Galaxy formation in the Planck cosmology - II. Star-formation histories and post-processing magnitude reconstruction

We adapt the L-Galaxies semi-analytic model to follow the star-formation histories (SFH) of galaxies -- by which we mean a record of the formation time and metallicities of the stars that are present in each galaxy at a given time. We use these to construct stellar spectra in post-processing, which offers large efficiency savings and allows user-defined spectral bands and dust models to be applied to data stored in the Millennium data repository. We contrast model SFHs from the Millennium Simulation with observed ones from the VESPA algorithm as applied to the SDSS-7 catalogue. The overall agreement is good, with both simulated and SDSS galaxies showing a steeper SFH with increased stellar mass. The SFHs of blue and red galaxies, however, show poor agreement between data and simulations, which may indicate that the termination of star formation is too abrupt in the models. The mean star-formation rate (SFR) of model galaxies is well-defined and is accurately modelled by a double power law at all redshifts: SFR proportional to $1/(x^{-1.39}+x^{1.33})$, where $x=(t_a-t)/3.0\,$Gyr, $t$ is the age of the stars and $t_a$ is the loopback time to the onset of galaxy formation; above a redshift of unity, this is well approximated by a gamma function: SFR proportional to $x^{1.5}e^{-x}$, where $x=(t_a-t)/2.0\,$Gyr. Individual galaxies, however, show a wide dispersion about this mean. When split by mass, the SFR peaks earlier for high-mass galaxies than for lower-mass ones, and we interpret this downsizing as a mass-dependence in the evolution of the quenched fraction: the SFHs of star-forming galaxies show only a weak mass dependence.Comment: Accepted version of the paper, to appear in MNRAS. Compared to the original version, contains more detail on the post-processing of magnitudes, including a table of rms magnitude errors. SFHs available on Millennium database http://gavo.mpa-garching.mpg.de/MyMillennium

Robotic Harvesting of Fruiting Vegetables: A Simulation Approach in V-REP, ROS and MATLAB

In modern agriculture, there is a high demand to move from tedious manual harvesting to a continuously automated operation. This chapter reports on designing a simulation and control platform in V-REP, ROS, and MATLAB for experimenting with sensors and manipulators in robotic harvesting of sweet pepper. The objective was to provide a completely simulated environment for improvement of visual servoing task through easy testing and debugging of control algorithms with zero damage risk to the real robot and to the actual equipment. A simulated workspace, including an exact replica of different robot manipulators, sensing mechanisms, and sweet pepper plant, and fruit system was created in V-REP. Image moment method visual servoing with eye-in-hand configuration was implemented in MATLAB, and was tested on four robotic platforms including Fanuc LR Mate 200iD, NOVABOT, multiple linear actuators, and multiple SCARA arms. Data from simulation experiments were used as inputs of the control algorithm in MATLAB, whose outputs were sent back to the simulated workspace and to the actual robots. ROS was used for exchanging data between the simulated environment and the real workspace via its publish-and-subscribe architecture. Results provided a framework for experimenting with different sensing and acting scenarios, and verified the performance functionality of the simulator

Polymorphism and synergism of angiotensin-converting enzyme (ACE) and plasminogen activator inhibitor-1 (PAI-1) genes in coronary artery disease

Introduction: Among the genetic factors for coronary artery diseases, PAI-1 4G/5G and ACE I/D polymorphisms can be noted. This study was carried out to investigate the association of these two polymorphisms and their synergism in coronary artery disease (CAD) from a sample of the Iranian population. Materials and methods: Sixty-one patients with a history of CAD and 92 healthy controls participated in our study. After DNA extraction from leukocytes, PCR was performed to characterize PAI-1 4G/5G and ACE I/D polymorphisms, using an amplification refractory mutation system technique. Results: In the studied patients, PAI-1 polymorphisms were 24.6, 45.9, and 29.5 for 4G/4G, 4G/5G and 5G/5G, respectively; the values for controls were 20.7, 42.2 and 37.0. The distribution rates of genotypes I/I, I/D and D/D in patients accounted for 29.5, 45.9 and 24.6; in the control group these figures were estimated to be 40.2, 40.2 and 19.6. Conclusion: Single and multivariate analyses showed a significant difference for the conventional risk factors, including hypertension, diabetes, hyperlipidemia, smoking and family history, for CAD between patients and controls (p value 0.001). However, no significant correlation was demonstrated considering ACE and PAI-1 polymorphisms either in association with 4G/4G or D/D genotypes or a combination of them in the Iranian population in the current study. © 2015 The Author(s)

Fundamental Research on Unmanned Aerial Vehicles to Support Precision Agriculture in Oil Palm Plantations

Unmanned aerial vehicles carrying multimodal sensors for precision agriculture (PA) applications face adaptation challenges to satisfy reliability, accuracy, and timeliness. Unlike ground platforms, UAV/drones are subjected to additional considerations such as payload, flight time, stabilization, autonomous missions, and external disturbances. For instance, in oil palm plantations (OPP), accruing high resolution images to generate multidimensional maps necessitates lower altitude mission flights with greater stability. This chapter addresses various UAV-based smart farming and PA solutions for OPP including health assessment and disease detection, pest monitoring, yield estimation, creation of virtual plantations, and dynamic Web-mapping. Stabilization of UAVs was discussed as one of the key factors for acquiring high quality aerial images. For this purpose, a case study was presented on stabilizing a fixed-wing Osprey drone crop surveillance that can be adapted as a remote sensing research platform. The objective was to design three controllers (including PID, LQR with full state feedback, and LQR plus observer) to improve the automatic flight mission. Dynamic equations were decoupled into lateral and longitudinal directions, where the longitudinal dynamics were modeled as a fourth order two-inputs-two-outputs system. State variables were defined as velocity, angle of attack, pitch rate, and pitch angle, all assumed to be available to the controller. A special case was considered in which only velocity and pitch rate were measurable. The control objective was to stabilize the system for a velocity step input of 10m/s. The performance of noise effects, model error, and complementary sensitivity was analyzed

Development of a Field Robot Platform for Mechanical Weed Control in Greenhouse Cultivation of Cucumber

A prototype robot that moves on a monorail along the greenhouse for weed elimination between cucumber plants was designed and developed. The robot benefits from three arrays of ultrasonic sensors for weed detection and a PIC18 F4550-E/P microcontroller board for processing. The feedback from the sensors activates a robotic arm, which moves inside the rows of the cucumber plants for cutting the weeds using rotating blades. Several experiments were carried out inside a greenhouse to find the best combination of arm motor (AM) speed, blade rotation (BR) speed, and blade design. We assigned three BR speeds of 3500, 2500, and 1500 rpm, and two AM speed of 10 and 30 rpm to three blade designs of S-shape, triangular shape, and circular shape. Results indicated that different types of blades, different BR speed, and different AM speed had significant effects (P < 0.05) on the percentage of weeds cut (PWC); however, no significant interaction effects were observed. The comparison between the interaction effect of the factors (three blade designs, three BR speeds, and two AM speeds) showed that maximum mean PWC was equal to 78.2% with standard deviation of 3.9% and was achieved with the S-shape blade when the BR speed was 3500 rpm, and the AM speed was 10 rpm. Using this setting, the maximum PWC that the robot achieved in a random experiment was 95%. The lowest mean PWC was observed with the triangular-shaped blade (mean of 50.39% and SD = 1.86), which resulted from BR speed of 1500 rpm and AM speed of 30 rpm. This study can contribute to the commercialization of a reliable and affordable robot for automated weed control in greenhouse cultivation of cucumber

Optimization of an Active Electrokinetic Micromixer Based on the Number and Arrangement of Microelectrodes

This paper reports enhancement of mixing process via electroosmotic phenomenon using a microelectrode system, which is structured by aligning a number of electrodes placed on the walls of a mixing chamber integrated within a T-Shape micromixer. A number of electrodes are dispositioned on the inner and outer loops of the annular mixing chamber, and different design patterns based on a variety of arrangements for these electrodes are investigated using numerical methods. The electric potentials on the microelectrodes are time-dependent, and this is found to be a key element for chaotic mixing. Also, it is deduced that due to the impact of the applied AC electric field and the induced surface charge on the fluid particles, a number of vortices are generated in the aqueous solution. These vortices significantly enhance the mixing of the species in the mixing chamber. In order to find an optimum pattern based on electrode dispositioning and the number of electrodes, effects of the geometric configuration of the microelectrodes are analyzed and the mixing effects for different design patterns are investigated via comparing the associated flow structure, concentration transport mechanism, and the mixing performance. Analyzing different designs, an optimum pattern based on the electrode arrangement and the number of electrodes is found to be the case for which the electrodes are placed on the inner and outer loops of the mixing chamber in a cross-like pattern

Efficient Ground Surface Displacement Monitoring Using Sentinel-1 Data: Integrating Distributed Scatterers (DS) Identified Using Two-Sample t-Test with Persistent Scatterers (PS)

Combining persistent scatterers (PS) and distributed scatterers (DS) is important for effective displacement monitoring using time-series of SAR data. However, for large stacks of synthetic aperture radar (SAR) data, the DS analysis using existing algorithms becomes a time-consuming process. Moreover, the whole procedure of DS selection should be repeated as soon as a new SAR acquisition is made, which is challenging considering the short repeat-observation of missions such as Sentinel-1. SqueeSAR is an approach for extracting signals from DS, which first applies a spatiotemporal filter on images and optimizes DS, then incorporates information from both optimized DS and PS points into interferometric SAR (InSAR) time-series analysis. In this study, we followed SqueeSAR and implemented a new approach for DS analysis using two-sample t-test to efficiently identify neighboring pixels with similar behaviour. We evaluated the performance of our approach on 50 Sentinel-1 images acquired over Trondheim in Norway between January 2015 and December 2016. A cross check on the number of the identified neighboring pixels using the Kolmogorov–Smirnov (KS) test, which is employed in the SqueeSAR approach, and the t-test shows that their results are strongly correlated. However, in comparison to KS-test, the t-test is less computationally intensive (98% faster). Moreover, the results obtained by applying the tests under different SAR stack sizes from 40 to 10 show that the t-test is less sensitive to the number of image

Simulating Cotton Growth and Productivity Using AquaCrop Model under Deficit Irrigation in a Semi-Arid Climate

AquaCrop is a water-driven model that simulates the effect of environment and management on crop production under deficit irrigation. The model was calibrated and validated using three databases and four irrigation treatments (i.e., 100%ET, 80%ET, 70%ET, and 50%ET). Model performance was evaluated by simulating canopy cover (CC), biomass accumulation, and water productivity (WP). Statistics of root mean square error (RMSE) and Willmott’s index of agreement (d) showed that model predictions are suitable for non-stressed and moderate stressed conditions. The results showed that the simulated biomass and yield were consistent with the measured values with a coefficient of determination (R2) of 0.976 and 0.950, respectively. RMSE and d-index values for canopy cover (CC) were 2.67% to 4.47% and 0.991% to 0.998% and for biomass were 0.088 to 0.666 ton/ha and 0.991 to 0.999 ton/ha, respectively. Prediction of simulated and measured biomass and final yield was acceptable with deviation ˂10%. The overall value of R2 for WP in terms of yield was 0.943. Treatment with 80% ET consumed 20% less water than the treatment with 100%ET and resulted in high WP in terms of yield (0.6 kg/m3) and biomass (1.74 kg/m3), respectively. The deviations were in the range of −2% to 11% in yield and −2% to 4% in biomass. It was concluded that AquaCrop is a useful tool in predicting the productivity of cotton under different irrigation scenarios

Varicella Zoster antibodies among health care workers in a university hospital, Teheran, Iran

Objectives: This study was designed to evaluate the immune status of health care workers against varicella zoster in a university hospital in Teheran, Iran, and to compare the history of chickenpox infection with the presence of varicella antibodies in this population. Methods: Serologic testing for varicella was performed for 405 health care workers with different job categories and at different age. The enzyme immunoassay was used for determining IgG antibodies against varicella zoster virus Results: A total of 405 health care workers, aged 19-50 years (median: 29 years), were examined. Of these, 289 (71.4) were found to be seropositive. No statistically significant differences were observed between gender, age, or occupation, and seropositivity (p = 0.09, 0.75, 0.54. respectively). Statistical analysis revealed that the correlation between chickenpox history and seropositivity showed a 62.3 sensitivity, 72.4 specificity, 84.9 positive predictive value, and 43.5 negative predictive value. Conclusions: Serologic screening of health care workers is essential to determine their immunity to varicella, regardless of the age, occupation and history of infection. This population is recommended to be considered a target group for future immunization programs in Iran

Temperature and Humidity Control for the Next Generation Greenhouses: Overview of Desiccant and Evaporative Cooling Systems

Temperature and humidity control are crucial in next generation greenhouses. Plants require optimum temperature/humidity and vapor pressure deficit conditions inside the greenhouse for optimum yield. In this regard, an air-conditioning system could provide the required conditions in harsh climatic regions. In this study, the authors have summarized their published work on different desiccant and evaporative cooling options for greenhouse air-conditioning. The direct, indirect, and Maisotsenko cycle evaporative cooling systems, and multi-stage evaporative cooling systems have been summarized in this study. Different desiccant materials i.e., silica-gels, activated carbons (powder and fiber), polymer sorbents, and metal organic frameworks have also been summarized in this study along with different desiccant air-conditioning options. However, different high-performance zeolites and molecular sieves are extensively studied in literature. The authors conclude that solar operated desiccant based evaporative cooling systems could be an alternate option for next generation greenhouse air-conditioning