Separate Channels Research Articles

High-temperature thermal disturbance elimination method based on multi-channel extraction and correction.

Digital image correlation (DIC) technology has been widely used in high-temperature measurement fields. However, due to the complexity of high-temperature environments, there are many interference factors that limit the development of high-temperature DIC technology, among which thermal disturbance is one of the most significant factors that severely affects the measurement accuracy of high-temperature DIC. In this paper, a multi-channel separation technique combined with a low-cost laser speckle device is proposed to eliminate thermal disturbance errors in high-temperature DIC measurements. First, a blue laser speckle generation system is independently designed to produce the most suitable speckle particles, and the best laser speckle is determined and projected onto the blue background white spot pattern. Then a green LED illuminates the sample to provide illumination for the sample's own grayscale characteristics. A color camera collects photos, and the obtained images are processed with channel separation to extract and calculate the displacement of different channels. Finally, the displacement fields of the green and blue channels are subtracted to separate the thermal disturbance error and correct the measurement values. In this paper, a laser speckle projection system is first assembled, followed by a comprehensive evaluation of the projected speckle and, finally, a DIC experimental system is constructed for verification experiments at both room temperature and high temperature, and the corrected values are compared with the true values. The results show that the corrected values are highly consistent with the true values, which verifies the reliability of the proposed method.

Controlling the droplet cell environment in scanning electrochemical cell microscopy (SECCM) via migration and electroosmotic flow.

Scanning electrochemical cell microscopy (SECCM) is a powerful nanoscale electrochemical technique that advances our understanding of heterogeneity at the electrode-electrolyte interface. In SECCM, dual-channel nanopipettes can serve as the probe, and a voltage bias between the channels can control the local electrolyte environment inside the droplet cell via migration and electroosmotic flow (EOF) between the channels, enabling applications including controlled electrodeposition of bimetallic nanoparticles with variable compositions. Herein, we show quantitatively how the voltage bias between the channels modulates the local electrolyte environment via experiment and finite element modeling. Experimentally, redox molecules of different charges (e.g., ferrocene derivatives and Ruthenium(III) hexamine) were filled in separate channels, where their limiting currents at the substrate electrode were used to distinguish the contribution of migration and EOF. Furthermore, EOF was visualized by fluorescence imaging. Finite element models were developed to further validate the experimental results quantitively. We showed that migration is affected by the charge number of the redox molecule. Meanwhile, EOF is affected by the surface charge on the wall of the nanopipette and the location of the slipping plane inside the electrical double layer, which can be tuned by the solution pH and the ionic strength of the electrolyte, respectively. The experimentally validated model can guide the precise modulation of droplet cell environment in SECCM, potentially enabling new scanning modes in SECCM.

Multi-lineage heart-chip models drug cardiotoxicity and enhances maturation of human stem cell-derived cardiovascular cells.

Cardiovascular toxicity causes adverse drug reactions and may lead to drug removal from the pharmaceutical market. Cancer therapies can induce life-threatening cardiovascular side effects such as arrhythmias, muscle cell death, or vascular dysfunction. New technologies have enabled cardiotoxic compounds to be identified earlier in drug development. Human induced pluripotent stem cell (hiPSC)-derived cardiomyocytes (CMs) and vascular endothelial cells (ECs) can screen for drug-induced alterations in cardiovascular cell function and survival. However, most existing hiPSC models for cardiovascular drug toxicity utilize two-dimensional, immature cells grown in static culture. Improved in vitro models to mechanistically interrogate cardiotoxicity would utilize more adult-like, mature hiPSC-derived cells in an integrated system whereby toxic drugs and protective agents can flow between hiPSC-ECs that represent systemic vasculature and hiPSC-CMs that represent heart muscle (myocardium). Such models would be useful for testing the multi-lineage cardiotoxicities of chemotherapeutic drugs such as VEGFR2/PDGFR-inhibiting tyrosine kinase inhibitors (VPTKIs). Here, we develop a multi-lineage, fully-integrated, cardiovascular organ-chip that can enhance hiPSC-EC and hiPSC-CM functional and genetic maturity, model endothelial barrier permeability, and demonstrate long-term functional stability. This microfluidic organ-chip harbors hiPSC-CMs and hiPSC-ECs on separate channels that can be subjected to active fluid flow and rhythmic biomechanical stretch. We demonstrate the utility of this cardiovascular organ-chip as a predictive platform for evaluating multi-lineage VPTKI toxicity. This study may lead to the development of new modalities for the evaluation and prevention of cancer therapy-induced cardiotoxicity.

A dual photocarrier separation channel in CdS/ZnS for outstanding photocatalytic hydrogen evolution

The role of pre-adsorption in the conversion of a less soluble precipitate to a more soluble precipitate is explored and the CdS/ZnS carrier separation pathway is scrutinised, suggesting the existence of a dual-carrier separation channel.

STABILITY ROBUSTNESS OF CONTROL SYSTEMS OF MULTIROTOR UNMANNED AERIAL VEHICLES

Multirotor unmanned aerial vehicles (UAVs) are broadly used in various military and civilian areas and tasks. In real flights of the multirotor UAVs, certain unexpected situations may occur, which can lead to improper functionality and even failures of elements or devices of the UAV’s control system. In some cases, this can even lead to the complete collapse of the UAV. Therefore, the safety of UAV flights is nowadays of prime importance. A method of analysis of the stability robustness of the UAV’s control systems with respect to the parameters multiplicative uncertainties (or perturbations), including possible efficiency degradation of DC motors, is proposed in the paper. Stability robustness is determined by a simple graphical procedure on the complex plane of the Nyquist or Nichols hodographs of the control system’s separate channels. That procedure is quite similar to the well-known classical feedback control procedure of determining the peak gain of the single-input, single-output closed-loop control system by the Nyquist hodograph of the open-loop system. A numerical example illustrating the proposed method is given.

PSRDP: A Parallel Processing Method for Pulsar Baseband Data

To address the problem of real-time processing of ultra-wide bandwidth pulsar baseband data, we designed and implemented a pulsar baseband data processing algorithm (PSRDP) based on GPU parallel computing technology. PSRDP can perform operations such as baseband data unpacking, channel separation, coherent dedispersion, Stokes detection, phase and folding period prediction, and folding integration in GPU clusters. We tested the algorithm using the J0437-4715 pulsar baseband data generated by the CASPSR and Medusa backends of the Parkes, and the J0332+5434 pulsar baseband data generated by the self-developed backend of the NanShan Radio Telescope. We obtained the pulse profiles of each baseband data. Through experimental analysis, we have found that the pulse profiles generated by the PSRDP algorithm in this paper are essentially consistent with the processing results of Digital Signal Processing Software for Pulsar Astronomy (DSPSR), which verified the effectiveness of the PSRDP algorithm. Furthermore, using the same baseband data, we compared the processing speed of PSRDP with DSPSR, and the results showed that PSRDP was not slower than DSPSR in terms of speed. The theoretical and technical experience gained from the PSRDP algorithm research in this article lays a technical foundation for the real-time processing of QTT (Qi Tai radio Telescope) ultra-wide bandwidth pulsar baseband data.

Designing biomimetic two-dimensional channels for uranium separation from seawater.

Efficient separation of uranium from seawater stands as a pivotal challenge. This study unveils an approach focusing on the ingenious design of biomimetic two-dimensional (2D) membranes tailored explicitly for this purpose. Leveraging the unique interplay of DNA strands housing U aptamers, pH-responsive i-motifs, and poly A(10) segments ingeniously embedded within graphene oxide membranes, a distinctive biomimetic 2D channel is engineered. The strategic integration of these bio-inspired elements enables dynamic adjustment of interlayer spacing, augmenting both the permeability of the membrane and the selectivity of the aptamer for uranyl ions. During the separation process, the encounter between uranyl ions and the enhanced aptamer within the interlayers initiates a crucial interaction, triggering a specific concentration polarization mechanism. This mechanism stands as the cornerstone for achieving a highly selective separation of uranyl ions from the vast and complex matrix of seawater. The membrane exhibits excellent performance in real seawater, with a rejection rate of uranyl ions of ≈100% and sustained selectivity of uranyl ions over ten cycles. Importantly, the selectivity of uranium and vanadium can reach 14.66. The significance of this research lies not only in the effective separation of uranyl ions but also in showcasing the broader applicability of 2D membrane design in chemical engineering.

A novel MIMO BMS design for user-friendly replacement of batteries

The proposed design introduces an innovative Multiple-Input Multiple-Output (MIMO) based Battery Management System (BMS) design that facilitates convenient battery replacement in battery packs. The technology allows for real-time monitoring of battery health through separate communication channels, making it easier to identify and replace batteries without the need for complicated disassembly. Granular control of charging/discharging and cell balancing allows for the achievement of enhanced safety and increased pack performance.

A liquid metal based, integrated parallel electroosmotic micropump cluster drive system.

The application of liquid metal in a microfluidic system enables the fabrication of highly integrated on-chip electroosmotic micropumps (EOPs). In this work, a low-voltage driveable integrated parallel EOP cluster drive system is proposed. This system consists of two layers, a branch-channel layer and a trunk-channel layer. The lower branch-channel layer contains separate parallel pumping channels and a pair of comb liquid metal electrodes. The separated branch channels are connected together through the trunk channels in the upper layer. With this structural arrangement, the parallel micropumps form an integrated micropump cluster for larger pumping capacity. The distance between the pumping channel and the electrode next to it is controlled to 20 μm. To guide the pump design, parametric studies are performed and fully discussed. According to the experimental results, the micropump cluster can be driven at a low voltage of 0.5 V, and the flow rate reaches 274 nL min-1 at 5 V. In addition, the paper finally proposes an electrode protection strategy and an integrated pump-valve drive system which is expected to solve the shortcoming of electroosmotic pumps in terms of long-time storage and driving.

FPGA-based Lightweight QDS-CNN System for sEMG Gesture and Force Level Recognition.

Deep learning (DL) has been used for electromyographic (EMG) signal recognition and achieved high accuracy for multiple classification tasks. However, implementation in resource-constrained prostheses and human-computer interaction devices remains challenging. To overcome these problems, this paper implemented a low-power system for EMG gesture and force level recognition using Zynq architecture. Firstly, a lightweight network model structure was proposed by Ultra-lightweight depth separable convolution (UL-DSC) and channel attention-global average pooling (CA-GAP) to reduce the computational complexity while maintaining accuracy. A wearable EMG acquisition device for real-time data acquisition was subsequently developed with size of 36mm×28mm×4mm. Finally, a highly parallelized dedicated hardware accelerator architecture was designed for inference computation. 18 gestures were tested, including force levels from 22 healthy subjects. The results indicate that the average accuracy rate was 94.92% for a model with 5.0k parameters and a size of 0.026MB. Specifically, the average recognition accuracy for static and force-level gestures was 98.47% and 89.92%, respectively. The proposed hardware accelerator architecture was deployed with 8-bit precision, a single-frame signal inference time of 41.9μs, a power consumption of 0.317W, and a data throughput of 78.6 GOP/s.

Multiscale Spatial-Temporal Feature Fusion Neural Network for Motor Imagery Brain-Computer Interfaces.

Motor imagery, one of the main brain-computer interface (BCI) paradigms, has been extensively utilized in numerous BCI applications, such as the interaction between disabled people and external devices. Precise decoding, one of the most significant aspects of realizing efficient and stable interaction, has received a great deal of intensive research. However, the current decoding methods based on deep learning are still dominated by single-scale serial convolution, which leads to insufficient extraction of abundant information from motor imagery signals. To overcome such challenges, we propose a new end-to-end convolutional neural network based on multiscale spatial-temporal feature fusion (MSTFNet) for EEG classification of motor imagery. The architecture of MSTFNet consists of four distinct modules: feature enhancement module, multiscale temporal feature extraction module, spatial feature extraction module and feature fusion module, with the latter being further divided into the depthwise separable convolution block and efficient channel attention block. Moreover, we implement a straightforward yet potent data augmentation strategy to bolster the performance of MSTFNet significantly. To validate the performance of MSTFNet, we conduct cross-session experiments and leave-one-subject-out experiments. The cross-session experiment is conducted across two public datasets and one laboratory dataset. On the public datasets of BCI Competition IV 2a and BCI Competition IV 2b, MSTFNet achieves classification accuracies of 83.62% and 89.26%, respectively. On the laboratory dataset, MSTFNet achieves 86.68% classification accuracy. Besides, the leave-one-subject-out experiment is performed on the BCI Competition IV 2a dataset, and MSTFNet achieves 66.31% classification accuracy. These experimental results outperform several state-of-the-art methodologies, indicate the proposed MSTFNet's robust capability in decoding EEG signals associated with motor imagery.

I2-FaçadeNet: An Illumination-invariant Façade Recognition Network Leveraging Sparsely Gated Mixture of Multi-color Space Experts for Aerial Oblique Imagery

Façade image recognition under complex illumination conditions is crucial for various applications, including urban three-dimensional modeling and building identification. Existing methods relying solely on Red-Green-Blue (RGB) images are prone to texture ambiguity in complex illumination environments. Furthermore, façades display varying orientations and camera viewing angles, resulting in performance issues within the RGB color space. In this study, we introduce an illumination-invariant façade recognition network (I2-FaçadeNet) that leverages sparsely gated multi-color space experts for enhanced façade image recognition in challenging illumination environments. First, RGB façade images are converted into multi-color spaces to eliminate the ambiguous texture in complex illumination. Second, we train expert networks using separate channels of multi-color spaces. Finally, a sparsely gated mechanism is introduced to manage the expert networks, enabling dynamic activation of expert networks and the merging of results. Experimental evaluations leveraging both the International Society for Photogrammetry and Remote Sensing benchmark data sets and the Shenzhen data sets reveal that our proposed I2 -FaçadeNet surpasses various depths of ResNet in façade recognition under complex illumination conditions. Specifically, the classification accuracy for poorly illuminated façades in Zurich improves by nearly 8%, while the accuracy for over-illuminated areas in Shenzhen increases by approximately 3%. Moreover, ablation studies conducted on façade images with complex illumination indicate that compared to traditional RGB-based ResNet, the proposed network achieves an accuracy improvement of 3% to 4% up to 100% for overexposed images and an accuracy improvement of 3% to 10% for underexposed images.

Аналіз одношарового руху зернового матеріалу у вертикальному пневмосепараційному каналі

The separation of grain and light impurities in a vertical pneumatic separation channel with an increase in its capacity occurs under rather difficult conditions, since the thickness of the grain flow increases, which leads to a redistribution of particles of grain material and reduces the probability of passing light impurities through the grain layers and their release into the sedimentation chamber. To increase the productivity of vertical pneumatic separation channels, it is necessary to create conditions for single-layer placement of grain material in the separation zone at a distance that excludes the interaction of other layers of grain input. This will allow the majority of grain particles to be in the same conditions and increase the percentage of probability of separation into the sedimentation chamber to the maximum value. Therefore, a theoretical flow analysis aimed at studying the interaction of grain mixture particles with the air flow, taking into account the single-layer arrangement of several grain layers and the contamination of the air flow with light impurities in the separation zone, is a rather important task. Theoretical dependences have been obtained that allow substantiating the main parameters of the pneumatic separation channel and determine the residence time of a grain particle in the separation zone, taking into account the clogging of the air flow. For a grain material of mass characterized by the values of the windage coefficient kз = 0.075...0.12 for full grain, kз = 0.11...0.14 for substandard grain, and kз = 0.125...0.55 for light impurities, it is possible to clearly separate the grain mixture into fractions by setting the appropriate parameters and operating modes of the pneumatic separation channel under the condition of a single-layer multilevel input. Due to the selection of rational parameters of the feeding devices for delivering the material into the separation zone and establishment of appropriate aerodynamic modes of air flow, it is possible to separate up to 96% of light impurities from the grain material, while ensuring minimal losses of full grain to waste.

Peripherally Inserted Central Catheter (PICC) Guidelines - Nursing Perspective

A Peripherally Inserted Central Catheter PICC is a form of intravenous line that grants access to the central venous system. It is inserted through a vein in the arm and then carefully advanced until it reaches a large vein close to the heart. The PICC has one two or three separate channels called lumens that can be used for different purposes such as blood sampling medication administration fluid infusion and other interventions. Each lumen has a cap and a connector that prevents contamination and allows needle-free access. Venous access is crucial for many patients who need frequent or complex treatments such as critically ill patients who require blood tests drugs that affect blood pressure fluid replacement long-term antibiotics and other indications.

Guidance on configuring volumetric targets for AUT using CIVA

The main standards relating to AUT (Automated Ultrasonic Testing) using zonal discrimination have long had requirements to incorporate separate channels dedicated to detecting volumetric flaws. However, none of the standards specify how the beams are to be configured. The instructions are quite generic indicating that the channels are to ensure the complete volumetric examination of the weld through-thickness. Scattering flat bottom hole targets in a calibration block such that they evenly distribute in the volume is not a guarantee that the target placement provides the required complete volume coverage. This paper illustrates how the Coverage component of the CIVA AUT module helps to identify the best placement of volumetric targets in an AUT Zonal Discrimination procedure and prevents target redundancy.

An Integrated Analysis of Production, Marketing, and Value Addition in Rose and Gerbera Cultivation and Distribution

This comprehensive study offers an integrated investigation of various elements of rose and gerbera farming, marketing, and value-added operations. First, by evaluating the Cobb-Douglas production function’s coefficients and associated statistics, the production aspect is examined. which reveals strong relationships between inputs such as labour, seedlings, fertilisers, and output yield. Second, the marketing channels used in the distribution of rose and gerbera flowers are identified, with eight separate channels ranging from direct farmer-to-consumer transactions to multi-tiered networks comprising local and Dhaka wholesalers. Third, examine average marketing expenditures for performers or agents in each channel, including expenses for baskets, packing, transportation, storage, waste loss, commission, and other costs. Finally, the net value addition for each agent across various channels is derived by subtracting the selling price from the total marketing costs. The findings shed light on the intricacies of rose and gerbera cultivation and distribution, assisting stakeholders in optimising production methods, marketing approaches, and resource allocation to boost floriculture profits and efficiency in the floriculture industry.

Attention-based gating units separate channels in neural radiance fields

Attention-based gating units separate channels in neural radiance fields

A Forked Microvascular Phantom for Ultrasound Localization Microscopy Investigations.

In the development of ultrasound localization microscopy (ULM) methods, appropriate test beds are needed to facilitate algorithmic performance calibration. Here, we present the design of a new ULM-compatible microvascular phantom with a forked, V-shaped wall-less flow channel pair ( 250 μ m channel width) that is bifurcated at a separation rate of 50 μ m/mm. The lumen core was fabricated using additive manufacturing, and it was molded within a polyvinyl alcohol (PVA) tissue-mimicking slab using the lost-core casting method. Measured using optical microscopy, the lumen core's flow channel width was found to be 252 ± 15 μ m with a regression-derived flow channel separation gradient of 50.89 μ m/mm. The new phantom's applicability in ULM performance analysis was demonstrated by feeding microbubble (MB) contrast flow (1.67 to 167 μ L/s flow rates) through the phantom's inlet and generating ULM images with a previously reported method. Results showed that, with longer acquisition times (10 s or longer), ULM image quality was expectedly improved, and the variance of ULM-derived flow channel measurements was reduced. Also, at axial depths near the lumen's bifurcation point, the current ULM algorithm showed difficulty in properly discerning between the two flow channels because of the narrow channel-to-channel separation distance. Overall, the new phantom serves well as a calibration tool to test the performance of ULM methods in resolving small vasculature.

Performance Analysis of New 2D Spatial OCDMA Encoding based on HG Modes in Multicore Fiber

This paper presents a pioneering 2D spatial Optical Code-Division Multiple Access (OCDMA) encoding system that exploits Mode Division Multiplexing (MDM) and Multicore Fiber (MCF) technologies. This innovative approach utilizes two spatial dimensions to enhance the performance and security of OCDMA systems. In the first dimension, we employ Hermite-Gaussian modes (HG00, HG01, HG11) to modulate each user's signal individually. This unique approach offers a robust means of data transmission while ensuring minimal interference among users. The second-dimension leverages MCF encoding, introducing two incoherent OCDMA codes: the Zero Cross Correlation (ZCC) code (λc=0) and the ZFD code (λc=1). These codes are thoughtfully designed and simulated, taking into account their cross-correlation properties to guarantee minimal interference and heightened data security. To assess the efficiency of this novel OCDMA encoding system, we implemented simulations with three active users using the Opti system software. At the transmitter end, each user's signal is modulated individually by their designated HG mode (HG00, HG01, HG11), resulting in separate channels. Subsequently, at the multicore fiber, each user's data is encoded with a unique code-word, and they are directed through specific core groups, ensuring data isolation and integrity. In this paper, the BER and eye pattern are examined with respect to different parameters such as data rate and distance. At a distance of 5 km and data rate of 10 Gbit/s, a BER value around 10-70 is achieved.

Performance Analysis of New 2D Spatial OCDMA Encoding based on HG Modes in Multicore Fiber

This paper presents a pioneering 2D spatial Optical Code-Division Multiple Access (OCDMA) encoding system that exploits Mode Division Multiplexing (MDM) and Multicore Fiber (MCF) technologies. This innovative approach utilizes two spatial dimensions to enhance the performance and security of OCDMA systems. In the first dimension, we employ Hermite-Gaussian modes (HG00, HG01, HG11) to modulate each user's signal individually. This unique approach offers a robust means of data transmission while ensuring minimal interference among users. The second-dimension leverages MCF encoding, introducing two incoherent OCDMA codes: the Zero Cross Correlation (ZCC) code (λc=0) and the ZFD code (λc=1). These codes are thoughtfully designed and simulated, taking into account their cross-correlation properties to guarantee minimal interference and heightened data security. To assess the efficiency of this novel OCDMA encoding system, we implemented simulations with three active users using the Opti system software. At the transmitter end, each user's signal is modulated individually by their designated HG mode (HG00, HG01, HG11), resulting in separate channels. Subsequently, at the multicore fiber, each user's data is encoded with a unique code-word, and they are directed through specific core groups, ensuring data isolation and integrity. In this paper, the BER and eye pattern are examined with respect to different parameters such as data rate and distance. At a distance of 5 km and data rate of 10 Gbit/s, a BER value around 10-70 is achieved.