Shifts In Patterns Research Articles

Transposable element small and long RNAs in aging brains and implications in Huntington's and Parkinson's disease.

Transposable Elements (TEs) are implicated in aging and neurodegenerative disorders, but the impact of brain TE RNA dynamics on these phenomena is not fully understood. Therefore, we quantified TE RNA changes in aging post-mortem human and mouse brains and in the neurodegenerative disorders Huntington's Disease (HD) and Parkinson's Disease (PD). We tracked TE small RNAs (smRNAs) expression landscape to assess the relationship to the active processing from TE long RNAs (lnRNAs). Human brain transcriptomes from the BrainSpan Atlas displayed a significant shift of TE smRNA patterns at age 20 years, whereas aging mouse brains lacked any such marked change, despite clear shift in aging-associated mRNA levels. Human frontal cortex displayed pronounced sense TE smRNAs during aging with a negative relationship between the TE smRNAs and lnRNAs indicative of age associated regulatory effects. Our analysis revealed TE smRNAs dysregulation in HD, while PD showed a stronger impact on TE lnRNAs, potentially correlating with the early average age of death for HD relative to PD. Furthermore, TE-silencing factor TRIM28 was down-regulated only in aging human brains, possibly explaining the lack of substantial TE RNA changes in aging mouse brains. Our study suggests brain TE RNAs may serve as novel biomarkers of human brain aging and neurodegenerative disorders.

Utilizing graph neural networks for adverse health detection and personalized decision making in sensor-based remote monitoring for dementia care

Background:Sensor-based remote health monitoring is increasingly used to detect adverse health in people living with dementia (PLwD) at home, aiming to prevent hospitalizations and reduce caregiver burden. However, home sensor data is often noisy, overly granular, and suffers from unreliable labeling, data drift and high variability between households. Current anomaly detection methods lack generalizability and personalization, often requiring anomaly-free training data and frequent model updates. Objective:To develop a lightweight, explainable, self-supervised approach with personalized alert thresholds to detect adverse health events in PLwD, using changes in home activity. Methods:We hypothesized that health downturns manifest as detectable shifts in household movement patterns. Our approach leverages a Graph Barlow Twins contrastive model, which uses granular activity data and a macroscopic view to extract noise-robust, high-level and low-level discriminative features that represent daily activity patterns. Household-personalized alert thresholds are calculated based on clinician-set target alert rates, and daily anomaly scores are compared against these thresholds, triggering alerts for the clinical monitoring team. Model attention weights support explainability. Data were collected from a real-world dataset by the UK Dementia Research Institute (August 2019-April 2022). Results:Our model outperformed state-of-the-art temporal graph algorithms in detecting agitation and fall events across three patient cohorts, achieving 81% average recall and 88% generalizability at a target alert rate of 7%. Conclusion:We developed a novel, lightweight, explainable, and personalized Graph Barlow Twins model for real-world remote health monitoring in dementia care, with potential for broader applications in healthcare and sensor-based environments.

Extracting Meso- and Microscale Patterns of Urban Morphology Evolution: Evidence from Binhai New Area of Tianjin, China

Understanding and recognizing urban morphology evolution is a crucial issue in urban planning, with extensive research dedicated to detecting the extent of urban expansion. However, as urban development patterns shift from incremental expansion to stock optimization, related studies on meso- and microscale urban morphology evolution face limitations such as insufficient spatiotemporal data granularity, poor generalizability, and inability to extract internal evolution patterns. This study employs deep learning and meso-/microscopic urban form indicators to develop a generic framework for extracting and describing the evolution of meso-/microscale urban morphology. The framework includes three steps: constructing specific urban morphology datasets, semantic segmentation to extract urban form, and mapping urban form evolution using the Tile-based Urban Change (TUC) classification system. We applied this framework to conduct a combined quantitative and qualitative analysis of the internal urban morphology evolution of Binhai New Area from 2009 to 2022, with detailed visualizations of morphology evolution at each time point. The study identified that different locations in the area exhibited seven distinct evolution patterns: edge areal expansion, preservation of developmental potential, industrial land development pattern, rapid comprehensive demolition and construction pattern, linear development pattern, mixed evolution, and stable evolution. The results indicate that in the stock development phase, high-density urban areas exhibit multidimensional development characteristics by region, period, and function. Our work demonstrates the potential of using deep learning and grid classification indicators to study meso-/microscale urban morphology evolution, providing a scalable, cost-effective, quantitative, and portable approach for historical urban morphology understanding.

Could resistance training prevent or improve work-related musculoskeletal disorders among surgeons?

Studies have demonstrated the negative impact that work-related musculoskeletal disorders (WMSDs) have on surgeons. These are also likely to affect some allied healthcare professionals such as interventional radiologists. Problems from WMSDs include pain, diminished technical and cognitive performance, and work absence. These could contribute to burnout, to which surgeons are already vulnerable owing to other working practices such as shift patterns and long hours. WMSDs could negatively affect working performance, and lead to poorer surgical outcomes and patient care. Surgeons are at risk of WMSDs of the neck and back that result from fixed and damaging postures while operating. Some have reduced their operation numbers and working days as result of WMSDs. Theatre ergonomics (e.g. table positioning, operating stools and monitors), intraoperative breaks and stretching may improve WMSDs for some. Strength/resistance training (RT) may be used to prevent or mitigate WMSDs. RT can also enhance general health and concentration, and combat intraoperative fatigue. Low engagement times of moderate-intensity RT of 20 minutes, twice a week, improve neck and back pain from WMSDs. Moreover, RT has been shown to reduce all-cause mortality by up to 15%, increase bone density, improve proprioception and reduce the fear of movement due to pain. Alongside ergonomic improvement and stretching, we recommend RT as an activity to improve general health and WMSDs.

Incidence of Self-Reported Bothersome Tinnitus Versus Tinnitus Diagnosis Among U.S. Army Soldiers.

U.S. Army Soldiers undergo annual audiometric surveillance to facilitate prevention of auditory injury. Soldiers are screened for bothersome tinnitus and subsequently referred for a clinical audiological evaluation as warranted. Presumably, most Soldiers seen in the clinic for bothersome tinnitus receive a tinnitus diagnosis. The incidence of self-reported bothersome tinnitus at the time of annual audiometric surveillance and subsequent diagnosis of tinnitus in the medical record has not been examined to date. This study estimated the incidence of tinnitus diagnosis in a population of Soldiers who reported new onset bothersome tinnitus and explored trends associated with tinnitus diagnosis to refine hearing health education. A subset of hearing conservation records retrieved for a previous study were selected based on change in self-reporting of bothersome tinnitus. Corresponding medical records were retrieved for this sample of Active Duty (AD) Soldiers. The data were retrospectively examined, and analyses were conducted to identify statistically significant differences between Soldiers with and Soldiers without a tinnitus diagnosis. In addition, trend patterns of bothersome tinnitus and significant threshold shift (STS) were examined. Of the sample of 730,350 AD Soldiers, 16.7% self-reported new onset bothersome tinnitus and 7.1% of those recorded as having bothersome tinnitus had a diagnosis of tinnitus in their medical record. Soldiers with a tinnitus diagnosis were older and had higher pure-tone averages than Soldiers without a tinnitus diagnosis. Counterintuitively, overall trend percentages of bothersome tinnitus increased per calendar year, while the percentages of STS decreased throughout the study period. The rate of tinnitus diagnosis in the medical record is vastly lower than the prevalence of bothersome tinnitus recorded in the annual surveillance system. Steps should be taken to screen, refer, and diagnose tinnitus more consistently. Based on the outcome of the study analysis, we recommend that screening for bothersome tinnitus more closely follows procedure recommendations from the Department of Veterans Affairs and Department of Defense (VA/DOD) Tinnitus Working Group, which may reduce the rate at which Soldiers report bothersome tinnitus.

Ichnoguild analysis of the Bajocian-Bathonian Yellow Flagstone Member (Goradongar Formation) from the Kachchh Basin, Western India

The Yellow Flagstone is the oldest member of the Goradongar Formation exposed in the Pachchham Island, Kachchh Basin. The members exposed in four sections are mapped for trace fossils, and 17 ichnofossils have been documented. The concept of ichnoguild (IG) is applied to reveal the infaunal tiering structure and the strategies organisms adapt to exploit the resources. Ten IG of similar characteristics and ecological functions have been identified. Five are shallow-tier IGs ( Asterosoma IG, Gyrochorte IG, Nereites IG, Planolites IG and Bolonia IG), three middle-tier IGs ( Rhizocorallium IG, Arenicolites-Diplocraterion IG and Zoophycos-Teichichnus IG) and two deep-tier IGs ( Skolithos Arenicolites IG and Thalassinoides-Ophiomorpha IG). The analysis of three ichnological tiers and their IGs, namely shallow, middle and deep-tiers across the stratigraphy of Yellow Flagstone Member suggests a transition from a lower shoreface environment to offshore transition environments. The transition is supported by an increase in deep-tier IG and the marginal increase in the ichnodiversity and density. Changes in the composition and abundance of IGs over time can indicate shifts in sedimentation patterns, sea level fluctuations and paleoenvironmental conditions within the basin. Thus, the findings suggest an environmental shift from shoreface to offshore transition indicative of a transgression during the deposition of upper Bajocian to lower Bathonian Yellow Flagstone Member in the Kachchh Basin. The study also examines the temporal and spatial changes in the IGs, contributing to a better understanding of ecological changes within the basin. The findings contribute to the broader knowledge of paleoecology and provide valuable data for sedimentological and stratigraphic interpretations in sedimentary basins.

Peri-Urban Floodscapes: Identifying and Analyzing Flood Risk Areas in North Bhubaneswar in Eastern India

Peri-urban catchment areas are increasingly susceptible to floods due to rapid land use transformations and unplanned urban expansion. This study comprehensively examines flood vulnerability in the rapidly developing peri-urban areas of North Bhubaneswar, focusing on significant changes in Land Use/Land Cover (LULC) and hydrological dynamics from 2004 to 2024, utilizing Geographic Information System (GIS) tools. The analysis reveals substantial shifts in land use patterns, with the urban footprint expanding by 71.8%, cropland decreasing by 21.7%, and forest areas by 13.6%. These changes have led to increased impervious surfaces, resulting in higher surface runoff and decreased groundwater recharge, thereby exacerbating flood risks in the region. The GRID-based vulnerability analysis classifies 90 villages within the catchment area based on their vulnerability levels, identifying 20 villages as high-risk areas requiring urgent attention, 44 villages as medium vulnerable, and 26 villages as low vulnerable. These classifications are based on factors such as proximity to drainage networks, slope, geomorphology, and LULC characteristics, with areas near drainage channels and low-lying regions being prone to flooding. The analysis integrates multiple factors to provide a comprehensive assessment of flood risk, highlighting the need for sustainable land use planning, conservation of vegetated areas, and the implementation of advanced flood prevention strategies in the peri-urban areas. Extending this research to other fringe regions could offer further valuable insights, guiding flood prevention and sustainable development strategies for areas undergoing significant land use transformations to effectively mitigate future flood risks.

The impact of technological advancements on global warming

Global warming, or climate change, refers to long term shifts in temperature and weather patterns. These shifts may be natural, however, from 1870, which is the start of the technical or second industrial revolution, there has been abnormally large amount of carbon dioxide (CO2) and other greenhouse gases such as methane and nitrous oxide getting trapped in the atmosphere, resulting in an enhanced greenhouse effect causing global temperatures to increase. This study seeks to assess and analyse the impact technology, its advancements and how it has impacted the global temperatures. By examining the correlation between technological development and CO2 emissions from machinery, this study will provide a comprehensive analysis of the relationship between the two.

Gender characterization in Lady Windermere’s Fan and its Chinese translations: A corpus stylistic approach

This study examines gender representation in Oscar Wilde’s comedy and satire, Lady Windermere’s Fan (1892), using corpus stylistic analysis. Specifically, it analyzes gender characterization patterns in the original drama and explores how these patterns shift in two Chinese translations: Shen Xingren’s translation in 1918 and Hong Shen’s translation in 1923. By analyzing keyword patterns, collocational patterns, and characterization cues, the study reveals the intricate nature of gender characterization in the source text. Subsequently, a comparison is made between the textual patterns of the source text and their manifestations in the translations. The findings indicate that while Shen Xingren’s translation quite faithfully (re)represents the gender images and relations of the source text, Hong Shen’s selective appropriation of women and men characterization in his translation not only suppresses the source text’s potential to challenge moral absolutism towards women but also undermines the voices of women present in the original text. The article suggests that the re-representation or shifts in gender characterization observed between the source and target texts can be attributed to the translator’s ideology and adherence to particular poetics.

Relationship Between Land Use Transformation and Ecosystem Service Value in the Process of Urban–Rural Integration: An Empirical Study of 17 Prefecture-Level Cities in Henan Province, China

Urban–rural integration, which aims to balance economic growth with sustainable land use, is becoming an increasingly critical strategy for regional development. This study provides crucial insights into the relationship between land use changes and ecosystem service values (ESVs) in rapidly urbanizing areas by analyzing the urban–rural integration process in Henan Province, a typical agricultural province in China. This research investigated the relationship between land use transformation and ESVs in Henan Province, China, from 1990 to 2020. Utilizing land use data and employing the equivalent factor method and elasticity model, we analyzed shifts in land use and their impacts on ecosystem services across 17 prefecture-level cities. Results indicated a gradual improvement in the urban–rural integration development index of Henan Province, particularly after 2000, but with notable disparities among cities. Zhengzhou, the provincial capital, consistently demonstrated high urban–rural integration development index (URII) values, influencing the integration efforts of neighboring cities. Conversely, peripheral cities exhibited lower integration indices. Notable shifts in land use patterns characterized by diverse transfer dynamics distinctively influenced ESVs across regions. Urban sprawl initially exerted substantial impacts on ecosystem services and stabilized over time. Suburbanization impacts peaked in the early and middle stages, while agricultural intensification initially affected ecosystem services, but their effects diminished with increased efficiency. Ecological restoration efforts consistently enhanced ESVs. The findings contribute to a more comprehensive understanding of the dynamic interactions between land use transitions and ecosystem services in the context of urban–rural integration.

The Shift Towards Plant-Based Lifestyles: Factors Driving Young Consumers’ Decisions to Choose Plant-Based Food Products

The shift in consumer dietary patterns from meat-based to plant-based food products has become a prominent trend worldwide. This shift is driven by various factors, including concerns about personal health and environmental awareness. Despite the global growth of the plant-based food industry, developing nations tend to be slow with adopting non-meat-based diets. This is mainly due to high levels of food insecurity and meat being the main source of protein, especially in countries like South Africa where food consumption is needs-based, and consumers are unaware of the environmental footprint of meat production. This paper is part of a two-phase study and reports on the quantitative results, which were obtained during the second phase. The main aim of this study was to investigate the factors that influence consumers’ decisions to choose plant-based food products. The factors that were selected were informed by the thematic results from phase 1, which involved focus groups that explored consumers’ opinions and behaviours towards plant-based lifestyles. By means of survey distribution, 426 online questionnaires were distributed among young consumers in South Africa. A conceptual model with six hypotheses was tested and the data were analysed using SmartPLS 4.1.0.8. The findings indicated the product taste and product knowledge are the most important factors that drive young consumers’ decisions to choose plant-based food products. The study further found that product quality, affordability, social influence, and product packaging play a role but to a lesser degree. Food marketers can utilise these findings and implement marketing strategies that can assist with persuading consumers to choose plant-based food products and adopt a healthier, more sustainable lifestyle.

Uncovering Hidden Risks in IoT devices: A Post-Pandemic National Study of SOHO Wi-Fi Router Security

This study thoroughly analyzes the cybersecurity status of Small Office/Home Office (SOHO) Wi-Fi routers. These routers are crucial but frequently overlooked elements in network infrastructure, particularly in light of the impact of the COVID-19 pandemic on network security. The pandemic has led to shifts in network usage patterns, blurring traditional security perimeters and extending them into private residences, creating additional points of vulnerability in urban environments. Our nationwide research evaluated an extensive dataset of router brands and models currently used at scale. We measured the prevalence of known vulnerabilities, assessed the currency of userspace and kernel software versions, and compared the security robustness of proprietary firmware against open-source alternatives. Our findings reveal a concerning landscape of widespread vulnerabilities and outdated software components, posing latent risks to end-users. The results indicate a predominance of Linux on MIPS and ARM architectures, with an average delay of 5 to 10 years between the release of the kernel and the implementation of the most recent firmware versions. As a result, we observed an average of 1344 and 72 vulnerabilities in the kernel and applications. One significant discovery from our research is that replacing the manufacturer's original firmware with open-source alternatives, such as DD-WRT, OpenWrt, and Tomato, can substantially enhance the security of the software stack. This enhancement results in improvements of up to 97% in the case of binaries and 98.42% in the kernel. Our research helps increase cybersecurity awareness by pinpointing critical home network environment weaknesses and alerting the need for more rigorous security practices in producing and maintaining SOHO routers. This investigation also allowed the report of a new remote code execution vulnerability (disclosed in CVE-2022-46552).

Climate Change Effects on Spatiotemporal Distribution of Precipitation over West Central India: A Statistical Downscaling Approach

The long-term shifts in temperatures and weather patterns are referred to as climate change. Climate change not only leads to long-term shifts in average temperatures but also changes in the spatial and temporal distribution of rainfall over continents. This study aims to predict likely changes in the rainfall pattern induced by climate change over the West Central (WC) region of India. The approach uses a statistical downscaling technique that converts coarse-scale outputs of the global climate model (GCM) to high-resolution future precipitation projections giving refined distribution. The decision support tool that uses a robust statistical downscaling technique viz. statistical downscaling model (SDSM) is used for assessing local climate change impacts. The research includes the study of likely regional climate variability, by integrating historical observational data and empirical relationships between large-scale climate variables and local weather patterns. Historical data and the SDSM, version 4.2, are employed to forecast future rainfall trends. Rainfall data from the India Meteorological Department and the National Centre for Environmental Prediction (NCEP) from 1961 to 2001 are used along with outputs from general circulation models (GCMs), viz. Hadley Centre coupled model, version 3 (HadCM3), and coupled global climate model, version 3 (CGCM3), for the period 1961–2099. Rainfall scenarios are presented for three future time periods (2011–2040, 2041–2070, and 2071–2099). The study indicates a significant increase in the mean annual precipitation across the West Central India region, particularly in the 2050s and 2080s. Mean annual rainfall is projected to rise by 10–19.4% under HadCM3 A2 and B2 scenarios. The HadCM3 indicates the month of September as the month of the highest precipitation in later time periods, whereas it is the month of August, according to CGCM3 simulations. When comparing the results of the two models, HadCM3 gives better results, as indicated by better R2 value in validation. Thus, the analysis gives climate change-induced likely changes in the spatiotemporal distribution of precipitation over the West Central India region. The insight given by the work will be useful for decision making in many sectors like agriculture, water management, disaster risk reduction, and infrastructure planning.

The Effects of Climate Change on Kenya’s Economic Growth

Changes in the climate and natural disasters have hampered Kenya's growth in economy, as seen by periodic droughts, floods, and shifts in rainfall and temperature patterns. The research investigated the effects of climatic change on Kenya's GDP growth. Modeling was done using Autoregressive Distributed Lag (ARDL) model estimation technique while analyzing data from 1990 to 2023. Climate change was represented by annual rainfall fluctuations, carbon emissions, and forest depletion, with inflation, exchange rates, and government spending serving as the controlling factors. The regression results indicated that at 5% level of significance short run carbon emissions affect growth negatively but the long run results indicated a positive effect. Forest depletion positively impacts growth in the long run period. Government expenditure, changes in the exchange rate and economic growth had an inverse relationship. Inflation did not have potential long term impact on GDP. This study recommended that the government to balance economic growth with environmental sustainability by promoting cleaner technologies and renewable energy projects. Investments advanced irrigation and drought resistant crops are crucial. Sustainable forest management should involve controlled logging and reforestation to ensure long term health. Reducing exchange rate volatility through foreign reserves and diversified exports will stabilize the economy. Enhancing government expenditure efficiency by focusing on high return investments and minimizing waste will boost GDP stability.

Glacier Retreat Induces Contrasting Shifts in Bacterial Biodiversity Patterns in Glacial Lake Water and Sediment

Glacial lake ecosystems are experiencing rapid changes due to accelerated glacier retreat. As glaciers recede, their influence on downstream habitats diminishes, potentially affecting the biodiversity of glacial lake microbial communities. However, there remains a knowledge gap regarding how bacterial biodiversity patterns in glacial lakes are altered by diminishing glacial influence. Here, we investigated shifts in bacterial communities in paired water and sediment samples collected from seven glacial lakes on the Tibetan Plateau, using a space-for-time substitution approach to understand the consequences of glacier retreat. Our findings reveal that bacterial diversity in lake water increases significantly with a higher glacier index (GI), whereas sediment bacterial diversity exhibits a negative correlation with GI. Both the water and sediment bacterial communities display significant structural shifts along the GI gradient. Notably, reduced glacial influence decreases the complexity of bacterial co-occurrence networks in lake water but enhances the network complexity in sediment. This divergence in diversity and co-occurrence patterns highlights that water and sediment bacterial communities respond differently to changes in glacial influence in these lake ecosystems. This study provides insights into how diminishing glacial influence impacts the bacterial biodiversity in glacial lake water and sediments, revealing contrasting patterns between the two habitats. These findings emphasize the need for comprehensive monitoring to understand the implications of glacier retreat on these fragile ecosystems.

Understanding the local implications of climate change: Unpacking the experiences of smallholder farmers in Thulamela Municipality, Vhembe District, Limpopo Province, South Africa

Climate change is experienced locally. However, climate change impact assessments are often done at the international, regional and national levels. Local level impacts are less prolific. When international, regional and national level predictions are applied to the local level, they are out of context. Therefore, it is important to understand the local impact of climate change to enhance formulation of suitable adaptation strategies. This study aimed to understand the local impacts of climate change on smallholder farmers in Thulamela Municipality, Vhembe District, Limpopo Province, South Africa. The actual experiences of smallholder farmers were unpacked. Face-to-face interviews with farmers in the region were conducted to solicit data on the climatic changes experienced, the impacts on crop and livestock production and social wellbeing. Data on the intensity of the impacts was also solicited. Results show that the experienced climatic changes emanated from temperature changes and shifts in rainfall patterns. The impacts on crop and livestock production as well as social wellbeing are all negative. Farmers indicated that the impacts were mostly average to high. It is concluded that smallholder farmers are aware that climate change impacts are negatively affecting their livelihoods. Investments towards building the capacity of smallholder farmers are pertinent.

Molecular Characterization and Genomic Surveillance of SARS-CoV-2 Lineages in Central India.

Since the first reported case of COVID-19 in December 2019, several SARS-CoV-2 variants have evolved, and some of them have shown higher transmissibility, becoming the prevalent strains. Genomic epidemiological investigations into strains from different time points, including the early stages of the pandemic, are very crucial for understanding the evolution and transmission patterns. Using whole-genome sequences, our study describes the early landscape of SARS-CoV-2 variants in central India retrospectively (including the first known occurrence of SARS-CoV-2 in Madhya Pradesh). We performed amplicon-based whole-genome sequencing of randomly selected SARS-CoV-2 isolates (n = 38) collected between 2020 and 2022 at state level VRDL, ICMR-NIRTH, Jabalpur, from 11899 RT-qPCR-positive samples. We observed the presence of five lineages, namely B.1, B.1.1, B.1.36.8, B.1.195, and B.6, in 19 genomes from the first wave cases and variants of concern (VOCs) lineages, i.e., B.1.617.2 (Delta) and BA.2.10 (Omicron) in the second wave cases. There was a shift in mutational pattern in the spike protein coding region of SRAS-CoV-2 strains from the second wave in contrast to the first wave. In the first wave of infections, we observed variations in the ORF1Ab region, and with the emergence of Delta lineages, the D614G mutation associated with an increase in infectivity became a prominent change. We have identified five immune escape variants in the S gene, P681R, P681H, L452R, Q57H, and N501Y, in the isolates collected during the second wave. Furthermore, these genomes were compared with 2160 complete genome sequences reported from central India that encompass 109 different SARS-CoV-2 lineages. Among them, VOC lineages Delta (28.93%) and Omicron (56.11%) were circulating predominantly in this region. This study provides useful insights into the genetic diversity of SARS-CoV-2 strains over the initial course of the COVID-19 pandemic in central India.

Innovative upcycling gabions with coal bottom ash for nonpoint source pollution control against climate change

Climate change accelerates extreme temperature fluctuations and rainfall volatility, and shifts in rainfall patterns, rapidly increasing nonpoint source pollution originated from turbid water and soil erosion. The climate changes also pose serious threats to the agricultural environment and food security. This study innovates the conventional control facilities of turbid water and soil erosion in the sloping field, using coal bottom ash as a harmful waste of thermal power generation. Typical gabion and side modified gabion are designed in consideration with geographical characteristics. The adsorption capacity of coal bottom ash for turbidity, suspended solids (SS), total nitrogen (T-N), and total phosphorus (T-P) were increased as the amounts of coal bottom ash increase. At the rate of 20-g coal bottom ash, the turbidity, SS, T-N, and T-P were absorbed by 84.0%, 80.2%, 40.2%, and 53.2%, respectively. The typical gabion (TG) and side modified gabion (SMG) installed in the sloping field also decreased the turbidity, SS, T-N, and T-P by up to 98.1%, 99.4%, 77.6%, and 84.0%, respectively, during the natural rainfall events. The use of coal bottom ash cannot only be an effective upcycling way to control nonpoint source pollution but also be an ecofriendly approach against climate change.

Reassessing water resource challenges in a changing climate in the Kagera transboundary river basin, Tanzania

The dynamic shifts in climatic patterns, particularly alterations in precipitation, have significantly impacted water resource availability and accessibility. These climate-induced changes affect hydrological processes, encompassing runoff, groundwater replenishment, water demand, and biophysical patterns within river basins. This study seeks to unravel the multifaceted implications encountered and challenges in water resource management within the river basin. It employed a survey-based approach for data collection, including Key informant interviews (KI), consultation methods and documentary reviews. The study utilized Statistical Package for the Social Sciences (SPSS) and Microsoft Excel for quantitative analysis and thematic synthesis for qualitative insights, including local community perspectives. The findings reveal substantial fluctuations in precipitation, protracted droughts, severe flooding, and other climatic extremes. The observed annual mean rainfall of 832 mm, with a standard deviation of 248, a standard error of 361, and a skewness of −945, accentuates the pronounced variability in mean precipitation, exhibiting a declining trend indicative of climatic shifts (R2 = 0.1797 and P = 0.002). The challenges are limited access to hydrological and meteorological data, undermining prediction accuracy, infrastructure planning, and response strategies for water resource allocation and management. The absence of unified approaches, influenced by the politics of riparian states, feeble coordination, conflicting sectoral policies, and ambiguous priorities, hinders effective transboundary water resource management. The study addresses these complexities and advocates for institutionalizing robust water management strategies that capitalize on existing resources and foster innovative capacities among critical stakeholders. Central to these efforts is harmonizing and enforcing policies, regulations, and laws governing water use, coupled with a concerted focus on inclusive governance to ensure the sustainability of water resource management. Such effort entails synchronized strategies, programs, plans, and livelihood practices underpinned by active stakeholder involvement in pivotal facets of water resources management.

Geospatial assessment of cropping pattern shifts and their impact on water demand in the Kaleshwaram lift irrigation project command area, Telangana

Geospatial assessment of cropping pattern shifts and their impact on water demand in the Kaleshwaram lift irrigation project command area, Telangana