Application Scenarios Research Articles

Two-peak envelope spectrum of a subwavelength grating microring resonator for wide-range and high-sensitivity refractive index sensing

The detectable range and sensitivity play a key role in the accuracy and range of applications available for lab-on-a-chip sensing systems. Here, we propose and numerically demonstrate an on-chip refractive index sensor simultaneously possessing wide detectable range and high sensitivity through monitoring the two-peak envelope spectrum of a subwavelength grating microring resonator. The principle lies in the combination of the envelope spectrum tracking scheme and the light field releasing in subwavelength grating waveguides. The structure of the subwavelength grating microring resonator is designed to adjust the wavelength dependence of its critical coupling condition, so that the two-peak envelope spectrum can be formed and centered at critically coupled wavelengths. By probing the drift of the two-peak envelope spectrum within the C+L band (1530–1625 nm), we lift the free spectral range constraint on the detectable range and broaden it up to 0.46 RIU. Meanwhile, a sensitivity of 444 nm/RIU is achieved. This investigation provides an attractive candidate for high performance integrated sensors, and thus may pave the way for lab-on-chip sensing, especially in application scenarios demanding both wide detectable range and high sensitivity.

A review on motion sickness of autonomous driving vehicles

The objective of this study is to investigate the symptoms, types, etiology, and assessment methods of motion sickness in autonomous vehicles in order to gain a comprehensive understanding of its occurrence mechanism and emphasize the significance of enhancing autonomous vehicle algorithms for improved ride comfort. Thus, this paper provides a synthesis and discussion of various theories while exploring strategies for mitigating motion sickness from three perspectives: passengers, vehicles, and external equipment. Firstly, it summarizes the clinical manifestations and classification of motion sickness while conducting an in-depth analysis of associated factors. Secondly, it evaluates different approaches for quantitatively measuring the severity and extent of motion sickness. Subsequently, it analyzes the reasons behind increased motion sickness caused by autonomous vehicles and emphasizes the importance of algorithmic improvements to enhance travel comfort. Finally, mitigation strategies are proposed considering passengers' needs as well as advancements in accurate motion prediction models and optimization techniques for autonomous planning and control algorithms that can effectively reduce the risk of motion sickness. As application scenarios for autonomous technology continue to expand, meeting user requirements while ensuring safety has become a benchmark for assessing technical proficiency. Therefore, promoting unmanned travel services necessitates a thorough analysis of existing issues related to autonomous technology along with prioritizing algorithm design enhancements through effective means to achieve an enhanced user experience.

Optimization of three dimensional rGO@MWCNTs/Fe3O4-PVA composite film through regulated structure for convenient and replaceable electromagnetic wave absorption material

Optimizing the composition and structure of polymers and carbon nanomaterials to obtain composite films with excellent mechanical and electromagnetic wave (EMW) properties is an excellent solution for exploring EMW absorbing materials. In this work, a flexible composite film with a regular three-dimensional network structure was designed and prepared. The modified rGO@MWCNTs/Fe3O4-PVA composite nanofilm with optimized composition and structure has a multi-component heterogeneous interface, three-dimensional network structure. The composite film has high EMW absorption performance, excellent flexibility, mechanical strength and stability, and can be used in a wide range of application scenarios. At a thickness of 2.8 mm, the effective absorption bandwidth (fE) reaches 3.72 GHz, the minimum reflection loss (RLmin) is -48.99 dB, and the tensile stress reaches 32 MPa. This work realizes the regulation of the mechanical properties and EMW absorbing properties of the composite film, and provides an efficient and stable flexible composite EMW absorbing material.

Coverage Performance of Non-Lambertian Underwater Wireless Optical Communications for 6G Internet of Things

In medium- and short-range underwater application scenarios, thanks to the superior performance in transmission bandwidth, link latency, and security, underwater wireless optical communication (UWOC) is growing to be a promising complement to the mature underwater acoustic communication technique. In order to extend the future 6G Internet of Things (IOT) to various challenging and valuable underwater scenarios, the underwater spatial coverage and transmission performance has been actively discussed in typical seawater environments. However, almost all current works focus on underwater scenarios including light-emitting diode (LED) transmitters with well-known Lambertian optical beams and fail to characterize the scenarios adopting LED transmitters with distinctive non-Lambertian beam patterns. For addressing this limitation, in this article, the coverage performance of non-Lambertian UWOC for 6G is analyzed and illustrated. Furthermore, the switchable optical beam configuration scheme is proposed and estimated for UWOC. Numerical results illustrate that, compared with about 15.42 dB signal-to-noise ratio (SNR) fluctuation amplitude for UWOC with baseline Lambertian optical beam configuration, the corresponding SNR fluctuation amplitudes of UWOC based with two typical non-Lambertian optical beams are 8.71 dB and 24.60 dB. Furthermore, once the receiver depth is increased to 6.0 m, the SNR fluctuation amplitude for the above three UWOC coverage with distinct beam configuration could be reduced to 5.61 dB, 1.58 dB, and 10.33 dB, respectively.

Control Strategies, Economic Benefits, and Challenges of Vehicle-to-Grid Applications: Recent Trends Research

With the rapid growth in the number of EVs, a huge number of EVs are connected to the power grid for charging, which places a great amount of pressure on the stable operation of the power grid. This paper focuses on the development of V2G applications, based on the current research status of V2G technology. Firstly, the standards on V2G applications and some pilot projects involving more representative V2G systems are introduced. Comparing V2G applications with ordered charging and unordered charging, the social and economic benefits of V2G applications are highlighted. Analysis of the social benefits of V2G applications concerns three points: the grid demand response, personalized charging, and the coordination of renewable energy sources. And analysis of the economic benefits of V2G applications is divided into three parties: the grid, the aggregator, and individuals. From the perspective of innovative EVs expanding the application scenarios through V2G technology, V2G applications for commercial EVs, emergency power applications, and vehicle-to-vehicle energy trading are introduced. The current challenges related to V2G applications are presented: users’ willingness to participate in V2G applications, battery loss, charging and discharging tariffs, privacy and security, and power loss. Finally, some research recommendations for the development of V2G applications are given and the current state of research in regard to those recommendations is presented.

The Artistic Characteristics of Biological Art

The new application scenarios and technology applications of biological art provide people with new ideas and ways of expression. In this space, biologists and artists can conduct more levels and richer research from different perspectives and in different ways. Biological art has made great progress in breaking through the rigid "dialogue" between biological artists and organisms to the flexible application of biological materials, the aesthetic paradigm of ecological art, and the bold expression of biological images, so that this complex has a wider tolerance. In this context, art and biotechnology in the traditional sense are converging and merging, and the cross penetration of biotechnology and art industries is spawning a new trend that is redefining design and its future. In their mutual cooperation, they try to find more and deeper cultural problems, so as to obtain more accurate and novel artistic expression.

A Comprehensive Evaluation and Comparison of Enhanced Learning Methods

This paper provides a comprehensive evaluation and comparison of current reinforcement learning methods. By analyzing the strengths and weaknesses of the main methods, such as value function-based, strategy gradient-based, and value and strategy-based methods, the differences in their performances on standard problems and the applicable scenarios are explored. Meanwhile, other methods such as Monte Carlo Tree Search (MCTS) and evolutionary methods are also briefly introduced. Through the research and analysis in this paper, it provides reference and guidance for choosing appropriate reinforcement learning methods, and promotes the development and application of reinforcement learning techniques in practical applications.

Navigating the Manifold of Translucent Appearance

AbstractWe present a perceptually‐motivated manifold for translucent appearance, designed for intuitive editing of translucent materials by navigating through the manifold. Classic tools for editing translucent appearance, based on the use of sliders to tune a number of parameters, are challenging for non‐expert users: These parameters have a highly non‐linear effect on appearance, and exhibit complex interplay and similarity relations between them. Instead, we pose editing as a navigation task in a low‐dimensional space of appearances, which abstracts the user from the underlying optical parameters. To achieve this, we build a low‐dimensional continuous manifold of translucent appearance that correlates with how humans perceive this type of materials. We first analyze the correlation of different distance metrics in image space with human perception. We select the best‐performing metric to build a low‐dimensional manifold, which can be used to navigate the space of translucent appearance. To evaluate the validity of our proposed manifold within its intended application scenario, we build an editing interface that leverages the manifold, and relies on image navigation plus a fine‐tuning step to edit appearance. We compare our intuitive interface to a traditional, slider‐based one in a user study, demonstrating its effectiveness and superior performance when editing translucent objects.

Photothermal performance of vitreous products from high-temperature melting of hazardous waste

High-temperature molten vitreous (HTMV), as the primary means of hazardous waste disposal, was produced in large quantities. Exploring its potential in photothermal applications could extend its high-value. Herein, the HTMV was used to explore the photothermal performance potential. It indicates that the HTMV possesses significant photothermal conversion capability, capable of increasing the tested water temperature by 6.65 °C. The HTMV mass and water volume are critical factors affecting the water temperature outcomes. The HTMV exhibits distinct conversion capabilities when applied at different application scenarios on the test object. Application on the bottom primarily focuses on photothermal conversion with high heat production efficiency, while side application additionally demonstrates excellent thermal insulation properties. Based on heat balance and backpropagation neural network predictions, optimal scheme of HTMV on both inside and outside bottom application scenarios of the heated object can achieve a maximum heat input of 660.6 kJ m−2 and 570.1 kJ m−2, respectively, and reduce carbon emissions by 0.062 kg CO2 m−2 and 0.054 kg CO2 m−2. This study not only provides a foundation for the further application of HTMV but also opens a new direction for the development of photothermal conversion materials, which is of great significance in advancing sustainable energy technology.

Microstructure regulation and enhanced VOC removal performance of carbon aerogels by surface carbon nanotube grown

Carbon aerogels were newly employed in adsorption for volatile organic compounds (VOCs) as an emerging material. In contrast, the microstructure and high carbon consumption are the primary factors restricting their application scenarios. Carbon nanotubes, recognized for their controllable cylindrical hollow structure and hydrophobic walls, generally possess higher adsorption capacities than typical carbon adsorbents. In this study, carbon nanotubes were grown on the surface of carbon aerogels using the chemical vapor deposition method by controlling different deposition conditions. The results showed that the modified samples displayed the maximum adsorption capacity of 145.0 mg/g and 178.3 mg/g for toluene and 1,2- dichlorobenzene, respectively. After ten regeneration cycles, the performance decreased by 7.9 % and 5.6 %, respectively. Meanwhile, the carbon replenishment was about 0.2 g/g, which is an excellent complement for carbon consumption. Various characterization patterns showed that deposition temperature was reflected in its deposition rate, deposition times influenced the formation of multi-walled carbon nanotubes, and deposition concentration affected the length of carbon nanotubes. This study offers valuable insight into the growth patterns of carbon nanotubes and the microscale regulation of carbon material surfaces, and this method is expected to be an effective means of carbon replenishment, carbon addition to carbon-poor materials, and enhancement of VOCs removal performance, and the growth mechanisms investigated are instructive for practical applications.

Variable horizon multivariate driving pattern recognition framework based on vehicle-road two-dimensional information for electric vehicle

Driving condition is the core factor influencing vehicle energy management and power output strategies, hence realistic and accurate driving pattern recognition is crucial for realizing intelligent control of Electric Vehicles in complex scenarios. However, driving patterns mismatch with real scenarios caused by lack of road environment information and the reduced global recognition accuracy triggered by the fixed recognition horizon together constrain the development of intelligent control strategies. In this study, a framework for variable horizon multivariate driving pattern recognition strategy based on vehicle-road two-dimensional (2D) information is proposed. Specifically, multivariate driving pattern extraction is carried out based on real vehicle-road 2D data, and the extraction data serves as input for training offline driving pattern recognizer. To meet the challenge of large differences and frequent changes in driving conditions during the online application, a variable horizon recognition strategy is proposed based on the optimal horizon matching regularity. Finally, test results show that the proposed approach achieves an average recognition accuracy of 88.42% under different cycles, including 88.39% for complex driving cycles. Furthermore, the recognition accuracy is improved by 63.14% and 47.51% compared with the fixed long/short horizon. The framework can provide a basis for intelligent control strategies, thus broadening the Electric Vehicle application scenarios.

Application and analysis of contemporary flexible tactile sensors

In order to meet the increasing demand for electronic products in contemporary society, relevant manufacturers have been continuously improving related technologies. While electronic products are convenient, they are plagued by issues such as rapid power consumption, susceptibility to damage, and inconvenience in portability. Therefore, many countries have developed foldable screen smartphones, computers, and other electronic products. In China, major brands such as OPPO and Huawei have released foldable screen smartphones, effectively addressing issues like portability. In this article, a background study of flexible tactile sensors is first conducted to ensure a thorough understanding of their applications. Secondly, based on the working principle of flexible tactile sensors and their different categories, the current research status is analyzed. The classification can be further refined according to the information transmission mechanism and application scenarios. In the former classification, detailed principal introductions are provided for each type of sensor. In the latter classification, based on the existing environment, detailed analyses of the production methods and characteristics are carried out in multiple fields such as tablets and smartphones, laying the groundwork for subsequent discussions. Furthermore, from the perspectives of preparation, characteristics, and power supply, I identify the existing problems and shortcomings that need improvement today, providing detailed explanations. Finally, relevant solutions are proposed for the aforementioned issues, and prospects for the extensive application and bright future of flexible tactile sensors are discussed, including in the fields of biointerfaces, cellular domains, and future mechanical domains.

Efficiency of working coveralls and chemical resistant gloves in reducing operator exposure to pesticides

Personal Protective Equipment (PPE) is used to reduce exposure when working with chemicals. For pesticides, exposure scenarios comprise mixing and loading (M&L) and application. The exposure prediction model recommended by European regulatory agencies for operator risk assessments—the Agricultural Operator Exposure Model (AOEM) – is based on 48 operator exposure studies involving over 500 professional operators from 10 European countries in typical working situations to assess exposure under realistic field conditions. We used the AOEM data to assess the efficiency of exposure reduction resulting from wearing chemical-resistant nitrile gloves and non-certified working coveralls during M&L (tank and backpack sprayer), applications using groundboom and airblast spraying, and outdoor and indoor (greenhouse) applications using handheld sprayers. All studies indicated consistent and high exposure reduction > 90% for gloves and non-certified coveralls across all investigated scenarios. Exceptions were almost exclusively observed when an operator incorrectly used the PPE. The mean exposure reduction from all operators, including those that used PPE incorrectly, was 95.0% for gloves and 96.4% for polyester/cotton working coveralls during M&L, and 91.1% for gloves and 94.9% for non-certified coveralls during all application scenarios. This analysis confirms the essential role of PPE and non-certified working coveralls in reducing operator exposure to pesticides. Outliers indicate that operators need to be properly trained and adhere to label instructions to apply pesticides according to good agricultural practices.

A Universal Biomineralization‐Like Interfacial‐Confined Strategy Enables Practicable, Meter‐Scale, Transmittance‐Adjustable, Highly‐Ordered, Photothermal‐Capable, 2D Conducting Polymers

AbstractConducting polymers (CPs) encompass various cutting‐edge fields owing to their combination of polymer and conducting properties. However, the mismatch between the polymer growth process and the carrier mobility design leads to poor material and device consistency, and insufficient long‐term device stability, thus hindering the practical application of CPs. Although 2D construction has been explored to address these challenges, it typically leads to materials instability and lacks methods for large‐scale synthesis, making it unsuitable for many application scenarios. Here a universal biomineralization‐like strategy relying on the joint impaction of hydrogen‐bond and gravity for large‐scale fabrication of 2D CPs is developed. As‐fabricated meter‐scale Polypyrrole films exhibit high orderliness and can be assembled into multilayers, allowing for adjustable thickness and transparency. Notably, these films demonstrate exceptional photothermal properties and remarkable long‐term stability, as their surface temperature can reach 140 °C when irradiated with an 808 nm laser at 0.7 W cm−2, with almost no attenuation after 170 days. Furthermore, under sunlight, the temperature can reach nearly 100 °C, showcasing significant potential in smart building and energy management applications. Importantly, this strategy can be extended to the 2D design of numerous light organic compounds, thus opening up possibilities for their practical applications.

Crystallization behavior and compatibility analysis of palm kernel stearin/anhydrous milk fat blends and application.

In this paper, the compatibility, phase behavior, and crystallization properties of the binary blends of palm kernel stearin (PKS) and anhydrous milk fat (AMF) were investigated by analyzing the solid fat content (SFC), thermal properties, polymorphism, and microstructure, with the aim of providing theoretical guidance for the blending of oils. The results showed that the PKS content primarily determined the SFC trend of the binary blends. However, the binary blends demonstrated poor miscibility and eutectic behavior was predominantly observed in the system, particularly at higher temperatures. Only α and β' forms appeared in this blended system. Simultaneously, the addition of PKS elevated the liquid phase transition temperature of the binary blends, considerably significantly increased their crystallization rate when the addition of PKS was more than 20% and increased the density and size of the fat crystals. Finally, the mixing design optimization method was used to get the most suitable ratio of the binary blends in the refrigerated cream system with PKS:AMF to be 0.914:0.086. The cream prepared with the above binary blends was indeed superior in overrun and firmness and had high stability. PRACTICAL APPLICATION: Some fats with special advantages are often limited in their wide application because of their poor crystallization ability. In this paper, the crystallization ability of fats is improved, and their application scenarios are increased through the combination of fats, so as to provide reference for the production of special fats for food.

Robust 3D coordinate transformation based on genetic algorithm intelligent weighting

In order to improve the solution quality of 3D coordinate transformation parameters, a robust optimization model is obtained by integrating the 3D coordinate transformation model within the overall framework of the genetic algorithm in this paper. The minimum of the weighted sum of squares of the point residuals of the common points is taken as the objective function for optimization, and the parallel search is started from the initial population, and the updating process of the solution set is used to generate new and better individuals, and the adaptive weight combination corresponding to the optimum of the fitness function is obtained at the end of the generation iteration. The generated simulated data and measured data were analyzed using the Hefei Light Source tunnel control network as an application scenario. The results show that the method in this paper can automatically reduce the influence of low-quality data on the model, and compared with the two robust conversion models of IGG III iterative weighting, the method in this paper is not affected by the empirical parameters in determining the weight combinations and the weighted sum of squares of the residuals of the solved points are smaller, so it can effectively improve the quality of the solved conversion parameters.

A “three-in-one” multifunctional palladium/platinum nanoparticles-driven multimodal lateral flow immunoassays for point-of-care testing of Staphylococcus aureus

Staphylococcus aureus (S. aureus) is a prevalent bacterium that affects patient recovery post-surgery and can cause postoperative complications. Consequently, detecting S. aureus in clinical settings is critical for ensuring patient well-being. In our work, a “visual-colorimetric-photothermal” three-in-one multimodal lateral flow immunoassays (LFIA) was developed for S. aureus detection to meet the growing demand for point-of-care testing (POCT) of bacteria in the field. The sensors relied on Pd/Pt@Ab1 NPs nanoprobes, created by decorating the surface of bimetallic nanoprobes (Pd/Pt NPs) with S. aureus antibodies (Ab1). A visual detection mode was realized by the Pd/Pt@Ab1 NPs being captured on the surface of test line (T line) using the sandwich method, offering a limit of detection (LOD) of 103 CFU/mL. Subsequently, Pd/Pt@Ab1 NPs catalyzed the TMB system into oxTMB to achieve colorimetric analysis, covering a detection range from 102 to 107 CFU/mL. Remarkably, the oxTMB exhibited the photothermal conversion efficiency under near-infrared (NIR) light, leading to temperature variations under 808 nm irradiation, correlating with different bacteria concentrations, with an LOD as low as 4 CFU/mL. The methodology enabled quantitative analysis of bacteria in clinical samples with satisfactory results. The diversity, complementarity, and synergy of the integrated output signals in this multimode LFIA improved the flexibility, utility, and accuracy of the assay, performing well as a POCT platform for various application scenarios.

Enhancing thermal safety of hydrophobic SiO2 aerogels through introducing ammonium polyphosphate intercalated layered double hydroxides

Enhancing the thermal safety of hydrophobic SiO2 aerogels (SAs) is crucial for its practical thermal insulation applications. Here, we explore a facile method to enhance the thermal safety of hydrophobic SAs with the introduction of ammonium polyphosphate intercalated layered double hydroxide (APP-LDH). The obtained results show that as-produced APP-LDH/SA composites maintain excellent fundamental properties, including low density (0.14–0.16 g/cm3), high porosity (92.8–93.5 %), high specific surface area (680.0–762.6 m2/g), and low thermal conductivity (25.3–26.9 mW/m/K). Notably, APP-LDH effectively inhibits the thermal oxidation decomposition of SAs. In comparison to pristine SAs and those modified solely with LDH, the APP-LDH/SA composites exhibit significantly improved thermal stability. The gross calorific value of the APP-LDH/SA-20 % (i.e., containing 20 wt% APP-LDH) decreases by 13.9 % and 5.2 % compared with that of neat SAs and SAs modified solely with 20 wt% LDH, respectively. The improved thermal stability and reduced gross calorific value completely confirm the enhancement of the thermal safety of the APP-LDH/SA composites. This work provides a simple method to improve the thermal safety of hydrophobic SAs, which expands the thermal insulation application scenarios of SAs.

Sensitive data identification for multi‐category and multi‐scenario data

AbstractSensitive data identification is the prerequisite for protecting critical user and business data. Traditional methods usually only target a certain type of application scenario or a certain type of data, thus making it difficult to meet the needs of enterprise‐level data protection. This paper proposes an introduction to the end‐to‐end sensitive data identification system of Beike Inc. The system consists of the data identification & annotation platform, dataset management platform, and sensitive data identification model, which propose different governance methods for batch data and streaming data respectively. Specifically, we propose a sliding window‐based identification method for long text to improve the identification of streaming data. Evaluation results show that this method can improve the effect of identifying long text sensitive data without losing the ability on short text, for the open source test dataset, the value can be up to 94.15, so it is applicable in diverse scenarios.

Flexible bidirectional pulse charging regulation achieving long-life lithium-ion batteries

Typical application scenarios, such as vehicle to grid (V2G) and frequency regulation, have imposed significant long-life demands on lithium-ion batteries. Herein, we propose an advanced battery life-extension method employing bidirectional pulse charging (BPC) strategy. Unlike traditional constant current charging methods, BPC strategy not only achieves comparable charging speeds but also facilitates V2G frequency regulation simultaneously. It significantly enhances battery cycle ampere-hour throughput and demonstrates remarkable life extension capabilities. For this interesting conclusion, adopting model identification and postmortem characterization to reveal the life regulation mechanism of BPC: it mitigates battery capacity loss attributed to loss of lithium-ion inventory (LLI) in graphite anodes by intermittently regulating the overall battery voltage and anode potential using a negative charging current. Then, from the perspective of internal side reaction, the life extension mechanism is further revealed as inhibition of solid electrolyte interphase (SEI) and lithium dendrite growth by regulating voltage with a bidirectional pulse current, and a semi-empirical life degradation model combining SEI and lithium dendrite growth is developed for BPC scenarios health management, the model parameters are identified by genetic algorithm with the life simulation exhibiting an accuracy exceeding 99%. This finding indicates that under typical rate conditions, adaptable BPC strategies can extend the service life of LFP battery by approximately 123%. Consequently, the developed advanced BPC strategy offers innovative perspectives and insights for the development of long-life battery applications in the future.