Miracle-dz/UniFAR-FTUs huggingface dataset:
BLISS: Balancing Performance, Fairness and Complexity in Memory Access Scheduling

In a multicore system, applications running on different cores interfere at main memory. This inter-application interference degrades overall system performance and unfairly slows down applications. Prior works have developed application-aware memory request schedulers to tackle this problem. State-of-the-art application-aware memory request schedulers prioritize memory requests of applications that are vulnerable to interference, by ranking individual applications based on their memory access characteristics and enforcing a total rank order. In this paper, we observe that state-of-the-art application-aware memory schedulers have two major shortcomings. First, such schedulers trade off hardware complexity in order to achieve high performance or fairness, since ranking applications individually with a total order based on memory access characteristics leads to high hardware cost and complexity. Such complexity could prevent the scheduler from meeting the stringent timing requirements of state-of-the-art DDR protocols. Second, ranking can unfairly slow down applications that are at the bottom of the ranking stack, thereby sometimes leading to high slowdowns and low overall system performance. To overcome these shortcomings, we propose the Blacklisting Memory Scheduler (BLISS), which achieves high system performance and fairness while incurring low hardware cost and complexity. BLISS design is based on two new observations. First, we find that, to mitigate interference, it is sufficient to separate applications into only two groups, one containing applications that are vulnerable to interference and another containing applications that cause interference, instead of ranking individual applications with a total order. Vulnerable-to-interference group is prioritized over the interference-causing group. Second, we show that this grouping can be efficiently performed by simply counting the number of consecutive requests served from each application. We evaluate BLISS across a wide variety of workloads and system configurations and compare its performance and hardware complexity (via RTL implementations), with five state-of-the-art memory schedulers. Our evaluations show that BLISS achieves 5 percent better system performance and 25 percent better fairness than the best-performing previous memory scheduler while greatly reducing critical path latency and hardware area cost of the memory scheduler (by 79 and 43 percent, respectively), thereby achieving a good trade-off between performance, fairness and hardware complexity.
Association between serum 25-hydroxyvitamin D levels and adiposity measurements in the general Korean population

BACKGROUND/OBJECTIVES Obesity, which is a known risk factor for many chronic diseases, has also been associated with vitamin D deficiency. This study explored the relationship between serum 25-hydroxy-vitamin D [25(OH)D] concentrations and adiposity measures in a general Korean population using the most recent, nationally representative survey data. SUBJECTS/METHODS The study sample consisted of 4,771 Korean adults (≥ 19 years) who participated in the fifth Korean National Health and Nutrition Examination Surveys. Serum 25(OH)D was determined by radioimmunoassay. Body mass index (BMI), waist circumference (WC) and total body fat content were measured as adiposity measurements. Total body fat content was measured by dual-energy X-ray absorptiometry. RESULTS The serum 25(OH)D level was significantly higher in men than in women. Serum 25(OH)D concentration was positively correlated with energy intake, and it was negatively correlated with total body fat content (P < 0.0001) and percentage body fat (P < 0.0001) after adjustment for age in both sexes, while was inversely correlated with BMI only in women. In multivariable regression analysis, serum 25(OH)D was inversely associated with the total body fat content after adjustment for age, BMI, education, region, smoking, alcohol consumption, physical activity, and energy intake only in men (P = 0.0047). However, the serum 25(OH)D concentration was not associated with WC or BMI, indicators of adiposity after adjustment for potential risk factors. CONCLUSIONS Serum 25(OH)D concentration was independently associated with the total body fat content in a general Korean population, but it may be not associated with the indicators for estimating adiposity, such as WC or BMI.
Performance improvement of TCP on wireless cellular networks by adaptive FEC combined with explicit loss notification

We propose a new adaptive FEC scheme combined with ELN (explicit loss notification) that was proposed for improving TCP performance in wireless cellular networks. In our method, transmission errors on the wireless link are measured at the packet level and the error status is notified the TCP sender with ELN. According to this information, an appropriate FEC code is determined in order to maximize the TCP performance. We first compare the TCP performance using the Snoop protocol, ELN and the fixed FEC, through which we find the appropriate FEC code against given BER (bit error ratio). We then show how the adaptive FEC can be realized using our solution, and also examine the appropriate observation period of measuring BER enough for the fading speed on the noisy wireless link. We finally demonstrate that our method can achieve better performance than the conventional fixed FEC by using the Gilbert model as a wireless error model.
A Uniform Resource Identifier for Geographic Locations ('geo' URI)

This document specifies a Uniform Resource Identifier (URI) for geographic locations using the 'geo' scheme name. A 'geo' URI identifies a physical location in a two- or three-dimensional coordinate reference system in a compact, simple, human-readable, and protocol-independent way. The default coordinate reference system used is WGS-84.
Social Impact and Diffusion of Telecenter Use: A Study from the Sustainable Access in Rural India Project

In a study of social diffusion of telecenter use in rural south India, we find that these centers are being used only by a relatively small proportion of the village households despite their having been in operation for well over a year. Based on a survey of the telecenter users, we find that these users are, in general, young, male, school or college students, relatively more educated, belong to relatively higher income households, and come from socially and economically advanced communities. Thus the telecenters may sustain existing socioeconomic inequalities within these communities. However, we find some significant exceptions. We find that location of telecenters close to the residential localities where socially and economically backward communities live and presence of local champions within those communities are associated with attracting more users from those communities. We also find that providing localized content and services and making these services more affordable are other important factors in increasing usage and diffusion. We posit that incorporating these factors in the planning, spatial location, and operation of the telecenters can significantly improve their social diffusion and improve their long-term financial and social sustainability.
Blood pressure reduction due to hemoglobin glycosylation in type 2 diabetic patients

Pedro Cabrales1 Miguel A Salazar Vázquez2,3 Beatriz Y Salazar Vázquez3,4 Martha Rodríguez-Morán5 Marcos Intaglietta4 Fernando GuerreroRomero5 1La Jolla Bioengineering Institute, La Jolla, California, USA; 2Hospital Regional No. 1, of the Mexican Social Security Institute, Victoria de Durango, Dgo. Mexico; 3Faculty of Medicine and Dept. of Physical Chemistry, Universidad Juárez del Estado de Durango, Victoria de Durango, Dgo. Mexico; 4Department of Bioengineering, University of California, San Diego, La Jolla, California, USA; 5Biomedical Research Unit, of the Mexican Social Security Institute, Victoria de Durango, Dgo. Mexico
Distinct phenotypes of antigen-selected CD8 T cells emerge at different stages of an in vivo immune response.

We have previously described a unique system for identifying Ag-selected CD8 T cells during an in vivo response in normal mice. In this system, lymphocytes isolated from DBA/2 mice injected i.p. with HLA-CW3 transfected syngeneic (H-2d) P815 cells show a remarkable expansion of CD8 cells that utilize TCR expressing the V beta 10 gene segment and additional structural features characteristic of Kd-restricted CW3-specific CTL clones. We have now taken advantage of this system to characterize the surface phenotype of CD8 cells selected by Ag in vivo. We observed several distinct phenotypes at different stages of the response. At the peak of the response, Ag-selected cells were low in CD62L and CD45RB expression but displayed high levels of CD44. In addition, there was a partial down-regulation of CD8 and TCR. Cells of this phenotype were present in lymphoid tissues for several mo after immunization. Much later in the response, Ag-selected cells expressed higher levels of CD8 and TCR. Moreover, a distinct subset of these long-term immune cells emerged that now expressed CD62L and CD45RB. Analysis of CD8 cells from different tissues also revealed certain differences, particularly in TCR and co-receptor levels from liver-derived cells compared with circulating cells at the peak of the response. Our findings suggest that the function of Ag-selected CD8 cells may be regulated over time and according to location by subtle changes in cell-surface phenotype.
The dual inhibitory effect of thiostrepton on FoxM1 and EWS/FLI1 provides a novel therapeutic option for Ewing’s sarcoma

The poor prognosis of Ewing’s sarcoma (EWS), together with its high lethal recurrence rate and the side-effects of current treatments, call for novel targeted therapies with greater curative effectiveness and substantially reduced side-effects. The oncogenic chimeric protein EWS/FLI1 is the key malignancy driver in most EWSs, regulating numerous target genes, many of which influence cell cycle progression. It has often been argued that targeting proteins regulated directly or indirectly by EWS/FLI1 may provide improved therapeutic options for EWS. In this context, our study examined FoxM1, a key cell cycle regulating transcription factor, reported to be expressed in EWS and influenced by EWS/FLI1. Thiostrepton, a naturally occurring small molecule, has been shown to selectively inhibit FoxM1 expression in cancer cells. We demonstrate that in EWS, in addition to inhibiting FoxM1 expression, thiostrepton downregulates the expression of EWS/FLI1, both at the mRNA and protein levels, leading to cell cycle arrest and, ultimately, to apoptotic cell death. We also show that thiostrepton treatment reduces the tumorigenicity of EWS cells, significantly delaying the growth of nude mouse xenograft tumors. Results from this study demonstrate a novel action of thiostrepton as inhibitor of the expression of the EWS/FLI1 oncoprotein in vitro and in vivo, and that it shows greater efficacy against EWS than against other tumor types, as it is active on EWS cells and tumors at concentrations lower than those reported to have effective inhibitory activity on tumor cells derived from other cancers. Owing to the dual action of this small molecule, our findings suggest that thiostrepton may be particularly effective as a novel agent for the treatment of EWS patients.
Computational methods for discovering gene networks from expression data

Designing and conducting experiments are routine practices for modern biologists. The real challenge, especially in the post-genome era, usually comes not from acquiring data, but from subsequent activities such as data processing, analysis, knowledge generation and gaining insight into the research question of interest. The approach of inferring gene regulatory networks (GRNs) has been flourishing for many years, and new methods from mathematics, information science, engineering and social sciences have been applied. We review different kinds of computational methods biologists use to infer networks of varying levels of accuracy and complexity. The primary concern of biologists is how to translate the inferred network into hypotheses that can be tested with real-life experiments. Taking the biologists' viewpoint, we scrutinized several methods for predicting GRNs in mammalian cells, and more importantly show how the power of different knowledge databases of different types can be used to identify modules and subnetworks, thereby reducing complexity and facilitating the generation of testable hypotheses.
Metro Maps of Information

When information is abundant, it becomes increasingly difficult to fit nuggets of knowledge into a single coherent picture. Complex stories spaghetti into branches, side stories, and intertwining narratives. In order to explore these stories, one needs a map to navigate unfamiliar territory. We have developed a methodology for creating structured summaries of information, which we call metro maps. Our algorithm generates a concise structured set of documents which maximizes coverage of salient pieces of information. Most importantly, metro maps explicitly show the relations among retrieved pieces in a way that captures the evolution of a story. We first formalize characteristics of good maps and formulate their construction as an optimization problem. Then, we provide efficient methods with theoretical guarantees for generating maps. Finally, we integrate capabilities for supporting user interaction into the framework, allowing users to guide the formulation of the maps so as to better reflect their interests. Pilot user studies with a realworld dataset demonstrate that the method is able to produce maps which help users to acquire knowledge efficiently.
Soft residuated lattice based on intuitionistic fuzzy sets

In this paper, the concept of intuitionistic fuzzy soft sets is applied to residuated lattices. The notion of intuitionistic fuzzy soft filters of a residuated lattice is introduced and some related properties are investigated. Then the representations of generated intuitionistic fuzzy soft filters are established. We prove that the lattice of all intuitionistic fuzzy soft filters of a residuated lattice is a complete lattice. We determine the compact elements of this lattice and show that it is a distributive algebraic lattice. 2010 AMS Classification: 03G25, 03E72, 08A72, 06D99
Lean startup for materials ventures and other science-based ventures: under what conditions is it useful?

Materials-based ventures face a high degree of technology uncertainty and market uncertainty when engaging in the technology entrepreneurial process. Recently, the lean startup methodology (LSM) has been introduced to practice and education as an integrated approach on how entrepreneurs can resolve these uncertainties when starting up a business. While the literature provides examples of LSM's successful application in a range of application areas, its focus application tends to be on consumer software. The purpose of this article is to discuss the degree to which LSM can be applied to the context of technology entrepreneurship. We find that LSM has strengths in addressing market uncertainty, but is largely silent on addressing technology uncertainty. In situations of a low degree of technology readiness, strongly intertwined process and product innovation processes such as those common in materials translation, and of addressing business markets, LSM may not suffice. We discuss the case of competence leveraging as one where technology uncertainty is lower for materials companies and illustrate the benefits on LSM in this context.
Improved Multiobjective Binary Biogeography Based Optimization using CVM for Feature Selection Using Gene Expression Data

Gene expression data play an important role in the development of efficient cancer diagnoses and classification. The genes identified are subsequently used to classify independent test set samples. The different feature selection methods are investigated and most frequent features are selected among all methods. This paper provides gene selection strategies for multiclass classification that can be used to reach high prediction accuracies with a tiny low number of selected genes. In this paper, a multi-objective biogeography based optimization method is proposed to select the small subset of informative gene relevant to the classification. In the proposed algorithm, firstly, the KNN (K’s Nearest Neighbour) algorithm is used to choose the 60 top gene expression data. Secondly, to make biogeography based optimization suitable for the discrete problem, binary biogeography based optimization, as called BBBO, is proposed based on a binary migration model and a binary mutation model. Then Core Vector Machine (CVM), is proposed by integrating the nondominated sorting method and the crowding distance method into the BBBO framework. In order to show the effective and efficiency of the algorithm, the proposed algorithm is tested on ten gene expression dataset benchmarks. Experimental results demonstrate that the proposed method is better or at least comparable with previous particle swarm optimization (PSO) algorithm and support vector machine (SVM) from literature when considering the quality of the solutions obtained.
Molecular Switching by Turing Automata

We study the switching aspects of molecular computing from a novel algebraic point of view. Our approach is based on the concept indexed monoidal algebra, which provides an equivalent formalism for compact closed categories being used recently in the literature in connection with quantum computing. The point is to separate syntax, as the algebra G of graphs, from semantics, which is related to the algebra T of Turing automata, and define meaning as a homomorphism. Eventually, the syntax is restricted to the Gallai-Edmonds algebra G-E of graphs having a perfect internal matching, and the corresponding semantical structure, defined as the algebra S of soliton automata, is the quotient of an appropriate subalgebra of T .
Anti‐inflammatory antioxidants attenuate the expression of inducible nitric oxide synthase mediated by advanced glycation endproducts in murine microglia

Advanced glycation endproducts (AGEs) accumulate on long‐lived protein deposits including β‐amyloid plaques in Alzheimer's disease (AD). AGE‐modified amyloid deposits contain oxidized and nitrated proteins as markers of a chronic neuroinflammatory condition and are surrounded by activated microglial and astroglial cells. We show in this study that AGEs increase nitric oxide production by induction of the inducible nitric oxide synthase (iNOS) on the mRNA and protein level in the murine microglial cell line N‐11. Membrane permeable antioxidants including oestrogen derivatives (e.g. 17β‐oestradiol) thiol antioxidants (e.g. (R+)‐α‐lipoic acid) and Gingko biloba extract EGb 761, but not phosphodiesterase inhibitors such as propentophylline, prevent the up‐regulation of AGE‐induced iNOS expression and NO production. These results indicate that oxygen free radicals serve as second messengers in AGE‐induced pro‐inflammatory signal transduction pathways. As this pharmacological mechanism is not only relevant for Alzheimer's disease, but also for many chronic inflammatory conditions, such membrane‐permeable antioxidants could be regarded not only as antioxidant, but also as potent therapeutic anti‐inflammatory drugs.
Optimal Rates for Regularized Least Squares Regression

We establish a new oracle inequality for kernelbased, regularized least squares regression methods, which uses the eigenvalues of the associated integral operator as a complexity measure. We then use this oracle inequality to derive learning rates for these methods. Here, it turns out that these rates are independent of the exponent of the regularization term. Finally, we show that our learning rates are asymptotically optimal whenever, e.g., the kernel is continuous and the input space is a compact metric space.
MRSA Nasal Colonization in Children: Prevalence Meta-analysis, Review of Risk Factors and Molecular Genetics

Background: We report a meta-analysis of methicillin-resistant Staphylococcus aureus (MRSA) nasal colonization prevalence in children and a review of the risk factors as well as molecular genetic characterization. Methods: All relevant studies reporting prevalence data on MRSA nasal colonization in children published between January 2000 and August 2010 were retrieved from the MEDLINE database and analyzed. Results: After screening 544 studies, 50 studies were included. We obtained an estimate of MRSA prevalence of 2.7% (95% confidence interval [CI]: 2.2–3.1); of 5.2% (95% CI: 3.1–7.3) in children with underlying conditions and of 2.3% (95% CI: 1.8–2.7) in healthy children; 5.4% (95% CI: 3.1–7.7) in children recruited in hospitals and 3% (95% CI: 2.4–3.6) in children recruited in the community. Staphylococcal cassette chromosome mec type IV is the most diffused cassette globally. Conclusion: The hospital remains the environment where the microorganism circulates most. Children with underlying conditions could act as vectors of microorganisms between the hospital and the community. MRSA prevention strategies should be tailored to each specific institution, taking into account the nosocomial prevalence of MRSA nasal colonization and infections, and the prevalence of nasal colonization in the community that refers to the specific health care center.
High‐resolution intersubject averaging and a coordinate system for the cortical surface

The neurons of the human cerebral cortex are arranged in a highly folded sheet, with the majority of the cortical surface area buried in folds. Cortical maps are typically arranged with a topography oriented parallel to the cortical surface. Despite this unambiguous sheetlike geometry, the most commonly used coordinate systems for localizing cortical features are based on 3‐D stereotaxic coordinates rather than on position relative to the 2‐D cortical sheet. In order to address the need for a more natural surface‐based coordinate system for the cortex, we have developed a means for generating an average folding pattern across a large number of individual subjects as a function on the unit sphere and of nonrigidly aligning each individual with the average. This establishes a spherical surface‐based coordinate system that is adapted to the folding pattern of each individual subject, allowing for much higher localization accuracy of structural and functional features of the human brain. Hum. Brain Mapping 8:272–284, 1999. © 1999 Wiley‐Liss, Inc.
Code Coverage-Based Power Estimation Techniques for Microprocessors

We have developed a function-level power estimation methodology for predicting the power dissipation of embedded software. For a given microprocessor core, we empirically build the "power data bank", which stores the power information of the built-in library functions and basic instructions. To estimate the average power of an embedded software on this core, we first decompose the machine code into library functions and user-defined functions. We then use program profiling/tracing tools to get the execution information of the target software. Next, we evaluate the total energy consumption and execution time based on the "power data bank", and their ratio is taken as the average power. High efficiency is achieved because no power simulator is used once the "power data bank" is built. We apply this method to a commercial microprocessor core and get power estimates with an average error of 3%. Using this method, microprocessor vendors can provide users the "power data bank" without releasing details of the core to help users get early power estimates and eventually guide power optimization.