Standardized Index Research Articles

Readiness for behaviour change after gestational diabetes mellitus: A prospective cohort study.

Women with gestational diabetes mellitus (GDM) have a high risk of developing type 2 diabetes (T2D). Readiness for behaviour change to mitigate this risk may be low after pregnancy and may further decrease over time without appropriate interventions. This study aimed to evaluate readiness for behaviour change in the first and second postpartum years in women with recent GDM to determine the best timing for lifestyle interventions to prevent T2D. This study included a subset of women with GDM between 2009 and 2013 in Ontario, Canada from a larger prospective cohort study who completed a survey in the first and second postpartum years (N = 329). The primary outcome was stage of readiness for behaviour change for diet and physical activity, compared between the first and second postpartum years. The mean age was 34.3 ± 4.4 standard deviation (SD) years and mean pre-pregnancy body-mass index (BMI) was 26.7 ± 6.9 kg/m2. In the first postpartum year, 86% of women reported a pre-action stage of change, which was 87% by the second postpartum year (p = 0.646). Non-Caucasian ethnicity was associated with lower odds of being in the action stage of readiness for behaviour change overall and for physical activity in both time periods. Most postpartum women with recent GDM are in a pre-action stage of change after delivery, which does not increase by the second postpartum year. Behavioural interventions should continue to be prioritized in postpartum women with GDM to optimize this slim window of opportunity for T2D prevention.

Integrating standardized indices and performance indicators for better drought assessment in semi-arid coastal aquifers

Aquifers in arid and semi-arid coastal regions, such as along the Mediterranean rim, are severely affected by droughts. The natural decrease in water levels is often exacerbated by excessive abstraction, resulting in both degradation of water quality and the risk of seawater intrusion. In these regions it is crucial to conduct thorough monitoring of wells, employing a wide range of indicators to forecast and mitigate the consequences of decreased precipitation and intensified pumping. This study proposes an analysis and monitoring methodology involving the calculation of performance indicators based on the Standardized Groundwater level Index (SGI), supplemented with information on the optimal accumulation time of the Standardized Precipitation Evapotranspiration Index (SPEI). Atmospheric reanalysis datasets and in-situ groundwater level observations are used together to derive the groundwater system memory and find consistent optimal SPEI accumulation times at each individual location. The inverse of memory derived from the autocorrelation of the SGI is used to estimate each well's ability to recover from drought conditions. This value provides the most reliable indication of resilience and sustainability. In the Algarve, the average regional variability of groundwater level is well captured by the SPEI-12 index. However, groundwater memories and optimal SPEI accumulation times are spatially very heterogeneous varying between SPEI-5 and SPEI-48. Wells with shorter memories (<6 months) demonstrate greater sustainability, whereas those with longer memories (>16 months), whether situated inland or along the coast, exhibit lower resilience and lower sustainability. Coastal wells with groundwater levels close to sea level, exhibiting minimal resilience, are of particular concern and require intensified monitoring efforts to adapt management strategies.

Landscape Fire Air Pollution as a Mediator in Drought and Childhood Stunting Pathway in Low- and Middle-Income Countries.

Drought induces dry hazards, including wildfire, and increased air pollution from wildfire may be a mechanism by which drought increases health risks. We examined whether the drought-wildfire pathway increases the risk of childhood stunting. We analyzed all geocoded children under five across 44 low- and middle-income countries (LMICs). We first conducted mixed-effect regressions to examine the three pairwise associations between standardized precipitation evapotranspiration index (SPEI), fire-sourced PM2.5, and childhood stunting. We then employed a causal mediation analysis to determine whether compounding drought-wildfire (cascading or co-occurring) events significantly impact the drought-stunting pathway. We found that each 1-unit decrease in SPEI exposure was associated with a 2.16% [95% confidence interval (CI): 0.79, 3.49%] increase in stunting risk and 0.57 (95% CI 0.55, 0.59%) μg/m3 increase in fire-sourced PM2.5. Additionally, each 1 μg/m3 increase in 24 month average fire-sourced PM2.5 was associated with an increased risk of 2.46% (95% CI: 2.16, 2.76%) in stunting. Drought-mediated fires accounted for 26.7% (95% CI: 14.5, 36.6%) of the linkage between SPEI and stunting. Our study revealed fire-sourced PM2.5 is a mediator in the drought-stunting pathway in LMICs. To protect child health under increasing drought conditions, personal interventions against wildfire should be considered to enhance climate resilience.

Investigating tooth morbidity risks, prevalence, and interventions in tribal setting: a study protocol focused on the Irula community in Tamil Nadu

AimDentistry is uniquely positioned as a healthcare profession, distinguished from allied health or paramedical fields. It operates within a university-based structure, maintaining primary care responsibilities. Oral diseases impose a substantial worldwide health and economic burden, profoundly affecting the well-being of those affected. This cross-sectional study is centered on the Irula tribes in Tamil Nadu, India. Investigating the extent of tooth morbidity and loss, identifying possible risk factors, looking at oral hygiene habits, and evaluating the oral health-associated quality of life (OHRQoL) in this population are the main goals. As this population is at high risk for dental issues, promoting good oral hygiene becomes crucial. Indigenous populations, including the Irula tribes, have been underrepresented in research studies. The vulnerability of the Irula tribes is exacerbated by their remote locations, resulting in limited access to fundamental healthcare facilities.Materials and methodsThis study employs a cluster sampling approach, aiming to include 880 individuals aged 60 and above from Kancheepuram and Chengalpattu districts. The methodology encompasses a community-based questionnaire, clinical assessments utilizing standardized indices, and the assessment of the Oral Health-Related Quality of Life (OHRQoL). The Statistical Package for Social Services, version 20, will be used to analyze all of the data that has been gathered (SPSS).Categorical variables will undergo analysis, with descriptive statistics and frequency percentages computed.ConclusionThis study evaluates tooth morbidity and dentistry's role in screening chronic diseases like diabetes among the Irula tribes. It explores risk factors, oral hygiene practices, treatment seeking behavior, and oral health-related quality of life to gain a comprehensive understanding.

Cross-gradient joint inversion and clustering of ERT and SRT data on structured meshes incorporating topography

Summary The combination of electrical resistivity and seismic refraction tomography is a common practice for the characterization of subsurface features. Presently, the cross-gradient inversion scheme stands out as one of the most robust joint approaches, and some authors modified it to manage complex topographies on unstructured meshes even if at the expense of introducing additional parameters in the inversion process. We propose in this work a cross-gradient algorithm for jointly inverting electrical and seismic tomographic data on structured meshes in cases with non-flat topography. The proposed approach preserves the benefit of the classical cross-gradient approach without the need to impose physical length scales, as for irregular meshes. The quality of the results is evaluated in comparison with independent inversion through a new standardized cross-gradient index and a fuzzy c-means analysis that provides an assessment of the reconstruction accuracy through the membership function. The proposed method was applied to both synthetic models and field-scale examples located in Central Italy, where an accurate geophysical reconstruction is needed for the rehabilitation of existing dams. For all cases, joint inversion yielded superior results compared to independent inversion, demonstrating better agreement with available borehole data. The effectiveness of the joint approach was also demonstrated by the post-inversion tools, where the new cross-gradient index highlighted changes in structural similarity whilst fuzzy c-means clustering allowed for a quantitative reconstruction (position and shape) of the main units at the sites, facilitating the detection of site layering modifications.

Maximum mouth opening in patients with cleft lip and palate or craniofacial anomalies compared with non-affected controls: A cross-sectional study.

There are limited published data on maximum mouth opening (MMO) for children with cleft lip or palate (CLP) or craniofacial anomalies (CFA). To report MMO of patients with CLP or CFA compared with non-affected controls. Retrospective cross-sectional review of electronic medical and dental records. Patients with CLP or CFA with recorded MMO, height, and weight were included and compared with a non-affected control individuals seen during orthodontic screening. Outcome measures included MMO, recorded in millimeters of inter-incisal distance, age, height, weight, and sex. Patients with CLP or CFA (n = 376) were matched by age and body mass standardized index (BMIz) to the non-affected pool (n = 376). The affected group had a MMO of 43.14 mm (±7.1 mm) compared with the control group MMO of 48.01 mm (±7.6 mm) with a statistically significant difference of -4.86 mm (p < .0001). Specifically, MMO of the unilateral cleft group is 4.26 mm smaller than that of non-affected controls (p < .0001). MMO of the bilateral cleft group is 3.65 mm smaller than that of non-affected controls (p = 0.0063). MMO for patients with CLP was significantly smaller as compared to non-affected controls. This study helps establish MMO values for children with CLP and CFA.

Effect of Body Weight on Glycaemic Indices in People with Type 1 Diabetes Using Continuous Glucose Monitoring.

Background/Objectives: Obesity and overweight have become increasingly prevalent in different populations of people with type 1 diabetes (PwT1D). This study aimed to assess the effect of body weight on glycaemic indices in PwT1D. Methods: Adult PwT1D using continuous glucose monitoring (CGM) and followed up at a regional academic diabetes centre were included. Body weight, body mass index (BMI), waist circumference, glycated haemoglobin (HbA1c), and standard CGM glycaemic indices were recorded. Glycaemic indices were compared according to BMI, and correlation and linear regression analysis were performed to estimate the association between measures of adiposity and glycaemic indices. Results: A total of 73 PwT1D were included (48% normal weight, 33% overweight, and 19% obese). HbA1c was 7.2% (5.6-10), glucose management indicator (GMI) 6.9% (5.7-8.9), coefficient of variation (CV) for glucose 39.5% ± 6.4, mean glucose 148 (101-235) mg/dL, TIR (time in range, glucose 70-180 mg/dL) 66% (25-94), TBR70 (time below range, 54-69 mg/dL) 4% (0-16), TBR54 (<54 mg/dL) 1% (0-11), TAR180 (time above range, 181-250 mg/dL) 20% ± 7, and TAR250 (>250 mg/dL) 6% (0-40). Glycaemic indices and achievement (%) of optimal glycaemic targets were similar between normal weight, overweight, and obese patients. BMI was associated negatively with GMI, mean glucose, TAR180, and TAR250 and positively with TIR; waist circumference was negatively associated with TAR250. Conclusions: CGM-derived glycaemic indices were similar in overweight/obese and normal weight PwT1D. Body weight and BMI were positively associated with better glycaemic control. PwT1D should receive appropriate ongoing support to achieve optimal glycaemic targets whilst maintaining a healthy body weight.

A framework for drought monitoring and assessment from a drought propagation perspective under non-stationary environments

According to the coupled influence of climate variation and anthropogenic activities, hydro-meteorological variables are hard to keep stationary in a changing environment. Consequently, the efficacy of traditional standardized drought indices, predicated upon the assumption of stationarity, has been called into question. In China, the challenge of drought monitoring and declaration is exacerbated by the need for multiple drought indices covering meteorological, agricultural, hydrological, and groundwater aspects, often lacking real-time availability. To address these challenges, we developed a framework for drought monitoring and assessment from a drought propagation perspective. Central to this is the Nonstationary Integrated Drought Index (NIDI), which integrates responses from meteorological, agricultural, hydrological, and groundwater droughts, accounting for climate change and anthropogenic influences. First, we analyse the process of drought propagation to select the suitable time scale standardized drought index. Subsequently, significant large-scale climatic indices are selected through linear and nonlinear correlation analyses to identify climate anomalies. Anthropogenic influences are assessed using indicators such as the Normalized Difference Vegetation Index (NDVI), Impervious Surface Ratio (ISR), and population density (POP). Nonstationary probability models are then developed for precipitation, soil moisture, runoff, and groundwater series, incorporating climatic and human-induced factors. Finally, the NIDI is calculated using a D-vine copula model, with parameter estimation and updating facilitated by a genetic algorithm, representing the temporal dependence structure among the variables. A case study in the Hulu River Basin of western China validated the NIDI. Results showed that the NIDI effectively accounts for nonstationary hydro-meteorological variables due to climate change and human activities, accurately reproducing their time-dependent structure. Compared to conventional indices like SPI, SSI, SRI, and SGI, the NIDI identifies more extreme drought events. In conclusion, the presented NIDI offers a more comprehensive approach to drought identification, providing valuable insights for accurate drought detection and effective drought-related policy-making.

Modeling and Application of Drought Monitoring with Adaptive Spatial Heterogeneity Using Eco–Geographic Zoning: A Case Study of Drought Monitoring in Yunnan Province, China

Drought, characterized by frequent occurrences, an extended duration, and a wide range of destruction, has become one of the natural disasters posing a significant threat to both socioeconomic progress and agricultural livelihoods. Large-scale geographical environments often exhibit obvious spatial heterogeneity, leading to significant spatial differences in drought’s development and outcomes. However, traditional drought monitoring models have not taken into account the impact of regional spatial heterogeneity on drought, resulting in evaluation results that do not match the actual situation. In response to the above-mentioned issues, this study proposes the establishment of ecological–geographic zoning to adapt to the spatially stratified heterogeneous characteristics of large-scale drought monitoring. First, based on the principles of ecological and geographical zoning, an appropriate index system was selected to carry out ecological and geographical zoning for Yunnan Province. Second, based on the zoning results and using data from NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) and the Tropical Rainfall Measuring Mission (TRMM) 3B43, the vegetation condition index (VCI), the temperature condition index (TCI), the precipitation condition index (TRCI), and three topographic factors including the digital elevation model (DEM), slope (SLOPE), and aspect (ASPECT) were selected as model parameters. Multiple linear regression models were then used to establish integrated drought monitoring frameworks at different eco–geographical zoning scales. Finally, the standardized precipitation evapotranspiration index (SPEI) was used to evaluate the monitoring effects of the model, and the spatiotemporal variation patterns and characteristics of winter and spring droughts in Yunnan Province from 2008–2019 were further analyzed. The results show that (1) compared to the traditional non-zonal models, the drought monitoring model constructed based on ecological–geographic zoning has a higher correlation and greater accuracy with the SPEI and (2) Yunnan Province experiences periodic and seasonal drought patterns, with spring being the peak period of drought occurrence and moderate drought and light drought being the main types of drought in Yunnan Province. Therefore, we believe that ecological–geographic zoning can better adapt to geographical spatial heterogeneity characteristics, and the zonal drought monitoring model constructed can more effectively identify the actual occurrence of drought in large regions. This research finding can provide reference for the formulation of drought response policies in large-scale regions.

Attribution of hydrological droughts in large river-connected lakes: Insights from an explainable machine learning model

Large lakes play an important role in water resource supply, regional climate regulation, and ecosystem support, but they face threats from frequent extreme drought events, necessitating an understanding of the mechanisms behind these events. In this study, we developed an explainable machine learning (ML) model that combines the Bayesian optimized (BO) long short-term memory (LSTM) model and the integrated gradients (IG) interpretation method to simulate and explain lake water level variations. In addition, the hydrological drought trends and extreme drought events in Poyang Lake from 1960 to 2022 were identified using the standardized water level index (SWI) and run theory. The analysis revealed that the frequency of hydrological droughts in Poyang Lake increased from 1960 to 2022, especially in the autumn after 2003. By selecting the flows of the catchment and the Yangtze River as the input features, the BO-LSTM model accurately predicted the water level of Poyang Lake. The IG method was then used to interpret the prediction results from three aspects: the importance ranking of the input features, their roles in the seasonal drought trends, and their roles in extreme drought events. The results indicate that (1) the most influential factor affecting the water level of Poyang Lake was the inflow of the Ganjiang River in the catchment. (2) The increase in the lake outflow caused by the Yangtze River's draining effect was the reason for the intensification of the autumn drought in Poyang Lake. (3) The extreme hydrological drought events were primarily caused by low catchment inflows. Overall, this research provides a new approach that balances prediction accuracy with interpretability for predicting and understanding the hydrological processes in large river-connected lakes. Moreover, this method was also applied to the attribution analysis of hydrological drought in Poyang Lake, providing theoretical support for regional water resource management.

Drought Assessment based on Different Metrological Drought indices in Sulaymaniyah Governorate, KRG, Iraq

Drought is a dangerous situation that lowers individual standards of living. It is considered a devastating natural event. This study intends to thoroughly examine the occurrence and characteristics of drought events in the Sulaymaniyah Governorate from 1985 to 2015. The study employed three standardized indices: the standardized precipitation evapotranspiration index (SPEI), the standardized precipitation index (SPI), and the Reconnaissance Drought Index (RDI). These indices were utilized at different periods, namely 3, 6, 9, and 12 months. According to findings, the maximum percent of extremely dry highlighted in Sulaymaniyah and Dukan stations for SPI index and time scale three months was 48% and 30%, respectively; the maximum percent of severely dry highlighted using RDI index and time scale three months with 41%, 32%, 44% in Sulaymaniyah, Dukan, and Darbandikhan stations respectively. Results revealed that the years 1998, 1999, 2000, 2007, 2008, 2009, and 2010 saw a drought for the used indices, Dukan station has the maximum severity of 112.25 for SPEI12 for the event happened from Nov. 2007 to Sep 2015. The maximum durations were observed at Dukan station using SPI and SPEI as well, and Darbandikhan station has the highest drought frequency. The correlations of drought indices, using the coefficient of determination ( ) showed the lowest and highest agreement between SPI-SPEI and SPI-RDI, respectively. The findings revealed that water resources in the study area are at risk of depletion due to drought. Therefore, water management techniques are required to mitigate drought in the study area.

Three-dimensional morphometry of the human thoracic aorta using centerline analysis based on least-squares plane fitting

ObjectiveA novel approach to 3-dimensional morphometry of the thoracic aorta was developed by applying centerline analysis based on least-squares plane fitting, and a preliminary study was conducted using computed tomography imaging data. MethodsWe retrospectively compared 3 groups of patients (16 controls without aortic disease, and 16 cases each with acute type B aortic dissection and congenital bicuspid aortic valve). In addition to the standard assessment indices for curvature κ and torsion τ, we conducted coordinate transformation based on the least-squares plane, divided the centerline into 3 representative features (transverse, anterior-posterior, and longitudinal displacements), and analyzed the overall and local displacement in each direction. The transverse displacement, represented by the distance of the centerline from the least-squares plane, was curve-fitted to the damped oscillation waveform. Thereafter, damped oscillation parameters were compared for each group. ResultsCurvature κ exhibited a bimodal distribution, with peaks observed in the ascending aorta and aortic arch, and torsion τ exhibited a transition from positive to negative values in the arch. There were significant differences in the mean displacement between the groups for each direction (transverse P = .0083, anteroposterior P = .010, longitudinal P = 1.32 × 10−6). Furthermore, interval integral analysis revealed that several intervals exhibited significant differences between groups in each direction. The amplitude of damped oscillation parameters was significantly larger in the bicuspid aortic valve group than in the control and type B aortic dissection groups. ConclusionsThe novel analytical approach permitted a quantitative assessment of the 3-dimensional morphological differences between the control, type B aortic dissection, and bicuspid aortic valve groups.

A novel framework for assessing the joint and relative impacts of precipitation and groundwater on ecological drought processes in Northwest China

AbstractEcological drought has emerged as a critical research topic within eco‐hydrology, driven by the increased drought risk associated with global warming. This study aims to unravel the hydrological processes driving ecological drought in Northwest China by (1) constructing standardized indices for precipitation, groundwater storage anomaly, and ecological water deficit to detect variation across different hydrological components; (2) developing a framework to assess the joint and relative impacts of precipitation and groundwater variations on ecological drought; and (3) identifying the primary hydrological drivers of ecological drought across different regions. The results indicate that the joint impact of precipitation and groundwater on ecological drought variation dominates approximately 60% of the area, primarily in arid and semi‐arid regions. The average contribution of this joint impact to the alleviation of ecological drought ranges between 0.26 and 0.43 across all seasons. Notably, groundwater scarcity, rather than precipitation variation, is the primary driver of ecological drought in regions such as southern Shaanxi, southeastern Gansu, and southern Qinghai, accounting for 12.7% to 21.8% of the total area. These insights into the complex hydrological processes underlying ecological drought have significant implications for water resource management and ecosystem conservation in drought‐prone regions. This research provides valuable information for mitigating drought impacts and protecting vulnerable ecosystems in Northwest China and similar regions worldwide.

Spatiotemporal variability of hydro-meteorological droughts over the Arabian Peninsula and associated mechanisms

This study examines the spatiotemporal variability of drought and associated physical processes over the Arabian Peninsula (AP). For this purpose, we computed the standardized precipitation evapotranspiration index (SPEI) for the period 1951–2020 using the Climate Research Unit and fifth generation ECMWF atmospheric reanalysis datasets. By applying rotated empirical orthogonal function analysis on the SPEI data, we identified four homogeneous and coherent drought regions. The droughts in the northern regions follow a relatively similar temporal evolution as compared to those in the southern region. All four sub-regions of the AP exhibit a significant drying trend (p < 0.01) with an abrupt acceleration in drought frequency and intensity over the last two decades. The increase in droughts is associated with the reduction of synoptic activity and an increase in the high pressure over the AP. Seasonally, potential evapotranspiration is the dominant driver of summer droughts in the AP, whereas both precipitation and temperature are important for driving winter droughts. The summer droughts, mainly over the northern AP, are due to the occurrence of an anomalous equivalent barotropic high associated with anomalous dry and hot conditions. However, anomalous dry conditions in winter are a result of an anomalous paucity of winter storms caused by the weakening of the sub-tropical jets.

SCREENING OF RICE GERMPLASM AGAINST DROUGHT STRESS USING MORPHOLOGICAL PARAMETERS

Oryza sativa L. is a staple diet for billions of people in the world. Different rice varieties' drought stress responses and their effects on both qualitative and quantitative variables. Rice is the second main exportable product of Pakistan and the agriculture sector has shown remarkable growth, with the crop sector posting a growth of 6.58% in Fiscal year 2022. Drought have a bad effect on the vegetative and reproductive stages of crops. Drought stress can reduce crop yield production. The RCBD design, two-way ANOVA factorial analysis, Tukey test, Genetic advance and Heritability were used for this experiment. This study specifically focuses on the response of rice genotypes to drought stress and its effect on morphological parameters such as plant height, panicle length, stem diameter, flag leaf length and width, number of panicles per plant, and 1000-grain weight. Drought tolerance genotypes were screened out and used to the standard Index of IRRI to identify morphological processing in Rice Research Institute Kala Shah Kaku, Pakistan. Total 35 rice genotypes were sown under drought stress with checked variety. Six varieties perform better production under drought stress conditions. These varieties like Pokkoli, Vehari, Nonabokra, Kalomonk, PK10683, and Basmati 375 show better perform under drought stress. The findings of this research can contribute to the development of drought-tolerant rice varieties and enhance food security in drought-prone areas. The importance of qualitative parameters, such as panicle curvature and awning, is also explored, with potential implications for the visual appearance and market preferences of rice grains. Overall, this research provides valuable insights into the genetic basis and potential breeding strategies for improving drought tolerance in rice.

Dynamic Stochastic Model of Atmospheric Drought Forecast in Uzbekistan

The article considers a predictive model of atmospheric dryness with a one-month lead time, developed at the Scientific Research Hydrometeorological Institute. The model is based on a dynamic stochastic approach to constructing a regression predictive equation. From the set of existing methods for constructing regression equations, a method based on the characteristic roots (eigenvalues) of a correlation matrix, including a column of the predicted variable and predictor columns (extended matrix) is applied. The predicted variable is the standardized drought index SPI, and the predictors are the average monthly precipitation for the 3 months preceding the forecast month, the average monthly value of variations in solar activity (Wolf numbers) and the average monthly value of the Southern Oscillation index for the month preceding the forecast. The predictors were selected on the basis of mutual correlation and applied time series analyses between the aridity index SPI and the indicated heliogeophysical values. The performed estimates of the studied dependence of the aridity index SPI on the state of solar activity, the influence of El Niño (La Niña) and precipitation preceding the forecast date showed their high correlation. Estimates of the accuracy of the SPI forecast with a monthly advance lead time for the territory of Uzbekistan, performed on an independent sample, were quite high, which was the basis for the introduction of this model into the operational work of the hydrometeorological service of Uzbekistan (Uzhydromet).

Evaluation of Geotechnical Properties of Soil at Selected Sites in Al-Nasiriya City

Soil index properties are used to calculate and determine the geotechnical properties of soils and then determine soil suitability for the construction of engineering projects. Most of the geotechnical properties of soil affect each other directly or indirectly, and these properties can be utilized as indicators to calculate other properties. In the present study, some soil index properties were used to identify the geotechnical properties of soil. According to the unified classification system for soil, most soils were classified as low and high plasticity hilt. In addition, the soils showed a medium to a high degree of expansion according to the values of the Atterberg limit and were generally considered inactive clay soil. Based on the Standard Penetration Test values, consistency index, and compression index, the soil was stiff to extremely stiff and had high to extremely high compressibility. Finally, the results showed the need for soil for some engineering works, such as stabilization and modification, before the construction of engineering projects.

Ambient Air Quality Detection System Powered by Internet of Things-Based Sansevieria Plant (Case Study of Manduro Health Center)

Puskesmas Manduro is one of the public health service centers located at Jl. Raya Ngoro KM 14, Manduro MG Village, Ngoro District, Mojokerto Regency, East Java. As a basic health service center, it is important to monitor air quality and maintain air quality in accordance with the Environmental Quality Standard (SBMKL). This study aims to design an Internet of Things-based air quality detection system that utilizes Sansevieria plants as one of the natural solutions in absorbing air pollution levels. The method used is the research and development method which includes system design, tool making, website design, tool integration, and system testing. The sensors used are MQ-7 sensors for carbon monoxide gas, MQ-135 sensors for nitrogen dioxide gas, MQ-131 sensors for ozone gas, Dust GP2Y1010AU0F sensors for PM2.5, and DHT22 sensors for temperature and humidity. The results of testing the system for three days obtained the average temperature 30.64C, humidity 73.62%, CO 735.63 µg/m³. NO2 27.30 µg/m³, O3 32.13 30 µg/m³, and PM2.5 2.14 µg/m³. Based on the test results that have been carried out, it shows that the air quality monitoring system can provide data, graphs, and indicator levels for the Air Pollution Standard Index (ISPU). Air quality data obtained from sensors can be displayed on the LCD and also displayed in real-time through the website.

Drought sensitivity analysis of meteorological and vegetation indices in Dak Nong, Vietnam

ABSTRACT Drought poses an increasing threat to agricultural sustainability in Dak Nong, Vietnam. This study investigates the sensitivity of meteorological and vegetation indices (VIs) to drought conditions in the region. We analyzed 23 years (2000–2022) of data from 11 meteorological stations and remote sensing imagery covering various crop types. Our methodology involved correlating multiple VIs (VHI, VCI, TCI, and TVDI) with meteorological drought indices (SPI and SPEI) at different time scales. Results reveal a strong correlation (r &amp;gt; 0.7, p &amp;lt; 0.001) between the vegetation health index (VHI) and the standardized precipitation evapotranspiration index (SPEI), particularly at a 4-month time scale (SPEI4). This combination proved most effective for drought monitoring across diverse vegetation types. Spatial analysis identified drought-sensitive zones covering 10.8% of the province, with steep terrain and limited river density. These areas, predominantly occupied by perennial agriculture, annual crops, and production forests, show heightened vulnerability to water scarcity. Our findings provide a scientific basis for targeted drought management strategies, including establishing an early warning system using SPEI4 and VHI, implementing water-efficient agricultural practices, and prioritizing farmer support in high-risk areas. This study enhances drought resilience and sustainable water resource management in Dak Nong and similar tropical regions.

Determining diagnostic characteristics of the nonmarine Ostracoda (Crustacea) and their habitat selection with unique functional traits in the Kastamonu province (Türkiye)

Nonmarine ostracods are widely distributed in a variety of aquatic habitats, from mountain lakes to underground waters, where each species tends to show species-specific habitat preferences with unique functional traits to increase their survival chances. To understand the patterns of such a relationship between habitat preferences and functional traits of the species, 101 different aquatic sites in the Kastamonu province (Türkiye) were randomly sampled during August 2023. A total of 39 ostracods (20 species, 19 unnamed taxa) were encountered from 49 sites. Seventeen species are new reports for the province. Among them, six species are the most common species with cosmopolitan (or cosmoecious) characteristics. The contribution of these species to the diversity of alpha species (p < 0.05) was more than 90 %. The species with relatively high ecological tolerances generally unveiled low-optimum estimates. Canonical correspondence analysis explained 62.5 % of the correlation between environmental variables and species in which redox potential, electrical conductivity, calcium, and pH were found to be the most related variables to the species (p < 0.05). Fundiversity analysis showed that the presence of swimming setae was correlated with high values of functional diversity, functional richness, and functional distribution of species among five elevation ranges. The results of the habitat selection index and the standardized selection index coincided with the functional traits of the most common species. The species characterized by their habitat selection can be considered as diagnostic species of those specific habitats. Among them, Neglecandona neglecta, reported primarily from dams, springs, and troughs, is considered a typical diagnostic species of these habitats, while Cypridopsis vidua found in lakes and dams can be used as an indicator species for these types of lentic habitats. Similarly, three species (Heterocypris incongruens, Ilyocypris bradyi, Psychrodromus olivaceus) can play a critical role as diagnostic species in troughs but reporting them from different habitats such as ditches and rivers / lakes (I. bradyi) and dams (P. olivaceus and H. salina) indicated their wide range of habitat preferences. Hence, the results suggest that the occurrence of diagnostic species seems to correspond to certain habitat types and their functional traits.