Optimization Design of the Multi-Layer Cross-Sectional Layout of An Umbilical Based on the GA-GLM

Marine umbilical is one of the key equipment for subsea oil and gas exploitation,which is usually integrated by a great number of different functional components with multi-layers.The layout of these components directly affects manufacturing,operation and storage performances of the umbilical.For the multi-layer cross-sectional layout design of the umbilical,a quantifiable multi-objective optimization model is established according to the operation and storage requirements.Considering the manufacturing factors,the multi-layering strategy based on contact point identification is introduced for a great number of functional components.Then,the GA-GLM global optimization algorithm is proposed combining the genetic algorithm and the generalized multiplier method,and the selection operator of the genetic algorithm is improved based on the steepest descent method.Genetic algorithm is used to find the optimal solution in the global space,which can converge from any initial layout to the feasible layout solution.The feasible layout solution is taken as the initial value of the generalized multiplier method for fast and accurate solution.Finally,taking umbilicals with a great number of components as examples,the results show that the cross-sectional performance of the umbilical obtained by optimization algorithm is better and the solution efficiency is higher.Meanwhile,the multi-layering strategy is effective and feasible.The design method proposed in this paper can quickly obtain the optimal multi-layer cross-sectional layout,which replaces the manual design,and provides useful reference and guidance for the umbilical industry.

Multi-layer perceptron-based data-driven multiscale modelling of granular materials with a novel Frobenius norm-based internal variable

One objective of developing machine learning(ML)-based material models is to integrate them with well-established numerical methods to solve boundary value problems(BVPs).In the family of ML models,recurrent neural networks(RNNs)have been extensively applied to capture history-dependent constitutive responses of granular materials,but these multiple-step-based neural networks are neither sufficiently efficient nor aligned with the standard finite element method(FEM).Single-step-based neural networks like the multi-layer perceptron(MLP)are an alternative to bypass the above issues but have to introduce some internal variables to encode complex loading histories.In this work,one novel Frobenius norm-based internal variable,together with the Fourier layer and residual architectureenhanced MLP model,is crafted to replicate the history-dependent constitutive features of representative volume element(RVE)for granular materials.The obtained ML models are then seamlessly embedded into the FEM to solve the BVP of a biaxial compression case and a rigid strip footing case.The obtained solutions are comparable to results from the FEM-DEM multiscale modelling but achieve significantly improved efficiency.The results demonstrate the applicability of the proposed internal variable in enabling MLP to capture highly nonlinear constitutive responses of granular materials.

Altered synaptic currents,mitophagy,mitochondrial dynamics in Alzheimer's disease models and therapeutic potential of Dengzhan Shengmai capsules intervention

Emerging research suggests a potential association of progression of Alzheimer's disease(AD)with alterations in synaptic currents and mitochondrial dynamics.However,the specific associations between these pathological changes remain unclear.In this study,we utilized Aβ42-induced AD rats and primary neural cells as in vivo and in vitro models.The investigations included behavioural tests,brain magnetic resonance imaging(MRI),liquid chromatography-tandem mass spectrometry(UPLC-MS/MS)analysis,Nissl staining,thioflavin-S staining,enzyme-linked immunosorbent assay,Golgi-Cox staining,transmission electron microscopy(TEM),immunofluorescence staining,proteomics,adenosine triphosphate(ATP)detection,mitochondrial membrane potential(MMP)and reactive oxygen species(ROS)assessment,mitochondrial morphology analysis,electrophysiological studies,Western blotting,and molecular docking.The results revealed changes in synaptic currents,mitophagy,and mitochondrial dynamics in the AD models.Remarkably,intervention with Dengzhan Shengmai(DZSM)capsules emerged as a pivotal element in this investigation.Aβ42-induced synaptic dysfunction was significantly mitigated by DZSM intervention,which notably amplified the frequency and amplitude of synaptic transmission.The cognitive impairment observed in AD rats was ameliorated and accompanied by robust protection against structural damage in key brain regions,including the hippocampal CA3,primary cingular cortex,prelimbic system,and dysgranular insular cortex.DZSM intervention led to increased IDE levels,augmented long-term potential(LTP)amplitude,and enhanced dendritic spine density and length.Moreover,DZSM intervention led to favourable changes in mitochondrial parameters,including ROS expression,MMP and ATP contents,and mitochondrial morphology.In conclusion,our findings delved into the realm of altered synaptic currents,mitophagy,and mitochondrial dynamics in AD,concurrently highlighting the therapeutic potential of DZSM intervention.

Capsule endoscopy and panendoscopy:A journey to the future of gastrointestinal endoscopy

In 2000,the small bowel capsule revolutionized the management of patients with small bowel disorders.Currently,the technological development achieved by the new models of double-headed endoscopic capsules,as miniaturized devices to evaluate the small bowel and colon[pan-intestinal capsule endoscopy(PCE)],makes this non-invasive procedure a disruptive concept for the management of patients with digestive disorders.This technology is expected to identify which patients will require conventional invasive endoscopic procedures(colonoscopy or balloon-assisted enteroscopy),based on the lesions detected by the capsule,i.e.,those with an indication for biopsies or endoscopic treatment.The use of PCE in patients with inflammatory bowel diseases,namely Crohn’s disease,as well as in patients with iron deficiency anaemia and/or overt gastrointestinal(GI)bleeding,after a non-diagnostic upper endoscopy(esophagogastroduodenoscopy),enables an effective,safe and comfortable way to identify patients with relevant lesions,who should undergo subsequent invasive endoscopic procedures.The recent development of magnetically controlled capsule endoscopy to evaluate the upper GI tract,is a further step towards the possibility of an entirely non-invasive assessment of all the segments of the digestive tract,from mouth-to-anus,meeting the expectations of the early developers of capsule endoscopy.

Effect of Polyvinyl Alcohol in Inner Aqueous Phase on Stability of Millimeter-scale Capsules

The millimeter-scale capsules with controllable morphology,ultra-low permeability and excellent mechanical stability were fabricated by millifluidics.Viscosity of inner phase was adjusted to control the morphology and properties of the capsules.In detail,as the concentration of polyvinyl alcohol(PVA)increased from 0 to 8% in the inner phase of the capsules,the diameter of capsules decreased from 3.33 ± 0.01mm to 2.97 ± 0.01 mm,the shell thickness of capsules decreased from 0.183 ± 0.004 mm to 0.155 ± 0.003 mm.While the capsules had round shape and high sphericity.Notably,the capsules with 2% PVA in the inner phase had remarkably decreased water permeability and good morphological stability.Specifically,the end-time of water losing of the capsules was up to 49 days,while the dehydrated capsules maintained spherical appearance,and crushing force of the capsules was up to 13.73 ± 0.79 N,which ensured stability during processing and transportation.This research provides a new strategy for stable encapsulation of small molecules.

Target Controllability of Multi-Layer Networks With High-Dimensional Nodes

This paper studies the target controllability of multilayer complex networked systems,in which the nodes are highdimensional linear time invariant(LTI)dynamical systems,and the network topology is directed and weighted.The influence of inter-layer couplings on the target controllability of multi-layer networks is discussed.It is found that even if there exists a layer which is not target controllable,the entire multi-layer network can still be target controllable due to the inter-layer couplings.For the multi-layer networks with general structure,a necessary and sufficient condition for target controllability is given by establishing the relationship between uncontrollable subspace and output matrix.By the derived condition,it can be found that the system may be target controllable even if it is not state controllable.On this basis,two corollaries are derived,which clarify the relationship between target controllability,state controllability and output controllability.For the multi-layer networks where the inter-layer couplings are directed chains and directed stars,sufficient conditions for target controllability of networked systems are given,respectively.These conditions are easier to verify than the classic criterion.

A flexible ultra-broadband multi-layered absorber working at 2 GHz-40 GHz printed by resistive ink

A flexible extra broadband metamaterial absorber(MMA)stacked with five layers working at 2 GHz–40 GHz is investigated.Each layer is composed of polyvinyl chloride(PVC),polyimide(PI),and a frequency selective surface(FSS),which is printed on PI using conductive ink.To investigate this absorber,both one-dimensional analogous circuit analysis and three-dimensional full-wave simulation based on a physical model are provided.Various crucial electromagnetic properties,such as absorption,effective impedance,complex permittivity and permeability,electric current distribution and magnetic field distribution at resonant peak points,are studied in detail.Analysis shows that the working frequency of this absorber covers entire S,C,X,Ku,K and Ka bands with a minimum thickness of 0.098λ_(max)(λ_(max) is the maximum wavelength in the absorption band),and the fractional bandwidth(FBW)reaches 181.1%.Moreover,the reflection coefficient is less than-10 dB at 1.998 GHz–40.056 GHz at normal incidence,and the absorptivity of the plane wave is greater than 80%when the incident angle is smaller than 50°.Furthermore,the proposed absorber is experimentally validated,and the experimental results show good agreement with the simulation results,which demonstrates the potential applicability of this absorber at 2 GHz–40 GHz.

Dynamic Multi-Layer Perceptron for Fetal Health Classification Using Cardiotocography Data

Fetal health care is vital in ensuring the health of pregnant women and the fetus.Regular check-ups need to be taken by the mother to determine the status of the fetus’growth and identify any potential problems.To know the status of the fetus,doctors monitor blood reports,Ultrasounds,cardiotocography(CTG)data,etc.Still,in this research,we have considered CTG data,which provides information on heart rate and uterine contractions during pregnancy.Several researchers have proposed various methods for classifying the status of fetus growth.Manual processing of CTG data is time-consuming and unreliable.So,automated tools should be used to classify fetal health.This study proposes a novel neural network-based architecture,the Dynamic Multi-Layer Perceptron model,evaluated from a single layer to several layers to classify fetal health.Various strategies were applied,including pre-processing data using techniques like Balancing,Scaling,Normalization hyperparameter tuning,batch normalization,early stopping,etc.,to enhance the model’s performance.A comparative analysis of the proposed method is done against the traditional machine learning models to showcase its accuracy(97%).An ablation study without any pre-processing techniques is also illustrated.This study easily provides valuable interpretations for healthcare professionals in the decision-making process.

Multi-layer network embedding on scc-based network with motif

Interconnection of all things challenges the traditional communication methods,and Semantic Communication and Computing(SCC)will become new solutions.It is a challenging task to accurately detect,extract,and represent semantic information in the research of SCC-based networks.In previous research,researchers usually use convolution to extract the feature information of a graph and perform the corresponding task of node classification.However,the content of semantic information is quite complex.Although graph convolutional neural networks provide an effective solution for node classification tasks,due to their limitations in representing multiple relational patterns and not recognizing and analyzing higher-order local structures,the extracted feature information is subject to varying degrees of loss.Therefore,this paper extends from a single-layer topology network to a multi-layer heterogeneous topology network.The Bidirectional Encoder Representations from Transformers(BERT)training word vector is introduced to extract the semantic features in the network,and the existing graph neural network is improved by combining the higher-order local feature module of the network model representation network.A multi-layer network embedding algorithm on SCC-based networks with motifs is proposed to complete the task of end-to-end node classification.We verify the effectiveness of the algorithm on a real multi-layer heterogeneous network.

Dynamic interwell connectivity analysis of multi-layer waterflooding reservoirs based on an improved graph neural network

The analysis of interwell connectivity plays an important role in the formulation of oilfield development plans and the description of residual oil distribution. In fact, sandstone reservoirs in China's onshore oilfields generally have the characteristics of thin and many layers, so multi-layer joint production is usually adopted. It remains a challenge to ensure the accuracy of splitting and dynamic connectivity in each layer of the injection-production wells with limited field data. The three-dimensional well pattern of multi-layer reservoir and the relationship between injection-production wells can be equivalent to a directional heterogeneous graph. In this paper, an improved graph neural network is proposed to construct an interacting process mimics the real interwell flow regularity. In detail, this method is used to split injection and production rates by combining permeability, porosity and effective thickness, and to invert the dynamic connectivity in each layer of the injection-production wells by attention mechanism.Based on the material balance and physical information, the overall connectivity from the injection wells,through the water injection layers to the production layers and the output of final production wells is established. Meanwhile, the change of well pattern caused by perforation, plugging and switching of wells at different times is achieved by updated graph structure in spatial and temporal ways. The effectiveness of the method is verified by a combination of reservoir numerical simulation examples and field example. The method corresponds to the actual situation of the reservoir, has wide adaptability and low cost, has good practical value, and provides a reference for adjusting the injection-production relationship of the reservoir and the development of the remaining oil.

Target layer state estimation in multi-layer complex dynamical networks considering nonlinear node dynamics

In many engineering networks, only a part of target state variables are required to be estimated.On the other hand,multi-layer complex network exists widely in practical situations.In this paper, the state estimation of target state variables in multi-layer complex dynamical networks with nonlinear node dynamics is studied.A suitable functional state observer is constructed with the limited measurement.The parameters of the designed functional observer are obtained from the algebraic method and the stability of the functional observer is proven by the Lyapunov theorem.Some necessary conditions that need to be satisfied for the design of the functional state observer are obtained.Different from previous studies, in the multi-layer complex dynamical network with nonlinear node dynamics, the proposed method can estimate the state of target variables on some layers directly instead of estimating all the individual states.Thus, it can greatly reduce the placement of observers and computational cost.Numerical simulations with the three-layer complex dynamical network composed of three-dimensional nonlinear dynamical nodes are developed to verify the effectiveness of the method.

Expression Recognition Method Based on Convolutional Neural Network and Capsule Neural Network

Convolutional neural networks struggle to accurately handle changes in angles and twists in the direction of images,which affects their ability to recognize patterns based on internal feature levels. In contrast, CapsNet overcomesthese limitations by vectorizing information through increased directionality and magnitude, ensuring that spatialinformation is not overlooked. Therefore, this study proposes a novel expression recognition technique calledCAPSULE-VGG, which combines the strengths of CapsNet and convolutional neural networks. By refining andintegrating features extracted by a convolutional neural network before introducing theminto CapsNet, ourmodelenhances facial recognition capabilities. Compared to traditional neural network models, our approach offersfaster training pace, improved convergence speed, and higher accuracy rates approaching stability. Experimentalresults demonstrate that our method achieves recognition rates of 74.14% for the FER2013 expression dataset and99.85% for the CK+ expression dataset. By contrasting these findings with those obtained using conventionalexpression recognition techniques and incorporating CapsNet’s advantages, we effectively address issues associatedwith convolutional neural networks while increasing expression identification accuracy.

Ischemic colitis induced by a platelet-raising capsule: A case report

BACKGROUND Ischemic colitis(IC)is also known as colon ischemia and is caused by colon vascular occlusion or nonocclusion,which results in a reduced blood supply to the colon and is not significant enough to maintain the metabolic function of cells,leading to intestinal wall ischemia.Its main symptoms include abdominal pain,diarrhea,and bloody stool.In severe cases,intestinal gangrene,peritonitis,intestinal stenosis and even intestinal obstruction may occur.IC induced by long-term use of certain special drugs is relatively rare in clinical practice.This article describes the clinical diagnosis and treatment of a typical case and provides a new treatment idea for the treatment of IC.CASE SUMMARY The patient was admitted to the hospital with"abdominal pain for half a month and bloody stool with mucous and pus for 3 d"and was diagnosed with"IC".Symptomatic and supportive treatment,such as antibiotics(levofloxacin),acid inhibition and stomach protection,fluid replenishment,and intravenous nutrition,was given.The patient's colonic ulcers were considered to be related to the oral administration of platelet(PLT)-raising capsules;the patient was asked to stop PLT-raising drugs for selective review via colonoscopy,and antibiotics and mesalazine enteric-coated tablets were stopped.Under the guidance of hematology consultation,60 mg of methylprednisolone was given in combination with PLT infusion to increase the PLT.After treatment,the patient's condition stabilized,the patient’s stool turned yellow,the patient’s symptoms improved,and the patient was allowed to leave the hospital.CONCLUSION PLT-raising capsules can lead to IC,so clinicians should have a full understanding of the application of these drugs in the treatment of various causes of thrombocyt-INTRODUCTION Ischemic colitis(IC)is also known as colon ischemia(CI)and is caused by colon vascular occlusion or nonocclusion,which results in a reduced blood supply to the colon;this process is not significant enough to maintain the metabolic function of cells,leading to intestinal wall ischemia[1].Its main symptoms include abdominal pain,diarrhea,and bloody stool.In severe cases,intestinal gangrene,peritonitis,intestinal stenosis and even intestinal obstruction may occur[2,3].The pathogenesis of this disease has not been extensively studied,but increased clotting ability has been recognized as an important factor in the pathogenesis of IC[4].People older than 60 years(especially women)who suffer from certain underlying diseases,such as cardiovascular and cerebrovascular diseases,diabetes,and shock,are the most prone to colon IC.The lesions can involve any segment of the colon,among which the left half of the colon,such as the sigmoid colon,descending colon and spleen region,is the most common site of lesions.This is because the region south of the sigmoid colon is the"watershed region"of the colonic blood supply,where vascular dysplasia may easily cause ischemia.In addition,the left half of the colon is supplied by the inferior mesenteric artery,which is at an acute angle to the abdominal aorta and affects blood perfusion.The rectum is supplied by both the inferior mesenteric artery and the rectal artery,and ischemia is rare.Therefore,the IC lesions were mainly in the left colon,and most of them were of the first pass type.The disease is relatively mild and can be cured after conservative medical treatment,so the prognosis is favorable[5-7].Once ischemia improves,the patient’s condition can recover in a relatively short time,and this condition can be distin-guished from other types of enteritis[5-7],such as infectious colitis,inflammatory bowel disease,pseudomembranous enteritis,diverticulitis,colon cancer,and acute mesenteric ischemia.Clinically,ischemic colitis can be divided into gangrene and nongrene.The latter can also be subdivided into transient and chronic types.Treatment for IC usually includes fasting,gastrointestinal decompression,intravenous nutritional support,improved circulation,fluid resuscitation,empirical use of antibiotics and other symptomatic supportive treatments,and attention should be given to the treatment of the primary disease.Most patients will experience improvements in clinical symp-toms within 1 to 2 d,and patients with complications may require surgery.However,IC induced by long-term use of certain special drugs is relatively rare in clinical practice.This article describes the clinical diagnosis and treatment of a typical case and provides a new treatment idea for the treatment of ischemic colitis.

A Well Productivity Model for Multi-Layered Marine and Continental Transitional Reservoirs with Complex Fracture Networks

Using the typical characteristics of multi-layered marine and continental transitional gas reservoirs as a basis,a model is developed to predict the related well production rate.This model relies on the fractal theory of tortuous capillary bundles and can take into account multiple gas flow mechanisms at the micrometer and nanometer scales,as well as the flow characteristics in different types of thin layers(tight sandstone gas,shale gas,and coalbed gas).Moreover,a source-sink function concept and a pressure drop superposition principle are utilized to introduce a coupled flow model in the reservoir.A semi-analytical solution for the production rate is obtained using a matrix iteration method.A specific well is selected for fitting dynamic production data,and the calculation results show that the tight sandstone has the highest gas production per unit thickness compared with the other types of reservoirs.Moreover,desorption and diffusion of coalbed gas and shale gas can significantly contribute to gas production,and the daily production of these two gases decreases rapidly with decreasing reservoir pressure.Interestingly,the gas production from fractures exhibits an approximately U-shaped distribution,indicating the need to optimize the spacing between clusters during hydraulic fracturing to reduce the area of overlapping fracture control.The coal matrix water saturation significantly affects the coalbed gas production,with higher water saturation leading to lower production.

Multi-layer phenomena in petawatt laser-driven acceleration of heavy ions

Laser-accelerated high-flux-intensity heavy-ion beams are important for new types of accelerators.A particle-in-cell program(Smilei) is employed to simulate the entire process of Station of Extreme Light(SEL) 100 PW laser-accelerated heavy particles using different nanoscale short targets with a thickness of 100 nm Cr, Fe, Ag, Ta, Au, Pb, Th and U, as well as 200 nm thick Al and Ca. An obvious stratification is observed in the simulation. The layering phenomenon is a hybrid acceleration mechanism reflecting target normal sheath acceleration and radiation pressure acceleration, and this phenomenon is understood from the simulated energy spectrum,ionization and spatial electric field distribution. According to the stratification, it is suggested that high-quality heavy-ion beams could be expected for fusion reactions to synthesize superheavy nuclei. Two plasma clusters in the stratification are observed simultaneously, which suggest new techniques for plasma experiments as well as thinner metal targets in the precision machining process.

Wuling capsule combined with sertraline in the therapy of anxiety and depression with insomnia in adolescents

BACKGROUND The treatment of adolescent patients with anxiety,depression and insomnia is challenging,and there is no ideal treatment method.AIM To evaluate the clinical efficacy of Wuling capsule combined with sertraline in the treatment of adolescent anxiety,depression and insomnia.METHODS Eighty adolescent patients with anxiety,depression with insomnia who were admitted to our hospital from April 1,2022 to March 30,2024.And the subjects were randomly classified into the control group(n=40)and the observational group(n=40).The control group was treated with a combination of sertraline and placebo.The observation group was treated with Wuling capsule in addition to sertraline.The two groups were cured continuously for 8 weeks.Insomnia severity index(ISI),Hamilton Anxiety Scale(HAMA)and Hamilton Depression Scale(HAMD)were used to evaluate the clinical symptoms before treatment and at 2,4,6 and 8 weeks after treatment.The Treatment Emergent Symptom Scale(TESS)was used to evaluate adverse reactions during treatment.RESULTS There was no obvious difference in HAMD,HAMA and ISI scores between the two groups before treatment(P>0.05).After treatment,the HAMD,HAMA and ISI scores of patients in both groups decreased compared with before treatment,and HAMD,HAMA and ISI scores of patients in the observation group were remarkedly lower than those in the control group at each time point after treatment(P<0.05).Compared with the control group,the TESS score of the study group were sharply lower(t=18.239,P<0.001).CONCLUSION Wuling capsule can further alleviate the insomnia symptoms of adolescents with anxiety and depression,and the efficacy and safety are high.It is recommended to promote the application.

Image detection method for multi-category lesions in wireless capsule endoscopy based on deep learning models

BACKGROUND Wireless capsule endoscopy(WCE)has become an important noninvasive and portable tool for diagnosing digestive tract diseases and has been propelled by advancements in medical imaging technology.However,the complexity of the digestive tract structure,and the diversity of lesion types,results in different sites and types of lesions distinctly appearing in the images,posing a challenge for the accurate identification of digestive tract diseases.AIM To propose a deep learning-based lesion detection model to automatically identify and accurately label digestive tract lesions,thereby improving the diagnostic efficiency of doctors,and creating significant clinical application value.METHODS In this paper,we propose a neural network model,WCE_Detection,for the accurate detection and classification of 23 classes of digestive tract lesion images.First,since multicategory lesion images exhibit various shapes and scales,a multidetection head strategy is adopted in the object detection network to increase the model's robustness for multiscale lesion detection.Moreover,a bidirectional feature pyramid network(BiFPN)is introduced,which effectively fuses shallow semantic features by adding skip connections,significantly reducing the detection error rate.On the basis of the above,we utilize the Swin Transformer with its unique self-attention mechanism and hierarchical structure in conjunction with the BiFPN feature fusion technique to enhance the feature representation of multicategory lesion images.RESULTS The model constructed in this study achieved an mAP50 of 91.5%for detecting 23 lesions.More than eleven single-category lesions achieved an mAP50 of over 99.4%,and more than twenty lesions had an mAP50 value of over 80%.These results indicate that the model outperforms other state-of-the-art models in the end-to-end integrated detection of human digestive tract lesion images.CONCLUSION The deep learning-based object detection network detects multiple digestive tract lesions in WCE images with high accuracy,improving the diagnostic efficiency of doctors,and demonstrating significant clinical application value.

The role of polyurethane foam compressible layer in the mechanical behaviour of multi-layer yielding supports for deep soft rock tunnels

The polyurethane foam(PU)compressible layer is a viable solution to the problem of damage to the secondary lining in squeezing tunnels.Nevertheless,the mechanical behaviour of the multi-layer yielding supports has not been thoroughly investigated.To fill this gap,large-scale model tests were conducted in this study.The synergistic load-bearing mechanics were analyzed using the convergenceconfinement method.Two types of multi-layer yielding supports with different thicknesses(2.5 cm,3.75 cm and 5 cm)of PU compressible layers were investigated respectively.Digital image correlation(DIC)analysis and acoustic emission(AE)techniques were used for detecting the deformation fields and damage evolution of the multi-layer yielding supports in real-time.Results indicated that the loaddisplacement relationship of the multi-layer yielding supports could be divided into the crack initiation,crack propagation,strain-hardening,and failure stages.Compared with those of the stiff support,the toughness,deformability and ultimate load of the yielding supports were increased by an average of 225%,61%and 32%,respectively.Additionally,the PU compressible layer is positioned between two primary linings to allow the yielding support to have greater mechanical properties.The analysis of the synergistic bearing effect suggested that the thickness of PU compressible layer and its location significantly affect the mechanical properties of the yielding supports.The use of yielding supports with a compressible layer positioned between the primary and secondary linings is recommended to mitigate the effects of high geo-stress in squeezing tunnels.

Treatment of 198 Cases of Thyroid Nodules with Sanying Capsule Combined with Xiaoying Patch

[Objectives]To observe the clinical efficacy of Sanying capsule combined with Xiaoying Patch in treating thyroid nodule(TN).[Methods]Two groups were treated similarly,with 200 cases in the control group undergoing basic treatment for 12 weeks and 198 cases in the observation group receiving Sanying capsule combined with Xiaoying patches for the same duration.The clinical symptoms,number of nodules,diameter of the largest nodule,and maximum reduction of nodules were observed before and after treatment.A control analysis was performed,and the underlying mechanisms were explored.[Results]The primary symptoms of the observation group exhibited a more favorable improvement than those of the control group.Additionally,the number of nodules decreased,the diameter of the largest nodule decreased,and the maximum reduction of nodules decreased in both groups following treatment.However,the observation group demonstrated a more pronounced improvement than the control group(P<0.05).[Conclusions]The combination of Sanying capsule and Xiaoying patch has been demonstrated to be an effective treatment for TN,with a high degree of reliability in terms of safety.

Helicobacter pylori infection may result in poor gastric cleanliness in magnetically controlled capsule gastroscopy examination: A singlecenter retrospective study

Objective:Magnetically controlled capsule gastroscopy(MCCG)is an effective method for screening gastric diseases;however,its performance may be affected by gastric cleanliness.We aimed to explore the correlation between Helicobacter pylori infection and the degree of gastric cleanliness in the MCCG.Methods:This retrospective study enrolled 297 participants from October 2020 to April 2024 at Sir Run Run Shaw Hospital,Zhejiang University School of Medicine.Participant characteristics,MCCG examination results,and(13)C-urea breath test(C13-UBT)results were collected.The gastric cleanliness in MCCG examinations was assessed using a gastric cleanliness score.Binary logistic regression was used to analyze the relationships among participant characteristics,H.pylori infection,and gastric cleanliness.Chi-square tests and Fisher's exact tests were used to analyze the relationships among gastric lesions,H.pylori infection,and gastric cleanliness.Results:Among the participants,24.2%had H.pylori infection,and 17.5%had poor gastric cleanliness.Hypertension(odds ratio[OR]:2.63;95%confidence interval[CI]:1.36e5.09;p?0.004)was associated with a greater likelihood of H.pylori infection.H.pylori infection(OR:3.76;95%CI:1.99e7.09;p<0.001)was an independent risk factor for poor gastric cleanliness in the MCCG.A significant disparity was noted in the prevalence of focal erosions(p<0.001),gastric ulcers(p?0.001),and positive gastric lesions(p?0.027)between the 2 groups with and without H.pylori infection.The proportion of positive gastric lesions was not significantly different between the good gastric cleanliness group and the poor gastric cleanliness group(25.7%vs.21.2%;p?0.490).Conclusion:The findings of this study revealed that H.pylori infection was associated with hypertension.H.pylori infection may lead to poor gastric cleanliness.Institutions are advised to perform C13-UBT before MCCG,and participants should be informed of the risk of poor gastric cleanliness if the results are positive.The decision to perform H.pylori eradication before MCCG should take into account patient willingness and the benefit-to-risk ratio.