Miracle-dz/UniFAR-FTUs huggingface dataset:
Alginate Particles for Encapsulation of Phenolic Extract from Spirulina sp. LEB-18: Physicochemical Characterization and Assessment of In Vitro Gastrointestinal Behavior

Encapsulation can be used as a strategy to protect and control the release of bioactive extracts. In this work, an extract from Spirulina sp. LEB-18, rich in phenolic compounds, was encapsulated in biopolymeric particles (i.e., composed of alginate) and characterized concerning their thermal behavior using differential scanning calorimetry (DSC), size, morphology, swelling index (S), and encapsulation efficiency (EE%); the release profile of the phenolic compounds at different pHs and the particle behavior under in vitro gastrointestinal digestion were also evaluated. It was shown that it is possible to encapsulate the phenolic extract from Spirulina sp. LEB-18 in alginate particles with high encapsulation efficiency (88.97%). It was also observed that the particles are amorphous and that the encapsulated phenolic compounds were released at a pH 7.2 but not at pH 1.5, which means that the alginate particles are able to protect the phenolic compounds from the harsh stomach conditions but lose their integrity under intestinal pH conditions. Regarding bioaccessibility, it was observed that the encapsulated phenolic compounds showed higher bioaccessibility compared to phenolic compounds in free form. This work increases the knowledge about the behavior of alginate particles encapsulating phenolic compounds during in vitro gastrointestinal digestion. It also provides essential information for designing biopolymeric particle formulations encapsulating phenolic compounds for application in pharmaceutical and food products.
Entanglement and the fermion sign problem in auxiliary field quantum Monte Carlo simulations

Quantum Monte Carlo simulations of fermions are hampered by the notorious sign problem whose most striking manifestation is an exponential growth of sampling errors with the number of particles. With the sign problem known to be an NP-hard problem and any generic solution thus highly elusive, the Monte Carlo sampling of interacting many-fermion systems is commonly thought to be restricted to a small class of model systems for which a sign-free basis has been identified. Here we demonstrate that entanglement measures, in particular the so-called Renyi entropies, can intrinsically exhibit a certain robustness against the sign problem in auxiliary-field quantum Monte Carlo approaches and possibly allow for the identification of global ground-state properties via their scaling behavior even in the presence of a strong sign problem. We corroborate these findings via numerical simulations of fermionic quantum phase transitions of spinless fermions on the honeycomb lattice at and below half-filling.
Surgical Reconstruction Options for a Case of Near Total Intestinal Aganglionosis

Hirschsprung’s disease is a congenital anomaly affecting neural crest cell migration and proliferation in the myenteric plexi resulting in dysmotility, which can present as bilious emesis, delayed meconium passage, and bowel obstruction in neonates, or chronic constipation in older children. Depending on the extent of aganglionosis, this disease can involve the whole gut. Treatment involves a temporary ostomy and interval definitive surgical reconstruction. In patients with near or total intestinal aganglionosis, however, there is no consensus on the most effective surgical reconstruction as consideration of the length and function of the normal remnant bowel create concerns for complications with short bowel syndrome post-operatively. We present a case of near-total intestinal aganglionosis highlighting the various options for definitive surgical reconstruction.
Three-dimensional hydrodynamic simulations of L2 Puppis

Recent observations of the L2 Puppis system suggest that this Mira-like variable may be in the early stages of forming a bipolar planetary nebula (PN). As one of nearest and brightest AGB stars, thought be a binary, L2 Puppis serves as a benchmark object for studying the late-stages of stellar evolution. We perform global, three-dimensional, adaptive-mesh-refinement hydrodynamic simulations of the L2 Puppis system with AstroBEAR. We use the radiative transfer code RADMC-3D to construct the broad-band spectral-energy-distribution (SED) and synthetic observational images from our simulations. Given the reported binary parameters, we are able to reproduce the current observational data if a short pulse of dense material is released from the AGB star with a velocity sufficient to escape the primary but not the binary. Such a situation could result from a thermal pulse, be induced by a periastron passage of the secondary, or could be launched if the primary ingests a planet.
The Effect of Primordial Non-Gaussianities on the Seeds of Super-Massive Black Holes

The origin of the seeds which develop into the observed super-massive black holes at high redshifts may be hard to interpret in the context of the standard $\Lambda CDM$ of early universe cosmology based on Gaussian primordial perturbations. Here we consider the modification of the halo mass function obtained by introducing skewness and kurtosis of the primordial fluctuations. We show that such primordial non-Gaussianities constrained by the current observational bounds on the nonlinearity parameters of $f_{NL}$ and $g_{NL}$ are not effective at greatly increasing the number density of seeds which could develop into super-massive black holes at high redshifts. This is to be contrasted with the role which cosmic string loops could play in seeding super-massive black holes.
Source extraction and photometry for the far-infrared and sub-millimeter continuum in the presence of complex backgrounds

Context. Large-scale astronomical surveys from ground-based as well as space-borne facilities have always posed significant challenges concerning the problem of automatic extraction and flux estimate of sources. The recent explosion of surveys in the mid-and far infrared, as well as in the sub-millimeter, brings an increase to the complexity of the source extraction and photometry task because of the extraordinary level of foreground/background due to the thermal emission of cosmic cold dust. The maximum complexity is likely reached in star forming regions and on the Galactic Plane, where the emission from cold dust is dominant. Aims. We present a new method for detecting and measuring compact sources in conditions of intense, and highly variable, fore/background. Methods. While all most commonly used packages carry out the source detection over the signal image, our proposed method builds from the measured image a ”curvature” image by double-di erentiation in four di erent directions. In this way point-like as well as resolved, yet relatively compact, objects are easily revealed while the slower varying fore/background is greatly diminished. Candidate sources are then identified by looking for pixels where the curvature exceeds, in absolute terms, a given threshold; the methodology easily allows us to pinpoint breakpoints in the source brightness profile and then derive reliable guesses for the sources extent. Identified peaks are fit with 2D elliptical Gaussians plus an underlying planar inclined plateau, with mild constraints on size and orientation. Mutually contaminating sources are fit with multiple Gaussians simultaneously using flexible constraints. Results. We ran our method on simulated large-scale fields with 1000 sources of di erent peak flux overlaid on a realistic realization of di use background. We find detection rates in excess of 90% for sources with peak fluxes above the 3 signal noise limit; for about 80% of the sources the recovered peak fluxes are within 30% of their input values.
DeepCCB-OCC: Deep Learning-Driven Complementary Color Barcode-Based Optical Camera Communications

Display-to-camera (D2C) communications has emerged as a key method for next-generation videos that offer side information to camera-equipped devices during normal viewing. This paper presents Deep learning-driven Complementary Color Barcode-based Optical Camera Communications (DeepCCB-OCC), a D2C system using multiple deep neural networks built for imperceptible transmission and reliable communication in a D2C link. DeepCCB-OCC takes advantage of a the You Only Look Once (YOLO) model to provide seamless detection of a color barcode area in electronic displays. To identify transmitted color barcode symbols in the received image, we define various color barcode patterns caused by the synchronization jitter between the camera and the display. Then, DeepCCB-OCC incorporates convolutional neural network (CNN) models to accurately detect the pilot and data symbols in the transmission packets, regardless of the various D2C environments. Experiments with a commercial monitor and a smartphone demonstrate that DeepCCB-OCC outperforms the conventional CCB-OCC system from various distances and angles of a D2C link. The experiment results prove that, when the alignment angle was 20 degrees at a distance of 90 cm between the display and the camera, the proposed scheme achieved approximately 79.1 bps, which showed a performance improvement of 14.1% compared to the existing technique.
THE EXTENDED SPATIAL DISTRIBUTION OF GLOBULAR CLUSTERS IN THE CORE OF THE FORNAX CLUSTER

We report the discovery of a complex extended density enhancement in the Globular Clusters (GCs) in the central ∼ 0.5 ( ° ) 2 ? > ( ∼ 0.06 ? > Mpc2) of the Fornax cluster, corresponding to ∼ 50 % ? > of the area within 1 core radius. This overdensity connects the GC system of NGC 1399 to most of those of neighboring galaxies within ∼ 0 &fdg; 6 ? > ( ∼ 210 ? > kpc) along the W–E direction. The asymmetric density structure suggests that the galaxies in the core of the Fornax cluster experienced a lively history of interactions that have left a clear imprint on the spatial distribution of GCs. The extended central dominant structure is more prominent in the distribution of blue GCs, while red GCs show density enhancements that are more centrally concentrated on the host galaxies. We propose that the relatively small-scale density structures in the red GCs are caused by galaxy–galaxy interactions, while the extensive spatial distribution of blue GCs is due to stripping of GCs from the halos of core massive galaxies by the Fornax gravitational potential. Our investigations are based on density maps of candidate GCs extracted from the multi-band VLT Survey Telescope (VST) survey of Fornax (FDS), identified in a three-dimensional color space and further selected based on their g-band magnitude and morphology.
Spectral Evolution of a New X-Ray Transient MAXI J0556-332 Observed by MAXI, Swift, and RXTE

We report on the spectral evolution of a new X-ray transient, MAXI J0556−332, observed by MAXI, Swift, and RXTE. The source was discovered on 2011 January 11 (MJD=55572) by MAXI Gas Slit Camera all-sky survey at (l,b) = (238 ◦ .9,−25 ◦ .2), relatively away from the Galactic plane. Swift/XRT follow-up observations identified it with a previously uncatalogued bright X-ray source and led to optical identification. For more than one year since its appearance, MAXI J0556−332 has been X-ray active, with a 2-10 keV intensity above 30 mCrab. The MAXI/GSC data revealed rapid X-ray brightening in the first five days, and a hard-to-soft transition in the meantime. For the following ∼ 70days, the 0.5–30 keV spectra, obtained by the Swift/XRT and the RXTE/PCA on an almost daily basis, show a gradual hardening, with large flux variability. These spectra are approximated by a cutoff power-law with a photon index of 0.4–1 and a high-energy exponential cutoff at 1.5–5keV, throughout the initial 10 months where the spectral evolution is mainly represented by a change of the cutoff energy. To be more physical, the spectra are consistently explained by thermal emission from an accretion disk plus a Comptonized emission from a boundary layer around a neutron star. This supports the source identification as a neutron-star X-ray binary. The obtained spectral parameters agree with those of neutron-star X-ray binaries in the soft state, whose luminosity is higher than 1.8×10 37 erg s −1 . This suggests a source distance of > 17 kpc.
The challenge of measuring magnetic fields in strongly pulsating stars: the case of HD 96446

Among the early B-type stars, He-rich Bp stars exhibit the strongest large-scale organized magnetic fields with a predominant dipole contribution. The presence of $\beta$ Cep-like pulsations in the typical magnetic early Bp-type star HD 96446 was announced a few years ago, but the analysis of the magnetic field geometry was hampered by the absence of a reliable rotation period and a sophisticated procedure for accounting for the impact of pulsations on the magnetic field measurements. Using new spectropolarimetric observations and a recently determined rotation period based on an extensive spectroscopic time series, we investigate the magnetic field model parameters of this star under more detailed considerations of the pulsation behaviour of the line profiles.
Constraining thawing and freezing models with cluster number counts

Measurements of the cluster abundance as a function of mass and redshift provide an important cosmological test that probe not only the expansion rate but also the growth of perturbations. In this paper we adopt a scalar field scenario which admits both thawing and freezing solutions from an appropriate choice of the model parameters and derived all relevant expressions to calculate the mass function and the cluster number density. We discuss the ability of cluster observations to distinguish between these scalar field behaviors and the standard ΛCDM scenario by considering the eROSITA and SPT cluster surveys.
Design Analysis and Implementation of Stock Market Forecasting System using Improved Soft Computing Technique

In this paper, a stock market prediction model was created utilizing artificial neural networks. Many people nowadays are attempting to predict future trends in bonds, currencies, equities, and stock markets. It is quite challenging for a capitalist and an industry to forecast changes in stock market prices. Due to the numerous economic, political, and psychological aspects at play, forecasting future value changes on the stock markets is quite challenging. In addition, stock market forecasting is a difficult endeavor because it relies on a wide range of known and unknown variables. Many approaches, including technical analysis, fundamental analysis, time series analysis, and statistical analysis are used to attempt to predict the share price; however, none of these methods has been demonstrated to be a consistently effective prediction tool. Artificial neural networks (ANNs), a subfield of artificial intelligence, are one of the most modern and promising methods for resolving financial issues, such as categorizing corporate bonds and anticipating stock market indexes and bankruptcy (AI). Artificial neural networks (ANN) are a prominent technology used to forecast the future of the stock market. In order to understand financial time series, it is often essential to extract relevant information from enormous data sets using artificial neural networks. An outcome prediction neural network with three layers is trained using the back propagation method. Analysis shows that ANN outperforms every other prediction technique now available to academics in terms of stock market price predictions. It is concluded that ANN is a useful technique for predicting stock market movements globally.
Complete and consistent chiral transport from Wigner function formalism

Recently, there has been significant interest in understanding the macroscopic quantum transport in a many-body system of chiral fermions. A natural framework for describing such a system that is generally out of equilibrium is the transport equation for its phase space distribution function. In this paper, we obtain a complete solution of the covariant chiral transport for massless fermions, by starting from the general Wigner function formalism and carrying out a complete and consistent semiclassical expansion up to O^(ℏ) order. In particular, we clarify certain subtle and confusing issues surrounding the Lorentz noninvariance and frame dependence associated with the three-dimensional chiral kinetic theory. We prove that such frame dependence is uniquely and completely fixed by an unambiguous definition of the O^(ℏ) correction to the distribution function in each reference frame.
It’s Complicated: Examining Political Realities and Challenges in the Context of Research-Practice Partnerships from the School District Leader’s Perspective

Growing interest in the potential of education research-practice partnerships (RPPs) as a promising strategy for increasing the relevance and use of research has led the field to create an expanding body of literature documenting both the promise and the potential perils of RPPs. Insightful frameworks abound, outlining the structural and organizational considerations for forming and maintaining a successful RPP. Yet, less is known about how political realities within practice side organizations influence these partnerships. Drawing on Farrell et al.s’ framework describing RPPs as learning at the boundaries, I examine several examples of political challenges confronted by RPPs involving school districts and the degree to which school district leaders’ actions were able to mitigate the political challenges. Power imbalance exacerbated by funder priorities, the ripple effect of leadership change, and school board member priorities will be explored, along with discussions of implications.
Identification and Compensation for D-Dot Measurement System in Transient Electromagnetic Pulse Measurement

The measurement of the transient pulsed electromagnetic (EM) field is essential for analyzing electromagnetic compatibility. Due to their good performance, D-dot sensors, combined with numerical integration computation for signal recovery, are commonly used to measure electromagnetic pulses (EMPs). However, the integration approach is occasionally flawed due to a non-ideal frequency response or noise, causing distortions in the reconstructed signal. In order to better understand the dynamic performance of the sensor, a nonlinear Hammerstein model is employed in the system identification for the sensor with the calibration data collected in the laboratory environment. When identifying the linear component based on the ultra-wideband characteristics of the measured transient pulse, a two-step identification approach with two different pulse excitation modes, low frequency and high frequency, is utilized to conduct the modeling across the entire frequency range. Based on the reliable identification and modeling of the D-dot sensor, a compensation system that corresponds to the nonlinear Hammerstein model has been developed for the practical signal recovery of the incident E-field. After compensation, the dynamic characteristics of the sensor are significantly improved, and the system compensation approach outperforms the integration method in signal recovery for the incident E-field.
Dynamics of sessile drops. Part 3. Theory of forced oscillations

A partially-wetting sessile drop is driven by a sinusoidal pressure field that produces capillary waves on the liquid/gas interface. The analysis presented in Part 1 of this series (Bostwick & Steen 2014) is extended by computing response diagrams and phase shifts for the viscous droplet, whose three phase contact-line moves with contact-angle that is a smooth function of the contact line speed. Viscous dissipation is incorporated through the viscous potential flow approximation and the critical Ohnesorge number bounding regions beyond which a given mode becomes over-damped is computed. Davis dissipation originating from the contact-line speed condition leads to damped oscillations for drops with finite contact-line mobility, even for inviscid fluids. The critical mobility and associated driving frequency to generate the largest Davis dissipation is computed. Lastly, regions of modal coexistence where two modes can be simultaneously excited by a single forcing frequency are identified. Predictions compare favorably to related experiments on vibrated drops.
MOLECULAR OUTFLOWS FROM THE PROTOCLUSTER SERPENS SOUTH

We present the results of CO (J = 3–2) and HCO+ (J = 4–3) mapping observations toward a nearby embedded cluster, Serpens South, using the ASTE 10 m telescope. Our CO (J = 3–2) map reveals that many outflows are crowded in the dense cluster-forming clump that can be recognized as an HCO+ clump with a size of ∼0.2 pc and mass of ∼80 M☉. The clump contains several subfragments with sizes of ∼0.05 pc. By comparing the CO (J = 3–2) map with the 1.1 mm dust continuum image taken by AzTEC on ASTE, we find that the spatial extents of the outflow lobes are sometimes anti-correlated with the distribution of the dense gas, and some of the outflow lobes apparently collide with the dense gas. The total outflow mass, momentum, and energy are estimated to be 0.6 M☉, 8 M☉ km s−1, and 64 M☉ km2 s−2, respectively. The energy injection rate due to the outflows is comparable to the turbulence dissipation rate in the clump, implying that the protostellar outflows can maintain the supersonic turbulence in this region. The total outflow energy seems only about 10% of the clump gravitational energy. We conclude that the current outflow activity is not enough to destroy the whole cluster-forming clump, and therefore star formation is likely to continue for several or many local dynamical times.
Garlic Powder Supplementation Improves Growth, Nonspecific Immunity, Antioxidant Capacity, and Intestinal Flora of Chinese Mitten Crabs (Eriocheir sinensis)

This study was conducted to survey the effects of garlic powder on growth performance, nonspecific immunity, antioxidant capacity, and intestinal flora structure of Chinese mitten crabs. Altogether, 216 crabs which originally weigh 20.71 ± 0.13 g were randomly allocated into three treatment groups with 6 replicates of 12 crabs per replicate. The control group (CN) was fed a basal diet, while the other two groups were fed the basal diet supplemented with 1000 mg/kg (GP1000) and 2000 mg/kg (GP2000) garlic powder, respectively. This trial lasted 8 weeks. The results showed that the supplementation of garlic powder improved the final body weight, weight gain rate, and specific growth rate of the crabs (P < 0.05). Meanwhile, in serum, better nonspecific immune was confirmed by the enhancement of phenoloxidase and lysozyme levels, with the improvement of phosphatase activities in GP1000 and GP2000 (P < 0.05). On the other hand, the levels of total antioxidant capacity, glutathione peroxidases, and total superoxide dismutase in serum and hepatopancreas were increased (P < 0.05) while malondialdehyde content declined (P < 0.05) as the garlic powder was added to the basal diet. And, catalase in serum also shows an increase (P < 0.05). In both GP1000 and GP2000, genes related to antioxidant and immunity, for instance, Toll-like receptor 1, glutathione peroxidase, catalase, myeloid differentiation factor 88, TuBe, Dif, relish, crustins, antilipopolysaccharide factor, lysozyme, and prophenoloxidase mRNA expression levels, were increased (P < 0.05). The abundance of Rhizobium and Rhodobacter was reduced by adding garlic powder (P < 0.05). This study indicated that dietary addition of garlic powder promoted growth, enhanced nonspecific immunity and antioxidant capacity, activated Toll pathway, IMD pathway, and proPO system, increased antimicrobial peptide expression, while simultaneously improving the intestinal flora of Chinese mitten crabs.