Regarding the special potential of ports located on international coastlines such as Makoran Sea (Iran) for goods and human smuggling, national level of coastline security is very important. They can play a significan...Regarding the special potential of ports located on international coastlines such as Makoran Sea (Iran) for goods and human smuggling, national level of coastline security is very important. They can play a significant role in the development of power and security. Based on military reviews and analyses, police location and monitoring field view in the coastlines are strategic issues in modern security development. This research proposes a tool for development of coastal roads and coastal walking routes in the deployment of police. The main focuses are monitoring field view and accessibility to the strategic coastline. GIS tool plays an essential role in producing important security maps. Chabahar Port in Iran, as the most important port of Makoran Sea, has been selected as the study area, regarding its strategic role in the national economy and security. Research method focused on these major axes: successful establishment of police stations in shoreline for increasing monitoring and coastal security and suitable patrol of patrol police car in the coastal roads. This study adopts a scientific approach to the analysis of the present and future development in urban and security planning in coastal towns in the national and regional levels.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
Concerning about the rapid urban growth in recent China, this study takes Beijing as a case and puts forward that urban sprawl can be measured from spatial configuration, urban growth efficiency and external impacts, ...Concerning about the rapid urban growth in recent China, this study takes Beijing as a case and puts forward that urban sprawl can be measured from spatial configuration, urban growth efficiency and external impacts, and then develops a geo-spatial indices system for measuring sprawl, a total of 13 indicators. In order to calculate these indices, different sources data are selected, including land use maps, former land use planning, land price and floor-area-ratio samples, digitized map of the highways and city centers, population and GDP statistical data, etc. Various GIS spatial analysis methods are used to spatialize these indices into 100mx100m cells. Besides, an integrated urban sprawl index is calculated by weight sum of these 13 indices. The application result indicates that geo-spatial indices system can capture most of the typical features and interior differentia of urban sprawl. Construction land in Beijing has kept fast growing with large amount, low efficiency and disordered spatial configuration, indicating a typical sprawling tendency. The following specific sprawl features are identified by each indicator： （1） typical spatial configuration of sprawling： obvious fragmentation and irregularity of landscape due to unsuccessful enforcement of land use planning, unadvisable pattern of typical discontinuous development, strip development and leapfrog development; （2） low efficiency of sprawl： low development density, low population density and economic output in newly developed area; and （3） negative impacts on agriculture, environment and city life. According to the integrated sprawl index, the sprawling amount in the northern part is larger than that in the southern, but the sprawling extent is in converse case; most sprawling area include the marginal area of the near suburbs and the area between highways, etc. Four sprawling patterns are identified： randomly expansion at urban fringe, strip development along or between highways, scattered development of industrial land, leapfrog development of urban residence and industrial area.展开更多
The paper presents a set of techniques of digital watermarking by which copyright and user rights messages are hidden into geo-spatial graphics data,as well as techniques of compressing and encrypting the watermarked ...The paper presents a set of techniques of digital watermarking by which copyright and user rights messages are hidden into geo-spatial graphics data,as well as techniques of compressing and encrypting the watermarked geo-spatial graphics data.The technology aims at tracing and resisting the illegal distribution and duplication of the geo-spatial graphics data product,so as to effectively protect the data producer＇s rights as well as to facilitate the secure sharing of geo-spatial graphics data.So far in the CIS field throughout the world,few researches have been made on digital watermarking.The research is a novel exploration both in the field of security management of geo-spatial graphics data and in the applications of digital watermarking technique.An application software employing the proposed technology has been developed.A number of experimental tests on the 1：500,000 digital bathymetric chart of the South China Sea and 1：10,000 digital topographic map of Jiangsu Province have been conducted to verify the feasibility of the proposed technology.展开更多
China' Mainland has a poor distribution of meteorological stations.Existing models’estimation accuracy for creating high-resolution surfaces of meteorological data is restricted for air temperature,and low for re...China' Mainland has a poor distribution of meteorological stations.Existing models’estimation accuracy for creating high-resolution surfaces of meteorological data is restricted for air temperature,and low for relative humidity and wind speed(few studies reported).This study compared the typical generalized additive model(GAM)and autoencoder-based residual neural network(hereafter,residual network for short)in terms of predicting three meteorological parameters,namely air temperature,relative humidity,and wind speed,using data from 824 monitoring stations across China’s mainland in 2015.The performance of the two models was assessed using a 10-fold cross-validation procedure.The air temperature models employ basic variables such as latitude,longitude,elevation,and the day of the year.The relative humidity models employ air temperature and ozone concentration as covariates,while the wind speed models use wind speed coarse-resolution reanalysis data as covariates,in addition to the fundamental variables.Spatial coordinates represent spatial variation,while the time index of the day captures time variation in our spatiotemporal models.In comparison to GAM,the residual network considerably improved prediction accuracy:on average,the coefficient of variation(CV)R2 of the three meteorological parameters rose by 0.21,CV root-mean square(RMSE)fell by 37%,and the relative humidity model improved the most.The accuracy of relative humidity models was considerably improved once the monthly index was included,demonstrating that varied amounts of temporal variables are crucial for relative humidity models.We also spoke about the benefits and drawbacks of using coarse resolution reanalysis data and closest neighbor values as variables.In comparison to classic GAMs,this study indicates that the residual network model may considerably increase the accuracy of national high spatial(1 km)and temporal(daily)resolution meteorological data.Our findings have implications for high-resolution and high-accuracy meteorological parameter mapping in China.展开更多
Tourism is a rapidly growing investment point in Sri Lanka, where huge investment is takeing place. Even though the investment is very massive, the planning, development, and marketing are key components of success in...Tourism is a rapidly growing investment point in Sri Lanka, where huge investment is takeing place. Even though the investment is very massive, the planning, development, and marketing are key components of success in tourism zone enhancement. The main objective of this study was to implement a geo-spatial information system for development of tourism in Kandy district. Primary data collection methods i.e. questionnaire survey, interviews, focus group interviews, and observations were employed for data collection. Google maps with Google API standards which are specially designed for developers and computer programmers were used for implementation of the system. System requirements were identified by interviewing tourists and observations made on tourist sites. Proximity analysis, spatial joint, and network analysis with Google direction application program interface （API） and Google place API were used to analyze data. The study highlights the potential tourist attractions and the accessibility and other required details through a web output. Issues and challenges faced by travelers are mainly lack of specific location information, public transport schedules, and reliable tourist attraction information. Online geo-spatial information system created in this study provides a guide for tourists to fred the destination routes, the service areas, and all necessary details on particular destinations.展开更多
In integrating geo-spatial datasets, sometimes layers are unable to perfectly overlay each other. In most cases, the cause of misalignment is the cartographic variation of objects forming features in the datasets. Eit...In integrating geo-spatial datasets, sometimes layers are unable to perfectly overlay each other. In most cases, the cause of misalignment is the cartographic variation of objects forming features in the datasets. Either this could be due to actual changes on ground, collection, or storage approaches used leading to overlapping or openings between features. In this paper, we present an alignment method that uses adjustment algorithms to update the geometry of features within a dataset or complementary adjacent datasets so that they can align to achieve perfect integration. The method identifies every unique spatial instance in datasets and their spatial points that define all their geometry;the differences are compared and used to compute the alignment parameters. This provides a uniform geo-spatial features’ alignment taking into consideration changes in the different datasets being integrated without affecting the topology and attributes.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
文摘Regarding the special potential of ports located on international coastlines such as Makoran Sea (Iran) for goods and human smuggling, national level of coastline security is very important. They can play a significant role in the development of power and security. Based on military reviews and analyses, police location and monitoring field view in the coastlines are strategic issues in modern security development. This research proposes a tool for development of coastal roads and coastal walking routes in the deployment of police. The main focuses are monitoring field view and accessibility to the strategic coastline. GIS tool plays an essential role in producing important security maps. Chabahar Port in Iran, as the most important port of Makoran Sea, has been selected as the study area, regarding its strategic role in the national economy and security. Research method focused on these major axes: successful establishment of police stations in shoreline for increasing monitoring and coastal security and suitable patrol of patrol police car in the coastal roads. This study adopts a scientific approach to the analysis of the present and future development in urban and security planning in coastal towns in the national and regional levels.
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.
基金National Natural Science Foundation of China, No.40571056 Sustentation Fund on Doctoral Thesis from Beijing Science and Technology Committee, No.ZZ0608
文摘Concerning about the rapid urban growth in recent China, this study takes Beijing as a case and puts forward that urban sprawl can be measured from spatial configuration, urban growth efficiency and external impacts, and then develops a geo-spatial indices system for measuring sprawl, a total of 13 indicators. In order to calculate these indices, different sources data are selected, including land use maps, former land use planning, land price and floor-area-ratio samples, digitized map of the highways and city centers, population and GDP statistical data, etc. Various GIS spatial analysis methods are used to spatialize these indices into 100mx100m cells. Besides, an integrated urban sprawl index is calculated by weight sum of these 13 indices. The application result indicates that geo-spatial indices system can capture most of the typical features and interior differentia of urban sprawl. Construction land in Beijing has kept fast growing with large amount, low efficiency and disordered spatial configuration, indicating a typical sprawling tendency. The following specific sprawl features are identified by each indicator： （1） typical spatial configuration of sprawling： obvious fragmentation and irregularity of landscape due to unsuccessful enforcement of land use planning, unadvisable pattern of typical discontinuous development, strip development and leapfrog development; （2） low efficiency of sprawl： low development density, low population density and economic output in newly developed area; and （3） negative impacts on agriculture, environment and city life. According to the integrated sprawl index, the sprawling amount in the northern part is larger than that in the southern, but the sprawling extent is in converse case; most sprawling area include the marginal area of the near suburbs and the area between highways, etc. Four sprawling patterns are identified： randomly expansion at urban fringe, strip development along or between highways, scattered development of industrial land, leapfrog development of urban residence and industrial area.
基金Under the auspices of Jiangsu Provincial Science and Technology Fundation of Surveying and Mapping (No. 200416 )
文摘The paper presents a set of techniques of digital watermarking by which copyright and user rights messages are hidden into geo-spatial graphics data,as well as techniques of compressing and encrypting the watermarked geo-spatial graphics data.The technology aims at tracing and resisting the illegal distribution and duplication of the geo-spatial graphics data product,so as to effectively protect the data producer＇s rights as well as to facilitate the secure sharing of geo-spatial graphics data.So far in the CIS field throughout the world,few researches have been made on digital watermarking.The research is a novel exploration both in the field of security management of geo-spatial graphics data and in the applications of digital watermarking technique.An application software employing the proposed technology has been developed.A number of experimental tests on the 1：500,000 digital bathymetric chart of the South China Sea and 1：10,000 digital topographic map of Jiangsu Province have been conducted to verify the feasibility of the proposed technology.
文摘China' Mainland has a poor distribution of meteorological stations.Existing models’estimation accuracy for creating high-resolution surfaces of meteorological data is restricted for air temperature,and low for relative humidity and wind speed(few studies reported).This study compared the typical generalized additive model(GAM)and autoencoder-based residual neural network(hereafter,residual network for short)in terms of predicting three meteorological parameters,namely air temperature,relative humidity,and wind speed,using data from 824 monitoring stations across China’s mainland in 2015.The performance of the two models was assessed using a 10-fold cross-validation procedure.The air temperature models employ basic variables such as latitude,longitude,elevation,and the day of the year.The relative humidity models employ air temperature and ozone concentration as covariates,while the wind speed models use wind speed coarse-resolution reanalysis data as covariates,in addition to the fundamental variables.Spatial coordinates represent spatial variation,while the time index of the day captures time variation in our spatiotemporal models.In comparison to GAM,the residual network considerably improved prediction accuracy:on average,the coefficient of variation(CV)R2 of the three meteorological parameters rose by 0.21,CV root-mean square(RMSE)fell by 37%,and the relative humidity model improved the most.The accuracy of relative humidity models was considerably improved once the monthly index was included,demonstrating that varied amounts of temporal variables are crucial for relative humidity models.We also spoke about the benefits and drawbacks of using coarse resolution reanalysis data and closest neighbor values as variables.In comparison to classic GAMs,this study indicates that the residual network model may considerably increase the accuracy of national high spatial(1 km)and temporal(daily)resolution meteorological data.Our findings have implications for high-resolution and high-accuracy meteorological parameter mapping in China.
文摘Tourism is a rapidly growing investment point in Sri Lanka, where huge investment is takeing place. Even though the investment is very massive, the planning, development, and marketing are key components of success in tourism zone enhancement. The main objective of this study was to implement a geo-spatial information system for development of tourism in Kandy district. Primary data collection methods i.e. questionnaire survey, interviews, focus group interviews, and observations were employed for data collection. Google maps with Google API standards which are specially designed for developers and computer programmers were used for implementation of the system. System requirements were identified by interviewing tourists and observations made on tourist sites. Proximity analysis, spatial joint, and network analysis with Google direction application program interface （API） and Google place API were used to analyze data. The study highlights the potential tourist attractions and the accessibility and other required details through a web output. Issues and challenges faced by travelers are mainly lack of specific location information, public transport schedules, and reliable tourist attraction information. Online geo-spatial information system created in this study provides a guide for tourists to fred the destination routes, the service areas, and all necessary details on particular destinations.
文摘In integrating geo-spatial datasets, sometimes layers are unable to perfectly overlay each other. In most cases, the cause of misalignment is the cartographic variation of objects forming features in the datasets. Either this could be due to actual changes on ground, collection, or storage approaches used leading to overlapping or openings between features. In this paper, we present an alignment method that uses adjustment algorithms to update the geometry of features within a dataset or complementary adjacent datasets so that they can align to achieve perfect integration. The method identifies every unique spatial instance in datasets and their spatial points that define all their geometry;the differences are compared and used to compute the alignment parameters. This provides a uniform geo-spatial features’ alignment taking into consideration changes in the different datasets being integrated without affecting the topology and attributes.
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.
