In order to take into account the uncertainties linked to the variables in the evaluation of the statistical properties of structural response, a reliability approach with probabilistic aspect was considered. This is ...In order to take into account the uncertainties linked to the variables in the evaluation of the statistical properties of structural response, a reliability approach with probabilistic aspect was considered. This is called the Probabilistic Transformation Method (PTM). This method is readily applicable when the function between the input and the output of the system is explicit. However, the situation is much more involved when it is necessary to perform the evaluation of implicit function between the input and the output of the system through numerical models. In this work, we propose a technique that combines Finite Element Analysis (FEA) and Probabilistic Transformation Method (PTM) to evaluate the Probability Density Function (PDF) of response where the function between the input and the output of the system is implicit. This technique is based on the numerical simulations of the Finite Element Analysis (FEA) and the Probabilistic Transformation Method (PTM) using an interface between Finite Element software and Matlab. Some problems of structures are treated in order to prove the applicability of the proposed technique. Moreover, the obtained results are compared to those obtained by the reference method of Monte Carlo. A second aim of this work is to develop an algorithm of global optimization using the local method SQP, because of its effectiveness and its rapidity of convergence. For this reason, we have combined the method SQP with the Multi start method. This developed algorithm is tested on test functions comparing with other methods such as the method of Particle Swarm Optimization (PSO). In order to test the applicability of the proposed approach, a structure is optimized under reliability constraints.展开更多
The wireless signals emitted by base stations serve as a vital link connecting people in today’s society and have been occupying an increasingly important role in real life.The development of the Internet of Things(I...The wireless signals emitted by base stations serve as a vital link connecting people in today’s society and have been occupying an increasingly important role in real life.The development of the Internet of Things(IoT)relies on the support of base stations,which provide a solid foundation for achieving a more intelligent way of living.In a specific area,achieving higher signal coverage with fewer base stations has become an urgent problem.Therefore,this article focuses on the effective coverage area of base station signals and proposes a novel Evolutionary Particle Swarm Optimization(EPSO)algorithm based on collective prediction,referred to herein as ECPPSO.Introducing a new strategy called neighbor-based evolution prediction(NEP)addresses the issue of premature convergence often encountered by PSO.ECPPSO also employs a strengthening evolution(SE)strategy to enhance the algorithm’s global search capability and efficiency,ensuring enhanced robustness and a faster convergence speed when solving complex optimization problems.To better adapt to the actual communication needs of base stations,this article conducts simulation experiments by changing the number of base stations.The experimental results demonstrate thatunder the conditionof 50 ormore base stations,ECPPSOconsistently achieves the best coverage rate exceeding 95%,peaking at 99.4400%when the number of base stations reaches 80.These results validate the optimization capability of the ECPPSO algorithm,proving its feasibility and effectiveness.Further ablative experiments and comparisons with other algorithms highlight the advantages of ECPPSO.展开更多
Major solar plasma disturbances are subjected to Lomb-Scargle periodogram and wavelet analysis to determine the occurrence frequency.These disruptions include interplanetary coronal mass ejection,sudden storm commence...Major solar plasma disturbances are subjected to Lomb-Scargle periodogram and wavelet analysis to determine the occurrence frequency.These disruptions include interplanetary coronal mass ejection,sudden storm commencement,high-speed streams,corotating interaction regions,interplanetary shocks and Forbush decreases.We included information on all of the aforementioned solar disturbances for the last six solar cycles,from 1965 to 2023,for this study.Our findings reveal some intriguing and noteworthy results that clearly distinguish between even and odd-numbered solar cycles.The study suggests that the Sun behaves differently in odd and even-numbered solar cycles as it comes from the massive solar eruptions.During even-numbered solar cycles,variations with a period of∼44 days are prominently observed in addition to solar rotation(∼27 days)and extended solar(∼36 days)rotation.However,in addition to solar rotation,prolonged solar rotation,and periods of around 44 days,we also detect a number of intermittent changes with nearly comparable amplitude during the oddnumbered solar cycles.The findings also demonstrate that,in contrast to odd-numbered solar cycles,the emissions rate of these disruptions is more distinct and predictable during even-numbered solar cycles.展开更多
Performance evaluation,as a multidimensional and comprehensive assessment tool,plays a pivotal role in accurately reflecting the quality of higher education and effectively promoting institutional governance.In the ev...Performance evaluation,as a multidimensional and comprehensive assessment tool,plays a pivotal role in accurately reflecting the quality of higher education and effectively promoting institutional governance.In the evolving landscape of educational reform,nonprofit private universities in China face pressing challenges in leveraging performance evaluations to standardize internal operations,guide strategic development,and foster public trust.This paper focuses on these institutions and conducts an in-depth analysis of existing problems in performance evaluation practices.Drawing on contemporary theoretical frameworks and empirical experiences,it proposes feasible,targeted governance strategies.The aim is to offer both theoretical insights and practical guidelines to support the sustainable development of non-profit private universities and to help these institutions better integrate into the national education system while fulfilling their social missions.展开更多
In this paper, a bearing-based three-dimensional self-localization and distributed circumnavigation with connectivity preservation and collision avoidance are investigated for a group of quadrotor-type unmanned aerial...In this paper, a bearing-based three-dimensional self-localization and distributed circumnavigation with connectivity preservation and collision avoidance are investigated for a group of quadrotor-type unmanned aerial vehicles (UAVs). A leader–follower structure is adopted, wherein the leader moves with reference dynamics (a target). Different from the existing approaches that necessitate full knowledge of the time-varying reference trajectory, in this paper, it is assumed that only some vehicles (at least one) have access to the bearing relative to the target, and all other vehicles are equipped with sensors capable of measuring the bearings relative to neighboring vehicles. In this paper, a consensus estimator is proposed to estimate the global position for each vehicle using relative bearing measurements and an estimate of neighboring vehicles received from a direct communication network. Then, a continuous robust integral of the sign of the error (RISE) control approach is effectively integrated with the distributed vector field approach to ensure UAV formation orbiting around the moving target while avoiding obstacles and maintaining network links within available communication ranges. In contrast to the classical RISE control rule, a \(\tanh (\cdot )\) function is used instead of the \(\text {sgn}(\cdot )\) function to further decrease the high-gain feedback and to obtain a smoother control signal. Furthermore, by using the localized radial basis function (RBF) neural networks (NNs) in a cooperative way, deterministic learning theory is employed to accurately identify/learn model uncertainties resulting from the attitude dynamics. The convergence of the entire closed-loop system is illustrated using the Lyapunov theory and is shown to be uniformly ultimately bounded. Finally, numerical simulations show the effectiveness of the proposed approach.展开更多
Under the background of the Healthy China strategy,the construction of teaching cases in the field of medical care and health is of great significance.This paper systematically analyzes the urgency,feasibility,challen...Under the background of the Healthy China strategy,the construction of teaching cases in the field of medical care and health is of great significance.This paper systematically analyzes the urgency,feasibility,challenges and future development paths of the construction of teaching cases in the field of medical care and health.With the intensification of the global aging trend and the continuous growth of the number of patients with chronic diseases,the field of medical care and health urgently needs professionals with interdisciplinary knowledge and practical ability.However,the current teaching case resources are scarce and the update is lagging behind,which is difficult to meet the needs of cultivating high-quality talents.Therefore,this paper proposes to use the popularization of network technology,the diversification of multimedia technology and big data technology to broaden the channels for case collection,improve the authenticity and timeliness of cases,and establish a scientific quality assessment and update mechanism.At the same time,specific solutions are proposed for bottleneck problems such as data integration and copyright interest distribution.Looking forward to the future,by strengthening interdisciplinary cooperation and improving the practicality and pertinence of cases,it will help promote the continuous improvement of the quality of education in the field of medical care and health,and provide strong support for coping with the challenges of population aging.展开更多
BACKGROUND A recently developed method enables automated measurement of the hallux valgus angle(HVA)and the first intermetatarsal angle(IMA)from weightbearing foot radiographs.This approach employs bone segmentation t...BACKGROUND A recently developed method enables automated measurement of the hallux valgus angle(HVA)and the first intermetatarsal angle(IMA)from weightbearing foot radiographs.This approach employs bone segmentation to identify anatomical landmarks and provides standardized angle measurements based on established guidelines.While effective for HVA and IMA,preoperative radiograph analysis remains complex and requires additional measurements,such as the hallux interphalangeal angle(IPA),which has received limited research attention.AIM To expand the previous method,which measured HVA and IMA,by incorporating the automatic measurement of IPA,evaluating its accuracy and clinical relevance.METHODS A preexisting database of manually labeled foot radiographs was used to train a U-Net neural network for segmenting bones and identifying landmarks necessary for IPA measurement.Of the 265 radiographs in the dataset,161 were selected for training and 20 for validation.The U-Net neural network achieves a high mean Sørensen-Dice index(>0.97).The remaining 84 radiographs were used to assess the reliability of automated IPA measurements against those taken manually by two orthopedic surgeons(OA and OB)using computer-based tools.Each measurement was repeated to assess intraobserver(OA1 and OA2)and interobserver(O_(A2) and O_(B))reliability.Agreement between automated and manual methods was evaluated using the Intraclass Correlation Coefficient(ICC),and Bland-Altman analysis identified systematic differences.Standard error of measurement(SEM)and Pearson correlation coefficients quantified precision and linearity,and measurement times were recorded to evaluate efficiency.RESULTS The artificial intelligence(AI)-based system demonstrated excellent reliability,with ICC3.1 values of 0.92(AI vs OA2)and 0.88(AI vs O_(B)),both statistically significant(P<0.001).For manual measurements,ICC values were 0.95(OA2 vs OA1)and 0.95(OA2 vs OB),supporting both intraobserver and interobserver reliability.Bland-Altman analysis revealed minimal biases of:(1)1.61°(AI vs O_(A2));and(2)2.54°(AI vs O_(B)),with clinically acceptable limits of agreement.The AI system also showed high precision,as evidenced by low SEM values:(1)1.22°(O_(A2) vs O_(B));(2)1.77°(AI vs O_(A2));and(3)2.09°(AI vs O_(B)).Furthermore,Pearson correlation coefficients confirmed strong linear relationships between automated and manual measurements,with r=0.85(AI vs O_(A2))and r=0.90(AI vs O_(B)).The AI method significantly improved efficiency,completing all 84 measurements 8 times faster than manual methods,reducing the time required from an average 36 minutes to just 4.5 minutes.CONCLUSION The proposed AI-assisted IPA measurement method shows strong clinical potential,effectively corresponding with manual measurements.Integrating IPA with HVA and IMA assessments provides a comprehensive tool for automated forefoot deformity analysis,supporting hallux valgus severity classification and preoperative planning,while offering substantial time savings in high-volume clinical settings.展开更多
The Suizhou meteorite is a heavily shock-met-amorphosed L6 chondrite which contains thin shock melt veins.So far,26 high-pressure phases have been identified from the meteorite.Among the high-pressure phases,ten of th...The Suizhou meteorite is a heavily shock-met-amorphosed L6 chondrite which contains thin shock melt veins.So far,26 high-pressure phases have been identified from the meteorite.Among the high-pressure phases,ten of them were approved as new minerals which include tuite,xieite,wangdaodeite,chenmingite,hemleyite,poirierite,asimowite,hiroseite,elgoresyite,and ohtaniite,by the Commission on New Minerals,Nomenclature and Classification of the International Mineralogical Association.Other high-pressure phases identified from the meteorite are ahrensite,akimotoite,bridgmanite,lingunite,magnesiowüstite,majorite,majorite-pyrope_(ss),maskelynite,riesite,ringwoodite,wadsleyite,and 5 other phases including phase A,vitrified phase B and phase C,phase D(Ca-rich majorite),and partly inverted ringwoodite.The occurrence and abundance of high-pressure phases makes this meteorite the one with the richest variety of high-pressure minerals to date.展开更多
With China being gradually transformed into an open society where population can flow freely,it deserves more attention that interregional population flow will bring about the interactive growth of insurance.Based on ...With China being gradually transformed into an open society where population can flow freely,it deserves more attention that interregional population flow will bring about the interactive growth of insurance.Based on the traditional insurance growth theory,this paper focuses on the internal mechanism how interregional population flow can affect insurance growth,uses the provincial panel data from 2012 to 2015 to construct a flow spatial weighting matrix based on the interregional population flow scale,and sets up a spatial econometric model for empirical analysis.Results show that,if the population flow increases by 1 percentage point,the region's insurance industry will grow 0.0794 percentage points,and other regions'insurance will grow 0.184 percentage points,making the national insurance industry increase by 0.264 percentage points.,which is to say,the indirect effects of spatial knowledge spillover on insurance growth account for more than two thirds of the overall effects.This conclusion provides the policy enlightenment for promoting the interregional population flow,adjusting the product structure and marketing strategy in time by insurance companies,and promoting the balanced and coordinative development of the insurance industry in China.展开更多
Reconstruction of a traumatic distal femur defect remains a therapeutic challenge.Bone defect implants have been proposed to substitute the bone defect,and their biomechanical performances can be analyzed via a numeri...Reconstruction of a traumatic distal femur defect remains a therapeutic challenge.Bone defect implants have been proposed to substitute the bone defect,and their biomechanical performances can be analyzed via a numerical approach.However,the material assumptions for past computational human femur simulations were mainly homogeneous.Thus,this study aimed to design and analyze scaffolds for reconstructing the distal femur defect using a patient-specific finite element modeling technique.A three-dimensional finite element model of the human femur with accurate geometry and material distribution was developed using the finite element method and material mapping technique.An intact femur and a distal femur defect model treated with nine microstructure scaffolds and two solid scaffolds were investigated and compared under a single-leg stance loading.The results showed that the metal solid scaffold design could provide the most stable fixation for reconstructing the distal femur defect.However,the fixation stability was affected by various microstructure designs and pillar diameters.A microstructure scaffold can be designed to satisfy all the biomechanical indexes,opening up future possibilities for more stable reconstructions.A three-dimensional finite element model of the femur with real bone geometry and bone material distribution can be developed,and this patient-specific femur model can be used for studying other femoral fractures or injuries,paving the way for more comprehensive research in the field.Besides,this patient-specific finite element modeling technique can also be applied to developing other human or animal bone models,expanding the scope of biomechanical research.展开更多
The electrochemical conversion of carbon dioxide into valuable products is pivotal for maintaining the global carbon cycle and mitigating global warming.This review explores the advancements in electrochemical CO_(2) ...The electrochemical conversion of carbon dioxide into valuable products is pivotal for maintaining the global carbon cycle and mitigating global warming.This review explores the advancements in electrochemical CO_(2) conversion,particularly focusing on producing methanol,ethanol,and n-propanol using various catalysts such as metals,metal oxides,metal alloys,and metal organic frameworks.Additionally,it covers the photoelectrochemical(PEC)conversion of CO_(2) into alcohols.The primary objective is to identify efficient electrocatalysts for ethanol,methanol,and n-propanol production,prioritizing selectivity,stability,Faradaic efficiency(FE),and current density.Notable catalysts include PtxZn nanoalloys,which exhibit an FE of~81.4% for methanol production,and trimetallic Pt/Pb/Zn nanoalloys,aimed at reducing Pt costs while enhancing catalyst stability and durability.Metal oxide catalysts like thin film Cu_(2)O/CuO on nickel foam and Cu_(2)O/ZnO achieve FE values of~38% and~16.6% for methanol production,respectively.Copper-based metal-organic frameworks,such as Cu@Cu_(2)O,demonstrate an FE of~45% for methanol production.Similarly,Ag_(0.14)/Cu_(0.86) and Cu-Zn alloys exhibit FEs of~63% and~46.6%,respectively,for ethanol production.Notably,n-propanol production via Pd–Cu alloy and graphene/ZnO/Cu_(2)O yields FEs of~13.7% and~23%,respectively.Furthermore,the review discusses recent advancements in PEC reactor design,photoelectrodes,reaction mechanisms,and catalyst durability.By evaluating the efficiency of these devices in liquid fuel production,the review addresses challenges and prospects in CO_(2) conversion for obtaining various valuable products.展开更多
Objective:To Isolate,purify,characterize,and evaluate the bioaclive compounds from the sponge-derived fungus Penicillium sp.FF001 and to elucidate its structure.Methods:The fungal strain FF001 with an interesting bioa...Objective:To Isolate,purify,characterize,and evaluate the bioaclive compounds from the sponge-derived fungus Penicillium sp.FF001 and to elucidate its structure.Methods:The fungal strain FF001 with an interesting bioactivity profile was isolated from a marine Fijian sponge Melophlus sp.Based on conidiophores aggregation,conidia development and mycelia morphological characteristics,the isolate FF001 was classically identified as a Penicillium sp.The bioactive compound was identified using various spectral analysis of UV,high resolution electrospray ionization mass spectra,1H and 13C NMR spectral data.Further minimum inhibitory concentrations(MICs)assay and brine shrimp cytotoxicity assay were also carried out to evaluate the biological properties of the purified compound.Results:Bioassay guided fractionation of the EtOAc extract of a static culture of this Penicillium sp.by different chromatographic methods led the isolation of an antibacterial,anticryptococcal and cytotoxic active compound,which was identified as citrinin(1).Further,citrinin(1)is reported for its potent antibacterial activity against methicillin-resistant Staphylococcus aureus(S.aureus),rifampicin-resistant 5.aureus,wild type S.aureus and vancomycin-resistant Enterococcus faecium showed MICs of 3.90,0.97,1.95 and7.81μg/mL,respectively.Further citrinin(1)displayed significant activity against the pathogenic yeast Cryptococcus neoformans(MIC 3.90μg/mL),and exhibited cytotoxicity against brine shrimp larvae LD_(50)of 96μg/mL.Conclusions:Citrinin(1)is reported from sponge associated Penicillium sp.from this study and for its strong antibacterial activity against multi-drug resistant human pathogens including cytotoxicity against brine shrimp larvae,which indicated that sponge associated Penicillium spp.are promising sources of natural bioactive metabolites.展开更多
Leakage of oil and its derivatives into the soil can change the engineering behavior of soil as well as cause environmental disasters.Also,recovering the contaminated sites into their natural condition and making cont...Leakage of oil and its derivatives into the soil can change the engineering behavior of soil as well as cause environmental disasters.Also,recovering the contaminated sites into their natural condition and making contaminated materials as both environmentally and geotechnically suitable construction materials need the employment of remediation techniques.Bioremediation,as an efficient,low cost and environmentalfriendly approach,was used in the case of highly plastic clayey soils.To better understand the change in geotechnical properties of highly plastic fine-grained soil due to crude oil contamination and bioremediation,Atterberg limits,compaction,unconfined compression,direct shear,and consolidation tests were conducted on natural,contaminated,and bioremediated soil samples to investigate the effects of contamination and remediation on fine-grained soil properties.Oil contamination reduced maximum dry density(MDD),optimum moisture content(OMC),unconfined compressive strength(UCS),shear strength,swelling pressure,and coefficient of consolidation of soil.In addition,contamination increased the compression and swelling indices and compressibility of soil.Bioremediation reduced soil contamination by about 50%.Moreover,in comparison with contaminated soil,bioremediation reduced the MDD,UCS,swelling index,free swelling and swelling pressure of soil,and also increased OMC,shear strength,cohesion,internal friction angle,failure strain,porosity,compression index,and settlement.Microstructural analyses showed that oil contamination does not alter the soil structure in terms of chemical compounds,elements,and constituent minerals.While it decreased the specific surface area of the soil,and the bioremediation significantly increased the mentioned parameters.Bioremediation resulted in the formation of quasi-fibrous textures and porous and agglomerated structures.As a result,oil contamination affected the mechanical properties of soil negatively,but bioremediation improved these properties.展开更多
Hedgerows with intercropping systems were established at the ICIMOD test and demonstration site at Godawari to assess the effective- ness of Sloping Agricultural Land Technology （SALT） in reducing run- off water vol...Hedgerows with intercropping systems were established at the ICIMOD test and demonstration site at Godawari to assess the effective- ness of Sloping Agricultural Land Technology （SALT） in reducing run- off water volume, controlling soil loss, increasing crop production, and improving soil fertility in the mid-hills of Nepal. Runoff water volume （1996-2002）, soil loss （1996-2002） and maize yield （1995-2001）, and soil fertility-related parameters were assessed on SALT models with three factors： the type of nitrogen-fixing plant, the farmers＇ practice, and fertilizer use. Results showed a significant effect of Alnus nepalensis and/or Indigofera dosua on runoff water volume, soil loss, crop produc- tion, soil water retention, and soil nutrients （NPK）. Farmers＇ practice and fertilization did not play a significant role in reducing runoff water and soil loss. However, farmers＇ practice significantly increased crop produc- tion. Therefore, integrating soil conservation approaches on SALT sys- tems enhances stable economic output to hills and mountain farmers.展开更多
Defatted rice bran dietary fiber (DRBDF) was modified by micronization, ultrasound, microwave and extrusion cooking. We investigated the impacts of these physical treatments on the fermentation ability and bile salts ...Defatted rice bran dietary fiber (DRBDF) was modified by micronization, ultrasound, microwave and extrusion cooking. We investigated the impacts of these physical treatments on the fermentation ability and bile salts binding capacity of DRBDF. In-vitro fermentation by human fecal bacteria of modified fibers showed that the major fermentation products were propionic, acetate and butyrate acid. Fermentation of extruded fiber gave the highest amounts of propionic and acetic acid 135.76 and 25.45 mmol/L respectively, while, the fermented product with microwaved fiber had the highest butyric acid content (10.75 mmol/L). The amount of short-chain fatty acid increased from 12 h to 24 h and propionic acid was the predominant. On the other hand,in-vitrobile salts binding showed that extruded fiber had higher affinity with sodium deoxycholate and sodium chenodeoxycholate (66.14% and 30.25% respectively) while microwaved fiber exhibited the highest affinity with sodium taurocholate (14.38%). In the light of obtained results we can affirmed that these physical treatments significantly improved the fermentation products and bile salts binding capacity of DRBDF. Extrusion compared to the other physical treatment methods used in this study has greatly and positively influenced the fermentation and bile binding capacity of DRBDF.展开更多
Agriculture plays an important role in the economy of all countries.However,plant diseases may badly affect the quality of food,production,and ultimately the economy.For plant disease detection and management,agricult...Agriculture plays an important role in the economy of all countries.However,plant diseases may badly affect the quality of food,production,and ultimately the economy.For plant disease detection and management,agriculturalists spend a huge amount of money.However,the manual detection method of plant diseases is complicated and time-consuming.Consequently,automated systems for plant disease detection using machine learning(ML)approaches are proposed.However,most of the existing ML techniques of plants diseases recognition are based on handcrafted features and they rarely deal with huge amount of input data.To address the issue,this article proposes a fully automated method for plant disease detection and recognition using deep neural networks.In the proposed method,AlexNet and VGG19 CNNs are considered as pre-trained architectures.It is capable to obtain the feature extraction of the given data with fine-tuning details.After convolutional neural network feature extraction,it selects the best subset of features through the correlation coefficient and feeds them to the number of classifiers including K-Nearest Neighbor,Support Vector Machine,Probabilistic Neural Network,Fuzzy logic,and Artificial Neural Network.The validation of the proposed method is carried out on a self-collected dataset generated through the augmentation step.The achieved average accuracy of our method is more than 96%and outperforms the recent techniques.展开更多
The identification of brain tumors is multifarious work for the separation of the similar intensity pixels from their surrounding neighbours.The detection of tumors is performed with the help of automatic computing te...The identification of brain tumors is multifarious work for the separation of the similar intensity pixels from their surrounding neighbours.The detection of tumors is performed with the help of automatic computing technique as presented in the proposed work.The non-active cells in brain region are known to be benign and they will never cause the death of the patient.These non-active cells follow a uniform pattern in brain and have lower density than the surrounding pixels.The Magnetic Resonance(MR)image contrast is improved by the cost map construction technique.The deep learning algorithm for differentiating the normal brain MRI images from glioma cases is implemented in the proposed method.This technique permits to extract the linear features from the brain MR image and glioma tumors are detected based on these extracted features.Using k-mean clustering algorithm the tumor regions in glioma are classified.The proposed algorithm provides high sensitivity,specificity and tumor segmentation accuracy.展开更多
Objective:To investigate the total phenolics,flavonoids and tannins content and the in vitro antioxidant activities of methanolic extracts of six wild Mentha species which are Mentha aquatica,Mentha arvensis,Mentha pi...Objective:To investigate the total phenolics,flavonoids and tannins content and the in vitro antioxidant activities of methanolic extracts of six wild Mentha species which are Mentha aquatica,Mentha arvensis,Mentha piperita,Mentha pulegium,Mentha rotundifolia and Mentha villosa.Methods:The Folin–Ciocalteu method was used to determine the total phenols content while flavonoids were estimated according to the aluminum chloride colorimetric method.To evaluate tannins content,vanillin and HCl were added to methanolic extracts.The antioxidant potential was measured by 1,1-diphenyl-2-picrylhydrazyl radical scavenging,ferrous ion chelating and the inhibition of b-carotene bleaching assays.Results:The methanol extracts of Algerian mints were rich in phenolic compounds and exhibited powerful antioxidant activity ranging from 7.5 mg/mL to 44.66 mg/mL,which varied significantly among species.Mentha aquatica stood out with efficient antioxidant ability which was correlated to the high total phenolics content,followed by Mentha arvensis and Mentha piperita with very close values,comparing to Mentha pulegium,Mentha rotundifolia and Mentha villosa with lowest values.Conclusions:These results show that methanolic extracts of Mentha species from Algeria have a great potential of polyphenols which can be used as a natural food preservative and antioxidant source.展开更多
In this paper, we present a new sufficient condition for absolute stability of Lure system with two additive time-varying delay components. This criterion is expressed as a set of linear matrix inequalities （LMIs）, ...In this paper, we present a new sufficient condition for absolute stability of Lure system with two additive time-varying delay components. This criterion is expressed as a set of linear matrix inequalities （LMIs）, which can be readily tested by using standard numerical software. We use this new criterion to stabilize a class of nonlinear time-delay systems. Some numerical examples are given to illustrate the applicability of the results using standard numerical software.展开更多
文摘In order to take into account the uncertainties linked to the variables in the evaluation of the statistical properties of structural response, a reliability approach with probabilistic aspect was considered. This is called the Probabilistic Transformation Method (PTM). This method is readily applicable when the function between the input and the output of the system is explicit. However, the situation is much more involved when it is necessary to perform the evaluation of implicit function between the input and the output of the system through numerical models. In this work, we propose a technique that combines Finite Element Analysis (FEA) and Probabilistic Transformation Method (PTM) to evaluate the Probability Density Function (PDF) of response where the function between the input and the output of the system is implicit. This technique is based on the numerical simulations of the Finite Element Analysis (FEA) and the Probabilistic Transformation Method (PTM) using an interface between Finite Element software and Matlab. Some problems of structures are treated in order to prove the applicability of the proposed technique. Moreover, the obtained results are compared to those obtained by the reference method of Monte Carlo. A second aim of this work is to develop an algorithm of global optimization using the local method SQP, because of its effectiveness and its rapidity of convergence. For this reason, we have combined the method SQP with the Multi start method. This developed algorithm is tested on test functions comparing with other methods such as the method of Particle Swarm Optimization (PSO). In order to test the applicability of the proposed approach, a structure is optimized under reliability constraints.
基金supported by the National Natural Science Foundation of China(Nos.62272418,62102058)Basic Public Welfare Research Program of Zhejiang Province(No.LGG18E050011)the Major Open Project of Key Laboratory for Advanced Design and Intelligent Computing of the Ministry of Education under Grant ADIC2023ZD001,National Undergraduate Training Program on Innovation and Entrepreneurship(No.202410345054).
文摘The wireless signals emitted by base stations serve as a vital link connecting people in today’s society and have been occupying an increasingly important role in real life.The development of the Internet of Things(IoT)relies on the support of base stations,which provide a solid foundation for achieving a more intelligent way of living.In a specific area,achieving higher signal coverage with fewer base stations has become an urgent problem.Therefore,this article focuses on the effective coverage area of base station signals and proposes a novel Evolutionary Particle Swarm Optimization(EPSO)algorithm based on collective prediction,referred to herein as ECPPSO.Introducing a new strategy called neighbor-based evolution prediction(NEP)addresses the issue of premature convergence often encountered by PSO.ECPPSO also employs a strengthening evolution(SE)strategy to enhance the algorithm’s global search capability and efficiency,ensuring enhanced robustness and a faster convergence speed when solving complex optimization problems.To better adapt to the actual communication needs of base stations,this article conducts simulation experiments by changing the number of base stations.The experimental results demonstrate thatunder the conditionof 50 ormore base stations,ECPPSOconsistently achieves the best coverage rate exceeding 95%,peaking at 99.4400%when the number of base stations reaches 80.These results validate the optimization capability of the ECPPSO algorithm,proving its feasibility and effectiveness.Further ablative experiments and comparisons with other algorithms highlight the advantages of ECPPSO.
文摘Major solar plasma disturbances are subjected to Lomb-Scargle periodogram and wavelet analysis to determine the occurrence frequency.These disruptions include interplanetary coronal mass ejection,sudden storm commencement,high-speed streams,corotating interaction regions,interplanetary shocks and Forbush decreases.We included information on all of the aforementioned solar disturbances for the last six solar cycles,from 1965 to 2023,for this study.Our findings reveal some intriguing and noteworthy results that clearly distinguish between even and odd-numbered solar cycles.The study suggests that the Sun behaves differently in odd and even-numbered solar cycles as it comes from the massive solar eruptions.During even-numbered solar cycles,variations with a period of∼44 days are prominently observed in addition to solar rotation(∼27 days)and extended solar(∼36 days)rotation.However,in addition to solar rotation,prolonged solar rotation,and periods of around 44 days,we also detect a number of intermittent changes with nearly comparable amplitude during the oddnumbered solar cycles.The findings also demonstrate that,in contrast to odd-numbered solar cycles,the emissions rate of these disruptions is more distinct and predictable during even-numbered solar cycles.
文摘Performance evaluation,as a multidimensional and comprehensive assessment tool,plays a pivotal role in accurately reflecting the quality of higher education and effectively promoting institutional governance.In the evolving landscape of educational reform,nonprofit private universities in China face pressing challenges in leveraging performance evaluations to standardize internal operations,guide strategic development,and foster public trust.This paper focuses on these institutions and conducts an in-depth analysis of existing problems in performance evaluation practices.Drawing on contemporary theoretical frameworks and empirical experiences,it proposes feasible,targeted governance strategies.The aim is to offer both theoretical insights and practical guidelines to support the sustainable development of non-profit private universities and to help these institutions better integrate into the national education system while fulfilling their social missions.
文摘In this paper, a bearing-based three-dimensional self-localization and distributed circumnavigation with connectivity preservation and collision avoidance are investigated for a group of quadrotor-type unmanned aerial vehicles (UAVs). A leader–follower structure is adopted, wherein the leader moves with reference dynamics (a target). Different from the existing approaches that necessitate full knowledge of the time-varying reference trajectory, in this paper, it is assumed that only some vehicles (at least one) have access to the bearing relative to the target, and all other vehicles are equipped with sensors capable of measuring the bearings relative to neighboring vehicles. In this paper, a consensus estimator is proposed to estimate the global position for each vehicle using relative bearing measurements and an estimate of neighboring vehicles received from a direct communication network. Then, a continuous robust integral of the sign of the error (RISE) control approach is effectively integrated with the distributed vector field approach to ensure UAV formation orbiting around the moving target while avoiding obstacles and maintaining network links within available communication ranges. In contrast to the classical RISE control rule, a \(\tanh (\cdot )\) function is used instead of the \(\text {sgn}(\cdot )\) function to further decrease the high-gain feedback and to obtain a smoother control signal. Furthermore, by using the localized radial basis function (RBF) neural networks (NNs) in a cooperative way, deterministic learning theory is employed to accurately identify/learn model uncertainties resulting from the attitude dynamics. The convergence of the entire closed-loop system is illustrated using the Lyapunov theory and is shown to be uniformly ultimately bounded. Finally, numerical simulations show the effectiveness of the proposed approach.
基金National Natural Science Foundation of China general project"Research on the transmission mechanism,welfare effect and path optimization of long-term care insurance embedded in rural medical and health service system(No.:72274107)","Typical case of long-term care insurance embedded in medical and health service system to promote Chinese-style modernization","Digital empowerment crossintegration-health and medical big data"course construction,"Insurance"smart course construction,"One construction and three chains"integration path under the modern financial and economic industrial college education model research,"12456"postgraduate joint training base quality improvement system construction,Shandong Province"Taishan Scholars Project",Shandong Province Youth Entrepreneurship Science and Technology Support Plan,Ministry of Education Degree Center theme case"Digital empowerment of healthy China construction:innovative practice of social security robots".
文摘Under the background of the Healthy China strategy,the construction of teaching cases in the field of medical care and health is of great significance.This paper systematically analyzes the urgency,feasibility,challenges and future development paths of the construction of teaching cases in the field of medical care and health.With the intensification of the global aging trend and the continuous growth of the number of patients with chronic diseases,the field of medical care and health urgently needs professionals with interdisciplinary knowledge and practical ability.However,the current teaching case resources are scarce and the update is lagging behind,which is difficult to meet the needs of cultivating high-quality talents.Therefore,this paper proposes to use the popularization of network technology,the diversification of multimedia technology and big data technology to broaden the channels for case collection,improve the authenticity and timeliness of cases,and establish a scientific quality assessment and update mechanism.At the same time,specific solutions are proposed for bottleneck problems such as data integration and copyright interest distribution.Looking forward to the future,by strengthening interdisciplinary cooperation and improving the practicality and pertinence of cases,it will help promote the continuous improvement of the quality of education in the field of medical care and health,and provide strong support for coping with the challenges of population aging.
文摘BACKGROUND A recently developed method enables automated measurement of the hallux valgus angle(HVA)and the first intermetatarsal angle(IMA)from weightbearing foot radiographs.This approach employs bone segmentation to identify anatomical landmarks and provides standardized angle measurements based on established guidelines.While effective for HVA and IMA,preoperative radiograph analysis remains complex and requires additional measurements,such as the hallux interphalangeal angle(IPA),which has received limited research attention.AIM To expand the previous method,which measured HVA and IMA,by incorporating the automatic measurement of IPA,evaluating its accuracy and clinical relevance.METHODS A preexisting database of manually labeled foot radiographs was used to train a U-Net neural network for segmenting bones and identifying landmarks necessary for IPA measurement.Of the 265 radiographs in the dataset,161 were selected for training and 20 for validation.The U-Net neural network achieves a high mean Sørensen-Dice index(>0.97).The remaining 84 radiographs were used to assess the reliability of automated IPA measurements against those taken manually by two orthopedic surgeons(OA and OB)using computer-based tools.Each measurement was repeated to assess intraobserver(OA1 and OA2)and interobserver(O_(A2) and O_(B))reliability.Agreement between automated and manual methods was evaluated using the Intraclass Correlation Coefficient(ICC),and Bland-Altman analysis identified systematic differences.Standard error of measurement(SEM)and Pearson correlation coefficients quantified precision and linearity,and measurement times were recorded to evaluate efficiency.RESULTS The artificial intelligence(AI)-based system demonstrated excellent reliability,with ICC3.1 values of 0.92(AI vs OA2)and 0.88(AI vs O_(B)),both statistically significant(P<0.001).For manual measurements,ICC values were 0.95(OA2 vs OA1)and 0.95(OA2 vs OB),supporting both intraobserver and interobserver reliability.Bland-Altman analysis revealed minimal biases of:(1)1.61°(AI vs O_(A2));and(2)2.54°(AI vs O_(B)),with clinically acceptable limits of agreement.The AI system also showed high precision,as evidenced by low SEM values:(1)1.22°(O_(A2) vs O_(B));(2)1.77°(AI vs O_(A2));and(3)2.09°(AI vs O_(B)).Furthermore,Pearson correlation coefficients confirmed strong linear relationships between automated and manual measurements,with r=0.85(AI vs O_(A2))and r=0.90(AI vs O_(B)).The AI method significantly improved efficiency,completing all 84 measurements 8 times faster than manual methods,reducing the time required from an average 36 minutes to just 4.5 minutes.CONCLUSION The proposed AI-assisted IPA measurement method shows strong clinical potential,effectively corresponding with manual measurements.Integrating IPA with HVA and IMA assessments provides a comprehensive tool for automated forefoot deformity analysis,supporting hallux valgus severity classification and preoperative planning,while offering substantial time savings in high-volume clinical settings.
基金Science and Technology Planning Project of Guangdong Province(2023B1212060048).
文摘The Suizhou meteorite is a heavily shock-met-amorphosed L6 chondrite which contains thin shock melt veins.So far,26 high-pressure phases have been identified from the meteorite.Among the high-pressure phases,ten of them were approved as new minerals which include tuite,xieite,wangdaodeite,chenmingite,hemleyite,poirierite,asimowite,hiroseite,elgoresyite,and ohtaniite,by the Commission on New Minerals,Nomenclature and Classification of the International Mineralogical Association.Other high-pressure phases identified from the meteorite are ahrensite,akimotoite,bridgmanite,lingunite,magnesiowüstite,majorite,majorite-pyrope_(ss),maskelynite,riesite,ringwoodite,wadsleyite,and 5 other phases including phase A,vitrified phase B and phase C,phase D(Ca-rich majorite),and partly inverted ringwoodite.The occurrence and abundance of high-pressure phases makes this meteorite the one with the richest variety of high-pressure minerals to date.
基金National Natural Science Foundation of China"Research on the transmission mechanism,welfare effect and path optimization of long-term care insurance embedded in the rural medical and health service system(No.:72274107)""Special Funds for Shandong Taishan Scholars Project(No.:tsqn202312226)"+1 种基金"Shandong Province Youth Entrepreneurship Science and Technology Support Plan for Higher Education Institutions(No.2022RW044)"Shandong University of Finance and Economics 2024 Experimental Teaching Reform Research Project(zb202401):"Research on the Construction of Health and Medical Big Data Experimental Teaching Courses","Typical Cases of Embedding Long-term Care Insurance into the Medical and Health Service System to Promote Chinese Modernization","Digital Intelligence Empowerment Cross-integration-Health and Medical Big Data"Course Construction,"Insurance"Smart Course Construction,Research on the Education Model of Modern Financial and Economic Colleges under the"One Construction and Three Chains"Integration Path,"12456"Postgraduate Joint Training Base Quality Improvement System Construction,and the Ministry of Education Degree Center Theme Case"Digital Empowerment of Healthy China Construction:Innovative Practice of Social Security Robots"Interim Results.
文摘With China being gradually transformed into an open society where population can flow freely,it deserves more attention that interregional population flow will bring about the interactive growth of insurance.Based on the traditional insurance growth theory,this paper focuses on the internal mechanism how interregional population flow can affect insurance growth,uses the provincial panel data from 2012 to 2015 to construct a flow spatial weighting matrix based on the interregional population flow scale,and sets up a spatial econometric model for empirical analysis.Results show that,if the population flow increases by 1 percentage point,the region's insurance industry will grow 0.0794 percentage points,and other regions'insurance will grow 0.184 percentage points,making the national insurance industry increase by 0.264 percentage points.,which is to say,the indirect effects of spatial knowledge spillover on insurance growth account for more than two thirds of the overall effects.This conclusion provides the policy enlightenment for promoting the interregional population flow,adjusting the product structure and marketing strategy in time by insurance companies,and promoting the balanced and coordinative development of the insurance industry in China.
基金funded by the TaipeiMedical University-National Taiwan University of Science and Technology joint research program under Grant No.TMU-NTUST-109-09.
文摘Reconstruction of a traumatic distal femur defect remains a therapeutic challenge.Bone defect implants have been proposed to substitute the bone defect,and their biomechanical performances can be analyzed via a numerical approach.However,the material assumptions for past computational human femur simulations were mainly homogeneous.Thus,this study aimed to design and analyze scaffolds for reconstructing the distal femur defect using a patient-specific finite element modeling technique.A three-dimensional finite element model of the human femur with accurate geometry and material distribution was developed using the finite element method and material mapping technique.An intact femur and a distal femur defect model treated with nine microstructure scaffolds and two solid scaffolds were investigated and compared under a single-leg stance loading.The results showed that the metal solid scaffold design could provide the most stable fixation for reconstructing the distal femur defect.However,the fixation stability was affected by various microstructure designs and pillar diameters.A microstructure scaffold can be designed to satisfy all the biomechanical indexes,opening up future possibilities for more stable reconstructions.A three-dimensional finite element model of the femur with real bone geometry and bone material distribution can be developed,and this patient-specific femur model can be used for studying other femoral fractures or injuries,paving the way for more comprehensive research in the field.Besides,this patient-specific finite element modeling technique can also be applied to developing other human or animal bone models,expanding the scope of biomechanical research.
基金the financial support from National Science Centre Poland(NCN)based on the decision number UMO-2021/43/D/ST5/00824financial support of research project supported by the program“Excellence Initiative-Research University”for the AGH University of Krakow.
文摘The electrochemical conversion of carbon dioxide into valuable products is pivotal for maintaining the global carbon cycle and mitigating global warming.This review explores the advancements in electrochemical CO_(2) conversion,particularly focusing on producing methanol,ethanol,and n-propanol using various catalysts such as metals,metal oxides,metal alloys,and metal organic frameworks.Additionally,it covers the photoelectrochemical(PEC)conversion of CO_(2) into alcohols.The primary objective is to identify efficient electrocatalysts for ethanol,methanol,and n-propanol production,prioritizing selectivity,stability,Faradaic efficiency(FE),and current density.Notable catalysts include PtxZn nanoalloys,which exhibit an FE of~81.4% for methanol production,and trimetallic Pt/Pb/Zn nanoalloys,aimed at reducing Pt costs while enhancing catalyst stability and durability.Metal oxide catalysts like thin film Cu_(2)O/CuO on nickel foam and Cu_(2)O/ZnO achieve FE values of~38% and~16.6% for methanol production,respectively.Copper-based metal-organic frameworks,such as Cu@Cu_(2)O,demonstrate an FE of~45% for methanol production.Similarly,Ag_(0.14)/Cu_(0.86) and Cu-Zn alloys exhibit FEs of~63% and~46.6%,respectively,for ethanol production.Notably,n-propanol production via Pd–Cu alloy and graphene/ZnO/Cu_(2)O yields FEs of~13.7% and~23%,respectively.Furthermore,the review discusses recent advancements in PEC reactor design,photoelectrodes,reaction mechanisms,and catalyst durability.By evaluating the efficiency of these devices in liquid fuel production,the review addresses challenges and prospects in CO_(2) conversion for obtaining various valuable products.
基金Supported by the U.S.National Institutes of Health's International Cooperative Biodiversity Groups program(Grant No.NIH ICBG U01-TW007401)
文摘Objective:To Isolate,purify,characterize,and evaluate the bioaclive compounds from the sponge-derived fungus Penicillium sp.FF001 and to elucidate its structure.Methods:The fungal strain FF001 with an interesting bioactivity profile was isolated from a marine Fijian sponge Melophlus sp.Based on conidiophores aggregation,conidia development and mycelia morphological characteristics,the isolate FF001 was classically identified as a Penicillium sp.The bioactive compound was identified using various spectral analysis of UV,high resolution electrospray ionization mass spectra,1H and 13C NMR spectral data.Further minimum inhibitory concentrations(MICs)assay and brine shrimp cytotoxicity assay were also carried out to evaluate the biological properties of the purified compound.Results:Bioassay guided fractionation of the EtOAc extract of a static culture of this Penicillium sp.by different chromatographic methods led the isolation of an antibacterial,anticryptococcal and cytotoxic active compound,which was identified as citrinin(1).Further,citrinin(1)is reported for its potent antibacterial activity against methicillin-resistant Staphylococcus aureus(S.aureus),rifampicin-resistant 5.aureus,wild type S.aureus and vancomycin-resistant Enterococcus faecium showed MICs of 3.90,0.97,1.95 and7.81μg/mL,respectively.Further citrinin(1)displayed significant activity against the pathogenic yeast Cryptococcus neoformans(MIC 3.90μg/mL),and exhibited cytotoxicity against brine shrimp larvae LD_(50)of 96μg/mL.Conclusions:Citrinin(1)is reported from sponge associated Penicillium sp.from this study and for its strong antibacterial activity against multi-drug resistant human pathogens including cytotoxicity against brine shrimp larvae,which indicated that sponge associated Penicillium spp.are promising sources of natural bioactive metabolites.
文摘Leakage of oil and its derivatives into the soil can change the engineering behavior of soil as well as cause environmental disasters.Also,recovering the contaminated sites into their natural condition and making contaminated materials as both environmentally and geotechnically suitable construction materials need the employment of remediation techniques.Bioremediation,as an efficient,low cost and environmentalfriendly approach,was used in the case of highly plastic clayey soils.To better understand the change in geotechnical properties of highly plastic fine-grained soil due to crude oil contamination and bioremediation,Atterberg limits,compaction,unconfined compression,direct shear,and consolidation tests were conducted on natural,contaminated,and bioremediated soil samples to investigate the effects of contamination and remediation on fine-grained soil properties.Oil contamination reduced maximum dry density(MDD),optimum moisture content(OMC),unconfined compressive strength(UCS),shear strength,swelling pressure,and coefficient of consolidation of soil.In addition,contamination increased the compression and swelling indices and compressibility of soil.Bioremediation reduced soil contamination by about 50%.Moreover,in comparison with contaminated soil,bioremediation reduced the MDD,UCS,swelling index,free swelling and swelling pressure of soil,and also increased OMC,shear strength,cohesion,internal friction angle,failure strain,porosity,compression index,and settlement.Microstructural analyses showed that oil contamination does not alter the soil structure in terms of chemical compounds,elements,and constituent minerals.While it decreased the specific surface area of the soil,and the bioremediation significantly increased the mentioned parameters.Bioremediation resulted in the formation of quasi-fibrous textures and porous and agglomerated structures.As a result,oil contamination affected the mechanical properties of soil negatively,but bioremediation improved these properties.
基金supported in part by the Nepal Academy of Science and Technology(NAST)
文摘Hedgerows with intercropping systems were established at the ICIMOD test and demonstration site at Godawari to assess the effective- ness of Sloping Agricultural Land Technology （SALT） in reducing run- off water volume, controlling soil loss, increasing crop production, and improving soil fertility in the mid-hills of Nepal. Runoff water volume （1996-2002）, soil loss （1996-2002） and maize yield （1995-2001）, and soil fertility-related parameters were assessed on SALT models with three factors： the type of nitrogen-fixing plant, the farmers＇ practice, and fertilizer use. Results showed a significant effect of Alnus nepalensis and/or Indigofera dosua on runoff water volume, soil loss, crop produc- tion, soil water retention, and soil nutrients （NPK）. Farmers＇ practice and fertilization did not play a significant role in reducing runoff water and soil loss. However, farmers＇ practice significantly increased crop produc- tion. Therefore, integrating soil conservation approaches on SALT sys- tems enhances stable economic output to hills and mountain farmers.
文摘Defatted rice bran dietary fiber (DRBDF) was modified by micronization, ultrasound, microwave and extrusion cooking. We investigated the impacts of these physical treatments on the fermentation ability and bile salts binding capacity of DRBDF. In-vitro fermentation by human fecal bacteria of modified fibers showed that the major fermentation products were propionic, acetate and butyrate acid. Fermentation of extruded fiber gave the highest amounts of propionic and acetic acid 135.76 and 25.45 mmol/L respectively, while, the fermented product with microwaved fiber had the highest butyric acid content (10.75 mmol/L). The amount of short-chain fatty acid increased from 12 h to 24 h and propionic acid was the predominant. On the other hand,in-vitrobile salts binding showed that extruded fiber had higher affinity with sodium deoxycholate and sodium chenodeoxycholate (66.14% and 30.25% respectively) while microwaved fiber exhibited the highest affinity with sodium taurocholate (14.38%). In the light of obtained results we can affirmed that these physical treatments significantly improved the fermentation products and bile salts binding capacity of DRBDF. Extrusion compared to the other physical treatment methods used in this study has greatly and positively influenced the fermentation and bile binding capacity of DRBDF.
基金the MSIT(Ministry of Science and ICT),Korea,under the ITRC(Information Technology Research Center)support program(IITP-2020-2016-0-00312)supervised by the IITP(Institute for Information&Communications Technology Planning&Evaluation)in part by the MSIP(Ministry of Science,ICT&Future Planning),Korea,under the National Program for Excellence in SW(2015-0-00938)supervised by the IITP(Institute for Information&communications Technology Planning&Evaluation).
文摘Agriculture plays an important role in the economy of all countries.However,plant diseases may badly affect the quality of food,production,and ultimately the economy.For plant disease detection and management,agriculturalists spend a huge amount of money.However,the manual detection method of plant diseases is complicated and time-consuming.Consequently,automated systems for plant disease detection using machine learning(ML)approaches are proposed.However,most of the existing ML techniques of plants diseases recognition are based on handcrafted features and they rarely deal with huge amount of input data.To address the issue,this article proposes a fully automated method for plant disease detection and recognition using deep neural networks.In the proposed method,AlexNet and VGG19 CNNs are considered as pre-trained architectures.It is capable to obtain the feature extraction of the given data with fine-tuning details.After convolutional neural network feature extraction,it selects the best subset of features through the correlation coefficient and feeds them to the number of classifiers including K-Nearest Neighbor,Support Vector Machine,Probabilistic Neural Network,Fuzzy logic,and Artificial Neural Network.The validation of the proposed method is carried out on a self-collected dataset generated through the augmentation step.The achieved average accuracy of our method is more than 96%and outperforms the recent techniques.
文摘The identification of brain tumors is multifarious work for the separation of the similar intensity pixels from their surrounding neighbours.The detection of tumors is performed with the help of automatic computing technique as presented in the proposed work.The non-active cells in brain region are known to be benign and they will never cause the death of the patient.These non-active cells follow a uniform pattern in brain and have lower density than the surrounding pixels.The Magnetic Resonance(MR)image contrast is improved by the cost map construction technique.The deep learning algorithm for differentiating the normal brain MRI images from glioma cases is implemented in the proposed method.This technique permits to extract the linear features from the brain MR image and glioma tumors are detected based on these extracted features.Using k-mean clustering algorithm the tumor regions in glioma are classified.The proposed algorithm provides high sensitivity,specificity and tumor segmentation accuracy.
基金Supported by Ministry of Higher Education Scientific Research and Technology,Algeria(Grant No.F03120130013/2014)
文摘Objective:To investigate the total phenolics,flavonoids and tannins content and the in vitro antioxidant activities of methanolic extracts of six wild Mentha species which are Mentha aquatica,Mentha arvensis,Mentha piperita,Mentha pulegium,Mentha rotundifolia and Mentha villosa.Methods:The Folin–Ciocalteu method was used to determine the total phenols content while flavonoids were estimated according to the aluminum chloride colorimetric method.To evaluate tannins content,vanillin and HCl were added to methanolic extracts.The antioxidant potential was measured by 1,1-diphenyl-2-picrylhydrazyl radical scavenging,ferrous ion chelating and the inhibition of b-carotene bleaching assays.Results:The methanol extracts of Algerian mints were rich in phenolic compounds and exhibited powerful antioxidant activity ranging from 7.5 mg/mL to 44.66 mg/mL,which varied significantly among species.Mentha aquatica stood out with efficient antioxidant ability which was correlated to the high total phenolics content,followed by Mentha arvensis and Mentha piperita with very close values,comparing to Mentha pulegium,Mentha rotundifolia and Mentha villosa with lowest values.Conclusions:These results show that methanolic extracts of Mentha species from Algeria have a great potential of polyphenols which can be used as a natural food preservative and antioxidant source.
文摘In this paper, we present a new sufficient condition for absolute stability of Lure system with two additive time-varying delay components. This criterion is expressed as a set of linear matrix inequalities （LMIs）, which can be readily tested by using standard numerical software. We use this new criterion to stabilize a class of nonlinear time-delay systems. Some numerical examples are given to illustrate the applicability of the results using standard numerical software.
