Margin Of Error Research Articles

Incidence of neurological complication symptoms post-mRNA vaccination among the urban population of Makkah Province of Kingdom of Saudi Arabia

ObjectiveThis research aimed to assess the incidence of neurological complication symptoms among residents of the Makkah province in Saudi Arabia following the rapid approval and administration of mRNA vaccines. Given the differences in demographic factors such as age, race, medical history, and lifestyle among individuals, close monitoring of vaccine-related side effects becomes crucial, especially in mass vaccination campaigns. MethodA cross-sectional online survey study was conducted in both English and Arabic languages, with a sample size determined using the Raosoft sample size calculator statistical analyzer. The study aimed for a 95% confidence level, a 5% margin of error, and a response distribution of 50%. Descriptive statistics were employed using Statistical Package for Social Sciences version 22.0. The Shapiro–Wilk test was utilized to assess data normality, and the statistical significance of the data was determined using Pearson's Chi-Squared test and the Kruskal–Wallis test. ResultThe study included 846 volunteers aged 18 and above, all of whom had received mRNA vaccine in the Makkah region. Data were systematically tabulated and categorized for descriptive analysis. The study found P-values less than .05, and the summarized P-values were presented. The majority of participants (73%) were from the Taif area (32%) within the Makkah region. ConclusionThis study sheds light on the challenges faced by the population of the Makkah region in Saudi Arabia following mRNA vaccinations. Although some complications were reported post-vaccination, it is noteworthy that these challenges were effectively managed by the medical authorities.

A Novel Model for Instance Segmentation and Quantification of Bridge Surface Cracks-The YOLOv8-AFPN-MPD-IoU.

Surface cracks are alluded to as one of the early signs of potential damage to infrastructures. In the same vein, their detection is an imperative task to preserve the structural health and safety of bridges. Human-based visual inspection is acknowledged as the most prevalent means of assessing infrastructures' performance conditions. Nonetheless, it is unreliable, tedious, hazardous, and labor-intensive. This state of affairs calls for the development of a novel YOLOv8-AFPN-MPD-IoU model for instance segmentation and quantification of bridge surface cracks. Firstly, YOLOv8s-Seg is selected as the backbone network to carry out instance segmentation. In addition, an asymptotic feature pyramid network (AFPN) is incorporated to ameliorate feature fusion and overall performance. Thirdly, the minimum point distance (MPD) is introduced as a loss function as a way to better explore the geometric features of surface cracks. Finally, the middle aisle transformation is amalgamated with Euclidean distance to compute the length and width of segmented cracks. Analytical comparisons reveal that this developed deep learning network surpasses several contemporary models, including YOLOv8n, YOLOv8s, YOLOv8m, YOLOv8l, and Mask-RCNN. The YOLOv8s + AFPN + MPDIoU model attains a precision rate of 90.7%, a recall of 70.4%, an F1-score of 79.27%, mAP50 of 75.3%, and mAP75 of 74.80%. In contrast to alternative models, our proposed approach exhibits enhancements across performance metrics, with the F1-score, mAP50, and mAP75 increasing by a minimum of 0.46%, 1.3%, and 1.4%, respectively. The margin of error in the measurement model calculations is maintained at or below 5%. Therefore, the developed model can serve as a useful tool for the accurate characterization and quantification of different types of bridge surface cracks.

Tamanhos de parcelas e amostras para variáveis biométricas em mudas de alface

ABSTRACT: In order to ensure reliable inferences in scientific experiments, sampling criteria should be determined and defined during the experimental design phase. Determining plot and sample sizes without scientific criteria could result in resource and labor inefficiencies with no gain in experimental precision. In this work we estimate plot and sample sizes for biometric variable analyses in lettuce seedlings. The seedlings were sown in four expanded polystyrene foam transplant trays with 128 and 200 cells. Foliar area, stem diameter, shoot height, root length, root volume, root area, fresh and dry shoot and root masses. The methods described by Paranaiba (PARANAIBA et al., 2009) and Cochran (COCHRAN, 1977) were used for plot size and sample size estimations, respectively. Sample size varied according to the variables analysed and transplant tray cell number. Root variables required the highest number of samples. For a 10% margin of error, 12 seedlings were necessary for evaluations in a 128 cell tray, while 11 seedlings were required for analysis in 200 cell trays.

Adam Pinkhurst and the Baffled Jury: Assessing Scribal Identifications within the Margin of Error

Adam Pinkhurst and the Baffled Jury: Assessing Scribal Identifications within the Margin of Error

Sound amplitude of discrete bubbles entrained by an impacting water stream.

Experiments were undertaken to develop a relationship between bubble size and acoustic-emission amplitude for a vertical stream of water impacting a water pool. A particular focus is the formation of the discrete bubbles. Although the relationship between bubble diameter and the natural frequency of sound emissions has been established through Minnaert's work, a comprehensive investigation into the amplitude of sound emissions is missing. Air bubbles were generated from the impact of falling-water streams of varying diameters on an underlying water pool and their acoustic emissions were recorded using a nearby hydrophone. Sound amplitude was found to increase monotonically with bubble size. A second-order polynomial relationship between logarithmic acoustic sound pressure level (L) and bubble diameter (Db) was found, L=-0.0401Db2+1.5781Db+110.7225 within the ±3 dB margin of error. The relationship between linear sound pressure level (P) and bubble diameter (Db) is expressed by the equation P=0.0059Db2+0.0505Db+0.3591, within the ±3 dB margin of error. Results demonstrate that larger bubbles (D > 4 mm) exhibit noise emissions similar to bubbles produced by other mechanisms, such as the underwater nozzle, while smaller diameters tend to produce higher noise levels compared to the same mechanism.

Multidimensional analysis for assessing sustainability determinants of rice farming in Siak, Riau

Abstract This study was conducted in five villages in Bunga Raya District (Kemuning Muda, Bunga Raya, Tuah Indrapura, Jayapura, and Buantan Lestari), the rice production centers of Siak Regency, Riau. The research location was selected based on the largest percentage of rice field area. The research was conducted from January to July 2019. This research aims to determine sustainable lowland rice farming management variables for future lowland rice farming development in Bunga Raya District, Siak Regency. Purposive sampling was used to choose the 82 sample farmers, who were selected using the Slovin equation. The respondents are selected with a margin of error of 7% of the total population of farmer families. Data was gathered through the use of interview techniques, questionnaires, and field observations. Multi-dimensional scaling (MDS) was used to analyze sustainable rice farming management factors after updating the Rapfish program. According to the findings of the sustainability study of 42 studied variables, 12 of them show sensitivity. Five of the ten stakeholder needs attributes were examined to provide sensitivity. The combined analysis of current prospective sustainability with stakeholders yielded five attributes determining factors for the sustainability of lowland rice farming in Bunga Raya: land conversion, participation in training/extension services, pesticide use, agro-tourism potential, and farmer capital availability. Another recommendation that policy makers need to consider, which is no less important, is to always preserve the rice field ecosystem by developing natural and human resources, so that increasing the welfare of farmers and increasing regional income can be achieved.

Biometric description of 34 589 eyes undergoing cataract surgery: sex differences.

To describe gender differences in the biometric parameters of a large sample of patients with cataract. Cataract surgery has evolved from a vision restoration to a refractive procedure, and population-based studies are vital to optimize normative databases and postsurgical outcomes. Miguel Servet University Hospital, Zaragoza, Spain. Retrospective single-center observational study. The study included 34 589 eyes (20 004 patients with cataract). Biometric data were obtained from IOL Master 700 and Pentacam HR. Linear mixed models were used to account for intereye correlation. HofferQST formula was used to calculate the hypothetical distribution of intraocular lens (IOL) power (arbitrary lens; A = 119.2). Most biometric variables showed significant differences between sexes ( P < .0001), such as 0.53 mm shorter eyes found in females, of which 0.16 mm are explained by shorter aqueous depth. Steeper anterior keratometries (∼0.75 diopter [D]) were found in women, to end up in no difference on anterior astigmatism magnitude, but different orientation ( P < .0001). The distribution of IOL power differed between sexes ( P < .001), with the interquartile range shifting 1 D toward more powerful lenses in women and odds ratio (power >26 D) = 2.26, P < .0001 (Fisher). Large sample size studies provide smaller margin of error, higher power, and controlled risk of reporting false (negative or positive) findings. Highly significant differences between sexes in ocular biometry were found; this supports the idea that including sex as a parameter in IOL calculation should be explored and may improve results. In addition, the distribution of IOL powers was provided, which may be useful for manufacturers and hospital stock planning.

Pengaruh Kompensasi dan Gaya Kepemimpinan terhadap Loyalitas Karyawan di Rumah Sakit Bhakti Husada Cikarang – Bekasi

The development of increasingly sophisticated technology requires corporate organisations to be able to compete for the continuity of the company's operations. Reliable and qualified human resources are needed in carrying out company operations. It will be very difficult for companies to achieve targets and goals and win business competition, if not supported by employees who have high loyalty. Loyalty is an employee's loyal attitude towards the company where he works to maintain or protect the company and make optimal contributions for the achievement of company goals. The purpose of this study was to determine the effect of compensation and leadership style on employee loyalty at Bhakti Husada Hospital Cikarang Bekasi both partially and simultaneously. This study uses associative research with quantitative research methods. The sampling technique uses the slovin formula with a margin of error of 5%. The data collection technique used a questionnaire as many as 100 respondents of Bhakti Husada Cikarang Bekasi Hospital employees. The analysis technique used is multiple linear regression analysis using SPSS version 26 statistical analysis. Based on the results of the study, it can be seen that Compensation has a positive and significant effect on employee loyalty at Bhakti Husada Hospital Cikarang Bekasi by looking at the t test results obtained t count 5.692&gt; t table 1.984 and a significance value of 0.00 &lt; 0.05. Leadership style has a positive and significant effect on employee loyalty at Bhakti Husada Hospital Cikarang Bekasi by looking at the t test results obtained t count 8.206&gt; t table 1.984 and a significance value of 0.00 &lt;0.05. Compensation and leadership style simultaneously have a positive and significant effect on employee loyalty at Bhakti Husada Hospital Cikarang Bekasi by looking at the results of the F test obtained F count 38.613&gt; F table 3.09 and a significance value of 0.00 &lt;0.05

Numerical and experimental studies on the heat transfer characteristics and process optimization of the billet soaking furnace

The precision of furnace temperature control in the soaking furnace is critical to the quality of billet heating. This paper develops a three-dimensional(3D) mathematical model of the heating process of steel billets in the soaking furnace, which can be monitored online in real time. The accuracy of the model was verified by black-box experiments. A comparative analysis of the model’s simulated and experimental data revealed a hit rate exceeding 70 % (with a relative error margin within ± 5 %). Leveraging this mathematical model, we propose a direct optimization strategy that effectively saves 24 % of heating time, accelerates the process of achieving temperature uniformity within the billet, and boosts overall heating effectiveness. This approach offers potential for broader application in optimizing the heating processes of various materials.

Classification of Diabetic Retinopathy Severity Using Deep Learning Techniques on Retinal Images

In order to diagnose DR by utilizing the grayscale intensity and texture information extracted from the fundus image, deep learning approach is used. The writers came up with the strategy on their own. The APTOS 2019 Blindness Detection (APTOS 2019 BD) dataset is employed. extensively during the course of this investigation. A method powered by deep learning was used to locate and recover the photos. We use a large number of image processing methods, as well as two ways to feature extraction, and one method for feature selection. Because of this, the F-measure is 92.3% (0.5%), and the classification accuracy is 93.2% (with an error margin of 0.32%). Durability and dependability of the approach that was proposed have been shown by performance-related criteria for the operation. There is a possibility that classification performance might be improved using a weighted ensemble model that makes use referring to the models EfficientNet-B0, B5, and B7.This research highlights the need of extra diagnostic procedures being performed by medical experts in order to avoid incorrect diagnoses as well as false positives.

Investigation of novel organic-based anti-microbial agents with polyolefins

This study investigated the anti-microbial efficacy of Nouvex N950-9010 MB, an organic-based master batch, when integrated into polypropylene (PP) and high-density polyethylene (HDPE). The focus centers on its effectiveness against two common bacterial strains: E. coli K-12 MG1655 and S. aureus ATCC 6538P. The master batch was compounded at a 5 wt.% loading concentration with PP and HDPE, and was utilized to create monolayer and multilayer films. The findings reveal significant anti-microbial activity at both 4-hour and 24-hour intervals. SEM analysis confirmed homogeneous mixing and optimal adhesion within the films. Thermal stability, assessed via DSC and TGA, remained consistent, with variations within experimental error margins. Surprisingly, FTIR results indicated no substantial differences between modified and unmodified materials, suggesting that Nouvex N950-9010 MB. preserves material integrity. Mechanical properties, including Izod impact and tensile strengths, remained stable in the modified materials. Moreover, the modified PP and HDPE exhibited improved oxygen and water vapor barrier properties (OTR and WVTR) compared with their neat counterparts. UV spectra validated the non-leachability of Nouvex N950-9010 MB, aligning with the manufacturer’s claims. A groundbreaking revelation from the study is that this master batch functions via reactive oxygen species (ROS), marking a pioneering discovery in the field of novel anti-microbial agents. The research demonstrates Nouvex N950-9010 MB’s potential as a powerful and safe solution for antimicrobial applications, opening new avenues for further exploration and practical implementation.

‘If you name a child and then change the name, it is someone else’: opinions of Graaff-Reinet residents on the proposed name change of their town to Robert Mangaliso Sobukwe

ABSTRACT In August 2023, residents of Graaff-Reinet received news that the town’s name is being considered for a change to Robert Mangaliso Sobukwe. Community reactions to the proposed name change have sparked a need to scientifically investigate the opinions of a representative sample of the community regarding the proposed name change. The study employed a quantitative approach, utilizing a representative sample survey with stratified random sampling to ensure diverse population representation from the town. Three strata were identified: former white and former coloured group areas, and the township. A total of 367 interviews were conducted, determined by the physical count of residential erven (7,748) to achieve a 95% confidence level with a 5% margin of error. The questionnaire gathered data on demographics, opinions on renaming, and connections to Graaff-Reinet. Results indicated that 83.6% expressing the opinion that the name should not change, a sentiment prevalent across all three strata. Reasons against change included familiarity, historical significance, and a focus on service delivery. The study revealed a strong sense of community identity and place attachment. The study highlighted the resistance to changing toponyms as a unifying force in Graaff-Reinet, emphasizing the significance of place names in shaping identity and community dynamics.

Determining Adequate Sample Size for Social Survey Research

Determination of a valid sample size is a fundamental step in research. This paper explains how existing formulas are tied in a single thread by applying the concept of standard error, margin of error, Z and t scores, confidence interval and sampling distribution. Bringing the concept of sample control ratio, we suggest a unified formula which is where I is the sample size, N is the population, t is the t-value at a desired level of probability with df = (N-1) and  is the sample control ratio to be estimated by for continuous variables and for categorical variables where  is the proportion of acceptable error and p is the proportion of presence of an attribute in the population. This formula does not need the finite population correction, and it has been derived from and consistent with existing formulas. A researcher does not need to calculate the error margin in absolute terms for this formula, and it is sufficient to provide only the proportion of error (e.g., 0.03 or 0.05). This paper should help social scientists, researchers, academicians and students determine the appropriate sample size for their research with greater confidence and clarity. J Bangladesh Agril Univ 22(2): 146-157, 2024

Social Media Political Communication and Misinformation: A Case Study of the Youth in Kiambu County, Kenya

Social media in recent times has proven to be extremely persuasive in influencing the public’s opinion on political affairs. Since 2007, election campaigns have actively utilized several social media platforms in Kenya for communicating with, mobilizing, and organizing supporters. Politicians and political activists along with their parties make maximum use of it to interact and provide civic education to the public. However, few written materials are available on how Kenyan youth, particularly those who live in Kiambu County, use social media for political engagement. The objective of this research is therefore to explore patterns as well as practices characterizing social media use by young people in Kiambu County and how this affects their political involvement and discourse. This research is guided by Habermas’s Theory of the Public Sphere, which asserts that public political discourse that is free from government interference is important for creating functional democracies. Social media, which acts as a public sphere, can allow the youth to engage in political discussions and other civic activities. The research employs a descriptive research design, utilizing an online survey as the primary tool for data collection, administered via Survey Monkey. The research’s target population includes young people enrolled in institutions of higher learning in Kiambu County who use social media for communication. The sample size was determined based on the number of university students in Kiambu County. It utilized stratified random sampling on a target population of 115,330 to draw a sample of 380 youths using a Survey Monkey online sample calculator with a 95% confidence level and 5% margin of error. Initially, a pilot study was conducted on 10% of the sample, which is 38 respondents, to ascertain the reliability of the research instruments, eventually, from the 342 surveys sent out, 224 were completed and returned. For data analysis, Microsoft Excel was utilized in coding and organizing the data to create tables and graphs. The findings showed that X was the respondents' most used platform for political discourse. Most respondents were aware of and engaged in political discussions on social media, and believed that social media influenced their political attitudes and beliefs. Although most viewed social media as a source of civic education, they were skeptical about its reliability due to misinformation. The study concludes that many youths in Kiambu County are actively participating in political discussions online and therefore it recommends that better education should be provided to help the youth discern credible information from misinformation. Additionally, interventions should be established to curb digital crimes like cyberbullying and online fraud.

Assessment of Emotional Distress among Hepatitis C Patients Undergoing Antiviral Therapy at Jinnah Hospital Lahore

Hepatitis C is a significant worldwide health issue, causing mental and psychological distress in individuals, resulting in heightened stress and depression. Objective: To assess the emotional distress and assess the relationship between emotional distress and demographic variables of hepatitis c patients undergoing antiviral therapy at Jinnah Hospital Lahore. Methods: A quantitative cross sectional study design was used for this study. The study was carried out in Jinnah Hospital Lahore. Sample size of 108 patients is calculated with 95% confidence interval and 5% margin of error. Data were collected by using self-developed through convenient sampling technique. Both Male and female conscious patient, have a confirmed diagnosis of Hepatitis C and on antiviral therapy for 12 weeks were included in the study. Patients with Liver Cirrhosis and emotional trauma were excluded from study. An adopted Emotional Distress scale, consists of 14 questions was used to collect data from patients Emotional Distress Scale was used to collect data. Data were analyzed using SPSS 25.0. Chi square test applied to assess association between emotional distress and demographic variables of Hepatitis C patients. Results: The result showed that among 108, the most of the participants are the age group of 18-40 years and 58.3% are female. Emotional distress among hepatitis C patients undergoing antiviral therapy revealed varying degrees of emotional experiences and majority 45.4% of participants had severe distress. Conclusions: It was concluded that majority experienced severe emotional distress during antiviral therapy, offering valuable insights for interventions.

Calibration of Thermal Viscoelastic Material Models for the Dynamic Responses of PVB and SG Interlayer Materials.

Laminated glass interlayer materials polyvinyl butyral (PVB) and SentryGlas® (SG, kuraray, Houstan, TX, USA) exhibit thermal viscoelastic behavior under dynamic tensile loading. Significant temperature and strain rate effects on the behavior of these interlayer materials pose a challenge for accurately modeling the dynamic response of laminated glass. Many researchers have simplified their approaches by modeling the response of the interlayer material using a bilinear approximation or established hyperelastic models. However, temperature and strain rate effects can be captured using the three-network viscoplastic (TNV) model. Therefore, the objective of this study is to calibrate material models for the thermal viscoelastic dynamic responses of PVB and SG interlayer materials. Uniaxial tensile tests were performed at strain rates of 2, 20, and 45 s-1 and temperatures of 0, 23, and 60 °C, and material models were calibrated using the experimental data. Finite element analysis using the calibrated material models successfully predicted the dynamic responses of PVB and SG under the experimental test conditions within a 10% error margin. This suggests that the calibrated models using the TNV model represent significant improvements over existing approaches to modeling the dynamic response of laminated glass. Similar procedures can be applied to other thermoplastics, laying the groundwork for establishing a standard calibration guide.

Integration of electromagnetic and mechanical models for effective lightning protection in buildings

The study focused on the design of an advanced algorithm for the optimal sizing of protection systems against atmospheric discharges in architectural structures, applying the rolling sphere method. This technique facilitated the incorporation of user-specified parameters through an advanced graphical interface. The methodology began with the exhaustive accumulation of data relevant to the project. Risk indices were estimated through sophisticated risk analysis software applications. If adjustments were required, the process continued; If not, the building was considered to be adequately secured. The ground resistivity was evaluated according to IEEE Std. 81, and the rolling sphere method was implemented according to IEC 662305-3. The grounding systems were configured in accordance with IEEE Std. 142 and IEEE Std. 80. To analyze the interaction of electrical discharges with the protected building, the electrical equivalents of elements such as meshes, fused copper rods were computed. , and conductors positioned horizontally and vertically. Using these data, a model was built in ATPDraw, interconnected with Python for the generation of graphical representations of the current waves in the different protection subsystems. To conclude and corroborate the effectiveness of the process, the risk indices were reevaluated. The validation of the algorithm was achieved by minimizing the margin of error to insignificant levels by incorporating standardized data proposed by organizations such as IEC and IEEE, thus confirming the precision of the designed algorithm

Sustainability Level Analysis of the Application of 21st Century Skills By University Students

In order to meet the challenge of 21st-century skills, every human resource must be prepared with complex problem-solving skills. Colleges, particularly state colleges in Pekanbaru City, have a vested interest in helping their students develop 21st-century skills. To overcome these problems, we need a 21st-century approach for college students, particularly Riau University students. No one has yet evaluated the long-term viability of the use of 21st-century talents at Riau University. As a result, the author is interested in doing research to develop a strategy to improve students' 21st-century abilities at the University of Riau. The study was conducted solely on Riau University students. The Simple Random Sampling Technique was used to choose the samples. Riau University has a total of 35.785 students spread across the faculty. Based on the necessary sample size chart, the number of samples necessary is 654, with a confidence rating of 99% and a margin of error of 5%. As the results of the analysis, it is possible to identify multidimensional sustainability status at a value of 74.88, where this value is in the range of 50,01–75,00, with a fairly sustainable category. This condition gives the idea that the updating of 21st-century skills by students at Riau University is only in a sufficient category, or, in a state of warning to stakeholders. Riau University can ensure that its students not only have strong academic knowledge but also have the relevant and necessary skills to cope with the complex dynamics of the 21st century by implementing robust strategies and involving all stakeholders.

Influence of Religiosity on Occupational Well-Being and the Role of Mindfulness as a Mediator in Kindergarten Teachers as the SDGs Implementation

Early childhood educators are among those professionals susceptible to excessive job-related stressors. This study explores the relationship between religiosity, mindfulness, and occupational well-being and analyzes mindfulness's role as a mediator between religiosity and occupational well-being. Employing a quantitative correlational method, the study's population comprised 177 teachers from Aashiya Kindergarten in Sidoarjo. The Krejcie Morgan table with a 5% error margin determined a sample size of 118 teachers. The sampling technique used in data collection is accidental sampling techniques, using Google Forms to collect the data. Research instruments for religiosity, mindfulness, and occupational well-being were adapted, translated from previous studies, and validated for reliability. Data analysis used mediation analysis with path analysis technique, using JASP software. Findings indicated partial mediation, revealing that mindfulness mediates the relationship between religiosity and occupational well-being. Results imply that when accompanied by mindfulness, teachers' religiosity level can have a significant positive impact on early childhood teachers. This research can also be reference to future for well-being research in the context of occupation among teacher.

Assessment of thermal performance of energy-active window systems in hot climates

Window systems, particularly in hot climates, are the source of considerable heat transfer that affects the buildings’ indoor environment and energy consumption. Proper design and optimization of its thermal performance significantly contribute to the overall envelope energy performance. Using a multi-layer glazing system, Energy Active Window (EAW) adapts window insulation technology to reuse low-grade air from the HVAC system, keeping the temperature at the internal surface of the window close to the indoor air temperature, minimizing heat exchange between indoor and outdoor. This study aims to reduce energy consumption by optimizing EAW to increase its thermal resistance by channeling the return air (RA) from the HVAC system into the curtain frame, thereby lowering the temperature of the air gap and air film layer. The study examined the window system’s exhaust/return air behavior using the Computational Fluid Dynamics (CFD) tool (Fluent) to simulate the heat exchange between outdoor and indoor building environments. The CFD simulation was validated using experimental measurements. Results show a surface temperature decrease of 4 to 7 °C based on the inner and outer pane airflow conditions when the outdoor temperature is 45 °C with an 8 % margin of error. Various EAW components were tested, including air velocity, air–gap width, volume, and outdoor temperatures, examining both triple and double-glazing layers.