Miracle-dz/UniFAR-FTUs huggingface dataset:
microRNA Biology on Brain Development and Neuroimaging Approach

Proper brain development requires the precise coordination and orchestration of various molecular and cellular processes and dysregulation of these processes can lead to neurological diseases. In the past decades, post-transcriptional regulation of gene expression has been shown to contribute to various aspects of brain development and function in the central nervous system. MicroRNAs (miRNAs), short non-coding RNAs, are emerging as crucial players in post-transcriptional gene regulation in a variety of tissues, such as the nervous system. In recent years, miRNAs have been implicated in multiple aspects of brain development, including neurogenesis, migration, axon and dendrite formation, and synaptogenesis. Moreover, altered expression and dysregulation of miRNAs have been linked to neurodevelopmental and psychiatric disorders. Magnetic resonance imaging (MRI) is a powerful imaging technology to obtain high-quality, detailed structural and functional information from the brains of human and animal models in a non-invasive manner. Because the spatial expression patterns of miRNAs in the brain, unlike those of DNA and RNA, remain largely unknown, a whole-brain imaging approach using MRI may be useful in revealing biological and pathological information about the brain affected by miRNAs. In this review, we highlight recent advancements in the research of miRNA-mediated modulation of neuronal processes that are important for brain development and their involvement in disease pathogenesis. Also, we overview each MRI technique, and its technological considerations, and discuss the applications of MRI techniques in miRNA research. This review aims to link miRNA biological study with MRI analytical technology and deepen our understanding of how miRNAs impact brain development and pathology of neurological diseases.
Investigation of optical thin films printed on the surface of facets of photonic crystal fibers

Optical fibres are widely used in various applications as a medium for optical signals or optical transfer. This transport can be realized on long distance, compared to free space optics, which significantly extends reach of applications. Free space optics and fibre optics are combined in practice to yield the maximum performance of individual components forming a particular system. In such cases, light coupling from free space into fibres is required and it is frequently implemented with the use of lenses. An optical signal coupled into a fibre may also need certain modifications of spectral and spatial properties to allow its propagation down the fibre or reduce the amount of power carried in. The above requirement has been fulfilled by modifying surface of facets of photonic crystal fibres. By extrusion of a certain amount of host material from the surface, it is possible to obtain a structure resembling a thin film or an opaque layer for certain wavelengths. Several different structures of photonic crystal fibres and materials are considered to show influence of such thin-film on signal properties. This investigation is carried out in context of abilities of ablation of material from surfaces of photonic crystal fibres. Only certain shapes and geometrical arrangements can be considered. One of the goals is to specify, which of them are key for potential modification of spectral characteristics of photonic crystal fibres. The printed structures could potentially work like a thin-film ablation. Rigorous and versatile finite difference method has been employed to model propagation of light, its incidence onto a surface of the photonic crystal fibre, and subsequent propagation down the fibre. The simulations are carried on small pieces of photonic crystal fibres, with the length of tens of micrometres, due to well-known demands of the simulation technique on computational resources. Nevertheless, such a simplification is valid, since the structure is longitudinally uniform beyond the thin-film layer. However, this is aspect is not covered in the presented paper and it is our ongoing effort. Finally, the goal is to verify if the investigated structures can work as a slot waveguide.
Mixed non-Gaussianity in multiple-DBI inflation

We study a model of multiple-field DBI inflation leading to mixed form of primordial non-Gaussianity, including equilateral and local bispectrum shapes. We present a general formalism based on the Hamilton-Jacobi approach, allowing us to go beyond slow-roll, combining the three-point function for the fields at Hubble-exit with the non-linear evolution of super-Hubble scales. We are able to obtain analytic results by taking a separable Ansatz for the Hubble rate. We find general expressions for both the equilateral and local type non-Gaussianity parameter fNL. The equilateral non-Gaussianity includes the usual enhancement for small sound speeds, but multiplied by an analytic factor which can lead to a suppression. We illustrate our results with two scenarios. In the first model, previously found to have detectable local non-Gaussianity, we find that the equilateral signal is not sufficiently suppressed to evade current observational bounds. In our second scenario we construct a model which exhibits both a detectable equilateral fNL and a negative local fNL.
The Potential Neuroprotective Effects of Extracts from Oat Seedlings against Alzheimer’s Disease

The physiological or dietary advantages of germinated grains have been the subject of numerous discussions over the past decade. Around 23 million tons of oats are consumed globally, making up a sizeable portion of the global grain market. Oat seedlings contain more protein, beta-glucan, free amino acids, and phenolic compounds than seeds. The progressive neurodegenerative disorder of Alzheimer’s is accompanied by worsening memory and cognitive function. A key indicator of this disorder is the unusual buildup of amyloid-beta protein (or Aβ) in human brains. In this context, oat seedling extract (OSE) has been identified as a new therapeutic candidate for AD, due to its antioxidant activity and AD-specific mechanism of action. This study directly investigated how OSE affected AD and its impacts by examining the cognitive function and exploring the inflammatory response mechanism. The dried oat seedlings were grounded finely with a grinder, inserted with 50% fermented ethanol 10 times (w/v), and extracted by stirring for 10 h at 45 °C. After filtering the extract by 0.22 um filter, some of it was used for UHPLC analysis. The results indicated that the treatment with OSE protects against Aβ25–35-induced cytotoxicity in BV2 cells. Tg-5Xfad AD mice had strong deposition of Aβ throughout their brains, while WT mice did not exhibit any such deposition within their brains. A drastic reduction was observed in terms of numbers, as well as the size, of Aβ plaques within Tg-5Xfad AD mice exposed to OSE. This study indicated OSE’s neuroprotective impacts against neurodegeneration, synaptic dysfunction, and neuroinflammation induced by amyloid-beta. Our results suggest that OSE acts as a neuroprotective agent to combat AD-specific apoptotic cell death, neuroinflammation, amyloid-beta accumulation, as well as synaptic dysfunction in AD mice’s brains. Furthermore, the study indicated that OSE treatment affects JNK/ERK/p38 MAPK signaling, with considerable inhibition in p-JNK, p-p38, and p-ERK levels seen in the brain of OSE-treated Tg-5Xfad AD mice.
Identifying the Top-k Influential Spreaders in Social Networks: a Survey and Experimental Evaluation

Identifying the influential and spreader nodes in complex networks solves many types of complex scientific problems. In social networks, identifying the influential individuals can be useful for structuring techniques that accelerate or hinder information propagation. Each node in the network has unique characteristics that reflect its importance. These characteristics are used by researchers to design many different centrality algorithms. Unfortunately, current survey papers categorize these algorithms into broad classes and do not draw distinguishable boundaries among the specific techniques adopted by them. This can result in misclassifying unrelated algorithms into the same analysis category. To overcome this, we introduce a methodology-based taxonomy for classifying the algorithms that identify top-<inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> influential spreaders into hierarchically nested, specific, and fine-grained categories. We survey 184 papers and discuss their algorithms, which fall under 26 specific techniques. Our methodological taxonomy classifies the algorithms hierarchically into the following manner: Analysis type <inline-formula> <tex-math notation="LaTeX">$ \rightarrow $ </tex-math></inline-formula> analysis scope <inline-formula> <tex-math notation="LaTeX">$ \rightarrow $ </tex-math></inline-formula> analysis approach <inline-formula> <tex-math notation="LaTeX">$ \rightarrow $ </tex-math></inline-formula> analysis category <inline-formula> <tex-math notation="LaTeX">$ \rightarrow $ </tex-math></inline-formula> analysis sub-category <inline-formula> <tex-math notation="LaTeX">$ \rightarrow $ </tex-math></inline-formula> analysis specific technique. We introduce in this paper a comprehensive survey, review, and experimental evaluation of the recent and state-of-the-art algorithms that identify the top-<inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> and influential spreader nodes in social networks.
A Machine Learning approach to the classification of chemo-structural determinants in label-free SERS detection of proteins

Establishing standardized methods for a consistent analysis of spectral data remains a largely underexplored aspect in surface-enhanced Raman spectroscopy (SERS), particularly applied to biological and bio-medical research. Here we propose a Machine Learning (ML) based approach for classification of protein species. Principal Component Analysis (PCA), t-distributed stochastic neighbour embedding (t-SNE) and Uniform Manifold Approximation and Projection (UMAP) where used for dimensionality reduction, along with supervised and unsupervised methods to quantify how closely resembled SERS spectral profiles belonging to different species (Albumin from bovine serum, Albumin from human serum, Lysozyme, Human holo-transferrin, Human apo-transferrin) are. In particular, ML algorithms such as Support Vector Machine, K-Nearest Neighbours, Linear Discriminant Analysis and the unsupervised K-means were applied to original and multipeak fitting on SERS spectra respectively. This strategy simultaneously assures a fast, full and successful discrimination of proteins and a thorough characterization of the chemo-structural differences among them, ultimately opening up new routes for SERS evolution toward sensing applications and diagnostics of interest in life sciences.
NMA Analysis Center

The Norwegian Mapping Authority (NMA) has during the last few years had a close cooperation with Norwegian Defence Research Establishment (FFI) in the analysis of space geodetic data using the GEOSAT software. In 2012 NMA has taken over the full responsibility for the GEOSAT software. This implies that FFI stopped being an IVS Associate Analysis Center in 2012. NMA has been an IVS Associate Analysis Center since 28 October 2010. NMA's contributions to the IVS as an Analysis Centers focus primarily on routine production of session-by-session unconstrained and consistent normal equations by GEOSAT as input to the IVS combined solution. After the recent improvements, we expect that VLBI results produced with GEOSAT will be consistent with results from the other VLBI Analysis Centers to a satisfactory level.
An Improved RANSAC Outlier Rejection Method for UAV-Derived Point Cloud

A common problem with matching algorithms, in photogrammetry and computer vision, is the imperfection of finding all correct corresponding points, so-called inliers, and, thus, resulting in incorrect or mismatched points, so-called outliers. Many algorithms, including the well-known randomized random sample consensus (RANSAC)-based matching, have been developed focusing on the reduction of outliers. RANSAC-based methods, however, have limitations such as increased false positive rates of outliers, and, consequently resulting in fewer inliers, an unnecessary high number of iterations, and high computational time. Such deficiencies possibly result from the random sampling process, the presence of noise, and incorrect assumptions of the initial values. This paper proposes a modified version of RANSAC-based methods, called Empowered Locally Iterative SAmple Consensus (ELISAC). ELISAC improves RANSAC by utilizing three basic modifications individually or in combination. These three modifications are (a) to increase the stability and number of inliers using two Locally Iterative Least Squares (LILS) loops (Basic LILS and Aggregated-LILS), based on the new inliers in each loop, (b) to improve the convergence rate and consequently reduce the number of iterations using a similarity termination criterion, and (c) to remove any possible outliers at the end of the processing loop and increase the reliability of results using a post-processing procedure. In order to validate our proposed method, a comprehensive experimental analysis has been done on two datasets. The first dataset contains the commonly-used computer vision image pairs on which the state-of-the-art RANSAC-based methods have been evaluated. The second dataset image pairs were captured by a drone over a forested area with various rotations, scales, and baselines (from short to wide). The results show that ELISAC finds more inliers with a faster speed (lower computational time) and lower error (outlier) rates compared to M-estimator SAmple Consensus (MSAC). This makes ELISAC an effective approach for image matching and, consequently, for 3D information extraction of very high and super high-resolution imagery acquired by space-borne, airborne, or UAV sensors. In particular, for applications such as forest 3D modeling and tree height estimations where standard matching algorithms are problematic due to spectral and textural similarity of objects (e.g., trees) on image pairs, ELISAC can significantly outperform the standard matching algorithms.
Cosmic reionization study: principle component analysis after Planck

The study of reionization history plays an important role in understanding the evolution of our universe. It is commonly believed that the intergalactic medium (IGM) in our universe are fully ionized today, however the reionizing process remains to be mysterious. A simple instantaneous reionization process is usually adopted in modern cosmology without direct observational evidence. However, the history of ionization fraction, xe(z) will influence CMB observables and constraints on optical depth τ. With the mocked future data sets based on featured reionization model, we find the bias on τ introduced by instantaneous model can not be neglected. In this paper, we study the cosmic reionization history in a model independent way, the so called principle component analysis (PCA) method, and reconstruct xe (z) at different redshift z with the data sets of Planck, WMAP 9 years temperature and polarization power spectra, combining with the baryon acoustic oscillation (BAO) from galaxy survey and type Ia supernovae (SN) Union 2.1 sample respectively. The results show that reconstructed xe(z) is consistent with instantaneous behavior, however, there exists slight deviation from this behavior at some epoch. With PCA method, after abandoning the noisy modes, we get stronger constraints, and the hints for featured xe(z) evolution could become a little more obvious.
Dynamics of clumps embedded in a hot accretion flow with toroidal magnetic field

Dynamics of clumps within a magnetized advection dominated accretion flow is investigated by solving the collisionless Boltzmann equation and considering the drag force due to the relative velocity between the clumps and the gas. Toroidal component of the magnetic field is assumed to be dominant. Dynamical properties of the hot gaseous component such as the radial and the rotational velocities are affected by the magnetic effects, and so, drag force varies depending on the strength of magnetic field and the velocity dispersion of the clumps is then modified significantly. We show that when magnetic pressure is less than the gas pressure, the root of the averaged radial velocity square of the clumps decreases at the inner parts of the hot flow and increases slightly at its outer edge.
Fabrication and calibration of search coils

In this paper the techniques available to make and calibrate magnetic search coils are reviewed, with emphasis on harmonic coil systems as the commonly-used optimal choice for integral measurements of accelerator magnets in terms of measuring range, accuracy, and cost. The topics treated, drawing extensively on half a century of experience at CERN, include mechanical and electrical design criteria, practical fabrication techniques, metrological considerations, and various calibration methods for coil parameters such as surface area, rotation radius, tilt angle etc. in both static or time-varying magnetic fields.
A Three Phase Grid Interactive Bidirectional Off-board EV Charger with Weak and Strong Grid Durability

This paper presents a grid interactive off-board three phase EV charger capable for both distorted and healthy grid scenarios. The charging system incorporates three phase VSC, working in active rectification mode during forward power transfer whereas, in grid power fed mode it works as inverter mode. The controlled charging or discharging is made through full bridge (FB) LLC converter. The control for active power factor correction (APFC) stage is designed to not allow any reflection in grid angle with the presence of harmonics, DC offsets and frequency drift in grid voltage due to grid faults, sensing unit anomalies and distributed generation. The intermediate DC link reference is regulated in conjunction with the variation in battery terminal voltage to achieve wide EV charging voltage range and soft switching over complete charging profile with limited range of switching frequency. For this, a coordinated control is designed to cater wide range of EV charging with optimum efficiency point tracking over complete charging profile. The control for DC-DC stage uses both frequency modulation and phase shift over both H-bridges to regulate power in and out from the EV battery. For this, a 6.6 kW system is designed and simulated to validate the effectiveness of the claimed benefits of the designed charging system over both strong and weak grid scenarios.
Differentially expressed genes related to plant height and yield in two alfalfa cultivars based on RNA-seq

Background Alfalfa (Medicago sativa L.) is a kind of forage with high relative feeding value in farming and livestock breeding, and is of great significance to the development of animal husbandry. The growth of the aboveground part of alfalfa is an important factor that limits crop yield. Clarifying the molecular mechanisms that maintain vigorous growth in alfalfa may contribute to the development of molecular breeding for this crop. Methods Here, we evaluated the growth phenotypes of five cultivars of alfalfa (WL 712, WL 525HQ, Victoria, Knight 2, and Aohan). Then RNA-seq was performed on the stems of WL 712, chosen as a fast growing cultivar, and Aohan, chosen as a slow growing cultivar. GO enrichment analysis was conducted on all differentially expressed genes (DEGs). Result Among the differentially expressed genes that were up-regulated in the fast growing cultivar, GO analysis revealed enrichment in the following seven categories: formation of water-conducting tissue in vascular plants, biosynthesis and degradation of lignin, formation of the primary or secondary cell wall, cell enlargement and plant growth, cell division and shoot initiation, stem growth and induced germination, and cell elongation. KEGG analysis showed that differentially expressed genes were annotated as being involved in plant hormone signal transduction, photosynthesis, and phenylpropanoid biosynthesis. KEGG analysis also showed that up-regulated in the fast growing cultivar were members of the WRKY family of transcription factors related to plant growth and development, members of the NAC and MYB gene families related to the synthesis of cellulose and hemicellulose, and the development of secondary cell wall fibres, and finally, MYB family members that are involved in plant growth regulation. Our research results not only enrich the transcriptome database of alfalfa, but also provide valuable information for explaining the molecular mechanism of fast growth, and can provide reference for the production of alfalfa.
Clarifying the nature of the brightest submillimetre sources: interferometric imaging of LH 850.02

We present high-resolution interferometric imaging of LH 850.02, the brightest 850- and 1200-μm submillimetre (submm) galaxy in the Lockman Hole. Our observations were made at 890 μm with the Submillimetre Array (SMA). Our high-resolution submm imaging detects LH 850.02 at ≳6σ as a single compact (size ≲1 arcsec or ≲8 kpc) point source and yields its absolute position to ∼0.2-arcsec accuracy. LH 850.02 has two alternative radio counterparts within the Submillimetre Common User Bolometer Array (SCUBA) beam (LH 850.02N and LH 850.02S), both of which are statistically very unlikely to be so close to the SCUBA source position by chance. However, the precise astrometry from the SMA shows that the submm emission arises entirely from LH 850.02N, and is not associated with LH 850.02S (by far the brighter of the two alternative identifications at 24 μm). Fits to the optical–infrared (IR) multicolour photometry of LH 850.02N and LH 850.02S indicate that both lie at z≈ 3.3, and are therefore likely to be physically associated. At these redshifts, the 24-μm-to-submm flux density ratios suggest that LH 850.02N has an Arp 220-type starburst-dominated far-IR spectral energy distribution (SED), while LH 850.02S is more similar to Mrk 231, with less dust enshrouded star formation activity, but a significant contribution at 24 μm (rest frame 5–6 μm) from an active nucleus. This complex mix of star formation and active galactic nucleus (AGN) activity in multicomponent sources may be common in the high-redshift ultraluminous galaxy population, and highlights the need for precise astrometry from high-resolution interferometric imaging for a more complete understanding.
Coupled polar–axial magnetar oscillations

We study coupled axial and polar axisymmetric oscillations of a neutron star endowed with a strong magnetic field, having both poloidal and toroidal components. The toroidal component of the magnetic field is driving the coupling between the polar and axial oscillations. The star is composed of a fluid core as well as a solid crust. Using a two-dimensional general relativistic simulation and a magnetic field B= 1016 G, we study the change in the polar and axial spectrum caused by the coupling. We find that the axial spectrum suffers a dramatic change in its nature, losing its continuum character. In fact, we find that only the ‘edges’ of the continua survive, generating a discrete spectrum. As a consequence the crustal frequencies, which in our previous simulation could be absorbed by the continua, if they were embedded inside it, are now long-living oscillations. They may lose their energy only in the very special case that they are in resonance with the ‘edges’ of the continua.