Lithium–Sulfur Battery Cable Made from Ultralight,Flexible Graphene/Carbon Nanotube/Sulfur Composite Fibers

The emergence of flexible and wearable electronic devices with shape amenability and high mobility has stimulated the development of flexible power sources to bring revolutionary changes to daily lives. The conventional rechargeable batteries with fixed geometries and sizes have limited their functionalities in wearable applications. The first‐ever graphene‐based fibrous rechargeable batteries are reported in this work. Ultralight composite fibers consisting of reduced graphene oxide/carbon nanotube filled with a large amount of sulfur (rGO/CNT/S) are prepared by a facile, one‐pot wet‐spinning method. The liquid crystalline behavior of high concentration GO sheets facilitates the alignment of rGO/CNT/S composites, enabling rational assembly into flexible and conductive fibers as lithium–sulfur battery electrodes. The ultralight fiber electrodes with scalable linear densities ranging from 0.028 to 0.13 mg cm^?1 deliver a high initial capacity of 1255 mAh g^?1 and an areal capacity of 2.49 mAh cm^?2 at C /20. A shape‐conformable cable battery prototype demonstrates a stable discharge characteristic after 30 bending cycles.     

hiPSC-Derived Epidermal Keratinocytes from Ichthyosis Patients Show Altered Expression of Cornification Markers

Inherited ichthyoses represent a large heterogeneous group of skin disorders characterised by impaired epidermal barrier function and disturbed cornification. Current knowledge about disease mechanisms has been uncovered mainly through the use of mouse models or human skin organotypic models. However, most mouse lines suffer from severe epidermal barrier defects causing neonatal death and human keratinocytes have very limited proliferation ability in vitro. Therefore, the development of disease models based on patient derived human induced pluripotent stem cells (hiPSCs) is highly relevant. For this purpose, we have generated hiPSCs from patients with congenital ichthyosis, either non-syndromic autosomal recessive congenital ichthyosis (ARCI) or the ichthyosis syndrome trichothiodystrophy (TTD). hiPSCs were successfully differentiated into basal keratinocyte-like cells (hiPSC-bKs), with high expression of epidermal keratins. In the presence of higher calcium concentrations, terminal differentiation of hiPSC-bKs was induced and markers KRT1 and IVL expressed. TTD1 hiPSC-bKs showed reduced expression of FLG, SPRR2B and lipoxygenase genes. ARCI hiPSC-bKs showed more severe defects, with downregulation of several cornification genes. The application of hiPSC technology to TTD1 and ARCI demonstrates the successful generation of in vitro models mimicking the disease phenotypes, proving a valuable system both for further molecular investigations and drug development for ichthyosis patients.     

A New Route to Highly Stretchable and Soft Inorganic–Organic Hybrid Elastomers Using Polydimethylsiloxane as Crosslinker of Epoxidized Natural Rubber

Sulfur or peroxide crosslinking is the most common and conventional method to develop elastomeric materials. A new approach to crosslink epoxidized natural rubber (ENR) by aminopropyl terminated polydimethylsiloxane (AT-PDMS) is described, intending to develop a new kind of hybrid organic–inorganic elastomers. The curing reaction is accelerated by using hydroquinone as a catalyst. The formation of the hybrid structure is evident from the appearance of two glass transition temperatures, at −1 and −120 °C, for the ENR and PDMS phases, respectively. The curing reaction is found to be of first order with respect to amine concentration with the estimated activation energy of ≈62 kJ mol⁻¹. Comparing the mechanical properties to a typical ENR-sulfur system leads to the conclusion that the ENR/AT-PDMS hybrid structure is highly stretchable and soft, as demonstrated by its relatively higher strain at failure (up to ≈630%), and lower hardness and modulus values. The higher stretchability and soft nature of the material are achieved by introducing flexible PDMS chains during the curing process resulting to a hybrid elastomer networks. This kind of soft but robust materials can find several applications in diverse fields, such as soft robotics, flexible, and stretchable electronics.     

The max-INAR(1) model for count processes

This paper proposes a discrete counterpart of the conventional max-autoregressive process of order one. It is based on the so-called binomial thinning operator and driven by a sequence of independent and identically distributed nonnegative integer-valued random variables with either regularly varying right tail or exponential-type right tail. Basic probabilistic and statistical properties of the process are discussed in detail, including the analysis of conditional moments, transition probabilities, the existence and uniqueness of a stationary distribution, and the relationship between the observations’ and innovations’ distribution. We also provide conditions on the marginal distribution of the process to ensure that the innovations’ distribution exists and is well defined. Several examples of families of distributions satisfying such conditions are presented, but also some counterexamples are analyzed. Furthermore, the analysis of its extremal behavior is also considered. In particular, we look at the limiting distribution of sample maxima and its corresponding extremal index.     

State of the Art on Monocular 3D Face Reconstruction,Tracking, and Applications

The computer graphics and vision communities have dedicated long standing efforts in building computerized tools for reconstructing, tracking, and analyzing human faces based on visual input. Over the past years rapid progress has been made, which led to novel and powerful algorithms that obtain impressive results even in the very challenging case of reconstruction from a single RGB or RGB‐D camera. The range of applications is vast and steadily growing as these technologies are further improving in speed, accuracy, and ease of use. Motivated by this rapid progress, this state‐of‐the‐art report summarizes recent trends in monocular facial performance capture and discusses its applications, which range from performance‐based animation to real‐time facial reenactment. We focus our discussion on methods where the central task is to recover and track a three dimensional model of the human face using optimization‐based reconstruction algorithms. We provide an in‐depth overview of the underlying concepts of real‐world image formation, and we discuss common assumptions and simplifications that make these algorithms practical. In addition, we extensively cover the priors that are used to better constrain the under‐constrained monocular reconstruction problem, and discuss the optimization techniques that are employed to recover dense, photo‐geometric 3D face models from monocular 2D data. Finally, we discuss a variety of use cases for the reviewed algorithms in the context of motion capture, facial animation, as well as image and video editing.     

Analysis of burstiness monitoring and detection in an adaptive Web system

Due to the heavy tailed pattern of Internet traffic, it is crucial to monitor the incoming arrival rate in a Web system to preserve its performance. In this study, we focus on the arrival rate processing mechanism as part of the design of an adaptive load balancing Web algorithm. The arrival rate is one of the most important metrics to be monitored in a Web site to avoid the possible congestion of Web servers. Six methods are analysed to detect the burstiness of incoming traffic in a Web system. We define six burstiness factors to be individually included in an adaptive load balancing algorithm, which also needs to monitor some Web servers’ parameters continuously, such as the arrival rate at the server or its CPU utilization in order to avoid an unexpected overload situation.We also define adaptive time slot scheduling based on the burstiness factor, which reduces considerably the overhead of the monitoring process by increasing the monitoring frequency when bursty traffic arrives at the system and by decreasing the frequency when no bursts are detected in the arrival rate. Simulation results of the behaviour of the six burstiness factors and adaptive time slot scheduling when sudden changes are detected in the arrival rate are presented and discussed. We have considered a scenario made up of a locally distributed cluster-based Web information system for simulations.     

Anatomically-based musculoskeletal modeling: prediction and validation of muscle deformation during walking

Accurate modeling of the musculoskeletal system during motion is a challenging task that has not yet been solved. In this paper, we outline and validate a free-form deformation method called the Host Mesh Fitting (HMF) technique for predicting muscle deformation during walking of a subject-specific musculoskeletal model. 20 lower limb muscles were deformed according to the HMF solution of a surrounding host mesh that resembled the skin boundary, resulting in a realistic walking simulation of the anatomically-based model. The shape changes of five muscles were further validated by comparing the predicted deformations with magnetic resonance image data in two lower limb positions.

State of the Art on Neural Rendering

Efficient rendering of photo-realistic virtual worlds is a long standing effort of computer graphics. Modern graphics techniques have succeeded in synthesizing photo-realistic images from hand-crafted scene representations. However, the automatic generation of shape, materials, lighting, and other aspects of scenes remains a challenging problem that, if solved, would make photo-realistic computer graphics more widely accessible. Concurrently, progress in computer vision and machine learning have given rise to a new approach to image synthesis and editing, namely deep generative models. Neural rendering is a new and rapidly emerging field that combines generative machine learning techniques with physical knowledge from computer graphics, e.g., by the integration of differentiable rendering into network training. With a plethora of applications in computer graphics and vision, neural rendering is poised to become a new area in the graphics community, yet no survey of this emerging field exists. This state-of-the-art report summarizes the recent trends and applications of neural rendering. We focus on approaches that combine classic computer graphics techniques with deep generative models to obtain controllable and photorealistic outputs. Starting with an overview of the underlying computer graphics and machine learning concepts, we discuss critical aspects of neural rendering approaches. Specifically, our emphasis is on the type of control, i.e., how the control is provided, which parts of the pipeline are learned, explicit vs. implicit control, generalization, and stochastic vs. deterministic synthesis. The second half of this state-of-the-art report is focused on the many important use cases for the described algorithms such as novel view synthesis, semantic photo manipulation, facial and body reenactment, relighting, free-viewpoint video, and the creation of photo-realistic avatars for virtual and augmented reality telepresence. Finally, we conclude with a discussion of the social implications of such technology and investigate open research problems.