Miracle-dz/UniFAR-FTUs huggingface dataset:
DNA concentration can specify DNA melting point in a high-resolution melting analysis master mix.

To the Editor: High-resolution melting analysis (HRMA)1 can be used to discriminate sequence variants of PCR-amplified DNA fragments (1). We attempted to develop an HRMA-based procedure to discriminate multilocus sequence typing (MLST) (2) alleles from a divergent lineage of Staphylococcus aureus (3) using a Corbett Rotorgene 6000. In the case of the 573-bp glycerol uptake facilitator (glpF) fragment, there were 4 known alleles in our culture collection. Allele discrimination performed with the nonsaturating dye SYBR Green was not reliable. We therefore tested the saturating dye LCGreenPlus (Biofire Diagnostics) (4). Initial experiments revealed very poor allele discrimination due to lack of correlation between the melting temperature ( T m) and allele identity/allele percentage of guanine plus cytosine (%G+C) content. Here we report an investigation of the basis for this poor performance. Our initial results with LCGreenPlus suggested that the T m was primarily a function of the PCR yield rather than the allele sequence. This was tested by subjecting a glpF allele 321 sample to PCR in LCGreenPlus master mix, making a dilution series of the reaction products in the same master mix, and then subjecting the dilutions to HRMA. As predicted, the T m values in both melting domains were inversely correlated with DNA concentration (Fig. 1 …
Distinguishing Ichthyoses by Protein Profiling

To explore the usefulness of protein profiling for characterization of ichthyoses, we here determined the profile of human epidermal stratum corneum by shotgun proteomics. Samples were analyzed after collection on tape circles from six anatomic sites (forearm, palm, lower leg, forehead, abdomen, upper back), demonstrating site-specific differences in profiles. Additional samples were collected from the forearms of subjects with ichthyosis vulgaris (filaggrin (FLG) deficiency), recessive X-linked ichthyosis (steroid sulfatase (STS) deficiency) and autosomal recessive congenital ichthyosis type lamellar ichthyosis (transglutaminase 1 (TGM1) deficiency). The ichthyosis protein expression patterns were readily distinguishable from each other and from phenotypically normal epidermis. In general, the degree of departure from normal was lower from ichthyosis vulgaris than from lamellar ichthyosis, parallel to the severity of the phenotype. Analysis of samples from families with ichthyosis vulgaris and concomitant modifying gene mutations (STS deficiency, GJB2 deficiency) permitted correlation of alterations in protein profile with more complex genetic constellations.
Intermittent peritoneal dialysis (IPD): an old but still effective modality for severely disabled ESRD patients.

BACKGROUND Hospital-based intermittent peritoneal dialysis (IPD) is an old PD modality applied for as long as 40 h per week using high volumes of PD fluid, but it has almost been abandoned due to its low solute clearances. However, IPD might be the only option for elderly dialysis patients with significant comorbidities, unable to undergo haemodialysis (HD) or PD at home without any assistance, for various reasons. METHODS We describe our experience with 25 patients aged 71.2 +/- 7.5 years with a previous history of HD for 55.4 +/- 54 months, dialysed with IPD for more than 3 months. IPD was performed three times weekly for 8-10 h. RESULTS Mean values for haematocrit, serum urea, creatinine, sodium, potassium and calcium were comparable with other ESRD populations, whereas there were significantly lower values for albumin (3.2 +/- 0.3 mg/dL) and significantly higher values for phosphorus (7.1 +/- 1.7 mg/dL) despite the use of phosphate binders. The patients survived for a mean of 16.8 +/- 11.5 (3-43) months despite very low solute clearances, as expressed by Kt/V urea (1 +/- 0.26) and weekly creatinine clearance (27.2 +/- 7.6 L/week). However, by using 22.9 +/- 4.5 L of various combinations of isotonic and hypertonic PD fluids, the mean ultrafiltrate was 1854 +/- 326 mL per session. There were only two cases of peritonitis, unrelated to IPD per se. CONCLUSIONS Considering the underlying comorbidities, IPD remains a valuable and effective option with acceptable survival rates, for a special population of ESRD patients not able for various reasons to undergo HD, neither PD at home.
Physical Validation of Global Illumination Methods: Measurement and Error Analysis

In this paper, we present a physical validation of global illumination algorithms based on measurements from a simple experimental setup. The validation methodology emphasizes tractability and error minimization. To this end, we discuss issues such as the acquisition and accurate simulation of material bidirectional reflection distribution functions (BRDFs) and the light source distribution, as well as error analysis. In addition, we present a nearest‐neighbor resampling technique for BRDFs and a simple method for extracting the light source distribution from digitized high dynamic range (HDR) images. Finally, we compare the measurements to a forward and backward raytracing solution (photon map and RADIANCE, respectively) in a set of case studies.
CLOSE TOPOGRAPHICAL RELATIONSHIP BETWEEN MITOCHONDRIA AND ERGASTOPLASM OF LIVER CELLS IN A DEFINITE PHASE OF CELLULAR ACTIVITY

1. In most rat liver cells, no special topographical relationship between mitochondria and ergastoplasmic lamellae is to be observed. In some cells, nevertheless, the two organelles are grouped together in dense zones clearly separated from the hyaloplasm. 2. Such an association can be produced at will in the livers of animals refed after prolonged fasting, or in the regenerative phases after partial hepatectomy and intoxication with carbon tetrachloride. In all these cells, the ergastoplasm, after having disappeared, suddenly reappears in the cytoplasm, either along the nucleus or cell membranes, where the mitochondria are grouped. 3. It may be supposed that these topographical relationships between mitochondria and ergastoplasm during a definite period of cellular activity indicate a close functional link between chondrioma and basophilic structures. Mitochondria seem to play an important part in the elaboration of hepatic ergastoplasm.
On the use of Dirichlet process mixtures for the modelling of pseudorange errors in multi-constellation based localisation

In Global Navigation Satellite Systems (GNSS) positioning, the receiver measures the pseudoranges with respect to each observable navigation satellite and determines the user position. The use of many constellations should lead to highly available, highly accurate navigation anywhere. However, it is important to notice that even if modern receivers achieve high position accuracy in line-of-sight (LOS) conditions, multipath propagation highly degrades positioning performances even in multi-constellation based localisation (”GPS + Galileo” for instance). In urban area, some obstacles (cars, pedestrians, etc) can appear suddenly and thus can induce a random error in the pseudorange measure. We address here the case where the noise probability density functions are of unknown functional form. A flexible Bayesian nonparametric noise model based on Dirichlet process mixtures (DPM) is introduced. Hence, the paper will contain two main parts. The first part focuses on the modelling of the pseudorange noises using DPMs and its suitability in the estimation problem handled by an efficient particle filter. The other part contains interesting validation schemes.
DCM-based orientation estimation using cascade of two adaptive extended Kalman filters

In this paper, we propose an effective algorithm to estimate orientation angles (roll, pitch, and yaw) from Inertial Measurement Unit (IMU). This algorithm uses two adaptive extended Kalman filters (AEKF) to estimate the Direction Cosine Matrix (DCM), the external acceleration and the magnetic disturbance. First 6-state filter estimates three elements in the third row of the DCM and the external acceleration on three axes. The second one estimates three elements in the first row of the DCM and the magnetic disturbance on three axes. The last three elements of the DCM are computed from the DCM orthogonalization property. This method overcomes original problems when IMU is moved by external acceleration, and it is disturbed in magnetic environment. In addition, it helps reduce effort on computation from 15-states filter to two 6-states filters. The performance of proposed algorithm is verified by applying it to a 9-DOF IMU and testing its accuracy in various conditions. Experiment results have shown that the proposed algorithm achieves accurate estimation of orientation. The RMS error of all three angles is less than 2°.
Valid Assessment of the Clinical Features of Depression by Relatives Appears to Slip Under the RADAR

Objective: We report on the development of an observational measure designed for completion by relatives, the Recent Appearance of Depression Assessed by Relatives (RADAR), and consider its validity. Method: One hundred and one patients with a current major depressive episode had a relative or close friend complete the RADAR, while psychiatrists and research assistants collected extensive data. Results: Correlated against both patient self-report and psychiatrist-rated depression severity measures, RADAR scores evidenced poor validity overall. Recent Appearance of Depression Assessed by Relatives scores also failed to differentiate depressive subtypes, in that scores for patients with melancholic depression were not significantly higher than for those with non-melancholic depression. Conclusions: Results are consistent with previous findings of poor agreement between clinicians and corroborative witnesses in assessing clinical depressive features, and argue against reliance on corroborative witness reports.
On Motifs and Functional Blocks in Technological Networks

One primary focus of complex systems research has been the topological analysis of the network underlying a complex system. One key question is the size and structure/function of the underlying building blocks. Two proposed building blocks are called motif and functional module. A motif has been defined as a subgraph that occurs significantly more frequently in real-world networks than expected by chance alone [5]. The observed over-representation of motifs has been interpreted as a manifestation of functional constraints and design principles that have shaped network architectures at the local level. In contrast, a functional module or block in a network is a set of nodes that have strong interactions and a distinct function [1]. We distinguish the two by emphasizing small size and recurrence for motifs, endowing modules with larger size, and perhaps a composition dominated by interconnected motifs [7]. However, the relation between motifs and functional blocks lacks adequate precision, and has not received sufficient experimental analysis. This article addresses the relation between motifs and functional modules (or blocks) for a class of complex network, electronic circuits, where nodes are electronic components (e.g. logic gates and flip-flops in digital circuits), and edges are wires [2]. We compared a library of functional modules used by engineers for circuit design with the modules that are automatically identified using motif-finding algorithms [6]. This library of circuit functional blocks was either reverseengineered [3] or identified from IC databooks, cell libraries or textbooks. Given this library, we calculated the relative frequency of the occurrence of the functional modules; we also compared the topologies and instances of motifs and functional blocks. Comparing the hand-generated functional modules with the experimentally-computed motifs showed that: (1) functional modules are much larger than the 3-4 node motifs proposed in [4], and (2) a functional module typically consists of a collection of several 3-4 node motifs. We argue that, for electronic circuits, the statistical overrepresentation of 3-4 node motifs is due to functional modules consisting of motif-clusters, and not that motifs, in and of themselves, play a significant functional role in a circuit. More generally, the common functional modules discovered in benchmark circuits can be considered as “large motifs” themselves.
The use of deep learning in image segmentation, classification and detection

Recent years have shown that deep learned neural networks are a valuable tool in the field of computer vision. This paper addresses the use of two different kinds of network architectures, namely LeNet and Network in Network (NiN). They will be compared in terms of both performance and computational efficiency by addressing the classification and detection problems. In this paper, multiple databases will be used to test the networks. One of them contains images depicting burn wounds from pediatric cases, another one contains an extensive number of art images and other facial databases were used for facial keypoints detection.
Interactive exploration of extra-and intracranial blood vessels (case study)

We present a system for interactive explorations of extra-and intracranial blood vessels. Starting with a stack of images from 3D angiography, we use virtual clips to limit the segmentation of the vessel tree to the parts the neuroradiologists are interested in. Furthermore, methods of interactive virtual endoscopy are applied in order to provide an interior view of the blood vessles.
Readability of French as a foreign language and its uses

Reading is an important means of foreign language acquisition, particularly for vocabulary. Providing reading material that is of a suitable level of difficulty allows users to acquire vocabulary the most efficiently. Thus an on-line reading material recommender system for language learners requires a readability measure so that the difficulty of texts can be automatically assessed. However, most readability measures were developed for native child speakers of English. In this article I discuss an experiment in readability for learners of French. I conclude that using the average number of words per sentence correlates more closely with human judgements than many commonly available readability measures. I propose a new readability measure for learners of French that have English as their main language, which combines sentence length with the number of words that are similar in both languages (cognates). This measure slightly improves on sentence length for modelling French readability.
Deriving Explicit Data Links in WS-BPEL Processes

WS-BPEL is a standard language to model business processes. Control flow is modeled explicitly using links. Data is passed via shared variables and there is no notion of explicit data links. However, explicit data links are an important means to reason about business process models. We present an algorithm to derive explicit data links in WS-BPEL processes. By considering dead path elimination as defined in WS-BPEL, we reduce the number of derived data links when compared to existing approaches that ignore dead path elimination.
A Multimodal Augmented Reality System for Alignment Research

In this paper we present the Augmented Reality-based Interception Interface (ARbInI), a multimodal Augmented Reality (AR) system to investigate effects and structures of human-human interaction in collaborative tasks. It is introduced as a novel methodology to monitor, record, and simultaneously manipulate multimodal perception and to measure so-called alignment signals. The linguistic term 'alignment' here refers to automatic and unconscious processes during communication of interactants. As a consequence of these processes, the structure of communication between the two interactants conforms to each other (for example, they use the same terms, gestures, etc.). Alignment is a debated model for communication in the community [1] and here we strive for providing novel means to study it by instrumenting the interaction channels of human interactants [2]. AR allows for a very close coupling between the user and a technical system. ARbInI adds to this a decoupling mechanism between two interacting users from the outside world and from each other via cameras and head-mounted displays (resp. microphone and headphones). This allows to monitor and record the exact perceived auditory and visual stimuli. This furthermore adds full control to the audiovisual input of the subjects: for instance, AR allows the manipulalion of shown virtual objects on top of physical objects by displaying a different size, shape or level of detail to the participants. Thus, the ARbInI has full control on the visual and auditory input of the subjects by means of the perceptual decoupling. With the help of visual and auditory AR techniques it is possible to manipulate the stimuli, for example by selectively changing the size, color or shape of virtual objects that are augmented in the views of cooperating users. Using ARToolKit markers attached to physical objects we make full use of augmented reality to realize physical interaction with virtual objects in our studies. In this paper, we also present VideoDB as a scenario. It focuses on the task to collaboratively organize and arrange multimodal video snippets. We discuss its potential regarding the recording and investigation of alignment.
Schenkerian Analysis by Computer: A Proof of Concept

Abstract A system for automatically deriving a Schenkerian reduction of an extract of tonal music is described. Schenkerian theory is formalized in a quasi-grammatical manner, expressing a reduction as a binary-tree structure. Computer software which operates in the manner of a chart parser using this grammar has been implemented, capable of deriving a matrix of reduction possibilities, in polynomial time, from a representation of the score. A full reduction of the extract can be discovered by selecting a tree from this matrix. The number of possible valid reductions for even short extracts is found to be extremely large, so criteria are required to distinguish good reductions from bad ones. To find such criteria, themes from five Mozart piano sonatas are analysed and samples of ‘good’ reductions (defined by reference to pre-existing analyses of these themes) are compared with randomly sampled reductions. Nine criteria are thereby derived, which can be applied in the process of parsing and selecting a reduction. The results are promising, but the process is still too computationally expensive—only extracts of a few bars in length can be reduced—and more extensive testing is required before the system can be properly claimed to perform automatic Schenkerian analysis.
THE EVOLUTION OF ADAPTATION : THE INFLUENCE OF MANUFACTURING REQUIREMENTS AND CAPABILITIES ON PRODUCTIVITY AT A CHANGING FOCUSED FACTORY

This paper examines how a focused factory adapts to a change in its manufacturing task. Specifically, we examine what factors may influence the success of production lines of a focused factory in adapting to the change. We use the organizational nature of production operations to suggest that the effectiveness of adaptation may depend on the manufacturing requirements of the new task, as well as on the manufacturing capabilities of a production line. We test our hypotheses using primary data from a well-known focused factory of the Copeland Corporation. The results suggest that the factors that influence adaptability may derive from individual as well as organizational competence, and that the direction and extent of their influence may depend on the nature of the operational activity concerned. The results also highlight important roles of carefully designed complexity into operations, and of process-oriented decision making on the shop-floor, in successful adaptation.
Nonlinear Complex and Cross Diffusion

This paper addresses nonlinear cross diffusion systems in the context of image processing tasks. While nonlinear diffusion is a celebrated tool, it still lacks a proper theoretical foundation is some areas. Especially the question of existence of solutions for edge preserving equations like the Perona-Malik equation has not been dealt with satisfactorily: For the pure edge preserving equation it is known that no global solution exists (unless the initial value is very smooth), while well posed variants like space averaging in the sense of Catté, Lions, Morel and Coll introduce artificial smoothing to prevent the blowup of the gradient. By considering cross-diffusion systems we are able to provide a diffusion equation which fully degenerates, for which the existence of global bounded solutions can be shown. This is achieved by providing smoothed derivative information intrinsically.
Functional semi-automated segmentation of renal DCE-MRI sequences

In dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), segmentation of internal kidney structures is essential for functional evaluation. Manual morphological segmentation of cortex, medulla and cavities remains difficult and time-consuming especially because the different renal compartments are hard to distinguish on a single image. We propose to test a semi-automated method to segment internal kidney structures from a DCE-MRI registered sequence. As the temporal intensity evolution is different in each of the three kidney compartments, pixels are sorted according to their time-intensity curves using a k-means partitioning algorithm. No ground truth is available to evaluate resulting segmentations so a manual segmentation by a radiologist is chosen as a reference. We first evaluate some similarity criteria between the functional segmentations and this reference. The same measures are then computed between another manual segmentation and the reference. Results are similar for the two types of comparisons.
ECE 544 NA Final Project : Robust Machine Learning Hardware via Classifier Ensemble

In this paper, we propose to use classifier ensemble (CE) as a method to enhance the robustness of machine learning (ML) kernels in presence of hardware error. Different ensemble methods (Bagging and Adaboost) are explored with decision tree (C4.5) and artificial neural network (ANN) as base classifiers. Simulation results show that ANN is inherently tolerant to hardware errors with up to 10% hardware error rate. With simple majority voting scheme, CE is able to effectively reduce the classification error rate for almost all tested data sets, with maximum test error reduction of 48%. For tree ensemble, Adaboost with decision stump as weak learner gives best results; while for ANN, bagging and boosting outperform each other depending on data set.
Rotor Walks and Markov Chains

The rotor walk is a derandomized version of the random walk on a graph. On successive visits to any given vertex, the walker is routed to each of the neighboring vertices in some fixed cyclic order, rather than to a random sequence of neighbors. The concept generalizes naturally to Markov chains on a countable state space. Subject to general conditions, we prove that many natural quantities associated with the rotor walk (including normalized hitting frequencies, hitting times and occupation frequencies) concentrate around their expected values for the random walk. Furthermore, the concentration is stronger than that associated with repeated runs of the random walk, with discrepancy at most C/n after n runs (for an explicit constant C), rather than c/sqrt n.