Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance-driven register insertion in placement

As the CMOS technology is scaled into the dimension of nanometer, the clock frequencies and die sizes of ICs are shown to be increasing steadily [5]. Today, global wires that require multiple clock cycles to propagate electrical signal are prevalent in many deep sub-micron designs. Efforts have been made to pipe ine the long wires by introducing registers along these global paths, trying to reduce the impact of wire delay dominance [2, 8]. The technique of retiming to relocate registers in a circuit without affecting the circuit functionality can be applied in this problem. Though the problem of retiming with gate and wire delay has been studied recent y [17, 1], the placement of registers after retiming is a new challenge. In this paper, we study the problem of realizing a retiming solution on a global netlist by inserting registers in the placement to achieve the target clock period.In contrast to many previous works [16, 11] that performed simple calculations to determine the positions of the registers, our proposed algorithm can preserve the given clock period and utilize as few registers as possible in the realization. What is more, the algorithm is shown to be optimal for nets with 4 or fewer pins and this type of nets constitutes over 90% of the nets in a sequential circuit on average.Using the ISCAS89 benchmark suite, we tested our algorithm with a 0.35 μm CMOS standard cell library, and Silicon Ensemble was used to layout the design with row utilization of 50%. Experimenta results showed that our algorithm can find the best sharing of registers for a net in most of the cases, i.e., using the minimum number of registers while preserving the target clock period, within a minute running on an Intel Pentium IV 1.5GHz PC with 512MB RAM.
SocialTransfer: Transferring Social Knowledge for Cold-Start Cowdsourcing

An essential component of building a successful crowdsourcing market is effective task matching, which matches a given task to the right crowdworkers. In order to provide high- quality task matching, crowdsourcing systems rely on past task-solving activities of crowdworkers. However, the average number of past activities of crowdworkers in most crowd- sourcing systems is very small. We call the workers who have only solved a small number of tasks cold-start crowdworkers. We observe that most of the workers in crowdsourcing systems are cold-start crowdworkers, and crowdsourcing systems actually enjoy great benefits from cold-start crowd-workers. However, the problem of task matching with the presence of many cold-start crowdworkers has not been well studied. We propose a new approach to address this issue. Our main idea, motivated by the prevalence of online social networks, is to transfer the knowledge about crowdworkers in their social networks to crowdsourcing systems for task matching. We propose a SocialTransfer model for cold-start crowdsourcing, which not only infers the expertise of warm- start crowdworkers from their past activities, but also transfers the expertise knowledge to cold-start crowdworkers via social connections. We evaluate the SocialTransfer model on the well-known crowdsourcing system Quora, using knowledge from the popular social network Twitter. Experimental results show that, by transferring social knowledge, our method achieves significant improvements over the state-of-the-art methods.
Optimizing the MEAM potential for silicon

By applying simulated annealing techniques we fit the modified embedded atom method (MEAM) potential to a database of ab initio energies for silicon and construct an improved parametrization of this potential. In addition, we introduce a new, reference-free version of the MEAM potential. This MEAM version is also fitted to the silicon data and shows an even better agreement, although the improvement is modest. Finally, we investigate whether increasing the number of different angular terms in the MEAM potential from 3 to 4 will lead to a better potential. The aim of this work is to determine a broad-ranged potential, one that is reliable in many different low- and high-energy atomic geometries in silicon crystals, molecules, near defects and under strain. To verify this, the performance of the new potentials is tested in different circumstances that were not explicitly included in the fit: relaxed defect energies, thermal expansion, melting temperature and liquid silicon. The new MEAM parametrizations found in this work, called MEAM-M and RF-MEAM, are shown to be overall more accurate than previous potentials—although a few defect energies are exceptions—and we recommend them for future work. The melting temperatures are closer to the experiment than those of other MEAM potentials, but they are still too high.
Differential Topic Models

In applications we may want to compare different document collections: they could have shared content but also different and unique aspects in particular collections. This task has been called comparative text mining or cross-collection modeling. We present a differential topic model for this application that models both topic differences and similarities. For this we use hierarchical Bayesian nonparametric models. Moreover, we found it was important to properly model power-law phenomena in topic-word distributions and thus we used the full Pitman-Yor process rather than just a Dirichlet process. Furthermore, we propose the transformed Pitman-Yor process (TPYP) to incorporate prior knowledge such as vocabulary variations in different collections into the model. To deal with the non-conjugate issue between model prior and likelihood in the TPYP, we thus propose an efficient sampling algorithm using a data augmentation technique based on the multinomial theorem. Experimental results show the model discovers interesting aspects of different collections. We also show the proposed MCMC based algorithm achieves a dramatically reduced test perplexity compared to some existing topic models. Finally, we show our model outperforms the state-of-the-art for document classification/ideology prediction on a number of text collections.
Poor air quality in classrooms related to asthma and rhinitis in primary schoolchildren of the French 6 Cities Study

Background Relationships between indoor air quality (IAQ) found in schools and the allergic and respiratory health of schoolchildren have been insufficiently explored. A survey was conducted in a large sample of classrooms of primary schools in France to provide objective assessments of IAQ to which young schoolchildren are exposed in classrooms, and to relate exposure to major air pollutants found in classrooms to asthma and allergies of schoolchildren. Methods Concentrations of fine particles with aerodynamic diameter ≤2.5 μm (PM2.5), nitrogen dioxide (NO2) and three aldehydes were objectively assessed in 401 randomly chosen classrooms in 108 primary schools attended by 6590 children (mean age 10.4 years, SD ±0.7) in the French 6 Cities Study. The survey incorporated a medical visit including skin prick testing (SPT) for common allergens, a test for screening exercise-induced asthma (EIA) and a standardised health questionnaire completed by parents. Results Children were differently exposed to poor air quality in classrooms, with almost 30% being highly exposed according to available standards. After adjusting for confounders, past year rhinoconjunctivitis was significantly associated with high levels of formaldehyde in classrooms (OR 1.19; 95% CI 1.04 to 1.36). Additionally, an increased prevalence of past year asthma was found in the classrooms with high levels of PM2.5 (OR 1.21; 95% CI 1.05 to 1.39), acrolein (OR 1.22; 95% CI 1.09 to 1.38) and NO2 (OR 1.16; 95% CI 0.95 to 1.41) compared with others. The relationship was observed mostly for allergic asthma as defined using SPT. A significant positive correlation was found between EIA and the levels of PM2.5 and acrolein in the same week. Conclusions In this random sample, air quality in classrooms was poor, varied significantly among schools and cities, and was related to an increased prevalence of clinical manifestations of asthma and rhinitis in schoolchildren. Children with a background of allergies seemed at increased risk.
Trans-Golgi Network Localized ECHIDNA/Ypt Interacting Protein Complex Is Required for the Secretion of Cell Wall Polysaccharides in Arabidopsis[C][W][OPEN]

The evolutionarily conserved ECHIDNA (ECH) and Ypt Interacting Protein4 (YIP4) proteins form a complex that localizes to the trans-Golgi network (TGN). The ECH-YIP4 complex is required for TGN function and plays a crucial role in the secretion of cell wall polysaccharides in plant cells. The secretion of cell wall polysaccharides through the trans-Golgi network (TGN) is required for plant cell elongation. However, the components mediating the post-Golgi secretion of pectin and hemicellulose, the two major cell wall polysaccharides, are largely unknown. We identified evolutionarily conserved YPT/RAB GTPase Interacting Protein 4a (YIP4a) and YIP4b (formerly YIP2), which form a TGN-localized complex with ECHIDNA (ECH) in Arabidopsis thaliana. The localization of YIP4 and ECH proteins at the TGN is interdependent and influences the localization of VHA-a1 and SYP61, which are key components of the TGN. YIP4a and YIP4b act redundantly, and the yip4a yip4b double mutants have a cell elongation defect. Genetic, biochemical, and cell biological analyses demonstrate that the ECH/YIP4 complex plays a key role in TGN-mediated secretion of pectin and hemicellulose to the cell wall in dark-grown hypocotyls and in secretory cells of the seed coat. In keeping with these observations, Fourier transform infrared microspectroscopy analysis revealed that the ech and yip4a yip4b mutants exhibit changes in their cell wall composition. Overall, our results reveal a TGN subdomain defined by ECH/YIP4 that is required for the secretion of pectin and hemicellulose and distinguishes the role of the TGN in secretion from its roles in endocytic and vacuolar trafficking.
2007 Ieee International Conference on Granular Space Structure on a Micrometric Scale for Industrial Robots

We study the statistical relationship between angular position and target for industrial robots on a micrometric scale and this leads us to understand the angular position stochastic structure. The concept of granular angular space is introduced and transposed in the Cartesian space. Modeling is based on experimental work performed for a Kuka and a Samsung robot. The influence of workspace location, posture and angular granularity ratio on the Cartesian granular space are then analysed.
Web Services based Framework for Knowledge Management in Peer-to-Peer Environment

The problem of Knowledge Management (KM) is eminent in the P2P area. This paper presents a general framework of knowledge management based on web services in peer-to-peer (P2P) environment. P2P knowledge management yields significant advantages when combined and applied as web services for KM. By adopting web services techniques and distributed approaches, we partition the knowledge network into numerous knowledge communities self-adaptively, and provide a mechanism for knowledge management in these knowledge communities with our framework. Our framework implements the integration of KM functions and autonomy of knowledge peers in knowledge network, and at the same time, the cost of building and maintaining KM systems is reduced.
At the horizon of a supersymmetric AdS(5) black hole: Isometries and half-BPS giants

The near-horizon geometry of an asymptotically AdS5 supersymmetric black hole discovered by Gutowski and Reall is analysed. After lifting the solution to 10 dimensions, we explicitly solve the Killing spinor equations in both AdS2 Poincare and global coordinates. It is found that exactly four supersymmetries are preserved which is twice the number for the full black hole. The full set of isometries is constructed and the isometry supergroup is shown to be SU(1,1|1) × SU(2) × U(3). We further study half-BPS configurations of D3-branes in the near-horizon geometry in Poincare and global coordinates. Both giant graviton probes and dual giant graviton probes are found.
Anatomic Surface Reconstruction from Sampled Point Cloud Data and Prior Models

In this paper, we propose an approach for reconstruction of an anatomic surface model from point cloud data using the Screened Poisson Surface Reconstruction algorithm, which requires a collection of points and their normal vectors. Various algorithms exist for estimating normal vectors for point cloud data; however, in this work we describe a novel approach to estimating the normal vectors from a high-resolution prior model. In many medical applications, a preoperative high-resolution scan is acquired for diagnostic and planning purposes, whereas intraoperative, lower fidelity imaging is utilized during the procedure. This approach assumes an already existing registration between intra-operatively acquired data and the preoperative model. We conducted simulation experiments to evaluate the effect of registration error, point sampling rate, and noise levels on the acquired point cloud data samples. In addition, we evaluated the effect of using both the closest point, as well as a neighborhood of closest points on the prior model for estimating the normal. Our results showed that surface reconstruction error increases with higher registration error; however, acceptable performance was achieved with clinically-acceptable registration error. In addition, the best reconstruction was obtained when estimating the normal using only the closest point on the prior model, as opposed to utilizing a neighborhood of points. When combining the effect of all factors (Gaussian sampling noise of zero mean and σ=1.8mm; Gaussian translational error of zero mean and σ=2.0mm; and Gaussian rotational error of zero mean and σ=3°) the overall RMS reconstruction error was 0.88±0.03mm.
Recombination Does Not Hinder Formation or Detection of Ecological Species of Synechococcus Inhabiting a Hot Spring Cyanobacterial Mat

Recent studies of bacterial speciation have claimed to support the biological species concept—that reduced recombination is required for bacterial populations to diverge into species. This conclusion has been reached from the discovery that ecologically distinct clades show lower rates of recombination than that which occurs among closest relatives. However, these previous studies did not attempt to determine whether the more-rapidly recombining close relatives within the clades studied may also have diversified ecologically, without benefit of sexual isolation. Here we have measured the impact of recombination on ecological diversification within and between two ecologically distinct clades (A and B') of Synechococcus in a hot spring microbial mat in Yellowstone National Park, using a cultivation-free, multi-locus approach. Bacterial artificial chromosome (BAC) libraries were constructed from mat samples collected at 60°C and 65°C. Analysis of multiple linked loci near Synechococcus 16S rRNA genes showed little evidence of recombination between the A and B' lineages, but a record of recombination was apparent within each lineage. Recombination and mutation rates within each lineage were of similar magnitude, but recombination had a somewhat greater impact on sequence diversity than mutation, as also seen in many other bacteria and archaea. Despite recombination within the A and B' lineages, there was evidence of ecological diversification within each lineage. The algorithm Ecotype Simulation identified sequence clusters consistent with ecologically distinct populations (ecotypes), and several hypothesized ecotypes were distinct in their habitat associations and in their adaptations to different microenvironments. We conclude that sexual isolation is more likely to follow ecological divergence than to precede it. Thus, an ecology-based model of speciation appears more appropriate than the biological species concept for bacterial and archaeal diversification.
Possibilistic rings detection for RICH pattern recognition

Leonard Studer Francesco Masulli IPHE Institut de Physique DISI Dipartimento di Informatica des Hautes Energies e Scienze del171nformazione Universitk de Lausanne Universiti degli Studi di Genova BSP, 10 1 5 Lausanne Via Dodecaneso, 35 Switzerland 1-16146 Genova, Italy Leonard. Studer@iphe.unil. ch INFM Istituto Nazionale per la Fisica della Materia Via Dodecaneso, 33 116 146 Genova, Italy masulli@disi.unige. it In this paper we present some results obtained using an algorithm whose core is the Possibilistic C-Spherical Shell algorithm, to detect complex images full of rings without any preliminary knowledge of number and position of the rings. This algorithm depends on the choice of several critical parameters. The statistical study described in this paper lead to high success rates even for large number of rings.
On social learning and robust evolutionary algorithm design in economic games

Agent-based computational economics (ACE) combines elements from economics and computer science. In this paper, the authors focused on the relation between the evolutionary technique that is used and the economic problem that is modeled. In the field of ACE, economic simulations often derive parameter settings for the genetic algorithm directly from the values of the economic model parameters. In this paper, two important approaches that are dominating in ACE were compared and showed that the above practice may hinder the performance of the GA and thereby hinder agent learning. More specifically, it is shown that economic model parameters and evolutionary algorithm parameters should be treated separately by comparing the two widely used approaches to social learning with respect to their convergence properties and robustness. This leads to new considerations for the methodological aspects of evolutionary algorithm design within the field of ACE. Improved social (ACE) simulation results were also presented for the Cournot oligopoly game, yielding (higher profit) Cournot-Nash equilibria instead of the competitive equilibria.
RNAi nanomedicines: challenges and opportunities within the immune system

RNAi, as a novel therapeutic modality, has an enormous potential to bring the era of personalized medicine one step further from notion into reality. However, delivery of RNAi effector molecules into their target tissues and cells remain extremely challenging. Major attempts have been made in recent years to develop sophisticated nanocarriers that could overcome these hurdles. This review will present the recent progress with the challenges and opportunities in this emerging field, focusing mostly on the in vivo applications with special emphasis on the strategies for RNAi delivery into immune cells.
Predictors of motor, daily function, and quality-of-life improvements after upper-extremity robot-assisted rehabilitation in stroke.

OBJECTIVE A subgroup of patients benefiting most from robot-assisted therapy (RT) has not yet been described. We examined the predictors of improved outcomes after RT. METHOD Sixty-six patients with stroke receiving RT were analyzed. The outcome measures were the Fugl-Meyer Assessment (FMA), Wolf Motor Function Test (WMFT), Motor Activity Log (MAL), and Stroke Impact Scale (SIS). The potential predictors were age, side of lesion, time since onset, Modified Ashworth Scale (MAS) scores, accelerometer data, Box and Block Test (BBT) scores, and kinematic parameters. RESULTS BBT scores were predictive of FMA (29%) and MAL (9%-15%) improvements. Reduced shoulder flexion synergy, as measured by less shoulder abduction during forward reach, and MAS-distal were predictive of WMFT-function improvements. MAS-distal was predictive of SIS-physical improvements. Demographic variables did not predict outcomes. CONCLUSION Manual dexterity was a valuable predictor of motor impairment and daily function after RT. Outcomes at different levels may have different predictors.
Supporting wireless application development via virtual execution

We introduce our ldquoholisticrdquo platform for building wireless ad hoc sensor networks and focus on its most representative and essential virtualization component: VUE2 (the Virtual Underlay Emulation Engine). Its role is to provide a vehicle for authoritative emulation of complete networked applications before physically deploying the wireless nodes. The goal is to be able to verify those applications exhaustively before programming the hardware, such that no further (field) tests are necessary. We explain how VUE2 achieves this goal owing to several facilitating factors, most notably the powerful programming paradigm adopted in our platform. As implied by the holistic nature of the discussed system, our presentation touches upon operating systems, simulation, network protocols, real-time systems, and programming methodology.
Preparation of MPS (mercaptopropyltrimethoxysilane)-coated SiO2 nanoparticle and its effect on mechanical properties of surface treated SiO2/EVA nanocomposite

SiO2 nanoparticles were synthesized from different three precursors, namely, TEOS (tetraethyl orthosilicate), sodium metasilicate and sodium silicate. First, SiO2 nanoparticles were prepared by a controlled hydrolysis of TEOS. In another method, SiO2nanoparticles were prepared by precipitation in an emulsion medium from sodium metasilicate and hydrochloric acid solution. Finally, SiO2 nanoparticles were also synthesized from sodium silicate by an emulsion method. In this study, we concentrated on dispersion and compatibility between nanosized SiO2 particles and EVA (ethylene vinyl acetate). Therefore, surface modification of synthesized SiO2 nanoparticles was accomplished with MPS (3-mercaptopropyl trimethoxysilane) to enhance homogeneous dispersion and compatibility between the obtained SiO2 nanoparticles and EVA. Finally, nanocomposites of surface treated SiO2 nanoparticles and EVA were prepared. By inserting the MPS-coated SiO2 nanoparticles into EVA, abrasion resistance and hardness were increased remarkably. On the other hand, insertion of SiO2 nanoparticles barely decreased original tensile strength and elongation of EVA. Consequently, MPS-coated SiO2/EVA nanocomposite can have an improved abrasion resistance and hardness compared with raw EVA, without decrease tensile strength and elongation. The characterization of synthesized SiO2 nanoparticles and their nanocomposite with EVA was conducted by TEM, SEM, FTIR photography and mechanical property tests such as abrasion, hardness, tensile strength and elongation.
Faster Compact Top-k Document Retrieval

An optimal index solving top-k document retrieval [Navarro and Nekrich, SODA'12] takes O(m+k) time for a pattern of length m, but its space is at least 80n bytes for a collection of n symbols. We reduce it to 1.5n-3n bytes, with O(m + (k+log log n)log log n) time, on typical texts. The index is up to 25 times faster than the best previous compressed solutions, and requires at most 5% more space in practice (and in some cases as little as one half). Apart from replacing classical by compressed data structures, our main idea is to replace suffix tree sampling by frequency thresholding to achieve compression.
Learning experience is important for the attitude of using statistical software

The purpose of this study is to test the effect of learning experience on attitude of using statistical software. Under a context of natural experimental setting, there are experimental and control groups. The experimental group is learning to use the statistical software in a course of software application. The control group is learning to apply the statistical software for analyzing data in a course of research method. The participants are 63 university students, 42 in experimental group and 21 in control group. The results show that learning experience has effect on attitude of using statistical software. It is concluded that learning experience is important for the attitude of statistical software usage.