Study of Zero-Inflated Regression Models in a Large-Scale Population Survey of Sub-Health Status and Its Influencing Factors

Objective Sub-health status has progressively gained more attention from both medical professionals and the publics. Treating the number of sub-health symptoms as count data rather than dichotomous data helps to completely and accurately analyze findings in sub-healthy population. This study aims to compare the goodness of fit for count outcome models to identify the optimum model for sub-health study.Methods The sample of the study derived from a large-scale population survey on physiological and psychological constants from 2007 to 2011 in 4 provinces and 2 autonomous regions in China. We constructed four count outcome models using SAS: Poisson model, negative binomial (NB) model, zero-inflated Poisson (ZIP) model and zero-inflated negative binomial (ZINB) model. The number of sub-health symptoms was used as the main outcome measure. The alpha dispersion parameter and O test were used to identify over-dispersed data, and Vuong test was used to evaluate the excessive zero count. The goodness of fit of regression models were determined by predictive probability curves and statistics of likelihood ratio test.Results Of all 78 307 respondents, 38.53% reported no sub-health symptoms. The mean number of sub-health symptoms was 2.98, and the standard deviation was 3.72. The statistic O in over-dispersion test was 720.995 (P<0.001); the estimated alpha was 0.618 (95% CI: 0.600-0.636) comparing ZINB model and ZIP model; Vuong test statistic Z was 45.487. These results indicated over-dispersion of the data and excessive zero counts in this sub-health study. ZINB model had the largest log likelihood (-167 519), the smallest Akaike’s Information Criterion coefficient (335 112) and the smallest Bayesian information criterion coefficient (335455),indicating its best goodness of fit. The predictive probabilities for most counts in ZINB model fitted the observed counts best. The logit section of ZINB model analysis showed that age, sex, occupation, smoking, alcohol drinking, ethnicity and obesity were determinants for presence of sub-health symptoms; the binomial negative section of ZINB model analysis showed that sex, occupation, smoking, alcohol drinking, ethnicity, marital status and obesity had significant effect on the severity of sub-health.Conclusions All tests for goodness of fit and the predictive probability curve produced the same finding that ZINB model was the optimum model for exploring the influencing factors of sub-health symptoms.

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.

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.

KCNQ1 rs2237895 gene polymorphism increases susceptibility to type 2 diabetes mellitus in Asian populations

BACKGROUND The association of single nucleotide polymorphism of KCNQ1 gene rs2237895 with type 2 diabetes mellitus(T2DM)is currently controversial.It is unknown whether this association can be gene realized across different populations.AIM To determine the association of KCNQ1 rs2237895 with T2DM and provide reliable evidence for genetic susceptibility to T2DM.METHODS We searched PubMed,Embase,Web of Science,Cochrane Library,Medline,Baidu Academic,China National Knowledge Infrastructure,China Biomedical Literature Database,and Wanfang to investigate the association between KCNQ1 gene rs2237895 and the risk of T2DM up to January 12,2022.Review Manager 5.4 was used to analyze the association of the KCNQ1 gene rs2237895 polymorphism with T2DM and to evaluate the publication bias of the selected literature.RESULTS Twelve case–control studies(including 11273 cases and 11654 controls)met our inclusion criteria.In the full population,allelic model[odds ratio(OR):1.19;95%confidence interval(95%CI):1.09–1.29;P<0.0001],recessive model(OR:1.20;95%CI:1.11–1.29;P<0.0001),dominant model(OR:1.27.95%CI:1.14–1.42;P<0.0001),and codominant model(OR:1.36;95%CI:1.15–1.60;P=0.0003)(OR:1.22;95%CI:1.10–1.36;P=0.0002)indicated that the KCNQ1 gene rs2237895 polymorphism was significantly correlated with susceptibility to T2DM.In stratified analysis,this association was confirmed in Asian populations:allelic model(OR:1.25;95%CI:1.13–1.37;P<0.0001),recessive model(OR:1.29;95%CI:1.11–1.49;P=0.0007),dominant model(OR:1.35;95%CI:1.20–1.52;P<0.0001),codominant model(OR:1.49;95%CI:1.22–1.81;P<0.0001)(OR:1.26;95%CI:1.16–1.36;P<0.0001).In non-Asian populations,this association was not significant:Allelic model(OR:1.06,95%CI:0.98–1.14;P=0.12),recessive model(OR:1.04;95%CI:0.75–1.42;P=0.83),dominant model(OR:1.06;95%CI:0.98–1.15;P=0.15),codominant model(OR:1.08;95%CI:0.82–1.42;P=0.60.OR:1.15;95%CI:0.95–1.39;P=0.14).CONCLUSION KCNQ1 gene rs2237895 was significantly associated with susceptibility to T2DM in an Asian population.Carriers of the C allele had a higher risk of T2DM.This association was not significant in non-Asian populations.

Evaluating the performance of genomic selection on purebred population by incorporating crossbred data in pigs

Genomic selection(GS)has been widely used in livestock,which greatly accelerated the genetic progress of complex traits.The population size was one of the significant factors affecting the prediction accuracy,while it was limited by the purebred population.Compared to directly combining two uncorrelated purebred populations to extend the reference population size,it might be more meaningful to incorporate the correlated crossbreds into reference population for genomic prediction.In this study,we simulated purebred offspring(PAS and PBS)and crossbred offspring(CAB)base on real genotype data of two base purebred populations(PA and PB),to evaluate the performance of genomic selection on purebred while incorporating crossbred information.The results showed that selecting key crossbred individuals via maximizing the expected genetic relationship(REL)was better than the other methods(individuals closet or farthest to the purebred population,CP/FP)in term of the prediction accuracy.Furthermore,the prediction accuracy of reference populations combining PA and CAB was significantly better only based on PA,which was similar to combine PA and PAS.Moreover,the rank correlation between the multiple of the increased relationship(MIR)and reliability improvement was 0.60-0.70.But for individuals with low correlation(Cor(Pi,PA or B),the reliability improvement was significantly lower than other individuals.Our findings suggested that incorporating crossbred into purebred population could improve the performance of genetic prediction compared with using the purebred population only.The genetic relationship between purebred and crossbred population is a key factor determining the increased reliability while incorporating crossbred population in the genomic prediction on pure bred individuals.

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.

Changes in the adult sex ratio of six duck species breeding populations over two decades

Despite all efforts,long-term changes in the adult sex ratios of breeding duck populations are still unclear;this uncertainty is especially true for male-bias populations,which are often under the scrutiny of researchers lacking convenient results for the active protection of endangered species.Species with male-bias populations are usually strongly affected by a decline in population size that leads to a higher extinction risk.In this study,we examined our long-term data of the abundance of breeding populations in six duck species(Mallard Anas platyrhynchos,Gadwall Mareca strepera,Red-crested Pochard Netta rufina,Common Pochard Aythya ferina,Tufted Duck Aythya fuligula,and Common Goldeneye Bucephala clangula)from fishponds in South Bohemia,Czechia,between 2004 and 2022.This evidence was used to assess long-term changes in the adult sex ratio in these breeding populations and investigate the possible effects of the NAO index(North Atlantic Oscillation index)on them,indicating climate conditions in winter.We determined a long-term decrease of the proportion of females in the breeding season in two of the six examined species:Common Pochard and Red-crested Pochard,which is driven by the long-term increase in the number of males in contrast to the decreasing or stable number of females likely caused by different migration behaviours between females and males.In the case of Common Pochard,in breeding populations,we estimated 60-65%of males in the early 2000s rising to 75-80%in the early 2020s.However,we establish no significant effects linked to climate conditions of the previous winter in these species as a crucial cause of the changes of the proportion of females in the breeding population.

Multi Location Field Evaluation of BC1F2 Sorghum Populations for Striga Resistance in Niger

In Niger, a landlocked country, sorghum is the second staple food cultivated over the country by smallholder farmer. The crop is important for human and animal consumption. Despite its importance, the crop is affected by biotic and abiotic constraints. Among those constraints, striga has a high impact on yield. In fact, to survive, farmers are growing their local preferred sorghum varieties wish is highly sensible to the weed. Striga management is a challenge that requires a permanent solution. In addition, the development of high-yielding Striga resistant genotypes will be appreciated by farmers. The development of striga resistance will be based on the breeding population performances under farmer’s diverse environmental conditions adaptation. The main objective of this study is to evaluate two breeding populations for striga resistance in two different environments at Boulke and Dibissou in Tahoua region, to identify the early and high-yielding striga tolerant genotypes under natural infestation.

Evolution and Determinants of Population Agglomeration in Less Developed Metropolitan Areas:A Case Study of the Taiyuan Metropolitan Area,China

It is of importance to enhance the urban areas'capacity for population aggregation in underdeveloped regions,aiming to rectify the imbalanced and insufficient pattern of economic development in China.Taking the Taiyuan Metropolitan Area(TMA)in central China as a case study,this paper examines the evolutionary process and characteristics of population agglomeration from 2000 to 2020,and identifies factors associated with agglomeration and their spatial effects.The findings indicated that:1)against the background of sustained population shrinkage in the provincial area,the TMA showed a demographic trend of steady increase,albeit with a decelerated growth rate.In the metropolitan area,urban population size continued to grow rapidly,whereas the rural areas endured sustained losses.Disparities in city size continued to widen,and the polarization of concentrated population in the core cities kept increasing.2)Agglomerations in both secondary and service industries had significant positive effects on local population agglomeration,with the former effect being stronger.Regional economic development,government fiscal expenditure,and financial advancement all contributed to facilitating local population clustering.From a spatial spillover perspective,service agglomeration and financial development promoted population agglomeration in surrounding areas.Conversely,fiscal expenditure inhibited such agglomeration.As for industrial agglomeration and regional economic development,their spatial spillover effects were non-significant.The results obtained reveal several policy implications aimed at enhancing the population agglomeration capacity of the metropolitan area in underdeveloped regions during the new era.

Mercury Levels Assessment in the Population of Aby and Frambo Villages in the Vinicity of Aby Lagoon in Côte d’Ivoire (West Africa)

The Minamata Convention in the aim to protect human life and the environment, seeks to reduce mercury (Hg) by monitoring it concentrations in the environment. Artisanal and Small-scale Gold Mining (ASGM) has been identified as the most important anthropogenic source of human exposure to Hg. In this context, the main goal of this study was to assess the level of mercury in hair of two (2) populations living along two lagoons respectively Aby and Tendo, in Ivory Coast. To reach this goal, hair samples of 138 residents were collected and analyzed by using Cold Vapor Atomic Fluorescence Spectrophotometry (CV-AFS) technique for mercury concentration. Results showed that for the entire population the Hg mean was 2.34 μg/g. Also, they were ranged between 0.15 to 8.53 μg/g and presented substantial differences amongst the villages. In Aby village, we observed the highest Hg concentrations (Mean = 2.62 μg/g). Our findings showed that almost the entire sample group (82%) exceed the USEPA recommended limit, furthermore 56% of them exceed the normal level of WHO and 2% of the respondent has the unhealthy levels of mercury (≥6 μg Hg/g) of hair by WHO standards. Gender differences in hair mercury varies greatly among reports. Lower levels in women’s hair compared to men were reported in the both village. Considering age, the lowest concentrations were observed with children. However, when we take in account the age groups, data suggested that the most exposed sub-population of [18-29] years old is from Aby village in opposite at Frambo village, the same case those who were ≥ 40 years old. It’s convenient to note that, the proportion of Mercury levels would not to be neglected among studied population especially with the resident from Aby village. So, some measures need to be taken at the political level to control mercury contamination.

Comparative Study of Genetic Structure and Genetic Diversity betweenWild and Cultivated Populations of Taxus cuspidata,Northeast China

Taxus cuspidata is a rare plant with important medicinal and ornamental value.Aiming at the obvious differences between wild and cultivated populations of T.cuspidata from Northeast China,a total of 61 samples,that is,33 wild yews and 28 cultivated yews were used to analyze the differences and correlations of the kinship,genetic diversity,and genetic structure between them by specific length amplified fragment sequencing(SLAF-seq).Finally,470725 polymorphic SLAF tags and 58622 valid SNP markers were obtained.Phylogenetic analysis showed that 61 samples were classified into 2 clusters:wild populations and cultivated populations,and some wild yews were categorized into the cultivated populations;the genetic diversity analysis showed that the Nei diversity index of wild populations(0.4068)was smaller than that of cultivated populations(0.4414),and the polymorphic information content(PIC)of wild populations(0.2861)was smaller than that of cultivated populations(0.3309).The genetic differentiation analysis showed that the total populations of gene diversity(H_(t))of cultivated and wild populations were respectively 0.8159 and 0.5685,the coefficient of gene differentiation(G_(st))of cultivated and wild populations was respectively 0.3021 and 0.1068,and the gene flow(N_(m))(2.4967)of wild populations was larger than cultivated populations(0.8199).The molecular variance(AMOVA)revealed that inter-population variation accounted for 29.57%of the total genetic variation,while intra-population variation accounted for 70.42% of the total genetic variation(p<0.001),this suggested that the genetic variation in the T.cuspidata is mainly attributed to within-population factors.In conclusion,the genetic distance between geographical ecological groups of wild populations was generally smaller than that of cultivated populations,and the degree of genetic diversity and genetic differentiation was smaller than that of cultivated populations.As evident,the utilization of SLAF-seq technology enables efficient and accurate development of SNP markers suitable for genetic analysis of T.cuspidata species.These developed SNP markers can provide a molecular foundation for T.cuspidata breeding,construction of genetic maps,variety identification,and association analysis of agronomic traits.

Large-scale model testing of high-pressure grouting reinforcement for bedding slope with rapid-setting polyurethane

Bedding slope is a typical heterogeneous slope consisting of different soil/rock layers and is likely to slide along the weakest interface.Conventional slope protection methods for bedding slopes,such as retaining walls,stabilizing piles,and anchors,are time-consuming and labor-and energy-intensive.This study proposes an innovative polymer grout method to improve the bearing capacity and reduce the displacement of bedding slopes.A series of large-scale model tests were carried out to verify the effectiveness of polymer grout in protecting bedding slopes.Specifically,load-displacement relationships and failure patterns were analyzed for different testing slopes with various dosages of polymer.Results show the great potential of polymer grout in improving bearing capacity,reducing settlement,and protecting slopes from being crushed under shearing.The polymer-treated slopes remained structurally intact,while the untreated slope exhibited considerable damage when subjected to loads surpassing the bearing capacity.It is also found that polymer-cemented soils concentrate around the injection pipe,forming a fan-shaped sheet-like structure.This study proves the improvement of polymer grouting for bedding slope treatment and will contribute to the development of a fast method to protect bedding slopes from landslides.

Land-population-industry based village evolution and its influencing factors in the upper Tuojiang River

With economic development and urbanization in China,the rural settlements have experienced great change.To explore the evolution process of rural settlements in terms of land,population and industry can reveal the development law of rural spatial distribution,population structure and industrial economy in different stages and regions.Studying the development status and evolution characteristics of villages in the upper Tuojiang River basin in Southwest China in the past 20 years are of significant value.The upper Tuojiang River basin includes the main types of terrain found in the Southwest region:mountainous,plains,and hills,exhibiting a certain typicality of geographical characteristics.This study took towns and townships at the town-level scale as the basic unit of research,and constructed an evaluation system for village evolution based on'land,population,and industry'.It employed Criteria Importance Through Inter-Criteria Correlation(CRITIC)analysis to examine the characteristics of village evolution in the area from 2000 to 2020,and used geographic detector analysis to identify the leading factors affecting village evolution.The results show that:(1)From 2000 to 2010,villages in the upper Tuojiang River basin experienced significant changes,and the pace of these transformations slowed from 2010 to 2020.(2)From a comprehensive perspective,from 2000 to 2020,villages in hilly areas show a decline,while villages in plain areas near the city center show a positive urbanization development.(3)Road accessibility and distance from the city center are the main factors that explain the spatial differentiation of village evolution degree in the study area.This study elucidates the spatiotemporal evolution characteristics of villages in the upper Tuojiang River basin and identifies the primary factors contributing to their changes,which will provide a reference for investigating the development of rural areas in different terrains of Southwest China.

Heterogeneous population distribution enhances resistance to wheat lodging by optimizing the light environment

Lodging is still the key factor that limits continuous increases in wheat yields today,because the mechanical strength of culms is reduced due to low-light stress in populations under high-yield cultivation.The mechanical properties of the culm are mainly determined by lignin,which is affected by the light environment.However,little is known about whether the light environment can be sufficiently improved by changing the population distribution to inhibit culm lodging.Therefore,in this study,we used the wheat cultivar“Xinong 979”to establish a low-density homogeneous distribution treatment(LD),high-density homogeneous distribution treatment(HD),and high-density heterogeneous distribution treatment(HD-h)to study the regulatory effects and mechanism responsible for differences in the lodging resistance of wheat culms under different population distributions.Compared with LD,HD significantly reduced the light transmittance in the middle and basal layers of the canopy,the net photosynthetic rate in the middle and lower leaves of plants,the accumulation of lignin in the culm,and the breaking resistance of the culm,and thus the lodging index values increased significantly,with lodging rates of 67.5%in 2020–2021 and 59.3%in 2021–2022.Under HD-h,the light transmittance and other indicators in the middle and basal canopy layers were significantly higher than those under HD,and the lodging index decreased to the point that no lodging occurred.Compared with LD,the activities of phenylalanine ammonia-Lyase(PAL),4-coumarate:coenzyme A ligase(4CL),catechol-O-methyltransferase(COMT),and cinnamyl-alcohol dehydrogenase(CAD)in the lignin synthesis pathway were significantly reduced in the culms under HD during the critical period for culm formation,and the relative expression levels of TaPAL,Ta4CL,TaCOMT,and TaCAD were significantly downregulated.However,the activities of lignin synthesis-related enzymes and their gene expression levels were significantly increased under HD-h compared with HD.A partial least squares path modeling analysis found significant positive effects between the canopy light environment,the photosynthetic capacity of the middle and lower leaves of plants,lignin synthesis and accumulation,and lodging resistance in the culms.Thus,under conventional high-density planting,the risk of wheat lodging was significantly higher.Accordingly,the canopy light environment can be optimized by changing the heterogeneity of the population distribution to improve the photosynthetic capacity of the middle and lower leaves of plants,promote lignin accumulation in the culm,and enhance lodging resistance in wheat.These findings provide a basis for understanding the mechanism responsible for the lower mechanical strength of the culm under high-yield wheat cultivation,and a theoretical basis and for developing technical measures to enhance lodging resistance.

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.

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.

Epidemiological, Clinical Aspects and Factors Associated with Typical Gastroesophageal Reflux Disease in the General Population of Parakou, Republic of Benin

Introduction: Gastroesophageal reflux disease (GERD) is a benign and chronic disease that can impair the quality of life. Objective: To study the epidemiological, clinical aspects and factors associated with typical GERD in the general population of Parakou in the Republic of Benin. Methods: This was a descriptive and analytical cross-sectional study with prospective data collection which took place from May 1, 2019 to June 30, 2019. The study population consisted of any subject aged at least 15 years and living in Parakou. Subjects aged at least 15 years, present on the day of the survey and having given their free and informed verbal consent were included. The Short form of QRS®(Reflux-Qual Short form) questionnaire and the “Hospital Anxiety and Depression” score were used to assess the quality of life and anxiety/depression, respectively. The sampling was probabilistic through a 2-stage cluster sampling. The variable of interest was the presence of GERD. Results: Out of 390 subjects surveyed, 28 had symptoms of typical GERD, representing a prevalence of 7.18%. The average age of these subjects was 27.11 ± 7.88 years. Fifteen subjects (53.57%) were male, giving a sex ratio of 1.15. Fourteen (50%) had a secondary level of education, 12 (42.86%) were pupils/students, 18 (64.29%) were single. The monthly income of 22 subjects (78.57%) was lower than the guaranteed interprofessional minimum wage (40,000 FCFA). The average duration of progression of symptoms was 15.89 ± 4.97 months. Symptoms occurred less than twice a week in 22 subjects (78.57%). The clinical manifestations were both diurnal and nocturnal in 12 subjects (42.86%). None of the 28 subjects with GERD had clinical warning signs. Asthma, diabetes, consumption of high fat or spice foods, carbonated drinks, non-steroidal anti-inflammatory drugs, alcoholic beverages and tobacco were statistically associated with the occurrence of GERD. Each of the 28 subjects had at least one associated factor. A significant impair in quality of life was observed in 27 patients (96.43%). Conclusion: Typical GERD is relatively common in the general population of Parakou in the Republic of Benin. It often affects young males. Among the risk factors identified, the most common are carbonated drinks, spicy meals and diabetes. GERD significantly impairs quality of life. Raising awareness about the disease and its associated factors is necessary among the general population.

Theoretical investigations of population trapping phenomena in atomic four-color,three-step photoionization scheme

The four-color three-step selective photoionization process of atom is very important in laser isotope separation technology.The population trapping phenomena and their influences are studied theoretically in monochromatic and non-monochromatic laser fields based on the density matrix theory in this work.Time evolutions of the photoionization properties of the four-color,three-step process are given.The population trapping effects occur intensely in monochromatic excitation,while it gradually turns weak as the laser bandwidth increases.The effects of bandwidth,Rabi frequency,time delay,and frequency detuning on the population trapping effect are investigated in monochromatic and non-monochromatic laser fields.The effects of laser process parameters and atomic parameters on the effective selective photoionization are also discussed.The ionization probability and selectivity factors,as evaluation indexes,are difficult to improve synchronously by adjusting systematic parameters.Besides,the existence of metastable state may play a negative role when its population is low enough.

Profiling of the Retrospective Epidemiology of the Human Papillomavirus and Related Cancers in the United Arab Emirates Population

The human papillomavirus (HPV) is a leading cause of infectious cancers, leading to a growing global interest on the profiling of HPV-related cancers. Therefore, the aim of the study was to determine the retrospective epidemiological profile of HPV-related cancer in the United Arab Emirates (UAE). The incidence profiling of HPV-related cancers in males and females of UAE of all ages ranged from a minimum of 0.6% to a maximum of 4.5% for testes cancer and colon cancer respectively in males;whilst in females it ranged from a minimum of 1.0% and a maximum of 34% for Hodgkin lymphoma, kidney, bladder, liver and pancreas cancer and breast cancer, respectively. The incidence profiling of HPV-related cancers in males and females of ages 15 - 44 years old ranged from a minimum of 0.1% to a maximum of 11.2% for pancreas cancer, and colon and rectum cancer respectively in males, whilst in females it ranged from a minimum of 0.1% and a maximum of 18% for pancreas and breast cancer, respectively. The mortality profiling of HPV-related cancers in males and females of all ages in the UAE ranged from a minimum of 0.1% for Hodgkin lymphoma and testicular cancer to a maximum of 4.5% for colon and rectum cancer respectively in males, whilst in females it ranged from a minimum of 0.2% and a maximum of 4.5% for pancreas and breast cancer, respectively. The mortality profiling of HPV-related cancers mortality in males and females of ages 15 - 44 years old in the UAE ranged from a minimum of 0.2% to a maximum of 4.3% for testicular cancer and colon cancer respectively in males, whilst in females it ranged from a minimum of 0.2% and a maximum of 7.2% for bladder and breast cancer respectively. In conclusion, the profiling of HPV-related cancers in UAE for both males and females of all ages is similar to that reported for other parts of the world.

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.