Miracle-dz/UniFAR-FTUs huggingface dataset:
Absence of a Role for Absorption, Translocation, and Metabolism in Differential Sensitivity of Hemp Dogbane (Apocynum cannabinum) to Two Pyridine Herbicides

Hemp dogbane is sensitive to fluroxypyr and tolerant to clopyralid. Absorption, translocation, and metabolism of clopyralid and fluroxypyr were studied in hemp dogbane to determine if differences in these processes could be responsible for differential sensitivity. In addition, the effect of growth stage on herbicide absorption and translocation was evaluated. The 14C-herbicides were applied to the adaxial side of a single leaf located near the midpoint of hydroponically cultured plants. Uptake of fluroxypyr was more rapid than clopyralid. At 72 h after treatment (HAT), fluroxypyr and clopyralid absorption was 62 and 38%, respectively. Clopyralid was much more mobile than fluroxypyr, with 75% of the absorbed 14C from 14C-clopyralid recovered outside the treated leaf compared to only 45% for fluroxypyr 72 HAT. Relative to fluroxypyr, a higher percentage of 14C-clopyralid recovered outside the treated leaf translocated acropetally, especially when plants were treated during the vegetative stage. Treatment during the early reproductive stage increased basipetal and reduced acropetal translocation relative to the vegetative stage. Neither herbicide was metabolized rapidly. Approximately 60 and 90% of the recovered 14C was attributable to unaltered fluroxypyr and clopyralid, respectively, 72 HAT. Some differences in absorption, translocation, and metabolism between clopyralid and fluroxypyr exist, but they cannot fully account for differential sensitivity of hemp dogbane to these two herbicides. Differences in activity at the target site may be responsible for differential activity of these herbicides on hemp dogbane.
High Throughput Expression Screening of Arabinofuranosyltransferases from Mycobacteria

Studies on membrane proteins can help to develop new drug targets and treatments for a variety of diseases. However, membrane proteins continue to be among the most challenging targets in structural biology. This uphill endeavor can be even harder for membrane proteins from Mycobacterium species, which are notoriously difficult to express in heterologous systems. Arabinofuranosyltransferases are involved in mycobacterial cell wall synthesis and thus potential targets for antituberculosis drugs. A set of 96 mycobacterial genes coding for Arabinofuranosyltransferases was selected, of which 17 were successfully expressed in E. coli and purified by metal-affinity chromatography. We herein present an efficient high-throughput strategy to screen in microplates a large number of targets from Mycobacteria and select the best conditions for large-scale protein production to pursue functional and structural studies. This methodology can be applied to other targets, is cost and time effective and can be implemented in common laboratories.
Predictability of earnings and its impact on stock returns: Evidence from India

Abstract The purpose of this paper is to analyse the predictability of earnings information before the quarterly disclosure date. Two categories of firms are contrasted: the firms that announce better quarterly earnings than the prior period and the firms that do not. The paper uses a sample of 67 large-cap Indian stocks over 33 quarters from 2010 to 2018. Panel data estimation with fixed and random effects is applied to examine the impact of quarterly earnings announcements on stock returns. Results show that all stocks experience return premiums in the pre-announcement period, which is already documented in the literature. The paper adds to the literature by finding that the firms that report better earnings numbers than the previous period generate significantly higher stock returns. It is inferred that the market can anticipate whether the firm will announce better earnings than the prior period. The paper shows that changes in revenue and core earnings are better anticipated. Post-announcement, stock prices adjust to reflect the disclosed earnings information, and only non-performers experience a drop in stock prices. It is the first comprehensive study of liquid large-cap Indian stocks that provides evidence on the behaviour of stock returns around earnings announcements.
Enabling Efficient Scheduling in Large-Scale UAV-Assisted Mobile-Edge Computing via Hierarchical Reinforcement Learning

Due to the high maneuverability and flexibility, unmanned aerial vehicles (UAVs) have been considered as a promising paradigm to assist mobile edge computing (MEC) in many scenarios including disaster rescue and field operation. Most existing research focuses on the study of trajectory and computation-offloading scheduling for UAV-assisted MEC in stationary environments, and could face challenges in dynamic environments where the locations of UAVs and mobile devices (MDs) vary significantly. Some latest research attempts to develop scheduling policies for dynamic environments by means of reinforcement learning (RL). However, as these need to explore in high-dimensional state and action space, they may fail to cover in large-scale networks where multiple UAVs serve numerous MDs. To address this challenge, we leverage the idea of “divide-and-conquer” and propose HT3O, a scalable scheduling approach for large-scale UAV-assisted MEC. First, HT3O is built with neural networks via deep RL to obtain real-time scheduling policies for MEC in dynamic environments. More importantly, to make HT3O more scalable, we decompose the scheduling problem into two-layered subproblems and optimize them alternately via hierarchical RL. This not only substantially reduces the complexity of each subproblem, but also improves the convergence efficiency. Experimental results show that HT3O can achieve promising performance improvements over state-of-the-art approaches.
Individual entrepreneurial orientation, entrepreneurship education and entrepreneurial intention: The mediating role of entrepreneurial motivations

This paper examines the direct and indirect roles of individual entrepreneurial orientation and entrepreneurship education in determining students’ entrepreneurial intention through the mediation of entrepreneurial motivations. The study also attempts to ascertain the influence of entrepreneurship education on individual entrepreneurial orientation. Cross-sectional data were collected from 323 university students using the convenience sampling method. Confirmatory factor analysis was used to assess the model fitness and the reliability and validity of the data while hypotheses were tested using structural equation modeling. The findings affirm that entrepreneurship education facilitates both individual entrepreneurial orientation and entrepreneurial motivations and also has a positive association with entrepreneurial intention. More importantly, entrepreneurial motivations significantly mediate individual ‘entrepreneurial orientation–entrepreneurial intention’ and ‘entrepreneurship education–entrepreneurial intention’ relationships. The findings provide practical support for the framing of new educational policies to assist students in their existing and future entrepreneurial projects. The study contributes to the literature by recognizing the mediating effect of entrepreneurial motivations on the above relationships. It also adds to the scarce literature on the lately recognized individual entrepreneurial orientation construct.
Unravelling the Habenaria repens (Orchidaceae) complex in Brazil: a biosystematic and molecular phylogenetic approach

Habenaria repens (Orchidaceae) represents a species complex distributed from the southern USA to northern Argentina, including several morphological variants, here referred to as morphotypes. To investigate and clarify the morphological and genetic relationships between these morphotypes and resolve the taxonomy of the complex, we applied a biosystematic multi-population approach using molecular phylogenetic, morphometric and population genetics analyses in the group. We sampled 31 (phylogenetic analyses) and 20 (morphometric and microsatellite analyses) populations of Habenaria aranifera and H. repens from Brazil and the USA, including six morphotypes of H. repens. Bayesian and maximum parsimony phylogenetic analyses of nuclear ribosomal (ITS and ETS) and plastid (matK, trnK and rps16-trnK) markers revealed that the complex is polyphyletic, subdivided into three distantly related clades. Population genetic analyses using microsatellites showed a remarkably similar structure to the phylogenetic analyses, but both were different from the morphometric analyses of floral characters, indicating cases of diversification and convergence, probably due to pollination processes. Habenaria aranifera is embedded in a paraphyletic and polymorphic H. repens with a broad geographical distribution and other attributes of an ochlospecies, probably constituting a progenitor–derivative pair. Our results support the recognition of H. aranifera, H. repens and three or four new species.
Global Comparisons of ERA5 and the Operational HRES Tropospheric Delay and Water Vapor Products With GPS and MODIS

Precipitable water vapor (PWV) from numerical weather models, such as the latest generation of European Centre for Medium‐Range Weather Forecasts (ECMWF) reanalysis (ERA5) and the ECMWF High RESolution (HRES) models, are important to meteorological studies and to error mitigation of geodetic observations such as Interferometric Synthetic Aperture Radar. In this study, we provide global validations of these new weather models with respect to Global Positioning System (GPS, ∼13,000 stations) and Moderate Resolution Imaging Spectrometer (MODIS, ∼1 km resolution) using data from January 2016 to December 2018 of every 1 h. The global standard deviations of the Zenith Tropospheric Delay (ZTD) differences (DSTDs) between weather models and GPS are 1.69 cm for ERA5 and 1.54 cm for HRES. The global PWV DSTDs between weather models and MODIS are 0.34 cm for ERA5 and 0.32 cm for HRES. The two weather models generally perform better in western North America, Europe, and Arctic by having low ZTD DSTDs (<1.3 cm) or PWV DSTDs (<0.3 cm). HRES also has a low ZTD DSTD of less than 1.3 cm in Antarctic, Japan, New Zealand, and Africa and outperforms ERA5 in most regions of the world, despite the fact that 83% of the HRES PWV values are temporally interpolated (from 6 to 1‐h). However, under extreme weather conditions, ERA5 performs better owing to its high temporal resolution (1 h). Our results can be used as a global reference for evaluating uncertainties when utilizing these weather models.
Local field enhancement: comparing self-similar and dimer nanoantennas

We study the local field enhancement properties of self-similar nanolenses and compare the obtained results with the performance of standard dimer nanoantennas. We report that, despite the additional structural complexity, self-similar nanolenses are unable to provide significant improvements over the field enhancement performance of standard plasmonic dimers.
Divorce and female labour force participation: Do women who expect an upcoming divorce increase their employment? Evidence from Flanders

Women who expect an upcoming divorce have the possibility of taking action in order to protect themselves against the projected negative financial consequences. In this paper we investigate whether they do. Using retrospective data for a sample of 884 divorced women from the Divorce in Flanders (DiF)-survey, we estimate the difference in the probability that women increase their employment intensity surrounding the time a couple stops living together between women who expected the divorce and those who did not. We find that in the year leading up to the factual separation, women who expect the divorce are three to five times more likely to increase their employment. Our results suggest that when anticipatory employment behaviour is not considered when researching the negative consequences of relationship dissolution, both the magnitude of the downturn as well as the time to recovery is likely underestimated for a large group of women.
ANTIOXIDANT ACTIVITY, TOTAL PHENOLIC AND CHLOROPHYLL CONTENT OF KENINGAU GROWN CUCUMIS SATIVUS L. AT TWO GROWTH STAGES

The maturation stage of Cucumis sativus is among the important factors affecting its composition and quality. Hence, this study monitored the differences in total phenolic content (TPC), antioxidant activity, pigment and colour of Keningau-grown cucumbers (Cucumis sativus L.) at two stages of maturities, namely the semi-ripe (SR) and ripe (R). The colourimetric and spectroscopic findings revealed significant differences in the assessed variables (P < 0.05) in the two growth stages except for the pigment. The colour of semi-ripe cucumbers was of lower L* (33.39 ± 4.26) and a* (−10.00 ± 1.74) mean values, while the ripe cucumbers registered the corresponding mean values of 36.71 ± 2.85 and −8.90 ± 1.85. R cucumbers gave a higher mean b* coordinate (16.38 ± 3.16) over the SR ones (14.52 ± 2.52). Compositions of pigments, namely, chlorophyll-a (SR: 4.86 ±0.01 μg/mL, R: 3.55 ± 0.00 μg/mL), chlorophyll-b (SR: 2.12 ± 0.02 μg/mL, R: 1.79, 0.02 μg/mL) and total chlorophyll were higher in SR (6.98 ± 0.02 μg/mL) than R ( 5.34 ± 0.02 μg/mL) cucumbers, except for the composition of carotenoids (SR: 0.82 ± 0.01 μg/mL, R: 1.78 ± 0.01 μg/mL). The TPC in SR was higher (424.21± 5.32 mg/g) than the R ones (185.51±4.62 mg/g), with the corresponding antioxidant activity (IC50) for SR and R at 157.98 ± 1.57 and 191.66 ± 2.58 μg/mL, respectively. TPC and antioxidant activity between the SR and R cucumbers were negatively correlated (−0.992), which meant that not all phenolic compounds were involved in free radical scavenging.
Computational tissue staining of non-linear multimodal imaging using supervised and unsupervised deep learning

Hematoxylin and Eosin (H&E) staining is the ’gold-standard’ method in histopathology. However, standard H&E staining of high-quality tissue sections requires long sample preparation times including sample embedding, which restricts its application for ’real-time’ disease diagnosis. Due to this reason, a label-free alternative technique like non-linear multimodal (NLM) imaging, which is the combination of three non-linear optical modalities including coherent anti-Stokes Raman scattering, two-photon excitation fluorescence and second-harmonic generation, is proposed in this work. To correlate the information of the NLM images with H&E images, this work proposes computational staining of NLM images using deep learning models in a supervised and an unsupervised approach. In the supervised and the unsupervised approach, conditional generative adversarial networks (CGANs) and cycle conditional generative adversarial networks (cycle CGANs) are used, respectively. Both CGAN and cycle CGAN models generate pseudo H&E images, which are quantitatively analyzed based on mean squared error, structure similarity index and color shading similarity index. The mean of the three metrics calculated for the computationally generated H&E images indicate significant performance. Thus, utilizing CGAN and cycle CGAN models for computational staining is beneficial for diagnostic applications without performing a laboratory-based staining procedure. To the author’s best knowledge, it is the first time that NLM images are computationally stained to H&E images using GANs in an unsupervised manner.
Factors Affecting the Sustainability of Micro�nance Institutions: A Case of Malawi Micro�nance Institutions

Background: Micro Finance Institutions (MFIs) have been used as a tool for poverty alleviation in many developing economies globally, including Malawi. However, their sustainability in many countries has been dependent solely on loan repayment, donor aid, and subsidies. Aim: This study aimed at investigating the factors that in�uence the sustainability of MFIs in Malawi. Methods: A cross-sectional survey was conducted from November to December 2020 among the MFIs employees in the central region of Malawi. Convenience and purposive sampling techniques were used to collect data online using a google form sent via social media platforms. Data were analyzed using IBM SPSS software with Statistical signi�cance placed at . 05. Results: 120 respondents completed the survey representing a 79.3% response rate, of which 63% were male. The majority of the respondents fell within the age group of 31-40 years, representing 58%, having attained universities and vocational colleges' education level, representing 32.8%. With an experience of above 16 years, representing 41.2% of which were branch managers, representing 49.6%. The results of the ordinary least square regression indicated that reporting and loan management system (RLMS) (β=0.200, P=0.021), corporate-governance (β=0.257, P=0.004), and commercialization (β=0.161, P=0.047) were positively signi�cantly in�uencing the sustainability of MFI. On the other hand, loan design/type (β =-0.211, P=0.006), loan portfolio management (β =-0.179, P=0.050) were found to be negatively impacting the MFI. Lastly, variables of over-indebtedness (B= 0.077, P=0.426), loan disbursement (β =0.121, P=0.104) were found statistically insigni�cant. Conclusion: Our study argues that commercialization, standardized reporting, and effective loan portfolio management systems, stakeholder-based approach to corporate governance, and favored board independence through scale and cost management is critical to improving MFIs' �nancial sustainability.
Communication Via Social Media: How Employees Will Paradoxically Support the Organization while Putting Less Effort at Work

Research on the effects of social media use by employees on work behaviors is inconclusive and showed mixed findings. To bring clarity to the extant literature, instead of focusing on generic social media use, we focus on a specific social media behavior—communication via social media with coworkers and friends—and theorize that it simultaneously triggers positive and negative effects on work behaviors through the mediation of opposite emotions. More specifically, our empirical study shows that employee communication via social media leads simultaneously to positive behaviors, predicting organizational citizenship behaviors, and negative behaviors, predicting counterproductive work behaviors. Happiness mediates the relationship between communication with social media and organizational citizenship behavior. Fatigue mediates the relationship between communication with social media and counterproductive work behaviors. The negative effects are stronger for communication with friends while the positive effects are more pronounced for communication with colleagues. Results are particularly revealing. Paradoxically, communication via social media makes employees happy and tired at the same time, making them likely to support the organization and coworkers while simultaneously working in counterproductive manner.
Sex disparity in skin carcinogenesis and potential influence of sex hormones

Abstract Background Sex or gender disparity in skin cancer has been documented for a long time at the population level. UV radiation (UVR) is a common environmental risk for all three major types of skin cancer: cutaneous melanoma (CM), basal cell carcinoma (BCC) and cutaneous squamous cell carcinoma (cSCC). The underlying mechanism for sex disparity has been largely attributed to sex‐differentiated behaviour patterns related to UVR. Non‐UVR factors such as intrinsic physiological differences have been suggested but remain understudied. Aims, Materials and Methods This review summarizes and compares the known sex differences in three skin cancer types with regard to body site distribution and age influence. Results We found a similar age‐dependent sex difference pattern in CM and BCC. Specifically, CM and BCC tend to show higher incidence in young women and old men, with a switching age around menopause. The switching age suggests involvement of sex hormones, which has shown controversial influence on skin cancers at epidemiological level. Literatures regarding sex hormone receptors for oestrogen, androgen and progesterone are summarized for potential explanations at molecular level. Discussion Overall, more and more evidence suggests non‐UVR factors such as sex hormones play critical roles in skin cancer (especially CM and BCC), yet solid population and molecular evidence are required. Incidences of skin cancer are increasing which suggests limited effect for the current UVR‐avoidance prevention methods. Conclusion Fully understanding the causes of sex disparities in incidence is necessary for developing a comprehensive prevention strategy.
Stock Price Movement Prediction Based on a Deep Factorization Machine and the Attention Mechanism

The prediction of stock price movement is a popular area of research in academic and industrial fields due to the dynamic, highly sensitive, nonlinear and chaotic nature of stock prices. In this paper, we constructed a convolutional neural network model based on a deep factorization machine and attention mechanism (FA-CNN) to improve the prediction accuracy of stock price movement via enhanced feature learning. Unlike most previous studies, which focus only on the temporal features of financial time series data, our model also extracts intraday interactions among input features. Further, in data representation, we used the sub-industry index as supplementary information for the current state of the stock, since there exists stock price co-movement between individual stocks and their industry index. The experiments were carried on the individual stocks in three industries. The results showed that the additional inputs of (a) the intraday interactions among input features and (b) the sub-industry index information effectively improved the prediction accuracy. The highest prediction accuracy of the proposed FA-CNN model is 64.81%. It is 7.38% higher than that of traditional LSTM, and 3.71% higher than that of the model without sub-industry index as additional input features.
Environmental Education: Ecological Wisdom of Indigenous Peoples in Western Siberia

The goal of environmental education is to form a respectful attitude towards nature in the interests of sustainable development. This paper describes the environmental education program at an ethnic camp, which enables visitors to become familiar with the ecological wisdom of the indigenous peoples of Western Siberia, Russia. This program illustrates how indigenous communities can participate in the global agenda as actors suggesting their responses to global environmental challenges. This paper aims to assess the content, form, and effectiveness of the environmental education program at the ethnic camp. The content and form were assessed in compliance with the elements of modern environmental education. To measure the effectiveness of the education program, the Theory of Planned Behavior (TPB) was used to study the students’ intentions to engage in sustainable behavior after visiting the ethnic camp. The research participants were 210 university students. This program is rich in content and form, including traditional activities and the ecological wisdom of the indigenous peoples. However, the findings demonstrated that the program had little effect on their sustainable environmental behavior. No significant differences were found between the results of the experimental and control groups. The study suggests ways to improve the education program.