Miracle-dz/UniFAR-FTUs huggingface dataset:
Development of a Novel Flavored Goat Cheese with Gentiana lutea Rhizomes

Gentiana lutea rhizomes, generally used as a bittering agent in food, were harvested from two geographical sites (Massif Central: MC and Jura: J) to evaluate their potential use in the flavoring step during goat cheesemaking. Gentian flavored goat cheeses (MCGC and JGC) were elaborated by a one-night immersion of unflavored goat cheeses (CGC) into gentian-infused whey. The impregnation of gentian in goat cheeses was evaluated by chemical and sensory analysis. The chemical composition of cheeses was analyzed by HS-SPME-GC-MS (Head-Space—Solid Phase MicroExtraction—Gas Chromatography—Mass Spectrometry) for volatile compounds (alcohols, ketones, aldehydes, esters, alkenes, alkanes, acids, terpenes) and UHPLC-DAD (Ultra High-Performance Liquid Chromatography—Diode Array Detector) for gentian bitter compounds (seco-iridoids). The sensory analysis consisted of a bitterness rating and a free description of cheeses by 17 trained panelists. Results of the study highlighted that unflavored goat cheeses presented higher unpleasant notes (goaty and lactic whey) and higher amounts of hexanoic acid and toluene compared to gentian flavored goat cheeses. The bitterness of gentian flavored goat cheeses was higher compared to unflavored cheeses and could be explained by loganic acid transfer from yellow gentian to flavored cheeses. Other free descriptors of gentian flavored goat cheeses revealed more complex notes (herbal, vegetal, floral, sweet, spicy and creamy) and higher relative amounts of volatile compounds such as 3-methyl butanoic acid, 2-methyl propanoic acid, 4-methyl decane, 2,3-butanediol, ethanol, diacetyl, methyl acetate and 2-phenylethyl acetate, compared to unflavored cheeses. Phenylethyl acetate was the only volatile compound that enabled differentiation of gentian origin on gentian flavored goat cheeses. Gentian rhizomes could be considered a promising flavoring agent contributing to the olfactive and gustative complexity of flavored goat cheeses and the reduction of their goaty perceptions.
Risk Factors for Surgery in Patients with Intestinal Behçet’s Disease During Anti-Tumor Necrosis Factor-Alpha Therapy

Purpose Behçet’s disease (BD) is a chronic inflammatory immune-mediated disease involving multiorgan systems. Gastrointestinal (GI) manifestations of BD include abdominal pain, vomiting, GI bleeding, fistula formation, obstruction, and perforation that might require surgery. Recently, anti-tumor necrosis factor-alpha (anti-TNF-α) therapy has been shown to have favorable outcomes in patients with intestinal BD who are refractory to conventional therapy. This study sought to figure out the risk factors for undergoing surgery during anti-TNF-α therapy in patients with intestinal BD. Materials and Methods In this retrospective analysis of intestinal BD patients who were treated with anti-TNF-α, we collected the baseline patient data including comorbidities, clinical, endoscopic, and radiologic characteristics, and the Disease Activity Index for Intestinal Behçet’s Disease at the time of anti-TNF-α initiation. Each potential risk factor was compared. For multivariate analysis, Cox regression was used. Results A total of 62 patients were considered eligible for analysis, and 15 of them (24.1%) underwent surgery. In univariate analysis, the presence of extraintestinal manifestation, such as joint symptoms and erythrocyte sedimentation rate (ESR), were significantly associated with surgery during therapy. In multivariate analysis, drug response within 4 weeks [hazard ratio (HR), 64.59], skin and joint manifestation (HR, 10.23 and HR, 6.22), geographic ulcer (HR, 743.97), and ESR >42.5 mm/h (HR, 9.16) were found to be factors predictive of undergoing surgery during anti-TNF-α therapy. Conclusion We found five risk factors predictive of surgery in patients with intestinal BD receiving anti-TNF-α therapy, which can guide physicians in selecting appropriate patients between anti-TNF-α therapy and early surgery.
A Spitzer Space Telescope Infrared Spectrograph Spectral Atlas of Luminous 8 μm Sources in the Large Magellanic Cloud

We present an atlas of Spitzer Space Telescope Infrared Spectrograph (IRS) spectra of highly luminous, compact, mid-IR sources in the Large Magellanic Cloud. Sources were selected on the basis of IR colors and 8 μm (Midcourse Space Experiment) fluxes indicative of highly evolved, intermediate-to-high-mass stars with current or recent mass loss at large rates. We determine the chemistry of the circumstellar envelope from the mid-IR continuum and spectral features and classify the spectral types of the stars. In the sample of 60 sources, we find 21 red supergiants (RSGs), 16 C-rich asymptotic giant branch (AGB) stars, 11 H II regions, 4 likely O-rich AGB stars, 4 Galactic O-rich AGB stars, 2 OH/IR stars, and 2 B[e] supergiants with peculiar IR spectra. We find that the overwhelming majority of the sample AGB stars (with typical IR luminosities of ∼104 L⊙) have C-rich envelopes, while the O-rich objects are predominantly luminous RSGs with LIR ∼ 105 L⊙. For both classes of evolved star (C-rich AGB stars and RSGs), we use the near-to-mid-IR spectral energy distributions to determine mean bolometric corrections to the stellar K-band flux densities. For carbon stars, the bolometric corrections depend on the IR color, whereas for RSGs, the bolometric correction is independent of IR color. Our results reveal that objects previously classified as planetary nebulae on the basis of IR colors are, in fact, compact H II regions with very red IRS spectra that include strong atomic recombination lines and polycyclic aromatic hydrocarbon emission features. We demonstrate that the IRS spectral classes in our sample separate clearly in IR color-color diagrams that use combinations of Two Micron All Sky Survey data and synthetic Spitzer Infrared Array Camera and Multiband Imaging Photometer for Spitzer fluxes derived from the IRS spectra. On this basis we suggest diagnostics to identify and classify, with high confidence levels, IR-luminous evolved stars and compact H II regions in nearby galaxies using Spitzer and near-IR photometry.
A systematic review of therapeutic proteins as a promising approach to treat various diseases

Proteins if said as ‘magic molecules’ will not prove false because of a varied play it can deal with in view of health sector. In the past couple of decades, therapeutic proteins have gained significance as therapy for a wide range of diseases like cancer, cardiovascular, diabetes and some other diseases. Moreover, recently USFDA protein therapeutic products are also playing an important role in this concern. Whereas therapeutic application of whey protein is rapidly on its way to be proved helpful. The thing of concern to use of these therapeutic proteins for the treatment of various diseases is a proper and rational formulation of protein-based therapeutics. Advancements in the field of biotechnology have increased and facilitated the production of therapeutically significant proteins to combat various potentially fatal diseases. However, there are still a few factors that hinder the efficient use of these valuable therapeutics. For instance, the oral route of administration faces proteolysis and/or hydrolysis in the GIT, whereas some drugs go through the hepatic first pass effect or show poor distribution. Therefore, a better insight into the routes of administration and the drug absorption mechanisms (paracellular, transcellular, and carrier mediated) is essential. This review has explained all the possible factors that are linked with the basis of therapeutic proteins, including their introduction, classification, their importance in the healthcare system, and possible challenges that are currently being faced by scientists during the development of protein-based therapeutics.
Quantitative analysis of wing interference patterns in Drosophila spp. using hyperspectral images

Recent studies have reported wing interference patterns (WIPs), which reflect the microstructure of the wing, for small insects belonging to the Diptera and Hymenoptera orders. WIPs have been evaluated using RGB or multispectral images, but in contrast to these approaches, hyperspectral images allow a more detailed analysis of spectral variation, which may not be captured by RGB or multispectral images. Here, I investigated the WIPs of 12 Drosophila species using hyperspectral images. The average spectrum was calculated for each of the six compartments of the wing region and for the entire wing, including all six compartments. This information was used to evaluate sexual and interspecific differences in the WIPs of 12 Drosophila species. In addition, the possibility of species discrimination based on WIPs was explored using the random forest machine learning algorithm. The present study demonstrates significant sex and interspecific differences in WIPs for each of the six compartments of the wing regions as well as for the entire wing region. The results of the random forest machine learning algorithm suggested the possibility of species identification based on WIPs.
Adaptive Response in Rat Retinal Cell Cultures Irradiated with γ-rays

Retina can receive incidental γ-ray exposure from various sources. For example, although radiation therapy is a crucial tool for managing head and neck tumors, patients may develop ocular complications as collateral damage from accidental irradiation. Recently, there has been concern that retinal irradiation during space flight may compromise mission goals and long-term quality of life after space travel. Previously, in our in vitro model, we proved that immature retinal cells are more vulnerable to γ-radiation than differentiated neurons. Here, we investigate if a low-dose pre-irradiation (0.025 Gy), known to have a protective effect in various contexts, can affect DNA damage and oxidative stress in cells exposed to a high dose of γ-rays (2 Gy). Our results reveal that pre-irradiation reduces 2 Gy effects in apoptotic cell number, H2AX phosphorylation and oxidative stress. These defensive effects are also evident in glial cells (reduction in GFAP and ED1 levels) and antioxidant enzymes (catalase and CuZnSOD). Overall, our results confirm that rat retinal cultures can be an exciting tool to study γ-irradiation toxic effects on retinal tissue and speculate that low irradiation may enhance the skill of retinal cells to reduce damage induced by higher doses.
Are Turbo-like Codes Effective on Nonstandard Channels?*

Turbo codes and their close relatives, e.g. Gallager and RA codes, have been shown to be extraordinarily effective on the istandardichannel models, e.g. the binary erasure, binary symmetric, and the AWGN channels. In this paper we discuss the possibility of using turbo-like codes on a variety of other channel models, including some that are nonsymmetric, nonbinary, and multiuser. Our basic conclusion is that binary turbo-like codes with graph-based iterative decoding have great potential on nearly all such channels.
ESTABLISHING ZONES IN SINGLE-COMMAND CLASS-BASED RECTANGULAR AS/RS

Abstract In this paper, we develop procedures for dividing rectangular warehouses into classes. We describe three types of classes and develop their corresponding traveling time models. A solution procedure involving a one-dimensional (or at most two-dimensional) search is developed. We show that the one-dimensional search procedure is very effective in solving most practical problems. Additionally, we show that most of the savings obtained by a full-turnover policy can be obtained with a relatively few classes—a result similar to the one obtained for the square AS/RS.
Unitary spherical esprit: 2-d angle estimation with spherical arrays for scalar fields

The authors consider the problem of two-dimensional (2-D) direction-of-arrival estimation of multiple plane waves incident on a spherical array. We propose a novel subspace technique that provides automatically paired source azimuth and elevation estimates relying on a spherical phase-mode excitation approach. The algorithm is remarkable for the low computational complexity and enhanced performance in correlated source scenarios by relying on a real beamspace approach, which allows forward-backward averaging. Moreover, the technique yields very accurate estimates by including spherical phase modes of different orders. This is demonstrated by comparing the mean error of the angle estimates obtained by spherical ESPRIT and the corresponding Cramer Rao bounds.
Intraspecific competition in common coastal dune grasses overshadows facilitation on the dune face

Restoration of degraded dunes through revegetation of native dune building species is critical to preserve multiple ecosystem services (i.e., coastal protection, habitat). As dunes exhibit high levels of abiotic stress, it is likely that facilitative interactions among plants occur, reducing stress caused by harsh abiotic conditions, and benefiting restoration efforts. The research was to determine how plant spatial arrangement (clumped vs. dispersed) at the dune slope affects the growth of two dominant dune grasses along the United States Atlantic coast, Ammophila breviligulata (American beachgrass) and Uniola paniculata (sea oats). We determined the local distribution and density of each species through field surveys to inform a manipulative study of planting arrangement and to assess plant growth and survival under different spatial arrangements. Planting arrangement did not influence the survival of U. paniculata, but dispersed plantings had a positive effect on growth parameters (height, stem number, ramet number), compared to the clumped arrangement. No plantings of A. breviligulata survived by the end of the second season, regardless of planting arrangement. Clumped arrangements did not improve growth of U. paniculata or growth and survival of A. breviligulata over the two growing seasons studied; thus, creating clumped arrangements may not be necessary for revegetation efforts. However, observing natural spatial patterns and using this information to guide restoration planting may be beneficial as climate change may impact revegetation results due to increased abiotic stress. Further research focusing on biotic interactions and density of plantings at multiple locations along dunes will contribute to dune restoration planning.
Hypersonic flight experience

The flight test results from the X-15, Asset, Prime, Reentry F and Shuttle Orbiter flight research programmes are reviewed and compared with theory and ground- based experiments. Primary emphasis is placed on our present capability to predict aerodynamic coefficients and stability derivatives, and distributions of surface pressure and aerodynamic heating rate for typical orbital and sub-orbital hypersonic vehicles. Overall, this comparison demonstrates the feasibility of designing hypersonic vehicles based on tests in conventional perfect-gas wind tunnels supplemented by state-of-the-art CFD analysis. At Mach numbers up to approximately 8, real-gas effects are small and Mach number/Reynolds number simulation is sufficient to insure accurate prediction of aerodynamic characteristics. At higher mach numbers, real-gas effects become important but appear to affect primarily pitching moment and to have little influence on other aerodynamic characteristics. Viscous interaction effects appear to be well correlated by the viscous interaction parameter V̄'∞, and to affect primarily axial force. With the exception of RCS jet interactions, stability and control derivatives are well predicted throughout the hypersonic flight régime. State-of-the-art aerodynamic heating techniques appear to give accurate predictions for laminar and fully turbulent attached flows so long as there are no strong shock interactions or non-equilibrium chemistry effects. For such flows, heating rate distributions depend only weakly on Mach number for M∞ ≥ 8 and hence M∞ ≈ 8-10 wind tunnel results can be used throughout the hypersonic speed range. For high- speed, high-altitude flight, surface catalycity effects can have a major influence on heating rates but modern, finite-rate boundary layer analyses are capable of predicting major trends. The major remaining challenges are the accurate prediction of: (1) real-gas effects on longitudinal trim, (2) the effectiveness of blended high altitude control systems, (3) shock interaction heating, (4) heating rates for separated vortex-dominated leeside flows, and (5) boundary layer transition and relaminarzation. Finally, it is pointed out that there are no flight data on the propulsion-airframe integration effects that are so important for airbreathing launch vehicles.
SLOPE AND GEOMETRY IN VARIATIONAL MATHEMATICS

Various notions of the "slope" of a real-valued function pervade optimization, and variational mathematics more broadly. In the semialgebraic setting an appealing model for concrete variational problems the slope is particularly well-behaved. This talk sketches a variety of surprising applications, illustrating the unifying power of slope. Highlights include error bounds for level sets, the existence and regularity of steepest descent curves in complete metric spaces (following Ambrosio et al.), transversality and the convergence of von Neumann's alternating projection algorithm, and the geometry underlying nonlinear programming active-set algorithms. This talk will be self-contained, requiring no familiarity with variational analysis, optimization theory, or semi-algebraic geometry. Joint work with A. Daniilidis (Barcelona), A.D. Io e (Technion), M. Larsson (Lausanne), A.S. Lewis (Cornell).
On vector Lyapunov functions for stochastic dynamical systems

Vector Lyapunov functions are used in the stability analysis of large-scale stochastic systems described by Ito differential equations (with stochastic disturbances in the subsystems and in the interconnecting structure). Sufficient conditions for asymptotic stability and exponential stability with probability 1 and in probability are established, in all cases the objective is the same: to analyze large-scale systems in terms of their lower order (and simpler) subsystems and in terms of their interconnecting structure. Use of the method presented makes it often possible to circumvent difficulties usually encountered when the Lyapunov method is applied to high-dimensional systems and to systems with complicated interconnecting structure. In order to demonstrate the usefulness of the present approach, a specific example is considered.
Optimized Fast Filtration-Based Sampling and Extraction Enables Precise and Absolute Quantification of the Escherichia coli Central Carbon Metabolome

Precise and accurate quantification is a prerequisite for interpretation of targeted metabolomics data, but this task is challenged by the inherent instability of the analytes. The sampling, quenching, extraction, and sample purification conditions required to recover and stabilize metabolites in representative extracts have also been proven highly dependent on species-specific properties. For Escherichia coli, unspecific leakage has been demonstrated for conventional microbial metabolomics sampling protocols. We herein present a fast filtration-based sampling protocol for this widely applied model organism, focusing on pitfalls such as inefficient filtration, selective loss of biomass, matrix contamination, and membrane permeabilization and leakage. We evaluate the effect of and need for removal of extracellular components and demonstrate how residual salts can challenge analytical accuracy of hyphenated mass spectrometric analyses, even when sophisticated correction strategies are applied. Laborious extraction procedures are bypassed by direct extraction in cold acetonitrile:water:methanol (3:5:2, v/v%), ensuring compatibility with sample concentration and thus, any downstream analysis. By applying this protocol, we achieve and demonstrate high precision and low metabolite turnover, and, followingly, minimal perturbation of the inherent metabolic state. This allows us to herein report absolute intracellular concentrations in E. coli and explore its central carbon metabolome at several commonly applied cultivation conditions.
A Survey of Far Ultraviolet Spectroscopic Explorer and Hubble Space Telescope Sight Lines through High-Velocity Cloud Complex C

Using archival Far Ultraviolet Spectroscopic Explorer (FUSE) and Hubble Space Telescope (HST) data, we have assembled a survey of eight sight lines through high-velocity cloud Complex C. Abundances of the observed ion species vary significantly for these sight lines, indicating that Complex C is not well characterized by a single metallicity. Reliable metallicities based on [O I/H I] range from 0.1 to 0.25 Z☉. Metallicities based on [S II/H I] range from 0.1 to 0.6 Z☉, but the trend of decreasing abundance with H I column density indicates that photoionization corrections may affect the conversion to [S/H]. We present models of the dependence of the ionization correction on H I column density; these ionization corrections are significant when converting ion abundances to elemental abundances for S, Si, and Fe. The measured abundances in this survey indicate that parts of the cloud have a higher metallicity than previously thought and that Complex C may represent a mixture of "Galactic fountain" gas with infalling low-metallicity gas. We find that [S/O] and [Si/O] have a solar ratio, suggesting little dust depletion. Further, the measured abundances suggest an overabundance of O, S, and Si relative to N and Fe. The enhancement of these α-elements suggests that the bulk of the metals in Complex C were produced by Type II supernovae and then removed from the star-forming region, possibly via supernova-driven winds or tidal stripping, before the ISM could be enriched by N and Fe.
A Physics-Guided Graph Convolution Neural Network for Optimal Power Flow

The data-driven method with strong approximation capabilities and high computational efficiency provides a promising tool for optimal power flow (OPF) calculation with stochastic renewable energy. However, the topology change dramatically increases the learning difficulties and the demand for learning samples. In this work, we propose a physics-guided graph convolution neural network (GCNN) for OPF calculation with consideration of varying topologies, including the physics-guided graph convolution kernel, feature construction, and loss function formulation. Specifically, a physics-embedded graph convolution kernel is derived by aggregating the features from local neighborhoods utilizing the nodal OPF model formulation. An iterative feature construction method is also developed that encodes both the physical feature and practical constraints into the node vector. Finally, a correlative learning loss function to optimize the unbalanced power injection is developed. Extensive numerical results carried out on various IEEE test systems show that the prediction accuracy of OPF using the proposed method under varying topology changes can be improved by an average of 13.30% and up to 32.63% compared with state-of-the-art methods.