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The Partition of the Indian Subcontinent in 1947 unleashed unprecedented violence. In Feminist Fiction and the Indian Partition of 1947, Indian scholar Priyanka Gupta explores how women were doubly suppressed and victimized before and after the partition. The violence, and the displacement of large populations, made this historical episode of separation more and more significant for women. Novels set during the Partition offer unique viewpoints and perspectives that have not previously been explored.

Planning a rapid eye movement (saccade) changes how we perceive our visual world. Even before we move the eyes visual discrimination sensitivity improves at the impending target of eye movements, a phenomenon termed “presaccadic attention.” Yet, it is unknown if such presaccadic selection merely affects perceptual sensitivity, or also affects downstream decisional processes, such as choice bias. We report a surprising lack of presaccadic perceptual benefits in a common, everyday setting—detection of changes in the visual field. Despite the lack of sensitivity benefits, choice bias for reporting changes increased reliably for the saccade target. With independent follow-up experiments, we show that presaccadic change detection is rendered more challenging because percepts at the saccade target location are biased toward, and more precise for, only the most recent of two successive stimuli. With a Bayesian model, we show how such perceptual and choice biases are crucial to explain the effects of saccade plans on change detection performance. In sum, visual change detection sensitivity does not improve presaccadically, a result that is readily explained by teasing apart distinct components of presaccadic selection. The findings may have critical implications for real-world scenarios, like driving, that require rapid gaze shifts in dynamically changing environments.

The third gender refers to people who are exclusively masculine or feminine, but cannot be completely identified as male or female. In India, the third gender community is an important part of the society, but they face serious discrimination and harassment, including oral torture, physical and sexual violence, false arrest, ancestral property, services and admission to educational institutions. The goal of the Indian Constitution is to provide equal opportunity and rights to each citizen, but in the context of converts, this is not a reality. The amended transgender Persons (Protection of Rights) Act of India in 2019 is to tackle constitutional rights, gender identity recognition and anti -anti-discriminatory regulations in institutional settings such as family, employment, school and health care. However, the law lacks practical support and policies to earn proper rights. Writers have suggested a number of proposals to eliminate these gaps, including increasing the proportion of non-generous people in the discussion position, increasing educational fairness, providing transitional-specific training for healthcare practitioners, alignment in the family and supervising in public places. International Transformation Visibility Day respects the courage to transformative and non-generous people who disobey different social rules.  

Aim/Purpose: This paper focuses on designing and implementing the rubric for objective JAVA programming assessments. An unsupervised learning approach was used to group learners based on their performance in the results obtained from the rubric, reflecting their learning ability. Background: Students' learning outcomes have been evaluated subjectively using a rubric for years. Subjective assessments are simple to construct yet inconsistent and biased to evaluate. Objective assessments are stable, reliable, and easy to conduct. However, they usually lack rubrics. Methodology: In this study, a Top-Down assessment approach is followed, i.e., a rubric focused on the learning outcome of the subject is designed, and the proficiency of learners is judged by their performance in conducting the task given. A JAVA rubric is proposed based on the learning outcomes like syntactical, logical, conceptual, and advanced JAVA skills. A JAVA objective quiz (with multiple correct options) is prepared based on the rubric criteria, comprising five questions per criterion. The examination was conducted for 209 students (100 from the MCA course and 109 from B.Tech. course). The suggested rubric was used to compute the results. K-means clustering was applied to the results to classify the students according to their learning preferences and abilities. Contribution: This work contributes to the field of rubric designing by creating an objective programming assessment and analyzing the learners’ performance using machine learning techniques. It also facilitates a reliable feedback approach offering various possibilities in student learning analytics. Findings: The designed rubric, partial scoring, and cluster analysis of the results help us to provide individual feedback and also, group the students based on their learning skills. Like on average, learners are good at remembering the syntax and concepts, mediocre in logical and critical thinking, and need more practice in code optimization and designing applications. Recommendations for Practitioners: The practical implications of this work include rubric designing for objective assessments and building an informative feedback process. Faculty can use this approach as an alternative assessment measure. They are the strong pillars of e-assessments and virtual learning platforms. Recommendation for Researchers: This research presents a novel approach to rubric-based objective assessments. Thus, it provides a fresh perspective to the researchers promising enough opportunities in the current era of digital education. Impact on Society: In order to accomplish the shared objective of reflective learning, the grading rubric and its accompanying analysis can be utilized by both instructors and students. As an instructional assessment tool, the rubric helps instructors to align their pedagogies with the students’ learning levels and assists students in updating their learning paths based on the informative topic-wise scores generated with the help of the rubric. Future Research: The designed rubric in this study can be extended to other programming languages and subjects. Further, an adaptable weighted rubric can be created to execute a flexible and reflective learning process. In addition, outcome-based learning can be achieved by measuring and analyzing student improvements after rubric evaluation.

Metabolic dysfunction-associated steatotic liver disease (MASLD), previously known as non-alcoholic fatty liver disease (NAFLD), is the most common liver disorder worldwide, with an estimated global prevalence of more than 31%. Metabolic dysfunction-associated steatohepatitis (MASH), formerly known as non-alcoholic steatohepatitis (NASH), is a progressive form of MASLD characterized by hepatic steatosis, inflammation, and fibrosis. This review aims to provide a comprehensive analysis of the extrahepatic manifestations of MASH, focusing on chronic diseases related to the cardiovascular, muscular, and renal systems. A systematic review of published studies and literature was conducted to summarize the findings related to the systemic impacts of MASLD and MASH. The review focused on the association of MASLD and MASH with metabolic comorbidities, cardiovascular mortality, sarcopenia, and chronic kidney disease. Mechanistic insights into the concept of lipotoxic inflammatory “spill over” from the MASH-affected liver were also explored. MASLD and MASH are highly associated (50%–80%) with other metabolic comorbidities such as impaired insulin response, type 2 diabetes, dyslipidemia, hypertriglyceridemia, and hypertension. Furthermore, more than 90% of obese patients with type 2 diabetes have MASH. Data suggest that in middle-aged individuals (especially those aged 45–54), MASLD is an independent risk factor for cardiovascular mortality, sarcopenia, and chronic kidney disease. The concept of lipotoxic inflammatory “spill over” from the MASH-affected liver plays a crucial role in mediating the systemic pathological effects observed. Understanding the multifaceted impact of MASH on the heart, muscle, and kidney is crucial for early detection and risk stratification. This knowledge is also timely for implementing comprehensive disease management strategies addressing multi-organ involvement in MASH pathogenesis.

Abiotic stresses are the foremost limiting factors for agricultural productivity. Crop plants need to cope up adverse external pressure created by environmental and edaphic conditions with their intrinsic biological mechanisms, failing which their growth, development, and productivity suffer. Microorganisms, the most natural inhabitants of diverse environments exhibit enormous metabolic capabilities to mitigate abiotic stresses. Since microbial interactions with plants are an integral part of the living ecosystem, they are believed to be the natural partners that modulate local and systemic mechanisms in plants to offer defense under adverse external conditions. Plant-microbe interactions comprise complex mechanisms within the plant cellular system. Biochemical, molecular and physiological studies are paving the way in understanding the complex but integrated cellular processes. Under the continuous pressure of increasing climatic alterations, it now becomes more imperative to define and interpret plant-microbe relationships in terms of protection against abiotic stresses. At the same time, it also becomes essential to generate deeper insights into the stress-mitigating mechanisms in crop plants for their translation in higher productivity. Multi-omics approaches comprising genomics, transcriptomics, proteomics, metabolomics and phenomics integrate studies on the interaction of plants with microbes and their external environment and generate multi-layered information that can answer what is happening in real-time within the cells. Integration, analysis and decipherization of the big-data can lead to a massive outcome that has significant chance for implementation in the fields. This review summarizes abiotic stresses responses in plants in-terms of biochemical and molecular mechanisms followed by the microbe-mediated stress mitigation phenomenon. We describe the role of multi-omics approaches in generating multi-pronged information to provide a better understanding of plant-microbe interactions that modulate cellular mechanisms in plants under extreme external conditions and help to optimize abiotic stresses. Vigilant amalgamation of these high-throughput approaches supports a higher level of knowledge generation about root-level mechanisms involved in the alleviation of abiotic stresses in organisms.

Listeria monocytogenes is a serious public health hazard responsible for the foodborne illness listeriosis. L. monocytogenes is ubiquitous in nature and can become established in food production facilities, resulting in the contamination of a variety of food products, especially ready-to-eat foods. Effective and risk-based environmental monitoring programs and control strategies are essential to eliminate L. monocytogenes in food production environments. Key elements of the environmental monitoring program include (i) identifying the sources and prevalence of L. monocytogenes in the production environment, (ii) verifying the effectiveness of control measures to eliminate L. monocytogenes, and (iii) identifying the areas and activities to improve control. The design and implementation of the environmental monitoring program are complex, and several different approaches have emerged for sampling and detecting Listeria monocytogenes in food facilities. Traditional detection methods involve culture methods, followed by confirmation methods based on phenotypic, biochemical, and immunological characterization. These methods are laborious and time-consuming as they require at least 2 to 3 days to obtain results. Consequently, several novel detection approaches are gaining importance due to their rapidness, sensitivity, specificity, and high throughput. This paper comprehensively reviews environmental monitoring programs and novel approaches for detection based on molecular methods, immunological methods, biosensors, spectroscopic methods, microfluidic systems, and phage-based methods. Consumers have now become more interested in buying food products that are minimally processed, free of additives, shelf-stable, and have a better nutritional and sensory value. As a result, several novel control strategies have received much attention for their less adverse impact on the organoleptic properties of food and improved consumer acceptability. This paper reviews recent developments in control strategies by categorizing them into thermal, non-thermal, biocontrol, natural, and chemical methods, emphasizing the hurdle concept that involves a combination of different strategies to show synergistic impact to control L. monocytogenes in food production environments.

PurposeThe relationship between the various existing smell taxonomies and the smell impacting factors has been established. The ideology is to identify the most critical smell influencing factors in the vicinity of various software development environments.Design/methodology/approachTo fulfill the said task, the utilization of the amalgamation of two multicriteria decision-making techniques, namely, Entropy method and CODAS method, is presented.FindingsThrough this article, the most critical smell impacting criteria with respect to the smell taxonomies is identified. Furthermore, the behaviour of 4 software development principles was then analysed, and their working state has been successfully assessed.Originality/valueThe ideology to study design-related smells in the software system has been studied by a lot of researchers. Some of them have worked upon their detection and the corresponding refactoration process with the help of several algorithms like machine learning and artificial intelligence. But how and to what extent these design-related smells impact the software development environment has remained out of the limelight till now. Through this article, this research gap has been identified, and an attempt to fill it has been made.

Rapid advances in the fields of genetics and genomics after the discovery of Mendel’s laws of inheritance have led to map many genes/QTL controlling qualitative and quantitative traits in plant species. Mapping of genomic regions controlling the variation of quantitatively inherited traits has become routine with the abundance of polymorphic molecular markers. Recently, the next generation sequencing methods have accelerated research on QTL mapping using both linkage and association mapping approaches. These efforts have led to identification of closely linked markers with gene/QTLs and identified markers even within the gene/QTL controlling the trait of interest. Some of the notable successes of utilizing major QTL in cultivar development include Fhb1 for Fusarium head vlight ressitance in wheat, Sub1 for submergence tolereance in rice and major QTL for resistance to cyst nematode in soybean. Efforts have also directed towards cloning of gene/QTLs for identification of potential candidate genes responsible for a trait. New concepts such as crop QTLome and QTL prioritization hold promise to accelerate the precise application of QTL for genetic improvement of complex traits in crop plants. In the present article, we reviewed QTL mapping approaches from identification to exploitation in plant breeding programs, and introgression of favourable QTL alleles through marker assisted breeding for improving productivity in major crops.

PurposeThe ideology of this article is to study the performance concerns of SDN Controllers, with the help of developed SRGM and thereby obtain its optimal testing duration. The effect of undetected uncertainty in the parameter values have also been catered in the proposal.Design/methodology/approachThese uncertainties in the parameter values are studied as the risk of not meeting desired set of requirements, whose removal causes additional cost. Considering these two constructs as attributes of MAUT, the controller's optimal testing duration is obtained.FindingsThe article focuses towards obtaining the optimal duration for which the SDN Controllers must be tested. It was observed that the inculcation of risk-attribute has provided the higher utility value as compared to any other existing scenarios.Originality/valuePlenty of SRGM have been proposed in the literature which talks about the testing stop time determination problems. But, none of them have considered the impact of risk of not meeting the requirements (reliability) along with cost to obtain its testing stop time. Further, validation of the proposed model in presented with the help of two releases versions of SDN controller platform, ONOS, entitled as “Kingfisher” and “Loon” and has acquired promising results.