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Conversion efficiency, power production, and cost of PV panels’ energy are remarkably impacted by external factors including temperature, wind, humidity, dust aggregation, and induction characteristics of the PV system such as tilt angle, altitude, and orientation. One of the prominent elements affecting PV panel performance and capability is dust. Nonetheless, dust features including size, shape, type, etc. are geologically known. Several mitigation methods have been studied for the reduction of dust concentration on the exterior face of the PV modules. The outcomes have demonstrated that dust concentration and pollutants remarkably affect the PV panel energy production. This paper reviews the recently developed research on the outcomes of the dust effect on PV panels in different locations and meets the needs of future research on this subject. Moreover, different cleaning methods that could be advantageous for future researchers in opting for the most applicable technique for dust removal are reviewed.

Human-elephant conflict (HEC) is a severe conservation, socio-economic and environmental issue of forests and ecosystems in elephant inhabiting countries, including Sri Lanka. Due to the rapid growth of human and elephant populations, both struggles to share limited land resources. The major causes and contexts of HEC in Sri Lanka include land use change, habitat loss due to human population growth, crop raiding behavior, problem elephants, and changes in agriculture practices. Since 2019, 125 people and 370 elephants have killed annually on average due to the conflict. Also, Sri Lanka has recorded the highest annual elephant deaths and second-highest human deaths due to HEC. The human death rate has increased by approximately 42% over previous three decades. The Sri Lankan government provides compensation for death and disability of the human caused by elephants and for elephant-damaged houses or properties. The Sri Lankan elephant (Elephas maximus maximus) is an endangered subspecies. It’s home range is restricted to 50–150 km2 and depends on the availability of food, water, and shelter of the habitat in which they live. Various management strategies have been developed by the government and villagers to prevent and mitigate HEC. Today, Sri Lankan elephants are protected under Sri Lankan law, with punishment by fines and jail terms. This article reviews the history, present status, and traditional conflict management of HEC in Sri Lanka. We suggest a satellite data fusion approach with GIS modeling to identify risk zones of HEC to develop further protective measures for humans and elephants.

Climate change can negatively affect crop productivity decreasing food production in many regions across the world. Literature suggests forest carbon sequestration (FCS) is a good alternative to mitigate climate change due to its ability to sequester carbon at low cost. Nevertheless, FCS subsidies have not been addressed together with impacts on food security and climate change reduced crop yields. In our multidisciplinary work, we collected the crop yield shocks from global circulation—crop modeling. We also developed a new version of a computable general equilibrium model for the economic analysis. Thus, we evaluate the global economic impacts of using carbon taxes and FCS to achieve 50% emission reductions. We find that implementing an aggressive FCS incentive can cause substantial increases in food prices because of land competition between forest and crop production. Without climate induced yield reductions, FCS is attractive, but not with the yield reductions. With the climate induced yield shocks, food price increases are huge—so large that it is clear this approach could not be adopted in the real world. The results cry out for investment in agricultural research on climate adaptation. Our findings suggest economic well-being falls more without mitigation than with 50% emission reductions.

With the development of Software Defined Networking (SDN), its security is becoming increasingly important. Since SDN has the characteristics of centralized management and programmable, attackers can easily take advantage of the security vulnerabilities of SDN to carry out distributed denial of service (DDoS) attacks, which will cause the memory of controllers and switches to be occupied, network bandwidth and server resources to be exhausted, affecting the use of normal users. To solve this problem, this paper designs and implements an online attack detection and mitigation SDN defense system. The SDN defense system consists of two modules: anomaly detection module and mitigation module. The anomaly detection model uses a lightweight hybrid deep learning method—Convolutional Neural Network and Extreme Learning Machine (CNN-ELM) for anomaly detection of traffic. The mitigation model uses IP traceback to locate the attacker and effectively filters out abnormal traffic by sending flow rule commands from the controller. Finally, we evaluate the SDN defense system. The experimental results show that the SDN defense system can accurately identify and effectively mitigate DDoS attack flows in real-time.

Methane (CH4) emission, which is mainly produced during normal fermentation of feeds by the rumen microorganisms, represents a major contributor to the greenhouse gas (GHG) emissions. Several enteric CH4 mitigation technologies have been explored recently. A number of new techniques have also been developed and existing techniques have been improved in order to evaluate CH4 mitigation technologies and prepare an inventory of GHG emissions precisely. The aim of this review is to discuss different CH4 measuring and mitigation technologies, which have been recently developed. Respiration chamber technique is still considered as a gold standard technique due to its greater precision and reproducibility in CH4 measurements. With the adoption of recent recommendations for improving the technique, the SF6 method can be used with a high level of precision similar to the chamber technique. Short-term measurement techniques of CH4 measurements generally invite considerable within- and between-animal variations. Among the short-term measuring techniques, Greenfeed and methane hood systems are likely more suitable for evaluation of CH4 mitigation studies, if measurements could be obtained at different times of the day relative to the diurnal cycle of the CH4 production. Carbon dioxide and CH4 ratio, sniffer, and other short-term breath analysis techniques are more suitable for on farm screening of large number of animals to generate the data of low CH4-producing animals for genetic selection purposes. Different indirect measuring techniques are also investigated in recent years. Several new dietary CH4 mitigation technologies have been explored, but only a few of them are practical and cost-effective. Future research should be directed toward both the medium- and long-term mitigation strategies, which could be utilized on farms to accomplish substantial reductions of CH4 emissions and to profitably reduce carbon footprint of livestock production systems. This review presents recent developments and critical analysis on different measurements and dietary mitigation of enteric CH4 emissions technologies.

IRNSS/NavIC is an independent navigation system developed by India. The dependence on external satellite-based navigation systems is gradually decreasing as a result of the deployment of our own navigation system, IRNSS/NavIC, which exhibits enhanced reliability. In this paper, a software-based IRNSS/NavIC receiver is developed using the standard Signal-In-Space Interface Control Document as a reference for signal structure, subframe patterns and parameter calculations. The IRNSS/NavIC receiver is validated with the I/Q data file as input which is generated by software based IRNSS/NavIC simulator. Analysis of the effect of a specific error on receiver output position necessitates repeated trials and modification, or in some cases, the development of new algorithms. The intermediate stage data can be viewed or stored as needed; a few examples are provided. In this paper Squared Correlators Code Discriminator (SCCD), a new multipath mitigation method has been designed and developed for IRNSS/NavIC receiver. The SCCD method is derived from Strobe Correlator (SC) and Combination of squared correlator method (CSC). The pseudorange bias is investigated and eliminated from the SCCD approach. The performance parameters of the IRNSS/NavIC receiver using each of the four approaches are compared, and the outcomes are discussed.

Renewable penetration, particularly the increasing deployment of PV by residential customers, organizations, and utilities, is leading to the rapid evolution of the power grid. However, the power system’s architectural changes affect the quality of supply and give rise to power quality issues such as harmonics, fluctuations, disturbances, etc., at the point of common coupling (PCC). Therefore, in this work, a power network was modeled to study the impact of PV systems on PCC. At first, a detailed review is presented for on-grid PV systems with different inverter topologies, control techniques, sources of harmonic generation, and their mitigation strategies. After that, several use cases considering various sources of harmonics in a network with on-grid PV are modeled and simulated using MATLAB/Simulink. In-depth research was performed in this work to examine the many variables that affect harmonics, such as solar radiation levels, controller tuning, and load changes. Results with a real-time simulation platform (OPAL-RT) are presented in this paper for several use cases. Lastly, comprehensive discussions are presented from the acquired offline and real-time simulation results.

Antimicrobial contamination and antimicrobial resistance have become global environmental and health problems. A large number of antimicrobials are used in medical and animal husbandry, leading to the continuous release of residual antimicrobials into the environment. It not only causes ecological harm, but also promotes the occurrence and spread of antimicrobial resistance. The role of environmental factors in antimicrobial contamination and the spread of antimicrobial resistance is often overlooked. There are a large number of antimicrobial-resistant bacteria and antimicrobial resistance genes in human beings, which increases the likelihood that pathogenic bacteria acquire resistance, and also adds opportunities for human contact with antimicrobial-resistant pathogens. In this paper, we review the fate of antimicrobials and antimicrobial resistance in the environment, including the occurrence, spread, and impact on ecological and human health. More importantly, this review emphasizes a number of environmental factors that can exacerbate antimicrobial contamination and the spread of antimicrobial resistance. In the future, the timely removal of antimicrobials and antimicrobial resistance genes in the environment will be more effective in alleviating antimicrobial contamination and antimicrobial resistance.

Cybersickness (CS) is a pressing issue in virtual reality (VR) systems. While various mitigation methods (MMs) have been developed to counteract CS, their effects on human behavior remain largely unexplored, raising concerns about their potential applications. Using Jens Rasmussen’s skill–rule–knowledge (SRK) model as a framework, our study investigated the effects of two widely adopted MMs—dynamic field of view and dynamic blurring—in VR. We compared these methods to a baseline condition where no MM was applied. We designed three VR tasks that align with the behavioral levels of the SRK model. In a within-subject study (N = 22), participants completed each task using these MMs. We measured task performance, CS symptoms, and locomotion control. Additionally, qualitative feedback was collected. Our results revealed that neither MM significantly alleviated CS across different VR scenarios. Furthermore, while some participants found MMs helpful, a larger portion reported visual hindrances, and a significant performance drop was measured in the skill-based task. More critically, participants indicated behavioral adaptations in response to the MMs, including changes in locomotion strategies and viewing behavior. Potential causes and implications were discussed. In conclusion, MMs offer promise, but their application necessitates a nuanced understanding of their impacts. We recommend a context-sensitive approach when designing and integrating MMs, prioritizing both maximizing CS mitigation and minimizing interference with the natural behaviors of users.

Livestock ranching overlaps extensively with jaguar and puma distribution in the Casanare Department of east-central Colombia. Conservation programs prioritize large carnivores in the region. Ranchers retaliate by killing them in response to economic losses or fear related to their presence. Reducing retaliatory hunting is a top priority in the conservation of feline species. Predation mitigation methods (PMMs) are necessary to reduce depredation and increase tolerance for large felines. In a prospective cohort study, 16 ranches between 2017 and 2019 used electric fences (n = 14) and introduced creole cattle (n = 2) as PMMs. There was a significant difference in the risk and odds ratios between the control and treatment groups. Livestock depredation was 14.78 times higher outside PMM areas (OR, 14.78; RR, 0.069; p < 0.001) than inside such areas. The losses caused by depredation were much higher than the investments made in PMMs.