A lateralized alpha-band marker of the interference of exogenous attention over endogenous attention.

Current theories of attention differentiate exogenous from endogenous orienting of visuospatial attention. While both forms of attention orienting engage different functional systems, endogenous and exogenous attention are thought to share resources, as shown by empirical evidence of their functional interactions. The present study aims to uncover the neurobiological basis of how salient events that drive exogenous attention disrupts endogenous attention processes. We hypothesize that interference from exogenous attention over endogenous attention involves alpha-band activity, a neural marker of visuospatial attention. To test this hypothesis, we contrast the effects of endogenous attention across two experimental tasks while we recorded electroencephalography (n = 32, both sexes): a single cueing task where endogenous attention is engaged in isolation, and a double cueing task where endogenous attention is concurrently engaged with exogenous attention. Our results confirm that the concurrent engagement of exogenous attention interferes with endogenous attention processes. We also found that changes in alpha-band activity mediate the relationship between endogenous attention and its effect on task performance, and that the interference of exogenous attention on endogenous attention occurs via the moderation of this indirect effect. Altogether, our results substantiate a model of attention, whereby endogenous and exogenous attentional processes involve the same neurophysiological resources. SIGNIFICANCE STATEMENT: Scientists differentiate top-down from bottom-up visuospatial attention processes. While bottom-up attention is rapidly engaged by emerging demands from the environment, top-down attention in contrast reflects slow voluntary shifts of spatial attention. Several lines of research substantiate the idea that top-down and bottom-up attentional processes involve distinct functional systems. An increasing number of studies, however, argue that both attention systems share brain processing resources. The current study examines how salient visual events that engage bottom-up processes interfere with top-down attentional processes. Using neurophysiological recordings and multivariate pattern classification techniques, the authors show that these patterns of interference occur within the alpha-band of neural activity (8-12 Hz), which implies that bottom-up and top-down attention processes share this narrow-band frequency brain resource. The results further demonstrate that patterns of alpha-band activity explains, in part, the interference between top-down and bottom-up attention at the behavioral level.

Residual loads from tilapia farming on the sediment of a Brazilian reservoir.

This study investigated the sediment geochemistry of a fish farming area in net cage tanks in the Rosário reservoir, Brazil. Three areas were investigated: reference (RA), fish farming (FFA), and dispersion (DA). The results were analyzed through correlation, similarity, principal component analysis, comparison with legislation, sediment quality guidelines, and sediment pollution indices. The mean concentrations for RA, FFA, and DA areas were respectively: Cu (mg.kg-1) 37.74, 62.23, and 71.83; Mn (mg.kg-1) 22.55, 66.48, and 55.90; Zn (mg.kg-1) 9.13, 114.83, and 94.27; Fe (%) 0.28, 0.40, and 0.43; OM (%) 15.84, 21.95, and 18.45; TOC (%) 1.86, 3.69, and 6.05; TN (mg.kg-1) 2365.00, 5015.00, and 3447.51; TP (mg.kg-1) 780.00, 6896.00, and 2585.50; ORP (mV) -95.50, -135.20, and -127.10; pH 6.60, 6.58, and 6.05; <63 µm 90.59, 78.68, and 87.30. Statistically, the influence of fish farming on sediment, organic matter, and pollutant sedimentation was demonstrated. Cu and Zn concentrations were below sediment quality guidelines. Regarding legal limits (resolution 454/2012/CONAMA), nutrients in the FFA area exceeded by 60% (TN) and 100% (TP), while in DA and RA areas they were 100% lower. TOC was 100% lower in all areas. Organic matter exceeded the limit by 100% in all areas. Pollution indices resulted in: low contamination factor 78%; unpolluted for 87% of pollution load and 83% of combined pollution; moderately polluted for 75% of the Nemerow index. The greatest impacts and influence of farming on pollutant sedimentation were more concentrated in the fish farming area. In terms of legal aspects and pollution indices, fish farming produced low levels of trace metal pollution and nutrient concentrations exceeded legal limits.

Non-target analysis of Danish wastewater treatment plant effluent: Statistical analysis of chemical fingerprinting as a step toward a future monitoring tool.

In an attempt to discover and characterize the plethora of xenobiotic substances, this study investigates chemical compounds released into the environment with wastewater effluents. A novel non-targeted screening methodology based on ultra-high resolution Orbitrap mass spectrometry and nanoflow ultra-high performance liquid chromatography together with a newly optimized data-processing pipeline were applied to effluent samples from two state-of-the-art and one small wastewater treatment facility. In total, 785 molecular structures were obtained, of which 38 were identified as single compounds, while 480 structures were identified at a putative level. Most of these substances were therapeutics and drugs, present as parent compounds and metabolites. Using R packages Phyloseq and MetacodeR, originally developed for bioinformatics, significant differences in xenobiotic presence in the wastewater effluents between the three sites were demonstrated.

Predictive role of NICU-related stress, postpartum depression trajectory and family coping on growth trajectory of moderate-to-late preterm infants: A longitudinal study.

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.

Multi-Omics Approaches for Freshness Estimation and Detection of Illicit Conservation Treatments in Sea Bass (Dicentrarchus Labrax): Data Fusion Applications.

Fish freshness consists of complex endogenous and exogenous processes; therefore, the use of a few parameters to unravel illicit practices could be insufficient. Moreover, the development of strategies for the identification of such practices based on additives known to prevent and/or delay fish spoilage is still limited. The paper deals with the identification of the effect played by a Cafodos solution on the conservation state of sea bass at both short-term (3 h) and long-term (24 h). Controls and treated samples were characterized by a multi-omic approach involving proteomics, lipidomics, metabolomics, and metagenomics. Different parts of the fish samples were studied (muscle, skin, eye, and gills) and sampled through a non-invasive procedure based on EVA strips functionalized by ionic exchange resins. Data fusion methods were then applied to build models able to discriminate between controls and treated samples and identify the possible markers of the applied treatment. The approach was effective in the identification of the effect played by Cafodos that proved to be different in the short- and long-term and complex, involving proteins, lipids, and small molecules to a different extent.

Multi-layered physical factors govern mercury release from soil: Implications for predicting the environmental fate of mercury.

Despite the recognised risks of human exposure to mercury (Hg), the drivers of gaseous elemental mercury (GEM) emissions from the soil remain understudied. In this study, we aimed to identify the environmental parameters that affect the GEM flux from soil and derive the correlations between environmental parameters and GEM flux. Principal component analysis (PCA), factor analysis (FA), and structural equation modelling (SEM) were performed on samples from forest and non-forest sites. The associated results revealed the impact of each environmental parameter on GEM flux, either due to the interaction between the parameters or as a coherent set of parameters. An introductory correlation matrix examining the relationship between two components showed a negative correlation between GEM flux and atmospheric pressure at the two sites, as well as strong correlations between atmospheric pressure and soil temperature. In cases of non-forest open sites with no trees, the PCA and FA results were consistent, indicating that atmospheric pressure, solar irradiance, and soil moisture-defined as primary causality-are largely independent drivers of GEM flux. In contrast, the PCA and FA results for the forest areas with high humidity, tree coverage, and shade were inconsistent, confirming the hypothesis that primary causality affects GEM flux rather than consequent parameters driven by primary causality, such as air and soil temperature and atmospheric humidity. The SEM results provided further evidence for primary and consequent causality as crucial drivers of the GEM flux. This study demonstrates the importance of key primary parameters, such as atmospheric pressure, solar irradiance, and soil moisture content, that can be used to predict mercury release from soils, as well as the importance of consequent parameters, such as air and soil temperature and atmospheric humidity. Monitoring the magnitude of these environmental parameters alone may facilitate the estimation of mercury release from soils and be useful for detailed modelling of soil-air Hg exchange.

Evaluating long-term impacts of land use/land cover changes on pollution loads at a catchment scale.

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.

Graphical, statistical and index-based techniques integrated for identifying the hydrochemical fingerprints and groundwater quality of In Salah, Algerian Sahara.

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.

Data-driven multivariate identification of gyrification patterns in a transdiagnostic patient cohort: A cluster analysis approach.

BACKGROUND: Multivariate data-driven statistical approaches offer the opportunity to study multi-dimensional interdependences between a large set of biological parameters, such as high-dimensional brain imaging data. For gyrification, a putative marker of early neurodevelopment, direct comparisons of patterns among multiple psychiatric disorders and investigations of potential heterogeneity of gyrification within one disorder and a transdiagnostic characterization of neuroanatomical features are lacking. METHODS: In this study we used a data-driven, multivariate statistical approach to analyze cortical gyrification in a large cohort of N = 1028 patients with major psychiatric disorders (Major depressive disorder: n = 783, bipolar disorder: n = 129, schizoaffective disorder: n = 44, schizophrenia: n = 72) to identify cluster patterns of gyrification beyond diagnostic categories. RESULTS: Cluster analysis applied on gyrification data of 68 brain regions (DK-40 atlas) identified three clusters showing difference in overall (global) gyrification and minor regional variation (regions). Newly, data-driven subgroups are further discriminative in cognition and transdiagnostic disease risk factors. CONCLUSIONS: Results indicate that gyrification is associated with transdiagnostic risk factors rather than diagnostic categories and further imply a more global role of gyrification related to mental health than a disorder specific one. Our findings support previous studies highlighting the importance of association cortices involved in psychopathology. Explorative, data-driven approaches like ours can help to elucidate if the brain imaging data on hand and its a priori applied grouping actually has the potential to find meaningful effects or if previous hypotheses about the phenotype as well as its grouping have to be revisited.

An integrated strategy for the geographical origin traceability of Goji berries by antioxidants characteristic fingerprint based online ultra-performance liquid chromatography-2,2-diphenyl-1-picrylhydrazyl- photodiode array detector-mass spectrometry combined with multivariate statistics analysis.

Goji berries are now becoming increasingly popular in the human diet due to their potential health benefits. Unscrupulous traders deliberately mislabel with certain origins to gain illegal profits, which seriously affected the consumers' benefits. In this study, an online ultra-performance liquid chromatography-2,2-diphenyl-1 -picrylhydrazyl-photodiode array detector-electrospray ionization-quadrupole time of flight mass was developed for rapid screening and identification of the antioxidants from Goji berry; then, the antioxidants characteristic fingerprint was established and explored in the origins discrimination of Goji berries from China combined with multivariate statistics analysis. As a result, twenty-eight compounds were screened from Goji berry extract, 19 of which were identified by accurate molecular and ultraviolet information according to references. Principal components analysis and partial least squares discrimination analysis achieved the accurate classification from the four regions, eight compounds were selected as origin-related antioxidant markers with variable importance in projection >1 and one-way analysis of variance (P<0.05), including rutin, rutin di-hexose, P-coumaric acid tri-hexose, dicaffeoylquinic acid isomer, Quercetin-rhamno-di-hexoside, peak14, peak16, and peak27. This study provides a feasible strategy for the geographical origins discrimination of Goji berries based on antioxidant ingredients difference and will be helpful for improving the quality control level of Goji berries.

Evolution of social mood in Spain throughout the COVID-19 vaccination process: a machine learning approach to tweets analysis.

OBJECTIVES: This paper presents a new approach based on the combination of machine learning techniques, in particular, sentiment analysis using lexicons, and multivariate statistical methods to assess the evolution of social mood through the COVID-19 vaccination process in Spain. METHODS: Analysing 41,669 Spanish tweets posted between 27 February 2020 and 31 December 2021, different sentiments were assessed using a list of Spanish words and their associations with eight basic emotions (anger, fear, anticipation, trust, surprise, sadness, joy and disgust) and three valences (neutral, negative and positive). How the different subjective emotions were distributed across the tweets was determined using several descriptive statistics; a trajectory plot representing the emotional valence vs narrative time was also included. RESULTS: The results achieved are highly illustrative of the social mood of citizens, registering the different emerging opinion clusters, gauging public states of mind via the collective valence, and detecting the prevalence of different emotions in the successive phases of the vaccination process. CONCLUSIONS: The present combination in formal models of objective and subjective information would therefore provide a more accurate vision of social reality, in this case regarding the COVID-19 vaccination process in Spain, which will enable a more effective resolution of problems.

Simultaneous modeling of multivariate heterogeneous responses and heteroskedasticity via a two-stage composite likelihood.

Multivariate heterogeneous responses and heteroskedasticity have attracted increasing attention in recent years. In genome-wide association studies, effective simultaneous modeling of multiple phenotypes would improve statistical power and interpretability. However, a flexible common modeling system for heterogeneous data types can pose computational difficulties. Here we build upon a previous method for multivariate probit estimation using a two-stage composite likelihood that exhibits favorable computational time while retaining attractive parameter estimation properties. We extend this approach to incorporate multivariate responses of heterogeneous data types (binary and continuous), and possible heteroskedasticity. Although the approach has wide applications, it would be particularly useful for genomics, precision medicine, or individual biomedical prediction. Using a genomics example, we explore statistical power and confirm that the approach performs well for hypothesis testing and coverage percentages under a wide variety of settings. The approach has the potential to better leverage genomics data and provide interpretable inference for pleiotropy, in which a locus is associated with multiple traits.

The Role of Steroidomics in the Diagnosis of Alzheimer's Disease and Type 2 Diabetes Mellitus.

Epidemiological studies suggest an association between Alzheimer's disease (AD) and type 2 diabetes mellitus (T2DM). This study aimed to investigate the pathophysiological markers of AD vs. T2DM for each sex separately and propose models that would distinguish control, AD, T2DM, and AD-T2DM comorbidity groups. AD and T2DM differed in levels of some circulating steroids (measured mostly by GC-MS) and in other observed characteristics, such as markers of obesity, glucose metabolism, and liver function tests. Regarding steroid metabolism, AD patients (both sexes) had significantly higher sex hormone binding globulin (SHBG), cortisol, and 17-hydroxy progesterone, and lower estradiol and 5α-androstane-3α,17ß-diol, compared to T2DM patients. However, compared to healthy controls, changes in the steroid spectrum (especially increases in levels of steroids from the C21 group, including their 5α/ß-reduced forms, androstenedione, etc.) were similar in patients with AD and patients with T2DM, though more expressed in diabetics. It can be assumed that many of these steroids are involved in counter-regulatory protective mechanisms that mitigate the development and progression of AD and T2DM. In conclusion, our results demonstrated the ability to effectively differentiate AD, T2DM, and controls in both men and women, distinguish the two pathologies from each other, and differentiate patients with AD and T2DM comorbidities.

Multivariate Exploratory Analysis of the Bulgarian Soil Quality Monitoring Network.

The goal of the present study is to assess the soil quality in Bulgaria using (i) an appropriate set of soil quality indicators, namely primary nutrients (C, N, P), acidity (pH), physical clay content and potentially toxic elements (PTEs: Cu, Zn, Cd, Pb, Ni, Cr, As, Hg) and (ii) respective data mining and modeling using chemometrical and geostatistical methods. It has been shown that five latent factors are responsible for the explanation of nearly 70% of the total variance of the data set available (principal components analysis) and each factor is identified in terms of its contribution to the formation of the overall soil quality-the mountain soil factor, the geogenic factor, the ore deposit factor, the low nutrition factor, and the mercury-specific factor. The obtained soil quality patterns were additionally confirmed via hierarchical cluster analysis. The spatial distribution of the patterns throughout the whole Bulgarian territory was visualized via the mapping of the factor scores for all identified latent factors. The mapping of identified soil quality patterns was used to outline regions where additional measures for the monitoring of the phytoavailability of PTEs were required. The suggested regions are located near to thermoelectric power plants and mining and metal production facilities and are characterized by intensive agricultural activity.

Contrasting effects of polysaccharide components on the cooking properties of roots, tubers and bananas.

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.

A geochemical and mineralogical characterization of soils associated with podoconiosis.

Podoconiosis is a disease that causes swelling and disfiguration of the lower legs found in several developing countries where shoes are not regularly worn. The current model for the etiology of the disease proposes that mineralogical agents enter the lymph system through the skin leading to inflammation that causes swelling of the feet and legs. We collected 125 soil samples from 21 towns associated with podoconiosis, 8 towns unassociated with Podoconiosis as controls, and 3 towns of unknown status. Data collected for each soil sample included color, particle size, mineralogy, and geochemistry to distinguish unique components within the podoconiosis-associated soils. Our results indicate podoconiosis-associated soils are more highly weathered than non-podoconiosis associated soils. The enrichment of kaolinite and gibbsite suggests that these minerals, their surface chemistry, and trace elements associated with them should be prioritized in future podoconiosis research. In addition, we found that color may be a valuable tool to identify soils at greater risk for inducing podoconiosis.

Deployment of entropy information theory in the Indian Sundarban region using hydrogeochemical parameters and GIS for assessment of irrigation suitability.

The evaluation of irrigation suitability plays a crucial role for the socio-economic development of the society, especially in the region of Sundarban. For sustainable agricultural practices, groundwater quality must be suitable for irrigation; otherwise, it can degrade soil and diminish crop yield. The entropy information theory, several irrigational indices, multivariate statistics, GIS, and geostatistics are used in this work to evaluate the geographical distribution and quality of groundwater in the Indian Sundarban region. In total, 33 groundwater samples were collected in 2018 (April and May), and they were evaluated for major cations, anions, as well as other parameters like electrical conductivity (EC), soluble sodium percentage (SSP), potential salinity (PS), total dissolved solids (TDS), Kelly ratio (KR), sodium absorption ratio (SAR), permeability index (PI), residual sodium carbonate (RSC), magnesium hazard (MH), and residual sodium bicarbonate (RSBC). The overall trend of the principal cations and anions is in the sequence of Na+ ≥ Mg2+ ≥ Ca2+ ≥ K2+ and HCO3- ≥ Cl- ≥ NO3- ≥ SO42- ≥ F-, respectively, whereas the spatial variation of %Na, SAR, RSBC, and MH demonstrate very poor irrigation water quality, and spatial variation of KR, RSC, SSP, PI, and PS signifies that the irrigation water quality is excellent to good. In order to identify the specific association and potential source of the dissolved chemical in the groundwater, statistical techniques like correlation and principal component analysis were also employed. The hydrochemical facies indicates that mixed type makes up the bulk (51.51%) of the water samples. Following the Wilcox plot, more than 75% of the water samples are good to doubtful; however, by the US salinity hazard map, roughly 60.60% of the samples had high salinity (C3-S1 zone). The EWQII reports that no samples fall into the very good (no restriction) category, whereas 30.30%, 30.30%, and 39.40% of the sample wells record good (low restriction), average (moderate restriction), and poor (severe restriction) irrigation water quality, respectively. Based on this study, the bulk of the groundwater samples taken from the study area are unsuitable for cultivation. The findings of this study will also help decision-makers develop adequate future plans for irrigation and groundwater resource management.

Assessment of the water quality using multivariate statistics and the water quality index: a case study of the Yaglidere Stream (Giresun) in the Eastern Black Sea region, Turkey.

In this study, the water quality of the Yaglidere Stream passing through Espiye (Giresun-NE Turkey) and Yaglidere districts, where old and new mining activities are present, was evaluated, and characterized by using the water quality index (WQI), multivariate statistical, and GIS techniques. The downstream aquifer of the Yaglidere Stream, which originates from Erimez Mountains and reaches the sea from the west of Espiye district, meets the domestic and drinking water needs of Yaglidere and Espiye districts. In addition, activities such as energy production and fish farming are carried out along the stream. Therefore, it is of great importance to investigate the water quality of the stream. In order to evaluate the water quality, 50 water samples were taken from 10 sampling points (5 periods) along the flow direction of the stream. Parameters other than T, DO, Mg, F, NH3, CN, and HS show significant spatial variations indicating the influence of geogenic and anthropogenic activities. Some of the investigated parameters (T, DO, Ca2+, Mg2+, SO42-, NH3, CN, Fe, Se) exhibit important seasonal variations due to high seasonality in water temperature and water flow. Principal component analysis/factor analysis reveals that the parameters responsible for water quality changes in the Yaglidere Stream are mainly related to the geogenic structure, mining wastes, agricultural activities, and domestic wastes. According to the WQI values, the water samples taken from the upstream and middle part of the stream are in the water quality between "Excellent" and "Good", on the other hand, in the downstream regions where anthropogenic and geogenic effects are dominant, the water samples are in the quality of "Poor water" and "Unsuitable for drinking". The most effective water quality parameters on WQI are Al, Fe, and Mn and the water quality in the basin is negatively affected by geogenic and anthropogenic effects.

Dynamic Feature Extraction-Based Quadratic Discriminant Analysis for Industrial Process Fault Classification and Diagnosis.

This paper introduces a novel method for enhancing fault classification and diagnosis in dynamic nonlinear processes. The method focuses on dynamic feature extraction within multivariate time series data and utilizes dynamic reconstruction errors to augment the feature set. A fault classification procedure is then developed, using the weighted maximum scatter difference (WMSD) dimensionality reduction criterion and quadratic discriminant analysis (QDA) classifier. This method addresses the challenge of high-dimensional, sample-limited fault classification, offering early diagnosis capabilities for online samples with smaller amplitudes than the training set. Validation is conducted using a cold rolling mill simulation model, with performance compared to classical methods like linear discriminant analysis (LDA) and kernel Fisher discriminant analysis (KFD). The results demonstrate the superiority of the proposed method for reliable industrial process monitoring and fault diagnosis.

Phoenicin Switch: Discovering the Trigger for Radical Phoenicin Production in Multiple Wild-Type Penicillium Species.

Society faces the challenge of storing energy from sustainable sources in inexpensive, nontoxic ways that do not deplete the limited resources of Earth. In this regard, quinone redox flow batteries have been proposed as ideal; however, industrially used quinones have traditionally been synthesized from fossil fuels. Therefore, we investigated the production of phoenicin (compound 1), a deep violet dibenzoquinone produced by certain Penicillium species, for its industrial potential. Strains grew as surface cultures on customized growth media with varying production parameters, and phoenicin production was assessed by ultrahigh-performance liquid chromatography-diode array detection-quadrupole time of flight mass spectrometry (UHPLC-DAD-QTOF MS) analysis of the supernatant. Phoenicin production was reliant on the sucrose concentration, and by varying that, we produced 4.94 ± 0.56 g/L phoenicin on a Czapek yeast autolysate broth (CY)-based medium with Penicillium phoeniceum (CBS 249.32) as the production host, with 71.91% phoenicin purity in the resulting medium broth. Unexpectedly, metabolites corresponding to phoenicin polymers were tentatively identified in P. phoeniceum, of which the dimer (diphoenicin) was a major chromatographic peak. An MS-based metabolomics study was conducted on P. atrosanguineum using feature-based molecular networking and multivariate statistics, and it was found that few or no known secondary metabolites besides phoenicin were secreted into the growth medium. Finally, the effects of sucrose, sodium nitrate, and yeast extract (YE) in the growth medium were investigated in a 23 full factorial design. The results indicated an optimal sucrose concentration of 92.87 g/L on CY when NaNO3 and YE were fixed at 3 and 5 g/L, respectively. IMPORTANCE This work was undertaken to explore the production of fungal quinones in wild-type strains for use as electrolytes in redox flow batteries. As society converts energy production in a more sustainable direction, it becomes increasingly more important to store sustainable energy in smart ways. Conventional battery technologies imply the use of highly toxic, expensive, and rare metals; thus, quinone redox flow batteries have been proposed to be a desirable alternative. In this study, we explored the possibility of producing the fungal quinone phoenicin in Penicillium spp. by changing the growth parameters. The production of other secondary metabolites and known mycotoxins was also investigated in a metabolomics study. It was shown that phoenicin production was activated by optimizing the carbon concentration of the medium, resulting in high titers and purity of the single metabolite.