A crosstalk-free dual-mode sweat sensing system for naked-eye sweat loss quantification via changes in structural reflectance

Sweat loss monitoring is important for understanding the body’s thermoregulation and hydration status,as well as for comprehensive sweat analysis.Despite recent advances,developing a low-cost,scalable,and universal method for the fabrication of colorimetric microfluidics designed for sweat loss monitoring remains challenging.In this study,we propose a novel laserengraved surface roughening strategy for various flexible substrates.This process permits the construction of microchannels that show distinct structural reflectance changes before and after sweat filling.By leveraging these unique optical properties,we have developed a fully laser-engraved microfluidic device for the quantification of naked-eye sweat loss.This sweat loss sensor is capable of a volume resolution of 0.5µL and a total volume capacity of 11µL,and can be customized to meet different performance requirements.Moreover,we report the development of a crosstalk-free dual-mode sweat microfluidic system that integrates an Ag/AgCl chloride sensor and a matching wireless measurement flexible printed circuit board.This integrated system enables the real-time monitoring of colorimetric sweat loss signals and potential ion concentration signals without crosstalk.Finally,we demonstrate the potential practical use of this microfluidic sweat loss sensor and its integrated system for sports medicine via on-body studies.

One stone two birds:electrochemical and colorimetric dual-mode biosensor based on copper peroxide/covalent organic framework nanocomposite for ultrasensentive norovirus detection

Norovirus(NoV)is regarded as one of the most common causes of foodborne diarrhea in the world.It is urgent to identify the pathogenic microorganism of the diarrhea in short time.In this work,we developed an electrochemical and colorimetric dual-mode detection for NoV based on the excellent dual catalytic properties of copper peroxide/COF-NH_(2)nanocomposite(CuO_(2)@COF-NH_(2)).For the colorimetric detection,NoV can be directly detected by the naked eye based on CuO_(2)@COF-NH_(2)as a laccase-like nonazyme using“peptide-NoV-antibody”recognition mode.The colorimetric assay displayed a wide and quality linear detection range from 1 copy/mL to 5000 copies/mL of NoV with a low limit of detection(LOD)of 0.125 copy/mL.For the electrochemical detection of NoV,CuO_(2)@COF-NH_(2)showed an oxidation peak of copper ion from Cu^(+)to Cu^(2+)using“peptide-NoV-antibody”recognition mode.The electrochemical assay showed a linear detection range was 1-5000 copies/mL with a LOD of 0.152 copy/mL.It's worthy to note that this assay does not need other electrical signal molecule,which provide the stable and sensitive electrochemial detection for NoV.The electrochemical and colorimetric dual-mode detection was used to detect NoV in foods and faceal samples,which has the potential for improving food safety and diagnosing of NoV-infected diarrhea.

CF-BFT:A Dual-Mode Byzantine Fault-Tolerant Protocol Based on Node Authentication

The consensus protocol is one of the core technologies in blockchain,which plays a crucial role in ensuring the block generation rate,consistency,and safety of the blockchain system.Blockchain systems mainly adopt the Byzantine Fault Tolerance(BFT)protocol,which often suffers fromslow consensus speed and high communication consumption to prevent Byzantine nodes from disrupting the consensus.In this paper,this paper proposes a new dual-mode consensus protocol based on node identity authentication.It divides the consensus process into two subprotocols:Check_BFT and Fast_BFT.In Check_BFT,the replicas authenticate the primary’s identity by monitoring its behaviors.First,assume that the systemis in a pessimistic environment,Check_BFT protocol detects whether the current environment is safe and whether the primary is an honest node;Enter the fast consensus stage after confirming the environmental safety,and implement Fast_BFT protocol.It is assumed that there are 3f+1 nodes in total.If more than 2f+1 nodes identify that the primary is honest,it will enter the Fast_BFT process.In Fast_BFT,the primary is allowed to handle transactions alone,and the replicas can only receive the messages sent by the primary.The experimental results show that the CF-BFT protocol significantly reduces the communication overhead and improves the throughput and scalability of the consensus protocol.Compared with the SAZyzz protocol,the throughput is increased by 3 times in the best case and 60%in the worst case.

On Dual-Mode Driving Control Method for a Novel Unmanned Tractor With High Safety and Reliability

Due to the non-standardization and complexity of the farmland environment,it is always a huge challenge for tractors to achieve fully autonomy(work at Self-driving mode)all the time in agricultural industry.Whereas,when tractors work in the Tele-driving(or Remote driving)mode,the operators are prone to fatigue because they need to concentrate for long periods of time.In response to these,a dual-mode control strategy was proposed to integrate the advantages of both approaches,i.e.,by combing Self-driving at most of the time with Tele-driving under special(complex and hazardous)conditions through switching control method.First,the state switcher was proposed,which is used for smooth switching the driving modes according to different working states of a tractor.Then,the state switching control law and the corresponding subsystem tracking controllers were designed.Finally,the effectiveness and superiority of the dualmode control method were evaluated via actual experimental testing of a tractor whose results show that the proposed control method can switch smoothly,stably,and efficiently between the two driving modes automatically.The average control accuracy has been improved by 20%and 15%respectively,compared to the conventional Tele-driving control and Self-driving control with low-precision navigation.In conclusion,the proposed dualmode control method can not only satisfy the operation in the complex and changeable farmland environment,but also free drivers from high-intensity and fatiguing work.This provides a perfect application solution and theoretical support for the intelligentization of unmanned farm agricultural machinery with high safety and reliability.

Collaborative positioning for swarms:A brief survey of vision,LiDAR and wireless sensors based methods

As positioning sensors,edge computation power,and communication technologies continue to develop,a moving agent can now sense its surroundings and communicate with other agents.By receiving spatial information from both its environment and other agents,an agent can use various methods and sensor types to localize itself.With its high flexibility and robustness,collaborative positioning has become a widely used method in both military and civilian applications.This paper introduces the basic fundamental concepts and applications of collaborative positioning,and reviews recent progress in the field based on camera,LiDAR(Light Detection and Ranging),wireless sensor,and their integration.The paper compares the current methods with respect to their sensor type,summarizes their main paradigms,and analyzes their evaluation experiments.Finally,the paper discusses the main challenges and open issues that require further research.

Rao Algorithms-Based Structure Optimization for Heterogeneous Wireless Sensor Networks

The structural optimization of wireless sensor networks is a critical issue because it impacts energy consumption and hence the network’s lifetime.Many studies have been conducted for homogeneous networks,but few have been performed for heterogeneouswireless sensor networks.This paper utilizes Rao algorithms to optimize the structure of heterogeneous wireless sensor networks according to node locations and their initial energies.The proposed algorithms lack algorithm-specific parameters and metaphorical connotations.The proposed algorithms examine the search space based on the relations of the population with the best,worst,and randomly assigned solutions.The proposed algorithms can be evaluated using any routing protocol,however,we have chosen the well-known routing protocols in the literature:Low Energy Adaptive Clustering Hierarchy(LEACH),Power-Efficient Gathering in Sensor Information Systems(PEAGSIS),Partitioned-based Energy-efficient LEACH(PE-LEACH),and the Power-Efficient Gathering in Sensor Information Systems Neural Network(PEAGSIS-NN)recent routing protocol.We compare our optimized method with the Jaya,the Particle Swarm Optimization-based Energy Efficient Clustering(PSO-EEC)protocol,and the hybrid Harmony Search Algorithm and PSO(HSA-PSO)algorithms.The efficiencies of our proposed algorithms are evaluated by conducting experiments in terms of the network lifetime(first dead node,half dead nodes,and last dead node),energy consumption,packets to cluster head,and packets to the base station.The experimental results were compared with those obtained using the Jaya optimization algorithm.The proposed algorithms exhibited the best performance.The proposed approach successfully prolongs the network lifetime by 71% for the PEAGSIS protocol,51% for the LEACH protocol,10% for the PE-LEACH protocol,and 73% for the PEGSIS-NN protocol;Moreover,it enhances other criteria such as energy conservation,fitness convergence,packets to cluster head,and packets to the base station.

Ultraconformable Integrated Wireless Charging Micro-Supercapacitor Skin

Conformable and wire-less charging energy storage devices play important roles in enabling the fast development of wearable,non-contact soft electronics.However,current wire-less charging power sources are still restricted by limited flexural angles and fragile connection of components,resulting in the failure expression of performance and constraining their fur-ther applications in health monitoring wearables and moveable artificial limbs.Herein,we present an ultracompatible skin-like integrated wireless charging micro-supercapacitor,which building blocks(including electrolyte,electrode and substrate)are all evaporated by liquid precursor.Owing to the infiltration and permeation of the liquid,each part of the integrated device attached firmly with each other,forming a compact and all-in-one configuration.In addition,benefitting from the controllable volume of electrode solution precursor,the electrode thickness is easily regulated varying from 11.7 to 112.5μm.This prepared thin IWC-MSC skin can fit well with curving human body,and could be wireless charged to store electricity into high capacitive micro-supercapacitors(11.39 F cm-3)of the integrated device.We believe this work will shed light on the construction of skin-attachable electronics and irregular sensing microrobots.

Highly Flexible Graphene-Film-Based Rectenna for Wireless Energy Harvesting

Herein,we report the design,fabrication,and performance of two wireless energy harvesting devices based on highly flexible graphene macroscopic films(FGMFs).We first demonstrate that benefiting from the high conductivity of up to 1×10^(6)S m^(-1)and good resistive stability of FGMFs even under extensive bending,the FGMFs-based rectifying circuit(GRC)exhibits good flexibility and RF-to-DC efficiency of 53%at 2.1 GHz.Moreover,we further expand the application of FGMFs to a flexible wideband monopole rectenna and a 2.45 GHz wearable rectenna for harvesting wireless energy.The wideband rectenna at various bending conditions produces a maximum conversion efficiency of 52%,46%,and 44%at the 5th Generation(5G)2.1 GHz,Industrial Long-Term Evolution(LTE)2.3 GHz,and Scientific Medical(ISM)2.45 GHz,respectively.A 2.45 GHz GRC is optimized and integrated with an AMC-backed wearable antenna.The proposed 2.45 GHz wearable rectenna shows a maximum conversion efficiency of 55.7%.All the results indicate that the highly flexible graphene-film-based rectennas have great potential as a wireless power supplier for smart Internet of Things(loT)applications.

UAV-assisted data collection for wireless sensor networks with dynamic working modes

Wireless Sensor Network(WSN)is a cornerstone of Internet of Things(IoT)and has rich application scenarios.In this work,we consider a heterogeneous WSN whose sensor nodes have a diversity in their Residual Energy(RE).In this work,to protect the sensor nodes with low RE,we investigate dynamic working modes for sensor nodes which are determined by their RE and an introduced energy threshold.Besides,we employ an Unmanned Aerial Vehicle(UAV)to collect the stored data from the heterogeneous WSN.We aim to jointly optimize the cluster head selection,energy threshold and sensor nodes’working mode to minimize the weighted sum of energy con-sumption from the WSN and UAV,subject to the data collection rate constraint.To this end,we propose an efficient search method to search for an optimal energy threshold,and develop a penalty-based successive convex approximation algorithm to select the cluster heads.Then we present a low-complexity iterative approach to solve the joint optimization problem and discuss the implementation procedure.Numerical results justify that our proposed approach is able to reduce the energy consumption of the sensor nodes with low RE significantly and also saves energy for the whole WSN.

Combining Polarization-Division Multiplexing and Ferromagnetic Nonreciprocity to Achieve In-Band Ultra-High Isolation for Full-Duplex Wireless Systems

The in-band full-duplex(IBFD)wireless system is a promising candidate for 6G and beyond,as it can double data throughput and enormously lower transmission latency by supporting simultaneous in-band transmission and reception of signals.Enabling IBFD systems requires a substantial mitigation of a transmitter(Tx)’s strong self-interference(SI)signal into the receiver(Rx)channel.However,current state-ofthe-art approaches to tackle this challenge are inefficient in terms of performance,cost,and complexity,hindering the commercialization of IBFD techniques.In this work,we devise and demonstrate an innovative approach to realize IBFD systems that exhibit superior performance with a low-cost and lesscomplex architecture in an all-passive module.Our scheme is based on meticulously combining polarization-division multiplexing(PDM)with ferromagnetic nonreciprocity to achieve ultra-high isolation between Tx and Rx channels.Such an unprecedented conception has become feasible thanks to a concurrent dual-mode circulator—a new component introduced for the first time—as a key feature of our module,and a dual-mode waveguide that transforms two orthogonally polarized waves into two orthogonal waveguide modes.In addition,we propose a unique passive tunable secondary SI cancellation(SIC)mechanism,which is embedded within the proposed module and boosts the isolation over a relatively broad bandwidth.We report,solely in the analog domain,experimental isolation levels of 50,70,and 80 dB over 340,101,and 33 MHz bandwidth at the center frequency of interest,respectively,with excellent tuning capability.Furthermore,the module is tested in two real IBFD scenarios to assess its performance in connection with Tx-to-Rx leakage and modulation error in the presence of a Tx’s strong interference signal.

Highlights in recent wireless power IC research

Wireless power transfer(WPT)has been a popular topic in power integrated circuit(IC)designs in the past decade.As slogan"cutting the last wire"presented in ISSCC’15[1],WPT is poised to take over many wired power deliveries applica-tions today,just like what happened to wireless communica-tion nowadays.Over the years,WPT has become more mature and more wirelessly charged or powered products have become available on the market.This mini review intends to summarize recent breakthroughs in WPT inte-grated circuits(IC)research.

Intelligent Reflecting Surface Assisted Transmission Optimization Strategies in Wireless Networks

Wireless Power Transfer(WPT)technology can provide real-time power for many terminal devices in Internet of Things(IoT)through millimeterWave(mmWave)to support applications with large capacity and low latency.Although the intelligent reflecting surface(IRS)can be adopted to create effective virtual links to address the mmWave blockage problem,the conventional solutions only adopt IRS in the downlink from the Base Station(BS)to the users to enhance the received signal strength.In practice,the reflection of IRS is also applicable to the uplink to improve the spectral efficiency.It is a challenging to jointly optimize IRS beamforming and system resource allocation for wireless energy acquisition and information transmission.In this paper,we first design a Low-Energy Adaptive Clustering Hierarchy(LEACH)clustering protocol for clustering and data collection.Then,the problem of maximizing the minimum system spectral efficiency is constructed by jointly optimizing the transmit power of sensor devices,the uplink and downlink transmission times,the active beamforming at the BS,and the IRS dynamic beamforming.To solve this non-convex optimization problem,we propose an alternating optimization(AO)-based joint solution algorithm.Simulation results show that the use of IRS dynamic beamforming can significantly improve the spectral efficiency of the system,and ensure the reliability of equipment communication and the sustainability of energy supply under NLOS link.

Jamming Assisted Covert Wireless Communication in Multi-Channel Systems

This paper investigates the jammerassisted multi-channel covert wireless communication(CWC)by exploiting the randomness of sub-channel selection to confuse the warden.In particular,we propose two sub-channel selection transmission schemes,named random sub-channel selection(RSS)scheme and maximum sub-channel selection(MSS)scheme,to enhance communication covertness.For each proposed scheme,we first derive closed-form expressions of the transmission outage probability(TOP),the average effective rate,and the minimum average detection error probability(DEP).Then,the average effective covert rate(ECR)is maximized by jointly optimizing the transmit power at the transmitter and the number of sub-channels.Numerical results show that there is an optimal value of the number of sub-channels that maximizes the average ECR.We also find that to achieve the maximum average ECR,a larger number of subchannels are needed facing a stricter covertness constraint.

A Fuzzy Trust Management Mechanism with Dynamic Behavior Monitoring for Wireless Sensor Networks

Traditional wireless sensor networks(WSNs)are typically deployed in remote and hostile environments for information collection.The wireless communication methods adopted by sensor nodes may make the network highly vulnerable to various attacks.Traditional encryption and authentication mechanisms cannot prevent attacks launched by internal malicious nodes.The trust-based security mechanism is usually adopted to solve this problem in WSNs.However,the behavioral evidence used for trust estimation presents some uncertainties due to the open wireless medium and the inexpensive sensor nodes.Moreover,how to efficiently collect behavioral evidences are rarely discussed.To address these issues,in this paper,we present a trust management mechanism based on fuzzy logic and a cloud model.First,a type-II fuzzy logic system is used to preprocess the behavioral evidences and alleviate uncertainty.Then,the cloud model is introduced to estimate the trust values for sensor nodes.Finally,a dynamic behavior monitoring protocol is proposed to provide a balance between energy conservation and safety assurance.Simulation results demonstrate that our trust management mechanism can effectively protect the network from internal malicious attacks while enhancing the energy efficiency of behavior monitoring.

Comparison of the clinical effects of dual-modality endoscopy and traditional laparotomy for the treatment of intra-and extrahepatic bile duct stones

BACKGROUND Bile duct stones(BDSs)may cause patients to develop liver cirrhosis or even liver cancer.Currently,the success rate of surgical treatment for intrahepatic and extrahepatic BDSs is not satisfactory,and there is a risk of postoperative complic-ations.AIM To compare the clinical effects of dual-modality endoscopy(duodenoscopy and laparoscopy)with those of traditional laparotomy in the treatment of intra-and extrahepatic BDSs.METHODS Ninety-five patients with intra-and extrahepatic BDSs who sought medical services at Wuhan No.1 Hospital between August 2019 and May 2023 were selected;45 patients in the control group were treated by traditional laparotomy,and 50 patients in the research group were treated by dual-modality endoscopy.The following factors were collected for analysis:curative effects,safety(incision infection,biliary fistula,lung infection,hemobilia),surgical factors[surgery time,intraoperative blood loss(IBL)volume,gastrointestinal function recovery time,and length of hospital stay],serum inflammatory markers[tumor necrosis factor(TNF)-α,interleukin(IL)-6,and IL-8],and oxidative stress[glutathione peroxidase(GSH-Px),superoxide dismutase(SOD),malondialdehyde(MDA),and advanced protein oxidation products(AOPPs)].RESULTS The analysis revealed markedly better efficacy(an obviously higher total effective rate)in the research group than in the control group.In addition,an evidently lower postoperative complication rate,shorter surgical duration,gastrointestinal function recovery time and hospital stay,and lower IBL volume were observed in the research group.Furthermore,the posttreatment serum inflammatory marker(TNF-α,IL-6,and IL-8)levels were significantly lower in the research group than in the control group.Compared with those in the control group,the posttreatment GSH-Px,SOD,MDA and AOPPs in the research group were equivalent to the pretreatment levels;for example,the GSH-Px and SOD levels were significantly higher,while the MDA and AOPP levels were lower.CONCLUSION Dual-modality endoscopy therapy(duodenoscopy and laparoscopy)is more effective than traditional laparotomy in the treatment of intra-and extrahepatic BDSs and has a lower risk of postoperative complications;significantly shortened surgical time;shorter gastrointestinal function recovery time;shorter hospital stay;and lower intraop-erative bleeding volume,while having a significant inhibitory effect on excessive serum inflammation and causing little postoperative oxidative stress.

Mechanism analysis of regulating Turing instability and Hopf bifurcation of malware propagation in mobile wireless sensor networks

A dynamical model is constructed to depict the spatial-temporal evolution of malware in mobile wireless sensor networks(MWSNs). Based on such a model, we design a hybrid control scheme combining parameter perturbation and state feedback to effectively manipulate the spatiotemporal dynamics of malware propagation. The hybrid control can not only suppress the Turing instability caused by diffusion factor but can also adjust the occurrence of Hopf bifurcation induced by time delay. Numerical simulation results show that the hybrid control strategy can efficiently manipulate the transmission dynamics to achieve our expected desired properties, thus reducing the harm of malware propagation to MWSNs.

Enhancing Wireless Sensor Network Efficiency through Al-Biruni Earth Radius Optimization

The networks of wireless sensors provide the ground for a range of applications,including environmental moni-toring and industrial operations.Ensuring the networks can overcome obstacles like power and communication reliability and sensor coverage is the crux of network optimization.Network infrastructure planning should be focused on increasing performance,and it should be affected by the detailed data about node distribution.This work recommends the creation of each sensor’s specs and radius of influence based on a particular geographical location,which will contribute to better network planning and design.By using the ARIMA model for time series forecasting and the Al-Biruni Earth Radius algorithm for optimization,our approach bridges the gap between successive terrains while seeking the equilibrium between exploration and exploitation.Through implementing adaptive protocols according to varying environments and sensor constraints,our study aspires to improve overall network operation.We compare the Al-Biruni Earth Radius algorithm along with Gray Wolf Optimization,Particle Swarm Optimization,Genetic Algorithms,and Whale Optimization about performance on real-world problems.Being the most efficient in the optimization process,Biruni displays the lowest error rate at 0.00032.The two other statistical techniques,like ANOVA,are also useful in discovering the factors influencing the nature of sensor data and network-specific problems.Due to the multi-faceted support the comprehensive approach promotes,there is a chance to understand the dynamics that affect the optimization outcomes better so decisions about network design can be made.Through delivering better performance and reliability for various in-situ applications,this research leads to a fusion of time series forecasters and a customized optimizer algorithm.

Advances in Wireless,Batteryless,Implantable Electronics for Real‑Time,Continuous Physiological Monitoring

This review summarizes recent progress in developing wireless,batteryless,fully implantable biomedical devices for real-time continuous physiological signal monitoring,focusing on advancing human health care.Design considerations,such as biological constraints,energy sourcing,and wireless communication,are discussed in achieving the desired performance of the devices and enhanced interface with human tissues.In addition,we review the recent achievements in materials used for developing implantable systems,emphasizing their importance in achieving multi-functionalities,biocompatibility,and hemocompatibility.The wireless,batteryless devices offer minimally invasive device insertion to the body,enabling portable health monitoring and advanced disease diagnosis.Lastly,we summarize the most recent practical applications of advanced implantable devices for human health care,highlighting their potential for immediate commercialization and clinical uses.

A Practical Approach for Missing Wireless Sensor Networks Data Recovery

In wireless sensor networks(WSNs),the performance of related applications is highly dependent on the quality of data collected.Unfortunately,missing data is almost inevitable in the process of data acquisition and transmission.Existing methods often rely on prior information such as low-rank characteristics or spatiotemporal correlation when recovering missing WSNs data.However,in realistic application scenarios,it is very difficult to obtain these prior information from incomplete data sets.Therefore,we aim to recover the missing WSNs data effectively while getting rid of the perplexity of prior information.By designing the corresponding measurement matrix that can capture the position of missing data and sparse representation matrix,a compressive sensing(CS)based missing data recovery model is established.Then,we design a comparison standard to select the best sparse representation basis and introduce average cross-correlation to examine the rationality of the established model.Furthermore,an improved fast matching pursuit algorithm is proposed to solve the model.Simulation results show that the proposed method can effectively recover the missing WSNs data.

Stackelberg Game for Wireless Powered and Backscattering Enabled Sensor Networks

This paper investigates a wireless powered and backscattering enabled sensor network based on the non-linear energy harvesting model, where the power beacon(PB) delivers energy signals to wireless sensors to enable their passive backscattering and active transmission to the access point(AP). We propose an efficient time scheduling scheme for network performance enhancement, based on which each sensor can always harvest energy from the PB over the entire block except its time slots allocated for passive and active information delivery. Considering the PB and wireless sensors are from two selfish service providers, we use the Stackelberg game to model the energy interaction among them. To address the non-convexity of the leader-level problem, we propose to decompose the original problem into two subproblems and solve them iteratively in an alternating manner. Specifically, the successive convex approximation, semi-definite relaxation(SDR) and variable substitution techniques are applied to find a nearoptimal solution. To evaluate the performance loss caused by the interaction between two providers, we further investigate the social welfare maximization problem. Numerical results demonstrate that compared to the benchmark schemes, the proposed scheme can achieve up to 35.4% and 38.7% utility gain for the leader and the follower, respectively.