Effect of foliar fertilization using micronutrient fertilizers on the content of nitrates(V), nitrites(III) in potato tubers

The research was based on a 3-year field experiment carried out in south-eastern Poland, in 2013‒2015, on brown, slightly acidic soil. The experiment was established by the randomized subblock method, where the first-order factors were foliar fertilization: (A) Fortis Duotop Zn Mn + Fortis Aminotop, (B) Fortis B Mo + Ferti Agro, (C) Fortis Zn Mn + Fortis B Mo and (0) standard object, without foliar fertilization. The factors of the second order were 4 edible potato cultivars (‘Viviana’, ‘Vineta’, ‘Jelly’ and ‘Agnes’). Foliar application of all fertilizer combinations contributed to the reduction of the content of nitrates and nitrites in potato tubers. However, the response of cultivars to foliar fertilization was varied. The medium late cultivar ‘Jelly’ was characterized by the lowest tendency to accumulate nitrates, while the early cultivar ‘Vineta’ was the highest. The highest content of both nitrates and nitrites in tubers was recorded in the dry year, with a significant shortage of rainfall during the potato growing season, and the lowest in the year, about wet June, and September.

Advertising Pragmatics of Contemporary Media for Polylingualism and Polyculturalism

The article considers advertising pragmatics of contemporary media for polylingualism and polyculturalism as the urgent need for advertising information about different types of goods has become a prerequisite for the development and dissemination of a hybrid type of text – advertising text, announcement of things or services. The research aims at the functional specifics of advertising texts in polycultural and polylingual contexts, among which is a variety of publications and outdoor advertising. To achieve the objective, it is important to consider the goals (set tasks) associated with the research questions. They are: (i) to outline the presentation patterns of trademarks and define the essence of the advertising text in the poly-lingual context, (ii) to determine the pragmatic direction of advertising texts of modern media, accounting for the discursive-functional aspects, (iii) to trace manifestation of multiculturalism and/or polyculturalism and polylingualism of the advertising text as a non-standard type of text. It is stated advertising slogan is a communicative message that has a pragmatic instruction to convey true information about the subject of advertising to the largest number of people in order to encourage them to take action - to use and purchase the advertised product. The slogan is focused primarily on achieving the maximum pragmatic effect: to present the brand, distribute the advertised products, actually sell the product, and even forcibly impose it on a potential consumer. It is found the following aspects are clearly combined, which logically represent the advertising text as a non-standard object of linguistic description in the polylingual cultures: 1) polylingual components:introduction into the advertising message of linguistic facts by different types of fonts, a combination of natural and unnatural semiotic systems (signs, drawings, symbols), introduction to the text of visuals; 2) multicultural and/or polycultural components.

Towards Accurate Detection of Axial Spondyloarthritis by Using Deep Learning to Capture Sacroiliac Joints on Plain Radiographs.

BackgroundWell-informed decisions about how to best treat patients with axial spondyloarthritis (SpA) regularly include an evaluation of the sacroiliac joints (SIJ) on plain radiographs. However, grading radiographic findings correctly has proven to be a considerable challenge to expert readers as well as to state-of-the-art convolutional neural networks (CNNs). A method to reduce image information to the clinically relevant core would undoubtedly lead to more accurate results. We, therefore, trained a CNN only to detect SIJs on radiographs and evaluated its potential as a preprocessing pipeline in the automated classification of SpA.Materials and MethodsWe employed a CNN of the RetinaNet architecture, which was trained on a total of 423 plain radiographs of the sacroiliac joints (SIJs). Images were taken from two completely independent datasets. Training and tuning were performed on image data from the Patients With Axial Spondyloarthritis (PROOF) study and testing was executed using images from the German Spondyloarthritis Inception Cohort (GESPIC). Performance was evaluated by manual review and standard object detection metrics from PASCAL and Microsoft COCO.ResultsThe CNN produced excellent results in detecting SIJs on the tuning (n =106) and on the holdout dataset (n =140). Object detection metrics for the tuning data were AP = 0.996 and mAP = 0.538; values for the independent holdout data were AP = 0.981 and mAP = 0.515. ConclusionsThe developed CNN was highly accurate in detecting SIJs on radiographs. Such a model could increase the reliability of deep learning-based algorithms in detecting and grading SpA.

Investigating the Potential of Network Optimization for a Constrained Object Detection Problem

Object detection models are usually trained and evaluated on highly complicated, challenging academic datasets, which results in deep networks requiring lots of computations. However, a lot of operational use-cases consist of more constrained situations: they have a limited number of classes to be detected, less intra-class variance, less lighting and background variance, constrained or even fixed camera viewpoints, etc. In these cases, we hypothesize that smaller networks could be used without deteriorating the accuracy. However, there are multiple reasons why this does not happen in practice. Firstly, overparameterized networks tend to learn better, and secondly, transfer learning is usually used to reduce the necessary amount of training data. In this paper, we investigate how much we can reduce the computational complexity of a standard object detection network in such constrained object detection problems. As a case study, we focus on a well-known single-shot object detector, YoloV2, and combine three different techniques to reduce the computational complexity of the model without reducing its accuracy on our target dataset. To investigate the influence of the problem complexity, we compare two datasets: a prototypical academic (Pascal VOC) and a real-life operational (LWIR person detection) dataset. The three optimization steps we exploited are: swapping all the convolutions for depth-wise separable convolutions, perform pruning and use weight quantization. The results of our case study indeed substantiate our hypothesis that the more constrained a problem is, the more the network can be optimized. On the constrained operational dataset, combining these optimization techniques allowed us to reduce the computational complexity with a factor of 349, as compared to only a factor 9.8 on the academic dataset. When running a benchmark on an Nvidia Jetson AGX Xavier, our fastest model runs more than 15 times faster than the original YoloV2 model, whilst increasing the accuracy by 5% Average Precision (AP).

Effect of Attractants and Micronutrient Biofortification on the Yield and Quality of Red Clover (Trifolium pratense L.) Seeds

The aim of the research was to develop an innovative technique in the seed production of red clover. The research was carried out in 2013–2016, in Felin (51°22′ N, 22°65′ E), in a dependent arrangement (split-split-plot) in four replications. The first order factor was the use of an attractant: (1) control object, with pure water spraying, (2) attractant used in the 60 BBCH phase, (3) attractant applied twice—in the 60 and 65 phase, in the BBCH scale. The factor of the second order was fertilization: (a) standard object with PK fertilization; (b) fertilization with microelements (B + Mo) against the background of constant PK fertilization. The use of attractant ‘Pollinus’ preparation in the cultivation of red clover, both once and twice, in the form of spraying on plants, contributed to an increase in the seed yield, number of heads, share of seeds in the head, thousand seeds weight, and seed germination capacity, compared to the control object. Elements of the red clover yield structure achieved more favorable values with foliar feeding (B + Mo) compared to the standard one. Under the influence of plant biofortification with boron and molybdenum, the number of seeds infected with fungal pathogens and abnormally germinating decreased.

The effect of foliar fertilization on darkening of tuber flesh of selected potato cultivars

The aim of the study was to determine the effect of foliar fertilizers with the content of macro- and microelements used in the form of chelates on darkening of the tuber flesh of selected potato cultivars. The research was based on a 3-year (2013‒2015) field experiment carried out in Haczów (49°40'N, 21°54'E) on brown, slightly acidic soil. The experiment was based on the method of randomized sub-blocks, where the first order factor was foliar fertilization: Fortis Zn Mn + Fortis Aminotop (A), Fortis B Mo + Ferti Agro (B), Fortis Zn Mn + Fortis B Mo (C) and a standard object without foliar fertilization (0). Second-order factor included four edible potato cultivars of all earliness classes (‘Viviana’, ‘Vineta’, ‘Agnes’, ‘Jelly’). Significant differences in tuber darkening due to foliar application were observed only for tubers 24 h after cooking. The application of Fortis B Mo + Ferti Agro and Fortis Duotop Zn Mn + Fortis Aminotop fertilizers reduced the darkening of the apical part tuber to the greatest extent. Genetic factor differentiated the most the value of all examined traits. The cultivars tested showed varied response to foliar fertilizers.

Spontaneous object-location memory based on environmental geometry is impaired by both hippocampal and dorsolateral striatal lesions

We examined the role of the hippocampus and the dorsolateral striatum in the representation of environmental geometry using a spontaneous object recognition procedure. Rats were placed in a kite-shaped arena and allowed to explore two distinctive objects in each of the right-angled corners. In a different room, rats were then placed into a rectangular arena with two identical copies of one of the two objects from the exploration phase, one in each of the two adjacent right-angled corners that were separated by a long wall. Time spent exploring these two objects was recorded as a measure of recognition memory. Since both objects were in different locations with respect to the room (different between exploration and test phases) and the global geometry (also different between exploration and test phases), differential exploration of the objects must be a result of initial habituation to the object relative to its local geometric context. The results indicated an impairment in processing the local geometric features of the environment for both hippocampus and dorsolateral striatum lesioned rats compared with sham-operated controls, though a control experiment showed these rats were unimpaired in a standard object recognition task. The dorsolateral striatum has previously been implicated in egocentric route-learning, but the results indicate an unexpected role for the dorsolateral striatum in processing the spatial layout of the environment. The results provide the first evidence that lesions to the hippocampus and dorsolateral striatum impair spontaneous encoding of local environmental geometric features.

Effect of fertilization on the growth rate of aboveground part of Jerusalem artichoke

The research was based on the field experiment conducted in 2013–2015 at the Experimental Station of the University of Life Sciences, in Parczew (51°38'24"N, 22°54'02"E), on podzolic soil. The experiment was established using the split-split-plot method in three replications. The factors of the first order were three cultivars: ‘Albik’, ‘Rubik’ and ‘Violet de Rennes’. The second order factor was mineral fertilization (N0P0K0 – as standard object and P43, K124, N100, P43K124, N50P43K124, N100P43K124, N150P43K124), calculated as the elemental form of fertilizers. As the basic fertilization, bovine manure was used in the amount of 30 t·ha–1. The aim of the research was to develop the basis for managing the fertilization of Jerusalem artichoke, which will allow to obtain the maximum increase of aboveground part of this species. It was found that for the rate of plant growth, the most optimal fertilization was manure and mineral fertilization in the amount of 100 kg of N·ha–1 in the nitrate-ammonium form. The phosphorus-potassium fertilization, despite the use of manure, significantly reduced the growth of plants in comparison with the standard object.

Foliar fertilization in shaping the potato yield in the conditions of south-eastern Poland

The study aimed at determining the effect of macro- and microelements contained in foliar fertilizers on potato productivity of tubers. The field experiment was conducted in 2015–2017 in Uhnin using the random blocks method. The first order factor were 2 cultivars of potatoes, the second order factor were 3 foliar fertilization technologies and standard object − without foliar spraying. Mineral fertilizers were constant. Foliar fertilizers were used in accordance with the recommendation of the producers. Foliar fertilizing has contributed to a significant increase in total and commercial yield. The cultivars determined the majority of potato's economic traits.