Artificial intelligence models for predicting calcium and magnesium removal by polyfunctional ketone using ensemble machine learners.

Calcium (Ca2+) and magnesium (Mg2+) are the major scaling ions of reverse osmosis concentrate in zero-liquid discharge systems, causing performance decline. In this study, we predicted the removal of Ca2+ and Mg2+ from simulated reverse osmosis concentrate by functional polyketones (FPKs). Four amines, including 1,2-diaminopropane (DAP), 1-(2-aminoethyl) piperazine (AEP), 1-(3-aminopropyl) imidazole (API), and butyl amine (BA) used to synthesize FPKs. The effects of various factors such as the amount of adsorbent, feed water concentration, and pH were investigated for process optimization. In this study, ensemble learner artificial intelligence models, decision tree (DT), extreme gradient boost (XGB), and random forest (RF) were used to predict Ca2+ and Mg2+ removal by the FPKs. Datasets were collected experimentally using FPKs to remove Ca2+ and Mg2+ from the simulated reverse osmosis concentrate. The predictions were made by XGB, DT, and RF models for the first chosen amine for Ca2+ and then for Mg2+, subsequently, this process was repeated with each amine. The developed DT, RF, and XGB models demonstrated higher coefficients of determination for predicting Mg2+ removal by AEP and DAP (R2 = 0.841-0.935) than by API and BA (R2 = 0.774-0.801) except in the RF and XGB model results (R2 = 0.801-0.846). Overall, the XGB model displayed good results for both Ca2+ and Mg2+ removal but slight changes were observed in the AEP and BA predictions by DT and RF. Therefore, artificial intelligence models may be a viable alternative for further insight in predicting Ca2+ and Mg2+ removal by FPKs from simulated reverse osmosis concentrate.

Self-Esteem Trajectories After Occupational Injuries and Diseases and Their Relation to Changes in Subjective Health: Result From the Panel Study of Workers' Compensation Insurance (PSWCI).

BACKGROUND: Occupational injuries and diseases are life events that significantly impact an individuals' identity. In this study, we examined the trajectories of self-esteem among victims of occupational injury and disease and their relation to health. METHODS: The Panel Study of Workers' Compensation Insurance conducted annual follow-ups on workers who had experienced occupational injury or disease. A total of 2,000 participants, who had completed medical care, were followed from 2013 to 2017. Growth mixture modeling was utilized to identify latent classes in the self-esteem trajectory. Additionally, logistic regressions were conducted to explore the association between trajectory membership, baseline predictors, and outcomes. RESULTS: Three distinct trajectory classes were identified. Total 65.8% of the samples (n = 1,316) followed an increasing self-esteem trajectory, while 31.1% (n = 623) exhibited a constant trajectory, and 3.1% (n = 61) showed a decreasing trajectory. Individuals with an increasing trajectory were more likely to have a higher educational attainment (odds ratio [OR], 1.86; 95% confidence interval [CI], 1.20-2.88), an absence of a moderate-to-severe disability rating (OR, 0.49; 95% CI, 0.25-0.96), no difficulty in daily living activities (OR, 0.81; 95% CI, 0.75-0.88), and were economically active (re-employed: OR, 2.46; 95% CI, 1.52-3.98; returned to original work: OR, 4.46; 9% CI, 2.65-7.50). Those with a decreasing self-esteem trajectory exhibited an increased risk of poor subjective health (OR, 1.89; 95% CI, 0.85-4.85 in 2013 to OR, 3.17; 95% CI, 1.04-13.81 in 2017), whereas individuals with an increasing trajectory showed a decreased risk (OR, 0.54; 95% CI, 0.43-0.68 in 2013 to OR, 0.44; 95% CI, 0.33-0.57 in 2017). CONCLUSION: Our findings emphasize the diversity of psychological responses to occupational injury or disease. Policymakers should implement interventions to enhance the self-esteem of victims.

Association between job satisfaction and current smoking and change in smoking behavior: a 16-year longitudinal study in South Korea.

BACKGROUND AND AIMS: Previous studies have found that job satisfaction is closely associated with various health outcomes of workers. Our study measured the association between job satisfaction and current smoking and change in smoking behavior. DESIGN: Data from the longitudinal Korea Labor and Income Panel Study (KLIPS) that consist of nationally representative samples were used. The repeated measures analysis was conducted. SETTING: South Korea, 2005-2021. PARTICIPANTS: In total, 21 154 workers in Korea followed from 2005 to 2021 (145 120 observations) were included as study participants. MEASUREMENTS: The main predictor variable, job satisfaction, was assessed using a five-item general job satisfaction questionnaire. Job satisfaction was classified into 'dissatisfied', 'neutral' and 'satisfied', according to the tertiles of the sum of scores. The outcomes of interest were current smoking and initiation and cessation of smoking in the subsequent year. FINDINGS: Compared with those with a neutral level of job satisfaction, those who reported dissatisfaction with their job had an increased risk of smoking initiation [odds ratio (OR) = 1.11, 95% confidence interval (CI) = 1.01-1.22)]. Workers satisfied with their jobs were associated with a decreased likelihood of current smoking (OR = 0.96, 95% CI = 0.94-0.98) and smoking initiation (OR = 0.90, 95% CI = 0.81-0.99). There was a positive relationship between cumulative years of job dissatisfaction and smoking risk: > 4 years of experiencing job dissatisfaction was positively related to current smoking (OR = 1.14, 95% CI = 1.06-1.24) and smoking initiation (OR = 1.22, 95% CI = 1.00-1.49) and negatively related to smoking cessation (OR = 0.84, 95% CI = 0.72-0.99). CONCLUSIONS: In Korea, job dissatisfaction appears to be associated with an increased risk of smoking initiation.

Critical Factors to Understanding the Electrochemical Performance of All-Solid-State Batteries: Solid Interfaces and Non-Zero Lattice Strain.

All-solid-state lithium batteries have been developed to secure safety by substituting a flammable liquid electrolyte with a non-flammable solid electrolyte. However, owing to the nature of solids, interfacial issues between cathode materials and solid electrolytes, including chemical incompatibility, electrochemo-mechanical behavior, and physical contact, pose significant challenges for commercialization. Herein, critical factors for understanding the performance of all-solid-state batteries in terms of solid interfaces and non-zero lattice strains are identified through a strategic approach. The initial battery capacity can be increased via surface coating and electrode-fabrication methods; however, the increased lattice strain causes significant stress to the solid interface, which degrades the battery cycle life. However, this seesaw effect can be alleviated using a more compacted electrode microstructure between the solid electrolyte and oxide cathode materials. The compact solid interfaces contribute to low charge-transfer resistance and a homogeneous reaction between particles, thereby leading to improved electrochemical performance. These findings demonstrate, for the first time, a correlation between the uniformity of the electrode microstructure and electrochemical performance through the investigation of the reaction homogeneity among particles. Additionally, this study furthers the understanding of the relationship between electrochemical performance, non-zero lattice strain, and solid interfaces.

Estimated trends in hospitalizations due to occupational injuries in Korea based on the Korean National Hospital Discharge In-depth Injury Survey (2006-2019).

OBJECTIVES: In recent years, occupational injuries have sparked a huge social and political debate. Thus, in this study, we focused on the characteristics and trends of occupational injuries requiring hospitalization in Korea. METHODS: The Korea National Hospital Discharge In-depth Injury Survey was designed to estimate the annual number and characteristics of all injury-related hospitalizations in Korea. The annual number of hospitalizations due to occupational injuries and the age-standardized rates (ASRs) were estimated from 2006 to 2019. The annual percentage change (APC) and average annual percentage change (AAPC) of ASRs and their 95% confidence intervals (CIs) were calculated using joinpoint regression. All analyses were stratified by gender. RESULTS: In men, the APC of the ASRs of all-cause occupational injuries was -3.1% (95% CI, -4.5 to -1.7) in 2006-2015. However, a non-significant upward trend was observed after 2015 (APC, 3.3%; 95% CI, -1.6 to 8.5). In women, the APC of all-cause occupational injuries was -8.6% (95% CI, -12.1 to -5.1) in 2006-2012. However, a non-significant upward trend was observed after 2012 (APC, 2.1%; 95% CI, -0.9 to 5.2). A recent upward trend in stabbing injuries was observed after 2012 (APC, 4.7%; 95% CI, -1.8 to 11.8) in women. A non-significant overall increasing trend was also observed for occupational injuries caused by exposure to extreme temperatures (AAPC, 3.7%; 95% CI, -1.1 to 8.7) in women. CONCLUSIONS: A recent upward trend in all-cause injury hospitalizations and hospitalizations caused by stabbing injuries was observed. Therefore, active policy interventions are required to prevent occupational injuries.

Association between long working hours and physical inactivity in middle-aged and older adults: a Korean longitudinal study (2006-2020).

BACKGROUND: We investigated associations for long working hours in relation to physical inactivity and high-level physical activity among middle-aged and older adults. METHODS: Our study included 5402 participants and 21 595 observations from the Korean Longitudinal Study of Ageing (2006-2020). Logistic mixed models were used to estimate ORs and 95% CIs. Physical inactivity was defined as not engaging in any type of physical activity, while high-level physical activity was defined as engaging in ≥150 min per week of physical activity. RESULTS: Working >40 hours weekly was positively related to physical inactivity (OR (95% CI) 1.48 (1.35 to 1.61)) and negatively related to high-level physical activity (0.72 (95% CI 0.65 to 0.79)). Exposure to long working hours consecutively for ≥3 waves was associated with the highest OR for physical inactivity (1.62 (95% CI 1.42 to 1.85)) and the lowest OR for high-level physical activity (0.71 (95% CI 0.62 to 0.82)). Furthermore, compared with persistent short working hours (≤40 hours → ≤40 hours), long working hours in a previous wave (>40 hours → ≤40 hours) were associated with a higher OR of physical inactivity (1.28 (95% CI 1.11 to 1.49)). Exposure to an increase in working hours (≤40 hours → >40 hours) was also associated with a higher OR of physical inactivity (1.53 (95% CI 1.29 to 1.82)). CONCLUSION: We found that having working long hours was associated with a higher risk of physical inactivity and a lower likelihood of high-level physical activity. Moreover, accumulation of long working hours was associated with a higher risk of physical inactivity.

Ultrasoft edge-labelled hydrogel sensors reveal internal tissue stress patterns in invasive engineered tumors.

Measuring internal mechanical stresses within 3D tissues can provide important insights into drivers of morphogenesis and disease progression. Cell-sized hydrogel microspheres have recently emerged as a powerful technique to probe tissue mechanobiology, as they can be sufficiently soft as to deform within remodelling tissues, and optically imaged to measure internal stresses. However, measuring stresses at resolutions of ∼10 Pa requires ultrasoft, low-polymer content hydrogel formulations that are challenging to label with sufficiently fluorescent materials to support repeated measurements, particularly in optically dense tissues over 100 µm thick, as required in cancer tumor models. Here, we leverage thermodynamic partitioning of hydrogel components to create "edge-labelled" ultrasoft hydrogel microdroplets, in a single polymerization step. Bright and stable fluorescent nanoparticles preferentially polymerize at the hydrogel droplet interface, and can be used to repeatedly track sensor surfaces over long-term experiments, even when embedded deep in light-scattering tissues. We utilize these edge-labelled microspherical stress gauges (eMSGs) in inducible breast cancer tumor models of invasion, and demonstrate distinctive internal stress patterns that arise from cell-matrix interactions at different stages of breast cancer progression. Our studies demonstrate a long-term macroscale compaction of the tumor during matrix encapsulation, but only a short-term increase in local stress as non-invasive tumors rapidly make small internal reorganizations that reduce the mechanical stress to baseline levels. In contrast, once invasion programs are initiated, internal stress throughout the tumor is negligible. These findings suggest that internal tumor stresses may initially prime the cells to invade, but are lost once invasion occurs. Together, this work demonstrates that mapping internal mechanical stress in tumors may have utility in advancing cancer prognostic strategies, and that eMSGs can have broad utility in understanding dynamic mechanical processes of disease and development.

Performance-Based Pay System and Job Stress Related to Depression/Anxiety in Korea: Analysis of Korea Working Condition Survey.

The adoption rate of performance-based pay systems has increased in recent years, and the adverse effects of systems have been emphasized. However, no study has analyzed the increase in the risk of depression/anxiety symptoms caused by the pay system in Korea. This study aimed to reveal the association between performance-based pay systems and symptoms of depression/anxiety, using data from the fifth Korean Working Conditions Survey. Depressive/anxiety symptoms were assessed using "yes" or "no" questions regarding medical problems related to depression/anxiety. The performance-based pay system and job stress were estimated using self-response answers. Logistic regression analyses were conducted to determine the association between performance-based pay systems, job stress, and symptoms of depression/anxiety using data from 27,793 participants. The performance-based pay system significantly increased the risk of the symptoms. Additionally, risk increments were calculated after grouping by pay system and job stress. Workers with two risk factors had the highest risk of symptoms of depression/anxiety for both sexes (male: OR 3.05; 95% CI 1.70-5.45; female: OR 2.15; 95% CI 1.32-3.50), implying synergistic effect of performance-based pay system and job stress on depression/anxiety symptoms. Based on these findings, policies should be established for early detection and protection against the risk of depression/anxiety.

Risks of Leukemia in Various Industrial Groups in Korea: A Retrospective National Cohort Study.

It is known that occupational exposure to specific agents is associated with leukemia. However, whether the occupational risks of leukemia differ among various industrial groups remains unclear. Therefore, the purpose of this study was to elucidate the occupational risks of leukemia among different worker groups by industry. Data for a total of 11,050,398 people from the National Health Insurance System's claim data from 2007 to 2015 were analyzed. By cohort inclusion of workers whose industry had not changed for three years and with total workers as a control group, the risk for a specific industry group was expressed as an age-standardized incidence ratio (SIR). Among groups by industry, 'Manufacture of motor vehicles and engines for motor vehicles', 'Sale of motor vehicle parts and accessories', and 'Personal care services' showed significantly higher SIRs. In division analysis, the 'Manufacture of other machinery and equipment' and 'Waste collection, treatment and disposal activities' divisions showed significantly higher SIRs than other divisions. We identified an increased risk of leukemia in workers of certain industries in Korea. Based on the results of this study, it is necessary to create a policy to protect workers at risk of leukemia. Various additional studies are needed to protect workers by revealing more precise relationships between individual hazardous substances, processes, and leukemia.

Achieving structural stability and enhanced electrochemical performance through Nb-doping into Li- and Mn-rich layered cathode for lithium-ion batteries.

Although Li- and Mn-rich layered oxides are attractive cathode materials possessing high energy densities, they have not been commercialized owing to voltage decay, low rate capability, poor capacity retention, and high irreversible capacity in the first cycle. To circumvent these issues, we propose a Li1.2Ni0.13Co0.13Mn0.53Nb0.01O2 (Nb-LNCM) cathode material, wherein Nb doping strengthens the transition metal oxide (TM-O) bond and alleviates the anisotropic lattice distortion while stabilizing the layered structure. During long-term cycling, maintaining a wider LiO6 interslab thickness in Nb-LNCM creates a favorable Li+ diffusion path, which improves the rate capability. Moreover, Nb doping can decrease oxygen loss, suppress the phase transition from layered to spinel and rock-salt structures, and relieve structural degradation. Nb doping results in less capacity contributions of Mn and Co and more reversible Ni and O redox reactions compared to pristine Li1.2Ni0.133Co0.133Mn0.533O2 (LNCM), which significantly mitigates the voltage decay (Δ0.289 and Δ0.516 V for Nb-LNCM and LNCM, respectively) and ensures stable capacity retention (82.7 and 70.3% for Nb-LNCM and LNCM, respectively) during the initial 100 cycles. Our study demonstrates that Nb doping is an effective and practical strategy to enhance the structural and electrochemical integrity of Li- and Mn-rich layered oxides. This promotes the development of stable cathode materials for high-energy-density lithium-ion batteries.

Synthesis of heated aluminum oxide particles impregnated with Prussian blue for cesium and natural organic matter adsorption: Experimental and machine learning modeling.

Heated aluminum oxide particles impregnated with Prussian blue (HAOPs-PB) are synthesized for the first time using different molar ratios of aluminum sulfate and PB to improve the adsorption of cesium (133Cs+) and natural organic matter (NOM) from an aqueous solution. The Cs+ adsorption from various aqueous solutions, including surface, tap and deionized water by synthesized HAOPs-PB, is investigated. The influencing factors such as HAOPs-PB mixing ratio, pH and dosage are studied. In addition, pseudo 1st and 2nd order is tested for adsorption kinetics study. A machine learning model is developed using gene expression programming (GEP) to evaluate and optimize the adsorption process for Cs+ and NOM removal. Synthesized adsorbent showed maximum adsorption at a 1:1 M ratio of aluminum sulfate and PB in DI, tap, and surface water. The pseudo 2nd order kinetics model described the Cs + adsorption by HAOPs-PB more accurately that indicating physiochemical adsorption. Adsorption of Cs+ showed an increasing trend with higher HAOPs-PB concentration, while high pH also favored the adsorption. Maximum NOM adsorption is found at a higher HAOPs-PB dosage and a neutral pH value. Furthermore, the proposed GEP model shows outstanding performance for Cs+ adsorption modeling, whereas a modified-GEP model presents promising results for NOM adsorption prediction for testing dataset by learning the relationship between inputs and output with R2 values of 0.9348 and 0.889, respectively.

Predictive modeling of pharmaceutical product removal by a managed aquifer recharge system: Comparison and optimization of models using ensemble learners.

Pharmaceutical products (PPs) are emerging water pollutants with adverse environmental and health-related impacts, owing to their toxic, persistent, and undetectable microscopic nature. Globally, increasing scientific knowledge and advanced technologies have allowed researchers to study PP-associated problems and their removal for water reuse. Experimental modeling methods require laborious, lengthy, expensive, and environmentally hazardous lab-work to optimize the process. On the other hand, predictive machine learning (ML) models can trace the complex input-output relationship of a process using available datasets. In this study, ensemble ML techniques, including decision tree (DT), random forest (RF), and Xtreme gradient boost (XGB), were used to explore PP (diclofenac, iopromide, propranolol, and trimethoprim) removal by a managed aquifer recharge (MAR) system. The model input parameters included characteristics of reclaimed water and soil used in the columns, pH, dissolved organic carbon, operating time, nitrogen dioxide, sulfate, nitrate, electrical conductivity, manganese, and iron. The selected PP removal was the model output. Datasets were collected through a one-year experimental study of continuous MAR system operation to predict the removal of PPs. DT, RF, and XGB models were then developed for one of the selected compounds and tested for the others to check the reliability of the ML model results. The developed models were assessed using statistical performance matrices. The experimental results showed >80% removal of propranolol and trimethoprim; however, removal of diclofenac and iopromide was only ≈50% by the MAR system. The proposed DT and RF models presented higher coefficients of determination (R2 ≥ 0.92) for diclofenac, propranolol, and trimethoprim than for iopromide (R2 ≤ 0.63). In contrast, the XGB model showed better results for diclofenac, iopromide, propranolol, and trimethoprim, with R2 values of 0.92, 0.72, 0.96, and 0.97, respectively. Therefore, XGB could be the best predictive model to provide insight into the adaptation of ML models to predict PP removal by the MAR system, thereby minimizing experimental work.

The effect of job insecurity, employment type and monthly income on depressive symptom: analysis of Korean Longitudinal Study on Aging data.

Background: In modern society, depression is serious issue that causes socioeconomic and family burden. To decrease the incidence of depression, risk factors should be identified and managed. Among many risk factors for depression, this study examined socioeconomic risk factors for depression. Methods: We utilized first (2006), second (2008), and third (2010)-wave data from the Korean Longitudinal Study of Aging (KLoSA). Depressive symptom was measured with the 10-item Center for Epidemiological Studies Depression Scale, Short Form (CES-D-10) in the survey in 2008 and 2010. Three risk factors including job security, employment type and monthly income were measured in the survey in 2006. The association between risk factors and depressive symptom was analyzed by Cox proportional-hazard model. Results: We analyzed data from 1,105 workers and hazard ratios (HRs) for 3 risk factors were significant entirely. In addition, regular worker with high income group is the most vulnerable group of poor job insecurity on depression among male workers (HR: 1.73; 95% confidence interval [CI]: 1.07-2.81). Finally, HRs for 7 groups who had at least 1 risk factor had higher HRs compared to groups who had no risk factors after stratifying 3 risk factors. In the analysis, significantly vulnerable groups were total 5 groups and the group who had highest HR was temporary/daily workers with poor job security (HR: 2.51; 95% CI: 1.36-4.64). The results concerning women, regardless of job type, were non-significant. Conclusions: This study presented one or more risk factors among poor job security, low income, temporary/daily employment type increase hazard for depressive symptom in 2 or 4 years after the exposure. These results inform policy to screen for and protect against the risk of depression in vulnerable groups.

Resilience and Depressive Symptoms among Medical Staff in a Military Hospital Dedicated to the Treatment of COVID-19.

Coronavirus disease 2019 (COVID-19) is prevalent around the world, and many studies suggest that depression among medical staff is on the rise during the pandemic. This study aims to assess the relationship between depressive symptoms and individual resilience among military hospital personnel responsible for treating patients with COVID-19. Individuals from the Armed Forces Daejeon Hospital who responded to the questionnaires from 8 February to 15 February 2022 participated in this study. Resilience and depressive symptoms were measured via the Korean Resilience Quotient Test-53 and Patient Health Questionnaire-9, respectively. We employed multivariable logistic regression analysis to estimate Odds Ratios (ORs) and 95% Confidence Intervals (CIs) of depressive symptoms. Among 181 participants, the individuals with depressive symptoms and high resilience accounted for 8.8% and 61.9%, respectively. Significant correlations between depressive symptoms and both the low resilience and low resilience positivity groups were found (adjusted OR 10.30 [95% CI 1.74-61.01] and OR 13.90 [95% CI 1.93-100.02], respectively). This study notes a significant inverse relationship between depressive symptoms and resilience even after adjusting for demographic and occupational characteristics. To overcome depressive symptoms among hospital personnel, it is necessary to seek ways to improve individual resilience, especially positivity.

Analyzing decline in quality of life by examining employment status changes of occupationally injured workers post medical care.

Background: This study aimed to investigate the decline in quality of life (QOL) by examining changes in the employment status of workers who had completed medical treatment after an industrial accident. Methods: This study utilized the Panel Study of Worker's Compensation Insurance cohort (published in October 2020) containing a sample survey of 3,294 occupationally injured workers who completed medical care in 2017. We divided this population into four groups according to changes in working status. A multivariate logistic regression model was utilized for evaluating QOL decline by adjusting for the basic characteristics and working environment at the time of accident. Subgroup analysis evaluated whether QOL decline differed according to disability grade and industry group. Results: The QOL decline in the "maintained employment," "employed to unemployed," "remained unemployed," and "unemployed to employed" groups were 15.3%, 28.1%, 20.2%, and 11.9%, respectively. The "maintained employment" group provided a reference. As a result of adjusting for the socioeconomic status and working environment, the odds ratios (ORs) of QOL decline for the "employed to unemployed" group and the "remained unemployed" group were 2.13 (95% confidence interval [CI], 1.51-3.01) and 1.47 (95% CI, 1.13-1.90), respectively. The "unemployed to employed" group had a non-significant OR of 0.76 (95% CI, 0.54-1.07). Conclusions: This study revealed that continuous unemployment or unstable employment negatively affected industrially injured workers' QOL. Policy researchers and relevant ministries should further develop and improve "return to work" programs that could maintain decent employment avenues within the workers' compensation system.

Treating reverse osmosis concentrate to address scaling and fouling problems in zero-liquid discharge systems: A scientometric review of global trends.

Currently, reverse osmosis concentrate (ROC) treatment is one of the most promising techniques for its disposal because it produces freshwater with high recovery and valuable materials such as salts and reduces waste volume and environmental pollution. Public attention to the severe consequences of water pollution and strict environmental regulations on wastewater discharge has pushed water-polluting industries toward zero-liquid discharge (ZLD). However, scaling and fouling problems increase energy consumption and limit permeate flux at high salt concentrations, mainly due to calcium, magnesium, and silica precipitation, ultimately decreasing ZLD performance. Therefore, this study discusses drivers and ROC pretreatment technologies to improve ZLD efficiency and presents a scientometric review of global trends. The advantages, disadvantages, and economic and environmental aspects of conventional and emerging pre-treatment technologies were studied. Traditional treatment of chemical processes combined with precipitation removes a large amount of scaling ions; however, high operation and maintenance costs and limited full-scale plant experience are the main drawbacks. Softening and coagulation are most commonly applied to treat large volumes at a moderate cost; however, substantial sludge production and increased conductivity are major operational issues. Moreover, emerging technologies efficiently remove scale-forming ions with high capital and operating costs. New variations in standard reverse osmosis technologies have improved ZLD efficiency; nonetheless, scaling and fouling are of concern. Therefore, this review presents the studies on ROC pre-treatment technologies for removing scaling ions to enhance ZLD efficiency, which can help in future research.

Mental health symptoms among dependent contractors in Korea: a cross-sectional study based on the Fifth Korean Working Condition Survey.

Background: Recently, there has been a call to improve the holistic welfare of dependent contractors (DCs). Thus, our study examined the relationship between DCs and mental health symptoms and how this relationship was modified by age, sex, and income status of workers. Methods: A total of 27,980 workers from the Fifth Korean Working Conditions Survey are included in our study. The participants who reported having depression or anxiety over the last 12 months are defined those who had mental health symptoms. We performed exact matching for age group and sex, followed by conditional logistic regression with survey weights. Finally, stratified analyses by age, sex and income level were conducted. Results: DCs were found to be at increased risk of depression/anxiety compared to other workers. The odds ratio (OR) is 1.52 (95% confidence interval [CI]: 1.06-2.17). In the stratified analyses, vulnerable groups were middle-aged (OR [95% CI]: 1.68 [1.10-2.54]), female (OR [95% CI]: 1.85 [1.20-2.84]), and low-income (OR [95% CI]: 3.18 [1.77-5.73]) workers. Conclusions: Our study's results reinforce those of other studies that show that DCs are at greater risk of experiencing mental health issues than other workers and that and this risk is greater for middle-aged, female, and low-income workers. These results suggest that appropriate policy efforts should be made to improve the psychological well-being of DCs.

Association between Changes in the Regularity of Working Hours and Cognitive Impairment in Middle-Aged and Older Korean Workers: The Korean Longitudinal Study of Aging, 2008-2018.

Changes in the regularity of working hours affect the cognitive function of middle-aged workers. This study investigated the association between alterations in the regularity of working hours and cognitive impairment in middle-aged and elderly Korean workers. The data from the Korean Longitudinal Study of Aging were analyzed and cognitive function was evaluated using the Korean version of the mini−mental state examination. A score of <23 points was defined as cognitive impairment. The effect of changes in the regularity of working hours on cognitive impairment development was assessed using the generalized estimating equation model. Compared with regular working hours group, the odds ratios (ORs; 95% confidence interval) of the "consistently irregular", "regular to irregular", and "irregular to regular" groups were 1.56 (1.30−1.88), 1.46 (1.20−1.77), and 1.24 (1.01−1.53), respectively. The risk of cognitive deterioration was found in the "consistently irregular" group. However, only workers with normal working hours in the "regular to irregular" group had a significant risk of cognitive deterioration (1.51 (1.21−1.89)). Altered working hours were associated with cognitive impairment in middle-aged and older workers. The study emphasizes the need to implement a standard work schedule that is suitable for middle-aged workers.

Risk of Heat-Related Mortality, Disease, Accident, and Injury Among Korean Workers: A National Representative Study From 2002 to 2015.

Many studies have shown that heat waves can cause both death and disease. Considering the adverse health effects of heat waves on vulnerable groups, this study highlights their impact on workers. The present study thus investigated the association between heat exposure and the likelihood of hospitalization and death, and further identified the risk of heat-related diseases or death according to types of heat and dose-response modeling with heat threshold. Workers were selected from the Korean National Health Insurance Service-National Sample Cohort 2002-2015, and regional data measured by the Korea Meteorological Administration were used for weather information. The relationship between hospitalization attributable to disease and weather variables was analyzed by applying a generalized additional model. Using the Akaike information criterion, we selected a model that presented the optimal threshold. Maximum daily temperature (MaxT) was associated with an increased risk of death and outdoor mortality. The association between death outdoors and MaxT had a threshold of 31.2°C with a day zero lag effect. History of medical facility visits due to the health effects of heat waves was evident in certain infectious and parasitic diseases (A and B), cardio and cerebrovascular diseases (I20-25 and I60-69), injury, poisoning, and other consequences of external causes (S, T). The study demonstrated that heat exposure is a risk factor for death and infectious, cardio-cerebrovascular, and genitourinary diseases, as well as injuries or accidents among workers. The finding that heat exposure affects workers' health has future implications for decision makers and researchers.

Adsorptive removal of dyes from wastewater using a metal-organic framework: A review.

Water pollution from synthetic dyes is a growing environmental concern because many dyes have carcinogenic effects on humans and aquatic life. Adsorption is a widely used technology for the separation and removal of dyes from wastewater. However, the dye removal process using conventional adsorbents is not sufficiently efficient for industrial wastewater. Metal-organic frameworks (MOFs) addresses these drawbacks. MOF showed excellent dye removal and degradation capacity owing to its multifunctionality, water-stability, large surface area, tunable pore size and recyclability. Magnetic MOFs retained excellent performance up to several consecutive cycles. Modified MOFs performed as Fenton-like catalysis process which generated abundant reactive radicals that degraded complex organic dyes into simple and less toxic forms which were further adsorbed onto the MOF. This review systematically compiles in-depth studies on the adsorptive removal of dyes from wastewater, MOF adsorption mechanisms, major influencing factors, to adsorption efficiency of MOFs. While all MOFs adsorb dyes through electrostatic attraction, the type of MOF, presence of functional groups, ligands, and pH significantly control the adsorption mechanism. Before developing an MOF, optimization and upgradation of factors and interaction between available adsorption site and adsorbate is needed. Finally, the prospects and new frontiers of MOFs in sustainable water treatment is discussed.