bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multiple vehicle cooperation and collision avoidance in automated vehicles: survey and an AI-enabled conceptual framework
Authors: Muzahid Abu Jafar Md , Kamarulzaman Syafiq Fauzi , Rahman Md Arafatur , Murad Saydul Akbar , Kamal Md Abdus Samad , Alenezi Ali H 
Published: January 2023

AbstractProspective customers are becoming more concerned about safety and comfort as the automobile industry swings toward automated vehicles (AVs). A comprehensive evaluation of recent AVs collision data indicates that modern automated driving systems are prone to rear-end collisions, usually leading to multiple-vehicle collisions. Moreover, most investigations into severe traffic conditions are confined to single-vehicle collisions. This work reviewed diverse techniques of existing literature to provide planning procedures for multiple vehicle cooperation and collision avoidance (MVCCA) strategies in AVs while also considering their performance and social impact viewpoints. Firstly, we investigate and tabulate the existing MVCCA techniques associated with single-vehicle collision avoidance perspectives. Then, current achievements are extensively evaluated, challenges and flows are identified, and remedies are intelligently formed to exploit a taxonomy. This paper also aims to give readers an AI-enabled conceptual framework and a decision-making model with a concrete structure of the training network settings to bridge the gaps between current investigations. These findings are intended to shed insight into the benefits of the greater efficiency of AVs set-up for academics and policymakers. Lastly, the open research issues discussed in this survey will pave the way for the actual implementation of driverless automated traffic systems.
Neural decoding of music from the EEG
Authors: Daly Ian 
Published: January 2023

AbstractNeural decoding models can be used to decode neural representations of visual, acoustic, or semantic information. Recent studies have demonstrated neural decoders that are able to decode accoustic information from a variety of neural signal types including electrocortiography (ECoG) and the electroencephalogram (EEG). In this study we explore how functional magnetic resonance imaging (fMRI) can be combined with EEG to develop an accoustic decoder. Specifically, we first used a joint EEG-fMRI paradigm to record brain activity while participants listened to music. We then used fMRI-informed EEG source localisation and a bi-directional long-term short term deep learning network to first extract neural information from the EEG related to music listening and then to decode and reconstruct the individual pieces of music an individual was listening to. We further validated our decoding model by evaluating its performance on a separate dataset of EEG-only recordings. We were able to reconstruct music, via our fMRI-informed EEG source analysis approach, with a mean rank accuracy of 71.8% ($$n~=~18$$

n

=

18

, $$p~<~0.05$$

p

<

0.05

). Using only EEG data, without participant specific fMRI-informed source analysis, we were able to identify the music a participant was listening to with a mean rank accuracy of 59.2% ($$n~=~19$$

n

=

19

, $$p~<~0.05$$

p

<

0.05

). This demonstrates that our decoding model may use fMRI-informed source analysis to aid EEG based decoding and reconstruction of acoustic information from brain activity and makes a step towards building EEG-based neural decoders for other complex information domains such as other acoustic, visual, or semantic information.
Realizing acoustic qubit analogues with nonlinearly tunable phi-bits in externally driven coupled acoustic waveguides
Authors: Deymier P. A. , Runge K. , Hasan M. A. , Lata T. D. , Levine J. A. , Cutillas P. 
Published: January 2023

AbstractUsing experiments and theory, we investigate the behavior of nonlinear acoustic modes in a physical system composed of an array of three coupled acoustic waveguides, two of which are externally driven with two different frequencies. Nonlinear modes with frequency given by linear combinations of the driving frequencies are realizations of so-called logical phi-bits. A phi-bit is a two-state degree of freedom of an acoustic wave, which can be in a coherent superposition of states with complex amplitude coefficients, i.e., a qubit analogue. We demonstrate experimentally that phi-bit modes are supported in the array of waveguides. Using perturbation theory, we show that phi-bits may result from the intrinsic nonlinearity of the material used to couple the waveguides. We have also isolated possible effects on phi-bit states associated with the systems’ electronics, transducers and ultrasonic coupling agents used to probe the array and that may introduce extrinsic nonlinearities. These extrinsic effects are shown to be easily separable from the intrinsic behavior. The intrinsic behavior includes sharp jumps in phi-bit phases occurring over very narrow ranges of driving frequency. These jumps may also exhibit hysteretic behavior dependent on the direction of driving frequency tuning. The intrinsic states of phi-bits and multiple nonlinearly correlated phi-bits may serve as foundation for robust and practical quantum-analogue information technologies.
Intended cycling frequency and the role of happiness and environmental friendliness after COVID-19
Authors: Barbour Natalia , Mannering Fred 
Published: January 2023

AbstractAlthough the COVID-19 pandemic has contributed to an increase in cycling in many countries worldwide, it is not yet known whether this increase becomes a long-lasting change in mobility. The current study explores this increase by analyzing data collected in a U.S. nationwide longitudinal survey. Using a total of 7421 observations, a mixed logit model with heterogeneity in the means of random parameters was estimated. In the resulting sample, nearly 14 percent of the respondents stated that they were planning to cycle more while only 4 percent of the respondents stated that they were planning to cycle less post COVID-19 pandemic. The estimation results provide insights into socio-demographic and psychological factors that play a role in planned cycling behavior post COVID-19. The study also establishes that age, race, employment status, gender, and household size impact intended cycling frequency. The model estimation results further indicate that workers (full time and part time), individuals with a high degree of life satisfaction, and individuals who are environmentally friendly all have higher cycling-frequency probabilities relative to others. The findings can be used to support policies that target sustainable mobility and further our understanding of the transportation, psychology, and well-being relationships.
Imaging and seismic modelling inside volcanoes using machine learning
Authors: O’Brien Gareth Shane , Bean Christopher J. , Meiland Hugo , Witte Philipp 
Published: January 2023

AbstractDespite advances in seismology and computing, the ability to image subsurface volcanic environments is poor, limiting our understanding of the overall workings of volcanic systems. This is related to substantive structural heterogeneities which strongly scatters seismic waves obscuring the ballistic arrivals normally used in seismology for wave velocity determination. Here we address this constraint by, using a deep learning approach, a Fourier neural operator (FNO), to model and invert seismic signals in volcanic settings. The FNO is trained using 40,000+ simulations of elastic wave propagation through complex volcano models, and includes the full scattered wavefield. Once trained, the forward network is used to predict elastic wave propagation and is shown to accurately reproduce the seismic wavefield. The FNO is also trained to predict heterogeneous velocity models given a limited set of input seismograms. It is shown to capture details of the complex velocity structure that lie far outside the ability of current methods available in volcano imagery.
Automatic segmentation of bladder cancer on MRI using a convolutional neural network and reproducibility of radiomics features: a two-center study
Authors: Moribata Yusaku , Kurata Yasuhisa , Nishio Mizuho , Kido Aki , Otani Satoshi , Himoto Yuki , Nishio Naoko , Furuta Akihiro , Onishi Hiroyuki , Masui Kimihiko , Kobayashi Takashi , Nakamoto Yuji 
Published: January 2023

AbstractThis study aimed to develop a versatile automatic segmentation model of bladder cancer (BC) on MRI using a convolutional neural network and investigate the robustness of radiomics features automatically extracted from apparent diffusion coefficient (ADC) maps. This two-center retrospective study used multi-vendor MR units and included 170 patients with BC, of whom 140 were assigned to training datasets for the modified U-net model with five-fold cross-validation and 30 to test datasets for assessment of segmentation performance and reproducibility of automatically extracted radiomics features. For model input data, diffusion-weighted images with b = 0 and 1000 s/mm2, ADC maps, and multi-sequence images (b0-b1000-ADC maps) were used. Segmentation accuracy was compared between ours and existing models. The reproducibility of radiomics features on ADC maps was evaluated using intraclass correlation coefficient. The model with multi-sequence images achieved the highest Dice similarity coefficient (DSC) with five-fold cross-validation (mean DSC = 0.83 and 0.79 for the training and validation datasets, respectively). The median (interquartile range) DSC of the test dataset model was 0.81 (0.70–0.88). Radiomics features extracted from manually and automatically segmented BC exhibited good reproducibility. Thus, our U-net model performed highly accurate segmentation of BC, and radiomics features extracted from the automatic segmentation results exhibited high reproducibility.
Telerehab at Home: Mobile Tablet Technology for Patients With Poststroke Communication Deficits—A Pilot Feasibility Randomized Control Trial
Authors: Mallet Karen H. , Shamloul Rany M. , Lecompte-Collin Jacinthe , Winkel Jennifer , Donnelly Beth , Dowlatshahi Dar 
Published: January 2023

Purpose:
Poststroke communication deficits (PSCD) are common following stroke. Early and intensive speech and language therapy is recommended to maximize outcomes. We wanted to test the feasibility of providing telerehabilitation for patients with PSCD using mobile tablet-based technology to bridge the gap between acute stroke care and outpatient speech-language therapy (SLT) services.

Method:
This was a prospective, randomized, open-label, blinded end-point design. Patients were randomized to either the treatment arm (mobile tablet) or the control arm (standard of care). The study duration was either 8 weeks or when the patient was called to start outpatient SLT services, whichever occurred first. The primary outcome was feasibility, while secondary objective was to assess patient engagement and to explore improvement in communication ability.

Results:
We had a 38% recruitment rate, with a 100% retention rate for the treatment arm and a 50% retention rate for the control arm. Fifty percent of patients in the treatment arm adhered to the recommended 1 hr per day, whereas none of the control arm did. Patients were engaged in using the mobile tablet and feedback on the protocol was positive.

Conclusions:
SLT using telerehabilitation via mobile technology is feasible in the very early stages of acute stroke recovery. It is potentially an effective means of bridging the gap between discharge from the acute care setting to the start of outpatient SLT services. Our study supported proceeding to a clinical trial to assess efficacy of the intervention.

Supplemental Material:

https://doi.org/10.23641/asha.21844569
Partition decoupling model and method in power distribution network, part II: A novel partitioning optimisation operation method
Authors: Sheng Wanxing 
Published: January 2023

AbstractIn this study, a partition optimisation method for distribution network is proposed to realise decoupling coordination, which provides a research basis for optimising power flow and operation regulation. Firstly, a partition model of distribution network is established, in which the electrical distance, parallel computing efficiency, and operation stability indexes are considered at the same time; Secondly, the AHC algorithm is used to realise the automatic search partition of the distribution network, and the class spacing measurement factors of point‐to‐point, cluster‐to‐cluster are considered in this method. Finally, the Distributed Sequential Quadratic Programming for Distributed Generation (DSQP‐DG) is introduced, and the parallel decoupling coordination of the distribution network is realised by alternate iteration of its inner and outer layers.
User-Centered Design to Reduce Inappropriate Blood Transfusion Orders
Authors: Morse Brad , Anstett Tyler , Mistry Neelam , Porter Samuel , Pincus Sharon , Lin Chen-Tan , Novins-Montague Sylvie , Ho P. Michael 
Published: January 2023

Abstract
Background To improve blood transfusion practices, we applied user-centered design (UCD) to evaluate potential changes to blood transfusion orders.
Objectives The aim of the study is to build effective transfusion orders with different designs to improve guideline adherence.
Methods We developed three different versions of transfusion orders that varied how information was presented to clinicians ordering blood transfusions. We engaged 14 clinicians (residents, advanced practice providers [APPs], and attending physicians) from different specialties. We used the think aloud technique and rapid qualitative analysis to generate themes to incorporate into our modified orders.
Results Most end-users who participated in the semi-structured interviews preferred the interruptive alert design plus behavioral nudges (n = 8/14, 57%). The predominant rationale was that the in-line alert was not visually effective in capturing the end-user's attention, while the interruptive alert forced a brief stop in the workflow to consider the guidelines. All users supported the general improvements, though for different reasons, and as a result, the general improvements remained in the designs for the forthcoming trial.
Conclusion The user experience uncovered through the think aloud approach produced a clear and rich understanding of potentially confounding factors in the initial design of different intervention versions. Input from end-users guided the creation of all three designs so each was addressing human factors with parity, which ensured that the results of our study reflected differences in interruptive properties of the alerts and not differences in design.
Melatonin Treatment of Circadian Rhythm Sleep-Wake Disorder in Obese Children Affects the Brain-Derived Neurotrophic Factor Level
Authors: Huang Xuesong , Huang Ying , Hu Bing 
Published: January 2023

Abstract
Background Previous studies proved that the brain-derived neurotrophic factor (BDNF) is correlated with sleep regulation, yet how BDNF functions and reacts in the melatonin treatment of circadian rhythm sleep-wake disorder (CRSWD) among obese children remain enigmatic. Focusing on CRSWD in obese children, this study monitored their sleep efficiency and serum BDNF level changes during the treatment of melatonin.
Methods In total, 35 obese children diagnosed with CRSWD were included in this study and administrated melatonin (3 mg/night) for 3 months. Blood samples were collected 24 hours before and after the treatment (08:00, 12:00, 16:00, 20:00, 24:00, and 04:00). Subsequently, the plasma melatonin level and serum BDNF level were measured by enzyme-linked immunosorbent assay. Sleep parameters, including sleep quality, Pittsburgh Sleep Quality Index as well as melatonin and BDNF levels before and after treatment, were recorded to profile the effectiveness and safety of melatonin treatment.
Results Melatonin treatment increased plasma melatonin concentration and restored circadian rhythm. Besides, the serum BDNF level showed a significant increase, representing a strong positive correlation with melatonin concentration (p = 0.026). Patients experienced much-improved sleep efficiency (P < 0.001), with longer actual sleep time (P < 0.001), shorter sleep onset latency, and fewer awakenings after treatment (P < 0.001). Besides, melatonin was well tolerated by patients without producing severe side effects.
Conclusion Melatonin treatment effectively improved CRSWD among obese children with their serum BDNF levels increased, indicating that BDNF is a key regulator in CRSWD in obese children. This study may offer theoretical support for melatonin treatment of CRSWD in obese children.
Intelligence artificielle et traduction
Authors: Cennamo Ilaria , de Faria Pires Loïc 
Published: January 2023

Résumé
S’il est vrai que « l’intelligence artificielle et les médias sociaux ont considérablement modifié notre rapport à
la communication en général et à la traduction en particulier » (EMT 2017, 2), il faut
pourtant constater que l’impact de ce nouveau paradigme de l’intelligence artificielle sur la formation universitaire et sur la
pratique professionnelle est loin de contribuer à une harmonisation des pratiques. Dans le cadre de cette contribution, nous
essaierons de développer une réflexion autour de la compétence traductive à l’ère de l’intelligence artificielle (IA) en vue de
déterminer la mesure dans laquelle la compétence traductive évolue actuellement dans le contexte de la formation universitaire et
celui de la traduction institutionnelle pour répondre aux nouveaux modes d’interaction avec les systèmes de traduction automatique
neuronale. Notre objectif est, en ce sens, de contribuer à l’identification des perspectives d’intégration de la traduction
automatique neuronale, dans le sens d’une convergence entre formation et profession. Dans un premier temps (cf. Sections 1 et 2), on se propose de définir ce que devient
la traduction à l’ère de l’intelligence artificielle, en accordant une attention particulière à l’acquisition des compétences
technologiques. Dans un deuxième temps (cf. Sections 3 et 4), ces compétences spécifiques seront mises en relation avec les pratiques professionnelles et notamment celles qui
caractérisent le flux de traduction de la direction générale de la traduction (DGT) de la Commission européenne. Les compétences
technologiques telles qu’elles ont été définies par le réseau européen des masters en traduction (EMT), dans le référentiel
élaboré en 2017 et adopté pour la période 2018–2024, seront utilisées ici pour appuyer
nos propos, dans le sens où ce référentiel constitue un pont entre la formation et la pratique professionnelle.
Racialized differences across experiences and measurements of pain in genitopelvic pain/penetration disorder
Authors: Azim Katharina A , Happel-Parkins Alison , Moses Amy , Haardoerfer Regine 
Published: January 2023

AbstractBackgroundDespite a growing body of research on genitopelvic pain/penetration disorder (GPPPD), few studies have examined racial and ethnic differences.AimThe goal of this study was to examine differences across racial groups pertaining to GPPPD with sexual vaginal intercourse in young college women at 2 public US universities.MethodsData were collected from 1197 students from 2 public US universities. We limited our sample to 667 sexually active participants aged ≥18 years (mean, 19.21). Participants responded to survey items on their sexual history, wellness, and practices and to the Female Sexual Function Index. Data were analyzed through standard bivariate and regression analyses.OutcomesParticipants were asked, “In general, do you feel pain with sexual intercourse?” and categorized into 1 of 3 pain groups: occasional (10%-25% of the time), frequent (≥50%), and no pain (&lt;10%).ResultsGPPPD was prevalent among young college women, with 162 (24.3%) reporting pain occasionally, 119 (17.8%) frequently, and 386 (57.9%) never or very seldom. While there were no differences in pain between Latina and non-Latina participants, our analysis indicated that pain was significantly higher among all other minoritized racial groups as compared with White women but particularly high in Black women, who had 2.15-higher odds of reporting pain than White women. Differences persisted when adjusting for socioeconomic status. Specific descriptors for pain sensation were more aligned with traditional descriptors of GPPPD (eg, burning, stinging, cramping, and pinching) in the White sample than among participants of color. Pain intensity did not differ among racial groups. We also found that a significant number of participants, particularly Black women, reported experiencing painful sex occasionally. No differences were noted across racial groups when assessing sexual function with the Female Sexual Function Index.Clinical ImplicationsExisting surveys and physician intake forms should be critically examined for usability with patients of color. As evidenced, Black women’s GPPPD seems to go underdetected/undetected by current measures.Strengths and LimitationsThis study is the first to explicitly compare racial differences among adolescents/young adults. The most notable limitation is the reliance on participant self-report and the absence of gynecologic examination to determine pain-contributing etiologies.ConclusionPainful intercourse affects young Black women at a higher rate than White women. Further research is needed into categories and metrics that capture their experiences of pain.
Predictors of female sexual problems in Shanxi, China: a population-based cross-sectional epidemiologic survey
Authors: Yuan Duo , Zhang Xian-hui , Pan Jie , Zhang Ying-an , Li Zhao-ai , Li Xiao-li 
Published: January 2023

AbstractBackgroundLarge studies on female sexual function have been conducted globally. Nonetheless, whether the state of female sexual function in China is significantly different from that in the rest of the world is largely unknown.AimIn this study, we aimed to investigate the associated risk factors for sexual problems in women in Shanxi, China, by conducting a population-based cross-sectional epidemiological survey.MethodsUsing the Chinese version of the Female Sexual Function Index (CV-FSFI), we surveyed women aged 20-70 years to diagnose the sexual problems. We used multiple linear regression models to estimate the risk factors for sexual problems.OutcomesWe used the CV-FSFI for investigating the female sexual function.ResultsOur results included 6720 women, of whom 1205 were the sexually inactive and 5515 were sexually active. The mean FSFI score for sexually active women was 25.38 ± 4.20 (99% CI 25.27-25.49). Negative numerical coefficients were found for model predictors of age (B = −0.134, P &lt; 0.001), postmenopausal status (B = −2.250, P &lt; 0.001), chronic diseases (B = −0.512, P &lt; 0.001), and gynecologic diseases (B = −0.767, P &lt; 0.001). In contrast, positive numerical coefficients were found for education (B = 0.466, P &lt; 0.001) and cesarean section (B = 0.312, P = 0.009).Clinical ImplicationsIt is important to pay attention to the sexual health of women and explore the factors influencing the sexual problems of women in China.Strengths and LimitationsThe present study is to our knowledge the first to evaluate the sexual function of women in Shanxi, China. Answers to questions asked in the CV-FSFI survey may be somewhat subjective, and thus additional tools and documentation are probably needed for accurate assessment.ConclusionSimilarly to other worldwide studies, our study found that increasing age, postmenopausal status, chronic diseases, and gynecological diseases were risk factors for sexual problems, whereas high education levels and cesarean section childbirth were protective factors for sexual problems.