Miracle-dz/UniFAR-FTUs huggingface dataset:
First MHD simulation of collapse and fragmentation of magnetized molecular cloud cores

This is the first paper about fragmentation and mass outflow in molecular clouds by using three-dimensional magnetohydrodynamical (MHD) nested-grid simulations. The binary star formation process is studied, paying particular attention to the fragmentation of a rotating magnetized molecular cloud. We assume an isothermal rotating and magnetized cylindrical cloud in hydrostatic balance. Non-axisymmetric as well as axisymmetric perturbations are added to the initial state and the subsequent evolutions are studied. The evolution is characterized by three parameters: the amplitude of the non-axisymmetric perturbations, the rotation speed and the magnetic field strength. As a result, it is found that non-axisymmetry hardly evolves in the early phase, but begins to grow after the gas contracts and forms a thin disc. Disc formation is strongly promoted by the rotation speed and the magnetic field strength. There are two types of fragmentation: that from a ring and that from a bar. Thin adiabatic cores fragment if their thickness is less than 1/4 of the radius. For the fragments to survive, they should be formed in a heavily elongated barred core or a flat round disc. In the models showing fragmentation, outflows from respective fragments are found as well as those driven by the rotating bar or the disc.
The Early X-Ray Emission from V382 Velorum (Nova Velorum 1999): An Internal Shock Model

We present the results of ASCA and RXTE observations of the early X-ray emission from the classical nova V382 Velorum. Its ASCA spectrum was hard (kT ~ 10 keV) with strong (1023 cm-2) intrinsic absorption. In the subsequent RXTE data, the spectra became softer, because of both a declining temperature and a diminishing column. We argue that this places the X-ray emission interior to the outermost ejecta produced by V382 Vel in 1999, and therefore it must have been the result of a shock internal to the nova ejecta. The weakness of the Fe Kα lines probably indicates that the X-ray-emitting plasmas are not in ionization equilibrium.
Connectomic Analysis of Brain Networks: Novel Techniques and Future Directions

Brain networks, localized or brain-wide, exist only at the cellular level, i.e., between specific pre- and post-synaptic neurons, which are connected through functionally diverse synapses located at specific points of their cell membranes. “Connectomics” is the emerging subfield of neuroanatomy explicitly aimed at elucidating the wiring of brain networks with cellular resolution and a quantified accuracy. Such data are indispensable for realistic modeling of brain circuitry and function. A connectomic analysis, therefore, needs to identify and measure the soma, dendrites, axonal path, and branching patterns together with the synapses and gap junctions of the neurons involved in any given brain circuit or network. However, because of the submicron caliber, 3D complexity, and high packing density of most such structures, as well as the fact that axons frequently extend over long distances to make synapses in remote brain regions, creating connectomic maps is technically challenging and requires multi-scale approaches, Such approaches involve the combination of the most sensitive cell labeling and analysis methods available, as well as the development of new ones able to resolve individual cells and synapses with increasing high-throughput. In this review, we provide an overview of recently introduced high-resolution methods, which researchers wanting to enter the field of connectomics may consider. It includes several molecular labeling tools, some of which specifically label synapses, and covers a number of novel imaging tools such as brain clearing protocols and microscopy approaches. Apart from describing the tools, we also provide an assessment of their qualities. The criteria we use assess the qualities that tools need in order to contribute to deciphering the key levels of circuit organization. We conclude with a brief future outlook for neuroanatomic research, computational methods, and network modeling, where we also point out several outstanding issues like structure–function relations and the complexity of neural models.
Semi-Supervised Discriminative Mutual Subspace Method

Subspace recognition has recently attracted more attention for vector set or image set matching in machine learning and computer vision. In this paper, we firstly give a more simple proof of Procrustes metric (Theorem 2) than literature [1,7]. Then, a novel Semi-Supervised Discriminative Mutual Subspace Method (SS-DMSM) is proposed based on Procrustes metric. For finding a better discriminative subspace, our SS-DMSM algorithm sufficiently considers the intrinsic geometric information on Grassmann manifold that is the set of all subspaces, and effectively uses the label information of those training subspaces. Experimental results on Cambridge gesture database and ETH-80 database show that our SS-DMSM algorithm outperforms the classical MSM and CMSM algorithms.
Effect of Copulins on Rating of Female Attractiveness, Mate-Guarding, and Self-Perceived Sexual Desirability

Olfaction and chemical signaling play an important role in the mating behaviors of many taxa, yet there is minimal empirical research on human putative pheromones. A mixture of five volatile fatty acids secreted vaginally, identified and named “copulins,” significantly increase in concentration during the follicular phase and decrease in concentration during the luteal phase in nonpill using women. Men exposed to copulins exhibit an increase in testosterone, are inhibited in discriminating the attractiveness of women’s faces, and behave less cooperatively. According to Anisogamy, Sexual Selection and Parental Investment Theory, mammalian males, having low cost and high benefit from any copulatory interaction, may adaptively utilize any useful cues to identifying ovulating females and adjust their behavior accordingly in order to maximize their potential reproductive success. In the current study, we attempted a replication of Jütte and Grammer’s finding indicating copulins inhibit the ability of men to discriminate attractiveness of women’s faces, and we examined the role of copulins in self-reported mate-guarding behaviors and self-perceived sexual desirability. We utilized a randomized placebo-controlled design and as predicted, results indicated men exposed to copulins were more likely to rate themselves as sexually desirable to women and, on average, the copulin group rated women’s faces as more attractive than controls. There were no significant findings with mate guarding.
Uplink Downlink Rate Balancing in Cooperating Cellular Networks

Broadcast MIMO techniques can significantly increase the throughput in the downlink of cellular networks, at the price of channel state information (CSI) feedback from the mobiles, sent over the uplink. Thus, these techniques create a mechanism that can tradeoff some uplink capacity for increased downlink capacity. In this paper, we quantify this tradeoff and study the exchange ratio between the feedback rate (over the uplink) and the downlink rate. We study both finite and infinite networks and show that for high enough (but finite) SNR, the uplink rate can be exchanged for increased downlink rate with a favorable exchange ratio. This exchange ratio is an increasing function of the channel coherence time, and a decreasing function of the number of measured base stations. We also show that in finite networks, devoting a constant fraction of the uplink to CSI feedback can increase the downlink multiplexing gain continuously from 0 to 1, as a function of the fraction size. On the other hand, in infinite networks (with infinite connectivity) our lower bound is only able to show doubly logarithmic scaling of the rate with SNR. The presented results prove that the adaptation of the feedback rate can control the balance between the uplink and downlink rates. This capability is very important in modern cellular networks, where the operators need to respond to continuously changing user demands.
Diviz: an MCDA workflow design, execution and sharing tool

The diviz software is a tool for designing, executing and sharing Multiple Criteria Decision Aid (MCDA) techniques. The target user community of diviz reaches from researchers who require to construct algorithmic workflows from elementary MCDA components to teachers who need to present MCDA methods and let their students experiment them. Besides, one of the principal features of diviz is to ease the comparison of results results issued from different methods on the same decision problem. This allows among others to check the robustness of the output of a decision aid process with respect to the choice of the decision aid technique.
Teaching Mathematics using Augmented Reality

Information technology enables us to develop innovative learning/teaching tools for mathematics education both in the classroom and out-of-school activities. This paper shows a brief potential and challenges of using Augmented Reality (AR) in mathematics education. The learners can view geometrical objects in 3dimention having better understanding of the structures. Mobile phones or computer tablets can be used to view the 3D geometrical objects using special application software. Autodesk Maya software is used to draw geometrical objects and some AR viewing software can be used to view the objects in 3D. This paper will describe how to develop a simple AR system for the improvement of abilities of learning mathematics. Sample AR materials used for mathematics education at high school as well as university level will also be discussed.
Safety and Effectiveness of Mycophenolate in Systemic Sclerosis. A Systematic Review

Background Mycophenolate is increasingly being used in the rheumatic diseases. Its main adverse effects are gastrointestinal, myelosuppression, and infection. These may limit use in systemic sclerosis (SSc) since gastrointestinal involvement is common. The objective of this study is to evaluate gastrointestinal adverse events of mycophenolate in SSc. Secondarily we evaluated other adverse events, and the effectiveness of mycophenolate in skin and lung disease. Methods A literature search of Medline, Embase, Cochrane Central Register of Controlled Trials, and CINAHL (inception-2013) was performed. Studies reporting use of mycophenolate in SSc patients, adverse events, modified Rodnan skin score (MRSS), forced vital capacity (FVC), or diffusing capacity of carbon monoxide (DLCO) were included. The primary outcome was gastrointestinal events occurring after the initiation of mycophenolate. Secondary safety outcomes included myelosuppression, infection, malignancy, and death after the initiation of mycophenolate. Results 617 citations were identified and 21 studies were included. 487 patients were exposed to mycophenolate. The mean disease duration ranged between 0.8-14.1 years. There were 18 deaths and 90 non-lethal adverse events. The non-lethal adverse events included 43 (47.7%) gastrointestinal events, 34 (26%) infections, 6 (5%) cytopenias and 2 (2%) malignancies. The most common gastrointestinal events included diarrhea (n=18 (14%)), nausea (n=12 (9%)), and abdominal pain (n=3 (2%)). The rate of discontinuation ranged between 8%-40%. Seven observational studies reported improvement or stabilization in FVC, and 5 studies report stabilization or improvement in MRSS. Conclusion Mycophenolate-associated gastrointestinal adverse events are common in SSc, but not severe enough to preclude its use. Observational data suggests mycophenolate may be effective in improving or stabilizing interstitial lung disease, and skin involvement.
Landscape genomics reveal signatures of local adaptation in barley (Hordeum vulgare L.)

Land plants are sessile organisms that cannot escape the adverse climatic conditions of a given environment. Hence, adaptation is one of the solutions to surviving in a challenging environment. This study was aimed at detecting adaptive loci in barley landraces that are affected by selection. To that end, a diverse population of barley landraces was analyzed using the genotyping by sequencing approach. Climatic data for altitude, rainfall and temperature were collected from 61 weather sites near the origin of selected landraces across Ethiopia. Population structure analysis revealed three groups whereas spatial analysis accounted significant similarities at shorter geographic distances (< 40 Km) among barley landraces. Partitioning the variance between climate variables and geographic distances indicated that climate variables accounted for most of the explainable genetic variation. Markers by climatic variables association analysis resulted in altogether 18 and 62 putative adaptive loci using Bayenv and latent factor mixed model (LFMM), respectively. Subsequent analysis of the associated SNPs revealed putative candidate genes for plant adaptation. This study highlights the presence of putative adaptive loci among barley landraces representing original gene pool of the farming communities.
A manual alphabet for touchless gesture-controlled writing input with a myoelectric device : Design, evaluation and user experience

The research community around gesture-based interaction has so far not paid attention to the possibility of replacing the keyboard with natural gestures for writing purposes. Additionally, insight into the actual user experience of such an interaction style is only insufficiently provided. This work presents a novel approach for text input that is based on a manual alphabet, MATImyo. The hand alphabet was developed in a user-centered design process involving potential users in pre-studies, design process and evaluation procedure. In a Wizard-of-Oz style experiment with accompanying interviews, the alphabet’s quality as input language for composing electronic texts was evaluated and the user experience of such an interaction style assessed. MATImyo was found to be very suitable as gestural input language with a positive user experience. The whole process of designing MATImyo and evaluating its suitability and user experience was based on the principles of Embodied Interaction, which was chosen as theoretical framework. This work contributes to understanding the bigger picture of the user experience of gesture-based interaction and presents a novel, more natural text input method.
Image fusion based on steerable pyramid and PCNN

A new image fusion algorithm, based on steerable pyramid and Pulse Coupled Neural Network (PCNN), is proposed in this paper. First, original images are decomposed into several subbands of different levels and orientations by steerable pyramid. Then, low frequency subbands are fused by weighting and high frequency subbands are fused by PCNN. The fused image is obtained by inverse steerable pyramid transform. Results testify our approach in comparison with wavelets fusion in both subjective visual effect and objective evaluation criteria while using four different pairs of test images.
Massive MIMO Performance Evaluation Based on Measured Propagation Data

Massive MIMO, also known as very-large MIMO or large-scale antenna systems, is a new technique that potentially can offer large network capacities in multi-user scenarios. With a massive MIMO system, we consider the case where a base station equipped with a large number of antenna elements simultaneously serves multiple single-antenna users in the same time-frequency resource. So far, investigations are mostly based on theoretical channels with independent and identically distributed (i.i.d.) complex Gaussian coefficients, i.e., i.i. d. Rayleigh channels. Here, we investigate how massive MIMO performs in channels measured in real propagation environments. Channel measurements were performed at 2.6 GHz using a virtual uniform linear array (ULA), which has a physically large aperture, and a practical uniform cylindrical array (UCA), which is more compact in size, both having 128 antenna ports. Based on measurement data, we illustrate channel behavior of massive MIMO in three representative propagation conditions, and evaluate the corresponding performance. The investigation shows that the measured channels, for both array types, allow us to achieve performance close to that in i.i. d. Rayleigh channels. It is concluded that in real propagation environments we have characteristics that can allow for efficient use of massive MIMO, i.e., the theoretical advantages of this new technology can also be harvested in real channels.
Toward a Better Understanding of Leaderboard

The leaderboard in machine learning competitions is a tool to show the performance of various participants and to compare them. However, the leaderboard quickly becomes no longer accurate, due to hack or overfitting. This article gives two pieces of advice to prevent easy hack or overfitting. By following these advice, we reach the conclusion that something like the Ladder leaderboard introduced in [blum2015ladder] is inevitable. With this understanding, we naturally simplify Ladder by eliminating its redundant computation and explain how to choose the parameter and interpret it. We also prove that the sample complexity is cubic to the desired precision of the leaderboard.
No Systematic Early Bias to Mediterranean 14C Ages: Radiocarbon Measurements from Tree-Ring and Air Samples Provide Tight Limits to Age Offsets

Existing data and theory do not support a recent assertion that upwelling of old carbon has led to systematically 100–300 yr too old radiocarbon ages for the Mediterranean region. Similarly, the prehistoric tree-ring record produced over 3 decades by the Aegean Dendrochronology Project is shown to provide robust, well-replicated data, contrary to a recent unfounded assertion. 14C and dendrochronology provide an accurate and precise chronometric framework for the Mediterranean region.
Association between the rs2910164 Polymorphism in Pre-Mir-146a Sequence and Thyroid Carcinogenesis

Background Rs2910164, a Single nucleotide polymorphism (SNP) located in the precursor microRNA sequence of miR-146a, is the only MicroRNA sequence SNP studied in papillary thyroid cancer (PTC). Association studies had been performed in US and UK-Northern European populations, but results were inconsistence. This study evaluated the association between rs2910164 and the risk of PTC as well as benign thyroid tumor (BN), and examined the clinicopathological characteristics of PTC and BN for different genotypes. Methods This case-control study genotyped rs2910164 in 753 PTCs, 484 BNs and 760 controls in a Chinese Han population. Clinicopathological and genetic data were collected and compared. Multivariate logistic regression was performed to calculate adjusted odds ratios (ORs). Results There were no differences in rs2910164 genotype distributions between the three groups. PTC cases with three genotypes (CC, CG, GG) had similar clinicopathological characteristics except the existence of “para-cancer” BN (PTC/BN, P = 0.006). PTC/BN patients were older (P = 0.009), and had smaller cancer lesions (P<0.001), lower serum thyrotropin levels (1.82±1.42 vs. 2.21±1.74, P = 0.04), and lower rates of level VI lymph node metastasis (20.8% vs. 52.7%, P<0.001) and lateral neck lymph node metastasis (11.5% vs. 23.0%, P = 0.011) compared with PTC only. Then we supposed a possible progression from BN to PTC which may involve rs2910164 in and performed a multivariate logistic regression analysis of PTC/BN and BN cases to determine risk factors of this progression. Results showed that the rs2910164 GG homozygote (OR = 2.25, 95% CI 1.22–4.14, P = 0.01) was the only risk factor in this study. Conclusion Rs2910164 was not associated with increased risk of PTC and BN in Chinese patients, but may play a latent role in the transformation from BN to PTC.
Texture-less object tracking with online training using an RGB-D camera

We propose a texture-less object detection and 3D tracking method which automatically extracts on the fly the information it needs from color images and the corresponding depth maps. While texture-less 3D tracking is not new, it requires a prior CAD model, and real-time methods for detection still have to be developed for robust tracking. To detect the target, we propose to rely on a fast template-based method, which provides an initial estimate of its 3D pose, and we refine this estimate using the depth and image contours information. We automatically extract a 3D model for the target from the depth information. To this end, we developed methods to enhance the depth map and to stabilize the 3D pose estimation. We demonstrate our method on challenging sequences exhibiting partial occlusions and fast motions.
(Web Search) shared Social Aspects of a Collaborative, Community-based Search Network

Collaborative Web search (CWS) is a community-based approach to Web search that supports the sharing of past result selections among a group of related searchers so as to personalize result-lists to reﬂect the preferences of the community as a whole. In this paper, we present the results of a recent live-user trial which demonstrates how CWS elicits high levels of participation and how the search activities of a community of related users form a type of social search network.
Hybrid force/position control of robotic drilling system

This paper presents the design steps and implementation results of a hybrid force/position control of the arm. The HFP control is based on a Proportional-Derivative Controller combined with feed-forward position control and multi-stage Infinite Impulse Response (IIR) filter in the joint space position control loop. In the outer loop, a resolved-velocity force control scheme is used. The performance of system is tested experimentally on CRS robot arm with Kflop based controller. The results obtained in terms of motion error and force control show that the proposed system can be efficiently used for critical robot drilling applications such as robot assisted orthopedic surgical procedures.
Why Do Households Forego High Returns from Technology Adoption

Around 3 billion people in developing countries rely on woodfuels for their daily cooking needs with profound negative implications for their workload, health, and budget as well as the environment. Improved cookstove (ICS) technologies in many cases appear to be an obvious solution. Despite continuous efforts of the international community to disseminate ICS, take up rates in most developing countries are strikingly low. In this paper, we examine the reasons for (non-)adoption of a very simple ICS in urban Burkina Faso. As a first result, we find that ICS users save between 20 and 30 percent of fuels compared to traditional stoves making the investment a very profitable one. Nonetheless, adoption rates are low at a mere 10 percent. It turns out that the major deterrent of adoption are the upfront investment costs – which are much more important than access to information, taste preferences, or the woman’s role in the household. These findings suggest that more direct promotion strategies such as subsidies would help the household to overcome its liquidity constraints and hence improve adoption rates.