Intrahepatic portal venous systems in adult patients with cavernous transformation of portal vein: Imaging features and a new classification

Background: Cavernous transformation of the portal vein(CTPV) due to portal vein obstruction is a rare vascular anomaly defined as the formation of multiple collateral vessels in the hepatic hilum. This study aimed to investigate the imaging features of intrahepatic portal vein in adult patients with CTPV and establish the relationship between the manifestations of intrahepatic portal vein and the progression of CTPV. Methods: We retrospectively analyzed 14 CTPV patients in Beijing Tsinghua Changgung Hospital. All patients underwent both direct portal venography(DPV) and computed tomography angiography(CTA) to reveal the manifestations of the portal venous system. The vessels measured included the left portal vein(LPV), right portal vein(RPV), main portal vein(MPV) and the portal vein bifurcation(PVB). Results: Nine males and 5 females, with a median age of 40.5 years, were included in the study. No significant difference was found in the diameters of the LPV or RPV measured by DPV and CTA. The visualization in terms of LPV, RPV and PVB measured by DPV was higher than that by CTA. There was a significant association between LPV/RPV and PVB/MPV in term of visibility revealed with DPV( P = 0.01), while this association was not observed with CTA. According to the imaging features of the portal vein measured by DPV, CTPV was classified into three categories to facilitate the diagnosis and treatment. Conclusions: DPV was more accurate than CTA for revealing the course of the intrahepatic portal vein in patients with CTPV. The classification of CTPV, that originated from the imaging features of the portal vein revealed by DPV, may provide a new perspective for the diagnosis and treatment of CTPV.

Performance evaluation of seven multi-label classification methods on real-world patent and publication datasets

Purpose:Many science,technology and innovation(STI)resources are attached with several different labels.To assign automatically the resulting labels to an interested instance,many approaches with good performance on the benchmark datasets have been proposed for multi-label classification task in the literature.Furthermore,several open-source tools implementing these approaches have also been developed.However,the characteristics of real-world multi-label patent and publication datasets are not completely in line with those of benchmark ones.Therefore,the main purpose of this paper is to evaluate comprehensively seven multi-label classification methods on real-world datasets.Research limitations:Three real-world datasets differ in the following aspects:statement,data quality,and purposes.Additionally,open-source tools designed for multi-label classification also have intrinsic differences in their approaches for data processing and feature selection,which in turn impacts the performance of a multi-label classification approach.In the near future,we will enhance experimental precision and reinforce the validity of conclusions by employing more rigorous control over variables through introducing expanded parameter settings.Practical implications:The observed Macro F1 and Micro F1 scores on real-world datasets typically fall short of those achieved on benchmark datasets,underscoring the complexity of real-world multi-label classification tasks.Approaches leveraging deep learning techniques offer promising solutions by accommodating the hierarchical relationships and interdependencies among labels.With ongoing enhancements in deep learning algorithms and large-scale models,it is expected that the efficacy of multi-label classification tasks will be significantly improved,reaching a level of practical utility in the foreseeable future.Originality/value:(1)Seven multi-label classification methods are comprehensively compared on three real-world datasets.(2)The TextCNN and TextRCNN models perform better on small-scale datasets with more complex hierarchical structure of labels and more balanced document-label distribution.(3)The MLkNN method works better on the larger-scale dataset with more unbalanced document-label distribution.

Anticancer Activity of Rice Callus Suspension Cultures from Aromatic Varieties and Metabolites Regulated in Treated Cancer Cell Lines

Tissue culture techniques were used to produce large amounts of bioactive compounds with medicinal potential, overcoming space and time constraints for cancer prevention. Rice callus suspension cultures(RCSC) and seed extracts prepared from aromatic rice varieties were used to evaluate the cytotoxic impact on human colon and lung cancer cell lines, as well as a normal control cell line, using Taxol as a positive control. RCSC and seed extracts from two Indian aromatic rice varieties were applied at different concentrations to treat the cancer cell lines and normal lung fibroblasts over varying time intervals. Apoptosis was assessed in 1:5 dilutions of the A549 and HT-29 cell lines treated with RCSC for 72 h, using propidium iodide staining and flow cytometry. RCSC showed a more potent cytotoxic effect than seed extracts with minimal effect on the normal cell line, in contrast to Taxol. Confocal microscopy and flow cytometry further confirmed the apoptotic effect of RCSC. Gas chromatography-mass spectrometry-based metabolic profiling identified metabolites involved in cytotoxicity and highlighted altered pathways. RCSC is proposed as an alternative source for the development of novel anticancer drugs with reduced side effects.

Classification of Sailboat Tell Tail Based on Deep Learning

The tell tail is usually placed on the triangular sail to display the running state of the air flow on the sail surface.It is of great significance to make accurate judgement on the drift of the tell tail of the sailboat during sailing for the best sailing effect.Normally it is difficult for sailors to keep an eye for a long time on the tell sail for accurate judging its changes,affected by strong sunlight and visual fatigue.In this case,we adopt computer vision technology in hope of helping the sailors judge the changes of the tell tail in ease with ease.This paper proposes for the first time a method to classify sailboat tell tails based on deep learning and an expert guidance system,supported by a sailboat tell tail classification data set on the expert guidance system of interpreting the tell tails states in different sea wind conditions,including the feature extraction performance.Considering the expression capabilities that vary with the computational features in different visual tasks,the paper focuses on five tell tail computing features,which are recoded by an automatic encoder and classified by a SVM classifier.All experimental samples were randomly divided into five groups,and four groups were selected from each group as the training set to train the classifier.The remaining one group was used as the test set for testing.The highest resolution value of the ResNet network was 80.26%.To achieve better operational results on the basis of deep computing features obtained through the ResNet network in the experiments.The method can be used to assist the sailors in making better judgement about the tell tail changes during sailing.

Comprehensive understanding of glioblastoma molecular phenotypes:classification,characteristics,and transition

Among central nervous system-associated malignancies,glioblastoma(GBM)is the most common and has the highest mortality rate.The high heterogeneity of GBM cell types and the complex tumor microenvironment frequently lead to tumor recurrence and sudden relapse in patients treated with temozolomide.In precision medicine,research on GBM treatment is increasingly focusing on molecular subtyping to precisely characterize the cellular and molecular heterogeneity,as well as the refractory nature of GBM toward therapy.Deep understanding of the different molecular expression patterns of GBM subtypes is critical.Researchers have recently proposed tetra fractional or tripartite methods for detecting GBM molecular subtypes.The various molecular subtypes of GBM show significant differences in gene expression patterns and biological behaviors.These subtypes also exhibit high plasticity in their regulatory pathways,oncogene expression,tumor microenvironment alterations,and differential responses to standard therapy.Herein,we summarize the current molecular typing scheme of GBM and the major molecular/genetic characteristics of each subtype.Furthermore,we review the mesenchymal transition mechanisms of GBM under various regulators.

Investigation of the Acceptability of Cultured Meat in University Students

Background: Over the past 20 years, cultured meat has drawn a lot of public attention as a potential solution to issues with animal husbandry, including inadequate use of natural sources, improper animal welfare practices, and possible risks to public health and safety. The novel method of producing meat through culture reduces the need for animals to produce muscle fiber, thereby obviating the necessity for animal slaughter. Apart from its ethical advantages, cultured meat presents a possible way to fulfill the expanding need for food among growing populations. The purpose of this research was to find out whether Turkish students would be willing to pay for and accept cultured meat. Technique: Method: 371 university students who willingly consented to fill out a questionnaire and provide demographic data make up the research sample. Questions from previous studies on the acceptability of cultured meat were compiled to create the survey. The research’s data collection took place in March and April of 2022. The research was completed in June 2022 after the data had been processed and analyzed. Results: The results showed that the majority of participants were female and had omnivorous eating habits. Based on the results of the Bonferroni correction test, students with a higher intention to purchase and consume cultured meat were those who received economics and business education. Students with two years of university education had a higher overall survey score than those with four years of education (p < 0.05). Furthermore, it is discovered that there is a negative correlation between the participants’ ages and their Factor 2 (using cultured meat as an alternative to industrial meat) and Factor 3 (consuming and purchasing it) section points (r = -109, p = 0.036) (r = -0.121, p = 0.019). In conclusion, university students generally have a negative outlook on health-related issues, such as eating cultured meat as an alternative.

Depression Intensity Classification from Tweets Using Fast Text Based Weighted Soft Voting Ensemble

Predicting depression intensity from microblogs and social media posts has numerous benefits and applications,including predicting early psychological disorders and stress in individuals or the general public.A major challenge in predicting depression using social media posts is that the existing studies do not focus on predicting the intensity of depression in social media texts but rather only perform the binary classification of depression and moreover noisy data makes it difficult to predict the true depression in the social media text.This study intends to begin by collecting relevant Tweets and generating a corpus of 210000 public tweets using Twitter public application programming interfaces(APIs).A strategy is devised to filter out only depression-related tweets by creating a list of relevant hashtags to reduce noise in the corpus.Furthermore,an algorithm is developed to annotate the data into three depression classes:‘Mild,’‘Moderate,’and‘Severe,’based on International Classification of Diseases-10(ICD-10)depression diagnostic criteria.Different baseline classifiers are applied to the annotated dataset to get a preliminary idea of classification performance on the corpus.Further FastText-based model is applied and fine-tuned with different preprocessing techniques and hyperparameter tuning to produce the tuned model,which significantly increases the depression classification performance to an 84%F1 score and 90%accuracy compared to baselines.Finally,a FastText-based weighted soft voting ensemble(WSVE)is proposed to boost the model’s performance by combining several other classifiers and assigning weights to individual models according to their individual performances.The proposed WSVE outperformed all baselines as well as FastText alone,with an F1 of 89%,5%higher than FastText alone,and an accuracy of 93%,3%higher than FastText alone.The proposed model better captures the contextual features of the relatively small sample class and aids in the detection of early depression intensity prediction from tweets with impactful performances.

Classification and rating of disintegrated dolomite strata for slope stability analysis

Although disintegrated dolomite,widely distributed across the globe,has conventionally been a focus of research in underground engineering,the issue of slope stability issues in disintegrated dolomite strata is gaining increasing prominence.This is primarily due to their unique properties,including low strength and loose structure.Current methods for evaluating slope stability,such as basic quality(BQ)and slope stability probability classification(SSPC),do not adequately account for the poor integrity and structural fragmentation characteristic of disintegrated dolomite.To address this challenge,an analysis of the applicability of the limit equilibrium method(LEM),BQ,and SSPC methods was conducted on eight disintegrated dolomite slopes located in Baoshan,Southwest China.However,conflicting results were obtained.Therefore,this paper introduces a novel method,SMRDDS,to provide rapid and accurate assessment of disintegrated dolomite slope stability.This method incorporates parameters such as disintegrated grade,joint state,groundwater conditions,and excavation methods.The findings reveal that six slopes exhibit stability,while two are considered partially unstable.Notably,the proposed method demonstrates a closer match with the actual conditions and is more time-efficient compared with the BQ and SSPC methods.However,due to the limited research on disintegrated dolomite slopes,the results of the SMRDDS method tend to be conservative as a safety precaution.In conclusion,the SMRDDS method can quickly evaluate the current situation of disintegrated dolomite slopes in the field.This contributes significantly to disaster risk reduction for disintegrated dolomite slopes.

Classification of congenital cataracts based on multidimensional phenotypes and its association with visual outcomes

●AIM:To establish a classification for congenital cataracts that can facilitate individualized treatment and help identify individuals with a high likelihood of different visual outcomes.●METHODS:Consecutive patients diagnosed with congenital cataracts and undergoing surgery between January 2005 and November 2021 were recruited.Data on visual outcomes and the phenotypic characteristics of ocular biometry and the anterior and posterior segments were extracted from the patients’medical records.A hierarchical cluster analysis was performed.The main outcome measure was the identification of distinct clusters of eyes with congenital cataracts.●RESULTS:A total of 164 children(299 eyes)were divided into two clusters based on their ocular features.Cluster 1(96 eyes)had a shorter axial length(mean±SD,19.44±1.68 mm),a low prevalence of macular abnormalities(1.04%),and no retinal abnormalities or posterior cataracts.Cluster 2(203 eyes)had a greater axial length(mean±SD,20.42±2.10 mm)and a higher prevalence of macular abnormalities(8.37%),retinal abnormalities(98.52%),and posterior cataracts(4.93%).Compared with the eyes in Cluster 2(57.14%),those in Cluster 1(71.88%)had a 2.2 times higher chance of good best-corrected visual acuity[<0.7 logMAR;OR(95%CI),2.20(1.25–3.81);P=0.006].●CONCLUSION:This retrospective study categorizes congenital cataracts into two distinct clusters,each associated with a different likelihood of visual outcomes.This innovative classification may enable the personalization and prioritization of early interventions for patients who may gain the greatest benefit,thereby making strides toward precision medicine in the field of congenital cataracts.

Pathological and Clinical Correlation European Union-Thyroid Imaging Reporting and Data System (EU-TIRADS) Classification of Thyroid Nodules in Two University Hospitals in Cotonou

Introduction: Since its creation in 2017 by the European community, the EU-TIRADS classification has enjoyed an excellent reputation in several countries around the world. Indeed, several studies conducted in these countries testify to the effectiveness of this tool for the management of nodular thyroid pathology. However, in Benin, the contribution of this classification has not yet been evaluated. It is therefore to overcome this inadequacy that we undertook this study. Objective: Participate in improving the diagnostic and therapeutic management of thyroid nodules at the CNHU HKM in Cotonou and at the CHUZ in Suru-Léré. Methods: This is a cross-sectional study with retrospective data collection spread over a period of 3 years 5 months, from January 2019 to May 2022 and carried out jointly in the Endocrinology Metabolism Nutrition and ORL-CCF departments of the CNHU HKM of Cotonou and in the ORL-CCF department of the CHUZ of Suru-Léré. The study population consisted of patients who consulted the University Clinic of Endocrinology Metabolism Nutrition, the University Clinic of ORL-CCF of the CNHU-HKM and the University Clinic of ORL-CCF of the CHUZ of Suru-Léré for thyroid nodule and who have had surgery. The study data was collected from patients hospitalization records using a survey form. Results: On ultrasound, according to the EU-TIRADS classification, 56.8% of nodules presented a low risk of malignancy (EU-TIRADS 3) compared to respectively 19.8%;23% and 2.5% of nodules with zero (EU-TIRADS 2), intermediate (EU-TIRADS 4) and high (EU-TIRADS 5) risk of malignancy. Regarding the performance of this classification, it is sensitive in 37.5% of cases and has a specificity of 78.5% with a PPV (Positive Predictive Value) and a NPV (Negative Predictive Value) respectively of 6.6 % and 91.6%. Furthermore, the bivariate correlations revealed that the size of the nodule was significantly associated with the malignancy of the nodule (p = 0.014) and the calculated value of the Yule’s Q coefficient (0.375) reflects a moderate intensity of the connection between the EU-TIRADS and histology. Conclusion: the EU-TIRADS classification, due to its excellent NPV, is of great interest for the management of thyroid nodules at the CNHU-HKM of Cotonou and at the CHUZ of Suru-Léré. In view of this, particular emphasis must be placed on its regular and rigorous use.

Development of a novel staging classification for Siewert Ⅱ adenocarcinoma of the esophagogastric junction after neoadjuvant chemotherapy

BACKGROUND Stage classification for Siewert Ⅱ adenocarcinoma of the esophagogastric junction(AEG)treated with neoadjuvant chemotherapy(NAC)has not been established.AIM To investigate the optimal stage classification for Siewert Ⅱ AEG with NAC.METHODS A nomogram was established based on Cox regression model that analyzed variables associated with overall survival(OS)and disease-specific survival(DSS).The nomogram performance in terms of discrimination and calibration ability was evaluated using the likelihood-ratio test,Akaike information criterion,Harrell concordance index,time-receiver operating characteristic curve,and decision curve analysis.RESULTS Data from 725 patients with Siewert type Ⅱ AEG who underwent neoadjuvant therapy and gastrectomy were obtained from the Surveillance,Epidemiology,and End Results database.Univariate and multivariate analyses revealed that sex,marital status,race,ypT stage,and ypN stage were independent prognostic factors of OS,whereas sex,race,ypT stage,and ypN stage were independent prognostic factors for DSS.These factors were incorporated into the OS and DSS nomograms.Our novel nomogram model performed better in terms of OS and DSS prediction compared to the 8th American Joint Committee of Cancer pathological staging system for esophageal and gastric cancer.Finally,a user-friendly web application was developed for clinical use.CONCLUSION The nomogram established specifically for patients with Siewert type Ⅱ AEG receiving NAC demonstrated good prognostic performance.Validation using external data is warranted before its widespread clinical application.

Historiography and Scientific Research of Religious Buildings of the Cucuteni-Trypillian Culture

The purpose of this article is to reveal the historiography and current state of research related to the cult buildings of the Eneolithic period of the Cucuteni-Trypillian cultural community.The article describes the historical path of archaeological discoveries,from the first Trypillian sanctuaries to the discovery of the largest Nebelivka temple complex in Ukraine in 2012.At the same time,the work partially raises the issue of religious beliefs of the ancient farmers of Central Europe in connection with the discovery of their sacred buildings.Since special scientific works have not comprehensively addressed this issue and are still fragmentary in nature,it is important at the present stage of research to make some coverage and systematization of existing materials on this issue.

Evaluation of slope stability through rock mass classification and kinematic analysis of some major slopes along NH-1A from Ramban to Banihal, North Western Himalayas

The network of Himalayan roadways and highways connects some remote regions of valleys or hill slopes,which is vital for India’s socio-economic growth.Due to natural and artificial factors,frequency of slope instabilities along the networks has been increasing over last few decades.Assessment of stability of natural and artificial slopes due to construction of these connecting road networks is significant in safely executing these roads throughout the year.Several rock mass classification methods are generally used to assess the strength and deformability of rock mass.This study assesses slope stability along the NH-1A of Ramban district of North Western Himalayas.Various structurally and non-structurally controlled rock mass classification systems have been applied to assess the stability conditions of 14 slopes.For evaluating the stability of these slopes,kinematic analysis was performed along with geological strength index(GSI),rock mass rating(RMR),continuous slope mass rating(CoSMR),slope mass rating(SMR),and Q-slope in the present study.The SMR gives three slopes as completely unstable while CoSMR suggests four slopes as completely unstable.The stability of all slopes was also analyzed using a design chart under dynamic and static conditions by slope stability rating(SSR)for the factor of safety(FoS)of 1.2 and 1 respectively.Q-slope with probability of failure(PoF)1%gives two slopes as stable slopes.Stable slope angle has been determined based on the Q-slope safe angle equation and SSR design chart based on the FoS.The value ranges given by different empirical classifications were RMR(37-74),GSI(27.3-58.5),SMR(11-59),and CoSMR(3.39-74.56).Good relationship was found among RMR&SSR and RMR&GSI with correlation coefficient(R 2)value of 0.815 and 0.6866,respectively.Lastly,a comparative stability of all these slopes based on the above classification has been performed to identify the most critical slope along this road.

Design of a novel hybrid quantum deep neural network in INEQR images classification

We redesign the parameterized quantum circuit in the quantum deep neural network, construct a three-layer structure as the hidden layer, and then use classical optimization algorithms to train the parameterized quantum circuit, thereby propose a novel hybrid quantum deep neural network(HQDNN) used for image classification. After bilinear interpolation reduces the original image to a suitable size, an improved novel enhanced quantum representation(INEQR) is used to encode it into quantum states as the input of the HQDNN. Multi-layer parameterized quantum circuits are used as the main structure to implement feature extraction and classification. The output results of parameterized quantum circuits are converted into classical data through quantum measurements and then optimized on a classical computer. To verify the performance of the HQDNN, we conduct binary classification and three classification experiments on the MNIST(Modified National Institute of Standards and Technology) data set. In the first binary classification, the accuracy of 0 and 4 exceeds98%. Then we compare the performance of three classification with other algorithms, the results on two datasets show that the classification accuracy is higher than that of quantum deep neural network and general quantum convolutional neural network.

Comparative Study of the Widal Test against Stool Culture in the Diagnosis of Suspected Cases of Typhoid Fever in Some Low Income Communities in the Adamawa Region of Cameroon

Introduction: Infectious diseases constitute a major concern of public health in developing countries. Facilities and well trained staff have been shown to be one of the major obstacles in the rapid and quality diagnosis of these diseases. As such, we carried out an analysis to compare the Widal test and stool culture to identify febrile patients with Salmonella infection. Method: A cross sectional study was conducted to diagnose salmonella infection with out-patients who demonstrated signs of salmonella infection. Serum was harvested from blood collected from 368 (Vina = 234, Mayo Banyo 65, and Djerem = 69) patients accompanied by stool, Widal test was conducted on the spot and stool was taken to a reference laboratory for culture using standard microbiological methods, sociological set up was calculated in percentages, prevalence was calculated using excel while statistical difference was calculated using SPSS. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated to compare the Widal test against stool culture. Results: A total of 368 (50.8% females and 49.2% males) participants took part in the survey. Salmonella prevalence (66.24%) in stool culture in the Vina division was significantly different (p 0.05). The sensitivity,specificity, PPV, and NPV of slide agglutination test against stool culture varied from different areas (Vina: 51.6%, 73.62%, 79.21% and 43.61%;Mayo Banyo: 60.53%, 77.78%, 79.31% and 58.33%;Djerem: 53.18%, 83.73% 73.91% and 67.39%) respectively. Slide agglutination test has a fair agreement with the stool culture (kappa, Vina = 0.202;Mayo Banyo = 0.37 and Djerem = 0.38). Conclusion: Generally, in the three areas of study, the Widal test had a fair correlation with the stool culture;This means the Widal test should not be used alone but in combination with stool culture in the detection of salmonella infections.

Effect of Butternut Squash (Cucurbita moschata) Seed Powder on the Chemical and Rheological Properties of Stirred Cultured Camel Milk and Yoghurt

Research shows that producing fermented camel milk is hard because of the milk’s inability to form a firm coagulum, attributed to low levels of κ-casein and ꞵ-lactoglobulin and the large casein micelle size, leading to a weak network of casein formation. In an effort to address this issue, researchers turned to corn starch as a thickening agent, discovering that a concentration of 2.0% effectively improved the viscosity and significantly reduced syneresis in stirred camel milk yoghurt and cultured camel milk. This study explores alternatives to corn starch, focusing on butternut squash seeds as a promising substitute due to their hydrocolloid composition. By incorporating butternut squash (Cucurbita moschata) seed powder (BSSP) as a thickening agent, this study aimed at enhancing the chemical and rheological properties of stirred camel milk yoghurt and cultured camel milk. Fermented camel milk was prepared using 4 litres of camel milk, 2% starter cultures (thermophilic culture for yoghurt and mesophilic aromatic culture for stirred cultured camel milk) and BSSP 0.0% (negative control), 0.4%, 0.8%, 1.2%, 1.6%, 2.0% mixed with 0.4% gelatin. 2.0% corn starch mixed with 0.4% gelatin was used as a standard for comparison. Results showed that increasing the BSSP level significantly (p < 0.05) decreased the moisture content while increasing the total solid content of stirred fermented camel milk products. There was an increase in ash content with an increase in BSSP levels. There was a significant (p < 0.05) reduction in the pH, with an increase in BSSP levels in stirred fermented camel milk samples. Increasing the concentration of BSSP from 0.4% to 2.0% resulted in a significant (p < 0.05) increase in viscosity and a reduction in syneresis of stirred camel milk yoghurt and stirred cultured camel milk samples. This study demonstrated that BSSP effectively enhances the viscosity, reduces syneresis and increases acidity in stirred fermented camel milk products during storage.

Classification of anatomical morphology of cystic duct and its association with gallstone

BACKGROUND Gallstones are common lesions that often require surgical intervention.Laparo-scopic cholecystectomy is the treatment of choice for symptomatic gallstones.Preoperatively,the anatomical morphology of the cystic duct(CD),needs to be accurately recognized,especially when anatomical variations occur in the CD,which is otherwise prone to bile duct injury.However,at present,there is no optimal classification system for CD morphology applicable in clinical practice,and the relationship between anatomical variations in CDs and gallstones remains to be explored.AIM To create a more comprehensive clinically applicable classification of the morphology of CD and to explore the correlations between anatomic variants of CD and gallstones.METHODS A total of 300 patients were retrospectively enrolled from October 2021 to January 2022.The patients were divided into two groups:The gallstone group and the nongallstone group.Relevant clinical data and anatomical data of the CD based on magnetic resonance cholangiopancreatography(MRCP)were collected and analyzed to propose a morphological classification system of the CD and to explore its relationship with gallstones.Multivariate analysis was performed using logistic regression analyses to identify the independent risk factors using variables that were significant in the univariate analysis.RESULTS Of the 300 patients enrolled in this study,200(66.7%)had gallstones.The mean age was 48.10±13.30 years,142(47.3%)were male,and 158(52.7%)were female.A total of 55.7%of the patients had a body mass index(BMI)≥24 kg/m2.Based on the MRCP,the CD anatomical typology is divided into four types:Type I:Linear,type II:n-shaped,type III:S-shaped,and type IV:W-shaped.Univariate analysis revealed differences between the gallstone and nongallstone groups in relation to sex,BMI,cholesterol,triglycerides,morphology of CD,site of CD insertion into the extrahepatic bile duct,length of CD,and angle between the common hepatic duct and CD.According to the multivariate analysis,female,BMI(≥24 kg/m2),and CD morphology[n-shaped:Odds ratio(OR)=10.97,95%confidence interval(95%CI):5.22-23.07,P<0.001;S-shaped:OR=4.43,95%CI:1.64-11.95,P=0.003;W-shaped:OR=7.74,95%CI:1.88-31.78,P=0.005]were significantly associated with gallstones.CONCLUSION The present study details the morphological variation in the CD and confirms that CD tortuosity is an independent risk factor for gallstones.

The effect of"rural cultural auditorium"on the revitalization of rural culture:A case study of villages A and B in Zhejiang Province

The construction of rural cultural auditorium is conducive to gathering local popularity,excavating history and continuing civilization,and it has become a powerful driving force for cultural revitalization in rural revitalization.However,the development of"Rural Cultural Auditorium"encountered many problems so far.From the perspective of rural cultural revitalization,and under the background of the new socialist rural cultural construction in China,this paper takes the rural cultural auditorium as the topic.The field questionnaire survey and semi-structured interview were constructed in Village A and Village B of Zhejiang Province,.SPSS software is used to analyze the collected questionnaire data.On the basis of combing related concepts and theories,it summs up the problems of"rural cultural auditorium",such as the existence of cultural auditorium,low participation rate of cultural auditorium activities,poor information communication,etc.Through visiting and investigating,going deep into the local area,according solutions are put forward such as increasing content diversity,paying attention to publicity and increasing interaction,so as to promote the healthy and sustainable development of rural cultural auditorium.It is hoped that this paper will explore the significance of the construction of rural cultural auditorium to the revitalization of rural culture in China,and put forward ideas on how to further build rural cultural auditorium,so as to provide reference for rural cultural construction services.

Terrorism Attack Classification Using Machine Learning: The Effectiveness of Using Textual Features Extracted from GTD Dataset

One of the biggest dangers to society today is terrorism, where attacks have become one of the most significantrisks to international peace and national security. Big data, information analysis, and artificial intelligence (AI) havebecome the basis for making strategic decisions in many sensitive areas, such as fraud detection, risk management,medical diagnosis, and counter-terrorism. However, there is still a need to assess how terrorist attacks are related,initiated, and detected. For this purpose, we propose a novel framework for classifying and predicting terroristattacks. The proposed framework posits that neglected text attributes included in the Global Terrorism Database(GTD) can influence the accuracy of the model’s classification of terrorist attacks, where each part of the datacan provide vital information to enrich the ability of classifier learning. Each data point in a multiclass taxonomyhas one or more tags attached to it, referred as “related tags.” We applied machine learning classifiers to classifyterrorist attack incidents obtained from the GTD. A transformer-based technique called DistilBERT extracts andlearns contextual features from text attributes to acquiremore information from text data. The extracted contextualfeatures are combined with the “key features” of the dataset and used to perform the final classification. Thestudy explored different experimental setups with various classifiers to evaluate the model’s performance. Theexperimental results show that the proposed framework outperforms the latest techniques for classifying terroristattacks with an accuracy of 98.7% using a combined feature set and extreme gradient boosting classifier.

On the Dissemination and Acceptance of Dongpo Culture in the UK and the US

This study delves into the intricate dissemination and acceptance of Dongpo Culture,epitomized by Su Shi,in the UK and the US,aiming to bolster the global recognition of Chinese literary and cultural values and advance the national strategy of“Going Out”.Su Shi’s multifaceted contributions—spanning literature,philosophy,calligraphy,and art—serve as a pinnacle of Northern Song Dynasty culture.This research evaluates the varied translations,monographs,biographies,journal articles,and doctoral dissertations about Su Shi in these Western nations,using literature analysis,typical analysis,and comparative methods.The findings reveal a robust interest in Su Shi studies in the US,marked by a proliferation of scholarly works and translations across diverse disciplines,such as literature,art,and aesthetics,establishing the US as a leading center for Dongpo Culture studies.Conversely,the UK,despite its early engagement,shows limited scholarly outputs and significant research papers on the subject.By examining Dongpo Culture’s overseas communication path and influence paradigm,this paper seeks to enhance China’s cultural soft power and self-confidence.It underscores the vital role of international cultural exchange in constructing a positive image of China’s national identity,facilitating its peaceful rise,and providing strategic insights for the global promotion of Chinese culture.