Volume 11 | Issue 9 | September-2023

 Abstract

The auto rickshaws are India's most important intermediate public transport mode (IPT). Kerala, a southern state of India also depends on this mode as a vital part of public transportation. The COVID-19 situation affects the public transport system and a corresponding drop was observed during that period in this kind of para-transit system. This work analyzes the present status of the autorickshaw-based intermediate public transport system in Kerala on the basis of its number of registrations per year by the transport authority. The trend in registration is observed and suggestions were proposed. The existing nature of the E-Auto sector in Kerala is addressed based on its challenges.

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 Keywords

Intermediate Public Transport, autorickshaws, E-autorickshaws, growth rate.

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Abstract: Objective: The goal of the current study was to assess the effects of paraquat (PQ)-induced Parkinsonism in rats and the methanolic extract of rhizomes of Acorus calamus (MEAC) on that condition. Methods: In this study, three doses of MEAC (100, 200 and 400 mg/kg p.o) and standard Madopar (10mg/kg p.o)were daily administered to rat for consecutive 28 days and Paraquat was administered once a week by intraperitoneal route for 4 consecutive weeks .The effect of extract was monitored using various behavioural ,anti-oxidant and histopathological assessments . Researchers examined how the activity of various biomarkers of oxidative stress and brain aging changed over time. Results: The optimum anti-parkinsonian activity was observed at 400mg/kg group of animals. All the behavioural parameters like Catalepsy, Akinesia, No. of falls, immobile period, tremors were significantly elevated and rearing behaviour is declined in PQ treated animals. However, a dose-dependent protection of the activities was seen in the rats after pre-treatment with MEAC. When PQ was chronically administered, the levels of reduced glutathione, glutathione reductase, glutathione peroxidase, and catalase, which are indicators of oxidative stress, considerably dropped and lipid peroxidation significantly increased, according to biochemical analyses of the brain tissue. MEAC treatment improved various biochemical indicators and reduced lipid peroxidation. Following pre-treatment of rats with MEAC, a dose-dependent protection of activities was observed. Conclusion: The In vivo studies showed a dose dependent increase in neuroprotective activity against Paraquat induced Parkinsonism. It was established that MEAC therapy effectively reduced motor deficits and protected the brain from oxidative stress.

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 Keywords

Parkinson's disease (PD), Oxidative stress, Lipid peroxidation, Catalase, Acorus calamus, Behavioural parameters, MEAC, Biochemical Parameters

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Malware detection is a critical task in cybersecurity to protect systems and networks from malicious software threats. Traditional signature- based approaches often struggle to keep up with the rapidly evolving landscape of malware. In recent years, deep learning techniques have shown promising results in detecting malware by leveraging the sequential nature of the data. This paper presents a novel approach that combines Long Short- Term Memory ( LSTM) and Gated Recurrent Unit ( GRU) networks for effective malware detection. The LSTM and GRU architectures are bot h variants of Recurrent Neural Networks ( RNNs) known for their ability to capture long- term dependencies in sequential data. By combining these architectures, the proposed method aims to leverage the complementary strengths of LSTM and GRU models for enhanced malware detection performance. The model's performance is rigorously evaluated using established metrics, including accuracy, precision, recall and F1- score. Comparisons are made wit h baseline models, including single LSTM and GRU models, as well as traditional machine learning classifiers. The results demonstrate the effectiveness of the combined LSTM and GRU ensemble model in accurately detecting malware, particularly previously unseen variants. The ensemble approach capitalizes on the diverse capabilities of LSTM and GRU networks, resulting in improved detection rates and reduced false positives. The results obtained with model accuracy of 99% are presented.

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Malware, LSTM, deep learning,GRU,RNN

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This research derives the lasting ecological consequences of colonialism on African landscapes, examining deforestation, land degradation, and cultural identity shifts. African literature emerges as a potent tool for eco-critique, conveying the environmental impacts of colonialism while celebrating the resilience of African ecosystems and communities. The study employs a positivist research philosophy, descriptive research design, and inductive research approach, collecting secondary data from sources such as Google Scholar. Three data analysis themes explored ecological impacts, eco-critical themes in literature, cultural and identity responses, literature's role in activism, and regional variations. Literature serves as a bridge between environmental issues, cultural narratives, and activism. The recommendations encourage eco-literacy, support indigenous knowledge, promote multilingual literature, amplify marginalized voices, and engage literature in eco-activism. "Colonial Shadows on Natural Landscapes" derives the transformative potential of literature in addressing environmental challenges and fostering sustainable futures in Africa.

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Colonialism, Ecology, African Literature, Postcolonial Eco-Critique, Environmental Impact, Cultural Identity, Literature and Activism

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The early prevention of crop diseases and identifyingthem at early stage is very important for crop production. The usage of fertilizers and chemicals is causing a negative effect on the agriculture eco-system and causes economic loss. A reliable method to identify and diagnose the diseases will benefit the farmers. In this paper, a new model is introduced with depthwise separable convolution architecture for tomato plant disease detection using leaf images. The models were trained and tested on a subset of publicly available plant village dataste containing six different classes of healthy and diseased leaves. These depthwise separable convolutions achieved high gain in convergence speed and the accuracy is also improved. A novel model called CNNLDD is proposed and it is compared with reduced CNNLDD model and this reduced model achieved a classification accuracy of 98.39% with fewer parameters. The satisfactory accuracy and small size of this model makes it suitable for real time crop diagnosis with less computation cost and the training time is also minimized. The standard CNN model requires a huge number of parameters, computation cost is high and also the training time is more. Standard convolution is replaced with the depth wise separable convolution in order to minimize the number of parameters and computation cost.

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Plant diseases, Deep learning, point wise convolution, convolutional neural network, depth wise convolution, classification

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This study delves into the intricate world of eco-literature to explore the subtle yet profound interplay between the human subconscious and the wilderness. Focusing on the emergence of eco-anxiety and eco-guilt as prominent psychological themes in contemporary literary characters, analyze how authors skillfully weave these emotions into their narratives, reflecting the growing societal awareness of environmental issues. These emotions add depth and relatability to characters, serving as potent vehicles for conveying the emotional nuances of our environmental consciousness. In this study, positivism research philosophy, an inductive research approach has been adopted. On the other hand, descriptive research design and secondary thematic data analysis have been used in this particular work. The wilderness itself emerges as a metaphor for the uncharted realm of the human unconscious, with characters embarking on journeys into the wild mirroring inner journeys of self-discovery and introspection. The challenges they face in the wilderness symbolize the psychological obstacles encountered when delving into the depths of the mind.

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Eco-literature, Subconscious motifs, Wilderness symbolism, Eco-anxiety, Eco-guilt, Psychological themes, Environmental consciousness

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This study explores the rich symbolism of nature, as embodied in flora and fauna, within the context of literature and art. Drawing from examples such as "The Secret Garden", discussed into how these natural elements enhance the depth and complexity of creative works, offering a universal language that resonates across cultures. This symbolism bridges the human experience with the natural world, fostering reflection on our relationship with the environment and its broader implications. Positivism research philosophy and descriptive research design has been adopted in this study. Along with this, inductive research approach and secondary thematic data analysis has also been included in this work. This research underscores the significance of nature symbolism as a catalyst for discussions surrounding environmental awareness, ecological literacy, and the need for responsible stewardship of the planet. As a recommendation, it can be proposed incorporating discussions about nature symbolism into educational curricula to promote ecological consciousness and appreciation of the natural world among students. This study illuminates the enduring connection between humanity and nature, emphasizing the importance of preserving and nurturing the environment for future generations.

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Nature symbolism, Flora and fauna, Literature, Art, 'The Secret Garden', Universal language

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An ultra-high-performance concrete (UHPC) also called as (RPC) developed years ago by Bouygues, with the aim to build strong, durable, and sustainable structures. Some differences can be underlined between the RPC and high-performance concrete (HPC); that is to say, RPC exhibits higher compressive and flexural strength, higher toughness, lower porosity, and lower permeability compared to HPC. This paper reviews the reported literature on RPC, and it offers a comparison between RPC and HPC. Therefore, some RPC potential applications may be inferred. For instance, some examples of footbridges and structural repair applications are given. Experimental measurements on air permeability, porosity, water absorption, carbonation rate, corrosion rate, and resistivity are evidence of the better performance of RPC over HPC. When these ultra-high-performance concretes are reinforced with discontinuous, short fibers, they exhibit better tensile strain-hardening performance

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UHPC, reactive powder concrete; durability; silica fume; microstructure; composites; bond strength; interfacial transition zon

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Peptic Ulcer Disease is the ulceration of the gastrointestinal tract due to hyper acidity, resulting in mucosal erosion, acute pain and discomfort. Perforated Peptic Ulcer (PPU) is a life-threatening complication of peptic ulcer disease which is observed in around 2-14% of cases of peptic ulcer disease. A total of 100 patients were enrolled for study. Maximum incidence of ulcer perforation was seen in fourth decade. The ratio of male to female was approximately 12:1. Out of 100 patients, 92 patients were found to have pre-pyloric perforation while in 08 patients, the site of perforation was found to be in first part of duodenum. Fifty-five patients were positive for helicobacter pylori while 45 patients were tested negative. H.Pylori associated PUD is reported to be the commonest cause of morbidity and mortality, in especially LMIC nations. It is also one of the commonest abdominal emergency causing peritonitis. The outcome is multi-factorial depending on various factors like the underlying pathology, any co-morbid condition, the interval between perforation and treatment and the patient's age.

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Peptic ulcer disease, PPU, Perforation, Vagotomy, SSI.

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Evacuation of CO2, CH4, and N2O from air and partition of CO2 from CH4 are significant division processes in energy creation and ecological assurance. These divisions can be accomplished in pressure swing adsorption processes assuming reasonable adsorbents with adequately huge selectivity and adsorption limit can be distinguished. Assessment of different adsorbents for their balance and dynamic properties is a powerful method for evaluating reasonable adsorbents for these applications; it additionally adds to better comprehension of essentials of adsorption processes.

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 Keywords

MOF, ZEOLITE , MOF-177

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