Two-dimensional perovskite ferroelectric which strongly couple ferroelectricity with semiconducting properties are promising candidates for optoelectronic applications.However,it is still a great challenge to fabricat...Two-dimensional perovskite ferroelectric which strongly couple ferroelectricity with semiconducting properties are promising candidates for optoelectronic applications.However,it is still a great challenge to fabricate self-powered broadband photodetectors with low detection limit.Herein,we successfully realized self-powered broadband photodetection with low detection limit by using a trilayered perovskite ferroelectric(BA)_(2)EA_(2)Pb_(3)I_(10)(1,BA=n-butylamine,EA=ethylamine).Giving to its large spontaneous polarization(5.6μC/cm^(2)),1 exhibits an open-circuit voltage of 0.25 V which provide driving force to separate carriers.Combining with its low dark current(~10^(-14)A)and narrow bandgap(Eg=1.86 e V),1 demonstrates great potential on detecting the broadband weak lights.Thus,a prominent photodetection performance with high open-off ratio(~10^(5)),outstanding responsivity(>10 m A/W),and promising detectivity(>1011Jones),as well as the low detecting limit(~nW/cm^(2))among the wide wavelength from 377 nm to637 nm was realized based on the single crystal of 1.This work demonstrates the great potential of 2D perovskite ferroelectric on self-powered broadband photodetectors.展开更多
Traditional Pt/C electrode materials are prone to corrosion and detachment during H_(2)S detection,leading to a decrease in fuel cell-type sensor performance.Here,a high-performance H_(2)S sensor based on Pt loaded Ti...Traditional Pt/C electrode materials are prone to corrosion and detachment during H_(2)S detection,leading to a decrease in fuel cell-type sensor performance.Here,a high-performance H_(2)S sensor based on Pt loaded Ti_(3)C_(2)electrode material with-O/-OH terminal groups was designed and prepared.Experimental tests showed that the Pt/Ti_(3)C_(2)sensor has good sensitivity(0.162μA/ppm)and a very low detection limit to H_(2)S(10 ppb).After 90 days of stability testing,the response of the Pt/Ti_(3)C_(2)sensor shows a smaller decrease of 2%compared to that of the Pt/C sensor(22.9%).Meanwhile,the sensor also has high selectivity and repeatability.The density functional theory(DFT)calculation combined with the experiment results revealed that the improved H_(2)S sensing mechanism is attributed to the fact that the strong interaction between Pt and Ti_(3)C_(2)via the Pt-O-Ti bonding can reduce the formation energy of Pt and Ti_(3)C_(2),ultimately prolonging the sensor’s service life.Furthermore,the catalytic property of Pt can decrease the adsorption energy and dissociation barrier of H_(2)S on Pt/Ti_(3)C_(2)surface,greatly enhance the ability to generate protons and effectively transfer charges,realizing good sensitivity and high selectivity of the sensor.The sensor works at room temperature,making it very promising in the field of H_(2)S detection in future.展开更多
Liver transplantation(LT)remains the optimal life-saving intervention for patients with end-stage liver disease.Despite the recent advances in LT several barriers,including organ allocation,donor-recipient matching,an...Liver transplantation(LT)remains the optimal life-saving intervention for patients with end-stage liver disease.Despite the recent advances in LT several barriers,including organ allocation,donor-recipient matching,and patient education,persist.With the growing progress of artificial intelligence,particularly large language models(LLMs)like ChatGPT,new applications have emerged in the field of LT.Current studies demonstrating usage of ChatGPT in LT include various areas of application,from clinical settings to research and education.ChatGPT usage can benefit both healthcare professionals,by decreasing the time spent on non-clinical work,but also LT recipients by providing accurate information.Future potential applications include the expanding usage of ChatGPT and other LLMs in the field of LT pathology and radiology as well as the automated creation of discharge summaries or other related paperwork.Additionally,the next models of ChatGPT might have the potential to provide more accurate patient education material with increased readability.Although ChatGPT usage presents promising applications,there are certain ethical and practical limitations.Key concerns include patient data privacy,information accuracy,misinformation possibility and lack of legal framework.Healthcare providers and policymakers should collaborate for the establishment of a controlled framework for the safe use of ChatGPT.The aim of this minireview is to summarize current literature on ChatGPT in LT,highlighting both opportunities and limitations,while also providing future possible applications.展开更多
The increasing global prevalence of mild cognitive impairment(MCI)necessitates a paradigm shift in early detection strategies.Conventional neuropsychological assessment methods,predominantly paper-and-pencil tests suc...The increasing global prevalence of mild cognitive impairment(MCI)necessitates a paradigm shift in early detection strategies.Conventional neuropsychological assessment methods,predominantly paper-and-pencil tests such as the Mini-Mental State Examination and the Montreal Cognitive Assessment,exhibit inherent limitations with respect to accessibility,administration burden,and sensitivity to subtle cognitive decline,particularly among diverse populations.This commentary critically examines a recent study that champions a novel approach:The integration of gait and handwriting kinematic parameters analyzed via machine learning for MCI screening.The present study positions itself within the broader landscape of MCI detection,with a view to comparing its advantages against established neuropsychological batteries,advanced neuroimaging(e.g.,positron emission tomography,magnetic resonance imaging),and emerging fluid biomarkers(e.g.,cerebrospinal fluid,blood-based assays).While the study demonstrates promising accuracy(74.44%area under the curve 0.74 with gait and graphic handwriting)and addresses key unmet needs in accessibility and objectivity,we highlight its cross-sectional nature,limited sample diversity,and lack of dual-task assessment as areas for future refinement.This commentary posits that kinematic biomarkers offer a distinctive,scalable,and ecologically valid approach to widespread MCI screening,thereby complementing existing methods by providing real-world functional insights.Future research should prioritize longitudinal validation,expansion to diverse cohorts,integration with multimodal data including dual-tasking,and the development of highly portable,artificial intelligence-driven solutions to achieve the democratization of early MCI detection and enable timely interventions.展开更多
A special Fe3O4nanoparticles–graphene（Fe3O4–GN） composite as a magnetic label was employed for biodetection using giant magnetoresistance（GMR） sensors with a Wheatstone bridge. The Fe3O4–GN composite exhibits a...A special Fe3O4nanoparticles–graphene（Fe3O4–GN） composite as a magnetic label was employed for biodetection using giant magnetoresistance（GMR） sensors with a Wheatstone bridge. The Fe3O4–GN composite exhibits a strong ferromagnetic behavior with the saturation magnetization MS of approximately 48 emu/g, coercivity HC of 200 Oe, and remanence Mr of 8.3 emu/g, leading to a large magnetic fringing field. However, the Fe3O4 nanoparticles do not aggregate together, which can be attributed to the pinning and separating effects of graphene sheet to the magnetic particles. The Fe3O4–GN composite is especially suitable for biodetection as a promising magnetic label since it combines two advantages of large fringing field and no aggregation. As a result, the concentration x dependence of voltage difference ｜？V｜ between detecting and reference sensors undergoes the relationship of ｜？V｜ = 240.5 lgx ＋ 515.2 with an ultralow detection limit of 10 ng/mL（very close to the calculated limit of 7 ng/mL） and a wide detection range of 4 orders.展开更多
In this work,multivariate detection limits(MDL)estimator was obtained based on the microelectro-mechanical systems–near infrared(MEMS–NIR)technology coupled with two sampling accessories to assess the detection capa...In this work,multivariate detection limits(MDL)estimator was obtained based on the microelectro-mechanical systems–near infrared(MEMS–NIR)technology coupled with two sampling accessories to assess the detection capability of four quality parameters(glycyrrhizic acid,liquiritin,liquiritigenin and isoliquiritin)in licorice from di®erent geographical regions.112 licorice samples were divided into two parts(calibration set and prediction set)using Kennard–Stone(KS)method.Four quality parameters were measured using high-performance liquid chromatography(HPLC)method according to Chinese pharmacopoeia and previous studies.The MEMS–NIR spectra were acquired from¯ber optic probe(FOP)and integrating sphere,then the partial least squares(PLS)model was obtained using the optimum processing method.Chemometrics indicators have been utilized to assess the PLS model performance.Model assessment using chemometrics indicators is based on relative mean prediction error of all concentration levels,which indicated relatively low sensitivity for low-content analytes(below 1000 parts per million(ppm)).Therefore,MDL estimator was introduced with alpha error and beta error based on good prediction characteristic of low concentration levels.The result suggested that MEMS–NIR technology coupled with fiber optic probe(FOP)and integrating sphere was able to detect minor analytes.The result further demonstrated that integrating sphere mode(i.e.,MDL0:05;0:05,0.22%)was more robust than FOP mode(i.e.,MDL0:05;0:05,0.48%).In conclusion,this research proposed that MDL method was helpful to determine the detection capabilities of low-content analytes using MEMS–NIR technology and successful to compare two sampling accessories.展开更多
Based on fundamental arguments, the expressions for the decision limit and the detection limit both in the count domain and in the count rate domain are derived.These expressions are found to be different from those s...Based on fundamental arguments, the expressions for the decision limit and the detection limit both in the count domain and in the count rate domain are derived.These expressions are found to be different from those shown in the existing literature.展开更多
For determining the accuracy of a calorimeter over the instrument’s entire measuring range,a novel method has been established.For this new approach,(a)benzoic acid(C_(6)H_(5)CO_(2)H) as a certified reference materia...For determining the accuracy of a calorimeter over the instrument’s entire measuring range,a novel method has been established.For this new approach,(a)benzoic acid(C_(6)H_(5)CO_(2)H) as a certified reference material(CRM),(b)SiO_(2) and(c)a mixture of CRM benzoic acid and SiO_(2) have been used.To illustrate the essential difference between 1)the novel analytical method for control of the entire measurement range and 2)the calorimeter calibration,both applications of benzoic acid(BA)have been demonstrated.An experimental result showed that BA was successfully used to check the whole calorimeter measurement range.The results also showed that the same new method was successfully applied to determine the limit of detection and quantification.A new instrument testing process and a new measurement technique have thus been established.In this way,the cost of using CRM to control the accuracy of measuring the entire measuring range of the calorimeter,as shown in this paper,is minimized.The requirements of the ISO/IEC 17025:2017 standard are satisfied.ISO/IEC 17025:2017,together with ISO 9001:2015(quality management systems),ISO 14001:2015(relate to environmental protection)and ISO45001:2018(occupational safety),constitute an integrated quality system by which a testing laboratory may also accredit.展开更多
Early diagnosis of diseases is critical in its effective management. Traditional disease detection methods require specialized equipment and trained personnel. With the introduction of rapid diagnostic test kits (RDTs...Early diagnosis of diseases is critical in its effective management. Traditional disease detection methods require specialized equipment and trained personnel. With the introduction of rapid diagnostic test kits (RDTs), disease detection has become easier and faster. However, these RDTs have failed to compete with the specialized laboratory equipment due to their high detection limits and false alarm rates. This paper presents a novel method of using carbon nanofibers (CNFs) grown on glass microballoons (NMBs) to achieve ultra-low detection limits in RDTs. The NMBs have millions of nanosized CNFs grown on each microballoon, with each CNF having a strong bonding affinity for antibodies. The NMBs conjugated with secondary antibodies have therefore a significantly higher probability of capturing minute antigen concentrations in solution. Furthermore, the dark color formation at the capture zone makes visual disease detection possible. Human Immunoglobulin G (IgG) was selected as the model analyte to study the performance of NMBs using a sandwich immunoassay protocol. Ultra-low electrical detection limit of (4 pg/ml) and rapid re- sponse (~1 minute) was achieved using this method.展开更多
In the implementation of CARS nanoscopy, signal strength decreases with focal volume size decreasing. A crucial problem that remains to be solved is whether the reduced signal generated in the suppressed focal volume ...In the implementation of CARS nanoscopy, signal strength decreases with focal volume size decreasing. A crucial problem that remains to be solved is whether the reduced signal generated in the suppressed focal volume can be detected. Here reported is a theoretical analysis of detection limit （DL） to time-resolved CARS （T-CARS） nanoscopy based on our proposed additional probe-beam-induced phonon depletion （APIPD） method for the low concentration samples. In order to acquire a detailed shot-noise limited signal-to-noise （SNR） and the involved parameters to evaluate DL, the T-CARS process is described with full quantum theory to estimate the extreme power density levels of the pump and Stokes beams determined by saturation behavior of coherent phonons, which are both actually on the order of ~ 109 W/cm2. When the pump and Stokes intensities reach such values and the total intensity of the excitation beams arrives at a maximum tolerable by most biological samples in a certain suppressed focal volume （40-nm suppressed focal scale in APIPD method）, the DL correspondingly varies with exposure time, for example, DL values are 103 and 102 when exposure times are 20 ms and 200 ms respectively.展开更多
A new method was developed to decrease the mass limit of detection (LOD) and increase the number of theoretical plates (N) in capillary electrophoresis with amperometric detection. When the single microcylinder electr...A new method was developed to decrease the mass limit of detection (LOD) and increase the number of theoretical plates (N) in capillary electrophoresis with amperometric detection. When the single microcylinder electrode, the 10 um ID capillary with the etched detection end and the in-capillary alignment were used, the mass LOD for phenol was reduced 124 times and N was increased 36 times in comparison with the normal situation.展开更多
Laser-induced breakdown spectroscopy(LIBS) was examined to detect a trace substance adhered onto Al alloys for the surface inspection of materials to be adhesively bonded. As an example of Si contamination, silicone o...Laser-induced breakdown spectroscopy(LIBS) was examined to detect a trace substance adhered onto Al alloys for the surface inspection of materials to be adhesively bonded. As an example of Si contamination, silicone oil was employed and sprayed onto substrates with a controlled surface concentration. LIBS measurements employing nanosecond UV pulses(λ?=?266 nm) and an off-axis emission collection system with different detecting heights were performed. Because surface contaminants are involved in the plasma formed by laser ablation of the substrates, the relative contribution of the surface contaminants and the substrates to the plasma emission could be changed depending on the conditions for plasma formation. The limit of detection(LOD) was evaluated under several detecting conditions for investigating the factors that affected the LOD. A significant factor was the standard deviation values of signal intensities obtained for the clean substrates. This value varied depending on the measurement conditions.For the Al alloy(A6061), the smallest LOD obtained was 0.529 μg?·?cm^(-2). Furthermore, an improved LOD(0.299 μg?·?cm^(-2)) was obtained for the Al alloy with a lower Si content.展开更多
In recent years,the number of patientswith colon disease has increased significantly.Colon polyps are the precursor lesions of colon cancer.If not diagnosed in time,they can easily develop into colon cancer,posing a s...In recent years,the number of patientswith colon disease has increased significantly.Colon polyps are the precursor lesions of colon cancer.If not diagnosed in time,they can easily develop into colon cancer,posing a serious threat to patients’lives and health.A colonoscopy is an important means of detecting colon polyps.However,in polyp imaging,due to the large differences and diverse types of polyps in size,shape,color,etc.,traditional detection methods face the problem of high false positive rates,which creates problems for doctors during the diagnosis process.In order to improve the accuracy and efficiency of colon polyp detection,this question proposes a network model suitable for colon polyp detection(PD-YOLO).This method introduces the self-attention mechanism CBAM(Convolutional Block Attention Module)in the backbone layer based on YOLOv7,allowing themodel to adaptively focus on key information and ignore the unimportant parts.To help themodel do a better job of polyp localization and bounding box regression,add the SPD-Conv(Symmetric Positive Definite Convolution)module to the neck layer and use deconvolution instead of upsampling.Theexperimental results indicate that the PD-YOLO algorithm demonstrates strong robustness in colon polyp detection.Compared to the original YOLOv7,on the Kvasir-SEG dataset,PD-YOLO has shown an increase of 5.44 percentage points in AP@0.5,showcasing significant advantages over other mainstream methods.展开更多
The application of deep learning for target detection in aerial images captured by Unmanned Aerial Vehicles(UAV)has emerged as a prominent research focus.Due to the considerable distance between UAVs and the photograp...The application of deep learning for target detection in aerial images captured by Unmanned Aerial Vehicles(UAV)has emerged as a prominent research focus.Due to the considerable distance between UAVs and the photographed objects,coupled with complex shooting environments,existing models often struggle to achieve accurate real-time target detection.In this paper,a You Only Look Once v8(YOLOv8)model is modified from four aspects:the detection head,the up-sampling module,the feature extraction module,and the parameter optimization of positive sample screening,and the YOLO-S3DT model is proposed to improve the performance of the model for detecting small targets in aerial images.Experimental results show that all detection indexes of the proposed model are significantly improved without increasing the number of model parameters and with the limited growth of computation.Moreover,this model also has the best performance compared to other detecting models,demonstrating its advancement within this category of tasks.展开更多
A detection system for American English glides/w y r 1] in a knowledge-based automatic speech recognition system is presented. The method uses detection of dips in band-limited energy to total energy ratios, instead o...A detection system for American English glides/w y r 1] in a knowledge-based automatic speech recognition system is presented. The method uses detection of dips in band-limited energy to total energy ratios, instead of detecting dips along the unmodified band-limited energy contours. By using band-limited energy ratio, the dip detection is applicable in not only intervocalic regions but also in non-intervocalic regions. A Gaussian mixture model（GMM） based classifier is then used to separate the detected vowels and nasals. This approach is tested using the TIMIT corpus and results in an overall detection rate of 69.5 %, which is a 4.7 % absolute increase in detection rate compared with an hidden Markov model （HMM） based phone recognizer.展开更多
The presence of aluminum(Al^(3+))and fluoride(F^(−))ions in the environment can be harmful to ecosystems and human health,highlighting the need for accurate and efficient monitoring.In this paper,an innovative approac...The presence of aluminum(Al^(3+))and fluoride(F^(−))ions in the environment can be harmful to ecosystems and human health,highlighting the need for accurate and efficient monitoring.In this paper,an innovative approach is presented that leverages the power of machine learning to enhance the accuracy and efficiency of fluorescence-based detection for sequential quantitative analysis of aluminum(Al^(3+))and fluoride(F^(−))ions in aqueous solutions.The proposed method involves the synthesis of sulfur-functionalized carbon dots(C-dots)as fluorescence probes,with fluorescence enhancement upon interaction with Al^(3+)ions,achieving a detection limit of 4.2 nmol/L.Subsequently,in the presence of F^(−)ions,fluorescence is quenched,with a detection limit of 47.6 nmol/L.The fingerprints of fluorescence images are extracted using a cross-platform computer vision library in Python,followed by data preprocessing.Subsequently,the fingerprint data is subjected to cluster analysis using the K-means model from machine learning,and the average Silhouette Coefficient indicates excellent model performance.Finally,a regression analysis based on the principal component analysis method is employed to achieve more precise quantitative analysis of aluminum and fluoride ions.The results demonstrate that the developed model excels in terms of accuracy and sensitivity.This groundbreaking model not only showcases exceptional performance but also addresses the urgent need for effective environmental monitoring and risk assessment,making it a valuable tool for safeguarding our ecosystems and public health.展开更多
With the approval of more and more genetically modified(GM)crops in our country,GM safety management has become more important.Transgenic detection is a major approach for transgenic safety management.Nevertheless,a c...With the approval of more and more genetically modified(GM)crops in our country,GM safety management has become more important.Transgenic detection is a major approach for transgenic safety management.Nevertheless,a convenient and visual technique with low equipment requirements and high sensitivity for the field detection of GM plants is still lacking.On the basis of the existing recombinase polymerase amplification(RPA)technique,we developed a multiplex RPA(multi-RPA)method that can simultaneously detect three transgenic elements,including the cauliflower mosaic virus 35S gene(CaMV35S)promoter,neomycin phosphotransferaseⅡgene(NptⅡ)and hygromycin B phosphotransferase gene(Hyg),thus improving the detection rate.Moreover,we coupled this multi-RPA technique with the CRISPR/Cas12a reporter system,which enabled the detection results to be clearly observed by naked eyes under ultraviolet(UV)light(254 nm;which could be achieved by a portable UV flashlight),therefore establishing a multi-RPA visual detection technique.Compared with the traditional test strip detection method,this multi-RPA-CRISPR/Cas12a technique has the higher specificity,higher sensitivity,wider application range and lower cost.Compared with other polymerase chain reaction(PCR)techniques,it also has the advantages of low equipment requirements and visualization,making it a potentially feasible method for the field detection of GM plants.展开更多
Security and safety remain paramount concerns for both governments and individuals worldwide.In today’s context,the frequency of crimes and terrorist attacks is alarmingly increasing,becoming increasingly intolerable...Security and safety remain paramount concerns for both governments and individuals worldwide.In today’s context,the frequency of crimes and terrorist attacks is alarmingly increasing,becoming increasingly intolerable to society.Consequently,there is a pressing need for swift identification of potential threats to preemptively alert law enforcement and security forces,thereby preventing potential attacks or violent incidents.Recent advancements in big data analytics and deep learning have significantly enhanced the capabilities of computer vision in object detection,particularly in identifying firearms.This paper introduces a novel automatic firearm detection surveillance system,utilizing a one-stage detection approach named MARIE(Mechanism for Realtime Identification of Firearms).MARIE incorporates the Single Shot Multibox Detector(SSD)model,which has been specifically optimized to balance the speed-accuracy trade-off critical in firearm detection applications.The SSD model was further refined by integrating MobileNetV2 and InceptionV2 architectures for superior feature extraction capabilities.The experimental results demonstrate that this modified SSD configuration provides highly satisfactory performance,surpassing existing methods trained on the same dataset in terms of the critical speedaccuracy trade-off.Through these innovations,MARIE sets a new standard in surveillance technology,offering a robust solution to enhance public safety effectively.展开更多
In recent years,advancements in autonomous vehicle technology have accelerated,promising safer and more efficient transportation systems.However,achieving fully autonomous driving in challenging weather conditions,par...In recent years,advancements in autonomous vehicle technology have accelerated,promising safer and more efficient transportation systems.However,achieving fully autonomous driving in challenging weather conditions,particularly in snowy environments,remains a challenge.Snow-covered roads introduce unpredictable surface conditions,occlusions,and reduced visibility,that require robust and adaptive path detection algorithms.This paper presents an enhanced road detection framework for snowy environments,leveraging Simple Framework forContrastive Learning of Visual Representations(SimCLR)for Self-Supervised pretraining,hyperparameter optimization,and uncertainty-aware object detection to improve the performance of YouOnly Look Once version 8(YOLOv8).Themodel is trained and evaluated on a custom-built dataset collected from snowy roads in Tromsø,Norway,which covers a range of snow textures,illumination conditions,and road geometries.The proposed framework achieves scores in terms of mAP@50 equal to 99%and mAP@50–95 equal to 97%,demonstrating the effectiveness of YOLOv8 for real-time road detection in extreme winter conditions.The findings contribute to the safe and reliable deployment of autonomous vehicles in Arctic environments,enabling robust decision-making in hazardous weather conditions.This research lays the groundwork for more resilient perceptionmodels in self-driving systems,paving the way for the future development of intelligent and adaptive transportation networks.展开更多
Recent studies suggest per-and polyfluoroalkyl substances(PFAS)are ubiquitous in rivers worldwide.In the Asia-Pacific region,the frequency of PFAS detection in rivers is increasing.However,the overwhelming majority of...Recent studies suggest per-and polyfluoroalkyl substances(PFAS)are ubiquitous in rivers worldwide.In the Asia-Pacific region,the frequency of PFAS detection in rivers is increasing.However,the overwhelming majority of studies and data represent high population and urbanized river catchments.In this study,we investigate PFAS occurrence in major Philippines river systems characterized by both high and low population densities.In the Pasig Laguna de Bay River,which drains a major urban conurbation,we detected PFAS at concentrations typical of global rivers.Unexpectedly,we did not detect PFAS in river water or sediments in low population density river catchments,despite our instrument detection limits being lower than the vast majority of river concentrations reported worldwide.We hypothesize that septic tanks,as the dominant wastewater treatment practice in Philippines catchments,may control the release of PFAS into groundwater and rivers in the Philippines.However,no groundwater PFAS data currently exist to validate this supposition.More broadly,our findings highlight the need for more representative PFAS sampling and analysis in rivers to more accurately represent regional and global detection frequencies and trends.展开更多
基金financially supported by the National Natural Science Foundation of China(Nos.22435005,22193042,21921001,22305105,52202194,22201284)Natural Science Foundation of Jiangxi Province(No.20224BAB213003)+1 种基金the Natural Science Foundation of Fujian Province(No.2023J05076)Jiangxi Provincial Education Department Science and Technology Research Foundation(No.GJJ2200384)。
文摘Two-dimensional perovskite ferroelectric which strongly couple ferroelectricity with semiconducting properties are promising candidates for optoelectronic applications.However,it is still a great challenge to fabricate self-powered broadband photodetectors with low detection limit.Herein,we successfully realized self-powered broadband photodetection with low detection limit by using a trilayered perovskite ferroelectric(BA)_(2)EA_(2)Pb_(3)I_(10)(1,BA=n-butylamine,EA=ethylamine).Giving to its large spontaneous polarization(5.6μC/cm^(2)),1 exhibits an open-circuit voltage of 0.25 V which provide driving force to separate carriers.Combining with its low dark current(~10^(-14)A)and narrow bandgap(Eg=1.86 e V),1 demonstrates great potential on detecting the broadband weak lights.Thus,a prominent photodetection performance with high open-off ratio(~10^(5)),outstanding responsivity(>10 m A/W),and promising detectivity(>1011Jones),as well as the low detecting limit(~nW/cm^(2))among the wide wavelength from 377 nm to637 nm was realized based on the single crystal of 1.This work demonstrates the great potential of 2D perovskite ferroelectric on self-powered broadband photodetectors.
基金the National Key R&D Program of China(No.2023YFB3210102).
文摘Traditional Pt/C electrode materials are prone to corrosion and detachment during H_(2)S detection,leading to a decrease in fuel cell-type sensor performance.Here,a high-performance H_(2)S sensor based on Pt loaded Ti_(3)C_(2)electrode material with-O/-OH terminal groups was designed and prepared.Experimental tests showed that the Pt/Ti_(3)C_(2)sensor has good sensitivity(0.162μA/ppm)and a very low detection limit to H_(2)S(10 ppb).After 90 days of stability testing,the response of the Pt/Ti_(3)C_(2)sensor shows a smaller decrease of 2%compared to that of the Pt/C sensor(22.9%).Meanwhile,the sensor also has high selectivity and repeatability.The density functional theory(DFT)calculation combined with the experiment results revealed that the improved H_(2)S sensing mechanism is attributed to the fact that the strong interaction between Pt and Ti_(3)C_(2)via the Pt-O-Ti bonding can reduce the formation energy of Pt and Ti_(3)C_(2),ultimately prolonging the sensor’s service life.Furthermore,the catalytic property of Pt can decrease the adsorption energy and dissociation barrier of H_(2)S on Pt/Ti_(3)C_(2)surface,greatly enhance the ability to generate protons and effectively transfer charges,realizing good sensitivity and high selectivity of the sensor.The sensor works at room temperature,making it very promising in the field of H_(2)S detection in future.
文摘Liver transplantation(LT)remains the optimal life-saving intervention for patients with end-stage liver disease.Despite the recent advances in LT several barriers,including organ allocation,donor-recipient matching,and patient education,persist.With the growing progress of artificial intelligence,particularly large language models(LLMs)like ChatGPT,new applications have emerged in the field of LT.Current studies demonstrating usage of ChatGPT in LT include various areas of application,from clinical settings to research and education.ChatGPT usage can benefit both healthcare professionals,by decreasing the time spent on non-clinical work,but also LT recipients by providing accurate information.Future potential applications include the expanding usage of ChatGPT and other LLMs in the field of LT pathology and radiology as well as the automated creation of discharge summaries or other related paperwork.Additionally,the next models of ChatGPT might have the potential to provide more accurate patient education material with increased readability.Although ChatGPT usage presents promising applications,there are certain ethical and practical limitations.Key concerns include patient data privacy,information accuracy,misinformation possibility and lack of legal framework.Healthcare providers and policymakers should collaborate for the establishment of a controlled framework for the safe use of ChatGPT.The aim of this minireview is to summarize current literature on ChatGPT in LT,highlighting both opportunities and limitations,while also providing future possible applications.
文摘The increasing global prevalence of mild cognitive impairment(MCI)necessitates a paradigm shift in early detection strategies.Conventional neuropsychological assessment methods,predominantly paper-and-pencil tests such as the Mini-Mental State Examination and the Montreal Cognitive Assessment,exhibit inherent limitations with respect to accessibility,administration burden,and sensitivity to subtle cognitive decline,particularly among diverse populations.This commentary critically examines a recent study that champions a novel approach:The integration of gait and handwriting kinematic parameters analyzed via machine learning for MCI screening.The present study positions itself within the broader landscape of MCI detection,with a view to comparing its advantages against established neuropsychological batteries,advanced neuroimaging(e.g.,positron emission tomography,magnetic resonance imaging),and emerging fluid biomarkers(e.g.,cerebrospinal fluid,blood-based assays).While the study demonstrates promising accuracy(74.44%area under the curve 0.74 with gait and graphic handwriting)and addresses key unmet needs in accessibility and objectivity,we highlight its cross-sectional nature,limited sample diversity,and lack of dual-task assessment as areas for future refinement.This commentary posits that kinematic biomarkers offer a distinctive,scalable,and ecologically valid approach to widespread MCI screening,thereby complementing existing methods by providing real-world functional insights.Future research should prioritize longitudinal validation,expansion to diverse cohorts,integration with multimodal data including dual-tasking,and the development of highly portable,artificial intelligence-driven solutions to achieve the democratization of early MCI detection and enable timely interventions.
基金supported by the National Natural Science Foundation of China(Grant Nos.11074040,11504192,11674187,11604172,and 51403114)the Natural Science Foundation of Shandong Province,China(Grant Nos.ZR2012FZ006 and BS2014CL010)the China Postdoctoral Science Foundation(Grant Nos.2014M551868 and 2015M570570)
文摘A special Fe3O4nanoparticles–graphene（Fe3O4–GN） composite as a magnetic label was employed for biodetection using giant magnetoresistance（GMR） sensors with a Wheatstone bridge. The Fe3O4–GN composite exhibits a strong ferromagnetic behavior with the saturation magnetization MS of approximately 48 emu/g, coercivity HC of 200 Oe, and remanence Mr of 8.3 emu/g, leading to a large magnetic fringing field. However, the Fe3O4 nanoparticles do not aggregate together, which can be attributed to the pinning and separating effects of graphene sheet to the magnetic particles. The Fe3O4–GN composite is especially suitable for biodetection as a promising magnetic label since it combines two advantages of large fringing field and no aggregation. As a result, the concentration x dependence of voltage difference ｜？V｜ between detecting and reference sensors undergoes the relationship of ｜？V｜ = 240.5 lgx ＋ 515.2 with an ultralow detection limit of 10 ng/mL（very close to the calculated limit of 7 ng/mL） and a wide detection range of 4 orders.
基金This work was financially supported fromthe National Natural Science Foundation of China(81303218)Doctoral Fund of China (20130013120006)Special Fund of Outstanding Young Teachers and Innovation Team.
文摘In this work,multivariate detection limits(MDL)estimator was obtained based on the microelectro-mechanical systems–near infrared(MEMS–NIR)technology coupled with two sampling accessories to assess the detection capability of four quality parameters(glycyrrhizic acid,liquiritin,liquiritigenin and isoliquiritin)in licorice from di®erent geographical regions.112 licorice samples were divided into two parts(calibration set and prediction set)using Kennard–Stone(KS)method.Four quality parameters were measured using high-performance liquid chromatography(HPLC)method according to Chinese pharmacopoeia and previous studies.The MEMS–NIR spectra were acquired from¯ber optic probe(FOP)and integrating sphere,then the partial least squares(PLS)model was obtained using the optimum processing method.Chemometrics indicators have been utilized to assess the PLS model performance.Model assessment using chemometrics indicators is based on relative mean prediction error of all concentration levels,which indicated relatively low sensitivity for low-content analytes(below 1000 parts per million(ppm)).Therefore,MDL estimator was introduced with alpha error and beta error based on good prediction characteristic of low concentration levels.The result suggested that MEMS–NIR technology coupled with fiber optic probe(FOP)and integrating sphere was able to detect minor analytes.The result further demonstrated that integrating sphere mode(i.e.,MDL0:05;0:05,0.22%)was more robust than FOP mode(i.e.,MDL0:05;0:05,0.48%).In conclusion,this research proposed that MDL method was helpful to determine the detection capabilities of low-content analytes using MEMS–NIR technology and successful to compare two sampling accessories.
文摘Based on fundamental arguments, the expressions for the decision limit and the detection limit both in the count domain and in the count rate domain are derived.These expressions are found to be different from those shown in the existing literature.
基金the funding by the Ministry of Education and Science,the Republic of Serbia for Registration(No.451-03-68/2022-14/200052)。
文摘For determining the accuracy of a calorimeter over the instrument’s entire measuring range,a novel method has been established.For this new approach,(a)benzoic acid(C_(6)H_(5)CO_(2)H) as a certified reference material(CRM),(b)SiO_(2) and(c)a mixture of CRM benzoic acid and SiO_(2) have been used.To illustrate the essential difference between 1)the novel analytical method for control of the entire measurement range and 2)the calorimeter calibration,both applications of benzoic acid(BA)have been demonstrated.An experimental result showed that BA was successfully used to check the whole calorimeter measurement range.The results also showed that the same new method was successfully applied to determine the limit of detection and quantification.A new instrument testing process and a new measurement technique have thus been established.In this way,the cost of using CRM to control the accuracy of measuring the entire measuring range of the calorimeter,as shown in this paper,is minimized.The requirements of the ISO/IEC 17025:2017 standard are satisfied.ISO/IEC 17025:2017,together with ISO 9001:2015(quality management systems),ISO 14001:2015(relate to environmental protection)and ISO45001:2018(occupational safety),constitute an integrated quality system by which a testing laboratory may also accredit.
文摘Early diagnosis of diseases is critical in its effective management. Traditional disease detection methods require specialized equipment and trained personnel. With the introduction of rapid diagnostic test kits (RDTs), disease detection has become easier and faster. However, these RDTs have failed to compete with the specialized laboratory equipment due to their high detection limits and false alarm rates. This paper presents a novel method of using carbon nanofibers (CNFs) grown on glass microballoons (NMBs) to achieve ultra-low detection limits in RDTs. The NMBs have millions of nanosized CNFs grown on each microballoon, with each CNF having a strong bonding affinity for antibodies. The NMBs conjugated with secondary antibodies have therefore a significantly higher probability of capturing minute antigen concentrations in solution. Furthermore, the dark color formation at the capture zone makes visual disease detection possible. Human Immunoglobulin G (IgG) was selected as the model analyte to study the performance of NMBs using a sandwich immunoassay protocol. Ultra-low electrical detection limit of (4 pg/ml) and rapid re- sponse (~1 minute) was achieved using this method.
基金Project supported by the National Basic Research Program of China(Grant No.2012CB825802)the Major Scientific Instruments Equipment Development of China(Grant No.2012YQ15009203)+1 种基金the National Natural Science Foundation of China(Grant Nos.60878053 and 11004136)the State Key Laboratory of Precision Measurement Technology and Instruments,Tsinghua University,China(Grant No.DL12-01)
文摘In the implementation of CARS nanoscopy, signal strength decreases with focal volume size decreasing. A crucial problem that remains to be solved is whether the reduced signal generated in the suppressed focal volume can be detected. Here reported is a theoretical analysis of detection limit （DL） to time-resolved CARS （T-CARS） nanoscopy based on our proposed additional probe-beam-induced phonon depletion （APIPD） method for the low concentration samples. In order to acquire a detailed shot-noise limited signal-to-noise （SNR） and the involved parameters to evaluate DL, the T-CARS process is described with full quantum theory to estimate the extreme power density levels of the pump and Stokes beams determined by saturation behavior of coherent phonons, which are both actually on the order of ~ 109 W/cm2. When the pump and Stokes intensities reach such values and the total intensity of the excitation beams arrives at a maximum tolerable by most biological samples in a certain suppressed focal volume （40-nm suppressed focal scale in APIPD method）, the DL correspondingly varies with exposure time, for example, DL values are 103 and 102 when exposure times are 20 ms and 200 ms respectively.
基金This project was supported by the National Natural Science Foundation of China.
文摘A new method was developed to decrease the mass limit of detection (LOD) and increase the number of theoretical plates (N) in capillary electrophoresis with amperometric detection. When the single microcylinder electrode, the 10 um ID capillary with the etched detection end and the in-capillary alignment were used, the mass LOD for phenol was reduced 124 times and N was increased 36 times in comparison with the normal situation.
基金supported by a future pioneering project commissioned by the New Energy and Industrial Technology Development Organization (NEDO)
文摘Laser-induced breakdown spectroscopy(LIBS) was examined to detect a trace substance adhered onto Al alloys for the surface inspection of materials to be adhesively bonded. As an example of Si contamination, silicone oil was employed and sprayed onto substrates with a controlled surface concentration. LIBS measurements employing nanosecond UV pulses(λ?=?266 nm) and an off-axis emission collection system with different detecting heights were performed. Because surface contaminants are involved in the plasma formed by laser ablation of the substrates, the relative contribution of the surface contaminants and the substrates to the plasma emission could be changed depending on the conditions for plasma formation. The limit of detection(LOD) was evaluated under several detecting conditions for investigating the factors that affected the LOD. A significant factor was the standard deviation values of signal intensities obtained for the clean substrates. This value varied depending on the measurement conditions.For the Al alloy(A6061), the smallest LOD obtained was 0.529 μg?·?cm^(-2). Furthermore, an improved LOD(0.299 μg?·?cm^(-2)) was obtained for the Al alloy with a lower Si content.
基金funded by the Undergraduate Higher Education Teaching and Research Project(No.FBJY20230216)Research Projects of Putian University(No.2023043)the Education Department of the Fujian Province Project(No.JAT220300).
文摘In recent years,the number of patientswith colon disease has increased significantly.Colon polyps are the precursor lesions of colon cancer.If not diagnosed in time,they can easily develop into colon cancer,posing a serious threat to patients’lives and health.A colonoscopy is an important means of detecting colon polyps.However,in polyp imaging,due to the large differences and diverse types of polyps in size,shape,color,etc.,traditional detection methods face the problem of high false positive rates,which creates problems for doctors during the diagnosis process.In order to improve the accuracy and efficiency of colon polyp detection,this question proposes a network model suitable for colon polyp detection(PD-YOLO).This method introduces the self-attention mechanism CBAM(Convolutional Block Attention Module)in the backbone layer based on YOLOv7,allowing themodel to adaptively focus on key information and ignore the unimportant parts.To help themodel do a better job of polyp localization and bounding box regression,add the SPD-Conv(Symmetric Positive Definite Convolution)module to the neck layer and use deconvolution instead of upsampling.Theexperimental results indicate that the PD-YOLO algorithm demonstrates strong robustness in colon polyp detection.Compared to the original YOLOv7,on the Kvasir-SEG dataset,PD-YOLO has shown an increase of 5.44 percentage points in AP@0.5,showcasing significant advantages over other mainstream methods.
文摘The application of deep learning for target detection in aerial images captured by Unmanned Aerial Vehicles(UAV)has emerged as a prominent research focus.Due to the considerable distance between UAVs and the photographed objects,coupled with complex shooting environments,existing models often struggle to achieve accurate real-time target detection.In this paper,a You Only Look Once v8(YOLOv8)model is modified from four aspects:the detection head,the up-sampling module,the feature extraction module,and the parameter optimization of positive sample screening,and the YOLO-S3DT model is proposed to improve the performance of the model for detecting small targets in aerial images.Experimental results show that all detection indexes of the proposed model are significantly improved without increasing the number of model parameters and with the limited growth of computation.Moreover,this model also has the best performance compared to other detecting models,demonstrating its advancement within this category of tasks.
基金The Ministry of Knowledge Economy,Korea,under the Infor mation Technology Research Center support program supervised by the National IT Industry Promotion Agency(NIPA-2012-H0301-12-2006)
文摘A detection system for American English glides/w y r 1] in a knowledge-based automatic speech recognition system is presented. The method uses detection of dips in band-limited energy to total energy ratios, instead of detecting dips along the unmodified band-limited energy contours. By using band-limited energy ratio, the dip detection is applicable in not only intervocalic regions but also in non-intervocalic regions. A Gaussian mixture model（GMM） based classifier is then used to separate the detected vowels and nasals. This approach is tested using the TIMIT corpus and results in an overall detection rate of 69.5 %, which is a 4.7 % absolute increase in detection rate compared with an hidden Markov model （HMM） based phone recognizer.
基金supported by the National Natural Science Foundation of China(No.U21A20290)Guangdong Basic and Applied Basic Research Foundation(No.2022A1515011656)+2 种基金the Projects of Talents Recruitment of GDUPT(No.2023rcyj1003)the 2022“Sail Plan”Project of Maoming Green Chemical Industry Research Institute(No.MMGCIRI2022YFJH-Y-024)Maoming Science and Technology Project(No.2023382).
文摘The presence of aluminum(Al^(3+))and fluoride(F^(−))ions in the environment can be harmful to ecosystems and human health,highlighting the need for accurate and efficient monitoring.In this paper,an innovative approach is presented that leverages the power of machine learning to enhance the accuracy and efficiency of fluorescence-based detection for sequential quantitative analysis of aluminum(Al^(3+))and fluoride(F^(−))ions in aqueous solutions.The proposed method involves the synthesis of sulfur-functionalized carbon dots(C-dots)as fluorescence probes,with fluorescence enhancement upon interaction with Al^(3+)ions,achieving a detection limit of 4.2 nmol/L.Subsequently,in the presence of F^(−)ions,fluorescence is quenched,with a detection limit of 47.6 nmol/L.The fingerprints of fluorescence images are extracted using a cross-platform computer vision library in Python,followed by data preprocessing.Subsequently,the fingerprint data is subjected to cluster analysis using the K-means model from machine learning,and the average Silhouette Coefficient indicates excellent model performance.Finally,a regression analysis based on the principal component analysis method is employed to achieve more precise quantitative analysis of aluminum and fluoride ions.The results demonstrate that the developed model excels in terms of accuracy and sensitivity.This groundbreaking model not only showcases exceptional performance but also addresses the urgent need for effective environmental monitoring and risk assessment,making it a valuable tool for safeguarding our ecosystems and public health.
基金the Experimental Technology Research Project of Zhejiang University(SYB202138)National Natural Science Foundation of China(32000195)。
文摘With the approval of more and more genetically modified(GM)crops in our country,GM safety management has become more important.Transgenic detection is a major approach for transgenic safety management.Nevertheless,a convenient and visual technique with low equipment requirements and high sensitivity for the field detection of GM plants is still lacking.On the basis of the existing recombinase polymerase amplification(RPA)technique,we developed a multiplex RPA(multi-RPA)method that can simultaneously detect three transgenic elements,including the cauliflower mosaic virus 35S gene(CaMV35S)promoter,neomycin phosphotransferaseⅡgene(NptⅡ)and hygromycin B phosphotransferase gene(Hyg),thus improving the detection rate.Moreover,we coupled this multi-RPA technique with the CRISPR/Cas12a reporter system,which enabled the detection results to be clearly observed by naked eyes under ultraviolet(UV)light(254 nm;which could be achieved by a portable UV flashlight),therefore establishing a multi-RPA visual detection technique.Compared with the traditional test strip detection method,this multi-RPA-CRISPR/Cas12a technique has the higher specificity,higher sensitivity,wider application range and lower cost.Compared with other polymerase chain reaction(PCR)techniques,it also has the advantages of low equipment requirements and visualization,making it a potentially feasible method for the field detection of GM plants.
文摘Security and safety remain paramount concerns for both governments and individuals worldwide.In today’s context,the frequency of crimes and terrorist attacks is alarmingly increasing,becoming increasingly intolerable to society.Consequently,there is a pressing need for swift identification of potential threats to preemptively alert law enforcement and security forces,thereby preventing potential attacks or violent incidents.Recent advancements in big data analytics and deep learning have significantly enhanced the capabilities of computer vision in object detection,particularly in identifying firearms.This paper introduces a novel automatic firearm detection surveillance system,utilizing a one-stage detection approach named MARIE(Mechanism for Realtime Identification of Firearms).MARIE incorporates the Single Shot Multibox Detector(SSD)model,which has been specifically optimized to balance the speed-accuracy trade-off critical in firearm detection applications.The SSD model was further refined by integrating MobileNetV2 and InceptionV2 architectures for superior feature extraction capabilities.The experimental results demonstrate that this modified SSD configuration provides highly satisfactory performance,surpassing existing methods trained on the same dataset in terms of the critical speedaccuracy trade-off.Through these innovations,MARIE sets a new standard in surveillance technology,offering a robust solution to enhance public safety effectively.
文摘In recent years,advancements in autonomous vehicle technology have accelerated,promising safer and more efficient transportation systems.However,achieving fully autonomous driving in challenging weather conditions,particularly in snowy environments,remains a challenge.Snow-covered roads introduce unpredictable surface conditions,occlusions,and reduced visibility,that require robust and adaptive path detection algorithms.This paper presents an enhanced road detection framework for snowy environments,leveraging Simple Framework forContrastive Learning of Visual Representations(SimCLR)for Self-Supervised pretraining,hyperparameter optimization,and uncertainty-aware object detection to improve the performance of YouOnly Look Once version 8(YOLOv8).Themodel is trained and evaluated on a custom-built dataset collected from snowy roads in Tromsø,Norway,which covers a range of snow textures,illumination conditions,and road geometries.The proposed framework achieves scores in terms of mAP@50 equal to 99%and mAP@50–95 equal to 97%,demonstrating the effectiveness of YOLOv8 for real-time road detection in extreme winter conditions.The findings contribute to the safe and reliable deployment of autonomous vehicles in Arctic environments,enabling robust decision-making in hazardous weather conditions.This research lays the groundwork for more resilient perceptionmodels in self-driving systems,paving the way for the future development of intelligent and adaptive transportation networks.
基金Natural Environment Research Council,Grant/Award Number:NE/W006871/1。
文摘Recent studies suggest per-and polyfluoroalkyl substances(PFAS)are ubiquitous in rivers worldwide.In the Asia-Pacific region,the frequency of PFAS detection in rivers is increasing.However,the overwhelming majority of studies and data represent high population and urbanized river catchments.In this study,we investigate PFAS occurrence in major Philippines river systems characterized by both high and low population densities.In the Pasig Laguna de Bay River,which drains a major urban conurbation,we detected PFAS at concentrations typical of global rivers.Unexpectedly,we did not detect PFAS in river water or sediments in low population density river catchments,despite our instrument detection limits being lower than the vast majority of river concentrations reported worldwide.We hypothesize that septic tanks,as the dominant wastewater treatment practice in Philippines catchments,may control the release of PFAS into groundwater and rivers in the Philippines.However,no groundwater PFAS data currently exist to validate this supposition.More broadly,our findings highlight the need for more representative PFAS sampling and analysis in rivers to more accurately represent regional and global detection frequencies and trends.
