A Role for Human Renal Tubular Epithelial Cells in Direct Allo-Recognition by CD4+ T-Cells and the Effect of Ischemia-Reperfusion

Direct allorecognition is the earliest and most potent immune response against a kidney allograft. Currently, it is thought that passenger donor professional antigen-presenting cells (APCs) are responsible. Further, many studies support that graft ischemia-reperfusion injury increases the probability of acute rejection. We evaluated the possible role of primary human proximal renal tubular epithelial cells (RPTECs) in direct allorecognition by CD4+ T-cells and the effect of anoxia-reoxygenation. In cell culture, we detected that RPTECs express all the required molecules for CD4+ T-cell activation (HLA-DR, CD80, and ICAM-1). Anoxia-reoxygenation decreased HLA-DR and CD80 but increased ICAM-1. Following this, RPTECs were co-cultured with alloreactive CD4+ T-cells. In T-cells, zeta chain phosphorylation and c-Myc increased, indicating activation of T-cell receptor and co-stimulation signal transduction pathways, respectively. T-cell proliferation assessed with bromodeoxyuridine assay and with the marker Ki-67 increased. Previous culture of RPTECs under anoxia raised all the above parameters in T-cells. FOXP3 remained unaffected in all cases, signifying that proliferating T-cells were not differentiated towards a regulatory phenotype. Our results support that direct allorecognition may be mediated by RPTECs even in the absence of donor-derived professional APCs. Also, ischemia-reperfusion injury of the graft may enhance the above capacity of RPTECs, increasing the possibility of acute rejection.     

Graphite Oxide and Aromatic Amines: Size Matters

Experimental and theoretical studies are performed in order to illuminate, for first time, the intercalation mechanism of polycyclic aromatic molecules into graphite oxide. Two representative molecules of this family, aniline and naphthalene amine are investigated. After intercalation, aniline molecules prefer to covalently connect to the graphene oxide matrix via chemical grafting, while napthalene amine molecules bind with the graphene oxide surface through π–π interactions. The presence of intercalated aromatic molecules between the graphene oxide layers is demonstrated by X‐ray diffraction, while the type of interaction between graphene oxide and polycyclic organic molecules is elucidated by X‐ray photoelectron spectroscopy. Combined quantum mechanical and molecular mechanical calculations describe the intercalation mechanism and the aniline grafting, rationalizing the experimental data. The present work opens new perspectives for the interaction of various aromatic molecules with graphite oxide and the so‐called “intercalation chemistry”.     

Sub-optimal solutions to track detection problem using graph theoretic concepts

This paper demonstrates how the problem of tracking targets, which appear as either straight or curved lines in two-dimensional display images (or data images) can be formulated in terms of a directed weighted graph model and how dynamic programming techniques can be efficiently applied to reach an optimal or sub-optimal solution. In general, track detection algorithms providing optimal solutions have good detective ability, but most of them suffer from the inability to detect discontinuous lines or to resolve efficiently pairs of crossing lines. A sub-optimal solution is provided that efficiently overcomes these weaknesses. We focus on modeling the track detection problem in terms of a graph, formulating fast sequential/parallel sub-optimal track detection algorithms and testing them on simulated data in order to show their detective ability. Moreover, we specify the conditions under which sub-optimal algorithms can perform at least as well as their corresponding optimal algorithms. This is significant for the track detection problem where fast, accurate and real-time detection is considered a necessity.     

A quantitative analysis of the European Automakers’ voluntary commitment to reduce CO2 emissions from new passenger cars based on independent experimental data

The reduction of CO₂ emissions and fuel consumption from road transportation constitutes an important pillar of the European Union strategy for implementing the Kyoto Protocol. The commitment to reduce passenger car average CO₂ emissions at 140 g/km in 2008 signed by European car manufacturers and the European Commission is up to now the most important initiative towards limiting CO₂ emissions from road transportation and particularly from passenger cars. Until today, annual reports show the manufacturers’ efforts in limiting CO₂ emissions is within the intermediate target set by the commitment and these results are incorporated in emissions estimations and scientific studies. This paper analyses the origin of the progress achieved so far in CO₂ emissions and attempts an assessment of the commitment using independent experimental emission data. Additionally, the applicability of the commitment-monitoring data into policy and decision-making tools is being examined. The results indicate that a significant part of the reductions achieved so far is due to a market shift towards diesel vehicle sales and that no reduction factors should be applied yet in CO₂ emissions estimation models.     

Design of radiation-emission measurements of an air-traffic surveillance radar

The current work presents the procedure of designing and carrying out measurements of radiation emission from an air-traffic surveillance radar. The system requirements are first given, and then the equipment used is described. The steps to determine the operating characteristics of the radar are specified in detail. The necessary methods for manual power measurements and calculations are next explained. Since the final measurement system was fully automated, its main features (topology, protocol of operation) are also given. Finally, some measurement results taken during the initial phase of system operation are presented and discussed.     

A higher-order unsplit-field perfectly matched layer for the reflectionless truncation of 3-D spherical FDTD lattices

An enhanced higher-order finite-difference time-domain (FDTD) method for the systematic implementation of 3-D reflectionless perfectly matched layers (PML) in spherical coordinates is presented. By establishing a topologically unsplit-field formulation, the novel technique introduces accurate nonstandard schemes that eliminate the notably intricate lattice dispersion errors. Moreover, the wider spatial increments are treated via self-adaptive compact operators, while a mesh expansion process yields a significant reduction of the absorber's depth. For the temporal variable, the proposed method employs a multistage leapfrog integration that guarantees stability and excitation universality. Hence, because of the optimal configuration of the new PML, it attains a critical annihilation of both propagating and spurious wave families, even for complicated domains. Numerical investigation verifies the superiority of the higher-order algorithm via several unbounded radiation and scattering spherical problems.     

Power efficiency through tuple ranking in?wireless sensor network monitoring

In this paper, we present an innovative framework for efficiently monitoring Wireless Sensor Networks (WSNs). Our framework, coined KSpot, utilizes a novel top-k query processing algorithm we developed, in conjunction with the concept of in-network views, in order to minimize the cost of query execution. For ease of exposition, consider a set of sensors acquiring data from their environment at a given time instance. The generated information can conceptually be thought as a horizontally fragmented base relation R. Furthermore, the results to a user-defined query Q, registered at some sink point, can conceptually be thought as a view V. Maintaining consistency between V and R is very expensive in terms of communication and energy. Thus, KSpot focuses on a subset V??(?V) that unveils only the k highest-ranked answers at the sink, for some user defined parameter k. To illustrate the efficiency of our framework, we have implemented a real system in nesC, which combines the traditional advantages of declarative acquisition frameworks, like TinyDB, with the ideas presented in this work. Extensive real-world testing and experimentation with traces from UC-Berkeley, the University of Washington and Intel Research Berkeley, show that KSpot provides an up to 66% of energy savings compared to TinyDB, minimizes both the size and number of packets transmitted over the network (up to 77%), and prolongs the longevity of a WSN deployment to new scales.     

Combining feature spaces for classification

In this paper we offer a variational Bayes approximation to the multinomial probit model for basis expansion and kernel combination. Our model is well-founded within a hierarchical Bayesian framework and is able to instructively combine available sources of information for multinomial classification. The proposed framework enables informative integration of possibly heterogeneous sources in a multitude of ways, from the simple summation of feature expansions to weighted product of kernels, and it is shown to match and in certain cases outperform the well-known ensemble learning approaches of combining individual classifiers. At the same time the approximation reduces considerably the CPU time and resources required with respect to both the ensemble learning methods and the full Markov chain Monte Carlo, Metropolis-Hastings within Gibbs solution of our model. We present our proposed framework together with extensive experimental studies on synthetic and benchmark datasets and also for the first time report a comparison between summation and product of individual kernels as possible different methods for constructing the composite kernel matrix.     

Quantifying the water–energy nexus in Greece

In this paper we provide an assessment of the water–energy nexus for Greece. More specifically, the amount of freshwater consumed per unit of energy produced is determined: for both conventional (lignite, diesel and fuel oil-fired) and advanced (combined operation of gas turbine) thermal power plants in the electricity generation sector; for extraction and refining activities in the primary energy production sector; and for the production of biodiesel that is used as a blend in the ultimately delivered automotive diesel fuel. In addition, the amount of electricity consumed for the purposes of water supply and sewerage is presented. In view of the expected effects of climate change in the Mediterranean region, the results of this study highlight the need for authorities to prepare a national strategy that will ensure climate resilience in both energy and water sectors of the country.