Performance Benefits Research Articles

An Examination of Factors Influencing Physicians' Acceptance and Use of the e-Nabız System

Aim: This study aims to identify the factors influencing physicians' acceptance and use of the e-Nabız system by comparing two models. Methods: Conducted with 388 physicians from university hospitals across Turkey, the study utilized an online survey based on the Unified Theory of Acceptance and Use of Technology (UTAUT) scale. Descriptive analyses, frequency and percentage distributions, reliability analysis, confirmatory factor analysis, and structural equation modelling were applied to the collected data. Results: In Model 1, the behavioral intention was influenced by performance expectancy and social influence, while usage behavior was shaped by social influence, facilitating conditions, and behavioral intention. Model 1 accounted for 75% of the variance in behavioral intention and 69% in usage behavior. In contrast, Model 2 identified performance expectancy, anxiety, habit, personal technology innovativeness, and workflow as significant predictors of behavioral intention. Usage behavior in Model 2 was influenced by habit, facilitating conditions, anxiety, personal technology innovativeness, workflow, and behavioral intention, explaining 84% of the variance in behavioral intention and 85% in usage behavior. Conclusion: The findings indicate that Model 2 provides a more comprehensive explanation of the factors affecting the acceptance and use of the system. To enhance acceptance and usage, the study suggests focusing on anxiety management, emphasizing performance benefits, aligning the system with workflow, educating users about new technologies, and implementing incentives to foster habitual use. Future research should explore other technology acceptance models in various healthcare information systems to deepen understanding.

Noise schemas aid hearing in noise

Human hearing is robust to noise, but the basis of this robustness is poorly understood. Several lines of evidence are consistent with the idea that the auditory system adapts to sound components that are stable over time, potentially achieving noise robustness by suppressing noise-like signals. Yet background noise often provides behaviorally relevant information about the environment and thus seems unlikely to be completely discarded by the auditory system. Motivated by this observation, we explored whether noise robustness might instead be mediated by internal models of noise structure that could facilitate the separation of background noise from other sounds. We found that detection, recognition, and localization in real-world background noise were better for foreground sounds positioned later in a noise excerpt, with performance improving over the initial second of exposure to a noise. These results are consistent with both adaptation-based and model-based accounts (adaptation increases over time and online noise estimation should benefit from acquiring more samples). However, performance was also robust to interruptions in the background noise and was enhanced for intermittently recurring backgrounds, neither of which would be expected from known forms of adaptation. Additionally, the performance benefit observed for foreground sounds occurring later within a noise excerpt was reduced for recurring noises, suggesting that a noise representation is built up during exposure to a new background noise and then maintained in memory. These findings suggest that noise robustness is supported by internal models-"noise schemas"-that are rapidly estimated, stored over time, and used to estimate other concurrent sounds.

A INFLUÊNCIA DA MÚSICA NO DESEMPENHO DURANTE ATIVIDADES FÍSICAS

This study aims to describe evidence of how music preference can mediate exercise responses and performance benefits, identifying which factors may be particularly beneficial for optimizing performance. In addition, the practical implications for practitioners will be highlighted with considerations for strategies to elicit maximum performance through musical preference. The research methodology of this study was based on a literature review study, without the participation of the population or samples. Thus, the articles were extracted for the first time by the authors. The full texts of the relevant articles were then independently evaluated by the authors and advisor. The understandings of each study related to the proposed theme were extracted from all the experiments included. When the data on music and its relationship with physical activity were not explicitly provided, the other significant contents were analyzed to verify which data extraction would be feasible from the works to incorporate this review study. Through the current evidence, it is therefore concluded that an important aspect to increase performance with music is personal choice. In many gyms, locker rooms, and competition environments, music is played over a loudspeaker. The current data available therefore suggests that if music played over the speakers is not preferred by the individual who strives, the performance may suffer from depredations. Thus, coaches and athletes must consider individual musical preferences when trying to optimize performance and training.

Building Thermal Insulation Performance and economic benefits

Three different insulating scenarios were investigated using Energy-plus software, to study the effect of using expanded polystyrene boards on building energy consumption at the Libyan Center for Solar Energy Research and Studies. The three insulation scenarios with different polystyrene insulation thicknesses and densities were investigated. Polystyrene total cost, Payback period, total and net money saving using insulation, as well as the percentage gain were calculated for each case in the three investigated scenarios for 50 years. The most money saving scenarios after 50 years is by insulating the building roof and external walls with an average insulation thickness of 7 cm, reaching about 78000 L.D and a tariff of 0.9261 L.D /kWh. While the least money saving is the roof scenario with an insulation thickness of 2.5 cm, reaching more than 29000 L.D and the same tariff. The highest percentage gain values are 76 %, 103 % and1090 % at the roof scenario, 2.5 cm insulation thickness and energy tariffs of 0.15 L.D /kWh, 0.1732 L.D/kWh and 0.9261 L.D/kWh, respectively. While the lowest percentage gain values are about 17.5 %, 35.7 % and 725 % at the wall scenario 10 cm insulation thickness and energy tariffs of 0.15 L.D/kWh, 0.1732 L.D/kWh and 0.9261 L.D/kWh, respectively. the payback period of total insulation cost is significantly dependent on insulation thickness and energy tariff. These results show that low energy tariff (current energy tariff) values economically are not cost effective regarding the payback period. Consequently, prices do not motivate residents to save energy with the use of thermal insulation unless actual energy prices are considered.

Oxide-Perovskites for Automotive Catalysts Biotransform and Induce Multicomponent Clearance and Hazard.

Oxide-perovskites designed for automotive catalysts contain multiple metal elements whose presence is crucial to achieving the targeted performance. They are highly stable in exhaust operating conditions; however, little is known about their stability under physiological conditions. As some of the metallic components are hazardous to humans and the environment, perovskite benefits in cleaner air must be balanced with risks in a Safe and Sustainable Design (SSbD) approach. New approach methodologies (NAMs), including in chemico and in silico methods, were used for testing hazards and benefits, including catalytic activity and tolerance for temporary excess of oxygen under dynamic driving conditions. The composition and surface properties of six different lanthanum-based oxide-perovskites compromised their stability under lung physiological conditions, influencing the oxidative damage of the particles and the bioacessibility of leaching metals. We found consistent biotransformation of the oxide-perovskite materials at pH 4.5. The leached lanthanum ions, but not other metals, respeciated into lanthanum phosphate nanoparticles, which increased the overall oxidative damage in additive synergy. The NAM results in the presented SSbD approach were challenged by in vivo studies in rats and mice, which confirmed multicomponent clearance from lungs into urine and supported the comparative ranking of effects against well-characterized spinel materials. Among the perovskites, the version with reduced nickel content and doped with palladium offered the best SSbD balance, despite not improving the conventional benchmark catalytic performance and related sustainability benefits. Redesign by industry may be necessary to better fulfill all SSbD dimensions.

Strength Training Among Male Master Cyclists—Practices, Challenges, and Rationales

Background: Cycling performance declines with age due to reduced aerobic capacity, along with reductions in muscle mass and bone density. Strength training can help counter these effects. This study aims to explore the strength training practices, challenges, and decision-making rationale of male master cyclists to optimize performance and health as they age. Methods: A total of 555 male master cyclists aged 35 and above completed an online questionnaire, distributed via social media platforms, that included Likert-type, single- and multiple-selection, and open-ended questions. Participants were then divided into two age groups: 35–49 years (n = 359) and ≥50 years (n = 196). Analyses involved descriptive statistics, Wilcoxon signed-rank tests, Mann–Whitney U-tests, and chi-square tests, with qualitative data analyzed using content analysis. Results: More cyclists engaged in strength training during the off-/pre-season, with a significant reduction in both frequency and the number of cyclists engaging in strength training during the race season. The strength training practice was focused mainly on core and lower body, employing hypertrophy and maximal strength training methods. Key challenges included fatigue induced by strength training and limited time to perform strength training. The main rationale for the strength training revolved around improving cycling performance, reducing injury risk, and the health benefits of strength training. Both age categories, but the older group in particular, reported bone health as a primary rationale for strength training. Conclusions: While strength training offers performance and health benefits, issues of fatigue and time constraints remain substantial, suggesting the need for tailored training programs to improve adherence and effectiveness.

Board gender diversity (BGD): compelling evidence in support for the critical mass theory

PurposeThe paper aims to identify the level of support and expand on the issues recently raised in the literature concerning critical mass theory and board gender diversity (BGD).Design/methodology/approachThe authors systematically searched relevant articles on the Scopus database in March 2024, identifying 132 articles. After removing book chapters, conference papers and reviews, the number was reduced to 122. An additional 16 were discarded as they were irrelevant (e.g. political, theoretical or conceptual) to the current study, leaving a final sample of 106 articles. This longitudinal study covers the period from 2016 to 2024.FindingsThe paper finds compelling evidence supporting the critical mass theory and underscores the importance of corporate BGD in today’s society. It also offers explanations for the few cases where critical mass theory may not be fully supported. It highlights that the performance benefits of corporate BGD, in many cases, only exist when there is a critical mass of female directors on the board.Practical implicationsIt lends support to policymakers in pursuing corporate BGD through quotas, provided that the incentive is not just to fill the numbers.Originality/valueThe paper offers a unique perspective on the level of support for the critical mass theory. It is believed to be the first paper to conduct a longitudinal study to investigate the support for the critical mass theory.

Efficient Electrosynthesis of Valuable para‐Benzoquinone from Aqueous Phenol on NiRu Hybrid Catalysts

AbstractElectrocatalytic oxidation of aqueous phenol to para‐benzoquinone (p‐BQ) offers a sustainable approach for both pollutant abatement and value‐added chemicals production. However, achieving high phenol conversion and p‐BQ yield under neutral conditions remains challenging. Herein, we report a Ni(OH)2‐supported Ru nanoparticles (NiRu) hybrid electrocatalyst, which exhibits a superior phenol conversion of 96.5 % and an excellent p‐BQ yield of 83.4 % at pH 7.0, significantly outperforming previously reported electrocatalysts. This exceptional performance benefits from the triple synergistic modulation of the NiRu catalyst, including enhanced phenol adsorption, increased p‐BQ desorption, and suppressed oxygen evolution. By coupling a flow electrolyzer with an extraction‐distillation separation unit, the simultaneous phenol removal and p‐BQ recovery are realized. Additionally, the developed electrocatalytic system with the NiRu/C anode displays good stability, favorable energy consumption, and reduced greenhouse gas emissions for phenol‐containing wastewater treatment, demonstrating its potential for practical applications. This work offers a promising strategy for achieving low‐carbon emissions in phenol wastewater treatment.

Speed-Dedup: A New Deduplication Framework for Enhanced Performance and Reduced Overhead in Scale-Out Storage

Conventional deduplication systems face critical challenges such as excessive write amplification, high read/write latency, and sub-optimal storage utilization. These limitations often undermine the performance benefits of deduplication by slowing down I/O acknowledgements due to amplified deduplication I/Os, excessive data chunk replication, and strict consistency requirements. To address these issues, we present Speed-Dedup, a novel deduplication framework that employs a deduplicated primary–semi-deduplicated replica object approach. This strategy reduces write amplification by restricting deduplication to the primary object while maintaining a semi-deduplicated replica object used for immediate read/write acknowledgements, thus enhancing I/O latency and storage efficiency. Speed-Dedup also replaces traditional strong consistency models with eventual consistency, allowing for non-blocking read operations and improving overall system throughput. Experimental results demonstrate that Speed-Dedup significantly outperforms traditional methods like GRATE and CAO, showing up to 21% improvement in I/O performance under low deduplication ratios and maintaining 14% or more gains under higher ratios. Additionally, write amplification is substantially reduced and latency improves by over 100% with faster recovery times during system failures. These findings highlight the effectiveness of Speed-Dedup as a scalable and efficient solution.

Scabbard: An Exploratory Study on Hardware Aware Design Choices of Learning with Rounding-based Key Encapsulation Mechanisms

Recently, the construction of cryptographic schemes based on hard lattice problems has gained immense popularity. Apart from being quantum resistant, lattice-based cryptography allows a wide range of variations in the underlying hard problem. As cryptographic schemes can work in different environments under different operational constraints such as memory footprint, silicon area, efficiency, power requirement, and so on, such variations in the underlying hard problem are very useful for designers to construct different cryptographic schemes. In this work, we explore various design choices of lattice-based cryptography and their impact on performance in the real world. In particular, we propose a suite of key-encapsulation mechanisms based on the learning with rounding problem with a focus on improving different performance aspects of lattice-based cryptography. Our suite consists of three schemes. Our first scheme is Florete, which is designed for efficiency. The second scheme is Espada, which is aimed at improving parallelization, flexibility, and memory footprint. The last scheme is Sable, which can be considered an improved version in terms of key sizes and parameters of the Saber key-encapsulation mechanism, one of the finalists in the National Institute of Standards and Technology’s post-quantum standardization procedure. In this work, we have described our design rationale behind each scheme. Furthermore, to demonstrate the justification of our design decisions, we have provided software and hardware implementations. Our results show Florete is faster than most state-of-the-art KEMs on software platforms. For example, the key-generation algorithm of high-security version Florete outperforms the National Institute of Standards and Technology’s standard Kyber by 47%, the Federal Office for Information Security’s standard Frodo by 99%, and Saber by 57% on the ARM Cortex-M4 platform. Similarly, in hardware, Florete outperforms Frodo and NTRU Prime for all KEM operations. The scheme Espada requires less memory and area than the implementation of most state-of-the-art schemes. For example, the encapsulation algorithm of high-security version Espada uses 30% less stack memory than Kyber, 57% less stack memory than Frodo, and 67% less stack memory than Saber on the ARM Cortex-M4 platform. The implementations of Sable maintain a tradeoff between Florete and Espada regarding software performance and memory requirements. Sable outperforms Saber at least by 6% and Frodo by 99%. Through an efficient polynomial multiplier design, which exploits the small secret size, Sable outperforms most state-of-the-art KEMs, including Saber, Frodo, and NTRU Prime. The implementations of Sable that use number theoretic transform-based polynomial multiplication (SableNTT) surpass all the state-of-the-art schemes in performance, which are optimized for speed on the Cortext M4 platform. The performance benefit of SableNTT against Kyber lies in between 7-29%, 2-13% for Saber, and around 99% for Frodo.

The Impact of Corporate Social Responsibility on Corporate Reputation

This research paper explores the profound impact of Corporate Social Responsibility (CSR) on corporate reputation, focusing on the mechanisms through which CSR initiatives enhance or protect a company’s public image. By analyzing key theoretical frameworks such as stakeholder theory, social contract theory, and legitimacy theory, the paper examines how businesses strategically use CSR to manage reputational risks, improve brand trust, and foster positive public perception. Case studies of companies with successful CSR strategies highlight the benefits in financial performance, consumer loyalty, and crisis resilience. The challenges of managing CSR in a digital age, where transparency and scrutiny are heightened, are also discussed. The paper concludes with recommendations for balancing ethical responsibility with business objectives, stressing the importance of integrating CSR into core business strategies to build long-term reputational capital and sustainable growth. This research underscores CSR as a critical tool in modern corporate reputation management in both local and global contexts.

Situational and Dispositional Achievement Goals and Measures of Sport Performance: A Systematic Review with a Meta-Analysis

The purposes of this systematic review (PROSPERO ID: CRD42024510614, no funding source) were to quantify relationships between situational and dispositional dichotomous achievement goals and sport performance and explore potential relationship moderators. Published studies that reported at least one situational or dispositional achievement goal and a performance score were included. Studies without performance scores or based in a non-sport context were excluded. Information sources consisted of studies found in relevant published meta-analyses and EBSCOhost databases (finalized September 2024). The following statistics were conducted to assess the risk of bias: class-fail-safe n, Orwin’s fail-safe n, and funnel plots with trim and fill estimates. The summary statistics were r and d. Thirty studies from 1994 to 2024 met all inclusion criteria with 8708 participants from Europe, Asia, North America, and Oceania. The majority of samples were non-elite male youths and adolescents. The random-effects relationships (r) between task climate, 0.20 [0.14, 0.25], task orientation, 0.17 [0.12, 0.23], ego orientation, 0.09 [0.03, 0.16], and sport performance were small and significantly different (p < 0.05) from zero, while the ego motivational climate relationship was not, −0.00 [−0.48, 0.05]. The random-effects standard differences in means (d) for both the task orientation, 0.08 [0.02, 0.14], and ego orientation, 0.11 [−0.05, 0.26] were minimal in meaningfulness. Mixed-effects moderator analyses resulted in the following significant (p < 0.05) sub-group differences: subjective compared to objective performance measures (task orientation), elite compared to non-elite samples (task climate), and athlete-completed compared to coach-completed performance measures and performance records (task orientation). Finding only 30 studies meeting the inclusion criteria, which limited sub-group samples for moderation analyses, was the main limitation. Despite this limitation, AGT provides athletes and practitioners performance enhancement strategies. However, caution is warranted regarding relationship expectations given the small mean effect size values and the true prediction interval ranging from negative to positive, perhaps as a result of the heterogeneous samples and performance measures. A clear line of future research, considering the reviewed studies, with elite athletes is needed to verify the performance benefits of the task climate and ego orientation as well as the use of the ego goal orientation in selection decisions.

Enhancing Urban Surveillance with Fog Computing, Mobile Cloud, and Big Data Analytics in 5G Networks

The new emerging applications in 5G network, in the context of the Internet of Everything (IoE), will introduce high mobility, high scalability, real-time, and low latency requirements that raise new challenges on the services being provided to the users. Fortunately, Fog Computing and Cloud Computing, with their service orchestration mechanisms offer virtually unlimited dynamic resources for computation, storage and service provision, that will effectively cope with the requirements of the forthcoming services. 5G will use the benefits of centralized high performance computing cloud centers, cloud and fog RANs and distributed peer-to-peer mobile cloud that will create opportunities for companies to deploy many new real-time services that cannot be delivered over current mobile and wireless networks. This paper evaluates a model for fog and cloud hybrid environment service orchestration mechanisms for 5G network in terms of energy efficiency per user for different payloads.

Sex differences in elite track and field performances and inferences about steroid doping.

Females likely experience larger performance benefits from androgenic-anabolic steroids than males. We set out to determine if there were temporal differences in select athletics (track and field) records between females and males. Exploratory aims included: (1) evaluating the improvements in female and male world records over time, and (2) investigating the influence of doping programs on male and female world records before and after 1990, when sports governing bodies began to implement random out-of-competition and systematic in-competition drug testing. We collected the top 500 performances of all time for both sexes from an online database (worldathletics.org) in four running events (100, 200, 400 and 800m) and two throwing events (discus throw and shot-put). Data were stratified into quintiles based on world record ranking (1st to 100th, 101st to 200th, etc.). The temporal distribution of the top 100 female performers was significantly earlier than the top 100 male performers (year: 2000±1 vs. 2005±1, respectively; P<0.0001). Within the event, the top performances occurred significantly earlier for females in the 800m (year: 1995±15 vs. 2003±12; P=0.0007) and shot-put (year: 1992±14 vs. 2003±17; P=0.0004). Among females, world records rapidly improved through the 1980s, but following 1990, the world records ceased to improve. Geographically, there was a greater representation of countries with state-sponsored doping programs, specifically among female performances. We postulate these sex differences in the temporal distribution of top performances are likely associated with enhanced effectiveness of exogenous androgens (steroid doping) among female athletes with lower endogenous androgen hormones compared to males.

Construction of OSA-related hypertension prediction model based on nomogram

Objective:This study aimed to construct a risk prediction model for obstructive sleep apnea（OSA） related hypertension based on the nomogram, and to explore the independent risk factors for OSA-related hypertension, so as to provide reference for clinical treatment decision-making. Methods:The clinical data of OSA patients diagnosed by polysomnography from October 2019 to December 2021 were collected retrospectively and randomly divided into training sets and validation sets. A total of 1 493 OSA patients with 27 variables were included. The least absolute shrinkage and selection operator（Lasso） logistic regression model was used to select potentially relevant features and establish a nomogram for OSA-related hypertension.The performance and clinical benefits of this nomogram were verified in terms of discrimination, calibration ability and clinical net benefit. Results:Multivariate logistic regression showed that body mass index（BMI）, family history of hypertension, lowest oxygen saturation（LSaO2）, age and cumulative percentage of total sleep time with oxygen saturation below 90% were independent risk factors for OSA-related hypertension. Lasso logistic regression identified BMI, family history of hypertension, LSaO2 and age as predictive factors for inclusion in the nomogram. The nomogram provided a favorable discrimination, with a C-indexes of 0.835（95% confidence interval[CI ]0.806-0.863） 0.865（95%CI 0.829-0.900） for the training and validation cohort, respectively, and well calibrated. The clinical decision curve analysis displayed that the nomogram was clinically useful. Conclusion:Compared with cumulative percentage of total sleep time with blood oxygen saturation below 90%, LSaO2 may have a greater impact on the incidence of OSA-related hypertension, and the effects of different times and degrees of hypoxia on OSA-related hypertension should be further explored in the future. Apnea hypopnea index involvement is weak in predicting OSA-related hypertension, and the blood oxygen index may be a better predictor variable. Furthermore, we established a risk prediction model for OSA-related hypertension patients using nomogram, and demonstrated that this prediction model was helpful to identify high-risk OSA-related hypertension patients. This model can provide early and individualized diagnosis and treatment plans, protect patients from the serious.

Role of Charlson comorbidity index in predicting intensive care unit readmission in patients with aortic aneurysm.

The purpose of this study was to investigate the value of the Charlson comorbidity index (CCI) in predicting intensive care unit (ICU) readmission in aortic aneurysm (AA) patients. Patient information came from the Medical Information Mart for Intensive Care- IV (MIMIC-IV) database. The relationship between CCI and ICU readmission was analyzed by restricted cubic spline, generalized linear regression, trend analysis, and hierarchical analysis. The clinical value of CCI in predicting ICU readmission was analyzed by receiver operating characteristic curve, decision curve analysis, XGBoost regression, and random forest regression. A total of 523 patients with AA were enrolled in the study. Patients with AA who were readmitted to the ICU had higher width of red blood cell distribution width (RDW) and higher CCI. CCI had better performance and clinical net benefit for predicting ICU readmission than RDW. An independent nonlinear relationship was found between CCI and ICU readmission. The trend analysis suggested that the risk of ICU readmission increased with higher CCI scores. The hierarchical analysis showed that their association was mainly found in surgery requirement populations regardless of AA types. Further, CCI was found to have better clinical value in predicting ICU readmission of thoracic aortic aneurysm (TAA) patients undergoing surgery. Age, renal disease, chronic lung disease, and dementia were important components of CCI in predicting ICU readmission of TAA patients undergoing surgery. CCI was independently associated with the ICU readmission of AA patients in a positive relationship and had more favorable prediction performance in TAA patients who underwent surgery.

Study on characteristics and prediction of the pressure drag of the swept strut under supersonic wide-range conditions

In this paper, the numerical simulation of the swept strut ramjet combustor was carried out under wide-range conditions (Ma3 = 1.8 ∼ 5.0), and the pressure drag characteristics of the swept strut were discussed. The results show that the pressure drag characteristics of the swept strut are related to the Mach number of the combustor inlet and the swept angle of the strut. The decreased boundary of the strut pressure drag coefficient gradually advances with the decrease of the Mach number of the combustor inlet. When Ma3 = 1.8 ∼ 2.0, the pressure drag reduction boundary is α = 15°. When Ma3 = 2.2 ∼ 2.8, the pressure drag reduction boundary is α = 45°. When Ma3 = 3.0 ∼ 4.0, the pressure drag reduction boundary is α = 60°. When Ma3 = 5.0, the pressure drag reduction boundary is α = 65°. In addition, with the decrease of the Mach number of the combustor inlet, the pressure drag reduction performance benefit brought by increasing the swept angle of the strut will gradually increase. Furthermore, a pressure drag coefficient prediction model suitable for wide-range conditions and multiple configurations of swept struts was proposed based on deep learning. The prediction model consists of two parts in series, which includes the prediction model of the surface pressure coefficient of the swept strut based on multilayer perceptron (MLP) and the prediction model of the pressure drag coefficient of the swept strut based on convolutional neural network (CNN). To improve the prediction accuracy of the MLP model, new training samples were added based on the ensemble-based uncertainty quantification, and the improved MLP model was obtained by retraining. The results show that both the two prediction models have high prediction accuracy under the effect of multiple complex flow characteristics on the strut. The results of this study are helpful to provide a reference for the aerodynamic drag reduction design of the strut in the wide-speed supersonic combustor.

OpenQP: A Quantum Chemical Platform Featuring MRSF-TDDFT with an Emphasis on Open-Source Ecosystem.

The OpenQP (Open Quantum Platform) is a new open-source quantum chemistry library developed to tackle sustainability and interoperability challenges in the field of computational chemistry. OpenQP provides various popular quantum chemical theories as autonomous modules such as energy and gradient calculations of HF, DFT, TDDFT, SF-TDDFT, and MRSF-TDDFT, thereby allowing easy interconnection with third-party software. A scientifically notable feature is the innovative mixed-reference spin-flip time-dependent density functional theory (MRSF-TDDFT) and its customized exchange-correlation functionals such as the DTCAM series of VAEE, XI, XIV, AEE, and VEE, which significantly expand the applicability scope of DFT and TDDFT. OpenQP also supports parallel execution and is optimized with BLAS and LAPACK for high performance. Future enhancements such as extended Koopman's theorem (EKT)-MRSF-TDDFT and spin-orbit coupling (SOC)-MRSF-TDDFT will further expand OpenQP's capabilities. Additionally, a Python wrapper PyOQP is provided that performs tasks such as geometry optimization, conical intersection searches, and nonadiabatic coupling calculations, among others, by prototyping the modules of the OpenQP library in combination with third-party libraries. Overall, OpenQP aligns with modern trends in high-performance scientific software development by offering flexible prototyping and operation while retaining the performance benefits of compiled languages like Fortran and C. They enhance the sustainability and interoperability of quantum chemical software, making OpenQP a crucial platform for accelerating the development of advanced quantum theories like MRSF-TDDFT.

Welfare and performance benefits of shade provision during summer for feedlot cattle in a temperate climatic zone.

There is increasing interest from cattle lot-feeders in the use of shade to mitigate the effects of a potential heat stress event, though it is unclear whether the reported benefits of shade in previous studies conducted in more high-risk heat stress zones are pertinent in cooler temperate zones. The objectives of this study were to measure the welfare and performance benefits of shade provision for lot-fed cattle at a commercial feedlot located in a mild heat-stress risk zone in Western Australia. Six blocks of black Angus (Bos taurus) steers were inducted into the feedlot over six time-windows across a southern hemisphere summer, with 80 cattle per block housed in a partially shaded pen (providing 3.125 m2 of shade per animal) and 80 in an unshaded pen. Parameters assessed in 960 cattle over the first 70 days in the feedlot included weight gain, feed intake, and physiological and behavioral indices of overall health and welfare. Over the months of October through to May in which the experiment was conducted, shaded cattle demonstrated a modest 0.13kg overall increase in average daily gain across the 70-day feedlot period (P = 0.13). There was no difference in dry matter intake between any block or treatment. The physiological and behavioral markers of health and welfare revealed that, even during to hottest times of the experiment, the cattle were quite able to thermoregulate, via increased panting and seeking shade (if available), to maintain physiological homeostasis. In addition, we measured the effect of heat stress and shade provision on the affective state of the cattle. Qualitative behavioral assessment was used to indicate that the cattle in the 'no stress' temperature humidity index (THI) category and the shaded cattle in the 'moderate stress' THI category displayed the most positive demeanor (P < 0.05), being described as more 'settled and sociable', while the unshaded cattle in the 'moderate stress' THI category and all cattle in the 'severe stress' THI category were described as more 'agitated/anxious' (P < 0.05). Overall, the findings from the present study suggest that there are definite welfare and modest performance benefits associated with providing cattle with shade in summer in a feedlot situated in a temperate climatic zone.

Investigation of EDM erosion behavior for Ni-based superalloy using experimental and machine learning approach

The rapid growth of the global population and the consequent increase in manufacturing activities have heightened the need for sustainable practices to protect the environment. Non-traditional manufacturing processes, such as electric discharge machining (EDM), often use oil-based dielectric fluids like kerosene, which emit toxic fumes and aerosols, contributing to environmental pollution. To address this, the reuse of waste cooking oil (WCO) as a dielectric fluid in EDM presents a promising solution. This method not only tackles the issue of waste oil disposal but also supports the circular economy by repurposing waste materials. EDM, frequently criticized for its low cutting rates, can be enhanced by using nitrogen assisted modified Cu electrodes (cryogenically treated (CT)). This study focused on machining the difficult-to-cut nickel-based superalloy, IN718 by incorporating Sillimanite nano-powder with Span-60 (S-60). The erosion performance characteristics such as material removal rate (MRR), electrode wear rate (EWR), and accuracy index (AI) were evaluated. An artificial neural network (ANN) was employed to predict and correlate experimental and predicted values. Significant improvements were achieved using the non-dominated sorting genetic algorithm (NSGA-II) in the confirmation investigations. With a non-treated (NT) Cu electrode, the confirmatory experiments showed a 79.81 % increase in MRR, an 18.99 % decrease in EWR, and a 0.89 % improvement in AI. For the CT Cu electrode, MRR increased by 85.48 %, EWR decreased by 32.90 %, and AI improved by 0.53 % when using optimal processing parameters. This study demonstrates the potential for significant environmental and performance benefits in EDM by reusing WCO and optimizing electrode treatments.