Miracle-dz/UniFAR-FTUs huggingface dataset:
Multiple Object 3D-Mapping using a Physics Simulator ; CU-CS-1069-10

—This paper presents a novel method for mapping multiple objects such that their positions are consistent with physics laws. We propose the use of a physics engine to help the robot understand the behavior of rigid bodies and their interaction in the real world. We show how pose estimates obtained from other tracking or modeling techniques can be used in conjunction with the physics simulator in order to reject physically impossible hypotheses in a manner similar to human cognition. We present three different examples which exhibit the advantages of such a paradigm for constructing geometrically and physically sound models of the world.
Physically-based strength model of tantalum incorporating effects of temperature, strain rate and pressure

In this work, we develop a tantalum strength model that incorporates effects of temperature, strain rate and pressure. Dislocation kink-pair theory is used to incorporate temperature and strain rate effects while the pressure dependent yield is obtained through the pressure dependent shear modulus. Material constants used in the model are parameterized from tantalum single crystal tests and polycrystalline ramp compression experiments. It is shown that the proposed strength model agrees well with the temperature and strain rate dependent yield obtained from polycrystalline tantalum experiments. Furthermore, the model accurately reproduces the pressure dependent yield stresses up to 250 GPa. The proposed strength model is then used to conduct simulations of a Taylor cylinder impact test and validated with experiments. This approach provides a physically-based multi-scale strength model that is able to predict the plastic deformation of polycrystalline tantalum through a wide range of temperature, strain and pressure regimes.
Diabetes and Cardiovascular Disease: The “Common Soil” Hypothesis

Unlike classical microvascular complications, large-vessel atherosclerosis can precede the development of diabetes, suggesting that rather than atherosclerosis being a complication of diabetes, both conditions have common genetic and environmental antecedents, i.e., they spring from a “common soil. ” It is now known that adverse environmental conditions, perhaps related to less-than-optimal nutrition, in fetal and early life are associated with an enhanced risk of both diabetes and cardiovascular disease many decades later. These same adverse environmental conditions are also associated with the development in adult life of abdominal obesity and the insulin-resistance syndrome (IRS). The IRS consists of glucose intolerance, hyperinsulinemia, dyslipidemia (high triglyceride and low high-density lipoprotein [HDL] cholesterol levels), and hypertension. Although the mechanism underlying this cluster is controversial, the statistical association is well established. All of the elements of the IRS have been documented as risk factors for type II diabetes. Some, but not all, of these elements are also cardiovascular disease risk factors, in particular, hypertension and low HDL cholesterol. Other factors associated with the IRS that may enhance cardiovascular disease risk are plasminogen activator inhibitor 1 and small, dense low-density lipoprotein particles. Whether insulin itself is a risk factor remains controversial, but recent epidemiological evidence has been mostly negative. This question has marked clinical relevance because if the IRS enhances cardiovascular disease risk by virtue of its concomitant factors and not the hyperinsulinemia per se, this would tend to alleviate concerns that intensive insulin management of type II diabetic subjects could enhance the risk of large-vessel atherosclerosis. Clinical trials are urgently needed to settle this point.
Multi-scale modelling of cracking in cross-ply laminates

Publisher Summary Cross-ply laminates demonstrate a broad variety of failure mechanisms at different scales. Several of these mechanisms are not linked to an instantaneous fracture event of the entire component/structure but result in deterioration of the load-bearing capacity of composite materials. Application of tensile fatigue to cross-ply composites results in matrix-crack initiation at very early stages of their service and, in many cases, at stress levels below the one necessary for the first-crack formation under static loading conditions. With an increase in the number of cycles, the density of matrix cracks grows up to a certain saturation level, known as the characteristic damage state. Matrix cracking in cross-ply laminates under fatigue conditions was extensively studied experimentally using mainly the edge replication technique, X-ray radiography or direct observations of cracking in transparent glass-epoxy laminates. It was found that matrix cracking in cross-ply laminates is not the immediate cause of the global failure of a laminate. It affects the longitudinal stiffness of composites, to a greater extent—glass/epoxy laminates as compared to carbon/epoxy ones; which has been explained by the higher transverse ply stiffness of the former group.
Complementary learning systems within the hippocampus: A neural network modeling approach to reconciling episodic memory with statistical learning

A growing literature suggests that the hippocampus is critical for the rapid extraction of regularities from the environment. Although this fits with the known role of the hippocampus in rapid learning, it seems at odds with the idea that the hippocampus specializes in memorizing individual episodes. In particular, the Complementary Learning Systems theory argues that there is a computational trade-off between learning the specifics of individual experiences and regularities that hold across those experiences. We asked whether it is possible for the hippocampus to handle both statistical learning and memorization of individual episodes. We exposed a neural network model that instantiates known properties of hippocampal projections and subfields to sequences of items with temporal regularities. We found that the monosynaptic pathway — the pathway connecting entorhinal cortex directly to region CA1 — was able to support statistical learning, while the trisynaptic pathway — connecting entorhinal cortex to CA1 through dentate gyrus and CA3 — learned only individual episodes, with apparent representations of regularities resulting from associative reactivation through recurrence. Thus, in paradigms involving rapid learning, the computational trade-off between learning episodes and regularities may be handled by separate anatomical pathways within the hippocampus itself.
Response of the Unicellular Diazotrophic Cyanobacterium Crocosphaera watsonii to Iron Limitation

Iron (Fe) is widely suspected as a key controlling factor of N2 fixation due to the high Fe content of nitrogenase and photosynthetic enzymes complex, and to its low concentrations in oceanic surface seawaters. The influence of Fe limitation on the recently discovered unicellular diazotrophic cyanobacteria (UCYN) is poorly understood despite their biogeochemical importance in the carbon and nitrogen cycles. To address this knowledge gap, we conducted culture experiments on Crocosphaera watsonii WH8501 growing under a range of dissolved Fe concentrations (from 3.3 to 403 nM). Overall, severe Fe limitation led to significant decreases in growth rate (2.6-fold), C, N and chlorophyll a contents per cell (up to 4.1-fold), N2 and CO2 fixation rates per cell (17- and 7-fold) as well as biovolume (2.2-fold). We highlighted a two phased response depending on the degree of limitation: (i) under a moderate Fe limitation, the biovolume of C. watsonii was strongly reduced, allowing the cells to keep sufficient energy to maintain an optimal growth, volume-normalized contents and N2 and CO2 fixation rates; (ii) with increasing Fe deprivation, biovolume remained unchanged but the entire cell metabolism was affected, as shown by a strong decrease in the growth rate, volume-normalized contents and N2 and CO2 fixation rates. The half-saturation constant for growth of C. watsonii with respect to Fe is twice as low as that of the filamentous Trichodesmium indicating a better adaptation of C. watsonii to poor Fe environments than filamentous diazotrophs. The physiological response of C. watsonii to Fe limitation was different from that previously shown on the UCYN Cyanothece sp, suggesting potential differences in Fe requirements and/or Fe acquisition within the UCYN community. These results contribute to a better understanding of how Fe bioavailability can control the activity of UCYN and explain the biogeography of diverse N2 fixers in ocean.
Speciation on Oceanic Islands: Rapid Adaptive Divergence vs. Cryptic Speciation in a Guadalupe Island Songbird (Aves: Junco)

The evolutionary divergence of island populations, and in particular the tempo and relative importance of neutral and selective factors, is of central interest to the study of speciation. The rate of phenotypic evolution upon island colonization can vary greatly among taxa, and cases of convergent evolution can further confound the inference of correct evolutionary histories. Given the potential lability of phenotypic characters, molecular dating of insular lineages analyzed in a phylogenetic framework provides a critical tool to test hypotheses of phenotypic divergence since colonization. The Guadalupe junco is the only insular form of the polymorphic dark-eyed junco (Junco hyemalis), and shares eye and plumage color with continental morphs, yet presents an enlarged bill and reduced body size. Here we use variation in mtDNA sequence, morphological traits and song variables to test whether the Guadalupe junco evolved rapidly following a recent colonization by a mainland form of the dark-eyed junco, or instead represents a well-differentiated “cryptic” lineage adapted to the insular environment through long-term isolation, with plumage coloration a result of evolutionary convergence. We found high mtDNA divergence of the island lineage with respect to both continental J. hyemalis and J. phaeonotus, representing a history of isolation of about 600,000 years. The island lineage was also significantly differentiated in morphological and male song variables. Moreover, and contrary to predictions regarding diversity loss on small oceanic islands, we document relatively high levels of both haplotypic and song-unit diversity on Guadalupe Island despite long-term isolation in a very small geographic area. In contrast to prevailing taxonomy, the Guadalupe junco is an old, well-differentiated evolutionary lineage, whose similarity to mainland juncos in plumage and eye color is due to evolutionary convergence. Our findings confirm the role of remote islands in driving divergence and speciation, but also their potential role as repositories of ancestral diversity.
Automatic music transcription using accelerated multiplicative update for non-negative spectrogram factorization

Music Transcription has been a core field of Music Information Retrieval. Most of the development in MIR is dependent on how efficiently and accurately the notes are extracted. Various methods have been used for Automatic Music Transcription. The most effective ones have been based on Spectral factorization technique for which Non-Negative Matrix Factorization has been profoundly used. Here we use a variant of NMF which is based on Accelerated Multiplicative Update with some predefined templates. The method provides good results on the Disklavier Dataset.
On the Design of Probe Signals in Wireless Acoustic Sensor Networks Self-Positioning Algorithms

A wireless acoustic sensor network comprises a distributed group of devices equipped with audio transducers. Typically, these devices can interoperate with each other using wireless links and perform collaborative audio signal processing. Ranging and self-positioning of the network nodes are examples of tasks that can be carried out collaboratively using acoustic signals. However, the environmental conditions can distort the emitted signals and complicate the ranging process. In this context, the selection of proper acoustic signals can facilitate the attainment of this goal and improve the localization accuracy. This letter deals with the design and evaluation of acoustic probe signals allowing the implementation of ranging applications using unsynchronized audio signals acquired by different network nodes. The proposed signals have been evaluated in diverse simulated environments and implemented in a real deployment. The results confirm the suitability of these signals for implementing localization applications with an accuracy that is in the order of 1 cm.
Clinical Pharmacology in Sleep Medicine

The basic treatment goals of pharmacological therapies in sleep medicine are to improve waking function by either improving sleep or by increasing energy during wakefulness. Stimulants to improve waking function include amphetamine derivatives, modafinil, and caffeine. Sleep aids encompass several classes, from benzodiazepine hypnotics to over-the-counter antihistamines. Other medications used in sleep medicine include those initially used in other disorders, such as epilepsy, Parkinson's disease, and psychiatric disorders. As these medications are prescribed or encountered by providers in diverse fields of medicine, it is important to recognize the distribution of adverse effects, drug interaction profiles, metabolism, and cytochrome substrate activity. In this paper, we review the pharmacological armamentarium in the field of sleep medicine to provide a framework for risk-benefit considerations in clinical practice.
Sol-Gel Synthesis of Bioglasses: A Growth Kinetics Study by Dynamic Light Scattering

In this work, the nucleation of bioglasses particles was approached through Dynamic Light Scattering in order to analyze how different synthesis parameters influence on the particle growth. It was evaluated the following parameters: pH between 10 and 11; surfactant concentration (PEG) between 0 to 20g/L; Three different compositions were chosen based on the 47SiO2-(38 – x)Na2O-(9 + x)CaO-6P2O5 system ( x = 0, 10 and 20). For each experimental condition, the growth kinetics (Kc.t-1) was calculated, and the obtained values were analyzed by factorial design of experiments. The results evidence that higher pH, higher surfactant concentration and lower Na/Ca ionic ratio lead to lower values growth kinetics in which, in turn, are associated with lower particle size.
Design of Multiple-Parameterisation PDC Controllers via Relaxed Conditions for Multi-Dimensional Fuzzy Summations

In this paper, fuzzy controllers extending the Takagi-Sugeno PDC framework are proposed. Instead of being linear in the membership functions, quadratically, cubically, etc. parameterised controllers can be dealt with using recent LMI stability and performance conditions. As a particular case, LMI stability conditions are devised in order to prove state-feedback stabilizability of Takagi-Sugeno fuzzy systems with controllers quadratic in the membership functions, and numerical examples are provided.
Characterization of LiF-based soft X-ray imaging detectors by confocal fluorescence microscopy

X-ray microscopy represents a powerful tool to obtain images of samples with very high spatial resolution. The main limitation of this technique is represented by the poor spatial resolution of standard imaging detectors. We proposed an innovative high-performance X-ray imaging detector based on the visible photoluminescence of colour centres in lithium fluoride. In this work, a confocal microscope in fluorescence mode was used to characterize LiF-based imaging detectors measuring CC integrated visible fluorescence signals of LiF crystals and films (grown on several kinds of substrates) irradiated by soft X-rays produced by a laser plasma source in different exposure conditions. The results are compared with the CC photoluminescence spectra measured on the same samples and discussed.
Pavement Subgrade Stabilization Using Polymers: Characterization and Performance

This paper reports a laboratory investigation aimed at evaluating the potential of polymer binders to stabilize pavement subgrades in Qatar. The conclusions regarding the impact of the polymer stabilizers are based on comparisons with selected physical, chemical, mechanical, and microstructural properties of natural Qatari subgrade soil and soils stabilized with the traditional standard, portland cement (PC). The results demonstrate that the polymer binders modify the Qatari subgrade soils resulting in more favorable engineering properties: for example, the compressive strengths of the polymer-stabilized soils are superior to those of the unstabilized soils and those stabilized using PC. The mechanical properties of the stabilized and unstabilized soils were incorporated in the analysis of asphalt pavement sections using the state-of-the-art protocol for pavement design and analysis. Results of the analysis further demonstrated the benefits of using stabilized subgrade soils in improving pavement performance. Of particular practical importance is that polymer subgrade stabilization significantly reduces subgrade rutting. Consequently, polymer subgrade stabilization is a key consideration for perpetual pavements, especially considering the extremely high truck traffic in Qatar. Although the work reported in this paper was carried out with Qatari soil, the results are expected to be relevant to other types of soil and weather conditions experienced throughout the Middle East and in similar climates throughout the world.
Synthesis of vertically aligned ultra-long ZnO nanowires on heterogeneous substrates with catalyst at the root

The synthesis of ultra-long high-quality ZnO nanowires with uniform size and orientation on heterogeneous substrates is highly desirable, not only for investigating the fundamental properties of ZnO nanowires, but also for fabricating integrated functional nanodevices. Here we present a novel and general technique for growing vertically aligned ultra-long ZnO nanowires on various substrates. More importantly, the metal catalyst is experimentally determined not at the tip ends of the nanowires but at the junction area between the nanowires and the underlying substrate. Based on detailed analysis and control group results, we then propose a three-stage growth mechanism, in which vapor–liquid–solid growth and vapor–solid growth compete with each other to become dominant.
Characterisation of the p53-Mediated Cellular Responses Evoked in Primary Mouse Cells Following Exposure to Ultraviolet Radiation

Exposure to ultraviolet (UV) light can cause significant damage to mammalian cells and, although the spectrum of damage produced varies with the wavelength of UV, all parts of the UV spectrum are recognised as being detrimental to human health. Characterising the cellular response to different wavelengths of UV therefore remains an important aim so that risks and their moderation can be evaluated, in particular in relation to the initiation of skin cancer. The p53 tumour suppressor protein is central to the cellular response that protects the genome from damage by external agents such as UV, thus reducing the risk of tumorigenesis. In response to a variety of DNA damaging agents including UV light, wild-type p53 plays a role in mediating cell-cycle arrest, facilitating apoptosis and stimulating repair processes, all of which prevent the propagation of potentially mutagenic defects. In this study we examined the induction of p53 protein and its influence on the survival of primary mouse fibroblasts exposed to different wavelengths of UV light. UVC was found to elevate p53 protein and its sequence specific DNA binding capacity. Unexpectedly, UVA treatment failed to induce p53 protein accumulation or sequence specific DNA binding. Despite this, UVA exposure of wild-type cells induced a p53 dependent G1 cell cycle arrest followed by a wave of p53 dependent apoptosis, peaking 12 hours post-insult. Thus, it is demonstrated that the elements of the p53 cellular response evoked by exposure to UV radiation are wavelength dependent. Furthermore, the interrelationship between various endpoints is complex and not easily predictable. This has important implications not only for understanding the mode of action of p53 but also for the use of molecular endpoints in quantifying exposure to different wavelengths of UV in the context of human health protection.
Image annotation using deep learning: A review

In the last few years, deep learning has led to huge success in the field of computer vision and natural language understanding and also in the interplay between them. Among different types of deep learning models, convolutional neural networks have been most extensively studied for the tasks related to visual perception and machine vision. Due to lack of computational resources and training data, it is very hard to the use high-capacity convolutional neural network without overfitting. But recent growth in the availability of annotated data and high performance GPUs have made it possible to obtain state-of-the-art results using convolutional neural networks. In this paper, we present a review on how and why CNNs are extensively getting used in the computer vision community. It also introduces an application of ConvNets for annotating contents of the image by partially localizing them.
Mapping between 6 Multiattribute Utility Instruments

Background: Cost-utility analyses commonly employ a multiattribute utility (MAU) instrument to estimate the health state utilities, which are needed to calculate quality-adjusted life years. Different MAU instruments predict significantly different utilities, which makes comparison of results from different evaluation studies problematical. Aim: This article presents mapping functions (“crosswalks”) from 6 MAU instruments (EQ-5D-5L, SF-6D, Health Utilities Index 3 [HUI 3], 15D, Quality of Well-Being [QWB], and Assessment of Quality of Life 8D [AQoL-8D]) to each of the other 5 instruments in the study: a total of 30 mapping functions. Methods: Data were obtained from a multi-instrument comparison survey of the public and patients in 7 disease areas conducted in 6 countries (Australia, Canada, Germany, Norway, United Kingdom, and United States). The 8022 respondents were administered each of the 6 study instruments. Mapping equations between each instrument pair were estimated using 4 econometric techniques: ordinary least squares, generalized linear model, censored least absolute deviations, and, for the first time, a robust MM-estimator. Results: Goodness-of-fit indicators for each of the results are within the range of published studies. Transformations reduced discrepancies between predicted utilities. Incremental utilities, which determine the value of quality-related health benefits, are almost perfectly aligned at the sample means. Conclusion: Transformations presented here align the measurement scales of MAU instruments. Their use will increase confidence in the comparability of evaluation studies, which have employed different MAU instruments.
Toward Dual-functional Radar-Communication Systems: Optimal Waveform Design

We focus on a dual-functional multi-input-multi-output (MIMO) radar-communication (RadCom) system, where a single transmitter with multiple antennas communicates with downlink cellular users and detects radar targets simultaneously. Several design criteria are considered for minimizing the downlink multiuser interference. First, we consider both omnidirectional and directional beampattern design problems, where the closed-form globally optimal solutions are obtained. Based on the derived waveforms, we further consider weighted optimizations targeting a flexible tradeoff between radar and communications performance and introduce low-complexity algorithms. Moreover, to address the more practical constant modulus waveform design problem, we propose a branch-and-bound algorithm that obtains a globally optimal solution, and derive its worst-case complexity as function of the maximum iteration number. Finally, we assess the effectiveness of the proposed waveform design approaches via numerical results.