Miracle-dz/UniFAR-FTUs huggingface dataset:
Pace—A Toolset for the Performance Prediction of Parallel and Distributed Systems

This paper describes a methodology that provides detailed predictive performance information throughout the software design and implementation cycles. It is structured around a hierarchy of performance models that describe the computing system in terms of its software, parallelization, and hardware components. The methodology is illustrated with an implementation, the performance analysis and characterization environment (PACE) system, which provides information concerning execution time, scalability, and resource use. A principal aim of the work is to provide a capability for rapid calculation of relevant performance numbers without sacrificing accuracy. The predictive nature of the approach provides both pre and post implementation analyses and allows implementation alternatives to be explored prior to the commitment of an application to a system. Because of the relatively fast analysis times, these techniques can be used at runtime to assist in application steering and scheduling with reference to dynamically changing systems and metacomputing.
Shrinkage Behavior of Alkali-Activated Slag Cement Pastes

Nowadays, alkali-activated cements (AACs) are the most promising alternatives to ordinary portland cement (OPC). Such cements characterized by better strength and corrosion resistance that determine improved durability of materials based on them. However, the shrinkage of AAC systems is noticeably higher compared with OPC. The purpose of this work was to study the shrinkage behavior of alkali-activated slag cement (AASC) pastes. To improve early age performance of AASCs – OPC and Ca(OH)2, as mineral additives, were added to the designed cement mixtures. The properties, like, flexural and compressive strength of cement mortars, chemical shrinkage, autogenous shrinkage and drying shrinkage of cement pastes were studied. The results showed that the chemical shrinkage, autogenous shrinkage and drying shrinkage at 28 days were between 0.064 – 0.074 ml/g, 4.5 – 7.9 mm/m and 3.3 – 4.9 mm/m, respectively. The relationship between the nature of alkaline components, the type of mineral additives and the shrinkage behavior of cements were discussed.
When Good Brands Do Bad

This paper reports results from a longitudinal field experiment examining the evolution of relationships between consumers and an on-line photography brand in response to brand personality and transgression manipulations. Development patterns differed significantly for the two personalities, whereby relationships with sincere brands deepened over time in line with friendship templates, and relationships with exciting brands evinced a trajectory characteristic of short-lived flings. However, these patterns held only when the relationship proceeded without a brand transgression. Relationships with sincere brands suffered dramatically and irrevocably in the wake of transgressions but, surprisingly, showed signs of reinvigoration for exciting brands. Character inferences concerning the quality of the brand as a relationship partner mediated the results. Findings suggest a dynamic construal of brand personality, greater attention to interrupt events including transgressions, and consideration of the relationship contracts formed at the hands of different brands.
Variations in the requirement for v-SNAREs in GLUT4 trafficking in adipocytes

Vesicle transport in eukaryotic cells is regulated by SNARE proteins, which play an intimate role in regulating the specificity of vesicle fusion between discrete intracellular organelles. In the present study we investigated the function and plasticity of v-SNAREs in insulin-regulated GLUT4 trafficking in adipocytes. Using a combination of knockout mice, v-SNARE cleavage by clostridial toxins and total internal reflection fluorescence microscopy, we interrogated the function of VAMPs 2, 3 and 8 in this process. Our studies reveal that the simultaneous disruption of VAMPs 2, 3 and 8 completely inhibited insulin-stimulated GLUT4 insertion into the plasma membrane, due to a block in vesicle docking at the plasma membrane. These defects could be rescued by re-expression of VAMP2, VAMP3 or VAMP8 alone, but not VAMP7. These data indicate a plasticity in the requirement for v-SNAREs in GLUT4 trafficking to the plasma membrane and further define an important role for the v-SNARE proteins in pre-fusion docking of vesicles.
Riemannian simplices and triangulations

We study a natural intrinsic definition of geometric simplices in Riemannian manifolds of arbitrary finite dimension, and exploit these simplices to obtain criteria for triangulating compact Riemannian manifolds. These geometric simplices are defined using Karcher means. Given a finite set of vertices in a convex set on the manifold, the point that minimises the weighted sum of squared distances to the vertices is the Karcher mean relative to the weights. Using barycentric coordinates as the weights, we obtain a smooth map from the standard Euclidean simplex to the manifold. A Riemannian simplex is defined as the image of this barycentric coordinate map. In this work we articulate criteria that guarantee that the barycentric coordinate map is a smooth embedding. If it is not, we say the Riemannian simplex is degenerate. Quality measures for the “thickness” or “fatness” of Euclidean simplices can be adapted to apply to these Riemannian simplices. For manifolds of dimension 2, the simplex is non-degenerate if it has a positive quality measure, as in the Euclidean case. However, when the dimension is greater than two, non-degeneracy can be guaranteed only when the quality exceeds a positive bound that depends on the size of the simplex and local bounds on the absolute values of the sectional curvatures of the manifold. An analysis of the geometry of non-degenerate Riemannian simplices leads to conditions which guarantee that a simplicial complex is homeomorphic to the manifold.
Effect of Dietary Fiber on Morphine-induced Constipation in Rats

Morphine is used to alleviate chronic cancer pain. However, constipation is a major adverse effect that often detracts from the patient's quality of life. In this study, we investigated the effectiveness of dietary fiber on morphine-induced constipation. Rats were fed on a normal diet or one containing either 10% or 20% apple fiber for two weeks before morphine was administered. In the control diet group, the fecal number and dry weight were decreased by treating with morphine in a dose-dependent manner. Moreover, the motility of the small and large intestines was reduced. The fecal number and weight were increased and the colon motility was promoted by dietary fiber, regardless of whether morphine was being administered. The dietary fiber increased the concentration of short-chain fatty acids (SCFAs) in the cecum. These results suggest that dietary fiber has a preventative effect on morphine-induced constipation by increasing SCFAs in the cecum, and thereby promoting colon motility in rats.
Lattice Codes for Many-to-One Interference Channels With and Without Cognitive Messages

A new achievable rate region is given for the Gaussian cognitive many-to-one interference channel. The proposed novel coding scheme is based on the compute-and-forward approach with lattice codes. Using the idea of decoding sums of codewords, our scheme improves considerably upon the conventional coding schemes which treat interference as noise or decode messages simultaneously. Our strategy also extends directly to the usual many-to-one interference channels without cognitive messages. Comparing to the usual compute-and-forward scheme where a fixed lattice is used for the code construction, the novel scheme employs scaled lattices and also encompasses key ingredients of the existing schemes for the cognitive interference channel. With this new component, our scheme achieves a larger rate region in general. For some symmetric channel settings, new constant gap or capacity results are established, which are independent of the number of users in the system.
Greedy Algorithms for Optimal Distribution Approximation

The approximation of a discrete probability distribution t by an M-type distribution p is considered. The approximation error is measured by the informational divergence D ( t ∥ p ) , which is an appropriate measure, e.g., in the context of data compression. Properties of the optimal approximation are derived and bounds on the approximation error are presented, which are asymptotically tight. A greedy algorithm is proposed that solves this M-type approximation problem optimally. Finally, it is shown that different instantiations of this algorithm minimize the informational divergence D ( p ∥ t ) or the variational distance ∥ p − t ∥ 1 .
Towards concept analysis in categories: limit inferior as algebra, limit superior as coalgebra

While computer programs and logical theories begin by declaring the concepts of interest, be it as data types or as predicates, network computation does not allow such global declarations, and requires *concept mining* and *concept analysis* to extract shared semantics for different network nodes. Powerful semantic analysis systems have been the drivers of nearly all paradigm shifts on the web. In categorical terms, most of them can be described as bicompletions of enriched matrices, generalizing the Dedekind-MacNeille-style completions from posets to suitably enriched categories. Yet it has been well known for more than 40 years that ordinary categories themselves in general do not permit such completions. Armed with this new semantical view of Dedekind-MacNeille completions, and of matrix bicompletions, we take another look at this ancient mystery. It turns out that simple categorical versions of the *limit superior* and *limit inferior* operations characterize a general notion of Dedekind-MacNeille completion, that seems to be appropriate for ordinary categories, and boils down to the more familiar enriched versions when the limits inferior and superior coincide. This explains away the apparent gap among the completions of ordinary categories, and broadens the path towards categorical concept mining and analysis, opened in previous work.
Combined DEM and SPH simulation of ball milling

A deeper understanding of the milling operation of ball mills helps mineral processing engineers to control and optimize them, and therefore, reduce their consuming power. In this work, the milling operation of ball mills is investigated using two methods, i.e. DEM and combined DEM-SPH. First, a pilot scale ball mill with no lifter is simulated by both methods. Then another pilot scale ball mill with eight rectangle lifters is simulated again by both methods. The effects of lifters on ball shoulder and toe points as well as on creation of cascading and cataracting movements for balls are studied by both methods. At the present time, there is not enough measured data available for dense slurries interacting with the coarse particulates available in the public domain that can be used adequately to validate these types of predictions. The results obtained indicated that fluid slurry in the mill lowered the charge shoulder by about 28 cm and 25 cm in the no-lifter and eight-lifter cases, respectively. However, it raised the charge toe by about 36 cm and 6 cm in the no-lifter and eight-lifter cases, respectively.
A Scheme for Integrating Concrete Domains into Concept Languages

A drawback which concept languages based on KL-ONE have is that all the terminological knowledge has to be defined on an abstract logical level. In many applications, one would like to be able to refer to concrete domains and predicates on these domains when defining concepts. Examples for such concrete domains are the integers, the real numbers, or also non-arithmetic domains, and predicates could be equality, inequality, or more complex predicates. In the present paper we shall propose a scheme for integrating such concrete domains into concept languages rather than describing a particular extension by some specific concrete domain. We shall define a terminological and an assertional language, and consider the important inference problems such as subsumption, instantiation, and consistency. The formal semantics as well as the reasoning algorithms are given on the scheme level. In contrast to existing KL-ONE based systems, these algorithms will be not only sound but also complete. They generate subtasks which have to be solved by a special purpose reasoner of the concrete domain.
KAP-1 Promotes Resection of Broken DNA Ends Not Protected by γ-H2AX and 53BP1 in G1-Phase Lymphocytes

ABSTRACT The resection of broken DNA ends is required for DNA double-strand break (DSB) repair by homologous recombination (HR) but can inhibit normal repair by nonhomologous end joining (NHEJ), the main DSB repair pathway in G1-phase cells. Antigen receptor gene assembly proceeds through DNA DSB intermediates generated in G1-phase lymphocytes by the RAG endonuclease. These DSBs activate ATM, which phosphorylates H2AX, forming γ-H2AX in flanking chromatin. γ-H2AX prevents CtIP from initiating resection of RAG DSBs. Whether there are additional proteins required to promote resection of these DNA ends is not known. KRAB-associated protein 1 (KAP-1) (TRIM28) is a transcriptional repressor that modulates chromatin structure and has been implicated in the repair of DNA DSBs in heterochromatin. Here, we show that in murine G1-phase lymphocytes, KAP-1 promotes resection of DSBs that are not protected by H2AX and its downstream effector 53BP1. In these murine cells, KAP-1 activity in DNA end resection is attenuated by a single-amino-acid change that reflects a KAP-1 polymorphism between primates and other mammalian species. These findings establish KAP-1 as a component of the machinery that can resect DNA ends in G1-phase cells and suggest that there may be species-specific features to this activity.
Genomic Analysis of QTLs and Genes Altering Natural Variation in Stochastic Noise

Quantitative genetic analysis has long been used to study how natural variation of genotype can influence an organism's phenotype. While most studies have focused on genetic determinants of phenotypic average, it is rapidly becoming understood that stochastic noise is genetically determined. However, it is not known how many traits display genetic control of stochastic noise nor how broadly these stochastic loci are distributed within the genome. Understanding these questions is critical to our understanding of quantitative traits and how they relate to the underlying causal loci, especially since stochastic noise may be directly influenced by underlying changes in the wiring of regulatory networks. We identified QTLs controlling natural variation in stochastic noise of glucosinolates, plant defense metabolites, as well as QTLs for stochastic noise of related transcripts. These loci included stochastic noise QTLs unique for either transcript or metabolite variation. Validation of these loci showed that genetic polymorphism within the regulatory network alters stochastic noise independent of effects on corresponding average levels. We examined this phenomenon more globally, using transcriptomic datasets, and found that the Arabidopsis transcriptome exhibits significant, heritable differences in stochastic noise. Further analysis allowed us to identify QTLs that control genomic stochastic noise. Some genomic QTL were in common with those altering average transcript abundance, while others were unique to stochastic noise. Using a single isogenic population, we confirmed that natural variation at ELF3 alters stochastic noise in the circadian clock and metabolism. Since polymorphisms controlling stochastic noise in genomic phenotypes exist within wild germplasm for naturally selected phenotypes, this suggests that analysis of Arabidopsis evolution should account for genetic control of stochastic variance and average phenotypes. It remains to be determined if natural genetic variation controlling stochasticity is equally distributed across the genomes of other multi-cellular eukaryotes.
Functional Domain of Bovine Milk Lactoferrin Which Inhibits the Adherence of Streptococcus mutans Cells to a Salivary Film

ABSTRACT The bovine lactoferrin molecule and relatively long lactoferrin fragments containing residues 473 to 538 strongly inhibited adherence of Streptococcus mutans to saliva-coated hydroxyapatite beads. Each cysteine residue in Lf411 (residues 473 to 538) was replaced by a serine residue, and the mutants Lf411-C481S and Lf411-C532S strongly inhibited S. mutans adherence. These results suggest that the functional domain of lactoferrin that binds to a salivary film lies in residues 473 to 538 and that the region might be concealed by disulfide bond formation between Cys481 and Cys532 in the Lf411 fragment.
Estimating inflation in GWAS summary statistics due to variance distortion from cryptic relatedness

Cryptic relatedness is inherently a feature of large genome-wide association studies (GWAS), and can give rise to considerable inflation in summary statistics for single nucleotide polymorphism (SNP) associations with phenotypes. It has proven difficult to disentangle these inflationary effects from true polygenic effects. Here we present results of a model that enables estimation of polygenicity, mean strength of association, and residual inflation in GWAS summary statistics. We show that there is substantial residual inflation in recent large GWAS of height and schizophrenia; correcting for this reduces the number of independent genome-wide significant loci from the reported values of 697 for height and 108 for schizophrenia to 368 and 61, respectively. In contrast, a larger GWAS of educational attainment shows no residual inflation. Additionally, we find that height has a relatively low polygenicity, with approximately 8k SNPs having causal association, more than an order of magnitude less than has been reported. The residual inflation in GWAS summary statistics can be corrected using the standard genomic control procedure with the estimated residual inflation factor.
How to keep a secret: leakage deterring public-key cryptosystems

How is it possible to prevent the sharing of cryptographic functions? This question appears to be fundamentally hard to address since in this setting the owner of the key is the adversary: she wishes to share a program or device that (potentially only partly) implements her main cryptographic functionality. Given that she possesses the cryptographic key, it is impossible for her to be prevented from writing code or building a device that uses that key. She may though be deterred from doing so. We introduce leakage-deterring public-key cryptosystems to address this problem. Such primitives have the feature of enabling the embedding of owner-specific private data into the owner's public-key so that given access to any (even partially functional) implementation of the primitive, the recovery of the data can be facilitated. We formalize the notion of leakage-deterring in the context of encryption, signature, and identification and we provide efficient generic constructions that facilitate the recoverability of the hidden data while retaining privacy as long as no sharing takes place.
Is the peripheral arterial disease in low risk type 2 diabetic patients influenced by body mass index, lipidemic control, and statins?

Objective: To correlate BMI, lipidemic control, and statin therapy with PAD measured by ABI in low risk type 2 diabetics. Materials and Methods: A sample of 101 nonsmoking, asymptomatic type 2 diabetics (50 males, 51 females) with known glycemic (fasting blood sugar, postprandial blood sugar, glycosylated hemoglobin) and lipidemic (total cholesterol, lipoproteins, and triglycerides [TGAs]) control was taken. Vascular Doppler was used to derive ABI and PAD was defined as ABI <0.9. ABI values were compared amongst groups and P < 0.05 was considered statistically significant. Results: We found fairly good lipid but poor glycemic control and prevalence of PAD 30%. There was insignificantly low ABI profile in patient having BMI ≥25, hyperlipidemia and absent statin therapy with odds ratio being highest for TGAs ≥150 (3.23) followed by BMI ≥25 (2.61), high-density lipoprotein ≤50 (1.61), low-density lipoprotein ≥100 (1.20), and disuse of statin (1.14) with significance only for BMI. Conclusion: We observed small, insignificant PAD risk by dyslipidemia or non-use of statins in low-risk ambulatory T2DM patients, not so by BMI. This suggests importance of good glycemic control, maintenance of optimum weight, and lifestyle modifications as primary prevention rather than opting for costly and inefficient secondary prevention.
ANSIG - An Analytic Signature for Arbitrary 2D Shapes (or Bags of Unlabeled Points)

In image analysis, many tasks require representing two-dimensional (2D) shape, often specified by a set of 2D points, for comparison purposes. The challenge of the representation is that it must not only capture the characteristics of the shape but also be invariant to relevant transformations. Invariance to geometric transformations, such as translation, rotation, and scale, has received attention in the past, usually under the assumption that the points are previously labeled, i.e., that the shape is characterized by an ordered set of landmarks. However, in many practical scenarios, the points describing the shape are obtained from automatic processes, e.g., edge or corner detection, thus without labels or natural ordering. Obviously, the combinatorial problem of computing the correspondences between the points of two shapes in the presence of the aforementioned geometrical distortions becomes a quagmire when the number of points is large. We circumvent this problem by representing shapes in a way that is invariant to the permutation of the landmarks, i.e., we represent bags of unlabeled 2D points. Within our framework, a shape is mapped to an analytic function on the complex plane, leading to what we call its analytic signature (ANSIG). To store an ANSIG, it suffices to sample it along a closed contour in the complex plane. We show that the ANSIG is a maximal invariant with respect to the permutation group, i.e., that different shapes have different ANSIGs and shapes that differ by a permutation (or re-labeling) of the landmarks have the same ANSIG. We further show how easy it is to factor out geometric transformations when comparing shapes using the ANSIG representation. Finally, we illustrate these capabilities with shape-based image classification experiments.
GNG-Based Q-Learning

In this paper, we present a new developmental architecture that joins the categorizational power of Growing Neural Gas networks with an action policy for discrete states and actions. The result is a robot brain that can choose its next move by associating its current sensor inputs with a particular subsection of the possible input vectors. GNG networks are used for vector quantization, to generate a set of input prototypes and a separate set of output prototypes. A Q-learning process that treats the input model vectors as states and the output model vectors as actions yields a Q-table that should efficiently guide a robot through the state-action space on which it is trained. We apply this reinforcement learning system to a Pioneer robot in simulation, operating in a simple maze in which the goal is to reach a stationary light located in a far quadrant of the world. We examine the effects of varying the maximum permissible error in the category creation, and of varying the number of steps for which we run Q-learning. Additionally, we investigate two methods of rewarding goal-finding behaviors in the Q-learning algorithm.