Assessment of Wet Season Precipitation in the Central United States by the Regional Climate Simulation of the WRFG Member in NARCCAP and Its Relationship with Large-Scale Circulation Biases

Assessment of past-climate simulations of regional climate models(RCMs)is important for understanding the reliability of RCMs when used to project future regional climate.Here,we assess the performance and discuss possible causes of biases in a WRF-based RCM with a grid spacing of 50 km,named WRFG,from the North American Regional Climate Change Assessment Program(NARCCAP)in simulating wet season precipitation over the Central United States for a period when observational data are available.The RCM reproduces key features of the precipitation distribution characteristics during late spring to early summer,although it tends to underestimate the magnitude of precipitation.This dry bias is partially due to the model’s lack of skill in simulating nocturnal precipitation related to the lack of eastward propagating convective systems in the simulation.Inaccuracy in reproducing large-scale circulation and environmental conditions is another contributing factor.The too weak simulated pressure gradient between the Rocky Mountains and the Gulf of Mexico results in weaker southerly winds in between,leading to a reduction of warm moist air transport from the Gulf to the Central Great Plains.The simulated low-level horizontal convergence fields are less favorable for upward motion than in the NARR and hence,for the development of moist convection as well.Therefore,a careful examination of an RCM’s deficiencies and the identification of the source of errors are important when using the RCM to project precipitation changes in future climate scenarios.

Association of physical activity with risk of chronic kidney disease in China:A population-based cohort study

Background:Information on the association between physical activity(PA)and the risk of chronic kidney disease(CKD)is limited.We aimed to explore the associations of total,domain-specific,and intensity-specific PA with CKD and its subtypes in China.Methods:The study included 475,376 adults from the China Kadoorie Biobank aged 30-79 years during 2004-2008 at baseline.An interviewer-administered questionnaire was used to collect the information about PA,which was quantified as metabolic equivalent of task hours per day(MET-h/day)and categorized into 4 groups based on quartiles.Cox regression was used to analyze the association between PA and CKD risk.Results:During a median follow-up of 12.1 years,5415 incident CKD cases were documented,including 1159 incident diabetic kidney disease(DKD)cases and 362 incident hypertensive nephropathy(HTN)cases.Total PA was inversely associated with CKD risk,with an adjusted hazard ratio(HR,95%confidence interval(95%CI))of 0.83(0.75-0.92)for incident CKD in the highest quartile of total PA as compared with participants in the lowest quartile.Similar results were observed for risk of DKD and HTN,and the corresponding HRs(95%CIs)were 0.75(0.58-0.97)for DKD risk and 0.56(0.37-0.85)for HTN risk.Increased nonoccupational PA,low-intensity PA,and moderate-to-vigorous-intensity PA were significantly associated with a decreased risk of CKD,with HRs(95%CIs)of 0.80(0.73-0.88),0.85(0.77-0.94),and 0.85(0.76-0.95)in the highest quartile,respectively.Conclusion:PA,including nonoccupational PA,low-intensity PA,and moderate-to-vigorous-intensity PA,was inversely associated with the risk of CKD,including DKD,HTN,and other CKD,and such associations were dose dependent.

The association of diet quality and physical activity with cardiovascular disease and mortality in 85,545 older Australians:A longitudinal study

Background:A quality diet and an active lifestyle are both important cornerstones of cardiovascular disease(CVD)prevention.However,despite their interlinked effects on metabolic health,the 2 behaviors are rarely considered jointly,particularly within the context of CVD prevention.We examined the independent,interactive,and joint associations of diet and physical activity with CVD hospitalization,CVD mortality,and all-cause mortality.Methods:CVD-free Australian participants aged 4574 years(n=85,545)reported physical activity,diet,sociodemographic,and lifestyle characteristics at baseline(20062009)and follow-up(20122015),and data were linked to hospitalization and death registries(03/31/2019 for CVD hospitalization and all-cause mortality and 12/08/2017 for CVD mortality).Diet quality was categorized as low,medium,and high based on meeting dietary recommendations.Physical activity was operationalized as(a)total moderate-to-vigorous physical activity(MVPA)as per guidelines,and(b)the composition of MVPA as the ratio of vigorous-intensity physical activity(VPA)to total MVPA.We used a left-truncated cause-specific Cox proportional hazards model using time-varying covariates.Results:During a median of 10.7 years of follow-up,6576 participants were admitted to the hospital for CVD and 6581 died from all causes(876 from CVD during 9.3 years).A high-quality diet was associated with a 17%lower risk of all-cause mortality than a low-quality diet,and the highest MVPA category(compared with the lowest)was associated with a 44%and 48%lower risk of CVD and all-cause mortality,respectively.Multiplicative interactions between diet and physical activity were non-significant.For all outcomes,the lowest risk combinations involved a high-quality diet and the highest MVPA categories.Accounting for total MVPA,some VPA was associated with further risk reduction of CVD hospitalization and all-cause mortality.Conclusion:For CVD prevention and longevity,one should adhere to both a healthy diet and an active lifestyle and incorporate some VPA when possible.

Association between physical activity and risk of gastroesophageal reflux disease:A systematic review and meta-analysis

Background:Lifestyle plays an important role in preventing and managing gastroesophageal reflux disease(GERD).In response to the conflicting results in previous studies,we performed a systematic review and meta-analysis to investigate this association.Methods:Relevant studies published until January 2023 were retrieved from 6 databases,and the prevalence of symptomatic gastroesophageal reflux(GER)or GERD was determined from the original studies.A random effects model was employed to meta-analyze the association by computing the pooled relative risk(RR)with 95%confidence intervals(95%CIs).Furthermore,subgroup and dose-response analyses were performed to explore subgroup differences and the association between cumulative physical activity(PA)time and GERD.Results:This meta-analysis included 33 studies comprising 242,850 participants.A significant negative association was observed between PA and the prevalence of symptomatic GER(RR=0.74,95%CI:0.66-0.83;p<0.01)or GERD(RR=0.80,95%CI:0.76-0.84;p<0.01),suggesting that engaging in PA might confer a protective benefit against GERD.Subgroup analyses consistently indicated the presence of this association across nearly all subgroups,particularly among the older individuals(RR_(<40 years):RR_(≥40 years)=0.85:0.69,p<0.01)and smokers(RR_(smoker):RR_(non-smoker)=0.67:0.82,p=0.03).Furthermore,a dose-response analysis revealed that individuals who engaged in 150 min of PA per week had a 72.09%lower risk of developing GERD.Conclusion:Maintaining high levels of PA decreased the risk of GERD,particularly among older adults and smokers.Meeting the recommended PA level of 150 min per week may significantly decrease the prevalence of GERD.

Association of daily sitting time and leisure-time physical activity with body fat among U.S.adults

Background:Prolonged sitting and reduced physical activity lead to low energy expenditures.However,little is known about the joint impact of daily sitting time and physical activity on body fat distribution.We investigated the independent and joint associations of daily sitting time and physical activity with body fat among adults.Methods:This was a cross-sectional analysis of U.S.nationally representative data from the National Health and Nutrition Examination Survey2011-2018 among adults aged 20 years or older.Daily sitting time and leisure-time physical activity(LTPA)were self-reported using the Global Physical Activity Questionnaire.Body fat(total and trunk fat percentage)was determined via dual X-ray absorptiometry.Results:Among 10,808 adults,about 54.6%spent 6 h/day or more sitting;more than one-half reported no LTPA(inactive)or less than 150 min/week LTPA(insufficiently active)with only 43.3%reported 150 min/week or more LTPA(active)in the past week.After fully adjusting for sociodemographic data,lifestyle behaviors,and chronic conditions,prolonged sitting time and low levels of LTPA were associated with higher total and trunk fat percentages in both sexes.When stratifying by LTPA,the association between daily sitting time and body fat appeared to be stronger in those who were inactive/insuufficiently active.In the joint analyses,inactive/insuufficiently active adults who reported sitting more than 8 h/day had the highest total(female:3.99%(95%confidence interval(95%CI):3.09%-4.88%);male:3.79%(95%CI:2.75%-4.82%))and trunk body fat percentages(female:4.21%(95%CI:3.09%-5.32%);male:4.07%(95%CI:2.95%-5.19%))when compared with those who were active and sitting less than 4 h/day.Conclusion:Prolonged daily sitting time was associated with increased body fat among U.S.adults.The higher body fat associated with 6 h/day sitting may not be offset by achieving recommended levels of physical activity.

Bridging the gap:Unveiling the crisis of physical inactivity in inflammatory bowel diseases

In this editorial we comment on the article titled“Inflammatory bowel diseases patients suffer from significant low levels and barriers to physical activity:The BE-FIT-IBD study”published in a recent issue of the World Journal of Gastroen-terology 2023;29(41):5668-5682.Inflammatory bowel diseases(IBD)are emerging as a significant global health concern as their incidence continues to rise on a global scale,with detrimental impacts on quality of life.While many advances have been made regarding the management of the disease,physical inactivity in these patients represents an underexplored issue that may hold the key for further and better understanding the ramifications of IBD.Chronic pain,fatigue,and fear of exacerbating symptoms promotes physical inactivity among IBD patients,while the lack of clear guidelines on safe exercise regimens contributes to a norm of physical inactivity.Physical activity(PA)is accepted to have a positive effect on disease outcomes and quality of life,while inactivity exacerbates comorbidities like cardiovascular disease and mental health disorders.The“BE-FIT-IBD”study,focusing on PA levels and barriers in IBD patients of Southern Italy,revealed that a significant proportion(42.9%)were physically inactive.This lack of PA is attributed to barriers such as fear of flare-ups and misconceptions about exercise exacerbating the disease.The study also highlighted the need for better communication between healthcare providers and patients regarding the benefits of PA and safe incorporation into lifestyles.Moreover,physical inactivity may also contribute to disability in IBD patients,having a great impact on employment status.Of note is the fact that IBD also comes with an important psychological burden with relevant evidence suggesting that regular PA can improve mood,reduce anxiety,and enhance mental health.The“BE-FIT-IBD”study advocated for the integration of PA into IBD management,emphasizing the bidirectional link between PA and IBD.Regular exercise can influence the course of IBD,potentially reducing symptom severity and prolonging remission periods.As such,it is mandatory that healthcare providers actively educate patients,dispel misconceptions,and tailor exercise recommendations to improve the quality of life and reduce IBD-related complications.

Association of accelerometer-measured sleep duration and different intensities of physical activity with incident type 2 diabetes in a population-based cohort study

Purpose:The aim of the current study was to investigate the association of accelerometer-measured sleep duration and different intensities of physical activity(PA)with the risk of incident type 2 diabetes in a population-based prospective cohort study.Methods:Altogether,88,000 participants(mean age=62.2±7.9 years,mean±SD)were included from the UK Biobank.Sleep duration(short:<6 h/day;normal:6-8 h/day;long:>8 h/day)and PA of different intensities were measured using a wrist-won accelerometer over a 7-day period between 2013 and 2015.PA was classified according to the median or World Health Organization-recommendation:total volume of PA(high,low),moderate-to-vigorous PA(MVPA)(recommended,not recommended),and light-intensity PA(high,low).Incidence of type 2diabetes was ascertained using hospital records or death registries.Results:During a median follow-up of 7.0 years,1615 incident type 2 diabetes cases were documented.Compared with normal sleep duration,short(hazard ratio(HR)=1.21,95%confidence interval(95%CI):1.03-1.41)but not long sleep duration(HR=1.01,95%CI:0.89-1.15)was associated with excessive type 2 diabetes risk.This increased risk among short sleepers seems to be protected against by PA.Compared with normal sleepers with high or recommended PA,short sleepers with low volume of PA(HR=1.81,95%CI:1.46-2.25),not recommended(below the World Health Organization-recommended level of)MVPA(HR=1.92,95%CI:1.55-2.36),or low light-intensity PA(HR=1.49,95%CI:1.13-1.90)had a higher risk of type 2 diabetes,while short sleepers with a high volume of PA(HR=1.14,95%CI:0.88-1.49),recommended MVPA(HR=1.02,95%CI:0.71-1.48),or high light-intensity PA(HR=1.14,95%CI:0.92-1.41)did not.Conclusion:Accelerometer-measured short but not long sleep duration was associated with a higher risk of incident type 2 diabetes.A higher level of PA,regardless of intensity,potentially ameliorates this excessive risk.

Shifting the Paradigm:A Fresh Look at Physical Activity Frequency and Its Impact on Mental Health,Life Satisfaction,and Self-Rated Health in Adolescents

As adolescent mental health problems are becoming a more serious issue globally,this paper explores the relationship of physical activity in adolescents and its frequency on mental health as well as examines the mediating effects of life satisfaction and self-rated health in order to provide a reference for the promotion of mental health in adolescents.A sample of 3578 Chinese high school students completed questionnaires assessing their mental health,physical activity frequency,life satisfaction,and self-rated health.The mean SCL-90 value for adolescents was found to be 1.629%,and 24.73%of adolescents had varying degrees of mental health issue.Increased physical activity frequency is positively associated with improved mental health(p<0.001).Additionally,life satisfaction and self-rated health were found to play significant mediating roles in the relationship between physical activity frequency and mental health.Specifically,low-frequency physical activity had the most pronounced mediating effect on mental health through life satisfaction,while high-frequency physical activity exerted the most significant mediating effect on mental health through self-rated health.These findings underscore the importance of promoting physical activity among adolescents and highlight the distinct pathways through which physical activity frequency can influence mental health outcomes.Further research is needed to explore these relationships in diverse populations and settings,as well as to develop targeted intervention.

Structure and immunomodulatory activity of Lentinus edodes polysaccharides modified by probiotic fermentation

Plant-based fermentations provide an untapped source for novel biotechnological applications.In this study,a probiotic named Lactobacillus fermentum 21828 was introduced to ferment Lentinus edodes.Polysaccharides were extracted from fermented and non-fermented L.edodes and purified via DEAE-52 and Sephadex G-100.The components designated F-LEP-2a and NF-LEP-2a were analyzed by FT-IR,HPGPC,HPAEC,SEM,GC-MS and NMR.The results revealed that probiotic fermentation increased the molecular weight from 1.16×10^(4) Da to 1.87×10^(4) Da and altered the proportions of glucose,galactose and mannose,in which glucose increased from 45.94%to 48.16%.Methylation analysis and NMR spectra indicated that F-LEP-2a and NF-LEP-2a had similar linkage patterns.Furthermore,their immunomodulatory activities were evaluated with immunosuppressive mice.NF-LEP and F-LEP improved immune organ indices,immunoglobulin(Ig G and Ig M)and cytokines concentrations;restored the antioxidation capacity of liver;and maintained the balance of gut microbiota.F-LEP displayed better moderating effects on the spleen index,immunoglobulin,cytokines and the diversity of gut microbiota than NF-LEP(200,400 mg/kg).Our study provides an efficient and environment-friendly way for the structural modification of polysaccharides,which helps to enhance their biological activity and promote their wide application in food,medicine and other fields.

A Two-Layer Encoding Learning Swarm Optimizer Based on Frequent Itemsets for Sparse Large-Scale Multi-Objective Optimization

Traditional large-scale multi-objective optimization algorithms(LSMOEAs)encounter difficulties when dealing with sparse large-scale multi-objective optimization problems(SLM-OPs)where most decision variables are zero.As a result,many algorithms use a two-layer encoding approach to optimize binary variable Mask and real variable Dec separately.Nevertheless,existing optimizers often focus on locating non-zero variable posi-tions to optimize the binary variables Mask.However,approxi-mating the sparse distribution of real Pareto optimal solutions does not necessarily mean that the objective function is optimized.In data mining,it is common to mine frequent itemsets appear-ing together in a dataset to reveal the correlation between data.Inspired by this,we propose a novel two-layer encoding learning swarm optimizer based on frequent itemsets(TELSO)to address these SLMOPs.TELSO mined the frequent terms of multiple particles with better target values to find mask combinations that can obtain better objective values for fast convergence.Experi-mental results on five real-world problems and eight benchmark sets demonstrate that TELSO outperforms existing state-of-the-art sparse large-scale multi-objective evolutionary algorithms(SLMOEAs)in terms of performance and convergence speed.

Enhancing Evolutionary Algorithms With Pattern Mining for Sparse Large-Scale Multi-Objective Optimization Problems

Sparse large-scale multi-objective optimization problems(SLMOPs)are common in science and engineering.However,the large-scale problem represents the high dimensionality of the decision space,requiring algorithms to traverse vast expanse with limited computational resources.Furthermore,in the context of sparse,most variables in Pareto optimal solutions are zero,making it difficult for algorithms to identify non-zero variables efficiently.This paper is dedicated to addressing the challenges posed by SLMOPs.To start,we introduce innovative objective functions customized to mine maximum and minimum candidate sets.This substantial enhancement dramatically improves the efficacy of frequent pattern mining.In this way,selecting candidate sets is no longer based on the quantity of nonzero variables they contain but on a higher proportion of nonzero variables within specific dimensions.Additionally,we unveil a novel approach to association rule mining,which delves into the intricate relationships between non-zero variables.This novel methodology aids in identifying sparse distributions that can potentially expedite reductions in the objective function value.We extensively tested our algorithm across eight benchmark problems and four real-world SLMOPs.The results demonstrate that our approach achieves competitive solutions across various challenges.

A semantic vector map-based approach for aircraft positioning in GNSS/GPS denied large-scale environment

Accurate positioning is one of the essential requirements for numerous applications of remote sensing data,especially in the event of a noisy or unreliable satellite signal.Toward this end,we present a novel framework for aircraft geo-localization in a large range that only requires a downward-facing monocular camera,an altimeter,a compass,and an open-source Vector Map(VMAP).The algorithm combines the matching and particle filter methods.Shape vector and correlation between two building contour vectors are defined,and a coarse-to-fine building vector matching(CFBVM)method is proposed in the matching stage,for which the original matching results are described by the Gaussian mixture model(GMM).Subsequently,an improved resampling strategy is designed to reduce computing expenses with a huge number of initial particles,and a credibility indicator is designed to avoid location mistakes in the particle filter stage.An experimental evaluation of the approach based on flight data is provided.On a flight at a height of 0.2 km over a flight distance of 2 km,the aircraft is geo-localized in a reference map of 11,025 km~2using 0.09 km~2aerial images without any prior information.The absolute localization error is less than 10 m.

Online identification and extraction method of regional large-scale adjustable load-aggregation characteristics

This article introduces the concept of load aggregation,which involves a comprehensive analysis of loads to acquire their external characteristics for the purpose of modeling and analyzing power systems.The online identification method is a computer-involved approach for data collection,processing,and system identification,commonly used for adaptive control and prediction.This paper proposes a method for dynamically aggregating large-scale adjustable loads to support high proportions of new energy integration,aiming to study the aggregation characteristics of regional large-scale adjustable loads using online identification techniques and feature extraction methods.The experiment selected 300 central air conditioners as the research subject and analyzed their regulation characteristics,economic efficiency,and comfort.The experimental results show that as the adjustment time of the air conditioner increases from 5 minutes to 35 minutes,the stable adjustment quantity during the adjustment period decreases from 28.46 to 3.57,indicating that air conditioning loads can be controlled over a long period and have better adjustment effects in the short term.Overall,the experimental results of this paper demonstrate that analyzing the aggregation characteristics of regional large-scale adjustable loads using online identification techniques and feature extraction algorithms is effective.

Large-Scale Multi-Objective Optimization Algorithm Based on Weighted Overlapping Grouping of Decision Variables

The large-scale multi-objective optimization algorithm(LSMOA),based on the grouping of decision variables,is an advanced method for handling high-dimensional decision variables.However,in practical problems,the interaction among decision variables is intricate,leading to large group sizes and suboptimal optimization effects;hence a large-scale multi-objective optimization algorithm based on weighted overlapping grouping of decision variables(MOEAWOD)is proposed in this paper.Initially,the decision variables are perturbed and categorized into convergence and diversity variables;subsequently,the convergence variables are subdivided into groups based on the interactions among different decision variables.If the size of a group surpasses the set threshold,that group undergoes a process of weighting and overlapping grouping.Specifically,the interaction strength is evaluated based on the interaction frequency and number of objectives among various decision variables.The decision variable with the highest interaction in the group is identified and disregarded,and the remaining variables are then reclassified into subgroups.Finally,the decision variable with the strongest interaction is added to each subgroup.MOEAWOD minimizes the interactivity between different groups and maximizes the interactivity of decision variables within groups,which contributed to the optimized direction of convergence and diversity exploration with different groups.MOEAWOD was subjected to testing on 18 benchmark large-scale optimization problems,and the experimental results demonstrate the effectiveness of our methods.Compared with the other algorithms,our method is still at an advantage.

A Large-Scale Group Decision Making Model Based on Trust Relationship and Social Network Updating

With the development of big data and social computing,large-scale group decisionmaking(LGDM)is nowmerging with social networks.Using social network analysis(SNA),this study proposes an LGDM consensus model that considers the trust relationship among decisionmakers(DMs).In the process of consensusmeasurement:the social network is constructed according to the social relationship among DMs,and the Louvain method is introduced to classify social networks to form subgroups.In this study,the weights of each decision maker and each subgroup are computed by comprehensive network weights and trust weights.In the process of consensus improvement:A feedback mechanism with four identification and two direction rules is designed to guide the consensus of the improvement process.Based on the trust relationship among DMs,the preferences are modified,and the corresponding social network is updated to accelerate the consensus.Compared with the previous research,the proposedmodel not only allows the subgroups to be reconstructed and updated during the adjustment process,but also improves the accuracy of the adjustment by the feedbackmechanism.Finally,an example analysis is conducted to verify the effectiveness and flexibility of the proposed method.Moreover,compared with previous studies,the superiority of the proposed method in solving the LGDM problem is highlighted.

Phytochemical Analysis and Antimicrobial Activity of Lawsonia inermis Leaf Extracts from Burkina Faso

Lawsonia inermis is a hairless plant growing in various regions of North Africa, the Indian subcontinent, and the Middle East. It possesses many medicinal attributes, including curative properties against infectious dermatoses. This study was carried out to evaluate the phytochemical profile of the crude ethanolic extract of the plant leaves and its fractions as well as their antimicrobial activities. The phytochemical profile was performed using high-performance thin-layer chromatography (HPTLC), gas chromatography-mass spectrometry (GC-MS), and high-performance liquid chromatography (HPLC). Additionally, the phenolic and flavonoid contents were determined using the Folin-Ciocalteu spectrophotometric and the aluminum trichloride methods. Antimicrobial activity was tested using disc diffusion and microdilution methods. The presence of flavonoids, tannins, sterols, and triterpenes was revealed. GC-MS detected twelve compounds main compounds consisting of saturated and unsaturated fatty acids and phenolic and terpenoid compounds among twenty-seven components. HPLC also detected high contents of phenolic acids and flavonoids. The most abundant triterpene and sterols were ursolic acid (around 43.14 g/100g DW, 13.9 g/100g dry weight (DW), and 0.68 g/100g DW) in the crude ethanolic extract of leaves (FeLi), hexane fraction (FHLi) and dichloromethane fraction (FDLi), respectively and, β-sitosterol in FeLi (56.7 mg/100g DW), FHLi (10.55 g/100g DW), FDLi (106.1 mg/100g DW) and butanol fraction (FBLi) (357.4 mg/100g DW). Among the flavonoids, rutin = 3.24 g/100g and quercetin = 0.63 g/100g in the ethanolic extract, rutin = 15.73 g/100g in the dichloromethane fraction, and rutin = 0.23 g/100g) in the aqueous fraction;and among phenolic compounds, caffeic acid (37.65 g/100g DW) and vanillic acid (22.70 g/100g DW) were the most important in the ethyl acetate fraction (FAeLi). All organic fractions exhibited interesting antibacterial and antifungal activities against the tested strains, with the best activity recorded with the dichloromethane and ethyl acetate fractions. The leaf extracts’ phytochemical profile and antimicrobial activity support the use of Lawsonia inermis against infectious skin diseases.

“Active Feedback” Fitbit-Based Physical Activity and Sleep Hygiene Intervention for Memory Assessment Service (MAS) Patients with Cognitive Deficits: Feasibility, Acceptability, Sleep Quality, Stress, and Wellbeing Outcomes

Research Background: Compared to the general population, people experiencing age-related cognitive decline are more likely to have low levels of physical activity and sleep problems. Sufficient physical activity and quality sleep are protective factors against cognitive decline and poor health and can improve coping with stressors. The “Active Feedback” intervention comprises a wearable activity and sleep tracker (Fitbit), access to Fitbit software healthy lifestyle software apps;one session with Memory Assessment Service (MAS) staff providing physical activity and sleep hygiene advice and two further engagement, discussion, and feedback sessions. Purpose/Aim: This study investigates the acceptability and feasibility of Active Feedback and the effect on stress, mental wellbeing, and sleep quality, and the links between these factors. Methods: An open-label patient cohort design with no control group was used. Pre-intervention, 4-week and 8-week intervention assessments were performed using participant self-report measures: Perceived Stress Scale (PSS), Warwick-Edinburgh Mental Wellbeing Scale (WEMWBS), and Sleep Conditioning Index (SCI). Twenty-five participants completed an eight-week three-session intervention (18 males and 7 females), with the age range of 66 - 84 years old, and average age of 73.8 years (SD = 5.09). Fifteen participants had a diagnosis of MCI, ten participants did not. Results: There were non-significant improvements in SCI scores from 21.0 (SD = 8.84) to 21.6 (SD = 6.20) at 8 weeks, PSS scores from 17.5 (SD = 5.89) to 17.0 (SD = 6.20) at 8 weeks, and WEMWBS scores from 46.9 (SD = 9.23) to 48.8 (SD = 9.69) at 8 weeks. There were negative correlations between WEMWBS and PSS. Conclusion: Active Feedback intervention was found to be feasible and acceptable. Active Feedback could be enhanced to include motivational interviewing and goal setting.

Evaluation of Four Anthropogenic Activity Impacts on Heavy Metal Quality of the Kumba River in the South West Region of Cameroon

Anthropogenic activities have contributed to pollution of water bodies through deposition of diverse pollutants amongst which are heavy metals. These pollutants, which at times are above the maximum concentration levels recommended, are detrimental to the quality of the water, soil and crops (plant) with subsequent human health risks. The objective of the work was to evaluate the impacts of human-based activities on the heavy metal properties of surface water with focus on the Kumba River basin. Field observations, interviews, field measurements and laboratory analyses of different water samples enabled us to collect the different data. The results show four main human-based activities within the river basin (agriculture, livestock production, domestic waste disposal and carwash activities) that pollute surface water. Approximately 20.61 tons of nitrogen and phosphorus from agricultural activities, 156.48 tons of animal wastes, 2517.5 tons of domestic wastes and 1.52 tons of detergent from carwash activities were deposited into the river each year. A highly significant difference at 1% was observed between the upstream and downstream heavy metal loads in four of the five heavy metals tested except for copper that was not significant. Lead concentrations were highest in all the activities with an average of 2.4 mg∙L−1 representing 57.81%, followed by zinc with 1.596 mg∙L−1 (38.45%) and manganese with 0.155 mg∙L−1 (3.74%) for the different anthropogenic activities thus indicating that these activities highly lead to pollution of the Kumba River water. The level of zinc and manganese was significantly influenced at ρ 005 by anthropogenic activities though generally the variations were in the order: carwash (3.196 mg∙L−1) < domestic waste disposal (3.347 mg∙L−1) < agriculture (4.172 mg∙L−1) < livestock (4.886 mg∙L−1) respectively and leading to a total of 14.04 tons of heavy metal pollutants deposited each day.

Total Alkaloid Content, Total Phenolic Content, In Vitro Antioxidant Activity, and Preliminary Antiglycemic Potential of the Methanol Extract from Mozambican Wild Fruits of Vangueria infausta

This study investigated the antioxidant activity and alpha-amylase inhibitory potential of the methanolic extract from Vangueria infausta fruits with the aim of exploring its therapeutic and nutritional applications. Bioactive compounds such as total phenolics (TPC) and total alkaloids (TAC) were analyzed. Antioxidant activity was assessed using the DPPH, ABTS, FRAP, Ferrozine, Phosphomolybdate, and Folin-Ciocalteu methods, while alpha-amylase inhibitory activity was determined using the 3,5-Dinitrosalicylic Acid (DNSA) and 2-chloro-p-nitrophenyl-α-D-maltotrioside (CNPG3) methods. The results revealed significant variations in antioxidant activity across the methods used, with IC50 values ranging from 318.42 to 1255.56 µg/mL. Alpha-amylase inhibition was also significant, with IC50 values ranging from 140.85 to 121.06 µg/mL. The TPC was found to be 95.6 mg of gallic acid equivalent per 100 g of dry powder, and the TAC was 0.188 mg of atropine equivalent per 100 g of dry powder. These findings suggest that Vangueria infausta possesses promising antioxidant and alpha-amylase inhibitory potential, indicating its potential application in antioxidant therapies and in the management of carbohydrate digestion.

Research progress on catalysts for organic sulfur hydrolysis: Review of activity and stability

The removal of organic sulfur through catalytic hydrolysis is a significant area of research in the field of desulfurization.This review provides an overview of recent advancements in catalytic hydrolysis technology of organic sulfur,including the activity,stability,and atmosphere effects of hydrolysis catalysts.The emphasis is on strategies for enhancing hydrolysis activity and anti-oxygen poisoning property of catalysts.Surface modification,metal doping and nitrogen doping have been found to improve the activity of catalysts.Alkaline components modification is the most commonly used method,the formation of oxygen vacancies through metal doping and creation of nitrogen basic sites through nitrogen doping also contribute to the hydrolysis of organic sulfur.The strategies for anti-oxygen poisoning are discussed in a systematic manner.The structural regulation of catalysts is beneficial for the desorption and diffusion of hydrogen sulfide(H_(2)S),thereby effectively inhibiting its oxidation.Nitrogen doping and the addition of electronic promoters such as transition metals can protect active sites and decrease the number of active oxygen species.These methods have been proven to enhance the anti-poisoning performance of catalysts.Additionally,this article summarizes how different atmospheres affect the activity of hydrolysis catalysts.The objective of this review is to pave the way for the development of efficient,stable and widely used catalysts for organic sulfur hydrolysis.