Miracle-dz/UniFAR-FTUs huggingface dataset:
Monitoring of User Generated Video Broadcasting Services

Mobile video broadcasting services offer users the opportunity to instantly share content from their mobile handhelds to a large audience over the Internet. However, existing data caps in cellular network contracts and limitations in their upload capabilities restrict the adoption of mobile video broadcasting services. Additionally, the quality of those video streams is often reduced by the lack of skills of recording users and the technical limitations of the video capturing devices. Our research focuses on large-scale events that attract dozens of users to record video in parallel. In many cases, available network infrastructure is not capable to upload all video streams in parallel. To make decisions on how to appropriately transmit those video streams, a suitable monitoring of the video generation process is required. For this scenario, a measurement framework is proposed that allows Internet-scale mobile broadcasting services to deliver samples in an optimized way. Our framework architecture analyzes three zones for effectively monitoring user-generated video. Besides classical Quality of Service metrics on the network state, video quality indicators and additional auxiliary sensor information is gathered. Aim of this framework is an efficient coordination of devices and their uploads based on the currently observed system state.
The challenge of putting vision algorithms into a car

Current and future driver assistance systems rely heavily on environment perception. Using radar, ultrasound, laser, and camera systems they address the demand for comfortable and safe transportation. In this talk, we present the special biotope of vehicle-based machine vision algorithms. Developing software for computer vision tasks in the car industry is accompanied by several tough constraints, such as: · working with limited hardware resources · running with little energy consumption · using software economically · demanding reliable and robust building blocks · requiring methods that handle adverse environmental conditions, e.g. atmospheric disturbances or low light. We outline and discuss the steps of the development process starting with a first idea for an assistance system up to a final embedded system.
The Neighbor is King: Customer Discrimination in the Housing Market

This paper provides a method to single out customer-based discrimination in the housing market. We build a matching model with ethnic externalities where landlords differ in the number of housing units they own within the same building. Multiple-dwelling landlords discriminate more often than single-dwelling landlords only if some tenants are prejudiced against the minority group. By testing the null hypothesis whereby minority tenants are equally likely to have a multiple-dwelling landlord, we can test whether there is customer discrimination or not. We run the test on French data and show evidence of customer discrimination in the rental market.
In Silico Analysis of the Conservation of Human Toxicity and Endocrine Disruption Targets in Aquatic Species

Pharmaceuticals and industrial chemicals, both in the environment and in research settings, commonly interact with aquatic vertebrates. Due to their short life-cycles and the traits that can be generalized to other organisms, fish and amphibians are attractive models for the evaluation of toxicity caused by endocrine disrupting chemicals (EDCs) and adverse drug reactions. EDCs, such as pharmaceuticals or plasticizers, alter the normal function of the endocrine system and pose a significant hazard to human health and the environment. The selection of suitable animal models for toxicity testing is often reliant on high sequence identity between the human proteins and their animal orthologs. Herein, we compare in silico the ligand-binding sites of 28 human “side-effect” targets to their corresponding orthologs in Danio rerio, Pimephales promelas, Takifugu rubripes, Xenopus laevis, and Xenopus tropicalis, as well as subpockets involved in protein interactions with specific chemicals. We found that the ligand-binding pockets had much higher conservation than the full proteins, while the peroxisome proliferator-activated receptor γ and corticotropin-releasing factor receptor 1 were notable exceptions. Furthermore, we demonstrated that the conservation of subpockets may vary dramatically. Finally, we identified the aquatic model(s) with the highest binding site similarity, compared to the corresponding human toxicity target.
The Value of U.S. Patents by Owner and Patent Characteristics

This paper uses renewal data to estimate the value of U.S. patents, controlling for patent and owner characteristics. Estimates of U.S. patent value are substantially larger than estimates for European patents, however, the ratio of U.S. patent value to R&D for firms is only about 3%. Patents issued to small patentees are much less valuable than those issued to large corporations, perhaps reflecting imperfect markets for technology. Litigated patents are more valuable, as are highly cited patents. However, patent citations explain little variance in value, suggesting limits to their use as a measure of patent quality.
An Application of Combined Classifiers to Remotely Sensed Images

Studies in the area of Pattern Recognition have indicated that a classification model performs differently from one pattern class to another. This observation gave birth to the idea of combining the individual results of different classifiers to derive a consensus decision. This work investigates the potential of combining classifiers to remotely sensed images. A classifier system is built integrating the results of a feed-forward neural network and of a maximal likelihood classifier. Fuzzy Integrals are used as the combining strategy. Experiments carried out to evaluate the system, using a satellite image of an area undergoing a rapid degradation process, has shown that the combination may considerably improve the classification performance of the individual classifiers. Key-Words: Combining Classifiers, Remote Sensing, Pattern Recognition, Fuzzy Integrals, Back Propagation, Maximal Likelihood
C-terminal interactions mediate the quaternary dynamics of αB-crystallin

αB-crystallin is a highly dynamic, polydisperse small heat-shock protein that can form oligomers ranging in mass from 200 to 800 kDa. Here we use a multifaceted mass spectrometry approach to assess the role of the C-terminal tail in the self-assembly of αB-crystallin. Titration experiments allow us to monitor the binding of peptides representing the C-terminus to the αB-crystallin core domain, and observe individual affinities to both monomeric and dimeric forms. Notably, we find that binding the second peptide equivalent to the core domain dimer is considerably more difficult than the first, suggesting a role of the C-terminus in regulating assembly. This finding motivates us to examine the effect of point mutations in the C-terminus in the full-length protein, by quantifying the changes in oligomeric distribution and corresponding subunit exchange rates. Our results combine to demonstrate that alterations in the C-terminal tail have a significant impact on the thermodynamics and kinetics of αB-crystallin. Remarkably, we find that there is energy compensation between the inter- and intra-dimer interfaces: when one interaction is weakened, the other is strengthened. This allosteric communication between binding sites on αB-crystallin is likely important for its role in binding target proteins.
Revisiting Security Relations Between Signature Schemes and their Inner Hash Functions

After years of almost full confidence in the security of common hash functions such as MD5 and SHA-1, the cryptographic community is now facing the unprecedented threat of seeing practical security applications succumb to concrete attacks. A way to cope with this crisis is to fasten the development of new hash functions, but another crucial task is to assess the implications these attacks on hash functions may have on cryptographic systems. This paper reports a thorough investigation on how recent attacks on hash functions impact the security of signature schemes. We suggest the notion of probabilistic hash-and-sign signatures and further classify signature schemes into various related categories which allow us to identify completely the nature of security relations between signature schemes and their inner hash functions. We also determine how using iterated hash functions a la Merkle-Damgard impacts the security of deterministic (resp. probabilistic) hash-and-sign signatures. We confirm that the security gain inherent to using the probabilistic hash-and-sign paradigm may be lost completely if instantiated with a Merkle-Damgard hash function and unwise operating mode.
Post-inflation reheating in an expanding universe.

An analytic means of studying the resonant decay of the inflaton field is developed for the case of background expansion H # 0. It is shown that the parametric resonance in the in0aton’s decay need not disappear when the expansion of the universe is taken into account, although the total number of particles produced is fewer than that in the H Y 0 case.
TEI-power

FinFETs have emerged as a promising replacement for planar CMOS devices in sub-20nm technology nodes. However, based on the temperature effect inversion (TEI) phenomenon observed in FinFET devices, the delay characteristics of FinFET circuits in sub-, near-, and superthreshold voltage regimes may be fundamentally different from those of CMOS circuits with nominal voltage operation. For example, FinFET circuits may run faster in higher temperatures. Therefore, the existing CMOS-based and TEI-unaware dynamic power and thermal management techniques would not be applicable. In this article, we present TEI-power, a dynamic voltage and frequency scaling--based dynamic thermal management technique that considers the TEI phenomenon and also the superlinear dependencies of power consumption components on the temperature and outlines a real-time trade-off between delay and power consumption as a function of the chip temperature to provide significant energy savings, with no performance penalty—namely, up to 42% energy savings for small circuits where the logic cell delay is dominant and up to 36% energy savings for larger circuits where the interconnect delay is considerable.
Regularity-oriented analog placement with diffusion sharing and well island generation

This paper presents a novel regularity evaluation of placement structure and MOS analog specific layout techniques called diffusion sharing and well island generation, which are developed based on Sequence-Pair. The regular structures such as topological row, array and repetitive structure are characterized by the way of forming subsequences of a sequence-pair. A placement objective is formulated balancing the regularity and the area efficiency. Furthermore, diffusion sharing and well island can be also identified looking into forming of a sequence-pair. In experiments, we applied our regularity-oriented placement mixed with the constrait-driven technique to real analog designs, and attained the results comparable to manual designs even when imposing symmetry constraints. Besides, the results also revealed the regularity serves to increase row-structures applicable to the diffusion-sharing for the area and wire-length saving.
A Genome-wide Microsatellite Polymorphism Database for the Indica and Japonica Rice

Abstract Microsatellite (MS) polymorphism is an important source of genetic diversity, providing support for map-based cloning and molecular breeding. We have developed a new database that contains 52 845 polymorphic MS loci between indica and japonica, composed of ample Class II MS markers, and integrated 18 828 MS loci from IRGSP and genetic markers from RGP. Based on genetic marker positions on the rice genome (http://rise.genomics.org.cn/rice2/index.jsp ), we determined the approximate genetic distances of these MS loci and validated 100 randomly selected markers experimentally with 90% success rate. In addition, we recorded polymorphic MS positions in indica cv. 9311 that is the most important paternal parent of the two-line hybrid rice in China. Our database will undoubtedly facilitate the application of MS markers in genetic researches and marker-assisted breeding. The data set is freely available from www.wigs. zju.edu. cn/achievment/polySSR.
Bayesian Inference with Spiking Neurons

Humans and other animals behave as if we perform fast Bayesian inference underlying decisions and movement control given uncertain sense data. Here we show that a biophysically realistic model of the subthreshold membrane potential of a single neuron can exactly compute the numerator in Bayes rule for inferring the Poisson parameter of a sensory spike train. A simple network of spiking neurons can construct and represent the Bayesian posterior density of a parameter of an external cause that affects the Poisson parameter, accurately and in real time.
Interleaved Current Sensorless Control for Multiphase Boost-Type Switch-Mode Rectifier With Phase-Shedding Operation

Multiphase boost-type switch-mode rectifiers (SMRs) are often used to improve the efficiency of ac-dc conversion. In particular, the light-load efficiency can be increased by turning off some phases (i.e., phase-shedding operation). To keep the number of feedback signals fixed regardless of the topology phase number N, the interleaved current sensorless control (ICSC) with consideration of the phase-shedding operation is proposed in this paper. In ICSC, no current sensing is needed, and only input and output voltages are sensed. To demonstrate the proposed ICSC, a two-phase boost-type SMR is established for test, and the proposed ICSC is implemented in a field-programmable-gate-array-based system. The provided simulation and experimental results show good performance of the proposed ICSC.
Cross-view object classification in traffic scene surveillance based on transductive transfer learning

Object classification in traffic scene surveillance has been a hot topic in image processing field. A big challenge is that shooting view changes in different scenes, which leads to sharp accuracy decrease since training and test samples do not share the same distribution. Inductive transfer learning methods try to bridge this gap by making use of manually labeled target samples. However, it is in line with reality to conduct unsupervised transfer without manually labeling. In this paper, we propose an intuitive transductive transfer method by transferring instances across view. Experimental results indicate that our method outperforms traditional approaches such as inductive SVM and cluster method, and could even achieve a comparable performance compared with manually labeling approach.
Tyrosine phosphorylation of type Iγ phosphatidylinositol phosphate kinase by Src regulates an integrin–talin switch

Engagement of integrin receptors with the extracellular matrix induces the formation of focal adhesions (FAs). Dynamic regulation of FAs is necessary for cells to polarize and migrate. Key interactions between FA scaffolding and signaling proteins are dependent on tyrosine phosphorylation. However, the precise role of tyrosine phosphorylation in FA development and maturation is poorly defined. Here, we show that phosphorylation of type Iγ phosphatidylinositol phosphate kinase (PIPKIγ661) on tyrosine 644 (Y644) is critical for its interaction with talin, and consequently, localization to FAs. PIPKIγ661 is specifically phosphorylated on Y644 by Src. Phosphorylation is regulated by focal adhesion kinase, which enhances the association between PIPKIγ661 and Src. The phosphorylation of Y644 results in an ∼15-fold increase in binding affinity to the talin head domain and blocks β-integrin binding to talin. This defines a novel phosphotyrosine-binding site on the talin F3 domain and a “molecular switch” for talin binding between PIPKIγ661 and β-integrin that may regulate dynamic FA turnover.
Challenging on-chip SRAM security with boot-state statistics

On-chip memory is regarded by most secure system designers as a safe memory space, beyond the eyes of all but the most sophisticated attackers. Once a value is overwritten or the power has been removed, it is assumed that the data stored inside fully ceases to persist. However, as writes occur, the bit cells gradually wear; if data is written in an asymmetric way (with repeated writes of the same data), the stored information can later be partially reconstructed solely from statistical measurements of the cells' startup states. We present a technique for measuring the vulnerability of memory systems to such wear-in leakage, modeling the process as the recovery of bits from a noisy channel. We demonstrate our techniques on a 130nm SRAM device and demonstrate that if no countermeasures are used, a very simple prediction model is able to correctly reconstruct 27% of the bits of the written secret — enough to probabilistically reconstruct an RSA key.
Interesting-phrase mining for ad-hoc text analytics

Large text corpora with news, customer mail and reports, or Web 2.0 contributions offer a great potential for enhancing business-intelligence applications. We propose a framework for performing text analytics on such data in a versatile, efficient, and scalable manner. While much of the prior literature has emphasized mining keywords or tags in blogs or social-tagging communities, we emphasize the analysis of interesting phrases. These include named entities, important quotations, market slogans, and other multi-word phrases that are prominent in a dynamically derived ad-hoc subset of the corpus, e.g., being frequent in the subset but relatively infrequent in the overall corpus. We develop preprocessing and indexing methods for phrases, paired with new search techniques for the top-k most interesting phrases in ad-hoc subsets of the corpus. Our framework is evaluated using a large-scale real-world corpus of New York Times news articles.
Smart Decision Module for Streaming 3 D Meshes over Lossy Networks

This paper describes a smart decision module for transmitting 3D meshes over QoS networks. Any 3D multiresolution compression techniques assume no loss during the transmission. Reliable transport protocol such as TCP seems to be an excellent solution. However, time sensive applications find TCP suffering long delay in the presence of network congestion. This motives to use unreliable transport protocol such as UDP. Yet UDP introduces distortion between the reconstructed mesh and the original mesh due to the packet loss. In this paper, we modify CPM(Compressed Progressive Meshes) and develop a smart decision module. The smart decision module can intelligently select transport protocol for each geometric sub-layer to achieve minimum delay and distortion under a given network bandwidth and loss ratio. Simulations show that this smart decision module correctly evaluates the transmission time and average distortion and thus makes the optimized transport decisions.
High-Redshift Intergalactic C IV Abundance Measurements from the Near-Infrared Spectra of Two z ~ 6 QSOs

New measurements of the z ~ 6 intergalactic C IV abundance are presented, using moderate-resolution IR spectra of two QSOs taken with GNIRS on Gemini-South. These data were systematically searched for high-redshift C IV absorption lines, using objective selection criteria. Comprehensive tests were performed to quantify sample incompleteness, as well as the rate of false-positive C IV identifications. The trend of constant Ω(z) observed at z ~ 2-5 appears to continue to z ~ 6, the highest observed redshift. The C IV sample is also consistent with the redshift-invariant form of the C IV column density distribution reported by Songaila at lower redshift, although with fairly large uncertainties due to a smaller sample size and noisier infrared data. The constant value of Ω does not necessarily imply that the IGM was infused with an early metallicity "floor," but the presence of early C IV does indicate that heavy-element enrichment began ≲1 Gyr after the big bang. The lack of a decline in Ω at high redshift may indicate that integrated C IV measurements are sensitive to the instantaneous rate of feedback from galaxy formation at each epoch. Alternatively, it could result from a balance in the evolution of the intergalactic gas density, ionization conditions, and heavy-element abundance over time.
Parametric data-parallel architectures for TLM acceleration

We discuss the architecture and microarchitecture of a scalable, parametric vector accelerator for the TLM algorithm. Architecture-level experimentation demonstrates an order of magnitude complexity reduction for vector lengths of 16 32-bit single-precision elements. We envisage the proposed architecture replicated in a SoC environment, thus forming a multiprocessor system capable of tapping. parallelism at the thread level as well as the data level.
Implantación de las competencias: percepciones de directivos y docentes de educación física / Implementation of Key Competences: Perceptions of Headmasters and Physical Education Teachers

El objetivo del estudio fue conocer las percepciones que tienen sobre la implantacion de las Competencias Basicas (CCBB) los equipos directivos y los docentes de Educacion Fisica (EF). Participaron todos los centros de Educacion Secundaria de la capital de Burgos (Espana). Se empleo una metodologia mixta, utilizando un cuestionario validado para obtener datos de los directores (N=30) y de los jefes de departamento de EF (N=30) y un estudio de caso unico. Los equipos directivos consideran que estas potencian el aprendizaje del alumnado y favorecen la evaluacion. Los docentes valoran la variedad de alternativas en el aula mediante el uso de metodologias cooperativas. La menor edad de los equipos directivos es un factor que influye en su percepcion positiva, mientras que la menor experiencia es el factor determinante de esta percepcion entre los docentes. El estudio de caso refleja que los profesores de EF de un mismo departamento trabajan de manera diferente las CCBB. PALABRAS CLAVE : Competencias basicas, percepcion del profesorado, cooperacion, implicacion del alumno, estrategias docentes. ABSTRACT The purpose was to assess headmasters and Physical Education teachers’ perceptions on the implementation of Key Competencies (KKCC). All the secondary schools located in Burgos (Spain) agreed to participate. A mixed research design was used. On one hand, an expert validated questionnaire was used to obtain data from all the headmasters (N=30) and all the heads of the Physical Education departments (N=30); on the other hand, a single case study was conducted in one of the schools. Headmasters highlighted that KKCC foster students’ learning and help assess the whole learning process. Teachers underlined that the KKCC promote the use of different learning methods in class and they believed that cooperative learning strategies are needed. Age influenced headmasters’ positive perception on KKCC, and teaching experience influenced teachers’ perceptions. The single case study showed that PE teachers in the same department work differently the KKCC. KEY WORDS : Key Competences, teacher perception, cooperation, student involvement, teaching strategies.