Place recognition: An Overview of Vision Perspective

Place recognition is one of the most fundamental topics in computer vision and robotics communities, where the task is to accurately and efficiently recognize the location of a given query image. Despite years of wisdom accumulated in this field, place recognition still remains an open problem due to the various ways in which the appearance of real-world places may differ. This paper presents an overview of the place recognition literature. Since condition invariant and viewpoint invariant features are essential factors to long-term robust visual place recognition system, We start with traditional image description methodology developed in the past, which exploit techniques from image retrieval field. Recently, the rapid advances of related fields such as object detection and image classification have inspired a new technique to improve visual place recognition system, i.e., convolutional neural networks (CNNs). Thus we then introduce recent progress of visual place recognition system based on CNNs to automatically learn better image representations for places. Eventually, we close with discussions and future work of place recognition.Comment: Applied Sciences (2018

Study on the Utilization of Aphid Resistant Character in Wild Soybean. I. Aphid Resistant Performance of F2 Generation from Crosses Between Cultivated and Wild Soybeans

Three crosses between 3 cultivat ed (G. max) and 2 aphid resistant wild soybean (G. soja) lines were made to study the inheritance of resistance and segregation patterns in F 2 generation with artificial inoculation technique s. The aphid resistance of F2 plants showed continuous mono-peek distributions which are inclined towards the susceptible parents. Most F2 plants were susceptible or highly susceptible. Only about 7.2 to 10.2% of the F2 plants were resistant to soybean aphid. The segregations in 2 out of 3 crosses studied fitted the hyp othesis that there are 2 independent gene pairs controlling the aphid resistant character of the wild soybean lines (P > 0.50). The segregation of the other cross also tended to fit the 2 major gene model. These results indicated that the aphid resistance of the wild parents might be controlled by 2 independent recessive genes and some other minor genes. Supposing that the aphid resistant character was quantitatively inherited, the overall inheritability estimated from the variances of parents and F 2 populations was between 85.5% and 97.0%. Despite of the high inheritability of aphid resistance, it is recommended that the selection of resistance should be postponed to later generations such as F3 or F4 , because the scarcity of resistant genes may be recessively inherited, and the number of backcrosses made in each cycle of selection should be limited to avoid the resistant genes being lost.Originating text in Chinese.Citation: Sun, Zhiqiang, Tian, Peizhan, Wang, Jian. (1991). Study on the Utilization of Aphid Resistant Character in Wild Soybean. I. Aphid Resistant Performance of F2 Generation from Crosses Between Cultivated and Wild Soybeans. Soybean Science, 10(2), 98-103

Asymptotically Sharp Upper Bound for the Column Subset Selection Problem

This paper investigates the spectral norm version of the column subset selection problem. Given a matrix $\mathbf{A}\in\mathbb{R}^{n\times d}$ and a positive integer $k\leq\text{rank}(\mathbf{A})$, the objective is to select exactly $k$ columns of $\mathbf{A}$ that minimize the spectral norm of the residual matrix after projecting $\mathbf{A}$ onto the space spanned by the selected columns. We use the method of interlacing polynomials introduced by Marcus-Spielman-Srivastava to derive an asymptotically sharp upper bound on the minimal approximation error, and propose a deterministic polynomial-time algorithm that achieves this error bound (up to a computational error). Furthermore, we extend our result to a column partition problem in which the columns of $\mathbf{A}$ can be partitioned into $r\geq 2$ subsets such that $\mathbf{A}$ can be well approximated by subsets from various groups. We show that the machinery of interlacing polynomials also works in this context, and establish a connection between the relevant expected characteristic polynomials and the $r$-characteristic polynomials introduced by Ravichandran and Leake. As a consequence, we prove that the columns of a rank-$d$ matrix $\mathbf{A}\in\mathbb{R}^{n\times d}$ can be partitioned into $r$ subsets $S_1,\ldots S_r$, such that the column space of $\mathbf{A}$ can be well approximated by the span of the columns in the complement of $S_i$ for each $1\leq i\leq r$

Effects of different corn silage: Alfalfa silage ratios and full fat extruded soybeans on milk composition, conjugated linoleic acids content in milk fat and performance of dairy cows

The objective of this study was to investigate the effects of different corn silage : alfalfa silage ratios and full fat extruded soybeans on milk composition, especially that of conjugated linoleic acids content in milk fat and performance of dairy cows. Sixty Holstein cows were divided into 6 groups for a 12 week study. Treatments were arranged in a 2 × 3 factorial with 0 or 5% full fat extruded soybeans meal (dry matter basis) and three forage treatments (dry matter basis): (1) 13.5% corn silage, (2) 10.1% corn silage and 4.1% alfalfa silage, (3) 6.8% corn silage and 7.8% alfalfa silage. Full fat extruded soybeans addition increased the ether extract in diets and content of conjugated linoleic acids in milk, but it had no effect on fat, protein and lactose content in milk. Milk fat and lactose were not affected by replacing corn silage with alfalfa silage in diets. Increasing alfalfa silage content in the diets increased milk yield and milk content of conjugated linoleic acids and protein. Results from this study suggested that more alfalfa silage can be used in the diet of cow as a good source of forages.Keywords: Conjugated linoleic acid, alfalfa silage, corn silage, full fat extruded soybeansAfrican Journal of Biotechnology Vol. 9(33), pp. 5465-5464, 16 August, 201

RigNet++: Efficient Repetitive Image Guided Network for Depth Completion

Depth completion aims to recover dense depth maps from sparse ones, where color images are often used to facilitate this task. Recent depth methods primarily focus on image guided learning frameworks. However, blurry guidance in the image and unclear structure in the depth still impede their performance. To tackle these challenges, we explore an efficient repetitive design in our image guided network to gradually and sufficiently recover depth values. Specifically, the efficient repetition is embodied in both the image guidance branch and depth generation branch. In the former branch, we design a dense repetitive hourglass network to extract discriminative image features of complex environments, which can provide powerful contextual instruction for depth prediction. In the latter branch, we introduce a repetitive guidance module based on dynamic convolution, in which an efficient convolution factorization is proposed to reduce the complexity while modeling high-frequency structures progressively. Extensive experiments indicate that our approach achieves superior or competitive results on KITTI, VKITTI, NYUv2, 3D60, and Matterport3D datasets.Comment: 15 pages. arXiv admin note: text overlap with arXiv:2107.1380

Efectos del cobre disuelto sobre la supervivencia, estado antioxidante, expresión de la metalotionina-I mRNA y la respuesta fisiológica de las larvas del cangrejo de Shangai, Eriocheir sinensis (Decapoda: Brachyura)

The lethal concentration of water-borne copper in Chinese mitten crab Eriocheir sinensis larvae was tested by exposing the animals to 0, 0.1, 0.2, 0.3, 0.5 and 0.8 mg Cu L-1 at 20°C for 96 h. The 96-h median lethal concentration (LC50) and its corresponding 95% confident interval was estimated on zoea 1 larvae and megalopa larvae, respectively. Acute dissolved copper toxicity was higher for zoea 1 larvae (0.16 mg L-1) than for megalopa larvae (0.21 mg L-1). The antioxidant status, metallothionein-I mRNA expression and physiological response of the crab to copper toxicity was further investigated by exposing the megalopa larvae to 0, 0.08 and 0.16 mg Cu L-1 for 96 h. The superoxide dismutase activity, catalase activity, glutathione S-transferase (GST) activity and lipid peroxidation content of megalopa larvae increased concomitantly with the exposure time and copper concentration. MT-I mRNA expression levels were positively correlated with both the concentration and duration of copper exposure. The oxygen consumption and respiratory quotient of megalopa larvae in response to 0.16 mg L-1 copper were significantly higher than those in the control group after 96 h of exposure (P < 0.05). The results of this study highlight the potential effects of copper as a common stressor in E. sinensis larvae. MT-I and GST appear to be suitable biomarkers of environmental copper exposure stress in E. sinensis larvaeLa concentración letal de cobre disuelto se determina mediante la exposición de larvas del cangrejo de Shangai (Eriocheir sinensis) a dosis de 0, 0.1, 0.2, 0.3, 0.5 y 0.8 mg Cu L–1, a 20°C durante 96 h. La concentración letal media (LC50) y su correspondiente intervalo de confianza del 95% fueron estimados en los estadios larvales zoea I y megalopa. La toxicidad aguda del cobre disuelto fue mayor sobre larvas de zoea I (0.16 mg L–1) que sobre las de megalopa (0.21 mg L–1). El estado antioxidante, la expresión del mRNA de la metalotionina–I y la respuesta fisiológica del cangrejo a la toxicidad del cobre fueron posteriormente investigados exponiendo las larvas de megalopa a dosis de 0, 0.08 y 0.16 mg Cu L–1 durante 96 h. La actividad de la superóxido dismutasa (SOD), de la catalasa (CAT), de la glutatión-S-transferasa (GST) y la peroxidación lipídica de las larvas de megalopa se incrementó en relación con el tiempo de exposición y la concentración de cobre. Los niveles de expresión de MT-1 mRNA se correlacionaron positivamente con la concentración de cobre y el tiempo de exposición. El consumo de oxígeno y la tasa respiratoria de las larvas de megalopa fueron significativamente más elevadas que las del grupo control (P < 0.05) en respuesta a dosis de 0.16 mg Cu L–1, durante 96 h de exposición. Los resultados presentados en este estudio ponen de manifiesto los efectos potenciales del cobre como factor de estrés sobre las larvas de E. sinensis. MT-I y GST parecen ser adecuados biomarcadores de estrés a la exposición de Cu ambiental en larvas de E. sinensis

Identification of Protein Pupylation Sites Using Bi-Profile Bayes Feature Extraction and Ensemble Learning

Pupylation, one of the most important posttranslational modifications of proteins, typically takes place when prokaryotic ubiquitin-like protein (Pup) is attached to specific lysine residues on a target protein. Identification of pupylation substrates and their corresponding sites will facilitate the understanding of the molecular mechanism of pupylation. Comparing with the labor-intensive and time-consuming experiment approaches, computational prediction of pupylation sites is much desirable for their convenience and fast speed. In this study, a new bioinformatics tool named EnsemblePup was developed that used an ensemble of support vector machine classifiers to predict pupylation sites. The highlight of EnsemblePup was to utilize the Bi-profile Bayes feature extraction as the encoding scheme. The performance of EnsemblePup was measured with a sensitivity of 79.49%, a specificity of 82.35%, an accuracy of 85.43%, and a Matthews correlation coefficient of 0.617 using the 5-fold cross validation on the training dataset. When compared with other existing methods on a benchmark dataset, the EnsemblePup provided better predictive performance, with a sensitivity of 80.00%, a specificity of 83.33%, an accuracy of 82.00%, and a Matthews correlation coefficient of 0.629. The experimental results suggested that EnsemblePup presented here might be useful to identify and annotate potential pupylation sites in proteins of interest. A web server for predicting pupylation sites was developed