Application Prospects Research Articles

Enhanced hydrophilicity and stability of carbon-based aerogel with assembling of halloysite nanotubes and silica fibers for efficient solar seawater evaporation and desalination

Solar vapor generation has emerged as a sustainable technique for seawater evaporation and desalination. Integrating high hydrophilicity, strong light absorbance, good salt resistance, fast water transfer and good structural stability simultaneously in one evaporator at low cost for achieving cost-effective evaporation and long-term utilization is highly desirable but still challenging. Herein, an eco-friendly and low-cost aerogel (CSH) with natural chitosan, halloysite nanotubes and silica fibers was prepared by freeze-casting, which was then carbonized to construct a robust aerogel (cCSH) as evaporator. The cellular structure of cCSH aerogel with microchannels enables fast water transfer and rapid salt dissolution, the carbonized chitosan favors enhanced light absorption, the halloysite assembled on the walls endows the aerogel with excellent hydrophilicity, and the silica fibers penetrating the multilayer guarantee good structural stability. As expected, the prepared evaporator (cCSH200) exhibits remarkable evaporation rates of 2.49/7.20 kg·m−2·h−1 under one/four sun, respectively, exceeding most biomacromolecule-derived aerogels. Besides, it displays outstanding salt resistance, wastewater purification ability and long-term cycle stability. Outdoor test further substantiates the admirable evaporation performance, long-term durability and enormous application prospect of the cCSH200. This work affords a low-cost tactic for the development of efficient evaporator for solar-driven seawater desalination and wastewater treatment.

Human-robot interaction in motor imagery: A system based on the STFCN for unilateral upper limb rehabilitation assistance

BackgroundRehabilitation training based on the brain-computer interface of motor imagery (MI-BCI) can help restore the connection between the brain and movement. However, the performance of most popular MI-BCI system is coarse-level, which means that they are good at guiding the rehabilitation exercises of different parts of the body, but not for the individual component. New methodsIn this paper, we designed a fine-level MI-BCI system for unilateral upper limb rehabilitation assistance. Besides, due to the low discrimination of different sample classes in a single part, a classification algorithm called spatial-temporal filtering convolutional network (STFCN) was proposed that used spatial filtering and deep learning. Comparison with existing methodsOur STFCN outperforms popular methods in recent years using BCI IV 2a and 2b data sets. ResultsTo verify the effectiveness of our system, we recruited 6 volunteers and collected their data for a four-classification online experiments, resulting in an average accuracy of 62.7 %. ConclusionThis fine-level MI-BCI system has good appli-cation prospects, and inspires more exploration of rehabilitation in a single part of the human body.

Carbon Micro/Nano Machining toward Miniaturized Device: Structural Engineering, Large-Scale Fabrication, and Performance Optimization.

With the rapid development of micro/nano machining, there is an elevated demand for high-performance microdevices withhigh reliability and low cost. Due to their outstanding electrochemical, optical, electrical, and mechanical performance, carbon materials are extensively utilized in constructing microdevices for energy storage, sensing, and optoelectronics. Carbon micro/nano machining is fundamental in carbon-based intelligent microelectronics, multifunctional integrated microsystems, high-reliability portable/wearable consumer electronics, and portable medical diagnostic systems. Despite numerous reviews on carbon materials, a comprehensive overview is lacking that systematically encapsulates the development of high-performance microdevices based on carbon micro/nano structures, from structural design to manufacturing strategies and specific applications. This review focuses on the latest progress in carbon micro/nano machining toward miniaturized device, including structural engineering, large-scale fabrication, and performance optimization. Especially, the review targets an in-depth evaluation of carbon-based micro energy storage devices, microsensors, microactuators, miniaturized photoresponsive and electromagnetic interference shielding devices. Moreover, it highlights the challenges and opportunities in the large-scale manufacturing of carbon-based microdevices, aiming to spark further exciting research directions and application prospectives.

Design and Application of Virtual Cloud OMS Computing in Smart Airport

Airport management takes airport information management as its key link, and it is also the key to ensure the safe operation of airports. As a modern information management and processing technology, cloud computing plays an indispensable role in the fields of efficient information processing, strengthening management and improving work efficiency. Under the development background of the information age, the management mode of airport operation and maintenance has also changed to some extent. In the growth of the new era, airport operation and maintenance managers need to introduce new technologies and then combine more advanced technologies with the airport operation and maintenance system (OMS) so as to promote the normal operation of the airport OMS based on advanced data acquisition, analysis, and integration technologies. This article studies the application of cloud computing technology and designs a virtual cloud OMS based on deep learning (DL) from the perspective of the security requirements of the management information system (MIS) to realize the fault diagnosis and identification of the airport MIS. The fault diagnosis technology of the airport MIS based on virtual cloud OMS and DL proposed in this study has broad prospects in practical application. It can be applied to airport operation and maintenance management, security, and other links, providing intelligent support for airport operation.

Noninvasive reconstruction of internal heat source in biological tissue using adaptive simulated annealing algorithm

The heat distribution information of human lesions is of great value for disease analysis, diagnosis, and treatment. It is a typical inverse problem of heat conduction that deriving the distribution of internal heat sources from the temperature distribution on the body surface. This paper transforms such an inverse problem of bio-heat transfer into a direct one, thereby avoiding complex boundary conditions and regularization processes. To noninvasively reconstruct the internal heat source and its corresponding 3D temperature field in biological tissue, the adaptive simulated annealing (ASA) algorithm is used in the simulation module, where the position P(x, y, z) of point heat source in biological tissue and its corresponding temperature T are set as the optimization variables. Under a certain optimized sample, one can obtain the simulated temperature distributing on the surface of the module, then subtract the simulated temperature from the measured temperature of the same surface which was measured using a thermal infrared imager. If the sum of absolute values of the difference is smaller, it indicates that the current sample is closer to the true location and temperature of the heat source. When the values of optimization variables are determined, the corresponding 3D temperature field is also confirmed. The simulation results show the simulated position and temperature of the heat source are very approximate with those of the real experimental module. The method presented in this paper has enormous potential and promising prospects in clinical research and application, such as tumor hyperthermia, disease thermal diagnosis technology, etc.

A Sodium Bis(fluorosulfonyl)imide (NaFSI)-based Multifunctional Electrolyte Stabilizes the Performance of NaNi1/3Fe1/3Mn1/3O2/hard Carbon Sodium-ion Batteries.

A sodium bis(fluorosulfonyl)imide (NaFSI)-based multifunctional electrolyte is developed by partially replacing NaPF6 salt in the electrolyte to improve the wide temperature range working capability of NaNi1/3Fe1/3Mn1/3O2/hard carbon (NNFM111/HC) sodium-ion batteries (SIBs). The capacity retention of the SIBs with NaFSI-NaPF6 dual salt electrolyte increases from 47.2 % to 75.5 % after 250 cycles at 25 °C, and from 51.0 % to 82.3 % after 80 cycles at 45 °C, and the 1 C discharge capacity retention at the low temperature of -20 °C also increases 26.8 %. In the single salt system, NaPF6 effectively passivate the aluminum foil and NaFSI passivate the electrode/electrolyte interface. The synergistic effect of NaPF6 and NaFSI greatly improves the battery performance in a wide temperature range. This NaFSI-based dual salt electrolyte also effectively overcomes the flaws when the SIBs using NaFSI or NaPF6 independently, and makes it more suitable for SIBs, indicating promising prospects in the commercial application of NNFM111/HC SIBs.

Targeting Ferroptosis: A Novel Strategy for the Treatment of Atherosclerosis.

Since ferroptosis was reported in 2012, its application prospects in various diseases have been widely considered, initially as a treatment direction for tumors. Recent studies have shown that ferroptosis is closely related to the occurrence and development of atherosclerosis. The primary mechanism is to affect the occurrence and development of atherosclerosis through intracellular iron homeostasis, ROS and lipid peroxide production and metabolism, and a variety of intracellular signaling pathways. Inhibition of ferroptosis is effective in inhibiting the development of atherosclerosis, and it can bring a new direction for treating atherosclerosis. In this review, we discuss the mechanism of ferroptosis and focus on the relationship between ferroptosis and atherosclerosis, summarize the different types of ferroptosis inhibitors that have been widely studied, and discuss some issues worthy of attention in the treatment of atherosclerosis by targeting ferroptosis.

LSOTB-TIR: A Large-Scale High-Diversity Thermal Infrared Single Object Tracking Benchmark.

Unlike visual object tracking, thermal infrared (TIR) object tracking methods can track the target of interest in poor visibility such as rain, snow, and fog, or even in total darkness. This feature brings a wide range of application prospects for TIR object-tracking methods. However, this field lacks a unified and large-scale training and evaluation benchmark, which has severely hindered its development. To this end, we present a large-scale and high-diversity unified TIR single object tracking benchmark, called LSOTB-TIR, which consists of a tracking evaluation dataset and a general training dataset with a total of 1416 TIR sequences and more than 643 K frames. We annotate the bounding box of objects in every frame of all sequences and generate over 770 K bounding boxes in total. To the best of our knowledge, LSOTB-TIR is the largest and most diverse TIR object tracking benchmark to date. We spilt the evaluation dataset into a short-term tracking subset and a long-term tracking subset to evaluate trackers using different paradigms. What's more, to evaluate a tracker on different attributes, we also define four scenario attributes and 12 challenge attributes in the short-term tracking evaluation subset. By releasing LSOTB-TIR, we encourage the community to develop deep learning-based TIR trackers and evaluate them fairly and comprehensively. We evaluate and analyze 40 trackers on LSOTB-TIR to provide a series of baselines and give some insights and future research directions in TIR object tracking. Furthermore, we retrain several representative deep trackers on LSOTB-TIR, and their results demonstrate that the proposed training dataset significantly improves the performance of deep TIR trackers. Codes and dataset are available at https://github.com/QiaoLiuHit/LSOTB-TIR.

Identification and Quantitative Analysis of the Pharmacologically Active Components of Jianxin Granules by UHPLC-QTOF-MS/MS-Based Metabolomics

Jianxin Granules, a Traditional Chinese Medicine (TCM), consisting of eight flavors, including Huang Qi (astragalus), Hong Shen (red ginseng), Pu Huang (pollen typhae), Dan Shen (salvia miltiorrhiza), Zhu Ling (polyporus), Bai Zhu (atractylodes macrocephala), Gui Zhi (cassia twig), Ting Li Zi (semen lepidii). Jianxin granules has a multi-system, multi-target, and multi-directional comprehensive regulatory effect on inhibiting ventricular remodeling, which is an effective formulation for the prevention and treatment of heart failure, and has a good application prospect. However, many of the ingredients, including pharmacologically active ingredients, in the Jianxin granules remain unclear. Here, we attempted to develop a metabolomics method of component identification, quantitation, pattern recognition, and cross-comparison of Jianxin granules. Chemical analysis, component identification and quantification analyse of Jianxin granules were conducted with a combination of UHPLC-QTOF-MS/MS with bioinformatics. Assessment of the correlation between technical and bio-replicated pharmacological active ingredients was implemented by Principal Component Analysis (PCA), in addition to Partial Least Squares Discriminant Analysis (PLS-DA). UHPLC-QTOFMS/ MS, a metabolomics method, was developed and adapted to characterize Jianxin granules, which consisted of 178 to 216 molecular signatures. The quantitative analysis of 95 frequently occurring molecular signatures of Jianxin granules was carried out by a single exogenous reference internal standard. Of these, 47 have been identified using diverse databases, including 2 glycosylglycerol derivatives, 2 lipids, 2 spiro compounds, 2 cyclohexanecarboxylic acids, 2 glycosides, 5 terpenoids, 7 oligopeptides, 17 favonoids, and 8 various compounds, such as hydroxycoumarin, chalcone, benzofuran, benzodioxole, benzaldehyde, aromatic ketone, and alkyl cafeate ester. The established method demonstrates robust reliability and reproducibility, making it suitable for various applications including compositional identification, quantification, and quality assessment of the pharmacologically active constituents in Jianxin granules.

Machine Learning and Natural Language Processing Algorithms in the Remote Mobile Medical Diagnosis System of Internet Hospitals

In order to alleviate the contradiction between supply and demand of professional pharmacists, integrate medical resources, and ensure the safety of patients’ medication, the telemedicine diagnosis system has played a great role. Today, in this “Internet +” era, all walks of life have begun to integrate with Internet technology. The purpose of this article was to discuss the practical utility of machine learning and natural language processing algorithms in the remote mobile medical diagnosis system of Internet hospitals, for which this article conducted in-depth discussion. This article first introduced the basic concepts, development, and characteristics of machine learning and natural language processing algorithms in detail, and carefully studied and analyzed the development and culture of traditional offline medical diagnosis models. Based on machine learning and natural language processing algorithms, a remote mobile medical diagnosis is designed. By combining with the medical diagnosis system of traditional hospitals, a new type of remote mobile medical diagnosis system for Internet hospitals was designed and developed, and the combination of traditional medical industry and Internet technology was deeply studied. According to each functional requirement, the image module, heart rate measurement module, and user setting module are designed, respectively. Compared to traditional medical diagnosis systems, the accuracy of the remote mobile medical diagnosis system based on machine learning applied in Internet hospital diagnosis in this article reached 80% or even higher. At the same time, it was found through experiments that when the evolution number was 3, the maximum fit value and average fit value were the same, both of which were 0.6. This indicates that the system can accommodate more than 10,000 people at the same time, and patients can receive good treatment plans, with a very broad application prospect

Stable and Durable Superhydrophobic Cotton Fabrics Prepared via a Simple 1,4-Conjugate Addition Reaction for Ultrahigh Efficient Oil-Water Separation.

Superhydrophobic materials used for oil-water separation have received wide attention. However, the simple and low-cost strategy for making durable superhydrophobic materials remains a major challenge. Here, this work reports that stable and durable superhydrophobic cotton fabrics can be prepared using a simple two-step impregnation process. Silica nanoparticles are surface modified by hydrolysis condensation of 3-aminopropyltrimethoxysilane (APTMS). 1,4-conjugate addition reaction between the acrylic group of cross-linking agent pentaerythritol triacrylate (PETA) and the amino group of octadecylamine (ODA) forms a covalent cross-linked rough network structure. The long hydrophobic chain of ODA makes the cotton fabric exhibit excellent superhydrophobic properties, and the water contact angle (WCA) of the fabric surface reaches 158°. The modified cotton fabric has good physical and chemical stability, self-cleaning, and anti-fouling. At the same time, the modified fabric shows excellent oil/water separation efficiency (98.16% after 20 cycles) and ultrahigh separation flux (15413.63 L m-2 h-1) due to its superhydrophobicity, superoleophilicity, and inherent porous structure. The method provides a broad prospect in the future diversification applications of oil/water separation and oil spill cleaning.

Biochemical characterization of purified phytase produced from Aspergillus awamori AFE1 associated with the gastrointestinal tract of longhorn beetle (Cerambycidae latreille)

ABSTRACT The need for industrially and biotechnologically significant enzymes, such as phytase, is expanding daily as a result of the increased use of these enzymes in a variety of operations, including the manufacture of food, animal feed, and poultry feed. This study sought to characterize purified phytase from A. awamori AFE1 isolated from longhorn beetle for its prospect in industrial applications. Ammonium sulfate precipitation, ion-exchange chromatography, and gel-filtration chromatography were used to purify the crude enzyme obtained from submerged fermentation using phytase-producing media, and its physicochemical characteristics were examined. The homogenous 46.8-kDa phytase showed an 8.1-fold purification and 40.7% recovery. At 70 C and pH 7, the optimum phytase activity was noted. At acidic pH 4–6 and alkaline pH 8–10, it likewise demonstrated relative activity of 88–95% and 67–88%, respectively. It showed 67–70% residual activity between 30 and 70 C after 40 min, and 68–94% residual activity between pH 2 and 12 after 2 h. The presence of Hg+, Mg2+, and Al3+ significantly decreased the enzymatic activity, whereas Ca2+ and Cu2+ enhanced it. Ascorbic acid increased the activity of the purified enzyme, whereas ethylenediaminetetraacetic acid (EDTA) and mercaptoethanol inhibited it. The calculated values for Km and Vmax were 55.4 mM and1.99 μmol/min/mL respectively. A. awamori phytase, which was isolated from a new source, showed unique and remarkable qualities that may find use in industrial operations such as feed pelleting and food processing.

High Fischer ratio oligopeptides in food: sources, functions and application prospects

High Fischer ratio oligopeptides in food: sources, functions and application prospects

Decomposition iteration strategy for low-dose CT denoising.

In the medical field, computed tomography (CT) is a commonly used examination method, but the radiation generated increases the risk of illness in patients. Therefore, low-dose scanning schemes have attracted attention, in which noise reduction is essential. We propose a purposeful and interpretable decomposition iterative network (DISN) for low-dose CT denoising. This method aims to make the network design interpretable and improve the fidelity of details, rather than blindly designing or using deep CNN architecture. The experiment is trained and tested on multiple data sets. The results show that the DISN method can restore the low-dose CT image structure and improve the diagnostic performance when the image details are limited. Compared with other algorithms, DISN has better quantitative and visual performance, and has potential clinical application prospects.

Electroactive composite biofilms integrating Kombucha, Chlorella and synthetic proteinoid Proto-Brains.

In this study, we present electroactive biofilms made from a combination of Kombucha zoogleal mats and thermal proteinoids. These biofilms have potential applications in unconventional computing and robotic skin. Proteinoids are synthesized by thermally polymerizing amino acids, resulting in the formation of synthetic protocells that display electrical signalling similar to neurons. By incorporating proteinoids into Kombucha zoogleal cellulose mats, hydrogel biofilms can be created that have the ability to efficiently transfer charges, perform sensory transduction and undergo processing. We conducted a study on the memfractance and memristance behaviours of composite biofilms, showcasing their capacity to carry out unconventional computing operations. The porous nanostructure and electroactivity of the biofilm create a biocompatible interface that can be used to record and stimulate neuronal networks. In addition to in vitro neuronal interfaces, these soft electroactive biofilms show potential as components for bioinspired robotics, smart wearables, unconventional computing devices and adaptive biorobotic systems. Kombucha-proteinoids composite films are a highly customizable material that can be synthesized to suit specific needs. These films belong to a unique category of 'living' materials, as they have the ability to support cellular systems and improve bioelectronic functionality. This makes them an exciting prospect in various applications. Ongoing efforts are currently being directed towards enhancing the compositional tuning of conductivity, signal processing and integration within hybrid bioelectronic circuits.

Emulsifying property, antioxidant activity, and bitterness of soybean protein isolate hydrolysate obtained by Corolase PP under high hydrostatic pressure

Enzymatic hydrolysis of proteins can enhance their emulsifying properties and antioxidant activities. However, the problem related to the hydrolysis of proteins was the generation of the bitter taste. Recently, high hydrostatic pressure (HHP) treatment has attracted much interest and has been used in several studies on protein modification. Hence, the study aimed to investigate the effects of enzymatic hydrolysis by Corolase PP under different pressure treatments (0.1, 100, 200, and 300 MPa for 1–5 h at 50 °C) on the emulsifying property, antioxidant activity, and bitterness of soybean protein isolate hydrolysate (SPIH). As observed, the hydrolysate obtained at 200 MPa for 4 h had the highest emulsifying activity index (47.49 m2/g) and emulsifying stability index (92.98 %), and it had higher antioxidant activities (44.77 % DPPH free radical scavenging activity, 31.12 % superoxide anion radical scavenging activity, and 61.50 % copper ion chelating activity). At the same time, the enhancement of emulsion stability was related to the increase of zeta potential and the decrease of mean particle size. In addition, the hydrolysate obtained at 200 MPa for 4 h had a lower bitterness value and showed better palatability. This study has a broad application prospect in developing food ingredients and healthy foods.

Preparation and optical properties of rare earth fluoride and its related composite materials

Rare earth fluoride and its composite materials have shown broad application prospects in fields such as optoelectronics and photocatalysis. In this study, we prepared rare earth fluoride (β-NaYF4 nanocrystals) and its related composite materials (β-NaYF4/ZnO composite and GQDs@NaYF4 nanomaterials) using a solvothermal method and investigated their optical performance. The characterization and performance of the prepared materials were analyzed using a transmission electron microscope, X-ray diffraction, upconversion emission spectra, and fluorescence lifetime imaging microscopy. The results show that the crystal thickness of β-NaYF4 nanocrystals is approximately 45.0 nm when the F−: Ln3+ value is 6. Furthermore, X-ray diffraction analysis reveals that diffraction peak positions in β-NaYF4 nanocrystals correspond to the peak positions of standard card at different doping concentrations of Zn2+ Moreover, it was observed that the highest fluorescence lifetime of Tm3+ ion in 1G4 is 778 μs when the doping concentration of Zn2+ is 1 mol%. When the concentration of exonuclease III increases to 22.5U, the upconversion fluorescence emission intensity of GQDs@NaYF4 nanomaterial is about 34 ∗ 106 a.u. When the activation reaction time is 90 minutes, the upconversion emission intensity of GQDs@NaYF4 nanomaterial is about 37 ∗ 106 a.u. In conclusion, we successfully prepared rare earth fluoride and its composite materials with excellent optical properties through the solvothermal method.

Molecular Engineering to Achieve AIE-active Fluorophore with Near-infrared (NIR) Emission and Temperature-sensitive Property.

Near-infrared organic small molecule luminescent materials have the advantages of easy modification, high quantum efficiency, good biological affinity, and color adjustability; thus, have promising application prospects in the fields of photoelectric devices, sensitive detection, photodynamic therapy, and biomedical imaging. However, traditional organic luminescent molecules have the problems of short emission wavelength, aggregation-causing emission quenching, and low quantum yield. Herein, we successfully synthesized four D-π-A-D light-emitting molecules based on electron-withdrawing malonitrile group and different electron-donating arylamine groups. These compounds showed satisfactory solvatochromism, aggregation-induced emission, red and near-infrared fluorescence, high photoluminescence quantum efficiency and temperature response properties. This successful example of molecular engineering provides a valuable reference for the development of advanced NIR materials with AIE and temperature-sensitive properties.

Reconstruction of internal heat source in biological tissue using parallel particle swarm optimization

With the rapid development of engineering thermophysics, researches on human biological heat transfer phenomena has gradually shifted from qualitative to quantitative. The heat distribution information of human lesions is of great value for disease analysis, diagnosis, and treatment. It is a typical inverse problem of heat conduction that deriving the distribution of internal heat sources from the temperature distribution on the body surface. Differing from traditional numerical methods for solving heat conduction, this paper transforms such an inverse problem of bio-heat transfer into a direct one, thereby avoiding complex boundary conditions and regularization processes. To noninvasively reconstruct the internal heat source and its corresponding 3D temperature field in biological tissue, the parallel particle swarm optimization (PPSO) is used in the simulation module, where the position P(x, y, z) of point heat source in biological tissue and its corresponding temperature T are set as the optimization variables. Under a certain optimized sample, one can obtain the simulated temperature distributing on the surface of the module, then subtract the simulated temperature from the measured temperature of the same surface which was measured using a thermal infrared imager. If the absolute value of the difference is smaller, it indicates that the current sample is closer to the true location and temperature of the heat source. When the values of optimization variables are determined, the corresponding 3D temperature field is also confirmed. The simulation results show the simulated position and temperature of the heat source are very approximate with those of the real experimental module. The method presented in this paper has enormous potential and promising prospects in clinical research and application, such as tumor hyperthermia, disease thermal diagnosis technology, etc.

Substrate-Independent Superhydrophobic Coating Capable of Photothermal-Induced Repairability for Multiple Damages Fabricated via Simple Blade Coating.

Repairable superhydrophobic surfaces have promising application potential in many fields. However, so far, it is still a challenge to develop a superhydrophobic surface with repairability for multiple types of damage through a simple method. In this paper, a repairable superhydrophobic coating was obtained on various substrates by blade-coating mixtures of polydimethylsiloxane (PDMS), polyvinylidene fluoride (PVDF), and multiwalled carbon nanotubes (MWCNTs) modified with dopamine (PDA) and octadecylamine (ODA). The obtained coating has a good liquid-repellent property with a water contact angle above 150° and a water sliding angle of ∼6° and possesses an excellent absorbance (∼97%) in the wavelength range of 250-2500 nm. Due to its high absorbance, the coating displays an outstanding photothermal effect with a temperature rise of ∼65 °C under irradiation by 1.0 kW/m2 of simulated sunlight. Furthermore, after being degraded by multiple stimuli, including plasma treatment, acid/alkali/oil immersion, sand impact, and the icing-thawing cycle, the coating can recover superhydrophobicity via sunlight irradiation, demonstrating the good photothermal-induced repairability of the coating. It can be expected that the good water-repellent property, photothermal effect, and repairability give this coating a promising prospect in practical applications.