Research Progress on Structure, Function and Application of β-1,3-Glucanases

β-1,3-Glucanases are enzymes that specifically hydrolyze β-1,3-glycosidic linkages bonds in β-1,3-glucan to generate a range of oligosaccharides or monosaccharides. β-1,3-Glucanases have important potential applications in functional oligosaccharide preparation, fruit and vegetable preservation, biopharmaceuticals, and plant disease resistance. β-1,3-Glucanases belonging to 12 glycoside hydrolase (GH) families have been identified, including GH16, GH17, GH55, GH64, GH81, GH128 and GH132. β-1,3-Glucanases are widely distributed in bacteria, fungi, plants and insects, which exhibit diverse structures and catalytic functions due to differences in sources and sequence evolution. Structural and functional studies of enzymes are the basis for exploring the catalytic mechanism, enzyme properties, and molecular modification. Therefore, this paper reviews the current state of research on the structure, function and application of β-1, 3-glucanases, in order to provide a reference for the basic research and application of β-1,3-glucanases

MRI characteristics of lumbosacral dural arteriovenous fistulas

Background and purposeSpinal dural arteriovenous fistulas located in the lumbosacral region are rare and present with nonspecific clinical signs. The purpose of this study was to find out the specific radiologic features of these fistulas.MethodsWe retrospectively reviewed the clinical and radiological data of 38 patients diagnosed with lumbosacral spinal dural arteriovenous fistulas in our institution from September 2016 to September 2021. All patients underwent time-resolved contrast-enhanced three-dimensional MRA and DSA examinations, and were treated with either endovascular or neurosurgical strategies.ResultsMost of the patients (89.5%) had motor or sensory disorders in both lower limbs as the first symptoms. On MRA, the dilated filum terminale vein or radicular vein was seen in 23/30 (76.7%) patients with lumbar spinal dural arteriovenous fistulas and 8/8 (100%) patients with sacral spinal dural arteriovenous fistulas. T2W intramedullary abnormally high signal intensity areas were found in all lumbosacral spinal dural arteriovenous fistula patients, with involvement of the conus present in 35/38 (92.1%) patients. The “missing piece sign” in the intramedullary enhancement area was seen in 29/38 (76.3%) patients.ConclusionDilatation of the filum terminale vein or radicular vein is powerful evidence for diagnosis of lumbosacral spinal dural arteriovenous fistulas, especially for sacral spinal dural arteriovenous fistulas. T2W intramedullary hyperintensity in the thoracic spinal cord and conus, and the missing-piece sign could be indicative of lumbosacral spinal dural arteriovenous fistula

A High Precision and Multifunctional Electro‐Optical Conversion Efficiency Measurement System for Metamaterial‐Based Thermal Emitters

In this study, a multifunctional high-vacuum system was established to measure the electro-optical conversion efficiency of metamaterial-based thermal emitters with built-in heaters. The system is composed of an environmental control module, an electro-optical conversion measurement module, and a system control module. The system can provide air, argon, high vacuum, and other conventional testing environments, combined with humidity control. The test chamber and sample holder are carefully designed to minimize heat transfer through thermal conduction and convection. The optical power measurements are realized using the combination of a water-cooled KBr flange, an integrating sphere, and thermopile detectors. This structure is very stable and can detect light emission at the μW level. The system can synchronously detect the heating voltage, heating current, optical power, sample temperatures (both top and bottom), ambient pressure, humidity, and other environmental parameters. The comprehensive parameter detection capability enables the system to monitor subtle sample changes and perform failure mechanism analysis with the aid of offline material analysis using scanning electron microscopy, energy dispersive X-ray spectroscopy, and X-ray diffraction. Furthermore, the system can be used for fatigue and high-low temperature impact tests

Towards prediction of ordered phases in rechargeable battery chemistry via group–subgroup transformation

Abstract: The electrochemical thermodynamic and kinetic characteristics of rechargeable batteries are critically influenced by the ordering of mobile ions in electrodes or solid electrolytes. However, because of the experimental difficulty of capturing the lighter migration ion coupled with the theoretical limitation of searching for ordered phases in a constrained cell, predicting stable ordered phases involving cell transformations or at extremely dilute concentrations remains challenging. Here, a group-subgroup transformation method based on lattice transformation and Wyckoff-position splitting is employed to predict the ordered ground states. We reproduce the previously reported Li0.75CoO2, Li0.8333CoO2, and Li0.8571CoO2 phases and report a new Li0.875CoO2 ground state. Taking the advantage of Wyckoff-position splitting in reducing the number of configurations, we identify the stablest Li0.0625C6 dilute phase in Li-ion intercalated graphite. We also resolve the Li/La/vacancy ordering in Li3xLa2/3−xTiO3 (0 < x < 0.167), which explains the observed Li-ion diffusion anisotropy. These findings provide important insight towards understanding the rechargeable battery chemistry

Digitally Integrated Self-Trained Predistortion Curve Finder for Passive Sweep Linearization of Semiconductor Lasers

This paper reports a digitally integrated, self-trained predistortion curve finder for linearly frequency-swept semiconductor lasers. In this method, we introduce an iteration machine to train the laser current curves by utilizing the feedback signals from the laser\u27s output. By measuring the phase and frequency information of lasers, we find that the predistortion finder in our design can generate various high sweep velocities (THz/ms) of lasers in 1 s with phase error range less than π 2. This method is universal for semiconductor lasers at any sweep frequency velocity

A novel approach based on similarity measure for the multiple attribute group decision-making problem in selecting a sustainable cryptocurrency

Environmental impact and sustainability challenges in the cryptocurrencies has become increasingly examined in the literature. However, studies of the multiple attribute group decision making (MAGDM) method for major selection of cryptocurrencies in advancing sustainability are still at an early stage. In particular, research on the fuzzy-MAGDM method in the evaluation of sustainability in cryptocurrencies is scarce. This paper adds contributions by developing a novel MAGDM approach to evaluate the sustainability development of major cryptocurrencies. It proposes a similarity measure for interval-valued Pythagorean fuzzy numbers (IVPFNs) based on whitenisation weight function and membership function in grey systems theory for IVPFNs. It further developed a novel generalised interval-valued Pythagorean fuzzy weighted grey similarity (GIPFWGS) measure approach to provide a more rigorous evaluation in complex decision marking problem with embedding ideal solution and membership degree. It also conducts a sustainability evaluation model of major cryptocurrencies as a numerical application and performs a robustness assessment with different variations of the expert’s weight to test how different values of parameter θ can affect the ranking results of alternatives. The results suggest that Stellar is the most sustainable cryptocurrency, while Bitcoin with its intensive energy consumption, high mining cost and high computing power provides the least effective support for its sustainable development. A comparative analysis with the average value method and Euclidean distance method was performed to validate the reliability of the proposed decision-making model and provides evidence that the GIPFWGS has better fault tolerance

Self-adaptive method for performance enhancement of sweep-velocity-locked lasers

Optical frequency-domain reflectometry and frequency-modulated continuous wave (FMCW)-based sensing technologies, such as LiDAR and distributed fiber sensors, fundamentally rely on the performance of frequency-swept laser sources. Specifically, frequency-sweep linearity, which determines the level of measurement distortion, is of paramount importance. Sweep-velocity-locked semiconductor lasers (SVLLs) controlled via phase-locked loops (PLLs) have been studied for many FMCW applications owing to its simplicity, low cost, and low power consumption. We demonstrate an alternative, self-adaptive laser control system that generates an optimized predistortion curve through PLL iterations. The described self-adaptive algorithm was successfully implemented in a digital circuit. The results show that the phase error of the SVLL improved by around 1 order of magnitude relative to the one without using this method, demonstrating that this self-adaptive algorithm is a viable method of linearizing the output of frequency-swept laser sources

Real-time signal processing for sub-THz range grating-based distributed fiber sensing

Distributed optical fiber sensors are an increasingly utilized method of gathering distributed strain and temperature data. However, the large amount of data they generate present a challenge that limits their use in real-time, in-situ applications. This letter describes a parallel and pipelined computing architecture that accelerates the signal-processing speed of sub-terahertz fiber sensor (sub-THz-fs) arrays, maintaining high spatial resolution while allowing for expanded use for real-time sensing and control applications. The computing architecture described was successfully implemented in a field programmable gate array (FPGA) chip. The signal processing for the entire array takes only 12 system clock cycles. In addition, this design removes the necessity of storing any raw or intermediate data

A high-linear sweep laser source to interrogate sub-terahertz range fiber sensors for dynamic strain sensing applications

Sub-terahertz range fiber sensors have been well investigated for distributed stain sensing applications. Due to the use to sub-millimeter range structures, high accuracy measurement using relative small interrogation bandwidth (∼ 100 GHz) can be achieved. The interrogation system is based on optical frequency domain reflectometry (OFDR), where the key component is the high-linear frequency sweep laser source. Previously the external cavity lasers have been employed as the frequency sweep sources. The external cavity lasers are capable to sweep over large interrogation bandwidth (\u3e3 THz). However, compared with the 100 GHz resonation period of sub-terahertz range fiber sensors with a pitch length of 1mm, this broad sweep bandwidth is unnecessary. Besides, the external cavity lasers require the use of moving mechanical components, which limits the system update rate and increases the system complexity. This paper presents a design of a high linear sweep laser source suitable for sub-terahertz range fiber sensors. A distributed feedback laser is employed as the frequency sweep source based on the injection current modulation technique, and the sweep velocity is locked at a constant value (14.2 GHz/ms) using a semi-digital feedback control system. A high-linear sweep bandwidth of 117.69 GHz with a system update rate of 50 Hz has been demonstrated. In addition, a dynamic experiment was conducted to demonstrate the system distributed strain sensing capability. The proposed system holds the potential for dynamic structural health monitoring