With the improvement of equipment reliability,human factors have become the most uncertain part in the system.The standardized Plant Analysis of Risk-Human Reliability Analysis(SPAR-H)method is a reliable method in th...With the improvement of equipment reliability,human factors have become the most uncertain part in the system.The standardized Plant Analysis of Risk-Human Reliability Analysis(SPAR-H)method is a reliable method in the field of human reliability analysis(HRA)to evaluate human reliability and assess risk in large complex systems.However,the classical SPAR-H method does not consider the dependencies among performance shaping factors(PSFs),whichmay cause overestimation or underestimation of the risk of the actual situation.To address this issue,this paper proposes a new method to deal with the dependencies among PSFs in SPAR-H based on the Pearson correlation coefficient.First,the dependence between every two PSFs is measured by the Pearson correlation coefficient.Second,the weights of the PSFs are obtained by considering the total dependence degree.Finally,PSFs’multipliers are modified based on the weights of corresponding PSFs,and then used in the calculating of human error probability(HEP).A case study is used to illustrate the procedure and effectiveness of the proposed method.展开更多
Ten physical and environmental variables collected from an on-the-go soil sensor at two field sites (MF3E and MF11S) in Mississippi, USA, were analyzed to assess soil variability and the interrelationships among the m...Ten physical and environmental variables collected from an on-the-go soil sensor at two field sites (MF3E and MF11S) in Mississippi, USA, were analyzed to assess soil variability and the interrelationships among the measurements. At MF3E, moderate variability was observed in apparent electrical conductivity shallow (ECas), slope, and ECa ratio measurements, with coefficients of variation ranging from 20% to 27%. In contrast, MF11S exhibited higher variability, particularly in ECas and ECad (deep) measurements, which exceeded 30% in their coefficient of variation values, indicating significant differences in soil composition and moisture content. Correlation analysis revealed strong positive relationships between the near-infrared-to-red ratio and red reflectance (r = 0.897***) soil values at MF3E. MF11S demonstrated a strong negative correlation between ECas and ECad readings with the x-coordinate (r ***). Scatter plots and fitted models illustrated the complexity of relationships, with many showing nonlinear trends. These findings emphasize the need for continuous monitoring and advanced modeling to understand the dynamic nature of soil properties and their implications for agricultural practices. Future research should explore the underlying mechanisms driving variability in the soil characteristics to enhance soil management strategies at the study sites.展开更多
Accurate forecasting of blast furnace gas(BFG)production is an essential prerequisite for reasonable energy scheduling and management to reduce carbon emissions.Coupling forecasting between BFG generation and consumpt...Accurate forecasting of blast furnace gas(BFG)production is an essential prerequisite for reasonable energy scheduling and management to reduce carbon emissions.Coupling forecasting between BFG generation and consumption dynamics was taken as the research object.A multi-task learning(MTL)method for BFG forecasting was proposed,which integrated a coupling correlation coefficient(CCC)and an inverted transformer structure.The CCC method could enhance key information extraction by establishing relationships between multiple prediction targets and relevant factors,while MTL effectively captured the inherent correlations between BFG generation and consumption.Finally,a real-world case study was conducted to compare the proposed model with four benchmark models.Results indicated significant reductions in average mean absolute percentage error by 33.37%,achieving 1.92%,with a computational time of 76 s.The sensitivity analysis of hyperparameters such as learning rate,batch size,and units of the long short-term memory layer highlights the importance of hyperparameter tuning.展开更多
Since antiquity,humans have been involved in designing materials through alloying strategies to meet the ever-growing technological demands.In 2004,this endeavor witnessed a significant breakthrough with the discovery...Since antiquity,humans have been involved in designing materials through alloying strategies to meet the ever-growing technological demands.In 2004,this endeavor witnessed a significant breakthrough with the discovery of high-entropy alloys(HEAs)comprising multi-principal elements.Owing to the four“core-effects”,these alloys exhibit exceptional properties including better structural stability,high strength and ductility,improved fatigue/fracture toughness,high corrosion and oxidation resistance,superconductiv-ity,magnetic properties,and good thermal properties.Different synthesis routes have been designed and used to meet the properties of interest for particular applications with varying dimensions.How-ever,HEAs are providing new opportunities and challenges for computational modelling of the complex structure-property correlations and in predictions of phase stability necessary for optimum performance of the alloy.Several attempts have been made to understand these alloys by empirical and computa-tional models,and data-driven approaches to accelerate the materials discovery with a desired set of properties.The present review discusses advances and inferences from simulations and models spanning multiple length and time scales explaining a comprehensive set of structure-properties relations.Addi-tionally,the role of machine learning approaches is also reviewed,underscoring the transformative role of computational modelling in unravelling the multifaceted properties and applications of HEAs,and the scope for future efforts in this direction.展开更多
Geomagnetic observatory data are crucial for all branches of geophysics because they can contribute to earthquake research by detecting anomalies in the Earth’s magnetic field.Recently,data records from the Misallat(...Geomagnetic observatory data are crucial for all branches of geophysics because they can contribute to earthquake research by detecting anomalies in the Earth’s magnetic field.Recently,data records from the Misallat(MLT)and Abu Simbel(ABS)Egyptian geomagnetic observatories were processed and found to be of good quality.In this study,Egyptian observatory data were tested during both quiet and disturbed events and compared with data from INTERMAGNET observatories worldwide at different latitudes and within a narrow range of longitudes in both hemispheres.This study investigated the relationships between magnetic field components from Egyptian observatories and those from INTERMAGNET observatories using graphical representations of the X components;Pearson’s correlation for the X,Y,Z,and F components;cross-correlation for the X component;and wavelet coherence for the F component.The results of this study showed a high correlation between Egyptian observatories and all utilized INTERMAGNET stations,except those located at high latitudes,during both quiet and disturbed events.Additionally,the study confirmed the observed consistency between Egyptian observatories and selected INTERMAGNET stations.Therefore,Egyptian observatories can feasibly fill the gap in the Middle East and North Africa.展开更多
The morphological distribution of absorbent in composites is equally important with absorbents for the overall electromagnetic properties,but it is often ignored.Herein,a comprehensive consideration including electrom...The morphological distribution of absorbent in composites is equally important with absorbents for the overall electromagnetic properties,but it is often ignored.Herein,a comprehensive consideration including electromagnetic component regulation,layered arrangement structure,and gradient concentration distribution was used to optimize impedance matching and enhance electromagnetic loss.On the microscale,the incorporation of magnetic Ni nanoparticles into MXene nanosheets(Ni@MXene)endows suitable intrinsic permittivity and permeability.On the macroscale,the layered arrangement of Ni@MXene increases the effective interaction area with electromagnetic waves,inducing multiple reflection/scattering effects.On this basis,according to the analysis of absorption,reflection,and transmission(A-R-T)power coefficients of layered composites,the gradient concentration distribution was constructed to realize the impedance matching at low-concentration surface layer,electromagnetic loss at middle concentration interlayer and microwave reflection at high-concentration bottom layer.Consequently,the layered gradient composite(LG5-10-15)achieves complete absorption coverage of X-band at thickness of 2.00-2.20 mm with RL_(min) of-68.67 dB at 9.85 GHz in 2.05 mm,which is 199.0%,12.6%,and 50.6%higher than non-layered,layered and layered descending gradient composites,respectively.Therefore,this work confirms the importance of layered gradient structure in improving absorption performance and broadens the design of high-performance microwave absorption materials.展开更多
BACKGROUND Resilience is an individual’s ability and psychological rebound capacity to adapt well after experiencing adversity,trauma,etc.Patients with strong resilience can face illnesses actively.AIM To determine t...BACKGROUND Resilience is an individual’s ability and psychological rebound capacity to adapt well after experiencing adversity,trauma,etc.Patients with strong resilience can face illnesses actively.AIM To determine the association of resilience with coping styles and quality of life in patients with malignancies.METHODS This study included patients with malignant tumors who were hospitalized at Fuyang Hospital Affiliated to Anhui Medical University from March 2022 to March 2024.The Connor-Davidson Resilience Scale,Medical Coping Modes Questionnaire,Social Support Rating Scale,and the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 were utilized to assess patients’resilience,coping styles,social support,and quality of life,respectively.Pearson correlation analysis was conducted to assess the correlations.RESULTS A total of 175 patients with malignant tumors demonstrated no marked difference in terms of age,education level,employment status,monthly household income,and disease staging(P<0.05).Further,patients with malignancies demonstrated scores of 17.49±1.20,17.27±1.46,and 11.19±1.29 points in terms of coping styles in confrontation,avoidance,and resignation dimensions,respectively.Subjective support,objective support,and support utilization scores in terms of social support were 10.67±1.80,11.26±2.08,and 9.24±1.14 points,respectively.The total resilience score and tenacity,self-improvement,and optimism dimension scores were positively correlatedwith the confrontation coping style score,whereas the total resilience score and tenacity and self-improvementscores were negatively associated with avoidance and resignation coping style scores(P<0.05).The total resiliencescore and the tenacity dimension score were positively associated with physical,role,cognitive,emotional,andsocial functions,as well as global health status(P<0.05),and were inversely related to fatigue,insomnia,andeconomic difficulties(P<0.05).CONCLUSIONThe resilience of patients with malignancies is positively associated with the confrontation dimension in the copingstyle,the total and various social support domain scores,and the overall quality of life.Clinical medical staff needto pay attention to the effect of medical coping styles and social support on the resilience level of patients withmalignancies to further improve their quality of life.展开更多
Video snapshot compressive imaging(Video SCI) modulates scenes using various encoding masks and captures compressed measurements with a low-speed camera during a single exposure. Subsequently, reconstruction algorithm...Video snapshot compressive imaging(Video SCI) modulates scenes using various encoding masks and captures compressed measurements with a low-speed camera during a single exposure. Subsequently, reconstruction algorithms restore image sequences of dynamic scenes, offering advantages such as reduced bandwidth and storage space requirements. The temporal correlation in video data is crucial for Video SCI, as it leverages the temporal relationships among frames to enhance the efficiency and quality of reconstruction algorithms, particularly for fast-moving objects.This paper discretizes video frames to create image datasets with the same data volume but differing temporal correlations. We utilized the state-of-the-art(SOTA) reconstruction framework, EfficientSCI++, to train various compressed reconstruction models with these differing temporal correlations. Evaluating the reconstruction results from these models, our simulation experiments confirm that a reduction in temporal correlation leads to decreased reconstruction accuracy. Additionally, we simulated the reconstruction outcomes of datasets devoid of temporal correlation, illustrating that models trained on non-temporal data affect the temporal feature extraction capabilities of transformers, resulting in negligible impacts on the evaluation of reconstruction results for non-temporal correlation test datasets.展开更多
The Fushan Depression is one of the petroliferous depressions in the Beibuwan Basin,South China Sea.Previous studies have preliminarily explored the origin and source of crude oils in some areas of this depression.Nev...The Fushan Depression is one of the petroliferous depressions in the Beibuwan Basin,South China Sea.Previous studies have preliminarily explored the origin and source of crude oils in some areas of this depression.Nevertheless,no systematic investigations on the classification and origin of oils and hy-drocarbon migration processes have been made for the entire petroleum system in this depression,which has significantly hindered the hydrocarbon exploration in the region.A total of 32 mudstone and 58 oil samples from the Fushan Depression were analyzed to definite the detailed oil-source correlation within the sequence and sedimentary framework.The organic matter of third member of Paleogene Liushagang Formation(Els(3))source rocks,both deltaic and lacustrine mudstone,are algal-dominated with high abundance of C_(23)tricyclic terpane and C_(30)4-methylsteranes.The deltaic source rocks occur-ring in the first member(Els_(1))and second member(Els_(2))of the Paleogene Liushagang Formation are characterized by high abundance of C_(19+20)tricyclic terpane and oleanane,reflecting a more terrestrial plants contribution.While lacustrine source rocks of Els_(1)and Els_(2)display the reduced input of terrige-nous organic matter with relatively low abundance of C 19+20 tricyclic terpane and oleanane.Three types of oils were identified by their biomarker compositions in this study.Most of the oils discovered in the Huachang and Bailian Els_(1)reservoir belong to group A and were derived from lacustrine source rocks of Els_(1)and Els_(2).Group B oils are found within the Els_(1)and Els_(2)reservoirs,showing a close relation to the deltaic source rocks of Els_(1)and Els_(2),respectively.Group C oils,occurring in the Els3 reservoirs,have a good affinity with the Els3 source rocks.The spatial distribution and accumulation of different groups of oils are mainly controlled by the sedimentary facies and specific structural conditions.The Els_(2)reservoir in the Yong'an area belonging to Group B oil,are adjacent to the source kitchen and could be considered as the favorable exploration area in the future.展开更多
Passive acoustic monitoring(PAM)technology is increasingly becoming one of the mainstream methods for bird monitoring.However,detecting bird audio within complex natural acoustic environments using PAM devices remains...Passive acoustic monitoring(PAM)technology is increasingly becoming one of the mainstream methods for bird monitoring.However,detecting bird audio within complex natural acoustic environments using PAM devices remains a significant challenge.To enhance the accuracy(ACC)of bird audio detection(BAD)and reduce both false negatives and false positives,this study proposes a BAD method based on a Dual-Feature Enhancement Fusion Model(DFEFM).This method incorporates per-channel energy normalization(PCEN)to suppress noise in the input audio and utilizes mel-frequency cepstral coefficients(MFCC)and frequency correlation matrices(FCM)as input features.It achieves deep feature-level fusion of MFCC and FCM on the channel dimension through two independent multi-layer convolutional network branches,and further integrates Spatial and Channel Synergistic Attention(SCSA)and Multi-Head Attention(MHA)modules to enhance the fusion effect of the aforementioned two deep features.Experimental results on the DCASE2018 BAD dataset show that our proposed method achieved an ACC of 91.4%and an AUC value of 0.963,with false negative and false positive rates of 11.36%and 7.40%,respectively,surpassing existing methods.The method also demonstrated detection ACC above 92%and AUC values above 0.987 on datasets from three sites of different natural scenes in Beijing.Testing on the NVIDIA Jetson Nano indicated that the method achieved an ACC of 89.48%when processing an average of 10 s of audio,with a response time of only 0.557 s,showing excellent processing efficiency.This study provides an effective method for filtering non-bird vocalization audio in bird vocalization monitoring devices,which helps to save edge storage and information transmission costs,and has significant application value for wild bird monitoring and ecological research.展开更多
BACKGROUND At present,the conventional methods for diagnosing cerebral edema in clinical practice are computed tomography(CT)and magnetic resonance imaging(MRI),which can evaluate the location and degree of peripheral...BACKGROUND At present,the conventional methods for diagnosing cerebral edema in clinical practice are computed tomography(CT)and magnetic resonance imaging(MRI),which can evaluate the location and degree of peripheral cerebral edema,but cannot realize quantification.When patients have symptoms of diffuse cerebral edema or high cranial pressure,CT or MRI often suggests that cerebral edema is lagging and cannot be dynamically monitored in real time.Intracranial pressure monitoring is the gold standard,but it is an invasive operation with high cost and complications.For clinical purposes,the ideal cerebral edema monitoring should be non-invasive,real-time,bedside,and continuous dynamic monitoring.The dis-turbance coefficient(DC)was used in this study to dynamically monitor the occu-rrence,development,and evolution of cerebral edema in patients with cerebral hemorrhage in real time,and review head CT or MRI to evaluate the development of the disease and guide further treatment,so as to improve the prognosis of patients with cerebral hemorrhage.AIM To offer a promising new approach for non-invasive adjuvant therapy in cerebral edema treatment.METHODS A total of 160 patients with hypertensive cerebral hemorrhage admitted to the Department of Neurosurgery,Second Affiliated Hospital of Xi’an Medical University from September 2018 to September 2019 were recruited.The patients were randomly divided into a control group(n=80)and an experimental group(n=80).Patients in the control group received conventional empirical treatment,while those in the experimental group were treated with mannitol dehydration under the guidance of DC.Subsequently,we compared the two groups with regards to the total dosage of mannitol,the total course of treatment,the incidence of complications,and prognosis.RESULTS The mean daily consumption of mannitol,the total course of treatment,and the mean hospitalization days were 362.7±117.7 mL,14.8±5.2 days,and 29.4±7.9 in the control group and 283.1±93.6 mL,11.8±4.2 days,and 23.9±8.3 in the experimental group(P<0.05).In the control group,there were 20 patients with pulmonary infection(25%),30 with electrolyte disturbance(37.5%),20 with renal impairment(25%),and 16 with stress ulcer(20%).In the experimental group,pulmonary infection occurred in 18 patients(22.5%),electrolyte disturbance in 6(7.5%),renal impairment in 2(2.5%),and stress ulcers in 15(18.8%)(P<0.05).According to the Glasgow coma scale score 6 months after discharge,the prognosis of the control group was good in 20 patients(25%),fair in 26(32.5%),and poor in 34(42.5%);the prognosis of the experimental group was good in 32(40%),fair in 36(45%),and poor in 12(15%)(P<0.05).CONCLUSION Using DC for non-invasive dynamic monitoring of cerebral edema demonstrates considerable clinical potential.It reduces mannitol dosage,treatment duration,complication rates,and hospital stays,ultimately lowering hospital-ization costs.Additionally,it improves overall patient prognosis,offering a promising new approach for non-invasive adjuvant therapy in cerebral edema treatment.展开更多
BACKGROUND Various stone factors can affect the net results of shock wave lithotripsy(SWL).Recently a new factor called variation coefficient of stone density(VCSD)is being considered to have an impact on stone free r...BACKGROUND Various stone factors can affect the net results of shock wave lithotripsy(SWL).Recently a new factor called variation coefficient of stone density(VCSD)is being considered to have an impact on stone free rates.AIM To assess the role of VCSD in determining success of SWL in urinary calculi.METHODS Charts review was utilized for collection of data variables.The patients were subjected to SWL,using an electromagnetic lithotripter.Mean stone density(MSD),stone heterogeneity index(SHI),and VCSD were calculated by generating regions of interest on computed tomography(CT)images.Role of these factors were determined by applying the relevant statistical tests for continuous and categorical variables and a P value of<0.05 was gauged to be statistically significant.RESULTS There were a total of 407 patients included in the analysis.The mean age of the subjects in this study was 38.89±14.61 years.In total,165 out of the 407 patients could not achieve stone free status.The successful group had a significantly lower stone volume as compared to the unsuccessful group(P<0.0001).Skin to stone distance was not dissimilar among the two groups(P=0.47).MSD was significantly lower in the successful group(P<0.0001).SHI and VCSD were both significantly higher in the successful group(P<0.0001).CONCLUSION VCSD,a useful CT based parameter,can be utilized to gauge stone fragility and hence the prediction of SWL outcomes.展开更多
Joint roughness coefficient(JRC)is the most commonly used parameter for quantifying surface roughness of rock discontinuities in practice.The system composed of multiple roughness statistical parameters to measure JRC...Joint roughness coefficient(JRC)is the most commonly used parameter for quantifying surface roughness of rock discontinuities in practice.The system composed of multiple roughness statistical parameters to measure JRC is a nonlinear system with a lot of overlapping information.In this paper,a dataset of eight roughness statistical parameters covering 112 digital joints is established.Then,the principal component analysis method is introduced to extract the significant information,which solves the information overlap problem of roughness characterization.Based on the two principal components of extracted features,the white shark optimizer algorithm was introduced to optimize the extreme gradient boosting model,and a new machine learning(ML)prediction model was established.The prediction accuracy of the new model and the other 17 models was measured using statistical metrics.The results show that the prediction result of the new model is more consistent with the real JRC value,with higher recognition accuracy and generalization ability.展开更多
Let f be a primitive holomorphic cusp form with even integral weight k≥2 for the full modular groupΓ=SL(2,Z)andλ_(sym^(j)f)(n)be the n-th coefficient of Dirichlet series of j-th symmetric L-function L(s,sym^(j)f)at...Let f be a primitive holomorphic cusp form with even integral weight k≥2 for the full modular groupΓ=SL(2,Z)andλ_(sym^(j)f)(n)be the n-th coefficient of Dirichlet series of j-th symmetric L-function L(s,sym^(j)f)attached to f.In this paper,we study the mean value distribution over a specific sparse sequence of positive integers of the following sum∑(a^(2)+b^(2)+c^(2)+d^(2)≤x(a,b,c,d)∈Z^(4))λ_(sym^(j))^(i)f(a^(2)+b^(2)+c^(2)+d^(2))where j≥2 is a given positive integer,i=2,3,4 andαis sufficiently large.We utilize Python programming to design algorithms for higher power conditions,combining Perron's formula,latest results of representations of natural integers as sums of squares,as well as analytic properties and subconvexity and convexity bounds of automorphic L-functions,to ensure the accuracy and verifiability of asymptotic formulas.The conclusion we obtained improves previous results and extends them to a more general settings.展开更多
Quanto options allow the buyer to exchange the foreign currency payoff into the domestic currency at a fixed exchange rate. We investigate quanto options with multiple underlying assets valued in different foreign cur...Quanto options allow the buyer to exchange the foreign currency payoff into the domestic currency at a fixed exchange rate. We investigate quanto options with multiple underlying assets valued in different foreign currencies each with a different strike price in the payoff function. We carry out a comparative performance analysis of different stochastic volatility (SV), stochastic correlation (SC), and stochastic exchange rate (SER) models to determine the best combination of these models for Monte Carlo (MC) simulation pricing. In addition, we test the performance of all model variants with constant correlation as a benchmark. We find that a combination of GARCH-Jump SV, Weibull SC, and Ornstein Uhlenbeck (OU) SER performs best. In addition, we analyze different discretization schemes and their results. In our simulations, the Milstein scheme yields the best balance between execution times and lower standard deviations of price estimates. Furthermore, we find that incorporating mean reversion into stochastic correlation and stochastic FX rate modeling is beneficial for MC simulation pricing. We improve the accuracy of our simulations by implementing antithetic variates variance reduction. Finally, we derive the correlation risk parameters Cora and Gora in our framework so that correlation hedging of quanto options can be performed.展开更多
By introducing noncanonical vortex pairs to partially coherent beams, spatial correlation singularity (SCS) and orbital angular momenta (OAM) of the resulting beams are studied using the Fraunhofer diffraction integra...By introducing noncanonical vortex pairs to partially coherent beams, spatial correlation singularity (SCS) and orbital angular momenta (OAM) of the resulting beams are studied using the Fraunhofer diffraction integral. The effect of noncanonical strength, off-axis distance and vortex sign on spatial correlation singularities in far field is stressed. Furthermore, far-field OAM spectra and densities are also investigated, and the OAM detection and crosstalk probabilities are discussed. The results show that the number of dislocations of SCS always equals the sum of absolute values of topological charges for canonical or noncanonical vortex pairs. Although the sum of the product of each OAM mode and its power weight equals the algebraic sum of topological charges for canonical vortex pairs, the relationship no longer holds in the noncanonical case except for opposite-charge vortex pairs. The changes of off-axis distance, noncanonical strength or coherence length can lead to a more dominant power in adjacent mode than that in center detection mode, which also indicates that crosstalk probabilities of adjacent modes exceed the center detection probability. This work may provide potential applications in OAM-based optical communication, imaging, sensing and computing.展开更多
Background: The use of assisted reproductive technique (ART) is becoming more common in infertility. During ART most patients undergo ovarian stimulation. In this study we study the correlation between ovarian reserve...Background: The use of assisted reproductive technique (ART) is becoming more common in infertility. During ART most patients undergo ovarian stimulation. In this study we study the correlation between ovarian reserve markers: Anti-Mullerian hormone (AMH) and antral follicle count (AFC), and the response to ovarian stimulation at in vitro fertilization (IVF) centres in Douala Cameroon. Methods: This was a hospital based cross-sectional sectional analytic study carried out over a period of 3 years, 4 months at Clinique de l’Aéroport, Clinique Odyssée and Clinique Urogyn. Inclusion criteria were: Female partners of infertile couples undergoing ovarian stimulation for an in vitro fertilization cycle, patients who had both ovaries and had done either AMH, AFC or both before ovarian stimulation. Patients were divided into three groups based on the number of oocytes retrieved: low ovarian response for ≤3 oocytes, normal ovarian response for 4 - 15 oocytes and high ovarian response for >15 oocytes. Data obtained was analyzed by SPSS version 25.0. Results: The ages of participants ranged from 20 - 4 7 years, with a mean age of 34.11 ± 5.11 years. Most of them had secondary infertility (57.9%). The GnRH antagonist protocol was mainly used, and ovulation was triggered using HCG predominantly. On Multivariate analysis, age and history of PCOS were significantly associated with ovarian response in the low and high ovarian response groups, respectively. Conclusion: AMH has a better predictive value than AFC, however, it is less sensitive but more specific than AFC.展开更多
The Infrared Hyperspectral Atmospheric SounderⅡ(HIRAS-Ⅱ)is the key equipment on FengYun-3E(FY-3E)satellite,which can realize vertical atmospheric detection,featuring hyper spectral,high sensitivity and high precisio...The Infrared Hyperspectral Atmospheric SounderⅡ(HIRAS-Ⅱ)is the key equipment on FengYun-3E(FY-3E)satellite,which can realize vertical atmospheric detection,featuring hyper spectral,high sensitivity and high precision.To ensure its accuracy of detection,it is necessary to correlate their thermal models to in-orbit da⁃ta.In this work,an investigation of intelligent correlation method named Intelligent Correlation Platform for Ther⁃mal Model(ICP-TM)was established,the advanced Kriging surrogate model and efficient adaptive region opti⁃mization algorithm were introduced.After the correlation with this method for FY-3E/HIRAS-Ⅱ,the results indi⁃cate that compared with the data in orbit,the error of the thermal model has decreased from 5 K to within±1 K in cold case(10℃).Then,the correlated model is validated in hot case(20℃),and the correlated model exhibits good universality.This correlation precision is also much superiors to the general ones like 3 K in other similar lit⁃erature.Furthermore,the process is finished in 8 days using ICP-TM,the efficiency is much better than 3 months based on manual.The results show that the proposed approach significantly enhances the accuracy and efficiency of thermal model,this contributes to the precise thermal control of subsequent infrared optical payloads.展开更多
The study of the morphometric parameters of the three most abundant species in the lower course of the Kouilou River (Chrysichthys auratus, Liza falcipinnis and Pellonula vorax) was carried out. The standard length of...The study of the morphometric parameters of the three most abundant species in the lower course of the Kouilou River (Chrysichthys auratus, Liza falcipinnis and Pellonula vorax) was carried out. The standard length of Chrysichthys auratus varies between 43.57 and 210 mm, for an average of 96.70 ± 28.63 mm;the weight varies between 2.92 and 140.83 mg, an average of 73.03 ± 21.62 mg. The condition coefficient is equal to 4.42 ± 1.52. Liza falcipinnis has a standard length which varies between 59.9 mm and 158.08 mm for an average of 88.15 ± 29.74 mm;its weight varies between 4.77 and 76.21 mg, an average of 18.61 ± 11.82 mg. The condition coefficient is equal to 2.47 ± 1.57. Pellonula vorax has a standard length which varies between 60.33 mm and 117.72 mm;for an average of 80.48 ± 17.75 mm;the weight varies between 3.61 and 25.17 mg, an average of 9.03 ± 3.61 mg. The condition coefficient is equal to 2.17 ± 0.57. These three species have a minor allometric growth.展开更多
Portfolio selection based on the global minimum variance(GMV)model remains a significant focus in financial research.The covariance matrix,central to the GMV model,determines portfolio weights,and its accurate estimat...Portfolio selection based on the global minimum variance(GMV)model remains a significant focus in financial research.The covariance matrix,central to the GMV model,determines portfolio weights,and its accurate estimation is key to effective strategies.Based on the decomposition form of the covariance matrix.This paper introduces semi-variance for improved financial asymmetric risk measurement;addresses asymmetry in financial asset correlations using distance,asymmetric,and Chatterjee correlations to refine covariance matrices;and proposes three new covariance matrix models to enhance risk assessment and portfolio selection strategies.Testing with data from 30 stocks across various sectors of the Chinese market confirms the strong performance of the proposed strategies.展开更多
基金Shanghai Rising-Star Program(Grant No.21QA1403400)Shanghai Sailing Program(Grant No.20YF1414800)Shanghai Key Laboratory of Power Station Automation Technology(Grant No.13DZ2273800).
文摘With the improvement of equipment reliability,human factors have become the most uncertain part in the system.The standardized Plant Analysis of Risk-Human Reliability Analysis(SPAR-H)method is a reliable method in the field of human reliability analysis(HRA)to evaluate human reliability and assess risk in large complex systems.However,the classical SPAR-H method does not consider the dependencies among performance shaping factors(PSFs),whichmay cause overestimation or underestimation of the risk of the actual situation.To address this issue,this paper proposes a new method to deal with the dependencies among PSFs in SPAR-H based on the Pearson correlation coefficient.First,the dependence between every two PSFs is measured by the Pearson correlation coefficient.Second,the weights of the PSFs are obtained by considering the total dependence degree.Finally,PSFs’multipliers are modified based on the weights of corresponding PSFs,and then used in the calculating of human error probability(HEP).A case study is used to illustrate the procedure and effectiveness of the proposed method.
文摘Ten physical and environmental variables collected from an on-the-go soil sensor at two field sites (MF3E and MF11S) in Mississippi, USA, were analyzed to assess soil variability and the interrelationships among the measurements. At MF3E, moderate variability was observed in apparent electrical conductivity shallow (ECas), slope, and ECa ratio measurements, with coefficients of variation ranging from 20% to 27%. In contrast, MF11S exhibited higher variability, particularly in ECas and ECad (deep) measurements, which exceeded 30% in their coefficient of variation values, indicating significant differences in soil composition and moisture content. Correlation analysis revealed strong positive relationships between the near-infrared-to-red ratio and red reflectance (r = 0.897***) soil values at MF3E. MF11S demonstrated a strong negative correlation between ECas and ECad readings with the x-coordinate (r ***). Scatter plots and fitted models illustrated the complexity of relationships, with many showing nonlinear trends. These findings emphasize the need for continuous monitoring and advanced modeling to understand the dynamic nature of soil properties and their implications for agricultural practices. Future research should explore the underlying mechanisms driving variability in the soil characteristics to enhance soil management strategies at the study sites.
基金supported by the National Natural Science Foundation of China(No.52474435)China Baowu Low Carbon Metallurgy Innovation Foundation(BWLCF202307).
文摘Accurate forecasting of blast furnace gas(BFG)production is an essential prerequisite for reasonable energy scheduling and management to reduce carbon emissions.Coupling forecasting between BFG generation and consumption dynamics was taken as the research object.A multi-task learning(MTL)method for BFG forecasting was proposed,which integrated a coupling correlation coefficient(CCC)and an inverted transformer structure.The CCC method could enhance key information extraction by establishing relationships between multiple prediction targets and relevant factors,while MTL effectively captured the inherent correlations between BFG generation and consumption.Finally,a real-world case study was conducted to compare the proposed model with four benchmark models.Results indicated significant reductions in average mean absolute percentage error by 33.37%,achieving 1.92%,with a computational time of 76 s.The sensitivity analysis of hyperparameters such as learning rate,batch size,and units of the long short-term memory layer highlights the importance of hyperparameter tuning.
基金the Science and Engineering Re-search Board(SERB),India for providing the financial assistance to support this work(Project No.SRG/2020/002449).
文摘Since antiquity,humans have been involved in designing materials through alloying strategies to meet the ever-growing technological demands.In 2004,this endeavor witnessed a significant breakthrough with the discovery of high-entropy alloys(HEAs)comprising multi-principal elements.Owing to the four“core-effects”,these alloys exhibit exceptional properties including better structural stability,high strength and ductility,improved fatigue/fracture toughness,high corrosion and oxidation resistance,superconductiv-ity,magnetic properties,and good thermal properties.Different synthesis routes have been designed and used to meet the properties of interest for particular applications with varying dimensions.How-ever,HEAs are providing new opportunities and challenges for computational modelling of the complex structure-property correlations and in predictions of phase stability necessary for optimum performance of the alloy.Several attempts have been made to understand these alloys by empirical and computa-tional models,and data-driven approaches to accelerate the materials discovery with a desired set of properties.The present review discusses advances and inferences from simulations and models spanning multiple length and time scales explaining a comprehensive set of structure-properties relations.Addi-tionally,the role of machine learning approaches is also reviewed,underscoring the transformative role of computational modelling in unravelling the multifaceted properties and applications of HEAs,and the scope for future efforts in this direction.
文摘Geomagnetic observatory data are crucial for all branches of geophysics because they can contribute to earthquake research by detecting anomalies in the Earth’s magnetic field.Recently,data records from the Misallat(MLT)and Abu Simbel(ABS)Egyptian geomagnetic observatories were processed and found to be of good quality.In this study,Egyptian observatory data were tested during both quiet and disturbed events and compared with data from INTERMAGNET observatories worldwide at different latitudes and within a narrow range of longitudes in both hemispheres.This study investigated the relationships between magnetic field components from Egyptian observatories and those from INTERMAGNET observatories using graphical representations of the X components;Pearson’s correlation for the X,Y,Z,and F components;cross-correlation for the X component;and wavelet coherence for the F component.The results of this study showed a high correlation between Egyptian observatories and all utilized INTERMAGNET stations,except those located at high latitudes,during both quiet and disturbed events.Additionally,the study confirmed the observed consistency between Egyptian observatories and selected INTERMAGNET stations.Therefore,Egyptian observatories can feasibly fill the gap in the Middle East and North Africa.
基金support for this work by Key Research and Development Project of Henan Province(Grant.No.241111232300)the National Natural Science Foundation of China(Grant.No.52273085 and 52303113)the Open Fund of Yaoshan Laboratory(Grant.No.2024003).
文摘The morphological distribution of absorbent in composites is equally important with absorbents for the overall electromagnetic properties,but it is often ignored.Herein,a comprehensive consideration including electromagnetic component regulation,layered arrangement structure,and gradient concentration distribution was used to optimize impedance matching and enhance electromagnetic loss.On the microscale,the incorporation of magnetic Ni nanoparticles into MXene nanosheets(Ni@MXene)endows suitable intrinsic permittivity and permeability.On the macroscale,the layered arrangement of Ni@MXene increases the effective interaction area with electromagnetic waves,inducing multiple reflection/scattering effects.On this basis,according to the analysis of absorption,reflection,and transmission(A-R-T)power coefficients of layered composites,the gradient concentration distribution was constructed to realize the impedance matching at low-concentration surface layer,electromagnetic loss at middle concentration interlayer and microwave reflection at high-concentration bottom layer.Consequently,the layered gradient composite(LG5-10-15)achieves complete absorption coverage of X-band at thickness of 2.00-2.20 mm with RL_(min) of-68.67 dB at 9.85 GHz in 2.05 mm,which is 199.0%,12.6%,and 50.6%higher than non-layered,layered and layered descending gradient composites,respectively.Therefore,this work confirms the importance of layered gradient structure in improving absorption performance and broadens the design of high-performance microwave absorption materials.
文摘BACKGROUND Resilience is an individual’s ability and psychological rebound capacity to adapt well after experiencing adversity,trauma,etc.Patients with strong resilience can face illnesses actively.AIM To determine the association of resilience with coping styles and quality of life in patients with malignancies.METHODS This study included patients with malignant tumors who were hospitalized at Fuyang Hospital Affiliated to Anhui Medical University from March 2022 to March 2024.The Connor-Davidson Resilience Scale,Medical Coping Modes Questionnaire,Social Support Rating Scale,and the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 were utilized to assess patients’resilience,coping styles,social support,and quality of life,respectively.Pearson correlation analysis was conducted to assess the correlations.RESULTS A total of 175 patients with malignant tumors demonstrated no marked difference in terms of age,education level,employment status,monthly household income,and disease staging(P<0.05).Further,patients with malignancies demonstrated scores of 17.49±1.20,17.27±1.46,and 11.19±1.29 points in terms of coping styles in confrontation,avoidance,and resignation dimensions,respectively.Subjective support,objective support,and support utilization scores in terms of social support were 10.67±1.80,11.26±2.08,and 9.24±1.14 points,respectively.The total resilience score and tenacity,self-improvement,and optimism dimension scores were positively correlatedwith the confrontation coping style score,whereas the total resilience score and tenacity and self-improvementscores were negatively associated with avoidance and resignation coping style scores(P<0.05).The total resiliencescore and the tenacity dimension score were positively associated with physical,role,cognitive,emotional,andsocial functions,as well as global health status(P<0.05),and were inversely related to fatigue,insomnia,andeconomic difficulties(P<0.05).CONCLUSIONThe resilience of patients with malignancies is positively associated with the confrontation dimension in the copingstyle,the total and various social support domain scores,and the overall quality of life.Clinical medical staff needto pay attention to the effect of medical coping styles and social support on the resilience level of patients withmalignancies to further improve their quality of life.
基金supported in part by the National Natural Science Foundation of China (No. U23B2011)。
文摘Video snapshot compressive imaging(Video SCI) modulates scenes using various encoding masks and captures compressed measurements with a low-speed camera during a single exposure. Subsequently, reconstruction algorithms restore image sequences of dynamic scenes, offering advantages such as reduced bandwidth and storage space requirements. The temporal correlation in video data is crucial for Video SCI, as it leverages the temporal relationships among frames to enhance the efficiency and quality of reconstruction algorithms, particularly for fast-moving objects.This paper discretizes video frames to create image datasets with the same data volume but differing temporal correlations. We utilized the state-of-the-art(SOTA) reconstruction framework, EfficientSCI++, to train various compressed reconstruction models with these differing temporal correlations. Evaluating the reconstruction results from these models, our simulation experiments confirm that a reduction in temporal correlation leads to decreased reconstruction accuracy. Additionally, we simulated the reconstruction outcomes of datasets devoid of temporal correlation, illustrating that models trained on non-temporal data affect the temporal feature extraction capabilities of transformers, resulting in negligible impacts on the evaluation of reconstruction results for non-temporal correlation test datasets.
基金funded by the South Oil Exploration and Development Company of PetroChina(2021-HNYJ-010).
文摘The Fushan Depression is one of the petroliferous depressions in the Beibuwan Basin,South China Sea.Previous studies have preliminarily explored the origin and source of crude oils in some areas of this depression.Nevertheless,no systematic investigations on the classification and origin of oils and hy-drocarbon migration processes have been made for the entire petroleum system in this depression,which has significantly hindered the hydrocarbon exploration in the region.A total of 32 mudstone and 58 oil samples from the Fushan Depression were analyzed to definite the detailed oil-source correlation within the sequence and sedimentary framework.The organic matter of third member of Paleogene Liushagang Formation(Els(3))source rocks,both deltaic and lacustrine mudstone,are algal-dominated with high abundance of C_(23)tricyclic terpane and C_(30)4-methylsteranes.The deltaic source rocks occur-ring in the first member(Els_(1))and second member(Els_(2))of the Paleogene Liushagang Formation are characterized by high abundance of C_(19+20)tricyclic terpane and oleanane,reflecting a more terrestrial plants contribution.While lacustrine source rocks of Els_(1)and Els_(2)display the reduced input of terrige-nous organic matter with relatively low abundance of C 19+20 tricyclic terpane and oleanane.Three types of oils were identified by their biomarker compositions in this study.Most of the oils discovered in the Huachang and Bailian Els_(1)reservoir belong to group A and were derived from lacustrine source rocks of Els_(1)and Els_(2).Group B oils are found within the Els_(1)and Els_(2)reservoirs,showing a close relation to the deltaic source rocks of Els_(1)and Els_(2),respectively.Group C oils,occurring in the Els3 reservoirs,have a good affinity with the Els3 source rocks.The spatial distribution and accumulation of different groups of oils are mainly controlled by the sedimentary facies and specific structural conditions.The Els_(2)reservoir in the Yong'an area belonging to Group B oil,are adjacent to the source kitchen and could be considered as the favorable exploration area in the future.
基金supported by the Beijing Natural Science Foundation(5252014)the National Natural Science Foundation of China(62303063)。
文摘Passive acoustic monitoring(PAM)technology is increasingly becoming one of the mainstream methods for bird monitoring.However,detecting bird audio within complex natural acoustic environments using PAM devices remains a significant challenge.To enhance the accuracy(ACC)of bird audio detection(BAD)and reduce both false negatives and false positives,this study proposes a BAD method based on a Dual-Feature Enhancement Fusion Model(DFEFM).This method incorporates per-channel energy normalization(PCEN)to suppress noise in the input audio and utilizes mel-frequency cepstral coefficients(MFCC)and frequency correlation matrices(FCM)as input features.It achieves deep feature-level fusion of MFCC and FCM on the channel dimension through two independent multi-layer convolutional network branches,and further integrates Spatial and Channel Synergistic Attention(SCSA)and Multi-Head Attention(MHA)modules to enhance the fusion effect of the aforementioned two deep features.Experimental results on the DCASE2018 BAD dataset show that our proposed method achieved an ACC of 91.4%and an AUC value of 0.963,with false negative and false positive rates of 11.36%and 7.40%,respectively,surpassing existing methods.The method also demonstrated detection ACC above 92%and AUC values above 0.987 on datasets from three sites of different natural scenes in Beijing.Testing on the NVIDIA Jetson Nano indicated that the method achieved an ACC of 89.48%when processing an average of 10 s of audio,with a response time of only 0.557 s,showing excellent processing efficiency.This study provides an effective method for filtering non-bird vocalization audio in bird vocalization monitoring devices,which helps to save edge storage and information transmission costs,and has significant application value for wild bird monitoring and ecological research.
基金Supported by the Shaanxi Provincial Key Research and Development Plan Project,No.2020ZDLSF01-02.
文摘BACKGROUND At present,the conventional methods for diagnosing cerebral edema in clinical practice are computed tomography(CT)and magnetic resonance imaging(MRI),which can evaluate the location and degree of peripheral cerebral edema,but cannot realize quantification.When patients have symptoms of diffuse cerebral edema or high cranial pressure,CT or MRI often suggests that cerebral edema is lagging and cannot be dynamically monitored in real time.Intracranial pressure monitoring is the gold standard,but it is an invasive operation with high cost and complications.For clinical purposes,the ideal cerebral edema monitoring should be non-invasive,real-time,bedside,and continuous dynamic monitoring.The dis-turbance coefficient(DC)was used in this study to dynamically monitor the occu-rrence,development,and evolution of cerebral edema in patients with cerebral hemorrhage in real time,and review head CT or MRI to evaluate the development of the disease and guide further treatment,so as to improve the prognosis of patients with cerebral hemorrhage.AIM To offer a promising new approach for non-invasive adjuvant therapy in cerebral edema treatment.METHODS A total of 160 patients with hypertensive cerebral hemorrhage admitted to the Department of Neurosurgery,Second Affiliated Hospital of Xi’an Medical University from September 2018 to September 2019 were recruited.The patients were randomly divided into a control group(n=80)and an experimental group(n=80).Patients in the control group received conventional empirical treatment,while those in the experimental group were treated with mannitol dehydration under the guidance of DC.Subsequently,we compared the two groups with regards to the total dosage of mannitol,the total course of treatment,the incidence of complications,and prognosis.RESULTS The mean daily consumption of mannitol,the total course of treatment,and the mean hospitalization days were 362.7±117.7 mL,14.8±5.2 days,and 29.4±7.9 in the control group and 283.1±93.6 mL,11.8±4.2 days,and 23.9±8.3 in the experimental group(P<0.05).In the control group,there were 20 patients with pulmonary infection(25%),30 with electrolyte disturbance(37.5%),20 with renal impairment(25%),and 16 with stress ulcer(20%).In the experimental group,pulmonary infection occurred in 18 patients(22.5%),electrolyte disturbance in 6(7.5%),renal impairment in 2(2.5%),and stress ulcers in 15(18.8%)(P<0.05).According to the Glasgow coma scale score 6 months after discharge,the prognosis of the control group was good in 20 patients(25%),fair in 26(32.5%),and poor in 34(42.5%);the prognosis of the experimental group was good in 32(40%),fair in 36(45%),and poor in 12(15%)(P<0.05).CONCLUSION Using DC for non-invasive dynamic monitoring of cerebral edema demonstrates considerable clinical potential.It reduces mannitol dosage,treatment duration,complication rates,and hospital stays,ultimately lowering hospital-ization costs.Additionally,it improves overall patient prognosis,offering a promising new approach for non-invasive adjuvant therapy in cerebral edema treatment.
文摘BACKGROUND Various stone factors can affect the net results of shock wave lithotripsy(SWL).Recently a new factor called variation coefficient of stone density(VCSD)is being considered to have an impact on stone free rates.AIM To assess the role of VCSD in determining success of SWL in urinary calculi.METHODS Charts review was utilized for collection of data variables.The patients were subjected to SWL,using an electromagnetic lithotripter.Mean stone density(MSD),stone heterogeneity index(SHI),and VCSD were calculated by generating regions of interest on computed tomography(CT)images.Role of these factors were determined by applying the relevant statistical tests for continuous and categorical variables and a P value of<0.05 was gauged to be statistically significant.RESULTS There were a total of 407 patients included in the analysis.The mean age of the subjects in this study was 38.89±14.61 years.In total,165 out of the 407 patients could not achieve stone free status.The successful group had a significantly lower stone volume as compared to the unsuccessful group(P<0.0001).Skin to stone distance was not dissimilar among the two groups(P=0.47).MSD was significantly lower in the successful group(P<0.0001).SHI and VCSD were both significantly higher in the successful group(P<0.0001).CONCLUSION VCSD,a useful CT based parameter,can be utilized to gauge stone fragility and hence the prediction of SWL outcomes.
基金funding from the National Natural Science Foundation of China (Grant No.42277175)the pilot project of cooperation between the Ministry of Natural Resources and Hunan Province“Research and demonstration of key technologies for comprehensive remote sensing identification of geological hazards in typical regions of Hunan Province” (Grant No.2023ZRBSHZ056)the National Key Research and Development Program of China-2023 Key Special Project (Grant No.2023YFC2907400).
文摘Joint roughness coefficient(JRC)is the most commonly used parameter for quantifying surface roughness of rock discontinuities in practice.The system composed of multiple roughness statistical parameters to measure JRC is a nonlinear system with a lot of overlapping information.In this paper,a dataset of eight roughness statistical parameters covering 112 digital joints is established.Then,the principal component analysis method is introduced to extract the significant information,which solves the information overlap problem of roughness characterization.Based on the two principal components of extracted features,the white shark optimizer algorithm was introduced to optimize the extreme gradient boosting model,and a new machine learning(ML)prediction model was established.The prediction accuracy of the new model and the other 17 models was measured using statistical metrics.The results show that the prediction result of the new model is more consistent with the real JRC value,with higher recognition accuracy and generalization ability.
文摘Let f be a primitive holomorphic cusp form with even integral weight k≥2 for the full modular groupΓ=SL(2,Z)andλ_(sym^(j)f)(n)be the n-th coefficient of Dirichlet series of j-th symmetric L-function L(s,sym^(j)f)attached to f.In this paper,we study the mean value distribution over a specific sparse sequence of positive integers of the following sum∑(a^(2)+b^(2)+c^(2)+d^(2)≤x(a,b,c,d)∈Z^(4))λ_(sym^(j))^(i)f(a^(2)+b^(2)+c^(2)+d^(2))where j≥2 is a given positive integer,i=2,3,4 andαis sufficiently large.We utilize Python programming to design algorithms for higher power conditions,combining Perron's formula,latest results of representations of natural integers as sums of squares,as well as analytic properties and subconvexity and convexity bounds of automorphic L-functions,to ensure the accuracy and verifiability of asymptotic formulas.The conclusion we obtained improves previous results and extends them to a more general settings.
文摘Quanto options allow the buyer to exchange the foreign currency payoff into the domestic currency at a fixed exchange rate. We investigate quanto options with multiple underlying assets valued in different foreign currencies each with a different strike price in the payoff function. We carry out a comparative performance analysis of different stochastic volatility (SV), stochastic correlation (SC), and stochastic exchange rate (SER) models to determine the best combination of these models for Monte Carlo (MC) simulation pricing. In addition, we test the performance of all model variants with constant correlation as a benchmark. We find that a combination of GARCH-Jump SV, Weibull SC, and Ornstein Uhlenbeck (OU) SER performs best. In addition, we analyze different discretization schemes and their results. In our simulations, the Milstein scheme yields the best balance between execution times and lower standard deviations of price estimates. Furthermore, we find that incorporating mean reversion into stochastic correlation and stochastic FX rate modeling is beneficial for MC simulation pricing. We improve the accuracy of our simulations by implementing antithetic variates variance reduction. Finally, we derive the correlation risk parameters Cora and Gora in our framework so that correlation hedging of quanto options can be performed.
文摘By introducing noncanonical vortex pairs to partially coherent beams, spatial correlation singularity (SCS) and orbital angular momenta (OAM) of the resulting beams are studied using the Fraunhofer diffraction integral. The effect of noncanonical strength, off-axis distance and vortex sign on spatial correlation singularities in far field is stressed. Furthermore, far-field OAM spectra and densities are also investigated, and the OAM detection and crosstalk probabilities are discussed. The results show that the number of dislocations of SCS always equals the sum of absolute values of topological charges for canonical or noncanonical vortex pairs. Although the sum of the product of each OAM mode and its power weight equals the algebraic sum of topological charges for canonical vortex pairs, the relationship no longer holds in the noncanonical case except for opposite-charge vortex pairs. The changes of off-axis distance, noncanonical strength or coherence length can lead to a more dominant power in adjacent mode than that in center detection mode, which also indicates that crosstalk probabilities of adjacent modes exceed the center detection probability. This work may provide potential applications in OAM-based optical communication, imaging, sensing and computing.
文摘Background: The use of assisted reproductive technique (ART) is becoming more common in infertility. During ART most patients undergo ovarian stimulation. In this study we study the correlation between ovarian reserve markers: Anti-Mullerian hormone (AMH) and antral follicle count (AFC), and the response to ovarian stimulation at in vitro fertilization (IVF) centres in Douala Cameroon. Methods: This was a hospital based cross-sectional sectional analytic study carried out over a period of 3 years, 4 months at Clinique de l’Aéroport, Clinique Odyssée and Clinique Urogyn. Inclusion criteria were: Female partners of infertile couples undergoing ovarian stimulation for an in vitro fertilization cycle, patients who had both ovaries and had done either AMH, AFC or both before ovarian stimulation. Patients were divided into three groups based on the number of oocytes retrieved: low ovarian response for ≤3 oocytes, normal ovarian response for 4 - 15 oocytes and high ovarian response for >15 oocytes. Data obtained was analyzed by SPSS version 25.0. Results: The ages of participants ranged from 20 - 4 7 years, with a mean age of 34.11 ± 5.11 years. Most of them had secondary infertility (57.9%). The GnRH antagonist protocol was mainly used, and ovulation was triggered using HCG predominantly. On Multivariate analysis, age and history of PCOS were significantly associated with ovarian response in the low and high ovarian response groups, respectively. Conclusion: AMH has a better predictive value than AFC, however, it is less sensitive but more specific than AFC.
基金Supported by the National Key Research and Development Program of China(2022YFB3904803)。
文摘The Infrared Hyperspectral Atmospheric SounderⅡ(HIRAS-Ⅱ)is the key equipment on FengYun-3E(FY-3E)satellite,which can realize vertical atmospheric detection,featuring hyper spectral,high sensitivity and high precision.To ensure its accuracy of detection,it is necessary to correlate their thermal models to in-orbit da⁃ta.In this work,an investigation of intelligent correlation method named Intelligent Correlation Platform for Ther⁃mal Model(ICP-TM)was established,the advanced Kriging surrogate model and efficient adaptive region opti⁃mization algorithm were introduced.After the correlation with this method for FY-3E/HIRAS-Ⅱ,the results indi⁃cate that compared with the data in orbit,the error of the thermal model has decreased from 5 K to within±1 K in cold case(10℃).Then,the correlated model is validated in hot case(20℃),and the correlated model exhibits good universality.This correlation precision is also much superiors to the general ones like 3 K in other similar lit⁃erature.Furthermore,the process is finished in 8 days using ICP-TM,the efficiency is much better than 3 months based on manual.The results show that the proposed approach significantly enhances the accuracy and efficiency of thermal model,this contributes to the precise thermal control of subsequent infrared optical payloads.
文摘The study of the morphometric parameters of the three most abundant species in the lower course of the Kouilou River (Chrysichthys auratus, Liza falcipinnis and Pellonula vorax) was carried out. The standard length of Chrysichthys auratus varies between 43.57 and 210 mm, for an average of 96.70 ± 28.63 mm;the weight varies between 2.92 and 140.83 mg, an average of 73.03 ± 21.62 mg. The condition coefficient is equal to 4.42 ± 1.52. Liza falcipinnis has a standard length which varies between 59.9 mm and 158.08 mm for an average of 88.15 ± 29.74 mm;its weight varies between 4.77 and 76.21 mg, an average of 18.61 ± 11.82 mg. The condition coefficient is equal to 2.47 ± 1.57. Pellonula vorax has a standard length which varies between 60.33 mm and 117.72 mm;for an average of 80.48 ± 17.75 mm;the weight varies between 3.61 and 25.17 mg, an average of 9.03 ± 3.61 mg. The condition coefficient is equal to 2.17 ± 0.57. These three species have a minor allometric growth.
基金National Natural Science Foundation of China(Project No.:12201579)。
文摘Portfolio selection based on the global minimum variance(GMV)model remains a significant focus in financial research.The covariance matrix,central to the GMV model,determines portfolio weights,and its accurate estimation is key to effective strategies.Based on the decomposition form of the covariance matrix.This paper introduces semi-variance for improved financial asymmetric risk measurement;addresses asymmetry in financial asset correlations using distance,asymmetric,and Chatterjee correlations to refine covariance matrices;and proposes three new covariance matrix models to enhance risk assessment and portfolio selection strategies.Testing with data from 30 stocks across various sectors of the Chinese market confirms the strong performance of the proposed strategies.
