Miracle-dz/UniFAR-FTUs huggingface dataset:
Crowdedness-balanced multilevel partitioning for uniform resource utilization

In this paper, we propose a new multi-objective multilevel K-way partitioning which is aware of resource utilization distribution, assuming the resource utilization for a partitioned block is proportional to the logic occupation and the interconnections required for the block. A new quality of the partitioning solution, crowdedness, is defined as a virtual complexity metric where the physical size and the local connectivity of a partitioned block are considered simultaneously in the form of a weighted sum. The partitioning solutions driven by overall cut quality minimization tend to have wide variances of local interconnections for different blocks. The difference of block sizes, combining with the variance of the interconnections, potentially leads to the significant imbalance of the crowdedness (equivalently. resource utilization), even though the feasibility imposed by a block-size constraint is satisfied. Using the crowdedness metric, we explore the new partitioning solution space where the local interconnections are adaptively adjusted according to the block sizes, still under the same objective of overall interconnections minimization. By the carefully designed prioritized cell move policy, the proposed crowdedness-based partitioning achieves near-optimal solutions in terms of resource utilization distribution, while the overall interconnection quality also is improved but the feasibility is barely violated. The proposed approach is practically beneficial to multi-FPGA applications, in which excessive interconnections for a FPGA generate additional logics inside of the FPGA.
Information Modeling Based on a Meaningful Use of Language

In traditional modelling approaches, such as entity-relationship modelling, the predominant information modelling problem is how to represent external reality in the system in a ‘true’ way. In these approaches semantic aspects of language are in focus. In contrast to this, the main information modelling problem could be to understand how information systems may support a meaningful use of language and information in a social action context. The paper presents an information modelling approach based on speech act theory that takes both semantic and pragmatic aspects into consideration. With such an approach it is possible to reconcile traditional information modelling and the pragmatic aspects of language and information use. Such reconciliation is essential to arrive at information systems that support meaningful communication between different actors within a social action context.
Lateral Transfer of Genes and Gene Fragments in Prokaryotes

Lateral genetic transfer (LGT) involves the movement of genetic material from one lineage into another and its subsequent incorporation into the new host genome via genetic recombination. Studies in individual taxa have indicated lateral origins for stretches of DNA of greatly varying length, from a few nucleotides to chromosome size. Here we analyze 1,462 sets of single-copy, putatively orthologous genes from 144 fully sequenced prokaryote genomes, asking to what extent complete genes and fragments of genes have been transferred and recombined in LGT. Using a rigorous phylogenetic approach, we find evidence for LGT in at least 476 (32.6%) of these 1,462 gene sets: 286 (19.6%) clearly show one or more “observable recombination breakpoints” within the boundaries of the open reading frame, while a further 190 (13.0%) yield trees that are topologically incongruent with the reference tree but do not contain a recombination breakpoint within the open reading frame. We refer to these gene sets as observable recombination breakpoint positive (ORB+) and negative (ORB−) respectively. The latter are prima facie instances of lateral transfer of an entire gene or beyond. We observe little functional bias between ORB+ and ORB− gene sets, but find that incorporation of entire genes is potentially more frequent in pathogens than in nonpathogens. As ORB+ gene sets are about 50% more common than ORB− sets in our data, the transfer of gene fragments has been relatively frequent, and the frequency of LGT may have been systematically underestimated in phylogenetic studies.
Type IIB Random Superstrings

We consider random superstrings of type IIB in $d$-dimensional space. The discretized action is constructed from the supersymetric matrix model, which has been proposed as a constructive definition of superstring theory. Our action is invariant under the local N=2 super transformations, and doesn't have any redundant fermionic degrees of freedom.
Interactive global illumination based on coherent surface shadow maps

Interactive rendering of global illumination effects is a challenging problem. While precomputed radiance transfer (PRT) is able to render such effects in real time the geometry is generally assumed static. This work proposes to replace the precomputed lighting response used in PRT by precomputed depth. Precomputing depth has the same cost as precomputing visibility, but allows visibility tests for moving objects at runtime using simple shadow mapping. For this purpose, a compression scheme for a high number of coherent surface shadow maps (CSSMs) covering the entire scene surface is developed. CSSMs allow visibility tests between all surface points against all points in the scene. We demonstrate the effectiveness of CSSM-based visibility using a novel combination of the lightcuts algorithm and hierarchical radiosity, which can be efficiently implemented on the GPU. We demonstrate interactive n-bounce diffuse global illumination, with a final glossy bounce and many high frequency effects: general BRDFs, texture and normal maps, and local or distant lighting of arbitrary shape and distribution -- all evaluated per-pixel. Furthermore, all parameters can vary freely over time -- the only requirement is rigid geometry.
Performance Comparison of Speaker Recognition using Vector Quantization by LBG and KFCG

In this paper, two approaches for speaker Recognition based on Vector quantization are proposed and their performances are compared. Vector Quantization (VQ) is used for feature extraction in both the training and testing phases. Two methods for codebook generation have been used. In the 1 st method, codebooks are generated from the speech samples by using the Linde-Buzo-Gray (LBG) algorithm. In the 2 nd method, the codebooks are generated using the Kekre‟s Fast Codebook Generation (KFCG) algorithm. For speaker identification, the codebook of the test sample is similarly generated and compared with the codebooks of the reference samples stored in the database. The results obtained for both the methods have been compared. The results show that KFCG gives better results than LBG.
The performance of three database storage structures for managing large objects

This study analyzes the performance of the storage structures and algorithms employed in three experimental database storage systems – EXODUS, Starburst, and EOS – for managing large unstructured general-purpose objects. All three mechanisms are segment-based in that the large object is stored in a sequence of segments, each consisting of physically continuous disk block. To analyze the algorithms we measured object creation time, sequential scan time, storage utilization in the presence of updates, and the I/O cost of random reads, inserts, and deletes.
The Degrowth Spectrum: Convergence and Divergence within a Diverse and Conflictual Alliance

The call for ‘sustainable degrowth’ has recently turned into a focal point of critical social and ecological debate, as well as a framework for diverse strands of activism. So far, little is known about the motives, attitudes and practices of grassroots activists within the degrowth spectrum. This article presents results of a survey conducted at the 2014 International Degrowth Conference, revealing both the presence of a widely shared basic consensus among respondents and their broad division into five distinguishable sub-currents. A cluster analysis shows that degrowth provides a framework for a diversity of critical and transformational approaches. We identify and describe five such currents: eco-radical sufficiency-oriented critics of civilisation; moderate immanent reformers; a transitory group of voluntarist-pacifist idealists; the modernist rationalist Left; and the alternative practical Left.
Sound signal processing for a virtual room

This paper presents the audio system built for the virtual room at Helsinki University of Technology. First we discuss the general problems for multichannel sound reproduction caused by the construction of, and the equipment in virtual rooms. We also describe the acoustics of the room in question, and the effect of the back-projected screens and reverberation to the sound. Compensation of the spectral deficiencies and the problems with the large listening area and high frequency attenuation are introduced. The hardware configuration used for sound reproduction is shortly described. We also report the software applications and libraries built for sound signal processing and 3-D sound reproduction.
Evolved transforms for improved image compression and reconstruction under quantization

Previously reported research efforts demonstrated that a genetic algorithm can evolve coefficients describing transforms that outperform standard wavelets, by reducing the mean squared error (MSE) apparent in reconstructed signals under conditions subject to quantization. This paper describes new results that substantially improve the state-of-the-art in evolved transform performance. Matched forward and inverse transform pairs trained against selected images consistently reduce MSE by more than 22% (1.126 dB) when applied to an arbitrary population of similarly quantized test images, yet still achieve the same amount of compression.
A multilevel adaptive projection method for unsteady incompressible flow

There are two main requirements for practical simulation of unsteady flow at high Reynolds number: the algorithm must accurately propagate discontinuous flow fields without excessive artificial viscosity, and it must have some adaptive capability to concentrate computational effort where it is most needed. We satisfy the first of these requirements with a second-order Godunov method similar to those used for high-speed flows with shocks, and the second with a grid-based refinement scheme which avoids some of the drawbacks associated with unstructured meshes. These two features of our algorithm place certain constraints on the projection method used to enforce incompressibility. Velocities are cell-based, leading to a Laplacian stencil for the projection which decouples adjacent grid points. We discuss features of the multigrid and multilevel iteration schemes required for solution of the resulting decoupled problem. Variable-density flows require use of a modified projection operator--we have found a multigrid method for this modified projection that successfully handles density jumps of thousands to one. Numerical results are shown for the 2D adaptive and 3D variable-density algorithms.
Detecting Communities over Large Scale Graph Structure Data using MapReduce

With the appearances of the internet there is growing interest in executing analysis tasks over large scale graph structure data. This task includes processing of subgraph or multi-hop neighborhoods in graph. Examples of these graphs include identifying social circles, modified recommendation, Anomaly finding, link prediction and so on. These works are not well served by the vertex centric approach and by using this approach there is a problem of high communication, scheduling and memory expenses. There is an NSCALE approach that is a novel end-to-end graph processing approach for distributed execution of complex subgraph analytics over the large scale graph in the cloud. The phase GEL, graph extraction and loading of the NSCALE approach extracts only the appropriate portions of the graph to minimize the communication cost.
Cholesterol and Triglycerides May Reached the Undesirable Level in Gestational Diabetes Mellitus

4 Abstract: Lipid profile including cholesterol, triglycerides, High Density Lipoprotein-cholesterol (HDL-C) and Low Density Lipoprotein-cholesterol (LDL-C) level was determined in patients with Gestational Diabetes Mellitus (GDM) and compared to Healthy Pregnant Women (HPW). 103 GDM women and 97 HPW were registered in the Khyber Teaching Hospital, Peshawar in the time period of May to December 2012. Total cholesterol, triglycerides, HDL-C and LDL-C was determined by standard kit procedures. Mean Total Cholesterol (TC) and mean Triglyceride (TG) were significantly higher at P<0.05 in GDM group as compared to HPW group. The mean value of total cholesterol in GDM group was 205.81±19.09 mg/dL while in HPW (control group) it was 194.86±23.70 mg/dL. The mean TG level of GDM women was 189.62±20.01 mg/dL while of HPW was 169±22.26 mg/dL. The mean HDL cholesterol (HDL-C) and the mean LDL cholesterol (LDL-C) of GDM women were non significantly higher than HPW. The percentage of GDM in undesirable level of cholesterol (P = 0.03) and triglycerides (P = 0.003) was significantly higher as compared to HPW, however the percentage of GDM in undesirable level of HDL-C and LDL-C was non significantly different from HPW.
Multi-Class Tweet Categorization Using Map Reduce Paradigm

Twitter is one of the most popular micro- blogging website in today's globalized world. Twitter messages can be mined to gain valuable information. Although Twitter provides a list of most popular topics people tweet about known as Trending Topics in real time, it is often hard to understand what these trending topics are about. Therefore, various efforts are being made to classify these topics into general categories with high accuracy for better information retrieval. We propose the use of one of the classification algorithm called Naive Bayes for the categorization of tweets which has been discussed in this paper. It then proposes how the Map - Reduce paradigm can be applied to existing Naive Bayes algorithm to handle large number of tweets.
Deciding between the Common and Private Values Paradigm: An Application to Experimental Data

In the application of auction theory to the real world, practitioners must choose ex ante which of the common value or the private values paradigm applies. Since intuition may fail, some authors have proposed to decide statistically between the two models. These studies, however, did not confirm whether the tests validated the true model since field data were used. I propose to use experimental data as well as Monte-Carlo simulations to study different nonstructural rules to decide between the two paradigms. I find that regressions are inconclusive whereas a nonparametric procedure seems to be powerful and robust. Copyright Economics Department of the University of Pennsylvania and the Osaka University Institute of Social and Economic Research Association
Very low-mass white dwarfs with a C-O core

Context. The lower limit for the mass of white dwarfs (WDs) with a C−O core is commonly assumed to be roughly 0.5 M� . As a consequence, WDs of lower masses are usually identified as He-core remnants. Aims. When the initial mass of the progenitor star is between 1.8 and 3 M� , which corresponds to the so-called red giant (RGB) phase transition, the mass of the H-exhausted core at the tip of the RGB is 0.3 < MH/M� < 0.5. Prompted by this well known result of stellar evolution theory, we investigate the possibility to form C−O WDs with mass M < 0.5 M� . Methods. The pre-WD evolution of stars was computed with initial mass of about 2.3 M� , undergoing anomalous mass-loss episodes during the RGB phase and leading to the formation of WDs with He-rich or CO-rich cores. The cooling sequences of the resulting WDs are also described. Results. We show that the minimum mass for a C−O WD is about 0.33 M� , so that both He and C−O core WDs can exist in the mass range 0.33−0.5 M� . The models computed for the present paper provide the theoretical tools for indentifying the observational counterpart of very low-mass remnants with a C−O core among those commonly ascribed to the He-core WD population in the progressively growing sample of observed WDs of low mass. Moreover, we show that the central He-burning phase of the stripped
Impact of Recommender System on Competition Between Personalizing and Non-Personalizing Firms

Abstract How do recommender systems affect prices and profits of firms under competition? To explore this question, we model the strategic behavior of customers who make repeated purchases at two competing firms: one that provides personalized recommendations and another that does not. When a customer intends to purchase a product, she obtains recommendations from the personalizing firm and uses this recommendation to eventually purchase from one of the firms. The personalizing firm profiles the customer (based on past purchases) to recommend products. Hence, if a customer purchases less frequently from the personalizing firm, the recommendations made to her become less relevant. While considering the impact on the quality of recommendations received, a customer must balance two opposing forces: (1) the lower price charged by the non-personalizing firm, and (2) an additional fit cost incurred when purchasing from the non-personalizing firm and the increased cost due to recommendations of reduced quality in the future. An outcome of the analysis is that the customers should distribute their purchases across both firms to maximize surplus over a planning horizon. Anticipating this response, the firms simultaneously choose prices. We study the sensitivity of the equilibrium prices and profits of the firms with respect to the effectiveness of the recommender system and the profile deterioration rate. We also analyze some interesting variants of the base model in order to study how its key results could be influenced. One of the key takeaways of this research is that the recommender system can influence the price and profit of not only the personalizing firm but also the non-personalizing firm.
Aggressive congestion control mechanism for space systems

The concept of a space system of systems (SoS) is becoming a key consideration in space communication, navigation, and Earth observation. The space SoS is defined as a network of assets on the Earth, in orbit around the Earth, in orbit around solar system bodies and on the surface of solar system bodies that is interconnected and/or interoperated to perform a mission, and/or provide services that cannot be performed by monolithic space systems alone. However, current space information systems are basically operated in a point-to-point pattern between the control center and the spacecrafts, which are only adequate for the individual space missions rather than collaborative missions. In other words, the ground network, space network, and the deep-space network evolve independently and focus on their individual communication regimes. To address these issues, the National Aeronautics and Space Administration (NASA) has developed an integrated space system that integrates the Internet protocols, routers, and interfaces into space networks [3], [4]. The space system, which is also called space Internet, enables large quantities of collaborative operations of those networks. Therefore, the integrated space Internet is essentially an SoS.
The perils and merits (or the Good, the Bad and the Ugly) of DNA barcoding of sponges - a controversial discussion

DNA barcodes are defined as signature sequences used to identify unknown specimens. They have been proposed as a means to quickly solve the taxonomical impediment, through an organised and highly structured effort, using the same part of the mitochondrial sub-unit I of the Cytochrome c oxidase gene to identify all species of the planet. There has been much debate about the uses and misuses of DNA for taxonomy, and the radical proposition of DNA barcodes has heated the debate. In this paper we present two contrasting views of how DNA barcodes may or may not help sponge taxonomy.
Preprint 1 UPPER EXPECTATION PARAMETRIC REGRESSION

In regression analysis, some predictors might be unobservable, not observed, or ignored. These factors actually affect the response randomly. The observed data thus follows a conditional distribution when these factors are given. This phenomenon is called the distribution randomness. For such a working model, we propose an upper expectation regression and a two-step penalized maximum least squares procedure to estimate parameters in the mean function and the upper expectation of the error. The resulting estimators are consistent and asymptotically normal under certain conditions. Simulation studies and a data example are used to show that the classical least squares estimation fails but the proposed estimation performs well.
SPIN90 Phosphorylation Modulates Spine Structure and Synaptic Function

The correct rearrangement of postsynaptic components in dendritic spines is important for driving changes of spine structure and synaptic function. SPIN90 plays an essential role in many cellular processes including actin polymerization, endocytosis, growth cone formation and dendritic spine morphogenesis. Here, we demonstrate that SPIN90, which is a binding partner of PSD95 and Shank in spines, is targeted to synapses and leads to enhanced synaptic activity in neurons. We show, using in vitro and in vivo kinase assays, that SPIN90 is tyrosine phosphorylated by Src kinase. SPIN90 that was tyrosine-phosphorylated by Src was targeted to dendritic spines in cultured hippocampal neurons. Moreover, a SPIN90 phospho-deficient mutant was unable to accumulate at dendritic spines whereas SPIN90 WT and a phospho-mimicking mutant were localized at spines and bound PSD95 and Shank with increased efficiency. Consistent with these findings, hippocampal neurons that overexpressed SPIN90 WT or a phospho-mimicking mutant had enlarged spine heads, leading to enhanced postsynaptic function in terms of both amplitude and frequency. Together, our findings show that SPIN90 modulates synaptic activity in neurons as a result of its phosphorylation.
A power scalable 6-bit 1.2GS/s flash ADC with power on/off Track-and-Hold and preamplifier

A power scalable 6-bit 1.2 GS/s flash Analog-to-Digital Converter (ADC) is designed in 90 nm CMOS. Rapid power on/off Track-and-Hold (T/H) and preamplifiers are proposed to provide scalable power consumption with sampling rate variation. Full transistor-level simulations of the ADC are presented from 1 MS/s (3 mW) to 1.2 GS/s (41 mW). At the maximum sampling rate the DNL is -0.9/+0.7 LSB and the INL is -0.8/+0.6 LSB. The ADC achieves 33 dB SNDR, 44 dB SFDR, and 0.9 pj/conversion-step at Nyquist from 1.2V power supply.