Separate Channels Research Articles

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.

Flake-like SnS anchored on the carbon layer for supercapacitor electrode with photo-responsive capacitance enhancement

Photo-responsive supercapacitors incorporate light-responsive materials on capacitive electrodes, making them capable of solar energy conversion and storage within single device. Herein, composite structures consisting of flake-like stannous sulfide (SnS) anchored on a carbon layer (CL) covered nickel foam (CL@SnS/NF) are synthesized as photo-responsive supercapacitor electrode for capacitance enhancement under visible light. SnS as a light-absorbing layer has a narrow bandgap that matches well with the wavelength of visible light, while CL serves as an electron transport channel for effective separation of photogenerated carriers. Due to the synergetic effect of two components above, the areal specific capacitance of the CL@SnS/NF electrode increases from 15.7 to 21.0 mF·cm−2 in light conditions under 0.1 mA·cm−2, which is 1.7 and 6.6 times larger than that of CL/NF and SnS/NF electrodes under the same conditions, respectively, indicating the remarkable light-induced capacitance enhancement performance. The CL@SnS/NF electrode also presents higher photocurrent and photovoltage than two single electrodes, implying its excellent photosensitivity. In addition, the assembled CL@SnS/NF-based symmetric supercapacitor exhibits great capacitance gain under illumination (185.8% at 50 µA·cm−2) and excellent capacitance maintenance (87.7% over 6000 cycles). This work supplies a novel strategy to the development of high-performance solar energy conversion and storage devices.

An advanced miniature fluidic system in multilayer ceramic technology with precise temperature and flow control for in situ pollution monitoring

Rapid, on-site, water-quality monitoring is necessary to prevent and remediate environmental pollution. This study aims to develop a miniature, portable, fluidic system (MFS) designed for the easy insertion of disposable, screen-printed electrodes (SPEs) and the measurement of an electrochemical response (EC) under controlled temperature and flow conditions. The three-dimensional MFS, realised in low-temperature, cofired ceramic and multilayer ceramic technology, consist of three distinct cavities, each with separate inlet and outlet channels. These channels are designed to maintain an equivalent flow rate across all three cavities. The MFS allows simultaneous measurements at three measuring sites, temperature control of the fluid from room temperature to 125 °C via integrated heaters and temperature sensors, and flow regulation up to 20 mL/min via an external fluid pump. The EC values obtained from the SPEs in a standard solution of potassium ferrocyanide/potassium ferricyanide at room temperature and under stagnant conditions were consistent with measurements conducted in the MFS, droplet and conventional electrochemical cells, confirming the accuracy and reliability of the MFS. The EC response was confirmed in the MFS under flow conditions of 4 mL/min and temperatures of 25 °C, 35 °C, and 45 °C. This shows that multilayer ceramic technology enables the fabrication of a miniature, three-dimensional MFS with integrated fluidic and electronic components that provide reliable and accurate electrochemical measurements using a commercial SPE under controlled flow and temperature conditions.

Distribution of Heterogeneous, Highly Impure Soy Material in a Deep Air Channel

The paper highlights a lack of machines and equipment capable of cleaning highly impure soybean material efficiently and productively. Most of the existing grain cleaning machines are designed for the materials conforming to GOST 17109-88 that specifies weed and oilseed impurity contents of 2 and 6 percent, respectively. In reality, a typical soybean post-harvest waste often contains 20 to 60 percent of material unsuitable for extracting raw protein, that makes this type of material completely non–separable for this type of machine. (Research purpose) The research aims to determine the optimal efficiency of separating heterogeneous bulk mixtures in a vertically ascending air channel. (Materials and methods) To accomplish this, the authors employed a rotary batch classifier RBK 30 and a prototype sample of a precision air classifier PAC with column air flow accelerators. The paper defines impurity separation completeness and soybean waste separation efficiency in a novel pneumatic classifier, considering the accelerator thickness and the height above the processed material. (Results and discussion) The findings reveal that traditional pneumatic channels achieve no more than 20 percent of separation efficiency for highly impure soybean material, while the precision air classifier demonstrates approximately a 45 percent separation. (Conclusions) Typical air flow machines struggle with high impurity of material. The separation efficiency of highly impure material can be enhanced by equalizing the air flow velocity inside and above the layer of the separated material and installing a core air flow accelerator. The study indicates that the material being processed can be separated by air flow, provided a specialized pneumatic separation channel is used. Due to the ratio of the core accelerator height and the height above the material, the air flow velocity inside and above the separated layer is equalized.

Minimum Noise Fraction Analysis of TGO/NOMAD LNO Channel High-Resolution Nadir Spectra of Mars

NOMAD is a suite of spectrometers on the board of the ESA-Roscosmos Trace Gas Orbiter (TGO) spacecraft and is capable of investigating the Martian environment at very high spectral resolution in the ultraviolet–visible and infrared spectral ranges by means of three separate channels: UVIS (0.2–0.65 μm), LNO (2.2–3.8 μm), and SO (2.3–4.3 μm). Among all channels, LNO is the only one operating at infrared wavelengths in nadir-viewing geometry, providing information on the whole atmospheric column and on the surface. Unfortunately, the LNO data are characterized by an overall low level of signal-to-noise ratio (SNR), limiting their contribution to the scientific objectives of the TGO mission. In this study, we assess the possibility of enhancing LNO nadir data SNR by applying the Minimum Noise Fraction (MNF), a well-known algorithm based on the Principal Components technique that has the advantage of providing transform eigenvalues ordered with increasing noise. We set up a benchmark process on an ensemble of synthetic spectra in order to optimize the algorithm specifically for LNO datasets. We verify that this optimization is limited by the presence of spectral artifacts introduced by the MNF itself, and the maximum achievable SNR is dependent on the scientific purpose of the analysis. MNF application study cases are provided to LNO data subsets in the ranges 2.627–2.648 μm and 2.335–2.353 μm (spectral orders 168 and 189, respectively) covering absorption features of gaseous H2O and CO and CO2 ice, achieving a substantial enhancement in the quality of the observations, whose SNR increases up to a factor of 10. While such an enhancement is still not enough to enable the investigation of spectral features of faint trace gases (in any case featured in orders whose spectral calibration is not fully reliable, hence preventing the application of the MNF), interesting perspectives for improving retrieval of both atmospheric and surface features from LNO nadir data are implied.

Release of windowed multipole library for ENDF/B-VIII.0 in support of OpenMC criticality and depletion analysis

Major evaluations have been updated in the latest release of the Evaluated Nuclear Data library (ENDF/B-VIII.0) and is the currently recommended pointwise library for criticality and depletion analysis in the open-source Monte Carlo code — OpenMC. However, the currently released OpenMC library does not yet include an accompanying windowed multipole library (WMP) that enables on-the-fly Doppler broadening. This paper revisits the windowed multipole representation and fixes a major drawback that has prevented its use for depletion analysis. The new WMP library presented in this paper explicitly treats key absorption reactions as separate channels such that proper reaction rates are provided during depletion analysis. Based on this improvement, the new WMP library is processed for ENDF/B-VIII.0 and then verified against the pointwise data through direct comparison, criticality benchmarks and fuel assembly depletion. The numerical results show good agreement and efficiency with the pointwise library.