Bose–Einstein distribution temperature features of quasiparticles around magnetopolaron in Gaussian quantum wells of alkali halogen ions

We have applied strong coupling unitary transformation method combined with Bose–Einstein statistical law to investigate magnetopolaron energy level temperature effects in halogen ion crystal quantum wells.The obtained results showed that under magnetic field effect,magnetopolaron quasiparticle was formed through the interaction of electrons and surrounding phonons.At the same time,magnetopolaron was influenced by phonon temperature statistical law and important energy level shifts down and binding energy increases.This revealed that lattice temperature and magnetic field could easily affect magnetopolaron and the above results could play key roles in exploring thermoelectric conversion and conductivity of crystal materials.

Temperature is a cryptic factor shaping the geographical pattern of genetic variation in Ceratophyllum demersum across a subtropical freshwater lake

Macrophyte habitats exhibit remarkable heterogeneity,encompassing the spatial variation of abiotic and biotic components such as changes in water conditions and weather as well as anthropogenic stressors.Environmental factors are thought to be important drivers shaping the genetic and epigenetic variation of aquatic plants.However,the links among genetic diversity,epigenetic variation,and environmental variables remain largely unclear,especially for clonal aquatic plants.Here,we performed population genetic and epigenetic analyses in conjunction with habitat discrimination to elucidate the environmental factors driving intraspecies genetic and epigenetic variation in hornwort(Ceratophyllum demersum)in a subtropical lake.Environmental factors were highly correlated with the genetic and epigenetic variation of C.demersum,with temperature being a key driver of the genetic variation.Lower temperature was detected to be correlated with greater genetic and epigenetic variation.Genetic and epigenetic variation were positively driven by water temperature,but were negatively affected by ambient air temperature.These findings indicate that the genetic and epigenetic variation of this clonal aquatic herb is not related to the geographic feature but is instead driven by environmental conditions,and demonstrate the effects of temperature on local genetic and epigenetic variation in aquatic systems.

Theoretical characterization of the temperature-dependent saturation magnetization of magnetic metallic materials

Based on the force-heat equivalence energy density principle,a theoretical model for magnetic metallic materials is developed,which characterizes the temperature-dependent magnetic anisotropy energy by considering the equivalent relationship between magnetic anisotropy energy and heat energy;then the relationship between the magnetic anisotropy constant and saturation magnetization is considered.Finally,we formulate a temperature-dependent model for saturation magnetization,revealing the inherent relationship between temperature and saturation magnetization.Our model predicts the saturation magnetization for nine different magnetic metallic materials at different temperatures,exhibiting satisfactory agreement with experimental data.Additionally,the experimental data used as reference points are at or near room temperature.Compared to other phenomenological theoretical models,this model is considerably more accessible than the data required at 0 K.The index included in our model is set to a constant value,which is equal to 10/3 for materials other than Fe,Co,and Ni.For transition metals(Fe,Co,and Ni in this paper),the index is 6 in the range of 0 K to 0.65T_(cr)(T_(cr) is the critical temperature),and 3 in the range of 0.65T_(cr) to T_(cr),unlike other models where the adjustable parameters vary according to each material.In addition,our model provides a new way to design and evaluate magnetic metallic materials with superior magnetic properties over a wide range of temperatures.

Source localization in signed networks with effective distance

While progress has been made in information source localization,it has overlooked the prevalent friend and adversarial relationships in social networks.This paper addresses this gap by focusing on source localization in signed network models.Leveraging the topological characteristics of signed networks and transforming the propagation probability into effective distance,we propose an optimization method for observer selection.Additionally,by using the reverse propagation algorithm we present a method for information source localization in signed networks.Extensive experimental results demonstrate that a higher proportion of positive edges within signed networks contributes to more favorable source localization,and the higher the ratio of propagation rates between positive and negative edges,the more accurate the source localization becomes.Interestingly,this aligns with our observation that,in reality,the number of friends tends to be greater than the number of adversaries,and the likelihood of information propagation among friends is often higher than among adversaries.In addition,the source located at the periphery of the network is not easy to identify.Furthermore,our proposed observer selection method based on effective distance achieves higher operational efficiency and exhibits higher accuracy in information source localization,compared with three strategies for observer selection based on the classical full-order neighbor coverage.

A study on the temperature sensitivity of NMR porosity in porous media based on the intensity of magnetization Dedicated to the special issue “Magnetic Resonance in Porous Media”

The measurement of nuclear magnetic resonance(NMR)porosity is affected by temperature.Without considering the impact of NMR logging tools,this phenomenon is mainly caused by variations in magnetization intensity of the measured system due to temperature fluctuations and difference between the temperature of the porous medium and calibration sample.In this study,the effect of temperature was explained based on the thermodynamic theory,and the rules of NMR porosity responses to temperature changes were identified through core physics experiments.In addition,a method for correcting the influence of temperature on NMR porosity measurement was proposed,and the possible factors that may affect its application were also discussed.

A Quasi-Linear Relationship between Planetary Outgoing Longwave Radiation and Surface Temperature in a Radiative-Convective-Transportive Climate Model of a Gray Atmosphere

In this study,we put forward a radiative-convective-transportive energy balance model of a gray atmosphere to examine individual roles of the greenhouse effect of water vapor,vertical convection,and atmospheric poleward energy transport as well as their combined effects for a quasi-linear relationship between the outgoing longwave radiation(OLR)and surface temperature(T_(S)).The greenhouse effect of water vapor enhances the meridional gradient of surface temperature,thereby directly contributing to a quasi-linear OLR-T_(S) relationship.The atmospheric poleward energy transport decreases the meridional gradient of surface temperature.As a result of the poleward energy transport,tropical(high-latitude)atmosphere-surface columns emit less(more)OLR than the solar energy input at their respective locations,causing a substantial reduction of the meridional gradient of the OLR.The combined effect of reducing the meridional gradients of both OLR and surface temperature by the poleward energy transport also contributes to the quasi-linear OLR-T_(S) relationship.Vertical convective energy transport reduces the meridional gradient of surface temperature without affecting the meridional gradient of OLR,thereby suppressing part of the reduction to the increasing rate of OLR with surface temperature by the greenhouse effect of water vapor and poleward energy transport.Because of the nature of the energy balance in the climate system,such a quasi-linear relationship is also a good approximation for the relationship between the annual-mean net downward solar energy flux at the top of the atmosphere and surface temperature.

An Explanation of the Temperature-Dependent Upper Critical Field Data of H3S on the Basis of the Thermodynamics of a Superconductor in a Magnetic Field

Excellent fits to a couple of the data-sets on the temperature (T)-dependent upper critical field (Hc2) of H3S (critical temperature, Tc ≈ 200 K at pressure ≈ 150 GPa) reported by Mozaffari, et al. (2019) were obtained by Talantsev (2019) in an approach based on an ingenious mix of the Ginzberg-Landau (GL), the Werthamer, Helfand and Hohenberg (WHH), and the Gor’kov, etc., theories which have individually been employed for the same purpose for a long time. Up to the lowest temperature (TL) in each of these data-sets, similarly accurate fits have also been obtained by Malik and Varma (2023) in a radically different approach based on the Bethe-Salpeter equation (BSE) supplemented by the Matsubara and the Landau quantization prescriptions. For T TL, however, while the (GL, WHH, etc.)-based approach leads to Hc2(0) ≈ 100 T, the BSE-based approach leads to about twice this value even at 1 K. In this paper, a fit to one of the said data-sets is obtained for the first time via a thermodynamic approach which, up to TL, is as good as those obtained via the earlier approaches. While this is interesting per se, another significant result of this paper is that for T TL it corroborates the result of the BSE-based approach.

Permanent Magnet Temperature Estimation for PMSMs Using Virtual Position-offset Injection

This paper proposes a virtual position-offset injection based permanent magnet temperature estimation approach for permanent magnet synchronous machines(PMSMs). The concept of virtual position-offset injection is mathematically transforming the machine model to a virtual frame with a position-offset. The virtual frame temperature estimation model is derived to calculate the permanent magnet temperature(PMT) directly from the measurements with computation efficiency. The estimation model involves a combined inductance term, which can simplify the establishment of saturation compensation model with less measurements. Moreover, resistance and inverter distorted terms are cancelled in the estimation model, which can improve the robustness to the winding temperature rise and inverter distortion. The proposed approach can achieve simplified computation in temperature estimation and reduced memory usage in saturation compensation. While existing model-based approaches could be affected by either the need of resistance and inverter information or complex saturation compensation. Experiments are conducted on the test machine to verify the proposed approach under various operating conditions.

Prediction of three-dimensional ocean temperature in the South China Sea based on time series gridded data and a dynamic spatiotemporal graph neural network

Ocean temperature is an important physical variable in marine ecosystems,and ocean temperature prediction is an important research objective in ocean-related fields.Currently,one of the commonly used methods for ocean temperature prediction is based on data-driven,but research on this method is mostly limited to the sea surface,with few studies on the prediction of internal ocean temperature.Existing graph neural network-based methods usually use predefined graphs or learned static graphs,which cannot capture the dynamic associations among data.In this study,we propose a novel dynamic spatiotemporal graph neural network(DSTGN)to predict threedimensional ocean temperature(3D-OT),which combines static graph learning and dynamic graph learning to automatically mine two unknown dependencies between sequences based on the original 3D-OT data without prior knowledge.Temporal and spatial dependencies in the time series were then captured using temporal and graph convolutions.We also integrated dynamic graph learning,static graph learning,graph convolution,and temporal convolution into an end-to-end framework for 3D-OT prediction using time-series grid data.In this study,we conducted prediction experiments using high-resolution 3D-OT from the Copernicus global ocean physical reanalysis,with data covering the vertical variation of temperature from the sea surface to 1000 m below the sea surface.We compared five mainstream models that are commonly used for ocean temperature prediction,and the results showed that the method achieved the best prediction results at all prediction scales.

A study on temperature monitoring method for inverter IGBT based on memory recurrent neural network

The power module of the Insulated Gate Bipolar Transistor(IGBT)is the core component of the traction transmission system of high-speed trains.The module's junction temperature is a critical factor in determining device reliability.Existing temperature monitoring methods based on the electro-thermal coupling model have limitations,such as ignoring device interactions and high computational complexity.To address these issues,an analysis of the parameters influencing IGBT failure is conducted,and a temperature monitoring method based on the Macro-Micro Attention Long Short-Term Memory(MMALSTM)recursive neural network is proposed,which takes the forward voltage drop and collector current as features.Compared with the traditional electricalthermal coupling model method,it requires fewer monitoring parameters and eliminates the complex loss calculation and equivalent thermal resistance network establishment process.The simulation model of a highspeed train traction system has been established to explore the accuracy and efficiency of MMALSTM-based prediction methods for IGBT power module junction temperature.The simulation outcomes,which deviate only 3.2% from the theoretical calculation results of the electric-thermal coupling model,confirm the reliability of this approach for predicting the temperature of IGBT power modules.

Quality of Service and Security on Cisco Network Devices, Coupled with the Development of a Mobile Application Prototype Software for Server Room Temperature Monitoring

In an era where digital technology is paramount, higher education institutions like the University of Zambia (UNZA) are employing advanced computer networks to enhance their operational capacity and offer cutting-edge services to their academic fraternity. Spanning across the Great East Road campus, UNZA has established one of the most extensive computer networks in Zambia, serving a burgeoning community of over 20,000 active users through a Metropolitan Area Network (MAN). However, as the digital landscape continues to evolve, it is besieged with burgeoning challenges that threaten the very fabric of network integrity—cyber security threats and the imperatives of maintaining high Quality of Service (QoS). In an effort to mitigate these threats and ensure network efficiency, the development of a mobile application to monitor temperatures in the server room was imperative. According to L. Wei, X. Zeng, and T. Shen, the use of wireless sensory networks to monitor the temperature of train switchgear contact points represents a cost-effective solution. The system is based on wireless communication technology and is detailed in their paper, “A wireless solution for train switchgear contact temperature monitoring and alarming system based on wireless communication technology”, published in the International Journal of Communications, Network and System Sciences, vol. 8, no. 4, pp. 79-87, 2015 [1]. Therefore, in this study, a mobile application technology was explored for monitoring of temperatures in the server room in order to aid Cisco device performance. Additionally, this paper also explores the hardening of Cisco device security and QoS which are the cornerstones of this study.

The Impact of Temperature on the Electromagnet and Structural Optimization of a Solenoid Valve

The mathematical model of the solenoid valve under varying temperatures is constructed to investigate its performance and enhance heat dissipation balance.The relationship between temperature and electromagnetic force is determined.Electrothermal coupling simulation using COMSOL is conducted,optimizing the outer diameter and length structure parameters of the coil.It is established that the heat dissipation of the coil is influenced by its outer diameter.Subsequently,based on optimized coil structure parameters,an orthogonal experimental design method combined with Ansys Maxwell is employed for simulation solution analysis to study the impact of structural parameters such as length,position,front and rear angles of the magnetic barrier ring in the iron core,armature length,and through-hole size on electromagnetic force.Optimal structural parameters are identified.Results indicate a decrease in steady-state electromagnet temperature by 3-4℃,an increase in the initial electromagnetic force by 32.63%,and a rise in the maximum electromagnetic force by 27.10%.

光伏型红外焦平面探测器NETD的理论计算和测试分析

噪声等效温差(NETD)是表征红外焦平面探测器灵敏度的重要参数,除了器件本身的因素以外,与实际应用条件及测试条件密切相关。从红外焦平面探测器NETD的测试方法和流程出发,对光伏型红外焦平面探测器NETD的理论计算公式进行了推导,分析了影响器件NETD的主要因素,对典型红外焦平面探测器在不同积分时间、不同电荷存储量、不同F数及半阱输出条件下的背景限NETD进行了理论计算及分析。在固定背景温度下,通过理论公式可从某一温差的NETD推算出不同温差的NETD,选择典型器件进行验证,从常规NETD测试结果推算出的一组NETD与相应温差下的实测结果符合较好,其中1 K温差的NETD推算结果已非常接近实际情况,可为热像仪系统应用提供参考。

基于U-net神经网络的油浸式变压器绕组流-热耦合快速计算

该文针对采用传统数值方法进行大型油浸变压器绕组温升仿真时间较长的问题,提出一种基于U-net神经网络训练的快速计算方法,可以迅速地预测变压器绕组温升及热点。首先,根据流热耦合原理筛选输入变量,并运用流热耦合方法计算不同工况下的输出结果,并将之制作成训练集和测试集。同时,详细讨论3个对网络训练影响最显著的超参数;其次,将归一化后的训练集输入U-net神经网络进行训练,并设置超参数最佳组合;最后,将预测集输入训练好的模型进行预测计算及反归一化操作,预测绕组热点与Fluent仿真结果相差仅0.44 K,单次仿真时间从200 s缩短为0.07 s。预测结果与实验温度平均误差最大为2.31 K,最小为0.98 K,预测方差为0.31左右。结果表明:该方法可用于快速获得油浸式变压器绕组的温度及热点,可满足变压器温度热点数字孪生的实时性仿真要求。

An Environment‑Tolerant Ion‑Conducting Double‑Network Composite Hydrogel for High‑Performance Flexible Electronic Devices

High-performance ion-conducting hydrogels(ICHs)are vital for developing flexible electronic devices.However,the robustness and ion-conducting behavior of ICHs deteriorate at extreme tempera-tures,hampering their use in soft electronics.To resolve these issues,a method involving freeze–thawing and ionizing radiation technology is reported herein for synthesizing a novel double-network(DN)ICH based on a poly(ionic liquid)/MXene/poly(vinyl alcohol)(PMP DN ICH)system.The well-designed ICH exhibits outstanding ionic conductivity(63.89 mS cm^(-1) at 25℃),excellent temperature resistance(-60–80℃),prolonged stability(30 d at ambient temperature),high oxidation resist-ance,remarkable antibacterial activity,decent mechanical performance,and adhesion.Additionally,the ICH performs effectively in a flexible wireless strain sensor,thermal sensor,all-solid-state supercapacitor,and single-electrode triboelectric nanogenerator,thereby highlighting its viability in constructing soft electronic devices.The highly integrated gel structure endows these flexible electronic devices with stable,reliable signal output performance.In particular,the all-solid-state supercapacitor containing the PMP DN ICH electrolyte exhibits a high areal specific capacitance of 253.38 mF cm^(-2)(current density,1 mA cm^(-2))and excellent environmental adaptability.This study paves the way for the design and fabrication of high-performance mul-tifunctional/flexible ICHs for wearable sensing,energy-storage,and energy-harvesting applications.

The impact of Internet access on household dietary quality:Evidence from rural China

Over the past few decades,the Internet has rapidly diffused across China.The spread of the Internet has had a profound economic and social impact on Chinese rural areas.Existing research shows that Internet access significantly impacts agricultural production and improves smallholder farmers’income.Beyond these,the Internet can affect other dimensions of social welfare.However,research about the impact of Internet access on dietary quality in rural China remains scarce.This study utilizes multi-period panel data from Fixed Observation Point in rural China from 2009 to 2015 to estimate the impact of Internet access on dietary quality and food consumption of rural households and conducts a causal analysis.Regression models with time and household fixed effects allow robust estimation while reducing potential issues of unobserved heterogeneity.The estimates show that Internet access has significantly increased rural household dietary quality(measured by the Chinese Diet Balance Index).Further research finds that Internet access has increased the consumption of animal products,such as aquatic and dairy products.We also examine the underlying mechanisms.Internet access improves dietary quality and food consumption mainly through increasing household income and food expenditure.These results encourage the promotion of Internet access as a valuable tool for nutritional improvements,especially in rural areas.

“Buckets effect”in the kinetics of electrocatalytic reactions

In this study,we systematically investigated the effect of proton concentration on the kinetics of the oxygen reduction reaction(ORR)on Pt(111)in acidic solutions.Experimental results demonstrate a rectangular hyperbolic relationship,i.e.,the ORR current excluding the effect of other variables increases with proton concentration and then tends to a constant value.We consider that this is caused by the limitation of ORR kinetics by the trace oxygen concentration in the solution,which determines the upper limit of ORR kinetics.A model of effective concentration is further proposed for rectangular hyperbolic relationships:when the reactant concentration is high enough to reach a critical saturation concentration,the effective reactant concentration will become a constant value.This could be due to the limited concentration of a certain reactant for reactions involving more than one reactant or the limited number of active sites available on the catalyst.Our study provides new insights into the kinetics of electrocatalytic reactions,and it is important for the proper evaluation of catalyst activity and the study of structureperformance relationships.

Two-dimensional investigation of characteristic parameters and their gradients for the self-generated electric and magnetic fields of laser-induced zirconium plasma

Two-dimensional diagnosis of laser-induced zirconium(Zr)plasma has been experimentally performed using the time-of-flight method by employing Faraday cups in addition to electric and magnetic probes.The characteristic parameters of laser-induced Zr plasma have been evaluated as a function of different laser irradiances ranging from 4.5 to 11.7 GW cm-2 at different axial positions of 1–4 cm with a fixed radial distance of 2 cm.A well-supporting correlation between the plume parameters and the laser-plasma-produced spontaneous electric and magnetic(E and B)fields was established.The measurements of the characteristic parameters and spontaneously induced fields were observed to have an increasing trend with the increasing laser irradiance.However,when increasing the spatial distance in both the axial and radial directions,the plasma parameters(electron/ion number density,temperature and kinetic energy)did not show either continuously increasing or decreasing trends due to various kinetic and dynamic processes during the spatial evolution of the plume.However,the E and B fields were observed to be always diffusing away from the target.The radial component of electron number densities remained higher than the axial number density component,whereas the axial ion number density at all laser irradiances and axial distances remained higher than the radial ion number density.The higher axial self-generated electric field(SGEF)values than radial SGEF values are correlated with the effective charge-separation mechanism of electrons and ions.The generation of a self-generated magnetic field is observed dominantly in the radial direction at increasing laser irradiance as compared to the axial one due to the deflection of fast-moving electrons and the persistence of two-electron temperature on the radial axis.

Exciton Bose–Einstein Condensation in Transition Metal Dichalcogenide Monolayer under In-Plane Magnetic Fields

Based on the Gross–Pitaevskii equation,we theoretically investigate exciton Bose–Einstein condensation(BEC)in transition metal dichalcogenide monolayers(TMDC-MLs)under in-plane magnetic fields.We observe that the in-plane magnetic fields exert a strong influence on the exciton BEC wave functions in TMDC-MLs because of the mixing of the bright and dark exciton states via Zeeman effect.This leads to the brightening of the dark exciton BEC states.The competition between the dipole–dipole interactions caused by the long-range Coulomb interaction and the Zeeman effect induced by the in-plane magnetic fields can effectively regulate dark exciton BEC states.Our findings emphasize the utility of TMD-MLs as platforms for investigating collective phenomenon involving excited states.

Nonreciprocal Photon Blockade Based on Zeeman Splittings Induced by a Fictitious Magnetic Field

Quantum nonreciprocity, such as nonreciprocal photon blockade, has attracted a great deal of attention due to its unique applications in quantum information processing. Its implementation primarily relies on rotating nonlinear systems, based on the Sagnac effect. Here, we propose an all-optical approach to achieve nonreciprocal photon blockade in an on-chip microring resonator coupled to a V-type Rb atom, which arises from the Zeeman splittings of the atomic hyperfine sublevels induced by the fictitious magnetic field of a circularly polarized control laser. The system manifests single-photon blockade or multi-photon tunneling when driven from opposite directions. This nonreciprocity results from the directional detunings between the countercirculating probe fields and the V-type atom, which does not require the mechanical rotation and facilitates integration. Our work opens up a new route to achieve on-chip integrable quantum nonreciprocity, enabling applications in chiral quantum technologies.