Monitoring Efforts Research Articles

Assessment of emerging and persistent contaminants in an anthropogenic-impacted watershed: Application using targeted, non-targeted, and in vitro bioassay techniques

Emerging and persistent contaminants (EPC) pose a significant challenge to water quality monitoring efforts. Effect-based monitoring (EBM) techniques provide an efficient and systematic approach in water quality monitoring, but they tend to be resource intensive. In this study, we investigated the EPC distribution for various land uses using target analysis (TA) and non-target screening (NTS) and in vitro bioassays, both individually and integrated, in the upper Ping River Catchment, northern Thailand. Our findings of NTS showed that urban areas were the most contaminated of all land use types, although agriculture sites had high unexpected pollution levels. We evaluated the reliability of NTS data by comparing it to TA and observed varying inconsistencies likely due to matrix interferences and isobaric compound interferences. Integrating NTS with in vitro bioassays for a thorough analysis posed challenges, primary due to a scarcity of concentration data for key compounds, and potentially additive or non-additive effects of mixture samples that could not be accounted for. While EBM approaches place emphasis on toxic sites, this study demonstrated the importance of considering non-bioactive sites that contain toxic compounds with antagonistic effects that may go undetected by traditional monitoring approaches. The present work emphasizes the importance of improving NTS workflows and ensuring high-quality EBM analyses in future water quality monitoring programs.

A baseline monitoring of radiological sediment quality and associated risk assessment in coastal ecosystems of the Republic of Congo.

This study presents the first data on levels of natural radioactive elements in sediments from coastal ecosystems of the Republic of Congo. Sediment samples from five coastal sites were collected and analyzed by high-resolution gamma spectrometry for determination of activities of long-lived gamma-emitting radionuclides (234Th, 238U, 226Ra, 210Pb, 228Th, 228Ra, and 40K). The specific activities were of the same order of magnitude as those measured in sediments of most countries neighboring the Republic of Congo. However, variations in activities were observed from one site to another and also from one sampling point to another within the same site without exceeding the global average reference values. It can be assumed, therefore, that no significant anthropogenic impact is perceptible in the study area. The most commonly used radiological hazard parameters, based mainly on 238U, 232Th, and 40K activities, were assessed and the ERICA tool was applied to quantify the radiation exposure burden to human and biota resulting from radionuclides in sediments. Besides being useful for future monitoring efforts, the data produced in this work could be important for the worldwide database on radioactivity in the oceans and seas (MARIS) since no data are available in the Congolese marine environment.

Stronger together: different community science platforms all contribute to wildlife research

Context Engaging the general public can increase spatio-temporal coverage of wildlife monitoring. Given the potentially substantial costs, we need to evaluate the contribution of known and planned initiatives and confirm whether multiple platforms increase the efficiency of data collection. As observer behaviour affects data quantity and quality, users of specialised and generalist platforms are expected to behave differently, resulting in more connected networks for specialised and higher nestedness for generalist platforms. Specialist observers are expected to contribute a balanced ratio of rare and common species, whereas non-specialist contribution will depend more on species detectability. Aims We aim to evaluate whether the combined contribution of observers from different platforms can improve the quality of occurrence and distribution data of 218 endemic Atlantic Forest bird species in Brazil. We also describe and compare observer-bird species interaction networks to illustrate observer behaviour on different platforms. Methods On the basis of data from five community science platforms in Brazil, namely, eBird, WikiAves, Biofaces, iNaturalist and Táxeus, we compared the spatial distribution of bird observations, the number of observers, the presence of the same observers on various platforms, bird species coverage, and the proportion of duplicate observations within and among platforms. Key results Although species coverage of the joint dataset increased by up to 100%, spatial completeness among the five platforms was low. The network of individual platforms had low values of clustering, and the network of the joint dataset had low connectance and high nestedness. Conclusions Each platform had a somewhat unique contribution. Pooling these datasets and integrating them with standardised data can inform our knowledge on bird distributions and trends in this fragile biome. Nevertheless, we encourage observers to provide precise coordinates, dates and other data (and platforms to accommodate such data) and recommend submitting data from all platforms into the Global Biodiversity Information Facility to support wildlife research and conservation. Implications If new platforms engage more and different people, new initiatives can cover poorly represented areas and successfully expand monitoring effort for Atlantic Forest endemic bird species.

Public health use and lessons learned from a statewide SARS-CoV-2 wastewater monitoring program (MiNET)

The global SARS-CoV-2 monitoring effort has been extensive, resulting in many states and countries establishing wastewater-based epidemiology programs to address the spread of the virus during the pandemic. Challenges for programs include concurrently optimizing methods, training new laboratories, and implementing successful surveillance programs that can rapidly translate results for public health, and policy making. Surveillance in Michigan early in the pandemic in 2020 highlights the importance of quality-controlled data and explores correlations with wastewater and clinical case data aggregated at the state level. The lessons learned and potential measures to improve public utilization of results are discussed.The Michigan Network for Environmental Health and Technology (MiNET) established a network of laboratories that partnered with local health departments, universities, wastewater treatment plants (WWTPs) and other stakeholders to monitor SARS-CoV-2 in wastewater at 214 sites in Michigan. MiNET consisted of nineteen laboratories, twenty-nine local health departments, 6 Native American tribes, and 60 WWTPs monitoring sites representing 45 % of Michigan's population from April 6 and December 29, 2020. Three result datasets were created based on quality control criteria. Wastewater results that met all quality assurance criteria (Dataset Mp) produced strongest correlations with reported clinical cases at 16 days lag (rho = 0.866, p < 0.05).The project demonstrated the ability to successfully track SARS-CoV-2 on a large, state-wide scale, particularly data that met the outlined quality criteria and provided an early warning of increasing COVID-19 cases. MiNET is currently poised to leverage its competency to complement public health surveillance networks through environmental monitoring for new and emerging pathogens of concern and provides a valuable resource to state and federal agencies to support future responses.

Western spotted skunk spatial ecology in the temperate rainforests of the Pacific Northwest

AbstractA major threat to small mammalian carnivore populations is human‐induced land use change, but conservation and management are inhibited by limited knowledge about their ecology and natural history. To fill a key knowledge gap of the western spotted skunk (Spilogale gracilis), we investigated their spatial ecology at the landscape and home range scale in the temperate rainforests of the Oregon Cascades during 2017–2019. For the landscape scale analysis, we used detections of western spotted skunks at 112 baited camera traps and fitted a dynamic occupancy model to investigate spatial distribution and drivers of inter‐seasonal and inter‐annual changes in occupancy. Concurrently, we radio‐collared 25 spotted skunks (9 female, 16 male) and collected 1583 relocations. Using continuous‐time movement models, we estimated large home range sizes for both male and female spotted skunks, relative to their body mass, and highly overlapping home ranges that indicated a lack of territoriality. Using these home ranges, we fitted a resource selection function using environmental covariates that we assigned to various hypotheses such as resources, predator avoidance, thermal tolerance, and disturbance. Overall, western spotted skunks were widely distributed across our study area (seasonal occupancy up to 63.7 ± 5.3%) and highly detectable (weekly detection probability = 41.2%). At both spatial scales, spotted skunks selected wetter areas and local valleys, which we attributed to areas with more food resources. At the home range scale, spotted skunks selected locations with lower predation risk and areas surrounded by more previously logged forests. In this montane environment, inter‐seasonal contractions in the spatial distributions of spotted skunks were strongly driven by their response to cold temperature and accumulated snow. This was especially evident when seasonal occupancy declined significantly following a severe heavy snow event in February 2019. Given that there is little information available on the natural history of the western spotted skunk, these results provide essential information about their ecology to focus future monitoring efforts and may help identify potential threats (e.g., forest management, severe snow events, or wildfires) to this species.

When enough is enough: Optimising monitoring effort for large-scale wolf population size estimation in the Italian Alps.

The ongoing expansion of wolf (Canis lupus) populations in Europe has led to a growing demand for up-to-date abundance estimates. Non-invasive genetic sampling (NGS) is now widely used to monitor wolves, as it allows individual identification and abundance estimation without physically capturing individuals. However, NGS is resource-intensive, partly due to the elusive behaviour and wide distribution of wolves, as well as the cost of DNA analyses. Optimisation of sampling strategies is therefore a requirement for the long-term sustainability of wolf monitoring programs. Using data from the 2020-2021 Italian Alpine wolf monitoring, we investigate how (i) reducing the number of samples genotyped, (ii) reducing the number of transects, and (iii) reducing the number of repetitions of each search transect impacted spatial capture-recapture population size estimates. Our study revealed that a 25% reduction in the number of transects or, alternatively, a 50% reduction in the maximum number of repetitions yielded abundance estimates comparable to those obtained using the entire dataset. These modifications would result in a 2046 km reduction in total transect length and 19,628 km reduction in total distance searched. Further reducing the number of transects resulted in up to 15% lower and up to 17% less precise abundance estimates. Reducing only the number of genotyped samples led to higher (5%) and less precise (20%) abundance estimates. Randomly subsampling genotyped samples reduced the number of detections per individual, whereas subsampling search transects resulted in a less pronounced decrease in both the total number of detections and individuals detected. Our work shows how it is possible to optimise wolf monitoring by reducing search effort while maintaining the quality of abundance estimates, by adopting a modelling framework that uses a first survey dataset. We further provide general guidelines on how to optimise sampling effort when using spatial capture-recapture in large-scale monitoring programmes.

Legionnaires’ Disease Surveillance and Public Health Policies in Italy: A Mathematical Model for Assessing Prevention Strategies

Legionella is the pathogen that causes Legionnaires’ disease, an increasingly prevalent and sometimes fatal disease worldwide. In 2021, 97% of cases in Europe were caused by Legionella pneumophila. We present a mathematical model that can be used by public health officials to assess the effectiveness and efficiency of different Legionella monitoring and control strategies to inform government requirements to prevent community-acquired Legionnaires’ disease in non-hospital buildings. This simulation model was built using comprehensive data from multiple scientific and field-based sources. It is a tool for estimating the relative economic and human costs of monitoring and control efforts targeting either L. pneumophila or Legionella species and was designed to analyze the potential application of each approach to specific building classes across Italy. The model results consistently showed that targeting L. pneumophila is not only sufficient but preferable in optimizing total cost (direct and economic) for similar human health benefits, even when stress-tested with extreme inputs. This cost–benefit analytical tool allows the user to run different real-life scenarios with a broad range of epidemiological and prevalence assumptions across different geographies in Italy. With appropriate modifications, this tool can be localized and applied to other countries, states, or provinces.

Improving pollen-bearing honey bee detection from videos captured at hive entrance by combining deep learning and handling imbalance techniques

The number of pollen-bearing honey bees serves as a vital indicator for assessing colony balance and health. Despite its significance, prevailing detection techniques still rely heavily on manual observation and annotation, leading to time-consuming processes that cannot sustain long-term, continuous monitoring efforts. To facilitate automatic beehive monitoring, this study introduces an efficient method for pollen-bearing bee detection. Initially, we furnish a comprehensive dataset, dubbed VnPollenBee, meticulously annotated for pollen-bearing honey bee detection and classification. The dataset comprises 60,826 annotated boxes that delineate both pollen-bearing and non-pollen-bearing bees in 2051 images captured at the entrances of beehives under various environmental conditions. To the best of our knowledge, this represents the first dedicated dataset for pollen-bearing bee detection. The VnPollenBee dataset is publicly accessible to the research community at https://comvis-hust.github.io/datasets/pollenbee.html. Subsequently, we propose the incorporation of diverse techniques into two baseline models, namely YOLOv5 and Faster RCNN, to effectively address the imbalance that arises during the detection of pollen-bearing bees due to their number being typically much lower than the total number of bees present at hive entrances. The experimental results demonstrate that our proposed method outperforms the baseline models on the VnPollenBee dataset, yielding Precision, Recall, and F1 score of 99%, 93%, and 95%, respectively. Specifically, the improvements obtained are 3% and 2% in Recall and F1 score when using YOLOv5, and 3%, 2%, and 2% in Precision, Recall, and F1 score when using Faster RCNN. These findings confirm the potential of our approach to facilitate bee foraging behavior analysis and automated bee monitoring.

Pemetaan Indeks Kerawanan Pemilu 2024 Perspektif Siyasah Dusturiyah

Introduction: This research is motivated by the general election vulnerability that will occur in Bandung Regency in 2024. The Bandung Regency Election Vulnerability Index has reached 91.5 percent. The IKP measures include monitoring campaign violations, voting rights, income, money politics, ASN neutrality, hoax news.Purposes of the Research: The aim of this research is to analyze the vulnerabilities that occurred during the general election in Bandung Regency, highlighting the importance of comprehensive prevention and supervision efforts. With this mapping, stakeholders can focus more on monitoring, intervention and prevention efforts. The election vulnerability index also functions as a measuring tool to evaluate the effectiveness of the policies and strategies implemented in order to create clean, honest and fair elections.Methods of the Research: The research method used is qualitative with a descriptive type based on the focus of the study used, namely empirical research.Results of the Research: The results of the research show that there are potential vulnerabilities that occur in Bandung Regency. Bawaslu's function in preventing election violations includes identification and mapping of violations, coordination, monitoring and evaluation of election implementation. Bawaslu also coordinates with related government agencies and increases public participation in election supervision.

A novel technique for estimating age and demography of long-lived seabirds (genus Pterodroma) using an epigenetic clock for Gould's petrel (Pterodroma leucoptera).

Understanding the demography of wildlife populations is a key component for ecological research, and where necessary, supporting the conservation and management of long-lived animals. However, many animals lack phenological changes with which to determine individual age; therefore, gathering this fundamental information presents difficulties. More so for species that are rare, highly mobile, migratory and those that reside in inaccessible habitats. Until recently, the primary method to measure demography is through labour intensive mark-recapture approaches, necessitating decades of effort for long-lived species. Gadfly petrels (genus: Pterodroma) are one such taxa that are overrepresented with threatened and declining species, and for which numerous aspects of their ecology present challenges for research, monitoring and recovery efforts. To overcome some of these challenges, we developed the first DNA methylation (DNAm) demography technique to estimate the age of petrels, using the epigenetic clock of Gould's petrels (Pterodroma leucoptera). We collected reference blood samples from known-aged Gould's petrels at a long-term monitored population on Cabbage Tree Island, Australia. Epigenetic ages were successfully estimated for 121 individuals ranging in age from zero (fledgling) to 30 years of age, showing a mean error of 2.24 ± 0.17 years between the estimated and real age across the population. This is the first development of an epigenetic clock using multiplex PCR sequencing in a bird. This method enables demography to be measured with relative accuracy in a single sampling trip. This technique can provide information for emerging demographic risks that can mask declines in long-lived seabird populations and be applied to other Pterodroma populations.

Evaluating the portable X-ray fluorescence reliability for metal(loid)s detection and soil contamination status.

Marginalized communities experience barriers that can prevent soil monitoring efforts and knowledge transfer. To address this challenge, this study compared two analytical methods: portable X-ray fluorescence spectroscopy (pXRF, less time, cost) and inductively coupled plasma mass spectrometry (ICP-MS, "gold standard"). Surface soil samples were collected from residential sites in Arizona, USA (N = 124) and public areas in Troy, New York, USA (N = 33). Soil preparation differed between groups to account for community practice. Statistical calculations were conducted, paired t test, Bland-Altman plot, and a two-way ANOVA indicated no significant difference for As, Ba, Ca, Cu, Mn, Pb, and Zn concentrations except for Ba in the t test. Iron, Ni, Cr, and K were statistically different for Arizona soils and V, Ni, Fe, and Al concentrations were statistically different for New York soils. Zinc was the only element with high R2 and low p value. Pollution load index (PLI), enrichment factors (EF), and geo-accumulation index (Igeo) were calculated for both methods using U.S. Geological Survey data. The PLI were > 1, indicating soil pollution in the two states. Between pXRF and ICP-MS, the Igeo and EF in Arizona had similar degree of contamination for most elements except Zn in garden and Pb in yard, respectively. For New York, the Igeo of As, Cu, and Zn differed by only one classification index between the two methods. The pXRF was reliable in determining As, Ba, Ca, Cu, Mn, Pb, and Zn in impacted communities. Therefore, the pXRF can be a cost-effective alternative to using ICP-MS techniques to screen soil samples for several environmentally relevant contaminants to protect environmental public health.

Ecosystem risk-based prioritization of micropollutants in wastewater treatment plant effluents across China

Identifying priority pollutants in wastewater treatment plant (WWTP) effluents is crucial for optimizing monitoring efforts, improving regulations, and developing targeted mitigation strategies. Despite the presence of numerous trace organic pollutants in WWTP effluents, a comprehensive prioritization scheme is lacking, hindering effective control. This study screened 216 micropollutants, including pharmaceuticals, pesticides, and industrial chemicals, which had been detected in effluents from 46 WWTPs across China. A multi-criteria prioritization method was developed, considering exposure potential based on median concentrations and detection frequencies, as well as hazard potential determined by persistence, bioaccumulation, in vitro toxicity, and in vivo toxicity. Pollutants with low exposure or hazard potential were filtered out, and a priority index was calculated to rank the remaining 59 substances. The top 15 priority pollutants included regulated persistent organic pollutants like perfluorooctanoic acid and their alternatives such as perfluorobutane sulfonate, pesticide transformation products, and emerging contaminants such as bisphenol A, which are not currently regulated in WWTP effluents. This study provides a systematic approach to identify priority pollutants and generates a guiding framework for monitoring, regulation, and control of both well-recognized and overlooked contaminants in WWTP effluents.

Anticipating the winds of change: A baseline assessment of Northeastern US continental shelf surficial substrates

AbstractThe introduction of thousands of wind turbines along the North American Atlantic continental shelf over the next decade will constitute the largest regional change in marine substrates since the retreat of the Laurentide Ice Sheet over 14,000 years ago. Here, two large data sets, SMAST drop camera survey (242,949 samples, 2003 to 2019) and the US Geological Survey databases (27,784 samples, 1966 to 2011), are combined to derive sea floor surficial substrate probability maps for the Northeastern US continental shelf from Virginia Beach to the Gulf of Maine to 300 m depth (218,571 km2). Geostatistical models were used to estimate the probability of five geologic and one biogenic substrate types being present at a 250 m resolution, and the proportional contribution of each substrate type to the seabed composition at a 500 m resolution. By providing the first synoptic maps depicting the probability of a particular substrate or combination of substrates occurring at any location on the Northeastern US continental shelf, including planned wind energy sites, we aim to (1) provide insights regarding how substrates in the areas selected for wind energy development compare with other locations, (2) motivate the development of a priori expectations for ecosystem changes to inform monitoring and research efforts going forward, and (3) to provide a baseline characterization of the Northeastern US continental shelf surficial substrates to support robust examination of the future changes observed in areas impacted by wind energy installations.

Impact of Environmental Conditions on Soil Geochemistry in Southern Kazakhstan

This study investigated the elemental composition of soils in Kyzylorda and Turkestan (southern Kazakhstan), an area rich in natural resources but facing potential environmental threats from industry and agriculture. The goal was to establish baseline geochemical values and assess soil contamination risks. Soil samples were collected from across the region and analyzed using ICP-MS and INAA techniques, providing a comprehensive profile of 72 elements. Statistical analysis revealed significant variations in elemental concentrations, with enrichments observed for specific elements when compared with reference values. Notably, both regions shared a core set of elements including rare earth elements (yttrium series: holmium, erbium, thulium), noble metals (gold, platinum, ruthenium, palladium), and tungsten. Enrichment patterns, however, provided distinct insights. Rare earth element enrichments likely reflect the region’s geology, while elevated radioactive elements necessitate further investigation to understand potential environmental and health risks. Enrichment of iron group elements might be linked to a combination of geological factors and anthropogenic activities like mining or industrial processes. A significantly higher number of elements exceeded background levels in Kyzylorda compared with Turkestan, suggesting greater element accumulation in Kyzylorda’s soil. This difference could be attributed to variations in regional geology or historical anthropogenic activities. The established geochemical baseline for 72 elements and the identified areas of potential contamination will inform land management practices, guide future environmental monitoring efforts, and ultimately contribute to the safeguarding of public health in southern Kazakhstan.

Assessing groundwater fluoride contamination scenario in West Bengal, India: A combined approach using meta-analysis, current research, and health risk evaluation

The present study was initiated by the findings of a comprehensive systematic review and meta-analysis, which synthesized all available literature on the patterns and trends of groundwater fluoride (F−) contamination in West Bengal, India. This investigation aimed to provide detailed information on F− contamination at the block level within the state, which is essential for effective monitoring and alleviation efforts addressing the acute and evolving human health concerns in affected areas. This study focuses on the six districts (South 24 Parganas, West Medinipur, Jhargram, East Bardhaman, West Bardhaman and Murshidabad) of West Bengal. Findings from more than 3000 datasets revealed that approximately 10%, 11%, 4%, and 14% of groundwater samples exceeded the safe limit of F− (1.5 mgL−1) from South 24 Parganas, Jhargram, West Bardhaman, and Murshidabad district, respectively. Notably 3% of samples from West Bardhaman displayed class V toxicity where F− concentrations exceeding >10 mgL−1. This research introduces an initial assessment of F− concentrations in groundwater from nine newly identified F− contaminated blocks (Baruipur, Sonarpur, Binpur II, Salanpur, Baraboni, Jamuriya, Pandabeswar, Kandi and Khargram) within the region. Overall, 65 blocks from ten districts have been recognized as F− contaminated zones in West Bengal till 2023. The non-cancerous health risk was found to be disproportionately higher in the western districts (Jhargram, West Bardhaman, and western part of Murshidabad) compared to their southeastern counterparts (East Bardhaman, Paschim Medinipur, and South 24 Parganas). A demographic analysis of health risk indicated infants as the most susceptible group to F− toxicity. The probabilistic health risk at P95 dose for eight blocks further corroborated the heightened vulnerability of infants. These insights offer critical implications for the policy-makers, suggesting an urgent need for tailored health policies to mitigate the risk associated with F− contamination in West Bengal.

Assessing Ecosystem Health: A Comparative Study Using Water Quality Index Analysis across Ten Lotic System in the Cross River System

This review synthesizes findings from 10 scientific publications utilizing the weighted arithmetic Water Quality Index (WQI) to assess the status of diverse water bodies (Ikpa River, Lower Enyong Creek, Nwaniba River, Imo River, Etim Ekpo River, Lower Qua Iboe River, Ibeno Estuary, Cross River, Ikot Ebak River and Oboroenyin River) all within the Cross River System. The Analysis reveals that 6 out of 10 sampled water bodies are moderately polluted, while the remaining 4 exhibit slight pollution levels. These findings underscore significant concerns regarding water quality degradation, predominantly attributed to industrial effluents, agricultural runoff and urban contaminants. The WQI proves effective in consolidating multiple water quality parameters into a comprehensive index, facilitating a holistic assessment of pollution levels and guiding management strategies. Moving forward, concerted efforts are imperative to enhance monitoring efforts, implement stringent regulatory measures, and adopt sustainable practices to safeguard freshwater resources globally. This review underscores the urgency of integrated approaches to mitigate pollution and ensure resilience of aquatic ecosystems and public health.

Evaluating the spatiotemporal dynamics of driving factors for multiple drought types in different climate regions of China

Extreme weather events and natural hazards are increasingly prevalent with global warming, making it imperative to focus on the driving factors and dynamic changes associated with drought—a disaster with widespread impacts and significant losses. This study used a longtime-series of ERA5 reanalysis data to elucidate the dynamic change characteristics of direct and indirect driving factors across China. Ground observation data spanning an extended period were used to estimate the performance of the reanalysis data. The selected driving factors for drought included precipitation (PRE), potential evapotranspiration, soil moisture (SM), bare soil evapotranspiration (BSET), vegetation canopy evapotranspiration (VCET), subsurface runoff (SUBRO), surface runoff (SURRO), temperature (TEM), specific humidity, and near-surface wind speed (WS). Meteorological drought, hydrological drought, and agricultural drought were delineated using the Standardized Precipitation Evapotranspiration Index, Standardized Runoff Index, and Standardized Soil Moisture Index. The Random Forest method was used to ascertain the relative importance of driving factors and their main contributions to different types of droughts. The findings revealed that ERA5 exhibited great simulation performance compared to observational data. However, the correlation coefficient of SM might be relatively lower than that of other driving factors across China. Notably, BSET and PRE exhibited higher relative importance degrees (RID) for meteorological drought in subregions 1, 2, and 3. At the same time, SUBRO demonstrated a more statistically significant influence in subregions 3, 4, and 5. SURRO played a statistically significant role in subregion 1. Moreover, BSET and PRE were pivotal for meteorological drought in northern China, whereas VCET assumes importance for hydrological drought in southern China and the North China Plain. Across different types of droughts, PRE, SM, and TEM generally exhibited relatively large RID values in China. The dynamic changes in RID for both direct and indirect driving factors varied for different drought types across different subregions of China. Notably, the RID displayed contrasting dynamic changes between PRE and BSET for meteorological drought in most subregions. Additionally, the degree of relative importance of near-surface WS tended to be lower for hydrological drought across various subregions. This study contributed to a deeper understanding of drought evolution and enhanced monitoring efforts.

Food safety and surveillance studies on the quality of traditional cold-pressed edible vegetable oils

This study has been conducted to investigate quality and safety of cold-pressed vegetable oils processed at cottage level industries. A total number of 75 samples of coconut, groundnut, and sesame oils collected from different districts of Tamil Nadu, analyzed to ascertain its quality and safety in compliance with the Food Safety Standard Regulations (FSSR) of FSSAI, 2011. Physico – chemical, fatty acid profile, vitamin and trace elemental analysis were carried out. Results revealed that though some of the oils samples are complied with the specification as per the standard, but on the other side 80% of the collected samples were found to fail in meeting at least for one parameter as per the requirements. Results are in deviations for the parameters such as refractive index, specific gravity, iodine value, and saponification value are also noticed and few samples are reported positive results for the presence of mineral oil and argemone oil and possibilities for adulteration. Notably, 15 samples were found to comply with the requirements for physiochemical parameters, fatty acid profiles and trace element levels which are found below permissible limits (≤0.05 mg/kg). Vitamin E was detected only in coconut oil (0.1059 to 0.1622 mg/100g). Whereas, antioxidant assay and color, remained satisfactory. Overall, the study underscores the importance of consumer awareness and adherence to established standards to ensure the integrity and safety of edible oils, highlighting the need for continued monitoring and enforcement efforts to address identified shortcomings and uphold market integrity.

First Report for Painted Globular Frog Uperodon taprobanicus in North Bastar Kanker District of Chhattisgarh, (India)

The North Bastar Kanker is full of natural wealth where different types of species are found every year, out of which new species are found the Painted Globular Frog (Uperodon taprobanicus) has been seen for the first time, according to the current study. One year of observation throughout the village badgaon near Khandi Rivershowed this species to be present in this microhabitat. The species' taxonomic validity in the area was aided by morphological and photographsanalysis that validated its identification. The known distribution range of U. taprobanicus, which was previously primarily reported in South India and Sri Lanka, is expanded by this finding. In order to shed light on the state of the species' conservation in this area, ecological characteristics like habitat choice, microhabitat usage and potential threats were also evaluated. The exploration underscores the importance of continued monitoring and conservation efforts to safeguard the diversity of amphibians in Chhattisgarh and highlights the need for further research to elucidate the ecological requirements and population dynamics of U. taprobanicus in its newly identified habitat. This species has been marked in the IUCN data and its conservation is very important in time. If we cannot conserve it, then we will eliminate this species from our ecosystem and we may see natural calamity and loss in the near future.

Review on IoT-Driven Infusion Monitoring &amp; Management System

Effective intravenous (IV) infusion management and monitoring are essential in today's healthcare environment to guarantee patient safety and improve the standard of care. In order to overcome the drawbacks of conventional IV drip monitoring techniques, this study describes the creation of a contactless, Internet of Things-driven infusion monitoring and management system. With the use of cutting-edge sensor technology and Internet of Things connection, the suggested system combines real-time IV drip liquid level monitoring and control, delivering precise and ongoing updates. Healthcare practitioners may now monitor and analyse patient data remotely thanks to the gathered data's constant updating and transmission to the Think Speak cloud platform. With its combination of real- time data collecting, cloud-based analytics, and emergency alert features, the proposed contactless IoT-driven infusion monitoring and management system represents a substantial improvement in healthcare technology. Using the power of IoT and cloud computing, this invention seeks to enhance overall patient outcomes, optimize IV treatment administration, and decrease human monitoring efforts. To increase patient safety, the system has an emergency alarm mechanism based on GSM modules. This feature ensures that caregivers are notified promptly of any irregularities or critical IV drip levels, allowing for prompt treatment. By providing real-time signals, the device lessens the risks related to delayed reactions to IV fluid failure or depletion. Formulating a real-time model for IV drip liquid level monitoring is the main goal of the system. By employing non-invasive sensors to identify and record the drip rate and fluid levels, this gadget assures precise tracking without having physical contact with the IV apparatus. Keywords: Internet of Things, ESP32 microcontroller, Biomedical, GSM, Relay, LCD Display.