Miracle-dz/UniFAR-FTUs huggingface dataset:
Advanced Multilinear Data Analysis and Sparse Representation Approaches and Their Applications

Multifactor analysis plays an important role in data analysis since most real-world datasets usually exist with a combination of numerous factors. These factors are usually not independent but interdependent together. Thus, it is a mistake if a method only considers one aspect of the input data while ignoring the others. Although widely used, Multilinear PCA (MPCA), one of the leading multilinear analysis methods, still suffers from three major drawbacks. Firstly, it is very sensitive to outliers and noise and unable to cope with missing values. Secondly, since MPCA deals with huge multidimensional datasets, it is usually computationally expensive. Finally, it loses original local geometry structures due to the averaging process. This thesis sheds new light on the tensor decomposition problem via the ideas of fast low-rank approximation in random projection and tensor completion in compressed sensing. We propose a novel approach called Compressed Submanifold Multifactor Analysis (CSMA) to solve the three problems mentioned above. Our approach is able to deal with the problem of missing values and outliers via our proposed novel sparse Higher-order Singular Value Decomposition approach, named HOSVD-L1 decomposition. The Random Projection method is used to obtain the fast low-rank approximation of a given multifactor dataset. In addition, our method can preserve geometry of the original data. In the second part of this thesis, we present a novel pattern classification approach named Sparse Class-dependent Feature Analysis (SCFA), to connect the advantages of sparse representation in an overcomplete dictionary, with a powerful nonlinear classifier. The classifier is based on the estimation of class-specific optimal filters, by solving an L1-norm optimization problem using the Alternating Direction Method of Multipliers. Our method as well as its Reproducing Kernel Hilbert Space (RKHS) version is tolerant to the presence of noise and other variations in an image. Our proposed methods achieve very high classification accuracies in face recognition on two challenging face databases, i.e. the CMU Pose, Illumination and Expression (PIE) database and the Extended YALE-B that exhibit pose and illumination variations; and the AR database that has occluded images. In addition, they also exhibit robustness on other evaluation modalities, such as object classification on the Caltech101 database. Our method outperforms state-of-the-art methods on all these databases and hence they show their applicability to general computer vision and pattern recognition problems.
Nonlinear control of complex systems using algorithmic differentiation

In mechatronics and robotics one often encounters highly complex nonlinear systems, whose dynamics are described by a system of nonlinear ordinary differential equations. In simulation, one can use very sophisticated models, whereas controllers are typically designed on strongly simplified models. Quite often, this results in linear controllers which are unsuitable for the original nonlinear system. We suggest an approach allowing nonlinear controller design even for very complicated models. Our approach is based on an alternative differentiation method called algorithmic or automatic differentiation. With this computation method we can circumvent problems that may arise in symbolic computation.
High dietary K intake inhibits proximal tubule transport.

The impact of chronic dietary Kloading on proximal tubule (PT) function was measured using free-flow micropuncture, along with measurements of overall kidney function, including urine volume (UV), glomerular filtration rate (GFR), and absolute (ENa, EK) and fractional (FENa, FEK) Na+ and K+ excretion in the rat. Feeding animals a diet with 5% KCl (HK) for 7 days reduced GFR by 29%, increased UV by 77%, and increased EK by 202% compared with rats on a 1% KCl (CK) diet. HK did not change ENa but significantly increased FENa (1.40 vs. 0.64%), indicating that fractional Na+ absorption is reduced by HK. PT reabsorption was assessed using free-flow micropuncture in anesthetized animals. At 80% of the accessible length of the PT measurements of inulin concentration indicated volume reabsorption of 73% and 54% in CK and HK, respectively. At the same site, fractional PT Na+ reabsorption was 66% in CK and 37% in HK animals. Fractional PT K+ reabsorption was 66% in CK and 37% in HK. To assess the role of the Na-H exchanger NHE3 in mediating these changes we measured NHE3 protein expression in total kidney microsomes as well as surface membranes using Western blots. We found no significant changes in protein in either cell fraction. Expression of the S552 phosphorylated form of NHE3 was also similar in CK and HK animals. Reduction in PT transport may facilitate K+ excretion and help balance Na+ excretion by shifting Na+ reabsorption from K+ -reabsorbing to K+ -secreting nephron segments.
Language development of extremely premature infants: parental orientation

ABSTRACT Purpose: to analyze the linguistic development of extremely premature children at birth, through the Initial Speech and Language Acquisition Scale, and to verify the knowledge of these children's parents about language. Methods: the study included 21 parents of extremely premature children at birth. A booklet on the development of children's language and a questionnaire was prepared for the study, in order to investigate the efficiency of guidance to parents. Initially, the children were assessed using the Initial Speech and Language Acquisition Scale, and then, the parents received oral guidance on how to stimulate their children's language. Therefore, the questionnaire was applied to verify the impact of the guidelines on their knowledge. The data obtained through the scale were related to the answers obtained through the questionnaire applied to the parents, through descriptive percentages and Mann-Whitney test, with p<0.05. Results: most of the children performed as expected for their age in the evaluated aspects. The questionnaire showed that most parents had guidance on the general development of their children, but only half of them had knowledge about language. All participants felt contemplated with the educational material. Conclusion: despite the extreme prematurity, most children performed as expected for their age in terms of language, and parents had moderate knowledge on language.
Solution of the nonlinear diffusion equation using the dual reciprocity boundary element method and the relaxation type time integration scheme

We present the combined application of the dual reciprocity boundary element method (DRBEM) and the finite difference method (FDM) with a relaxation parameter to the nonlinear diffusion equation: ∂u ∂t = ν⊇ 2 u + p(u) where p(u) is the nonlinear term. The DRBEM is employed to discretize the spatial partial derivatives by using the fundamental solution of the Laplace operator, keeping the time derivative and the nonlinearity as the nonhomogeneous terms in the equation. The resulting system of ordinary differential equations is solved using the FDM with a relaxation procedure. A relaxation parameter is used to position the solution from the two time levels aiming to increase the convergence rate with a moderate time step to the steady state and also to obtain a stable solution. The non-linear terms do not present problems since they are treated as the nonhomogeneity of the diffusion equation with the help of the DRBEM. The solution procedure described here is also applicable to the diffusion and convection-diffusion equation and can be considered as the extension to the nonlinear reaction-diffusion equation. Numerical experiments are given to illustrate this scheme and to compare its performance with the other numerical schemes as well as the exact solution whenever it is available. The solution agrees very well with the exact solution while some other numerical schemes may result with some unwanted oscillations in the computed solution. The optimal value of the relaxation parameter is obtained numerically for preventing use of very small time increments and to achieve a stable solution. The DRBEM with a relaxation type time integration scheme exhibits a superior accuracy at large time values for the problems tending towards a steady state.
Macrofungi in Stands of the Endemic Pine Pinus peuce as Inferred from Morphological and Molecular Data

Pinus peuce (Balkan, Macedonian or Molika pine) is an endemic tree for the Balkans and a Tertiary relict, one of the two European five-needled pines of the subgenus Strobus (white pines). This work summarizes the data on macrofungal diversity in natural forests and artificial plantations of Macedonian pine in Bulgaria, based on three year survey of epigeous and hypogeous fungi in selected sampling plots, and combining morphology-based and molecularly inferred identification. The study registered 190 species in total. Higher diversity of macrofungi was recorded on sampling plots in natural stands compared to artificial plantings. Nine species are reported for the first time for the Bulgarian mycobiota. The paper provides the first public set of sequences of macrofungi of P. peuce stands, comprising 62 accessions.
A hybrid metaheuristic for the partitioning problem with homogeneity constraints on the number of objects

Partitioning is a combinatorial optimization problem that has been widely discussed because of two main aspects: its computational complexity and its application to diverse kind of problems. In addition, partitioning has been used on the solution of some clustering issues that arise when dealing with territorial design problems. Besides the particular properties of the classic partitioning, in some cases, it is needed to consider additional constraints that need to be solved, such as the homogeneity of the number of objects that made up the final clusters. In this paper, we present a solution applied to partitioning problems having the moderate balance constraint, by determining thresholds which allows it obtaining a well defined range on the dimensionality of the groups. The aforementioned problem with constraints is considered to have a high computational complexity and, therefore, in order to obtain approximate solutions for this problem, we have incorporated a particular hybrid metaheuristic of partitioning that combines simulated annealing and variable neighborhood search. We present the problem, a solution proposal, the mathematical model and a set of experimental tests for samples taken from a study case based on 469 geographical data of the Metropolitan Zone of the Toluca Valley.
An Anthropomorphic Robotic Hand With a Soft-Rigid Hybrid Structure and Positive- Negative Pneumatic Actuation

Anthropomorphic robotic hands are seeking to achieve key features such as multi-degree-of-freedom motion ability, bi-directional actuation, high adaptability, and sufficient stiffness. In this research, we propose a 10 active degrees-of-freedom anthropomorphic robotic hand with a soft-rigid hybrid structure and positive-negative pneumatic actuation. The fingers of the hand utilize pneumatic actuators composed of soft bellows to actuate a rigid skeleton for bending motion with unidirectional-stretchable nylon elastic fabric as a strain limiting layer. The positive-negative pneumatic actuation mimics the flexors and extensors of the human hand to implement bi-directional finger actuation. We present a prototype implementation of this robotic hand and provide a preliminary evaluation. The experimental results show that the combined positive-negative pneumatic actuation can extend the workspace of the finger and increase the finger stiffness compared to using only positive pneumatic actuation. The proposed robotic hand has good comprehensive performance (generated a blocking force of 7.5 N, scored seven in the Kapandji test, achieved 32 of the 33 grasp postures from the Feix taxonomy, and could implement five human grasping strategies) compared to other robotic hands in literatures.
Ceriporiopsistianshanensis (Polyporales, Agaricomycetes) and Sideratianshanensis (Hymenochaetales, Agaricomycetes), two new species of wood-inhabiting fungi from Xinjiang, Northwest China

﻿Abstract Wood-inhabiting fungi are abundant in China, but their distribution is uneven, with more fungi in southwest China and fewer fungi in northwest China. During the investigation of wood-inhabiting fungi in Xinjiang, we collected a large number of specimens. Eight specimens growing on Piceaschrenkiana were collected from Tianshan Mountains, and they were described as two new species in Ceriporiopsis and Sidera based on morphological characters and molecular evidence. Ceriporiopsistianshanensis is characterized by a cream to salmon-buff pore surface, larger pores measuring 1–3 per mm, and broadly ellipsoid basidiospores 5–6.5 × 3–4 μm. Sideratianshanensis is characterized by annual to perennial basidiocarps, measuring 15 mm thick, pores 5–7 per mm, cream to rosy buff pore surface, and allantoid basidiospores 3–3.5 × 1–1.4 µm. Detailed illustrations and descriptions of the novel species are provided.
NTRK Gene Fusions in Non-Small-Cell Lung Cancer: Real-World Screening Data of 1068 Unselected Patients

Simple Summary The identification of potential molecular alterations is standard in the diagnostic pathway of non-small-cell lung cancer (NSCLC). The aim of this study is to determine the prevalence of NTRK fusions in NSCLC in a routine diagnostic setting using immunohistochemistry, fluorescence in situ hybridization, and RNA-based next-generation sequencing. A total of 1068 unselected consecutive patients with NSCLC were screened in two scenarios, either with initial IHC followed by RNA-NGS (n = 973) or direct FISH testing (n = 95). In total, 0.2% of all patients were NTRK positive. Both RNA-NGS and FISH are suitable to determine clinically relevant NTRK fusions in a real-world setting. RNA-NGS or FISH NTRK positive results were mutually exclusive with alterations in EGFR/ALK/ROS1/BRAF/RET or KRAS. Abstract (1) Background: The main objectives of our study are (i) to determine the prevalence of NTRK (neurotrophic tyrosine kinase) fusions in a routine diagnostic setting in NSCLC (non-small cell lung cancer) and (ii) to investigate the feasibility of screening approaches including immunohistochemistry (IHC) as a first-line test accompanied by fluorescence in situ hybridization (FISH) and RNA-(ribonucleic acid-)based next-generation sequencing (RNA-NGS). (2) Methods: A total of 1068 unselected consecutive patients with NSCLC were screened in two scenarios, either with initial IHC followed by RNA-NGS (n = 973) or direct FISH testing (n = 95). (3) Results: One hundred and thirty-three patients (14.8%) were IHC positive; consecutive RNA-NGS testing revealed two patients (0.2%) with NTRK fusions (NTRK1-EPS15 (epidermal growth factor receptor pathway substrate 15) and NTRK1-SQSTM1 (sequestosome 1)). Positive RNA-NGS was confirmed by FISH, and NTRK-positive patients benefited from targeted treatment. All patients with direct FISH testing were negative. RNA-NGS- or FISH-positive results were mutually exclusive with alterations in EGFR (epidermal growth factor receptor), ALK (anaplastic lymphoma kinase), ROS1 (ROS proto-oncogene 1), BRAF (proto-oncogene B-Raf), RET (rearranged during transfection) or KRAS (kirsten rat sarcoma viral oncogene). Excluding patients with one of these alterations raised the prevalence of NTRK-fusion positivity among panTrk-(tropomyosin receptor kinase-) IHC positive samples to 30.5%. (4) Conclusions: NTRK fusion-positive lung cancers are exceedingly rare and account for less than 1% of patients in unselected all-comer populations. Both RNA-NGS and FISH are suitable to determine clinically relevant NTRK fusions in a real-world setting. We suggest including panTrk-IHC in a diagnostic workflow followed by RNA-NGS. Excluding patients with concurrent molecular alterations to EGFR/ALK/ROS1/BRAF/RET or KRAS might narrow the target population.
Positive Semi-definiteness and Extremal H-eigenvalues of Extended Essentially Nonnegative Tensors

Positive semi-definiteness and spectral properties of tensors are important topics in tensor computation and multilinear algebra. In this paper, we study positive semi-definiteness and extremal $H$-eigenvalues of extended essentially nonnegative tensors. We first prove that checking positive semi-definiteness of a symmetric extended essentially nonnegative tensor is equivalent to checking positive semi-definiteness of all its condensed subtensors. Then, we prove that, for a symmetric positive semi-definite extended essentially nonnegative tensor, it has a sum-of-squares (SOS) tensor decomposition if each positive off-diagonal element corresponds to an SOS term in the homogeneous polynomial of the tensor. Using this result, we can compute the minimum $H$-eigenvalue of such kinds of extended essentially nonnegative tensors. Then, for general symmetric even order extended essentially nonnegative tensors, we show that the largest $H$-eigenvalue of the tensor is equivalent to the optimal value of an SOS programming problem. As an application, we show this approach can be used to check copositivity of symmetric extended $Z$-tensors. Numerical experiments are given to show the efficiency of the proposed methods.
Relationship Between the Expression of LC3 (Microtubule-Associated Protein 1A/1B-Light Chain 3) in Nasal Mucosa and Serum IL-5 and IL-4 Concentrations in Allergic Rhinitis Mice

Objective To investigate the expression and correlation of autophagy-related microtubule-associated protein 1 light chain 3 beta LC3 and interleukin-5 IL-5 in allergic rhinitis AR. Methods Fifty-six 7-week-old BALC/C mice were randomly divided into experimental group (n = 56) and control group (n = 8). The experimental group used Dermatophagoides farinae (Der f) for AR modeling, and control group used PBS solution. As the experimental group sampled at 6 time points, and 8 mice were sacrificed each time, while the control group was sacrificed 24 hours after the last dose. The contents of serum IL-4, IL-5, and dust mite specific IgE HDM-sIgE in mice were detected by enzyme-linked immunosorbent assay ELISA, and the morphological changes of nasal mucosa were detected by a hematoxylin-eosin H&E staining. The expression of LC3 in mouse nasal mucosa was detected by immunohistochemical staining. Spearman correlation coefficient was used to assess the relationship between LC3 and IL-5 levels. Results In AR mice modelled with dust mites, the serum levels of IL-4 and HDM-sIgE increased gradually, and the serum IL-5 concentration had a peak at the early intraperitoneal administration stage similar to that at the end of modelling. The LC3 level in nasal mucosa of AR mice modelled with dust mites increased gradually in the early stages, but stabilized in the later stages. The expression of LC3 level in nasal mucosa was a positively correlated ration between serum IL-5 level in AR mice. Conclusion In the early stage of AR mice, the level of nasal mucosal autophagy and serum IL-5 levels were significantly increased and correlated, suggesting that nasal mucosal autophagy played a promoting role in the early stage of AR.
Application of Firefly and Flower Pollination Algorithm for Wireless Sensor Network Localization

A wireless sensor network is a cluster of sensors that work communally to carry out a certain important job. The nodes that make up these sensor clusters have their own power and communication capabilities with the other nodes in the cluster. Identification of the sensor locations inside the cluster is necessary for accurate data analysis. Only then, based on the signal and position, can the appropriate action be done. In wireless sensor network (WSN), a select few sensor positions are referred to as anchors, and it is from such anchors that the positions of unknown sensors have been inferred. The location of the sensors is identified using firefly and flower pollination algorithms (FFPA) in this research work. The effectiveness of the proposed technique is assessed by evaluating their accuracy of the position and convergence rate. The firefly and flower pollination algorithms are utilized to detect the position of the unidentified sensor nodes after the ninth iteration. When we compare both algorithms, the firefly algorithm is incapable to discover the nodes which are available in the location area. From the results it is evident that the flower pollination algorithm successfully identifies all the unknown sensor locations.
Design of new robust backstepping control for three-phase grid-connected fourleg source voltage PWM converters

Due to high performance demands of grid-connected pulse-width modulation (PWM) converters in power applications, backstepping control (BSC) has drawn wide research interest for its advantages, including high robustness against parametric variations and external disturbances. In order to guarantee these advantages while providing high static and dynamic responses, in this work, a robust BSC (RBSC) with consideration of grid-connected PWM converter parameter uncertainties is proposed for three-phase grid-connected four-leg voltage source rectiﬁers (GC-FLVSR). The proposed RBSC for GC-FLVSR is composed of four independent controllers based on the Lyabonov theory that control DC bus voltage and input currents simultaneously. As a result, unit power factor, stable DC-bus voltage, sinusoidal four-leg rectiﬁer input currents with lower harmonics and zero-sequence (ZS), and natural currents can be accurately achieved. Furthermore, the stability and robustness against load, DC capacitor, and ﬁlter inductance variations can be tested. The eﬀectiveness and superiority of the proposed RBSC compared to the PI control (PIC) have been validated by processor-in-the-loop (PIL) co-simulation using the STM32F407 discovery-development-board as an
Seeded Sequential LDA: A Semi-Supervised Algorithm for Topic-Specific Analysis of Sentences

Topic models have been widely used by researchers across disciplines to automatically analyze large textual data. However, they often fail to automate content analysis, because the algorithms cannot accurately classify individual sentences into pre-defined topics. Aiming to make topic classification more theoretically grounded and content analysis in general more topic-specific, we have developed Seeded Sequential Latent Dirichlet allocation (LDA), extending the existing LDA algorithm, and implementing it in a widely accessible open-source package. Taking a large corpus of speeches delivered by delegates at the United Nations General Assembly as an example, we explain how our algorithm differs from the original algorithm; why it can classify sentences more accurately; how it accepts pre-defined topics in deductive or semi-deductive analysis; how such ex-ante topic mapping differs from ex-post topic mapping; how it enables topic-specific framing analysis in applied research. We also offer practical guidance on how to determine the optimal number of topics and select seed words for the algorithm.