Global warming has increased drought frequency, especially seasonal droughts in China's Ultisol regions, which are characterized by a topsoil water deficiency while retaining water in the subsoil. Bio-tillage helps crops cope with drought by utilizing subsoil water, but the key pathways regulating this drought tolerance remain unclear. This study investigates whether bio-tillage mitigates drought in summer maize on clayey red soil and explores its underlying mechanism via a field experiment. The treatments included four winter cover crops (taproot crops of two rapes and lucerne, and fibrous-rooted vetiver) and CK (fallow, no plant), used as cover crops prior to summer maize, investigating their influence on soil water content (SWC) and available water content (SAWC), soil aggregate stability (mean weight diameter and geometric mean diameter), aggregates larger than 0.25 mm, alkaline hydrolyzable nitrogen (N), available phosphorus (P) and potassium (K), organic matter (SOM), root exudates and microbial diversity, gradients between the maize and soil water potential (1root - 1soil, 1leaf - 1root), drought indicators (soil drought degree, marked by D, crop water stress index, marked by CWSI) and maize yield over three distinct years: 2019, characterized by drought, 2021, representing average conditions, and 2022, marked by severe drought. Our findings revealed that bio-tillage significantly mitigated yield losses by 5.3-42.6% compared to CK in 2019 and 2022, and increased SWC (12-116% at 40-60 cm depth) at different maize growth stages in three years. Bio-tillage improved soil structure, increased the availability of N, P, K and SOM, although enhancements in biological properties were less pronounced in the severe seasonal drought. Notably, fibrous root vetiver treatment excelled in enhancing soil physical properties (soil aggregate stability and SAWC), further reducing D by over 33%, and exhibited higher gradients (1root - 1soil, 1leaf - 1root) and a lower CWSI than taproot crops (two rapes and lucerne) and CK. Partial least squares path modeling analysis further revealed that bio-tillage primarily modulated D, CWSI and yield indirectly through regulation of SWC via changes in soil physical properties. Soil aggregate stability had a greater impact on drought reduction (0.88 in total effect) than SOM and N (0.45 in total effect), and root exudates and microbial diversity (0.13 in total effect). Bio-tillage mitigated maize drought by improving soil water content and its availability, particularly in deep soil. This was mainly driven by the synergistic improvements in soil aggregate stability, aggregates larger than 0.25 mm and SOM. It suggests that bio-tillage is an effective measure for mitigating seasonal drought in humid areas under crop rotation systems.

Groundwater contamination by fluoride (F⁻) and arsenic (As) is a serious environmental issue and poses significant human health risks in many developing countries, including Pakistan, particularly in Sindh Province. To investigate a realistic situation of groundwater contamination, a total of 170 groundwater samples were collected and analyzed concerning F− and (As) along with other physicochemical parameters. The concentrations of fluoride (F⁻) and arsenic (As) in groundwater samples ranged from 0.5 to 6.35 mg/L and 0.5 to 22 µg/L, with mean values of 1.82 mg/L and 5.78 µg/L, respectively. Hydrochemical facies result show that water type of the groundwater resources of the study area belong to mixed CaNaHCO3 followed by CaHCO3 type while few samples fall into NaCl type. Gibbs diagrams indicate that rock–water interaction controls groundwater hydrochemistry, with saturation indices showing calcite, dolomite, fluorite, and goethite are saturated in the study area. Machine Learning (ML) models, including Random Forest (RF), Artificial Neural Network (ANN) and Logistic Regression (LR), were applied and the target variable was F− due to its higher concentration in groundwater samples as compared to As. In ML, models the permutation feature, as well as the mean decrease in impurity (MDI), was used to identify the variables affecting F− in the research region. Among the models, RF achieved the highest accuracy (0.94) and sensitivity (0.97), along with a relatively low error rate (0.06). ANN showed strong performance with an accuracy of 0.92 and sensitivity of 0.88, while LR demonstrated comparatively lower sensitivity (0.81) despite achieving an accuracy of 0.90. The study shows that groundwater in the Dadu Canal Command area is affected by dual contamination, and that integrating hydrogeochemical analysis with machine learning helps identify sources and spatial risk, supporting groundwater management in Sindh.

It has been widely recognized that replacing chemical fertilizers with organic fertilizers (organic substitution) could significantly increase the long-term productivity of the land and potentially enhance resilience to climate change. Nevertheless, there is limited information on the accurate monitoring of soil greenhouse gas (GHG) fluxes at different levels of organic substitution in rubber plantations. Before accurate estimation of soil GHG fluxes can be made, it is important to investigate diurnal variations and suitable sampling times. In this study, six treatment groups of rubber plantations in the Longjiang Farm of Baisha Li autonomous county, Hainan Island, including the control (CK), conventional fertilizer (NPK), and organic substitution treatments in which organic fertilizer replaced 25% (25%M), 50% (50%M), 75% (75%M), and 100% (100%M) of chemical nitrogen fertilizer were selected as study objectives. The soil GHG fluxes were observed by static chamber-gas chromatography for a whole day (24 h) during both wet and dry seasons. The results showed the following: (1) There was a significant single-peak daily variation of GHGs in rubber plantation soils. (2) The soil GHG fluxes observed from 9:00–12:00 are closer to the daily average fluxes. (3) Organic fertilizer substitution influenced soil CO2 and N2O fluxes and had no significant effect on soil CH4 fluxes. Fluxes of soil CO2 and N2O increased firstly and then decreased gradually when the substitution ratios exceeded 50% or 75%. (4) Soil CO2 and N2O fluxes were positively correlated with soil temperature and soil moisture, and CH4 fluxes were negatively correlated with soil temperature and soil moisture in both wet and dry seasons. The study indicated that understanding the daily pattern of GHG changes in rubber forest soils under different levels of organic fertilizer substitution and the optimal observation time could improve the accurate assessment of long-timescale observation studies.

Federated learning (FL) has received much attention in privacy-preserving and responsible recommender systems. Recent studies have shown promising results while federating widely-used recommendation methods such as collaborative filtering. A major barrier when bringing FL into production is that the model complexity or the volume of gradients to be transmitted over the communication channel grows linearly as the number of items in a particular system increases. To address this challenge, we propose a communication-efficient neural collaborative filtering method for federated recommender systems. First, to align our solution with other deep neural architectures, we construct standard neural collaborative filtering in federated settings. Second, to solve the underlying model complexity challenge, a multi-armed bandit framework is used that intelligently selects a smaller set of payloads for each iteration of federated model training. The item selection is based on a carefully designed reward function that determines which portion of the overall payloads would be optimal for a particular user. The FL model only comprising of the selected items is transmitted over the network. The FL users train their local models in the regular federated learning way utilizing the payload-efficient global model, requiring no additional optimizations. The results show that using only 10% of the model’s payload, our method can achieve recommendation performance comparable with the standard federated neural collaborative filtering.

Recommender systems (RS) play an integral role in many online platforms. Exponential growth and potential commercial interests are raising significant concerns around privacy, security, fairness, and overall responsibility. The existing literature around responsible recommendation services is diverse and multidisciplinary. Most literature reviews cover a specific aspect or a single technology for responsible behavior, such as federated learning or blockchain. This study integrates relevant concepts across disciplines to provide a broader representation of the landscape. We review the latest advancements toward building privacy-preserved and responsible recommendation services for the e-commerce industry. The survey summarizes recent, high-impact works on diverse aspects and technologies that ensure responsible behavior in RS through an interconnected taxonomy. We contextualize potential privacy threats, practical significance, industrial expectations, and research remedies. From the technical viewpoint, we analyze conventional privacy defenses and provide an overview of emerging technologies including differential privacy, federated learning, and blockchain. The methods and concepts across technologies are linked based on their objectives, challenges, and future directions. In addition, we also develop an open source repository that summarizes a wide range of evaluation benchmarks, codebases, and toolkits to aid the further research. The survey offers a holistic perspective on this rapidly evolving landscape by synthesizing insights from both RS and responsible AI literature.

Privacy concerns in recommender systems are potentially addressed due to constitutional and commercial requirements. Centralized recommendation models are susceptible to poisoning attacks, which threaten their integrity. In this context, federated learning has emerged as an optimal solution to privacy concerns. However, recent investigations proved that Federated Recommender Systems (FedRS) are also vulnerable to model poisoning attacks. Existing attack possibilities highlighted in academic literature require a large fraction of Byzantine clients to effectively influence the training process, which is unrealistic for practical systems with millions of users. Additionally, most attack models neglected the role of the defense mechanism running at the aggregation server. To this end, we propose a novel undetectable hidden attack strategy (HidAttack) for FedRS, aiming to raise the exposure ratio of targeted items with minimum Byzantine clients. To achieve this goal, we construct a cluster of baseline attacks, on top of which a bandit model is designed that intelligently infers effective poisoned gradients. It ensures a diverse pattern of poisoned gradients and therefore, Byzantine clients cannot be distinguished from benign clients by the defense mechanism. Extensive experiments demonstrate that: 1) our attack model significantly increases the target item's exposure rate covertly without compromising the recommendation accuracy; and 2) the current defenses are insufficient, emphasizing the need for better security improvements against our model poisoning attack to FedRS.

Amphibians, especially frogs, play a critical role in ecosystems, acting as prey and predator and influencing nutrient cycling between aquatic and terrestrial habitats. This study aimed to isolate and identify fungal species present on the skin of the bullfrog ( Hoplobatrachus tigerinus) in District Kasur, Pakistan. A total of 20 bullfrogs were sampled, and mucus swabs were taken from their skin to analyze fungal communities. The swabs were cultured on Sabouraud Dextrose Agar, Potato Dextrose Agar, and Brain Heart Infusion Agar. Morphological and biochemical techniques were used for the identification of fungal species. A total of 35 fungal isolates representing four species including Aspergillus niger, Aspergillus fumigatus, Aspergillus terreus, and Rhizopus stolonifer were identified. Aspergillus niger (60%) was the most prevalent species, followed by Aspergillus fumigatus (50%), Rhizopus stolonifer (30%) and Aspergillus terreus (15%). It can be concluded that the presence of Aspergillus spp., may have significant effects on health of Hoplobatrachus tigerinus. However, more research is needed to determine whether these fungi are benign, symbiotic, or pathogenic in amphibians. Future studies should aim to investigate the specific interactions between these fungi and their amphibian hosts, especially under various environmental stress conditions, such as pollution or climate change.

Poor soil physical properties related to the least limiting water range (LLWR) limit the productivity of clayey red soil (Ultisol) under a subtropical monsoon climate in southern China. This study evaluated the effects of bio-tillage on LLWR and identified the key factors influencing LLWR through a field experiment. The treatments included no plant, two cultivars of oilseed rape (Brassica napus L. cv. Huashuang 4 and Brassica napus L. cv. Xinan 28), one-year-old and perennial lucerne (Medicago sativa L. cv. Ladino), and one-year-old and perennial vetiver (Vetiveria zizanioides L. cv. Wild), used as cover crops prior to summer maize. Key parameters measured included plant root morphological traits, and soil bulk density, field capacity (FC), wilting point (PWP), available water content (AWC), penetration resistance (PR) and air-filled porosity (AFP) were determined. The two rape cultivars exhibited the shallowest root distribution (limited to 20 cm depth) and the lowest root surface density (RSD, similar to 16.61 cm(2)cm(-)(3)) and root volume density (RVD, similar to 0.58 cm(3)cm(-)(3)). In contrast, lucerne and vetiver demonstrated greater root development, with deeper root penetration (>60 cm), and higher RSD and RVD, with vetiver showing the highest values (RSD similar to 24.01 cm(2)cm(-)(3), RVD similar to 0.96 cm(3)cm(-)(3)). Lucerne and vetiver treatments increased AWC and AFP but reduced PR. Soil planted with vetiver had lower FC (0.35-0.48 cm(3)cm(-3)) and PR (1362-3297 kPa) than soil planted with lucerne, while soil planted with lucerne had a lower PWP (0.25-0.35 cm(3)cm(-3)) than soil planted with vetiver. All crops improved LLWR at 0-20 cm depth, but vetiver increased LLWR below the depth of 20 cm due to its higher root length density (RLD) and RSD. Path analysis revealed that PR had the strongest direct negative effect on LLWR (coefficients from -1.0528 to -1.7642), while redundancy analysis showed a strong correlation between LLWR and the RSD (12.00 %) and RLD (11.33 %) of perennial vetiver, with weaker correlation to root diameter (7.00 %). Bio-tillage reduced PR through root growth, enhancing LLWR particularly at depth of 20-40 cm, with perennial vetiver showing the most significant improvement due to its deeper rooting depth and denser root distribution.

This study examines arsenic (As), a toxic environmental metal, with a focus on its health and trade risks, speciation, and biogeochemical cycling in Pakistan's alluvial rice ecosystem. Soil total As levels achieved an average of 26.02 mg/kg (10.29-84.85 mg/kg), surpassing the WHO's guideline of 10 mg/kg for agricultural soils, indicating widespread contamination. Rice As concentrations ranged from 0.0001 to 4.12 mg/kg, with 56.8 % of samples exceeding the FDA's permissible limit of 0.1 mg/kg-the discrepancy between total As and its species concentrations is due to the different As forms present. Inorganic species (AsIII and AsV) ranged from 2.08 to 10.06 μg/kg and 1.23-10.96 μg/kg, while organic species (MMAs and DMAs) ranged from 1.09 to 9.18 μg/kg and 1.05-9.30 μg/kg, respectively, indicating active methylation. Strong correlations were found between total arsenic and both inorganic (R2 = 0.607 and 0.602) and organic species (R2 = 0.677 and 0.654). This suggests that total As levels in rice reflect both inorganic and organic forms, with transformation processes contributing to the variation in concentrations. The hazard risk model indicates that 69 % of Pakistan's population (approximately 100 million) faces a high risk of inorganic As exposure due to daily rice consumption, exceeding 0.02-0.04 mg/kg/day. Pakistan, the fourth-largest rice exporter globally, distributes 63.33 % of its rice to Asia, 29.2 % to Africa, 4.96 % to Europe, 1.54 % to North America, and 0.98 % to Oceania. The study predicts that the largest importers of rice with elevated As levels are China (138.25 kg/year), Malaysia (50.93 kg/year), Indonesia (49.20 kg/year), Afghanistan (46.76 kg/year), the UAE (46.50 kg/year), and Saudi Arabia (16.06 kg/year). The study assumes that Indonesia (5,953), China (3,555), Malaysia (2,322), Saudi Arabia (1,481), the UAE (1,092), and Afghanistan (635) face the highest health risks per 100,000 people, which has a significant impact on their populations. Countries with robust monitoring systems are better equipped to mitigate risks, while those with weak or inadequate monitoring face higher exposure. The study advocates for stricter agricultural regulations and enhanced monitoring of As levels in both domestic and exported rice.

Flocculated particles, formed by the aggregation of clay particles, are common in rivers. These flocs exhibit a different behaviour than primary particles: they can deform and break apart, and they have greater settling velocities than the particles of which they are composed. The latter allows flocs, unlike primary clay particles, to deposit on the river bed in mildly turbulent conditions, potentially leading to interactions with the bed. Particularly in sand-bedded rivers, where bedforms shape the riverbed, there exists a potential interaction between flocs and the riverbed.Physical experiments were carried out in an annular flume, using a flocculant to induce flocculation. Different amounts of flocculant and various shear stress conditions were applied, and the resulting floc characteristics and bedform geometry were measured.Under lower shear conditions, the flocs were larger and transport rates were lower than under high shear conditions. However, under both shear conditions, flocs were transported via saltation and in suspension, and they became integrated within the sediment bed either as individual flocs, clusters, or sheets. Deposition occurred predominantly on the leeward side of the dune, revealing distinct stratigraphy patterns. The presence of flocs had a negligible impact on the actual geometry of the bedforms.This investigation highlights the active role of flocculated clay particles in sediment transport in riverine systems, contrary to the general assumption that clay particles behave passively as wash load. This finding has the potential to affect sediment transport rates of fines and contaminants and could have far-reaching impacts on the interpretation of mud deposits in the sedimentary rock record. For modelling and predicting the sediment dynamics in river systems a comprehensive understanding of the transport mechanisms of clay flocs is essential and should be taken into account.

Low sunlight availability/shading stress is one of the major abiotic stresses, limiting plant photosynthesis and biomass production. Maize is a C4 species and requires more sunshine for efficient photosynthesis rate. Thus, maize is a highly shade-sensitive species. We used carbon dots (CDs) and single-walled carbon nanotubes (SWCNTs) as a foliar application to enhance maize photosynthesis under no-shading and shading stress. The results revealed that under shading stress, the higher concentration of CDs and SWCNTs reduced the MDA (Malondialdehyde) content and increased the expression level of superoxide dismutase ( SOD ), peroxidase ( POD ), and catalase ( CAT ) genes. Moreover, under shading stress, CDs and SWCNTs increased the average thickness of leaf lamina, vascular bundle, mesophyll, and epidermis. CDs and SWCNTs reduced the damaging effects of shading stress on the chloroplast (Ch) formation. CDs and SWCNTs upregulated Rubisco and related genes under shading stress. The chlorophyll fluorescence parameters, including the efficiency of quantum yield of photosystem II (Fv/Fm), electron transport rate (ETR), non-photochemical quenching coefficient (NPQ), and photochemical quenching coefficient (qP) were improved with the foliar application of CDs and SWCNTs under shading stress. Higher stomatal conductance, intercellular CO2 concentration, transpiration, and net photosynthesis were observed in maize plants treated with CDs and SWCNTs under shading stress. The results of our study suggest that using higher concentrations of CDs and SWCNTs can enhance plant growth and photosynthesis under shading stress conditions. However, to avoid nanotoxicity, great care is recommended when selecting different concentrations of nanomaterials based on the growing conditions.

The herpetofauna diversity of Pakistan is underestimated due to the country's lack of molecularbased identification. Field surveys were conducted from August 2018 through July 2022 to collect as many as possible specimens from Punjab, Pakistan. A total of 21 species were collected and initially identified by morphological characteristics. The three gene fragments in four amphibian species and seven reptile species were successfully amplified and sequenced. A total of 18 DNA sequences of 11 species representing nine genera and five families were deposited in GenBank, and accession numbers were obtained. Furthermore, phylogenetic analysis was performed through the Neighbor-joining method using 100 bootstrap pseudo-replicates in MEGA X. Closely related toad species, namely Duttaphrynus melanostictus and Duttaphrynus stomatitis, were clearly separated in the tree inferred from Cytb gene sequences. Similarly, conspecific sequences were analyzed for multiple individuals of Platyceps rhodorachis clustered together in the tree inferred from COI gene sequences. In our findings, 16S rRNA appears to be more reliable in identifying amphibian species, while COI has a better success rate in reptile species identification. In our recommendations, molecular-based identification of herpetofauna is necessary nationwide to document any new subspecies.

Climate change has increased drought frequency, necessitating strategies to reduce water stress, increase water use efficiency, and improve agricultural productivity. The impacts of different fall/winter cover crops on alleviating maize drought in the subsequent season by changing soil water content remain unclear in Ultisol. Our aim was to investigate whether different fall/winter cover crops (taproot and fibrous root) can improve soil water content to attenuate subsequent season maize drought and its underlying mechanism. This research compared four fall/winter cover crops (2 rapeseed cultivars, lucerne and vetiver) and fallow control (no cover crop in winter) to investigate their root traits, root effect on subsequent season soil water content (SWC), soil drought degree (D), maize leaf and root water potential (Ψl, Ψr), maize crop water stress index (CWSI), and maize growth components (aboveground plant and root parameters) in 2019 (a dry year), 2021 (a normal wet year), and 2022 (a severe dry year). The fibrous-rooted vetiver displayed higher average root diameter and higher average root length density, leading to increased SWC (17%, 15%, 15%), and lower D values in all three years. Additionally, it exhibited a more substantial gradient between Ψl, and Ψr and lower CWSI than taproot (rapeseed cultivars and lucerne) and fallow treatment. Furthermore, the cover crop treatments enhanced the gradient between maize Ψl and Ψr to varying degrees in different drought years. Ultimately, the improvement in SWC resulting from cover crop treatments increased maize aboveground growth (plant height, stem diameter, and leaf area) and maize root development, ultimately improving maize yield. This study introduces a new perspective on investigating the role of cover crops in alleviating seasonal drought in subsequent crops, especially by changing soil water properties in the subtropical climate.

Intense neuroinflammation contributes to neurodegenerative diseases, such as Alzheimer’s disease and Parkinson’s disease. Lipopolysaccharides (LPSs) are an integral part of the cell wall of Gram-negative bacteria that act as pathogen-associated molecular patterns (PAMPs) and potentially activate the central nervous system’s (CNS) immune system. Microglial cells are the local macrophages of the CNS and have the potential to induce and control neuroinflammation. This study aims to evaluate the anti-inflammatory and antioxidant effect of kojic acid against the toxic effects of LPSs, such as neuroinflammation-induced neurodegeneration and cognitive decline. The C57BL/6N mice were subjected to LPS injection for 2 weeks on alternate days (each mouse received 0.25 mg/kg/i.p. for a total of seven doses), and kojic acid was administered orally for 3 weeks consecutively (50 mg/kg/mouse, p. o). Bacterial endotoxins, or LPSs, are directly attached to TLR4 surface receptors of microglia and astrocytes and alter the cellular metabolism of immune cells. Intraperitoneal injection of LPS triggers the toll-like receptor 4 (TLR4), phospho-nuclear factor kappa B (p-NFκB), and phospho-c-Jun n-terminal kinase (p-JNK) protein expressions in the LPS-treated group, but these expression levels were significantly downregulated in the LPS + KA-treated mice brains. Prolong neuroinflammation leads to the generation of reactive oxygen species (ROS) followed by a decrease in nuclear factor erythroid-2-related factor 2 (Nrf2) and the enzyme hemeoxygenase 1 (HO-1) expression in LPS-subjected mouse brains. Interestingly, the levels of both Nrf-2 and HO-1 increased in the LPS + KA-treated mice group. In addition, kojic acid inhibited LPS-induced TNF-α and IL-1β production in mouse brains. These results indicated that kojic acid may suppress LPS-induced neuroinflammation and oxidative stress in male wild-type mice brains (in both the cortex and the hippocampus) by regulating the TLR4/NF-κB signaling pathway.

The resilience of tomato plants under different cultivation environments, particularly saline and non-saline conditions, was investigated by applying various treatments, including 0.5% Ascorbic Acid (AsA) and 1% Sulphur-treated Biochar (BS). The study evaluated parameters such as fruit length, diameter, yield per plant and pot, Total Soluble Solids (TSS) content, chlorophyll content, electrolyte leakage, enzyme activities (Superoxide Dismutase - SOD, Peroxidase - POD, Catalase - CAT), and nutrient content (Nitrogen - N%, Phosphorus - P%, Potassium - K%). Under saline conditions, significant enhancements were observed in fruit characteristics and yield metrics with the application of AsA and BS individually, with the combined treatment yielding the most substantial improvements. Notably, AsA and BS treatments exhibited varying effects on TSS levels, chlorophyll content, electrolyte leakage, and enzyme activities, with the combination treatment consistently demonstrating superior outcomes. Additionally, nutrient content analysis revealed notable increases, particularly under non-saline conditions, with the combined treatment showcasing the most significant enhancements. Overall, the study underscores the potential of AsA and BS treatments in promoting tomato resilience, offering insights into their synergistic effects on multiple physiological and biochemical parameters crucial for plant growth and productivity.

Alzheimer’s disease (AD) is the most predominant cause of dementia, considered a progressive decline in cognitive function that ultimately leads to death. AD has posed a substantial challenge in the records of medical science over the past century, representing a predominant etiology of dementia with a high prevalence rate. Neuroinflammation is a common characteristic of various central nervous system (CNS) pathologies like AD, primarily mediated by specialized brain immune and inflammatory cells, such as astrocytes and microglia. The present study aims to elucidate the potential mechanism of physcion that mitigates LPS-induced gliosis and assesses oxidative stress in mice. Physcion reduced the reactivity of Iba-1- and GFAP-positive cells and decreased the level of inflammatory cytokines like TNF-α and IL-1β. Physcion also reversed the effect of LPS-induced oxidative stress by upregulating the expression of Nrf2 and HO-1. Moreover, physcion treatment reversed LPS-induced synaptic disorder by increasing the level of presynaptic protein SNAP-23 and postsynaptic protein PSD-95. Our findings may provide a contemporary theoretical framework for clinical investigations aimed at examining the pathogenic mechanisms and therapeutic approaches for neuroinflammation and AD.