Miracle-dz/UniFAR-FTUs huggingface dataset:
MITTS: Memory Inter-arrival Time Traffic Shaping

Memory bandwidth severely limits the scalability and performance of multicore and manycore systems. Application performance can be very sensitive to both the delivered memory bandwidth and latency. In multicore systems, a memory channel is usually shared by multiple cores. Having the ability to precisely provision, schedule, and isolate memory bandwidth and latency on a per-core basis is particularly important when different memory guarantees are needed on a per-customer, per-application, or per-core basis. Infrastructure as a Service (IaaS) Cloud systems, and even general purpose multicores optimized for application throughput or fairness all benefit from the ability to control and schedule memory access on a fine-grain basis. In this paper, we propose MITTS (Memory Inter-arrival Time Traffic Shaping), a simple, distributed hardware mechanism which limits memory traffic at the source (Core or LLC). MITTS shapes memory traffic based on memory request inter-arrival time, enabling fine-grain bandwidth allocation. In an IaaS system, MITTS enables Cloud customers to express their memory distribution needs and pay commensurately. For instance, MITTS enables charging customers that have bursty memory traffic more than customers with uniform memory traffic for the same aggregate bandwidth. Beyond IaaS systems, MITTS can also be used to optimize for throughput or fairness in a general purpose multi-program workload. MITTS uses an online genetic algorithm to configure hardware bins, which can adapt for program phases and variable input sets. We have implemented MITTS in Verilog and have taped-out the design in a 25-core 32nm processor and find that MITTS requires less than 0.9% of core area. We evaluate across SPECint, PARSEC, Apache, and bhm Mail Server workloads, and find that MITTS achieves an average 1.18× performance gain compared to the best static bandwidth allocation, a 2.69× average performance/cost advantage in an IaaS setting, and up to 1.17x better throughput and 1.52× better fairness when compared to conventional memory bandwidth provisioning techniques.
Long range attachments - a method to simulate inextensible clothing in computer games

Inextensibility is one of the most fundamental properties of cloth. Existing approaches to handle inextensibility often require solving global non-linear systems and remain computationally expensive for computer game uses. Real time performance can be achieved by allowing damping or stretching at reduced solver costs, but these compromise visual realism - the cloth either looks stretchy or fine wrinkles get lost. Our long range attachment (LRA) method exploits that typical game character clothing tends to be attached to some kinematic parts of the character. LRA method applies unilateral distance constraint between free particles of the cloth to distant attachment point on the character, preventing them from stretching away from the kinematically driven attachments (e.g. shoulder for a cape). This simple step provides an efficient shortcut for enforcing global inextensibility that can be readily implemented into existing game physics methods such as PBD.
Rapid similarity search of proteins using alignments of domain arrangements

MOTIVATION Homology search methods are dominated by the central paradigm that sequence similarity is a proxy for common ancestry and, by extension, functional similarity. For determining sequence similarity in proteins, most widely used methods use models of sequence evolution and compare amino-acid strings in search for conserved linear stretches. Probabilistic models or sequence profiles capture the position-specific variation in an alignment of homologous sequences and can identify conserved motifs or domains. While profile-based search methods are generally more accurate than simple sequence comparison methods, they tend to be computationally more demanding. In recent years, several methods have emerged that perform protein similarity searches based on domain composition. However, few methods have considered the linear arrangements of domains when conducting similarity searches, despite strong evidence that domain order can harbour considerable functional and evolutionary signal. RESULTS Here, we introduce an alignment scheme that uses a classical dynamic programming approach to the global alignment of domains. We illustrate that representing proteins as strings of domains (domain arrangements) and comparing these strings globally allows for a both fast and sensitive homology search. Further, we demonstrate that the presented methods complement existing methods by finding similar proteins missed by popular amino-acid-based comparison methods. AVAILABILITY An implementation of the presented algorithms, a web-based interface as well as a command-line program for batch searching against the UniProt database can be found at http://rads.uni-muenster.de. Furthermore, we provide a JAVA API for programmatic access to domain-string–based search methods.
AMPK agonist AICAR improves cognition and motor coordination in young and aged mice

Normal aging can result in a decline of memory and muscle function. Exercise may prevent or delay these changes. However, aging-associated frailty can preclude physical activity. In young sedentary animals, pharmacological activation of AMP-activated protein kinase (AMPK), a transcriptional regulator important for muscle physiology, enhanced spatial memory function, and endurance. In the present study we investigated effects of AMPK agonist 5-aminoimidazole-4-carboxamide riboside (AICAR) on memory and motor function in young (5- to 7-wk-old) and aged (23-mo-old) female C57Bl/6 mice, and in young (4- to 6-wk-old) transgenic mice with muscle-specific mutated AMPK α2-subunit (AMPK-DN). Mice were injected with AICAR (500 mg/kg) for 3–14 d. Two weeks thereafter animals were tested in the Morris water maze, rotarod, and open field. Improved water maze performance and motor function were observed, albeit at longer duration of administration, in aged (14-d AICAR) than in young (3-d AICAR) mice. In the AMPK-DN mice, the compound did not enhance behavior, providing support for a muscle-mediated mechanism. In addition, microarray analysis of muscle and hippocampal tissue derived from aged mice treated with AICAR revealed changes in gene expression in both tissues, which correlated with behavioral effects in a dose-dependent manner. Pronounced up-regulation of mitochondrial genes in muscle was observed. In the hippocampus, genes relevant to neuronal development and plasticity were enriched. Altogether, endurance-related factors may mediate both muscle and brain health in aging, and could play a role in new therapeutic interventions.
Optimization of Matrix Multiply on the Itanium 2

Since the Itanium 2 does not allow floating point values in its L1 cache, the first level of cache blocking possible is for the L2 cache. Though the original blocked implementation found 56 to be optimal the block size, no block sizes larger than 64 were attempted, so we tried larger block sizes. To simplify matters, we only tested block sizes that were powers of 2. Figure 1 shows that 128 is the optimal L2 block size, agreeing with the result computed by the formula in [1].
ROBOTIC RESEARCH PLATFORM FOR IMAGE-GUIDED SURGERY ASSISTANCE

In the context of surgery, it is very common to face challenging scenarios during the preoperative plan implementation. The surgical technique’s complexity, the human anatomical variability and the occurrence of unexpected situations generate issues for the intervention’s goals achievement. To support the surgeon, robotic systems are being integrated to the operating room. However, current commercial solutions are specialized for a particular technique or medical application, being difficult to integrate with other systems. Thus, versatile and modular systems are needed to conduct several procedures and to help solving the problems that surgeons face. This article aims to describe the implementation of a robotic research platform prototype that allows novel applications in the field of image-guided surgery. In particular, this research is focused on the topics of medical image acquisition during surgery, patient registration and surgical/medical equipment operation. In this paper, we address the implementation of the general purpose teleoperation and path following modes of the platform, which constitute the base of future developments. Also, we discuss relevant aspects of the system, as well as future directions and application fields to investigate.
Deriving Models for Software Project Effort Estimation by Means of Genetic Programming

This paper presents the application of a computational intelligence methodology in effort estimation for software projects. Namely, we apply a genetic programming model for symbolic regression; aiming to produce mathematical expressions that (1) are highly accurate and (2) can be used for estimating the development effort by revealing relationships between the project’s features and the required work. We selected to investigate the effectiveness of this methodology into two software engineering domains. The system was proved able to generate models in the form of handy mathematical expressions that are more accurate than those found in literature.
How much stress do researchers inflict on their study animals? A case study using a scincid lizard, Eulamprus heatwolei

SUMMARY Research on live vertebrates is regulated by ethics committees, who prohibit `excessively stressful' procedures. That judgment is based on intuition – a notoriously unreliable criterion when dealing with animals phylogenetically distant from humans. To objectively evaluate the stress imposed by research practices, we measured plasma corticosterone levels in lizards (Eulamprus heatwolei Wells & Wellington, Scincidae). Some procedures (handling and measuring, toe-clipping for identification, exposure to predator scent) did not induce significant increases in corticosterone levels, suggesting that these stimuli generated relatively little stress. However, other stimuli (testing locomotor speed, microchip implantation, blood sampling, an unfamiliar enclosure, tail autotomy, exposure to a heterospecific lizard) were more stressful, with corticosterone levels increasing only transiently in some treatments (<2 h for tail autotomy), but persisting much longer in others (14 days for microchip implantation). Overall, our data suggest that the levels of stress induced by routine laboratory procedures are no greater than those often experienced by lizards in nature; but that intuition provides a poor basis for evaluating the levels of stress induced by research. For example, toe-clipping is often criticized and sometimes banned; but our data suggest that this method is actually less stressful than the technique frequently recommended to replace it on ethical grounds (microchip implantation). Toe-clipping also was less stressful than superficially trivial manipulations such as housing the animal in an unfamiliar enclosure. More generally, we urge researchers to seek objective information on the effects of their activities on research subjects, rather than relying upon subjectivity and anthropomorphism in making these evaluations.
The Personality Analyzer

In this paper, we describe the Personality Analyzer. It is an artifact that analyses the users personality. The motivation for the project was to enter deeply in the aesthetics of interaction design with a physical artifact as an outcome. Focus for the project has been on aesthetics and expressions rather than functionality. The primary target group was girls from 8 years and up. During development we used, brainstorming, mind maps, sketches and interviews and we also made mock-ups for initial testing. The result was an artifact that analyses the users personality. The most unique aspect of the artifact is the input device. A user describes her personality to the system by selecting clothes used to dress a paper doll. All technology is hidden from the user.
In-Depth Quantitative Proteomic Analysis of de Novo Protein Synthesis Induced by Brain-Derived Neurotrophic Factor

Measuring the synthesis of new proteins in the context of a much greater number of pre-existing proteins can be difficult. To overcome this obstacle, bioorthogonal noncanonical amino acid tagging (BONCAT) can be combined with stable isotope labeling by amino acid in cell culture (SILAC) for comparative proteomic analysis of de novo protein synthesis (BONLAC). In the present study, we show that alkyne resin-based isolation of l-azidohomoalanine (AHA)-labeled proteins using azide/alkyne cycloaddition minimizes contamination from pre-existing proteins. Using this approach, we isolated and identified 7414 BONCAT-labeled proteins. The nascent proteome isolated by BONCAT was very similar to the steady-state proteome, although transcription factors were highly enriched by BONCAT. About 30% of the methionine residues were replaced by AHA in our BONCAT samples, which allowed for identification of methionine-containing peptides. There was no bias against low-methionine proteins by BONCAT at the proteome level. When we applied the BONLAC approach to screen for brain-derived neurotrophic factor (BDNF)-induced protein synthesis, 53 proteins were found to be significantly changed 2 h after BDNF stimulation. Our study demonstrated that the newly synthesized proteome, even after a short period of stimulation, can be efficiently isolated by BONCAT and analyzed to a depth that is similar to that of the steady-state proteome.
Approaching the Zero-Outage Capacity of MIMO-OFDM without Water-Filling

Orthogonal-frequency-division multiplexing (OFDM) transforms a frequency-selective multiple-input multipleoutput (MIMO) fading channel into a MIMO-OFDM channel that has a well-defined outage capacity. According to Shannon theory, a transmitter with channel knowledge can achieve this capacity by a combination of eigenbeamformingand water-filling; the eigenbeamforming transforms the MIMO-OFDM channel into a parallel bank of scalar channels, and the water-filling procedure optimally allocates rate and energy to the scalar channels. Since water-filling adapts the rate to match the channel, it can be viewed as a form of adaptive modulation. Despite its optimality, the practicality of this procedure is limited by its high complexity. This paper shows that the full-blown water-filling procedure is not necessary to approach the zero-outage capacity of the MIMO-OFDM channel; it is sufficient instead to use a combination of eigenbeamforming and a fixed (nonadaptive) rate allocation. The fixed allocation requires no water-filling; instead, it allocates the rates deterministically to match the channel statistics, independent of the particular channel realization. This paper proves that the capacity penalty incurred by the fixed allocation approaches zero as the number of antennas grows large. Furthermore, at high signal-to-noise ratio (SNR), we show that the convergence is fast and that the fixed allocation strategy performs well for even a moderate number of antennas. For example, the fixed allocation suffers a SNR penalty of less than 0.2 dB for a 6×6 Rayleigh-fading MIMO-OFDM channel at 8 bits per signaling interval, when the channel is assumed to be uncorrelated between antennas and between channel taps. A main conclusion is that eigenbeamforming is the most valuable way to exploit knowledge of the channel at the transmitter, and that any subsequent adaptive modulation has minimal relative value.
Mining Naturally-occurring Corrections and Paraphrases from Wikipedia’s Revision History

Naturally-occurring instances of linguistic phenomena are important both for training and for evaluating automatic text processing. When available in large quantities, they also prove interesting material for linguistic studies. In this article, we present WiCoPaCo (Wikipedia Correction and Paraphrase Corpus), a new freely-available resource built by automatically mining Wikipedias revision history. The WiCoPaCo corpus focuses on local modifications made by human revisors and include various types of corrections (such as spelling error or typographical corrections) and rewritings, which can be categorized broadly into meaning-preserving and meaning-altering revisions. We present an initial hand-built typology of these revisions, but the resource allows for any possible annotation scheme. We discuss the main motivations for building such a resource and describe the main technical details guiding its construction. We also present applications and data analysis on French and report initial results on spelling error correction and morphosyntactic rewriting. The WiCoPaCo corpus can be freely downloaded from http://wicopaco.limsi. fr.
The monopolistic competition revolution in retrospect

In this paper we argue that there have been two monopolistic competition revolutions. The first was started by Joan Robinson and Edward Chamberlin in the 1930s but failed to have much impact on economic theory. The second was initiated by Avinash Dixit and Joseph Stiglitz in the early 1970s. Their revolution succeeded because it yielded an analytically tractable model of Chamberlinian monopolistic competition (the ``large group'' case). This model has been used in such diverse fields as international trade theory, economic geography, economic growth theory, and macroeconomics. Its popularity shows no sign of decline.
Electro-hydraulic piston control using neural MRAC based on a modified state observer

A new model reference adaptive control design method using neural networks that improves both transient and steady stage performance is proposed in this paper. Stable tracking of a desired trajectory can be achieved for nonlinear systems having significant uncertainties. A modified state observer structure is designed to enable desired transient performance during uncertainty learning. The neural network adaptation rule is derived using Lyapunov theory, which guarantees stability of the error dynamics and boundedness of the neural network weights. An extra term is added in the controller expression to introduce a 'soft switching' sliding mode that can be used to adjust tracking errors. The method is applied to control the velocity of an electro-hydraulic piston, and experimental results demonstrate the desired performance is achieved with smooth control effort.
A semi-discrete high resolution scheme for nonlinear scalar conservation laws

The purpose of this paper is twofold. Firstly we carry out an extension of the fully discrete third order TVD scheme, for linear case, presented in [8] to nonlinear scalar hyperbolic conservation laws for one and two dimensions. Secondly, we propose a semi-discrete version of the scheme. Time evolution is carried out by the third order TVD Runge- Kutta method. The advantages of the scheme are its simplicity, third order, non-oscillatory and that can be used for large time steps which can save more time. Examples and convergence rates are presented for the Burger equation for one and two dimensions which confirm the high resolution content of the proposed schemes. We use exact solutions and other methods to validate the results.
Reinforcement learning in the robocup-soccer keepaway

Many researchers purpose reinforcement learning (RL) as a form of machine learning for robot learning. However, there are several issues that need to be considered when applying (RL) techniques to robot tasks. There are many different (RL) algorithms available such as Q-learning or Sarsa. These algorithms may produce different results. In complex domains with large states and action spaces is necessary to apply generalization techniques such as function approximation. Last, a right balance between exploration and exploitation is required. In this paper we review these issues in order to improve the learning process in the keepaway domain. We present some new combinations in the choice of the RL algorithm, the generalization method and the exploration-exploitation strategy.
Tight bounds for asynchronous randomized consensus

A distributed consensus algorithm allows n processes to reach a common decision value starting from individual inputs. Wait-free consensus, in which a process always terminates within a finite number of its own steps, is impossible in an asynchronous shared-memory system. However, consensus becomes solvable using randomization when a process only has to terminate with probability 1. Randomized consensus algorithms are typically evaluated by their total step complexity, which is the expected total number of steps taken by all processes. This article proves that the total step complexity of randomized consensus is Θ(n2) in an asynchronous shared memory system using multi-writer multi-reader registers. This result is achieved by improving both the lower and the upper bounds for this problem. In addition to improving upon the best previously known result by a factor of log2n, the lower bound features a greatly streamlined proof. Both goals are achieved through restricting attention to a set of layered executions and using an isoperimetric inequality for analyzing their behavior. The matching algorithm decreases the expected total step complexity by a log n factor, by leveraging the multi-writing capability of the shared registers. Its correctness proof is facilitated by viewing each execution of the algorithm as a stochastic process and applying Kolmogorov's inequality.
Data Source Selection for Large-Scale Deep Web Data Integration

Deep web has been an important resource on the web due to its rich and high quality information, leading to emerging a new application area in data mining and integrates. There may be hundreds or thousands of data sources providing data of relevance to a particular domain on the web, So a primary challenge to large-scale deep web data integration is to determine in what order to user integrate candidate data sources. In this paper, we develop a most-benefit approach (MBA) for ordering candidate data sources for user integration. At the core of this approach is a utility function that quantifies the utility of a given the state of integration system; thus, we devise a utility function for integration system based on query result number. We show in practice how to efficiently apply MBA in concert with this utility function to order data sources. A detailed experimental evaluation on real datasets shows that the ordering of data sources produced by this MBA-based yields a integration system with a significantly higher utility than a wide range of other ordering strategies.
Efficiency improvement in Doherty power amplifier by using Class F approach

In this contribution, the design of an uneven AB-C Doherty power amplifier (DPA) in GaN technology, implementing a Class F configuration for the Main device, is presented. Theoretical support will be given to understand why and how some relevant DPA's design parameters have to be carefully selected when a Class F strategy is adopted. Moreover, a comparison between the output performance obtained from a simple Tuned Load DPA and the here presented Class F DPA will be given. From the experimental results, the realised Class F DPA achieved, in an Output Back-off of 6dB, an average drain efficiency of 50% with a saturated output power of 3.2W at 2.14GHz.