Endoscopic intramural cystogastrostomy for treatment of peripancreatic fluid collection: A viewpoint from a surgeon

Percutaneous or endoscopic drainage is the initial choice for the treatment of peripancreatic fluid collection in symptomatic patients.Endoscopic transgastric fenestration(ETGF)was first reported for the management of pancreatic pseu-docysts of 20 patients in 2008.From a surgeon’s viewpoint,ETGF is a similar procedure to cystogastrostomy in that they both produce a wide outlet orifice for the drainage of fluid and necrotic debris.ETGF can be performed at least 4 wk after the initial onset of acute pancreatitis and it has a high priority over the surgical approach.However,the surgical approach usually has a better success rate because surgical cystogastrostomy has a wider outlet(>6 cm vs 2 cm)than ETGF.However,percutaneous or endoscopic drainage,ETGF,and surgical approach offer various treatment options for peripancreatic fluid collection patients based on their conditions.

Customized Convolutional Neural Network for Accurate Detection of Deep Fake Images in Video Collections

The motivation for this study is that the quality of deep fakes is constantly improving,which leads to the need to develop new methods for their detection.The proposed Customized Convolutional Neural Network method involves extracting structured data from video frames using facial landmark detection,which is then used as input to the CNN.The customized Convolutional Neural Network method is the date augmented-based CNN model to generate‘fake data’or‘fake images’.This study was carried out using Python and its libraries.We used 242 films from the dataset gathered by the Deep Fake Detection Challenge,of which 199 were made up and the remaining 53 were real.Ten seconds were allotted for each video.There were 318 videos used in all,199 of which were fake and 119 of which were real.Our proposedmethod achieved a testing accuracy of 91.47%,loss of 0.342,and AUC score of 0.92,outperforming two alternative approaches,CNN and MLP-CNN.Furthermore,our method succeeded in greater accuracy than contemporary models such as XceptionNet,Meso-4,EfficientNet-BO,MesoInception-4,VGG-16,and DST-Net.The novelty of this investigation is the development of a new Convolutional Neural Network(CNN)learning model that can accurately detect deep fake face photos.

Species’ geographical range, environmental range and traits lead to specimen collection preference of dominant plant species of grasslands in Northern China

Many different factors,such as species traits,socio-economic factors,geographical and environmental factors,can lead to specimen collection preference.This study aims to determine whether grassland specimen collection in China is preferred by species traits(i.e.,plant height,flowering and fruiting period),environmental range(i.e.,the temperature and precipitation range)and geographical range(i.e.,distribution range and altitudinal range).Ordinary least squares models and phylogenetic generalized linear mixed models were used to analyze the relationships between specimen number and the explanatory variables.Random Forest models were then used to find the most parsimonious multivariate model.The results showed that interannual variation in specimen number between 1900 and 2020 was considerable.Specimen number of these species in southeast China was notably lower than that in northwest China.Environmental range and geographical range of species had significant positive correlations with specimen number.In addition,there were relatively weak but significant associations between specimen number and species trait(i.e.,plant height and flowering and fruiting period).Random Forest models indicated that distribution range was the most important variable,followed by flowering and fruiting period,and altitudinal range.These findings suggest that future floristic surveys should pay more attention to species with small geographical range,narrow environmental range,short plant height,and short flowering and fruiting period.The correction of specimen collection preference will also make the results of species distribution model,species evolution and other works based on specimen data more accurate.

Flight Time Minimization of UAV for Cooperative Data Collection in Probabilistic LoS Channel

This paper investigates the data collection in an unmanned aerial vehicle(UAV)-aided Internet of Things(IoT) network, where a UAV is dispatched to collect data from ground sensors in a practical and accurate probabilistic line-of-sight(LoS) channel. Especially, access points(APs) are introduced to collect data from some sensors in the unlicensed band to improve data collection efficiency. We formulate a mixed-integer non-convex optimization problem to minimize the UAV flight time by jointly designing the UAV 3D trajectory and sensors’ scheduling, while ensuring the required amount of data can be collected under the limited UAV energy. To solve this nonconvex problem, we recast the objective problem into a tractable form. Then, the problem is further divided into several sub-problems to solve iteratively, and the successive convex approximation(SCA) scheme is applied to solve each non-convex subproblem. Finally,the bisection search is adopted to speed up the searching for the minimum UAV flight time. Simulation results verify that the UAV flight time can be shortened by the proposed method effectively.

A research on the effect of plasma spectrum collection device on LIBS spectral intensity

Only a small amount of spectral information is collected because the collection solid angle of the optical fiber probe and lens is very limited when collecting spectral information.To overcome this limitation,this study presents a novel method for acquiring plasma spectral information from various spatial directions.A parabolic-shaped plasma spectral collection device(PSCD)is employed to effectively collect more spectral information into the spectrometer,thereby enhancing the overall spectral intensity.The research objects in this study were soil samples containing different concentrations of heavy metals Pb,Cr,and Cd.The results indicate that the PSCD significantly enhances the spectral signal,with an enhancement rate of up to 45%.Moreover,the signal-to-noise ratio also increases by as much as 36%.Simultaneously,when compared to the absence of a device,it is found that there is no significant variation in plasma temperature when the PSCD is utilized.This observation eliminates the impact of the spatial effect caused by the PSCD on the spectral intensity.Consequently,a concentrationspectral intensity relationship curve is established under the PSCD.The results revealed that the linear fitting R^(2)for Pb,Cr,and Cd increased by 0.011,0.001,and 0.054,respectively.Additionally,the limit of detection(LOD)decreased by 0.361 ppm,0.901 ppm,and 0.602 ppm,respectively.These findings indicate that the spectral enhancement rate elevates with the increase in heavy metal concentration.Hence,the PSCD can effectively enhance the spectral intensity and reduce the detection limit of heavy metals in soil.

Actor-Critic-Based UAV-Assisted Data Collection in the Wireless Sensor Network

Wireless Sensor Network(WSN)is widely utilized in large-scale distributed unmanned detection scenarios due to its low cost and flexible installation.However,WSN data collection encounters challenges in scenarios lacking communication infrastructure.Unmanned aerial vehicle(UAV)offers a novel solution for WSN data collection,leveraging their high mobility.In this paper,we present an efficient UAV-assisted data collection algorithm aimed at minimizing the overall power consumption of the WSN.Firstly,a two-layer UAV-assisted data collection model is introduced,including the ground and aerial layers.The ground layer senses the environmental data by the cluster members(CMs),and the CMs transmit the data to the cluster heads(CHs),which forward the collected data to the UAVs.The aerial network layer consists of multiple UAVs that collect,store,and forward data from the CHs to the data center for analysis.Secondly,an improved clustering algorithm based on K-Means++is proposed to optimize the number and locations of CHs.Moreover,an Actor-Critic based algorithm is introduced to optimize the UAV deployment and the association with CHs.Finally,simulation results verify the effectiveness of the proposed algorithms.

Reliable Data Collection Model and Transmission Framework in Large-Scale Wireless Medical Sensor Networks

Large-scale wireless sensor networks(WSNs)play a critical role in monitoring dangerous scenarios and responding to medical emergencies.However,the inherent instability and error-prone nature of wireless links present significant challenges,necessitating efficient data collection and reliable transmission services.This paper addresses the limitations of existing data transmission and recovery protocols by proposing a systematic end-to-end design tailored for medical event-driven cluster-based large-scale WSNs.The primary goal is to enhance the reliability of data collection and transmission services,ensuring a comprehensive and practical approach.Our approach focuses on refining the hop-count-based routing scheme to achieve fairness in forwarding reliability.Additionally,it emphasizes reliable data collection within clusters and establishes robust data transmission over multiple hops.These systematic improvements are designed to optimize the overall performance of the WSN in real-world scenarios.Simulation results of the proposed protocol validate its exceptional performance compared to other prominent data transmission schemes.The evaluation spans varying sensor densities,wireless channel conditions,and packet transmission rates,showcasing the protocol’s superiority in ensuring reliable and efficient data transfer.Our systematic end-to-end design successfully addresses the challenges posed by the instability of wireless links in large-scaleWSNs.By prioritizing fairness,reliability,and efficiency,the proposed protocol demonstrates its efficacy in enhancing data collection and transmission services,thereby offering a valuable contribution to the field of medical event-drivenWSNs.

Seismic effectiveness evaluation and optimized design of tie up method for securing museum collections

To quantify the seismic effectiveness of the most commonly used fishing line tie up method for securing museum collections and optimize fixed strategies for exhibitions,shaking table tests of the seismic systems used for typical museum collection replicas have been carried out.The influence of body shape and fixed measure parameters on the seismic responses of replicas and the interaction behavior between replicas and fixed measures have been explored.Based on the results,seismic effectiveness evaluation indexes of the tie up method are proposed.Reasonable suggestions for fixed strategies are given,which provide a basis for the exhibition of delicate museum collections considering the principle of minimizing seismic responses and intervention.The analysis results show that a larger ratio of height of mass center to bottom diameter led to more intense rocking responses.Increasing the initial pretension of fishing lines was conducive to reducing the seismic responses and stress variation of the lines.Through comprehensive consideration of the interaction forces and effective securement,it is recommended to apply 20%of breaking stress as the initial pretension.For specific museum collections that cannot be effectively protected by the independent tie up method,an optimized strategy of a combination of fishing lines and fasteners is recommended.

Early endoscopic management of an infected acute necrotic collection misdiagnosed as a pancreatic pseudocyst: A case report

BACKGROUND Infected acute necrotic collection(ANC)is a fatal complication of acute pancre-atitis with substantial morbidity and mortality.Drainage plays an exceedingly important role as the first step in invasive intervention for infected necrosis;however,there is great controversy about the optimal drainage time,and better treatment should be explored.CASE SUMMARY We report the case of a 43-year-old man who was admitted to the hospital with severe intake reduction due to early satiety 2 wk after treatment for acute pancre-atitis;conservative treatment was ineffective,and a pancreatic pseudocyst was suspected on contrast-enhanced computed tomography(CT).Endoscopic ultra-sonography(EUS)suggested hyperechoic necrotic tissue within the cyst cavity.The wall was not completely mature,and the culture of the puncture fluid was positive for A-haemolytic Streptococcus.Thus,the final diagnosis of ANC in-fection was made.The necrotic collection was not walled off and contained many solid components;therefore,the patient underwent EUS-guided aspiration and lavage.Two weeks after the collection was completely encapsulated,pancreatic duct stent drainage via endoscopic retrograde cholangiopancreatography(ERCP)was performed,and the patient was subsequently successfully discharged.On repeat CT,the pancreatic cysts had almost disappeared during the 6-month fo-llow-up period after surgery.CONCLUSION Early EUS-guided aspiration and lavage combined with late ERCP catheter drainage may be effective methods for intervention in infected ANCs.

Endoscopic ultrasound-guided pancreatic fluid collection drainage: Where are we?

Pancreatic fluid collections(PFCs)result from injury to the pancreas from acute or chronic pancreatitis,surgery,or trauma.Management of these collections has evolved over the last 2 decades.The choice of interventions includes percu-taneous,endoscopic,minimally invasive surgery,or a combined approach.Endoscopic drainage is the drainage of PFCs by creating an artificial communication between the collection and gastrointestinal lumen that is maintained by placing a stent across the fistulous tract.In this editorial,we endeavored to update the current status of endoscopic ultrasound-guided drainage of PFCs.

Association between acute peripancreatic fluid collections and early readmission in acute pancreatitis:A propensity-matched analysis

BACKGROUND Patients with acute pancreatitis(AP)frequently experience hospital readmissions,posing a significant burden to healthcare systems.Acute peripancreatic fluid collection(APFC)may negatively impact the clinical course of AP.It could worsen symptoms and potentially lead to additional complications.However,clinical evidence regarding the specific association between APFC and early readmission in AP remains scarce.Understanding the link between APFC and readmission may help improve clinical care for AP patients and reduce healthcare costs.AIM To evaluate the association between APFC and 30-day readmission in patients with AP.METHODS This retrospective cohort study is based on the Nationwide Readmission Database for 2016-2019.Patients with a primary diagnosis of AP were identified.Participants were categorized into those with and without APFC.A 1:1 propensity score matching for age,gender,and Elixhauser comorbidities was performed.The primary outcome was early readmission rates.Secondary outcomes included the incidence of inpatient complications and healthcare utilization.Unadjusted analyses used Mann-Whitney U andχ2 tests,while Cox regression models assessed 30-day readmission risks and reported them as adjusted hazard ratios(aHR).Kaplan-Meier curves and log-rank tests verified readmission risks.RESULTS A total of 673059 patients with the principal diagnosis of AP were included.Of these,5.1%had APFC on initial admission.After propensity score matching,each cohort consisted of 33914 patients.Those with APFC showed a higher incidence of inpatient complications,including septic shock(3.1%vs 1.3%,P<0.001),portal venous thrombosis(4.4%vs 0.8%,P<0.001),and mechanical ventilation(1.8%vs 0.9%,P<0.001).The length of stay(LOS)was longer for APFC patients[4(3-7)vs 3(2-5)days,P<0.001],as were hospital charges($29451 vs$24418,P<0.001).For 30-day readmissions,APFC patients had a higher rate(15.7%vs 6.5%,P<0.001)and a longer median readmission LOS(4 vs 3 days,P<0.001).The APFC group also had higher readmission charges($28282 vs$22865,P<0.001).The presence of APFC increased the risk of readmission twofold(aHR 2.52,95%confidence interval:2.40-2.65,P<0.001).The independent risk factors for 30-day readmission included female gender,Elixhauser Comorbidity Index≥3,chronic pulmonary diseases,chronic renal disease,protein-calorie malnutrition,substance use disorder,depression,portal and splenic venous thrombosis,and certain endoscopic procedures.CONCLUSION Developing APFC during index hospitalization for AP is linked to higher readmission rates,more inpatient complications,longer LOS,and increased healthcare costs.Knowing predictors of readmission can help target high-risk patients,reducing healthcare burdens.

Exploring Corporate Tax Compliance in the Era of Digital Tax Collection and Administration:Insights from the“Golden Tax Phase Four”Project

This article primarily examines the current state of tax collection and management,alongside other associated issues.It integrates insights from China’s“14th Five-Year Plan”and anticipates the imminent implementation of the“Golden Tax Phase Four.”With this backdrop,the article offers recommendations for advancing the reform of the tax collection and management system,fostering the development of intelligent taxation,and accelerating the modernization of tax collection and management in China.

Optimal Design of Aperture Illuminations for Microwave Power Transmission with Annular Collection Areas

This work presents an optimal design method of antenna aperture illumination for microwave power transmission with an annular collection area.The objective is to maximize the ratio of the power radiated on the annular collection area to the total transmitted power.By formulating the aperture amplitude distribution through a summation of a special set of series,the optimal design problem can be reduced to finding the maximum ratio of two real quadratic forms.Based on the theory of matrices,the solution to the formulated optimization problem is to determine the largest characteristic value and its associated characteristic vector.To meet security requirements,the peak radiation levels outside the receiving area are considered to be extra constraints.A hybrid grey wolf optimizer and Nelder–Mead simplex method is developed to deal with this constrained optimization problem.In order to demonstrate the effectiveness of the proposed method,numerical experiments on continuous apertures are conducted;then,discrete arrays of isotropic elements are employed to validate the correctness of the optimized results.Finally,patch arrays are adopted to further verify the validity of the proposed method.

Study on Rural Solid Waste Collection and Transportation Mode and Route Optimization Strategy in the Cold Regions of Northern China

Rural vitalization is a major strategy for reform and development of agriculture and rural areas in China,the key task of which is improving rural living environment.Imperfect rural solid waste(RSW)collection and transportation system exacerbates the pollution of RSW to rural living environment,while it has not been established and improved in the cold region of Northern China due to climate and economy.Through the analysis of the current situation of RSW source separation,collection,transportation and disposal in China,an RSW collection and transportation system suitable for the northern cold region was developed.Considering the low winter temperature in the northern cold region,different requirements for RSW collection,transportation and terminal disposal,scattered source points and single terminal disposal nodes in rural areas,the study focused on determining the number and location of transfer stations,established a model for transfer stations selection and RSW collection and transportation routes optimization for RSW collection and transportation system,and proposed the elite retention particle swarm optimization–genetic algorithm(ERPSO–GA).The rural area of Baiquan County was taken as a representative case,the collection and transportation scheme of which was given,and the feasibility of the scheme was clarified by simulation experiment.

Endoscopic transgastric fenestration versus percutaneous drainage for management of(peri)pancreatic fluid collections adjacent to gastric wall(with video)

BACKGROUND Percutaneous drainage(PCD)and endoscopic approaches have largely replaced surgical drainage as the initial approach for(peri)pancreatic fluid collections(PFC)s,while complications associated with endoscopic stent implantation are common.AIM To introduce a novel endoscopic therapy named endoscopic transgastric fenestration(ETGF),which involves resection of tissue by endoscopic accessory between gastric and PFCs without stent implantation,and to evaluate its efficacy and safety compared with PCD for the management of PFCs adjacent to the gastric wall.METHODS Patients diagnosed with PFCs adjacent to the gastric wall and who subsequently received ETGF or PCD were restrospectively enrolled.Indications for intervention were consistent with related guidelines.We analyzed patients baseline characteristics,technical and clinical success rate,recurrence and reintervention rate,procedure-related complications and adverse events.RESULTS Seventy-two eligible patients were retrospectively identified(ETGF=34,PCD=38)from October 2017 to May 2021.Patients in the ETGF group had a significantly higher clinical success rate than those in the PCD group(97.1 vs 76.3%,P=0.01).There were no statistically significant differences regarding recurrence,reintervention and incidence of complication between the two groups.While long-term catheter drainage was very common in the PCD group.CONCLUSION Compared with PCD,ETGF has a higher clinical success rate in the management of PFCs adjacent to the gastric wall.ETGF is an alternative effective strategy for the treatment of PFCs adjacent to the gastric wall.

Design and implementation of railway green performance basic data collection system

This study addressed the issues related to the collection and management of basic data for railway green performance. A railway green performance basic database has been constructed based on metadata and data exchange schemas. A data classification system has been established from the perspectives of businesses, processes,and entities. A BIM(Building Information Modelling) model data extraction scheme is proposed based on field similarity matching and a document content extraction scheme is proposed based on image recognition. A railway green performance basic data collection system has been developed, achieving efficient collection and integrated management of railway green performance basic data. This system can provide data support for applications such as railway carbon emissions accounting, green cost-benefit analysis, and evaluation of green design solutions.

Core collection construction of tea plant germplasm in Anhui Province based on genetic diversity analysis using simple sequence repeat markers

The tea plant[Camellia sinensis(L.)O.Kuntze]is an industrial crop in China.The Anhui Province has a long history of tea cultivation and has a large resource of tea germplasm with abundant genetic diversity.To reduce the cost of conservation and utilization of germplasm resources,a core collection needs to be constructed.To this end,573 representative tea accessions were collected from six major tea-producing areas in Anhui Province.Based on 60 pairs of simple sequence repeat(SSR)markers,phylogenetic relationships,population structure and principal coordinate analysis(PCoA)were conducted.Phylogenetic analysis indicated that the 573 tea individuals clustered into five groups were related to geographical location and were consistent with the results of the PCoA.Finally,we constructed a core collection consisting of 115 tea individuals,accounting for 20%of the whole collection.The 115 core collections were considered to have a 90.9%retention rate for the observed number of alleles(Na),and Shannon’s information index(I)of the core and whole collections were highly consistent.Of these,39 individuals were preserved in the Huangshan area,accounting for 33.9%of the core collection,while only 10 individuals were reserved in the Jinzhai County,accounting for 8.9%of the core set.PCoA of the accessions in the tea plant core collection exhibited a pattern nearly identical to that of the accessions in the entire collection,further supporting the broad representation of the core germplasm in Anhui Province.The results demonstrated that the core collection could represent the genetic diversity of the original collection.Our present work is valuable for the high-efficiency conservation and utilization of tea plant germplasms in Anhui Province.

NOMA Empowered Energy Efficient Data Collection and Wireless Power Transfer in Space-Air-Ground Integrated Networks

As the sixth generation network(6G)emerges,the Internet of remote things(IoRT)has become a critical issue.However,conventional terrestrial networks cannot meet the delay-sensitive data collection needs of IoRT networks,and the Space-Air-Ground integrated network(SAGIN)holds promise.We propose a novel setup that integrates non-orthogonal multiple access(NOMA)and wireless power transfer(WPT)to collect latency-sensitive data from IoRT networks.To extend the lifetime of devices,we aim to minimize the maximum energy consumption among all IoRT devices.Due to the coupling between variables,the resulting problem is non-convex.We first decouple the variables and split the original problem into four subproblems.Then,we propose an iterative algorithm to solve the corresponding subproblems based on successive convex approximation(SCA)techniques and slack variables.Finally,simulation results show that the NOMA strategy has a tremendous advantage over the OMA scheme in terms of network lifetime and energy efficiency,providing valuable insights.

Autonomous UAV 3D trajectory optimization and transmission scheduling for sensor data collection on uneven terrains

This paper considers a time-constrained data collection problem from a network of ground sensors located on uneven terrain by an Unmanned Aerial Vehicle(UAV),a typical Unmanned Aerial System(UAS).The ground sensors harvest renewable energy and are equipped with batteries and data buffers.The ground sensor model takes into account sensor data buffer and battery limitations.An asymptotically globally optimal method of joint UAV 3D trajectory optimization and data transmission schedule is developed.The developed method maximizes the amount of data transmitted to the UAV without losses and too long delays and minimizes the propulsion energy of the UAV.The developed algorithm of optimal trajectory optimization and transmission scheduling is based on dynamic programming.Computer simulations demonstrate the effectiveness of the proposed algorithm.

AUV-Aided Data Collection Considering Adaptive Ocean Currents for Underwater Wireless Sensor Networks

Autonomous underwater vehicle(AUV)-assisted data collection is an efficient approach to implementing smart ocean.However,the data collection in time-varying ocean currents is plagued by two critical issues:AUV yaw and sensor node movement.We propose an adaptive AUV-assisted data collection strategy for ocean currents to address these issues.First,we consider the energy consumption of an AUV in conjunction with the value of information(VoI)over the sensor nodes and formulate an optimization problem to maximize the VoI-energy ratio.The AUV yaw problem is then solved by deriving the AUV's reachable region in different ocean current environments and the optimal cruising direction to the target nodes.Finally,using the predicted VoI-energy ratio,we sequentially design a distributed path planning algorithm to select the next target node for AUV.The simulation results indicate that the proposed strategy can utilize ocean currents to aid AUV navigation,thereby reducing the AUV's energy consumption and ensuring timely data collection.