bluuebunny/crossref_metadata_2025 huggingface dataset:
Movie Question Answering: Remembering the Textual Cues for Layered Visual Contents
Authors: Wang Bo , Xu Youjiang , Han Yahong , Hong Richang
Published: June 2022

Movies provide us with a mass of visual content as well as attracting stories. Existing methods have illustrated that understanding movie stories through only visual content is still a hard problem. In this paper, for answering questions about movies, we put forward a Layered Memory Network (LMN) that represents frame-level and clip-level movie content by the Static Word Memory module and the Dynamic Subtitle Memory module, respectively. Particularly, we firstly extract words and sentences from the training movie subtitles. Then the hierarchically formed movie representations, which are learned from LMN, not only encode the correspondence between words and visual content inside frames, but also encode the temporal alignment between sentences and frames inside movie clips. We also extend our LMN model into three variant frameworks to illustrate the good extendable capabilities. We conduct extensive experiments on the MovieQA dataset. With only visual content as inputs, LMN with frame-level representation obtains a large performance improvement. When incorporating subtitles into LMN to form the clip-level representation, we achieve the state-of-the-art performance on the online evaluation task of 'Video+Subtitles'. The good performance successfully demonstrates that the proposed framework of LMN is effective and the hierarchically formed movie representations have good potential for the applications of movie question answering.
R-FCN++: Towards Accurate Region-Based Fully Convolutional Networks for Object Detection
Authors: Li Zeming , Chen Yilun , Yu Gang , Deng Yangdong
Published: June 2022

Region based detectors like Faster R-CNN and R-FCN have achieved leading performance on object detection benchmarks. However, in Faster R-CNN, RoI pooling is used to extract feature of each region, which might harm the classification as the RoI pooling loses spatial resolution. Also it gets slow when a large number of proposals are utilized. R-FCN is a fully convolutional structure that uses a position-sensitive pooling layer to extract prediction score of each region, which speeds up network by sharing computation of RoIs and prevents the feature map from losing information in RoI-pooling. But R-FCN can not benefit from fully connected layer (or global average pooling), which enables Faster R-CNN to utilize global context information. In this paper, we propose R-FCN++ to address this issue in two-fold: first we involve Global Context Module to improve the classification score maps by adopting large, separable convolutional kernels. Second we introduce a new pooling method to better extract scores from the score maps, by using row-wise or column-wise max pooling. Our approach achieves state-of-the-art single-model results on both Pascal VOC and MS COCO object detection benchmarks, 87.3% on Pascal VOC 2012 test dataset and 42.3% on COCO 2015 test-dev dataset. Code will be made publicly available.
Deep Stereo Matching With Explicit Cost Aggregation Sub-Architecture
Authors: Yu Lidong , Wang Yucheng , Wu Yuwei , Jia Yunde
Published: June 2022

Deep neural networks have shown excellent performance for stereo matching. Many efforts focus on the feature extraction and similarity measurement of the matching cost computation step while less attention is paid on cost aggregation which is crucial for stereo matching. In this paper, we present a learning-based cost aggregation method for stereo matching by a novel sub-architecture in the end-to-end trainable pipeline. We reformulate the cost aggregation as a learning process of the generation and selection of cost aggregation proposals which indicate the possible cost aggregation results. The cost aggregation sub-architecture is realized by a two-stream network: one for the generation of cost aggregation proposals, the other for the selection of the proposals. The criterion for the selection is determined by the low-level structure information obtained from a light convolutional network. The two-stream network offers a global view guidance for the cost aggregation to rectify the mismatching value stemming from the limited view of the matching cost computation. The comprehensive experiments on challenge datasets such as KITTI and Scene Flow show that our method outperforms the state-of-the-art methods.
Residual Encoder Decoder Network and Adaptive Prior for Face Parsing
Authors: Guo Tianchu , Kim Youngsung , Zhang Hui , Qian Deheng , Yoo ByungIn , Xu Jingtao , Zou Dongqing , Han Jae-Joon , Choi Changkyu
Published: June 2022

Face Parsing assigns every pixel in a facial image with a semantic label, which could be applied in various applications including face recognition, facial beautification, affective computing and animation. While lots of progress have been made in this field, current state-of-the-art methods still fail to extract real effective feature and restore accurate score map, especially for those facial parts which have large variations of deformation and fairly similar appearance, e.g. mouth, eyes and thin eyebrows. In this paper, we propose a novel pixel-wise face parsing method called Residual Encoder Decoder Network (RED-Net), which combines a feature-rich encoder-decoder framework with adaptive prior mechanism. Our encoder-decoder framework extracts feature with ResNet and decodes the feature by elaborately fusing the residual architectures in to deconvolution. This framework learns more effective feature comparing to that learnt by decoding with interpolation or classic deconvolution operations. To overcome the appearance ambiguity between facial parts, an adaptive prior mechanism is proposed in term of the decoder prediction confidence, allowing refining the final result. The experimental results on two public datasets demonstrate that our method outperforms the state-of-the-arts significantly, achieving improvements of F-measure from 0.854 to 0.905 on Helen dataset, and pixel accuracy from 95.12% to 97.59% on the LFW dataset. In particular, convincing qualitative examples show that our method parses eye, eyebrow, and lip regins more accurately.
Visual Relationship Detection With Deep Structural Ranking
Authors: Liang Kongming , Guo Yuhong , Chang Hong , Chen Xilin
Published: June 2022

Visual relationship detection aims to describe the interactions between pairs of objects. Different from individual object learning tasks, the number of possible relationships are much larger, which makes it hard to explore only based on the visual appearance of objects. In addition, due to the limited human effort, the annotations for visual relationships are usually incomplete which increases the difficulty of model training and evaluation. In this paper, we propose a novel framework, called Deep Structural Ranking, for visual relationship detection. To complement the representation ability of visual appearance, we integrate multiple cues for predicting the relationships contained in an input image. Moreover, we design a new ranking objective function by enforcing the annotated relationships to have higher relevance scores. Unlike previous works, our proposed method can both facilitate the co-occurrence of relationships and mitigate the incompleteness problem. Experimental results show that our proposed method outperforms the state-of-the-art on the two widely used datasets. We also demonstrate its superiority in detecting zero-shot relationships.
Audio Visual Attribute Discovery for Fine-Grained Object Recognition
Authors: Zhang Hua , Cao Xiaochun , Wang Rui
Published: June 2022

Current progresses on fine-grained recognition are mainly focus on learning the discriminative feature representation via introducing the visual supervisions e.g. part labels. However, it is time-consuming and needs the professional knowledge to obtain the accuracy annotations. Different from these existing methods based on the visual supervisions, in this paper, we introduce a novel feature named audio visual attributes via discovering the correlations between the visual and audio representations. Specifically, our unified framework is training with video-level category label, which consists of two important modules, the encoder module and the attribute discovery module, to encode the image and audio into vectors and learn the correlations between audio and images, respectively. On the encoder module, we present two types of feed forward convolutional neural network for the image and audio modalities. While an attention driven framework based on recurrent neural network is developed to generate the audio visual attribute representation. Thus, our proposed architecture can be implemented end-to-end in the step of inference. We exploit our models for the problem of fine-grained bird recognition on the CUB200-211 benchmark. The experimental results demonstrate that with the help of audio visual attribute, we achieve the superior or comparable performance to that of strongly supervised approaches on the bird recognition.
Multi-Scale Face Restoration With Sequential Gating Ensemble Network
Authors: Lin Jianxin , Zhou Tiankuang , Chen Zhibo
Published: June 2022

Restoring face images from distortions is important in face recognition applications and is challenged by multiple scale issues, which is still not well-solved in research area. In this paper, we present a Sequential Gating Ensemble Network (SGEN) for multi-scale face restoration issue. We first employ the principle of ensemble learning into SGEN architecture design to reinforce predictive performance of the network. The SGEN aggregates multi-level base-encoders and base-decoders into the network, which enables the network to contain multiple scales of receptive field. Instead of combining these base-en/decoders directly with non-sequential operations, the SGEN takes base-en/decoders from different levels as sequential data. Specifically, the SGEN learns to sequentially extract high level information from base-encoders in bottom-up manner and restore low level information from base-decoders in top-down manner. Besides, we propose to realize bottom-up and top-down information combination and selection with Sequential Gating Unit (SGU). The SGU sequentially takes two inputs from different levels and decides the output based on one active input. Experiment results demonstrate that our SGEN is more effective at multi-scale human face restoration with more image details and less noise than state-of-the-art image restoration models. By using adversarial training, SGEN also produces more visually preferred results than other models through subjective evaluation.
A Deep Cascade Network for Unaligned Face Attribute Classification
Authors: Ding Hui , Zhou Hao , Zhou Shaohua , Chellappa Rama
Published: June 2022

Humans focus attention on different face regions when recognizing face attributes. Most existing face attribute classification methods use the whole image as input. Moreover, some of these methods rely on fiducial landmarks to provide defined face parts. In this paper, we propose a cascade network that simultaneously learns to localize face regions specific to attributes and performs attribute classification without alignment. First, a weakly-supervised face region localization network is designed to automatically detect regions (or parts) specific to attributes. Then multiple part-based networks and a whole-image-based network are separately constructed and combined together by the region switch layer and attribute relation layer for final attribute classification. A multi-net learning method and hint-based model compression is further proposed to get an effective localization model and a compact classification model, respectively. Our approach achieves significantly better performance than state-of-the-art methods on unaligned CelebA dataset, reducing the classification error by 30.9%.
Unsupervised Articulated Skeleton Extraction From Point Set Sequences Captured by a Single Depth Camera
Authors: Lu Xuequan , Chen Honghua , Yeung Sai-Kit , Deng Zhigang , Chen Wenzhi
Published: June 2022

How to robustly and accurately extract articulated skeletons from point set sequences captured by a single consumer-grade depth camera still remains to be an unresolved challenge to date. To address this issue, we propose a novel, unsupervised approach consisting of three contributions (steps): (i) a non-rigid point set registration algorithm to first build one-to-one point correspondences among the frames of a sequence; (ii) a skeletal structure extraction algorithm to generate a skeleton with reasonable numbers of joints and bones; (iii) a skeleton joints estimation algorithm to achieve accurate joints. At the end, our method can produce a quality articulated skeleton from a single 3D point sequence corrupted with noise and outliers. The experimental results show that our approach soundly outperforms state of the art techniques, in terms of both visual quality and accuracy.
Show, Reward and Tell: Automatic Generation of Narrative Paragraph From Photo Stream by Adversarial Training
Authors: Wang Jing , Fu Jianlong , Tang Jinhui , Li Zechao , Mei Tao
Published: June 2022

Impressive image captioning results (i.e., an objective description for an image) are achieved with plenty of training pairs. In this paper, we take one step further to investigate the creation of narrative paragraph for a photo stream. This task is even more challenging due to the difficulty in modeling an ordered photo sequence and in generating a relevant paragraph with expressive language style for storytelling. The difficulty can even be exacerbated by the limited training data, so that existing approaches almost focus on search-based solutions. To deal with these challenges, we propose a sequence-to-sequence modeling approach with reinforcement learning and adversarial training. First, to model the ordered photo stream, we propose a hierarchical recurrent neural network as story generator, which is optimized by reinforcement learning with rewards. Second, to generate relevant and story-style paragraphs, we design the rewards with two critic networks, including a multi-modal and a language-style discriminator. Third, we further consider the story generator and reward critics as adversaries. The generator aims to create indistinguishable paragraphs to human-level stories, whereas the critics aim at distinguishing them and further improving the generator by policy gradient. Experiments on three widely-used datasets show the effectiveness, against state-of-the-art methods with relative increase of 20.2% by METEOR. We also show the subjective preference for the proposed approach over the baselines through a user study with 30 human subjects.
Multimodal Keyless Attention Fusion for Video Classification
Authors: Long Xiang , Gan Chuang , Melo Gerard , Liu Xiao , Li Yandong , Li Fu , Wen Shilei
Published: June 2022

The problem of video classification is inherently sequential and multimodal, and deep neural models hence need to capture and aggregate the most pertinent signals for a given input video. We propose Keyless Attention as an elegant and efficient means to more effectively account for the sequential nature of the data. Moreover, comparing a variety of multimodal fusion methods, we find that Multimodal Keyless Attention Fusion is the most successful at discerning interactions between modalities. We experiment on four highly heterogeneous datasets, UCF101, ActivityNet, Kinetics, and YouTube-8M to validate our conclusion, and show that our approach achieves highly competitive results. Especially on large-scale data, our method has great advantages in efficiency and performance. Most remarkably, our best single model can achieve 77.0% in terms of the top-1 accuracy and 93.2% in terms of the top-5 accuracy on the Kinetics validation set, and achieve 82.2% in terms of GAP@20 on the official YouTube-8M test set.
DLPaper2Code: Auto-Generation of Code From Deep Learning Research Papers
Authors: Sethi Akshay , Sankaran Anush , Panwar Naveen , Khare Shreya , Mani Senthil
Published: June 2022

With an abundance of research papers in deep learning, reproducibility or adoption of the existing works becomes a challenge. This is due to the lack of open source implementations provided by the authors. Even if the source code is available, then re-implementing research papers in a different library is a daunting task. To address these challenges, we propose a novel extensible approach, DLPaper2Code, to extract and understand deep learning design flow diagrams and tables available in a research paper and convert them to an abstract computational graph. The extracted computational graph is then converted into execution ready source code in both Keras and Caffe, in real-time. An arXiv-like website is created where the automatically generated designs is made publicly available for 5,000 research papers. The generated designs could be rated and edited using an intuitive drag-and-drop UI framework in a crowd sourced manner. To evaluate our approach, we create a simulated dataset with over 216,000 valid deep learning design flow diagrams using a manually defined grammar. Experiments on the simulated dataset show that the proposed framework provide more than 93% accuracy in flow diagram content extraction.
Mix-and-Match Tuning for Self-Supervised Semantic Segmentation
Authors: Zhan Xiaohang , Liu Ziwei , Luo Ping , Tang Xiaoou , Loy Chen
Published: June 2022

Deep convolutional networks for semantic image segmentation typically require large-scale labeled data, e.g., ImageNet and MS COCO, for network pre-training. To reduce annotation efforts, self-supervised semantic segmentation is recently proposed to pre-train a network without any human-provided labels. The key of this new form of learning is to design a proxy task (e.g., image colorization), from which a discriminative loss can be formulated on unlabeled data. Many proxy tasks, however, lack the critical supervision signals that could induce discriminative representation for the target image segmentation task. Thus self-supervision’s performance is still far from that of supervised pre-training. In this study, we overcome this limitation by incorporating a "mix-and-match" (M&M) tuning stage in the self-supervision pipeline. The proposed approach is readily pluggable to many self-supervision methods and does not use more annotated samples than the original process. Yet, it is capable of boosting the performance of target image segmentation task to surpass fully-supervised pre-trained counterpart. The improvement is made possible by better harnessing the limited pixel-wise annotations in the target dataset. Specifically, we first introduce the "mix" stage, which sparsely samples and mixes patches from the target set to reflect rich and diverse local patch statistics of target images. A ‘match’ stage then forms a class-wise connected graph, which can be used to derive a strong triplet-based discriminative loss for finetuning the network. Our paradigm follows the standard practice in existing self-supervised studies and no extra data or label is required. With the proposed M&M approach, for the first time, a self-supervision method can achieve comparable or even better performance compared to its ImageNet pretrained counterpart on both PASCAL VOC2012 dataset and CityScapes dataset.
Accelerated Training for Massive Classification via Dynamic Class Selection
Authors: Zhang Xingcheng , Yang Lei , Yan Junjie , Lin Dahua
Published: June 2022

Massive classification, a classification task defined over a vast number of classes (hundreds of thousands or even millions), has become an essential part of many real-world systems, such as face recognition. Existing methods, including the deep networks that achieved remarkable success in recent years, were mostly devised for problems with a moderate number of classes. They would meet with substantial difficulties, e.g., excessive memory demand and computational cost, when applied to massive problems. We present a new method to tackle this problem. This method can efficiently and accurately identify a small number of "active classes" for each mini-batch, based on a set of dynamic class hierarchies constructed on the fly. We also develop an adaptive allocation scheme thereon, which leads to a better tradeoff between performance and cost. On several large-scale benchmarks, our method significantly reduces the training cost and memory demand, while maintaining competitive performance.
Transfer Adversarial Hashing for Hamming Space Retrieval
Authors: Cao Zhangjie , Long Mingsheng , Huang Chao , Wang Jianmin
Published: June 2022

Hashing is widely applied to large-scale image retrieval due to the storage and retrieval efficiency. Existing work on deep hashing assumes that the database in the target domain is identically distributed with the training set in the source domain. This paper relaxes this assumption to a transfer retrieval setting, which allows the database and the training set to come from different but relevant domains. However, the transfer retrieval setting will introduce two technical difficulties: first, the hash model trained on the source domain cannot work well on the target domain due to the large distribution gap; second, the domain gap makes it difficult to concentrate the database points to be within a small Hamming ball. As a consequence, transfer retrieval performance within Hamming Radius 2 degrades significantly in existing hashing methods. This paper presents Transfer Adversarial Hashing (TAH), a new hybrid deep architecture that incorporates a pairwise t-distribution cross-entropy loss to learn concentrated hash codes and an adversarial network to align the data distributions between the source and target domains. TAH can generate compact transfer hash codes for efficient image retrieval on both source and target domains. Comprehensive experiments validate that TAH yields state of the art Hamming space retrieval performance on standard datasets.
Biocement treatment for upcycling construction and demolition wastes as concrete aggregates
Authors: Mistri Abhijit , Dhami Navdeep , Bhattacharyya Sriman Kumar , Barai Sudhirkumar V. , Mukherjee Abhijit
Published: June 2022

Reutilisation of the construction and demolition (C&D) wastes as aggregate in concrete is a vital step towards sustainability as it prevents depletion of natural resources as well as alleviates wastes. However, the attached mortar on the aggregate surface renders certain shortcomings like excessive water absorption, high porosity, and weak interfaces. Recycled aggregates can be treated to improve these shortcomings. However, the minimisation of the drawbacks involves huge energy, materials, and cost. Moreover, the efficacy of such adopted method is sometime questionable, and which needs further research. This study demonstrates bio-treatment of recycled coarse aggregate (RCA) as a means of upcycling and compares it with conventional cement slurry treatment. A novel spraying technique has been applied that significantly economises biocement treatment. The experimental results show that biocement treatment reduced the water absorption by 70%. The treatment has filled the pores of RCA and has prevented water absorption. In contrast, cement slurry coating treatment shows increase in water absorption of RCA by 19%. The compressive strength of concrete with 100% biocement treated RCA surpasses that of concrete with natural coarse aggregates. The genesis of this dramatic improvement in case of biocement has been established through micro-scale studies including scanning electron microscopy and energy-dispersive X-ray spectroscopy. The cost analysis demonstrates that RCA upcycled with biocement treatment is more economical than natural aggregates or cement treated ones. Findings of the present study led to the conclusion that 100% replacement of natural coarse aggregates can be achieved by upcycling C&D wastes as coarse aggregate through bio-treatment.
Liberatory violence or the gift: paths to decoloniality in Black Panther
Authors: Mabasa Xiletelo , Boshoff Priscilla
Published: June 2022

Black Panther's (Coogler 2018) popularity amongst its black audiences in part stems from its foregrounding of the persistent social injustices engendered by colonialism and slavery (what Aníbal Quijano (2000:533) terms 'coloniality') and black people's struggles to overcome them. As a representational tactic in approaching this theme, the Hollywood blockbuster draws on the imaginings of Afrofuturism, which variously endorses radical or more conciliatory approaches to decoloniality. This southern theoretical approach and the critique of coloniality offered by Afrofuturism frame our exploration of how the film positions the hero, T'Challa and the villain, Erik Killmonger, as embodiments of contrasting approaches to emancipation from colonialism's entrenched legacy. Using a structuralist approach that draws on the narrative models of Tsvetan Todorov, Vladimir Propp and Claude Levi-Strauss, we analyse the film's approach to decoloniality by examining the relationship between T'Challa and Killmonger as the protagonist and antagonist respectively. The analysis reveals the limitations of the film's construction of the hero's and villain's understandings of the path to liberation. Rather than offering a revolutionary remedy for the injustices of colonialism and its aftermath, the film embraces a liberal standpoint that remains palatable to the white establishment, both within Hollywood and the broader socio-political milieu.
[RETRACTED] Pioneer Woman CBD Gummies Reviews: Best Gummy Bears In USA v1
Authors: not provided pioneerwomangummireviews
Published: June 2022

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[RETRACTED] Exposed (Scam or Legit) Condor CBD Gummies Reviews Shark Tank Price Benefit Ingredient 2022? v1
Authors: CBD Gummies Reviews Condor
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[RETRACTED] Applied Science Keto v1
Authors: Shi H
Published: June 2022

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Immunohistochemistry of liver tissue sections v1
Authors: Rajbhandari Presha
Published: June 2022

This protocol outlines the steps used to perform standard immunohistochemistry for antibody validation in frozen human liver tissue samples, performed at Molecular Pathology Core facility at Columbia University.
[RETRACTED] Oprah Winfrey Keto Gummies v1
Authors: not provided jamshruckz
Published: June 2022

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[RETRACTED] Vigorplex Reviews v1
Authors: A J
Published: June 2022

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[RETRACTED] Keto Blast Gummies CanadaDiet Pills Easily Decrease Your Body Weight in 1 week? v1
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[RETRACTED] Prodentim Reviews: Does Prodentim advanced oral probiotics Works For Gums& Teeth? v1
Authors: not provided tryProDentim
Published: June 2022

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Conflictos por el agua y el uso de agroquímicos en Salta y Santiago del Estero, Argentina: un análisis desde la ecología política
Authors: Schmidt Mariana , Tobías Melina , Toledo López Virginia , Merlinsky María Gabriela
Published: June 2022

Este artículo explora las consecuencias del uso de agroquímicos en Salta y Santiago del Estero, provincias del norte argentino. Ofrece una caracterización y análisis del rol de las autoridades competentes y las normativas, así como un abordaje de la conflictividad en torno a las consecuencias de las fumigaciones, con énfasis en la contaminación del agua y sus efectos en la salud. A partir de fuentes secundarias y de entrevistas con diferentes actores, los hallazgos muestran que existen leyes específicas y cierta institucionalidad destinada a la conservación ambiental en general y de los recursos hídricos en particular, junto con normas que regulan el uso de agroquímicos. No obstante, existen conflictos que, con diverso grado de visibilidad, problematizan los efectos sanitarios y ambientales en las escalas locales. En consecuencia, la crítica situación sanitaria e hídrica regional se vuelve central, a través de renovados interrogantes que emergen desde una perspectiva de justicia ambiental.
Drinking water tariff policy: vulnerability, regulation, and sustainability in the Colombian case
Authors: GONZALEZ PEREZ MARIO GUADALUPE
Published: June 2022

Until four years ago, regulations of the drinking water consumption in Colombia did not consider climate change variables and national and international water-urban guidelines in its rate policy. In this sense, it is proposed to determine the scenario of the basic water consumption through a normative revision implemented to guarantee the supply, considering the six socioeconomic strata and classifying three types of cities according to the water endowment and geographic location. It was found, that the Bogotá city shows an initial increase of 58% for stratum 1, which can be considered as high, compared with Medellín and Cali cities (53% and 43%). Hence, changes presented in resolution CRA/750/2016, according to a new consumption of household public services of the Aqueduct, have a large impact on the economy of families, especially for strata 1, 2, and 3.
The Concept and Types of Preliminary Analysis of Material Traces, their Legal and Forensic Aspects
Authors: Korma V. D.
Published: June 2022

The paper deals with the theoretical problems of understanding preliminary forensic analysis of material traces, their distinguished types, technological essence, goals, objectives, as well as the subjects of these studies. Based on an analysis of modern forensic and legal literature, the author concludes that preliminary forensic analysis is undoubtedly non-procedural in nature and is carried out on the basis of special knowledge, relevant technical and forensic tools and methods, and information support. These are applied both in an inspection of the scene and other investigative actions in non-laboratory (field) conditions, and in laboratory conditions on the basis of a written task of the body of inquiry, empowered to carry out operational-search activities. It is also carried out when checking objects for forensic records in order to obtain guiding information about the relevance of the objects under study, their characteristics used to identify the persons involved in the criminal event, the mechanism of trace formation, crime instruments, other items and substances that are important for the detection and investigation of crimes. The paper emphasizes that at present only an expert (forensic specialist — for objects of traditional forensic research, other specialists — for objects of non-traditional research) can be a subject in the field of technology for the direct conduct of all types of preliminary forensic research. At the same time, the methodological support of these studies has a simplified (lighter) design in comparison with the methods of expert conclusions.
Working with Dynamic Earthquake Rupture Models: A Practical Guide
Authors: Ramos Marlon D. , Thakur Prithvi , Huang Yihe , Harris Ruth A. , Ryan Kenny J.
Published: June 2022

Dynamic rupture models are physics-based simulations that couple fracture mechanics to wave propagation and are used to explain specific earthquake observations or to generate a suite of predictions to understand the influence of frictional, geometrical, stress, and material parameters. These simulations can model single earthquakes or multiple earthquake cycles. The objective of this article is to provide a self-contained and practical guide for students starting in the field of earthquake dynamics. Senior researchers who are interested in learning the first-order constraints and general approaches to dynamic rupture problems will also benefit. We believe this guide is timely given the recent growth of computational resources and the range of sophisticated modeling software that are now available. We start with a succinct discussion of the essential physics of earthquake rupture propagation and walk the reader through the main concepts in dynamic rupture model design. We briefly touch on fully dynamic earthquake cycle models but leave the details of this topic for other publications. We also highlight examples throughout that demonstrate the use of dynamic rupture models to investigate various aspects of the faulting process.
ESTUDOS AMBIENTAIS PARA AVALIAÇÃO DAS RESPOSTAS FISIOLÓGICAS DA ESPÉCIE RAPANEA FERRUGINEA SUBMETIDAS A DIFERENTES CONDIÇÕES DE INCIDÊNCIA SOLAR POR ESPECTROSCOPIA NO INFRAVERMELHO COM TRANSFORMADA DE FOURIER (FTIR-ATR)
Authors: Lins Evandro Faria , Aquino-Silva Maria Regina de , Sakane Kumiko Koibuchi
Published: June 2022

With the advances in technology, the use of computer programs has become increasingly present in scientific research. Fourier-transform infrared spectroscopy (FTIR-ATR) combined with computational analysis is an important technique used in environmental studies to characterize biological systems. This technique studies how the chemical bonds present in the molecules interact with the radiation in the infrared range of the electromagnetic spectrum (10-6 to 10-3m) turning into vibrational energy, graphically represented in the form of an infrared spectrum. This study aimed to qualitative and quantitative analysis of lignin, starch and chlorophyll in leaf of Rapanea ferruginea (common name: capororoca) subject to different conditions of sunlight. To establish the different conditions of sunlight were made four frames in wood lined with shading screen in percentages by 30%, 50%, 70% and 85% shading. The seedlings were divided into five groups, each group being arranged in a frame, except one that was willing to full sun (frameless). The sample collection was carried out after expiry of a month from the beginning of the experiment. The infrared spectra of the samples were obtained in the range 4.000 to 450cm-1. The absorbance ratio between the aromatic ring of the absorption band (1.609cm-1) C-N-C (1.159cm-1) and C-O (1.034cm-1) with the C-H stretching band (2.917cm-1) were considered to determine the amounts of lignin, starch and chlorophyll, respectively. From the quantification of these three constituents, the most favorable condition for the development of the plant is 70% shading, followed by 50% shading, 30% shading, 85% shading and last is the full sun.
Perfil socioeconômico de Caxias do Sul 2021
Authors: Fachinelli Ana Cristina , Giacomello Cíntia Paese , Libardi Bianca , Borsatto Catiane , Lucena Perini Rafael de , Atayde Moschen Suane de , Bebber Suélen
Published: June 2022

Ao produzir este perfil socioeconômico, analisamos a estrutura social e econômica de Caxias do Sul. Destacamos em todo o material as qualidades de Caxias do Sul, apresentando-o como um ambiente favorável para viver com qualidade de vida e desenvolver negócios. Esta publicação consolida diversas informações sobre Caxias do Sul e serve como referência para apoiar decisões de investimento, formulação de políticas, informar os visitantes e o público sobre os ativos e passivos do município, e seus fatos socioeconômicos. A revista Perfil Socioeconômico de Caxias do Sul tem como objetivo apresentar à comunidade os aspectos que mais se destacam na cidade. Os eixos temáticos foram definidos e, com base neles, são apresentados os dados primários obtidos de fontes oficiais. Séries históricas e comparações com dados estatais e nacionais nos permitem posicionar Caxias do Sul em relação a outros lugares. A responsabilidade pela coleta e análise dos dados cabe à equipe da Citylivinglab, um grupo de pesquisa do Programa de Pós-Graduação em Administração da Universidade de Caxias do Sul. A publicação é baseada em dados secundários, e todas as fontes são citadas em toda a revista. Sempre utilizamos os dados mais recentes disponíveis.
Estrategias empleadas por pequeños productores de quinua real para llegar al mercado agroalimentario global
Authors: Valdivia Gabriel , Vera Villanueva Nestor , Valdivia Bondarenko Fabián ,   BID Invest
Published: June 2022

La quinua orgánica y convencional, es uno de los rubros agrícolas de mayor importancia económica y social para Bolivia y Perú, por su rol en la seguridad alimentaria y aporte a las exportaciones no tradicionales de ambos países, es una de las cadenas productiva que ha crecido en forma consistente en los 20 últimos años, tanto en superficie y rendimiento, como en volumen de exportaciones, gracias a un marco político y normativo dinámico, e inversiones público privadas en toda la cadena de valor. El estudio intenta dar respuesta a las preguntas centrales de la investigación ¿Qué explica la integración exitosa de las asociaciones y empresas bolivianas y peruanas en los modernos mercados mundiales agroalimentarios? ¿Qué tipo de estrategias se aplicaron? ¿Cómo los gobiernos apoyaron a las organizaciones y las empresas, en su búsqueda del éxito? Las respuestas tratadas e interpretadas, se presentan en el documento a continuación en tres partes, una introductoria, que presenta conceptos e historia de la quinua, una segunda con los estudios de caso y los hallazgos en temas transversales, y una tercera, con conclusiones y recomendaciones de política pública destinada a mejorar la competitividad de los productores, empresas y países.
Geneza niepozywistycznych koncepcji prawa – zarys problematyki
Authors: Kołodziejczak Wiktor
Published: June 2022

Artykuł dotyczy przekrojowego zarysu rozwoju nurtu niepozytywistycznego w filozofii prawa, zaczynając od niemieckiej powojennej filozofii społecznej. W artykule o tej tematyce nie mogło zabraknąć obszerniejszego opracowania dotyczącego filozofii Gustawa Radbrucha i jego słynnej formuły, która sprowadza się do postulatu o koniecznym oparciu prawa stanowionego o prawo naturalne. Kolejna część artykułu dotyczy kilku autorów, których można uznać za prekursorów bądź kontynuatorów myśli niepozytywistycznej, wliczając w to Ronalda Dworkina z jego teorią zasad prawnych. W zakończeniu ujęta została ogólna refleksja na temat debat naukowych, które często bazują na niezrozumieniu stanowiska oponentów.
Morphoanatomical characterization of Brassavola tuberculata Hook´s (Orchidaceae) leaf and root upon the rocky outcrop
Authors: Silva Fernanda Maria Trindade da , Barbosa Wellington Marota , Ferreira-Júnior Walnir Gomes
Published: June 2022

Orchids have morphological and anatomical adaptations that make them able to occupy the most different environments with the most varied conditions. These adaptations, together with the physiological attributes are essential for the establishment, growth, reproduction, and colonization of orchids. Therefore, this study was developed to describe the leaf and root anatomy of Brassavola tuberculata Hook found in a phorophyte located on a rocky outcrop in Campestre, southern Minas Gerais. The collected leaf and root samples were freehand cut and stained with astra blue and safranin. The histochemical tests applied wer: sudan III for lipids and lugol for starch. The leaves are subulate, succulent and grooved containing a continuous longitudinal cannula. The epidermis has a thick cuticle, stomata with a suprastomatal chamber on both leaf faces and the mesophyll is homogeneous with aquifer parenchyma in the central portion. In the root, the velamen and cortical tissue are composed of several cell layers that allow it to store water. There were starch grains in the leaf and root. These xeromorphic characters found allow to the species to survive in the restricted conditions found in the phorophyte on rocky outcrops.
De obligaciones y pagos y finiquitos: instrumenta publica para la gestión de la vida económica en la Corona de Castilla en el siglo XVI
Authors: Marchant Rivera Alicia
Published: June 2022

Sobre la base ofrecida por los tratados de literatura notarial de la época, la finalidad del presente estudio será proporcionar el análisis de dos tipologías documentales notariales, la obligación y el pago y finiquito, estrechamente relacionadas entre sí, durante la primera mitad del siglo XVI, etapa de reinado de Carlos i (1516-1556). De esta forma, el análisis diplomático acompañará a la revisión histórica de los antecedentes legales de cada modelo y la comparativa con lo que sobre ellos aportan los diversos formularios y tratados. El corpus documental corresponde a la sección de protocolos del Archivo Histórico Provincial de Málaga, ciudad incorporada a la Corona castellana en 1487, cuyos escribanos públicos se plegaron desde los inicios a la práctica notarial consolidada desde el siglo XIII en el solar hispánico.
Sobre la funcionalidad del Derecho concursal: the second chance?
Authors: Candelario Macías María Isabel
Published: June 2022

En esta contribución se reflexiona acerca de la evolución y la virtualidad del Derecho concursal desde el enfoque que nos ofrece la legislación española, teniendo muy presentes las dificultades económicas que atraviesan los operadores dentro de la situación de pandemia ocasionada por el covid-19. Desde esta óptica, se analiza un instituto de gran interés, conocido como “segunda oportunidad” (beneficio de la exoneración del pasivo insatisfecho), que es traslación de instituciones procedentes de otras legislaciones. Se estudia cómo está reglamentado y cuáles son las cuestiones que aún están pendientes de aclarar y mejorar para que sirva a los objetivos pretendidos.
Evaluation of the Potential of Higher Education Institutions in the Context of Achieving Sustainability
Authors: Suslenco Alina
Published: June 2022

This paper represents a theoretical-methodological incursion on the requirements of higher education institutions to achieve sustainability. The relevance of the topic derives from the need to assess the potential of higher education institutions in order to achieve sustainability. The aim of the research is to assess the potential of universities in the context of sustainability. The paper focuses on making an approach to achieving educational performance, in terms of assessing the human, innovative potential of higher education institutions which represents a vital factor in achieving university sustainability. Universities as active actors in sustainable development must demonstrate the necessary training, competent human potential, viable educational policies, and effective tools to achieve sustainability. The research methodology focused on the use of the following methods such as: analysis, synthesis, qualitative research, scientific abstraction, which contributed to a comprehensive and complex study on the training of Moldovan universities to achieve sustainability. In conclusion, we reiterate that universities as “vectors of change” are demanded to develop successful strategies to achieve sustainability, in terms of certain effective activities that would ensure their sustainable development. The undertaken research allowed us to elucidate that Moldovan universities do not have a model for achieving university sustainability. In this context, we can point out the need to develop a viable tool for assessing the steps taken by universities to achieve sustainability.
Trello as a Tool for the Development of Lifelong Learning Skills of Senior Students
Authors: Shchetynina Olha , Kravchenko Nataliia , Horbatiuk Larysa , Alieksieieva Hanna , Mezhuyev Vitaliy
Published: June 2022

The article focuses on the problem of development of the lifelong learning skills of senior students in secondary school of general education. The model of interaction between the subjects of learning in the Trello project management system is developed.  The foreign literature learning environment in the Trello system is developed. The experience of using the Trello project management system in the process of teaching foreign literature in 10th and 11th grades is described. It has been found that according to the lifelong learning approach a person has to possess skills: goal setting, self-regulation, motivation, time management, self-directed learning, collaboration skills, and self-development. It was pointed out that there are common approaches to project management and educational process management. The use of online systems for collaborative work in the educational process in the secondary school of general education is suggested. Online systems for teamwork that support Kanban methodologies for project management have been analyzed. To confirm the effectiveness of the implementation of the Trello project management system as a tool for the development of lifelong learning skills of senior students, an experiment was conducted: criteria, indicators, levels, and the state of formation of lifelong learning skills of senior students were determined; statistical analysis of the results of the experiment was carried out. The effectiveness of the implementation of the Trello project management system as a tool of the formation of the lifelong learning skills of senior students has been experimentally proven. The study can be applied in educational institutions interested in using agile methods in teaching.
Artistic and Pedagogical Competences of the Fine Arts Teacher: an Adaptation to the Postmodern Society
Authors: Tomashevskyi Volodymyr , Digtiar Nataliia , Chumak Larisa , Batiievska Tetiana , Hnydina Olena , Malytska Olena
Published: June 2022

The importance of the outlined problem lies in the fact that professional training of future fine arts teachers should take into account the trends of recent general scientific, socio-cultural and moral-aesthetic processes.
Analysis of the professional training system in the context of the requirements of postmodern society gives grounds to claim that it requires significant updating. In particular, individualization and democratization of education, interdisciplinarity, departure from traditional patterns of professional training, rethinking of pedagogical ideas and postulates in the context of quality assurance, etc. are paramount.
The article defines the structure of artistic and pedagogical competence of a fine arts teacher. Its structural elements (artistic component (artistic and aesthetic education, skill)) and pedagogical component (psychological and pedagogical culture, reflection) and ways of their formation are determined.
Ways to improve professional training of future fine arts teachers taking into account the postmodern features of higher education development (ensuring continuity of creative education; updating the scope of professional training; the use of information technology in the process of professional training of future fine arts teachers; emphasis of the educational programme on personal and creative development, self-fulfilment of students of artistic specialties.
Development of pedagogical conditions for formation of artistic and pedagogical competence in future fine arts teachers and organization of a pedagogical experiment in order to determine their effectiveness seems promising.