ZeroEGGS: Zero-shot Example-based Gesture Generation from Speech

We present ZeroEGGS, a neural network framework for speech-driven gesture generation with zero-shot style control by example. This means style can be controlled via only a short example motion clip, even for motion styles unseen during training. Our model uses a Variational framework to learn a style embedding, making it easy to modify style through latent space manipulation or blending and scaling of style embeddings. The probabilistic nature of our framework further enables the generation of a variety of outputs given the input, addressing the stochastic nature of gesture motion. In a series of experiments, we first demonstrate the flexibility and generalizability of our model to new speakers and styles. In a user study, we then show that our model outperforms previous state-of-the-art techniques in naturalness of motion, appropriateness for speech, and style portrayal. Finally, we release a high-quality dataset of full-body gesture motion including fingers, with speech, spanning across 19 different styles. Our code and data are publicly available at https://github.com/ubisoft/ubisoft-laforge-ZeroEGGS .     

Effects of Sc Addition and Direct Aging Treatment on Microstructure and Hardness of AlSi10Mg Alloy

Cu-mold centrifugal cast processing is employed as a rapid solidification method for producing samples with and without Sc. The Al–Si–Mg and Al–Si–Mg–Sc alloy samples are exposed to direct aging treatments varying temperature and time to verify the microstructural changes. Both rapidly solidified samples and as-aged samples are characterized by a number of methods, including optical microscopy, SEM–EDS, transmission Electron Microscopy (TEM)–EDS, TEM–HAADF, X-ray diffraction (XRD), differential scanning calorimetry (DSC), and Vickers hardness. At first, the results point to a strong precipitate-related hardening effect formed as a result of the Sc addition to the alloy. All samples containing Sc show a higher hardness value when compared to their respective treated samples without Sc. Second, when comparing the Al–10Si–Mg–0.4Sc alloy samples among themselves after being treated at different conditions, high temperatures, and excessive treatment times are recognized as detrimental to the hardness. This is due to the growth of larger Sc-bearing precipitates of approximately 1 μm in size under such conditions, having lower efficiency in pinning dislocations during loading. The best aging condition is 255 °C for 60 min, which produces a very fine dispersion of Mg and Sc intermetallics (200 nm in size) with a peak hardness of 110 HV.     

Topological map-based approach for localization and mapping memory optimization

Robotics in agriculture faces several challenges, such as the unstructured characteristics of the environments, variability of luminosity conditions for perception systems, and vast field extensions. To implement autonomous navigation systems in these conditions, robots should be able to operate during large periods and travel long trajectories. For this reason, it is essential that simultaneous localization and mapping algorithms can perform in large-scale and long-term operating conditions. One of the main challenges for these methods is maintaining low memory resources while mapping extensive environments. This work tackles this issue, proposing a localization and mapping approach called VineSLAM that uses a topological mapping architecture to manage the memory resources required by the algorithm. This topological map is a graph-based structure where each node is agnostic to the type of data stored, enabling the creation of a multilayer mapping procedure. Also, a localization algorithm is implemented, which interacts with the topological map to perform access and search operations. Results show that our approach is aligned with the state-of-the-art regarding localization precision, being able to compute the robot pose in long and challenging trajectories in agriculture. In addition, we prove that the topological approach innovates the state-of-the-art memory management. The proposed algorithm requires less memory than the other benchmarked algorithms, and can maintain a constant memory allocation during the entire operation. This consists of a significant innovation, since our approach opens the possibility for the deployment of complex 3D SLAM algorithms in real-world applications without scale restrictions.     

A technical characterization of APTs by leveraging public resources

Advanced persistent threats (APTs) have rocketed over the last years. Unfortunately, their technical characterization is incomplete—it is still unclear if they are advanced usages of regular malware or a different form of malware. This is key to develop an effective cyberdefense. To address this issue, in this paper we analyze the techniques and tactics at stake for both regular and APT-linked malware. To enable reproducibility, our approach leverages only publicly available datasets and analysis tools. Our study involves 11,651 regular malware and 4686 APT-linked ones. Results show that both sets are not only statistically different, but can be automatically classified with F1 > 0.8 in most cases. Indeed, 8 tactics reach F1 > 0.9. Beyond the differences in techniques and tactics, our analysis shows thats actors behind APTs exhibit higher technical competence than those from non-APT malwares.

     

Application of the MOSFET device structure in characterizing imperfection centers in indium-doped silicon

C.T. Sah has published a review article demonstrating the application of high-frequency small signal capacitance and current transients of a space charge layer. Application of such transients is a powerful technique in characterizing deep level imperfection center concentrations, energy levels, thermal and optical emission rates and thermal capture cross sections. The MOSFET device structure is particularly convenient for low temperature measurements of shallow levels where deionization occurs and the substrate becomes highly resistive, seriously limiting capacitance transient techniques. Examples are given by results on indium-doped silicon, such as employed in extrinsic IR detectors. The emission time constant of holes from the neutral indium center has been found to depend on the indium doping. Measurements on lightly doped samples yield a value for the emission rate, $\text{1}\text{e}{}_{\mathrm{p}}$, of 6.0 msec at 77°K and a thermal activation energy of 0.15 eV. Measurements on heavily doped samples yield values of $\text{1}\text{e}{}_{\mathrm{p}}$ of 20 μsec at 77°K and an activation energy of 0.117 eV. These results are consistent with the Poole-Frenkel effect describing field enhanced thermal emission of holes from the indium center. Measurements of the hole capture coefficient at 77°K yield values for c_p of 3.7 × 10^?7 cm³/sec. These measurements have been made on heavily doped samples. The capture coefficient measured is the zero field or quasi-equilibrium value. The temperature dependence of the hole capture coefficient has been found to be T^?4. Small transients in the thermal emission rate measurements have been observed. These transients have thermal activation energies of around 0.08 eV and are associated with the 0.11 eV level as reported by Hughes Research Labs after accounting for barrier lowering by the Poole-Frenkel effect.     

Epidemiology of Trauma and Posttraumatic Stress Disorder in Mexico.

Prevalence rates of trauma and posttraumatic stress disorder (PTSD) were estimated from a probability sample of 2,509 adults from 4 cities in Mexico. PTSD was assessed according to Diagnostic and Statistical Manual of Mental Disorders (American Psychiatric Association, 1994) criteria using the Composite International Diagnostic Interview (CIDI; WHO, 1997). Lifetime prevalence of exposure and PTSD were 76% and 11.2%, respectively. Risk for PTSD was highest in Oaxaca (the poorest city), persons of lower socioeconomic status, and women. Conditional risk for PTSD was highest following sexual violence, but nonsexual violence and traumatic bereavement had greater overall impact because of their frequency. Of lifetime cases, 62% became chronic; only 42% received medical or professional care. The research demonstrates the importance of expanding the epidemiologic research base on trauma to include developing countries around the world. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Optimal Multi-Criteria Waypoint Selection for Autonomous Vehicle Navigation in Structured Environment

This paper deals with autonomous navigation of unmanned ground vehicles (UGV). The UGV has to reach its assigned final configuration in a structured environments (e.g. a warehouse or an urban environment), and to avoid colliding neither with the route boundaries nor any obstructing obstacles. In this paper, vehicle planning/set-points definition is addressed. A new efficient and flexible methodology for vehicle navigation throughout optimal and discrete selected waypoints is proposed. Combining multi-criteria optimization and expanding tree allows safe, smooth and fast vehicle overall navigation. This navigation through way-points permits to avoid any path/trajectory planning which could be time consuming and complex, mainly in cluttered and dynamic environment. To evaluate the flexibility and the efficiency of the proposed methodology based on expanding tree (taking into account the vehicle model and uncertainties), an important part of this paper is dedicated to give an accurate comparison with another proposed optimization based on the commonly used grid map. A set of simulations, comparison with other methods and experiments, using an urban electric vehicle, are presented and demonstrate the reliability of our proposals.     

Comparison of metaheuristics for the k‐labeled spanning forest problem

In this paper, we study the k‐labeled spanning forest (kLSF) problem in which an undirected graph whose edges are labeled and an integer‐positive value are given; the aim is to find a spanning forest of the input graph with the minimum number of connected components and the upper bound on the number of labels. The problem is related to the minimum labeling spanning tree problem and has several applications in the real world. In this paper, we compare several metaheuristics to solve this NP‐hard problem. In particular, the proposed intelligent variable neighborhood search (VNS) shows excellent performance, obtaining high‐quality solutions in short computational running time. This approach integrates VNS with other complementary approaches from machine learning, statistics, and experimental algorithmics, in order to produce high‐quality performance and completely automate the resulting optimization strategy.     

Engineering an efficient two‐phase local search algorithm for the co‐rotating twin‐screw extruder configuration problem

The twin‐screw configuration problem arises during polymer extrusion and compounding. It consists in defining the location of a set of pre‐defined screw elements along the screw axis in order to optimize different, typically conflicting objectives. In this paper, we present a simple yet effective stochastic local search (SLS) algorithm for this problem. Our algorithm is based on efficient single‐objective iterative improvement algorithms, which have been developed by studying different neighborhood structures, neighborhood search strategies, and neighborhood restrictions. These algorithms are embedded into a variation of the two‐phase local search framework to tackle various bi‐objective versions of this problem. An experimental comparison with a previously proposed multi‐objective evolutionary algorithm shows that a main advantage of our SLS algorithm is that it converges faster to a high‐quality approximation to the Pareto front.     

Allometric relationships in the bioconcentration of heavy metals by the edible tropical clam Gafrarium tumidum

Although metal contamination is a problem of major concern in the lagoon of New Caledonia due to intense mining activities conducted on land, very little is known on the metal ecotoxicology of local marine organisms. The clam Gafrarium tumidum was investigated to assess its usefulness as a bioindicator species of metal contamination in this lagoon. More particularly, allometric relationships between metal accumulation and clam size were determined for five common metals in New Caledonian lagoon waters (Cd, Cr, Co, Zn and Ag) using a highly sensitive radiotracer technique. Experimental results showed that allometric relationships were dependent on the element and on the body compartment considered. As a rule, allometric relationships of metal concentration factor were more pronounced in shell than in soft parts. Significant relationships with clam size for Cd, Cr, Co and Zn followed inverse power functions. In contrast, the degree of Ag bioaccumulation was positively correlated with size. In view of the literature on Ag in bivalves, the latter observation suggests the occurrence of a specific detoxification mechanism (sequestration) that would be more efficient in old individuals. Overall, the experimental results indicate that the use of G. tumidum as a bioindicator in monitoring programmes requires selecting individuals of a specific size range in order to obtain comparable information about ambient metal levels. Since the size effect is greatest among smaller individuals, it is recommended to select clams with a shell width greater than 35 mm.