Important Applications Research Articles

Highly Sensitive Paper-Based Force Sensors with Natural Micro-Nanostructure Sensitive Element.

Flexible paper-based force sensors have garnered significant attention for their important potential applications in healthcare wearables, portable electronics, etc. However, most studies have only used paper as the flexible substrate for sensors, not fully exploiting the potential of paper's micro-nanostructure for sensing. This article proposes a novel approach where paper serves both as the sensitive element and the flexible substrate of force sensors. Under external mechanical forces, the micro-nanostructure of the conductive-treated paper will change, leading to significant changes in the related electrical output and thus enabling sensing. To demonstrate the feasibility and universality of this new method, the article takes paper-based capacitive pressure sensors and paper-based resistive strain sensors as examples, detailing their fabrication processes, constructing sensing principle models based on the micro-nanostructure of paper materials, and testing their main sensing performance. For the capacitive paper-based pressure sensor, it achieves a high sensitivity of 1.623 kPa-1, a fast response time of 240 ms, and a minimum pressure resolution of 4.1 Pa. As for the resistive paper-based strain sensor, it achieves a high sensitivity of 72 and a fast response time of 300 ms. The proposed new method offers advantages such as high sensitivity, simplicity in the fabrication process, environmental friendliness, and cost-effectiveness, providing new insights into the research of flexible force sensors.

Accelerating Discovery of Polyimides with Intrinsic Microporosity for Membrane‐Based Gas Separation: Synergizing Physics‐Informed Performance Metrics and Active Learning

AbstractPolymer membranes are widely used for gas separation, addressing critical environmental and energy issues. Nevertheless, crafting high‐performance polymer membranes remains a challenging task, often relies on labor‐intensive trial‐and‐error experiments. Different from the traditional Edisonian approach, machine learning offers significant potential to expedite the design of new polymer membranes for gas separation, yet it faces a substantial hurdle due to limited data availability. To overcome this challenge, in this study two physics‐informed performance metrics are introduced, namely fractional free volume and average void size, to assess the separation performance of polymer membranes. By employing active learning and multi‐target screening, top‐performing polyimides with intrinsic microporosity are efficiently discovered from a pool of 155 610 candidates, through calculations of only 709 (0.45%) in the entire search space. As validated by molecular simulations, the top‐performing polyimides exhibit exceptional separation performance for CO2/N2, CO2/CH4, and O2/N2 mixtures, superior to existing polymers and surpassing the current upper bound. The utilization of physics‐informed performance metrics provides a novel strategy to advance the design and accelerate the discovery of new polymer membranes for gas separation and many other important applications.

C-type natriuretic peptide treatment before in vitro maturation enhances maturation of yak oocytes and developmental competence of their crossbred embryos

ABSTRACT The effects of C-type natriuretic peptide (CNP) pre-treatment on the in vitro maturation (IVM) and developmental competence of yak (Bos grunniens) oocytes were evaluated. The results showed that 100 nM CNP could effectively maintain meiotic arrest of yak oocytes in vitro within 6 h. Yak oocytes matured in two-step IVM (pre-IVM with 100 nM CNP for 6 h followed by conventional IVM for 28 h) yielded a significantly (P < .05) increased cleavage rate, blastocyst rate after in vitro fertilization with cattle spermatozoa compared to the conventional one-step IVM method. The density of transzonal projections (TZPs) decreased after 6 h standard IVM (P < .05), whereas, COCs pre-IVM with 100 nM CNP for 6 h maintained the same density of TZPs compared to the fresh COCs. This pre-IVM resulted in lesser reactive oxygen species level (P < .05). Two-step IVM resulted in the increased glutathione levels, mRNA expression levels of BCL2, BMP15, and GDF9 (P < .05) in oocytes. In conclusion, these results indicate that CNP treatment (100 nM, 6 h) before IVM could enhance the maturation of yak oocytes and developmental competence of their crossbred embryos. This may have important applications in in vitro production of yak crossbred embryos.

Advances in reprogramming of energy metabolism in tumor T cells.

Cancer is a leading cause of human death worldwide, and the modulation of the metabolic properties of T cells employed in cancer immunotherapy holds great promise for combating cancer. As a crucial factor, energy metabolism influences the activation, proliferation, and function of T cells, and thus metabolic reprogramming of T cells is a unique research perspective in cancer immunology. Special conditions within the tumor microenvironment and high-energy demands lead to alterations in the energy metabolism of T cells. In-depth research on the reprogramming of energy metabolism in T cells can reveal the mechanisms underlying tumor immune tolerance and provide important clues for the development of new tumor immunotherapy strategies as well. Therefore, the study of T cell energy metabolism has important clinical significance and potential applications. In the study, the current achievements in the reprogramming of T cell energy metabolism were reviewed. Then, the influencing factors associated with T cell energy metabolism were introduced. In addition, T cell energy metabolism in cancer immunotherapy was summarized, which highlighted its potential significance in enhancing T cell function and therapeutic outcomes. In summary, energy exhaustion of T cells leads to functional exhaustion, thus resulting in immune evasion by cancer cells. A better understanding of reprogramming of T cell energy metabolism may enable immunotherapy to combat cancer and holds promise for optimizing and enhancing existing therapeutic approaches.

Synthesis of Superelastic, Highly Conductive Graphene Aerogel/Liquid Metal Foam and its Piezoresistive Application.

Graphene aerogel (GA) has important application potential as piezoresistive sensors due to its low density, high conductivity, high porosity, and good mechanical properties. However, the fabrication of GA-based sensors with good mechanical properties and excellent sensing performance is still challenging. Herein, liquid- metal-modified GAs (GA/LM) are proposed for the development of an excellent GA-based sensor. GA/LM with three-dimensional interconnected layered structure exhibits excellent compressive stress of 41 KPa and fast response time (<20 ms). While generally flexible GA composites cannot be compressed beyond 80 % strain without plastic deformation, GA/LM demonstrates a high compressive strength of 60 kPa under a strain of 90 %. A real-time pressure sensor was fabricated based on GA/LM-2 to monitor swallowing, pulse beating, finger, wrist and knee bending, and even plantar pressure during walking. These excellent features enable potential applications in health detection.

Photoredox-Catalyzed Hydroacylation of Azobenzenes with Carboxylic Acids.

Acyl hydrazides are widely found in bioactive compounds and have important applications as versatile synthetic intermediates. In the current report, a photoredox-catalyzed hydroacylation of azobenzenes was disclosed with carboxylic acids as the acylation reagent, affording a variety of N,N'-disubstituted hydrazides. The process possesses the advantages of mild reaction conditions, broad substrate scope, and high efficiency. Preliminary mechanistic investigation indicated that the addition of an acyl radical to the azo compound should be involved.

Arc-Scanning Synthetic Aperture Radar for Accurate Location of Targets

The purpose of this article is to present the advantages that the use of arc-scanning synthetic aperture radar (Arc-SAR) would provide for accurate location of target to the weapon systems. Arc-SAR systems have an extraordinary capacity of angular discrimination of the targets, this fact make possible they can be used for the precise location of targets by replacing the large antennas required by the monopulse systems, used in this kind of applications, with a small rotating antenna. However, to carry out the real-time location of targets with the current processors a much more complex signal processing is needed. A simulator has been developed in this work, which allows the comparison of the theoretical and experimental results obtained by the classical systems against those obtained with the proposed Arc-SAR system working in the millimeter frequency bands. The results obtained demonstrate the ability of the proposed technique to accurately locate targets. This confirms that the obtained precisions allow the use the presented system in some important applications as Sense &amp; Avoid (S&amp;A) and weapon-pointing systems. Finally, possible applications of these techniques are described, especially useful is onboard sensors, because of the small size and weight of the antenna needed to implement an Arc-SAR system.

Assessment of agricultural land suitability for cereal crops based on the analysis of soil physico-chemical characteristics

This research aimed at evaluation of a given land resource suitable for selected rain fed crops production (malt barley, wheat and teff) in Ambesh watershed. It also quantified suitable land and classified into the land mapping units (LMUs), and presents a land suitability map. Land suitability assessment (LSA) made using climatic condition, topography, soil physical and chemical properties as a major factor integrated with a multi criteria decision making (MCDM) analysis in Ambesh watershed. Fourteen composite soil samples were taken by categorizing the watershed into different land mapping units (LMUs) and analyzed in a soil laboratory. Climatic data, rainfall was obtained from two meteorological stations nearby to the study area. Temperature data derived from Landsat 8 satellite thermal bands data. Data obtained from the soil laboratory and others were finally analyzed using ArcGIS environment and priority estimation tool (PriEsT) software’s. Weighted Sum Overlay was implemented to investigate the final LSA map of the watershed. Results revealed that LMUs, VRe–LPq and LPK.Pq–FLc LMUs has higher overall suitability for all the selected rain fed crops. However, LMUs (VRe–NTu and NTu–VRe) has lower overall suitability values particularly for S1 suitability class (0.05% and 10.6%, respectively). The least suitable LMU is VRe–NTu with 0.05% S1 suitability class and above 99% of the land laid under the suitability classes of moderately suitable, marginally suitable and not suitable for the selected land utilization types. Moreover, about 219.06 ha (17.76%), 217.6 ha (17.64%), 168.9 ha (13.7%), of land are highly suitable for malt barley, teff and wheat crop production, respectively. In conclusion, during MCDM, classifying the land into closer homogeneities (LMU) an important application of LSA integrated with remote sensing and GIS for a better decision making. Meanwhile, majority (above two third’s) of the land in the watershed is under moderate and marginally suitable, it needs intensive land management activities to increase the land qualities and obtain high yields. LSA recommended before land utilization decision has to be made. It is also important to classifying the land into LMUs to make it more homogeneous for sample taking and reducing the prestigious soil laboratory analysis costs.

Investigating Ultrafast Electron Transfer in Graphene and Its Derivatives Composites by Femtosecond Transient Absorption Spectroscopy

AbstractAs excellent functional materials, the composite materials based on graphene and its derivatives (GNDs) have lots of important application values in the emerging fields such as solar energy conversion, and the exploration of electron (or energy) transfer properties of those composites is the key for revealing their further applications. In this review, femtosecond transient absorption spectroscopy (TAS) has been introduced as an essential technique to understand the carrier behaviors in GNDs composites, as well as the advancements of TAS. The specific examples of electron transport in various composite materials characterized by TAS are summarized and discussed, which consist of GNDs with semiconductor quantum dots (QDs), organic dyes, organic polymers, perovskites and other materials, respectively. This review provides a deep insight into the electron transfer (ET) kinetics of various GNDs composites from the perspective of TAS.

Research on denoising and enhancing methods of medical images based on convolutional neural networks

SummaryIn the process of modern medical diagnosis, medical image‐assisted diagnosis plays a very important role. However, the process of medical image acquisition, will be affected by various types and degrees of noise, and there will be a certain probability of producing strip artifacts, which will interfere with the doctor's diagnosis, analysis, and treatment of diseases to a certain extent. However, the traditional medical image denoising method will cause problems such as image edge blurring and detail loss, and it is difficult to achieve the balance between noise removal and detail information retention. Therefore, denoising medical images and improving the accuracy of denoising as much as possible have very important scientific research significance and clinical application value. Based on this, this article proposes a medical image denoising method based on a double residual convolutional neural network and compares it with traditional medical images denoising methods such as K‐SVD, BM3D, and PNLM3. Experimental results show that the medical image denoising method based on the double residual convolutional neural network proposed in this article has excellent performance.

Numerical Evaluation of the Elastic Moduli of AlN and GaN Nanosheets.

Two-dimensional (2D) nanostructures of aluminum nitride (AlN) and gallium nitride (GaN), called nanosheets, have a graphene-like atomic arrangement and represent novel materials with important upcoming applications in the fields of flexible electronics, optoelectronics, and strain engineering, among others. Knowledge of their mechanical behavior is key to the correct design and enhanced functioning of advanced 2D devices and systems based on aluminum nitride and gallium nitride nanosheets. With this background, the surface Young's and shear moduli of AlN and GaN nanosheets over a wide range of aspect ratios were assessed using the nanoscale continuum model (NCM), also known as the molecular structural mechanics (MSM) approach. The NCM/MSM approach uses elastic beam elements to represent interatomic bonds and allows the elastic moduli of nanosheets to be evaluated in a simple way. The surface Young's and shear moduli calculated in the current study contribute to building a reference for the evaluation of the elastic moduli of AlN and GaN nanosheets using the theoretical method. The results show that an analytical methodology can be used to assess the Young's and shear moduli of aluminum nitride and gallium nitride nanosheets without the need for numerical simulation. An exploratory study was performed to adjust the input parameters of the numerical simulation, which led to good agreement with the results of elastic moduli available in the literature. The limitations of this method are also discussed.

Exploration of Intelligent Teaching Means of Ideological and Political Education in Colleges and Universities Under the Background of “Mass Entrepreneurship”

The concept of “great ideological and political education” requires comprehensive ideological education to better achieve the educational goals of “innovation and entrepreneurship.” This article analyzes and explores the intelligent teaching methods of ideological and political education in universities under the background of “innovation and entrepreneurship,” and constructs an intelligent teaching system of ideological and political education in universities under this background. The experimental results show that the stability of the system reaches 95.2%, and the learning efficiency of students has been improved by 11.5%. This work provides important application guidance for big data analysis and IoT sensor data.

Experimental and Theoretical Investigation of the Mechanism of the Reduction of O2 from Air to O22- by VIVO2+-N,N,N-Amidate Compounds and Their Potential Use in Fuel Cells.

The two-electron reductive activation of O2 to O22- is of particular interest to the scientific community mainly due to the use of peroxides as green oxidants and in powerful fuel cells. Despite of the great importance of vanadium(IV) species to activate the two-electron reductive activation of O2, the mechanism is still unclear. Reaction of VIVO2+ species with the tridentate-planar N,N,N-carboxamide (ΗL) ligands in solution (CH3OH:H2O) under atmospheric O2, at room temperature, resulted in the quick formation of [VV(═O)(η2-O2)(κ3-L)(H2O)] and cis-[VV(═O)2(κ3-L)] compounds. Oxidation of the VIVO2+ complexes with the sterically hindered tridentate-planar N,N,N-carboxamide ligands by atmospheric O2 gave only cis-[VV(═O)2(κ3-L)] compounds. The mechanism of formation of [VV(═O)(η2-O2)(κ3-L)(H2O)] (I) and cis-[VV(═O)2(κ3-L)] (II) complexes vs time, from the interaction of [VIV(═O)(κ3-L)(Η2Ο)2]+ with atmospheric O2, was investigated with 51V, 1H NMR, UV-vis, cw-X-band EPR, and 18O2 labeling IR and resonance Raman spectroscopies revealing the formation of a stable intermediate (Id). EPR, MS, and theoretical calculations of the mechanism of the formation of I and II revealed a pathway, through a binuclear [VIV(═O)(κ3-L)(H2O)(η1,η1-O2)VIV(═O)(κ3-L)(H2O)]2+ intermediate. The results from cw-EPR, 1H NMR spectroscopies, cyclic voltammetry, and the reactivity of the complexes [VIV(═O)(κ3-L)(Η2Ο)2]+ toward O2 reduction fit better to an intermediate with a binuclear nature. Dynamic experiments in combination with computational calculations were undertaken to fully elucidate the mechanism of the O2 reduction to O22- by [VIV(═O)(κ3-L)(Η2Ο)2]+. The galvanic cell {Zn|VIII,VII||Id, [VIVO(κ3-L)(H2O)2]+|O2|C(s)} was manufactured, demonstrating the important applicability of this new chemistry to Zn|H2O2 fuel cells technology generating H2O2 in situ from the atmospheric O2.

Ultra-Efficient and Cost-Effective Platinum Nanomembrane Electrocatalyst for Sustainable Hydrogen Production

HighlightsA percolating network of distorted 2D Pt nanomembranes was synthesized by polymer surface buckling-enabled exfoliation for hydrogen evolution reaction.The 2D Pt nanomembrane enabled important technological applications for its high efficiency, low costs, and good stability, making it potential alternative to commercial Pt/C.Our 2D Pt nanomembranes offer insights into a new mechanism for efficient catalyst design strategy: lattice distortion-induced heterogeneous strain.

Ratiometric Fluorescent Probe for Real-Time Detection of β-Galactosidase Activity in Lysosomes and Its Application in Drug-Induced Senescence Imaging.

Senescence is an important biological process, which leads to the gradual degradation of its physiological function and increases morbidity and mortality. Herein, a novel ratiometric fluorescent probe (P1) was constructed by using benzothiazolyl acetonitrile dye as fluorophore, exhibiting significantly enhanced blue-shifted emission to indicate the activity of β-galactosidase (β-gal), a commonly used biomarker for the detection of senescent cells. After incubation with β-gal, the excimer emission of P1 at 620 nm was weakened, while the emission at 533 nm was significantly enhanced, forming an obvious ratiometric probe with high sensitivity and low detection limit (2.7 mU·mL-1). More importantly, probe P1 can locate lysosomes accurately, allowing us to monitor the emergence of living cell senescence in real time. P1 was successfully used to detect β-gal activity in PC-12 cells, Hep G2 cells, and RAW 264.7 cells. It showed strong green fluorescence signal in senescent cells and red fluorescence signal in normal cells, indicating that it can detect endogenous senescence-related β-gal content in living cells. For in vivo drug-induced senescence imaging, after 5 weeks of injection of D-galactose or hydroxyurea, the mice showed significant fluorescence enhancement in specific channels to indicate the activity of β-gal in vivo. At the same time, the senescence of cell-specific organs and skin tissues at the organ level were also detected, which proved that the drug-induced senescence of brain, skin, and muscle tissues was the most serious. These results supported the important application value of P1 in senescence biomedical research.

Offline and online task allocation algorithms for multiple UAVs in wireless sensor networks

In recent years, UAV techniques are developing very fast, and UAVs are becoming more and more popular in both civilian and military fields. An important application of UAVs is rescue and disaster relief. In post-earthquake evaluation scenes where it is difficult or dangerous for human to reach, UAVs and sensors can form a wireless sensor network and collect environmental information. In such application scenarios, task allocation algorithms are important for UAVs to collect data efficiently. This paper firstly proposes an improved immune multi-agent algorithm for the offline task allocation stage. The proposed algorithm provides higher accuracy and convergence performance by improving the optimization operation. Then, this paper proposes an improved adaptive discrete cuckoo algorithm for the online task reallocation stage. By introducing adaptive step size transformation and appropriate local optimization operator, the speed of convergence is accelerated, making it suitable for real-time online task reallocation. Simulation results have proved the effectiveness of the proposed task allocation algorithms.

Lean manufacturing + healthcare= lean healthcare, a way to optimize efficiency in the healthcare sector

The concept of Lean Manufacturing arises within the Toyota Production System (TPS) with the aim of eliminating all activities that do not generate value to enhance and increase productivity. Lean Manufacturing is applied in the West, and the concept transforms into Lean Manufacturing (LM). This concept no longer belongs solely to the automotive sector; all its tools have now migrated to all activities of daily life. An important application, particularly in dealing with human lives, is in the healthcare sector, specifically in hospitals. This gives rise to the concept of Lean Healthcare, which has broad applications, often resulting in process improvements, the elimination of non-value-generating activities, and better resource management.

Research on establishing a joint time-scale of pulsar time and atomic time based on a wavelet analysis method

ABSTRACT Pulsar time has different physical mechanisms from atomic time, and these two time-scales are complementary in terms of stability performance. The joint timekeeping of pulsar and atomic time is currently an important application direction. Our research utilizes a wavelet analysis method to perform multiscale analysis of time signals in both the time and frequency domains, and assigns corresponding weights to different frequency bands for synthesis, which solves the problem of balancing long- and short-term stability in unified weighted synthesis. In this paper, a joint time-scale APT (atomic pulsar time) is obtained by a fusion of pulsar ensemble time (EPT) and atomic time TA(NTSC) (AT) based on wavelet analysis. The results show that APT effectively integrates the stability advantages of both EPT and AT, and the short-term stability of APT at 0.4 yr is consistent with that of AT, reaching 5.6 × 10−15 as evaluated by σz variance. The stability of APT remains consistent with EPT after 3.2 yr, and the long-term stability at 13.1 yr is close to 1.3 × 10−16, perfectly retaining the excellent long-term stability characteristics of pulsar time. The root mean square of APT’s clock difference relative to TT(BIPM) is much lower than that of TA(NTSC). Moreover, we propose ways to improve the stability of APT through experimental comparisons. The results indicate that APT has the potential to serve as a reference for steering UTC(NTSC) in the future, improving the long-term timekeeping capability of local atomic time in China, thereby comprehensively improving the stability and reliability of China’s time reference.

Picard and Adomian solutions of nonlinear fractional differential equations system containing Atangana – Baleanu derivative

In this paper, we apply two methods for solving nonlinear system of fractional differential equations (FDEs); these two methods are Picard and Adomian decomposition methods (ADM). The type of fractional derivative in this system will be the Atangana–Baleanu derivative. The existence and uniqueness of the solution will be proved. In addition, the convergence of ADM series solution and the maximum expected error will be discussed. Some numerical examples will be solved by using these two method and a comparison between their solutions will be done. There exist an important application to these types of systems, this application is the fractional-order rabies model and it will be solved here. From the obtained results, it is noticed that the obtained results from using these two methods are coincide with each other, and also these results are coincide with the obtained results from the classical fractional derivatives such as Caputo sense.

Entire Monogenic Functions of Given Proximate Order and Continuous Homomorphisms

Infinite order differential operators appear in different fields of mathematics and physics. In the past decade they turned out to play a crucial role in the theory of superoscillations and provided new insight in the study of the evolution as initial data for the Schrödinger equation. Inspired by the infinite order differential operators arising in quantum mechanics, in this paper we investigate the continuity of a class of infinite order differential operators acting on spaces of entire hyperholomorphic functions. Precisely, we consider homomorphisms acting on functions in the kernel of the Dirac operator. For this class of functions, often called monogenic functions, we introduce the proximate order and prove some fundamental properties. As an important application, we are able to characterize infinite order differential operators that act continuously on spaces of monogenic entire functions.