Sensor nodes in a wireless sensor network （WSN） are typically powered by batteries, thus the energy is constrained. It is our design goal to efficiently utilize the energy of each sensor node to extend its lifetime,...Sensor nodes in a wireless sensor network （WSN） are typically powered by batteries, thus the energy is constrained. It is our design goal to efficiently utilize the energy of each sensor node to extend its lifetime, so as to prolong the lifetime of the whole WSN. In this paper, we propose a path-based data aggregation scheme （PBDAS） for grid-based wireless sensor networks. In order to extend the lifetime of a WSN, we construct a grid infrastructure by partitioning the whole sensor field into a grid of cells. Each cell has a head responsible for aggregating its own data with the data sensed by the others in the same cell and then transmitting out. In order to efficiently and rapidly transmit the data to the base station （BS）, we link each cell head to form a chain. Each cell head on the chain takes turn becoming the chain leader responsible for transmitting data to the BS. Aggregated data moves from head to head along the chain, and finally the chain leader transmits to the BS. In PBDAS, only the cell heads need to transmit data toward the BS. Therefore, the data transmissions to the BS substantially decrease. Besides, the cell heads and chain leader are designated in turn according to the energy level so that the energy depletion of nodes is evenly distributed. Simulation results show that the proposed PBDAS extends the lifetime of sensor nodes, so as to make the lifetime of the whole network longer.展开更多
BACKGROUND Due to the increasing rate of thyroid nodules diagnosis,and the desire to avoid the unsightly cervical scar,remote thyroidectomies were invented and are increasingly performed.Transoral endoscopic thyroidec...BACKGROUND Due to the increasing rate of thyroid nodules diagnosis,and the desire to avoid the unsightly cervical scar,remote thyroidectomies were invented and are increasingly performed.Transoral endoscopic thyroidectomy vestibular approach and trans-areolar approaches(TAA)are the two most commonly used remote approaches.No previous meta-analysis has compared postoperative infections and swallowing difficulties among the two procedures.AIM To compared the same among patients undergoing lobectomy for unilateral thyroid carcinoma/benign thyroid nodule.METHODS We searched PubMed MEDLINE,Google Scholar,and Cochrane Library from the date of the first published article up to August 2025.The term used were transoral thyroidectomy vestibular approach,trans areolar thyroidectomy,scarless thyroidectomy,remote thyroidectomy,infections,postoperative,inflammation,dysphagia,and swallowing difficulties.We identified 130 studies,of them,30 full texts were screened and only six studies were included in the final meta-analysis.RESULTS Postoperative infections were not different between the two approaches,odd ratio=1.33,95%confidence interval:0.50-3.53,theχ2 was 1.92 and the P-value for overall effect of 0.57.Similarly,transient swallowing difficulty was not different between the two forms of surgery,with odd ratio=0.91,95%confidence interval:0.35-2.40;theχ2 was 1.32,and the P-value for overall effect of 0.85.CONCLUSION No significant statistical differences were evident between trans-oral endoscopic Mirghani H.Infections and swallowing difficulty in scarless thyroidectomy WJCC https://www.wjgnet.com 2 January 6,2026 Volume 14 Issue 1 thyroidectomy vestibular approach and trans-areolar approach regarding postoperative infection and transient swallowing difficulties.Further longer randomized trials are needed.展开更多
The photoacoustic imaging of lipid is intrinsically constrained by the feeble nature of endogenous lipid signals,posing a persistent sensitivity challenge that demands innovative solutions.Although adopting high-effic...The photoacoustic imaging of lipid is intrinsically constrained by the feeble nature of endogenous lipid signals,posing a persistent sensitivity challenge that demands innovative solutions.Although adopting high-efficiency excitation and detection elements may improve the imaging sensitivity to a certain extent,the application of the elements is inevitably subject to various limitations in practical applications,particularly during in vivo imaging and endoscopic imaging.In this study,we propose a multi-combinatorial approach to enhance the sensitivity of lipid photoacoustic imaging.The approach involves wavelet transform processing of one-dimensional A-line signals,gradient-based denoising of two-dimensional B-scan images,and finally,threedimensional spatial weighted averaging of the data processed by the previous two steps.This method not only significantly improves the signal-to-noise ratio(SNR)in distinguished feature regions of the image by around 10 dB,but also efficiently extracts weak signals with no distinct features in the original image.After processing with this method,the images acquired under single scanning were compared with those obtained under multiple scanning.The results showed highly consistent image features,with the structural similarity index increasing from 0.2 to 0.8,confirming the accuracy and reliability of the multi-combinatorial approach.展开更多
With the rapid development of intelligent navigation technology,efficient and safe path planning for mobile robots has become a core requirement.To address the challenges of complex dynamic environments,this paper pro...With the rapid development of intelligent navigation technology,efficient and safe path planning for mobile robots has become a core requirement.To address the challenges of complex dynamic environments,this paper proposes an intelligent path planning framework based on grid map modeling.First,an improved Safe and Smooth A*(SSA*)algorithm is employed for global path planning.By incorporating obstacle expansion and cornerpoint optimization,the proposed SSA*enhances the safety and smoothness of the planned path.Then,a Partitioned Dynamic Window Approach(PDWA)is integrated for local planning,which is triggered when dynamic or sudden static obstacles appear,enabling real-time obstacle avoidance and path adjustment.A unified objective function is constructed,considering path length,safety,and smoothness comprehensively.Multiple simulation experiments are conducted on typical port grid maps.The results demonstrate that the improved SSA*significantly reduces the number of expanded nodes and computation time in static environmentswhile generating smoother and safer paths.Meanwhile,the PDWA exhibits strong real-time performance and robustness in dynamic scenarios,achieving shorter paths and lower planning times compared to other graph search algorithms.The proposedmethodmaintains stable performance across maps of different scales and various port scenarios,verifying its practicality and potential for wider application.展开更多
The 17 Sustainable Development Goals(SDGs)for 2030,adopted by all United Nations member states in 2015,are facing a range of challenges.Factors such as climate change,regional conflicts and economic recession are havi...The 17 Sustainable Development Goals(SDGs)for 2030,adopted by all United Nations member states in 2015,are facing a range of challenges.Factors such as climate change,regional conflicts and economic recession are having a significant impact,particularly on global poverty governance.As a platform for dialogue,exchange and technical cooperation,the 2025 International Seminar on Global Poverty Reduction Partnerships was held in Beijing on 10 December 2025.展开更多
The rapid identification of γ-emitting radionuclides with low activity levels in public areas is crucial for nuclear safety.However,classical methods rely on full-energy peaks in the integral spectrum,requiring suffi...The rapid identification of γ-emitting radionuclides with low activity levels in public areas is crucial for nuclear safety.However,classical methods rely on full-energy peaks in the integral spectrum,requiring sufficient count accumulation for evaluation,thereby limiting response time.The sequential Bayesian approach,which utilizes prior information and considers both photon energies and interarrival times,can significantly enhance the performance of radionuclides identification.This study proposes a theoretical optimization method for the traditional sequential Bayesian approach.Each photon is processed sequentially,and the corresponding posterior probability is updated in real time using a noninformative prior from the Bayesian theory.By comparing the posterior probabilities of the background and radionuclides based on the energy variance and time interval,the type of γ-rays can be identified(background characteristic γ-rays,Compton plateaus γ-rays,or radionuclide-specific characteristic γ-rays).By integrating the information from these multiple characteristic γ-rays,the presence and type of radionuclides were determined based on the final decision function and a set threshold.Based on theoretical research,verification experiments were conducted using a LaBr_(3)(Ce)detector in both low-and natural background radiation environments with typical radionuclides(^(137)Cs,^(60)Co,and ^(133)Ba).The results show that this approach can identify ^(137)Cs in 7.9 s and 8.5 s(source dose rate contribution:approximately 6.5×10^(−3)μGy/h),^(60)Co in 8.1 s and 9.8 s(approximately 4.8×10^(−2)μGy/h),and ^(133)Ba in 4.05 s and 5.99 s(approximately 3.4×10^(−2)μGy/h)under low and natural background radiation,respectively,with a miss rate below 0.01%.This demonstrates the effectiveness of the proposed approach for fast radionuclides identification,even at low activity levels and highlights its potential for enhancing public safety in diverse radiation environments.展开更多
In this paper, we present a malicious node detection scheme using confidence-level evaluation in a grid-based wireless sensor network. The sensor field is divided into square grids, where sensor nodes in each grid for...In this paper, we present a malicious node detection scheme using confidence-level evaluation in a grid-based wireless sensor network. The sensor field is divided into square grids, where sensor nodes in each grid form a cluster with a cluster head. Each cluster head maintains the confidence levels of its member nodes based on their readings and reflects them in decision-making. Two thresholds are used to distinguish between false alarms due to malicious nodes and events. In addition, the center of an event region is estimated, if necessary, to enhance the event and malicious node detection accuracy. Experimental results show that the scheme can achieve high malicious node detection accuracy without sacrificing normal sensor nodes.展开更多
This report introduced new concept and technics for a grid-based fishery management system. The fishing ground was first divided into small grid of equal area, each with predefined longitudes and latitudes (both 0.033...This report introduced new concept and technics for a grid-based fishery management system. The fishing ground was first divided into small grid of equal area, each with predefined longitudes and latitudes (both 0.033 degrees or approximately 2 × 2 nautical miles in this study). All grids were laid and formatted into a Microsoft-Excel spreadsheet system, as defined by the coastline. Individual sheets were also constructed to represent different ecological characters, serving as supporting data of the main grid-map. Including individual fishing record, water depth, wind & current vector, benthic character, etc. Cellular automata (CA) mathematics was applied for simulation studies. They were programmed on the built-in Visual BASIC langrage in EXCEL. In a three-year research project, the author was able to accomplish the following major results: 1) An EXCEL-based spreadsheet system for storage of fishing effort in each grid. Provided that data of fishing yield is also available for each grid, research model for fishery management can be constructed, leading toward solutions for total allowable catch (TAC) as well as maximum economic yield (MEY). 2) A multi-layered, 2-dimentional spread-sheet system demonstrating the distribution of relative intensity for individual grids. The system can be decked up with different ecological data for more advanced studies. 3) Estimation of the nearest distance between two special grids as well as fishing harbors. This would help in more efficient navigation management and allocation of fishing rights for the fishing vessels.展开更多
When senors transmit their data to the sink via multi-hop communication,the sensors closer to the sink are burdened with heavy relay traffic and tend to die early.On the contrary,if all sensors transmit datas to the s...When senors transmit their data to the sink via multi-hop communication,the sensors closer to the sink are burdened with heavy relay traffic and tend to die early.On the contrary,if all sensors transmit datas to the sink via single-hop communication,the sensors further from the sink will die much more quickly than those closer to the sink.In this paper,we first develop an analytical model to derive the optimal cluster radius.Then we propose a mixed communication method on grid-based where the sensors can transmit data to the sink in either single-hop or multi-hop.Finally,we conduct extensive experiments and show that our method outperforms LEACH and HEED in terms of network lifetime by balancing energy consumption.展开更多
This work proposes a geographic routing protocol for UWSNs based on the construction of a 3D virtual grid structure, called Void-Avoidance Grid-based Multipath Position-based Routing (VA-GMPR). It consists of two main...This work proposes a geographic routing protocol for UWSNs based on the construction of a 3D virtual grid structure, called Void-Avoidance Grid-based Multipath Position-based Routing (VA-GMPR). It consists of two main components, the multipath routing scheme and the grid-based void avoidance (GVA) mechanism for handling routing holes. The multipath routing scheme adopts node-disjoint routes from the source to the sink in order to enhance network reliability and load balancing. While the GVA mechanism handles the problem of holes in 3D virtual grid structure based on three techniques: Hole bypass, path diversion, and path backtracking. The performance evaluation of the VA-GMPR protocol was compared to a recently proposed grid-based routing protocol for UWSNs, called Energy-efficient Multipath Geographic Grid-based Routing (EMGGR). The results showed that the VA-GMPR protocol outperformed the EMGGR protocol in terms of packet delivery ratio, and end-to end-delay. However, the results also showed that the VA-GMPR protocol exhibited higher energy consumption compared to EMGGR.展开更多
This work proposes an efficient disjoint multipath geographic routing algorithm for dense wireless sensor networks (WSN), called Multipath Grid-based Enabled Geographic Routing (MGEGR). The proposed algorithm relies o...This work proposes an efficient disjoint multipath geographic routing algorithm for dense wireless sensor networks (WSN), called Multipath Grid-based Enabled Geographic Routing (MGEGR). The proposed algorithm relies on the construction of a 2-D logical grid in the geographical region of deployment. The objective of the proposed scheme is to determine optimal or near-optimal (within a defined constant) multiple disjoint paths (multipath) from a source node to the sink, in order to enhance the reliability of the network. The determined multiple disjoint paths would be used by the source node in a round-robin way to balance the traffic across the disjoint paths, and to avoid discovered paths with cell holes. The proposed scheme limits the use of broadcasting to the process of gateway election within each cell, and the process of maintaining the table of neighbors of each gateway. Our simulation results show the effectiveness and scalability of our routing scheme with increased network size compared to on-demand routing protocols.展开更多
Cardiovascular diseases(CVDs)remain the leading cause of morbidity and mortality worldwide,necessitating innovative diagnostic and prognostic strategies.Traditional biomarkers like C-reactive protein,uric acid,troponi...Cardiovascular diseases(CVDs)remain the leading cause of morbidity and mortality worldwide,necessitating innovative diagnostic and prognostic strategies.Traditional biomarkers like C-reactive protein,uric acid,troponin,and natriuretic peptides play crucial roles in CVD management,yet they are often limited by sensitivity and specificity constraints.This narrative review critically examines the emerging landscape of cardiac biomarkers and advocates for a multiple-marker approach to enhance early detection,prognosis,and risk stratification of CVD.In recent years,several novel biomarkers have shown promise in revolutionizing CVD diagnostics.Gamma-glutamyltransferase,microRNAs,endothelial microparticles,placental growth factor,trimethylamine N-oxide,retinol-binding protein 4,copeptin,heart-type fatty acid-binding protein,galectin-3,growth differentiation factor-15,soluble suppression of tumorigenicity 2,fibroblast growth factor 23,and adrenomedullin have emerged as significant indicators of CV health.These biomarkers provide insights into various pathophysiological processes,such as oxidative stress,endothelial dysfunction,inflammation,metabolic disturbances,and myocardial injury.The integration of these novel biomarkers with traditional ones offers a more comprehensive understanding of CVD mechanisms.This multiple-marker approach can improve diagnostic accuracy,allowing for better risk stratification and more personalized treatment strategies.This review underscores the need for continued research to validate the clinical utility of these biomarkers and their potential incorporation into routine clinical practice.By leveraging the strengths of both traditional and novel biomarkers,precise therapeutic plans can be developed,thereby improving the management and prognosis of patients with CVDs.The ongoing exploration and validation of these biomarkers are crucial for advancing CV care and addressing the limitations of current diagnostic tools.展开更多
For large-scale heterogeneous multi-agent systems(MASs)with characteristics of dense-sparse mixed distribution,this paper investigates the practical finite-time deployment problem by establishing a novel crossspecies ...For large-scale heterogeneous multi-agent systems(MASs)with characteristics of dense-sparse mixed distribution,this paper investigates the practical finite-time deployment problem by establishing a novel crossspecies bionic analytical framework based on the partial differential equation-ordinary differential equation(PDE-ODE)approach.Specifically,by designing a specialized network communication protocol and employing the spatial continuum method for densely distributed agents,this paper models the tracking errors of densely distributed agents as a PDE equivalent to a human disease transmission model,and that of sparsely distributed agents as several ODEs equivalent to the predator population models.The coupling relationship between the PDE and ODE models is established through boundary conditions of the PDE,thereby forming a PDE-ODE-based tracking error model for the considered MASs.Furthermore,by integrating adaptive neural control scheme with the aforementioned biological models,a“Flexible Neural Network”endowed with adaptive and self-stabilized capabilities is constructed,which acts upon the considered MASs,enabling their practical finite-time deployment.Finally,effectiveness of the developed approach is illustrated through a numerical example.展开更多
The progressive loss of dopaminergic neurons in affected patient brains is one of the pathological features of Parkinson's disease,the second most common human neurodegenerative disease.Although the detailed patho...The progressive loss of dopaminergic neurons in affected patient brains is one of the pathological features of Parkinson's disease,the second most common human neurodegenerative disease.Although the detailed pathogenesis accounting for dopaminergic neuron degeneration in Parkinson's disease is still unclear,the advancement of stem cell approaches has shown promise for Parkinson's disease research and therapy.The induced pluripotent stem cells have been commonly used to generate dopaminergic neurons,which has provided valuable insights to improve our understanding of Parkinson's disease pathogenesis and contributed to anti-Parkinson's disease therapies.The current review discusses the practical approaches and potential applications of induced pluripotent stem cell techniques for generating and differentiating dopaminergic neurons from induced pluripotent stem cells.The benefits of induced pluripotent stem cell-based research are highlighted.Various dopaminergic neuron differentiation protocols from induced pluripotent stem cells are compared.The emerging three-dimension-based brain organoid models compared with conventional two-dimensional cell culture are evaluated.Finally,limitations,challenges,and future directions of induced pluripotent stem cell–based approaches are analyzed and proposed,which will be significant to the future application of induced pluripotent stem cell-related techniques for Parkinson's disease.展开更多
Deep learning algorithms have been rapidly incorporated into many different applications due to the increase in computational power and the availability of massive amounts of data.Recently,both deep learning and ensem...Deep learning algorithms have been rapidly incorporated into many different applications due to the increase in computational power and the availability of massive amounts of data.Recently,both deep learning and ensemble learning have been used to recognize underlying structures and patterns from high-level features to make predictions/decisions.With the growth in popularity of deep learning and ensemble learning algorithms,they have received significant attention from both scientists and the industrial community due to their superior ability to learn features from big data.Ensemble deep learning has exhibited significant performance in enhancing learning generalization through the use of multiple deep learning algorithms.Although ensemble deep learning has large quantities of training parameters,which results in time and space overheads,it performs much better than traditional ensemble learning.Ensemble deep learning has been successfully used in several areas,such as bioinformatics,finance,and health care.In this paper,we review and investigate recent ensemble deep learning algorithms and techniques in health care domains,medical imaging,health care data analytics,genomics,diagnosis,disease prevention,and drug discovery.We cover several widely used deep learning algorithms along with their architectures,including deep neural networks(DNNs),convolutional neural networks(CNNs),recurrent neural networks(RNNs),and generative adversarial networks(GANs).Common healthcare tasks,such as medical imaging,electronic health records,and genomics,are also demonstrated.Furthermore,in this review,the challenges inherent in reducing the burden on the healthcare system are discussed and explored.Finally,future directions and opportunities for enhancing healthcare model performance are discussed.展开更多
This article provides a comprehensive analysis of the study by Hou et al,focusing on the complex interplay between psychological and physical factors in the postoperative recovery(POR)of patients with perianal disease...This article provides a comprehensive analysis of the study by Hou et al,focusing on the complex interplay between psychological and physical factors in the postoperative recovery(POR)of patients with perianal diseases.The study sheds light on how illness perception,anxiety,and depression significantly influence recovery outcomes.Hou et al developed a predictive model that demonstrated high accuracy in identifying patients at risk of poor recovery.The article explores the critical role of pre-operative psychological assessment,highlighting the need for mental health support and personalized recovery plans in enhancing POR quality.A multidisciplinary approach,integrating mental health professionals with surgeons,anesthesiologists,and other specialists,is emphasized to ensure comprehensive care for patients.The study’s findings serve as a call to integrate psychological care into surgical practice to optimize outcomes for patients with perianal diseases.展开更多
Microwave-assisted rock-breaking technology,as a novel hybrid approach,is anticipated to facilitate the efficient excavation of complex rock formations.It is therefore crucial to understand the damage and failure mech...Microwave-assisted rock-breaking technology,as a novel hybrid approach,is anticipated to facilitate the efficient excavation of complex rock formations.It is therefore crucial to understand the damage and failure mechanisms of rocks that have been subjected to irradiation.In this study,uniaxial compression experiments were conducted on granite specimens after 1.4 kW microwave irradiation for varying durations.Furthermore,a numerical method was proposed to solve electromagnetic-thermal-mechanical coupling problems by integrating finite and discrete elements.The results demonstrated a differential temperature distribution(high temperature in the middle and low-temperature areas at the ends)in the granite specimens under microwave irradiation,which resulted in a notable reduction in their physical and mechanical properties.As the duration of irradiation increased,the rate of heating and the extent of strength reduction both diminished,while the morphology and distribution of cracks at ultimate failure became increasingly complex.The numerical method effectively addresses the simulation challenges associated with the electromagnetic selective heating of granite containing multiple polar minerals under microwave irradiation.This approach accounted for the non-uniform thermal expansion of the minerals and provided a comprehensive model of damage progression under compression.展开更多
Objective: To explore the effect of Health Action Process Approach (HAPA) theory in patients with type D personality psoriasis. Methods: A total of 66 patients with type D personality psoriasis admitted to the dermato...Objective: To explore the effect of Health Action Process Approach (HAPA) theory in patients with type D personality psoriasis. Methods: A total of 66 patients with type D personality psoriasis admitted to the dermatology department of a top-three hospital in Jingzhou City from November 2022 to July 2023 were selected and divided into control group and test group with 33 cases in each group by random number table method. The control group received routine health education, and the experimental group received health education based on the HAPA theory. Chronic disease self-efficacy scale, hospital anxiety and depression scale and skin disease quality of life scale were used to evaluate the effect of intervention. Results: After 3 months of intervention, the scores of self-efficacy in experimental group were higher than those in control group (P P Conclusion: Health education based on the theory of HAPA can enhance the self-efficacy of patients with type D personality psoriasis, relieve negative emotions and improve their quality of life.展开更多
Background:Social anxiety is prevalent among adolescents and severely impacts their mental health and social functioning.This study aims to explore the underlying mechanisms and subgroup differences in adolescent soci...Background:Social anxiety is prevalent among adolescents and severely impacts their mental health and social functioning.This study aims to explore the underlying mechanisms and subgroup differences in adolescent social anxiety to provide a theoretical basis for targeted interventions.Methods:3025 Chinese adolescents(Meanage=13.91±1.60 years;47%male)completed self-report measures of physical activity,core self-evaluation,and social anxiety.Variable-centered analyses employed PROCESS Model 4 with 5000 bootstrap samples;covariates were gender,grade,and place of residence.Person-centered analyses used latent profile analysis in Mplus 8.3 to identify subgroups based on social anxiety item profiles.Results:Variable-centered analyses showed that physical activity had a significant negative association with social anxiety(β=−0.224,p<0.001)and a significant positive association with core self-evaluation(β=0.471,p<0.001);core self-evaluation partially mediated this relationship,accounting for 30%of the total effect.Person-centered analyses revealed an optimal two-profile solution:a low social anxiety profile(89.6%)and a high social anxiety profile(10.4%).The high social anxiety profile reported significantly lower physical activity and lower core self-evaluation than the low social anxiety profile.Conclusions:This study integrates variable-centered and person-centered evidence,identifies physical activity and core self-evaluation as key modifiable factors in reducing social anxiety,providing a theoretical basis for targeted and differentiated interventions.展开更多
BACKGROUND The root of mesentery dissection is one of the critical maneuvers,especially in borderline resectable pancreatic head cancer.Intra-abdominal chyle leak(CL)including chylous ascites may ensue in up to 10%of ...BACKGROUND The root of mesentery dissection is one of the critical maneuvers,especially in borderline resectable pancreatic head cancer.Intra-abdominal chyle leak(CL)including chylous ascites may ensue in up to 10%of patients after pancreatic resections.Globally recognized superior mesenteric artery(SMA)first approaches are invariably performed.The mesenteric dissection through the inferior infracolic approach has been discussed in this study emphasizing its post-operative impact on CL which is the cornerstone of this study.AIM To assess incidence,risk factors,clinical impact of CL following root of mesentery dissection,and the different treatment modalities.METHODS This is a retrospective study incorporating the patients who underwent dissection of the root of mesentery with inferior infracolic SMA first approach pancreat-oduodenectomy for the ventral body and uncinate mass of pancreas in the Department of Gastrointestinal and General Surgery of Kathmandu Medical College and Teaching Hospital from January 1,2021 to February 28,2024.Intraop-erative findings and postoperative outcomes were analyzed.RESULTS In three years,ten patients underwent root of mesentery dissection with inferior infracolic SMA first approach pancreatoduodenectomy.The mean age was 67.6 years with a male-to-female ratio of 4:5.CL was seen in four patients.With virtue of CL,Clavien-Dindo grade Ⅱ or higher morbidity was observed in four patients.Two patients had a hospital stay of more than 20 days with the former having a delayed gastric emptying and the latter with long-term total parenteral nutrition requirement.The mean operative time was 330 minutes.Curative resection was achieved in 100%of the patients.The mean duration of the intensive care unit and hospital stay were 2.55±1.45 days and 15.7±5.32 days,respectively.CONCLUSION Root of mesentery dissection with lymphadenectomy and vascular resection correlated with occurrence of CL.After complete curative resection,these were managed with total parenteral nutrition without adversely impacting outcome.展开更多
基金supported by the NSC under Grant No.NSC-101-2221-E-239-032 and NSC-102-2221-E-239-020
文摘Sensor nodes in a wireless sensor network （WSN） are typically powered by batteries, thus the energy is constrained. It is our design goal to efficiently utilize the energy of each sensor node to extend its lifetime, so as to prolong the lifetime of the whole WSN. In this paper, we propose a path-based data aggregation scheme （PBDAS） for grid-based wireless sensor networks. In order to extend the lifetime of a WSN, we construct a grid infrastructure by partitioning the whole sensor field into a grid of cells. Each cell has a head responsible for aggregating its own data with the data sensed by the others in the same cell and then transmitting out. In order to efficiently and rapidly transmit the data to the base station （BS）, we link each cell head to form a chain. Each cell head on the chain takes turn becoming the chain leader responsible for transmitting data to the BS. Aggregated data moves from head to head along the chain, and finally the chain leader transmits to the BS. In PBDAS, only the cell heads need to transmit data toward the BS. Therefore, the data transmissions to the BS substantially decrease. Besides, the cell heads and chain leader are designated in turn according to the energy level so that the energy depletion of nodes is evenly distributed. Simulation results show that the proposed PBDAS extends the lifetime of sensor nodes, so as to make the lifetime of the whole network longer.
文摘BACKGROUND Due to the increasing rate of thyroid nodules diagnosis,and the desire to avoid the unsightly cervical scar,remote thyroidectomies were invented and are increasingly performed.Transoral endoscopic thyroidectomy vestibular approach and trans-areolar approaches(TAA)are the two most commonly used remote approaches.No previous meta-analysis has compared postoperative infections and swallowing difficulties among the two procedures.AIM To compared the same among patients undergoing lobectomy for unilateral thyroid carcinoma/benign thyroid nodule.METHODS We searched PubMed MEDLINE,Google Scholar,and Cochrane Library from the date of the first published article up to August 2025.The term used were transoral thyroidectomy vestibular approach,trans areolar thyroidectomy,scarless thyroidectomy,remote thyroidectomy,infections,postoperative,inflammation,dysphagia,and swallowing difficulties.We identified 130 studies,of them,30 full texts were screened and only six studies were included in the final meta-analysis.RESULTS Postoperative infections were not different between the two approaches,odd ratio=1.33,95%confidence interval:0.50-3.53,theχ2 was 1.92 and the P-value for overall effect of 0.57.Similarly,transient swallowing difficulty was not different between the two forms of surgery,with odd ratio=0.91,95%confidence interval:0.35-2.40;theχ2 was 1.32,and the P-value for overall effect of 0.85.CONCLUSION No significant statistical differences were evident between trans-oral endoscopic Mirghani H.Infections and swallowing difficulty in scarless thyroidectomy WJCC https://www.wjgnet.com 2 January 6,2026 Volume 14 Issue 1 thyroidectomy vestibular approach and trans-areolar approach regarding postoperative infection and transient swallowing difficulties.Further longer randomized trials are needed.
基金supported by the National Key Research and Development Program of China(2022YFC2402400)the National Natural Science Foundation of China(82027803,62275062)+7 种基金the Guangdong Provincial Key Laboratory of Biomedical Optical Imaging Technology(2020B121201010)the Shenzhen Science and Technology Innovation Committee under Grant(JCYJ20220818101417039)the Shenzhen Key Laboratory for Molecular lmaging(ZDSY20130401165820357)the Shenzhen Medical Research Fund(D2404002)the Project of Shandong Innovation and Startup Community of High-end Medical Apparatus and Instruments(2023-SGTTXM-002 and 2024-SGTTXM-005)the Shandong Province Technology Innovation Guidance Plan(Central Leading Local Science and Technology Development Fund)(YDZX2023115)the Taishan Scholar Special Funding Project of Shandong Provinceand the Shandong Laboratory of Advanced Biomaterials and Medical Devices in Weihai(ZL202402).
文摘The photoacoustic imaging of lipid is intrinsically constrained by the feeble nature of endogenous lipid signals,posing a persistent sensitivity challenge that demands innovative solutions.Although adopting high-efficiency excitation and detection elements may improve the imaging sensitivity to a certain extent,the application of the elements is inevitably subject to various limitations in practical applications,particularly during in vivo imaging and endoscopic imaging.In this study,we propose a multi-combinatorial approach to enhance the sensitivity of lipid photoacoustic imaging.The approach involves wavelet transform processing of one-dimensional A-line signals,gradient-based denoising of two-dimensional B-scan images,and finally,threedimensional spatial weighted averaging of the data processed by the previous two steps.This method not only significantly improves the signal-to-noise ratio(SNR)in distinguished feature regions of the image by around 10 dB,but also efficiently extracts weak signals with no distinct features in the original image.After processing with this method,the images acquired under single scanning were compared with those obtained under multiple scanning.The results showed highly consistent image features,with the structural similarity index increasing from 0.2 to 0.8,confirming the accuracy and reliability of the multi-combinatorial approach.
文摘With the rapid development of intelligent navigation technology,efficient and safe path planning for mobile robots has become a core requirement.To address the challenges of complex dynamic environments,this paper proposes an intelligent path planning framework based on grid map modeling.First,an improved Safe and Smooth A*(SSA*)algorithm is employed for global path planning.By incorporating obstacle expansion and cornerpoint optimization,the proposed SSA*enhances the safety and smoothness of the planned path.Then,a Partitioned Dynamic Window Approach(PDWA)is integrated for local planning,which is triggered when dynamic or sudden static obstacles appear,enabling real-time obstacle avoidance and path adjustment.A unified objective function is constructed,considering path length,safety,and smoothness comprehensively.Multiple simulation experiments are conducted on typical port grid maps.The results demonstrate that the improved SSA*significantly reduces the number of expanded nodes and computation time in static environmentswhile generating smoother and safer paths.Meanwhile,the PDWA exhibits strong real-time performance and robustness in dynamic scenarios,achieving shorter paths and lower planning times compared to other graph search algorithms.The proposedmethodmaintains stable performance across maps of different scales and various port scenarios,verifying its practicality and potential for wider application.
文摘The 17 Sustainable Development Goals(SDGs)for 2030,adopted by all United Nations member states in 2015,are facing a range of challenges.Factors such as climate change,regional conflicts and economic recession are having a significant impact,particularly on global poverty governance.As a platform for dialogue,exchange and technical cooperation,the 2025 International Seminar on Global Poverty Reduction Partnerships was held in Beijing on 10 December 2025.
基金supported by the Program for NIM-Basic Research Business Expenses Key Field Program,China(No.AKYCX2315).
文摘The rapid identification of γ-emitting radionuclides with low activity levels in public areas is crucial for nuclear safety.However,classical methods rely on full-energy peaks in the integral spectrum,requiring sufficient count accumulation for evaluation,thereby limiting response time.The sequential Bayesian approach,which utilizes prior information and considers both photon energies and interarrival times,can significantly enhance the performance of radionuclides identification.This study proposes a theoretical optimization method for the traditional sequential Bayesian approach.Each photon is processed sequentially,and the corresponding posterior probability is updated in real time using a noninformative prior from the Bayesian theory.By comparing the posterior probabilities of the background and radionuclides based on the energy variance and time interval,the type of γ-rays can be identified(background characteristic γ-rays,Compton plateaus γ-rays,or radionuclide-specific characteristic γ-rays).By integrating the information from these multiple characteristic γ-rays,the presence and type of radionuclides were determined based on the final decision function and a set threshold.Based on theoretical research,verification experiments were conducted using a LaBr_(3)(Ce)detector in both low-and natural background radiation environments with typical radionuclides(^(137)Cs,^(60)Co,and ^(133)Ba).The results show that this approach can identify ^(137)Cs in 7.9 s and 8.5 s(source dose rate contribution:approximately 6.5×10^(−3)μGy/h),^(60)Co in 8.1 s and 9.8 s(approximately 4.8×10^(−2)μGy/h),and ^(133)Ba in 4.05 s and 5.99 s(approximately 3.4×10^(−2)μGy/h)under low and natural background radiation,respectively,with a miss rate below 0.01%.This demonstrates the effectiveness of the proposed approach for fast radionuclides identification,even at low activity levels and highlights its potential for enhancing public safety in diverse radiation environments.
文摘In this paper, we present a malicious node detection scheme using confidence-level evaluation in a grid-based wireless sensor network. The sensor field is divided into square grids, where sensor nodes in each grid form a cluster with a cluster head. Each cluster head maintains the confidence levels of its member nodes based on their readings and reflects them in decision-making. Two thresholds are used to distinguish between false alarms due to malicious nodes and events. In addition, the center of an event region is estimated, if necessary, to enhance the event and malicious node detection accuracy. Experimental results show that the scheme can achieve high malicious node detection accuracy without sacrificing normal sensor nodes.
文摘This report introduced new concept and technics for a grid-based fishery management system. The fishing ground was first divided into small grid of equal area, each with predefined longitudes and latitudes (both 0.033 degrees or approximately 2 × 2 nautical miles in this study). All grids were laid and formatted into a Microsoft-Excel spreadsheet system, as defined by the coastline. Individual sheets were also constructed to represent different ecological characters, serving as supporting data of the main grid-map. Including individual fishing record, water depth, wind & current vector, benthic character, etc. Cellular automata (CA) mathematics was applied for simulation studies. They were programmed on the built-in Visual BASIC langrage in EXCEL. In a three-year research project, the author was able to accomplish the following major results: 1) An EXCEL-based spreadsheet system for storage of fishing effort in each grid. Provided that data of fishing yield is also available for each grid, research model for fishery management can be constructed, leading toward solutions for total allowable catch (TAC) as well as maximum economic yield (MEY). 2) A multi-layered, 2-dimentional spread-sheet system demonstrating the distribution of relative intensity for individual grids. The system can be decked up with different ecological data for more advanced studies. 3) Estimation of the nearest distance between two special grids as well as fishing harbors. This would help in more efficient navigation management and allocation of fishing rights for the fishing vessels.
文摘When senors transmit their data to the sink via multi-hop communication,the sensors closer to the sink are burdened with heavy relay traffic and tend to die early.On the contrary,if all sensors transmit datas to the sink via single-hop communication,the sensors further from the sink will die much more quickly than those closer to the sink.In this paper,we first develop an analytical model to derive the optimal cluster radius.Then we propose a mixed communication method on grid-based where the sensors can transmit data to the sink in either single-hop or multi-hop.Finally,we conduct extensive experiments and show that our method outperforms LEACH and HEED in terms of network lifetime by balancing energy consumption.
文摘This work proposes a geographic routing protocol for UWSNs based on the construction of a 3D virtual grid structure, called Void-Avoidance Grid-based Multipath Position-based Routing (VA-GMPR). It consists of two main components, the multipath routing scheme and the grid-based void avoidance (GVA) mechanism for handling routing holes. The multipath routing scheme adopts node-disjoint routes from the source to the sink in order to enhance network reliability and load balancing. While the GVA mechanism handles the problem of holes in 3D virtual grid structure based on three techniques: Hole bypass, path diversion, and path backtracking. The performance evaluation of the VA-GMPR protocol was compared to a recently proposed grid-based routing protocol for UWSNs, called Energy-efficient Multipath Geographic Grid-based Routing (EMGGR). The results showed that the VA-GMPR protocol outperformed the EMGGR protocol in terms of packet delivery ratio, and end-to end-delay. However, the results also showed that the VA-GMPR protocol exhibited higher energy consumption compared to EMGGR.
文摘This work proposes an efficient disjoint multipath geographic routing algorithm for dense wireless sensor networks (WSN), called Multipath Grid-based Enabled Geographic Routing (MGEGR). The proposed algorithm relies on the construction of a 2-D logical grid in the geographical region of deployment. The objective of the proposed scheme is to determine optimal or near-optimal (within a defined constant) multiple disjoint paths (multipath) from a source node to the sink, in order to enhance the reliability of the network. The determined multiple disjoint paths would be used by the source node in a round-robin way to balance the traffic across the disjoint paths, and to avoid discovered paths with cell holes. The proposed scheme limits the use of broadcasting to the process of gateway election within each cell, and the process of maintaining the table of neighbors of each gateway. Our simulation results show the effectiveness and scalability of our routing scheme with increased network size compared to on-demand routing protocols.
文摘Cardiovascular diseases(CVDs)remain the leading cause of morbidity and mortality worldwide,necessitating innovative diagnostic and prognostic strategies.Traditional biomarkers like C-reactive protein,uric acid,troponin,and natriuretic peptides play crucial roles in CVD management,yet they are often limited by sensitivity and specificity constraints.This narrative review critically examines the emerging landscape of cardiac biomarkers and advocates for a multiple-marker approach to enhance early detection,prognosis,and risk stratification of CVD.In recent years,several novel biomarkers have shown promise in revolutionizing CVD diagnostics.Gamma-glutamyltransferase,microRNAs,endothelial microparticles,placental growth factor,trimethylamine N-oxide,retinol-binding protein 4,copeptin,heart-type fatty acid-binding protein,galectin-3,growth differentiation factor-15,soluble suppression of tumorigenicity 2,fibroblast growth factor 23,and adrenomedullin have emerged as significant indicators of CV health.These biomarkers provide insights into various pathophysiological processes,such as oxidative stress,endothelial dysfunction,inflammation,metabolic disturbances,and myocardial injury.The integration of these novel biomarkers with traditional ones offers a more comprehensive understanding of CVD mechanisms.This multiple-marker approach can improve diagnostic accuracy,allowing for better risk stratification and more personalized treatment strategies.This review underscores the need for continued research to validate the clinical utility of these biomarkers and their potential incorporation into routine clinical practice.By leveraging the strengths of both traditional and novel biomarkers,precise therapeutic plans can be developed,thereby improving the management and prognosis of patients with CVDs.The ongoing exploration and validation of these biomarkers are crucial for advancing CV care and addressing the limitations of current diagnostic tools.
基金The National Key R&D Program of China(2021ZD0201300)the National Natural Science Foundation of China(624B2058,U1913602 and 61936004)+1 种基金the Innovation Group Project of the National Natural Science Foundation of China(61821003)the 111 Project on Computational Intelligence and Intelligent Control(B18024).
文摘For large-scale heterogeneous multi-agent systems(MASs)with characteristics of dense-sparse mixed distribution,this paper investigates the practical finite-time deployment problem by establishing a novel crossspecies bionic analytical framework based on the partial differential equation-ordinary differential equation(PDE-ODE)approach.Specifically,by designing a specialized network communication protocol and employing the spatial continuum method for densely distributed agents,this paper models the tracking errors of densely distributed agents as a PDE equivalent to a human disease transmission model,and that of sparsely distributed agents as several ODEs equivalent to the predator population models.The coupling relationship between the PDE and ODE models is established through boundary conditions of the PDE,thereby forming a PDE-ODE-based tracking error model for the considered MASs.Furthermore,by integrating adaptive neural control scheme with the aforementioned biological models,a“Flexible Neural Network”endowed with adaptive and self-stabilized capabilities is constructed,which acts upon the considered MASs,enabling their practical finite-time deployment.Finally,effectiveness of the developed approach is illustrated through a numerical example.
基金supported by Singapore National Medical Research Council(NMRC)grants,including CS-IRG,HLCA2022(to ZDZ),STaR,OF LCG 000207(to EKT)a Clinical Translational Research Programme in Parkinson's DiseaseDuke-Duke-NUS collaboration pilot grant(to ZDZ)。
文摘The progressive loss of dopaminergic neurons in affected patient brains is one of the pathological features of Parkinson's disease,the second most common human neurodegenerative disease.Although the detailed pathogenesis accounting for dopaminergic neuron degeneration in Parkinson's disease is still unclear,the advancement of stem cell approaches has shown promise for Parkinson's disease research and therapy.The induced pluripotent stem cells have been commonly used to generate dopaminergic neurons,which has provided valuable insights to improve our understanding of Parkinson's disease pathogenesis and contributed to anti-Parkinson's disease therapies.The current review discusses the practical approaches and potential applications of induced pluripotent stem cell techniques for generating and differentiating dopaminergic neurons from induced pluripotent stem cells.The benefits of induced pluripotent stem cell-based research are highlighted.Various dopaminergic neuron differentiation protocols from induced pluripotent stem cells are compared.The emerging three-dimension-based brain organoid models compared with conventional two-dimensional cell culture are evaluated.Finally,limitations,challenges,and future directions of induced pluripotent stem cell–based approaches are analyzed and proposed,which will be significant to the future application of induced pluripotent stem cell-related techniques for Parkinson's disease.
基金funded by Taif University,Saudi Arabia,project No.(TU-DSPP-2024-263).
文摘Deep learning algorithms have been rapidly incorporated into many different applications due to the increase in computational power and the availability of massive amounts of data.Recently,both deep learning and ensemble learning have been used to recognize underlying structures and patterns from high-level features to make predictions/decisions.With the growth in popularity of deep learning and ensemble learning algorithms,they have received significant attention from both scientists and the industrial community due to their superior ability to learn features from big data.Ensemble deep learning has exhibited significant performance in enhancing learning generalization through the use of multiple deep learning algorithms.Although ensemble deep learning has large quantities of training parameters,which results in time and space overheads,it performs much better than traditional ensemble learning.Ensemble deep learning has been successfully used in several areas,such as bioinformatics,finance,and health care.In this paper,we review and investigate recent ensemble deep learning algorithms and techniques in health care domains,medical imaging,health care data analytics,genomics,diagnosis,disease prevention,and drug discovery.We cover several widely used deep learning algorithms along with their architectures,including deep neural networks(DNNs),convolutional neural networks(CNNs),recurrent neural networks(RNNs),and generative adversarial networks(GANs).Common healthcare tasks,such as medical imaging,electronic health records,and genomics,are also demonstrated.Furthermore,in this review,the challenges inherent in reducing the burden on the healthcare system are discussed and explored.Finally,future directions and opportunities for enhancing healthcare model performance are discussed.
基金Supported by National Research Foundation of Korea,No.NRF-2021S1A5A8062526.
文摘This article provides a comprehensive analysis of the study by Hou et al,focusing on the complex interplay between psychological and physical factors in the postoperative recovery(POR)of patients with perianal diseases.The study sheds light on how illness perception,anxiety,and depression significantly influence recovery outcomes.Hou et al developed a predictive model that demonstrated high accuracy in identifying patients at risk of poor recovery.The article explores the critical role of pre-operative psychological assessment,highlighting the need for mental health support and personalized recovery plans in enhancing POR quality.A multidisciplinary approach,integrating mental health professionals with surgeons,anesthesiologists,and other specialists,is emphasized to ensure comprehensive care for patients.The study’s findings serve as a call to integrate psychological care into surgical practice to optimize outcomes for patients with perianal diseases.
基金funded by the Postgraduate Research and Practice Innovation Program of Jiangsu Province(Grant No.KYCX23_2744)the Fundamental Research Funds for the Central Universities(Grant No.2023XSCX051)the Graduate Innovation Program of China University of Mining and Technology(Grant No.2023WLKXJ182).
文摘Microwave-assisted rock-breaking technology,as a novel hybrid approach,is anticipated to facilitate the efficient excavation of complex rock formations.It is therefore crucial to understand the damage and failure mechanisms of rocks that have been subjected to irradiation.In this study,uniaxial compression experiments were conducted on granite specimens after 1.4 kW microwave irradiation for varying durations.Furthermore,a numerical method was proposed to solve electromagnetic-thermal-mechanical coupling problems by integrating finite and discrete elements.The results demonstrated a differential temperature distribution(high temperature in the middle and low-temperature areas at the ends)in the granite specimens under microwave irradiation,which resulted in a notable reduction in their physical and mechanical properties.As the duration of irradiation increased,the rate of heating and the extent of strength reduction both diminished,while the morphology and distribution of cracks at ultimate failure became increasingly complex.The numerical method effectively addresses the simulation challenges associated with the electromagnetic selective heating of granite containing multiple polar minerals under microwave irradiation.This approach accounted for the non-uniform thermal expansion of the minerals and provided a comprehensive model of damage progression under compression.
文摘Objective: To explore the effect of Health Action Process Approach (HAPA) theory in patients with type D personality psoriasis. Methods: A total of 66 patients with type D personality psoriasis admitted to the dermatology department of a top-three hospital in Jingzhou City from November 2022 to July 2023 were selected and divided into control group and test group with 33 cases in each group by random number table method. The control group received routine health education, and the experimental group received health education based on the HAPA theory. Chronic disease self-efficacy scale, hospital anxiety and depression scale and skin disease quality of life scale were used to evaluate the effect of intervention. Results: After 3 months of intervention, the scores of self-efficacy in experimental group were higher than those in control group (P P Conclusion: Health education based on the theory of HAPA can enhance the self-efficacy of patients with type D personality psoriasis, relieve negative emotions and improve their quality of life.
基金The Ministry of Education of China supported this work under the Humanities and Social Sciences Research Project for Young Scholars(Grant No.20YJC890020).
文摘Background:Social anxiety is prevalent among adolescents and severely impacts their mental health and social functioning.This study aims to explore the underlying mechanisms and subgroup differences in adolescent social anxiety to provide a theoretical basis for targeted interventions.Methods:3025 Chinese adolescents(Meanage=13.91±1.60 years;47%male)completed self-report measures of physical activity,core self-evaluation,and social anxiety.Variable-centered analyses employed PROCESS Model 4 with 5000 bootstrap samples;covariates were gender,grade,and place of residence.Person-centered analyses used latent profile analysis in Mplus 8.3 to identify subgroups based on social anxiety item profiles.Results:Variable-centered analyses showed that physical activity had a significant negative association with social anxiety(β=−0.224,p<0.001)and a significant positive association with core self-evaluation(β=0.471,p<0.001);core self-evaluation partially mediated this relationship,accounting for 30%of the total effect.Person-centered analyses revealed an optimal two-profile solution:a low social anxiety profile(89.6%)and a high social anxiety profile(10.4%).The high social anxiety profile reported significantly lower physical activity and lower core self-evaluation than the low social anxiety profile.Conclusions:This study integrates variable-centered and person-centered evidence,identifies physical activity and core self-evaluation as key modifiable factors in reducing social anxiety,providing a theoretical basis for targeted and differentiated interventions.
文摘BACKGROUND The root of mesentery dissection is one of the critical maneuvers,especially in borderline resectable pancreatic head cancer.Intra-abdominal chyle leak(CL)including chylous ascites may ensue in up to 10%of patients after pancreatic resections.Globally recognized superior mesenteric artery(SMA)first approaches are invariably performed.The mesenteric dissection through the inferior infracolic approach has been discussed in this study emphasizing its post-operative impact on CL which is the cornerstone of this study.AIM To assess incidence,risk factors,clinical impact of CL following root of mesentery dissection,and the different treatment modalities.METHODS This is a retrospective study incorporating the patients who underwent dissection of the root of mesentery with inferior infracolic SMA first approach pancreat-oduodenectomy for the ventral body and uncinate mass of pancreas in the Department of Gastrointestinal and General Surgery of Kathmandu Medical College and Teaching Hospital from January 1,2021 to February 28,2024.Intraop-erative findings and postoperative outcomes were analyzed.RESULTS In three years,ten patients underwent root of mesentery dissection with inferior infracolic SMA first approach pancreatoduodenectomy.The mean age was 67.6 years with a male-to-female ratio of 4:5.CL was seen in four patients.With virtue of CL,Clavien-Dindo grade Ⅱ or higher morbidity was observed in four patients.Two patients had a hospital stay of more than 20 days with the former having a delayed gastric emptying and the latter with long-term total parenteral nutrition requirement.The mean operative time was 330 minutes.Curative resection was achieved in 100%of the patients.The mean duration of the intensive care unit and hospital stay were 2.55±1.45 days and 15.7±5.32 days,respectively.CONCLUSION Root of mesentery dissection with lymphadenectomy and vascular resection correlated with occurrence of CL.After complete curative resection,these were managed with total parenteral nutrition without adversely impacting outcome.
