Miracle-dz/UniFAR-FTUs huggingface dataset:
The Carter constant for inclined orbits about a massive Kerr black hole: I. Circular orbits

In an extreme binary black hole system, an orbit will increase its angle of inclination (ι) as it evolves in Kerr spacetime. We focus our attention on the behaviour of the Carter constant (Q) for near-polar orbits, and develop an analysis that is independent of and complements radiation-reaction models. For a Schwarzschild black hole, the polar orbits represent the abutment between the prograde and retrograde orbits at which Q is at its maximum value for given values of the latus rectum () and the eccentricity (e). The introduction of spin () to the massive black hole causes this boundary, or abutment, to be moved towards greater orbital inclination; thus, it no longer cleanly separates prograde and retrograde orbits. To characterize the abutment of a Kerr black hole (KBH), we first investigated the last stable orbit (LSO) of a test-particle about a KBH, and then extended this work to general orbits. To develop a better understanding of the evolution of Q we developed analytical formulae for Q in terms of , e and to describe elliptical orbits at the abutment, polar orbits and LSOs. By knowing the analytical form of at the abutment, we were able to test a 2PN flux equation for Q. We also used these formulae to numerically calculate the of hypothetical circular orbits that evolve along the abutment. From these values we have determined that . By taking the limit of this equation for , and comparing it with the published result for the weak-field radiation reaction, we found the upper limit on for the full range of up to the LSO. Although we know the value of at the abutment, we find that the second and higher derivatives of Q with respect to exert an influence on . Thus the abutment becomes an important analytical and numerical laboratory for studying the evolution of Q and ι in Kerr spacetime and for testing current and future radiation-back-reaction models for near-polar retrograde orbits.
Direct Capture and Early Detection of Lyme Disease Spirochete in Skin with a Microneedle Patch

Borrelia burgdorferi sensu lato family of spirochetes causes Lyme disease (LD) in animals and humans. As geographic territory of ticks expands across the globe, surveillance measures are needed to measure transmission rates and provide early risk testing of suspected bites. The current standard testing of LD uses an indirect two-step serological assay that detects host immune reactivity. Early detection remains a challenge because the host antibody response develops several weeks after infection. A microneedle (MN) device was developed to sample interstitial fluid (ISF) and capture spirochetes directly from skin. After sampling, the MN patch is easily dissolved in water or TE buffer, and the presence of spirochete DNA is detected by PCR. Performance was tested by spiking porcine ear skin with inactivated Borrelia burgdorferi, which had an approximate recovery of 80% of spirochetes. With further development, this simple direct PCR method could be a transformative approach for early detection of the causative agent of Lyme disease and enable rapid treatment to patients when infection is early, and numbers of systemic spirochetes are low.
Platelet-Derived Extracellular Vesicles Stimulate Migration through Partial Remodelling of the Ca2+ Handling Machinery in MDA-MB-231 Breast Cancer Cells

Background: Platelets can support cancer progression via the release of microparticles and microvesicles that enhance the migratory behaviour of recipient cancer cells. We recently showed that platelet-derived extracellular vesicles (PEVs) stimulate migration and invasiveness in highly metastatic MDA-MB-231 cells by stimulating the phosphorylation of p38 MAPK and the myosin light chain 2 (MLC2). Herein, we assessed whether the pro-migratory effect of PEVs involves the remodelling of the Ca2+ handling machinery, which drives MDA-MB-231 cell motility. Methods: PEVs were isolated from human blood platelets, and Fura-2/AM Ca2+ imaging, RT-qPCR, and immunoblotting were exploited to assess their effect on intracellular Ca2+ dynamics and Ca2+-dependent migratory processes in MDA-MB-231 cells. Results: Pretreating MDA-MB-231 cells with PEVs for 24 h caused an increase in Ca2+ release from the endoplasmic reticulum (ER) due to the up-regulation of SERCA2B and InsP3R1/InsP3R2 mRNAs and proteins. The consequent enhancement of ER Ca2+ depletion led to a significant increase in store-operated Ca2+ entry. The larger Ca2+ mobilization from the ER was required to potentiate serum-induced migration by recruiting p38 MAPK and MLC2. Conclusions: PEVs stimulate migration in the highly metastatic MDA-MB-231 breast cancer cell line by inducing a partial remodelling of the Ca2+ handling machinery.
Hitch Angle Estimation for Trailer Backup System—An Object Detection and Tracking Approach

This article proposes a novel technique for trailer angle detection (TAD) for use in an advanced trailer backup assistance system (TBAS) to accomplish a semiautonomous or full-autonomous backup maneuver. TBAS incorporates a combined trailer-tow vehicle kinematic model that requires an accurate estimate of the hitch angle. The proposed computer vision (CV) and machine learning (ML) TAD model process the image frames, acquired from the rear-facing camera, to detect and track the trailer and estimate its orientation in relation to the tow vehicle. The technique is based on a deep learning object detection and CV tracking model to detect and track one or more identifiable objects on the trailer (the marker-lights on the front edges of the trailer in this work). The estimated positions of the detected marker-lights are used to perform the hitch angle estimation. The model detects the hitch angle within the specified limit with an acceptance rate of 98%. The model is implemented in real time with a processing rate of more than 30 frames/s.
Kepler Eclipsing Binary Stars. VI. Identification of Eclipsing Binaries in the K2 Campaign 0 Data-set

The original {\it Kepler} mission observed and characterized over 2400 eclipsing binaries in addition to its prolific exoplanet detections. Despite the mechanical malfunction and subsequent non-recovery of two reaction wheels used to stabilize the instrument, the {\it Kepler} satellite continues collecting data in its repurposed {\it K2} mission surveying a series of fields along the ecliptic plane. Here we present an analysis of the first full baseline {\it K2} data release: the Campaign 0 data-set. In the 7761 light curves, we have identified a total of 207 eclipsing binaries. Of these, 97 are new discoveries that were not previously identified. Our pixel-level analysis of these objects has also resulted in identification of several false positives (observed targets contaminated by neighboring eclipsing binaries), as well as the serendipitous discovery of two short period exoplanet candidates. We provide catalog cross-matched source identifications, orbital periods, morphologies and ephemerides for these eclipsing systems. We also describe the incorporation of the K2 sample into the Kepler Eclipsing Binary Catalog\footnote{\url{keplerebs.villanova. edu/k2}}, present spectroscopic follow-up observations for a limited selection of nine systems, and discuss prospects for upcoming {\it K2} campaigns.
Lagrangian perturbation theory at one loop order: successes, failures, and improvements

We apply the convolved Lagrangian perturbation theory (CLPT) formalism, in which one can express the matter density power spectrum in terms of integrals over a function of cumulants of the displacement field, allowing for a resummation of the terms, to evaluate the full one loop power spectrum. We keep the cumulants up to third order, extending the Zel'dovich approximation and providing the power spectrum analogous to the calculations recently performed for the correlation function. We compare the results to the N-body simulations and to the Lagrangian perturbation simulations up to the second order. We find that the analytic calculations are in a good agreement with the LPT simulations, but when compared to full N-body simulations, we find that while one loop calculations improve upon the Zel'dovich approximation in the power spectrum, they still significantly lack power. As found previously in the correlation function one loop CLPT improves slightly against Zel'dovich above 30Mpc/h, but is actually worse than Zel'dovich below that. We investigate the deficiencies of the CLPT approach and argue that main problem of CLPT is its inability to trap particles inside dark matter halos, which leads to an overestimate of the small scale power of the displacement field and to an underestimate of the small scale power from one halo term effects. We model this using the displacement field damped at a nonlinear scale (CLPTs). To explore this in more detail we decompose the power spectrum and correlation function into three additive components: Zel'dovich, residual BAO wiggle, and residual broad band. One loop CLPT predicts small modifications to BAO wiggles that are enhanced in CLPTs, with up to 5\% corrections to correlation function around BAO scale.
Gut Microbiota in Nutrition and Health with a Special Focus on Specific Bacterial Clusters

Health is influenced by how the gut microbiome develops as a result of external and internal factors, such as nutrition, the environment, medication use, age, sex, and genetics. Alpha and beta diversity metrics and (enterotype) clustering methods are commonly employed to perform population studies and to analyse the effects of various treatments, yet, with the continuous development of (new) sequencing technologies, and as various omics fields as a result become more accessible for investigation, increasingly sophisticated methodologies are needed and indeed being developed in order to disentangle the complex ways in which the gut microbiome and health are intertwined. Diseases of affluence, such as type 2 diabetes (T2D) and cardiovascular diseases (CVD), are commonly linked to species associated with the Bacteroides enterotype(s) and a decline of various (beneficial) complex microbial trophic networks, which are in turn linked to the aforementioned factors. In this review, we (1) explore the effects that some of the most common internal and external factors have on the gut microbiome composition and how these in turn relate to T2D and CVD, and (2) discuss research opportunities enabled by and the limitations of some of the latest technical developments in the microbiome sector, including the use of artificial intelligence (AI), strain tracking, and peak to trough ratios.
Usability testing of intensive course mobile application using the usability scale system

The Mobile Intensive Course (MIC) application version 2 is an application designed to assist the learning process of the English intensive course subject. Measurement of the application usability has never been done before, so the effectiveness, efficiency, and user satisfaction for this application have not been measured yet. Also, usability measurement can be used as a reference for the level of user loyalty, whether it is net promoters, passive users, or detractors. One of the usability measuring tools that are easy to use but still valid and reliable, is the System Usability Scale (SUS). The purpose of this study was to test the usability of the application to determine the quality using the SUS questionnaire. This research was conducted in four steps, namely 1) trying out the application to the respondents; 2) distributing SUS questionnaires; 3) calculating the average SUS score; 4) analyzing the average SUS score. This study involved 37 respondents consisting of students and EIC lecturers. The results of this study indicates that the usability of the application can be accepted by users with an average SUS score of 70.61 and obtained C mark based on the CGS assessment. Nevertheless, the application only obtained passive users. The average contribution value for learnability was still low, namely 1.9 from the maximum score 4. It is necessary to improve future applications in terms of application learnability that allowing users to be more familiar with applications and potentially becoming net promoters.
A simple method to convert sink particles into stars

Hydrodynamical simulations of star formation often do not possess the dynamic range needed to fully resolve the build-up of individual stars and star clusters, and thus have to resort to subgrid models. A popular way to do this is by introducing Lagrangian sink particles, which replace contracting high density regions at the point where the resolution limit is reached. A common problem then is how to assign fundamental stellar properties to sink particles, such as the distribution of stellar masses. We present a new and simple statistical method to assign stellar contents to sink particles. Once the stellar content is specified, it can be used to determine a sink particle's radiative output, supernovae rate or other feedback parameters that may be required in the calculations. Advantages of our method are (i) it is simple to implement, (ii) it guarantees that the obtained stellar populations are good samples of the initial mass function, (iii) it can easily deal with infalling mass accreted at later times, and (iv) it does not put restrictions on the sink particles' masses in order to be used. The method works very well for sink particles that represent large star clusters and for which the stellar mass function is well sampled, but can also handle the transition to sink particles that represent a small number of stars.
Association between MnSOD Activity and Cognitive Impairment in Unmedicated First-Episode Schizophrenia: Regulated by MnSOD Ala-9Val Gene Polymorphism

The imbalance between pro-oxidants and antioxidants is thought to be responsible for aging and cognitive impairment in many degenerative diseases, including schizophrenia (SZ). As the first antioxidant enzyme to detoxify superoxide radicals in mitochondria, manganese superoxide dismutase (MnSOD) activity and its functional polymorphism of Ala-9Val have been found to be associated with SZ. In this study, we explored the association between MnSOD activity, MnSOD Ala-9Val polymorphism and cognitive dysfunction in unmedicated first-episode (UMFE) SZ patients, which has not been examined. We recruited 234 UMFE SZ patients and 232 healthy controls (HC) and evaluated them with Repeated Battery for the Assessment of Neuropsychological Status (RBANS), plasma MnSOD activity and MnSOD Ala-9Val (rs4880) polymorphism. In addition, we used the Positive and Negative Syndrome Scale (PANSS) to assess the severity of patients’ psychopathological symptoms. Compared with HC, UMFE patients showed extensive cognitive impairment on RBANS, and had higher MnSOD activity. MnSOD Ala-9Val polymorphism was not associated with SZ susceptibility and cognitive impairment, but only affected MnSOD activity in patients. Moreover, only in SZ patients with Val homozygotes, MnSOD activity was significantly correlated with cognitive impairment, especially in RBANS total score, visuospatial/constructional and attention index scores. Our results suggest that cognitive impairment is associated with MnSOD activity in patients with first-episode SZ, which may be regulated by MnSOD Ala-9Val polymorphism.
A DISTINCT PEAK-FLUX DISTRIBUTION OF THE THIRD CLASS OF GAMMA-RAY BURSTS: A POSSIBLE SIGNATURE OF X-RAY FLASHES?

Gamma-ray bursts (GRBs) are the most luminous events in the universe. Going beyond the short–long classification scheme, we work in the context of three burst populations with the third group of intermediate duration and softest spectrum. We are looking for physical properties which discriminate the intermediate duration bursts from the other two classes. We use maximum likelihood fits to establish group memberships in the duration–hardness plane. To confirm these results we also use k-means and hierarchical clustering. We use Monte Carlo simulations to test the significance of the existence of the intermediate group and we find it with 99.8% probability. The intermediate duration population has a significantly lower peak flux (with 99.94% significance). Also, long bursts with measured redshift have higher peak fluxes (with 98.6% significance) than long bursts without measured redshifts. As the third group is the softest, we argue that we have related them with X-ray flashes among the GRBs. We give a new, probabilistic definition for this class of events.
A Role of Local Influence in Selecting Regressors

A procedure for selecting regressors in the linear regression model is suggested using local influence approach. Under an appropriate perturbation scheme, the effect of perturbation of regressors on the profile log-likelihood displacement is assessed for variable selection. A numerical example is provided for illustration. Variable selection or subset selection problem has been studied in various statistical models, especially in the linear regression model. Numerous selection procedures based on diverse selection criteria have been suggested. Miller (2001) gave a comprehensive treatment of variable selection methods in regression. From Chapter 3 of Miller's book we can see that most selection methods do not guarantee a finding of the best-fitting subsets, or that some methods need enormous computation even when the number of regressors becomes a little large. Also, many selection methods do not consider all of regressors simultaneously at each selection stage. and this may be one reason why most selection methods do not guarantee a finding of the best-fitting subsets. In this work a procedure for selecting a regressor at each step is suggested. The procedure starts with the location model. At each step, we find the direction vector corresponding to the largest curvature of the profile log-likelihood displacement surface in view of Cook (1986) and select a regressor associated with the element of the above direction vector that has the largest absolute value. If an F-test of the hypothesis that the regression coefficients for regressors not selected so far are zero is not significant, then the selection procedure stops, and otherwise, we proceed further. This selection method considers all of regressors simultaneously at each step and it needs far less computation compared with the existing selection methods.
QUANTIFYING THE COLLISIONLESS NATURE OF DARK MATTER AND GALAXIES IN A1689

We use extensive measurements of the cluster A1689 to assess the expected similarity in the dynamics of galaxies and dark matter (DM) in their motion as collisionless “particles” in the cluster gravitational potential. To do so, we derive the radial profile of the specific kinetic energy of the cluster galaxies from the Jeans equation and observational data. Assuming that the specific kinetic energies of galaxies and DM are roughly equal, we obtain the mean value of the DM velocity anisotropy parameter and the DM density profile. Since this deduced profile has a scale radius that is higher than inferred from lensing observations, we tested the validity of the assumption by repeating the analysis using results of simulations for the profile of the DM velocity anisotropy. Results of both analyses indicate a significant difference between the kinematics of galaxies and DM within r ≲ 0.3rvir. This finding is also reflected in the shape of the galaxy number density profile, which flattens markedly with respect to the steadily rising DM profile at small radii. Thus, r ∼ 0.3rvir seems to be a transition region interior to which collisional effects significantly modify the dynamical properties of the galaxy population with respect to those of DM in A1689.
A BRIGHT, SPATIALLY EXTENDED LENSED GALAXY AT z = 1.7 BEHIND THE CLUSTER RCS2 032727-132623

We present the discovery of an extremely bright and extended lensed source from the second Red Sequence Cluster Survey (RCS2). RCSGA 032727-132609 is spectroscopically confirmed as a giant arc and counterimage of a background galaxy at z = 1.701, strongly lensed by the foreground galaxy cluster RCS2 032727-132623 at z = 0.564. The giant arc extends over ∼38″ and has an integrated r-band magnitude of 19.1, making it ∼20 times larger and ∼3.5 times brighter than the prototypical lensed galaxy MS1512-cB58. This is the brightest distant lensed galaxy in the universe known to date. We have collected photometry in nine bands, ranging from u to Ks, which densely sample the rest-frame UV and optical light, including the age-sensitive 4000 Å break. A lens model is constructed for the system and results in a robust total magnification of 2.04 ± 0.16 for the counterimage; we estimate an average magnification of 17.2 ± 1.4 for the giant arc based on the relative physical scales of the arc and counterimage on the sky. Fits of single-component spectral energy distribution models to the photometry result in a moderately young age, t = 80 ± 40 Myr, small amounts of dust, E(B − V) ⩽ 0.11, and an exponentially declining star formation history with e-folding time τ = 10 − 50 Myr. After correcting for the lensing magnification, we find a stellar mass of M* ∼ 1010 M☉ and a current star formation rate (SFR) ⩽77 M☉ yr−1. Allowing for episodic star formation, an underlying old burst could contain up to twice the mass inferred from single-component modeling. RCSGA 032727-132609 is typical of the known population of star-forming galaxies near this redshift in terms of its age and stellar mass. Its large magnification and spatial extent provide a unique opportunity to study the physical properties of an individual high-redshift star-forming galaxy in great detail, opening up a new window to the process of galaxy evolution between z = 1.7 and our local universe.
Secure Socket Shell Bruteforce Attack Detection With Petri Net Modeling

Secure Socket Shell exposes a secure interface for login to remote users. Password based authentication mechanism used by remote users is vulnerable to bruteforcing. In this attack an adversary systematically tries many passwords. These attacks can either be generated from a single source or collectively from a set of sources. In this paper we propose a method to detect such bruteforcing attacks and subsequently classify these attempts into three types as originating from single source, single domain and distributed attacks. We develop Petri-Net based model which identifies SSH connections corresponding to failed login attempts using network flow characteristics. The model also keeps track of sources of failed login attempts using which it subsequently labels a time interval as experiencing bruteforcing or not and if the interval is experiencing bruteforcing which type of attack it is. We experiment with network traffic collected from a production level server and also generated within a testbed setup and show that our model can detect attacks and also classify them. We also experiment with stealth attack variant where attacker keeps a low profile of attacks and suggest methods to handle such attack instances.