Miracle-dz/UniFAR-FTUs huggingface dataset:
Evolution of asymptotic giant branch stars. I. Updated synthetic TP-AGB models and their basic calibration

We present new synthetic models of the TP-AGB evolution. They are computed for 7 values of initial metal content (Z from 0.0001 to 0.03) and for initial masses between 0.5 and 5.0 M� , thus extending the low- and intermediate-mass tracks of Girardi et al. (2000) to the beginning of the post-AGB phase. The calculations are performed by means of a synthetic code that incorporates many recent improvements, among which we mention: (1) the use of detailed and revised analytical relations to describe the evolution of quiescent luminosity, inter-pulse period, third dredge-up, hot bottom burning, pulse cycle luminosity variations, etc.; (2) the use of variable molecular opacities – i.e. opacities consistent with the changing photospheric chemical composition – in the integration of a complete envelope model, instead of the standard choice of scaled-solar opacities; (3) the use of formalisms for the mass-loss rates derived from pulsating dust-driven wind models of C- and O-rich AGB stars; and (4) the switching of pulsation modes between the first overtone and the fundamental one along the evolution, which has consequences in terms of the history of mass loss. It follows that, in addition to the time evolution on the HR diagram, the new models also consistently predict variations in surface chemical compositions, pulsation modes and periods, and mass-loss rates. The onset and efficiency of the third dredge-up process are calibrated in order to reproduce basic observables like the carbon star luminosity functions in the Magellanic Clouds and TP-AGB lifetimes (star counts) in Magellanic Cloud clusters. In this first paper, we describe in detail the model ingredients, basic properties, and calibration. Particular emphasis is put on illustrating the effects of using variable molecular opacities. Forthcoming papers will present the theoretical isochrones and chemical yields derived from these tracks and additional tests performed with the aid of a complete population synthesis code.
Stable, Robust, and Super Fast Reconstruction of Tensors Using Multi-Way Projections

In the framework of multidimensional Compressed Sensing (CS), we introduce an analytical reconstruction formula that allows one to recover an Nth-order data tensor X ∈ \BBRI1×I2×. ×IN from a reduced set of multi-way compressive measurements by exploiting its low multilinear-rank structure. Moreover, we show that, an interesting property of multi-way measurements allows us to build the reconstruction based on compressive linear measurements taken only in two selected modes, independently of the tensor order N. In addition, it is proved that, in the matrix case and in a particular case with 3rd-order tensors where the same 2D sensor operator is applied to all mode-3 slices, the proposed reconstruction Xτ is stable in the sense that the approximation error is comparable to the one provided by the best low-multilinear-rank approximation, where τ is a threshold parameter that controls the approximation error. Through the analysis of the upper bound of the approximation error we show that, in the 2D case, an optimal value for the threshold parameter τ = τ0 > 0 exists, which is confirmed by our simulation results. On the other hand, our experiments on 3D datasets show that very good reconstructions are obtained using τ = 0, which means that this parameter does not need to be tuned. Our extensive simulation results demonstrate the stability and robustness of the method when it is applied to real-world 2D and 3D signals. A comparison with state-of-the-arts sparsity based CS methods specialized for multidimensional signals is also included. A very attractive characteristic of the proposed method is that it provides a direct computation, i.e., it is non-iterative in contrast to all existing sparsity based CS algorithms, thus providing super fast computations, even for large datasets.
Myelination of major white matter tracts continues beyond childhood—combining tractography and myelin water imaging

Axonal myelination is a key white matter maturation process as it increases conduction velocity, synchrony, and reliability. While diffusion tensor imaging (DTI) is sensitive to myelination, it is also sensitive to unrelated microstructural properties, thus hindering straightforward interpretations. Myelin water imaging (MWI) provides a more reliable and direct in vivo measure of myelination. Although early histological studies show protracted myelination from childhood to adulthood, reliable tract-specific in vivo evidence from MWI is still lacking. Here, we combine MWI and DTI tractography to investigate myelination in middle childhood, late childhood, and adulthood in 18 major white matter tracts. In the vast majority of major white matter tracts, myelin water fraction continued to increase beyond late childhood. Our study provides first in vivo evidence for protracted myelination beyond late childhood.
Non-rigid Segmentation Using Sparse Low Dimensional Manifolds and Deep Belief Networks

In this paper, we propose a new methodology for segmenting non-rigid visual objects, where the search procedure is onducted directly on a sparse low-dimensional manifold, guided by the classification results computed from a deep belief network. Our main contribution is the fact that we do not rely on the typical sub-division of segmentation tasks into rigid detection and non-rigid delineation. Instead, the non-rigid segmentation is performed directly, where points in the sparse low-dimensional can be mapped to an explicit contour representation in image space. Our proposal shows significantly smaller search and training complexities given that the dimensionality of the manifold is much smaller than the dimensionality of the search spaces for rigid detection and non-rigid delineation aforementioned, and that we no longer require a two-stage segmentation process. We focus on the problem of left ventricle endocardial segmentation from ultrasound images, and lip segmentation from frontal facial images using the extended Cohn-Kanade (CK+) database. Our experiments show that the use of sparse low dimensional manifolds reduces the search and training complexities of current segmentation approaches without a significant impact on the segmentation accuracy shown by state-of-the-art approaches.
Appears in Working Notes, Integrating Multiple Learned Models for Improving and Scaling Machine Learning Algorithms

This paper presents the Plannett system, which combines artiicial neural networks to achieve expert-level accuracy on the diicult scientiic task of recognizing volcanos in radar images of the surface of the planet Venus. Plannett uses ANNs that vary along two dimensions: the set of input features used to train and the number of hidden units. The ANNs are combined simply by averaging their output activations. When Plannett is used as the classiication module of a three-stage image analysis system called JAR-tool, the end-to-end accuracy (sensitivity and speci-city) is as good as that of a human planetary geologist on a four-image test suite. JARtool-Plannett also achieves the best algorithmic accuracy on these images to date.
Minimal Clinically Important Difference in Parkinson's Disease as Assessed in Pivotal Trials of Pramipexole Extended Release

Background. The minimal clinically important difference (MCID) is the smallest change in an outcome measure that is meaningful for patients. Objectives. To calculate the MCID for Unified Parkinson's Disease Rating Scale (UPDRS) scores in early Parkinson's disease (EPD) and for UPDRS scores and “OFF” time in advanced Parkinson's disease (APD). Methods. We analyzed data from two pivotal, double-blind, parallel-group trials of pramipexole ER that included pramipexole immediate release (IR) as an active comparator. We calculated MCID as the mean change in subjects who received active treatment and rated themselves “a little better” on patient global impression of improvement (PGI-I) minus the mean change in subjects who received placebo and rated themselves unchanged. Results. MCIDs in EPD (pramipexole ER, pramipexole IR) for UPDRS II were −1.8 and −2.0, for UPDRS III −6.2 and −6.1, and for UPDRS II + III −8.0 and −8.1. MCIDs in APD for UPDRS II were −1.8 and −2.3, for UPDRS III −5.2 and −6.5, and for UPDRS II + III −7.1 and −8.8. MCID for “OFF” time (pramipexole ER, pramipexole IR) was −1.0 and −1.3 hours. Conclusions. A range of MCIDs is emerging in the PD literature that provides the basis for power calculations and interpretation of clinical trials.
Compiling CHR to parallel hardware

This paper investigates the compilation of a committed-choice rule-based language, Constraint Handling Rules (CHR), to specialized hardware circuits. The developed hardware is able to turn the intrinsic concurrency of the language into parallelism. Rules are applied by a custom executor that handles constraints according to the best degree of parallelism the implemented CHR specification can offer. Our framework deploys the target digital circuits through the Field Programmable Gate Array (FPGA) technology, by first compiling the CHR code fragment into a low level hardware description language. We also discuss the realization of a hybrid CHR interpreter, consisting of a software component running on a general purpose processor, coupled with a hardware accelerator. The latter unburdens the processor by executing in parallel the most computational intensive CHR rules directly compiled in hardware. Finally the performance of a prototype system is evaluated by time efficiency measures.
Inflammasome Sensor Nlrp1b-Dependent Resistance to Anthrax Is Mediated by Caspase-1, IL-1 Signaling and Neutrophil Recruitment

Bacillus anthracis infects hosts as a spore, germinates, and disseminates in its vegetative form. Production of anthrax lethal and edema toxins following bacterial outgrowth results in host death. Macrophages of inbred mouse strains are either sensitive or resistant to lethal toxin depending on whether they express the lethal toxin responsive or non-responsive alleles of the inflammasome sensor Nlrp1b (Nlrp1bS/S or Nlrp1bR/R, respectively). In this study, Nlrp1b was shown to affect mouse susceptibility to infection. Inbred and congenic mice harboring macrophage-sensitizing Nlrp1bS/S alleles (which allow activation of caspase-1 and IL-1β release in response to anthrax lethal toxin challenge) effectively controlled bacterial growth and dissemination when compared to mice having Nlrp1bR/R alleles (which cannot activate caspase-1 in response to toxin). Nlrp1bS-mediated resistance to infection was not dependent on the route of infection and was observed when bacteria were introduced by either subcutaneous or intravenous routes. Resistance did not occur through alterations in spore germination, as vegetative bacteria were also killed in Nlrp1bS/S mice. Resistance to infection required the actions of both caspase-1 and IL-1β as Nlrp1bS/S mice deleted of caspase-1 or the IL-1 receptor, or treated with the Il-1 receptor antagonist anakinra, were sensitized to infection. Comparison of circulating neutrophil levels and IL-1β responses in Nlrp1bS/S,Nlrp1bR/ R and IL-1 receptor knockout mice implicated Nlrp1b and IL-1 signaling in control of neutrophil responses to anthrax infection. Neutrophil depletion experiments verified the importance of this cell type in resistance to B. anthracis infection. These data confirm an inverse relationship between murine macrophage sensitivity to lethal toxin and mouse susceptibility to spore infection, and establish roles for Nlrp1bS, caspase-1, and IL-1β in countering anthrax infection.
Quality Control in Pharmaceuticals: Residual Solvents Testing and Analysis

Organic solvents are constantly present in the pharmaceutical production processes. They are usually used at any step of the synthesis pathway during the drug product formulation process. Organic solvents play an important role in the pharmaceutical industry, and appropriate selection of the solvents for the synthesis of drug substance may enhance the yield, or determine characteristics such as crystal form, purity, and solubility. Because of some physical and chemical property, the solvents are not completely removed by practical manufacturing techniques. Usually some small amounts of solvents may remain in the final drug product. They are called as residual solvents. Thus, residual solvents in pharmaceuticals are defined as organic volatile chemicals that are used or produced in the manufacture of drug substances or excipients, or in the preparation of drug products (International Conference on Harmonisation of Technical Requirement for Registration of Pharmaceuticals for Human Use [ICH], 2009). Since there is no therapeutic benefit from residual solvents, all residual solvents should be removed to the extent possible to meet product specifications, good manufacturing practices, or other quality-based requirements. If the presence of residual solvents in pharmaceuticals exceeds tolerance limits as suggested by safety data, they may be harmful to the human health and to the environment. That’s the reason that residual solvents testing become one of the important parts of quality control in pharmaceuticals. This chapter will review the regulation of residual solvents and methods for residual solvents testing and analysis. Special emphasis will be given to the recent progress of residual solvents analysis and systematic study on residual solvents analysis in pharmaceuticals.
Matrix vesicles in the fibrous cap of atherosclerotic plaque: possible contribution to plaque rupture

Plaque rupture is the most common type of plaque complication and leads to acute ischaemic events such as myocardial infarction and stroke. Calcification has been suggested as a possible indicator of plaque instability. Although the role of matrix vesicles in the initial stages of arterial calcification has been recognized, no studies have yet been carried out to examine a possible role of matrix vesicles in plaque destabilization. Tissue specimens selected for the present study represented carotid specimens obtained from patients undergoing carotid endarterectomy. Serial frozen cross‐sections of the tissue specimens were cut and mounted on glass slides. The thickness of the fibrous cap (FCT) in each advanced atherosclerotic lesion, containing a well developed lipid/necrotic core, was measured at its narrowest sites in sets of serial sections. According to established criteria, atherosclerotic plaque specimens were histologically subdivided into two groups: vulnerable plaques with thin fibrous caps (FCT <100 μm) and presumably stable plaques, in which fibrous caps were thicker than 100 μm. Twenty‐four carotid plaques (12 vulnerable and 12 presumably stable plaques) were collected for the present analysis of matrix vesicles in fibrous caps. In order to provide a sufficient number of representative areas from each plaque, laser capture microdissection (LCM) was carried out. The quantification of matrix vesicles in ultrathin sections of vulnerable and stable plaques revealed that the numbers of matrix vesicles were significantly higher in fibrous caps of vulnerable plaques than those in stable plaques (8.908±0.544 versus 6.208±0.467 matrix vesicles per 1.92 μm2 standard area; P= 0.0002). Electron microscopy combined with X‐ray elemental microanalysis showed that some matrix vesicles in atherosclerotic plaques were undergoing calcification and were characterized by a high content of calcium and phosphorus. The percentage of calcified matrix vesicles/microcalcifications was significantly higher in fibrous caps in vulnerable plaques compared with that in stable plaques (6.705±0.436 versus 5.322±0A94; P= 0.0474). The findings reinforce a view that the texture of the extracellular matrix in the thinning fibrous cap of atherosclerotic plaque is altered and this might contribute to plaque destabilization.
Selecting indicators for the quality of diabetes care at the health systems level in OECD countries.

PURPOSE In the context of the Organization for Economic Cooperation and Development (OECD) Quality Indicators Project, a set of quality indicators for diabetes care was developed, to be used for benchmarking the performance of health care systems. BACKGROUND Diabetes complications markedly reduce quality and length of life and are also responsible for enormous health care costs. A large body of evidence has shown that several effective treatments and practices may substantially reduce this burden. However, a marked variability has been documented in preventive and therapeutic approaches, thus suggesting that the level of diabetes care currently delivered may not produce the possible health-related gains. METHODS Existing quality indicators have been reviewed, with particular attention to the work done by the National Diabetes Quality Improvement Alliance (NDQIA) in the US. All the measures identified were evaluated for their importance, scientific soundness, and feasibility. In addition, the panel members selected new distal outcome measures. These measures are currently not used in provider comparisons, but they could reveal valuable insight into the differential performance of health systems. RESULTS /b>. Four process and two proximal outcome measures were selected among those endorsed by the NDQIA. In addition, three new long-term outcome measures have been proposed to gain insight into whether and to what degree differences in the processes and intermediate outcomes that are captured by the established measures translate into better outcomes for patients. CONCLUSIONS The measures selected can contribute to policymakers' and researchers' understanding of differences in the quality of diabetes care between health systems. Further work is required to assess the availability of reliable and comparable data across OECD countries.
A Formal Model of Text Summarization Based on Condensation Operators of a Terminological Logic

An automobile antenna mounting structure comprises a base supporting and electrically insulating an antenna mast, the base extending through a bore of laterally elongated cross-section in a lower mounting plate, a circular mounting aperture in a mounting surface, and a bore of laterally elongated cross-section in an upper mounting means, respectively. A pair of downwardly concave shouldered portions on the base support a pair of downwardly depending legs on the lower mounting plate, so formed to permit limited relative pivotal movement between the base and plate in a vertical plane. The base and lower mounting plate are further formed to be both insertable through the mounting aperture in the support surface from the exterior thereof. The lower mounting plate and upper mounting means are adapted to be clamped to the support surface by a nut threaded on the upper portion of the base. The nut is formed with a hemispherical lower portion and the upper mounting means is formed with a correspondingly shaped seat at its upper end communicating with the bore therein so that the mast can be securely mounted on the support surface at a predetermined angle thereto.
Analytical Hierarchy Process in Requirements Analysis

We describe a group of related approaches to quantitative evaluation and prioritization of system requirements and proposals. In formulating requirements for new systems, analysts face difficult tasks of selecting between alternative requirement decompositions, identifying questionable or low-priority requirements, eliminating requirements that add unnecessary costs, projecting cost impact of the requirements and then evaluating alternative system design proposals against the stated requirements. We seek approaches that require modest investments of time and can be applied even at the early stages of the requirements formulation process. We show that the Analytical Hierarchy Process can be applied to provide such evaluation mechanisms and illustrate our approach with a detailed example.
Non-Adjacent Form Recursive Algorithm on Elliptic Curves Cryptograph

Multiplication of a point is the main operation in elliptic curves cryptography system. It is well-known this operation be expensive in time-consuming. we try to improve the computing efficiency of multiple point which will increase the efficiency of elliptic curves cryptograph. In order to reach this goal, on the basis of addition-subtraction method, we adopt recursive formula of double point to improve the efficiency of multiple points algorithm. By the improved algorithm, the efficiency of computing multiple point be improved greatly. The improved algorithm be more effective than addition-subtraction method.
Altered Serotonin Innervation Patterns in the Forebrain of Monkeys Treated with (±)3,4-Methylenedioxymethamphetamine Seven Years Previously: Factors Influencing Abnormal Recovery

The recreational drug (±)3,4-methylenedioxymethamphetamine (MDMA, “Ecstasy”) is a potent and selective brain serotonin (5-HT) neurotoxin in animals and, possibly, in humans. The purpose of the present study was to determine whether brain 5-HT deficits persist in squirrel monkeys beyond the 18-month period studied previously and to identify factors that influence recovery of injured 5-HT axons. Seven years after treatment, abnormal brain 5-HT innervation patterns were still evident in MDMA-treated monkeys, although 5-HT deficits in some regions were less severe than those observed at 18 months. No loss of 5-HT nerve cell bodies in the rostral raphe nuclei was found, indicating that abnormal innervation patterns in MDMA-treated monkeys are not the result of loss of a particular 5-HT nerve cell group. Factors that influence recovery of 5-HT axons after MDMA injury are (1) the distance of the affected axon terminal field from the rostral raphe nuclei, (2) the degree of initial 5-HT axonal injury, and possibly (3) the proximity of damaged 5-HT axons to myelinated fiber tracts. Additional studies are needed to better understand these and other factors that influence the response of primate 5-HT neurons to MDMA injury and to determine whether the present findings generalize to humans who use MDMA for recreational purposes.
Encoding Definitional Fragments of Temporal Action Logic into Logic Programming

Temporal Action Logics (TAL) is an expressive class of nonmonotonic temporal logics for reasoning about action and change. In previous work, it has been shown that a very general fragment of the logic can be reduced to firstorder logic with equality. Consequently, standard theorem proving techniques can be used to reason in TAL. TAL is intended to be used for robotics. In this case, standard theorem proving techniques are too general and do not provide efficient decision procedures. The goal of this article is to identify a limited subset of TAL that can be directly mapped to a normal logic program. Although quite restrictive, this sets the lower bound on what can be done with direct mappings to logic programs. Discussions concerning extensions to the restricted fragment are also provided.
A Requirements Metamodel Framework for Enhancing Product Adoption

The body of knowledge on Product Line Software Engineering is an emerging paradigm alternative to developing software systems from scr atch. However, it will only be adopted if it helps enterprises maximize their profits. Whether this investment results in greater profit depends on the particular methodologies and strategy adopted. A number of methodologies have been proposed, with most requiri ng a requirement metamodel to be constructed as a basi s for documenting domain artifacts using three components, namely (i) functional requirement; (ii) non functional requirement component; (iii) and a variation component, which captures variation points. In this paper we argue that a domain is not only comprised of these elements, but in addition is a merger of thos e components with operating context such as users, policies, and culture which affect product adoption and acceptance rate. The paper proposes a requirement metamodel framework that not only serves as a construct of the business sub process, but also ser v s as a basis for understanding, interpreting and predicting user’s views and adoption rate.