Statistical Regression Analysis Research Articles

Adaptive evaluation of gross total resection rates for endoscopic endonasal approach based on preoperative MRI morphological features of pituitary adenomas

ObjectiveThis study aims to define a set of related anatomical landmarks based on preoperative Magnetic Resonance Imaging (MRI) of patients with pituitary adenomas (PAs). It explores the impact of the dynamic relationships between different anatomical landmarks and the tumor on the resection rate and tumor progression/recurrence during the endoscopic endonasal approach (EEA).MethodsA single-center institutional database review was conducted, identifying patients with PAs treated with EEA from December 2018 to January 2023. Clinical data were reviewed, and anatomical landmarks were categorized into two regions: the suprasellar region and the cavernous sinus region. Following basic statistical and univariate logistic regression analyses, patients were randomly divided into training and validation sets. A nomogram was then established through the integration of least absolute shrinkage and selection operator (LASSO) regression and multivariable logistic regression analysis. The clinical prediction model was evaluated using the area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis. Kaplan-Meier curves were plotted for survival analysis.ResultsA total of 626 patients with PAs were included in the study, with gross total resection (GTR) achieved in 570 cases (91.05%). Significant differences were observed in the distribution of age, Knosp grade, and tumor size between the GTR and near total resection (NTR) groups. LASSO regression identified 8 key anatomical landmarks. The resulting model demonstrated an AUC of 0.96 in both the training and validation sets. Calibration curves indicated a strong agreement between the nomogram model and actual observations. Survival analysis revealed that the extent of resection (EOR), age, Knosp grade, tumor size, and PAs extending beyond several anatomical landmarks identified were significantly associated with the progression or recurrence of PAs.ConclusionThis study proposes a model for adaptively assessing the resection rate of PAs by delineating relevant anatomical landmarks. The model comprehensively considers instrument manipulation angles, surgical accessibility during EEA procedures, anatomical variations, and the displacement of related anatomical structures in pathological states. This approach can assist neurosurgeons in preoperative planning and developing personalized surgical strategies.

Pengaruh Budaya Religius dan Program Ubudiyah terhadap Pembinaan Akhlak Siswa SMPIT Assalamah Jakarta

<p><em>The research aims to assess how much the influence of religious cultural values through the ubudiyah program have on developing students' morals and to identify obstacles that may occur in its implementation. The research methodology used is a quantitative approach using a questionnaire as a data collection instrument. The research sample consisted of 38 students from various grade levels at SMPIT Assalaamah. The collected data was analyzed using descriptive statistical techniques and regression analysis to test the relationship between the variables studied. The partial test results show that religious culture has a positive effect on moral development. With </em>a<em> = 0,05, religious culture shows a significance value of 0,000 (0,000< 0,05) with a t count of 4,211. So 4,211 is greater than the t-table data obtained, which is 1,688 (4,211>1,688). Partial test results show that the Ubudiyah program has a significant positive influence on moral development. With </em>a<em>= 0,05, the Ubudiyah program achieves higher correlation and influence values. The ubudiyah program shows a significance value of 0,000 (0,000 < 0,05) with a calculated t of 6,785, making 6,785 greater than the data obtained from the t table, which is 1,688 (6,785 > 1,688). The implication of this research is the need to increase teacher supervision and understanding as well as the active participation of students in religious programs to maximize their impact in coaching and forming students' morals.</em><em></em></p>

Statistical Modeling of Space Mean Speed for Accurate Traffic Volume Estimation on Two-Lane Highways in IbadanMetropolis, Nigeria.

This study investigated the statistical modeling of Space MeanSpeed for traffic volume forecasting on two-lane highways in Ibadan metropolis in Nigeria. The focus was on two primary roads: Ojoo–Mokola Expressway and Mokola–Agodi Gates (Queen Elizabeth Road). Statistical Regression analysis model were developed to represent the relationship between space mean speed (u) and traffic density (k). The results obtained revealed correlation coefficient (R) value of 0.9333 and correlation determination (R²) value of 0.9876 for the Ojoo – Mokola Expressway and correlation coefficient (R) value of 0.8762 and correlation determination (R²) value of 0.7863 for Mokola – Agodi Gates road; with both road network indicated a positive linear correlation between space mean speed and traffic density. Furthermore, the calibrated space mean speedtraffic density model for both road networks indicated that Ojoo–Mokola road had a better R and R² than Mokola–Agodi Gate road. The increase in space mean speed with increasing traffic density during the peak hour was consistent with previous literature. The research provided useful insights for traffic management system and speed control measures, recommending further studies to reduce traffic congestion and improve road safety in Nigeria.

Determinan Financial Distress: A Study on The Property and Real Estate Sector in The Indonesia Stock Exchange

The property and real estate sector plays a crucial role in the Indonesian economy but faces significant risks of financial distress. This study aims to identify the determinants of financial distress within this sector, focusing on companies listed on the Indonesia Stock Exchange between 2018 and 2022. The research examines the effects of profitability, liquidity, leverage, interest rates, and inflation on financial distress. Using a quantitative approach, this study applies statistical techniques and regression analysis to secondary data from various property and real estate companies. The findings reveal that: (i) profitability has a negative impact on financial distress, indicating that lower profitability increases the likelihood of financial difficulties; (ii) liquidity also shows a negative relationship with financial distress, meaning reduced liquidity elevates financial risk; (iii) leverage negatively influences financial distress, suggesting that higher debt levels exacerbate financial instability; (iv) rising interest rates contribute to financial distress by increasing borrowing costs, thereby straining company resources; and (v) inflation worsens financial distress by eroding purchasing power and dampening property demand. This study provides valuable insights for stakeholders, including investors and policymakers, to enhance their understanding of financial risk management in the property and real estate sector. The novelty of this research lies in its specific focus on a critical period and sector within the Indonesian economic landscape, addressing key areas of concern for financial stability

Evaluating a Virtual Reality Game to Enhance Teen Distracted Driving Education: Mixed Methods Pilot Study.

Inexperienced adolescent drivers are particularly susceptible to engaging in distracted driving behaviors (DDBs) such as texting while driving (TWD). Traditional driver education approaches have shown limited success in reducing motor vehicle crashes among young drivers. We tested an innovative approach to help address the critical issue of DDB among teenagers. We investigated the effectiveness of using a novel virtual reality (VR) game "Distracted Navigator" to educate novice teenage drivers about DDB. The game consisted of maneuvering a spaceship around asteroids while engaging in simulated DDB (eg, inputting numbers into a keypad). A physician-facilitated discussion, based on the theory of planned behavior, linked gameplay to real-life driving. Teenagers were recruited for the in-person study and randomly assigned at the block level to intervention (VR gameplay or discussion) and control groups (discussion only), approximating a 2:1 ratio. Unblinded, bivariate statistical analyses (all 2-tailed t tests or chi-square tests) and regression analyses measured programming impact on TWD-related beliefs and intentions. Content analysis of focus group interviews identified thematic feedback on the programming. Of the 24 participants, 15 (63%) were male; their ages ranged from 14 to 17 (mean 15.8, SD 0.92) years, and all owned cell phones. Compared to the control group (n=7, 29%), the intervention group (n=17, 71%) was more likely to report that the programming had positively changed how they felt about texting and driving (?218=-8.3; P=.02). However, specific TWD attitudes and intentions were not different by treatment status. Irrespective of treatment, pre- and postintervention scores indicated reduced confidence in safely TWD (ie, perceived behavioral control; β=-.78; t46=-2.66; P=.01). Thematic analysis revealed the following: (1) the VR gameplay adeptly portrayed real-world consequences of texting and driving, (2) participants highly valued the interactive nature of the VR game and discussion, (3) both the VR game and facilitated discussion were deemed as integral and complementary components, and (4) feedback for improving the VR game and discussion. Our findings show that the novel use of immersive VR experiences with interactive discussions can raise awareness of DDB consequences and is a promising method to enhance driving safety education. The widespread accessibility of VR technology allows for scalable integration into driver training programs, warranting a larger, prospective, randomized study.

Connecting the Computer Skills with General Performance of Companies—An Eastern European Study

In the current era, the economic model that measures the dependence of the training offered by companies to their employees on certain variables allows for identifying the steps taken on account of digital transformations, given the fact that companies want to be competitive, to develop sustainably and the positive effect to it spreads globally. However, how digital transformation contributes remains unclear in both the literature and practice. Five descriptors of information on the economy in relation to the digital economy were extracted from the Eurostat database, and data on eight Eastern European countries in the period 2012–2020 served as primary data in the analysis. A generalized linear model was used as a statistical tool to infer the data series. Following the statistical regression analysis, it was found that the variable measuring the share of companies that offered training for the development/improvement of information and communication technology (ICT) skills is influenced by the combined effect of several other variables: ‘country’, ‘country × year’, ‘country × share of ICT personnel in total employees’, year × “share of ICT sector in GDP”. Based on the results, we noticed that the studied countries are included in two groups with distinct features, which influence the obtained GLZ model, showing the increase in the dependency effect or, on the contrary, the decrease in this effect.

Trends in the Use of Augmented Reality in Character Development within Local Wisdom in Schools: A Bibliometric Study

This paper provides a thorough assessment and analysis of prior research literature. The objective of this review is to ascertain the disparities in research about the Application of Augmented Reality in character development and to determine the best actions to continue this research. This goal is achieved through bibliometric analysis and descriptive content. The keywords "Augmented reality" and "character" were Derived from the Scopus research database for bibliometric analysis. Publications from 2014 to 2024 can only be accessed. The data indicate a substantial rise in the amount Investigation carried out on the application of augmented reality in character development. Specifically, there were 22 papers published in 2022, marking the largest amount of studies and citations was documented during that year. The IEEE Transactions on Visualization and Computer Graphics journal is the most cited source. Quantitative methods are used more often than qualitative methods. Methods such as Descriptive Statistical Analysis and Regression Analysis are the most frequently used, with fifty and forty-five occurrences, respectively. This research could be a valuable reference for other academics exploring the implementation of augmented reality in character analysis. Moreover, the presence of research deficiencies can motivate other scholars to confront these deficiencies with the aim of enhancing the utilization of augmented reality in the cultivation of character in children.

Effect of Teachers Attitudes towards Teaching on Students’ Performance in Mathematics Subject in Public Day Secondary Schools in Rwanda: A Case of Huye District

The study investigated how teachers' attitudes toward teaching influenced students' academic progress in mathematics in a public secondary school in Huye District. Specifically, the research identifies the teachers' attitudes toward teaching that could influence the achievement of pupils in Mathematics-related subjects in public day secondary schools in Huye district. Guided by the Theory of Planned Behavior, this study used a combined method approach to collect both quantitative and qualitative data to examine how teachers' attitudes influence their teaching practices in Mathematics. Purposive and random sampling were applied to select sectors, schools, and participants, allowing for systematic data collection and analysis on teachers' attitudes and their influence on students’ performance. The target population for this study was 200, including 3 sector educational officers, 5 head teachers, 25 mathematics teachers and 167 Mathematics students; and the Yamane method was used to calculate a sample size of 134 respondents including 2 sector educational officers, 3 Head teachers, 15 teachers and 114 students. Primary data sources included surveys, while secondary data came from observation and interview methods. This study used purposive, stratified and simple random sampling procedures to create a sample group of respondents. The research collected and analyzed data using both quantitative and qualitative approaches. Content analysis helped with qualitative data analysis, while quantitative data was presented in SPSS Version 21.0 utilizing statistical methods such as descriptive (frequency, percentage, imply and deviation from the mean) and inferential statistics (correlational and regression analysis). For the study objective, the results show that 76.3% strongly agreed that teachers' communication skills, 69.3% strongly agreed that effective goal-setting, 64.9% strongly agreed that lesson preparation, 61.4% strongly agreed that lesson preparation, 78.1% strongly accepted that professional commitment, and 68.0% highly agreed that adaptability and flexibility reflect my teachers' attitudes toward teaching. 64.9% strongly agreed that early arrival in class during the teaching lesson reflects the teachers' attitudes toward teaching. The study found a strong positive correlation between exams, test results, and factors like interpersonal skills, goal-setting, lesson preparation, and professional commitment, which all contributed to improved student performance. The researcher concluded that early attendance and communication skills of teachers were also linked to positive educational outcomes, with tests enhancing performance across subjects. With a p-value below 0.05, the study showed that active class participation boosts effectiveness. Recommendations included improving teacher attitudes towards math, enhancing confidence, making Math enjoyable, investing in teacher training, providing resources and encouraging community involvement in Math careers. Regular follow-ups and ongoing professional development for teachers were also advised.

Statistical analysis of the impact of profitability in the manufacturing and service sectors on the UK Economy’s Growth

The UK economy's performance is closely tied to the profitability of its Manufacturing Sector (MS) and Service Sector (SS). Understanding these sectors' dynamics is crucial for effective policymaking. Integrating sustainable practices in both sectors enhances profitability and operational efficiency while contributing to economic growth and reducing environmental impact. This study investigates the relationship between UK economic growth and profitability in the MS and SS from 1998 to 2022. The primary objective is to examine how profitability influences the UK's growth trajectory. Employing various statistical methods, including correlation, regression, cointegration, and variance decomposition analyses, the study aims to provide insights into the interplay between GDP and sector profitability. A quantitative approach using secondary data on GDP and profitability from reliable sources is adopted. Correlation analysis explores relationships between these variables, while regression analysis assesses the impact of MS and SS profitability on GDP. Cointegration tests identify long-term equilibrium relationships, and variance decomposition analysis reveals the variability of GDP and sector profitability over time. The correlation matrix indicates positive associations between GDP and both sectors, with the SS showing a stronger correlation. Regression analysis confirms significant effects of both sectors on GDP, with the SS exerting a positive influence and the MS a negative impact. Cointegration tests highlight long-term stability, and variance decomposition analysis emphasizes the dynamic nature of these relationships. This study elucidates the intricate link between UK economic growth and sector profitability, underscoring the SS's critical role in driving expansion while addressing challenges in the MS. Policy recommendations include enhancing productivity and innovation in both sectors, informed by evidence-based decision-making. Overall, the study contributes valuable insights into the UK economy's growth dynamics, guiding sustainable economic development strategies.

The Effect of Maternal Attachment on Independence and Self-Confidence of 4-5 Years Old Children from the Aspect of Mother’s Occupation Status

This study was conducted to determine the effect of maternal attachment on independence and self-confidence of 4-5 years old children from the aspect of Mother’s Occupation Status. This research was quantitative research. The population and sample in this study were working and non-working mothers who had children aged 4-5 years in Kradenan Village, Grobogan Regency, totalling 92 people consisting of 27 working mothers and 65 non-working mothers. The sample collection technique in this study was a saturated sample, where all populations were used as research samples. The data analysis technique in this study used descriptive and regression statistical analysis using the SPSS 23 program. The results of this study found that maternal attachment affected the independence of 4-5 years old children; maternal attachment affected the self-confidence of 4-5 years old children; maternal attachment affected the children’s independence by controlling the status of mother’s occupation; maternal attachment affected children’s self-confidence by controlling the status of mother’s occupation. Keywords: Maternal Attachment, Children Independence, Children Self-confidence, Mother’s Occupation Status

Feedback Spillovers across Unrelated Tasks

In this paper we describe the results of a laboratory experiment involving 130 students of Lomonosov Moscow State University. The participants were asked to perform unrelated tasks involving different skills: a test of analytical skills and a capitals quiz. After the first task, participants in the treatment group are given feedback on whether they did better or worse than half of the other participants in their group. This feedback is uninformative about the new task, as success or failure in the analytical ability test is not related to whether the individual knows the countries and their capitals. It is revealed that students respond to negative feedback: participants from the group that received negative feedback significantly lower their probability of success in the next task. The peculiarity of the work is to conduct the experiment within 2 days in order to avoid the occurrence of the “hot hand error” described in previous studies. Statistical tests and regression analysis as well as bootstrap are used to test the hypotheses. A time-stable effect of uninformative relative to the new task feedback is obtained.

Investigating carbon peak prediction scenarios and implementation strategies in higher education institutions: A case study of Shandong Jianzhu university

The potential for energy conservation and emission reduction in Chinese universities is significant. The exploration of scenarios for predicting carbon peaking and identifying implementation pathways can offer valuable insights and demonstrations for achieving dual carbon goals. This paper develops a research methodology for carbon peaking in universities, with a focus on four main aspects: carbon emission accounting, the analysis of influencing factors, carbon emission prediction, and implementation pathways for carbon peaking. By utilizing the campus of Shandong Jianzhu University as a case study, the paper practically demonstrates the prediction of carbon peaking scenarios and offers technical solutions for universities. The results demonstrate that: (1) Using the Logarithmic Mean Divisia Index (LMDI) decomposition method to investigate the influencing factors of carbon emissions in universities, we confirm that the energy structure effect, economic effect, and population effect have a promoting impact on the increase of carbon emissions at Shandong Jianzhu University, while the energy intensity effect exhibits a significant inhibitory effect. (2) By employing Partial Least Squares (PLS) regression analysis of annual carbon emission statistics from universities, we construct a STIRPAT model with high predictive accuracy for carbon emission regression. The carbon emission prediction model for Shandong Jianzhu University is: lnC^t=-25.899+3.571lnPt+0.966lnARt+0.716lnTMt-0.279lnTEt (3) Both the low-carbon scenario and the enhanced scenario for Shandong Jianzhu University are capable of achieving carbon peaking by 2027. From the perspectives of energy-saving renovation of existing building envelopes, improving the efficiency of lighting systems, utilizing solar photovoltaic buildings, and electrifying cooking energy, implementation pathways for carbon peaking under low-carbon and enhanced scenarios are delineated.

Data-Driven Decisions: Leveraging Analytics for Strategic Marketing Management

This study investigates the impact of data-driven decision-making, customer data utilization, and predictive analytics on the marketing performance of small and medium enterprises (SMEs) in Medan. Utilizing a quantitative research design, data was collected through structured questionnaires from a sample of 83 SMEs that possess a Business Identification Number (NIB). The analysis involved statistical techniques, including t-tests, F-tests, and regression analysis, using the Statistical Package for the Social Sciences (SPSS). The results reveal a significant positive relationship between the independent variables and marketing performance, with the regression model explaining approximately 58.3% of the variance in marketing outcomes. Findings indicate that prioritizing data-driven strategies can lead to enhanced decision-making and improved business performance for SMEs. This research contributes valuable insights for practitioners and scholars by highlighting the critical role of analytics in developing effective marketing strategies and fostering sustainable growth in a competitive landscape.

Shaping The Future of Work Readiness of Internship Students : Role of Gen Z’s Resilience

This study aims to analyze the role of resilience on work readiness in MBKM (Merdeka Belajar Kampus Merdeka) internship students. Non-experimental correlational study design was used. A quantitative approach through regression and descriptive statistical analysis was used to analyze the collected data. Non-probability sampling, specifically the convenience sampling, was also used. Data collection was carried out through an online questionnaire using Google Forms. The respondents consisted of 140 students from a university in West Java who had participated in the MBKM internship program. The Resilience Quotient Test (RQ-Test) and Work Readiness Scale (WRS) were used to measure resilience and work readiness, respectively. The result of this study showed that resilience had a significant role on work readiness (r2 = 0.285; p = 0.000). This study is expected to present information and contribute theoretically towards resilience and its role towards work readiness in MBKM internship students. The result of this study can be used by students that participate in the internship program to evaluate themselves and to show them the importance of developing resilience for their work readiness in the future.

Oxygen-Carbon and Strontium Isotope Composition in Primary Carbonatites of the World: The Data Summary and Linear Trends

A statistical regression analysis was performed of a summary of borrowed literary isotopic data on 176 carbonatite occurrences worldwide (a total of 1829 paired δ18О-δ13С values in primary carbonatites). For most of the occurrences, distinct linear trends in δ18О-δ13С values were revealed, approximated in diagrams by vectors using the regression formula y = kx + b. Trends in three directions are distinguished. The dominating trend possesses the angular coefficient k in the range of 0.0÷+0.6, averaging at + 0.31 (direct correlation δ18О-δ13С). In the literature, it is associated with the Rayleigh high-temperature fractionation of carbonatite melts or with their sedimentary crustal contamination. The second trend with k from 0.0 to -0.7 (inverse correlation δ18О-δ13С) is associated with CO2 degassing from the melts. The third trend with k from +0.6 to +1.5 is rare. In other carbonatite occurrences, no linear trends in δ18О-δ13С values are detected. This may be a consequence of a combined action of the multidirectional linear trends. In this regard, the initial point of the trend vectors is accepted as a universal isotope indicator for all the carbonatite occurrences. In the δ18О-δ13С diagram, the box PC-90 is outlined in the field of the initial points, including 90 % of the primary carbonatite occurrences. The coordinates of the corner points of the box in δ18О-δ13С ‰ are (+5÷-8), (+5÷-5), (+5.5÷-2.5), (+12÷-2.5), (+12÷-7), (+9÷-8.5). The box PC-90 is subdivided into two parts by the carbon isotope composition, using the value δ13C = -5.2 ‰. This suggests that the deep sources differ in carbon isotope composition. No correlation is found in the oxygen-carbon and strontium isotope compositions in the carbonatites, which suggests that the deep sources are also heterogeneous in the strontium isotope composition.

The Influence of Weather Temperature on Crime Occurrence in Babylon Province

Objectives: This study investigates the influence of temperature fluctuation on specific types of crimes in Babylon in Iraq. It also analyzes how varying temperatures leave an impact on crime patterns and trajectories. Methods: The study uses quantitative analysis, descriptive statistics, and Geographic Information Systems (GIS) to examine temperature and crime data. Statistical techniques, including correlation and regression analysis, are applied to assess the relationships between temperature variables and crime rates. Results: The study results showed that there is a strong affinity between temperatures and crime rates. Murder crimes reach their peak in hot summer months. The study also showed that theft crimes, including burglary, increase during cold winter months. Statistical analysis validates these findings, highlighting a direct correlation between temperature and murder rates and an inverse correlation with theft rates. Conclusions: This study confirms the huge impact of temperature fluctuation on criminal behavior in Babylon, Iraq. Recognizing these seasonal variations may help construct effective crime prevention strategies. Additionally, the study explores multiple theoretical perspectives, underlining the importance of adopting a multidisciplinary approach to comprehensively grasp the intricate relationship between climate and crime.

Excessive Gestational Weight Gain, Independent of Body Mass Index, Is Associated With Child Fat Mass Index at Age 2 Years in the Growing life, Optimizing Wellness Study

BackgroundExcessive gestational weight gain (eGWG) increases risk for pregnancy complications and future obesity for pregnant persons and children. Yet, it is unclear whether eGWG leads to higher child adiposity at 2 years, independent of the pregnant person’s body mass index (BMI) while considering important covariates. Moreover, understanding the characteristics of pregnant persons experiencing eGWG will help design future targeted interventions. ObjectiveThe objectives of the analyses were to assess the association between eGWG and childhood adiposity at age 2 years, while controlling for pregnant persons’ BMI and other important covariates and to describe the characteristics of pregnant persons who experience eGWG during their second pregnancy. DesignThis is a secondary analysis of 221 pregnant persons and their children aged 2 years who were enrolled in the Growing Life, Optimizing Wellness longitudinal observational study. Participants/settingParticipants were recruited between 2011 and 2014 in central Arkansas. Participants were secundigravida persons with BMI 18.5 to 35, older than age 20 years, and who conceived without assistance. Main outcome measuresThe main outcome measure was fat mass index of children aged 2 years measured by quantitative nuclear magnetic resonance imaging. Secondary outcomes included first pregnancy GWG, dietary and physical activity characteristics between pregnancies, second pregnancy nausea levels, and motivation level to adhere to the GWG guidelines. Statistical analysis performedMultivariable regression analyses were used to examine the associations between GWG and childhood fat mass index at age 2 years. Pearson correlations and Wilcoxon rank sum tests were used to identify the characteristics of pregnant persons who experienced eGWG. ResultsPregnant persons’ eGWG (β = .503; P = .03) was positively associated with child adiposity at age 2 years independent of maternal BMI (P = 0.3). Pregnant persons who experienced eGWG during their second pregnancy had greater odds of eGWG during first pregnancies (odds ratio 7.5; P < .001), dieting behavior (odds ratio 14.3; P = .02), and low motivation to adhere to the GWG guidelines (odds ratio 11.2; P = .009). Fewer participants had eGWG during their second pregnancy (52.5%) compared with their first pregnancy (66.8%), which was different by BMI groups (BMI 18.5 to 24.9: 23.6% decrease in participants who gained eGWG, BMI 25 to 29.9: 20.0% decrease, and BMI ≥ 30: 37.9% decrease). ConclusionseGWG among pregnant persons is associated with child adiposity at age 2 years. Pregnant persons who experienced eGWG during their second pregnancy reported low motivation to gain weight within guidelines, eGWG in first pregnancy, and reported prior dieting behavior. Future research focusing on patients with these characteristics may increase success of interventions designed to limit eGWG.

Psychosocial Impact of Covid-19 Pandemic on Women’s Mental Health

Women mental health and impact of psychosocial factors on it, is highlighted in various psychological &amp; clinical studies, due to pandemic made it a matter of more focus. Studying the long-term impacts of the coronavirus on society, our mind, body and its analysis perhaps will take more time. Out of the total population, a number of people felt a disrupted sleep as a hallmark of the pandemic, and suffered from depression, insomnia, irritability, violence including domestic violence, distress, work pressure due to online culture of work, and other related negative mental health symptoms as idiosyncratic attributes especially in covid sufferers. Covid-19 pandemic has altered family dynamics. More screen time, unended &amp; fluctuated routines, for working women dissolving boundaries in workplace and personal life altered &amp; flicking habits, all impacted mental health adversely. The human brain is evolved to live in social groups &amp; wired for social interactions, epidemiological studies conducted on covid survivors, convalescents &amp; victims shows altered brain biochemistry due to various psychosocial factors including financial losses, social isolation, intimate partner’s negative mental state, discrimination, disrupted sleep &amp; routines, etc. Pandemic might has altered the romantic and loving relationships, and adversity of such psychosocial factors impacted people. Psychological strengths and resilience mainly depend on social determinants like social support, social culture, respect, engagement at workplace, parenting style in childhood &amp; emotional attachment, society &amp; family bonds, self-regulation &amp; behavior controlling, and collective efficacy, all these determinants are positively associated with self-esteem that have direct impact on enhancing psychological strengths. Population for the study as participants were females in early adulthood &amp; studying, professional and housewives. For data analysis, the statistical tools, descriptive, co-relational and regression analysis is used. The study focuses on effect of adverse aspects of adversity like pandemics financial crises like job losses, allowances or salary deductions, led to economic abuses, and somewhere gender discrimination, sexual abuse, household workload, escalation in family members expectations and responsibilities, adverse impact of these psychosocial factors on women’s mental health and role of education, knowledge, skills, and aptitude i.e. abilities &amp; cognitive competencies in coping and managing the adversities like pandemic.

Medications Associated with Geriatric Syndromes and Prescribing Patterns: The Impact of Excessive Polypharmacy in Older Adult Patients.

To assess the prescribing patterns of medications associated with geriatric syndromes (MAGS) in older adult patients with multiple comorbidities and to identify factors that may increase the risk of MAGS prescribing in the same population. This study involved a retrospective analysis of the electronic medical records of older adult patients (≥ 65 years) who visited outpatient clinics at King Abdullah University Hospital (KAUH) in Jordan between January 1, 2019, and June 1, 2024. The collected data included patient demographics, medical history, and medications, focusing on those associated with geriatric syndromes. Descriptive and logistic regression statistical analyses were performed using SPSS with the significance level set at p < 0.05. The study included 1087 older adult patients (52.7% female), with a median age of 71 years. The common conditions existed were peptic ulcer disease (57.1%), hypertension (54.65%), and uncomplicated diabetes (50%). Polypharmacy was presented in 94.8% of total patients number, with 41.6% experiencing excessive polypharmacy. Antihypertensives (78.4%), non-opioid analgesics (56.5%), and antidiabetics (51.8%) were the most frequently prescribed MAGS, which frequently resulted in falls (96%), urinary incontinence (87.6%), and depression (87.3%). Patients with excessive polypharmacy had significantly higher MAGS scores than those with moderate or mild polypharmacy (95% CI: -2.230 to -1.770 and -3.322 to -2.678, respectively, P < 0.001). The findings demonstrate a high prevalence of excessive polypharmacy among older adult patients, significantly contributing to the elevated prescription level of medications associated with geriatric syndrome occurrence, particularly falls, urinary incontinence, and depression.

Impact of Material Balance Calculation on Trapped Gas in Water-drive Gas Reservoir

Abstract The development of water-drive gas reservoir takes a very important position in China. Not only its recovery is markedly lower than that of dry gas reservoir, but also its residual gas saturation is higher. The main reason has been proven in the lab is water invasion which can generate trapped gas by sealing gas in porous media. However, it is still difficult to calculate the volume of trapped gas theoretically and practically. In order to quantify trapped gas, we designed experiments to simulate the development of water-drive gas reservoir. The experimental system can provide accurate measurements on gas production, water influx, pressure and so on. The results showed that the original material balance equations are not consistent with experimental data when water invasion happens. With water influx increasing, the errors become more obvious. This phenomenon has been repeated for many times in our lab. On basis of this phenomenon and with the analysis of many experimental data, we observed that water influx causes some high pressure trapped gas which is not considered in original material balance equation. By regression analysis, we proposed a correction term which can be added to the original material balance equation to effectively eliminate the disagreements between the results of original equation and the experiments. The modified material balance equation was also verified by field cases. The correction term can be applied to quantify the degree of trapped gas, which is significant to calculate the water influx and to predict production and improves the original material balance equation so that the trapped gas in water-drive gas reservoir can be fully considered. The correction term is proposed through statistical regression analysis based on a large number of experimental data. The modified material balance equation with the correction term can quantify the trapped gas and have a great significant impact on the development of water-drive gas reservoir, especially on the water influx calculation and production prediction.