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This study investigates the impact of various auxiliary cooling techniques on machinability, energy consumption, carbon emissions, and economic factors in the drilling process of AA7075T6 aluminium alloy using TiO2 and C-reinforced composites. The study employed various cooling conditions (dry, MQL, CO2, and hybrid MQL+CO2), with different cutting speeds and feed rates, to evaluate their effects on drilling characteristics. The findings indicated that the combined MQL and CO2 cooling notably enhanced the drilling process by reducing cutting forces by 32% and surface roughness by 65% compared to dry cutting. This synergy between lubrication and cooling significantly improves machinability, resulting in higher-quality machining outputs with smoother surfaces and more precise circularity. Energy analysis revealed that the MQL+CO2 method reduces energy consumption to 64% observed under dry conditions, underscoring its efficiency through better heat dissipation and reduced friction. Furthermore, this method demonstrates a significant reduction in carbon emissions, contributing to environmental sustainability. Economically, although initial costs associated with the implementation of cooling systems are higher, they are offset by reduced tool wear and energy costs, making it a viable solution for sustainable manufacturing practices.

Slope reliability analysis can be conducted based on representative slip surfaces (RSSs) more efficiently than the conventional analysis based on many potential slip surfaces (PSSs). Various methods for selecting RSSs are proposed to enhance the efficiency of slope reliability analysis. These methods, however, generally require a complex calculation procedure (e.g., evaluation of reliability index for each PSS and/or correlation coefficients among PSSs) that cannot adaptively single out the RSSs, and the selected RSSs by these methods are commonly related to the statistics of soil properties. This leads to the question of how to efficiently and adaptively identify the RSSs of a slope for a subsequent reliability analysis with many parametric studies. To answer this question, an adaptive K-means clustering-based RSSs (AKCBR) selection method has been recently developed that is able to select the RSSs adaptively and efficiently from many PSSs. The RSSs identified by AKCBR do not vary with the variation of soil statistics, such as the inherent spatial variability that is beneficial to slope reliability analysis involving many parametric studies. As such, limitations of the available methods are tackled in AKCBR. A comprehensive comparative study is conducted in this paper to explore in detail the strength and weaknesses of the AKCBR against the available methods. Four slope examples that represent four kinds of slope stability problems are considered. Results show that AKCBR provides reliability results comparable with the available methods in terms of probability of failure and the most dominant failure modes, and it is generally more efficient. The AKCBR can adaptively identify the RSSs of slopes belonging to different types, and the RSSs are statistically robust against the statistics of soil properties, which is beneficial to reliability analysis involving many parametric studies.

Dynamic memristors are considered as the optimal hardware devices for reservoir computing (RC) enabled by their nonlinear conductance variations. This significantly reduces the extensive training workload typically required by traditional neural networks. Lead halide perovskites, with their tunable band structure and active ion migration properties, have emerged as highly promising materials for developing dynamic memristors. However, large‐scale and consistently stable production remains a challenge for perovskite functional films, while lead elements' toxicity and environmental impact also partly restrict their practical device utilization. In this work, lead‐free copper‐based perovskite (i.e., CsCu2I3) films are prepared by thermal evaporation for constructing dynamic memristors. The effective conductivity modulation of CsCu2I3‐based memristor can be utilized in artificial neural networks, achieving a high handwritten digit recognition accuracy of 91.2%. In addition, the RC system is also constructed based on the dynamic behavior of the devices, by which a letter recognition accuracy of 98.2% with simple training is achieved. This technology provides a feasible pathway to construct copper‐based perovskite dynamic memristors for future neural network information processing. [ABSTRACT FROM AUTHOR]

AbstractAlzheimer’s disease (AD) is the most prevalent neurodegenerative disease. There are currently no effective interventions to slow down or prevent the occurrence and progression of AD. Neutrophil extracellular traps (NETs) have been proven to be tightly linked to AD. This project attempted to identify hub genes for AD based on NETs. Gene expression profiles of the training set and validation set were downloaded from the Gene Expression Omnibus (GEO) database, including non-demented (ND) controls and AD samples. NET-related genes (NETRGs) were collected from the literature. Differential analysis identified 21 AD differentially expressed NETRGs (AD-DE-NETRGs) majorly linked to functions such as defense response to bacterium as well as pathways including IL-17 signaling pathway, as evidenced by enrichment analyses of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Protein–protein interaction (PPI) network, Minutia Cylinder-Code (MCC) algorithm, and molecular complex detection (MCODE) algorithm in the CytoHubba plug-in were employed to identify five hub genes (NFKBIA, SOCS3, CCL2, TIMP1, ACTB). Their diagnostic ability was validated in the validation set using receiver operating characteristic (ROC) curves and gene differential expression analysis. A total of 16 miRNAs and 132 lncRNAs were predicted through the mirDIP and ENCORI databases, and a lncRNA–miRNA–mRNA regulatory network was constructed using Cytoscape software. Small molecular compounds such as Benzo(a)pyrene and Copper Sulfate were predicted to target hub genes using the CTD database. This project successfully identified five hub genes, which may serve as potential biomarkers for AD, proffering clues for new therapeutic targets. [ABSTRACT FROM AUTHOR]

The rapid advancement of neuromorphic computing demands innovative hardware solutions capable of efficiently mimicking the functionality of biological neural systems. In this context, dynamic memristors have emerged as promising candidates for realizing neuromorphic reservoir computing (RC) architectures. The dynamic memristors characterized by their ability to exhibit nonlinear conductance variations and transient memory behaviors offer unique advantages for constructing RC systems. Unlike recurrent neural networks (RNNs) that face challenges such as vanishing or exploding gradients during training, RC leverages a fixed‐size reservoir layer that acts as a nonlinear dynamic memory. Researchers can capitalize on their adaptable and efficient characteristics by integrating dynamic memristors into RC systems to enable rapid information processing with low learning costs. This perspective provides an overview of the recent developments in dynamic memristors and their applications in neuromorphic RC. It highlights their potential to revolutionize artificial intelligence hardware by offering faster learning speeds and enhanced energy efficiency. Furthermore, it discusses challenges and opportunities associated with integrating dynamic memristors into RC architectures, paving the way for developing next‐generation cognitive computing systems. [ABSTRACT FROM AUTHOR]

Most stretchable film strain sensors generally present nonlinear electrical responses to applied strain, leading to an inaccurate acquisition of sophisticated signals, difficult signal processing, and zero‐calibration, which hampers practical applications severely. Here, a Janus hetero‐structured microarray film sensor is developed by in‐situ growth of silver nanoparticles on the surface of micro‐patterned elastomer films fabricated via low‐temperature imprinting followed by scraping‐induced particle trapping. Heterogeneous property designs in both modulus and electrical conductivity via introducing polymer microarrays enable modulating the electron transport manner in the conductive layer of elastic Janus films upon stretching, allowing to tune signal linearity effectively. Therefore, such a hetero‐structured film sensor shows good signal linearity (fluctuation of gauge factor [GF] below ±0.02) and relatively high sensitivity (GF > 10) within 55% strain, a detection limit of 0.2% strain, and a response/recovery time of 16.3/46.9 ms, respectively. Correspondingly, it enables monitoring human respiration and body motion with higher resolution compared with the nonlinear one, meanwhile, it is capable of detecting tiny pressure to discriminate braille alphabets via touch identification. Overall, it unveils a simple strategy to fabricate film strain sensors for high‐resolution healthcare and body motion monitoring, as well as electronic skins toward tactile sensing and touch identification. [ABSTRACT FROM AUTHOR]

Stretchable film strain sensors show potential applications in healthcare and human‐machine interfacing, while poor signal linearity restricts their practical applications owing to inaccurate and instable strain indication. Signal sensitivity and linearity can be improved via constructing hetero‐modulus microstructure on elastomeric substrate to some extent, though it is challenging to construct hetero‐structure with distinct modulus differences for electrical signal linearity modulation over a wide strain range. Herein, a simple strategy is proposed to tune signal sensitivity, linearity, and detection range of stretchable strain sensors by adjusting the distribution of rigid polystyrene (PS) nanospheres coated on electrospun thermoplastic polyurethane (TPU) fiber mats. Heterostructure characteristics can be controlled by spray coating times of PS nanospheres, which are immobilized onto the fiber mats by weak swelling of TPU and the linking layer of reduced graphene oxide (rGO) between TPU and PS induced by hydrogen bonding and π–π stacking. Relatively, the sensors with moderate spray coating times of PS nanospheres show balanced signal sensitivity and linearity over a strain range of 0–80%, as well as fast response to tensile strain and good signal reproducibility. Such elastomeric film strain sensors can be used for monitoring physiological activities and interfacing human hand and bionic fingers. [ABSTRACT FROM AUTHOR]

Photonic synapses integrate sensing and processing within a single device, making them promising candidates for emulating the visual perception of a biological retina. Most retinomorphic photonic synapses achieve image pre‐processing by differentially responding to red, green, and blue (RGB). However, the impact of invisible ultraviolet (UV) light on the retina remains insufficiently explored, hindering the perception of the full spectrum by retinomorphic devices. Herein, a photonic synapse is constructed with strong UV absorption of Poly[(9,9‐dioctylfluorenyl‐2,7‐diyl)‐co‐(4,4′‐(N‐(4‐sec‐butylphenyl) diphenylamine)] (TFB) as photosensitive layer. The device exhibits synaptic properties of long‐term memory (LTM) and short‐term memory (STM) at different UV radiation stages. Extracting the electrical conductance of the device under UV radiation generates patterns of different resolutions, facilitating the simulation of retinal damage's impact on object perception. Moreover, an electronic eye system, incorporating the photonic synapse under UV radiation, successfully replicates pupil constriction and eye‐closing behaviors akin to those observed in a real biological eye. This result underscores the authenticity of retinomorphic devices, expending a novel concept for the future development of visuomorphic computing. [ABSTRACT FROM AUTHOR]

Jiaguyou 404 was a new combination of high-quality hybrid rice bred by Quanzhou Institute of Agricultural Sciences, which was bred by crossing Jiagu A, a three-line sterile line with good quality and disease resistance, as the female parent and Quanhui 404 as the male parent. The combination had the characteristics of good plant-leaf shape, large panicle and multiple grains, moderate plant height and plant type, high and stable yield, and good rice quality, which was examined and approved by Fujian Crop Variety Approval Committee in 2022. The breeding process, characteristics, high-yield cultivation and seed production technologies of the new hybrid rice combination, namely Jiaguyou 404 were introduced . [ABSTRACT FROM AUTHOR]

Terahertz high-data communication creates numerous demands for terahertz wave amplitude modulation. Here, we experimentally demonstrate a high-speed terahertz wave modulator based on 4-N,N-dimethylamino-4'-N'-methyl-stilbazolium tosylate (DAST)/Si hybrid structure. An externally modulated 808-nm pumping laser is utilized to generate photoexcited free carriers at the DAST medium. With the increase of illumination laser intensity, the modulation depth continues to increase in the frequency range from 0.23 to 0.35 THz. A dynamic amplitude modulation at 0.25-THz carrier wave shows that the our modulator provides a modulation speed of 1.26 MHz with a depth of up to 53% at an external pump laser irradiance of 3.5 W/cm2. Our present DAST/Si hybrid structure provides a practicable route to achieve effective signal modulation for terahertz communication system.

Fluidic oscillators (FOs) can be used as an efficient fluidic vibration tool to solve high friction problems in extended-reach wells. However, the complex mechanism of FOs makes the design challenging, and the dynamic erosion behavior inside FOs is still unclear. In this paper, new FOs are proposed and the working characteristics under the influence of periodic particle-laden jets are investigated. Firstly, the results reveal the working mechanism of new FOs, showing that the generation of pressure pulses is closely connected with periodic jet switching and the development of vortices. Secondly, the important performance parameters, i.e., pressure pulse and oscillation frequency, are extensively studied through numerical simulation and experimental verification. It is found that the performance can be optimized by adjusting the tool structure according to different engineering requirements. Finally, the oscillating solidliquid two-phase flow inside FO is studied. It is demonstrated that the accumulation of particles leads to a significant reduction in performance. The results also reveal five locations that are susceptible to erosion and the erosion behavior of these locations are studied. It has been shown that the periodic jet causes fluctuations in the amount of erosion at the outlet and splitter. This research can provide valuable references for the design and optimization of vibration friction-reduction tools. [ABSTRACT FROM AUTHOR]

Artificial synaptic devices are the cornerstone of neuromorphic electronics. The development of new artificial synaptic devices and the simulation of biological synaptic computational functions are important tasks in the field of neuromorphic electronics. Although two-terminal memristors and three-terminal synaptic transistors have exhibited significant capabilities in the artificial synapse, more stable devices and simpler integration are needed in practical applications. Combining the configuration advantages of memristors and transistors, a novel pseudo-transistor is proposed. Here, recent advances in the development of pseudo-transistor-based neuromorphic electronics in recent years are reviewed. The working mechanisms, device structures and materials of three typical pseudo-transistors, including tunneling random access memory (TRAM), memflash and memtransistor, are comprehensively discussed. Finally, the future development and challenges in this field are emphasized. [ABSTRACT FROM AUTHOR]