Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of Board Characteristics on Bank Risk: The Case of Vietnam

The research identifies hypotheses evaluating the impact of board characteristics on the risk of the commercial bank as well as examining the determinants of bank risk in Vietnam over a 10-year period, starting from 2008. Also, in this research, the differences between the roles of women and men in decision-making are tested. Based on this decision, risks of the banks may arise. Ordinary least squares (OLS) regression, Random effect method, and Fixed effect method are used to estimate the factors that have an impact on bank risk for dataset of all commercial banks in Vietnam. The results found that equity-to-asset ratio, bank performance and the economic growth have an inverse relationship with bank risk, while the size of bank has a positive relationship with the bank risk. One of the highlights of this paper is a demonstration of the relationship between CEO’s gender and bank risk. The test result shows that the bank led by a female faces a higher overall risk level and credit risk than a bank led by a male. Based on this result, the paper also makes recommendations to Government, the State Bank of Vietnam and the commercial banks for effective risk management.
Bioavailability of zinc and iron in durum wheat: A trade‐off between grain weight and nutrition?

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2020 The Authors, Plants, People, Planet © New Phytologist Trust *Binh T. T. Tran and Stephanie J. Watts-Williams contributed equally to this work. 1The Waite Research Institute and the School of Agriculture, Food and Wine, the University of Adelaide, Adelaide, SA, Australia 2Faculty of Agriculture and Forestry, Taynguyen University, Buon Ma Thuot city, Daklak Province, Vietnam 3The Australian Research Council Centre of Excellence in Plant Energy Biology, the University of Adelaide, Adelaide, SA, Australia
On the Use of a Simplified Slip Limit Equation to Predict Screw Self-Loosening of Dental Implants Subjected to External Cycling Loading

Self-loosening of the prosthetic screws is a major mechanical problem affecting roughly 10% of dental implants, according to the literature. This phenomenon may lead to micro-movements that produce crestal bone loss, peri-implantitis, or structural failure of the implant assembly. In this paper, a simple and effective tool to predict self-loosening under masticatory loads is presented. The loads acting on the screw are obtained from a simple finite element (FE) model, and introduced in a mathematical formula that calculates the torque needed to loosen the screw; self-loosening will occur when this torque becomes zero. In this sense, all the parameters involved in self-loosening phenomenon can be easily identified, and their effect quantified. For validating purposes, 90 experimental tests were performed in a direct stress test bench. As a result, a powerful tool with a maximum experimental error of 7.6% is presented, allowing dental implant manufacturers to predict eventual occurrence of self-loosening in their developed dental implant products and take corrective actions at preliminary design stage. Furthermore, the following clinical implications can be directly derived from the methodology: a higher screw preload, that is a higher tightening torque, improves self-loosening response of the dental implant and, similarly, for a given preload force, higher friction coefficient and screw metric, as well as lower pitch and thread angle values, are also found to be beneficial.
Association of demographic, clinical, laboratory, and radiological characteristics with outcomes of COVID-19 patients: A systematic review and Meta-analysis

Objectives: The aim of this meta-analysis was to assess association between a composite clinical outcome (severe infection/ required ICU admission/ death) of COVID-19 pneumonia and demographic, clinical, laboratory and radiological findings of these patients. Methods: A literature search was conducted using the databases PubMed, Medline, Scopus and Web of Science till July. Relative risk (RRs), standardized mean difference (SMDs) and 95% confidence intervals (CIs) were pooled using random-effects models. We described overall estimates of relevant data of clinical importance from 116,260 COVID-19 pneumonia patients including 19,628 with composite end points from 40 observational studies of 5 countries. Results: The result showed that male gender (RR=1.24, p 64 years (RR=2.52, P <.001) followed aggravated course. Delayed hospitalization (SMD=.75, p= 0.005), presence of co-morbidity (RR= 1.76, p<.001) and multiple co-morbidities (RR=1.50, p<.001) were associated with higher risk of fatal course. Pooled data reported significantly high neutrophil-lymphocyte ratio (SMD=10.79, p<.001), low lymphocyte-to-C-reactive protein ratio (SMD=-3.89, p<.001), low platelet count (SMD=-1.622, p<.001), prolonged prothrombin time (SMD=0.98, p<.001), high lactate dehydrogenase (SMD=6.260, p<.001), D-dimer (SMD=1.92, p<.001), creatine kinase (SMD=1.68, p= 0.001) and interleukin-6 level (SMD=2.84, P=.001) in patients with fatal outcome. Funnel plots and Egger’s tests did not reveal any significant publication bias. Conclusions: Features like older age, male gender, presence of co-morbidities and delayed hospitalization along with the laboratory findings consistent with infection, immune system activation, coagulation disorder and tissue damage could help clinicians to identify COVID-19 patients with poor prognosis at an early stage. J Microbiol Infect Dis 2019; 9(3):121-135.
The Impact of Education for Sustainable Development on Romanian Economics and Business Students’ Behavior

Education for sustainable development (ESD) has presented long-lasting interest for researchers and policy makers. Despite a significant body of research, more in depth empirical studies are required for a better understanding of how sustainable development goals are applied in higher education and how sustainable behavior could be shaped via ESD. The need for this kind of research arises from, first, the scarceness of existing studies that explore economic and business higher education, and, second, the necessity to properly assess the connection between ESD principles and students’ behavior. Following this rationale, the present paper aims to provide an overview of how students’ sustainable behaviors are shaped via their perception of sustainable campus initiatives, teaching staff involvement and curricula. Statistical and econometric analysis applied on data collected via a survey on students from Bucharest University of Economic Studies (N = 1253) provides findings on the extent to which the awareness of sustainable development-specific issues acquired through education leads to sustainable behavior among students. According to the results, we argue that an increasing share of sustainable development topics combined with teaching staff involvement to raise awareness of sustainability issues are crucial to students’ sustainable behavior. However, on-campus actions are unlikely to change behavior unless they are optional rather than compulsory. Our findings ratify that, since education is one of the main drivers of sustainable development, there is an urgent need for coherence in shaping higher education according to sustainability issues.
Estimating the impact of oyster restoration scenarios on transient fish production

Oyster reef restoration projects are increasing in number both to enhance oyster density and to retain valuable ecosystem services provided by oyster reefs. Although some oyster restoration projects have demonstrated success by increasing density and biomass of transient fish, it still remains a challenge to quantify the effects of oyster restoration on transient fish communities. We developed a bioenergetics model to assess the impact of selected oyster reef restoration scenarios on associated transient fish species. We used the model to analyze the impact of changes in (1) oyster population carrying capacity; (2) oyster population growth rate; and (3) diet preference of transient fish on oyster reef development and associated transient fish species. Our model results indicate that resident fish biomass is directly affected by oyster restoration and oyster biomass, and oyster restoration can have cascading impacts on transient fish biomass. Furthermore, the results highlight the importance of a favorable oyster population growth rate during early restoration years, as it can lead to rapid increases in mean oyster biomass and biomass of transient fish species. The model also revealed that a transient fish's diet solely dependent on oyster reef‐derived prey could limit the biomass of transient fish species, emphasizing the importance of habitat connectivity in estuarine areas to enhance transient fish species biomass. Simple bioenergetics models can be developed to understand the dynamics of a system and make qualitative predictions of management and restoration scenarios.
The way bioclimatic variables are calculated has impact on potential distribution models

Bioclimatic variables (BCVs) are routinely used in potential distribution models, typically without considering their calculation options in detail. We aimed at studying the impact of a decision, yet unexamined, on the calculation of BCVs, namely whether the identity of specific months/quarters in the calculation of BCVs should be updated for the future periods (temporal context). Effects on the performance of potential distribution models and on their projections were investigated. Additionally, we also aimed at comparing the impact of month/quarter shifts to that of climate model selection and covariate selection. Potential natural vegetation models encompassing eight habitat types and the whole territory of Hungary were created using boosted regression trees. We tested multiple initial covariate sets to compare the impact of the temporal context to that of covariate selection. The resulting models were applied to the reference and one future time period (with data from two regional climate models). The effect of the BCV calculation approach was tested by linear mixed‐effects models and model goodness‐of‐fit measures in a comprehensive framework of 192 predictions. Area under the ROC curve (AUC) and true positive rate (TPR) curves were used to evaluate the models. Our results show that (a) temporal context of BCVs in interaction with covariate selection had a strong effect on model structure as well as on projections; (b) no evidence supporting the superiority of the widely applied calculation approach of BCVs was found. However, we found notable differences under the two approaches and examples of projection artefacts when applying the widespread way of calculation. We conclude that (a) more attention and more transparent communication is needed when BCVs are used as covariates in distribution models; (b) not only ecophysiology but also the way covariates are calculated should be considered when preselecting covariates for potential distribution models.
Use of extensive winter feeding systems for backgrounding beef calves and the effect on finishing

ABSTRACT The introduction of low heat unit corn varieties in western Canada has led to questions on how this crop might fit into an extensive backgrounding program. Therefore, a 3-yr study was conducted to evaluate the effects of grazing standing whole-plant corn (Zea mays L. ‘Pioneer P7443R’) or swathed whole-plant barley (Hordeum vulgare ‘Ranger’) compared with barley hay fed in drylot pens on beef steer performance during backgrounding and feedlot phases. The effect of backgrounding system was also assessed during finishing when steers were fed diets based on barley grain or corn grain. Each yr, 120 Angus steers (BW = 250.5 ± 1.8 kg) were allocated to 1 of 3 replicated (n = 2) backgrounding systems: (1) field grazing swathed whole-plant barley (BSG; 11.2% CP, 60.6% TDN); (2) field grazing standing whole-plant corn (CG; 8.7% CP, 64.6% TDN); or (3) drylot (DL) bunk feeding of processed barley hay (10.9% CP, 57.2% TDN) for an average 78 d (42 to 95 d) trial. All calves received 2.5 kg/d of a range pellet supplement (16% CP, 78% TDN). Treatment groups were similar (P > 0.05) in final BW (295.8 ± 5.0 kg), ADG (0.59 ± 0.03 kg/d), and G:F ratio (0.187 ± 0.03 kg/kg). The cost of gain of DL, BSG, and CG steers was CAN$6.32, CAN$3.14, and CAN$2.96/kg, respectively. Following backgrounding, each replicate group of steers was subdivided and placed in a feedlot for finishing on either a barley- (12.2% CP, 75.4% TDN) or corn grain–based (11.3% CP, 74.7% TDN) diet for an average of 120 d. There were no backgrounding system, finishing, or backgrounding system × finishing interaction effects (P > 0.05) for feedlot DMI, ADG, G:F, or carcass characteristics. Study results suggest that grazing either swathed barley or whole-plant corn for 65 d during backgrounding can reduce (P = 0.05) costs by CAN$60 and CAN$70/steer, respectively, compared with feeding steers barley hay in a drylot.
ARHGAP6 Promotes Apoptosis and Inhibits Glycolysis in Lung Adenocarcinoma Through STAT3 Signaling Pathway

Objective Constitutively activated signal transducer and activator of transcription 3 (STAT3) has been linked to cisplatin (DDP)-resistance in a wide range of cancers. Recent work has indicated that Rho GTPase-activating protein 6 (ARHGAP6) promotes cell cycle arrest and apoptosis in cervical and breast cancers. However, the role of ARHGAP6 in lung adenocarcinoma and DDP-resistance remains unknown. Materials and Methods Bioinformatic analysis, quantitative RT-PCR and IHC staining were used to explore ARHGAP6 expression patterns in The Cancer Genome Atlas (TCGA) dataset and patient samples. Statistical analysis was performed to establish the association of ARHGAP6 expression with the resistance to DDP-based chemotherapy in lung adenocarcinoma patients. Functional assays were then conducted to examine the effect of ARHGAP6 on the apoptosis and glycolysis in DDP-resistant/sensitive A549/DPP cells in vitro. Finally, the effects of ARHGAP6 on the chemosensitivity of DDP were explored in vivo. Results We show that decreased ARHGAP6 levels are a reliable marker of lung adenocarcinoma across published datasets, cell culture lines, and clinical samples. Low ARHGAP6 expression was linked to decreased apoptosis and increased metabolic activity, which highlights ARHGAP6’s role as a tumor suppressor. Furthermore, activated p-STAT3 levels increased dramatically in the absence of ARHGAP6, which suggests that ARHGAP6 can inhibit the STAT3 pathway. In agreement with previous studies that linked p-STAT3 levels to DDP-resistance, our in vitro and in vivo data indicate that tumors became more resistant to DDP-therapy with reduced ARHGAP6 levels and an associated increase in p-STAT3. Conclusion ARHGAP6 presents a novel study target for overcoming p-STAT3-associated DDP-resistance in lung adenocarcinoma and potentially other cancers.
Didactic Anticipation of Two Matrix Multiplication Learning

This study aims to create a didactic design in an effort to overcome the learning obstacle through DDR (Didactical Design Research) in learning multiplication of two matrices through prospective, meta-pedadidactic, and retrospective analysis stages. Data collection using the following techniques: 1) observation, namely observing learning activities, analyzing teaching materials and learning implementation plans used by teachers in classroom learning; 2) tests in the form of diagnostic tests for students to determine the learning obstacle, prerequisite ability tests, and final identification tests; 3) interviews with mathematics subject teachers by asking questions that lead to student difficulties and teacher difficulties in delivering mathematics learning material; and 4) instructional videos in the learning process. The data were analyzed to find a learning obstacle and based on these findings, a was prepared Hypothetical Learning Trajectory (HLT)which was outlined in a hypothetical didactic design. The didactic design that has been designed is implemented to test as well as validate HLT. The results of the instructional video recordings were analyzed in the meta-pedadactic stage. The didactic design of the two matrix multiplication material contains didactic anticipation that can be an alternative for the teacher when facing situations and responses that may occur.
Signaling of the T Cell Costimulatory Receptor CD28: Regulation and Initiation

T cells provide antigen-specific immunity to pathogens, but are also capable of inducing destructive autoimmunity when responding to self antigens. In order to achieve full activation, T cells must receive two signals: one from the T cell antigen receptor, and a second from a costimulatory receptor, such as CD28. Expression of the ligands for CD28 activation is strongly induced on professional antigen presenting cells under conditions of inflammation or dangersensing. Hence, CD28 costimulatory receptor acts as a gatekeeper to T cell activation and is essential in maintaining the balance between immunity and self-tolerance. CD28 function has been implicated in many animal models of T cell-dependent infection control and autoimmune disorders. Intensive study of CD28 signaling biology over more than two decades has elucidated key signaling pathways and transcriptional targets that help to explain the unique CD28-dependent functions in T cells. Some signaling pathways downstream of CD28 activation have been mapped to particular motifs within the CD28 cytoplasmic domain, although no consensus has emerged on the importance of these signaling motifs to CD28 function in vivo. This thesis describes the discovery of a novel motif within CD28 cytoplasmic domain that regulates receptor signal initiation through membrane binding and kinase recruitment, and discusses the new findings in light of existing literature.
Adaptive intelligent terminal sliding mode controller for stabilizing a chaotic plasma torch system

In this article, a novel adaptive intelligent control scheme is proposed to stabilize a chaotic nonlinear system with unknown dynamics in the presence of uncertainties and external disturbances. The proposed control scheme is a combination of terminal sliding mode, adaptive, and neural controllers. Terminal sliding mode control provides appropriate finite-time stability and robustness against uncertainties and external disturbances. A neural controller is used to provide suitable control action to eliminate chattering when the sliding surface is close to zero. For this purpose, a fuzzy module with simple rules is used to change the contributions of two neural and terminal sliding mode controllers, that is, when the sliding surface has a value around zero, the neural controller will take the control of the system to reduce chattering, and when the sliding surface is far from the zero region, the terminal sliding mode controller will control the system. Moreover, to cope with the unknown dynamics of the system, an online adaptive neural network is also used to approximate the unknown dynamics of the system. This hybrid control scheme is capable to decrease the contribution of the terminal sliding mode in the convergence region of the sliding surface which leads to the elimination of chattering. The combination of the several techniques to use the advantages of all the methods makes the proposed hybrid control scheme as an effective and practical scheme. Simulation results on a chaotic plasma torch system indicate the efficiency of the proposed control scheme in chattering elimination, high convergence, and also show the superior performance compared with the existing methods in the presence of disturbance and uncertainty.
More honour'd in the breach: predicting non-compliant behaviour through individual, situational and habitual factors

ABSTRACT A major issue in the digital age is how to safeguard the security of the massive amount of data being stored, processed and transferred through digital channels. Organisational communication research into data security shows that people are the weakest link. Non-compliant behaviour can lead to security breaches. Existing studies have focused above all on how employees can be motivated to comply with data security procedures. However, focusing on desirable behaviour does not explain why people often ignore security regulations. In addition, existing research tends to focus primarily on self-reported attitudes and perceptions, which can give a distorted impression of people’s actual behaviour. In this paper, we address these issues by combining individual, habitual and situational factors to explain non-compliant behaviour in a vignette study, using SmartPLS to analyse survey data from 651 subjects in a large Dutch government organisation. The results indicate that bad habits play a significant role in non-compliant behaviour. This behaviour is fuelled by situational factors like time pressure, while a lack of self-efficacy also increases non-compliant behaviour. Based on these results, a communication strategy that addresses bad habits in a situational context may provide an alternative way to improve people’s compliant behaviour.
Feature Extraction For Visual Speaker Authentication Against Computer-Generated Video Attacks

Recent research shows that the lip feature can achieve reliable authentication performance with a good liveness detection ability. However, with the development of sophisticated human face generation methods by the deepfake technology, the talking videos can be forged with high quality and the static lip information is not reliable in such case. Meeting with such challenge, in this paper, we propose a new deep neural network structure to extract robust lip features against human and Computer-Generated (CG) imposters. Two novel network units, i.e. the feature-level Difference block (Diffblock) and the pixel-level Dynamic Response block (DRblock), are proposed to reduce the influence of the static lip information and to represent the dynamic talking habit information. Experiments on the GRID dataset have demonstrated that the proposed network can extract discriminative and robust lip features and outperform two state-of-the-art visual speaker authentication approaches in both human imposter and CG imposter scenarios.