Active and passive modulation of solar light transmittance in a uniquely multifunctional dual-band single molecule for smart window applications

Functional materials may change color by heat and electricity separately or simultaneously in smart windows.These materials have not only demonstrated remarkable potential in the modulation of solar radiation but are also leading to the development of indoor environments that are more comfortable and conducive to improving individuals'quality of life.Unfortunately,dual-responsive materials have not received ample research attention due to economic and technological challenges.As a consequence,the broader utilization of smart windows faces hindrances.To address this new generational multistimulus responsive chromic materials,our group has adopted a developmental strategy to create a poly(NIPAM)n-HV as a switchable material by anchoring active viologen(HV)onto a phase-changing poly(NIPAM)n-based smart material for better utility and activity.These constructed smart windows facilitate individualistic reversible switching,from a highly transparent state to an opaque state(thermochromic)and a red state(electrochromic),as well as facilitate a simultaneous dual-stimuli response reversible switching from a clear transparent state to a fully opaque(thermochromic)and orange(electrochromic)states.Absolute privacy can be attained in smart windows designed for exclusive settings by achieving zero transmittance.Each unique chromic mode operates independently and modulates visible and near-infrared(NIR)light in a distinct manner.Hence,these smart windows with thermal and electric dual-stimuli responsiveness demonstrate remarkable heat regulation capabilities,rendering them highly attractive for applications in building facades,energy harvesting,privacy protection,and color display.

AI-Driven Prioritization and Filtering of Windows Artifacts for Enhanced Digital Forensics

Digital forensics aims to uncover evidence of cybercrimes within compromised systems.These cybercrimes are often perpetrated through the deployment of malware,which inevitably leaves discernible traces within the compromised systems.Forensic analysts are tasked with extracting and subsequently analyzing data,termed as artifacts,from these systems to gather evidence.Therefore,forensic analysts must sift through extensive datasets to isolate pertinent evidence.However,manually identifying suspicious traces among numerous artifacts is time-consuming and labor-intensive.Previous studies addressed such inefficiencies by integrating artificial intelligence(AI)technologies into digital forensics.Despite the efforts in previous studies,artifacts were analyzed without considering the nature of the data within them and failed to prove their efficiency through specific evaluations.In this study,we propose a system to prioritize suspicious artifacts from compromised systems infected with malware to facilitate efficient digital forensics.Our system introduces a double-checking method that recognizes the nature of data within target artifacts and employs algorithms ideal for anomaly detection.The key ideas of this method are:(1)prioritize suspicious artifacts and filter remaining artifacts using autoencoder and(2)further prioritize suspicious artifacts and filter remaining artifacts using logarithmic entropy.Our evaluation demonstrates that our system can identify malicious artifacts with high accuracy and that its double-checking method is more efficient than alternative approaches.Our system can significantly reduce the time required for forensic analysis and serve as a reference for future studies.

Case Report: Surgical Correction of Transposition of the Great Arteries with Aortopulmonary Window

Introduction:Transposition of the great arteries(TGA)with aortopulmonary window is a rare type of congenital heart disease with limited experience.We reported a neonate aged 25 days receiving the arterial switch operation and assisted with extracorporeal membrane oxygenation.Conclusion:TGA with aortopulmonary window can be safely correctly with the arterial switch operation.

Window Views of Wards in Foreign Hospitals

Through the collection and systematic analysis of documents related to window views of hospitals,it is found that natural window views had a significant impact on patients’health benefits.The research focused on three aspects:“shortening length of stay”,“pain reduction”and“improvement of recovery rate”,mainly covering three types of patients:“heart patients”,“postoperative patients”and“patients of rehabilitation centers”.Based on the above analysis,summary and sorting,new directions and perspectives of hospital environment design and research under the concept of comprehensive health of people’s physiological,psychological and social adaptation will be obtained to provide references for the research and practice of health architecture,rehabilitation architecture,biophile design and other fields.

Design of Intelligent Window Automatic Monitoring System Based on Microcontroller Control

To ensure the safety of residents’lives and property by using automatic opening and closing of ordinary windows,this article designs an intelligent window automatic monitoring system.The article proposes a software and hardware design scheme for the system,which comprises a microcontroller control module,temperature and humidity detection module,harmful gas detection module,rainfall detection module,human thermal radiation induction module,Organic Light-Emitting Diode(OLED)display module,stepper motor drive module,Wi-Fi communication module,etc.Users use this system to monitor environmental data such as temperature,humidity,rainfall,harmful gas concentrations,and human health.Users can control the opening and closing of windows through manual,microcontroller,and mobile application(app)remote methods,providing users with a more convenient,comfortable,and safe living environment.

通过交叉验证堆栈和VAD信息检测Windows代码注入

Windows 32/64位代码注入攻击是恶意软件常用的攻击技术,在内存取证领域,现存的代码注入攻击检测技术在验证完整性方面不能处理动态内容,并且在解析内存中数据结构方面无法兼容不同版本的Windows系统。因此提出了通过交叉验证进程堆栈和VAD信息定位注入代码方法,将基于遍历栈帧得到的函数返回地址、模块名等信息结合进程VAD结构来检测函数返回地址、匹配文件名以定位注入代码,并且研发了基于Volatility取证框架的Windows代码注入攻击检测插件codefind。测试结果表明,即使在VAD节点被恶意软件修改,方法仍能够有效定位Windows 32/64位注入代码攻击。

Development of RF windows for 650 MHz multibeam klystron

Radio frequency windows are developed and evaluated for a 650 MHz continuous-wave multibeam klystron.Thin-pillbox windows with alumina and beryllia disks are designed with an average RF power of CW 400 kW.Results of a cold test and tuning procedures are described.The final measured S11 curves under the required bandwidth are less than-32.0 and-26.9 dB for alumina and beryllia windows,respectively.The windows are tested up to CW 143 kW for traveling waves and CW 110 kW for standing waves using a solid-state amplifier as an RF power source.Multipactor simulations for windows and benchmark studies for the thermal analysis of ceramic disks are introduced.

Trend of Developing Aqueous Liquid and Gel Electrolytes for Sustainable,Safe,and High‑Performance Li‑Ion Batteries

Current lithium-ion batteries(LIBs)rely on organic liquid electrolytes that pose significant risks due to their flammability and toxicity.The potential for environmental pollution and explosions resulting from battery damage or fracture is a critical concern.Water-based(aqueous)electrolytes have been receiving attention as an alternative to organic electrolytes.However,a narrow electrochemicalstability window,water decomposition,and the consequent low battery operating voltage and energy density hinder the practical use of aqueous electrolytes.Therefore,developing novel aqueous electrolytes for sustainable,safe,high-performance LIBs remains challenging.This Review first commences by summarizing the roles and requirements of electrolytes–separators and then delineates the progression of aqueous electrolytes for LIBs,encompassing aqueous liquid and gel electrolyte development trends along with detailed principles of the electrolytes.These aqueous electrolytes are progressed based on strategies using superconcentrated salts,concentrated diluents,polymer additives,polymer networks,and artificial passivation layers,which are used for suppressing water decomposition and widening the electrochemical stability window of water of the electrolytes.In addition,this Review discusses potential strategies for the implementation of aqueous Li-metal batteries with improved electrolyte–electrode interfaces.A comprehensive understanding of each strategy in the aqueous system will assist in the design of an aqueous electrolyte and the development of sustainable and safe high-performance batteries.

A novel calculation strategy for optimized prediction of the reduction of electrochemical window at anode

The reduction of the electrochemical window(EW)of electrolytes plays a significant role in assessing their compatibility with the anode in lithium-ion batteries.However,the accurate calculation of the reduction of EW is still challenging due to missing the solvation effects,condensation effects,kinetic factors,and the passivation on anodes.The theoretical prediction of the intrinsic and apparent EW is confirmed by a comprehensive experimental analysis of ethylene carbonatedimethyl carbonate(EC-DMC)electrolytes,combining linear sweep voltammetry(LSV)and gas chromatography-mass spectrometry(GC-MS).The proposed novel kinetic normal distribution theory model can quantitatively explain the current density from LSV and affirm acetaldehyde(MeCHO)as one of the primary reduction products of EC.The solvent effect restricts the intrinsic EW of EC-DMC without lithium salt to 2.6 V(vs.Li^(+)/Li)arising from the Marcus-Gerischer theory and the passivation of MeCHO on the anode broadens the apparent EW to 0.3 V(vs.Li^(+)/Li)arising from the normal distribution of the lowest unoccupied molecular orbital(LUMO)for MeCHO produced by thermal motion.In addition,the passivation on the anode depends intensively on the lithium salt,resulting in more complicated influences on the apparent EW.

Bimetallic In_(2)O_(3)/Bi_(2)O_(3) Catalysts Enable Highly Selective CO_(2) Electroreduction to Formate within Ultra-Broad Potential Windows

CO_(2)electrochemical reduction reaction(CO_(2)RR)to formate is a hopeful pathway for reducing CO_(2)and producing high-value chemicals,which needs highly selective catalysts with ultra-broad potential windows to meet the industrial demands.Herein,the nanorod-like bimetallic ln_(2)O_(3)/Bi_(2)O_(3)catalysts were successfully synthesized by pyrolysis of bimetallic InBi-MOF precursors.The abundant oxygen vacancies generated from the lattice mismatch of Bi_(2)O_(3)and ln_(2)O_(3)reduced the activation energy of CO_(2)to*CO_(2)·^(-)and improved the selectivity of*CO_(2)·^(-)to formate simultaneously.Meanwhile,the carbon skeleton derived from the pyrolysis of organic framework of InBi-MOF provided a conductive network to accelerate the electrons transmission.The catalyst exhibited an ultra-broad applied potential window of 1200 mV(from-0.4 to-1.6 V vs RHE),relativistic high Faradaic efficiency of formate(99.92%)and satisfactory stability after 30 h.The in situ FT-IR experiment and DFT calculation verified that the abundant oxygen vacancies on the surface of catalysts can easily absorb CO_(2)molecules,and oxygen vacancy path is dominant pathway.This work provides a convenient method to construct high-performance bimetallic catalysts for the industrial application of CO_(2)RR.

Fluid simulation of the effect of a dielectric window with high temperature on plasma parameters in inductively coupled plasma

To maintain the high-density plasma source in inductively coupled plasma(ICP),very high radiofrequency power is often delivered to the antenna,which can heat the dielectric windows near the antenna to high temperature.This high temperature can modulate the plasma characteristics to a large degree.We thus study the effect of dielectric window temperature on plasma parameters in two different ICP structures based on COMSOL software.The distributions of various plasma species are examined at different dielectric window temperatures.The concentration of neutral gas is found to be largely modulated at high dielectric window temperature,which further affects the electron collision probability with neutrals and the electron temperature.However,the electron density profiles are barely affected by the dielectric window temperature,which is mainly concentrated at the center of the reactor due to the fixed power input and pressure.

Prediction of the Wastewater’s pH Based on Deep Learning Incorporating Sliding Windows

To protect the environment,the discharged sewage’s quality must meet the state’s discharge standards.There are many water quality indicators,and the pH(Potential of Hydrogen)value is one of them.The natural water’s pH value is 6.0–8.5.The sewage treatment plant uses some data in the sewage treatment process to monitor and predict whether wastewater’s pH value will exceed the standard.This paper aims to study the deep learning prediction model of wastewater’s pH.Firstly,the research uses the random forest method to select the data features and then,based on the sliding window,convert the data set into a time series which is the input of the deep learning training model.Secondly,by analyzing and comparing relevant references,this paper believes that the CNN(Convolutional Neural Network)model is better at nonlinear data modeling and constructs a CNN model including the convolution and pooling layers.After alternating the combination of the convolutional layer and pooling layer,all features are integrated into a full-connected neural network.Thirdly,the number of input samples of the CNN model directly affects the prediction effect of the model.Therefore,this paper adopts the sliding window method to study the optimal size.Many experimental results show that the optimal prediction model can be obtained when alternating six convolutional layers and three pooling layers.The last full-connection layer contains two layers and 64 neurons per layer.The sliding window size selects as 12.Finally,the research has carried out data prediction based on the optimal CNN deep learning model.The predicted pH of the sewage is between 7.2 and 8.6 in this paper.The result is applied in the monitoring system platform of the“Intelligent operation and maintenance platform of the reclaimed water plant.”

Effect of False Windows on Light Exposure and Sleep Quality in Hospitalized Patients

Purpose: We aimed to investigate the effects of installing false windows next to hospital beds without windows on the amount of light received by patients and their sleep quality. Methods: The study included patients admitted to the Department of Neurology at our hospital between September 2020 and August 2021. An Actigraph device was fitted to patients’ wrist and their beds to measure the amount of light received and sleep quality. Patients were divided into three groups: bed with a window, aisle bed with a false window, and aisle bed without a window. Mean sleep efficiency (%), mean steps (per day), and the amount of light (lux) received by the patients and beds were measured. Results: Valid data were obtained for 48 participants (median age, 66.5 years). There were 23 patients in beds with a window, 13 patients in aisle beds without a false window, and 12 in aisle beds with a false window. No statistically significant differences were found in terms of mean sleep efficiency, number of steps taken, and the amount of light received by the patients (P > 0.05);however, difference in the mean amount of light received by the beds at the location of the bed was statistically significant (P Conclusion: The amount of light that the patient receives is not necessarily affected by the location of the bed or the presence of a false window.

Path Planning of UAV by Combing Improved Ant Colony System and Dynamic Window Algorithm

A fusion algorithm is proposed to enhance the search speed of an ant colony system(ACS)for the global path planning and overcome the challenges of the local path planning in an unmanned aerial vehicle(UAV).The ACS search efficiency is enhanced by adopting a 16-direction 24-neighborhood search way,a safety grid search way,and an elite hybrid strategy to accelerate global convergence.Quadratic planning is performed using the moving average(MA)method.The fusion algorithm incorporates a dynamic window approach(DWA)to deal with the local path planning,sets a retracement mechanism,and adjusts the evaluation function accordingly.Experimental results in two environments demonstrate that the improved ant colony system(IACS)achieves superior planning efficiency.Additionally,the optimized dynamic window approach(ODWA)demonstrates its ability to handle multiple dynamic situations.Overall,the fusion optimization algorithm can accomplish the mixed path planning effectively.

基于Windows Server Failover Cluster的Apache故障转移集群应用实践

在当前互联网时代,Web应用程序的高可用性和可靠性是确保业务持续运行的关键因素。针对Apache Web服务器,介绍了利用Windows Server 2019 Failover Cluster构建Apache故障转移集群的实践方案。通过配置两个节点的故障转移集群,当某个节点发生故障时,Apache服务将自动在另一个节点上重新启动,从而最大程度地减少系统中断的时间,提高Web应用的可用性。详细阐述了集群搭建的具体步骤、配置要点、集群验证方法以及运行时的监控与维护方法,为构建高可用Apache Web服务器提供一种实用的解决方案。

Study on dynamic response of high speed train window glass under tunnel aerodynamic effects

Purpose-This paper aims to analyze the bearing characteristics of the high speed train window glass under aerodynamic load effects.Design/methodology/approach-In order to obtain the dynamic strain response of passenger compartment window glass during high-speed train crossing the tunnel,taking the passenger compartment window glass of the CRH3 high speed train onWuhan-Guangzhou High Speed Railway as the research object,this study tests the strain dynamic response and maximum principal stress of the high speed train passing through the tunnel entrance and exit,the tunnel and tunnel groups as well as trains meeting in the tunnel at an average speed of 300 km$h-1.Findings-The results show that while crossing the tunnel,the passenger compartment window glass of high speed train is subjected to the alternating action of positive and negative air pressures,which shows the typical mechanic characteristics of the alternating fatigue stress of positive-negative transient strain.The maximum principal stress of passenger compartment window glass for high speed train caused by tunnel aerodynamic effects does not exceed 5 MPa,and the maximum value occurs at the corresponding time of crossing the tunnel groups.The high speed train window glass bears medium and low strain rates under the action of tunnel aerodynamic effects,while the maximum strain rate occurs at the meeting moment when the window glass meets the train head approaching from the opposite side in the tunnel.The shear modulus of laminated glass PVB film that makes up high speed train window glass is sensitive to the temperature and action time.The dynamically equivalent thickness and stiffness of the laminated glass and the dynamic bearing capacity of the window glass decrease with the increase of the action time under tunnel aerodynamic pressure.Thus,the influence of the loading action time and fatigue under tunnel aerodynamic effects on the glass strength should be considered in the design for the bearing performance of high speed train window glass.Originality/value-The research results provide data support for the analysis of mechanical characteristics,damage mechanism,strength design and structural optimization of high speed train glass.

Research status and challenges in the manufacturing of IR conformal optics

The infrared conformal window is one of the most critical components in aircraft.Conformal windows with high performance bring low aberrations,high aerodynamic performance,reliability in extreme working environments,and added value for aircraft.Through the past decades,remarkable advances have been achieved in manufacturing technologies for conformal windows,where the machining accuracy approaches the nanometer level,and the surface form becomes more complex.These advances are critical to aircraft development,and these manufacturing technologies also have significant reference values for other directions of the ultra-precision machining field.In this review,the infrared materials suitable for manufacturing conformal windows are introduced and compared with insights into their performances.The remarkable advances and concrete work accomplished by researchers are reviewed.The challenges in manufacturing conformal windows that should be faced in the future are discussed.

Strong Interaction Between Redox Mediators and Defect-Rich Carbons Enabling Simultaneously Boosted Voltage Windows and Capacitance for Aqueous Supercapacitors

Energy density,the Achilles’heel of aqueous supercapacitors,is simultaneously determined by the voltage window and specific capacitance of the carbon materials,but the strategy of synchronously boosting them has rarely been reported.Herein,we demonstrate that the rational utilization of the interaction between redox mediators(RMs)and carbon electrode materials,especially those with rich intrinsic defects,contributes to extended potential windows and more stored charges concurrently.Using 4-hydroxy-2,2,6,6-tetramethylpiperidinyloxyl(4OH-TEMPO)and intrinsic defect-rich carbons as the RMs and electrode materials,respectively,the potential window and capacitance are increased by 67%and sixfold in a neutral electrolyte.Moreover,this strategy could also be applied to alkaline and acid electrolytes.The first-principle calculation and experimental results demonstrate that the strong interaction between 4OH-TEMPO and defectrich carbons plays a key role as preferential adsorbed RMs may largely prohibit the contact of free water molecules with the electrode materials to terminate the water splitting at elevated potentials.For the RMs offering weaker interaction with the electrode materials,the water splitting still proceeds with a thus sole increase of the stored charges.The results discovered in this work could provide an alternative solution to address the low energy density of aqueous supercapacitors.

Learning Epipolar Line Window Attention for Stereo Image Super-Resolution Reconstruction

Transformer-based stereo image super-resolution reconstruction(Stereo SR)methods have significantly improved image quality.However,existing methods have deficiencies in paying attention to detailed features and do not consider the offset of pixels along the epipolar lines in complementary views when integrating stereo information.To address these challenges,this paper introduces a novel epipolar line window attention stereo image super-resolution network(EWASSR).For detail feature restoration,we design a feature extractor based on Transformer and convolutional neural network(CNN),which consists of(shifted)window-based self-attention((S)W-MSA)and feature distillation and enhancement blocks(FDEB).This combination effectively solves the problem of global image perception and local feature attention and captures more discriminative high-frequency features of the image.Furthermore,to address the problem of offset of complementary pixels in stereo images,we propose an epipolar line window attention(EWA)mechanism,which divides windows along the epipolar direction to promote efficient matching of shifted pixels,even in pixel smooth areas.More accurate pixel matching can be achieved using adjacent pixels in the window as a reference.Extensive experiments demonstrate that our EWASSR can reconstruct more realistic detailed features.Comparative quantitative results show that in the experimental results of our EWASSR on the Middlebury and Flickr1024 data sets for 2×SR,compared with the recent network,the Peak signal-to-noise ratio(PSNR)increased by 0.37 dB and 0.34 dB,respectively.

Classification and Comprehension of Software Requirements Using Ensemble Learning

The software development process mostly depends on accurately identifying both essential and optional features.Initially,user needs are typically expressed in free-form language,requiring significant time and human resources to translate these into clear functional and non-functional requirements.To address this challenge,various machine learning(ML)methods have been explored to automate the understanding of these requirements,aiming to reduce time and human effort.However,existing techniques often struggle with complex instructions and large-scale projects.In our study,we introduce an innovative approach known as the Functional and Non-functional Requirements Classifier(FNRC).By combining the traditional random forest algorithm with the Accuracy Sliding Window(ASW)technique,we develop optimal sub-ensembles that surpass the initial classifier’s accuracy while using fewer trees.Experimental results demonstrate that our FNRC methodology performs robustly across different datasets,achieving a balanced Precision of 75%on the PROMISE dataset and an impressive Recall of 85%on the CCHIT dataset.Both datasets consistently maintain an F-measure around 64%,highlighting FNRC’s ability to effectively balance precision and recall in diverse scenarios.These findings contribute to more accurate and efficient software development processes,increasing the probability of achieving successful project outcomes.