Miracle-dz/UniFAR-FTUs huggingface dataset:
Spatial and temporal modelling for automatic human behavioral analysis

Human behavioral analysis from video is a topic of major interest in computer vision. It plays key role in a wide range of human-centric applications. A working technique involves processing both static visual cues and temporal dynamics of the entire sequence. In this thesis, we study two tasks for automatic human behavioral analysis from video: recovering 3D shape from 2D landmarks on a single image and action recognition from video. We propose efficient and accurate methods for these tasks. Estimating 3D shape from 2D landmarks not only provides richer information about objects such as human and face but also benefits other higher level tasks. It is a difficult and ill-posed problem. Previous approaches represent shape deformation using a linear combination of learned 3D shape bases. The linear assumption limits their applicability on human pose which is highly deformable and articulated. With the available 3D ground-truth of a number of 2D samples, we propose a deep network to directly estimate the mapping function from 2D landmark points to their depth. The 3D shape is recovered by combing the input and output of the neural network and is up to a scaling factor. The system is robust to noise and missing data. It runs at > 1, 000 fps during testing and outperforms state-of-the-art by up to two-fold. Recognizing action from video is an important step towards automatic human behavioral analysis. It is a very difficult problem because of many challenges including
Technical Criterion for an Effective Video in Learning Mathematics

Mathematics is a fundamental subject for all courses especially in engineering, business and economics. A good understanding of mathematics will help in daily activities and in many other situation either in simplified or complex forms. However, some students may have difficulties learning this subject and often felt that they need extra help from different resources. One of the learning methods that commonly used is through visualization where students view video in order to understand the topic. This study aimed to identify the technical criterion in producing an effective video to assist the process of teaching and learning. The main instrument implemented is by conducting a survey and follow-up by assessment questions with the respondents. The response and comments from the student’s perspective are taken as a guide to help educators to improve video making in learning mathematics.
Measuring Employment Inertia in a Period of Crisis: An Interpretation of Brechling Short-Run Model

In this paper, the Brechling model is used to measure employment inertia in five sectors of the Congolese economy between 1983 and 1993. During that period, the Congolese economy found itself at a crossroad. On the one hand, the implementation of the 1982-1986 five-year economic development plans involved considerable infrastructure investment. On the other hand, given the market reversal observed since 1985, the infrastructure funding and the tempo became less. A structural adjustment program had to be undertaken with the World Bank in 1987-1989 with its measures entirely designed to restore the country’s macroeconomic balance and to enable it to resume regular and sustainable growth over time. Thus, the result from the short-run employment model taken over the period in question demonstrates that there is strong employment inertia in the sectors investigated.
Laminated sediments in the Bering Sea reveal atmospheric teleconnections to Greenland climate on millennial to decadal timescales during the last deglaciation

Abstract. During the last glacial termination, the upper North Pacific Ocean underwent dramatic and rapid changes in oxygenation that lead to the transient intensification of oxygen minimum zones (OMZs), recorded by the widespread occurrence of laminated sediments on circum-Pacific continental margins. We present a new laminated sediment record from the mid-depth (1100 m) northern Bering Sea margin that provides insight into these deglacial OMZ maxima with exceptional, decadal-scale detail. Combined ultrahigh-resolution micro-X-ray-fluorescence (micro-XRF) data and sediment facies analysis of laminae reveal an alternation between predominantly terrigenous and diatom-dominated opal sedimentation. The diatomaceous laminae are interpreted to represent spring/summer productivity events related to the retreating sea ice margin. We identified five laminated sections in the deglacial part of our site. Lamina counts were carried out on these sections and correlated with the Bolling–Allerod and Preboreal phases in the North Greenland Ice Core (NGRIP) oxygen isotope record, indicating an annual deposition of individual lamina couplets (varves). The observed rapid decadal intensifications of anoxia, in particular within the Bolling–Allerod, are tightly coupled to short-term warm events through increases in regional export production. This dependence of laminae formation on warmer temperatures is underlined by a correlation with published Bering Sea sea surface temperature records and δ18O data of planktic foraminifera from the Gulf of Alaska. The rapidity of the observed changes strongly implies a close atmospheric teleconnection between North Pacific and North Atlantic regions. We suggest that concomitant increases in export production and subsequent remineralization of organic matter in the Bering Sea, in combination with oxygen-poor waters entering the Being Sea, drove down oxygen concentrations to values below 0.1 mL L−1 and caused laminae preservation. Calculated benthic–planktic ventilation ages show no significant variations throughout the last deglaciation, indicating that changes in formation rates or differing sources of North Pacific mid-depth waters are not prime candidates for strengthening the OMZ at our site. The age models established by our correlation procedure allow for the determination of calendar age control points for the Bolling–Allerod and the Preboreal that are independent of the initial radiocarbon-based chronology. Resulting surface reservoir ages range within 730–990 yr during the Bolling–Allerod, 800–1100 yr in the Younger Dryas, and 765–775 yr for the Preboreal.
Effects of relative humidity on aerosol light scattering

Atmospheric aerosols, which are defined as solid or liquid particles suspended in the air, are tiny and mostly not visible to our eyes. Nevertheless, they have an immense impact on our health and on our global climate as well. Anthropogenic emissions of greenhouse gases, like carbon dioxide or methane, and anthropogenic emissions of particulate matter have changed the Earth’s climate. Aerosols scatter and absorb solar radiation and by doing so they directly influence the Earth’s radiation budget. In addition, anthropogenic aerosol particles also modify cloud properties, causing e.g. brighter clouds with longer lifetimes and changed precipitation behavior. The net effect of anthropogenic aerosols on the Earth’s climate is a cooling one, in contrast to the greenhouse gases which are characterized by a warming effect. However, the Intergovernmental Panel on Climate Change concludes in his last assessment report that the high uncertainty in the net radiative forcing of all main climate agents (greenhouse gases, aerosols, surface changes, and natural forcings) is mainly dominated by the high uncertainty in the aerosol radiative forcing. This is mainly caused by the high temporal, spatial, and compositional variability of the aerosol and the poorly understood and quantified aerosol effects. Since aerosol particles can take up water, they can change in size and chemical composition depending on the ambient relative humidity (RH). This directly influences the aerosol radiative forcing because the aerosol optical properties will change with varying RH. Therefore, long-term in-situ measurements of aerosol optical and microphysical properties are usually performed at standardized dry conditions to avoid the RH-effect when quantifying and characterizing the main aerosol properties. This is especially important for the aerosol light scattering coefficient σsp(λ) which strongly depends on RH (λ denotes the wavelength). These dry measured values significantly differ from the ambient and thus climate relevant ones. The knowledge of this RH effect is therefore of crucial importance for climate forcing calculations. In addition, it is also needed for the comparison or validation of remote sensing with in-situ measurements. The key parameter to describe the influence of RH on the aerosol light scattering is the scattering enhancement factor f (RH,λ) which is defined as the aerosol scattering coefficientσsp(RH,λ) at a certain RH divided by the dry σsp(dry,λ). The magnitude of the scattering enhancement depends on the size and the chemical composition of the aerosol. The scattering enhancement can e.g. be measured by using a humidified nephelometer . It can also be calculated via Mie theory using e.g. the measured size distribution, hygroscopic growth, and chemical composition as input. In this thesis, the influence of relative humidity on the aerosol light scattering has been investigated using measurements and model studies from three European sites. These were selected according to the specific aerosol type typically encountered at the site. At the Jungfraujoch, located in the Swiss
Interactive comment on “ Freshwater discharge controlled deposition of Cenomanian-Turonian black shales on the NW European epicontinental shelf ( Wunstorf , North Germany ) ” by N . A

TEX86 record (which I concur), the influence of degradation on their palynological records is discarded based on the presence of a thin-walled dinocyst (Paleohystrichophora infusorioides). I find it hard to believe that BIT is (completely) driven by preservation, but that this had no impact on the pollen and spores, which we know can be heavily influenced by preferential degradation (see various papers of G. Versteegh). I am not an expert in dinoflaggelates, but is this thin-walled dinocyst a commonly used indicator of preservation in the Cretaceous? The authors don’t give a reference that would justify the use of this dino as preservation indicator. As far as I can see their main conclusions relies on this single line of evidence against preservation so I strongly urge the authors to provide additional evidence that preferential preservation is not primarily driving the observed changes in pollen and spores accumulation across OAE 2.
Evaluating the Usability of Mobile Instant Messaging Apps on iOS Devices

Instant messaging apps are experiencing a significant upturn in recent years in mobile devices. This paper shows the results of applying a systematic evaluation of these applications on iOS platform that was performed to identify their main usability issues. As a result of this evaluation some guidelines for improving the usability of these applications are proposed, such as a carefully designing the interface or not exceeding more than eight (and preferably not more than six) interactions to perform the main tasks. The results and the guidelines proposed will help in the future to create more effective mobile applications for instant messaging. KeywordsInstant messaging; mobile usability; keystroke level modeling; mobile heuristic evaluation
3D Façade Labeling over Complex Scenarios: A Case Study Using Convolutional Neural Network and Structure-From-Motion

Urban environments are regions in which spectral variability and spatial variability are extremely high, with a huge range of shapes and sizes, and they also demand high resolution images for applications involving their study. Due to the fact that these environments can grow even more over time, applications related to their monitoring tend to turn to autonomous intelligent systems, which together with remote sensing data could help or even predict daily life situations. The task of mapping cities by autonomous operators was usually carried out by aerial optical images due to its scale and resolution; however new scientific questions have arisen, and this has led research into a new era of highly-detailed data extraction. For many years, using artificial neural models to solve complex problems such as automatic image classification was commonplace, owing much of their popularity to their ability to adapt to complex situations without needing human intervention. In spite of that, their popularity declined in the mid-2000s, mostly due to the complex and time-consuming nature of their methods and workflows. However, newer neural network architectures have brought back the interest in their application for autonomous classifiers, especially for image classification purposes. Convolutional Neural Networks (CNN) have been a trend for pixel-wise image segmentation, showing flexibility when detecting and classifying any kind of object, even in situations where humans failed to perceive differences, such as in city scenarios. In this paper, we aim to explore and experiment with state-of-the-art technologies to semantically label 3D urban models over complex scenarios. To achieve these goals, we split the problem into two main processing lines: first, how to correctly label the façade features in the 2D domain, where a supervised CNN is used to segment ground-based façade images into six feature classes, roof, window, wall, door, balcony and shop; second, a Structure-from-Motion (SfM) and Multi-View-Stereo (MVS) workflow is used to extract the geometry of the façade, wherein the segmented images in the previous stage are then used to label the generated mesh by a “reverse” ray-tracing technique. This paper demonstrates that the proposed methodology is robust in complex scenarios. The façade feature inferences have reached up to 93% accuracy over most of the datasets used. Although it still presents some deficiencies in unknown architectural styles and needs some improvements to be made regarding 3D-labeling, we present a consistent and simple methodology to handle the problem.
Journal of Geophysical Research: Solid Earth Forecasting the path of a laterally propagating dike

An important aspect of eruption forecasting is predicting the path of propagating dikes. We show how lateral dike propagation can be forecast using the minimum potential energy principle. We compare theory to observed propagation paths of dikes originating at the Bár ð arbunga volcano, Iceland, in 2014 and 1996, by developing a probability distribution for the most likely propagation path. The observed propagation paths agree well with the model prediction. We ﬁnd that topography is very important for the model, and our preferred forecasting model considers its inﬂuence on the potential energy change of the crust and magma. We tested the inﬂuence of topography by running the model assuming no topography and found that the path of the 2014 dike could not be hindcasted. The results suggest that lateral dike propagation is governed not only by deviatoric stresses but also by pressure gradients and gravitational potential energy. Furthermore, the model predicts the formation of curved dikes around cone-shaped structures without the assumption of a local deviatoric stress ﬁeld. We suggest that a likely eruption site for a laterally propagating dike is in topographic lows. The method presented here is simple and computationally feasible. Our results indicate that this kind of a model can be applied to mitigate volcanic hazards in regions where the tectonic setting promotes formation of laterally propagating vertical intrusive sheets.
Control of the Unsteady Flow in a Stator Blade Row Interacting With Upstream Moving Wakes

A computational approach, based on a spectral-element Navier-Stokes solver, has been applied to the study of the unsteady flow arising from wake-stator interaction. Direct, as well as turbulence-model calculations, provide insight into the mechanics of the unsteady flow and demonstrate the potential for controlling its effects. The results show that the interaction between the wakes and the stator blades produces a characteristic pattern of vortical disturbances, which have been correlated to the pressure fluctuations. Within the stator passage, the wakes migrate towards the pressure surface where they evolve into counter-rotating vortices. These vortices are the dominant source of disturbances over the pressure surface of the stator blade. Over the suction surface of the stator blade, the disturbances are due to the distortion and detachment of boundary layer fluid. They can be reduced by tailoring the blade loading or by applying non-uniform suction.Copyright © 1993 by ASME
Scrutiny of Critical Thinking Concept.

Learning critical thinking skills are the goal of educational systems so the term “critical thinking” (CT) is frequently found in educational policy documents. Despite this frequency, however, precise understandings among teachers of what CT really means do not exit. The present study is designed to answer the following question. We can classify critical thinking concept in a conceptual framework. A qualitative content analysis with deductive categorization was used to classify critical thinking concept in a conceptual framework . The research field (statistical population) included all available digital and written sources related to critical thinking. The Research sample was a purposeful homogeneous sample. It is used to describe the sample that includes information based on the qualitative research goals. The results showed that critical thinking concept could be investigated in fields of both psychology and philosophy. While philosophers emphasis on the nature and quality of critical thinking, psychologists focus on cognitive process and components used to investigate the practical problems. So philosophers emphasize critical thinking attitudes while psychologists focus on critical thinking skills.
Dense Decoder Shortcut Connections for Single-Pass Semantic Segmentation

We propose a novel end-to-end trainable, deep, encoder-decoder architecture for single-pass semantic segmentation. Our approach is based on a cascaded architecture with feature-level long-range skip connections. The encoder incorporates the structure of ResNeXt's residual building blocks and adopts the strategy of repeating a building block that aggregates a set of transformations with the same topology. The decoder features a novel architecture, consisting of blocks, that (i) capture context information, (ii) generate semantic features, and (iii) enable fusion between different output resolutions. Crucially, we introduce dense decoder shortcut connections to allow decoder blocks to use semantic feature maps from all previous decoder levels, i.e. from all higher-level feature maps. The dense decoder connections allow for effective information propagation from one decoder block to another, as well as for multi-level feature fusion that significantly improves the accuracy. Importantly, these connections allow our method to obtain state-of-the-art performance on several challenging datasets, without the need of time-consuming multi-scale averaging of previous works.
Instance Based Social Network Representation

With the prevalence of personal information sharing on the Web, users are becoming more concerned with their privacy online. Social networks, in particular, represent a new challenge in this regard since they combine the sharing of highly personal data with ease of access. While most of the current discussion addresses the problem of providing a simple interface to configure complex privacy settings, this paper focuses on the user’s ability to reason about how privacy policies affect their data. We show that it is possible to concisely represent a large subset of a social network using only a few representing members. Moreover, we argue that such a representation can inform users about the implications of privacy policies on who can see their data.
Prevalence of Depression and Anxiety and Associated Factors among Patients Visiting Orthopedic Outpatient Clinic at Tikur Anbessa Specialized Hospital, Addis Ababa, Ethiopia, 2017

Introduction: Orthopedic Trauma exerts a holistic influence on survivors’ physical health including a range of mental health problems which interfere with survivors’ recovery. Psychiatric disorders and behavioral disturbances are reported to be 3-5 times more common among people with injuries and are predictor of poor outcome and ongoing disability. Therefore, assessing depression and anxiety among orthopedic trauma patients play a vital role in implementing further interventions.Methods: Institutional based cross-sectional study was conducted at Tikur Anbessa specialized hospital from May 29-June 30, 2017. Hospital anxiety and depression scale was used to assess anxiety and depression by using face to face interview. Systematic sampling technique was used to select a total of 407 participants. Data has been analyzed using SPSS 20. Bivariate and multivariate logistic regression was done to identify associated factors. Variables with p-value <0.05 have been considered as statistically significant.Result: Prevalence of depression and anxiety were 36.1% and 39.8% respectively. Being female (AOR=2.3595%CI (1.48,3.72)), poor social support (AOR=2.5195%CI (1.30,4.85)), developing complication (AOR=1.9195%CI (1.07,3.52)), presence of amputation (AOR=3.6495%CI (1.60,8.24)) and having pain (AOR=2.0295%CI (1.24,3.30)) for depression and being female (AOR=1.9995%CI(1.11,3.57)), having chronic medical illness (AOR=3.0795%CI(1.36,6.92)), having family history of mental illness (AOR=2.24 95%CI (1.05,5.4.91)), lower extremity injury (AOR=2.93 95%CI (1.38,6.21)) and having severe pain (AOR=2.75 95%CI (1.32,5.74)) for anxiety had significant association at p–value <0.05. Conclusion: Prevalence of depression and anxiety were high. Being female, having poor social support, developing complication, presence of amputation and having pain for depression; and being female, having chronic medical illness, having family history of mental illness, lower extremity injury and having severe pain for anxiety were significantly associated factors. It is good if clinicians give emphasis for orthopedic patients especially for females and with chronic medical illness.
Microbial Communities Associated with the Oxidation of Iron and Technetium in Bioreduced Sediments

Anoxic Tc(IV)-containing sediments representative of the UK Sellafield reprocessing facility were exposed to either air or NO3 − to investigate redox cycling of technetium and iron. With air, oxidation of Fe(II) in the reduced sediments was accompanied by ∼75% mobilization of Tc to solution, as soluble Tc(VII). Nitrate additions resulted in the bio-oxidation of Fe(II), coupled to microbially mediated NO− 3 reduction but was accompanied by only very limited (<5%) mobilization of the reduced, sediment-bound Tc, which remained as Tc(IV). PCR-based 16S rRNA and narG gene analyzes were used to investigate changes in the microbial community during sediment oxidation by air and nitrate. Contrasting microbial communities developed in the different treatments and were dominated by Betaproteobacteria (including Herbaspirillum and Janthinobacterium spp.) in the presence of high NO− 3 concentrations. This suggests that the Betaproteobacteria are involved in the redox cycling of Fe and N in these systems, but are unable to mediate NO3 −-dependent Tc(IV) oxidation. These microorganisms may play a previously unrecognized yet pivotal role in influencing contaminant fate and transport in these environments which can have implications to the long-term stewardship of radionuclide-contaminated sediments.