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The sustainability of global agricultural produce supply chains is crucial for ensuring global food security, fostering environmental protection, and advancing socio-economic development. This study integrates bibliometric analysis, knowledge mapping, and the ABCDE framework to conduct a comprehensive qualitative and quantitative analysis of 742 relevant articles from the Web of Science core database spanning January 2009 to July 2023. Initially, bibliometric analysis and knowledge mapping reveal the annual progression of research on the sustainability of global agricultural produce supply chains, the collaborative networks among research institutions and authors, and the geographic distribution of research activities worldwide, successfully pinpointing the current research focal points. Subsequently, the ABCDE framework, constructed from the quantitative findings, helps us identify and comprehend the antecedents, barriers and challenges, impacts, and driving forces affecting the sustainability of these supply chains. The study identifies globalization and technological advancement as the primary forces shaping the sustainability of agricultural produce supply chains, despite them also posing challenges such as resource constraints and environmental pressures. Moreover, the application of innovative technologies, the optimization of organizational models, and active stakeholder engagement are key to propelling supply chains toward more sustainable development, exerting a profound impact on society, the environment, and the economy. In conclusion, this study suggests future research directions. The integrated methodology presented offers new perspectives and deep insights into the complexities of sustainable global agricultural produce supply chains, demonstrating its potential to foster knowledge innovation and practical applications, providing valuable insights for academic research and policy formulation in this domain. [ABSTRACT FROM AUTHOR]

In the new wave of globalization, China's pre-cooked meal industry has rapidly emerged as a significant player in the food supply chain domain, owing to its convenience and diverse choices. Amidst intensifying market competition, crafting a sustainable supply chain for overseas expansion has become an indispensable core element for driving corporate internationalization. This study focuses on the sustainability generation mechanism of the overseas supply chain of Chinese pre-cooked meal A-share listed companies, employing the technology-organization-environment (TOE) framework and fuzzy-set qualitative comparative analysis (fsQCA) method. Herein, an in-depth analysis of 388 data points from 17 listed companies has been conducted. The study systematically reveals the key factors affecting the sustainability of overseas supply chains and identifies three critical sustainability generation paths: the technology-driven and norm compliance model (path 1), the market sensitivity and product innovation model (path 2), and the robust operation and risk control model (path 3). The present study not only introduces a novel perspective on the application of a TOE framework within the realms of sustainable supply chain management and environmental, social, and governance (ESG) criteria but also offers clear directions for companies to enhance sustainability in their overseas expansion process. This includes strengthening technological research and development, compliance construction, market adaptability, product diversity, infrastructure construction, and risk management. Moreover, the research findings provide valuable insights for policymakers in promoting the internationalization of the pre-cooked meal industry and enhancing industry competitiveness. [ABSTRACT FROM AUTHOR]

Protection suits are vital for firefighters' safety. Traditional protection suits physically protect firemen from burns, but cannot locate the position of bodily injuries caused by impact debris. Herein, we present a wearable impact debris positioning system for firefighter protection suits based on an accelerometer array. Wearable piezoelectric accelerometers are distributed regularly on the suit to detect the vibration on different body parts, which is conducive to determining the position of injured body parts. In addition, the injured parts can be displayed on a dummy body model on the upper computer with a higher localization accuracy of 4 cm. The positioning alarm system has a rapid response time of 0.11 ms, attributed to the smart signal processing method. This work provides a reliable and smart method for locating and assessing the position of bodily injuries caused by impact debris, which is significant because it enables fire commanders to rescue injured firefighters in time. [ABSTRACT FROM AUTHOR]

The increasing prominence of climate change, geopolitical crises, and global economic slowdown highlights the challenges and structural deficiencies of traditional cross-border agro-food supply chains. As a result, there has been a growing consensus on the need to leverage digital technology to rebuild and innovate a safe, stable, and sustainable global food system. This study assessed the knowledge progress and development trends in the sustainable development of cross-border agro-food supply chains enabled by digital technology. A total of 352 authoritative papers from the core Web of Science database were selected for analysis. The Citespace tool was utilized to visually examine research elements. The findings reveal that research outcomes in this territory experienced a significant period of rapid growth, particularly after 2020. Sustainability and IEEE Access are the journals with the highest and second-highest number of publications. China and the France National Institute are the countries and research institutions with the largest number of publications in this field. The research hotspots are mainly the application of digital technologies, food safety, and supply chain system model innovation. In the past ten years, the research in this territory has gone through three stages: precise timeliness orientation, intelligent strategic decision-making orientation, and model predictability orientation. We further construct the 'antecedent–practice–performance' conceptual framework of the sustainability of the digital technology-enabled cross-border agro-food supply chain. Finally, this paper presents the potential research directions in this territory, focusing on four aspects: research method, research mechanism, research topic, and research frontier. [ABSTRACT FROM AUTHOR]

Rare earth elements (REEs) are essential raw materials for modern industries but mining them has caused severe environmental issues, particularly the recovery of heavy REEs (HREEs) from ion-adsorption deposits (IADs). Very recently, an emerging technology, electrokinetic mining (EKM), has been proposed for the green and efficient recovery of REEs from IADs. However, the conduction mechanism of the weathering crust soil, which is also a prerequisite for EKM, remains unclear, making the EKM process unpredictable. Here, we systematically investigated the conductivity of weathering crust soil in the presence of light REEs (LREEs, i.e., La3+ and Sm3+) and HREEs (Er3+ and Y3+), respectively. Results suggested that the voltage was dynamically and spatially redistributed by the movement of REEs and water during EKM, and the conventional assumption of the linear distribution of voltage leads to an inaccurate description of soil voltage. We proposed an improved Archie's equation by coupling the mechanisms of liquid phase and solid-liquid interface conduction, which can predict soil conductivity more precisely. Moreover, the extended Archie's equation is able to recalculate the voltage distribution at distinct times and spaces well during EKM. More importantly, the water content in field-scale weathered-crust soils can be retrieved by the newly proposed Archie's equation, which helps optimize the leaching wells and improve the recovery rate of REE. This study focuses on the conduction mechanism of weathering crust soil, which provides a theoretical basis for better use of the EKM technology and promotes mining efficiency fundamentally. [ABSTRACT FROM AUTHOR]

Electrokinetic mining (EKM) is a novel method for rare earth element (REE) mining that can achieve green and efficient recovery of REEs. However, as yet, there is no accurate model for describing the electrokinetic transport of REEs in weathering crusts, and this hinders the wider application of EKM. The conventional model fails to capture the microscale transport physics occurring in the nanochannels that exist ubiquitously in weathering crusts. Consequently, the existing models cannot distinguish the mobilities of different REEs. Here, we report a new model for a more faithful description of the electrokinetic transport of REEs in weathering crusts that considers the ionic size, which has previously been neglected. We reveal that the electrokinetic transport of heavy REEs (HREEs) is faster than that of light REEs (LREEs) in weathering crusts, which is contrary to the predictions of conventional models. Our model was validated experimentally by measurements of the electrokinetic transport of two LREEs (La and Sm) and an HREE (Er) in weathering crusts. The speed of electrokinetic transport follows the order Er > Sm > La. Our findings suggest that the ionic size is a non-negligible factor affecting the electrokinetic transport of REEs in weathering crusts containing nanochannels. This work offers a constitutive model to describe the electrokinetic transport of REEs in weathering crusts, which promotes both theoretical developments and practical applications of EKM. [ABSTRACT FROM AUTHOR]

As cross-border e-commerce platforms become increasingly integrated into the agricultural supply chain, the establishment of a sustainable supply chain ecosystem is of paramount importance. This study, grounded in the platform theory and the supply chain ecosystem theory, combines the grounded theory and the DEMATEL–ISM–MICMAC model to thoroughly analyze the complex mechanisms driving sustainable development. Utilizing the grounded theory, we construct a system of driving factors comprising five primary indicators and eighteen secondary indicators. The hybrid model reveals the interrelationships, significance, system hierarchy, and dependence-driving relationships among these factors. Notably, the driving factor system is categorized into a six-level hierarchical structure, encompassing profound elements, such as policy optimization and digital empowerment, as well as surface-level factors, such as simplification of customs procedures and consumer demand forecasting. Based on the analysis results, this research proposes a set of pathways to achieve the sustainability of the supply chain. These strategies involve improving cross-border agricultural e-commerce policy frameworks, enhancing digital-driven supply–demand coordination, strengthening logistics infrastructure and transparency, and cultivating brand influence. The study's findings not only enrich the relevant theories but also provide practical guidance for the coordinated advancement of economic, social, environmental, and resilient development. Furthermore, they are conducive to advancing the United Nations Sustainable Development Goals. [ABSTRACT FROM AUTHOR]

Mountainous areas have become among the most developed areas of geological hazards due to special geological environmental conditions and intensive human engineering activities. Geological hazards are a main threat to urbanization, rural revitalization, and new rural construction in complex mountainous areas. It is of great strategic significance to conduct large-scale geological hazard investigation and risk assessment in urban areas, control the risk of geological hazards at the source and propose risk control measures. In this paper, we established the technical methods of geologic hazard risk assessment and control in complex mountain towns by taking Longlin Town in the mountainous region of Gansu Longnan, China as the study area, with the Quanjia bay debris flows and Panping Village landslides as the typical pilot investigation and assessment. The methods consist of six stages—risk identification, hazard disaster model investigation, risk analysis, vulnerability assessment, risk evaluation and risk management and control measures and proposals. On this basis, the results of geological hazards with different precipitation frequencies (5%, 2%, 1%) are presented. The results show that 75.23% of the regions remained at low risk levels; 24.38% of the regions increased a risk level with decreasing precipitation frequency, and 0.39% of the regions remained at extremely high risk levels under different precipitation frequency conditions. For the Quanjia bay debris flows and Panping Village landslides case, we discussed the geological hazards risk source control contents, management and control technologies, engineering and non-engineering measures of disaster prevention and control for urban disasters and specific disaster areas. This research can provide technical support and reference for disaster prevention and mitigation, and territorial spatial planning. [ABSTRACT FROM AUTHOR]

The organization and coordination of cross-border e-commerce platforms in agricultural product trading are continuously increasing, and the involvement of digital platforms has driven the integration and development of cross-border agricultural product supply chains with live-streaming e-commerce, effectively facilitating the comprehensive development of producers, sellers, and professional service providers within the ecosystem. However, despite the growing importance of this integration model in the market, there are still numerous unresolved issues from a supply chain perspective, and existing research provides relatively limited guidance on the effective operation of this integrated supply chain model. To address this gap in theoretical research, this study first delves into the essence and fundamental characteristics of sustainable cross-border agricultural product supply chains in the context of live streaming. Secondly, employing grounded theory as the primary research method and combining platform theory and ecosystem theory, an influencing factor system and an impact model for the development of sustainable cross-border agricultural product supply chains in the context of live streaming are constructed to gain a more comprehensive understanding of the complexity of this integrated supply chain model. Finally, from the perspectives of government agencies and practitioners, development pathways for sustainable cross-border agricultural product supply chains in the context of live-streaming e-commerce are proposed, aiming to enhance existing research and provide decision-making support for relevant stakeholders in formulating development strategies. The findings of this study contribute to expanding the research perspective on the ecosystem of live-streaming e-commerce and sustainable cross-border agricultural product supply chains, providing theoretical support for the establishment and operation of sustainable cross-border agricultural product supply chains in the context of live streaming. Additionally, it offers important references for promoting the sustainable development of live-streaming e-commerce and cross-border agricultural product supply chains, facilitating industry upgrading, global agricultural trade, and achieving mutually beneficial outcomes. [ABSTRACT FROM AUTHOR]

In this study, we present a novel dual-polarized patch antenna that exhibits high isolation and two in-band transmission zeros (TZs). The design consists of a suspended metal patch, two feeding probes connected to an internal neutralization line (I-NL), and a T-shaped decoupling network (T-DN). The I-NL is responsible for generating the first TZ, and its decoupling principles are explained through an equivalent circuit model. Rigorous design formulas are also derived to aid in the construction of the feeding structure. The T-DN realizes the second TZ, resulting in further improvement of the decoupling bandwidth. Simulation and experimental results show that the proposed antenna has a wide operating bandwidth (2.5–2.7 GHz), high port isolation (>30 dB), and excellent efficiency (>85%). [ABSTRACT FROM AUTHOR]

As a new type of one-dimensional semiconductor nanometer material, silicon nanowires (SiNWs) possess good application prospects in the field of biomedical sensing. SiNWs have excellent electronic properties for improving the detection sensitivity of biosensors. The combination of SiNWs and field effect transistors (FETs) formed one special biosensor with high sensitivity and target selectivity in real-time and label-free. Recently, SiNW-FETs have received more attention in fields of biomedical detection. Here, we give a critical review of the progress of SiNW-FETs, in particular, about the reversible surface modification methods. Moreover, we summarized the applications of SiNW-FETs in DNA, protein, and microbial detection. We also discuss the related working principle and technical approaches. Our review provides an extensive discussion for studying the challenges in the future development of SiNW-FETs. [ABSTRACT FROM AUTHOR]

How to reshape the cross-border agricultural supply chain is a common concern in the global agricultural field. Using the bibliometrics method, 761 studies in the literature were selected from the core database of WOS (Web of Science) to explore research hotspots and development trends in this field, clarify the historical context, and explore future trends. Using the knowledge map visualization software CiteSpace, an in-depth review and visualization analysis of hot topics in this field were conducted. The results showed that since 2017, research in this field has shown a strong development trend. The United States and the University of Wageningen are the field's most influential country and research institution, respectively. Sustainability is the journal with the highest number of publications in the field. Research hotspots included cross-border agricultural product safety, cross-border agricultural supply chain systematization, and technology integration, and gradually evolved towards the high-quality development of digital intelligence with informatization, digitization, and big data as the main focus. The sustainability of cross-border agricultural supply chains and the resilience of the global food supply system have become the main lines of research in this field. [ABSTRACT FROM AUTHOR]

A novel adaptive mesh generation technique for efficient electromagnetic simulation of radio-frequency integrated circuits (RFICs) is herein presented. By exploring the geometrical and physical characteristics of RFICs, some adaptive mesh treatments, such as mesh projection, edge refinement, via polymerization, etc., are utilized to improve the accuracy and efficiency of electromagnetic computations. For strong coupling structures, such as two conductors in close proximity for a relatively large area, a projection-based mesh scheme is introduced to improve the accuracy of numerical integration. Moreover, the current most likely concentrates near the edges of conductors due to the edge effect. To better model the edge effect, an edge refinement scheme is applied. For via arrays that appear common in RFICs, an automatic via aggregation approach is adopted to improve computational efficiency yet still keep good computational accuracy. Finally, some numerical examples are given to validate the computational accuracy and efficiency of the novel adaptive mesh generation technique. [ABSTRACT FROM AUTHOR]

We explored the influencing factors of the usage intention of a metaverse education application platform that directly influence the optimization of its service function, improve the usage intention, and realize the promotion and application of metaverse technology in the education domain. Based on the characteristics of the metaverse education application platform, we integrated the PPM (push–pull–mooring) model and the TAM (technology acceptance model) to construct the model of influencing factors of usage intention. Ultimately, 275 valid questionnaires were collected through expert demonstration, pre-investigation, formal investigation, and other processes. In addition, our paper used the SEM (structural equation model) and fsQCA (fuzzy-set qualitative comparative analysis) to analyze the influencing factors of user willingness and their configuration paths. The study found that personalized learning, contextualized teaching, perceived usefulness, perceived ease of use, social needs, and social impact play significant positive roles in the willingness to use the metaverse education platform. Meanwhile, the obtained findings show that the experience-led community-driven mode, personality-led community-driven mode, and social-led utility-driven mode serve as potential guidelines for usage intention enhancement. [ABSTRACT FROM AUTHOR]

A deep learning approach for the efficient electromagnetic analysis of an on-chip inductor with dummy metal fillings (DMFs) is proposed. By comparing different activation functions and loss functions, a deep neural network for DMF modeling is built using a smooth maximum unit activation function and log-cosh loss function. The parasitic capacitive effect of DMFs is quickly and accurately extracted though this model, and the effective permittivity can be obtained subsequently. An on-chip inductor containing DMFs with different filling densities is analyzed using this proposed method and compared with the electromagnetic simulation of entire structures. The results validate the accuracy and efficiency of this proposed method. [ABSTRACT FROM AUTHOR]

This study proposes an ultrahigh-sensitivity split-ring resonator-based microwave sensor for retrieving the complex permittivity of liquid samples. An interdigital capacitor structure was used to expand the sensing area and the sensitivity. A defected ground structure and A parallel dual split-ring resonator were introduced to improve the quality factor. A polydimethylsiloxane microfluidic channel substrate was placed above the interdigital capacitor structure. The channel route coincided with the interdigital gap to fully utilize the strong electric field. Ethanol–water solutions with varying ethanol fractions were injected into the channel as the testing liquid. It was demonstrated that the variation in resonant frequency can be used to retrieve the dielectric properties of liquid samples. The proposed sensor used a small liquid volume of ~0.68 μL and provided values in good agreement with the reference data. [ABSTRACT FROM AUTHOR]

The bifurcation process of self-sustained combustion instability pressure perturbations in a liquid rocket combustor is investigated based on the Helmholtz equations and a pressure dependent flame describing function. The modal frequency and growth rates are numerically resolved by the commercial software COMSOL multiphysics. Validation of the numerical approach is firstly conducted on a Rijke tube combustor, and a supercritical bifurcation for the first longitudinal mode is observed. The bifurcation diagrams for the first transverse mode for different time delays and gain index of the flame describing function are analyzed. Only the supercritical bifurcation presents for this configuration. The trajectory of Hopf points and the bifurcation diagram feature period motions with increasing the time delay. The effect of flame length distributions on the bifurcation diagrams is analyzed by considering a non-uniform flame length distribution model. Results show that the distribution has a large impact on the bifurcation process, e.g., the first transverse mode is more unstable for the non-uniform distribution. Finally, a subcritical bifurcation is found when a more complicated flame describing function is considered; the bistable region presents and the condition for this is discussed. [ABSTRACT FROM AUTHOR]

Breast cancer has the highest cancer incidence rate in women. Early screening of breast cancer can effectively improve the treatment effect of patients. However, the main diagnostic techniques available for the detection of breast cancer require the corresponding equipment, professional practitioners, and expert analysis, and the detection cost is high. Tumor markers are a kind of active substance that can indicate the existence and growth of the tumor. The detection of tumor markers can effectively assist the diagnosis and treatment of breast cancer. The conventional detection methods of tumor markers have some shortcomings, such as insufficient sensitivity, expensive equipment, and complicated operations. Compared with these methods, biosensors have the advantages of high sensitivity, simple operation, low equipment cost, and can quantitatively detect all kinds of tumor markers. This review summarizes the biosensors (2013–2021) for the detection of breast cancer biomarkers. Firstly, the various reported tumor markers of breast cancer are introduced. Then, the development of biosensors designed for the sensitive, stable, and selective recognition of breast cancer biomarkers was systematically discussed, with special attention to the main clinical biomarkers, such as human epidermal growth factor receptor-2 (HER2) and estrogen receptor (ER). Finally, the opportunities and challenges of developing efficient biosensors in breast cancer diagnosis and treatment are discussed. [ABSTRACT FROM AUTHOR]

In this work, a MEMS piezoresistive micro pressure sensor (1.5 × 1.5 × 0.82 mm) is designed and fabricated with SOI-based micromachining technology and assembled using anodic bonding technology. In order to optimize the linearity and sensitivity over a wide effective pressure range (0–5 MPa) and temperature range (25–125 °C), the diaphragm thickness and the insulation of piezoresistors are precisely controlled by an optimized micromachining process. The consistency of the four piezoresistors is greatly improved by optimizing the structure of the ohmic contact pads. Furthermore, the probability of piezoresistive breakdown during anodic bonding is greatly reduced by conducting the top and bottom silicon of the SOI. At room temperature, the pressure sensor with 40 µm diaphragm demonstrates reliable linearity (0.48% F.S.) and sensitivity (33.04 mV/MPa) over a wide pressure range of 0–5.0 MPa. In addition, a polyimide protection layer is fabricated on the top surface of the sensor to prevent it from corrosion by a moist marine environment. To overcome the linearity drift due to temperature variation in practice, a digital temperature compensation system is developed for the pressure sensor, which shows a maximum error of 0.43% F.S. in a temperature range of 25–125 °C. [ABSTRACT FROM AUTHOR]

As the interconnect delay exceeds the gate delay, the integrated circuit (IC) technology has evolved from a transistor-centric era to an interconnect-centric era. Conventional metallic interconnects face several serious challenges in aspects of performance and reliability. To address these issues, nanocarbon materials, including carbon nanotube (CNT) and graphene, have been proposed as promising candidates for interconnect applications. Considering the rapid development of nanocarbon interconnects, this paper is dedicated to providing a mini-review on our previous work and on related research in this field. [ABSTRACT FROM AUTHOR]

Closed-form expressions for the optimized number and size of repeaters in multi-walled carbon nanotube (MWCNT) interconnects are presented. The contact resistance and inductive effects are taken into account. It is found that the propagation delay of MWCNT interconnects can be reduced effectively by inserting repeaters. However, the contact resistance has a significant influence on the optimized number and size of repeaters. Moreover, it is found that both the optimal number of repeaters and the minimum propagation delay are kept almost unchanged with the variation of carbon nanotube (CNT) kinetic inductance. The optimal number of repeaters in the MWCNT interconnect is much smaller than that in its Cu counterpart, thus saving chip area and power consumption. [ABSTRACT FROM AUTHOR]

Direct determinations of the isothermal entropy increment, -△ST, in the Heusler alloy Ni50CoMn36Sn13 on demagnetization gave positive values, corresponding to a normal magnetocaloric effect. These values contradict the results derived from heat-capacity measurements and also previous results obtained from magnetization measurements, which indicated an inverse magnetocaloric effect, but showing different values depending on the technique employed. The puzzle is solved, and the apparent incompatibilities are quantitatively explained considering the hysteresis, the width of the martensitic transition and the detailed protocol followed to obtain each datum. The results show that these factors should be analyzed in detail when dealing with Heusler alloys. [ABSTRACT FROM AUTHOR]

The advent of optogenetics provides a well-targeted tool to manipulate neurons because of its high time resolution and cell-type specificity. Recently, closed-loop neural manipulation techniques consisting of optical stimulation and electrical recording have been widely used. However, metal microelectrodes exposed to light radiation could generate photoelectric noise, thus causing loss or distortion of neural signal in recording channels. Meanwhile, the biocompatibility of neural probes remains to be improved. Here, five kinds of neural interface materials are deposited on flexible polyimide-based neural probes and illuminated with a series of blue laser pulses to study their electrochemical performance and photoelectric noises for single-unit recording. The results show that the modifications can not only improve the electrochemical performance, but can also reduce the photoelectric artifacts. In particular, the double-layer composite consisting of platinum-black and conductive polymer has the best comprehensive performance. Thus, a layer of polypeptide is deposited on the entire surface of the double-layer modified neural probes to further improve their biocompatibility. The results show that the biocompatible polypeptide coating has little effect on the electrochemical performance of the neural probe, and it may serve as a drug carrier due to its special micromorphology. [ABSTRACT FROM AUTHOR]

Lasers distinguish themselves for the high coherence and high brightness of their radiation, features which have been exploited both in fundamental research and a broad range of technologies. However, emerging applications in the field of imaging, which can benefit from brightness, directionality and efficiency, are impaired by the speckle noise superimposed onto the picture by the interference of coherent scattered fields. We contribute a novel approach to the longstanding efforts in speckle noise reduction by exploiting a new emission regime typical of nanolasers, where low-coherence laser pulses are spontaneously emitted below the laser threshold. Exploring the dynamic properties of this kind of emission in the presence of optical reinjection we show, through the numerical analysis of a fully stochastic approach, that it is possible to tailor some of the properties of the emitted radiation, in addition to exploiting this naturally existing regime. This investigation, therefore, proposes semiconductor nanolasers as potential attractive, miniaturized and versatile future sources of low-coherence radiation for imaging. [ABSTRACT FROM AUTHOR]

With the rapid increase in the use of optogenetics to investigate nervous systems, there is high demand for neural interfaces that can simultaneously perform optical stimulation and electrophysiological recording. However, high-magnitude stimulation artifacts have prevented experiments from being conducted at a desirably high temporal resolution. Here, a flexible polyimide-based neural probe with polyethylene glycol (PEG) packaged optical fiber and Pt-Black/PEDOT-GO (graphene oxide doped poly(3,4-ethylene-dioxythiophene)) modified microelectrodes was developed to reduce the stimulation artifacts that are induced by photoelectrochemical (PEC) and photovoltaic (PV) effects. The advantages of this design include quick and accurate implantation and high-resolution recording capacities. Firstly, electrochemical performance of the modified microelectrodes is significantly improved due to the large specific surface area of the GO layer. Secondly, good mechanical and electrochemical stability of the modified microelectrodes is obtained by using Pt-Black as bonding layer. Lastly, bench noise recordings revealed that PEC noise amplitude of the modified neural probes could be reduced to less than 50 µV and no PV noise was detected when compared to silicon-based neural probes. The results indicate that this device is a promising optogenetic tool for studying local neural circuits. [ABSTRACT FROM AUTHOR]

In this study, the triangle interpolation method for the calculation of mapping functions of plates containing an opening with arbitrary shapes is investigated with an improved method for point adjudgment during iterations. Afterwards, four kinds of openings with typical shapes are considered and the mapping functions for them are calculated, based on which the influence of calculation parameters such as iteration time and the number of terms on the accuracy of mapping function is discussed. Finally, the stress around an inverted U-shaped opening and around an arched opening under different far-field stress conditions is calculated and the effect of opening shape and lateral pressure coefficient on stress distribution and rock mechanical behaviors is further analyzed combined with the discrete element method (DEM) numerical simulation. The result shows that the stability and failure pattern of the rock mass is correlated with the stress around the opening, which is affected by the opening shape. The existence of opening also greatly reduces the enhancing influence of confining stress on rock specimen. [ABSTRACT FROM AUTHOR]

In this paper, an innovative vertical MOSFET based on through-oxide via (TOV) technology is proposed for silicon-on-insulator (SOI)-based monolithic 3-D ICs. The proposed vertical MOSFET is investigated numerically. It was found that SOI can effectively reduce the parasitic capacitance, leakage current, power consumption, as well as suppress the pulse current interference of the substrate. The simulated results indicate that the proposed MOSFET possesses excellent characteristics in saturation current over 1500 μA, sub-threshold swing of 69 mV/dec, and on/off current ratio of 1.28 × 1011. Moreover, as temperature is a critical factor for the performance degradation of semiconductor devices, electrothermal simulations are conducted to predict the influence of the self-heating effect on device characteristics. The results show that device characteristics slightly deteriorate, but can still acceptable in their applications. [ABSTRACT FROM AUTHOR]

An advanced method of modeling radio-frequency (RF) devices based on a deep learning technique is proposed for accurate prediction of S parameters. The S parameters of RF devices calculated by full-wave electromagnetic solvers along with the metallic geometry of the structure, permittivity and thickness of the dielectric layers of the RF devices are used partly as the training and partly as testing data for the deep learning structure. To implement the training procedure efficiently, a novel selection method of training data considering critical points is introduced. In order to rapidly and accurately map the geometrical parameters of the RF devices to the S parameters, deep neural networks are used to establish the multiple non-linear transforms. The hidden-layers of the neural networks are adaptively chosen based on the frequency response of the RF devices to guarantee the accuracy of generated model. The Adam optimization algorithm is utilized for the acceleration of training. With the established deep learning model of a parameterized device, the S parameters can efficiently be obtained when the device geometrical parameters change. Comparing with the traditional modeling method that uses shallow neural networks, the proposed method can achieve better accuracy, especially when the training data are non-uniform. Three RF devices, including a rectangular inductor, an interdigital capacitor, and two coupled transmission lines, are used for building and verifying the deep neural network. It is shown that the deep neural network has good robustness and excellent generalization ability. Even for very wide frequency band (0–100 GHz), the maximum relative error of the coupled transmission lines using the proposed method is below 3%. [ABSTRACT FROM AUTHOR]

The effect of an anode composite electrode on the performance of a micro direct methanol fuel cell (μDMFC) is analyzed from sample preparation configurations and discussed in detail, with a specific focus on the catalyst layer and the micro-porous layer on the anode composite electrode. This study investigates the effects of Pt content, Pt-Ru molar ratio, Nafion content, catalyst support, and preparation method in the catalyst layer, along with the carbon loading and polytetrafluoroethylene (PTFE) content in the micro-porous layer, on the performance of the anode composite electrode. The results show that the anode composite electrode delivers the best performance with 30% Pt content, a 1:1.5 Pt-Ru molar ratio, 10% Nafion content on reduced graphene oxide as the catalyst support. The synthesis is optimized with the impregnation reduction method using NaBH4 as the reducing agent, with the addition of 1.5 mg/cm2 carbon loading and 5% PTFE. [ABSTRACT FROM AUTHOR]

Distinctive Cr-MOF@Da composites have been constructed using chromium-based metal-organic frameworks (MOFs) and diatomite (Da). The new materials have hierarchical pore structures containing micropores, mesopores and macropores. We have synthesized various morphologies of the MOF compound Cr-MIL-101 to combine with Da in a one-pot reaction step. These distinctive hierarchical pore networks within Cr-MIL-101@Da enable exceptional adsorptive performance for a range of molecules, including hydrogen (H2), carbon dioxide (CO2) and water (H2O) vapor. Selectivity for H2 or CO2 can be moderated by the morphology and composition of the Cr-MIL-101 included in the Cr-MOF@Da composite. The encapsulation and growth of Cr-MIL-101 within and on Da have resulted in excellent water retention as well as high thermal and hydrolytic stability. In some cases, Cr-MIL-101@Da composite materials have demonstrated increased thermal stability compared with that of Cr-MIL-101; for example, decomposition temperatures >340 ℃ can be achieved. Furthermore, these Cr-MIL-101@Da composites retain structural and morphological integrity after 60 cycles of repeated hydration/dehydration, and after storage for more than one year. These characteristics are difficult to achieve with many MOF materials, and thus suggest that MOF–mineral composites show high potential for practical gas storage and water vapor capture. [ABSTRACT FROM AUTHOR]

Gray mold disease caused by Botrytis cinerea is a devastating disease that leads to serious financial loss. In this study, the entomopathogenic fungus Metarhizium anisopliae that acts against the gray mold pathogen B. cinerea was evaluated. M. anisopliae produced a significant inhibition zone in front of the B. cinerea colony in the dual culture test. In addition, volatile organic compounds generated by M. anisopliae were shown to have an inhibitory effect on B. cinerea mycelia growth and reduced 41% of gray mold severity of postharvest tomatoes. The 10% concentration of the culture filtrate of M. anisopliae inhibited 88.62% of colony radial growth as well as 63.85% of sclerotia germination and all conidia germination of B. cinerea. Furthermore, the culture filtrate of M. anisopliae retained its inhibitory effect against the radial growth of B. cinerea even after heating for 15 min at 100 °C. Feasible mechanisms of M. anisopliae involved in the control of B. cinerea were explored, and it was demonstrated that the plasma membrane of B. cinerea conidia was damaged by the product of metabolism of M. anisopliae. In addition, after treating with culture filtrate of M. anisopliae, the B. cinerea phenotype was shown to be abnormal, and cell organelles of B. cinerea mycelia were damaged significantly. A significant control efficacy of M. anisopliae against tomato gray mold was detected on both the detached leaf assay (84.24%) as well as the whole plant (72.38%). In addition, a 78% reduction in tomato fruit mold was detected at a 10% treated concentration of M. anisopliae. These findings suggest that M. anisopliae possesses potential as a biocontrol agent against tomato gray mold in the greenhouse and during the postharvest stage. [ABSTRACT FROM AUTHOR]

Vitamin C supplementation has been shown to decrease triple-negative breast cancer (TNBC) metastasis. However, the molecular mechanism whereby vitamin C inhibits metastasis remains elusive. It has been postulated that vitamin C reduces the levels of HIF-1α, the master regulator of metastasis, by promoting its hydroxylation and degradation. Here, we show that vitamin C at 100 µM, a concentration achievable in the plasma in vivo by oral administration, blocks TNBC cell migration and invasion in vitro. The protein level of HIF-1α remains largely unchanged in cultured TNBC cells and xenografts, partially due to its upregulated transcription by vitamin C, suggesting that HIF-1α unlikely mediates the action of vitamin C on metastasis. Vitamin C treatment upregulates the expression of synaptopodin 2 and downregulates the expression of the transcription coactivator YAP1, both genes in the Hippo pathway. The changes in SYNPO2 and YAP1 expression were subsequently validated at mRNA and protein levels in cultured TNBC cells and xenografts. Further experiments showed that vitamin C treatment inhibits F-actin assembly and lamellipodia formation, which correlates with the changes in SYNPO2 and YAP1 expression. Overall, these results suggest that vitamin C inhibits TNBC metastasis by affecting the expression of SYNPO2 and YAP1. Vitamin C may thus have a potential role in the prevention and treatment of TNBC metastasis. [ABSTRACT FROM AUTHOR]

One major difficulty of parameter extraction for an equivalent circuit lies in applying an optimization algorithm to efficiently approach the global minimum. Traditional genetic algorithm (GA) is able to find the global minimum but it has very low convergence rate. On the other hand, direct search method may be easily trapped in local minima. In this work, an improved parameter extraction method which is capable of effectively performing the global minimum search is proposed. This method combines GA and Powell's method to efficiently determine circuit elements of an equivalent circuit model. A spiral inductor and an interdigital capacitor are used as design examples to illustrate the extraction procedure and validate the proposed hybrid method. [ABSTRACT FROM AUTHOR]

Purpureocillium lilacinum has been widely used as a commercial biocontrol agent for the control of plant parasitic nematodes. Whole genome analysis promotes the identification of functional genes and the exploration of their molecular mechanisms. The Cyclophilin (CYP) gene family belongs to the immunophillin superfamily, and has a conserved cyclophilin-like domain (CLD). CYPs are widely identified in prokaryotes and eukaryotes, and can be divided into single- and multi-domain proteins. In the present study, 10 CYP genes possessing the CLD, named PlCYP1–P10, were identified from the genome of P. lilacinum strain 36-1. Those 10 PlCYPs were predicted to have different cellular localizations in P. lilacinum. Phylogenetic and gene structure analysis revealed the evolutionary differentiation of CYPs between Ascomycotina and Saccharomycotina fungi, but conservation within the Ascomycotina fungi. Motif and gene structure distributions further support the result of phylogenetic analysis. Each PlCYP gene had a specific expression pattern in different development stages of P. lilacinum and its parasitism stage on eggs of Meloidogyne incognita. In addition, the 10 PlCYP genes exhibited different expression abundances in response to abiotic stresses, among which PlCYP4 was highly expressed at a high temperature (35 °C), while PlCYP6 was up-regulated under 5 mM of H2O2 stress. Furthermore, the heterologous expression of PlCYP4 and PlCYP6 in Escherichia coli enhanced the cellular tolerance against a high temperature and H2O2. In summary, our study indicates the potential functions of PlCYPs in virulence and the stress response, and also provides a frame for further analysis of the CYP gene family in Ascomycotina fungi. [ABSTRACT FROM AUTHOR]

This paper discusses the vibration-induced error in non-ideal MEMS tuning fork gyroscopes (TFGs). Ideal TFGs which are thought to be immune to vibrations do not exist, and imbalance between two gyros of TFGs is an inevitable phenomenon. Three types of fabrication imperfections (i.e., stiffness imbalance, mass imbalance, and damping imbalance) are studied, considering different imbalance radios. We focus on the coupling types of two gyros of TFGs in both drive and sense directions, and the vibration sensitivities of four TFG designs with imbalance are simulated and compared. It is found that non-ideal TFGs with two gyros coupled both in drive and sense directions (type CC TFGs) are the most insensitive to vibrations with frequencies close to the TFG operating frequencies. However, sense-axis vibrations with in-phase resonant frequencies of a coupled gyros system result in severe error outputs to TFGs with two gyros coupled in the sense direction, which is mainly attributed to the sense capacitance nonlinearity. With increasing stiffness coupled ratio of the coupled gyros system, the sensitivity to vibrations with operating frequencies is cut down, yet sensitivity to vibrations with in-phase frequencies is amplified. [ABSTRACT FROM AUTHOR]