Transport coefficients and nonextensive statistics

We discuss the basic transport phenomena in gases and plasmas obeying the $q$-nonextensive velocity distribution (power-law). Analytical expressions for the thermal conductivity ($K_q$) and viscosity ($\eta_q$) are derived by solving the Boltzmann equation in the relaxation-time approximation. The available experimental results to the ratio {$K_q$}/$\eta_q$ constrains the $q$-parameter on the interval $0.74 \leq q \leq 1$. In the extensive limiting case, the standard transport coefficients based on the local Gaussian distribution are recovered, and due to a surprising cancellation, the electric conductivity of a neutral plasma is not modified.Comment: 14 pages, 3 figures, REVTEX, submitted to PR

Monitoring Veenterpen : Effectmonitoring van waterberging in herinrichting Matsloot-Roderwolde en Peizer- & Eeldermaden, 2009-2014

In 2012 is een waterbergingsgebied binnen de herinrichting Peize- en Roderwoldermaden in gebruik genomen. De effecten hiervan op de conservering van veenterpen zijn gemeten. Tussen 2009 en 2014 zijn daartoe 15 veenterpen gemonitord op o.a. grondwaterstand en redoxpotentiaal, bodemvocht, bodemtemperatuur op verschillende diepten en zijn vegetatie-opnamen gedaan. Vermoedelijk door hogere grondwaterstanden, geringere -fluctuatie en ander landgebruik zijn de redoxpotentialen gedaald, wat duidt op betere conservering van archeologica in de veenterpen. De veenterpen zijn qua vegetatie wel sterk verruigd, met grotere en diepwortelende soorten. Een vorm van actief graslandbeheer wordt sterk aanbevolen. Verder is aangegeven dat voor een beter inzicht in de veranderde conservering en het effect van de vegetatie-ontwikkeling op de veenterpen het nodig is om in afgeslankte vorm nog enkele jaren door te meten en de vegetatie-ontwikkeling te blijven volgen

Entropy Production in a Persistent Random Walk

We consider a one-dimensional persisent random walk viewed as a deterministic process with a form of time reversal symmetry. Particle reservoirs placed at both ends of the system induce a density current which drives the system out of equilibrium. The phase space distribution is singular in the stationary state and has a cumulative form expressed in terms of generalized Takagi functions. The entropy production rate is computed using the coarse-graining formalism of Gaspard, Gilbert and Dorfman. In the continuum limit, we show that the value of the entropy production rate is independent of the coarse-graining and agrees with the phenomenological entropy production rate of irreversible thermodynamics.Comment: 21 pages, 8 figures, to appear in Physica

Aflibercept in the Treatment of Metastatic Colorectal Cancer

Colorectal cancer is the third most common cancer in the US. In recent decades, an improved understanding of the role of the angiogenesis pathway in colorectal cancer has led to advancements in treatment. Bevacizumab has been shown to improve the progression-free survival and overall survival when combined with cytotoxic chemotherapy in patients with metastatic colorectal cancer, and at present is the only antiangiogenesis agent approved for the treatment of this cancer. Aflibercept is a novel angiogenesis-targeting agent, and has demonstrated efficacy in treating metastatic colorectal cancer in a recent randomized Phase III trial. Here we review the role of angiogenesis in the tumorigenesis of colorectal cancer, strategies for targeting angiogenesis, and the clinical development of aflibercept

Attention mechanisms in the CHREST cognitive architecture

In this paper, we describe the attention mechanisms in CHREST, a computational architecture of human visual expertise. CHREST organises information acquired by direct experience from the world in the form of chunks. These chunks are searched for, and verified, by a unique set of heuristics, comprising the attention mechanism. We explain how the attention mechanism combines bottom-up and top-down heuristics from internal and external sources of information. We describe some experimental evidence demonstrating the correspondence of CHREST’s perceptual mechanisms with those of human subjects. Finally, we discuss how visual attention can play an important role in actions carried out by human experts in domains such as chess

The anti-tumor effect of RANKL inhibition in malignant solid tumors - A systematic review

Diabetes mellitus: pathophysiological changes and therap

Effect of electricity tariffs and cooling technologies on dairy farm electricity consumption, related costs and greenhouse gas emissions

The aim of this study was to provide insight into the variations in dairy farm electricity costs across five electricity tariffs. The effect of four milk cooling scenarios is also simulated to illustrate the effect of technologies on the electricity consumption, related costs and CO2 emissions of a dairy farm. Helping dairy farmers to make informed business decisions when confronted with future options in the sphere of electricity tariffs and energy efficient cooling systems will contribute to optimum farm profitability and will help to improve the profitability and sustainability of the industry. A previously developed model capable of simulating electricity consumption, related costs and CO2 emissions of dairy farms was used to simulate five electricity tariffs (Flat, Day&Night, Time of Use Tariff 1 (TOU1), TOU2 and Real Time Pricing (RTP)) on a dairy farm with 195 milking cows. The Flat tariff consisted on one electricity price for all time periods, the Day&Night tariff consisted of two electricity prices, a high rate from 09:00 to 00:00 h and a low rate thereafter. The TOU tariff structure was similar to that of the Day&Night tariff except that a third peak price band was introduced between 17:00 and 19:00 h. The RTP tariff varied dynamically according to the electricity demand on the national grid. The model used in these simulations is a mechanistic mathematical representation of the electricity consumption that simulates farm equipment under the following headings; milk cooling system, water heating system, milking machine system, lighting systems, water pump systems and the winter housing facilities. Direct expansion, ice bank and pre-cooling milk cooling systems were simulated to determine how dairy farm electricity consumption, related costs and CO2 emissions vary according to the milk cooling system installed on the farm. Annual simulated electricity consumption of the farm was 32,670 kWh when a direct expansion milk cooling system without pre-cooling of milk was included in the model. The annual electricity consumption of the farm on the day & night tariff was €4,571. Adding precooling with ground water to the direct expansion milk cooling system reduced annual electricity consumption by 28% to 23,660 kWh and reduced annual electricity costs by 38% to €2,875. The addition of a pre-cooling system to the direct expansion milk cooling system saved 3,973 kg of CO2. Simulation of an ice bank milk cooling system without pre-cooling resulted in annual simulated electricity consumption of 34,777 kWh. The annual electricity consumption on the day & night tariff was €3,793. Adding pre-cooling with ground water to the ice bank milk cooling system reduced annual electricity consumption by 30% to 24,181 kWh and reduced annual electricity costs by 33% to €2,527. The addition of a pre-cooling system to the ice bank milk cooling system saved 5,044 kg of CO2

A mechanistic model for electricity consumption on dairy farms: Definition, validation, and demonstration

Our objective was to define and demonstrate a mechanistic model that enables dairy farmers to explore the impact of a technical or managerial innovation on electricity consumption, associated CO2 emissions, and electricity costs. We, therefore, (1) defined a model for electricity consumption on dairy farms (MECD) capable of simulating total electricity consumption along with related CO2 emissions and electricity costs on dairy farms on a monthly basis; (2) validated the MECD using empirical data of 1 yr on commercial spring calving, grass-based dairy farms with 45, 88, and 195 milking cows; and (3) demonstrated the functionality of the model by applying 2 electricity tariffs to the electricity consumption data and examining the effect on total dairy farm electricity costs. The MECD was developed using a mechanistic modeling approach and required the key inputs of milk production, cow number, and details relating to the milk-cooling system, milking machine system, water-heating system, lighting systems, water pump systems, and the winter housing facilities as well as details relating to the management of the farm (e.g., season of calving). Model validation showed an overall relative prediction error (RPE) of less than 10% for total electricity consumption. More than 87% of the mean square prediction error of total electricity consumption was accounted for by random variation. The RPE values of the milk-cooling systems, water-heating systems, and milking machine systems were less than 20%. The RPE values for automatic scraper systems, lighting systems, and water pump systems varied from 18 to 113%, indicating a poor prediction for these metrics. However, automatic scrapers, lighting, and water pumps made up only 14% of total electricity consumption across all farms, reducing the overall impact of these poor predictions. Demonstration of the model showed that total farm electricity costs increased by between 29 and 38% by moving from a day and night tariff to a flat tariff