Performance Benefits Research Articles

Inclusive leadership: Study shows benefits for employee wellbeing and performance in study of migrant workers in GCC countries

PurposeThis paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies.Design/methodology/approachThis briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.FindingsA study of the impact of inclusive leadership among supervisors and employees in GCC countries showed the mediating role of employee psychological capital in the relationship between inclusive leadership and employee performance and also in the relationship between inclusive leadership and employee well-being. The moderating effect of supervisor family motivation in the relationship between inclusive leadership and employee performance was also significant.Originality/valueThe briefing saves busy executives, strategists and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

Greater benefits of deep learning-based computer-aided detection systems for finding small signals in 3D volumetric medical images.

Radiologists are tasked with visually scrutinizing large amounts of data produced by 3D volumetric imaging modalities. Small signals can go unnoticed during the 3D search because they are hard to detect in the visual periphery. Recent advances in machine learning and computer vision have led to effective computer-aided detection (CADe) support systems with the potential to mitigate perceptual errors. Sixteen nonexpert observers searched through digital breast tomosynthesis (DBT) phantoms and single cross-sectional slices of the DBT phantoms. The 3D/2D searches occurred with and without a convolutional neural network (CNN)-based CADe support system. The model provided observers with bounding boxes superimposed on the image stimuli while they looked for a small microcalcification signal and a large mass signal. Eye gaze positions were recorded and correlated with changes in the area under the ROC curve (AUC). The CNN-CADe improved the 3D search for the small microcalcification signal ( , ) and the 2D search for the large mass signal ( , ). The CNN-CADe benefit in 3D for the small signal was markedly greater than in 2D ( , ). Analysis of individual differences suggests that those who explored the least with eye movements benefited the most from the CNN-CADe ( , ). However, for the large signal, the 2D benefit was not significantly greater than the 3D benefit ( , ). The CNN-CADe brings unique performance benefits to the 3D (versus 2D) search of small signals by reducing errors caused by the underexploration of the volumetric data.

Multi-Task ADME/PK prediction at industrial scale: leveraging large and diverse experimental datasets.

ADME (Absorption, Distribution, Metabolism, Excretion) properties are key parameters to judge whether a drug candidate exhibits a desired pharmacokinetic (PK) profile. In this study, we tested multi-task machine learning (ML) models to predict ADME and animal PK endpoints trained on in-house data generated at Boehringer Ingelheim. Models were evaluated both at the design stage of a compound (i. e., no experimental data of test compounds available) and at testing stage when a particular assay would be conducted (i. e., experimental data of earlier conducted assays may be available). Using realistic time-splits, we found a clear benefit in performance of multi-task graph-based neural network models over single-task model, which was even stronger when experimental data of earlier assays is available. In an attempt to explain the success of multi-task models, we found that especially endpoints with the largest numbers of data points (physicochemical endpoints, clearance in microsomes) are responsible for increased predictivity in more complex ADME and PK endpoints. In summary, our study provides insight into how data for multiple ADME/PK endpoints in a pharmaceutical company can be best leveraged to optimize predictivity of ML models.

Evaluation of Growth Performance, Carcass Characteristics and Cost Benefit of Broiler Chicken Fed African Pear Seed Meal (APSM)

Evaluation of Growth Performance, Carcass Characteristics and Cost Benefit of Broiler Chicken Fed African Pear Seed Meal (APSM)

Analysing Customers’ Perception on QR Payment in Kathmandu Valley: An Empirical Study using UTAUT and PLS-SEM

Background: The growing use of the Fintech industry significantly impacts the popularity of QR payment. The easy and convenient use of digital payment systems has increased the adoption of QR payments. The study analyses customers' perceptions of QR payment in the Kathmandu Valley. Methods: The study uses explanatory research design to analyse the connections and causal effects between the determinants that affect the customer perceptions of using the QR payment system in the Kathmandu Valley. Non-probability sampling with convenient sampling is used for the study. Data is collected from 280 customers who have used QR payment services using the Structural Questionnaire through the Kobo Toolbox. Similarly, the Structural Equation Modeling (SEM) using the Partial Least Square (PLS) version 4.0 is adopted for analysis. Results: The study highlights a growing trend among respondents, with an increasing number habitually using QR payments for 1-3 years. E-sewa, Fone pay, and Connect IPS are popular choices for activities like fund transfers and bill payments. Despite facing challenges such as technical glitches and debited funds from failed transactions, respondents view QR payments as a convenient method. However, these challenges can be addressed through regular maintenance, enhanced internet infrastructure, transaction flexibility, stable connectivity, and improved system performance. Conclusions: The result shows a significant relationship between the independent variables, such as performance expectation and facilitating conditions and the dependent variable, i.e., customer perception. It indicates that when users perceive higher performance benefits from QR payment, their overall perception improves. Similarly, when users perceive a favourable environment for QR payment adoption, their perception is positively influenced, enforcing the increasing use of QR payment. Paper Type: Research Type

Study on recycling and utilization of phosphogypsum and lithium slag in vertical barrier materials

Traditional vertical barrier materials typically have a large carbon footprint and high cost. Phosphogypsum (PG) and lithium slag (LS), possess latent cementitious activity. This study investigated the potential use of PG and LS in vertical barrier materials. The basic characteristics of the system were studied for LS:PG (mass ratio) ranging from 1:1–1:9, with a bentonite content of 10 % and a water-to-solid ratio of 0.5. The PG-LS matrix was microscopically characterized using XRD, TG, FT-IR, and SEM analysis. Additionally, an economic and sustainability assessment was performed. The results indicated that when LS:PG was in the range of 1:3–1:1, the flowability and setting time ranged from 16.15 to 21.00 cm and 51–87 hours, respectively. The bleeding rate within 12 hours was consistently below 5 %. Furthermore, the compressive strength and permeability coefficient at 28 days were within the ranges of 1.81–7.99 MPa and 2.91×10−8 to 7.98×10−9 cm/s, respectively. Excessive addition of PG was found to be unfavorable for the formation of C-(A)-S-H gel, resulting in an increase in free alkali content in the system and promoting the carbonation-induced formation of Calcite, thereby reducing the compressive strength and increasing the permeability. Compared to traditional barrier materials, the PG-LS-based barrier material exhibited a 61 % reduction in CO2 emissions and a cost reduction of 75–82 %. Additionally, the leaching concentrations of Zn, Cr, Ni, Cu, Pb, Cd, and As were below the standard limits. Therefore, the utilization of PG and LS in vertical barrier systems demonstrated excellent performance, economic feasibility, and environmental benefits, indicating significant potential for widespread application.

Maximizing green innovation: the impact of government subsidies and R&D in digital supply chains

PurposeThis research examines the relationship between green innovation and firm performance, focusing on identifying the moderating effects of government subsidies and digital transformation R&D investments. The study aims to provide insights on how firms can leverage green innovation for enhanced performance while addressing potential drawbacks.Design/methodology/approachThis study adopts a mixed-methods approach, utilizing both analytical models and empirical analyses. It investigates the curvilinear relationship between green innovation and firm performance and explores the moderating roles of government subsidies and digital transformation R&D investments.FindingsThe findings reveal an inverted U-shaped relationship between green innovation and firm performance, indicating that initial investments in green innovation led to performance improvements, but beyond a certain point, the returns diminished. The study also finds that government subsidies and digital transformation R&D investments significantly enhance the positive impact of green innovation up to the optimal threshold and help mitigate negative effects.Practical implicationsThe research provides practical guidance for firms on managing their green innovation investments to maximize performance benefits. It also offers insights for policymakers on designing effective subsidies and support mechanisms to promote environmental sustainability and economic growth.Originality/valueThis study contributes to the literature by elucidating the complex relationship between green innovation and firm performance and highlighting the critical roles of government subsidies and digital transformation R&D investments. It offers valuable implications for businesses seeking to balance environmental and economic objectives and policymakers aiming to foster sustainable and profitable practices.

Synergy of Hybrid Fillers for Emerging Composite and Nanocomposite Materials-A Review.

Nanocomposites with polymer matrix provide tremendous opportunities to investigate new functions beyond those of traditional materials. The global community is gradually tending toward the use of composite and nanocomposite materials. This review is aimed at reporting the recent developments and understanding revolving around hybridizing fillers for composite materials. The influence of various analyses, characterizations, and mechanical properties of the hybrid filler are considered. The introduction of hybrid fillers to polymer matrices enhances the macro and micro properties of the composites and nanocomposites resulting from the synergistic interactions between the hybrid fillers and the polymers. In this review, the synergistic impact of using hybrid fillers in the production of developing composite and nanocomposite materials is highlighted. The use of hybrid fillers offers a viable way to improve the mechanical, thermal, and electrical properties of these sophisticated materials. This study explains the many tactics and methodologies used to install hybrid fillers into composite and nanocomposite matrices by conducting a thorough analysis of recent research. Furthermore, the synergistic interactions of several types of fillers, including organic-inorganic, nano-micro, and bio-based fillers, are fully investigated. The performance benefits obtained from the synergistic combination of various fillers are examined, as well as their prospective applications in a variety of disciplines. Furthermore, the difficulties and opportunities related to the use of hybrid fillers are critically reviewed, presenting perspectives on future research paths in this rapidly expanding area of materials science.

The Role of Musculoskeletal Training During Return to Performance Following Relative Energy Deficiency in Sport.

Relative energy deficiency in sport (REDs) is a condition that is associated with negative health and performance outcomes in athletes. Insufficient energy intake relative to exercise energy expenditure, resulting in low energy availability, is the underlying cause, which triggers numerous adverse physiological consequences including several associated with musculoskeletal (MSK) health and neuromuscular performance. This commentary aims to (1) discuss the health and performance implications of REDs on the skeletal and neuromuscular systems and (2) examine the role that MSK training (ie,strength and plyometric training) during treatment and return to performance following REDs might have on health and performance in athletes, with practical guidelines provided. REDs is associated with decreases in markers of bone health, lean body mass, maximal and explosive strength, and muscle work capacity. Restoration of optimal energy availability, mainly through an increase in energy intake, is the primary goal during the initial treatment of REDs with a return to performance managed by a multidisciplinary team of specialists. MSK training is an effective nonpharmacological component of treatment for REDs, which offers multiple long-term health and performance benefits, assuming the energy needs of athletes are met as part of their recovery. Supervised, prescribed, and gradually progressive MSK training should include a combination of resistance training and high-impact plyometric-based exercise to promote MSK adaptations, with an initial focus on achieving movement competency. Progressing MSK training exercises to higher intensities will have the greatest effects on bone health and strength performance in the long term.

Landmark-based guidance and cognitive saliency: Age-related benefits in spatial performance

Older adults have difficulties using a map, and the use of GPS systems seems beneficial to help them find their way in cities. The question arises however as to what extent the introduction of landmarks can be even more beneficial. While the visual saliency of landmarks has been well studied, the cognitive saliency of landmarks has received little attention. Our objective in this study was to determine if guiding young and older pedestrians with visually and cognitively salient landmarks inserted in a map or a GPS-like system improved spatial performances. Thirty-four young and 32 older adults navigated a virtual environment using a joystick. They were guided with a map or with GPS-like instructions, including either only visually or both visually and cognitively salient landmarks. After each itinerary, participants completed four tasks: landmark recognition and sequencing, direction recognition and sequencing. The results showed that the integration of visually and cognitively salient landmarks in a map or in GPS-like instructions improved the construction of landmark and route knowledge in both young and older participants. Results also suggested that age-related deficits in spatial memory could be reduced by using GPS-like instructions or by introducing cognitively salient landmarks, in a map or in a GPS-like system. This research opens several perspectives for research as well for the design of human-centred navigation aids.

NATURAL CAFFEINE, SOURCES, EXTRACTION, USAGE, AND EFFECT OF CAFFEINE ON HUMAN HEALTH

The primary method of absorbing natural caffeine (1,3,7-trimethylxanthine) is through the consumption of coffee.Natural Caffeine is a white crystalline purine containing methylxanthine alkaloids with a harsh flavour. It is the most often consumed bioactive substance across the world. It is a naturally occurring alkaloid found in over 60 plants, including coffee beans, tea leaves, cola nuts, and cocoa pods. Natural Caffeineis extracted from Coffee arabica beans . It can be found in various plant sources such as Coffee beans, tea leaves ,Cacao Beans , Yerba mate ,Guarana ,Kola nuts. It can have a favourable or harmful impact on human health. Natural sources of caffeine frequently include plant polyphenols (phenol-carboxylic acids, catechins) with known antioxidant properties however, stimulant drinks and dietary supplements frequently contain sugars or artificial sweeteners, which can significantly reduce caffeines effects on oxidative stress.C-14 testconducted for Natural Caffeine by Mangalore University and the University of California. An Inhouse testing method by HPLC has been developed by Bio-Med Ingredients Pvt. Ltd for determining Caffeine content in samples. Caffeine finds many applications, as it is used in dietary supplements ,Vitamin Premixes , Cosmetics and for energy performance benefits including improved physical endurance and reduced fatigue.

The strategic importance of Australian farmland as a property sector for institutional investors

PurposeFarmland is an important property sector that has attracted the attention of institutional investors globally in recent years. This paper examines the risk-adjusted performance and portfolio diversification benefits of Australian farmland in a portfolio over the eight-year period of Q2:2015–Q2:2023, highlighting the unique property management dimensions to this property sector for its effective role in an institutional investor's property portfolio.Design/methodology/approachUsing the quarterly ANREV Australian farmland index over Q2:2015–Q2:2023, the risk-adjusted performance and portfolio diversification potential of Australian farmland is assessed. Constrained mixed-asset portfolios are used to assess the potential added-value role of Australian farmland in a mixed-asset portfolio. Analyses are also done for the farmland sub-sectors of annual farmland and permanent farmland.FindingsAustralian farmland is seen to show strong risk-adjusted performance but at a much higher risk level than that seen for direct property. Diversification benefits from Australian farmland are also evident, with an important role by Australian farmland seen in the mixed-asset portfolio. Specific farmland property management strategies are identified for the effective inclusion of farmland in an institutional investor's property portfolio, including the potential benefits towards net zero carbon strategies.Originality/valueThis is the first research that provides an independent empirical examination of the strategic importance of Australian farmland property for institutional investors using the institutional investment-grade ANREV Australian farmland database, from both an investment and environmental perspective. The unique property management implications for Australian farmland property are also highlighted, including the potential role of Australian farmland in net zero carbon strategies by institutional investors.

Evaluation of energy performance and environmental benefits for transcritical CO2 thermal system in high-speed trains

The conventional air conditioning system used in high-speed railways has limitations in heating performance and environmental impact, necessitating the exploration of alternative refrigerants. The transcritical CO2 system has gained popularity due to its exceptional heating efficiency and environmental benefits. This study aims to evaluate the energy and environmental potentials for transcritical CO2 systems in high-speed trains based on four-vertical-and-four-horizontal railway lines within different climatic regions of China. A high-fidelity transcritical CO2 system model was first developed and validated through experiments. Then, a comprehensive energy and environmental evaluation method was proposed and applied to the four-vertical-and-four-horizontal railway lines. The results indicated that the transcritical CO2 system had a superior heating performance and competitive cooling performance based on daily and annual operations. Furthermore, the transcritical CO2 system exhibited significant environmental advantages with lower total life cycle climate performance for all lines, with an average emissions reduction ratio of 17.6% and a maximum emissions reduction ratio of 26.98%. These findings highlight the competitive energy performance and outstanding environmental benefits offered by transcritical CO2 systems as promising alternatives to air conditioning systems in railway transportation.

The Impact of Family Firms and Supervisory Boards on Corporate Environmental Quality

This paper examines the impact of family ownership and supervisory board characteristics on carbon emission disclosure. It uses balanced panel data and a matched-pair design of 124 non-financial firms listed on the Indonesia Stock Exchange from 2017 to 2019. This study finds that family firms and larger boards improve, while female board members harm carbon emission performance. Further analyses reveal non-linear relationships between family ownership and carbon performance. When control rights are limited, family firms prioritize controlling managers and improving carbon quality. Conversely, they prioritize personal objectives over environmental concerns when there are high control rights, resulting in decreased carbon emission performance. Additionally, family board members generate more carbon information, indicating the family owners effectively utilize their position on the supervisory boards to influence the company’s carbon emission performance. Finally, the study reports that more faculty member boards seem to hurt carbon emission reduction efforts. This result suggests that the diversity of their professional experiences does not affect the environmental effectiveness of supervisory boards. Our findings highlight the importance of understanding SEW principles and their connection to families in comprehending Indonesian corporate carbon emissions disclosures. The findings of this study enrich the worldwide literature by exploring the potential benefits of family business environmental performance. This study also adds to the literature on corporate governance, especially the role played by supervisory boards. Our findings align with the resource dependence theory, emphasizing the central function of supervisory boards as a monitoring tool. This study is constrained by its reliance on carbon emission data extracted from the annual reports of public firms, with a particular emphasis on pre-COVID-19 data. Future research should focus on sustainability reports and explore the time frame encompassing COVID-19 (2020–2022 datasets) to determine any differences in the findings.

The relationship of technological and organizational innovation with firm performance: Opening the black box of dynamic complementarities

This paper explores the dynamic nature of complementarities between technological and organizational innovation at firms. Using Spanish panel data of manufacturing firms (PITEC) over the period 2008–2016, it investigates how the formation and ending of the joint adoption of these two core types of innovation is associated with firm performance. We observe clear evidence that some sequential as well as simultaneous strategy switches towards combining technological and organizational novelties are associated with significant performance premia at firms. Our findings point out the crucial role of technological innovation in these complementarities. In the case of giving up the adoption of new elements of the complementarity bundle of innovation types, the critical disadvantage for the firm is related to dropping the adoption of technological innovation. Giving up adoption of new organizational innovation while keeping the adoption of new technological innovation appears to have no negative effect, on average, on firm performance. Our findings suggest significant coordination failures at firms attempting to introduce both core types of innovation in tandem. For many firms, the retention of the joint adoption of technological and organizational innovation over time is a costly and hard-to-maintain choice and not necessarily the one with the highest performance benefits.

A statistical boundary for 3D rarefied flows through meshes: implementation to a new version of dsmcFoam+ and wind tunnel validation

AbstractThe Direct Simulation Monte Carlo (DSMC) method has become a standard tool for rarefied aerodynamics and microchannel flows. However, the performance benefits of DSMC, such as adaptive grid sizes and number of particles, are constrained by the need to resolve small geometric details of mesh applications within relatively large simulation volumes. The requirement for a sufficient number of particles in even the smallest cells imposes a significant computational burden. A novel set of cyclic statistical boundary conditions is proposed to address the computational bottleneck associated with simulating micrometre-scale structures prevalent in atmospheric and space research under rarefied flow conditions. These conditions account for the geometric parameters of a geometric mesh and the angular dependency of impacting particles, aiming to alleviate the computational challenges posed by conventional approaches. Validation against wind tunnel measurements demonstrates excellent agreement for one of the implemented boundaries, able to simulate fine meshes for conditions of rocket soundings in the Mesosphere. The newly developed boundary conditions are implemented within the advanced DSMC solver, dsmcFoam+ framework. For this study, the solver is ported from OpenFOAM® version 2.4.0 to the OpenFOAM® version v2306 to leverage recent code developments, particularly in dynamic meshes, load balancing, and barycentric particle tracking. This advancement enhances the capabilities of DSMC simulations, offering improved fidelity and accuracy in capturing rarefied flow phenomena.

HubEnsembles: Ensembling Methods in R.

Combining predictions from multiple models into an ensemble is a widely used practice across many fields with demonstrated performance benefits. The R package hubEnsembles provides a flexible framework for ensembling various types of predictions, including point estimates and probabilistic predictions. A range of common methods for generating ensembles are supported, including weighted averages, quantile averages, and linear pools. The hubEnsembles package fits within a broader framework of open-source software and data tools called the "hubverse", which facilitates the development and management of collaborative modelling exercises.

Optimizing fertilization depth to promote yield performance and economic benefit in maize for hybrid seed production

Fertilization depth adjustment is a well-known strategy for increasing crop yields. However, the precise mechanism associated with this strategy remains unclear, particularly regarding increased nutrient absorption and utilization, and maize seed production. Thus, we examined the effects of different nitrogen fertilization depths [0 cm (L0), 5 cm (L5), 15 cm (L15), and 25 cm (L25)] on maize crop growth, nutrient uptake and distribution, fertilizer use efficiency, grain yield, and economic benefits in a field study conducted for two years (2021–2022) in Hexi Oasis Irrigation Area, northwest China. The optimal nitrogen fertilization depth was crucial for enhancing growth, dry matter production, and the grain yield. In particular, compared with L15 and L5, L25 significantly (P < 0.05) increased the average plant height by 5.00 % and 10.36 %, respectively, and dry matter accumulation by 2.65 % and 3.39 %. Furthermore, compared with L5 and L15, the total nutrient uptake was 19.17 % (P < 0.05) and 7.11 % higher under L25, respectively, and the average grain nutrient uptake was 23.33 % higher (P < 0.05). Moreover, L25 significantly increased the N, P, and K fertilizer utilization efficiency compared with L5 and L15, and the highest dry matter to grain translocation occurred under L25. Structural equation modeling confirmed that deep nitrogen fertilization promoted growth, dry matter translocation to grain, and the uptake and distribution of nutrients in maize plants to significantly improve the fertilizer use efficiency and yield. These findings are important for guiding fertilization management practices to increase maize seed production in regions with similar climate conditions.

Assessment of Innovative Technologies for Hazardous Waste Treatment and Remediation Review: A Sustainable Approach for Environmental Protection

&lt;p&gt;The management of hazardous waste is a critical environmental challenge that requires innovative and sustainable solutions to mitigate adverse impacts on ecosystems and human health. This research project aims to assess and evaluate cutting-edge technologies for the treatment and remediation of hazardous waste, focusing on their sustainability and effectiveness in environmental protection. The study will investigate various innovative methods such as advanced oxidation processes, bioremediation techniques, nanotechnology applications, and green chemistry strategies. These technologies offer promising opportunities to address hazardous waste contamination while minimizing resource consumption and environmental footprints. The research will include a comprehensive review of existing literature, case studies, and technical reports to gather insights into the performance, cost-effectiveness, and environmental benefits of these innovative technologies. Special emphasis will be placed on evaluating their applicability across different types of hazardous waste, ranging from industrial chemicals and pollutants to electronic waste and persistent organic pollutants. Furthermore, the study will analyze regulatory frameworks, policy implications, and socio-economic factors influencing the adoption and implementation of these technologies in diverse industrial sectors and geographical regions. Through rigorous assessment and analysis, this research aims to provide valuable insights and recommendations for stakeholders, policymakers, and environmental practitioners involved in hazardous waste management. The findings will contribute to advancing sustainable approaches for addressing hazardous waste challenges, promoting environmental protection, and fostering a circular economy mindset in waste management practices.&lt;/p&gt;

Multiphoton simultaneous multislice imaging.

To develop multiphoton excitation techniques for simultaneous multislice (SMS) imaging and evaluate their performance and specific absorption rate (SAR) benefit. To improve multiphoton SMS reconstruction quality with a novel CAIPIRINHA (controlled aliasing in parallel imaging results in higher acceleration) design. When a conventional single-slice RF field is applied together with an oscillating gradient field, the two can combine to generate multiphoton excitation at multiple discrete spatial locations. Because the conventional RF is reused at multiple spatial locations, multiphoton excitation offers reduced SAR for SMS applications. CAIPIRINHA shifts are often used to improve parallel-imaging acceleration. Interestingly, CAIPIRINHA-type shifts can be obtained for multiphoton SMS by updating the oscillating gradient phase at every phase encode. In this work, both a gradient-echo and a spin-echo sequence with multiphoton CAIPIRINHA-SMS excitation pulses are implemented for in vivo human imaging at 3 T. For three slices, multiphoton SMS provides a 51% reduction in SAR compared with conventional superposition SMS, whereas for five slices, SAR is reduced by 66%. Multiphoton SMS outperforms PINS (power independent of number of slices) and MultiPINS in terms of SAR reduction especially when the pulse duration is short, slices are thin, and/or the slice spacing is large. A custom CAIPIRINHA phase-encoding design for multiphoton SMS significantly improves reconstruction quality. Multiphoton SMS excitation can be obtained by combining conventional single-slice RF pulses with an oscillating gradient and offers significant SAR benefits compared with conventional superposition SMS. A novel CAIPIRINHA design allows higher multiband factors for multiphoton SMS imaging.