bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multiple Vehicle Cooperation and Collision Avoidance in Automated Vehicles: Survey and an AI-Enabled Conceptual Framework
Authors: Muza Abu Jafar Md , Kamarulzaman Syafiq Fauzi , Rahman Md Arafatur , Murad Saydul Akbar , Kamal Md Abdus Samad , Alenezi Ali H 
Published: June 2022

Abstract
Prospective 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 a AI-enable conceptual framework, 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 on the benefits of the greater efficiency of AVs set-up for academics and policymakers. Finally, the open research issues discussed in this article will pave the way for the actual implementation of driver-less automated traffic systems.
Development and influencing factors of ophthalmology residency training in a program in China--an analysis of a 360-degree evaluation results in the past 5 years
Authors: Sun Yaoyao , Zhang Qin , Zeng Qingqi , Liu Jing , Wu Huijuan , Huang Lvzhen , Peng Zisu , Qi Huijun , Bao Yongzhen , Li Xiaoxin , Palis Gabriela , Zhao Mingwei 
Published: June 2022

Abstract
Background
To explore the development of ophthalmology residents and the factors that influence resident performance in China with a 360-degree evaluation.
Methods
59 residents enrolled in the resident training system at Peking University People's Hospital were evaluated by a 360-degree evaluation system created by the Chinese Medical Doctor Association (CMDA) from July 2017 to September 2021. All residents were required to complete a 3-year training program. An online evaluation questionnaire was applied and resident's entire score was added together and transformed to a percentage system. The data was statistically analyzed with T-paired test and multiple linear regression analysis to determine the changes of resident’ evaluation results and the potential influencing factors on the residents' grades.
Results
A total of 364 evaluations for 59 residents and 20 instructors were conducted. By September 2021, a total of 28 residents had finished the program, with another 31 in the process. There was generally positive trend in performance ratings. In years 1, 2, and 3, the average scores were 82.67 ± 8.26, 89.85 ± 6.03, and 91.77 ± 4.03, respectively. There is a substantial difference in average scores between year 1 and year 2 (P = 0.000) but not between year 2 and 3 (P > 0.05). Residents' average clinical skills scores are 45.08 ± 3.36, 50.34 ± 4.95, and 51.06 ± 5.51 and non-clinical skills scores are 37.55 ± 3.42, 38.16 ± 5.07, and 38.93 ± 3.19 by the end of year 1, 2, and 3, respectively. There was a significant improvement in residents' clinical skills in the first year compared to the second year (P = 0.003) but not between the second and third year (P > 0.05). There was no significant improvement of non-clinical skills regardless of the year. Educational background, rather than other characteristics, had the biggest impact on residents’ achievement in the first and second years of training.
Conclusion
Ophthalmology residents' performance improved significantly from the first to the second year, after which they reached a plateau. Different education backgrounds had the greatest impact on their first-year performance. Additional attention should be devoted to senior residents and residents with inferior educational backgrounds.
A nomogram based on clinicopathologic characteristics and pretreatment systemic inflammation response index to predict pathological complete response of neoadjuvant systemic therapy in HER2-positive breast cancer: A dual-center study
Authors: Wu Hong-Yu , Tzeng Yen-Dun , Hung Chih-Chiang , Liu Shiuh-Inn , Yin Chun-Hao , Chen Jin-Shuen , Chen Yao-Shen , Yang Jie-Ru 
Published: June 2022

Abstract
Purpose:
Multiple pretreatment systemic inflammatory markers (SIMs) have been reported as predictors of pathological complete response (pCR) after neoadjuvant systemic therapy (NST) in patients with breast cancer (BC). However, the most significant SIM remains to be conclusively identified, and variations among different molecular subtypes remain unknown. The objective of the study was to identify the most significant SIM in patients with human epidermal growth factor receptor 2 (HER2) positive BC, and to construct a pCR-predictive nomogram combining it with other clinicopathological factors.
Methods:
We retrospectively reviewed the findings for 240 patients with stage I–III HER2-positive BC who underwent NST and subsequent surgery at Kaohsiung and Taichung Veterans General Hospital from 2011 to 2021. Clinicopathological factors were analyzed by stepwise logistic regression with forward selection. The data were used to construct a nomogram plot for determining the probability of pCR.
Results:
Among the pretreatment SIMs, only SIRI was significantly related to pCR, with an optimal cutoff value of 1.27 × 109/L. Stepwise logistic analyses indicated that clinical N stage, HER2 immunohistochemistry (IHC) score, hormone receptor status, targeted therapy regimen, and SIRI were independent predictors of pCR, with an area under the curve (AUC) of 0.722. The Hosmer–Lemeshow test and calibration curve revealed that the predictive ability was a good fit to actual observations. A nomogram was constructed based on the logistic model.
Conclusions:
Pretreatment SIRI < 1.27 is predictive of pCR in HER2-positive BC. Our nomogram could efficiently predict pCR and facilitate clinical decision-making before neoadjuvant treatment.
Identification and Validation of a Novel Prognostic Model Based on Platinum Resistance-Related Genes in Bladder Cancer
Authors: Hao Yining , Wang Chenghe , Xu Danfeng 
Published: June 2022

Abstract
Background: Bladder cancer (BC) is a heterogeneous disease with high recurrence rate. The depth of response to platinum-based chemotherapeutic agents in urothelial neoplasm tissues varies greatly. Biomarkers that have practical value in prognosis stratification and early determination of therapeutic effect are increasingly needed. Our study aimed to select a set of BC-related genes involved in both platinum resistance and survival, then use these genes to establish the prognostic model.Methods: Platinum resistance-related DEGs and tumorigenesis-related DEGs were identified. Among the intersection of them, 10 most predictive genes were acquired through Cox, lasso, and stepwise regressions followed by building a risk score model with their regression coefficients. Survival analysis and ROC plot were used to evaluate the predictive accuracy of our model. Combined with age and TMN stages, a nomogram was generated to create a graphical representation of survival rates at 1-, 3-, 5-, and 8-year in BC patients. The prognostic performance of risk score was also validated in three independent BC datasets including cisplatin-treated patients and a gastric cancer cohort with platinum-based chemotherapy. The potential mechanism of the gene-based model was explored by enrichment analysis.Results: PPP2R2B, TSPAN7, ATAD3C, SYT15, SAPCD1, AKR1B1, TCHH, AKAP12, AGLN3, and IGF2 were selected for our prognostic model. Patients in high- and low-risk groups exhibited a significant survival difference (HR = 2.7, p < 0.0001). The prognostic nomogram of predicting 3-year OS for BC patients could yield an AUC of 0.819. In the external validation dataset, the risk score also has a robust predictive ability. Conclusion: A prognostic model derived from platinum resistance-related genes was constructed, we confirmed its value in predicting platinum-based chemotherapy benefits and overall survival for BC patients. The model might assist in therapeutic decisions for bladder malignancy.Subjects: Urology, Oncology, Bioinformatics, Molecular Biology.
An Effective Hybrid Deep Learning Technique for Covid-19 Detection Using InceptionV3 and optimized Squeeze Net
Authors: B Srinivasarao , B Raviteja ,   Dr. Saichandana1 B, J Harikiran 
Published: June 2022

Abstract

Covid-19 is a virus that affects both animals and people and is quickly expanding. This deadly illness affects people's daily lives, health, and economy. The most significant imaging methods for detecting COVID-19 are a computed tomography (CT) scan and chest X-ray. For this epidemic, all researchers are striving for efficient solutions and quick treatment approaches. Fast and accurate automated detection approaches have been introduced to eliminate the requirement for medical professionals. This work proposes an efficient SqueezeNet for Covid classification to solve this challenge. Inception V3 is employed to extract some of the most important features. SqueezeNet is optimized by Deer Hunt Optimization algorithm (DHO) to improve the performance. From chest x-ray images, a multi-classification DL approach for diagnosing COVID-19, pneumonia, normal, and tuberculosis is proposed. The proposed categorization strategy is implemented in Python and compared to other approaches. In terms of f1-score, sensitivity, specificity, and accuracy experiments have shown that the proposed method outperforms other recent and state-of-the-art methodologies.
Nanopore ion sources deliver single amino acid and peptide ions directly into high vacuum
Authors: Drachman Nicholas , Lepoitevin Mathilde , Szapary Hannah , Wiener Benjamin , Maulbetsch William , Stein Derek 
Published: June 2022

Abstract

We report a nanopore ion source for mass spectrometry that delivers ions directly into high vacuum from aqueous solutions.
The ion source comprises a pulled quartz capillary with a sub-100~nm opening. Ions escape an electrified meniscus between the liquid and high vacuum by ion evaporation and travel along collisionless trajectories to the ion detector. We measure mass spectra of 16 different amino acid ions as well as post-translationally modified variants of glutathione in unsolvated states using the nanopore ion source. The emitted current is composed of ions rather than charged droplets, and more than 90% of the current can be recovered in a distant collector. The nanopore ion source could enable more sensitive proteomic analyses. It circumvents the sample loss mechanisms inherent to conventional electrospray ionization (ESI), where charged droplets are sprayed into a background gas that scatters ions and degrades their transmission.
Hemosuccus pancreaticus as an unusual cause of upper gastrointestinal bleeding: Case report and literature review
Authors: Ayala Daniela , T. Juliana González , Pedroza Felipe , M. Ana M. Gonzalez , Chaves Carlos Eduardo Rey , Acosta Mauricio , Conde Danny , Olarte Juan Carlos Sabogal 
Published: June 2022

Abstract

Background: Hemosuccus pancreaticus is a rare cause of upper gastrointestinal bleeding (1/1500) and represents the loss of blood through the main pancreatic duct and its exteriorization through the major duodenal papilla. It can lead to massive bleeding, which is potentially life-threatening. This condition most commonly follows pseudoaneurysm formation secondary to acute or chronic pancreatitis. As a result of its infrequency, it is difficult to diagnose, and the mortality rate remains high. To our knowledge this is the first case report of Latin-American population. Case presentation: A 70-year-old male patient presented with diffuse severe abdominal pain associated with melenas. Angiotomography was performed, ruling out mesenteric ischemia, with evidence of pancreatic head tumor with liver metastases. Sandblom's triad was present and the diagnosis of hemosuccus pancreaticus was confirmed. Multiple arteriograms were performed, with pseudoaneurysm of gastroduodenal artery findings. Therefore, endovascular coil embolization was performed in two opportunities to control the bleeding. Conclusion: Upper gastrointestinal bleeding is a clinical challenge for the surgeon and emergency medicine. It’s a complex entity with high mortality that should be suspected in patients with acute or chronic pancreatitis and periampullary tumors with non-established sources of bleeding. Clinically manifested by Sandblom's triad. Its diagnosis gold standard is the arteriography plus embolization which is also therapeutic. Surgery is related to higher mortality and reserved for specific situations.
Who should do as AI say? Only non-task expert physicians benefit from correct explainable AI advice
Authors: Gaube Susanne , Suresh Harini , Raue Martina , Lermer Eva , Koch Timo , Hudecek Matthias , Ackery Alun D. , Grover Samir C. , Coughlin Joseph F. , Frey Dieter , Kitamura Felipe , Ghassemi Marzyeh , Colak Errol 
Published: June 2022

Abstract
Artificial intelligence (AI)-generated clinical advice is becoming more prevalent in healthcare. However, the impact of AI-generated advice on physicians’ decision-making is underexplored. In this study, physicians received X-rays with correct diagnostic advice and were asked to make a diagnosis, rate the advice’s quality, and judge their own confidence. We manipulated whether the advice came with or without a visual annotation on the X-rays and whether it was labeled as coming from an AI or a human radiologist. Overall, receiving annotated advice from an AI resulted in the highest diagnostic accuracy. Physicians rated the quality of AI advice higher than human advice. Neither manipulation had strong effects on participants’ confidence. Importantly, the results varied among task experts and non-task experts, with only the latter considerably benefiting from correct explainable AI advice. These findings raise important considerations for the deployment of diagnostic advice in healthcare.
Optical Image Guided Multi-scale Learning for Synthetic Aperture Radar Image Super-resolution
Authors: Li Yanshan , Xu Fan , Zhou Li 
Published: June 2022

Abstract
Synthetic Aperture Radar (SAR) image Super-Resolution (SR) has various application including military reconnaissance and marine monitoring. Comparing with other natural images, the SAR images suffer from lower spatial resolution and less amplitude information, which provide insufficient information for SAR image reconstruction. Therefore, current SAR image SR methods show worse performance. In this paper, considering optical images have higher resolution and richer texture information, we propose a multi-scale learning based optical image guidance network (MLOG) to make good use of high-resolution (HR) optical image for SAR image SR. Specifically, we design an optical image weighted guidance network (OWG) to get more discriminative feature and reduce the impact of the lack of detailed information in LR SAR images. Then a multi-scale learning network (MLN) is proposed to obtain the global features from optical image. After that, a residual multi-scale block (RMB) is introduced to extract the global multi-scale context information. Finally, the extracted multi-scale features are reconstructed to generate high-resolution SAR images through a convolutional reconstruction layer. The experimental results show that the proposed MLOG method achieves state-of-the-art performance for SAR image SR on public available datasets.
Influence of AI-assisted motion correction algorithm (CardioCapture) on the correlation between HR and optimal reconstruction phase
Authors: Yin Wei , Xu Ruimin , Jia Zijun , Zhao Binghui , Lu Jianping , Shao Chengwei , Liu Shuilian , Wang Minjie 
Published: June 2022

Abstract
Background: The best suitable candidates for scanning mode and reconstruction phase according to the heart rate in coronary CTA. while the heart rate threshold depends on the hardware of the CT scanner. This study aims to find the heart rate threshold of CCTA using the latest CT scanner with AI-assisted motion correction algorithm(CardioCapture).Methods: All cases were examined from April 2021 to September 2021. two experienced radiologists scored these images on a four-point Likert scale. Images quality below three-point were reconstructed by CardioCapture. All images were divided into eight groups according to HR (at an interval of 5 bpm). The subjective score of images, the frequency of used CardioCapture and the proportion of diastolic reconstruction phase were compared in each group. The relationship between HR and the diastolic reconstruction phase was analyzed by the receiver operator characteristic curve(ROC).Result: The data of 515 patients were studied. With an increase in HR, the subjective image score decreased, the frequency of CardioCapture increased, and the phase ratio of diastolic reconstruction decreased. When the HR was less than 70 bpm, the percentage of excellence image in each group was more than 94.90%. The highest frequency of CardioCapture was 65.22%, and the lowest proportion of diastolic reconstruction was 72.46%. The best cut-off point between HR and the diastolic reconstruction ROC curve in the groups without CardioCapture was 65 bpm, while that in groups with CardioCapture was 68 bpm. Conclusion: The CardioCapture can effectively improve the image quality of CCTA with high HR. Keeping the HR below 68bpm and adopting the prospective ECG-gated narrow phase axial scan can ensure the image quality and reduce the radiation dose simultaneously.
Adaptive fixed-time fault-tolerant control of interconnected non-affine systems with full-state constraints.
Authors: Bai Wen , Liu Peter Xiaoping , Wang Huanqing 
Published: June 2022

Abstract
In this paper, the constrained control problem is considered for nonlinear interconnected non-affine systems with actuator faults. On the basis of the backstepping design framework, an adaptive controller is developed to deal with unknown items and the non-affine appearance by using neural networks and the mean value theorem. In an attempt to avert the constraint violation, the difficulties brought by the emergence of full state constraints can be eased by selecting an appropriate barrier Lyapunov function. A fault-tolerant controller is designed to handle actuator faults, involving stuck constant value and loss of effectiveness. The fixed time controller is designed to ensure that all the signals of the closed-loop system can maintain semi-globally stable. The simulation results show that the developed controller is effective for targeted nonlinear systems.
Assessment of Genetic Diversity of a Critically Endangered Species, Centaurea amaena (Asteraceae)
Authors: ATASAGUN Bayram 
Published: June 2022

Abstract
Centaurea amaena is an endemic and endangered species and listed as CR in Turkey. ISSR markers were used to detect the level of genetic diversity in two natural populations of C. amaena. A total of 50 ISSR primers were used and 13 primers producing polymorphic and reproducible products were selected. These primers yielded 102 amplified discernible loci, of which 80 (78%) were polymorphic. A high level of genetic diversity was detected both at population and species levels; the effective number of alleles (Ne) was 1.544, the observed number of alleles (Na) was 1.784, the Nei’s genetic diversity (H) was 0.306, and Shannon's information index was 0.447. The determined gene flow (Nm) was 2.329, indicating a high migration rate between the populations. Moderate level of genetic differentiation (GST: 0.176) was also observed. Analysis of molecular variance (AMOVA) revealed that 24.89% of the total genetic diversity resided among populations, while 75.10% within the populations. Cluster analysis showed that samples from the same locality clustered together and there was no cross-clustering between the samples. The patterns of genetic variation indicates that existing C. amaena populations should be conserved.
Health care use attributable to COVID-19: A propensity matched national electronic health records cohort study of 249,390 people in Wales, UK.
Authors: Kennedy Jonathan , Parker Michael , Seaborne Michael , Mhereeg Mohamed , Walker Alex , Walker Venexia , Denaxas Spiros , Kennedy Natasha , Katikireddi Srinivasa , Brophy Sinead 
Published: June 2022

Abstract
Background: To determine the extent and nature of changes in infected patients’ healthcare utilization, we studied healthcare contact in the 1-4 weeks and 5-24 weeks following a COVID-19 diagnosis compared to propensity matched controls.Methods: Survival analysis was used for time to death and first clinical outcomes including clinical terminology concepts for post-viral illness, fatigue, embolism, respiratory conditions, mental and developmental conditions, fit note, or hospital attendance. Increased instantaneous risk for the occurrence of an outcome for positive individuals was quantified using hazard ratios (HR) from Cox Regression and absolute risk was quantified using relative risk (RR) from life table analysis.Results: Compared to matched individuals testing negative, surviving positive community-tested patients had a higher risk of post-viral illness (HR: 4.57, 95%CI: 1.77-11.80, p=0.002), fatigue (HR: 1.47, 95%CI: 1.24-1.75, p<0.001) and embolism (HR: 1.51, 95%CI: 1.13-2.02, p=0.005) at 5-24 weeks post-diagnosis. In the four weeks after COVID-19 higher rates of sick notes were being issued for community-tested (HR: 3.04, 95%CI: 0.88 to 10.50, p<0.079); the risk was reduced after four weeks, compared to controls. Overall healthcare attendance for anxiety, depression was less likely in those with COVID-19 in the first four weeks (HR: 0.83, 95%CI: 0.73-1.06, p=0.007). After four weeks, anxiety, depression is less likely to occur for the positive community-tested individuals (HR: 0.87, 95%CI: 0.77-1.00, p=0.048), but more likely for positive hospital-tested individuals (HR: 1.16, 95%CI: 1.00-1.45, p=0.053). Although statistical associations between positive infection and post-infection healthcare use are clear, the absolute use of healthcare is very.Conclusions: Community COVID-19 disease is associated with increased risks of post-viral illness, fatigue, embolism, depression, anxiety and respiratory conditions. Despite these elevated risks, the absolute healthcare burden is low. Either very small proportions of people experience adverse outcomes following COVID-19 or they are not presenting to healthcare.Trial registration: Data held in SAIL databank are anonymised and therefore, no ethical approval is required. All data in SAIL has the permission from the relevant Caldicott Guardian or Data Protection Officer and SAIL-related projects are required to obtain Information Governance Review Panel (IGRP) approval. The IGRP approval number for this study is 1259.