates the need for periodic monitoring of the aquatic habitat to prevent disease outbreaks.
Pathogenesis of Chicken Astrovirus Related Illnesses

Of the several known viruses, chicken astrovirus (CAstV) has been associated with diarrhea, runting-stunting syndrome, severe kidney disease, and gout, and white chick syndrome (WCS) in young broiler chicks. Discovered in 2004, CAstV consists of two genogroups with an expanding subgroup because of the diversity exhibited in its viral capsid sequence. Despite these findings, there exists a dearth of knowledge on its pathogenesis. This review highlights the pathogenesis and development of in vivo and in vitro models.
Dynamic Python-Based Method Provides Quantitative Analysis of Intercellular Junction Organization During S. pneumoniae Infection of the Respiratory Epithelium

Many respiratory pathogens compromise epithelial barrier function during lung infection by disrupting intercellular junctions, such as adherens junctions and tight junctions, that maintain intercellular integrity. This includes Streptococcus pneumoniae, a leading cause of pneumonia, which can successfully breach the epithelial barrier and cause severe infections such as septicemia and meningitis. Fluorescence microscopy analysis on intercellular junction protein manipulation by respiratory pathogens has yielded major advances in our understanding of their pathogenesis. Unfortunately, a lack of automated image analysis tools that can tolerate variability in sample-sample staining has limited the accuracy in evaluating intercellular junction organization quantitatively. We have created an open source, automated Python computer script called “Intercellular Junction Organization Quantification” or IJOQ that can handle a high degree of sample-sample staining variability and robustly measure intercellular junction integrity. In silico validation of IJOQ was successful in analyzing computer generated images containing varying degrees of simulated intercellular junction disruption. Accurate IJOQ analysis was further confirmed using images generated from in vitro and in vivo bacterial infection models. When compared in parallel to a previously published, semi-automated script used to measure intercellular junction organization, IJOQ demonstrated superior analysis for all in vitro and in vivo experiments described herein. These data indicate that IJOQ is an unbiased, easy-to-use tool for fluorescence microscopy analysis and will serve as a valuable, automated resource to rapidly quantify intercellular junction disruption under diverse experimental conditions.
L2M1 and L2M2 Acquisition of Sign Lexicon: The Impact of Multimodality on the Sign Second Language Acquisition

In second language research, the concept of cross-linguistic influence or transfer has frequently been used to describe the interaction between the first language (L1) and second language (L2) in the L2 acquisition process. However, less is known about the L2 acquisition of a sign language in general and specifically the differences in the acquisition process of L2M2 learners (learners learning a sign language for the first time) and L2M1 learners (signers learning another sign language) from a multimodal perspective. Our study explores the influence of modality knowledge on learning Swedish Sign Language through a descriptive analysis of the sign lexicon in narratives produced by L2M1 and L2M2 learners, respectively. A descriptive mixed-methods framework was used to analyze narratives of adult L2M1 (n = 9) and L2M2 learners (n = 15), with a focus on sign lexicon, i.e., use and distribution of the sign types such as lexical signs, depicting signs (classifier predicates), fingerspelling, pointing, and gestures. The number and distribution of the signs are later compared between the groups. In addition, a comparison with a control group consisting of L1 signers (n = 9) is provided. The results suggest that L2M2 learners exhibit cross-modal cross-linguistic transfer from Swedish (through higher usage of lexical signs and fingerspelling). L2M1 learners exhibits same-modal cross-linguistic transfer from L1 sign languages (through higher usage of depicting signs and use of signs from L1 sign language and international signs). The study suggests that it is harder for L2M2 learners to acquire the modality-specific lexicon, despite possible underlying gestural knowledge. Furthermore, the study suggests that L2M1 learners’ access to modality-specific knowledge, overlapping access to gestural knowledge and iconicity, facilitates faster L2 lexical acquisition, which is discussed from the perspective of linguistic relativity (including modality) and its role in sign L2 acquisition.