This research implements a random dot kinematogram(RDK)using virtual reality(VR)and analyzes the results based on normal subjects.Visual motion perception is one of visual functions localized to a specific cortical ar...This research implements a random dot kinematogram(RDK)using virtual reality(VR)and analyzes the results based on normal subjects.Visual motion perception is one of visual functions localized to a specific cortical area,the human motion perception area(human analogue for the middle temporal/middle superior temporal area)located in the parieto–occipito–temporal junction of the human brain.The RDK measures visual motion perception capabilities.The stimuli in conventional RDK methods are presented using a monitor screen,so these devices require a spacious dark room for installation and use.Recently,VR technology has been implemented in different medical domains.The test method proposed in this study include a VR-based RDK that can independently measure human motion perception abilities without any spatial constraints via a VR head-mounted display.Subsequently,the VR-based RDK was implemented,and the visual perception abilities of the normal subjects were measured based on varying coherences.In both screen-and VR-based RDK tests,the easier the stimulus is,the higher the correct answer rate and the shorter the reaction time.No significant differences in coherence thresholds were observed between the two test methods.The VRbased RDK proposed in this study can be used as a diagnosis tool for visual motion perception and neurodegenerative disorders affecting the posterior region of the brain.展开更多
Photothermal conversion-based quantitative polymerase chain reaction(qPCR)is a fast,sensitive,and accurate method to diagnose infectious diseases.However,they have bottlenecks in test throughput scalability,cumbersome...Photothermal conversion-based quantitative polymerase chain reaction(qPCR)is a fast,sensitive,and accurate method to diagnose infectious diseases.However,they have bottlenecks in test throughput scalability,cumbersome oil cover,and a lack of multi-target capability.Here,the authors present an infectious disease diagnostic device with rapid photothermal conversion-based efficient reverse transcription(RT)-qPCR assays on a multi-target chip(idreamqPCR).The authors innovate an off-axis mirror-based three-channel fluorescence intensity measurement method,enabling concurrent non-contact temperature control of 16 mini-well reaction chambers for qPCRs without the necessity of actuating parts.A transparent adhesive film on a graphite mixed polydimethylsiloxane(PDMS)-based PCR chip with mini-wells avoids contamination and bubbles to achieve 16 RT-qPCRs(40 photothermal cycles)within 17 min.Finally,idream-qPCR is validated by amplifying severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)N172 bp,RdRP 100 bp,and E 113 bp genes using Fluorescein amidites(FAM),Carboxytetramethylrhodamine(TAMRA),and Cyanine5(CY5)fluorescent dyes,respectively,with 102.5%efficiency and a limit-of-detection(LoD)equivalent to 0.85 copies/μL.idream-qPCR can be efficiently used to prevent the spread of infectious diseases.展开更多
Since the onset of the HIV epidemic,assessing CD4+T-cells has become a routine procedure for evaluating immune deficiency,with flow cytometry established as the gold standard.Over time,various strategies and platforms...Since the onset of the HIV epidemic,assessing CD4+T-cells has become a routine procedure for evaluating immune deficiency,with flow cytometry established as the gold standard.Over time,various strategies and platforms have been introduced to improve CD4+cell enumeration,aiming to enhance the performance of diagnostic devices and bring the service closer to patients.These advancements are particularly critical for low-resource settings and point-of-care applications,where the excellent performance of flow cytometry is hindered by its unsuitability in such environments.This work presents an innovative electrochemical microfluidic device that,with further development,could be applied for HIV management in low resource settings.The setup integrates an electrochemical sensor within a PDMS microfluidic structure,allowing for on-chip electrode functionalization and cell detection.Using electrochemical impedance spectroscopy,the biosensor demonstrates a linear detection range from 1.25×105 to 2×106 cells/mL,with a detection limit of 1.41×105 cells/mL for CD4+cells isolated from blood samples,aligning with clinical ranges for both healthy and HIV+patients.The biosensor shows specificity towards CD4+cells with negligible response to monocytes,neutrophils,and bovine serum albumin.Its integration with a microfluidic chip for sensor fabrication and cell detection,compact size,minimal manual handling,ease of fabrication,electrochemical detection capability,and potential for multiplexing together with the detection range make the device particularly advantageous for use in low-resource settings,standing out among other devices described in the literature.This study also investigates the integration of a microfluidic Dean Flow Fractionation(DFF)chip for cell separation.展开更多
Heavy-duty diesel vehicles are important sources of urban nitrogen oxides(NOx)in actual applications for environmental compliance,emitting more than 80%of NOx and more than 90%of particulate matter(PM)in total vehicle...Heavy-duty diesel vehicles are important sources of urban nitrogen oxides(NOx)in actual applications for environmental compliance,emitting more than 80%of NOx and more than 90%of particulate matter(PM)in total vehicle emissions.The detection and control of heavy-duty diesel emissions are critical for protecting public health.Currently,vehicles on the road must be regularly tested,every six months or once a year,to filter out high-emission mobile sources at vehicle inspection stations.However,it is difficult to effectively screen high-emission vehicles in time with a long interval between annual inspections,and the fixed threshold cannot adapt to the dynamic changes of vehicle driving conditions.An on-board diagnostic device(OBD)is installed inside the vehicle and can record the vehicle’s emission data in real time.In this paper,we propose a temporal optimization long short-term memory(LSTM)and adaptive dynamic threshold approach to identify heavy-duty high-emitters by using OBD data,which can continuously track and record the emission status in real time.First,a temporal optimization LSTM emission prediction model is established to solve the attention bias discrepancy problem on time steps that is caused by the large number of OBD data streams in practice.Then,the concentration prediction error sequence is detected and distinguished from the anomalous emission contexts using flexible criteria,calculated by an adaptive dynamic threshold with changing driving conditions.Finally,a similarity metric strategy for the time series is introduced to correct some pseudo anomalous results.Experiments on three real OBD time-series emission datasets demonstrate that our method can achieve high accuracy anomalous emission identification.展开更多
基金This work was supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(Nos.2019R1F1A1062752 and 2019R1C1C1006539)and was supported by the Soonchunhyang University Research Fund.
文摘This research implements a random dot kinematogram(RDK)using virtual reality(VR)and analyzes the results based on normal subjects.Visual motion perception is one of visual functions localized to a specific cortical area,the human motion perception area(human analogue for the middle temporal/middle superior temporal area)located in the parieto–occipito–temporal junction of the human brain.The RDK measures visual motion perception capabilities.The stimuli in conventional RDK methods are presented using a monitor screen,so these devices require a spacious dark room for installation and use.Recently,VR technology has been implemented in different medical domains.The test method proposed in this study include a VR-based RDK that can independently measure human motion perception abilities without any spatial constraints via a VR head-mounted display.Subsequently,the VR-based RDK was implemented,and the visual perception abilities of the normal subjects were measured based on varying coherences.In both screen-and VR-based RDK tests,the easier the stimulus is,the higher the correct answer rate and the shorter the reaction time.No significant differences in coherence thresholds were observed between the two test methods.The VRbased RDK proposed in this study can be used as a diagnosis tool for visual motion perception and neurodegenerative disorders affecting the posterior region of the brain.
基金supported by the Korea Medical Device Development Fund grant funded by the Korean government(the Ministry of Science and ICT,the Ministry of Trade,Industry,and Energy,the Ministry of Health&Welfare,and the Ministry of Food and Drug Safety),Grant Number:RS-2020-KD000004National Research Foundation of Korea(NRF)grant funded by the Korean government.Grant Number:2020R1A5A1019649supported by a grant from the Korea Health Technology R&D Project through the Korea Health Industry Development Institute(KHIDI),funded by the Ministry of Health&Welfare,Republic of Korea.Grant number:RS-2025-02263957.
文摘Photothermal conversion-based quantitative polymerase chain reaction(qPCR)is a fast,sensitive,and accurate method to diagnose infectious diseases.However,they have bottlenecks in test throughput scalability,cumbersome oil cover,and a lack of multi-target capability.Here,the authors present an infectious disease diagnostic device with rapid photothermal conversion-based efficient reverse transcription(RT)-qPCR assays on a multi-target chip(idreamqPCR).The authors innovate an off-axis mirror-based three-channel fluorescence intensity measurement method,enabling concurrent non-contact temperature control of 16 mini-well reaction chambers for qPCRs without the necessity of actuating parts.A transparent adhesive film on a graphite mixed polydimethylsiloxane(PDMS)-based PCR chip with mini-wells avoids contamination and bubbles to achieve 16 RT-qPCRs(40 photothermal cycles)within 17 min.Finally,idream-qPCR is validated by amplifying severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)N172 bp,RdRP 100 bp,and E 113 bp genes using Fluorescein amidites(FAM),Carboxytetramethylrhodamine(TAMRA),and Cyanine5(CY5)fluorescent dyes,respectively,with 102.5%efficiency and a limit-of-detection(LoD)equivalent to 0.85 copies/μL.idream-qPCR can be efficiently used to prevent the spread of infectious diseases.
基金funding from Santander postgraduate mobility awards and Department of Electronic&Electrical Engineering,University of BathR.S.was funded through UK Engineering and Physical Sciences Research Council grant number EP/V040189/1.
文摘Since the onset of the HIV epidemic,assessing CD4+T-cells has become a routine procedure for evaluating immune deficiency,with flow cytometry established as the gold standard.Over time,various strategies and platforms have been introduced to improve CD4+cell enumeration,aiming to enhance the performance of diagnostic devices and bring the service closer to patients.These advancements are particularly critical for low-resource settings and point-of-care applications,where the excellent performance of flow cytometry is hindered by its unsuitability in such environments.This work presents an innovative electrochemical microfluidic device that,with further development,could be applied for HIV management in low resource settings.The setup integrates an electrochemical sensor within a PDMS microfluidic structure,allowing for on-chip electrode functionalization and cell detection.Using electrochemical impedance spectroscopy,the biosensor demonstrates a linear detection range from 1.25×105 to 2×106 cells/mL,with a detection limit of 1.41×105 cells/mL for CD4+cells isolated from blood samples,aligning with clinical ranges for both healthy and HIV+patients.The biosensor shows specificity towards CD4+cells with negligible response to monocytes,neutrophils,and bovine serum albumin.Its integration with a microfluidic chip for sensor fabrication and cell detection,compact size,minimal manual handling,ease of fabrication,electrochemical detection capability,and potential for multiplexing together with the detection range make the device particularly advantageous for use in low-resource settings,standing out among other devices described in the literature.This study also investigates the integration of a microfluidic Dean Flow Fractionation(DFF)chip for cell separation.
基金Project supported by the National Natural Science Foundation of China (Nos.62033012 and 62103124)the Major Special Science and Technology Project of Anhui Province,China (No.202003a07020009)。
文摘Heavy-duty diesel vehicles are important sources of urban nitrogen oxides(NOx)in actual applications for environmental compliance,emitting more than 80%of NOx and more than 90%of particulate matter(PM)in total vehicle emissions.The detection and control of heavy-duty diesel emissions are critical for protecting public health.Currently,vehicles on the road must be regularly tested,every six months or once a year,to filter out high-emission mobile sources at vehicle inspection stations.However,it is difficult to effectively screen high-emission vehicles in time with a long interval between annual inspections,and the fixed threshold cannot adapt to the dynamic changes of vehicle driving conditions.An on-board diagnostic device(OBD)is installed inside the vehicle and can record the vehicle’s emission data in real time.In this paper,we propose a temporal optimization long short-term memory(LSTM)and adaptive dynamic threshold approach to identify heavy-duty high-emitters by using OBD data,which can continuously track and record the emission status in real time.First,a temporal optimization LSTM emission prediction model is established to solve the attention bias discrepancy problem on time steps that is caused by the large number of OBD data streams in practice.Then,the concentration prediction error sequence is detected and distinguished from the anomalous emission contexts using flexible criteria,calculated by an adaptive dynamic threshold with changing driving conditions.Finally,a similarity metric strategy for the time series is introduced to correct some pseudo anomalous results.Experiments on three real OBD time-series emission datasets demonstrate that our method can achieve high accuracy anomalous emission identification.
