Miracle-dz/UniFAR-FTUs huggingface dataset:
Computational power of pipelined memory hierarchies

We define a model of computation, called the <i>Pipelined Hierarchical Random Access Machine</i> with <i>access function a</i> (<i>x</i>), denoted the <i>a</i>(<i>x</i>)-PH-RAM. In this model, a processor interacts with a memory which can accept requests at a constant rate and satisfy each of the requests to the location <i>x</i> within a(<i>x</i>) units of time. We investigate memory management strategies that lead to time efficient implementations of arbitrary computations on a PH-RAM. We begin by developing the so called <i>pipeline d decomposition-tree</i>memory management strategy, which can be tuned to the memory access function. Specifically, for a linear or sublinear access function <i>a</i>(<i>x</i>), w e define the concept of <i>latency-hiding depth d<subscrpt>a</subscrpt></i>(<i>x</i>) and show ho w an y computation of <i>N</i> operations can be implemented on an <i>a</i>(<i>x</i>)-PH-RAM in time <i>T</i>(<i>N</i>) = <i>&Ogr;</i>(<i>Nd<subscrpt>a</subscrpt></i>(<i>N</i>)). In particular, <i>T</i>(<i>N</i>) = <i>&Ogr;</i>(<i>N</i> log <i>N</i>) if <i>a</i>(<i>x</i>) = <i>&Ogr;</i>(<i>x</i>), <i>T</i>(<i>N</i>) = <i>&Ogr;</i>(<i>N</i> log log <i>N</i>) if <i>a</i>(<i>x</i>) = <i>&Ogr;</i>(<i>x<sup>Β</sup></i>) with 0 < <i>Β</i> < 1, and <i>T</i>(<i>N</i>) = O(<i>N</i> log* <i>N</i>) if <i>a</i>(<i>x</i>) = <i>&Ogr;</i>(log <i>x</i>). We develop lower bound techniques that allow to establish existential lower bounds on PH-RAMs. In particular, we exhibit computations for which <i>T</i>(<i>N</i>) = &OHgr;(<i>N</i>log <i>N</i>/ log log <i>N</i>) when <i>a</i>(<i>x</i>) = &OHgr;(<i>x</i>), <i>T</i>(<i>N</i>) = &OHgr;(<i>N</i>log log<i>N</i>) when <i>a</i>(<i>x</i>) = &OHgr;(<i>x<sup>Β</sup></i>) with 0 < <i>Β</i> < 1, and <i>T</i>(<i>N</i>) = &OHgr;(<i>N</i> log* <i>N</i>) when <i>a</i>(<i>x</i>) = &OHgr;(log <i>x</i>). The stated lower bounds show that the pipelined decomposition-tree strategy is existentially optimal for the latter case but indicates the potential for a modest, <i>&Ogr;</i>(log log <i>N</i>) improvement for linear access functions. To realize this potential, a <i>superpipelined</i> decomposition-tree memory manager is proposed, which achieves <i>T</i>(<i>N</i>) = <i>&Ogr;</i>(<i>N</i> log <i>N</i>/log log <i>N</i>). The pipelined decomposition-tree strategy can also be tuned to the computation, in order to exploit its <i>temporal locality</i> as characterized by the width parameters [9]. When the latter are suitably bounded, then <i>T</i>(<i>N</i>) = <i>&Ogr;</i>(<i>N</i>) on any PH-RAM with linear or sublinear access function. Finally, we discuss how performance could benefit from <i>parallelism</i> in the data-dependence dag of the computation or from architectural enhancements, such as <i>block-transfer</i> primitives, and formulate various questions that deserve further investigation.
Extracting preference terms from web browsing histories excluding pages unrelated to users' interests

Personalization is one of the most significant challenges in the World Wide Web. Extracting preference terms chiefly from Web browsing histories is a first step in personalization. However, a portion of Web pages includes information unrelated to the users' interests, and personalization results would probably be fuzzy owing to such pages. In this paper, we propose an approach to extract preference terms from Web browsing histories, excluding pages unrelated to the users' interests. Our proposed approach mainly consists of two steps. First is a page classification step, utilizing both URL expressions and keyphrase frequencies in the page, in order to eliminate keyphrases derived from pages unrelated to the users' interests. Second is a keyphrase scoring step, exploiting document frequency of terms, in order to obtain preference terms. Our empirical study for 5 participants over a period of 4 weeks reveals that the proposed approach is more effective for the users with specific Web browsing styles.
Danger-system: Exploring new ways to manage occupants safety in smart building

Safety has always been a main concern in complex buildings: automated solutions to respond to crisis events limiting damages and victims have been researched and adopted in commercial and private buildings since late 19th century. However, the methods available have some limitations: for example the impossibility to promptly detect false alarms and to provide context-dependent notification, which are fundamental to persuade tenants to a fast egress. In this paper we present the architecture of a system for the detection and management of emergencies in smart buildings. The designed architecture shows some novelties and key features which distinguish it from already existing solutions. Indeed, the proposed architecture exploits the existing building management systems leveraging mobile crowd sensing to collect valuable information during a crisis. The new generation of mobile devices are used to dispatch notification and collect users feedback. In order to test and validate the system, we have built a simulation framework which simulates the building environment.
Students perceive Team-Based Learning facilitates development of graduate learning outcomes and professional skills

In tertiary education, generic professional skills should be developed along with discipline-specific knowledge and skills. Team-Based Learning (TBL), an active learning strategy, creates deep learning and enhanced student engagement; however, its effects on the development of generic learning outcomes are unknown. The aim of this study was to evaluate postgraduate specialty nursing students’ perspectives of how TBL impacts the acquisition of skills defined by the university’s eight Graduate Learning Outcomes (GLOs). A descriptive exploratory design was used in this study. Postgraduate nursing students in 2016-2017 at one university were invited to participate. Data were collected via demographic survey, a ranking tool, and written reflections. Data were analysed using descriptive statistics and content analysis. The response rate was 97.2 per cent (172/177). Participants were mostly females (n=152, 88.4%) aged 25–34 years (n=115, 66.9%). Student (n=156) rankings showed TBL contributed to the acquisition of critical thinking (n=90, 57.7%) and problem solving skills (n=56, 35.9%) the most. Students (n=144) made 2719 comments regarding how TBL led to the acquisition of GLOs in written reflections. Almost 98 per cent (n=2657) of all reflective comments were positive. All students mentioned at least one GLO positively due to TBL. Most positive reflections related to self-management (n=520, 19.6%) and communication (n=434, 16.3%). Postgraduate specialty nursing students perceived TBL classes contributed to the acquisition of their university’s GLOs, particularly critical thinking, problem solving, and self-management skills. The active learning strategy of TBL facilitates learning and engagement, and the attainment of essential professional attributes which are highly valued by employers.
APOBEC3G Oligomerization Is Associated with the Inhibition of Both Alu and LINE-1 Retrotransposition

Alu and LINE-1 (L1), which constitute ~11% and ~17% of the human genome, respectively, are transposable non-LTR retroelements. They transpose not only in germ cells but also in somatic cells, occasionally causing cancer. We have previously demonstrated that antiretroviral restriction factors, human APOBEC3 (hA3) proteins (A–H), differentially inhibit L1 retrotransposition. In this present study, we found that hA3 members also restrict Alu retrotransposition at differential levels that correlate with those observed previously for L1 inhibition. Through deletion analyses based on the best-characterized hA3 member human APOBEC3G (hA3G), its N-terminal 30 amino acids were required for its inhibitory activity against Alu retrotransposition. The inhibitory effect of hA3G on Alu retrotransposition was associated with its oligomerization that was affected by the deletion of its N-terminal 30 amino acids. Through structural modeling, the amino acids 24 to 28 of hA3G were predicted to be located at the interface of the dimer. The mutation of these residues resulted in abrogated hA3G oligomerization, and consistently abolished the inhibitory activity of hA3G against Alu retrotransposition. Importantly, the anti-L1 activity of hA3G was also associated with hA3G oligomerization. These results suggest that the inhibitory activities of hA3G against Alu and L1 retrotransposition might involve a common mechanism.
The Impact of Alcohol Consumption on Occupational Attainment in England

In this study we provide evidence on the effect of alcohol consumption on occupational attainment in England. To do this we use samples of employees from the Health Survey for England between 1992 and 1996. We find that due to the endogenous nature of alcohol consumption, OLS estimates may provide a biased picture of the impact of alcohol consumption on occupational attainment. Using various sets of instrumental variables, we find positive and significant returns to moderate levels of drinking for male and female employees which drop-off rapidly as consumption increases.
Protein Classification Using Artificial Neural Networks with Different Protein Encoding Methods

The fast growth of annotated biological data implies in the need of developing new techniques and tools to classify these data, in such way that they can be useful. Protein classification is one relevant task in this context. This paper presents different models of neural network, aiming to compare the influence of the protein sequence encoding method in the performance of the Neural network to classify proteins. Besides, it is proposed two methods of protein sequence encoding, that were tested with several neural network, for classifying proteins using two approaches: based on families of proteins and based on function of proteins. The results of performance of the neural networks are presented and compared with other works in the area.
A Study of the Level of Intercultural Communicative Competence and Intercultural Sensitivity of Iranian Medical Students Based on Ethnicity

ABSTRACT Competence and sensitivity at intercultural communication are essential for an effective and appropriate communication in the context of health care. The present study sought to survey the levels of intercultural communicative competence (ICC) and intercultural sensitivity (IS) of 400 Iranian medical students based on their ethnic backgrounds (i.e. Fars, Turkish, Kurdish, and Lor). The findings of this study indicated that the four ethnic groups had moderate levels of ICC and IS, and that the Lor ethnic group had the lowest mean scores on the four dimensions of ICC (i.e. knowledge, attitude, skills, and awareness). Implications and suggestions for further research are discussed.
Auction-based power allocation for relay communication

In this paper, the auction theory based power allocation is investigated for relay communications, wherein all relays bid for the transmit power from a server. A target BER at the destination is introduced as the power-bidding criterion to guarantee the received signal's availability. For maximizing the revenue, all relay nodes compete for the limit power resource and attain the Nash equilibrium. Given the local information, we develop a dynamic updating algorithm to adjust the allocation. Moreover, the stability of the dynamic algorithm is demonstrated and analyzed.
Uses and Abuses of Factor Analysis

Factor analysis, if used cautiously and with a full understanding of its underlying logic, can illuminate many fields of research. It is a statistical method, based on correlation analysis, for combining a number of measured variables into a smaller number of groups of variables: the groups are the factors. They are in no way absolute and the basis of their choice is partly subjective: they constitute a hypothesis that requires to be tested. Examples are given to show the fruitfulness of factor analysis.
Adaptive nonparametric confidence sets

We construct honest confidence regions for a Hilbert space-valued parameter in various statistical models. The confidence sets can be centered at arbitrary adaptive estimators, and have diameter which adapts optimally to a given selection of models. The latter adaptation is necessarily limited in scope. We review the notion of adaptive confidence regions, and relate the optimal rates of the diameter of adaptive confidence regions to the minimax rates for testing and estimation. Applications include the finite normal mean model, the white noise model, density estimation and regression with random design. © Institute of Mathematical Statistics, 2006.
EMPATHIZING – SYSTEMIZING THEORY IN ROMANIAN UNIVERSITY CONTEXT

222 students of Transilvania University of Braov, from Humanities and Sciences faculties, with the average age of 23.07 years (SD = 3.92), out of which 88 (39.6%) males, 134 (6.4%) females, were investigated with four questionnaires destined to measure autism quotient (AQ), empathizing quotient (EQ), systemizing quotient (SQ) and the score for Reading the Mind in the Eyes Test (RMET). The study objectives were to investigate the relationships between variables, to determine psychometric qualities for some of the four questionnaires that were used in the Romanian university population context, to test the hypothesis of gender and specialisation differences for some variables and to propose a new method to determine the five categories of brain types. The results highlight psychometric qualities that are poorer than the initial ones of some of the used instruments, but they confirm the hypothesis of gender and of specialisation for some of the study variables in accord with data of other studies. The method of determining the five brain types proves to be more operational but congruent and highly correlated with the one that Goldenfeld et al. proposed.
Radar Signal Classification Based on Cascade of STFT, PCA and Naïve Bayes

In this paper, for radar signals with different ways of frequency or phase modulation, Cascade of Short Time Fourier Transform (STFT) and Principal Component Analysis (PCA) is employed for effective Feature Extraction. Compressive ratios of dimensions are quite impressive. For the same features, applying Naïve Bayes on the whole set of radar signals, higher accuracy rate is got than the case where classifier is SVM. Besides, a Hierarchical Structure is designed for finer classifications of radar signals. Comparison shows that Hierarchical Structure contributes little to increase of accuracy rate of radar signal classification by cascade systems on the whole set. Models are trained on 10db and tested on different Signal Noise Ratios (SNR).
Geometry of Admissible Parameter Region in Neural Learning

In general, a learning machine will behave better as the number of training examples increases. It is important to know how fast and how well the behavior is improved. The average prediction error, the average of the probability that the trained machine mispredicts the output signal, is one of the most popular criteria to see the behavior. However, it is not easy to evaluate the average prediction error even in the simplest case, that is, the linear dichotomy (perceptron) case. When a continuous deterministic dichotomy machine is trained by t examples of input-output pairs produced from a realizable teacher, these examples limits the region of the parameter space which includes the true parameter. Any parameter in the region can explain the input-output behaviors of the examples. Such a region, called the admissible region, forms in general a (curved) polyhedron in the parameter space, and it becomes smaller and smaller as the number of examples increases. The present paper studies the shape and volume of the admissible region. We use the stochastic geometrical approach to this problem. We have studied the stochastic geometrical features of the admissible region using the fact that it is dual to the convex hull the examples make in the example space. Since the admissible region is related to the average prediction error of the linearly dichotomy, we derived the new upper and lower bound of the average prediction error.
Extending representations of subgroups and the duality of induction and restriction

Suppose that G is a locally compact group and U is a representation of a closed subgroup H of G on a Hilbert space H. We use nonabelian duality for crossed products of C *-algebras to study the following problem: when does U extend to a representation of G on the same space H?
Visualizing software entities using a matrix layout

Understanding legacy systems is one of the major tasks in software engineering. The relations between different entities, e.g., packages and classes in Java, are important for this understanding process. We propose a matrix based visualization of the relations between these software entities. We explore several design decisions and show what works and what does not work.
Wild-Type Measles Viruses with Non-Standard Genome Lengths

The length of the single stranded, negative sense RNA genome of measles virus (MeV) is highly conserved at 15,894 nucleotides (nt). MeVs can be grouped into 24 genotypes based on the highly variable 450 nucleotides coding for the carboxyl-terminus of the nucleocapsid protein (N-450). Here, we report the genomic sequences of 2 wild-type viral isolates of genotype D4 with genome lengths of 15,900 nt. Both genomes had a 7 nt insertion in the 3′ untranslated region (UTR) of the matrix (M) gene and a 1 nt deletion in the 5′ UTR of the fusion (F) gene. The net gain of 6 nt complies with the rule-of-six required for replication competency of the genomes of morbilliviruses. The insertions and deletion (indels) were confirmed in a patient sample that was the source of one of the viral isolates. The positions of the indels were identical in both viral isolates, even though epidemiological data and the 3 nt differences in N-450 between the two genomes suggested that the viruses represented separate chains of transmission. Identical indels were found in the M-F intergenic regions of 14 additional genotype D4 viral isolates that were imported into the US during 2007–2010. Viral isolates with and without indels produced plaques of similar size and replicated efficiently in A549/hSLAM and Vero/hSLAM cells. This is the first report of wild-type MeVs with genome lengths other than 15,894 nt and demonstrates that the length of the M-F UTR of wild-type MeVs is flexible.
Active and dormant languages in the multilingual mental lexicon

ABSTRACT Two experimental paradigms, a picture-naming task and a Stroop interference task, were employed to address the structure of the multilingual mental lexicon; more specifically, the process of multilingual non-selective lexical access. German-English-French speakers named objects in their native and most dominant language in a task that included a manipulation of triple (Wein, wine, vin) and double cognates (Beere, berry or Zitrone, citron). The vocal Stroop task was administered in both within- and between-language conditions to explore the interference patterns between the languages. In general, it was hypothesised that differing levels of language proficiency will play an integral role in the observed results. The speech onset times were measured for both tasks and pointed to complex interaction patterns. German and English were seen as the most active and prone to interference systems, whilst French appeared more as a dormant language that does not exert much influence on the other two systems.
An Enhanced Multi-Pager Environment Support for Second Generation Microkernels

The main objective of this paper is to present a mechanism of enhanced paging support for the second generation microkernels in the form of explicit support of multi-pager environment for the tasks running in the system. Proposed mechanism is based on the intra-kernel high granularity pagers assignments per virtual address space, which allow efficient and simple dispatching of page faults to the appropriate pagers. The paging is one of the major features of the virtual memory, which is extensively used by advanced operating systems to provide an illusion of elastic memory. Original and present second generation microkernels provide only limited, inflexible and unnatural support for paging. Furthermore, facilities provided by current solutions for multi-pager support on the runtime level introduce an overhead in terms of mode switches and thread context switches which can be significantly reduced. Limited paging support limits the attractiveness of the second generation microkernel based systems use in real-life applications, in which processes usually have concurrent servicing of multiple paging servers. The purpose of this paper is to present a facilities for the efficient and flexible support of multi-pager environments for the second generation microkernels. A comparison of the proposed solution to the present architecture L4 + L4Re has been made and overhead of the page fault handling critical path has been evaluated. Proposed solution is simple enough and provides a natural and flexible support of multi-pager environments for second generation microkernels in efficient way. It introduces a third less overhead in terms of the mode switches and thread context switches in comparison to the present L4 + L4Re solution implemented in the Fiasco.OC.
High-Resolution Enabled 12-Plex DiLeu Isobaric Tags for Quantitative Proteomics

Multiplex isobaric tags (e.g., tandem mass tags (TMT) and isobaric tags for relative and absolute quantification (iTRAQ)) are a valuable tool for high-throughput mass spectrometry based quantitative proteomics. We have developed our own multiplex isobaric tags, DiLeu, that feature quantitative performance on par with commercial offerings but can be readily synthesized in-house as a cost-effective alternative. In this work, we achieve a 3-fold increase in the multiplexing capacity of the DiLeu reagent without increasing structural complexity by exploiting mass defects that arise from selective incorporation of 13C, 15N, and 2H stable isotopes in the reporter group. The inclusion of eight new reporter isotopologues that differ in mass from the existing four reporters by intervals of 6 mDa yields a 12-plex isobaric set that preserves the synthetic simplicity and quantitative performance of the original implementation. We show that the new reporter variants can be baseline-resolved in high-resolution higher-energy C-trap dissociation (HCD) spectra, and we demonstrate accurate 12-plex quantitation of a DiLeu-labeled Saccharomyces cerevisiae lysate digest via high-resolution nano liquid chromatography–tandem mass spectrometry (nanoLC–MS2) analysis on an Orbitrap Elite mass spectrometer.
Bounding WCET of applications using SDRAM with Priority Based Budget Scheduling in MPSoCs

SDRAM is a popular off-chip memory that provides large data storage, high data rates, and is in general significantly cheaper than SRAM. There is a growing interest in using SDRAMs in safety critical application domains like aerospace, automotive and industrial automation. Some of these applications have hard real-time requirements where missing a deadline can have devastating consequence. Before integrating any hardware or software in this type of system it needs to be proven that deadlines will always be met. In practice, this is done by analyzing application's timing behavior and calculating its Worst Case Execution Time (WCET). SDRAMs have variable access latencies depending on the refresh operation and the previous accesses. This paper builds on hardware techniques such as bank interleaving and applying Priority Based Budget Scheduling (PBS) to share the SDRAM among multiple masters. Its main contribution is a technique to bound the WCET of an application accessing a shared SDRAM of a multicore architecture using the worst case access pattern. We implemented and tested an overall memory system on an Altera Cyclone III FPGA and applied the proposed WCET estimation technique. The results show that our technique produces safe and low WCET bounds.