Miracle-dz/UniFAR-FTUs huggingface dataset:
LOCAL SIMILARITY SOLUTIONS FOR UNSTEADY TWO- DIMENSIONAL FORCED CONVECTIVE HEAT AND MASS TRANSFER FLOW ALONG A WEDGE WITH THERMOPHORESIS

In this paper we have investigated the effects of thermophoresis on an unsteady two dimensional forced convective heat and mass transfer flow along a wedge. The potential flow velocity has been taken as a function of the distance x and time t. The governing time dependent non-linear partial differential equations are reduced to a set of non-linear ordinary differential equations by introducing a new class of similarity transformations. The resulting local similarity equations for unsteady flow have been solved numerically by applying Nachtsheim-Swigert shooting iteration technique along with sixth order Runge-Kutta integration scheme. Steady solutions are compared with previously published works which show excellent agreement. Numerical results for the velocity, temperature and concentration profiles as well as local skin-friction coefficient, rate of heat and mass transfer, thermophoretic velocity and thermophoretic deposition velocity for different values of unsteadiness parameter, pressure gradient parameter, Prandtl number, Schmidt number, thermophoretic coefficient, thermophoresis parameter and concentration ratio are displayed in graphically and tabulated form. The results also show that the thermophoretic particle deposition velocity decreases as the thermophoretic coefficient increases whereas it increases as the unsteadiness parameter increases.
EXPLORING THE IMPACT FACTORS TO VALUE CO-CREATION OF RESIDENTS IN DA LAT CITY

This study evaluated the factors affecting residents’ value co-creation based on their attitudes towards tourism development, community attachment, and interactions with tourists. The study was conducted using structural equation modeling to analyze data from 481 residents of Da Lat city, Lam Dong, Vietnam. The research results reveal that residents’ value cocreation is impacted by community attachment, interactions with tourists, and attitudes toward tourism development. The most impactful factor on residents’ value co-creation is their attitudes toward tourism development. However, the relationship between the residents’ interactions with tourists and their attitudes toward tourism development gives no significant results. Finally, the study proposes some managerial implications for the authorities and service providers.
Implicit Regularization of SGD via Thermophoresis

A central ingredient in the impressive predictive performance of deep neural networks is optimization via stochastic gradient descent (SGD). While some theoretical progress has been made, the effect of SGD in neural networks is still unclear, especially during the early phase of training. Here we generalize the theory of thermophoresis from statistical mechanics and show that there exists an effective entropic force from SGD that pushes to reduce the gradient variance. We study this effect in detail in a simple two-layer model, where the thermophoretic force functions to decreases the weight norm and activation rate of the units. The strength of this effect is proportional to squared learning rate and inverse batch size, and is more effective during the early phase of training when the model’s predictions are poor. Lastly we test our quantitative predictions with experiments on various models and datasets.
CDS Trading and Relationship Lending Dynamics

We investigate how the development of the credit default swap (CDS) market affects lenders’ incentives to initiate new lending relationships. We predict that hedging loan exposure through CDSs and the revelation of private information through CDS spreads reduce the adverse selection that non-relationship lenders face when competing for loans. Consistent with our expectations, we find that, following CDS initiation on a borrower’s debt, non-relationship lead arrangers are more likely to originate its loans and non-relationship participants are more likely to join loan syndicates. We also show that, following CDS initiation, non-relationship lenders pursue new borrowers with high cross-selling potential and that lenders with low loan growth or profitability are more likely to initiate new relationships. We further find that, relative to relationship lead arrangers, non-relationship lead arrangers have lower monitoring incentives following CDS initiation, as reflected by their weaker control rights and lower loan share retained. As these lower monitoring incentives exacerbate agency problems within the syndicate, the increase in the likelihood of a non-relationship participant joining the syndicate following CDS initiation is attenuated if a loan is syndicated by a non-relationship lead arranger. Overall, our findings shed light on how CDS trading affects the evolution of lending relationships.
Interpersonal Deception Theory across Qur'an 12 Narrative: Cognitive-Interpersonal Sociolinguistic Analysis

This study lies at the heart of cognitive sociolinguistics and Translation Quality Assessment (TQA). Firstly, the interpersonal deception theory representing the 'cognitive sociolinguistics dimension' is integrated with the 'translation quality assessment approach' -focusing on the interpersonal meaning as one of the three functions stated by Halliday (1973)to examine Ghali's (2003) English rendition of the Qur'anic narrative 12: Surat Joseph/Yusuf. Given the cognitive sociolinguistic origin, the deceptive process is achieved through three main stages; rationalization, evasion, and jamming. The Qur'anic narrative depicts three 'interpersonal deception' instances a long Joseph's life; when he was a child 'i.e. father deception'; when he was a young man and Zulaikha attempted to deceive both him and the folk of women; and when he became the treasurer of Egypt deceiving his brothers. Secondly, translation refers to rendering the ST linguistic features as well as their functions to the TT. The problem of equivalence (i.e. function equivalence) stems from that the rendering of the ST linguistic features and/or their functions may/not be adequate in the TT due to the target language linguistic and socio-cultural rules (House, 2015). Therefore, this study addresses the issue of representing the equivalent linguistic terms as well as the interpersonal deceptive function across the three selected deceptive instances in Surat Yusuf to figure out the textual-situational dimensions.
DC‐sputtered ZnO:Al as transparent conductive oxide for silicon heterojunction solar cells with µc‐Si:H emitter

Silicon heterojunction (SHJ) solar cells are highly interesting, because of their high efficiency and low cost fabrication. So far, the most applied transparent conductive oxide (TCO) is indium tin oxide (ITO). The replacement of ITO with cheaper, more abundant and environmental friendly material with texturing capability is a promising way to reduce the production cost of the future SHJ solar cells. Here, we report on the fabrication of the SHJ solar cells with direct current‐sputtered aluminum‐doped zinc oxide (ZnO:Al) as an alternative TCO. Furthermore, we address several important differences between ITO and the ZnO:Al layers including a high Schottky barrier at the emitter/ZnO:Al interface and a high intrinsic resistivity of the ZnO:Al layers. To overcome the high Schottky barrier, we suggest employing micro‐crystalline silicon (µc‐Si:H) emitter, which also improves temperature threshold and passivation of the solar cell precursor. In addition, we report on the extensive studies of the effect of the ZnO:Al deposition parameters including layer thickness, oxygen flow, power density and temperature on the electrical properties of the fabricated SHJ solar cells. Finally, the results of our study indicate that the ZnO:Al deposition parameters significantly affect the electrical properties of the obtained solar cell. By understanding and fine‐tuning all these parameters, a high conversion efficiency of 19.2% on flat wafer (small area (5 × 5 mm2) and without any front metal grid) is achieved. Copyright © 2014 John Wiley & Sons, Ltd.
Prognostic Impact of Monocyte to Lymphocyte Ratio in Clinical Outcome of Patients with Hepatocellular Carcinoma: A Systematic Review and Meta-analysis

Background: Lymphocyte to monocyte ratio (LMR) is a surrogate marker of systemic inflammation which is shown to be related to the patient’s survival in multiple malignancies. An important implication of this marker potentially is neoplasms in which there is no correlation between prognosis and histopathological staging and also has no reliable chemical markers associated with prognosis. Herein, this meta-analysis aimed to investigate the prognostic role of LMR in patients with hepatocellular carcinoma (HCC). Materials and Methods: In the current systemic review and meta-analysis, we conducted a systemic search of databases and indexing sources, including PubMed, EMBASE, Cochrane, Scopus, and ProQuest up to May 2019 toinclude studies on the prognostic significance of LMR on patients with HCC. Overall survival (OS), disease-free survival (DFS) and recurrence-free survival (RFS) values were extracted from the studies and analyzed. The pooled hazard ratio with a 95% confidence interval was explored to identify the prognostic value of the LMR in the survival of the patients with HCC. Results: A total of 12 studies with a total sample size of 3750 cases were included. There was significant heterogeneity among the studies; therefore, subgroup analysis was also performed. Overall analysis regarding OS showed an insignificant relationship between LMR and patient’s prognosis, dividing to subgroups based on LMR cut-offs did not yield any significant result, subgroup analysis for RFS founded statistically significant results and LMR was significantly related to DFS. Conclusion: High LMR was associated with increased DFS and RFS, in return this association was not observed for OS.
Bayesian Neural Networks For Uncertainty Estimation In Particle Accelerator Applications

Particle accelerators are used in a wide array of industrial, medical, and scientiﬁc applications. Accurate system models can be useful in experiment planning and in operation of these systems, for example, in model-based tuning schemes. To this end, machine learning is increasingly being applied for modeling particle accelerators, and neural networks are a popular choice of modeling paradigm as they can handle the large data sets and high-dimensional data that is common in this domain, such as particle beam images, spectra. However, for their deployment in high-regret and safety-critical systems, estimates of the predictive uncertainty are essential. Here we evaluate Bayesian Neural Networks to provide accurate predictions, with quantiﬁed uncertainties for particle accelerator systems. We select problems across different accelerator designs (a storage ring, a beam line for a free electron laser and an injector system). The cases also have diverse data volumes and formats, e.g. particle beam phase space images and scalar parameters. We show that Bayesian Neural Networks provide accurate predictions with reliable uncertainty estimates across diverse accelerator problems.
FARE: Enabling Fine-grained Attack Categorization under Low-quality Labeled Data

—Supervised machine learning classiﬁers have been widely used for attack detection, but their training requires abundant high-quality labels. Unfortunately, high-quality labels are difﬁcult to obtain in practice due to the high cost of data labeling and the constant evolution of attackers. Without such labels, it is challenging to train and deploy targeted countermeasures. In this paper, we propose FARE , a clustering method to enable ﬁne-grained attack categorization under low-quality labels. We focus on two common issues in data labels: 1) missing labels for certain attack classes or families; and 2) only having coarse-grained labels available for different attack types. The core idea of FARE is to take full advantage of the limited labels while using the underlying data distribution to consolidate the low-quality labels. We design an ensemble model to fuse the results of multiple unsupervised learning algorithms with the given labels to mitigate the negative impact of missing classes and coarse-grained labels. We then train an input transformation network to map the input data into a low-dimensional latent space for ﬁne-grained clustering. Using two security datasets (Android malware and network intrusion traces), we show that FARE signiﬁcantly outperforms the state-of-the-art (semi-)supervised learning methods in clustering quality/correctness. Further, we perform an initial deployment of FARE by working with a large e-commerce service to detect fraudulent accounts. With real-world A/B tests and manual investigation, we demonstrate the effectiveness of FARE to catch previously-unseen frauds.
Fostering Teamwork Quality through Managerial Coaching: Mediating Role of Psychological Engagement in Project Organizations

Teamwork quality has important implications for organizational success. Drawing upon the wellbeing and positive psychology coaching theories, managerial coaching is known to induce positive work outcomes. However, little attention is paid to explore how coaching can prompt the quality of teamwork in the context of managing contemporary projects. We examined the mechanism through which managerial coaching impacts teamwork quality in projects using a sample of 463 managers from a variety of project organizations in Pakistan. Data was collected through an online survey by adopting existing measures; managerial coaching, psychological engagement, and teamwork quality. Simple and multiple regression analyses were used to test the hypotheses. We found that workplace managerial coaching was positively associated with teamwork quality and that psychological engagement of employees partially mediated this relationship. Findings indicate that developing a culture of managerial coaching can foster a psychological climate for employee engagement if teamwork quality is a priority for project success. We recommend that project managers should develop and practice coaching skills at work to reach success.
Arbuscular mycorrhizal fungi improve the antioxidant capacity of tea (Camellia sinensis) seedlings under drought stress

A pot experiment was carried out to evaluate the response of leaf antioxidant enzyme systems to inoculation with arbuscular mycorrhizal fungus (AMF) Clariodeoglomus etunicatum in tea (Camellia sinensis cv. ‘Fuding Dabaicha’) seedlings under drought stress (DS). Root AMF colonization was significantly decreased after an eight-week soil drought treatment. Plant growth performance (plant height, stem diameter, leaf number and root biomass), leaf relative water content, and leaf water potential were notably decreased under DS conditions, whereas these variables exhibited significantly higher responses in mycorrhizal seedlings than in non-mycorrhizal seedlings. The DS treatment markedly increased leaf superoxide anion concentration but did not affect malondialdehyde content, whereas both were reasonably decreased by AMF colonization regardless of water status. The seedlings colonized by AMF showed substantially higher antioxidant enzyme activities including superoxide dismutase (SOD), catalase (CAT), guaiacol peroxidase, and ascorbate peroxidase than the non-AMF colonized seedlings under both well-watered and DS conditions. DS markedly upregulated the relative expression of CsSOD in both AMF and non-AMF seedlings and the relative expression of CsCAT in AMF seedlings. Meanwhile, AMF-colonized seedlings represent markedly higher relative expressions of CsSOD and CsCAT than non-AMF seedlings, irrespective of water status. It concludes that mycorrhizal tea plants had higher antioxidant enzyme activity and corresponding gene expression under DS, indicating a stronger ability to alleviate the oxidative damage of drought.
Relevance of Metaphysics on Functional Performance of Commercial Building Designs

This paper presents the findings of a study on the relevancy of metaphysics on functional performance of commercial building design. Similarities in principles on building design and planning practices by three major Asian cultures, the Chinese-Buddhist, IndianHindu, and Malay-Islam, are looked into. The main aim of the study was to gouge whether the selected existing building designs were in compliance with any metaphysic theories and conformance with certain an established standard commercial building design guidelines. There are 13 commercial premises owned by Government agency were selected and of these, six were categorized under “performing”, while seven were “nonperforming”. Two locally well-known commercial premises were used as “benchmark”. A combination technique done previously by others with observational procedure was devised in the analysis process. The findings reveal some evidence that metaphysics had certain influence towards functional performance of the commercial buildings and could be considered to complement the modern design practices. However, further analysis needs to be carried out involving larger number of samples and area coverage to confirm the findings of the present study.
Association between Testosterone Levels and Clinical Markers of Atherosclerosis

1.2. Material and Methods: All subjects underwent a clinical exercise stress test and data on maximal heart rate, systolic blood pressure, diastolic blood pressure; and ST-segment levels in lead augmented vector foot (lead aVF) and lead left precordial voltage 5 (lead V5) were collected. Serum testosterone levels were measured. Data on age, Body Mass Index (BMI), smoking, alcohol consumption, and family history of CardioVascular Diseases (CVD) were gathered. Men were classified into two groups: hypogonadal (testosterone ≤ 12 nmol/L), and eugonadal (testosterone > 12 nmol/L).
Data Security for IoT Using Block chain

-Internet of Things is creating new opportunities and providing a competitive advantage for different fields. One of the key challenges of IoT world is security. In this article, our attempt is to critically view the use of Block chain Technology to secure IoT. Block chain is a distributed database technology that provides very hard to tamper, ledger records. It allows storage of all transactions into immutable records and every record distributed across many participant nodes. The security comes from use of strong public key cryptography, strong cryptographic hash and complete decentralization. In this project, we develop an IoT application to monitor temperature and store it securely in the block chain. We use Raspberry Pi 3 Model B for implementing the project. The prototype can be extended to any type of application.
RELATIONSHIP AND SEARCH FOR DISCOUNTS, AND THEIR EFFECTS ON LOYALTY AND ONLINE SHOPPING, WHEN MEDIATED BY SATISFACTION AND TRUST

This study analyzes the e-commerce relationships, since it can be less humanized and characterized by the search for discounts. Marketing stablishes that the consumption relationships must be based in multiple gains and on a long-term vision. However, although virtual environment fosters economies of scale to the organizations and more attractive prices to consumers, the intensification of this process suggests that there will be only price comparisons in the long term, eroding profitability and improving spurious relationships between companies and consumers. Through structural equation modeling, this study identified that the relationships based on propension to discount lead to satisfaction and trust, more than relationship based relations, as on more human business approaches. We also identified the mediation of loyalty and trust in online consumption environment by replicating the findings in physical stores, to reinforce business to consumer relations.
From Universal School-Based Management Model to Pattern Iran's Progress-Islamic School Board of Trustees: Qualitative Analysis Dimensions and Specific Indicators to Evaluate Performance

Article Type: The basic aim of this research is from universal school-based management model to pattern Iran's progress Islamic schools Board of trustees: qualitative analysis dimensions and specific indicators to evaluate performance. According to the study, functional and in terms of subject matter and the nature of the research component of the combination is mixed. In the first phase of this study, grounded theory as a qualitative approach was used and secondly from the descriptive survey has been used as a quantitative approach. The statistical population of the study included 12 experts, policymakers and experts in the ministry of education, and in the small part, all teachers and principals of the board of trustees of five provinces (Tehran, Isfahan, Mazandaran, Khuzestan and Semnan) during the school year 2015-2016, they were employed. Due to the high number of these schools, ten managers and teachers were selected from each province based on the Krejsi-Morgan's table of 234 people (184 teachers and 50 managers) by random sampling method and selected a researcher-made questionnaire with 140 items (with Cronbach's alpha = 0.901), which was compiled based on the categories identified in the qualitative section were responding. To ensure validity, the questionnaire was examined by university professors and several key experts in education. The qualitative data research through systematic project-based coding process grounded theory of Strauss and Corbin were analyzed. In the quantitative analysis of data gathered from structural equation modeling confirmatory factor analysis was performed using SPSS and Lisrel. The results of the qualitative research findings showed that 12 indicators were identified as the main components and 38 sub categories that were identified in the assessment of the performance of the schools of the board of trustees based on the comprehensive school-based management model. The findings of the quantitative research have also shown that the two components had the greatest impact on the board of trustee's schools. P Participation with path (0.69), organizational commitment with path (0.65), flexibility with path (0.62). Original Research