The purpose of this article is to give a characterization of families of expander graphs via right-angled Artin groups. We prove that a sequence of simplicial graphs {Γi}i∈ forms a family of expander graphs if and o...
详细信息
作者：
Kung, Chen-NingYeh, Chun-YinLai, Wei-ShuChen, Chin-MingKo, Nai-Ying1MSN
RN Department of Nursing Chi Mei Medical Center Taiwan ROC PhD
RN Postdoctoral Research Fellow Department of Computer Science and Information Engineering College of Electrical Engineering and Computer Science National Cheng Kung University Taiwan ROC PhD
RN Assistant Professor Department of Nursing College of Medicine National Cheng Kung University Taiwan ROC MD
Attending Physician and Professor Department of Intensive Care Medicine Chi Mei Medical Center ROC Taiwan PhD
RN Distinguished Professor Department of Nursing College of Medicine National Cheng Kung University Taiwan ROC
TITLE: 從加護病房家屬觀點探究重症病情告知的經驗. 背景: 病情告知是減少醫病認知落差的重要步驟，且能減輕家屬心理壓力。現階段研究仍缺乏家屬對重症病情告知經驗及需求之探討。. 目的: 瞭解重症家屬病情告知經驗及過程需求。. 方法: 採描述現象學，立意取樣5位加護病房疾病嚴重度≥ 20分的病人家屬進行深度訪談。以Giorgi現象學分析法，利用Nvivo 11分析歸納資料。. 結果: 整體經驗包含四大主題：（一）訊息聽了無法懂，希望疑問詳細解、（二）無助找尋為解答，期望護理來幫忙、（三）託付專業卻無奈，渴望醫療多些愛、（四）重重難關多牽絆，盼望見解來割斷。. 結論／實務應用: 病情告知著重傳遞結果，家屬無法理解病情變化原因。本研究建議醫療專業人員應體認家屬認知程度，並顧及其情緒反應，納入家屬需求及期待，以病人為中心提供個別化告知。.;BACKGROUND: Truth-telling is an important step toward reducing the cognitive gap between physicians and patients as well as reducing the psychological pressures applied to physicians by family members. There is a lack of research on the truth-telling experience and needs in the intensive care unit from the perspective of patient family members. PURPOSE: This study is designed to explore the experiences and needs of families in the intensive care unit. METHODS: A descriptive phenomenology method was used in this study. In-depth interviews were conducted with five participants who had family members assessed with acute physiology and chronic health evaluation II scores ≥ 20. Data were analyzed using Giorgi's phenomenological methods and Nvivo 11. RESULTS: Four experience themes were examined, including (1) nothing is clear, requires explanation;(2) helpless to find answers, need a nurse to resolve this issue;(3) professional conduct makes us feel helpless, longing for love from the medical team;(4) decisions are very difficult, hoping to get more help. CONCLUSIONS / IMPLICATIONS FOR PRACTICE: The family members expressed that they were unable to understand the underlying causes of the progression in patient condition because the medical team only presented outcomes to the family and did not discuss related causes. Thus, it is recommended that medical teams learn to recognize the cognitive processes of patient family members and consider their emotions, including their needs and expectations, in order to provide individualized explanations based on a patient's status and progress.
Hypotension is common in critically ill patients. Early prediction of hypotensive events in the Intensive Care Units (ICUs) allows clinicians to pre-emptively treat the patient and avoid possible organ damage. In this...
详细信息
ISBN:
(数字)9781728119908
ISBN:
(纸本)9781728119915
Hypotension is common in critically ill patients. Early prediction of hypotensive events in the Intensive Care Units (ICUs) allows clinicians to pre-emptively treat the patient and avoid possible organ damage. In this study, we investigate the performance of various supervised machine-learning classification algorithms along with a real-time labeling technique to predict acute hypotensive events in the ICU. It is shown that logistic regression and SVM yield a better combination of specificity, sensitivity and positive predictive value (PPV). Logistic regression is able to predict 85% of events within 30 minutes of their onset with 81% PPV and 96% specificity, while SVM results in 96% specificity, 83% sensitivity and 82% PPV. To further reduce the false alarm rate, we propose a high-level decision-making algorithm that filters isolated false positives identified by the machine-learning algorithms. By implementing this technique, 24% of the false alarms are filtered. This saves 21 hours of medical staff time through 2,560 hours of monitoring and significantly reduces the disturbance caused by alarming monitors.
Image segmentation is the process in which image is partitioned into multiple regions which results into number of fragments of objects. The main purpose of image segmentation is to make modifications and simplificati...
详细信息
ISBN:
(数字)9781538681138
ISBN:
(纸本)9781538681145
Image segmentation is the process in which image is partitioned into multiple regions which results into number of fragments of objects. The main purpose of image segmentation is to make modifications and simplifications in an image to make it more clear and meaningful. The main feature of segmentation is to find boundaries and objects in an image .Resultant of image segmentation composed of multiple regions that entitrely cover the whole image. Pixels in a common area are alike to each other on the basis of some computed property such as color, texture.
作者：
Saurabh TiwariS VeenadhariSanjeev K GuptaPhd Research Scholar
Department of Computer Science and Engineering RNTU Bhopal 462003 Madhya Pradesh India Associate Professor
RNTU Department of Computer Science and Engineering RNTU Bhopal 462003 Madhya Pradesh India Professor
RNTU Department of Electronics and Communication Engineering RNTU Bhopal 462003 Madhya Pradesh India
This paper presents a model which gives the detailed process of object identification. We need to identify class and location of object in image for completing process of objet identification. Proposed model works on ...
This paper presents a model which gives the detailed process of object identification. We need to identify class and location of object in image for completing process of objet identification. Proposed model works on the principal of reinforcement learning which takes action on the basis of rewards and experiences. Normally methods in literature uses sliding window which moves in same direction but proposed algorithm provides a variable mask which moves 360 degree for identifying object using action history vector proposed with RL also not only this work focuses on localization like other work but also used class information with Softmax classification able to classify multiple object in single image with efficient time which is novel. Proposed mask acts as agent and focuses on proposed candidate reason this saves time and works in efficient manner for identification. Agent depends on transformation action and by applying top down reasoning it gives location of object. Classification is done using Softmax classification as we are having features of image by CNN. Reinforcement learning concept used for training of agent and Pascal voc dataset used for testing. Analysis of only 10 to 25 regions is sufficient with proposed work to identify first instance of object. Experiment and performance evaluation shows the efficiency of proposed work.
作者：
M F EltanbolyM M AfifyArchitecture Department
Teaching Assistant Cairo Higher Institute for Engineering Computer Science and Management No.2 Banafseg Center2 first Settlement Cairo Postcode 11477 Egypt and PhD. Student Environmental Design and Energy Efficiency Department Cairo University Faculty of Engineering Giza Architecture department
Professor in Environmental Design and Energy Efficiency Department Cairo University Faculty of Engineering Giza
The path we are currently following to improve the physics of construction due to the destruction of our environment through the negative impact of the built environment around us. Current efforts to decrease carbon a...
The path we are currently following to improve the physics of construction due to the destruction of our environment through the negative impact of the built environment around us. Current efforts to decrease carbon and energy are noted by modifying and improving modern 'layered' envelopes and improving a misunderstanding of thermal comfort that has become much less effective than expected. Understanding construction physics is an important factor in improving the quality of life indoor and outdoor, relying primarily on theoretical and computational aspects, then applying the practical part to reduce excessive use of carbon and energy and hinder the elaboration of a sustainable and built environment. This paper shows how the problem stems from neglecting to think about the first principles and basic construction physics. Similarly, we show how combining good construction physics with reassessing old methodologies to construction and structure use provides some powerful and effective tools to address the climate emergency. The use of construction physics methods supports the search for new solutions to express the most important factors affecting thermal conduction and minimum surface temperatures. However, buildings have integrated concepts in which advanced systems work together to optimize energy, comfort, and health performance. Convergence between various engineering fields and the overlapping field of construction techniques and services has great potential in the future to achieve the next step in energy saving. As a result, the research highlights new methods that make our buildings interact with the external environment using climate data, responsive envelope design, simulation software, thereby achieving architectural response to surrounding variables, improving building physics to reduce environmental pollution, thermal comfort, and achieving the highest energy efficiency and performance in buildings. This is illustrated by the presentation of a case study
作者：
E V MatvienkoA L ZolkinD K SuchkovL A PankratovaPhD in Biological Science
Junior Researcher of the Laboratory of Breeding and Seed Farming of Cereal and Sorghum Crops Volga NIISS - branch of the Samara Scientific Center of the Russian Academy of Sciences Ph.D. in Engineering Science
Senior Lecturer of Computer and Information Sciences Department of the Povolzhskiy State University of Telecommunications and Informatics Junior Researcher
Federal Research Center for Agroecology Integrated Land Reclamation and Protective Afforestation of the Russian Academy of Sciences (Laboratory for Predicting the Bio-productivity of Agroforestscapes) PhD in Geography
Senior Lecturer of the Physical Geography and Landscape Planning Department Institute of Earth Sciences St.Petersburg State University
Breed is studied in the article as of significant factors that determine the level of yield and its quality. World experience shows that the consistent increase in the yield of cultivated crops is based on the improve...
Breed is studied in the article as of significant factors that determine the level of yield and its quality. World experience shows that the consistent increase in the yield of cultivated crops is based on the improvement of the cultivation technology and the achievements of breeding. The production of agricultural products is based on the variety of breeds. According to A.A. Zhuchenko, breed determines the basic requirements for cultivation technologies: productivity, energy efficiency, environmentally friendly quality and environmental protection. It is believed that 25% of the yield is determined by the genetic characteristics of the cultivated breed. The role of the genotype in increasing and stabilizing the yield is constantly increasing, and the contribution of the breed during zoning is estimated at 30 ... 50%.
The online comment for doctors plays an important role in assisting patients to master the real medical situation and choose medical treatment, which greatly reduces the adverse effects of online medical market inform...
The online comment for doctors plays an important role in assisting patients to master the real medical situation and choose medical treatment, which greatly reduces the adverse effects of online medical market information asymmetry. but because ordinary patients lack professional medical knowledge and can not accurately and efficiently write comments that are useful to similar patients, we identify useful topics from online medical reviews and make combination recommendations based on patients with different diseases. guide patients to write comments from the most useful dimensions to alleviate the problem of information overload, thus maximizing the limited human resource utility. This study aimed at online medical platforms such as good doctors and micro-doctors collected online doctor reviews for major diseases and used LDA topic mining and fsQCA fuzzy set qualitative comparative analysis to analyze key topics that affect the usefulness of reviews and optimal topic combinations under different disease types.
Segmentation of breast tumor is an important step for breast cancer follow-up and treatment. Automating this challenging task can help radiologists to reduce the high workload of breast cancer analysis. In this paper,...
详细信息
ISBN:
(纸本)9781728116389;9781728116372
Segmentation of breast tumor is an important step for breast cancer follow-up and treatment. Automating this challenging task can help radiologists to reduce the high workload of breast cancer analysis. In this paper, we propose a deep learning approach to automate the segmentation of breast tumors in DCE-MRI data. We build an architecture based on U-net fully convolutional neural network. The trained model can handle both detection and segmentation on each single breast slice. In this study, we used a dataset of 86 DCE-MRI, acquired before and after chemotherapy, of 43 patients with local breast cancer, a total of 5452 slices. The data have been annotated manually by an experienced radiologist. The model was trained and validated on 85% and 15% of the data and achieved a mean IoU of 76,14%.
OBJECTIVES:This study aims to investigate the molecular differences and commonalities between systemic sclerosis (SSc) and systemic lupus erythematosus (SLE) by analyzing RNA-sequencing (RNA-seq) data. By focusing on ...
详细信息
OBJECTIVES:This study aims to investigate the molecular differences and commonalities between systemic sclerosis (SSc) and systemic lupus erythematosus (SLE) by analyzing RNA-sequencing (RNA-seq) data. By focusing on differentially expressed genes and enriched pathways, the investigation seeks to identify unique biomarkers, shared pathways, and potential therapeutic targets for these autoimmune diseases.
METHODS:This study involved 10 patients with SSc and 24 with SLE who did not receive immunosuppressants. RNA-seq data from patients with SSc and SLE were analyzed using DESeq2 to identify differentially expressed genes. Functional and pathway enrichment analyses were conducted and comparative analyses were performed.
RESULTS:We identified 2055 differentially expressed genes (DEGs) between patients with SSc and controls. Notably, the expression of the shared gene RGS5 was significantly downregulated in both SLE and SSc, with a more pronounced downregulation in SSc. Additionally, the expression of the key transcription factor EGR1 was upregulated in SSc, whereas that of BLK, ITGAM, and IFNG was upregulated in SLE. Network analysis identified hub genes-AP3D1, FTX, USP47, CUX1, ZC3H4, CAND1, INTS1, TRNT1, MTERF1, and SETD1B-that may play critical roles in the progression of both SLE and SSc.
CONCLUSION:These findings suggest that RGS5 could serve as a shared biomarker for vascular dysfunction, while EGR1 and BLK may represent therapeutic targets in SSc and SLE. Overall, this analysis enhances understanding of distinct and overlapping gene expression signatures in SSc and SLE, providing a foundation for future targeted treatment strategies and requiring further validation in larger cohorts.
暂无评论