This study examined the integration of genomic tools with conservation biology to address genetic erosion in endangered mammals of Pakistan. The research focused on key species including the snow leopard, Indus river dolphin, and markhor, which faced increasing threats from habitat fragmentation, inbreeding, and environmental change. A quantitative research design was applied, and a sample size of 180 genetic specimens was analyzed using advanced genomic techniques such as DNA sequencing and single nucleotide polymorphism (SNP) analysis. The results indicated a moderate level of genetic diversity (mean = 3.21) alongside high inbreeding levels (mean = 4.05) and severe habitat fragmentation (mean = 4.18). Structural model findings showed that habitat fragmentation negatively affected genetic diversity (β = -0.42, p = 0.000), while inbreeding also exerted a significant negative effect (β = -0.39, p = 0.000). In contrast, genomic monitoring demonstrated a positive impact on genetic diversity (β = 0.36, p = 0.000), and conservation policy support also contributed positively (β = 0.31, p = 0.000). The study proposed an integrated framework combining genomic monitoring, habitat restoration, and policy interventions to enhance conservation effectiveness. The findings highlighted the importance of incorporating genomic data into conservation strategies to improve species resilience and reduce extinction risks. This research provided practical implications for policymakers, conservationists, and researchers aiming to preserve biodiversity and manage genetic erosion in endangered mammalian populations.

Post harvest processing methods such as thermal treatment, freezing, drying, and industrial canning have a significant impact on the nutritional integrity of fruits. This paper is a systematic review of and comparison of the phytochemical profiles of ten economically and nutritionally important fruit species (both fresh and processed) in terms of total phenolic content (TPC), total flavonoid content (TFC), ascorbic acid, carotenoid levels and anthocyanin content and antioxidant activity. Based on the known in vitro assay protocols such as DPPH, FRAP, and ABTS assays, we compared the effects that different processing modalities have on the bioactive compounds content and functional antioxidant properties differently. Findings indicate that thermal treatment invariably led to a 18-42 percent reduction in TPC and ascorbic acid content by 30-65 percent, and freezing retained more than 85 percent of phytochemicals. Lycopene bioavailability in tomato was enhanced by up to 35% following heat treatment. The highest overall retention rates were with freeze-drying. The implications of these findings include considerable implications to dietary recommendations, food industry processing standards and within the nutritional policy of the population health.

This study examined the integration of mathematics and artificial intelligence through a unified framework for intelligent computational modeling and optimization. The research aimed to enhance system performance by combining mathematical rigor with AI adaptability. A quantitative and model-based approach was applied, incorporating mathematical optimization techniques and machine learning algorithms within a structured computational framework. The results demonstrated significant improvements in performance metrics, with accuracy reaching 92%, computational efficiency at 88%, and convergence time reduced to 25 seconds. The framework also achieved a low error rate of 5% and a high optimization success rate of 93%, indicating improved reliability and robustness. Comparative analysis revealed that the proposed framework outperformed conventional mathematical models and standalone AI systems in terms of scalability, generalization, and computational cost. The findings highlighted that mathematical structures improved stability and interpretability, while AI techniques enhanced adaptability and predictive capability. The study contributed to the field of computational science by providing a scalable and efficient framework that addressed limitations of traditional approaches. The practical implications suggested that integrated models could support advanced decision-making in various domains, including engineering, finance, and data analytics. The research emphasized the importance of interdisciplinary approaches in developing next-generation intelligent systems.

Sophora alopecuroides belongs to genus Sophora and family Fabaceae. It consists of approximately 60 to 70 species. The present research work was performed for the identification of volatile constituents along with antibacterial and anti-inflammatory activities of Sophora alopecuroides. The plant was collected from Kalat, Balochistan. The n-hexane fraction of the plant was evaluated for the determination of volatile compounds by using gas chromatography-mass spectrometry (GC-MS). The fourier-transform infrared spectroscopy (FTIR) was used to identify the functional groups of the compounds. The methanolic extract of the plant was evaluated for anti-inflammatory and antibacterial by using chemiluminescence protocol and agar well diffusion method respectively. The GC-MS analysis showed the presence of 34 volatile compounds. The FTIR spectra of methanolic extract showed the presence of functional groups such as alcohol, alkane, carbonyl compound and ester. The plant extract showed moderate antibacterial activity against gram positive Staphylococcus aureus and gram negative Escherichia coli bacterial strains, and with zones of inhibition of 19 mm and 21 mm respectively. The plant extract exhibited strong activity IC50 56.14± 2.82 for anti-inflammatory activity against standard drug ibuprofen. The plant showed the presence of significant number of volatile compounds which belongs to different classes of compounds. It is further suggested that Sophora alopecuroides may further be studied for the isolation of naturally occurring compounds and more pharmacological activities.

Dairy is among the most vibrant industries in the global food system that is crucial to human nutrition, the rural economy and development. Nevertheless, the growing environmental issues, limited availability of resources and the growing demand of the consumers on high-quality dairy products have required a switch to sustainable processing practices. The modern dairy processing technologies are taking shape as the technological innovations to achieve the efficiency, diminish the environmental influence and develop the quality of the products. This review thoroughly examines advanced dairy food processing methods such as high-pressure processing (HPP), membrane filtration, pulsed electric fields (PEF), ultrasound, cold plasma and advanced thermal methods such as ultra-high temperature (UHT) processing. These technologies help in sustainability since they help to reduce energy consumption, lessen water usage, increase shelf life, maintain nutritional and sensory qualities. Moreover, the combination of automation, digitalization and by-product valorization approaches are mentioned as the drivers to the sustainable dairy production systems. Although they have benefits, the limitations include high cost of capital, complex technology and regulatory restrictions that bar their wide use. The future outlook involves the application of hybrid technologies and artificial intelligence to transform the dairy processing. On the whole, the current dairy processing methods offer great prospect to attain environmentally sustainable and economically viable dairy production systems.

This study investigated the computational design of functional materials for energy applications using Density Functional Theory (DFT). The primary objective was to analyze the structural, electronic, and catalytic properties of selected materials to evaluate their suitability for energy storage and conversion systems. A quantitative computational methodology was adopted, where materials such as graphene, molybdenum disulfide (MoS₂), titanium dioxide (TiO₂), and perovskites were analyzed using DFT-based simulations. Key parameters including band gap energy, total energy, density of states, and adsorption energy were calculated. The results revealed that graphene exhibited a band gap of 0.00 eV, indicating high electrical conductivity, while MoS₂ and perovskites showed moderate band gaps of 1.80 eV and 1.50 eV, respectively, making them suitable for photovoltaic applications. TiO₂ demonstrated a higher band gap of 3.20 eV, suggesting its suitability for photocatalytic processes. Adsorption energy analysis showed that MoS₂ (−0.85 eV) and perovskites (−0.65 eV) had optimal interaction strengths for catalytic efficiency, whereas graphene exhibited weak adsorption (−0.20 eV). The findings highlighted that DFT-based approaches significantly enhanced the efficiency of material design by reducing experimental efforts and enabling accurate prediction of properties. The study provided practical implications for developing advanced energy materials and emphasized the importance of computational techniques in achieving sustainable energy solutions.

During the current study, the causes, impacts, and mitigation efforts related to Glacial Lake Outburst Floods (GLOFs) in Bilhanz and Badswat, Ishkoman Valley, were thoroughly examined between July to September 2024. These events led to significant landscape alterations, transforming once fertile agricultural and forest lands into debris covered areas, as evidenced by satellite and digital camera imagery. A large lake formed in Badswat, destroying extensive agricultural and forest land, which forced the relocation of many residents. Most displaced individuals received housing support from the Aga Khan Agency for Habitat (AKAH), while the government provided limited assistance. The Saudi government also made notable contributions. Between 2018 and 2021, successive GLOF events damaged 186 hectares of agricultural land in both villages in addition to damages and losses to livestock and other life supporting systems. Climate change and deforestation were identified as the primary drivers of these disasters. A multivariate analysis revealed that gender, age, and education had significant impacts on awareness and perceptions of environmental degradation and climate change. Older respondents, particularly those aged 50-60, were the most influential in shaping future disaster preparedness and mitigation efforts. Although education had a smaller effect size, it still played a crucial role in raising environmental awareness. Mitigation strategies proposed include afforestation, carbon capture, renewable energy, and waste reduction. Many respondents emphasized the importance of community involvement and education in addressing environmental issues. However, opinions vary on the most effective methods for controlling soil pollution and improving overall environmental health.

The paper discusses the relation between Environmental, Social and Governance (ESG) performance and financial performance of the both the industries which are highly polluting in regards to profitability, market value, cost burden and risk reduction. It is analyzed in a quantitative form which is based on secondary data and the firms are divided into high, medium and low ESG performers. The results indicate that the percentage of high, medium and low ESG companies is 38, 42 and 20 respectively that implies that the industries are in a transitional stage of environmental scanning with ESG. The results indicate that there is a positive correlation between the ESG performance and profitability with the high ESG firms that reported an average of 18 proportion of profit margin compared to 14 and 10 proportion of profit margin of medium and low ESG firms respectively. Similarly, high ESF companies (22) relative to medium (16) and low (11) have greater growth in market values because of the preference of sustainable companies by investors. However, the realization of ESG is associated with the high-cost burden because ESG related costs increase by 26 percent that is greater than the revenue increase in the short term of 19%. The paper also mentions that, ESG plays a role in risk management, with high ESG firms having a smaller risk (30 percent) when compared to medium and low ESG firms (22 and 14 percent, respectively). In addition, the ESG ranks with a long-term financial impact (24) that is two times as much as its short-term impact (12), and this will serve to demonstrate its strategic importance. Overall, the findings suggest that, despite the fact that ESG investments may create short-term profitability, it has much to offer to the long-term financial performance, growth, and minimization of risks in highly polluting sectors.

The swift progression of sensor networks, IoT devices, and Big Data technology has changed the way data is being managed in numerous sectors including government agencies, healthcare and smart cities. For the emergent technological advancement, it is no longer sufficient to merely acquire data. The real value of big data lies in using AI to analyze data instantly and generate useful insights. When AI is used in big data technology, it creates concerns such as data scalability, data quality, interpretability, and global data privacy regulations. To address such issues, technologies like edge computing, federated learning, and zero-trust architecture are being cast-off. By means of an innovative synthesis of big data architectural development, ethical data practices, and AI integration, this paper offers a unified framework that conforms to emerging. By connecting these dimensions, the research offers a forward-looking view on creating intelligent, adaptive, and regulation-compliant data ecosystems.

Worldwide animal agriculture produces more greenhouse effects than the world’s other transportation altogether. Meat production and daily consumption interacts with each other. Lots of things affect the firmness of meat be it environmental, gregarious, economic, or religion based. Environmental factors comprise carbon depletion, greenhouse gas extraction and cutting of forest carbon monoxide emission. Unitary dairy animals used for milk can drink 50 gallons of water each day or twice, which adds up to swallowing the climate and it takes 683 gallons of water to produce just 1 gallon of milk. It will take more than 2,400 gallons of water to make 1 pound of meat. According to the United Nation's show "Combat Desertification", ten pounds of grain are needed to deliver just one pound of meat, and in the United States alone, 56 million acres of land were used to develop fodder for these animals goes. , While only 4 million land lands are delivering plants for people to eat. More than 90 percent of all Amazon rainforest cleared land since 1970 is used to brush pets. Similarly, one of the principle crops developed in the rainforest is soybean is used for animal feed. According to the report of California State Senate noted, “Studies have exposed that the lagoons produce toxic airborne chemicals that may be cause inflammation, immunity problems, allergy problems and neuron-chemical problems in humans.” Different countries have applied different radical steps to minimize the toxins from meat. Beef meat comes from cows and buffaloes and they are herbivores means they mostly reside on grass but due to deforestation their resources are getting lower. Strategies to control climate change include more production of fertilization, more greenery, more renewable resources, and more radical techniques to control overgrowing of population. In Brazil street farming technique is introduced to fight deforestation and carbon footprints by cleaning environment and producing more fertilizers for the growth of plant. In Japan, they are introducing totally pesticide free organic grass which is chemically free, as chemically manufactured pesticides produces more harmful effect in the environment and are not completely absorbed in the soil. In United states AMP grazing is introduced which means less grass more feeding which totally decays of harmful bacteria from soil. Meanwhile in Pakistan, no radical steps are being introduced other than comparisons with different countries. Pakistan is one of the emerging agriculture hubs in world radical steps must be taken to support this ratio.