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Marine protected areas contribute to mitigating the effects of human activities on marine ecosystems. The waters of Southampton Island, Nunavut, Canada are under consideration to become a marine protected area, but baseline information of marine mammal presence and habitat use is lacking. This study represents the first passive acoustic monitoring of marine mammals in this area, with data collected in 2018 and 2019. Bioacoustics analyses and generalized linear models were used to investigate species seasonal and temporal vocalization trends; infer behavior and habitat use from vocal cues; and explore vocal activity correlation with sea ice. Over a diel period, bearded seals (Erignathus barbatus (Erxleben, 1777)) and walruses (Odobenus rosmarus (Linnaeus, 1758)) were found to increase their vocal activity at night, whereas belugas (Delphinapterus leucas (Pallas, 1776)) mainly vocalized during daytime. Seasonally, bearded seals were recorded only during their breeding season at sea ice break-up, while walruses vocalized consistently throughout the open-water period outside their breeding season. Beluga vocal trends suggest their use of the area as a migratory corridor during sea ice break-up and freeze-up. Finally, bowhead whales (Balaena mysticetus Linnaeus, 1758) were recorded later than expected, concurrently with the onset of their mating vocal displays during the fall migration at sea ice freeze-up.

This article examines the jurisdictional status of the internet. Because of the underly ing nature of technology, nations cannot effectively monitor online transactions that originate or conclude within their borders. Governments can seek to enforce their laws within the constraints of their physical, geographical, and political domains as defined by an atlas, but a borderless cyberworld regulated by fast -expanding technology has a variety of challenges. This study sheds light on those challenges, the jurisdiction for parties to suit, the remedies accessible to them, and the territorial concerns discussed in various domestic courts. It also focuses on the pressures on stakeholders to act, as well as the economic, human rights, and techno logical infrastructure implications of jurisdictional concerns. In general, jurisdictional issues on the internet have resulted in haphazard and unrestricted jurisdictional implementations, and this article emphasizes the territorial difficulties of internet administration and its direct influence on many nations and elements.

This manuscript deals with a hyperbolic partial differential equation with fractional differential and fractional integral forcing functions. Semidiscretization method is used to establish a unique strong solution and also approximate solutions. Error estimates and continuous dependence of the strong solution on the given conditions have also been discussed. At the end, we illustrated the results with an example.

Background: This study aims to evaluate the effectiveness of the OSCEai, a large language model-based platform that simulates clinical encounters, in enhancing undergraduate medical education. Methods: A web-based application, OSCEai, was developed to bridge theoretical and practical learning. Following use, medical students from the University of Calgary Class of 2026 completed an anonymized survey on the usability, utility, and overall experience of OSCEai. Results: A total of 37 respondents answered the anonymized survey. The OSCEai platform was highly valued for its ability to provide data on demand (33/37), support self-paced learning (30/37), and offer realistic patient interactions (29/37). The ease of use and medical content quality were rated at 4.73 (95% CI: 4.58 to 4.88) and 4.70 (95% CI: 4.55 to 4.86) out of 5, respectively. Some participants (8/37) commented that few cases were not representative and needed clarification about app functionality. Despite these limitations, OSCEai was favorably compared to lecture-based teaching methods, with an overall reception rating of 4.62 (95% CI: 4.46 to 4.79) out of 5. Interpretation: The OSCEai platform fills a gap in medical training through its scalable, interactive, and personalized design. The findings suggest that integrating technologies, like OSCEai, into medical curricula can enhance the quality and efficacy of medical education.

Vertical profiles of salinity, and isotopic abundance ratios of hydrogen (δ2H ) and oxygen (@delta;18O) of 18 landfast ice cores, collected along the northeast coast of James Bay in March 2019, and one ice core collected in Belcher Islands, were used to obtain the winter timeseries of the spatiotemporal evolution of the under-ice plume of La Grande River (LGR), the dominant river in the area. Variability in the isotopic composition and salinity of the ice cores indicated changes to the water source composition at the ice-water interface when the ice layers formed. The increased presence of river water beneath the ice during January-March was marked by more negative isotopic ratios in the lower portion of the ice as river discharge was increased for hydroelectric production. River water was the source of ~43% of the ice in our ice core samples (n=320) with the interquartile range from 16% to 71%. The river water fractions incorporated into the ice indicate that LGR under-ice plume extended more than 75 km north and at least 30 km south of the river mouth for ~3 months. These findings correspond well with more challenging to obtain hydrographic observations. End-of-winter ice core sampling and analysis for isotopic abundance has potential as a tool to monitor dispersal of LGR discharge into the ice-covered coastal environment.

The academic literature scarcely covers court cases from the Global South on climate change. Hence, this paper examines the impact of existing climate litigation on shaping Africa’s climate action and the role of courts in climate change jurisprudence on the continent. The paper determines that: NGOs are key actors in challenging state granted environmental authorisations of projects whose activities violate human rights, affect climate change, and contravene formal procedures. Courts are deciding that fossil fuel activities like gas flaring violate fundamental human rights and exacerbate climate change. They call for amending laws allowing for such activities to bring them in conformity with laws on the protection of fundamental human rights. In a balancing act of the socio-economic rights and environmental human rights violations courts acknowledge that fossil fuels form part of the energy mix of sources on account of existing government laws and policies aimed at addressing priorities like energy security and poverty alleviation, a context that should inform climate change action. The implication is that short of laws banning fossil fuel activities, these activities will continue under enabling laws thus limiting the extent of court’s intervention in challenging climate change.

The university setting significantly impacts the student’s learning and academic achievement. A vital aspect shaping their productivity and well-being within this environment is the indoor soundscape. Different organizations, nationally and internationally, have emphasized the importance of addressing noise-related issues and have established guidelines. This study investigates how indoor soundscapes affect student learning and achievement in university classrooms. The present study analyses noise levels at nine locations during morning, afternoon, and evening study hours using a class 1 sound level meter. Results show noise levels ranging from 49.8 to 77.6 dBA, averaging 66.1 dBA. Over 96% exceeded the ANSI, CPCB noise limit of 50 dBA, with 62.96% surpassing WHO’s 55 dBA standards. Seven of nine locations maintained acceptable noise levels 95% of the time, considering a ±10 dBA fluctuation allowed by CPCB. Libraries and computer labs generally had lower noise, while engineering labs had higher levels due to noisy equipment. This research holds significance for educational institutions, policymakers, and stakeholders in creating conducive learning environments. Understanding prevailing soundscapes informs the design and management of study areas, and helps optimize learning spaces for improved productivity.

Post-disaster recovery is a multifaceted system essential for rebuilding communities and infrastructure. Despite its importance, many limitations obstruct powerful recuperation, main to tremendous loss of life and monetary assets. This paper synthesizes varied approaches in the direction of sustainable restoration, highlighting the increasing reliance on technology for disaster management. Image processing strategies, pivotal in addressing these demanding situations, are reviewed across studies. Those strategies range from SLIC segmentation and Random forest classification to advanced deep learning models together with U-net and YOLOv8, machine learning algorithms like SVM, and image category methodologies along with bi-temporal analysis. Comparative evaluation reveals that those strategies presents promising consequences, with accuracies starting from 75% to over 94%. The paper gives a framework for understanding the role of various image processing strategies in improving disaster control strategies, emphasizing their implications for future studies and application.

The images captured from SAR sensors are inherently weakened by speckle noise. The SAR image processing community targeted this problem with many feature-based filters. Since SAR images are low-contrast images, edge retention is the most crucial aspect to consider. This helps in the efficient retrieval of information. This paper provides a two-step edge-preserving homomorphic SAR image despeckling technique that implements a guided filter as the first step, and a modified method of noise thresholding using the bivariate shrinkage rule and canny edge operator in the Discrete Orthonormal Stockwell Transform (DOST) domain as the second step. The use of a canny edge operator improves overall edge preservation after despeckling. The use of noise thresholding delivers the highest level of speckle reduction in the DOST domain. The detected edges are added to the residual part obtained after removing the noise to produce more informative content. According to several qualitative and quantitative criteria, the suggested approach is compared to some of the newest despeckling methods. The execution time of the proposed method is around 7.2679 seconds. Upon conducting qualitative and quantitative analysis, it has been determined that the proposed method surpasses all other despeckling methods that were compared.

ABSTRACTChronic pain following distal biceps rupture (DBR) is often nonspecific in that it may arise due to the injury, subsequent surgical repair, or a combination of factors, making the painful symptoms challenging to treat. Peripheral nerve injury in the setting of DBR most commonly affects the musculocutaneous nerve or one of its terminal branches and may lead to chronic neuropathic pain involving the elbow and lateral/radial aspect of the forearm. In this brief technical report, we describe an ultrasound-guided (USG) technique for percutaneous implantation of a peripheral nerve stimulator (PNS) targeting the musculocutaneous nerve, along with an illustrative case report of successful treatment of chronic refractory pain following DBR utilizing this technique. Six months postimplantation, the patient reported a greater than 60% baseline pain intensity reduction, and no complications were noted.

Numerous studies have been conducted to enhance our understanding of how climate change impacts landfast ice and its break-up in spring or summer. Yet, predictions of break-up timing have proven elusive illusive, and dependent on multiple environmental drivers. In this study, we investigate whether/to what extent snow melt on land adjacent to the coast can serve as a precursor to landfast ice break-up. For the study, we used MODIS snowmelt timing products to explore the pattern of snowmelt across the study area. This was compared against landfast ice break-up dates generated mainly from CIS ice-chart, across the Hudson Bay and James Bay coast. Snowmelt timings recorded across the study area followed the same latitudinal gradient as the landfast ice break-up dates, with almost a 50-day difference between the south and the north snowmelt and ice break-up timings. The data shows that the timing of landfast ice break-up across the Hudson Bay and James Bay region showed significantly stronger correlations with the timing of terrestrial snowmelt, as compared to air temperature thresholds, with an average 17-day gap observed between snowmelt to landfast ice break-up. Based on the observations, we believe snowmelt can be a reliable precursor to landfast ice break-up.

We introduce a new diagnosis tool that is well suited to analyzing simulation results over large samples of watersheds. It consists of a modification of the classical Taylor diagram to simultaneously visualize several error components (based on bias, standard deviation or squared errors) that are commonly used in efficiency criteria (such as the Nash–Sutcliffe efficiency (NSE) or the Kling–Gupta efficiency (KGE)) to evaluate hydrological model performance. We propose a methodological framework that explicitly links the graphical and numerical evaluation approaches, and show how they can be usefully combined to visually interpret numerical experiments conducted on large datasets. The approach is illustrated using results obtained by testing two rainfall-runoff models on a sample of 2050 watersheds from 8 countries and calibrated with two alternative objective functions (NSE and KGE). The assessment tool clearly highlights well-documented problems related to the use of the NSE for the calibration of rainfall-runoff models, which arise due to interactions between the ratio of simulated to observed standard deviations and the correlation coefficient. We also illustrate the negative impacts of classical mathematical transformations (square root) applied to streamflow when employing NSE and KGE as metrics for model calibration.

The interaction between the environment and maternal health is critical to public health. It impacts the well-being of pregnant women globally. This paper investigates the connections between multiple environmental factors and their impact on maternal health, emphasizing the challenges and potential interventions. In diverse settings, ecological conditions shape maternal health outcomes. Factors such as air and water quality, sanitation, chemical exposure, nutritional food, and climate change play pivotal roles. The disparities in environmental exposures contribute to varying risks for pregnant women, particularly in low- and middle-income countries (LMIC). The detrimental effects of environmental pollution, inadequate sanitation, a rise in temperature, and limited access to healthcare services are explored concerning maternal health outcomes. Additionally, the abstract highlights the interconnectedness of socio-economic factors, cultural influences, and healthcare-seeking behaviour in shaping the impact of the environment on expectant mothers. Recognizing the complexity of these factors is essential for designing targeted interventions to improve maternal health in low-resource settings. The abstract concludes by advocating for comprehensive strategies encompassing healthcare improvements, environmental stewardship, and community empowerment to mitigate adverse environmental impacts on maternal health. Understanding and addressing these dynamics are crucial steps toward ensuring the well-being of mothers and promoting sustainable maternal healthcare practices.

The escalating urbanization and rapid traffic growth have accentuated the need for smart and efficient parking solutions. This paper explores the implementation of IoT technology to maximize the optimization of multi-storied parking facilities. The system that was proposed aims to enhance space utilization reduce congestion and improve the parking experience. It all begins by studying current challenges related to traditional parking structures including space utilization, limited accessibility, and huge waiting time. The system offers real-time data analysis by integrating IoT devices like sensors, data acquisition and communicating modules. It facilitates dynamic range space allocation for efficient utilization of allocated slots. For effectiveness, a prototype is developed and tested, where the results are described as a significant reduction rate in congestion and space utilization which further enhances user satisfaction. Using a lift and a DC motor for the movement of vehicles from one floor to another, the Installation of IoT technology enables the operators to manage and monitor the facility remotely, contributing to cost-effectiveness and operational efficiency.

Sustainable banking practices have increased prominently in the recent times as financial institutions realises the importance of integrating ESGs into their businesses. This paper aims to examine various sustainable banking practices that includes sustainable lending, green finance, responsible banking and also examines their contribution towards sustainable development and financial stability. The paper aims to insights the effectiveness of sustainable banking practices in promoting environmental sustainability, social inclusion and long term financial resilience.

The clap-based regulator proves an important role or invention in today’s day to day life for industries and home automation technology, contribute the wireless or automated approach to control the home, school and industries automations and appliances. By using sound recognition technique, the system provides signal to the ac and dc appliances with the help of Arduino which control the relay circuit. This invention provides a lot of benefits for environment as well. Moreover, through this innovation the project helps in energy preservation and encourage urban growth and progress. In this Project we associated an Artificial intelligence-based sound module which stimulates the lights in the home based on the threshold value of Clap and then off the lights based on consecutive clap sound.

Considering the disruptive potential of electric cars in the automotive industry, this studyaims to analyze the factors influencing electric car adoption behavior among Indian car usersMethodology:The research adopts both exploratory and descriptive approaches, conducted in two phases. Phase oneinvolves engaging with 200 prospective electric car buyers to identify critical adoption factors. Phase twoemploys conjoint analysis, involving 300 consumers and assessing nine attribute combinations (price,recharge time, and driving range) derived from literature review and interactions with potentialbuyers. Findings: The study reveals the three most valued attribute combinations for Indian consumers whenselecting electric cars. Practical Implications: Decision-makers and electric vehicle manufacturers can leveragethese results to introduce advanced technology into the Indian market. The conjoint analysis findings assistmanufacturers in understanding the relative importance of features influencing consumer utility. Originality: This study contributes to the existing literature by focusing on consumer behavior in developing markets,particularly India, which has been less explored compared to the asymmetry in research on electric caradoption behavior in developed markets.

The digital age is reshaping student reading habits, especially in management education, focusing on accessibility, affordability, technology, and mindset. This study examines how digital learning resources affect management students' reading habits, challenging the notion that students should only read textbooks. Despite the widespread availability of online reading materials, only some studies have explored how management students' reading habits are changing. This study used a mixed research design, starting with qualitative interviews with 20 management students to identify themes, which were then used to develop and validate a questionnaire with 20 experts. The questionnaire was then administered to 200 management students from public and private universities in Punjab, India. The findings identified four key factors influencing management students' changing textbook reading habits: convenience, price, technology, and attitude. Regression analysis indicated that attitude was the most significant predictor of changed reading habits, suggesting that promoting a positive attitude towards textbook reading could help counter the impact of digitalization. The study concludes with recommendations for publishers to update content regularly, offer online resources, and consider a hybrid publishing model combining free and premium content to adapt to the digital age and promote inclusive education, aligning with Sustainable Development Goal 4.

Air pollution, specifically the presence of particulate matter (PM10) is a growing concern in many parts of the world, including Sri Lanka because of their ability to cause series health risks, destructive environmental damage and their negative effects on the nation’s economy. Since Colombo is the commercial capital of Sri Lanka, this study analyzed the PM10 concentrations in Colombo over one-year period; impact of meteorological parameters on the PM10 levels and potential source regions. To accomplish this, data on 24-hour average PM10 concentrations and meteorological parameters were collected at Colombo from Jan to Dec 2022. Colombo experienced 40.5 ± 26.6µgm-3 average PM10 concentrations in 2022 which is about 3 times higher than WHO guidelines (15µgm-3). Seasonally, Northeast monsoon season experienced the highest average PM10 concentration (~56.8 µgm-3) in Colombo that may be attributed to low rainfall (~3.8mm) and low wind speed (~12.1mph). Conversely, minimum average PM10 level (~24.2 µgm-3) occur during Southwest monsoon which may be caused by higher rainfall (~8.4mm) and wind speed (~17.9mph). CBPF was used to evaluate the potential source regions for high PM10 levels in Colombo, indicating potential sources could be vehicular emission, thermal power plant, waste combustion and industrial emissions. The results of this study assist policy makers in charting the control strategies in the region.

These days, building sustainable infrastructure requires human endurance. In this sense, the idea of combining PET (polyethylene terephthalate) with pervious concrete is an intriguing field of study. On the one hand, by enabling water to percolate through voids and lowering surface runoff, pervious concrete helps to replenish groundwater levels. Conversely, waste PET plastic, which is produced more frequently these days, is recycled in building projects. Consequently, this leads to two main benefits: concrete’s mechanical and hydraulic qualities are changed, and plastic waste is effectively managed. This study looks at using leftover PET plastic fibres in varying amounts to create pervious concrete and assesses the mechanical properties (compressive strength, flexural strength, split. Porosity and permeability were also found to be correlated. Finally, an abrasion resistance test was conducted. Various percentages of PET plastic fibres, specifically 0%, 5%, 10%, 15%, and 20% by volume were used in place of natural coarse aggregates in this investigation while maintaining a constant water-to-cement ratio of 0.34. Compressive strength, flexural strength, and split tensile strength are all decreased when the amount of PET plastic in the concrete mix is increased. This decline in trend was notable for compressive strength at 20% replacement and for flexure strength at 10% replacement. Porosity, permeability, and abrasion resistance all indicated a progressive increase for different replacement percentages at the same time. The results of the experiment revealed that the porous concrete had an aggregate-to-binder ratio of 0.34 and a weight-to-cement ratio of 0.34.

Concrete infrastructures with embedded mild steel (EMS) have been implemented in various construction sectors to enhance their strength and durability. However, deleterious corrosion of the EMS in CA is a burdensome problem worldwide. Therefore, timely application of appropriate corrosion control techniques can mitigate the consequential effects of premature corrosion of such EMS in CA. Green plant-based leaf extracts have been recently utilized as anti-corrosive agents to prevent premature EMS corrosion. The present work focused on exploring the inhibitory impacts of leaf extracts of floss flower or Ageratum houstonianum (AgHE) and yam or Dioscorea alata (DiAE) each for controlling the rusting of the EMS in concrete beam (CB). The DiAE and AgHE comprise secondary metabolites like phenols, alkaloids, saponins, steroids, tannins, and flavonoids, confirmed from screening, GC-MS, and FTIR analysis. The EMS in CB with 1000-4000 ppm DiAE or AgHE showed a better corrosion inhibiting effect, compared with a concentration of 500 ppm from the observation of electrochemical corrosion potential (ECoP) value, measured using half-cell potential (HCP) method according to the ASTM C876-91 standard. The recent outcomes could be a part of an innovative solution to extend the lifespan of EMS in CB.

This study compares satellite-based observations of PM2.5 and Total Carbon (TC) concentrations derived from NASA’s MERRA-2 reanalysis dataset for the Ghaziabad region with ground-based observations at two sites (Site A and Site B) from June 2018 to May 2019. Results reveal consistent underestimation by MERRA-2, with daily mean biases of -85.34 (Site A) and -111.31 (Site B) for PM2.5, and -54.77 (Site A) to -59.08 (Site B) for TC, alongside monthly mean biases of -81.30 to -103.74 for PM2.5 and -54.77 to -59.08 for TC. The absolute error indicates a 49.01% to 53.85% underestimation for both PM2.5 and TC. Daily FAC2 values show around 39% agreement for PM2.5, reducing to 0.27 (Site A) and 0.3 (Site B) monthly, indicating reduced agreement over time. For TC, daily FAC2 is notably low at 0.04 (Site A) and 0.06 (Site B), with no monthly agreement within a factor of 2 of ground-level data. Strong correlations (R²=0.68-0.84 for PM2.5; R²=0.94-0.96 for TC) between biases and ground-level data are observed, indicating proportional relationships. However, discrepancies increase with higher PM2.5 mass concentration, highlighting MERRA-2’s limitations during elevated pollution periods. Significant monthly variations are observed in GLC-PM2.5 concentrations at Site A (F= 61.42, p= 1.68×10-11) and Site B (F=25.15, p=2.96×10-06), and For GLC-TC concentrations at Site A (F=103.85, p=4.10×10-16) and Site B (F=55.70, p=7.54×10-11). Both GLC and MERRA-2 PM2.5 and TC concentrations follow a consistent monthly pattern, with higher levels during post-monsoon and winter seasons and lower levels during monsoon and pre-monsoon periods. This study underscores MERRA-2’s limitations in estimating PM2.5 and TC concentrations compared to ground-based observations and emphasises the necessity for further refinement and validation of the MERRA-2 model to enhance accuracy across different spatial and temporal scales.

The conventional approach for solar collector design often requires performing large-scale experimentations or computationally intensive simulations which hinders the comprehensive screening and optimization of process design. This creates a strong rationale for developing a computationally efficient framework capable of leveraging a relatively small number of samples to generate a machine-learning model with sufficiently high fidelity. In this regard, the present study aims to integrate the concepts of random sampling, Gaussian process(GP), and Bayesian optimization for developing a computationally efficient data-driven framework for capturing the complete continuous domain of the parametric variation and predicting the desired performance measure. The proposed framework is rigorously tested at different stages with the help of unknown samples (out-of-fold test samples) to ensure the sound generalization capability of the constructed model. The model assessment revealed that the increase in sample size for training the GP model from 35 samples to 105 samples resulted in ≈ 56% reduction in root mean square error (RMSE), which further reduces to ≈ 96.5% after performing Bayesian optimization based hyperparameter tuning. The proposed framework will be extremely helpful in designing the highly efficient nanofluid-based solar thermal collector, by preventing the need of performing large-scale experimentations/simulations for screening purpose.

Global air quality trends suggest decreased PM10 levels with increased precipitation, however, Peninsular India exhibits a distinct pattern. This research investigates the correlation between precipitation and PM10 concentrations in Peninsular India, with special focus on the anomalous relationship between the two variables, where rainfall does not consistently lead to lower PM10 concentration levels. The study examines data from 11 air quality monitoring stations across four states, considering PM10 concentrations, precipitation intensities and meteorological data of wind. Statistical analyses were employed to study the distribution patterns of PM10 mass concentrations corresponding to the type of rainfall during the monsoon season in every city of research. To investigate further, the correlation between PM10 levels before the rainfall and the average precipitation intensity during the rainfall duration was established. Results have revealed that the impact of precipitation on PM10 concentration levels varies depending upon the pollutant’s concentration before the rainfall duration and precipitation intensities. Light rainfall (precipitation intensity between 2.5 mm/day to 7.6 mm/day) leads to a decrease in PM10 concentration levels in particular meteorological conditions, whereas very light rainfall (precipitation intensity less than 2.5 mm/day) increases the PM10 concentration levels post rainfall. The scavenging effect of precipitation is investigated by measuring the difference in PM10 concentration levels before and after a certain precipitation intensity. When initial PM10 concentration is lower than the seasonal average, results show a little increase in PM10 concentration levels after a light rainfall lasting less than 10 hours. This research also explores the fluctuations in the PM10 concentration levels under different wind directions and speeds. It is observed that increasing wind speed in one direction improves the clearance effect on PM10 concentrations. The objective of this research is to close the knowledge gap between regional meteorological conditions (primarily related to precipitation and wind dynamics) and regional air quality by offering data-backed observations. This facilitates effective air pollution management for such disparate air quality patterns.

This research examines the effectiveness of nanomaterial-based adsorbents in improving water treatment. It specifically looks at their ability to adsorb contaminants, their efficiency in removing pollutants, the speed at which they work, and their ability to be regenerated. Four distinct nanomaterials, labeled as Nanomaterials A, B, C, and D, were produced and analyzed to assess their effectiveness in eliminating contaminants from liquid solutions. The results showed that Nanomaterial D displayed the maximum adsorption capacity, measuring 142 mg/g, which indicates its exceptional capability to adsorb contaminants. In addition, Nanomaterial C had the best removal efficiency of 97.5%, highlighting its efficacy in decreasing pollutant concentrations in water. The analysis of kinetic characteristics revealed that Nanomaterial C had the greatest pseudo-second-order rate constant, indicating fast adsorption kinetics and robust surface contacts. In addition, Nanomaterial C had the greatest regeneration efficiency of 85%, suggesting its suitability for sustainable water treatment purposes. The results emphasize the impressive effectiveness of adsorbents made from nanomaterials in tackling water quality issues and advancing environmental sustainability. Nanomaterial-based adsorbents may have a significant impact on securing clean and secure water supplies for current and future generations by improving synthesis processes, comprehending adsorption mechanisms, and evaluating regeneration features. Additional study is required to investigate other parameters that affect the performance of adsorbents and to assess their long-term stability and cost- effectiveness for practical use in water treatment systems.

The appropriate percentages of cement, fine aggregates, coarse aggregates, and water are utilized to make concrete. Due to its relatively low price and widespread availability, it is a ubiquitous building material. Concrete in its fresh state can also be molded into any desired shape and size. Strength and durability are two of concrete’s most important characteristics (particularly when used for structural purposes). Verify the concrete’s compressive strength before placing it under the expected loads. NDT methods, both destructive and non-destructive, can be used to assess the compressive strength of hardened concrete. A non- destructive test does not harm the concrete specimen, whereas a destructive test (DT) crushes the cast specimen until it breaks. In non-destructive testing, materials, components or assemblies are inspected, tested or evaluated without destroying their serviceability. This study compares the compressive strength of concrete utilising an ultrasonic pulse velocity approach, which is both destructive and non-destructive. Concrete cubes measuring 150 mm by 150 mm by 150 mm were created using the concrete mix grades 25N/mm2 and 30N/mm2, and they were allowed to cure for 28 days. There were 12 cubes produced and used for the study. The determine compressive strength between destructive and non -destructive (ultra-sonic pulse velocity) test method.

ETABS software is used to analyze the structural response of reinforced concrete (RCC) and post-tensioned (PT) slabs under lateral loading. This study investigates RCC and PT slabs’ behavior by using finite element analysis to determine bending moments, shear forces, and storey drift. Prestrassed slabs display lower bending moments and shear forces than RCC slabs, demonstrating the effectiveness of prestressing in reducing structural requirements. A reduction in storey drift also indicates improved resistance to lateral deformations in PT slabs. In terms of structural performance and cost-effectiveness, PT slabs offer potential benefits for constructing layouts and construction, making them an attractive choice.

It has become increasingly apparent that wind energy can contribute to reducing carbon emissions and reducing fossil fuel reliance. In spite of this, wind's intermittent nature makes it challenging for grids to maintain stability. The objective of this paper is to review the current state of wind energy integration, highlighting key research findings on the potential of wind power, turbine performance, and approaches to enhance grid stability. A particular part of the research focuses on the modelling of DFIG systems, which includes the rotor control mechanism as well as the grid control mechanism at the grid side of the generator. Voltage fluctuations, transients in the power system, and reactive power management are among the technical challenges associated with wind power integration. SFCLs (Superconducting Fault Current Limiters) are also explored in the paper as innovative solutions for improving grid stability. As a result of simulations, it is demonstrated that SFCLs can mitigate power deviations and improve overall system stability to an extremely high degree.

This study optimizes the production of activated carbon (AC) from two distinct agricultural wastes, barley husk and maize cob. The process is refined using the Taguchi method with the goal of enhancing water treatment techniques. The study emphasizes how crucial it is to make the transition towards renewable and affordable raw materials for the manufacturing of AC given the predicted expansion of the worldwide demand for AC. The study assessed the impact of four crucial variables on the production and quality of AC using a L9 orthogonal array: phosphoric acid concentration, heating by microwave time, power from the microwave, and nitrogen flow rate. Findings indicated that the most important element for maximizing the production of AC from these agricultural leftovers was microwave power, along with the percentage of phosphoric acid and the time frame of the heating process.

The hybrid wind-solar system is a combination of renewable energy sources, specifically wind and solar, that is utilized for power generation. While wind power has historically been used for various purposes such as sails, windmills, and wind pumps, it is now predominantly used for electricity generation. This system incorporates solar panels and small wind turbine generators to produce electricity. The advantage of hybrid systems is that they can generate electricity as needed, taking into account the varying peak working hours of solar and wind systems throughout the year. To ensure a stable power system, UPQC (Unified Power Quality Conditioner) is employed. This multipurpose power conditioner serves multiple functions, including preventing harmonic load current from entering the power system, rectifying voltage fluctuations, and compensating for voltage disturbances from different power sources. It is specifically designed to minimize interference with sensitive or critical loads. With its series and shunt compensation capabilities, UPQC effectively manages power flow, reactive power, harmonics, and voltage disturbances. In this paper, the work addresses the issue of electricity quality that arises from the installation of wind turbines in the grid. To get over this issue, the suggested course of action demonstrates how to install a BESS and a unified power quality conditioner (UPQC) at the connection point. Even though wind power fluctuates, the use of battery energy storage technology helps to provide a constant power supply. With the power system block established in MATLAB/SIMULINK, one can simulate the UPQC control method of a grid-connected wind energy generating plant. As a result, the power's quality will increase. When the recommended approach lowers the load's and the induction generator's reactive power requirements, it is successful. Furthermore, the plan for raising the grid's power quality criteria and developing the grid coordination rule are also provided.

A Swing arm is a mechanical device that connects the rear wheel of the motorcycle to its body, allowing it to pivot vertically. It holds the rear axle firmly while pivoting to absorb bumps and suspension loads induced by acceleration and braking. Swing arm can be single or double-sided and has appeared in a variety of geometries. The original version consists of a pair of parallel pipes holding the rear axle at one end and pivoting at the other. A shock absorber is mounted just before the rear axle and attached to the frame, below the seat rail. The primary concern is to design a lightweight swing arm that can replace conventional motorcycle swing arm design, which consists of tubular sheet metal structure throughout the swing arm neglecting the stress-induced at various positions along the length of the swing arm, i.e. (from pivots to axle blocks). The vehicle selected for this project is Yamaha FZ-S V2. The material chosen for the swing arm are Al 6061, Al 6061 T6, and Al 7075. This project uses an iterative design method called Generative design to design a lightweight swing arm without compromising the mechanical properties and performance of its counterpart. Analysis of the part will be carried forward using static Analysis comprising various load cases and extreme load conditions. The whole design and analysis process is carried forward using Autodesk Fusion 360. This swing arm design involved economic utilization of material as it reflects the in the analysis through induced stresses.

Concrete’s compressive strength can be tested in a laboratory before construction begins. Since concrete is a natural material and cannot be destroyed, it is not possible to determine its compressive strength through destructive testing. Rebound hammers are typically used in the field to evaluate the structural elements’ ability to withstand hardened concrete. As part of the current study, a comparison was made between concrete’s compressive strength measured by destructive testing and its surface hardness measured by rebound hammering. Tests were conducted on laboratory-made concrete cubes in this study to determine destructive and non-destructive behavior. Minitab software was used for regression analysis. Schmidt rebound hammer tests, a type of nondestructive testing (NDT), were shown to have very strong relationships with concrete destructive compression tests. Schmidt rebound hammers are commonly used to measure the surface hardness of concrete, since the hammer rebound number and concrete strength are theoretically correlated. Utilising a Schmidt hammer, it was applied. Standard concrete cubes with crushing strengths between 20 and 30 MPa were created using various mix proportions. Using regression analysis, destructive and non-destructive values are correlated. The linear regression equation is well suited for obtaining the compressive strength using rebound value by using linear regression equation.

In this paper, the analysis of the directional heat flux and total heat flux for the bearing balls of Titanium alloy and Silicon Nitride has been demonstrated across a temperature range between 150 to 250 degree celcius. The obtained data allowed comparing the values of total heat flux and various directional heat flux. By comparing directional and total flux of heat in materials it enables the choice of the best-suited material creating bearings with regard to the performance needed. The use of the findings of the current comparison is to ensure efficiency and durability in particular operations. The data presented in the paper helped to analyze the patterns of heat distribution and see the differences between the materials and results a better material for ball bearing. Titanium alloy has excellent mechanical properties like mechanical strength and corrosion resistance. Silicon Nitride is characterized by thermal stability and high thermal resistance and also has excellent wear properties. Thus, using the results of the analysis allows choosing the material for bearing production for high-velocity and high-load operation based on a profound comparison to select the right material. The choice of right material will allow for a more efficient and durable bearing in an industrial setting.

Parking spaces, lobby areas, terrace gardens, and other amenities are highly sought-after in densely populated urban regions. Although floating columns can be useful and an achievable choice, it is important to research their structural performance and cost-effectiveness in the event of substantial ground motion imposed on by an earthquake. A building’s overall dimensions, geometry, and shape all impact how it acts and acts when subjected to seismic loads. For this reason, it is necessary to assess how well floating column buildings perform in seismically vulnerable places in comparison to conventional buildings. In this work, the performance of structures with floating columns for seismic loading is observed using dynamic analytic techniques in accordance with IS 1893 (2005). This study analyses both the floating columns and the conventional building without floating columns. When compared to a regular building, the research reveals that the floating column buildings exhibit a very quick increase in base shear and story displacement. The horizontal displacements experienced by floating column buildings are proportionally larger due to an increase in the fundamental time period. If the lateral displacement exceeds the codespecified maximum limit, damage to structural and non-structural parts may result. Because of the discontinuity in the load distribution path, seismic base shear and overturning moment are also increasing in the case of buildings with floating columns. Additionally, while asymmetrically introducing floating columns, torsional irregularity has been produced but the modal mass participation ratio has decreased. While it is true that the use of floating columns in high-rise structures allows for continuous open floor plans, they are also dangerous and susceptible in seismically active locations

Climate change is widely acknowledged as a prominent obstacle that significantly impacts agricultural productivity and the wellbeing of individuals. Farmers bear the brunt of the impact since they must consistently adapt to changes in climate. Questionnaire surveys were conducted in Bhopal, India to ascertain farmers' perspectives of climate change and its implications. The research was conducted out in Bhopal, Madhya Pradesh. M.P. possesses a range of meteorological conditions, soils, and a variable cropping pattern. This study utilises cross-sectional household survey data collected from farmers residing in Bhopal. The study employed a multi-stage sampling process to choose respondent houses for the sample. Ultimately, the study's sample size was established at 97 household heads. The study employed quantitative data. Data collection was conducted using household surveys. The researchers employed both structured and unstructured questionnaires to examine the farmers' impression of climate change. Given the nature of their work, researchers asked the farmers who took part in it what they thought about climate change. The findings imply that a variety of factors, including age, level of learning, and prior agrarian expertise, influence farmers’ perceptions of global warming.

The objective of this paper is the creation of a school to help the children of Kutikatoor live a more accessible and simpler life: students in the concentration range from 4 to 16 (Play School - Grade 10). The proposed location, which is around 18.3 acres in size, lies in Kuttikattoor, Kozhikode, and Kerala. The land is surrounded by greenery and situated in a mountainous area. The study will concentrate on how biophilic architecture and design may enhance students’ lives. This paper will discuss how biophilic design may benefit schools by creating circulation and spatial connections between the built and natural environments. The biophilic design can have quantifiable beneficial effects on student performance and well-being by including natural components. It is necessary to thoroughly analyze the biophilic design in relation to the learning environment for students, using ideas of ecological, visual, and spatial integration. By fostering a soothing atmosphere, lowering anxiety, and boosting physical fitness, biophilic design, which incorporates natural light, greenery, and nature vistas, can increase attention, decrease stress, stimulate creativity, and improve academic accomplishment. The school’s design will be implemented by incorporating the architectural design into the contoured regions and using the idea of biophilic design patterns. Depending on the climate and the site’s orientation, the design will be implemented such that locally accessible materials are employed in a hilly area. This detailed analysis of the case study and literature review for the school design will help us to design and conceptualize as an architect. Further, the study will also emphasize biophilic design which is aligned with the built environment in school design.

DTC, also known as Direct Torque Control, is a technique employed in variable frequency drives for regulating the torque and speed of three-phase AC electric motors. This method entails determining an approximation of the motor’s magnetic flux and torque by analyzing the voltage and current readings of the motor. In order to reduce flux ripples and ensure smooth speed operation, we have suggested the use of two fuzzy logic controllers based on DTC for induction motors. The proposed method offers a faster response compared to conventional DTC for induction motors. The MATLAB simulink software was used to illustrate the comprehensive results.

Switched Reluctance Motor (SRM) is one of the best alternative motor drives for induction and synchronous drives in present trends. However, the SRM can able to replace those synchronous and inductance machine by using effective controller for many applications. Apart from many controllers, Direct Torque Controller (DTC) has received much attention from researchers in these days due to its high superiority characteristics over other controllers. Moreover, compare to Proportional and Integral (PI) controller a Fuzzy controller can provide effective support to DTC during intermittent changes of speed and torque. Hence, Fuzzy controller based DTC has been implemented in this paper for novel configuration of converter to drive SRM. Generally more number of switches leads to more cost and poor performance. Therefore, a novel configuration of converter has been proposed in this paper for DTC of SRM. For analysis of system, the proposed method has been compared with vector based controller in this paper. The extensive results are presented to validate the proposed method for both the steady state and transient periods.

Energy storage device such as battery is playing very important aspect in microgrid since it can handle the bidirectional power flow to stabilize the power quality issues. Renewable energy sources based microgrids are becoming popular now a day because of those arte main networks which are playing key role in reduction of global warming as well as main power sources for many areas in world wide. The PV and wind based power generation systems are wildly used sources in microgrids. Unfortunately, these sources are depends on whether condition and cannot have a stable output to supply quality power to consumers. Therefore an storage device is must to incorporate in such kind of microgrids. Hence it is very important to have an optimization of scheduling a day-ahead energy storage system in case of renewable energy sources based microgrid power supply system. Ant colony optimization is one of the best optimization techniquesto get feasible solution for complexity networks such as microgrids. The data demonstrate the utilization of ant colony optimization technique in order to minimize microgrid expenses under a time-of-use tariff system. The findings also indicate the influence of the microgrid’s self-reliance and the storage system’s capability on the energy expenses of the microgrid.

Protection and control automation messages transfer between devices and the control center (CC) over IEC 61850 standard protocols in active distribution network (ADN) using Ethernet. Wireless communication network provides real-time monitoring and control of ADN. The proposed novel approach framework presentsline to ground (LG) faults protection and control method utilizing IEC 61850 standards at bay level between intelligent protection devices for fast and reliable protection. Moreover, this bay level peer to peer communication utilizes IEEE 802.11 wireless local area network (WLAN)to reduce the fault protection time and other messages transferring time instead of Ethernet communication by GOOSE multicast communication services. End to end time delay and throughput of data transmission between the coordination nodes are illustrated using NS2 simulation.

The deregulation of electricity has led to significant transformations in the market structure and policies governing the industry. The primary responsibility of a power system operator in this market is to establish the Market Clearing Price (MCP). The MCP is established by evaluating the incremental bids submitted by generators in various markets. But the quadratic bid functions have more information about the price structure and are more realistic. The Independent System Operator (ISO) determines the clearing price by analyzing the bids submitted. Conventional methods do not provide an accurate calculation of MCP for the spot market. This may lead to poor allocation of generation. This paper uses the basic Particle Swarm Optimization technique to maximize the generator bid function. By calculating MCP, the optimum generation with least cost is determined. Losses in the system with reactive power constraints are considered while the loads are kept in-elastic. The result of the proposed technique is compared with the classical approach. IEEE 9 bus system is taken to illustrate the proposed model.

Power generation from Photovoltaic (PV) modules is the best way to utilize the renewable energy in many places. The output of the PV modules will depends on many factors including changes in solar irradiance, temperature, partial shading conditions, operating voltage across terminals of module etc. Apart from operating voltage of PV modules, remaining all factors are depending on nature which we cannot change easily. Hence obtaining an effective voltage regulation of terminals to achieve maximum power from PV module is very important for best utilization. There are many existing maximum power point tracking (MPPT) mechanisms on PV systems but an effective integrating mechanism is required to achieve the best operation under all possible conditions. Artificial neural network (ANN) can able to produce best reference signal corresponding to maximum power location under various random changes very quickly. In other hand, sliding mode controller (SMC) is able to force the boost converter to deliver the best output voltage with fewer ripples under variable input voltage. Fastest response with fewer ripples in dc voltage can help to harvest maximum energy from PV panels. Therefore, integration of ANN with SMC can prepare the MPPT converter to deliver more energy under random changes in irradiance and temperature. The performance of ANN associated SMC for boost converter based MPPT of the PV system is presented in this paper. In order to obtain more realistic response, Hardware-in the-Loop (HIL) is established for proposed system with the help of two OPAL-RT modules. Extensive results by using HIL are presented and discussed under various case studies to enhance the proposed method.

The hybrid photovoltaic (PV)- wind based power generation systems are installing on many rooftops of individual houses, apartments, institutions, hospitals and small scale industries worldwide. Even though it is connected to single phase utility grid, a battery is used for backup power supply during power cuts. The diesel generators also can be integrated to this system for supplying continuous power long term. This configuration can establish a nanogrid under low power systems. Many loads are operated under this nanogrid system, hence a proper control technique is required to maintain power quality as well as to compensate reactive power. Compensating reactive power demanded in nanogrid through the inverter can reduce the reactive power demand on the main utility grid. Individual maximum power point tracker (MPPT) circuits are employed for both PV and wind to harvest maximum power. The system is synchronized with single phase utility grid through the control of the inverter. The proposed control method can able to regulate the phase voltage t its reference signal for improving the power quality. MATLAB Simulink platform is used to present the results for testing the performance of the proposed method.

This paper examines the potential of piezoelectric substances in presenting sustainable and renewable energy solutions, that specialize in energy harvesting and self-maintaining smart sensing mechanisms inside numerous systems. Highlighting the inefficacy of conventional construction substances like simple cement paste in energy capture, this study delves into current methodologies that expand the piezoelectric abilities of cement-based composites through innovative admixtures and physical treatments. Additionally, the research explores the broader utilization of piezoelectric materials across various sectors together with healthcare, environmental tracking, and consumer electronics, propelled by using the need for wireless sensing nodes and embedded microsystems to have a reliable power source. Emphasizing the environmental advantages, this paper affords a comparative analysis of cutting-edge developments, challenges, and future possibilities within the area of piezoelectric power harvesting (PEH), which include the exploration of lead-free substances and the advancement in hybrid energy harvesting devices.

Earthquakes are enormous natural disasters that increase the energy within the structural system, causing catastrophic destruction. Various control systems, such as passive, active, hybrid, and semi active control systems, can be used to dissipate this unwanted energy. The fluid viscous damper is one such dissipation device used in this study. The goal of this project is to use a fluid viscous damper to lessen the seismic response of the Symmetrical and unsymmetrical G+9 structure in ETABS2017. To obtain the seismic response with and without a fluid viscous damper, ETABS2017 was used to analyse symmetrical and unsymmetrical structures with and without a fluid viscous damper. The analysis takes into account nonlinear temporal history, which is derived using fast nonlinear analysis of Electro data. The position and function of dampers are discussed in this study. For seismic evaluation of buildings with and without fluid viscous dampers, the equivalent static approach and response spectrum method are utilised. The structure was examined utilizing ETABs 2017 programming, with seismic zone IV and medium soil (Type II) according to IS 1893-2016. The structure’s exhibition is assessed utilizing story removal, story shear, story float, and modular periods and frequencies. The objective of this study is to about the consequences of static and reaction range examination in both longitudinal and cross over bearings for damper development with and without damper structure.

The importance of using recycled materials like rubber in construction materials is rising rapidly today. By incorporating used rubber into cement and mortar, we can save landfill space and reduce our dependence on natural resources. Rubber scrap can be mixed in as either fine or coarse aggregate. Add it to Portland cement for a stronger, more durable product (PC). This paper reviews the studies conducted so far on the feasibility of using waste rubber in place of conventional PC-based mortar and concrete’s natural fine aggregate. The strength and water-absorption capacity of materials made from ash from scrap rubber tyres were measured. Test results indicate that waste rubber ash was substitute with natural sand up 10% then strengths of the sample were enhanced after increasing the content of waste rubber tyre ash then strength was decreased. Water absorption capacity of samples was improved as increased the content of waste rubber tyre ash into concrete mix.

The goal is to investigate the potential for employing byproducts from various industrial processes in the creation of ground-breaking mortar and concrete. The dust produced during the marble-cutting operation is put to good use. Different percentages of this garbage were recommended to be used in conjunction with or in place of cement in the making of concrete. The research looked into the possibility of using marble dust, which is produced during the shaping of marble blocks, as a cementitious material in concrete. In areas where they are readily available and can reduce construction costs, the study found that dust from marble slabs could be employed as a cementitious material in concrete mixtures. The discarded marble dust is mixed with cement in proportions of 5, 10, 15, and 20% of the standard concrete mix. Both the fresh and hardened characteristics of the produced combinations were investigated. Compressive and tensile strengths were measured after being cured for varying periods of time, both when marble dust was used as a partial replacement and when it was not.

This study examines the numerous pre-processing techniques used to convert biomass into greater sustainable biofuels and commodities, highlighting the boom in productivity and the supply of a greater uniform, dry, and suitable feedstock. by using addressing the demanding situations associated with biomass size, layout, moisture content, and variability, this study delves into mechanical procedures, drying, torrefaction, palletization, hydrolysis, hydrothermal, and microwave-primarily based strategies as possible solutions. It explores the utilization of various biomass types, which include wood, woody biomass, herbaceous streams, and agricultural streams, and assesses their impact on bioenergy production and environmental sustainability. The study also considers the position of algae, specially microalgae, in offering bioactive materials with substantial health advantages and their ability in overcoming land-use concerns associated with traditional biomass. moreover, the paper evaluates the environmental affects and sustainability of biomass usage, advocating for microalgae as a promising feedstock for 1/3-technology biofuels. The research is grounded in the context of the increasing need to reduce reliance on fossil fuels due to urbanization and population enlargement, which make contributions to environmental degradation.

Changes made to any soil property with the goal of improving the soil’s engineering performance are collectively referred to as soil improvement. This might include enhancing groundwater conditions, decreasing compressibility, minimising permeability, or strengthening the structure’s structural integrity. Soil enhancement might be a short-term solution to make building easier or a long-term strategy to improve the finished structure’s performance over time. Expansive soils, especially black cotton soil, pose serious problems for the building sector because of their negative swelling and shrinking characteristics. The purpose of this study is to better understand how stabilizing substances like fly ash and rice husk ash (RHA) might help address these issues and enhance the qualities of soil suitable for building. To evaluate the efficacy of RHA and fly ash as swell reduction layers and to improve unconfined compressive strength (UCS) in highway construction, the materials will be added to natural soil in different percentages (RHA: 0%, 15%, and 30%; fly ash: 10%, 20%, and 30%). Nine different combinations were tested using UCS after the quantities were established using the Taguchi optimization approach. The results suggest that adding these waste items can greatly strengthen the soil, and that certain combinations work best for stabilizing the soil. The study highlights how soils in construction can be addressed by utilizing sustainable resources like fly ash and RHA.

Time-dependent thermal analysis plays a pivotal role in the manufacturing industry as it greatly influences the overall performance of the final product. This study delves into transient thermal analysis of an aluminum alloy concerning both temperature and time. Employing ANSYS, a finite element-based software, an axisymmetric model is constructed. This model encompasses a mold made of sand and a pattern filled with aluminum alloy. The analysis focuses on temperatures ranging from 650 to 1050°C, examining the temperature changes in the mold and pattern after 1500 seconds, primarily due to the convection process. Parameters like heat flux and directional heat flux are also determined. Subsequently, machine learning models are utilized to interpret the data acquired from ANSYS, enabling the extension of the results to a broader temperature range of 1150 to 1550°C. This study is instrumental in facilitating the effective design of transient thermal analysis for various alloys at different temperatures.