Miracle-dz/UniFAR-FTUs huggingface dataset:
Mesenchymal Stem Cell Therapy in Traumatic Spinal Cord Injury: A Systematic Review

Recovery from a traumatic spinal cord injury (TSCI) is challenging due to the limited regenerative capacity of the central nervous system to restore cells, myelin, and neural connections. Cell therapy, particularly with mesenchymal stem cells (MSCs), holds significant promise for TSCI treatment. This systematic review aims to analyze the efficacy, safety, and therapeutic potential of MSC-based cell therapies in TSCI. A comprehensive search of PUBMED and COCHRANE databases until February 2023 was conducted, combining terms such as “spinal cord injury,” “stem cells,” “stem cell therapy,” “mesenchymal stem cells,” and “traumatic spinal cord injury”. Among the 53 studies initially identified, 22 (21 clinical trials and 1 case series) were included. Findings from these studies consistently demonstrate improvements in AIS (ASIA Impairment Scale) grades, sensory scores, and, to a lesser extent, motor scores. Meta-analyses further support these positive outcomes. MSC-based therapies have shown short- and medium-term safety, as indicated by the absence of significant adverse events within the studied timeframe. However, caution is required when drawing generalized recommendations due to the limited scientific evidence available. Further research is needed to elucidate the long-term safety and clinical implications of these advancements. Although significant progress has been made, particularly with MSC-based therapies, additional studies exploring other potential future therapies such as gene therapies, neurostimulation techniques, and tissue engineering approaches are essential for a comprehensive understanding of the evolving TSCI treatment landscape.
Impact of biased scores on ranking in bipartite competition networks and inference of modular structure via generalized modularity

In the common jury-contestant competition format, a jury consisting of multiple judges grade contestants on their performances to determine their ranking. Unlike in another common competition format where two contestants play a head-to-head match to produce the winner such as in football or basketball, the objectivity of judges are often called into question, potentially undermining the public's trust in the fairness of the competition. In this work we show, by modeling the jury-contestant competition format as a weighted bipartite network, how one can identify biased scores and how they impact the competition and its structure. Analyzing the prestigious International Chopin Piano Competition of 2015 as an example with a well-publicized scoring controversy, we show that the presence of even a very small fraction of biased edges can gravely distort our inference of the network structure —in the example a single biased edge is shown to lead to an incorrect “solution” that also wrongly appears to be robust exclusively, dominating other reasonable solutions— highlighting the importance of bias detection and elimination in network inference. In the process our work also presents a modified modularity measure for the one-mode projection of weighted complete bipartite networks.
Response of rhizobium inoculation on growth and productivity of fenugreek (Trigonella foenum-greacum) under salt stress condition

Soil salinity is a major restriction to crop production in many areas of the world. Crops growing in salt-affected soils may suffer from many physiological stress and ion toxicity which then lead to reduced growth and productivity. The present study was under taken on the effect of salinity and rhizobium inoculated seeds on plant growth and productivity of fenugreek (Trigonella foenum-greacum L.) cultivars (NDM-17 and Pusa Kasauri). The pot experiment was conducted in completely randomized block design with three replicates. Two sets of pot trails were maintained in which one inoculated with effective rhizobium strain (Rhizobium meliloti) while other set was uninoculated. Both sets were irrigated with saline water of different electrical conductivities (0, 3, 6, 7, 10, 12 and 14 dS/m). Salinity stress registered the highest detrimental effects on growth and productivity. Present findings revealed that the inoculated seeds with effective rhizobium strain minimized the deleterious effect of salinity at all levels. The maximum growth and productivity was found in NDM-17 in both sets inoculated and uninoculated with rhizobium as compared to Pusa Kasauri.
A Study of Particle Beam Spin Dynamics for High Precision Experiments

A STUDY OF PARTICLE BEAM SPIN DYNAMICS FOR HIGH PRECISION EXPERIMENTS Andrew J. Fiedler, MS Department of Physics Northern Illinois University, 2017 Michael Syphers, Director In the search for physics beyond the Standard Model, high precision experiments to measure fundamental properties of particles are an important frontier. One group of such measurements involves magnetic dipole moment (MDM) values as well as searching for an electric dipole moment (EDM), both of which could provide insights about how particles interact with their environment at the quantum level and if there are undiscovered new particles. For these types of high precision experiments, minimizing statistical uncertainties in the measurements plays a critical role. This work leverages computer simulations to quantify the effects of statistical uncertainty for experiments investigating spin dynamics. In it, analysis of beam properties and lattice design effects on the polarization of the beam is performed. As a case study, the beam lines that will provide polarized muon beams to the Fermilab Muon g-2 experiment are analyzed to determine the effects of correlations between the phase space variables and the overall polarization of the muon beam. NORTHERN ILLINOIS UNIVERSITY DE KALB, ILLINOIS MAY 2017 A STUDY OF PARTICLE BEAM SPIN DYNAMICS FOR HIGH PRECISION EXPERIMENTS BY ANDREW J. FIEDLER c © 2017 Andrew J. Fiedler A THESIS SUBMITTED TO THE GRADUATE SCHOOL IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE MASTER OF SCIENCE DEPARTMENT OF PHYSICS Thesis Director: Michael Syphers
The dynamics of spanwise vorticity perturbations in homogeneous viscoelastic shear flow

The viscoelastic analogue to the Newtonian Orr amplification mechanism is examined using linear theory. A weak, two-dimensional Gaussian vortex is superposed onto a uniform viscoelastic shear flow. Whilst in the Newtonian solution the spanwise vorticity perturbations are simply advected, the viscoelastic behaviour is markedly different. When the polymer relaxation rate is much slower than the rate of deformation by the shear, the vortex splits into a new pair of co-rotating but counter-propagating vortices. Furthermore, the disturbance exhibits a significant amplification in its spanwise vorticity as it is tilted forward by the shear. Asymptotic solutions for an Oldroyd-B fluid in the limits of high and low elasticity isolate and explain these two effects. The splitting of the vortex is a manifestation of vorticity wave propagation along the tensioned mean-flow streamlines, while the spanwise vorticity growth is driven by the amplification of a polymer torque perturbation. The analysis explicitly demonstrates that the polymer torque amplifies as the disturbance becomes aligned with the shear. This behaviour is opposite to the Orr mechanism for energy amplification in Newtonian flows, and is therefore labelled a ‘reverse-Orr’ mechanism. Numerical evaluations of vortex evolutions using the more realistic FENE-P model, which takes into account the finite extensibility of the polymer chains, show the same qualitative behaviour. However, a new form of stress perturbation is established in regions where the polymer is significantly stretched, and results in an earlier onset of decay.
Tumor-resident memory T cells as a biomarker of the response to cancer immunotherapy

Tumor-infiltrating lymphocytes (TIL) often include a substantial subset of CD8+ tissue-resident memory T (TRM) cells enriched in tumor-specific T cells. These TRM cells play a major role in antitumor immune response. They are identified on the basis of their expression of the CD103 (αE(CD103)β7) and/or CD49a (α1(CD49a)β1) integrins, and the C-type lectin CD69, which are involved in tissue residency. TRM cells express several T-cell inhibitory receptors on their surface but they nevertheless react strongly to malignant cells, exerting a strong cytotoxic function, particularly in the context of blocking interactions of PD-1 with PD-L1 on target cells. These TRM cells form stable conjugates with autologous tumor cells and interact with dendritic cells and other T cells within the tumor microenvironment to orchestrate an optimal in situ T-cell response. There is growing evidence to indicate that TGF-β is essential for the formation and maintenance of TRM cells in the tumor, through the induction of CD103 expression on activated CD8+ T cells, and for the regulation of TRM effector functions through bidirectional integrin signaling. CD8+ TRM cells were initially described as a prognostic marker for survival in patients with various types of cancer, including ovarian, lung and breast cancers and melanoma. More recently, these tumor-resident CD8+ T cells have been shown to be a potent predictive biomarker of the response of cancer patients to immunotherapies, including therapeutic cancer vaccines and immune checkpoint blockade. In this review, we will highlight the major characteristics of tumor TRM cell populations and the possibilities for their exploitation in the design of more effective immunotherapy strategies for cancer.
RGB-D SLAM in indoor dynamic environments with two channels based on scenario classification

In visual simultaneous localization and mapping (SLAM) systems, the limitations of the assumption of scene rigidity are usually broken by using learning-based or geometry-based methods. However, learning-based methods usually have a high time cost, and geometry-based methods usually do not result in clean maps which are useful for advanced robotic applications. In this paper, an RGB-D SLAM in indoor dynamic environments with two channels that classifies frames as slightly and highly dynamic scenarios based on matching accuracy is proposed. And a geometric constraint based on Hamming distance is proposed to improve the effectiveness of matching accuracy as a basis for scenario classification. Dynamic features are detected by affine consistency constraint and semantic method. The semantic method is only used for highly dynamic scenarios to reduce the time cost of dynamic feature detection and provide a basis for mapping. Furthermore, an improved adaptive threshold algorithm is proposed to improve the robustness of feature matching. The proposed method is evaluated in the TUM RGB-D dataset and a real scenario. The experimental results demonstrate that the proposed method achieves highly accurate tracking with appreciable time cost in both slightly and highly indoor dynamic environments while obtaining effective maps.
Convergence of Averages in Ergodic Theory

Von Neumann’s Mean Ergodic Theorem and Birkhoff’s Pointwise Ergodic Theorem lie in the foundation of Ergodic Theory. Over the years there have been many generalizations of the two, most recently a version of pointwise ergodic theorem for measure-preserving actions of amenable groups due to Elon Lindenstrauss. In the first chapter, we extend some of Lindenstrauss’ results to measure-preserving actions of countable left-cancellative amenable semigroups and to averaging along more general types of Følner sequences. In the next three chapters, we study convergence of Cesàro averages of the form 1 |Ln| ∑ g∈Ln s ∏ i=1 T (i) g fi for measure-preserving actions of countable amenable groups, where (Ln) is a Følner sequence. We extend some of the results obtained by D. Berend and V. Bergelson for joint properties of Z-actions to joint properties of actions of countable amenable groups. In particular, we obtain a criterion for joint ergodicity of actions of countable amenable groups by automorphisms of a not necessarily abelian compact group. In the last chapter of this dissertation, we investigate convergence of Cesàro averages for two non-commuting measure-preserving transformations along a regular sequence of intervals, i.e. we study averages of the form 1 bn − an bn ∑ k=an T f · Sg, (1)
INGENIERÍA DE REQUERMIENTOS E INTELIGENCIA ARTIFICIAL: UNA REVISIÓN DE LA LITERATURA

El presente estudio esboza una revisión sistemática de documentos que permitieron identificar cómo se han integrado diferentes algoritmos de inteligencia artificial en herramientas y procesos para el desarrollo y administración de ingeniería de requerimientos. Los resultados apuntan a que las principales tendencias en la ingeniería de requerimientos incluyen temas desde la clasificación y priorización de los requerimientos, la obtención de los requisitos de seguridad, la validación de las revisiones de los requisitos y la minería de procesos, y en cada aspecto es posible incorporar la aplicación de técnicas de inteligencia artificial. Dentro de los usos más destacados de IA se encuentra la detección de la ambigüedad de los requisitos, la identificación de la incertidumbre en los requisitos contextuales y la clasificación de los requisitos para comprobar la redundancia y la incoherencia.
Hantavirus infections in the South‑Eastern European countries: A study of two cases and literature review

Hantavirus infection is a rare zoonosis in South-Eastern Europe. Depending on the serotype involved, the virus can cause hemorrhagic fever with renal syndrome which is also known as endemic nephropathy, and cardiopulmonary syndrome. Prompt diagnosis of the disease is essential for reducing the risk of severe manifestations and complications like chronic kidney disease, secondary hypertension or even death because there is no specific treatment or vaccine approved. The present study reported two cases of hemorrhagic fever with renal syndrome diagnosed in the Department of Nephrology of The Fundeni Clinical Institute (Romania). In both patients, kidney needle biopsy played a major role in establishing the diagnosis. The difficulties encountered in diagnosing this disease were also emphasized, taking into consideration the rarity of this infection in South-Eastern Europe. The key literature data on the epidemiology, pathogenesis and management of this infection were further reviewed.
A modified cubic B-spline differential quadrature method for three-dimensional non-linear diffusion equations

Abstract This paper employs a differential quadrature scheme for solving non-linear partial differential equations. Differential quadrature method (DQM), along with modified cubic B-spline basis, has been adopted to deal with three-dimensional non-linear Brusselator system, enzyme kinetics of Michaelis-Menten type problem and Burgers’ equation. The method has been tested efficiently to three-dimensional equations. Simple algorithm and minimal computational efforts are two of the major achievements of the scheme. Moreover, this methodology produces numerical solutions not only at the knot points but also at every point in the domain under consideration. Stability analysis has been done. The scheme provides convergent approximate solutions and handles different cases and is particularly beneficial to higher dimensional non-linear PDEs with irregularities in initial data or initial-boundary conditions that are discontinuous in nature, because of its capability of damping specious oscillations induced by high frequency components of solutions.
A Global Poincaré inequality on Graphs via a Conical Curvature-Dimension Condition

Abstract We introduce and study the conical curvature-dimension condition, CCD(K, N), for finite graphs.We show that CCD(K, N) provides necessary and sufficient conditions for the underlying graph to satisfy a sharp global Poincaré inequality which in turn translates to a sharp lower bound for the first eigenvalues of these graphs. Another application of the conical curvature-dimension analysis is finding a sharp estimate on the curvature of complete graphs
SELF-RELIANCE CHARACTERISTICS IN TAYLOR SWIFT'S SONGS: A STUDY ON LYRICS AND MESSAGES

This research aims to contribute to the exploration of self-reliance by examining the lyrics of Taylor Swift’s songs. This research intends to categorizing the data based on the kinds of self-reliance characteristics in Taylor Swift songs’ lyrics and describing the contextual meanings which implied in Taylor Swift’s songs’ lyrics. The data were collected from Taylor Swift’s album “Lover”, with a focus on three of her songs, including “The Man”, “ME! ”, and “You Need to Calm Down”. The research employed a descriptive qualitative approach to analyze the data, which was obtained by a thorough examination of the lyrics and close listening to the songs. Subsequently, the data was classified according to the self-reliance concept proposed by Ralph Waldo Emerson. The study findings indicate the existence three different characteristics of self-reliance, including trust in oneself, nonconformity and independent thinking. Significantly, the most dominant of these characteristics was nonconformity, it found four lines of lyrics in all song which has examined. The study also identified two lines of lyrics in “The Man” and “ME! ” that express true in oneself characteristics, three lines of lyrics in “ME! ” and “You Need to Calm Down” that illustrate the independent thinking. The objective of this study is to make contribution to the current discourse on the important of self-reliance in modern society by examining the self-reliance characteristics found in Taylor Swift’s songs’ lyrics. Furthermore, the result of this study may have implication for the role of music, art and literary work in promoting values such as individualism, self-reliance and nonconformity.
Biocompatibility and inflammatory response of silver tungstate, silver molybdate, and silver vanadate microcrystals

Silver tungstate (α-Ag2WO4), silver molybdate (β-Ag2MoO4), and silver vanadate (α-AgVO3) microcrystals have shown interesting antimicrobial properties. However, their biocompatibility is not yet fully understood. Cytotoxicity and the inflammatory response of silver-containing microcrystals were analyzed in THP-1 and THP-1 differentiated as macrophage-like cells, with the alamarBlue™ assay, flow cytometry, confocal microscopy, and ELISA. The present investigation also evaluated redox signaling and the production of cytokines (TNFα, IL-1β, IL-6, and IL-8) and matrix metalloproteinases (MMP-8 and -9). The results showed that α-AgVO3 (3.9 μg/mL) did not affect cell viability (p > 0.05). α-Ag2WO4 (7.81 μg/mL), β-Ag2MoO4 (15.62 μg/mL), and α-AgVO3 (15.62 μg/mL) slightly decreased cell viability (p ≤ 0.003). All silver-containing microcrystals induced the production of O2 − and this effect was mitigated by Reactive Oxygen Species (ROS) scavenger and N-acetylcysteine (NAC). TNFα, IL-6 and IL-1β were not detected in THP-1 cells, while their production was either lower (p ≤ 0.0321) or similar to the control group (p ≥ 0.1048) for macrophage-like cells. The production of IL-8 by both cellular phenotypes was similar to the control group (p ≥ 0.3570). The release of MMP-8 was not detected in any condition in THP-1 cells. Although MMP-9 was released by THP-1 cells exposed to α-AgVO3 (3.9 μg/mL), no significant difference was found with control (p = 0.7). Regarding macrophage-like cells, the release of MMP-8 and -9 decreased in the presence of all microcrystals (p ≤ 0.010). Overall, the present work shows a promising biocompatibility profile of, α-Ag2WO4, β-Ag2MoO4, and α-AgVO3 microcrystals.
Dielectric properties characterization of saline solutions by near-field microwave microscopy

Saline solutions are of a great interest when characterizations of biological fluids are targeted. In this work a near-field microwave microscope is proposed for the characterization of liquids. An interferometric technique is suggested to enhance measurement sensitivity and accuracy. The validation of the setup and the measurement technique is conducted through the characterization of a large range of saline concentrations (0–160 mg ml−1). Based on the measured resonance frequency shift and quality factor, the complex permittivity is successfully extracted as exhibited by the good agreement found when comparing the results to data obtained from Cole–Cole model. We demonstrate that the near field microwave microscope (NFMM) brings a great advantage by offering the possibility to select a resonance frequency and a quality factor for a given concentration level. This method provides a very effective way to largely enhance the measurement sensitivity in high loss materials.
A review of combined neuromodulation and physical therapy interventions for enhanced neurorehabilitation

Rehabilitation approaches for individuals with neurologic conditions have increasingly shifted toward promoting neuroplasticity for enhanced recovery and restoration of function. This review focuses on exercise strategies and non-invasive neuromodulation techniques that target neuroplasticity, including transcranial magnetic stimulation (TMS), vagus nerve stimulation (VNS), and peripheral nerve stimulation (PNS). We have chosen to focus on non-invasive neuromodulation techniques due to their greater potential for integration into routine clinical practice. We explore and discuss the application of these interventional strategies in four neurological conditions that are frequently encountered in rehabilitation settings: Parkinson’s Disease (PD), Traumatic Brain Injury (TBI), stroke, and Spinal Cord Injury (SCI). Additionally, we discuss the potential benefits of combining non-invasive neuromodulation with rehabilitation, which has shown promise in accelerating recovery. Our review identifies studies that demonstrate enhanced recovery through combined exercise and non-invasive neuromodulation in the selected patient populations. We primarily focus on the motor aspects of rehabilitation, but also briefly address non-motor impacts of these conditions. Additionally, we identify the gaps in current literature and barriers to implementation of combined approaches into clinical practice. We highlight areas needing further research and suggest avenues for future investigation, aiming to enhance the personalization of the unique neuroplastic responses associated with each condition. This review serves as a resource for rehabilitation professionals and researchers seeking a comprehensive understanding of neuroplastic exercise interventions and non-invasive neuromodulation techniques tailored for specific diseases and diagnoses.
Low-Cost Attitude and Heading Reference System Filter Using Complementary Method

This paper presents an orientation filter using complementary filter applicable to low-cost sensors based on micro electro-mechanical system (MEMS). The MEMS implementation incorporates magnetic distortion and gyroscope bias drift compensation. The filter uses a quaternion representation, allowing accelerometer and magnetometer data to be used in an analytically derived and optimized gradient-descent algorithm to compute the direction of the gyroscope measurement error as a quaternion derivative. The benefits of the filter are: (1) low scalar arithmetic operations for each filter update, (2) It is effective at low sampling rates; e.g. 10 Hz and (3) It contains adjustable parameters defined by observable system characteristics. The Performance was evaluated empirically using a commercially available orientation sensor and reference measurements of orientation obtained using an accurate servo motor (resolution < 0.3 degree). A simple calibration method is presented for the use of the electric-mechanical measurement equipment in this application. Results indicate that the filter achieves levels of accuracy exceeding that of the Kalman-based algorithm; < 0.821 ◦ for static RMS error and < 2.093 ◦ for dynamic RMS (Root Mean Square) error. The implications of the low computational load and ability to operate at low sampling rates use of MARG (Magnetic, Angular Rate, and Gravity) sensor arrays in real-time applications of limited power, processing resources or applications that demand extremely high sampling rates.