Assessment of tremor activity in the Parkinson's disease using a set of wearable sensors

Tremor is the most common motor disorder of Parkinson's disease (PD) and consequently its detection plays a crucial role in the management and treatment of PD patients. The current diagnosis procedure is based on subject-dependent clinical assessment, which has a difficulty in capturing subtle tremor features. In this paper, an automated method for both resting and action/postural tremor assessment is proposed using a set of accelerometers mounted on different patient's body segments. The estimation of tremor type (resting/action postural) and severity is based on features extracted from the acquired signals and hidden Markov models. The method is evaluated using data collected from 23 subjects (18 PD patients and 5 control subjects). The obtained results verified that the proposed method successfully: 1) quantifies tremor severity with 87 % accuracy, 2) discriminates resting from postural tremor, and 3) discriminates tremor from other Parkinsonian motor symptoms during daily activities.     

Energy efficient network coding-based MAC for cooperative ARQ wireless networks

In this paper we introduce a network coding-aided energy efficient Medium Access Control (MAC) protocol that coordinates the transmissions among a set of relay nodes which act as helpers in cooperative Automatic Repeat reQuest-based (ARQ-based) wireless networks. Applying network coding techniques, we achieve to increase the energy efficiency of the network without compromising the system performance in terms of Quality of Service. Our proposed solution is evaluated by both analytical and simulation results.     

Capability-Based Defenses Against DoS Attacks in Multi-path MANET Communications

We present the design, implementation, and evaluation of CapMan, a capability-based security mechanism that prevents denial-of-service (DoS) attacks against mobile ad-hoc networks (MANETs). In particular, our approach is designed to mitigate insider attacks that exploit multi-path routing to flood with packets on other participating nodes in the network. CapMan is instantiated on every node and enforces capability limits that effectively regulate the traffic for all end-to-end network flows. Each capability is issued and advertised by the capability distribution module, and is globally maintained via the capability enforcement logic. By periodically exchanging small usage summaries, all cooperating nodes are informed of the global network state in a scalable and consistent manner. The distribution of summaries empowers individual nodes to make informed decisions and regulate traffic as dictated by the per-flow capabilities across multiple dynamic routing paths. We implemented a prototype of CapMan as a module of the NS2 simulator. We conducted extensive simulations with the prototype using AOMDV as the underlying multi-path routing protocol. Both theoretical analysis and experimental results validate that our mechanism can effectively curtail sophisticated DoS attacks that target multi-path routing in MANETs. We can protect the overall network health even when both the initiator and the responder are malicious insiders and collude in an attempt to deprive the network of valuable resources. Finally, our results show that CapMan introduces relatively small and configurable network overhead and imposes minimal impact on non-attacking traffic flows.     

The EPH/Ephrin System in Bone and Soft Tissue Sarcomas’ Pathogenesis and Therapy: New Advancements and a Literature Review

Musculoskeletal sarcomas represent rare heterogenous malignancies of mesenchymal origin that can be divided in two distinct subtypes, bone and soft tissue sarcomas. Current treatment options combine the surgical excision of local tumors and multidrug chemotherapy to prevent metastatic widespread disease. Due to the grim prognosis that usually accompanies such tumors, researchers have attempted to shed light on the molecular pathways implicated in their pathogenesis in order to develop novel, innovative, personalized therapeutic strategies. Erythropoietin-producing human hepatocellular receptors (EPHs) are tyrosine-kinase transmembrane receptors that, along with their ligands, ephrins, participate in both tumor-suppressive or tumor-promoting signaling pathways in bone and soft tissue sarcomas. The EPH/ephrin axis orchestrates cancerous processes such as cell–cell and cell–substrate adhesion and enhances the remodeling of the intracellular cytoskeleton to stimulate the motility and invasiveness of sarcoma cells. The purpose of our study was to review published PubMed literature to extract results from in vitro, in vivo and clinical trials indicative of the role of EPH/ephrin signaling in bone and soft tissue sarcomas. Based on these reports, significant interactions between the EPH/ephrin signaling pathway and a plethora of normal and abnormal cascades contribute to molecular mechanisms enhancing malignancy during sarcoma progression. In addition, EPHs and ephrins are prospective candidates for diagnostic, monitoring and therapeutic purposes in the clinical setting against bone and soft tissue sarcomas.     

Function-integrative Lightweight Engineering – Design Methods and Applications

Function-integrative lightweight engineering represents an essential element in modern design methods. Currently, there is a great need for the incorporation of sensors, actuators and electronics in novel, demand-oriented components. In contrast to a subsequent, mostly adhesive bonding, structural integration offers numerous advantages, for example in terms of space requirements and robustness. This paper demonstrates the potential of integrated sensors for various industrial sectors based on selected examples from mechanical engineering, aviation, mobility, sports, and medical technology.     

Bivariate semiparametric control charts for simultaneous monitoring of process mean and variance

In the present article, two semiparametric bivariate control charts are presented, which use order statistics and are effective in jointly monitoring of possible shifts in the process mean and/or variance. To achieve that both the median location (or more generally the location of a specific order statistic) and the number of specific observations of the test sample lying between the control limits are taken into account. The false alarm rate and the in-control average run length are not affected by the marginal distributions, while the effect of the dependence structure on them is negligible; therefore, they can be used as fully nonparametric charts. A performance-comparison study is carried out, and an illustrative example is provided using a real-world data set.     

Macroscopic and microscopic techno-economic analyses highlighting aspects of 5G transport network deployments

Photonic Network Communications - 5G networks will comprise multiple, versatile infrastructures at finest granularity consisting of multiple disaggregated pools of network, compute and storage...     

Parallel generation of meshes with cracks using binary spatial decomposition

This work describes a technique to generate tetrahedral meshes with cracks using parallel computers with distributed memory. This technique can be used for models without cracks as well. It employs a binary partitioning structure that uses axis-aligned planes to decompose the domain. Those decomposing planes are determined based on a refined octree that is built to estimate the amount of work necessary to generate the whole mesh, so that the amount of work in each subdomain is approximately the same. A serial advancing front technique is used in each subdomain concurrently, in such a way that the generated tetrahedra do not cross the decomposing planes. After local synchronizations, meshes are generated interfacing the subdomains. The results show that the prediction of the number of elements in each subdomain is accurate, leading to a well-balanced algorithm and to a good speed-up. Also, the meshes generated in parallel have very good quality, similar to the that of a serially generated mesh.     

Large-scale evaluation of splicing localization algorithms for web images

With the proliferation of smartphones and social media, journalistic practices are increasingly dependent on information and images contributed by local bystanders through Internet-based applications and platforms. Verifying the images produced by these sources is integral to forming accurate news reports, given that there is very little or no control over the type of user-contributed content, and hence, images found on the Web are always likely to be the result of image tampering. In particular, image splicing, i.e. the process of taking an area from one image and placing it in another is a typical such tampering practice, often used with the goal of misinforming or manipulating Internet users. Currently, the localization of splicing traces in images found on the Web is a challenging task. In this work, we present the first, to our knowledge, exhaustive evaluation of today’s state-of-the-art algorithms for splicing localization, that is, algorithms attempting to detect which pixels in an image have been tampered with as the result of such a forgery. As our aim is the application of splicing localization on images found on the Web and social media environments, we evaluate a large number of algorithms aimed at this problem on datasets that match this use case, while also evaluating algorithm robustness in the face of image degradation due to JPEG recompressions. We then extend our evaluations to a large dataset we formed by collecting real-world forgeries that have circulated the Web during the past years. We review the performance of the implemented algorithms and attempt to draw broader conclusions with respect to the robustness of splicing localization algorithms for application in Web environments, their current weaknesses, and the future of the field. Finally, we openly share the framework and the corresponding algorithm implementations to allow for further evaluations and experimentation.     

Reactivation of severely aged commercial three-way catalysts by washing with weak EDTA and oxalic acid solutions

Ethylene diamine tetraacetic acid (EDTA) which is a well-known reagent for its metal extraction efficiency was studied for the first time towards the improvement of the catalytic activity and oxygen storage and release properties (OSC) of severely aged commercial three-way catalysts (TWC) on a laboratory scale. Optimization of the experimental parameters of EDTA-washing procedure of TWC was carried out by varying the washing time, volumetric flow rate, and temperature of EDTA solution. The EDTA-washing procedure of TWC was compared with that of oxalic acid-washing regarding their efficiency in removing P, Pb, S, Ca, Zn, Fe, Cu, Cr, Ni, and Mn, all known TWC contaminants that many of them cause severe deterioration of TWC's activity and oxygen storage and release properties. EDTA appears to be significantly efficient in removing Pb, Zn, Ca, Mn, Fe, Cu and Ni metal contaminants and sulfur but not of phosphorus (P). Phosphorus-containing species were found to be efficiently removed from the aged TWCs after oxalic acid washing. All regeneration procedures applied led to a significant partial recovery of catalytic activity of TWC (CO, C_xH_y and NO_x conversions) under real exhaust gas conditions (dynamometer tests) due to the removal of large amounts of contaminants accumulated on the aged TWC. The washing procedures using oxalic acid alone or in combination with EDTA led to more significant improvements of both catalytic and OSC performance compared with those of EDTA washing alone. This was due to the ability of oxalic acid to remove P-containing compounds which appear to be one of the main causes of commercial three-way catalyst deactivation.