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.

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.

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.

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.

Progress of the bolometer diagnostic system on EAST

Measurements of the total radiated power and its spatial distribution are crucial for fusion research.On the experimental advanced superconducting tokamak(EAST),both the metal foil resistive bolometer and the absolute extreme ultraviolet(AXUV)photodiodes have been used to quantify the radiated power.This article introduces the latest improvement of the bolometer diagnostic system on EAST.It also details the successful design and installation of new divertor AXUV cameras,which are dedicated to the investigation of divertor physics.The shielding components of the bolometer detector have been refined,and the article provides a detailed exposition of the double shielding structures that have been verified as effective in microwave shielding.Additionally,the changes in the radiated power distribution in the divertor region during the plasma detachment process are measured using the divertor AXUV camera.Finally,the radiated power measured by the AXUV detector and metal foil resistive bolometer are compared,and different detector performances are presented.

Microfluidic preparation of surfactant-free ultrafine DAAF with tunable particle size for insensitive initiator explosives

High purity and ultrafine DAAF(u-DAAF)is an emerging insensitive charge in initiators.Although there are many ways to obtain u-DAAF,developing a preparation method with stable operation,accurate control,good quality consistency,equipment miniaturization,and minimum manpower is an inevitable requirement to adapt to the current social technology development trend.Here reported is the microfluidic preparation of u-DAAF with tunable particle size by a passive swirling microreactor.Under the guidance of recrystallization growth kinetics and mixing behavior of fluids in the swirling microreactor,the key parameters(liquid flow rate,explosive concentration and crystallization temperature)were screened and optimized through screening experiments.Under the condition that no surfactant is added and only experimental parameters are controlled,the particle size of recrystallized DAAF can be adjusted from 98 nm to 785 nm,and the corresponding specific surface area is 8.45 m^(2)·g^(-1)to 1.33 m^(2)·g^(-1).In addition,the preparation method has good batch stability,high yield(90.8%-92.6%)and high purity(99.0%-99.4%),indicating a high practical application potential.Electric explosion derived flyer initiation tests demonstrate that the u-DAAF shows an initiation sensitivity much lower than that of the raw DAAF,and comparable to that of the refined DAAF by conventional spraying crystallization method.This study provides an efficient method to fabricate u-DAAF with narrow particle size distribution and high reproducibility as well as a theoretical reference for fabrication of other ultrafine explosives.

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.

Evidence-Based Nursing Practice of Reducing Immune-Related Skin Toxicity of Tumor Patients Guided by Sensitive Indicators

Purpose research on nursing sensitive indicators in tumor Patients application effect in immune-related skin toxicity management. Method select our hospital April to June, 202360 cases patients with immune therapy settings as the control group. August-October, 2023 60 cases the patients treated with immune therapy were the experimental group. The control group adopted regular nursing methods, while the experimental group sensitive Indicators, evidence-based give preventive care. The social situation, psychological state, physical function, quality of life score, incidence of skin toxicity caused by immune checkpoint inhibitors, moderate and above of the two groups of patients were compared. Incidence of skin toxicity. Result: experience group SAS score, SDS score higher than the control group, the difference was statistically significant (P < 0.05);The incidence of skin toxic reactions caused by immune checkpoint inhibitors and the incidence of moderate and above skin toxic reactions in the experimental group are lower than those in the control group, and the difference is statistically significant (P < 0.05). Conclusion: sensitive indicator guidance evidence-based preventive care can reduce the degree of immune-related skin toxicity, improve the psychological state and quality of life of tumor patients treated with immune therapy and reduce the incidence of adverse reactions, improve nursing quality and patient satisfaction.

Sensitive skin syndrome: Research progress on mechanisms and applications

Sensitive skin is a clinical syndrome characterized by a hyper-reactive state of the skin,primarily on the face.It is accompanied by subjective symptoms such as burning,stinging,itching,and tightness when exposed to physical,chemical,or psychological stimuli.Objective signs,such as erythema,scales,and dilated blood vessels,may or may not be present.The discomfort associated with sensitive skin can be triggered by various endogenous and exogenous factors,which usually have no significant effect on the individual and do not induce irritant reactions.Sensitive skin often presents as a subjective state without clinical signs and exhibits diversity,posing challenges in sensitive skin research and care.This review summarizes the prevalence,key factors,pathophysiological mechanisms,diagnosis,and progress in daily care for sensitive skin.The aim is to provide a clearer and more systematic understanding of sensitive skin and offer guidance for sensitive skin care.

Sensitive Information Security Based on Elliptic Curves

The elliptic curve cryptography algorithm represents a major advancement in the field of computer security. This innovative algorithm uses elliptic curves to encrypt and secure data, providing an exceptional level of security while optimizing the efficiency of computer resources. This study focuses on how elliptic curves cryptography helps to protect sensitive data. Text is encrypted using the elliptic curve technique because it provides great security with a smaller key on devices with limited resources, such as mobile phones. The elliptic curves cryptography of this study is better than using a 256-bit RSA key. To achieve equivalent protection by using the elliptic curves cryptography, several Python libraries such as cryptography, pycryptodome, pyQt5, secp256k1, etc. were used. These technologies are used to develop a software based on elliptic curves. If built, the software helps to encrypt and decrypt data such as a text messages and it offers the authentication for the communication.

Promoting Ethical Sensitivity in Nursing Education:A Systematic Review of Case Study-Based Health Education

Introduction: Nursing ethical sensitivity refers to a nurse’s capacity for thoughtful consideration of ethical issues when faced with dilemmas. In the nursing domain, ethical dilemmas arise when nurses face challenges in making sound ethical decisions during clinical practice. These challenges may stem from conflicts between personal values and professional responsibilities. Methodology: Articles downloaded from Pub Med, CNKI, and Google Scholar were reviewed. Results: After rigorous screening, a meticulous analysis was conducted, encompassing 10 articles and involving a substantial cohort of 2863 participants. Existing literature revealed variations in the ethical dilemmas faced by nurses across different departments. The ethical sensitivity of nurses also varies, with higher ethical sensitivity correlating with stronger empathetic abilities. Zhen et al. classified the causes of ethical dilemmas into four main categories: (1) Ethical dilemmas arising from personal reasons of nursing students;(2) Ethical dilemmas stemming from the actions of teachers;(3) Ethical dilemmas triggered by patients;(4) Ethical dilemmas resulting from miscellaneous reasons. Conclusion: According to literature findings, nursing ethical sensitivity was positively linked to the nurse’s ethical decision-making ability. A case study-oriented teaching program has proven effective in enhancing ethical sensitivity among nursing students.

Introducing the nth-Order Features Adjoint Sensitivity Analysis Methodology for Nonlinear Systems (nth-FASAM-N): I. Mathematical Framework

This work presents the “nth-Order Feature Adjoint Sensitivity Analysis Methodology for Nonlinear Systems” (abbreviated as “nth-FASAM-N”), which will be shown to be the most efficient methodology for computing exact expressions of sensitivities, of any order, of model responses with respect to features of model parameters and, subsequently, with respect to the model’s uncertain parameters, boundaries, and internal interfaces. The unparalleled efficiency and accuracy of the nth-FASAM-N methodology stems from the maximal reduction of the number of adjoint computations (which are considered to be “large-scale” computations) for computing high-order sensitivities. When applying the nth-FASAM-N methodology to compute the second- and higher-order sensitivities, the number of large-scale computations is proportional to the number of “model features” as opposed to being proportional to the number of model parameters (which are considerably more than the number of features).When a model has no “feature” functions of parameters, but only comprises primary parameters, the nth-FASAM-N methodology becomes identical to the extant nth CASAM-N (“nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Nonlinear Systems”) methodology. Both the nth-FASAM-N and the nth-CASAM-N methodologies are formulated in linearly increasing higher-dimensional Hilbert spaces as opposed to exponentially increasing parameter-dimensional spaces thus overcoming the curse of dimensionality in sensitivity analysis of nonlinear systems. Both the nth-FASAM-N and the nth-CASAM-N are incomparably more efficient and more accurate than any other methods (statistical, finite differences, etc.) for computing exact expressions of response sensitivities of any order with respect to the model’s features and/or primary uncertain parameters, boundaries, and internal interfaces.

Impact of skin sensitivity mechanisms on sebum secretion: Management strategies for oily sensitive skin

Recent epidemiological surveys based on Baumann's classification have revealed a notable rise in the prevalence of oily sensitive skin.The development of oily sensitive skin is primarily linked to the abnormal function of sebaceous glands.The function of sebaceous glands is regulated by several factors,including inflammatory mediators,neurotransmitters,and endocrine signals.Sensitive skin,particularly oily sensitive skin,is prone to local inflammation,which in turn disrupts the normal functioning of sebaceous glands.This creates a loop wherein increased oil production exacerbates sensitivity,while heightened sensitivity further stimulates sebum secretion,perpetuating a vicious cycle.This article summarizes our understanding of the four primary mechanisms underlying skin sensitivity and their impact on sebaceous gland activity.Accordingly,it proposes management strategies for oily sensitive skin and seeks to guide the development of skin care regimens for this skin type.

Introducing the nth-Order Features Adjoint Sensitivity Analysis Methodology for Nonlinear Systems (nth-FASAM-N): II. Illustrative Example

This work highlights the unparalleled efficiency of the “nth-Order Function/ Feature Adjoint Sensitivity Analysis Methodology for Nonlinear Systems” (nth-FASAM-N) by considering the well-known Nordheim-Fuchs reactor dynamics/safety model. This model describes a short-time self-limiting power excursion in a nuclear reactor system having a negative temperature coefficient in which a large amount of reactivity is suddenly inserted, either intentionally or by accident. This nonlinear paradigm model is sufficiently complex to model realistically self-limiting power excursions for short times yet admits closed-form exact expressions for the time-dependent neutron flux, temperature distribution and energy released during the transient power burst. The nth-FASAM-N methodology is compared to the extant “nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Nonlinear Systems” (nth-CASAM-N) showing that: (i) the 1st-FASAM-N and the 1st-CASAM-N methodologies are equally efficient for computing the first-order sensitivities;each methodology requires a single large-scale computation for solving the “First-Level Adjoint Sensitivity System” (1st-LASS);(ii) the 2nd-FASAM-N methodology is considerably more efficient than the 2nd-CASAM-N methodology for computing the second-order sensitivities since the number of feature-functions is much smaller than the number of primary parameters;specifically for the Nordheim-Fuchs model, the 2nd-FASAM-N methodology requires 2 large-scale computations to obtain all of the exact expressions of the 28 distinct second-order response sensitivities with respect to the model parameters while the 2nd-CASAM-N methodology requires 7 large-scale computations for obtaining these 28 second-order sensitivities;(iii) the 3rd-FASAM-N methodology is even more efficient than the 3rd-CASAM-N methodology: only 2 large-scale computations are needed to obtain the exact expressions of the 84 distinct third-order response sensitivities with respect to the Nordheim-Fuchs model’s parameters when applying the 3rd-FASAM-N methodology, while the application of the 3rd-CASAM-N methodology requires at least 22 large-scale computations for computing the same 84 distinct third-order sensitivities. Together, the nth-FASAM-N and the nth-CASAM-N methodologies are the most practical methodologies for computing response sensitivities of any order comprehensively and accurately, overcoming the curse of dimensionality in sensitivity analysis.

Sensitive system calls based packed malware variants detection using principal component initialized MultiLayers neural networks

Malware detection has become mission sensitive as its threats spread from computer systems to Internet of things systems.Modern malware variants are generally equipped with sophisticated packers,which allow them bypass modern machine learning based detection systems.To detect packed malware variants,unpacking techniques and dynamic malware analysis are the two choices.However,unpacking techniques cannot always be useful since there exist some packers such as private packers which are hard to unpack.Although dynamic malware analysis can obtain the running behaviours of executables,the unpacking behaviours of packers add noisy information to the real behaviours of executables,which has a bad affect on accuracy.To overcome these challenges,in this paper,we propose a new method which first extracts a series of system calls which is sensitive to malicious behaviours,then use principal component analysis to extract features of these sensitive system calls,and finally adopt multi-layers neural networks to classify the features of malware variants and legitimate ones.Theoretical analysis and real-life experimental results show that our packed malware variants detection technique is comparable with the the state-of-art methods in terms of accuracy.Our approach can achieve more than 95.6\%of detection accuracy and 0.048 s of classification time cost.

The Impact of Moist Physics on the Sensitive Area Identification for Heavy Rainfall Associated Weather Systems

The impact of moist physics on the sensitive areas identified by conditional nonlinear optimal perturbation(CNOP)is examined based on four typical heavy rainfall cases in northern China through performing numerical experiments with and without moist physics.Results show that the CNOP with moist physics identifies sensitive areas corresponding to both the lower-(850−700 hPa)and upper-level(300−100 hPa)weather systems,while the CNOP without moist physics fails to capture the sensitive areas at lower levels.The reasons for the CNOP peaking at different levels can be explained in both algorithm and physics aspects.Firstly,the gradient of the cost function with respect to initial perturbations peaks at the upper level without moist physics which results in the upper-level peak of the CNOP,while it peaks at both the upper and lower levels with moist physics which results in both the upper-and lower-level peaks of the CNOP.Secondly,the upper-level sensitive area is associated with high baroclinicity,and these dynamic features can be captured by both CNOPs with and without moist physics.The lower-level sensitive area is associated with moist processes,and this thermodynamic feature can be captured only by the CNOP with moist physics.This result demonstrates the important contribution of the initial error of lower-level systems that are related to water vapor transportation to the forecast error of heavy rainfall associated weather systems,which could be an important reference for heavy rainfall observation targeting.

Tri-directional shaking table tests of vibration sensitive equipment with static dynamics interchangeable-ball pendulum system

Recently, the high-tech industry has become a key industry for economic development in many countries. However, vibration sensitive equipment located in these industrial buildings is vulnerable during earthquakes, which may cause huge economic loss. In this study, an innovative isolator for safeguarding the vibration sensitive equipment, namely, the static dynamics interchangeable^all pendulum system （SDI-BPS） is proposed and investigated to examine its protective capability for the vibration sensitive equipment during earthquakes through a series of tri-directional shaking table tests. The experimental results illustrate that the SDI-BPS isolator can provide significant damping to rolling types of base isolation systems for reducing the bearing displacement and size, and avoid the stress concentration, which can cause damage or scratches on the rolling surface of the isolator, to prolong its life span of service. The SDI-BPS isolator also provides excellent capability in protecting the vibration sensitive equipment and exhibits a stable behavior under long terms of service loadings and earthquakes.

Sensitive Resource and Traffic Density Risk Analysis of Marine Spill Accidents Using Automated Identification System Big Data

This study developed a new methodology for analyzing the risk level of marine spill accidents from two perspectives,namely,marine traffic density and sensitive resources.Through a case study conducted in Busan,South Korea,detailed procedures of the methodology were proposed and its scalability was confirmed.To analyze the risk from a more detailed and microscopic viewpoint,vessel routes as hazard sources were delineated on the basis of automated identification system(AIS)big data.The outliers and errors of AIS big data were removed using the density-based spatial clustering of applications with noise algorithm,and a marine traffic density map was evaluated by combining all of the gridded routes.Vulnerability of marine environment was identified on the basis of the sensitive resource map constructed by the Korea Coast Guard in a similar manner to the National Oceanic and Atmospheric Administration environmental sensitivity index approach.In this study,aquaculture sites,water intake facilities of power plants,and beach/resort areas were selected as representative indicators for each category.The vulnerability values of neighboring cells decreased according to the Euclidean distance from the resource cells.Two resulting maps were aggregated to construct a final sensitive resource and traffic density(SRTD)risk analysis map of the Busan–Ulsan sea areas.We confirmed the effectiveness of SRTD risk analysis by comparing it with the actual marine spill accident records.Results show that all of the marine spill accidents in 2018 occurred within 2 km of high-risk cells(level 6 and above).Thus,if accident management and monitoring capabilities are concentrated on high-risk cells,which account for only 6.45%of the total study area,then it is expected that it will be possible to cope with most marine spill accidents effectively.

Heterogeneity and non-linearity of ecosystem responses to climate change in the Qilian Mountains National Park, China

Ecosystem responses to climate change,particularly in arid environments,is an understudied topic.This study conducted a spatial analysis of ecosystem responses to short-term variability in temperature,precipitation,and solar radiation in the Qilian Mountains National Park,an arid mountainous region in Northwest China.We collected precipitation and temperature data from the National Science and Technology Infrastructure Platform,solar radiation data from the China Meteorological Forcing Dataset,and vegetation cover remote-sensing data from the Moderate Resolution Imaging Spectroradiometer.We used the vegetation sensitivity index to identify areas sensitive to climate change and to determine which climatic factors were significant in this regard.The findings revealed a high degree of heterogeneity and non-linearity of ecosystem responses to climate change.Four types of heterogeneity were identified:longitude,altitude,ecosystem,and climate disturbance.Furthermore,the characteristics of nonlinear ecosystem responses to climate change included:(1)inconsistency in the controlling climatic factors for the same ecosystems in different geographical settings;(2)the interaction between different climatic factors results in varying weights that affect ecosystem stability and makes them difficult to determine;and(3)the hysteresis effect of vegetation increases the uncertainty of ecosystem responses to climate change.The findings are significant because they highlight the complexity of ecosystem responses to climate change.Furthermore,the identification of areas that are particularly sensitive to climate change and the influencing factors has important implications for predicting and managing the impacts of climate change on ecosystems,which can help protect the stability of ecosystems in the Qilian Mountains National Park.

Secure Sharing Scheme of Sensitive Data in the Precision Medicine System

Numerous industries,especially the medical industry,are likely to exhibit significant developments in the future.Ever since the announcement of the precision medicine initiative by the United States in 2015,interest in the field has considerably increased.The techniques of precision medicine are employed to provide optimal treatment and medical services to patients,in addition to the prevention and management of diseases via the collection and analysis of big data related to their individual genetic characteristics,occupation,living environment,and dietary habits.As this involves the accumulation and utilization of sensitive information,such as patient history,DNA,and personal details,its implementation is difficult if the data are inaccurate,exposed,or forged,and there is also a concern for privacy,as massive amount of data are collected;hence,ensuring the security of information is essential.Therefore,it is necessary to develop methods of securely sharing sensitive data for the establishment of a precision medicine system.An authentication and data sharing scheme is presented in this study on the basis of an analysis of sensitive data.The proposed scheme securely shares sensitive data of each entity in the precision medicine system according to its architecture and data flow.