Miracle-dz/UniFAR-FTUs huggingface dataset:
An Example Based Non-local Mean Regularization For Image Super-resolution

Abstr act. Image super-resolution (SR) is a very useful technique for visual surveillance, high-definition TV and medical image processing. In the traditional method, the inferred high-resolution image patch is represented as a linear combination of dictionaries obtained by training images, and least square estimation or sparse regularization is used to find better solution. However, the methods proposed so far neglect the prior knowledge about local structure similarity in natural images. In this paper we introduce an adaptive regularization terms into LLE based SR framework. First, an example based image nonlocal mean regularization term is learned from the dataset of example image patches, which captures the local structure similarity between the input image and training images. Then, the image nonlocal self-similarity is used as another regularization term. In addition, we propose an iterative optimization framework to find the latent HR image. Experimental results on real surveillance images demonstrate the superiority of the proposed method over some state-of-the-art image SR approaches.
Axonal Guidance Using Biofunctionalized Straining Flow Spinning Regenerated Silk Fibroin Fibers as Scaffold

After an injury, the limited regenerative capacity of the central nervous system makes the reconnection and functional recovery of the affected nervous tissue almost impossible. To address this problem, biomaterials appear as a promising option for the design of scaffolds that promote and guide this regenerative process. Based on previous seminal works on the ability of regenerated silk fibroin fibers spun through the straining flow spinning (SFS) technique, this study is intended to show that the usage of functionalized SFS fibers allows an enhancement of the guidance ability of the material when compared with the control (nonfunctionalized) fibers. It is shown that the axons of the neurons not only tend to follow the path marked by the fibers, in contrast to the isotropic growth observed on conventional culture plates, but also that this guidance can be further modulated through the biofunctionalization of the material with adhesion peptides. Establishing the guidance ability of these fibers opens the possibility of their use as implants for spinal cord injuries, so that they may represent the core of a therapy that would allow the reconnection of the injured ends of the spinal cord.
Netrin-1 Monoclonal Antibody-Functionalized Nanoparticle Loaded with Metformin Prevents the Progression of Abdominal Aortic Aneurysms

Background Abdominal aortic aneurysms (AAAs) are a global health and economic burden. Therapeutic strategies to inhibit the progression of AAAs are currently lacking. Recently, the therapeutic effect of metformin on aneurysms has attracted considerable interest. However, the unfavorable pharmacokinetic properties of metformin limit its feasibility for AAA treatment. Methods and Results We constructed a metformin-loaded netrin-1-responsive AAA-targeted nanoparticle (Tgt-NP-Met) for AAA management. Evaluation of the therapeutic effect of Tgt-NP-Met was performed by in vitro and in vivo experiments. Our results showed that the binding of netrin-1 monoclonal antibodies enhanced the AAA-targeting capability of nanoparticles (NPs). Moreover, Tgt-NP-Met administration prevented AAA development and reduced the aneurysm diameter in apolipoprotein E (ApoE)-deficient (ApoE−/−) mice that received continuous infusion of angiotensin II. Furthermore, metformin prevented AAA progression by inhibiting the transformation of vascular smooth muscle cells (VSMCs) from a contractile phenotype to a synthetic phenotype, which is mediated by macrophage infiltration and activation. Conclusion Our findings identify metformin as a functional suppressor for macrophage-mediated phenotypic transformation of VSMCs and Tgt-NP-Met as an efficient therapeutic strategy for AAA management.
Fundamental Limits of Cache-Aided MIMO Wireless Networks

This paper studies the Multi-Input-Multi-Output (MIMO) interference networks with arbitrary number of transmitters and receivers, where both the transmitters and receivers are equipped with caches. The main goal is to design content placement and delivery schemes that minimize the worst case normalized delivery time (NDT). First, we propose a delivery scheme for the cache-aided Single-Input-Multiple-Output (SIMO) interference networks. Then, we obtain the achievable NDT of the cache-aided MIMO interference networks using the decomposition property of splitting each multi-antenna transmitter into multiple single antenna transmitters. Furthermore, we derive an information-theoretic bound on the optimal NDT of the cache-aided MIMO interference network. Analytical results show that the proposed scheme is within a multiplicative gap of 2 from the derived lower bound independent of all system parameters for any uncoded cache placement scheme. We also derive a novel delivery scheme for the cache-aided Multi-Input-Single-Output (MISO) interference network outperforming our proposed scheme for the cache-aided MIMO interference network. The numerical results show the superiority of our proposed scheme over the state-of-the-art schemes in the literature. Our results show that the coded caching gain has a more significant contribution in reducing the transmission latency than the spatial multiplexing gain. Our results indicate that the receive-antennas become more effective in reducing the NDT than the transmit-antennas in the presence of caches at the receiver-side. In addition, we show that increasing the number of transmit-antennas has a higher gain in reducing the NDT than adding more transmitters in the cache-aided MISO interference network.
A Novel Automatic Audiometric System Design Based on Machine Learning Methods Using the Brain’s Electrical Activity Signals

This study uses machine learning to perform the hearing test (audiometry) processes autonomously with EEG signals. Sounds with different amplitudes and wavelengths given to the person tested in standard hearing tests are assigned randomly with the interface designed with MATLAB GUI. The person stated that he heard the random size sounds he listened to with headphones but did not take action if he did not hear them. Simultaneously, EEG (electro-encephalography) signals were followed, and the waves created in the brain by the sounds that the person attended and did not hear were recorded. EEG data generated at the end of the test were pre-processed, and then feature extraction was performed. The heard and unheard information received from the MATLAB interface was combined with the EEG signals, and it was determined which sounds the person heard and which they did not hear. During the waiting period between the sounds given via the interface, no sound was given to the person. Therefore, these times are marked as not heard in EEG signals. In this study, brain signals were measured with Brain Products Vamp 16 EEG device, and then EEG raw data were created using the Brain Vision Recorder program and MATLAB. After the data set was created from the signal data produced by the heard and unheard sounds in the brain, machine learning processes were carried out with the PYTHON programming language. The raw data created with MATLAB was taken with the Python programming language, and after the pre-processing steps were completed, machine learning methods were applied to the classification algorithms. Each raw EEG data has been detected by the Count Vectorizer method. The importance of each EEG signal in all EEG data has been calculated using the TF-IDF (Term Frequency-Inverse Document Frequency) method. The obtained dataset has been classified according to whether people can hear the sound. Naïve Bayes, Light Gradient Strengthening Machine (LGBM), support vector machine (SVM), decision tree, k-NN, logistic regression, and random forest classifier algorithms have been applied in the analysis. The algorithms selected in our study were preferred because they showed superior performance in ML and succeeded in analyzing EEG signals. Selected classification algorithms also have features of being used online. Naïve Bayes, Light Gradient Strengthening Machine (LGBM), support vector machine (SVM), decision tree, k-NN, logistic regression, and random forest classifier algorithms were used. In the analysis of EEG signals, Light Gradient Strengthening Machine (LGBM) was obtained as the best method. It was determined that the most successful algorithm in prediction was the prediction of the LGBM classification algorithm, with a success rate of 84%. This study has revealed that hearing tests can also be performed using brain waves detected by an EEG device. Although a completely independent hearing test can be created, an audiologist or doctor may be needed to evaluate the results.
The evolution of vortices in vertical shear. II: Large‐scale asymmetries

The role of large‐scale asymmetries in the evolution of a tropical‐eye lone‐like vortex in vertical shear on an f‐plane is investigated. Idealized numerical calculations using a primitive‐equation model are used to illustrate the development of the asymmetries and their role in the evolution of the vortex lilt. The asymmetries develop in the outer region of the vortex, well outside the radius of maximum wind. For the vortex profile used in most of the calculations, the region where the asymmetries develop has anomalously negative potential vorticity (PV) compared with the undisturbed environment, and the flow fields associated with the asymmetries consist of large‐scale anticyclonic gyres. The orientation of the gyres changes with height and they are located on opposite sides of the vortex at lower and upper levels. The influence of the asymmetries on the vortex evolution depends on both the structure and location of the asymmetries and on the orientation of the tilted vortex within the asymmetries.
On rational cuspidal plane curves, open surfaces and local singularities

Let C be an irreducible projective plane curve in the complex projective space P(2). The classification of such curves, up to the action of the automorphism group PGL(3, C) on P(2), is a very difficult open problem with many interesting connections. The main goal is to determine, for a given d, whether there exists a projective plane curve of degree d having a fixed number of singularities of given topological type. In this note we are mainly interested in the case when C is a rational curve. The aim of this article is to present some of the old conjectures and related problems, and to complete them with some results and new conjectures from the recent work of the authors.
Effect of Acetazolamide on Postural Control in Patients with COPD Travelling to 3100 m Randomized Trial

Patients with chronic obstructive pulmonary disease (COPD) may be susceptible to impairments in postural control (PC) when exposed to hypoxia at high altitude. This randomized, placebo-controlled, double-blind, parallel-design trial evaluated the effect of preventive acetazolamide treatment on PC in lowlanders with COPD traveling to 3100 m. 127 lowlanders (85 men, 42 women) with moderate to severe COPD, aged 57 ± 8 y, living below 800 m, were randomized to treatment with acetazolamide 375 mg/d starting 24 h before ascent from 760 m to 3100 m and during a 2-day sojourn in a clinic at 3100 m. PC was evaluated at both altitudes with a balance platform on which patients were standing during five tests of 30 s each. The primary outcome was the center of pressure path length (COPL). In the placebo group, COPL significantly increased from (mean ± SD) 28.8 ± 9.7 cm at 760 m to 30.0 ± 10.0 cm at 3100 m (p = 0.002). In the acetazolamide group, COPL at 760 m and 3100 m were similar with 27.6 ± 9.6 cm and 28.4 ± 9.7 cm (p = 0.069). The mean between-groups difference (acetazolamide-placebo) in altitude-induced change of COPL was −0.54 cm (95%CI −1.66 to 0.58, p = 0.289). Multivariable regression analysis confirmed an increase in COPL of 0.98 cm (0.39 to 1.58, p = 0.001) with ascent from 760 to 3100 m, but no significant effect of acetazolamide (0.66 cm, 95%CI −0.25 to 1.57, p = 0.156) when adjusting for several confounders. In lowlanders with moderate to severe COPD, an ascent to high altitude was associated with impaired postural control and this was not prevented by acetazolamide.
Asteroid taxonomic classification in the Gaia photometric system

Aims. We evaluate the prospects of performing automatic taxonomic classification of asteroids in a proposed broad and medium band photometric system of Gaia . Methods. The study is based on asteroid colors from the Eight-Color Asteroid Survey (ECAS) and CCD spectra from the Small Mainbelt Asteroid Spectral Survey II (SMASSII). The success of the Gaia photometric systems for taxonomic classification is evaluated using supervised classification techniques and mean taxonomic class spectra in the Tholen and Bus&Binzel taxonomic systems. Our supervised classification method is based on rms differences between individual asteroid spectra and taxonomic mean spectra and provides probability estimates of membership in all taxonomic classes. Results. We find that both photometric systems of Gaia are able to discriminate between all of the twelve Tholen asteroid classes for noise-free data. The medium band system is able to discriminate between the majority of the 26 SMASSII asteroid classes in case of high quality photometric data. For both the Tholen and Bus & Binzel taxonomies we find that about 25% of the asteroids are spectrally more similar to another taxonomic class in a best-fit sense, though the differences within the three major complexes (C, S and X) are 1–10%. Conclusions. Among the two main existing taxonomies, the Gaia photometric system is found to be best suited for the Bus & Binzel taxonomy. The medium band system is the preferred system for all but the faintest objects. The classification method employed here results in more concentrated taxonomic class domains in principal component space, and mean taxonomic spectra that are formed from less divergent class members, than the case for the nominal classification systems. It provides statistical probability estimates for class memberships and naturally reflects the fact that asteroid spectral shapes form a continuum in principal component space.
Composition measurements near the second knee with the telescope array low-energy extension (TALE)

Cosmic rays with energies between 10 and10 eV exhibit a rich range of features. The energy spectrum changes index at at least two points, known a s the “second knee” and the “ankle”. There may be a composition change in this energy regime as well, per ha s indicative of a shift in predominance from galactic to extragalactic sources. The Telescop e Array Low-Energy Extension — planned for construction in Millard County, Utah, USA — stands well pois ed to make decisive simultaneous measurements of cosmic ray energy spectra and composition in th is transition region. Here, we present the results of simulation studies relevant to the design of the T ALE detectors, and estimate the sensitivity of TALE to composition changes in the 10 eV decade.
Effect of several fillers on some basic mechanical properties of asphalt concrete

Filler is one of the mandatory ingredients in asphalt mixture. It also plays a very significant role in influencing the properties and behavior of asphalt concrete. This paper presents the results of laboratory experiments to determine the influence of 4 different fillers (including conventional stone powder, Portland cement, rice husk ash, and fly ash) on some mechanical properties of asphalt concrete with Dmax of 12.5 (AC12.5). The content of filler used in the study was 5% of the total volume of aggregate. The results show that the designed AC with different fillers have the mechanical properties (air void, Marshall stability, flow, and retaining stability) that meet the specification requirements of Vietnam Ministry of Transport Decision No. 858/2014. In which the mechanical properties of AC using conventional stone powder filler are achieved with an overall better and stable effect. Although rice husk ash and fly ash filler also have certain improvements in Marshall stability and air void, AC using rice husk ash and fly ash filler does not meet the requirement of elastic modulus recommended in the Vietnam standard for flexible pavement design 22TCN 211 -06.
Classification of Papuan Batik Motifs Using Deep Learning and Data Augmentation

Papuan Batik motifs began to appear in 1984 and are only known in general with one designation, namely Papuan batik, even though these various motifs can be classified according to the area of origin of manufacture, culture and flora and fauna that have meaning. local wisdom of the community. The ability to recognize every batik motif from Papua requires experience and knowledge from certain circles, so that knowledge and meaning are maintained, a tool is needed that can classify various batik motifs from Papua. This study uses four classes of datasets, namely Cendrawasih Motifs, Raja Ampat Motifs, Tifa Honai Motifs and Asmat Motifs which are non-geometric. It is proposed to classify these motifs using deep learning using Vgg16 and Resnet50 architectures with fine tuning, to add data with various combinations in order to obtain better performance. The test results showed that without data augmentation on the VGG16 architecture, an accuracy of 78.79% was obtained and the Resnet50 architecture obtained an accuracy of 81.82% with several combinations of augmentation techniques giving the same better results without data augmentation with the results on the VGG16 architecture giving 84 results. , 85% and on the Resnet50 architecture it gives a yield of 87.88%.
Opioid-sparing opportunities in the thoracic surgery pathway

a heavy presence in the literature. An et al. performed a randomized controlled study comparing opioid-free anesthesia versus opioid-based anesthesia for lung cancer patients undergoing VATS resection with emphasis on intraoperative pain control and depth of sedation, which revealed equally effective analgesia but higher levels of sedation required for the opioid-free group (2). This study described the use of Dexmedetomidine, sevoflurane, and thoracic paravertebral blockade for intra-operative anesthesia, but other studies have described patient-centered anesthesia using various combinations including dexmedetomidine, ketamine, clonidine
Successful Whole Genome Nanopore Sequencing of Swine Influenza A Virus (swIAV) Directly from Oral Fluids Collected in Polish Pig Herds

Influenza A virus (IAV) is a single-stranded, negative-sense RNA virus and a common cause of seasonal flu in humans. Its genome comprises eight RNA segments that facilitate reassortment, resulting in a great variety of IAV strains. To study these processes, the genetic code of each segment should be unraveled. Fortunately, new third-generation sequencing approaches allow for cost-efficient sequencing of IAV segments. Sequencing success depends on various factors, including proper sample storage and processing. Hence, this work focused on the effect of storage of oral fluids and swIAV sequencing. Oral fluids (n = 13) from 2017 were stored at −22 °C and later transferred to −80 °C. Other samples (n = 21) were immediately stored at −80 °C. A reverse transcription quantitative PCR (RT-qPCR) pre- and post-storage was conducted to assess IAV viral loads. Next, samples were subjected to two IAV long-read nanopore sequencing methods to evaluate success in this complex matrix. A significant storage-associated loss of swIAV loads was observed. Still, a total of 17 complete and 6 near-complete Polish swIAV genomes were obtained. Genotype T, (H1avN2, seven herds), P (H1N1pdm09, two herds), U (H1avN1, three herds), and A (H1avN1, 1 herd) were circulated on Polish farms. In conclusion, oral fluids can be used for long-read swIAV sequencing when considering appropriate storage and segment amplification protocols, which allows us to monitor swIAV in an animal-friendly and cost-efficient manner.
Echocardiographic Parameters to Predict Malignant Events in Arrhythmic Mitral Valve Prolapse Population

Bileaflet Mitral Valve Prolapse (bMVP) has been linked to major arrhythmic events and sudden cardiac death (SCD). Consistent predictors in this field are still lacking. Echocardiography is the best tool for the analysis of the prolapse and its impact on the ventricular mechanics. The aim of this study was to find new echocardiographic predictors of malignant events within an arrhythmic MVP population. We evaluated 22 patients with arrhythmic bMVP with a transthoracic echocardiogram focused on mitral valve anatomy and ventricular contraction. Six of them had major arrhythmic events that required ICD implantation (ICD-MVP group), while sixteen presented with a high arrhythmic burden without major events (A-MVP group). The best predictors of malignant events were the Anterior Mitral Leaflet (AML) greater length and greater Mechanical Dispersion (MD) of basal and mid-ventricular segments, while other significant predictors were the larger mitral valve annulus (MVA) indexed area, lower MVA anteroposterior diameter/AML length ratio, higher inferolateral basal segment S3 velocity.
Stable States and Sufficient Conditions for Correct Retrieval in the Bidirectional Associative Memory

Bidirectional associative memories are used in pattern recognition applications and store the given input-output pairs. An important consideration in pattern association applications is the stability and recall accuracy of a given neural network. Some conditions for stability of library vectors using Hamming distances in a bidirectional associative memory are discussed. We also discuss the conditions for correct retrieval of stable states in a bidirectional associative memory. We derive the conditions for correct retrieval in terms of the maximum and minimum of the correlations as well as the number of pattern pairs and the size of the pattern vectors.
SHOCK ACCELERATION OF PARTICLES IN THE NONSTATIONARY EVOLUTION OF COROTATING INTERACTION REGIONS

One-dimensional hybrid simulations are used to investigate the particle energization process during the nonstationary evolution of corotating interaction regions (CIRs) in the heliosphere. The simulation model, where fast and slow solar wind streams interact with each other, allows the formation of a pair (forward/reverse) of shocks at the CIR boundaries and the stream interface interior, which prevents the interchange of both streams. While both shocks are quasi-perpendicular and are not capable of accelerating thermal particles (hundreds of eV) up to a suprathermal energy (tens to hundreds of keV) in the early phase of their development, the reverse shock in the fast wind experiences a transition to a quasi-parallel regime in the later phase. The quasi-parallel reverse shock can efficiently accelerate particles to the suprathermal range. The different timescale of the adiabatic expansion between the fast and slow wind leads to a transition of the shock geometry that can take place more easily in the reverse shock than in the forward shock, where the magnetic field in the fast wind remains more radial to the propagation direction than in the slow wind. The difference in the acceleration efficiency between these shocks follows a well-known observed asymmetry in the profile of the energetic particle fluxes, where the larger intensity increases more in the reverse shock than in the forward shock. The present results suggest that the solar wind thermal plasma, as well as interstellar pickup ions, can contribute to the composition of energetic particles associated with the CIRs.