Miracle-dz/UniFAR-FTUs huggingface dataset:
THE RELATIONSHIP BETWEEN CULTURAL INTELLIGENCE AND CROSS-CULTURAL ADJUSTMENT AMONG CONSTRUCTION PROFESSIONALS

Culture is proven to be one of the fundamental characteristics that will differentiate international management from domestic management. The capability to adapt to new cultural contexts effectively is necessary for an expatriate to perform well. Additionally, cross-cultural adjustment is an important criterion of expatriate success in the international workplace. Hence, this study aims to examine the relationship between the four facets of cultural intelligence (CQ) with the cross-cultural adjustment to those who are working in the construction industry. A total of 116 construction professional expatriates participated in this study through questionnaire surveys. The results revealed positive correlations between cultural intelligence and cross-cultural adjustment. Motivational CQ proved to be the most significant CQ when it comes to the cross-cultural adjustment, indicating that an expatriate’s interest in learning about cultural differences would help an individual to work efficiently in culturally diverse environments.
Electrode Modiﬁed with Carboxylated Multi-Walled Carbon Nanotubes and Electropolymerized Pyrogallol Red for the Determination of Eugenol

: Eugenol is the major component of cloves and clove-based products, which are widely used in food, the pharmaceutical industry, and medicine. Its content can be considered a marker of the sample quality. Therefore, simple, sensitive, and reliable methods for eugenol quantiﬁcation are required. Glassy carbon electrodes (GCEs) modiﬁed with carboxylated multi-walled carbon nanotubes (MWCNTs-COOH) and electropolymerized pyrogallol red were developed for the determination of eugenol in essential oils. The working conditions (supporting electrolyte, pH, monomer concentration, and electrolysis parameters) of pyrogallol red were found using voltammetric characteristics of eugenol. The electrodes developed were studied using scanning electron microscopy, voltammetry, and electrochemical impedance spectroscopy. The effectivity of the electrode surface modiﬁcation was demonstrated. Eugenol determination was performed in differential pulse mode, whose parameters have been optimized. The linear response of the electrodes towards eugenol was obtained in the range of 0.75–100 µ M with a detection limit of 0.73 µ M. The high selectivity of eugenol determination was observed in the presence of typical inorganic and organic compounds, including essential oils components. The approach developed was tested on commercial clove, cinnamon, and nutmeg essential oils. Validation with the independent method showed similar accuracy and the absence of systematic errors in eugenol determination.
A Variable Depth Search Algorithm for the Quadratic Assignment Problem

The Quadratic Assignment Problem arises in many real world applications and is known to be NP-hard. Several heuristics have been proposed for handling near optimum solutions to its instances. Most of those heuristics rely on neighborhood based search strategies, the most popular of them being those which exchange k elements of a solution. However, a drawback for those approaches is that, for growing values of k , the computational eﬀort to explore such neighborhoods rises rapidly. Variable depth neighborhoods can be interesting alternatives for these problems. In this paper, a stochastic variable depth search strategy is presented. The proposal is implemented under an iterated local search framework and compared with related approaches presented previously in the literature. Computational experiments show that the proposed algorithm presents consistently better performance than their counter-parts, showing that the proposed strategy is an attractive alternative to be embedded in algorithms based on metaheuristics.
Improved Lower Bounds for SAT-Based Haplotype Inference

Mutation in DNA is the principal cause for di(cid:11)erences among human beings, and Single Nucleotide Polymorphisms (SNPs) are the most common mutations. Hence, a fundamental task is to complete a map of haplotypes (which identify SNPs) in the human population. Associated with this e(cid:11)ort, a key computational problem is the inference of haplotype data from genotype data. Existing solutions for the haplotype inference by pure parsimony (HIPP) problem include Integer Linear Programming (ILP) [6, 1, 2] and branch and bound [13]. Recent work has shown that Boolean Satis(cid:12)ability (SAT) approaches to the HIPP problem, built on top of modern SAT solvers [3], are remarkably e(cid:14)cient, yielding most often orders of magnitude speedups with respect to previous solutions to the HIPP problem. The objectives of this paper are twofold. The (cid:12)rst objective is to provide a brief survey of SHIPs [10, 11], a SAT-based solution to the HIPP problem. An additional objective of the paper is to propose improvements to the SHIPs approach described in [10, 11]. One important aspect of SHIPs is the lower bounding procedure, which reduces the number of iterations of the basic algorithm, but also indirectly simpli(cid:12)es the resulting SAT model. The paper describes a new, much more e(cid:11)ective, lower bounding procedure. This new lower bounding procedure is guaranteed to always be as tight as the procedure of [10, 11]. In practice, however, the new lower bounding procedure is in most cases signi(cid:12)cantly tighter, allowing relevant performance speedups in challenging problem instances.
The Sulfated Polysaccharides of Brown Algae and Products of Their Enzymatic Transformation as Potential Vaccine Adjuvants

The review is devoted to critical analysis of literature data, deal with effects and mechanisms of action of sulfated polysaccharides (PSs) – fucoidans from brown algae and products of their enzymatic transformation as potential adjuvants for enhancement of anti-infective and antitumor immune response. Numerous experimental data indicate that sulfated PSs demonstrate properties of vaccine adjuvants. Application perspectiveness of fucoidans as vaccine adjuvants is defined by their high biocompatibility, low-toxicity, safety and good tolerance by macroorganism, and also mechanisms of their immunomodulatory action. In particular, fucoidans are agonists of receptors of innate immunity and strong inducers of cellular and humoral immune response. At presenting the data of structural - functional interrelations, attention focused to the defining role of degree of sulfation, uronic acids and polyphenols contents, and also molecular mass in actions of fucoidans to innate and adaptive immunity cells. Insufficiency of literary data on studying of correlation of structure – physicochemical characteristics with adjuvanticities of the sulfated PSs, and also the problem of standardization of their active fractions are noted. Special attention is paid to the analysis of immunomodulatory and adjuvant activity of fucoidan oligosaccharides. Presented here results of experimental trial indicate that, despite the difficulties due to preparation of highly purified structurally characterized fractions and complex structure of fucoidans, these substances can be used as safe and effective adjuvants in vaccines against various pathogens including viruses, and also in antitumor vaccines.
A Neurocomputational Model of Stimulus-Specific Adaptation to Oddball and Markov Sequences : Supplementary Text S 1

A further technique to characterise the dependence of a neuron’s spike count upon the sequence stastistics is the switching oddball paradigm of Ulanovsky et al. [1]. In this protocol, a single sequence of tones is presented, in which the deviant tone switches back and forth between f1 and f2 at regular intervals. By contrast, an oddball sequence consists of two sequences of tones, and a given frequency is deviant in one sequence and standard in the other. In the switching blocks experiments performed here, one thousand blocks of twenty tones are presented, and the statistics alternate between blocks: in the odd blocks, f1 is deviant; and in the even blocks, f2 is deviant. In every block, pdev = 0.2; and the ratio of standards to deviants is controlled, so there are always four deviants per block, and f1 and f2 appear an equal number of times over the entire sequence (i.e., ten thousand times). The probability of a deviant and the block length used here have been carried over from the original switching blocks experiments [1]. However, we use the same tone duration (200 ms) and tone rate (1 Hz) used in the oddball experiments—a presentation rate slightly slower than that used in [1] (∼ 1.36 Hz). The spike counts from the model are noisier and the adaptation effects more subtle, as in [2]; consequently, longer-term averaging is required to highlight the effect of the switching statistics. Ulanovsky et al. [1] generate two randomised blocks of twenty tones, and then repeat this “frozen sequence” twenty times. In the present experiments, each block of twenty tones is randomised independently, so that the pattern of deviants is shuffled from one block to the next, and large single trial effects are removed through averaging.
Refinement of numerical modeling and technology of global and regional water cycle

Japan Ministry of Education, Culture, Sport, Science and Technology (MEXT) started a new national research mission for the sustainable coexistence of human, nature and the earth. Under the auspices of this revolutionary research plan, we undertake a project entitled “Advanced Prediction System and Counter Measures of Regionaland Meso-scale Water Cycle” (Global Water Cycle Project). The purpose of this project is to make a master plan for the improvement of desert environment. This project will continue from March 2002 until March 2007. In the interdisciplinary project initiated by MEXT Mitsubishi Heavy Industries (MHI) plays a central role in organizing the multifaceted project involving industry and research organizations; Frontier Research Centre for Global Change (FRCGC), National Research Institute of Earth Science and Disaster Prevention (NRIESDP), Kyoto University, Tottori University and Sophia University in Japan.
P RIVACY ON A SUBSET OF DATASET VARIABLES

Differential privacy (DP) is a mathematical definition of privacy that has many attractive properties. This includes allowing data providers to quantify the privacy risk of a collection of data releases from a dataset. As DP is defined for mechanisms acting on the dataset, the privacy guarantee of DP is at the level of the entire dataset and does not require the determination of which variables are sensitive or identifying. While this provides privacy guarantees that do not depend on the often-subjective classification of variables, this also leads to needing all outputs from the dataset to be noisy, even those that only involve variables that are not considered sensitive or identifying. In this paper, we introduce privacy definitions that only protect a subset of the variables in a dataset, thus allowing statistics only involving unprotected variables to be released accurately. We show that the definitions are a generalisation and relaxation of DP and can be defined using the Pufferfish framework for privacy definitions, as well as provide an algorithm for generating privacy-protected count tables that are consistent with the counts that can be released accurately under the proposed privacy definition. We explore the properties of the definition in terms of composition and show how the definitions can be used to assign an epsilon value to each subset of variables. This contrasts with DP, which only assigns an epsilon value to the entire dataset. The epsilon value for a single variable is at most that of the entire dataset and can be smaller, reflecting that different variables in a dataset may be protected to different degrees in a data release. This may be useful for data providers who wish to protect some variables, for example more sensitive ones, more than others.
INFLUENCE OF TRUST ATTRIBUTES IN SUBCONTRACTORS’ SELECTION IN SOUTHWESTERN NIGERIA

Trust has an important role in project and construction management industry, the success of the project will depend upon many factors in which trust is crucial because it enhance the relationship between client and employee, it increases the productivity and helps to maintain qualities of work done during the construction stage. This study aims to conceptualise the trust attributes influencing the decisions of main contractor, clients and consultants in the selection of trade specialist subcontractors in southwestern Nigeria. Toward this aim, sixteen trust attributes were identified, grouped into four clusters and developed into a questionnaire. The study finds that the trust attributes in the integrity and operation clusters were the most influencing attributes in the selection process. Perhaps the reported problem of the use of incompetent subcontractors which on several occasions had contributed to building failure in Nigeria could be responsible for the high emphasis on these clusters. The study concluded that one of the prevailing values that should influence the selection of subcontractors are the requirements of trustworthiness in the construction operation and the need for integrity in collaborating. This will encourage parties to adopt higher technical standards, and achieve improved ethical performance in all their dealings which in turn has the potential to produce an improvement in the ethical climate of the construction industry.
Enhancing the Resistance of Pinus roxburghii Sarg. Seedlings against Pythium debaryanum R. Hesse using Vesicular-Arbuscular Mycorrhiza (VAM) and Acibenzolar-S-Methyl (ASM)

This study was conducted to assess the likely inhibitory effects of vesicular-arbuscular mycorrhizal fungus (VAM), acibenzolar-s-methyl (Bion®), and Rhizolex® 50WP fungicide against Pythium debaryanum pathogen. The results showed that the inoculation with VAM was able to markedly decrease the growth of the pathogen. Bion showed high antifungal efficacy against Pythium debaryanum Oomycete. The seedlings of Pinus roxburghii that were inoculated with VAM displayed the highest growth parameters in terms of shoot height, root dry weight, and total dry weight in both seasons, followed by the treated seedlings with Bion in both seasons. The enzymatic tests revealed that mycorrhiza and Bion were able to significantly enhance levels of enzyme activities related to disease resistance, including peroxidase and polyphenol oxidase, which were clearly increased compared with the control. Mycorrhiza showed a higher effect on increasing enzyme activities related to disease resistance than Bion. Total phenols increased in all treatments as compared to the nonmycorrhizal, non-pathogen-treated control, but were highest when plants were inoculated with both the mycorrhizal fungi and the pathogen. This study recommends VAM as an inoculum for increasing the productivity performance of P. roxburghii seedlings and controlling the growth of P. debaryanum .
Can Governments Enhance Long-run Growth by Reallocating Public Expenditure? Empirical Evidence from Tanzania

This study examines whether the government of Tanzania can enhance long-run economic growth by changing the composition of public expenditure. The Johansen’s maximum likelihood method is used to test for co-integration and then estimate the long-run relationship. The study shows that while government spending on physical and human capital investments has positive impact on economic growth, government spending on consumptions has negative effect on economic growth. Moreover, the results reveal that switching expenditure from consumption to physical and human capital investments enhance economic growth, but the opposite is growth retarding. The study, however, found no evidence of output costs associated with a bilateral switch between physical investment spending and human capital investment spending.
and Rita Improving Outcome of Psychosocial Treatments by Enhancing Memory and Learning

Mental disorders are prevalent and can lead to significant impairment. Some progress has been made toward establishing treatments; however, effect sizes are small to moderate, gains may not persist, and many patients derive no benefit. Our goal is to highlight the potential for empirically supported psychosocial treatments to be improved by incorporating insights from cognitive psychology and research on education. Our central question is: If it were possible to improve memory for the content of sessions of psychosocial treatments, would outcome substantially improve? We leverage insights from scientific knowledge on learning and memory to derive strategies for transdiagnostic and transtreatment cognitive support interventions. These strategies can be applied within and between sessions and to interventions delivered via computer, the Internet, and text message. Additional novel pathways to improving memory include improving sleep, engaging in exercise, and using imagery. Given that memory processes change across the lifespan, services to children and older adults may benefit from different types and amounts of cognitive support.
Predicting the Frequency of Drug Side effects

Drug side effects are a leading cause of morbidity and mortality. Currently, the frequency of drug side effects is determined experimentally during human clinical trials through placebo-controlled studies. Here we present a novel framework to computationally predict the frequency of drug side effects. Our algorithm is based on learning a latent variable model for drugs and side effects by matrix decomposition. Extensive evaluations on held out test sets show that the frequency class is predicted with 67.8% to 94% accuracy in the neighborhood of the correct class. Evaluations on prospective data confirm the commonly held hypothesis that most post-marketing side effects are very rare in the population, with occurrences of less than 1 in a 10,000. Importantly, our model provides explanations of the biology underlying drug side effect relationships. We show that the drug latent representations in our model are related to distinct anatomical drug activities and that the similarity between these representations are predictive of the drug clinical activity as well as drug targets. One summary sentence novel explainable machine learning algorithm predicts the frequency of drug side effects in the population
Mayaro virus replication restriction and induction of muscular inflammation in mice are dependent on age and type-I interferon response

Mayaro virus (MAYV) is an emergent Arbovirus belonging to the Alphavirus genus from the Togaviridae family which has been circulated in forest regions of American continent through small outbreaks. Recent studies warned for the risk of MAYV dispersion to new areas and for the potential establishment of an urban epidemic cycle. Similar to Chikungunya and other arthritogenic Alphavirus, MAYV-induced disease shows a high prevalence of arthralgia and myalgia that can persist for months. Despite this, knowledge regarding pathogenesis, characteristics of host immune response, and resolution of MAYV infections are still limited. Here we investigated the dependence of age, innate and adaptive immunity for the control of MAYV replication and induction of inflammation in mice. We observed that age and type I interferon response are related to restriction of MAYV infection and tissue inflammation in mice. Moreover, we showed that MAYV continues to replicate persistently in adult recombination activation gene-1 efficient mice (RAG1−/−), indicating that adaptive immunity is essential to MAYV clearance. Despite chronic replication, infected adult RAG1−/− mice did not develop an apparent signal of muscle damage at late infection. On the other hand, MAYV infection induces muscular and paw inflammation in young WT and adult Type I Interferon receptor deficient mice (IFNAR−/−). In addition, MAYV infection triggers an increase in the expression of pro-inflammatory mediators, such as TNF, IL-6, KC, IL-1β, MCP-1, and RANTES, in muscle tissue, and decreases TGF-β expression. Taken together, our study contributes to the comprehension of MAYV pathogenesis, and describes a translational mouse model for further studies of MAYV infection, as well for testing vaccine and therapeutic strategies against this virus. Author Summary MAYV-induced disease presents a high prevalence of arthralgia and myalgia that potentially persist for months, which is characteristic of the arthritogenic Alphavirus group. However, information regarding MAYV infection and the molecular mechanism of pathogenesis is still scarce. Here we investigated the dependence of age, innate and adaptive immunity for the control of MAYV replication and induction of inflammation in mice. We observed that tissue inflammation and the restriction of MAYV replication in mice are affected by aging and type I interferon response. Besides, we also showed that adaptive immunity was important for MAYV clearance in adult mice. Histological analyses demonstrated that MAYV replication triggered muscular and paw inflammation in young WT and adult type-I interferon receptor deficient mice. In addition, the level of expression of several pro-inflammatory cytokines was increased in the muscle MAYV-infected mice. Our data provide an advance for understanding the molecular mechanism involved in MAYV pathogenesis, as well as describes an in vivo model for further investigations on MAYV infection and for antiviral compounds and vaccine testing.
JOURNAL ARTICLE PRE-PROOF (as accepted)

Objectives : To investigate the role of optimism, hope, and gratitude as psychosocial factors for healthy development, especially with regard to anxiety in college students in the context of COVID-19. Methods: This is a quantitative and descriptive cross-sectional research. The sociodemographic questionnaire and the Brazilian versions of the anxiety scale B-GRAT, LOT-R, Hope Index, and BIG-FIVE were applied. Data were analyzed using Mann-Whitney correlation, Kruskal-Wallis, Spearman, and hierarchical linear regression. Results: A total of 297 students were assessed. In the hierarchical linear analysis, the relationship of gratitude with anxiety becomes positive, contradicting the negative association of these variables in Spearman's correlation. The contradictions may result from the suppression effect. When gratitude was added to the model, these three variables together accounted for 38% of the variance in anxiety. This indicates that optimism, hope, and gratitude together are significant predictors, but optimism alone accounts for a large part of the variance for decreased anxiety. Conclusions: The data confirm that family and religiosity are protective factors against mental illness, specifically non-adaptive anxiety. Furthermore, developing optimism as a protective factor makes it possible to experience less anxiety while hope has the potential to provide the individual with multiple pathways to healthy development. This study has highlighted that gratitude plays a dual role in these relationships as it has the potential to be associated with anxious feelings with likely negative outcomes while at the same time it can drive positive psychosocial factors of optimism and hope in decreasing anxiety.