scholarly journals Drone RGB Images as a Reliable Information Source to Determine Legumes Establishment Success

Drones ◽  
2021 ◽  
Vol 5 (3) ◽  
pp. 79
Author(s):  
Lorena Parra ◽  
David Mostaza-Colado ◽  
Salima Yousfi ◽  
Jose F. Marin ◽  
Pedro V. Mauri ◽  
...  
Keyword(s):  
Cell Size ◽  
Low Cost ◽  
Information Source ◽  
Initial Approximation ◽  
Flying Height ◽  
Training Dataset ◽  
Establishment Success ◽  
Aggregation Techniques ◽  
A Cell ◽  
Rgb Images

The use of drones in agriculture is becoming a valuable tool for crop monitoring. There are some critical moments for crop success; the establishment is one of those. In this paper, we present an initial approximation of a methodology that uses RGB images gathered from drones to evaluate the establishment success in legumes based on matrixes operations. Our aim is to provide a method that can be implemented in low-cost nodes with relatively low computational capacity. An index (B1/B2) is used for estimating the percentage of green biomass to evaluate the establishment success. In the study, we include three zones with different establishment success (high, regular, and low) and two species (chickpea and lentils). We evaluate data usability after applying aggregation techniques, which reduces the picture’s size to improve long-term storage. We test cell sizes from 1 to 10 pixels. This technique is tested with images gathered in production fields with intercropping at 4, 8, and 12 m relative height to find the optimal aggregation for each flying height. Our results indicate that images captured at 4 m with a cell size of 5, at 8 m with a cell size of 3, and 12 m without aggregation can be used to determine the establishment success. Comparing the storage requirements, the combination that minimises the data size while maintaining its usability is the image at 8 m with a cell size of 3. Finally, we show the use of generated information with an artificial neural network to classify the data. The dataset was split into a training dataset and a verification dataset. The classification of the verification dataset offered 83% of the cases as well classified. The proposed tool can be used in the future to compare the establishment success of different legume varieties or species.

Spindle scaling mechanisms

2020 ◽  
Vol 64 (2) ◽  
pp. 383-396
Author(s):  
Lara K. Krüger ◽  
Phong T. Tran
Keyword(s):  
Cell Size ◽  
Spindle Assembly ◽  
Dependent Manner ◽  
Post Translational Modification ◽  
Size Dependent ◽  
A Cell ◽  
Chromosome Separation ◽  
Spindle Elongation ◽  
Protein Gradients ◽  
Spindle Structure

Abstract The mitotic spindle robustly scales with cell size in a plethora of different organisms. During development and throughout evolution, the spindle adjusts to cell size in metazoans and yeast in order to ensure faithful chromosome separation. Spindle adjustment to cell size occurs by the scaling of spindle length, spindle shape and the velocity of spindle assembly and elongation. Different mechanisms, depending on spindle structure and organism, account for these scaling relationships. The limited availability of critical spindle components, protein gradients, sequestration of spindle components, or post-translational modification and differential expression levels have been implicated in the regulation of spindle length and the spindle assembly/elongation velocity in a cell size-dependent manner. In this review, we will discuss the phenomenon and mechanisms of spindle length, spindle shape and spindle elongation velocity scaling with cell size.

Emulsion flow which preparation excludes a presence of mechanical impurities

2012 ◽  
Vol 9 (2) ◽  
pp. 118-122
Author(s):  
A.A. Rakhimov
Keyword(s):  
Cell Size ◽  
First Case ◽  
A Cell ◽  
Emulsion Flow ◽  
Blocking Mechanism

Experiments were carried out with waterhydrocarbon emulsions with various emulsifiers in capillaries with a length of 2 cm, diameters of 40 and 100 µm. To eliminate the influence of mechanical impurities comparable in size with the diameter of the capillary in first case emulsion components were filtered through fine-meshed filters. In second case obtained that way emulsion was additionally filtered through a system consisting of 3 filters with a cell size of 30-40 microns. In a capillary of 100 µm such emulsion came in a blocked state. Additional filtration of the emulsion through the mesh filters have led to an increase in viscosity but in 100 µm capillaries the time until the blocking 2-3 times more than the original. Rheology of used emulsions is well described by the model of Ostwald-de Waale. It was determined that emulsion blocking mechanism is due to the presence of inclusions not emulsion viscosity.

scholarly journals Development and Performance Evaluation of a Very Low-Cost UAV-Lidar System for Forestry Applications

2020 ◽  
Vol 13 (1) ◽  
pp. 77
Author(s):  
Tianyu Hu ◽  
Xiliang Sun ◽  
Yanjun Su ◽  
Hongcan Guan ◽  
Qianhui Sun ◽  
...  
Keyword(s):  
Forest Inventory ◽  
Low Cost ◽  
Canopy Cover ◽  
Tree Height ◽  
Flying Height ◽  
Tree Level ◽  
Forest Site ◽  
Lidar System ◽  
Individual Tree ◽  
Gap Fraction

Accurate and repeated forest inventory data are critical to understand forest ecosystem processes and manage forest resources. In recent years, unmanned aerial vehicle (UAV)-borne light detection and ranging (lidar) systems have demonstrated effectiveness at deriving forest inventory attributes. However, their high cost has largely prevented them from being used in large-scale forest applications. Here, we developed a very low-cost UAV lidar system that integrates a recently emerged DJI Livox MID40 laser scanner (~$600 USD) and evaluated its capability in estimating both individual tree-level (i.e., tree height) and plot-level forest inventory attributes (i.e., canopy cover, gap fraction, and leaf area index (LAI)). Moreover, a comprehensive comparison was conducted between the developed DJI Livox system and four other UAV lidar systems equipped with high-end laser scanners (i.e., RIEGL VUX-1 UAV, RIEGL miniVUX-1 UAV, HESAI Pandar40, and Velodyne Puck LITE). Using these instruments, we surveyed a coniferous forest site and a broadleaved forest site, with tree densities ranging from 500 trees/ha to 3000 trees/ha, with 52 UAV flights at different flying height and speed combinations. The developed DJI Livox MID40 system effectively captured the upper canopy structure and terrain surface information at both forest sites. The estimated individual tree height was highly correlated with field measurements (coniferous site: R2 = 0.96, root mean squared error/RMSE = 0.59 m; broadleaved site: R2 = 0.70, RMSE = 1.63 m). The plot-level estimates of canopy cover, gap fraction, and LAI corresponded well with those derived from the high-end RIEGL VUX-1 UAV system but tended to have systematic biases in areas with medium to high canopy densities. Overall, the DJI Livox MID40 system performed comparably to the RIEGL miniVUX-1 UAV, HESAI Pandar40, and Velodyne Puck LITE systems in the coniferous site and to the Velodyne Puck LITE system in the broadleaved forest. Despite its apparent weaknesses of limited sensitivity to low-intensity returns and narrow field of view, we believe that the very low-cost system developed by this study can largely broaden the potential use of UAV lidar in forest inventory applications. This study also provides guidance for the selection of the appropriate UAV lidar system and flight specifications for forest research and management.

Glycans in scaffold design in tissue reconstruction

2021 ◽  
pp. 088391152199784
Author(s):  
Nipun Jain ◽  
Shashi Singh
Keyword(s):  
Cell Attachment ◽  
Low Cost ◽  
Growth Conditions ◽  
Downstream Signaling ◽  
Cell Carrier ◽  
Wide Range ◽  
Proliferation And Differentiation ◽  
Different Types ◽  
Tissue Reconstruction ◽  
A Cell

Development of an artificial tissue by tissue engineering is witnessed to be one of the long lasting clarified solutions for the damaged tissue function restoration. To accomplish this, a scaffold is designed as a cell carrier in which the extracellular matrix (ECM) performs a prominent task of controlling the inoculated cell’s destiny. ECM composition, topography and mechanical properties lead to different types of interactions between cells and ECM components that trigger an assortment of cellular reactions via diverse sensing mechanisms and downstream signaling pathways. The polysaccharides in the form of proteoglycans and glycoproteins yield better outcomes when included in the designed matrices. Glycosaminoglycan (GAG) chains present on proteoglycans show a wide range of operations such as sequestering of critical effector morphogens which encourage proficient nutrient contribution toward the growing stem cells for their development and endurance. In this review we discuss how the glycosylation aspects are of considerable importance in everyday housekeeping functions of a cell especially when placed in a controlled environment under ideal growth conditions. Hydrogels made from these GAG chains have been used extensively as a resorbable material that mimics the natural ECM functions for an efficient control over cell attachment, permeability, viability, proliferation, and differentiation processes. Also the incorporation of non-mammalian polysaccharides can elicit specific receptor responses which authorize the creation of numerous vigorous frameworks while prolonging the low cost and immunogenicity of the substance.

scholarly journals Confronting Deep-Learning and Biodiversity Challenges for Automatic Video-Monitoring of Marine Ecosystems

Sensors ◽  
2022 ◽  
Vol 22 (2) ◽  
pp. 497
Author(s):  
Sébastien Villon ◽  
Corina Iovan ◽  
Morgan Mangeas ◽  
Laurent Vigliola
Keyword(s):  
Deep Learning ◽  
Data Augmentation ◽  
Low Cost ◽  
Video Recording ◽  
Species Abundance ◽  
Automatic Monitoring ◽  
Training Dataset ◽  
Data Generation ◽  
Automatic Assessment ◽  
Open Set

With the availability of low-cost and efficient digital cameras, ecologists can now survey the world’s biodiversity through image sensors, especially in the previously rather inaccessible marine realm. However, the data rapidly accumulates, and ecologists face a data processing bottleneck. While computer vision has long been used as a tool to speed up image processing, it is only since the breakthrough of deep learning (DL) algorithms that the revolution in the automatic assessment of biodiversity by video recording can be considered. However, current applications of DL models to biodiversity monitoring do not consider some universal rules of biodiversity, especially rules on the distribution of species abundance, species rarity and ecosystem openness. Yet, these rules imply three issues for deep learning applications: the imbalance of long-tail datasets biases the training of DL models; scarce data greatly lessens the performances of DL models for classes with few data. Finally, the open-world issue implies that objects that are absent from the training dataset are incorrectly classified in the application dataset. Promising solutions to these issues are discussed, including data augmentation, data generation, cross-entropy modification, few-shot learning and open set recognition. At a time when biodiversity faces the immense challenges of climate change and the Anthropocene defaunation, stronger collaboration between computer scientists and ecologists is urgently needed to unlock the automatic monitoring of biodiversity.

scholarly journals Multi-Task Driven Feature Models for Thermal Infrared Tracking

2020 ◽  
Vol 34 (07) ◽  
pp. 11604-11611 ◽  
Author(s):  
Qiao Liu ◽  
Xin Li ◽  
Zhenyu He ◽  
Nana Fan ◽  
Di Yuan ◽  
...  
Keyword(s):  
Large Scale ◽  
State Of The Art ◽  
Thermal Infrared ◽  
Training Dataset ◽  
Feature Models ◽  
Relative Gain ◽  
Tir Domain ◽  
Fine Grained ◽  
Rgb Images ◽  
Infrared Tracking

Existing deep Thermal InfraRed (TIR) trackers usually use the feature models of RGB trackers for representation. However, these feature models learned on RGB images are neither effective in representing TIR objects nor taking fine-grained TIR information into consideration. To this end, we develop a multi-task framework to learn the TIR-specific discriminative features and fine-grained correlation features for TIR tracking. Specifically, we first use an auxiliary classification network to guide the generation of TIR-specific discriminative features for distinguishing the TIR objects belonging to different classes. Second, we design a fine-grained aware module to capture more subtle information for distinguishing the TIR objects belonging to the same class. These two kinds of features complement each other and recognize TIR objects in the levels of inter-class and intra-class respectively. These two feature models are learned using a multi-task matching framework and are jointly optimized on the TIR tracking task. In addition, we develop a large-scale TIR training dataset to train the network for adapting the model to the TIR domain. Extensive experimental results on three benchmarks show that the proposed algorithm achieves a relative gain of 10% over the baseline and performs favorably against the state-of-the-art methods. Codes and the proposed TIR dataset are available at https://github.com/QiaoLiuHit/MMNet.

Growth in cell length in the fission yeast Schizosaccharomyces pombe

1985 ◽  
Vol 75 (1) ◽  
pp. 357-376 ◽  
Author(s):  
J.M. Mitchison ◽  
P. Nurse
Keyword(s):  
Schizosaccharomyces Pombe ◽  
Cell Size ◽  
Single Cells ◽  
Temperature Shift ◽  
Time Lapse ◽  
Cell Length ◽  
Wild Type ◽  
Cycle Growth ◽  
A Cell ◽  
Mutant Cells

The cylindrical cells of Schizosaccharomyces pombe grow in length by extension at the ends and not the middle. At the beginning of the cell cycle, growth is restricted to the ‘old end’, which existed in the previous cycle. Later on, the ‘new end’, formed from the septum, starts to grow at a point in the cycle that we have called NETO (‘new end take-off’). Fluorescence microscopy on cells stained with Calcofluor has been used to study NETO in size mutants, in blocked cdc mutants and with different growth temperatures and media. In wild-type cells (strain 972) NETO happens at 0.34 of the cycle with a cell length of 9.5 microns. With size mutants that are smaller at division, NETO takes place at the same size (9.0-9.5 microns) but this is not achieved until later in the cycle. Another control operates in larger size mutants since NETO occurs at the same stage of the cycle (about 0.32) as in wild type but at a larger cell size. This control is probably a requirement to have completed an event in early G2, since most cdc mutant cells blocked before this point in the cycle do not show NETO whereas most of those blocked in late G2 do show it. We conclude that NETO only happens if: (1) the cell length is greater than a critical value of 9.0-9.5 microns; and (2) the cell has traversed the first 0.3-0.35 of the cycle and passed early G2. NETO is delayed in poor media, in which cell size is also reduced. Temperature has little effect on NETO under steady-state conditions, but there is a transient delay for some hours after a temperature shift. NETO is later in another wild-type strain, 132. Time-lapse photomicrography was used to follow the rates of length growth in single cells. Wild-type cells showed two linear segments during the first 75% of the cycle. There was a rate-change point (RCP), coincident with NETO, where the rate of total length extension increased by 35%. This increase was not due simply to the start of new-end growth, since old-end growth slowed down in some cells at the RCP. cdc 11.123 is a mutant in which septation and division is blocked at 35 degrees C but nuclear division continues.(ABSTRACT TRUNCATED AT 400 WORDS)

The chemistry, reflectance, and cell size of the erlichmanite (OsS2)-laurite (RuS2) series

1983 ◽  
Vol 47 (345) ◽  
pp. 465-471 ◽  
Author(s):  
J. F. W. Bowles ◽  
D. Atkin ◽  
J. L. M. Lambert ◽  
T. Deans ◽  
R. Phillips
Keyword(s):  
Solid Solution ◽  
Cell Size ◽  
Sierra Leone ◽  
Crystal Chemistry ◽  
First Report ◽  
Complete Solid Solution ◽  
A Cell ◽  
Platinum Group

AbstractMicroprobe analyses of members of the erlichmanite-laurite series from Guma Water and Senduma, Sierra Leone and Tanah Laut, Borneo, indicate that complete solid solution is possible between OsS2 and RuS2 with considerable substitution of Os and Ru by Ir, Rh, and Pt. The cell size of the erlichmanite from Guma Water is a = 5.6183±0.0003 Å at a composition (Os0.61Ru0.30Ir0.06Rh0.03)Σ0.93S2 whilst the laurite from Senduma has a composition of (Ru0.88Os0.05Ir0.04 Rh0.03)Σ0.93S2 and a cell size of a = 5.6089±0.0005 Å. Substitution of Os for Ru provides the predominant cause of the variation of cell size. Substitution by other elements of the platinum group appears to produce little effect on cell size and is presumably controlled by genesis rather than considerations of crystal chemistry or structure. The recorded analyses for these elements indicate a pre-dominance of Ir over Rh for members of the series containing more than about 15% of the laurite molecule. For the remainder of the series Rh is more important than Ir. The reflectance in air and oil of the members of the series from Sierra Leone and Borneo are presented and the microhardness of the erlichmanite from Guma Water shown to be 1854 kg/mm2. This is the first report of laurite from Senduma, Sierra Leone.

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