AULACOSEIRA PUSILLA (BACILLARIOPHYTA) – NEW SPECIES FOR THE FLORA OF THE VOLGA RESERVOIRS

In this paper, we restudy the morphology of A.subarctica low-frustule forms from the Volga reservoirs (Ivankovo, Gorky and Kuibyshev) using scanning electron microscopy. These forms occur as short colonies and one of them, by quantitative (colony size, valve diameter and mantle height, valve height/diameter ratio, number of areola rows and areolae in 10 µm) and qualitative (shape of spines, areolae arrangement of valve face and mantle) characteristics, corresponds to A.pusilla. The latter is a cosmopolitan species, new for the flora of Volga. A. Pusilla is very similar to A.subarctica by morphology and these two species are often found together that may cause problems with their identification.

Computer vision approach to characterize size and shape phenotypes of horticultural crops using high-throughput imagery

For many horticultural crops, variation in quality (e.g., shape and size) contribute significantly to the crop’s market value. Metrics characterizing less subjective harvest quantities (e.g., yield and total biomass) are routinely monitored. In contrast, metrics quantifying more subjective crop quality characteristics such as ideal size and shape remain difficult to characterize objectively at the production-scale due to the lack of modular technologies for high-throughput sensing and computation. Several horticultural crops are sent to packing facilities after having been harvested, where they are sorted into boxes and containers using high-throughput scanners. These scanners capture images of each fruit or vegetable being sorted and packed, but the images are typically used solely for sorting purposes and promptly discarded. With further analysis, these images could offer unparalleled insight on how crop quality metrics vary at the industrial production-scale and provide further insight into how these characteristics translate to overall market value. At present, methods for extracting and quantifying quality characteristics of crops using images generated by existing industrial infrastructure have not been developed. Furthermore, prior studies that investigated horticultural crop quality metrics, specifically of size and shape, used a limited number of samples, did not incorporate deformed or non-marketable samples, and did not use images captured from high-throughput systems. In this work, using sweetpotato (SP) as a use case, we introduce a computer vision algorithm for quantifying shape and size characteristics in a high-throughput manner. This approach generates 3D model of SPs from two 2D images captured by an industrial sorter 90 degrees apart and extracts 3D shape features in a few hundred milliseconds. We applied the 3D reconstruction and feature extraction method to thousands of image samples to demonstrate how variations in shape features across sweetptoato cultivars can be quantified. We created a sweetpotato shape dataset containing sweetpotato images, extracted shape features, and qualitative shape types (U.S. No. 1 or Cull). We used this dataset to develop a neural network-based shape classifier that was able to predict Cull vs. U.S. No. 1 sweetpotato with 84.59% accuracy. In addition, using univariate Chi-squared tests and random forest, we identified the most important features for determining qualitative shape (U.S. No. 1 or Cull) of the sweetpotatoes. Our study serves as the first step towards enabling big data analytics for sweetpotato agriculture. The methodological framework is readily transferable to other horticultural crops, particularly those that are sorted using commercial imaging equipment.

Leveraging the mathematics of shape for solar magnetic eruption prediction

Current operational forecasts of solar eruptions are made by human experts using a combination of qualitative shape-based classification systems and historical data about flaring frequencies. In the past decade, there has been a great deal of interest in crafting machine-learning (ML) flare-prediction methods to extract underlying patterns from a training set – e.g. a set of solar magnetogram images, each characterized by features derived from the magnetic field and labeled as to whether it was an eruption precursor. These patterns, captured by various methods (neural nets, support vector machines, etc.), can then be used to classify new images. A major challenge with any ML method is the featurization of the data: pre-processing the raw images to extract higher-level properties, such as characteristics of the magnetic field, that can streamline the training and use of these methods. It is key to choose features that are informative, from the standpoint of the task at hand. To date, the majority of ML-based solar eruption methods have used physics-based magnetic and electric field features such as the total unsigned magnetic flux, the gradients of the fields, the vertical current density, etc. In this paper, we extend the relevant feature set to include characteristics of the magnetic field that are based purely on the geometry and topology of 2D magnetogram images and show that this improves the prediction accuracy of a neural-net based flare-prediction method.

It sounds like an action potential: unification of electrical, chemical and mechanical aspects of acoustic pulses in lipids

In an ongoing debate on the physical nature of the action potential (AP), one group adheres to the electrical model of Hodgkin and Huxley, while the other describes the AP as a nonlinear acoustic pulse propagating within an interface near a transition. However, despite remarkable similarities, acoustics remains a non-intuitive mechanism for APs for the following reason. While acoustic pulses are typically associated with the propagation of density, pressure and temperature variation, APs are most commonly measured electrically. Here, we show that this discrepancy is lifted upon considering the electrical and chemical aspects of the interface, in addition to its mechanical properties. Specifically, we demonstrate how electrical and pH aspects of acoustic pulses emerge from an idealized description of the lipid interface, which is based on classical physical principles and contains no fit parameters. The pulses that emerge from the model show similarities to APs not only in qualitative shape and scales (time, velocity and voltage), but also demonstrate saturation of amplitude and annihilation upon collision.

Ceramic ware in the culture of mobile foragers of the Extreme north-east of Europe

In the paper the author summarized and systematized the initial data on ceramic ware of the Neolithic and Eneolithic of the Extreme north-east of Europe. He analyzed information about the archaeological contexts of ceramics, its quantitative (number of capacities in each complex) and qualitative (shape, proportionality and volume of vessels) characteristics. Critical analysis is used to assess the possibilities of available materials to extract information. As a result, the dynamics of quantitative and qualitative parameters of ceramic ware during the VI - first half of II millennium BC was traced. Its cultural and chronological features are determined as well. It is established that in the first half of the V millennium BC ceramics in the form of sets of vessels of different volumes and kinds becomes an integral part of the daily life of the hunters of the region. According to their lifestyle, the demand for ceramics was limited: the average number of simultaneously used vessels on average 3-4 containers per context. In this case, the simplest forms (round-bottomed pots with volumes up to 25 liters and bowl-shaped dishes up to 2,5 liters) predominate. Ceramic traditions presented in the region are associated with cultures that originate in different adjacent areas of the forest zone of Eastern Europe and Western Siberia, so the universality of the customary forms, volumes and, probably, the ways of using ceramic dishes, is universally accepted. The data obtained can be used as materials for the development of the problem of the distribution of early ceramics, for assessing the role and determining the place of it in the material culture of the prehistoric population.

EVALUASI PELAKSANAAN CORPORATE SOCIAL RESPONSIBILITY PADA PT UNILEVER INDONESIA, TBK.

<p>Corporate Social Responsibility is a must for companies, especially for a limited<br />liability company. It is attested in chapter V Social and Environmental Responsibility in<br />sections 74 subsection (1) until subsection (3) of law No. 40 year 2007 on limited liability<br />company. This study uses secondary data and qualitative shape that is from the website of<br />PT Unilever Indonesia, Tbk. regarding the activities of Corporate Social Responsibility<br />the company has done and using research on Corporate Social Responsibility that has<br />been done by researchers previously associated laws-an invitation about Corporate<br />Social Responsibility. Corporate Social Responsibility is also always associated with<br />Green Economy. The management of PT Unilever Indonesia, Tbk. was successfully<br />implementing Corporate Social Responsibility as part of a strong organizational culture<br />and also PT Unilever Indonesia, Tbk. has been successfully implementing adaptive culture.</p>

Dependence of Model Energy Spectra on Vertical Resolution

Many high-resolution atmospheric models can reproduce the qualitative shape of the atmospheric kinetic energy spectrum, which has a power-law slope of −3 at large horizontal scales that shallows to approximately −5/3 in the mesoscale. This paper investigates the possible dependence of model energy spectra on the vertical grid resolution. Idealized simulations forced by relaxation to a baroclinically unstable jet are performed for a wide range of vertical grid spacings Δz. Energy spectra are converged for Δz 200 m but are very sensitive to resolution with 500 m ≤ Δz ≤ 2 km. The nature of this sensitivity depends on the vertical mixing scheme. With no vertical mixing or with weak, stability-dependent mixing, the mesoscale spectra are artificially amplified by low resolution: they are shallower and extend to larger scales than in the converged simulations. By contrast, vertical hyperviscosity with fixed grid-scale damping rate has the opposite effect: underresolved spectra are spuriously steepened. High-resolution spectra are converged except for the stability-dependent mixing case, which are damped by excessive mixing due to enhanced shear over a wide range of horizontal scales. It is shown that converged spectra require resolution of all vertical scales associated with the resolved horizontal structures: these include quasigeostrophic scales for large-scale motions with small Rossby number and the buoyancy scale for small-scale motions at large Rossby number. It is speculated that some model energy spectra may be contaminated by low vertical resolution, and it is recommended that vertical-resolution sensitivity tests always be performed.