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Time-Series Mining (TSM) is an important research area since it shows great potential in practical applications. Deep learning models that rely on massive labeled data have been utilized for TSM successfully. However, constructing a large-scale well-labeled dataset is difficult due to data annotation costs. Recently, pre-trained models have gradually attracted attention in the time series domain due to their remarkable performance in computer vision and natural language processing. In this survey, we provide a comprehensive review of Time-Series Pre-Trained Models (TS-PTMs), aiming to guide the understanding, applying, and studying TS-PTMs. Specifically, we first briefly introduce the typical deep learning models employed in TSM. Then, we give an overview of TS-PTMs according to the pre-training techniques. The main categories we explore include supervised, unsupervised, and self-supervised TS-PTMs. Further, extensive experiments involving 27 methods, 434 datasets, and 679 transfer learning scenarios are conducted to analyze the advantages and disadvantages of transfer learning strategies, Transformer-based models, and representative TS-PTMs. Finally, we point out some potential directions of TS-PTMs for future work.

• The atomistic plastic deformation mechanisms in nano-sized Fe are revealed by combining both the in-situ transmission electron microscopy and molecular dynamics simulations. • Fe NWs show three distinct size regions, in which the full dislocation slip (d < 2.5 nm), twin variant reorientation (2.5 nm < d < 17 nm), and TB cracking (d > 17 nm) dominate plastic deformation, respectively. • The sample dimension can be utilized to construct the Fe interconnections in nano/micro-devices with specific deformability. Deformation twinning serves as an important mode of plastic dissipation processes in nanoscale body-centered cubic (BCC) metals, but its origin and spatio-temporal features are mysterious. Here, applying in situ tensile experiments, we report a strong size effect on mediating the twinning behaviors and twin boundary (TB)-dislocation interaction mechanisms in BCC iron (Fe) nanowires (NWs). There exists a critical diameter (d) of ∼2.5 nm, above which the deformation twinning rather than dislocation slip dominates the plasticity. Unlike the traditional reflection TBs, the intermediate isosceles TBs are consistently observed as mediated by the 1/12<111> partial dislocations. Moreover, we uncover two distinct TB-related deformation mechanisms, including twin variant re-orientation and TB cracking for NWs with d < 17 nm and d > 17 nm, respectively. Further molecular dynamics and statics simulations provide the basic underlying mechanisms for size-dependent plasticity, which have been largely overlooked in previous experimental investigations. Our findings highlight the importance of grain size in mediating the deformation behaviors in Fe, serving as possible guidance for exploring single-crystalline and poly-crystalline Fe-based materials (e.g. steel) with optimized mechanical performance. [Display omitted] [ABSTRACT FROM AUTHOR]

Type 2 diabetes is a group of metabolic diseases mainly characterized by chronic hyperglycemia. Diabetic kidney disease is the most common microvascular complication of diabetes.

Over the past 70 years, the semiconductor industry has undergone transformative changes, largely driven by the miniaturization of devices and the integration of innovative structures and materials. Two-dimensional (2D) materials like transition metal dichalcogenides (TMDs) and graphene are pivotal in overcoming the limitations of silicon-based technologies, offering innovative approaches in transistor design and functionality, enabling atomic-thin channel transistors and monolithic 3D integration. We review the important progress in the application of 2D materials in future information technology, focusing in particular on microelectronics and optoelectronics. We comprehensively summarize the key advancements across material production, characterization metrology, electronic devices, optoelectronic devices, and heterogeneous integration on silicon. A strategic roadmap and key challenges for the transition of 2D materials from basic research to industrial development are outlined. To facilitate such a transition, key technologies and tools dedicated to 2D materials must be developed to meet industrial standards, and the employment of AI in material growth, characterizations, and circuit design will be essential. It is time for academia to actively engage with industry to drive the next 10 years of 2D material research.

Birefringence is a fundamental optical property that can induce phase retardation of polarized light. Tuning the birefringence of liquid crystals is a core technology for light manipulation in current applications in the visible and infrared spectral regions. Due to the strong absorption or instability of conventional liquid crystals in deep-ultraviolet light, tunable birefringence remains elusive in this region, notwithstanding its significance in diverse applications. Here we show a stable and birefringence-tunable deep-ultraviolet modulator based on two-dimensional hexagonal boron nitride. It has an extremely large optical anisotropy factor of 6.5 × 10−12C2J−1m−1that gives rise to a specific magneto-optical Cotton–Mouton coefficient of 8.0 × 106T−2m−1, which is about five orders of magnitude higher than other potential deep-ultraviolet-transparent media. The large coefficient, high stability (retention rate of 99.7% after 270 cycles) and wide bandgap of boron nitride collectively enable the fabrication of stable deep-ultraviolet modulators with magnetically tunable birefringence.

Chitosan and chitooligosaccharides (COS), as derivatives of chitin through deacetylation reaction, have broad applications due to their good biodegradability, biocompatibility, and solubility. In addition, chitosan and COS are involved in cell wall morphogenesis and host–pathogen interactions in vivo. Chitin deacetylases (CDAs) are enzymes that can catalyze the de-N-acetylation of chitin. They are widely distributed in protozoa, algae, bacteria, fungi, and insects with important physiological functions. Compared with the traditional chemical method, enzymatic catalysis by CDAs provides an enzymatic catalysis method to produce chitosan and COS with controllable deacetylation site and environmental friendliness. These characteristics attract researchers to produce CDAs by fungicides or pesticides. However, researches on heterologous expression and directed evolution of CDAs are still lacking. In this review, we summarize the latest knowledge of CDAs, especially for heterologous expression systems and directed evolution strategies, which may contribute to the industrial production and future application of CDAs.

Magnetically influenced light-matter interaction provides a contactless, noninvasive and power-free way for material characterization and light modulation. Shape anisotropy of active materials mainly determines the sensitivity of magneto-optic response, thereby making magnetic two-dimensional (2D) materials suitable in achieving the giant magneto-birefringence effect as discovered recently. Consequently, relationship between magneto-birefringence response and shape anisotropy of 2D materials is critical but has remained elusive, restricting its widespread applications. Here, we report the highly sensitive and largely tunable magneto-coloration via manipulating the shape-anisotropy of magnetic 2D materials. We reveal a quadratic increasing relationship between the magneto-optic Cotton–Mouton coefficient and the lateral size of 2D materials and achieve a more than one order of magnitude tunable response. This feature enables the engineerable transmissive magneto-coloration of 2D materials by tailoring their shape anisotropy. Our work deepens the understanding of the tunability of magneto-optic response by size effect of active materials, offering various opportunities for their applications in vast areas where color is concerned.

Electro-optical effect-based liquid crystal devices have been extensively used in optical modulation techniques, in which the Kerr coefficient reflects the sensitivity of the liquid crystals and determines the strength of the device’s operational electric field. The Peterlin–Stuart theory and the O'Konski model jointly indicate that a giant Kerr coefficient could be obtained in a material with both a large geometrical anisotropy and an intrinsic polarization, but such a material is not yet reported. Here we reveal a ferroelectric effect in a monolayer two-dimensional mineral vermiculite. A large geometrical anisotropy factor and a large inherent electric dipole together raise the record value of Kerr coefficient by an order of magnitude, till 3.0 × 10−4m V−2. This finding enables an ultra-low operational electric field of 102–104V m−1and the fabrication of electro-optical devices with an inch-level electrode separation, which has not previously been practical. Because of its high ultraviolet stability (decay <1% under ultraviolet exposure for 1000 hours), large-scale production, and energy efficiency, prototypical displayable billboards have been fabricated for outdoor interactive scenes. This work provides new insights for both liquid crystal optics and two-dimensional ferroelectrics.A century-old clay material is discovered to show ferroelectricity in its monolayer thickness limit, leading to a record high electro-optical Kerr effect and sensitive electric field responsitivity.

Understanding and controlling the interfacial tension (IFT) of nanoconfined fluids has tremendous implications in scientific research and engineering applications. On the basis of the physical meaning of the equimolar dividing surface and the density distribution characteristic at the interface, we propose a simple model for the density profile at the vapor–liquid interface. The equimolar dividing surface and the surface of tension are assumed to coincide with each other in this work since the inhomogeneity of the interface is characterized by the proposed density profile model. Then, on the basis of the density distribution model, the density function theory (DFT) and the extended Peng–Robinson equation of state (PR EOS, which considers the effects of critical properties shift and capillary pressure) are used to estimate the confined interfacial properties and phase behavior in nanopores. Besides, the influences of temperature, pore radius, and wettability on IFT and capillarity are addressed. The developed model is validated as reliable for IFT calculation through comparison with the experimental data in the literature. Results show the following: (i) The IFT decreases with the reduction of pore size and the increase of temperature, and the decreasing rate is larger in smaller pores and higher temperatures. (ii) Capillary pressure increases with the decreasing pore size and the decreasing temperature, and it is more sensitive to pore size compared with the IFT. (iii) In the liquid phase-wet condition, as the contact angle decreases, the IFT decreases, while the capillary force increases, and the change rate is more obvious in smaller pores. Compared with other methods, the model for nanoconfined IFT proposed in this work, which is derived from the underlying physics mechanism, has a simper formulation with the similar reliability. Particularly, this work sheds light on the variation of IFT of hydrocarbons confined in nanopores of shale gas reservoirs, which provides an insight into the means of enhanced gas recovery in petroleum engineering.

Stevia rebaudianaBertoni is commonly called stevia and mostly found in the north east regions of South America. It is an herbaceous and shrubby plant belonging to the Asteraceaefamily. Stevia is considered as a natural sweetener and a commercially important plant worldwide. The leaves of S. rebaudianacontain steviol glycosides (SGs) which are highly potent and non-caloric sweeteners. The sweetening property of S. rebaudianais contributed to the presence of these high potency, calorie free steviol glycosides. SGs are considerably suitable for replacing sucrose and other artificial sweetening agents which are used in different industries and pharmaceuticals. SGs amount in the plant mostly varies from 8% to 10%, and the enhancement of SGs is always in demand. These glycosides have the potential to become healthier alternatives to other table sugars for having desirable taste and zero calories. SGs are almost 300 times sweeter than sucrose. Being used as alternative sugar intensifier the commercial value of this plant in biopharmaceutical, food and beverages industries and in international market is increasing day by day. SGs have made stevia an important part of the medicinal world as well as the food and beverage industry, but the limited production of plant material is not fulfilling the higher global market demand. Therefore, researchers are working worldwide to increase the production of important SGs through the intercession of different biotechnological approaches in S. rebaudiana. This review aims to describe the emerging biotechnological strategies and approaches to understand, stimulate and enhance biosynthesis of secondary metabolites in stevia. Conventional and biotechnological methods for the production of steviol glycosides have been briefly reviewed and discussed.

Distributed energy resources have been proven to be an effective and promising solution to enhance power system resilience and improve household-level reliability. In this paper, we propose a method to evaluate the reliability value of a photovoltaic (PV) energy system with a battery storage system (BSS) by considering the probability of grid outages causing household blackouts. Considering this reliability value, which is the economic profit and capital cost of PV+BSS, a simple formula is derived to calculate the optimal planning strategy. This strategy can provide household-level customers with a simple and straightforward expression for invested PV+BSS capacity. Case studies on 600 households located in eight zones of the US for the period of 2006 to 2015 demonstrate that adding the reliability value to economic profit allows households to invest in a larger PV+BSS and avoid loss of load caused by blackouts. Owing to the differences in blackout hours, households from the 8 zones express distinct willingness to install PV+BSS. The greater the probability of blackout, the greater revenue that household can get from the PV+BSS. The simulation example shows that the planning strategy obtained by proposed model has good economy in the actual operation and able to reduce the economic risk of power failure of the household users. This model can provide household with an easy and straightforward investment strategy of PV+BSS capacity.

Brain-computer interface (BCI) based on electroencephalogram (EEG) signals can provide a way for human to communicate with the outside world. This approach is independent of the body's peripheral nerves and muscle tissue. The brain-controlled robot is a new technology based on the brain-computer interface technology and the robot control technology. This technology allows the human brain to control a robot to perform a series of actions. The processing of EEG signals plays a vital role in the technology of brain-controlled robots. In this paper, the methods of EEG signal processing in recent years are summarized. In order to better develop the EEG signal processing methods in brain-controlled robots, this paper elaborate on three parts: EEG signal pre-processing, feature extraction and feature classification. At the same time, the correlation analysis methods and research contents are introduced. The advantages and disadvantages of these methods are analyzed and compared in this paper. Finally, this article looks forward to the EEG signal processing methods in the process of brain-controlled robots.

In agriculture, prolonged use of copper biocides increases the risk of development of Cu resistance and its accumulation in soil, demanding an alternative. In this paper, we report antimicrobial magnesium hydroxide nanoparticles (NPs) as an alternative to Cu biocides with low cytotoxicity. To improved bioavailability, Mg hydroxide NPs were synthesized followed by coating with water-soluble capping agents, trisodium citrate (zeta potential, ξ = −22 mV) or betaine (ξ = +35 mV). Electron microscopy study confirmed the formation of ∼10-nm-sized cubical NPs with citrate and ∼100-nm-sized lamellar NPs with betaine. As-synthesized Mg hydroxide NPs inhibited bacterial growth of X. alfalfae, P. syringae, and E. coliwithin 4 h. Significant bacterial growth inhibition and killing were observed at 24 h post-treatment. Phytotoxicity studies on tomato plants showed no significant tissue injury. Therefore, Mg hydroxide NPs have the potential to serve as a Cu alternative.

Hierarchical metal–organic frameworks (MOFs) have raised great concern on account of its enhanced multiplicity and control of internal sequences and structures. The controlled synthesis and multi-scale regulation of different morphologies of hierarchical MOFs is great crucial in practical applications. The research of hierarchical MOF makes outstanding contribution to the improvement of the performance of electrochemical energy storage device, and greatly improves its cyclic performance and capacitance. This review concentrates on synthesis methods, morphology and applications of zero, one, two-dimensional and other forms based hierarchical MOF and its derivative in electrochemical fields such as batteries, supercapacitors and electrocatalysis are reviewed. Based on theoretical knowledge and experimental experience, the future development of electrochemical energy storage and conversion device based on hierarchical MOF is proposed.

This article is dedicated to solving the problem of predefined-time cooperative control for autonomous surface vessels encountering model uncertainties and external perturbations. By virtue of the prescribed-time stable theory, a robust formation controller is constructed, with which the settling time of the cooperative system can be prescribed in advance. The controller is developed under the backstepping framework, where the dynamic surface control is applied to generate the real-time command. Considering the unmodeled autonomous surface vessel dynamics, the neural network-based nonlinear approximator is incorporated with minimum-learning-parameter technique. Under this scenario, the real-time control can be pursed with one parameter being estimated. Finally, comparative simulation examples are provided to exhibit the effectiveness and advantages of designed control strategies.

It is a long-lasting research topic to avoid the formation of oxidation layers on gallium-based liquid metals. This study has developed a simple general method for modification of the eutectic gallium–indium (EGaIn) surface with p-aniline derivatives to introduce a monolayer of organic molecules with versatile functional groups. The binding affinity of carboxylic acid groups, amine groups, or thiol groups with EGaIn is in the order SH > NH2> COOH. For the first time, it is evidenced that both NH2and SH groups can coexist on the EGaIn nanoparticle surface with the binding affinities of 30 and 70%, respectively. The formation of these organic molecules on the EGaIn surface antioxidizes and thus stabilizes the EGaIn nanoparticles, while increasing the conductivity of EGaIn significantly. The resulting EGaIn nanoparticles have very good distribution in both ethanol and aqueous solutions and rich surface chemistry, making them suitable for the following attachment of biomolecules such as aptamers, antibodies, or enzymes for biomedical applications. As an example, the EGaIn surface is successfully modified with p-aminobenzoic acid followed by the attachment of an insulin aptamer, which can be used for the electrochemical detection of insulin with the lowest detectable concentration limit of 1 pM. This study reveals the modification of EGaIn nanoparticles with p-aniline derivatives with versatile functional groups to antioxidize EGaIn in a biological environment, opening a door for gallium-based liquid metals toward biomedical applications.

Aluminum alloy matrix samples reinforced with short carbon fibers or hybrid SiCpcomposites were prepared, and friction and wear tests were carried out on a wear test machine using a rotation ring on a stationary disk at high load. Optical microscopy, scanning electron microscopy and energy-dispersive analysis of X-rays were used to investigate the composites, worn surface, wear debris and composition changes after wear. By comparison with Al alloy, Al/SCF and Al/SCF/SiCp, the results indicate that the incorporation of SCF into Al alloys improves the wear resistance significantly, the combination of a mechanically mixed layer formed on the worn surface and hard SiCpare responsible for the good tribological properties of the hybrid Al/SCF/SiCpcomposites at high load. During sliding, an obvious decrease in the temperature rise with SCF addition is attributed to the good anti-friction of SCF.

Collective behavior widely exists in nature, ranging from the macroscopic cloud of swallows to the microscopic cloud of colloidal particles. The behavior of an individual inside the collective is distinctive from its behavior alone, as it follows its neighbors. The introduction of such collective behavior in two-dimensional (2D) materials may offer new degrees of freedom to achieve desired but unattained properties. Here, we report a highly sensitive magneto-optic effect and transmissive magneto-coloration via introduction of collective behavior into magnetic 2D material dispersions. The increase of ionic strength in the dispersion enhances the collective behavior of colloidal particles, giving rise to a magneto-optic Cotton–Mouton coefficient up to 2700 T–2m–1which is the highest value obtained so far, being 3 orders of magnitude larger than other known transparent media. We also reveal linear dependence of magneto-coloration on the concentration and hydration ratios of ions. Such linear dependence and the extremely large Cotton–Mouton coefficient cooperatively allow fabrication of giant magneto-birefringent devices for color-centered visual sensing.

Laodelphax striatellus (Fallén) is a major pest of cultivated rice. Pymetrozine, a pyridine azomethine compound, represents a novel insecticide with a selective activity against sucking pests. The resistance of L. striatellus to thiamethoxam, nitenpyram, chlorpyrifos, and pymetrozine in five field populations, collected from Jiangsu, Anhui, and Zhejiang in China, was monitored from 2009 to 2011 in laboratory. All the populations kept susceptible to minor resistance to thiamethoxam and nitenpyram in the 3 yr (0.6- to 2.2-fold and 0.8- to 3.8-fold, respectively), while the insects developed low to high level resistance to chlorpyrifos (9.7- to 76.1-fold). Three populations were all susceptible to pymetrozine (1.1- to 2.1-fold) in 2009, but the Wuxi and Yancheng populations developed low level resistance to pymetrozine (5.5-fold and 5.3-fold, respectively) in 2011. Meanwhile, the resistance level of the selected strain reared in laboratory increased by 1.0-fold after 12-generation selection with pymetrozine. The realized heritability (h2) of resistance at different selection stages was estimated as 0.0470 (F1 to F13) and 0.2070 (F5 to F13) by using threshold trait analysis. It suggested that L. striatellus had the definite risk of resistance to pymetrozine.