bluuebunny/crossref_metadata_2025 huggingface dataset:
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.
Analysis of Emotional Deconstruction and the Role of Emotional Value for Learners in Animation Works Based on Digital Multimedia Technology
Authors: Liang Shilei
Published: November 2023

With the rapid development of artificial intelligence and digital media technology, modern animation technology has greatly improved the creative efficiency of creators through computer‐generated graphics, electronic manual painting, and other means, and its number has also experienced explosive growth. The intelligent completion of emotional expression identification within animation works holds immense significance for both animation production learners and the creation of intelligent animation works. Consequently, emotion recognition has emerged as a focal point of research attention. This paper focuses on the analysis of emotional states in animation works. First, by analyzing the characteristics of emotional expression in animation, the model data foundation for using sound and video information is determined. Subsequently, we perform individual feature extraction for these two types of information using gated recurrent unit (GRU). Finally, we employ a multiattention mechanism to fuse the multimodal information derived from audio and video sources. The experimental outcomes demonstrate that the proposed method framework attains a recognition accuracy exceeding 90% for the three distinct emotional categories. Remarkably, the recognition rate for negative emotions reaches an impressive 94.7%, significantly surpassing the performance of single‐modal approaches and other feature fusion methods. This research presents invaluable insights for the training of multimedia animation production professionals, empowering them to better grasp the nuances of emotion transfer within animation and, thereby, realize productions of elevated quality, which will greatly improve the market operational efficiency of animation industry.
First upper limits on the 21 cm signal power spectrum from cosmic dawn from one night of observations with NenuFAR
Authors: Munshi S. , Mertens F. G. , Koopmans L. V. E. , Offringa A. R. , Semelin B. , Aubert D. , Barkana R. , Bracco A. , Brackenhoff S. A. , Cecconi B. , Ceccotti E. , Corbel S. , Fialkov A. , Gehlot B. K. , Ghara R. , Girard J. N. , Grießmeier J. M. , Höfer C. , Hothi I. , Mériot R. , Mevius M. , Ocvirk P. , Shaw A. K. , Theureau G. , Yatawatta S. , Zarka P. , Zaroubi S.
Published: November 2023

The redshifted 21 cm signal from neutral hydrogen is a direct probe of the physics of the early universe and has been an important science driver of many present and upcoming radio interferometers. In this study we use a single night of observations with the New Extension in Nançay Upgrading LOFAR (NenuFAR) to place upper limits on the 21 cm power spectrum from cosmic dawn at a redshift ofz = 20.3. NenuFAR is a new low-frequency radio interferometer, operating in the 10–85 MHz frequency range, currently under construction at the Nançay Radio Observatory in France. It is a phased array instrument with a very denseuvcoverage at short baselines, making it one of the most sensitive instruments for 21 cm cosmology analyses at these frequencies. Our analysis adopts the foreground subtraction approach, in which sky sources are modeled and subtracted through calibration and residual foregrounds are subsequently removed using Gaussian process regression. The final power spectra are constructed from the gridded residual data cubes in theuvplane. Signal injection tests are performed at each step of the analysis pipeline, the relevant pipeline settings are optimized to ensure minimal signal loss, and any signal suppression is accounted for through a bias correction on our final upper limits. We obtain a best 2σupper limit of 2.4 × 107mK2atz = 20.3 andk = 0.041h cMpc−1. We see a strong excess power in the data, making our upper limits two orders of magnitude higher than the thermal noise limit. We investigate the origin and nature of this excess power and discuss further improvements to the analysis pipeline that can potentially mitigate it and consequently allow us to reach thermal noise sensitivity when multiple nights of observations are processed in the future.
Influence of Au0 metallic particles on NIR laser emission of Yb3+ ions in Li2O−HfO2−SiO2 glass ceramic
Authors: Pavani Koteswari Devi Pilli , Venkata Sekhar Ayyagari , Ravi Kumar Valluri , Venkatramaiah Nutalapati , Ravi Kumar Vandana , Veeraiah Nalluri
Published: November 2023

This study consists of the synthesis, characterization, and analysis of photoluminescence (PL) spectra for Li2O−HfO2−SiO2−Yb2O3 glass ceramics sensitized with small amounts of Au2O3. Using the results of XRD and X-ray photoelectron spectroscopy (XPS) studies indicated a progressive reduction of Au3+ ions into Au0 metallic particles (MPs) with increase of Au2O3 content. Investigations into the infrared spectra highlighted a growing concentration of induced defects in the samples due to the increased proportion of Au0 MPs. Optical absorption (OA) spectra exhibited a distinct band attributed to the 2F7/2 → 2F5/2 transition of Yb3+ within wavelength range of 800–980 nm. Furthermore, a wide absorption band linked to the surface plasmon resonance (SPR) of Au0 MPs was identified in the visible region. PL spectra, recorded at λexc = 450 nm, revealed a band between 980 to 1025 nm, associated with the 2F5/2 → 2F7/2 transition of Yb3+ ions. Another emission band was observed due to the sp → d transition of Au0 MPs within the visible region. Observed enhanced PL emission from Yb3+ ions in the NIR range was ascribed to the energy transfer from Au0 MPs to Yb3+ ions. Ultimately, it was deduced that Au0 MPs played a pivotal role in enhancing the PL output of Yb3+ ions in the Li2O−HfO2−SiO2 glass ceramic. Thus, glass ceramics incorporating an optimal concentration of Au2O3 hold significant potential as materials for NIR lasers.
Uncertainty quantification for Fisher-Kolmogorov equation on graphs with application to patient-specific Alzheimer’s disease
Authors: Corti Mattia , Bonizzoni Francesca , Antonietti Paola F. , Quarteroni Alfio M.
Published: November 2023

The Fisher-Kolmogorov equation is a diffusion-reaction PDE that models the accumulation of prionic proteins, which are responsible for many different neurological disorders. The most important and studied misfolded protein in literature is the Amyloid-β, responsible for the onset of Alzheimer’s disease. Moving from medical images we construct a reduced-order model based on a graph brain connectome. The reaction coefficient of the proteins which can hardly be measured is modeled as a stochastic random field, taking into account all the many different underlying physical processes. Its probability distribution is inferred by means of the Monte Carlo Markov Chain method applied to clinical data. The resulting model is patient-specific and can be employed for predicting the disease’s future development. Forward uncertainty quantification techniques (Monte Carlo and sparse grid stochastic collocation) are applied with the aim of quantifying the impact of the variability of the reaction coefficient on the progression of protein accumulation within the next 20 years.
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

Participating 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

In 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

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

In 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.
High efficiency design of metal–insulator–metal metasurface by ResNets-10
Authors: Liu Kaizhu , Chui Hsiang-Chen , Sun Changsen , Han Xue
Published: November 2023

Deep learning prediction of metasurface has been a widely discussed issue in recent years. However, the prediction accuracy is still one of the challenges to be solved. In this work, we proposed using the ResNets-10 model to predict plasmonic metasurface S11 parameters. The two-stage training was performed by the k-fold cross-validation and small learning rate. After the training was complete, the predicted logarithmic losses for aluminum, gold, and silver metal–insulator–metal metasurfaces were −48.45, −46.47, and −35.54, respectively. Due to the ultralow error value, the proposed network can efficiently replace the traditional computing methods within a certain structural range. The ResNets-10 can complete training within 1100 iterations, which is highly efficient. The ResNets-10 model we proposed can also be used to design meta-diffractive devices and meta-resonance biosensors, thereby reducing the time required for the simulation process. The ultralow lose value of the network indicates that this work contributes to the development of future artificial intelligence electromagnetic devices computing software.
Buoyancy-induced axis-asymmetric convection inside droplets
Authors: Bai Lihang , Fang Longhui , Ji Yulong , He Maogang
Published: November 2023

In addition to the well-known diffusion-only and toroidal convection, a seldom reported axis-asymmetric (single circulating) flow can also be induced by heat/mass transfer within a droplet (i.e., droplet rolling). To investigate the mechanism, this work compares their characteristic times and finds that (1) a large viscosity ratio between the droplet and its environment is required for the axis-asymmetric flow and (2) in contrast to precedent prediction, heat/mass transfer cannot incur the axis-asymmetric flow within a vanishingly tiny droplet, as verified by our experiments together with dimensionless dynamical equations. Moreover, our experiments reveal an unprecedented shift of the bound between the axis-asymmetric flow and toroidal convection zones when reversing the transition direction.
High field dielectric response in κ-Ga2O3 films
Authors: He Fan , Jiang Kunyao , Choi Yeseul , Aronson Benjamin L. , Shetty Smitha , Tang Jingyu , Liu Bangzhi , Liu Yongtao , Kelley Kyle P. , Rayner Gilbert B. , Davis Robert F. , Porter Lisa M. , Trolier-McKinstry Susan
Published: November 2023

κ-Ga2O3 has been predicted to be a potential ferroelectric material. In this work, undoped Ga2O3 films were grown by either plasma-enhanced atomic layer deposition (PEALD) or metal organic chemical vapor deposition (MOCVD) on platinized sapphire substrates. 50 nm thick PEALD films with a mixture of κ-Ga2O3 and β-Ga2O3 had a relative permittivity of ∼27, a loss tangent below 2%, and high electrical resistivity up to ∼1.5 MV/cm. 700 nm thick MOCVD films with predominantly the κ-Ga2O3 phase had relative permittivities of ∼18 and a loss tangent of 1% at 10 kHz. Neither film showed compelling evidence for ferroelectricity measured at fields up to 1.5 MV/cm, even after hundreds of cycles. Piezoresponse force microscopy measurements on bare κ-Ga2O3 showed a finite piezoelectric response that could not be reoriented for electric fields up to 1.33 MV/cm.
Microstructure evolution under thermo-mechanical operating of rocksalt-structure TiN via neural network potential
Authors: Guo Fangyu , Chen Bo , Zeng Qiyu , Yu Xiaoxiang , Chen Kaiguo , Kang Dongdong , Du Yong , Wu Jianhua , Dai Jiayu
Published: November 2023

In the process of high temperature service, the mechanical properties of cutting tools decrease sharply due to the peeling of the protective coating. However, the mechanism of such coating failure remains obscure due to the complicated interaction between atomic structure, temperature, and stress. This dynamic evolution nature demands both large system sizes and accurate description on the atomic scale, raising challenges for existing atomic scale calculation methods. Here, we developed a deep neural network (DNN) potential for Ti–N binary systems based on first-principles study datasets to achieve quantum-accurate large-scale atomic simulation. Compared with empirical interatomic potential based on the embedded-atom-method, the developed DNN-potential can accurately predict lattice constants, phonon properties, and mechanical properties under various thermodynamic conditions. Moreover, for the first time, we present the atomic evolution of the fracture behavior of large-scale rocksalt-structure (B1) TiN systems coupled with temperature and stress conditions. Our study validates that interatomic brittle fractures occur when TiN stretches beyond its tensile yield point. Such simulation of coating fracture and cutting behavior based on large-scale atoms can shed new light on understanding the microstructure and mechanical properties of coating tools under extreme operating conditions.
Electron-beam-driven plasma wakefield acceleration of photons
Authors: Sandberg R. T. , Thomas A. G. R.
Published: November 2023

The paper [R .T. Sandberg and A. G. R. Thomas, Phys. Rev. Lett. 130, 085001 (2023)] proposed a scheme to generate ultrashort, high energy pulses of XUV photons through dephasingless photon acceleration in a beam-driven plasma wakefield. An ultrashort laser pulse is placed in the plasma wake behind a relativistic electron bunch so that it experiences a density gradient and therefore shifts up in frequency. Using a tapered density profile provides phase-matching between the driver and witness pulses. In this paper, we study via particle-in-cell simulation the limits, practical realization, and 3D considerations for beam-driven photon acceleration using the tapered plasma density profile. We study increased efficiency by the use of a chirped drive pulse, establishing the necessity of the density profile shape we derived as opposed to a simple linear ramp, but also demonstrating that a piecewise representation of the profile—as could be experimentally achieved by a series of gas cells—is adequate for achieving phase matching. Scalings to even higher frequency shifts are given.
Enhanced photogalvanic effect in MoSSe monolayer with grain boundaries
Authors: Sun Naizhang , Ye Han , Zhou Wenlin , Yang Ruhao , Quhe Ruge , Liu Yumin , Chen Zhihui
Published: November 2023

The photogalvanic effect (PGE) in two-dimensional materials has emerged as a fascinating mechanism for generating photocurrent in non-centrosymmetric crystals without semiconductor p–n junction or bias voltage. In this paper, the impact of grain boundaries (GBs) on the performance of photogalvanic device with Janus MoSSe monolayer is theoretically investigated by quantum transport simulations. Two 4|8 GBs along armchair direction are taken into consideration. Under the illumination of linearly polarized light, we observe a significant enhancement of the PGE photocurrent in the visible light region, which can be attributed to the reduction of device's symmetry. The averaged enhancement ratios reach around 20 and 13 for two 4|8 GBs, respectively.
Evidence of nitrate-based nighttime atmospheric nucleation driven by marine microorganisms in the South Pacific
Authors: Chamba Guillaume , Rissanen Matti , Barthelmeß Theresa , Saiz-Lopez Alfonso , Rose Clémence , Iyer Siddharth , Saint-Macary Alexia , Rocco Manon , Safi Karl , Deppeler Stacy , Barr Neill , Harvey Mike , Engel Anja , Dunne Erin , Law Cliff S. , Sellegri Karine
Published: November 2023

Our understanding of ocean–cloud interactions and their effect on climate lacks insight into a key pathway: do biogenic marine emissions form new particles in the open ocean atmosphere? Using measurements collected in ship-borne air–sea interface tanks deployed in the Southwestern Pacific Ocean, we identified new particle formation (NPF) during nighttime that was related to plankton community composition. We show that nitrate ions are the only species for which abundance could support NPF rates in our semicontrolled experiments. Nitrate ions also prevailed in the natural pristine marine atmosphere and were elevated under higher sub-10 nm particle concentrations. We hypothesize that these nucleation events were fueled by complex, short-term biogeochemical cycling involving the microbial loop. These findings suggest a new perspective with a previously unidentified role of nitrate of marine biogeochemical origin in aerosol nucleation.
The mechanism of

Gα
q

regulation of
PLCβ3
-catalyzed
PIP2
hydrolysis
Authors: Falzone Maria E. , MacKinnon Roderick
Published: November 2023

PLCβ
(
Phospholipase Cβ
) enzymes cleave phosphatidylinositol 4,5-bisphosphate (
PIP2)
producing
IP3
and
DAG
(diacylglycerol).
PIP2
modulates the function of many ion channels, while
IP3
and
DAG
regulate intracellular Ca
2+
levels and protein phosphorylation by protein kinase C, respectively.
PLCβ
enzymes are under the control of G protein coupled receptor signaling through direct interactions with G proteins
Gβγ
and

Gα
q

and have been shown to be coincidence detectors for dual stimulation of

Gα
q

and
Gα

i

-coupled receptors.
PLCβs
are aqueous-soluble cytoplasmic enzymes but partition onto the membrane surface to access their lipid substrate, complicating their functional and structural characterization. Using newly developed methods, we recently showed that
Gβγ
activates
PLCβ3
by recruiting it to the membrane. Using these same methods, here we show that

Gα
q

increases the catalytic rate constant,

k
cat

, of
PLCβ3
. Since stimulation of
PLCβ3
by

Gα
q

depends on an autoinhibitory element (the X-Y linker), we propose that

Gα
q

produces partial relief of the X-Y linker autoinhibition through an allosteric mechanism. We also determined membrane-bound structures of the

PLCβ3·Gα
q

and
PLCβ3·Gβγ
(2)

·Gα
q

complexes, which show that these G proteins can bind simultaneously and independently of each other to regulate
PLCβ3
activity. The structures rationalize a finding in the enzyme assay, that costimulation by both G proteins follows a product rule of each independent stimulus. We conclude that baseline activity of
PLCβ3
is strongly suppressed, but the effect of G proteins, especially acting together, provides a robust stimulus upon G protein stimulation.
Lipid exchange at ER–trans-Golgi contact sites governs polarized cargo sorting
Authors: Kovács Dávid , Gay Anne-Sophie , Debayle Delphine , Abélanet Sophie , Patel Amanda , Mesmin Bruno , Luton Frédéric , Antonny Bruno
Published: November 2023

Oxysterol binding protein (OSBP) extracts cholesterol from the ER to deliver it to the TGN via counter exchange and subsequent hydrolysis of the phosphoinositide PI(4)P. Here, we show that this pathway is essential in polarized epithelial cells where it contributes not only to the proper subcellular distribution of cholesterol but also to the trans-Golgi sorting and trafficking of numerous plasma membrane cargo proteins with apical or basolateral localization. Reducing the expression of OSBP, blocking its activity, or inhibiting a PI4Kinase that fuels OSBP with PI(4)P abolishes the epithelial phenotype. Waves of cargo enrichment in the TGN in phase with OSBP and PI(4)P dynamics suggest that OSBP promotes the formation of lipid gradients along the TGN, which helps cargo sorting. During their transient passage through the trans-Golgi, polarized plasma membrane proteins get close to OSBP but fail to be sorted when OSBP is silenced. Thus, OSBP lipid exchange activity is decisive for polarized cargo sorting and distribution in epithelial cells.
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

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

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

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.
In situ observation of the phase transformation kinetics of bismuth during shock release
Authors: Li 李 Jiangtao 江涛 , Wang 王 Qiannan 倩男 , Xu 徐 Liang 亮 , Liu 柳 Lei 雷 , Zhang 张 Hang 航 , Takagi Sota , Ichiyanagi Kouhei , Fukaya Ryo , Nozawa Shunsuke , Hu 胡 Jianbo 建波
Published: November 2023

A time-resolved x-ray diffraction technique is employed to monitor the structural transformation of laser-shocked bismuth. Results reveal a retarded transformation from the shock-induced Bi-V phase to a metastable Bi-IV phase during the shock release, instead of the thermodynamically stable Bi-III phase. The emergence of the metastable Bi-IV phase is understood by the competitive interplay between two transformation pathways towards the Bi-IV and Bi-III, respectively. The former is more rapid than the latter because the Bi-V to B-IV transformation is driven by interaction between the closest atoms while the Bi-V to B-III transformation requires interaction between the second-closest atoms. The nucleation time for the Bi-V to Bi-IV transformation is determined to be 5.1±0.9 ns according to a classical nucleation model. This observation demonstrates the importance of the formation of the transient metastable phases, which can change the phase transformation pathway in a dynamic process.
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

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

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

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

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

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

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.
Bio-inspired Sky Polarized Orientation based on the atmospheric polarization symmetry mode and Inertial Sensors
Authors: Chen Zhihe , Teng Lianwei , Zhou Wenzhou , He Xiaofeng , Fan Chen
Published: November 2023

This paper presents a sky polarized orientation method based on the symmetry of the atmospheric polarization mode and the inertial sensors. Firstly, a method of extracting solar meridians based on canny operator and Hough Transform is proposed by using the symmetry of atmospheric polarization pattern. Then using the horizontal Angle information of the inertial sensor and the ephemeris information of the sun, a method for solving the yaw Angle of the polarized light is designed. Finally, a single axis rotation experiment and a vehicle-mounted dynamic experiment are carried out to verify and compare the proposed method. Compared with the least square method, the positioning accuracy of the single-axis turntable experiment is improved by 22.61%~73.86%, and that of the vehicle-mounted dynamic experiment is improved by 47.71%, which shows that the method can provide a new orientation means for unmanned vehicles and unmanned aerial vehicles.
Design and development of a hepatic lyo-dECM powder as a biomimetic component for 3D-printable hybrid hydrogels
Authors: Di Gravina Giulia M , Bari Elia , Croce Stefania , Scocozza Franca , Pisani Silvia , Conti Bice , Avanzini Maria A , Auricchio Ferdinando , Cobianchi Lorenzo , Torre Maria Luisa , Conti Michele
Published: November 2023

Bioprinting offers new opportunities to obtain reliable 3D in vitro models of the liver for testing new drugs and studying pathophysiological mechanisms, thanks to its main feature in controlling the spatial deposition of cell-laden hydrogels. In this context, decellularized extracellular matrix (dECM)-based hydrogels have caught more and more attention over the last years because of their characteristic to closely mimic the tissue-specific microenvironment from a biological point of view. In this work, we describe a new concept of designing dECM-based hydrogels; in particular, we set up an alternative and more practical protocol to develop a hepatic lyophilized dECM (lyo-dECM) powder as an ‘off-the-shelf’ and free soluble product to be incorporated as a biomimetic component in the design of 3D-printable hybrid hydrogels. To this aim, the powder was first characterized in terms of cytocompatibility on human and porcine mesenchymal stem cells (MSCs), and the optimal powder concentration (i.e. 3.75 mg ml−1) to use in the hydrogel formulation was identified. Moreover, its non-immunogenicity and capacity to reactivate the elastase enzyme potency was proved. Afterward, as a proof-of-concept, the powder was added to a sodium alginate/gelatin blend, and the so-defined multi-component hydrogel was studied from a rheological point of view, demonstrating that adding the lyo-dECM powder at the selected concentration did not alter the viscoelastic properties of the original material. Then, a printing assessment was performed with the support of computational simulations, which were useful to define a priori the hydrogel printing parameters as window of printability and its post-printing mechanical collapse. Finally, the proposed multi-component hydrogel was bioprinted with cells inside, and its post-printing cell viability for up to 7 d was successfully demonstrated.
Historical evaluation and future projections of compound heatwave and drought extremes over the conterminous United States in CMIP6
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Authors: Rastogi Deeksha , Trok Jared , Depsky Nicholas , Monier Erwan , Jones Andrew
Published: November 2023

Independently, both droughts and heatwaves can induce severe impacts on human and natural systems. However, when these two climate extremes occur concurrently in a given region, their compound impacts are often more pronounced. With the improvement in both the spatiotemporal resolution and representation of complex climate processes in the global climate models (GCMs), they are increasingly used to study future changes in these extremes and associated regional impacts. However, GCM selection for such impact assessments is generally based on historical performance and/or future mean changes, without considering individual or compound extremes. In contrast, this study evaluates historical performance and projected changes in heatwaves, droughts, and compound heatwave-droughts using an ensemble of GCMs from the latest Phase 6 of Coupled Models Intercomparison Project at a regional scale across the conterminous United States. Additionally, we explore the inter-model differences in the projected changes that are associated with various characteristics of extremes and the choice of drought indices. Our analysis reveals considerable variation among the GCMs, as well as substantial differences in the projected changes based on the choice of drought indices and region of interest. For example, the projected increases in both the frequency and intensity of drought and associated compound extreme days, based on the standardized precipitation evapotranspiration index far exceed those derived from the standard precipitation index. Further, the largest changes in the frequency of compound extremes are projected over the Southwest, South Central, and parts of the Southeast while the smallest changes are projected over the Northeast. Overall, this study provides important insights for the interpretation and selection of GCMs for future assessment studies that are crucial for the development of regional adaptation strategies in the face of climate change.