Article
Public, Environmental & Occupational Health
Annelieke Driessen, Erica Borgstrom, Simon Cohn
Summary: In recent years, policies have encouraged patients to choose their place of death, with a focus on dying at home. However, there is a tendency to simplify the concept of preferred place of death as a static geographical location, overlooking the continuous efforts of palliative care teams to create suitable environments for the dying process.
SOCIAL SCIENCE & MEDICINE
(2021)
Article
Health Care Sciences & Services
Xian Chen, Mengyu Su, Anne Arber, Chengping Qiao, Jinfeng Wu, Cuihua Sun, Dan Wang, Hui Zhou, Zhu Zhu
Summary: This study found that death anxiety among Chinese oncology nurses can be categorized into two groups: low death anxiety and high stress pain. Factors such as being female, having a short work experience, and lacking palliative care-related training increase the likelihood of death anxiety.
BMC PALLIATIVE CARE
(2023)
Article
Health Care Sciences & Services
Maria Herrera Abian, Cristina Anton Rodriguez, Antonio Noguera
Summary: The study shows that the cost is significantly lower when patients receive care from a palliative care unit during their last hospital stay.
JOURNAL OF PAIN AND SYMPTOM MANAGEMENT
(2022)
Article
Oncology
Alia Alawneh, Huda Anshasi
Summary: Hospital death is more common than home death in cancer patients in Jordan. Independent predictors for dying at home include male gender, age over 65, early involvement in palliative care, and utilization of home care services.
SUPPORTIVE CARE IN CANCER
(2021)
Article
Public, Environmental & Occupational Health
Kuai In Tam, Sok Leng Che, Mingxia Zhu, Sok Man Leong
Summary: This study explored the preferred place of care and death for Chinese residents in Macao. The majority of respondents preferred to be cared for at home in the last 6 months, but only a small proportion preferred to die at home. A significant number of respondents chose hospices or hospitals as their preferred place of death. The study suggests the need for palliative home care services in Macao and emphasizes the importance of education for healthcare professionals.
FRONTIERS IN PUBLIC HEALTH
(2023)
Article
Public, Environmental & Occupational Health
Aileen Collier, Alex Broom
Summary: This study critically examines the considerations of space, place, and affect in relation to dying at the end of life using data from two qualitative Australian data sets. By challenging traditional views on specific locations for dying, the research focuses on the meanings of space and place rooted in normative expectations, developing a critical social science perspective on the intersections of space and place at the end of life.
SOCIAL SCIENCE & MEDICINE
(2021)
Article
Geriatrics & Gerontology
M. Xue, X. Jia, X. Shi, C. Yang, R. Wang, C. Zhao, X. Xin, Yongli Yang
Summary: This study examined the relationship between sarcopenia and cognitive trajectories over time among middle-aged and older Chinese adults using repeatedly measured cognitive data. The results showed that sarcopenia was associated with a persistent low cognitive trajectory, and body mass index (BMI) mediated the relationship.
JOURNAL OF NUTRITION HEALTH & AGING
(2023)
Article
Oncology
Armin Fereidouni, Mahmood Salesi, Maryam Rassouli, Fariba Hosseinzadegan, Mohammad Javid, Maryam Karami, Maryam Elahikhah, Salman Barasteh
Summary: The purpose of this study was to determine the preferred place of end-of-life care and death in cancer patients in Iran. The majority of cancer patients chose their homes as the preferred location for end-of-life care and final disposition. Researchers recommend strengthening the home care system to meet the needs of patients near the end of life.
FRONTIERS IN ONCOLOGY
(2022)
Article
Health Care Sciences & Services
Sarah H. Cross, Joshua R. Lakin, Mallika Mendu, Ernest I. Mandel, Haider J. Warraich
Summary: The study showed that between 2003 and 2017, there were 222,247 deaths attributed to advanced CKD/ESKD in the United States. Although hospitals remained the most common place of death, there was an increase in deaths at home, nursing facilities, and hospice facilities during this period.
JOURNAL OF PAIN AND SYMPTOM MANAGEMENT
(2021)
Article
Multidisciplinary Sciences
Robrecht De Schreye, Luc Deliens, Lieven Annemans, Birgit Gielen, Tinne Smets, Joachim Cohen
Summary: This study aims to evaluate the appropriateness of end-of-life care for people with cancer, COPD or dementia in Belgium using population-level data. The results show an increase in the use of family physicians, specialist palliative care, and emergency department in the last days of life. Although there is an increase in appropriate care, there is also an increase in potentially inappropriate care.
Article
Multidisciplinary Sciences
Helena Ullgren, Per Fransson, Anna Olofsson, Ralf Segersvard, Lena Sharp
Summary: The study revealed an increase in several aspects of intensity of care at the end-of-life, stressing the need for further exploration of the optimal organization of end-of-life care. The results indicate fragmentation of care and the necessity to better organize and coordinate care for vulnerable patients.
Review
Medicine, General & Internal
Sara Pinto, Silvia Lopes, Andrea Bruno de Sousa, Barbara Gomes
Summary: This protocol describes a review that aims to examine and synthesize existing evidence regarding preferences about end-of-life care and death location in patients with life-threatening illnesses and their families. The review will involve searching for relevant systematic reviews, extracting data, and assessing quality. The results will be presented at conferences and published in a peer-reviewed journal.
Article
Geriatrics & Gerontology
Iris van Doorne, Marjon van Rijn, Sjoerd M. Dofferhoff, Dick L. Willems, Bianca M. Buurman
Summary: Almost half of the patients did not have a preferred place of death (PPD) at baseline. Previous hospital admissions, having more chronic diseases, and living alone were associated with having a PPD. Introducing PPD could raise awareness and facilitate optimal palliative care for older people.
Article
Pediatrics
Maria Jose Pelaez-Cantero, Jose Miguel Morales-Asencio, Alvaro Navarro-Mingorance, Aurora Madrid-Rodriguez, Angela Tavera-Tolmo, Olga Escobosa-Sanchez, Ricardo Martino-Alba
Summary: Each year, over 8 million children worldwide need specialized palliative care, but there is limited evidence on end-of-life characteristics in the context of pediatrics. This study aims to analyze the characteristics of patients who die under the care of specific pediatric palliative care teams. The study involved 14 pediatric palliative care teams and 164 patients, mostly with oncologic, neurologic, and neuromuscular conditions. The findings show that longer follow-up times and discussions regarding preferences of place of death are associated with the provision of services by the teams and the fulfillment of parents' preferences.
EUROPEAN JOURNAL OF PEDIATRICS
(2023)
Article
Endocrinology & Metabolism
Yuanzhou Peng, Na Han, Tao Su, Shuang Zhou, Heling Bao, Yuelong Ji, Shusheng Luo, Jue Liu, Hai-Jun Wang
Summary: This study investigated trajectories of gestational weight gain before diagnosis and its association with gestational diabetes mellitus (GDM) risk. Two trajectories of weight gain were identified, with women showing excessive weight gain having a significantly increased risk of developing GDM. Excessive weight gain also led to higher risks of macrosomia and cesarean delivery.
DIABETES RESEARCH AND CLINICAL PRACTICE
(2021)
Article
Computer Science, Information Systems
Jiashu Wu, Hao Dai, Yang Wang, Kejiang Ye, Chengzhong Xu
Summary: In this article, a geometric graph alignment (GGA) approach is proposed to address the problem of data scarcity in IoT intrusion detection (IID) algorithms. By utilizing the data-rich network intrusion detection (NID) domain, better intrusion detection performance for IID can be achieved. The experimental results demonstrate the state-of-the-art performance of the GGA approach.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Computer Science, Information Systems
Jiashu Wu, Yang Wang, Binhui Xie, Shuang Li, Hao Dai, Kejiang Ye, Chengzhong Xu
Summary: In this research, a joint semantic transfer network (JSTN) is proposed for effective intrusion detection (ID) in the large-scale scarcely labeled Internet of Things (IoT) domain. The JSTN integrates a knowledge-rich network intrusion (NI) domain and a small-scale IoT intrusion (II) domain as source domains to assist target II domain ID. The JSTN transfers three semantics to learn a domain-invariant and discriminative feature representation. The experiments demonstrate the superiority of the JSTN, achieving an average accuracy boost of 10.3% compared to state-of-the-art methods. The statistical soundness of each component and the computational efficiency are also verified.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Computer Science, Interdisciplinary Applications
Zhenning Li, Zhiwei Chen, Yunjian Li, Chengzhong Xu
Summary: This study presents a new multimodal trajectory prediction framework based on the transformer network to address the challenging task of predicting surrounding agent trajectories in heterogeneous traffic environments. The proposed framework includes a hierarchical-structured context-aware module and an efficient linear global attention mechanism. It also introduces a novel auxiliary loss to penalize infeasible off-road predictions. The empirical results demonstrate the state-of-the-art performance of the proposed model on the Lyft l5kit data set, enhancing the accuracy and feasibility of prediction outcomes.
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING
(2023)
Article
Computer Science, Hardware & Architecture
Jiashu Wu, Hao Dai, Yang Wang, Yong Zhang, Dong Huang, Chengzhong Xu
Summary: This paper addresses a data caching problem in the cloud environment and proposes an online algorithm called PackCache, which leverages the FP-Tree technique to mine frequently co-utilised data items for cost-effective serving of incoming requests. The algorithm is shown to be 2/alpha competitive, reaching the lower bound of the competitive ratio, and also efficient in terms of time and space.
IEEE TRANSACTIONS ON COMPUTERS
(2023)
Article
Computer Science, Hardware & Architecture
Bo Fan, Zixun Su, Yanyan Chen, Yuan Wu, Chengzhong Xu, Tony Q. S. Quek
Summary: The emergence of automated driving has led to the coexistence of vehicles with different automation levels in road traffic, but current traffic control systems fail to address the vehicular heterogeneity. A new traffic control framework empowered by digital twin (DT) empowered edge AI is proposed in this article to achieve fault-tolerant control over heterogeneous vehicles. The DT's virtualization capability enables virtual risk assessment and performance analysis, while its offline learning capability helps the edge AI make intelligent optimizations and decisions based on road traffic data.
IEEE WIRELESS COMMUNICATIONS
(2023)
Article
Computer Science, Hardware & Architecture
Peng Lin, Kejiang Ye, Yishen Hu, Yanying Lin, Cheng-Zhong Xu
Summary: Traffic classification is crucial for cybersecurity maintenance and network management. Traditional payload-based methods are ineffective in the presence of SSL/TLS encryption protocols. This paper presents a novel multimodal deep learning framework called PEAN for encrypted traffic classification, which uses raw bytes and length sequence as input and leverages self-attention mechanism for learning deep network packet relationships. Unsupervised pre-training is also incorporated to enhance PEAN's ability to characterize network packets. Experimental results demonstrate the effectiveness of PEAN, outperforming state-of-the-art methods.
IEEE-ACM TRANSACTIONS ON NETWORKING
(2023)
Article
Computer Science, Information Systems
Furong Zheng, Juanjuan Zhao, Jiexia Ye, Xitong Gao, Kejiang Ye, Chengzhong Xu
Summary: Short-term OD matrix prediction in metro systems is crucial for dynamic traffic operations. In this paper, a Multi-View Passenger Flow evolution trend based OD matrix prediction method is proposed, which learns high-level spatiotemporal-dependent representations of each station and passenger mobility patterns from origin to destination by considering real-time traffic information.
IEEE TRANSACTIONS ON BIG DATA
(2023)
Article
Ergonomics
Zhenning Li, Haicheng Liao, Ruru Tang, Guofa Li, Yunjian Li, Chengzhong Xu
Summary: Traffic crash datasets are often affected by outliers, which can greatly influence the results obtained from traditional methods like logit and probit models used in traffic safety analysis. This study proposes a robust Bayesian regression model called robit, which addresses this issue by using a heavy-tailed Student's t distribution to reduce the impact of outliers. A sandwich algorithm based on data augmentation is also proposed to improve the estimation efficiency of posteriors. The model is rigorously tested using a tunnel crash dataset and outperforms traditional methods in terms of efficiency, robustness, and performance. The study also identifies significant factors like night and speeding that impact the severity of injuries in tunnel crashes. This research provides a comprehensive understanding of outlier treatment methods in traffic safety studies and valuable recommendations for preventing severe injuries in tunnel crashes.
ACCIDENT ANALYSIS AND PREVENTION
(2023)
Article
Computer Science, Hardware & Architecture
Shuai Wang, Chengyang Li, Derrick Wing Kwan Ng, Yonina C. Eldar, H. Vincent Poor, Qi Hao, Chengzhong Xu
Summary: In order to address the challenges of rare and occluded perception in open driving scenarios, a federated learning assisted connected autonomous vehicle (FLCAV) is proposed, which establishes federated deep neural networks (DNNs) from distributed data captured by vehicles and road sensors. Networking and training frameworks are presented to solve the problems of network management and sensor deployment, respectively.
Article
Engineering, Civil
Yubin Guo, Xinlei Qi, Jin Xie, Cheng-Zhong Xu, Hui Kong
Summary: In this paper, an unsupervised visible light-guided cross-spectrum depth-estimation framework is proposed. It achieves reliable depth maps under variant-illumination conditions with a pair of dual-spectrum images. Through training a depth-estimation base network, transferring features from the TIR domain to the VIS domain, and introducing a mechanism of cross-spectrum depth cycle-consistency, our method outperforms existing methods in depth estimation.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Robotics
Zezhou Sun, Banghe Wu, Chengzhong Xu, Hui Kong
Summary: Existing RRT-based exploration methods often face interruptions in the exploration process due to the inability to detect all frontiers of the drivable area in the mapping map. We propose a solution by redefining exploration frontiers, designing a novel exploration gain, and constructing minimum RRT search spaces. Our method outperforms existing methods in simulated benchmarks and outdoor environments, demonstrating better robustness and reduced computational cost. We have made our method open source for the benefit of the community.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2023)
Proceedings Paper
Computer Science, Artificial Intelligence
Jiacheng Lu, Shuo Gu, Cheng-Zhong Xu, Hui Kong
Summary: In this paper, a cylindrical convolution network is proposed for dense semantic understanding in the top-view LiDAR data representation in autonomous driving systems. The method involves dividing 3D LiDAR point clouds into cylindrical partitions and conducting semantic segmentation in the cylindrical representation. A cylinder-to-BEV transformation module is introduced to obtain sparse semantic feature maps in the top view. Finally, a modified encoder-decoder network is used to achieve dense semantic estimations.
COMPUTER VISION - ACCV 2022, PT VII
(2023)
Article
Computer Science, Information Systems
Chengxi Gao, Shuhui Chu, Hong Xu, Minxian Xu, Kejiang Ye, Chengzhong Xu
Summary: Flow scheduling and congestion control are crucial techniques for minimizing flow completion time in data center networks. This paper introduces Flash, a scheme that integrates congestion-aware scheduling and priority-based packet dropping to improve performance. Experimental results demonstrate that Flash outperforms existing schemes in terms of latency and flow completion time.
IEEE TRANSACTIONS ON CLOUD COMPUTING
(2023)
Article
Computer Science, Information Systems
Yang Wang, Hao Dai, Xinxin Han, Pengfei Wang, Yong Zhang, Chengzhong Xu
Summary: In this paper, we investigate a data caching problem in an edge-based content delivery network (CDN) where multiple service requests share a data item. Instead of focusing on improving hit ratio given limited capacity, we study the problem using a semi-homogeneous cost model to reduce monetary costs. We propose an optimal offline caching algorithm based on shortest path to minimize transfer and caching costs, and an online reactive caching algorithm that is 2-competitive and achieves a tight bound of competitive ratio 2--o(1). We also present a hybrid algorithm that combines the advantages of both algorithms. Trace-based empirical studies show that our algorithms improve previous results in time complexity and competitive ratio, and also make the cost model more practical.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2023)
Article
Computer Science, Artificial Intelligence
Kahou Tam, Li Li, Bo Han, Chengzhong Xu, Huazhu Fu
Summary: Federated learning is a method that collaboratively trains a shared global model while preserving data privacy. However, the issue of noisy clients is often ignored, affecting the overall performance of the model. This study investigates the impact of noisy clients in federated learning and proposes a framework called Fed-NCL to address the issue. Experimental results demonstrate improved performance in systems with noisy clients.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
