Future Performance Research Articles

What are the primary stressors faced by Obstetrics and Gynaecology residents? Do their coping strategies align with adaptability or maladaptability, as per the Brief COPE assessment?

: Obstetrics and Gynaecology is a demanding and challenging speciality of medical education. The residents are the first level of contact of all patients. The aim and objectives of the study were to find what causes stress in the residents of Obstetrics and Gynaecology and their coping techniques. We conducted a cross-sectional study on 45 residents pursuing post-graduation in Obstetrics and Gynaecology at PGIMS, Rohtak. : The cause of stress in residents was long working hours, having less time for friends and family, too much paper work, new subject learnings, expectations to perform well in clinics. The coping techniques were identified like listening to music, watching movies, talking to friends and family. According to the Brief COPE assessment, the coping techniques used were adaptive in residents of Obstetrics and Gynaecology of our institute. Those working in demanding fields like Obstetrics and Gynaecology face unique challenges and have their own coping techniques. The well-being of medical residents directly impacts their future performance as physicians

Association of pedigree indexes and genomic breeding values with the performance of Polish Holstein-Friesian cows.

Pedigree indices (PI) and genomically enhanced breeding values (GBV) of Polish Holstein-Friesian heifers were compared with their future performance. Phenotypes of 15,794 cows from 294 herds were analyzed. The traits evaluated included milk, fat and protein yield, somatic cell score (SCC), stature, overall udder and feet and legs score, heifer conception rate, and longevity. PI and GBV were from official evaluation systems, and performance records were adjusted for non-genetic effects. Correlations between breeding values and adjusted phenotypes were analyzed. Additionally, cows within each herd were divided into quartiles based on their breeding values, and the performance of cows from the top and bottom quartiles was compared. For production traits, similar analyses were conducted separately for high and low milk-producing herds to check for possible genotype by environment interaction. The analyses confirmed the significant correlation between breeding values and cow performance. Incorporating genomic information into PI significantly improved the predictive accuracy for milk, fat, and protein yields, as well as for SCC and stature, with increases ranging from 34 to 64%. Comparisons of cows' performance from the top and bottom quartiles supported these observations for all these traits except protein yield, with differences in performance being 43-92% greater when cows were ranked by GBV instead of PI. In a more productive environment, greater differences in performance were found between the top and bottom quartiles. These findings suggest that Polish breeders can enhance the outcomes of their breeding decisions by using GBV instead of PI. This change offers particular benefits in improving the predictability of future performance for the most economically important traits such as milk yield, fat yield, protein yield, somatic cell score, and stature.

Lottery‐like features and mutual fund performance‐flow sensitivity

AbstractWe show that mutual funds' lottery‐like features weaken the performance‐flow sensitivity, particularly among low‐performing funds, thereby contributing to the convexity of the fund performance‐flow relation. The results hold when different model specifications are used to test the fund performance‐flow relation, are robust to alternative measures for funds' lottery‐like features, and cannot be attributed to fund search costs, marketing efforts, or fund performance volatility. Utilizing retail trading data at the account level from a large brokerage firm, we offer additional evidence that funds' lottery‐like features significantly reduce outflows for low‐performing funds. It confirms that the weakened performance‐flow sensitivity among low‐performing funds with lottery‐like features is driven by existing investors' reluctance to redeem their shares. Furthermore, we reveal that fund managers can cater to investors' gambling preference by tilting fund portfolios toward lottery‐type stocks. Funds' lottery‐like features, however, aggravate future fund performance, especially among those that have already underperformed in the past.

Analysis of the impact of deep learning know-how and data in modelling neonatal EEG.

The performance gains achieved by deep learning models nowadays are mainly attributed to the usage of ever larger datasets. In this study, we present and contrast the performance gains that can be achieved via accessing larger high-quality datasets versus the gains that can be achieved from harnessing the latest deep learning architectural and training advances. Modelling neonatal EEG is particularly affected by the lack of publicly available large datasets. It is shown that greater performance gains can be achieved from harnessing the latest deep learning advances than using a larger training dataset when adopting AUC as a metric, whereas using AUC90 or AUC-PR as metrics greater performance gains are achieved from using a larger dataset than harnessing the latest deep learning advances. In all scenarios the best performance is obtained by combining both deep learning advances and larger datasets. A novel developed architecture is presented that outperforms the current state-of-the-art model for the task of neonatal seizure detection. A novel method to fine-tune the presented model towards site-specific settings based on pseudo labelling is also outlined. The code and the weights of the model are made publicly available for benchmarking future model performances for neonatal seizure detection.

Are virtual wards for children safe and effective? A 3-year retrospective service evaluation of an urban Hospital at Home service for children and young people

ObjectiveService evaluation of an urban ‘Hospital at Home’ service which provides care in patients’ homes that would traditionally be delivered in the hospital setting.DesignRetrospective longitudinal review of routinely collected data...

Can the MD&A Tone of Listed Firms’ Annual Reports Predict Their Future Performance? Empirical Evidence Based on Machine Learning Text Analysis*

AbstractBased on a sample of listed companies in China's A‐share market between 2009 and 2019, we analyze the tone of the Management's Discussion and Analysis (MD&A) section of 15 743 annual reports through machine learning. The MD&A tone displays a significantly positive association with the firm's future financial performance, proving that the textual tone of MD&A includes forward‐looking aspects regarding management's intentions for the company's prospects, and investors can use it to forecast the firm's future performance. Additionally, higher levels of internal control quality, stronger analyst following, and higher holdings by institutional investors can enhance the correlation between the MD&A tone and the company's future performance.

Stock Market Forecasting Using a Neural Network Through Fundamental Indicators, Technical Indicators and Market Sentiment Analysis

AbstractThe objective of this research is to provide evidence that it is possible to obtain a prediction that better aligns with the future performance of a stock if a neural network model is trained with stock market analysis variables and qualitative variables. As a case study, thirty-three companies’ representative of the S&P 500 are selected, and a multilayer perceptron artificial neural network is built and trained with input parameter indicators of fundamental analysis, technical analysis, and market sentiment. By incorporating the latter as an additional variable, the model's accuracy increases by 1.5% for 66% of the companies analyzed. The results confirm the crucial role played by the selection of the neural network model and its variables depending on the type of company to be analyzed. The main contributions of this research are the identification of the best variables combination to train a neural network model depending on the market sector to be analyzed, likewise it is demonstrated that, by using market sentiment, it is possible obtain a high accuracy or increase the accuracy to an existing model.

Exploring statistical and machine learning methods for modeling probability distribution parameters in downtime length analysis: a paper manufacturing machine case study

Manufacturing companies focus on improving productivity, reducing costs, and aligning performance metrics with strategic objectives. In industries like paper manufacturing, minimizing equipment downtime is essential for maintaining high throughput. Leveraging the extensive data generated by these facilities offers opportunities for gaining competitive advantages through data-driven insights, revealing trends, patterns, and predicting future performance indicators like unplanned downtime length, which is essential in optimizing maintenance and minimizing potential losses. This paper explores statistical and machine learning techniques for modeling downtime length probability distributions and correlation with machine vibration measurements. We proposed a novel framework, employing advanced data-driven techniques like artificial neural networks (ANNs) to estimate parameters of probability distributions governing downtime lengths. Our approach specifically focuses on modeling parameters of these distribution, rather than directly modeling probability density function (PDF) values, as is common in other approaches. Experimental results indicate a significant performance boost, with the proposed method achieving up to 30% superior performance in modeling the distribution of downtime lengths compared to alternative methods. Moreover, this method facilitates unsupervised training, making it suitable for big data repositories of unlabelled data. The framework allows for potential expansion by incorporating additional input variables. In this study, machine vibration velocity measurements are selected for further investigation. The study underscores the potential of advanced data-driven techniques to enables companies to make better-informed decisions regarding their current maintenance practices and to direct improvement programs in industrial settings.

Forecasts of Video Game Sales based on the ARIMA Model

Abstract. With the rapid development of the digital age, video games have become an important component of the cultural industry, and their sales forecasting has become a focus of industry attention. This article aims to predict the sales of video games based on the ARIMA model and explore effective methods to improve prediction accuracy. Through in-depth research, this article found that the ARIMA model performs well in capturing the time series characteristics of sales data and can accurately predict future sales trends. The ARIMA model provides a systematic and scientific method for predicting the future market performance of video games by comprehensively considering the trends, seasonality, and random changes in historical sales data. This research achievement not only provides strong decision support for game developers, publishers, and platform operators but also promotes the optimization of resource allocation and market risk avoidance in the video games industry, which is of great significance for promoting the healthy and sustainable development of the industry.

PREDICTING LEADERSHIP EFFECTIVENESS THROUGH THE TALENTS THAT REALLY MATTER

AbstractConchie (founder and president of Conchie Associates) and Dalton (partner, Conchie Associates) explain that they apply science “to the study, application, and development of leadership,” adapted from the research in their book The Five Talents Really Matter. They discuss their criteria for outstanding leadership and point to “over 58,000 top level leaders in our global database.” Their scientific “assessment of The Five Talents That Really Matter carries a disproportionate weight, greater than all the other factors thought to be important in leadership selection, in predicting top leadership performance.” The Talents “capture the broad variability of traits, dispositions, and characteristics the very best leaders possess, and, through the Executive Leadership Assessment built to measure these talents, we are able to use the results to help predict future leadership performance.” In their words, the Talents are Setting Direction (using modern GPS technology as a metaphor), Harnessing Energy, Exerting Pressure (“Debate and dissent, we’ve found, is what many leaders claim to value yet precious few succeed in delivering”), Increasing Connectivity (“The very best leaders…are straight shooters who deliver difficult messages with compassion,”) and Controlling Traffic (“Exceptional leaders responsible for business execution follow rigid rules with maximum flexibility.”)

Entrustable professional activities and feedback for learning: Insights from a mixed methods study.

Entrustable professional activities (EPAs) are used to support clinical skills training by providing a scaffold for practice and feedback. The aim of this study was to evaluate how written feedback provided for EPAs supports medical students' learning. The written feedback for two EPAs (admit or consult patient and discharge summary) was analysed using a mixed methods approach. Content analysis determined the types of feedback received. Qualitative analysis identified themes related to the feedback quality. Hattie and Timperley's feedback model that provides a framework for effective feedback was used as an interpretive lens for our analysis and integrated findings. Written feedback was provided for 89.5% of 997 EPAs. The proportions of feedback types to support learning were as follows: feedback related to what was done well (75.6%), areas for improvement (27.7%) and next steps (17.4%). Only 10% of EPAs received all three types of feedback. EPAs completed independently were more likely to receive any feedback. Feedback for supervised EPAs was more likely to include areas for improvement or next steps. Qualitative analysis identified two themes: effective feedback for present and future performance with detailed description of performance or targeted advice, and lack of specific guidance for improvement with affirmative statements or non-specific directions. EPAs most often elicited feedback about what is done well without areas or strategies for improvement. Descriptive feedback and tailored advice are ideal, but uncommon. Students and supervisors need guidance on how to optimise feedback through instruction and EPA form design.

Spatiotemporal variation in grain production performance and efficiency of the cultivated landscapes in Upper Blue Nile Basin of Ethiopia: the impact of residual moisture-based farming on water and food security

Analysis of grain production performance can provide reference information to explore multiple cropping options and further improve the resource use efficiency of farming methods. This study investigated the spatiotemporal dynamics of grain production performance and efficiency of major crop production systems (CPS) in the Ethiopia’s Blue Nile Basin. The results show that only 39% of the basin is currently cultivated, although a significant cropland expansion (10%) was recorded between 1985 and 2020. The study identified 11 major CPS, mostly practiced in the basin. Of these, single cropping based on the main rainy season (Meher-Only) covers the largest area (26%), followed by Meher-Residual-Intermittent (12%) and Meher-Belg-Dependable (11%). Extended-Meher, Meher-Residual-Dependable, Meher-Residual-Intermittent, and Meher-Belg-Dependable are the four more powerful CPS with higher efficiency. Comparatively, CPS practiced in Wet-Woyna-Dega and Wet-Dega have better overall performance. Findings confirm that agricultural space management (land) and green-water (rainfall) utilization are the most influential factors, followed by land use planning and land use systems (CPS) invention. As landscape suitability for grain production governs future performance, in the low elevation and flood plains parts of the basin, the possibility of creating additional space into the food system is very high. In mountainous and high-altitude regions, the efficiency of grain production will decrease because incorporating additional arable land into the food system is trivial. In the last three decades, in BNB, only 10% of arable land (equivalent to 30 million quintals of food) has been added to the good system, which can support approximately 6 million people. Compared to the population growth of the basin (12 million 1985–2020), its contribution to the food system was less than 50%. This confirms that multiple cropping systems, such as Residual moisture-based CPS, have played a significant role in boosting the food system in the basin. Therefore, improving grain production performance/efficiency requires targeted investments, including the invention of more adaptable crop varieties, efficient cropping practices, and the introduction of advanced agricultural space and water management technologies. The results of the study will help identify important policy gaps and suggest possible options to enhance residual farming and other multiple cropping systems.

The NFL as “not for long”: the NFL draft and teams’ discount rates

PurposeTo present a method for calculating the discount rate that teams apply to future-year draft picks relative to current-year draft picks and then apply that method to the actual draft picks and trades over the period 2011–2022.Design/methodology/approachThe National Football League (NFL) Draft permits teams to trade the selection rights for current-year and future-year draft picks. We seek to calculate the discount rates associated with NFL Draft trades. With this method, we calculate the discount rate for each trade by NFL teams involving a combination of current-year and future-year draft picks since 2011, when the NFL ratified a new collective bargaining agreement that instituted a draft-pick salary scale and capped the length of draftees’ contracts.FindingsWe find that teams' annualized discount rates in trading away future-year draft picks are quite steep, averaging more than 100% per year. These steep discount rates suggest that teams are pressured by market competition to adopt a “win now” approach in devaluing the future draft choices relative to the present draft choices.Research limitations/implicationsThe actual discount rate for each trade is not known with certainty when the trade is transacted. This uncertainty arises because the within-round order of future-year picks is determined by teams’ future performance, which is not known at the time of the transaction.Practical implicationsIn reporting these findings, we acknowledge the limitations of our analysis. The dataset is small, as there are on average between five and six trades per year involving current-year and future-year picks. More observations could have been included by extending the timeframe to before 2011, but we opted against doing so because the NFL’s 2011 CBA changed teams’ draft calculus by imposing a draft-pick salary scale and capping the length of draftees’ contracts. In addition, our discount rates as calculated are ex post facto in that they are calculated after the future-year drafts have been held. While these are the actual discount rates for the trades as transacted, the actual discount rate for each trade is not known with certainty when the trade is transacted. This uncertainty arises because the within-round order of future-year picks is determined by teams’ future performance, which is not known at the time of the transaction. As an aside, we also re-estimated each trade’s discount rate with an adjustment for that uncertainty, and the median discount rate for all 61 trades was still over 100% per year.Originality/valueProviding insights into NFL Draft management behavior and decision-making for current-year and future-year draft picks since 2011, when the NFL ratified a new collective bargaining agreement that instituted a draft-pick salary scale and capped the length of draftees’ contracts.

Question Embedding on Weighted Heterogeneous Information Network for Knowledge Tracing

Knowledge Tracing (KT) aims to predict students’ future performance on answering questions based on their historical exercise sequences. To alleviate the problem of data sparsity in KT, recent works have introduced auxiliary information to mine question similarity, resulting in the enhancement of question embeddings. Nonetheless, there remains a gap in developing an approach that effectively incorporates various forms of auxiliary information, including relational information (e.g., question-student , question-skill relation), relationship attributes (e.g., correctness indicating a student's performance on a question), and node attributes (e.g., student ability ). To tackle this challenge, the Similarity-enhanced Question Embedding (SimQE) method for KT is proposed, with its central feature being the utilization of weighted and attributed meta-paths for extracting question similarity. To capture multi-dimensional question similarity semantics by integrating multiple relations, various meta-paths are constructed for learning question embeddings separately. These embeddings, each encoding different similarity semantics, are then fused to serve the task of KT. To capture finer-grained similarity by leveraging the relationship attributes and node attributes on the meta-paths, the biased random walk algorithm is designed. In addition, the auxiliary node generation method is proposed to capture high-order question similarity. Finally, extensive experiments conducted on 6 datasets demonstrate that SimQE performs the best among 10 representative question embedding methods. Furthermore, SimQE proves to be more effective in alleviating the problem of data sparsity.

‘E’ of ESG and firm performance: Evidence from China

Following the ESG rating divergence reported in the previous research studies, we develop a novel firm-level Green Commitment (GC) index by incorporating new dimensions of environmental management and governance. We construct GC scores for all A-share listed companies in China from 2015 to 2021 and analyze whether firms with greater environmental commitment exhibit improvements in their future performance. Our results show that firms with high GC scores achieve higher stock returns without incurring extra risk. Additionally, a strong environmental commitment can enhance operating performance by mitigating financial constraints. The evidence supports the view that environmental investing contributes to the creation of positive shareholder value. Our GC index can be applied more widely to resolve the mixed evidence on the value implications of corporate environmental commitments.

Habilidades no técnicas en la educación en cirugía. Una revisión panorámica de la literatura

IntroductionThere is a growing recognition of incorporating non-technical skills during the training process of a surgeon, as a strategy to increase their future professional performance. There is a gap in the educational methodology used. A panoramic review of the literature is carried out to identify the status, gaps and research opportunities. MethodsPanoramic review of the literature with the Joanna Briggs Institute methodology. Studies that addressed instruction, measurement, outcome evaluation, and the educational impact of non-technical skills on residents were analyzed. ResultsThe studies analyzed were carried out between 2012 and 2021. The skills studied were situational awareness, decision making, communication, teamwork, and leadership. There are studies on validation of instruments and implementation of education models. The knowledge gaps identified were the lack of standardization of the methods used for the training and evaluation of these competencies, as well as the lack of studies in Latin America. DiscussionThe teaching of non-technical skills is a pending issue in the training of a surgeon. The relevance of the topic requires its study and incorporation into study curricula.

Executive function is associated with the development of math performance in children born at

To describe associations between executive function (EF) domains (attentional control, information processing, cognitive flexibility, and goal setting) and concurrent math computation performance at age 7 and 13 years in children born <30 weeks' gestation or weighing <1,250 g, and second, to examine the impact of 7-year EF on math performance at 13 years. In a prospective, longitudinal cohort of children born <30 weeks' gestation or with a birthweight <1,250 g, assessment of EF and math performance was undertaken at 7 (n = 187) and 13 years (n = 174). Linear regression models were used to describe associations between EF domains with math performance at both time points, as well as to examine the impact of EF at 7 years on math performance at 13 years. At 7 and 13 years, all EF domains were positively and strongly associated with concurrent math performance (β = 11.35, 95% CI [9.28, 13.41] to β = 13.79, 95% CI [11.59, 15.98]). All EF domains at age 7 years were positively associated with math performance at 13 years, with the strongest associations observed for cognitive flexibility (β = 10.79 [8.64, 12.94]) and goal setting (β = 10.37 [8.08, 12.67]). This study provides evidence that EF is strongly associated with math performance in children born <30 weeks' gestation or with a birthweight <1,250 g and highlights the importance of early cognitive flexibility and goal setting performance for future math performance. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Application and simulation of IEC water chillers for summer free cooling in data centers

Free cooling is regarded as the most effective way to reduce the energy consumption of the cooling system in data centers. This study proposes a novel water-medium indirect evaporative cooling (IEC) chiller used in a data center to achieve free cooling throughout the year as an alternative to electrical chillers. Field tests and numerical modeling of the IEC water chillers are both reported to evaluate the performance and efficiency. This paper first-time reports on the application of IEC water chillers to deliver year-round free cooling for a data center in Changji, China. The wet-bulb efficiency of the tested chiller is measured as 120% to 152.8% and the dew-point efficiency is 27% to 62.7%. A numerical model is established to verify the operating conditions, and some common operational optimizations are pointed out in this test for energy savings. PUE can be reduced to 1.212 after the optimization. More future performance predictions of the IEC water chillers are studied when the data center load rate increases and when the local weather changes in a year to discuss the year-round availability. For further study, the performance of IEC water chillers in different climate regions is also forecasted. The results indicate that it’s an effective way for IEC to achieve free cooling in regions where natural cold resources are abundant. In this study, the field test performance and prediction of IEC water chillers are provided as a typical and practical application as the natural cooling source in data centers in hot and dry areas.

Design, Operation and Simulation of a Passive Osmosis-Integrated Electrolyzer for Seawater Electrolysis

Abstract Utilizing abundant seawater for green hydrogen production through electrolysis is a promising pathway to produce a sustainable energy carrier. However, modern seawater electrolyzers have shown insufficient durability due to electrode corrosion and/or competitive production of chlorinated products that result from the presence of Cl-. In this work, a new cell, driven by osmotic separation, was designed and operated that can passively draw fresh water from seawater into compartments with high acid and/or alkaline concentration for electrolysis, thereby eliminating the need for an external energy source for desalination. The work focuses first on demonstrating the passive transport of water through membranes over a wide range of acid and base concentrations. Then, electrodes are integrated, and the cells are operated under multiple configurations and current densities. It is observed that some co-ion diffusion occurs, which is quantified through pH measurements and quantitative Cl- titration. Water transport and ion crossover experiments are supported by comprehensive continuum-level modeling. Finally, strategies for improving future performance are discussed. The findings in this work, a first step in the development of an osmosis-driven electrolyzer cell (ODEC), showcase the promise of this novel electrolyzer design for future direct seawater electrolysis.

CEO Locality and Employment Stickiness

AbstractWe explore whether CEOs’ hometown identity involves labour adjustment decisions. We document that local CEOs, with their hometown ties, reduce employment to a lesser degree following sales downturns than nonlocal CEOs. This finding suggests that local CEOs’ strong local attachments motivate them to prioritise employee interests and build good reputations, which create private benefits or reserve future career paths in their hometowns. Our findings are more pronounced in areas where local connections are highly valued, thus supporting our argument. We further find that the retention efforts of local CEOs are related to low future performance. We extend the cost stickiness literature by documenting that CEOs’ place attachment influences resource adjustment decisions, particularly regarding labour, which eventually influences subsequent performance.