Intelligent fault diagnosis technology plays an indispensable role in ensuring the safety,stability,and efficiency of railway operations.However,existing studies have the following limitations.1)They are typical black-...Intelligent fault diagnosis technology plays an indispensable role in ensuring the safety,stability,and efficiency of railway operations.However,existing studies have the following limitations.1)They are typical black-box models that lacks interpretability as well as they fuse features by simply stacking them,overlooking the discrepancies in the importance of different features,which reduces the credibility and diagnosis accuracy of the models.2)They ignore the effects of potentially mistaken labels in the training datasets disrupting the ability of the models to learn the true data distribution,which degrades the generalization performance of intelligent diagnosis models,especially when the training samples are limited.To address the above items,an interpretable few-shot framework for fault diagnosis with noisy labels is proposed for train transmission systems.In the proposed framework,a feature extractor is constructed by stacked frequency band focus modules,which can capture signal features in different frequency bands and further adaptively concentrate on the features corresponding to the potential fault characteristic frequency.Then,according to prototypical network,a novel metric-based classifier is developed that is tolerant to mislabeled support samples in the case of limited samples.Besides,a new loss function is designed to decrease the impact of label mistakes in query datasets.Finally,fault simulation experiments of subway train transmission systems are designed and conducted,and the effectiveness as well as superiority of the proposed method are proved by ablation experiments and comparison with the existing methods.展开更多
The China National Institute of Standardization(CNIS)held the Academic Meeting on 20th Anniversary of China Energy Label in Beijing on June 27.The event took place during the 35th National Energy Conservation Publicit...The China National Institute of Standardization(CNIS)held the Academic Meeting on 20th Anniversary of China Energy Label in Beijing on June 27.The event took place during the 35th National Energy Conservation Publicity Week,which ran from June 23 to 29.展开更多
This study summarizes the examination data of registration labels for ordinary cosmetics in Beijing from May 2021 to April 2024.It analyzes and categorizes the issues identified during label evaluations,explores the u...This study summarizes the examination data of registration labels for ordinary cosmetics in Beijing from May 2021 to April 2024.It analyzes and categorizes the issues identified during label evaluations,explores the underlying causes,and proposes regulatory countermeasures and recommendations for registrants,regulatory authorities,and social organizations.The objective is to offer practical insights and regulatory guidance to support the enhancement of cosmetic registration and regulatory standards.展开更多
Since the 1970s,a series of international and national sources have supported the principle of accessibility,which slowly has become a statuary norm and a legislative obligation.Each country has implemented accessibil...Since the 1970s,a series of international and national sources have supported the principle of accessibility,which slowly has become a statuary norm and a legislative obligation.Each country has implemented accessibility through a singular policy.But in addition to the accessibility of a place or an activity,to inform about what is accessible is very important as well,and has not really taken off.Indeed,for disabled people,the difficulty lies not only with access to places and the use of resources,but also with the visibility of these resources.This means that information concerning accessibility has to be disclosed and provided effectively to disabled people,those involved with them and the relevant institutions.In different countries all over the world,many labels and pictograms have been created for this purpose and give information relating to accessibility.Using a socio-historical approach,we will present and analyze the different types of icons,symbols,pictograms and labels that have been put in place around the world and in France:what are they used for and for whom are they made?We will show that they are pointers which firstly reflect the diversity and range within the target group concerned by accessibility,and secondly the evolution of accessibility as a dynamic and ecological principle.展开更多
INTRODUCTION For a considerable time,psychiatry has grappled with how best to define its core diagnostic entities.1-3 Traditional psychiatric classification systems,predominantly the Diagnostic and Statistical Manual ...INTRODUCTION For a considerable time,psychiatry has grappled with how best to define its core diagnostic entities.1-3 Traditional psychiatric classification systems,predominantly the Diagnostic and Statistical Manual of Mental Disorders(DSM)and International Classification of Diseases(ICD),have long been the cornerstones of clinical psychiatry.These systems primarily characterise mental disorders through clusters of observable symptoms rather than underlying pathophysiological mechanisms,making few claims about aetiology or causal pathways.展开更多
Golgi apparatus(GA)-associated secretome runs through the endomembrane system and is critical for inter-and intracellular communication networks.However,achieving in situ dissection of the GA-associated secretome rema...Golgi apparatus(GA)-associated secretome runs through the endomembrane system and is critical for inter-and intracellular communication networks.However,achieving in situ dissection of the GA-associated secretome remains challenging owing to the scarcity of specific labeling methods.This work develops an aggregation-induced emission(AIE)luminogen-mediated photocatalytic proximity labeling strategy that allows profiling of the GA-associated secretome with high spatiotemporal precision.Leveraging an AIE luminogen-derived GA-targeting photocatalyst,this strategy achieves efficient labeling of proteins in minutes within the Golgi lumen upon light activation,which enables spatiotemporally resolved modification of histidine and tyrosine residues.We succeed in profiling secretome in both living HeLa cells and hard-to-transfect macrophage HMC3 cells,and a significant subset of GA-associated secretome with 80%specificity is determined,linking the distinct GA-associated secretory profiles to cellular characteristics.The method is further applied to proteome mapping of brain and bone metastatic lung cancer cells,which reveals the underlying roles the GA-associated secretome plays in extracellular matrix organization during metastasis.This work delivers a robust tool to break the dilemma of chemical labeling of GA-associated secretome in living cells,and provides mechanistic insights into secretion regulation at the subcellular level.展开更多
The study of target proteins is crucial for understanding molecular interactions and developing analytical platforms,therapeutic agents and functional tools.Herein,we present a novel nanoplatform activated by near-inf...The study of target proteins is crucial for understanding molecular interactions and developing analytical platforms,therapeutic agents and functional tools.Herein,we present a novel nanoplatform activated by near-infrared(NIR) light for triple-modal proteins study,which enabling target protein labeling,enrichment and visualization.Azido-naphthalimide-coated upconversion nanoparticles(UCNPs) serve as NIR light-responsive nanoplatforms,showing promising applications in studying interactions between various bioactive molecules and proteins in living systems.Under NIR light irradiation,azido-naphthalimides are activated by ultraviolet(UV) and blue light emitted from UCNPs and the resulting amino-naphthalimides intermediate not only crosslink nearby target proteins but also enable imaging performance.We demonstrate that this nanoplatform is capable of selective protein labeling and imaging in complex protein environments,achieving specific labeling and imaging of both intracellular and extracellular proteins in mammalian cells as well as bacteria.Furthermore,in vivo protein labeling has been achieved using this novel NIR light-activatable nanoplatform.This technique will open new avenues for discoveries and mechanistic interrogation in chemical biology.展开更多
Dear Editor,The long-term use of copper(Cu)fungicides to prevent downy mildew of vine led to the accumulation of Cu in vineyard topsoils(Komárek et al.,2010;Droz et al.,2021),which may alter the functioning and s...Dear Editor,The long-term use of copper(Cu)fungicides to prevent downy mildew of vine led to the accumulation of Cu in vineyard topsoils(Komárek et al.,2010;Droz et al.,2021),which may alter the functioning and sustainability of vineyard ecosystems(Cornu et al.,2022).展开更多
Astrocytes are the most abundant glial cells in the central nervous system.They perform a diverse array of functions,with a critical role in structural integrity,synapse formation,and neurotransmission.These cells exh...Astrocytes are the most abundant glial cells in the central nervous system.They perform a diverse array of functions,with a critical role in structural integrity,synapse formation,and neurotransmission.These cells exhibit substantial regional heterogeneity and display variable responses to different neurological diseases.Such diversity in astrocyte morphology and function is essential for understanding both normal brain function and the underlying mechanisms of neurological disorders.To investigate this heterogeneity,we developed a novel method for the selective and sparse labeling of astrocytes in various brain regions.This technique utilizes a dual adeno-associated virus system that allows for the expression of Cre recombinase and enhanced green fluorescent protein under the control of the glial fibrillary acidic protein(GfaABC1D)promoter.The system was tested in C57BL/6J mice and successfully labeled astrocytes across multiple brain regions.The method enabled the detailed visualization of individual astrocytes-including their intricate peripheral processes-through three-dimensional reconstructions from confocal microscopy images.Furthermore,the labeling efficiency of this dual adeno-associated virus technology was validated by examining astrocyte function in a spared nerve injury model and through chemogenetic modulation.This innovative approach holds great promise for future research because it enables a more comprehensive understanding of astrocyte variation not only in spared nerve injury but also in a broad spectrum of neurological diseases.The ability to selectively label and study astrocytes in different brain regions provides a powerful tool for exploring the complexities of these essential cells and their roles in physiological and pathological conditions.展开更多
Lateral flow immunoassays(LFIAs) have been developed rapidly in recent years and used in a wide range of application at point-of-care-testing(POCT),where small biomolecules can be conveniently examined on a test strip...Lateral flow immunoassays(LFIAs) have been developed rapidly in recent years and used in a wide range of application at point-of-care-testing(POCT),where small biomolecules can be conveniently examined on a test strip.Compared with other biochemical detection methods such as ELISA(enzyme linked immunosorbent assay) or mass spectrometry method,LFIAs have the advantages of low cost,easy operation and short time-consuming.However,it suffers from low sensitivity since conventional LFIA can only realize qualitative detection based on colorimetric signals.With the increasing demand for more accurate and sensitive determination,novel nanomaterials have been used as labels in LFIAs due to their unique advantages in physical and chemical properties.Colloidal gold,fluorescent nano particles,SERSactive nanomaterials,magnetic nanoparticles and carbon nanomaterials are utilized in LFIAs to produce different kinds of signals for quantitative or semi-quantitative detection.This review paper first gives a description of the LFIA principles,and then focuses on the state-of-the-art nanomaterial labelling technology in LFIAs.At last,the conclusion and outlook are given to inspire exploration of more advanced nanomaterials for the development of future LFIAs.展开更多
Radio frequency fingerprinting(RFF)is a remarkable lightweight authentication scheme to support rapid and scalable identification in the internet of things(IoT)systems.Deep learning(DL)is a critical enabler of RFF ide...Radio frequency fingerprinting(RFF)is a remarkable lightweight authentication scheme to support rapid and scalable identification in the internet of things(IoT)systems.Deep learning(DL)is a critical enabler of RFF identification by leveraging the hardware-level features.However,traditional supervised learning methods require huge labeled training samples.Therefore,how to establish a highperformance supervised learning model with few labels under practical application is still challenging.To address this issue,we in this paper propose a novel RFF semi-supervised learning(RFFSSL)model which can obtain a better performance with few meta labels.Specifically,the proposed RFFSSL model is constituted by a teacher-student network,in which the student network learns from the pseudo label predicted by the teacher.Then,the output of the student model will be exploited to improve the performance of teacher among the labeled data.Furthermore,a comprehensive evaluation on the accuracy is conducted.We derive about 50 GB real long-term evolution(LTE)mobile phone’s raw signal datasets,which is used to evaluate various models.Experimental results demonstrate that the proposed RFFSSL scheme can achieve up to 97%experimental testing accuracy over a noisy environment only with 10%labeled samples when training samples equal to 2700.展开更多
Multi-protocol label switching（MPLS） has the advantage of high efficiency in the second layer, which improves the performance of data packets routing. In this paper, a new structure to implement optical MPLS is prop...Multi-protocol label switching（MPLS） has the advantage of high efficiency in the second layer, which improves the performance of data packets routing. In this paper, a new structure to implement optical MPLS is proposed. We construct a code family for spectral-amplitude coding（SAC） labels in the optical MPLS networks. SAC labels are suitable for optical packet switching because they can be constructed and recognized quickly at each router. We use the label stacking to provide hierarchical routing to avoid swapping labels at each forwarding node and reduce system complexity. However, the phase-induced intensity noise（PIIN） appears due to the incoherent property of the light source when the stacked labels set makes the correlation decoding with the local node label,which degrades system performance.展开更多
Multimodal sentiment analysis utilizes multimodal data such as text,facial expressions and voice to detect people’s attitudes.With the advent of distributed data collection and annotation,we can easily obtain and sha...Multimodal sentiment analysis utilizes multimodal data such as text,facial expressions and voice to detect people’s attitudes.With the advent of distributed data collection and annotation,we can easily obtain and share such multimodal data.However,due to professional discrepancies among annotators and lax quality control,noisy labels might be introduced.Recent research suggests that deep neural networks(DNNs)will overfit noisy labels,leading to the poor performance of the DNNs.To address this challenging problem,we present a Multimodal Robust Meta Learning framework(MRML)for multimodal sentiment analysis to resist noisy labels and correlate distinct modalities simultaneously.Specifically,we propose a two-layer fusion net to deeply fuse different modalities and improve the quality of the multimodal data features for label correction and network training.Besides,a multiple meta-learner(label corrector)strategy is proposed to enhance the label correction approach and prevent models from overfitting to noisy labels.We conducted experiments on three popular multimodal datasets to verify the superiority of ourmethod by comparing it with four baselines.展开更多
An indirect competitive fluorescence immunoassay using a DNA/dye conjugate as antibody multiple labels was developed on 96-well plates for the identification and quantification of 2,2＇,4,4＇-tetrabromodiphenyl ether ...An indirect competitive fluorescence immunoassay using a DNA/dye conjugate as antibody multiple labels was developed on 96-well plates for the identification and quantification of 2,2＇,4,4＇-tetrabromodiphenyl ether （BDE-47） in aqueous samples. A hapten, 2,4,2＇- tribromodiphenyl ether-4＇-aldehyde, was synthesized, and was conjugated to bovine serum albumin to form a coating antigen. Specific recognition of the antigen by anti-PBDE antiserum was confirmed by a surface plasmon resonance measurement. In the immunoassay, the coating antigen was adsorbed on a 96-well plate first, and a sample, antiserum and biotinylated goat anti-rabbit secondary antibody were then added and reacted sequentially. A biotinylated, double-stranded DNA with 219 base pairs was attached to the secondary antibody by using streptavidin as a molecular bridge. In situ multiple labeling of the antibody was accomplished after addition of a DNA-binding fluorescent dye, SYBR Green I. The working range of the immunoassay for the BDE-47 standard was 3.1-390 ~tg/L, with an IC50 value of 15.6 Ixg/L. The calculated LOD of the immunoassay is 0.73 Ixg/L. The immunoassay demonstrated relatively high selectivity for BDE-47, showing very low cross-reactivity （〈 3%） with BDE-15, BDE-153 and BDE-209. With a spiked river water sample containing 50 Izg/L BDE-47, quantification by the immunoassay was 41.9 ~tg/L, which compared well with the standard GC-ECD method （45.7 Ixg/L）. The developed immunoassay provides a rapid screening tool for polybrominated diphenyl ethers in environmental samples.展开更多
The demand for Electronic Shelf Labels(ESL),according to the Internet of Things(IoT)paradigm,is expected to grow considerably in the immediate future.Various wireless communication standards are currently contending t...The demand for Electronic Shelf Labels(ESL),according to the Internet of Things(IoT)paradigm,is expected to grow considerably in the immediate future.Various wireless communication standards are currently contending to gain an edge over the competition and provide the massive connectivity that will be required by a world in which everyday objects are expected to communicate with each other.Low-Power Wide-Area Networks(LPWANs)are continuously gaining momentum among these standards,mainly thanks to their ability to provide long-range coverage to devices,exploiting license-free frequency bands.The main theme of this work is one of the most prominent LPWAN technologies,LoRa.The purpose of this research is to provide long-range,less intermediate node,less energy dissipation,and a cheaper ESL system.Much research has already been done on designing the LoRaWAN network,not capable to make a reliable network.LoRa is using different gateways to transmit the same data,collision,data jamming,and data repetition are expected.According to the transmission behavior of LoRa,50%of data is lost.In this paper,the Improved Backoff Algorithm with synchronization technique is used to decrease overlapping and data loss.Besides,the improved Adaptive Data Rate algorithm(ADR)avoids the collision in concurrently transmitted data by using different Spreading Factors(SFs).The allocation of SF has the main role in designing LoRa based network to minimize the impact of the intra-interference,cost function,and Euclidean distance.For this purpose,the K-means machine learning algorithm is used for clustering.The data rate model is using an intra-slicing technique based on Maximum Likelihood Estimation(MLE).The data rate model includes three critical communication slices,High Critical Communication(HCC),Medium Critical Communication(MCC),and Low Critical Communication(LCC),having the specified number of End devices(EDs),payload budget delay,and data rate.Finally,different combinations of gateways are used to build ESL for 200 electronic shelf labels.展开更多
This paper presents a novel algorithm for an extreme form of weak label learning, in which only one of all relevant labels is given for each training sample. Using genetic algorithm, all of the labels in the training ...This paper presents a novel algorithm for an extreme form of weak label learning, in which only one of all relevant labels is given for each training sample. Using genetic algorithm, all of the labels in the training set are optimally divided into several non-overlapping groups to maximize the label distinguishability in every group. Multiple classifiers are trained separately and ensembled for label predictions. Experimental results show significant improvement over previous weak label learning algorithms.展开更多
This study aimed to evaluate the features related to consumers’ reading nutritional labels in a city in the interior of the São Paulo State, Brazil. A questionnaire was answered by 100 consumers of a supermarket...This study aimed to evaluate the features related to consumers’ reading nutritional labels in a city in the interior of the São Paulo State, Brazil. A questionnaire was answered by 100 consumers of a supermarket chain, sociodemographic information and data related to label reading habits were collected. Tables with percentage values and bar graphs were used. Chi-square tests and logistic regression models were performed to verify the association between the variables and the label reading habits. The factors that showed significant associations with the reading labels were gender, ease to understand the labels and access to their information (p 0.10). People who had already read labels reported to have more difficulty to understand the information contained on them, and people who had already received instructions on the labels were three and a half times more likely to read the instructions contained on them than those who hadn’t received any guidance. This study points to the need to expand the disclosure to consumers about the contents present on the labels, through more accessible language, so that the labels fulfill their role to instruct consumers in their choices.展开更多
In order to improve the performance of classifiers in subjective domains, this paper defines a metric to measure the quality of the subjectively labelled training data (QoSTD) by means of K-means clustering. Then, the...In order to improve the performance of classifiers in subjective domains, this paper defines a metric to measure the quality of the subjectively labelled training data (QoSTD) by means of K-means clustering. Then, the QoSTD is used as a weight of the predicted class scores to adjust the likelihoods of instances. Moreover, two measurements are defined to assess the performance of the classifiers trained by the subjective labelled data. The binary classifiers of Traditional Chinese Medicine (TCM) Zhengs are trained and retrained by the real-world data set, utilizing the support vector machine (SVM) and the discrimination analysis (DA) models, so as to verify the effectiveness of the proposed method. The experimental results show that the consistency of likelihoods of instances with the corresponding observations is increased notable for the classes, especially in the cases with the relatively low QoSTD training data set. The experimental results also indicate the solution how to eliminate the miss-labelled instances from the training data set to re-train the classifiers in the subjective domains.展开更多
Proposed is a novel optical code(OC) label switching scheme in which an optical label is constructed by multiple parallel optical codes.The performances of splitting loss and BER are simulated and analyzed.Simulation ...Proposed is a novel optical code(OC) label switching scheme in which an optical label is constructed by multiple parallel optical codes.The performances of splitting loss and BER are simulated and analyzed.Simulation results show that the proposed label can be correctly recognized to perform packet switching.Compared with reported schemes using one OC as a label,the splitting loss in our proposal is lowered.展开更多
基金supported in part by the National Key R&D Program of China under Grant 2022YFB4300601in part by the State Key Laboratory of Advanced Rail Autonomous Operation under Grant RAO2023ZZ003.
文摘Intelligent fault diagnosis technology plays an indispensable role in ensuring the safety,stability,and efficiency of railway operations.However,existing studies have the following limitations.1)They are typical black-box models that lacks interpretability as well as they fuse features by simply stacking them,overlooking the discrepancies in the importance of different features,which reduces the credibility and diagnosis accuracy of the models.2)They ignore the effects of potentially mistaken labels in the training datasets disrupting the ability of the models to learn the true data distribution,which degrades the generalization performance of intelligent diagnosis models,especially when the training samples are limited.To address the above items,an interpretable few-shot framework for fault diagnosis with noisy labels is proposed for train transmission systems.In the proposed framework,a feature extractor is constructed by stacked frequency band focus modules,which can capture signal features in different frequency bands and further adaptively concentrate on the features corresponding to the potential fault characteristic frequency.Then,according to prototypical network,a novel metric-based classifier is developed that is tolerant to mislabeled support samples in the case of limited samples.Besides,a new loss function is designed to decrease the impact of label mistakes in query datasets.Finally,fault simulation experiments of subway train transmission systems are designed and conducted,and the effectiveness as well as superiority of the proposed method are proved by ablation experiments and comparison with the existing methods.
文摘The China National Institute of Standardization(CNIS)held the Academic Meeting on 20th Anniversary of China Energy Label in Beijing on June 27.The event took place during the 35th National Energy Conservation Publicity Week,which ran from June 23 to 29.
文摘This study summarizes the examination data of registration labels for ordinary cosmetics in Beijing from May 2021 to April 2024.It analyzes and categorizes the issues identified during label evaluations,explores the underlying causes,and proposes regulatory countermeasures and recommendations for registrants,regulatory authorities,and social organizations.The objective is to offer practical insights and regulatory guidance to support the enhancement of cosmetic registration and regulatory standards.
文摘Since the 1970s,a series of international and national sources have supported the principle of accessibility,which slowly has become a statuary norm and a legislative obligation.Each country has implemented accessibility through a singular policy.But in addition to the accessibility of a place or an activity,to inform about what is accessible is very important as well,and has not really taken off.Indeed,for disabled people,the difficulty lies not only with access to places and the use of resources,but also with the visibility of these resources.This means that information concerning accessibility has to be disclosed and provided effectively to disabled people,those involved with them and the relevant institutions.In different countries all over the world,many labels and pictograms have been created for this purpose and give information relating to accessibility.Using a socio-historical approach,we will present and analyze the different types of icons,symbols,pictograms and labels that have been put in place around the world and in France:what are they used for and for whom are they made?We will show that they are pointers which firstly reflect the diversity and range within the target group concerned by accessibility,and secondly the evolution of accessibility as a dynamic and ecological principle.
文摘INTRODUCTION For a considerable time,psychiatry has grappled with how best to define its core diagnostic entities.1-3 Traditional psychiatric classification systems,predominantly the Diagnostic and Statistical Manual of Mental Disorders(DSM)and International Classification of Diseases(ICD),have long been the cornerstones of clinical psychiatry.These systems primarily characterise mental disorders through clusters of observable symptoms rather than underlying pathophysiological mechanisms,making few claims about aetiology or causal pathways.
基金support from the National Key R&D Program of China(2023YFA0913902)the National Natural Science Foundation of China(32088101,22074140,and 22474136)the Dalian Institute of Chemical Physics,Chinese Academy of Sciences(DICP-I202316).
文摘Golgi apparatus(GA)-associated secretome runs through the endomembrane system and is critical for inter-and intracellular communication networks.However,achieving in situ dissection of the GA-associated secretome remains challenging owing to the scarcity of specific labeling methods.This work develops an aggregation-induced emission(AIE)luminogen-mediated photocatalytic proximity labeling strategy that allows profiling of the GA-associated secretome with high spatiotemporal precision.Leveraging an AIE luminogen-derived GA-targeting photocatalyst,this strategy achieves efficient labeling of proteins in minutes within the Golgi lumen upon light activation,which enables spatiotemporally resolved modification of histidine and tyrosine residues.We succeed in profiling secretome in both living HeLa cells and hard-to-transfect macrophage HMC3 cells,and a significant subset of GA-associated secretome with 80%specificity is determined,linking the distinct GA-associated secretory profiles to cellular characteristics.The method is further applied to proteome mapping of brain and bone metastatic lung cancer cells,which reveals the underlying roles the GA-associated secretome plays in extracellular matrix organization during metastasis.This work delivers a robust tool to break the dilemma of chemical labeling of GA-associated secretome in living cells,and provides mechanistic insights into secretion regulation at the subcellular level.
基金supported by the National Natural Science Foundation of China (No.22007008)the LiaoNing Revitalization Talents Program (No.XLYC1907021)the Fundamental Research Funds for the Central Universities (Nos.DUT23YG120,DUT19RC(3)009)。
文摘The study of target proteins is crucial for understanding molecular interactions and developing analytical platforms,therapeutic agents and functional tools.Herein,we present a novel nanoplatform activated by near-infrared(NIR) light for triple-modal proteins study,which enabling target protein labeling,enrichment and visualization.Azido-naphthalimide-coated upconversion nanoparticles(UCNPs) serve as NIR light-responsive nanoplatforms,showing promising applications in studying interactions between various bioactive molecules and proteins in living systems.Under NIR light irradiation,azido-naphthalimides are activated by ultraviolet(UV) and blue light emitted from UCNPs and the resulting amino-naphthalimides intermediate not only crosslink nearby target proteins but also enable imaging performance.We demonstrate that this nanoplatform is capable of selective protein labeling and imaging in complex protein environments,achieving specific labeling and imaging of both intracellular and extracellular proteins in mammalian cells as well as bacteria.Furthermore,in vivo protein labeling has been achieved using this novel NIR light-activatable nanoplatform.This technique will open new avenues for discoveries and mechanistic interrogation in chemical biology.
基金financially supported by the Bordeaux Wine Interprofessional Council(French acronym CIVB)in the framework of the EXTRACUIVRE projectby the French National Research Institute for Agriculture,Food and Environment(INRAE)in the framework of the COPOFTEA projectpartially supported by the TSU Program Priority 2030,Russia。
文摘Dear Editor,The long-term use of copper(Cu)fungicides to prevent downy mildew of vine led to the accumulation of Cu in vineyard topsoils(Komárek et al.,2010;Droz et al.,2021),which may alter the functioning and sustainability of vineyard ecosystems(Cornu et al.,2022).
基金National Natural Science Foundation of China,No.32271148(to JW)the National Key Research and the Development Program of China,No.2023M740625(to ML)+1 种基金the Natural Science Foundation of Guangdong Province,Nos.2021B1515120050(to HW)and 2023A1515110782(to ML)and Key R&D Program of Ningxia Hui Autonomous Region,No.2024BEG02027(to JW).
文摘Astrocytes are the most abundant glial cells in the central nervous system.They perform a diverse array of functions,with a critical role in structural integrity,synapse formation,and neurotransmission.These cells exhibit substantial regional heterogeneity and display variable responses to different neurological diseases.Such diversity in astrocyte morphology and function is essential for understanding both normal brain function and the underlying mechanisms of neurological disorders.To investigate this heterogeneity,we developed a novel method for the selective and sparse labeling of astrocytes in various brain regions.This technique utilizes a dual adeno-associated virus system that allows for the expression of Cre recombinase and enhanced green fluorescent protein under the control of the glial fibrillary acidic protein(GfaABC1D)promoter.The system was tested in C57BL/6J mice and successfully labeled astrocytes across multiple brain regions.The method enabled the detailed visualization of individual astrocytes-including their intricate peripheral processes-through three-dimensional reconstructions from confocal microscopy images.Furthermore,the labeling efficiency of this dual adeno-associated virus technology was validated by examining astrocyte function in a spared nerve injury model and through chemogenetic modulation.This innovative approach holds great promise for future research because it enables a more comprehensive understanding of astrocyte variation not only in spared nerve injury but also in a broad spectrum of neurological diseases.The ability to selectively label and study astrocytes in different brain regions provides a powerful tool for exploring the complexities of these essential cells and their roles in physiological and pathological conditions.
基金financial support from the National Natural Science Foundation of China(51802060)Shenzhen Science and Technology Program(Grant No.:KQTD20170809110344233)+1 种基金Shenzhen Bay Laboratory(SZBL2019062801005)Natural Science Foundation of Guangdong Province(No.2019A1515010762)。
文摘Lateral flow immunoassays(LFIAs) have been developed rapidly in recent years and used in a wide range of application at point-of-care-testing(POCT),where small biomolecules can be conveniently examined on a test strip.Compared with other biochemical detection methods such as ELISA(enzyme linked immunosorbent assay) or mass spectrometry method,LFIAs have the advantages of low cost,easy operation and short time-consuming.However,it suffers from low sensitivity since conventional LFIA can only realize qualitative detection based on colorimetric signals.With the increasing demand for more accurate and sensitive determination,novel nanomaterials have been used as labels in LFIAs due to their unique advantages in physical and chemical properties.Colloidal gold,fluorescent nano particles,SERSactive nanomaterials,magnetic nanoparticles and carbon nanomaterials are utilized in LFIAs to produce different kinds of signals for quantitative or semi-quantitative detection.This review paper first gives a description of the LFIA principles,and then focuses on the state-of-the-art nanomaterial labelling technology in LFIAs.At last,the conclusion and outlook are given to inspire exploration of more advanced nanomaterials for the development of future LFIAs.
基金supported by Innovation Talents Promotion Program of Shaanxi Province,China(No.2021TD08)。
文摘Radio frequency fingerprinting(RFF)is a remarkable lightweight authentication scheme to support rapid and scalable identification in the internet of things(IoT)systems.Deep learning(DL)is a critical enabler of RFF identification by leveraging the hardware-level features.However,traditional supervised learning methods require huge labeled training samples.Therefore,how to establish a highperformance supervised learning model with few labels under practical application is still challenging.To address this issue,we in this paper propose a novel RFF semi-supervised learning(RFFSSL)model which can obtain a better performance with few meta labels.Specifically,the proposed RFFSSL model is constituted by a teacher-student network,in which the student network learns from the pseudo label predicted by the teacher.Then,the output of the student model will be exploited to improve the performance of teacher among the labeled data.Furthermore,a comprehensive evaluation on the accuracy is conducted.We derive about 50 GB real long-term evolution(LTE)mobile phone’s raw signal datasets,which is used to evaluate various models.Experimental results demonstrate that the proposed RFFSSL scheme can achieve up to 97%experimental testing accuracy over a noisy environment only with 10%labeled samples when training samples equal to 2700.
文摘Multi-protocol label switching（MPLS） has the advantage of high efficiency in the second layer, which improves the performance of data packets routing. In this paper, a new structure to implement optical MPLS is proposed. We construct a code family for spectral-amplitude coding（SAC） labels in the optical MPLS networks. SAC labels are suitable for optical packet switching because they can be constructed and recognized quickly at each router. We use the label stacking to provide hierarchical routing to avoid swapping labels at each forwarding node and reduce system complexity. However, the phase-induced intensity noise（PIIN） appears due to the incoherent property of the light source when the stacked labels set makes the correlation decoding with the local node label,which degrades system performance.
基金supported by STI 2030-Major Projects 2021ZD0200400National Natural Science Foundation of China(62276233 and 62072405)Key Research Project of Zhejiang Province(2023C01048).
文摘Multimodal sentiment analysis utilizes multimodal data such as text,facial expressions and voice to detect people’s attitudes.With the advent of distributed data collection and annotation,we can easily obtain and share such multimodal data.However,due to professional discrepancies among annotators and lax quality control,noisy labels might be introduced.Recent research suggests that deep neural networks(DNNs)will overfit noisy labels,leading to the poor performance of the DNNs.To address this challenging problem,we present a Multimodal Robust Meta Learning framework(MRML)for multimodal sentiment analysis to resist noisy labels and correlate distinct modalities simultaneously.Specifically,we propose a two-layer fusion net to deeply fuse different modalities and improve the quality of the multimodal data features for label correction and network training.Besides,a multiple meta-learner(label corrector)strategy is proposed to enhance the label correction approach and prevent models from overfitting to noisy labels.We conducted experiments on three popular multimodal datasets to verify the superiority of ourmethod by comparing it with four baselines.
基金supported by the Chinese Academy of Sciences (No. KSSCX2-YW-G-059)the National Hi-Tech Research and Development Program of China (No.2007AA06A407)the National Natural Science Foundation of China (No. 20825519, 20890112, 20921063)
文摘An indirect competitive fluorescence immunoassay using a DNA/dye conjugate as antibody multiple labels was developed on 96-well plates for the identification and quantification of 2,2＇,4,4＇-tetrabromodiphenyl ether （BDE-47） in aqueous samples. A hapten, 2,4,2＇- tribromodiphenyl ether-4＇-aldehyde, was synthesized, and was conjugated to bovine serum albumin to form a coating antigen. Specific recognition of the antigen by anti-PBDE antiserum was confirmed by a surface plasmon resonance measurement. In the immunoassay, the coating antigen was adsorbed on a 96-well plate first, and a sample, antiserum and biotinylated goat anti-rabbit secondary antibody were then added and reacted sequentially. A biotinylated, double-stranded DNA with 219 base pairs was attached to the secondary antibody by using streptavidin as a molecular bridge. In situ multiple labeling of the antibody was accomplished after addition of a DNA-binding fluorescent dye, SYBR Green I. The working range of the immunoassay for the BDE-47 standard was 3.1-390 ~tg/L, with an IC50 value of 15.6 Ixg/L. The calculated LOD of the immunoassay is 0.73 Ixg/L. The immunoassay demonstrated relatively high selectivity for BDE-47, showing very low cross-reactivity （〈 3%） with BDE-15, BDE-153 and BDE-209. With a spiked river water sample containing 50 Izg/L BDE-47, quantification by the immunoassay was 41.9 ~tg/L, which compared well with the standard GC-ECD method （45.7 Ixg/L）. The developed immunoassay provides a rapid screening tool for polybrominated diphenyl ethers in environmental samples.
基金This work is supported by the National Natural Science Foundation of China(61702020)Beijing Natural Science Foundation(4172013)Beijing Natural Science Foundation-Haidian Primitive Innovation Joint Fund(L182007).
文摘The demand for Electronic Shelf Labels(ESL),according to the Internet of Things(IoT)paradigm,is expected to grow considerably in the immediate future.Various wireless communication standards are currently contending to gain an edge over the competition and provide the massive connectivity that will be required by a world in which everyday objects are expected to communicate with each other.Low-Power Wide-Area Networks(LPWANs)are continuously gaining momentum among these standards,mainly thanks to their ability to provide long-range coverage to devices,exploiting license-free frequency bands.The main theme of this work is one of the most prominent LPWAN technologies,LoRa.The purpose of this research is to provide long-range,less intermediate node,less energy dissipation,and a cheaper ESL system.Much research has already been done on designing the LoRaWAN network,not capable to make a reliable network.LoRa is using different gateways to transmit the same data,collision,data jamming,and data repetition are expected.According to the transmission behavior of LoRa,50%of data is lost.In this paper,the Improved Backoff Algorithm with synchronization technique is used to decrease overlapping and data loss.Besides,the improved Adaptive Data Rate algorithm(ADR)avoids the collision in concurrently transmitted data by using different Spreading Factors(SFs).The allocation of SF has the main role in designing LoRa based network to minimize the impact of the intra-interference,cost function,and Euclidean distance.For this purpose,the K-means machine learning algorithm is used for clustering.The data rate model is using an intra-slicing technique based on Maximum Likelihood Estimation(MLE).The data rate model includes three critical communication slices,High Critical Communication(HCC),Medium Critical Communication(MCC),and Low Critical Communication(LCC),having the specified number of End devices(EDs),payload budget delay,and data rate.Finally,different combinations of gateways are used to build ESL for 200 electronic shelf labels.
基金Supported by the National Natural Science Foundation of China(61672433)the Fundamental Research Fund for Shenzhen Science and Technology Innovation Committee(201703063000511,201703063000517)+1 种基金the National Cryptography Development Fund(MMJJ20170210)the Science and Technology Project of State Grid Corporation of China(522722180007)
文摘This paper presents a novel algorithm for an extreme form of weak label learning, in which only one of all relevant labels is given for each training sample. Using genetic algorithm, all of the labels in the training set are optimally divided into several non-overlapping groups to maximize the label distinguishability in every group. Multiple classifiers are trained separately and ensembled for label predictions. Experimental results show significant improvement over previous weak label learning algorithms.
文摘This study aimed to evaluate the features related to consumers’ reading nutritional labels in a city in the interior of the São Paulo State, Brazil. A questionnaire was answered by 100 consumers of a supermarket chain, sociodemographic information and data related to label reading habits were collected. Tables with percentage values and bar graphs were used. Chi-square tests and logistic regression models were performed to verify the association between the variables and the label reading habits. The factors that showed significant associations with the reading labels were gender, ease to understand the labels and access to their information (p 0.10). People who had already read labels reported to have more difficulty to understand the information contained on them, and people who had already received instructions on the labels were three and a half times more likely to read the instructions contained on them than those who hadn’t received any guidance. This study points to the need to expand the disclosure to consumers about the contents present on the labels, through more accessible language, so that the labels fulfill their role to instruct consumers in their choices.
文摘In order to improve the performance of classifiers in subjective domains, this paper defines a metric to measure the quality of the subjectively labelled training data (QoSTD) by means of K-means clustering. Then, the QoSTD is used as a weight of the predicted class scores to adjust the likelihoods of instances. Moreover, two measurements are defined to assess the performance of the classifiers trained by the subjective labelled data. The binary classifiers of Traditional Chinese Medicine (TCM) Zhengs are trained and retrained by the real-world data set, utilizing the support vector machine (SVM) and the discrimination analysis (DA) models, so as to verify the effectiveness of the proposed method. The experimental results show that the consistency of likelihoods of instances with the corresponding observations is increased notable for the classes, especially in the cases with the relatively low QoSTD training data set. The experimental results also indicate the solution how to eliminate the miss-labelled instances from the training data set to re-train the classifiers in the subjective domains.
基金National Natural Science Foundation of China(60577045 and 60677004)Doctoral Subject Foundation,State Education Ministry(20050013002)+1 种基金Program for New Century Excellent Talents in University( NECT-07 -0111)Scientific Research Foundation for the Returned Overseas Chinese Scholars,StateEducation Ministry
文摘Proposed is a novel optical code(OC) label switching scheme in which an optical label is constructed by multiple parallel optical codes.The performances of splitting loss and BER are simulated and analyzed.Simulation results show that the proposed label can be correctly recognized to perform packet switching.Compared with reported schemes using one OC as a label,the splitting loss in our proposal is lowered.
