bluuebunny/crossref_metadata_2025_split huggingface dataset:
Study on the rupture surface morphology and ultimate bearing capacity of a self-anchored test pile
Authors: Zhu Lin , Ma Hailong 
Published: September 2022

AbstractThe expression of the ultimate bearing capacity of the upper uplift pile and the lower compressive pile of a self-anchored test pile was obtained by studying their rupture surface morphology. The upper uplift pile had a composite shear rupture surface shape, and the lower compressive pile had the Meyerhof rupture surface shape. Since the interaction between the upper pile and lower pile of a self-anchored test pile is negligible, the expression form of the ultimate bearing capacity of a self-anchored test pile was obtained based on the transformation formula of its bearing capacity. Under the test conditions, the rupture surface morphology of a self-anchored test pile belongs to the situation when the equilibrium point is inside the rupture surface of the lower compressive pile. The theoretical rupture surface is approximately 0.09 m away from the pile side at ground level (1.8 d, where d is the pile diameter). Compared with the distance of the measured rupture surface of the upper uplift pile to the pile side, the difference value is -2.17%. The calculated ultimate bearing capacities of the upper uplift and lower compressive piles are 1287.34 N and 1201.65 N, respectively. The ultimate bearing capacity of the self-anchored test pile is approximately 2726.16 N. Compared with the experimental values of the upper pile and lower pile of the self-anchored test pile, the difference values are + 0.97% and − 7.57%, respectively. Compared with the experimental values of the traditional test piles, the difference value is − 2.64%. The rupture surface morphology and the expression of the ultimate bearing capacity of the self-anchored test pile in this paper can provide a research basis reference for calculating the ultimate bearing capacity of the self-anchored test piles with different pile sizes and soil properties.
Evolutionary implications of new Postopsyllidiidae from mid-Cretaceous amber from Myanmar and sternorrhynchan nymphal conservatism
Authors: Drohojowska Jowita , Zmarzły Marzena , Szwedo Jacek 
Published: September 2022

AbstractNymphs of extinct sternorrhynchan hemipterans are extremely rare, although very important for understanding of evolutionary traits of these insects. A protopsyllidioid nymph, in mid-Cretaceous amber from Kachin, Myanmar, placed in the family Postopsyllidiidae, is the first nymph of this family to be found in the fossil. Postopsyllidiidae previously comprised the sole genus Postopsyllidium with a few species: P. rebeccae, P. grimaldii and P. burmaticum from Kachin amber (Cenomanian) and P. emilyae from Turonian amber of New Jersey. Here, we report a new genus and species of postopsyllid Megalophthallidion burmapteron gen. et sp. nov. (imago) and the first known nymph of the family ascribed to the same genus. An overview of the fossil record of sternorrhynchan nymphs, and the importance of this finding, unlocking a new and complementary window to understanding the evolutionary traits of Protopsyllidioidea and other Sternorrhyncha hemipterans are presented.
Amiodarone improves anemia in a murine model of sickle cell disease and is associated with increased erythrocyte bis(monoacylglycerol) phosphate
Authors: Venugopal Jessica , Wang Jintao , Guo Chiao , Eitzman Daniel T. 
Published: September 2022

AbstractSickle cell disease (SCD) is associated with altered plasma and erythrocyte lipid profiles. In a previous study, SCD mice with deficiency of proprotein convertase subtilisin/kexin type 9 (PCSK9) were observed to have more severe anemia and increased sickling compared to control SCD mice. Although PCSK9 affects circulating low density lipoprotein (LDL) by regulation of the LDL receptor, the effect of PCSK9 on anemia was independent of LDL receptor expression. In the current study, erythrocyte metabolomics were performed and revealed altered erythrocyte lipid species between SCD mice with and without PCSK9. Of particular interest, the late endosome-specific lipid bis(mono)acylglycerol phosphate (BMP) 44:12 was markedly decreased in erythrocytes from SCD mice deficient in PCSK9 mice relative to control SCD mice. Incubation of sickle erythrocytes with a neutralizing antibody to BMP increased erythrocyte sickling in vitro. In vitro treatment of SCD erythrocytes with amiodarone (1.5 μM) or medroxyprogesterone (6.75 μM), two pharmacologic compounds known to increase BMP, resulted in reduced erythrocyte sickling. Treatment of SCD mice with amiodarone (10 mg/kg) for 2 weeks resulted in increased BMP, improvement in anemia with reduced reticulocytosis, and decreased ex vivo sickling. In conclusion, severity of anemia in SCD is improved with amiodarone treatment, an effect which may be mediated through increased erythrocyte BMP.
Effect of foveal morphology on visual acuity in 4–6-year-old children with retinopathy of prematurity: a J-CREST study
Authors: Nishi Tomo , Ueda Tetsuo , Mizusawa Yuutaro , Shinomiya Kayo , Mitamura Yoshinori , Kimura Naoki , Gomi Fumi , Miki Akiko , Nakamura Makoto , Kinoshita Takamasa , Obata Shumpei , Ohji Masahito , Tsuji Takuya , Yoshida Shigeo , Ogata Nahoko 
Published: September 2022

AbstractLaser therapy is the most effective treatment considered for retinopathy of prematurity (ROP). We compared the foveal morphology of the retina in eyes with a history of ROP to that of full-term children. This cross-sectional comparative study included 74 patients with a history of ROP, aged 4–6 years. Among them, 41 underwent laser treatment for ROP. The clinical findings and retinal morphology in these patients were compared to that of 33 patients who had spontaneous ROP regression and 30 age-matched full-term controls. All the patients with ROP had 20/40 or better best-corrected visual acuity (BCVA). The foveal thickness was significantly thicker in laser-treated ROP eyes than in regressed ROP eyes and controls. The outer nuclear layer was significantly thicker, and the inner segment (IS) of the photoreceptors and the inner retinal layer were significantly thicker in the laser-treated ROP eyes than that in the control eyes. In the patients with ROP and controls, better BCVA was associated positively with deeper foveal depression, which was associated with a later gestational age. Our results suggest that prematurity and laser treatment affect the foveal morphology and BCVA.
Addressing racial disparities in surgical care with machine learning
Authors: Halamka John , Bydon Mohamad , Cerrato Paul , Bhagra Anjali 
Published: September 2022

AbstractThere is ample evidence to demonstrate that discrimination against several population subgroups interferes with their ability to receive optimal surgical care. This bias can take many forms, including limited access to medical services, poor quality of care, and inadequate insurance coverage. While such inequalities will require numerous cultural, ethical, and sociological solutions, artificial intelligence-based algorithms may help address the problem by detecting bias in the data sets currently being used to make medical decisions. However, such AI-based solutions are only in early development. The purpose of this commentary is to serve as a call to action to encourage investigators and funding agencies to invest in the development of these digital tools.
Increased very low frequency pulsations and decreased cardiorespiratory pulsations suggest altered brain clearance in narcolepsy
Authors: Järvelä Matti , Kananen Janne , Korhonen Vesa , Huotari Niko , Ansakorpi Hanna , Kiviniemi Vesa 
Published: September 2022

Abstract
Background
Narcolepsy is a chronic neurological disease characterized by daytime sleep attacks, cataplexy, and fragmented sleep. The disease is hypothesized to arise from destruction or dysfunction of hypothalamic hypocretin-producing cells that innervate wake-promoting systems including the ascending arousal network (AAN), which regulates arousal via release of neurotransmitters like noradrenalin. Brain pulsations are thought to drive intracranial cerebrospinal fluid flow linked to brain metabolite transfer that sustains homeostasis. This flow increases in sleep and is suppressed by noradrenalin in the awake state. Here we tested the hypothesis that narcolepsy is associated with altered brain pulsations, and if these pulsations can differentiate narcolepsy type 1 from healthy controls.

Methods
In this case-control study, 23 patients with narcolepsy type 1 (NT1) were imaged with ultrafast fMRI (MREG) along with 23 age- and sex-matched healthy controls (HC). The physiological brain pulsations were quantified as the frequency-wise signal variance. Clinical relevance of the pulsations was investigated with correlation and receiving operating characteristic analysis.

Results
We find that variance and fractional variance in the very low frequency (MREGvlf) band are greater in NT1 compared to HC, while cardiac (MREGcard) and respiratory band variances are lower. Interestingly, these pulsations differences are prominent in the AAN region. We further find that fractional variance in MREGvlf shows promise as an effective bi-classification metric (AUC = 81.4%/78.5%), and that disease severity measured with narcolepsy severity score correlates with MREGcard variance (R = −0.48, p = 0.0249).

Conclusions
We suggest that our novel results reflect impaired CSF dynamics that may be linked to altered glymphatic circulation in narcolepsy type 1.
Abnormal Esophageal Clearance Identified During Modified Barium Swallow Study in an Acute Poststroke Cohort
Authors: Reedy Erin L. , Simpson Annie N. , O'Rourke Ashli K. , Bonilha Heather Shaw 
Published: September 2022

Purpose:
Dysphagia impacts many poststroke survivors with wide-ranging prevalence in the acute and chronic phases. One relatively unexplored manifestation of poststroke swallowing impairment is that of primary or co-occurring esophageal dysphagia. The incidence of esophageal dysphagia in this population is unknown despite the shared neuroanatomy and physiology with the oropharynx. We aimed to determine the presence of abnormal esophageal clearance in an acute poststroke sample using the Modified Barium Swallow Impairment Profile (MBSImP) Component 17 (esophageal clearance) as our outcome measure.

Method:
We performed a retrospective, cross-sectional, cohort study of 57 poststroke patients with acute, first-ever, ischemic strokes. All participants received a modified barium swallow study (MBSS) using the MBSImP protocol and scoring metrics. Swallowing impairment was determined using a combination of MBSImP scores and Penetration–Aspiration Scale scores. Swallowing outcome measures were collected including Functional Oral Intake Scale and International Dysphagia Diet Standardization Initiative (IDDSI) scores. We performed tests of association and logistic regression analysis to determine if statistically significant associations exist between judgments of esophageal clearance and other swallowing impairments and/or swallowing outcome measures.

Results:
In our study of poststroke patients who received an MBSS as part of their care, 57.9% had abnormal esophageal clearance. Statistically significant associations were also identified in measures of pharyngeal physiology (MBSImP scores) and swallowing outcome measures (IDDSI scores and alternate means of nutrition).

Conclusions:
Abnormal esophageal clearance was identified in greater than half of our poststroke patients. There is a dearth of scientific research regarding esophageal function poststroke. While esophageal visualization during the MBSS is not diagnostic of esophageal impairment, it may serve as an indicator for those poststroke patients who require dedicated esophageal testing to best determine the full nature of their swallowing pathophysiology and make the most effective treatment recommendations.
Observational Study to Preliminarily Characterize the Audiological Profile of Children With Down Syndrome
Authors: Porter Heather , Buss Emily , Merchant Gabrielle R. , Leibold Lori J. 
Published: September 2022

Purpose:Down syndrome occurs in one of 700 births, and high rates of hearing loss are reported in this population. This puts children with Down syndrome at risk for communication, learning, and social development difficulties, compounding known language and cognitive vulnerabilities in this population. The purpose of this study was to comprehensively characterize audiological profiles in children with Down syndrome, including the use of extended high-frequency sensitivity and speech intelligibility index assessment.Method:Participants were 18 children with Down syndrome between 5 and 17 years of age. Audiological profiles were characterized using behavioral audiometry, tympanometry, and wideband acoustic immittance (WAI). Audibility was characterized using the speech intelligibility index.Results:Of the participants successfully completing behavioral audiometry, hearing loss of a moderate or greater degree was observed in one or both ears for 46% of the participants at conventional audiometric test frequencies and 85% of the participants at frequencies above 8 kHz. Seven children met criteria for amplification based on the speech intelligibility index, but only two wore hearing aids. Abnormal middle ear function was found in approximately 50% of the participants for whom WAI or tympanometry were successfully measured.Conclusions:Consistent with prior research, high rates of hearing loss and middle ear dysfunction were observed. The high prevalence of hearing loss above 8 kHz suggests the importance of including extended high-frequency assessment in audiologic characterization of children with Down syndrome. Few children meeting audibility-based guidelines for amplification wore hearing aids, putting them at additional risk for speech/language and educational difficulties.Supplemental Material:https://doi.org/10.23641/asha.21200422
An improved evaluation model for supplier selection based on particle swarm optimisation‐back propagation neural network
Authors: Yu Jun , Li Daming , Wang Aihui , Liu Ping , Song Jingwen , Han Xiaobo 
Published: September 2022

AbstractWith the trend of supply chain globalisation, competition among enterprises is becoming more intense. Enterprises urgently need to improve their core competitiveness, and the enhancement of the competencies can depend on technologies services and the quality of suppliers. Since external factors are less controllable, this study starts with the quality of suppliers and proposes a supplier evaluation method that combines particle swarm optimisation with neural network algorithm to maximise the interests of enterprises. The particle swarm algorithm to lock the approximate location of the global optimum is first employed. Based on this, we establish an evaluation model of suppliers to train for the minimum errors between the desired and predicted values by constructing a back propagation (BP) neural network. Finally, the output results of the proposed method is compared with the BP neural network without the particle swarms optimisation. The proposed model is less empirically sensitive to the initialisation and can quickly converge to the local optimums, which overcomes the shortage of traditional neural networks and is more applicable to supplier evaluation.
Field strength prediction based on deep learning under small sample data
Authors: Zhou Min , Shao Wei , Liu Yang , Yang Xiaoqin 
Published: September 2022

AbstractThe accurate prediction of radio wave propagation is extremely important for wireless network planning and optimization. However, inexact matching between the traditional empirical model and actual propagation environments, as well as the insufficiency of the sample data required for training a deep learning model, lead to unsatisfactory prediction results. This paper proposes a field strength prediction model based on a deep neural network that is aimed at a tiny dataset composed of the geographic information and corresponding satellite images of a target area. This model connects two pretrained networks to minimize the parameters to be learned. Simultaneously, a convolutional neural network (CNN) model is constructed for comparison based on a previous advanced study in this field. Experimental results show that the proposed model can obtain the same accuracy as that of previously developed CNN models while requiring less data.
Coordinated suppression commutation torque ripple for brushless DC motor with commutation time
Authors: Wan Zhongxin , Huang Song , Zeng Chong , Liao Yong 
Published: September 2022

AbstractA commutation torque ripple suppression strategy for the brushless DC motor (BLDCM) with commutation time is proposed. First, a torque model considering back electromotive force (back‐EMF) variation is presented, and the cause of commutation torque ripple is analysed. The results show that the commutation torque ripple of BLDCM is inevitable even if the non‐commutation current remains steady. On this basis, the influence and quantitative relationships of non‐commutation current and commutation time on commutation torque ripple are studied. Furthermore, two impact factors are proposed to comprehensively consider their effects on commutation torque ripple. The three‐phase windings are modulated in the commutation process at individual duty cycles. The comprehensive optimisation index of commutation torque ripple for different working conditions is obtained by calculating the relative relationship of the impact factors. The optimisation index determines the proper modulation duty cycles. Therefore, the motor parameters and working conditions do not limit the strategy. Finally, the experimental results verify the correctness of the theoretical analysis and the feasibility of the proposed strategy. The proposed strategy can reduce the commutation torque ripple by 16.28% and 21.80% and shorten the commutation time by 50.00% and 36.67% at low speed and high speed, respectively, compared with the conventional strategy.
Salient object detection based on edge‐interior feature fusion
Authors: Shi Yadi , Qin Guihe , Liang Yanhua , Wang Xinchao , Yan Jie , Zhang Zhonghan 
Published: September 2022

AbstractRecently, existing FCNs‐based methods have shown their advantages in processing object boundaries. However, these methods still suffer from false object interference, which appears in saliency predictions. To solve this problem, an edge‐interior feature fusion (EIFF) framework is proposed, which consists of an internal‐boundary decoupled generation structure with receptive field enlargement and attention mechanism enhancement, and a salient feature refinement module. Specifically, the framework first learns edge features and interior features through an internal‐boundary decoupling generation network, which is supervised by labels obtained by decoupling ground‐truth through an image erosion algorithm. Then, feature refinement module (FRM) is designed to purify the coarse prediction by focusing on the ambiguous regions through a mining strategy to generate the final saliency map. To compensate for shortcomings of the BCE and IU loss, we also introduce a weighted loss to guide our model to focus more on the error‐prone parts. Experimental results on five benchmark datasets demonstrate that the proposed method performs favorably against 19 state‐of‐the‐art approaches under four standard metrics.
Insulator fault feature extraction system of substation equipment based on machine vision
Authors: Jiang Keruo , Xia Qiaoqun , Ma Lijun , Xu Xin , Shao Zhipeng 
Published: September 2022

AbstractThe artificial intelligence technology and intelligent automation are more and more widely used, the insulators play a supporting and insulating role in the operation of the grid. The use of machine vision inspection technology to detect insulator faults has become an inevitable trend of the times. In this study, based on BP neural network, the fault feature extraction system of substation insulator is studied, and then the system has some shortcomings in target detection algorithm. It then introduced two target detection algorithms, YOLOv3 and Canny, to improve the system. This study then analyses and compares the various indicators. It also analyses some external interference factors that exist when detecting insulator faults. It then further analyses the slenderness ratio of the smallest circumscribed rectangle of the insulator and the background region and the duty cycle of the insulator and the background region. The experimental results show that the recognition rates of both YOLOv3 and Canny target detection algorithms are around 90%. In this study, the influence of external factors is considered, and the fault features are further introduced, so that the true positive rate and accuracy of the algorithm have been improved.
Remote sensing image semantic segmentation network based on ENet
Authors: Wang Yiqin 
Published: September 2022

AbstractThe current image semantic segmentation methods cannot meet the requirements of high precision and high speed for remote sensing image analysis. The ENet network model builds a semantic segmentation network, which has the characteristics of few network parameters and fast operation speed. The attention mechanism module is integrated with the ENet network model, which can deeply mine image features in remote sensing datasets and ensure the accuracy of semantic segmentation. The author combines the ENet network with the attention mechanism to construct a new semantic segmentation network model. The model first constructed a remote sensing image semantic segmentation network model based on the ENet network, and simplified the model to further improve the speed of image segmentation and recognition. Then, the attention mechanism module is fused with the ENet network model, which can conduct deep and orderly mining of the image features of the remote sensing image data set. It can meet the accuracy requirements of remote sensing image semantic analysis. Simulations are performed based on three general datasets, and the experimental results show high accuracy and high speed.
Direct-retrograde orbit flips at planetary close encounters
Authors: Valsecchi G. B. , Rickman H. , Morbidelli A. , Wiśniowski T. , Gabryszewski R. , Wajer P. 
Published: September 2022

Aims. We want to find the conditions under which planetary close encounters transform the orbits of small Solar System bodies from direct to retrograde, and vice versa.
Methods. We derive analytical constraints on the orbital elements of the small body that allow direct-retrograde transitions at close encounters. We check the validity of the analytical constraints with numerical integrations of close encounters in the restricted, circular, three-dimensional three-body problem.
Results. For bound orbits, inclination flips at close encounters are possible only for values of the Tisserand parameter, computed with respect to the planet actually encountered, which are within certain limits. We give an analytical expression for the probability per revolution of this transition, as function of the orbital parameters. We show how to identify, among the known asteroids and comets on direct orbits, those that can flip to retrograde motion due to an encounter with an outer planet.
Conclusions. Inclination flips at planetary close encounters can be quantitatively characterized with the analytical theory of close encounters.