High Performance Research Articles

Navigating uncertainty: configurations of entrepreneurial behaviors for new venture performance

Purpose The entrepreneurial process often cannot be explained by a single entrepreneurial theory. Instead, it is more likely the result of the interaction between various entrepreneurial behavior patterns and different environmental conditions. However, existing research has frequently overlooked the complexity inherent in the entrepreneurial phenomenon. Building on a configurational perspective, this study aims to examine how new ventures can use different behavioral configurations to achieve high performance amid various uncertain environments. Design/methodology/approach Based on the survey data from 143 new start-ups in China’s software industry, this study uses fuzzy-set qualitative comparative analysis (fsQCA). Findings This study jointly considers multiple entrepreneurial behaviors − causation, effectuation and entrepreneurial bricolage and different types of environmental uncertainty − state uncertainty, effect uncertainty and response uncertainty. The findings reveal three behavioral configurations for high/nonhigh new venture performance. Originality/value This study expands previous insights into the relationship between entrepreneurial behaviors and new venture performance from the perspective of configurational theory. Moreover, it offers new insights into the types of uncertainty, further refining our understanding of the uncertainties inherent in entrepreneurial activities.

LiLnGeS4 (Ln = La–Nd): Designing High Performance Infrared Nonlinear Optical Sulfides through “Band Reformation of AGS”

LiLnGeS4 (Ln = La–Nd): Designing High Performance Infrared Nonlinear Optical Sulfides through “Band Reformation of AGS”

LiLnGeS4 (Ln = La–Nd): Designing High Performance Infrared Nonlinear Optical Sulfides through “Band Reformation of AGS”

LiLnGeS4 (Ln = La–Nd): Designing High Performance Infrared Nonlinear Optical Sulfides through “Band Reformation of AGS”

Analysis of Aluminum–Cerium Based Conductor Die-Casting Alloys for High Performance Electric Vehicle Powertrain Applications

Analysis of Aluminum–Cerium Based Conductor Die-Casting Alloys for High Performance Electric Vehicle Powertrain Applications

Electrospinning Fiber Membrane‐Derived Gel Polymer Electrolytes with High Mechanical Strength and Low Swelling Effect for High‐Safety Lithium Metal Batteries

AbstractThe practical application of lithium metal batteries (LMBs) is hindered by the issues of flammable electrolytes, lithium dendrites and the resulting thermal runaway. Designing flame‐retardant electrolytes with high performance is a valid strategy to break the current dilemma. In this work, the flame retardant of triphenyl phosphate (TPP) is elaborately encapsulated into the polymer shell of polyacrylonitrile (PAN) and polyvinylidene fluoride‐hexafluoropropylene (PVDF‐HFP) to realize the controllable release of TPP during the soaking process. The resulting TPP@PAN/PVDF‐HFP fiber membrane holds high thermal stability, high mechanical strength, and low swelling rate, which is essential for the preparation of flame‐retardant gel polymer electrolyte (GPE). As demonstrated, the TPP@PAN/PVDF‐HFP GPE can deliver high Li+ transference number of 0.877, low interfacial activation energy barrier of 26.6 kJ mol−1 and heterogeneous SEI composition of Li3PO4/Li2CO3/LiF. The corresponding Li||Li cells achieve stable voltage polarization over 1000 h, and the Li||Cu cells display high plating/stripping CE of 99.1%. Meanwhile, the optimized Li||LiFePO4 batteries exhibit high reversible capacity of 158 mAh g−1 after 200 cycles at 0.5 C, and present outstanding fire resistance through the thermal runaway and puncture test. This study will open window for the design of high‐safety electrolytes to promote the practical application of LMBs.

Collaborative control of circumferential yarn implantation system for large-scale 3D braiding equipment using fast nonsingular terminal sliding mode

To ensure high performance collaborative control of the circumferential yarn implantation system for a specific large-scale 3D braiding equipment, a multi-motor fast nonsingular terminal sliding mode (FNTSM) controller is proposed using time-delay estimation (TDE) and deviation coupling control (DCC). Then, comparative experiments were conducted among our proposed TDE-based FNTSM controller and PD controller and TDE-based PD controller. As shown in the experimental results, the root-mean-square error (RMSE) and maximum absolute error (MAE) ensured by our FNTSM controller tracking sine signal have decreased by 89.4% and 67.1% compared with the ones by PD controller; while the RMSE of our FNTSM controller tracking slope signal is ensured within 0.03°. Meanwhile, the RMSE and MAE of our FNTSM controller tracking sine signals has been reduced by 48.2% and 56.9% due to DCC, respectively. Afterwards, less than 3% error fluctuation has been observed with load using our FNTSM controller. High control performance and strong robustness have been experimentally observed.

A new Co‐based cathode with high performance for intermediate‐temperature solid oxide fuel cells

AbstractSolid oxide fuel cells (SOFCs) as highly effective energy conversation devices have gained substantial recognition and research interest. The electrochemical properties of the traditional SOFCs are restricted by the sluggish reaction kinetics for the cathode material when lowering the operation temperature to below 600°C. In addition, the stability of the cathode at reduced temperatures is also a big challenge for the widely popularization of SOFC technology. Achieving high activities and stable ORR in the cathode is crucial for the development of SOFCs. The doping active metal method has been demonstrated as an effective approach to optimize the phase structure and improve the ORR activity of the cathode. Herein, we successfully develop an Ir‐doped SrCoO3 − δ (SrCo0.98Ir0.02O3 − δ, SCI) cathode for SOFCs. SCI exhibits a low area‐specific resistance (ASR) of 0.057 Ω cm2 at 650°C, ~ 44% lower than 0.102 Ω cm2 of Ir‐free SrCoO3 − δ. The Ni–Sm0.2Ce0.8O1.90 (SDC) anode‐supported fuel cell with SDC electrolyte and SCI cathode obtains an excellent output performance (e.g., 1,128 mW cm−2 at 650°C). The desired results underscore the feasibility of the Ir‐doping strategy as an optimized method for the exploitation of advancing cathode in SOFCs.

Consumer Sentiment Analysis and Product Improvement Strategy Based on Improved GCN Model

In recent years, the amount of online shopping review data has increased dramatically. Obtaining information that helps business decision-making from such complex and massive reviews has become a difficult and important task for merchants. This paper uses sentiment analysis technology to innovatively introduce the attention mechanism on the LSTM infrastructure of the baseline model, and proposes a word vector structure and a BiGRU structure to build an online user sentiment analysis system based on deep learning. The system includes a user review sentiment classification and sentiment analysis model based on the improved GCN model. The experimental results also show the superiority of our method, which brings 4.73%, 7.84% and 5.72% F1-score improvements to the algorithm respectively. It proves that the two algorithms proposed in this paper can effectively achieve their goals and achieve high performance.

DECOMICS, a shiny application for unsupervised cell type deconvolution and biological interpretation of bulk omic data

Abstract Unsupervised deconvolution algorithms are often used to estimate cell composition from bulk tissue samples. However, applying cell type deconvolution and interpreting the results remains a challenge, even more without prior training in bioinformatics. We propose here a tool for estimating and identifying cell type composition from bulk transcriptomes or methylomes. DECOMICS is a shiny-web application dedicated to unsupervised deconvolution approaches of bulk omic data. It provides (i) a variety of existing algorithms to perform deconvolution on the gene expression or methylation-level matrix, (ii) an enrichment analysis module to aid biological interpretation of the deconvolved components, based on enrichment analysis, and (iii) some visualisation tools. Input data can be downloaded in csv format and pre-processed in the web application (normalisation, transformation and feature selection). The results of the deconvolution, enrichment and visualisation processes can be downloaded. DECOMICS is an R-shiny web application that can be launched (i) directly from a local R session using the R package available here https://gitlab.in2p3.fr/Magali.Richard/decomics (either by installing it locally, or via a virtual machine and a Docker image that we provide); or (ii) in the Biosphere—IFB Clouds Federation for Life Science, a multi-cloud environment scalable for high performance computing: Https://biosphere.france-bioinformatique.fr/catalogue/appliance/193/.

A photocatalysis-self-Fenton system based on NCDs@ZnIn2S4 composites at neutral pH and low amount of Fe2+ for the effective degradation of antibiotics

Photocatalysis-self-Fenton combining photocatalytic production of H2O2 with Fenton reaction has been a hotspot, but the pH limitation and iron sludge production problems remain unsolved. Herein, we proposed a self-fenton system based on N-doped carbon dots modified ZnIn2S4 (NCDs@ZnIn2S4) composites that exhibits effective degradation of antibiotics under neutral pH using low amounts of Fe2+. The decoration of ZnIn2S4 with NCDs significantly increased the surface area, visible light absorption, charge transfer ability and oxygen adsorption ability. NCDs@ZnIn2S4 composites exhibited a high H2O2 production rate (1528 μM g−1•h−1) under visible light, which was 1.9 and 5.3 times higher than ZnIn2S4 and NCDs, respectively. Meanwhile, the Fe2+/NCDs@ZnIn2S4 system with a low concentration of Fe2+(1 mg/L) could remove over 95% levofloxacin and oxytetracycline within 30 min. Interestingly, the highest degradation efficiency occurred under neutral pH. Quenching experiments and analytical measurements indicated that the high catalytic performance under pH = 7 with low amounts of Fe2+ stemmed from the higher amount of inner-generate H2O2 under neutral pH and easy regeneration of Fe2+ by photoinduced electrons for high •OH yields. Additionally, the Fe2+/NCDs@ZnIn2S4 system exhibited high degradation performance under different water matrix and ultrahigh degradation efficiency towards levofloxacin under real sunlight irradiation. The work shows the prospects of photocatalysis-self-Fenton systems for overcoming the pH limitation and the difficulty of iron sludge separation in the purification of effluents.

Design of DC bus voltage high dynamic performance control for single-phase converters

Design of DC bus voltage high dynamic performance control for single-phase converters

Facile Synthesis of a Layered Bismuth-Based MOF With Superhydrophobic-Oleophilic Property and High Oil-Water Separation Performance.

Metal organic frameworks (MOFs) are a class of potential superhydrophobic-oleophilic materials. The organic ligands in superhydrophobic MOFs usually contain long alkyl chains, fluorine groups or aromatic rings with large π conjugation, the preparation of which suffers from high cost, complex operation and so on. In addition, the topological structure of MOFs plays an important role in the hydrophobicity, which may be ignored previously. Here we report a superhydrophobic-oleophilic MOF (BiPPA2) obtained by a facile and fast method, which not only displays a large water contact angle of up to 163° and a small sliding angle of nearly equal to 0°, but also exhibits high sorption capacity for multiple oils and organic solvents, well reusability and high oil retention. In addition, BiPPA2 is stable in a wide pH range (0.5-11.0). Finally, the single crystal structure of BiPPA2 is resolved to reveal the intrinsic reason for the super-hydrophobicity. This work may inspire the further design of pristine superhydrophobic MOFs based on a simple method, which enriches the family of superhydrophobic MOFs and has great significance for practical applications.

Investigating the Relationship between the General Health of Mothers and their Maternal Performance following Vaginal Childbirth

Background Birthing parents need to use specialized skills as the first caregivers of the newborn. Several factors may affect maternal performance, the general health of the birthing parent (e.g., mother) being one of them. Yet, there is a paucity of research in this area, particularly in Iran, and evidence remains inconsistent. Consequently, this study aimed to determine any correlations between maternal performance and the general health of mothers following vaginal childbirth in the context of Iran. Methods This cross-sectional study was conducted with people identifying as mothers (n = 450) who had given birth (< two months) and been referred for the vaccination of their newborn. The multi-stage sampling method was carried out from April 2022 to February 2023. Participants who met the inclusion criteria completed a demographic and obstetric information questionnaire, along with the Barkin maternal performance and general health questionnaire. To investigate the relationship between maternal performance and the general health of the mothers, an independent t-test analysis was conducted . The level of statistical significance was set at p < 0.05. Results The mean age of participants was 26.78, and the mean total score of maternal performance was 91.04 (0 - 120). The highest and lowest scores related to the ‘maternal competence’ and the ‘maternal needs’ domains, respectively. Overall, 76.89% of participants had a favorable general health condition (a score of less than 3.5 is considered favorable). There was no statistically significant difference identified in terms of maternal performance scores between those with a favorable and those with an unfavorable general health status. Conclusion Although the results of the present study did not show a significant relationship between the general health of mothers and maternal performance, this research builds on a growing body of evidence in the context of Iran. Despite recording high maternal performance scores in this sample, it will be important to enhance and maintain good mental health in all childbearing people, particularly following vaginal childbirth, as it is this which will enhance care and outcomes overall.

Effect of plant species on wastewater treatment performance of a subsurface vertical-flow constructed wetland with step-feeding at low temperature

To improve the treatment performance of constructed wetlands under low-temperature conditions, this study investigated the effects of plant species on wastewater treatment performance at low temperature and the associated microbiological characteristics in a subsurface vertical-flow constructed wetland (VFCW) with step-feeding. The results showed that the redox microenvironment in the VFCW filter with step-feeding could be restored and optimized by planting appropriate species that can tolerate low temperature, ensuring a high nitrification performance for the system. Correspondingly, the abundance and activity of three functional microbes (namely nitrifiers, denitrifiers, and anammox bacteria) increased to different degrees in the system, eventually ensuring ideal nitrogen removal by the VFCW. Compared with the VFCW planted with Phragmites australis and Acorus gramineus, the operation performance of the VFCW planted with Iris wilsonii could be recovered at low temperature, and its chemical oxygen demand, total phosphorus, total nitrogen, and ammonium nitrate removal rates could respectively reach 95.7%, 99.2%, 93.0%, and 94.4%, respectively. Moreover, nitrogen removal in the system relied on the nitrification/denitrification and partial denitrification - anaerobic ammonium oxidation processes. Nitrosomonas, Nitrospira, Thauera, and Candidatus Brocadia were the four dominant bacterial genera in the filter layer.

Promotional Press Releases and Investor Processing Costs

Press releases are a primary disclosure channel firms use to communicate with investors. However, firms can also use press releases to self-promote to improve their public image. Promotional press releases are, on average, significantly less value relevant than those focused toward investors. They also contain more positive and emotional language as well as less specific and financially oriented language. Based on theories of disclosure processing costs and investor attention, we predict and find that firms’ recent high usage of this disclosure channel to self-promote is associated with increased investor attention and more efficient reactions to subsequent investor-focused disclosures. This effect is concentrated in less visible firms, whereas promotional press releases appear to have no effect on the pricing efficiency of more visible firms. We also provide evidence consistent with media attention being one channel through which these effects operate. Our findings deepen our understanding of how firms use press releases as a disclosure channel and contribute to the literature on disclosure processing costs. This paper was accepted by Eric So, accounting. Funding: This work was supported by resources at the Arkansas High Performance Computing Center. C. Rawson gratefully acknowledges financial support from the Sam M. Walton College of Business. B. J. Twedt gratefully acknowledges financial support from the Mays Business School. J. C. Watkins gratefully acknowledges financial support from the Mendoza College of Business.. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2023.01903 .

Emergency Response Competencies Strengthened by Sustainable Education: First Aid Training Program for Teachers

The primary aim of this study is to assess the knowledge, attitudes, and skills of primary school teachers regarding the management of musculoskeletal trauma through first aid interventions and to determine the effectiveness of a sustainable training program. The preparedness of 138 teachers who received first aid training for trauma intervention and the impact of these trainings on health practices were examined by pre- and post-tests. It was determined that 87% of the teachers participating in the study had not received emergency trauma training before. Pre-training test results showed that the participants had a low level of awareness. However, the increase in mean scores from 6 to 16 and the decrease in standard deviation after the training revealed a significant increase in teachers’ knowledge, attitudes, and skills. These results suggest that emergency trauma training programs significantly increase teachers’ ability to respond to emergencies and emphasize the importance of sustainable first aid training. Analyses based on gender and branch revealed that post-training test scores were similar and all teachers showed high performance. The findings emphasize the need for systematic and comprehensive emergency trauma training programs for all teachers and the importance of these programs for sustainable health and safety practices.

High performance chemiresistive carbon-nanotube ammonia gas sensor surface modified by tantalum oxide (Ta2O5) metal nanoparticles

High performance chemiresistive carbon-nanotube ammonia gas sensor surface modified by tantalum oxide (Ta2O5) metal nanoparticles

A Systematic Review of Fast, Scalable and Efficient Hardware Implementations of Elliptic Curve Cryptography for Blockchain

Blockchain technology entered the enterprise domain under the name of permissioned blockchains and hybrid or verifiable database systems, as they provide a distributed solution that allows multiple distrusting parties to share common information. One drawback of these systems is the overhead added by the cryptographic functions which impacts the throughput in terms of transactions per second and increases the latency of transaction processing. Many of the cryptographic functions and protocols used in blockchains are based on Elliptic Curve Cryptography (ECC). Unfortunately, ECC operations such as modulo inverse or scalar point multiplication have considerable latency which causes the slowdown of the entire system. In such situations, reconfigurable computing architectures, such as FPGAs, can be used to offload these tasks to overcome the performance loss. This survey analyzes the current state-of-the-art designs and implementations of ECC from a hardware perspective. We use a PRISMA-based approach to filter recent publications and to reduce their number from over 16,000 to only 43 highly relevant designs. In the end, we show that very few designs are able to fulfill all three properties of high performance, scalability, and efficiency.

Multi-Behavior Recommendation with Personalized Directed Acyclic Behavior Graphs

A well-developed recommendation system can not only leverage multi-typed interactions (such as page view, add-to-cart, and purchase) to better identify user preferences, but also demonstrate high performance, low complexity, and strong interpretability. However, many existing solutions for multi-behavior recommendation fall short of intuitive modeling of real-world scenarios, leading to overly complex models with massive parameters and cumbersome components. In particular, they share two critical limitations: (1) Some pioneering models are built upon the strict assumption of cascade effects across behaviors, which contradicts multifarious behavior paths in practical applications. (2) Existing approaches fail to explicitly capture the unique idiosyncrasies of users and even neglect the inherent nature of items involved in the multi-behavior interactions. To this end, we propose a novel Directed Acyclic Graph Convolutional Network (DA-GCN) for the multi-behavior recommendation task. Specifically, we pinpoint the partial order relations within the monotonic behavior chain and extend it to personalized directed acyclic behavior graphs to exploit behavior dependencies. Then, a GCN-based directed edge encoder is employed to distill rich collaborative signals embodied by each directed edge. In light of the information flows over the directed acyclic structure, we propose an attentive aggregation module to gather messages from all potential antecedent behaviors, representing distinct perspectives to understand the terminated behavior. Thus, we obtain comprehensive representations for the follow-up behavior through learnable distributions over its preceding behaviors, explicitly reflecting personalized interactive patterns of users and underlying properties of items simultaneously. Finally, we design a customized multi-task learning objective for flexible joint optimization. Extensive experiments on public benchmarking datasets fully demonstrate the superiority of DA-GCN with significant performance improvement and computational efficiency over a wide range of state-of-the-art methods. Our code is available at https://github.com/xizhu1022/DA-GCN .

Impact of Leadership on Employee Behaviour and Attitude in The Ministry of Finance, Ghana

Purpose: This study investigates the influence of leadership on employee behaviour and attitude in the Ministry of Finance in Ghana. It specifically focusses on how leadership practices affect productivity in a public sector setting. The research investigates the adaptive qualities of leadership styles and their efficacy in meeting the varied demands of employees, based on the principles of Situational Leadership Theory (SLT). Methodology: The study utilises a descriptive survey method. The study population consists of all 628 employees of the Ministry, with a sample size of 246 determined through a multi-stage sampling process. Data is obtained by questionnaires. Findings: The findings suggest that leadership roles and practices have a moderate impact on employee behaviour and productivity. Leaders are seen as successful role models, but they are lacking in providing personalised support and effectively communicating goals. The effectiveness of leadership tactics is not considerably influenced by age. The study's findings suggest that implementing leadership development programs, improving communication methods, and providing individualised support mechanisms will promote organisational efficiency and employee engagement in the Ministry of Finance. Policy Implications and Recommendations: Ministries should develop and implement comprehensive training programmes for leaders that focus on enhancing role modeling, setting high performance expectations, and providing effective intellectual stimulation. Governmental ministries should introduce policies and practices that improve the communication of organizational goals and increase employee involvement in the goal-setting process.