Miracle-dz/UniFAR-FTUs huggingface dataset:
Detecting key sentences for automatic assistance in peer reviewing research articles in educational sciences

The evaluation of scientific performance is gaining importance in all research disciplines. The basic process of the evaluation is peer reviewing, which is a time-consuming activity. In order to facilitate and speed up peer reviewing processes we have developed an exploratory NLP system in the field of educational sciences. The system highlights key sentences, which are supposed to reflect the most important threads of the article The highlighted sentences offer guidance on the content-level while structural elements -- the title, abstract, keywords, section headings -- give an orientation about the design of the argumentation in the article. The system is implemented using a discourse analysis module called concept matching applied on top of the Xerox Incremental Parser, a rule-based dependency parser. The first results are promising and indicate the directions for the future development of the system.
A Clinical Decision Support Framework for Incremental Polyps Classification in Virtual Colonoscopy

Abstract: We present in this paper a novel dynamic learning method for classifying polyp candidate detections in Computed Tomographic Colonography (CTC) using an adaptation of the Least Square Support Vector Machine (LS-SVM). The proposed technique, called Weighted Proximal Support Vector Machines ( WP-SVM ), extends the offline capabilities of the SVM scheme to address practical CTC applications. Incremental data are incorporated in the WP-SVM as a weighted vector space, and the only storage requirements are the hyper-plane parameters. WP-SVM performance evaluation based on 169 clinical CTC cases using a 3D computer-aided diagnosis (CAD) scheme for feature reduction comparable favorably with previously published CTC CAD studies that have however involved only binary and offline classification schemes. The experimental results obtained from iteratively applying WP-SVM to improve detection sensitivity demonstrate its viability for incremental learning, thereby motivating further follow on research to address a wider range of true positive subclasses such as pedunculated, sessile, and flat polyps, and over a wider range of false positive subclasses such as folds, stool, and tagged materials.
Arterial Wall Response to ex vivo Exposure to Oscillatory Shear Stress

Background: The aim of this study was to analyze the arterial wall response to plaque-prone hemodynamic environments, known to occur mainly in areas of arterial trees such as bifurcations and branching points. In these areas, the vasculature is exposed to cyclically reversing flow that induces an endothelial dysfunction predisposing thus arteries to local development of atherosclerotic plaques. Methods: We used an ex vivo perfusion system that allows culturing arterial segments under different hemodynamic conditions. Porcine carotid arteries were exposed for 3 days to unidirectional high and low shear stress (6 ± 3 and 0.3 ± 0.1 dyn/cm2) as well as to oscillatory shear stress (0.3 ± 3 dyn/cm2). This latter condition mimics the hemodynamics present at plaque-prone areas. At the end of the perfusion, the influence of different flow patterns on arterial metabolism was assessed in terms of matrix turnover as well as of smooth muscle cell function, differentiation and migration. Results: Our results show that after 3 days of perfusion none of the applied conditions influence smooth muscle cell phenotype retaining their full contraction capacity. However, an increase in the expression level of matrix metalloproteinase-2 and -9, as well as a decrease in plasminogen activator inhibitor-1 expression were observed in arteries exposed to oscillatory shear stress when compared to arteries exposed to unidirectional shear stress. Conclusion: These observations suggest that plaque-prone hemodynamic environment triggers a vascular wall remodelling process and promotes changes in arterial wall metabolism, with important implication in atherogenesis.
Active Trunk Stiffness During Voluntary Isometric Flexion and Extension Exertions

Objective: Compare muscle activity and trunk stiffness during isometric trunk flexion and extension exertions. Background: Elastic stiffness of the torso musculature is considered the primary stabilizing mechanism of the spine. Therefore, stiffness of the trunk during voluntary exertions provides insight into the stabilizing control of pushing and pulling tasks. Methods: Twelve participants maintained an upright posture against external flexion and extension loads applied to the trunk. Trunk stiffness, damping, and mass were determined from the dynamic relation between pseudorandom force disturbances and subsequent small-amplitude trunk movements recorded during the voluntary exertions. Muscle activity was recorded from rectus abdominus, external oblique, lumbar paraspinal, and internal oblique muscle groups. Results: Normalized electromyographic activity indicated greater antagonistic muscle recruitment during flexion exertions than during extension. Trunk stiffness was significantly greater during flexion exertions than during extension exertions despite similar levels of applied force. Trunk stiffness increased with exertion effort. Conclusion: Theoretical and empirical analyses reveal that greater antagonistic cocontraction is required to maintain spinal stability during trunk flexion exertions than during extension exertions. Measured differences in active trunk stiffness were attributed to antagonistic activity during flexion exertions with possible contributions from spinal kinematics and muscle lines of action. Application: When compared with trunk extension exertions, trunk flexion exertions such as pushing tasks require unique neuromuscular control that is not simply explained by differences in exertion direction. Biomechanical analyses of flexion tasks must consider the stabilizing muscle recruitment patterns when evaluating spinal compression and shear loads.
Nonholonomic Equivalent Disturbance Based Backward Motion Control of Tractor-Trailer With Virtual Steering

This paper describes a strategy of backward motion control in a tractor-trailer system. The backward motion of a tractor-trailer requires skilled control, because the position and orientation of the trailer can only be controlled by an input to the tractor. When a driver changes orientation while driving backward, the steering angle must be skillfully controlled. This operation is different in the case of a single vehicle moving backward. An uncontrollable situation of a tractor-trailer motion often happens, for example, the "jackknife phenomenon. " Such a situation is often induced by the nonholonomic constraint of a wheeled system. In this research, virtual steering is introduced to a trailer. This virtual steering controls the orientation of the trailer and suppresses the nonholonomic equivalent disturbance. With this virtual steering, the tractor-trailer is able to track a straight trajectory in backward driving independently of the nonholonomic constraint. Several numerical and experimental results are shown to confirm the validity of the proposed approach.
Long-term vasopressin-V2-receptor stimulation induces regulation of aquaporin 4 protein in renal inner medulla and cortex of Brattleboro rats.

BACKGROUND Desmopressin (dDAVP) induces a decrease in immunolabelling of aquaporin (AQP) 4 protein in the terminal inner medulla (IM) of the Brattleboro (BB) rat kidney. It is disputed, however, whether the decreased labelling reflects real down-regulation of protein abundance, or whether it is a result of epitope shielding in the AQP4 protein, preventing binding of the antibody as previously suggested. Furthermore, it is unknown if vasopressin regulates AQP4 in the connecting tubule (CNT) and in the cortical collecting duct (CCD). Using BB rats, we aimed to determine (i) whether the dDAVP-induced decrease in AQP4 labelling in the terminal IM reflects down-regulation in protein abundance and (ii) whether dDAVP increases the AQP4 protein abundance in the CNT and the CCD. METHODS BB rats received dDAVP or saline (control) via osmotic minipumps pumps for 6 days. RESULTS Immunolight microscopy revealed strong AQP4 labelling in the initial inner medullary collecting duct (IMCD1), weak labelling in the middle IMCD (IMCD2) and weak/absent labelling in the terminal IMCD (IMCD3) after 6 days of dDAVP administration. AQP3 labelling was similar to that of AQP4. Two-hour administration with dDAVP (previously described BB rats) did not change the labelling pattern of AQP4, suggesting that potential acute phosphorylation did not induce epitope shielding, thereby preventing the binding of the antibody. CONCLUSIONS In BB rats, long-term administration with dDAVP (i) increased the AQP4 protein abundance in the IMCD1 and decreased the abundance in the IMCD2 and the IMCD3, and (ii) increased the AQP4 protein abundance in the CNT and the CCD.
Commensal Microbiota Contributes to Chronic Endocarditis in TAX1BP1 Deficient Mice

Tax1-binding protein 1 (Tax1bp1) negatively regulates NF-κB by editing the ubiquitylation of target molecules by its catalytic partner A20. Genetically engineered TAX1BP1-deficient (KO) mice develop age-dependent inflammatory constitutions in multiple organs manifested as valvulitis or dermatitis and succumb to premature death. Laser capture dissection and gene expression microarray analysis on the mitral valves of TAX1BP1-KO mice (8 and 16 week old) revealed 588 gene transcription alterations from the wild type. SAA3 (serum amyloid A3), CHI3L1, HP, IL1B and SPP1/OPN were induced 1,180-, 361-, 187-, 122- and 101-fold respectively. WIF1 (Wnt inhibitory factor 1) exhibited 11-fold reduction. Intense Saa3 staining and significant I-κBα reduction were reconfirmed and massive infiltration of inflammatory lymphocytes and edema formation were seen in the area. Antibiotics-induced ‘germ free’ status or the additional MyD88 deficiency significantly ameliorated TAX1BP1-KO mice's inflammatory lesions. These pathological conditions, as we named ‘pseudo-infective endocarditis’ were boosted by the commensal microbiota who are usually harmless by their nature. This experimental outcome raises a novel mechanistic linkage between endothelial inflammation caused by the ubiquitin remodeling immune regulators and fatal cardiac dysfunction.
Parametric estimate of intensity inhomogeneities applied to MRI

Presents a new approach to the correction of intensity inhomogeneities in magnetic resonance imaging (MRI) that significantly improves intensity-based tissue segmentation. The distortion of the image brightness values by a low-frequency bias field impedes visual inspection and segmentation. The new correction method called parametric bias field correction (PABIC) is based on a simplified model of the imaging process, a parametric model of tissue class statistics, and a polynomial model of the inhomogeneity field. The authors assume that the image is composed of pixels assigned to a small number of categories with a priori known statistics. Further they assume that the image is corrupted by noise and a low-frequency inhomogeneity field. The estimation of the parametric bias field is formulated as a nonlinear energy minimization problem using an evolution strategy (ES). The resulting bias field is independent of the image region configurations and thus overcomes limitations of methods based on homomorphic filtering. Furthermore, PABIC can correct bias distortions much larger than the image contrast. Input parameters are the intensity statistics of the classes and the degree of the polynomial function. The polynomial approach combines bias correction with histogram adjustment, making it well suited for normalizing the intensity histogram of datasets from serial studies. The authors present simulations and a quantitative validation with phantom and test images. A large number of MR image data acquired with breast, surface, and head coils, both in two dimensions and three dimensions, have been processed and demonstrate the versatility and robustness of this new bias correction scheme.
Angiotensin-Converting Enzyme (ACE) Gene Insertion/Deletion Polymorphism and ACE Inhibitor-Related Cough: A Meta-Analysis

Objective An insertion/deletion (I/D) variant in the angiotensin-converting enzyme (ACE) gene was associated with ACE inhibitor (ACEI)–related cough in previous studies. However, the results were inconsistent. Our objective was to assess the relationship between the ACE I/D polymorphism and ACEI-related cough by meta-analysis and to summarize all studies that are related to ACE I/D polymorphism and ACEI-cough and make a summary conclusion to provide reference for the researchers who attempt to conduct such a study. Methods Databases including PubMed, EMbase, Cochrane Library, and China National Knowledge Infrastructure, were searched for genetic association studies. Data were extracted by two independent authors and pooled odds ratio (OR) with 95% confidence interval (CI) was calculated. Metaregression and subgroup analyses were performed to identify the source of heterogeneity. Results Eleven trials, including 906 cases (ACEI-related cough) and 1,175 controls, were reviewed in the present meta-analysis. The random effects pooled OR was 1.16 (95%CI: 0.78–1.74, p = 0.46) in the dominant model and 1.61 (95%CI: 1.18–2.20, p = 0.003) in the recessive model. Heterogeneity was found among and within studies. Metaregression indicated that the effect size was positively associated with age and negatively associated with follow-up duration of ACEI treatment. Subgroup analysis revealed a significant association between ACE I/D polymorphism and ACEI-related cough in studies with mean age >60 y, but not in studies with mean age ≤60 y. No heterogeneity was found within each mean age subgroup. We also found no association between ACE I/D polymorphism and ACEI-related cough in studies with follow-up>2 mo or in studies in Caucasians. No heterogeneity was detected in these two subgroups. Conclusions Synthesis of the available evidence supports ACE I/D polymorphism as an age-dependent predictor for risk of ACEI-related cough.
Trichinella spiralis Calreticulin Binds Human Complement C1q As an Immune Evasion Strategy

As a multicellular parasitic nematode, Trichinella spiralis regulates host immune responses by producing a variety of immunomodulatory molecules to escape from host immune attack, but the mechanisms underlying the immune evasion are not well understood. Here, we identified that T. spiralis calreticulin (Ts-CRT), a Ca2+-binding protein, facilitated T. spiralis immune evasion by interacting with the first component of human classical complement pathway, C1q. In the present study, Ts-CRT was found to be expressed on the surface of different developmental stages of T. spiralis as well as in the secreted products of adult and muscle larval worms. Functional analysis identified that Ts-CRT was able to bind to human C1q, resulting in the inhibition of C1q-initiated complement classical activation pathway reflected by reduced C4/C3 generation and C1q-dependent lysis of antibody-sensitized sheep erythrocytes. Moreover, recombinant Ts-CRT (rTs-CRT) binding to C1q suppressed C1q-induced THP-1-derived macrophages chemotaxis and reduced monocyte–macrophages release of reactive oxygen intermediates (ROIs). Blocking Ts-CRT on the surface of newborn larvae (NBL) of T. spiralis with anti-Ts-CRT antibody increased the C1q-mediated adherence of monocyte–macrophages to larvae and impaired larval infectivity. All of these results suggest that T. spiralis-expressed Ts-CRT plays crucial roles in T. spiralis immune evasion and survival in host mostly by directly binding to host complement C1q, which not only reduces C1q-mediated activation of classical complement pathway but also inhibits the C1q-induced non-complement activation of macrophages.
S-Restricted Monotone Alignments: Algorithm, Search Space, and Applications

We present a simple and straightforward alignment algorithm for monotone many-to-many alignments in grapheme-to-phoneme conversion and related fields such as morphology, and discuss a few noteworthy extensions. Moreover, we specify combinatorial formulas for monotone many-to-many alignments and decoding in G2P which indicate that exhaustive enumeration is generally possible, so that some limitations of our approach can easily be overcome. Finally, we present a decoding scheme, within the monotone many-to-many alignment paradigm, that relates the decoding problem to restricted integer compositions and that is, putatively, superior to alternatives suggested in the literature. Title and Abstract in German S-beschrankte monotone Alignierungen: Algorithmus, Suchraum und Anwendungen Wir prasentieren einen einfachen Alignment-Algorithmus fur monotone ‘many-tomany’ Alignierungen im Bereich Graphem-zu-Phonem-Konversion und verwandten Gebieten wie z.B. Morphologie, und besprechen sinnvolle Erweiterungen. Daruber hinaus geben wir kombinatorische Formeln im Bereich der monotonen ‘many-to-many’ Alignierungen und im Bereich des Decoding in G2P an, die suggerieren, dass vollstandige Enumeration hier im Allgemeinen moglich ist, sodass ein paar Einschrankungen unseres Ansatzes leicht behoben werden konnen. Schlieslich prasentieren wir ein Decoding-Schema, innerhalb des Paradigmas von ‘many-to-many’ Alignierungen, dass das Decoding-Problem mit beschrankten Zahlenkompositionen in Beziehung setzt und das in der Literatur vorgeschlagenen Alternativen vermeintlich uberlegen ist.
Construction of regulatory networks using expression time-series data of a genotyped population

The inference of regulatory and biochemical networks from large-scale genomics data is a basic problem in molecular biology. The goal is to generate testable hypotheses of gene-to-gene influences and subsequently to design bench experiments to confirm these network predictions. Coexpression of genes in large-scale gene-expression data implies coregulation and potential gene–gene interactions, but provide little information about the direction of influences. Here, we use both time-series data and genetics data to infer directionality of edges in regulatory networks: time-series data contain information about the chronological order of regulatory events and genetics data allow us to map DNA variations to variations at the RNA level. We generate microarray data measuring time-dependent gene-expression levels in 95 genotyped yeast segregants subjected to a drug perturbation. We develop a Bayesian model averaging regression algorithm that incorporates external information from diverse data types to infer regulatory networks from the time-series and genetics data. Our algorithm is capable of generating feedback loops. We show that our inferred network recovers existing and novel regulatory relationships. Following network construction, we generate independent microarray data on selected deletion mutants to prospectively test network predictions. We demonstrate the potential of our network to discover de novo transcription-factor binding sites. Applying our construction method to previously published data demonstrates that our method is competitive with leading network construction algorithms in the literature.
Physicochemical Aspects of Ultrathin Electrospun Zein Fibres for Encapsulation of Fish Oil

PHYSICOCHEMICAL ASPECTS OF ULTRATHIN ELECTROSPUN ZEIN FIBRES FOR ENCAPSULATION OF FISH OIL Khalid Moomand Advisor: University of Guelph , 2014 Dr. Loong-Tak Lim The ω-3 polyunsaturated fatty acids are beneficial to humans. The principal hurdle remains delivery of these fatty acids via foods or as nutraceuticals as they oxidize readily. In this study, an electrospinning method was developed to encapsulate fish oil, up to 30% (w/w), in zein fibres. The effects of aqueous ethanol and isopropanol solvents on the solubility of zein, viscosity, conductivity, and surface tension of the polymer solutions, were investigated and correlated with the morphology of the particles. Polymer solutions from both solvents exhibited shear-thinning behaviour, where ethanolic solutions had higher apparent viscosity values irrespective of the fish oil loading in comparison to isopropanolic solutions. Smooth and fibrous materials were generated from ethanol-based solutions, with increased diameter of 300 to 500 nm as the fish oil loading increased from 0 to 30% (w/w). Thinner fibres (190 ± 62 nm) with beads of an average size of 1 μm were produced from isopropanol zein solutions. Fish oil tends to migrate towards the core of the materials and concentrate in the beaded areas as a result of phase separation during the electrospinning process. This behaviour impacted encapsulation efficiency, loading capacity, as well as the stability of the fish oil when stored at 4, 25 and 60 °C for 14 days. The encapsulation efficiency of the electrospun zein fibres was 91% for ethanol-based and 96% for isopropanol-based fibres, at 30% (w/w) loading level. In addition to monitoring the formation of lipid peroxide, changes in covalent bond vibrations in fish oil and zein were studied using attenuated total reflection Fourier transform infrared (ATR-FTIR). Electrospun zein fibres provided a greater protection against oxidative degradation compared to the nonencapsulated fish oil. Aqueous ethanol solvent, in the presence of the added fish oil, promoted the formation of αhelix protein secondary structure, while isopropanol solvent promoted the formation of interand intramolecular β-sheet secondary structure. Under simulated gastrointestinal conditions, these electrospun materials exhibited gradual swelling and degradation rates while significantly higher when enzymes were introduced. The secondary structure of zein was impacted by the concentration of the polymer, solvent type, and exposure to SGI fluids.
Online data centering modifications for adaptive filtering with NLMS algorithm

This paper presents method with two modifications how to transform data in real-time for better performance of normalized least mean squares (NLMS) algorithm. The method centers input vector for adaptive filter online according to temporary or historical statistical attributes of the input vector. The method is derived for an adaptive filter with NLMS adaptation. The filter implementation is the linear neural unit. The stability condition for the given filter is also presented. The filter is tested on multiple simulated time series contaminated with white noise. The convergence of the suggested algorithms is also analyzed and time complexity is discussed.
Two Theorems on the Robust Designs of a Kind of Uncoupled CNNs with Applications

The cellular neural/nonlinear network (CNN) has become a new tool for image and signal processing, robotic and biological visions, and higher brain functions. The robust designs for CNN templates are one of the important issues for the practical applications of the CNNs. This paper sets up two new theorems for robust designs of a kind of uncoupled CNNs. The two theorems provide parameter inequalities to determine parameter intervals for implementing prescribed image processing functions, respectively. Four examples for detecting edges and corners in images are presented in order to illustrate the effectiveness of the methodology.