Miracle-dz/UniFAR-FTUs huggingface dataset:
Effective parameterization of architectural registers for register allocation algorithms

Code Selection in translation has been effectively abstracted out in terms of tree rewriting or pattern matching based approaches. However, modelling register files in an architecture independent way is a problem which is bypassed in most available algorithms. Architectural parameterization is frequently just code selector generation while architectural registers and operand constraints are handled in a machine-specific way. To partially address this issue, we present an abstraction for register allocation and assignment in non-uniform register file architectures in terms of bipartite graph matching.
Multiscale segmentation based on mode-shift clustering

We present a novel segmentation technique that effectively segments natural images. The method is designed for the purpose of image retrieval and follows the principle of clustering the regions visible in the image. The concept is based on the multiscale approach where the image undergoes a number of diffusions. The algorithm has been visually compared with a reference segmentation.
Metallothionein Lower Under-Expression in Benign Tumors than That in Malignant Tumors: Systematic Review Article and Meta-Analysis

Metallothionein (MT) manifests varying expression levels in carcinomas, and they may be considered as valuable cell cancerization biomarkers for diagnosis of patients with cancers. A meta-analysis was conducted to evaluate comprehensively the MT expression difference in various benign tumors and malignant tumors, which compared the high with low MT expression levels in patients of the available studies. Finally, a total of 13 studies dealing with various tumors were involved for this meta-analysis. The results indicated that lower expression of MT in various benign tumors tissue than that in corresponding malignant tumors with the pooled OR of 0.52 (95 % CI 0.18-1.47, P < 0.001). In conclusion, MT expression difference is associated with tumor various stages in tumor patients and could be a useful clinical criteria of distinguishing benign tumors and malignant tumors for those patients.
MASP: A Multi-attribute Secretary Problem Approach to Multi-objective Optimization with Fair Decision Maker

In the present paper we propose a multi-objective optimization procedure inspired by the famous secretary problem from optimal stopping theory. the proposed algorithm is designed to be applied to multi-attribute decision making problems that require fair solutions to be obtained. We consider two fairness relations, namely maxmin fairness and proportional fairness, and the evaluation is performed on the problem of wireless channel allocation. the performance is compared to random search, and the quality of the solution is measured with respect to the distance to the results obtained with brute-force in the whole search space. Results show that the proposed algorithm, compared to random search, can cover a much larger portion of the search space for the same number of pair wise comparisons.
Comparative Study of Topology of ANN Models for Adsorption of Colouring Agents from Aqueous Solutions using Adsorbents Synthesized from Agricultural Waste Material

The ability of some solids to remove colour from solutions containing dyes has been known for over a century. Activated carbon has been quite successful for removal of impurities from exhaust gas and waste water streams. The highly porous nature of the carbon provides a large surface area for contaminants to get deposited. Artificial neural network is a black box modeling tool & is applied for several chemical engineering operations. In the present work ANN models 1,2 & 3 having different topologies have been developed for correlating input parameters like name of adsorbate, name of adsorbent, initial concentration of solute in aqueous solution & quantity of adsorbent with output parameters such as % adsorption & equilibrium concentration of solute in adsorbent. The novel feature of present work is selection of suitable ANN model based on topology.
Social recommendation using quantified social tie strength

With the development of online social network (OSN), social recommendation approaches have gain more and more momentum. The users' OSN interactions which reflect the social tie strength put forward social recommendation approaches. But most of the previous work just classify the social tie strength into strong one and weak one. The coarse-grained social tie strength can not accurately reflect the social relationships between users and naturally affect the recommendation results. To address this problem, this paper presents a recommendation approach based on quantified social tie strength. We propose an unsupervised method to estimate tie strength from user similarity and online social interactions. Then the approach improve the social recommendation with quantified social tie strength. Experiments are made on a large book rating dataset from Douban.com. The experimental results show that this approach can effectively improve the recommendation accuracy.
OQuaRE: A SQuaRE-based Approach for Evaluating the Quality of Ontologies

The development of the Semantic Web has provoked an increasing interest in the development of ontologies. There are, however, few mechanisms for guiding users in making informed decisions on which ontology to use under given circumstances. In this paper, we propose a framework for evaluating the quality of ontologies based on the SQuaRE standard for software quality evaluation. This method requires the definition of both a quality model and quality metrics for evaluating the quality of the ontology. The quality model is divided into a series of quality dimensions or charac ter istics, such as structure or functional adequacy, which are organized into subcharacteristics, such as cohesion or tangledness. Thus, each subcharacteristic is evaluated by applying a series of quality metrics, which are automatically measured. Finally, each characteristic is evaluated by combining values of its subcharacteristics. This work also includes the application of this frame work for the evaluation of ontologies in two application domains.
Weight Status and Physical Activity

We tested the independent and combined influence of overweight/obesity and meeting moderate to vigorous physical activity (MVPA) guidelines (≥60 minutes per day) on cardiometabolic risk factors among healthy adolescents. We measured anthropometry, blood pressure, fasting lipids, and activity by accelerometer in 223 adolescents. They were categorized as overweight/obese versus normal weight and meeting the World Health Organization guidelines for MVPA per day. Adolescents were 16.8 years, 41% overweight/obese, 30% met MVPA guidelines, 50% low high-density lipoprotein, 22% high triglycerides, 12% high blood pressure, and 6% high fasting glucose. Controlling for sex, overweight/obese adolescents who did not meet MVPA guidelines had 4.0 and 11.9 increased odds for elevated triglycerides and systolic blood pressure, respectively, compared to normal weight adolescents who met MVPA guidelines. Overweight/obese and normal weight adolescents who met MVPA guidelines did not differ in cardiometabolic risk factors. Among overweight/obese adolescents, being physically active attenuated the likelihood of high triglycerides and systolic blood pressure.
Under Consideration for Publication in J. Functional Programming [draft] the Calculus of Dependent Lambda Eliminations *

Modern constructive type theory is based on pure dependently typed lambda calculus, augmented with user-defined datatypes. This paper presents an alternative called the Calculus of Dependent Lambda Eliminations, based on pure lambda encodings with no auxiliary datatype system. New typing constructs are defined which enable induction, as well as large eliminations with lambda encodings. These constructs are constructor-constrained recursive types, and a lifting operation to lift simply typed terms to the type level. Using a lattice-theoretic denotational semantics for types, the language is proved logically consistent. The power of CDLE is demonstrated through several examples, which have been checked with a prototype implementation called Cedille.
Distributed noun attribute based on its first appearance for text document clustering

Selection of attributes plays a vital role to improve the quality of clustering. We present a comparative study on three attribute selection techniques and it reveals unattempt combinations, and provides guidelines in selecting attributes. It is occasionally studied in unsupervised learning; however it has been extensively explored in supervised learning. The suggested framework is primarily concerned with the problem of determining and selecting key distributional noun attributes, which are nominated by ranking the attributes according to the importance measure scores from the original noun attributes without class information. Experimental results on Reuter, 20 Newsgroup, WebKB and SCJC (Specific Crime Judgment Corpus) datasets indicate that algorithm with different scores in the context are able to identify the important attributes.
Evaluating plagiarism detection software for introductory programming assignments

Plagiarism is an issue that all educators have had to deal with. Large numbers of students and assignments have resulted in the development of automated systems to detect code similarities with the aim of identifying cases that may have been plagiarised. These systems are of great value to assessors, allowing them to process submissions automatically. However, these automated systems do present possible disadvantages and drawbacks. In this study we explore and analyse the differences between various systems as well as how their performance compares with manual checking. We consider the different methods students use when committing plagiarism. Then we examine more closely the systems that can aid plagiarism detection, ranging from their characteristics to how they work. In the process, we determine how these systems compare with our own system and their suitability for aiding the identification of submissions which may have been plagiarised in our introductory C++ course.
The Reduction Method for Valuing Derivative Securities

It is well known that derivative security valuation often reduces to solving a certain linear partial differential equation with variable coefficients. We derive a complicated expression which the three coefficients must satisfy in order that this PDE can be transformed into the heat equation. We also present a technique for constructing a triplet of coefficients which solve this expression. We thereby exhibit a technique for generating closed form solutions for derivative security values in a wide array of models.
Distance-Dependent Processing of Adeno-Associated Virus Type 5 RNA Is Controlled by 5′ Exon Definition

ABSTRACT Adeno-associated virus type 5 (AAV5) is unique among human AAV serotypes in that it uses a polyadenylation site [(pA)p] within the single small intron in the center of the genome. We previously reported that inhibition of polyadenylation at (pA)p, necessary for read-through of P41-generated capsid gene pre-mRNAs which are subsequently spliced, requires binding of U1 snRNP to the upstream donor. Inhibition was reduced as the distance between the cap site and the donor was increased (increasing the size of the 5′ exon). Here, we have demonstrated that U1-70K is a key component of U1 snRNP that mediates inhibition of polyadenylation at (pA)p. Furthermore, introduction of a U-rich stretch, predicted to target TIA-1 and thus increase the affinity of U1 snRNP binding to the intervening donor site, significantly augmented inhibition of (pA)p, while depletion of TIA-1 by siRNA increased (pA)p read-through. Finally, artificially tethering the cap binding complex (CBC) components CBP80 and CBP20 upstream of the intron donor increased inhibition of polyadenylation at (pA)p. Our results suggest that interaction with the CBC strengthens U1 snRNP binding to the downstream intron donor in a manner inversely proportional to the size of the 5′ exon, thus governing the competition between intron splicing and polyadenylation at (pA)p. This competition must be optimized to program both the levels of polyadenylation of P7- and P19-generated RNA at (pA)p required to produce proper levels of the essential Rep proteins and the splicing of P41-generated RNAs to produce the proper ratio of capsid proteins during AAV5 infection.
Institute for Quantum Information Findings – 2009-10

Quantum information science is an exciting emerging field that addresses how fundamental physical laws can be harnessed to dramatically improve the acquisition, transmission, and processing of information. The primary goal of the Institute for Quantum Information (IQI) is to carry out and facilitate research in quantum information science. Our research covers six broad areas: (1) Quantum algorithms that achieve speedups relative to classical algorithms, and limits on such algorithms. (2) Quantum cryptographic protocols, and other types of communication involving quantum states. (3) Quantum entanglement and the theory of transformations among quantum states. (4) Protection of quantum information using quantum error correcting codes, fault-tolerant protocols for quantum information processing, and control of quantum systems. (5) Theory and practice regarding physical implementations of quantum information processing. (6) Connections between quantum information science and other aspects of fundamental physics. Since our last annual report in May 2009, IQI participants have produced 49 publications, which we summarize here. Quantum algorithms for testing properties of graphs. Property testing is a means to extract information from massive data sets, in which an algorithm distinguishes between inputs that have some property P , and inputs that are far from having P , while only reading a small (randomly selected) portion of the input. Yi-Kai Liu, with Andrew Childs, found quantum algorithms for testing bipartiteness and expansion of bounded-degree graphs, which achieve a polynomial speed-up compared to the best possible classical algorithms [1]. These results were obtained by combining the existing classical algorithms with the previously known quantum algorithm for element distinctness and a derandomization using k-wise independent bits. Universal adiabatic quantum computation with stoquastic Hamiltonians. Stephen Jordan, with long-term IQI visitor Peter Love and with David Gosset, showed that excited states of stoquastic Hamiltonians are sufficient for universal adiabatic quantum computation [2]. Stoquastic Hamiltonians arise in many physical systems, including many proposed architectures for quantum computation using superconducting flux qubits. Previous work had indicated that, in contrast,
Are there alternatives to bankruptcy? A study of small business distress in Spain

Small businesses, the majority of Spanish firms, rarely file for formal bankruptcy when dealing with financial distress. This is why business bankruptcy rates in Spain are among the lowest in the world, even during the current economic crisis. To explain this fact we present the following hypothesis. Filing for bankruptcy in Spain is very costly for both small firms and their creditors. Due to this, the capital structure of micro firms is biased towards mortgage loans, as it allows them to avoid bankruptcy by carrying out debt enforcement via mortgage foreclosures, which are cheaper procedures than bankruptcy, in case of financial distress. The empirical tests of our hypothesis consist of comparing the observed choices (choice of capital structure, choice between bankruptcy and mortgage) of Spanish firms with those of firms from countries (France and the UK) where their bankruptcy systems are more efficient and their laws do not incentivise them to bias their capital structure towards mortgage loans. Our findings corroborate the proposed hypothesis. As bankruptcy procedures and mortgage foreclosures are not perfect substitutes—i.e., they do not suit well the same type of firms- the underutilization of one of them—reflected in low bankruptcy rates- may lead to efficiency losses.
Toward a Framework for the Analysis and Design of Educational Games

We describe and illustrate the beginnings of a general framework for the design and analysis of educational games. Our students have used it to analyze existing educational games and to create prototype educational games. The framework is built on existing components: a method for precisely specifying educational objectives, a framework for relating a game’s mechanics, dynamics, and aesthetics, and principles for instructional design grounded in empirical research in the learning sciences. The power of the framework comes from the components themselves, as well as from considering these components in concert and making connections between them. The framework coordinates the many levels at which an educational game must succeed in order to be effective. We illustrate the framework by using it to analyze Zombie Division and to generate some redesign ideas for this game.
Efficacy of Alpha Blocker Treatment According to the Degree of Intravesical Prostatic Protrusion Detected by Transrectal Ultrasonography in Patients with Benign Prostatic Hyperplasia

Purpose To analyze the effectiveness of tamsulosin 0.2 mg once daily for 3 months according to the degree of intravesical prostatic protrusion (IPP) in patients with benign prostatic hyperplasia (BPH). Materials and Methods A total of 134 BPH patients over 40 years of age treated with tamsulosin 0.2 mg between January 2007 and January 2009 were enrolled retrospectively. The patients were classified into three groups according to the degree of IPP: below 5 mm (group A), between 5 and 10 mm (group B), and over 10 mm (group C). Prostate volume, prostate-specific antigen (PSA), prostatic urethral length (PUL), and prostatic adenoma urethral length (PAUL) were evaluated before treatment. International Prostate Symptom Score and Quality of Life (IPSS/QoL), maximal urine flow rate (Qmax), and postvoid residual (PVR) volume were measured before treatment, and improvement in the three groups was compared after 3 months. Results The mean age of the patients was 65.01±7.38 years. Mean IPPs were 0.90±1.39 mm (group A, n=90), 6.92±1.10 mm (group B, n=24), and 16.60±4.06 mm (group C, n=20). Prostate volume, PUL, PAUL, PSA, Qmax, and PVR showed significant correlations with IPP (p<0.05), but not with IPSS/QoL score (p>0.05). Comparison of parameters before and after 3 months showed that medication improved total IPSS and subscores (p<0.001), QoL (p<0.001), Qmax (p<0.001), and PVR (p=0.030) in group A. In group B, it improved total IPSS (p=0.01), irritative subscore (p<0.001), and obstructive subscore (p=0.03). In group C, only total IPSS (p=0.01) and irritative score (p<0.001) were significantly improved. Conclusions Tamsulosin may be more effective in improving symptom scores and Qmax in patients with mild IPP than in those with moderate or severe IPP.
Merging Genomes with Geochemistry in Hydrothermal Ecosystems

Thermophilic microbial inhabitants of active seafloor and continental hot springs populate the deepest branches of the universal phylogenetic tree, making hydrothermal ecosystems the most ancient continuously inhabited ecosystems on Earth. Geochemical consequences of hot water-rock interactions render these environments habitable and supply a diverse array of energy sources. Clues to the strategies for how life thrives in these dynamic ecosystems are beginning to be elucidated through a confluence of biogeochemistry, microbiology, ecology, molecular biology, and genomics. These efforts have the potential to reveal how ecosystems originate, the extent of the subsurface biosphere, and the driving forces of evolution.
The next information architecture evolution: the data lake wave

Data warehouses and data marts have long been considered as the unique solution for providing end-users with decisional information. More recently, data lakes have been proposed in order to govern data swamps. However, no formal definition has been proposed in the literature. Existing works are not complete and miss important parts of the topic. In particular, they do not focus on the influence of the data gravity, the infrastructure role of those solutions and of course are proposing divergent definitions and positioning regarding the usage and the interaction with existing decision support system. In this paper, we propose a novel definition of data lakes, together with a comparison with other over several criteria as the way to populate them, how to use, what is the Data Lake end user profile. We claim that data lakes are complementary components in decisional information systems and we discuss their position and interactions regarding the other components by proposing an interaction model.
Atmospheric Chemistry and Physics Ozone Air Quality during the 2008 Beijing Olympics: Effectiveness of Emission Restrictions

A series of aggressive measures was launched by the Chinese government to reduce pollutant emissions from Beijing and surrounding areas during the Olympic Games. Observations at Miyun, a rural site 100 km downwind of the Beijing urban center, show significant decreases in concentrations of O 3 , CO, NO y , and SO 2 during August 2008, relative to August 2006–2007. The mean daytime mixing ratio of O 3 was lower by about 15 ppbv, reduced to 50 ppbv, in August 2008. The relative reductions in daytime SO 2 , CO, and NO y were 61%, 25%, and 21%, respectively. Changes in SO 2 and in species correlations from 2007 to 2008 indicate that emissions of SO 2 , CO, and NO x were reduced at least by 60%, 32%, and 36%, respectively, during the Olympics. Analysis of meteorological conditions and interpretation of observations using a chemical transport model suggest that although the day-today variability in ozone is driven mostly by meteorology, the reduction in emissions of ozone precursors associated with the Olympic Games had a significant contribution to the observed decrease in O 3 during August 2008, accounting for 80% of the O 3 reduction for the month as a whole and 45% during the Olympics Period (8– 24 August). The model predicts that emission restrictions such as those implemented during the Olympics can affect O 3 far beyond the Beijing urban area, resulting in reductions in boundary layer O 3 of 2–10 ppbv over a large region of the North China Plain and Northeastern China.
Operation shuffling for low energy L0 cluster generation on heterogeneous VLIW processors

Clustering L0 buffers is effective for reduction of energy consumption in the instruction memory hierarchy of embedded VLIW processors. However, efficiency of the clustering depends on schedule and assignment of a target application. This paper proposes a tool flow to explore operation shuffling for improving generation of L0 clusters. The tools explore assignment of operations for each cycle and generate various schedules. This approach makes it possible to reduce energy consumption for various processor architectures, however, the computational complexity is large because of huge exploration space. Therefore, some heuristics are also developed, which reduce the size of exploration space while the quality of solution remains reasonable. The experimental results indicate potential gain of up to 22.0% in energy of the operation shuffling for various heterogeneous processor architectures. Furthermore, the proposed heuristics drastically reduce the exploration search space by about 90%, while the results are comparable to full search, differences of up to 1%.