Miracle-dz/UniFAR-FTUs huggingface dataset:
Pattern Coding Meets Censoring: (almost) Adaptive Coding on Countable Alphabets

Adaptive coding faces the following problem: given a collection of source classes such that each class in the collection has non-trivial minimax redundancy rate, can we design a single code which is asymptotically minimax over each class in the collection? In particular, adaptive coding makes sense when there is no universal code on the union of classes in the collection. In this paper, we deal with classes of sources over an infinite alphabet, that are characterized by a dominating envelope. We provide asymptotic equivalents for the redundancy of envelope classes enjoying a regular variation property. We finally construct a computationally efficient online prefix code, which interleaves the encoding of the so-called pattern of the message and the encoding of the dictionary of discovered symbols. This code is shown to be adaptive, within a loglogn factor, over the collection of regularly varying envelope classes. The code is both simpler and less redundant than previously described contenders. In contrast with previous attempts, it also covers the full range of slowly varying envelope classes.
Monolithic high power mode locked GaAs/AlGaAs quantum well lasers

In this thesis, approaches for increasing the output power in monolithically integrated semiconductor mode locked (ML) lasers were investigated. The wavelength range considered is the range of operation of low temperature grown GaAs photomixers, devices commonly used for THz generation. In particular, two GaAs/AlGaAs quantum well laser epistructures (operating at 830 nm and 795 nm) were considered, both with reduced optical confinement and elongated vertical optical mode size. In this work, such laser epistructures, commonly used by high power semiconductor laser manufacturers, were successfully employed, for the first time, for producing passively ML devices. Improved average powers (up to 48 mW) under ML operation were demonstrated, around ten times higher than values previously reported in monolithic GaAs/AlGaAs ML lasers. In continuous wave operation, the output power was limited by the catastrophic damage of the laser facets at around 50 mW. For this reason, facet passivation techniques were investigated, allowing for powers up to 124 mW to be achieved. In ML regime, the output power was instead limited by the catastrophic damage of the reverse biased section of the laser. This failure mechanism was investigated and explained considering thermal effects on the reverse biased section. Such effects limited the output power to around 27 mW in 830 nm devices, which was then improved by 70% in 795 nm devices with a 70% larger optical mode area. The larger mode size, combined to a small duty-cycle laser geometry, enabled a record peak power of 9.8 W to be achieved at 6.83 GHz. This particular repetition rate was specifically designed for coherent population trapping experiments in 87Rb vapors. Sub-picosecond transform limited pulses were achieved in both the laser materials considered, with a minimum duration of 0.43 ps at 126 GHz. With the values of peak power achieved, the developed devices may also be directly used for two-photon microscopy applications.
Pro-Angiogenic Effects of Chalcone Derivatives in Zebrafish Embryos in Vivo

The aim of this study was to investigate novel chalcones with potent angiogenic activities in vivo. Chalcone-based derivatives were evaluated using a transgenic zebrafish line with fluorescent vessels to real-time monitor the effect on angiogenesis. Results showed that the chalcone analogues did not possess anti-angiogenic effect on zebrafish vasculatures; instead, some of them displayed potent pro-angiogenic effects on the formation of the sub-intestinal vein. Similar pro-angiogenic effects can also be seen on wild type zebrafish embryos. Moreover, the expression of vegfa, the major regulator for angiogenesis, was also upregulated in their treatment. Taken together, we have synthesized and identified a series of novel chalcone-based derivatives as potent in vivo pro-angiogenic compounds. These novel compounds hold potential for therapeutic angiogenesis.
Acidic Digestion in a Teleost: Postprandial and Circadian Pattern of Gastric pH, Pepsin Activity, and Pepsinogen and Proton Pump mRNAs Expression

Two different modes for regulation of stomach acid secretion have been described in vertebrates. Some species exhibit a continuous acid secretion maintaining a low gastric pH during fasting. Others, as some teleosts, maintain a neutral gastric pH during fasting while the hydrochloric acid is released only after the ingestion of a meal. Those different patterns seem to be closely related to specific feeding habits. However, our recent observations suggest that this acidification pattern could be modified by changes in daily feeding frequency and time schedule. The aim of this study was to advance in understanding the regulation mechanisms of stomach digestion and pattern of acid secretion in teleost fish. We have examined the postprandial pattern of gastric pH, pepsin activity, and mRNA expression for pepsinogen and proton pump in white seabream juveniles maintained under a light/dark 12/12 hours cycle and receiving only one morning meal. The pepsin activity was analyzed according to the standard protocol buffering at pH 2 and using the actual pH measured in the stomach. The results show how the enzyme precursor is permanently available while the hydrochloric acid, which activates the zymogen fraction, is secreted just after the ingestion of food. Results also reveal that analytical protocol at pH 2 notably overestimates true pepsin activity in fish stomach. The expression of the mRNA encoding pepsinogen and proton pump exhibited almost parallel patterns, with notable increases during the darkness period and sharp decreases just before the morning meal. These results indicate that white seabream uses the resting hours for recovering the mRNA stock that will be quickly used during the feeding process. Our data clearly shows that both daily illumination pattern and feeding time are involved at different level in the regulation of the secretion of digestive juices.
Direct live imaging of cell–cell protein transfer by transient outer membrane fusion in Myxococcus xanthus

In bacteria, multicellular behaviors are regulated by cell–cell signaling through the exchange of both diffusible and contact-dependent signals. In a multicellular context, Myxococcus cells can share outer membrane (OM) materials by an unknown mechanism involving the traAB genes and gliding motility. Using live imaging, we show for the first time that transient contacts between two cells are sufficient to transfer OM materials, proteins and lipids, at high efficiency. Transfer was associated with the formation of dynamic OM tubes, strongly suggesting that transfer results from the local fusion of the OMs of two transferring cells. Last, large amounts of OM materials were released in slime trails deposited by gliding cells. Since cells tend to follow trails laid by other cells, slime-driven OM material exchange may be an important stigmergic regulation of Myxococcus social behaviors. DOI: http://dx.doi. org/10.7554/eLife.00868. 001
A model and regularization scheme for ultrasonic beamforming clutter reduction

Acoustic clutter produced by off-axis and multipath scattering is known to cause image degradation, and in some cases these sources may be the prime determinants of in vivo image quality. We have previously shown some success addressing these sources of image degradation by modeling the aperture domain signal from different sources of clutter, and then decomposing aperture domain data using the modeled sources. Our previous model had some shortcomings including model mismatch and failure to recover B-Mode speckle statistics. These shortcomings are addressed here by developing a better model and by using a general regularization approach appropriate for the model and data. We present results with L1 (lasso), L2 (ridge), and L1/L2 combined (elastic-net) regularization methods. We call our new method aperture domain model image reconstruction (ADMIRE). Our results demonstrate that ADMIRE with L1 regularization, or weighted toward L1 in the case of elastic-net regularization, have improved image quality. L1 by itself works well, but additional improvements are seen with elastic-net regularization over the pure L1 constraint. On in vivo example cases, L1 regularization showed mean contrast improvements of 4.6 and 6.8 dB on fundamental and harmonic images, respectively. Elastic net regularization (α = 0.9) showed mean contrast improvements of 17.8 dB on fundamental images and 11.8 dB on harmonic images. We also demonstrate that in uncluttered Field II simulations the de-cluttering algorithm produces the same contrast, contrast-to-noise ratio, and speckle SNR as normal B-mode imaging, demonstrating that ADMIRE preserves typical image features.
Contributions to the functional neuroanatomy of morphosyntactic processing in L2

Studies about bilingualism and second language acquisition (SLA) have a long tradition within linguistic and psycholinguistic research. With the global population becoming more and more multilingual and the recent proliferation of research in cognitive neuroscience, an increasing number of studies examining the way our brain is able to learn, represent, and handle more than one language at the same time are currently available. However, few attempts have been made to transpose psycholinguistic models of SLA into functional neuroanatomic models. An important problem that arises when pursuing this goal is partially due to the delay in the development of cognitive neuroscience of language compared to psycholinguistics. In general, neurolinguistic models focus on very broad and general questions about bilingualism, whereas psycholinguistic research is already at the stage of addressing more specific and fine-tuned questions. This Granularity Mismatch Problem (Poeppel & Embick, 2005) in the degree of zooming into this research topic is not exclusive of L2 research, but it is present in language research in general (Hauser & Bever, 2008). In either case, it often becomes difficult to put together the results from these different perspectives into one integrated model.
On Shephard groups with large triangles

Abstract Shephard groups are common extensions of Artin and Coxeter groups. They appear, for example, in algebraic study of manifolds. An infinite family of Shephard groups which are not Artin or Coxeter groups is considered. Using techniques form small cancellation theory we show that the groups in this family are bi-automatic.
Feature ensemble learning based on sparse autoencoders for image classification

Deep networks are well known for their powerful function approximations. To train a deep network efficiently, greedy layer-wise pre-training and fine tuning are required. Typically, pre-training, aiming to initialize a deep network, is implemented via unsupervised feature learning, with multiple feature representations generated. However, in general only the last layer representation is to be employed because of its abstraction and compactness being the best with comparisons to the ones of lower layers. To make full use of the representations of all layers, this paper proposes a feature ensemble learning method based on sparse autoencoders for image classification. Specifically, we train three softmax classifiers by using the representations of different layers, instead of one classifier trained by applying the last layer representation. Of the three softmax classifiers, two are obtained by training stacked autoencoders with fine tuning, and the other one is obtained by directly using a concatenation of two representations. To improve accuracy and stability of a single softmax classifier, the ensemble of multiple classifiers is considered, and some Naive Bayes combination rules are introduced to integrate the three classifiers. Experimental results on the MNTST and COIL datasets are presented, with comparisons to other classification methods.
Higher frequency band beamforming scheme for high speed train

With the increasing popularity of high speed trains (HSTs) and the traffic forecast for future cellular networks, the need to provide very high data rates using higher frequency bands (HFBs) for train passengers is becoming crucial. In this paper, we present a timer-based beamforming selection algorithm for HST, which exploits the prior knowledge of the position and direction of the HST. A sequential and hierarchical codebook is designed based on the array response vectors and linked to the line-of-sight (LOS) angle-of-arrival/departure base station (BS)-HST link. The effect of velocity feedback errors on the throughput performance was analyzed. The antenna deactivation and the sub-array approaches were considered to mitigate the effect of velocity feedback errors. Evaluation of our proposed beamforming scheme indicates a close performance to the optimal singular value decomposition (SVD) scheme when no velocity feedback error occurs and with the occurrence of velocity feedback errors, the sub-array approach proved to be an efficient way to reduce the effect of the errors.
Post-prandial glucose levels and consumption of omega 3 fatty acids and saturated fats among two rural populations in Kenya.

BACKGROUND Amount and quality of dietary fat modifies glucose tolerance. Omega 3 Fatty Acids (n-3F A) are polyunsaturated fats, mainly eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) found primarily in fish and they have a positive effect on glucose tolerance. OBJECTIVE To compare risk of type 2 diabetes mellitus (T2DM), as demonstrated thourough impaired glucose tolerance (IGT), and n-3FA intake among two rural populations. DESIGN A descriptive, cross-sectional comparative study. SETTING Bondo District (Luo Community) and Kericho District (Kipsigis Community) of the Lake Victoria basin of Kenya. SUBJECTS Sample of 150 individuals, aged above 18 years was randomly selected from each of the two communities. INTERVENTIONS Impaired glucose tolerance (IGT) was measured according to World Health Organisation diagnostic criteria. The intake of n-3FA was determined using a 24 hour dietary recall and food frequency schedule. Data was analysed using SPSS and Pearson Correlation Coefficient was used to test correlation between n-3FA consumption and IGT. The inter-group comparisons were done using the t-test and analysis of variance. RESULTS The prevalence of IGT was 11.8% among the Kipsigis and 4.8% among the Luo (P<0.001). The mean EPA and DHA intake was found to be 0.29 g/day and 0.34 g/day respectively among the Luo and 0.01 g/day and 0.01 g/day among the Kipsigis (P<0.001). The relationship between 2 hour post-prandial glucose level and consumption of DHA was (r=-0.111, p<0.05), EPA (r=-0.123, p<0.05), polyunsaturated fatty acids (r=-0.128, p<0.05) and saturated fats (r=-0.002, p=0.973). CONCLUSION The levels of IGT were significantly lower (P<0.001) among the Luo, than among the Kipsigis. There was also evidence of significant inverse relationship between IGT and consumption of n-3FA and polyunsaturated fatty acids (PUFA) but no association between saturated fats intake and IGT. The saturated fat ingested did not affect the level of post-prandial glucose. The Luo who consumed higher n-3FA amounts, recorded lower levels of IGT than the Kipsigis who had significantly lower consumption. RECOMMENDATIONS Effective screening methods should be used at the existing health units to determine risk factors of type 2 diabetes mellitus like IGT among patients. This could help in advising them accordingly on lifestyle changes, especially concerning diet and beneficial fats.
Wheel slippage and sinkage detection for planetary rovers

Mobile robots are increasingly being used in high-risk rough terrain situations, such as planetary exploration and military applications. Current control and localization algorithms are not well suited to rough terrain, since they generally do not consider the physical characteristics of the vehicle and its environment. Little attention has been devoted to the study of the dynamic effects occurring at the wheel-terrain interface, such as slip and sinkage. These effects compromise odometry accuracy, traction performance, and may even result in entrapment and consequent mission failure. This paper describes methods for wheel slippage and sinkage detection aiming at improving vehicle mobility on soft sandy terrain. Novel measures for wheel slip detection are presented based on observing different onboard sensor modalities and defining deterministic conditions that indicate vehicle slippage. An innovative vision-based algorithm for wheel sinkage estimation is discussed based on edge detection strategy. Experimental results, obtained with a Mars rover-type robot operating in high-slippage sandy environments and with a wheel sinkage testbed, are presented to validate our approach. It is shown that these techniques are effective in detecting wheel slip and sinkage.
Signal and Image Denoising via Wavelet Thresholding: Orthogonal and Biorthogonal, Scalar and Multiple Wavelet Transforms

The method of signal denoising via wavelet thresholding was popularised by Donoho and Johnstone (1994, 1995) and is now widely applied in science and engineering. It is based on thresholding of wavelet coefficients arising from the standard scalar orthogonal discrete wavelet transform (DWT). Recently this approach has been extended to incorporate thresholding coefficients arising from the discrete multiple wavelet transform (DMWT). Complications are introduced by the fact that non-orthogonal prefilters are required before the DMWT. Strela et al. (1999) applied scalar thresholding to the output from the Geronimo et al. (1994) DMWT with prefiltering, while Downie and Silverman (1998) gave a multivariate thresholding approach which takes account of the correlation in the DMWT coefficients induced by the prefiltering. In this paper we study wavelet thresholding in the context of scalar orthogonal, scalar biorthogonal, multiple orthogonal and multiple biorthogonal wavelet transforms. Two types of multiwavelet thresholding are considered: scalar and vector. Both of them take into account the covariance structure of the transform. The form of the universal threshold is carefully formulated and is the key to the excellent results obtained in the extensive numerical simulations of signal and image denoising reported here. Sections 2 to 5 are concerned with the deterministic formulation of relevant components of multiwavelet analysis. In Section 2 we give a summary of multiresolution analysis and semi-orthogonal, orthogonal and biorthogonal multiwavelet functions. The rest of the paper concentrates on the most-used practical cases of multiplicity 1 (scalar) and 2 (two scaling functions). Section 3 introduces two classes of orthogonal multiwavelets which may be used in multifilter banks — the Geronimo-Hardin-Massopust (GHM) and Chui-Lian (CL) classes, while Section 4 discusses biorthogonal multifilter banks, denoted BiGHM and BiHermite. For multifilter banks the given scalar input signal must be associated with a sequence of length-2 vectors: oversampling and critical sampling preprocessing is carefully studied in Section 5.
COMPARISON OF EM ALGORITHM WITH A GUASSIAN MULTIRESOLUTION ALGORITHM FOR MRI SEGMENTATION

Segmentation of anatomical regions of brain is fundamental problem in medical image analysis. In general, segmentation is process in which object is divided into its constituents parts. In this paper, MRI of brain is divided into its constituent's parts which may be used for medical diagnosis purpose. Consequently we used statistical approach to segment the brain image. Using this approach, we proved Gaussian multiresolution algorithm gives better result than EM algorithm under the variance. We know that EM algorithm fails to utilize the strong spatial correlation between pixels but this drawback is eliminated by combining Gaussian multiresolution algorithm with the EM algorithm. Finally Gaussian multiresolution EM algorithm displays the high powerful technique which keeps the advantage of EM algorithm and remove the drawback of EM algorithm.
Antibody-dependent cell-mediated cytotoxicity in the Moloney sarcoma virus system: differential activity of IgG and IgM with different subpopulations of lymphocytes

Antibody-dependent cell-mediated cytotoxicity in the Moloney sarcoma virus (MSV) system was evaluated in terms of the differential ability of IgG and IgM from MSV regressor animals to induce cytotoxicity by lymphocytes from lymph node, spleen, and thymus. The cell-mediated cytotoxicity induced by both IgM and IgG was specific for target possessing the appropriate virally determined cell surface antigen(s). IgM induced cytotoxicity by lymphocytes from all the organs tested. However, differences in magnitude and efficiency were revealed. Lymph node cells and thymocytes were most efficient against IgM-coated target cells. Against IgG-sensitized target cells, spleen and lymph node cells were about equally active, but thymocytes were inactive. Cortisone treatment of the donors of effector cells revealed that the cortisone resistant subpopulation of thymocytes, 2 days after cortisone injection, exhibited an increased cytotoxicity against target cells treated with unfractionated antiserum and its IgM fraction. This subpopulation of thymocytes was also cytotoxic against IgG-coated target cells. At 12 days after cortisone injection, the repopulated thymus showed little change in activity, compared to control thymus, against antibody-coated target cells.
Structured Identification of Reduced-Order Models of Power Systems in a Differential-Algebraic Form

In a recent paper, we proposed a system identification method for constructing reduced-order models for the electro-mechanical dynamics of large power systems, divided into multiple coherent clusters, using Synchrophasors. Every cluster in the actual model was represented as an aggregate generator in the reduced-order model. An aggregate network graph connected one aggregate generator to another. In this paper, we extend this identification approach to differential-algebraic (DAE) models. First, every cluster is associated with a unique terminal bus, referred to as the pilot bus, that couples its internal network to the rest of the system. The proposed algorithm uses Synchrophasor measurements from the pilot buses to identify the dynamic model of the aggregate generator for each cluster using nonlinear least squares while retaining the identity of all the pilot buses. The resulting reduced-order model is in the form of a nonlinear electric circuit described by aggregate differential and algebraic equations. We illustrate our results using two case studies, one for the IEEE 9-bus power system and another for the IEEE 39-bus power system. We also discuss how these reduced-order DAE models may be useful for designing shunt controllers at the pilot buses by using Synchrophasor feedback.
A String Motivated Approach to the Relativistic Point Particle

Using concepts developed in string theory, Cohen, Moore, Nelson and Polchinski calculated the propagator for a relativistic point particle. Following these authors we extend the technique to include the case of closed world lines. The partition function found corresponds to the Feynmann and Schwinger proper time formalism. We also explicitly verify that the partition function is equivalent to the usual path length action partition function. As an example of a sum over closed world lines, we compute the Euler-Heisenberg effective Lagrangian in a novel way.