Ultra‑High Sensitivity Anisotropic Piezoelectric Sensors for Structural Health Monitoring and Robotic Perception

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.

近红外无创血糖浓度的Label Sensitivity算法和支持向量机回归

近红外光谱分析技术在生物医学工程领域具有广阔应用前景。无创且持续性地测量能实时监控人体血糖水平,给糖尿病患者带来极大便利性、提高生存质量、降低糖尿病并发症发生率具有很大的社会效益。无创血糖监测的想法提出较早,但仍然存在预测精度低、预测值与标签值相关性不高等难点,至今没有达到临床要求。近年来,光谱检测技术发展迅猛且机器学习技术在智能信息处理方面具有明显优势,两者结合可以有效提高人体无创血糖医学监测模型的精度和普适性。提出了一种标签敏感度算法(LS),并结合支持向量机方法建立了人体血糖含量预测模型。使用近红外光谱仪采集了4名志愿者食指处动态血液光谱数据(每名志愿者28组数据),并使用多元散射矫正(MSC)方法消除了部分光散射的影响。考虑血糖对不同波长光的吸收有差异,提出了基于血糖浓度标签差的特征波长挑选方法,并构建了标签敏感度支持向量机(LSSVR)预测模型。设计实验,对比该模型与偏最小二乘回归(PLSR)和区分度支持向量机(FSSVR)算法。结果表明,LS算法的最佳特征波长数为32,经特征波长选择后的LSSVR表现最佳,其均方误差降低至0.02 mmol·L^(-1),明显优于全谱段PLSR模型,血糖浓度的预测值与标签值的相关系数提升至99.8%,预测值全部位于可容许误差的克拉克网格A区内。LSSVR模型的优异表现为早日实现血糖的无创监测提供了新思路。

A semi-analytical model for coupled flow in stress-sensitive multi-scale shale reservoirs with fractal characteristics

A large number of nanopores and complex fracture structures in shale reservoirs results in multi-scale flow of oil. With the development of shale oil reservoirs, the permeability of multi-scale media undergoes changes due to stress sensitivity, which plays a crucial role in controlling pressure propagation and oil flow. This paper proposes a multi-scale coupled flow mathematical model of matrix nanopores, induced fractures, and hydraulic fractures. In this model, the micro-scale effects of shale oil flow in fractal nanopores, fractal induced fracture network, and stress sensitivity of multi-scale media are considered. We solved the model iteratively using Pedrosa transform, semi-analytic Segmented Bessel function, Laplace transform. The results of this model exhibit good agreement with the numerical solution and field production data, confirming the high accuracy of the model. As well, the influence of stress sensitivity on permeability, pressure and production is analyzed. It is shown that the permeability and production decrease significantly when induced fractures are weakly supported. Closed induced fractures can inhibit interporosity flow in the stimulated reservoir volume (SRV). It has been shown in sensitivity analysis that hydraulic fractures are beneficial to early production, and induced fractures in SRV are beneficial to middle production. The model can characterize multi-scale flow characteristics of shale oil, providing theoretical guidance for rapid productivity evaluation.

Identification, pathogenicity, and fungicide sensitivity of Eutiarosporella dactylidis associated with leaf blight on maize in China

Maize(Zea mays L.) is an economically vital grain crop that is cultivated worldwide. In 2011, a maize foliar disease was detected in Lingtai and Lintao counties in Gansu Province, China. The characteristic signs and symptoms of this disease include irregular chlorotic lesions on the tips and edges of infected leaves and black punctate fruiting bodies in dead leaf tissues. Given favourable environmental conditions, this disease spread to areas surrounding Gansu. In this study, infected leaves were collected from Gansu and Ningxia Hui Autonomous Region between 2018and 2020 to identify the disease-causing pathogen. Based on morphological features, pathogenicity tests, and multilocus phylogenetic analysis involving internal transcribed spacer(ITS), 18S small subunit rDNA(SSU), 28S large subunit rDNA(LSU), translation elongation factor 1-alpha(TEF), and β-tubulin(TUB) sequences, Eutiarosporella dactylidis was identified as the causative pathogen of this newly discovered leaf blight. Furthermore, an in vitro bioassay was conducted on representative strains using six fungicides, and both fludioxonil and carbendazim were found to significantly inhibit the mycelial growth of E. dactylidis. The results of this study provide a reference for the detection and management of Eutiarosporella leaf blight.

Future changes in precipitation and water availability over the Tibetan Plateau projected by CMIP6 models constrained by climate sensitivity

Precipitation projections over the Tibetan Plateau(TP)show diversity among existing studies,partly due to model uncertainty.How to develop a reliable projection remains inconclusive.Here,based on the IPCC AR6–assessed likely range of equilibrium climate sensitivity(ECS)and the climatological precipitation performance,the authors constrain the CMIP6(phase 6 of the Coupled Model Intercomparison Project)model projection of summer precipitation and water availability over the TP.The best estimates of precipitation changes are 0.24,0.25,and 0.45 mm d^(−1)(5.9%,6.1%,and 11.2%)under the Shared Socioeconomic Pathway(SSP)scenarios of SSP1–2.6,SSP2–4.5,and SSP5–8.5 from 2050–2099 relative to 1965–2014,respectively.The corresponding constrained projections of water availability measured by precipitation minus evaporation(P–E)are 0.10,0.09,and 0.22 mm d^(−1)(5.7%,4.9%,and 13.2%),respectively.The increase of precipitation and P–E projected by the high-ECS models,whose ECS values are higher than the upper limit of the likely range,are about 1.7 times larger than those estimated by constrained projections.Spatially,there is a larger increase in precipitation and P–E over the eastern TP,while the western part shows a relatively weak difference in precipitation and a drier trend in P–E.The wetter TP projected by the high-ECS models resulted from both an approximately 1.2–1.4 times stronger hydrological sensitivity and additional warming of 0.6℃–1.2℃ under all three scenarios during 2050–2099.This study emphasizes that selecting climate models with climate sensitivity within the likely range is crucial to reducing the uncertainty in the projection of TP precipitation and water availability changes.

Efficient slope reliability and sensitivity analysis using quantile-based first-order second-moment method

This paper introduces a novel approach for parameter sensitivity evaluation and efficient slope reliability analysis based on quantile-based first-order second-moment method(QFOSM).The core principles of the QFOSM are elucidated geometrically from the perspective of expanding ellipsoids.Based on this geometric interpretation,the QFOSM is further extended to estimate sensitivity indices and assess the significance of various uncertain parameters involved in the slope system.The proposed method has the advantage of computational simplicity,akin to the conventional first-order second-moment method(FOSM),while providing estimation accuracy close to that of the first-order reliability method(FORM).Its performance is demonstrated with a numerical example and three slope examples.The results show that the proposed method can efficiently estimate the slope reliability and simultaneously evaluate the sensitivity of the uncertain parameters.The proposed method does not involve complex optimization or iteration required by the FORM.It can provide a valuable complement to the existing approximate reliability analysis methods,offering rapid sensitivity evaluation and slope reliability analysis.

MEAN SENSITIVITY AND BANACH MEAN SENSITIVITY FOR LINEAR OPERATORS

Let(X,T)be a linear dynamical system,where X is a Banach space and T:X→X is a bounded linear operator.This paper obtains that(X,T)is sensitive(Li-Yorke sensitive,mean sensitive,syndetically mean sensitive,respectively)if and only if(X,T)is Banach mean sensitive(Banach mean Li-Yorke sensitive,thickly multi-mean sensitive,thickly syndetically mean sensitive,respectively).Several examples are provided to distinguish between different notions of mean sensitivity,syndetic mean sensitivi`ty and mean Li-Yorke sensitivity.

Numerical analysis of downward progressive landslides in long natural slopes with sensitive clay

Landslides occurring in sensitive clay often result in widespread destruction,posing a significant risk to human lives and property due to the substantial decrease in undrained shear strength during deformation.Assessing the consequences of these landslides is challenging and necessitates robust numerical methods to comprehensively investigate their failure mechanisms.While studies have extensively explored upward progressive landslides in sensitive clays,understanding downward progressive cases remains limited.In this study,we utilised the nodal integration-based particle finite element method(NPFEM)with a nonlinear strain-softening model to analyse downward progressive landslides in sensitive clay on elongated slopes,induced by surcharge loads near the crest.We focused on elucidating the underlying failure mechanisms and evaluating the effects of different soil parameters and strainsoftening characteristics.The simulation results revealed the typical pattern for downward landslides,which typically start with a localised failure in proximity to the surcharge loads,followed by a combination of different types of failure mechanisms,including single flow slides,translational progressive landslides,progressive flow slides,and spread failures.Additionally,inclined shear bands occur within spread failures,often adopting distinctive ploughing patterns characterised by triangular shapes.The sensitive clay thickness at the base,the clay strength gradient,the sensitivity,and the softening rate significantly influence the failure mechanisms and the extent of diffused displacement.Remarkably,some of these effects mirror those observed in upward progressive landslides,underscoring the interconnectedness of these phenomena.This study contributes valuable insights into the complex dynamics of sensitive clay landslides,shedding light on the intricate interplay of factors governing their behaviour and progression.

Characterizing permeability-porosity relationships of porous rocks using a stress sensitivity model in consideration of elastic-structural deformation and tortuosity sensitivity

Clarifying the relationship between stress sensitivities of permeability and porosity is of great significance in guiding underground resource mining.More and more studies focus on how to construct stress sensitivity models to describe the relationship and obtain a comprehensive stress sensitivity of porous rock.However,the limitations of elastic deformation calculation and incompleteness of considered tortuosity sensitivity lead to the fact that the existing stress sensitivity models are still unsatisfactory in terms of accuracy and generalization.Therefore,a more accurate and generic stress sensitivity model considering elastic-structural deformation of capillary cross-section and tortuosity sensitivity is proposed in this paper.The elastic deformation is derived from the fractal scaling model and Hooke's law.Considering the effects of elastic-structural deformation on tortuosity sensitivity,an empirical formula is proposed,and the conditions for its applicability are clarified.The predictive performance of the proposed model for the permeability-porosity relationships is validated in several sets of publicly available experimental data.These experimental data are from different rocks under different pressure cycles.The mean and standard deviation of relative errors of predicted stress sensitivity with respect to experimental data are 2.63%and 1.91%.Compared with other models,the proposed model has higher accuracy and better predictive generalization performance.It is also found that the porosity sensitivity exponent a,which can describe permeability-porosity relationships,is 2 when only elastic deformation is considered.a decreases from 2 when structural deformation is also considered.In addition,a may be greater than 3 due to the increase in tortuosity sensitivity when tortuosity sensitivity is considered even if the rock is not fractured.

High-Precision Flow Numerical Simulation and Productivity Evaluation of Shale Oil Considering Stress Sensitivity

Continental shale oil reservoirs,characterized by numerous bedding planes and micro-nano scale pores,feature significantly higher stress sensitivity compared to other types of reservoirs.However,research on suitable stress sensitivity characterization models is still limited.In this study,three commonly used stress sensitivity models for shale oil reservoirs were considered,and experiments on representative core samples were conducted.By fitting and comparing the data,the“exponential model”was identified as a characterization model that accurately represents stress sensitivity in continental shale oil reservoirs.To validate the accuracy of the model,a two-phase seepage mathematical model for shale oil reservoirs coupled with the exponential model was introduced.The model was discretely solved using the finite volume method,and its accuracy was verified through the commercial simulator CMG.The study evaluated the productivity of a typical horizontal well under different engineering,geological,and fracture conditions.The results indicate that considering stress sensitivity leads to a 13.57%reduction in production for the same matrix permeability.Additionally,as the fracture half-length and the number of fractures increase,and the bottomhole flowing pressure decreases,the reservoir stress sensitivity becomes higher.

Sensitivity and resistance risk analysis of Didymella bryoniae populations to fluopyram

Fluopyram is an succinate dehydrogenase inhibitors(SDHI)fungicide that has been registered in China to control gummy stem blight(GSB)in watermelons for many years.However,whether the field pathogens of GSB are still sensitive to fluopyram or not is unknown.Therefore,we collected 69 Didymella bryoniae isolates from the fields that usually use fluopyram to control GSB to determine the sensitivity change.The EC_(50)(50%inhibition effect)values of fluopyram against D.bryoniae ranged from 0.0691 to 0.3503μg mL^(–1) and the variation factor was 5.07.The mean EC_(50) value was(0.1579±0.0669)μg mL^(–1) and the curve of sensitivity was unimodal.No resistant strains were found in the isolates,which means that the pathogens were still sensitive to fluopyram.The minimal inhibition concentration(MIC)of fluopyram against D.bryoniae was 3μg mL^(–1).Four low-resistant mutants and two medium-resistant mutants were obtained using fungicide taming and the resistance of mutants could be inherited stably.The growth rate of mutants decreased significantly compared with that of wild-type strains while the biomass of most mutants was similar to that of wild-type strains.The sensitivity of most resistant mutants to various stresses was increased compared with that of wild-type strains.The virulence of mutants receded except for low-resistant mutant XN51FR-1,which had the same lesion area as XN51 on the watermelon leaves.The results indicated that the fitness of resistant mutants was decreased compared with that of wild-type strains.The cross-resistance assay indicated that fluopyram-resistant mutants were positive cross-resistant to all six SDHI fungicides in this test but were still sensitive to fluazinam and tebuconazole.So the resistance risk of D.bryoniae to fluopyram was moderate.In addition,we found that the SdhB gene of low-resistant mutant XN30FR-1 had three new point mutations at positions K258N,A259P,and H277N.Medium-resistant mutant XN52FR-1 showed a mutation at position H277N and other mutants did not have any point mutation.

Synthesis and Charcterization of Silane Crosslinked Hydrogel to pH Sensitive Study

Eco-friendly and biodegradable novel hydrogel were prepared by blending and solution casting method. The designed hydrogel is based on chitosan/ PEG600/Gurgam with carbon nanofiller along silane crosslinked (TEOS) with pH sensitive response to controlled release of drug in biomedical materials and agriculture industry. The various concentration of carbon nanofiller is used to analyze its effect on the fabricated hydrogel characteristics by using FTIR, SEM, TGA, swelling studies (water, buffer and ionic solution). Spectra of FTIR reflected both established and newly developed groups (like hydrogel). COOH group presence is clearly observed in this range in the carbon filler reinforced hydrogel. The SEM micrographs show that CPG0.003 had a collection of polysaccharide chains as thin helices, which is attributed to the increase in the size of porosity. TGA shows to increase concentration of nanofiller enhanced the thermal stability of the designed hydrogels at temperature 25˚C to 550˚C mass loss percentage decrease upto 20% and increase thermal stability. This pH response made these resultant hydrogels as fruitful competitor against the many reported controlled release application.

Surface-sensitive electronic structure of kagome superconductor CsV_(3)Sb_(5)

We systematically study the electronic structure of a kagome superconductor CsV_(3)Sb_(5)at different temperatures coveringboth its charge density wave state and normal state with angle-resolved photoemission spectroscopy.We observe thatthe V-shaped band aroundГshows three different behaviors,referred to as a/a',βandγ,mainly at different temperatures.Detailed investigations confirm that these bands are all from the same bulk Sb-p_(z)origin,but they are quite sensitiveto the sample surface conditions mainly modulated by temperature.Thus,the intriguing temperature dependent electronicbehavior of the band nearГis affected by the sample surface condition,rather than intrinsic electronic behavior originatingfrom the phase transition.Our result systematically reveals the confusing electronic structure behavior of the energy bandsaroundГ,facilitating further exploration of the novel properties in this material.

Profile of Peanut Sensitization in Children Attending a Pneumo-Allergology Consultation at the Teaching Hospital Campus of Lomé, Togo

Introduction: Food allergies are on the constant increase worldwide. Among them is peanut allergy, which also affects children. The aim of this study was to determine the profile of peanut sensitization in children attending a pneumo-allergology consultation. Methods: This was a cross-sectional study, which ran from January 1, 2018, to December 31, 2022, on children sensitized to peanuts seen in pneumo-allergology consultations at the Teaching Hospital Campus of Lomé. Results: The sample included 137 children aged 3 months to 18 years. The frequency of peanut sensitization was 25.3%. The mean age of patients was 6.3 ± 4.3 years (minimum 6 months and maximum 18 years). The 6 months to 5 years age group was the most represented (43.1%). The sex ratio was 1.3. The main reasons for consultation were rhinorrhea (67.9%), sneezing (36.5%) and cough (35.8%). Allergic rhinitis was identified as a personal history in 75.2% of patients. Peanut allergy was manifested as rhinorrhea (62.5%), asthma (26.8%) and eczema (8.9%). The risk of onset of symptoms within 15 - 30 minutes was 1.87 times (p = 0.001, CI = [1.2 - 2.1]) for peanuts consumed in roasted form with shell. Severe clinical signs such as Quincke’s Edema and anaphylactic shock were found in 1.4% of cases. Conclusion: Peanut allergy was common in children. Severe clinical signs were rare.

An efficient data-driven global sensitivity analysis method of shale gas production through convolutional neural network

The shale gas development process is complex in terms of its flow mechanisms and the accuracy of the production forecasting is influenced by geological parameters and engineering parameters.Therefore,to quantitatively evaluate the relative importance of model parameters on the production forecasting performance,sensitivity analysis of parameters is required.The parameters are ranked according to the sensitivity coefficients for the subsequent optimization scheme design.A data-driven global sensitivity analysis(GSA)method using convolutional neural networks(CNN)is proposed to identify the influencing parameters in shale gas production.The CNN is trained on a large dataset,validated against numerical simulations,and utilized as a surrogate model for efficient sensitivity analysis.Our approach integrates CNN with the Sobol'global sensitivity analysis method,presenting three key scenarios for sensitivity analysis:analysis of the production stage as a whole,analysis by fixed time intervals,and analysis by declining rate.The findings underscore the predominant influence of reservoir thickness and well length on shale gas production.Furthermore,the temporal sensitivity analysis reveals the dynamic shifts in parameter importance across the distinct production stages.

Linear dichroism transition and polarization-sensitive photodetector of quasi-one-dimensional palladium bromide

Perpendicular optical reversal of the linear dichroism transition has promising applications in polarization-sensitive optoelectronic devices. We perform a systematical study on the in-plane optical anisotropy of quasi-one-dimensional PdBr_(2) by using combined measurements of the angle-resolved polarized Raman spectroscopy(ARPRS) and anisotropic optical absorption spectrum. The analyses of ARPRS data validate the anisotropic Raman properties of the PdBr_(2) flake.And anisotropic optical absorption spectrum of PdBr_(2) nanoflake demonstrates distinct optical linear dichroism reversal. Photodetector constructed by PdBr_(2) nanowire exhibits high responsivity of 747 A·W^(-1) and specific detectivity of 5.8×10^(12) Jones. And the photodetector demonstrates prominent polarization-sensitive photoresponsivity under 405-nm light irradiation with large photocurrent anisotropy ratio of 1.56, which is superior to those of most of previously reported quasi-one-dimensional counterparts. Our study offers fundamental insights into the strong optical anisotropy exhibited by PdBr_(2), establishing it as a promising candidate for miniaturization and integration trends of polarization-related applications.

Advancements in the Research of Gold Nanomaterials for Radiation Therapy Sensitization

Gold nanomaterials exhibit unique advantages in tumor radiotherapy sensitization due to their enhanced X-ray deposition capability, excellent biocompatibility, and superior chemical, electronic, and optical properties. To date, studies on gold nanomaterial-mediated radiosensitization have been reported, with related mechanisms including catalyzing reactive oxygen species (ROS) production, depleting intracellular glutathione (GSH), overcoming tumor hypoxia, and regulating cell cycles. This article will elaborate on the research progress of gold nanomaterial-mediated tumor radiotherapy sensitization and discuss its mechanisms and future research directions. In addition, the limitations of gold nanomaterials in clinical applications will be further discussed.

A polarization sensitive interferometer:Delta interferometer

A new type of polarization sensitive interferometer is proposed,named the Delta interferometer,inspired by its geometry resembling the Greek letter Delta.The main difference between the Delta interferometer and other existing interferometers,such as Michelson,Mach-Zehnder and Young's double-slit interferometers,is that the two interfering paths are asymmetrical in the Delta interferometer.The visibility of the first-order interference pattern observed in the Delta interferometer is dependent on the polarization of the incidental light.Optical coherence theory is employed to interpret this phenomenon and single-mode continuous-wave laser light is employed to verify the theoretical predictions.The theoretical and experimental results are consistent.The Delta interferometer is a perfect tool to study the reflection of electromagnetic fields in different polarizations and may find applications in polarization-sensitive scenarios.

Highly Sensitive Detection of Strontium Ions Using Metal-Organic Frameworks Functionalized Solid-state Nanochannels

Strontium-90,a highly radioactive isotope,accumulates within the food chain and skeletal structure,posing significant risks to human health.There is a critical need for a sensitive detection strategy for Strontium-90 in complex environmental samples.Here,solid-state nanochannels,modified with metal-organic frameworks(MOF)and specific aptamers,were engineered for highly sensitive detection of strontium ion(Sr^(2+)).The synergistic effect between the reduced effective diameter of the nanochannels due to MOF and the specific binding of Sr^(2+) by aptamers amplifies the difference in ionic current signals,enhancing detection sensitivity significantly.The MOF-modified nanochannels exhibit highly sensitive detection of Sr^(2+),with a limit of detection(LOD)being 0.03 nmol·L^(-1),whereas the LOD for anodized aluminum oxide(AAO)without the modified MOF nanosheets is only 1000 nmol·L^(-1).These findings indicate that the LOD of Sr^(2+) detected by the MOF-modified nanochannels is approximately 33,000 times higher than that by the nanochannels without MOF modification.Additionally,the highly reliable detection of Sr^(2+) in various water samples was achieved,with a recovery rate ranging from 94.00%to 118.70%.This study provides valuable insights into the rapidly advancing field of advanced nanochannel-based sensors and their diverse applications for analyzing complex samples,including environmental contaminant detection,food analysis,medical diagnostics,and more.

Assessment of desertification sensitivity using an improved MEDALUS model in Northern China

Assessment of land sensitivity to desertification is an important step to support desertification monitoring and control.Based on the Mediterranean Desertification and Land Use(MEDALUS)model,we defined four quality indicators(soil,climate,vegetation and management)to evaluate the sensitivity of land in northern China to desertification.We improved MEDALUS via excluding cities from the areas at risk of desertification by means of defining a threshold value for population density.The framework,validated in northern China,further optimizes the model to link priority areas and land restoration programmed to support desertification control.We found that the four indicators influenced and restricted each other,which jointly affected the distribution of desertification sensitivity in northern China.The spatial distribution of sensitivity in northern China showed large regional differences,with clear boundaries and concentrated distributions of regions with high and low sensitivity;the overall sensitivity decreased,with some areas rated as having moderate,severe,and extremely severe sensitivity changing to slight sensitivity;and the influence weight was much higher for the management quality index than for the climate,vegetation,and soil indexes.This suggests that management was the main factor that affected desertification sensitivity in northern China,and that climate factors exacerbated sensitivity,but the factors that are driving the spatial heterogeneity of the influencing factors need further study。