Through several waves of technological research and un‐matched innovation strategies,bio‐catalysis has been widely used at the industrial level.Because of the value of enzymes,methods for producing value‐added comp...Through several waves of technological research and un‐matched innovation strategies,bio‐catalysis has been widely used at the industrial level.Because of the value of enzymes,methods for producing value‐added compounds and industrially‐relevant fine chemicals through biological methods have been developed.A broad spectrum of numerous biochemical pathways is catalyzed by enzymes,including enzymes that have not been identified.However,low catalytic efficacy,low stability,inhibition by non‐cognate substrates,and intolerance to the harsh reaction conditions required for some chemical processes are considered as major limitations in applied bio‐catalysis.Thus,the development of green catalysts with multi‐catalytic features along with higher efficacy and induced stability are important for bio‐catalysis.Implementation of computational science with metabolic engineering,synthetic biology,and machine learning routes offers novel alternatives for engineering novel catalysts.Here,we describe the role of synthetic biology and metabolic engineering in catalysis.Machine learning algorithms for catalysis and the choice of an algorithm for predicting protein‐ligand interactions are discussed.The importance of molecular docking in predicting binding and catalytic functions is reviewed.Finally,we describe future challenges and perspectives.展开更多
This study investigated the impact of wheatgrass powder(WGP)as a functional ingredient in steamed bread from the nutritional and techno-functional perspective.The addition of WGP significantly enhanced the antioxidant...This study investigated the impact of wheatgrass powder(WGP)as a functional ingredient in steamed bread from the nutritional and techno-functional perspective.The addition of WGP significantly enhanced the antioxidant capacity in a dose-dependent manner,attributed to its bioactive compounds,though thermal processing led to a reduction due to heat sensitivity.Physicochemical analysis revealed that WGP enrichment decreased moisture content(34.27% and 33.82% for 2.5%and 5.0%WGP vs.38.37% for control)and increased weight loss(1.45% and 1.52% for 2.5%and 5.0% WGP vs.1.27% for control),likely due to fiber-gluten competition for water,while water absorption capacity(WAC)improved with higher WGP levels(1.60 g/g and 1.92 g/g for 2.5% and 5.0% WGP vs.1.40 g/g for control).The microstructural analysis demonstrated that WGP disrupted the glutenstarch matrix,increasing porosity and reducing starch gelatinization,correlating with altered textural properties.Notably,WGP extended microbial shelf life by 48–72 h(delaying mold growth to 3–4 d vs.2 d in control),likely due to its anti-microbial bioactive constituents.Sensory evaluation indicated that WGP-enriched steamed bread achieved optimal consumer acceptance.These findings suggest that WGP is a promising functional ingredient for improving the nutritional and sensory quality of steamed bread,though optimizing processing conditions is crucial to mitigate the thermal degradation of antioxidants.展开更多
Presently,many asphalts and modified asphalts fail to satisfy long-term serviceability and durability criteria.Researchers are utilizing several asphalt modifiers to enhance the overall performance of flexible pavemen...Presently,many asphalts and modified asphalts fail to satisfy long-term serviceability and durability criteria.Researchers are utilizing several asphalt modifiers to enhance the overall performance of flexible pavements.This study consolidated findings from multiple research efforts on using nanomaterials for modifying SBS modified asphalt(SBS MA)and conducted a comprehensive literature review.Initially,it discussed the importance of SBS MA within asphalt modification systems and identified the key nanomaterials utilized in SBS modified asphalt.After this,it reviewed their preparation methods,dispersion and characterization techniques,and their impact on the key performance parameters of SBS MA binder and its mixture such as viscosity,rutting resistance,fatigue resistance,ageing and moisture damage etc.Additionally,it highlighted the advantages of nanomaterials over other modifiers.This study also addressed the challenges and limitations of incorporating nanomaterials in SBS MA.The findings indicated that when properly integrated,nanomaterials could significantly improve the performance of SBS MA,making them a promising addition to future road construction and maintenance projects.However,using nanomaterials for SBS MA modifications and mixtures has been challenged by limited practical applications,insufficient life cycle cost analyses,a lack of standardized guidelines,cost-effective nanomaterials and insufficient mixing procedures.Those areas require additional research to realise the potential application of nanomaterials in SBS modified asphalt modifications full.展开更多
Increasing reliance on large-scale AI models has led to rising demand for intelligent services.The centralized cloud computing approach has limitations in terms of data transfer efficiency and response time,and as a r...Increasing reliance on large-scale AI models has led to rising demand for intelligent services.The centralized cloud computing approach has limitations in terms of data transfer efficiency and response time,and as a result many service providers have begun to deploy edge servers to cache intelligent services in order to reduce transmission delay and communication energy consumption.However,finding the optimal service caching strategy remains a significant challenge due to the stochastic nature of service requests and the bulky nature of intelligent services.To deal with this,we propose a distributed service caching scheme integrating deep reinforcement learning(DRL)with mobility prediction,which we refer to as DSDM.Specifically,we employ the D3QN(Deep Double Dueling Q-Network)framework to integrate Long Short-Term Memory(LSTM)predicted mobile device locations into the service caching replacement algorithm and adopt the distributed multi-agent approach for learning and training.Experimental results demonstrate that DSDM achieves significant performance improvements in reducing communication energy consumption compared to traditional methods across various scenarios.展开更多
Experimental and computational fluid dynamics (CFD) are investigated through the vortex tube system. The benefit of vortex tube is a counter flow type tube, which has further designed and fabricated for investigation....Experimental and computational fluid dynamics (CFD) are investigated through the vortex tube system. The benefit of vortex tube is a counter flow type tube, which has further designed and fabricated for investigation. The whole set up is consisting of a simple device that can separate a single stream of compressed air into two streams;one is at high temperature and the other is lower temperature following an inlet gas stream. The advantages of this tube are their compactness, safety, and low equipment cost mainly used in cooling and heating applications. This study addressed three-dimensional flows;the domain is using computational fluid dynamics (CFD) method and experimental approach to optimize the direction of RHVT. Through the CFD analysis, the best cold end diameter (dc), number of nozzles, and the best parameters for obtaining the highest hot gas temperature and lowest cold gas temperature were obtained and verified by experimental procedures.展开更多
The Far North Region of Cameroon is home to a great diversity of bird species, which unfortunately remains very little explored. This work was initiated to establish an inventory of birds and the factors affecting the...The Far North Region of Cameroon is home to a great diversity of bird species, which unfortunately remains very little explored. This work was initiated to establish an inventory of birds and the factors affecting their diversity and distribution for sustainable management in the Kalfou Forest Reserve (KFR) and its periphery. Two methods were used for sampling, linear strip transects from which direct counts and indirect observations were made and the mist netting to complement the first. In total, 2525 birds were observed, including 149 species, belonging to 20 orders and 55 families. Accipitridae had the greatest number of species (11). The species richness was greater in the KFR (117 species) compared to the periphery (95 species). The specific richness was higher in wooded savannah compared to other habitats. Shannon index was significantly higher in the KFR (3.99) compared to that obtained in the periphery (3.80). The value of the Simpson index was higher on the outskirts of the KFR than on the periphery. The indices of species diversity were greater in the wooded savannah compared to other vegetation types. The seasons had no influence on bird diversity. Among the human activities encountered, the pressure indices were more important for grazing (7.3 contacts/km). Human activities have resulted in a significant decrease in specific richness. Six endangered species were encountered, four belonging to the Accipitridae family. The greater bird diversity in the reserve compared to the periphery shows that protected areas are a long-term solution for biodiversity conservation.展开更多
Hijama is an alternative mode of treatment also known as cupping therapy. It involves removal of subcutaneous stagnant blood through suction cups after making superficial incisions at particular area of the body. This...Hijama is an alternative mode of treatment also known as cupping therapy. It involves removal of subcutaneous stagnant blood through suction cups after making superficial incisions at particular area of the body. This study was undertaken to evaluate the efficacy of hijama in sciatica pain at Aligarh Shifa hospital. 92 patients with the history of sciatica were selected randomly between 18 - 75 years of age and hijama cups were applied generally at C7, T2 and L5/S1 vertebrae, while two cups were also applied bilaterally on L4/L5 vertebrae, four cups were additionally applied on hip joint, back of thigh, knee and calf muscle, all cups were applied thrice at an interval of 15 days between each session. The decrease in sciatic pain was assessed after three sessions of Hijama by numeric pain rating scale there was overall significant reduction in pain with 67 percent patients showing relief in pain up to varying degree. Present study suggests that hijama has been found to be effective in relieving pain and improving quality of life in majority of the patient’s, hence may be used as effective alternative tool to alleviate pain.展开更多
Accurate sales forecasting is essential in the fast-paced world of business for effective strategic planning and resource allocation. However, traditional forecasting methods often lack precision and flexibility. This...Accurate sales forecasting is essential in the fast-paced world of business for effective strategic planning and resource allocation. However, traditional forecasting methods often lack precision and flexibility. This study aims to address this issue by incorporating machine learning (ML) techniques to improve forecasting accuracy and responsiveness to market changes. The methodology involves gathering extensive sales data and carefully preprocessing it to ensure quality. Various ML algorithms, such as time series analysis, regression models, and neural networks, are utilized to account for the complex and non-linear nature of sales patterns. These models are trained and validated using historical sales data, taking into consideration external factors like economic indicators and consumer trends. The results show a significant enhancement in forecast accuracy compared to traditional methods. The ML models effectively capture underlying trends and seasonal variations, providing reliable predictions that closely match actual sales results. Additionally, the models demonstrate strong adaptability, quickly adjusting to unexpected market shifts.展开更多
Flavonoids are widely-distributed polyphenolic secondary metabolites with diverse biological activities in plants and benefit human health as protective dietary agents.They participate in plants' responses to hars...Flavonoids are widely-distributed polyphenolic secondary metabolites with diverse biological activities in plants and benefit human health as protective dietary agents.They participate in plants' responses to harsh environmental conditions and effectively regulate the cell differentiation and growth.In plants,the majority of their functions are attributed to their strong antioxidative properties.Similarly,dietary flavonoids protect the human body against free radicals which are associated with the development of cancer and atherosclerosis.Plants rich in polyphenols have been used to cure various diseases because of their antibacterial,antiviral,antifungal and anticancer properties.This review summarizes the up-to-date research trends and development on flavonoids and its derivatives,working mechanisms and potential functions and applications particularly in relation to plant protection and human health.Towards the end,notable concluding remarks with a close-up look at the future research directions have also been presented briefly.展开更多
Internet of Vehicles(IoV)is an evolution of the Internet of Things(IoT)to improve the capabilities of vehicular ad-hoc networks(VANETs)in intelligence transport systems.The network topology in IoV paradigm is highly d...Internet of Vehicles(IoV)is an evolution of the Internet of Things(IoT)to improve the capabilities of vehicular ad-hoc networks(VANETs)in intelligence transport systems.The network topology in IoV paradigm is highly dynamic.Clustering is one of the promising solutions to maintain the route stability in the dynamic network.However,existing algorithms consume a considerable amount of time in the cluster head(CH)selection process.Thus,this study proposes a mobility aware dynamic clustering-based routing(MADCR)protocol in IoV to maximize the lifespan of networks and reduce the end-to-end delay of vehicles.The MADCR protocol consists of cluster formation and CH selection processes.A cluster is formed on the basis of Euclidean distance.The CH is then chosen using the mayfly optimization algorithm(MOA).The CH subsequently receives vehicle data and forwards such data to the Road Side Unit(RSU).The performance of the MADCR protocol is compared with that ofAnt Colony Optimization(ACO),Comprehensive Learning Particle Swarm Optimization(CLPSO),and Clustering Algorithm for Internet of Vehicles based on Dragonfly Optimizer(CAVDO).The proposed MADCR protocol decreases the end-toend delay by 5–80 ms and increases the packet delivery ratio by 5%–15%.展开更多
Extracellular manganese peroxidases （MnPs） produced by native and mutant strains of Trametes versicolor IBL‐04 （EB‐60, EMS‐90） were purified by ammonium sulphate precipitation and dialysis, followed by ion‐exc...Extracellular manganese peroxidases （MnPs） produced by native and mutant strains of Trametes versicolor IBL‐04 （EB‐60, EMS‐90） were purified by ammonium sulphate precipitation and dialysis, followed by ion‐exchange and gel‐permeation chromatography. The purified enzymes elucidated a single band in the 43‐kDa region on sodium dodecyl sulphate‐polyacrylamide gel electrophoresis. The optimum pH and temperature of the purified enzymes were found to be 5.0 and 40 °C, respec‐tively. Mutant strain MnPs exhibited a broader active pH range and higher thermal stability than native MnP. Purified MnPs from selected mutants showed almost identical properties to native MnP in electrophoresis, steady‐state kinetics, and metal ion and endocrine‐disrupting compound （EDC） degradation efficiency. Although the fastest reaction rates occurred with Mn2＋, MnPs displayed the highest affinity for ABTS, methoxyhydroquinone, 4‐aminophenol and reactive dyes. MnP activity was significantly enhanced by Mn2＋and Cu2＋, and inhibited in the presence of Zn2＋, Fe2＋, ethylene‐diaminetetraacetic acid and cysteine to various extents, with Hg2＋ as the most potent inhibitory agent. MnPs from all sources efficiently catalyzed the degradation of the EDCs, nonylphenol and triclosan, removing over 80%after 3 h of treatment, which was further increased up to 90%in the presence of MnP‐mediator system. The properties of T. versicolor MnPs, such as high pH and ther‐mal stability, as well as unique Michaelis‐Menten kinetic parameters and high EDC elimination effi‐ciency, render them promising candidates for industrial exploitation.展开更多
Non-alcoholic fatty liver disease(NAFLD),is a disease spectrum characterized by fat accumulation in hepatocytes presenting as hepatic steatosis to advance disease with active hepatic inflammation,known as nonalcoholic...Non-alcoholic fatty liver disease(NAFLD),is a disease spectrum characterized by fat accumulation in hepatocytes presenting as hepatic steatosis to advance disease with active hepatic inflammation,known as nonalcoholic steatohepatitis.Chronic steatohepatitis will lead to progressive hepatic fibrosis causing cirrhosis and increased risk for developing hepatocellular carcinoma(HCC).Fatty liver disease prevalence has increased at alarming rates alongside obesity,diabetes and metabolic syndrome to become the second most common cause of cirrhosis after alcohol related liver disease worldwide.Given this rise in prevalence,it is becoming increasingly more important to find non-invasive methods to diagnose disease early and stage hepatic fibrosis.Providing clinicians with the tools to diagnose and treat the full spectrum of NAFLD will help prevent known complications such as cirrhosis and HCC and improve quality of life for the patients suffering from this disease.This article discusses the utility of current noninvasive liver function testing in the clinical progression of fatty liver disease along with the imaging modalities that are available.Additionally,we summarize available treatment options including targeted medical therapy through four different pathways,surgical or endoscopic intervention.展开更多
In the quest for new agrochemicals and pharmaceuticals,chemists seek access to reliable and mild synthetic techniques to allow for the systematic modification of chemical structures,exploration of unexplored chemical ...In the quest for new agrochemicals and pharmaceuticals,chemists seek access to reliable and mild synthetic techniques to allow for the systematic modification of chemical structures,exploration of unexplored chemical space,and facilitation of practical synthesis in their search for novel agrochemicals and pharmaceuticals.In this regard,photocatalytic reactions enabled the synthesis of intricate and more functionalized compounds.This review overviews the developed synthetic methodologies and their utility in the chemical synthesis of pharmaceuticals.This review also offers in-depth insights into contemporary photoredox reactions such as allylic additions,cyclization,reductive cross-coupling,C–H activation,ring opening,oxidative cross-coupling,dehydrogenation,desulphonation,and decarboxylation.It provides a positive outlook for the promising future of this field.展开更多
The generation and controlled or uncontrolled release of hydrocarbon-contaminated industrial wastewater effluents to water matrices are a major environmental concern.The contaminated water comes to surface in the form...The generation and controlled or uncontrolled release of hydrocarbon-contaminated industrial wastewater effluents to water matrices are a major environmental concern.The contaminated water comes to surface in the form of stable emulsions,which sometimes require different techniques to mitigate or separate effectively.Both the crude emulsions and hydrocarbon-contaminated wastewater effluents contain suspended solids,oil/grease,organic matter,toxic elements,salts,and recalcitrant chemicals.Suitable treatment of crude oil emulsions has been one of the most important challenges due to the complex nature and the substantial amount of generated waste.Moreover,the recovery of oil from waste will help meet the increasing demand for oil and its derivatives.In this context,functional nanostructured materials with smart surfaces and switchable wettability properties have gained increasing attention because of their excellent performance in the separation of oil–water emulsions.Recent improvements in the design,composition,morphology,and fine-tuning of polymeric nanostructured materials have resulted in enhanced demulsification functionalities.Herein,we reviewed the environmental impacts of crude oil emulsions and hydrocarbon-contaminated wastewater effluents.Their effective treatments by smart polymeric nanostructured materials with wettability properties have been stated with suitable examples.The fundamental mechanisms underpinning the efficient separation of oil–water emulsions are discussed with suitable examples along with the future perspectives of smart materials.展开更多
Federated learning has been used extensively in business inno-vation scenarios in various industries.This research adopts the federated learning approach for the first time to address the issue of bank-enterprise info...Federated learning has been used extensively in business inno-vation scenarios in various industries.This research adopts the federated learning approach for the first time to address the issue of bank-enterprise information asymmetry in the credit assessment scenario.First,this research designs a credit risk assessment model based on federated learning and feature selection for micro and small enterprises(MSEs)using multi-dimensional enterprise data and multi-perspective enterprise information.The proposed model includes four main processes:namely encrypted entity alignment,hybrid feature selection,secure multi-party computation,and global model updating.Secondly,a two-step feature selection algorithm based on wrapper and filter is designed to construct the optimal feature set in multi-source heterogeneous data,which can provide excellent accuracy and interpretability.In addition,a local update screening strategy is proposed to select trustworthy model parameters for aggregation each time to ensure the quality of the global model.The results of the study show that the model error rate is reduced by 6.22%and the recall rate is improved by 11.03%compared to the algorithms commonly used in credit risk research,significantly improving the ability to identify defaulters.Finally,the business operations of commercial banks are used to confirm the potential of the proposed model for real-world implementation.展开更多
Internet of Things(IoT)defines a network of devices connected to the internet and sharing a massive amount of data between each other and a central location.These IoT devices are connected to a network therefore prone...Internet of Things(IoT)defines a network of devices connected to the internet and sharing a massive amount of data between each other and a central location.These IoT devices are connected to a network therefore prone to attacks.Various management tasks and network operations such as security,intrusion detection,Quality-of-Service provisioning,performance monitoring,resource provisioning,and traffic engineering require traffic classification.Due to the ineffectiveness of traditional classification schemes,such as port-based and payload-based methods,researchers proposed machine learning-based traffic classification systems based on shallow neural networks.Furthermore,machine learning-based models incline to misclassify internet traffic due to improper feature selection.In this research,an efficient multilayer deep learning based classification system is presented to overcome these challenges that can classify internet traffic.To examine the performance of the proposed technique,Moore-dataset is used for training the classifier.The proposed scheme takes the pre-processed data and extracts the flow features using a deep neural network(DNN).In particular,the maximum entropy classifier is used to classify the internet traffic.The experimental results show that the proposed hybrid deep learning algorithm is effective and achieved high accuracy for internet traffic classification,i.e.,99.23%.Furthermore,the proposed algorithm achieved the highest accuracy compared to the support vector machine(SVM)based classification technique and k-nearest neighbours(KNNs)based classification technique.展开更多
This paper studies the new families of exact traveling wave solutions with the modified nonlinear Schrodinger equation,which models the propagation of rogue waves in ocean engineering.The extended Fan sub-equation met...This paper studies the new families of exact traveling wave solutions with the modified nonlinear Schrodinger equation,which models the propagation of rogue waves in ocean engineering.The extended Fan sub-equation method with five parameters is used to find exact traveling wave solutions.It has been observed that the equation exhibits a collection of traveling wave solutions for limiting values of parameters.This method is beneficial for solving nonlinear partial differential equations,because it is not only useful for finding the new exact traveling wave solutions,but also gives us the solutions obtained previously by the usage of other techniques(Riccati equation,or first-kind elliptic equation,or the generalized Riccati equation as mapping equation,or auxiliary ordinary differential equation method)in a combined approach.Moreover,by means of the concept of linear stability,we prove that the governing model is stable.3 D figures are plotted for showing the physical behavior of the obtained solutions for the different values of unknown parameters with constraint conditions.展开更多
基金National Science and Technology Major Project(No.J2019-III-0005-0048)Ministry of Science and Technology of China(Nos.2021YFA0716200/2022YFB4003900)+2 种基金Natural Science Foundation of China(Nos.51976216,51888103,52161145105/M-0139)Beijing Municipal Natural Science Foundation(No.JQ20017)Chinese Academy of Sciences(Nos.YJKYYQ20210006,GJTD-2020-07),CAS-TWAS Scholarships。
文摘Through several waves of technological research and un‐matched innovation strategies,bio‐catalysis has been widely used at the industrial level.Because of the value of enzymes,methods for producing value‐added compounds and industrially‐relevant fine chemicals through biological methods have been developed.A broad spectrum of numerous biochemical pathways is catalyzed by enzymes,including enzymes that have not been identified.However,low catalytic efficacy,low stability,inhibition by non‐cognate substrates,and intolerance to the harsh reaction conditions required for some chemical processes are considered as major limitations in applied bio‐catalysis.Thus,the development of green catalysts with multi‐catalytic features along with higher efficacy and induced stability are important for bio‐catalysis.Implementation of computational science with metabolic engineering,synthetic biology,and machine learning routes offers novel alternatives for engineering novel catalysts.Here,we describe the role of synthetic biology and metabolic engineering in catalysis.Machine learning algorithms for catalysis and the choice of an algorithm for predicting protein‐ligand interactions are discussed.The importance of molecular docking in predicting binding and catalytic functions is reviewed.Finally,we describe future challenges and perspectives.
基金supported by the Hainan Province Science and Technology Special Fund(ZDYF2022XDNY233)the Fundamental Research Funds for the Central Universities(KJYQ2025018)+3 种基金National key research and development plan project(2022YFD2301401)Young Elite Scientists Sponsorship Program by the CAST(2022QNRC001)Key Technology Research and Development Program of Shandong and Jiangsu Province(2024TZXD070,BE2023370)a project funded by the Priority Academic Program Development(PAPD)of Jiangsu Higher Education Institutions。
文摘This study investigated the impact of wheatgrass powder(WGP)as a functional ingredient in steamed bread from the nutritional and techno-functional perspective.The addition of WGP significantly enhanced the antioxidant capacity in a dose-dependent manner,attributed to its bioactive compounds,though thermal processing led to a reduction due to heat sensitivity.Physicochemical analysis revealed that WGP enrichment decreased moisture content(34.27% and 33.82% for 2.5%and 5.0%WGP vs.38.37% for control)and increased weight loss(1.45% and 1.52% for 2.5%and 5.0% WGP vs.1.27% for control),likely due to fiber-gluten competition for water,while water absorption capacity(WAC)improved with higher WGP levels(1.60 g/g and 1.92 g/g for 2.5% and 5.0% WGP vs.1.40 g/g for control).The microstructural analysis demonstrated that WGP disrupted the glutenstarch matrix,increasing porosity and reducing starch gelatinization,correlating with altered textural properties.Notably,WGP extended microbial shelf life by 48–72 h(delaying mold growth to 3–4 d vs.2 d in control),likely due to its anti-microbial bioactive constituents.Sensory evaluation indicated that WGP-enriched steamed bread achieved optimal consumer acceptance.These findings suggest that WGP is a promising functional ingredient for improving the nutritional and sensory quality of steamed bread,though optimizing processing conditions is crucial to mitigate the thermal degradation of antioxidants.
基金supported by the Key R&D Project in Shaanxi Province(No.2024GX-YBXM-371)Shaanxi Qinchuangyuan“Scientists+Engineers”Team Construction Project(2025QCY-KXJ-141).
文摘Presently,many asphalts and modified asphalts fail to satisfy long-term serviceability and durability criteria.Researchers are utilizing several asphalt modifiers to enhance the overall performance of flexible pavements.This study consolidated findings from multiple research efforts on using nanomaterials for modifying SBS modified asphalt(SBS MA)and conducted a comprehensive literature review.Initially,it discussed the importance of SBS MA within asphalt modification systems and identified the key nanomaterials utilized in SBS modified asphalt.After this,it reviewed their preparation methods,dispersion and characterization techniques,and their impact on the key performance parameters of SBS MA binder and its mixture such as viscosity,rutting resistance,fatigue resistance,ageing and moisture damage etc.Additionally,it highlighted the advantages of nanomaterials over other modifiers.This study also addressed the challenges and limitations of incorporating nanomaterials in SBS MA.The findings indicated that when properly integrated,nanomaterials could significantly improve the performance of SBS MA,making them a promising addition to future road construction and maintenance projects.However,using nanomaterials for SBS MA modifications and mixtures has been challenged by limited practical applications,insufficient life cycle cost analyses,a lack of standardized guidelines,cost-effective nanomaterials and insufficient mixing procedures.Those areas require additional research to realise the potential application of nanomaterials in SBS modified asphalt modifications full.
基金supported by the National Natural Science Foundation of China under grants No.92267104 and 62372242。
文摘Increasing reliance on large-scale AI models has led to rising demand for intelligent services.The centralized cloud computing approach has limitations in terms of data transfer efficiency and response time,and as a result many service providers have begun to deploy edge servers to cache intelligent services in order to reduce transmission delay and communication energy consumption.However,finding the optimal service caching strategy remains a significant challenge due to the stochastic nature of service requests and the bulky nature of intelligent services.To deal with this,we propose a distributed service caching scheme integrating deep reinforcement learning(DRL)with mobility prediction,which we refer to as DSDM.Specifically,we employ the D3QN(Deep Double Dueling Q-Network)framework to integrate Long Short-Term Memory(LSTM)predicted mobile device locations into the service caching replacement algorithm and adopt the distributed multi-agent approach for learning and training.Experimental results demonstrate that DSDM achieves significant performance improvements in reducing communication energy consumption compared to traditional methods across various scenarios.
文摘Experimental and computational fluid dynamics (CFD) are investigated through the vortex tube system. The benefit of vortex tube is a counter flow type tube, which has further designed and fabricated for investigation. The whole set up is consisting of a simple device that can separate a single stream of compressed air into two streams;one is at high temperature and the other is lower temperature following an inlet gas stream. The advantages of this tube are their compactness, safety, and low equipment cost mainly used in cooling and heating applications. This study addressed three-dimensional flows;the domain is using computational fluid dynamics (CFD) method and experimental approach to optimize the direction of RHVT. Through the CFD analysis, the best cold end diameter (dc), number of nozzles, and the best parameters for obtaining the highest hot gas temperature and lowest cold gas temperature were obtained and verified by experimental procedures.
文摘The Far North Region of Cameroon is home to a great diversity of bird species, which unfortunately remains very little explored. This work was initiated to establish an inventory of birds and the factors affecting their diversity and distribution for sustainable management in the Kalfou Forest Reserve (KFR) and its periphery. Two methods were used for sampling, linear strip transects from which direct counts and indirect observations were made and the mist netting to complement the first. In total, 2525 birds were observed, including 149 species, belonging to 20 orders and 55 families. Accipitridae had the greatest number of species (11). The species richness was greater in the KFR (117 species) compared to the periphery (95 species). The specific richness was higher in wooded savannah compared to other habitats. Shannon index was significantly higher in the KFR (3.99) compared to that obtained in the periphery (3.80). The value of the Simpson index was higher on the outskirts of the KFR than on the periphery. The indices of species diversity were greater in the wooded savannah compared to other vegetation types. The seasons had no influence on bird diversity. Among the human activities encountered, the pressure indices were more important for grazing (7.3 contacts/km). Human activities have resulted in a significant decrease in specific richness. Six endangered species were encountered, four belonging to the Accipitridae family. The greater bird diversity in the reserve compared to the periphery shows that protected areas are a long-term solution for biodiversity conservation.
文摘Hijama is an alternative mode of treatment also known as cupping therapy. It involves removal of subcutaneous stagnant blood through suction cups after making superficial incisions at particular area of the body. This study was undertaken to evaluate the efficacy of hijama in sciatica pain at Aligarh Shifa hospital. 92 patients with the history of sciatica were selected randomly between 18 - 75 years of age and hijama cups were applied generally at C7, T2 and L5/S1 vertebrae, while two cups were also applied bilaterally on L4/L5 vertebrae, four cups were additionally applied on hip joint, back of thigh, knee and calf muscle, all cups were applied thrice at an interval of 15 days between each session. The decrease in sciatic pain was assessed after three sessions of Hijama by numeric pain rating scale there was overall significant reduction in pain with 67 percent patients showing relief in pain up to varying degree. Present study suggests that hijama has been found to be effective in relieving pain and improving quality of life in majority of the patient’s, hence may be used as effective alternative tool to alleviate pain.
文摘Accurate sales forecasting is essential in the fast-paced world of business for effective strategic planning and resource allocation. However, traditional forecasting methods often lack precision and flexibility. This study aims to address this issue by incorporating machine learning (ML) techniques to improve forecasting accuracy and responsiveness to market changes. The methodology involves gathering extensive sales data and carefully preprocessing it to ensure quality. Various ML algorithms, such as time series analysis, regression models, and neural networks, are utilized to account for the complex and non-linear nature of sales patterns. These models are trained and validated using historical sales data, taking into consideration external factors like economic indicators and consumer trends. The results show a significant enhancement in forecast accuracy compared to traditional methods. The ML models effectively capture underlying trends and seasonal variations, providing reliable predictions that closely match actual sales results. Additionally, the models demonstrate strong adaptability, quickly adjusting to unexpected market shifts.
基金supported by the National High-Tech R&D Program of China (863 Program,2013AA103000)the earmarked fund for Shanghai Modern Leaf Vegetable Industry Technology Research System,China (201802)
文摘Flavonoids are widely-distributed polyphenolic secondary metabolites with diverse biological activities in plants and benefit human health as protective dietary agents.They participate in plants' responses to harsh environmental conditions and effectively regulate the cell differentiation and growth.In plants,the majority of their functions are attributed to their strong antioxidative properties.Similarly,dietary flavonoids protect the human body against free radicals which are associated with the development of cancer and atherosclerosis.Plants rich in polyphenols have been used to cure various diseases because of their antibacterial,antiviral,antifungal and anticancer properties.This review summarizes the up-to-date research trends and development on flavonoids and its derivatives,working mechanisms and potential functions and applications particularly in relation to plant protection and human health.Towards the end,notable concluding remarks with a close-up look at the future research directions have also been presented briefly.
基金This work was supported by National Natural Science Foundation of China(No.61821001)Science and Tech-nology Key Project of Guangdong Province,China(2019B010157001).
文摘Internet of Vehicles(IoV)is an evolution of the Internet of Things(IoT)to improve the capabilities of vehicular ad-hoc networks(VANETs)in intelligence transport systems.The network topology in IoV paradigm is highly dynamic.Clustering is one of the promising solutions to maintain the route stability in the dynamic network.However,existing algorithms consume a considerable amount of time in the cluster head(CH)selection process.Thus,this study proposes a mobility aware dynamic clustering-based routing(MADCR)protocol in IoV to maximize the lifespan of networks and reduce the end-to-end delay of vehicles.The MADCR protocol consists of cluster formation and CH selection processes.A cluster is formed on the basis of Euclidean distance.The CH is then chosen using the mayfly optimization algorithm(MOA).The CH subsequently receives vehicle data and forwards such data to the Road Side Unit(RSU).The performance of the MADCR protocol is compared with that ofAnt Colony Optimization(ACO),Comprehensive Learning Particle Swarm Optimization(CLPSO),and Clustering Algorithm for Internet of Vehicles based on Dragonfly Optimizer(CAVDO).The proposed MADCR protocol decreases the end-toend delay by 5–80 ms and increases the packet delivery ratio by 5%–15%.
基金a part of a research project entitled "The development of immobilized ligninolytic enzymes for industrial applications" supported by Higher Education Commission (HEC), Islamabad, Pakistan
文摘Extracellular manganese peroxidases （MnPs） produced by native and mutant strains of Trametes versicolor IBL‐04 （EB‐60, EMS‐90） were purified by ammonium sulphate precipitation and dialysis, followed by ion‐exchange and gel‐permeation chromatography. The purified enzymes elucidated a single band in the 43‐kDa region on sodium dodecyl sulphate‐polyacrylamide gel electrophoresis. The optimum pH and temperature of the purified enzymes were found to be 5.0 and 40 °C, respec‐tively. Mutant strain MnPs exhibited a broader active pH range and higher thermal stability than native MnP. Purified MnPs from selected mutants showed almost identical properties to native MnP in electrophoresis, steady‐state kinetics, and metal ion and endocrine‐disrupting compound （EDC） degradation efficiency. Although the fastest reaction rates occurred with Mn2＋, MnPs displayed the highest affinity for ABTS, methoxyhydroquinone, 4‐aminophenol and reactive dyes. MnP activity was significantly enhanced by Mn2＋and Cu2＋, and inhibited in the presence of Zn2＋, Fe2＋, ethylene‐diaminetetraacetic acid and cysteine to various extents, with Hg2＋ as the most potent inhibitory agent. MnPs from all sources efficiently catalyzed the degradation of the EDCs, nonylphenol and triclosan, removing over 80%after 3 h of treatment, which was further increased up to 90%in the presence of MnP‐mediator system. The properties of T. versicolor MnPs, such as high pH and ther‐mal stability, as well as unique Michaelis‐Menten kinetic parameters and high EDC elimination effi‐ciency, render them promising candidates for industrial exploitation.
文摘Non-alcoholic fatty liver disease(NAFLD),is a disease spectrum characterized by fat accumulation in hepatocytes presenting as hepatic steatosis to advance disease with active hepatic inflammation,known as nonalcoholic steatohepatitis.Chronic steatohepatitis will lead to progressive hepatic fibrosis causing cirrhosis and increased risk for developing hepatocellular carcinoma(HCC).Fatty liver disease prevalence has increased at alarming rates alongside obesity,diabetes and metabolic syndrome to become the second most common cause of cirrhosis after alcohol related liver disease worldwide.Given this rise in prevalence,it is becoming increasingly more important to find non-invasive methods to diagnose disease early and stage hepatic fibrosis.Providing clinicians with the tools to diagnose and treat the full spectrum of NAFLD will help prevent known complications such as cirrhosis and HCC and improve quality of life for the patients suffering from this disease.This article discusses the utility of current noninvasive liver function testing in the clinical progression of fatty liver disease along with the imaging modalities that are available.Additionally,we summarize available treatment options including targeted medical therapy through four different pathways,surgical or endoscopic intervention.
文摘In the quest for new agrochemicals and pharmaceuticals,chemists seek access to reliable and mild synthetic techniques to allow for the systematic modification of chemical structures,exploration of unexplored chemical space,and facilitation of practical synthesis in their search for novel agrochemicals and pharmaceuticals.In this regard,photocatalytic reactions enabled the synthesis of intricate and more functionalized compounds.This review overviews the developed synthetic methodologies and their utility in the chemical synthesis of pharmaceuticals.This review also offers in-depth insights into contemporary photoredox reactions such as allylic additions,cyclization,reductive cross-coupling,C–H activation,ring opening,oxidative cross-coupling,dehydrogenation,desulphonation,and decarboxylation.It provides a positive outlook for the promising future of this field.
文摘The generation and controlled or uncontrolled release of hydrocarbon-contaminated industrial wastewater effluents to water matrices are a major environmental concern.The contaminated water comes to surface in the form of stable emulsions,which sometimes require different techniques to mitigate or separate effectively.Both the crude emulsions and hydrocarbon-contaminated wastewater effluents contain suspended solids,oil/grease,organic matter,toxic elements,salts,and recalcitrant chemicals.Suitable treatment of crude oil emulsions has been one of the most important challenges due to the complex nature and the substantial amount of generated waste.Moreover,the recovery of oil from waste will help meet the increasing demand for oil and its derivatives.In this context,functional nanostructured materials with smart surfaces and switchable wettability properties have gained increasing attention because of their excellent performance in the separation of oil–water emulsions.Recent improvements in the design,composition,morphology,and fine-tuning of polymeric nanostructured materials have resulted in enhanced demulsification functionalities.Herein,we reviewed the environmental impacts of crude oil emulsions and hydrocarbon-contaminated wastewater effluents.Their effective treatments by smart polymeric nanostructured materials with wettability properties have been stated with suitable examples.The fundamental mechanisms underpinning the efficient separation of oil–water emulsions are discussed with suitable examples along with the future perspectives of smart materials.
基金funded by the State Grid Jiangsu Electric Power Company(Grant No.JS2020112)the National Natural Science Foundation of China(Grant No.62272236).
文摘Federated learning has been used extensively in business inno-vation scenarios in various industries.This research adopts the federated learning approach for the first time to address the issue of bank-enterprise information asymmetry in the credit assessment scenario.First,this research designs a credit risk assessment model based on federated learning and feature selection for micro and small enterprises(MSEs)using multi-dimensional enterprise data and multi-perspective enterprise information.The proposed model includes four main processes:namely encrypted entity alignment,hybrid feature selection,secure multi-party computation,and global model updating.Secondly,a two-step feature selection algorithm based on wrapper and filter is designed to construct the optimal feature set in multi-source heterogeneous data,which can provide excellent accuracy and interpretability.In addition,a local update screening strategy is proposed to select trustworthy model parameters for aggregation each time to ensure the quality of the global model.The results of the study show that the model error rate is reduced by 6.22%and the recall rate is improved by 11.03%compared to the algorithms commonly used in credit risk research,significantly improving the ability to identify defaulters.Finally,the business operations of commercial banks are used to confirm the potential of the proposed model for real-world implementation.
基金This work has supported by the Xiamen University Malaysia Research Fund(XMUMRF)(Grant No:XMUMRF/2019-C3/IECE/0007)。
文摘Internet of Things(IoT)defines a network of devices connected to the internet and sharing a massive amount of data between each other and a central location.These IoT devices are connected to a network therefore prone to attacks.Various management tasks and network operations such as security,intrusion detection,Quality-of-Service provisioning,performance monitoring,resource provisioning,and traffic engineering require traffic classification.Due to the ineffectiveness of traditional classification schemes,such as port-based and payload-based methods,researchers proposed machine learning-based traffic classification systems based on shallow neural networks.Furthermore,machine learning-based models incline to misclassify internet traffic due to improper feature selection.In this research,an efficient multilayer deep learning based classification system is presented to overcome these challenges that can classify internet traffic.To examine the performance of the proposed technique,Moore-dataset is used for training the classifier.The proposed scheme takes the pre-processed data and extracts the flow features using a deep neural network(DNN).In particular,the maximum entropy classifier is used to classify the internet traffic.The experimental results show that the proposed hybrid deep learning algorithm is effective and achieved high accuracy for internet traffic classification,i.e.,99.23%.Furthermore,the proposed algorithm achieved the highest accuracy compared to the support vector machine(SVM)based classification technique and k-nearest neighbours(KNNs)based classification technique.
文摘This paper studies the new families of exact traveling wave solutions with the modified nonlinear Schrodinger equation,which models the propagation of rogue waves in ocean engineering.The extended Fan sub-equation method with five parameters is used to find exact traveling wave solutions.It has been observed that the equation exhibits a collection of traveling wave solutions for limiting values of parameters.This method is beneficial for solving nonlinear partial differential equations,because it is not only useful for finding the new exact traveling wave solutions,but also gives us the solutions obtained previously by the usage of other techniques(Riccati equation,or first-kind elliptic equation,or the generalized Riccati equation as mapping equation,or auxiliary ordinary differential equation method)in a combined approach.Moreover,by means of the concept of linear stability,we prove that the governing model is stable.3 D figures are plotted for showing the physical behavior of the obtained solutions for the different values of unknown parameters with constraint conditions.
