Miracle-dz/UniFAR-FTUs huggingface dataset:
Development of Suitable Mitigation Strategy to Counter the Adverse Effect of Heat Stress in Wheat Varieties (Triticum aestivum L.)

Wheat is a major cereal crop of the world and one third of the world's population uses it as a staple food. However, with the changing climatic scenario and prevalence of higher temperatures, heat stress has become a major factor limiting productivity. Hence, the present study was conducted with the objective to develop suitable mitigation strategy to counter the adverse effect of heat stress. The field experiment was conducted during rabi2017-18 and rabi 2018-19 in the Division of Seed Science and Technology, ICAR Indian Agricultural Research Institute (IARI), New Delhi, India. Seven representative varieties from different zones were used for the present study. The Laboratory studies were conducted in the Division of Seed Science and Technology and Division of Genetics, ICAR-IARI, New Delhi. Heat stress was found to have a significant influence on the seed quality parameters. Germination and vigour Index, I reduced significantly under late sown conditions. Similar trend was observed for VG II. Foliar sprays with different chemicals viz. alpha tocopherol (150ppm), ascorbic acid (10ppm) + citric acid (1.3%), KCl 1%, Brassinolides (0.1ppm) and salicylic acid (200ppm) were carried out at vegetative (booting stage) and seed filling stage. Seed harvested from heat stressed environment showed a significant increase in morphological and seed quality parameters when sprayed with various foliar sprays. The result also shows that foliar spray of salicylic acid @ 200ppm and KCl 1% is effective in increasing various morphological parameter like number of seed per spike, thousand seed weight and seed quality parameter of seed. The seed germination and VG I and II were also showing increasing trends. Salicylic acid interacts with proline metabolism and ethylene formation to alleviate the adverse effects of heat stress on photosynthesis in wheat. Application of KCl results in higher potassium content, increases soluble sugar and proline content in leaf and potentials in maintaining longer green area duration with higher leaf chlorophyll that ultimately contribute to yield and quality of wheat grain and thereby might contribute to heat tolerance. Hence, all foliar sprays could successfully mitigate the effect of heat stress, however, salicylic acid @ 200ppm and KCl 1%was found to be the most effective. K e y w o r d s Proline content, Suitable mitigation strategy, Tocopherol Accepted: 15 December 2019 Available Online: 20 January 2020 Article Info Int.J.Curr.Microbiol. App.Sci (2020) 9(1): 646-653
Awareness of Aflatoxin Contamination in Feed by Dairy Farmers of Punjab

250 dairy farmers were randomly contacted in Punjab during regional kisan melas conducted by the university. They were subjected to interview schedule to study their knowledge and practices being adopted to control aflatoxin in the dairy rations. Majority of the dairy farmers(56%)belonged to middle age group. (25.6%)of the dairy farmers had high school of education and (39.2%) had experience of more than 10 years in dairy farming. Only (37.2%) dairy farmers had any formal training. (53.20%) dairy farmers had medium herd strength and mostly comprised of buffaloes (66.0%). Majority (53.6%) of dairy farmers used mobile as a source of information and only 8.8% still relied on radio. Overall dairy farmers (80.8%) had medium exposure of mass media. (58.0%) dairy farmers did not hear about of aflatoxin contamination in feed. Only (22.4%) and (16.0%) dairy farmers knew that aflatoxin can be transferred to animals and milk International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 9 Number 1 (2020) Journal homepage: http://www.ijcmas. com
The Influence of CEO Social Capital on Firm Value: Evidence from CEO Succession

Anecdotal evidence suggests that corporate boards often use information concerning a CEO’s social capital in the selection decision as it is an important heuristic for her ability. Based on prior evidence it is assumed that CEOs with high social capital will improve firm value. However, a CEO can use her social capital in ways that are detrimental to the firm. We attempt to address this conundrum by firstly examining whether the social capital of a new chief executive officer (CEO) affects firm value and secondly whether the conditions faced by the firm influence the relation between the new CEO’s social capital and firm value. We present evidence that the new CEO’s connections have a significantly positive association with the hiring firm’s market value. We also find that CEO social ties have a stronger impact on firm value when firms face greater strategic uncertainty and have an independent board in place. Our supplemental tests also show that the most valuable connections are ‘advice networks’ and cross-industry connections. Furthermore, we find that well-connected CEOs tend to spend more on R&D projects, make greater SG&A investments and generate higher gross margins. Firms also reward CEOs for their social capital.
Effectiveness of Strengthening Resilience Training Program on Patients with Substance Abuse

Background: It is necessary to identify lack of resilience as risk a factor associated with drug dependency and high risk behaviors and coping strategies against them since these variables may form a constitutive part of a health and safety management plan among people with substance abuse disorders. It was founded that, resiliency in drug abusers is lower than others and such tendency could play a critical role in addiction. This study aimed to examine the effectiveness of Strengthening Resilience training program on patients with Substance Abuse. Design: Aquasi experimental research design was utilized. Sample: purposive sample of 45 patients with drug abuse attending at the inpatient of addiction management unit at Assiut University hospital was used. Tools: Data were collected through, Personal data sheet, Pattern of drug addiction questioner & Connor-Davidson Resilience scale (CD-RISC). Results: there were significant increase in the mean scores of achievement motivation, self-confidence, tenacity, and adaptability factors in post program and one month follow up than preprogram. Conclusion: According to the data, resilience of patients were improved significantly by resilience training (P < 0.001). Recommendations: Use the training program at hospitals, centers and institutions that deal with psychological rehabilitation for drug addicts and psychotropic substances. Key Word: Resilience, Training, program, patients, Substance Abuse. -------------------------------------------------------------------------------------------------------------------------------------Date of Submission: 08-05-2019 Date of acceptance: 23-05-2019 -------------------------------------------------------------------------------------------------------------------------------------------------
A Cognitive Diagnostic Analysis of the MELAB Reading Test

With cognitive diagnostic analysis, each examinee receives a multidimensional skill profile expressing whether he/she is a master or nonmaster of each skill measured by the test. Fine-grained diagnostic feedback that facilitates teaching and learning can thus be provided to teachers and students. This study investigated cognitive diagnostic analysis as applied to the Michigan English Language Assessment Battery (MELAB) reading test. The Fusion Model (Hartz, 2002) was used to estimate examinee profiles on each reading subskill underlying the MELAB reading test. With data collected from multiple sources, such as the think-aloud protocol and expert rating, a tentative Q-matrix was initially developed to indicate the subskills required by each item. This Q-matrix was then validated via an application of the Fusion Model using data from the MELAB reading test. Four subskills were found to underlie the test, e.g., vocabulary, syntax, extracting explicit information, and understanding implicit information. Examinee skill mastery profiles were produced as the result of the cognitive diagnostic analysis. Finally, issues involved in the cognitive diagnostic analysis of reading tests were discussed, and areas for future research were also suggested. With traditional Item Response Theory (IRT) (Lord & Novick, 1968) modeling, examinees’ abilities are ordered along a continuum. Typically, a scaled score and/or a percentile rank are provided as the reported score. Results of scoring via Cognitive Diagnostic Models (CDMs) are different, however, in that examinees are assigned multidimensional skill profiles by being classified as masters versus non-masters of each skill involved in the test (DiBello, Roussos, & Stout, 2007). A typical procedure of the cognitive diagnostic analysis using CDMs is as follows: (i) identifying a set of skills involved in a test; (ii) demonstrating which skills are required for correctly answering each item in the test; (iii) estimating the profiles of skill mastery for individual examinees based on actual test performance data using the CDM; and (iv) providing score reporting and/or diagnostic feedback to examinees and other stakeholders (Lee & Sawaki, 2009b). Fine-grained diagnostic feedback can thus be provided to facilitate teaching and learning. Despite their relatively new status, CDMs have been actively applied to large-scale language tests. For instance, the Rule Space Model (Tatsuoka, 1983) has been applied to the TOEFL reading (e.g, Kasai, 1997; Scott, 1998), the TOEIC reading (Buck, Tatsuoka, & Kostin, 1997), the TOEIC listening (Buck & Tatsuoka, 1998), and the SAT Verbal (Buck et al.,
Dynamics of Secured and Unsecured Debt over the Business Cycle

Abstract This paper studies corporate debt structure over the business cycle and its implications for aggregate macroeconomic dynamics. We develop a tractable macro-finance model featuring debt heterogeneity with both secured and unsecured debt. Unlike secured debt, unsecured debt gives the lenders no access to the borrowers' assets in the event of default, and borrowers keep their assets at the cost of losing future access to the unsecured debt market. The difference in the nature of debt contracts leads to different risk taking behavior in the two debt markets. Our model generates strongly procyclical unsecured debt and weakly procyclical secured debt, in line with the stylized facts in US data. Moreover, we show that the inclusion of heterogeneous debt structures creates additional amplification effects relative to Bernanke et al. (1999) .
Defensive Repurchases: The Managerial Entrenchment

This paper examines the relation between the ex ante takeover probability and firm’s stock abnormal return and operating performance in explaining the managerial incentives for the defensive open-market share repurchase. We find a significantly negative relation between a firm’s takeover probability and its stock abnormal return and operating performance response to announcements of open-market repurchase. This evidence supports the managerial entrenchment hypothesis that repurchasing firms generate a lower performance for firms with high takeover probability. The results are more pronounced for the CEOs of repurchasing firms with larger private control benefits or with more protected by antitakeover provisions. Furthermore, these findings hold even after controlling for other potentially influential variables. Our paper provides a better understanding of the managerial incentives for announcing open-market repurchase, as well as provides a new way to explain post-repurchase long-run stock abnormal return and operating performance.
The Effect of Offshoring on Productivity and Export Growth

This paper investigates the link between offshoring and growth in productivity and export intensity utilizing novel and detailed firmand product level dataset for the Danish manufacturing sector during the period 1995-2006. By using the information on all domestic export and import transactions disaggregated by destination/origin and product code (8-digit CN), I am able to define whether a firm is an exporter or not and also separate the firms’ intra-industry imports of intermediate inputs, i.e. narrow offshoring to highor low-wage countries. The result, after controlling for potential endogeneity of the offshoring decision by using instrument variable and DiD matching approach, shows that offshoring firms experience higher growth in both productivity and export intensity as compared to firms with no offshoring activities. However, the result suggests that it is only firms that mainly offshore to high-wage countries that experience this positive effect. Firms that offshore to low-wage countries do not seem to have different effect on neither productivity nor export intensity as compared to their non-offshoring counterparts.
GLOBAL JOURNAL OF ACCOUNTING AND FINANCE

In this study, we investigate using statistical time series analysis the effect NAFTA may have had on some economic factors in Canada. These factors were GDP growth rate, unemployment rate, total export, export to and import from the US, and labor productivity. Results from the intervention time series analysis and the regression analysis with auto correlated errors did not show any significant relationship between NAFTA and any of the above economic variables. The only significant negative effect of NAFTA on total export was explained as being primarily due to the 2009 observation resulting from the 2008 great recession.
Evolving Epidemiology and Impact of Non-pharmaceutical Interventions on the Outbreak of Coronavirus Disease 2019 in Wuhan, China

BACKGROUND We described the epidemiological features of the coronavirus disease 2019 (Covid-19) outbreak, and evaluated the impact of non-pharmaceutical interventions on the epidemic in Wuhan, China. METHODS Individual-level data on 25,961 laboratory-confirmed Covid-19 cases reported through February 18, 2020 were extracted from the municipal Notifiable Disease Report System. Based on key events and interventions, we divided the epidemic into four periods: before January 11, January 11-22, January 23 - February 1, and February 2-18. We compared epidemiological characteristics across periods and different demographic groups. We developed a susceptible-exposed-infectious-recovered model to study the epidemic and evaluate the impact of interventions. RESULTS The median age of the cases was 57 years and 50.3% were women. The attack rate peaked in the third period and substantially declined afterwards across geographic regions, sex and age groups, except for children (age <20) whose attack rate continued to increase. Healthcare workers and elderly people had higher attack rates and severity risk increased with age. The effective reproductive number dropped from 3.86 (95% credible interval 3.74 to 3.97) before interventions to 0.32 (0.28 to 0.37) post interventions. The interventions were estimated to prevent 94.5% (93.7 to 95.2%) infections till February 18. We found that at least 59% of infected cases were unascertained in Wuhan, potentially including asymptomatic and mild-symptomatic cases. CONCLUSIONS Considerable countermeasures have effectively controlled the Covid-19 outbreak in Wuhan. Special efforts are needed to protect vulnerable populations, including healthcare workers, elderly and children. Estimation of unascertained cases has important implications on continuing surveillance and interventions.
Investigating the Relationship Between Board of Directors and Corporate Financial in Jordan

This study provides clear evidences indication on the association of the board of directors and the corporate financial performance. This study investigates the relationship between board of directors’ mechanism namely (board size, board independence, board meeting frequency, and CEO duality) and corporate financial performance among industrial Jordanian listed corporations on Amman stock exchange (ASE) for the period 2016-2017. Corporate financial performance is measure by Return on Asset (ROA) and Return on Equity (ROE). This study contributes to the existing literature It adds values to the existing literature by providing extensive insights of the role of the board of director and corporate financial performance. The multiple regression analysis used to test the 4 hypotheses. Corporations listed in ASE are the subjects of this study for the years 2016 and 2017. The result of the independent variable namely board size, board independence, board meeting frequency, and CEO duality affects the Return on Asset (ROA) significantly. However, there is only one independent variable namely CEO duality that is insignificantly related to Return on Asset (ROA). Furthermore, the result of multiple regression analysis indicates that there is a significant relationship between highly linked to board size, board independence, and board meeting frequency and Return on Equity (ROE). On other hand contrary, the regression analysis shows the CEO Duality to be insignificantly related to Return on Equity (ROE).
Analysis of School Leaders Licensure Assessment Content Category I-V Scores and Principal Internship Self-Assessment Scores for ISLLC Standards I-V

This study compares School Leaders Licensure Assessment (SLLA) sub-scores with principal interns’ self-assessment sub-scores (ISA) for a principal internship evaluation instrument in one educational leadership graduate program. The results of the study will be used to help establish the effectiveness of the current principal internship program, performance on the School Leaders Licensure Assessment, and provide suggestions for program improvement. The researcher compared the sub-scores for the multiple choice section of the SLLA with sub-scores from the university’s principal interns’ selfassessments to look for correlations between the two data sets. The results indicated a positive correlation in two areas of the study.
Vitamin D deficiency and its correlation with pregnancy outcome

Vitamin D also known as calciferol, is a prohormone that plays an important role in calcium homeostasis and bone health in addition to its neuromuscular functions. Vitamin D has two major forms, vitamin D2 and vitamin D3. Vitamin D in the skin should undergo hydroxylation in the liver (25OHD) hydroxylation in the kidney to 1,25 dihydroxy vitamin D. This active form is required for absorption of calcium from gut and enables bone mineralization and growth.
Socio-economic Condition of Khadia Poultry Farmers and Phenotypic Characteristics of Khadia Chickenof Northern Odisha, India

India has 72.22 per cent of its population living in rural areas and 89 per cent rural livestock householder’s rear native poultry as an important supplementary source of cash income (Khandait et al., 2011). Poultry production in India evolved from back yard venture to full-fledged poultry industry in last three decades (Reddy et al., 2015) Poultry plays an important role in human nutrition, national income, employment, and income generation in India. Meat and egg from native chicken is preferred by people because of its taste, leanness and pigmentation (Nigussie et al., 2015). Native chicken arebest known for International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 9 Number 1 (2020) Journal homepage: http://www.ijcmas. com
Controllable Orthogonalization in Training DNNs

Orthogonality is widely used for training deep neural networks (DNNs) due to its ability to maintain all singular values of the Jacobian close to 1 and reduce redundancy in representation. This paper proposes a computationally efficient and numerically stable orthogonalization method using Newton's iteration (ONI), to learn a layer-wise orthogonal weight matrix in DNNs. ONI works by iteratively stretching the singular values of a weight matrix towards 1. This property enables it to control the orthogonality of a weight matrix by its number of iterations. We show that our method improves the performance of image classification networks by effectively controlling the orthogonality to provide an optimal tradeoff between optimization benefits and representational capacity reduction. We also show that ONI stabilizes the training of generative adversarial networks (GANs) by maintaining the Lipschitz continuity of a network, similar to spectral normalization (SN), and further outperforms SN by providing controllable orthogonality.
Generating primordial features at large scales in two field models of inflation

We investigate the generation of features at large scales in the primordial power spectrum (PPS) when inflation is driven by two scalar fields. In canonical single field models of inflation, these features are often generated due to deviations from the slow-roll regime. While deviations from slow-roll can be naturally achieved in two field models due to a sharp turn in the trajectory in the field space, features at the largest scales of the types suggested by CMB temperature anisotropies are more difficult to achieve in models involving two canonical scalar fields due to the presence of isocurvature fluctuations. We show instead that a coupling between the kinetic terms of the scalar fields can easily produce such features. We discuss models whose theoretical predictions are consistent with current observations and highlight the implications of our results.
Predictive Bandits

We introduce and study a new class of stochastic bandit problems, referred to as predictive bandits. In each round, the decision maker first decides whether to gather information about the rewards of particular arms (so that their rewards in this round can be predicted). These measurements are costly, and may be corrupted by noise. The decision maker then selects an arm to be actually played in the round. Predictive bandits find applications in many areas; e.g. they can be applied to channel selection problems in radio communication systems, or in recommendation systems. In this paper, we provide the first theoretical results about predictive bandits, and focus on scenarios where the decision maker is allowed to measure at most one arm per round and the rewards are Bernoulli random variables. We derive asymptotic instance-specific regret lower bounds for these problems, and develop algorithms whose regret match these fundamental limits. We illustrate the performance of our algorithms through numerical experiments. In particular, we highlight the gains that can be achieved by using reward predictions, and investigate the impact of the noise in the corresponding measurements.
Synchronizing Probability Measures on Rotations via Optimal Transport

We introduce a new paradigm, `measure synchronization', for synchronizing graphs with measure-valued edges. We formulate this problem as maximization of the cycle-consistency in the space of probability measures over relative rotations. In particular, we aim at estimating marginal distributions of absolute orientations by synchronizing the `conditional' ones, which are defined on the Riemannian manifold of quaternions. Such graph optimization on distributions-on-manifolds enables a natural treatment of multimodal hypotheses, ambiguities and uncertainties arising in many computer vision applications such as SLAM, SfM, and object pose estimation. We first formally define the problem as a generalization of the classical rotation graph synchronization, where in our case the vertices denote probability measures over rotations. We then measure the quality of the synchronization by using Sinkhorn divergences, which reduces to other popular metrics such as Wasserstein distance or the maximum mean discrepancy as limit cases. We propose a nonparametric Riemannian particle optimization approach to solve the problem. Even though the problem is non-convex, by drawing a connection to the recently proposed sparse optimization methods, we show that the proposed algorithm converges to the global optimum in a special case of the problem under certain conditions. Our qualitative and quantitative experiments show the validity of our approach and we bring in new perspectives to the study of synchronization.