Bariatric surgery and diabetes:Current challenges and perspectives

Diabetes mellitus(DM)and obesity have become public issues of global concern.Bariatric surgery for the treatment of obesity combined with type 2 DM has been shown to be a safe and effective approach;however,there are limited studies that have systematically addressed the challenges of surgical treatment of obesity combined with DM.In this review,we summarize and answer the most pressing questions in the field of surgical treatment of obesity-associated DM.I believe that our insights will be of great help to clinicians in their daily practice.

The influence of multi-metal-veins on fractures propagation investigated by the experiment and simulation

Fracture propagation is affected by multi-metal-veins formed by geological diagenesis in shale during the hydraulic fracturing.However,the influence of multi-metal-veins on fractures propagation remains unclear.To solve the problem,based on the semi-circle bending(SCB)test and the extended finite element(XFEM)theory,the interaction between multi-metal-veins and fractures is investigated.The experimental results reveal that the fractures usually deflect at the upper or lower interfaces between metal veins and rocks(e.g.the specimen S-2),which is different from the propagation behavior of fractures in calcite veins.Meanwhile,the fracture toughness of the specimen S-1 is 24.40%higher than that of the specimen S-2,indicating that the increasing of total thickness of multiple metal veins in-creases the resistance to the fracture vertical propagation.The simulation results show that the increasing of the number,total thickness of veins,the modulus difference between veins and rock,the approach angle and the notch angle all increase the resistance of the fracture passing through metal veins.The maximum deviation distance(Dmax)of the fracture decreases with the number of veins,while thickness combination types of metal veins do not affect Dmax.The reduction of the notch angle leads to the more tortuous fracture propagation path.Finally,we propose a new comprehensive fracture network pattern.Fracture networks are divided into two categories,including orthogonal fracture networks and sub-orthogonal fracture networks,and then divided into six sub-categories further.The research results will provide reference for hydraulic fracturing of shale reservoirs containing multi-metal-veins.

Correlation between COVID-19 vaccination and diabetes mellitus:A systematic review

BACKGROUND Coronavirus disease 2019(COVID-19)is one of the current global public health threats and vaccination is the most effective tool to reduce the spread and decrease the severity of COVID-19.Diabetes is one of the important chronic diseases threatening human health and is a common comorbidity of COVID-19.What is the impact of diabetes on the immunization effect of COVID-19 vaccination?Conversely,does vaccination against COVID-19 exacerbate the severity of pre-existing diseases in patients with diabetes?There are limited and conflicting data on the interrelationship between diabetes and COVID-19 vaccination.AIM To explore the clinical factors and possible mechanisms underlying the interaction between COVID-19 vaccination and diabetes.METHODS We conducted a comprehensive search of PubMed,MEDLINE,EMBASE,and Reference Citation Analysis(https://www.referencecitationanalysis.com)online datab-ases,and medRxiv and bioRxiv gray literature using the keywords"SARSCoV-2","COVID-19","vaccine","vaccination","antibody",and"diabetes"individually or in combination,with a cut-off date of December 2,2022.We followed inclusion and exclusion criteria and after excluding duplicate publications,studies with quantifiable evidence were included in the full-text review,plus three manually searched publications,resulting in 54 studies being included in this review.RESULTS A total of 54 studies were included,from 17 countries.There were no randomized controlled studies.The largest sample size was 350963.The youngest of the included samples was 5 years old and the oldest was 98 years old.The included population included the general population and also some special populations with pediatric diabetes,hemodialysis,solid organ transplantation,and autoimmune diseases.The earliest study began in November 2020.Thirty studies discussed the effect of diabetes on vaccination,with the majority indicating that diabetes reduces the response to COVID-19 vaccination.The other 24 studies were on the effect of vaccination on diabetes,which included 18 case reports/series.Most of the studies concluded that COVID-19 vaccination had a risk of causing elevated blood glucose.A total of 12 of the 54 included studies indicated a"no effect"relationship between diabetes and vaccination.CONCLUSION There is a complex relationship between vaccination and diabetes with a bidirectional effect.Vaccination may contribute to the risk of worsening blood glucose in diabetic patients and diabetic patients may have a lower antibody response after vaccination than the general population.

Fast-armored target detection based on multi-scale representation and guided anchor

Focused on the task of fast and accurate armored target detection in ground battlefield,a detection method based on multi-scale representation network(MS-RN) and shape-fixed Guided Anchor(SF-GA)scheme is proposed.Firstly,considering the large-scale variation and camouflage of armored target,a new MS-RN integrating contextual information in battlefield environment is designed.The MS-RN extracts deep features from templates with different scales and strengthens the detection ability of small targets.Armored targets of different sizes are detected on different representation features.Secondly,aiming at the accuracy and real-time detection requirements,improved shape-fixed Guided Anchor is used on feature maps of different scales to recommend regions of interests(ROIs).Different from sliding or random anchor,the SF-GA can filter out 80% of the regions while still improving the recall.A special detection dataset for armored target,named Armored Target Dataset(ARTD),is constructed,based on which the comparable experiments with state-of-art detection methods are conducted.Experimental results show that the proposed method achieves outstanding performance in detection accuracy and efficiency,especially when small armored targets are involved.

Gabor-CNN for object detection based on small samples

Object detection models based on convolutional neural networks(CNN)have achieved state-of-the-art performance by heavily rely on large-scale training samples.They are insufficient when used in specific applications,such as the detection of military objects,as in these instances,a large number of samples is hard to obtain.In order to solve this problem,this paper proposes the use of Gabor-CNN for object detection based on a small number of samples.First of all,a feature extraction convolution kernel library composed of multi-shape Gabor and color Gabor is constructed,and the optimal Gabor convolution kernel group is obtained by means of training and screening,which is convolved with the input image to obtain feature information of objects with strong auxiliary function.Then,the k-means clustering algorithm is adopted to construct several different sizes of anchor boxes,which improves the quality of the regional proposals.We call this regional proposal process the Gabor-assisted Region Proposal Network(Gabor-assisted RPN).Finally,the Deeply-Utilized Feature Pyramid Network(DU-FPN)method is proposed to strengthen the feature expression of objects in the image.A bottom-up and a topdown feature pyramid is constructed in ResNet-50 and feature information of objects is deeply utilized through the transverse connection and integration of features at various scales.Experimental results show that the method proposed in this paper achieves better results than the state-of-art contrast models on data sets with small samples in terms of accuracy and recall rate,and thus has a strong application prospect.

Numerical simulation on the multiple planar fracture propagation with perforation plugging in horizontal wells

Intra-stage multi-cluster temporary plugging and diverting fracturing(ITPF)is one of the fastest-growing techniques to obtain uniform reservoir stimulation in shale gas reservoirs.However,propagation geometries of multiple fractures during ITPF are not clear due that the existing numerical models cannot capture the effects of perforation plugging.In this paper,a new three-dimensional FEM based on CZM was developed to investigate multiple planar fracture propagation considering perforation plugging during ITPF.Meanwhile,the fluid pipe element and its subroutine were first developed to realize the flux partitioning before or after perforation plugging.The results showed that the perforation plugging changed the original distribution of the number of perforations in each fracture,thus changing the flux partitioning after perforation plugging,which could eliminate the effect of stress interference between multiple fractures and promote a uniform fluid distribution.The standard deviation of fluid distribution in the perforation plugging case was only 8.48%of that in the non-diversion case.Furthermore,critical plugging parameters have been investigated quantitatively.Specifically,injecting more diverters will create a higher fluid pressure rise in the wellbore,which will increase the risk of wellbore integrity.Comprehensively considering pressure rise and fluid distribution,the number of diverters should be 50%of the total number of perforations(N_(pt)),whose standard deviation of fluid distribution of multiple fractures was lower than those in the cases of injecting 10%N_(pt),30%N_(pt)and 70%N_(pt).The diverters should be injected at an appropriate timing,i.e.40%or 50%of the total fracturing time(tft),whose standard deviation of the fluid distribution was only about 20%of standard deviations in the cases of injecting at20%tftor 70%tft.A single injection with all diverters can maintain high bottom-hole pressure for a longer period and promote a more uniform fluid distribution.The standard deviation of the fluid distribution in the case of a single injection was 43.62%-55.41%of the other cases with multiple injection times.This study provides a meaningful perspective and some optimal plugging parameters on the field design during IPTF.

Effect of electrical contact on performance of WSe_(2) field effect transistors

Two-dimensional(2 D) transition metal dichalcogenides(TMDCs) such as tungsten diselenide(WSe_(2)) have spead many interesting physical properties, which may become ideal candidates to develop new generation electronic and optoelectronic devices. In order to reveal essential features of 2 D TMDCs, it is necessary to fabricate high-quality devices with reliable electrical contact. We systematically analyze the effect of graphene and metal contacts on performance of multilayered WSe_(2) field effect transistors(FETs). The temperature-dependent transport characteristics of both devices are tested.Only graphene-contacted WSe_(2) FETs are observed with the metal-insulator transition phenomenon which mainly attributes to the ultra-clean contact interface and lowered contact barrier. Further characterization on contact barrier demonstrates that graphene contact enables lower contact barrier with WSe_(2) than metal contact, since the Fermi level of graphene can be modulated by the gate bias to match the Fermi level of the channel material. We also analyze the carrier mobility of both devices under different temperatures, revealing that graphene contact can reduce the charge scattering of the device caused by ionized impurities and phonon vibrations in low and room temperature regions, respectively. This work is expected to provide reference for fabricating 2 D material devices with decent performances.

Simplified p-i-n Perovskite Solar Cells with a Multifunctional Polyfullerene Electron Transporter

In prevailing p-i-n perovskite solar cells(PSCs),solution-processible fullerene molecules are widely used as electron-transporting layers(ETLs)but they typically suffer from poor uniformity and undesirable stability issues.Additionally,a separate bathocuproine(BCP)layer is needed to block hole tran sfer,increasing fabrication complexity and cost.Here,we address these limitations by develo ping a novel polymeric ETL(named PF BCP)synthesized by polymerizing C_(60)with BCP.This innovative material achieves both efficient electron transport and hole blocking,while its excellent uniformity minimizes interface recombination and enhances stability.Consequently,our blade-coated PSCs utilizing PFBCP achieve a high power conversion efficiency exceeding 22%and retain 91%of initial efficiency after 1200 h of light exposure.This development not only paves the way for commercially viable PSCs but also opens avenues for future ETL design to realize even more efficient and stable PSCs.

Risk Models for the Prize Collecting Steiner Tree Problems with Interval Data

Given a connected graph G=（V,E）with a nonnegative cost on each edge in E,a nonnegative prize at each vertex in V,and a target set V′V,the Prize Collecting Steiner Tree（PCST）problem is to find a tree T in G interconnecting all vertices of V′such that the total cost on edges in T minus the total prize at vertices in T is minimized.The PCST problem appears frequently in practice of operations research.While the problem is NP-hard in general,it is polynomial-time solvable when graphs G are restricted to series-parallel graphs.In this paper,we study the PCST problem with interval costs and prizes,where edge e could be included in T by paying cost xe∈[c e,c＋e]while taking risk（c＋e xe）/（c＋e c e）of malfunction at e,and vertex v could be asked for giving a prize yv∈[p v,p＋v]for its inclusion in T while taking risk（yv p v）/（p＋v p v）of refusal by v.We establish two risk models for the PCST problem with interval data.Under given budget upper bound on constructing tree T,one model aims at minimizing the maximum risk over edges and vertices in T and the other aims at minimizing the sum of risks over edges and vertices in T.We propose strongly polynomial-time algorithms solving these problems on series-parallel graphs to optimality.Our study shows that the risk models proposed have advantages over the existing robust optimization model,which often yields NP-hard problems even if the original optimization problems are polynomial-time solvable.

Improved Algorithm for Broadcast Scheduling of Minimal Latency in Wireless Ad Hoc Networks

A wide range of applications for wireless ad hoc networks are time-critical and impose stringent requirement on the communication latency. One of the key communication operations is to broadcast a message from a source node. This paper studies the minimum latency broadcast scheduling problem in wireless ad hoc networks under collision-free transmission model. The previously best known algorithm for this NP-hard problem produces a broadcast schedule whose latency is at least 648（rmax/rmin）^2 times that of the optimal schedule, where rmax and rmin are the maximum and minimum transmission ranges of nodes in a network, respectively. We significantly improve this result by proposing a new scheduling algorithm whose approximation performance ratio is at most （1 ＋ 2rmax/rmin）^2＋32, Moreover, under the proposed scheduling each node just needs to forward a message at most once.

Preface:Special Issue on Combinatorial Optimization

Combinatorics is,as defined by MathWorld,the branch of mathematics that studies the enumeration,combination and permutation of sets of elements and the mathemat-ical relations that characterize their properties.Combinatorial optimization not only enumerates the sets studied,but also has the goal of finding the member of the set in an efficient manner that optimizes an objective function.Combinatorial optimization is an emerging field at the forefront of combinatorics,theoretical computer science and operations research that has various applications in many disciplines of science,engineering,industry,economy,military and so on.