Free-ranging eastern chipmunks (Tamias striatus) infected with bot fly (Cuterebra emasculator) larvae have higher resting but lower maximum metabolism

Given the ubiquity and evolutionary importance of parasites, their effect on the energy budget of mammals remains surprisingly unclear. The eastern chipmunk (Tamias striatus (L., 1758)) is a burrowing rodent that is commonly infected by cuterebrid bot fly (Cuterebra emasculator Fitch, 1856) larvae. We measured resting metabolic rate (RMR) and cold-induced [Vo.sub.2]-max (under heliox atmosphere) in 20 free-ranging individuals, of which 4 individuals were infected by one or two larva. We found that RMR was significantly higher in chipmunks infected by bot fly larvae (mean [+ or -] SE = 0.88 [+ or -] 0.05 W) than in uninfected individuals (0.74 [+ or -] 0.02 W). In contrast, V[O.sub.2]-max was significantly lower in chipmunks infected by bot fly larvae (4.96 [+ or -] 0.70 W) than in uninfected individuals (6.37 [+ or -] 0.16 W). Consequently, the aerobic scope (ratio of [Vo.sub.2]-max to RMR) was negatively correlated with the number of bot fly larvae (infected individuals = 5.74 [+ or -] 1.03 W; noninfected individuals = 8.67 [+ or -] 0.26 W). Finally, after accounting for the effects of body mass and bot fly parasitism on RMR and [Vo.sub.2]-max, there was no correlation between the two variables among individuals within our population. In addition to providing the first estimate of [Vo.sub.2]-max in T. striatus, these results offer additional evidence that bot fly parasitism has significant impacts on the metabolic ecology of this host species.

AdaM : adaptive-maximum imputation for neighborhood-based collaborative filtering

In the context of collaborative filtering, the well known data sparsity issue makes two like-minded users have little similarity, and consequently renders the k nearest neighbour rule inapplicable. In this paper, we address the data sparsity problem in the neighbourhood-based CF methods by proposing an Adaptive-Maximum imputation method (AdaM). The basic idea is to identify an imputation area that can maximize the imputation benefit for recommendation purposes, while minimizing the imputation error brought in. To achieve the maximum imputation benefit, the imputation area is determined from both the user and the item perspectives; to minimize the imputation error, there is at least one real rating preserved for each item in the identified imputation area. A theoretical analysis is provided to prove that the proposed imputation method outperforms the conventional neighbourhood-based CF methods through more accurate neighbour identification. Experiment results on benchmark datasets show that the proposed method significantly outperforms the other related state-of-the-art imputation-based methods in terms of accuracy.

Thermal evaluation of a greenhouse in a remote high altitude area of Nepal

Remote communities in the high altitude areas of Nepal suffer both chronic and acute malnutrition. This is due to a shortage of arable land and a harsh climate. For seven months of the year, the harvesting of fresh vegetables is almost impossible. Greenhouse technology, if appropriate for the location and its community, can extend the growing season considerably. Experience in the Ladakh region of India indicates that year-round cropping is possible in greenhouses in cold mountainous areas. A simple 50-m2 greenhouse has been constructed in Simikot, the main town of Humla, northwest Nepal. This paper describes the evaluation of the thermal performance of that greenhouse. Both measurement and simulation were used in the evaluation. Measurements during the winter of 2006-7 indicate that the existing design is capable of producing adequate growing conditions for some vegetable crops, but that improvements are required if crops like tomatoes are to be grown successfully. Options to improve the thermal performance of the greenhouse have been investigated by simulation. Improvements to the building envelope such as wall insulation, double-glazing and using a thermal screen were simulated with a validated TRNSYS model. The impact of the addition of nighttime heat from internal passive solar water collectors was also predicted. The simulations indicate that the passive solar water collectors would raise the average greenhouse air temperature by 2.5°C and the overnight air temperature would increase by 4.0°C. When used in combination, overnight temperatures are predicted to by almost 7°C higher.

Maximum power point tracking of partial shaded photovoltaic array using an evolutionary algorithm: a particle swarm optimization technique

 Partial shading is one of the unavoidable complications in the field of solar power generation. Although the most common approach in increasing a photovoltaic (PV) array’s efficiency has always been to introduce a bypass diode to the said array, this poses another problem in the form of multi-peaks curves whenever the modules are partially shaded. To further complicate matters, most conventional Maximum Power Point Tracking methods develop errors under certain circumstances (for example, they detect the local Maximum Power Point (MPP) instead of the global MPP) and reduce the efficiency of PV systems even further. Presently, much research has been undertaken to improve upon them. This study aims to employ an evolutionary algorithm technique, also known as particle swarm optimization, in MPP detection. VC 2014 Author(s).

Flight altitude of trans-Sahara migrants in autumn: a comparison of radar observations with predictions from meteorological conditions and water and energy balance models

Radar observations on the altitude of bird migration and altitudinal profiles of meteorological conditions over the Sahara desert are presented for the autumn migratory period. Migratory birds fly at an average altitude of 1016 m (a.s.l.) during the day and 571 m during the night. Weather data served to calculate flight range using two models: an energy model (EM) and an energy-and-water model (EWM). The EM assumes that fuel supply limits flight range whereas the EWM assumes that both fuel and water may limit flight range. Flight ranges estimated with the EM were generally longer than those with the EWM. This indicates that trans-Sahara migrants might have more problems balancing their water than their energy budget. However, if we assume fuel stores to consist of 70% instead of 100% fat (the remainder consisting of 9% protein and 21% water), predicted flight ranges of the EM and EWM largely overlap. Increased oxygen extraction, reduced flight costs, reduced exhaled air temperature, reduced cutaneous water loss and increased tolerance to water loss are potential physiological adaptations that would improve the water budget in migrants. Both the EM and EWM predict optimal flight altitudes in agreement with radar observations in autumn. Optimal flight altitudes are differently predicted by the EM and EWM for nocturnal spring migration. During spring, the EWM predicts moderately higher and the EM substantially higher flight altitudes than during autumn. EWM predictions are therefore in better agreement with radar observations on flight altitude of migrants over the Negev desert in spring than EM predictions.

Simulation and hardware implementation of new maximum power point tracking technique for partially shaded PV system using hybrid DEPSO method

In photovoltaic (PV) power generation, partial shading is an unavoidable complication that significantly reduces the efficiency of the overall system. Under this condition, the PV system produces a multiple-peak function in its output power characteristic. Thus, a reliable technique is required to track the global maximum power point (GMPP) within an appropriate time. This study aims to employ a hybrid evolutionary algorithm called the DEPSO technique, a combination of the differential evolutionary (DE) algorithm and particle swarm optimization (PSO), to detect the maximum power point under partial shading conditions. The paper starts with a brief description about the behavior of PV systems under partial shading conditions. Then, the DEPSO technique along with its implementation in maximum power point tracking (MPPT) is explained in detail. Finally, Simulation and experimental results are presented to verify the performance of the proposed technique under different partial shading conditions. Results prove the advantages of the proposed method, such as its reliability, system-independence, and accuracy in tracking the GMPP under partial shading conditions.

A comparative study on procedure and state of the art of conventional maximum power point tracking techniques for photovoltaic system

Due to the increasing world energy demand, renewable energy systems have been significantly applied in the power generation sector. Among the renewable energy options, photovoltaic system is one of the most popular resources which has been experiencing a huge attention during recent decades. The remarkable advantages, such as static and movement free characteristics, low maintenance costs, and longevity are the primary factors for the popularity of solar generation in the late years. Nevertheless, the low PV conversion efficiency in one side and high PV material cost in the other side have made PV generation comparably expensive system. Consequently, a capable maximum power point tracking (MPPT) is all important to elicit the maximum energy from the production of PV systems. Different researches have been conducted to design a fast, simple and robust MPPT technique under uniform conditions. However, due to the series and parallel connection of PV modules and according to the use of bypass diodes, in the structure of PV modules, a conventional techniques are unable to track a true MPP. Recently, several studies have been undertaken to modify these conventional methods and enable them to track the global MPP under rapidly changing environments and partial shading (PS) conditions. This report concentrates on the state of the art of these methods and their evolution to apply under PS conditions. The recent developments and modifications are analyzed through a comparison based on design complexity, cost, speed and the ability to track the MPP under rapid environmental variations and PS conditions.

Implementation of fuzzy logic maximum power point tracking controller for photovoltaic system

In this study, simulation and hardware implementation of Fuzzy Logic (FL) Maximum Power Point Tracking (MPPT) used in photovoltaic system with a direct control method are presented. In this control system, no proportional or integral control loop exists and an adaptive FL controller generates the control signals. The designed and integrated system is a contribution of different aspects which includes simulation, design and programming and experimental setup. The resultant system is capable and satisfactory in terms of fastness and dynamic performance. The results also indicate that the control system works without steady-state error and has the ability of tracking MPPs rapid and accurate which is useful for the sudden changes in the atmospheric condition. MATLAB/Simulink software is utilized for simulation and also programming the TMS320F2812 Digital Signal Processor (DSP). The whole system designed and implemented to hardware was tested successfully on a laboratory PV array. The obtained experimental results show the functionality and feasibility of the proposed controller.

Two maximum entropy-based algorithms for running quantile estimation in nonstationary data streams

The need to estimate a particular quantile of a distribution is an important problem that frequently arises in many computer vision and signal processing applications. For example, our work was motivated by the requirements of many semiautomatic surveillance analytics systems that detect abnormalities in close-circuit television footage using statistical models of low-level motion features. In this paper, we specifically address the problem of estimating the running quantile of a data stream when the memory for storing observations is limited. We make the following several major contributions: 1) we highlight the limitations of approaches previously described in the literature that make them unsuitable for nonstationary streams; 2) we describe a novel principle for the utilization of the available storage space; 3) we introduce two novel algorithms that exploit the proposed principle in different ways; and 4) we present a comprehensive evaluation and analysis of the proposed algorithms and the existing methods in the literature on both synthetic data sets and three large real-world streams acquired in the course of operation of an existing commercial surveillance system. Our findings convincingly demonstrate that both of the proposed methods are highly successful and vastly outperform the existing alternatives. We show that the better of the two algorithms (data-aligned histogram) exhibits far superior performance in comparison with the previously described methods, achieving more than 10 times lower estimate errors on real-world data, even when its available working memory is an order of magnitude smaller.