Miracle-dz/UniFAR-FTUs huggingface dataset:
A high performance and low energy hardware for intra prediction with Template Matching

H.264 intra prediction algorithm is not well suited for processing complex textures at low bit rates. Therefore, intra prediction with Template Matching (TM) is proposed for improving H.264 intra prediction. However, intra prediction with TM has high computational complexity. Therefore, in this paper, we propose a novel technique for reducing the amount of computations performed by intra prediction with TM, and therefore reducing the energy consumption of intra prediction with TM hardware. The proposed technique does not change the PSNR for some video frames, but it decreases the PSNR slightly for some video frames. We also designed and implemented a high performance 4×4 intra prediction with TM hardware including the proposed technique using Verilog HDL, and mapped it to a Xilinx Virtex 6 FPGA. The FPGA implementation is capable of processing 53 HD (1280×720) frames per second, and the proposed technique reduced its energy consumption up to 50%.
Improving Write Performance and Extending Endurance of Object-Based NAND Flash Devices

Write amplification is a major cause of performance and endurance degradations in NAND flash-based storage systems. In an object-based NAND flash device (ONFD), two causes of write amplification are onode partial update and cascading update. Here, onode is a type of small-sized object metadata, and multiple onodes are stored in one NAND flash page. Updating one onode invokes partial page update (i.e., onode partial update), incurring unnecessary migration of the un-updated data. Cascading update denotes updating object metadata in a cascading manner due to object data update or migration. Although there are only several bytes that need to be updated in the object metadata, one or more pages have to be re-written accordingly. In this work, we propose a system design to alleviate the write amplification issue in the object-based NAND flash device. The proposed design includes (1) a multi-level garbage collection technique to minimize unnecessary data migration incurred by onode partial update and (2) a B+ table tree, Semantics-Aware Flexible (SAF) data layout, and selective cache design to reduce the write operations associated with cascading update. To guarantee system consistency, we also propose a power failure handling technique. Experiment results show that our proposed design can achieve up to 20% write reduction compared to the best states of the art.
Pattern Recognition from One Example by Chopping

We investigate the learning of the appearance of an object from a single image of it. Instead of using a large number of pictures of the object to recognize, we use a labeled reference database of pictures of other objects to learn invariance to noise and variations in pose and illumination. This acquired knowledge is then used to predict if two pictures of new objects, which do not appear on the training pictures, actually display the same object. We propose a generic scheme called chopping to address this task. It relies on hundreds of random binary splits of the training set chosen to keep together the images of any given object. Those splits are extended to the complete image space with a simple learning algorithm. Given two images, the responses of the split predictors are combined with a Bayesian rule into a posterior probability of similarity. Experiments with the COIL-100 database and with a database of 150 degraded LATEX symbols compare our method to a classical learning with several examples of the positive class and to a direct learning of the similarity.
A Genetic Screen Based on in Vivo RNA Imaging Reveals Centrosome-Independent Mechanisms for Localizing gurken Transcripts in Drosophila

We have screened chromosome arm 3L for ethyl methanesulfonate−induced mutations that disrupt localization of fluorescently labeled gurken (grk) messenger (m)RNA, whose transport along microtubules establishes both major body axes of the developing Drosophila oocyte. Rapid identification of causative mutations by single-nucleotide polymorphism recombinational mapping and whole-genomic sequencing allowed us to define nine complementation groups affecting grk mRNA localization and other aspects of oogenesis, including alleles of elg1, scaf6, quemao, nudE, Tsc2/gigas, rasp, and Chd5/Wrb, and several null alleles of the armitage Piwi-pathway gene. Analysis of a newly induced kinesin light chain allele shows that kinesin motor activity is required for both efficient grk mRNA localization and oocyte centrosome integrity. We also show that initiation of the dorsoanterior localization of grk mRNA precedes centrosome localization, suggesting that microtubule self-organization contributes to breaking axial symmetry to generate a unique dorsoventral axis.
In Vivo and In Vitro Evidence for Placental DNA Damage in Preeclampsia

Preeclampsia (PE) is an idiopathic multisystem disease affecting 5–7% of pregnant women. Placental oxidative stress is a characteristic feature of PE and occurs when the production of reactive oxygen species (ROS) within the placenta overwhelms the intrinsic anti-oxidant defenses. We hypothesize that excessive oxidative DNA damage at the fetal-maternal interface coupled with a defective DNA damage/repair response is causally related to PE. Here we demonstrate that γH2AX (a sensitive marker of DNA damage) is expressed in the maternal decidua but not trophoblast of normal placentas, and that expression is significantly higher in PE placental tissues in vivo. Using primary in vitro cultures of maternal decidual stromal cells (DSCs) and fetal cytotrophoblast cells (CTs), we show an increase in γH2AX foci in DSCs cultured with vs without H2O2 (70.6% vs 11.6%; P<0.0001) or under hypoxia-reperfusion vs normoxia (20- vs 3-fold; P = 0.01); no foci were seen in CTs. We further demonstrate that Base Excision Repair (BER) intermediates are significantly increased in DSCs (not CTs) under these same conditions. Our data show that DNA damage is significantly more common in PE placentas, and that this DNA damage is localized to the maternal and not fetal side of the placenta. CTs may be selectively resistant to DNA damage in an effort to protect the fetus.
Nonlinear scale decomposition based features for visual speech recognition

A mathematical morphology based filter structure called a sieve is used to process mouth image sequences of a talker's mouth and form visual speech features. The effects of varying the type of filter, the post-processing and hidden Markov model (HMM) parameters on recognition accuracy are investigated using two audio-visual speech databases.
Accuracy of models for the 2001 foot-and-mouth epidemic

Since 2001 models of the spread of foot-and-mouth disease, supported by the data from the UK epidemic, have been expounded as some of the best examples of problem-driven epidemic models. These claims are generally based on a comparison between model results and epidemic data at fairly coarse spatio-temporal resolution. Here, we focus on a comparison between model and data at the individual farm level, assessing the potential of the model to predict the infectious status of farms in both the short and long terms. Although the accuracy with which the model predicts farms reporting infection is between 5 and 15%, these low levels are attributable to the expected level of variation between epidemics, and are comparable to the agreement between two independent model simulations. By contrast, while the accuracy of predicting culls is higher (20–30%), this is lower than expected from the comparison between model epidemics. These results generally support the contention that the type of the model used in 2001 was a reliable representation of the epidemic process, but highlight the difficulties of predicting the complex human response, in terms of control strategies to the perceived epidemic risk.
Automated Iris Recognition System: An Overview

Iris texture pattern can be used for biometric verification and identification of a person from a large dataset. Iris recognition is used in several fields, like border, security prone, industrial and medical institutes etc. Due to its high correctness and uniqueness, it is used in several fields of access control and border area security. The demand for iris recognition is increasing continuously due to its reliability, accuracy and uniqueness. To improve the overall recognition rate and performance of iris recognition system, the researchers have to work in different aspects like unconstrained environment, noisy images as well as blurred images. This paper overviews the different steps involve into iris recognition system as well as various methodology presents in the iris recognition system.
Many-to-One Mapping of Form to Function: A General Principle in Organismal Design?1

Abstract We introduce the concept of many-to-one mapping of form to function and suggest that this emergent property of complex systems promotes the evolution of physiological diversity. Our work has focused on a 4-bar linkage found in labrid fish jaws that transmits muscular force and motion from the lower jaw to skeletal elements in the upper jaws. Many different 4-bar shapes produce the same amount of output rotation in the upper jaw per degree of lower jaw rotation, a mechanical property termed Maxillary KT. We illustrate three consequences of many-to-one mapping of 4-bar shape to Maxillary KT. First, many-to-one mapping can partially decouple morphological and mechanical diversity within clades. We found with simulations of 4-bars evolving on phylogenies of 500 taxa that morphological and mechanical diversity were only loosely correlated (R2 = 0.25). Second, redundant mapping permits the simultaneous optimization of more than one mechanical property of the 4-bar. Labrid fishes have capitalized on this flexibility, as illustrated by several species that have Maxillary KT = 0.8 but have different values of a second property, Nasal KT. Finally, many-to-one mapping may increase the influence of historical factors in determining the evolution of morphology. Using a genetic model of 4-bar evolution we exerted convergent selection on three different starting 4-bar shapes and found that mechanical convergence only created morphological convergence in simulations where the starting forms were similar. Many-to-one mapping is widespread in physiological systems and operates at levels ranging from the redundant mapping of genotypes to phenotypes, up to the morphological basis of whole-organism performance. This phenomenon may be involved in the uneven distribution of functional diversity seen among animal lineages.
Joint Subcarrier Pairing and Power Allocation in OFDMA Cooperative Relay Networks

In this paper, we propose a joint subcarrier pairing and power allocation (JS2PA) scheme with fairness based on the Intelligent Water Drop (IWD) optimization method for Orthogonal Frequency Division Multiple Access (OFDMA) cooperative relay networks. The proposed scheme consists of a subcarrier pairing and selection algorithm and a power allocation algorithm. We first formulate the JS2PA problem as a mixed integer programming problem aiming to maximize the total network utility under the constraints of the total and individual power, subcarrier fairness requirement and pairing. To solve the non-convex JS2PA problem, firstly, we propose a subcarrier pairing and selection algorithm based on Hungarian method so as to select the appropriate subcarrier pairs for relaying. Secondly, we provide a power allocation algorithm based on the IWD method (PA-MIWD) in which water drops act as the agents to find the optimal power allocation for each node. Finally, we conduct simulations to validate the proposed algorithms and the results show that the proposed JS2PA scheme outperforms the existing methods in terms of convergence and total network utility.
A Multi-Objective and Multi-Product Advertising Billboard Location Model with Attraction Factor Mathematical Modeling and Solutions

Location﻿of﻿advertising﻿is﻿one﻿of﻿the﻿most﻿important﻿factors﻿of﻿marketing﻿strategy,﻿as﻿finding﻿the﻿ best﻿location﻿to﻿install﻿advertising﻿billboards﻿can﻿have﻿a﻿major﻿impact﻿on﻿profitability﻿of﻿the﻿entire﻿ marketing﻿process. ﻿This﻿paper﻿provides﻿a﻿billboard﻿location﻿model,﻿which﻿can﻿determine﻿the﻿optimal﻿ locations﻿for﻿installing﻿such﻿billboards. ﻿The﻿multi-objective﻿and﻿multi-product﻿model﻿developed﻿for﻿ this﻿purpose﻿has﻿two﻿objective﻿functions:﻿optimizing﻿the﻿sales﻿profit﻿minus﻿the﻿costs﻿of﻿designing﻿and﻿ installing﻿the﻿billboards,﻿and﻿attracting﻿most﻿visitors﻿through﻿maximization﻿of﻿an﻿attraction﻿factor. ﻿ The﻿designing﻿cost﻿is﻿assumed﻿to﻿be﻿associated﻿with﻿the﻿attraction﻿factor. ﻿This﻿model﻿finds﻿the﻿best﻿ location﻿of﻿billboards﻿based﻿on﻿constraint﻿such﻿as﻿number﻿of﻿visits﻿and﻿sales﻿volume. ﻿Finally,﻿a﻿set﻿ of﻿small﻿and﻿ large-scale﻿numerical﻿examples﻿are﻿solved﻿by﻿ implementing﻿ the﻿solution﻿method﻿ in﻿ GAMS\Cplex﻿solver﻿software. ﻿To﻿solve﻿the﻿large-scale﻿variants﻿of﻿the﻿problem,﻿the﻿genetic﻿algorithm. KeywORdS Advertising Billboard, Genetic Algorithm, Location, Multi-Objective, Multi-Product
An Affinity-Enhanced Neutralizing Antibody against the Membrane-Proximal External Region of Human Immunodeficiency Virus Type 1 gp41 Recognizes an Epitope between Those of 2F5 and 4E10

ABSTRACT The membrane-proximal external region (MPER) of human immunodeficiency virus type 1 (HIV-1) gp41 bears the epitopes of two broadly neutralizing antibodies (Abs), 2F5 and 4E10, making it a target for vaccine design. A third Ab, Fab Z13, had previously been mapped to an epitope that overlaps those of 2F5 and 4E10 but only weakly neutralizes a limited set of primary isolates. Here, libraries of Fab Z13 variants displayed on phage were engineered and affinity selected against an MPER peptide and recombinant gp41. A high-affinity variant, designated Z13e1, was isolated and found to be ∼100-fold improved over the parental Fab not only in binding affinity for the MPER antigens but also in neutralization potency against sensitive HIV-1. Alanine scanning of MPER residues 664 to 680 revealed that N671 and D674 are crucial for peptide recognition as well as for the neutralization of HIV-1 by Z13e1. Ab competition studies and truncation of MPER peptides indicate that Z13e1 binds with high affinity to an epitope between and overlapping with those of 2F5 and 4E10, with the minimal peptide epitope WASLWNWFDITN. Still, Z13e1 remained about an order of magnitude less potent than 4E10 against several isolates of pseudotyped HIV-1. The sum of our molecular analyses with Z13e1 suggests that the segment on the MPER of gp41 between the 2F5 and 4E10 epitopes is exposed on the functional envelope trimer but that access to the specific Z13e1 epitope within this segment is limited. Thus, the ability of MPER-bearing immunogens to elicit potent HIV-1-neutralizing Abs may depend in part on recapitulating the particular constraints that the functional envelope trimer imposes on the segment of the MPER to which Z13e1 binds.
Constructing a personal web map with anytime-control of Web robots

In this paper, we propose a PWM (Personal Web Map) which is a personal and small database of interesting Web pages to a user and develop a method to construct it under the user's control of multiple Web robots. Though general search engines with large databases like YaHoo, AltaVista, MetaCrawler are valid it is important that a user constructs a small, personal database of relevant Web pages to his/her interest like Bookmarks. For such a Web page database, we propose a PWM: a personal database of interesting Web pages to a user which he/she can control its construction. First a user gives keywords indicating his/her interest to a system, and it constructs a PWM concerned with the keywords. For building a useful PWM, it is necessary that a user can interrupt the construction of a PWM anytime and instruct a sub-field in which a PWM should be expanded more. For this function, we develop an anytime-control algorithm for multiple Web robots. A density distribution blackboard is used, and an uniform distributed PWM is built. Whenever a system is interrupted by a user it provides a valid PWM in terms of keeping search space wide, and indicates many alternatives on which he/she wants more information. From Web pages in a database, document vectors are generated and used to construct a 2D-map of a PWM by using self-organization maps. A user easily recognizes a PWM through the 2D-map, and gives instruction by clicking a node about which he/she wants more detail information. We made experiments by users and found out that our method outperformed breadth-first search for constructing a useful PWM. As results, a PWM system is considered as a promising approach to assist a user in gathering relevant information in the WWW.
Liveness and Flow in Notation Use

This paper presents concepts, models, and empirical findings relating to liveness and flow in the user experience of systems mediated by notation. Results from an extensive two-year field study of over 1,000 sequencer and tracker users, combining interaction logging, user surveys, and a video study, are used to illustrate the properties of notations and interfaces that facilitate greater immersion in musical activities and domains, borrowing concepts from programming to illustrate the role of visual and musical feedback, from the notation and domain respectively. The Cognitive Dimensions of Notations framework and Csikszentmihalyi’s flow theory are combined to demonstrate how non-realtime, notation-mediated interaction can support focused, immersive, energetic, and intrinsicallyrewarding musical experiences, and to what extent they are supported in the interfaces of music production software. Users are shown to maintain liveness through a rapid, iterative editaudition cycle that integrates audio and visual feedback.
Accuracy Versus Simplicity in Online Battery Model Identification

This paper presents a framework for battery modeling in online, real-time applications where accuracy is important but speed is the key. The framework allows users to select model structures with the smallest number of parameters that is consistent with the accuracy requirements of the target application. The tradeoff between accuracy and speed in a battery model identification process is explored using different model structures and parameter-fitting algorithms. Pareto optimal sets are obtained, allowing a designer to select an appropriate compromise between accuracy and speed. In order to get a clearer understanding of the battery model identification problem, “identification surfaces” are presented. As an outcome of the battery identification surfaces, a new analytical solution is derived for battery model identification using a closed-form formula to obtain a battery’s ohmic resistance and open circuit voltage from measurement data. This analytical solution is used as a benchmark for comparison of other fitting algorithms and it is also used in its own right in a practical scenario for state-of-charge estimation. A simulation study is performed to demonstrate the effectiveness of the proposed framework and the simulation results are verified by conducting experimental tests on a small NiMH battery pack.
Testing geomorphic signal of active normal faulting: The case of the Cittanova Fault (Calabria, southern Italy)

Extracting tectonic signals from the landscape is an important challenge for constraining the style and rate of deformation associated with active faults, especially where their displacement history cannot be independently determined. Based on previous paleoseismological data coupled with new geomorphological field work and 14C dating of geomorphic markers, we analysed the geomorphic signal of the along‐strike differential throw of the Cittanova Fault in southern Calabria (Italy), the recent activity of which is already well documented and constrained. Through DTM‐derived stream power law parameters (SL and χ), we provide evidence of drainage network disequilibrium and reorganization in response to fault growth and deformation style. Furthermore, a methodological test of the reliability of the χ metric as a proxy for the differential throw along the strike of active normal faults provided good preliminary results, consistent with a strong inverse linear correlation with fault throw. Copyright © 2018 John Wiley & Sons, Ltd.
Air Pollution and Daily Mortality in Two U.S. Counties: Season-Specific Analyses and Exposure-Response Relationships

I used generalized additive models to analyze the time series of daily total nonaccidental deaths and deaths due to vascular disease over the period 1987-1995 in two major metropolitan areas, Cook County, Illinois, and Los Angeles County, California, in the United States. In both counties I had monitoring information on PM 10, CO, SO 2, NO 2, and O 3. In Los Angeles, monitoring information on PM 2.5 was available as well. In addition to full-year analyses, I performed season-specific analyses. I present the results of both single- and multipollutant analyses. Although components of air pollution were associated with total nonaccidental and vascular disease mortality in both counties, the results indicate considerable heterogeneity of these associations in the two locations and also from season to season. In Los Angeles County, the gases, particularly CO and SO 2 but not ozone, were more strongly associated with mortality than was particulate matter, which exhibited only weak and inconsistent associations with both mortality endpoints. Both PM 10 and the gases were associated with total and vascular disease mortality in Cook County. The association of the gases with both mortality endpoints appeared to be stronger and more robust than that of PM 10. Exposure-response analyses using flexible smoothers showed significant departures from linearity, particularly for PM effects.
Dirichlet-Bernoulli Alignment: A Generative Model for Multi-Class Multi-Label Multi-Instance Corpora

We propose Dirichlet-Bernoulli Alignment (DBA), a generative model for corpora in which each pattern (e.g., a document) contains a set of instances (e.g., paragraphs in the document) and belongs to multiple classes. By casting predefined classes as latent Dirichlet variables (i.e., instance level labels), and modeling the multi-label of each pattern as Bernoulli variables conditioned on the weighted empirical average of topic assignments, DBA automatically aligns the latent topics discovered from data to human-defined classes. DBA is useful for both pattern classification and instance disambiguation, which are tested on text classification and named entity disambiguation in web search queries respectively.