bluuebunny/crossref_metadata_2025 huggingface dataset:
An In Silico Analysis of PCR-Based Monkeypox Virus Detection Assays: A Case Study for Ongoing Clinical Surveillance
Authors: Song Kuncheng , Brochu Hayden N. , Zhang Qimin , Williams Jonathan D. , Iyer Lakshmanan K.
Published: November 2023

The 2022 global Mpox outbreak swiftly introduced unforeseen diversity in the monkeypox virus (MPXV) population, resulting in numerous Clade IIb sublineages. This propagation of new MPXV mutations warrants the thorough re-investigation of previously recommended or validated primers designed to target MPXV genomes. In this study, we explored 18 PCR primer sets and examined their binding specificity against 5210 MPXV genomes, representing all the established MPXV lineages. Our results indicated that only five primer sets resulted in almost all perfect matches against the targeted MPXV lineages, and the remaining primer sets all contained 1–2 mismatches against almost all the MPXV lineages. We further investigated the mismatched primer-genome pairs and discovered that some of the primers overlapped with poorly sequenced and assembled regions of the MPXV genomes, which are consistent across multiple lineages. However, we identified 173 99% genome-wide conserved regions across all 5210 MPXV genomes, representing 30 lineages/clades with at least 80% lineage-specific consensus for future primer development and primer binding evaluation. This exercise is crucial to ensure that the current detection schemes are robust and serve as a framework for primer evaluation in clinical testing development for other infectious diseases.
Seroprevalence of Toxoplasma gondii, Neospora caninum and Trichinella spp. in Pigs from Cairo, Egypt
Authors: Fereig Ragab M. , El-Alfy El-Sayed , Abdelbaky Hanan H. , Abdel-Hamid Nour H. , Mazeed Amira M. , Menshawy Ahmed M. S. , Kelany Mohamed A. , El-Diasty Mohamed , Alawfi Bader S. , Frey Caroline F.
Published: November 2023

Pork production is a niche economy in Egypt, and pigs are typically raised as backyard animals with no sanitary control, potentially exposing them to various pathogens. Commercially available ELISAs were used to detect specific antibodies to the food-borne zoonotic parasites Toxoplasma gondii and Trichinella spp., as well as to Neospora caninum, in serum samples of pigs slaughtered at Egypt’s only licensed pig abattoir, the El-Bassatin abattoir in Cairo. Among the tested sera (n = 332), seroreactivity for T. gondii was 45.8% (95% confidence interval: 40.4–51.3), N. caninum was 28.0% (95% CI: 23.3–33.2), and Trichinella spp. was 1.2% (95% CI: 0.4–3.3). Mixed infection was only detected for T. gondii and N. caninum (18.7%; 95% CI: 14.7–23.4). The seroprevalence of T. gondii was significantly higher (p = 0.0003) in animals collected from southern Cairo (15 May city slum) than in eastern Cairo (Ezbet El Nakhl slum). Seroprevalence for N. caninum was higher in western (Manshiyat Naser slum; p = 0.0003) and southern Cairo (15 May city slum; p = 0.0003) than in that of eastern Cairo (Ezbet El Nakhl slum; p = 0.0003). Moreover, female pigs exhibited a higher rate of N. caninum antibodies than male ones (p < 0.0001). This study provides the first seroprevalence data for N. caninum in pigs in Egypt, and updates the prevalence of the zoonotic parasites Trichinella spp. and T. gondii.
Modulation of Swine Gut Microbiota by Phytogenic Blends and High Concentrations of Casein in a Validated Swine Large Intestinal In Vitro Model
Authors: Popov Igor V. , Einhardt Manzke Naiana , Sost Mônica Maurer , Verhoeven Jessica , Verbruggen Sanne , Chebotareva Iuliia P. , Ermakov Alexey M. , Venema Koen
Published: November 2023

Phytogenic feed additives are gaining popularity in livestock as a replacement for antibiotic growth promotors. Some phytogenic blends (PB) positively affect the production performance, inhibit pathogens within the gut microbiota, and improve the overall health of farm animals. In this study, a swine large intestine in vitro model was used to evaluate the effect of two PBs, alone or in combination with casein, on swine gut microbiota. As a result, the combination of casein with PB1 had the most beneficial effects on swine gut microbiota, as it increased the relative abundance of some commensal bacteria and two genera (Lactobacillus and Oscillospiraceae UCG-002), which are associated with greater production performance in pigs. At the same time, supplementation with PBs did not lead to an increase in opportunistic pathogens, indicating their safety for pigs. Both PBs showed fewer changes in swine gut microbiota compared to interventions with added casein. In contrast, casein supplementation significantly increased beta diversity and the relative abundance of commensal as well as potentially beneficial bacteria. In conclusion, the combination of casein with PBs, in particular PB1, had the most beneficial effects among the studied supplements in vitro, with respect to microbiota modulation and metabolite production, although this data should be proven in further in vivo studies.
Estimating Microbial Protein Synthesis in the Rumen—Can ‘Omics’ Methods Provide New Insights into a Long-Standing Question?
Authors: Lima Joana , Ingabire Winfred , Roehe Rainer , Dewhurst Richard James
Published: November 2023

Rumen microbial protein synthesis (MPS) provides at least half of the amino acids for the synthesis of milk and meat protein in ruminants. As such, it is fundamental to global food protein security. Estimating microbial protein is central to diet formulation, maximising nitrogen (N)-use efficiency and reducing N losses to the environment. Whilst factors influencing MPS are well established in vitro, techniques for in vivo estimates, including older techniques with cannulated animals and the more recent technique based on urinary purine derivative (UPD) excretion, are subject to large experimental errors. Consequently, models of MPS used in protein rationing are imprecise, resulting in wasted feed protein and unnecessary N losses to the environment. Newer ‘omics’ techniques are used to characterise microbial communities, their genes and resultant proteins and metabolites. An analysis of microbial communities and genes has recently been used successfully to model complex rumen-related traits, including feed conversion efficiency and methane emissions. Since microbial proteins are more directly related to microbial genes, we expect a strong relationship between rumen metataxonomics/metagenomics and MPS. The main aims of this review are to gauge the understanding of factors affecting MPS, including the use of the UPD technique, and explore whether omics-focused studies could improve the predictability of MPS, with a focus on beef cattle.
Stress Prediction Model of Super-High Arch Dams Based on EMD-PSO-GPR Model
Authors: Hou Chunyao , Wei Yilun , Zhang Hongyi , Zhu Xuezhou , Tan Dawen , Zhou Yi , Hu Yu
Published: November 2023

In response to the challenge of limited model availability for predicting the lifespan of super-high arch dams, a hybrid model named EMD-PSO-GPR (EPR) is proposed in this study. The EPR model leverages Empirical Mode Decomposition (EMD), Gaussian Process Regression (GPR), and Particle Swarm Optimization (PSO) to provide an effective solution for super-high arch dam stress prediction. This research focuses on three strategically selected measurement points within the dam, characterized by complex stress conditions. The predicted results from the EPR are compared with those from GPR, Long Short-Term Memory (LSTM), and Support Vector Regression (SVR), using actual stress data measured at research points within a super-high arch dam in Southwest China. The findings reveal that the proposed EPR model attains a maximum mean absolute error (MAE) of 0.02916 and a maximum root mean square error (RMSE) of 0.03055, surpassing the compared models. As a result, the EPR model introduces an innovative computational framework for stress prediction in super-high arch dams, excelling in handling stress data characterized by high vibration frequencies and providing more accurate predictions.
Identification of Breaches in a Regional Confining Unit Using Electrical Resistivity Methods in Southwestern Tennessee, USA
Authors: Hasan Md Rizwanul , Larsen Daniel , Schoefernacker Scott , Waldron Brian
Published: November 2023

Electrical resistivity and borehole data are applied to delineate lithostratigraphic boundaries and image the geometry of confining-unit breaches in Eocene coastal-plain deposits to evaluate inter-aquifer exchange pathways. Eight dipole–dipole array surveys were carried out, and apparent resistivity was inverted to examine the lateral continuity of lithologic units in different water-saturation and geomorphic settings. In addition, sensitivity analysis of inverted resistivity profiles to electrode spacing was performed. Resistivity profiles from Shelby Farms (SF) highlight the effect of varied electrode spacing (2.5, 5, and 10 m), showing an apparent ~0.63 to 0.75 depth shift in resistivity-layer boundaries when spacing is halved, with the 10 m spacing closely matching borehole stratigraphy. Grays Creek and Presidents Island profiles show clay-rich Eocene Cook Mountain Formation (CMF), with resistivity ranging from 10 to 70 Ω-m, overlying the Eocene Memphis Sand—a prolific water-supply aquifer. Resistivity profiles of SF and Audubon Park reveal sandy Cockfield Formation (CFF) paleochannels inset within and through the CMF, providing hydrogeologic connection between aquifers, and clarifying the sedimentary origin of confining-unit breaches in the region. The results underscore the efficacy of the electrical resistivity method in identifying sand-rich paleochannel discontinuities in a low-resistivity regional confining unit, which may be a common origin of breaches in coastal-plain confining units.
Exploring Climate Sensitivity in Hydrological Model Calibration
Authors: Lee Jeonghoon , Choi Jeonghyeon , Seo Jiyu , Won Jeongeun , Kim Sangdan
Published: November 2023

In the context of hydrological model calibration, observational data play a central role in refining and evaluating model performance and uncertainty. Among the critical factors, the length of the data records and the associated climatic conditions are paramount. While there is ample research on data record length selection, the same cannot be said for the selection of data types, particularly when it comes to choosing the climatic conditions for calibration. Conceptual hydrological models inherently simplify the representation of hydrological processes, which can lead to structural limitations, which is particularly evident under specific climatic conditions. In this study, we explore the impact of climatic conditions during the calibration period on model predictive performance and uncertainty. We categorize the inflow data from AnDong Dam and HapCheon Dam in southeastern South Korea from 2001 to 2021 into four climatic conditions (dry years, normal years, wet years, and mixed years) based on the Budyko dryness index. We then use data from periods within the same climatic category to calibrate the hydrological model. Subsequently, we analyze the model’s performance and posterior distribution under various climatic conditions during validation periods. Our findings underscore the substantial influence of the climatic conditions during the calibration period on model performance and uncertainty. We discover that when calibrating the hydrological model using data from periods with wet climatic conditions, achieving comparable predictive performance in validation periods with different climatic conditions remains challenging, even when the calibration period exhibits excellent model performance. Furthermore, when considering model parameters and predicted streamflow uncertainty, it is advantageous to calibrate the hydrological model under dry climatic conditions to achieve more robust results.
Data-Driven Models for Evaluating Coastal Eutrophication: A Case Study for Cyprus
Authors: Hadjisolomou Ekaterini , Rousou Maria , Antoniadis Konstantinos , Vasiliades Lavrentios , Kyriakides Ioannis , Herodotou Herodotos , Michaelides Michalis
Published: November 2023

Eutrophication is a major environmental issue with many negative consequences, such as hypoxia and harmful cyanotoxin production. Monitoring coastal eutrophication is crucial, especially for island countries like the Republic of Cyprus, which are economically dependent on the tourist sector. Additionally, the open-sea aquaculture industry in Cyprus has been exhibiting an increase in recent decades and environmental monitoring to identify possible signs of eutrophication is mandatory according to the legislation. Therefore, in this modeling study, two different types of artificial neural networks (ANNs) are developed based on in situ data collected from stations located in the coastal waters of Cyprus. These ANNs aim to model the eutrophication phenomenon based on two different data-driven modeling procedures. Firstly, the self-organizing map (SOM) ANN examines several water quality parameters’ (specifically water temperature, salinity, nitrogen species, ortho-phosphates, dissolved oxygen, and electrical conductivity) interactions with the Chlorophyll-a (Chl-a) parameter. The SOM model enables us to visualize the monitored parameters’ relationships and to comprehend complex biological mechanisms related to Chl-a production. A second feed-forward ANN model is also developed for predicting the Chl-a levels. The feed-forward ANN managed to predict the Chl-a levels with great accuracy (MAE = 0.0124; R = 0.97). The sensitivity analysis results revealed that salinity and water temperature are the most influential parameters on Chl-a production. Moreover, the sensitivity analysis results of the feed-forward ANN captured the winter upwelling phenomenon that is observed in Cypriot coastal waters. Regarding the SOM results, the clustering verified the oligotrophic nature of Cypriot coastal waters and the good water quality status (only 1.4% of the data samples were classified as not good). The created ANNs allowed us to comprehend the mechanisms related to eutrophication regarding the coastal waters of Cyprus and can act as useful management tools regarding eutrophication control.
Water and Salinity Variation along the Soil Profile and Groundwater Dynamics of a Fallow Cropland System in the Hetao Irrigation District, China
Authors: Hou Cong , Miao Qingfeng , Shi Haibin , Hu Zhiyuan , Zhao Yi , Yu Cuicui , Yan Yan , Feng Weiying
Published: November 2023

Managing soil salinity has always been a difficult problem for agriculture. Balancing water and salt while maintaining crop quality and yield is a key issue for agricultural sustainability. The Hetao lrrigation District in China has a complex mix of cultivated and uncultivated land which plays a crucial role in soil salinization processes. To investigate the dynamic properties of soil moisture and salinity, soil ions and groundwater, cultivated and fallow soils in the Hetao lrrigation District were analyzed, side by side, using a combination of field and laboratory tests, with data processed using univariate and multivariate statistical approaches. The results showed that soil moisture increased with increasing soil depth in both cultivated and fallow soils. Salinity showed an increasing trend in 2022 and 2023 from April to September. The soil ions were mainly sulfate in the cultivated soils and chloride in the fallow soils. The characteristic factors affecting salt accumulation in cultivated soils are Na++K+, Cl−, SSC, SO42−, HCO3−, and pH, and the characteristic factors affecting salt accumulation in fallow soils are Na++K+, Cl−, SSC, HCO3−, and pH. Water table depth varied with irrigation and precipitation and was strongly influenced by external environmental factors. Groundwater salinity remained stable throughout the study period. This study provides a theoretical basis for the prevention and control of soil salinization in arid and semiarid areas through the “dry drainage salt” measure.
The Identification of Selective Pathogenic Microbial Community Biofilms in Different Distribution Pipeline Materials and Their Disinfection Kinetics
Authors: Bhatti Sanam , Gadhi Tanveer A. , Mahar Rasool Bux , Ali Imran , Channa Najeebullah , Kori Junaid Ahmed , Bonelli Barbara
Published: November 2023

Biofilms in water distribution lines strongly affect water safety as they are the main carriers of pathogens. The current study investigated the biofilm formation and identification of selected pathogens in different distribution pipeline materials and their disinfection method in an annular reactor (AR). Initially, the quality of the flowing water from each pipeline material was analyzed, i.e., pH, TDS, EC, turbidity, and salinity; then, the biofilm formation was monitored for each material, i.e., ABS, PC, PVC, PP, and HDPE. Further, the disinfection kinetics of biofilm at different chlorine doses, i.e., 0.5, 1.0, 1.5, and 2.0 mg/L, was investigated. The selected pathogens, i.e., E. coli, Pseudomonas, Shigella, Salmonella sp., and Vibrio sp. were identified in biofilms formed in different pipeline materials. The disinfection kinetics results showed that a chlorine dose of 2.0 mg/L was the most effective in disinfecting selected pathogens. Following the disinfection kinetics, it was observed that Salmonella sp. was disinfected within 7 days, whereas other pathogenic biofilms were disinfected within 14 days. The efficacy of chlorine disinfection was affected by the types of pipeline materials. The study outcomes could provide insights into biofilms’ disinfection method and the selection of suitable pipeline materials to ensure drinking water safety.
Predicting the Overflowing of Urban Personholes Based on Machine Learning Techniques
Authors: Chang Ya-Hui , Tseng Chih-Wei , Hsu Hsien-Chieh
Published: November 2023

Urban stormwater drainage systems, which include many personholes to collect and discharge precipitation within a city, are extensively constructed to prevent streets and buildings from flooding. This research intends to build a machine learning model to predict whether a personhole will overflow soon, which is crucial to alleviate the damage caused by floods. To address the challenges posed by many diverse personholes, we proposed segmenting the personholes into several groups and have designed two methods employing different personhole features. The first, the geography-based method, uses the geographical locations of the personholes for the grouping. The second, the hydrology-based method, uses the characteristics that are directly related to the overflowing situation, such as the depth of the personhole, and the average and the maximum water level of the personholes. We also investigated several machine learning techniques, such as the multilayer perceptron (MLP) model and a fine-tuning architecture. The study area was located in the new Taipei city and the experimental results have shown the impressive predictive ability of the proposed approaches. Particularly, by applying the hydrology-based grouping method, and using a hybrid model combining the machine learning model prediction results with heuristic rules, we can obtain the best prediction result, and the accuracy is over 99%. We have also noticed the influence of the activation function used in the neural network and the number of frozen layers in the fine-tuning architecture. Particularly, using the tanh function with one frozen layer is good in some cases. However, since it is not general enough, we suggest the readers perform empirical studies before choosing the best setting in their own environment.
Coastal Water Clarity in Shenzhen: Assessment of Observations from Sentinel-2
Authors: Zhao Yelong , Chen Jinsong , Li Xiaoli , Li Hongzhong , Zhao Longlong
Published: November 2023

Shenzhen is a crucial city in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA). With high-intensity land development and rapid population growth, the ocean has become an essential space for expansion, leading to significant variations in water quality in the coastal area of Shenzhen. Water clarity (Zsd) is a key indicator for evaluating water quality. We applied the quasi-analytical algorithm (QAA) to Sentinel-2 data and retrieved the Zsd of the coastal area of Shenzhen. By adjusting the red band for distinguishing water types, we avoided underestimating Zsd for clear water. This study pioneered the production of a 10 m Zsd product for the coastal area of Shenzhen from 2016 to 2021. The results showed that the coastal area of Shenzhen exhibited a spatial distribution pattern with low Zsd in the west and high in the east, with Pearl River Estuary (PRE: 0.41–0.67 m) and Shenzhen Bay (SZB: 0.30–0.58 m) being lower than Dapeng Bay (DPB: 2.7–2.9 m) and Daya Bay (DYB: 2.5–2.9 m). We analyzed the seasonal and interannual variations and driving factors of the four areas, where PRE and SZB showed similar variation patterns, while DPB and DYB showed similar variation patterns. PRE and SZB are important estuaries in southern China, significantly affected by anthropogenic activities. DPB and DYB are important marine aquaculture areas, mainly affected by natural factors (wind speed, precipitation, and sea level). The Zsd of the coastal area of Shenzhen, along with the analysis of its results and driving factors, contributes to promoting local water resource protection and providing a reference for formulating relevant governance policies. It also provides a practical method for assessing and monitoring near-shore water quality.
Improved Deep Learning Predictions for Chlorophyll Fluorescence Based on Decomposition Algorithms: The Importance of Data Preprocessing
Authors: Wang Lan , Xie Mingjiang , Pan Min , He Feng , Yang Bing , Gong Zhigang , Wu Xuke , Shang Mingsheng , Shan Kun
Published: November 2023

Harmful algal blooms (HABs) have been deteriorating global water bodies, and the accurate prediction of algal dynamics using the modelling method is a challenging research area. High-frequency monitoring and deep learning technology have opened up new horizons for HAB forecasting. However, the non-stationary and stochastic process behind algal dynamics monitoring largely limits the prediction performance and the early warning of algal booms. Through an analysis of the published literature, we found that decomposition methods are widely used in time-series analysis for hydrological processes. Predictions of ecological indicators have received less attention due to their inherent fluctuations. This study explores and demonstrates the predictive enhancement for chlorophyll fluorescence data based on the coupling of three decomposition algorithms with conventional deep learning models: the convolutional neural network (CNN) and long short-term memory (LSTM). We found that the decomposition algorithms can successfully capture the time-series patterns of chlorophyll fluorescence concentrations. The results indicate that decomposition-based models can enhance the accuracy of single models in predicting chlorophyll concentrations in terms of the improvement percentages in RMSE (with increases ranging from 25.7% to 71.3%), MAE (ranging from 28.3% to 75.7%), and R2 values (increasing ranging from 14.8% to 34.8%). In addition, the comparison experiment for different decomposition methods might suggest the superiority of singular spectral analysis in hourly predictive tasks of chlorophyll fluorescence over the wavelet transform and empirical mode decomposition models. Overall, while decomposition methods come with their respective strengths and weaknesses, they are undeniably efficient in combination with deep learning models in dealing with the high-frequency monitoring of chlorophyll fluorescence data. We also suggest that model developers pay more attention to online data preprocessing and conduct comparative analyses to determine the best model combinations for forecasting algal blooms and water management.
Spatiotemporal Variations in Actual Evapotranspiration Based on LPJ Model and Its Driving Mechanism in the Three Gorges Reservoir Area
Authors: Zhang Xuelei , Wang Gaopeng , Wang Hejia
Published: November 2023

Under the influence of climate change and human activities, the ecohydrological processes in the Three Gorges Reservoir Area (TGRA) present new evolution characteristics at different temporal and spatial scales. Research on the evolution and driving mechanism of key ecohydrological element in the TGRA under the changing environment has important theoretical and practical values for correctly understanding the ecohydrological situation in the reservoir area and guiding the coordinated development of water and soil resources. In this study, the LPJ (Lund–Potsdam–Jena) model was used to simulate and analyze the spatiotemporal variations in evapotranspiration (AET) from 1981 to 2020. Sen’s slope and sensitivity analysis methods were used to quantify individual contributions of climate and human factors to changes in AET in different periods. The results indicate the following: (1) The simulation accuracy of the LPJ model for AET in the TGRA was high, with a certainty coefficient (R2), Nash efficiency coefficient (NSE), and mean relative error (MRE) of 0.89, 0.76, and 4.32%, respectively. (2) The multiyear average AET was 650.71 mm and increased at a rate of 21.63 mm/10a from 1981 to 2020. The annual distribution of AET showed a unimodal seasonal variation trend. The peak value occurred in July, reaching 113.02 mm, and the valley value occurred in January and December, less than 13 mm. (3) AET increased by 5.60% and 6.28% before and after impoundment, respectively. The contribution rate of human activities increased significantly from −3.75% before impoundment to 26.95% after impoundment, and the contribution ratios of climate change were 89.39% and 73.09%, respectively, during these two periods. From 1981 to 2020, AET increased by 5.28%, in which the contribution ratios of climate and human factors were 89.39% and 10.61%, respectively.
Bio-Based Decontamination and Detoxification of Total Petroleum Hydrocarbon-Contaminated Dredged Sediments: Perspectives to Produce Constructed Technosols in the Frame of the Circular Economy
Authors: Becarelli Simone , Bernabei Giacomo , Siracusa Giovanna , Baderna Diego , Ruffini Castiglione Monica , De Simone Giampiero , Di Gregorio Simona
Published: November 2023

To accelerate the depletion of total petroleum hydrocarbons, a hydrocarburoclastic ascomycetes, Lambertella sp. MUT 5852, was bioaugmented to dredged sediments co-composting with a lignocellulosic matrix. After only 28 days of incubation, a complete depletion of the contamination was observed. The 16S rDNA metabarcoding of the bacterial community and a predictive functional metagenomic analysis were adopted to evaluate potential bacterial degrading and detoxifying functions. A combination of toxicological assays on two eukaryotic models, the root tips of Vicia faba and the human intestinal epithelial Caco-2 cells, was adopted to assess the robustness of the process not only for the decontamination but also for the detoxification of the dredged sediments. Bacterial taxa, such as Kocuria and Sphingobacterium sps., resulted to be involved in both the decontamination and detoxification of the co-composting dredged sediments by potential activation of diverse oxidative processes. At the same time, the Kocuria sp. showed plant growth-promoting activity by the potential expression of the 1-aminocyclopropane-1-carboxylate deaminase activity, providing functional traits of interest for a technosol in terms of sustaining primary producer growth and development.
Managing the Taste and Odor Compound 2-MIB in a River-Reservoir System, South Korea
Authors: Kang Miri , Kim Deok-Woo , Park Minji , Kim Kyunghyun , Min Joong-Hyuk
Published: November 2023

High concentrations of 2-methylisoborneol (2-MIB) were reported during winter in the Paldang reservoir and North Han River, South Korea. The causes of the unusual taste and odor problems in the regulated river-reservoir system were not understood; however, a short-term solution is to flush out 2-MIB-rich water to secure water sources for over 20 million people. Approximately 150 million tons of water was released from upstream dams for 12 days (late November to early December 2018) to reduce the elevated levels of 2-MIB. Simultaneously, the spatio-temporal variations of the measured concentration of sample 2-MIB from five sites were simulated using a multi-dimensional hydrodynamics-based solute transport model to monitor the flushing effect. A modified environmental fluid dynamics code (EFDC) was adopted as the primary model framework. Five scenarios on the kinetic constants related to the characteristics of 2-MIB transport and behavior, such as conservative, net decay, and net production, were applied, and the results were compared. We found that the simulation errors on the elapsed times to satisfy the Korean drinking water monitoring standard (≤20 ngL−1) were smallest with the conservative dye transport option, indicating that the physical and biochemical characteristics of 2-MIB may not play an essential role.
Application of Multivariable Statistical and Geo-Spatial Techniques for Evaluation of Water Quality of Rudrasagar Wetland, the Ramsar Site of India
Authors: Debnath Pradip , Roy Stabak , Bharadwaj Satarupa , Hore Samrat , Nath Harjeet , Mitra Saptarshi , Ciobotaru Ana-Maria
Published: November 2023

The water quality of Rudrasagar Lake, the second-largest natural reservoir of Tripura is of great ecological and economic importance as it serves a diverse range of purposes, including fishing, irrigation, aquaculture, domestic use, and recreation activities. This study investigates the water quality of the study area, an esteemed Ramsar site in North Eastern India, using a combined application of multivariable statistical and geospatial techniques. In this study, 24 water samples were designed based on their use and collected along the periphery and the inner areas of the lake employing the Latin Square Matrix. This research also examines the spatial variations of water quality involving quartile-based water quality categorization of parameters, with Pearson’s Correlation analysis, Principal Component Analysis (PCA), and Hierarchy Cluster Analysis (HCA) applied for dimension reduction. The analysis involved quartile-based water quality categorization of parameters, with PCA and HCA applied for dimension reduction. Meanwhile, the Inverse distance weighted (IDW) approach was used to interpolate the spatial distribution of the quartile score using the ArcGIS platform. The Bureau of Indian Standards (BIS) was followed for water quality assessment. The results revealed significant spatial variation, providing valuable insights for future water management strategies. PCA indicates 57.26% of the variance in the dataset, whereas samples were classified into three subgroups and two groups in a dendrogram representing the result of the HCA. This study demonstrates the utility of PCA, HCA, and IDW interpolation in water quality assessment, highlighting the effect of human-induced activities in the lake’s vicinity.
Barriers and Motivators of Household Water-Conservation Behavior: A Bibliometric and Systematic Literature Review
Authors: Sanchez Carolina , Rodriguez-Sanchez Carla , Sancho-Esper Franco
Published: November 2023

Water scarcity, aggravated by growing demands, represents a significant challenge for humanity. Promoting household sustainable water-consumption behaviors has become vital. The Community-Based Social Marketing (CBSM) framework stands out among many strategies to promote water conservation. However, many interventions in this domain often neglect significant theoretical insights, leading to gaps in addressing key social and contextual drivers of behavior. This study conducts a systematic and bibliometric literature review aimed at identifying determinants underlying household water-conservation behaviors. This review encompasses 155 papers published from 1984 to early 2023. Our findings show that this is a highly multidisciplinary field of study with a marked increase in research attention discerned post-2010, particularly from water-stressed regions. Furthermore, our findings also reveal an often-overlooked integration of guiding theories and an over-reliance on self-reported measures in prior research. Factors such as attitude, perceived efficacy, emotions, and habits emerge as pivotal in understanding water conservation. However, while attitudes have been extensively analyzed in previous research, the other factors deserve greater attention from researchers. Inconsistencies in demographic predictors further hint at potential moderating roles. This paper offers valuable insights for designing effective household water-conservation interventions through a social marketing lens.
Estimating Soil Strength Using GIS-Based Maps - A case study in Sweden
Authors: MOHTASHAMİ Sima , HANSSON Linnea , ELİASSON Lars
Published: November 2023

Soil strength is an important parameter for planning of forest roads and harvesting operations. Locating roads to areas with high soil strength reduce both build and maintenance costs. Locating logging trails to high strength areas minimise soil disturbances, e.g., rutting and compaction of forest soils. GIS-based maps of soil type and soil moisture can be valuable tools to estimate soil strength. The aim of this study was to evaluate the use of soil moisture map, i.e., depth-to-water (DTW), maps and soil type maps, to estimate soil strength expressed as California bearing ratio (CBR). CBR, volumetric water content, and ground penetration depth were measured in 120 sample points, separated on three soil classes (clay-silt sediments, sand sediments, glacial till) and two soil moisture classes (wet, dry). In each point, soil samples were collected for validation of the soil type maps. There was a high conformance between soil moisture predicted by DTW maps and field measurements, but conformance of the soil type between maps and field estimates varied between soil types. For sediment soils, dry soils were consistently stronger than wet soils. Soil strength of glacial till soils was more complicated with a binary CBR distribution depending on soil stoniness. Glacial till soils possible to penetrate to 20 cm depth with the dynamic cone penetrometer had CBR values close to those for sand sediments. There is a potential to estimate soil strength from DTW and soil type maps, but these variables should preferably be complemented with other data.
Features of cultuvation allfalfa on light chestnut soils of the Volga-Don interfl uves area
Authors:   Volgograd branch of the Federal State Budgetary Scientifi c Institution “All-Russian Scientifi c Research Institute of Reclamation and Hydraulic Engineering named after A. N. Kostyakov, Russia, Volgograd, Misyuryaev V. Yu. , Dzhafarov V. V. ,   Federal State Budgetary Educational Institution of Higher Education “State University for Land Management,” Russia, Moscow
Published: November 2023

In the forage production system of the Lower Volga region, more than 60 % of feed crops are located on irrigated lands. More than 80 % of total feed production is harvested from irrigated lands. The main crops on irrigated lands are perennial grasses, among which alfalfa is the leader. Its share in the structure of sown areas is more than 65 %. The purpose of the research was to study the characteristics of cultivation alfalfa on light chestnut soils of the Volga-Don interfl uves area. The eff ective methods of basic tillage for cultivating alfalfa on light chestnut soils between the Volga and Don rivers have been identifi ed in the paper. The highest yield was formed in the variants of moldboard cultivation to a depth of 0,20–0,22 m with a depth of up to 0,38–0,40 m. A diff erentiated irrigation regime for alfalfa has been developed. The highest yield of alfalfa green mass depending on the irrigation regime was in the fi rst version of the irrigation regime 80–90–80 % lowest moisture capacity and ranged from 48,4 to 51,4 t/ha. The influence of plant growth stimulants on the effi ciency of irrigation water use during alfalfa cultivation has been established. The highest yield of alfalfa seeds of Talisman variety was formed by treating the seeds and spraying each cutting of alfalfa during the cultivation season in the budding-beginning of fl owering phase with the growth stimulator Zircon. In the variant of dump cultivation to the depth of 0,20–0,22 m with a deepening of up to 0,38–0,40 m with the irrigation regime of 80–90–80 % lowest moisture capacity, the seed yield using Zircon on average over three years of research was the highest and amounted to 0,308 t/ha.
Effectiveness of rearing Russian sturgeon with the introduction of highprotein feed concentrate Gorlinka to the diet
Authors:   Federal State Budgetary Educational Institution of Higher Education “Volgograd State Agrarian University”, Russia, Volgograd, Nikolaev S. I. , Batrakova Yu. M. ,   Federal State Budgetary Educational Institution of Higher Education “Volgograd State Agrarian University”, Russia, Volgograd
Published: November 2023

Formulating nutritionally balanced aquaculture feed is critical to ensuring that they meet the needs of aquatic animals. Fish is recognized as an essential component of a well-balanced diet as it provides healthy energy, high-quality proteins, vitamins (D, A, E and B12), essential metals (Se,Mn and Cu) and especially Omega-3, which play a vital role in human health from conception to all stages of human development, maturation and aging. The purpose of the research was to increase the effi ciency of growing Russian sturgeon by introducing high-protein feed concentrate Gorlinka into the diet partially or instead of sunfl ower cake. In order to conduct an experiment to study the eff ect of the feed concentrate Gorlinka, 4 groups of juvenile Russian sturgeon (one control and three experimental groups) of 50 animals in each were formed. The average live weight of juveniles at the beginning of the experiment was 100 g; the duration of the experiment was 175 days. In the compound feed for juvenile sturgeon of the experimental groups, the feed concentrate Gorlinka was introduced instead of sunfl ower presscake: the 1st experimental group – 50 %, the 2nd experimental group – 75 %. In the 3rd experimental group, sunfl ower presscake was completely replaced with Gorlinka feed concentrate. As a result of the research, the optimal dosage of replacing sunfl ower presscake with feed concentrate Gorlinka was established in the amount of 75 % (the 2nd experimental group) when growing Russian sturgeon, where the profi tability level was 31,69 %. The use of Gorlinka feed concentrate in aquafeed for Russian sturgeon helps to increase the economic effi ciency of its rearing by increasing productivity and reducing the cost of aquafeed. Thus, the level of profi tability in the experimental groups was higher by 2,47–6,67 abs.% compared to the control group that did not receive this concentrate.
On the question of the presence of natural reproduction in the “factory” population of the sterlet of the Oka river
Authors:   All-Russian Research Institute of Fisheries and Oceanography, Russia, Moscow, Bykov A.D. , Brazhnik S.Y. ,   All-Russian Research Institute of Fisheries and Oceanography, Russia, Moscow
Published: November 2023

The increase in the number of sterlets in the Oka in recent years has been associated with long-term re-climatization measures, the basis of which was mass releases of resilient juveniles grown in conditions of full-cycle industrial-type fish farms. Despite the high growth rate and relatively early puberty of the Oka sterlet, the completion of the naturalization process of this representative of sturgeon due to the lack of spawning behavior and replenishment of the population through natural reproduction probably does not occur. According to the results of accounting surveys of early juvenile fish with ichthyoplankton traps and net fishing gear for mature sterlet in different parts of the Oka River over a long period of observations, no signs indicating the spawning of sterlet producers of “factory” origin have been established. A complete biological analysis of a significant amount of sterlet samples showed a sharp predominance of males in the sexual structure of the population and the absence of post-spawning gonadal changes in mature fish of both sexes, characteristic of the VI–II stage of gonad maturity in May and June catches. In the structure of catches of ichthyoplankton traps for a long-term period of observations on different hydrological regime and depths of the upper and middle reaches of the Oka, despite the rich (up to 21 species per survey) species diversity and a significant volume (5.66 thousand copies) of identified early juvenile fish caught in the Ruslov stream during the rolling migrations, it was not recorded not a single instance of sterlet in the early stages of development. At the same time, the number and ichthyomass of mature sterlet in the river areas adjacent to the places of setting traps was relatively high.
PENGARUH MEKANISME COPING TERHADAP STRES REMAJA
Authors: Purnama Ni Luh Agustini , Widayanti Marcellina Rasemi , Yuliati Ignata , Kurniawaty Yuni
Published: November 2023

Teenagers are vulnerable to experiencing stress due to various factors. The study aimed to identify the influence of coping mechanisms on stress among high school teenagers. This research was conducted at Frateran Catholic High School in Surabaya in October to January 2023. This research was a prospective study where the measurement of coping mechanisms and stress was carried out twice. The research sample was 46 teenagers in high schools in Surabaya using a simple random sampling technique. Data collection on coping mechanisms used the BriefCOPE instrument, and stress measurement used the perceived stress scale (PSS10). Data were analyzed using Spearman correlation statistical analysis and linear regression tests. There is a relationship between coping mechanisms and adolescent stress in measurement 1(p= 0.000; correlation coefficient ρ= -0.37), The correlation between coping mechanisms and stress scores in measurement 2 (p=0.02; Correlation coefficient (ρ)=-0 .34) with the degree of strength of the relationship being weak and the direction of the relationship being negative, meaning that the better the coping mechanisms, the lower the adolescent stress score. The regression test between coping mechanisms at measurement 1 and stress scores at time 2 shows R square value of 0.017, meaning 1.7% of adolescent stress is determined by coping mechanisms, other factors determine the rest. In conclusion, there was a relationship between coping mechanisms and adolescent stress in measuring the degree of strength of weak relationships and the direction of negative relationships. Recommendation for further research is to explore the role of social support on adolescent stress.
Digital Resilience in the Area of Hybrid Threats: Perception of Concepts Associated with the Ukrainian Military Conflict by Generation Z in Slovakia
Authors: Spálová Lucia , Mikuláš Peter
Published: November 2023

Extreme situations, such as military conflicts, generate interest in how they are perceived by the public, which must process a broad array of media stimuli in a certain way. In this study, we discuss how the basic aspects of the current military conflict (the war in Ukraine) were perceived by young people (Generation Z) in Slovakia, with a focus on the initial part of the Russian invasion of Ukraine. We argue that the digital resistance of Slovakia’s citizens is currently low, which – in conjunction with the extremely focused activity of the disinformation scene – creates a risky environment. We use the Semantic Selection Test as a psychosemantic method on a sample of Slovak university students. One of our basic findings is the associative closeness of the concept of “Self” in Generation Z and Instagram, popular Internet memes and educational videos in connection with expertise. We also found that the recipients were subject to positive media manipulation (the Ghost of Kyiv) and were able to identify standard linguistic propaganda (negative associations of terms “war in Ukraine” and “special military operation”). The results can help us understand the perception of emergency situations by Generation Z.
Polarisation and Disinformation Content from Spanish Political Actors on Twitter/X
Authors: Said-Hung Elias , Merino-Arribas Adoración , Martínez-Torres Javier
Published: November 2023

This study analyses the role of the main Spanish political groups in the polarisation of public opinion and the promotion of the culture of disinformation through Twitter (now Platform X). The study carries out an analysis of issues associated with tweets and retweets in Spanish of the total published (n = 33,506 messages out of a total of 49,288 messages), which are contrasted with 2,730 disinformation publications identified by the two most relevant fact-checking projects in Spain (Maldita.es and Newtral.es). Based on the applied methodology, a political-communicative context is observed on Platform X characterised by a high level of self-promotion and polarisation, facilitated by the communication strategy of specific topics, applied by the actors analysed. The results show how these political actors can play an active and differentiated role in the promotion of disinformation content identified by the Maldita.es and Newtral.es data verification projects. This may contribute to the polarisation of Spanish public opinion on Platform X by delegitimising the opinions of their opponents on issues of interest to the public.
Unlocking Generation Y: Market Segmentation via Lifestyle Insights
Authors: Kopřivová Veronika , Matušínská Kateřina
Published: November 2023

One of the fundamental pillars of properly set up marketing communication is customer orientation, defining their needs and preferences and then creating their profiles. Following this fact, the aim of the study is to create subsegments of Generation Y (Millennials) in the Czech market based on identified factors in terms of lifestyle as the non-traditional segmentation descriptive variable. In order to achieve the aim of the study, AIO parameters within psychographic segmentation were used to process primary data collected by marketing research carried out in the form of a questionnaire. Overall, 999 respondents who are residents of the Czech Republic participated in this marketing research. The characteristics of Generation Y (Millennials) and the determination of the main points for external and internal marketing strategies create the basis for the comparison of subsegments based on the criteria determining the possible success of the company in this process.
Faktor Keuangan mempengaruhi Nilai Perusahaan pada Subsektor Retail di BEI
Authors: Tarigan Ketty Novelina , Arilyn Erika Jimena , Wahyudi A Sri
Published: November 2023

This study was conducted to see the effect of profitability, company growth, company size, liquidity, leverage, and dividend policy on firm value. The sample used in this study were listed companies in the wholesale sub-sector on the Indonesia Stock Exchange for the period 2007-2021 and used purposive sampling as a sampling method. With this method, there are 8 companies that meet the sampling criteria and are selected as samples with a total of 120 data. The research method used in this study is descriptive statistics and panel data regression, with the common effect model chosen. The result of this study indicate that company growth, company size, liquidity, leverage, and dividend policy do not effect the firm value. Meanwhile, profitability effects the firm value.