bluuebunny/crossref_metadata_2025_split huggingface dataset:
Inoculation of Azospirillum brasilense associated with silicon as a liming source to improve nitrogen fertilization in wheat crops
Authors: Galindo Fernando Shintate , Buzetti Salatiér , Rodrigues Willian Lima , Boleta Eduardo Henrique Marcandalli , Silva Vinicius Martins , Tavanti Renan Francisco Rimoldi , Fernandes Guilherme Carlos , Biagini Antônio Leonardo Campos , Rosa Poliana Aparecida Leonel , Teixeira Filho Marcelo Carvalho Minhoto 
Published: April 2020

AbstractThis research was developed to investigate whether inoculation with Azospirillum brasilense in combination with silicon (Si) can enhance N use efficiency (NUE) in wheat and to evaluate and correlate nutritional and productive components and wheat grain yield. The study was carried out on a Rhodic Hapludox under a no-till system with a completely randomized block design with four replications in a 2 × 2 × 5 factorial scheme: two liming sources (with Ca and Mg silicate as the Si source and limestone); two inoculations (control - without inoculation and seed inoculation with A. brasilense) and five side-dress N rates (0, 50, 100, 150 and 200 kg ha−1). The results of this study showed positive improvements in wheat growth production parameters, NUE and grain yield as a function of inoculation associated with N rates. Inoculation can complement and optimize N fertilization, even with high N application rates. The potential benefits of Si use were less evident; however, the use of Si can favour N absorption, even when associated with A. brasilense. Therefore, studies conducted under tropical conditions with Ca and Mg silicate are necessary to better understand the role of Si applied alone or in combination with growth-promoting bacteria such as A. brasilense.
Deep-Water Renewal Events; Insights into Deep Water Sediment Transport Mechanisms
Authors: Ayranci K. , Dashtgard S. E. 
Published: April 2020

AbstractDeep-water renewal (DWR) events are characterized in the Strait of Georgia, Canada using 11 years of real-time physical and chemical oceanographic data and seafloor videos. At least 6 DWRs occur per year at 300 m water depth and each event continues for over 3 days. They initiate during neap tides and are associated with increased turbidity. In the spring, DWRs introduce cold, oxygenated and nutrient-poor waters, and in the fall they introduce warm, oxygen-depleted, nutrient-rich and saline waters. Although the timing and magnitude of DWRs differ from year to year, we demonstrate that they are not restricted to two seasons, but continue throughout the year. High-resolution videos of DWRs show that these events comprise a plume of high suspended sediment concentration that flows parallel to the basin axis and deposits approximately 1.5 cm per event.
Differential Role for a Defined Lateral Horn Neuron Subset in Naïve Odor Valence in Drosophila
Authors: Lerner Hadas , Rozenfeld Eyal , Rozenman Bar , Huetteroth Wolf , Parnas Moshe 
Published: April 2020

AbstractValue coding of external stimuli in general, and odor valence in particular, is crucial for survival. In flies, odor valence is thought to be coded by two types of neurons: mushroom body output neurons (MBONs) and lateral horn (LH) neurons. MBONs are classified as neurons that promote either attraction or aversion, but not both, and they are dynamically activated by upstream neurons. This dynamic activation updates the valence values. In contrast, LH neurons receive scaled, but non-dynamic, input from their upstream neurons. It remains unclear how such a non-dynamic system generates differential valence values. Recently, PD2a1/b1 LH neurons were demonstrated to promote approach behavior at low odor concentration in starved flies. Here, we demonstrate that at high odor concentrations, these same neurons contribute to avoidance in satiated flies. The contribution of PD2a1/b1 LH neurons to aversion is context dependent. It is diminished in starved flies, although PD2a1/b1 neural activity remains unchanged, and at lower odor concentration. In addition, PD2a1/b1 aversive effect develops over time. Thus, our results indicate that, even though PD2a1/b1 LH neurons transmit hard-wired output, their effect on valence can change. Taken together, we suggest that the valence model described for MBONs does not hold for LH neurons.
Fasentin diminishes endothelial cell proliferation, differentiation and invasion in a glucose metabolism-independent manner
Authors: Ocaña Mª Carmen , Martínez-Poveda Beatriz , Marí-Beffa Manuel , Quesada Ana R. , Medina Miguel Ángel 
Published: April 2020

AbstractThe synthetic compound fasentin has been described as a modulator of GLUT-1 and GLUT-4 transporters, thus inhibiting glucose uptake in some cancer cells. Endothelial glucose metabolism has been recently connected to angiogenesis and it is now an emerging topic in scientific research. Indeed, certain compounds with a known effect on glucose metabolism have also been shown to inhibit angiogenesis. In this work we tested the capability of fasentin to modulate angiogenesis in vitro and in vivo. We show that fasentin inhibited tube formation in endothelial cells by a mechanism that involves a negative effect on endothelial cell proliferation and invasion, without affecting other steps related to the angiogenic process. However, fasentin barely decreased glucose uptake in human dermal microvascular endothelial cells and the GLUT-1 inhibitor STF-31 failed to inhibit tube formation in these cells. Therefore, this modulatory capacity on endothelial cells function exerted by fasentin is most likely independent of a modulation of glucose metabolism. Taken together, our results show a novel biological activity of fasentin, which could be evaluated for its utility in cancer and other angiogenesis-dependent diseases.
Indication of Thalamo-Cortical Circuit Dysfunction in Idiopathic Normal Pressure Hydrocephalus: A Diffusion Tensor Imaging Study
Authors: Eleftheriou Andreas , Blystad Ida , Tisell Anders , Gasslander Johan , Lundin Fredrik 
Published: April 2020

AbstractIdiopathic normal pressure hydrocephalus (iNPH) is a disorder with unclear pathophysiology. The diagnosis of iNPH is challenging due to its radiological similarity with other neurodegenerative diseases and ischemic subcortical white matter changes. By using Diffusion Tensor Imaging (DTI) we explored differences in apparent diffusion coefficient (ADC) and fractional anisotropy (FA) in iNPH patients (before and after a shunt surgery) and healthy individuals (HI) and we correlated the clinical results with DTI parameters. Thirteen consecutive iNPH-patients underwent a pre- and post-operative clinical work-up: 10 m walk time (w10mt) steps (w10ms), TUG-time (TUGt) and steps (TUGs); for cognitive function MMSE. Nine HI were included. DTI was performed before and 3 months after surgery, HI underwent DTI once. DTI differences analyzed by manually placing 12 regions-of-interest. In patients motor and balance function improved significantly after surgery (p = 0.01, p = 0.025). Higher nearly significant FA values found in the patients vs HI pre-operatively in the thalamus (p = 0.07) accompanied by an almost significant lower ADC (p = 0.08). Significantly FA and ADC-values were found between patients and HI in FWM (p = 0.02, p = 0.001) and almost significant (p = 0.057) pre- vs postoperatively. Postoperatively we found a trend towards the HIs FA values and a strong significant negative correlation between FA changes vs. gait results in the FWM (r = −0.7, p = 0.008). Our study gives a clear indication of an ongoing pathological process in the periventricular white matter, especially in the thalamus and in the frontal white matter supporting the hypothesis of a shunt reversible thalamo-cortical circuit dysfunction in iNPH.
A combination of genetics and microbiota influences the severity of the obesity phenotype in diet-induced obesity
Authors: Smoczek Margarethe , Vital Marius , Wedekind Dirk , Basic Marijana , Zschemisch Nils-Holger , Pieper Dietmar H. , Siebert Anja , Bleich Andre , Buettner Manuela 
Published: April 2020

AbstractObesity has emerged as a major global health problem and is associated with various diseases, such as metabolic syndrome, type 2 diabetes mellitus, and cardiovascular diseases. The inbred C57BL/6 mouse strain is often used for various experimental investigations, such as metabolic research. However, over time, genetically distinguishable C57BL/6 substrains have evolved. The manifestation of genetic alterations has resulted in behavioral and metabolic differences. In this study, a comparison of diet-induced obesity in C57BL/6JHanZtm, C57BL/6NCrl and C57BL/6 J mice revealed several metabolic and immunological differences such as blood glucose level and cytokine expression, respectively, among these C57BL/6 substrains. For example, C57BL/6NCrl mice developed the most pronounced adiposity, whereas C57BL/6 J mice showed the highest impairment in glucose tolerance. Moreover, our results indicated that the immunological phenotype depends on the intestinal microbiota, as the cell subset composition of the colon was similar in obese ex-GF B6NRjB6JHanZtm and obese B6JHanZtm mice. Phenotypic differences between C57BL/6 substrains are caused by a complex combination of genetic and microbial alterations. Therefore, in performing metabolic research, considering substrain-specific characteristics, which can influence the course of study, is important. Moreover, for unbiased comparison of data, the entire strain name should be shared with the scientific community.
Quadratic Mutual Information based Regression for Prediction of Quality Variable in Batch Process
Authors: Li Zheng , Wang Pu , Gao Xuejin , Qi Yongsheng , Gao Huihui 
Published: April 2020

Abstract
Quality prediction is of great importance for batch processes. Predicting quality variable is a challenging task because of various factors such as strong nonlinearity and non-Gaussian exist in batch data. A quadratic mutual information based regression method is proposed to handle the problem. The proposed method takes into account higher order statistics that reveal the non-linear dependencies between the process variables and important quality variables. Furthermore, the proposed method is implemented without the hypothesis of Gaussian distribution of the dataset as in MPLS. The effectiveness of the QMIR method is illustrated by a dataset of industrial Escherichia coli fermentation process, compared with MPLS.
Indoor Positioning by Weighted Fuzzy Matching in Lifi Based Hospital Ward Environment
Authors: Kyung Yu Ho , Gon Kim Jeong 
Published: April 2020

Abstract
Core technologies of the fourth industrial revolution include AI (Artificial Intelligence), IoT (Internet of Things), and Big Data. The field of effective use of these technologies is the field of navigation. However, in indoor navigation, the accuracy is very low due to objects and walls placed in various positions. In this paper, we propose an indoor location tracking technology based on LiFi (Light Fidelity) communication to determine the exact location of a user using location tracking technology and communication technology. First of all, the fingerprinting database is constructed by measuring the CIR (Channel Impulse Response) value of each SP (Sample Point) using the fingerprinting technique. Then we use the Weighted Fuzzy Matching Algorithm to track the user’s location. The simulation results show that the performance of the LiFi environment is superior to that of the WiFi (Wireless Fidelity) environment.
Realization of A Deformable Wheel Adapting to Running Conditions
Authors: Chen Yaowei , Iwase Masmi , Inoue Jun , Hatakeyama Shoshiro , Suyama Atsusi 
Published: April 2020

Abstract
The problem of the aging society has become more serious, and the use rate of the mobile auxiliary equipment such as wheelchair has increased. Moreover, the situation of the ground on which such wheelchairs run becomes complicated by the urbanization progress, and especially, for the rough terrain and the obstacle, the elderly and the their caregivers meet difficulties to pass through due to such as the distance and the external force. According to this situation, a new mobility device adapted to various running environments is required. This research has proposed a deformable wheel to overcome these issues. The deformation wheel was designed to be able to run in the rough plane such as a step, and it runs only by the rotation motion of the wheel, with the expansion mechanism with the variable diameter hub added, while retaining the performance of the circular wheel which can run on the high efficiency and high speed in the plane.
Construction of SLAM Algorithm for Window Cleaning Robot Moving Along Window Frame
Authors: Sasaki Shintaro , Hatakeyama Shoshiro , Iwase Masami , Nansai Shunsuke 
Published: April 2020

Abstract
The purpose of this study is to build SLAM algorithm for window cleaning robot which move along window frame. Automation of window cleaning in skyscraper by a robot is desired. It’s necessary for cleaning to the corner of window that the robot which move on the windowpane wall recognizes shape of the window frame and to estimations self-localization on the windowpane wall. However, since it is difficult to detect the glass surface directly with a non-contact sensor, it is not possible to acquire the features necessary for SLAM. Therefore, the window frame is detected as a feature point by the RGB-D sensor, and the SLAM algorithm on the windowpane wall is constructed using the detected feature value. In this paper, various window frame shapes are prepared, distance information from the RGB-D sensor to the window frame is acquired, and the results obtained as 3D information and the feature value acquisition results by image processing are described.
Weak Reverse attention with Context Aware for Person Re-identification
Authors: Gong Ke , Ning Xin , Yu Hanchao , Zhang Liping , Sun Linjun 
Published: April 2020

Abstract
Person re-identification is a difficult topic in computer vision. Some study think that current deep learning methods is biased to capture the most discriminative features and ignore low-level details, more serious is it pay too much attention on relevance between background appearances of person images. It might limit their accuracy or makes them needlessly expensive for a not best performance. In this paper, we carefully design the Weak Reverse attention with Context Aware Network (WRCANet). Specifically, by merging weak reverse attention network and content aware module, the model can not only remove the background noise to extract the main information of persons, but also suppress the loss of local detailed information as the network deepens. We experiment on the Market-1501, DukeMTMC-reID and CUHK03, and the results show that our method achieves the state-of-the-art performance.
Generalization and Visual Comprehension of CNN Models on Chromosome Images
Authors: Wang Chengyu , Huang Daiyun , Su Jionglong , Yu Limin , Ma Fei 
Published: April 2020

Abstract
Computer-aided image classification has achieved start-of-the-art performance since Convolutional Neural Network structures were employed. Classical neural networks such as AlexNet and VGG-Net inspired several rules of designing network models. Besides benchmark datasets such as MNIST, CIFAR and ImageNet, classification performance of medical images such as chromosome karyotyping images also improved via Convolutional Neural Network. However, there are few studies on generalization among different datasets. In this paper, we designed a neural network with nine layers, and achieved classification accuracy of 0.984, 0.816 and 0.921 on the dataset of MNIST, CIFAR and chromosome karyotype images. We also visualized the output of several layers of the model and explained that smooth output between neural network layers may induce lower accuracy on classification.
Control Performance Optimization of Variable Cycle Aero-engine Based on MTLBO
Authors: Qian Yifan , Ye Zhifeng , Xu Yongyuan , Zhang Haibo 
Published: April 2020

Abstract
In view of the characteristics of variable cycle aero-engine with many adjustable variables, Modified Teaching-Learning-Based Optimization (MTLBO) algorithm is adopted to construct an optimization program to optimize the steady-state performance of multi-variable. Under the condition of non-afterburner single-duct with constant main fuel flow, the maximum thrust is optimized under the operation points of low altitude & speed and high altitude & speed, respectively based on MTLBO algorithm. The results show that the convergence of the optimization algorithm is stable, and the possibility of falling into local optimum can be avoided, which proves that the MTLBO algorithm can solve the performance optimization problem of variable cycle aero-engine.
Oleoresin yield of Pinus merkusii trees from East Banyumas
Authors: Lukmandaru G , Amri S , Sunarta S , Listyanto T , Pujiarti R , Widyorini R 
Published: April 2020

Abstract

Pinus merkusii is the main pine found in Indonesia to produce oleoresin. The present study assessed the oleoresin yield treated by various stimulants (ETRAT, SR4, sulphuric acid, sulphuric acid-Ethepon mixtures), and relate it with several tree characteristics. Trees were selected from different two different class ages i.e. IV (16-20 years) and VII (31-35 years) and were tapped for 8 days by bark chipping method in 5 replications. The pine stand was located in East Banyumas of Perhutani. Results showed that the mixture of sulfuric acid and Ethephon gave comparatively high oleoresin yield levels. In general, tree from age class of VII exhibited higher amount of resin production than those of age class of IV. The levels of oleoresin yield were significantly correlated with tree height in 31-35-year-old trees. After combining data from the two age classes, only a positive relationship between tree diameter and oleoresin yield was measured in untreated trees. For stimulated trees, the oleoresin yield exhibited positive significant correlation coefficient with tree diameter, tree height, and crown closure for certain stimulants. The negative significant correlation was observed between oleoresin yield and site elevation. As no consistent pattern of correlations with regard to stimulating agents, it suggests that the role of other factors should be explored in future works.
Increase in accuracy forecast for electrical energy consumption of the WEM subjects using fuzzy neural networks
Authors: Fedorov Ya P , Burkovsky V L , Rutskov A L 
Published: April 2020

Abstract
This paper covers in depth functioning essence of the balancing electricity market in the Russian Federation in accordance with the current economic stimuli. Significant role of the prediction process for energy resources consumption has been noted, which has a direct influence on a pricing policy within the marked trade area. Analysis of different factors, that impact execution accuracy of the one day in advance model, was conducted. Problem of the weakly defined and unknown parameters, that influence the performance of the balancing electricity market, is suggested to resolve by means of fuzzy neural controller. The paper presents its structure and settings, and possibility to scale it to use not only as an analyzer but as an executive element in the subsystems of electric power systems. High accuracy performance of the fuzzy neural controller was shown - around (0,5-3) %, that is much higher than methods already in use (for instance, based on a coefficient of decline/growth of power consumption).
The selection of a priority package of measures for technical re-equipment and reconstruction of the district of electrical grids
Authors: Semenova N G , Chernova A D 
Published: April 2020

Abstract
Making decisions on the technical re-equipment and reconstruction of electrical grids needs analyzing a large amount of information, comparing a variety of options, evaluating the impact of a decision in the long term. Therefore, the process of formation of the package of measures is complicated. In this regard, it is necessary to develop an automated decision support system for selecting a priority package of measures for the technical re-equipment and reconstruction of the electrical grid district. The article presents the structure of the decisionmaking process for the technical re-equipment and reconstruction of the district of electrical grids, the model of formation and the method for selecting a priority package of measures. It is proposed to use graph theory for compiling a decision tree and methods of combinatorial optimization for the formation and selection of a priority package of measures. A two-level structural scheme of the decision-making process for the selection of a priority package of measures for the technical re-equipment and reconstruction of the electrical grids at the local and global levels has been developed.
Effect of carbon nanotube alignment on nanocomposite sensing performance
Authors: Lee Bo Mi , Huang Zachary , Loh Kenneth J 
Published: April 2020

Abstract
The objective of this study is to derive a numerical model of carbon nanotube (CNT)-based thin films that accurately reflect their electrical and electromechanical performance as observed through experimental tests. Although nanocomposites based on CNTs dispersed in polymer matrices have been studied extensively, their nanocomposite properties vary depending on CNT orientations. This study aimed to explain how differences in nanocomposite behavior could be revealed by numerical models considering different CNT alignment conditions. First, a percolation-based thin film model was generated by randomly dispersing CNT elements in a predefined two-dimensional domain. The degree of CNT alignment in the film was controlled by limiting the CNT elements’ maximum angle they make with respect to the film’s longitudinal axis. Then, numerical simulations on CNT-based film models were conducted. Second, multi-walled carbon nanotube (MWCNT)-epoxy films were prepared via drop casting. Alternating current was applied to the MWCNT-epoxy mixture before curing to prepare films with different degrees of CNT alignment. The electrical and electromechanical properties of these specimens were characterized, and the results were compared with simulations. Good agreement between experiments and simulations was observed.
Deformation Cones of Nested Braid Fans
Authors: Castillo Federico , Liu Fu 
Published: April 2020

AbstractGeneralized permutohedra are deformations of regular permutohedra and arise in many different fields of mathematics. One important characterization of generalized permutohedra is the Submodularity Theorem, which is related to the deformation cone of the Braid fan. We lay out general techniques for determining deformation cones of a fixed polytope and apply it to the Braid fan to obtain a natural combinatorial proof for the Submodularity Theorem. We also consider a refinement of the Braid fan, called the nested Braid fan, and construct usual (respectively, generalized) nested permutohedra that have the nested Braid fan as (respectively, a coarsening of) their normal fan. We extend many results on generalized permutohedra to this new family of polytopes, including a one-to-one correspondence between faces of nested permutohedra and chains in ordered partition posets, and a theorem analogous to the Submodularity Theorem. Finally, we show that the nested Braid fan is the barycentric subdivision of the Braid fan, which gives another way to construct this new combinatorial object.