Due to water conflicts and allocation in the Lancang-Mekong River Basin(LMRB),the spatio-temporal differentiation of total water resources and the natural-human influence need to be clarified.This work investigated LM...Due to water conflicts and allocation in the Lancang-Mekong River Basin(LMRB),the spatio-temporal differentiation of total water resources and the natural-human influence need to be clarified.This work investigated LMRB's terrestrial water storage anomaly(TWSA)and its spatio-temporal dynamics during 2002–2020.Considering the effects of natural factors and human activities,the respective contributions of climate variability and human activities to terrestrial water storage change(TWSC)were separated.Results showed that:(1)LMRB's TWSA decreased by 0.3158 cm/a.(2)TWSA showed a gradual increase in distribution from southwest of MRB to middle LMRB and from northeast of LRB to middle LMRB.TWSA positively changed in Myanmar while slightly changed in Laos and China.It negatively changed in Vietnam,Thailand and Cambodia.(3)TWSA components decreased in a descending order of soil moisture,groundwater and precipitation.(4)Natural factors had a substantial and spatial differentiated influence on TWSA over the LMRB.(5)Climate variability contributed 79%of TWSC in the LMRB while human activities contributed 21%with an increasing impact after 2008.The TWSC of upstream basin countries was found to be controlled by climate variability while Vietnam and Cambodia's TWSC has been controlled by human activities since 2012.展开更多
The ability to accurately predict urban traffic flows is crucial for optimising city operations.Consequently,various methods for forecasting urban traffic have been developed,focusing on analysing historical data to u...The ability to accurately predict urban traffic flows is crucial for optimising city operations.Consequently,various methods for forecasting urban traffic have been developed,focusing on analysing historical data to understand complex mobility patterns.Deep learning techniques,such as graph neural networks(GNNs),are popular for their ability to capture spatio-temporal dependencies.However,these models often become overly complex due to the large number of hyper-parameters involved.In this study,we introduce Dynamic Multi-Graph Spatial-Temporal Graph Neural Ordinary Differential Equation Networks(DMST-GNODE),a framework based on ordinary differential equations(ODEs)that autonomously discovers effective spatial-temporal graph neural network(STGNN)architectures for traffic prediction tasks.The comparative analysis of DMST-GNODE and baseline models indicates that DMST-GNODE model demonstrates superior performance across multiple datasets,consistently achieving the lowest Root Mean Square Error(RMSE)and Mean Absolute Error(MAE)values,alongside the highest accuracy.On the BKK(Bangkok)dataset,it outperformed other models with an RMSE of 3.3165 and an accuracy of 0.9367 for a 20-min interval,maintaining this trend across 40 and 60 min.Similarly,on the PeMS08 dataset,DMST-GNODE achieved the best performance with an RMSE of 19.4863 and an accuracy of 0.9377 at 20 min,demonstrating its effectiveness over longer periods.The Los_Loop dataset results further emphasise this model’s advantage,with an RMSE of 3.3422 and an accuracy of 0.7643 at 20 min,consistently maintaining superiority across all time intervals.These numerical highlights indicate that DMST-GNODE not only outperforms baseline models but also achieves higher accuracy and lower errors across different time intervals and datasets.展开更多
This paper introduces a high-precision bandgap reference(BGR)designed for battery management systems(BMS),fea-turing an ultra-low temperature coefficient(TC)and line sensitivity(LS).The BGR employs a current-mode sche...This paper introduces a high-precision bandgap reference(BGR)designed for battery management systems(BMS),fea-turing an ultra-low temperature coefficient(TC)and line sensitivity(LS).The BGR employs a current-mode scheme with chopped op-amps and internal clock generators to eliminate op-amp offset.A low dropout regulator(LDO)and a pre-regula-tor enhance output driving and LS,respectively.Curvature compensation enhances the TC by addressing higher-order nonlinear-ity.These approaches,effective near room temperature,employs trimming at both 20 and 60°C.When combined with fixed cur-vature correction currents,it achieves an ultra-low TC for each chip.Implemented in a CMOS 180 nm process,the BGR occu-pies 0.548 mm²and operates at 2.5 V with 84μA current draw from a 5 V supply.An average TC of 2.69 ppm/℃ with two-point trimming and 0.81 ppm/℃ with multi-point trimming are achieved over the temperature range of-40 to 125℃.It accommo-dates a load current of 1 mA and an LS of 42 ppm/V,making it suitable for precise BMS applications.展开更多
Introduction: Childbirth on a scarred uterus is a major issue for health centers, especially peripheral, due to the major obstetric risks it presents. The objectives were to evaluate the frequency, route of delivery a...Introduction: Childbirth on a scarred uterus is a major issue for health centers, especially peripheral, due to the major obstetric risks it presents. The objectives were to evaluate the frequency, route of delivery and maternal-fetal prognosis of this type of delivery at csref of Kolondiéba. Materials and Methods: This was a retrospective cross-sectional study for one year (1 January 2023-31 December 2023). All patients admitted to the maternity ward of the center with at least one uterine scar and treated in the center were included. We extracted data from partograms, OR records, birth records and obstetric records. Input was done on Excel 2010 and analysis on SPSS.23. Results: The frequency of scarring uterus was 16.8% (217/1285 births). The average age was 27. Pauciparous were most represented (59%). Patients were received from community health centers (44.7%). Prenatal consultation sessions (1 - 3 sessions) were performed at (64.9%). Uterine scars were obstetric in (99%). The cesarean section was performed immediately in (59.4%), it was prophylactic in 17%. The uterine test was attempted in (25.34%) with (69%) success. We recorded 3.6% uterine ruptures, 8.7% postoperative complications, 5.5% stillbirths and one maternal death (0.46%). Conclusion: Births on a scarred uterus are frequent and associated with a high rate of complications.展开更多
Computed tomography is an indispensable X-ray imaging modality used to diagnose numerous pathologies, but it can also involve the delivery of high ionizing radiation doses harmful to the health of patients. This study...Computed tomography is an indispensable X-ray imaging modality used to diagnose numerous pathologies, but it can also involve the delivery of high ionizing radiation doses harmful to the health of patients. This study aims to survey the level of radiation doses delivered to child patients during head exams in CT imaging to set up the Dosimetric Reference Levels (DRLs), a routine dose optimization tool, based on data acquired at the University Hospital of Angré (UHA), the University Hospital of Treichville (UHT) and the Polyclinic Hospital Farah (Farah) for optimizing procedures in Ivorian hospitals. Prospectively performed on 334 CT images of 186 child patients, this study was carried out on CT systems such as Hitachi Scenaria, Sinovision Insitum, and Philips Incisive used respectively at UHA, UHT and Farah. Children’s scan data were classified into four age bands: vol or dose-length product as DLP) value, whatever the hospital, increases with respect to the age of child patients. Based on the 75th percentile of the whole dose distributions, the DRLs of the CTDIvol is 54.37 mGy whatever the age groups and those of the DLP with respect to age bands are 1224.55 mGy∙cm, 1414.06 mGy∙cm, 1632.24 mGy.cm and 1544.57 mGy∙cm, respectively. The averaged values of CTDIvol and DLP smaller than the corresponding DRLs values suggest that practices in our three facilities are optimized. However, comparing our results with those from different international studies, we see that the CTDIvol and DLP values obtained in the present work are higher. These results suggest additional surveys to ensure our DRLs values and efforts from radiologists, imaging technicians and medical physicists to strengthen clinical procedures for the radiation protection of children undergoing CT scans in Côte d’Ivoire.展开更多
The purpose of this research was to evaluate radiological safety in pediatric radiology in hospitals in the Kongo Central province of the DRC. To this end, we surveyed a convenience sample of 50 health professionals, ...The purpose of this research was to evaluate radiological safety in pediatric radiology in hospitals in the Kongo Central province of the DRC. To this end, we surveyed a convenience sample of 50 health professionals, including 10 radiologists working in the hospitals covered by the survey, to assess the practice of pediatric radiology and the degree of compliance with radiation protection principles for the safety of children and the environment. We collected radiophysical parameters to calculate entrance doses in pediatric radiology in radiology departments to determine the dosimetric level by comparison with the diagnostic reference levels of the International Commission on Radiological Protection (ICRP). All in all, we found that in Kongo Central in the DRC, many health personnel surveyed reported that more than 30% of requested radiological examinations are not justified. Also, after comparing the entrance doses produced in the surveyed departments with those of the International Commission on Radiological Protection (ICRP), a statistically significant difference was found in pediatric radiology between the average doses in five out of six surveyed departments and those of the ICRP. Therefore, almost all of the surveyed departments were found to be highly irradiating in children, while excessive X-ray irradiation in children can have significant effects due to their increased sensitivity to radiation. Among the risks are: increased cancer risks, damage to developing cells, potential genetic effects, and neurological effects. This is why support for implementing radiation protection principles is a necessity to promote the safety of patients and the environment against the harmful effects of X-rays in conventional radiology.展开更多
Objective To investigate the spatiotemporal patterns and socioeconomic factors influencing the incidence of tuberculosis(TB)in the Guangdong Province between 2010 and 2019.Method Spatial and temporal variations in TB ...Objective To investigate the spatiotemporal patterns and socioeconomic factors influencing the incidence of tuberculosis(TB)in the Guangdong Province between 2010 and 2019.Method Spatial and temporal variations in TB incidence were mapped using heat maps and hierarchical clustering.Socioenvironmental influencing factors were evaluated using a Bayesian spatiotemporal conditional autoregressive(ST-CAR)model.Results Annual incidence of TB in Guangdong decreased from 91.85/100,000 in 2010 to 53.06/100,000in 2019.Spatial hotspots were found in northeastern Guangdong,particularly in Heyuan,Shanwei,and Shantou,while Shenzhen,Dongguan,and Foshan had the lowest rates in the Pearl River Delta.The STCAR model showed that the TB risk was lower with higher per capita Gross Domestic Product(GDP)[Relative Risk(RR),0.91;95%Confidence Interval(CI):0.86–0.98],more the ratio of licensed physicians and physician(RR,0.94;95%CI:0.90-0.98),and higher per capita public expenditure(RR,0.94;95%CI:0.90–0.97),with a marginal effect of population density(RR,0.86;95%CI:0.86–1.00).Conclusion The incidence of TB in Guangdong varies spatially and temporally.Areas with poor economic conditions and insufficient healthcare resources are at an increased risk of TB infection.Strategies focusing on equitable health resource distribution and economic development are the key to TB control.展开更多
BACKGROUND Pepsinogen(PG)and the PG I/II ratio(PGR)are critical indicators for diagnosing Helicobacter pylori infection and chronic atrophic gastritis,and assessing gastric cancer risk.Existing reference intervals(RIs...BACKGROUND Pepsinogen(PG)and the PG I/II ratio(PGR)are critical indicators for diagnosing Helicobacter pylori infection and chronic atrophic gastritis,and assessing gastric cancer risk.Existing reference intervals(RIs)often overlook age,sex,and demographic variations.Partitioned RIs,while considering these factors,fail to capture the gradual age-related physiological changes.Next-generation RIs offer a solution to this limitation.AIM To investigate age-and sex-specific dynamics of PG and establish next-generation RIs for adults and the elderly in northern China.METHODS After screening,708 healthy individuals were included in this observational study.Serum PG was measured using chemiluminescence immunoassay.Age-and sex-related effects on PG were analyzed with a two-way analysis of variance.RI partitioning was determined by the standard deviation ratio(SDR).Traditional RIs were established using a non-parametric approach.Generalized Additive Models for Location,Scale,and Shape(GAMLSS)modeled age-related trends and continuous reference percentiles for PG I and PG II.Reference limit flagging rates for both RI types were compared.RESULTS PG I and PG II levels were influenced by age(P<0.001)and sex(P<0.001),while PGR remained stable.Age-specific RIs were required for PG I(SDR=0.366)and PG II(SDR=0.424).Partitioned RIs were established for PG I and PG II,with a single RI for PGR.GAMLSS modeling revealed distinct age-dependent trajectories:PG I increased from a median of 39.75μg/L at age 20 years to 49.75μg/L at age 60 years,a 25.16%increase,after which it plateaued through age 80 years.In contrast,PG II showed a continuous rise throughout the age range,with the median value increasing from 5.07μg/L at age 20 years to 8.36μg/L at age 80 years,corresponding to a 64.89%increase.Continuous reference percentiles intuitively reflected these trends and were detailed in this study.Next-generation RIs demonstrated superior accuracy compared to partitioned RIs when applied to specific age subgroups.CONCLUSION This study elucidates the age-and sex-specific dynamics of PG and,to our knowledge,is the first to establish next-generation RIs for PG,supporting more individualized interpretation in laboratory medicine.展开更多
This study examines the effects of rapid land use changes in India,with a specific focus on Sonipat District in Haryana—a region undergoing significant urban expansion.Over the past two decades,rural landscapes in So...This study examines the effects of rapid land use changes in India,with a specific focus on Sonipat District in Haryana—a region undergoing significant urban expansion.Over the past two decades,rural landscapes in Sonipat have undergone notable transformation,as open spaces and agricultural lands are increasingly converted into residential colonies,commercial hubs,and industrial zones.While such changes reflect economic development and urban growth,they also raise critical concerns about sustainability,especially in terms of food security,groundwater depletion,and environmental degradation.The study examines land use changes between 2000 and 2024 using remote sensing techniques and spatial analysis.It further incorporates secondary data and insights from community-level interactions to assess the socio-economic and ecological impacts of this transformation.The findings indicate rising land fragmentation,loss of agricultural livelihoods,pressure on civic infrastructure,and increasing pollution—factors that threaten long-term regional sustainability.The study underscores the urgent need to reconcile urban development with environmental and social sustainability.By offering a detailed case study of Sonipat,this research contributes to the broader discourse on India’s urbanisation pathways.It aims to provide policymakers,planners,and researchers with evidence-based recommendations to manage land transitions more responsibly,promoting urban growth models that ensure ecological integrity,equitable development,and long-term resilience.展开更多
As Deepfake technology continues to evolve,the distinction between real and fake content becomes increasingly blurred.Most existing Deepfake video detectionmethods rely on single-frame facial image features,which limi...As Deepfake technology continues to evolve,the distinction between real and fake content becomes increasingly blurred.Most existing Deepfake video detectionmethods rely on single-frame facial image features,which limits their ability to capture temporal differences between frames.Current methods also exhibit limited generalization capabilities,struggling to detect content generated by unknown forgery algorithms.Moreover,the diversity and complexity of forgery techniques introduced by Artificial Intelligence Generated Content(AIGC)present significant challenges for traditional detection frameworks,whichmust balance high detection accuracy with robust performance.To address these challenges,we propose a novel Deepfake detection framework that combines a two-stream convolutional network with a Vision Transformer(ViT)module to enhance spatio-temporal feature representation.The ViT model extracts spatial features from the forged video,while the 3D convolutional network captures temporal features.The 3D convolution enables cross-frame feature extraction,allowing the model to detect subtle facial changes between frames.The confidence scores from both the ViT and 3D convolution submodels are fused at the decision layer,enabling themodel to effectively handle unknown forgery techniques.Focusing on Deepfake videos and GAN-generated images,the proposed approach is evaluated on two widely used public face forgery datasets.Compared to existing state-of-theartmethods,it achieves higher detection accuracy and better generalization performance,offering a robust solution for deepfake detection in real-world scenarios.展开更多
Bamboo was one of the first plants to be cultivated in China and is widely used in industry and daily life.The study of gene function has become an important part of bamboo breeding,whereas quantitative real-time PCR(...Bamboo was one of the first plants to be cultivated in China and is widely used in industry and daily life.The study of gene function has become an important part of bamboo breeding,whereas quantitative real-time PCR(qRT-PCR)is a powerful tool for gene expression analysis.The accuracy of qRT-PCR results largely depends on suitable reference genes.In this study,a transcriptome-wide identification of reference genes was conducted based on 447 transcriptome datasets,comprising 200 tissue samples,107 treated samples,and 140 samples from various moso bamboo(Phyllostachys edulis)forms.A total of 3444,1013,and 3962 stably expressed genes were identified from these three groups,respectively.Functional enrichment analysis revealed significant enrichment of these genes in pathways,including the spliceosome,proteasome,and oxidative phosphorylation.Eight candidate genes(ADPRE,GAPDH,TRX,TUBA,NRP,MBF,UNK,and CAM1),were selected for qRT-PCR validation using 112 samples.To assess their stability,five statistical methods(geNorm,NormFinder,BestKeeper,Delta-Ct,and RefFinder)were employed.The most suitable reference genes were ADPRE and GAPDH for different tissues,GAPDH and CAM1 for different treatments,and GAPDH and TRX for various moso bamboo forms.Overall,ADPRE and GAPDH were the most stable reference genes across all conditions,while TUBA and TRX were the least stable reference genes.In addition,a significant negative correlation was found between the Ct values of RT-qPCR and the log2TPM values from the transcriptome data(Ct=-1.534x+37.221),providing a potential method for estimating gene expression levels.The identified reference genes,particularly ADPRE and GAPDH,provide a robust set of references for gene expression studies in moso bamboo.展开更多
Agriculture holds a pivotal position in the economic fabric of every nation,yet concerns about agricultural carbon emission intensity(ACI)have become a major hurdle to achieving global economic sustainability.Focusing...Agriculture holds a pivotal position in the economic fabric of every nation,yet concerns about agricultural carbon emission intensity(ACI)have become a major hurdle to achieving global economic sustainability.Focusing on 31 provincial-level regions in China,this study uses the Exploratory Spatio-temporal Data Analysis(ESTDA)and Panel Quantile Regression(PQR)model to analyze the spatio-temporal interaction characteristics and influencing factors of ACI in China from 2004 to 2023.The findings are as follows:(1)ACI showed an overall downward trend,and the spatial distribution pattern was characterized by“high in the western region and low along the southeastern coast”.Although the overall disparity tended to converge,some high-carbon-intensity regions exhibited extreme trends.ACI displayed clear spatial directionality,with the spatial center shifting steadily toward the northeast.(2)Regions in the northwest,northeast,and central-south parts exhibited strong local spatial structural dynamics,and the local spatial dependence of ACI in each region showed a nonlinear trend.Generally speaking,the spatial association pattern demonstrated a certain degree of inertia in spatial transfer,reflecting strong path dependence or spatial lock-in characteristics.(3)Optimization of industrial structure and improvement in agricultural mechanization will increase ACI,while economic development can effectively reduce it.The impact of urbanization on ACI exhibits a nonlinear pattern.The coordinated development of economic growth and urbanization significantly reduces ACI,with a stronger emission reduction observed in regions with low ACI.The optimization of industrial structure,when combined with urbanization and environmental regulation,contributes to significant emission reductions particularly in high-ACI areas.Similarly,the synergy between agricultural mechanization and urbanization effectively lowers emissions in low-ACI regions,though this effect diminishes in areas with higher ACI.展开更多
Sloping farmland,particularly in mountainous and hilly areas,constitutes a significant component of regional farmland resources.An investigation into the spatio-temporal pattern of sloping farmland and its influencing...Sloping farmland,particularly in mountainous and hilly areas,constitutes a significant component of regional farmland resources.An investigation into the spatio-temporal pattern of sloping farmland and its influencing factors in China is imperative for the efficient utilization of farmland and the optimization of land space.We used land use transfer matrix,geographically weighted regression model and geographical detector to conduct this study.Results showed that sloping farmland in China firstly decreased and then increased from 2000 to 2020.The proportion of sloping farmland decreased radially outward from Sichuan basin to the surrounding areas.Change rates of sloping farmland with different slopes varied and the slope with 6°-15°underwent the fastest changes.The influencing factors of farmland at various slope degrees were different.For sloping farmland below 15°,land use intensity and elevation had the greatest contribution.For sloping farmland between 15°and 25°,elevation,land use intensity,and population density were the main influencing factors.Sloping farmland above 25°was mostly affected by natural factors.This study can provide scientific basis for rational development and protection of sloping farmland.展开更多
Current spatio-temporal action detection methods lack sufficient capabilities in extracting and comprehending spatio-temporal information. This paper introduces an end-to-end Adaptive Cross-Scale Fusion Encoder-Decode...Current spatio-temporal action detection methods lack sufficient capabilities in extracting and comprehending spatio-temporal information. This paper introduces an end-to-end Adaptive Cross-Scale Fusion Encoder-Decoder (ACSF-ED) network to predict the action and locate the object efficiently. In the Adaptive Cross-Scale Fusion Spatio-Temporal Encoder (ACSF ST-Encoder), the Asymptotic Cross-scale Feature-fusion Module (ACCFM) is designed to address the issue of information degradation caused by the propagation of high-level semantic information, thereby extracting high-quality multi-scale features to provide superior features for subsequent spatio-temporal information modeling. Within the Shared-Head Decoder structure, a shared classification and regression detection head is constructed. A multi-constraint loss function composed of one-to-one, one-to-many, and contrastive denoising losses is designed to address the problem of insufficient constraint force in predicting results with traditional methods. This loss function enhances the accuracy of model classification predictions and improves the proximity of regression position predictions to ground truth objects. The proposed method model is evaluated on the popular dataset UCF101-24 and JHMDB-21. Experimental results demonstrate that the proposed method achieves an accuracy of 81.52% on the Frame-mAP metric, surpassing current existing methods.展开更多
To solve the problem of the lack of reference material(RM)for determination of allergenic ingredients in food,a RM of cashew nut powder was developed in the study.Cashew nut powder was prepared from cashew nut kernel ...To solve the problem of the lack of reference material(RM)for determination of allergenic ingredients in food,a RM of cashew nut powder was developed in the study.Cashew nut powder was prepared from cashew nut kernel by selecting,cleaning,crushing,n-hexane degreasing and sieving treatment.The reliability and traceability of RM was verified using real-time quantitative polymerase chain reaction(qPCR)and phylogenetic tree analysis.The cashew nut powder RM showed good homogeneity,and good stability under long-term storage at 4℃and short-term simulated transportation from-20 to 45℃.The RM was determined jointly by 8 collaborative laboratories,and the characteristic CT value was 24.732,and the extended uncertainty was 1.052%(k=2).The RM was applied to verify the amplification efficiency and the limit of detection for qPCR assay,and showed good applicability.The RM could be used for method validation and quality control,for the determination of allergenic ingredients in food mixed with trace amounts of cashew nut.展开更多
Electrocardiogram (ECG) analysis is critical for detecting arrhythmias, but traditional methods struggle with large-scale Electrocardiogram data and rare arrhythmia events in imbalanced datasets. These methods fail to...Electrocardiogram (ECG) analysis is critical for detecting arrhythmias, but traditional methods struggle with large-scale Electrocardiogram data and rare arrhythmia events in imbalanced datasets. These methods fail to perform multi-perspective learning of temporal signals and Electrocardiogram images, nor can they fully extract the latent information within the data, falling short of the accuracy required by clinicians. Therefore, this paper proposes an innovative hybrid multimodal spatiotemporal neural network to address these challenges. The model employs a multimodal data augmentation framework integrating visual and signal-based features to enhance the classification performance of rare arrhythmias in imbalanced datasets. Additionally, the spatiotemporal fusion module incorporates a spatiotemporal graph convolutional network to jointly model temporal and spatial features, uncovering complex dependencies within the Electrocardiogram data and improving the model’s ability to represent complex patterns. In experiments conducted on the MIT-BIH arrhythmia dataset, the model achieved 99.95% accuracy, 99.80% recall, and a 99.78% F1 score. The model was further validated for generalization using the clinical INCART arrhythmia dataset, and the results demonstrated its effectiveness in terms of both generalization and robustness.展开更多
The use of a stable reference gene is fundamental for achieving reliable quantitative qRT-PCR (qPCR) results. Developing and evaluating the stability of reference genes is necessary for studying the molecular mechanis...The use of a stable reference gene is fundamental for achieving reliable quantitative qRT-PCR (qPCR) results. Developing and evaluating the stability of reference genes is necessary for studying the molecular mechanisms of M. transitoria in response to drought stress. In this study, 18 candidate reference genes were selected from transcriptome sequencing data of M. transitoria according to their FPKM values under different drought stress degrees. Cluster-23533.34641 was identified as the most stable reference gene for M. transitoria under drought stress based on qPCR results and combined analysis of Genorm, NormFinder, BestKeeper, and Delta Ct algorithms. The reference genes identified in this research offer improved accuracy for quantifying target gene expression in both M. transitoria and Malus species under drought stress. This study could provide insights into the drought stress-related functional gene or factor in M. transitoria, even in Malus species.展开更多
Sulfur isotopes of S-bearing materials are powerful tools to trace various geological processes and sulfur sources in earth sciences,especially in ore deposits where sulfide-sulfate pair coprecipitates widely.However,...Sulfur isotopes of S-bearing materials are powerful tools to trace various geological processes and sulfur sources in earth sciences,especially in ore deposits where sulfide-sulfate pair coprecipitates widely.However,in-situ S isotope determination of barite is challenging without natural matrix-matched reference material.In this study,we present two natural barite reference materials(1-YS and 294-YS)for in-situ sulfur isotopic analysis.Independent LA-MC-ICP-MS laboratories were utilized to test theδ34S micron-scale homogeneity of 1-YS and 294-YS barites that have 2s repeatabilities of better than±0.45‰and±0.41‰,respectively.Meanwhile,the in-situ analysis results are consistent with the results of the bulk analysis by GS-IRMS within uncertainty.The grand meanδ~(34)S values of 1-YS(13.37‰±0.42‰,2s)and 294-YS(14.38‰±0.44‰,2s)are the final recommended values obtained from four independent laboratories.All the results confirm the suitability of 1-YS and 294-YS barite used as calibration materials with respect to in-situ S isotopic analysis.Moreover,the new developed barite reference materials were used as matrix-matched standard to calibrate the barite samples from the Huayangchuan carbonatite-hosted U-polymetallic deposit(Qinling orogenic belt,western China)to obtainδ34S values.Utilizing the temperaturedependentδ34S fractionation of barite-pyrite pair,we calculate the formation temperature of barite(i.e.,506 to 537°C)and theδ34S value of mineralizing fluid(i.e.,-7.11‰to-7.59‰)in the Huayangchuan deposit.The results indicate an involvement of sedimentary sulfur,presumably acting as a potential uranium source(e.g.,upper crustal materials)for the giant Huayangchuan deposit.展开更多
Carbonaceous aerosol,including organic carbon(OC)and elemental carbon(EC),has significant influence on human health,air quality and climate change.Accurate measurement of carbonaceous aerosol is essential to reduce th...Carbonaceous aerosol,including organic carbon(OC)and elemental carbon(EC),has significant influence on human health,air quality and climate change.Accurate measurement of carbonaceous aerosol is essential to reduce the uncertainty of radiative forcing estimation and source apportionment.The accurate separation of OC and EC is controversial due to the charring of OC.Therefore,the development of reference materials(RM)for the validation of OC/EC separation is an important basis for further study.Previous RMs were mainly based on ambient air sampling,which could not provide traceability of OC and EC concentration.To develop traceable RMs with known OC/EC contents,our study applied an improved aerosol generation and mixing technique,providing uniform deposition of particles on quartz filters.To generate OC aerosol with similar pyrolytic property of ambient aerosol,both water soluble organic carbon(WSOC)and water insoluble organic carbon(WIOC)were used,and amorphous carbon was selected for EC surrogate.The RMs were analyzed using different protocols.The homogeneity within the filter was validated,reaching below 2%.The long-term stability of RMs has been validated with RSD ranged from 1.7%–3.2%.Good correlationwas observed between nominal concentration of RMswithmeasured concentration by two protocols,while the difference of EC concentration was within 20%.The results indicated that the newly developed RMs were acceptable for the calibration of OC and EC,which could improve the accuracy of carbonaceous aerosol measurement.Moreover,the laboratory-generated EC-RMs could be suitable for the calibration of equivalent BC concentration by Aethalometers.展开更多
Reference Evapotranspiration(ETo)iswidely used to assess totalwater loss between land and atmosphere due to its importance in maintaining the atmospheric water balance,especially in agricultural and environmental mana...Reference Evapotranspiration(ETo)iswidely used to assess totalwater loss between land and atmosphere due to its importance in maintaining the atmospheric water balance,especially in agricultural and environmental management.Accurate estimation of ETo is challenging due to its dependency onmultiple climatic variables,including temperature,humidity,and solar radiation,making it a complexmultivariate time-series problem.Traditional machine learning and deep learning models have been applied to forecast ETo,achieving moderate success.However,the introduction of transformer-based architectures in time-series forecasting has opened new possibilities formore precise ETo predictions.In this study,a novel algorithm for ETo forecasting is proposed,focusing on four transformer-based models:Vanilla Transformer,Informer,Autoformer,and FEDformer(Frequency Enhanced Decomposed Transformer),applied to an ETo dataset from the Andalusian region.The novelty of the proposed algorithm lies in determining optimized window sizes based on seasonal trends and variations,which were then used with each model to enhance prediction accuracy.This custom window-sizing method allows the models to capture ETo’s unique seasonal patterns more effectively.Finally,results demonstrate that the Informer model outperformed other transformer-based models,achievingmean square error(MSE)values of 0.1404 and 0.1445 for forecast windows(15,7)and(30,15),respectively.The Vanilla Transformer also showed strong performance,closely following the Informermodel.These findings suggest that the proposed optimized window-sizing approach,combined with transformer-based architectures,is highly effective for ETo modelling.This novel strategy has the potential to be adapted in othermultivariate time-series forecasting tasks that require seasonality-sensitive approaches.展开更多
基金National Natural Science Foundation of China,No.42161006Yunnan Fundamental Research Projects No.202201AT070094,No.202301BF070001-004+1 种基金Special Project for High-level Talents of Yunnan Province for Young Top Talents,No.C6213001159European Research Council(ERC)Starting-Grant STORIES,No.101040939。
文摘Due to water conflicts and allocation in the Lancang-Mekong River Basin(LMRB),the spatio-temporal differentiation of total water resources and the natural-human influence need to be clarified.This work investigated LMRB's terrestrial water storage anomaly(TWSA)and its spatio-temporal dynamics during 2002–2020.Considering the effects of natural factors and human activities,the respective contributions of climate variability and human activities to terrestrial water storage change(TWSC)were separated.Results showed that:(1)LMRB's TWSA decreased by 0.3158 cm/a.(2)TWSA showed a gradual increase in distribution from southwest of MRB to middle LMRB and from northeast of LRB to middle LMRB.TWSA positively changed in Myanmar while slightly changed in Laos and China.It negatively changed in Vietnam,Thailand and Cambodia.(3)TWSA components decreased in a descending order of soil moisture,groundwater and precipitation.(4)Natural factors had a substantial and spatial differentiated influence on TWSA over the LMRB.(5)Climate variability contributed 79%of TWSC in the LMRB while human activities contributed 21%with an increasing impact after 2008.The TWSC of upstream basin countries was found to be controlled by climate variability while Vietnam and Cambodia's TWSC has been controlled by human activities since 2012.
文摘The ability to accurately predict urban traffic flows is crucial for optimising city operations.Consequently,various methods for forecasting urban traffic have been developed,focusing on analysing historical data to understand complex mobility patterns.Deep learning techniques,such as graph neural networks(GNNs),are popular for their ability to capture spatio-temporal dependencies.However,these models often become overly complex due to the large number of hyper-parameters involved.In this study,we introduce Dynamic Multi-Graph Spatial-Temporal Graph Neural Ordinary Differential Equation Networks(DMST-GNODE),a framework based on ordinary differential equations(ODEs)that autonomously discovers effective spatial-temporal graph neural network(STGNN)architectures for traffic prediction tasks.The comparative analysis of DMST-GNODE and baseline models indicates that DMST-GNODE model demonstrates superior performance across multiple datasets,consistently achieving the lowest Root Mean Square Error(RMSE)and Mean Absolute Error(MAE)values,alongside the highest accuracy.On the BKK(Bangkok)dataset,it outperformed other models with an RMSE of 3.3165 and an accuracy of 0.9367 for a 20-min interval,maintaining this trend across 40 and 60 min.Similarly,on the PeMS08 dataset,DMST-GNODE achieved the best performance with an RMSE of 19.4863 and an accuracy of 0.9377 at 20 min,demonstrating its effectiveness over longer periods.The Los_Loop dataset results further emphasise this model’s advantage,with an RMSE of 3.3422 and an accuracy of 0.7643 at 20 min,consistently maintaining superiority across all time intervals.These numerical highlights indicate that DMST-GNODE not only outperforms baseline models but also achieves higher accuracy and lower errors across different time intervals and datasets.
基金supported by the National Natural Science Foundation of China(NSFC)under grant No.62204235。
文摘This paper introduces a high-precision bandgap reference(BGR)designed for battery management systems(BMS),fea-turing an ultra-low temperature coefficient(TC)and line sensitivity(LS).The BGR employs a current-mode scheme with chopped op-amps and internal clock generators to eliminate op-amp offset.A low dropout regulator(LDO)and a pre-regula-tor enhance output driving and LS,respectively.Curvature compensation enhances the TC by addressing higher-order nonlinear-ity.These approaches,effective near room temperature,employs trimming at both 20 and 60°C.When combined with fixed cur-vature correction currents,it achieves an ultra-low TC for each chip.Implemented in a CMOS 180 nm process,the BGR occu-pies 0.548 mm²and operates at 2.5 V with 84μA current draw from a 5 V supply.An average TC of 2.69 ppm/℃ with two-point trimming and 0.81 ppm/℃ with multi-point trimming are achieved over the temperature range of-40 to 125℃.It accommo-dates a load current of 1 mA and an LS of 42 ppm/V,making it suitable for precise BMS applications.
文摘Introduction: Childbirth on a scarred uterus is a major issue for health centers, especially peripheral, due to the major obstetric risks it presents. The objectives were to evaluate the frequency, route of delivery and maternal-fetal prognosis of this type of delivery at csref of Kolondiéba. Materials and Methods: This was a retrospective cross-sectional study for one year (1 January 2023-31 December 2023). All patients admitted to the maternity ward of the center with at least one uterine scar and treated in the center were included. We extracted data from partograms, OR records, birth records and obstetric records. Input was done on Excel 2010 and analysis on SPSS.23. Results: The frequency of scarring uterus was 16.8% (217/1285 births). The average age was 27. Pauciparous were most represented (59%). Patients were received from community health centers (44.7%). Prenatal consultation sessions (1 - 3 sessions) were performed at (64.9%). Uterine scars were obstetric in (99%). The cesarean section was performed immediately in (59.4%), it was prophylactic in 17%. The uterine test was attempted in (25.34%) with (69%) success. We recorded 3.6% uterine ruptures, 8.7% postoperative complications, 5.5% stillbirths and one maternal death (0.46%). Conclusion: Births on a scarred uterus are frequent and associated with a high rate of complications.
文摘Computed tomography is an indispensable X-ray imaging modality used to diagnose numerous pathologies, but it can also involve the delivery of high ionizing radiation doses harmful to the health of patients. This study aims to survey the level of radiation doses delivered to child patients during head exams in CT imaging to set up the Dosimetric Reference Levels (DRLs), a routine dose optimization tool, based on data acquired at the University Hospital of Angré (UHA), the University Hospital of Treichville (UHT) and the Polyclinic Hospital Farah (Farah) for optimizing procedures in Ivorian hospitals. Prospectively performed on 334 CT images of 186 child patients, this study was carried out on CT systems such as Hitachi Scenaria, Sinovision Insitum, and Philips Incisive used respectively at UHA, UHT and Farah. Children’s scan data were classified into four age bands: vol or dose-length product as DLP) value, whatever the hospital, increases with respect to the age of child patients. Based on the 75th percentile of the whole dose distributions, the DRLs of the CTDIvol is 54.37 mGy whatever the age groups and those of the DLP with respect to age bands are 1224.55 mGy∙cm, 1414.06 mGy∙cm, 1632.24 mGy.cm and 1544.57 mGy∙cm, respectively. The averaged values of CTDIvol and DLP smaller than the corresponding DRLs values suggest that practices in our three facilities are optimized. However, comparing our results with those from different international studies, we see that the CTDIvol and DLP values obtained in the present work are higher. These results suggest additional surveys to ensure our DRLs values and efforts from radiologists, imaging technicians and medical physicists to strengthen clinical procedures for the radiation protection of children undergoing CT scans in Côte d’Ivoire.
文摘The purpose of this research was to evaluate radiological safety in pediatric radiology in hospitals in the Kongo Central province of the DRC. To this end, we surveyed a convenience sample of 50 health professionals, including 10 radiologists working in the hospitals covered by the survey, to assess the practice of pediatric radiology and the degree of compliance with radiation protection principles for the safety of children and the environment. We collected radiophysical parameters to calculate entrance doses in pediatric radiology in radiology departments to determine the dosimetric level by comparison with the diagnostic reference levels of the International Commission on Radiological Protection (ICRP). All in all, we found that in Kongo Central in the DRC, many health personnel surveyed reported that more than 30% of requested radiological examinations are not justified. Also, after comparing the entrance doses produced in the surveyed departments with those of the International Commission on Radiological Protection (ICRP), a statistically significant difference was found in pediatric radiology between the average doses in five out of six surveyed departments and those of the ICRP. Therefore, almost all of the surveyed departments were found to be highly irradiating in children, while excessive X-ray irradiation in children can have significant effects due to their increased sensitivity to radiation. Among the risks are: increased cancer risks, damage to developing cells, potential genetic effects, and neurological effects. This is why support for implementing radiation protection principles is a necessity to promote the safety of patients and the environment against the harmful effects of X-rays in conventional radiology.
基金supported by the Guangdong Provincial Clinical Research Center for Tuberculosis(No.2020B1111170014)。
文摘Objective To investigate the spatiotemporal patterns and socioeconomic factors influencing the incidence of tuberculosis(TB)in the Guangdong Province between 2010 and 2019.Method Spatial and temporal variations in TB incidence were mapped using heat maps and hierarchical clustering.Socioenvironmental influencing factors were evaluated using a Bayesian spatiotemporal conditional autoregressive(ST-CAR)model.Results Annual incidence of TB in Guangdong decreased from 91.85/100,000 in 2010 to 53.06/100,000in 2019.Spatial hotspots were found in northeastern Guangdong,particularly in Heyuan,Shanwei,and Shantou,while Shenzhen,Dongguan,and Foshan had the lowest rates in the Pearl River Delta.The STCAR model showed that the TB risk was lower with higher per capita Gross Domestic Product(GDP)[Relative Risk(RR),0.91;95%Confidence Interval(CI):0.86–0.98],more the ratio of licensed physicians and physician(RR,0.94;95%CI:0.90-0.98),and higher per capita public expenditure(RR,0.94;95%CI:0.90–0.97),with a marginal effect of population density(RR,0.86;95%CI:0.86–1.00).Conclusion The incidence of TB in Guangdong varies spatially and temporally.Areas with poor economic conditions and insufficient healthcare resources are at an increased risk of TB infection.Strategies focusing on equitable health resource distribution and economic development are the key to TB control.
文摘BACKGROUND Pepsinogen(PG)and the PG I/II ratio(PGR)are critical indicators for diagnosing Helicobacter pylori infection and chronic atrophic gastritis,and assessing gastric cancer risk.Existing reference intervals(RIs)often overlook age,sex,and demographic variations.Partitioned RIs,while considering these factors,fail to capture the gradual age-related physiological changes.Next-generation RIs offer a solution to this limitation.AIM To investigate age-and sex-specific dynamics of PG and establish next-generation RIs for adults and the elderly in northern China.METHODS After screening,708 healthy individuals were included in this observational study.Serum PG was measured using chemiluminescence immunoassay.Age-and sex-related effects on PG were analyzed with a two-way analysis of variance.RI partitioning was determined by the standard deviation ratio(SDR).Traditional RIs were established using a non-parametric approach.Generalized Additive Models for Location,Scale,and Shape(GAMLSS)modeled age-related trends and continuous reference percentiles for PG I and PG II.Reference limit flagging rates for both RI types were compared.RESULTS PG I and PG II levels were influenced by age(P<0.001)and sex(P<0.001),while PGR remained stable.Age-specific RIs were required for PG I(SDR=0.366)and PG II(SDR=0.424).Partitioned RIs were established for PG I and PG II,with a single RI for PGR.GAMLSS modeling revealed distinct age-dependent trajectories:PG I increased from a median of 39.75μg/L at age 20 years to 49.75μg/L at age 60 years,a 25.16%increase,after which it plateaued through age 80 years.In contrast,PG II showed a continuous rise throughout the age range,with the median value increasing from 5.07μg/L at age 20 years to 8.36μg/L at age 80 years,corresponding to a 64.89%increase.Continuous reference percentiles intuitively reflected these trends and were detailed in this study.Next-generation RIs demonstrated superior accuracy compared to partitioned RIs when applied to specific age subgroups.CONCLUSION This study elucidates the age-and sex-specific dynamics of PG and,to our knowledge,is the first to establish next-generation RIs for PG,supporting more individualized interpretation in laboratory medicine.
文摘This study examines the effects of rapid land use changes in India,with a specific focus on Sonipat District in Haryana—a region undergoing significant urban expansion.Over the past two decades,rural landscapes in Sonipat have undergone notable transformation,as open spaces and agricultural lands are increasingly converted into residential colonies,commercial hubs,and industrial zones.While such changes reflect economic development and urban growth,they also raise critical concerns about sustainability,especially in terms of food security,groundwater depletion,and environmental degradation.The study examines land use changes between 2000 and 2024 using remote sensing techniques and spatial analysis.It further incorporates secondary data and insights from community-level interactions to assess the socio-economic and ecological impacts of this transformation.The findings indicate rising land fragmentation,loss of agricultural livelihoods,pressure on civic infrastructure,and increasing pollution—factors that threaten long-term regional sustainability.The study underscores the urgent need to reconcile urban development with environmental and social sustainability.By offering a detailed case study of Sonipat,this research contributes to the broader discourse on India’s urbanisation pathways.It aims to provide policymakers,planners,and researchers with evidence-based recommendations to manage land transitions more responsibly,promoting urban growth models that ensure ecological integrity,equitable development,and long-term resilience.
基金supported by National Natural Science Foundation of China(Nos.62477026,62177029,61807020)Humanities and Social Sciences Research Program of the Ministry of Education of China(No.23YJAZH047)the Startup Foundation for Introducing Talent of Nanjing University of Posts and Communications under Grant NY222034.
文摘As Deepfake technology continues to evolve,the distinction between real and fake content becomes increasingly blurred.Most existing Deepfake video detectionmethods rely on single-frame facial image features,which limits their ability to capture temporal differences between frames.Current methods also exhibit limited generalization capabilities,struggling to detect content generated by unknown forgery algorithms.Moreover,the diversity and complexity of forgery techniques introduced by Artificial Intelligence Generated Content(AIGC)present significant challenges for traditional detection frameworks,whichmust balance high detection accuracy with robust performance.To address these challenges,we propose a novel Deepfake detection framework that combines a two-stream convolutional network with a Vision Transformer(ViT)module to enhance spatio-temporal feature representation.The ViT model extracts spatial features from the forged video,while the 3D convolutional network captures temporal features.The 3D convolution enables cross-frame feature extraction,allowing the model to detect subtle facial changes between frames.The confidence scores from both the ViT and 3D convolution submodels are fused at the decision layer,enabling themodel to effectively handle unknown forgery techniques.Focusing on Deepfake videos and GAN-generated images,the proposed approach is evaluated on two widely used public face forgery datasets.Compared to existing state-of-theartmethods,it achieves higher detection accuracy and better generalization performance,offering a robust solution for deepfake detection in real-world scenarios.
基金supported by the National Key Research and Development Program of China(Grant No.2021YFD2200502)the National Natural Science Foundation of China(Grant No.31971736).
文摘Bamboo was one of the first plants to be cultivated in China and is widely used in industry and daily life.The study of gene function has become an important part of bamboo breeding,whereas quantitative real-time PCR(qRT-PCR)is a powerful tool for gene expression analysis.The accuracy of qRT-PCR results largely depends on suitable reference genes.In this study,a transcriptome-wide identification of reference genes was conducted based on 447 transcriptome datasets,comprising 200 tissue samples,107 treated samples,and 140 samples from various moso bamboo(Phyllostachys edulis)forms.A total of 3444,1013,and 3962 stably expressed genes were identified from these three groups,respectively.Functional enrichment analysis revealed significant enrichment of these genes in pathways,including the spliceosome,proteasome,and oxidative phosphorylation.Eight candidate genes(ADPRE,GAPDH,TRX,TUBA,NRP,MBF,UNK,and CAM1),were selected for qRT-PCR validation using 112 samples.To assess their stability,five statistical methods(geNorm,NormFinder,BestKeeper,Delta-Ct,and RefFinder)were employed.The most suitable reference genes were ADPRE and GAPDH for different tissues,GAPDH and CAM1 for different treatments,and GAPDH and TRX for various moso bamboo forms.Overall,ADPRE and GAPDH were the most stable reference genes across all conditions,while TUBA and TRX were the least stable reference genes.In addition,a significant negative correlation was found between the Ct values of RT-qPCR and the log2TPM values from the transcriptome data(Ct=-1.534x+37.221),providing a potential method for estimating gene expression levels.The identified reference genes,particularly ADPRE and GAPDH,provide a robust set of references for gene expression studies in moso bamboo.
基金National Natural Science Foundation of China,No.42230106,No.42171250State Key Laboratory of Earth Surface Processes and Resource Ecology,No.2022-ZD-04。
文摘Agriculture holds a pivotal position in the economic fabric of every nation,yet concerns about agricultural carbon emission intensity(ACI)have become a major hurdle to achieving global economic sustainability.Focusing on 31 provincial-level regions in China,this study uses the Exploratory Spatio-temporal Data Analysis(ESTDA)and Panel Quantile Regression(PQR)model to analyze the spatio-temporal interaction characteristics and influencing factors of ACI in China from 2004 to 2023.The findings are as follows:(1)ACI showed an overall downward trend,and the spatial distribution pattern was characterized by“high in the western region and low along the southeastern coast”.Although the overall disparity tended to converge,some high-carbon-intensity regions exhibited extreme trends.ACI displayed clear spatial directionality,with the spatial center shifting steadily toward the northeast.(2)Regions in the northwest,northeast,and central-south parts exhibited strong local spatial structural dynamics,and the local spatial dependence of ACI in each region showed a nonlinear trend.Generally speaking,the spatial association pattern demonstrated a certain degree of inertia in spatial transfer,reflecting strong path dependence or spatial lock-in characteristics.(3)Optimization of industrial structure and improvement in agricultural mechanization will increase ACI,while economic development can effectively reduce it.The impact of urbanization on ACI exhibits a nonlinear pattern.The coordinated development of economic growth and urbanization significantly reduces ACI,with a stronger emission reduction observed in regions with low ACI.The optimization of industrial structure,when combined with urbanization and environmental regulation,contributes to significant emission reductions particularly in high-ACI areas.Similarly,the synergy between agricultural mechanization and urbanization effectively lowers emissions in low-ACI regions,though this effect diminishes in areas with higher ACI.
基金supported by the Key Laboratory of Natural Resources Monitoring and Supervision in Southern Hilly Region,Ministry of Natural Resources(NRMSSHR2023Y02)Yunnan Key Laboratory of Plateau Geographic Processes and Environmental Changes,Faculty of Geography,Yunnan Normal University(PGPEC2304)China Scholarship Council。
文摘Sloping farmland,particularly in mountainous and hilly areas,constitutes a significant component of regional farmland resources.An investigation into the spatio-temporal pattern of sloping farmland and its influencing factors in China is imperative for the efficient utilization of farmland and the optimization of land space.We used land use transfer matrix,geographically weighted regression model and geographical detector to conduct this study.Results showed that sloping farmland in China firstly decreased and then increased from 2000 to 2020.The proportion of sloping farmland decreased radially outward from Sichuan basin to the surrounding areas.Change rates of sloping farmland with different slopes varied and the slope with 6°-15°underwent the fastest changes.The influencing factors of farmland at various slope degrees were different.For sloping farmland below 15°,land use intensity and elevation had the greatest contribution.For sloping farmland between 15°and 25°,elevation,land use intensity,and population density were the main influencing factors.Sloping farmland above 25°was mostly affected by natural factors.This study can provide scientific basis for rational development and protection of sloping farmland.
基金support for this work was supported by Key Lab of Intelligent and Green Flexographic Printing under Grant ZBKT202301.
文摘Current spatio-temporal action detection methods lack sufficient capabilities in extracting and comprehending spatio-temporal information. This paper introduces an end-to-end Adaptive Cross-Scale Fusion Encoder-Decoder (ACSF-ED) network to predict the action and locate the object efficiently. In the Adaptive Cross-Scale Fusion Spatio-Temporal Encoder (ACSF ST-Encoder), the Asymptotic Cross-scale Feature-fusion Module (ACCFM) is designed to address the issue of information degradation caused by the propagation of high-level semantic information, thereby extracting high-quality multi-scale features to provide superior features for subsequent spatio-temporal information modeling. Within the Shared-Head Decoder structure, a shared classification and regression detection head is constructed. A multi-constraint loss function composed of one-to-one, one-to-many, and contrastive denoising losses is designed to address the problem of insufficient constraint force in predicting results with traditional methods. This loss function enhances the accuracy of model classification predictions and improves the proximity of regression position predictions to ground truth objects. The proposed method model is evaluated on the popular dataset UCF101-24 and JHMDB-21. Experimental results demonstrate that the proposed method achieves an accuracy of 81.52% on the Frame-mAP metric, surpassing current existing methods.
基金supported by the National Key Research and Development Pro-gram of China(2021YFF0601902)the National Reference Material Development Project(S2022234).
文摘To solve the problem of the lack of reference material(RM)for determination of allergenic ingredients in food,a RM of cashew nut powder was developed in the study.Cashew nut powder was prepared from cashew nut kernel by selecting,cleaning,crushing,n-hexane degreasing and sieving treatment.The reliability and traceability of RM was verified using real-time quantitative polymerase chain reaction(qPCR)and phylogenetic tree analysis.The cashew nut powder RM showed good homogeneity,and good stability under long-term storage at 4℃and short-term simulated transportation from-20 to 45℃.The RM was determined jointly by 8 collaborative laboratories,and the characteristic CT value was 24.732,and the extended uncertainty was 1.052%(k=2).The RM was applied to verify the amplification efficiency and the limit of detection for qPCR assay,and showed good applicability.The RM could be used for method validation and quality control,for the determination of allergenic ingredients in food mixed with trace amounts of cashew nut.
基金supported by The Henan Province Science and Technology Research Project(242102211046)the Key Scientific Research Project of Higher Education Institutions in Henan Province(25A520039)+1 种基金theNatural Science Foundation project of Zhongyuan Institute of Technology(K2025YB011)the Zhongyuan University of Technology Graduate Education and Teaching Reform Research Project(JG202424).
文摘Electrocardiogram (ECG) analysis is critical for detecting arrhythmias, but traditional methods struggle with large-scale Electrocardiogram data and rare arrhythmia events in imbalanced datasets. These methods fail to perform multi-perspective learning of temporal signals and Electrocardiogram images, nor can they fully extract the latent information within the data, falling short of the accuracy required by clinicians. Therefore, this paper proposes an innovative hybrid multimodal spatiotemporal neural network to address these challenges. The model employs a multimodal data augmentation framework integrating visual and signal-based features to enhance the classification performance of rare arrhythmias in imbalanced datasets. Additionally, the spatiotemporal fusion module incorporates a spatiotemporal graph convolutional network to jointly model temporal and spatial features, uncovering complex dependencies within the Electrocardiogram data and improving the model’s ability to represent complex patterns. In experiments conducted on the MIT-BIH arrhythmia dataset, the model achieved 99.95% accuracy, 99.80% recall, and a 99.78% F1 score. The model was further validated for generalization using the clinical INCART arrhythmia dataset, and the results demonstrated its effectiveness in terms of both generalization and robustness.
基金supported by the Natural Science Foundation of Qinghai Province(2022-ZJ-902).
文摘The use of a stable reference gene is fundamental for achieving reliable quantitative qRT-PCR (qPCR) results. Developing and evaluating the stability of reference genes is necessary for studying the molecular mechanisms of M. transitoria in response to drought stress. In this study, 18 candidate reference genes were selected from transcriptome sequencing data of M. transitoria according to their FPKM values under different drought stress degrees. Cluster-23533.34641 was identified as the most stable reference gene for M. transitoria under drought stress based on qPCR results and combined analysis of Genorm, NormFinder, BestKeeper, and Delta Ct algorithms. The reference genes identified in this research offer improved accuracy for quantifying target gene expression in both M. transitoria and Malus species under drought stress. This study could provide insights into the drought stress-related functional gene or factor in M. transitoria, even in Malus species.
基金supported by the National Natural Science Foundation of China(Nos.42003014,42363004,42073051,42303023)Jiangxi Provincial Natural Science Foundation(No.20232BAB213070)the Natural Science Foundation of Shandong Province(No.ZR2022QD050)。
文摘Sulfur isotopes of S-bearing materials are powerful tools to trace various geological processes and sulfur sources in earth sciences,especially in ore deposits where sulfide-sulfate pair coprecipitates widely.However,in-situ S isotope determination of barite is challenging without natural matrix-matched reference material.In this study,we present two natural barite reference materials(1-YS and 294-YS)for in-situ sulfur isotopic analysis.Independent LA-MC-ICP-MS laboratories were utilized to test theδ34S micron-scale homogeneity of 1-YS and 294-YS barites that have 2s repeatabilities of better than±0.45‰and±0.41‰,respectively.Meanwhile,the in-situ analysis results are consistent with the results of the bulk analysis by GS-IRMS within uncertainty.The grand meanδ~(34)S values of 1-YS(13.37‰±0.42‰,2s)and 294-YS(14.38‰±0.44‰,2s)are the final recommended values obtained from four independent laboratories.All the results confirm the suitability of 1-YS and 294-YS barite used as calibration materials with respect to in-situ S isotopic analysis.Moreover,the new developed barite reference materials were used as matrix-matched standard to calibrate the barite samples from the Huayangchuan carbonatite-hosted U-polymetallic deposit(Qinling orogenic belt,western China)to obtainδ34S values.Utilizing the temperaturedependentδ34S fractionation of barite-pyrite pair,we calculate the formation temperature of barite(i.e.,506 to 537°C)and theδ34S value of mineralizing fluid(i.e.,-7.11‰to-7.59‰)in the Huayangchuan deposit.The results indicate an involvement of sedimentary sulfur,presumably acting as a potential uranium source(e.g.,upper crustal materials)for the giant Huayangchuan deposit.
基金supported by the National Natural Science Foundation of China(No.22206180)the funds for establishing basic quality and technology capabilities(No.ANL2203)the special fund for basic scientific research business of central public research institutes(No.AKYZD2207-4)。
文摘Carbonaceous aerosol,including organic carbon(OC)and elemental carbon(EC),has significant influence on human health,air quality and climate change.Accurate measurement of carbonaceous aerosol is essential to reduce the uncertainty of radiative forcing estimation and source apportionment.The accurate separation of OC and EC is controversial due to the charring of OC.Therefore,the development of reference materials(RM)for the validation of OC/EC separation is an important basis for further study.Previous RMs were mainly based on ambient air sampling,which could not provide traceability of OC and EC concentration.To develop traceable RMs with known OC/EC contents,our study applied an improved aerosol generation and mixing technique,providing uniform deposition of particles on quartz filters.To generate OC aerosol with similar pyrolytic property of ambient aerosol,both water soluble organic carbon(WSOC)and water insoluble organic carbon(WIOC)were used,and amorphous carbon was selected for EC surrogate.The RMs were analyzed using different protocols.The homogeneity within the filter was validated,reaching below 2%.The long-term stability of RMs has been validated with RSD ranged from 1.7%–3.2%.Good correlationwas observed between nominal concentration of RMswithmeasured concentration by two protocols,while the difference of EC concentration was within 20%.The results indicated that the newly developed RMs were acceptable for the calibration of OC and EC,which could improve the accuracy of carbonaceous aerosol measurement.Moreover,the laboratory-generated EC-RMs could be suitable for the calibration of equivalent BC concentration by Aethalometers.
基金funded by Princess Nourah bint Abdulrahman University and Researchers Supporting Project number(PNURSP2024R136),Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘Reference Evapotranspiration(ETo)iswidely used to assess totalwater loss between land and atmosphere due to its importance in maintaining the atmospheric water balance,especially in agricultural and environmental management.Accurate estimation of ETo is challenging due to its dependency onmultiple climatic variables,including temperature,humidity,and solar radiation,making it a complexmultivariate time-series problem.Traditional machine learning and deep learning models have been applied to forecast ETo,achieving moderate success.However,the introduction of transformer-based architectures in time-series forecasting has opened new possibilities formore precise ETo predictions.In this study,a novel algorithm for ETo forecasting is proposed,focusing on four transformer-based models:Vanilla Transformer,Informer,Autoformer,and FEDformer(Frequency Enhanced Decomposed Transformer),applied to an ETo dataset from the Andalusian region.The novelty of the proposed algorithm lies in determining optimized window sizes based on seasonal trends and variations,which were then used with each model to enhance prediction accuracy.This custom window-sizing method allows the models to capture ETo’s unique seasonal patterns more effectively.Finally,results demonstrate that the Informer model outperformed other transformer-based models,achievingmean square error(MSE)values of 0.1404 and 0.1445 for forecast windows(15,7)and(30,15),respectively.The Vanilla Transformer also showed strong performance,closely following the Informermodel.These findings suggest that the proposed optimized window-sizing approach,combined with transformer-based architectures,is highly effective for ETo modelling.This novel strategy has the potential to be adapted in othermultivariate time-series forecasting tasks that require seasonality-sensitive approaches.
