bluuebunny/crossref_metadata_2025_split huggingface dataset:
Influence of Perspective Distortion in Laryngoscopy
Authors: Veltrup Reinhard , Kniesburges Stefan , Semmler Marion 
Published: August 2023

Objective:
An experiment with controllable boundaries was designed to assess the influence of the recording angle and distance on two-dimensional (2D) imaging in laryngoscopy and resulting 2D parameter calculation derived from the glottal area waveform (GAW).

Method:
Two high-speed camera setups were used to synchronously record an oscillating synthetic vocal fold (VF) model, simulating a high-speed videoendoscopy. One camera recorded at variable lateral recording angles and a reference camera in superior perspective. This was performed at different physiological recording distances and for two oscillation modes (with/without contacting VFs). The GAW was derived from the segmented glottis, and two parameters each for the categories of symmetry, periodicity, and closure were calculated, as well as two derivative measures. The percentage difference between the variable and reference camera value pairs was calculated, and the angle and height dependencies were quantified using linear regression.

Results:

The visual perception of a laryngoscopy was found to be influenced by the lateral recording angle, which may lead to misinterpretation of VF symmetry among inexperienced observers. The strongest influence of recording angle was observed for symmetry parameters, the strongest being the Amplitude Symmetry Index with up to 2.6%/° (
p
< .05). A dependence on the recording distance was only found for the Maximum Area Declination Rate.

Conclusions:
The recording angle in 2D laryngoscopy should be carefully considered during visual inspection of the VF dynamics. Most of the investigated objective parameters were unaffected by the examined perspective distortion. However, especially left–right symmetry measures should only be used under controlled boundary conditions to avoid misdiagnosis and misinterpretation.

Supplemental Material:

https://doi.org/10.23641/asha.23961183
STFT: Spatial and temporal feature fusion for transformer tracker
Authors: Zhang Hao , Piao Yan , Qi Nan 
Published: August 2023

AbstractSiamese‐based trackers have demonstrated robust performance in object tracking, while Transformers have achieved widespread success in object detection. Currently, many researchers use a hybrid structure of convolutional neural networks and Transformers to design the backbone network of trackers, aiming to improve performance. However, this approach often underutilises the global feature extraction capability of Transformers. The authors propose a novel Transformer‐based tracker that fuses spatial and temporal features. The tracker consists of a multilayer spatial feature fusion network (MSFFN), a temporal feature fusion network (TFFN), and a prediction head. The MSFFN includes two phases: feature extraction and feature fusion, and both phases are constructed with a Transformer. Compared with the hybrid structure of “CNNs + Transformer,” the proposed method enhances the continuity of feature extraction and the ability of information interaction between features, enabling comprehensive feature extraction. Moreover, to consider the temporal dimension, the authors propose a TFFN for updating the template image. The network utilises the Transformer to fuse the tracking results of multiple frames with the initial frame, allowing the template image to continuously incorporate more information and maintain the accuracy of target features. Extensive experiments show that the tracker STFT achieves state‐of‐the‐art results on multiple benchmarks (OTB100, VOT2018, LaSOT, GOT‐10K, and UAV123). Especially, the tracker STFT achieves remarkable area under the curve score of 0.652 and 0.706 on the LaSOT and OTB100 benchmark respectively.
Public policies for cyber security of sustainable dominated renewable smart grids
Authors: Dehghani Moslem , Niknam Taher , GhasemiGarpachi Mina , Alhelou Hassan Haes , Pourbehzadi Motahareh , Javidi Giti , Sheybani Ehsan 
Published: August 2023

AbstractThe purpose of this paper is to examine cyber security issues related to smart grids (SGs), such as prior cyber‐attacks, possible vulnerability issues, and enhanced cyber‐security procedures for SGs on a technical and management basis. When designing public policies for SGs, it is important to consider both the motivations and obstacles to cyber protection and socio‐economic conditions. Furthermore, the importance of suggested policies is viewed from various perspectives. The present paper provides an assessment of a group of policies specified by various stakeholders as having the potential for developing SG cyber security. The methodology for the formation of such a group of policies includes a perfect examination of global experience and meetings with experts from various fields. Subsequently, such policies are evaluated using a Delphi questionnaire aimed at assessing their advantages in pursuing investment goals for cyber security. The first result is that every policy is considered a positive effect of all goals, different in the priority assigned to each of them. The policies that received the most attention were: “regulatory changes policy to foster innovation in cyber security of SGs,” “regulation of new business models to improve cyber security and detect malicious attacks” and “establish a cyber‐security governance strategy.”
Research on vibration energy harvesting technology of power equipment based on alternating magnet array
Authors: Lv Pinlei , Fan Chengyu , Yang Aijun , Yuan Huan , Chu Jifeng , Rong Mingzhe , Wang Xiaohua 
Published: August 2023

AbstractVibration with a frequency of 100 Hz is widely distributed in the power equipment, and it can provide a new way to supply energy for sensors by vibration energy harvesting. The vibration energy harvesting method based on electromagnetic induction principle was studied through the arrayed structure of magnets and coils. Static magnetic field models were established for four magnet array structures and it was found that the alternating magnet array has the largest magnetic flux and magnetic flux gradient. Based on the alternating magnet array, prototypes of energy harvester with vertical and parallel movement mode were proposed. Through structural parameter optimisation analysis, two different energy harvesters were fabricated and it was found that the energy harvester with a parallel movement mode has better output performances. The energy harvester could provide output voltage/current and power of 8.35 V/17.39 mA and 15.13 mW (matched resistance is 200 Ω) at an acceleration of 5 m·s−2. The 100 mF capacitor could be charged to 2.72 V within 300 s, and the final voltage of the capacitor is greater than 3 V, which could sustainably drive commercial wireless temperature/humidity sensors.
Next-generation sequencing of pancreatic cyst wall specimens obtained using micro-forceps for improving diagnostic accuracy
Authors: Astbury Stuart , Baskar Aishwarya , Grove Jane I. , Kaye Philip , Aravinthan Aloysious D. , James Martin W. , Clarke Christopher , Aithal Guruprasad P. , Venkatachalapathy Suresh Vasan 
Published: August 2023

Abstract
Background and study aims Pancreatic cysts are common incidental findings, with an estimated prevalence of 13% to 15% in imaging done for other reasons. Diagnosis often relies on collection of cyst fluid, but tissue sampling using micro-forceps may allow for a more reliable diagnosis and higher yield of DNA for next-generation sequencing (NGS). The primary aim was to assess the performance of NGS in identifying mucinous cyst. The secondary aims were to assess DNA yield between the cyst fluid and cyst wall tissue, complication rate and performance of conventional investigations.
Patients and methods Twenty-four patients referred for endoscopic ultrasound were recruited. Biopsies were taken using micro-forceps and the AmpliSeq Cancer Hotspot panel was used for NGS, a polymerase chain reaction assay targeting several hotspots within 50 genes, including GNAS, KRAS and VHL.
Results The concentration of DNA extracted from 24 cyst wall samples was significantly higher than in the nine of 24 available matched cyst fluid samples. The sensitivity, specificity, and diagnostic accuracy of NGS for diagnosing mucinous cyst were 93%, 50% and 84%; for standard of care, they were -66.6%, 50% and 63.1%; and for standard of care with NGS, they were 100%, 50%, and 89.4% respectively. Cyst wall biopsy was able to diagnose 19 of 24 cysts (4 high risk, 7 intraductal papillary mucinous neoplasms, 4 cysts of mucinous origin, and 4 benign).
Conclusions NGS data correlate well with histology and may aid in diagnosis and risk stratification of pancreatic cysts. Cyst wall biopsy performs well in diagnosing cysts but was inadequate in five of 24 patients.
Synthesis of N-Propargyl Pyrrolylamides and Theoretical Study of Pyrrolylimide Reduction by NaBH4
Authors: Basceken Sinan 
Published: August 2023

AbstractThis study is divided into two parts: experimental and theoretical. In the experimental part, N-propargyl-substituted pyrrolylamide derivatives are synthesized in five steps starting from pyrrole. The main features of this procedure are (i) the synthesis of 2- and 3-nitropyrrole, (ii) the introduction of a propargyl group on the nitrogen atom of the pyrrole, (iii) coupling of various substituents with the alkyne functionality by the Sonogashira reaction, (iv) synthesis of pyrrolylimides by a tin-catalyzed reaction with phthalic anhydride, and, finally, (v) reduction of pyrrolylimides with sodium borohydride (NaBH4) in the presence of water. The theoretical part concerns the reduction mechanism of the pyrrolylimide by NaBH4. The hybrid functional B3LYP in density functional theory is used to determine and discuss the energetics of the compounds.
Antenatal Care Services for Migrant Workers in Northern Thailand: Challenges, Initiatives, and Recommendations for Improvement
Authors: Wungrath Jukkrit 
Published: August 2023

AbstractThis review article emphasizes the importance of addressing the unique health care needs of migrant workers in northern Thailand, with a focus on antenatal care services. There has been an increase in the number of migrant workers in the region. The challenges include language and cultural barriers, legal and administrative issues, inadequate health facilities and staff, and stigma and discrimination. However, by implementing a comprehensive set of recommendations, including strengthening collaboration, developing culturally sensitive programs, and increasing health care facility accessibility, stakeholders can create a more inclusive and supportive health care environment for migrant workers. This will ultimately contribute to healthier pregnancies and better outcomes for both mothers and their newborns. Prioritizing the needs of migrant workers is crucial for the successful integration of this population into the local health care workforce, thereby improving the health care system in northern Thailand.
A Young Boy with 21q21.1 Microdeletion Showing Speech Delay, Spastic Diplegia, and MRI Abnormalities: Original Case Report
Authors: Pavone Piero , Falsaperla Raffaele , Ruggieri Martino , Marino Simona Domenica , Parano Enrico , Pappalardo Xena Giada 
Published: August 2023

AbstractChromosome 21q deletion syndrome is a rare disorder affecting the long arm of chromosome 21 and manifesting with wide phenotypic features depending on the size and position of the deleted region. In the syndrome, three distinct deleted regions have been distinguished: region 1, from the centromere to approximately 31.2 Mb (21q11.2-q22.11); region 2, from 31.2 to 36 Mb (21q22.11-q22.12); and region 3, from 36 to 37.5 Mb to the telomere (21q22.12-q22.3). The clinical features are highly variable manifesting with mild, poorly recognizable signs or with severe symptoms including craniofacial dysmorphism, growth failure, developmental delay, behavioral/affective abnormalities, and systemic malformations. We report here the case of a young boy with speech delay, mild spastic diplegia, and brain anomalies on magnetic resonance imaging (MRI). The genetic analysis displayed a microdeletion of the long arm of chromosome 21 approximately extending up to 1.08 Mb. Clinical presentation of the patient and cases of 21q21 deletion reported by the literature are discussed.
The electric flux through a square of a point charge near one corner
Authors: Atems Elisabeth 
Published: August 2023

Abstract
This paper presents two geometric models that can be used by students studying electrostatics to explore the electric flux of a point charge through a square in the limit of infinitesimal displacement from one corner. We first use qualitative reasoning to show that the limit is not a single value, but depends on the direction of displacement, and has significant discontinuities at the plane inside the square and along its sides. In the first model, the square is treated as one face of a cube. With this model, we discuss how to use Gauss’s law to determine the limiting flux through the square for displacements along symmetry lines of the cube, and their reflections through the planes of the faces. The second model treats the square as the base of a square pyramid and enables derivation of the limiting flux for displacements in an arbitrary direction. The result is verified against that obtained analytically, by integrating the definition of electric flux over the area of the square, in the limit of infinitesimal displacement from the corner. Both models require and facilitate an intuitive understanding of Gauss’s law and the limit concept, and the quantitative reasoning involves a minimum of algebra and no calculus. The first model, especially, is suitable for use in a guided-inquiry tutorial or problem-solving workshop for undergraduate physics students.
Challenges in addressing student difficulties with basics and change of basis for two-state quantum systems using a multiple-choice question sequence in online and in-person classes
Authors: Hu Peter , Li Yangqiuting , Singh Chandralekha 
Published: August 2023

AbstractResearch-validated multiple-choice questions comprise an easy-to-implement instructional tool for scaffolding student learning and providing formative assessment of students’ knowledge. We present findings from the implementation of a research-validated multiple-choice question sequence on the basics of two-state quantum systems, including inner products, outer products, translation between Dirac notation and matrix representation in a particular basis, and change of basis. This study was conducted in an advanced undergraduate quantum mechanics course, in both online and in-person learning environments, across three years. For each cohort, students had their learning assessed after traditional lecture-based instruction in relevant concepts before engaging with the multiple-choice question sequence. Their performance was evaluated again afterward with a similar assessment and compared to their earlier performance. We analyze, compare, and discuss the trends observed in the three implementations.
Solving time-independent Schrödinger equation variationally using random numbers
Authors: Praneel Pranjal , Kumar Ashish , Harbola Manoj K 
Published: August 2023

Abstract
Finding wavefunctions for even the simplest of interacting particle systems consisting of two particles is extremely difficult. It is therefore highly desirable that an accurate and easily implementable method be available to instructors and students of quantum-mechanics for obtaining wavefunctions for these particles. The usual approach taken to do this is to use parametrized functional form for the wavefunction in conjunction with the variational method to find approximate wavefunction and energy for the ground-state of such systems. In this paper, we employ random numbers to obtain ground-state wavefunctions and energies of two interacting particles in different one-dimensional potentials. The idea behind using random numbers is to search freely for functions that lead to lower and lower energy, converging eventually to its lowest value. The method presented is easily applicable numerically using a simple algorithm, and the wavefunctions obtained are highly accurate. Thus, the method presented makes study of two interacting particles accessible to instructors and students alike in a transparent manner.
Hypersonic FLEET velocimetry and uncertainty characterization in a tripped boundary layer
Authors: Pehrson J Clark , Leonov Boris S , Melone Kate , Lakebrink Matthew T , Bowersox Rodney , Miles Richard B , Limbach Christopher M 
Published: August 2023

Abstract
Femtosecond laser electronic excitation tagging (FLEET) velocimetry is applied in a hypersonic boundary layer behind an array of turbulence-inducing trips. One-dimensional mean velocity and root-mean-square (RMS) of velocity fluctuation profiles are extracted from FLEET emissions oriented across a 2.75∘ wedge and through a boundary layer above a flat plate in two test campaigns spanning 21 tunnel runs. The experiment was performed in the Texas A&M University Actively Controlled Expansion tunnel that operated near Mach 6.0 with a Reynolds number near 6 × 106 m−1 and a working fluid of air at a density near 2.5 × 10−2 kg m−3. Detailed analysis of random and systematic errors was performed using synthetic curves for error in the mean velocity due to emission decay and the error in the RMS velocity fluctuation due to random error. The boundary layer behind an array of turbulence-inducing trips is documented to show the breakdown of coherent structures. FLEET velocimetry is compared to the tunnel Data Acquisition System, Vibrationally Excited Nitric Oxide Monitoring results, and Reynolds-Averaged Navier–Stokes computational fluid dynamics to verify results.
A novel pre-trained model based on graph-labeling graph neural networks for tool wear prediction under variable working conditions
Authors: Xu Haitao , Yang Xu , Wang Wei , Du Jinsong , Gao Jie 
Published: August 2023

Abstract
In recent years, deep learning has made significant strides and found extensive applications in tool wear prediction. However, most methods based on deep learning rely on large-scale datasets for training and do not consider the method under variable working conditions. To address these limitations, this paper proposes a novel pre-trained fine-tuning model based on the graph-labeling graph neural network (GGPT) specifically designed to train on small-scale datasets. The GGPT model comprises two essential components: a feature extractor and a graph attention module (GAT). The feature extractor uses a residual connection constructed by maximum pooling and average pooling to improve the reliability of local feature learning. The GAT module enhances the global feature learning ability of the model by aggregating local features extracted by the feature extractor. In addition, Improved Pseudo-task Regularization is introduced to enable the model to converge better on small datasets. Experimental results substantiate the superiority of the GGPT model over other deep learning-based methods, particularly when confronted with variable working conditions for tool wear prediction.
Bearing fault diagnosis based on CNN-BiLSTM and residual module
Authors: Fu Guanghua , Wei Qingjuan , Yang Yongsheng , Li Chaofeng 
Published: August 2023

Abstract
Bearings are key components of rotating machinery, and their fault diagnosis is essential for machinery operation. Bearing vibration signals belong to time series data, but traditional convolutional neural networks (CNNs) or recurrent neural networks cannot fully extract the fault features from these signals. To address the insufficient feature extraction and poor noise resistance, this paper proposes a fault diagnosis model based on continuous wavelet transform (CWT), CNN with channel attention, bidirectional long short-term memory network (BiLSTM) and residual module. Firstly, a parallel dual-path feature extraction mechanism is constructed which takes time-domain signals and time–frequency images transformed via CWT as the input respectively. Then BiLSTM extracts the time features of the signal as one path, and the CNN with efficient channel attention extracts the spatial features as the other path. This parallel neural network contributes to better feature extraction. Then, the residual module is applied to extract the global features to further improve the feature extraction ability and noise immunity. The experimental results demonstrate that the proposed model on the Case Western Reserve University dataset has better diagnostic accuracy under different working conditions and different signal-to-noise ratios than other methods. In addition, the model shows good generalization performance on Jiangnan University dataset.
A rapid outliers detection and correction method for external ballistic velocity measurement data
Authors: Yan Lin , Qian Fucai , Li Yunfeng , Sha Xinyu , Huang Jiaoru 
Published: August 2023

Abstract
Due to the influence of various sudden and abnormal factors during the tracking environment, equipment working conditions, and operation process, there are inevitable outliers in the tracking measurement process of aircraft such as carrier rockets, artificial satellites, and missiles. Therefore, the prerequisite for ensuring the reliability of processing results is to timely and accurately detect and correct outliers. In this paper, we proposed the sliding window-based variable degree B-spline function method (SWVD B-spline), which can handle isolated outliers and spotted outliers. SWVD B-spline uses variable degree B-spline function to model observed data in sliding windows, which can detect and correct outliers point by point along with window sliding. Then, we propose an initial window data selection method to remove outliers in initial windows to ensure the processing effect. In addition, because there are often inflection points in external ballistic velocity measurement data, differential evolution is used to optimize variable degree B-spline in windows that include inflection points to improve processing accuracy. The experimental results verify that SWVD B-spline can handle various outliers rapidly and efficiently.
Relevance of alcoholic solvents in the growth of ZnO nanoparticles and ZnO hierarchical nanorod structures on their optical and opto-electrical properties
Authors: Nagpal Keshav , Rauwel Erwan , Ducroquet Frederique , Gélard Isabelle , Rauwel Protima 
Published: August 2023

Abstract
We report on the synthesis of ZnO nanoparticles and ZnO hierarchical nanorod structures using four different alcohols i.e. methanol, isopropanol, ethanol, and aqueous ethanol (70% alcohol, 30% water). The syntheses of the nanoparticles were carried out by non-aqueous and hydrothermal routes. In general, absolute alcohol allows a better control of the synthesis reaction and nanoparticles as small as 5 nm were obtained, confirmed by TEM. XPS analysis elucidated the chemical states that were correlated to the synthesis reaction. For the nanorod growth, these four alcohols were used as seeding solvents, followed by hydrothermal ZnO nanorod growth. Here, the seed layer tailored the nanorod diameters and surface defects, which were studied by SEM and photoluminescence spectroscopy. Subsequently, the ZnO nanorods were electrically characterized and exhibited persistent photoconductivity under UV irradiation of 365 nm. The differences in conductivity in dark and under UV irradiation were attributed to the size of the nanorods, defect states, semiconductor band bending and oxygen adsorption–desorption mechanisms. Parameters such as photoresponse and photosensitivity are also calculated in order to evaluate their applicability in UV sensors. This work demonstrates optimization of the physical, chemical, electrical and optical properties of both ZnO nanostructures via the use of alcoholic solvents.