Design of SkSP-R Plan for Popular Statistical Distributions

The design of a Skip-lot sampling plan of type SkSP-R is presented for time truncated life test for the Weibull, Exponentiated Weibull, and Birnbaum-Saunders lifetime distributions. The plan parameters of the SkSP-R plan under these three distributions are determined through a nonlinear optimization problem. Tables are also constructed for each distribution. The advantages of the proposed plan over the existing sampling schemes are discussed. Application of the proposed plan is explained with the help of an example. The Birnbaum-Saunders distribution is economically superior to other two distributions in terms of minimum average sample number

Complementarity of Semileptonic BB to K2∗(1430)K_2^*(1430) and K∗(892)K^*(892) Decays in the Standard Model with Fourth Generation

The $B\rightarrow K_{2}^{\ast}(1430)l^{+}l^{-}$ $(l=\mu,\tau)$ decays are analyzed in the Standard Model extended to fourth generation of quarks (SM4). The decay rate, forward-backward asymmetry, lepton polarization asymmetries and the helicity fractions of the final state $K^{*}_{2}(1430)$ meson are obtained using the form factors calculated in the light cone sum rules (LCSR) approach. We have utilized the constraints on different fourth generation parameters obtained from the experimental information on $K$, $B$ and $D$ decays and from the electroweak precision data to explore their impact on the $B\rightarrow K_{2}^{\ast}(1430)l^{+}l^{-}$ decay. We find that the values of above mentioned physical observables deviate deviate significantly from their minimal SM predications. We also identify a number of correlations between various observables in $B\rightarrow K_{2}^{\ast}(1430)l^{+}l^{-}$ and $B\rightarrow K^{\ast}(892)l^{+}l^{-}$ decays. Therefore a combined analysis of these two decays will compliment each other in the searches of SM4 effects in flavor physics.Comment: 28 pages, 12 figure

A Robust Deep Model for Classification of Peptic Ulcer and Other Digestive Tract Disorders Using Endoscopic Images

Accurate patient disease classification and detection through deep-learning (DL) models are increasingly contributing to the area of biomedical imaging. The most frequent gastrointestinal (GI) tract ailments are peptic ulcers and stomach cancer. Conventional endoscopy is a painful and hectic procedure for the patient while Wireless Capsule Endoscopy (WCE) is a useful technology for diagnosing GI problems and doing painless gut imaging. However, there is still a challenge to investigate thousands of images captured during the WCE procedure accurately and efficiently because existing deep models are not scored with significant accuracy on WCE image analysis. So, to prevent emergency conditions among patients, we need an efficient and accurate DL model for real-time analysis. In this study, we propose a reliable and efficient approach for classifying GI tract abnormalities using WCE images by applying a deep Convolutional Neural Network (CNN). For this purpose, we propose a custom CNN architecture named GI Disease-Detection Network (GIDD-Net) that is designed from scratch with relatively few parameters to detect GI tract disorders more accurately and efficiently at a low computational cost. Moreover, our model successfully distinguishes GI disorders by visualizing class activation patterns in the stomach bowls as a heat map. The Kvasir-Capsule image dataset has a significant class imbalance problem, we exploited a synthetic oversampling technique BORDERLINE SMOTE (BL-SMOTE) to evenly distribute the image among the classes to prevent the problem of class imbalance. The proposed model is evaluated against various metrics and achieved the following values for evaluation metrics: 98.9%, 99.8%, 98.9%, 98.9%, 98.8%, and 0.0474 for accuracy, AUC, F1-score, precision, recall, and loss, respectively. From the simulation results, it is noted that the proposed model outperforms other state-of-the-art models in all the evaluation metrics

Knowledge and attitudes about health research amongst a group of Pakistani medical students

Background Health research training is an important part of medical education. This study was conducted to assess the level of knowledge and attitudes regarding health research in a group of Pakistani medical students at Aga Khan University, Karachi. Methods It was a cross-sectional pilot study conducted among a group of Pakistani medical students. Through stratified random sampling, a pre-tested, structured and validated questionnaire was administered to 220 medical students. Knowledge and attitudes were recorded on a scale (graduated in percentages). Results Mean scores of students were 49.0% on knowledge scale and 53.7% on attitude scale. Both knowledge and attitudes improved significantly with increasing years of study in medical college [Regression coefficient 4.10 (p-value; 0.019) and 6.67 (p-value; \u3c 0.001) for knowledge and attitudes, respectively]. Conclusion Medical students demonstrate moderate level of knowledge and attitude towards health research. Intensive training in this regard is associated with significant improvement in knowledge and attitudes of students towards health research

Foliar applied proline and acetic acid improves growth and yield of wheat under salinity stress by improving photosynthetic pigments, physiological traits, antioxidant activities and nutrient uptake

Salinity stress (SS) is serious abiotic stress and a major limiting factor for crop productivity and global food security. In this context, the application of osmolytes is considered as an environmental friend approach to improve plant growth under SS. Thus, the present study was conducted to determine the impact of foliar applied proline (Pro) and acetic acid (AA) on growth, yield, physiological traits, photosynthetic pigments, ionic homeostasis and antioxidant activities of wheat under SS. The study contained SS levels 0, 6 and 12 dS m-1 and foliar spray of Pro and AA; water spray, Pro (75 mM), AA (15 mM) and AA (30 mM). The study was conducted in a completely randomized design with the factorial arrangement. Salinity stress significantly reduced wheat growth and yield, by decreasing relative water contents (-49.07%), photosynthetic pigments, free amino acids (FAA: -44.79%), total soluble proteins (TSP: -15.94%) and increasing the electrolyte leakage (EL: +27.28%), hydrogen peroxide (H2O2: +51.86%), and malondialdehyde (MDA: +36.91%) accumulation. The foliar spray of Pro and AA markedly improved the wheat growth and productivity through enhanced photosynthetic pigments, RWC, FAA, TSP, antioxidant activities (catalase: CAT, ascorbate peroxide: APX: peroxidase: POD), K+ and Ca2+ uptake and decreasing EL, MDA and H2O2 accumulation and restricted entry of toxic ions (Na+ and Cl-1).  Therefore, foliar application of AA and Pro effectively improves the growth and yield of wheat under SS by strengthening the antioxidant defense system, and maintaining ionic homeostasis and physiological performance

Suitability of various plant derived gelling agents as agar substitute in microbiological growth media

Eleven putative gelling agents were investigated as agar substitutes. These included arrowroot (Maranta arundinaceae), coconut powder (Cocos nucifera), corn flour (Zea mays var. amylacea), gel rite (a water-soluble polysaccharide produced by Sphingomonas elodea), glue (Cyanoacrylates), katira gum (Cochlospermum religiosum), guar gum (Cyamopsis tetragonolobus L.), isubgol husk (Plantago ovata), pectin and rice (Oryza sativa L.) powder. Among these, guar gum was found a promising alternate candidate for agar. Media solidified with 2.8% guar gum was transparent and supportive for the growth of three test fungi (Trichoderma harzianum, Alternaria alternata and Alternaria solani) as good as agar. Guar gum also excelled in terms of cost benefit ratio when compared with agar. Guar gum fortified media was found to cost $0.005/L as compared to agar supplemented media costing$ 1.17/L. Further, guar gum is easily available and can be added with ease thereby serving as a suitable and inexpensive substitute of agar and thus, can be adopted for routine microbiological testing in resource poor countries.Key words: Guar gum, media, agar, gelling agents

An innovative blockchain-based secured logistics management architecture:utilizing an RSA asymmetric encryption method

Purpose: The recent development in logistics due to the dawn of Logistics 4.0 has made global logistics providers more dependent on intelligent technologies. In this era, these technologies assist in data collection and transmission of logistical data and pose many security and privacy threats in logistics management systems. The customer’s private information, which is shared among the logistics stakeholders for optimal operation, faces unauthorized access due to a lack of privacy. This, amongst others, is a critical problem that needs to be addressed with blockchain. Blockchain is a disruptive technology that is transforming different sectors, and it has the potential to provide a solution to the issues mentioned above, with its unique features such as immutability, transparency, and anonymity. Method: This study designed a blockchain-based logistics management architecture on a decentralized peer-2-peer network using Ethereum smart contracts. The proposed system deployed the Rivest–Shamir–Adleman (RSA) asymmetric encryption method to protect the logistics system from cyber-attacks and secure customers’ private information from unauthorized access. Findings: Furthermore, the security and privacy of the proposed system are evaluated based on the theorem. The proof shows that the system can provide security to the logistics system and privacy to customers’ private data. The performance evaluation is based on throughput and latency. It shows that the proposed system is better than the baseline system, and the comparatives analysis shows that the proposed system is more secure and efficient than the existing systems. Implication and Limitation: The proposed system offers a better solution to the security/privacy of the logistics management system and provides recommendations to key stakeholders involved in the logistics industry while adopting blockchain technology. Apart from the study’s methodological limitation, it is also limited by a lack of reference materials

Observer–Based Control for a New Stochastic Maximum Power Point tracking for Photovoltaic Systems With Networked Control System

This study discusses the new stochastic maximum power point tracking (MPPT) control approach towards the photovoltaic cells (PCs). PC generator is isolated from the grid, resulting in a direct current (DC) microgrid that can provide changing loads. In the course of the nonlinear systems through the time-varying delays, we proposed a Networked Control Systems (NCSs) beneath an event-triggered approach basically in the fuzzy system. In this scenario, we look at how random, variable loads impact the PC generator’s stability and efficiency. The basic premise of this article is to load changes and the value matching to a Markov chain. PC generators are complicated nonlinear systems that pose a modeling problem. Transforming this nonlinear PC generator model into the Takagi–Sugeno (T–S) fuzzy model is another option. Takagi–Sugeno (T–S) fuzzy model is presented in a unified framework, for which 1) the fuzzy observer–based on this premise variables can be used for approximately in the infinite states to the present system, 2) the fuzzy observer–based controller can be created using this same premises be the observer, and 3) to reduce the impact of transmission burden, an event-triggered method can be investigated. Simulating in the PC generator model for the realtime climate data obtained in China demonstrates the importance of our method. In addition, by using a new Lyapunov–Krasovskii functional (LKF) for combining to the allowed weighting matrices incorporating mode-dependent integral terms, the developed model can be stochastically stable and achieves the required performances. Based on the T-P transformation, a new depiction of the nonlinear system is derived in two separate steps in which an adequate controller input is guaranteed in the first step and an adequate vertex polytope is ensured in the second step. To present the potential of our proposed method, we simulate it for PC generators

Can sulphur improve the nutrient uptake, partitioning, and seed yield of sesame?

Sulphur (S) is considered to improve the nutrient uptake of plants due to its synergistic relationship with other nutrients. This could ultimately enhance the seed yield of oilseed crops. However, there is limited quantitative information on nutrient uptake, distribution, and its associated impacts on seed yield of sesame under the S application. Thus, a two-year field study (2018 and 2019) was conducted to assess the impacts of different S treatments (S-0 = Control, S-20 = 20, S-40 = 40, and S-60 = 60 kg ha(-1)) on total dry matter production, nitrogen, phosphorus, potassium, S uptake and distribution at the mid-bloom stage and physiological maturity. Furthermore, treatment impacts were studied on the number of capsules per plant, number of seeds per capsule, thousand seed weight, and seed yield at physiological maturity in sesame. Compared to S-0, over the years, treatment S-40 significantly increased the total uptake of nitrogen, phosphorus, potassium, and S (by 13, 22, 11% and 16%, respectively) at physiological maturity, while their distribution by 13, 36, 14, and 24% (in leaves), 12, 15, 11, and 15% (in stems), 15, 42, 18, and 10% (in capsules), and 14, 22, 9, and 15% (in seeds), respectively. Enhanced nutrient uptake and distribution in treatment S-40 improved the total biomass accumulation (by 28%) and distribution in leaves (by 34%), stems (by 27%), capsules (by 26%), and seeds (by 28%), at physiological maturity, as compared to S-0. Treatment S-40 increased the number of capsules per plant (by 13%), number of seeds per capsule (by 11%), and thousand seed weight (by 6%), compared to S-0. Furthermore, over the years, relative to control, sesame under S-40 had a higher seed yield by 28% and enhanced the net economic returns by 44%. Thus, our results suggest that optimum S level at the time of sowing improves the nutrient uptake and distribution during the plant lifecycle, which ultimately enhances total dry matter accumulation, seed yield, and net productivity of sesame