Miracle-dz/UniFAR-FTUs huggingface dataset:
The sensitivity of seafloor compliance measurements to sub-basalt sediments

SUMMARY We investigate the sensitivity of seafloor compliance ‐ the transfer function between the seafloor stress and displacement under ocean waves ‐ to sub-basalt sediments. Seafloor compliance is sensitive to the subsurface shear modulus as a function of depth and is particularly sensitive to low shear modulus regions such as fluid-saturated sediments. We generate synthetic seafloor compliance data for different models of sediments beneath basalts, run geophysical inversions on the data and compare the inversion results with the input models. Our input models are variations on a reference model in which sub-basalt sediments start 3.5 km beneath the seafloor and have an average shear modulus of 6.8 × 10 9 Pa (shear wave velocity ca 1.7 km s −1 ). The sensitivity of seafloor compliance to sub-basalt sediments depends mostly on the water depth and the sub-basalt sediment layer depth, thickness and shear modulus. If the water depth is 1 km or more, seafloor compliance measurements will detect a sub-basalt sediment layer 0.6 km or more thick and will constrain the depth to the top and bottom of a 2-km thick sub-basalt sediment layer to within 0.2 km. If the water depth is 0.25 km, the thinnest detectable layer will be 1.2 km and the depth uncertainty for a 2-km thick sub-basalt sediment layer will be 0.5‐0.8 km. Neither interlayered sediments within the basalts nor sediments above the basalt layer have a strong effect on the measurement sensitivity.
Multi-Robot Simultaneous Coverage and Mapping of Complex Scene - Comparison of Different Strategies

This paper addresses the problem of optimizing the observation of a human scene using several mobile robots. Mobile robots have to cooperate to find a position around the scene maximizing its coverage. The scene coverage is defined as the observation of the human pose skeleton. It is assumed that the robots can communicate but have no map of the environment. Thus the robots have to simultaneously cover and map the scene and the environment. We consider an incremental approach to master state-space complexity. Robots build an hybrid metric-topological map while evaluating the observation of the human pose skeleton. To this end we propose and evaluate different online optimization strategies exploiting local versus global information. We discuss the difference of the performance and cost. Experiments are performed both in simulation and with real robots.
AUTOMATIC QUANTIFICATION OF THREE-DIMENSIONAL VELOCITY FIELD IMPROVED BY SPATIALLY VARYING AVERAGING FILTERS

Automatic methods for quantifying velocity in cardiac images can be used to diagnose diseases, but the estimated velocity suffers from blurring in the region of motion discontinuities when using variational methods. In this paper, spatially varying filters were used to improve accuracy in these regions. These filters depend on: (i) image intensity and (ii) velocity estimates from previous iterations of the update equation. Methods were extended to voxel space, tested with synthetic images, and parameters optimized. The spatially varying filter which depends on velocity estimates was found to provide the greatest reduction in error measures, but the benefits were found to depend on careful choices of derivative scheme and other model parameters.
Upper Confidence Reinforcement Learning exploiting state-action equivalence

Leveraging an equivalence property on the set of states of state-action pairs in an Markov Decision Process (MDP) has been suggested by many authors. We take the study of equivalence classes to the reinforcement learning (RL) setup, when transition distributions are no longer assumed to be known, in a discrete MDP with average reward criterion and no reset. We study powerful similarities between state-action pairs related to optimal transport. We first analyze a variant of the UCRL2 algorithm called C-UCRL2, which highlights the clear benefit of leveraging this equivalence structure when it is known ahead of time: the regret bound scales as ~O(D√KCT) where C is the number of classes of equivalent state-action pairs and K bounds the size of the support of the transitions. A non trivial question is whether this benefit can still be observed when the structure is unknown and must be learned while minimizing the regret. We propose a sound clustering technique that provably learn the unknown classes, but show that its natural combination with UCRL2 empirically fails. Our findings suggests this is due to the ad-hoc criterion for stopping the episodes in UCRL2. We replace it with hypothesis testing, which in turns considerably improves all strategies. It is then empirically validated that learning the structure can be beneficial in a full-blown RL problem.
Analysis of Boundary Effects on PDE-Based Sampling of Whittle-Matérn Random Fields

We consider the generation of samples of a mean-zero Gaussian random field with Matern covariance function. Every sample requires the solution of a differential equation with Gaussian white noise forcing, formulated on a bounded computational domain. This introduces unwanted boundary effects since the stochastic partial differential equation is originally posed on the whole $\mathbb{R}^d$, without boundary conditions. We use a window technique, whereby one embeds the computational domain into a larger domain, and postulates convenient boundary conditions on the extended domain. To mitigate the pollution from the artificial boundary it has been suggested in numerical studies to choose a window size that is at least as large as the correlation length of the Matern field. We provide a rigorous analysis for the error in the covariance introduced by the window technique, for homogeneous Dirichlet, homogeneous Neumann, and periodic boundary conditions. We show that the error decays exponentially in the window size, independently of the type of boundary condition. We conduct numerical experiments in 1D and 2D space, confirming our theoretical results.
Further constraints on neutron star crustal properties in the low-mass X-ray binary 1RXS J180408.9−342058

We report on two new quiescent XMM–Newton observations (in addition to the earlier Swift/XRT and XMM–Newton coverage) of the cooling neutron star crust in the low-mass X-ray binary 1RXS J180408.9−342058. Its crust was heated during the ∼4.5 month accretion outburst of the source. From our quiescent observations, fitting the spectra with a neutron star atmosphere model, we found that the crust had cooled from ∼100 to ∼73 eV from ∼8 to ∼479 d after the end of its outburst. However, during the most recent observation, taken ∼860 d after the end of the outburst, we found that the crust appeared not to have cooled further. This suggested that the crust had returned to thermal equilibrium with the neutron star core. We model the quiescent thermal evolution with the theoretical crustal cooling code NSCOOL and find that the source requires a shallow heat source, in addition to the standard deep crustal heating processes, contributing ∼0.9 MeV per accreted nucleon during outburst to explain its observed temperature decay. Our high quality XMM–Newton data required an additional hard component to adequately fit the spectra. This slightly complicates our interpretation of the quiescent data of 1RXS J180408.9−342058. The origin of this component is not fully understood.
Heterogeneity of CD 4 + and CD 8 + T-cell Responses to Cytomegalovirus in HIV-Infected and HIV-Uninfected Men Who Have Sex With Men

Huifen Li, Joseph B. Margolick, Jay H. Bream, Tricia L. Nilles, Susan Langan, Hanhvy T. Bui, AndrewW. Sylwester, Louis J. Picker, and Sean X. Leng Division of Geriatrics Medicine and Gerontology, Johns Hopkins University School of Medicine and Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland; and Vaccine and Gene Therapy Institute and Oregon National Primate Research Center, Oregon Health and Science University, Beaverton, Oregon
Characterization of genomic clones using circulating tumor DNA in patients with hepatocarcinoma

Background: Hepatocarcinoma (HCC) is often diagnosed at an advanced stage with poor prognosis. A non-invasive method concerning circulating tumor DNA (ctDNA) has been recognized as a promising biomarker. ctDNA has been widely studied to monitor tumor dynamics and measure tumor burden. However, the results of previous studies for biomarkers for HCC have generally been inconsistent and limited in clinical application. Methods: HCC usually represent a mixture of different cancer cell clones differing in mutation content, which can be used to monitor important features such as treatment responses. In this study, we used Bayesian cluster with PyClone to identify clonal population structures based on variations from ctDNA of a 4 HCC patients dataset. Results: As a result, reductions in cellular prevalences of private mutation clusters were observed between preoperative and postoperative plasma samples, which reflected the treatment responses of surgery. We also identified expansion and sharing sub-clonality of initially minor clones in plasma samples after treatment, and located clusters in patients which might be used as actionable targets. Conclusions: These results provided a more complete picture of the liver cancer pathogenesis. The comparison of preoperative and postoperative plasma samples showed that ctDNA can be used to real-time sampling of clonal evolution in patients with hepatocarcinoma. In addition to dynamic monitoring of disease progression and response to therapy, characterizing of dynamics of genomic clones can be used to determine the benefit of new therapeutics and guide therapy.
Robot-assisted gait training for stroke patients: current state of art and perspectives

In this review, we give a brief outline of robot-mediated gait training for stroke patients, as an important field emerging in rehabilitation. Technological innovations are allowing rehabilitation to move towards more integrated processes, with improved efficiency and less long-term impairments. In particular, robot-mediated neurorehabilitation is a rapidly advancing field, which uses robotic systems, often coupled with virtual reality haptic interfaces and emerging theories in neuroscience, to define new methods for treating neurological injuries such as stroke, spinal cord injury, and traumatic brain injury. The use of robots in gait training can enhance rehabilitation, following neuroscientific principles that justify the use of the robot. The field of robot-mediated neurorehabilitation brings challenges to both bioengineering and clinical practice. This paper reviews the state of art (including commercially available systems) and perspectives of robotics in post-stroke rehabilitation for walking recovery. A critical revision, including the problems at stake regarding robotic clinical use will also be presented.
MOLECULAR EVIDENCE OF COTESIA FLAVIPES (CAMERON) (HYMENOPTERA: BRACONIDAE) ESTABLISHMENT IN ETHIOPIA

Cotesia flavipes (Cameron) is an Asian origin endo-larval parasitoid of cereal stemborers in the genera of Chilo, Sesamia and others. It was introduced into Kenya mainly for the control of Chilo partellus (Swinhoe) (Lepidoptera: Crambidae) from India, and North and South Pakistan. After introduction, the parasitoid was released in C. partellus prone areas of Eastern and Southern African countries. The establishment rate varies from country to country and region to region within the country. In Ethiopia, the parasitoid was not released, but for the first time recorded in 1999 as identified morphologically. Morphological traits in many instances lead to wrong taxonomic conclusion. Hence, molecular investigation was carried out to confirm whether the parasitoid recorded in Ethiopia is C. flavipes or not by running Polymerase Chain Reaction (PCR) of DNA fragments of C. flavipes collected from Ethiopia and other African and Asian countries. The PCR analysis using 16S gene (primer) indicated that C. flavipes collected from Ethiopia had similar bands with C. flavipes from other countries confirming the correctness of the morphological traits used to identify the parasitoid. Hence, the parasitoid recorded in 1999 in Ethiopia was Cotesia flavipes which was established without release. To partition the differences that could exist among the different populations of C. flavipes and possibly trace the origin of Ethiopian population, advanced molecular techniques such as restricted fragment polymorphism (RFLP) and sequencing will be recommended although the exercises are expensive.
A closer look and comparison of cross-platform development environment for smartphones

A problem with having a fast and wide production of different platforms for mobile devices is that you can’t code for one and deploy on all devices at the same time. This thesis is focused on cross-plat1form development environments for smartphones and mainly to see what options there are on the market. This report will investigate how well a cross-compiler solution compares to hybrid cross-platform development. To do this we took a closer look at their architecture and then compared this with the results from different tests made. All the tests were made on the same smartphone to ensure fairness between them. All the tests strive to be as equal as possible even though the languages might differ from each other. The tested frameworks were PhoneGap, Qt, Unity3D and GameMaker. The different tests were about performance, power consumption, difficulty in accessing web browsers to perform HTML parsing and lastly to see if the platforms can access different native APIs such as the camera and accelerometer. The previously mentioned topics were compared between all the frameworks. We also compared the documentation found on their webpage to figure out which is the easiest to get started on.
Migration Status, Familial Risk for Mental Disorder, and Schizotypal Personality Traits

Markedly raised incidence rates of schizophrenia and other psychotic disorders have been observed in several migrant and ethnic minority groups. To contribute to a better understanding of the elevated risk for psychotic disorders that is conferred by migration status, the present study examined effects associated with migration risk status on schizotypal personality traits, which are thought to reflect an underlying vulnerability to psychotic disorder. Effects of migration status were also compared to effects associated with a family history of psychopathology, which represents a robust nonspecific risk factor. We assessed schizotypal traits, using the Schizotypal Personality Questionnaire (SPQ), in a community-based sample of 62 Moroccan migrants and 41 Dutch nonmigrants, who were classified by the presence or absence of a family history of psychopathology. Overall, Moroccan migrants obtained higher SPQ scores than Dutch nonmigrants. However, migrants who had been classified as having a familial load of psychopathology displayed higher SPQ scores than migrants without such a family history, who in turn did not differ from Dutch nonmigrants. Furthermore, migrants with a familial load, relative to migrants without such a family history, reported higher levels of substance use and feelings of anxiety or depression, and perceived more often ethnic discrimination, which closely paralleled their SPQ scores. These findings indicate that primarily those migrants who are both intrinsically vulnerable and chronically exposed to social adversity, particularly ethnic discrimination, are at elevated risk for psychotic and other disorders. The results add to the evidence that migration status and perceived discrimination are associated with mental health.
Title Forward Scan based Plane Sweep Algorithm for Parallel

The interval join is a basic operation that finds application in temporal, spatial, and uncertain databases. Although a number of centralized and distributed algorithms have been proposed for the efficient evaluation of interval joins, classic plane sweep approaches have not been considered at their full potential. A recent piece of related work proposes an optimized approach based on plane sweep (PS) for modern hardware, showing that it greatly outperforms previous work. However, this approach depends on the development of a complex data structure and its parallelization has not been adequately studied. In this paper, we explore the applicability of a largely ignored forward scan (FS) based plane sweep algorithm, which is extremely simple to implement. We propose two optimizations of FS that greatly reduce its cost, making it competitive to the state-of-the-art single-threaded PS algorithm while achieving a lower memory footprint. In addition, we show the drawbacks of a previously proposed hash-based partitioning approach for parallel join processing and suggest a domain-based partitioning approach that does not produce duplicate results. Within our approach we propose a novel breakdown of the partition join jobs into a small number of independent mini-join jobs with varying cost and manage to avoid redundant comparisons. Finally, we show how these mini-joins can be scheduled in multiple CPU cores and propose an adaptive domain partitioning, aiming at load balancing. We include an experimental study that demonstrates the efficiency of our optimized FS and the scalability of our parallelization framework.
TRADE CREDIT FINANCING IN AFRICAN AGRO-FOOD MANUFACTURING INDUSTRY: INCIDENCE AND MOTIVES

Trade credit is a form of short-term financing employed by non-financial firms in inter-firm trade. This study examines the incidence and the motives for extending trade credit among agro-food manufacturing firms in Africa. The study uses a subsample of agro-food firms from 2014 World Bank Enterprise Survey data from eight African countries: Burundi, Malawi, Mauritania, Namibia, Nigeria, Senegal, Sudan and South Sudan. The incidence of trade credit is relatively high among agro-food firms as 60.5% and 55% of firms extend and receive trade credit respectively. However, the mean proportion of yearly total input purchases received as trade credit (22%) is higher than the mean proportion of yearly total sales extended as trade credit (19%). From the two-limit Tobit estimation, firm size, manager experience, degree of product diversification, access to bank credit, overdraft availability and supplier credit are found to play a significant role in the level of trade credit firms extend to customers. However, when supplier credit is added to the model, it completely absorbs the effect of access to bank credit. For suspected endogeneity of supplier credit, an instrumental variable (IV) two-limit Tobit is estimated and the results show no presence of endogeneity. From the results, transaction, quality verification, marketing and long-term relationship motives for extending trade credit to customers are implied.
Adapting Batch Scheduling to Workload Characteristics: What Can We Expect From Online Learning?

Despite the impressive growth and size of super-computers, the computational power they provide still cannot match the demand. Efficient and fair resource allocation is a critical task. Super-computers use Resource and Job Management Systems to schedule applications, which is generally done by relying on generic index policies such as First Come First Served and Shortest Processing time First in combination with Backfilling strategies. Unfortunately, such generic policies often fail to exploit specific characteristics of real workloads. In this work, we focus on improving the performance of online schedulers. We study mixed policies, which are created by combining multiple job characteristics in a weighted linear expression, as opposed to classical pure policies which use only a single characteristic. This larger class of scheduling policies aims at providing more flexibility and adaptability. We use space coverage and black-box optimization techniques to explore this new space of mixed policies and we study how can they adapt to the changes in the workload. We perform an extensive experimental campaign through which we show that (1) even the best pure policy is far from optimal and that (2) using a carefully tuned mixed policy would allow to significantly improve the performance of the system. (3) We also provide empirical evidence that there is no one size fits all policy, by showing that the rapid workload evolution seems to prevent classical online learning algorithms from being effective.
Crack growth modes in inhomogeneous materials: analysis of bi- and multi-material interfaces

Most structural components contain inhomogeneities such as hardened surface layers or coatings, welded or bonded elements, etc. The crack growth mode then depends not only on applied loading and structure geometry but also on material inhomogeneity. In the presentation the analysis of crack growth mode will be discussed for two cases: a bi-material structure with two materials of different thermo-elastic and plastic properties connected along the interface and a structure with introduced interlayer of different material. The simplified approach is presented, namely the MK-criterion (1,2) based on the linear elastic fracture mechanics (LEFM). In the criterion it is assumed that crack growth follows the direction of minimum distortion energy density at a distance corresponding to specified value of dilatation energy. For two materials, A and B the crack growth from A to B or along the interface AB may occur depending on relative critical stress and fracture energy values. For a three-phases structure, various modes of crack growth are possible.
Arguing with Preferences in EcoBioCap Madalina Croitoru

In this paper we present the EcoBioCap project and the modelling needs of this project in terms of argumentation based preference aggregation. The aim of the paper is to well describe the problem encountered in this context and to propose a preference logic in line with the expressivity needed by the application. We then show how to embed this logic within the ASPIC+ system. Finally, we show how argument by expert opinion could be integrated within our framework where preference aggregation needs to take into consideration the different expertise of the project stakeholders.
High-dispersion spectroscopic monitoring of the Be/X-ray binary A0535+26/V725 Tau I: The long-term profile variability

We report on optical high-dispersion spectroscopic monitoring observations of the Be/X-ray binary A0535+26/V725 Tau, carried out from November 2005 to March 2009. The main aim of these monitoring observations is to study spectral variabilities in the Be disc, on both the short (a week or so) and long (more than hundreds of days) timescales, by taking long-term frequent observations. Our four-year spectroscopic observations indicate that the V/R ratio, i.e., the relative intensity of the violet (V) peak to the red (R) one, of the double-peaked H-alpha line profile varies with a period of 500 days. The H-beta line profile also varies in phase with the H-alpha profile. With these observations covering two full cycles of the V/R variability, we reconstruct the 2-D structure of the Be disc by applying the Doppler tomography method to the H-alpha and H-beta emission line profiles, using a rigidly rotating frame with the V/R variability period. The resulting disc structure reveals non-axisymmetric features, which can be explained by a one-armed perturbation in the Be disc. It is the first time that an eccentric disc structure is directly detected by using a method other than the interferometric one.