Discrimination of vegetation types in alpine sites with ALOS PALSAR-, RADARSAT-2-, and lidar-derived information

Natural vegetation monitoring in the alpine mountain range is a priority in the European Union in view of climate change effects. Many potential monitoring tools, based on advanced remote sensing sensors, are still not fully integrated in operational activities, such as those exploiting very high-resolution synthetic aperture radar (SAR) or light detection and ranging (lidar) data. Their testing is important for possible incorporation in routine monitoring and to increase the quantity and quality of environmental information. In this study the potential of ALOS PALSAR and RADARSAT-2 SAR scenes' synergic use for discrimination of different vegetation types was tested in an alpine heterogeneous and fragmented landscape. The integration of a lidar-based canopy height model (CHM) with SAR data was also tested. A SPOT image was used as a benchmark to evaluate the results obtained with different input data. Discrimination of vegetation types was performed with maximum likelihood classification and neural networks. Six tested data combinations obtained more than 85% overall accuracy, and the most complex input which integrates the two SARs with lidar CHM outperformed the result based on SPOT. Neural network algorithms provided the best results. This study highlights the advantages of integrating SAR sensors with lidar CHM for vegetation monitoring in a changing environment.     

Minimization of exceptional elements and voids in the cell formation problem using a multi-objective genetic algorithm

Cell formation problem is the main issue in designing cellular manufacturing systems. The most important objective in the cell formation problem is to minimize the number of exceptional elements which helps to reduce the number of intercellular movements. Another important but rarely used objective function is to minimize the number of voids inside of the machine cells. This objective function is considered in order to increase the utilization of the machines. We present a bi-objective mathematical model to simultaneously minimize the number of exceptional elements and the number of voids in the part machine incidence matrix. An ε-constraint method is then applied to solve the model and to generate the efficient solutions. Because of the NP-hardness of the model, the optimal algorithms can not be used in large-scale problems and therefore, we have also developed a bi-objective genetic algorithm. Some numerical examples are considered to illustrate the performance of the model and the effectiveness of the solution algorithms. The results demonstrate that in comparison with the ε-constraint method, the proposed genetic algorithm can obtain efficient solution in a reasonable run time.     

Development of a disposable sensor for electrocatalytic detection of guanine and ss-DNA using a modified sol-gel screen-printed carbon electrode

The electrocatalytic oxidation of guanine and DNA is demonstrated on a sol-gel coated carbon screen printed electrode modified with {MeReO(edt)}₂ using cyclic and differential pulse voltammetric techniques. An oxidation peak at 370 mV was found, but no corresponding reduction peaks could be detected in the negative scan, which indicates that the oxidation of guanine is completely irreversible process. The oxidation peak potentials are shifted to more negative values with increasing pH. The utility of applying the sensor for determination of guanine and ss-DNA were investigated. The linear ranges were 0.19-10.8 and 0.45-7.8 μg ml⁻¹ for guanine and DNA, respectively. Detection limits of 0.1 and 0.32 μg ml⁻¹ were obtained for guanine and ss-DNA, respectively.     

Choosing Rhetorical Structures To Plan Instructional Texts

This paper discusses a fundamental problem in natural language generation: how to organize the content of a text in a coherent and natural way. In this research, we set out to determine the semantic content and the rhetorical structure of texts and to develop heuristics to perform this process automatically within a text generation framework. The study was performed on a specific language and textual genre: French instructional texts. From a corpus analysis of these texts, we determined nine senses typically communicated in instructional texts and seven rhetorical relations used to present these senses. From this analysis, we then developed a set of presentation heuristics that determine how the senses to be communicated should be organized rhetorically in order to create a coherent and natural text. The heuristics are based on five types of constraints: conceptual, semantic, rhetorical, pragmatic, and intentional constraints. To verify the heuristics, we developed the spin natural language generation system, which performs all steps of text generation but focuses on the determination of the content and the rhetorical structure of the text.     

An investigation into the effects of lime on compressive and shear strength characteristics of fiber-reinforced clays

To meet the ever-increasing construction demands around the world during recent years,reinforcement and stabilization methods have been widely used by geotechnical engineers to improve the performances and behavior of fine-grained soils.Although lime stabilization increases the compressive strength of soils,it reduces the soil ductility at the same time.Recent research shows that random fiber inclusion modifies the brittleness of soils.In the current research,the effects of lime and polypropylene(PP) fiber additions on such characteristics as compressive and shear strengths,failure strain,secant modulus of elasticity(E_(50)) and shear strength parameters of mixtures were investigated.Kaolinite was treated with 1%,3% and 5% lime by dry weight of soil and reinforced with 0.1% monovalent PP fibers with the length of 6 mm.Samples were prepared at optimum conditions and cured at 35℃ for 1 d,7 d and28 d at 90% relative humidity and subsequently subjected to uniaxial and triaxial compression tests(UCT and TCT) under cell pressures of 25 kPa,50 kPa and 100 kPa.Results showed that inclusion of random PP fibers to clay-lime mixtures increases both compressive and shear strengths as well as the ductility.Lime content and curing period were found to be the most influential factors.Scanning electron microscopy(SEM) analysis showed that lime addition and the formation of cementitious compounds bind soil particles and increase soil/fiber interactions at interface,leading to enhanced shear strength.The more ductile the stabilized and reinforced composition,the less the cracks in roads and waste landfill covers.     

Inhibitors of Polyhydroxyalkanoate (PHA) Synthases: Synthesis,Molecular Docking,and Implications

Polyhydroxyalkanoate (PHA) synthases (PhaCs) catalyze the formation of biodegradable PHAs that are considered to be ideal alternatives to non‐biodegradable synthetic plastics. However, study of PhaCs has been challenging because the rate of PHA chain elongation is much faster than that of initiation. This difficulty, along with lack of a crystal structure, has become the main hurdle to understanding and engineering PhaCs for economical PHA production. Here we report the synthesis of two carbadethia CoA analogues—sT‐CH₂‐CoA ( 26 a ) and sTet‐CH₂‐CoA ( 26 b )—as well as sT‐aldehyde (saturated trimer aldehyde, 29 ), as new PhaC inhibitors. Study of these analogues with PhaEC_Av revealed that 26 a / b and 29 are competitive and mixed inhibitors, respectively. Both the CoA moiety and extension of PHA chain will increase binding affinity; this is consistent with our docking study. Estimation of the K_ic values of 26 a and 26 b predicts that a CoA analogue incorporating an octameric hydroxybutanoate (HB) chain might facilitate the formation of a kinetically well‐behaved synthase.     

Development and Integration of Sub-hourly Rainfall–Runoff Modeling Capability Within a Watershed Model

Increasing urbanization changes runoff patterns to be flashy and instantaneous with decreased base flow. A model with the ability to simulate sub-daily rainfall–runoff processes and continuous simulation capability is required to realistically capture the long-term flow and water quality trends in watersheds that are experiencing urbanization. Soil and Water Assessment Tool (SWAT) has been widely used in hydrologic and nonpoint sources modeling. However, its subdaily modeling capability is limited to hourly flow simulation. This paper presents the development and testing of a sub-hourly rainfall–runoff model in SWAT. SWAT algorithms for infiltration, surface runoff, flow routing, impoundments, and lagging of surface runoff have been modified to allow flow simulations with a sub-hourly time interval as small as one minute. Evapotranspiration, soil water contents, base flow, and lateral flow are estimated on a daily basis and distributed equally for each time step. The sub-hourly routines were tested on a 1.9 km² watershed (70% undeveloped) near Lost Creek in Austin Texas USA. Sensitivity analysis shows that channel flow parameters are more sensitive in sub-hourly simulations (Δt = 15 min) while base flow parameters are more important in daily simulations (Δt = 1 day). A case study shows that the sub-hourly SWAT model reasonably reproduces stream flow hydrograph under multiple storm events. Calibrated stream flow for 1 year period with 15 min simulation (R ² = 0.93) shows better performance compared to daily simulation for the same period (R ² = 0.72). A statistical analysis shows that the improvement in the model performance with sub-hourly time interval is mostly due to the improvement in predicting high flows. The sub-hourly version of SWAT is a promising tool for hydrology and non-point source pollution assessment studies, although more development on water quality modeling is still needed.     

B4C reinforced NiTi-based composites: Microstructure and wear performance

In this study, NiTi–x wt.% B₄C (x = 0, 2, and 4) composites were consolidated with spark plasma sintering method, and the effects of boron carbide reinforcement addition on the microstructure and wear behavior of samples were investigated. Identification of the constituent phases of samples by the X-ray diffraction method plus Rietveld analysis revealed that the stability of the martensite phase increased in the composite samples because of mismatch stresses between the NiTi matrix phase and the reinforcing particles, which increases the density of the dislocations and facilitates the diffusion process that subsequently leads to the formation of stable intermetallics. The results of hardness test indicated that the hardness value increased from 3.67 GPa for pure NiTi to 10.99 GPa for NiTi–4 wt.% B₄C. Results of wear test revealed that boron carbide reinforced composite specimens had higher wear resistance, whereas wear rate of NiTi sample was 3.6 × 10⁻³ mm³/N m, and it reached to .21 × 10⁻³ mm³/N m for NiTi–4 wt.% B₄C. Investigation of microstructure by scanning electron microscopy images and EDS analysis revealed that the wear mechanism in NiTi samples was abrasive and the addition of B₄C to NiTi changed the wear mechanisms from abrasive to a combination of oxidation, adhesive, and delamination mechanisms.