Simulation based on a modified social force model for sensitivity to emergency signs in subway station

The subway is the primary travel tool for urban residents in China. Due to the complex structure of the subway and high personnel density in rush hours, subway evacuation capacity is critical. The subway evacuation model is explored in this work by combining the improved social force model with the view radius using the Vicsek model. The pedestrians are divided into two categories based on different force models. The first category is sensitive pedestrians who have normal responses to emergency signs. The second category is insensitive pedestrians. By simulating different proportions of the insensitive pedestrians, we find that the escape time is directly proportional to the number of insensitive pedestrians and inversely proportional to the view radius. However, when the view radius is large enough, the escape time does not change significantly, and the evacuation of people in a small view radius environment tends to be integrated. With the improvement of view radius conditions, the escape time changes more obviously with the proportion of insensitive pedestrians. A new emergency sign layout is proposed, and the simulations show that the proposed layout can effectively reduce the escape time in a small view radius environment. However, the evacuation effect of the new escape sign layout on the large view radius environment is not apparent. In this case, the exit setting emerges as an additional factor affecting the escape time.

Epidemiology and Clinical Signs of Gynecological Cancers in an African Country South of the Sahara: Case of the Republic of Benin in 2022

Introduction: Gynaecological cancers are the deadliest of the women’s cancers in the Republic of Benin. Late diagnosis is the most common reason. Objective: This paper aims to describe the epidemiological characteristics, and clinical and pathological signs of gynaecological cancers treated in the Republic of Benin between 2018 and 2022. Patients and Methods: This was a cross-sectional, descriptive, retrospectively collected study of patient data treated between 2018 and 2022 in two university gynaecology departments in Cotonou. All gynaecological cancers that have histological evidence were included. The epidemiological, clinical and pathological characteristics of the cancers were assessed. Results: Cervical, endometrial and ovarian cancers were the most common in the proportions of 62.0%, 24.1%, 12.0% and 1.8% respectively. The mean age at diagnosis was 54 years. The victims were uneducated and had low economic power in 81% and 85% of cases, respectively. The consultation was late in 82.1% of cases. Metrorrhagia, postmenopausal metrorrhagia and pelvic cluster headache were the common reasons for consultation for cervical, endometrial and ovarian cancer, respectively. Diagnosis was late in 66.7% (n = 71). The most common histological types were squamous cell carcinoma, endometrioid adenocarcinoma, and serous cystadenocarcinoma for cervical, endometrial, and ovarian cancers, respectively. Conclusion: Gynaecological cancers were common and their consultation time was delayed. The diagnosis was made at the advanced stage and there were several reasons for this.

A Deep Learning Model of Traffic Signs in Panoramic Images Detection

To pursue the ideal of a safe high-tech society in a time when traffic accidents are frequent,the traffic signs detection system has become one of the necessary topics in recent years and in the future.The ultimate goal of this research is to identify and classify the types of traffic signs in a panoramic image.To accomplish this goal,the paper proposes a new model for traffic sign detection based on the Convolutional Neural Network for com-prehensive traffic sign classification and Mask Region-based Convolutional Neural Networks(R-CNN)implementation for identifying and extracting signs in panoramic images.Data augmentation and normalization of the images are also applied to assist in classifying better even if old traffic signs are degraded,and considerably minimize the rates of discovering the extra boxes.The proposed model is tested on both the testing dataset and the actual images and gets 94.5%of the correct signs recognition rate,the classification rate of those signs discovered was 99.41%and the rate of false signs was only around 0.11.

Recognizing Early Warning Signs (EWS) in Patients Is Critically Important

Introduction: Monitoring vital signs is a basic indicator of a patient’s health status and allows prompt detection of delayed recovery or adverse effects and early intervention. Patients with adverse events during hospitalization often display clinical decline for several hours before the event is observed. Non-critical care Nurses’ inconsistent recognition and response to patient deterioration lead to an increase in the length of hospital stay, unexpected admissions to the ICU, and increased morbidity and mortality. Aim: The study aimed to assess the factors that facilitate or impede the detection of early warning signs among adult patients hospitalized in tertiary care settings. Training should be provided to improve nurses’ knowledge, practice and attitude toward early warning signs of deteriorating patients leading to enhanced clinical judgment, skills and decision-making in addressing alerts. Methodology: A literature search was carried out in various databases;these were Cumulative Index to Nursing and Allied Health Literature (CINHAL), Google Scholar, PubMed, Science Direct, and Sage. The search area was narrowed from 2017 to 2022. The keywords used were “prevalence” AND “unplanned ICU admission”, “the importance of early warning signs” “outcome failure in rescue” “patient deterioration, communication” “improvement in early detection” AND “patient outcome admission” AND “early warning signs” AND “Pakistan”. After the analysis process, around 33 articles that met the inclusion criteria and were most relevant to the scope and context of the current study were considered. Conclusion: Most of the studies had reviewed literature in a qualitative retrospective observational study, content analysis, mixed method, and quasi-experimental study. The literature review identified that long hours of shift, nurse staffing levels, missed vital signs, lack of nursing training and education, and communication impact nurses’ ability to recognize and respond to early warning signs.

Source localization in signed networks with effective distance

While progress has been made in information source localization,it has overlooked the prevalent friend and adversarial relationships in social networks.This paper addresses this gap by focusing on source localization in signed network models.Leveraging the topological characteristics of signed networks and transforming the propagation probability into effective distance,we propose an optimization method for observer selection.Additionally,by using the reverse propagation algorithm we present a method for information source localization in signed networks.Extensive experimental results demonstrate that a higher proportion of positive edges within signed networks contributes to more favorable source localization,and the higher the ratio of propagation rates between positive and negative edges,the more accurate the source localization becomes.Interestingly,this aligns with our observation that,in reality,the number of friends tends to be greater than the number of adversaries,and the likelihood of information propagation among friends is often higher than among adversaries.In addition,the source located at the periphery of the network is not easy to identify.Furthermore,our proposed observer selection method based on effective distance achieves higher operational efficiency and exhibits higher accuracy in information source localization,compared with three strategies for observer selection based on the classical full-order neighbor coverage.

Recent Advances on Deep Learning for Sign Language Recognition

Sign language,a visual-gestural language used by the deaf and hard-of-hearing community,plays a crucial role in facilitating communication and promoting inclusivity.Sign language recognition(SLR),the process of automatically recognizing and interpreting sign language gestures,has gained significant attention in recent years due to its potential to bridge the communication gap between the hearing impaired and the hearing world.The emergence and continuous development of deep learning techniques have provided inspiration and momentum for advancing SLR.This paper presents a comprehensive and up-to-date analysis of the advancements,challenges,and opportunities in deep learning-based sign language recognition,focusing on the past five years of research.We explore various aspects of SLR,including sign data acquisition technologies,sign language datasets,evaluation methods,and different types of neural networks.Convolutional Neural Networks(CNN)and Recurrent Neural Networks(RNN)have shown promising results in fingerspelling and isolated sign recognition.However,the continuous nature of sign language poses challenges,leading to the exploration of advanced neural network models such as the Transformer model for continuous sign language recognition(CSLR).Despite significant advancements,several challenges remain in the field of SLR.These challenges include expanding sign language datasets,achieving user independence in recognition systems,exploring different input modalities,effectively fusing features,modeling co-articulation,and improving semantic and syntactic understanding.Additionally,developing lightweight network architectures for mobile applications is crucial for practical implementation.By addressing these challenges,we can further advance the field of deep learning for sign language recognition and improve communication for the hearing-impaired community.

Japanese Sign Language Recognition by Combining Joint Skeleton-Based Handcrafted and Pixel-Based Deep Learning Features with Machine Learning Classification

Sign language recognition is vital for enhancing communication accessibility among the Deaf and hard-of-hearing communities.In Japan,approximately 360,000 individualswith hearing and speech disabilities rely on Japanese Sign Language(JSL)for communication.However,existing JSL recognition systems have faced significant performance limitations due to inherent complexities.In response to these challenges,we present a novel JSL recognition system that employs a strategic fusion approach,combining joint skeleton-based handcrafted features and pixel-based deep learning features.Our system incorporates two distinct streams:the first stream extracts crucial handcrafted features,emphasizing the capture of hand and body movements within JSL gestures.Simultaneously,a deep learning-based transfer learning stream captures hierarchical representations of JSL gestures in the second stream.Then,we concatenated the critical information of the first stream and the hierarchy of the second stream features to produce the multiple levels of the fusion features,aiming to create a comprehensive representation of the JSL gestures.After reducing the dimensionality of the feature,a feature selection approach and a kernel-based support vector machine(SVM)were used for the classification.To assess the effectiveness of our approach,we conducted extensive experiments on our Lab JSL dataset and a publicly available Arabic sign language(ArSL)dataset.Our results unequivocally demonstrate that our fusion approach significantly enhances JSL recognition accuracy and robustness compared to individual feature sets or traditional recognition methods.

Existence of Monotone Positive Solution for a Fourth-Order Three-Point BVP with Sign-Changing Green’s Function

This paper is concerned with the following fourth-order three-point boundary value problem , where , we discuss the existence of positive solutions to the above problem by applying to the fixed point theory in cones and iterative technique.

Study of C-E Translation of Public Signs in China: Review and Reflection

In the last decade,Chinese scholars have made great achievements in the study of public sign translation.Their re-search findings are analyzed from the following perspectives:definition,functions and features of public signs;differences betweenChinese and English public signs;and related academic research.Reflection on the previous studies suggests that more empiricalstudies should be conducted under the guidance of translation theories in the future.

The Connotations of Non-linguistic Signs in Communication

The silent communication of non-linguistic signs occurs in human cognition.This can be proved from four points of view:to introduce the definitions of linguistics,non-linguistic signs and meaning;all of them can communicate in human cognition through their comparison;the connotations of many kinds of non-linguistic signs in daily life;the position of non-linguistic signs in linguistic fields;from the above the conclusion can be reached.

On C-E Translation of Tourism Public Signs in the Light of Skopostheorie

Public signs have the functions of prompting,directing,restricting and compelling people's behaviors in public.Thoughexperts and government have done a lot to improve and regulate tourism public signs translation,there still exist many problems re-flecting in linguistic translation errors,pragmatic translation errors and cultural translation errors.In the light of Skopostheorie,thetranslation purpose justifies the translation process and translation methods according to its purpose and function.So translatorscan flexibly adopt some methods such as literal translation,liberal translation,additional translation,omission and analogy to guidetourism public signs translation.

On the Study of the Translation of Public Signs

Public sign is a unique writing style,the article talks about its definition and classification;it also discusses the existing problems,exploring some possible causes in Chinese-English translations.It offers some useful suggestions to establish standard translation so as to give people an accurate direction on public signs translation.

The Exploration for Cultural Differences of Chinese and English Public Signs and Their Pragmatic Translation

With China’s accession to WTO,public signs are frequently seen in cities.However,there are lots of pragmatic errors and many improper translation,which we can find everywhere.In addition,this situation exerts serious side effects on our international image in foreign exchange.In order to regulate translation and application of public signs and even with an aim to bring about the realization of globalization,this paper discusses and analyzes some translating strategies and principles from the perspective of cultural differences and pragmatics.

A Pragmatic Analysis of Public Signs in Chinese-English Translation——Based on the Example of Shaoguan National Forest Park

With the rapid development of economy and close international exchanges, the English translation of public signs is in-creasingly important and cannot be ignored. This paper takes Shaoguan National Forest Park as an example to analyze its publicsigns translation and points out some pragmatic failures from two aspects:pragmatic language failures and social pragmatic failures.Also, the paper puts forward some suggestions based on the translation error analysis.

The Study of Public Signs Mistranslation and Coping Strategies

With the rapid development of China's economy and the deepening of globalization,more and more foreigners head to China for study,work and travel.Therefore,the quality of the translation of public signs is of great importance.Proper translation of public signs does not only hint and help foreign friends,but embodies the degree of openness,internationalization and overall quality of a city as well.Based on Christiane Nord's classification of translation errors,this paper will analyze the mistranslation in public signs and put forward the corresponding strategies.

C-E Translation of Public Signs in Xi'an under the Guidance of Skopostheorie

Public signs are widely used in our lives, and increasingly play a significant role with the boom of international tourism. Xi'an, as a major tour destination of China, needs more accurate public signs. Skopostheorie offers a new perspective for translation and translating. In Skopostheorie, translation is seen as translational action with purposes. The TT which doesn't achieve the function and purpose is not an adequate translation. In this thesis, C-E translation of public signs under the guidance of Skopostheorie in Xi'an is discussed.

Symptoms and signs of acute alcoholic hepatitis

Although there is not one specific sign or symptom related to alcoholic hepatitis(AH),a constellation of symptoms and signs can help make the diagnosis of AH with reasonable accuracy.Documentation of chronic and active alcohol abuse is paramount in making a diagnosis of AH.Clinical presentation after abstinence for more than 3 m should raise doubts about the diagnosis of AH and dictate the need for considering other causes of liver disease,decompensation of alcoholic cirrhosis,sepsis and malignancy as the cause of patient's clinical profile.

On the Status quo and Countermeasures of English-Chinese Public Signs Translation: A Case Study of Tianjin

Bilingual public signs are extensively used in Chinese-speaking regions such as China's Mainland, Taiwan and Hong Kong. This article concentrates on issues relating to English-Chinese public signs in Tianjin and their translation countermeasures. Based on examples collected from public places, it can be found that English-Chinese public signs in these places constitute a special genre and tend to use a descriptive and/or figurative language style to convey a simple message, which creates challenges for translation. The paper mainly discusses the status quo of public signs in Tianjin, the Skopos theory and its application in public signs translation. It is found that under the guidance of the Skopos theory the translation may be well conducted. The paper concludes that the unique nature of public signs in public places suggests a need for further investigation of the language styles used in such signs in both languages and the most appropriate strategies for their translation.

The Use of Dynamic Message Signs (DMSs) on the Freeways: An Empirical Analysis of DMSs Logs and Survey Data

This study evaluates the Dynamic Message Signs (DMSs) use to dissipate incident information on the freeways in Las Vegas, Nevada. It focuses on the DMSs message timing, extent, and content, from the operators’ and drivers’ perspectives, considering the variability in drivers’ freeway experience. Two-week incidents data with fifty-nine incidents, DMS log data, and responses from a survey questionnaire were used. The descriptive analysis of the incidents revealed that about 54% of the incidents had their information posted on the DMSs;however, information of only 18.6% of the incidents was posted on time. The posted information covered the incident type (54.2%), location (49.2%), and lane blockage (45.8%), while the expected delay or the time the incident has lasted are rarely posted. Further, the standard DMSs are the most preferred sources of traffic information on the freeway compared to the travel time only DMSs, and the graphical map boards. The logistic regression applied to the survey responses revealed that regular freeway users are less likely to take an alternative route when they run into congestion, given no other information is available. Conversely, when given accurate information through DMSs, regular freeway users are about 2.9 times more likely to detour. Furthermore, regular freeway users perceive that the DMSs show clear information about the incident location. Upon improving the DMSs usage, 73% of respondents suggested that the information be provided earlier, and 54% requested improvements on congestion duration and length information. These findings can be used by the DMSs operators in Nevada and worldwide to improve freeway operations.

Using markedly abnormal vital signs in the emergency department to anticipate needs for intensive care unit admission

Objective: To assess the utility and relative strength of markedly abnormal vital signs thresholds (triggers) in prediction of the needs for intensive care unit (ICU) admission from the emergency department (ED). Methods: A retrospective cohort study performed in a 37 000 annual visit, urban, community teaching ED. All adult patient encounters from July 10, 2011 to July 9, 2013 were eligible for inclusion. The primary outcome was ICU admission from the ED. We collected the incidence of trigger vital signs (heart rate>130 bpm, heart rate<40 bpm, respiratory rate>30 breaths per minute, respiratory rate< breaths 8 per minute, oxygen saturation<90%, systolic blood pressure<90 mmHg) as binary variables for each patient enrolled. Univariate and multi-variable logistic regression models were created to determine the ability of the trigger vital signs to predict ICU admission. Results: Total of 68 554 patient encounters were included in the analysis. Of these, 2 355 [3.4%, 95% confidence intervals (CI) 3.3%-3.6%] patients exhibited trigger vital signs, and 1 135 (1.7%, 95% CI 1.6%-1.8%) patients were admitted to ICU. All trigger vital signs were strongly associated with admission to the ICU and demonstrated higher odds of ICU admission with HR<40 (odds ratio 5.2, with 95% CI 2.7-10.1) being the best predictor among the studied covariates. The likelihood of ICU admission increased in a linear fashion with the number of trigger vital signs exhibited. Conclusions: Trigger vital signs serve as predictors that an ED patient may need admission to the ICU and may serve as a tool to expedite disposition of these resource-intensive patients.