SymFET: A Proposed Symmetric Graphene Tunneling Field Effect Transistor

In this work, an analytical model to calculate the channel potential and current-voltage characteristics in a Symmetric tunneling Field-Effect-Transistor (SymFET) is presented. The current in a SymFET flows by tunneling from an n-type graphene layer to a p-type graphene layer. A large current peak occurs when the Dirac points are aligned at a particular drain-to- source bias VDS . Our model shows that the current of the SymFET is very weakly dependent on temperature. The resonant current peak is controlled by chemical doping and applied gate bias. The on/off ratio increases with graphene coherence length and doping. The symmetric resonant peak is a good candidate for high-speed analog applications, and can enable digital logic similar to the BiSFET. Our analytical model also offers the benefit of permitting simple analysis of features such as the full-width-at-half-maximum (FWHM) of the resonant peak and higher order harmonics of the nonlinear current. The SymFET takes advantage of the perfect symmetry of the bandstructure of 2D graphene, a feature that is not present in conventional semiconductors

Mechanism of pulse magneto-oscillation grain refinement on pure Al

Pulse magneto-oscillation (PMO) was developed as a novel technique to refine the solidification structure of pure aluminium. Its grain refining mechanism was proposed. The PMO refinement mechanism is that the nucleus falls off from the mould wall and drifts into the melt under the action of PMO. The solidification structure of Al melt depends on the linear electric current density, and also the discharge and oscillation frequencies. The radial pressure of PMO sound wave is the major factor that contributes to the migration of nucleus into the melt

Effectiveness of folic acid fortified flour for prevention of neural tube defects in a high risk region

Despite efforts to tackle folate deficiency and Neural Tube Defects (NTDs) through folic acid fortification, its implementation is still lacking where it is needed most, highlighting the need for studies that evaluate the effectiveness of folic acid fortified wheat flour in a poor, rural, high-risk, NTD region of China. One of the most affected regions, Shanxi Province, was selected as a case study. A community intervention was carried out in which 16,648 women of child-bearing age received fortified flour (eight villages) and a control group received ordinary flour (three villages). NTD birth prevalence and biological indicators were measured two years after program initiation at endline only. The effect on the NTD burden was calculated using the disability-adjusted life years (DALYs) method. In the intervention group, serum folate level was higher than in the control group. NTDs in the intervention group were 68.2% lower than in the control group (OR = 0.313, 95% CI = 0.207-0473, p < 0.001). In terms of DALYs, burden in intervention group was approximately 58.5% lower than in the control group. Flour fortification was associated with lower birth prevalence and burden of NTDs in economically developing regions with a high risk of NTDs. The positive findings confirm the potential of fortification when selecting an appropriate food vehicle and target region. As such, this study provides support for decision makers aiming for the implementation of (mandatory) folic acid fortification in China

Limit Analysis On Seismic Stability Of Anisotropic And Nonhomogeneous Slopes With Anti-slide Piles

This study employs the limit analysis method to evaluate the seismic stability of anisotropic and nonhomogeneous slopes stabilized with anti-slide piles. The pseudo-static approach is used to simplify the earthquake load. The yield seismic acceleration factor is obtained from the optimization procedure and the results are verified with the published data. Then, the seismically unstable slope is reinforced with anti-slide piles, and the seismic stability of the reinforced slope is explored. The results show that the anisotropy and Non homogeneity of soils have significant effects on the stabilizing force required from the anti-slide piles and the optimal location of the pile is near the toe of the slope

PAK6: a potential anti-cancer target

p21-activated kinase 6 (PAK6) is a member of the PAK family of serine/threonine kinases that are known effectors of Rho GTPases Cdc42 and Rac. PAKs regulate a large number of complex cellular mechanisms, including cell motility, morphology, and tumor development. PAK6, initially cloned as an interacting partner of the androgen receptor (AR), is associated with an array of cellular processes implicated in tumor progression. However, the full biological implications of PAK6 activity during cancer remain poorly understood. In this review, we assess our current understanding of the physiological roles of classical PAK6 functionality in mammals, in addition to its emerging role in tumorigenesis

Parametric and economic analysis of high-temperature cascade organic Rankine cycle with a biphenyl and diphenyl oxide mixture

High-temperature organic Rankine cycle (ORC) systems have the potential to improve the heat-to-power conversion efficiency and expand the temperature range for heat recovery, heat battery and solar power generation. Restricted by the critical temperature of the commonly used organic working fluids, the current ORC technology has a maximum working temperature of around 300 °C. This paper proposes a high-temperature cascade organic Rankine cycle (CORC) system using a biphenyl and diphenyl oxide (BDO) mixture as the top cycle fluid and conventional organic fluids for the bottom cycle. The BDO mixture has excellent heat stability over a wide operation condition from 12 °C to 400 °C in single-phase and binary-phase states. However, at present a detailed study on the ORC using the mixture is lacking. In this paper, a parametric analysis of the high-temperature CORC system is conducted. A mathematical model based on the equivalent hot side temperature is built to simulate the ORC efficiency. The thermodynamic and exergetic performances of the novel CORC system under different bottom ORC working fluids, mixing chamber temperatures, evaporation temperatures, and condensation temperatures are investigated. The results show the maximum thermal efficiency of the CORC system is 38.74 % and 40.26 % at top ORC evaporation temperatures of 360 °C and 400 °C. The largest exergy destruction takes place in the heat exchanger between the top and bottom ORCs. Besides, the heat regenerators have a significant impact on the thermodynamic performance and can elevate the CORC efficiency by about 4 %. The proposed system has a higher efficiency and a lower equipment cost than conventional steam Rankine cycle at 400 °C while eliminating the challenges of wet steam turbines

CMAS-resistance of a yttria graded thermal barrier coating fabricated by plasma activated EB-PVD

EB-PVD yttria stabilized zirconia (YSZ) thermal barrier coatings (TBCs) are susceptible to calcia-magnesia-aluminum-silicate (CMAS) corrosion. The service lifetime of typical 8YSZ TBCs can be significantly reduced by CMAS attack. Currently, composition and microstructure modifications are the most commonly used methods for CMAS infiltration resistance. It has been reported by previous researchers that reactive elements, including Y, Gd, La, and etc., doped in TBCs can promote the formation of a dense protective layer by a sacrificing reaction with CMAS. It is therefore that the CMAS infiltration can be retarded. Besides, tailored columnar grains of TBCs are are also proved to be effective for CMAS mitigation. In this work, TBCs specimens with graded microstructure were fabricated by EB-PVD. The upper region of the TBC was doped with a higher Y2O3 content up to 25 wt.%, compared with the conventional 8YSZ composition. Besides, plasma activation was also introduced in the EB-PVD process to yield a tailored coating morphology and prosity. The coating specimens were tested at 1250 oC for evaluating CMAS resistance. Conventional YSZ coatings and graded coatings without plasma activation were also investigated for comparison

RUEL: Retrieval-Augmented User Representation with Edge Browser Logs for Sequential Recommendation

Online recommender systems (RS) aim to match user needs with the vast amount of resources available on various platforms. A key challenge is to model user preferences accurately under the condition of data sparsity. To address this challenge, some methods have leveraged external user behavior data from multiple platforms to enrich user representation. However, all of these methods require a consistent user ID across platforms and ignore the information from similar users. In this study, we propose RUEL, a novel retrieval-based sequential recommender that can effectively incorporate external anonymous user behavior data from Edge browser logs to enhance recommendation. We first collect and preprocess a large volume of Edge browser logs over a one-year period and link them to target entities that correspond to candidate items in recommendation datasets. We then design a contrastive learning framework with a momentum encoder and a memory bank to retrieve the most relevant and diverse browsing sequences from the full browsing log based on the semantic similarity between user representations. After retrieval, we apply an item-level attentive selector to filter out noisy items and generate refined sequence embeddings for the final predictor. RUEL is the first method that connects user browsing data with typical recommendation datasets and can be generalized to various recommendation scenarios and datasets. We conduct extensive experiments on four real datasets for sequential recommendation tasks and demonstrate that RUEL significantly outperforms state-of-the-art baselines. We also conduct ablation studies and qualitative analysis to validate the effectiveness of each component of RUEL and provide additional insights into our method.Comment: CIKM 2023 AD

Threatening Patch Attacks on Object Detection in Optical Remote Sensing Images

Advanced Patch Attacks (PAs) on object detection in natural images have pointed out the great safety vulnerability in methods based on deep neural networks. However, little attention has been paid to this topic in Optical Remote Sensing Images (O-RSIs). To this end, we focus on this research, i.e., PAs on object detection in O-RSIs, and propose a more Threatening PA without the scarification of the visual quality, dubbed TPA. Specifically, to address the problem of inconsistency between local and global landscapes in existing patch selection schemes, we propose leveraging the First-Order Difference (FOD) of the objective function before and after masking to select the sub-patches to be attacked. Further, considering the problem of gradient inundation when applying existing coordinate-based loss to PAs directly, we design an IoU-based objective function specific for PAs, dubbed Bounding box Drifting Loss (BDL), which pushes the detected bounding boxes far from the initial ones until there are no intersections between them. Finally, on two widely used benchmarks, i.e., DIOR and DOTA, comprehensive evaluations of our TPA with four typical detectors (Faster R-CNN, FCOS, RetinaNet, and YOLO-v4) witness its remarkable effectiveness. To the best of our knowledge, this is the first attempt to study the PAs on object detection in O-RSIs, and we hope this work can get our readers interested in studying this topic