BACKGROUND Patients with different stages of colorectal cancer(CRC)exhibit different abdominal computed tomography(CT)signs.Therefore,the influence of CT signs on CRC prognosis must be determined.AIM To observe abdomi...BACKGROUND Patients with different stages of colorectal cancer(CRC)exhibit different abdominal computed tomography(CT)signs.Therefore,the influence of CT signs on CRC prognosis must be determined.AIM To observe abdominal CT signs in patients with CRC and analyze the correlation between the CT signs and postoperative prognosis.METHODS The clinical history and CT imaging results of 88 patients with CRC who underwent radical surgery at Xingtan Hospital Affiliated to Shunde Hospital of Southern Medical University were retrospectively analyzed.Univariate and multivariate Cox regression analyses were used to explore the independent risk factors for postoperative death in patients with CRC.The three-year survival rate was analyzed using the Kaplan-Meier curve,and the correlation between postoperative survival time and abdominal CT signs in patients with CRC was analyzed using Spearman correlation analysis.RESULTS For patients with CRC,the three-year survival rate was 73.86%.The death group exhibited more severe characteristics than the survival group.A multivariate Cox regression model analysis showed that body mass index(BMI),degree of periintestinal infiltration,tumor size,and lymph node CT value were independent factors influencing postoperative death(P<0.05 for all).Patients with characteristics typical to the death group had a low three-year survival rate(log-rankχ2=66.487,11.346,12.500,and 27.672,respectively,P<0.05 for all).The survival time of CRC patients was negatively correlated with BMI,degree of periintestinal infiltration,tumor size,lymph node CT value,mean tumor long-axis diameter,and mean tumor short-axis diameter(r=-0.559,0.679,-0.430,-0.585,-0.425,and-0.385,respectively,P<0.05 for all).BMI was positively correlated with the degree of periintestinal invasion,lymph node CT value,and mean tumor short-axis diameter(r=0.303,0.431,and 0.437,respectively,P<0.05 for all).CONCLUSION The degree of periintestinal infiltration,tumor size,and lymph node CT value are crucial for evaluating the prognosis of patients with CRC.展开更多
Objective:This study aimed to determine the effectiveness of aromatherapy with lavender essential oil compared to progressive muscle relaxation(PMR)on anxiety and vital signs of patients under spinal anesthesia.Materi...Objective:This study aimed to determine the effectiveness of aromatherapy with lavender essential oil compared to progressive muscle relaxation(PMR)on anxiety and vital signs of patients under spinal anesthesia.Materials and Methods:This clinical trial was conducted on 120 spinal anesthesia candidates who were randomly assigned into three groups of 40 including control,PMR(Jacobsen group),and aromatherapy.The state-trait anxiety inventory was completed on surgery day and 15 min after the end of the intervention by the samples of all three groups,and at the same time as completing the questionnaire,vital signs were also measured and recorded.Results:The mean score of anxiety after intervention was lower than that before the intervention in the aromatherapy group(P<0.001).The mean score of anxiety in the aromatherapy group was significantly lower than that in the Jacobsen group(P<0.001).Moreover,data analysis showed a significant decrease in the mean arterial blood pressure scores of the PMR(P=008)and aromatherapy(P<0.001)groups and a statistically significant increase in the mean heart rate scores in the control group(P=0.002).Conclusion:The use of aromatherapy with lavender is more effective than PMR therapy in reducing the anxiety level of patients undergoing spinal anesthesia.Due to the high level of anxiety and its serious effects on the patient’s hemodynamics,aromatherapy with lavender can be used as an easy and cheap method to reduce anxiety in operation rooms.展开更多
This study presents results from sentiment analysis of Dynamic message sign (DMS) message content, focusing on messages that include numbers of road fatalities. As a traffic management tool, DMS plays a role in influe...This study presents results from sentiment analysis of Dynamic message sign (DMS) message content, focusing on messages that include numbers of road fatalities. As a traffic management tool, DMS plays a role in influencing driver behavior and assisting transportation agencies in achieving safe and efficient traffic movement. However, the psychological and behavioral effects of displaying fatality numbers on DMS remain poorly understood;hence, it is important to know the potential impacts of displaying such messages. The Iowa Department of Transportation displays the number of fatalities on a first screen, followed by a supplemental message hoping to promote safe driving;an example is “19 TRAFFIC DEATHS THIS YEAR IF YOU HAVE A SUPER BOWL DON’T DRIVE HIGH.” We employ natural language processing to decode the sentiment and undertone of the supplementary message and investigate how they influence driving speeds. According to the results of a mixed effect model, drivers reduced speeds marginally upon encountering DMS fatality text with a positive sentiment with a neutral undertone. This category had the largest associated amount of speed reduction, while messages with negative sentiment with a negative undertone had the second largest amount of speed reduction, greater than other combinations, including positive sentiment with a positive undertone.展开更多
This paper applies Newmark’s communicative translation and semantic translation theory to analyzing the English translation of Chinese public signs and its pragmatic functions. It finds that communicative translation...This paper applies Newmark’s communicative translation and semantic translation theory to analyzing the English translation of Chinese public signs and its pragmatic functions. It finds that communicative translation is typically used to fulfill the communicative function of public signs. Both communicative and semantic translation are employed to adapt to different situational contexts, in order to preserve the pragmatic functions of the Chinese public signs. The differences between Chinese and English lead to pragmatic errors in translation, making the translator’s bilingual proficiency and familiarity with English culture necessary. The fundamental principle of public sign translation is to be concise and clear, which often requires modifying some complex rhetorical devices from Chinese in translation.展开更多
This paper contends that the public sign is a kind of text with such vocative functions as indicating,instructing,restricting,prohibiting,persuading,and publicizing,so it falls into the type of vocative texts.The pape...This paper contends that the public sign is a kind of text with such vocative functions as indicating,instructing,restricting,prohibiting,persuading,and publicizing,so it falls into the type of vocative texts.The paper suggests that conveying the vocative function of the public sign is the essential task of the translator,so as to achieve the intended effect of the public sign.展开更多
As an integral part of children’s safety education,safety signs hold significant importance for preschoolers’safety.This study aims to investigate the comprehension level of safety signs and its influencing factors ...As an integral part of children’s safety education,safety signs hold significant importance for preschoolers’safety.This study aims to investigate the comprehension level of safety signs and its influencing factors among preschoolers and explore the role of background factors such as safety education in children’s learning of safety signs.Sixty-seven preschoolers participated in the questionnaire investigation on 11 safety signs.The results were encoded by a binary method and subjected to descriptive analysis and multiple correspondence analysis.The results indicated that preschoolers can understand symbols,but there is a certain degree of arbitrariness.The existing thematic education fails to improve their understanding of safety signs.This study provides a theoretical basis for improving and optimizing child safety education.展开更多
Background:Occupational therapists can play a key role in early identifica-tion of delay at the population health level by providing education to public health employees on how to implement developmental monitoring wi...Background:Occupational therapists can play a key role in early identifica-tion of delay at the population health level by providing education to public health employees on how to implement developmental monitoring with caregivers of children birth to age 5.Methods:A pretest posttest design was utilized to assess the online education and training that was provided to Department of Public Health employees(N=339),including Head Start,Special Supplemental Nutrition Program for Women,Infants and Children,Home Visiting,and Early Intervention.Results:Analysis of pretest‐posttest survey data showed significant results for all 12 key learning outcomes.Six out of 12 outcomes were found to have a large effect size(d>0.8),4 outcomes indicated a medium effect size(d>0.5),and 2 outcomes had a small effect size(d>0.2).Participants gained knowledge of the“Learn the Signs.Act Early.”(LTSAE)developmental monitoring program,the difference between developmental monitoring and screening,the state's referral system and age‐appropriate parental engagement activities through knowledge of child development.Conclusions:Occupational therapists are child development specialists who can provide education on developmental monitoring and activities for parental engagement.The online course proved to be an effective platform to promote LTSAE within state agencies.展开更多
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 mo...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.展开更多
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 go...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.展开更多
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 characteris...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.展开更多
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 ho...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.展开更多
BACKGROUND Appendiceal intussusception is a pathological condition in which the appendix is inverted into the cecum,which may cause symptoms that resemble those of other gastrointestinal disorders and may induce intes...BACKGROUND Appendiceal intussusception is a pathological condition in which the appendix is inverted into the cecum,which may cause symptoms that resemble those of other gastrointestinal disorders and may induce intestinal obstruction.The rarity of this case presentation is the co-occurrence of appendiceal intussusception and cecal adenocarcinoma,a combination that to our knowledge has not previously been reported in the medical literature.This case provides new insights into the complexities of diagnosing and managing overlapping pathologies.CASE SUMMARY A 25-year-old woman presented with persistent periumbilical pain and bloody stools.An initial biopsy showed cecal cancer;however,subsequent colonoscopy and computed tomography findings raised the suspicion of appendiceal intussus-ception,which was later confirmed postoperatively.This unique case was charac-terized by a combination of intussusception and adenocarcinoma of the cecum.The intervention included a laparoscopic right hemicolectomy,which led to the histopathological diagnosis of mucinous adenocarcinoma with appendiceal intussusception.The patient recovered well postoperatively and was advised to initiate adjuvant chemotherapy.This case highlights not only the importance of considering appendiceal intussusception in the differential diagnosis,but also the possibility of appendicitis and the atypical presentation of neoplastic lesions.CONCLUSIONS Physicians should consider the possibility of appendiceal intussusception in cases of atypical appendicitis,particularly when associated with neoplastic presentation.展开更多
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 ...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.展开更多
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 automa...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.展开更多
We theoretically study nonlinear thermoelectric transport through a topological superconductor nanowire hosting Majorana bound states(MBSs) at its two ends, a system named as Majorana nanowire(MNW). We consider that t...We theoretically study nonlinear thermoelectric transport through a topological superconductor nanowire hosting Majorana bound states(MBSs) at its two ends, a system named as Majorana nanowire(MNW). We consider that the MNW is coupled to the left and right normal metallic leads subjected to either bias voltage or temperature gradient. We focus our attention on the sign change of nonlinear Seebeck and Peltier coefficients induced by mechanisms related to the MBSs, by which the possible existence of MBSs might be proved. Our results show that for a fixed temperature difference between the two leads, the sign of the nonlinear Seebeck coefficient(thermopower) can be reversed by changing the overlap amplitude between the MBSs or the system equilibrium temperature, which are similar to the cases in linear response regime. By optimizing the MBS–MBS interaction amplitude and system equilibrium temperature, we find that the temperature difference may also induce sign change of the nonlinear thermopower. For zero temperature difference and finite bias voltage, both the sign and magnitude of nonlinear Peltier coefficient can be adjusted by changing the bias voltage or overlap amplitude between the MBSs. In the presence of both bias voltage and temperature difference, we show that the electrical current at zero Fermi level and the states induced by overlap between the MBSs keep unchanged, regardless of the amplitude of temperature difference. We also find that the direction of the heat current driven by bias voltage may be changed by weak temperature difference.展开更多
The correct identification of traffic signs plays an important role in automatic driving technology and road safety driving.Therefore,to address the problems of misdetection and omission in traffic sign detection due ...The correct identification of traffic signs plays an important role in automatic driving technology and road safety driving.Therefore,to address the problems of misdetection and omission in traffic sign detection due to the variety of sign types,significant size differences and complex background information,an improved traffic sign detection model for RT-DETR was proposed in this study.Firstly,the HiLo attention mechanism was added to the Attention-based Intra-scale Feature Interaction,which further enhanced the feature extraction capability of the network and improved the detection efficiency on high-resolution images.Secondly,the CAFMFusion feature fusion mechanism was designed,which enabled the network to pay attention to the features in different regions in each channel.Based on this,the model could better capture the remote dependencies and neighborhood feature correlation,improving the feature fusion capability of the model.Finally,the MPDIoU was used as the loss function of the improved model to achieve faster convergence and more accurate regression results.The experimental results on the TT100k-2021 traffic sign dataset showed that the improved model achieves the performance with a precision value of 90.2%,recall value of 88.1%and mAP@0.5 value of 91.6%,which are 4.6%,5.8%,and 4.4%better than the original RT-DETR model respectively.The model effectively improves the problem of poor traffic sign detection and has greater practical value.展开更多
Hand gestures have been used as a significant mode of communication since the advent of human civilization.By facilitating human-computer interaction(HCI),hand gesture recognition(HGRoc)technology is crucial for seaml...Hand gestures have been used as a significant mode of communication since the advent of human civilization.By facilitating human-computer interaction(HCI),hand gesture recognition(HGRoc)technology is crucial for seamless and error-free HCI.HGRoc technology is pivotal in healthcare and communication for the deaf community.Despite significant advancements in computer vision-based gesture recognition for language understanding,two considerable challenges persist in this field:(a)limited and common gestures are considered,(b)processing multiple channels of information across a network takes huge computational time during discriminative feature extraction.Therefore,a novel hand vision-based convolutional neural network(CNN)model named(HVCNNM)offers several benefits,notably enhanced accuracy,robustness to variations,real-time performance,reduced channels,and scalability.Additionally,these models can be optimized for real-time performance,learn from large amounts of data,and are scalable to handle complex recognition tasks for efficient human-computer interaction.The proposed model was evaluated on two challenging datasets,namely the Massey University Dataset(MUD)and the American Sign Language(ASL)Alphabet Dataset(ASLAD).On the MUD and ASLAD datasets,HVCNNM achieved a score of 99.23% and 99.00%,respectively.These results demonstrate the effectiveness of CNN as a promising HGRoc approach.The findings suggest that the proposed model have potential roles in applications such as sign language recognition,human-computer interaction,and robotics.展开更多
Autonomous driving technology has entered a period of rapid development,and traffic sign detection is one of the important tasks.Existing target detection networks are difficult to adapt to scenarios where target size...Autonomous driving technology has entered a period of rapid development,and traffic sign detection is one of the important tasks.Existing target detection networks are difficult to adapt to scenarios where target sizes are seriously imbalanced,and traffic sign targets are small and have unclear features,which makes detection more difficult.Therefore,we propose aHybrid Feature Fusion Traffic Sign detection algorithmbased onYOLOv7(HFFTYOLO).First,a self-attention mechanism is incorporated at the end of the backbone network to calculate feature interactions within scales;Secondly,the cross-scale fusion part of the neck introduces a bottom-up multi-path fusion method.Design reuse paths at the end of the neck,paying particular attention to cross-scale fusion of highlevel features.In addition,we found the appropriate channel width through a lot of experiments and reduced the superfluous parameters.In terms of training,a newregression lossCMPDIoUis proposed,which not only considers the problem of loss degradation when the aspect ratio is the same but the width and height are different,but also enables the penalty term to dynamically change at different scales.Finally,our proposed improved method shows excellent results on the TT100K dataset.Compared with the baseline model,without increasing the number of parameters and computational complexity,AP0.5 and AP increased by 2.2%and 2.7%,respectively,reaching 92.9%and 58.1%.展开更多
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 Japane...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.展开更多
文摘BACKGROUND Patients with different stages of colorectal cancer(CRC)exhibit different abdominal computed tomography(CT)signs.Therefore,the influence of CT signs on CRC prognosis must be determined.AIM To observe abdominal CT signs in patients with CRC and analyze the correlation between the CT signs and postoperative prognosis.METHODS The clinical history and CT imaging results of 88 patients with CRC who underwent radical surgery at Xingtan Hospital Affiliated to Shunde Hospital of Southern Medical University were retrospectively analyzed.Univariate and multivariate Cox regression analyses were used to explore the independent risk factors for postoperative death in patients with CRC.The three-year survival rate was analyzed using the Kaplan-Meier curve,and the correlation between postoperative survival time and abdominal CT signs in patients with CRC was analyzed using Spearman correlation analysis.RESULTS For patients with CRC,the three-year survival rate was 73.86%.The death group exhibited more severe characteristics than the survival group.A multivariate Cox regression model analysis showed that body mass index(BMI),degree of periintestinal infiltration,tumor size,and lymph node CT value were independent factors influencing postoperative death(P<0.05 for all).Patients with characteristics typical to the death group had a low three-year survival rate(log-rankχ2=66.487,11.346,12.500,and 27.672,respectively,P<0.05 for all).The survival time of CRC patients was negatively correlated with BMI,degree of periintestinal infiltration,tumor size,lymph node CT value,mean tumor long-axis diameter,and mean tumor short-axis diameter(r=-0.559,0.679,-0.430,-0.585,-0.425,and-0.385,respectively,P<0.05 for all).BMI was positively correlated with the degree of periintestinal invasion,lymph node CT value,and mean tumor short-axis diameter(r=0.303,0.431,and 0.437,respectively,P<0.05 for all).CONCLUSION The degree of periintestinal infiltration,tumor size,and lymph node CT value are crucial for evaluating the prognosis of patients with CRC.
基金financially supported by Arak University of Medical Sciences.
文摘Objective:This study aimed to determine the effectiveness of aromatherapy with lavender essential oil compared to progressive muscle relaxation(PMR)on anxiety and vital signs of patients under spinal anesthesia.Materials and Methods:This clinical trial was conducted on 120 spinal anesthesia candidates who were randomly assigned into three groups of 40 including control,PMR(Jacobsen group),and aromatherapy.The state-trait anxiety inventory was completed on surgery day and 15 min after the end of the intervention by the samples of all three groups,and at the same time as completing the questionnaire,vital signs were also measured and recorded.Results:The mean score of anxiety after intervention was lower than that before the intervention in the aromatherapy group(P<0.001).The mean score of anxiety in the aromatherapy group was significantly lower than that in the Jacobsen group(P<0.001).Moreover,data analysis showed a significant decrease in the mean arterial blood pressure scores of the PMR(P=008)and aromatherapy(P<0.001)groups and a statistically significant increase in the mean heart rate scores in the control group(P=0.002).Conclusion:The use of aromatherapy with lavender is more effective than PMR therapy in reducing the anxiety level of patients undergoing spinal anesthesia.Due to the high level of anxiety and its serious effects on the patient’s hemodynamics,aromatherapy with lavender can be used as an easy and cheap method to reduce anxiety in operation rooms.
文摘This study presents results from sentiment analysis of Dynamic message sign (DMS) message content, focusing on messages that include numbers of road fatalities. As a traffic management tool, DMS plays a role in influencing driver behavior and assisting transportation agencies in achieving safe and efficient traffic movement. However, the psychological and behavioral effects of displaying fatality numbers on DMS remain poorly understood;hence, it is important to know the potential impacts of displaying such messages. The Iowa Department of Transportation displays the number of fatalities on a first screen, followed by a supplemental message hoping to promote safe driving;an example is “19 TRAFFIC DEATHS THIS YEAR IF YOU HAVE A SUPER BOWL DON’T DRIVE HIGH.” We employ natural language processing to decode the sentiment and undertone of the supplementary message and investigate how they influence driving speeds. According to the results of a mixed effect model, drivers reduced speeds marginally upon encountering DMS fatality text with a positive sentiment with a neutral undertone. This category had the largest associated amount of speed reduction, while messages with negative sentiment with a negative undertone had the second largest amount of speed reduction, greater than other combinations, including positive sentiment with a positive undertone.
文摘This paper applies Newmark’s communicative translation and semantic translation theory to analyzing the English translation of Chinese public signs and its pragmatic functions. It finds that communicative translation is typically used to fulfill the communicative function of public signs. Both communicative and semantic translation are employed to adapt to different situational contexts, in order to preserve the pragmatic functions of the Chinese public signs. The differences between Chinese and English lead to pragmatic errors in translation, making the translator’s bilingual proficiency and familiarity with English culture necessary. The fundamental principle of public sign translation is to be concise and clear, which often requires modifying some complex rhetorical devices from Chinese in translation.
文摘This paper contends that the public sign is a kind of text with such vocative functions as indicating,instructing,restricting,prohibiting,persuading,and publicizing,so it falls into the type of vocative texts.The paper suggests that conveying the vocative function of the public sign is the essential task of the translator,so as to achieve the intended effect of the public sign.
基金Research on the Development of Art Education in Rural Community Kindergarten,a general project of key research base of Humanities and Social Sciences in Sichuan Universities“Rural Early Childhood Education Research Center”(NYJ20190605)。
文摘As an integral part of children’s safety education,safety signs hold significant importance for preschoolers’safety.This study aims to investigate the comprehension level of safety signs and its influencing factors among preschoolers and explore the role of background factors such as safety education in children’s learning of safety signs.Sixty-seven preschoolers participated in the questionnaire investigation on 11 safety signs.The results were encoded by a binary method and subjected to descriptive analysis and multiple correspondence analysis.The results indicated that preschoolers can understand symbols,but there is a certain degree of arbitrariness.The existing thematic education fails to improve their understanding of safety signs.This study provides a theoretical basis for improving and optimizing child safety education.
基金OT18‐1802:National Capacity Building Center on Disability in Public Health,Grant/Award Number:SUBAWARD AGREEMENT#28‐21‐8814。
文摘Background:Occupational therapists can play a key role in early identifica-tion of delay at the population health level by providing education to public health employees on how to implement developmental monitoring with caregivers of children birth to age 5.Methods:A pretest posttest design was utilized to assess the online education and training that was provided to Department of Public Health employees(N=339),including Head Start,Special Supplemental Nutrition Program for Women,Infants and Children,Home Visiting,and Early Intervention.Results:Analysis of pretest‐posttest survey data showed significant results for all 12 key learning outcomes.Six out of 12 outcomes were found to have a large effect size(d>0.8),4 outcomes indicated a medium effect size(d>0.5),and 2 outcomes had a small effect size(d>0.2).Participants gained knowledge of the“Learn the Signs.Act Early.”(LTSAE)developmental monitoring program,the difference between developmental monitoring and screening,the state's referral system and age‐appropriate parental engagement activities through knowledge of child development.Conclusions:Occupational therapists are child development specialists who can provide education on developmental monitoring and activities for parental engagement.The online course proved to be an effective platform to promote LTSAE within state agencies.
基金supported by the National Natural Science Foundation of China (Grant Nos. 51874183 and 51874182)the National Key Research and Development Program of China (Grant No. 2018YFC0809300)。
文摘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.
文摘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.
文摘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.
文摘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.
基金the National Natural Science Foundation of China,No.82060440.
文摘BACKGROUND Appendiceal intussusception is a pathological condition in which the appendix is inverted into the cecum,which may cause symptoms that resemble those of other gastrointestinal disorders and may induce intestinal obstruction.The rarity of this case presentation is the co-occurrence of appendiceal intussusception and cecal adenocarcinoma,a combination that to our knowledge has not previously been reported in the medical literature.This case provides new insights into the complexities of diagnosing and managing overlapping pathologies.CASE SUMMARY A 25-year-old woman presented with persistent periumbilical pain and bloody stools.An initial biopsy showed cecal cancer;however,subsequent colonoscopy and computed tomography findings raised the suspicion of appendiceal intussus-ception,which was later confirmed postoperatively.This unique case was charac-terized by a combination of intussusception and adenocarcinoma of the cecum.The intervention included a laparoscopic right hemicolectomy,which led to the histopathological diagnosis of mucinous adenocarcinoma with appendiceal intussusception.The patient recovered well postoperatively and was advised to initiate adjuvant chemotherapy.This case highlights not only the importance of considering appendiceal intussusception in the differential diagnosis,but also the possibility of appendicitis and the atypical presentation of neoplastic lesions.CONCLUSIONS Physicians should consider the possibility of appendiceal intussusception in cases of atypical appendicitis,particularly when associated with neoplastic presentation.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.62103375 and 62006106)the Zhejiang Provincial Philosophy and Social Science Planning Project(Grant No.22NDJC009Z)+1 种基金the Education Ministry Humanities and Social Science Foundation of China(Grant Nos.19YJCZH056 and 21YJC630120)the Natural Science Foundation of Zhejiang Province of China(Grant Nos.LY23F030003 and LQ21F020005).
文摘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.
基金supported from the National Philosophy and Social Sciences Foundation(Grant No.20BTQ065).
文摘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.
基金Project supported by the National Natural Science Foundation of China(Grant No.12264037)the Innovation Team of Colleges and Universities in Guangdong Province(Grant No.2021KCXTD040)+2 种基金Guangdong Province Education Department(Grant No.2023KTSCX174)the Key Laboratory of Guangdong Higher Education Institutes(Grant No.2023KSYS011)Science and Technology Bureau of Zhongshan(Grant No.2023B2035)。
文摘We theoretically study nonlinear thermoelectric transport through a topological superconductor nanowire hosting Majorana bound states(MBSs) at its two ends, a system named as Majorana nanowire(MNW). We consider that the MNW is coupled to the left and right normal metallic leads subjected to either bias voltage or temperature gradient. We focus our attention on the sign change of nonlinear Seebeck and Peltier coefficients induced by mechanisms related to the MBSs, by which the possible existence of MBSs might be proved. Our results show that for a fixed temperature difference between the two leads, the sign of the nonlinear Seebeck coefficient(thermopower) can be reversed by changing the overlap amplitude between the MBSs or the system equilibrium temperature, which are similar to the cases in linear response regime. By optimizing the MBS–MBS interaction amplitude and system equilibrium temperature, we find that the temperature difference may also induce sign change of the nonlinear thermopower. For zero temperature difference and finite bias voltage, both the sign and magnitude of nonlinear Peltier coefficient can be adjusted by changing the bias voltage or overlap amplitude between the MBSs. In the presence of both bias voltage and temperature difference, we show that the electrical current at zero Fermi level and the states induced by overlap between the MBSs keep unchanged, regardless of the amplitude of temperature difference. We also find that the direction of the heat current driven by bias voltage may be changed by weak temperature difference.
文摘The correct identification of traffic signs plays an important role in automatic driving technology and road safety driving.Therefore,to address the problems of misdetection and omission in traffic sign detection due to the variety of sign types,significant size differences and complex background information,an improved traffic sign detection model for RT-DETR was proposed in this study.Firstly,the HiLo attention mechanism was added to the Attention-based Intra-scale Feature Interaction,which further enhanced the feature extraction capability of the network and improved the detection efficiency on high-resolution images.Secondly,the CAFMFusion feature fusion mechanism was designed,which enabled the network to pay attention to the features in different regions in each channel.Based on this,the model could better capture the remote dependencies and neighborhood feature correlation,improving the feature fusion capability of the model.Finally,the MPDIoU was used as the loss function of the improved model to achieve faster convergence and more accurate regression results.The experimental results on the TT100k-2021 traffic sign dataset showed that the improved model achieves the performance with a precision value of 90.2%,recall value of 88.1%and mAP@0.5 value of 91.6%,which are 4.6%,5.8%,and 4.4%better than the original RT-DETR model respectively.The model effectively improves the problem of poor traffic sign detection and has greater practical value.
基金funded by Researchers Supporting Project Number(RSPD2024 R947),King Saud University,Riyadh,Saudi Arabia.
文摘Hand gestures have been used as a significant mode of communication since the advent of human civilization.By facilitating human-computer interaction(HCI),hand gesture recognition(HGRoc)technology is crucial for seamless and error-free HCI.HGRoc technology is pivotal in healthcare and communication for the deaf community.Despite significant advancements in computer vision-based gesture recognition for language understanding,two considerable challenges persist in this field:(a)limited and common gestures are considered,(b)processing multiple channels of information across a network takes huge computational time during discriminative feature extraction.Therefore,a novel hand vision-based convolutional neural network(CNN)model named(HVCNNM)offers several benefits,notably enhanced accuracy,robustness to variations,real-time performance,reduced channels,and scalability.Additionally,these models can be optimized for real-time performance,learn from large amounts of data,and are scalable to handle complex recognition tasks for efficient human-computer interaction.The proposed model was evaluated on two challenging datasets,namely the Massey University Dataset(MUD)and the American Sign Language(ASL)Alphabet Dataset(ASLAD).On the MUD and ASLAD datasets,HVCNNM achieved a score of 99.23% and 99.00%,respectively.These results demonstrate the effectiveness of CNN as a promising HGRoc approach.The findings suggest that the proposed model have potential roles in applications such as sign language recognition,human-computer interaction,and robotics.
基金funded by National Natural Science Foundation of China(Grant No.U2004163).
文摘Autonomous driving technology has entered a period of rapid development,and traffic sign detection is one of the important tasks.Existing target detection networks are difficult to adapt to scenarios where target sizes are seriously imbalanced,and traffic sign targets are small and have unclear features,which makes detection more difficult.Therefore,we propose aHybrid Feature Fusion Traffic Sign detection algorithmbased onYOLOv7(HFFTYOLO).First,a self-attention mechanism is incorporated at the end of the backbone network to calculate feature interactions within scales;Secondly,the cross-scale fusion part of the neck introduces a bottom-up multi-path fusion method.Design reuse paths at the end of the neck,paying particular attention to cross-scale fusion of highlevel features.In addition,we found the appropriate channel width through a lot of experiments and reduced the superfluous parameters.In terms of training,a newregression lossCMPDIoUis proposed,which not only considers the problem of loss degradation when the aspect ratio is the same but the width and height are different,but also enables the penalty term to dynamically change at different scales.Finally,our proposed improved method shows excellent results on the TT100K dataset.Compared with the baseline model,without increasing the number of parameters and computational complexity,AP0.5 and AP increased by 2.2%and 2.7%,respectively,reaching 92.9%and 58.1%.
基金supported by the Competitive Research Fund of the University of Aizu,Japan.
文摘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.
