Variance In Performance Research Articles

Technology Integration in Predicting Financial Performance: Big Data, Intellectual Capital, and Board Diversity

The relationship between technological integration, diversity on the board, and intellectual capital management and how these factors affect the financial performance of Indonesian start-ups is examined in this study. Structural Equation Modeling (SEM) using Partial Least Squares (PLS) approach is used in this work to evaluate the intricate interactions among these critical parameters using a diverse sample of 195 start-ups. A thorough knowledge of the dynamics that influence startups' financial success is facilitated by the use of descriptive statistics, measurement model assessment, and structural model analysis. The findings indicate that there are strong positive correlations between financial performance and board diversity, intellectual capital, and technological integration. Furthermore, the mechanisms involved are clarified by mediation effects. The model explains half of the variance in financial performance (R2 = 0.504) and demonstrates strong predictive relevance (Q2 = 0.354). For practitioners, politicians, and investors navigating Indonesia's competitive start-up entrepreneurship scene, the findings provide insightful information.

A survey of transmission control protocol variants

TCP (Transmission Control Protocol), is a reliable connection oriented end-to-end protocol. It contains within itself, mechanisms for ensuring reliability by requiring the receiver to acknowledge the segments that it receives. The network is not perfect and a small percentage of packets are lost enroute, either due to network error or due to the fact that there is congestion in the network and the routers are dropping packets. TCP ensures reliability by starting a timer whenever it sends a segment. If it does not receive an acknowledgement from the receiver within the ‘time-out’ interval then it retransmits the segment. In this paper a review of various TCP is carried out. There are a number of TCP variants for application in the management of network efficiency in terms of network congestion and transmission efficiency. These variants include: - TCP Tahoe, TCP Reno, TCP New Reno, TCP Vegas, TCP SACK, TCP FACK, TCP Asym, TCP RBP, Full TCP and TCP CUBIC. Therefore, the main objective of this paper is to study the tcp types on the network performance variances. All have different features and advantages but with maximal throughput as main objective, which are termed as the clones of TCP, have been incorporated into TCP/IP protocol for handling congestion efficiently in different network scenarios.

Response to Difficulty Drives Variation in IQ Test Performance.

In a large (N = 300), pre-registered experiment and data analysis model, we find that individual variation in overall performance on Raven's Progressive Matrices is substantially driven by differential strategizing in the face of difficulty. Some participants choose to spend more time on hard problems while others choose to spend less and these differences explain about 42% of the variance in overall performance. In a data analysis jointly predicting participants' reaction times and accuracy on each item, we find that the Raven's task captures at most half of participants' variation in time-controlled ability (48%) down to almost none (3%), depending on which notion of ability is assumed. Our results highlight the role that confounding factors such as motivation play in explaining individuals' differential performance in IQ testing.

Performance Measurement Integration And Performance Of Manufacturing Firms in Rwanda

Rwanda's manufacturing industry is essential to the country's economic growth and employment generation. Achieving sustainable development and global competitiveness necessitates the integration of performance assessment effectively. This entails measuring and optimizing organizational performance, especially in supply chains, using a variety of measures. Global market trends and resource limitations are two ongoing challenges that emphasize the necessity for reliable measuring methods. In order to give policymakers and business practitioners useful information, this study aims to assess the effect of performance measurement integration on manufacturing company performance in Rwanda, concentrating on important industries and geographical areas. Expectancy Theory and the Balanced Scorecard Framework (BSC), two important theoretical frameworks related to performance measurement integration in manufacturing businesses, are examined in the literature study. According to expectation theory, people are driven by their conviction that performance, effort, and results are all related. The BSC provides a strategy-based framework for decision-making at various organizational levels. It was created by Kaplan and Norton. The significance of integrating performance assessment in order to increase productivity, quality, customer happiness, and decision-making for small and medium-sized enterprises (SMEs) is underscored by empirical research. Performance in manufacturing is evaluated and optimized via the use of a variety of instruments and methods, including the BSC and KPIs. 
 The study methodology utilized a quantitative analytic strategy with an explanatory approach to comprehend the relationship between manufacturing company performance and supply chain integration. The research philosophy was shaped by positivism, which prioritized quantitative approaches. Semi-structured questionnaires were used to gather data from 213 manufacturing companies; 94% of the respondents answered the questions. The integration of performance measurement has been found to have a favorable influence on the performance of manufacturing organizations through effective communication, information exchange, and strategic supplier relationships. These findings were supported by descriptive statistics. The findings showed a positive relationship between measurement integration and company performance, with integration accounting for 49.9% of the variance in performance. The results showed that efficient decision-making and information exchange among supply chain participants were influenced. Notably, framework agreements with key suppliers were frequently used in emergency situations. The functions of logistics companies, funders, governments, media, and security personnel in relief efforts were emphasized using qualitative analysis. Issues with inadequate coordination and information exchange were noted. Enhancing IT infrastructure, adopting emerging technologies, collaborating with many stakeholders, and establishing legal frameworks for production readiness are among the recommendations. The study emphasizes how crucial technology, collaboration, and integration are to maximizing the performance of industrial firms and disaster relief in Rwanda.

Abstract P256: Rationale, Development, and Implementation of a Multidisciplinary Digital Lifestyle Health Education Program for Older Adults With Cardiovascular Disease and Osteoarthritis

Introduction: Cardiovascular disease (CVD) is the leading cause of death worldwide. Globally, osteoarthritis (OA) affects 654 million. In 2018, of the 1.2 million Australians who had CVD, half also had arthritis, with the most common form in Australia being OA. Ongoing pain and physical limitations from OA can affect lifestyle choices, contributing to the shared risk factor profile of CVD and OA (physical inactivity, overweight/obesity, poor diet, high medication use). This contributes further to the burden of both diseases including reduced 6-minute walk (6MW) performance, which is directly related to increased CVD mortality. This project outlines the rationale for and development of a multidisciplinary digital lifestyle health education program for the treatment and secondary prevention of CVD and its common comorbidity of OA. Methods: This study is a cross-sectional analysis of older adults in Sydney. Class was classified based on the Australian socioeconomic index for areas. Conditions were defined according to Australian national guidelines. Medical history, body mass index (BMI), waist measurement, muscle strength, and 6MW measurements were assessed. Differences between those with and without OA were determined via one-way analysis of variance. Simple linear regressions assessed potential relationships. Results: In a cohort of 532 adults; n=341 (64.1%) had diagnosed CVD; 48.4% of which had OA (mean age 66±12 years; 73.3% female). Socioeconomic index was deemed high. In the OA cohort mean BMI and waist were above healthy heart recommendations according to the World Health Organisation. There were no significant differences between those with OA and those without for cardiovascular risk factors of body weight, BMI, waist measurement, blood pressure, 6MW, or muscle strength. However, in those with CVD and OA, the relationship between age and 6MW was stronger and age accounted for more of the variance in performance (r=-0.44; r 2 =0.19; p<0.001) than those without OA (r=-0.37; r 2 =0.17; p<0.001), indicating a greater reduction in walking ability in those with OA as they get older. Conclusion: With 6MW performance being related to CVD mortality, interventions are needed to improve health and fitness in this cohort. International guidelines for CVD and OA recommend treatment should prioritise lifestyle changes, including a healthy diet, regular physical activity, and interventions that address all risk factors. Lifestyle LIFEMAP will assess the efficacy of a widely translatable multidisciplinary digital evidence-based 10-module lifestyle, food, exercise, medication, and park prescription education program for adults with the comorbidity of CVD and OA. We expect this program to improve knowledge, and healthy lifestyle choices, thereby improving physical activity and health outcomes in this highly vulnerable population.

Impact Of Academic Supervision on Improving Performance of Early Childhood Education Teachers in Early Age Learning

This research aims to understand and describe the implementation of academic supervision by school principals; assess the performance of Early Childhood Education (PAUD) teachers; determine the influence of academic supervision on PAUD teacher performance; and identify the impact of academic supervision implementation on PAUD teacher performance. This study employed an ex-post facto correlational research design. The population consisted of 594 respondents from various PAUD institutions, with a sample size of 44 respondents selected using Stratified Random Sampling based on the accreditation status of the PAUD institutions. Data were collected through non-test methods, including questionnaires validated using Likert scales and Cronbach's Alpha reliability test, interviews, observations, and documentation. Instrument content validity was 0.89 < 0.75, and reliability was 0.815 < 0.6. Data analysis involved parametric statistical analysis and Spearman correlation tests.
 The findings revealed: 1) Academic supervision by school principals in Manggarai Raya was implemented with a percentage of 40% for accreditation A, indicating excellent performance. However, when viewed comprehensively, it was considered low or unsatisfactory due to being below 50%; 2) PAUD teacher performance in Manggarai Raya, assessed using all indicators, fell into the very good category with a percentage of 20%. Yet, when viewed holistically, it was deemed inadequate/poor as it was below 50%; 3) There was a positive influence of academic supervision by school principals on PAUD teacher performance in Manggarai Raya, with a Cohen's value of 0.99, indicating that 99% of the variance in teacher performance was influenced by academic supervision by school principals; 4) The contribution of academic supervision to PAUD teacher performance in Manggarai Raya, assessed using an R2 coefficient, was 0.27% or 27%; and 5) There was an impact of academic supervision on PAUD teacher performance.
 Keywords: academic supervision, PAUD teacher performance

Effect of Strategic Leadership on Performance of SMEs During Covid-19 Pandemic in Nairobi County, Kenya

The global economy and enterprises have faced significant impacts due to the COVID-19 pandemic, necessitating leadership styles capable of navigating change and uncertainty effectively. Strategic leadership has emerged as a promising approach for establishing agile strategies amidst rapid transformations in business environments. This study aimed to assess the impact of strategic leadership on the performance of Small and Medium-sized Enterprises (SMEs) during the pandemic in Nairobi County, Kenya. Employing a descriptive and correlational research design, the study targeted 584 respondents from various SME industries in Kenya, with 237 respondents obtained using a stratified random sampling technique. Descriptive and inferential statistics, including correlation and regression analyses, were conducted using SPSS version 23. The findings revealed that SMEs in Nairobi County recognized the importance of strategic leadership for their prosperity, with a significant positive correlation between strategic leadership and performance (r (183) = 0.430, p < 0.05). Strategic leadership accounted for 18.5% of performance variance, indicating a substantial impact (F (1,181) = 41.174, p < 0.05). Moreover, the intercept between strategic leadership and performance showed a notable improvement (β = 0.230, p < 0.01), suggesting a 23% performance enhancement with effective strategic leadership implementation. In conclusion, the majority of SMEs in Nairobi County demonstrated strong strategic leadership, fostering absorptive and adaptive capacities crucial for navigating turbulent business environments. The study underscores the importance of institutionalizing strategic leadership within SMEs to enhance their ability to formulate and execute strategies effectively amidst rapid changes.

Modelling business performance from marketing practices of architecture firms in Nigeria

Purpose This study aims to establish marketing practices which predict business performance of architecture firms within the Nigerian Construction Industry (NCI) to address the sustained poor business performance of firms, which affects allied professionals as many projects in the built environment depend on design proposals from architects. Design/methodology/approach Survey responses from 86 firms were used to model business performance measured as total revenue of the firms from 40 commonly deployed marketing practices in construction. Findings Two-thirds of the marketing practices most used by architectural firms were ineffective in predicting business performance. The model also explains up to half the variance in business performance (37.4–49.9%), supporting the view that marketing in the CI affects business performance. Researching client needs and competitors emerged as the only significant positive predictor of business performance (β = 0.827, p = 0.043). Using social media (β = −1.247, p = 0.004), regular participation in awards/competitions (β = −1.420, p = 0.013) and inclusion of political offers in bids (β = −1.050, p = 0.016) negatively predicted business performance. Practical implications Architecture and allied professional bodies in Nigeria need to rethink existing restrictions regarding marketing based on traditional code of ethics in light of present-day realities of digital and internet business environments. Principals and management of architecture firms require a paradigm shift in deploying the appropriate marketing practices, especially as it relates to research regarding changing client expectations and current competition within the NCI. Originality/value The study established marketing practices which model business performance and demonstrate their value in a framework for improving the financial sustainability of architecture firms within the NCI.

Multiple choice as formative assessment in dental education.

The effectiveness of multiple-choice questions (MCQs) in dental education is pivotal to student performance and knowledge advancement. However, their optimal implementation requires exploration to enhance the benefits. An educational tool incorporating MCQs was administered from the 5th to the 10th semester in a dental curriculum. The students filled out a questionnaire after the MCQ, which was linked to the learning management system. Four cohorts of four semesters generated 2300 data points analysed by Spearmen correlation and mixed model regression analysis. Demonstrated a significant correlation between early exam preparation and improved student performance. Independent study hours and lecture attendance emerged as significant predictors, accounting for approximately 10.27% of the variance in student performance on MCQs. While the number of MCQs taken showed an inverse relationship with study hours, the perceived clarity of these questions positively correlated with academic achievement. MCQs have proven effective in enhancing student learning and knowledge within the discipline. Our analysis underscores the important role of independent study and consistent lecture attendance in positively influencing MCQ scores. The study provides valuable insights into using MCQs as a practical tool for dental student learning. Moreover, the clarity of assessment tools, such as MCQs, remains pivotal in influencing student outcomes. This study underscores the multifaceted nature of learning experiences in dental education and the importance of bridging the gap between student expectations and actual performance.

Investigation of the impact of Covid-19 pandemic in motor and visuomotor performance of Brazilian schoolchildren

Motor skills are important for building autonomy in daily life activities and school activities, being acquired through lived experiences and neurocognitive maturation. However, with the pandemic, there was a period of social restrictions. With the COVID-19 pandemic, Brazilian schoolchildren stopped attending school in person from March 2020 to July 2021. The effects of this change are still largely unknown, as the school is the main means of socialization, communication and to practice motor activities for many children. Therefore, this study aimed investigate, correlate and find predictors of gross and fine motor proficiencies and visual perception between pre- and post-pandemic schoolchildren. This was a cross-sectional study with a convenience sample. Forty schoolchildren participated in this study, being divided into groups GI (20 schoolchildren, from the 1st and 2nd grades, evaluated after remote teaching); GII (20 schoolchildren, paired with GI, in relation to sex and chronological age, being evaluated before the Pandemic). They underwent the procedures of motor Proficiency and visual perception development test. GI showed lower performance when compared to GII for motor and visual variables. No correlation was found between the motor and visual variables. Regression analysis explained 86.5% to 98.7% of the variance of motor performance. The visual variables of did not influence motor performance. Regression analysis explained between 75.8% and 96.7% of the variance of the visual performance. GI showed lower performance when compared to GII for motor and visual variables. The presence of several predictors for the classification of motor and visual performance suggests the presence of neurodevelopmental delay, which might be aggravated by social isolation resulting from the Pandemic, which must be seen as a warning sign for speech therapists and pedagogues.

Investigating the Impact of Polypharmacy and Anticholinergic Medication Burden on Objective Cognitive Performance in Adults With Multiple Sclerosis.

Polypharmacy, or the use of 5 or more daily medications, is common in adults with multiple sclerosis (MS), and is often due to various physical, cognitive, and emotional symptoms. However, research regarding the association between polypharmacy and cognitive outcomes in MS is sparse. Furthermore, individuals with MS often use medications with anticholinergic properties, which are commonly associated with cognitive impairment and other central nervous system adverse effects. Currently, the utility of scales measuring anticholinergic burden in MS is unknown. This study aims to investigate the relationship between polypharmacy, anticholinergic burden, and objective cognitive performance in MS. We recruited 90 individuals with MS during routine visits at an MS specialty clinic in Kansas City. Participants completed a brief, virtual cognitive assessment and answered questions about their health. Participants provided their medication lists from which we determined polypharmacy and scores on several anticholinergic burden scales. Statistical analyses included Spearman correlations and linear regression models. Approximately 44% of the individuals surveyed met the criteria for polypharmacy. The number of daily medications was negatively correlated with cognitive performance (rs = -0.45, P < .001). Further, the Drug Burden Index accounted for additional variance in cognitive performance beyond that explained by age, education, MS disease duration, and comorbidities [ΔR2 = .12, F(5, 84) = 7.84, P < .001.]. Clinicians should consider the possible negative consequences of polypharmacy when addressing cognitive concerns in MS. Anticholinergic burden scales may be valuable in this regard. Future investigations could explore behavioral and pharmacological interventions aimed at reducing polypharmacy in MS.

Performance Evaluation of Noninvasive Prenatal Testing in Screening Chromosome Disorders: A Single-Center Observational Study of 15,304 Consecutive Cases in China.

This study was to evaluate the performance of noninvasive prenatal testing (NIPT) in detecting fetal chromosome disorders in pregnant women. From October 1st, 2017, to December 31th, 2022, a total of 15,304 plasma cell free DNA-NIPT samples were collected for fetal chromosome disorders screening. The results of NIPT were validated by confirmatory invasive testing or clinical outcome follow-up. Further, NIPT performance between low-risk and high-risk groups, as well as singleton pregnancy and twin pregnancy groups was compared. Besides, analysis of 111 false-positive cases was performed. Totally, NIPT was performed on 15,086 eligible venous blood samples, of which 179 (1.19%) showed positive NIPT results and 68 were further validated to be true positive samples via confirmatory invasive testing or follow-up of clinical outcomes. For common chromosome aneuploidies, sex chromosome abnormalities (SCA) and other chromosomal aneuploidies, the detection sensitivities of NIPT were all 100%, the specificities were 99.87%, 99.70%, and 99.68% and the positive predictive values (PPVs) were 65.45%, 31.82%, and 10.91%, respectively. No statistically significant variance in detection performance was observed among 2987 high-risk and 12,099 low-risk subjects, as well as singleton and twin pregnancy subjects. The concentration of cell-free fetal DNA of 111 false-positive cases ranged from 5.5% to 33.7%, which was higher than the minimum requirement of NIPT. With stringent protocol, NIPT shows high sensitivity and specificity for detecting fetal chromosome disorders in a large-scale clinical service, helping improving overall pregnancy management.

Validity and Reliability of Finger-Strength Testing in 6 Common Grip Techniques for the Assessment of Bouldering Ability in Men.

To determine the criterion validity and test-retest reliability of isometric finger-strength testing in 6 differentiated grip techniques for the assessment of bouldering ability among male climbers. We recruited participants at climbing gyms in Sweden and through online advertisements. We included climbers over 15 years of age with a minimum bouldering performance level of 17 International Rock Climbing and Research Association (IRCRA) for men and 15 IRCRA for women. We tested unilateral, maximal isometric peak finger strength in the front 3 drag, half crimp, closed crimp, 35 sloper, 45 × 90-mm, and 90 × 90-mm pinch through maximal force deloaded of a force plate. We analyzed criterion validity, test-retest reliability, and capacity to determine bouldering performance ability using a stepwise multivariable regression model. Women were excluded from the analysis due to insufficient sample size (n=16). Thirty-two male participants were included in the primary analysis. The median (interquartile range) age in the advanced and elite group was 27 (25; 35) and 23 (22; 32) years, respectively. The half crimp for the participants' weak and strong hand displayed the highest ability to determine bouldering grade performance, explaining 48% to 58% of the variance. In the stepwise regression, maximal strength in the half crimp and the front 3 drag collectively explained 66% of the variance for performance. Strength in the half crimp proved the most important performance indicator. The results of this study provide a reliable and valid framework for maximal isometric peak finger-strength testing in advanced and elite male boulderers.

Empirical approach to understanding natural language models

In this paper, we try to understand natural language models by treating them as black boxes. We want to learn about these models without going into their technical details pertaining to network architecture, tuning parameters, training datasets, and schedules. We instead take an empirical approach, where we classify the datasets into various categories. For scalability and avoiding subjective bias, we use Latent Dirichlet Allocation (LDA) to categorize language text. We fine-tune and evaluate natural language models for our tasks. We compare the performance of the same model across multiple categories and for the same category across multiple models. This can help not only in choosing models for the desired categories but is also useful in understanding the model attributes that can explain performance variation. We report here the observations from this empirical study and our hypotheses. We find that models do not perform uniformly across all the categories, which could be because of uneven representation of these categories in their training datasets. Models that specialized/fine-tuned for specific tasks had higher variance in performance across categories than the generic models. Some categories have high performance consistently across all models, while others have high variance. The code for this research paper is available here: https://github.com/bhuvishi/llm_understanding

The Influence of School Principal Leadership on Teacher Performance in Private Vocational Schools in Biak Numfor Regency, Papua Province

Achieving national education goals heavily relies on the effectiveness of teachers, who serve as the cornerstone of educational excellence. However, the variance in teacher performance remains a challenge, necessitating exploration into influential factors. Among these, principal leadership emerges as a significant determinant. This study endeavors to examine the influence of principal leadership on teacher performance within private vocational schools in Biak Numfor Regency, Papua Province. Employing a quantitative correlational approach, data was collected from 115 teachers through questionnaires and document analysis. Utilizing simple linear regression, the analysis revealed a substantial positive correlation between principal leadership and teacher performance, accounting for 31.4% of the variance. The findings underscore the pivotal role of principal leadership in enhancing teacher performance, underscoring the imperative for cultivating effective leadership within educational institutions. These insights hold profound implications for educational policymakers, administrators, and stakeholders, emphasizing the need for targeted interventions to bolster leadership capabilities and thereby elevate overall educational outcomes.

The Interaction Effect of Stakeholder Engagement on Managerial Competencies- Financial Performance Nexus; Empirical Evidence from Microfinance Institutions in Uganda

Purpose: This study examined the moderation effect of stakeholder management on the relationship between managerial competencies and financial performance of MFIs in Uganda. Materials and Methods: The study used a cross-sectional design, adopting a quantitative approach. This design was preferred because it does not require follow-up on the respondents as would be the case with a longitudinal design. The study used a structured self-administered questionnaire to collect data from the senior managers of 76 MFIs in Uganda. MFIs were selected using stratified simple random sampling while purposive sampling was applied to select senior management. Hierarchical multiple regression analysis using SPSS was employed to test the hypothesis. Hierarchical regression was preferred to other techniques because of its capacity to indicate what happens to the model as different predictor variables are introduced. Findings: Empirical findings from this study revealed that the financial performance of MFIs in Uganda is explained by managerial competencies and the relationship is moderated by stakeholder management. The results concretize that managerial competencies and stakeholder management fuse to influence financial performance. The study revealed that managerial competencies (β= .65, p&lt;.001) and stakeholder management (β=.61, p&lt;.001) are significant antecedents, accounting for a substantial 58% of the variance in the financial performance of MFIs (R2=.58, p&lt;.001). Implications to Theory, Practice and Policy: The present study has confirmed that managerial competencies are a multidimensional predictor comprising of skills, knowledge, and abilities of the management team. It emerged that stakeholder management is a potent predictor with the potential to strengthen the effect of managerial competencies on financial performance. The study addresses mixed findings in the literature on financial performance and confirms upper-echelons and the stakeholder theory.

Factors Associated With Diabetes Self-Care Performance in Indonesians With Type 2 Diabetes: A Cross-Sectional Study.

In Indonesia, the number of Type 2 diabetes cases is increasing rapidly, making it the third leading cause of death and among the leading noncommunicable disease healthcare expenditures in the country. Thus, there is a critical need for Indonesians with Type 2 diabetes to perform better self-care to optimize their health and prevent the onset of comorbidities. This study was designed to investigate the influence of knowledge, depression, and perceived barriers on Type 2 diabetes self-care performance in Indonesia. A cross-sectional study was conducted on 185 patients with Type 2 diabetes, with demographic, diabetes history, obesity status, diabetes knowledge, depression, perceived barriers, and self-care performance data collected. The Indonesian version of the Revised Diabetes Knowledge Test, Depression Anxiety Stress Scale, Perceived Barrier Questionnaire and Self-Care Inventory-Revised were used. Descriptive, bivariate, and multiple linear regression analyses were performed. Study participants were found to have moderate diabetes self-care performance scores. Annual eye checks, blood glucose self-monitoring, healthy diet selection, and regular exercise were the least common self-management techniques performed and were consistent with the perceived difficulties of the participants. Being illiterate or having an elementary school education (β = 4.59, p = .002), having a junior or senior high school education (β = 3.01, p = .006), having moderate depression (β = -0.92, p = .04), diabetes knowledge (β = 0.09, p = .006), and perceived barriers (β = 0.31, p < .001) were found to explain 40% of the variance in self-care performance. Educational level, depression, and perceived barriers were the strongest factors that impacted Type 2 diabetes self-care performance in this study. Nurses should not only provide diabetes education but also identify barriers to diabetes self-care early, screen for the signs and symptoms of depression, and target patients with lower levels of education.

Experimental design using the Taguchi method for the development of conductive textiles used in flexible thermoelectric generators

This paper presents several aspects of the robust experimental design methodology using the Taguchi method to develop electrically conductive textiles. These conductive textiles will be used to make thermoelectric generators based on the Seebeck effect. Since the experimental development involves the use of the magnetron sputtering method with more than three variables, the Taguchi method was selected to observe how different parameters (5 independent variables such as argon flow, power, pressure, deposition surface area and metal type used for solid targets) influence the mean and variance of the process performance defined by the thickness of the metal film deposited (dependent variable). In the experimental design framework, the analysis using the Taguchi method, followed by optimisation, helped select the optimal experiments from the set of possible experiments. This methodology reduced the number of experiments by 21–42% and minimised resource consumption (e.g., metal targets, argon, energy).

Gray and White Matter Metrics Demonstrate Distinct and Complementary Prediction of Differences in Cognitive Performance in Children: Findings from ABCD (N = 11,876).

Individual differences in cognitive performance in childhood are a key predictor of significant life outcomes such as educational attainment and mental health. Differences in cognitive ability are governed in part by variations in brain structure. However, studies commonly focus on either gray or white matter metrics in humans, leaving open the key question as to whether gray or white matter microstructure plays distinct or complementary roles supporting cognitive performance. To compare the role of gray and white matter in supporting cognitive performance, we used regularized structural equation models to predict cognitive performance with gray and white matter measures. Specifically, we compared how gray matter (volume, cortical thickness, and surface area) and white matter measures (volume, fractional anisotropy, and mean diffusivity) predicted individual differences in cognitive performance. The models were tested in 11,876 children (ABCD Study; 5,680 female, 6,196 male) at 10 years old. We found that gray and white matter metrics bring partly nonoverlapping information to predict cognitive performance. The models with only gray or white matter explained respectively 15.4 and 12.4% of the variance in cognitive performance, while the combined model explained 19.0%. Zooming in, we additionally found that different metrics within gray and white matter had different predictive power and that the tracts/regions that were most predictive of cognitive performance differed across metrics. These results show that studies focusing on a single metric in either gray or white matter to study the link between brain structure and cognitive performance are missing a key part of the equation.

Using Probabilistic Machine Learning Methods to Improve Beef Cattle Price Modeling and Promote Beef Production Efficiency and Sustainability in Canada

Accurate agricultural commodity price models enable efficient allocation of limited natural resources, leading to improved sustainability in agriculture. Because of climate change, price volatility and uncertainty in the sector are expected to increase in the future, increasing the need for improved price modeling. With the emergence of machine learning (ML) algorithms, novel tools are now available to enhance the modeling of agricultural commodity prices. This research explores both univariate and multivariate ML techniques to perform probabilistic price prediction modeling for the Canadian beef industry, taking into account beef production, commodity markets, and international trade features to enhance accuracy. We model Alberta fed steer prices using three multivariate ML algorithms (support vector regression (SVR), random forest (RF), and Adaboost (AB)) and three univariate ML algorithms (autoregressive integrated moving average (ARIMA), seasonal ARIMA (SARIMA), and the seasonal autoregressive integrated moving average with exogenous factors (SARIMAX)). We apply these models to monthly fed steer price data between January 2005 and September 2023 and compare predicted prices with observed prices using several validation metrics. The outcomes indicate that both random forest (RF) and Adaboost (AB) show superior overall performance in accurately predicting Alberta fed steer prices in comparison to other algorithms. To better account for the variance of the best model performance, we subsequently adopted a probabilistic approach by considering uncertainty in our best-selected ML model. The beef industry can use these improved price models to minimize resource waste and inefficiency in the sector and improve the long-term sustainability prospects for beef producers in Canada.