Miracle-dz/UniFAR-FTUs huggingface dataset:
Phytotoxicity and Antimicrobial Activity of Green Synthesized Silver Nanoparticles Using Nigella sativa Seeds on Wheat Seedlings

Recently, the green synthesis of nanomaterials has grown in popularity and has become one of the most used approaches. Plant extracts are safe for the environment and could be cost-effective for nanoparticle preparation. Silver nanoparticles (AgNPs) have been synthesized using aqueous extracts of Nigella sativa (N. sativa) seeds. The formation of AgNPs was confirmed by using an X-ray diffractometer, a UV-visible spectrometer, and a transmission electron microscope. The phytotoxicity and genotoxicity of different AgNP concentrations (12.5, 25, 50, 75, and 100 μg·L−1) were evaluated by wheat (Triticum aestivum L.) seed germination. The results showed that AgNPs did not significantly affect germination, while root and coleoptile lengths decreased considerably. On the contrary, the biomass of seedlings markedly increased in response to AgNP treatments. Moreover, genotoxicity was detected, especially at high concentrations of AgNPs. DNA, RNA, and total soluble proteins of wheat seedlings significantly decreased. In addition, antimicrobial activities of biosynthesized AgNPs were detected.
Proof of Karma (PoK): A Novel Consensus Mechanism for Consortium Blockchain

In blockchain-based systems, participants can be malicious. Therefore, this work first characterizes several properties expected in systems where the honest behaviour of involved parties plays significant role in the success. Considering these properties, a new consensus mechanism, Proof of Karma (PoK), is proposed based on karma (actions) of nodes. PoK incorporates a self-stabilizing leader election algorithm based on karma score to ensure consistency in the system. In PoK, both new and existing nodes get a fair chance to earn profit by becoming a leader and adding a valid block to the blockchain. PoK gives incentives and imposes penalties to encourage and discourage the nodes’ honest and malicious actions, respectively. PoK is analyzed with respect to the CAP theorem. The work provides security analysis to demonstrate the resistance of PoK against various blockchain specific attacks and karma specific attacks. Several experiments are also performed to assess the performance of PoK and compare it with the baseline model. The results show the feasibility, effectiveness, usability and scalability of PoK. PoK is also compared based on the characterized properties with various existing consensus mechanisms that consider malicious actions of nodes. PoK achieves consensus finality, decentralization and fairness, outperforming existing works.
Electronic structures of capped carbon nanotubes under electric fields

We have investigated the electronic structure of capped carbon nanotubes under electric fields by density functional calculations. The calculated effective work function of the capped armchair nanotubes decreases linearlywith increasing electric fields, whereas that of the metal tip decreases quadratically. We analyzed the density of states, highest occupied molecular orbitals (HOMO's) and lowest unoccupied molecular orbitals (LUMO's) for various charged states under electric fields, While the HOMO and the LUMO are not localized at the cap for a neutral state, the HOMO and LUMO of a negatively charged state are localized at the cap, particularly under electric fields, This localization plays an important role in the field emission. The Mulliken charge population shows that the charge accumulation is not dependent on the local atomic geometry but on the sharpness of the tip.
PIRET—A Platform for Treatment Planning in Electroporation-Based Therapies

Tissue electroporation is the basis of several therapies. Electroporation is performed by briefly exposing tissues to high electric fields. It is generally accepted that electroporation is effective where an electric field magnitude threshold is overreached. However, it is difficult to preoperatively estimate the field distribution because it is highly dependent on anatomy and treatment parameters. Objective: We developed PIRET, a platform to predict the treatment volume in electroporation-based therapies. Methods: The platform seamlessly integrates tools to build patient-specific models where the electric field is simulated to predict the treatment volume. Patient anatomy is segmented from medical images and 3D reconstruction aids in placing the electrodes and setting up treatment parameters. Results: Four canine patients that had been treated with high-frequency irreversible electroporation were retrospectively planned with PIRET and with a workflow commonly used in previous studies, which uses different general-purpose segmentation (3D Slicer) and modeling software (3Matic and COMSOL Multiphysics). PIRET outperformed the other workflow by 65 minutes (× 1.7 faster), thanks to the improved user experience during treatment setup and model building. Both approaches computed similarly accurate electric field distributions, with average Dice scores higher than 0.93. Conclusion: A platform which integrates all the required tools for electroporation treatment planning is presented. Treatment plan can be performed rapidly with minimal user interaction in a stand-alone platform. Significance: This platform is, to the best of our knowledge, the most complete software for treatment planning of irreversible electroporation. It can potentially be used for other electroporation applications.
You Are In My Way: Non-verbal Social Cues for Legible Robot Navigation Behaviors

People and robots may need to cross each other in narrow spaces when they are sharing environments. It is expected that autonomous robots will behave in these contexts safely but also show social behaviors. Thereby, developing an acceptable behavior for autonomous robots in the area mentioned above is a foreseeable problem for the Human-Robot Interaction (HRI) field. Our current work focuses on integrating legible non-verbal behaviors into the robot's social navigation to make nearby humans aware of its intended trajectory. Results from a within-subjects study involving 33 participants show that deictic gestures as navigational cues for humanoid robots result in fewer navigation conflicts than the use of a simulated gaze. Additionally, an increase in the perceived anthropomorphism is found when the robot uses the deictic gesture as a cue. These findings show the importance of social behaviors for people avoidance and suggest a paradigm of such behaviors in future humanoid robotic applications.
Position-based Treadmill Drive with Wire Traction for Experience of Level Ground Walking from Gait Acceleration State to Steady State

A treadmill system has a large potential to provide humans with an augmented walking experience in real-life without a spatial limitation. However, a treadmill gait is different from walking on level ground. In previous studies, the adaptive belt speed control of a treadmill was developed to achieve a self-paced walking for making the users' treadmill gait similar to their level ground gait. Such studies have focused on steady-state walking and regulating the user's position on the treadmill. A normal gait can be divided into an acceleration state after gait initiation, a steady state, and a deceleration state for stopping. The objective of this study is to develop a treadmill system with a wire tension application enabling a human to experience a similar gait to a level ground gait during the transition phase from an acceleration state to a steady state. We developed a treadmill 4 m long × 1 m wide. To allow a user to move on the treadmill during the gait acceleration phase, an insensitive zone where a user can move without the treadmill belt drive was set. In addition, the treadmill was equipped with a wire traction system to apply a traction force canceling the effect of the belt floor acceleration of the treadmill when the belt speed of the treadmill changes. Through an experiment with six participants, the proposed treadmill system allowed the users to move in an acceleration state with the same head acceleration pattern as with level ground walking and cancel the inertial effect with the wire traction, which enabled the users to transition to a steady state from an acceleration state.
Pedestrian Intention Prediction Based on Traffic-Aware Scene Graph Model

Anticipating the future behavior of pedestrians is a crucial part of deploying Automated Driving Systems (ADS) in urban traffic scenarios. Most recent works utilize a convolutional neural network (CNN) to extract visual information, which is then input to a recurrent neural network (RNN) along with pedestrian-specific features like location and speed to obtain temporal features. However, the majority of these approaches lack the ability to parse the relationships of the related objects in the specific traffic scene, which leads to omitting the interactions between the pedestrians and the interactions between the pedestrians and the traffic. For this purpose, we propose a graph-structured model which can dig out pedestrians' dynamic constraints by constructing a traffic-aware scene graph within each frame. In addition, to capture pedestrian movement more effectively, we also introduce a temporal feature representation model, which first uses inter-frame and intra-frame GRU (II-GRU) to mine inter-frame information and intra-frame information together, and then employs a novel attention mechanism to adaptively generate attention weights. Extensive experiments on the JAAD and PIE datasets prove that our proposed model is effective in reaching and enhancing the state-of-the-art performance.
Circuit-to-Circuit Attacks in SoCs via Trojan-Infected IEEE 1687 Test Infrastructure

We demonstrate a Hardware Trojan (HT)-based circuit-to-circuit attack mechanism in the context of Systems-on-Chip (SoCs). The HT trigger is hidden inside the attacking circuit and the HT payload travels from the attacking circuit to the victim circuit via the test infrastructure. The common test infrastructure is configured accordingly by the HT so as to propagate the HT payload. We demonstrate the capability of this HT to perform a denial-of-service attack on an industrial Analog-to-Digital Converter (ADC) connected to a IEEE 1687 test infrastructure.
Adaptive Sampling Site Selection for Robotic Exploration in Unknown Environments

Autonomously selecting the right sequence of locations to sample is critical during exploration missions in unknown environments, with constraints on the number of samples that can be collected, and a possibility of system failure. A key idea for decision-making in unknown environments is to exploit side information available to the agent, combined with the information gained from samples collected so far, to estimate the sampling values. In this paper, we pose the problem of sampling site selection as a problem of finding the optimal policy in a Markov decision process modeling the unknown sampling values and the outcomes associated with sampling attempts at different locations. Our solution exploits the fact that the partially unknown rewards of this Markov decision process are correlated to each other to devise a strategy that attempts to maximize the total sample value while also ensuring that the agent achieves its minimum mission requirement. We validate the utility of the proposed approach by evaluating the method against a baseline strategy that pursues collecting the samples that are estimated to be of the highest value. Our evaluations use a simulated sampling problem on Martian terrain and using OceanWATERS, a high-fidelity simulator of a future Europa lander mission.
Consistent shadow values for painters

A simple visual aid is presented, that can be produced in black-and-white on a piece of paper. A painter can use this aid to insure the consistency of shadow values in a painting. Consistency is necessary when an object with multiple colours, such as a shirt with red and white stripes, is seen in both light and shadow. All the values (the values of white in light, red in light, white in shadow, and red in shadow) must be correctly related to each other to make the painting convincing. Consistent values can be found by drawing a few lines on the visual aid. The scientific derivation of the visual aid is described. Finally, an application is suggested, that could heighten Adelson’s “checkerblock” illusions.
Ultraviolet and optical observations of OB associations in M31

Images of the central and southern parts of the local group Sb spiral galaxy M31 were obtained by the Ultraviolet Imaging Telescope during the Astro-1 Spacelab mission. Stellar photometry is obtained for 611 stars in 59 van den Bergh associations in the near-UV A1 band (central wavelngth 2490 A), and for 130 of these stars in the far UV B1 band (central wavlength 1520 A). In addition, B-band magnitudes for 456 of the stars in approximately 30 associations, together with U- and R-band photometry for approximately 290 stars in approximately 15 associations are determined from CCD images. B-magnitudes from the catalog of Magnier et al. (1992) are given for 137 stars and R-magnitudes for 233 stars. Stellar positions are obtained from the ground based CCD images and from UIT images. Total fluxes in the UV bands are measured for 63 associations . Finding charts are presented in the NUV and FUV bands, as well as, one optical band. Tables give the images utilized in this investigation, the associations observed, with positions, total UV fluxes, extinctions estimated from color-magnitude diagrams, and stellar positions with photometry in up to five bands. UV color magnitude diagrams are presented with extinctions estimated by comparing the observed association color magnitude diagrams with colors and magnitudes of early-type stars computed from the IUE spectral atlas of Fanelli et al. (1992). Comparison with evolutionary models suggests a maximum initial mass approx. 85 solar mass. Ultraviolet extinctions within most M31 OB associations is found to follow an extinction curve similar to that of Hutchings et al. (1992). The variation in the fraction of near-UV stars also measured in the far-UV among the associations is probably caused by variations in age, extinction, and the degree of foreground contamination.
SELECTING SUSTAINABILITY KEY PERFORMANCE INDICATORS FOR SMART LOGISTICS ASSESSMENT

The application of smart technologies and applications is becoming increasingly common in the logistics processes of companies and supply chains. However, standard logistics indicators are still used to evaluate their performance, which contradicts the sustainable development strategy of many industrial enterprises and their supply chains. Thus, the article aims to design a methodology for selecting sustainability key performance indicators (SKPIs) suitable for assessing smart logistics and its technologies and applications. The research relies on cluster analysis of the SKPIs recommended in the relevant literature, frequency analysis of indicators used in practice and their comparison. The cluster analysis showed that the primary attention in the references is given to sustainability’s economic and environmental dimensions. Most frequently, the authors highlighted the importance of the following indicators: production-related costs and investments, planning performance and quality, customer satisfaction, energy efficiency, waste intensity and treatment, emissions, and resource efficiency. On the contrary, the frequency analysis corroborated that leading industrial enterprises paid more-or-less balanced attention to all areas of sustainability, but at the company level. The article’s primary result constitutes a methodology comprising six steps, respecting the results of the analyses carried out: (1) Sustainability objectives definition; (2) Establishing SKPIs cluster pool; (3) Definition of criteria for selecting SKPIs clusters; (4) Selection of SKPIs clusters; (5) Definition of SKPIs and their parameters; and (6) Development of SKPIs hierarchical structure.
AI-Driven Assurance of Hardware IP against Reverse Engineering Attacks

The modern horizontal semiconductor supply chain has introduced a plethora of security threats targeting the integrity and confidentiality of hardware intellectual properties (IPs) and integrated circuits (ICs). Threats, such as reverse engineering, cloning, tampering, extraction of design intent have given rise to serious concerns for both the user and the producer of microelectronic devices. Logic locking, a recently proposed methodology, aims to defend against some of these threats through strategic logic gate insertions (key gates) and structural modifications. However, we observed that most existing logic locking techniques are vulnerable to structural analysis attacks. Furthermore, there is no technique available to quantify the robustness against structural analysis attacks of logic locking techniques. Based on these observations, we have developed a set of artificial intelligence guided evaluation frameworks and metrics to identify structural (SAIL, SIVA) and joint structural-functional (SURF) vulnerabilities in locked designs and quantify them. We have also developed a learning-guided logic locking framework, LeGO, that iteratively hardens a design against a set of known attacks with the possibility of expanding this attack database over time as new attacks are discovered. SAIL, SURF, and SIVA have opened up a new research area on structural attack vulnerability analysis of logic locking, while LeGO serves as a building block for developing the next generation of AI-guided logic locking techniques.
Metamaterial Loaded Microstrip Patch Antenna For Biomedical Applications

Recent growth in medicinal technology requires limited and valuable devices for biomedical applications. In previous years, the research community has shown an enormous pact of attention in proposing medical implantable to analysis various signals inside and outside the human body. To communicate wirelessly, an implantable antenna incorporated in an implantable medical device is needed. On the radiating patch, a unique dual-band microstrip patch antenna is integrated with a metamaterial structure with two L-shaped slots. At both operating frequencies, the integration of the metamaterial structure on the superstrate results in gain improvement. And it is applicable for medical applications, particularly measuring the intracranial pressure, and operates at 915MHz and also 2.45 GHz. The total size of the radiator is 48 x 47 mm2 and is placed on a dielectric constant of FR4 is 4.4, 1.6 mm thickness and the loss tangent of 0.025. The metamaterial structure has a total area of 7 x 6 mm2. The proposed metamaterial-loaded microstrip patch antenna gain value of 2 dBi and the return loss of the proposed antenna has -14 dB & -19 dB. The proposed antenna obtains better performance for the relevant frequency ranges in terms of gain, radiation pattern, return loss, and efficiency.
Positive exchange bias observed in Pt-inserted Cr2O3/Co exchange coupled bilayers

We investigated the effect of Pt insertion on a Cr2O3/Co exchange coupling system. The perpendicular exchange bias μ0Hex decreased with increasing Pt insertion layer thickness, and we observed positive μ0Hex for samples with relatively thick Pt insertion layers. We also examined the cooling field μ0Hfc dependence of μ0Hex for the samples. At small μ0Hfc, all samples exhibited negative μ0Hex. With increasing μ0Hfc, a shift of μ0Hex from negative to positive was observed. In the past, similar behaviors were observed for FeF2/Fe systems exhibiting positive μ0Hex. In addition, the μ0Hfc dependence of μ0Hex was well fitted by an equation taking into account the Zeeman energy at the surface of an antiferromagnet as well as an antiferromagnetic exchange coupling. The results strongly suggest that (1) Cr2O3 surface spin is affected by the external magnetic field and (2) the coupling at the Cr2O3/Pt/Co interface is antiferromagnetic.
Incidence, predictors, and impact on outcome of underlying intracranial atherosclerotic disease in acute vertebrobasilar artery occlusion undergoing endovascular therapy: Data from ANGEL-ACT registry

Background and Purpose: Intracranial atherosclerotic disease (ICAD) is a common etiology of acute vertebrobasilar artery occlusion (VBAO) in Asia, which complicated endovascular treatment (EVT). We aimed to investigate the incidence, impacts, and predictors of ICAD in VBAO. Methods: Subjects were selected from the Endovascular Treatment Key Technique and Emergency Work Flow Improvement of Acute Ischemic Stroke registry and divided into two groups based on whether underlying ICAD existed. Underlying ICAD was determined when the following situations arise in the occlusion site during EVT: (1) fixed stenosis degree >70% or (2) stenosis >50% with distal blood flow impairment or evidence of repeated reocclusion. Multivariable regression models were used to investigate the effect of underlying ICAD on outcomes measured by modified Rankin Scale (mRS) score at 90 days and to identify baseline characteristics associated with underlying ICAD. Results: Among the 315 patients enrolled, 171 (54.3%) had underlying ICAD. Favorable functional outcomes (mRS 0–3) occurred in 79 of 163 patients (48.5%) with ICAD and 69 of 137 patients (50.4%) without ICAD (p = 0.743). Outcomes were similar between the two groups and remained similar after adjusting for the confounders. History of hypertension and elevated admission neutrophil to lymphocyte ratio were strong predictors of underlying ICAD, whereas history of atrial fibrillation and distal basilar artery occlusion were negative predictors. Conclusions: In our study, underlying ICAD was recognized in approximately half of the VBAO patients, leading to comparable outcomes after more complex EVT strategies. Some baseline characteristics were identified to be predictors for underlying ICAD, which were helpful to guide the EVT strategies before the procedure.
Learning of Balance Controller Considering Changes in Body State for Musculoskeletal Humanoids

The musculoskeletal humanoid is difficult to modelize due to the flexibility and redundancy of its body, whose state can change over time, and so balance control of its legs is challenging. There are some cases where ordinary PID controls may cause instability. In this study, to solve these problems, we propose a method of learning a correlation model among the joint angle, muscle tension, and muscle length of the ankle and the zero moment point to perform balance control. In addition, information on the changing body state is embedded in the model using parametric bias, and the model estimates and adapts to the current body state by learning this information online. This makes it possible to adapt to changes in upper body posture that are not directly taken into account in the model, since it is difficult to learn the complete dynamics of the whole body considering the amount of data and computation. The model can also adapt to changes in body state, such as the change in footwear and change in the joint origin due to recalibration. The effectiveness of this method is verified by a simulation and by using an actual musculoskeletal humanoid, Musashi.