Multiple Information Channels Research Articles

Reducing consequences of extreme heat: The role of weather information access

This study investigates the impact of weather information sources on consequences associated with extreme heat events, employing a cross-sectional survey conducted on hospitalized individuals who have experienced heat stress in Central Vietnam. Multiple information channels, including official agencies and social media, were found to significantly reduce the Cost of Illness (COI) associated with heat-related ailments. Social media, in particular, emerged as a potent tool for climate adaptation. Improving the clarity and accessibility of weather information through official channels is crucial, especially for households with varying income levels. Demographic factors such as age and gender should be considered when fine-tuning communication strategies, with special attention given to individuals with underlying medical conditions, who are particularly susceptible to extreme heat effects. These findings underscore the need to maximize the reach of weather-related information and reduce economic burdens on affected populations. This provides valuable insights for policymakers aiming to bolster climate resilience in vulnerable regions like Vietnam, emphasizing the significance of diverse information sources and tailored communication in climate change adaptation.

A Review on Non-Invasive Multimodal Approaches to Detect Deception Based on Machine Learning Techniques

Detecting deception has been investigated by the scientific community for over a century due to its importance in the justice system and homeland security. Attempts to come up with an approach, a system or a framework that serves the purpose of discerning lies from truths has therefore been a major field. This has led researchers to automate the detection process and reduce its invasiveness as much as possible. In addition, machine learning techniques are used with multiple channels of information, known as modals, to increase accuracy in what is known as a multimodal approach. As a result, several research and datasets are currently available, and it could be challenging to identify successful patterns, gaps, and future directions. In this paper, over fifty state-of-the-art publications in the field of deception detection using non-invasive approaches based on machine learning techniques are analyzed after reviewing more than one thousand publications from Scopus, IEEE Xplore, Web of Science, ScienceDirect, and Google Scholar. The work presents the classification techniques and datasets used with their detection performance and finally analyzing the data to draw conclusions. The reported detection accuracy ranges from about 50% to 95% for monomodal approaches based on facial expression, body movement, audio, or thermal imaging. In conclusion, the multimodal approach shows promising results as it reaches a detection accuracy approaching 100%. It outperforms any alternative non-invasive approach, especially when dealing with small datasets, which seems to be the biggest challenge in this field. Future research directions should focus on experimenting with multimodal systems by developing larger datasets as well as implementing classification algorithms that can work with multiple modals effectively.

Multi-Channel Sensing System Utilizing Mott Memristors for Single-Wire Data Fusion and Back-End Greedy Strategy Data Recovery

This paper presents a novel Mott memristor-based multi-channel sensing system designed for the simultaneous processing of multiple sensing channels, employing single-wire data fusion and a greedy search strategy for back-end data recovery. Multiple channels of external stimulus information are simultaneously encoded into analog signals with varying frequencies, utilizing a Mott memristor array. Auxiliary circuits then convert the analog sensing signals into square wave signals which are further transformed into narrow (100 ns) pulse signals through pulse generation circuitry. Subsequently, these narrow pulse signals are fused into a single-wire signal by using an OR gate. At the back-end of the system, a greedy searching strategy is applied to accurately identify all frequencies within the fused pulse signal, enabling seamless analog-to-frequency conversion across multiple channels. The system is suitable for a wide range of sensors and can be directly connected to FPGAs for data processing, eliminating the need for traditional analogue front-end and ADC circuits and greatly reducing circuit complexity and power consumption. By leveraging the innovative capabilities of Mott memristors, the proposed system achieves precise analog-to-frequency conversion with significantly reduced power consumption.

Multichannel meta-imagers for accelerating machine vision.

Rapid developments in machine vision technology have impacted a variety of applications, such as medical devices and autonomous driving systems. These achievements, however, typically necessitate digital neural networks with the downside of heavy computational requirements and consequent high energy consumption. As a result, real-time decision-making is hindered when computational resources are not readily accessible. Here we report a meta-imager designed to work together with a digital back end to offload computationally expensive convolution operations into high-speed, low-power optics. In this architecture, metasurfaces enable both angle and polarization multiplexing to create multiple information channels that perform positively and negatively valued convolution operations in a single shot. We use our meta-imager for object classification, achieving 98.6% accuracy in handwritten digits and 88.8% accuracy in fashion images. Owing to its compactness, high speed and low power consumption, our approach could find a wide range of applications in artificial intelligence and machine vision applications.

Dynamic multifunctional metasurfaces: an inverse design deep learning approach

Optical metasurfaces (OMs) offer unprecedented control over electromagnetic waves, enabling advanced optical multiplexing. The emergence of deep learning has opened new avenues for designing OMs. However, existing deep learning methods for OMs primarily focus on forward design, which limits their design capabilities, lacks global optimization, and relies on prior knowledge. Additionally, most OMs are static, with fixed functionalities once processed. To overcome these limitations, we propose an inverse design deep learning method for dynamic OMs. Our approach comprises a forward prediction network and an inverse retrieval network. The forward prediction network establishes a mapping between meta-unit structure parameters and reflectance spectra. The inverse retrieval network generates a library of meta-unit structure parameters based on target requirements, enabling end-to-end design of OMs. By incorporating the dynamic tunability of the phase change material Sb2Te3 with inverse design deep learning, we achieve the design and verification of dynamic multifunctional OMs. Our results demonstrate OMs with multiple information channels and encryption capabilities that can realize multiple physical field optical modulation functions. When Sb2Te3 is in the amorphous state, near-field nano-printing based on meta-unit amplitude modulation is achieved for X-polarized incident light, while holographic imaging based on meta-unit phase modulation is realized for circularly polarized light. In the crystalline state, the encrypted information remains secure even with the correct polarization input, achieving double encryption. This research points towards ultra-compact, high-capacity, and highly secure information storage approaches.

Advanced techniques in automated high-resolution scanning transmission electron microscopy

Scanning transmission electron microscopy is a common tool used to study the atomic structure of materials. It is an inherently multimodal tool allowing for the simultaneous acquisition of multiple information channels. Despite its versatility, however, experimental workflows currently rely heavily on experienced human operators and can only acquire data from small regions of a sample at a time. Here, we demonstrate a flexible pipeline-based system for high-throughput acquisition of atomic-resolution structural data using an all-piezo sample stage applied to large-scale imaging of nanoparticles and multimodal data acquisition. The system is available as part of the user program of the Molecular Foundry at Lawrence Berkeley National Laboratory.

Detailed muscle state analysis method based on real-time wavelet analysis of surface myoelectric potential

Myoelectric refers to the use of electricity generated by muscles and is harnessed in the development of electrically powered prostheses, which are controlled by electromyographic (EMG) signals created in the residual musculature. Assistant professor Hidetoshi Nagai, Department of Artificial Intelligence, Kyushu Institute of Technology, Japan, is interested in surface myoelectric signals and is working on a project to develop technology that can advance their use. Nagai will capture motor unit activities using surface electromyography, which is easy to measure during exercise, and use this as the basis for more detailed muscle activity analysis. The methods Nagai has developed require no special equipment, other than the ability to sample at frequencies of several tens of kHz, and only require a single channel, which indicates the potential for more sophisticated analysis when multiple channels of information are present. It is also a simple and lightweight process that can be executed in real time. Conventional analysis and evaluation of muscle activity cannot be performed from the perspective of motor unit activity but Nagai has built on the basic premise that given that muscle activity is the sum of motor unit activities, the analysis of muscle activity should be based on the analysis of motor unit activity. He will analyse the surface EMG signal from the viewpoint of its component waveform the motor unit waveform so that muscle activity analysis can be performed as it should be.

Angular Momentum Multiplexing via a Shared Aperture Patch Antenna

Angular momentum (AM) multiplexing technique provides multiple information channels for electromagnetic waves (EMWs) modulation at the same frequency, improving spectrum efficiency effectively. Among AM multiplexing techniques, the patch antenna has the advantage of minimization, simple feeding circuits, and easy integration. Nevertheless, limited reports provide theoretical guidance for designing AM multiplexing patch antennas. Herein, we propose a scheme to achieve AM multiplexing via a shared-aperture patch antenna. The radiating structure consists of multiple radiating patches sharing a common physical aperture, each of which is responsible for producing different AM-carrying waves. By analyzing the theoretical model built on a dipole representation of the patch antenna, the shapes and the desired current patterns of these patches can be determined according to the AM mode of the expected EMWs. Besides, the sizes and feeding structures of these patches can be studied by investigating their radiating characteristics using characteristic mode (CM) theory. For proof-of-concept, a prototype was designed, fabricated, and measured for the generation of four orthogonal AM-carrying waves coaxially at 5.8GHz. The experimental results agree reasonably well with the simulated ones, demonstrating that the proposed scheme provides an efficient guidance for the design of AM multiplexing patch antennas.

Chiroptical Nanocellulose Bio-Labels for Independent Multi-Channel Optical Encryption.

Advanced multiplexing optical labels with multiple information channels provide a powerful strategy for large-capacity and high-security information encryption. However, current optical labels face challenges of difficulty to realize independent multi-channel encryption, cumbersome design, and environmental pollution. Herein, multiplexing chiroptical bio-labels integrating with multiple optical elements, including structural color, photoluminescence (PL), circular polarized light activity, humidity-responsible color, and micro/nano physical patterns, are constructed in complex design based on host-guest self-assembly of cellulose nanocrystals and bio-gold nanoclusters. The thin nanocellulose labels exhibit tunable circular polarized structural color crossover the entire visible wavelength and circularly polarized PL with the highest-recorded dissymmetry factor up to 1.05 due to the well-ordered chiral organization of templated gold nanoclusters. Most importantly, these elements can independently encode customized anti-counterfeiting information to achieve five independent channels of high-level anti-counterfeiting, which are rarely achieved in traditional materials and design counterparts. Considering the exceptional seamless integration of five independent encryption channels and the recyclable features of labels, the bio-labels have great potential for the next generation anti-counterfeiting materials technology.

Implementation of a Hybrid Intelligence System Enabling the Effectiveness Assessment of Interaction Channels Use in HMI.

The article presents a novel idea of Interaction Quality Sensor (IQS), introduced in the complete solution of Hybrid INTelligence (HINT) architecture for intelligent control systems. The proposed system is designed to use and prioritize multiple information channels (speech, images, videos) in order to optimize the information flow efficiency of interaction in HMI systems. The proposed architecture is implemented and validated in a real-world application of training unskilled workers-new employees (with lower competencies and/or a language barrier). With the help of the HINT system, the man-machine communication information channels are deliberately chosen based on IQS readouts to enable an untrained, inexperienced, foreign employee candidate to become a good worker, while not requiring the presence of either an interpreter or an expert during training. The proposed implementation is in line with the labor market trend, which displays significant fluctuations. The HINT system is designed to activate human resources and support organizations/enterprises in the effective assimilation of employees to the tasks performed on the production assembly line. The market need of solving this noticeable problem was caused by a large migration of employees within (and between) enterprises. The research results presented in the work show significant benefits of the methods used, while supporting multilingualism and optimizing the preselection of information channels.

Arena3Dweb: interactive 3D visualization of multilayered networks supporting multiple directional information channels, clustering analysis and application integration.

Arena3Dweb is an interactive web tool that visualizes multi-layered networks in 3D space. In this update, Arena3Dweb supports directed networks as well as up to nine different types of connections between pairs of nodes with the use of Bézier curves. It comes with different color schemes (light/gray/dark mode), custom channel coloring, four node clustering algorithms which one can run on-the-fly, visualization in VR mode and predefined layer layouts (zig-zag, star and cube). This update also includes enhanced navigation controls (mouse orbit controls, layer dragging and layer/node selection), while its newly developed API allows integration with external applications as well as saving and loading of sessions in JSON format. Finally, a dedicated Cytoscape app has been developed, through which users can automatically send their 2D networks from Cytoscape to Arena3Dweb for 3D multi-layer visualization. Arena3Dweb is accessible at http://arena3d.pavlopouloslab.info or http://arena3d.org.

The role of option‐based information on StockTwits, options trading volume, and stock returns

AbstractWe examine the relations between activities of multiple information channels for stocks simultaneously covered on the StockTwits social media platform, the options market, and the stock market. First, we show that, for our focal firms, net trade options volume ratio from the options market is positively and significantly related to the bullish sentiment of posts on StockTwits. Second, we find that net trade options volume ratio and bullish posts are positively and significantly related to stock returns. Third, we show that higher agreement amongst the sentiment of posts on StockTwits and net trade options volume ratio for options that are deeply out‐of‐the‐money (high leverage) both predict future stock returns for up to 20 days. This finding is consistent with the explanation that informed investors have an affinity to trade deeply levered options to maximize their returns at the lowest cost.

Systems factorial technology provides novel insights into the cognitive processing characteristics of open-skill athletes

Sport expertise has been shown to modulate the cognitive advantage in open-skill athletes, with evidence for a greater advantage for athletes practicing interceptive sports relative to strategic sports. However, this conclusion is solely based on central tendency measures such as accuracy or mean reaction time (RT), dismissing important information embedded in the intra-individual temporal dynamics of cognitive performance. This study aimed to better understand the cognitive advantage associated with open-skill sports, with a non-parametric approach assessing cognitive process at the level of RT distribution (i.e., systems factorial technology, SFT). Twenty-eight interceptive sport athletes, 27 strategic sport athletes, and 26 physically active non-athletes performed a go/nogo version of the redundant target task to assess their processing capacity of simultaneously monitoring multiple information channels. SFT was applied to assess resilience capacity, an estimate of workload capacity underlying inhibitory control. Our findings showed that interceptive sport athletes exhibited shorter mean RT relative to non-athletes selectively in the task condition involving distracting information, while strategic sport athletes showed greater resilience capacity over earlier responses relative to the other groups. These findings suggest that the two types of open-skill sports may be associated with different processing specificity, possibly reflecting the domain-specific rules and requirements.

Broadband spin-multiplexed single-celled metasurface holograms: a comprehensive comparison between different strategies

Abstract Metasurface-generated holograms have emerged as a unique platform for arbitrarily shaping the reflected/transmitted wavefronts with the advantages of subwavelength large pixel sizes and multiple information channels. However, achieving multiple holographic images with large operation bandwidths is a rather complicated and arduous issue due to the dissimilar dispersion of all meta-atoms involved. In this work, we design and experimentally demonstrate single-celled metasurfaces to realize broadband and spin-multiplexed holograms, whose phase modulation is based only on the geometric phase supplied by a judiciously designed high-performance nanoscale half-wave plate operating in reflection. Four different multiplexing strategies are implemented, and the resulting holograms are systemically assessed and compared with respect to background levels, image fidelities, holograms efficiencies, and polarization conversion ratios. Our work complements the methodologies available for designing multiplexed meta-holograms with versatile functionalities.

Impact of SARS-CoV-2 variants on the incidence of paediatric inflammatory multisystem syndrome (PIMS-TS).

Impact of SARS-CoV-2 variants on the incidence of paediatric inflammatory multisystem syndrome (PIMS-TS).

Strategic new product media planning under emergent channel substitution and synergy

New product and service introductions require careful joint planning of production and marketing campaigns. Consequently, they typically utilize multiple information channels to stimulate customer awareness and resultant word‐of‐mouth (WOM), availing of standard budget allocation tools. By contrast, when enacting strategic allocation decisions—which must align with other management imperatives—dividing expenditures across channels is far more complex. To this end, we formulate a multichannel demand model for new products (or services), amenable to analysis of inter‐ and intrachannel interaction patterns and with the WOM process, without building such interactions directly into the modeling framework. To address the notorious complexity of media planning over time, we propose a novel decomposition of the multichannel dynamic programming problem into two distinct “tiers”: the strategic tier addresses how to allocate total expenditure across channels, while the tactical tier studies how to allocate the channel‐specific budgets (determined in the strategic tier) over time periods. This decomposition enables optimal media strategies to sidestep the curse of dimensionality and renders the model pragmatically estimable. Strategic tier analysis suggests a variety of novel insights, primarily that funds should not be allocated based on (relative) channel effectiveness alone but also systematically aligned with WOM generation. Specifically, each channel can face a “chasm‐crossing” threshold, abruptly transitioning the adoption process from lead‐users to mass‐market penetration. Moreover, the model provides actionable managerial insights into when, and which, channel interactions are synergistic versus substitutive. Specifically, a channel's interactions are governed primarily by its own “leverage” (potential demand impact) and the WOM‐based demand “momentum” (market penetration) it can generate, affording a novel basis for channel typography and firm action. The modeling framework is illustrated by examining camera sales for two media channels (free‐standing inserts and radio) and their effects over 28 months. We use Bayesian machinery to estimate a highly flexible diffusion‐based model, along with forecasts, media plans, and both theoretical and empirically‐based qualitative insights.

State disinformation: emotions at the service of the cause

Disinformation is not only a phenomenon of modern democratic societies, but also a tool at the service of states. In the current communication ecosystem, politics and society interrelate in the face of a phenomenon characterised by multiple information channels and sources in which emotions now play a central role. In international relations, the expression of a state’s political will through charisma and populism are the chief aspects detected in the analysis of emotions in political science. This has led to the construction of a narrative based on security threats and the friend-enemy distinction, among other things. On the basis of an exhaustive literature review, this study offers an overview of the political and social factors underlying the use of emotions in disinformation as regards four aspects: politics, economy, diplomacy and security. Likewise, it identifies the main defining traits and behaviours of domestic and international audiences. The analysis and verification of the research question contribute to elaborate an international theory of emotionally driven disinformation which has begun to play a leading role in both academia and politics.

The magnitude of LFA-1/ICAM-1 forces fine-tune TCR-triggered T cell activation.

T cells defend against cancer and viral infections by rapidly scanning the surface of target cells seeking specific peptide antigens. This key process in adaptive immunity is sparked upon T cell receptor (TCR) binding of antigens within cell-cell junctions stabilized by integrin (LFA-1)/intercellular adhesion molecule–1 (ICAM-1) complexes. A long-standing question in this area is whether the forces transmitted through the LFA-1/ICAM-1 complex tune T cell signaling. Here, we use spectrally encoded DNA tension probes to reveal the first maps of LFA-1 and TCR forces generated by the T cell cytoskeleton upon antigen recognition. DNA probes that control the magnitude of LFA-1 force show that F>12 pN potentiates antigen-dependent T cell activation by enhancing T cell–substrate engagement. LFA-1/ICAM-1 mechanical events with F>12 pN also enhance the discriminatory power of the TCR when presented with near cognate antigens. Overall, our results show that T cells integrate multiple channels of mechanical information through different ligand-receptor pairs to tune function.

Bringing sustainable agricultural intensification practices and technologies to scale through campaign-based extension approaches: lessons from Africa Soil Health Consortium

ABSTRACT Sustainable agricultural intensification (SAI) practices have been developed with the aim of increasing agricultural productivity. However, most of them are not achieving their potential because of low adoption, linked to limited extension support to make them known and accessible by end-users. This paper reviews the effectiveness of the Africa Soil Health Consortium (ASHC) extension-based campaigns, contributing knowledge for formulating novel and cost-effective extension approaches. Results show that ASHC campaigns achieved scale of farmer reach and spurred adoption of promoted SAI technologies. Adoption levels for a range of practices were at least 20%, which favourably compares with reported adoption rates for the training and visit extension approach; 1-7% and 11-21% for complex and simple practices respectively. In comparison to a single channel, exposure to multiple communication approaches was associated with higher uptake of promoted practices and technologies, and also increased participation of men, women and youth, by addressing inherent differences in access to, proficiency with, and preferences of communication channels. Success factors associated with ASHC campaigns were; the deployment of multiple and complementary information channels; harnessing public-private partnerships to establish sustainable input supply chains; and development of localized content and fit-for-purpose information materials to facilitate information diffusion.

Code Division Multiplexing Inspired Dynamic Metasurface Holography

AbstractMetasurface holography is attracting increasing attention owing to its numerous advantages over conventional holography techniques, such as precise control of phase profiles, compact sizes, and multiple information channels via a single optical element. Metasurfaces provide a flexible platform for incorporating various multiplexing techniques. Inspired by code division multiplexing (CDM), which is widely employed in networking and wireless digital communications, metasurface holography for generating dynamic holographic images controlled by both the patterned beam profiles and polarization states is designed and realized in this study. Specifically, two orthogonal polarization states and 16 code bases of light illumination are combined to generate 32 independent channels. Only the correct code reference can decode the target image for a specific channel, providing encryption for information transportation. Meanwhile, the demonstrated metasurface holography with CDM can realize active modulation via a digital micromirror device. The proposed metasurface can be utilized to achieve dynamic information display, data storage, optical encryption, and other applications in optics.