Madhur Taneja

Nonlinear interactions and temporal evolution in a biological system can be mathematically modeled by differential equations and can be analysed quantitatively....

There is compelling evidence that organic inputs encourage soil health and sustainable agriculture. Nonetheless, it is currently unclear how long-lasting organic additions in combination with chemical fertilizers affect soil macro aggregate production and the soil's ability to store organic carbon (SOC). Therefore, the research goal was to determine how after 14 years of fertilizing, there is interaction between soil carbon sequestration and soil aggregate. Seven interventions were used in a field trial. Farmer-applied nitrogen (N), improved N executives, bio-char and manure, straw, compost, biogas waste, or enhanced N management alone is chosen. The research showed that, increasing by 30.6-120.8% and 11.3-36.3% in the soil layers between 0 -16 cm and 16 - 31 cm, respectively. A indicator of the soil's carbon storage process, human carbon (HUC) was one of the soil's humus carbon pools that grew by 15.7 to 206.2% in the soil depth of 0–16 cm and between its high aromatic carbon concentration and biodegradation resistance, adding bio-char to the organic components was the most successful tactic. The concentrations of dissolved organic matter (DOC), particulate organic carbon (POC), and microbial biomass carbon (MBC) and - the oxidizable carbon (ROC) all increased on average by, 122.5%, 94.3%, 218.2%, and 87.5%, respectively. The amount of exchangeable , , and Fe, with soil Al oxides, the mean weight diameter (MWD),these indicators had a strong association. According to the findings, adding organic materials to calcareous soil could be a useful management technique for encouraging carbon retention and creating soil macro aggregates in the ground.

The integration of Artificial Intelligence (AI) and Knowledge Management (KM) structures have emerged as a powerful strategy to streamline business processes and gain a competitive edge. The primary objective is to examine how the integration of AI and KM improves business efficiency, fosters innovation, and enhances competitive advantage across various industries, providing insights into the measurable benefits. Key variables include the level of AI integration, knowledge management (KM) effectiveness, business process efficiency, competitive advantage, and employee satisfaction. These factors were measured using standardized scales to determine their interrelations and impact on business performance. Data was collected using surveys from 750 employees across 10 companies, alongside 15 interviews with senior managers. SPSS was used to analyze quantitative data. SPSS was also used for correlation, regression, and descriptive statistics of key variables. There are strong positive correlations between business process efficiency and AI integration level (0.64) as well as between competitive advantage and KM effectiveness (0.67), and the results show that all variables have high mean scores, with business process efficiency having the highest mean (4.22) and employee satisfaction having the lowest (3.98). The investigation concludes that integrating AI technologies with KM systems significantly improves business process efficiency and provides a competitive edge. Organizations should prioritize these integrations to stay competitive, though challenges such as resistance to change must be managed.

Particularly with regard to health issue prediction and patient monitoring in real time, edge computing, artificial intelligence, and the Internet of Things (IoT) are altering the healthcare industry. This paper investigates how these technologies may be used, what technological issues they could have, and how they might develop in the medical domain. Continuous patient vital sign monitoring made possible by Internet of Things (IoT) devices and monitors Low-latency data processing guaranteed by edge computing facilitates real-time decision-making by means of simplicity. By simplifying early assessment and tailored treatment regimens, AI-powered predictive analytics used at the edge dramatically enhances healthcare results. New technologies handle significant issues like security, scale, data privacy, and interoperability by means of bitcoin and 5G networks. This guarantees effective and safe data flow. For instance, the research underlines the importance of consistent standards and secure patient data processing for the use of emerging technologies in the healthcare environment. Healthcare will grow more integrated, efficient, and patient-centered as IoT, cloud computing, and artificial intelligence keep improving.

Introduction: Increasing interest in human well-being has drawn attention to the need for healthy and sustainable environments, culminating in the emerging field of environmental health. Consequently, approaches aimed at enhancing ecological quality have emerged as one of the key strategies to promote better quality of life.Methods: Interventions were extracted and analyzed from a literature review on environmental health and quality of life. Several databases were searched for articles published from 2010 to 2020.Results: The findings sug­gest that environ­men­tal health inter­ven­tions are asso­ci­at­ed to mark­ed improve­ments in the qual­ity of life of dif­fer­ent pop­u­la­tions. These interventions include improvements in air and water quality, waste management, green space development, and other policies that support sustainable and healthy living environments.Conclusions: This highlights the importance of environmental health efforts in addressing the unique challenges faced by the populations in the study and their communities at large. Nevertheless, more investigation is required to track the long-term implications of these discernments inducing sustainability in social, economic and environmental aspects. Moreover, the role of public health professionals within interdisciplinary teams is emerging as vital to understanding and facilitating this process further in order to ensure the effective implementation and sustainability of these interventions through collaboration with policymakers and communities.

This study explores sustainable methods for recycling lithium-ion battery (LIB) materials, with the goal of tackling the issues of resource depletion and environmental pollution linked to LIB production and end-of-life management. An analysis of the composition shows that graphite (30%), nickel (20%), lithium (15%), and cobalt (10%) are the main components of LIBs. This emphasizes the economic potential of recycling methods to reclaim these valuable materials. Recovery efficiency assessments show different levels of success, with graphite having the highest recovery efficiency at 95%, followed by lithium at 90%, aluminum at 90%, and cobalt at 85%. The analysis of energy consumption highlights the disassembly and electrolysis steps as the ones that require the most energy. This emphasizes the need to optimize recycling processes in order to reduce environmental impact and improve sustainability. The analysis of costs highlights the significant expenses related to disassembly and electrolysis, underscoring the importance of implementing cost-effective approaches to enhance the economic feasibility of lithium-ion battery recycling. This study offers important insights into the feasibility and implications of sustainable LIB recycling approaches. It emphasizes opportunities for resource recovery, energy efficiency improvements, and cost optimization to support the transition towards a circular economy and a greener future.