Unmonitored Sources Research Articles

The significance of information variables in polydrug use by adolescents: insights from a cross-sectional study in Tarragona (Spain).

Substance use, especially among adolescents, is a significant public health concern, with profound implications for physical and psychological development. This study aimed to evaluate the quantity and sources of information available to adolescents regarding polydrug use. A cross-sectional survey was conducted in Tarragona involving adolescents with an average age of 16.44 years. This study assessed the number of substances used (alcohol, cigarettes, and cannabis) in the past month, along with information sources related to substance use. Monitored sources (e.g., schools, parents, and mass media) and unmonitored sources (e.g., peers, siblings, internet) were distinguished. In addition, four individual and four environmental control variables were considered. Multinomial logistic regression analysis revealed that incorporating variables related to adolescents' substance use information and its sources enhanced the explanatory model, surpassing control variables. The degree of information about substance use did not significantly explain consumption patterns, but the number of information sources, both monitored and unmonitored, did. The unmonitored sources were associated with increased polydrug use. Conversely, greater reliance on supervised sources for information was linked to reduced single-substance and polydrug use. This protective effect increased with an increase in the number of substances used. In conclusion, information obtained from monitored sources acts as a deterrent to substance consumption, consistent with findings suggesting that greater health literacy among adolescents discourages substance use. Conversely, this study suggests that information from more informal sources may encourage heavier polydrug use, aligning with reports indicating that adolescents with a more comprehensive understanding of substance use consequences tend to engage in heavier drug use.

Predicting nitrate exposure from groundwater wells using machine learning and meteorological conditions

AbstractPrivate groundwater wells can be unmonitored sources of contaminated water that can harm human health. Developing models that predict exposure could allow residents to take action to reduce risk. Machine learning models have been successful in predicting nitrate contamination using geospatial information such as proximity to nitrate sources, but previous models have not considered meteorological factors that change temporally. In this study, we test random forest (regression and classification) and linear regression models to predict nitrate contamination using rainfall, temperature, and readily available soil parameters. We trained and tested models for (1) all of North Carolina, (2) each geographic region in North Carolina, (3) a three‐county region with a high density of animal agriculture, and (4) a three‐county region with a low density of animal agriculture. All regression models had poor predictive performance (R2 < 0.09). The random forest classification model for the coastal plain showed fair agreement (Cohen's κ = 0.23) when trying to predict whether contamination occurred. All other classification models had slight or poor predictive performance. Our results show that temporal changes in rainfall and temperature, or in combination with soil data, are not enough to predict nitrate contamination in most areas of North Carolina. The low level of contamination (<25%) measured during the study could have contributed to the poor performance of the models.

Understanding the causes, effects, and remediation of salinity in irrigated fields: A review

To boost agricultural production, irrigation will turn out to be more reliant on inadequately described and virtually unmonitored sources of irrigation water supply. Amplified use of irrigation water has resulted in degradation of water and soil quality in numerous areas. The objective of this review is highlighting the causes, effects, and remediation of salinity in irrigated fields. The study analysed some major ions affecting the quality of irrigation water. Precisely, elements including boron, chloride, and nitrogen are harmful to crops. Consequently, it is imperative to detect their origin and consequences. Likewise, there is a need for understanding how they can be removed from irrigation waters. Continuous water quality analysis using chemical indices such as sodium adsorption ratio, sodium percent, residual sodium carbonate, magnesium hazard and permeability index in irrigation water analysis is recommended. The review also highlights the crop tolerance in saline conditions and tolerance limits of individual crops to salinity. Salinity should be monitored for improved irrigation scheme performance. This has necessitated the application of salinity management techniques in irrigation water.

CONCEPTUAL MODEL DEPICTING RISK FACTORS INFLUENZING CLOUD DATA SECURITY

Cloud Platform has the data stored in a remote server and accessed with the help of services provided by cloud service providers. The primary objective is to provide data security due to the confidentiality of data transmitted to the remote server, over an unmonitored and multi-tenancy channel (internet). The major components of cloud platform are application, service, runtime cloud, storage and infrastructure. This is a conceptual paper trying to explain the risk factors to be deemed in a cloud environment. The benefits include scalability, availability, reliability, flexibility, increased collaboration, competitive edge, sustainability, reduced proportional cost. Risk factors influencing the data security and Integrity are identified up to three level of sub-constructs.. All the risk factors including hackers, mishandling of passwords, risk of data accessed from public /unmonitored sources, security in communication channels, intentional and unintentional data security threats created due to human interference are included in the scope of this paper. In this paper, the identification of sub factors of cloud data security risk components is achieved. The futuristics scope of this paper is to identify early risk prediction and mitigation strategies to all the identified risk factors related to data security by implementing SEM methodology.

Understanding the causes, effects, and remediation of salinity in irrigated fields: A review

To boost agricultural production, irrigation will turn out to be more reliant on inadequately described and virtually unmonitored sources of irrigation water supply. Amplified use of irrigation water has resulted in degradation of water and soil quality in numerous areas. The objective of this review is highlighting the causes, effects, and remediation of salinity in irrigated fields. The study analysed some major ions affecting the quality of irrigation water. Precisely, elements including boron, chloride, and nitrogen are harmful to crops. Consequently, it is imperative to detect their origin and consequences. Likewise, there is a need for understanding how they can be removed from irrigation waters. Continuous water quality analysis using chemical indices such as sodium adsorption ratio, sodium percent, residual sodium carbonate, magnesium hazard and permeability index in irrigation water analysis is recommended. The review also highlights the crop tolerance in saline conditions and tolerance limits of individual crops to salinity. Salinity should be monitored for improved irrigation scheme performance. This has necessitated the application of salinity management techniques in irrigation water.

Irrigation Water Quality—A Contemporary Perspective

In the race to enhance agricultural productivity, irrigation will become more dependent on poorly characterized and virtually unmonitored sources of water. Increased use of irrigation water has led to impaired water and soil quality in many areas. Historically, soil salinization and reduced crop productivity have been the primary focus of irrigation water quality. Recently, there is increasing evidence for the occurrence of geogenic contaminants in water. The appearance of trace elements and an increase in the use of wastewater has highlighted the vulnerability and complexities of the composition of irrigation water and its role in ensuring proper crop growth, and long-term food quality. Analytical capabilities of measuring vanishingly small concentrations of biologically-active organic contaminants, including steroid hormones, plasticizers, pharmaceuticals, and personal care products, in a variety of irrigation water sources provide the means to evaluate uptake and occurrence in crops but do not resolve questions related to food safety or human health effects. Natural and synthetic nanoparticles are now known to occur in many water sources, potentially altering plant growth and food standard. The rapidly changing quality of irrigation water urgently needs closer attention to understand and predict long-term effects on soils and food crops in an increasingly fresh-water stressed world.

Metals in select beers commercially available in the US: Unmonitored sources of concerning exposure

Stemming from the need to inform US consumers about the potential health hazards originating from regulatory deficiencies and an inadequate capacity to conduct the complete screening of beverage products entering the US, this study aimed to answer two questions: (1) how do concerning metal concentrations of beers imported to the US market compare to those in US produced beers; and (2) do imported and domestic beers exhibit concerning metal concentrations below the existing US primary drinking water standards. To address this aim: (1) beers manufactured worldwide, which were commercially available on the US market were obtained; (2) the concentration of concerning metals in the beers was analyzed; and (3) data were examined and correlated to explore any US maximum contaminant level (MCL) exceedances and determine whether geographic or grain-related trends exist. The results showed that there are no significant differences between the concerning metal concentrations of imported vs. domestic beers in the US market. Some specific heavy metals, like arsenic, are present in both imported and domestic beers in concentrations that exceed the national primary drinking water standards MCLs. Although water quality may be a factor contributing to the elevated concentrations of concerning metals in beers, it is more likely that the grain ingredients are greater contributors to the observed trends.

Oak Ridge Reservation Environmental Protection Rad Neshaps Radionuclide Inventory Web Database and Rad Neshaps Source and Dose Database.

The U.S. Environmental Protection Agency promulgated national emission standards for emissions of radionuclides other than radon from US Department of Energy facilities in Chapter 40 of the Code of Federal Regulations (CFR) 61, Subpart H. This regulatory standard limits the annual effective dose that any member of the public can receive from Department of Energy facilities to 0.1 mSv. As defined in the preamble of the final rule, all of the facilities on the Oak Ridge Reservation, i.e., the Y-12 National Security Complex, Oak Ridge National Laboratory, East Tennessee Technology Park, and any other U.S. Department of Energy operations on Oak Ridge Reservation, combined, must meet the annual dose limit of 0.1 mSv. At Oak Ridge National Laboratory, there are monitored sources and numerous unmonitored sources. To maintain radiological source and inventory information for these unmonitored sources, e.g., laboratory hoods, equipment exhausts, and room exhausts not currently venting to monitored stacks on the Oak Ridge National Laboratory campus, the Environmental Protection Rad NESHAPs Inventory Web Database was developed. This database is updated annually and is used to compile emissions data for the annual Radionuclide National Emission Standards for Hazardous Air Pollutants (Rad NESHAPs) report required by 40 CFR 61.94. It also provides supporting documentation for facility compliance audits. In addition, a Rad NESHAPs source and dose database was developed to import the source and dose summary data from Clean Air Act Assessment Package-1988 computer model files. This database provides Oak Ridge Reservation and facility-specific source inventory; doses associated with each source and facility; and total doses for the Oak Ridge Reservation dose.