Ecological impact of heavy metals on aquatic environment with reference to fish and human health

Heavy metals have a high density that is harmful even in low quantity. These metals enter aquatic habitats through various sources, home effluents, including industrial waste, atmospheric sources, and other metal-based businesses, as well as E-Waste. Heavy metal pollution is responsible for degenerating aquatic species, creating physical abnormalities in creatures and contaminating the aquatic environment. These poisonous heavy metals cause a variety of fish ailments like decrease in hatching rate, teratogenesis and bioaccumulation in the tissues etc. The contamination of heavy metals in aquatic bodies and ecosystems has a significant influence on the food chain. Because fish people consume fish, it has an indirect impact on their health. These heavy metals also have a higher impact on the environment because they remain for longer periods and have bio-accumulative capabilities, leading water health to deteriorate. This study offers insight into the disruption of fish and human physiology, their reproductive ability by heavy metals. This review provides baseline data on the heavy metals and aquatic environment, especially fish and human health. The data will increase sensitivity to preventing and managing aquatic environmental pollution, particularly heavy metal contamination

Community composition and status of avian diversity at Campus and Agricultural landscapes of Chaudhary Charan Singh Haryana Agricultural University, Hisar (Haryana)

Avian species diversity and their assemblage are responsible for maintaining the integrity and health of any ecosystem. Documentation of avian diversity in different habitats is sensitive tool for monitoring the environmental condition. The present investigation aimed to record the diversity of avian fauna at the main campus and agricultural landscapes of Chaudhary Charan Singh Haryana agricultural University, Hisar (Haryana). Line transect and point count methods were used to taking observations on different species of birds. A total of 101 bird species under 17 orders 43 families and 86 genera were recorded; out of them, 78, 17, 5 and one species were resident, winter migrant, summer migrant and passage migrant, respectively. Species richness of order Passeriformes was highest, followed by Pelecaniformes and Muscicapidae, the most diverse family in the study area. Analysis of food and feeding guilds revealed that the insectivorous guild is predominant, followed by Omnivore, Carnivore, Granivore, Frugivore and Nectarivore. Out of the total observed species, 23 have declining population trends at global level, whereas three species (Alexandrine Parakeet, Asian Woollyneck, Black-headed ibis) are listed as Near Threatened and Common Pochard is vulnerable as per IUCN Red List. The species richness was significantly higher in farmland, followed by main campus and experimental orchards. Jaccard’s similarity index between habitats revealed that the main campus and farmland area has a maximum (0.73) similarity in bird communities. This emphasises the significance of these study sites as key habitats for bird species of conservation priorities

A cybersecurity approach for improved system resilience

The ongoing digitalisation of industrial systems is bringing new challenges in managing, monitoring, and predicting the overall reliability performance. The overall reliability of a cyber-physical system, such as railways, is highly influenced by the level of resilience in its inherent digital items. The objective of this paper is to propose a systematic approach, based on an enhanced Cyber Kill Chain model, to improve the overall system resilience through monitoring and prediction. The proposed cybersecurity approach can be used to assess the future cyberattack penetration probabilities based on the present security controls. With the advancement in cybersecurity defensive controls, cyberattacks have continued to evolve through the exploitation of vulnerabilities within the cyber-physical systems. Assuming the possibility of a cyberattack it is necessary to select appropriate security controls so that this attack can be predicted, prevented, or detected before any catastrophic consequences to retain the resilience of the system. Insufficient cybersecurity in the context of cyber-physical systems, such as railways, might have a fatal effect on the whole system availability performance and sometimes may lead to safety risks. However, to improve the overall resilience of a cyber-physical system there is a need of a systematic approach to continuously monitor, predict, and manage the health of the system’s digital items with respect to security. Furthermore, the paper will provide a case-study description in railway sector, which has been used for the verification of the proposed approach.ISBN för värdpublikation: 978-981-18-5183-4</p

A Human-Centric Model for Sustainable Asset Management in Railway: A Case Study

The ongoing digital transformation is changing asset management in the railway industry. Emerging digital technologies and Artificial Intelligence is expected to facilitate decision-making in management, operation, and maintenance of railway by providing an integrated data-driven and model-driven solution. An important aspect when developing decision-support solutions based on AI and digital technology is the users’ experience. User experience design process aims to create relevance, context-awareness, and meaningfulness for the end-user. In railway contexts, it is believed that applying a human-centric design model in the development of AI-based artefacts, will enhance the usability of the solution, which will have a positive impact on the decision-making processes. In this research, the applicability of such advanced technologies i.e., Virtual Reality, Mixed Reality, and AI have been reviewed for the railway asset management. To carry out this research work, literature review has been conducted related to available Virtual Reality/Augmented Reality/Mixed Reality technologies and their applications within railway industry. It has been found that these technologies are available, but not applied in railway asset management. Thus, the aim of this paper is to propose a human-centric design model for the enhancement of railway asset management using Artificial Intelligence, Virtual Reality, and Mixed Reality technologies. The practical implication of the findings from this work will benefit in increased efficiency and effectiveness of the operation and maintenance processes in railway

A Human-Centric Model for Sustainable Asset Management in Railway: A Case Study

The ongoing digital transformation is changing asset management in the railway industry. Emerging digital technologies and Artificial Intelligence is expected to facilitate decision-making in management, operation, and maintenance of railway by providing an integrated data-driven and model-driven solution. An important aspect when developing decision-support solutions based on AI and digital technology is the users&rsquo; experience. User experience design process aims to create relevance, context-awareness, and meaningfulness for the end-user. In railway contexts, it is believed that applying a human-centric design model in the development of AI-based artefacts, will enhance the usability of the solution, which will have a positive impact on the decision-making processes. In this research, the applicability of such advanced technologies i.e., Virtual Reality, Mixed Reality, and AI have been reviewed for the railway asset management. To carry out this research work, literature review has been conducted related to available Virtual Reality/Augmented Reality/Mixed Reality technologies and their applications within railway industry. It has been found that these technologies are available, but not applied in railway asset management. Thus, the aim of this paper is to propose a human-centric design model for the enhancement of railway asset management using Artificial Intelligence, Virtual Reality, and Mixed Reality technologies. The practical implication of the findings from this work will benefit in increased efficiency and effectiveness of the operation and maintenance processes in railway

Heavy metal toxicity in earthworms and its environmental implications: A review

Earthworms are important soil organisms, contributing to many beneficial ecological services that can be harmed by heavy metal contamination. Because of their permeable skin and constant contact with soil through their digestive tract, they are extremely sensitive to soil contamination. Heavy metals get bioaccumulated in their bodies and cause major health problems. In this review, we describe the findings of various studies on the toxicity of heavy metals to earthworms, mechanisms of toxicity, detoxification responses and consequences on the environment. Heavy metals have deleterious impact on earthworms at all levels of organization, including inhibiting enzyme activities, causing DNA damage, reducing survival, growth and cocoon production, altering behavior and reducing total earthworm community diversity and biomass. These negative effects of heavy metals on earthworms can have disproportionate adverse consequences for community stability as well as serious ecological consequences for the entire terrestrial ecosystem. So, heavy metal pollution of soil poses a serious threat to earthworms, reducing their activity and posing a risk to the environment and human health

Measurement of Ds + production and nuclear modification factor in Pb-Pb collisions at √sNN = 2.76 TeV

The production of prompt D s + mesons was measured for the first time in collisions of heavy nuclei with the ALICE detector at the LHC. The analysis was performed on a data sample of Pb-Pb collisions at a centre-of-mass energy per nucleon pair, sNN−−−√ , of 2.76 TeV in two different centrality classes, namely 0–10% and 20–50%. D s + mesons and their antiparticles were reconstructed at mid-rapidity from their hadronic decay channel D s +  → ϕπ +, with ϕ → K−K+, in the transverse momentum intervals 4 < p T < 12GeV/c and 6 < p T < 12 GeV/c for the 0–10% and 20–50% centrality classes, respectively. The nuclear modification factor R AA was computed by comparing the p T-differential production yields in Pb-Pb collisions to those in proton-proton (pp) collisions at the same energy. This pp reference was obtained using the cross section measured at s√=7 TeV and scaled to s√=2.76 TeV. The R AA of D s + mesons was compared to that of non-strange D mesons in the 10% most central Pb-Pb collisions. At high p T (8 < p T < 12 GeV/c) a suppression of the D s + -meson yield by a factor of about three, compatible within uncertainties with that of non-strange D mesons, is observed. At lower p T (4 < p T < 8 GeV/c) the values of the D s + -meson R AA are larger than those of non-strange D mesons, although compatible within uncertainties. The production ratios D s + /D0 and D s + /D+ were also measured in Pb-Pb collisions and compared to their values in proton-proton collisions