The Association of Human Herpesviruses with Malignant Brain Tumor Pathology and Therapy: Two Sides of a Coin

The role of certain viruses in malignant brain tumor development remains controversial. Experimental data demonstrate that human herpesviruses (HHVs), particularly cytomegalovirus (CMV), Epstein–Barr virus (EBV) and human herpes virus 6 (HHV-6), are implicated in brain tumor pathology, although their direct role has not yet been proven. CMV is present in most gliomas and medulloblastomas and is known to facilitate oncomodulation and/or immunomodulation, thus promoting cancer cell proliferation, invasion, apoptosis, angiogenesis, and immunosuppression. EBV and HHV-6 have also been detected in brain tumors and high-grade gliomas, showing high rates of expression and an inflammatory potential. On the other hand, due to the neurotropic nature of HHVs, novel studies have highlighted the engagement of such viruses in the development of new immunotherapeutic approaches in the context of oncolytic viral treatment and vaccine-based strategies against brain tumors. This review provides a comprehensive evaluation of recent scientific data concerning the emerging dual role of HHVs in malignant brain pathology, either as potential causative agents or as immunotherapeutic tools in the fight against these devastating diseases.     

Synthesis, optical and morphological characterization of soluble main chain 1,3,4-oxadiazole copolyarylethers—potential candidates for solar cells applications as electron acceptors

New copoly(arylether)s containing substituted terphenyl, quinquephenyl, fluorene and anthracene moieties with aromatic 1,3,4-oxadiazole units were prepared and the resulting copolymers are soluble in common organic solvents. Investigation of their optical properties revealed that they emit blue and yellow light. Moreover, their photovoltaic response was studied in blends with poly(3-hexylthiophene) (P3HT) as the electron donor. Despite the low power conversion efficiencies it was shown that photo-induced electron transfer does take place and the performances are higher than a single layer P3HT device. In addition, an anthracene-fluorene-oxadiazole main chain copolymer (PAFOXD) was also examined in a single layer photovoltaic device and gave one of the highest reported open-circuit voltage (V_oc) values in the literature (0.89 V). Finally, a detailed morphological study of the blends and the PAFOXD surface using the atomic force microscopy (AFM) technique, revealed the effect of solvent selection to the preparation of thin films exhibiting the desired performance characteristics.     

Game theoretic distributed uplink power control for CDMA networks with real-time services

In this paper, the issue of efficient power allocation in the uplink of CDMA wireless networks supporting real-time services with various QoS constraints, is addressed. Within the proposed framework, utility functions are adopted to reflect a user’s degree of satisfaction with respect to its actual throughput requirements satisfaction and respective power consumption. The corresponding problem is formulated as a non-cooperative game where users aim selfishly at maximizing their utility-based performance under the imposed limitations. The existence and uniqueness of a Nash equilibrium point of the proposed Uplink Power Control (UPC) game is proven, at which all users have attained a targeted SINR threshold value or transmit with their maximum power, leading essentially to an SINR-balanced system. Moreover, a distributed iterative algorithm for reaching UPC game’s equilibrium is provided. The properties of equilibrium in a pure optimization theoretical framework are studied, and the tradeoffs between users’ overall throughput performance and real-time services’ QoS requirements satisfaction, in channel aware resource allocation processes, are revealed and quantified. Through modeling and simulation the efficacy of the introduced framework and proposed UPC algorithm are demonstrated and evaluated.     

Subclass discriminant Nonnegative Matrix Factorization for facial image analysis

Nonnegative Matrix Factorization (NMF) is among the most popular subspace methods, widely used in a variety of image processing problems. Recently, a discriminant NMF method that incorporates Linear Discriminant Analysis inspired criteria has been proposed, which achieves an efficient decomposition of the provided data to its discriminant parts, thus enhancing classification performance. However, this approach possesses certain limitations, since it assumes that the underlying data distribution is unimodal, which is often unrealistic. To remedy this limitation, we regard that data inside each class have a multimodal distribution, thus forming clusters and use criteria inspired by Clustering based Discriminant Analysis. The proposed method incorporates appropriate discriminant constraints in the NMF decomposition cost function in order to address the problem of finding discriminant projections that enhance class separability in the reduced dimensional projection space, while taking into account subclass information. The developed algorithm has been applied for both facial expression and face recognition on three popular databases. Experimental results verified that it successfully identified discriminant facial parts, thus enhancing recognition performance.     

Cache-aided full-duplex: delivery time analysis and optimization

Edge caching has received much attention as a promising technique to overcome the stringent latency and data-hungry challenges in the future generation wireless networks. Meanwhile, full-duplex (FD) transmission can potentially double the spectral efficiency by allowing a node to receive and transmit at the same frequency band simultaneously. In this paper, we investigate the delivery time performance of a cache-aided FD system, in which an edge node, operates in FD mode, serves users via wireless channels and is equipped with a cache memory. Firstly, we derive a closed-form expression for the average delivery time by taking into account the uncertainties of both backhaul and access wireless channels. The derived analysis allows the examination of the impact of key parameters, e.g., cache size and transmit power. Secondly, a power optimization problem is formulated to minimize the average delivery time. To deal with the non-convexity of the formulated problem, we propose an iterative optimization algorithm based on the bisection method. Finally, numerical results are presented to demonstrate the effectiveness of the proposed algorithm. A significant delivery time reduction is achieved by the proposed optimization compared to the FD reference and half-duplex counterpart.

     

Community detection in Social Media

The proposed survey discusses the topic of community detection in the context of Social Media. Community detection constitutes a significant tool for the analysis of complex networks by enabling the study of mesoscopic structures that are often associated with organizational and functional characteristics of the underlying networks. Community detection has proven to be valuable in a series of domains, e.g. biology, social sciences, bibliometrics. However, despite the unprecedented scale, complexity and the dynamic nature of the networks derived from Social Media data, there has only been limited discussion of community detection in this context. More specifically, there is hardly any discussion on the performance characteristics of community detection methods as well as the exploitation of their results in the context of real-world web mining and information retrieval scenarios. To this end, this survey first frames the concept of community and the problem of community detection in the context of Social Media, and provides a compact classification of existing algorithms based on their methodological principles. The survey places special emphasis on the performance of existing methods in terms of computational complexity and memory requirements. It presents both a theoretical and an experimental comparative discussion of several popular methods. In addition, it discusses the possibility for incremental application of the methods and proposes five strategies for scaling community detection to real-world networks of huge scales. Finally, the survey deals with the interpretation and exploitation of community detection results in the context of intelligent web applications and services.     

Stabilization of Nanoalumina Colloidal Slips

The processing of nanosized powders to produce dense components is a difficult task, mainly due to the strong agglomeration of nanoparticles. In this work, deagglomeration studies were carried out on sol–gel‐derived γ‐alumina suspensions through the addition of dispersant or dispersant in combination with ethylene glycol as binder and the proper wet ball‐milling. For this purpose, zeta‐potential, viscosity, and sedimentation studies were carried out, whereas dilatometric studies accompanied by XRD analyses were performed on the powders derived from the most stable suspensions. Sintering studies followed and the as received ceramics were evaluated by SEM. The optimum stabilization was achieved through the synergistic addition of 2.75 mg/g ammonium polymethacrylate with 1 wt% ethylene glycol. The respective powder, although it indicates a shift of the sintering start to higher temperature, leads to the densest ceramic with the finest (500 nm mean grain size) and the most homogeneous microstructure.     

Organic Food: Buying More Safety or Just Peace of Mind? A Critical Review of the Literature

Consumer concern over the quality and safety of conventional food has intensified in recent years, and primarily drives the increasing demand for organically grown food, which is perceived as healthier and safer. Relevant scientific evidence, however, is scarce, while anecdotal reports abound. Although there is an urgent need for information related to health benefits and/or hazards of food products of both origins, generalized conclusions remain tentative in the absence of adequate comparative data. Organic fruits and vegetables can be expected to contain fewer agrochemical residues than conventionally grown alternatives; yet, the significance of this difference is questionable, inasmuch as actual levels of contamination in both types of food are generally well below acceptable limits. Also, some leafy, root, and tuber organic vegetables appear to have lower nitrate content compared with conventional ones, but whether or not dietary nitrate indeed constitutes a threat to human health is a matter of debate. On the other hand, no differences can be identified for environmental contaminants (e.g. cadmium and other heavy metals), which are likely to be present in food from both origins. With respect to other food hazards, such as endogenous plant toxins, biological pesticides and pathogenic microorganisms, available evidence is extremely limited preventing generalized statements. Also, results for mycotoxin contamination in cereal crops are variable and inconclusive; hence, no clear picture emerges. It is difficult, therefore, to weigh the risks, but what should be made clear is that 'organic' does not automatically equal 'safe.' Additional studies in this area of research are warranted. At our present state of knowledge, other factors rather than safety aspects seem to speak in favor of organic food.     

Minimum Moment Method for Resource Leveling Using Entropy Maximization

The minimum moment method for resource leveling is revisited and restated as an entropy-maximization problem. The minimum moment method assumes that the moment of the daily resource demands about the horizontal axis of a project’s resource histogram is a good measure of the resource utilization and that the optimal resource allocation exists when the total moment is at a minimum, thus when the resource histogram is of rectangular shape. The entropy-maximization method proposed in this paper makes use of the general theory of entropy and two of its principal properties (subadditivity and maximality) to revisit the minimum moment method for resource leveling. The entropy-maximization method presented allows for activity stretching and provides resource allocation solutions that show improvement over previous approaches. A case study is also presented that validates the results.     

An axiomatization of graphs

The magmoid of hypergraphs labelled over a finite doubly ranked alphabet, is characterized as the quotient of the free magmoid generated by this alphabet divided by a finite set of equations. Thus a relevant open problem, posed by Engelfriet and Vereijken, is being solved.Received: 27 April 2004, Published online: 14 October 2004