Population Mean Research Articles

Distribution of Private Dental Healthcare Facilities in Riyadh City: A GIS-Based Approach.

The dental healthcare private sector in Riyadh city has been growing rapidly over the past few years; however, there is a lack of information on the accessibility and spatial distribution of private dental healthcare facilities (PDHFs) in the area. This study aimed to evaluate the spatial distribution of PDHFs in Riyadh city in relation to population density in each sub-municipality. The current information regarding the number, location, and operability of PDHFs in Riyadh city was obtained from the Ministry of Health. A total of 632 operating PDHFs were included with the precise location plotted on Quantum Geographic Information System software (version 3.32.1, Essen, Germany) using Google Earth. Four levels of buffer zones-1 km, 3 km, 5 km, and >5 km-were determined. The population statistics and mean monthly individual income per district were gathered from Zadd.910ths. Microsoft Excel (version 16.0, Microsoft, Redmond, WA, USA) and RStudio software (version 4.1.3, Posit Software, PBC, Boston, MA, USA) were used for additional data analysis. There was an overall ratio of one PDHF per 9958 residents in Riyadh city. Olaya and Maather sub-municipalities had the largest PDHF-to-population ratios: (1:4566) and (1:4828), respectively. Only 36.3% of the city's total area was within a 1 km buffer zone from a PDHF. There was an overall weak positive correlation between the number of PDHFs and the total area in each sub-municipality (r = 0.29), and the distribution of PDHFs was uneven corresponding to the area (G* = 0.357). There was an uneven distribution of PDHFs in Riyadh city. Some areas were underserved while others were overserved in several sub-municipalities. Policy-makers and investors are encouraged to target underserved areas rather than areas with significant clustering to improve access to care.

Executive functions & metabolic control in phenylketonuria (PKU) and mild hyperphenylalaninemia (mHPA)

BackgroundDue to newborn screening and early treatment, patients with phenylketonuria (PKU) and mild hyperphenylalaninemia (mHPA) develop largely normal, in terms of IQ testing and academic attainment. However, the impact of metabolic control in various stages of development on more complex cognitive abilities, i.e. executive functions (EF), is still unclear. MethodsEFs were tested in 28 patients with PKU/mHPA, aged 8–17 years, identified by newborn screening and continuously treated. The relation to current (testing day & past 10 phenylalanine (Phe) values) and long-term metabolic control (age periods: childhood <6, 6–10, adolescence >10 years, lifetime Phe) was analyzed. ResultsEFs were in the lower normative range (IQR of T-values: 47.35–51.00). Patients reaction time was significantly slower than the population mean (divided attention/TAP: median 40, p < 0.01). Both, long-term and current metabolic control correlated with performance in EF tests: Higher current Phe impaired reaction times (Go/No-Go, r = −0.387; working memory, r = −0.425; p < 0.05) and performance in planning ability (ToL r = −0.465, p < 0.01). Higher long-term Phe values both in childhood and adolescence mainly affected attention (omissions/TAP r = −0.357 and − 0.490, respectively, both p < 0.05) as well as planning ability (ToL r = −0.422 and − 0.387, adolescence and lifetime, p < 0.05). ConclusionCurrent and long-term metabolic control in PKU/mHPA, including the adolescent period, influence EFs, especially affecting reaction time and planning abilities. This should be taken into account in patient counselling.

Estimation of Population Mean Using Some Improved Imputation Methods for Missing Data in Sample Surveys

. In this research article, we present novel imputation methods designed to address missing data challenges in sample surveys. We then introduce innovative estimation procedures for calculating population means based on these methods. Our study thoroughly examines the properties of these new estimation procedures, assessing their biases and mean square errors. Through the use of both real and simulated data sets, we demonstrate the superior performance of our proposed estimators compared to existing methods in similar scenarios. In conclusion, we offer practical recommendations for survey practitioners.

Exploring population genetics for mutant mungbean [Vigna radiata (L.) R. Wilczek] lines: Insights from augmented block design

AbstractThe current study was initiated to assess mungbean [Vigna radiata (L.) R. Wilczek] mutant lines for yield and their attributes in the mutation generation third (M3) generation using an augmented block design. Note that 1200 mutated mungbean lines were selected from the γ‐irradiated (400–700 Gy) population and distributed into 21 blocks, along with three popular varieties (checks) replicated in each block. To evaluate mean performance, variance, and population genetics, the observations on days to flowering, days to maturity, plant height (cm), number of clusters per plant, number of pods per plant, pod length (cm), protein percentage, seed index, and seed yield (g) were measured and analyzed. All the lines under consideration showed highly significant variations for all the variables, except for days to flowering. Seventy‐nine mutant lines were found to have significantly better yield attributes than checks and are currently being evaluated under station trial. Skewness and kurtosis analysis unveiled the presence of gene interactions, offering opportunities for targeted improvement and efficacy of γ rays as a mutagen, facilitating the release of variability within the population. Future mungbean breeding programs will benefit from the successful isolation of mutant plants with yield‐enhancing traits, such as up to 20 clusters per plant, 71 pods per plant, 8.55 cm pod length, 26.69% protein content (5% higher than parent), and 29 gram seeds per plant. In early selection cycles without the need for replicated trials, this study demonstrated the effectiveness of the mutagen and augmented design in creating novel variations, evaluating and identifying superior genotypes with improved yield potential.

Regional Assessment of Groundwater Contamination Risk from Crude Oil Spillages in the Niger Delta: A Novel Application of the Source-Pathway-Receptor Model

AbstractOnshore oil spills are known for their disastrous environmental impacts and potential to cause lasting damage to underlying groundwater. The Niger Delta is particularly vulnerable to widespread spillages linked to extensive oil exploration, transportation, and theft-related incidents. This research employed a geospatial approach in formulating risk equations, based on the source-pathway-receptor (S-P-R) model using multiple openly available data sets, to assess groundwater contamination risk in the Niger Delta Region (NDR), Nigeria. To develop the overall risk equation, the study combined fourteen thematic data layers including the volume of oil spilled, type of spill, slope, elevation, proximity to spill site, pipeline, oil wells and streams, drainage density, mean annual precipitation and population density. These layers were integrated into source potency, pathway transmissivity, and receptor susceptibility. The NDR was systematically categorized into low, moderate, and high groundwater risk zones. The delineation revealed that high-risk zones predominantly span the central areas, extending from southeast to northwest, effectively encircled by regions of low to medium risk located in both the northern and southern extents of the delta. The efficacy of the risk model was corroborated by existing knowledge. Moderate to high-risk zones were found to be in about 16% of the NDR, revealing previously unknown areas of risk. This spatial configuration underscores a significant gradient in contamination risk across the NDR, with the central corridor emerging as a critical focus for groundwater protection and remediation efforts. In line with UN Sustainable Development Goal (SDG) #6, this study recommends targeted strategies to ensure clean water provision in these identified high-risk areas. By leveraging the S-P-R model within this complex and sensitive ecological area, this research both advances environmental risk assessment and sets a precedent for future large-scale environmental risk assessments utilizing open-source data.

An effective computational and simulation study for population mean estimation on current occasion

An effective computational and simulation study for population mean estimation on current occasion

Impact of truncating historical data on prediction ability of dairy sheep selection candidates

Along the last decades, the genetic evaluation methodology has evolved, improving breeding value estimates. Many breeding programmes have historical phenotypic records and large number of generations, but to make use of them could result in more inconveniences than benefits. In this study, the prediction ability of genotyped young animals was assessed by simultaneously evaluating the removal of historical data, two pedigree deepness and two methodologies (traditional BLUP and single−step genomic BLUP or ssGBLUP), using milk yield records of 40 years of three Latxa dairy sheep populations. The linear regression method was used to compare predictions of young rams before and after progeny testing, with six cut-off points, by intervals of 4 years (from 1992 to 2012), and statistics of ratio of accuracies, bias, and dispersion were calculated. The prediction accuracy of selection candidates, when genomic information was included, was the highest in all Latxa populations (between 0.54 and 0.69 with full data set). Nevertheless, the deletion of historical phenotypic data resulted on moderate accuracy gain in the bigger data size populations (mean gain 2.5%), and the smaller population took advantage of a moderate data deletion (2.7% gain by removing data until 2004), reducing accuracy when more records were removed. The bias of validation individuals was lower when the breeding value was predicted based on genomic information (between 2.1 and 13.9), being lower when the biggest amount of data was deleted in the bigger data size populations (5.2% reduction), and the smaller population was benefited from data deletion between 1996 and 2008 (3.8% bias reduction). Meanwhile, the slope of estimated genetic trend was lower when less data were included, and an overestimation of the unknown parent group estimates was observed. The results indicated that ssGBLUP evaluations were outstanding, compared with traditional BLUP evaluations, while the depth of pedigree had a very small influence, and deletion of historical phenotypic data was beneficial. Thus, Latxa routine genetic evaluations would benefit from truncating phenotypic records between 2000 and 2004, the use of two pedigree generations and the implementation of ssGBLUP methodology.

Population density and vegetation resources influence demography in a hibernating herbivorous mammal.

Demography of herbivorous mammal populations may be affected by changes in predation, population density, harvesting, and climate. Whereas numerous studies have focused on the effect of single environmental variables on individual demographic processes, attempts to integrate the consequences of several environmental variables on numerous functional traits and demographic rates are rare. Over a 32-year period, we examined how forage availability (vegetation assessed through NDVI) and population density affected the functional traits and demographic rates of a population of Columbian ground squirrels (Urocitellus columbianus), a herbivorous hibernating rodent. We focused on mean population phenology, body mass, breeding success, and survival. We found a negative effect of population density on demographic rates, including on breeding success and pup and adult survival to the next year. We found diverging effects of vegetation phenology on demographic rates: positive effects of alater start of the growing season on adultand yearling femalesurvival, and juvenile survival, but no clear effect on male survival. Interestingly, neither population density nor vegetation affected population phenology or body condition in the following year. Vegetative growth rate had a positive influence on female mass gain (somatic investment) over a season, but bothvegetative growth rate and biomass, surprisingly, had negative effects on the survival of young through their first hibernation. Thus, ground squirrels appeared to benefit more from later timing of vegetation than increases in vegetative biomass per se. Our study provides evidence for complex ecological effects of vegetation and population density on functional traits and demographic rates of small mammal populations.

GWAS elucidated grain yield genetics in Indian spring wheat under diverse water conditions.

Underpinned natural variations and key genes associated with yield under different water regimes, and identified genomic signatures of genetic gain in the Indian wheat breeding program. A novel KASP marker for TKW under water stress was developed and validated. A comprehensive genome-wide association study was conducted on 300 spring wheat genotypes to elucidate the natural variations associated with grain yield and its eleven contributing traits under fully irrigated, restricted water, and simulated no water conditions. Utilizing the 35K Wheat Breeders' Array, we identified 1155 quantitative trait nucleotides (QTNs), with 207 QTNs exhibiting stability across diverse conditions. These QTNs were further delimited into 539 genomic regions using a genome-wide LD value of 3.0Mbp, revealing pleiotropic control across traits and conditions. Sub-genome A was significantly associated with traits under irrigated conditions, while sub-genome B showed more QTNs under water stressed conditions. Favourable alleles with significantly associated QTNs were delineated, with a notable pyramiding effect for enhancing trait performance. Additionally, allele of only 921 QTNs significantly affected the population mean. Allele profiling highlighted C-306 as a most potential source of drought tolerance. Moreover, 762 genes overlapping significant QTNs were identified, narrowing down to 27 putative candidate genes overlapping 29 novel and functional SNPs expressing (≥ 0.5tpm) relevance across various growth conditions. A new KASP assay was developed, targeting a gene TraesCS2A03G1123700 regulating thousand kernel weight under severe drought condition. Genomic selection models (GBLUP, BayesB, MxE, and R-Norm) demonstrated an average prediction accuracy of 0.06-0.58 across environments, indicating potential for trait selection. Retrospective analysis of the Indian wheat breeding program supported a genetic gain in GY at the rate of ca. 0.56% per breeding cycle, since 1960, supporting the identification of genomic signatures driving trait selection and genetic gain. These findings offer insight into improving the rate of genetic gain in wheat breeding programs globally.

Comprehensive insights into health services accessibility and quality of life of families with individuals with 22q11.2 deletion syndrome in Brazil

BackgroundThe 22q11.2 Deletion Syndrome (22q11.2 DS) presents unique healthcare challenges for affected individuals, families, and healthcare systems. Despite its rarity, 22q11.2 DS is the most common microdeletion syndrome in humans, emphasizing the need to understand and address the distinctive healthcare requirements of those affected. This paper examines the multifaceted issue of health service access and caregivers’ quality of life in the context of 22q11.2 DS in Brazil, a condition with diverse signs and symptoms requiring multidisciplinary care. This study employs a comprehensive approach to evaluate health service accessibility and the quality of life of caregivers of individuals with 22q11.2 DS. It utilizes a structured Survey and the WHOQOL-bref questionnaire for data collection.ResultsIndividuals with 22q11.2 DS continue to receive incomplete clinical management after obtaining the diagnosis, even in the face of socioeconomic status that enabled an average age of diagnosis that precedes that found in sample groups that are more representative of the Brazilian population (mean of 3.2 years versus 10 years, respectively). In turn, caring for individuals with 22q11.2 DS who face difficulty accessing health services impacts the quality of life associated with the caregivers' environment of residence.ConclusionsResults obtained help bridge the research gap in understanding how caring for individuals with multisystem clinical conditions such as 22q11.2 DS and difficulties in accessing health are intertwined with aspects of quality of life in Brazil. This research paves the way for more inclusive healthcare policies and interventions to enhance the quality of life for families affected by this syndrome.

Comparative Analysis of Health Outcomes Between Migrants and Native Spaniards

In 2012, Spain enacted a law which changed its Universal Health System from ensuring government funded healthcare for all residents, regardless of immigration status, to restricting migrant healthcare access. This study investigates health records from 2017, one year before this restrictive legislation was repealed, to determine if such legislative action coincides with disparities in health outcomes between migrants to Spain and native Spaniards. Because a health record analysis from 2012 suggests that migrants in Spain exhibited poorer overall health even before the legislative restrictions, we hypothesized that migrant communities would continue to demonstrate lower health outcomes than native Spaniards while these restrictions were enforced. We extracted nationality and health data from the Spanish Ministry of Health’s 2017 National Health Survey. We grouped thirteen health sub-indicators into four main health indicators to compare the general physical and mental well-being of migrants and native Spaniards. These main indicators included disease prevalence, risk factors for future infirmities, mental health, and self-perceived health. After quantifying interviewees’ responses, we compared population means of migrants and natives for each sub-indicator through an unpaired t-test of means to determine trend significance. We integrated the results of sub-indicator comparisons to determine overall trends in the four main indicators. With only one exception, all eight sub-indicators for disease prevalence demonstrated decreased prevalence among migrant populations which indicates lower overall disease for migrants compared to native Spaniards. This trend continued for self-perceived health as well as all sub- indicators used to assess mental health and predisposition to future illnesses. These results suggest that migrants in Spain are healthier than their native counterparts. The better health outcomes experienced by the migrants relative to native Spaniards contradict our hypothesis. Nevertheless, previous findings explain these results as demonstrative of an established phenomenon, the “healthy migrant effect,” in which migrants typically demonstrate higher healthcare outcomes than their native counterparts. The observed “healthy migrant effect” despite legislative restrictions on migrant healthcare access, as well as the effect’s apparent disappearance during the aftermath of Spain’s 2008 economic recession, suggests that the health disparities between migrants and natives correlated more directly with a nation’s economic well-being than their legislative actions.

Effects of Melia azedarach extract on demographic and biochemical characteristics of the cabbage aphid, Brevicoryne brassicae

The cabbage aphid, Brevicoryne brassicae L. (Aphididae: Hemiptera) a destructive aphid, is native to Europe and is now found in many other parts of the world. Currently, one of the main problems of Iranian cabbage growers is the significant damage caused by this pest. Also, due to the fresh eating of cabbage, it is necessary to use non-chemical methods to control the pests. Our bioassay tests showed that Melia azedarach L. (Meliaceae) fruit extract showed high toxicity to cabbage aphid. In this study, sublethal effects of M. azedarach extract was investigated on some demographic and biochemical properties of B. brassicae. The results showed that the sublethal concentrations (LC10 and LC20) and LC50 values were 0.68, 1.16, and 3.42 μg/ml, respectively. Compared to the control, sublethal concentrations of insecticide significantly decreased the gross reproductive rate (GRR), net reproductive rate (R0), intrinsic rate of increase (rm), finite rate of increase (λ), intrinsic rate of birth (b), intrinsic rate of death (d), weekly growth rate (rw), reproductive rate and adult longevity of the pest. Meanwhile, the mean generation time (T) and population doubling time (DT) of this aphid increased significantly. Additionally, sublethal doses of insecticide reduced the energy reserves of the pest such as carbohydrate, protein and lipid content compared to the controls. In addition to modify the pH, this extract also changed the distribution and concentration of sodium and potassium ions in haemolymph. Therefore, sublethal concentrations of M. Azedarach fruit extract can be used in the management program of B. brassicae.

P-464 Patients satisfaction with Hypnosis during Oocyte Retrieval

Abstract Study question Are patients receiving hypnosis during oocyte retrieval (OR) satisfied with this support? Summary answer Three-quarters of the women receiving hypnosis during OR were satisfied with this support, considering it beneficial for both pain and anxiety. What is known already OR is a crucial component in the management of assisted reproductive technology (ART). Despite being a safe and efficient procedure, OR is often perceived as the most stressful and painful aspect of ART. OR can be performed under local anesthesia with a paracervical block analgesia but may still cause discomfort for some patients (pain, anxiety related to the procedure). Therefore, exploring non-pharmacological approaches, such as hypnosis, to enhance anesthesia is of major interest. Hypnosis has demonstrated efficacy in pain management across various medical indications, prompting an investigation into its potential benefits during OR. Study design, size, duration A cohort study involving women undergoing an OR under local anesthesia combined with hypnosis at our institution between November 2022 to November 2023. A questionnaire was distributed to patients just after the OR, assessing women’s satisfaction with hypnosis support, along with their experiences of pain (Visual Analogic scale (VAS)) and anxiety (State-Trait Anxiety Inventory (STAI) questionnaire) during the OR procedure. Participants/materials, setting, methods Women for whom hypnosis was administered during the entire OR procedure, using either a virtual reality headset or with a hypnotherapist were included. Exclusions comprised incomplete questionnaires and patients unable to communicate in French. Objectives were (i) to assess the women satisfaction concerning hypnosis during OR on pain and anxiety through specific questions of the survey, (ii) to evaluate pain (VAS) and anxiety (STAI) during the procedure and (iii) to compare the two hypnosis techniques. Main results and the role of chance Two hundred and nine women undergoing OR under local anesthesia fully responded to the questionnaire out of six hundred surveyed. The mean population age was 34.4±4.1 years. Hypnosis support was provided by a hypnotherapist for 79.9% (167/209) of women and using a virtual reality headset for 20.1% (42/209). 73.7% were satisfied of hypnosis for pain, and 86.1% for anxiety. A higher proportion found hypnosis beneficial for anxiety in the therapist group compared to the virtual reality headset group (88.6% (148/167) versus 76.2% (32/42) respectively, p:0.037). For a new oocyte retrieval, 70.8% of women preferred undergoing the procedure under local anesthesia with hypnosis. The mean VAS score was 5.3 ± 2.6 and the mean STAI score was 36.7± 17.8 during oocyte retrieval. No significant differences concerning VAS and STAI scores were found between the therapist and virtual reality headset groups. Limitations, reasons for caution The study evaluates the satisfaction of women with hypnosis support; hence, there is no assessment of long-term benefits on pregnancy chances. Additionally, a potential selection bias exists as not all surveyed women returned the questionnaire. Wider implications of the findings Positive feedback suggests a potential role for hypnosis in enhancing patient well-being during oocyte retrieval, warranting further research and clinical exploration to improve the overall patient experience during what is often perceived as a stressful procedure. Trial registration number NA

Understanding stunting and its determinant among children in the most populous state of India using estimation of population mean under ranked set sampling in the presence of missing data

ABSTRACT In real-life scenarios, encountering data with missing values is common, and if not managed carefully from the outset of a study, it can lead to significant biases in survey estimates. Various methods exist for imputing missing values in sampling procedures. Ranked set sampling (RSS) is widely recognized for its superior efficiency compared to simple random sampling. However, limited research has been conducted on ranked set sampling in the presence of missing data. This article introduces novel imputation methods designed to estimate population means in the context of missing data under RSS. These innovative estimators are developed by integrating ratio, exponential, and logarithmic estimators judiciously. Expressions for the bias and mean squared error of the proposed estimators are derived up to the first-order approximation. Through simulation studies and an application to stunting and its determinants among children in Uttar Pradesh, India’s most populous state, the effectiveness of the suggested estimators in handling missing data is demonstrated. Numerical examples involving stunting in Uttar Pradesh, as well as simulated data generated using R software, confirm the superior performance of the proposed estimators over existing methods, as evidenced by comparisons of percentage relative efficiency and mean squared error. The results are promising, indicating improvement over all existing imputation methods. Additionally, pertinent recommendations are provided for survey professionals regarding future research.

Estimation of human height using ulnar length in the Muslim community of Golbazar Municipality, Siraha, Nepal

Calculating an individual's height based on bone measurements is critical in identifying unknown bodies, body parts, or skeletal remains. Anthropologists, anatomists, and forensic experts have used a variety of anthropometric approaches to forecast stature from skeletal remains. Although few studies have been conducted to understand ulnar length and height, it has not been conducted in a few ethnic communities of Nepal. This study aimed to analyze the relationship between human height and ulnar length in Muslim communities of Golbazar Municipality, Siraha, Nepal. Two hundred people (male 100 and female 100) aged 20 to 40 years were purposively selected from Golbazaar, Siraha, Nepal. Ulnar length was measured as the distance between the tip of the Olecranon process and the styloid process with the elbow fully flexed. Height was measured from the top of the head to the floor while the participants stood upright in the anatomical position with their heads in the Frankfort plane. Statistical techniques, such as linear regression analysis and correlation coefficients, were used to determine a correlation between ulna length and height. The population's mean ulna length was 26.53 cm (SD = 2.06), and the mean height was 159.59 cm (SD = 9.72). The correlation between ulna length and height was stronger in males (0.46) than in females (0.36). The study established regression equations for height estimation based on ulna length for different age groups, with the strongest correlations found in the 31–35 years age group and weaker ones in the 20–25 years and 26–30 years age groups. The study suggests that ulna length could be a reliable predictor of height, especially when direct measurement is challenging or impossible. However, additional study is required to explore potential differences based on age, ethnicity, and gender and to validate the findings in more extensive and more diverse populations.

Morphological simulation tests the limits on phenotype discovery in 3D image analysis.

In the past few decades, advances in 3D imaging have created new opportunities for reverse genetic screens. Rapidly growing datasets of 3D images of genetic knockouts require high-throughput, automated computational approaches for identifying and characterizing new phenotypes. However, exploratory, discovery-oriented image analysis pipelines used to discover these phenotypes can be difficult to validate because, by their nature, the expected outcome is not known a priori . Introducing known morphological variation through simulation can help distinguish between real phenotypic differences and random variation; elucidate the effects of sample size; and test the sensitivity and reproducibility of morphometric analyses. Here we present a novel approach for 3D morphological simulation that uses open-source, open-access tools available in 3D Slicer, SlicerMorph, and Advanced Normalization Tools in R (ANTsR). While we focus on diffusible-iodine contrast-enhanced micro-CT (diceCT) images, this approach can be used on any volumetric image. We then use our simulated datasets to test whether tensor-based morphometry (TBM) can recover our introduced differences; to test how effect size and sample size affect detectability; and to determine the reproducibility of our results. In our approach to morphological simulation, we first generate a simulated deformation based on a reference image and then propagate this deformation to subjects using inverse transforms obtained from the registration of subjects to the reference. This produces a new dataset with a shifted population mean while retaining individual variability because each sample deforms more or less based on how different or similar it is from the reference. TBM is a widely-used technique that statistically compares local volume differences associated with local deformations. Our results showed that TBM recovered our introduced morphological differences, but that detectability was dependent on the effect size, the sample size, and the region of interest (ROI) included in the analysis. Detectability of subtle phenotypes can be improved both by increasing the sample size and by limiting analyses to specific body regions. However, it is not always feasible to increase sample sizes in screens of essential genes. Therefore, methodical use of ROIs is a promising way to increase the power of TBM to detect subtle phenotypes. Generating known morphological variation through simulation has broad applicability in developmental, evolutionary, and biomedical morphometrics and is a useful way to distinguish between a failure to detect morphological difference and a true lack of morphological difference. Morphological simulation can also be applied to AI-based supervised learning to augment datasets and overcome dataset limitations.

A Descriptive Study of Pulmonary Function Comparison Between Spot Welding and Assembly Line Workers in a Large Automotive Factory in Iran

Background: This study seeks to define the pulmonary function of a considerably large group in one of the largest automotive companies in Iran. The aim of this study was to compare the two groups of spot-welding (exposed) and assembly line (unexposed) workers in terms of pulmonary function and conclude the probable impacts of metal fumes on pulmonary function in the two groups. Methods: A total of 1,798 spot-welding personnel and 2,160 assembly line personnel were compared in terms of pulmonary function. Moreover, 120 breathing zone samples were collected from the welders’ metal fumes and were analyzed. The parameters of age, anthropometric indices, smoking, and pulmonary symptoms were also compared with across the two groups. Results: Results revealed the FEV1 mean of the total population to be 3.9 ± 0.5 liters and FVC to have been 4.9 ± 0.7 liters. Besides, predicted FEV1 and FVC percentages across the whole population were close to 100%, suggesting the better condition of the studied population compared with normal individuals in the society. All the parameters of age, weight, height, and smoking status were similar in the two groups, and no statistically significant difference was observed between the two groups in terms of pulmonary functions. Conclusion: Implementation of professional health and health improvement programs, running screening programs, and hiring personnel with no history of mild pulmonary disorders, and healthy workers effect at the recruitment stage could be the reasons behind the lack of significant difference between the two exposed and unexposed groups to metal fumes in the automotive industry in terms of pulmonary function.

Improved memory-type ratio estimator for population mean in stratified random sampling under linear and non-linear cost functions

This paper offers an improved memory-type ratio estimator in stratified random sampling under linear and non-linear cost functions. The issue is given as all integer non-linear programming problems (AINLPPs). The sampling properties mainly the bias and the mean squared error of the introduced estimator are derived up to the first order of approximation. The optimum value of the characterizing scalar is obtained by the Lagrange method of maxima–minima. The least value of the MSE of the suggested estimator is also obtained for this optimum value of the charactering constant. The suggested estimator is compared both theoretically and empirically with the competing estimators. Under this setup, the optimum allocation with mean square error of the suggested estimator is attained, and the estimator is compared to other comparable estimators. The AINLPP is solved using the genetic programming approach, which is applied to both actual and simulated data sets from a bivariate normal distribution.

A Class of Ratio Estimators for Estimating Population Mean Using a Transformed Auxiliary Variable Under Stratified Random Sampling

A Class of Ratio Estimators for Estimating Population Mean Using a Transformed Auxiliary Variable Under Stratified Random Sampling

Modified median quartile double ranked set sampling for estimation of population mean

Environmental monitoring and assessment aim to gather data economically, without bias, using efficient and cost-effective sampling methods. One such traditional method is Ranked Set Sampling (RSS), often employed to achieve observational economy. This article introduces an innovative two-stage sampling approach for ranked set sampling (RSS) to get a more precise estimate of the population mean. Modified Median Quartile Double Ranked Set Sampling (MMQDRSS) highlights the ranked base technique's potential as a cost-effective sampling method. To evaluate the performance of the proposed estimator by using real-life data and conducting a simulation study to compare the relative efficiency of the proposed estimator with some existing methods.