bluuebunny/crossref_metadata_2025 huggingface dataset:
Individual Predictors of Language Treatment Response in Children With Developmental Language Disorder: A Systematic Review
Authors: Ebert Kerry Danahy , Lee HaeJi
Published: July 2024

Purpose:

Treatment response is the degree to which an individual benefits from a treatment. This systematic review sought to identify and synthesize research evidence regarding individual characteristics that predict language treatment response among children with developmental language disorder (DLD).

Method:

To be eligible for inclusion, articles needed to report results of an oral language treatment program in a group of children aged 4–10 years with identified DLD and also include a quantitative analysis of the relation between one or more pretreatment child characteristics and the outcome of language treatment. Seven databases (Cumulated Index to Nursing and Allied Health Literature, Dissertations and Theses Global, Education Resources Information Center, Linguistics and Language Behavior Abstracts, PsycINFO, Medline, and Web of Science) were searched for articles in June and July 2021, with search updates conducted in May 2023. Studies were categorized by the type of treatment provided, and results were synthesized qualitatively.

Results:

The review included 31 studies, 1,551 participants with DLD, and over 300 statistical tests of a predictor's effect on language treatment response. Most studies (
n
= 21) included only monolingual speakers of English, with five studies including bilinguals and five including monolingual speakers of non-English languages. Language treatments targeted word learning in controlled or clinical conditions, grammatical learning in controlled or clinical conditions, or multiple language targets in clinical conditions. Predictors of treatment response are summarized across four categories: cognitive, demographic, pretreatment language levels, and other.

Conclusions:

There were relatively few significant tests of the predictors of language treatment response. A central limitation of the evidence is that most included studies were designed to consider language treatment efficacy, not predictors of treatment response. Increasing research attention to the question of predictors of language treatment response in children with DLD is needed to enhance treatment and optimize outcomes for individual children.

Supplemental Material:

https://doi.org/10.23641/asha.26170006
Data‐sharing strategies in medical consortium based on master‐slave multichain and federated learning
Authors: Kang Bohan , Zhang Ning , Zhu Jianming
Published: July 2024

In order to encourage participants to actively join the data sharing and to meet the distributed structure and privacy requirement in the medical consortium, the data‐sharing strategy based on the master‐slave multichain is presented in this paper. According to the different computing resources and the responsibility of participants, the adaptive Proof of Liveness and Quality consensus and hierarchical federated learning algorithm for master‐slave multichain are proposed. Meanwhile, by quantifying the utility function and the optimization constraint of participants, this paper designs the cooperative incentive mechanism of medical consortium in multi‐leader Stackelberg game to solve the optimal decision and pricing selection of the master‐slave multichain. The simulation experiments show that the proposed methods can decrease the training loss and improve the parameter accuracy by MedMINST datasets, as well as reach the optimal equilibrium in selection and pricing strategy in the system, guaranteeing the fairness of profit distribution for participants in master‐slave multichain.
Efficient knowledge distillation for hybrid models: A vision transformer‐convolutional neural network to convolutional neural network approach for classifying remote sensing images
Authors: Song Huaxiang , Yuan Yuxuan , Ouyang Zhiwei , Yang Yu , Xiang Hui
Published: July 2024

In various fields, knowledge distillation (KD) techniques that combine vision transformers (ViTs) and convolutional neural networks (CNNs) as a hybrid teacher have shown remarkable results in classification. However, in the realm of remote sensing images (RSIs), existing KD research studies are not only scarce but also lack competitiveness. This issue significantly impedes the deployment of the notable advantages of ViTs and CNNs. To tackle this, the authors introduce a novel hybrid‐model KD approach named HMKD‐Net, which comprises a CNN‐ViT ensemble teacher and a CNN student. Contrary to popular opinion, the authors posit that the sparsity in RSI data distribution limits the effectiveness and efficiency of hybrid‐model knowledge transfer. As a solution, a simple yet innovative method to handle variances during the KD phase is suggested, leading to substantial enhancements in the effectiveness and efficiency of hybrid knowledge transfer. The authors assessed the performance of HMKD‐Net on three RSI datasets. The findings indicate that HMKD‐Net significantly outperforms other cutting‐edge methods while maintaining a significantly smaller size. Specifically, HMKD‐Net exceeds other KD‐based methods with a maximum accuracy improvement of 22.8% across various datasets. As ablation experiments indicated, HMKD‐Net has cut down on time expenses by about 80% in the KD process. This research study validates that the hybrid‐model KD technique can be more effective and efficient if the data distribution sparsity in RSIs is well handled.
Fixed‐time prescribed performance control method for nonlinear systems with unknown time‐varying parameters
Authors: Sun Wei , Yuan Junhao , Yang Xiaoqin
Published: July 2024

In this study, it is considered that the question of adaptive tracking control of nonlinear systems containing unknown time‐varying parameters. To optimize the control effect, a fixed‐time control strategy is adopted, in which the upper bound of the settling time is connected with the designed parameters, but not to the initial conditions. In the design, the unknown time‐varying parameters are treated as the multiplication of known and unknown vectors, and the adaptive laws are constructed to estimate the mean value of the components in the unknown ones, which availably solve the difficulty of unknown control gains. Besides, the application of command filtered technique, which combined with the compensation signals containing the adaptive parameters, effectively avoids the “complexity explosion” problem. Further, Lyapunov stability theory verifies that the tracking error can always be kept within the boundaries of the performance functions, and converges to a designated neighbourhood of the origin within a fixed time, beyond that all signals of the closed‐loop system are bounded. Finally, the simulation results prove the effectiveness of the proposed control scheme.
WNet: A dual‐encoded multi‐human parsing network
Authors: Hosen Md Imran , Aydin Tarkan , Islam Md Baharul
Published: July 2024

In recent years, multi‐human parsing has become a focal point in research, yet prevailing methods often rely on intermediate stages and lacking pixel‐level analysis. Moreover, their high computational demands limit real‐world efficiency. To address these challenges and enable real‐time performance, low‐latency end‐to‐end network is proposed. This approach leverages vision transformer and convolutional neural network in a dual‐encoded network, featuring a lightweight Transformer‐based vision encoder) and a convolution encoder based on Darknet. This combination adeptly captures long‐range dependencies and spatial relationships. Incorporating a fuse block enables the seamless merging of features from the encoders. Residual connections in the decoder design amplify information flow. Experimental validation on crowd instance‐level human parsing and look into person datasets showcases the WNet's effectiveness, achieving high‐speed multi‐human parsing at 26.7 frames per second. Ablation studies further underscore WNet's capabilities, emphasizing its efficiency and accuracy in complex multi‐human parsing tasks.
Gap setting control strategy for connected and automated vehicles in freeway lane‐drop bottlenecks
Authors: Chung Sungyong , Ka Dongju , Kim Yongju , Lee Chungwon
Published: July 2024

Commercial automated vehicles equipped with adaptive cruise control (ACC) systems offer multiple gap settings that determine their longitudinal behaviour. This study introduces two novel strategies—inflow control and combined control—that leverage the distinct driving behaviours associated with different gap settings in connected and automated vehicles. These strategies aim to enhance traffic efficiency in freeway lane‐drop bottlenecks, where capacity drops are common, by maintaining bottleneck occupancy at the target level using a proportional‐integral‐derivative controller. Simulation experiments were conducted using VISSIM to validate the proposed strategies. The results from a hypothetical lane‐drop bottleneck indicate that the proposed strategies enhanced both efficiency and safety across all simulated demand levels, with the combined control outperforming inflow control by redistributing the relative positions of vehicles before the mandatory lane changes using a new gap setting. Moreover, the proposed strategies were effective under all the simulated market penetration rates (MPRs), where better performances were demonstrated at higher MPRs. An evaluation of a calibrated real‐world network further demonstrated the potential of recommending gap settings to drivers of ACC‐equipped vehicles using variable message signs to enhance freeway efficiency in the near future.
Two‐stage power control method of rotary power flow controller for flexible interconnection of distribution network
Authors: Shao Chen , Yan Xiangwu , Siddique Abubakar , Aslam Waseem , Jia Jiaoxin , Xie Wenqiang , Alqahtani Salman A. , Alamri Atif M.
Published: July 2024

With the rapid development of active distribution network construction, flexible interconnected distribution networks have become the mainstream power supply structure. To ensure the safe power supply of the distribution system, power control methods suitable for flexible interconnected distribution networks should be further studied. The electromagnetic rotating power flow controller (RPFC) is a feasible solution for power control in distribution networks. This paper first constructs an RPFC steady‐state power decoupling control model based on instantaneous reactive power theory. However, it is difficult to achieve stable power control due to the difficulty of coordinated control of the rotor position angle of the rotating phase transfer transformer. On this basis, the servo motor's two‐stage speed control and speed coordination scheme are used to achieve stable and error‐free control of the two rotor angles, meeting the power regulation requirements of high precision, high reliability, and fast response. A 380 V/40 kVA RPFC prototype and experimental platform were developed, and power regulation and power equalization experiments were conducted. The results indicate that the proposed control scheme can regulate at the second level. Control accuracy is maintained within 4%, showing good dynamic and static performance. This meets the requirements for flexible closed‐loop operation in the interconnected distribution network.
Methodologies for assessing building embodied carbon in a circular economy perspective
Authors: Li Yangxiaoxia , Masera Gabriele
Published: July 2024

The global warming effect represents an increasingly severe environmental issue in the contemporary world, with the construction industry contributing up to 40% of greenhouse gas emissions. Therefore, as advancements in technology have enabled the realization of net-zero energy buildings, there has recently been a growing focus on research primarily aimed at reducing the embodied carbon (EC) of building materials. Assessment and calculation of EC emissions in buildings typically utilize life cycle assessment (LCA) methodologies, evaluating both direct and indirect carbon emissions throughout all stages, from raw material extraction to end-of-life demolition. However, the substantial potential of carbon reduction within the material beyond life cycle stage in the building, which is the decisive process of closing the loop of circular economy, is often overlooked. This paper examines a large number of research cases on EC in buildings over the past 20 years, selectively identifying those including the benefits beyond life cycle of buildings. By conducting a case-by-case analysis of methods and tools employed for the assessment of circular practices, their respective strengths, weaknesses, and variances are evaluated. Following the normalization of EC in phase A-D, a significant research finding revealing that buildings can offset an average of -113.9 kg CO2e/m2 of carbon emissions through recycling and reuse in phase D, accounting for 16.85% of the total EC assessed in LCA. Steel recycling offsets the highest amount of carbon emissions, with an average number of -183.86 kg CO2e/m2. The objective of this paper is to identify the key factors that influence carbon emissions in the circular economy and to identify methods and tools for integrating building materials at the early design stage to minimize EC emissions throughout the entire lifecycle of buildings.
Comparison of future weather files for Brazilian cities
Authors: Vaz Igor Catão Martins , Viana Marina Ribeiro , Ghisi Enedir
Published: July 2024

There is an increasing interest from academia, government, and private companies in future weather generation to predict new climate realities and prepare our assets for resilience and adaptability. In the built environment, practitioners have evolved by building simulation weather files with new tools to implement updated climate change predictions. Thus, this paper focuses on testing and understanding Brazilian climate change using the tool Future Weather Generator. Simulations under different Shared Socioeconomic Pathways were carried out, and future climate variables were discussed. This paper is part of an ongoing effort to understand how future climates may impact buildings, including comfort and energy consumption. In conclusion, the climate in Brazil is expected to become warmer in all cities, although there is a higher dry bulb temperature increase in the centre-west and northern regions. As for wind speed, relative humidity and radiation, different trends were observed in each climate. Brazil must adapt to each new climate reality and focus on efforts to provide adaptability and resilience.
The application and potentialities of textile facade retrofit strategies for energy-efficient and resilient buildings
Authors: Procaccini Giulia , Monticelli Carol
Published: July 2024

In a time when energy efficiency and sustainable development are of utmost importance, retrofitting the current building stock is crucial for reducing ecological impact. The advancement in building technology introduces innovative solutions that challenge traditional practices, paving the way for more sustainable and efficient buildings. Innovative Textile Facade Retrofit Strategies (TFRS) can contribute significantly to the dialogue on retrofitting solutions. TFRS stands at the crossroads of aesthetics, functionality, and environmental consciousness. By exploring the adaptability of textile materials in the retrofitting processes, the paper aligns seamlessly with the broader theme of sustainable practices. It delves into how textile facades, thanks to their intrinsic properties, can offer substantial benefits in terms both of aesthetic appeal and thermal performance, aligning with the objectives of sustainable buildings. This paper presents a novel framework for classifying Textile Facade Retrofit Strategies into three macro categories: Replace, Add and Wrap It. These encompass nine innovative strategies, each suited to different retrofit scenarios, and are assessed for their benefits and applications. The strategies vary in operation, involving facade part replacement, element addition, or complete encasement. The discussion highlights promising textile solutions, emphasizing their contribution in the resilience and adaptation of existing building facades. The results point toward a new paradigm in facade retrofitting, where flexibility, efficiency, and aesthetics coalesce to create more sustainable urban environments.
An overview of Artificial Intelligence applications to electrical power systems and DC microgrids
Authors: Rajitha Morampudi , Raghu Ram A.
Published: July 2024

Microgrids are composed of distributed energy resources such as energy storage devices, photovoltaic (PV) systems, backup generators, and wind energy conversion systems. Because renewable energy sources are intermittent, modern power networks must overcome the stochastic problem of increasing the penetration of renewable energy, which necessitates precise demand forecasting to deliver the best possible power supply. Technologies based on artificial intelligence (AI) have become a viable means of implementing and optimizing microgrid energy management. Owing to the sporadic nature of renewable energy sources, artificial intelligence offers a range of solutions based on the growth in sensor data and compute capacity to create sustainable and dependable power. Artificial intelligence (AI) techniques continue to evolve in DC Microgrids with the aim of perfect voltage profile, minimum distribution losses, optimal schedule of power, planning and controlling of grid parameters and lowering unit price. AI methods can improve DC Micro grid performance by monitoring and controlling the grid parameters by reducing the computational and processing time. This paper offers a comprehensive summary of some of the most recent research on artificial intelligence techniques used to DC Micro grids and electrical power system networks.
Enhancing Power Quality in Integrated PV Systems and DFIG Systems through MPPT and Fuzzy logic controller for Grid Systems
Authors: Anjum S. Vasiha , Suryanarayanareddy V. , Leela Mounika Mallela , Yamini Nellore , Sai Sandeep M.
Published: July 2024

This article investigates incorporating solar energy into a grid connected system or process— Photo-Voltaic (PV) and Double Fed Induction Generator ( DFIG) systems aimed at improving energy efficiency. Because of its lower efficiency, successfully using the power from solar PV connected to the utility grid is a challenging operation. The hybrid system operation is optimized using a Fuzzy Logic Controller (FLC), which effectively manages the variability and intermittency of renewable sources. The FLC dynamically adjusts parameters to ensure seamless grid integration and power quality enhancements. The study compares the FLC's performance with the Incremental Conductance method, evaluating their ability to manage the hybrid system's components under diverse environmental conditions. Key focus areas include voltage regulation, frequency stability, and harmonic distortion mitigation. A power point tracking controller's primary function is to increase or maximize solar systems' power generation. This proposed method includes a presentation of a fuzzy controller with Maximum power point tracking (MPPT) for a 10 kW-PV grid connected systems, highlighting its advantages over the Incremental Conductance method (Inc- Con). The output results are verified and validated with MATLAB Simulink platform.
DSM Solutions for Distribution Networks with Electric Vehicle Integration
Authors: Badugu Jayababu , Manikanta A. , Hemanth Kumar A. , Sai Prasanthi D. Naga , Krupakar M.
Published: July 2024

Electric vehicles (EVs) are known for being zero emissions and environmentally friendly, making them extremely popular for transportation. In general, electric vehicles are often charged in residential areas. Due to this uncoordinated charging of electric vehicles, the low-voltage distribution network must face many challenges to maintain the new load conditions without blackouts and voltage fluctuations. Failure to properly measure and address these impacts of EVs on the distribution network will result in replacement and reinforcement of the distribution system, which is costly and time-consuming. This study introduces a Demand Side Management (DSM) approach aimed at minimizing overhead in residential distribution systems with electric vehicle (EV) integration. DSM emerges as the optimal strategy for mitigating severe power spikes within the distribution network. The study compares the effects of uncoordinated planned EV loads with those achieved through the implementation of the DSM strategy in a residential distribution system. The analysis encompasses the system's stability and end-user satisfaction as key parameters
Development of an Artificial Intelligent Firefighting Robot and Experiment Investigation on Fire Scene Patrol
Authors: Sivakumar M. , Kanakarajan P. , Dharun S. , Kirubakaran R. , Girivasan M.
Published: July 2024

Nowadays, due to human irresponsibility, unpredictable climate fluctuations, and household and industrial settings, fire incidents happen regularly. This study describes a firefighting robot that uses artificial intelligence to identify fire incidents and have capability to put out a fire remotely, minimising the risk to fire fighters. The firefighting robot moves according to a combination of user supervision and sensor-based inputs. Software includes integrated tracking, flame detection, obstacle avoidance, and fire extinguishing. The direction and amount of water sprayed can be adjusted by the servo motor that is attached to the firefighting hose. In the final phase, a simulated fire trial environment was used to assess the firefighting robot's performance. During an autonomous inspection of the fire affected area, the firefighting robot has the ability to identify flame in real time, initiate the automatic fire extinguishing by the fire extinguishing system, and manage the fire during its initial stages.
Life Guardian: Enhancing Health Awareness through Sensor Fusion
Authors: Satyanarayana Salava V. , Madhavi Pillalamarri , Arthi G. , Sathwika K. , Suman L. , Abdul Adil Shaik
Published: July 2024

This ground-breaking technology provides a health monitoring system that smoothly incorporates temperature, infrared (IR), heart rate, and SpO2 sensors. By combining these sensors, the initiative offers real-time, non-invasive tracking of critical physiological indicators, enabling proactive health management and early detection of possible concerns. With data representing body temperature, blood pressure, cardiovascular activity, and oxygen saturation levels, sensor fusion technology users can comprehensively understand their health. This user-friendly technology gives people the power to decide for themselves what is best for their health. It has the potential to revolutionize telemedicine, remote patient monitoring, and early warning systems in the healthcare industry. This study not only demonstrates the potential of sensor fusion for health monitoring, but it also can revolutionize personal healthcare and promote a society that is more concerned with its overall health. Our application is being developed to be operated by an authority that will have access to all of the data about every individual user's reading. In case of an abnormality, the application will offer an indication in addition to an image of the affected person. To capture visuals of the user in unusual circumstances, we are deploying a pie camera.
Evaluation of Regional Wall Motion Abnormalities with Echocardiography in the Emergency Department
Authors: Karancı Yusuf , Bedel Cihan , Selvi Fatih , Zortuk Ökkeş
Published: July 2024

Introduction Acute coronary syndrome (ACS) is a major cardiovascular disease, particularly in cases where standard electrocardiogram findings are equivocal. Focused cardiac ultrasound (FOCUS) has become increasingly accepted as a tool in emergency medicine. The primary objective of this study was to evaluate the accuracy, sensitivity, and specificity of FOCUS in detecting regional wall motion abnormalities (RWMA) compared with standard echocardiography (ECHO).

Materials and Methods This prospective observational study included 91 patients who presented to the emergency department between June 1, 2023, and November 30, 2023. Senior emergency physicians performed FOCUS examinations, which were performed by an emergency assistant or specialist who works in the emergency department, has at least 2 years of experience in ultrasonography (USG), and has basic USG and advanced USG certificates. The examinations assessed the presence of RWMA in each patient's left ventricle.

Results All 91 patients were included in the study for comparison with formal ECHO. The mean age was 58, and 32% of patients were female. Compared with the criterion standard of formal ECHO, the sensitivity of FOCUS performed by emergency physicians for detecting RWMA was 85% (95% confidence interval [CI], 73–92), the specificity was 53% (95% CI, 36–69), and the overall accuracy was 74% (95% CI, 64–82).

Conclusion Our study demonstrates the potential utility of FOCUS performed by emergency physicians in detecting RWMA in patients with high suspicion of ACS.
Multivariate Analysis of Factors Associated with Feeding Mother's Own Milk at Discharge in Preterm Infants: A Retrospective Cohort Study
Authors: Reis Jordan D. , Sánchez-Rosado Mariela , Mathai Daizy , Kiefaber Isabelle , Brown L Steven , Lair Cheryl S. , Nelson David B. , Burchfield Patti , Brion Luc P.
Published: July 2024

Objective This study aimed to develop a predictive model of feeding mother's own milk (MOM) at discharge using social determinants of health (SDOH), maternal and neonatal factors after deliveries at <33 weeks of gestational age (GA), or birth weight <1,500 g.

Study Design Secondary analysis of a retrospective cohort in an inner-city hospital before (Epoch-1, 2018–2019) and after (Epoch-2, 2020–2021) implementing a donor human milk (DHM) program.

Results Among 986 neonates, 495 were born in Epoch-1 (320 Hispanic White, 142 Non-Hispanic Black, and 33 Other) and 491 in Epoch-2 (327, 137, and 27, respectively). Feeding any MOM was less frequent in infants of non-Hispanic Black mothers than in those of Hispanic mothers (p < 0.05) but did not change with epoch (p = 0.46). Among infants who received any MOM, continued feeding MOM to the time of discharge was less frequent in infants of non-Hispanic Black mothers versus those of Hispanic mothers, 94/237 (40%) versus 339/595 (57%; p < 0.05), respectively. In multivariate analysis including SDOH and maternal variables, the odds of feeding MOM at discharge were lower with SDOH including neighborhoods with higher poverty levels, multiparity, substance use disorder, non-Hispanic Black versus Hispanic and young maternal age and increased with GA but did not change after implementing DHM. The predictive model including SDOH, maternal and early neonatal variables had good discrimination (area under the curve 0.85) and calibration and was internally validated. It showed the odds of feeding MOM at discharge were lower in infants of non-Hispanic Black mothers and with feeding DHM, higher need for respiratory support and later initiation of feeding MOM.

Conclusion Feeding MOM at discharge was associated with SDOH, and maternal and neonatal factors but did not change after implementing DHM. Disparity in feeding MOM at discharge was explained by less frequent initiation and shorter duration of feeding MOM but not by later initiation of feeding MOM.

Key Points
A Comparison of Commercially Available Digital Microscopes for Their Use in Bench-Model Simulation of Microsurgery
Authors: Awad Laura , Abdi Zakee , Langridge Benjamin J. , Karoshi Akul , Butler Peter E. M.
Published: July 2024

Background Surgical education has seen a transition in the delivery of training, with increased use of online platforms to facilitate remote learning. Simulation training can increase access to education and reduce cost implications, while reducing patient risk. This study aims to compare commercially available digital microscopes, alongside a standard binocular surgical microscope, and determine whether they can be used as an alternative tool for remote microsurgery simulation.

Methods Data were collected for a total of four microscopes, including three commercially available digital microscopes, smartphone, and a binocular table microscope. Product characteristics were collated, and a subjective assessment was conducted using an 11-criteria questionnaire, graded with a 5-point scale. Results of digital microscopes were compared with the table binocular microscope.

The Kruskal–Wallis test was used to compare the performance of digital microscopes to the standard binocular microscope

Results The questionnaire was completed by 31 participants: two consultants, nine surgical registrars, fourteen junior trainees, and six medical students. Digital microscopes were found to be significantly more affordable and convenient for trainees; however, the cost of the smartphone was significant. Overall, the Pancellant Digital Microscope performed the poorest, with trainees commenting on its unsuitability for surgical practice; the Plugable USB Digital Microscope (PLDM) was rated overall most like the binocular table microscope. The Depth of field was shallow in all digital microscopes.

Conclusion With the increasing role of remote learning and simulation training in surgical education, the PLDM can provide a cheaper, more accessible alternative for junior trainees, in their pursuit of microsurgical skill acquisition.
Establishing Expectancy Values for Fibrin Monomer in Uncomplicated Pregnancy
Authors: Seidel Holger , Duncklenberg Melina , Hertfelder Hans-Jörg , Gnida Christine , Westhofen Philipp , Stremlau Anna , Feriel Joffrey , Depasse François , McRae Hannah L. , Kruppenbacher Johannes Philipp
Published: July 2024

Background During pregnancy, a physiological increase of molecular activation markers (MAM) of hemostasis such as prothrombin fragments 1 + 2, thrombin–antithrombin complex, and D-dimers (DD) occurs. Therefore, monitoring MAM levels during pregnancy to evaluate the risk of venous thromboembolism (VTE) may be unreliable; nevertheless, DD analysis in pregnancy is widely performed. In contrast to DD, fibrin monomer (FM) levels have been reported to remain stable during pregnancy.

Objectives The main aim of this study was to define the expected range for FM levels in pregnant outpatients. In addition, we examined the impact of the individual VTE risk, as calculated by the pregnancy risk score of the Royal College of Obstetricians and Gynaecologists (RCOG), as well as that of antithrombotic treatment on FM levels.

Methods A total of 342 pregnant women seen at our hemostasis unit were included throughout 350 pregnancies in 899 samples.

Results Low-risk thrombophilia, but not the RCOG score itself, was found to influence all MAM levels, whereas antithrombotic treatment had only an impact on DD. For FM, a reference range could be calculated irrespective of the pregnancy term, in contrast to other MAMs, which fluctuated throughout pregnancy.

Conclusions Our findings suggest a stronger impact of inherited thrombophilia on hemostasis activity during pregnancy as compared with acquired or other predisposing thrombophilic risk factors. FM levels showed a marginal increase during pregnancy in contrast to other MAM and remain a potential candidate to improve the laboratory assessment of VTE risk during pregnancy. Further prospective studies in pregnant patients with suspicion of VTE are needed.
Ethical leadership, internal job satisfaction and OCB: the moderating role of leader empathy in emerging industries
Authors: Li Qin
Published: July 2024

Leadership with ethical values can generally elicit high levels of employee input behavior. This is particularly important in strategic emerging industries, where job satisfaction among research and development (R&D) personnel plays a crucial role as a primary driver of innovation. While scholars have emphasized the significance of internal work value orientation in recent years, the previous literature has mainly focused on leadership and employee behavior, and few studies have explored spontaneous organizational citizenship behavior (OCB). Therefore, this study seeks to investigate the correlation between ethical leadership (EL) and OCB and to consider the moderating role of leader empathy (LE) as well as the mediating role of internal job satisfaction (IJS). The data for this research were collected from 248 R&D personnel employed in companies within China’s emerging industry sector. The analysis was conducted using partial least squares path modeling, and the moderating effect was examined using Hayes’ PROCESS macro. The results validate the idea that IJS serves as a positive mediator of the relationship between EL and OCB. Furthermore, LE plays a significant moderating role in the relationship between IJS and OCB.
Fabrication of high-quality Al-polar and N-polar AlN templates through self-forming tiny-pit layers and polarity inversion
Authors: Okada Narihito , Hidaka Ryota , Kowaki Taketo , Saito Takahiro , Sugawara Yoshihiro , Yokoe Daisaku , Yao Yongzhao , Ishikawa Yukari , Kurai Satoshi , Yamada Yoichi , Tadatomo Kazuyuki
Published: July 2024

A fabrication technique for high-quality AlN templates using only metalorganic vapor phase epitaxy, which involves a tiny-pit AlN layer optimized by changing the growth temperature and V/III ratio, is proposed. Combining the tiny-pit AlN layer with the main AlN layer can be beneficial for achieving epitaxial lateral overgrowth and reducing threading dislocation density (TDD). According to transmission electron microscopy observations, the TDD in the AlN layer on the tiny-pit layer was 7.3 × 109 cm–2, and the TDD was further reduced to 2.6 × 108 cm–2 by adopting multiple tiny-pit layers. Tiny voids were observed at the interface between the tiny-pit AlN and main AlN layers, and the radius of curvature of the AlN layer also increased compared with that for a conventional AlN template by reducing stress in the AlN layer. In addition, the N-polar AlN layer was grown using Al-polar tiny-pit AlN layers through polarity inversion on a sapphire substrate with an offcut angle of 2.0°. Consequently, it was found that the Al-polar tiny-pit AlN is highly effective in improving the crystalline quality of the N-polar AlN layer. The surface flatness of the N-polar AlN layer with the tiny-pit layer and polarity inversion retained the conventional N-polar AlN template.
X-point radiator and power exhaust control in configurations with multiple X-points in TCV
Authors: Gorno S. , Février O. , Theiler C. , Ewalds T. , Felici F. , Lunt T. , Merle A. , Bagnato F. , Colandrea C. , Degrave J. , Ducker R. , Durr-Legoupil-Nicoud G. , Duval B. P. , Lee K. , Martinelli L. , Oliveira D. S. , Perek A. , Reimerdes H. , Simons L. , Sun G. , Tracey B. , Wischmeier M. , Wüthrich C. ,   TCV Team,   EUROfusion Tokamak Exploitation Team
Published: July 2024

Novel power exhaust solutions are being developed to address the challenge of integrating a high performance fusion core plasma with a well-protected divertor, if the single null configuration does not scale to a reactor device. This work aims to elucidate the physics mechanisms responsible for the reduction in peak target heat flux in configurations with multiple X-points. Experimental studies on tokamak à configuration variable in the Snowflake Minus configuration are extended to a novel configuration with three nearby divertor X-points, termed a Jellyfish, allowing us to enhance the expected effects of an additional divertor X-point. These studies are complemented by simplified 1D scrape-off layer (SOL) modeling with the SPLEND1D code and by interpretative modeling with the edge transport code EMC3-EIRENE applied to the Snowflake Minus, to further elucidate some of the key underlying processes. We find that configurations with multiple nearby X-points, and increased near-SOL connection length, exhibit reductions in peak target heat flux and an earlier detachment onset compared to a reference single null configuration, consistent with expectations from SPLEND1D. A strong correlation is experimentally observed between the radially localized radiated power and connection length. While this does not necessarily map to higher total divertor radiative losses for configurations with multiple X-points, it can, at least, provide some control over the radial position of the spatial radiation distribution. Experiments are shown to exhibit radial striations in the emissivity of multiple spectral lines in the inter-null region in these configurations. Although comparisons with EMC3-EIRENE simulations support enhanced cross field transport in the inter-null region, additional transport physics is required in the model to obtain a quantitative match with experiment. No significant differences in divertor-core compatibility are attributed to the presence of additional divertor X-points. However, impurity source optimization is required in such geometries to ensure a low core impurity content is maintained.
The flow interference investigation of multi-square prisms under fluid–structure interaction. I. Proximal wake characteristics of tandem square prisms
Authors: Chen Zengshun , Guan Tengda , Zhang Likai , Li Sunwei , Kim Bubryur , Fu Yunfei , Li Cruz Y. , Zhang Xuelin
Published: July 2024

This study investigates the aerodynamic characteristics and interference effect of tandem square prisms in fluid–structure interaction. Using large eddy simulation, three-dimensional tandem square prisms are analyzed under different spacing and vibration. Based on the mean pressure coefficient and flow field phenomenology, the specific reasons and underlying mechanisms of the changes are discussed. The results show that the structural vibration accelerates the curling of the shear layer around the upstream structure, increases the vortex shedding frequency of the structure, and reduces the distance between the vortices. It also amplifies the transverse correlation between vortex structures and intensifies the influence of the gap flow on the downstream structure. The increased spacing between the tandem square prisms changes the flow mechanism of the wake separated from the upstream structure, leading to a more uniform and regular streamlined pattern. Simultaneously, a flow field phenomenon is observed, such as an early rolled-up shear layer, turbulence enhancement, preliminary vortex formation, weakened downwash flow, and the change of field flow due to the vibration. This study is expected to deepen the understanding of flow interference investigation between tandem square prisms in the fluid–structure interaction field.
Temperature-responsive microcapsules alleviating the hazards of thermal runaway for lithium-ion batteries
Authors: Tong Jingjing , Peng Yong , Liu Jie , Wang Li , Hou Bowen , Feng Xuning , Ouyang Minggao
Published: July 2024

Safety problems hinder the large-scale application of high-specific energy battery system. In this paper, a type of temperature thermo-responsive microcapsules to enhance the safety performance of lithium-ion batteries is proposed. The microcapsule is manufactured by encapsulating hydrates with melamine urea formaldehyde, and the outer shell will automatically rupture and release hydrates at ∼100 °C. It can react with the anode in advance and block reaction between the anode and the electrolyte, thereby reducing the generation of reductive gas and lowering down gas crosstalk. The thermos-responsive microcapsules are prepared by in situ polymerization, and the addition of the microcapsules could effectively reduce the reaction enthalpy by differential scanning calorimetry. Through a adiabatic accelerated calorimetry test, only 0.25 g microcapsules can increase the thermal runaway trigger temperature by 16.2 °C and reduce the maximum temperature by 117.5 °C. This innovative approach enhances the safety of high specific energy lithium-ion battery systems, providing extended thermal-runaway warning time and minimizing the hazard caused by high temperatures.
Development of a gyrokinetic-MHD energetic particle simulation code. I. MHD version
Authors: Jiang P. Y. , Liu Z. Y. , Liu S. Y. , Bao J. , Fu G. Y.
Published: July 2024

A new magnetohydrodynamics (MHD) code based on initial value approach, GMEC_I, has been developed for simulating various MHD physics in tokamak plasmas, as the MHD foundation of the gyrokinetic-MHD energetic particle simulation code (GMEC) family. GMEC_I solves multi-level reduced-MHD models that form a hierarchy of physics complexity, which provide conveniences for the cross-code verification and the identification of key physics effect in tokamak geometry. The field-aligned coordinates are used to represent mode structure efficiently. High-order finite difference methods are used for spatial discretization. The shifted metric methods are used for numerical stability. The discrete expansion forms of physics equations in the code are generated symbolically using the compile-time symbolic solver, which is specifically developed to reduce the complexity of the high-order finite difference form of the MHD equations. Advanced computational techniques have been implemented for optimizing memory access and code parallelization that show a good efficiency using both thread building block and message passing interface. Benchmarks between GMEC_I and the eigenvalue code MAS are presented for ballooning modes without and with diamagnetic drift effects, and tearing modes, which show excellent agreements.
Development of a gyrokinetic-MHD energetic particle simulation code. II. Linear simulations of Alfvén eigenmodes driven by energetic particles
Authors: Liu Z. Y. , Jiang P. Y. , Liu S. Y. , Zhang L. L. , Fu G. Y.
Published: July 2024

We have developed a hybrid code GMEC: Gyro-kinetic Magnetohydrodynamics (MHD) Energetic-particle Code that can numerically simulate energetic particle-driven Alfvén eigenmodes and energetic particle transport in tokamak plasmas. In order to resolve the Alfvén eigenmodes with high toroidal numbers effectively, the field-aligned coordinates and meshes are adopted. The extended MHD equations are solved with the five-point finite difference method and the fourth-order Runge–Kutta method. The gyrokinetic equations are solved by particle-in-cell method for the perturbed energetic particle pressures that are coupled into the MHD equations. Up to now, a simplified version of the hybrid code has been completed with several successful verifications, including linear simulations of toroidal Alfvén eigenmodes and reversed shear Alfvén eigenmodes.
Accelerating structure search using atomistic graph-based classifiers
Authors: Slavensky Andreas Møller , Hammer Bjørk
Published: July 2024

We introduce an atomistic classifier based on a combination of spectral graph theory and a Voronoi tessellation method. This classifier allows for the discrimination between structures from different minima of a potential energy surface, making it a useful tool for sorting through large datasets of atomic systems. We incorporate the classifier as a filtering method in the Global Optimization with First-principles Energy Expressions (GOFEE) algorithm. Here, it is used to filter out structures from exploited regions of the potential energy landscape, whereby the risk of stagnation during the searches is lowered. We demonstrate the usefulness of the classifier by solving the global optimization problem of two-dimensional pyroxene, three-dimensional olivine, Au12, and Lennard-Jones LJ55 and LJ75 nanoparticles.
Efficient all-electron hybrid density functionals for atomistic simulations beyond 10 000 atoms
Authors: Kokott Sebastian , Merz Florian , Yao Yi , Carbogno Christian , Rossi Mariana , Havu Ville , Rampp Markus , Scheffler Matthias , Blum Volker
Published: July 2024

Hybrid density functional approximations (DFAs) offer compelling accuracy for ab initio electronic-structure simulations of molecules, nanosystems, and bulk materials, addressing some deficiencies of computationally cheaper, frequently used semilocal DFAs. However, the computational bottleneck of hybrid DFAs is the evaluation of the non-local exact exchange contribution, which is the limiting factor for the application of the method for large-scale simulations. In this work, we present a drastically optimized resolution-of-identity-based real-space implementation of the exact exchange evaluation for both non-periodic and periodic boundary conditions in the all-electron code FHI-aims, targeting high-performance central processing unit (CPU) compute clusters. The introduction of several new refined message passing interface (MPI) parallelization layers and shared memory arrays according to the MPI-3 standard were the key components of the optimization. We demonstrate significant improvements of memory and performance efficiency, scalability, and workload distribution, extending the reach of hybrid DFAs to simulation sizes beyond ten thousand atoms. In addition, we also compare the runtime performance of the PBE, HSE06, and PBE0 functionals. As a necessary byproduct of this work, other code parts in FHI-aims have been optimized as well, e.g., the computation of the Hartree potential and the evaluation of the force and stress components. We benchmark the performance and scaling of the hybrid DFA-based simulations for a broad range of chemical systems, including hybrid organic–inorganic perovskites, organic crystals, and ice crystals with up to 30 576 atoms (101 920 electrons described by 244 608 basis functions).
A 4–8 GHz kinetic inductance traveling-wave parametric amplifier using four-wave mixing with near quantum-limited noise performance
Authors: Faramarzi Farzad , Stephenson Ryan , Sypkens Sasha , Eom Byeong H. , LeDuc Henry , Day Peter
Published: July 2024

Kinetic inductance traveling-wave parametric amplifiers (KI-TWPAs) have a wide instantaneous bandwidth with a near quantum-limited noise performance and a relatively high dynamic range. Because of this, they are suitable readout devices for cryogenic detectors and superconducting qubits and have a variety of applications in quantum sensing. This work discusses the design, fabrication, and performance of a KI-TWPA based on four-wave mixing in a NbTiN microstrip transmission line. This device amplifies a signal band from 4 to 8 GHz without contamination from image tones, which are produced in a separate higher frequency band. The 4–8 GHz band is commonly used to read out cryogenic detectors, such as microwave kinetic inductance detectors and Josephson junction-based qubits. We report a measured maximum gain of over 20 dB using four-wave mixing with a 1 dB gain compression point of −58 dBm at 15 dB of gain over that band. The bandwidth and peak gain are tunable by adjusting the pump-tone frequency and power. Using a Y-factor method, we measure an amplifier-added noise of 0.5 ≤ Nadded ≤ 1.5 photons from 4.5 to 8 GHz.
Carrier confinement and alloy disorder exacerbate Auger–Meitner recombination in AlGaN ultraviolet light-emitting diodes
Authors: Pant Nick , Bushick Kyle , McAllister Andrew , Lee Woncheol , Van de Walle Chris G. , Kioupakis Emmanouil
Published: July 2024

The quantum efficiency of AlGaN ultraviolet light-emitting diodes declines (droops) at increasing operating powers due to Auger–Meitner recombination (AMR). Using first-principles density-functional theory, we show that indirect AMR mediated by electron–phonon coupling and alloy disorder can induce bulk C coefficients as large as ∼10−31 cm6/s. Furthermore, we find that the confinement of carriers by polarization fields within quantum wells severely relaxes crystal-momentum conservation, which exacerbates the rate of AMR over radiative recombination by an order of magnitude relative to the bulk. This results in a striking decrease in quantum efficiency at high power. Suppressing polarization fields and jointly increasing the well width would greatly mitigate AMR and efficiency droop.