Improving creep strength of the fine-grained heat-affected zone of novel 9Cr martensitic heat-resistant steel via modified thermo-mechanical treatment

The infamous type Ⅳ failure within the fine-grained heat-affected zone (FGHAZ) in G115 steel weldments seriously threatens the safe operation of ultra-supercritical (USC) power plants.In this work,the traditional thermo-mechanical treatment was modified via the replacement of hot-rolling with cold rolling,i.e.,normalizing,cold rolling,and tempering (NCT),which was developed to improve the creep strength of the FGHAZ in G115 steel weldments.The NCT treatment effectively promoted the dissolution of preformed M_(23)C_(6)particles and relieved the boundary segregation of C and Cr during welding thermal cycling,which accelerated the dispersed reprecipitation of M_(23)C_(6) particles within the fresh reaustenitized grains during post-weld heat treatment.In addition,the precipitation of Cu-rich phases and MX particles was promoted evidently due to the deformation-induced dislocations.As a result,the interacting actions between precipitates,dislocations,and boundaries during creep were reinforced considerably.Following this strategy,the creep rupture life of the FGHAZ in G115 steel weldments can be prolonged by 18.6%,which can further push the application of G115 steel in USC power plants.

Fine-Grained Ship Recognition Based on Visible and Near-Infrared Multimodal Remote Sensing Images: Dataset,Methodology and Evaluation

Fine-grained recognition of ships based on remote sensing images is crucial to safeguarding maritime rights and interests and maintaining national security.Currently,with the emergence of massive high-resolution multi-modality images,the use of multi-modality images for fine-grained recognition has become a promising technology.Fine-grained recognition of multi-modality images imposes higher requirements on the dataset samples.The key to the problem is how to extract and fuse the complementary features of multi-modality images to obtain more discriminative fusion features.The attention mechanism helps the model to pinpoint the key information in the image,resulting in a significant improvement in the model’s performance.In this paper,a dataset for fine-grained recognition of ships based on visible and near-infrared multi-modality remote sensing images has been proposed first,named Dataset for Multimodal Fine-grained Recognition of Ships(DMFGRS).It includes 1,635 pairs of visible and near-infrared remote sensing images divided into 20 categories,collated from digital orthophotos model provided by commercial remote sensing satellites.DMFGRS provides two types of annotation format files,as well as segmentation mask images corresponding to the ship targets.Then,a Multimodal Information Cross-Enhancement Network(MICE-Net)fusing features of visible and near-infrared remote sensing images,has been proposed.In the network,a dual-branch feature extraction and fusion module has been designed to obtain more expressive features.The Feature Cross Enhancement Module(FCEM)achieves the fusion enhancement of the two modal features by making the channel attention and spatial attention work cross-functionally on the feature map.A benchmark is established by evaluating state-of-the-art object recognition algorithms on DMFGRS.MICE-Net conducted experiments on DMFGRS,and the precision,recall,mAP0.5 and mAP0.5:0.95 reached 87%,77.1%,83.8%and 63.9%,respectively.Extensive experiments demonstrate that the proposed MICE-Net has more excellent performance on DMFGRS.Built on lightweight network YOLO,the model has excellent generalizability,and thus has good potential for application in real-life scenarios.

Flume experiments to study fine-grain migration and its impact on slope stability

Fine grains migration is a primary cause of landslides and debris flows.This study investigates the effect of fine-grain migration on slope failure through flume experiments,focusing on the spatiotemporal characteristics and mechanisms of slope stability.A series of artificial rainfall flume experiments with varying rainfall intensities and slopes were conducted using soil samples collected from Wei Jia Gully.The experiments monitored pore-water pressure,grain migration,and failure sequences.Grain-size distribution parameters(μand Dc)were analyzed to understand the migration path and accumulation of fine grains.The experiments reveal that fine-grain migration significantly alters soil structure,leading to random blockage and interconnection of internal pore channels.These changes result in fluctuating pore-water pressure distributions and uneven fine-grain accumulation,critical factors in slope stability.Slope failures occur randomly and intermittently,influenced by fine-grain content in runoff and resulting pore-water pressure variations.This study highlights that fine-grain migration plays a vital role in slope stability,with significant implications for predicting and mitigating slope failures.The stochastic nature of fine-grain migration and its impact on soil properties should be incorporated into predictive models to enhance their accuracy and reliability.

Distal margin distance in radical resection of locally advanced rectal cancer after neoadjuvant therapy

Colorectal cancer has a high incidence and mortality rate in China, with the majority of cases being middle and low rectal cancer. Surgical intervention is currently the main treatment modality for locally advanced rectal cancer, with the common goal of improving oncological outcomes while preserving function. The controversy regarding the circumferential resection margin distance in rectal cancer surgery has been resolved. With the promotion of neoadjuvant therapy concepts and advancements in technology, treatment strategies have become more diverse.Following tumor downstaging, there is an increasing trend towards extending the safe distance of distal rectal margin. This provides more opportunities for patients with low rectal cancer to preserve their anal function.However, there is currently no consensus on the specific distance of distal resection margin.

Knee Osteoarthritis Progression after Distal Femur Closing Wedge Osteotomy

Background: Despite the conservative treatment of tibio-femoral osteoarthritis through realignment osteotomies, the rate of total knee replacements following an osteotomy is increasing. The aim of this study was to identify the factors associated with the progression of knee osteoarthritis after a medial closing-wedge distal femoral osteotomy. Methods: Hospital-based observational study on 20 patients who underwent a medial closing-wedge distal femoral osteotomy evaluating the progression of osteoarthritis using the Kellgren and Laurence classification. The Wilcoxon test was used to compare the variation in the progressive stage of the Kellgren and Laurence classification of knee osteoarthritis preoperatively and at the final follow up. Univariate analysis made it possible to determine the factors associated with progression. The final significance threshold for statistical tests was set at 5% (p Results: Overall, the mean follow-up of 46 months ± 6.6 months, with a mean age of 43 years (range: 27 - 69 years) and a female predominance (M: F = 3/7). The progression of tibiofemoral osteoarthritis following a medial closing-wedge distal femoral osteotomy is associated with valgus or varum malalignment been a moderate valgus (OR 6.2 [1.5 - 42.7] at 95% CI;p-value = 0.02), a correction of the mechanical deviation angle with a valgus alignment (OR 2.7 [0.9 - 8.3] at 95% CI), and loss of correction (OR 3.8 [1.3 - 11.6] at 95% CI;p -value) for the lateral compartment while varus alignment (OR 1.7 [0.9 - 8.3] 95% CI, p-value = 0.05) and with rupture of the lateral cortex (OR 2.8 [1.7 - 11.5] 95% CI, p-value = 0.02) were those of the medial compartment. Conclusion: Distal femur closing wedge osteotomy does not definitively interrupt the progression of valgus knee osteoarthritis. The factors associated with the progression of this pathology are modifiable. Taking them into account when performing this surgical technique could improve the osteotomy survival curve.

Evaluation of Surgical Treatment of Distal Humeral Fractures in Adults

Introduction: Fractures of the distal end of the humerus are becoming increasingly frequent in young subjects because of the increase in road traffic accidents, and in elderly subjects because of osteoporosis related to aging populations. Materials and Methods: It was a prospective, monocentric study from January 2018 to December 2020 involving 14 patients who received and were treated surgically for distal humeral fractures and followed up. Results: We collected 14 patients, including 11 men (78.57%) and 3 women (21.43%), with a sex ratio of 3.7. The mean age was 36.41 years. The circumstances of onset were dominated by road traffic accidents, with 12 cases (85.71%). The dominant side was right-handed, with 11 cases (78.57%). Standard elbow radiography revealed 8 cases of type A fractures (57.14%), 4 cases of type B and 2 cases of type C fractures of the AO. We performed Lecestre plate osteosynthesis in 12 patients and external fixator in 2 others, using the trans-olecranial and transtricipital approaches. Elbow stiffness was the most frequent complication, with 6 cases (42.86%). After six months’ follow-up, our results were excellent and good in 78.57% of cases (MEPS). Conclusion: Surgical treatment with posterior approaches enabled us to achieve restitution of the articular surfaces, solid restraint and early mobilization of the elbow with satisfactory functional results.

Fine-grained grid computing model for Wi-Fi indoor localization in complex environments

The fingerprinting-based approach using the wireless local area network(WLAN)is widely used for indoor localization.However,the construction of the fingerprint database is quite time-consuming.Especially when the position of the access point(AP)or wall changes,updating the fingerprint database in real-time is difficult.An appropriate indoor localization approach,which has a low implementation cost,excellent real-time performance,and high localization accuracy and fully considers complex indoor environment factors,is preferred in location-based services(LBSs)applications.In this paper,we proposed a fine-grained grid computing(FGGC)model to achieve decimeter-level localization accuracy.Reference points(RPs)are generated in the grid by the FGGC model.Then,the received signal strength(RSS)values at each RP are calculated with the attenuation factors,such as the frequency band,three-dimensional propagation distance,and walls in complex environments.As a result,the fingerprint database can be established automatically without manual measurement,and the efficiency and cost that the FGGC model takes for the fingerprint database are superior to previous methods.The proposed indoor localization approach,which estimates the position step by step from the approximate grid location to the fine-grained location,can achieve higher real-time performance and localization accuracy simultaneously.The mean error of the proposed model is 0.36 m,far lower than that of previous approaches.Thus,the proposed model is feasible to improve the efficiency and accuracy of Wi-Fi indoor localization.It also shows high-accuracy performance with a fast running speed even under a large-size grid.The results indicate that the proposed method can also be suitable for precise marketing,indoor navigation,and emergency rescue.

Hemiarthroplasty for irreparable distal radius fractures in the elderly:A comprehensive review

BACKGROUND Elderly patients maintaining functional independence can now be candidates for primary wrist hemiarthroplasty to manage acute irreparable distal radius fractures(DRFs).However,further investigation with long-term follow-up is required to validate these initial findings.AIM To review the literature on the outcomes of distal radius hemiarthroplasty with available implants to assess its viability as a treatment option.METHODS A comprehensive review of the literature was conducted using electronic databases,including PubMed,Medline,and Scopus.The search terms employed were"distal radius fracture","hemiarthroplasty","wrist arthroplasty",and related terminology.The search was restricted to articles published in English from 1980 until June 2023.Inclusion criteria encompassed cases or case series of DRF treated with hemiarthroplasty,providing clinical or radiographic outcomes,and published in peer-reviewed journals.RESULTS A total of 2508 articles from PubMed and 883 from Scopus were identified initially.Following screening and removal of duplicates,13 articles met the inclusion criteria.These articles,predominantly clinical retrospective studies,provided insights into hemiarthroplasty outcomes,including functional improvements and complications.Hemiarthroplasty was a treatment option for complex DRF,particularly those cases with severe comminution,intraarticular involvement,or severe osteoporosis.Functional outcomes demonstrated improvements in pain relief,wrist mobility,and grip strength,with variability across studies.Complications included implant loosening,infection,nerve injury,and stiffness,with varying incidence rates influenced by surgical techniques and implant choice.Long-term outcomes were inadequately documented,warranting further research.CONCLUSION Hemiarthroplasty is a promising treatment for irreparable DRF in the elderly.Long-term outcomes and complications require further study.

Preoperative systemic inflammatory response index as a prognostic marker for distal cholangiocarcinoma after pancreatoduodenectomy

BACKGROUND The relationship between preoperative inflammation status and tumorigenesis as well as tumor progression is widely acknowledged.AIM To assess the prognostic significance of preoperative inflammatory biomarkers in patients with distal cholangiocarcinoma(dCCA)who underwent pancreat-oduodenectomy(PD).METHODS This single-center study included 216 patients with dCCA after PD between January 1,2011,and December 31,2022.The individuals were categorized into two sets based on their systemic inflammatory response index(SIRI)levels:A low SIRI group(SIRI<1.5,n=123)and a high SIRI group(SIRI≥1.5,n=93).Inflam-matory biomarkers were evaluated for predictive accuracy using receiver operating characteristic curves.Both univariate and multivariate Cox proportional hazards analyses were performed to estimate SIRI for overall survival(OS)and recurrence-free survival(RFS).RESULTS The study included a total of 216 patients,with 58.3%being male and a mean age of 65.6±9.6 years.123 patients were in the low SIRI group and 93 were in the high SIRI group after PD for dCCA.SIRI had an area under the curve value of 0.674 for diagnosing dCCA,showing better performance than other inflammatory biomarkers.Multivariate analysis indicated that having a SIRI greater than 1.5 independently increased the risk of dCCA following PD,leading to lower OS[hazard ratios(HR)=1.868,P=0.006]and RFS(HR=0.949,P<0.001).Additionally,survival analysis indicated a significantly better prognosis for patients in the low SIRI group(P<0.001).CONCLUSION It is determined that a high SIRI before surgery is a significant risk factor for dCCA after PD.

Lung cancer metastasis-induced distal esophageal segmental spasm confirmed by individualized peroral endoscopic myotomy:A case report

BACKGROUND Peroral endoscopic myotomy(POEM)has been widely performed as a standard treatment for achalasia;however,its efficacy and safety for treating distal esophageal segmental spasms induced by cancer metastasis remain unknown.CASE SUMMARY A 72-year-old male was referred to our hospital and complained of progressive dysphagia for two years.Endoscopy revealed a 2 cm long segment esophageal stenosis with intact mucosa and normal cardia.Computed tomography showed a right upper lung mass,and pathology of the right pleural effusion confirmed the diagnosis of right upper lung adenocarcinoma with multiple rib and mediastinal lymph node metastases and right malignant pleural effusion.Individualized POEM was performed first to alleviate dysphagia,and the final diagnosis was changed to esophageal muscle metastasis arising from lung adenocarcinoma.After treatment,the patient could eat soft solid food and received multiple rounds of pembrolizumab-combination chemotherapy.The patient’s progression-free survival was approximately 16 months.Long stable disease was obtained during the 24-month follow-up.CONCLUSION The incidence of distal esophageal segmental spasms induced by muscular metastasis arising from lung adenocarcinoma is extremely low.Individualized POEM can effectively improve a patient’s nutritional status before subsequent chemotherapy can be combined with immune checkpoint inhibitors.

Experimental Study on the Effect of Fine-Grained Soil Content on the Freezing Strength of Aeolian Sand-Cement Interface

In cold regions,understanding the freezing strength of the interface between soil and structure is crucial for designing frost-resistant foundations.To investigate how the content of cement powder in aeolian sand affects this strength,we conducted direct shear tests under various conditions such as different fine-grained soil content,normal stress,and initial moisture content of the soil.By analyzing parameters like soil properties,and volume of ice content,and using the Mohr-Coulomb strength theory to define interface strength,we aimed to indirectly measure the cementation strength of the interface.Our findings revealed that as the particle content increased,the interface stress-strain curves became noticeably stiffer.We also observed a positive linear relationship between freezing strength and silt content,while the initial moisture content of the soil did not significantly impact the strengthening effect of fine-grained soil on freezing strength.Moreover,we discovered that as the powder content increased,the force binding the ice to the interface decreased,while the friction angle at the interface increased.However,the cohesion force at the interface remained relatively unchanged.Overall,our analysis suggests that the increase in freezing strength due to fine-grained soil content is primarily due to the heightened friction between aeolian sand and the interface.

Anisotropy of Trabecular Bone from Ultra-Distal Radius Digital X-Ray Imaging: Effects on Bone Mineral Density and Age

Background: When applied to trabecular bone X-ray images, the anisotropic properties of trabeculae located at ultra-distal radius were investigated by using the trabecular bone scores (TBS) calculated along directions parallel and perpendicular to the forearm. Methodology: Data from more than two hundred subjects were studied retrospectively. A DXA (GE Lunar Prodigy) scan of the forearm was performed on each subject to measure the bone mineral density (BMD) value at the location of ultra-distal radius, and an X-ray digital image of the same forearm was taken on the same day. The values of trabecular bone score along the direction perpendicular to the forearm, TBSx, and along the direction parallel to the forearm, TBSy, were calculated respectively. The statistics of TBSx and TBSy were calculated, and the anisotropy of the trabecular bone, which was defined as the ratio of TBSy to TBSx and changed with subjects’ BMD and age, was reported and analyzed. Results: The results show that the correlation coefficient between TBSx and TBSy was 0.72 (p BMD and age was reported. The results showed that decreased trabecular bone anisotropy was associated with deceased BMD and increased age in the subject group. Conclusions: This study shows that decreased trabecular bone anisotropy was associated with decreased BMD and increased age.

Robotic versus laparoscopic distal pancreatectomy for pancreatic ductal adenocarcinoma: A propensity score-matched analysis

Background: Minimally invasive surgery is becoming increasingly popular in the field of pancreatic surgery. However, there are few studies of robotic distal pancreatectomy(RDP) for pancreatic ductal adenocarcinoma(PDAC). This study aimed to investigate the efficacy and feasibility of RDP for PDAC. Methods: Patients who underwent RDP or laparoscopic distal pancreatectomy(LDP) for PDAC between January 2015 and September 2020 were reviewed. Propensity score matching analyses were performed. Results: Of the 335 patients included in the study, 24 underwent RDP and 311 underwent LDP. A total of 21 RDP patients were matched 1:1 with LDP patients. RDP was associated with longer operative time(209.7 vs. 163.2 min;P = 0.003), lower open conversion rate(0% vs. 4.8%;P < 0.001), higher cost(15 722 vs. 12 699 dollars;P = 0.003), and a higher rate of achievement of an R0 resection margin(90.5% vs. 61.9%;P = 0.042). However, postoperative pancreatic fistula grade B or C showed no significant intergroup difference(9.5% vs. 9.5%). The median disease-free survival(34.5 vs. 17.3 months;P = 0.588) and overall survival(37.7 vs. 21.9 months;P = 0.171) were comparable between the groups. Conclusions: RDP is associated with longer operative time, a higher cost of surgery, and a higher likelihood of achieving R0 margins than LDP.

Fine-grained gravity flow sedimentation and its influence on development of shale oil sweet sections in lacustrine basins in China

The geological conditions and processes of fine-grained gravity flow sedimentation in continental lacustrine basins in China are analyzed to construct the model of fine-grained gravity flow sedimentation in lacustrine basin,reveal the development laws of fine-grained deposits and source-reservoir,and identify the sweet sections of shale oil.The results show that fine-grained gravity flow is one of the important sedimentary processes in deep lake environment,and it can transport fine-grained clasts and organic matter in shallow water to deep lake,forming sweet sections and high-quality source rocks of shale oil.Fine-grained gravity flow deposits in deep waters of lacustrine basins in China are mainly fine-grained high-density flow,fine-grained turbidity flow(including surge-like turbidity flow and fine-grained hyperpycnal flow),fine-grained viscous flow(including fine-grained debris flow and mud flow),and fine-grained transitional flow deposits.The distribution of fine-grained gravity flow deposits in the warm and humid unbalanced lacustrine basins are controlled by lake-level fluctuation,flooding events,and lakebed paleogeomorphology.During the lake-level rise,fine-grained hyperpycnal flow caused by flooding formed fine-grained channel–levee–lobe system in the flat area of the deep lake.During the lake-level fall,the sublacustrine fan system represented by unconfined channel was developed in the flexural slope breaks and sedimentary slopes of depressed lacustrine basins,and in the steep slopes of faulted lacustrine basins;the sublacustrine fan system with confined or unconfined channel was developed on the gentle slopes and in axial direction of faulted lacustrine basins,with fine-grained gravity flow deposits possibly existing in the lower fan.Within the fourth-order sequences,transgression might lead to organic-rich shale and fine-grained hyperpycnal flow deposits,while regression might cause fine-grained high-density flow,surge-like turbidity flow,fine-grained debris flow,mud flow,and fine-grained transitional flow deposits.Since the Permian,in the shale strata of lacustrine basins in China,multiple transgression-regression cycles of fourth-order sequences have formed multiple source-reservoir assemblages.Diverse fine-grained gravity flow sedimentation processes have created sweet sections of thin siltstone consisting of fine-grained high-density flow,fine-grained hyperpycnal flow and surge-like turbidity flow deposits,sweet sections with interbeds of mudstone and siltstone formed by fine-grained transitional flows,and sweet sections of shale containing silty and muddy clasts and with horizontal bedding formed by fine-grained debris flow and mud flow.The model of fine-grained gravity flow sedimentation in lacustrine basin is significant for the scientific evaluation of sweet shale oil reservoir and organic-rich source rock.

Toward Fine-grained Image Retrieval with Adaptive Deep Learning for Cultural Heritage Image

Fine-grained image classification is a challenging research topic because of the high degree of similarity among categories and the high degree of dissimilarity for a specific category caused by different poses and scales.A cul-tural heritage image is one of thefine-grained images because each image has the same similarity in most cases.Using the classification technique,distinguishing cultural heritage architecture may be difficult.This study proposes a cultural heri-tage content retrieval method using adaptive deep learning forfine-grained image retrieval.The key contribution of this research was the creation of a retrieval mod-el that could handle incremental streams of new categories while maintaining its past performance in old categories and not losing the old categorization of a cul-tural heritage image.The goal of the proposed method is to perform a retrieval task for classes.Incremental learning for new classes was conducted to reduce the re-training process.In this step,the original class is not necessary for re-train-ing which we call an adaptive deep learning technique.Cultural heritage in the case of Thai archaeological site architecture was retrieved through machine learn-ing and image processing.We analyze the experimental results of incremental learning forfine-grained images with images of Thai archaeological site architec-ture from world heritage provinces in Thailand,which have a similar architecture.Using afine-grained image retrieval technique for this group of cultural heritage images in a database can solve the problem of a high degree of similarity among categories and a high degree of dissimilarity for a specific category.The proposed method for retrieving the correct image from a database can deliver an average accuracy of 85 percent.Adaptive deep learning forfine-grained image retrieval was used to retrieve cultural heritage content,and it outperformed state-of-the-art methods infine-grained image retrieval.

Prediction of compaction parameters for fine-grained soil: Critical comparison of the deep learning and standalone models

A comparison between deep learning and standalone models in predicting the compaction parameters of soil is presented in this research.One hundred and ninety and fifty-three soil samples were randomly picked up from two hundred and forty-three soil samples to create training and validation datasets,respectively.The performance and accuracy of the models were measured by root mean square error(RMSE),coefficient of determination(R2),Pearson product-moment correlation coefficient(r),mean absolute error(MAE),variance accounted for(VAF),mean absolute percentage error(MAPE),weighted mean absolute percentage error(WMAPE),a20-index,index of scatter(IOS),and index of agreement(IOA).Comparisons between standalone models demonstrate that the model MD 29 in Gaussian process regression(GPR)and model MD 101 in support vector machine(SVM)can achieve over 96%of accuracy in predicting the optimum moisture content(OMC)and maximum dry density(MDD)of soil,and outperformed other standalone models.The comparison between deep learning models shows that the models MD 46 and MD 146 in long short-term memory(LSTM)predict OMC and MDD with higher accuracy than ANN models.However,the LSTM models outperformed the GPR models in predicting the compaction parameters.The sensitivity analysis illustrates that fine content(FC),specific gravity(SG),and liquid limit(LL)highly influence the prediction of compaction parameters.

Fine-Grained Multivariate Time Series Anomaly Detection in IoT

Sensors produce a large amount of multivariate time series data to record the states of Internet of Things(IoT)systems.Multivariate time series timestamp anomaly detection(TSAD)can identify timestamps of attacks and malfunctions.However,it is necessary to determine which sensor or indicator is abnormal to facilitate a more detailed diagnosis,a process referred to as fine-grained anomaly detection(FGAD).Although further FGAD can be extended based on TSAD methods,existing works do not provide a quantitative evaluation,and the performance is unknown.Therefore,to tackle the FGAD problem,this paper first verifies that the TSAD methods achieve low performance when applied to the FGAD task directly because of the excessive fusion of features and the ignoring of the relationship’s dynamic changes between indicators.Accordingly,this paper proposes a mul-tivariate time series fine-grained anomaly detection(MFGAD)framework.To avoid excessive fusion of features,MFGAD constructs two sub-models to independently identify the abnormal timestamp and abnormal indicator instead of a single model and then combines the two kinds of abnormal results to detect the fine-grained anomaly.Based on this framework,an algorithm based on Graph Attention Neural Network(GAT)and Attention Convolutional Long-Short Term Memory(A-ConvLSTM)is proposed,in which GAT learns temporal features of multiple indicators to detect abnormal timestamps and A-ConvLSTM captures the dynamic relationship between indicators to identify abnormal indicators.Extensive simulations on a real-world dataset demonstrate that the proposed algorithm can achieve a higher F1 score and hit rate than the extension of existing TSAD methods with the benefit of two independent sub-models for timestamp and indicator detection.

Fine-Grained Action Recognition Based on Temporal Pyramid Excitation Network

Mining more discriminative temporal features to enrich temporal context representation is considered the key to fine-grained action recog-nition.Previous action recognition methods utilize a fixed spatiotemporal window to learn local video representation.However,these methods failed to capture complex motion patterns due to their limited receptive field.To solve the above problems,this paper proposes a lightweight Temporal Pyramid Excitation(TPE)module to capture the short,medium,and long-term temporal context.In this method,Temporal Pyramid(TP)module can effectively expand the temporal receptive field of the network by using the multi-temporal kernel decomposition without significantly increasing the computational cost.In addition,the Multi Excitation module can emphasize temporal importance to enhance the temporal feature representation learning.TPE can be integrated into ResNet50,and building a compact video learning framework-TPENet.Extensive validation experiments on several challenging benchmark(Something-Something V1,Something-Something V2,UCF-101,and HMDB51)datasets demonstrate that our method achieves a preferable balance between computation and accuracy.

Optimal choice of stapler and digestive tract reconstruction method after distal gastrectomy for gastric cancer:A prospective case–control study

BACKGROUND Gastric cancer is the most common cause of cancer-related deaths,and is classified according to its location in the proximal,middle,or distal stomach.Surgical resection is the primary approach for treating gastric cancer.This prospective study aimed to determine the best reconstruction method after distal gastrectomy for gastric cancer.AIM To explore the efficacy of different staplers and digestive tract reconstruction(DTR)methods after radical gastrectomy and their influence on prognosis.METHODS Eighty-seven patients who underwent radical gastrectomy for distal gastric cancer at our institution between April 2017 and April 2020 were included in this study,with a follow-up period of 12-26 mo.The patients were assigned to four groups based on the stapler and DTR plan as follows:BillrothⅠ(B-I)reconstruction+linear stapler group(group A,22 cases),B-I reconstruction+circular stapler group(group B,22 cases),Billroth II(B-II)reconstruction+linear stapler group(group C,22 cases),and B-II reconstruction+circular stapler group(group D,21 cases).The pathological parameters,postoperative gastrointestinal function recovery,postoperative complications,and quality of life(QOL)were compared among the four groups.RESULTS No significant differences in the maximum diameter of the gastric tumors,total number of lymph nodes dissected,drainage tube removal time,QLQ(QOL questionnaire)-C30 and QLQ-STO22 scores at 1 year postoperatively,and incidence of complications were observed among the four groups(P>0.05).However,groups A and C(linear stapler)had significantly lower intraoperative blood loss and significantly shorter anastomosis time,operation time,first fluid diet intake time,first exhaust time,and length of postoperative hospital stay(P<0.05)than groups B and D(circular stapler).CONCLUSION Linear staplers offer several advantages for postoperative recovery.B-I and B-II reconstruction methods had similar effects on QOL.The optimal solution can be selected according to individual conditions and postoperative convenience.

Distal clavicle fractures treated by anteroinferior plating with a single screw: Two case reports

BACKGROUND For the treatment of distal clavicle fractures,each treatment method has its own advantages and disadvantages,and there is no optimal surgical solution.CASE SUMMARY Based on this,we report 2 cases of distal clavicle fractures treated utilizing an anterior inferior plate with a single screw placed in the distal,in anticipation of providing a better surgical approach to distal clavicle fracture treatment.Two patients were admitted to the hospital after trauma with a diagnosis of distal clavicle fracture,and were admitted to the hospital for internal fixation of clavicle fracture by incision and reduction,with good postoperative functional recovery.CONCLUSION With solid postoperative fixation and satisfactory prognostic functional recovery,this technique has been shown to be simple,easy to perform and effective.