Miracle-dz/UniFAR-FTUs huggingface dataset:
Learning 6-D compliant motion primitives from demonstration

We present a novel method for learning 6-D compliant motions from demonstration. The key advantage of our learning method compared to current Learning from Demonstration (LfD) methods is that we learn to take advantage of existing mechanical gradients (such as chamfers) with compliance to perform in-contact motions consisting of both translation and rotation, as in aligning workpieces or attaching hose couplers. We find the desired direction, which leads the robot's end-effector to the location shown in the demonstration either in free space or in contact, separately for translational and rotational motions. The key idea is to first compute a set of directions which would result in the observed motion at each timestep during a demonstration. By taking an intersection over all such sets from a demonstration we find a single desired direction which can reproduce the demonstrated motion. Finding the number of compliant axes and their directions in both rotation and translation is based on the assumption that in the presence of a desired direction of motion, all other observed motion is caused by the contact force of the environment, signalling the need for compliance. We evaluate the method on a KUKA LWR4+ robot with test setups imitating typical tasks where a human would use compliance to cope with positional uncertainty. Results show that the method can successfully learn and reproduce compliant motions by taking advantage of the geometry of the task, therefore reducing the need for initial accuracy.
Approach to Prevent SYN Flood DoS Attacks in Cloud

Denial-of-service (DOS) attacks are the most frequent attacks in Cloud. Usually this type of attack consists in sending a large number of requests that will overwhelm the functioning of Cloud. DOS attack implies IP spoofing because each request needs to be different. So the server will consume its resources and it will not be able to reply to a legitimate connection request. SYN floods are the second most common type of DOS attack for Cloud in the last 3 years. SYN floods exploit the flaws in TCP three-way handshake procedures. The attacker sends multiple SYN requests from a spoofed IP address. The server will allocate all the resources needed without receiving any ACK from the attacker. We propose an approach of solving this type of attack for Big Data in Cloud while respecting the Service Level Agreement (SLA) and show that the improvement is considerable.
Citrus peel polymethoxyflavones, sudachitin and nobiletin, induce distinct cellular responses in human keratinocyte HaCaT cells

ABSTRACT A variety of polyphenols have been isolated from plants, and their biological activities have been examined. Sudachitin (5,7,4′-trihydroxy-6,8,3′-trimethoxyflavone) is a polymethoxyflavone that is isolated from the peel of Citrus sudachi. Although we previously reported that sudachitin possesses an anti-inflammatory activity, its other biological activities are not yet understood. In this study, we report a novel biological activity of sudachitin, which selectively induced apoptosis in human keratinocyte HaCaT cells. Another polymethoxyflavone, nobiletin (5,6,7,8,3′,4′-hexamethoxyflavone), promoted autophagy but not apoptosis in HaCaT cells. On the other hand, 3′-demethoxysudachitin (5,7,4′-trihydroxy-6,8-dimethoxyflavone) failed to induce apoptosis and autophagy. These results show that three polymethoxyflavones have different effects on apoptosis and autophagy in HaCaT cells. Understanding the structure and biological activity of polymethoxyflavones may lead to the discovery of potential candidates for cancer drug development without significant toxic side effects. Abbreviations: ROS: reactive oxygen species; DMSO: dimethyl sulfoxide; MTT: 3-(4, 5-dimethylthiazol-2yl)-2, 5-diphenyltetrazolium bromide; GAPDH: glyceraldehyde-3-phosphate dehydrogenase; PARP: poly(ADP-ribose) polymerase; PI: propidium iodide; MAPK: mitogen-activated protein kinase. Graphical Abstract Three polymethoxyflavones have different effects on apoptosis and autophagy in human keratinocytes.
A High-Selectivity Quad-Band Bandpass Filter Utilizing Asymmetrical Interdigital Coupled Lines and Circular Spiral Lines

This letter proposes a novel high-selectivity quad-band bandpass filter (BPF) with nine transmission zeros (TZs) using asymmetrical interdigital coupled lines and circular spiral lines. By deploying five asymmetrical circular interdigital coupling lines, a quad-band BPF with seven TZs is achieved. With adding two open circular spiral lines, two additional independent TZs are obtained. The nine controllable TZs contribute to selectivity improvement significantly. The fabricated BPF demonstrates four passbands located at 2.4, 3.5, 4.5, and 5.8 GHz, which are suitable for Wi-Fi and 5G communication. Within the four passbands, the minimum insertion losses are 1.3, 0.9, 2.2, and 1.3 dB, and the shape factors are 2.4, 1.8, 1.9, and 1.9, respectively. The overall size of the fabricated filter is $15.5 \times 22.5$ mm2. Compared with the other double-layered works, this letter demonstrates significantly enhanced selectivity and competitive insertion loss.
Learning the Parameters of Spatially-Referring Natural Language Likelihoods in Binary Models

Despite imprecision and possible ambiguity expressed by spatially referring natural language statements, they are potentially useful “measurements” (also known as soft data) for target localisation and tracking. The likelihood functions of such measurements typically include the parameters that model the inherent uncertainty in soft data. Adopting a binary model for spatially referring statements involving the word “near”, the paper derives the theoretical posterior Cramér-Rao bound for the estimation (learning) of the parameter which features in the likelihood function. A numerical analysis of the bound is presented with an example demonstrating estimation/learning in practice.
Screw Tightening Monitoring with RFID Passive Tag

The specific application of monitoring the tightening status of critical screws, e.g., screws for metallic structures which require high reliability, is herein discussed. A solution based on radio frequency identification (RFID) passive tag devices is proposed, and the design of a simple tag for metallic surfaces which allows for detecting the screw relaxing is presented. A tag prototype is manufactured on a 0.5 mm thick FR4 substrate of size 40 mm × 40 mm based on the commercial tag chip Impinj Monza R6 for working within the ultra-high frequency (UHF) FCC band 920.5-924.5 MHz, and measurement results reveal that the screw status can be detected up to a range of 2.5 m.
Superpixel-Level Target Discrimination for High-Resolution SAR Images in Complex Scenes

Traditional synthetic aperture radar (SAR) target discrimination methods are implemented at the chip-level, which may have good discrimination performance in simple scenes but may lose the effectiveness in complex scenes. To improve the discrimination performance in complex scenes, this paper proposes a superpixel-level target discrimination method directly in high-resolution SAR images. The proposed discrimination method mainly contains three stages. First, based on the superpixel-level target detection results, we describe each superpixel via the multilevel and multidomain feature descriptor, which can reflect the differences between targets and clutter comprehensively. Second, we employ the support vector machine as the discriminator to obtain the discriminated target superpixels. Finally, we cluster the discriminated target superpixels and extract the target chips from the original SAR image based on the clustering results. The experimental results based on the miniSAR real SAR data show that the proposed discrimination method has about 25% higher F1-score than the traditional discrimination methods.
Associations between the peripheral blood Wilms tumor gene 1 level and both bone marrow blast cells and the prognosis in patients with myelodysplastic syndrome

Abstract Wilms tumor gene 1 (WT1) is highly expressed in myelodysplastic syndrome (MDS) cells and is known to reflect the tumor burden in MDS. We evaluated the usefulness of WT1 mRNA levels for predicting the prognosis of MDS. At diagnosis, WT1 levels were strongly correlated with the percentage of blasts calculated based on non-erythroid cells, but not with that based on all nucleated cells (r = 0.57, p < .05 vs r = 0.42, p = .13). Among the allogeneic transplant recipients, the presence of two consecutive WT1 levels ≥100 copies/μg RNA with a median interval of one month was associated with a 77.8% relapse rate at nine months from the first detection of a high WT1 level, and the median time to relapse was only 114 [36–257] days. WT1 levels at diagnosis were correlated with known prognostic factors. In addition, the presence of two consecutive high WT1 levels after allogeneic transplantation may predict early relapse of MDS.
Localizing Moments in Video with Temporal Language

Localizing moments in a longer video via natural language queries is a new, challenging task at the intersection of language and video understanding. Though moment localization with natural language is similar to other language and vision tasks like natural language object retrieval in images, moment localization offers an interesting opportunity to model temporal dependencies and reasoning in text. We propose a new model that explicitly reasons about different temporal segments in a video, and shows that temporal context is important for localizing phrases which include temporal language. To benchmark whether our model, and other recent video localization models, can effectively reason about temporal language, we collect the novel TEMPOral reasoning in video and language (TEMPO) dataset. Our dataset consists of two parts: a dataset with real videos and template sentences (TEMPO - Template Language) which allows for controlled studies on temporal language, and a human language dataset which consists of temporal sentences annotated by humans (TEMPO - Human Language).
Commentary: Phylogenomics and Comparative Genomic Studies Robustly Support Division of the Genus Mycobacterium into an Emended Genus Mycobacterium and Four Novel Genera

Citation: Tortoli E (2018) Commentary: Phylogenomics and Comparative Genomic Studies Robustly Support Division of the Genus Mycobacterium into an Emended Genus Mycobacterium and Four Novel Genera. Front. Microbiol. 9:2065. doi: 10.3389/fmicb.2018. 02065 Commentary: Phylogenomics and Comparative Genomic Studies Robustly Support Division of the Genus Mycobacterium into an Emended Genus Mycobacterium and Four Novel Genera
A Truthful Mechanism for Scheduling and Pricing Pleasingly Parallel Jobs in a Service Cloud

As more and more users outsource their job executions to service clouds, effective job scheduling and pricing models are needed to solve resource and service competitions between users. Considering the particularity of scheduling and pricing problems in a service cloud whose goal is generally social welfare maximization, current commonly used models, such as fixed-pricing schemes, have obvious shortcomings and thus are unfeasible. Therefore, in this paper, we propose a randomized mechanism to schedule and charge job executions in service clouds. Our proposed mechanism can schedule jobs in a flexible way to achieve approximate social welfare maximization while guaranteeing non-preemption. Flexibility means the number of instances which are allocated to a job can be changed over time. The mechanism is truthful in expectation, computationally efficient and individually rational. The theoretical analysis shows that our mechanism can achieve an expected social welfare approximation ratio α, which can be 2 in some situations. Extensive simulations show that our proposed mechanism can efficiently solve the job scheduling problem in service clouds.
Repoxy: Replication Proxy for Trustworthy SDN Controller Operation

Software Defined Networks (SDN) is envisaged as a future model for large-scale, elastic, and adaptive networks. However, such flexibility comes with a major cost. Relying heavily on software across the entire architecture and the centralized nature of the most important component, the controller, gave the attackers asymmetric advantage. for decades, we used to build security tools to secure the network traffic, but network components security was always protected by physical perimeters behind doors. In this paper, we present REPlication prOXY(Repoxy), a smart gateway isolating the north and southbound to enhance controller resilience, availability, and reliability in presence of attacks and also discuss our first version of the implementation. Repoxy presents a novel SDN-controller intrusion detection system to detect any malicious manipulations to the controller software. Further, Repoxy enables elasticity and high-availability for SDN controllers by facilitating southbound-oblivious seamless multi-controller replication, and handover for same network traffic. Additionally, Repoxy helps forensic analysts to easily find attack traces by exploiting Repoxy's information-rich database logging all the switch controller interactions. Results and evaluations showed the enhanced trustworthiness in the SDN network with a reasonable overhead when Repoxy is used.
Experimental Assessments of a Triple Redundant Nine-Phase Fault-Tolerant PMA SynRM Drive

Fault-tolerant machine drives are key enabling technologies in safety critical applications. The machine drives are expected to exhibit high performance in healthy conditions and accommodate as many faults as possible, namely open circuit or short circuit in the machine and inverter or even an interturn short circuit. This paper aims to assess a triple redundant nine-phase (3 × 3-phase) permanent magnet assisted synchronous reluctance machine (PMASynRM) drive by comprehensive experimental tests under both healthy and fault conditions on a 35 kW machine drive prototype. The healthy performance, fault behavior, fault detection, and mitigation strategy are presented and assessed by extensive tests which demonstrate that the machine drive exhibits high performance and excellent fault tolerance with simple and cost-effective implementation. Therefore, the proposed machine drive has proven to be a practical candidate for safety critical applications.
Quantitative Evaluation of Carrier Distribution in Silicon Solar Cell Using Scanning Nonlinear Dielectric Microscopy

The carrier distribution in solar cell is important evaluation target. Scanning nonlinear dielectric microscopy is applied to the cross section of phosphorus implanted emitter in monocrystalline silicon solar cell and visualizes the carrier distribution quantitatively. The effective diffusivities of phosphorus are estimated from the experimental results. Then, the three-dimensional carrier distribution is simulated. The experimental and simulation results show good correlation.
Gait Recognition Algorithm Based on Feature Fusion of GEI Dynamic Region and Gabor Wavelets

The paper proposes a novel gait recognition algorithm based on feature fusion of gait energy image (GEI) dynamic region and Gabor, which consists of four steps. First, the gait contour images are extracted through the object detection, binarization and morphological process. Secondly, features of GEI at different angles and Gabor features with multiple orientations are extracted from the dynamic part of GEI, respectively. Then averaging method is adopted to fuse features of GEI dynamic region with features of Gabor wavelets on feature layer and the feature space dimension is reduced by an improved Kernel Principal Component Analysis (KPCA). Finally, the vectors of feature fusion are input into the support vector machine (SVM) based on multi classification to realize the classification and recognition of gait. The primary contributions of the paper are: a novel gait recognition algorithm based on based on feature fusion of GEI and Gabor is proposed; an improved KPCA method is used to reduce the feature matrix dimension; a SVM is employed to identify the gait sequences. The experimental results suggest that the proposed algorithm yields over 90% of correct classification rate, which testify that the method can identify better different human gait and get better recognized effect than other existing algorithms.
Disentangling the role of users’ preferences and impulsivity traits in problematic Facebook use

The use of social network sites (SNSs) has grown dramatically. Numerous studies have shown that SNS users may suffer from excessive use, associated with addictive-like symptoms. With a focus on the popular SNS Facebook (FB), our aims in the current study were twofold: First, to explore the heterogeneity of FB usage and determine which kind of FB activity predicts problematic usage; second, to test whether specific impulsivity facets predict problematic use of FB. To this end, a sample of FB users (N = 676) completed an online survey assessing usage preferences (e.g., types of activities performed), symptoms of problematic FB use and impulsivity traits. Results indicated that specific usage preferences (updating one’s status, gaming via FB, and using notifications) and impulsive traits (positive and negative urgency, lack of perseverance) are associated to problematic FB use. This study underscores that labels such as FB “addiction” are misleading and that focusing on the actual activities performed on SNSs is crucial when considering dysfunctional usage. Furthermore, this study clarified the role of impulsivity in problematic FB use by building on a theoretically driven model of impulsivity that assumes its multidimensional nature. The current findings have identifiable theoretical and public health implications.
Arm Orientation Estimation Method with Multiple Devices for NUI/NUX

Motion estimation is a key Natural User Interface/Natural User Experience (NUI/NUX) technology to utilize motions as commands. HTC VIVE is an excellent device for estimating motions but only considers the positions of hands, not the orientations of arms. Even if the positions of the hands are the same, the meaning of motions can differ according to the orientations of the arms. Therefore, when the positions of arms are measured and utilized, their orientations should be estimated as well. This paper proposes a method for estimating the arm orientations based on the Bayesian probability of the hand positions measured in advance. In experiments, the proposed method was used to measure the hand positions with HTC VIVE. The results showed that the proposed method estimated orientations with an error rate of about 19%, but the possibility of estimating the orientation of any body part without additional devices was demonstrated.
Eye-Tracking Sensors for Adaptive Aerospace Human-Machine Interfaces and Interactions

Whereas current aerospace Human-Machine Interfaces and Interactions (HMI2) are mostly static in their behaviour/appearance and require direct input from human operators, innovative HMI2 concepts are being proposed which allow for multimodal interactions or sense the functional state of human operators and dynamically adapt the level of automation. In particular, to facilitate trust between the human and machine, such systems need sensors that can reliably detect changes in the operator state. However, a number of environmental factors can affect the sensor's accuracy and precision. When used together with other novel sensors, eye tracking hasa significant potential to enhance the adaptiveness of aerospace HMI2. This paper presents the activities carried out to quantify the uncertainty associated with eye tracking equipment available in the Avionics and Air Traffic Management (ATM) systems laboratory of RMIT University, whichis being used to support the development of Cognitive HMI2. The presented methodology is used to characterise its measurement uncertainty based on a number of considerations, including the calibration error as well as gaze angle in static and dynamic conditions. The uncertainty associated with the eye tracker is used for error budgeting of a Cognitive HMI2 system which employs fuzzy logics to infer operator cognitive states based on eye tracking inputs.
Phase Transition in Bayesian Tracking in Clutter

A simple model of Bayesian object tracking, in the presence of clutter (i.e. spurious detections), is studied. In this model a single object is known to be present, and is detected in every time-step with additional detections of Poisson distributed clutter. Its position is estimated using Gaussian models of measurement errors and diffusion for the object's unknown motion. Neglecting fluctuations, in three or more dimensions a phase transition is found at a certain critical clutter density, above which long-term tracking is not possible, but below which the posterior probability remains localised around the true object position even after infinite time. In fewer dimensions there is no phase transition and long-term tracking is always possible in principle. Bounds on the critical clutter density are calculated for a continuous model. Numerical results for a discrete model confirm the approximate prediction of the critical clutter density. It is anticipated that similar behaviour will occur for more general models of multiple-object tracking.
Prognostic impact of serum soluble interleukin-2 receptor level at diagnosis in elderly patients with diffuse large B-cell lymphoma treated with R-CHOP

Abstract Diffuse large B-cell lymphoma (DLBCL) is a clinically heterogeneous disease. To evaluate the clinical relevance of the serum soluble interleukin-2 receptor (sIL-2R) level, we retrospectively analyzed 178 patients aged ≥60 years who were newly diagnosed with DLBCL. We determined the cutoff value of the sIL-2R level to be 1280 U/mL using the area under the receiver operating characteristic curve. The high sIL-2R group exhibited significantly inferior 5-year progression-free survival (PFS) (36.2% vs. 86.1%, p < .001) and 5-year overall survival (OS) (49.7% s. 83.8%, p < .001) than the low sIL-2R group. Multivariate analysis revealed that a high sIL-2R level was a significant prognostic factor for PFS and OS (hazard ratio [HR]: 5.65, p < .001 and HR: 2.99, p = .001, respectively). This study showed that measurement of the sIL-2R level at diagnosis is clinically beneficial for identifying elderly patients with DLBCL who have a poor prognosis.
An Ultra-Sensitive Glucose Sensor by Using Metamaterial-Based Microfluidic Chip

A large-scale lithography-free metamaterial (MM) is presented, which is integrated with a microfluidic chip for effective glucose sensing. MM is composed of hybrid nanopillars fabricated with SiO2 and Au thin-films on Si substrate. It exhibits angle-independence, and polarization-independence, which are the most important factors for color filters for industrial applications. The resonance shift is 56 nm with a stable bandwidth (~30 nm) by varying concentration of glucose solution. The sensitivity is 158 nm/RIU and the corresponding figure-of-merit is 5.3.
Multi-Beam Antennas for Massive MIMO System with Vertical Spatial Filtering Technique

To alleviate the RF -complexity of massive multiple-input multiple-output (MIMO) system, in this paper, we first introduce a new technique named vertical spatial filtering (VSF). Based on the proposed technique, the reduced system with only a small amount of radio frequency chains has the performance comparable to the complete system. Then, three antenna arrays are presented as good candidates for massive MIMO system with the VSF technique. With simplified feeding network or phase compensation in free space, dual beams with single-polarization, eight beams with single-polarization and ten beams with dual-polarization are achieved by the antenna arrays, respectively.