Miracle-dz/UniFAR-FTUs huggingface dataset:
Variable region gene analysis of B cell subsets derived from a 4-year- old child: somatically mutated memory B cells accumulate in the peripheral blood already at young age

Tonsillar germinal center and immunoglobulin M+ (IgM+)IgD+ B cells as well as peripheral blood (PB) CD5+ and CD5- (conventional) B cells from a 4-yr-old child were isolated and nucleotide sequences of expressed Ig heavy chain variable regions encoded by VH4 gene family members were determined from amplified cDNA. Whereas both tonsillar IgM+IgD+ cells and the majority of IgM-expressing CD5+ and CD5- PB B cells showed no or little somatic mutation, tonsillar germinal center (GC) B cells and IgG-expressing PB B cells carried a high load of somatic mutations in their V region genes. This suggests that somatically mutated memory B cells which have switched isotype accumulate in the PB already at young age. Their frequency seems to increase with age. On the other hand, the antibody repertoire of tonsillar IgM+IgD+ B cells and the majority of IgM-expressing PB B cells is determined by germline-encoded specificities and by generation of variability in the complementary determining region III through VH-DH-JH recombination. A fraction of IgM-bearing PB B cells carries somatically mutated V region genes and probably represents GC-derived B cells which have left the GC at an early stage of the GC reaction without undergoing isotype switching. 10 VH4 germline genes were found to be expressed. Three gene segments were overrepresented in the sequence collection (35 of 50 clones): VH4.21 (30%), V71-4 (20%), and 3D279D (20%). It appears that most potentially functional VH4 germline genes are expressed in peripheral B cells. Some members of this VH gene family are clearly overrepresented over others.
noVel BIoMarKer CandIdates

The locus ceruleus is among the earliest affected brain regions in Parkinson’s disease (PD) showing Lewy body pathology and neuronal loss. To improve our understanding of the pathogenesis of PD, we performed the first proteomic analysis ever of post-mortem locus ceruleus tissue of six pathologically confirmed PD patients, and six ageand gendermatched non-neurological controls. In total 2495 proteins were identified, of which 87 proteins were differentially expressed in the locus ceruleus of PD patients compared to controls. The majority of these differentially expressed proteins are known to be involved in processes that have been implicated in the pathogenesis of PD previously, including mitochondrial dysfunction, oxidative stress, protein misfolding, cytoskeleton dysregulation and inflammation. Several individual proteins were identified that have hitherto not been associated with PD, such as regucalcin, which plays a role in maintaining intracellular calcium homeostasis, and isoform 1 of kinectin, which is involved in transport of cellular components along microtubules. In addition, pathway analysis suggests a pathogenetic role for aminoacyl-tRNA-biosynthesis. These findings indicate that the proteome of the locus ceruleus of PD patients and non-neurological controls provides data that are relevant to the pathogenesis of PD, reflecting both known and potentially novel pathogenetic pathways. Karin d. van dijk1,2, Henk W. Berendse3, Benjamin drukarch1, silvina a. Fratantoni3, Thang V. Pham3, sander r. Piersma3, evelien Huisman1, John J.P. Brevé1, Henk J. Groenewegen1, Connie r. Jimenez3*, Wilma d.J. van de Berg3* 1Department of Anatomy and Neurosciences, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands, 2Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands, 3OncoProteomics Laboratory of the Department of Medical Oncology, VU University Medical Center, Amsterdam, The Netherlands. *Shared senior authorship Brain Pathology 2012; 22(4):485-98
Efficient Multi-view Performance Capture of Fine-Scale Surface Detail

We present a new effective way for performance capture of deforming meshes with fine-scale time-varying surface detail from multi-view video. Our method builds up on coarse 4D surface reconstructions, as obtained with commonly used template-based methods. As they only capture models of coarse-to-medium scale detail, fine scale deformation detail is often done in a second pass by using stereo constraints, features, or shading-based refinement. In this paper, we propose a new effective and stable solution to this second step. Our framework creates an implicit representation of the deformable mesh using a dense collection of 3D Gaussian functions on the surface, and a set of 2D Gaussians for the images. The fine scale deformation of all mesh vertices that maximizes photo-consistency can be efficiently found by densely optimizing a new model-to-image consistency energy on all vertex positions. A principal advantage is that our problem formulation yields a smooth closed form energy with implicit occlusion handling and analytic derivatives. Error-prone correspondence finding, or discrete sampling of surface displacement values are also not needed. We show several reconstructions of human subjects wearing loose clothing, and we qualitatively and quantitatively show that we robustly capture more detail than related methods.
Inhibitors of the Glyoxylate Cycle Enzyme ICL1 in Candida albicans for Potential Use as Antifungal Agents

Candida albicans is an opportunistic pathogen that causes candidiasis in humans. In recent years, metabolic pathways in C. albicans have been explored as potential antifungal targets to treat candidiasis. The glyoxylate cycle, which enables C. albicans to survive in nutrient-limited host niches and its. Key enzymes (e.g., isocitrate lyase (ICL1), are particularly attractive antifungal targets for C. albicans. In this study, we used a new screening approach that better reflects the physiological environment that C. albicans cells experience during infection to identify potential inhibitors of ICL. Three compounds (caffeic acid (CAFF), rosmarinic acid (ROS), and apigenin (API)) were found to have antifungal activity against C. albicans when tested under glucose-depleted conditions. We further confirmed the inhibitory potential of these compounds against ICL using the ICL enzyme assay. Lastly, we assessed the bioavailability and toxicity of these compounds using Lipinski's rule-of-five and ADMET analysis.
Exploiting Job Response-Time Information in the Co-Design of Real-Time Control Systems

We consider a real-time system of multiple tasks, each task having a plant to control. The overall quadratic control cost is to be optimized. We exploit the periodicity of the task response time, which corresponds to a periodic delay pattern in the feedback control loop. Perturbed periods are used as a tool to find a finite hyper period. We present an analytical procedure to design a periodic linear-quadratic-Gaussian (LQG) controller for tasks with fixed execution times as well as a numerical solution to the periodic -- stochastic LQG problem for tasks with variable execution times. The controllers are evaluated using simulations in real-time scheduling and control co-design examples.
Coalescing Texture Descriptors

ARPA Image Understanding Workshop 1996 As an alternative to texture segmentation for the description of the images, we propose a method for coalescing descriptors of adjacent image patches with similar textural content i n to tight clusters. We a c hieve this result by extending the notion of edge-preserving smoothing and anisotropic diiusion from gray-level and color images to vector-valued images that describe the textural content o f e a c h image patch. To this end, we rst compute raw texture descrip-tors, that is, vectors that describe local texture appearance. We then deene texture c ontrast as the maximum derivative of the texture descrip-tor vector, and we deene signiicant regions as those in which contrast is low. We propose an eecient implementation of edge-preserving smoothing and show that it is closely related to anisotropic diiusion. Experiments on texture mosaics and real images show that clear texture edges are found even where intensity edges are weak or poorly deened, and that signiicant texture regions yield tight clusters of texture de-scriptors.
The Tree Representation of Feasible Solutions for the TSP with Pickup and Delivery and LIFO Loading

The feasible solutions of the traveling salesman problem with pickup and delivery (TSPPD) are represented by vertex lists in existing literature. However, when the TSPPD requires that the loading and unloading operations must be performed in a last-in-first-out (LIFO) manner, we show that its feasible solutions can be represented by trees. Consequently, we develop a variable neighbourhood search (VNS) heuristic for the TSPPD with last-in-first-out loading (TSPPDL) involving several search operators based on the tree data structure. Experiments show that our VNS heuristic is superior to the current best heuristics for TSPPDL in terms of both solution quality and computing time.
Association between personality traits and job performance among secondary school teachers

This paper examines the association between personality traits and job performance among Malaysian public secondary school teachers. It focuses on Big Five personality dimensions: Openness to Experience, Conscientiousness, Extraversion, Agreeableness and Neurot icism. A total of 954 questionnaires were distributed to teachers in eight public secondary schools, however only 489 usable responses were used. Descriptive, correlation and multiple regression statistics are used to analyse the data. The findings reveale d that there is a positive association between Openness to Experience and Agreeableness and job performance. On the contrary, there is a negative association between Neuroticism and job performance. The most predictive trait that influences job performance is Neuroticism and followed by Openness to Experience. The implications of this study suggests that understanding the influence of personality traits on job performance is essential and its justify the use of personality test by the Ministry of Education Malaysia for recruiting and selecting suitable candidates to become an educator. The Ministry of Education Malaysia is aiming to implement a world - class teacher education to ensure that the teachers are competent to meet the national inspiration
Hardware Design and Implementation of a Wavelet De-Noising Procedure for Medical Signal Preprocessing

In this paper, a discrete wavelet transform (DWT) based de-noising with its applications into the noise reduction for medical signal preprocessing is introduced. This work focuses on the hardware realization of a real-time wavelet de-noising procedure. The proposed de-noising circuit mainly consists of three modules: a DWT, a thresholding, and an inverse DWT (IDWT) modular circuits. We also proposed a novel adaptive thresholding scheme and incorporated it into our wavelet de-noising procedure. Performance was then evaluated on both the architectural designs of the software and. In addition, the de-noising circuit was also implemented by downloading the Verilog codes to a field programmable gate array (FPGA) based platform so that its ability in noise reduction may be further validated in actual practice. Simulation experiment results produced by applying a set of simulated noise-contaminated electrocardiogram (ECG) signals into the de-noising circuit showed that the circuit could not only desirably meet the requirement of real-time processing, but also achieve satisfactory performance for noise reduction, while the sharp features of the ECG signals can be well preserved. The proposed de-noising circuit was further synthesized using the Synopsys Design Compiler with an Artisan Taiwan Semiconductor Manufacturing Company (TSMC, Hsinchu, Taiwan) 40 nm standard cell library. The integrated circuit (IC) synthesis simulation results showed that the proposed design can achieve a clock frequency of 200 MHz and the power consumption was only 17.4 mW, when operated at 200 MHz.
Improved spatial learning is associated with increased hippocampal but not prefrontal long‐term potentiation in mGluR4 knockout mice

Although much information about metabotropic glutamate receptors (mGluRs) and their role in normal and pathologic brain function has been accumulated during the last decades, the role of group III mGluRs is still scarcely documented. Here, we examined mGluR4 knockout mice for types of behavior and synaptic plasticity that depend on either the hippocampus or the prefrontal cortex (PFC). We found improved spatial short‐ and long‐term memory in the radial arm maze, which was accompanied by enhanced long‐term potentiation (LTP) in hippocampal CA1 region. In contrast, LTP in the PFC was unchanged when compared with wild‐type controls. Changes in paired‐pulse facilitation that became overt in the presence of the GABAA antagonist picrotoxin indicated a function of mGluR4 in maintaining the excitation/inhibition balance, which is of crucial importance for information processing in the brain and the deterioration of these processes in neuropsychological disorders such as autism, epilepsy and schizophrenia.
Efficiency of mechanical activation of inspiratory muscles in COPD using sample entropy

Respiratory muscle dysfunction is a common problem in patients with chronic obstructive pulmonary disease (COPD) and has mostly been related to pulmonary hyperinflation [1, 2]. Associated diaphragm shortening and deleterious changes in the muscle force-length relationship cause a reduction in the muscles' capacity to generate pressure, placing them at a mechanical disadvantage [1, 3]. Specifically, both inspiratory muscle strength and mechanical efficiency may be reduced in COPD patients [1, 4–6], although, at isovolume, the contractile strength of the diaphragm in COPD is preserved or may even be improved in some cases [7]. The ratio between transdiaphragmatic pressure and electrical diaphragm activity has been used as a measure of respiratory muscle efficiency [8, 9]. However, in clinical practice, it is complex to measure this parameter directly, as invasive measures are required and these are uncomfortable for patients [4]. Respiratory muscle mechanomyogram exhibits significant differences between severe and very severe COPD patients http://ow.ly/SdV6Y
Automatic language identification using wavelets

Spoken language identification consists in recognizing a language based on a sample of speech from an unknown speaker. The traditional approach for this task mainly considers the phonothactic information of languages. However, for marginalized languages –languages with few speakers or oral languages without a fixed writing standard–, this information is practically not at hand and consequently the usual approach is not applicable. In this paper, we present a method that only considers the acoustic features of the speech signal and does not use any kind of linguistic information. This method applies a wavelet transform to extract the acoustic features of the speech signal. The experimental results on a pairwise discrimination task among nine languages demonstrated that this approach considerably outperforms other previous methods based on the sole use of acoustic features.
Effect of fly ash on tensile properties of ultra-high performance fiber reinforced cementitious composites (UHP-FRCC)

This article presents and compare the tensile strain hardening behavior, compressive strength, energy absorption, and CO2 emission of environmental friendly ultrahigh performance fiber reinforced cementitious composites (UHP-FRCC) containing various fly ash contents as partial replacement of premix cement (consisted of 82% low heat cement and 18% silica fume). Six series of UHP-FRCC are considered in this study. The first two series are control series while the rest four series contain 20, 30, 40, and 50% fly ash as partial replacement of premix cement. A small amount of nano silica (2 wt.%) is also added to compensate the low early age strength properties of the fly ash based UHP-FRCC. Results show that fly ash contents of 30–40% exhibited better compressive strength, tensile strain hardening behavior, and energy absorption than the other fly ash contents in the UHP-FRCC. The UHP-FRCC containing 40% fly ash shows about 12, 14, 10, and 22% reduction in compressive strength, ultimate tensile strength, ultimate tensile strain, and energy absorption capacities, respectively, than the control, while its CO2 emission is about 35% lower than the control. The reported properties of UHP-FRCC containing 40% fly ash are still higher than other reported UHP-FRCC containing other SCMs as well as many reported UHP-FRCC containing no SCMs except the silica fume.
Comparison of Partitioning Techniques for Two-Level Iterative Solvers on Large, Sparse Markov Chains

Experimental results for large, sparse Markov chains, especially the ill-conditioned nearly completely decomposable (NCD) ones, are few. We believe there is need for further research in this area, specifically to aid in the understanding of the effects of the degree of coupling of NCD Markov chains and their nonzero structure on the convergence characteristics and space requirements of iterative solvers. The work of several researchers has raised the following questions that led to research in a related direction: How must one go about partitioning the global coefficient matrix into blocks when the system is NCD and a two-level iterative solver (such as block SOR) is to be employed? Are block partitionings dictated by the NCD form of the stochastic one-step transition probability matrix necessarily superior to others? Is it worth investigating alternative partitionings? Better yet, for a fixed labeling and partitioning of the states, how does the performance of block SOR (or even that of point SOR) compare to the performance of the iterative aggregation-disaggregation (IAD) algorithm? Finally, is there any merit in using two-level iterative solvers when preconditioned Krylov subspace methods are available? We seek answers to these questions on a test suite of 13 Markov chains arising in 7 applications.
The Wreath Process: A totally generative model of geometric shape based on nested symmetries

We consider the problem of modelling noisy but highly symmetric shapes that can be viewed as hierarchies of whole-part relationships in which higher level objects are composed of transformed collections of lower level objects. To this end, we propose the stochastic wreath process, a fully generative probabilistic model of drawings. Following Leyton's "Generative Theory of Shape", we represent shapes as sequences of transformation groups composed through a wreath product. This representation emphasizes the maximization of transfer --- the idea that the most compact and meaningful representation of a given shape is achieved by maximizing the re-use of existing building blocks or parts. The proposed stochastic wreath process extends Leyton's theory by defining a probability distribution over geometric shapes in terms of noise processes that are aligned with the generative group structure of the shape. We propose an inference scheme for recovering the generative history of given images in terms of the wreath process using reversible jump Markov chain Monte Carlo methods and Approximate Bayesian Computation. In the context of sketching we demonstrate the feasibility and limitations of this approach on model-generated and real data.
Comparative Evaluation of Argument Extraction Algorithms in Discourse Relation Parsing

Discourse relation parsing is an important task with the goal of understanding text beyond the sentence boundaries. One of the subtasks of discourse parsing is the extraction of argument spans of discourse relations. A relation can be either intra-sentential – to have both arguments in the same sentence – or inter-sentential – to have arguments span over different sentences. There are two approaches to the task. In the ﬁrst approach the parser decision is not conditioned on whether the relation is intra-or inter-sentential. In the second approach relations are parsed separately for each class. The paper evaluates the two approaches to argument span extraction on Penn Discourse Treebank explicit relations; and the problem is cast as token-level sequence labeling. We show that processing intra-and inter-sentential relations separately, reduces the task complexity and signiﬁcantly outperforms the single model approach.
A system-theory approach to decompose CPM signals into PAM waveforms

In 1986, Laurent showed that binary continuous phase modulated (CPM) signals can be decomposed into pulse amplitude modulated (PAM) waveforms. This result, later extended to multilevel CPM signals by Mengali and Morelli, has attracted much attention, especially for the design of simplified receivers. The paper proceeds from the premise that the decomposition into PAM waveforms is not unique, and follows a systemtheory approach that leads to a natural formulation. First, the CPM modulator is represented by a nonlinear part (encoder) followed by a linear part (bank of PAM modulators). The two parts are then rearranged with the aim of obtaining real-valued continuous PAM waveforms and to reduce their number. Several classes of decompositions arise with this approach, each of which admits an infinite number of different decompositions of the same CPM signal, among which the Laurent and MengaliMorelli results appear as special cases. Throughout the paper, a systematic use is made of the Kronecker product, which appears to be the natural tool for dealing with CPM decompositions and for expressing results in a very simple form.
Endocarditis due to vancomycin-resistant enterococci: case report and review of the literature.

BACKGROUND Endocarditis due to vancomycin-resistant enterococci (VRE) is rare, and the literature consists almost exclusively of reports of single cases. METHODS We report a case of VRE prosthetic valve endocarditis and review 18 cases of native and prosthetic valve VRE endocarditis reported in the literature. RESULTS The majority of cases were due to Enterococcus faecium. Nearly all of these infections were hospital acquired, and the vast majority of patients had significant underlying disease processes, including dialysis and transplantation. More than three-quarters of cases were left-sided, and the aortic valve was most commonly involved. Peripheral stigmata of endocarditis were not reported in any of the cases. Approximately 40% of patients developed cardiac complications. Nearly three-quarters of patients survived, despite the difficulties associated with providing bactericidal antimicrobial therapy, and only 4 patients underwent valve replacement. CONCLUSIONS VRE endocarditis is an uncommon nosocomial infection that affects patients with significant comorbid conditions. Most cases are due to E. faecium, and the aortic valve is involved in at least one-half of cases. One-third of patients require surgical treatment. Optimal antimicrobial therapy remains undefined, but an attempt to identify bactericidal combination therapy should be sought.
Candidate Gene Prioritization Using Network Based Probabilistic Models

We present a new gene prioritization method that learns a probabilistic knowledge model from a knowledge base and free text research documents and exploits it to prioritize candidate genes. The knowledge model is represented by a network of associations among the domain entities (e.g., genes) and is extracted from a domain knowledge base (e.g., protein-protein interaction database) or a corpus of text documents (e.g., PubMed documents). This knowledge model is then used to perform probabilistic inferences and applied to the task of candidate gene prioritization. We evaluate our new method on five diseases and show that it outperforms a recently described network based method for candidate gene prioritization.