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X-ray fluorescence (XRF) analyses are fast, clean, non-destructive, and compatible with on-field operations, which are some advantages over traditional determinations using coupled plasma optical emission spectroscopy (ICP-OES). The aim of this study was to advance in situ XRF approaches for assessing the nutritional status of soybean leaves (i.e. , P, S, K, Ca, Mn, Fe, Cu and Zn). More specifically, we propose a protocol to ensure accuracy of in-field analysis and then evaluate the predictive performance of XRF via different data modelling strategies for macro- and micronutrient determination. Therefore, the XRF sensor dwell time of 60 s and the maximum time of 5 min were determined for the analysis of the leaves after leaf abscission, taking into account the influence of moisture loss on the signal intensity of the lighter elements. Regarding the predictive performance of XRF data for nutrients determination, multiple linear regression (MLR) models resulted in lower root mean square errors (RMSE) for P (433 mg kg−1), S (204 mg kg−1) and K (1957 mg kg−1); Partial least squares regression (PLS) for Ca (519 mg kg−1); and simple linear regression (SLR) for Mn (9 mg kg−1), Fe (18 mg kg−1), Zn (5 mg kg−1). The different modelling strategies exhibited equivalent RMSE for Cu (2 mg kg−1). These prediction errors are within a ±20% range, demonstrating that the in situ protocols developed in this research are useful for predicting the nutrients concentration in soybean leaves. Our study shows the possibility of using the in situ XRF sensor for the rapid and practical nutrients determination in soybean leaves, presenting good potential as a crop diagnosis tool. • X-ray fluorescence: fast, clean, non-destructive tool for leaf nutrient analysis. • Protocols for soybean leaf nutrient analysis were evaluated. • X-rays fluorescence speed up foliar fertilizer decisions for soybeans. [ABSTRACT FROM AUTHOR]

Exploring the impact of performance audits on public company management becomes a crucial field of study, highlighting how these critical assessments not only reveal operational effectiveness but also shape strategic and policy decisions. Plithogenic statistics analysis, in particular, emerges as an innovative approach that goes beyond traditional methods, introducing the inherent complexity of multiple interdependent variables and their dynamic effects on organizational outcomes. This statistical framework not only captures the inherent fluctuations in the data, but also unravels the root causes of varying performances, providing deep insights that challenge static perceptions of public administration. From a practical perspective, plithogenic analysis not only quantifies current performance, but also anticipates future trends, equipping managers with powerful tools to adjust strategies and policies more precisely. By considering the complex interaction between multiple factors, from resource management to operational efficiency, this statistical approach allows for a more holistic and nuanced assessment of the impacts of performance audits. Thus, a dynamic landscape is revealed where each piece of data reflects not only superficial results, but also the hidden connections that define the effectiveness and long-term sustainability of modern public companies. [ABSTRACT FROM AUTHOR]

The exploration of the impact of educational reforms on teacher performance is a topic that has gained unusual relevance in recent decades. By analyzing these reforms through the prism of Plithogenic statistics, a window opens to a new approach that allows us to understand the inherent complexity of contemporary educational systems. Plithogenic statistics, which integrate heterogeneous and multivariate data, provide a powerful tool for unraveling how educational policies affect teacher performance. In this study, a multifaceted approach has been employed, ranging from longitudinal data analysis to qualitative evaluation of teacher perceptions, revealing an intricate interconnection between the reforms implemented and the results observed in the classrooms. The conclusions derived from this analysis are revealing and, in a certain sense, paradigmatic. Educational reforms, far from being mere administrative interventions, emerge as agents of dynamic change that influence the motivation, professional development and, ultimately, the performance of teachers. However, this impact is not homogeneous; varies significantly depending on the institutional context and the individual characteristics of educators. Through the application of Plithogenic methods, it has been possible to capture the subtle interaction of these factors, providing a more nuanced and holistic vision of educational reality. In summary, this study not only expands the understanding of educational reforms, but also highlights the importance of using advanced statistical approaches to capture the complexity of modern educational phenomena. [ABSTRACT FROM AUTHOR]

Water quality monitoring is paramount in identifying and mitigating pollution sources, protecting aquatic ecosystems, and ensuring safe water for human and wildlife consumption. This study is aimed at evaluating the quality of drinking water sources in three communities located in a Sustainable Use Conservation Unit in the municipality of Mangaratiba, Rio de Janeiro, Brazil, employing a multivariate statistical analysis. A total of 161 water samples were collected from January to December 2022, encompassing 32 surface water and 129 tap water samples. Physicochemical parameters were determined in situ employing a Horiba U50 multiparameter probe. The samples were stored and transported at 4 °C to the laboratory for microbiological analyses concerning total coliforms and Escherichia coli using a commercial enzymatic test. All samples contained coliforms, while E. coli were detected in 87% of the samples. The multivariate analysis indicated that the microbiological water quality in sampling region R2 was influenced by rainy periods and that, in general, the water quality within R3 was the most affected by the transport of solids to the water sources. The statistical methods applied herein aided in characterizing the study areas and detecting points of attention regarding physicochemical and microbiological parameters that significantly influence the water quality of each sampling point. Representative points for each study region were identified and may be employed for future monitoring and prevention actions. [ABSTRACT FROM AUTHOR]

The occurrence of Potentially Toxic Elements (PTEs) and other chemical elements in urban and peri-urban soils impacts human health and quality of life, posing a challenge for geoscientists. This study investigated the soil geochemistry of Lamia City, focusing on identifying the geogenic and anthropogenic origins of elements. A total of 168 topsoil samples (0–10 cm) were collected in April 2023, and the analysis included the near-total concentrations of 51 elements. Descriptive, correlation, multivariate statistics (i.e., Factor Analysis-FA and Hierarchical Cluster Analysis-HCA), Geographic Information Systems (GIS) mapping, and mineralogical analysis were employed to identify potential element sources. The results indicated that the elements in soils originated from geogenic, anthropogenic, and mixed sources. Geogenic origins are associated with ultramafic rocks (e.g., Mg, Cr, Ni, Co, Fe, Sc, Mn), carbonate rocks (e.g., Ca, Sr), and Quaternary sediments (e.g., K, Na, Ba, Tl, Be, Rb, Ti, V, Ga, and Rare Earth Elements-REEs); associations are linked to specific identified minerals. All applied statistical analyses reveal that the mobility of chemical elements in the urban and peri-urban soils of Lamia city is primarily affected by geochemical processes such as element substitution, chemical weathering, pedogenesis, adsorption, precipitation, evaporation, and organic matter presence. The P, Ag, Hg, Pb, Sn, Zn, Sb, Cd, Cu, and U were associated with anthropogenic influences, particularly in areas with high population density, heavy vehicle traffic, and intensive agricultural practices. Additionally, some elements (e.g., Ca, Cd, Cu, Mo, Mn, and Li) exhibited mixed origins. This integrated approach offers valuable insights into the spatial distribution and sources of PTEs in urban and peri-urban environments, providing critical information for environmental management and public health protection strategies. [ABSTRACT FROM AUTHOR]

The aim of this study was to assess the spatiotemporal variation in water quality in the Grande River and the Ondas River, in the city of Barreiras, Bahia, Brazil. Water samples were collected at 11 points along the rivers, and eight physical–chemical parameters (electrical conductivity, pH, alkalinity, apparent and true color, turbidity, dissolved oxygen, and biochemical oxygen demand) and three microbiological indicators (heterotrophic bacteria, total and thermotolerant coliforms) were analyzed. Spatiotemporal variation was assessed using the multivariate techniques of principal component analysis/factorial analysis (PCA/FA) and hierarchical cluster analysis (HCA). The results of the PCA/FA highlighted eight of the eleven parameters as the main ones responsible for the variations in water quality, with the greatest increase in these parameters being observed in the rainy season, especially among the points influenced by sewage discharges and by the influence of the urban area. The CA grouped the results from 11 points into three main groups: group 1 corresponded to points influenced by sewage discharges; group 2 grouped points with mainly urban influences; and group 3 grouped points in rural areas. These groupings showed the negative influence of urbanization and also statistically significant variations between the groups and periods. The most degraded conditions were in group 1, and the least degraded conditions were in group 3. Assessment of the variations between the monitoring periods showed that rainfall had a significant impact on the increase or decrease in the parameters assessed, as a result of surface runoff linked to urbanization and increased river flow. [ABSTRACT FROM AUTHOR]

Background: Complexity in landscape structure is often assessed using individual metrics related to ecological processes. However, this rarely incorporates important relationships among metrics and may miss landscape structure effects. Multivariate statistics provide techniques for assessing overall landscape structure effects. We assessed how multivariate statistics could be used to connect landscape structure with an ecological process [bobcat (Lynx rufus) wildlife crossing structure (WCS) use]. We tested how landscape structure at WCS sites compared to the surrounding landscape and how structure affected detections at WCS sites. Our study was conducted in Cameron County, Texas, USA where WCSs are in various stages of construction and monitoring. We used a classified land use/land cover map and aerial LiDAR to calculate configuration and density metrics at WCS and random sites. We created indices for configuration and density using principal components analysis to assess landscape structure effects on camera trap detections at WCSs. Results: Landscape structure at WCSs did not differ from random locations. Wildlife crossing structure use increased with greater woody cover and decreased with increasing vegetation density. Our indices allowed identification of differences in how configuration and density impacted WCS use. Ordination methods helped identify individual contributions of landscape metrics to the overall landscape structure effect. Conclusions: Wildlife crossing structures are permanent fixtures on landscapes, so selecting appropriate locations using broad-scale landscape structure likely increases target species use. Using indices of landscape structure provides planners with a more holistic approach to WCS placement and provides a more comprehensive picture of landscape pattern and process relationships. [ABSTRACT FROM AUTHOR]

We used lipid, fatty acid, and stable isotope analyses to investigate variation, over nine months, in the trophodynamics of 10 dominant cryptofaunal, macroalgal/algal, and environmental components from two sites within a rhodolith (Lithothamnion glaciale) bed in southeastern Newfoundland (Canada). There was an overall shift from a diatom-based food web following the spring phytoplankton bloom to a kelp/algae-based food web during fall, accompanied by preferred use of EPA (20:5ω3) over DHA (22:6ω3) in most cryptofauna. The food web contained three trophic levels that encompassed: (1) direct feeding relationships from primary producers (e.g., rhodoliths, macroalgae) to second-order consumers (e.g., sea stars, polychaetes); (2) trophic subsidy from within and outside the rhodolith bed via settlement, resuspension, and consumption of macroalgal fragments and other detrital organic matter; and (3) strong pelagic/benthic coupling. Riverine input did not affect cryptofaunal diets, as shown by the lack of terrestrial biomarkers at the study site nearest to the riverine input, and there were minor differences in trophodynamics between both study sites. The present study's findings, applicable to relatively broad spatial and temporal domains, as well as those of complementary studies of the same rhodolith bed, uncover high spatio-temporal stability of the rhodolith bed framework and of resident cryptofaunal abundance, diversity, and trophodynamics. [ABSTRACT FROM AUTHOR]

This research aimed to evaluate the efficiency of composting waste from urban and agro-industrial forestry pruning in the broiler production chain (BPC), using PCA multivariate statistics and FTIR spectroscopic analysis. Three composting windrows were assembled, weighing 419 kg (dry matter) with an initial C/N ratio of 22.2. Organic materials such as pruning residues from urban afforestation, cellulosic sausage casing, hatchery residue, floater sludge, and agro-industrial broiler ash composed the windrows. The evaluated treatments were S35: 35 days, S63: 63 days, and S95: 95 days of stabilization. Physicochemical parameters, FTIR, and absorbance index assessed the process. These values were submitted to PCA multivariate statistics to select two PC, capable of explaining 90.2% of the data. PC1 divided the parameters into two groups exhibiting the residues stabilization characteristics at 35, 63, and 95 days of composting. The FTIR displayed an increase in the 1650/2925 and 1650/2845 ratios and a decrease in the 2920/1640 ratio for all treatments as compared to its initial composition. An outcome reflects the degradation of aliphatic groups and increase of aromatic structures as the composting time progresses. The PCA allowed the evaluation of physicochemical parameters and the degree of stabilization of the residues in the composting process. FTIR found significant transformations of the organic matter in the first 35 days of the process. [ABSTRACT FROM AUTHOR]

The branches and leaves of 8 varieties of Lonicera japonica as materials, a high-performance liquid chromatography detection method for 8 phenolic acid components was established to determine the content characteristics of phenolic acids in the samples. The content determination results were evaluated by multivariate statistical methods such as cluster analysis, factor comprehensive analysis, and partial least squares discriminant analysis (PLS-DA). The results indicated that the established method for determining the content of 8 phenolic acids in the branches and leaves of L. japonica was stable, reliable and simple. The variation range of phenolic acids total content in the branches and leaves of 8 varieties of L. japonica was 19.4162~33.6684 mg⋅g-1, and 40.9900~80.3068 mg⋅g-1, respectively. The total content of phenolic acids varied greatly among different varieties, with 'Beihua No.1' had the highest total content in both branches and leaves, and 'Juhua No.1' had the lowest total content. Cluster analysis found that among the branches of 'Beihua No.1' was clustered separately into one group, with higher content of each component than other varieties. Factor comprehensive analysis showed that the comprehensive score of 'Beihua No.1' was >1. PLS-DA analysis identified isochlorogenic acid A, isochlorogenic acid C, ferulic acid and chlorogenic acid as the main components that might cause differences in phenolic acid content in branches. Among leaves, 'Beihua No.1' and 'Jiufeng No.1' were clustered into one category, and their comprehensive factor analysis scores were both greater than 1. PLS-DA analysis identified chlorogenic acid, caffeic acid and ferulic acid as the main components that might cause differences in phenolic acid content in leaves. In summary, there were differences in the main phenolic acid composition characteristics of different varieties. In terms of phenolic acid content, the branches and leaves of 'Beihua No.1' and 'Jiufeng No.1' have more advantages. This study provides a scientific basis for the utilization of L. japonica branches and leaves. [ABSTRACT FROM AUTHOR]

Edible insects are considered among the most promising sustainable sources of protein to address the predicted deficiency of conventional food protein. Due to their nutritional and environmental benefits, there is an increasing interest in the ways insects could become part of the Western diet. Little is known about Greek consumers' attitudes toward the habit of consuming insects as food. This study provides insight into Greek consumers' preferences for insect-based food products. The data were collected through an online questionnaire (n = 1531). A two-step cluster analysis and a categorical regression were employed to classify the respondents into discernible clusters and determine the relationship between their socioeconomic characteristics and their willingness to adopt insect-based food products. Feelings of disgust and rejection were the predominant reactions to the concept of insects as food. The acceptance of novel foods derived from edible insects could be potentially enhanced by providing information regarding their positive effects, using familiar food products, and decreasing the insect's degree of visibility by employing processed forms. Finally, the categories of insect protein-enriched food products (bakery, meat, snacks) that Greek consumers are more likely to consume were revealed. Such findings may be useful for promoting strategies regarding consuming insect-based products. [ABSTRACT FROM AUTHOR]

Groundwater is gradually becoming the primary water source for humans and other living organisms to sustain life on Earth. The groundwater quality in the industrial regions has been significantly contaminated in recent years due to anthropogenic activities, leading to various human health issues. In this study, the groundwater quality and hydrogeochemical characteristics of the Ranipet Industrial Corridor (RIC) were assessed by employing multivariate statistics, standard scatter plots, and the water quality index (WQI). Forty groundwater samples (12 bore wells and 28 open wells) were collected during the post-monsoon (January 2022) season, and the estimation of physicochemical parameters was carried out based on American Public Health Association (APHA) guidelines. The evaporation and rock-water interaction are controlling groundwater hydrochemistry in the study area, as illustrated by Gibbs's diagram. In contrast, 82% of groundwater samples are severely affected by human activity, and 12% are impacted by silicate weathering, illustrated by scatter plots. According to the Chadha diagram, gypsum dissolution is the primary reason for the chemical composition of groundwater in the RIC (87.5%). The primary hydrochemical processes in the study area include silicate weathering, evaporation, ion exchange, and rock-water interaction. The Mukundarayapuram, Navlock, and Melvisharam region's groundwater quality is unsuitable (92.5%) for irrigation due to the high concentration of sodium, based on Sodium Adsorption Ratio (SAR) results. Anthropogenic activities are the primary cause of groundwater degradation and hydrogeochemical changes, with the groundwater quality of RIC being over 60% very poor. A comprehensive treatment procedure before effluent discharge and stringent water regulating policies governed by environmental monitoring organizations are the pressing priorities to build a sustainable environment and reduce the health risks of groundwater. [ABSTRACT FROM AUTHOR]

The article "The Evil Twin: Older Bronze Age Ceramic Typology of the Nordic Circle" examines the older Bronze Age ceramics of the Nordic Circle. The study uses a classical typology and multivariate statistical analysis to categorize the ceramics. Ten vessel categories are identified, which can be further divided into different types and variants. The study demonstrates how ceramic production evolved in terms of diversity of forms, variation in sizes, and expression throughout the Older Bronze Age. Connections are also made between this increasing complexity and the changes in burial customs around 1300 BC. Therefore, the study provides important insights into the older Bronze Age ceramics of the Nordic Circle. [Extracted from the article]

Several authors have shown that hematological parameters can be used to detect poor prognosis in patients with cancer. Thus, such features could be used in artificial intelligence (AI-based) models to predict mortality among these patients. This work aimed to develop and compare several AI-based models to predict the prognosis (death vs. survival) of cancer in patients using blood tests and patient data as inputs. At total, 908 cancer patients were assisted in a prospective study. Four artificial intelligence models were compared: artificial neural networks (ANN), supporting vector machines (SVM), decision trees and neuro-fuzzy networks. Also, four different input strategies were tested, considering the use of 49, 45, 22 and 14 inputs. The results of this study showed that the ANN and the SVM presented the best results, using 45 inputs. The ANN was the best model since it presented better statistical values for the positive (death) and negative (survival) classes. The use of blood parameters as inputs for AI-based models could be used to predict death in patients with cancer, and this methodology can be expanded to other diseases. [ABSTRACT FROM AUTHOR]

Karst groundwater is an important water resource for the production and lives of native residents in the Qingjiang River Basin, and even the only water source for some karst areas. It is necessary to determine the pollution sources and potential health risks of metal elements in karst groundwater. In this study, 10 metal elements (i.e., Al, Cu, Pb, Zn, Cr, Ni, Co, Cd, Mn and As) in 46 groups of karst groundwater samples were analyzed. Multivariate statistical analysis and positive matrix factorization model (PMF) were used to analyze the distribution characteristics, potential sources and contribution share of metal elements in karst groundwater in the Basin. The health risk assessment model was used to evaluate the potential health risks of metal elements exposed to adults and children through different intake pathways. The results showed that the qualitative analysis was consistent with the quantitative analysis of PMF. The qualitative results showed that Co, Cu, Pb, Mn and Al were mainly affected by primary geological processes, Ni and Cd were mainly affected by industrial activities, and As was mainly affected by agricultural activities. The quantitative results of the PMF model show that there are five main influencing factors in the study area. Factor 1 is mining activity, with an average contribution rate of 14.4%. Factor 2 is light industrial production activity, with an average contribution rate of 26.3%. Factor 3 is agricultural activity, with an average contribution rate of 19.3%. Factor 4 is road traffic action, with an average contribution rate of 17.8%. Factor 5 is primary geological action, with an average contribution rate of 22.2%. The total health risks exposed for residents through drinking pathway were higher than these through skin infiltration. The health risks of adults exposed through drinking pathway were lower than that of children, but the health risks of adults exposed through skin infiltration were higher than that of children. The main metal element causing carcinogenic health risk was identified as Cr, which should be paid more attention in the development and utilization of karst groundwater resources in the Basin. [ABSTRACT FROM AUTHOR]

Abstract Background Complexity in landscape structure is often assessed using individual metrics related to ecological processes. However, this rarely incorporates important relationships among metrics and may miss landscape structure effects. Multivariate statistics provide techniques for assessing overall landscape structure effects. We assessed how multivariate statistics could be used to connect landscape structure with an ecological process [bobcat (Lynx rufus) wildlife crossing structure (WCS) use]. We tested how landscape structure at WCS sites compared to the surrounding landscape and how structure affected detections at WCS sites. Our study was conducted in Cameron County, Texas, USA where WCSs are in various stages of construction and monitoring. We used a classified land use/land cover map and aerial LiDAR to calculate configuration and density metrics at WCS and random sites. We created indices for configuration and density using principal components analysis to assess landscape structure effects on camera trap detections at WCSs. Results Landscape structure at WCSs did not differ from random locations. Wildlife crossing structure use increased with greater woody cover and decreased with increasing vegetation density. Our indices allowed identification of differences in how configuration and density impacted WCS use. Ordination methods helped identify individual contributions of landscape metrics to the overall landscape structure effect. Conclusions Wildlife crossing structures are permanent fixtures on landscapes, so selecting appropriate locations using broad-scale landscape structure likely increases target species use. Using indices of landscape structure provides planners with a more holistic approach to WCS placement and provides a more comprehensive picture of landscape pattern and process relationships.

The branches and leaves of 8 varieties of Lonicera japonica as materials, a high-performance liquid chromatography detection method for 8 phenolic acid components was established to determine the content characteristics of phenolic acids in the samples. The content determination results were evaluated by multivariate statistical methods such as cluster analysis, factor comprehensive analysis, and partial least squares discriminant analysis (PLS-DA). The results indicated that the established method for determining the content of 8 phenolic acids in the branches and leaves of L. japonica was stable, reliable and simple. The variation range of phenolic acids total content in the branches and leaves of 8 varieties of L. japonica was 19.4162~33.6684 mg·g−1, and 40.9900~80.3068 mg·g−1, respectively. The total content of phenolic acids varied greatly among different varieties, with 'Beihua No.1' had the highest total content in both branches and leaves, and 'Juhua No.1' had the lowest total content. Cluster analysis found that among the branches of 'Beihua No.1' was clustered separately into one group, with higher content of each component than other varieties. Factor comprehensive analysis showed that the comprehensive score of 'Beihua No.1' was >1. PLS-DA analysis identified isochlorogenic acid A, isochlorogenic acid C, ferulic acid and chlorogenic acid as the main components that might cause differences in phenolic acid content in branches. Among leaves, 'Beihua No.1' and 'Jiufeng No.1' were clustered into one category, and their comprehensive factor analysis scores were both greater than 1. PLS-DA analysis identified chlorogenic acid, caffeic acid and ferulic acid as the main components that might cause differences in phenolic acid content in leaves. In summary, there were differences in the main phenolic acid composition characteristics of different varieties. In terms of phenolic acid content, the branches and leaves of 'Beihua No.1' and 'Jiufeng No.1' have more advantages. This study provides a scientific basis for the utilization of L. japonica branches and leaves.

Megalobrama amblycephala, which belongs to the genus Megalobrama of the subfamily Culterinae in the family Cyprinidae, is an important freshwater cultured species in China because of its low culture cost and high growth rate. Culter alburnus, belonging to the subfamily Culter, is another slender carnivorous species, whose meat is more delicate and delicious than that of M. amblycephala; however, the scales of C. alburnus are small and thin and are easily injured and fall off, and these fish are slow-growing and expensive to feed. Although both the fish are quite different in terms of diet, growth, and stress resistance, they are highly complementary to each other. Crossbreeding can combine the desired characteristics of both parents; however, this advantage is usually limited to the F1 generation. Theoretically, because the gonads are almost undeveloped during triploid growth and development, F1 heterosis can be maintained to avoid germplasm decline caused by continuous reproduction, and energy can be saved to accelerate growth and improve muscle quality. This will greatly expand the breeding space of new hybrid varieties and ensure high economic, social, and ecological value. Therefore, the triploids of M. amblycephala ♀ × C. alburnus ♂ have superior growth and economic value. To understand the growth and morphological characteristics of the triploids of M. amblycephala ♀ × C. alburnus ♂, the triploid population of M. amblycephala ♀ × C. alburnu ♂ was induced by hydrostatic pressure, and successfully induced triploid (hybrid-3n) and uninduced diploid (hybrid-2n) populations were obtained. At the same time, two self-breeding populations of Megalobrama (MA) and Culter (CA) were established. The growth performance and morphological characteristics of the four kinds of fish were compared and analyzed in growth contrast experiments. The results showed that during the 210-day growth cycle, the absolute weight gain (0.88±0.11 g/day) of hybrid-3n was 8.64% higher than that of hybrid-2n, 20.55% higher than that of MA, and 120.00% higher than that of CA. In terms of countable traits, the hybrid index of hybrid-3n and hybrid-2n was 41.05 and 36.07, respectively. In terms of measurable traits, the hybrid index of hybrid-3n and hybrid-2n was 36.73 and 57.57, respectively. Cluster analysis showed that hybrid-3n was first grouped with hybrid-2n, then grouped with maternal MA, and finally grouped with paternal CA. The results showed that hybrid-3n and hybrid-2n were closer to their mothers in quantifiable traits and frame structure, showing a maternal effect. Discriminant analysis showed that the discriminant accuracy of hybrid-3n was 90%, and the comprehensive discriminant rate of the four populations was 95%. A scatterplot of the discriminant analysis showed that the distribution centers of hybrid-3n and hybrid-2n were located between the parents and closer to the mothers. Hybrid-3n and hybrid-2n occupied partially overlapping areas, which indicates that the two are similar in proportion and frame structure, making it difficult to distinguish between them. These results are basically consistent with those obtained by cluster analysis. Most of the 11 biological traits used to construct the discriminant function were related to the longitudinal axis of the body, especially the ratio of the height of the body to the trunk, which is similar to the results obtained by principal component analysis. During principal component analysis, four principal components with a cumulative contribution rate of 75.10% were obtained, which mainly reflect morphological variations of body height and trunk length. In this study, the experimental fish were cultured in still water ponds with abundant bait. The morphological differences may be attributed to the adaptation of the fish to this ecological environment. Comprehensive analysis showed that: Hybrid-3n has a fast growth rate and has the basic conditions for promotion and application in production; The body size of hybrid-3n and hybrid-2n is between the parents, and both are slightly biased towards the mother, which mainly reflect the morphological variations of body height and trunk length; In this study, three multivariate analyses were used to effectively reflect the morphological differences among the four populations of hybrid-3n, hybrid-2n, MA, and CA from different perspectives, which has made them irreplaceable. In conclusion, this study confirmed the superior breeding potential of triploids of M. amblycephala ♀ × C. alburnu ♂, and provided basic data for the morphological comparison of hybrid offspring of M. amblycephala and C. alburnu, which is significant for the identification and protection of fish resources, and is expected to provide a theoretical basis for the establishment of new strains of M. amblycephala and C. alburnu. The results are of great significance for population identification and ploidy breeding of hybrid offspring of M. amblycephala and C. alburnu.

This study analyzed the water quality of the Yamuna river in Prayagraj across nine locations where the sampling was done upstream, downstream and middle stream from May 2019 to April 2020 using fourteen water quality parameters. Quarterly samples showed good Water Quality Index (WQI) values for summer (95.19), monsoon (77.28), and winter (90.77), but a decline in spring (102.11) due to religious activities was observed. Inductively coupled plasma mass spectroscopy suggested high concentration of Ca2+, Mg2+, K, and P in the river. Principal Component Analysis revealed 9 significant factors (eigen value >0.5) covering 25.13 – 93.89 % variance. Strong correlations included TDS-EC (0.853) and Ca2+ – Mg2+ (1.00) was observed. The correlation between water quality parameters generated by principal component analysis showed that the main parameters affecting the water quality vary in all the seasons. Based on the water quality indicators, anthropogenic activities are accountable to deteriorate the quality of river water. Therefore, the pollution status of the river need to be made publicly.

The ancient city of Phaselis, which is located along gravel, coarse sandy, and sandy beaches, is a popular area visited by thousands of domestic and foreign tourists every year, and has been selected as the study area. Sediment samples collected from 57 different locations in the ancient city of Phaselis were analyzed using an X-ray fluorescence (XRF) spectrometer, and the major, trace, and rare earth element contents of the samples were revealed. The heavy metals arsenic (As), cobalt (Co), chromium (Cr), copper (Cu), nickel (Ni), lead (Pb), tin (Sn), stronsium (Sr), and zinc (Zn) were used in the pollution index calculations. Distribution maps revealed that heavy metal concentrations reached higher levels, especially in the eastern part of the study area. Therefore, it is recommended to plant rooted macrophytes that can absorb the heavy metals Cr and Ni and perform phytoremediation of the sediment in the region. [ABSTRACT FROM AUTHOR]

Knowledge of the technological properties of wood is important for its use and the quality of its products. The aim was to assess the quality of charcoal produced from wood grown in the Cerrado biome. Wood samples of Handroanthus roseoalba (ipê branco), Handroanthus heptaphyllus (ipê roxo) and Piptocarpha rotundifolia ('blackheart') were selected. Charcoals from these samples were produced at two charring temperatures (500 and 550 °C). Basic density, total extractives, lignin and holocellulose, gravimetric yield, higher calorific value and immediate chemical properties of the charcoals were determined. Near infrared (NIR) spectra were obtained on the transverse and longitudinal faces of the wood using a DLP® NIRscan™ portable spectrometer. Partial least squares regression was used to adjust predictive models of charcoal properties using the NIR spectra measured in the precursor wood. The coefficients of determination in the cross-validation (R2cv) ranged from 0.49 to 0.87 for volatile materials, from 0.48 to 0.88 for fixed carbon and from 0.49 to 0.85 for higher calorific value of charcoal. The spectra generated better models for properties of charcoals produced at 500 °C. The models generated were satisfactory, indicating that the NIR spectrometry can predict the quality of charcoal before it is produced. [ABSTRACT FROM AUTHOR]

Evaluating how pollutant loads react to changes in land use/land cover (LULC) is a challenging task due to the intricate relationships among the many elements within a watershed. However, the difficulty in connecting LULC change and nonpoint source (NPS) pollution loads to streams may be lessened by combining hydrological modeling with geospatial tools and multivariate statistics. The objective of this study was to investigate the long-term effects of LULC change on NPS pollution loads in a highly human-dominated catchment, in central Ethiopia. In the study, hydrologic modeling was used to estimate the NPS parameters from multispectral Landsat images, and multivariate statistical techniques were then used to extract major LULC types that explain the variances of NPS loads between 1981 and 2020. The results demonstrated that there were human-induced LULC changes in the area, as the built-up and agricultural landscapes are rising (186.4% and 5.8%, respectively), and shrub and forest lands are decreasing (67.1% and 41%, respectively). As a result of these changes, the concentrations of nitrate (NO3), total P, total N, organic N, and organic P loads were increased by 69.41, 19.83, 18.45, 18.88, and 24.05%, respectively. Reductions in natural vegetation, as well as agriculture intensification, are the major contributors to the NPS pollutant losses to surface water sources. The result also revealed that pollution nutrients are strongly related to deforestation and agricultural land expansion. Proper adaptation strategies should be implemented to minimize the negative impact of LULC changes in the area. HIGHLIGHTS The proposed approaches are robust in characterizing diffusive pollution loads.; NPS nutrient loadings are estimated to increase in the area.; Deforestation and intensive agricultural activities are major contributors to the NPS loadings.; Multivariate statistical techniques have great potential for estimating significant pollution loads.;

Schizophrenia is associated with numerous abnormalities, including imbalances in all hormonal axes, among which steroids play a major role. Steroidomic studies therefore represent a promising tool for early diagnosis and appropriate treatment of schizophrenia. A total of 51 adult male schizophrenics aged 27 (22, 34) years (shown as median with quartiles) and 16 healthy controls (HCs) aged 28 (25, 32) years were enrolled into this study. Our results showed the effective differentiation of men with schizophrenia from controls based on steroidomic profiles. We also found an altered metabolic pathway from pregnenolone and its sulfate (PREG/S) to cortisol in schizophrenics with several metabolic bottlenecks such as lower PREG levels due to increased PREG sulfation and/or suppressed PREGS desulfation and attenuated conversion of 17-hydroxy-PREG to 17-hydroxy-progesterone, as well as the results suggestive of suppressed CYP11B1 activity. In contrast, steroid molar ratios suggested two counterregulatory steps involving increased conversion of PREG/S to 17-hydroxy-PREG/S and decreased conversion of cortisol to cortisone, which may maintain unchanged basal cortisol levels but may not ensure a sufficient cortisol response to stress. Our data also indicated a trend to higher 7α-, 7β-, and 16α-hydroxylation that may counteract the autoimmune complications and proinflammatory processes accompanying schizophrenia. Finally, a possible suppression of HSD17B3 activity was suggested, resulting in decreased circulating testosterone levels with increased androstenedione levels. [ABSTRACT FROM AUTHOR]

Background: Rapid monitoring of biomass conversion processes using techniques such as near-infrared (NIR) spectroscopy can be substantially quicker and less labor-, resource-, and energy-intensive than conventional measurement techniques such as gas or liquid chromatography (GC or LC) due to the lack of solvents and preparation methods, as well as removing the need to transfer samples to an external lab for analytical evaluation. The purpose of this study was to determine the feasibility of rapid monitoring of a biomass conversion process using NIR spectroscopy combined with multivariate statistical modeling, and to examine the impact of (1) subsetting the samples in the original dataset by process location and (2) reducing the spectral range used in the calibration model on model performance. Results: We develop multivariate calibration models for the concentrations of soluble xylo-oligosaccharides (XOS), monomeric xylose, and total solids at multiple points in a biomass conversion process which produces and then purifies XOS compounds from sugar cane bagasse. A single model using samples from multiple locations in the process stream showed acceptable performance as measured by standard statistical measures. However, compared to the single model, we show that separate models built by segregating the calibration samples according to process location show improved performance. We also show that combining an understanding of the sample spectra with simple multivariate analysis tools can result in a calibration model with a substantially smaller spectral range that provides essentially equal performance to the full-range model. Conclusions: We demonstrate that real-time monitoring of soluble xylo-oligosaccharides (XOS), monomeric xylose, and total solids concentration at multiple points in a process stream using NIR spectroscopy coupled with multivariate statistics is feasible. Segregation of sample populations by process location improves model performance. Models using a reduced spectral range containing the most relevant spectral signatures show very similar performance to the full-range model, reinforcing the importance of performing robust exploratory data analysis before beginning multivariate modeling. [ABSTRACT FROM AUTHOR]

Various industries, including cement production, petrochemical processing, and power plants, exert significant environmental impacts on their surroundings. The close proximity of these industries within the study area underscores the critical need to investigate soil pollution of potentially toxic elements and elucidate possible pollution sources and associated risks. The present study involved taking 44 topsoil (0–10 cm) samples of Arsenic (As), Cadmium (Cd) Cobalt (Co), Chromium (Cr), Copper (Cu), Nickel (Ni), Lead (Pb), and Zinc (Zn) concentrations, which their mean concentration were found to be 11.29, 0.46, 15.89, 67.36, 44.36, 79.93, 8.50 and 68.27 mg kg−1, respectively. Comparison with the baseline values stated in local and international soil quality guidelines has indicated higher As, Cd, Cr, Cu, and Ni concentrations. The soil pollution indices of the geoaccumulation index, pollution index, pollution load index, and enrichment factor pollution have evaluated the pollution status of the study area to be uncontaminated to moderately contaminated, moderately polluted, polluted, deficient enrichment to moderate enrichment classes, respectively. Ecological and health risks that involved the application of the single index of ecological risk, potential ecological risk, hazard quotient, hazard index, and cancer risk have revealed that the study area was ecologically in a low-risk state with an average potential ecological risk value of 90.38, while carcinogenic (10−6-10−4) and non-carcinogenic risks (>1) were also found to be in a tolerable range for human health. Possible pollution sources were identified using multivariate statistics and further confirmed and visualized by the spatial distribution maps obtained from the deterministic interpolation method of inverse distance weighting. These analyses have suggested that the soil pollution which its existence was confirmed by the related indices and comparisons, to the potentially toxic elements of Cr and Ni can be possibly attributed to the petrochemical and power plants, to Cd could be appointed to cement plant, and to Cu could be associated with agricultural activities. It has also been found that arsenic was determined to be a common pollutant among the three main industries. [ABSTRACT FROM AUTHOR]

Aims: To describe the changes in moderate‐to‐late preterm infants' (MLPIs) growth during 12 months of corrected age (CA) and to examine the predictive role of NICU‐related stress, postpartum depression trajectory and family coping ability on the physical developmental trajectory of MLPIs. Design: A prospective longitudinal study. Methods: There were 237 mother–infant dyads with at least two follow‐up data records included. General characteristics and NICU‐related stress were recorded from medical records at baseline. Infants' physical growth was measured at 40 weeks, 1, 3, 6, 9 and 12 months CA during outpatient follow‐up. Maternal postpartum depressive symptoms and family coping ability were assessed by questionnaires at 1, 3, 6, 9 and 12 months CA and 1 month CA respectively. We investigated the modifiable factors inside and outside of NICU on the trajectories of physical growth in the first year in MLPIs, mainly by using latent growth curve models with time‐varying covariates. Results: The curved trajectories of weight, length and head circumference in the first year in MLPIs demonstrated gradually slowed growth rates and these infants were above the WHO growth standards for the same age and sex. The latent growth curve models indicated that more NICU‐related stress was negatively associated with the weight and length at 40 weeks CA, and family coping ability (parent–child relationship) at 1 month CA was associated with the growth rate of weight. Besides, more NICU‐related stress predicted faster length growth rate. The infants of mothers who were in the group of high‐level postpartum depression trajectory had a slower growth rate of head circumference. Conclusions: Our study identified the modifiable factors along the care continuum influencing the trajectory of MLPIs' physical growth. Nurses should receive more training about infant stress measurement and family‐centred care to work in partnership with parents so that MLPIs can reach their full developmental potential. Also, multidisciplinary interventions including stress reduction strategies, close psychological monitoring and education improving parent–infant relationships should be further developed to achieve optimizing growth in the first year of MLPIs. Implications for the Profession and/or Patient Care: It is recommended that nurses pay attention to the long‐term physical growth status of MLPIs, and closely support their families. Quantifying NICU‐related stress and developing reduction strategies should be the priority for clinical staff during hospitalization. After discharge, persistent screening of depressive symptoms, psychological intervention and education about the parent–child relationship need to be included in the follow‐up visits. Patient or Public Contribution: No patient or public contribution. The study only included patients who were research participants. [ABSTRACT FROM AUTHOR]

We introduce a mixture of mixtures of bounded asymmetric generalized Gaussian and uniform distributions. Based on this framework, we propose model-based classification and model-based clustering algorithms. We develop an objective function for the minimum message length (MML) model selection criterion to discover the optimal number of clusters for the unsupervised approach of our proposed model. Given the crucial attention received by Explainable AI (XAI) in recent years, we introduce a method to interpret the predictions obtained from the proposed model in both learning settings by defining their boundaries in terms of the crucial features. Integrating Explainability within our proposed algorithm increases the credibility of the algorithm's predictions since it would be explainable to the user's perspective through simple If-Then statements using a small binary decision tree. In this paper, the proposed algorithm proves its reliability and superiority to several state-of-the-art machine learning algorithms within the following real-world applications: fault detection and diagnosis (FDD) in chillers, occupancy estimation and categorization of residential energy consumers. [ABSTRACT FROM AUTHOR]

The selection of sites for permanent environmental monitoring of natural water bodies should rely on corresponding source apportionment studies. Tools like the water quality index (WQI) assessment may support this objective. This study aims to analyze a decade-long dataset of measurements of 26 chemical components at 26 observation points within the Irtysh River Basin, aiming to identify priority zones for stricter environmental regulations. It was achieved through the WQI tool integrated with geoinformation systems (GISs) and multivariate statistical techniques. The findings highlighted that both upstream sections of tributaries (Oba and Bukhtarma rivers) and the mainstream of the basin are generally in good condition, with slight fluctuations observed during flooding periods. Areas in the basin experiencing significant impacts from mining and domestic wastewater treatment activities were identified. The rivers Glubochanka (GL) and Krasnoyarka (KR) consistently experienced marginal water quality throughout the observation period. Various contaminant sources were found to influence water quality. The impact of domestic wastewater treatment facilities was represented by twofold elevated concentrations of chemical oxygen demand, reaching 22.6 and 27.1 mg/L for the KR and GL rivers, respectively. Natural factors were indicated by consistent slight exceedings of recommended calcium levels at the KR and GL rivers. These exceedances were most pronounced during the cold seasons, with an average value equal to 96 mg/L. Mining operations introduced extremal concentrations of trace elements like copper, reaching 0.046–0.051 mg/L, which is higher than the threshold by 12–13 times; zinc, which peaked at 1.57–2.96 mg/L, exceeding the set limit by almost 50–100 times; and cadmium, peaking at levels surpassing 1000 times the safe limit, reaching 0.8 mg/L. The adverse impact of mining activities was evident in the Tikhaya, Ulba, and Breksa rivers, showing similar trends in trace element concentrations. Seasonal effects were also investigated. Ice cover formation during cold seasons led to oxygen depletion and the exclusion of pollutants into the stream when ice melted, worsening water quality. Conversely, flooding events led to contaminant dilution, partially improving the WQI during flood seasons. Principal component analysis and hierarchical cluster analysis indicated that local natural processes, mining activities, and domestic wastewater discharge were the predominant influences on water quality within the study area. These findings can serve as a basis for enhanced environmental regulation in light of updated ecological legislation in Kazakhstan, advocating for the establishment of a comprehensive monitoring network and the reinforcement of requirements governing contaminating activities. [ABSTRACT FROM AUTHOR]

Elodea nuttallii represents non-native and highly invasive species in Europe that significantly influence freshwater plant communities by decreasing the diversity of native species. This study aimed to determine whether the morphological and anatomical features of Potamogeton gramineus, a native species in Vlasina Lake, differ between sites where it coexists with E. nuttallii and those where E. nuttallii is not present. Environmental variables such as water depth, temperature, pH, conductivity, saturation, and O2 concentration were included in the analysis. Analyses were conducted on 32 morphological and anatomical features of P. gramineus collected from six sites within Vlasina Lake, comprising three sites where E. nuttallii was present and three sites where it was absent. The datasets containing morphometric and environmental variables underwent analysis using standard univariate techniques (Descriptive, ANOVA), Tukey's Honest Significant Difference (HSD) test, Student's t-test, and the Mann–Whitney U test, as well as multivariate statistical methods such as Canonical Discriminant Analysis (CDA). The results show the presence of morphological differentiation among P. gramineus individuals across the analyzed sites. These findings suggest that morphological and anatomical features, such as epidermis, mesophyll, palisade, and aerenchyma tissue thickness in floating leaves, number, length, width, and the surface area of stomata, as well as the width of submersed leaves and stem aerenchyma tissue thickness, effectively differentiate individuals that coexist with E. nuttallii and individuals that growth without its presence. Moreover, they indicate that P. gramineus exhibits a notable ability to modify its morphological traits in response to invasion. [ABSTRACT FROM AUTHOR]

Natural and anthropogenic water pollution caused by heavy metals has become a major problem worldwide. As a result of these processes, many harmful heavy metals are mixed into the water and endanger the environment and human health. Therefore, this study aimed to investigate the hydrogeochemical properties of the stream waters of Göynük Canyon (Göynük Stream), which is located in southern Turkey, an important touristic region of Antalya. A total of 44 water samples were retained to evaluate the geochemical type, heavy metal contamination level, and suitability for drinking and irrigation of Göynük Canyon Stream waters. All samples were analysed by inductively coupled plasma mass spectrometry (ICP-MS), X-ray fluorescence (XRF), and multi-parameter portable water quality assessment. Analysed water samples were found to be of classes II and III in terms of overall water quality. The average hardness level is above the limit values. The results of geochemical analyses showed that the common water types in the region are Mg–Ca–HCO3, Ca–Mg–HCO3, Ca–Mg–HCO3–SO4, and Ca–Mg–HCO3–Cl-water facies. Most of the samples belong to the "rock weathering dominated" region represented in the Gibbs diagram. The hydrogen ion concentration (pH), electrical conductivity (EC), and total dissolved solids (TDS) values vary between respectively 6.5–7.9; 230.4–720.8 μS/cm, and 149–468 mg/L. Cations and anions followed the order Ca2+ > Mg2+ > Na+ > K+ and HCO3 − > SO42− > Cl− > F− > NO3 − . Heavy metal anomalies in water followed an increasing order: Cu < As < Pb < Ni < Ba < Fe < Cr < Mn < Zn < Sr. These heavy metals showed high index values (Poseidon index (PoS), contamination factor (CF), enrichment factor (EF), geochemical index (Igeo), heavy metals pollution index (HPI), contamination degree (Cd), in some water samples. There is a spatial anomaly in these locations related to limestone and ophiolite. This water can be used for irrigation purposes according to Wilcox, the United States salinity laboratory diagram (USSL), permeability index (PI), Kelly’s ratio (KR), and Residual Sodium Carbonate (RSC). [ABSTRACT FROM AUTHOR]

The rankings of universities around the world were created with the aim of measuring the performance of higher education institutions as well as the quality of institutions. Such lists provide a basis for better informed decisions by applicants to the higher education market but can also be an important source of information for decision-makers in individual states on how each country's institutions are performing in the field of international scientific competitiveness. There are numerous examples of such rankings. The authors aimed to select a leading one, namely, the QS World University Rankings 2021, and to examine the ranked universities based on statistical variables obtained from the Scopus and SciVal databases created by the Dutch academic publishing company Elsevier. Thus, the aim was not to rank institutions but instead to closely examine the statistical variables and criteria of the universities ranked by QS with the help of multivariate statistics. The results show that Scopus/SciVal data can be used to examine not only researchers but also universities. The results also show a high degree of similarity. [ABSTRACT FROM AUTHOR]

Owing to increasing anthropogenic impacts, wetlands have suffered a serious environmental decline in recent decades. The sustainable management of these natural resources is fundamental to maintain both the ecosystems and the economic activities. The Lake Massaciuccoli and nearby areas represent one of the largest residual coastal marshy areas in Tuscany (Italy). This wetland is characterized by large-scale and intensive agricultural use and affected by reclamation activities, with consequent problems of erosion, subsidence and lake eutrophication and siltation. In this context, an integrated study combining hydrochemical data (water levels, electrical conductivity, pH, turbidity, major ions, trace metals) and stable isotopes (H, O, S) has been performed in the southernmost part of the basin, to better disentangle processes and interactions between groundwater and surface water and to understand the origin of solutes and their evolution. Our results indicated that both groundwater and surface water have a meteoric origin and that geochemical composition of groundwater is mainly affected by local geological and biological processes. Moreover, surface water is affected by sea water mixing and evapotranspiration/precipitation processes. The impact of agricultural activity and the use of fertilizers on the water quality appears to be limited as regards nitrates, indicating that less intense agricultural practices implemented in recent years have been successful. As regards sulfates, Fe, and Mn, we cannot fully elucidate the mechanisms underlying human influence, but the oscillation of water level and degradation of peat enhanced by reclamation and agriculture activities likely played an important role in controlling the fate of these elements. Overall, these results underline the importance of integrated approaches to disentangle geochemical processes and will be useful in supporting policy implementation and environmental protection in this valuable area of Tuscany. Findings from this work suggest the need for policy-making authorities to take actions as soon as possible to mitigate risks. Closer co-operation is essential between authorities and farmers to reduce inputs of fertilizers and chemicals into the lake and the surrounding area. Also, additional policy measures should be enforced to reduce the mechanical soil tillage and limit erosion and runoff, such as the NBSs implemented within the Phusicos Project. [ABSTRACT FROM AUTHOR]

BACKGROUND: Consumer preferences for boiled or fried pieces of roots, tubers and bananas (RTBs) are mainly related to their texture. Different raw and cooked RTBs were physiochemically characterized to determine the effect of biochemical components on their cooking properties. RESULTS: Firmness in boiled sweetpotato increases with sugar and amylose contents but no significant correlation was observed between other physicochemical characteristics and cooking behaviour. Hardness of boiled yam can be predicted by dry matter (DM) and galacturonic acid (GalA) levels. For cassava, no significant correlation was found between textural properties of boiled roots and DM, but amylose and Ca2+ content were correlated with firmness, negatively and positively, respectively. Water absorption of cassava root pieces boiled in calcium chloride solutions was much lower, providing indirect evidence that pectins are involved in determining cooking quality. A highly positive correlation between textural attributes and DM was observed for fried plantain, but no significant correlation was found with GalA, although frying slightly reduced GalA. CONCLUSION: The effect of main components on texture after cooking differs for the various RTBs. The effect of global DM and major components (i.e. starch, amylose) is prominent for yam, plantain and sweetpotato. Pectins also play an important role on the texture of boiled yam and play a prominent role for cassava through interaction with Ca2+. © 2023 Bill and Melinda Gates Foundation. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

Identifying potassium (K+) deficiency in plants has traditionally been a difficult and expensive process. Traditional methods involve inspecting leaves for symptoms and conducting a laboratory analysis. These methods are not only time-consuming but also use toxic reagents. Additionally, the analysis is performed during the reproductive stage of growth, which does not allow enough time for corrective fertilization. Moreover, soybean growers do not have other tools to analyze the nutrition status during the earlier stages of development. Thus, this study proposes a quick approach for monitoring K+ in soybean crops using hyperspectral data through principal component analysis (PCA) and linear discriminant analysis (LDA) with a wavelength selection algorithm. The experiment was carried out at the Brazilian National Soybean Research Center in the 2017–2018, 2018–2019, and 2019–2020 soybean crop seasons, at the stages of development V4–V5, R1–R2, R3–R4, and R5.1–R5.3. Three treatments were evaluated that varied in K+ availability: severe potassium deficiency (SPD), moderate potassium deficiency (MPD), and an adequate supply of potassium (ASP). Spectral data were collected using an ASD Fieldspec 3 Jr. hyperspectral sensor. The results showed a variation in the leaf spectral signature based on the K+ availability, with SPD having higher reflectance in the visible region due to a lower concentration of pigments. PCA explained 100% of the variance across all stages and seasons, making it possible to distinguish SPD at an early development stage. LDA showed over 70% and 59% classification accuracies for discriminating a K+ deficiency in the simulation and validation stages. This study demonstrates the potential of the method as a rapid nondestructive and accurate tool for identifying K+ deficiency in soybean leaves. [ABSTRACT FROM AUTHOR]

The long, gracile morphology of the limb bones of the Late Miocene hyaenid Ictitherium ebu has led to the hypothesis that this animal was cursorial. The forelimb and femur of the holotype were compared with specimens of extant Hyaenidae and Canidae. Two morphometric methods were used. The first used measurements to calculate indices of different morphological characters. The second method involved capturing photographs of the anterior distal humerus of each specimen, mapping six landmarks on them, and calculating truss distances. These distances represent a schematic reproduction of the elbow. Multivariate statistical analysis primarily separated the data based on taxonomy, yet locomotor and habitat categories were also considered. Ictitherium ebu has an overall morphology similar to that of the maned wolf and a distal humerus reminiscent of that of the aardwolf. The long, gracile limb bones of I. ebu are suggested to be adaptations for pouncing on prey, for locomotor efficiency, and for looking over the tall grass of the open environments the animal lived in, much like the present-day maned wolf. [ABSTRACT FROM AUTHOR]

This study focuses on the critical issue of access to clean water in water-stressed regions like the Middle East and North Africa (MENA). To address the challenges of water stress, the study proposes an integrated approach involving geographical, statistical, and geophysical analysis. The objectives are to assess the distribution of pollutants such as heavy metals, salts, and water turbidity near industrial facilities; identify their sources and pathways; evaluate water quality and its impact on human health; and improve environmental classification using geophysical and geochemical methods. The study area, located southeast of Qena city, is characterized by an arid climate with minimal rainfall and is primarily covered by Upper Cretaceous and Lower Eocene rocks. The third layer in the study area is considered a shallow aquifer of Quaternary alluvial deposits; it deepens from 20 m to 93 m, displaying resistivity from 18 Ω∙m to 120 Ω∙m, with thickness increasing downstream to approximately 90 m. Understanding groundwater flow from northeast to southeast is crucial for understanding pollutant distribution in the region. The research reveals variations in groundwater quality, including high total dissolved solids (TDS) ranging from 240 to 531 mg/L and electrical conductivity (EC) values ranging from 376–802 μS/cm, as well as the presence of heavy metals. Some water samples exceeded the recommended limits for certain parameters set by the World Health Organization (WHO). Spatial distribution analysis showed higher mineralization toward the northeast of the study area. Overall, the integrated approach proposed in this study can contribute to effective water-management strategies to ensure sustainable water resources and protect public health in water-stressed regions like Egypt. [ABSTRACT FROM AUTHOR]

This study includes groundwater quality data from 290 monitoring sites from 69 districts of Uttar Pradesh, India. The analysis of the data showed that 98.97, 24.48, 52.07, and 68.97% of groundwater samples had concentrations of electrical conductivity (EC), total hardness (TH), Mg2+, and HCO3−, respectively, higher than the maximum permissible limit. Groundwater quality index (GWQI) was calculated for these 290 monitoring sites which revealed that 21 sites (7.24%) had inappropriate GWQI for drinking water, and 18 sites (6.21%) had an unsuitable index for irrigation. Most of the sampling sites (98.97%) showed high EC contents in groundwater with a mean value of 999.33 μS/cm. Fluoride content was found within the permissible limits in 95.52% of the samples, while 4.48% had high concentrations. The use of hierarchical cluster analysis differentiated all the sites into two clusters: one with high pollution and the other with low pollution. Significant correlations exist between physicochemical and irrigation indicators in the correlation matrix. High loadings of EC, TH, Ca2+, Mg2+, Na+, Cl−, and SO42− were identified in the first principal component, which are thought to be pollution-controlled processes from anthropogenic sources. According to the Chadha diagram, CaHCO3 and Ca–Mg–HCl were the two most prevalent chemicals in the water. HIGHLIGHTS Water quality data from 290 sites in 69 districts in Uttar Pradesh were calculated.; Water quality index for drinking, ranging from excellent (1.38%) to unsuitable (7.24%).; Water quality index for irrigation ranges from none (83.79%) to severe (6.21%).; The significant correlations between physicochemical and irrigation indicators in the correlation matrix.; Confirmation of less fluoride contamination.;

Anthropogenic pressures on the environment are increasingly evident, characterized by uncontrolled changes in land use that adversely affect water quality. This study aims to assess how land use and land cover contribute to water quality and to evaluate the influence of spatial landscape metrics on water quality variability in eight tributary sub-basins of the Paraopeba River. The analysis considers two seasonal periods reflective of the region's tropical climate. The dataset includes spatial data on land use and land cover, digital elevation models, soil types, geology, geomorphology, spatial-temporal data, and landscape fragmentation metrics. First, spatial differences in water quality data collected at each sampling site were tested, and the significance of seasonal variations was assessed. Correlation analyses were then conducted to determine the relationships between landscape metrics and water quality parameters across the eight sub-basins, considering both seasonal periods. Key findings include the identification of mixed pollution sources, such as pasture, urban areas, and mining, which significantly affect water quality, particularly during the rainy period. Conversely, forest plantations were found to be the land use category that most positively contributed to the preservation of water quality. The relationships between landscape patterns and water quality, analyzed using redundancy analysis, revealed that the influence of landscape metrics on the variation of water quality parameters was significantly more pronounced during the dry period, explaining 75 % of the variation, compared to 49 % during the rainy period.

Copyright of Revista Brasileira de Engenharia Agricola e Ambiental - Agriambi is the property of Revista Brasileira de Engenharia Agricola e Ambiental and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Groundwater, a predominant reservoir of freshwater, plays a critical role in providing a sustainable potable water and water for agricultural and industry uses in the In Salah desert region of Algeria. This research collected 82 underground water samples from Albian aquifers to assess water quality and identify hydrogeochemical processes influencing mineralization. To achieve this objective, various methods were employed to evaluate water quality based on its intended uses. The drinking water quality index utilized revealed the water potability status, while the indicators of irrigation potability were employed to evaluate its quality for agricultural purposes. Additionally, an assessment of groundwater susceptibility to corrosion and scaling in an industrial context was conducted using several indices, e.g., Langelier index, Larson-Skold index, Ryznar index, chloride-sulfate mass ratio, Puckorius index, aggressiveness index, and the Revelle index. The findings of this study revealed that the groundwater quality for consumption fell into four categories: good (2.44%), fair (29.27%), poor (65.85%), and non-potable (2.44%). Concerning agricultural irrigation, the indexical results indicated that 15.85% of the waters exhibited adequate quality, while 84.15% were questionable for irrigation. Calculations based on various corrosion and scaling evaluation indices showed that most wells were prone to corrosion, with a tendency for calcium bicarbonate deposit formation. Furthermore, the hydrochemical study identified three water types: Na–Cl (53.66%), Ca–Mg–Cl (37.80%), and Ca–Cl (8.54%) waters. Analyses of correlation matrices, R-type clustering, factor loadings, Gibbs diagrams, scatterplots, and chloro-alkaline indices highlighted that the chemistry of the Albian groundwater is fundamentally impacted by a number of processes such as silicate weathering, evaporite dissolution, ionic exchange, and anthropogenic inputs, that played impactful role in the aquifer's water chemistry. [ABSTRACT FROM AUTHOR]

Sadhukarn, a sacred music composition performed ritually to salute and invite divine powers to open a ceremony or feast, is played in Thailand, Cambodia, and Laos. Different countries have unique versions, arranged based on musicians' skills and en vogue styles. This study presents the results of multivariate statistical analyses of 26 different versions of Sadhukarn main melodies using non-metric multidimensional scaling (NMDS) and cluster analysis. The objective was to identify the optimal number of parameters for identifying the origin and relationships among Sadhukarn versions, including rhyme structures, pillar tone, rhythmic and melodic patterns, intervals, pitches, and combinations of these parameters. The data were analyzed using both full and normalized datasets (32 phrases) to avoid biases due to differences in phrases among versions. Overall, the combination of six parameters is the best approach for data analysis in both full and normalized datasets. The analysis of the 'full version' shows the separation of Sadhukarn versions from different countries of origin, while the analysis of the 'normalized version' reveals the rhyme structure, rhythmic structure, and pitch as crucial parameters for identifying Sadhukarn versions. We conclude that multivariate statistics are powerful tools for identifying relationships among different versions of Sadhukarn compositions from Thailand, Laos, and Cambodia and within the same countries of origin. [ABSTRACT FROM AUTHOR]

In this article, an investigation into the natural radioactivity content in natural inorganic pigments was carried out, together with the assessment of the radiological health risk for the public related to external exposure to ionizing radiations, via High-Purity Germanium (HPGe) γ-ray spectrometry measurements and the calculation of several indices like the absorbed γ-dose rate (D), the annual effective dose equivalent outdoor (AEDEout) and indoor (AEDEin), and the activity concentration index (I). From the obtained results, it was possible to reasonably exclude radiological hazard effects. In addition, Pearson's correlation, principal component analysis (PCA), and hierarchical cluster analysis (HCA) were carried out with the aim of determining correlations between natural radioactivity content and radiological indices and with the analyzed samples. As a result, five clusters of the investigated pigments were recognized at the highest level of detail based on their chemical composition and mineralogical nature. [ABSTRACT FROM AUTHOR]

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Introduction: Lentil is a rich source of protein, fiber, minerals, antioxidants, folate, zinc, selenium, iron, and low amounts of fat and carbohydrates. Increasing water shortage and drought stress will be a major threat to global lentil production. The present study was conducted to determine the morphophysiological traits and grain of yield under normal and drought stress conditions, investigate tolerance indices and identify drought tolerance in some lentil genotypes. Materials and methods: In this experiment, twenty - four lentil genotypes were evaluated in the research farm of Shahrekord Faculty of Agriculture in two drought-stress environments and the normal conditions of the region in two separate randomized complete block designs with three replications experiments. In the 50% flowering stage, drought stress was done by completely stopping irrigation for the genotypes. Sampling was done at the end of the growing season. In this experiment, morphophysiological and yield traits were measured. Results and discussion: The results of composite data analysis showed that the effect of environment, genotype and the interaction effect of genotype × environment were significant on most traits. The share of these sources of variation in diversity of triats was different and environment placed on the most role in the diversity of seed yield (55.27%), genotype in the diversity of 100 seed weight (64.6%) and the number of single seed pods (53.9%). Seed yield in normal agricultural conditions has a positive correlation with most of the traits. In addition, under stress conditions, more traits had a significant correlation with grain yield. STI and GMP indices were highly correlated with yield in both environments and these indices can be used to select the superior genotype. Examining the main components of the indicators showed that the first component and two components justify 97.66% of the changes, the first component was introduced as a semi-tolerant component and the second component as a tolerant component. The results of the cluster analysis put the genotypes in three general groups. The results of cluster analysis based on STI and GMP indices put the genotypes in three separate groups. Conclusion: One of the main goals of production programs in arid and semi-arid regions is the screening of germplasm in different stages of plant growth. The results of the present research showed that drought stress in the reproductive stage reduces the morphophysiological traits and yield of lentil genotypes. Based on the results of seed yield, Kimia genotype with the lowest yield loss is known as the tolerant variety and C113 variety with the highest yield loss is known as the sensitive variety. Based on the results of seed yield, Kimia genotype with the lowest yield loss is known as the tolerant variety and C113 variety with the highest yield loss is known as the sensitive variety. [ABSTRACT FROM AUTHOR]

Surface water quality has major environmental and socioeconomic consequences, notably in terms of the country's long-term fresh water supply. This study aimed at assessing the current state of water quality and status of the Boesmanspruit in a coal mining environment. The study used historical water quality data for a period of five years from 2017 to 2021. Aluminum, calcium, iron, manganese, magnesium, sodium, sulfate, electrical conductivity, pH, and total dissolved solids were the water quality variables selected for the study; the chosen variables were chosen based on the available secondary data. The water quality was evaluated against South African resource quality objectives, the South African water quality guidelines, and the Canadian Council of Ministers of the Environment water quality index (CCME-WQI). The data were analyzed using such as the CCME-WQI, the comprehensive pollution index (CPI), and multivariate statistics. The following parameters were above the prescribed thresholds: pH, total dissolved solids, electrical conductivity, sulfate, manganese, and iron. The CCME-WQI results showed that monitoring locations GR S26 and GR S21 near mining activities had poor water quality (40–44), whereas comprehensive pollution index (CPI) also had similar category results for the monitoring points, indicating that they were heavily polluted (2.4–4.8). The WQI showed that if certain variables, such as aluminum, iron, magnesium, sulfate, electrical conductivity, and total dissolved solids, exceed the permissible range, the water quality would deteriorate in accordance with the CPI classification. Therefore, the CPI was the best way to categorize the water quality. The principal component analysis and cluster analysis identified two primary sources of pollution which are anthropogenic and natural. The utilization of statistical analysis proved to be effective in determining the ideal quantity of significant variables within the study area. The study recommends low-cost options for reducing the effects of acid mine drainage, which includes passive mine water treatment methods using artificial wetlands. [ABSTRACT FROM AUTHOR]

The quality of food is influenced by several factors during production and storage. When using marker compounds, different steps in the production chain, as well as during storage, can be monitored. This might enable an optimum prediction of food's shelf life and avoid food waste. Especially, proteoforms and peptides thereof can serve as indicators for exogenous influences. The development of a proteomics-based workflow for detecting and identifying differences in the proteome is complex and time-consuming. The aim of the study was to develop a fast and universal workflow with ultra-high temperature (UHT) milk as a proteinaceous model food with expectable changes in protein/peptide composition. To find an optimum shelf life without sticking to a theoretically fixed best-before date, new evaluation and analytical methods are needed. Consequently, a modeling approach was used to monitor the shelf life of the milk after it was treated thermally and stored. The different peptide profiles determined with high-resolution mass spectrometry (HRMS) showed a significant difference depending on the preparation method of the samples. Potential marker peptides were determined using orthogonal projections to latent structures discriminant analysis (OPLSDA) and principal component analysis (PCA) following a typical proteomics protocol with tryptic hydrolysis. An additional Python-based algorithm enabled the identification of eight potential tryptic marker peptides (with mass spectrometric structural indications m/z 885.4843, m/z 639.3500, m/z 635.8622, m/z 634.3570, m/z 412.7191, m/z 623.2967, m/z 880.4767, and m/z 692.4041), indicating the effect of the heat treatment. The developed workflow is flexible and can be easily adapted to different research questions in the field of peptide analysis. In particular, the process of feature identification can be carried out with significantly less effort than with conventional methods. [ABSTRACT FROM AUTHOR]

This study is carried out to understand the degree of soil pollution, transport mechanism, and distribution pattern of potentially toxic elements (PTEs), including the exposure effects on human health. Towards this, topsoil samples were collected from the Saman wetland and surrounding agricultural fields in the Gangetic plain, India. The results show that the mean concentration of Cu, Hg, Zn, Pb, Th, As, U, and Cd of both soil types exceed the natural background values. The multivariate analysis suggests the soils are moderately contaminated with As, Cd, Zn, Pb, and Hg (possibly from anthropogenic sources) and heavily contaminated with Th and U, likely ascended from geogenic sources. The GIS-based geostatistical plots coupled with principal component analysis (PCA) and hierarchical cluster analysis (HCA) apportion the sources of these toxic elements, which vary greatly and are closely correlated to the geogenic processes and local anthropogenic sources like pesticides and agrochemicals. The health risk assessment revealed that the cumulative hazard index (HI) values of PTEs are lower than the safe level, suggesting no significant noncarcinogenic effect for adults and children. However, excess cancer risk (ECR) values exceed the permissible limit (1 × 10−6), signifying that exposure to the toxic element concentration may cause cancer in the exposed population, most probably in the children subpopulation. Thus, this study highlights the importance of local compliance, ensuring the quality checks and management policies in using pesticides and other agrochemicals containing PTEs to control the imposed cancer risks. [ABSTRACT FROM AUTHOR]