Effective Measures Research Articles

An intelligent interval forecasting system based on fuzzy time series and error distribution characteristics for air quality index

Due to the emergency environment pollution problems, it is imperative to understand the air quality and take effective measures for environmental governance. As a representative measure, the air quality index (AQI) is a single conceptual index value simplified by the concentrations of several routinely monitored air pollutants according to the proportion of various components in the air. With the gradual enhancement of awareness of environmental protection, air quality index forecasting is a key point of environment management. However, most of the traditional forecasting methods ignore the fuzziness of original data itself and the uncertainty of forecasting results which causes the unsatisfactory results. Thus, an innovative forecasting system combining data preprocessing technique, kernel fuzzy c-means (KFCM) clustering algorithm and fuzzy time series is successfully developed for air quality index forecasting. Concretely, the fuzzy time series that handle the fuzzy set is used for the main forecasting process. Then the complete ensemble empirical mode decomposition and KFCM are respectively developed for data denoising and interval partition. Furthermore, the interval forecasting method based on error distribution is developed to measure the forecasting uncertainty. Finally, the experimental simulation and evaluation system verify the great performance of proposed forecasting system and the promising applicability in a practical environment early warning system.

Effective splitting of invariant measures for a stochastic reaction diffusion equation with multiplicative noise

This work is concerned with the effective dynamics for the stochastic reaction diffusion equations with cubic nonlinearity driven by a multiplicative noise. By splitting the solution into the finite dimension kernel space and its complement space with some appropriate multi-scale, it derives the dominant solution and the effective invariant measure in the sense of the Wasserstein distance, which capture the complex dynamical behaviors of the original system as a singular parameter is enough small. Furthermore, the effective invariant measure is decomposed to a product of two invariant measures.

Visible-light‑sensitive AgCu nanocomposites for sustainable inactivation of virus

The coronavirus disease 2019 (COVID-19) caused a large number of deaths and serious economic losses. Safety precautions and effective measures are urgently demanded to control the virus spread in public places. Owing to the longevity of the viruses in the aerosols and surfaces, sustained nanomaterials with efficient antiviral abilities during both daytime and night appear to be a promising way to control virus spread. Here, AgCu nanocomposites, which are outstanding antibacterial and antiviral elements, including Ag2Cu2O3 and AgCuO2, have been successfully prepared via a simple co-precipitation method for inactivation of model Qbeta (Qβ) bacteriophage. Notably, Ag2Cu2O3 has uniform nanorods morphology with a width of 50–100 nm and a length of 200–500 nm, regular elemental states of Cu2+ and Ag+, and good visible light response. Instead, AgCuO2 has more complex elemental states of Cu2+, Ag+, and Ag3+, including morphology with large particles of 500–1000 nm surrounded by small nanorods and nanoplates. Density functional theory (DFT) calculations showed that Ag2Cu2O3 has a lower work function than AgCuO2, indicating the charges can be better released from the surface. The accumulated surface charge can bind to the virus to inactivate it. As a result, Ag2Cu2O3 shows outstanding antiviral properties with a 6-log reduction (99.9999 %) of Qβ phage after 45 min contact under dark condition, and the activity can be further promoted to 7.5-log inactivation of Qβ phage after the same time contact under visible light irradiation, revealing its potential to sustainably prevent viruses spread in indoor environments.

The Prospective Effect of Protective Gaming Beliefs and Behaviors on Problematic Gaming, Mental Health, and Well-Being of Video Game Players

While most players enjoy video gaming, a minority suffer from problematic gaming. Existing studies focused on risk factors and proposed legislative and technological measures to contain the undesirable consequences. The present study aims to examine whether players’ healthy gaming practices can protect themselves against problematic gaming. We conducted a longitudinal survey at a public university in China, 604 college students took the first wave survey, and 365 of them completed the second wave six months later. The results showed that protective gaming beliefs and behaviors at baseline were negatively associated with problematic gaming tendency, and positively associated with mental health and well-being at follow-up. Problematic gaming tendency did not predict mental health and well-being. The findings suggested that players’ self-regulation can be an effective measure against problematic gaming and promote mental health and well-being. The present study can inspire stakeholders to develop additional approaches to help at-risk and problematic players.

Совершенствование механизмов привлечения к административной ответственности субъектов топливно-энергетического комплекса

This scientific article examines the mechanisms for bringing fuel and energy complex entities to administrative liability in order to improve them. The study of specific aspects in the process of bringing fuel and energy complex entities to administrative liability is of high importance and relevance, since offenses in this industry can lead to serious environmental consequences, threaten the safety and health of the population, and violate the energy security of the state. That is why the development of effective measures for bringing entities to administrative liability is crucial for ensuring sustainable and safe development of the fuel and energy complex. The author identifies the reasons that lead to the risk of committing administrative offenses by fuel and energy complex entities and proposes specific multilateral measures to prevent them. The article raises issues that deepen our understanding of the mechanisms and peculiarities of bringing fuel and energy complex entities to administrative liability. This understanding contributes to the development of effective strategies and measures to prevent offenses in this field.

Comparison between novel zipper device and conventional methods for skin closure: a systematic review and meta-analysis.

The zipper device is a wound closure device that can be directly applied over the intact skin on either side of the wound edges and does not need anchoring into the skin or subcutaneous plane. The noninvasive nature of the zipper device makes it less time-consuming and less painful, but its effectiveness and related complications need to be studied. Prospective registration of the protocol followed in this study was done. Electronic databases were searched for relevant articles, and their screening was completed, followed by data extraction and analysis. The odds ratio, mean difference, or standardised mean difference were used as an effect measure per the nature of the variables. Surgical site infection, wound dehiscence, skin closure time, scar score, and patient satisfaction were compared in this study. A total of 10 studies were identified, out of which eight compared zippers with sutures and two compared zippers with stapler devices. Compared to the suture, the zipper device took 4.9 min less to close the incision, and the scar scale outcome reported after one month was inferior, while other results were not significant. Staples showed a lower patient satisfaction level and no difference in complications. The zipper device is a less technically demanding and less time-consuming method of skin closure, with no significant difference in the complication rate compared to conventional methods. The zipper device is an effective measure to use in settings with less expertise or at health institutions after assessing the cost at the local level.

Feasibility study for test rig assessments of fish passage conditions in a Kaplan turbine

The assessment of fish passage conditions in hydroelectric turbines consists of identifying and quantifying physical magnitudes leading to increased risks of injury of fish passing through turbines in operation. Such assessments are usually carried out either with the use of computer-based methods during design or with field testing of live fish and sensors passing through prototypes. A method in between consists of test rig experimentation, which is critical for testing fish-focused design concepts and offers the opportunity for implementing the most effective design measures for improved fish survivability. However, fish-related assessments in test rigs are not sufficiently documented for industrial applications. This work presents the main findings of an experimental campaign to quantify fish-related hydraulic magnitudes in a physical model of a Kaplan turbine in a commercial test rig. Two operating conditions were tested by releasing miniaturized autonomous sensor devices (termed Sensor Fish Mini) at the turbine intake flow, passing them through the runner in motion and recovering them at the draft tube exit. During passage, time series of acceleration, absolute pressure and rotational velocity were recorded. The recordings were then interpreted to determine the magnitude and likely location of hydraulic stressors hazardous to fish. The statistical tests on the reported measurements indicated that low pressure, collisions on the runner and rotations in the draft tube were not different between the two tested operating points. On the other hand, pressure drop and collision rates on the distributor differed considerably as a function of net head. The outcomes of this investigation showed that test rig evaluations of fish-related properties with Sensor Fish Mini can contribute to an evidence-based development of turbine geometries designed for providing safer passage conditions. Future work will investigate the scaling of test rig measurements to hydraulically equivalent magnitudes in the prototype and their biological consequences.

Assessing the Physical and Psychological Well-being of Construction Workers During the COVID-19 Pandemic: A Prospective Study in Italy.

This prospective study aimed to assess the physical and psychological health of construction workers and examine the relationship between their well-being and the preventive measures implemented against SARS-CoV-2. During occupational visit, the workers were invited to participate the survey. Two measurements were made and compared: after the Italian lockdown and on the second wave of COVID-19 pandemic. Fifty-three workers participated in the study. The percentage of workers who considered themselves in good health increased from 66.0% to 81.1%, and there was a significant decrease in the 12-item General Health Questionnaire score (16.8 vs 14.0, P = 0.0003). This reduction was associated with a higher perception of security by preventive measures. The study highlights the importance of addressing the health and safety concerns of construction workers during the pandemic, and the positive impact of effective preventive measures.

Enhancements in the world of digital forensics

<p>Currently, the rapid advancement of computer systems and mobile phones has resulted in their utilization in unlawful acts. Ensuring adequate and effective security measures poses a difficult task due to the intricate nature of these devices, thereby exacerbating the challenges associated with investigating crimes involving them. Digital forensics, which involves investigating cyber crimes, plays a crucial role in this realm. Extensive research has been conducted in this field to aid forensic investigations in addressing contemporary obstacles. This paper aims to explore the progress made in the applications of digital forensics and security, encompassing various aspects, and provide insights into the evolution of digital forensics over the past five years.</p>

Genomic surveillance of emerging SARS-CoV-2 Omicron variations in Tianjin Municipality, China 2022

The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has severely impacted public health. In 2022, the Omicron variant of SARS-CoV-2 rapidly became the dominant circulating variant in the local COVID-19 outbreaks in Tianjin Municipality, China. To gain a deeper understanding of the genetic variations of the Omicron variant in Tianjin, specimens from individuals who tested positive for SARS-CoV-2 between December 2021 and November 2022 were used for virus whole genome sequencing and phylogenetic analysis. A total of 1,674 high-quality Omicron sequences were obtained, consisting of 1,339 sequences from local cases belonging to 20 PANGO lineages and 335 sequences from imported cases belonging to 70 lineages. Tianjin experienced five waves of local outbreaks, accompanied by multiple substitutions among subvariants, ranging from the initial BA.1.1 lineage to the subsequent BA.2, BF.7, and BA.5.2 lineages. The evolutionary rate of local strains, estimated to be 28.999 subs per year, and the evolutionary rate of imported strains, estimated to be 24.946 subs per year, were lower than that of the strains circulating globally. The additional substitutions and deletions of local strains have been used to identify and disrupt the virus transmission chains. The subvariants such as BA.5.2.48, BA.5.2.49, BF.7.14, and XBB.1 circulating in the fifth epidemic wave presented criterial immune escape mutations including S: R346T, S: L452R and S: F486V. It is essential to implement genomic surveillance strategies to investigate further the development of genomic mutation characteristics in the SARS-CoV-2 variant. This ongoing monitoring will contribute to a better understanding of the virus's genetic changes and aid in effective control measures.

The Molecular Mechanism of the Response of Rice to Arsenic Stress and Effective Strategies to Reduce the Accumulation of Arsenic in Grain.

Rice (Oryza sativa L.) is the staple food for more than 50% of the world's population. Owing to its growth characteristics, rice has more than 10-fold the ability to enrich the carcinogen arsenic (As) than other crops, which seriously affects world food security. The consumption of rice is one of the primary ways for humans to intake As, and it endangers human health. Effective measures to control As pollution need to be studied and promoted. Currently, there have been many studies on reducing the accumulation of As in rice. They are generally divided into agronomic practices and biotechnological approaches, but simultaneously, the problem of using the same measures to obtain the opposite results may be due to the different species of As or soil environments. There is a lack of systematic discussion on measures to reduce As in rice based on its mechanism of action. Therefore, an in-depth understanding of the molecular mechanism of the accumulation of As in rice could result in accurate measures to reduce the content of As based on local conditions. Different species of As have different toxicity and metabolic pathways. This review comprehensively summarizes and reviews the molecular mechanisms of toxicity, absorption, transport and redistribution of different species of As in rice in recent years, and the agronomic measures to effectively reduce the accumulation of As in rice and the genetic resources that can be used to breed for rice that only accumulates low levels of As. The goal of this review is to provide theoretical support for the prevention and control of As pollution in rice, facilitate the creation of new types of germplasm aiming to develop without arsenic accumulation or within an acceptable limit to prevent the health consequences associated with heavy metal As as described here.

An unprotected vulnerable relict subtropical conifer— Keteleeria evelyniana: its forests, populations, growth and endangerment by invasive alien plant species in China

Relict subtropical coniferous forests in China face severe fragmentation, resulting in declining populations, and some are under significant threat from invasive alien species. Despite the crucial importance of understanding forest dynamics, knowledge gaps persist, particularly regarding the impact of invasive plants on vulnerable natives like Keteleeria evelyniana. In this study, we investigated the impact of invasive plants on the regeneration of forests dominated by K. evelyniana, a subtropical relict species in southwestern China. For this purpose, we characterized forest dynamics of 160 forest plots featuring K. evelyniana as the primary dominant species and determined whether the presence of invasive plants was correlated with regeneration of K. evelyniana. We identified four distinct forest types in which K. evelyniana was dominant. We found that radial growth of K. evelyniana trees is faster in younger age-classes today than it was for older trees at the same age. The population structure of K. evelyniana in each forest type exhibited a multimodal age-class distribution. However, three forest types lacked established saplings younger than 10 years old, a situation attributed to the dense coverage of the invasive alien Ageratina adenophora. This invasive species resulted in a reduction of understory species diversity. Additionally, our analysis uncovered a significant negative correlation in phylogenetic relatedness (net relatedness index) between native and invasive alien plant species in eastern Yunnan. This suggests closely related invasive species face heightened competition, hindering successful invasion. Taken together, our findings indicate that successful establishment and habitat restoration of K. evelyniana seedling/saplings require effective measures to control invasive plants.

Indoor Air Sources of Outdoor Air Pollution: Health Consequences, Policy, and Recommendations: An Official American Thoracic Society Workshop Report.

Indoor sources of air pollution worsen indoor and outdoor air quality. Thus, identifying and reducing indoor pollutant sources would decrease both indoor and outdoor air pollution, benefit public health, and help address the climate crisis. As outdoor sources come under regulatory control, unregulated indoor sources become a rising percentage of the problem. This American Thoracic Society workshop was convened in 2022 to evaluate this increasing proportion of indoor contributions to outdoor air quality. The workshop was conducted by physicians and scientists, including atmospheric and aerosol scientists, environmental engineers, toxicologists, epidemiologists, regulatory policy experts, and pediatric and adult pulmonologists. Presentations and discussion sessions were centered on 1) the generation and migration of pollutants from indoors to outdoors, 2) the sources and circumstances representing the greatest threat, and 3) effective remedies to reduce the health burden of indoor sources of air pollution. The scope of the workshop was residential and commercial sources of indoor air pollution in the United States. Topics included wood burning, natural gas, cooking, evaporative volatile organic compounds, source apportionment, and regulatory policy. The workshop concluded that indoor sources of air pollution are significant contributors to outdoor air quality and that source control and filtration are the most effective measures to reduce indoor contributions to outdoor air. Interventions should prioritize environmental justice: Households of lower socioeconomic status have higher concentrations of indoor air pollutants from both indoor and outdoor sources. We identify research priorities, potential health benefits, and mitigation actions to consider (e.g., switching from natural gas to electric stoves and transitioning to scent-free consumer products). The workshop committee emphasizes the benefits of combustion-free homes and businesses and recommends economic, legislative, and education strategies aimed at achieving this goal.

Inclusive education peculiarities of teachers' perception of a learner with a disability

Introduction. Currently, in the context of the of the education system humanization and with the tendency to increase the proportion of students with disabilities in the total number of children, special attention is paid to creating an inclusive educational environment in basic education institutions. There is a natural increase in requirements for the quality of differentiated educational programs implementation, which is largely determined not only by special professional competences among teachers, but by their individual characteristics as well. In this regard, the issue of accounting for teachers' perception of students with disabilities in the education system is brought out. Aim. The aim of the presented study was to identify the characteristics of the perception of students with disabilities by teachers who have different experiences of interacting with this category of students. Methods of research. The questionnaire survey was attended by 336 teachers. Methods of mathematical statistics: nonparametric criterion Mann–Whitney U-test, correlation coefficient r-Spearman. Statistical calculations were done using a specialized IBM SPSS Statistics 22 program. The results of the study. It is found that the structure of perception of a student with a disability among teachers with diverse experience of interaction with students with disabilities is characterized by a significant number of positive connections between its components. Differences in teachers' attitudes towards students with disabilities (U=121.0; p = 0.003), their emotional attitude (U=120,0; p = 0,000) as well as in the readiness of teachers to implement the educational process (U=118.0; p = 0.000) were revealed. The lack of this experience leads a teacher to the prejudiced assessment of difficulties when organizing and implementing the educational process with the participation of students with disabilities and contributes to the growth of emotional stress in teachers during classes. Scientific novelty. The structure of perception of a learner with a disability by teachers was developed and empirically confirmed on the basis of significant connections of mindsets, attitude and readiness of the teacher. Practical significance. The results of the study will make it possible to develop effective measures of psychological and pedagogical support for teachers in inclusive education, including additional professional programs on inclusive education, accumulation of practical experience of interaction with persons with disabilities in the educational process and everyday life, discussion and elaboration of emotional experiences that arise when interacting with students with a disability.

A Two-Stage Framework for Exploiting the Multi-Elasticity of Multi-Energy Demands in Integrated Electricity and Gas Markets

With the development of integrated electricity and gas markets (IEGM), the participation of multi-energy demands (MEDs) is an effective measure to achieve a win-win goal of market efficiency improvement and demand cost reduction. The MEDs, composed of terminal users and energy conversion equipment (ECE), can adjust purchased electricity and gas with the variation in energy prices. Such adjustment behaviors of purchased energy in response to energy prices are defined as the multi-elasticity of MEDs. Considering that, this paper aims to analyze and quantify the multi-elasticity of MEDs and exploit it using a market-based approach. Firstly, the volume-price bidding curves are proposed to describe the multi-elasticity of MEDs considering the price-response features of terminal loads and multi-energy substitution features of ECE. Based on the proposed bidding curves, the energy consumption behaviors of MEDs with the change in prices can be effectively quantified. Moreover, a decentralized two-stage market framework is proposed to exploit the multi-elasticity in the IEGM clearing based on the multi-elasticity bidding curves of MEDs. In the proposed framework, the electricity market and gas market are cleared separately with the information exchange of the MEDs' clearing results of purchased gas and electricity. Furthermore, the consensus ADMM-based algorithm is applied to coordinately solve the IEGM clearing problem integrated with the multi-elasticity of MEDs. Numerical simulations are carried out for different test systems to validate the effectiveness of the proposed models.

The optimization method based on the coupling of genetic algorithm and ant colony algorithm for the exhaust outlet space arrangement

The exhaust outlet space arrangement is a crucial part to avoid casualties and economic losses in the event of contaminant gas leakage. To handle this problem, this work proposed a novel optimization method based on the coupling of the genetic algorithm (GA) and ant colony algorithm optimization (ACO), and the fitness function used in the optimization method is constructed as an implicit form. In this proposed optimization method, the ACO is used to obtain the implicit fitness function value, while the GA is selected to conduct the space arrangement optimization based on the iteration results transferred from ACO. With the help of this novel methodology, the influence of obstacles in space could be well considered into the space arrangement optimization, which leads to a reliable optimization result of the exhaust outlet configuration. Moreover, to validate the accuracy and efficiency of this coupling method, the optimization results are taken into the computational fluid dynamics numerical model to give a comparison with the conventional configuration. The comparison results indicate that the exhaust outlet arrangement following the optimization results shows a lower gas concentration value during the diffusion process. In addition, based on this optimal exhaust outlet space arrangement, the models with various leakage rates are also investigated and discussed in the numerical work. It is believed that the proposed method could provide an effective measure for the space arrangement optimization and the design of gas leakage protection.

The prevalence of fibromyalgia in adults at Al-Karak Jordan: a cross-sectional study.

Fibromyalgia is a chronic and intricate musculoskeletal disorder characterized by widespread pain, fatigue, and tenderness in specific anatomical regions. Although its prevalence varies among populations, understanding the prevalence in different geographical areas is crucial for healthcare planning. This cross-sectional study aims to determine the prevalence of fibromyalgia in adults residing in Al-Karak, Jordan. The city's unique demographic and environmental characteristics may influence the occurrence of fibromyalgia among its adult population. The study aims to address gaps in knowledge, provide localized insights, and shed light on fibromyalgia's burden on the community's health. Accurate prevalence data aids healthcare planning and resource allocation. This research collected data from 965 social media participants using Google Forms. The American College of Rheumatology survey criteria for diagnosing fibromyalgia were used. To investigate the predictive value of various parameters, univariate and multivariate logistic regression analyses were performed. The study found a 26.5% prevalence of fibromyalgia in the studied population. Female gender, mental health illnesses, and comorbidities like irritable bowel syndrome, psychiatric disorders, and rheumatological and neurological diseases were significantly associated with fibromyalgia. Age, BMI, marital status, employment status, and certain comorbidities did not show statistically significant predictive value. This study sheds light on fibromyalgia's prevalence and associated factors in the Al-Karak population. The identified predictors highlight the necessity for comprehensive healthcare strategies and interventions to mitigate the disease burden. These findings aid policymakers and healthcare professionals in planning and implementing effective measures for fibromyalgia management and prevention. Further research is warranted to deepen our understanding of fibromyalgia's complexity and its implications in this region.

The Role of Digital Media on Students’ Management in Higher Vocational College

This study uses a combination of empirical analysis to conduct a comprehensive analysis of the role of digital media and student management in higher vocational colleges. The results show that the current application status of digital media in student management shows extensive and profound impact. With the rapid development of information technology, digital media has become an important tool for student management in higher vocational colleges, covering many aspects such as course management, attendance management, and student information inquiry, greatly improving management efficiency and convenience. By establishing a digital system, the school has achieved comprehensive coverage of student information management and online education. At the same time, digital media also plays an important role in students' social interaction and has become an indispensable part of students' daily lives. However, digital media applications also bring some problems. Information overload and distraction can make it difficult for students to focus, while security risks threaten student privacy. Solving these problems requires schools to take effective measures, such as improving information literacy and security awareness, and establishing a complete information security system. The impact of digital media on student development is complex and diverse. Its advantage lies in providing a broad learning space and diversified learning methods to promote students' communication and socialization. However, negative effects such as information overload and Internet addiction cannot be ignored. In order to better guide students to use digital media, schools and families need to strengthen digital media literacy education, pay attention to students' mental health, and strengthen network security. In student management, the advantages of digital media are mainly reflected in improving efficiency and interactivity, and promoting management innovation and development. However, the popularization of digital media needs to face issues such as technical and device support, security and privacy protection. By strengthening measures such as construction, training, supervision and management, schools can better leverage the advantages of digital media and improve management efficiency and service quality. Going forward, digital media will play an even more important role in student management. Intelligent management, expanding management fields and promoting student self-management will be the direction of future development. However, the security and popularity of digital media remain challenges that need to be addressed. By strengthening comprehensive measures such as construction, training, supervision and management, schools can better guide the future development of digital media in student management, provide students with more intelligent, personalized and efficient services, and promote their all-round development.

Comparison of disease and economic burden between MRSA infection and MRSA colonization in a university hospital: a retrospective data integration study

BackgroundAlthough there is a growing concern and policy regarding infections or colonization caused by resistant bacteria, including methicillin-resistant Staphylococcus aureus (MRSA), the prognosis of MRSA infections compared to that of methicillin-susceptible Staphylococcus aureus (MSSA) infections remains controversial. Moreover, there have not been any studies comparing both the burden of disease and its impact on the healthcare economy between MRSA infection and colonization while adjusting for confounding factors. These comparisons are crucial for developing effective infection control measures and healthcare policies. We aimed to compare the disease and economic burden between MRSA and MSSA infections and between MRSA infection and colonization.MethodsWe retrospectively investigated data of 496 in-patients with MRSA or MSSA infections and of 1178 in-patients with MRSA infections or MRSA colonization from a university hospital in Japan from 2016 to 2021. We compared in-hospital mortality, length of stay, and hospital charges between in-patients with MRSA and MSSA infections and those with MRSA infections and MRSA colonization using multiple regressions. We combined surveillance data, including all microbiological test results, data on patients with infections, treatment histories, and clinical outcomes, to create the datasets.ResultsThere was no statistically significant difference in in-hospital mortality rates between matched MRSA vs. MSSA infections and MRSA infection vs. colonization. On the contrary, the adjusted effects of the MRSA infection compared to those of MSSA infection on length of stay and hospital charges were 1.21-fold (95% confidence interval [CI] 1.03–1.42, P = 0.019) and 1.70-fold (95% CI 1.39–2.07, P < 0.00001), respectively. The adjusted effects of the MRSA infection compared to those of MRSA colonization on length of stay and hospital charges were 1.41-fold (95% CI 1.25–1.58, P < 0.00001) and 1.53-fold (95% CI 1.33–1.75, P < 0.00001), respectively. Regarding confounding factors, hemodialysis or hemofiltration was consistently identified and adjusted for in the multiple regression analyses comparing MRSA and MSSA infections, as well as MRSA infection and MRSA colonization.ConclusionsMRSA infection was associated with longer length of stay and higher hospital charges than both MSSA infection and MRSA colonization. Furthermore, hemodialysis or hemofiltration was identified as a common underlying factor contributing to increased length of stay and hospital charges.

Flood Susceptibility Mapping Using SAR Data and Machine Learning Algorithms in a Small Watershed in Northwestern Morocco

Flood susceptibility mapping plays a crucial role in flood risk assessment and management. Accurate identification of areas prone to flooding is essential for implementing effective mitigation measures and informing decision-making processes. In this regard, the present study used high-resolution remote sensing products, i.e., synthetic aperture radar (SAR) images for flood inventory preparation and integrated four machine learning models (Random Forest: RF, Classification and Regression Trees: CART, Support Vector Machine: SVM, and Extreme Gradient Boosting: XGBoost) to predict flood susceptibility in Metlili watershed, Morocco. Initially, 12 independent variables (elevation, slope angle, aspect, plan curvature, topographic wetness index, stream power index, distance from streams, distance from roads, lithology, rainfall, land use/land cover, and normalized vegetation index) were used as conditioning factors. The flood inventory dataset was divided into 70% and 30% for training and validation purposes using a popular library, scikit-learn (i.e., train_test_split) in Python programming language. Additionally, the area under the curve (AUC) was used to evaluate the performance of the models. The accuracy assessment results showed that RF, CART, SVM, and XGBoost models predicted flood susceptibility with AUC values of 0.807, 0.780, 0.756, and 0.727, respectively. However, the RF model performed better at flood susceptibility prediction compared to the other models applied. As per this model, 22.49%, 16.02%, 12.67%, 18.10%, and 31.70% areas of the watershed are estimated as being very low, low, moderate, high, and very highly susceptible to flooding, respectively. Therefore, this study showed that the integration of machine learning models with radar data could have promising results in predicting flood susceptibility in the study area and other similar environments.