ECPR: Environment- and Context-aware Combined Power and Rate Distributed Congestion Control for Vehicular Communications

Safety and efficiency applications in vehicular networks rely on the exchange of periodic messages between vehicles. These messages contain position, speed, heading, and other vital information that makes the vehicles aware of their surroundings. The drawback of exchanging periodic cooperative messages is that they generate significant channel load. Decentralized Congestion Control (DCC) algorithms have been proposed to minimize the channel load. However, while the rationale for periodic message exchange is to improve awareness, existing DCC algorithms do not use awareness as a metric for deciding when, at what power, and at what rate the periodic messages need to be sent in order to make sure all vehicles are informed. We propose an environment- and context-aware DCC algorithm combines power and rate control in order to improve cooperative awareness by adapting to both specific propagation environments (e.g., urban intersections, open highways, suburban roads) as well as application requirements (e.g., different target cooperative awareness range). Studying various operational conditions (e.g., speed, direction, and application requirement), ECPR adjusts the transmit power of the messages in order to reach the desired awareness ratio at the target distance while at the same time controlling the channel load using an adaptive rate control algorithm. By performing extensive simulations, including realistic propagation as well as environment modeling and realistic vehicle operational environments (varying demand on both awareness range and rate), we show that ECPR can increase awareness by 20% while keeping the channel load and interference at almost the same level. When permitted by the awareness requirements, ECPR can improve the average message rate by 18% compared to algorithms that perform rate adaptation only.Comment: 37 Pages, 12 Figures, 5 Tables, Elsevier Computer Communications, May 201

Insight in the phenolic composition and antioxidative properties of Vitis vinifera leaves extracts

In the present investigation, leaf ethanolic extracts of Vitis vinifera were assayed for their polyphenolic composition and antioxidative properties. The leaves were collected during lush vegetation period (May leaves) and after the harvest (September leaves). Air dried plant material was homogenized and the polyphenolic constituents were extracted using conventional solvent extraction procedure. Total phenolics, flavonoids, non-flavonoids, catechins and flavanols were determined using spectrophotometric methods. Both extracts were very rich in phenolic compounds. The concentration of total phenols in September leaves extract was about 30 % higher compared to May leaves extract, due to the increase of flavonoid (catechin) fraction. Non-flavonoid compound content was almost equal in both extracts. The amount of flavanols, determined with p-dimethylaminocinnamaldehyde method, was taken as indicator of flavan-3-ol monomers, while high catechin content determined by vanillin method, indicated the presence of polymeric fraction. The total catechin content in September leaves extract was more than 3 folds higher in comparison to May leaves extract. Principal phenolic compounds were separated by high pressure liquid chromatography on reverse phase. Antioxidant properties, determined as: 2,2-diphenyl-1-picrylhydrazyl radical and 2,2\u27-azinobis-(3-ethylbenzthiazoline-6-sulfonate) radical cation scavenging ability, ferric reducing/antioxidant power, Fe2+ chelating activity, and using β-carotene bleaching assay, were total phenol concentration dependent. September leaves extract had better free radical scavenging capacity, higher reducing power, and was more efficient in protecting the oxidation of emulsified linoleic acid, in comparison with May leaves extract which showed better chelating ability. The presence of active phenolic compounds: phenolic acids (3-hydroxybenzoic acid, caffeic acid, gallic acid, vanillin acid), flavonoids ((+)-catechin, (-)-epicatechin, apigenin, myricetin, quercetin, quercetin-4\u27-glucoside, rutin), and stilbenes (trans-resveratrol and resveratrol derivatives) was confirmed in both extracts. According to the results achieved, vine leaf extracts can be considered rich natural source of polyphenols with significant antioxidant properties

The Application of Bass Diffusion Model in Forecasting Telecommunication Services Users in Military Assistance to Civilian Authorities

This paper analyses the application of Bass’s diffusion model in forecasting the number of telecommunication services users in the event of natural disasters. Citizens’ behaviour has been modelled in the case of an emergency situation caused by an earthquake with high magnitude. We analysed the area of an administrative district in the south-west part of the Republic of Serbia which includes two cities and three municipalities. To control the consequences of natural disasters, a unit of the Army of Serbia with the required number of radio transceivers for establishing communication between the vulnerable population and rescuers with command staff at the observed territory has been dimensioned. Special emphasis is given to the provision of telecommunication support in the military assistance in a relief operation with civil authorities.Defence Science Journal, Vol. 65, No. 2, March 2015, pp.144-149, DOI:http://dx.doi.org/10.14429/dsj.65.602

Huxley muscle model surrogates for high-speed multi-scale simulations of cardiac contraction

The computational requirements of the Huxley-type muscle models are substantially higher than those of Hill-type models, making large-scale simulations impractical or even impossible to use. We constructed a data-driven surrogate model that operates similarly to the original Huxley muscle model but consumes less computational time and memory to enable efficient usage in multiscale simulations of the cardiac cycle. The data was collected from numerical simulations to train deep neural networks so that the neural networks’ behavior resembles that of the Huxley model. Since the Huxley muscle model is history-dependent, time series analysis is required to take the previous states of the muscle model into account. Recurrent and temporal convolutional neural networks are typically used for time series analysis. These networks were trained to produce stress and instantaneous stiffness. Once the networks have been trained, we compared the similarity of the produced stresses and achieved speed-up to the original Huxley model, which indicates the potential of the surrogate model to replace the model efficiently. We presented the creation procedure of the surrogate model and integration of the surrogate model into the finite element solver. Based on similarities between the surrogate model and the original model in several types of numerical experiments, and also achieved speed-up of an order of magnitude, it can be concluded that the surrogate model has the potential to replace the original model within multiscale simulations. Finally, we used our surrogate model to simulate a full cardiac cycle in order to demonstrate the application of the surrogate model in larger-scale problems

Merkel Cell Carcinoma: The Past, the Present, and the Future

Since the first description of the Merkel cell carcinoma by Cyril Toker in 1972, the number of studies has significantly increased over the last 4 decades. In this review, we will illustrate the historical background of the Merkel cell carcinoma beginning with the 19th century, the first description of the Merkel cell to the finding of the CK20 as a highly specific diagnostic marker and finally to the recently detected Merkel cell polyomavirus (MCPyV). Moreover, we will highlight the beginning of adjuvant therapeutic regimens with radiotherapy and chemotherapy and discuss the diagnostic work-up including imaging and histology of patients with Merkel cell carcinoma. Another very rapidly growing and interesting field of research is the development of patients' specific and tailored targeted therapy, in particular in patients with distant metastatic disease

Performance Analysis of One Model of Communication and Information System in Military Operation

This paper presents a model of communication and information system in military operations. Here OPNET MODELER simulation package is applied because it is suitable for network modelling, topology and capacity planning. Simulation of different types of IP traffic and monitor their performance to optimise the functionality of network elements, management performance network applications, and as well as in research and development of new network technologies. Application of the method of mass service are determined by the capacity needed for voice transmission on the links in the model and using the OPNET MODELER simulation program are analysed performance modeled communication information system in data transmission. The results of the simulation are presented through target the service settings: workload links communication and information system, e-mail download response time, http page download response time and packet loss in data transfer. The aim of the research has shown that modeled communication information system with defined elements (nodes), the capacity of links (according to the specification of telecommunication devices) and defined traffic can respond to the requirements of command forces in the military operation in terms of telecommunication service. The results of the analysed service target parameters show that modeled communication and information system provides an efficient flow of information and the tra nsfer of voice and IP data for the needs of command and control in military operations

Hemijski sastav ekstrakta semenki bele ribizle

From the seeds of white currant (Ribes rubrum, cv. White Champagne), a new sesquiterpenoid glycoside 1 was isolated, along with two known compounds: dihydrophaseic acid 3'-O-beta-D-glucopyranoside (2), and 3-carboxymethyl-indole-1-N-beta-D-glucopyranoside (3). The structure of the new compound was identified as dihydrophaseic acid 3'-O-beta-gentiobioside, based on extensive NMR and MS spectral studies.Iz semena bele ribizle (Ribes rubrum, cv. bela šampanjska) izolovan je novi seskviterpenski glukozid (1), zajedno sa dva poznata jedinjenja: 3'-O-b-D-glukopiranozidom dihidrofazeinske kiseline (2) i 3-karboksimetilindol-1-N-b-D-glukopiranozidom (3). Na osnovu detaljnih NMR i MS studija, struktura novog jedinjenja je određena kao 3'-O-b-genciobiozid dihidrofazeinske kiseline

Three-dimensional stochastic model of actin–myosin binding in the sarcomere lattice

The effect of molecule tethering in three-dimensional (3-D) space on bimolecular binding kinetics is rarely addressed and only occasionally incorporated into models of cell motility. The simplest system that can quantitatively determine this effect is the 3-D sarcomere lattice of the striated muscle, where tethered myosin in thick filaments can only bind to a relatively small number of available sites on the actin filament, positioned within a limited range of thermal movement of the myosin head. Here we implement spatially explicit actomyosin interactions into the multiscale Monte Carlo platform MUSICO, specifically defining how geometrical constraints on tethered myosins can modulate state transition rates in the actomyosin cycle. The simulations provide the distribution of myosin bound to sites on actin, ensure conservation of the number of interacting myosins and actin monomers, and most importantly, the departure in behavior of tethered myosin molecules from unconstrained myosin interactions with actin. In addition, MUSICO determines the number of cross-bridges in each actomyosin cycle state, the force and number of attached cross-bridges per myosin filament, the range of cross-bridge forces and accounts for energy consumption. At the macroscopic scale, MUSICO simulations show large differences in predicted force-velocity curves and in the response during early force recovery phase after a step change in length comparing to the two simplest mass action kinetic models. The origin of these differences is rooted in the different fluxes of myosin binding and corresponding instantaneous cross-bridge distributions and quantitatively reflects a major flaw of the mathematical description in all mass action kinetic models. Consequently, this new approach shows that accurate recapitulation of experimental data requires significantly different binding rates, number of actomyosin states, and cross-bridge elasticity than typically used in mass action kinetic models to correctly describe the biochemical reactions of tethered molecules and their interaction energetics