Pressure-dependent Schottky barrier at the metal-nanotube contact

We carry out first-principles density-functional calculations to investigate the electronic structure of the gold-carbon nanotube contact. It is found that a pressure applied on the gold-nanotube contact shifts the Fermi level from the valence edge to the conduction edge of the carbon nanotube. This can explain the n -type transport behavior frequently observed in the nanotube field-effect transistor using the gold as electrodes. An atomistic model is proposed for a possible origin of the pressure when the nanotube is embedded in the gold electrode.open101

Conditional Cube Attacks on Ascon-128 and Ascon-80pq in a Nonce-misuse Setting

Ascon-128 and Ascon-80pq use 12-round Ascon permutation for initialization and finalization phases and 6-round Ascon permutation for processing associate data and message. In a nonce-misuse setting, we present a new partial-state-recovery conditional-cube attack on Ascon-128 and Ascon-80pq, where 192 bits out of 320-bit state are recovered. For our partial state-recovery attack, its required data complexity, $D$, is about $2^{44.8}$ and its required memory complexity, $M$, is negligible. After a 192-bit partial state is recovered, in a nonce-misuse setting, we can further recover the full 320-bit state with time complexity, $T=2^{128}$, and then we can recover the secret key with extra data complexity of $2^{31.5}$, extra time complexity of $2^{129.5}$, and memory complexity of $2^{31.5}$. A similar attack of recovering the partial state was independently developed by Baudrin et al. at NIST fifth Lightweight Cryptography workshop. Note that our attack does not violate the NIST LWC security requirements on Ascon-128 and Ascon-80pq as well as the designers\u27 claims

A STUDY OF MOTION CHARACTERISTICS LED BY CONNECTION METHODS AND POSITIONS OF A WAVE-ENERGY CONVERTER IN A REGULAR WAVE

The potential of wave power as an alternative energy resource is being studied to address problems associated with fossil fuel exhaustion and environmental pollution. In this paper, to improve the power generation efficiency of a floating-type wave-energy converter that has an activating body, the effects of the positions of a connecting bridge and different connecting methods between a main body and the activating body of the wave-energy converter were studied. In order to research the activating body’s motion characteristics that are caused by the changes of connecting bridge’s position and connecting methods; hinged or fixed connector, the wave-energy converter was modeled and simulated by using a commercial software. The moment and angular velocity of the axis of power generation were measured from the results of simulations and then the power outputs were calculated based on the moment and angular velocity. The outputs, which were analyzed under several regular wave conditions, were compared to each other

Novel Pyoverdine Inhibitors Mitigate Pseudomonas aeruginosa Pathogenesis

Pseudomonas aeruginosa is a clinically important pathogen that causes a variety of infections, including urinary, respiratory, and other soft-tissue infections, particularly in hospitalized patients with immune defects, cystic fibrosis, or significant burns. Antimicrobial resistance is a substantial problem in P. aeruginosa treatment due to the inherent insensitivity of the pathogen to a wide variety of antimicrobial drugs and its rapid acquisition of additional resistance mechanisms. One strategy to circumvent this problem is the use of anti-virulent compounds to disrupt pathogenesis without directly compromising bacterial growth. One of the principle regulatory mechanisms for P. aeruginosa’s virulence is the iron-scavenging siderophore pyoverdine, as it governs in-host acquisition of iron, promotes expression of multiple virulence factors, and is directly toxic. Some combination of these activities renders pyoverdine indispensable for pathogenesis in mammalian models. Here we report identification of a panel of novel small molecules that disrupt pyoverdine function. These molecules directly act on pyoverdine, rather than affecting its biosynthesis. The compounds reduce the pathogenic effect of pyoverdine and improve the survival of Caenorhabditis elegans when challenged with P. aeruginosa by disrupting only this single virulence factor. Finally, these compounds can synergize with conventional antimicrobials, forming a more effective treatment. These compounds may help to identify, or be modified to become, viable drug leads in their own right. Finally, they also serve as useful tool compounds to probe pyoverdine activity

An Interacting Multiple Model Approach for Target Intent Estimation at Urban Intersection for Application to Automated Driving Vehicle

Research shows that urban intersections are a hotspot for traffic accidents which cause major human injuries. Predicting turning, passing, and stop maneuvers against surrounding vehicles is considered to be fundamental for advanced driver assistance systems (ADAS), or automated driving systems in urban intersections. In order to estimate the target intent in such situations, an interacting multiple model (IMM)-based intersection-target-intent estimation algorithm is proposed. A driver model is developed to represent the driver’s maneuvering on the intersection using an IMM-based target intent classification algorithm. The performance of the intersection-target-intent estimation algorithm is examined through simulation studies. It is demonstrated that the intention of a target vehicle is successfully predicted based on observations at an individual intersection by proposed algorithms. Document type: Articl

Heating Experiment of CNT Cementitious Composites with Single-Walled and Multiwalled Carbon Nanotubes

Carbon nanotubes (CNTs) are a primary nanomaterial that have outstanding physical and mechanical characteristics, and CNTs can be combined with cement-based materials to alter their heating characteristics. In this study, the types of CNTs used were multiwalled carbon nanotubes (MWCNTs) and single-walled carbon nanotubes (SWCNTs). Experiments were performed to determine the altered heating characteristics of the CNT cement mortars. The parameters of the experiment were CNT type, CNT content, curing age, and applied voltage. The results for the different CNT cement mortars indicate that mixing SWCNTs with water to produce CNT cement mortars was more effective for modifying the heating characteristics compared to mixing MWCNTs with water. In addition, field emission scanning electron microscope (FE-SEM) images supported the results found in the heating experiments

Resistance of Ascon Family against Conditional Cube Attacks in Nonce-Misuse Setting

Ascon family is one of the finalists of the National Institute of Standards and Technology (NIST) lightweight cryptography standardization process. The family includes three Authenticated Encryption with Associated Data (AEAD) schemes: Ascon-128 (primary), Ascon-128a, and Ascon-80pq. In this paper, we study the resistance of the Ascon~family against conditional cube attacks in nonce-misuse setting, and present new state- and key-recovery attacks. Our attack recovers the full state information and the secret key of Ascon-128a using 7-round Ascon-permutation for the encryption phase, with $2^{117}$ data and $2^{116.2}$ time. This is the best known attack result for Ascon-128a as far as we know. We also show that the partial state information of Ascon-128 can be recovered with $2^{44.8}$ data. Finally, by assuming that the full state information of Ascon-80pq was recovered by Baudrin et al.\u27s attack, we show that the 160-bit secret key of Ascon-80pq can be recovered with $2^{128}$ time. Although our attacks do not invalidate designers\u27 claim, those allow us to understand the security of Ascon in nonce-misuse setting

Graphene quantum dots as anti-inflammatory therapy for colitis

While graphene and its derivatives have been suggested as a potential nanomedicine in several biomimetic models, their specific roles in immunological disorders still remain elusive. Graphene quantum dots (GQDs) may be suitable for treating intestinal bowel diseases (IBDs) because of their low toxicity in vivo and ease of clearance. Here, GQDs are intraperitoneally injected to dextran sulfate sodium (DSS)-induced chronic and acute colitis model, and its efficacy has been confirmed. In particular, GQDs effectively prevent tissue degeneration and ameliorate intestinal inflammation by inhibiting T(H)1/T(H)17 polarization. Moreover, GQDs switch the polarization of macrophages from classically activated M1 to M2 and enhance intestinal infiltration of regulatory T cells (T-regs). Therefore, GQDs effectively attenuate excessive inflammation by regulating immune cells, indicating that they can be used as promising alternative therapeutic agents for the treatment of autoimmune disorders, including IBDs.

Privacy-Preserving Machine Learning with Fully Homomorphic Encryption for Deep Neural Network

Fully homomorphic encryption (FHE) is one of the prospective tools for privacypreserving machine learning (PPML), and several PPML models have been proposed based on various FHE schemes and approaches. Although the FHE schemes are known as suitable tools to implement PPML models, previous PPML models on FHE encrypted data are limited to only simple and non-standard types of machine learning models. These non-standard machine learning models are not proven efficient and accurate with more practical and advanced datasets. Previous PPML schemes replace non-arithmetic activation functions with simple arithmetic functions instead of adopting approximation methods and do not use bootstrapping, which enables continuous homomorphic evaluations. Thus, they could not use standard activation functions and could not employ a large number of layers. The maximum classification accuracy of the existing PPML model with the FHE for the CIFAR-10 dataset was only 77% until now. In this work, we firstly implement the standard ResNet-20 model with the RNS-CKKS FHE with bootstrapping and verify the implemented model with the CIFAR-10 dataset and the plaintext model parameters. Instead of replacing the non-arithmetic functions with the simple arithmetic function, we use state-of-the-art approximation methods to evaluate these non-arithmetic functions, such as the ReLU, with sufficient precision [1]. Further, for the first time, we use the bootstrapping technique of the RNS-CKKS scheme in the proposed model, which enables us to evaluate a deep learning model on the encrypted data. We numerically verify that the proposed model with the CIFAR-10 dataset shows 98.67% identical results to the original ResNet-20 model with non-encrypted data. The classification accuracy of the proposed model is 90.67%, which is pretty close to that of the original ResNet-20 CNN model...Comment: 12 pages, 4 figure

Association of Plasma Retinol-Binding Protein 4, Adiponectin, and High Molecular Weight Adiponectin with Insulin Resistance in Non-Diabetic Hypertensive Patients

∙The authors have no financial conflicts of interest. Purpose: The aim of this study was to determine whether retinol-binding protein 4 (RBP4), adiponectin and high molecular weight (HMW) adiponectin are associated with insulin resistance (IR) and metabolic parameters in non-diabetic hypertensive patients. Also, we sought to compare the predictive values of these adipocytokines for IR in non-diabetic hypertensive patients. Materials and Methods: Analyses of RBP4, adiponectin, and HMW adiponectin were performed on 308 non-diabetic hypertensives (148 males, age 58 ± 10 years, 189 non-metabolic syndrome and 119 metabolic syndrome). The homeostasis model assessment (HOMA) index for IR, lipid profiles, and anthropometric measure-ments were assessed. Results: There was no significant difference in RBP4 levels according to the presence of metabolic syndrome, although adiponectin and HMW adiponectin were significantly lower in metabolic syndrome. Correlation analysis of log RBP4 with IR and metabolic indices revealed that there was no significant correlation of RBP4 with wais