Design and characteristic analysis of micro multi-core fiber vibration sensor.

We proposed and fabricated a miniaturized multi-core fiber grating vibration sensor. The size of the miniaturized vibration sensor is 10mm × 10mm × 10 mm with a mass of only 0.25g. Finite element analysis and experimental tests were carried out to validate the performance of the vibration sensor. The experiment results indicate that the sensor has a sensitivity of 68.72 pm/g in the X direction and 64.52 pm/g in the Y direction within the operating frequency range of 20-240Hz. The cross-interference between the two directions of vibration measurement falls within 4 %. The sensor is suitable for measuring mechanical vibrations in the mid-low frequency range, especially in cases where size, quality, and distributed measurement are of particular concern.

Multi-Core Fiber Bragg Grating and Its Sensing Application.

With the increase in the demand for large-capacity optical communication capacity, multi-core optical fiber (MCF) communication technology has developed, and both the types of MCFs and related devices have become increasingly mature. The application of MCFs in the field of sensing has also received more and more attention, among which MCF fiber Bragg grating (FBG) devices have received more and more attention and have been widely used in various fields. In this paper, the main writing methods of MCF FBGs and their sensing applications are reviewed. The future development of the MCF FBG is also prospected.

Enhanced Coexistence of Quantum Key Distribution and Classical Communication over Hollow-Core and Multi-Core Fibers.

In this paper, we investigate the impact of classical optical communications in quantum key distribution (QKD) over hollow-core fiber (HCF), multi-core fiber (MCF) and single-core fiber (SCF) and propose wavelength allocation schemes to enhance QKD performance. Firstly, we theoretically analyze noise interference in QKD over HCF, MCF and SCF, such as spontaneous Raman scattering (SpRS) and four-wave mixing (FWM). To mitigate these noise types and optimize QKD performance, we propose a joint noise suppression wavelength allocation (JSWA) scheme. FWM noise suppression wavelength allocation and Raman noise suppression wavelength allocation are also proposed for comparison. The JSWA scheme indicates a significant enhancement in extending the simultaneous transmission distance of classical signals and QKD, reaching approximately 100 km in HCF and 165 km in MCF under a classical power per channel of 10 dBm. Therefore, MCF offers a longer secure transmission distance compared with HCF when classical signals and QKD coexist in the C-band. However, when classical signals are in the C-band and QKD operates in the O-band, the performance of QKD in HCF surpasses that in MCF. This research establishes technical foundations for the design and deployment of QKD optical networks.

Probe-Type Multi-Core Fiber Optic Sensor for Simultaneous Measurement of Seawater Salinity, Pressure, and Temperature.

In this article, we propose and demonstrate a probe-type multi-core fiber (MCF) sensor for the multi-parameter measurement of seawater. The sensor comprises an MCF and two capillary optical fibers (COFs) with distinct inner diameters, in which a 45° symmetric core reflection (SCR) structure and a step-like inner diameter capillary (SIDC) structure filled with polydimethylsiloxane (PDMS) are fabricated at the fiber end. The sensor is equipped with three channels for different measurements. The surface plasmon resonance (SPR) channel (CHSPR) based on the side-polished MCF is utilized for salinity measurement. The fiber end air cavity, forming the Fabry-Pérot interference (FPI) channel (CHFPI), is utilized for pressure and temperature measurement. Additionally, the fiber Bragg grating (FBG) channel (CHFBG), which is inscribed in the central core, serves as temperature compensation for the measurement results. By combining three sensing principles with space division multiplexing (SDM) technology, the sensor overcomes the common challenges faced by multi-parameter sensors, such as channel crosstalk and signal demodulation difficulties. The experimental results indicate that the sensor has sensitivities of 0.36 nm/‱, -10.62 nm/MPa, and -0.19 nm/°C for salinity, pressure, and temperature, respectively. As a highly integrated and easily demodulated probe-type optical fiber sensor, it can serve as a valuable reference for the development of multi-parameter fiber optic sensors.

Research Progress in Tunable Fiber Lasers Based on Multimode Interference Filters.

Tunable fiber lasers have the advantages of good beam quality, high integration, and adjustable output wavelength, and they are widely used in fields such as optical fiber communication and optical fiber sensing. The fiber filter is one of the key components of tunable fiber lasers. Among the various filters currently used, multimode interference filters have the advantages of simple structure, convenient implementation, flexible tuning methods, and convenient spectral range design. The structures of multimode interference filters based on multimode fibers, no-core fibers, multi-core fibers, tapered fibers, and other special fibers are introduced in this paper. The working principles and tuning methods are analyzed and the research progress of tunable fiber lasers based on these filters is summarized. Finally, the development trend of tunable fiber lasers based on multimode interference filters is discussed. The rapid development and applications of multimode interference filters can help improve the performance of continuous and pulse lasers as well as promote the practicality of tunable fiber lasers.

Dual core processors: Coupled queues: Transient performance evaluation.

High-Performance Computing (HiPC) systems routinely employ multi/many - core processors. Specifically, dual - core processors find many applications in pervasive computing devices. Dual-core processors employ buffers for queueing the incoming jobs. Traditionally, the queues at the processors are assumed to be independent and the queueing system is analyzed in equilibrium for tractability purposes. Queues are modeled using Continuous Time Markov Chains (CTMC's) and the equilibrium performance measures are determined to analyze as well as design the queueing systems. In most interesting cases, the incoming jobs are routed to the queues using the Join the Shortest Queue (JSQ) policy. Thus, with such an adaptive routing algorithm, the two queues are evidently coupled and are not statistically independent. Hence traditional equilibrium performance evaluation doesn't provide realistic performance measures. In this research paper, the two queues associated with buffers in dual-core processors are considered to be coupled. The Coupled Queues are modeled using a Quasi - Birth - and - Death (QBD) process. Using traditional results related to QBD processes, equilibrium performance measures are determined. More interestingly, we demonstrate the tractability of the computation of transient probability distribution of a QBD process. In the research literature, transient analysis of the QBD process was shown to be tractable in the Laplace transform domain. But in this research paper, we prove that the matrix exponential eQt arising in transient analysis (where Q is the generator matrix of the QBD process) can be computed directly in the time domain rendering efficient transient analysis of QBD process. Using the transient probability mass function of queue length, estimation of transient performance measures such as expected queue length, average delay, and tail distribution can be determined. Further, optimal adaptive routing algorithms for coupled queues can be designed.

A Simple Denoising Algorithm for Real-World Noisy Camera Images.

The noise statistics of real-world camera images are challenging for any denoising algorithm. Here, I describe a modified version of a bionic algorithm that improves the quality of real-word noisy camera images from a publicly available image dataset. In the first step, an adaptive local averaging filter was executed for each pixel to remove moderate sensor noise while preserving fine image details and object contours. In the second step, image sharpness was enhanced by means of an unsharp mask filter to generate output images that are close to ground-truth images (multiple averages of static camera images). The performance of this denoising algorithm was compared with five popular denoising methods: bm3d, wavelet, non-local means (NL-means), total variation (TV) denoising and bilateral filter. Results show that the two-step filter had a performance that was similar to NL-means and TV filtering. Bm3d had the best denoising performance but sometimes led to blurry images. This novel two-step filter only depends on a single parameter that can be obtained from global image statistics. To reduce computation time, denoising was restricted to the Y channel of YUV-transformed images and four image segments were simultaneously processed in parallel on a multi-core processor.

A Novel Catheter Shape-Sensing Method Based on Deep Learning with a Multi-Core Optical Fiber.

In this paper, we propose a novel shape-sensing method based on deep learning with a multi-core optical fiber for the accurate shape-sensing of catheters and guidewires. Firstly, we designed a catheter with embedded multi-core fiber containing three sensing outer cores and one temperature compensation middle core. Then, we analyzed the relationship between the central wavelength shift, the curvature of the multi-core Fiber Bragg Grating (FBG), and temperature compensation methods to establish a Particle Swarm Optimization (PSO) BP neural network-based catheter shape sensing method. Finally, experiments were conducted in both constant and variable temperature environments to validate the method. The average and maximum distance errors of the PSO-BP neural network were 0.57 and 1.33 mm, respectively, under constant temperature conditions, and 0.36 and 0.96 mm, respectively, under variable temperature conditions. This well-sensed catheter shape demonstrates the effectiveness of the shape-sensing method proposed in this paper and its potential applications in real surgical catheters and guidewire.

Efficient SNN multi-cores MAC array acceleration on SpiNNaker 2.

The potential low-energy feature of the spiking neural network (SNN) engages the attention of the AI community. Only CPU-involved SNN processing inevitably results in an inherently long temporal span in the cases of large models and massive datasets. This study introduces the MAC array, a parallel architecture on each processing element (PE) of SpiNNaker 2, into the computational process of SNN inference. Based on the work of single-core optimization algorithms, we investigate the parallel acceleration algorithms for collaborating with multi-core MAC arrays. The proposed Echelon Reorder model information densification algorithm, along with the adapted multi-core two-stage splitting and authorization deployment strategies, achieves efficient spatio-temporal load balancing and optimization performance. We evaluate the performance by benchmarking a wide range of constructed SNN models to research on the influence degree of different factors. We also benchmark with two actual SNN models (the gesture recognition model of the real-world application and balanced random cortex-like network from neuroscience) on the neuromorphic multi-core hardware SpiNNaker 2. The echelon optimization algorithm with mixed processors realizes 74.28% and 85.78% memory footprint of the original MAC calculation on these two models, respectively. The execution time of echelon algorithms using only MAC or mixed processors accounts for ≤ 24.56% of the serial ARM baseline. Accelerating SNN inference with algorithms in this study is essentially the general sparse matrix-matrix multiplication (SpGEMM) problem. This article explicitly expands the application field of the SpGEMM issue to SNN, developing novel SpGEMM optimization algorithms fitting the SNN feature and MAC array.

BrainS: Customized multi-core embedded multiple scale neuromorphic system.

Research on modeling and mechanisms of the brain remains the most urgent and challenging task. The customized embedded neuromorphic system is one of the most effective approaches for multi-scale simulations ranging from ion channel to network. This paper proposes BrainS, a scalable multi-core embedded neuromorphic system capable of accommodating massive and large-scale simulations. It is designed with rich external extension interfaces to support various types of input/output and communication requirements. The 3D mesh-based topology with an efficient memory access mechanism makes exploring the properties of neuronal networks possible. BrainS operates at 168 MHz and contains a model database ranging from ion channel to network scale within the Fundamental Computing Unit (FCU). At the ion channel scale, the Basic Community Unit (BCU) can perform real-time simulations of a Hodgkin-Huxley (HH) neuron with 16000 ion channels, using 125.54 KB of the SRAM. When the number of ion channels is within 64000, the HH neuron is simulated in real-time by 4 BCUs. At the network scale, the basal ganglia-thalamus (BG-TH) network consisting of 3200 Izhikevich neurons, providing a vital motor regulation function, is simulated in 4 BCUs with a power consumption of 364.8 mW. Overall, BrainS has an excellent performance in real-time and flexible configurability, providing an embedded application solution for multi-scale simulation.

Three-dimensional catheter tip force sensing using multi-core fiber Bragg gratings.

Awareness of catheter tip interaction forces is a crucial aspect during cardiac ablation procedures. The most important contact forces are the ones that originate between the catheter tip and the beating cardiac tissue. Clinical studies have shown that effective ablation occurs when contact forces are in the proximity of 0.2 N. Lower contact forces lead to ineffective ablation, while higher contact forces may result in complications such as cardiac perforation. Accurate and high resolution force sensing is therefore indispensable in such critical situations. Accordingly, this work presents the development of a unique and novel catheter tip force sensor utilizing a multi-core fiber with inscribed fiber Bragg gratings. A customizable helical compression spring is designed to serve as the flexural component relaying external forces to the multi-core fiber. The limited number of components, simple construction, and compact nature of the sensor makes it an appealing solution towards clinical translation. An elaborated approach is proposed for the design and dimensioning of the necessary sensor components. The approach also presents a unique method to decouple longitudinal and lateral force measurements. A force sensor prototype and a dedicated calibration setup are developed to experimentally validate the theoretical performance. Results show that the proposed force sensor exhibits 7.4 mN longitudinal resolution, 0.8 mN lateral resolution, 0.72 mN mean longitudinal error, 0.96 mN mean lateral error, a high repeatability, and excellent decoupling between longitudinal and lateral forces.

A Heterogeneity-Aware Replacement Policy for the Partitioned Cache on Asymmetric Multi-Core Architectures.

In an asymmetric multi-core architecture, multiple heterogeneous cores share the last-level cache (LLC). Due to the different memory access requirements among heterogeneous cores, the LLC competition is more intense. In the current work, we propose a heterogeneity-aware replacement policy for the partitioned cache (HAPC), which reduces the mutual interference between cores through cache partitioning, and tracks the shared reuse state of each cache block within the partition at runtime to guide the replacement policy to keep cache blocks shared by multiple cores in multithreaded programs. In the process of updating the reuse state, considering the difference of memory accesses to LLC by heterogeneous cores, the cache replacement policy tends to keep cache blocks required by big cores, to better improve the LLC access efficiency of big cores. Compared with LRU and the SRCP, which are the state-of-the-art cache replacement algorithms, the performance of big cores can be significantly improved by HAPC when running multithreaded programs, while the impact on little cores is almost negligible, thus improving the overall performance of the system.

One-Step Synthesis of Multi-Core-Void@Shell Structured Silicon Anode for High-Performance Lithium-Ion Batteries.

The core-void@shell architecture shows great advantages in enhancing cycling stability and high-rate performance of Si-based anodes. However, it is usually synthesized by template methods which are complex and environmentally unfriendly and would lead to low-efficiency charge and mass exchange because of the single-point van der Waals contact between the Si core and the shell. Here, a facile and benign one-step method to synthesize multi-Si-void@SiO2 structure, where abundant void spaces exist between multiple Si cores that are multi-point attached to a SiO2 shell through strong chemical bonding, is reported. The corresponding electrode exhibits highly stable cycling stability and excellent electrochemical performance. After 200 cycles at a current density of 0.1 A g-1 and then another 200 cycles at 1.2 A g-1 , the electrode outputs a specific capacity of 1440 mAh g-1 . Even at 2.0 A g-1 , it outputs a specific capacity as high as 1182 mAh g-1 . Such an anode can match almost all the cathode materials presently used in lithium-ion batteries. These results demonstrate the multi-Si-void@SiO2 as a promising anode to be used in future commercial lithium-ion batteries of high energy density and high power density.

Selective Photocatalytic Activation of Ethanol C-H and O-H Bonds over Multi-Au@SiO2/TiO2: Role of Catalyst Surface Structure and Reaction Kinetics.

The chemical bond diversity and flexible reactivity of biomass-derived ethanol make it a vital feedstock for the production of value-added chemicals but result in low conversion selectivity. Herein, composite catalysts comprising SiO2-coated single- or multiparticle Au cores hybridized with TiO2 nanoparticles (mono- or multi-Au@SiO2/TiO2, respectively) were fabricated via electrostatic self-assembly. The C-H and O-H bonds of ethanol were selectively activated (by SiO2 and TiO2, respectively) under irradiation to form CH3CH•(OH) or CH3CH2O• radicals, respectively. The formation and depletion kinetics of these radicals was analyzed by electron spin resonance to reveal marked differences between mono- and multi-Au@SiO2/TiO2. Consequently, the selectivity of these catalysts for 1,1-diethoxyethane after 6 h irradiation was determined as 81 and 99%, respectively, which was attributed to the more pronounced effect of localized surface plasmon resonance for multi-Au@SiO2/TiO2. Notably, only acetaldehyde was formed on a Au/TiO2 catalyst without a SiO2 shell. Fourier transform infrared (FTIR) spectroscopy indicated that the C-H adsorption of ethanol was enhanced in the case of multi-Au@SiO2/TiO2, while NH3 temperature-programmed desorption and pyridine adsorption FTIR spectroscopy revealed that multi-Au@SiO2/TiO2 exhibited enhanced surface acidity. Collectively, the results of experimental and theoretical analyses indicated that the adsorption of acetaldehyde on multi-Au@SiO2/TiO2 was stronger than that on Au/TiO2, which resulted in the oxidative coupling of ethanol to afford 1,1-diethoxyethane on the former and the dehydrogenation of ethanol to acetaldehyde on the latter.

Novel glass capillary microfluidic devices for the flexible and simple production of multi-cored double emulsions.

HYPOTHESIS: Double emulsions with many monodispersed internal droplets are required for the fabrication of multicompartment microcapsules and tissue-like synthetic materials. These double emulsions can also help to optically resolve different coalescence mechanisms contributing to double emulsion destabilization. Up to date microfluidic double emulsions are limited to either core-shell droplets or droplets with eight or less inner droplets. By applying a two-step jet break-up within one setup, double emulsion droplets filled with up to several hundred monodispersed inner droplets can be achieved. EXPERIMENTS: Modular interconnected CNC-milled Lego®-inspired blocks were used to create two separated droplet break-up points within coaxial glass capillaries. Inner droplets were formed by countercurrent flow focusing within a small inner capillary, while outer droplets were formed by co-flow in an outer capillary. The size of inner and outer droplets was independently controlled since the two droplet break-up processes were decoupled. FINDINGS: With the developed setup W/O/W and O/W/O double emulsions were produced with different surfactants, oils, and viscosity modifiers to encapsulate 25-400 inner droplets in each outer drop with a volume percentage of inner phase between 7% and 50%. From these emulsions monodispersed multicompartment microcapsules were obtained. The report offers insights on the relationship between the coalescence of internal droplets and their release.

From Adsorbent to Photocatalyst: The Sensitization Effect of SnO2 Surface towards Dye Photodecomposition.

Semiconductor photocatalysis is considered one of the most promising technologies for water purification from toxic organic dyes. However, to reliably evaluate the possibility of using a given material as a photocatalyst, it is crucial to investigate not only the photocatalytic activity but also its affinity towards various dyes and reusability. In this work, we studied the adsorptive/photocatalytic properties of hollow-spherical raspberry-like SnO2 and its SnO2/SnS2 heterostructures that were obtained via a chemical conversion method using three different concentrations of a sulfide precursor (thioacetamide). The adsorptive/photocatalytic properties of the samples towards cationic rhodamine B (RhB) and anionic indigo carmine (IC) were analyzed using uncommon wall zeta potential measurements, hydrodynamic diameter studies, and adsorption/photodecomposition tests. Moreover, after conducting cyclic experiments, we investigated the (micro)structural changes of the reused photocatalysts by scanning electron microscopy and Fourier-transform infrared spectroscopy. The obtained results revealed that the sensitization of SnO2 resulted not only in the significantly enhanced photocatalytic performance of the heterostructures, but also completely changed their affinity towards dyes. Furthermore, despite the seemingly best photocatalytic performance, the sample with the highest SnS2 content was unstable due to its (micro)structure. This work demonstrates that dye adsorption/desorption processes may overlap the results of cyclic photodecomposition kinetics.

FBG-Based Estimation of External Forces Along Flexible Instrument Bodies.

A variety of medical treatment and diagnostic procedures rely on flexible instruments such as catheters and endoscopes to navigate through tortuous and soft anatomies like the vasculature. Knowledge of the interaction forces between these flexible instruments and patient anatomy is extremely valuable. This can aid interventionalists in having improved awareness and decision-making abilities, efficient navigation, and increased procedural safety. In many applications, force interactions are inherently distributed. While knowledge of their locations and magnitudes is highly important, retrieving this information from instruments with conventional dimensions is far from trivial. Robust and reliable methods have not yet been found for this purpose. In this work, we present two new approaches to estimate the location, magnitude, and number of external point and distributed forces applied to flexible and elastic instrument bodies. Both methods employ the knowledge of the instrument's curvature profile. The former is based on piecewise polynomial-based curvature segmentation, whereas the latter on model-based parameter estimation. The proposed methods make use of Cosserat rod theory to model the instrument and provide force estimates at rates over 30 Hz. Experiments on a Nitinol rod embedded with a multi-core fiber, inscribed with fiber Bragg gratings, illustrate the feasibility of the proposed methods with mean force error reaching 7.3% of the maximum applied force, for the point load case. Furthermore, simulations of a rod subjected to two distributed loads with varying magnitudes and locations show a mean force estimation error of 1.6% of the maximum applied force.

Clustering Algorithms on Low-Power and High-Performance Devices for Edge Computing Environments.

The synergy between Artificial Intelligence and the Edge Computing paradigm promises to transfer decision-making processes to the periphery of sensor networks without the involvement of central data servers. For this reason, we recently witnessed an impetuous development of devices that integrate sensors and computing resources in a single board to process data directly on the collection place. Due to the particular context where they are used, the main feature of these boards is the reduced energy consumption, even if they do not exhibit absolute computing powers comparable to modern high-end CPUs. Among the most popular Artificial Intelligence techniques, clustering algorithms are practical tools for discovering correlations or affinities within data collected in large datasets, but a parallel implementation is an essential requirement because of their high computational cost. Therefore, in the present work, we investigate how to implement clustering algorithms on parallel and low-energy devices for edge computing environments. In particular, we present the experiments related to two devices with different features: the quad-core UDOO X86 Advanced+ board and the GPU-based NVIDIA Jetson Nano board, evaluating them from the performance and the energy consumption points of view. The experiments show that they realize a more favorable trade-off between these two requirements than other high-end computing devices.

In Situ Reduced Multi-Core Yolk-Shell Co@C Nanospheres for Broadband Microwave Absorption.

The preparation of yolk-shell microwave absorption materials with low density and excellent microwave absorption property requires reasonable design and economical manufacture. In this study, an efficient strategy without any templates or reducing gases has been designed to fabricate multi-core yolk-shell Co@C nanospheres by high temperature carbonization. The results showed that Co3O4 was completely reduced by the carbon shell to metal cobalt at temperatures above 750 °C. This unique multi-core yolk-shell structure with shell of 600 nm and multiple cores of tens of nanometers can provide sufficient interface and space to reflect and scatter electromagnetic waves. At the same time, the metal cobalt layer and carbon layer provide magnetic loss ability and dielectric loss ability, respectively, making the composite show good wave absorption performance. The minimal RL value of samples carbonized at 750 °C reaches -40 dB and the efficient absorption band reaches 9 GHz with the thickness ranges from 2-9 mm. Therefore, this is a facile, effective and economical strategy to prepare yolk-shell structure, which provides a new idea for the preparation of microwave absorption materials.

Rapid Synthesis of Thiol-Co-Capped-CdTe/CdSe/ZnSe Core Shell-Shell Nanoparticles: Their Optical and Structural Morphology.

CdTe QDs has been demonstrated in many studies to possess good outstanding optical and photo-physical properties. However, it has been established from literature that the toxic Cd2+ that tends to leak out into nearby solutions can be protected by less toxic ZnS or ZnSe shells leading to the synthesis of core-shells and multi-core-shells. Hence, this has allowed the synthesis of CdTe multi-core-shells to have gained much interest. The preparation of most CdTe multi-core-shells reported from various studies usually has a longer reaction time (6-24 h) in reaching their highest emission maxima. The synthesis of CdTe multi-core-shells in this study only took 35 min to obtain a highest emission maximum compared to what has been reported from the literature. CdTe multi-core-shells were synthesized by injecting 7, 14, and 21 mL each of Zn complex solution and Se ions into the reacting mixture containing CdTe core-shells (3 h) at 5 min intervals over a 35 min reaction time. The emission maxima of the MPA-TGA-CdTe multi-core-shells at 21 mL injection was recorded around 625 nm. Therefore, we are reporting the rapid synthesis of five different thiol co-capped CdTe/CdSe/ZnSe multi-core-shell QDs with the highest emission maxima obtained at 35 min reaction time.