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Climatic variability has been acquiring an extensive consideration due to its widespread ability to impact food production and livelihoods. Climate change has the potential to intersperse global approaches in alleviating hunger and undernutrition. It is hypothesized that climate shifts bring substantial negative impacts on food production systems, thereby intimidating food security. Vast developments have been made addressing the global climate change, undernourishment, and hunger for the last few decades, partly due to the increase in food productivity through augmented agricultural managements. However, the growing population has increased the demand for food, putting pressure on food systems. Moreover, the potential climate change impacts are still unclear more obviously at the regional scales. Climate change is expected to boost food insecurity challenges in areas already vulnerable to climate change. Human-induced climate change is expected to impact food quality, quantity, and potentiality to dispense it equitably. Global capabilities to ascertain the food security and nutritional reasonableness facing expeditious shifts in biophysical conditions are likely to be the main factors determining the level of global disease incidence. It can be apprehended that all food security components (mainly food access and utilization) likely be under indirect effect via pledged impacts on ménage, incomes, and damages to health. The corroboration supports the dire need for huge focused investments in mitigation and adaptation measures to have sustainable, climate-smart, eco-friendly, and climate stress resilient food production systems. In this paper, we discussed the foremost pathways of how climate change impacts our food production systems as well as the social, and economic factors that in the mastery of unbiased food distribution. Likewise, we analyze the research gaps and biases about climate change and food security. Climate change is often responsible for food insecurity issues, not focusing on the fact that food production systems have magnified the climate change process. Provided the critical threats to food security, the focus needs to be shifted to an implementation oriented-agenda to potentially cope with current challenges. Therefore, this review seeks to have a more unprejudiced view and thus interpret the fusion association between climate change and food security by imperatively scrutinizing all factors.

Acoustic modem is one of the key elements of an underwater wireless sensor network (UWSN). Compared to a terrestrial wireless sensor network (WSN), designing a UWSN is more time consuming and expensive due to harsh conditions of the aquatic environment. Commercial modems provide better characteristics, but they consume more energy and are more expensive, while research modems have exploited diverse alternatives with varying success. The main contribution of the article is a comparative analyses of commercial and research modems based on their characteristics and design constraints, in order to describe the current trends and more promising techniques. This paper is focused on the state-of-the-art underwater acoustic modems designed, developed and implemented in the last few years. Various parameters of the modems are considered and analyzed: operating range, data-rate, modulation schemes, center frequency, bandwidth, power consumption, bit error rates, etc. Finally, design challenges, which need to be addressed, are identified. This study is useful for the engineering community to comprehend the characteristics, trends and design challenges of state-of-the-art underwater acoustic communication modems.

In this paper we introduce a robust numerical framework for simulating the nonlocal extended epidemic models that incorporate the fractional diffusion to capture the complex spatial–temporal dynamics of disease spread. The presented numerical scheme uses the Fourier spectral approach for spatial discretization and a positivity-preserving exponential time differencing approach for temporal integration. Two fractional epidemic models—the SIR model with a modified saturated incidence rate and the SEIR model—are analyzed to investigate the impact of fractional diffusion on disease transmission. The transmission dynamics are explored using the developed L-stable, positivity-preserving numerical method. Numerical experiments demonstrate the influences of the fractional diffusion on the spatial distribution and temporal evolution of infectious diseases. These experiments also highlight the importance of fractional diffusion in epidemic models and provide a rigorous computational framework that can be used in future research in public health policy and epidemic control strategies. A benchmark test problem with a known exact solution is considered, which confirms that the proposed L-stable scheme achieves second-order accuracy for different values of .

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused about 2 million infections and is responsible for more than 100,000 deaths worldwide. To date, there is no specific drug registered to combat the disease it causes, named coronavirus disease 2019 (COVID-19). In the current study, we used an in silico approach to screen natural compounds to find potent inhibitors of the host enzyme transmembrane protease serine 2 (TMPRSS2). This enzyme facilitates viral particle entry into host cells, and its inhibition blocks virus fusion with angiotensin-converting enzyme 2 (ACE2). This, in turn, restricts SARS-CoV-2 pathogenesis. A three-dimensional structure of TMPRSS2 was built using SWISS-MODEL and validated by RAMPAGE. The natural compounds library Natural Product Activity and Species Source (NPASS), containing 30,927 compounds, was screened against the target protein. Two techniques were used in the Molecular Operating Environment (MOE) for this purpose, i.e., a ligand-based pharmacophore approach and a molecular docking-based screening. In total, 2140 compounds with pharmacophoric features were retained using the first approach. Using the second approach, 85 compounds with molecular docking comparable to or greater than that of the standard inhibitor (camostat mesylate) were identified. The top 12 compounds with the most favorable structural features were studied for physicochemical and ADMET (absorption, distribution, metabolism, excretion, toxicity) properties. The low-molecular-weight compound NPC306344 showed significant interaction with the active site residues of TMPRSS2, with a binding energy score of −14.69. Further in vitro and in vivo validation is needed to study and develop an anti-COVID-19 drug based on the structures of the most promising compounds identified in this study.

The fuzzy fractional generalized FitzHugh-Nagumo differential equations (FFGFH-NDEs) is a well-known and generalized model that plays a significant role in biological systems, including complex synchronization in brain networks, cardiac dynamics, propagation of signals through nerve impulses, and digital circuit theory. The analytical study of the FFGFH-NDEs is more complex and difficult to deal with. An effective and efficient technique is required to solve FFGFH-NDEs analytically. This article introduces and investigates the analytical fuzzy solutions of FFGFH-NDEs using fuzzy fractional Caputo generalized Hukuhara ( FFCgH )-differentiability. The closed-form solutions of FFGFH-NDEs for various cases and types of FFCgH -differentiability are extracted for the homogeneous and nonhomogeneous case of the concerned model. The potential solutions are determined using fuzzy Laplace transform ( FLT ) and are presented in terms of multivariate Mittag-Leffler functions (MLFs). To highlight the innovation of this work, the digital memristor networks problem is designed and solved as an application of the proposed study including the graphical analysis to understand the uncertain behavior of the proposed model.

Arsenic (As) contamination in groundwater is a worldwide concern for drinking water safety. Environmental changes and anthropogenic activities are making groundwater vulnerable in Pakistan, especially in Southern Punjab. This study explores the distribution, hydrogeochemical behavior, and pathways of As enrichment in groundwater and discusses the corresponding evolution mechanism, mobilization capability, and health risks. In total, 510 groundwater samples were collected from three tehsils in the Punjab province of Pakistan to analyze As and other physiochemical parameters. Arsenic concentration averaged 14.0 μg/L in Vehari, 11.0 μg/L in Burewala, and 13.0 μg/L in Mailsi. Piper-plots indicated the dominance of Na+, SO42−, Ca2+, and Mg2+ ions in the groundwater and the geochemical modeling showed negative saturation indices with calcium carbonate and salt minerals, including aragonite (CaCO3), calcite (CaCO3), dolomite (CaMg(CO3)2), and halite (NaCl). The dissolution process hinted at their potential roles in As mobilization in groundwater. These results were further validated with an inverse model of the dissolution of calcium-bearing mineral, and the exchange of cations between Ca2+ and Na+ in the studied area. Risk assessment suggested potential carcinogenic risks (CR > 10−4) for both children and adults, whereas children had a significant non-carcinogenic risk hazard quotient (HQ > 1). Accordingly, children had higher overall health risks than adults. Groundwater in Vehari and Mailsi was at higher risk than in Burewala. Our findings provide important and baseline information for groundwater As assessment at a provincial level, which is essential for initiating As health risk reduction. The current study also recommends efficient management strategies for As-contaminated groundwater.

The presence of residual Cr(VI) in soils causes groundwater contamination in aquifers, affecting the health of exposed populations. Initially, permeable reactive barriers(PRB) effectively removed Cr(VI) from groundwater. However, as PRB clogging increased and Cr(VI) was released from upstream soils, the contamination plume continued to spread downstream. By 2020, the level of contamination in the downstream was nearly identical to that in the upstream. The study results show that during normal operation, the PRB can successfully remove Cr(VI) from contaminated groundwater and reduce the carcinogenic and non-carcinogenic risks to humans from the downstream side of groundwater. However, the remediated groundwater still poses an unacceptable risk to human health. The sensitivity analysis revealed that the concentration of the pollutant was the most sensitive parameter and interacted significantly with other factors. Ultimately, it was determined that the residual Cr(VI) in the soil of the study region continues to contaminate the groundwater and constitutes a serious health danger to residents in the vicinity. As remediated groundwater still poses a severe threat to human health, PRB may not be as effective as people believe.

For shallow groundwater, hydrogeochemical processes and quality assessment must be addressed because shallow groundwater is freely available in many parts of the globe. Due to recent anthropogenic activities and environmental changes in Sakrand, Sindh, Pakistan, the groundwater is extremely vulnerable. To provide safe drinking and agricultural water, hydrogeochemical analysis is required. Ninety-five groundwater samples were analyzed using agricultural and drinking indices to determine the hydrogeochemical parameters using multivariate analysis such as Pearson correlations, principal component cluster analysis, as well as Piper diagrams and Gibbs plot for drinking and agricultural indices. An abundance of ions was observed through the statistical summary; however, cations and anions were recorded in the orders Na+ > Ca2+ > Mg2+ > K+ and HCO3− > Cl− > SO42− > NO3− > F−. The hydrogeochemical process used to quantify the major reactions occurring in the groundwater system showed rock dominance; the Piper diagrams evaluated the water type. A mixed pattern of calcium, magnesium, and chloride ions (Ca2+−Mg2+−Cl− type) was observed. Additionally, the ion exchange method showed an excess of bicarbonate ions due to carbonic acid weathering. The water quality index (WQI) resulted 32.6% of groundwater being unsuitable for human consumption; however, the United States Salinity Laboratory (USSL) diagram showed 60% of samples were unsuitable for irrigation due to high salinity and the Wilcox diagram depicted 5% of samples lying in the unsuitable region. Most of the water samples were suitable for drinking; only a few samples were unsafe for drinking purposes for children due to the high hazard index.

This study presents a novel integration of the Water Ratio Index (WRI), Normalized Difference Chlorophyll Index (NDCI), Land Use/Land Cover (LULC) mapping, and Cellular Automata–Markov (CA–Markov) modeling with temperature fluctuations to monitor irrigated land dynamics using high-resolution (30m) satellite imagery in South Africa’s North West Province between 2016 to 2023, revealing critical challenges to agricultural sustainability and water resource management. Satellite imagery and geospatial analysis show irrigated lands concentrated in the region, which declined from 25,732 km 2 to 24,322 km 2 , while urbanization expanded built-up areas from 4,146 to 6,581 km 2 , competing for arable land. The CA–Markov model predicts further agricultural loss by the year 2033, with barren land dominating (62.54%) and water bodies shrinking to 1.72%, worsening water scarcity. WRI values dropped from 0.40 in 2016 to 0.28 in 2023, reflecting increasing water stress, while temperatures rose sharply in summer, peaks up to 35.99 °C in 2023, intensifying evapotranspiration and irrigation demands. The study identifies institutional barriers such as biased subsidies, poor rural infrastructure, and climate extremes as key drivers of irrigation decline, mirroring global patterns in arid regions. The integration of the CA Markov model with WRI and temperature trends provides a robust framework for adaptive land-use planning, emphasizing stakeholder engagement and technology adoption to mitigate climate impacts and ensure food-water security in this vulnerable semi-arid region. This manuscript reflects the multi-dimensional approach to synthesizes multi-index, multi-temporal remote sensing analysis to deliver both spatial and predictive insights. This multi-model fusion bridges the gap between biophysical water availability, vegetation health, land transition trends, and future irrigation scenarios, offering a more holistic and scalable solution for water-scarce regions, driven by climate change provides critical insights into the interplay of water supply, land suitability, and climate variability, offering a foundation for adaptive strategies that support food security, livelihoods, and environmental sustainability in vulnerable regions.

The excessive use of chemical fertilizers is deteriorating both the environment and soil, making it a big challenge faced by sustainable agriculture. To assist the efforts for the solution of this burning issue, nine different potential native strains of plant growth-promoting bacteria (PGPB) namely, SA-1( Bacillus subtilis) , SA-5 ( Stenotrophomonas humi) ,SA-7( Azospirillum brasilense ), BH-1( Azospirillum oryzae ), BH-7( Azotobacter armeniacus ), BH-8( Rhizobium pusense ), BA-3( Azospirillum zeae ), BA-6( Rhizobium pusense ), and BA-7( Pseudomonas fragi ) were isolated that were characterized morphologically, biochemically and molecularly on the basis of 16S rRNA sequencing. Furthermore, the capability of indigenous PGPB in wheat ( Triticum aestivum , Chakwal-50) under control, DAP+FYM, SA -1,5,7 , BH -1,7,8 , BA -3,6,7 , DAP+ FYM + SA -1,5,7 , DAP+FYM+ BH -1,7,8 and DAP+FYM+ BA -3,6,7 treatments was assessed in a randomized complete block design (RCBD). The results of the study showed that there was a significant increase in plant growth, nutrients, quality parameters, crop yield, and soil nutrients at three depths under SA -1,5,7 , BH -1,7,8 , and BA -3,6,7 in combination with DAP+FYM. Out of all these treatments, DAP+ FYM + BA -3,6,7 was found to be the most efficient for wheat growth having the highest 1000-grain weight of 55.1 g. The highest values for plant height, no. of grains/spike, spike length, shoot length, root length, shoot dry weight, root dry weight, 1000 grain weight, biological yield, and economic yield were found to be 90.7 cm, 87.7 cm, 7.20 cm, 53.5 cm, 33.5 cm, 4.87 g, 1.32 g, 55.1 g, 8209 kg/h, and 4572 kg/h, respectively, in the DAP+FYM+BA treatment. The DAP+FYM+BA treatment had the highest values of TN (1.68 µg/mL), P (0.38%), and K (1.33%). Likewise, the value of mean protein (10.5%), carbohydrate (75%), lipid (2.5%), and available P (4.68 ppm) was also highest in the DAP+FYM+BA combination. C:P was found to be significantly highest (20.7) in BA alone but was significantly lowest (11.9) in DAP+FYM+BA. Hence, the integration of strains BA-3, BA-5, and BA-7 in fertilizers can be regarded as the most suitable choice for agricultural growth in the sub-mountainous lower region of AJK. This could serve as the best choice for sustainable wheat growth and improved soil fertility with lesser impacts on the environment.