Multiple Channels Research Articles

Myoelectric pattern recognition with virtual reality and serious gaming improves upper limb function in chronic stroke: a single case experimental design study

BackgroundMyoelectric pattern recognition (MPR) combines multiple surface electromyography channels with a machine learning algorithm to decode motor intention with an aim to enhance upper limb function after stroke. This study aims to determine the feasibility and preliminary effectiveness of a novel intervention combining MPR, virtual reality (VR), and serious gaming to improve upper limb function in people with chronic stroke.MethodsIn this single case experimental A-B-A design study, six individuals with chronic stroke and moderate to severe upper limb impairment completed 18, 2 h sessions, 3 times a week. Repeated assessments were performed using the Fugl-Meyer Assessment of Upper Extremity (FMA-UE), Action Research Arm Test (ARAT), grip strength, and kinematics of the drinking task at baseline, during, and post intervention. The results were analyzed by using visual analysis and Tau-U statistics.ResultsAll participants improved upper limb function assessed by FMA-UE (Tau-U 0.72–1.0), and five out of six improved beyond the minimal clinical important difference (MCID). Four participants improved ARAT and grip strength scores (Tau-U 0.84–1.0), with one reaching the MCID for ARAT. Three out of four participants in the kinematic analysis achieved improvements beyond the MCID in movement time and smoothness, two with a Tau-U > 0.90, and two participants improved trunk displacement beyond the MCID (Tau-U 0.68). Most participants showed some deterioration in the follow-up phase.ConclusionsMPR combined with VR and serious gaming is a feasible and promising intervention for improving upper limb function in people with chronic stroke.Trial Registration: ClinicalTrials.gov, reference number NCT04154371.

Multi-Color Channel Gamma Correction in Fringe Projection Profilometry

Three-dimensional shape measurement plays an important role in various fields. As a way of three-dimensional measurement, fringe projection profilometry (FPP) is widely used because of its non-contact, simple structure, and high stability. One of the key challenges affecting measurement accuracy is the gamma effect. With the development of FPP technology, multi-color channels are gradually applied to the measurement, and the response of different colors in the projector-camera system (pro-cam system) is not exactly the same. Therefore, more accurate gamma correction for different color channels is required. To solve this problem, a model of joint gamma correction for different color channels is proposed. In this model, the light is subdivided into three channels: red; green; and blue (RGB). In the pro-cam system, the different responses of different colors and the influence of background light intensity on gamma correction are comprehensively considered, and some error compensation is made for color crosstalk. Compared with the traditional gamma correction methods, the gamma correction method proposed in this paper is more accurate and has a larger effective working range after correction. This method is particularly beneficial in scenarios where multiple color channels are used for measurement, as it more accurately reflects the true measurement results for each channel. The effectiveness and accuracy of the method are validated through experiments.

Setting the tone: crossmodal emotional face-voice combinations in continuous flash suppression

Emotional stimuli are preferentially processed in the visual system, in particular, fearful faces. Evidence comes from unimodal studies with emotional faces, although real-life emotional encounters typically involve input from multiple sensory channels, such as a face paired with a voice. Therefore, in this study, we investigated how emotional voices influence preferential processing of co-occurring emotional faces. To investigate early visual processing, we used the breaking continuous flash suppression paradigm (b-CFS): We presented fearful, happy, or neutral faces to one eye, which were initially inaccessible to conscious awareness due to the predominant perception of a dynamic mask presented to the other eye. Faces were presented either unimodally or paired with non-linguistic vocalizations (fearful, happy, neutral). Thirty-six healthy participants were asked to respond as soon as the faces reached conscious awareness. We replicated earlier findings that fearful faces broke suppression faster overall, supporting a threat bias. Moreover, all faces broke suppression faster when paired with voices. Interestingly, faces paired with neutral and happy voices broke suppression the fastest, followed by faces with fearful voices. Thus, in addition to supporting a threat bias in unimodally presented fearful faces, we found evidence for crossmodal facilitation.

26-Week Repeated-Dose Toxicity Study of a Novel Antiarrhythmic Drug Sulcardine Sulfate in Sprague-Dawley Rats.

Sulcardine sulfate (Sul) is a novel antiarrhythmic agent blocking multiple channels and exhibits unique pharmacological properties such as lower APD-dependent prolongation and reduced arrhythmia risk. Sul is currently in Phase III clinical trials, yet studies on its long-term toxicological profile and potential target organs remain unexplored. This study investigated the related toxicity of Sul in Sprague Dawley (SD) rats through repeated oral administration for 26 weeks, followed by a 4-week recovery period. Consistent with the clinical intended mode of administration, Sul was administered via oral gavage at daily doses of 0, 175, 350, and 700/525 mg/kg in rats. On account of clinically observed body weight loss of male and female rats in the high-dose group compared with the control group, with one female rat in the high-dose group dying after 8 weeks of administration, the high dose was adjusted to 525 mg/kg. Aspartate aminotransferase (AST) and alanine aminotransferase (ALT) levels in male rats significantly increased in the medium- and high-dose groups, whereas female rats in these groups showed a significant rise in alkaline phosphatase (ALP) levels, accompanied by varying degrees of weight gain in the liver and lungs. Additionally, brownish-red pigment deposition was observed in hepatocytes and Kupffer cells across all dosing groups, along with foam cell deposition in the alveolar cavities. Concomitant toxicokinetics showed that the drug accumulated to some extent in the animals. Consequently, the liver and lungs were identified as potential target organs, and the no observed adverse effect level (NOAEL) was determined to be 175 mg/kg.

Implementing an In-House Digital Acknowledgment Solution for SAP MRA Returns in the Pharmaceutical Industry

This article comprehensively implements an in-house digital acknowledgment solution for pharmaceutical returns management using the SAP MRA (Material Returns Authorization) system. The solution addresses critical challenges in the pharmaceutical industry's return process, including regulatory compliance, operational efficiency, and cost optimization. Integrating SAP S/4 HANA, SAP PI/PO, and Microsoft Outlook provides a robust framework for handling return requests through multiple channels while maintaining stringent security standards. The implementation demonstrates significant improvements in processing times, customer satisfaction, and cost reduction through automation and digital transformation. The solution's architecture emphasizes scalability, security, and performance optimization, incorporating advanced features such as digital signatures, real-time monitoring, and automated workflow management. This article details the technical configuration, system architecture, end-to-end process implementation, and security framework while highlighting the business impact and future enhancement opportunities aligned with Industry 4.0 principles.

Ultra-miniaturized Bloch mode metasplitters for one-dimensional grating waveguides.

We present, for the first time, to our knowledge, power splitters with multiple channel configurations in one-dimensional grating waveguides (1DGWs) that maintain crystal lattice-sensitive Bloch mode profiles without perturbation across all output channels, all within an ultra-miniaturized footprint of just 2.1 × 2.2 μm2. This novel capability reduces the need for transition regions, simplifies multi-channel configurations of 1DGWs, and maximizes the effective use of chip area. The pixelated metamaterial approach, integrated with a time-domain heuristic algorithm, is utilized to concurrently achieve broadband operation, optimized dispersion control, and minimal loss. We experimentally demonstrate that the 1 × 2 and 1 × 3 metasplitters achieve average minimum losses per channel of 3.80 dB and 5.36 dB, respectively, which are just 0.80 dB and 0.59 dB above ideal splitting. The measurements for both designs demonstrate a 1 dB bandwidth of 15 nm, with excellent uniformity across all output channels. These versatile metasplitter designs can serve as fundamental building blocks for ultrahigh-bandwidth, densely integrated photonic circuits and in scenarios where slow light is essential.

Feδ+ diaspora titanium dioxide and graphene: A study of conductive powder materials and coating applications.

Developing new conductive primers to ensure electrostatic spraying is crucial in response to the call for lightweight production of new energy vehicles. We report a stabilized material, Fe-T/G, of Fe-doped TiO2 composite graphene synthesized by a simple hydrothermal and electrostatic self-assembly method. The resistivity decreases from 0.9165Ω·cm to 0.0943Ω·cm for T/G. XPS and EPR confirm that Fe3+ is doped into the TiO2 lattice to generate OVs, and Feδ+ is introduced to activate the surrounding Fe-Ti active sites to break the obstruction of the Ti-O bond and build the Ti-O-C and Feδ+-O-C bonds between TiO2 and graphene to connect the two tightly. Multiple electron transfer channels promote Feδ+ impurity energy levels in the TiO2 valence and conduction bands to build electron leaping pathways, enhancing the electron transport ability. Based on this, Fe-T/G can be used as a conductive coating material to develop various insulator surfaces. With Fe-T/G powder material and PVDF, a conductive primer coating can be made and overlaid on a plastic plate to simulate actual applications. The resistance can still be maintained below 25Ω·cm. Through contact angle experiments, it has been confirmed that the superhydrophobic surface has a water contact angle of 142.8°, with self-cleaning potential.

A microfluidic system for the cultivation of cyanobacteria with precise light intensity and CO2 control: enabling growth data acquisition at single-cell resolution.

Quantification of cell growth is central to any study of photoautotrophic microorganisms. However, cellular self-shading and limited CO2 control in conventional photobioreactors lead to heterogeneous conditions that obscure distinct correlations between the environment and cellular physiology. Here we present a microfluidic cultivation platform that enables precise analysis of cyanobacterial growth with spatio-temporal resolution. Since cyanobacteria are cultivated in monolayers, cellular self-shading does not occur, allowing homogeneous illumination and precise knowledge of the photon-flux density at single-cell resolution. A single chip contains multiple channels, each connected to several hundred growth chambers. In combination with an externally applied light gradient, this setup enables high-throughput multi-parameter analysis in short time. In addition, the multilayered microfluidic design allows continuous perfusion of defined gas mixtures. Transversal CO2 diffusion across the intermediate polydimethylsiloxane membrane results in homogeneous CO2 supply, with a unique exchange-surface to cultivation-volume ratio. Three cyanobacterial model strains were examined under various, static and dynamic environmental conditions. Phase-contrast and chlorophyll fluorescence images were recorded by automated time-lapse microscopy. Deep-learning trained cell segmentation was used to efficiently analyse large image stacks, thereby generating statistically reliable data. Cell division was highly synchronized, and growth was robust under continuous illumination but stopped rapidly upon initiating dark phases. CO2-Limitation, often a limiting factor in photobioreactors, was only observed when the device was operated under reduced CO2 between 50 and 0 ppm. Here we provide comprehensive and precise data on cyanobacterial growth at single-cell resolution, accessible for further growth studies and modeling.

A Cross-Layer Game-Theoretic Approach to Resilient Control of Networked Switched Systems Against DoS Attacks.

This article investigates the resilient control strategies of networked switched systems (NSSs) against denial-of-service (DoS) attacks and external disturbance. In the network layer, both the defender and the attacker allocate energy over multiple channels. Considering the impact of switching characteristic in the physical layer on the network layer, a dynamic regulating factor is proposed to adjust the total energy of the defender. To optimize the signal-to-interference-noise ratio and energy consumption simultaneously at each player's side, a multiobjective game problem is formulated. Furthermore, a nondominated sorting genetic algorithm framework is employed, incorporating the knee point selection mechanism to attain the Pareto-Nash equilibrium, based on which the optimal defense strategy can be derived to achieve resilience against DoS attacks. In the physical-layer, taking the dynamic packet loss caused by DoS attacks and external disturbance into account, an H∞ minimax controller containing control inputs and the switching signal is designed to guarantee the optimal performance for NSSs through the dynamic game-theoretic approach. Finally, the networked continuous stirred tank reactor system is provided to verify the effectiveness of the proposed method.

Phytosomes Loaded with Mastoparan-M Represent a Novel Strategy for Breast Cancer Treatment.

Mastoparan-M (Mast-M) has cytotoxic effects on various tumor cells in vitro, including liver cancer and colorectal cancer. However, the anti-tumor mechanism of Mast-M remains unclear and its potential for anti-tumor therapy has not been investigated. Herein, we aimed to develop a novel phytosome formulation loaded with Mast-M and evaluate its efficacy against breast cancer both in vitro and in vivo. Furthermore, we investigated the underlying anti-tumor mechanisms of Mast-M. The synthesis of Phy-Mast-M involved a co-solvent technique, followed by solvent evaporation. Its anti-tumor mechanism was investigated using CCK-8, clone formation, and apoptosis assays. Subsequently, the biodistribution and anti-tumor efficacy of Phy-Mast-M were assessed in vivo using the 4T1 tumor-bearing mouse model. Finally, the safety of Phy-Mast-M was evaluated in vivo. The prepared Phy-Mast-M demonstrated an exceptional monodisperse size distribution (125.67 ± 45.79 nm), and exhibited excellent stability under different physiological conditions. Phy-Mast-M could inhibit 4T1 cells growth through multiple channels, including arresting cell growth cycle and disturbing mitochondrial membrane integrity. Phy-Mast-M proved significantly higher accumulation at tumor sites in a tumor-bearing mouse model as compared to free Mast-M. Moreover, in vivo anti-tumor studies demonstrated that Phy-Mast-M exhibited superior curative inhibitory effects on tumor growth and favorable biocompatibility. Phy-Mast-M demonstrates significant anti-tumor activity both in vitro and in vivo. Moreover, its potential for clinical translation suggests promising prospects for cancer therapy, offering more drug options for breast cancer patients.

Byzantine Multiple Access Channels—Part II: Communication With Adversary Identification

Byzantine Multiple Access Channels—Part II: Communication With Adversary Identification

Construction of proton exchange membrane with high proton conductivity based on 3D self-assembly structures as multiple proton transport channels

Proton exchange membranes are currently of a great interest due to their tunable proton transport channels in design. However, the construction of proton transport channels in composite membranes still encounters enormous challenges. In this study, a series of composite membranes composed of nanocomposites reinforced with electrostatically self-assembly of zirconium phosphate (ZrP) and poly(diallyldimethylammonium chloride) (PDDA)modified sulfonated halloysite (PSHNT) were designed and prepared. Further, long-range ordered proton transport channels were constructed in the membrane owing to synergistic effect of ZrP and PSHNT. It is revealed that acidic groups of ZrP nanoparticles and PSHNT yield more acidic sites for effective proton transport, and hollow tubular halloysite creates a fast channel for proton transport via a vehicle-type mechanism. The excellent hydrophilicity of ZrP/PSHNT and their good dispersion in polymer matrices result in a much higher water absorption of 45.5% and a lower swelling rate of 6.4% at 80⁰C. More impressively, SPI-ZrP/PSHNT-6 exhibits a remarkable proton conductivity of 288.2 mS cm-1 at 80°C under hydrated conditions. In addition, due to its excellent proton conductivity, a high peak power density up to 230.2 mW cm-2 has been achieved in H2-Air fuel cell. The excellent material performance of such proton exchange membranes in this study paves a new way towards the commercialization of high-performance proton exchange membranes in future applications for hydrogen fuel cell.

Ultrafast structural dynamics of UV photoexcited cis,cis-1,3-cyclooctadiene observed with time-resolved electron diffraction.

Conjugated diene molecules are highly reactive upon photoexcitation and can relax through multiple reaction channels that depend on the position of the double bonds and the degree of molecular rigidity. Understanding the photoinduced dynamics of these molecules is crucial for establishing general rules governing the relaxation and product formation. Here, we investigate the femtosecond time-resolved photoinduced excited-state structural dynamics of cis,cis-1,3-cyclooctadiene, a large-flexible cyclic conjugated diene molecule, upon excitation with 200 nm using mega-electron-volt ultrafast electron diffraction and trajectory surface hopping dynamics simulations. We tracked the photoinduced structural changes from the Franck-Condon region through the conical intersection seam to the ground state. Our findings revealed a novel primary reaction coordinate involving ring distortion, where the ring stretches along one axis and compresses along the perpendicular axis. The nuclear wavepacket remains compact along this reaction coordinate until it reaches the conical intersection seam, and it rapidly spreads as it approaches the ground state, where multiple products are formed.

Optimal path of China's economic structure and energy demand to carbon neutrality

The changing economic structure may impact future trends in energy demand and carbon emissions since various economic production sectors have differentiated energy dependencies. Compared to consumer goods sector, investment goods sector usually has higher energy intensity, and its energy is weakly substitutable with other input factors. This paper constructs an energy-economy dynamic optimization model (EED) with heterogeneous energy dependences between investment and consumer goods sectors, and applies it to analyze the structural transformation of the Chinese economy and energy prospect. The optimization model generates a drop of investment share in GDP to 27 % in 2060, 15 percentage points lower than in 2020. Along the above transformation path, the peak demand for energy is expected to be between 6.1 and 6.3 billion (tce) in the baseline scenario, and overall energy intensity by 2060 will be 54 % lower than in 2020. The forecasting results also subject to uncertainties including technological progress. Moreover, we find that macroeconomic policy to promote consumption can help alleviate energy and environmental pressures. Thus, the development of the Chinese economy in the future needs to combine multiple channels such as promoting consumption and improving investment efficiency.

Evolving Attribution Models in Digital Advertising: Balancing Clicks, Views and Customer Journeys

As digital advertising continues to grow, accurately measuring the impact of marketing efforts across multiple channels has become a complex but essential task. Traditional attribution models like last-touch fail to capture the diverse ways consumers interact with ads before converting. Multi-touch attribution (MTA) models offer a solution by distributing credit across various interactions, reflecting the true influence of each touchpoint. This paper provides a comprehensive review of popular attribution models, including linear, time-decay, U-shaped, and custom models, assessing their strengths and limitations. Additionally, it highlights the importance of integrating both click-through and view-through metrics to understand customer engagement more fully. By exploring these models, this paper aims to guide marketers in selecting the most effective attribution strategies to optimize ad spend, improve campaign performance, and gain a holistic view of customer journeys.

Immediate and High-Precision Hypocentral Determination for Earthquake Early Warning Applications Using Distributed Acoustic Sensing

ABSTRACT Earthquake early warning (EEW) systems in Japan use data from as little as a single observation point, even at the stage in which only the P wave is detected at one point, to estimate the epicentral distance and magnitude to rapidly issue a warning. This approach aims to maximize lead time but has the drawback of significant estimation errors (epicentral distance: half to double, back azimuth: ±30°). Using distributed acoustic sensing (DAS) with a dense network of observation points allows for rapid and precise earthquake hypocenter determination, significantly reducing estimation errors compared to single-station methods in EEW system. However, no prior studies have investigated the immediacy of using DAS data—which is indispensable for early earthquake warnings. Therefore, we examined the use of DAS for rapid and precise hypocenter determination with the goal of integrating it into the EEW system. We used fiber-optic cables along the Kyushu Shinkansen to analyze strain-rate waveforms, detect P waves, and determine earthquake hypocenter locations. We detected P waves using short-term average /long-term average simultaneously across multiple channels. We then determined the epicenter using Hypomh. For rapid determination of the hypocenter location after P-wave detection, we assessed the hypocenter location each time the number of P-wave detection points increased by 20. For earthquakes with an epicentral distance of less than 50 km, we successfully determined the hypocenter within 12 km of the Japan Meteorological Agency-reported location. This was achieved by identifying the point where the sum of the maximum-likelihood estimation errors was minimized within 2 s of the initial P-wave detection in any channel. The findings suggest that an EEW system using DAS holds potential as a powerful tool to provide rapid and accurate hypocenter information, especially for near-field earthquakes that occur directly beneath populated areas, where lead times are short, and the potential damage is substantial.

Multiple attention channels aggregated network for multimodal medical image fusion.

In clinical practices, doctors usually need to synthesize several single-modality medical images for diagnosis, which is a time-consuming and costly process. With this background, multimodal medical image fusion (MMIF) techniques have emerged to synthesize medical images of different modalities, providing a comprehensive and objective interpretation of the lesion. Although existing MMIF approaches have shown promising results, they often overlook the importance of multiscale feature diversity and attention interaction, which are essential for superior visual outcomes. This oversight can lead to diminished fusion performance. To bridge the gaps, we introduce a novel approach that emphasizes the integration of multiscale features through a structured decomposition and attention interaction. Our method first decomposes the source images into three distinct groups of multiscale features by stacking different numbers of diverse branch blocks. Then, to extract global and local information separately for each group of features, we designed the convolutional and Transformer block attention branch. These two attention branches make full use of channel and spatial attention mechanisms and achieve attention interaction, enabling the corresponding feature channels to fully capture local and global information and achieve effective inter-block feature aggregation. For the MRI-PET fusion type, MACAN achieves average improvements of 24.48%, 27.65%, 19.24%, 27.32%, 18.51%, and 10.33% over the compared methods in terms of Qcb, AG, SSIM, SF, Qabf, and VIF metrics, respectively. Similarly, for the MRI-SPECT fusion type, MACAN outperforms the compared methods with average improvements of 29.13%, 26.43%, 18.20%, 27.71%, 16.79%, and 10.38% in the same metrics. In addition, our method demonstrates promising results in segmentation experiments. Specifically, for the T2-T1ce fusion, it achieves a Dice coefficient of 0.60 and a Hausdorff distance of 15.15. Comparable performance is observed for the Flair-T1ce fusion, with a Dice coefficient of 0.60 and a Hausdorff distance of 13.27. The proposed multiple attention channels aggregated network (MACAN) can effectively retain the complementary information from source images. The evaluation of MACAN through medical image fusion and segmentation experiments on public datasets demonstrated its superiority over the state-of-the-art methods, both in terms of visual quality and objective metrics. Our code is available at https://github.com/JasonWong30/MACAN.

Detection of Human Bladder Epithelial Cancerous Cells with Atomic Force Microscopy and Machine Learning.

The development of noninvasive methods for bladder cancer identification remains a critical clinical need. Recent studies have shown that atomic force microscopy (AFM), combined with pattern recognition machine learning, can detect bladder cancer by analyzing cells extracted from urine. However, these promising findings were limited by a relatively small patient cohort, resulting in modest statistical significance. In this study, we corroborated the AFM technique's capability to identify bladder cancer cells with high accuracy using a controlled model system of genetically purified human bladder epithelial cell lines, comparing cancerous cells with nonmalignant controls. By processing AFM adhesion maps through machine learning algorithms, following previously established methods, we achieved an area under the ROC curve (AUC) of 0.97, with 91% accuracy in cancer cell identification. Furthermore, we enhanced cancer detection by incorporating multiple imaging channels recorded with AFM operating in Ringing mode, achieving an AUC of 0.99 and 93% accuracy. These results demonstrated strong statistical significance (p < 0.0001) in this well-defined model system. While this controlled study does not capture the biological variation present in clinical settings, it provides independent support for AFM-based detection methods and establishes a rigorous technical foundation for further clinical development of AFM imaging-based methods for bladder cancer detection.

Analysis of Marketing Strategies for New Products

Choosing the marketing strategy analysis of a new product as a topic is an interesting and practical option. It will not only help me to understand consumer behavior and psychology, but also help me to study market research and positioning. As well as exploring branding and communication strategies at a deeper level. The purpose of this thesis is to analyze the marketing strategy of a new product and explore its positioning and promotion effect in the market competition. First, the target market and product differentiation advantages are identified through market research and consumer demand analysis. Then, the choice of multiple marketing channels is examined, including online and offline advertising, social media promotion, KOL cooperation, and content marketing. The paper also evaluates the impact of pricing strategies, promotional activities, and brand positioning on consumer purchase decisions. Ultimately, case studies and data analysis validate the effectiveness of the selected strategies and suggest further optimization to increase market share and brand awareness.

Crisis Communication through Social Media Platforms by Malaysian Indian Agencies

Crisis communication must be prompt, accurate, and accessible to all. Government agencies often use multiple channels to disseminate critical information quickly. Social media has been helpful in informing all stakeholders about institutional short- and long-term interests as well as raising public health awareness. Mitigative strategies and crisis response are improved when crisis communication is tailored to the social, cultural, and economic context of minority communities. Identifying and directing communications that are unique to a group, however, presents difficulties when a crisis arises. Therefore, this research aims to investigate how the Malaysian Indian Agencies (MIAs), use social media to reach out to minority Malaysian Indians to disseminate information during the COVID-19 pandemic. 16 MIAs with active social media pages, Facebook and Twitter, registered with the Registrar of Societies (ROS) were shortlisted. Content analysis was performed on social media posts which were published from 18 March 2020 until 31 August 2020. The posts were categorized based on crisis communication strategies, outlined based on past studies. Subsequently, a semi-structured interview was conducted among the urban middle class and urban poor Indian residents in the Klang Valley. Findings reveal a notable paucity in the proactive presence of these agencies on social media platforms, indicating limited engagement in disseminating essential information during a crisis. While Facebook and Twitter were used, diverse channels like WhatsApp contributed to reaching out to the non-urban Indians. The use of Tamil shows efforts to overcome language barriers, supporting government initiatives to control the pandemic while potentially boosting the agencies’ political influence among Tamil-speaking communities. This study underscores the need for government agencies and community organizations to adapt their outreach methods to ensure all segments of the population, especially linguistic minorities, have access to timely and accurate information during a crisis.