bluuebunny/crossref_metadata_2025_split huggingface dataset:
Test–Retest Reliability of Behavioral Assays of Feedforward and Feedback Auditory–Motor Control of Voice and Articulation
Authors: Kapsner-Smith Mara R. , Abur Defne , Eadie Tanya L. , Stepp Cara E. 
Published: November 2023

Purpose:
Behavioral assays of feedforward and feedback auditory–motor control of voice and articulation frequently are used to make inferences about underlying neural mechanisms and to study speech development and disorders. However, no studies have examined the test–retest reliability of such measures, which is critical for rigorous study of auditory–motor control. Thus, the purpose of the present study was to assess the reliability of assays of feedforward and feedback control in voice versus articulation domains.

Method:

Twenty-eight participants (14 cisgender women, 12 cisgender men, one transgender man, one transmasculine/nonbinary) who denied any history of speech, hearing, or neurological impairment were measured for responses to predictable versus unexpected auditory feedback perturbations of vocal (fundamental frequency,
f
o
) and articulatory (first formant,
F
1
) acoustic parameters twice, with 3–6 weeks between sessions. Reliability was measured with intraclass correlations.

Results:

Opposite patterns of reliability were observed for
f
o
and
F
1
;
f
o
reflexive responses showed good reliability and
f
o
adaptive responses showed poor reliability, whereas
F
1
reflexive responses showed poor reliability and
F
1
adaptive responses showed moderate reliability. However, a criterion-referenced categorical measurement of
f
o
adaptive responses as typical versus atypical showed substantial test–retest agreement.

Conclusions:

Individual responses to some behavioral assays of auditory–motor control of speech should be interpreted with caution, which has implications for several fields of research. Additional research is needed to establish reliable criterion-referenced measures of
F
1
adaptive responses as well as
f
o
and
F
1
reflexive responses. Furthermore, the opposite patterns of test–retest reliability observed for voice versus articulation add to growing evidence for differences in underlying neural control mechanisms.
Do Adult Naïve Listeners Perceive Differences in Speech Before and After Therapy for Cleft Palate Speech Disorders? A Reliability Study of Perceptual Speech Ratings
Authors: Alighieri Cassandra , Meerschaert Silke , Van Lierde Kristiane 
Published: November 2023

Purpose:
This study compared the interrater reliability of adult naïve listeners' perceptual assessments of different speech variables in children with a cleft palate with or without a cleft lip (CP ± L). In addition, the study investigated whether the listeners were able to perceive differences in these speech variables before and after speech therapy for cleft palate speech disorders.

Method:
Thirty-four speech samples of 14 children with a CP ± L (14 samples collected immediately before 10 hr of speech intervention, 14 samples collected immediately after speech intervention, and six randomly selected samples that were duplicated to assess intrarater reliability) were perceptually assessed by 26 adult naïve listeners. The listening panel consisted of nine men and 17 women (age range: 18–51 years). The speech variables included speech understandability, speech acceptability, hypernasality, hyponasality, nasal airflow, and articulation, which were assessed on a visual analog scale. Furthermore, the need for speech therapy was assessed.

Results:
Good to very good interrater reliability was observed for the naïve listeners' ratings of all speech variables. A significant time effect was found for the pre- and postevolution of the speech variables “speech understandability,” “speech acceptability,” “nasal airflow,” and “articulation.” This time effect indicates an improvement of these variables postintervention. According to the naïve listeners, children were less in need of additional speech therapy after the 10-hr intervention period compared to assessments before this intervention period.

Conclusions:
Adult naïve listeners perceptually identified an improvement in different speech variables after 10 hr of cleft palate speech therapy. These findings confirm previous assessments of expert speech-language pathologists and suggest that speech improvements after cleft palate speech therapy can also be perceived by communication partners outside the therapy room. Perceptual ratings of naïve listeners can, thus, be used to add life-situation significance to the assessments of experts. Future research could include both expert raters and caregivers or relatives of children with a CP ± L in listening panels, as previous knowledge on craniofacial anomalies may lead to different results.
Jet Lag and COVID-19: Extra Challenges for Athletes during the Tokyo 2020 Olympic Games
Authors: Ishikura Isabela Antunes , Xerfan Ellen Maria Sampaio , Porcacchia Allan Saj , Tufik Sergio , Andersen Monica Levy 
Published: November 2023

AbstractParticipating in the Tokyo 2020 Olympic Games demanded great efforts and had become extremely challenging compared with previous competitions. In addition to the physical performance of each modality, athletes had to deal with the coronavirus disease 2019 (COVID-19) pandemic and jet lag. The present manuscript pointed out negative factors that encompass the COVID-19 pandemic and the features brought out by the jet lag experienced by the athletes of this last Olympics. The influences of the pandemic and the procedures adopted to reduce transmission risk of the virus may have amplified the weight of jet lag for the athletes of Tokyo 2020 Olympic Games, even more considering the occurrence of this event in the far east of the globe.
Intersectionality and Its Relevance in the Context of Aboriginal People with Brain Injury in Australia
Authors: Armstrong Elizabeth , Colegate Kerri , Papertalk Lenny , Crowe Stuart , McAllister Meaghan , Hersh Deborah , Ciccone Natalie , Godecke Erin , Katzenellenbogen Judith , Coffin Juli 
Published: November 2023

AbstractIn this article, we explore the benefits of recognizing the impact of intersectionality on access to, and provision of, brain injury care in a First Nations context. While disadvantage and discrimination are often associated with the intersection of culture, gender, disability, and socioeconomic disadvantage, it is only when these factors are explored together that clinicians can really understand what people need to recover and thrive following acquired brain injury. In this article, we challenge speech-language pathologists to examine their own practices, to look beyond Western models of health and constraints of many current institutional models of care and ways of framing research, to acknowledge historical and ongoing colonizing influences, and to engage with community-led solutions. We provide a model of Aboriginal-led care, where intersection of discrimination and marginalization is minimized and the multiple components of the individual, carers/communication partners, and the environment become empowering factors instead.
Characteristics of Patients with Subjective Sleep Problems after Cognitive Behavioral Therapy for Insomnia: Secondary Analyses of a Randomized Controlled Trial
Authors: Sandlund Christina , Westman Jeanette , Norell-Clarke Annika 
Published: November 2023

Abstract
Objective Cognitive behavioral therapy for insomnia (CBT-I) is the first-line treatment for insomnia, but half of the patients do not reach remission. This study aimed to explore subjective remission by investigating the characteristics of patients who reported lingering sleep problems after CBT-I.
Methods Secondary analyses of a randomized controlled trial of group CBT-I in 72 primary care patients with insomnia disorder. Sociodemographic characteristics and outcomes (insomnia severity, sleep variables, hypnotics use, fatigue, depressive symptoms, and dysfunctional beliefs/attitudes), including baseline data and symptom change, were investigated in relation to patients' posttreatment response to the yes-or-no question “Would you say that you have sleep problems?”
Results A total of 56.9% of patients reported sleep problems after CBT-I. At baseline, they had worse depressive symptoms (14.9 (SD 7.5) vs. 10.2 (SD 5.9), p = 0.006) and more awakenings (2.6 (SD 1.5) vs. 1.8 (SD 1.3), p = 0.034) than those in subjective remission from sleep problems. Patients in the non-remission and remission groups showed similar improvements in sleep, fatigue, and depressive symptoms, but patients in the non-remission group had improved less in insomnia severity, dysfunctional beliefs/attitudes about sleep, and hypnotic use. In patients with more pronounced depressive symptoms before CBT-I, change in depressive symptoms during treatment partially explained subjective remission from sleep problems.
Discussion More severe depressive symptoms prior to CBT-I and less improvements in depressive symptoms during treatment predicted remaining subjective sleep problems after treatment. These findings highlight the importance of assessing depressive symptoms in primary care patients with insomnia, as patients with pronounced depressive symptoms may need tailored treatment.
The mediating role of job satisfaction in the stressor–strain relationship among Chinese government employees
Authors: Li Yong , Yang Fengyin , Zhang Wei , Zhang Zhao 
Published: November 2023

AbstractIn recent years, China has seen a sharp increase in job stress-related suicides among government employees. Existing research already identifies a stressor–strain relationship, although more studies are warranted to investigate how this relationship is played out among Chinese government employees. The Healthy Work Organization model posits that work adjustment (such as job satisfaction) can mediate the stressor–strain relationship. The purpose of this study is to examine the role of job satisfaction (as a mediator variable) in the relationship between job stressors and job strain among Chinese government employees. Convenience sampling was used to collect data among 505 government employees in Hangzhou, China. Online and face-to-face survey data were collected and analyzed in Mplus Version 8.3. Mediation analyses using the bootstrapping method revealed that job satisfaction fully mediated the effects of relationships and recognition and partially mediated the effect of home-work balance. However, it did not mediate the effect of personal responsibility. Given these findings, Chinese government agencies can boost job satisfaction by providing more supervisory support and career development opportunities and by reducing the interference of work with their employees’ family life. These moves will likely reduce job stress-related mental and physical health symptoms.
Looking for optimal concentric ring electrodes: influence of design aspects on their performance
Authors: Garcia-Casado Javier , Ye-Lin Yiyao , Prats-Boluda Gema , Makeyev Oleksandr 
Published: November 2023

Abstract
Concentric ring electrodes (CREs) allow improved spatial resolution, reduced crosstalk and interference, and increased bandwidth in the sensing of bioelectrical activity. A wide variety of designs have been used, but their selection is rarely well-founded. The aim of this work is to assess the implications of aspects of CRE design such as the distance between poles, their width and their maximum diameter on aspects such as the signal amplitude (and, therefore, quality), Laplacian estimation error and spatial selectivity (SS). For this purpose, a finite dimensional model of the CRE was used, and its response to the activity of an electric dipole of variable depth was simulated via finite element method modeling. Our results show that increasing the electrode size increases the error to a greater extent than the signal amplitude increases. Pole widths should be as small as possible. The middle ring of the tripolar CRE should be as far away as possible from the central disc. Tripolar CREs typically outperform bipolar CREs of the same outer diameter, significantly reducing the Laplacian estimation error and improving the SS at the cost of a small decrease in signal amplitude. Our results also show that the design of current commercial versions of CREs can be optimized. Furthermore, we propose a methodology that facilitates the selection of an adequate CRE configuration based on the specifications for CRE performance and practical aspects, such as the depth of activity sources to be recorded from and/or the maximum size of electrodes to be used. The monitoring and analysis of bioelectrical signals in a wide range of applications can benefit from the enhanced electrode design and methodology proposed in this work.
A new image reconstruction strategy for capacitively coupled electrical impedance tomography
Authors: Wu Yimin , Jiang Yandan , Ji Haifeng , Wang Baoliang , Huang Zhiyao , Soleimani Manuchehr 
Published: November 2023

Abstract
Capacitively coupled electrical impedance tomography (CCEIT) is an attractive improvement of electrical resistance tomography (ERT) that offers contactless measurement and utilizes both the real and imaginary parts of the impedance for monitoring conductive gas-liquid two-phase flows in the industry. The conventional CCEIT adopts the finite element method under the benchmark of conductive liquid background to obtain the sensitivity matrices, which has been validated effective in ERT for the usage of the real part information. However, few researches on the usage of the imaginary part information of the conductive fluid have been reported. More research work should be undertaken to seek the most effective sensitivity calculation benchmark for the imaginary part utilization in CCEIT. In this work, the usage of the imaginary part information under different sensitivity calculation benchmarks is studied and a new image reconstruction strategy is proposed for CCEIT. By comparing the imaginary part sensitivity matrices and the corresponding imaging performance under different backgrounds, the benchmark that can make better use of the imaginary part information is determined. With the determined benchmark, a new image reconstruction strategy of CCEIT, which utilizes the respective effective benchmarks for the image reconstruction of the two parts of the fluid impedance, and employs a novel hybrid image fusion method to obtain the final image, is presented. Research results show that the benchmark of non-conductive gas background is more effective for the usage of the imaginary part information of the conductive gas-liquid two-phase flow. And the experimental results demonstrate the effectiveness of the proposed strategy in obtaining high-quality images. Compared with the conventional image reconstruction strategy of CCEIT, the proposed strategy has better imaging performance. This research provides valuable experience in utilizing the imaginary part information of the fluid impedance and lays a good foundation for the further development of CCEIT.
Recent progress in modifications of g-C3N4 for photocatalytic hydrogen evolution and CO2 reduction
Authors: Rana Garima , Dhiman Pooja , Kumar Amit , Dawi Elmuez A , Sharma Gaurav 
Published: November 2023

Abstract
Photocatalytic H2 evolution and CO2 reduction are promising technologies for addressing environmental and energy issues. g-C3N4 is one of most promising materials to form improved catalysts because of its exceptional electrical structure, physical and chemical characteristics, and distinctive metal-free feature. This article provides a summary of current advancements in g-C3N4-based catalysts from innovative design approaches and their applications. Hydrogen evolution has reached 6305.18 µmol g−1 h−1 and >9 h of stability using the SnS2/g-C3N4 heterojunction. Additionally, the ZnO/Au/g-C3N4 maintains a constant CO generation rate of 689.7 mol m−2 during the 8 h reaction. To fully understand the interior relationship of theory–structure performance on g-C3N4-based materials, modifications are studied simultaneously. Furthermore, the synthesis of g-C3N4 and g-C3N4-based materials, as well as their respective instances, have been reported. The reduction of CO2 and H2 generation is summarized. Lastly, a short overview of the present issues and potential alternatives for g-C3N4-based materials is provided.
ETG turbulent transport in the Mega Ampere Spherical Tokamak (MAST) pedestal
Authors: Li P.-Y. , Hatch D.R. , Chapman-Oplopoiou B. , Saarelma S. , Roach C.M. , Kotschenreuther M. , Mahajan S.M. , Merlo G. ,   the MAST Team
Published: November 2023

Abstract
The results of a gyrokinetic analysis of turbulent transport driven by the electron temperature gradient (ETG) in the MAST pedestal are presented. Local nonlinear simulations from the gyrokinetic code, GENE, show that heat flux produced by ETG turbulence is 10%–30% of the total applied heating power in the upper pedestal and pedestal top during both the pre-edge-localized mode (ELM) (80%–99% inter-ELM period) and post-ELM (0%–20%) periods. Increasing strongly with the ETG, the ETG transport appears to be stiff. Considering radiation losses, ion thermal transport, and the strong sensitivity of the transport to the ETG, we propose that ETG transport is a plausible mechanism mediating the inter-ELM temperature profile on MAST. Cognizant of the possibility that sharp variations in the pedestal profiles may violate the local approximation, we conducted global nonlinear simulations; the results are in good agreement with local simulations except near the pedestal top, where extended radial structures and high transport levels (far beyond experimental) develop in the local simulations. We quantify and parameterize the discrepancy between local and global simulations by calculating the ratio of the radial correlation length to a length scale representative of the profile curvature. When this ratio is sufficiently small, local and global simulations agree as expected.
Sleep Apnea Detection Based on Snoring Sound Analysis Using DS-MS neural network
Authors: Shang Yuzhuo , Guo Bin , Zhao Zijun 
Published: November 2023

Abstract
Sleep apnea hypopnea syndrome (OSAHS) is a high-incidence disease with serious harm and potential dangers. Currently, the traditional scheme for monitoring sleep quality mainly focuses on monitoring two physiological signals: electroencephalogram (EEG) and heartbeat. However, in the sleep state, respiration is also an important physiological signal. This paper proposes a sleep apnea detection method based on snoring sound analysis using deep learning. Firstly, snoring sound signals are preprocessed and feature extraction is performed using Mel-frequency cepstral coefficients (MFCC). The extracted features are then used to train a DS-MS neural network model, and the optimal detection model is obtained through iterations. The experimental results show that the accuracy of the proposed detection model can reach 94.17%.
Hardware Acceleration Schemes for Convolutional Neural Networks
Authors: Xie Zhiqing , Jiang Xue , Peng Meihua , Yang Ziheng 
Published: November 2023

Abstract
This paper presents a hardware acceleration design for convolutional neural networks. Floating-point fixed-point operations, pipeline interlayer parallel acceleration, and design space exploration are the three key areas of optimization, and optimized modules can be used to build various networks with convolutions according to specifications for the application scenario, thus achieving a universal design. The experimental results show that the optimization of hardware resources improves the speed and performance of the algorithm, and can withstand larger data volumes and higher real-time requirements. The system achieves an accuracy of 95.09% and an inference speed of 0.237 ms per image, with a high processing speed. As a result, convolutional neural networks may now be used in a wider variety of application scenarios and manage larger datasets and higher real-time demands thanks to the design solutions presented in this research.
YOLOv5 UAV Detection Algorithm Based on Attention Mechanism
Authors: Wang Qi , Zhao Haili , Wang Kang 
Published: November 2023

Abstract
To address the poor accuracy issue with tiny target recognition by UAVs, this study provides an improved YOLOv5 detection method with an attention mechanism. Firstly, CBAM is integrated into Backbone to suppress irrelevant features and enhance the network’s attention to space and channels. This can help the network learn more discriminative representations of objects in the image. Then, the introduction to Biformer in Neck removes redundant information on the algorithm structure, endows the network with dynamic query-aware sparsity, and enhances its ability to detect small targets. The experimental findings demonstrate that the suggested algorithm model has a detection accuracy of 84.6% on average. in the self-built UAV dataset, and can accurately complete the detection task of small UAV targets.
Classification of Clavicle Fractures based on Multi-View Fusion
Authors: Huang Yongfeng , Cao Qingyu , Huang Yongfeng , Tong Hongfang 
Published: November 2023

Abstract
Clavicle fracture is a common shoulder injury. Clinical Allman classification divides clavicle fracture into middle fracture, distal fracture and proximal fracture. Different fracture types have corresponding treatment methods and different healing standards. The diagnosis of clavicle fractures can be misdiagnosed and missed by doctors due to blurring of the fracture line. In order to improve the diagnostic efficiency of clinicians and provide clearer treatment ideas, this paper establishes a two-stage clavicle-assisted diagnostic model. The first stage is based on 3D U-Net to segment the shoulder CT of normal clavicle and clavicle fracture in 3D, with dice coefficient reaching 0.9441, and then calculates the two-dimensional image information entropy of the image to select the key layers of the clavicle for classification of the segmented 3D image. The second stage of classification was performed to fuse the key layers data under the three views. The experimental results showed that the three-view fusion had a higher classification accuracy compared to the single-view slice, and the accuracy was improved by 1.3% to 93.4% compared to the best coronal classification, which showed that the two-stage classification method showed good classification effect and could help doctors improve the diagnostic efficiency.
Algorithm Research for Bubble Detection in Capacitive Liquid Level Sensor of Fully Automated Immunoassay Analyzer
Authors: Huang Kai , Zhang Zhengyong 
Published: November 2023

Abstract
Fully automated immunoassay analyzers are integral to clinical testing, with liquid-level detection crucial to mitigate false measurements and cross-contamination. This study introduces a bubble detection algorithm based on the Random Forest machine learning model to address bubble detection in analyzers using capacitive sensors. The algorithm processes collected capacitance data, accurately identifying bubbles and ensuring sampling accuracy. Data preprocessing, feature extraction, and classification enable precise bubble detection. Compared to the traditional CART decision tree algorithm, this algorithm demonstrates superior bubble detection performance, indicating its significant research value and potential for liquid-level detection in fully automated immunoassay analyzers.