Effective wastewater management is crucial in regions experiencing water scarcity and environmental stressors, such as pollution and climate change. Optimizing treatment processes is essential for achieving environmental sustainability. This study aims to highlight the importance of effective wastewater management strategies, particularly in regions facing water scarcity. Our objective was to identify key factors influencing the treatment process. Therefore, we evaluated associations between physicochemical parameters using multivariate statistical methods, including Principal Component Analysis (PCA) and Hierarchical Ascendant Classification (HAC). Our findings categorize the monthly water samples into three distinct groups based on levels of organic pollution: the first group (July, August, and September) is characterized by high oxygenation levels and significantly low organic pollution, indicating optimal system operation. The second group (April, October, November, and December) exhibits low oxygenation and low organic pollution, promoting sludge settling and pollutant reduction. The third group (January, February, March, May, and June) shows significantly high organic pollution and low oxygenation, which corresponds to unfavorable environmental conditions. Our study demonstrates the effectiveness of multivariate statistical methods in optimizing wastewater treatment processes, providing crucial insights for environmental sustainability and water resource management.

Urbanization and economic development cause water pollution in the inner-city canals and rivers globally. Bung Xang canal in Can Tho city of Vietnam is facing problems with water pollution due to the lack of centralized wastewater treatment plants and low public awareness on environmental protection. Perception of local residents was collected using structured questionnaires including both qualitative and quantitative information. Regression analysis was employed to evaluate the factors affecting the decision of respondents on the willingness to pay (WTP) to improve water quality in the Bung Xang canal. Knowledge about the environmental protection fee for domestic wastewater (10% of the VAT-excluded from the selling price of 1 m3 of tap water purchased), age of the respondents and their education levels affected the WTP positively, while respondents\' perception on water quality affected the WTP negatively. There was 58.33% of the respondents showed the WTP for improved water quality in the canal. They agreed to pay a small fee of VND 10,000 to 15,000 (equivalent to USD 0.42-0.63)/month (1 US$= 23,700 VND). The result indicates that environmental education is the only way forward for a successful sustainable urban city.

UNASSIGNED: Factors associated with the appropriateness of antibiotic prescribing in primary care have been poorly explored. In particular, the impact of computerised decision-support systems (CDSS) remains unknown.
UNASSIGNED: We aim at investigating the uptake of CDSS and its association with physician characteristics and professional activity.
UNASSIGNED: Since May 2022, users of a CDSS for antibiotic prescribing in primary care in France have been invited, when registering, to complete three case vignettes assessing clinical situations frequently encountered in general practice and identified as at risk of antibiotic misuse. Appropriateness of antibiotic prescribing was defined as the rate of answers in line with the current guidelines, computed by individuals and by specific questions. Physician\'s characteristics associated with individual appropriate antibiotic prescribing (< 50%, 50-75% and > 75% appropriateness) were identified by multivariate ordinal logistic regression.
UNASSIGNED: In June 2023, 60,067 physicians had registered on the CDSS. Among the 13,851 physicians who answered all case vignettes, the median individual appropriateness level of antibiotic prescribing was 77.8% [Interquartile range, 66.7%-88.9%], and was < 50% for 1,353 physicians (10%). In the multivariate analysis, physicians\' characteristics associated with appropriateness were prior use of the CDSS (OR = 1.71, 95% CI 1.56-1.87), being a general practitioner vs. other specialist (OR = 1.34, 95% CI 1.20-1.49), working in primary care (OR = 1.14, 95% CI 1.02-1.27), mentoring students (OR = 1.12, 95% CI 1.04-1.21) age (OR = 0.69 per 10 years increase, 95% CI 0.67-0.71).
UNASSIGNED: Individual appropriateness for antibiotic prescribing was high among CDSS users, with a higher rate in young general practitioners, previously using the system. CDSS could improve antibiotic prescribing in primary care.
Individual appropriateness for antibiotic prescribing is high among CDSS users.CDSS use could passively improve antibiotic prescribing in primary care.Factors associated with appropriateness for antibiotic prescribing for primary care diseases are: prior use of CDSS, general practice speciality vs. other specialities, younger age and mentoring of students.

Determining the origin and pathways of contaminants in the natural environment is key to informing any mitigation process. The mass magnetic susceptibility of soils allows a rapid method to measure the concentration of magnetic minerals, derived from anthropogenic activities such as mining or industrial processes, i.e., smelting metals (technogenic origin), or from the local bedrock (of geogenic origin). This is especially effective when combined with rapid geochemical analyses of soils. The use of multivariate analysis (MVA) elucidates complex multiple-component relationships between soil geochemistry and magnetic susceptibility. In the case of soil mining sites, X-ray fluorescence (XRF) spectroscopic data of soils contaminated by mine waste shows statistically significant relationships between magnetic susceptibility and some base metal species (e.g., Fe, Pb, Zn, etc.). Here, we show how qualitative and quantitative MVA methodologies can be used to assess soil contamination pathways using mass magnetic susceptibility and XRF spectra of soils near abandoned coal and W/Sn mines (NW Portugal). Principal component analysis (PCA) showed how the first two primary components (PC-1 + PC-2) explained 94% of the sample variability, grouped them according to their geochemistry and magnetic susceptibility in to geogenic and technogenic groups. Regression analyses showed a strong positive correlation (R2 > 0.95) between soil geochemistry and magnetic properties at the local scale. These parameters provided an insight into the multi-element variables that control magnetic susceptibility and indicated the possibility of efficient assessment of potentially contaminated sites through mass-specific soil magnetism.

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BACKGROUND: A treatment\'s overall favorable benefit-risk profile does not imply that every individual patient will benefit from the treatment.
OBJECTIVE: To describe a statistical methodology for quantifying the benefit-risk trade-off in individual patients.
METHODS: The method requires a large randomized controlled trial containing a primary efficacy outcome and a primary safety outcome, for instance, the Thrombin Receptor Antagonist in Secondary Prevention of Atherothrombotic Ischemic Events-Thrombolysis in Myocardial Infarction 50 placebo-controlled trial of vorapaxar in 17 779 patients following myocardial infarction. Multivariate regression models predict each individual patient\'s risk of ischemic events (benefit) and major bleeding events (harm) based on their profile. Hence, each patient\'s predicted benefit from vorapaxar (reduction in ischemic events) and predicted risk (increase in bleeding events) were estimated. The relative importance of ischemic and bleeding events based on links to all-cause mortality was quantified, although the limitations of such weightings are noted.
RESULTS: Overall results demonstrated both clear benefit and harm from vorapaxar. Substantial interindividual variation in both benefit and risk facilitated distinguishing patients with a favorable benefit-risk trade-off from those who did not. Such findings were applied to recommend vorapaxar in as many as 98.3% of patients in which a favorable mortality-weighted benefit-risk trade-off was present, in 77.2% of patients with ischemic benefit 20% greater than bleeding risk, or in as few as 45.5% of patients if an annual decrease in ischemic risk of ≥0.5% was also required.
CONCLUSIONS: While overall randomized controlled trials of treatment benefit vs risk are valuable, models determining each individual patient\'s estimated absolute benefit and risk provide more useful insight regarding patient-specific benefit-risk trade-offs to better enable personalized therapeutic decision-making.

This study performed toxicity assays with microalgae, microcrustaceans, and fish as well as evaluated biochemical and behavioral biomarkers in fish and microcrustaceans to assess the quality of the surface water of Mirim Lagoon, which belongs to one of the largest hydrographic basins in the world, located in southern Brazil. Three distinct sampling periods were chosen (January, March, and June 2022) based on the rice plantation dynamics which is the main activity surrounding the lagoon. In January, the plantation is irrigated; in March, the water is drained into the Mirim Lagoon, and July is the off-season. Concerning toxicity tests, there was significant inhibition in microalgae growth when exposed to water collected in March, but no mortality was observed for Ceriodaphia dubia, Daphnia magna, and Danio rerio. Regarding biomarkers, behavioral variables contributed more to the higher values of the Integrated Biomarker Response (IBR) index for both D. magna and D. rerio, in March. The Redundancy Analysis (RDA) indicated a correlation between the biomarkers for both organisms and abiotic parameters, mainly nutrients (total phosphorus and total nitrogen), thermotolerant coliforms, total solids, and turbidity. Spatially, there was no difference during monitoring, but the most significant ecotoxicological effects were observed in March. Multivariate analysis and the IBR index proved to be useful tools for monitoring of water bodies such as Mirim Lagoon.

In Japan, use of a report for providing information from pharmacies to medical institutions called as \"tracing report (TR)\" is not widespread especially in the field of cancer chemotherapy. Identification of the factors related to submission of TRs could enhance the necessity of TRs. The purpose of this study is to clarify the factors related to submission of TRs regarding cancer chemotherapy through a questionnaire survey. A questionnaire survey was conducted at the live web-based seminar regarding cancer chemotherapy held for pharmacists in January 2023. After the questionnaire survey, the participants were divided into those who had submitted at least one TR regarding cancer chemotherapy within one month before the seminar (TR group) and those who had not (non-TR group). The multivariate analysis was conducted to identify factors related to submission of TRs regarding cancer chemotherapy. Of 118 participants, the responses from 93 pharmacy pharmacists involved in dispensing drugs who agreed to participate in this study and fulfilled all questionnaire were analyzed. TR group included 21 participants and non-TR group included 72. As a result of multivariate analysis, \"Years of experience in counseling and following-up with patients undergoing cancer chemotherapy (odds ratio: 4.81, p=0.02)\" and \"Types of workplaces (odds ratio: 3.79, p=0.02)\" significantly increased the incidence of submission of TRs regarding cancer chemotherapy. It was revealed that experience of intervention in cancer chemotherapy cases and an environment in which prescriptions for cancer chemotherapy can be handled on a daily basis are important for submission of TRs regarding cancer chemotherapy.

Lake Nokoué, a major component of the hydrographic system of the Ouémé delta, is the largest lagoon-estuarine ecosystem in Benin. Recent studies have shown that benthic processes would actively participate in the maintenance of the eutrophication and biogeochemical cycle of this ecosystem. In order to understand the implication of the bottom on the quality of the waters of the lake, a monthly follow-up of ten (10) parameters of quality of the waters of the bottom was undertaken from July 2020 to December 2021 on a network of nineteen (19) stations distributed on the whole lake. Univariate and multivariate analysis techniques were used to assess the spatial and temporal dynamics of these waters. The Kruskal-Wallis test, PCA, correlation analysis and discriminant analysis all showed a very marked influence of the hydrological regime on the concentration of nutrients compared to the influence of anthropogenic activities around the lake and an influence of climatic conditions on internal processes. Indeed, water inflows from the Ouémé watershed are the main contributors of phosphorus in the lake while benthic processes are the most important contributors of nitrogen. Cluster analysis defined three significantly different areas in Lake Nokoué: the channel, the centre of the lake and the river mouth. A single station in each cluster could be used for a spatial assessment of water quality over the entire lake.

Many physicochemical and biological monitored parameters must be taken into consideration to fully evaluate the surface water environmental condition. However, there are situations where a simple and rapid assessment of the poor water quality situations is critically important. This work presents a universal methodology for monitoring of many parameters simultaneously and early detection out-of-control samples in a real-time mode. The approach uses multivariate statistical quality control chart based on Principal Component Analysis (PCA) model with two well-known measures of abnormal behaviour in a process or system: Hoteling\'s T2 statistics and Q-statistic. The proposed TQ_PCA quality index provides on-line assessment of the water sample quality, with no specific knowledge and assumptions about control limits for monitored parameters required. A water sample is assessed through the simple control chart using the PCA model established for training/reference samples. The power of the proposed index has been tested using water quality data from the Oder River, including the time of the largest ecological disaster in recent European river history. The proposed index showed excellent analysis performance for physicochemical water quality dataset from Polish stations and physicochemical and biological water quality dataset from German/Frankfurt station, confirming earlier reports. There were consecutive number of alarms reported by the statistical index, a month prior to the disaster when there were no evident changes in the individual parameters. The method presented in this study demonstrated capability of assessment of the major water quality parameters, whose changes preempt the uncommon event. The presented TQ_PCA index could be easily extended to any research involving a large dataset of monitoring parameters from any industrial chemical process.