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The purpose of this manuscript is to derive new convergence results for several subgradient methods applied to minimizing nonsmooth convex functions with Hölderian growth. The growth condition is satisfied in many applications and includes functions with quadratic growth and weakly sharp minima as special cases. To this end there are three main contributions. First, for a constant and sufficiently small stepsize, we show that the subgradient method achieves linear convergence up to a certain region including the optimal set, with error of the order of the stepsize. Second, if appropriate problem parameters are known, we derive a decaying stepsize which obtains a much faster convergence rate than is suggested by the classical O (1 / k) result for the subgradient method. Thirdly we develop a novel "descending stairs" stepsize which obtains this faster convergence rate and also obtains linear convergence for the special case of weakly sharp functions. We also develop an adaptive variant of the "descending stairs" stepsize which achieves the same convergence rate without requiring an error bound constant which is difficult to estimate in practice. [ABSTRACT FROM AUTHOR]

To address the challenges posed by large-scale development, validation, and adoption of artificial intelligence (AI) in pathology, we have constituted a consortium of academics, small enterprises, and pharmaceutical companies and proposed the BIGPICTURE project to the Innovative Medicines Initiative. Our vision is to become the catalyst in the digital transformation of pathology by creating the first European, ethically compliant, and quality-controlled whole slide imaging platform, in which both large-scale data and AI algorithms will exist. Our mission is to develop this platform in a sustainable and inclusive way, by connecting the community of pathologists, researchers, AI developers, patients, and industry parties based on creating value and reciprocity in use based on a community model as the mechanism for ensuring sustainability of the platform. [ABSTRACT FROM AUTHOR]

Severely obese patients undergoing bariatric surgery (BS) are at increased risk for venous thromboembolism (VTE). How standard low molecular weight heparin (LMWH) regimen should be adapted to provide both sufficient efficacy and safety in this setting is unclear. We aimed to compare the influence of four body size descriptors (BSD) on peak anti-Xa levels in BS obese patients receiving LMWH fixed doses to identify which one had the greatest impact. One hundred and thirteen BS obese patients [median body mass index (BMI), 43.3 kg/m 2 (IQR, 40.6–48.7 kg/m 2 )] receiving subcutaneous dalteparin 5000 IU twice daily were included in this prospective monocenter study. Peak steady-state anti-Xa levels were measured peri-operatively following thromboprophylaxis initiation. Only 48% of patients achieved target anti-Xa levels (0.2–0.5 IU/ml). In univariate analysis, age, gender, total body-weight (TBW), lean body-weight (LBW), ideal body-weight (IBW), BMI and estimated glomerural filtration rate (eGFR) were associated with anti-Xa levels. The strongest negative association was observed with LBW (r = −0.56, p < .0001). Receiver operating characteristic curves indicated that among BSD, LBW (cut-off >55.8 kg) had the highest sensitivity (73%) and specificity (69%) to predict sub-prophylactic anti-Xa levels. In multivariate analysis, LBW and eGFR remained associated with anti-Xa levels (β = −0.47 ± 0.08, p < .0001 and β = −0.19 ± 0.08; p = .02, respectively). In BS morbidly obese patients receiving LMWH for thromboprophylaxis after BS, LBW and eGFR are the main determinants of anti-Xa level, and could be proposed in LMWH-based thromboprophylaxis dosing algorithms. The efficacy of a LBW-scale based dosing algorithm for optimal VTE prevention deserves further prospective randomized trials. [ABSTRACT FROM AUTHOR]

Shannon’s analysis of the fundamental capacity limits for memoryless communication channels has been refined over time. In this paper, the maximum volume M_ \mathrm avg^*(n,\epsilon ) of length- n codes subject to an average decoding error probability \epsilon is shown to satisfy the following tight asymptotic lower and upper bounds as n \to \infty : , where C is the Shannon capacity, V_\epsilon is the \epsilon -channel dispersion, or second-order coding rate, Q and \overline A_\epsilon are explicitly identified. This expression holds under mild regularity assumptions on the channel, including nonsingularity. The gap \overline A_\epsilon - \underline A_\epsilon is one nat for weakly symmetric channels in the Cover–Thomas sense, and typically a few nats for other symmetric channels, for the binary symmetric channel, and for the $Z$ channel. The derivation is based on strong large-deviations analysis and refined central limit asymptotics. A random coding scheme that achieves the lower bound is presented. The codewords are drawn from a capacity-achieving input distribution modified by an O(1/\sqrt {n}) correction term. [ABSTRACT FROM PUBLISHER]

In this paper, we investigate order-preserving sparse coding for classifying structured data whose atomic features possess ordering relationships. Examples include time sequences where individual frame-wise features are temporally ordered, as well as still images (landscape, street view, etc.) where different regions of the image are spatially ordered. Classification of these structured data is often tackled by first decomposing the input data into individual atomic features, then performing sparse coding or other processing for each atomic feature vector independently, and finally aggregating individual responses to classify the input data. However, this heuristic approach ignores the underlying order of the individual atomic features within the input data, and results in suboptimal discriminative capability. In this work, we introduce an order preserving regularizer which aims to preserve the ordering structure of the reconstruction coefficients within the sparse coding framework. An efficient Nesterov-type smooth approximation method is developed for optimization of the new regularization criterion, with theoretically guaranteed error bound. We perform extensive experiments for time series classification on a synthetic dataset, several machine learning benchmarks, and an RGB-D human activity dataset. We also report experiments for scene classification on a benchmark image dataset. The encoded representation is discriminative and robust, and our classifier outperforms state-of-the-art methods on these tasks. [ABSTRACT FROM PUBLISHER]

Ineffective spatial-temporal motion feature pooling has been a fundamental bottleneck for human action recognition/detection for decades. Previous pooling schemes such as global, spatial-temporal pyramid, or human and object centric pooling fail to capture discriminative motion patterns because informative movements only occur in specific regions of the human body, that depend on the type of action being performed. Global (holistic) motion feature pooling methods therefore often result in an action representation with limited discriminative capability. To address this fundamental limitation, we propose an adaptive motion feature pooling scheme that utilizes human poses as side information. Such poses can be detected for instance in assisted living and indoor smart surveillance scenarios. Taking both video sub-volumes for pooling and human pose types as hidden variables, we formulate the motion feature pooling problem as a latent structural learning problem where the relationship between the discriminative pooling video sub-volumes and the pose types is learned. The resulting pose adaptive motion feature pooling scheme is extensively tested on assisted living and smart surveillance datasets and on general action recognition benchmarks. Improved action recognition and detection performances are demonstrated. [ABSTRACT FROM AUTHOR]

When information is to be transmitted over a unknown, possibly unreliable channel, an erasure option at the decoder is desirable. Using constant-composition random codes, we propose a generalization of Csiszár and Körner's maximum mutual information (MMI) decoder with an erasure option for discrete memoryless channels. The new decoder is parameterized by a weighting function that is designed to optimize the fundamental tradeoff between undetected-error and erasure exponent for a compound class of channels. The class of weighting functions may be further enlarged to optimize a similar tradeoff for list decoders--in that case, undetected-error probability is replaced with average number of incorrect messages in the fist. Explicit solutions are identified. The optimal exponents admit simple expressions in terms of the sphere-packing exponent, at all rates below capacity. For small erasure exponents, these expressions coincide with those derived by Forney (1968) for symmetric channels, using maximum a posteriori decoding. Thus, for those channels at least, ignorance of the channel law is inconsequential. Conditions for optimality of the Csiszfir-Körner rule and of the simpler empirical-mutual-information thresholding rule are identified. The error exponents are evaluated numerically for the binary symmetric channel. [ABSTRACT FROM AUTHOR]

Hypophosphatasia is an inheritable disorder characterised by defective bone mineralisation due to the impaired activity of tissue-non-specific alkaline phosphatase (AP). Clinical presentation ranges from stillbirth without mineralised bone to pathological fractures in late adulthood. During childhood, the main manifestations include rickets, growth delay and dental problems. Fractures and bone pain usually characterise the adult form. A 9-year-old girl was referred for repetitive fractures after minimal trauma. She had normal growth, normal sclerae, no rickets and minimal dental abnormalities. Her sister had also presented fractures. The proband, her sister and mother had low total and bone-specific AP levels and E435K mutation in exon 12 of the liver/bone/kidney AP gene. Low AP levels must lead to genetic analysis. Bone fragility and repetitive fractures may be symptoms of hypophosphatasia in childhood, which must not be neglected. Associated factors such as vitamin D or calcium deficiency must be prevented. In conclusion, hypophosphatasia must not be forgotten as an aetiological factor of repetitive fractures or bone pain in children and AP activity should be checked accurately. [ABSTRACT FROM AUTHOR]

In congenital hyperinsulinism of infancy (CHI), the loss of K-ATP channels (composed of Kir6.2 and SUR1 subunits) in β cells induces permanent insulin secretion and severe hypoglycaemia. By contrast, Sur1 −/− mice do not present such defects. We have investigated the impact of Sur1 gene inactivation on mouse islet cell morphology, structure and basic physiology. Pancreata were collected from young, adult and old wild-type (WT) and Sur1 −/− mice. After immunostaining for hormone, the total endocrine tissue, cell proportion, cell size and intra-insular distribution, hormone content and Glut-2 expression were quantified by morphometry. Basic physiological parameters were also measured. In young Sur1 −/− mice, the total endocrine tissue and proportion of β cells were higher ( P<0.05) than in WT mice, whereas the proportion of δ cells was lower ( P<0.01). In old Sur1 −/− mice, α cells were frequently located in the central regions of islets (unlike WT islets) and their proportion was increased ( P<0.05). Glut-2 protein and mRNA levels were lower in old Sur1 −/− islets ( P<0.02). Insulinaemia, fasting insulin and glucagon contents were equivalent in both groups of pancreata. Thus, the islets of Sur1 −/− mice present morphological modifications that have not been described in CHI and that might reflect an adaptive mechanism controlling insulin secretion in these mice. [ABSTRACT FROM AUTHOR]

An analysis of steganographic systems subject to the following perfect undetectability condition is presented in this paper. Following embedding of the message into the covertext, the resulting stegotext is required to have exactly the same probability distribution as the covertext. Then no statistical test can reliably detect the presence of the hidden message. We refer to such steganographic schemes as perfectly secure. A few such schemes have been proposed in recent literature, but they have vanishing rate. We prove that communication performance can potentially be vastly improved; specifically, our basic setup assumes independent and identically distributed (i.i.d.) covertext, and we construct perfectly secure steganographic codes from public watermarking codes using binning methods and randomized permutations of the code. The permutation is a secret key shared between encoder and decoder. We derive (positive) capacity and random-coding exponents for perfectly secure steganographic systems. The error exponents provide estimates of the code length required to achieve a target low error probability. In some applications, steganographic communication may be disrupted by an active warden, modeled here by a compound discrete memoryless channel (DMC). The transmitter and warden are subject to distortion constraints. We address the potential loss in communication performance due to the perfect-security requirement. This loss is the same as the loss obtained under a weaker order-1 steganographic requirement that would just require matching of first-order marginals of the covertext and stegotext distributions. Furthermore, no loss occurs if the covertext distribution is uniform and the distortion metric is cyclically symmetric; steganographic capacity is then achieved by randomized linear codes. Our framework may also be useful for developing computationally secure steganographic systems that have near-optimal communication performance. [ABSTRACT FROM AUTHOR]

Capacity formulas and random-coding exponents are derived for a generalized family of Gel'fand-Pinsker coding problems. These exponents yield asymptotic upper bounds on the achievable log probability of error. In our model, information is to be reliably transmitted through a noisy channel with finite input and output alphabets and random state sequence, and the channel is selected by a hypothetical adversary. Partial information about the state sequence is available to the encoder, adversary, and decoder. The design of the transmitter is subject to a cost constraint. Two families of channels are considered: 1) compound discrete memoryless channels (CDMC), and 2) channels with arbitrary memory, subject to an additive cost constraint, or more generally, to a hard constraint on the conditional type of the channel output given the input. Both problems are closely connected. The random-coding exponent is achieved using a stacked binning scheme and a maximum penalized mutual information decoder, which may be thought of as an empirical generalized maximum a posteriori decoder. For channels with arbitrary memory, the random-coding exponents are larger than their CDMC counterparts. Applications of this study include watermarking, data hiding, communication in presence of partially known interferers, and problems such as broadcast channels, all of which involve the fundamental idea of binning. [ABSTRACT FROM AUTHOR]

This paper derives fundamental performance bounds for statistical estimation of parametric surfaces embedded in R3. Unlike conventional pixel-based image reconstruction approaches, our problem is reconstruction of the shape of binary or homogeneous objects. The fundamental uncertainty of such estimation problems can be represented by global confidence regions, which facilitate geometric inference and optimization of the imaging system. Compared to our previous work on global confidence region analysis for curves [two-dimensional (2-D) shapes], computation of the probability that the entire surface estimate lies within the confidence region is more challenging because a surface estimate is an inhomogeneous random field continuously indexed by a 2-D variable. We derive an asymptotic lower bound to this probability by relating it to the exceedence probability of a higher dimensional Gaussian random field, which can, in turn, be evaluated using the tube formula due to Sun. Simulation results demonstrate the tightness of the resulting bound and the usefulness of the three-dimensional global confidence region approach. [ABSTRACT FROM AUTHOR]

The Karhunen-Loéve transform (KLT) is known to be optimal for high-rate transform coding of Gaussian vectors for both fixed-rate and variable-rate encoding. The KLT is also known to be suboptimal for some non-Gaussian models. This paper proves high-rate optimality of the KLT for variable-rate encoding of a broad class of non-Gaussian vectors: Gaussian vector-scale mixtures (GVSM), which extend the Gaussian scale mixture (GSM) model of natural signals. A key concavity property of the scalar GSM (same as the scalar GVSM) is derived to complete the proof. Optimality holds under a broad class of quadratic criteria, which include mean-squared error (MSE) as well as generalized f-divergence loss in estimation and binary classification systems. Finally, the theory is illustrated using two applications: signal estimation in multiplicative noise and joint optimization of classification/reconstruction systems. [ABSTRACT FROM AUTHOR]

Modulo lattice additive noise (MLAN) channels appear in the analysis of structured binning codes for Costa's dirty-paper channel and of nested lattice codes for the additive white Gaussian noise (AWGN) channel. In this paper, we derive a new lower bound on the error exponents of the MLAN channel. With a proper choice of the shaping lattice and the scaling parameter, the new lower bound coincides with the random-coding lower bound on the error exponents of the AWGN channel at the same signal-to-noise ratio (SNR) in the sphere-packing and straight-line regions. This result implies that, at least for rates close to channel capacity, 1) writing on dirty paper is as reliable as writing on clean paper; and 2) lattice encoding and decoding suffer no loss of error exponents relative to the optimal codes (with maximum-likelihood decoding) for the AWGN channel. [ABSTRACT FROM AUTHOR]

A broad set of sufficient conditions that guarantees the existence of the maximum entropy (maxent) distribution consistent with specified bounds on certain generalized moments is derived. Most results in the literature are either focused on the minimum cross-entropy distribution or apply only to distributions with a bounded-volume support or address only equality constraints. The results of this work hold for general moment inequality constraints for probability distributions with possibly unbounded support, and the technical conditions are explicitly on the underlying generalized moment functions. An analytical characterization of the maxent distribution is also derived using results from the theory of constrained optimization in infinite-dimensional norms linear spaces. Several auxiliary results of independent Interest pertaining to certain properties of convex coercive functions are also presented. [ABSTRACT FROM AUTHOR]

This paper develops a joint hashing/watermarking scheme in which a short hash of the host signal is available to a detector. Potential applications include content tracking on public networks and forensic identification. The host data into which the watermark is embedded are selected from a secret subset of the full-frame discrete cosine transform of an image, and the watermark is inserted through multiplicative embedding. The hash is a binary version of selected original image coefficients. We propose a maximum likelihood watermark detector based on a statistical image model. The availability of a hash as side information to the detector modifies the posterior distribution of the marked coefficients. We derive Chernoff bounds on the receiver operating characteristic performance of the detector. We show that host-signal interference can be rejected if the hash function is suitably designed. The relative difficulty of an eavesdropper's detection problem is also determined; the eavesdropper does not know the secret key used. Monte Carlo simulations are performed using photographic test images. Finally, various attacks on the watermarked image are introduced to study the robustness of the derived detectors. The joint hashing/watermarking scheme outperforms the traditional "hashless" watermarking technique. [ABSTRACT FROM AUTHOR]

Rates of reliable transmission of hidden information are derived for watermarking problems involving parallel Gaussian sources, which are often used to model host images and audio signals. Constraints are imposed on the average squared-error distortion that can be introduced by the information hider and by the attacker. When distortions are measured with respect to the original host data, the optimal covert and attack channels are two banks of Gaussian test channels. The solution to the watermarking game involves an optimal allocation of distortions by the information hider and by the attacker to the different channels. A fast algorithm is given for computing the optimal solution based on duality theory. For each channel, we derive analytical expressions for two asymptotic regimes: weak and strong host signals. Finally, we extend these results to the class of stationary Gaussian host signals with bounded, continuous spectral density. The analysis also provides an upper bound on watermarking capacity for non-Gaussian host signals. [ABSTRACT FROM AUTHOR]

Altered polarity and expression of H+ -ATPase without ultrastructural changes in kidneys of Dent's disease patients. Background. Dent's disease is a proximal tubule (PT) disorder characterized by low-molecular-weight proteinuria (LWMP) that may be associated with hypercalciuria, nephrocalcinosis, and renal failure. It is caused by inactivating mutations of the renal chloride channel ClC-5, which colocalizes with the vacuolar H+ -ATPase in PT cells and α-type intercalated cells. Examinations of knockout mice have established the role of ClC-5 in PT endocytosis, but the consequences of ClC-5 mutations on the polarity of H+ -ATPase and other plasma membrane proteins remain unknown. Methods. We have studied renal biopsies from eight patients with Dent's disease, due to inactivating ClC-5 mutations, by light and electron microscopy, and by immunohistochemical staining. All patients exhibited LMWP, and renal function ranged from normal to end-stage renal failure. Results. Light microscopy revealed either normal renal architecture or glomerulosclerosis, tubular dedifferentiation and atrophy, and mild interstitial fibrosis. Focal, hyaline casts, sometimes calcified, were identified at all stages. Electron microscopy did not reveal any ultrastructural abnormalities in PT cells, and the endocytic apparatus was apparently normal. However, immunohistochemical studies demonstrated a consistent inversion of H+ -ATPase polarity in PT cells to a basolateral distribution contrasting with its apical location in the normal kidney. This inversion of polarity was specific for H+ -ATPase and did not affect distribution of aminopeptidase, megalin, and Na+ /K+ -ATPase. Furthermore, apical H+ -ATPase expression was absent in α-type intercalated cells. Conclusion. ClC-5 mutations are associated with modifications in the polarity and expression of H+ -ATPase, but not... [ABSTRACT FROM AUTHOR]

This paper develops a game-theoretic methodology to design and embed M messages in signals and images in the presence of an adversary. Here, M is assumed to be subexponential in the signal's sample size (zero-rate transmission), and the embedding is done using spread-spectrum watermarking. The detector performs statistical hypothesis testing. The system is designed to minimize probability of error under the worst-case attack in a prescribed class of attacks. The variables in this game are probability distributions for the watermarker and attacker. Analytical solutions are derived under the assumption of Gaussian host vectors, watermarks and attacks, and squared-error distortion constraints for the watermarker and the attacker. The Karhunen-Lo&egamma;ve transform (KLT) plays a central role in this study. The optimal distributions for the watermarker and the attacker are Gaussian test channels applied to the KLT coefficients; the game is then reduced to a maxmin power-allocation problem between the channels. As a byproduct of this analysis, we can determine the optimal tradeoff between using the most efficient (in terms of detection performance) signal components for transmission and spreading the transmission across many components (to fool the attacker's attempts to eliminate the watermark). We also conclude that in this framework, additive watermarks are suboptimal; they are, however, nearly optimal in a small-distortion regime. The theory is applied to watermarking of autoregressive processes and to wavelet-based image watermarking. The optimal watermark design outperforms conventional designs based on heuristic power allocations and/or simple correlation detectors. [ABSTRACT FROM AUTHOR]

An information-theoretic analysis of information hiding is presented in this paper, forming the theoretical basis for design of information-hiding systems. Information hiding is an emerging research area which encompasses applications such as copyright protection for digital media, watermarking, fingerprinting, steganography, and data embedding. In these applications, information is hidden within a host data set and is to be reliably communicated to a receiver. The host data set is intentionally corrupted, but in a covert way, designed to be imperceptible to a casual analysis. Next, an attacker may seek to destroy this hidden information, and for this purpose, introduce additional distortion to the data set. Side information (in the form of cryptographic keys and/or information about the host signal) may be available to the information hider and to the decoder. We formalize these notions and evaluate the hiding capacity, which upper-bounds the rates of reliable transmission and quantifies the fundamental tradeoff between three quantities: the achievable information-hiding rates and the allowed distortion levels for the information hider and the attacker. The hiding capacity is the value of a game between the information hider and the attacker. The optimal attack strategy is the solution of a particular rate-distortion problem, and the optimal hiding strategy is the solution to a channel-coding problem. The hiding capacity is derived by extending the Gel'fand-Pinsker theory of communication with side information at the encoder. The extensions include the presence of distortion constraints, side information at the decoder, and unknown communication channel. Explicit formulas for capacity are given in several cases, including Bernoulli and Gaussian problems, as well as the important special case of small distortions. In some cases, including the last two above, the hiding capacity is the same whether or not the decoder knows the host data set. It is shown that... [ABSTRACT FROM AUTHOR]

In this papers we establish an equivalence between two conceptually different methods of signal estimation under modeling uncertainty viz. set-theoretic (ST) estimation and maximum entropy (maxent) MAP estimation. The first method assumes constraints on the signal to be estimated, and the second assumes constraints on a probability distribution for the signal. We provide broad conditions under which the two aforementioned estimation paradigms produce the same signal estimate. We also show how the maxent formalism can be used to provide solutions to three important problems: How to select sizes of constraint sets in ST estimation (the analysis highlights the role of shrinkage); how to choose the values of parameters in regularized restoration when using multiple regularization functionals; and how to trade off model complexity and goodness of fit in a model selection problem. [ABSTRACT FROM AUTHOR]

Details the derivation of information-theoretic bounds on the performance statistical object recognition systems. Geometric representation of probability sets and information distances; Performance bounds for tank imagery.

Evaluates the data-hiding capacity of image sources using an information-theoretic model. Construction of a hyper media document; Rejection of the host-signal interference at the decoder; Derivation of the fundamental limits on watermarking.

Presents an information-theoretic analysis of statistical dependencies between image wavelet coefficients. Formulation of the modeling problem in terms of mutual information; Illustration of concepts in the case of an AR-1 Gaussian image process; Information on reduced-order models.

Presents a study which examined an approach to image denoising based on complexity regularization. Overview of complexity-regularized denoising algorithms; Theoretical analysis; Experimental results.

Investigates the design of subband coders without the traditional perfect-reconstruction constraint on the filters. Subband coder model; Design criterion; Fundamental properties of optimal subband coder; Optimal filters for a given bit allocation.

Introduces a method that simultaneously preserves the benefits of higher-order interpolative schemes such as control grid interpolation (CGI). Block matching and CGI algorithms; Adaptive version of overlapped block motion compensation; Video-coding results comparing smoothness-adapted versus nonadapted motion-compensated prediction methods.

Presents a study which applied the complexity-regularization principle to statistical ill-posed inverse problems in imaging. Methodology; Results; Discussion.

Presents information on a study which analyzed the rate-distortion-optimal constrained filterbanks and its application to infinite impulse response (IIR) and finite IR biorthogonal designs. Properties of the filter banks; Conclusions.

Investigates various connections between shrinkage methods and Maximum A Posteriori estimation using Gaussian and complexity priors. Application of the Minimum Description Length principle; Development of analytical expressions implied by Gaussian distributions.

Presents information on a study that explored the application of signal-adapted filter banks to image coding. Information on the proposed coding paradigm to optimize rate-distortion (R/D) performance; Design of the codebook; Description of problem solving using a fast optimization algorithm; Conclusion.

Studies the design of signal-adapted far-infrared radiation paraunitary filter banks, using energy compaction as the adaptation criterion. Information on the semi-infinite problem (SIP); Discussion of the SIP algorithms; Numerical results of the SIP.

Considers the problem of designing a perfect reconstruction, quadrature-mirror filter (QMF) bank adapted to input signal statistics. Views on maximization of the coding gain; Theoretical analysis of the linear semi-infinite programming (SIP) problem; Application of discretization and cutting plane algorithms.

Presents a systematic approach to forward-motion-compensated predictive video coding. Definition of a flexible model which represents motion fields; How inhomogeneity and spatial coherence properties of motion fields are captured.

The article presents several case studies of a 24-year-old sub-Saharan woman, a 28-year-old Madagascan woman, and a 52-year-old Malaysian man who have Southeast Asian ovalocytosis (SAO) and who was taken to the North Hospital located in Marseilles, France. Blood tests showed no and mild anemia, corpuscular hemoglobin concentration, the width of red cell distribution thorough Advia2120i hematology analyzer. Blood smear examination found the poikilocytosis and anisocytosis with ovalocytes.

Comments on the characterization and risk analysis of penalized least square estimators in an article by leading mathematician Anestis Antoniadis regarding non-parametric wavelet regression. Characterization of penalized least square estimators; Comment on closely related work in the statistical signal and image processing literature; Risk analysis of penalized least squares.

Plant–herbivore interactions mediated by plant–plant signalling have been documented in different species but its within‐species variability has hardly been quantified. Here, we tested if herbivore foraging activity on plants was influenced by a prior contact with a damaged plant and if the effect of such plant–plant signalling was variable across 113 natural genotypes of Arabidopsis thaliana. We filmed the activity of the generalist herbivore Cornu aspersum during 1 h on two plants differing only in a prior contact with a damaged plant or not. We recorded each snails' first choice, and measured its first duration on a plant, the proportion of time spent on both plants and leaf consumption. Overall, plant–plant signalling modified the foraging activity of herbivores in A. thaliana. On average, snails spent more time and consumed more of plants that experienced a prior contact with a damaged plant. However, the effects of plant–plant signalling on snail behaviour was variable: depending on genotype identity, plant–plant signalling made undamaged plants more repellant or attractive to snails. Genome‐wide associations revealed that genes related to stress coping ability and jasmonate pathway were associated to this variation. Together, our findings highlight the adaptive significance of plant–plant signalling for plant–herbivore interactions. [ABSTRACT FROM AUTHOR]

The article discusses the IEEE Transactions on Information Forensics and Security (T-IFS) supplement featured within the publication.

This article presents information on the October 2004 issue of the IEEE Transactions on Signal Processing. This issue is the first among three supplements on secure media. It contains ten papers which covers a broad range of topics and were selected based on their high level of technical quality, mathematical rigor, significance and novelty. The topics include steganography, watermarking codes, temporal geometric robustness of video watermarks, cryptography for multimedia, performance analysis of biometric systems.

This paper presents a new approach to image-set-based face recognition, where each training and testing example is a set of face images captured from varying poses, illuminations, expressions, and resolutions. While a number of image set based face recognition methods have been proposed in recent years, most of them model each face image set as a single linear subspace or as the union of linear subspaces, which may lose some discriminative information for face image set representation. To address this shortcoming, we propose exploiting statistics information as feature representations for face image sets and develop a localized multikernel metric learning algorithm to effectively combine different statistics for recognition. Moreover, we propose a localized multikernel multimetric learning method to jointly learn multiple feature-specific distance metrics in the kernel spaces, one for each statistic feature, to better exploit complementary information for recognition. Our methods achieve state-of-the-art performance on four widely used video face datasets including the Honda, MoBo, YouTube Celebrities, and YouTube Face datasets. [ABSTRACT FROM AUTHOR]

The aim of this research is to understand how patients' characteristics increase healthcare providers' perceived workload. Patients ' characteristics and dependency, technical and relational complexities of care seem to increase healthcare providers' workload. As workload is multidimensional, we examine which dimensions are affected by patients' characteristics. Our methodology is based on 121 patients assessed with the NASA task load index (NASA-TLX) and a questionnaire filled in by 57 health providers in 2 emergency wards in French hospital settings, to evaluate their attitudes to different patients' characteristics. Our results show that physical demand is the dimension most affected by patients ' behaviour and characteristics. Next, we observe that workload increases more due to patients' behaviour than their social characteristics. We propose that a regulation mechanism be taken into account in further research, using methodology based on observations to identify how healthcare providers might adapt their activities to compensate for workload variations caused by patients. [ABSTRACT FROM AUTHOR]

Background/Aims: Endometrial cells are chronically exposed to iron due to cyclic menstrual bleeding. Iron induces expression of adhesion molecules in endothelial cells. The purpose of this study was to investigate iron incorporation by human endometrial cells and to test whether iron may stimulate expression of intercellular adhesion molecule (ICAM)-1 and vascular cell adhesion molecule (VCAM)-1. Methods: Endometrial stromal and epithelial cells were cultured in medium alone or supplemented with INF-γ or transferrin (Tf). Iron incorporation by cells was quantified by densitometry of ferritin immunostaining. ICAM-1 and VCAM-1 expression were evaluated at the transcriptional level by real-time RT-PCR. Membrane-bound and soluble protein levels of ICAM-1 were measured by quantitative immunohistochemistry and ELISA, respectively. Results: Tf induced a significant increase in ferritin immunostaining in both endometrial cell types. Endometrial cells treated with INF-γ expressed more ICAM-1 and VCAM-1 than untreated cells. By contrast, Tf treatment did not alter ICAM-1 and VCAM-1 expression in cultured endometrial cells. Conclusions: Endometrial cells are able to incorporate iron from Tf and to metabolize it to ferritin. Iron, unlike interferon-γ, does not appear to be involved in the regulation of ICAM-1 and VCAM-1 expression in cultured endometrial cells. Copyright © 2007 S. Karger AG, Basel [ABSTRACT FROM AUTHOR]

The contribution of Na+/H+ exchange (achieved by NHE proteins) to the regulation of β-cell cytosolic pHc, and the role of pHc changes in glucose-induced insulin secretion are disputed and were examined here. Using real-time PCR, we identified plasmalemmal NHE1 and intracellular NHE7 as the two most abundant NHE isoforms in mouse islets. We, therefore, compared insulin secretion, cytosolic free Ca2+ ([Ca2+]c) and pHc in islets from normal mice and mice bearing an inactivating mutation of NHE1 (Slc9A1-swe/swe). The experiments were performed in HCO-3/CO2 or HEPES/NaOH buffers. PCR and functional approaches showed that NHE1 mutant islets do not express compensatory pH-regulating mechanisms. NHE1 played a greater role than HCO-3-dependent mechanisms in the correction of an acidification imposed by a pulse of NH4Cl. In contrast, basal pHc (in low glucose) and the alkalinization produced by high glucose were independent of NHE1. Dimethylamiloride, a classic blocker of Na+/H+ exchange, did not affect pHc but increased insulin secretion in NHE1 mutant islets, indicating unspecific effects. In control islets, glucose similarly increased [Ca2+]c and insulin secretion in HCO-3 and HEPES buffer, although pHc changed in opposite directions. The amplification of insulin secretion that glucose produces when [Ca2+]c is clamped at an elevated level by KCl was also unrelated to pHc and pHc changes. All effects of glucose on [Ca2+]c and insulin secretion proved independent of NHE1. In conclusion, NHE1 protects -cells against strong acidification, but has no role in stimulus-secretion coupling. The changes in pHc produced by glucose involve HCO-3-dependent mechanisms. Variations in β-cell pHc are not causally related to changes in insulin secretion. [ABSTRACT FROM AUTHOR]

Defrère S, Van Langendonckt A, Moulin P, Befahy P, Gonzalez D, Martinez-Madrid B, Dolmans M-M, Donnez J. Human endometrial epithelial cells (EEC) constitutively express more intercellular adhesion molecule (ICAM)-1 than endometrial stromal cells (ESC) in culture. AJRI 2005; 54:5–12 © Blackwell Munksgaard, 2005 Intercellular adhesion molecule-1 (ICAM-1) is thought to play an important role in pathophysiological processes in endometrial tissue. The aim of this study was to quantify and compare the expression of ICAM-1 mRNA and protein in cultured endometrial epithelial cells (EEC) versus endometrial stromal cells (ESC). EEC and ESC were isolated from human endometrium and cultured. At confluency, ICAM-1 mRNA was measured by real-time reverse transcriptase-polymerase chain reaction, the membrane-bound form (mICAM-1) by immunocytodensitometry, and the soluble form (sICAM-1) by enzyme-linked immunosorbent assay. At the transcriptional level, we observed a 1.7-fold increase in ICAM-1 expression in EEC versus ESC. mICAM-1 immunostaining in EEC [cell-relative membrane-bound signal-specific optical density (CR-M-SOD): 0.056 ± 0.05] was stronger ( P < 0.05) than in ESC (CR-M-SOD: 0.009 ± 0.07). EEC were found to secrete more ( P < 0.01) sICAM-1 ([sICAM-1] = 15.59 ± 2.96 ng/mL) than ESC ([sICAM-1] = 5.14 ± 2.61 ng/mL). Cultured EEC constitutively express significantly more ICAM-1 mRNA and protein than ESC. [ABSTRACT FROM AUTHOR]

Background: Elevated plasma ghrelin levels have recently been reported in adults and children with Prader-Willi syndrome (PWS). The aim of the study is to investigate the relationship between obesity, growth hormone (GH) deficiency (GHD) and ghrelinemia in PWS and to examine whether hyperghrelinemia is specific to PWS. Methods: We measured fasting ghrelinemia in children with PWS, idiopathic GHD (iGHD), obese children, controls and in 6 children presenting another congenital syndrome associated with GHD: pituitary stalk interruption (PSI). Results: Children with PWS exhibited significantly higher ghrelin levels (995 pg/ml (801/1,099, median 1st/3rd quartile)) than iGHD (517 pg/ml (392/775)), obese (396 pg/ml (145/610)) and control (605 ng/ml (413/753)) children. Similar to PWS hyperghrelinemia was found in PSI children (1,029 pg/ml (705/1,151)), and was not modified by GH treatment. Conclusion: We conclude that hyperghrelinemia in PWS and PSI is not related to GH secretion. We hypothesize that a major site of ghrelin action is at the hypothalamic level and that a ‘ghrelin resistance’ syndrome may be present in these patients, primarily due to a hypothalamic defect. Combined alterations such as impaired serotonin receptor regulation associated with abnormal ghrelin responsiveness are probably responsible for obesity in PWS. Copyright © 2004 S. Karger AG, Basel [ABSTRACT FROM AUTHOR]

Objectives: The objective of this multicenter cross‐sectional study was to determine predictors of poor glycaemic control in children with type 1 diabetes mellitus (T1DM), particularly with respect to socioeconomic status (SES). Methods: Our study population consisted of 1154 children who attended T1DM follow‐up consultation with a pediatric diabetes specialist. Clinical and demographic data were retrieved retrospectively from patients' records. Individual deprivation was defined by an EPICES (Evaluation of the Deprivation and Inequalities of Health in Healthcare Centers) score ≥ 30. Patients were assigned to quintiles of the European Deprivation Index (EDI) based on their area deprivation scores. We used multivariable linear regression models to detect potential associations between glycaemic control and indicators of low SES. Results: In total, 33% (n = 376) of patients had an EPICES score ≥ 30 and 23% (n = 268) were in the 5th EDI quintile. Multivariable linear regression analysis showed that poor glycaemic control was associated with both individual (β 0.38; 95%CI 0.26–0.5; p < 0.001) and area deprivation (β 0.26; 95%CI 0.08–0.43; p = 0.004). Demographic factors, body mass index (BMI) and insulin regimen were also independently associated with poor glycaemic control (p < 0.001). Interestingly, access to diabetes technologies was not related to SES or either glycaemic control. Conclusion: Low SES is associated with a higher risk of poor glycaemic control, independently of insulin regimen. BMI, age at the time of consultation, duration of diabetes, and insulin regimen. Also have an impact on HbA1c. These parameters need to be considered when developing novel treatment strategies for children with T1DM to better target at‐risk patients. [ABSTRACT FROM AUTHOR]

Background: Aristolochic acid nephropathy (AAN) is a rapidly progressive interstitial nephropathy linked to the exposure to aristolochic acid (AA) and characterized by extensive fibrosis and urothelial atypia. Although the fibrotic process has been documented in extrarenal tissues, the involvement of the peritoneum, as well as the efficacy of peritoneal dialysis in AAN patients, remain uncertain.Methods: The structure of the peritoneal membrane and the expression of basic fibroblast growth factor (bFGF), collagen type III, endothelial nitric oxide synthase (eNOS), and aquaporin-1 (AQP1) were investigated in peritoneal biopsies from an index AAN patient, four other AAN patients, four regular peritoneal dialysis patients, and two controls. Similar methods were used to investigate a rabbit model of AAN after intraperitoneal exposure to high-dose AA. AA-DNA adducts were screened by 32P-postlabeling analysis.Results: The AAN patients had renal failure, renal fibrosis, and urothelial atypia. The peritoneum of AAN patients had a normal structure, lacked cellular atypia, and, in comparison with regular peritoneal dialysis patients and controls, did not show abnormal regulation of fibrotic and endothelial markers. Furthermore, specific AA-DNA adducts were not identified in the peritoneum of AAN patients. In contrast, AA-DNA adducts were detected in peritoneal and kidney tissues of all exposed rabbits, and one of them developed a malignant mesothelioma.Conclusion: These data demonstrate the lack of fibrotic and vascular alterations and the absence of cellular atypia in the peritoneum from AAN patients. Thus, peritoneal dialysis should not be discouraged in these patients. Nevertheless, studies in a rabbit model of high-dose AA exposure may suggest a potential risk of peritoneal malignancy. [ABSTRACT FROM AUTHOR]

We address the problem of computing fundamental performance bounds for estimation of object boundaries from noisy measurements in inverse problems, when the boundaries are parameterized by a finite number of unknown variables. Our model applies to multiple unknown objects, each with its own unknown gray level, or color, and boundary parameterization, on an arbitrary known background. While such fundamental bounds on the performance of shape estimation algorithms can in principle be derived from the Cramér-Rao lower bounds, very few results have been reported due to the difficulty of computing the derivatives of a functional with respect to shape deformation. In this paper, we provide a general formula for computing CramérRao lower bounds in inverse problems where the observations are related to the object by a general linear transform, followed by a possibly nonlinear and noisy measurement system. As an illustration, we derive explicit formulas for computed tomography, Fourier imaging, and deconvolution problems. The bounds reveal that highly accurate parametric reconstructions are possible in these examples, using severely limited and noisy data. [ABSTRACT FROM AUTHOR]

Presents methods for computing performance limits for two-dimensional parametric shape estimation in nonlinear inverse scattering problems with an application to passive radar imaging. Analysis for nonlinear inverse scattering problems using Cramer-Rao lower bounds; Use of normalized Fourier descriptors for boundary parameterization; Extension of the global confidence region analysis using transverse electric polarized incident plane waves.