Double enzyme mimetic activities of multifunctional Ag nanoparticle-decorated Co_(3)V_(2)O_(8)hollow hexagonal prismatic pencils for application in colorimetric sensors and disinfection

Since the catalytic activity of most nanozymes is still far lower than the corresponding natural enzymes,there is urgent need to discover novel highly efficient enzyme-like materials.In this work,Co_(3)V_(2)O_(8)with hollow hexagonal prismatic pencil structures were prepared as novel artificial enzyme mimics.They were then decorated by photo-depositing Ag nanoparticles(Ag NPs)on the surface to further improve its catalytic activities.The Ag NPs decorated Co_(3)V_(2)O_(8)(ACVPs)showed both excellent oxidase-and peroxidase-like catalytic activities.They can oxidize the colorless 3,3’,5,5’-tetramethylbenzidine rapidly to induce a blue change.The enhanced enzyme mimetic activities can be attributed to the surface plasma resonance(SPR)effect of Ag NPs as well as the synergistic catalytic effect between Ag NPs and Co_(3)V_(2)O_(8),accelerating electron transfer and promoting the catalytic process.ACVPs were applied in constructing a colorimetric sensor,validating the occurrence of the Fenton reaction,and disinfection,presenting favorable catalytic performance.The enzyme-like catalytic mechanism was studied,indicating the chief role of⋅O_(2)-radicals in the catalytic process.This work not only discovers a novel functional material with double enzyme mimetic activity but also provides a new insight into exploiting artificial enzyme mimics with highly efficient catalytic ability.

Current sensor based on diamond nitrogen-vacancy color center

High precision current measurement is very important for the calibration of various high-precision equipment and the measurement of other precision detection fields.A new current sensor based on diamond nitrogen-vacancy(NV)color center magnetic measurement method is proposed to realize the accurate measurement of current.This new current method can greatly improve the accuracy of current measurement.Experiments show that the linearity of the current sensor based on diamond NV color center can reach up to 33 ppm,which is superior to other current sensors and solves the problem of low linearity.When the range of input current is 5-40 A,the absolute error of the calculated current is less than 51μA,and the relative error is 2.42×10^(-6) at 40 A.Combined with the research content and results of the experiment,the application of the current sensor in the field of current precision measurement is prospected.

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.

Non-volatile dynamically switchable color display via chalcogenide stepwise cavity resonators

High-resolution multi-color printing relies upon pixelated optical nanostructures,which is crucial to promote color display by producing nonbleaching colors,yet requires simplicity in fabrication and dynamic switching.Antimony trisulfide(Sb_(2)S_(3))is a newly rising chalcogenide material that possesses prompt and significant transition of its optical characteristics in the visible region between amorphous and crystalline phases,which holds the key to color-varying devices.Herein,we proposed a dynamically switchable color printing method using Sb_(2)S_(3)-based stepwise pixelated Fabry-Pérot(FP)cavities with various cavity lengths.The device was fabricated by employing a direct laser patterning that is a less timeconsuming,more approachable,and low-cost technique.As switching the state of Sb_(2)S_(3) between amorphous and crystalline,the multi-color of stepwise pixelated FP cavities can be actively changed.The color variation is due to the profound change in the refractive index of Sb_(2)S_(3) over the visible spectrum during its phase transition.Moreover,we directly fabricated sub-50 nm nano-grating on ultrathin Sb_(2)S_(3) laminate via microsphere 800-nm femtosecond laser irradiation in far field.The minimum feature size can be further decreased down to~45 nm(λ/17)by varying the thickness of Sb_(2)S_(3) film.Ultrafast switchable Sb_(2)S_(3) photonic devices can take one step toward the next generation of inkless erasable papers or displays and enable information encryption,camouflaging surfaces,anticounterfeiting,etc.Importantly,our work explores the prospects of rapid and rewritable fabrication of periodic structures with nano-scale resolution and can serve as a guideline for further development of chalcogenide-based photonics components.

Intelligent Recognition Using Ultralight Multifunctional Nano‑Layered Carbon Aerogel Sensors with Human‑Like Tactile Perception

Humans can perceive our complex world through multi-sensory fusion.Under limited visual conditions,people can sense a variety of tactile signals to identify objects accurately and rapidly.However,replicating this unique capability in robots remains a significant challenge.Here,we present a new form of ultralight multifunctional tactile nano-layered carbon aerogel sensor that provides pressure,temperature,material recognition and 3D location capabilities,which is combined with multimodal supervised learning algorithms for object recognition.The sensor exhibits human-like pressure(0.04–100 kPa)and temperature(21.5–66.2℃)detection,millisecond response times(11 ms),a pressure sensitivity of 92.22 kPa^(−1)and triboelectric durability of over 6000 cycles.The devised algorithm has universality and can accommodate a range of application scenarios.The tactile system can identify common foods in a kitchen scene with 94.63%accuracy and explore the topographic and geomorphic features of a Mars scene with 100%accuracy.This sensing approach empowers robots with versatile tactile perception to advance future society toward heightened sensing,recognition and intelligence.

Coupling of reduced inorganic fertilizer with plant-based organic fertilizer as a promising fertilizer management strategy for colored rice in tropical regions

Colored rice is a type of high-quality,high-added-value rice that has attracted increasing attention in recent years.The use of large amounts of inorganic nitrogen fertilizer in rice fields results in low fertilizer use efficiency and high environmental pollution.Organic fertilizer is a promising way to improve soil quality and sustain high yields.However,most studies focus on the effect of animal-based organic fertilizers.The effects of different ratios of plantbased organic fertilizer and inorganic fertilizer on the grain yield and quality of colored rice have rarely been reported.Therefore,a two-year field experiment was conducted in 2020 and 2021 to study the effects of replacing inorganic N fertilizers with plant-based organic fertilizers on the yield,nitrogen use efficiency(NUE),and anthocyanin content of two colored rice varieties in a tropical region in China.The experimental treatments included no nitrogen fertilization(T1),100% inorganic nitrogen fertilizer(T2),30%inorganic nitrogen fertilizer substitution with plant-based organic fertilizer(T3),60%inorganic nitrogen fertilizer substitution with plant-based organic fertilizer(T4),and 100% plantbased organic fertilizer(T5).The total nitrogen provided to all the treatments except T1 was the same at 120 kg ha-1.Our results showed that the T3 treatment enhanced the grain yield and anthocyanin content of colored rice by increasing nitrogen use efficiency compared with T2.On average,grain yields were increased by 9 and 8%,while the anthocyanin content increased by 16 and 10% in the two colored rice varieties under T3 across the two years,respectively,as compared with T2.Further study of the residual effect of partial substitution of inorganic fertilizers showed that the substitution of inorganic fertilizer with plant-based organic fertilizer improved the soil physiochemical properties,and thus increased the rice grain yield,in the subsequent seasons.The highest grain yield of the subsequent rice crop was observed under the T5 treatment.Our results suggested that the application of plantbased organic fertilizers can sustain the production of colored rice with high anthocyanin content in tropical regions,which is beneficial in reconciling the relationship between rice production and environmental protection.

A chromosome-level genome assembly for Chinese plum‘Wushancuili'reveals the molecular basis of its fruit color and susceptibility to rain-cracking

Chinese plum(Prunus salicina Lindl.)originates from China and makes a large contribution to the global production of plums.The P.salicina‘Wushancuili'has a green coloration and high fruit quality and is economically important in eliminating poverty and protecting ecology in the Yangtze River Three Gorges Reservoir.However,rain-induced cracking(rain-cracking,literally skin cracking caused by rain)is a limitation to‘Wushancuili'fruit production and causes severe losses.This study reported a high-quality‘Wushancuili'genome assembly consisting of a 302.17-Mb sequence with eight pseudo-chromosomes and a contig N50 of 23.59 Mb through the combination of Illumina sequencing,Pacific Biosciences HiFiⅢsequencing,and high-throughput chromosome conformation capture technology.A total of 25109 protein-coding genes are predicted and 54.17%of the genome is composed of repetitive sequences.‘Wushancuili'underwent a remarkable orthoselection during evolution.Gene identification revealed that loss-of-function in four core MYB10 genes results in the anthocyanin deficiency and absence of red color,revealing the green coloration due to the residual high chlorophyll in fruit skin.Besides,the occurrence of cracking is assumed to be closely associated with cell wall modification and frequently rain-induced pathogen enrichment through transcriptomic analysis.The loss of MYB10 genes might render fruit more susceptible to pathogen-mediated cracking by weakening the epidermal strength and reactive oxygen species(ROS)scavenging.Our findings provided fundamental knowledge regarding fruit coloration and rain-cracking and will facilitate genetic improvement and cultivation management in Chinese plums.

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.

Electrochemical biosensors for point-of-care testing

Point-of-care testing(POCT)is the practice of diagnosing and monitoring diseases where the patient is located,as opposed to traditional treatment conducted solely in a medical laboratory or other clinical setting.POCT has been less common in the recent past due to a lack of portable medical devices capable of facilitating effective medical testing.However,recent growth has occurred in this field due to advances in diagnostic technologies,device miniaturization,and progress in wearable electronics.Among these developments,electrochemical sensors have attracted interest in the POCT field due to their high sensitivity,compact size,and affordability.They are used in various applications,from disease diagnosis to health status monitoring.In this paper we explore recent advancements in electrochemical sensors,the methods of fabricating them,and the various types of sensing mechanisms that can be used.Furthermore,we delve into methods for immobilizing specific biorecognition elements,including enzymes,antibodies,and aptamers,onto electrode surfaces and how these sensors are used in real-world POCT settings.

MXene-Based Elastomer Mimetic StretchableSensors: Design, Properties, and Applications

Flexible sensors based on MXene-polymer composites are highly prospective for next-generation wearable electronics used in human-machine interfaces.One of the motivating factors behind the progress of flexible sensors is the steady arrival of new conductive materials.MXenes,a new family of 2D nanomaterials,have been draw-ing attention since the last decade due to their high electronic conduc-tivity,processability,mechanical robustness and chemical tunability.In this review,we encompass the fabrication of MXene-based polymeric nanocomposites,their structure-property relationship,and applications in the flexible sensor domain.Moreover,our discussion is not only lim-ited to sensor design,their mechanism,and various modes of sensing platform,but also their future perspective and market throughout the world.With our article,we intend to fortify the bond between flexible matrices and MXenes thus promoting the swift advancement of flexible MXene-sensors for wearable technologies.

The protective effect of cyclodextrin on the color quality and stability of Cabernet Sauvignon red wine

The impact of cyclodextrins(CDs)on wine quality and stability remains largely unknown.This study systematically assessed the protective effect of the post-fermentation addition of CDs on color stability of red wine from the viewpoints of color characteristics,copigmentation and phenolic profiles.The grey relational analysis(GRA)and principal component analysis(PCA)methods were employed to dissect the key effective determinants related to color quality.The addition of CDs induced a significant hyperchromic effect of 8.19-25.40%,a significant bathochromic effect and an enhancement of the color intensity.Furthermore,the evolution of anthocyanin forms and the content of monomeric anthocyanins revealed that β-CD is a superior favorable cofactor during wine aging,but for long-term aging,2-HP-β-CD and 2-HP-γ-CD are more beneficial in promoting the formation of polymerized anthocyanins and color stability.This work provides an important reference for the use of CDs to enhance the color quality and stability of red wines.

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.

Intelligent diagnosis of retinal vein occlusion based on color fundus photographs

AIM:To develop an artificial intelligence(AI)diagnosis model based on deep learning(DL)algorithm to diagnose different types of retinal vein occlusion(RVO)by recognizing color fundus photographs(CFPs).METHODS:Totally 914 CFPs of healthy people and patients with RVO were collected as experimental data sets,and used to train,verify and test the diagnostic model of RVO.All the images were divided into four categories[normal,central retinal vein occlusion(CRVO),branch retinal vein occlusion(BRVO),and macular retinal vein occlusion(MRVO)]by three fundus disease experts.Swin Transformer was used to build the RVO diagnosis model,and different types of RVO diagnosis experiments were conducted.The model’s performance was compared to that of the experts.RESULTS:The accuracy of the model in the diagnosis of normal,CRVO,BRVO,and MRVO reached 1.000,0.978,0.957,and 0.978;the specificity reached 1.000,0.986,0.982,and 0.976;the sensitivity reached 1.000,0.955,0.917,and 1.000;the F1-Sore reached 1.000,0.9550.943,and 0.887 respectively.In addition,the area under curve of normal,CRVO,BRVO,and MRVO diagnosed by the diagnostic model were 1.000,0.900,0.959 and 0.970,respectively.The diagnostic results were highly consistent with those of fundus disease experts,and the diagnostic performance was superior.CONCLUSION:The diagnostic model developed in this study can well diagnose different types of RVO,effectively relieve the work pressure of clinicians,and provide help for the follow-up clinical diagnosis and treatment of RVO patients.

Synthesis and Coloring Mechanism of Metallic Glaze in R_(2)O-RO-Al_(2)O_(3)-SiO_(2)-P_(2)O_(5)System

A copper-red and silver-white metallic glaze of R_(2)O-RO-Al_(2)O_(3)-SiO_(2)-P_(2)O_(5)system was synthesized by adjusting the firing temperature and glaze components.The coloration mechanism of the metallic glaze was revealed via investigation of the microstructure of the glaze.Our research reveals that the metallic glaze with different colors is mainly due to the amount of Fe_(2)O_(3).The metallic glaze shows a silver-white luster due to a structural color ofα-Fe_(2)O_(3)crystals with a good orientation when the sample contains 0.0939 mol of Fe_(2)O_(3),maintaining temperatures at 1150℃for 0.5 h.The metallic glaze is copper-red which is dominated by the coupling of chemical and structural color ofα-Fe_(2)O_(3)crystals when the sample contains 0.0783 mol of Fe_(2)O_(3).After testing the amount of SiO_(2),we find that 4.0499 mol is the optimal amount to form the ceramic network,and 0.27 mol AlPO_(4)is the best amount to promote phase separation.

Physiological and psychological responses to tended plant communities with varying color characteristics

Exposure to plants has been reported to promote health and reduce stress,and plant color has direct impacts on physical and mental health.We used images of common types of tended plant communities in Shenyang,China,with combinations of yellow,green,and red foliage,as experimental stimuli.A total of 27 images were used as visual stimuli.We used electroencephalography to measureαwave activity(8-13 Hz)in 40 subjects while they viewed visual stimuli.These data were combined with subjective questionnaire data to analyze the relaxing effect of images of tended plant communities with different color types and proportions on people.The results revealed that,although there were slight differences between the electroencephalography and psychological findings,women were significantly more relaxed than men after viewing the images.Physiological and psychological responses varied with the types and proportions of colors in the tended plant communities:those of foliage with combinations of two or three colors induced stronger responses than images with a single color.Specifically,(1)for one-color plant communities,green or yellow plant communities induced a stronger relaxation effect than red plant communities;(2)for two-color plant communities,the optimal color proportion was 55%+45%,and the green+yellow and green+red color combinations induced a stronger relaxation effect;(3)for three-color plant communities,the relaxation effect was strongest when the color proportion was 55%green+25%yellow+20%red.These data would provide a plant color matching in future plant landscape design,which may be helpful for creating healthy and relaxing environments.

Force and impulse multi-sensor based on flexible gate dielectric field effect transistor

Nowadays,force sensors play an important role in industrial production,electronic information,medical health,and many other fields.Two-dimensional material-based filed effect transistor(2D-FET)sensors are competitive with nano-level size,lower power consumption,and accurate response.However,few of them has the capability of impulse detection which is a path function,expressing the cumulative effect of the force on the particle over a period of time.Herein we fabricated the flexible polymethyl methacrylate(PMMA)gate dielectric MoS_(2)-FET for force and impulse sensor application.We systematically investigated the responses of the sensor to constant force and varying forces,and achieved the conversion factors of the drain current signals(I_(ds))to the detected impulse(I).The applied force was detected and recorded by I_(ds)with a low power consumption of~30 nW.The sensitivity of the device can reach~8000%and the 4×1 sensor array is able to detect and locate the normal force applied on it.Moreover,there was almost no performance loss for the device as left in the air for two months.

Progress of Proximity Sensors for Potential Applications in Electronic Skins

Recently,electronic skins and fl exible wearable devices have been developed for widespread applications in medical monitoring,artifi cial intelligence,human–machine interaction,and artifi cial prosthetics.Flexible proximity sensors can accurately perceive external objects without contact,introducing a new way to achieve an ultrasensitive perception of objects.This article reviews the progress of fl exible capacitive proximity sensors,fl exible triboelectric proximity sensors,and fl exible gate-enhanced proximity sensors,focusing on their applications in the electronic skin fi eld.Herein,their working mechanism,materials,preparation methods,and research progress are discussed in detail.Finally,we summarize the future challenges in developing fl exible proximity sensors.

Flexible piezoresistive pressure sensor based on a graphene-carbon nanotube-polydimethylsiloxane composite

Flexible sensors are used widely in wearable devices, specifically flexible piezoresistive sensors, which are common and easy to manipulate.However, fabricating such sensors is expensive and complex, so proposed here is a simple fabrication approach involving a sensor containing microstructures replicated from a sandpaper template onto which polydimethylsiloxane containing a mixture of graphene and carbon nanotubes is spin coated. The surface morphologies of three versions of the sensor made using different grades of sandpaper are observed, and the corresponding pressure sensitivities and linearity and hysteresis characteristics are assessed and analyzed. The results show that the sensor made using 80-mesh sandpaper has the best sensing performance. Its sensitivity is 0.341 kPa-1in the loading range of 0–1.6 kPa, it responds to small external loading of 100 Pa with a resistance change of 10%, its loading and unloading response times are 0.126 and 0.2 s, respectively,and its hysteresis characteristic is ~7%, indicating that the sensor has high sensitivity, fast response, and good stability. Thus, the presented piezoresistive sensor is promising for practical applications in flexible wearable electronics.

Overcoming the Limits of Cross-Sensitivity:Pattern Recognition Methods for Chemiresistive Gas Sensor Array

As information acquisition terminals for artificial olfaction,chemiresistive gas sensors are often troubled by their cross-sensitivity,and reducing their cross-response to ambient gases has always been a difficult and important point in the gas sensing area.Pattern recognition based on sensor array is the most conspicuous way to overcome the cross-sensitivity of gas sensors.It is crucial to choose an appropriate pattern recognition method for enhancing data analysis,reducing errors and improving system reliability,obtaining better classification or gas concentration prediction results.In this review,we analyze the sensing mechanism of crosssensitivity for chemiresistive gas sensors.We further examine the types,working principles,characteristics,and applicable gas detection range of pattern recognition algorithms utilized in gas-sensing arrays.Additionally,we report,summarize,and evaluate the outstanding and novel advancements in pattern recognition methods for gas identification.At the same time,this work showcases the recent advancements in utilizing these methods for gas identification,particularly within three crucial domains:ensuring food safety,monitoring the environment,and aiding in medical diagnosis.In conclusion,this study anticipates future research prospects by considering the existing landscape and challenges.It is hoped that this work will make a positive contribution towards mitigating cross-sensitivity in gas-sensitive devices and offer valuable insights for algorithm selection in gas recognition applications.

Unsupervised Color Segmentation with Reconstructed Spatial Weighted Gaussian Mixture Model and Random Color Histogram

Image classification and unsupervised image segmentation can be achieved using the Gaussian mixture model.Although the Gaussian mixture model enhances the flexibility of image segmentation,it does not reflect spatial information and is sensitive to the segmentation parameter.In this study,we first present an efficient algorithm that incorporates spatial information into the Gaussian mixture model(GMM)without parameter estimation.The proposed model highlights the residual region with considerable information and constructs color saliency.Second,we incorporate the content-based color saliency as spatial information in the Gaussian mixture model.The segmentation is performed by clustering each pixel into an appropriate component according to the expectation maximization and maximum criteria.Finally,the random color histogram assigns a unique color to each cluster and creates an attractive color by default for segmentation.A random color histogram serves as an effective tool for data visualization and is instrumental in the creation of generative art,facilitating both analytical and aesthetic objectives.For experiments,we have used the Berkeley segmentation dataset BSDS-500 and Microsoft Research in Cambridge dataset.In the study,the proposed model showcases notable advancements in unsupervised image segmentation,with probabilistic rand index(PRI)values reaching 0.80,BDE scores as low as 12.25 and 12.02,compactness variations at 0.59 and 0.7,and variation of information(VI)reduced to 2.0 and 1.49 for the BSDS-500 and MSRC datasets,respectively,outperforming current leading-edge methods and yielding more precise segmentations.