Global estimates of evapotranspiration and gross primary production based on MODIS and global meteorology data

The simulation of gross primary production (GPP) at various spatial and temporal scales remains a major challenge for quantifying the global carbon cycle. We developed a light use efficiency model, called EC-LUE, driven by only four variables: normalized difference vegetation index (NDVI), photosynthetically active radiation (PAR), air temperature, and the Bowen ratio of sensible to latent heat flux. The EC-LUE model may have the most potential to adequately address the spatial and temporal dynamics of GPP because its parameters (i.e., the potential light use efficiency and optimal plant growth temperature) are invariant across the various land cover types. However, the application of the previous EC-LUE model was hampered by poor prediction of Bowen ratio at the large spatial scale. In this study, we substituted the Bowen ratio with the ratio of evapotranspiration (ET) to net radiation, and revised the RS-PM (Remote Sensing-Penman Monteith) model for quantifying ET. Fifty-four eddy covariance towers, including various ecosystem types, were selected to calibrate and validate the revised RS-PM and EC-LUE models. The revised RS-PM model explained 82% and 68% of the observed variations of ET for all the calibration and validation sites, respectively. Using estimated ET as input, the EC-LUE model performed well in calibration and validation sites, explaining 75% and 61% of the observed GPP variation for calibration and validation sites respectively.Global patterns of ET and GPP at a spatial resolution of 0.5° latitude by 0.6° longitude during the years 2000-2003 were determined using the global MERRA dataset (Modern Era Retrospective-Analysis for Research and Applications) and MODIS (Moderate Resolution Imaging Spectroradiometer). The global estimates of ET and GPP agreed well with the other global models from the literature, with the highest ET and GPP over tropical forests and the lowest values in dry and high latitude areas. However, comparisons with observed GPP at eddy flux towers showed significant underestimation of ET and GPP due to lower net radiation of MERRA dataset. Applying a procedure to correct the systematic errors of global meteorological data would improve global estimates of GPP and ET. The revised RS-PM and EC-LUE models will provide the alternative approaches making it possible to map ET and GPP over large areas because (1) the model parameters are invariant across various land cover types and (2) all driving forces of the models may be derived from remote sensing data or existing climate observation networks.     

Deadlock free routing algorithms for irregular mesh topology NoC systems with rectangular regions

The simplicity of regular mesh topology Network on Chip (NoC) architecture leads to reductions in design time and manufacturing cost. A weakness of the regular shaped architecture is its inability to efficiently support cores of different sizes. A proposed way in literature to deal with this is to utilize the region concept, which helps to accommodate cores larger than the tile size in mesh topology NoC architectures. Region concept offers many new opportunities for NoC design, as well as provides new design issues and challenges. One of the most important among these is the design of an efficient deadlock free routing algorithm. Available adaptive routing algorithms developed for regular mesh topology cannot ensure freedom from deadlocks. In this paper, we list and discuss many new design issues which need to be handled for designing NoC systems incorporating cores larger than the tile size. We also present and compare two deadlock free routing algorithms for mesh topology NoC with regions. The idea of the first algorithm is borrowed from the area of fault tolerant networks, where a network topology is rendered irregular due to faults in routers or links, and is adapted for the new context. We compare this with an algorithm designed using a methodology for design of application specific routing algorithms for communication networks. The application specific routing algorithm tries to maximize adaptivity by using static and dynamic communication requirements of the application. Our study shows that the application specific routing algorithm not only provides much higher adaptivity, but also superior performance as compared to the other algorithm in all traffic cases. But this higher performance for the second algorithm comes at a higher area cost for implementing network routers.     

Passivation of pyrite due to surface treatment

Two samples of naturally occurring pyrite were treated with acetyl acetone, silanes, humic acids, lignin-NaOH mixture, and oxalic acid. The corrosion rate of pyrite was observed to decrease significantly due to the surface treatment by the chemicals used in this study. Surface characterization methods indicate that phenyl triacetoxy silane forms a passive coating a few Angstroms thick on the pyrite, thus preventing its dissolution in 1M H₂SO₄.     

Soft computing-based approaches to predict energy consumption and stability margin of six-legged robots moving on gradient terrains

Soft computing-based approaches have been developed to predict specific energy consumption and stability margin of a six-legged robot ascending and descending some gradient terrains. Three different neuro-fuzzy and one neural network-based approaches have been developed. The performances of these approaches are compared among themselves, through computer simulations. Genetic algorithm-tuned multiple adaptive neuro-fuzzy inference system is found to perform better than other three approaches for predicting both the outputs. This could be due to a more exhaustive search carried out by the genetic algorithm in comparison with back-propagation algorithm and the use of two separate adaptive neuro-fuzzy inference systems for two different outputs. A designer may use the developed soft computing-based approaches in order to predict specific energy consumption and stability margin of the robot for a set of input parameters, beforehand.     

Effects of turning gait parameters on energy consumption and stability of a six-legged walking robot

Minimization of energy consumption plays a key role in the locomotion of a multi-legged robot used for various purposes. Turning gaits are the most general and important factors for omni-directional walking of a six-legged robot. This paper presents an analysis on energy consumption of a six-legged robot during its turning motion over a flat terrain. An energy consumption model is developed for statically stable wave gaits in order to minimize dissipating energy for optimal feet forces distributions. The effects of gait parameters, namely angular velocity, angular stroke and duty factors are studied on energy consumption, as the six-legged robot walks along a circular path of constant radius with wave gait. The variations of average power consumption and energy consumption per unit weight per unit traveled length with the angular velocity and angular stroke are compared for the turning gaits of a robot with four different duty factors. Computer simulations show that wave gait with a low duty factor is more energy-efficient compared to that with a high duty factor at the highest possible angular velocity. A stability analysis based on normalized energy stability margin is performed for turning motion of the robot with four duty factors for different angular strokes.     

A study of external mass transfer effect on biodegradation of phenol using low‐density polyethylene immobilized Bacillus flexus GS1 IIT (BHU) in a packed bed bioreactor

The impact of external mass transport on the biodegradation rate of phenol in a packed bed bioreactor (PBBR) was studied. A potential bacterial species, Bacillus flexus GS1 IIT (BHU), was isolated from the petroleum‐contaminated soil. Low‐density polyethylene (LDPE) immobilized with the B. flexus GS1 IIT (BHU) was used as packing material in the PBBR. The PBBR was operated by varying the inlet feed flow rate from 4 to 10 mL/min, and the corresponding degradation rate coefficients were found to be in the range of 0.119–0.157 L/g h. In addition, the highest removal rate of phenol was obtained to be 1.305 mg/g h at an inlet feed rate of 10 mL/min. The external mass transfer was studied using the model . A new empirical correlation for the biodegradation of phenol in the PBBR was developed after the evaluation at various values of K and n.     

A simulation as a service cloud middleware

Many seemingly simple questions that individual users face in their daily lives may actually require substantial number of computing resources to identify the right answers. For example, a user may want to determine the right thermostat settings for different rooms of a house based on a tolerance range such that the energy consumption and costs can be maximally reduced while still offering comfortable temperatures in the house. Such answers can be determined through simulations. However, some simulation models as in this example are stochastic, which require the execution of a large number of simulation tasks and aggregation of results to ascertain if the outcomes lie within specified confidence intervals. Some other simulation models, such as the study of traffic conditions using simulations may need multiple instances to be executed for a number of different parameters. Cloud computing has opened up new avenues for individuals and organizations with limited resources to obtain answers to problems that hitherto required expensive and computationally-intensive resources. This paper presents SIMaaS, which is a cloud-based Simulation-as-a-Service to address these challenges. We demonstrate how lightweight solutions using Linux containers (e.g., Docker) are better suited to support such services instead of heavyweight hypervisor-based solutions, which are shown to incur substantial overhead in provisioning virtual machines on-demand. Empirical results validating our claims are presented in the context of two case studies.     

Modelling and kinetic aspects of a BTEX contaminated air-treating biofilter

In this study, the overall performance of a biofilter was evaluated in terms of its elimination capacity by using 3-D mesh techniques. The overall results indicate that the agreement between experimental data and model predictions is excellent for benzene, toluene, ethylbenzene and o-xylene (BTEX). In this study, the maximum removal rate (r _max) values for BTEX were 0.0117, 0.0126, 0.0081 and 0.0146 g m^–3 h^–1, and the half-saturation constant (K_S ) values were calculated to be 0.269, 0.297, 0.156 and 0.394 g m^–3, respectively. For this system, the coefficients of determination (r ²) of BTEX compounds were greater than 0.97. The BTEX concentration profiles along the depth were also determined using a convection–diffusion reactor (CDR) model. The sums of squares of the errors (SSEs) of BTEX were 0.0078, 0.0059, 0.0129 and 0.0269, respectively, with r ² values greater than 0.99 for all four compounds at low concentrations.     

Novel-stratified low reflectivity anti-reflective coatings derived from self-assembly of high refractive index nanoparticles

We describe new anti-reflective multilayer optical coatings formed from a single liquid coating solution in a single coating step. The nanoparticles in these coatings self-organize as the liquid coating dries on the substrate. The self-assembly of the nanoparticles results in the formation of a two-layer dielectric stack composed of alternating high and low refractive index layers. For the first time, using this process, an ultra-low reflectivity film can be inexpensively and simply formed using high refractive index titanium oxide nanoparticles and a low refractive index fluoropolymer. These films can be made scratch or abrasion resistant by the inclusion of silane coupling agents and low refractive index nanoparticles.