[Objectives]This study aimed to evaluate the detection sensitivity of Staphylococcus aureus in dairy products utilizing the chip digital PCR(cdPCR)technique.[Methods]Specific primers and probes were designed and synth...[Objectives]This study aimed to evaluate the detection sensitivity of Staphylococcus aureus in dairy products utilizing the chip digital PCR(cdPCR)technique.[Methods]Specific primers and probes were designed and synthesized based on the conserved sequence of the heat-resistant nuclease gene nuc of S.aureus.cdPCR was employed to detect S.aureus,and the sensitivity of this technique was systematically assessed in samples exhibiting low levels of contamination.[Results]cdPCR demonstrated precise quantification when the initial concentration of the sample enrichment solution was equal to or greater than 50 CFU/mL.The detection dynamic range extended across at least five orders of magnitude,with a minimum DNA detection limit of 0.2304 pg/μL.In artificially contaminated cheese samples,the method s lower limit of quantification for detecting S.aureus was 8×10^(2) CFU/g.Regression analysis demonstrated that the gene copy number concentration measured by cdPCR exhibited a strong linear correlation with bacterial contamination concentration across a broad range.[Conclusions]The cdPCR method developed in this study demonstrates high sensitivity and robust quantitative capabilities,offering a reliable technical approach for the precise detection of low-level S.aureus contamination in dairy products.展开更多
Tilt-to-length(TTL)coupling noise is a critical issue in space-based gravitational wave detection due to its complex dependence on multiple interacting factors,which complicates the identification of dominant paramete...Tilt-to-length(TTL)coupling noise is a critical issue in space-based gravitational wave detection due to its complex dependence on multiple interacting factors,which complicates the identification of dominant parameters.To address this challenge,we develop a simulation model of the Taiji scientific interferometer,generating noise datasets under multiparameter conditions.Given the uniqueness of the telescope as well as the convergence behavior of the algorithm,the analysis is structured hierarchically:(i)the telescope level and(ii)the optical bench level.A hierarchical framework combining XGBoost and SHapley Additive exPlanations(SHAP)values is employed to model the intricate relationships between parameters and TTL coupling noise,supplemented by sensitivity analysis.Our results identify pointing jitter and telescope radius as the dominant parameters at the telescope level,while the angles of the plane mirrors and beam splitters are most influential at the optical bench level.The parameter space is reduced from 86 dimensions to 14 dimensions without sacrificing model accuracy.This approach offers actionable insights for optimizing the Taiji interferometer design.展开更多
To curb the worsening tropospheric ozone(O_(3))pollution problem in China,a rapid and accurate identification of O_(3)-precursor sensitivity(OPS)is a crucial prerequisite for formulating effective contingency O_(3) po...To curb the worsening tropospheric ozone(O_(3))pollution problem in China,a rapid and accurate identification of O_(3)-precursor sensitivity(OPS)is a crucial prerequisite for formulating effective contingency O_(3) pollution control strategies.However,currently widely-used methods,such as statistical models and numerical models,exhibit inherent limitations in identifying OPS in a timely and accurate manner.In this study,we developed a novel approach to identify OPS based on eXtreme Gradient Boosting model,Shapley additive explanation(SHAP)al-gorithm,and volatile organic compound(VOC)photochemical decay adjustment,using the meteorology and speciated pollutant monitoring data as the input.By comparing the difference in SHAP values between base sce-nario and precursor reduction scenario for nitrogen oxides(NO_(x))and VOCs,OPS was divided into NO_(x)-limited,VOCs-limited and transition regime.Using the long-lasting O_(3) pollution episode in the autumn of 2022 at the Guangdong-Hong Kong-Macao Greater Bay Area(GBA)as an example,we demonstrated large spatiotemporal heterogeneities of OPS over the GBA,which were generally shifted from NO_(x)-limited to VOCs-limited from September to October and more inclined to be VOCs-limited at the central and NO_(x)-limited in the peripheral areas.This study developed an innovative OPS identification method by comparing the difference in SHAP value before and after precursor emission reduction.Our method enables the accurate identification of OPS in the time scale of seconds,thereby providing a state-of-the-art tool for the rapid guidance of spatial-specific O_(3) control strategies.展开更多
Excellent detonation performances and low sensitivity are prerequisites for the deployment of energetic materials.Exploring the underlying factors that affect impact sensitivity and detonation performances as well as ...Excellent detonation performances and low sensitivity are prerequisites for the deployment of energetic materials.Exploring the underlying factors that affect impact sensitivity and detonation performances as well as exploring how to obtain materials with desired properties remains a long-term challenge.Machine learning with its ability to solve complex tasks and perform robust data processing can reveal the relationship between performance and descriptive indicators,potentially accelerating the development process of energetic materials.In this background,impact sensitivity,detonation performances,and 28 physicochemical parameters for 222 energetic materials from density functional theory calculations and published literature were sorted out.Four machine learning algorithms were employed to predict various properties of energetic materials,including impact sensitivity,detonation velocity,detonation pressure,and Gurney energy.Analysis of Pearson coefficients and feature importance showed that the heat of explosion,oxygen balance,decomposition products,and HOMO energy levels have a strong correlation with the impact sensitivity of energetic materials.Oxygen balance,decomposition products,and density have a strong correlation with detonation performances.Utilizing impact sensitivity of 2,3,4-trinitrotoluene and the detonation performances of 2,4,6-trinitrobenzene-1,3,5-triamine as the benchmark,the analysis of feature importance rankings and statistical data revealed the optimal range of key features balancing impact sensitivity and detonation performances:oxygen balance values should be between-40%and-30%,density should range from 1.66 to 1.72 g/cm^(3),HOMO energy levels should be between-6.34 and-6.31 eV,and lipophilicity should be between-1.0 and 0.1,4.49 and 5.59.These findings not only offer important insights into the impact sensitivity and detonation performances of energetic materials,but also provide a theoretical guidance paradigm for the design and development of new energetic materials with optimal detonation performances and reduced sensitivity.展开更多
In recent decades,capacitive pressure sensors(CPSs)with high sensitivity have demonstrated significant potential in applications such as medical monitoring,artificial intelligence,and soft robotics.Efforts to enhance ...In recent decades,capacitive pressure sensors(CPSs)with high sensitivity have demonstrated significant potential in applications such as medical monitoring,artificial intelligence,and soft robotics.Efforts to enhance this sensitivity have predominantly focused on material design and structural optimization,with surface microstructures such as wrinkles,pyramids,and micro-pillars proving effective.Although finite element modeling(FEM)has guided enhancements in CPS sensitivity across various surface designs,a theoretical understanding of sensitivity improvements remains underexplored.This paper employs sinusoidal wavy surfaces as a representative model to analytically elucidate the underlying mechanisms of sensitivity enhancement through contact mechanics.These theoretical insights are corroborated by FEM and experimental validations.Our findings underscore that optimizing material properties,such as Young’s modulus and relative permittivity,alongside adjustments in surface roughness and substrate thickness,can significantly elevate the sensitivity.The optimal performance is achieved when the amplitude-to-wavelength ratio(H/)is about 0.2.These results offer critical insights for designing ultrasensitive CPS devices,paving the way for advancements in sensor technology.展开更多
Increasing temperatures and severe droughts threaten forest vitality globally.Prediction of forest response to climate change requires knowledge of the spatiotemporal patterns of monthly or seasonal climatic impacts o...Increasing temperatures and severe droughts threaten forest vitality globally.Prediction of forest response to climate change requires knowledge of the spatiotemporal patterns of monthly or seasonal climatic impacts on the growth of tree species,likely driven by local climatic aridity,climate trends,edaphic conditions,and the climatic adaption of tree species.The ability of tree species to cope with changing climate and the effects of environmental variables on growth trends and growth-climate relationships across diverse bioclimatic regions are still poorly understood for many species.This study investigated radial growth trends,interannual growth variability,and growth-climate sensitivity of two dominant tree species,Pinus tabulaeformis(PT)and Pinus sylvestris var.mongolica(PS),across a broad climatic gradient with a variety of soil properties in temperate Northern China.Using a network of 83 tree ring chronologies(54 for PT and 29 for PS)from 1971 to 2010,we documented that both species maintained constant growth trends at wet sites,while both displayed rapid declines at dry sites.We reported the species-specific drivers of spatial heterogeneity in growth trends,interannual growth variability,and growth-climate relationships.Calculated climatic variables and soil properties were identified as the most critical factors affecting the growth trends and growth-climate relationships.However,climatic variables play more essential roles than soil properties in determining the spatial heterogeneity of the growth-climate relationship.Lower clay content and higher soil nutrient regimes can exacerbate the moisture-related susceptibility of tree growth.Our findings highlight that soil properties emerged as important modulating factors to predict the drought vulnerability of forests in addition to climatic variables.Considering the continued climate warmingdrying trend in the future,both pines will face a more severe growth decline and increase in drought vulnerability at drier sites with lower clayed soil or higher nutrient regimes.展开更多
BACKGROUND Sensitivity to stress is essential in the onset,clinical symptoms,course,and prognosis of major depressive disorder(MDD).Meanwhile,it was unclear how variously classified but connected stress-sensitivity va...BACKGROUND Sensitivity to stress is essential in the onset,clinical symptoms,course,and prognosis of major depressive disorder(MDD).Meanwhile,it was unclear how variously classified but connected stress-sensitivity variables affect MDD.We hypothesize that high-level trait-and state-related stress-sensitivity factors may have different cumulative effects on the clinical symptoms and follow-up outcomes of MDD.AIM To investigate how stress-sensitivity factors added up and affected MDD clinical symptoms and follow-up results.METHODS In this prospective study,281 MDD patients were enrolled from a tertiary care setting.High-level stress-sensitivity factors were classified as trait anxiety,state anxiety,perceived stress,and neuroticism,with a total score in the top quartile of the research cohort.The cumulative effects of stress-sensitivity factors on cognitive dysfunction,disability and functional impairment,suicide risk,and depressive and anxiety symptoms were examined using an analysis of variance with linear trend analysis.Correlations were investigated further using multiple regression analysis.RESULTS Regarding high-level stress-sensitivity factors,53.40%of patients had at least one at baseline,and 29.61%had two or more.Four high-level stress-sensitivity components had significant cumulative impacts on MDD symptoms at baseline(all P<0.001).Perceived stress predicted the greatest effect sizes of state-related factors on depressive symptoms(partialη^(2)=0.153;standardizedβ=0.195;P<0.05).The follow-up outcomes were significantly impacted only by the high-level trait-related components,mainly when it came to depressive symptoms and suicide risk,which were predicted by trait anxiety and neuroticism,respectively(partialη^(2)=0.204 and 0.156;standardizedβ=0.247 and 0.392;P<0.05).CONCLUSION To enhance outcomes of MDD and lower the suicide risk,screening for stress-sensitivity factors and considering multifaceted measures,mainly focusing on trait-related ones,should be addressed clinically.展开更多
As a means of quantitative interpretation,forward calculations of the global lithospheric magnetic field in the Spherical Harmonic(SH)domain have been widely used to reveal geophysical,lithological,and geothermal vari...As a means of quantitative interpretation,forward calculations of the global lithospheric magnetic field in the Spherical Harmonic(SH)domain have been widely used to reveal geophysical,lithological,and geothermal variations in the lithosphere.Traditional approaches either do not consider the non-axial dipolar terms of the inducing field and its radial variation or do so by means of complicated formulae.Moreover,existing methods treat the magnetic lithosphere either as an infinitesimally thin layer or as a radially uniform spherical shell of constant thickness.Here,we present alternative forward formulae that account for an arbitrarily high maximum degree of the inducing field and for a magnetic lithosphere of variable thickness.Our simulations based on these formulae suggest that the satellite magnetic anomaly field is sensitive to the non-axial dipolar terms of the inducing field but not to its radial variation.Therefore,in forward and inverse calculations of satellite magnetic anomaly data,the non-axial dipolar terms of the inducing field should not be ignored.Furthermore,our results show that the satellite magnetic anomaly field is sensitive to variability in the lateral thickness of the magnetized shell.In particular,we show that for a given vertically integrated susceptibility distribution,underestimating the thickness of the magnetic layer overestimates the induced magnetic field.This discovery bridges the greatest part of the alleged gap between the susceptibility values measured from rock samples and the susceptibility values required to match the observed magnetic field signal.We expect the formulae and conclusions of this study to be a valuable tool for the quantitative interpretation of the Earth's global lithospheric magnetic field,through an inverse or forward modelling approach.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
Monitoring minuscule mechanical signals,both in magnitude and direction,is imperative in many application scenarios,e.g.,structural health monitoring and robotic sensing systems.However,the piezoelectric sensor strugg...Monitoring minuscule mechanical signals,both in magnitude and direction,is imperative in many application scenarios,e.g.,structural health monitoring and robotic sensing systems.However,the piezoelectric sensor struggles to satisfy the requirements for directional recognition due to the limited piezoelectric coefficient matrix,and achieving sensitivity for detecting micrometer-scale deformations is also challenging.Herein,we develop a vector sensor composed of lead zirconate titanate-electronic grade glass fiber composite filaments with oriented arrangement,capable of detecting minute anisotropic deformations.The as-prepared vector sensor can identify the deformation directions even when subjected to an unprecedented nominal strain of 0.06%,thereby enabling its utility in accurately discerning the 5μm-height wrinkles in thin films and in monitoring human pulse waves.The ultra-high sensitivity is attributed to the formation of porous ferroelectret and the efficient load transfer efficiency of continuous lead zirconate titanate phase.Additionally,when integrated with machine learning techniques,the sensor’s capability to recognize multi-signals enables it to differentiate between 10 types of fine textures with 100%accuracy.The structural design in piezoelectric devices enables a more comprehensive perception of mechanical stimuli,offering a novel perspective for enhancing recognition accuracy.展开更多
Accuracy allocation is crucial in the accuracy design of machining tools.Current accuracy allocation methods primarily focus on positional deviation,with little consideration for tool direction deviation.To address th...Accuracy allocation is crucial in the accuracy design of machining tools.Current accuracy allocation methods primarily focus on positional deviation,with little consideration for tool direction deviation.To address this issue,we propose a geometric error cost sensitivity-based accuracy allocation method for five-axis machine tools.A geometric error model consisting of 4l error components is constructed based on homogeneous transformation matrices.Volumetric points with positional and tool direction deviations are randomly sampled to evaluate the accuracy of the machine tool.The sensitivity of each error component at these sampling points is analyzed using the Sobol method.To balance the needs of geometric precision and manufacturing cost,a geometric error cost sensitivity function is developed to estimate the required cost.By allocating error components affecting tool direction deviation first and the remaining components second,this allocation scheme ensures that both deviations meet the requirements.We also perform numerical simulation of a BC-type(B-axis and C-axis type)five-axis machine tool to validate the method.The results show that the new allocation scheme reduces the total geometric error cost by 27.8%compared to a uniform allocation scheme,and yields the same positional and tool direction machining accuracies.展开更多
Objective: We describe patients with MCS, the evolution of the Quick Environmental Exposure and Sensitivity Inventory (QEESI) score with a special focus on people whose fillings were removed. Methods: We have conducte...Objective: We describe patients with MCS, the evolution of the Quick Environmental Exposure and Sensitivity Inventory (QEESI) score with a special focus on people whose fillings were removed. Methods: We have conducted a retrospective longitudinal cohort study in patients diagnosed with MCS and attended in the outpatient Internal Medicine department of the University Hospital of San Juan de Alicante, from January 1, 2008 to January 1, 2021. Sociodemographic, clinical, QEESI and treatment-related variables were collected. We performed descriptive and inferential analyses. Mixed linear models were used to analyze the QEESI. Calculations were carried out with an α error of 5%. Results: Thirty-three patients were included (72.7% women, mean age 56.2). MCS was mainly triggered by mercury (N = 20) and food intolerance (N = 22). The mean interval from symptoms onset was 120 months (SD 81.6). 114 QEESIs were analyzed: 82 (N = 17 without amalgams) and 32 (N = 16 with amalgams). In patients without amalgams, severity scores increased across all subscales except the masking index (vs. with amalgams). Mean scores for the group without amalgams (vs. with amalgams) were: chemical intolerance, 62.8 points (vs. 63.4 and 46.7);other intolerances, 52.7 points (vs. 62.8 and 50.3);symptom severity, 63.2 (vs. 76.7 and 63.3);masking index, 3.9 (vs. 3.2 and 2.8);and life impacts, 63.1 (vs. 58.4 and 49.8). Conclusion: The profile of patient with MCS is a middle-aged woman who is a frequent user of healthcare services, presents a long diagnostic delay and has borne a great personal, work and socioeconomic impact. The QEESI is useful for the clinical follow-up of patients, including the optimal treatment response in the case of amalgams. Clinical Significance: People affected by Multiple Chemical Sensitivity deserve the attention, understanding and help of health professionals and family members, to face an invisible illness for those who do not suffer from it. Support is needed and doctors must raise awareness, and make an effort to understand and address this pathology. We suggest that protocolized amalgam extraction in accredited and prepared centers can reduce symptoms and improve quality of life, generating clinical, personal, family, occupational, social and occupational benefits.展开更多
Saline aquifers are considered as highly favored reservoirs for CO_(2)sequestration due to their favorable properties.Understanding the impact of saline aquifer properties on the migration and distribution of CO_(2)pl...Saline aquifers are considered as highly favored reservoirs for CO_(2)sequestration due to their favorable properties.Understanding the impact of saline aquifer properties on the migration and distribution of CO_(2)plume is crucial.This study focuses on four key parameters-permeability,porosity,formation pressure,and temperature-to characterize the reservoir and analyse the petrophysical and elastic response of CO_(2).First,we performed reservoir simulations to simulate CO_(2)saturation,using multiple sets of these four parameters to examine their significance on CO_(2)saturation and the plume migration speed.Subsequently,the effect of these parameters on the elastic properties is tested using rock physics theory.We established a relationship of compressional wave velocity(V_(p))and quality factor(Q_(p))with the four key parameters,and conducted a sensitivity analysis to test their sensitivity to V_(p) and Q_(p).Finally,we utilized visco-acoustic wave equation simulated time-lapse seismic data based on the computed V_(p) and Q_(p) models,and analysed the impact of CO_(2) saturation changes on seismic data.As for the above nu-merical simulations and analysis,we conducted sensitivity analysis using both homogeneous and heterogeneous models.Consistent results are found between homogeneous and heterogeneous models.The permeability is the most sensitive parameter to the CO_(2)saturation,while porosity emerges as the primary factor affecting both Q_(p) and V_(p).Both Q_(p) and V_(p) increase with the porosity,which contradicts the observations in gas reservoirs.The seismic simulations highlight significant variations in the seismic response to different parameters.We provided analysis for these observations,which serves as a valuable reference for comprehensive CO_(2)integrity analysis,time-lapse monitoring,injection planning and site selection.展开更多
基金Supported by Science and Technology Program of Inner Mongolia Autonomous Region"Research and Demonstration of Novel Molecular Biological Identification Technology for Multiple Source Components in Milk and Dairy Products"(2025YFSH0029).
文摘[Objectives]This study aimed to evaluate the detection sensitivity of Staphylococcus aureus in dairy products utilizing the chip digital PCR(cdPCR)technique.[Methods]Specific primers and probes were designed and synthesized based on the conserved sequence of the heat-resistant nuclease gene nuc of S.aureus.cdPCR was employed to detect S.aureus,and the sensitivity of this technique was systematically assessed in samples exhibiting low levels of contamination.[Results]cdPCR demonstrated precise quantification when the initial concentration of the sample enrichment solution was equal to or greater than 50 CFU/mL.The detection dynamic range extended across at least five orders of magnitude,with a minimum DNA detection limit of 0.2304 pg/μL.In artificially contaminated cheese samples,the method s lower limit of quantification for detecting S.aureus was 8×10^(2) CFU/g.Regression analysis demonstrated that the gene copy number concentration measured by cdPCR exhibited a strong linear correlation with bacterial contamination concentration across a broad range.[Conclusions]The cdPCR method developed in this study demonstrates high sensitivity and robust quantitative capabilities,offering a reliable technical approach for the precise detection of low-level S.aureus contamination in dairy products.
基金Project supported by the National Key Research and Development Program of China(Grant No.2020YFC2200100)the CAS's Strategic Pioneer Program on Space Science(Grant No.XDA1502110201)。
文摘Tilt-to-length(TTL)coupling noise is a critical issue in space-based gravitational wave detection due to its complex dependence on multiple interacting factors,which complicates the identification of dominant parameters.To address this challenge,we develop a simulation model of the Taiji scientific interferometer,generating noise datasets under multiparameter conditions.Given the uniqueness of the telescope as well as the convergence behavior of the algorithm,the analysis is structured hierarchically:(i)the telescope level and(ii)the optical bench level.A hierarchical framework combining XGBoost and SHapley Additive exPlanations(SHAP)values is employed to model the intricate relationships between parameters and TTL coupling noise,supplemented by sensitivity analysis.Our results identify pointing jitter and telescope radius as the dominant parameters at the telescope level,while the angles of the plane mirrors and beam splitters are most influential at the optical bench level.The parameter space is reduced from 86 dimensions to 14 dimensions without sacrificing model accuracy.This approach offers actionable insights for optimizing the Taiji interferometer design.
基金supported by the Key-Area Research and Development Program of Guangdong Province(No.2020B1111360003)the National Natural Science Foundation of China(Nos.42465008 and 42105164)+2 种基金Yunnan Science and Technology Department Project(No.202501AT070239)Yunnan Science and Technology Department Youth Project(No.202401AU070202)Xianyang Rapid Response Decision Support Project for Ozone(No.YZ2024-ZB019).
文摘To curb the worsening tropospheric ozone(O_(3))pollution problem in China,a rapid and accurate identification of O_(3)-precursor sensitivity(OPS)is a crucial prerequisite for formulating effective contingency O_(3) pollution control strategies.However,currently widely-used methods,such as statistical models and numerical models,exhibit inherent limitations in identifying OPS in a timely and accurate manner.In this study,we developed a novel approach to identify OPS based on eXtreme Gradient Boosting model,Shapley additive explanation(SHAP)al-gorithm,and volatile organic compound(VOC)photochemical decay adjustment,using the meteorology and speciated pollutant monitoring data as the input.By comparing the difference in SHAP values between base sce-nario and precursor reduction scenario for nitrogen oxides(NO_(x))and VOCs,OPS was divided into NO_(x)-limited,VOCs-limited and transition regime.Using the long-lasting O_(3) pollution episode in the autumn of 2022 at the Guangdong-Hong Kong-Macao Greater Bay Area(GBA)as an example,we demonstrated large spatiotemporal heterogeneities of OPS over the GBA,which were generally shifted from NO_(x)-limited to VOCs-limited from September to October and more inclined to be VOCs-limited at the central and NO_(x)-limited in the peripheral areas.This study developed an innovative OPS identification method by comparing the difference in SHAP value before and after precursor emission reduction.Our method enables the accurate identification of OPS in the time scale of seconds,thereby providing a state-of-the-art tool for the rapid guidance of spatial-specific O_(3) control strategies.
基金supported by the Fundamental Research Funds for the Central Universities(Grant No.2682024GF019)。
文摘Excellent detonation performances and low sensitivity are prerequisites for the deployment of energetic materials.Exploring the underlying factors that affect impact sensitivity and detonation performances as well as exploring how to obtain materials with desired properties remains a long-term challenge.Machine learning with its ability to solve complex tasks and perform robust data processing can reveal the relationship between performance and descriptive indicators,potentially accelerating the development process of energetic materials.In this background,impact sensitivity,detonation performances,and 28 physicochemical parameters for 222 energetic materials from density functional theory calculations and published literature were sorted out.Four machine learning algorithms were employed to predict various properties of energetic materials,including impact sensitivity,detonation velocity,detonation pressure,and Gurney energy.Analysis of Pearson coefficients and feature importance showed that the heat of explosion,oxygen balance,decomposition products,and HOMO energy levels have a strong correlation with the impact sensitivity of energetic materials.Oxygen balance,decomposition products,and density have a strong correlation with detonation performances.Utilizing impact sensitivity of 2,3,4-trinitrotoluene and the detonation performances of 2,4,6-trinitrobenzene-1,3,5-triamine as the benchmark,the analysis of feature importance rankings and statistical data revealed the optimal range of key features balancing impact sensitivity and detonation performances:oxygen balance values should be between-40%and-30%,density should range from 1.66 to 1.72 g/cm^(3),HOMO energy levels should be between-6.34 and-6.31 eV,and lipophilicity should be between-1.0 and 0.1,4.49 and 5.59.These findings not only offer important insights into the impact sensitivity and detonation performances of energetic materials,but also provide a theoretical guidance paradigm for the design and development of new energetic materials with optimal detonation performances and reduced sensitivity.
基金supported by the National Natural Science Foundation of China(Grant No.12272369)the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDB0620101).
文摘In recent decades,capacitive pressure sensors(CPSs)with high sensitivity have demonstrated significant potential in applications such as medical monitoring,artificial intelligence,and soft robotics.Efforts to enhance this sensitivity have predominantly focused on material design and structural optimization,with surface microstructures such as wrinkles,pyramids,and micro-pillars proving effective.Although finite element modeling(FEM)has guided enhancements in CPS sensitivity across various surface designs,a theoretical understanding of sensitivity improvements remains underexplored.This paper employs sinusoidal wavy surfaces as a representative model to analytically elucidate the underlying mechanisms of sensitivity enhancement through contact mechanics.These theoretical insights are corroborated by FEM and experimental validations.Our findings underscore that optimizing material properties,such as Young’s modulus and relative permittivity,alongside adjustments in surface roughness and substrate thickness,can significantly elevate the sensitivity.The optimal performance is achieved when the amplitude-to-wavelength ratio(H/)is about 0.2.These results offer critical insights for designing ultrasensitive CPS devices,paving the way for advancements in sensor technology.
基金funded by the National Key Research and Development Plan of China(No.2022YFE0127900)the National Natural Science Foundation of China(Nos.32071558,32171559)+2 种基金the Natural Science Foundation Key Project of Inner Mongolia Autonomous Region,China(No.2023ZD23)the Hulunbuir Science and Technology Plan Project(No.SF2022001)the Fundamental Research Funds of CAF(CAFYBB2023ZA002).
文摘Increasing temperatures and severe droughts threaten forest vitality globally.Prediction of forest response to climate change requires knowledge of the spatiotemporal patterns of monthly or seasonal climatic impacts on the growth of tree species,likely driven by local climatic aridity,climate trends,edaphic conditions,and the climatic adaption of tree species.The ability of tree species to cope with changing climate and the effects of environmental variables on growth trends and growth-climate relationships across diverse bioclimatic regions are still poorly understood for many species.This study investigated radial growth trends,interannual growth variability,and growth-climate sensitivity of two dominant tree species,Pinus tabulaeformis(PT)and Pinus sylvestris var.mongolica(PS),across a broad climatic gradient with a variety of soil properties in temperate Northern China.Using a network of 83 tree ring chronologies(54 for PT and 29 for PS)from 1971 to 2010,we documented that both species maintained constant growth trends at wet sites,while both displayed rapid declines at dry sites.We reported the species-specific drivers of spatial heterogeneity in growth trends,interannual growth variability,and growth-climate relationships.Calculated climatic variables and soil properties were identified as the most critical factors affecting the growth trends and growth-climate relationships.However,climatic variables play more essential roles than soil properties in determining the spatial heterogeneity of the growth-climate relationship.Lower clay content and higher soil nutrient regimes can exacerbate the moisture-related susceptibility of tree growth.Our findings highlight that soil properties emerged as important modulating factors to predict the drought vulnerability of forests in addition to climatic variables.Considering the continued climate warmingdrying trend in the future,both pines will face a more severe growth decline and increase in drought vulnerability at drier sites with lower clayed soil or higher nutrient regimes.
基金Supported by Science and Technology Innovation 2030-Major Projects,No.2021ZD0202000National Key Research and Development Program of China,No.2019YFA0706200+2 种基金National Natural Science Foundation of China,No.82371535Science and Technology Innovation Program of Hunan Province,No.2023RC3083Fundamental Research Funds for the Central Universities of Central South University,No.2023ZZTS0838.
文摘BACKGROUND Sensitivity to stress is essential in the onset,clinical symptoms,course,and prognosis of major depressive disorder(MDD).Meanwhile,it was unclear how variously classified but connected stress-sensitivity variables affect MDD.We hypothesize that high-level trait-and state-related stress-sensitivity factors may have different cumulative effects on the clinical symptoms and follow-up outcomes of MDD.AIM To investigate how stress-sensitivity factors added up and affected MDD clinical symptoms and follow-up results.METHODS In this prospective study,281 MDD patients were enrolled from a tertiary care setting.High-level stress-sensitivity factors were classified as trait anxiety,state anxiety,perceived stress,and neuroticism,with a total score in the top quartile of the research cohort.The cumulative effects of stress-sensitivity factors on cognitive dysfunction,disability and functional impairment,suicide risk,and depressive and anxiety symptoms were examined using an analysis of variance with linear trend analysis.Correlations were investigated further using multiple regression analysis.RESULTS Regarding high-level stress-sensitivity factors,53.40%of patients had at least one at baseline,and 29.61%had two or more.Four high-level stress-sensitivity components had significant cumulative impacts on MDD symptoms at baseline(all P<0.001).Perceived stress predicted the greatest effect sizes of state-related factors on depressive symptoms(partialη^(2)=0.153;standardizedβ=0.195;P<0.05).The follow-up outcomes were significantly impacted only by the high-level trait-related components,mainly when it came to depressive symptoms and suicide risk,which were predicted by trait anxiety and neuroticism,respectively(partialη^(2)=0.204 and 0.156;standardizedβ=0.247 and 0.392;P<0.05).CONCLUSION To enhance outcomes of MDD and lower the suicide risk,screening for stress-sensitivity factors and considering multifaceted measures,mainly focusing on trait-related ones,should be addressed clinically.
基金supported by the National Natural Science Foundation of China(Grant Nos.42250103 and 42174090)the Opening Fund of Key Laboratory of Geological Survey and Evaluation of Ministry of Education(Grant No.GLAB2023ZR02)the Ministry of Science and Technology(MOST)Special Fund from the State Key Laboratory of Geological Processes and Mineral Resources(Grant No.MSFGPMR2022-4)。
文摘As a means of quantitative interpretation,forward calculations of the global lithospheric magnetic field in the Spherical Harmonic(SH)domain have been widely used to reveal geophysical,lithological,and geothermal variations in the lithosphere.Traditional approaches either do not consider the non-axial dipolar terms of the inducing field and its radial variation or do so by means of complicated formulae.Moreover,existing methods treat the magnetic lithosphere either as an infinitesimally thin layer or as a radially uniform spherical shell of constant thickness.Here,we present alternative forward formulae that account for an arbitrarily high maximum degree of the inducing field and for a magnetic lithosphere of variable thickness.Our simulations based on these formulae suggest that the satellite magnetic anomaly field is sensitive to the non-axial dipolar terms of the inducing field but not to its radial variation.Therefore,in forward and inverse calculations of satellite magnetic anomaly data,the non-axial dipolar terms of the inducing field should not be ignored.Furthermore,our results show that the satellite magnetic anomaly field is sensitive to variability in the lateral thickness of the magnetized shell.In particular,we show that for a given vertically integrated susceptibility distribution,underestimating the thickness of the magnetic layer overestimates the induced magnetic field.This discovery bridges the greatest part of the alleged gap between the susceptibility values measured from rock samples and the susceptibility values required to match the observed magnetic field signal.We expect the formulae and conclusions of this study to be a valuable tool for the quantitative interpretation of the Earth's global lithospheric magnetic field,through an inverse or forward modelling approach.
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.
基金financially supported by the National Key Research and Development Program of China(No.2022YFA1205300 and No.2022YFA1205304)the Oceanic Interdisciplinary Program of Shanghai Jiao Tong University(SL2022ZD103).
文摘Monitoring minuscule mechanical signals,both in magnitude and direction,is imperative in many application scenarios,e.g.,structural health monitoring and robotic sensing systems.However,the piezoelectric sensor struggles to satisfy the requirements for directional recognition due to the limited piezoelectric coefficient matrix,and achieving sensitivity for detecting micrometer-scale deformations is also challenging.Herein,we develop a vector sensor composed of lead zirconate titanate-electronic grade glass fiber composite filaments with oriented arrangement,capable of detecting minute anisotropic deformations.The as-prepared vector sensor can identify the deformation directions even when subjected to an unprecedented nominal strain of 0.06%,thereby enabling its utility in accurately discerning the 5μm-height wrinkles in thin films and in monitoring human pulse waves.The ultra-high sensitivity is attributed to the formation of porous ferroelectret and the efficient load transfer efficiency of continuous lead zirconate titanate phase.Additionally,when integrated with machine learning techniques,the sensor’s capability to recognize multi-signals enables it to differentiate between 10 types of fine textures with 100%accuracy.The structural design in piezoelectric devices enables a more comprehensive perception of mechanical stimuli,offering a novel perspective for enhancing recognition accuracy.
基金supported by the Key R&D Program of Zhejiang Province(Nos.2023C01166 and 2024SJCZX0046)the Zhejiang Provincial Natural Science Foundation of China(Nos.LDT23E05013E05 and LD24E050009)the Natural Science Foundation of Ningbo(No.2021J150),China.
文摘Accuracy allocation is crucial in the accuracy design of machining tools.Current accuracy allocation methods primarily focus on positional deviation,with little consideration for tool direction deviation.To address this issue,we propose a geometric error cost sensitivity-based accuracy allocation method for five-axis machine tools.A geometric error model consisting of 4l error components is constructed based on homogeneous transformation matrices.Volumetric points with positional and tool direction deviations are randomly sampled to evaluate the accuracy of the machine tool.The sensitivity of each error component at these sampling points is analyzed using the Sobol method.To balance the needs of geometric precision and manufacturing cost,a geometric error cost sensitivity function is developed to estimate the required cost.By allocating error components affecting tool direction deviation first and the remaining components second,this allocation scheme ensures that both deviations meet the requirements.We also perform numerical simulation of a BC-type(B-axis and C-axis type)five-axis machine tool to validate the method.The results show that the new allocation scheme reduces the total geometric error cost by 27.8%compared to a uniform allocation scheme,and yields the same positional and tool direction machining accuracies.
文摘Objective: We describe patients with MCS, the evolution of the Quick Environmental Exposure and Sensitivity Inventory (QEESI) score with a special focus on people whose fillings were removed. Methods: We have conducted a retrospective longitudinal cohort study in patients diagnosed with MCS and attended in the outpatient Internal Medicine department of the University Hospital of San Juan de Alicante, from January 1, 2008 to January 1, 2021. Sociodemographic, clinical, QEESI and treatment-related variables were collected. We performed descriptive and inferential analyses. Mixed linear models were used to analyze the QEESI. Calculations were carried out with an α error of 5%. Results: Thirty-three patients were included (72.7% women, mean age 56.2). MCS was mainly triggered by mercury (N = 20) and food intolerance (N = 22). The mean interval from symptoms onset was 120 months (SD 81.6). 114 QEESIs were analyzed: 82 (N = 17 without amalgams) and 32 (N = 16 with amalgams). In patients without amalgams, severity scores increased across all subscales except the masking index (vs. with amalgams). Mean scores for the group without amalgams (vs. with amalgams) were: chemical intolerance, 62.8 points (vs. 63.4 and 46.7);other intolerances, 52.7 points (vs. 62.8 and 50.3);symptom severity, 63.2 (vs. 76.7 and 63.3);masking index, 3.9 (vs. 3.2 and 2.8);and life impacts, 63.1 (vs. 58.4 and 49.8). Conclusion: The profile of patient with MCS is a middle-aged woman who is a frequent user of healthcare services, presents a long diagnostic delay and has borne a great personal, work and socioeconomic impact. The QEESI is useful for the clinical follow-up of patients, including the optimal treatment response in the case of amalgams. Clinical Significance: People affected by Multiple Chemical Sensitivity deserve the attention, understanding and help of health professionals and family members, to face an invisible illness for those who do not suffer from it. Support is needed and doctors must raise awareness, and make an effort to understand and address this pathology. We suggest that protocolized amalgam extraction in accredited and prepared centers can reduce symptoms and improve quality of life, generating clinical, personal, family, occupational, social and occupational benefits.
基金supported by the State Key Laboratory of Offshore Oil and Gas Exploitation, Open Fund Project (No. CCL2023RCPS0162RQN)the primary funding, National Natural Science Foundation of China (No. ZX20230400)
文摘Saline aquifers are considered as highly favored reservoirs for CO_(2)sequestration due to their favorable properties.Understanding the impact of saline aquifer properties on the migration and distribution of CO_(2)plume is crucial.This study focuses on four key parameters-permeability,porosity,formation pressure,and temperature-to characterize the reservoir and analyse the petrophysical and elastic response of CO_(2).First,we performed reservoir simulations to simulate CO_(2)saturation,using multiple sets of these four parameters to examine their significance on CO_(2)saturation and the plume migration speed.Subsequently,the effect of these parameters on the elastic properties is tested using rock physics theory.We established a relationship of compressional wave velocity(V_(p))and quality factor(Q_(p))with the four key parameters,and conducted a sensitivity analysis to test their sensitivity to V_(p) and Q_(p).Finally,we utilized visco-acoustic wave equation simulated time-lapse seismic data based on the computed V_(p) and Q_(p) models,and analysed the impact of CO_(2) saturation changes on seismic data.As for the above nu-merical simulations and analysis,we conducted sensitivity analysis using both homogeneous and heterogeneous models.Consistent results are found between homogeneous and heterogeneous models.The permeability is the most sensitive parameter to the CO_(2)saturation,while porosity emerges as the primary factor affecting both Q_(p) and V_(p).Both Q_(p) and V_(p) increase with the porosity,which contradicts the observations in gas reservoirs.The seismic simulations highlight significant variations in the seismic response to different parameters.We provided analysis for these observations,which serves as a valuable reference for comprehensive CO_(2)integrity analysis,time-lapse monitoring,injection planning and site selection.
