An in-built N^(+)pocket electrically doped tunnel field-effect transistor(ED-TFET)-based biosensor has been reported for the first time.The proposed device begins with a PN junction structure with a control gate(CG)an...An in-built N^(+)pocket electrically doped tunnel field-effect transistor(ED-TFET)-based biosensor has been reported for the first time.The proposed device begins with a PN junction structure with a control gate(CG)and two polarity gates(PG1 and PG2).Utilizing the polarity bias concept,a narrow N^(+)pocket is formed between the source and channel without the need for additional doping steps,achieved through biasing PG1 and PG2 at-1.2 V and 1.2 V,respectively.This method not only addresses issues related to doping control but also eliminates constraints associated with thermal budgets and simplifies the fabrication process compared to traditional TFETs.To facilitate biomolecule sensing within the device,a nanogap cavity is formed in the gate dielectric by selectively etching a section of the polarity gate dielectric layer toward the source side.The investigation into the presence of neutral and charged molecules within the cavities has been conducted by examining variations in the electrical properties of the proposed biosensor.Key characteristics assessed include drain current,energy band,and electric field distribution.The performance of the biosensor is measured using various metrics such as drain current(I_(DS)),subthreshold swing(SS),threshold voltage(V_(TH)),drain current ratio(I_(ON)/I_(OFF)).The proposed in-built N^(+)pocket ED-TFET-based biosensor reaches a peak sensitivity of 1.08×10~(13)for a neutral biomolecule in a completely filled nanogap with a dielectric constant of 12.Additionally,the effects of cavity geometry and different fill factors(FFs)on sensitivity are studied.展开更多
Objective:To investigate the relationship between triterpenoid saponin content and antioxidant,antimicrobial,and α-glucosidase inhibitory activities of 70%ethanolic,butanolic,aqueous,supernate and precipitate extract...Objective:To investigate the relationship between triterpenoid saponin content and antioxidant,antimicrobial,and α-glucosidase inhibitory activities of 70%ethanolic,butanolic,aqueous,supernate and precipitate extracts of Juglans regia leaves.Methods:Triterpenoid saponins of different Juglans regia leaf extracts were measured by the vanillin method.Antioxidant activity was evaluated against DPPH and ABTS free radicals.We also assessed α-glucosidase inhibitory and antimicrobial activities of the leaf extracts.Pearson’s correlation coefficient was evaluated to determine the correlation between the saponin content and biological activities.Results:The butanolic extract was most effective against DPPH with an IC50of 6.63μg/mL,while the aqueous extract showed the highest scavenging activity against ABTS free radical with an IC50of 42.27μg/mL.Pearson’s correlation analysis indicated a strong negative correlation (r=-0.956) between DPPH radical scavenging activity (IC50) and the saponin content in the samples examined.In addition,the aqueous extract showed the best α-glucosidase inhibitory activity compared with other extracts.All the extracts had fair antibacterial activity against Bacillus subtilis,Escherichia coli,and Klebsiella pneumoniae except for the aqueous extract.Conclusions:Juglans regia extracts show potent antioxidant,antimicrobial,and α-glucosidase inhibitory activities.There is a correlation between saponin levels in Juglans regia leaf extracts and the studied activities.However,additional research is required to establish these relationships by identifying the specific saponin molecules responsible for these activities and elucidating their mechanisms of action.展开更多
Objective:To evaluate the prevalence and types of complementary and alternative medicine(CAM)modalities among patients with cancer in Karachi,Pakistan.Methods:This descriptive cross-sectional study was conducted from ...Objective:To evaluate the prevalence and types of complementary and alternative medicine(CAM)modalities among patients with cancer in Karachi,Pakistan.Methods:This descriptive cross-sectional study was conducted from March 2021 to December 2021.Five hundred patients with cancer were invited to participate in the study.Electronic databases,namely,Google scholar,Publons,EMBASE,PubMed,Chinese National Knowledge Infrastructure Database,and ResearchGate was used for questionnaire designed.The self-administered survey included questions on demographic characteristics,education level,socio-economic conditions and information about CAM therapies,prevalence,effectiveness,and common CAM modalities.Statistical analysis was conducted using SPSS software version 22.Results:Out of the 500 invited patients,433(86.6%)successfully completed and returned the questionnaires.In contrast to patients who were with younger,highly educated,professionally active,higher income,and had advanced cancer,time since diagnosis,type of treatment,cancer types and family history are significantly associated with CAM use.The results showed that 59.8%of the participants were acquainted with complementary and/or alternative medicine and considered safe owing to its natural ingredients.The prevalence of CAM usage among cancer patients was 40.9%and the most widely used CAM modality was herbal medicine(27.7%)and dietary supplements(28.8%).Patients used CAM as a complementary therapy to improve the morphological parameter(28.2%),strengthen the immune system(6.8%),and to decrease the side effects of conventional treatment(18.1%).Most of the respondents get the information regarding CAM therapy from the electronic media(43.2%)and the family members(48%)rather than healthcare personnel.Conclusions:Participants used CAM modalities along with the conventional health care practices.Further multicentre studies should be conducted to provide information regarding the usage of CAM therapies and their eventual benefits in patients with cancer.展开更多
Video analytics is an integral part of surveillance cameras. Comparedto video analytics, audio analytics offers several benefits, includingless expensive equipment and upkeep expenses. Additionally, the volume ofthe a...Video analytics is an integral part of surveillance cameras. Comparedto video analytics, audio analytics offers several benefits, includingless expensive equipment and upkeep expenses. Additionally, the volume ofthe audio datastream is substantially lower than the video camera datastream,especially concerning real-time operating systems, which makes it lessdemanding of the data channel’s bandwidth needs. For instance, automaticlive video streaming from the site of an explosion and gunshot to the policeconsole using audio analytics technologies would be exceedingly helpful forurban surveillance. Technologies for audio analytics may also be used toanalyze video recordings and identify occurrences. This research proposeda deep learning model based on the combination of convolutional neuralnetwork (CNN) and recurrent neural network (RNN) known as the CNNRNNapproach. The proposed model focused on automatically identifyingpulse sounds that indicate critical situations in audio sources. The algorithm’saccuracy ranged from 95% to 81% when classifying noises from incidents,including gunshots, explosions, shattered glass, sirens, cries, and dog barking.The proposed approach can be applied to provide security for citizens in openand closed locations, like stadiums, underground areas, shopping malls, andother places.展开更多
Objective:To assess the acute and subacute toxicity as well as the phytochemical composition of two extracts and three fractions of Ammi majus L.Methods:The aqueous extracts were prepared separately by maceration for ...Objective:To assess the acute and subacute toxicity as well as the phytochemical composition of two extracts and three fractions of Ammi majus L.Methods:The aqueous extracts were prepared separately by maceration for 48 h and by infusion for 1 h,while the fractions were prepared by the Soxhlet extractor,successively employing cyclohexane,ethyl acetate,and ethanol.The acute toxicity study was carried out in accordance with the OECD N°423 guideline at a single dose(2000 mg/kg)in mice for 14 days.The subacute toxicity study was performed by a daily oral administration of 250 mg/kg 2 for 10 d and 100 mg/kg doses for 28 d.Phytochemical screening was performed using staining and precipitation reactions,while the chemical characterization of some analytes was detected by HPLC-MS/MS analysis.Results:In the acute toxicity study,no signs of toxicity such as convulsion,salivation,diarrhea,sleep and coma were observed during 30 minutes and 14 days,so the lethal dose was higher than 2000 mg/kg for each extract and fraction.The subacute toxicity results showed that at a dose of 250 mg/kg,61.10%of the animals died and the rest developed morbidity.On the other hand,at a dose of 100 mg/kg,all the animals were still alive after 28 days,with no morbidity and the biochemical parameters were normal with no abnormalities in the liver,kidneys and pancreas.Phytochemical screening indicated the presence of flavonoids,tannins,coumarins,and free quinones and the absence of alkaloids and anthocyanins.Conclusions:The extracts and fractions of Ammi majus L.are not toxic in the short and long term with a varied chemical composition.Toxicological tests on animals other than rodents and in the long term(more than 28 days)are needed to further confirm the safety of Ammi majus extracts.展开更多
The integration of Green Artificial Intelligence(AI)technologies into educational systems offers a promising avenue to enhance operational efficiency while addressing sustainability challenges.Through a rigorous three...The integration of Green Artificial Intelligence(AI)technologies into educational systems offers a promising avenue to enhance operational efficiency while addressing sustainability challenges.Through a rigorous three-phase methodology combining literature review,AI agent development,and participatory workshop-based case analysis,this paper highlights the pivotal role of AI agents,as applications of Green AI technologies,in driving transformative outcomes within schools.By directly improving self-learning efficiency and reducing learning costs for students,enhancing management and service efficiency,reducing labor costs for schools,as well as minimizing resource dependence for both teachers and students,AI agents create a foundation for sustainable operations.These direct effects generate positive spillover effects,cascading into broader outcomes,including innovation performance,economic efficiency,and environmental sustainability,aligning with the United Nations Sustainable Development Goals(SDGs).By presenting a comprehensive conceptual model,this study demonstrates the pathways through which Green AI contributes to sustainable development in education and emphasizes its critical role in bridging technological innovation with sustainability.This framework provides significant theoretical insights for further empirical research while offering actionable strategies for policymakers and educators to harness Green AI for building sustainable schools with a student-centered approach.展开更多
Counterfeiting is still a pervasive global issue,affecting multiple industries and hindering industrial innovation,while causing substantial financial losses,reputational damage,and risks to consumer safety.From luxur...Counterfeiting is still a pervasive global issue,affecting multiple industries and hindering industrial innovation,while causing substantial financial losses,reputational damage,and risks to consumer safety.From luxury goods and pharmaceuticals to electronics and automotive parts,counterfeit products infiltrate supply chains,leading to a loss of revenue for legitimate businesses and undermining consumer trust.Traditional anti-counterfeiting measures,such as holograms,serial numbers,and barcodes,have proven to be insufficient as counterfeiters continuously develop more sophisticated replication techniques.As a result,there is a growing need for more advanced,secure,and reliable methods to prevent counterfeiting.This paper presents a novel,holistic anti-counterfeiting platform that integrates Near Field Communication(NFC)-enabled mobile applications with blockchain technology to provide an innovative,secure,and consumer-friendly authentication mechanism.Our approach addresses key gaps in existing solutions by incorporating dynamic product identifiers,which make replication significantly more difficult.The system enables consumers to verify the authenticity of products instantly using their smartphones,enhancing transparency and trust in the supply chain.Blockchain technology plays a crucial role in our proposed solution by providing an immutable,decentralized ledger that records product authentication data.This ensures that product verification records cannot be tampered with or altered,adding a layer of security that is absent in conventional systems.Additionally,NFC technology enhances security by offering unique identification capabilities,enabling real-time product verification.To validate the effectiveness of the proposed system,real-world testing was conducted across different industries.The results demonstrated the platform’s ability to significantly reduce counterfeit products in the supply chain,offering businesses and consumers a more robust and reliable authentication method.By leveraging the combined strengths of blockchain and NFC,this solution represents a significant advancement in the fight against counterfeiting,ensuring enhanced security,transparency,and consumer trust.展开更多
The development of society and the advancement of science and technology have led to the widespread integration of digital transformation in the field of education.However,the current establishment of green schools fa...The development of society and the advancement of science and technology have led to the widespread integration of digital transformation in the field of education.However,the current establishment of green schools faces various challenges,including non-environmental building facilities,high renovation costs,low organizational management efficiency,high energy consumption,outdated office tools,and insufficient environmental awareness among teachers and students.Through thorough research and analysis,it becomes evident that digital technology can play a pivotal role in addressing these challenges and contribute to all aspects of green school establishment.The incorporation of digital thinking concepts is essential for the construction of ecologically civilized campuses and inclusive innovation.The process of digital design and transformation proves instrumental in optimizing both software and hardware facilities within the campus,thereby reducing energy consumption.Simultaneously,comprehensive digital teaching management enhances overall efficiency in management and service delivery.Innovative digital teaching and learning models emerge as transformative tools,providing new avenues to create low-carbon,green classrooms for both teachers and students.By exploring the application of digital transformation in establishing green schools and examining the resulting spillover effects,valuable insights can be gained.These insights,in turn,serve as reference points for building diversified digital technology paths on campus and fostering the creation of green schools.展开更多
This paper presents a biosensor utilizing a whispering gallery mode(WGM)resonator characterized by azimuthal symmetry and crescent-shaped coatings of silver.The study investigates the impact of the coupling gap on the...This paper presents a biosensor utilizing a whispering gallery mode(WGM)resonator characterized by azimuthal symmetry and crescent-shaped coatings of silver.The study investigates the impact of the coupling gap on the extinction ratio and Q-factor of the setup.The resonator is coated with silver in crescent shapes,ranging from 40 nm to 65 nm in thickness.Coupling is achieved with a silica waveguide,simulating the tapered fiber coupling method.Notably,the resonator exhibits a maximum sensitivity of 220 nm/RIU when coated with 55-nm-thick silver in conjunction with a 4-nm-thick layer of thiol-tethered deoxyribonucleic acid(DNA).This biosensor holds promise for biomolecule detection applications.展开更多
Background Pediatric anemia is a pervasive public health issue in Asia,significantly impairing children’s growth,cognitive development,and future potential.This study evaluates trends,prevalence,and socio-economic di...Background Pediatric anemia is a pervasive public health issue in Asia,significantly impairing children’s growth,cognitive development,and future potential.This study evaluates trends,prevalence,and socio-economic disparities of pediatric anemia across Asia from 1990 to 2021,leveraging data from the Global Burden of Disease Study(GBD)2021 study.Methods Using estimated annual percentage change(EAPC)and Pearson’s correlation coefficient,geographic variations and temporal trends were analysed alongside associations between prevalence,years lived with disability(YLDs),and Socio-demographic index(SDI).Results The study reveals a modest overall decline in anemia prevalence by 11.9%,from 464.53 million cases in 1990 to 409.07 million in 2021.High-SDI regions such as East Asia achieved significant reductions(−71.36%),with countries like Singapore,the Republic of Korea,Seychelles,Qatar,and the United Arab Emirates(UAE)showing substantial progress.In stark contrast,low-SDI countries,including Yemen(108.34%)and Afghanistan(130.28%),along with Cambodia,India,and Pakistan,experienced alarming increases.Dietary iron deficiency was the dominant cause,followed by hemoglobinopathies and neglected tropical diseases.Females,particularly adolescents,and children under five faced disproportionate burdens,with prevalence rates in low-SDI regions exceeding 47,000 per 100,000 compared to<10,000 per 100,000 in high-SDI areas.Conclusions These findings emphasize profound regional and socio-economic inequalities in anemia burden.Urgent,evidence-based interventions are imperative,focusing on enhancing nutrition,expanding healthcare access,and integrating sex-sensitive strategies to address this multifaceted issue.Strengthened policies and targeted actions are critical to mitigating the burden and fostering health equity,particularly in vulnerable low-SDI regions.展开更多
Graphene oxide(GO)is a 2D coating material used to improve fiber optics sensors’response to relative humidity.Microbottle resonators(MBRs)have garnered more attention as sensing media structures.An MBR with a 190μm ...Graphene oxide(GO)is a 2D coating material used to improve fiber optics sensors’response to relative humidity.Microbottle resonators(MBRs)have garnered more attention as sensing media structures.An MBR with a 190μm diameter was coated with GO.Then,tapered fiber light coupling was used to investigate the relative humidity sensing performance in the range of 35—70%RH at 25℃.The MBR showed a higher Q factor before and after GO coating.The sensitivity of 0.115 dB/%RH was recorded with the 190μm GO-coated MBR sample compared to a sensitivity of 0.022 dB/%RH for the uncoated MBR sample.These results show that the MBR can be used in fiber optic sensing applications for environmental sensing.展开更多
Federated learning is a decentralized model training paradigm with significant potential.However,the quality of Federated Network’s client updates can vary due to non-IID data distributions,leading to suboptimal glob...Federated learning is a decentralized model training paradigm with significant potential.However,the quality of Federated Network’s client updates can vary due to non-IID data distributions,leading to suboptimal global models.To address this issue,we propose a novel client selection strategy called FedPA(Performance-Based Federated Averaging).This proposed model selectively aggregates client updates based on a predefined performance threshold.Only clients whose local models achieve an F1 score of 70%or higher after training are included in the aggregation process.Clients below this threshold receive the updated global model but do not contribute their parameters.In this way,the low-performance clients are still in the process of learning and,after some rounds,will be able to contribute.If no client meets the performance threshold in a given round,the system falls back to standard FedAvg aggregation.This ensures the global model continues to improve even when most clients perform poorly.We evaluate FedPA on a subset of the MURA dataset for abnormality detection in radiographs of four bone types.Compared to baseline federated learning algorithms such as Federated Averaging(FedAvg),Federated Proximal(FedProx),Federated Stochastic Gradient Descent(FedSGD),and Federated Batch Normalization(FedBN),FedPA consistently ranks first or second across key performance metrics,particularly in accuracy,F1 score,and recall.Moreover,FedPA demonstrates notable efficiency,achieving the lowest average round time(≈2270 s)and minimal memory usage(≈645.58 MB),all without relying on GPU resources.These results highlight FedPA’s effectiveness in improving global model quality while reducing computational overhead,positioning it as a promising approach for real-world federated learning applications in resource-constrained environments.展开更多
基金Project supported by the Ministry of Education’s Supply and Demand Matching Employment and Education Project(Grant No.2024110776329)。
文摘An in-built N^(+)pocket electrically doped tunnel field-effect transistor(ED-TFET)-based biosensor has been reported for the first time.The proposed device begins with a PN junction structure with a control gate(CG)and two polarity gates(PG1 and PG2).Utilizing the polarity bias concept,a narrow N^(+)pocket is formed between the source and channel without the need for additional doping steps,achieved through biasing PG1 and PG2 at-1.2 V and 1.2 V,respectively.This method not only addresses issues related to doping control but also eliminates constraints associated with thermal budgets and simplifies the fabrication process compared to traditional TFETs.To facilitate biomolecule sensing within the device,a nanogap cavity is formed in the gate dielectric by selectively etching a section of the polarity gate dielectric layer toward the source side.The investigation into the presence of neutral and charged molecules within the cavities has been conducted by examining variations in the electrical properties of the proposed biosensor.Key characteristics assessed include drain current,energy band,and electric field distribution.The performance of the biosensor is measured using various metrics such as drain current(I_(DS)),subthreshold swing(SS),threshold voltage(V_(TH)),drain current ratio(I_(ON)/I_(OFF)).The proposed in-built N^(+)pocket ED-TFET-based biosensor reaches a peak sensitivity of 1.08×10~(13)for a neutral biomolecule in a completely filled nanogap with a dielectric constant of 12.Additionally,the effects of cavity geometry and different fill factors(FFs)on sensitivity are studied.
基金supported by the Deanship of Scientific Research at Umm Al-Qura University(Grant code:22UQU4331128DSR77).
文摘Objective:To investigate the relationship between triterpenoid saponin content and antioxidant,antimicrobial,and α-glucosidase inhibitory activities of 70%ethanolic,butanolic,aqueous,supernate and precipitate extracts of Juglans regia leaves.Methods:Triterpenoid saponins of different Juglans regia leaf extracts were measured by the vanillin method.Antioxidant activity was evaluated against DPPH and ABTS free radicals.We also assessed α-glucosidase inhibitory and antimicrobial activities of the leaf extracts.Pearson’s correlation coefficient was evaluated to determine the correlation between the saponin content and biological activities.Results:The butanolic extract was most effective against DPPH with an IC50of 6.63μg/mL,while the aqueous extract showed the highest scavenging activity against ABTS free radical with an IC50of 42.27μg/mL.Pearson’s correlation analysis indicated a strong negative correlation (r=-0.956) between DPPH radical scavenging activity (IC50) and the saponin content in the samples examined.In addition,the aqueous extract showed the best α-glucosidase inhibitory activity compared with other extracts.All the extracts had fair antibacterial activity against Bacillus subtilis,Escherichia coli,and Klebsiella pneumoniae except for the aqueous extract.Conclusions:Juglans regia extracts show potent antioxidant,antimicrobial,and α-glucosidase inhibitory activities.There is a correlation between saponin levels in Juglans regia leaf extracts and the studied activities.However,additional research is required to establish these relationships by identifying the specific saponin molecules responsible for these activities and elucidating their mechanisms of action.
文摘Objective:To evaluate the prevalence and types of complementary and alternative medicine(CAM)modalities among patients with cancer in Karachi,Pakistan.Methods:This descriptive cross-sectional study was conducted from March 2021 to December 2021.Five hundred patients with cancer were invited to participate in the study.Electronic databases,namely,Google scholar,Publons,EMBASE,PubMed,Chinese National Knowledge Infrastructure Database,and ResearchGate was used for questionnaire designed.The self-administered survey included questions on demographic characteristics,education level,socio-economic conditions and information about CAM therapies,prevalence,effectiveness,and common CAM modalities.Statistical analysis was conducted using SPSS software version 22.Results:Out of the 500 invited patients,433(86.6%)successfully completed and returned the questionnaires.In contrast to patients who were with younger,highly educated,professionally active,higher income,and had advanced cancer,time since diagnosis,type of treatment,cancer types and family history are significantly associated with CAM use.The results showed that 59.8%of the participants were acquainted with complementary and/or alternative medicine and considered safe owing to its natural ingredients.The prevalence of CAM usage among cancer patients was 40.9%and the most widely used CAM modality was herbal medicine(27.7%)and dietary supplements(28.8%).Patients used CAM as a complementary therapy to improve the morphological parameter(28.2%),strengthen the immune system(6.8%),and to decrease the side effects of conventional treatment(18.1%).Most of the respondents get the information regarding CAM therapy from the electronic media(43.2%)and the family members(48%)rather than healthcare personnel.Conclusions:Participants used CAM modalities along with the conventional health care practices.Further multicentre studies should be conducted to provide information regarding the usage of CAM therapies and their eventual benefits in patients with cancer.
基金funded by the project,“Design and implementation of real-time safety ensuring system in the indoor environment by applying machine learning techniques”.IRN:AP14971555.
文摘Video analytics is an integral part of surveillance cameras. Comparedto video analytics, audio analytics offers several benefits, includingless expensive equipment and upkeep expenses. Additionally, the volume ofthe audio datastream is substantially lower than the video camera datastream,especially concerning real-time operating systems, which makes it lessdemanding of the data channel’s bandwidth needs. For instance, automaticlive video streaming from the site of an explosion and gunshot to the policeconsole using audio analytics technologies would be exceedingly helpful forurban surveillance. Technologies for audio analytics may also be used toanalyze video recordings and identify occurrences. This research proposeda deep learning model based on the combination of convolutional neuralnetwork (CNN) and recurrent neural network (RNN) known as the CNNRNNapproach. The proposed model focused on automatically identifyingpulse sounds that indicate critical situations in audio sources. The algorithm’saccuracy ranged from 95% to 81% when classifying noises from incidents,including gunshots, explosions, shattered glass, sirens, cries, and dog barking.The proposed approach can be applied to provide security for citizens in openand closed locations, like stadiums, underground areas, shopping malls, andother places.
文摘Objective:To assess the acute and subacute toxicity as well as the phytochemical composition of two extracts and three fractions of Ammi majus L.Methods:The aqueous extracts were prepared separately by maceration for 48 h and by infusion for 1 h,while the fractions were prepared by the Soxhlet extractor,successively employing cyclohexane,ethyl acetate,and ethanol.The acute toxicity study was carried out in accordance with the OECD N°423 guideline at a single dose(2000 mg/kg)in mice for 14 days.The subacute toxicity study was performed by a daily oral administration of 250 mg/kg 2 for 10 d and 100 mg/kg doses for 28 d.Phytochemical screening was performed using staining and precipitation reactions,while the chemical characterization of some analytes was detected by HPLC-MS/MS analysis.Results:In the acute toxicity study,no signs of toxicity such as convulsion,salivation,diarrhea,sleep and coma were observed during 30 minutes and 14 days,so the lethal dose was higher than 2000 mg/kg for each extract and fraction.The subacute toxicity results showed that at a dose of 250 mg/kg,61.10%of the animals died and the rest developed morbidity.On the other hand,at a dose of 100 mg/kg,all the animals were still alive after 28 days,with no morbidity and the biochemical parameters were normal with no abnormalities in the liver,kidneys and pancreas.Phytochemical screening indicated the presence of flavonoids,tannins,coumarins,and free quinones and the absence of alkaloids and anthocyanins.Conclusions:The extracts and fractions of Ammi majus L.are not toxic in the short and long term with a varied chemical composition.Toxicological tests on animals other than rodents and in the long term(more than 28 days)are needed to further confirm the safety of Ammi majus extracts.
基金2024 Academic Research of Zhejiang Technical Institute of Economics:“Spillover Effects of Multimodal AI Agents on Green School Development”(Project No.:X2024038)2024-2025 Research and Creative Project,Department of Culture and Tourism:“The Application of Digital Information Technology in Safety Early Warning and Supervision of Cultural Relics in Zhejiang,China”(Project No.:2024KYY045)2024 General Research Project of Zhejiang Provincial Department of Education:“Empirical Research on Low-Carbon Economy Driving the Development of New Quality Productivity:A Case Study of Zhejiang Province”(Project No.:Y202456145)。
文摘The integration of Green Artificial Intelligence(AI)technologies into educational systems offers a promising avenue to enhance operational efficiency while addressing sustainability challenges.Through a rigorous three-phase methodology combining literature review,AI agent development,and participatory workshop-based case analysis,this paper highlights the pivotal role of AI agents,as applications of Green AI technologies,in driving transformative outcomes within schools.By directly improving self-learning efficiency and reducing learning costs for students,enhancing management and service efficiency,reducing labor costs for schools,as well as minimizing resource dependence for both teachers and students,AI agents create a foundation for sustainable operations.These direct effects generate positive spillover effects,cascading into broader outcomes,including innovation performance,economic efficiency,and environmental sustainability,aligning with the United Nations Sustainable Development Goals(SDGs).By presenting a comprehensive conceptual model,this study demonstrates the pathways through which Green AI contributes to sustainable development in education and emphasizes its critical role in bridging technological innovation with sustainability.This framework provides significant theoretical insights for further empirical research while offering actionable strategies for policymakers and educators to harness Green AI for building sustainable schools with a student-centered approach.
文摘Counterfeiting is still a pervasive global issue,affecting multiple industries and hindering industrial innovation,while causing substantial financial losses,reputational damage,and risks to consumer safety.From luxury goods and pharmaceuticals to electronics and automotive parts,counterfeit products infiltrate supply chains,leading to a loss of revenue for legitimate businesses and undermining consumer trust.Traditional anti-counterfeiting measures,such as holograms,serial numbers,and barcodes,have proven to be insufficient as counterfeiters continuously develop more sophisticated replication techniques.As a result,there is a growing need for more advanced,secure,and reliable methods to prevent counterfeiting.This paper presents a novel,holistic anti-counterfeiting platform that integrates Near Field Communication(NFC)-enabled mobile applications with blockchain technology to provide an innovative,secure,and consumer-friendly authentication mechanism.Our approach addresses key gaps in existing solutions by incorporating dynamic product identifiers,which make replication significantly more difficult.The system enables consumers to verify the authenticity of products instantly using their smartphones,enhancing transparency and trust in the supply chain.Blockchain technology plays a crucial role in our proposed solution by providing an immutable,decentralized ledger that records product authentication data.This ensures that product verification records cannot be tampered with or altered,adding a layer of security that is absent in conventional systems.Additionally,NFC technology enhances security by offering unique identification capabilities,enabling real-time product verification.To validate the effectiveness of the proposed system,real-world testing was conducted across different industries.The results demonstrated the platform’s ability to significantly reduce counterfeit products in the supply chain,offering businesses and consumers a more robust and reliable authentication method.By leveraging the combined strengths of blockchain and NFC,this solution represents a significant advancement in the fight against counterfeiting,ensuring enhanced security,transparency,and consumer trust.
基金2022 School-Level Topic“Research on the Spillover Effects of Digital Transformation of Universities on Establishing Green Schools”(No.X2022094)。
文摘The development of society and the advancement of science and technology have led to the widespread integration of digital transformation in the field of education.However,the current establishment of green schools faces various challenges,including non-environmental building facilities,high renovation costs,low organizational management efficiency,high energy consumption,outdated office tools,and insufficient environmental awareness among teachers and students.Through thorough research and analysis,it becomes evident that digital technology can play a pivotal role in addressing these challenges and contribute to all aspects of green school establishment.The incorporation of digital thinking concepts is essential for the construction of ecologically civilized campuses and inclusive innovation.The process of digital design and transformation proves instrumental in optimizing both software and hardware facilities within the campus,thereby reducing energy consumption.Simultaneously,comprehensive digital teaching management enhances overall efficiency in management and service delivery.Innovative digital teaching and learning models emerge as transformative tools,providing new avenues to create low-carbon,green classrooms for both teachers and students.By exploring the application of digital transformation in establishing green schools and examining the resulting spillover effects,valuable insights can be gained.These insights,in turn,serve as reference points for building diversified digital technology paths on campus and fostering the creation of green schools.
基金supported by the Airlangga University through Mandate Research Grant(Nos.216/UN3.15/PT/2022 and 217/UN3.15/PT/2022)。
文摘This paper presents a biosensor utilizing a whispering gallery mode(WGM)resonator characterized by azimuthal symmetry and crescent-shaped coatings of silver.The study investigates the impact of the coupling gap on the extinction ratio and Q-factor of the setup.The resonator is coated with silver in crescent shapes,ranging from 40 nm to 65 nm in thickness.Coupling is achieved with a silica waveguide,simulating the tapered fiber coupling method.Notably,the resonator exhibits a maximum sensitivity of 220 nm/RIU when coated with 55-nm-thick silver in conjunction with a 4-nm-thick layer of thiol-tethered deoxyribonucleic acid(DNA).This biosensor holds promise for biomolecule detection applications.
文摘Background Pediatric anemia is a pervasive public health issue in Asia,significantly impairing children’s growth,cognitive development,and future potential.This study evaluates trends,prevalence,and socio-economic disparities of pediatric anemia across Asia from 1990 to 2021,leveraging data from the Global Burden of Disease Study(GBD)2021 study.Methods Using estimated annual percentage change(EAPC)and Pearson’s correlation coefficient,geographic variations and temporal trends were analysed alongside associations between prevalence,years lived with disability(YLDs),and Socio-demographic index(SDI).Results The study reveals a modest overall decline in anemia prevalence by 11.9%,from 464.53 million cases in 1990 to 409.07 million in 2021.High-SDI regions such as East Asia achieved significant reductions(−71.36%),with countries like Singapore,the Republic of Korea,Seychelles,Qatar,and the United Arab Emirates(UAE)showing substantial progress.In stark contrast,low-SDI countries,including Yemen(108.34%)and Afghanistan(130.28%),along with Cambodia,India,and Pakistan,experienced alarming increases.Dietary iron deficiency was the dominant cause,followed by hemoglobinopathies and neglected tropical diseases.Females,particularly adolescents,and children under five faced disproportionate burdens,with prevalence rates in low-SDI regions exceeding 47,000 per 100,000 compared to<10,000 per 100,000 in high-SDI areas.Conclusions These findings emphasize profound regional and socio-economic inequalities in anemia burden.Urgent,evidence-based interventions are imperative,focusing on enhancing nutrition,expanding healthcare access,and integrating sex-sensitive strategies to address this multifaceted issue.Strengthened policies and targeted actions are critical to mitigating the burden and fostering health equity,particularly in vulnerable low-SDI regions.
文摘Graphene oxide(GO)is a 2D coating material used to improve fiber optics sensors’response to relative humidity.Microbottle resonators(MBRs)have garnered more attention as sensing media structures.An MBR with a 190μm diameter was coated with GO.Then,tapered fiber light coupling was used to investigate the relative humidity sensing performance in the range of 35—70%RH at 25℃.The MBR showed a higher Q factor before and after GO coating.The sensitivity of 0.115 dB/%RH was recorded with the 190μm GO-coated MBR sample compared to a sensitivity of 0.022 dB/%RH for the uncoated MBR sample.These results show that the MBR can be used in fiber optic sensing applications for environmental sensing.
文摘Federated learning is a decentralized model training paradigm with significant potential.However,the quality of Federated Network’s client updates can vary due to non-IID data distributions,leading to suboptimal global models.To address this issue,we propose a novel client selection strategy called FedPA(Performance-Based Federated Averaging).This proposed model selectively aggregates client updates based on a predefined performance threshold.Only clients whose local models achieve an F1 score of 70%or higher after training are included in the aggregation process.Clients below this threshold receive the updated global model but do not contribute their parameters.In this way,the low-performance clients are still in the process of learning and,after some rounds,will be able to contribute.If no client meets the performance threshold in a given round,the system falls back to standard FedAvg aggregation.This ensures the global model continues to improve even when most clients perform poorly.We evaluate FedPA on a subset of the MURA dataset for abnormality detection in radiographs of four bone types.Compared to baseline federated learning algorithms such as Federated Averaging(FedAvg),Federated Proximal(FedProx),Federated Stochastic Gradient Descent(FedSGD),and Federated Batch Normalization(FedBN),FedPA consistently ranks first or second across key performance metrics,particularly in accuracy,F1 score,and recall.Moreover,FedPA demonstrates notable efficiency,achieving the lowest average round time(≈2270 s)and minimal memory usage(≈645.58 MB),all without relying on GPU resources.These results highlight FedPA’s effectiveness in improving global model quality while reducing computational overhead,positioning it as a promising approach for real-world federated learning applications in resource-constrained environments.
