Miracle-dz/UniFAR-FTUs huggingface dataset:
Are Positive and Negative Outcomes of Organizational Justice Conditioned by LeaderMember Exchange?

The workplace is complex, comprising many entities (abstract and tangible) – affective states, attitudes, and perceptions, but also workers and managers themselves and their behaviors. Understanding the link between them is vital for organizational prosperity. In the current paper, the perceptions of organizational justice are investigated as a precursor to two important outcomes – organizational citizenship behavior and counterproductive work behavior. To that end, a two-step research study was conducted to test a moderated-mediation model. First, a pilot study of 93 Romanian employees was undertaken, followed by a larger study consisting of 3293 Romanian workers. There were distinct differences between the two studies. Implications, limitations, and suggestions for future research are discussed.
JSkel: Towards a Formalization of JavaScript’s Semantics

We present JSkel, a formalization of the semantics of JavaScript in Skel, the concrete language used to write skeletal semantics. We describe the improvements to Skel we designed and implemented to signiﬁcantly simplify the formalization. We show the formalization is both close to the speciﬁcation and executable.
Predictive processing as a systematic basis for identifying the neural correlates of consciousness

The search for the neural correlates of consciousness is in need of a systematic, principled foundation that can endow putative neural correlates with greater predictive and explanatory value. Here, we propose the predictive processing framework for brain function as a promising candidate for providing this systematic foundation. The proposal is motivated by that framework’s ability to address three general challenges to identifying the neural correlates of consciousness, and to satisfy two constraints common to many theories of consciousness. Implementing the search for neural correlates of consciousness through the lens of predictive processing delivers strong potential for predictive and explanatory value through detailed, systematic mappings between neural substrates and phenomenological structure. We conclude that the predictive processing framework, precisely because it at the outset is not itself a theory of consciousness, has significant potential for advancing the neuroscience of consciousness.
Shrubland biomass and root-shoot allocation along a climate gradient in China

Background – Shrublands are receiving increasing attention because of climate change. However, knowledge about biomass allocation of shrublands at the community level and how this is regulated by climate is of limited availability but critical for accurately estimating carbon stocks and predicting global carbon cycles. Methods – We sampled 50 typical shrublands along a climate gradient in China and investigated the biomass allocation of shrubland at the community level and the effect of climate on biomass allocation. Shrub biomass was estimated using species-specific allometric relationships and the biomass of understory herbs was collected by excavating the whole plant. Regression analysis was used to examine the relationships between the biomass and the climate factors. RMA were conducted to establish the allometric relationships between the root and the shoot biomass at the community level. Key results – Shoot, root, and total biomass of shrub communities across different sites were estimated with median values of 206.5, 145.8, and 344.5 g/m2, respectively. Shoot, root, and total biomass of herb communities were estimated at 68.2, 58.9, and 117.2 g/m2, respectively. The median value of the R/S ratio of shrub communities was 0.58 and that of herb communities was 0.84. The R/S ratio of the shrub community showed a negative relationship with mean annual temperature and mean annual precipitation and a positive relationship with total annual sunshine and the aridity index. The R/S ratio of the herb community however showed a weak relationship with climate factors. Shoot biomass of the shrub community was nearly proportional to root biomass with a scaling exponent of 1.17, whereas shoot biomass of the herb community was disproportional to root biomass with a scaling exponent of 2.1. Conclusions – In shrublands, root biomass was more affected than shoot biomass by climate factors and this is related to water availability as a result of biomass allocation change of the shrub community. The understory herb community was less affected by climate due to the modification of the overstory–understory interaction to the climate-induced biomass allocation pattern. Shoot biomass of shrubs scales isometrically with root biomass at the community level, which supports the isometric theory of above-ground and belowground biomass partitioning.
The Relationship between the Factors of Risk in Asset Evaluation Models and Future Economic Growth: Evidence from Three Regional Markets

This study seeks to ascertain whether the risk factors in the asset evaluation models proposed by Fama and French (1993, 2015) contain information that help in forecasting regional economic growth. To this end, based upon samples of Gross Domestic Product for three regions, North America, Asia Pacific and Europe, covering the period between 1991 and 2018, we applied the quantile regression analysis technique. The empirical results suggest that the performance of regional risk factors contains information that helps in forecasting the regional level of economic growth. This furthermore concludes that the regional risk factors help in forecasting the economic growth of countries with developed and large-scale share markets.
Explants selection for in vitro propagation of Pachyrhizus erosus L.

Pachyrhizus erosus tuber is rich in protein asides its agronomical value as a legume, but the seeds by which it is propagated have very low viability. This study established sterilization protocol and effect of various concentrations of auxins and cytokinins on callus production and shoot regeneration from explants of P. erosus. Explants and seeds were sterilized using sodiumhypochlorite (NaClO) solution (5, 10 and 15% v/v) for 5 and 10 mins. Nodal, stem and leaf explants from in vitro germinated P. erosus and tuber from field grown plant were sterilized and cultured on Murashige and Skoog (MS) medium (control) and MS combined with different concentrations of auxins (NAA and 2, 4-D) and cytokinin (BA and Kinetin) and the cultured explants were monitored in terms of degree of callus formation, morphology and colour of callus and also for shoot induction. The results showed that seeds of P. erosus sterilized with 10% NaClO solution for 10 mins and germinated in vitro is the best way of getting sterile nodal, stem and leaf explants for the in vitro propagation of the plant, while tuber explants could be sterilized with 15% NaClO for 10 minutes. Nodal explants inoculated in MS medium supplemented with 1.0 mg/L BA gave the highest shoot regeneration response, while stem explants inoculated on MS medium supplemented with 1.0 mg/L BA and 0.5 mg/L NAA also gave the highest amount of friable callus. The study concluded that in vitro germinated seeds were the best way of getting explant for P. erosus.
Your Username Can Give You Away: Matching Turkish OSN Users with Usernames

—User profile matching (i.e., user cross-referencing, user identification) aims to find accounts that belong to the same users over different websites or online social networks (OSNs). Solving this problem can be useful for many operations and functionalities such as friend recommendation and link prediction across different OSNs. Additionally, identifying users across different OSNs may enable an adversary to aggregate incomplete information of users. Hereby, an adversary can extract and use online footprint of users to violate their privacy and security via putting them into threats such as identity theft, online stalking, and blackmailing among many others. Usernames are indispensable elements of all websites that require user registration. Even though usernames are generally short strings, they potentially reflect users’ characteristics and habits such as the political sense of belonging, hometown, and so on. In this study, we make an effort to match users of distinct OSNs relying only on their usernames. We use two different approaches based on machine learning and vector-based username similarity to build our learning function. We also explore different feature spaces from the literature and further investigate which approach produces better results. We conducted our experiments on a real-world username data set that is extracted from the OSN accounts of Turkish users we crawled in our previous work. Our results show that building learning function by binary classification outperforms the similarity approach and it achieves the best F-score of 0.921 without feature selection and extension.
ANT COLONY OPTIMIZATION APPLIED TO LAMINATED COMPOSITE PLATES

Laminated composite materials consist of stacks of layers, each layer usually composed by a matrix of polymeric material and fibers oriented in a specific direction. Laminated composite materials have excellent mechanical properties due to their good characteristics, specially the ratio stiffness-weight. These materials offer the possibility to create an unlimited set of different combinations depending on the structural design needs, being the number of layers, orientation of the plies and type of material of each layer, usually the design variables. In order to achieve superior designs, optimization techniques have been developed. The more successful ones to solve this class of problems are those based on stochastic procedures (like genetic algorithms) because their capability of avoiding getting stuck in local optima. Another technique, which is still in progress and has not been much used to solve laminated composite problems, is the Ant Colony Optimization (ACO). Thus, this work aims at analyzing the ACO applied to weight minimization and buckling load maximization of laminated composite plates under static loading. ACO is a new class of algorithms initially proposed to solve combinatorial optimization problems. It takes inspiration from the studies of real ant colonies foraging behavior. The ants deposit on the ground a chemical substance called pheromone. The pheromone concentration influences the choice of subsequent ants probabilistically. Called stigmergy, this kind of behavior is the mechanism that controls ant activity and connects them to take the shortest paths. The ACO is based in the information obtained in the pheromone matrix. Artificial ants are used to construct solutions for laminated composite plates, by choosing probabilistically the orientation of the stacks of the laminated. The solutions are built on the past search experience based on the level of pheromone, and the heuristic matrix, which brings the information about the laminated problem. The ACO procedure starts with the random selection of fiber orientation for a laminated layup. After the artificial ants have finished building the first laminated configurations, the pheromone is released with evaporation and deposited the new amount of pheromone based on the best solutions found at local and global iterations. The algorithm stops when the maximum number of iterations or function evaluations is reached. The following optimization constraints are considered in this work: first ply failure criterion, buckling and maximum number of contiguous plies with the same orientation. Also, the plate is considered symmetric and balanced, and the allowable ply orientations are (0/0/+ 45/45/90/90). To obtain the structural response, the plates are analyzed using the classical lamination theory. The results of this study are compared with those obtained from the literature, showing that ACO has a good performance in solving laminated optimization problems.
THE ANALYSIS OF LINKAGE BETWEEN CORPORATE SOCIAL RESPONSIBILITY AND FINANCIAL PERFORMANCE: EVIDENCE FROM INDONESIAN BANKS

Corporate Social Responsibility (CSR) has become one of the policies that the Indonesian Government uses to persuade companies to deal with various social problems. The Indonesian government has realized that this traditional mindset is supposed to have very important practical importance in the banking industry and has already stipulated a new regulation to change the local industry into a more modern mindset This paper tackles the question on whether or not CSR should be forcefully implemented in Indonesian banks. Data from eight (8) banks, between 2013 and 2015, were gathered in order to see how CSR affects the Financial Performance (FP) in the Banking Sector in Indonesia. The analyzed data of FP consist of Return on Asset (ROA), Return on Equity (ROE), and Earnings per share (EPS). A new indicator called Corporate Social Disclosure Index (CSDI) is introduced to measure CSR activity. A bivariate analysis strategy is used to determine the significance level and correlation between CSR and FP. The results show an indubitable correlation between CSR and FP of the banking industry in Indonesia during 2013 till 2015, even though the FP is not appearing to be significantly impacted.
The Progress of Interface Design in Perovskite‐Based Solar Cells

Organic–inorganic halide perovskite has received extensive attention as a light harvester for next‐generation low‐cost and high‐performance photovoltaics. Its superior optoelectronic properties are attractive among most thin film absorber materials, such as an extremely high absorption coefficient, optimal band gap, ambipolar carrier transport property, and high defects tolerance. However, it requires suitable electrodes and carrier transport materials to fulfill efficient photovoltaic process within an entire device. Thus, the interfaces along the device play a crucial role in determining device photovoltaic performance. Here, the progress of understanding interfaces in perovskite photovoltaics is reviewed from the perspective of processing chemistry and photophysics of carriers, which are the key parameters for the corresponding device photovoltaic behavior. This study is mainly focused on the relevant working mechanism, interface design fundamentals, and the resulting carrier dynamic control over the entire architecture. The study of the interfaces with appropriate materials design provides a fundamental understanding of the photocarrier behavior, including separation, transportation, and collection. The accumulative efforts will contribute to the construction of high‐efficiency perovskite‐based single junction and multijunction photovoltaic devices. It also affects other properties of perovskite solar cells, including J–V hysteresis phenomenon, and long‐term stability. Suggestions with respect to required improvements and future research directions are provided based on the current field of available literature.
Investigation of the price linkage between Asian LNG spot and Far East Asian LNG prices and its implications

For so many times, Far East Asian liquid natural gas (LNG) buyers have been using price linked to crude oil-indexed, now they need to find another alternative pricing formula for their crucial energy supply as a better price structure that could reflect the market is needed. LNG spot price is expected to be the pillar for the future LNG trading, especially for Far East Asia Market. As less and less long-term contracts are signed in the Far East Asia Market, this creates an additional demand for the LNG in the spot market, while it raises some issues about the presence of different LNG pricing mechanisms. Most of the LNG spot prices in Asia are indexed to the relatively low natural gas prices in Atlantic Basin. Furthermore, the advancement of drilling technology in the US drives down its natural gas prices, resulting in price discrepancies between Asian LNG spot and East Asian LNG prices. This study investigates whether there is a price linkage between Asian LNG spot and East Asian LNG prices. This study comprehends 91 observations collected from January 2010 to July 2017. Johansen co-integration tests were carried out to examine the existence of long-run relationship on the spot, Japanese and South Korean LNG prices. The Augmented Dickey-Fuller (ADF), Phillip-Perron (PP), and Kwiatkowski-Phillips-Schmidt-Shin (KPSS) unit root tests were conducted first before proceeding to the cointegration tests. The results showed that Asian LNG spot prices did not have price linkage for monthly averages of Japanese and South Korean LNG prices. The analyses also indicated that Taiwan LNG markets move together with Asian LNG spot markets. As a conclusion, the results inferred that supply dependency on LNG spot cargoes governed the price linkage among these Asian LNG markets. The use of gas indexed LNG price mechanism did not reflect the economic fundamentals in Asia-Pacific Basin. JEL Classification: Q41
Nanoencapsulation of montmorillonite clay within poly(ethylene glycol) nanobeads by electrospraying

The present study describes the preparation and characterization of a novel nanocomposite, based on montmorillonite clay (MMT) encapsulation in poly(ethylene glycol) (PEG) by an electrospraying process. PEG/MMT nanocomposites with MMT contents ranging from 1 to 5 wt % were successfully prepared and characterized in relation to their morphological, spectroscopic, structural, and thermal properties. Scanning electron microscopy, transmission electron microscopy, and atomic force microscopy micrographs showed that the PEG nanobeads formed spherical shapes, and with increasing amount of MMT clay, the size of the beads decreased significantly, ranging from 120 to 3.7 nm. The Fourier transform infrared spectroscopy results suggested that there was no significant chemical interaction between PEG and MMT clay. However, the d-spacing of MMT clay in PEG/MMT increased, a clear indication of the intercalation of PEG in the interlayer spaces of MMT clay. Furthermore, the thermal stability of PEG polymer decreased upon encapsulation of MMT clay in PEG/MMT composites. Nanoindentation results showed that the hardness and Young's modulus of the PEG/MMT composites increased with 3 wt % loading of MMT. © 2017 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2017, 134, 45048.
Pupillometry in children: a good method for assessing listening effort

The additional cognitive effort required during listening activity, for example in case of inadequate acoustic conditions, may lead to a general worsening of cognitive performances, especially in children, who are still developing adult-like language skills which may help them compensating for inaccurate speech recognition. For this reason, it is increasingly important to have a more objective method for assessing listening effort. Pupillometry could be a good solution for evaluating the effect that background noise has on children’ cognitive abilities, particularly in the case of hearing-impaired children. As it has been proved that eye pupil dilation can be considered a psychophysiological marker of cognitive effort, pupillometry may indeed be a practical and reliable method for this type of evaluation. This review aims to provide more information on this technique and how to use it when assessing listening effort in children.
Bayesian Online Change Point Detection for Baseline Shifts

In time series data analysis, detecting change points on a real-time basis (online) is of great interest in many areas, such as finance, environmental monitoring, and medicine. One promising means to achieve this is the Bayesian online change point detection (BOCPD) algorithm, which has been successfully adopted in particular cases in which the time series of interest has a fixed baseline. However, we have found that the algorithm struggles when the baseline irreversibly shifts from its initial state. This is because with the original BOCPD algorithm, the sensitivity with which a change point can be detected is degraded if the data points are fluctuating at locations relatively far from the original baseline. In this paper, we not only extend the original BOCPD algorithm to be applicable to a time series whose baseline is constantly shifting toward unknown values but also visualize why the proposed extension works. To demonstrate the efficacy of the proposed algorithm compared to the original one, we examine these algorithms on two real-world data sets and six synthetic data sets.
A Text Classification Method Based on Combination of Information Gain and Graph Clustering

—Text classification has a wide range of applications such as: spam filtering, automated indexing of scientific articles, identifying the genre of documents, news monitoring, and so on. Text datasets usually contain much irrelevant and noisy information which eventually reduces the efficiency and cost of their classification. Therefore, for effective text classification, feature selection methods are widely used to handle the high dimensionality of data. In this paper, a novel feature selection method based on the combination of information gain and FAST algorithm is proposed. In our proposed method, at first, the information gain is calculated for the features and those with higher information gain are selected. The FAST algorithm is then used on the selected features which uses graph-theoretic clustering methods. To evaluate the performance of the proposed method, we carry out experiments on three text datasets and compare our algorithm with several feature selection techniques. The results confirm that the proposed method produces smaller feature subset in shorter time. In addition, the evaluation of a K-nearest neighborhood classifier on validation data show that, the novel algorithm gives higher classification accuracy.
Effect of Maternal Empowerment Program on Neonatal Colostomy Complications and Maternal Distress Tolerance

Background: Different complications of colostomy in neonates can lead to readmission, surgery, and even death. Therefore, prevention of colostomy complications highlights the empowerments of mother to care for the neonate and reduce maternal distress. Aim: The present study aimed to determine the effect of maternal empowerment programs on neonatal colostomy complications and maternal distress tolerance. Method: This randomized clinical trial was conducted on 60 mothers of newborns aged 1-90 days with colostomy referred to two specialized pediatric centers in northeastern Iran in 2019. The control group received a training session. The intervention group, in addition to one training session, participated in two sessions of maternal empowerment program regarding the care of neonates with a colostomy. The collected data were analyzed in SPSS software (version 21) using ANOVA, Friedman, and Mann-Whitney U tests. Results: The two groups were homogeneous considering demographic variables (P<0.05). According to the results of the Mann-Whitney U test, the skin complication in the neonates was less in the intervention group than in the control group at all three stages of assessment (P<0.001). Moreover, the repeated measures ANOVA results demonstrated that the effect of group (P=0.006), effect of time (P<0.001), and interaction of group and time (P<0.001) were significant on the total score of distress tolerance. Implications for Practice: Considering the positive effect of the maternal empowerment program on reducing maternal distress and skin complications of colostomy among neonates, it is recommended to use this program in surgical wards and neonatal intensive care unit.