bluuebunny/crossref_metadata_2025_split huggingface dataset:
Throughput Enhancement of 3D Multi-hop Wireless Network Using Concurrent Transmission Group Based Scheduling and minimum angle Routing Technique
Authors: Begum Afruza , Hussain Md Anwar , Ask Sikdar Md S 
Published: December 2022

Abstract
Multi-hop wireless networks are designed to support long-distance, cost-effective communication with high data transfer rate. Maximizing network throughput is one of the critical goals while developing a multi-hop wireless network. Efficient routing and scheduling techniques enhance throughput and reduce delay, which improves the overall network performance. This paper proposes a transmission group-based routing and scheduling (𝑇𝐺𝑅𝑆) technique implemented in centralized and distributed ways. The main aim of this study is to enhance the performance of 3D multi-hop wireless networks in terms of throughput and delay. Users establish a routing path to the base station based on the minimum angle-based IM selection process. In 𝑇𝐺𝑅𝑆, multiple groups are formed for all the IM links of the routing path; links are included in the same group if they do not interfere mutually. All the links of a group are transmitted concurrently, which maximizes throughput and minimizes delay. The proposed 𝑇𝐺𝑅𝑆 technique dramatically improves network performance by increasing concurrent transmission and throughput. The effectiveness of the proposed techniques is demonstrated through extensive simulation.
Sociological and psychological factors related to prostate cancer screening of Chinese males over 40：a qualitative study
Authors: Hao Shutao , Zheng Jin , Ju Min , Sun Longfeng 
Published: December 2022

Abstract
Objective
Based on the theory of planned behavior, this qualitative study attempted to explore the influence of personal and social levels on prostate cancer screening behavior towards men over 40 years old.
Methods
Semi-structured interviews were conducted with 21 men over 40 (n = 21) in a health check-up center. The interviews were analyzed using the Collazzi's phenomenological method.
Results
57.14% respondents performed PSA test,but almost of them all belong to involuntary and non-autonomous screening. 70% respondents indicated they would screen prostate cancer according to doctors' recommendations. 50% respondents believed that screening should be performed after symptoms appear and emphasized the convenience of including items in the health check-up package. 10% respondents considered screening as an opportunity to obtain psycho-social support. In addition, cognitive impairment and cancer fatalism are obstacles. Of course, external economic conditions and access also have a definite impact.
Conclusion
This study provided a reference for understanding the complexity and uniqueness of influencing factors of prostate cancer screening willingness in China. As for potential challenges of insufficient prostate cancer screening in China, these findings also provide interventions that can be used to guide prostate cancer screening projects.
High-resolution and reliable automatic target recognition based on photonic ISAR imaging system with explainable deep learning
Authors: Zou Weiwen , Zou Xiuting , Deng Anyi , Hu Yiheng , Hua Shiyu , Zhang Linbo , Xu Shaofu 
Published: December 2022

Abstract
Automatic target recognition (ATR) based on inverse synthetic aperture radar (ISAR) images, which is extensively utilized to surveil environment in military and civil fields, must be high-precision and reliable. Photonic technologies’ advantage of broad bandwidth enables ISAR systems to realize high-resolution imaging, which is in favor of achieving high-performance ATR. Deep learning (DL) algorithms have achieved excellent recognition accuracies. However, the lack of interpretability of DL algorithms causes the head-scratching problem of credibility. In this paper, we exploit the inner relationship between a photonic ISAR imaging system and behaviors of a convolutional neural network (CNN) to deeply comprehend the intelligent recognition. Specifically, we manipulate imaging physical process and analyze the network outputs, the relevance between the ISAR image and network output, and the visualization of features in the network output layer. Consequently, the broader imaging bandwidths and appropriate imaging angles lead to more detailed structural and contour features and the bigger discrepancy among ISAR images of different targets, which contributes to the CNN recognizing and distinguishing objects according to physical laws. Then, based on the photonic ISAR imaging system and the explainable CNN, we accomplish a high-accuracy and reliable ATR. To the best of our knowledge, there is no precedent of explaining the DL algorithms by exploring the influence of the physical process of data generation on network behaviors. It is anticipated that this work can not only inspire the accomplishment of a high-performance ATR but also bring new insights to explore network behaviors and thus achieve better intelligence.
3D CSAMT Forward Modeling of Landslide Sliding Surfaces
Authors: Wang Ruo , Di Qingyun , Wang Miaoyue , Lei Da , Cao Wenjing 
Published: December 2022

Abstract
Landslides are natural disasters that cause significant harm to humans. Therefore, it is crucial to monitor and predict the initiation of landslides to reduce disaster-related and commercial losses. Herein, we used a finite element method to provide theoretical and technical support for applying Controlled Source Audio-frequency Magnetotellurics method to landslide exploration. We modeled a landslide sliding surface and analyzed the characteristics of its electromagnetic field and apparent resistivity. We found that the sliding surface can be recognized by the apparent resistivity rather than the total electromagnetic field. Additionally, the sliding surface can be clearly recognized using the pure anomaly electromagnetic field of the sliding surface, which is obtained by removing the response of the electromagnetic field of the landform from the total electromagnetic field. Based on our results, we discussed the survey parameters to be used, such as configuration (TM/TE mode), frequency range, and the length of the survey line, the suggestion parameter will provide instruction to the field work. This study shows that Controlled Source Audio-frequency Magnetotellurics method is a potentially effective method for landslide exploration.
Efficacy of silicone oil removal combined with intravitreal injection of triamcinolone acetonide in the treatment of macular edema in eyes filled with silicone oil
Authors: Ke Xixuan , Li Cuilian , Huang Yuqiang , Xia Honghe , Jin Chuang , Shi Tingkun , Cheng Yinglin , Liao Xulong , Zhang Qi , Chen Haoyu 
Published: December 2022

Abstract
Purpose
To investigate the efficacy of silicone oil removal combined with intravitreal injection of triamcinolone acetonide in treating macular edema in silicone oil eyes.
Methods
Retrospective analysis was performed on the patients with macular edema in eyes filled with silicone oil. The retinal detachment of each patient has been resolved for more than three months. Silicone oil was removed from each patient through pars plana trocar, and 2 mg triamcinolone acetonide suspension was injected into the vitreous cavity. The patients were followed up for at least three months. The best-corrected visual acuity (BCVA) and central foveal thickness (CFT) in each patient were compared with paired t-test.
Results
Twenty eyes of 20 patients were enrolled in this study and the mean follow-up time was 12.1 months. The mean BCVA improved from 1.08 ± 0.44 LogMAR before the operation to 0.61 ± 0.31 LogMAR at the final visit (P < 0.001). The mean CFT reduced from 478.95 ± 121.97 µm before the operation to 270.20 ± 135.35 µm at the final visit (P < 0.001). Four patients (20%) developed temporal high intraocular pressure (IOP), all of which could be treated with topical IOP-lowering drugs.
Conclusion
Silicon oil removal combined with intravitreal triamcinolone injection can effectively improve visual acuity and alleviate macular edema without severe complications in silicone oil eyes with macular edema.
A Traffic Flow Data Recovery Method Based on An Auxiliary Discrimination Mechanism-oriented GAN Model
Authors: Wang Can , Li Linheng , Yang Qiao , Jin Xiongwei , Qu Xu , Ran Bin 
Published: December 2022

Abstract
Traffic flow detection methods tend to be diversified and intelligent, and the data anomalies become a prominent problem due to the influence of equipment, network and environment. Recovering abnormal data to obtain complete and accurate traffic flow data is crucial for traffic flow research work. To address this issue, traditional and mainstream traffic flow data recovery methods require a large amount of complete historical traffic flow data as a priori information for learning the trend of traffic flow data. Large amount of complete historical traffic flow data is hard to obtain in real traffic scenarios because traffic flow data collection is always accompanied by data anomalies. In this paper, we analyze the causes of abnormal data, classify the types of abnormal data, and propose identification methods applicable to different types of abnormal data based on the collection principles of freeway multi-source traffic data. We propose an auxiliary discrimination mechanism-oriented generative adversarial network (ADM-GAN) model to overcome the difficulties of traffic flow data recovery. Different from previous studies, we develop an auxiliary discrimination matrix to increase the utilization of original data, enhance the recovery accuracy, and improve the computational efficiency. We evaluate our model under different data missing rates (10%, 20%, 30%, 40% and 50%) by manually introducing missingness to the actual traffic flow data on the G50 freeway near Suzhou, China. The experimental results show that the proposed model outperforms other comparative methods. Under different missing rates, the recovery results obtained by ADM-GAN method are better than those obtained by comparative methods, and the lower the missing rate, the more obvious the advantages.
A comparison between ARIMA, LSTM, ARIMA-LSTM and SSA for cross-border rail freight traffic forecasting: the case of Alpine-Western Balkan Rail Freight Corridor
Authors: Milenković Miloš , Gligorić Miloš , Bojović Nebojša , Gligorić Zoran 
Published: December 2022

AbstractExcessive delays of railway traffic at border crossing points as a consequence of poor planning of border crossing procedures lower the performance of train service, increase its cost and reduce the satisfaction of shippers. Mid-term prediction of traffic flows may improve the process of planning border-crossing activities. In this paper, we model the intensity of cross-border railway traffic on the Alpine-Western Balkan Rail Freight Corridor (AWB RFC). For each of the four border crossing points: Dimitrovgrad, Presevo, Sid and Subotica, time series composed of 102 monthly export and import railway freight traffic observations are used for training and testing of alternative forecasting models. Traditional ARIMA, Long-Short-Term Memory (LSTM) neural network, hybrid ARIMA-LSTM and Singular Spectrum Analysis (SSA) models, are fitted to each of the eight time series. To enable the practical applicability of the proposed approach the “Best fit forecast” tool is developed.
Neoadjuvent androgen deprivation for seminal vesicle reduction:The optimal portion of seminal vesicle included in the high-dose CTV in localized prostate cancer radiotherapy
Authors: Qi Xin , Gao Xian-Shu , Li Xiao-mei , Qin Shang-bin , Li Xiao-ying , Ma Ming-wei , Bai Yun , Chen Jia-yan , Ren Xue-ying , Li Hong-zhen 
Published: December 2022

Abstract
Purpose
It is indicated by prostatectomy specimens that the proximal 1- to 2-cm seminal vesicles (SVs) be irradiated in radiotherapy for prostate cancer with intermediate- to high-risk factors. However, patients usually receive neo-adjuvant hormonal therapy (NHT) before radiotherapy. The purpose of this study is to clarify the length and volume reduction of SVs after NHT, and to help contour the optimal SV included into high-dose clinical target volume (CTV) for radiotherapy in intermediate- and high-risk patients.
Methods and Materials:
MR images both before and after NHT (5.3 ± 2.2 months) were collected from thirty-one patients with cT2-4N0M0 prostate cancer. SV volume was measured in axial T1WI, while SV length was obtained in a reconstructed oblique coronary plane through its long axial from a 3D sequence.
Results
SVs showed evident reduction both in length and volume (length: median 12.1%, range 4.0–28.0%, volume: median 39.9%, range 9.4%-66.2%). For SVs with and without MR detected involvement, length shortening were 16.7 ± 4.8% and 11.1 ± 4.4% (P < 0.001); for involved SVs and lesions within, volume reduction were 41.0 ± 16.0% and 66.3 ± 14.4% (P < 0.001), both indicating a more sensitive response to NHT of the involved portion than normal SV.
Conclusion
Both volume and length of the SV will reduce after receiving NHT. Besides, the invaded segments shrink more than normal SV tissue, indicating that SV portion included within the CTV can be reduced.
Soil erosion susceptibility assessment of Swat River sub-watersheds using the morphometry-based compound factor approach and GIS
Authors: Nasir Muhammad Jamal , Ahmad Waqas , Jun Changhyun , Iqbal Javed 
Published: December 2022

Abstract
Watershed prioritization is essential in sub-watershed (SW) natural resource management. The Swat River watershed in the Hindukush mountains of Pakistan's Khyber Pakhtunkhwa province covers an area of 5337 km2. Using an Advanced Spaceborne Thermal Emission and Reflection Radiometer digital elevation model with a resolution of 30 m obtained from the United States Geological Survey (USGS), the present study identified 17 SWs (SW1–17) with drainage patterns ranging from dendritic to sub-dendritic in nature. The SWs were assessed for their susceptibility to erosion via GIS-based assessment using a morphometry-based compound factor (CF) approach. A total of 15 linear, aerial, and relief morphometric characteristics were identified and analyzed. The SWs were ranked for each morphometric parameter based on its contribution to the erodibility of the SW. A ranking of 1 indicated that the SW had the greatest susceptibility to erosion for that parameter and a ranking of 17 indicates that it had the lowest. These rankings were summed to calculate the CF, which thus indicated the combined influence of these characteristics on the erosion susceptibility of the SW (a lower CF indicated a higher susceptibility to erosion). The SWs were consequently divided into four groups based on their susceptibility to erosion using the calculated CF: very high, high, moderate, and low susceptibility. SW8, SW12, and SW15 had the lowest CFs (8.0, 8.9, and 8.9, respectively) and were thus extremely vulnerable to erosion. In contrast, SW1, SW2, and SW4 had the highest CFs (13.4, 13.8, and 11.8, respectively) and were the least vulnerable to erosion. The very high-priority SWs were characterized by the presence of fifth-order streams, a length of overland flow of 1.20–1.61, a very high basin relief of 1720–2937, the highest relief ratio of 102.10–205.24, a low shape factor of 1.51–2.67, and a farm factor of 0.37–0.66. The present study demonstrates that the key morphometric characteristics that impact soil erosion are basin form and relief parameters, such as the basin relief and relief ratio. This study illustrates that the CF approach to determining the susceptibility of SWs to soil erosion is extremely valuable for planners and decision-makers for soil conservation efforts at the SW level.
Associations between Sleep Quality, Depression, and Mild Cognitive Impairment in Community-dwelling Older Persons
Authors: Chen Xiaoli , Peng Wenjia , Wang Meng , Liu Xinya , Wang Pengfei , Li Mengying , Yang Yinghua , Li Junxi , Wang Ying 
Published: December 2022

Abstract
Background
Few studies have examined the trilateral relationships among sleep quality, depression, and cognitive function. Therefore, this study aimed to explore these relationships in an older population. Furthermore, we examined mediation models for sleep quality, depression, and mild cognitive impairment (MCI).
Methods
From December 2020 to July 2021, a cross-sectional survey was conducted among 5000 older people 60 years and over in Shanghai communities, of whom 4897 (97.9%) provided responses, using a random cluster sampling method. Sleep quality and depression status were assessed using the Pittsburgh Sleep Quality Index (PSQI) and 30-item Geriatric Depression Scale (GDS-30), respectively. The Barthel Index (BADL) and Ascertain Dementia 8 (AD-8) scales were combined to assess cognitive function. T-tests and chi-square tests were used to compare the sociodemographic characteristics of the participants. Pearson’s correlations were used to determine the direction and strength of the relationships between the primary variables. We further assessed the mediating role of sleep quality and depression.
Results
The prevalence of MCI was 21.7%. After adjusting for covariates, there were bidirectional relationships between sleep quality and depression and between MCI and depression. The significant mediating effect of sleep quality on the association between depressive symptoms and cognition function (95% CI: 0.0011 to 0.0026, p = 0.001) and mediated19.29% of the total effect of depressive symptoms on cognitive function. The mediation analysis showed that sleep quality had an indirect effect on cognitive function through the mediating variable of depression (95% CI: 0.0030 to 0.0050, p = 0.001) and mediated 36.50% of the total effect of sleep quality on cognitive function. Meanwhile, sleep quality partially mediated the relationship between cognitive function and depression symptoms (95% CI: 0.4594 to 0.7643, p = 0.001) and mediated26.77% of the total effect of cognitive function on depression.
Conclusion
Sleep quality and depression had significant direct (independent) and indirect (as a mediator) effects on MCI. We believe that improving screening for depression and sleep quality among older persons could significantly contribute to their health and well-being.
Zone extrapolations in parametric timed automata
Authors: Arcile Johan , André Étienne 
Published: December 2022

Abstract
Timed automata (TAs) are an efficient formalism to model and verify systems with hard timing constraints, and concurrency.While TAs assume exact timing constants with infinite precision, parametric timed automata (PTAs) leverage this limitation and increase their expressiveness, at the cost of undecidability.A practical explanation for the efficiency of TAs is zone extrapolation, where clock valuations beyond a given constant are considered equivalent.This concept cannot be easily extended to PTAs, due to the fact that parameters can be unbounded, meaning that the constants compared to the clocks have no upper bound.In this work, we propose several definitions of extrapolation for PTAs, and we study their correctness.Our experiments show an overall decrease of the computation time and, most importantly, allow termination of some previously unsolvable benchmarks.
An Accessible Clinical Decision Support System to Curtail Anesthetic Greenhouse Gases in a Large Health Network: Implementation Study
Authors: Ramaswamy Priya , Shah Aalap , Kothari Rishi , Schloemerkemper Nina , Methangkool Emily , Aleck Amalia , Shapiro Anne , Dayal Rakhi , Young Charlotte , Spinner Jon , Deibler Carly , Wang Kaiyi , Robinowitz David , Gandhi Seema 
Published: December 2022

Background
Inhaled anesthetics in the operating room are potent greenhouse gases and are a key contributor to carbon emissions from health care facilities. Real-time clinical decision support (CDS) systems lower anesthetic gas waste by prompting anesthesia professionals to reduce fresh gas flow (FGF) when a set threshold is exceeded. However, previous CDS systems have relied on proprietary or highly customized anesthesia information management systems, significantly reducing other institutions’ accessibility to the technology and thus limiting overall environmental benefit.

Objective
In 2018, a CDS system that lowers anesthetic gas waste using methods that can be easily adopted by other institutions was developed at the University of California San Francisco (UCSF). This study aims to facilitate wider uptake of our CDS system and further reduce gas waste by describing the implementation of the FGF CDS toolkit at UCSF and the subsequent implementation at other medical campuses within the University of California Health network.

Methods
We developed a noninterruptive active CDS system to alert anesthesia professionals when FGF rates exceeded 0.7 L per minute for common volatile anesthetics. The implementation process at UCSF was documented and assembled into an informational toolkit to aid in the integration of the CDS system at other health care institutions. Before implementation, presentation-based education initiatives were used to disseminate information regarding the safety of low FGF use and its relationship to environmental sustainability. Our FGF CDS toolkit consisted of 4 main components for implementation: sustainability-focused education of anesthesia professionals, hardware integration of the CDS technology, software build of the CDS system, and data reporting of measured outcomes.

Results
The FGF CDS system was successfully deployed at 5 University of California Health network campuses. Four of the institutions are independent from the institution that created the CDS system. The CDS system was deployed at each facility using the FGF CDS toolkit, which describes the main components of the technology and implementation. Each campus made modifications to the CDS tool to best suit their institution, emphasizing the versatility and adoptability of the technology and implementation framework.

Conclusions
It has previously been shown that the FGF CDS system reduces anesthetic gas waste, leading to environmental and fiscal benefits. Here, we demonstrate that the CDS system can be transferred to other medical facilities using our toolkit for implementation, making the technology and associated benefits globally accessible to advance mitigation of health care–related emissions.
In-hospital mortality in amyloid light chain amyloidosis: analysis of the Premier Healthcare Database
Authors: Quock Tiffany P , D'Souza Anita , Broder Michael S , Bognar Katalin , Chang Eunice , Tarbox Marian H 
Published: December 2022

Aim:
Describe the clinical and economic burden of hospitalizations for amyloid light chain (AL) amyloidosis.
Materials & methods:
This retrospective analysis used nationally representative hospital discharge data (2017–2020) to report discharge status, resource use and costs for hospitalizations among patients with AL amyloidosis.
Results:
Of 1341 patients identified, 92% were discharged alive and 8% experienced in-hospital death. Compared with the average US hospital stay during 2017–2019 (4.7 days, mean costs of $13,046 and mean charges of $54,496), hospital stays for AL amyloidosis were longer and costlier (9.7 days, $27,098.61, $111,233.91), especially in patients with in-hospital death (12.2 days, $44,966, $182,338.18).
Conclusion:
AL amyloidosis is associated with significant clinical and economic burden.