Miracle-dz/UniFAR-FTUs huggingface dataset:
Regularized wavelength average velocity estimator for quantitative ultrasound elastography

Crawling Wave Sonoelastography (CWS) provides quantitative information of tissue stiffness by the application of two mechanical vibrations into the tissue. However, most of the shear wave speed (SWS) estimators for CWS report lateral artifacts that could undermine the detection accuracy of lesion by increasing the false-positive rate. In previous works, a low-cost estimator (WAVE) based on the crawling wave spatial wavelength (CSPW) averaging along the slow-time domain was proposed, where an underestimation in stiffer inclusions with size smaller than the CSPW was reported. In this study, an improved estimator is developed from the linear model of the CSPW function and solved with an implementation of generalized Tikhonov regularization. Experiments with inclusion phantoms demonstrate that the new estimator copes with the underestimation of WAVE while increase lateral resolution and contrast-to-noise ratio in comparison with other estimators found in the literature.
Uncertainty Quantification in Graph-Based Classification of High Dimensional Data

Classification of high dimensional data finds wide-ranging applications. In many of these applications equipping the resulting classification with a measure of uncertainty may be as important as the classification itself. In this paper we introduce, develop algorithms for, and investigate the properties of a variety of Bayesian models for the task of binary classification; via the posterior distribution on the classification labels, these methods automatically give measures of uncertainty. The methods are all based on the graph formulation of semisupervised learning. We provide a unified framework which brings together a variety of methods that have been introduced in different communities within the mathematical sciences. We study probit classification [C. K. Williams and C. E. Rasmussen, “Gaussian Processes for Regression,” in Advances in Neural Information Processing Systems 8, MIT Press, 1996, pp. 514--520] in the graph-based setting, generalize the level-set method for Bayesian inverse problems [M. A. Iglesias, Y. Lu, and A. M. Stuart, Interfaces Free Bound. , 18 (2016), pp. 181--217] to the classification setting, and generalize the Ginzburg--Landau optimization-based classifier [A. L. Bertozzi and A. Flenner, Multiscale Model. Simul. , 10 (2012), pp. 1090--1118], [Y. Van Gennip and A. L. Bertozzi, Adv. Differential Equations, 17 (2012), pp. 1115--1180] to a Bayesian setting. We also show that the probit and level-set approaches are natural relaxations of the harmonic function approach introduced in [X. Zhu et al., “Semi-supervised Learning Using Gaussian Fields and Harmonic Functions,” in ICML, Vol. 3, 2003, pp. 912--919]. We introduce efficient numerical methods, suited to large datasets, for both MCMC-based sampling and gradient-based MAP estimation. Through numerical experiments we study classification accuracy and uncertainty quantification for our models; these experiments showcase a suite of datasets commonly used to evaluate graph-based semisupervised learning algorithms.
Safe Motion Planning for Autonomous Driving

Self-driving cars have the potential to revolutionize transportation by making it cheaper, safer, and more efficient. In this thesis we describe a novel motion planning system, which translates high-level navigation goals into low-level actions for controlling a vehicle. Specifically, the motion planning system is responsible for choosing at each time step an appropriate velocity and steering angle, which can then be implemented by the driving hardware or simulator. Our planner is able to compute a safe and efficient trajectory in a dynamic environment while staying within its lane and avoiding obstacles. The planner works as follows: given a road map represented as a graph, an incremental heuristic search method is used to generate an optimal path. A section of this path nearest to the agent is smoothed using spline techniques to generate an arclength parameterized reference path for the agent to follow. A two-level hierarchical state space is produced that encompasses the various possible choices of steering angle. Using a vehicle motion model, the future positions of the car are determined for each action. Those actions that lead to invalid states (those that bring the agent in contact with an obstacle or out of its lane) are ruled out, and the action cost for each state is computed according to its path-following behavior. Finally, the action that leads to the lowest cost state is chosen and executed. The planner was implemented in simulation and tested in various driving scenarios with results comparable or better to those produced by other motion planning systems in terms of speed, safety, path-following behavior and comfort.
Tree Species with Photosynthetic Stems Have Greater Nighttime Sap Flux

An increasing body of evidence has shown that nighttime sap flux occurs in most plants, but the physiological implications and regulatory mechanism are poorly known. The significance of corticular photosynthesis has received much attention during the last decade, however, the knowledge of the relationship between corticular photosynthesis and nocturnal stem sap flow is limited at present. In this study, we divided seven tree species into two groups according to different photosynthetic capabilities: trees of species with (Castanopsis hystrix, Michelia macclurei, Eucalyptus citriodora, and Eucalyptus grandis × urophylla) and without (Castanopsis fissa, Schima superba, and Acacia auriculiformis) photosynthetic stems, and the sap flux (Js) and chlorophyll fluorescence parameters for these species were measured. One-way ANOVA analysis showed that the Fv/Fm (Maximum photochemical quantum yield of PSII) and ΦPSII (effective photochemical quantum yield of PSII) values were lower in non-photosynthetic stem species compared to photosynthetic stem species. The linear regression analysis showed that Js,d (daytime sap flux) and Js,n (nighttime sap flux) of non-photosynthetic stem species was 87.7 and 60.9% of the stem photosynthetic species. Furthermore, for a given daytime transpiration water loss, total nighttime sap flux was higher in species with photosynthetic stems (SlopeSMA = 2.680) than in non-photosynthetic stems species (SlopeSMA = 1.943). These results mean that stem corticular photosynthesis has a possible effect on the nighttime water flow, highlighting the important eco-physiological relationship between nighttime sap flux and corticular photosynthesis.
Hemolytic Uremic Syndrome in Post-Infectious Glomerulonephritis: Possible Pathophysiological Mechanisms

Malignant hypertension is able to induce glomerular Thrombotic Microangiopathy (TMA) and Hemolytic Uremic Syndrome (HUS) in the absence of Glomerulonephritis (GN). It is therefore commonly admitted that hypertension is the only cause of Glomerular Endothelial Cells (GEC) damage leading to TMA and HUS observed in GN. However, recent literature on TMA in IgA nephropathy calls this hypothesis into question. It is also questionable why so few cases of HUS are reported in association with Post-Infectious GN (PIGN) for which more than 50% of cases necessitate anti-hypertension treatment, we report the case of a 10 years old girl presenting with an extensive cutaneous streptococcal infection, hematuria, nephrotic syndrome, hypertension (146/106) and HUS needing dialysis. The kidney biopsy revealed a severe exudative GN, 30% of crescentic glomeruli and TMA. Immunofluorescence and electron microscopy suggested intense complement activation at the basal level of GEC and podocytes. Genotyping of complement factors was normal. A rapid recovery of a normal renal function was observed after intensive Plasma Exchange (PE) therapy. We speculate that a high amount of group A streptococcal (GAS) toxins produced in extensive cutaneous lesions might have facilitated TMA initiation by: 1/ a direct damage of endothelial cells; 2/ an intense complement activation induced by the binding of GAS toxins to the complement factor H (CFH), leading to GEC and podocytes’ lesions. The favorable effect of PE can be explained by removal of GAS toxins and inactivated CFH on one side and by supply of free CFH on another side. Multicentre studies should be initiated in order to evaluate the frequency and the pathophysiology of TMA and HUS in PIGN.
Formulation of nimesulide floating microparticles using low-viscosity hydroxypropyl methylcellulose.

Purpose: To formulate prolonged-release floating microparticles that would minimise the irritant effect of weakly acidic drugs, such as nimesulide, on the stomach by avoiding direct contact with gastric mucosa. Methods: Sustained release floating microparticles of nimesulide was prepared by a coacervation (nonsolvent addition technique. Three different ratios of the coacervating polymer, low-viscosity hydroxypropyl methylcellulose (HPMC), were used, and the dissolution characteristics of the floating microparticles in simulated gastric and intestinal media were evaluated. In order to determine whether there was drug – polymer interaction, the microparticles were also assessed by infra-red (FTIR) spectroscopy and x-ray diffraction (XRD). Micromeritic properties of the microparticles were also assessed. Results: The drug content of the floating microparticles increased with increase in the level of HPMC incorporated. All floating microparticles formulations showed good flow properties while particle size analysis revealed that the appearance and size distribution of the formulations varied with polymer concentration. FTIR and XRD data indicated the crystalline nature of the drug but there was no chemical interaction between the drug and the polymer in the microparticles. Nimesulide release was faster in simulated intestinal fluid (pH 6.8) than in simulated gastric fluid (pH 1.2) and distilled water (pH 6.5). Conclusion: Coacervation non-solvent addition is a suitable technique for preparing floating microparticles of nimesulide using low-viscosity HPMC.
Classification of forearm movements from sEMG time domain features using machine learning algorithms

Surface electromyography (sEMG) signal is one of the best choices for building human machine interfaces due to its non-invasive nature and ease of capturing. The proposed work aims at classifying the pronation and supination movements of the forearm. The primary actuators of these movements are located in the forearm whereas upper arm muscles provide assistance. Instead of forearm muscles, upper arm muscles namely biceps brachii and triceps brachii are chosen for sEMG signal collection. This makes it suitable for the development of an arm orthosis even if the person has a below elbow amputation. Features extracted from the pre-processed sEMG are used as predictors for machine learning (ML) algorithms. Multilayer perceptron neural network (MLPNN) and random forest (RF) are the machine learning algorithms addressed in this work. Each feature is used individually to train MLPNN to distinguish between pronation and supination. Two features namely IEMG (Integrated EMG) and SSC (Number of Slope Sign changes) were chosen as best predictors from experimentation. These two features were used together for prediction but the improvement was not satisfactory. Effects of using delayed inputs were studied, and it improved the classification by a considerable margin. RF model was then trained with the same predictor set, and it outperformed MLPNN. The average classification accuracy for MLPNN was 91.6%, and that of RF was 97.7%.
Incidence and outcome of ventilator-associated pneumonia in Inkosi Albert Luthuli and King Edward VIII Hospital surgical intensive care units

Background. Ventilator-associated pneumonia (VAP) is one of the most common causes of hospital morbidity and mortality, but has been poorly studied in the South African context. Objective. To evaluate the incidence and outcome of VAP in the intensive care units (ICUs) of two major centres in the Durban metropolitan area. Methods. The study was conducted over a period of 6 months with all intubated and mechanically ventilated patients who were screened on admission to ICU. A questionnaire was prepared to note patients’ age, gender, date and time of intubation or reintubation. Patients were monitored from date of admission to the date of discharge from ICU or death. A diagnosis of VAP was made on a clinical pulmonary infection score (CPIS) of ≥6. Results. Of 32 patients evaluated, eight patients (25%) were diagnosed with VAP. Median duration of ventilation in the VAP group was 249 hours v. 65.5 hours in the non-VAP group ( p =0.0002). We found no statistically significant association between age or gender with the development of VAP ( p =0.28 and p =0.59, respectively). The most common organism isolated was Acinetobacter baumannii , followed by Pseudomonas aeruginosa . Three of the eight (37.5%) patients diagnosed with VAP died in the ICU. Conclusion. VAP is common in critically ill patients, possibly associated with poor outcome. These results highlight the need for strict adherence to evidence-based preventive measures.
Velocity correlation in flocking with different motion model robots

Most of robotic systems introduce a directionless neighborhood area, such as a circle or sphere, for robot communication and interaction because it reflects a natural property of some physical sensors and devices. On the other hand, it has reported that some of natural birds employ directional neighborhood for neighbor observation. In this paper, we introduce the directional neighbor to a robotic swarm system, and we investigate how it affects to the connectivity and stability of the system.
TEACHING AND LEARNING PRODUCTION AND OPERATIONS MANAGEMENT: the journey from identity crisis to a cross-disciplinary approach

This ar ticle has its roots in a number of issues concerning the “form” and “content” of what we, professors, teach in the area of Production and Operations Management (POM). First, I will describe the historical evolution of this field. Following, I will discuss the identity crisis that the field is undergoing. In an attempt to provide an answer to this situation, I will present six proposals for the development and consolidation of POM. Finally, I will describe a practical initiative, involving one specific POM discipline, taught to graduate students. This initiative emphasizes the “content dimension” (technical-operational approach to strategic-managerial approach), as well as the “form dimension” (focus on teaching to focus on learning). The success of this ongoing experience confirms that the proposed agenda is coherent and deserves further development.
Conditional generation of sub-Poissonian light from two-mode squeezed vacuum via balanced homodyne detection on idler mode

A simple scheme for conditional generation of nonclassical light with sub-Poissonian photon-number statistics is proposed. The method utilizes entanglement of signal and idler modes in two-mode squeezed vacuum state generated in optical parametric amplifier. A quadrature component of the idler mode is measured in balanced homodyne detector and only those experimental runs where the absolute value of the measured quadrature is higher than certain threshold are accepted. If the threshold is large enough then the conditional output state of signal mode exhibits reduction of photon-number fluctuations below the coherent-state level.
Numerical Performances of Absorbing Boundary Conditions for ADI-FDTD Method

In this paper, the numerical performances of the Mur's first order and perfectly matched layer (PML) absorbing boundary conditions (ABCs) for the alternating direction implicit finite-difference time-domain (ADI-FDTD) method are presented. By taking the dispersion error of the ADI-FDTD method into account, it is shown that the two ABCs have almost the same level of accuracy with large time step. A microstrip lowpass filter is studied to compare the calculation accuracy and efficiency of these two ABCs. Our study shows that the Mur's ABC for ADI-FDTD method with large time step is more practicable due to its simplicity and efficiency
WIFO-Weißbuch: Mehr Beschäftigung durch Wachstum auf Basis von Innovation und Qualifikation

Das WIFO-Weisbuch baut auf elf Strategieelementen auf, in denen eine Neuausrichtung der osterreichischen Innovationsstrategie vom Technologienehmer zum Technologiegeber und eine radikale Umgestaltung des Aus- und Weiterbildungssystems an zentraler Stelle stehen. Die Strategieelemente ubersetzen sich in acht zielorientierte Masnahmenpakete. Die Umsetzung der Gesamtstrategie soll in drei Phasen erfolgen – beginnend mit der Kick-off-Periode 2007 bis 2009. Ab 2015 kann Wachstum dann nur noch auf technischen Fortschritt und Qualitatsverbesserungen aufbauen.
VALIDATION STUDY OF DIMENSIONALITY REDUCTION IMPACT ON BREAST CANCER CLASSIFICATION

A fundamental problem in machine learning is identifying the most representative subset of features from which we can construct a predictive model for a classification task. This paper aims to present a validation study of dimensionality reduction effect on the classification accuracy of mammographic images. The studied dimensionality reduction methods were: locality-preserving projection (LPP), locally linear embedding (LLE), Isometric Mapping (ISOMAP) and spectral regression (SR). We have achieved high rates of classifications. In some combinations the classification rate was 100%. But in most of the cases the classification rate is about 95%. It was also found that the classification rate increases with the size of the reduced space and the optimal value of space dimension is 60. We proceeded to validate the obtained results by measuring some validation indices such as: Xie-Beni index, Dun index and Alternative Dun index. The measurement of these indices confirms that the optimal value of reduced space dimension is d=60.
XML Implementation of Role Based Control in Healthcare Adhoc Networks

As mobile adhoc networks (MANETs) are becoming popular for a variety of applications, so are the issues engulfing corresponding implementations. In this paper, a healthcare application is described for the environment where normal network connectivity may not be available hence adhoc networking of small scale healthcare units and corresponding devices becomes necessary. Different roles of such units are discussed to develop policy framework to facilitate role based access control conformant access. Furthermore, implementation of such access control within a typical healthcare environment is investigated.
Adaptive Quantization Index Modulation Audio Watermarking based on Fuzzy Inference System

Many of the adaptive watermarking schemes reported in the literature consider only local audio signal properties. Many schemes require complex computation along with manual parameter settings. In this paper, we propose a novel, fuzzy, adaptive audio watermarking algorithm based on both global and local audio signal properties. The algorithm performs well for dynamic range of audio signals without requiring manual initial parameter selection. Here, mean value of energy (MVE) and variance of spectral flux (VSF) of a given audio signal constitutes global components, while the energy of each audio frame acts as local component. The Quantization Index Modulation (QIM) step size Δ is made adaptive to both the global and local features. The global component automates the initial selection of Δ using the fuzzy inference system while the local component controls the variation in it based on the energy of individual audio frame. Hence Δ adaptively controls the strength of watermark to meet both the robustness and inaudibility requirements, making the system independent of audio nature. Experimental results reveal that our adaptive scheme outperforms other fixed step sized QIM schemes and adaptive schemes and is highly robust against general attacks.
AKT plays a central role in tumorigenesis

AKT is emerging as a central player in tumorigenesis. In this issue of PNAS, Mayo and Donner (1) report on yet another function of AKT, involving regulation of the Mdm2/p53 pathway. The first evidence pointing to a role of AKT in oncogenesis was provided by early studies of transforming viruses. A novel retrovirus, isolated from an AKR mouse T cell lymphoma (2), harbored transduced sequences of cellular origin (3). In 1991, our collaborative studies with Philip Tsichlis and Stephen Staal resulted in the cloning of the viral oncogene v- akt (4). The predicted oncoprotein contained viral Gag sequences fused to a kinase related to protein kinase C. The oncogenic potential of v-akt arises from the creation of a myristylation site at the amino terminus and consequent constitutive kinase activity (5). By different approaches, aimed at identifying novel protein kinases, two other groups independently cloned the identical cellular sequence at about the same time (6, 7). AKT is now known to define a family of closely related, highly conserved cellular homologues (reviewed in ref. 8). In human, these are designated AKT1 , AKT2 , and AKT3 , located at chromosomes 14q32, 19q13, and 1q44, respectively (reviewed in ref. 9). The encoded proteins are serine/threonine kinases belonging to the protein kinase B (PKB) family, and the AKT1, AKT2, and AKT3 proteins are also known as PKBα, PKBβ, and PKBγ, respectively. Each AKT family member contains an amino-terminal pleckstrin homology (PH) domain, a short α-helical linker, and a carboxyl-terminal kinase domain (8). PH domains exist in diverse signaling molecules and permit anchorage of proteins to the cell membrane via phospholipid interactions (10). The degree of functional redundancy between AKT1, AKT2, and AKT3 is currently unclear. Although each kinase responds similarly to various stimuli, their different tissue-specific expression patterns suggest distinct roles, …
Automatic flow signal analysis for airway secretion detection in ventilator-dependent patients with artificial immunological systems

Airway secretion must be avoid-ed due to liquid The accumulation in ventilator-dependent patients. As this cause serious complications to the patient. In this work we use an artificial immune system algorithm able to detect secretion automatically only from the flow signal analysis. The training and validation of the algorithm was done from a database containing flow signals of 457 respiratory cycles, obtained from three patients in different ventilation modes. The algorithm trained with 60% of the base cycles, was able to achieve specificity and sensitivity above 0.98 in the classification of the remaining cycles of the base.
Controlling heaving wave energy converter using function-based model predictive control technique

This paper proposes a new reactive control technique for controlling single body heaving wave energy converter (WEC). A function-based continuous model predictive controller (MPC) is implemented to maximize the absorbed energy while respecting the physical limitations of the device. Laguerre orthonormal functions are deployed to approximate the input variable trajectory, which reduces the computational burden associated with MPC. The developed control strategy is evaluated using both monochromatic and polychromatic sea states. The function-based mode predictive controller showed decent reference signal tracking capabilities, optimizing the control effort to achieve maximum power transfer, while respecting the actuators mechanical and electrical limitations. Also the controller provides means to alleviate the problem of excessive real/reactive power flows.