Characterization of Flame Retardancy and Oil-Water Separation Capacity of Superhydrophobic Silylated Melamine Sponges

A silylated melamine sponge(SMS)was prepared by two simple steps,namely,immersion and dehydration of a melamine sponge coated with methyltrichlorosilane.The silylated structure of SMS was characterized by FT-IR(Fourier-transform infrared)spectroscopy,SEM(Scanning electron microscopy)and in terms of water contact angles.Its oil-water absorption and separation capacities were measured by FT-IR and UV-visible spectrophoto-metry.The experimental results have shown that oligomeric silanol covalently bonds by Si-N onto the surface of melamine sponge skeletons.SMS has shown superhydrophobicity with a water contact angle exceeding 150°±1°,a better separation efficiency with regard to diesel oil(by 99.31%(wt/wt%)in oil-water mixture and even up to 99.99%(wt/wt%)for diesel oil in its saturated aqueous solution.Moreover,SMS inherited the intrinsicflame retardancy of the melamine sponge.In general,SMS has shown superhydrophobicity,high porosity,excellent selectivity,remarkable recyclability,and better absorption capacity for various oils and organic solvents,and a high separation efficiency for oil in saturated aqueous solutions.

Artificial Intelligence for Maximizing Agricultural Input Use Efficiency: Exploring Nutrient, Water and Weed Management Strategies

Agriculture plays a crucial role in the economy,and there is an increasing global emphasis on automating agri-cultural processes.With the tremendous increase in population,the demand for food and employment has also increased significantly.Agricultural methods traditionally used to meet these requirements are no longer ade-quate,requiring solutions to issues such as excessive herbicide use and the use of chemical fertilizers.Integration of technologies such as the Internet of Things,wireless communication,machine learning,artificial intelligence(AI),and deep learning shows promise in addressing these challenges.However,there is a lack of comprehensive documentation on the application and potential of AI in improving agricultural input efficiency.To address this gap,a desk research approach was used by utilizing peer-reviewed electronic databases like PubMed,Scopus,Goo-gle Scholar,Web of Science,and Science Direct for relevant articles.Out of 327 initially identified articles,180 were deemed pertinent,focusing primarily on AI’s potential in enhancing yield through better management of nutrients,water,and weeds.Taking into account researchfindings worldwide,we found that AI technologies could assist farmers by providing recommendations on the optimal nutrients to enhance soil quality and deter-mine the best time for irrigation or herbicide application.The present status of AI-driven automation in agricul-ture holds significant promise for optimizing agricultural input utilization and reducing resource waste,particularly in the context of three pillars of crop management,i.e.,nutrient,irrigation,and weed management.

Review of preferentially selective lithium extraction from spent lithium batteries: Principle and performance

Lithium,as the lightest and lowest potential metal,is an ideal "battery metal" and the core strategic metal of the new energy industry revolution.Recovering lithium from spent lithium batteries(LIBs)has become one of the significant approaches to obtaining lithium resources.At present,the lithium extraction being generally placed at the last step of the spent LIBs recovery process has puzzles such as high acid consumption,low Li recovery purity and low recovery efficiency.Selective lithium extraction at the first step of the recovery process can effectively solve those puzzles.Since lithium leaching is a non-spontaneous reaction requiring additional energy to achieve,it is found that these methods can be divided into five ways according to the different types of energy driving the reaction occurring:(ⅰ)electric energy driving lithium extraction;(ⅱ) chemical energy driving lithium extraction;(ⅲ) mechanical energy driving lithium extraction;(ⅳ) thermal energy driving lithium extraction;(ⅴ) other energy driving lithium extraction.Through the analysis of the principle,reaction process and results of recovering lithium methods can provide a few directions for scholars’ subsequent research.It is necessary to speed up the exploration of the principle of these methods.It is expected that this study could provide a reference for the research on the selective lithium extraction.

Investigating the Effects of Eichhornia Crassipes Biodiesel and Liquefied Petroleum Gas on the Performance and Emissions of a Dual-Fuel Engine

This study considers the effect of Eichhornia Crassipes Biodiesel(ECB)blends on the performances,combustion,and emission characteristics of a direct injection compression ignition engine operated in a dual-fuel mode(DFM)and equipped with an Exhaust gas recirculation technique(EGR).In particular,a single-cylinder,four-stroke,water-cooled diesel engine was utilized and four modes of fuel operation were considered:mode I,the engine operated with an ordinary diesel fuel;mode II,the engine operated with the addition of 2.4 L/min of lique-fied petroleum gas(LPG)and 20%EGR;mode III,20%ECB with 2.4 L/min LPG and 20%EGR;mode IV,40%ECB with 2.4 L/min LPG and 20%EGR.The operation conditions were constant engine speed(1500 rpm),var-iation of load(25%,50%,75%,and 100%),full load,with a compression ratio of 18,and a time injection of 23°BTDC(Before top died center).With regard to engine emissions,carbon dioxide(CO_(2)),carbon monoxide(CO),hydrocarbons(UHC),and nitrogen oxide(NOX)were measured using a gas analyzer.The smoke opacity was measured using an OPABOX smoke meter.By comparing the results related to the different modes with mode I at full load,the BTE(Brake thermal efficiency)increased by 20.17%,11.45%,and 12.66%with modes II,III,and IV,respectively.In comparison to the results for mode II,the BTE decreased due to the combustion of ECB blends by 7.26%and 6.24%for mode III and mode IV,respectively,at full load.In comparison to mode II,the Brake specific energy consumption(BSEC)increased with the ECB substitution.With ECB blends,there is a noticeable decrease in the CO,CO_(2),and UHC emissions at a partial load.Furthermore,the 20%ECB has no effect on CO emissions at full load.For modes II and IV,the CO_(2)increased by 33.33%and 19%,respectively,while the UHC emissions were reduced by 14.49%for mode III and 26.08%for mode IV.The smoke of mode III was lower by 7.21%,but for mode IV,it was higher by 12.37%.In addition,with mode III and mode IV,the NOx emissions increased by 30.50%and 18.80%,respectively.

Energy Efficient Networks Using Ant Colony Optimization with Game Theory Clustering

Real-time applications based on Wireless Sensor Network(WSN)tech-nologies quickly lead to the growth of an intelligent environment.Sensor nodes play an essential role in distributing information from networking and its transfer to the sinks.The ability of dynamical technologies and related techniques to be aided by data collection and analysis across the Internet of Things(IoT)network is widely recognized.Sensor nodes are low-power devices with low power devices,storage,and quantitative processing capabilities.The existing system uses the Artificial Immune System-Particle Swarm Optimization method to mini-mize the energy and improve the network’s lifespan.In the proposed system,a hybrid Energy Efficient and Reliable Ant Colony Optimization(ACO)based on the Routing protocol(E-RARP)and game theory-based energy-efficient clus-tering algorithm(GEC)were used.E-RARP is a new Energy Efficient,and Reli-able ACO-based Routing Protocol for Wireless Sensor Networks.The suggested protocol provides communications dependability and high-quality channels of communication to improve energy.For wireless sensor networks,a game theo-ry-based energy-efficient clustering technique(GEC)is used,in which each sen-sor node is treated as a player on the team.The sensor node can choose beneficial methods for itself,determined by the length of idle playback time in the active phase,and then decide whether or not to rest.The proposed E-RARP-GEC improves the network’s lifetime and data transmission;it also takes a minimum amount of energy compared with the existing algorithms.

活血消癥方联合隔药饼灸周期调治肾虚血瘀型子宫腺肌症痛经的疗效观察

目的探讨活血消癥方联合隔药饼灸周期调治治疗子宫腺肌症痛经(肾虚血瘀)对临床症状及子宫体积的影响。方法选取2020年10月—2022年10月就诊于我院的122例子宫腺肌症痛经患者,按随机数字表法分为对照组和观察组,各61例。对照组采用隔药饼灸周期治疗,观察组采用活血消癥方联合隔药饼灸周期治疗。比较2组临床疗效、临床症状、痛经情况、治疗前后疼痛相关因子、子宫体积、子宫内膜厚度、性激素及不良反应。结果观察组总有效率高于对照组(P<0.05);治疗3个月经周期后,观察组症状积分、痛经症状评分量表(CMSS)评分、疼痛持续时间、视觉模拟评分法(VAS)、血清前列腺素F2(PGF2α)、P物质(SP)、子宫体积及内膜厚度、血清促卵泡刺激素(FSH)、促黄体生成素(LH)低于对照组,β-内啡肽(β-EP)、雌二醇(E_2)高于对照组(P<0.05)。结论活血消癥方联合隔药饼灸周期调治治疗子宫腺肌症痛经(肾虚血瘀)的疗效确切,能缓解患者临床症状,改善痛经情况,调节疼痛相关因子水平,减少子宫体积及子宫内膜厚度,调节性激素表达。

4BM-780型黄、红麻剥皮机的设计与试验

针对现有中小型黄、红麻剥皮机剥麻工效低的问题,研究了一种多速差高效分离装置,设计了一种大型黄、红麻剥皮机样机。该机主要由喂入装置、剥皮装置、输出装置、传动系统及控制系统5个部分组成。根据黄、红麻茎秆的物料特性以及剥制时的力学特性,通过理论计算与试验分析,确定了机器剥皮装置主要结构及其设计参数。机器的剥皮装置由碾压夹持滚筒、螺旋揉搓滚筒、梳理分离滚筒组成。碾压夹持辊筒线速度为2.10 m/s,滚筒直径200 mm;螺旋揉搓滚筒线速度为2.72 m/s,滚筒直径为260 mm;梳理分离滚筒线速度为4.39 m/s,滚筒直径为280 mm。对样机进行生产性能试验,结果表明:鲜茎出皮率为43.44%,鲜皮含杂率为12.54%,生产率(鲜茎)2481 kg/h,满足生产要求。该研究丰富了黄、红麻剥制机具类型,为其规模化生产提供了技术支撑,同时为黄、红麻联合收剥一体机的设计与开发提供了系统的理论依据及应用基础。

Performance Analysis of a Chunk-Based Speech Emotion Recognition Model Using RNN

Recently,artificial-intelligence-based automatic customer response sys-tem has been widely used instead of customer service representatives.Therefore,it is important for automatic customer service to promptly recognize emotions in a customer’s voice to provide the appropriate service accordingly.Therefore,we analyzed the performance of the emotion recognition(ER)accuracy as a function of the simulation time using the proposed chunk-based speech ER(CSER)model.The proposed CSER model divides voice signals into 3-s long chunks to effi-ciently recognize characteristically inherent emotions in the customer’s voice.We evaluated the performance of the ER of voice signal chunks by applying four RNN techniques—long short-term memory(LSTM),bidirectional-LSTM,gated recurrent units(GRU),and bidirectional-GRU—to the proposed CSER model individually to assess its ER accuracy and time efficiency.The results reveal that GRU shows the best time efficiency in recognizing emotions from speech signals in terms of accuracy as a function of simulation time.

Overcoming power efficiency limitation of white fluorescence light-emitting diodes via multilevel-hydrogen-bond matrix

High power efficiency and low efficiency roll-off at practical luminance are two requirements for new-generation energy-saving lighting technologies,which are still bottlenecks of thermally activated delayed fluorescence(TADF)white organic light-emitting diodes(WOLED),despite the advantages of TADF materials and devices in low cost and high sustainability.Herein,we developed a spiro phosphine oxide host named SSOXSPO,which can form multiple and multidirectional intermolecular hydrogen bonds(IHB).The resulted multilevel IHB network integrates long-range ordered and short-range disordered alignments for suppressing triplet-polaron quenching(TPQ)and triplet-triplet annihilation(TTA).Electronic characteristics of SSOXSPO matrix are further regulated,leading to the optimal exciton allocation through balancing energy and charge transfer.As consequence,using SSOXSPO as host,the single-emissive-layer TADF WOLEDs realized the record performance,including ultralow operation voltage as∼4.0 V,power efficiency beyond fluorescent tube(70.1 lm W−1)and negligible external quantum efficiency roll-off(3%)at 1000 nits for indoor lighting.This work demonstrates that multiple interplays supported by host matrixes in TADF WOLEDs can facilitate the synergistic effects of TADF emitters on 100%exciton utilization.

Chaotic Sandpiper Optimization Based Virtual Machine Scheduling for Cyber-Physical Systems

Recently,with the growth of cyber physical systems(CPS),several applications have begun to deploy in the CPS for connecting the cyber space with the physical scale effectively.Besides,the cloud computing(CC)enabled CPS offers huge processing and storage resources for CPS thatfinds helpful for a range of application areas.At the same time,with the massive development of applica-tions that exist in the CPS environment,the energy utilization of the cloud enabled CPS has gained significant interest.For improving the energy effective-ness of the CC platform,virtualization technologies have been employed for resource management and the applications are executed via virtual machines(VMs).Since effective scheduling of resources acts as an important role in the design of cloud enabled CPS,this paper focuses on the design of chaotic sandpi-per optimization based VM scheduling(CSPO-VMS)technique for energy effi-cient CPS.The CSPO-VMS technique is utilized for searching for the optimum VM migration solution and it helps to choose an effective scheduling strategy.The CSPO algorithm integrates the concepts of traditional SPO algorithm with the chaos theory,which substitutes the main parameter and combines it with the chaos.In order to improve the process of determining the global optimum solutions and convergence rate of the SPO algorithm,the chaotic concept is included in the SPO algorithm.The CSPO-VMS technique also derives afitness function to choose optimal scheduling strategy in the CPS environment.In order to demonstrate the enhanced performance of the CSPO-VMS technique,a wide range of simulations were carried out and the results are examined under varying aspects.The simulation results ensured the improved performance of the CSPO-VMS technique over the recent methods interms of different measures.

High Linear Voltage Gain in QZNC Through Synchronizing Switching Circuits

The solar powered systems require high step-up converter for efficient energy transfer.For this,quasi-impedance network converter has been introduced.The quasi-impedance network converter(QZNC)is of two types:type-1 and type-2 configuration.Both the type-1 and type-2 QZNC configurations have drooping voltage gain profile due to presence of high switching noise.To overcome this,a new quasi-impedance network converter synchronizing the switching circuit with low frequency noise has been proposed.In this paper,the proposed QZNC con-figuration utilizes the current controlling diode to prevent the output voltage drop.Thus,the suggested topology provides linear high voltage gain profile,low load voltage ripple,and reduced impedance network stress and device stress.There-fore,the efficiency of proposed QZNC has been improved.The topology descrip-tion,working principle,parameter design and comparison with traditional converters are illustrated.Andfinally,both simulation and practical results are presented to confirm the converter characteristics and performance.From the results,it has been found that the performance of the suggested topology is better as it achieves a higher efficiency of 81%and hence,it is suitable for high power applications.

Genetic-Chicken Swarm Algorithm for Minimizing Energy in Wireless Sensor Network

Wireless Sensor Network(WSN)technology is the real-time applica-tion that is growing rapidly as the result of smart environments.Battery power is one of the most significant resources in WSN.For enhancing a power factor,the clustering techniques are used.During the forward of data in WSN,more power is consumed.In the existing system,it works with Load Balanced Cluster-ing Method(LBCM)and provides the lifespan of the network with scalability and reliability.In the existing system,it does not deal with end-to-end delay and deliv-ery of packets.For overcoming these issues in WSN,the proposed Genetic Algo-rithm based on Chicken Swarm Optimization(GA-CSO)with Load Balanced Clustering Method(LBCM)is used.Genetic Algorithm generates chromosomes in an arbitrary method then the chromosomes values are calculated using Fitness Function.Chicken Swarm Optimization(CSO)helps to solve the complex opti-mization problems.Also,it consists of chickens,hens,and rooster.It divides the chicken into clusters.Load Balanced Clustering Method(LBCM)maintains the energy during communication among the sensor nodes and also it balances the load in the gateways.The proposed GA-CSO with LBCM improves the life-span of the network.Moreover,it minimizes the energy consumption and also bal-ances the load over the network.The proposed method outperforms by using the following metrics such as energy efficiency,ratio of packet delivery,throughput of the network,lifetime of the sensor nodes.Therefore,the evaluation result shows the energy efficiency that has achieved 83.56%and the delivery ratio of the packet has reached 99.12%.Also,it has attained linear standard deviation and reduced the end-to-end delay as 97.32 ms.

Hybrid Optimisation with Black Hole Algorithm for Improving Network Lifespan

Wireless sensor networks(WSNs)are projected to have a wide range of applications in the future.The fundamental problem with WSN is that it has afinite lifespan.Clustering a network is a common strategy for increasing the life-time of WSNs and,as a result,allowing for faster data transmission.The cluster-ing algorithm’s goal is to select the best cluster head(CH).In the existing system,Hybrid grey wolf sunflower optimization algorithm(HGWSFO)and optimal clus-ter head selection method is used.It does not provide better competence and out-put in the network.Therefore,the proposed Hybrid Grey Wolf Ant Colony Optimisation(HGWACO)algorithm is used for reducing the energy utilization and enhances the lifespan of the network.Black hole method is used for selecting the cluster heads(CHs).The ant colony optimization(ACO)technique is used tofind the route among origin CH and destination.The open cache of nodes,trans-mission power,and proximity are used to improve the CH selection.The grey wolf optimisation(GWO)technique is the most recent and well-known optimiser module which deals with grey wolves’hunting activity(GWs).These GWs have the ability to track down and encircle food.The GWO method was inspired by this hunting habit.The proposed HGWACO improves the duration of the net-work,minimizes the power consumption,also it works with the large-scale net-works.The HGWACO method achieves 25.64%of residual energy,25.64%of alive nodes,40.65%of dead nodes also it enhances the lifetime of the network.

Modeling and Control of Parallel Hybrid Electric Vehicle Using Sea-Lion Optimization

This paper develops a parallel hybrid electric vehicle(PHEV)propor-tional integral controller with driving cycle.To improve fuel efficiency and reduce hazardous emissions in hybrid electric vehicles(HEVs)combine an electric motor(EM),a battery and an internal combustion engine(ICE).The electric motor assists the engine when accelerating,driving longer highways or climbing hills.This enables the use of a smaller,more efficient engine.It also makes use of the concept of regenerative braking to maximize energy efficiency.In a Hybrid Electric Vehicle(HEV),energy dissipated while braking is utilized to charge the battery.The proportional integral controller was used in this paper to analyze engine,motor performance and the New European Driving Cycle(NEDC)was used in the vehicle driving test using Matlab/Simulink.The proportional integral controllers were designed to track the desired vehicle speed and manage the vehi-cle’s energyflow.The Sea Lion Optimization(SLnO)methods were created to reduce fuel consumption in a parallel hybrid electric vehicle and the results were obtained for the New European Driving Cycle.

微重力下气液分离特性的数值模拟

微重力下离心式气液分离技术以分离环境不受重力条件的影响而广泛应用于航天器流体技术、环境控制与生命保障系统等领域.本文对微重力工况下离心式气液分离特性进行了数值模拟研究,通过正交实验法分析在转速、入口速度、含气量、黏度、温度综合作用时,各因素影响的主次关系.结果表明,转速、含气量、温度、黏度对分离效率的影响比较明显,且随转速、含气量、温度的增加,分离效率逐渐增加,而随黏度的增加分离效率逐渐降低,入口速度对分离效率的影响较小,这与美国地面实验的趋势大致相同,分离效率在92％～94％范围内.研究结果可为我国空间站环控生保技术采用蒸汽压缩蒸馏方法进行尿液分离的进一步研究提供基础数据.

支管方向对T形管气液分离效果影响的数值模拟分析

应用计算流体动力学方法对T形管气、液分离器进行了数值模拟,采用标准k-ε模型为湍流计算模型,针对不同支管放置方向对T形管气、液分离效果的影响进行了模拟分析。分析表明,支管水平放置和竖直向上放置时支管均以气相采出占优;支管竖直向下放置时,分流率为临界值时气液两相均匀分流;支管竖直向上放置时,质量分离效率最高。

基于柱效指数监测的双波长定量比率指纹图谱评价朱砂安神丸

目的建立色谱指纹图谱柱效指数模型,用以检测定量指纹图谱的变化。方法用高效液相色谱二极管阵列检测器同时测定12批朱砂安神丸(ZSASP)在203 nm和286 nm指纹谱(NFP)和比率指纹图谱(ROFP),分别以均值法整合同波长下指纹图谱,最后进行双波长指纹图谱的二次均值整合,计算双波长指纹图谱柱效指数并进行比较。结果以小檗碱(BBR)为参照物峰,确定57(203 nm)和50(286 nm)个共有指纹峰,建立了双波长ZSASP-HPLC指纹图谱和比率指纹图谱。首先将同波长下的NFP和ROFP进行均值整合,之后进行双波长二次均值整合鉴定出S1、S4、S5、S6、S9和S10质量极好(1级),S2、S3、S11和S12质量很好(2级),S7和S8质量次(7级)。在203 nm,S4、S5、S6、S9柱效指数较高,而在286 nm下四者柱效指数较低造成两者差值很大,S8呈现上述反变化过程造成较大差异值。结论色谱指纹图谱柱效指数能监测中药定量指纹图谱的柱效关联分离度后的变化情况,因此柱效指数标志着信号均化性和分离度均化性以及峰宽变动情况。

共吸附剂对染料敏化太阳能电池光伏性能的影响

利用市售联吡啶钌染料TG6为敏化剂制备染料敏化太阳能电池,引入鹅去氧胆酸(CDCA)为共吸附剂优化电池的光伏性能。实验结果表明,当TG6浓度为0.3 mmol/L,共吸附剂CDCA浓度为10 mmol/L时,以TG6敏化的太阳能电池的光电转换效率为4.64%,比未优化的同类电池提高了23%。电化学阻抗分析表明CDCA的引入,使染料/二氧化钛/电解液界面的回传电阻提升了近50%,有效提升了光生电子寿命,实现了抑制光生电子复合的目的。

固体轻分散相旋流分离的研究

通过试验研究了固体轻分散相和液体介质旋流分离的操作性能和分离性能,结果表明:固体轻分散分离用旋流器的压力降随入口流量增加而变大;溢流分率随压降比的增大而增大;分离效率随底流管长度的增加基本不变;分离效率随入口流量的增加而增大,并趋近某个<100%的值;分离效率随着分流比的变大先变大,到达一个最大值之后又变小。

LWZ1200×1800A型沉降过滤式离心脱水机在济三选煤厂的应用

阐述了LWZ1200×1800A型沉降过滤式离心脱水机在济三选煤厂的应用情况,并介绍了该离心机的结构、工作原理、特点及技术参数。生产实践表明:LWZ1200×1800A型沉降过滤式离心脱水机脱水效果好、运行故障少、性能稳定,完全满足选煤厂对煤泥回收的需求。