The coupling control of biological precursors and environmental factors onβ-carotane enrichment in alkaline lacustrine source rocks:A case study from the Fengcheng formation in the western Junggar Basin,NW China

The organic-rich mudstones and dolostones of the Permian Fengcheng Formation(Fm.)are typically alkaline lacustrine source rocks,which are typified by impressively abundantβ-carotane.Abundant β-carotane has been well acknowledged as an effective indicator of biological sources or depositional environments.However,the specific biological sources of β-carotane and the coupling control of biological sources and environmental factors on the enrichment of β-carotane in the Fengcheng Fm.remains obscure.Based on a comprehensive investigation of the bulk,molecular geochemistry,and organic petrology of sedimentary rocks and the biochemistry of phytoplankton in modern alkaline lakes,we proposed a new understanding of the biological precursors of β-carotane and elucidated the enrichment mechanism of β-carotane in the Fengcheng Fm.The results show that the biological precursors crucially control the enrichment of β-carotane in the Fengcheng Fm.The haloalkaliphilic cyanobacteria are the primary biological sources of β-carotane,which is suggested by a good positive correlation between the 2-methylhopane index,7-+8-methyl heptadecanes/C_(max),C_(29%),and β-carotane/C_(max)in sedimentary rocks and the predominance of cyanobacteria with abundantβ-carotene in modern alkaline lakes.The enrichment of β-carotane requires the reducing condition,and the paleoredox state that affects the enrichment of β-carotane appears to have a threshold.The paleoclimate conditions do not considerably impact the enrichment of β-carotane,but they have some influence on the water's paleosalinity by affecting evaporation and precipitation.While it does not directly affect the enrichment of β-carotane in the Fengcheng Fm.,paleosalinity does have an impact on the cyanobacterial precursor supply and the preservation conditions.

Analysis of the Impact of Big Data Technology on Environmental Pollution Control Audit

As China strives towards the second centenary goal,increasing attention is being paid to environmental pollution and other related issues.Concurrently,with the rapid development of big data technology,many big data solutions have been applied to environmental pollution control audits,exerting a significant impact.This paper presents the current situation of environmental pollution audits,summarizing the application of big data from the perspectives of both domestic and international research.In terms of data collection and data analysis for environmental pollution audits,cloud platform technology,and visualization technology are selected based on multiple data sources.The impact in the field of environmental pollution control audits is further analyzed.It is found that the environmental pollution audit cloud platform is not yet perfect,the technical skills of audit personnel are insufficient,and some technologies are not mature.Relevant suggestions are put forward to provide a reference for the future development of big data technology and its integration with environmental pollution control audits.

Recent Progress in Reinforcement Learning and Adaptive Dynamic Programming for Advanced Control Applications

Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and its applications to various advanced control fields. First, the background of the development of ADP is described, emphasizing the significance of regulation and tracking control problems. Some effective offline and online algorithms for ADP/adaptive critic control are displayed, where the main results towards discrete-time systems and continuous-time systems are surveyed, respectively.Then, the research progress on adaptive critic control based on the event-triggered framework and under uncertain environment is discussed, respectively, where event-based design, robust stabilization, and game design are reviewed. Moreover, the extensions of ADP for addressing control problems under complex environment attract enormous attention. The ADP architecture is revisited under the perspective of data-driven and RL frameworks,showing how they promote ADP formulation significantly.Finally, several typical control applications with respect to RL and ADP are summarized, particularly in the fields of wastewater treatment processes and power systems, followed by some general prospects for future research. Overall, the comprehensive survey on ADP and RL for advanced control applications has d emonstrated its remarkable potential within the artificial intelligence era. In addition, it also plays a vital role in promoting environmental protection and industrial intelligence.

The impact of demographic dynamics on food consumption and its environmental outcomes:Evidence from China

With increasing population and changing demographics,food consumption has experienced a significant transition in quantity and quality.However,a dearth of knowledge remains regarding its environmental impacts and how it responds to demographic dynamics,particularly in emerging economies like China.Using the two-stage Quadratic Almost Demand System(QUAIDS)model,this study empirically examines the impact of demographic dynamics on food consumption and its environmental outcomes based on the provincial data from 2000 to 2020 in China.Under various scenarios,according to changes in demographics,we extend our analysis to project the long-term trend of food consumption and its environmental impacts,including greenhouse gas(GHG)emissions,water footprint(WF),and land appropriation(LA).The results reveal that an increase in the proportion of senior people significantly decreases the consumption of grain and livestock meat and increases the consumption of poultry,egg,and aquatic products,particularly for urban residents.Moreover,an increase in the proportion of males in the population leads to higher consumption of poultry and aquatic products.Correspondingly,in the current scenario of an increased aging population and sex ratio,it is anticipated that GHG emissions,WF,and LA are likely to decrease by 1.37,2.52,and 3.56%,respectively.More importantly,in the scenario adhering to the standards of nutritional intake according to the Dietary Guidelines for Chinese Residents in 2022,GHG emissions,WF,and LA in urban areas would increase by 12.78,20.94,and 18.32%,respectively.Our findings suggest that changing demographics should be considered when designing policies to mitigate the diet-environment-health trilemma and achieve sustainable food consumption.

Vibration Control of A Flexible Marine Riser System Subject to Input Dead Zone and Extraneous Disturbances

An observer-based adaptive backstepping boundary control is proposed for vibration control of flexible offshore riser systems with unknown nonlinear input dead zone and uncertain environmental disturbances.The control algorithm can update the control law online through real-time data to make the controller adapt to the environment and improve the control precision.Specifically,based on the adaptive backstepping framework,virtual control laws and Lyapunov functions are designed for each subsystem.Three direction interference observers are designed to track the timevarying boundary disturbance.On this basis,the inverse of the dead zone and linear state transformation are used to compensate for the original system and eliminate the adverse effects of the dead zone.In addition,the stability of the closed-loop system is proven by Lyapunov stability theory.All the system states are bounded,and the vibration offset of the riser converges to a small area of the initial position.Finally,four examples of flexible marine risers are simulated in MATLAB to verify the effectiveness of the proposed controller.

Control of highly pathogenic avian influenza through vaccination

The stamping-out strategy has been used to control highly pathogenic avian influenza viruses in many countries,driven by the belief that vaccination would not be successful against such viruses and fears that avian influenza virus in vaccinated birds would evolve more rapidly and pose a greater risk to humans.In this review,we summarize the successes in controlling highly pathogenic avian influenza in China and make suggestions regarding the requirements for vaccine selection and effectiveness.In addition,we present evidence that vaccination of poultry not only eliminates human infection with avian influenza virus,but also significantly reduces and abolishes some harmful characteristics of avian influenza virus.

A Blockchain-Based Access Control Scheme for Reputation Value Attributes of the Internet of Things

The Internet of Things(IoT)access controlmechanism may encounter security issues such as single point of failure and data tampering.To address these issues,a blockchain-based IoT reputation value attribute access control scheme is proposed.Firstly,writing the reputation value as an attribute into the access control policy,and then deploying the access control policy in the smart contract of the blockchain system can enable the system to provide more fine-grained access control;Secondly,storing a large amount of resources fromthe Internet of Things in Inter Planetary File System(IPFS)to improve system throughput;Finally,map resource access operations to qualification tokens to improve the performance of the access control system.Complete simulation experiments based on the Hyperledger Fabric platform.Fromthe simulation experimental results,it can be seen that the access control system can achieve more fine-grained and dynamic access control while maintaining high throughput and low time delay,providing sufficient reliability and security for access control of IoT devices.

Mitochondrial dysfunction and quality control lie at the heart of subarachnoid hemorrhage

The dramatic increase in intracranial pressure after subarachnoid hemorrhage leads to a decrease in cerebral perfusion pressure and a reduction in cerebral blood flow.Mitochondria are directly affected by direct factors such as ischemia,hypoxia,excitotoxicity,and toxicity of free hemoglobin and its degradation products,which trigger mitochondrial dysfunction.Dysfunctional mitochondria release large amounts of reactive oxygen species,inflammatory mediators,and apoptotic proteins that activate apoptotic pathways,further damaging cells.In response to this array of damage,cells have adopted multiple mitochondrial quality control mechanisms through evolution,including mitochondrial protein quality control,mitochondrial dynamics,mitophagy,mitochondrial biogenesis,and intercellular mitochondrial transfer,to maintain mitochondrial homeostasis under pathological conditions.Specific interventions targeting mitochondrial quality control mechanisms have emerged as promising therapeutic strategies for subarachnoid hemorrhage.This review provides an overview of recent research advances in mitochondrial pathophysiological processes after subarachnoid hemorrhage,particularly mitochondrial quality control mechanisms.It also presents potential therapeutic strategies to target mitochondrial quality control in subarachnoid hemorrhage.

A Review on Vibration Control of Multiple Cylinders Subjected to FlowInduced Vibrations

The fatigue damage caused by flow-induced vibration(FIV)is one of the major concerns for multiple cylindrical structures in many engineering applications.The FIV suppression is of great importance for the security of many cylindrical structures.Many active and passive control methods have been employed for the vibration suppression of an isolated cylinder undergoing vortex-induced vibrations(VIV).The FIV suppression methods are mainly extended to the multiple cylinders from the vibration control of the isolated cylinder.Due to the mutual interference between the multiple cylinders,the FIV mechanism is more complex than the VIV mechanism,which makes a great challenge for the FIV suppression.Some efforts have been devoted to vibration suppression of multiple cylinder systems undergoing FIV over the past two decades.The control methods,such as helical strakes,splitter plates,control rods and flexible sheets,are not always effective,depending on many influence factors,such as the spacing ratio,the arrangement geometrical shape,the flow velocity and the parameters of the vibration control devices.The FIV response,hydrodynamic features and wake patterns of the multiple cylinders equipped with vibration control devices are reviewed and summarized.The FIV suppression efficiency of the vibration control methods are analyzed and compared considering different influence factors.Further research on the FIV suppression of multiple cylinders is suggested to provide insight for the development of FIV control methods and promote engineering applications of FIV control methods.

Compositional and Hollow Engineering of Silicon Carbide/Carbon Microspheres as High-Performance Microwave Absorbing Materials with Good Environmental Tolerance

Microwave absorbing materials(MAMs)characterized by high absorption efficiency and good environmental tolerance are highly desirable in practical applications.Both silicon carbide and carbon are considered as stable MAMs under some rigorous conditions,while their composites still fail to produce satisfactory microwave absorption performance regardless of the improvements as compared with the individuals.Herein,we have successfully implemented compositional and structural engineering to fabricate hollow Si C/C microspheres with controllable composition.The simultaneous modulation on dielectric properties and impedance matching can be easily achieved as the change in the composition of these composites.The formation of hollow structure not only favors lightweight feature,but also generates considerable contribution to microwave attenuation capacity.With the synergistic effect of composition and structure,the optimized SiC/C composite exhibits excellent performance,whose the strongest reflection loss intensity and broadest effective absorption reach-60.8 dB and 5.1 GHz,respectively,and its microwave absorption properties are actually superior to those of most SiC/C composites in previous studies.In addition,the stability tests of microwave absorption capacity after exposure to harsh conditions and Radar Cross Section simulation data demonstrate that hollow SiC/C microspheres from compositional and structural optimization have a bright prospect in practical applications.

A 16-bit 18-MSPS flash-assisted SAR ADC with hybrid synchronous and asynchronous control logic

This paper presents a 16-bit,18-MSPS(million samples per second)flash-assisted successive-approximation-register(SAR)analog-to-digital converter(ADC)utilizing hybrid synchronous and asynchronous(HYSAS)timing control logic based on an on-chip delay-locked loop(DLL).The HYSAS scheme can provide a longer settling time for the capacitive digital-to-analog converter(CDAC)than the synchronous and asynchronous SAR ADC.Therefore,the issue of incomplete settling or ringing in the DAC voltage for cases of either on-chip or off-chip reference voltage can be solved to a large extent.In addition,the fore-ground calibration of the CDAC’s mismatch is performed with a finite-impulse-response bandpass filter(FIR-BPF)based least-mean-square(LMS)algorithm in an off-chip FPGA(field programmable gate array).Fabricated in 40-nm CMOS process,the proto-type ADC achieves 94.02-dB spurious-free dynamic range(SFDR),and 75.98-dB signal-to-noise-and-distortion ratio(SNDR)for a 2.88-MHz input under 18-MSPS sampling rate.

The Impact of Satellite Communications on Environmental Hazard Control: Tool for the Realization of African Union Agenda 2063 Aspirations

Africa is a developing economy and as such, emphasis has been placed on the achievement of revolutionary goals that will place her on a similar rank as the developed economies. Pertaining to this objective, Heads of States and government all over Africa instigated the African Union (AU) Agenda 2063, which is a framework put in place to achieve a continental transformation over the next 40 years. The use of satellites has been proven to be a major influence on economic growth since it facilitates the exchange of information. Environmental hazards such as climate changes, pollution, and inefficient waste management can be classified as one of the drawbacks to achieving this economic growth we hope to accomplish. The purpose of this paper is to analyze and examine satellite communication as a tool for the attainment of an integrated, prosperous and peaceful Africa by means of combatting environmental hazards in the continent.

Communication Resource-Efficient Vehicle Platooning Control With Various Spacing Policies

Platooning represents one of the key features that connected automated vehicles may possess as it allows multiple automated vehicles to be maneuvered cooperatively with small headways on roads. However, a critical challenge in accomplishing automated vehicle platoons is to deal with the effects of intermittent and sporadic vehicle-to-vehicle data transmissions caused by limited wireless communication resources. This paper addresses the co-design problem of dynamic event-triggered communication scheduling and cooperative adaptive cruise control for a convoy of automated vehicles with diverse spacing policies. The central aim is to achieve automated vehicle platooning under various gap references with desired platoon stability and spacing performance requirements, while simultaneously improving communication efficiency. Toward this aim, a dynamic event-triggered scheduling mechanism is developed such that the intervehicle data transmissions are scheduled dynamically and efficiently over time. Then, a tractable co-design criterion on the existence of both the admissible event-driven cooperative adaptive cruise control law and the desired scheduling mechanism is derived. Finally, comparative simulation results are presented to substantiate the effectiveness and merits of the obtained results.

Path Planning and Tracking Control for Parking via Soft Actor-Critic Under Non-Ideal Scenarios

Parking in a small parking lot within limited space poses a difficult task. It often leads to deviations between the final parking posture and the target posture. These deviations can lead to partial occupancy of adjacent parking lots, which poses a safety threat to vehicles parked in these parking lots. However, previous studies have not addressed this issue. In this paper, we aim to evaluate the impact of parking deviation of existing vehicles next to the target parking lot(PDEVNTPL) on the automatic ego vehicle(AEV) parking, in terms of safety, comfort, accuracy, and efficiency of parking. A segmented parking training framework(SPTF) based on soft actor-critic(SAC) is proposed to improve parking performance. In the proposed method, the SAC algorithm incorporates strategy entropy into the objective function, to enable the AEV to learn parking strategies based on a more comprehensive understanding of the environment. Additionally, the SPTF simplifies complex parking tasks to maintain the high performance of deep reinforcement learning(DRL). The experimental results reveal that the PDEVNTPL has a detrimental influence on the AEV parking in terms of safety, accuracy, and comfort, leading to reductions of more than 27%, 54%, and 26%respectively. However, the SAC-based SPTF effectively mitigates this impact, resulting in a considerable increase in the parking success rate from 71% to 93%. Furthermore, the heading angle deviation is significantly reduced from 2.25 degrees to 0.43degrees.

Interplay between microglia and environmental risk factors in Alzheimer's disease

Alzheimer s disease,among the most common neurodegenerative disorders,is chara cterized by progressive cognitive impairment.At present,the Alzheimer’s disease main risk remains genetic ris ks,but major environmental fa ctors are increasingly shown to impact Alzheimer’s disease development and progression.Microglia,the most important brain immune cells,play a central role in Alzheimer’s disease pathogenesis and are considered environmental and lifestyle"sensors."Factors like environmental pollution and modern lifestyles(e.g.,chronic stress,poor dietary habits,sleep,and circadian rhythm disorde rs)can cause neuroinflammato ry responses that lead to cognitive impairment via microglial functioning and phenotypic regulation.However,the specific mechanisms underlying interactions among these facto rs and microglia in Alzheimer’s disease are unclear.Herein,we:discuss the biological effects of air pollution,chronic stress,gut micro biota,sleep patterns,physical exercise,cigarette smoking,and caffeine consumption on microglia;consider how unhealthy lifestyle factors influence individual susceptibility to Alzheimer’s disease;and present the neuroprotective effects of a healthy lifestyle.Toward intervening and controlling these environmental risk fa ctors at an early Alzheimer’s disease stage,understanding the role of microglia in Alzheimer’s disease development,and to rgeting strategies to to rget microglia,co uld be essential to future Alzheimer’s disease treatments.

Contract Mechanism of Water Environment Regulation for Small and Medium Sized Enterprises Based on Optimal Control Theory

The small and scattered enterprise pattern in the county economy has formed numerous sporadic pollution sources, hindering the centralized treatment of the water environment, increasing the cost and difficulty of treatment. How enterprises can make reasonable decisions on their water environment behavior based on the external environment and their own factors is of great significance for scientifically and effectively designing water environment regulation mechanisms. Based on optimal control theory, this study investigates the design of contractual mechanisms for water environmental regulation for small and medium-sized enterprises. The enterprise is regarded as an independent economic entity that can adopt optimal control strategies to maximize its own interests. Based on the participation of multiple subjects including the government, enterprises, and the public, an optimal control strategy model for enterprises under contractual water environmental regulation is constructed using optimal control theory, and a method for calculating the amount of unit pollutant penalties is derived. The water pollutant treatment cost data of a paper company is selected to conduct empirical numerical analysis on the model. The results show that the increase in the probability of government regulation and public participation, as well as the decrease in local government protection for enterprises, can achieve the same regulatory effect while reducing the number of administrative penalties per unit. Finally, the implementation process of contractual water environmental regulation for small and medium-sized enterprises is designed.

A Tutorial on Quantized Feedback Control

In this tutorial paper, we explore the field of quantized feedback control, which has gained significant attention due to the growing prevalence of networked control systems. These systems require the transmission of feedback information, such as measurements and control signals, over digital networks, presenting novel challenges in estimation and control design. Our examination encompasses various topics, including the minimal information needed for effective feedback control, the design of quantizers, strategies for quantized control design and estimation,achieving consensus control with quantized data, and the pursuit of high-precision tracking using quantized measurements.

Risk-Informed Model-Free Safe Control of Linear Parameter-Varying Systems

This paper presents a risk-informed data-driven safe control design approach for a class of stochastic uncertain nonlinear discrete-time systems.The nonlinear system is modeled using linear parameter-varying(LPV)systems.A model-based probabilistic safe controller is first designed to guarantee probabilisticλ-contractivity(i.e.,stability and invariance)of the LPV system with respect to a given polyhedral safe set.To obviate the requirement of knowing the LPV system model and to bypass identifying its open-loop model,its closed-loop data-based representation is provided in terms of state and scheduling data as well as a decision variable.It is shown that the variance of the closedloop system,as well as the probability of safety satisfaction,depends on the decision variable and the noise covariance.A minimum-variance direct data-driven gain-scheduling safe control design approach is presented next by designing the decision variable such that all possible closed-loop system realizations satisfy safety with the highest confidence level.This minimum-variance approach is a control-oriented learning method since it minimizes the variance of the state of the closed-loop system with respect to the safe set,and thus minimizes the risk of safety violation.Unlike the certainty-equivalent approach that results in a risk-neutral control design,the minimum-variance method leads to a risk-averse control design.It is shown that the presented direct risk-averse learning approach requires weaker data richness conditions than existing indirect learning methods based on system identification and can lead to a lower risk of safety violation.Two simulation examples along with an experimental validation on an autonomous vehicle are provided to show the effectiveness of the presented approach.

Finite-time Prescribed Performance Time-Varying Formation Control for Second-Order Multi-Agent Systems With Non-Strict Feedback Based on a Neural Network Observer

This paper studies the problem of time-varying formation control with finite-time prescribed performance for nonstrict feedback second-order multi-agent systems with unmeasured states and unknown nonlinearities.To eliminate nonlinearities,neural networks are applied to approximate the inherent dynamics of the system.In addition,due to the limitations of the actual working conditions,each follower agent can only obtain the locally measurable partial state information of the leader agent.To address this problem,a neural network state observer based on the leader state information is designed.Then,a finite-time prescribed performance adaptive output feedback control strategy is proposed by restricting the sliding mode surface to a prescribed region,which ensures that the closed-loop system has practical finite-time stability and that formation errors of the multi-agent systems converge to the prescribed performance bound in finite time.Finally,a numerical simulation is provided to demonstrate the practicality and effectiveness of the developed algorithm.

Quantization and Event-Triggered Policy Design for Encrypted Networked Control

This paper proposes a novel event-driven encrypted control framework for linear networked control systems(NCSs),which relies on two modified uniform quantization policies,the Paillier cryptosystem,and an event-triggered strategy.Due to the fact that only integers can work in the Pailler cryptosystem,both the real-valued control gain and system state need to be first quantized before encryption.This is dramatically different from the existing quantized control methods,where only the quantization of a single value,e.g.,the control input or the system state,is considered.To handle this issue,static and dynamic quantization policies are presented,which achieve the desired integer conversions and guarantee asymptotic convergence of the quantized system state to the equilibrium.Then,the quantized system state is encrypted and sent to the controller when the triggering condition,specified by a state-based event-triggered strategy,is satisfied.By doing so,not only the security and confidentiality of data transmitted over the communication network are protected,but also the ciphertext expansion phenomenon can be relieved.Additionally,by tactfully designing the quantization sensitivities and triggering error,the proposed event-driven encrypted control framework ensures the asymptotic stability of the overall closedloop system.Finally,a simulation example of the secure motion control for an inverted pendulum cart system is presented to evaluate the effectiveness of the theoretical results.