Optimal Cutting Problem

One of the tasks of the Construction office of company STOBET Ltd is to create large sheets of paper containing a lot of objects describing a building construction as tables, charts, drawings, etc. For this reason it is necessary to arrange the small patterns in a given long sheet of paper with a minimum wastage. Another task of the company is to provide a way of cutting a stock material, e.g. given standard steel rods, into different number of smaller sized details in a way that minimizes the wasted material

Herb Stem Cutter -Design and Research

Abstract IVANOV, D., G. KOSTADINOV, T. MITOVA and I. DIMITROV, 2006. Herb stem cutter -design and research. Bulg. J. Agric. Sci., The article presents the results of investigations on a herb stem cutting machine. Investigations were performed as a series of controlled single-factor experiments. The basic target functions of the study were as follows: drive's absorbed power of the machine (kW); specific energy consumption (kWh/t) and average cutting length (mm). The levels of controlled trial factors were as follows: machine load capacity with herb stem mass: Q = 0.5; 1 and 1.5 kg/s and feeding velocity of stem mass to the cutting drum: V = 2.0; 2.4 and 2.8 m/s. Here are the factors, maintained at stable levels: cutting drum peripheral velocity -25 m/s at rotation frequency of 1176 min -1 ; cutting drum working width -Β=0.558 mm; cutting drum diameter D=0.406 m; number of blades z=6; blade thickness b=10 mm; blade sharpening angle β=34°; inclination of blades' edges to the counteredge α=15°; front cutting angle ϕ=50°; gap between blade and counterblade edges ∆=0.5 mm; sharpening angle of the counterblade β 1 =90° and sharpness of counterblade cutting edge δ=0.2 mm. The correlation between the variation of drive's absorbed power for startup of the cutting drum, specific energy consumption and average cutting length, on the one hand, and the variation of controlled factors, on the other, was established. The respective adequate regression equations were simulated, describing the herb stem cutting processes with specific accuracy

Contrasting ENSO Types With Satellite‐Derived Ocean Phytoplankton Biomass in the Tropical Pacific

Observed variations in the tropical phytoplankton community structure and biogeochemical processes have been linked to the El Niño Southern Oscillation, a driver of large‐scale natural climate variability on interannual timescales. Satellite bio‐optical algorithms have allowed us to derive complex biological parameters from the surface ocean via remote sensing, providing a scientific platform to investigate biological relationships with climate indices. Studies have focused in‐depth on contrasting types of the ENSO types with various physical parameters with only a few recent studies focusing on satellite‐observed chlorophyll‐a, with however none focusing on phytoplankton biomass itself. Here we review the types of ENSO and its effect on backscattering‐based biomass using different statistical techniques, over the 1997‐2007 period. We also contrast the responses of phytoplankton biomass with those of chlorophyll‐a and their physical drivers in various types of ENSO. Signatures of various ENSO types are observed in the physical and biological fields

Inter-comparison of phytoplankton functional type phenology metrics derived from ocean color algorithms and Earth System Models

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this recordOcean color remote sensing of chlorophyll concentration has revolutionized our understanding of the biology of the oceans. However, a comprehensive understanding of the structure and function of oceanic ecosystems requires the characterization of the spatio-temporal variability of various phytoplankton functional types (PFTs), which have differing biogeochemical roles. Thus, recent bio-optical algorithm developments have focused on retrieval of various PFTs. It is important to validate and inter-compare the existing PFT algorithms; however direct comparison of retrieved variables is non-trivial because in those algorithms PFTs are defined differently. Thus, it is more plausible and potentially more informative to focus on emergent properties of PFTs, such as phenology. Furthermore, ocean color satellite PFT data sets can play a pivotal role in informing and/or validating the biogeochemical routines of Earth System Models. Here, the phenological characteristics of 10 PFT satellite algorithms and 7 latest-generation climate models from the Coupled Model Inter-comparison Project (CMIP5) are inter-compared as part of the International Satellite PFT Algorithm Inter-comparison Project. The comparison is based on monthly satellite data (mostly SeaWiFS) for the 2003–2007 period. The phenological analysis is based on the fraction of microplankton or a similar variable for the satellite algorithms and on the carbon biomass due to diatoms for the climate models. The seasonal cycle is estimated on a per-pixel basis as a sum of sinusoidal harmonics, derived from the Discrete Fourier Transform of the variable time series. Peak analysis is then applied to the estimated seasonal signal and the following phenological parameters are quantified for each satellite algorithm and climate model: seasonal amplitude, percent seasonal variance, month of maximum, and bloom duration. Secondary/double blooms occur in many areas and are also quantified. The algorithms and the models are quantitatively compared based on these emergent phenological parameters. Results indicate that while algorithms agree to a first order on a global scale, large differences among them exist; differences are analyzed in detail for two Longhurst regions in the North Atlantic: North Atlantic Drift Region (NADR) and North Atlantic Subtropical Gyre West (NASW). Seasonal cycles explain the most variance in zonal bands in the seasonally-stratified subtropics at about 30° latitude in the satellite PFT data. The CMIP5 models do not reproduce this pattern, exhibiting higher seasonality in mid and high-latitudes and generally much more spatially homogeneous patterns in phenological indices compared to satellite data. Satellite data indicate a complex structure of double blooms in the Equatorial region and mid-latitudes, and single blooms on the poleward edges of the subtropical gyres. In contrast, the CMIP5 models show single annual blooms over most of the ocean except for the Equatorial band and Arabian Sea.NASAEuropean Space Agency (ESA

VALIDATION OF SCIAMACHY NO 2 VERTICAL COLUMN DENSITIES WITH MT.CIMONE AND STARA ZAGORA GROUND-BASED ZENITH SKY DOAS OBSERVATIONS

ABSTRACT Ground-based zenith sky Differential Optical Absorption Spectroscopy (DOAS) measurements performed by means of GASCOD instruments at Mt. Cimone (44N 11E), Italy and Stara Zagora (42N, 25E), Bulgaria are used for validation of SCIAMACHY NO 2 vertical column density (vcd) of ESA SCI_NL product retrieved with 5.01 processor version. The results presented in this work regard satellite data for the JulyDecember 2002 period. On this base it is concluded that during summer-autumn period the overall NO 2 vcd above both stations is fairly well reproduced by the SCIAMACHY data, while towards the winter period they deviate from the seasonal behaviour of NO 2 vcd derived at both stations

Distributions of phytoplankton carbohydrate, protein and lipid in the world oceans from satellite ocean colour

Energy value of phytoplankton regulates the growth of higher trophic species, affecting the tropic balance and sustainability of marine food webs. Therefore, developing our capability to estimate and monitor, on a global scale, the concentrations of macromolecules that determine phytoplankton energy value, would be invaluable. Reported here are the first estimates of carbohydrate, protein, lipid, and overall energy value of phytoplankton in the world oceans, using ocean-colour data from satellites. The estimates are based on a novel bio-optical method that utilises satellite-derived bio-optical fingerprints of living phytoplankton combined with allometric relationships between phytoplankton cells and cellular macromolecular contents. The annually-averaged phytoplankton energy value, per cubic meter of sub-surface ocean, varied from less than 0.1 kJ in subtropical gyres, to 0.5–1.0 kJ in parts of the equatorial, northern and southern latitudes, and rising to more than 10 kJ in certain coastal and optically complex waters. The annually-averaged global stocks of carbohydrate, protein and lipid were 0.044, 0.17 and 0.108 gigatonnes, respectively, with monthly stocks highest in September and lowest in June, over 1997-2013. The fractional contributions of phytoplankton size classes e.g., picoplankton, nanoplankton and microplankton to surface concentrations and global stocks of macromolecules varied considerably across marine biomes classified as Longhurst provinces. Among these provinces, the highest annually-averaged surface concentrations of carbohydrate, protein, and lipid were in North-East Atlantic Coastal Shelves, whereas, the lowest concentration of carbohydrate or lipid were in North Atlantic Tropical Gyral, and that of protein was in North Pacific Subtropical Gyre West. The regional accuracy of the estimates and their sensitivity to satellite inputs are quantified from the bio-optical model, which show promise for possible operational monitoring of phytoplankton energy value from satellite ocean colour. Adequate in situ measurements of macromolecules and improved retrievals of inherent optical properties from high-resolution satellite images, would be required to validate these estimates at local sites, and to further improve their accuracy in the world oceans

Phytoplankton functional types from Space.

The concept of phytoplankton functional types has emerged as a useful approach to classifying phytoplankton. It finds many applications in addressing some serious contemporary issues facing science and society. Its use is not without challenges, however. As noted earlier, there is no universally-accepted set of functional types, and the types used have to be carefully selected to suit the particular problem being addressed. It is important that the sum total of all functional types matches all phytoplankton under consideration. For example, if in a biogeochemical study, we classify phytoplankton as silicifiers, calcifiers, DMS-producers and nitrogen fix- ers, then there is danger that the study may neglect phytoplankton that do not contribute in any significant way to those functions, but may nevertheless be a significant contributor to, say primary production. Such considerations often lead to the adoption of a category of “other phytoplankton” in models, with no clear defining traits assigned them, but that are nevertheless necessary to close budgets on phytoplankton processes. Since this group is a collection of all phytoplankton that defy classification according to a set of traits, it is difficult to model their physi- ological processes. Our understanding of the diverse functions of phytoplankton is still growing, and as we recognize more functions, there will be a need to balance the desire to incorporate the increasing number of functional types in models against observational challenges of identifying and mapping them adequately. Modelling approaches to dealing with increasing functional diversity have been proposed, for example, using the complex adaptive systems theory and system of infinite diversity, as in the work of Bruggemann and Kooijman (2007). But it is unlikely that remote-sensing approaches might be able to deal with anything but a few prominent functional types. As long as these challenges are explicitly addressed, the functional- type concept should continue to fill a real need to capture, in an economic fashion, the diversity in phytoplankton, and remote sensing should continue to be a useful tool to map them. Remote sensing of phytoplankton functional types is an emerging field, whose potential is not fully realised, nor its limitations clearly established. In this report, we provide an overview of progress to date, examine the advantages and limitations of various methods, and outline suggestions for further development. The overview provided in this chapter is intended to set the stage for detailed considerations of remote-sensing applications in later chapters. In the next chapter, we examine various in situ methods that exist for observing phytoplankton functional types, and how they relate to remote-sensing techniques. In the subsequent chapters, we review the theoretical and empirical bases for the existing and emerging remote-sensing approaches; assess knowledge about the limitations, assumptions, and likely accuracy or predictive skill of the approaches; provide some preliminary comparative analyses; and look towards future prospects with respect to algorithm development, validation studies, and new satellite mis- sions

Sites of Circadian Clock Neuron Plasticity Mediate Sensory Integration and Entrainment

Networks of circadian timekeeping in the brain display marked daily changes in neuronal morphology. In Drosophila melanogaster, the striking daily structural remodeling of the dorsal medial termini of the small ventral lateral neurons has long been hypothesized to mediate endogenous circadian timekeeping. To test this model, we have specifically abrogated these sites of daily neuronal remodeling through the reprogramming of neural development and assessed the effects on circadian timekeeping and clock outputs. Remarkably, the loss of these sites has no measurable effects on endogenous circadian timekeeping or on any of the major output functions of the small ventral lateral neurons. Rather, their loss reduces sites of glutamatergic sensory neurotransmission that normally encodes naturalistic time cues from the environment. These results support an alternative model: structural plasticity in critical clock neurons is the basis for proper integration of light and temperature and gates sensory inputs into circadian clock neuron networks