Miracle-dz/UniFAR-FTUs huggingface dataset:
Elementary Equivalence of ∑-Injective Modules

Let R be a ring with 1 and consider the problem of assigning numerical invariants to right K-modules so that two such modules are elementarily equivalent if and only if they have the same invariants. This general problem has been solved by Baur [1], Garavaglia [8], and Monk [18]. The invariants they produce are however rather more model-theoretic than algebraic and are in general highly redundant. In this paper I consider the problem for a restricted class of modules but obtain invariants which have a direct algebraic significance. These invariants are of the Baur-Garavaglia-Monk type (see the comments at the end of the paper) but form a minimal set of such. The results here are considered from a fairly algebraic point of view. Some comments on a more model-theoretic approach are made at the end. Those with some knowledge of stability theory (in the model-theoretic sense) or who are acquainted with [9] might find it useful to refer to these comments and to bear them in mind while reading the paper. I have attempted to make this paper accessible both to algebraists and to modeltheorists. Thus for instance I have avoided the use of too powerful machinery from either area and have given some arguments with rather more detail than would normally be included. This applies in particular to arguments which are fairly routine but with which I would not expect all readers of this paper to be familiar. For definitions and background not included here I recommend [27] for the algebra and [25] or [4, §0] for the model theory. Throughout, R will be some fixed ring with 1 and 'module' will mean an object of the category JtR of right /^-modules. Associated with JtR is the usual first-order language Z£R: the variables of the language are to be thought of as varying over module elements; there is a constant symbol '0' for the zero element of a module; there is a symbol ' + ' to represent module addition; for each element r of R there is a function symbol (V written on the right of its argument without parentheses) with which to express multiplication of module elements by r. Thus, for example, '3u(/\"= 1 vrt = 0 A D ^ 0 ) ' where ri9. ,rn e R, is a formula in this language (which says of any module which satisfies it that there is an element which kills each of rx,.,rn and which is non-zero—i.e. there is a non-zero element whose annihilator contains YJ=I «^)Note that quantification over elements of R is not possible in ££R. My main concern will be with elementary equivalence of injective modules. Two modules M,N are elementarily equivalent, M = N, if they satisfy precisely the same sentences of S£R. An embedding M ^ N is an elementary embedding, M<N, if the same is true when parameters from M are allowed to appear in the sentences. Write M =i N if M,N satisfy precisely the same existential sentences of S£R (those of the form 3vq)(v) where (p{v) contains no quantifiers, e.g. the sentence in the previous paragraph is such). The following result is easily proved using the above-mentioned
The Use of Lausanne Trilogue Play in Three Cases of Gastroschisis Diagnosed during Pregnancy

From pregnancy to the 1st years of a child’s life, families develop and increase representations and interactive competences toward the child. Prenatal diagnosis of a severe fetus’ defect could profoundly alter the parental perception and development of these representations. The aim of the study was to evaluate triadic interactions in families, whose baby was prenatally diagnosed with severe gastroschisis. Three families took part in the preliminary case study, which was carried out when the babies were 6 months old. The Lausanne Trilogue Play shows that prenatal diagnosis of fetal malformation may affect family triadic interactions as follows: (a) parents, especially mothers, tend to be intrusive during the play; (b) parents presents maladjustments in the child stimulations, especially during the third part, when both parents have to simultaneously interact with the baby; (c) parents experience difficulties in creating a space that allows them to communicate directly with each other, leaving the child in a peripheral position. Observational data and clinical implications are discussed.
Uncertainty quantification of inflow boundary condition and proximal arterial stiffness–coupled effect on pulse wave propagation in a vascular network

This work aims at quantifying the effect of inherent uncertainties from cardiac output on the sensitivity of a human compliant arterial network response based on stochastic simulations of a reduced‐order pulse wave propagation model. A simple pulsatile output form is used to reproduce the most relevant cardiac features with a minimum number of parameters associated with left ventricle dynamics. Another source of significant uncertainty is the spatial heterogeneity of the aortic compliance, which plays a key role in the propagation and damping of pulse waves generated at each cardiac cycle. A continuous representation of the aortic stiffness in the form of a generic random field of prescribed spatial correlation is then considered. Making use of a stochastic sparse pseudospectral method, we investigate the sensitivity of the pulse pressure and waves reflection magnitude over the arterial tree with respect to the different model uncertainties. Results indicate that uncertainties related to the shape and magnitude of the prescribed inlet flow in the proximal aorta can lead to potent variation of both the mean value and standard deviation of blood flow velocity and pressure dynamics due to the interaction of different wave propagation and reflection features. Lack of accurate knowledge in the stiffness properties of the aorta, resulting in uncertainty in the pulse wave velocity in that region, strongly modifies the statistical response, with a global increase in the variability of the quantities of interest and a spatial redistribution of the regions of higher sensitivity. These results will provide some guidance in clinical data acquisition and future coupling of arterial pulse wave propagation reduced‐order model with more complex beating heart models.
Architecture Design and Implementation of the Metric First List Sphere Detector Algorithm

Soft-output detection of a multiple-input-multiple-output (MIMO) signal pose a significant challenge in future wireless systems. In this paper, we introduce a soft-output modified metric first (MMF)-LSD algorithm for MIMO detection. We design a scalable architecture and address a method to decrease memory requirements. We provide implementation results for a spatial multiplexing (SM) system with four transmitted streams and with 16- and 64-quadrature amplitude modulation (QAM) on a 0.18-μ m CMOS application specific integrated circuit (ASIC) technology. The MFF-LSD implementation is more efficient than the depth first (DF)-LSD in the crucial low signal-to-noise rate (SNR) region and the detection rate of the 64-QAM implementation is 39.2 Mbps@26 db with 48.2 kGEs complexity.
Characterization of the Microenvironment in Positive and Negative Sentinel Lymph Nodes from Melanoma Patients

Melanomas are aggressive skin tumors characterized by high metastatic potential. Our previous results indicate that Natural Killer (NK) cells may control growth of melanoma. The main defect of blood NK cells was a decreased expression of activating NCR1/NKp46 receptor and a positive correlation of NKp46 expression with disease outcome in stage IV melanoma patients was found. In addition, in stage III melanoma patients, we identified a new subset of mature NK cells in macro-metastatic Lymph nodes (LN). In the present studies, we evaluated the numbers of NK cells infiltrating primary cutaneous melanoma and analyzed immune cell subsets in a series of sentinel lymph nodes (SLN). First, we show that NKp46+ NK cells infiltrate primary cutaneous melanoma. Their numbers were related to age of patients and not to Breslow thickness. Then, a series of patients with tumor-negative or -positive sentinel lymph nodes matched for Breslow thickness of the cutaneous melanoma was constituted. We investigated the distribution of macrophages (CD68), endothelial cells, NK cells, granzyme B positive (GrzB+) cells and CD8+ T cells in the SLN. Negative SLN (SLN-) were characterized by frequent adipose involution and follicular hyperplasia compared to positive SLN (SLN+). High densities of macrophages and endothelial cells (CD34), prominent in SLN+, infiltrate SLN and may reflect a tumor favorable microenvironment. Few but similar numbers of NK and GrzB+ cells were found in SLN- and SLN+: NK cells and GrzB+ cells were not correlated. Numerous CD8+ T cells infiltrated SLN with a trend for higher numbers in SLN-. Moreover, CD8+ T cells and GrzB+ cells correlated in SLN- not in SLN+. We also observed that the numbers of CD8+ T cells negatively correlated with endothelial cells in SLN-. The numbers of NK, GrzB+ or CD8+ T cells had no significant impact on overall survival. However, we found that the 5 year-relapse rate was higher in SLN with higher numbers of NK cells.
The Real-World Wide Web Browser: An Interface for a Continuously Available, General Purpose, Spatialized Information Space

In this paper we describe an augmented reality (AR) system that acts as continuously available interface to a spatialized information space based on the World Wide Web. We call such an information space the Real-World Wide Web (RWWW). We present the assumptions we make about the characteristics of such a system, discuss the implications of those assumptions for an AR interface, and describe a RWWW browser we are building.
Syntactic Category Prediction for Improving Translation Quality in English-Korean Machine Translation

This paper proposes the syntactic category prediction for improving translation quality. In parsing using sentence segmentation, the segments are separately parsed and then the parsing results of each segment are combined to generate a global sentence structure. The syntactic category prediction guides the parser to identify relationships among segments and to select the correct parsing results for each segment. We design features for predicting syntactic categories and generate decision trees for the prediction using training data from the Penn Treebank. In experiment, we show the prediction accuracy and comparison results with the prediction by human-built rules, heuristic probability function, and neural networks. Also, we present how much the category prediction contributes to improving translation quality.
An adaptive microphone array for optimum beamforming and noise reduction

We present a new adaptive microphone array efficiently implemented as a multi-channel FFT-filterbank. The array design is based on a minimum variance distortionless response (MVDR) optimization criterion. MVDR beamformer weights are updated for each signal frame using an estimated spatio-spectral correlation matrix of the environmental noise field. We avoid matrix inversion by means of an iterative algorithm for weight vector computation. The beamformer performance is superior to designs based on an assumed homogeneous diffuse noise field. The new design also outperforms LMS-adaptive beamformers at the expense of a higher computational load. Additional noise reduction is achieved with the well-known beamformer/postfilter combination of the optimum multi-channel filter. An Ephraim-Malah spectral amplitude modification with minimum statistics noise estimation is employed as a postfilter. Experimental results are presented using sound recordings in a reverberant noisy room.
Range-Aggregate Queries for Geometric Extent Problems

Let S be a set of n points in the plane. We present data structures that solve range-aggregate query problems on three geometric extent measure problems. Using these data structures, we can report, for any axis-parallel query rectangle Q, the area/perimeter of the convex hull, the width, and the radius of the smallest enclosing disk of the points in S ∩ Q.
Spatial pattern alterations from JPEG2000 lossy compression of remote sensing images: massive variogram analysis in high performance computing

Abstract We evaluate the implications of JPEG2000 lossy compression of remote sensing images for spatial analytical purposes. The main issue is to identify which cases and conditions in geostatistical studies are suitable for using lossy compressed images. For these purposes, an extensive test using Landsat, compact airborne spectrographic imager (CASI), and moderate resolution imaging spectroradiometer (MODIS) image series has been analyzed, through applying and comparing two-dimensional and three-dimensional (spectral and time domains) compression methods with a wide range of compression ratios for several dates, different landscape regions, and spectral bands. Due to the massive test bed and consequently to the high time consuming executions, a parallel solution was specifically developed. Variogram analyses showed that all the compression ratios maintain the variogram shapes, but high compression ratios ( > 20 ∶ 1 ) degrade the spatial patterns of the remote sensing images. These alterations are lower for the three-dimensional compression method, which was a considerable improvement (25%) on the two-dimensional method for large three-dimensional series (CASI, MODIS). However, the two methods behave similarly in the Landsat case. Finally, the parallel solution in a distributed environment demonstrates that high performance computing offers a suitable scientific platform for highly demanding time execution applications, such as geostatistical analyses of remote sensing images.
Collective Information Seeking : Supporting Search with Low-Cost Activity Sharing and Collaboration

When searching for information, people often seek help from others. However, while people can benefit from communicating with others, they can usually satisfy their information needs, to some degree, without help. Because establishing explicit collaborations is often seen as onerous, there are many missed opportunities where shared experiences could save time and effort. In this work, we propose Collective Information Seeking, which integrates theory of group work with previous research in Social Navigation and Collaborative Information Seeking. We propose that by sharing and visualizing activities within groups of information seekers a low-cost form of collaboration is made possible. Shared activities provide both a form of implicit communication that can provide guidance, and provide cues and context facilitating entry into direct collaboration at a later time.
Identification of the Candida albicans Cap1p Regulon

ABSTRACT Cap1p, a transcription factor of the basic region leucine zipper family, regulates the oxidative stress response (OSR) in Candida albicans. Alteration of its C-terminal cysteine-rich domain (CRD) results in Cap1p nuclear retention and transcriptional activation. To better understand the function of Cap1p in C. albicans, we used genome-wide location profiling (chromatin immunoprecipitation-on-chip) to identify its transcriptional targets in vivo. A triple-hemagglutinin (HA3) epitope was introduced at the C terminus of wild-type Cap1p (Cap1p-HA3) or hyperactive Cap1p with an altered CRD (Cap1p-CSE-HA3). Location profiling using whole-genome oligonucleotide tiling microarrays identified 89 targets bound by Cap1p-HA3 or Cap1p-CSE-HA3 (the binding ratio was at least twofold; P ≤ 0.01). Strikingly, Cap1p binding was detected not only at the promoter region of its target genes but also at their 3′ ends and within their open reading frames, suggesting that Cap1p may associate with the transcriptional or chromatin remodeling machinery to exert its activity. Overrepresented functional groups of the Cap1p targets (P ≤ 0.02) included 11 genes involved in the OSR (CAP1, GLR1, TRX1, SOD1, CAT1, and others), 13 genes involved in response to drugs (PDR16, MDR1, FLU1, YCF1, FCR1, and others), 4 genes involved in phospholipid transport (PDR16, GIT1, RTA2, and orf19.932), and 3 genes involved in the regulation of nitrogen utilization (GST3, orf19.2693, and orf19.3121), suggesting that Cap1p has other cellular functions in addition to the OSR. Bioinformatic analyses of the bound sequences suggest that Cap1p recognizes the DNA motif 5′-MTKASTMA. Finally, transcriptome analyses showed that increased expression generally accompanies Cap1p binding at its targets, indicating that Cap1p functions as a transcriptional activator.
Child and parental self-monitoring as determinants of success in the treatment of morbid obesity in low-income minority children.

OBJECTIVE To examine self-monitoring by children and parents as related to weight control over 6 months within a long-term multidisciplinary program for low-income minority children with morbid obesity. METHODS The weight changes of 228 children with obesity were evaluated according to frequency of child and parental self-monitoring. Predictors of self-monitoring were also evaluated. RESULTS Children who self-monitored on most days lost more weight over 6 months of treatment compared with less-consistent self-monitors. Children whose parents self-monitored were also more likely to self-monitor and lose weight. CONCLUSIONS Self-monitoring seems just as critical for successful weight control among low-income minority children with obesity as it is in the middle-class populations. Although lower education and higher levels of psychosocial stress may decrease self-monitoring and participation by these families, they might still benefit from targeting highly consistent self-monitoring (by parents and children) as a primary goal in weight-control programs.
The control infrastructure for reconfigurable DSP system

A heterogeneous embedded reconfigurable computing platform with loosely-coupled structure for DSP is constructed. Based on the platform, the signal processing task model and control model are discussed. The control unit based on finite state machine in combine to the signal processing functional unit is defined. A combination mechanism for control units is also brought out. Through the control units and combination mechanism, the hierarchical control infrastructure of the DSP system is present. The experiments show that the control infrastructure can serve the signal processing correctly and effectively.
Basin Bifurcations in a Two-Dimensional Logistic Map

Previous works have been devoted to the study of two-dimensional noninvertible maps, obtained using a coupling between one-dimensional logistic maps. This paper is devoted to the study of a specific one, in order to complete previous results (Ref. 5 and 7), regarding the evolution of basins and attractors, when considering the tool of critical manifolds.
Convergent Input from Brainstem Coincidence Detectors onto Delay-Sensitive Neurons in the Inferior Colliculus

Responses of low-frequency neurons in the inferior colliculus (IC) of anesthetized guinea pigs were studied with binaural beats to assess their mean best interaural phase (BP) to a range of stimulating frequencies. Phase plots (stimulating frequency vs BP) were produced, from which measures of characteristic delay (CD) and characteristic phase (CP) for each neuron were obtained. The CD provides an estimate of the difference in travel time from each ear to coincidence-detector neurons in the brainstem. The CP indicates the mechanism underpinning the coincidence detector responses. A linear phase plot indicates a single, constant delay between the coincidence-detector inputs from the two ears. In more than half (54 of 90) of the neurons, the phase plot was not linear. We hypothesized that neurons with nonlinear phase plots received convergent input from brainstem coincidence detectors with different CDs. Presentation of a second tone with a fixed, unfavorable delay suppressed the response of one input, linearizing the phase plot and revealing other inputs to be relatively simple coincidence detectors. For some neurons with highly complex phase plots, the suppressor tone altered BP values, but did not resolve the nature of the inputs. For neurons with linear phase plots, the suppressor tone either completely abolished their responses or reduced their discharge rate with no change in BP. By selectively suppressing inputs with a second tone, we are able to reveal the nature of underlying binaural inputs to IC neurons, confirming the hypothesis that the complex phase plots of many IC neurons are a result of convergence from simple brainstem coincidence detectors.
Security Applications of Formal Language Theory

We present a formal language theory approach to improving the security aspects of protocol design and message-based interactions in complex composed systems. We argue that these aspects are responsible for a large share of modern computing systems' insecurity. We show how our approach leads to advances in input validation, security modeling, attack surface reduction, and ultimately, software design and programming methodology. We cite examples based on real-world security flaws in common protocols, representing different classes of protocol complexity. We also introduce a formalization of an exploit development technique, the parse tree differential attack, made possible by our conception of the role of formal grammars in security. We also discuss the negative impact unnecessarily increased protocol complexity has on security. This paper provides a foundation for designing verifiable critical implementation components with considerably less burden to developers than is offered by the current state of the art. In addition, it offers a rich basis for further exploration in the areas of offensive analysis and, conversely, automated defense tools, and techniques.
Limiting performance of block-fading channels with multiple antennas

We study the performance limits of a radio system consisting of a transmitter with t antennas and a receiver with r antennas over a block-fading additive white Gaussian noise channel. We derive the optimal coding scheme minimizing the information outage probability and analyze its performance in terms of outage probability and delay-limited capacity. We show that, asymptotically, the delay-limited capacity grows linearly and is almost independent of the number of fading blocks M which implies the existence of a trade-off between spatial (multiple antennas) and time diversity (interleaving).
Mapping Latent Heat Flux in the Western Forest Covered Regions of Algeria Using Remote Sensing Data and a Spatialized Model

The present paper reports on an investigation to monitor the drought status in Algerian forest covered areas with satellite Earth observations because ground data are scarce and hard to collect. The main goal of this study is to map surface energy fluxes with remote sensing data, based on a simplified algorithm to solve the energy balance equation on each data pixel. Cultivated areas, forest cover and a large water surface were included in the investigated surfaces. The input parameters involve remotely sensed data in the visible, near infrared and thermal infrared. The surface energy fluxes are estimated by expressing the partitioning of energy available at the surface between the sensible heat flux (H) and the latent heat flux (LE) through the evaporative fraction (Λ) according to the S-SEBI (Simplified Surface Energy Balance Index) concept. The method is applicable under the assumptions of constant atmospheric conditions and sufficient wet and dry pixels over a Landsat 7 image. The results are analyzed and discussed considering instantaneous latent heat flux at the data acquisition time. The results confirm the relationships between albedo (r0), the surface temperature (T0) and the evaporative fraction. The method provides estimates of air temperature and LE close to reference measurements. The estimate of latent heat flux and other variables are comparable to those of previous studies. Their comparison with other methods shows reasonable agreement. This approach has demonstrated its simplicity and the fact that remote sensing data alone is sufficient; it could be very promising in areas where data are scarce and difficult to collect.