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Six Collembola species from five families and two orders are for the first time recorded from India. All the described new records are mainly from two states, West Bengal and Arunachal Pradesh and collected from the surveys conducted in the Eastern Himalayan Region. Sphyrotheca multifasciata (Reuter, 1881) (Sminthuridae), Sminthurinus bimaculatus Axelson, 1902 (Katiannidae), Dicranocentrus nepalensis Mari Mutt & Bhattacharjee, 1980 (Orchesellidae), Isotomurus plumosus Bagnall, 1940 (Isotomidae), Isotomurus pseudopalustris Carapelli, Frati, Fanciulli & Dallai, 2001, (Isotomidae), Willowsia jacobsoni (Börner, 1913) (Entomobryidae), are the Collembola species whose occurrence is first time observed in India. As a result of the present work Collembola fauna of India reached up to 348 species. Material examined, a brief description and microscopic images of the new records are provided in the present study.

Abstract With the tremendous increase in the number of vehicles, the dense traffic created can lead to accidents and fatalities. In a traffic system, the costs for accidents are immeasurable. Numerous studies have been carried out to predict the cost of fatal accidents but have provided the actual values. Therefore, in this study, a monkey-based modular neural system (MbMNS) is developed to identify accident cost. The accident cases and cost data were collected and preprocessed to remove the noise, and the required features were extracted using the spider monkey function. Based on the extracted features, the accidents and the costs were identified. For rail engineering, this will support evaluating the number of railroad crossing accidents with different time intervals. The impact of every accident was also measured with different cost analysis constraints, including insurance, medical, and legal and administrative costs. Therefore, the present study contributes to the field by collecting and organizing the present railroad level crossing accident data from crossing inventory dashboards. Then, the introduction of a novel MbMNS for the cost analysis is the primary contribution of this study to further enrich the railroad level crossing protection system. The third contribution is the tuning of the prediction layer of a modular neural network to the desired level to achieve the highest predictive exactness score. Hence, the designed MbMNS was tested in the Python environment, and the results were validated with regard to recall, accuracy, F-measure, precision, and error values; a comparative analysis was also conducted to confirm the improvement. The novel MbMNS recorded high accuracy of 96.29% for accident and cost analysis, which is better than that reported for other traditional methods.

Road-railroad level crossing accidents pose serious safety risks to road users, and their significant increase requires more research efforts to propose substitute solutions. Such a solution must consider the impact of intersection geometry, user perception, traffic characteristics, driver behavior, environment, and seasonal variations on accidents. This study explores the considerable number of such accidents and develops a predictive model using all the factors that influence them. For these objectives, data were collected from databases maintained by the zonal head office of the East Central Railway (ECR) in India. Data included 175 level crossings that experienced at least one accident between 2006 and 2021 in the ECR region. This study presents two accident prediction models using logistic regression and ANN for the predominant factors of accidents in the ECR zone of Indian railways. The accuracy of fatal accident prediction was 96% for logistic regression and 98% for ANN.

Two species new to science Willowsia sikkimensis sp. nov. and W. arunachalensis sp. nov., and one new record of the genus Willowsia Shoebotham, 1917 are described and illustrated here. The new species are mainly distinguished from the others on the basis of pigment pattern, scale type and chaetotaxy. The species were collected from the states of Arunachal Pradesh and Sikkim (India). Willowsia shiae Pan, Zhang & Chen, 2006 is recorded for the first time from India (Arunachal Pradesh) and redescribed with detailed chaetotaxic nomenclature. A key to the Indian species of Willowsia and a comparison table of related species are also provided.