Miracle-dz/UniFAR-FTUs huggingface dataset:
A Remote Sensing Image Registration Method Based on Wavelet Decomposition and the Improved Hausdorff Distance

In recent years,the continuing development of remote sensing technology makes the conventional remoting sensing image registration techniques inefficient.An accurate and efficient image registration method for remote sensing images is introduced.The method integrates image hierarchical structure,multi-resolution wavelet decomposition technique and Harris corner detector to create a feature point pyramid.And the improved Hausdorff distance is used as the similarity measure for realizing remote sensing image registration.
A Bound for the Matrix Square Root with Application to Eigenvector Perturbation

Let $H$ be positive definite, let $\Delta H$ be Hermitian, and suppose that $\|H^{-1/2} (\Delta H) H^{-1/2} \| \\ =1$. It is shown that the least constant $c_n$ such that \[ || (H + \eta \Delta H)^{1/2}H^{-1/2} - I || \leq c_n \eta + 0(\eta^2) \] for all $n \times n$ $H$ and $\Delta H$ grows like $\log n$. This fact has consequences in eigenvector perturbation theory.
BitBrain and Sparse Binary Coincidence (SBC) memories: Fast, robust learning and inference for neuromorphic architectures

We present an innovative working mechanism (the SBC memory) and surrounding infrastructure (BitBrain) based upon a novel synthesis of ideas from sparse coding, computational neuroscience and information theory that enables fast and adaptive learning and accurate, robust inference. The mechanism is designed to be implemented efficiently on current and future neuromorphic devices as well as on more conventional CPU and memory architectures. An example implementation on the SpiNNaker neuromorphic platform has been developed and initial results are presented. The SBC memory stores coincidences between features detected in class examples in a training set, and infers the class of a previously unseen test example by identifying the class with which it shares the highest number of feature coincidences. A number of SBC memories may be combined in a BitBrain to increase the diversity of the contributing feature coincidences. The resulting inference mechanism is shown to have excellent classification performance on benchmarks such as MNIST and EMNIST, achieving classification accuracy with single-pass learning approaching that of state-of-the-art deep networks with much larger tuneable parameter spaces and much higher training costs. It can also be made very robust to noise. BitBrain is designed to be very efficient in training and inference on both conventional and neuromorphic architectures. It provides a unique combination of single-pass, single-shot and continuous supervised learning; following a very simple unsupervised phase. Accurate classification inference that is very robust against imperfect inputs has been demonstrated. These contributions make it uniquely well-suited for edge and IoT applications.
Risk Factors, Genetic Diversity, and Antimicrobial Resistance of Staphylococcus spp. Isolates in Dogs Admitted to an Intensive Care Unit of a Veterinary Hospital

Intensive Care Units (ICU) usually provide an excellent environment for the selection of pathogens associated with hospital-acquired infections (HAI), leading to increased mortality and hospitalization costs. Methicillin-resistant Staphylococcus pseudintermedius (MRSP) is a major cause of HAI in dogs worldwide, but the risk factors and dynamics of colonization by MRSP are largely unknown. This study aimed to evaluate the risk factors associated with the acquisition of MRSP in dogs admitted to an ICU, and to report the antimicrobial resistance profiles and genetic relatedness of MRSP isolates. Sterile swabs from the nostril, axilla, and rectum were collected daily during the hospitalization of 54 dogs. Samples were subjected to Mannitol Salt Agar, and colonies were identified by MALDI-ToF, polymerase chain reaction (PCR), and sequencing of the rpoB gene. Antimicrobial susceptibility testing and PCR detection of mecA were performed. Staphylococcus spp. was isolated from 94% of the dogs, and the most frequently isolated species was S. pseudintermedius (88.2%). Carriage of multidrug resistant (MDR) staphylococci was observed in 64.4% of the dogs, and approximately 39% had methicillin-resistant Staphylococcus sp. (MRS), of which 21.6% had MRSP and 1.9% had methicillin-resistant S. aureus (MRSA). The acquisition of MRSP during ICU hospitalization was associated with sex (female), age (>7 years), and dogs that had previously been treated with antimicrobials. Animals colonized by MRSP resistant to ≥9 antimicrobial classes had longer hospital stays than those colonized by other MRS strains. Among the 13 MRSP isolates that were subjected to whole-genome sequencing, ten were classified as ST71. A single nucleotide polymorphism (SNP) analysis revealed three clones, including one that was detected in infected dogs outside the ICU. This study indicates novel risk factors associated with colonization by MRSP. The detection of the same MRSP clone causing HAI outside the ICU reinforces the need for improved infection prevention and control practices at veterinary hospitals in general and at the ICU in particular.
An Elementary Proof of Dirichlet's Theorem About Primes in an Arithmetic Progression

1. A classical theorem by Dirichlet asserts that every arithmetic progression ky + 1, where the positive integers k and 1 are relatively prime, represents infinitely many primes as y runs over the positive integers. The object of this paper is to give a new and more elementary proof of this theorem. More elementary in the respect that we do not use the complex characters mod k, and also in that we consider only finite sums. More precisely the theorem that is proved in this paper is the following: For every positive integer k, there exist positive numbers Ck and xo depending only on k, such that, when (k, 1) = 1 we have
Sample size estimation and sampling techniques for selecting a representative sample

Introduction: The purpose of this article is to provide a general understanding of the concepts of sampling as applied to health-related research. Sample Size Estimation: It is important to select a representative sample in quantitative research in order to be able to generalize the results to the target population. The sample should be of the required sample size and must be selected using an appropriate probability sampling technique. There are many hidden biases which can adversely affect the outcome of the study. Important factors to consider for estimating the sample size include the size of the study population, confidence level, expected proportion of the outcome variable (for categorical variables)/standard deviation of the outcome variable (for numerical variables), and the required precision (margin of accuracy) from the study. The more the precision required, the greater is the required sample size. Sampling Techniques: The probability sampling techniques applied for health related research include simple random sampling, systematic random sampling, stratified random sampling, cluster sampling, and multistage sampling. These are more recommended than the nonprobability sampling techniques, because the results of the study can be generalized to the target population.
An Elementary Proof of Convergence for the Forward-Backward Splitting Algorithm

The forward-backward splitting (FBS) algorithm is a quite general iterative method that includes, as particular cases, the projected gradient descent algorithm for constrained minimization, the CQ algorithm for the split feasibility problem, the projected Landweber algorithm for constrained least squares, and the simultaneous orthogonal projection algorithm for the convex feasibility problem. The FBS algorithm involves iterating with respect to an averaged operator that is the product of two rmly non-expansive operators, one of which is Moreau’s proximity operator. The usual proof of convergence employs the Krasnosel’ski i-Mann Theorem. This proof depends, therefore, on knowing that if the gradient of a convex dierentiable function is non-expansive, then it is rmly non-expansive, and that the composition of averaged operators is again averaged. Neither of these results is trivial to prove, especially the former. In this paper we give an elementary proof of convergence of the FBS algorithm that does not rely on these results.
A Study of Adaptive Elastic Net Estimators with Different Adaptive Weights

We study the performance of two adaptive elastic net estimation methods where the adaptive weights are constructed using elastic net and least squares estimators. Simulation studies show that two adaptive weights perform differently. When the elastic net estimator is used, the adaptive elastic net performs best in estimation accuracy and variable selection performance. If the least squares estimator is used, the adaptive elastic net has prediction performance better than using the other adaptive weight. Keywords: adaptive elastic net; elastic net; adaptive weight; L1-penalty; variable selection.
Spontaneous mode locking of a multimode semiconductor laser under continuous wave operation

Self-starting mode-locking is observed in a laser based on a compact III-V diode-pumped quantum-well surface-emitting semiconductor laser technology with a saturable-absorber-free but dispersive cavity. Continuous wave generation of picosecond pulses at a rate of 100 GHz is demonstrated by recording microwave intensity noises, beat frequency, time-resolved optical spectra, and intensity autocorrelation. Coherence of the pulse train is obtained through the frequency noise measurement of the demodulated beat note, demonstrating a timing jitter as low as 110 fs, near the quantum limit. Using a theoretical model based on a generalized Haus master equation, we demonstrate the existence of this mode locked state without the need for saturable absorption. The fundamental physical mechanism is the interplay between self-phase modulation and anomalous dispersion like in cavity soliton together with light–matter interaction-induced time symmetry breaking.
A viral peptide for intracellular delivery

Biological membranes represent a critical hindrance for administering active molecules which are often unable to reach their designated intracellular target sites. In order to overcome this barrier-like behavior not easily circumvented by many pharmacologically-active molecules, synthetic transporters have been exploited to promote cellular uptake. Linking or complexing therapeutic molecules to peptides that can translocate through the cellular membranes could enhance their internal delivery, and consequently, a higher amount of active compound would reach the site of action. Use of cell penetrating peptides (CPPs) is one of the most promising strategy to efficiently translocate macromolecules through the plasma membrane, and have attracted a lot of attention. New translocating peptides are continuously described and in the present review, we will focus on viral derived peptides, and in particular a peptide (gH625) derived from the herpes simplex virus type 1 (HSV-1) glycoprotein H (gH) that has proved to be a useful delivery vehicle due to its intrinsic properties of inducing membrane perturbation.
Box-cox transformation and the problem of heteroscedasticity

It is known that heteroscedasticity in the context of the well-known family of power transformations suggested by Box and Cox creates complications because it depends upon the heteros- cedasticity of the original values of the dependent variable in a regression model set-up) as well as upon the transforma- tion parameter In this paper we attempt at generalizing the original Box-Cox model in this direction, and suggest maximum likelihood method of estimation for the parameters of the model. Through illustrative examples we show the seriousness of the problem of heteroscedasticity in the context of this trans- formation, and indicate how one can separate out the problem of non-linearity from the influence of stabilization of error variance in an estimate of the transformation parameter in our generalized model.
The frontal transition zone and microphysical properties of associated clouds

Une etude de la structure des nuages ainsi que celle des precipitations dans la zone de transition d'un front froid au-dessus du Victoria oriental, montre que les parametres importants de precipitation, tels que temperature du sommet et profondeur des nuages, sont determines par la voie synoptique. Les nuages pre-frontaux effectuent une lente ascension sur une hauteur appreciable, ceci provoque des nuages froids profonds avec une duree de vie de l'ordre de la dizaine d'heures. Dans les nuages post-frontaux, l'ascension est de meso-echelle et peu profonde et forme des elements nuageux de courte duree de vie. Ces proprietes dynamiques et thermodynamiques determinent la microphysique des nuages et, largement, la chute de pluie associee. Les precipitations dans les nuages pre-frontaux, se forment principalement via les cristaux de glace legerement givres, produits a basse temperature; le processus peut etre tres efficace pour provoquer la glaciation du nuage mais non necessairement efficace pour produire des cristaux de glace suffisamment gros pour survivre a une precipitation au sol
Treating Hypopituitarism in the Over 65s: Review of Clinical Studies

Abstract The current increase of life expectancy is associated with the presence of endocrine diseases in the elderly. The management of hypopituitarism in this group of patients is a challenging task. A correct diagnosis, which represents an essential requisite for an appropriate medical treatment, can be difficult because of the physiological changes occurring in pituitary function with aging, which may lead to challenges in the interpretation of laboratory results. Furthermore, the treatment requires several careful considerations: the need to restore the hormonal physiology with replacement therapies must be balanced with the need to avoid the risks of the over-replacement, especially in the presence of concomitant cardiovascular and metabolic disease. Interactions with other drugs able to modify the absorption and/or the metabolism of hormonal replacement therapies should be considered, in particular for the treatment of hypoadrenalism and hypothyroidism. The most important challenges stem from the lack of specific studies focused on the management of hypopituitarism in older people.
Review on recent advances in structural health monitoring paradigm for looseness detection in bolted assemblies

The integrity of bolted joints is still a challenging problem owing to the gross or localized slip at the interfacial surfaces of the joints when subjected to external disturbances such as vibrations. This slip escalates the interfacial movement and, thus, leads to a decrease in preload levels, that is, looseness of the bolted assemblies. In the last decade, modal analysis, wave propagation, and percussion methods were traditionally used to detect looseness in bolted connections. With an increase in computational power, machine learning algorithms such as neural networks, random forests, decision trees, and support vector machines complemented the traditional methods in accurate looseness estimation. Subsequently, this integration paved the path for real-time health monitoring of bolted joints. This paper summarizes recent investigations on looseness detection in bolted assemblies based on traditional methods and machine learning algorithms. The working principle, advantages, challenges, and applications of the aforementioned methods are also detailed in this paper. Apart from these investigations, the latest studies on the Internet of Things-based health monitoring of structures are also reviewed to explore their adaptability in remote monitoring of bolted connections for damage detection in the future.
Lower visual processing speed relates to greater subjective cognitive complaints in community-dwelling healthy older adults

Introduction Subjective cognitive complaints in older age may reflect subtle objective impairments in basic cognitive functions that might foreshadow broader cognitive problems. Such cognitive functions, however, are not captured by standard neuropsychological testing. Visual processing speed is a basic visual attention function that underlies the performance of cognitive tasks relying on visual stimuli. Here, we test the hypothesis that lower visual processing speed correlates with greater subjective cognitive complaints in healthy older adults from the community. Methods To do so, we assessed a sample of 30 healthy, cognitively normal older adults (73.07 ± 7.73 years old; range: 60–82; 15 females) with respect to individual subjective cognitive complaints and visual processing speed. We quantified the degree of subjective cognitive complaints with two widely-used questionnaires: the Memory Functioning Questionnaire and the Everyday Cognition. We used verbal report tasks and the theory of visual attention to estimate a visual processing speed parameter independently from motor speed and other visual attention parameters, i.e., visual threshold, visual short-term memory storage capacity, top-down control, and spatial weighting. Results We found that lower visual processing speed correlated with greater subjective complaints and that this relationship was not explained by age, education, or depressive symptoms. The association with subjective cognitive complaints was specific to visual processing speed, as it was not observed for other visual attention parameters. Discussion These results indicate that subjective cognitive complaints reflect a reduction in visual processing speed in healthy older adults. Together, our results suggest that the combined assessment of subjective cognitive complaints and visual processing speed has the potential to identify individuals at risk for cognitive impairment before the standard tests show any abnormal results.
Electrical impedance mismatch in capacitive micromachined ultrasonic transducers

Several investigations on the electrical impedance mismatch, the insertion loss and the noise performance of capacitive micromachined ultrasonic transducers (cMUTs) are reported. The theoretical analysis applies the concepts of radio communication circuits to the analytical modeling of a two-way system made of a transmitting cMUT and a receiving one. Since the simulation results can emphasize the effects of either the transmitting and receiving electronics or the characteristics of the transducers on the performance of the system, the proposed approach is very useful for the purpose of optimization. For example, a selection between receivers can be easily done as a trade-off between the insertion loss and the noise sensitivity of the system.
Clostridium tyrobutyricum occurrence in silages and cattle feed: Use of molecular and simulation data to optimize predictive models

Introduction Poor quality silage can derive from the presence of deleterious microorganisms such as clostridia. Their dissemination along the food chain, especially in milk, causes issues such as the cheese late-blowing defect, particularly triggered by Clostridium tyrobutyricum. The scope of our study was to determine the C. tyrobutyricum occurrence in three different farms across four time periods in relation to the animal diets, specifically the Total Mixed Ration (TMR), by using real-time PCR. Methods For this purpose, molecular-derived data were exploited to optimize a predictive model that simulated the farm conditions favoring the growth of butyric acid bacteria such as C. tyrobutyricum. Results Our results showed that the originally utilized predictive model strongly underestimated the growth of C. tyrobutyricum in comparison to the molecular data. At the same time, our findings uncovered an additional source of contamination in the TMR related to silage and dietary residues that represent a reservoir of microbial contamination during successive TMR preparation. Based on these findings, the optimization of the model parameters such as growth rate range and the inclusion of the residues in the model, allowed a more accurate prediction of the contamination levels. Therefore, this study revealed that proper hygiene practices such as the removal of silage and TMR residues within the farm environment is essential to control the contamination by C. tyrobutyricum and avoid food waste and economic losses.
TEN YEARS OF FUNDAMENTAL PHYSICS IN ESA'S SPACE SCIENCE PROGRAMME

Early days In the beginning, ESA’s Space Science Programme (actually ESRO’s in those days) consisted only of small magnetospheric satellites. ESRO-II, ESRO-IA, HEOS-1, ESROIB, HEOS-2 and ESRO-IV were launched between 1968 and 1972, addressing primarily problems in plasma physics. Throughout the 1970s, Solar System exploration continued to be limited to magnetospheric research, with the launches of GEOS-1 and -2 and ISEE-2. The first astronomy satellites (TD-1, COS-B and IUE) were launched between 1972 and 1978, making observations at UV, Xand γ-ray wavelengths.
Extragalactic H II regions in the UV - Implications for primeval galaxies

Three extragalactic regions of rapid star formation with redshifts great enough to separate the Ly.cap alpha. region from geocoronal Ly.cap alpha. have been observed with the IUE satellite. Only the low metal abundance object had detectable Ly.cap alpha. emission with Ly.cap alpha. /H.beta. approx.6; the other two have Ly.cap alpha. /H.beta. <0.6 (2sigma). In the normal metallicity objects, there is some evidence for Ly.cap alpha. extinction in addition to that computed from the Balmer decrement. Ly.cap alpha. is therefore expected to be weak or absent in collapsed primeval galaxies because of their predicted moderate to high metallicity.
Arthrogenic muscle inhibition after anterior cruciate ligament injury: Injured and uninjured limb recovery over time

Introduction It is well documented that marked weakness of the quadriceps is present after knee joint injury. This joint trauma induces a presynaptic reflex inhibition of musculature surrounding the joint, termed arthrogenic muscle inhibition (AMI). The extent to which anterior cruciate ligament (ACL) injury affects thigh musculature motor unit activity, which may affect restoration of thigh muscle strength after injury, is undetermined. Methods A randomized protocol of knee flexion and extension isometric contractions (10%–50% maximal voluntary isometric contraction) were performed for each leg on 54 subjects with electromyography array electrodes placed on the vastus medialis, vastus lateralis, semitendinosus, and biceps femoris. Longitudinal assessments for motor unit recruitment and average firing rate were acquired at 6-month intervals for 1 year post ACL injury. Results The ACL-injured population demonstrated smaller quadriceps and hamstrings motor unit size (assessed via motor unit action potential peak-to-peak amplitude) and altered firing rate activity in both injured and uninjured limbs compared to healthy controls. Motor unit activity remained altered compared to healthy controls at 12 months post ACL reconstruction (ACLR). Discussion Motor unit activity was altered after ACLR up to 12 months post-surgery. Further research is warranted to optimize rehabilitation interventions that adequately address altered motor unit activity and improve safety and success with return to sport after ACLR. In the interim, evidence based clinical reasoning with a focus on development of muscular strength and power capacity should be the impetus behind rehabilitation programming to address motor control deficits.