Identification Of Sources Research Articles

Source identification of nitrate in groundwater of an agro-pastoral ecotone in a semi-arid zone, northern China: Coupled evidences from MixSIAR model and DOM fluorescence

In the extensive agro-pastoral ecotone of northern China, groundwater is a valuable resource, but it suffers from severe nitrate pollution. However, the extent of the contributions of agricultural and pastoral activities to nitrate accumulation in the groundwater of the region remains unclear. This study aimed to identify the main sources of groundwater nitrate in Chahannur Basin, a typical agro-pastoral ecotone in the semi-arid zone of northern China, using the MixSIAR model based on dual stable isotopes and dissolved organic matter (DOM) fluorescence. The hydrochemical and isotopic results showed that the groundwater has high concentrations of nitrate (up to 208.19 mg/L) with weak denitrification, and nitrate accumulation is mainly driven by mixed input from different sources. The MixSIAR model results indicated that the largest contributors to groundwater nitrate accumulation are manure & sewage, followed by soil nitrogen, chemical fertilizers, and atmospheric deposition. According to the DOM fluorescence characteristics, the groundwater is strongly affected by livestock and poultry waste, followed by soil humic substances. Moreover, the DOM fluorescence results further supported the MixSIAR model results based on the significant correlation between the contributions of nitrate sources and the percentages of fluorescent components, jointly confirming that the main source of nitrate in groundwater is manure and sewage, followed by soil nitrogen. These findings indicate that coupled evidences from the MixSIAR model and DOM fluorescence could be applied to identify the sources of nitrate in groundwater, and this coupling can provide valuable information for local authorities to achieve sustainable groundwater management.

Analysis and measurement of magnetic noise for tesla shielding based on superconducting coils applied to SERF magnetometer

Tesla Shielding (TS) is closed superconducting coils composed of superconducting tape, designed to resist changing magnetic fields, thereby achieving magnetic shielding. TS, optically transparent, is suitable for integration with spin exchange relaxation-Free (SERF) magnetometers, thereby improving the sensitivity of SERF magnetometers. However, no prior research has been conducted on the magnetic noise of TS. Noise source identification was conducted on the superconducting tapes used in the TS. We modeled the magnetic noise of superconducting coils, analyzed the the relationship between geometric parameters and magnetic noise of coils, and proposed methods to suppress magnetic noise. Finally, we established a measurement system to measure the magnetic noise of superconducting coils. The results confirm the feasibility of the magnetic noise calculation model and the effectiveness of the methods for suppressing magnetic noise. This study can guide the design of TS, which is important for improving the sensitivity of SERF magnetometers.

Pollution Characteristics, Risk Assessment and Source Identification of Heavy Metals in Surface Sediments from the Cage Fish Farm of Poyang Lake, China

ABSTRACT With the development of cage culture, increasing heavy metals concentrations are being taken into sediments. The accumulation of heavy metals in sediments may cause long term environmental issues and pose threat to human health. Fourteen surface sediment samples were collected to assess the contamination status and potential ecological risk of heavy metals, and identify their potential sources from the cage fish farm of Poyang Lake. The concentrations of Cu, Pb, Zn, Cd, Cr, As and Ni in the sediments were measured by ICP-MS. The geo-accumulation index, enrichment factor and potential ecological risk index were implied to evaluate their pollution levels and ecological risk. The principal component analysis was used to identify their potential sources. The results showed that all of the examined heavy metals content exceeded their background values. These heavy metals (except Cd, Cr and As) presented moderately polluted level. Cu showed significant enrichment, Zn, Pb and Ni exhibited moderate enrichment, As and Cd presented minimal enrichment. Cu and Cd posed a moderate ecological risk, and the other heavy metals posed a low ecological risk. The comprehensive potential ecological risk was associated with considerable ecological risk. Cage culture, smelting, mining and agriculture activities were their primary pollution sources.

Identification of resistant sources against collar rot disease in groundnut (Arachis hypogaea) incited by Aspergillus niger

Collar rot disease incited by Aspergillus niger van Tiegham is one of the major constraint to groundnut (Arachis hypogaea L.) production in India. This fungus is ubiquitous, soil inhabitant causing severe reduction in seed germination. Infected seeds appear surrounded by black conidia and post-emergence infection occurs on collar region of plants leading to mortality of emerged seedlings at the seedling stage. Therefore, present study was carried out during rainy (kharif) seasons of 2022 and 2023 at Regional Research Station (CCS Haryana Agricultural University, Hisar, Haryana), Bawal, Haryana to identify the strategy of disease management by identification of new resistant lines which will be useful to develop introgression lines using marker-assisted backcrossing approach to improve disease resistance against soil-borne pathogens in popular groundnut varieties. A total of 245 groundnut genotypes were screened under natural epiphytotic field conditions in randomized block design (RBD) with three replications for their resistance against collar rot disease The results of the investigation indicated that 65 genotypes displayed resistant reactions among which ICGV-6285, GC-131-1, ICGV-06319, ICGV-02038, GC-100, GC-98, ICGV-02038, ICGV-7403, ICGV-7214, TG-37A and GC-133 exhibited the lowest collar rot incidence while, rest of the genotypes displayed moderately resistant, susceptible and highly susceptible reaction. Thus, these resistant genotypes could be utilized in the hybridization programme to develop high yielding groundnut variety with inbuilt resistance against collar rot of groundnut.

Identification and characterization of potential sources of waterlogging tolerance in Vigna species as revealed by physiological, biochemical and gene expression profiling

Identification and characterization of potential sources of waterlogging tolerance in Vigna species as revealed by physiological, biochemical and gene expression profiling

Research on an identification model for mine water inrush sources based on the HBA-CatBoost algorithm

Accurate and efficient identification of water inrush sources, as one of the three critical elements of mine water hazards, is crucial for mine water management. To identify the sources of mine water inrush effectively, a model named HBA-CatBoost is introduced. This model is established on the hybrid bat algorithm (HBA)-optimized category feature gradient boosting tree (CatBoost), and the shapley additive explanation (SHAP) method is employed to elucidate the model’s decision-making process. Given the prevalent occurrence of water hazards in coal seam roofs and floors in the northern Guizhou coalfield, coupled with the challenges in pinpointing water inrush sources in mines, the HBA-CatBoost model is tested at the Longfeng Coal Mine in northern Guizhou to validate its practicality. Comparative analysis with the HBA-RF, HBA-XGBoost, CatBoost, RF, and XGBoost models demonstrates that the hybrid bat algorithm significantly enhances the classification performance of the CatBoost model, resulting in improved convergence speed and classification accuracy. The HBA-CatBoost model outperforms the aforementioned models in terms of classification effectiveness, achieving accuracy, recall, precision, and F1 scores of 96.43%, 97.22%, 96.43%, and 96.61%, respectively. The SHAP method elucidates the decision mechanism of the optimal HBA-CatBoost model, highlighting the significance of sample features and bolstering the model’s credibility. These outcomes underscore the superior performance of the HBA-CatBoost model and its potential for effectively identifying water inrush sources in mines.

A multi-disciplinary approach based on chemical characterization of foreshore sediments, ecotoxicity assessment and statistical analyses for environmental monitoring of marine-coastal areas

The present work aims at providing a multi-disciplinary approach for environmental monitoring in marine-coastal areas. A monitoring campaign of 13 months (October 2022–October 2023) was carried out on sandy foreshore sediments (SFSs). The SFSs were analysed for potentially toxic elements (PTEs) and rare earth elements (REEs) content determination. In the investigated area, variable contamination trends were assessed through Friedman and Nemenyi tests. Further results also indicated the usefulness of statistical data elaboration in the identification of potential contamination sources. In fact, from Spearman test, significant positive correlations (between 0.650 and 0.981) were observed among PTEs of possible anthropogenic origin (such as Co, Cr, Cu, Pb, V, and Zn). For REEs, La and Nd showed strong correlations with Ce (0.909 and 0.920, respectively). The study also integrated luminescence inhibition (Aliivibrio fischeri), algal growth inhibition (Phaeodactylum tricornutum), and embryotoxicity assessment (Paracentrotus lividus) on sediment elutriates showing varying degrees of toxicity. Also these data were analysed through statistics in order to highlight possible correlations between contaminants and observed ecotoxicological effects on the involved bioindicators. The results outline an approach useful for more comprehensive monitoring of marine areas quality and identification of suitable environmental restoration strategies.

Fingerprinting to trace sources of suspended solids in the transport of heavy metals in urban stormwater runoff

Suspended solids are an important pollutant in urban stormwater runoff. Past studies have mainly focused on a single transport stage of pollutants, constraining source identification of suspended solids at the catchment scale. Therefore, identifying the sources of suspended solids in stormwater runoff for the formulation of effective pollution mitigation measures is an effective way to manage suspended solids pollution in receiving waters. Sediment source fingerprinting is a widely used technique to trace the sources of river sediments, which can accurately identify the source of sediment through widely used tracers. This study used six heavy metals including Cd, Cr, Ni, Cu, Zn and Pb as tracers to quantify the sources of suspended solids in stormwater runoff from urban catchments. The spatial and temporal distribution characteristics of suspended solids during stormwater transport were investigated. The study results showed that the concentration of suspended solids was the highest in road runoff and sewer flow, especially particles <44 μm. In addition, relatively large rainfall depth, high rainfall intensity and long antecedent dry periods can lead to higher concentrations of suspended solids in roof and road runoff whereas longer rainfall duration can result in more suspended solids in sewer runoff. Sediment source fingerprinting and principal component analysis confirmed that coarse (>105 μm) particles primarily originate from road deposited sediments (63.80%), while fine (<105 μm) particles primarily originate from stormwater grate sediments and soil. The outcomes derived can help to comprehensively understand the sources of suspended solids and provide guidance for the management of urban stormwater particulate pollution, as well as being a technical reference for pollutant source traceability in urban stormwater runoff.

Письмо татарского воина своей супруге

Purpose of the study: to identify sources on everyday life during the Crimean Khanate. An attempt to reconstruct individual episodes of everyday life through the study and reference to materials of the epistolary genre. Research materials: The article analyzes and translates into Russian a letter from Suleiman Effendi to his wife, presumably written during the Polish-Turkish War (1632–1634). This letter was published in 1864 in the collection of V. Velyaminov-Zernov “Materials for the history of the Crimean Khanate”, but until today it remained completely unexplored. Results and scientific novelty: The topic of everyday life during the Crimean Khanate period remains unstudied and unconsidered. In view of this circumstance, the relevance of the problem raised in the study lies in identifying and considering sources containing descriptions of individual aspects of everyday life. The work examines a letter of a private nature, which reveals several aspects from the past: the private life and relationships of people in the family, the ethics of mental behavior in society, the tactics and techniques used by the warring parties during military campaigns, the names of historical figures, the language of that time. Based on the research and identification of sources of the epistolary genre, the author comes to the conclusion that today the letters of a private nature from the period of the Crimean Khanate are very rare. An analysis of the contents of the letter suggests that there was correspondence between Suleiman Effendi and his wife, and this letter is Suleiman Effendi’s response to a letter sent earlier by his wife. It also turns out that letters from military campaigns were probably delivered by special mounted messengers.

Advanced ENF Region Classification Using UniTS-SinSpec: A Novel Approach Integrating Sinusoidal Activation Function and Spectral Attention

The electric network frequency (ENF), often referred to as the industrial heartbeat, plays a crucial role in the power system. In recent years, it has found applications in multimedia evidence identification for court proceedings and audio–visual temporal source identification. This paper introduces an ENF region classification model named UniTS-SinSpec within the UniTS framework. The model integrates the sinusoidal activation function and spectral attention mechanism while also redesigning the model framework. Training is conducted using a public dataset on the open science framework (OSF) platform, with final experimental results demonstrating that, after parameter optimization, the UniTS-SinSpec model achieves an average validation accuracy of 97.47%, surpassing current state-of-the-art and baseline models. Accurate classification can significantly aid in ENF temporal source identification. Future research will focus on expanding dataset coverage and diversity to verify the model’s generality and robustness across different regions, time spans, and data sources. Additionally, it aims to explore the extensive application potential of ENF region classification in preventing crimes such as telecommunications fraud, terrorism, and child pornography.

High density genomic surveillance and risk profiling of clinical Listeria monocytogenes subtypes in Germany

BackgroundFoodborne infections such as listeriosis caused by the bacterium Listeria monocytogenes represent a significant public health concern, particularly when outbreaks affect many individuals over prolonged time. Systematic collection of pathogen isolates from infected patients, whole genome sequencing (WGS) and phylogenetic analyses allow recognition and termination of outbreaks after source identification and risk profiling of abundant lineages.MethodsWe here present a multi-dimensional analysis of > 1800 genome sequences from clinical L. monocytogenes isolates collected in Germany between 2018 and 2021. Different WGS-based subtyping methods were used to determine the population structure with its main phylogenetic sublineages as well as for identification of disease clusters. Clinical frequencies of materno-foetal and brain infections and in vitro infection experiments were used for risk profiling of the most abundant sublineages. These sublineages and large disease clusters were further characterised in terms of their genetic and epidemiological properties.ResultsThe collected isolates covered 62% of all notified cases and belonged to 188 infection clusters. Forty-two percent of these clusters were active for > 12 months, 60% generated cases cross-regionally, including 11 multinational clusters. Thirty-seven percent of the clusters were caused by sequence type (ST) ST6, ST8 and ST1 clones. ST1 was identified as hyper- and ST8, ST14, ST29 as well as ST155 as hypovirulent, while ST6 had average virulence potential. Inactivating mutations were found in several virulence and house-keeping genes, particularly in hypovirulent STs.ConclusionsOur work presents an in-depth analysis of the genomic characteristics of L. monocytogenes isolates that cause disease in Germany. It supports prioritisation of disease clusters for epidemiological investigations and reinforces the need to analyse the mechanisms underlying hyper- and hypovirulence.

Mapping Ecological Security Patterns Based on Ecosystem Service Valuation in the Qinling-Daba Mountain Area, China: A Multi-Scenario Study for Development and Conservation Tradeoffs

When focusing on biodiversity maintenance, ecological security pattern (ESP) planning gradually becomes a multi-objective planning strategy for sustainable development; wildlife conservation and ecosystem health maintenance should be balanced with local economic development and people’s livelihood enhancement goals. This study focuses on ESP mapping in the Qinling-Daba Mountain area, which is an ecologically significant and socioeconomically underdeveloped area. The tradeoff between conservation and development is made by varying the area of ecological sources and incorporating ecosystem service tradeoffs into ecological source identification through multi-scenario designation. ESPs under six scenarios were generated based on the minimum resistance model, and the important ecological corridors and strategic points in each scenario were identified and compared. The results show the following: (1) The scenario that sets around 30 percent of the study area as ecological sources maintains the integrity of natural ecosystems and leaves space for food and material supply to residents. (2) In this scenario, the ecological sources are connected by 60 corridors that cross 137 townships with high population densities (&gt;100 people/km2) and intersect with major traffic lines at 71 points. Engineering, management, or education strategies must be taken in these townships or intersections to avoid human–wildlife conflicts. (3) The study area needs to construct both short (north–south) corridors linking proximate ecological sources for species’ daily movement and long (west–east) corridors connecting large and distant sources for species’ seasonal migration and gene flow. (4) The multi-scenario approach turns out to be an effective strategy for ESP planning with considerations for development–conservation tradeoffs.

Box Constraints and Weighted Sparsity Regularization for Identifying Sources in Elliptic PDEs

We explore the possibility for using boundary data to identify sources in elliptic PDEs. Even though the associated forward operator has a large null space, it turns out that box constraints, combined with weighted sparsity regularization, can enable rather accurate recovery of sources with constant magnitude/strength. In addition, for sources with varying strength, the support of the inverse solution will be a subset of the support of the true source. We present both an analysis of the problem and a series of numerical experiments. Our work only addresses discretized problems. The reason for introducing the weighting procedure is that standard (unweighted) sparsity regularization fails to provide adequate results for the source identification task considered in this paper. This investigation is also motivated by applications, e.g. recovering mass distributions from measurements of gravitational fields and inverse scattering. We develop the methodology and the analysis in terms of Euclidean spaces, and our results can therefore be applied to many problems. For example, the results are equally applicable to models involving the screened Poisson equation as to models using the Helmholtz equation, with both large and small wave numbers.

Chemical Fingerprinting, PAHs Characterization and Ecological Risks of Carcinogenic PAHs in Surficial Sediments of Egi Crude Oil Producing Communities, Niger-Delta, Nigeria

In order to do PAHs rings analysis, its source identification, extent to which cPAHs present and what kind of ecological risk they pose, the surface sediments from various freshwaters in the Egi crude oil producing cities in the Niger Delta, Nigeria were analyzed. Sediments collected from the research areas for PAHs loadings (in mg/kg dry weight) ranged from 0.020 to 1.790, 0.050 to 1.880, and 0.020 to 1.640, respectively for Obite, Obagi, and Ibewa cluster areas, as measured by gas chromatography-mass spectrometer. In these clusters, the respective average concentration of the three dominant carcinogenic PAHs were Indeno(1,2,3-cd)pyrene (1.170.0mg/kg), Dibenz[a,h]anthrancene (0.870.0 mg/kg), and Dibenz[a,h]anthrancene (1.3670 mg/kg) for Ibewa, Obagi and Obite cluster areas. The findings showed that dominant PAHs rings are of high molecular weight (HMW) PAHs in these sediments are, 5 member rings, which are benzo(b)fluoranthene, Benzo(k)fluoranthene, and Benzo(a)pyrène, and 6-member ring which are, Indeno(1,2,3-cd)pyrene, Dibenz[a,h]anthrancene, and Benzo[ghi] perylene, respectively. Their fingerprints points majorly to pyrogenic sources, combustion of coal, biomass, petroleum, and other related anthropogenic petroleum activities as the primary source of PAHs in the environment. Notably, the RQNCs and RQMPCs for single PAHs molecule are both less than 1, it means the contamination it generates is considered of low ecological risk. Again, the research area experiences frequent flooding, it is believed that this contributes to the low ecological risk of PAHs chemical pollution. Consequently, the area is deemed to be quite safe.

8014 Cushing’s Syndrome: Two Sides of The Spectrum

Abstract Disclosure: M. Aguilera: None. A. Vu: None. J. Shakil: None. R. Al-Ward: None. Introduction: Cushing’s syndrome (CS) is a rare condition with an annual incidence of 2-8 per million. Endogenous CS is mainly due to corticotroph adenoma of the pituitary followed by excessive glucocorticoid production from adrenal and ectopic sources. CS has significant morbidity and mortality hence the need for timely diagnosis. The varied presentations often pose great challenges in identifying the source of hypercortisolism. We present two unusual cases of CS with distinct clinical presentations and atypical laboratory profiles. Case 1: 25-year-old male with no medical history presented with 9 months of facial puffiness, weight gain, fluid retention, hypertension and blurred vision. Physical examination revealed round facies, bilateral supraclavicular fat pads and wide abdominal striae. Laboratory workup showed markedly elevated ACTH 537 pg/mL [7.2-63 pg/mL], serum cortisol 8.5 ug/dL [6.2-19.4 ug/dl], 24-hour urine free cortisol (UFC) 30 [5-62 ug/24H] and normal late-night salivary cortisol (LNSC). Repeat workup a month later showed serum cortisol of 56ug/dL, ACTH 874 pg/dL, 24-hour UFC of 11880ug/24H and elevated LNSC. Pituitary MRI showed a large heterogenous 3.1 cm partially cystic sellar mass with suprasellar extension. Due to significantly elevated ACTH and short duration of symptoms, we suspected an ectopic source. Due to initial negative testing, except for high ACTH level, a silent corticotroph adenoma was also considered. The patient underwent transsphenoidal resection resulting in significant decrease of cortisol and ACTH postoperatively. Pathology showed a corticotroph adenoma with Ki-67 index of &amp;lt;1%. Case 2: 47-year-old woman with medical history of obesity, polycystic ovary syndrome and a stable 1 cm lung nodule since 2020, presented with fluid retention, worsening acne and resistant hypertension over a 1-year period. She required hospitalization for hypertensive emergency and hypokalemia. Laboratory data showed morning serum cortisol 28 ug/dL, ACTH of 90.1 pg/mL, 24-hour UFC 346 ug/24H, elevated LNSC on two occasions and cortisol 24.3 ug/dl after a 1mg dexamethasone suppression. MRI did not show a pituitary mass. PET dotatate scan revealed a tracer avid 1 cm right upper lobe pulmonary nodule. She underwent a right upper lobe lobectomy, resulting in a significant decrease in cortisol and ACTH levels on postoperative day 1. Pathology confirmed a typical carcinoid tumor. Discussion: High ACTH levels and a short symptom duration often point to ectopic production, paraneoplastic syndromes or corticotroph carcinomas. Cushing's disease typically exhibits mildly elevated ACTH levels, but our cases deviate from this norm, complicating source identification. This atypical presentation highlights the complexity of Cushing's syndrome, challenging conventional diagnostic paradigms. Presentation: 6/1/2024

Consideration and case study using a time-difference-of-arrival directional device for occupational noise measurement

To protect worker's hearing in noisy workplaces, noise levels are measured periodically, and noise sources are located based on the results of recordings or video cameras. If the noise level is above a certain level, noise abatement measures are taken, or workers are suggested to wear hearing protection. Measuring the noise level can be done simply by placing a sound level meter on the floor, but finding the noise abatement is a time-consuming task. It is necessary to listen to the recordings one by one or review the video to find the noise abatement. We believe that a simple method of estimating noise abatement is very useful, since some noisy workplaces do not allow recordings or video cameras for privacy and confidentiality reasons. In this paper, noise source identification using a time-difference-of-arrival directional device in an indoor environment is examined. The results are analyzed in the context of room properties such as reverberation time, dimensions, and device localization. The paper also reports on practical use-cases in actual sites.

Comparative analysis of CNN and TNN models in environmental noise source identification

This paper presents a focused examination of environmental noise, an issue of relevance due to its implications for human health and well-being, compliant with ISO 1996-2:2017 standards. Moving beyond the traditional methodologies that primarily rely on level exceedance, our study integrates advanced machine learning techniques to address the challenges in noise source identification. With the advent of IoT Noise Monitoring Terminals, the conventional manual auditory analysis methods have become less feasible. Our research explores the application of convolutional neural networks (CNNs), a standard in environmental noise analysis, and assesses the emerging utility of Transformer Neural Network (TNN) models in this domain. The aim is to conduct an objective comparison of these models, applying them to identical datasets to determine their effectiveness in identifying noise sources. Through this analysis, the study seeks to contribute to the field of environmental acoustics by offering insights into the comparative strengths and limitations of CNN and TNN models.

Spatial variability, source identification, and partitioning of groundwater constituents in a typical lakeside plain on Yungui Plateau

The fragile ecological balance of lakeside plains on plateau makes groundwater hydrochemical composition highly susceptible to human disturbances. This research investigates a typical plain on Yunnan Plateau to quantitatively identify the potential sources of groundwater pollution in lakeside plains on plateau by combining receptor models with risk assessment models. Receptor models show there are three potential pollution sources for groundwater including water-rock interactions, agricultural pollution, and domestic sewage/manure discharge. Groundwater hydrochemical composition is predominantly shaped by natural water-rock interactions, accounting for an average of 50.12 % of the influence. This is followed by agricultural non-point source pollution, which contributes 10.79 %, and the discharge of domestic sewage and manure, which accounts for 10.61 %. Groundwater in the current plain could pose a minor non-carcinogenic risk for long-term drinking, with the total hazard index (THI) for adults varying between 0.015 and 1.089, and for children between 0.024 and 1.737. Notably, 4.35 % of groundwater samples have a THI exceeding the safe threshold of 1. NO3- (72 %) is the primary contributor to non-carcinogenic risks, accounting for 72 %, trailed by Mn (13 %), NH4+ (9 %), Fe (6 %) and NO2- (1 %). The non-carcinogenic risks are predominantly attributed to agricultural non-point source pollution (71.6 %) and the discharge of domestic sewage and manure (26.9 %). A conceptual model has been developed to encapsulate the dynamics of groundwater quality formation in lakeside plains on plateau. This research will aid residents in safeguarding against groundwater contamination and enhancing agricultural practices in present plain and similar lakeside plain worldwide.

A Credibility Monitoring Approach and Software Monitoring System for VHF Data Exchange System Data Link Based on a Combined Detection Method

Due to VDES’s higher data transmission speed and complex communication protocols, vulnerabilities within its data link infrastructure are more pronounced. To ensure the reliability of VDES data transmission, this manuscript proposes a credibility monitoring approach based on the combined detection method of radio interference detection and spoofing source identification and localization, focusing on key data link vulnerabilities outlined in the IALA G1181 VDES VDL Integrity Guide. Automated monitoring is achieved through VDES data link monitoring software (VDES(AIS 2.0)), which is based on a three-tier architecture and a Client/Server (C/S) model. The software validates monitoring techniques and software against various interference scenarios. Visualization of monitoring results, alarm notifications, and relevant data through the front-end interface enhances understanding of VDES data link credibility. This framework supports effective surveillance and detection of vulnerabilities, such as radio interference and spoofing sources.

Microbial source tracking and identification of fecal contamination patterns in saltwater estuaries between base- and storm-flow events using dual genome-based approaches

Fecal contamination from natural and anthropogenic sources poses significant threats to saltwater estuaries, particularly after storms or heavy rainfall. Monitoring fecal contamination is essential for protecting these vulnerable ecosystems having important ecological and economic values. In this study, we investigated the abundance, sources, and potential causes of fecal contamination at three marine and seven freshwater stations across Vaughn Bay (WA, USA), a shellfish growing district, during base- and storm-flow events. Additionally, we evaluated the performance of fecal indicator bacteria (FIB) quantification, optical brightener assessment, and qPCR analysis for fecal contamination quantification. We compared the effectiveness of qPCR-based microbial source tracking (MST), which targeted a broad range of hosts including, such as humans, birds, cows, horses, ruminants, dogs, and pigs, with sequencing-based MST in identifying fecal contamination sources. Both MST analysis approaches identified birds and humans as the primary sources of fecal contamination. For marine water stations, freshwater creeks VBU001, VBU002, and VB047, along with drain VB007, were identified as the main sources of human-derived fecal contamination in Vaughn Bay, based on Kendall's tau analysis (τ: 0.58–0.97). This information indicates that the septic systems in the catchment areas of these creeks and drains require further investigation to achieve effective fecal contamination control. Optical brightener, FIB enumeration and qPCR quantification results were generally higher during storm-flow events, although they showed poor correlation with each other (Pearson r < 0.40), likely due to physiological and phylogenetic differences among the target organisms of these methods. However, the sequencing-based method faces challenges in precise quantitative identification of differences in fecal contamination between base- and storm-flow events. Due to its high-throughput and cost-effectiveness, we recommend using sequencing-based analysis for large-scale identification of the primary sources of fecal contamination in water environments, followed by targeted qPCR quantification of MST markers for more precise assessments.