Miracle-dz/UniFAR-FTUs huggingface dataset:
The tangential velocity of M31: CLUES from constrained simulations

Determining the precise value of the tangential component of the velocity of M31 is a non trivial astrophysical issue, that relies on complicated modeling. This has recently lead to con- flicting estimates, obtained by several groups that used different methodologies and assump- tions. This letter addresses the issue by computing a Bayesian posterior distribution function of this quantity, in order to measure the compatibility of those estimates with LambdaCDM. This is achieved using an ensemble of local group (LG) look-alikes collected from a set of Con- strained Simulations (CSs) of the local Universe, and a standard unconstrained LambdaCDM. The latter allows us to build a control sample of LG-like pairs and to single out the influence of the environment in our results. We find that neither estimate is at odds with LambdaCDM; how- ever, whereas CSs favour higher values of vtan , the reverse is true for estimates based on LG samples gathered from unconstrained simulations, overlooking the environmental element
MTSv: rapid alignment-based taxonomic classification and high-confidence metagenomic analysis

As the size of reference sequence databases and high-throughput sequencing datasets continue to grow, it is becoming computationally infeasible to use traditional alignment to large genome databases for taxonomic classification of metagenomic reads. Exact matching approaches can rapidly assign taxonomy and summarize the composition of microbial communities, but they sacrifice accuracy and can lead to false positives. Full alignment tools provide higher confidence assignments and can assign sequences from genomes that diverge from reference sequences; however, full alignment tools are computationally intensive. To address this, we designed MTSv specifically for alignment-based taxonomic assignment in metagenomic analysis. This tool implements an FM-index assisted q-gram filter and SIMD accelerated Smith-Waterman algorithm to find alignments. However, unlike traditional aligners, MTSv will not attempt to make additional alignments to a TaxID once an alignment of sufficient quality has been found. This improves efficiency when many reference sequences are available per taxon. MTSv was designed to be flexible and can be modified to run on either memory or processor constrained systems. Although MTSv cannot compete with the speeds of exact k-mer matching approaches, it is reasonably fast and has higher precision than popular exact matching approaches. Because MTSv performs a full alignment it can classify reads even when the genomes share low similarity with reference sequences and provides a tool for high confidence pathogen detection with low off-target assignments to near neighbor species.
Mechanisms of nonthermal destruction of the superconducting state and melting of the charge-density-wave state by femtosecond laser pulses

The processes leading to nonthermal condensate vaporization and charge-density-wave (CDW) melting with femtosecond laser pulses is systematically investigated in different materials. We find that vaporization is relatively slow (${\ensuremath{\tau}}_{v}\ensuremath{\sim}1$ ps) and inefficient in superconductors, exhibiting a strong systematic dependence of the vaporization energy ${U}_{v}$ on ${T}_{c}$. In contrast, melting of CDW order proceeds rapidly (${\ensuremath{\tau}}_{m}=50$\char21{}200 fs) and more efficiently. A quantitative model describing the observed systematic behavior in superconductors is proposed based on a phonon-mediated quasiparticle (QP) bottleneck mechanism. In contrast, Fermi-surface disruption by hot QPs is proposed to be responsible for CDW state melting.
Descendants of the first stars: the distinct chemical signature of second-generation stars

Extremely metal-poor (EMP) stars in the Milky Way (MW) allow us to infer the properties of their progenitors by comparing their chemical composition to the metal yields of the first supernovae. This method is most powerful when applied to mono-enriched stars, i.e. stars that formed from gas that was enriched by only one previous supernova. We present a novel diagnostic to identify this subclass of EMP stars. We model the first generations of star formation semi-analytically, based on dark matter halo merger trees that yield MW-like halos at the present day. Radiative and chemical feedback are included self-consistently and we trace all elements up to zinc. Mono-enriched stars account for only $\sim 1\%$ of second generation stars in our fiducial model and we provide an analytical formula for this probability. We also present a novel analytical diagnostic to identify mono-enriched stars, based on the metal yields of the first supernovae. This new diagnostic allows us to derive our main results independently from the specific assumptions made regarding Pop III star formation, and we apply it to a set of observed EMP stars to demonstrate its strengths and limitations. Our results may provide selection criteria for current and future surveys and therefore contribute to a deeper understanding of EMP stars and their progenitors.
Speaker-Adapted End-to-End Visual Speech Recognition for Continuous Spanish

Different studies have shown the importance of visual cues throughout the speech perception process. In fact, the development of audiovisual approaches has led to advances in the field of speech technologies. However, although noticeable results have recently been achieved, visual speech recognition remains an open research problem. It is a task in which, by dispensing with the auditory sense, challenges such as visual ambiguities and the complexity of modeling silence must be faced. Nonetheless, some of these challenges can be alleviated when the problem is approached from a speaker-dependent perspective. Thus, this paper studies, using the Spanish LIP-RTVE database, how the estimation of specialized end-to-end systems for a specific person could affect the quality of speech recognition. First, different adaptation strategies based on the fine-tuning technique were proposed. Then, a pre-trained CTC/Attention architecture was used as a baseline throughout our experiments. Our findings showed that a two-step fine-tuning process, where the VSR system is first adapted to the task domain, provided significant improvements when the speaker adaptation was addressed. Furthermore, results comparable to the current state of the art were reached even when only a limited amount of data was available.
CMUT on Glass Substrate for Next-Generation Medical Imaging and Beyond

CMUT technology was invented and has been widely researched on silicon substrates. In recent years, fabrication of CMUT on glass substrates has raised significant interests because a number of advantages it can offer. First, parasitic capacitance could be easily reduced since glass is an insulating material. Second, insulation steps required in the silicon-based CMUT fabrication process could be avoided, leading to a reduced fabrication complexity. Third, anodic bonding can be used when the substrate is borosilicate glass, which is a low-temperature bonding technique and has a high tolerance to bonding surface area and roughness in addition to the advantages of silicon wafer bonding. Moreover, glass transparency can enable novel applications beyond pulse-echo ultrasound medical imaging and enlarge the potential markets of CMUTs.
Conservation laws in gravitational theories with general nonminimal coupling

We use the Lagrange-Noether methods to derive the conservation laws for models in which matter interacts nonminimally with the gravitational field. The nonminimal coupling function can depend arbitrarily on the gravitational field strength. The obtained result generalizes earlier findings. The generalized conservation laws provide the basis for the derivation of the equations of motion for the nonminimally coupled test bodies.
Restricted random walk model as a new testing ground for the applicability of q-statistics

We present exact results obtained from Master Equations for the probability function P(y, T) of sums of the positions xt of a discrete random walker restricted to the set of integers between −L and L. We study the asymptotic properties for large values of L and T. For a set of position-dependent transition probabilities the functional form of P(y, T) is with very high precision represented by q-Gaussians when T assumes a certain value T*∝L2. The domain of y values for which the q-Gaussian apply diverges with L. The fit to a q-Gaussian remains of very high quality even when the exponent a of the transition probability g(x)=|x/L|a+p with 0<p≪1 is different from 1, although weak, but essential, deviation from the q-Gaussian does occur for a≠1. To assess the role of correlations we compare the T dependence of P(y, T) for the restricted random walker case with the equivalent dependence for a sum y of uncorrelated variables x each distributed according to 1/g(x).
Human-Behavior-Based Personalized Meal Recommendation and Menu Planning Social System

The traditional dietary recommendation systems are basically nutrition or health-aware where the human feelings on food are ignored. Human affects vary when it comes to food cravings, and not all foods are appealing in all moods. It takes a lot of effort to learn people’s food preferences and make recommendations based on their affects and nutrition. A questionnaire-based and preference-aware meal recommendation system can be a solution. However, automated recognition of social affects on different foods and planning the menu considering nutritional demand and social affect has some significant benefits over the questionnaire-based and preference-aware meal recommendations. A patient with severe illness, a person in a coma, or patients with locked-in syndrome and amyotrophic lateral sclerosis (ALS) cannot express their meal preferences. Therefore, the proposed framework includes a social-affective computing module to recognize the affects of different meals where the person’s affect is detected using electroencephalography (EEG) signals. EEG allows to capture the brain signals and analyze them to anticipate affective state toward a food. In this study, we have used a 14-channel wireless Emotiv Epoc+ to measure affectivity for different food items. A hierarchical ensemble method is applied to predict affectivity upon multiple feature extraction methods and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is used to generate a food list based on the predicted affectivity. In addition to the meal recommendation, an automated menu planning approach is also proposed considering a person’s energy intake requirement, affectivity, and nutritional values of the different menus. The bin-packing algorithm is used for the personalized menu planning of breakfast, lunch, dinner, and snacks. The experimental findings reveal that the suggested affective computing, meal recommendation, and menu planning algorithms perform well across a variety of assessment parameters.
Path-integral representation for quantum spin models: Application to the quantum cavity method and Monte Carlo simulations

The cavity method is a well established technique for solving classical spin models on sparse random graphs (mean-field models with finite connectivity). Laumann et al. [arXiv:0706.4391] proposed recently an extension of this method to quantum spin-1/2 models in a transverse field, using a discretized Suzuki-Trotter imaginary time formalism. Here we show how to take analytically the continuous imaginary time limit. Our main technical contribution is an explicit procedure to generate the spin trajectories in a path integral representation of the imaginary time dynamics. As a side result we also show how this procedure can be used in simple heat-bath like Monte Carlo simulations of generic quantum spin models. The replica symmetric continuous time quantum cavity method is formulated for a wide class of models, and applied as a simple example on the Bethe lattice ferromagnet in a transverse field. The results of the methods are confronted with various approximation schemes in this particular case. On this system we performed quantum Monte Carlo simulations that confirm the exactness of the cavity method in the thermodynamic limit.
Probing Black Hole Magnetic Fields with QED.

The effect of vacuum birefringence is one of the first predictions of quantum electrodynamics (QED): the presence of a charged Dirac field makes the vacuum birefringent when threaded by magnetic fields. This effect, extremely weak for terrestrial magnetic fields, becomes important for highly magnetized astrophysical objects, such as accreting black holes. In the X-ray regime, the polarization of photons traveling in the magnetosphere of a black hole is not frozen at emission but is changed by the local magnetic field. We show that, for photons traveling along the plane of the disk, where the field is expected to be partially organized, this results in a depolarization of the X-ray radiation. Because the amount of depolarization depends on the strength of the magnetic field, this~effect can provide a way to probe the magnetic field in black-hole accretion disks and to study the role of magnetic fields in astrophysical accretion in general.
Developing of SiO2 Nanoshells Loaded with Fluticasone Propionate for Potential Nasal Drug Delivery: Determination of Pro-Inflammatory Cytokines through mRNA Expression

Mesoporous Silica Nanoparticles (MSN) are porous inorganic materials that have been extensively used for drug delivery due to their special qualities, such as biocompatibility, biodegradability, and non-toxicity. MSN is a promising drug delivery system to enhance the efficacy and safety of drug administration in nasal diseases like chronic rhinitis (CR). In this study, we used the sol-gel technique for MSN synthesis and incorporate fluticasone propionate (FP) for intranasal drug administration for the treatment of chronic rhinitis (CR). In order to confirm the particle size, shape, drug release, and compatibility, various instruments were used. MSN was effectively prepared with average sizes ranging between 400 ± 34 nm (mean ± SD) as measured by dynamic light scattering (DLS), while zeta potential verified in all cases their positive charged surface. To investigate MSN features, the Fourier transform infrared spectrometer (FTIR), scanning electron microscopy (SEM), transmission electron microscope (TEM), thermal analysis, X-ray diffraction (XRD), and nitrogen adsorption/desorption measurement were used. The loaded compound was submitted to in vitro dissolution tests, and a remarkable dissolution rate improvement was observed compared to the crystalline drug in both pH conditions (1.2 and 7.4 pH). By using an MTT assay cell viability was assessed. The expression levels of the anti-inflammatory cytokines IL-4 and IL-5 were also measured using mRNA extraction from rat blood. Other characterizations like acute toxicity and hemolytic activity were also performed to confirm loaded MSN safety. Loaded MSN was incorporated in nasal spray prepared by using innovator excipients including poloxamer. After this, its nasal spray’s physical characteristics were also determined and compared with a commercial product (Ticovate).
Using Programme Theory to evaluate Lean interventions in healthcare

Lean in healthcare has continued to attract practitioner and research interest over the past two deca-des yet lacks evidence of sustained application. This longitudinal case study examines Lean healthcare interventions through the lens of Programme Theory, to provide an understanding of the design and implementation of a Lean programme. Through a qualitative single case study of an NHS organisation implementing Lean, content analysis of 70 reports from a 6-year period was undertaken and supported by interview data from 12 respondents involved in Lean initiatives. Through Programme Theory, we identify contextual moderators, internal and external, informing the design and develop- ment of Lean efforts. The key to successful and sustained Lean efforts is staff acceptance of the Programme Theory for delivering and maintaining outcomes. This has been identified as a key social determinant for Lean sustainability. Results from the research provide practical implications for design- ing a programme that accommodates resource challenges while incorporating multiple contextual drivers. The case study highlights an organisation ’ s Lean journey and the best practices that evolved; however, further longitudinal investigations are required to validate the findings.
New observational constraints on interacting dark energy using galaxy clusters virial equilibrium states

The nature of the dark sector components of the Universe still remains one of the largest unknown. Among many possibilities, it has been speculated that dark matter and dark energy may be more tightly coupled than usually thought, one component interacting with the other. Here, we continue to explore the possible dark sector interaction through means of the Layzer–Irvine equation together with a model of an interacting dark sector applied to clusters of galaxies. We have selected galaxy clusters that have their mass profiles determined by gravitational lensing effect (optical observations) and have their intracluster gas temperatures measured from X-ray observations and spectral fit found in the literature. Using a simple model based on semi-analytical simulations, we derived a putative dynamical evolution of the clusters and used it to estimate the coupling parameter of the dark sector interaction. Through a Bayesian analysis, we obtain a 3σ detection of the interaction strength for 11 clusters at −0.027 ± 0.009 that translates in a compounded Universal equilibrium virial ratio, U/T, of $-0.61^{+0.04}_{-0.03}$. We note that the X-ray temperature determination is sometimes inconsistent, depending on the instrument and/or methodology used. The level of detection and these inconsistencies call for caution. We expect that future observations will give us a clearer indication of an eventual dark sector interaction.
Weak gravitational lensing with CO galaxies.

Optical weak lensing surveys have become a powerful tool for precision cosmology, but remain subject to systematic effects that can severely bias cosmological parameter estimates if not carefully removed. We discuss the possibility of performing complementary weak lensing surveys at radio/microwave frequencies, using detections of CO-emitting galaxies with resolved continuum images from ngVLA. This method has completely different systematic uncertainties to optical weak lensing shear measurements (e.g. in terms of blending, PSF, and redshift uncertainties), and can provide additional information to help disentangle intrinsic alignments from the cosmological shear signal. A combined analysis of optical and CO galaxy lensing surveys would therefore provide an extremely stringent validation of highly-sensitive future surveys with Euclid, LSST, and WFIRST, definitively rejecting biases due to residual systematic effects. A lensing survey on ngVLA would also provide valuable spectral (kinematic) and polarimetric information, which can be used to develop novel cosmological analyses that are not currently possible in the optical.
Development and Application of Dual-Sensors Label in Combination with Active Chitosan-Based Coating Incorporating Yarrow Essential Oil for Freshness Monitoring and Shelf-Life Extension of Chicken Fillet

This study aimed for the application of active chitosan coating incorporating yarrow essential oil (YEO) together with the development of an on-package sensor label based on bromocresol purple (BCP) and methyl red (MR) for shelf-life extension and freshness monitoring of chicken breast fillet. Physiochemical and microbiological attributes of chicken meat coated with sole chitosan, YEO, and chitosan + YEO were compared with those of uncoated (control) samples. Chitosan + YEO coated chicken meat stayed fresh with no significant changes (p > 0.05) in pH (5.42–5.56), TVB-N (12.55–15.36 mg N/100 g), TBARs (0.35–0.40 mg MDA/kg) and total aerobic psycrotrophic bacteria (3.97–4.65 log CFU/g) in days 1–15. There was no response of the dual-sensors label toward the variation in chemical and microbiological indicators of chicken meat coated with chitosan + YEO. However, either uncoated, sole chitosan, or sole YEO treatments indicated a three-stage freshness status with the fresh stage belonged to a period earlier than day 7 (with no distinct color change in both sensor labels); the semi-fresh stage corresponded to storage days between 7–9, wherein a gradual color change appeared (MR from pink to orange, BCP from yellow to light purple); and the spoiled stage occurred in day 9 onward with a drastic color change (MR from orange to light yellow, BCP from light purple to deep purple). In general, the dual-sensors successfully responded to the variation of chemical and microbiological indicators and visual color of uncoated samples during storage time. Based on the obtained results, the application of chitosan + YEO coating efficiently prolonged the freshness of chicken breast meat, where on-package dual-sensors systems were able to detect the freshness stages of meat samples during storage time.
Low $Q^2$ weak mixing angle measurements and rare Higgs decays

A weighted average weak mixing angle theta_W derived from relatively low Q^2 experiments is compared with the Standard Model prediction obtained from precision measurements. The approximate 1.8 sigma discrepancy is fit with an intermediate mass (~ 10-35 GeV) "dark" Z boson Z_d, corresponding to a U(1)_d gauge symmetry of hidden dark matter, which couples to our world via kinetic and Z-Z_d mass mixing. Constraints on such a scenario are obtained from precision electroweak bounds and searches for the rare Higgs decays H -> Z Z_d -> 4 charged leptons at the LHC. The sensitivity of future anticipated low Q^2 measurements of sin^2 theta_W(Q^2) to intermediate mass Z_d is also illustrated. This dark Z scenario can provide interesting concomitant signals in low energy parity violating measurements and rare Higgs decays at the LHC, over the next few years.
Circadian Disruption and Consequences on Innate Immunity and Inflammatory Response

Circadian rhythms control almost all aspects of physiology and behavior, allowing temporal synchrony of these processes between each other, as well as with the external environment. In the immune system, daily rhythms of leukocyte functions can determine the strength of the immune response, thereby regulating the efficiency of defense mechanisms to cope with infections or tissue injury. The natural light/dark cycle is the prominent synchronizing agent perceived by the circadian clock, but this role of light is highly compromised by irregular working schedules and unintentional exposure to artificial light at night (ALAN). The primary concern is disrupted circadian control of important physiological processes, underlying potential links to adverse health effects. Here, we first discuss the immune consequences of genetic circadian disruption induced by mutation or deletion of specific clock genes. Next, we evaluate experimental research into the effects of disruptive light/dark regimes, particularly light-phase shifts, dim ALAN, and constant light on the innate immune mechanisms under steady state and acute inflammation, and in the pathogenesis of common lifestyle diseases. We suggest that a better understanding of the mechanisms by which circadian disruption influences immune status can be of importance in the search for strategies to minimize the negative consequences of chronodisruption on health.