Crop yield prediction from remotely sensed vegetation indices and primary productivity in arid and semi-arid lands

Global demands for biomass and arable lands are expected to double in the next 35 years. Scarcity of water resources in arid and semi-arid areas poses a serious threat to their agricultural productivity and hence their food security. In this study, we examine whether crop yields can be predicted from remotely sensed vegetation indices and remotely sensed estimates of primary productivity. Spatial relationships between remotely sensed enhanced vegetation index (EVI), net photosynthesis (P_Net), and gross and net primary production (GPP and NPP, respectively) in irrigated semi-arid and arid agro-ecosystems since the beginning of the century are analysed. The conflict-affected country of Syria is selected as the case study. Relationships between EVI and crop yield are investigated in an effort to enhance food production estimates in affected areas outside governmental jurisdictions. Estimates of NPP derived from reported irrigated agriculture crop data in a semi-arid and an arid zone are compared to remotely sensed NPP in a geospatial environment. Results show that winter crop yields are correlated with spring GPP in semi-arid zones of the study area (R² = 0.85). Summer crop yield can be predicted from either cumulative summer EVI (R² = 0.77) or P_Net in most zones. Where fully irrigated fields are surrounded by hyper-arid landscape, summer P_Net was negative in all instances and EVI was inversely correlated with yield. NPP from crops was much higher (290 gC m^?2 year^?1) in those regions than MOD17 NPP (70 gC m^–2), where 1.0 g of carbon is equivalent to 2.2 g of oven-dry organic matter (= 45% carbon by weight). The gap was less in semi-arid zones (2–39% difference). Overall crop-derived NPP for the period 2000–2013 was 322 versus 300 gC m^–2 for that remotely sensed within the cropped zones of the political units. The results of this study are crucial to derive accurate estimates of irrigated agriculture productivity and to study the effect of the latter on net ecosystem carbon storage.     

PASTA: a power-aware solution to scheduling of precedence-constrained tasks on heterogeneous computing resources

Power efficiency is one of the main challenges in large-scale distributed systems such as datacenters, Grids, and Clouds. One can study the scheduling of applications in such large-scale distributed systems by representing applications as a set of precedence-constrained tasks and modeling them by a Directed Acyclic Graph. In this paper we address the problem of scheduling a set of tasks with precedence constraints on a heterogeneous set of Computing Resources (CRs) with the dual objective of minimizing the overall makespan and reducing the aggregate power consumption of CRs. Most of the related works in this area use Dynamic Voltage and Frequency Scaling (DVFS) approach to achieve these objectives. However, DVFS requires special hardware support that may not be available on all processors in large-scale distributed systems. In contrast, we propose a novel two-phase solution called PASTA that does not require any special hardware support. In its first phase, it uses a novel algorithm to select a subset of available CRs for running an application that can balance between lower overall power consumption of CRs and shorter makespan of application task schedules. In its second phase, it uses a low-complexity power-aware algorithm that creates a schedule for running application tasks on the selected CRs. We show that the overall time complexity of PASTA is $O(p.v^{2})$ where $p$ is the number of CRs and $v$ is the number of tasks. By using simulative experiments on real-world task graphs, we show that the makespan of schedules produced by PASTA are approximately 20 % longer than the ones produced by the well-known HEFT algorithm. However, the schedules produced by PASTA consume nearly 60 % less energy than those produced by HEFT. Empirical experiments on a physical test-bed confirm the power efficiency of PASTA in comparison with HEFT too.     

Aging fingerprint characterization of beer using electronic nose

In this work, attempts were made in order to characterize the change of aroma of alcoholic and non alcoholic beers during the aging process by use of a metal oxide semiconductor based electronic nose. The aged beer samples were statistically characterized in several classes. Linear techniques as principal component analysis (PCA) and Linear Discriminant Analaysis (LDA) were performed over the data that revealed non alcoholic beer classes are separated except a partial overlapping between zones corresponding to two specified classes of the aged beers. A clear discrimination was not found among the alcoholic beer classes showing the more stability of such type of beer compared with non alcoholic beer. In this research, to classify the classes, two types of artificial neural networks were used: Probabilistic Neural Networks (PNN) with Radial Basis Functions (RBF) and FeedForward Networks with Backpropagation (BP) learning method. The classification success was found to be 90% and 100% for alcoholic and non alcoholic beers, respectively. Application of PNN showed the classification accuracy of 83% and 100%, respectively for the aged alcoholic and non alcoholic beer classes as well. Finally, this study showed the capability of the electronic nose system for the evaluation of the aroma fingerprint changes in beer during the aging process.     

Compressive sensing based high-resolution passive bistatic radar

Passive bistatic radar (PBR) systems using different communication signals can only offer low-resolution target detection due to their inherent low bandwidth. In this paper, compressive sensing (CS) is applied to multichannel FM and GSM PBR to achieve improved range-Doppler resolutions and avoid some limitations of classical multiband PBR processing. In CS context, block-structured time-domain dictionary which is formed from multichannel signals suffers from coherence when fine range resolution is employed. To overcome such a pitfall, this work first transforms the dictionary to spectral domain where only the most important spectral components are retained. Principle component analysis followed by a whitening method are then applied to this spectrally transformed data in order to reduce the dimensionality of problem, thereby reducing the dictionary size and most importantly fulfilling the required condition of dictionary incoherence for better CS-based recovery. Two different block-structured dictionary formations are tested. The performance of the recovery of spatially close targets, in both FM and GSM PBR setups, are reported.     

Identification of Trend in Reference Evapotranspiration Series with Serial Dependence in Iran

Monitoring the temporal variations of reference evapotranspiration (ET_o) and quantifying any trends offer valuable information for regional hydrology, agricultural water requirements and water resources management. This study aimed to examine the temporal trends in the Penman–Monteith ET_o in the west and southwest of Iran by using the Kendall and Spearman tests after eliminating the influence of significant lag-1 serial correlation from the ET_o time series. The magnitudes and starting years of significant ET_o trends were determined by the Mann-Kendall rank statistic and the Theil–Sen’s estimator, respectively. For the study period of 1966–2005, a significant positive lag-1 serial correlation coefficient was observed at almost all the stations. The existence of the positive serial correlation in the ET_o series increased the possibility of the Kendall and Spearman tests to reject the null hypothesis of no trend while it is true. It was found that the Kendall test was more sensitive than the Spearman test to the existence of the positive serial correlation in the ET_o series. After removing the serial correlation effect with pre-whitening method, only three significant increasing ET_o trends were obtained at Khorram-Abad, Shahrekord and Zanjan stations at the rates of 0.16, 0.06 and 0.06 mm/day per decade, respectively. The significant increasing ET_o trends of Khorram-Abad, Zanjan and Shahrekord stations started in 1997, 1994 and 1998, respectively. The stepwise regression method showed that wind speed was the most dominating variable affecting on the significant changes of ET_o.     

On the location of different titanium sites in Ti–OMS-2 and their catalytic role in oxidation of styrene

Octahedral manganese oxide molecular sieves (OMS-2) modified by impregnation of TiO₂ exhibit a higher catalytic activity for oxidation of styrene with tert-butylhydroperoxide in comparison to titanium-incorporated OMS-2, where the styrene conversions were ca. 70% and 45–50%, respectively. The framework of titanium species has no effect on the enhancement of catalytic activity, while the non-framework of titanium species induces a synergetic effect that enhances the oxidation of styrene with tert-butylhydroperoxide.     

Numerical investigation of flow field configuration and contact resistance for PEM fuel cell performance

A steady-state three-dimensional non-isothermal computational fluid dynamics (CFD) model of a proton exchange membrane fuel cell is presented. Conservation of mass, momentum, species, energy, and charge, as well as electrochemical kinetics are considered. In this model, the effect of interfacial contact resistance is also included. The numerical solution is based on a finite-volume method. In this study the effects of flow channel dimensions on the cell performance are investigated. Simulation results indicate that increasing the channel width will improve the limiting current density. However, it is observed that an optimum shoulder size of the flow channels exists for which the cell performance is the highest. Polarization curves are obtained for different operating conditions which, in general, compare favorably with the corresponding experimental data. Such a CFD model can be used as a tool in the development and optimization of PEM fuel cells.     

Investigation of chitosan‐g‐PEG grafted nanoparticles as a half‐life enhancer carrier for tissue plasminogen activator delivery

Tissue plasminogen activator (tPA) a thrombolytic agent is commonly used for digesting the blood clot. tPA half‐life is low (4–6 min) and its administration needs a prolonged continuous infusion. Improving tPA half‐life could reduce enzyme dosage and enhance patient compliance. Nano‐carries could be used as delivery systems for the protection of enzymes physically, enhancing half‐life and increasing the stability of them. In this study, chitosan (CS) and polyethylene glycol (PEG) were used for the preparation of CS‐g‐PEG/tPA nanoparticles (NPs) via the ion gelation method. Particles’ size and loading capacity were optimised by central composite design. Then, NPs cytotoxicity, release profile, enzyme activity and in vivo half‐life and coagulation time were investigated. The results showed that NPs does not have significant cytotoxicity. Release study revealed that a burst effect happened in the first 5 min and resulted in releasing 30% of tPA. Loading tPA in NPs could decrease 25% of its activity but the half‐life of it increases in comparison to free tPA in vivo. Also, blood coagulation time has significantly affected (p ‐value = 0.041) by encapsulated tPA in comparison to free tPA. So, CS‐g‐PEG/tPA could increase enzyme half‐life during the time and could be used as a non‐toxic candidate delivery system for tPA.Inspec keywords: drug delivery systems, nanofabrication, drugs, nanomedicine, coagulation, biomedical materials, cellular biophysics, enzymes, biochemistry, toxicology, molecular biophysics, biological tissues, blood, nanoparticles, polymersOther keywords: chitosan‐g‐PEG grafted nanoparticles, half‐life enhancer carrier, tissue plasminogen activator delivery, tPA half‐life, prolonged continuous infusion, enzyme dosage, polyethylene glycol, cytotoxicity, enzyme activity, encapsulated tPA, enzyme half‐life, blood coagulation, time 5.0 min     

N ‐acetylcysteine–PLGA nano‐conjugate: effects on cellular toxicity and uptake of gadopentate dimeglumine

Gadolinium as a contrast agent in MRI technique combined with DTPA causes contrast induced nephropathy (CIN) and nephrogenic systemic fibrosis (NSF) which can reduce by usage of antioxidants such as N‐acetyl cysteine by increasing the membrane''s permeability leads to lower cytotoxicity. In this study, N ‐acetyl cysteine‐PLGA Nano‐conjugate was synthesized according to stoichiometric rules of molar ratios andafter assessment by FTIR, NMR spectroscopy and Atomic Force Microscopy (AFM) imaging was combined with Magnevist® (gadopentetate dimeglumine) and its effects on the renal cells were evaluated. MTT [3‐(4,5‐Dimethylthiazol‐2‐yl)‐2,5‐Diphenyltetrazolium Bromide] and cellular uptake assays have indicated relatively significant toxicity of magnevist (P  < 0.05) on three cell lines including HEK293, MCF7 and L929 compared to other synthesized ligands that shown no toxicity. Moreover, systemic evaluation has shown no notable changes of blood urea nitrogen (BUN) and creatinine in kidney of mice. In consequence, antioxidant effect was increased as well as the renal toxicity of the contrast agent reduced at the cell level. As a result, PLGA‐NAC nano‐conjugate can be a promising choice for decreasing the magnevist toxicity for treatment and prevention of CIN and will be able to open a new horizon to research on reduction of toxicity of contrast agents by using nanoparticles.Inspec keywords: blood, toxicology, nanofabrication, cellular biophysics, biomedical materials, nanoparticles, chromatography, cancer, biodegradable materials, biomedical MRI, kidney, pH, nanomedicine, patient treatment, diseases, atomic force microscopy, Fourier transform infrared spectraOther keywords: cellular toxicity, gadopentate dimeglumine, contrast agent, magnetic resonance imaging technique, diethylenetriamine pentaacetate, contrast‐induced nephropathy, nephrogenic systemic fibrosis, stoichiometric rules, molar ratios, dimethyl sulphoxide solution, chromatography techniques, nuclear magnetic resonance spectroscopy, atomic force microscopy imaging, Magnevist®, gadopentetate dimeglumine, renal cells, MTT cytotoxicity, human embryonic kidney‐293, L929 cell lines, in vitro conditions, cellular uptake assays, Magnevist uptake, antioxidant effect, renal toxicity, cell level, PLGA nanocarrier, acetylcysteine nanoconjugate, Magnevist toxicity, N‐acetylcysteine–PLGA nano‐conjugate, N‐acetyl cysteine‐poly‐lactic‐co‐glycolic acid nanoconjugate     

A comparative study between gravel and rubber drainage columns for mitigation of liquefaction hazards

Liquefaction is one of the most destructive natural hazards that cause damage to engineering structures during an earthquake. This study aims to examine the effect of rubber and gravel drainage columns on the reduction of liquefaction potential of saturated sandy soils using a shaking table. Experiments were carried out in various conditions such as construction materials, different arrangements and diameters of drainage columns. Effects of the relative density and the input motion on the base test were investigated as well. The results demonstrate that rubber drainage columns have slightly better performance compared to gravel drainage columns at high relative density and high input acceleration. Soil improvement using gravel drainage columns, which leads to reduction in liquefaction effects at moderate input acceleration and low relative density, is a more effective method than that using rubber drainage columns. By increasing the number and diameter of gravel and rubber drainage columns, deformations due to liquefaction are reduced. The drainage rate of gravel drains is higher than that of rubber drains after shaking. Totally, the outcomes indicate that densification is the most important factor controlling liquefaction.