Miracle-dz/UniFAR-FTUs huggingface dataset:
Devenir d'une lithosphère en subduction dans le manteau terrestre : étude de sa déformation et des flux mantelliques associés

L'approche scientifique a consiste en la combinaison de trois differentes methodes de modelisation (analogique, semi analytique et numerique) afin de contraindre la rheologie qui regit la deformation de la lithosphere et les flux mantelliques associes au niveau des zones de subduction. Par l'etroite confrontation des predictions (modeles) et les observations disponibles (donnees sismologiques pour l'essentiel), j'apporte de nouvelles contraintes sur le devenir d'une lithosphere en subduction dans le manteau, couplees avec une precision sur la structuration du manteau. Les resultats des modeles au regard des donnees geophysiques predisent une lithosphere faiblement visqueuse (le rapport de viscosite entre la lithosphere et le manteau ne saurait exceder 100) qui atteint lors de sa descente dans le manteau la forme specifique d'une meduse. Ce resultat majeur apporte une nouvelle interpretation sur l'origine des epanchements de lithosphere dans le manteau profond et une precision sur la stratification entre le manteau superieur et le manteau inferieur faible pour permettre ainsi la penetration de la lithosphere dans le manteau inferieur. Cette etude apporte de nouvelles donnees sur la comprehension de l'interaction entre le flux mantellique et la lithosphere.
Waste management without direction in Indonesia: a proposed legal reform towards smart cities

This article delves into the regulation of municipal solid waste management (MSW) in Indonesia, viewed from the concepts of smart city and circular economy. The legal politics of Law Number 18 of 2008 on Waste Management has been restricted to the concept of 3Rs: reduce, reuse, and recycle. The idea of a circular economy refers to the principle of 10 Rs, consisting of refuse, rethink, reduce, reuse, repair, refurbish, remanufacture, repurpose, recycle, and recover. The concept of circular economy is believed to be essential to achieving the decarbonization goals mandated by the Paris Agreement. With a socio-legal approach, this research examines to what extent Waste Management Law can serve as the basis for implementing a circular economy in municipal areas. This research reveals that the concept of a circular economy has yet to be applied to manage waste in a municipal scope. Circular economy-based smart cities in MSW management can only be achieved through adequate facilities and changes in people’s behaviour. However, it is still questionable whether the Municipal Government is fully obliged to manage household waste because the Waste Management Law is silent on this matter but clearly states the community’s obligation to reduce and handle household waste as a waste producer. The division of waste-handling tasks also exacerbates this in several agencies, which, in practice, creates confusion for society. Hence, legal reforms are needed to reconcile the conflicting problems.
EVALUATION CRITERIA FOR NEEDS STATEMENTS IN DESIGN EDUCATION

Problem definition is essential to develop innovative products. The needs statement is a framework expressing design problems or user needs in a single sentence. In design education, needs statements are sometimes used to teach problem definition. Many novice students who do not major in design struggle to generate the needs statements and to understand key criteria. On the other hand, educators seem to have standard evaluation criteria. As a first step to effectively supporting design learners in writing needs statements, this study aims to identify design educators’ evaluation perspectives for needs statements. Semi-structured interviews with nine educators and qualitative content analysis were conducted. The results revealed an evaluation perspective on the function and quality of the statement. The five perspectives for evaluating the function of the statements are Adequacy of expression , Consistency with the theme , Whether it is based on research , Feasibility of idea generation, and Consistency with the solution . The three perspectives for evaluating its quality are Newness , Clarity, and Efficacy . The results corresponded to the criteria of idea creativity evaluation. Although these results were obtained in a limited context, it is expected to be the basis for supporting students’ activities on framing, problem definition, and user understanding in design projects.
Mapping extreme rainfall in the Northwest Portugal region: statistical analysis and spatial modelling

Extreme precipitation events are one of the causes of natural hazards, such as floods and landslides, making its investigation so important, and this research aims to contribute to the study of the extreme rainfall patterns in a Portuguese mountainous area. The study area is centred on the Arcos de Valdevez county, located in the northwest region of Portugal, the rainiest of the country, with more than 3000 mm of annual rainfall at the Peneda-Geres mountain system. This work focus on two main subjects related with the precipitation variability on the study area. First, a statistical analysis of several precipitation parameters is carried out, using daily data from 17 rain-gauges with a complete record for the 1960-1995 period. This approach aims to evaluate the main spatial contrasts regarding different aspects of the rainfall regime, described by ten parameters and indices of precipitation extremes (e.g. mean annual precipitation, the annual frequency of precipitation days, wet spells durations, maximum daily precipitation, maximum of precipitation in 30 days, number of days with rainfall exceeding 100 mm and estimated maximum daily rainfall for a return period of 100 years). The results show that the highest precipitation amounts (from annual to daily scales) and the higher frequency of very abundant rainfall events occur in the Serra da Peneda and Geres mountains, opposing to the valleys of the Lima, Minho and Vez rivers, with lower precipitation amounts and less frequent heavy storms. The second purpose of this work is to find a method of mapping extreme rainfall in this mountainous region, investigating the complex influence of the relief (e.g. elevation, topography) on the precipitation patterns, as well others geographical variables (e.g. distance from coast, latitude), applying tested geo-statistical techniques (Goovaerts, 2000; Diodato, 2005). Models of linear regression were applied to evaluate the influence of different geographical variables (altitude, latitude, distance from sea and distance to the highest orographic barrier) on the rainfall behaviours described by the studied variables. The techniques of spatial interpolation evaluated include univariate and multivariate methods: cokriging, kriging, IDW (inverse distance weighted) and multiple linear regression. Validation procedures were used, assessing the estimated errors in the analysis of descriptive statistics of the models. Multiple linear regression models produced satisfactory results in relation to 70% of the rainfall parameters, suggested by lower average percentage of error. However, the results also demonstrates that there is no an unique and ideal model, depending on the rainfall parameter in consideration. Probably, the unsatisfactory results obtained in relation to some rainfall parameters was motivated by constraints as the spatial complexity of the precipitation patterns, as well as to the deficient spatial coverage of the territory by the rain-gauges network.
Fiscal incentives and jobs: Bang for the buck or wasted resources?

This study conducted empirical exploration to quantify the tax incentives given by the government of Ethiopia and examine their effect on employment growth. It used a novel administrative and survey data to achieve these purposes. The analyses showed that firms that hire more workers operate in an environment with significant costs of raw material, professional services, and financial costs. These costs have hindered productivity growth and expansion of employment opportunities. While the incentive variable and its interaction with costs are mostly statistically insignificant in the empirical estimations, they have the expected signs. The elasticity of employment with respect to incentives is positive and decreases with increasing costs. These results indicate that the effect of the incentives may have been mitigated by significant production, distribution, and financial costs. The incentives need to be complemented with other measures that make the business environment more conducive for private investment.
Delayed Treatment of Bloodstream Infection at Admission is Associated With Initial Low Early Warning Score and Increased Mortality

OBJECTIVES: To identify factors associated with antibiotic treatment delay in patients admitted with bloodstream infections (BSIs). DESIGN: Retrospective cohort study. SETTING: North Zealand Hospital, Denmark. PATIENTS: Adult patients with positive blood cultures obtained within the first 48 hours of admission between January 1, 2015, and December 31, 2015 (n = 926). MEASUREMENTS AND MAIN RESULTS: First recorded Early Warning Score (EWS), patient characteristics, time to antibiotic treatment, and survival at day 60 after admission were obtained from electronic health records and medicine module. Presence of contaminants and the match between the antibiotic treatment and susceptibility of the cultured microorganism were included in the analysis. Data were stratified according to EWS quartiles. Overall, time from admission to prescription of antibiotic treatment was 3.7 (3.4–4.0) hours, whereas time from admission to antibiotic treatment was 5.7 (5.4–6.1) hours. A gap between prescription and administration of antibiotic treatment was present across all EWS quartiles. Importantly, 23.4% of patients admitted with BSI presented with an initial EWS 0–1. Within this group of patients, time to antibiotic treatment was markedly higher among nonsurvivors at day 60 compared with survivors. Furthermore, time to antibiotic treatment later than 6 hours was associated with increased mortality at day 60. Among patients with an initial EWS of 0–1, 51.3% of survivors received antibiotic treatment within 6 hours, whereas only 19.0% of nonsurvivors received antibiotic treatment within 6 hours. CONCLUSIONS: Among patients with initial low EWS, delay in antibiotic treatment of BSIs was associated with increased mortality at day 60. Lag from prescription to administration may contribute to delayed antibiotic treatment. A more frequent reevaluation of patients with infections with a low initial EWS and reduction of time from prescription to administration may reduce the time to antibiotic treatment, thus potentially improving survival.
Grounding Aleatoric Uncertainty in Unsupervised Environment Design

Adaptive curricula in reinforcement learning (RL) have proven effective for producing policies robust to discrepancies between the train and test environment. Recently, the Unsupervised Environment Design (UED) framework generalized RL curricula to generating sequences of entire environments, leading to new methods with robust minimax regret properties. Problematically, in partially-observable or stochastic settings, optimal policies may depend on the ground-truth distribution over aleatoric parameters of the environment in the intended deployment setting, while curriculum learning necessarily shifts the training distribution. We formalize this phenomenon as curriculum-induced covariate shift (CICS), and describe how its occurrence in aleatoric parameters can lead to suboptimal policies. Directly sampling these parameters from the ground-truth distribution avoids the issue, but thwarts curriculum learning. We propose SAMPLR, a minimax regret UED method that optimizes the ground-truth utility function, even when the underlying training data is biased due to CICS. We prove, and validate on challenging domains, that our approach preserves optimality under the ground-truth distribution, while promoting robustness across the full range of environment settings.
Makeup detection using Local Fisher Discriminant Analysis

Recent studies on face recognition, beauty analysis, age and health estimation, have found facial makeup application as a challenging issue. Hence, it is crucial for these algorithms to determine the makeup presence on faces. They can robust their recognition by utilizing makeup detection consequences. In this work we employ distinctive features to indicate the effect of makeup on the faces, moreover instead of utilizing whole face images, ten local patches have been extracted from images, then features assessed in each patch. Local patches which give the most information for each feature will be selected. At last two discriminant mapping methods, Marginal Fisher Analysis and Local Fisher Discriminant Analysis, are employed to trace more information from selected patches. Local Fisher Discriminant Analysis brought about accuracy rate of 95.03% for our makeup detection algorithm.
PRE-PRINT VERSION

Organizations’ information infrastructures are exposed to a large variety of threats. The most complex of these threats unfold in stages, as actors exploit multiple attack vectors in a sequence of calculated steps. Deciding how to respond to such serious threats poses a challenge that is of substantial practical relevance to IT security managers. These critical decisions require an understanding of the threat actors – including their various motivations, resources, capabilities, and points of access – as well as detailed knowledge about the complex interplay of attack vectors at their disposal. In practice, however, security decisions are often made in response to acute short-term requirements, which results in ineﬃcient resource allocations and ineﬀective overall threat mitigation. The decision support methodology introduced in this paper addresses this issue. By anchoring IT security managers’ decisions in an operational model of the organization’s information infrastructure, we provide the means to develop a better understanding of security problems, improve situational awareness, and bridge the gap between strategic security investment and operational implementation decisions. To this end, we
Generation of Correlated Nakagami-m Variates with a Generalized Cross-Correlation

—This paper presents a simple and efﬁcient method for generation of Nakagami-m random variables taking cross-correlation with arbitrary correlation parameters between the Rayleigh in phase and quadrature components that compose the Nakagami-m envelope. It is applied the Cholesky decomposition method to correlate the samples with the desired correlation values. As an application, a simulation demonstrates the use of this method in the Outage Probability curve in a selection combiner receiver output operating in a Nakagami-m fading channel, considering different fading and correlation parameters between the signals
Effectiveness Of Modified Dynamic Wrist Hand Orthosis In Treatment Of Ulnar Deviation For Patients With Rheumatoid Arthritis On Grip Strength & Hand Function

- Background: Rheumatoid arthritis (RA) is a chronic inflammatory disease that affects the hand joints and leading to impairment in hand function and reduce grip strength. Rheumatoid arthritis mostly affects small joints resulting in structural damage of metacarpophalangeal joint (MCP) resulting in ulnar deviation. Orthosis are designed to maintain the hand function but mostly the resting hand orthoses which are available hinders the activities of daily living. Hence, a modified dynamic wrist hand orthosis was designed keeping in mind that it does not restrict any activity and is helpful in correcting the alignment of hand by restoring biomechanical balance and reducing tissue stress thereby improving grip strength and hand function of patients with rheumatoid arthritis. Aim and objective: The present study shows the effectiveness of modified dynamic wrist hand orthosis on hand functions and grip strength for the treatment of ulnar deviation resulting due to rheumatoid arthritis. Methodology: A sample of 19 rheumatoid arthritis subjects having ulnar
Sensorless Impedance Control for Curved Surface Inspections Using the Omni-Drone Aerial Manipulator

In this work, we develop a novel aerial manipulator system with an omni-directional workspace. The system comprises of a quadrotor platform equipped with a rotating fivebar linkage, and serves the purpose of contour tracing tasks on complex shapes, whilst airborne. In order to remove the dependency on additional force sensors and keep the design lightweight, onboard force estimation is implemented based on the generalized momentum of the system, using the torque feedback from the manipulator’s actuators. The computed force estimate feeds in a position-based impedance controller with the purpose of maintaining continuous contact through the manipulator’s end-effector as the system traces contours of unknown curved geometry. Results demonstrate the estimator’s ability to track the applied forces, while the impedance controller shows adequate contour following capabilities. The preliminary results obtained on both stationary and flight experiments validate this approach and show potential for aerial contact inspections of more complex structures.
Why do deep convolutional networks generalize so poorly to small image transformations ? Why do deep convolutional networks generalize so poorly to small image transformations ?

Convolutional Neural Networks (CNNs) are commonly assumed to be invariant to small image transformations: either because of the convolutional architecture or because they were trained using data augmentation. Recently, several authors have shown that this is not the case: small translations or rescalings of the input image can drastically change the network’s prediction. In this paper, we quantify this phenomena and ask why neither the convolutional architecture nor data augmentation are sufficient to achieve the desired invariance. Specifically, we show that the convolutional architecture does not give invariance since architectures ignore the classical sampling theorem, and data augmentation does not give invariance because the CNNs learn to be invariant to transformations only for images that are very similar to typical images from the training set. We discuss two possible solutions to this problem: (1) antialiasing the intermediate representations and (2) increasing data augmentation and show that they provide only a partial solution at best. Taken together, our results indicate that the problem of insuring invariance to small image transformations in neural networks while preserving high accuracy remains unsolved.
Identification of aceNKPs, a committed common progenitor population of the ILC1 and NK cell continuum

Significance Changes in the balance of innate lymphoid cells (ILCs) can critically push anticancer immunity (mediated by natural killer (NK) cells) toward a tumor-permissive immune microenvironment (ILC2 or ILC3-mediated). ILCs develop from common ILC progenitors, but we and others have found previously defined NK cell-restricted progenitors (NKPs) still retain the ability to develop into other ILC lineages subject to tissue-specific cues. We delineate the existence of "aceNKPs" in murine bone marrow: NKG2A/C/E-expressing NKPs are the earliest hematopoietic precursors uniquely committed to become ILC1/NK cells with the capacity to further mature into group-1 ILCs capable of controlling tumor growth. Identification of aceNKPs is important for our understanding of the production of ILC1/NK cells and how they may be manipulated prior to maturation.
Scene Collages and Flexible Camera Arrays

This paper presents an automatic method for creating a collage from a collection of photos of a scene taken from different viewpoints. The collage is constructed by aligning the images (in terms of their positions, rotations and scales) using a least-squares formulation. We have developed a graph-based optimization algorithm for layering the images so as to minimize the fragmentation of the collage. A collage can be displayed with opaque layers, with transparent layers, or with blended image boundaries. A scene collage can be viewed as a piece-wise perspective representation of a scene with visible seams. This representation has not only aesthetic value but also conveys scene structure and camera motion in an intuitive way. To capture live-action collages of dynamic scenes we have developed camera arrays that can be physically flexed by the user to continuously vary the composition of the scene. The design of our camera arrays enables a user to reconfigure them in terms of the spatial arrangement of the cameras in a matter of minutes. We show several still and dynamic examples that demonstrate that scene collages provide a new and interesting way to experience scenes.
Development of the High Power Terahertz Light Sources at LEBRA Linac in Nihon University

Development of THz light source has been underway at Laboratory for Electron Beam Research and Application (LEBRA) at Nihon University in collaboration with National Institute of Advanced Industrial Science and Technology (AIST) since 2011. Basic research on coherent transition radiation (CTR) in the THz region has been carried out using the Parametric X-ray Radiation (PXR)-beam line of LEBRA. Since fiscal year 2016, the THz transport line has been constructed on the same axis as the PXR beam line taking the construction cost and simultaneous use of the two beams into account. Basic measurement and intensity upgrading test have been carried out for the THz lights generated on the PXRgenerating electron beam line. The average intensity of the THz lights obtained at the output port in the accelerator room has been 5 mW. In 2016, the superposition transport system of the THz lights to the PXR beam-line was installed in a multi-purpose vacuum chamber. The fundamental experiment of THz lights was performed at the PXR output port. Construction of the THz transport beam-line and the property of the THz lights is discussed in the report.
Street children in Egypt : group dynamics and subcultural constituents

The problem of street children in Egypt has gained attention in recent years due to the relentless efforts of Egyptian NGOs that care for street children, and because of the role played by researchers and the media in shedding light on its magnitude and associated hazards. This study aims to explore this problem by focusing on the major characteristics of street children, and investigating their basic demographics, the basis of their group formation and dynamics, their networks of interaction and relations, and the major constituents of their subculture. The research argues that street children, as a distinctive social group, have developed various scenarios to survive the cruel conditions they encounter in the street, and to cope with its various forms of vulnerability and jeopardy.
LTE Random Access Detection Based on a CA-CFAR Strategy

— Random Access is an important aspect of mobile systems where multiple users are always competing for resources. However, noise imposes a significant problem to those systems causing them to falsely detect access requests. In consequence, unnecessary processing and air traffic are generated based upon these unreal request events. This paper presents a modified Cell-Average Constant False Alarm Rate (CA-CFAR) strategy used for random access detection of CAZAC preambles in the presence of noise. Simulation results indicate that the proposed method performs well even in the case of low SNR.