Self-Supervised Relative Depth Learning for Urban Scene Understanding

As an agent moves through the world, the apparent motion of scene elements is (usually) inversely proportional to their depth. It is natural for a learning agent to associate image patterns with the magnitude of their displacement over time: as the agent moves, faraway mountains don't move much; nearby trees move a lot. This natural relationship between the appearance of objects and their motion is a rich source of information about the world. In this work, we start by training a deep network, using fully automatic supervision, to predict relative scene depth from single images. The relative depth training images are automatically derived from simple videos of cars moving through a scene, using recent motion segmentation techniques, and no human-provided labels. This proxy task of predicting relative depth from a single image induces features in the network that result in large improvements in a set of downstream tasks including semantic segmentation, joint road segmentation and car detection, and monocular (absolute) depth estimation, over a network trained from scratch. The improvement on the semantic segmentation task is greater than those produced by any other automatically supervised methods. Moreover, for monocular depth estimation, our unsupervised pre-training method even outperforms supervised pre-training with ImageNet. In addition, we demonstrate benefits from learning to predict (unsupervised) relative depth in the specific videos associated with various downstream tasks. We adapt to the specific scenes in those tasks in an unsupervised manner to improve performance. In summary, for semantic segmentation, we present state-of-the-art results among methods that do not use supervised pre-training, and we even exceed the performance of supervised ImageNet pre-trained models for monocular depth estimation, achieving results that are comparable with state-of-the-art methods

Unsupervised Learning of Video Representations via Dense Trajectory Clustering

This paper addresses the task of unsupervised learning of representations for action recognition in videos. Previous works proposed to utilize future prediction, or other domain-specific objectives to train a network, but achieved only limited success. In contrast, in the relevant field of image representation learning, simpler, discrimination-based methods have recently bridged the gap to fully-supervised performance. We first propose to adapt two top performing objectives in this class - instance recognition and local aggregation, to the video domain. In particular, the latter approach iterates between clustering the videos in the feature space of a network and updating it to respect the cluster with a non-parametric classification loss. We observe promising performance, but qualitative analysis shows that the learned representations fail to capture motion patterns, grouping the videos based on appearance. To mitigate this issue, we turn to the heuristic-based IDT descriptors, that were manually designed to encode motion patterns in videos. We form the clusters in the IDT space, using these descriptors as a an unsupervised prior in the iterative local aggregation algorithm. Our experiments demonstrates that this approach outperform prior work on UCF101 and HMDB51 action recognition benchmarks. We also qualitatively analyze the learned representations and show that they successfully capture video dynamics

Genotype-phenotype correlation and description of two novel mutations in Iranian patients with glycogen storage disease 1b (GSD1b)

Background: Glycogen storage disease (GSD) is a rare inborn error of the synthesis or degradation of glycogen metabolism. GSD1, the most common type of GSD, is categorized into GSD1a and GSD1b which caused by the deficiency of glucose-6-phosphatase (G6PC) and glucose-6-phosphate transporter (SLC37A4), respectively. The high rates of consanguineous marriages in Iran provide a desirable context to facilitate finding the homozygous pathogenic mutations. This study designates to evaluate the clinical and genetic characteristics of patients with GSD1b to assess the possible genotype-phenotype correlation. Results: Autozygosity mapping was performed on nineteen GSD suspected families to suggest the causative loci. The mapping was done using two panels of short tandem repeat (STR) markers linked to the corresponding genes. The patients with autozygous haplotype block for the markers flanking the genes were selected for direct sequencing. Six patients showed autozygosity in the candidate markers for SLC37A4. Three causative variants were detected. The recurrent mutation of c.10421043delCT (p.Leu348Valfs*53) and a novel missense mutation of c.365G > A (p.G122E) in the homozygous state were identified in the SLC37A4. In silico analysis was performed to predict the pathogenicity of the variants. A novel whole SLC37A4 gene deletion using long-range PCR and sequencing was confirmed as well. Severe and moderate neutropenia was observed in patients with frameshift and missense variants, respectively. The sibling with the whole gene deletion has shown both severe neutropenia and leukopenia. Conclusions: The results showed that the hematological findings may have an appropriate correlation with the genotype findings. However, for a definite genotype-phenotype correlation, specifically for the clinical and biochemical phenotype, further studies with larger sample sizes are needed. © 2020 The Author(s)

Molecular assay on Crimean Congo Hemorrhagic Fever virus in ticks (Ixodidae) collected from Kermanshah Province, Western Iran

Background: Crimean-Congo Hemorrhagic Fever (CCHF) is a feverous and hemorrhagic disease endemic in some parts of Iran and caused by an arbovirus related to Bunyaviridae family and Nairovirusgenus. The main virus reservoir in the nature is ticks, however small vertebrates and a wide range of domestic and wild animals are regarded as reservoir hosts. This study was conducted to determine the infection rate of CCHF virus in hard ticks of Sarpole- Zahab County, Kermanshah province, west of Iran. Methods: From total number of 851 collected ticks from 8 villages, 131 ticks were selected randomlyand investigated for detection of CCHF virus using RT-PCR. Results: The virus was found in 3.8 of the tested ticks. Hyalommaanatolicum, H.asiaticum and Rhipicephalus sanguineus species were found to have viral infection, with the highest infection rate (11.11) in Rh. sanguineus. Conclusion: These findings provide epidemiological evidence for planning control strategies of the disease in the study area

Overview of hydatid disease in Iranian children

Background: Hydatid disease (HD) is still an important health hazard in the world. This disease is a parasitic infestation endemic in many sheep- and cattle-raising areas such as Iran. Objectives: This study aimed to review the clinical manifestations, laboratory aspects, imaging findings, and management of HD. Patients and Methods: Data were collected from the medical records of patients diagnosed with HD in eight referral hospitals in different provinces of Iran from 2001 to 2014. Results: Overall, 161 children at a mean age of 9.25 ± 3.37 years (age range = 1 - 15 years old) hospitalized with a definite diagnosis of the hydatid cyst between 2001 and 2014 were studied. The male-to-female ratio was 1.6:1. The most commonly involved organ was the lung (67.1), followed by the liver (44.1) and a combined liver and lung involvement was found in 15.5 of the patients. The cysts were found more frequently in the right lobe of the liver and lung than in the left lobe. The most frequent complaints were fever (35.4) and abdominal pain (31.7), and the most frequent sign was an abdominal mass in the liver involvement and cough in the lung involvement. There was a high eosinophil count (> 500/micL) in 41 of our cases. A high erythrocyte sedimentation rate (> 30) or positive C-reactive protein (based on the qualitative method) was found in 18.6 of the patients and leukocytosis > 15000/micL in 29.2 of the children. Ultrasonography was the main imaging test, with an accuracy rate of 96, and chest X-ray was helpful in 88.6 of the cases. Surgery was performed in 89 of the patients, and selective patients underwent percutaneous aspiration-injection-reaspiration drainage or medical treatment. Conclusions: The lung was the most commonly involved organ in the children recruited in the present study. Given the high probability of multiple organ involvement, we recommend that patients with HD be assessed via ultrasonography and chest X-ray. In endemic regions, unexplained eosinophilia should be considered as a parasitic disease like HD and its complications. © 2015 Pediartric Infections Research Center

Additively manufactured multi-morphology bone-like porous scaffolds: experiments and micro-computed tomography-based finite element modeling approaches

Tissue engineering, whose aim is to repair or replace damaged tissues by combining the principle of biomaterials and cell transplantation, is one of the most important and interdisciplinary fields of regenerative medicine. Despite remarkable progress, there are still some limitations in the tissue engineering field, among which designing and manufacturing suitable scaffolds. With the advent of additive manufacturing (AM), a breakthrough happened in the production of complex geometries. In this vein, AM has enhanced the field of bioprinting in generating biomimicking organs or artificial tissues possessing the required porous graded structure. In this study, triply periodic minimal surface structures, suitable to manufacture scaffolds mimicking bone's heterogeneous nature, have been studied experimentally and numerically; the influence of the printing direction and printing material has been investigated. Various multi-morphology scaffolds, including gyroid, diamond, and I-graph and wrapped package graph (I-WP), with different transitional zone, have been three-dimensional (3D) printed and tested under compression. Further, a micro-computed tomography (µCT) analysis has been employed to obtain the real geometry of printed scaffolds. Finite element analyses have been also performed and compared with experimental results. Finally, the scaffolds' behavior under complex loading has been investigated based on the combination of µCT and finite element modeling

Multimodal database of emotional speech, video and gestures

People express emotions through different modalities. Integration of verbal and non-verbal communication channels creates a system in which the message is easier to understand. Expanding the focus to several expression forms can facilitate research on emotion recognition as well as human-machine interaction. In this article, the authors present a Polish emotional database composed of three modalities: facial expressions, body movement and gestures, and speech. The corpora contains recordings registered in studio conditions, acted out by 16 professional actors (8 male and 8 female). The data is labeled with six basic emotions categories, according to Ekman’s emotion categories. To check the quality of performance, all recordings are evaluated by experts and volunteers. The database is available to academic community and might be useful in the study on audio-visual emotion recognition

The Study of biology (age, feeding and, reproduction of Rutilus rutilus caspicus in south coast of the Caspian Sea (Iranian waters)

The Caspian Sea is an important source of water in terms of having valuable resources of sturgeon and bony fish is taken into consideration roach(Rutilus rutilus caspicus (L.)) is one of the most important commercial species in the southern coast of the Caspian Sea in Iran , the catch of this species has declined substantially in the last 10 years, The management and exploitation need of comprehensive review of its biology .This study as part of a comprehensive study of feeding , spawning and growth of this species.In this study, using samples caught in beach seine along the southern coast of the Caspian Sea coastal ( Iranian waters ) took place. The fork length and total weight ranged between 12.5 to29.5(cm) and 29 to293( grm),10.5 to23(cm) and17.2 to21(grm) in Golestan and Gilan Province respectively. The b value of the length-weight relationship ranged 3.02 to 3.25 and 3.28 to 3.75 for female and male, in Golestan and Gilan Province respectively. The age composition of the catch was from 1 to 4 year in both Province, there was one spawning peak and Fecundity variations were high and ranged 7260 to 231965 eggs. Average growth in length was described with the Von Bertalanffy growth model: L (t) = 30.94(1-exp (0.42(t-0.18) and L (t) = 20.49(1-exp (0.53(t-1). The percent of empty stomach and prey dominant evaluated during different seasons by specific formula. Result showed that gastropod, Polychaete worms and molluscs were dominated and specific food items respectively. Shrimp, fish, insects, zooplankton and clams were scare of prey

Asynchronous Testing of Synchronous Components in GALS Systems

International audienceGALS (Globally Asynchronous Locally Synchronous) systems, such as the Internet of Things or autonomous cars, integrate reactive synchronous components that interact asynchronously. The complexity induced by combining synchronous and asynchronous aspects makes GALS systems difficult to develop and debug. Ensuring their functional correctness and reliability requires rigorous design methodologies, based on formal methods and assisted by validation tools. In this paper we propose a testing methodology for GALS systems integrating: (1) synchronous and asynchronous concurrent models; (2) functional unit testing and behavioral conformance testing; and (3) various formal methods and their tool equipments. We leverage the conformance test generation for asynchronous systems to automatically derive realistic scenarios (input constraints and oracle), which are necessary ingredients for the unit testing of individual synchronous components, and are difficult and error-prone to design manually. We illustrate our approach on a simple, but relevant example inspired by autonomous cars

Developing argumentation skills in mathematics through computer-supported collaborative learning: the role of transactivity

Collaboration scripts and heuristic worked examples are effective means to scaffold university freshmen’s mathematical argumentation skills. Yet, which collaborative learning processes are responsible for these effects has remained unclear. Learners presumably will gain the most out of collaboration if the collaborators refer to each other’s contributions in a dialectic way (dialectic transactivity). Learners also may refer to each other’s contributions in a dialogic way (dialogic transactivity). Alternatively, learners may not refer to each other’s contributions at all, but still construct knowledge (constructive activities). This article investigates the extent to which constructive activities, dialogic transactivity, and dialectic transactivity generated by either the learner or the learning partner can explain the positive effects of collaboration scripts and heuristic worked examples on the learners’ disposition to use argumentation skills. We conducted a 2 × 2 experiment with the factors collaboration script and heuristic worked examples with N = 101 math teacher students. Results showed that the learners’ engagement in self-generated dialectic transactivity (i.e., responding to the learning partner’s contribution in an argumentative way by critiquing and/or integrating their learning partner’s contributions) mediated the effects of both scaffolds on their disposition to use argumentation skills, whereas partner-generated dialectic transactivity or any other measured collaborative learning activity did not. To support the disposition to use argumentation skills in mathematics, learning environments should thus be designed in a way to help learners display dialectic transactivity. Future research should investigate how learners might better benefit from the dialectic transactivity generated by their learning partners