Miracle-dz/UniFAR-FTUs huggingface dataset:
PERFORMANCE AND CARCASS YIELDS OF COBB 500 BROILERS FED DIFFERENT DIETARY PROGRAMS AND BIOACTIVE ADDITIVES

The experiment was performed to evaluate the impact of feeding different dietary programs having different levels of metabolizable energy (ME) during starter period and those of finisher ones which were less than that of the commercial standard (3150 kcal/kg) by 50, 100 and 150 kcal/kg with or without Bacillus amyloliquefaciens and energy enzymes on broilers productive performance and carcass characteristics. A total of 7300 Cobb 500 unsexed one day-old chicks were used. All chicks were fed pre-starter diet contained 23% crude protein (CP) and 2950 kcal ME /kg during the phase of (1-7) days. Afterward, experimental groups consist of 18 feeding programs where each program consists of two phases. During starter phase (8 -17) days, birds fed experimental diets contained constant level of CP (22%) with either of three ME levels (2950, 3000 or 3050 kcal/kg), whereas through the finisher phase (18 – 35 days), birds received diets of constant level of CP (21%) with either of the three graded ME levels being 3100, 3050 or 3000 kcal/kg with or without studied additives for each. Results showed that the best live body weight, body weight gain and feed conversion ratio (FCR) were observed in dietary program included starter diet of 3050 kcal ME/kg and finisher one of 3100 kcal ME/kg with additives inclusion compared with the worst FCR of dietary program included starter diet of 2950 kcal ME/kg and finisher one of 3000 kcal ME/kg without additives. Carcass and abdominal fat weights were significantly improved (P≤0.05) by either feed programs with additives compared with those un-supplemented. Furthermore, and no significant effects on dressed and carcass cut weight were observed among dietary treatments. It can be concluded that, feeding dietary program included starter diet of 3050 kcal ME/kg with 22% CP and finisher one of 21% CP and 3100 kcal ME/kg (50 kcal/kg less than recommended) with bioactive additives had a beneficial effect on broiler productive performance and carcass yields.
High resolution computed tomography and chest x-ray findings in patient with pulmonary tuberculosis

Background: Pulmonary Tuberculosis (PTB) is a major public health problem in Nepal. Diag­nosis of pulmonary tuberculosis is done by bacteriological confirmation of respiratory speci­men however Negative smear needs clinical and radiological evaluation for the diagnosis in suspected patient. This study focuses on radiological findings in both Pulmonary bacterio­logically confirmed (PBC) and pulmonary clinically diagnosed (PCD) Tuberculosis. Methods: This observational study was conducted at Chitwan Medical College between Feb 2019 to July 2019. 45 Patient diagnosed with PTB were enrolled. Chest X-ray (CXR) and High Resolution Computed Tomography (HRCT) chest reports were analysed for the presence of findings that suggest active infection like cavity, consolidation, tree in bud, etc in PBC and PCD. Results: A total of 45 PTB patients with mean age: 54.60 ± 19 years were included. 53.3 % were PBC and 46.7 % were PCD tuberculosis, CXR findings in PBC and PCD tuberculosis was nodular infiltrate 45.8% versus 2.4%, consolidation 45% versus 42.9%, cavity 8.3% versus 14.3% respectively however 12.5% PBC tuberculosis patient had a normal chest x-ray. HRCT chest in PBC and PCD showed cavity in 45.8% versus 23%, tree in bud 25% versus 52.4%, con­solidation 62.5 versus 57.1%, ground glass opacity 29.2% versus 23.8% respectively and none of the HRCT chest was normal. In comparison to the CXR, HRCT chest shows more cavitary lesions in PBC and tree in bud was more common in PCD. Conclusions: This study has found that radiological findings suggestive of active PTB was more obvious in HRCT than CXR. Presence of cavity, lobar consolidation and tree in bud lesion in HRCT chest were more frequently observed in both PBC and PCD Tuberculosis.
World Water Congress XV, 2015 Sensitivity of urban drainage networks to spatio-temporal rainfall variability: A case study in Seoul, South Korea

Prediction of runoff hydrographs has been being a long-standing topic of hydrology. It is well recognized that the surface runoff from a watershed depends on the hydro-meteorological characteristics of the rainfall and the physiographic properties of the watershed (Yen and Chow, 1969). Physiographic properties includes watershed properties including area, slope, geometry and land use of a watershed and drainage network properties. Physiographic properties can be divided into surface and subsurface features. Infiltration and antecedent conditions can also be regarded as additional factors affecting a flow hydrograph (Singh, 1997). The temporal and spatial rainfall variation caused by the rainstorm movement, which results in significant difference in hydrologic response at the outlet of a watershed for a given amount of rainfall.
Physics of Prodigious Lyman Continuum Leakers

An analysis of the dynamics of a star formation event is performed. It is shown that galaxies able to drive leftover gas to sufficient altitudes in a few million years are characterized by two basic properties: small sizes (≤1 kpc) and high star formation rate (SFR) surface densities ( ). For the parameter space of relevance, the outflow is primarily driven by supernovae with radiation pressure being significant but subdominant. Our analysis provides the unifying physical origin for a diverse set of observed Lyman continuum photons (LyC) leakers, including the green-pea galaxies, [S ii]-weak galaxies, and Lyα emitters, with these two characteristics as the common denominator. Among verifiable physical properties of LyC leakers, we predict that (1) the newly formed stellar masses are typically in the range of 108–1010 , except perhaps ultra-luminous infrared galaxies (ULIRGs), (2) the outflow velocities are typically in the range typically of 100–600 , but may exceed 103 in ULIRGs, with a strong positive correlation between the stellar masses formed and the outflow velocities, (3) the overall escape fraction of galaxies is expected to increase with increasing redshift, given the cosmological trend that galaxies become denser and more compact with increasing redshift. In addition, two interesting by-product predictions are also borne out. First, ULIRGs appear to be in a parameter region where they should be prodigious LyC leakers, unless there is a large ram pressure due to infalling gas with a rate exceeding about 30 times the SFR. Then, toward the tail end of a ULIRG event when the ram pressure relents, advanced ULIRGs are expected to leak more LyC photons than earlier ULIRGs. Second, Lyman-break galaxies (LBGs) are not supposed to be prodigious LyC leakers in our model, given their claimed effective radii exceeding 1 kpc. Thus, if LBGs are observed to have LyC leakers, it may be that the effective radii of their star-forming regions have been overestimated by a factor of 2–4.
Noncontextuality inequalities from antidistinguishability

Noncontextuality inequalities are usually derived from the distinguishability properties of quantum states, i.e. their orthogonality. Here, we show that antidistinguishability can also be used to derive noncontextuality inequalities. The Yu-Oh 13 ray noncontextuality inequality can be re-derived and generalized as an instance of our antidistinguishability method. For some sets of states, the antidistinguishability method gives tighter bounds on noncontextual models than just considering orthogonality, and the Hadamard states provide an example of this. We also derive noncontextuality inequalities based on mutually unbiased bases and symmetric informationally complete POVMs. Antidistinguishability based inequalities were initially discovered as overlap bounds for the reality of the quantum state. Our main contribution here is to show that they are also noncontextuality inequalities.
Formation channels of slowly rotating early-type galaxies

We study the evidence for a diversity of formation processes in early-type galaxies by presenting the first complete volume-limited sample of slow rotators with both integral-field kinematics from the ATLAS3D Project and high spatial resolution photometry from the Hubble Space Telescope. Analysing the nuclear surface brightness profiles of 12 newly imaged slow rotators, we classify their light profiles as core-less, and place an upper limit to the core size of about 10 pc. Considering the full magnitude and volume-limited ATLAS3D sample, we correlate the presence or lack of cores with stellar kinematics, including the proxy for the stellar angular momentum (λRe) and the velocity dispersion within one half-light radius (σe), stellar mass, stellar age, α-element abundance, and age and metallicity gradients. More than half of the slow rotators have core-less light profiles, and they are all less massive than 1011 M⊙. Core-less slow rotators show evidence for counter-rotating flattened structures, have steeper metallicity gradients, and a larger dispersion of gradient values (Δ[Z/H]¯ = −0.42 ± 0.18) than core slow rotators (Δ[Z/H]¯ = −0.23 ± 0.07). Our results suggest that core and core-less slow rotators have different assembly processes, where the former, as previously discussed, are the relics of massive dissipation-less merging in the presence of central supermassive black holes. Formation processes of core-less slow rotators are consistent with accretion of counter-rotating gas or gas-rich mergers of special orbital configurations, which lower the final net angular momentum of stars, but support star formation. We also highlight core fast rotators as galaxies that share properties of core slow rotators (i.e. cores, ages, σe, and population gradients) and core-less slow rotators (i.e. kinematics, λRe, mass, and larger spread in population gradients). Formation processes similar to those for core-less slow rotators can be invoked to explain the assembly of core fast rotators, with the distinction that these processes form or preserve cores.
Equilibrium models of the Milky Way mass are biased high by the LMC

Recent measurements suggest that the Large Magellanic Cloud (LMC) may weigh as much as 25 per cent of the Milky Way (MW). In this work, we explore how such a large satellite affects mass estimates of the MW based on equilibrium modelling of the stellar halo or other tracers. In particular, we show that if the LMC is ignored, the MW mass within 200 kpc is overestimated by as much as 50 per cent. This bias is due to the bulk motion in the outskirts of the Galaxy’s halo and can be, at least in part, accounted for with a simple modification to the equilibrium modelling. Finally, we show that the LMC has a substantial effect on the orbit Leo I which acts to increase its present-day speed relative to the MW. We estimate that accounting for a $1.5\times 10^{11} \, \mathrm{M}_\odot$ LMC would lower the inferred MW mass to $\sim 10^{12} \, \mathrm{M}_\odot$.
Unsupervised Pixel-level Road Defect Detection via Adversarial Image-to-Frequency Transform

In the past few years, the performance of road defect detection has been remarkably improved thanks to advancements in various studies on computer vision and deep learning. Although large-scale and well-annotated datasets enhance the performance of detecting road defects to some extent, it is still challengeable to derive a model which can perform reliably for various road conditions in practice, because it is intractable to construct a dataset considering diverse road conditions and defect patterns. To end this, we propose an unsupervised approach to detect road defects, using Adversarial Image-to-Frequency Transform (AIFT). AIFT adopts the unsupervised manner and adversarial learning in deriving the defect detection model, so AIFT does not require annotations for road defects. We evaluate the efficiency of AIFT using GAPs384 dataset, Cracktree200 dataset, CRACK500 dataset, and CFD dataset. The experimental results demonstrate that the proposed approach detects various road detects, and it outperforms existing state-of-the-art approaches.
Exploiting Uncertainty in Popularity Prediction of Information Diffusion Cascades Using Self-exciting Point Processes

Hawkes processes have been successfully applied to understand online information diffusion and popularity of online items. Most prior work concentrate on individually modeling successful diffusion cascades, while discarding smaller cascades which, however, account for a majority proportion of the available data. In this work, we propose a set of tools to leverage information in the small cascades: a joint fitting procedure that accounts for cascade size bias in the sample, a Borel mixture model and a clustering algorithm to uncover latent groups within these cascades, and the posterior final size distribution of Hawkes processes. On a dataset of Twitter cascades, we show that, compared to the state-of-art models, the proposed method improves the generalization performance on unseen data, delivers better prediction for final popularity and provides means to characterize online content from the way Twitter users discuss about it.
Urban2Vec: Incorporating Street View Imagery and POIs for Multi-Modal Urban Neighborhood Embedding

Understanding intrinsic patterns and predicting spatiotemporal characteristics of cities require a comprehensive representation of urban neighborhoods. Existing works relied on either inter- or intra-region connectivities to generate neighborhood representations but failed to fully utilize the informative yet heterogeneous data within neighborhoods. In this work, we propose Urban2Vec, an unsupervised multi-modal framework which incorporates both street view imagery and point-of-interest (POI) data to learn neighborhood embeddings. Specifically, we use a convolutional neural network to extract visual features from street view images while preserving geospatial similarity. Furthermore, we model each POI as a bag-of-words containing its category, rating, and review information. Analog to document embedding in natural language processing, we establish the semantic similarity between neighborhood (“document”) and the words from its surrounding POIs in the vector space. By jointly encoding visual, textual, and geospatial information into the neighborhood representation, Urban2Vec can achieve performances better than baseline models and comparable to fully-supervised methods in downstream prediction tasks. Extensive experiments on three U.S. metropolitan areas also demonstrate the model interpretability, generalization capability, and its value in neighborhood similarity analysis.
Neutrino Transport with Monte Carlo Method. I. Toward Fully Consistent Implementation of Nucleon Recoils in Core-collapse Supernova Simulations

The small energy exchange via nucleon recoils in neutrino–nucleon scattering is now supposed to be one of the important factors for successful explosions of core-collapse supernovae (CCSNe), as they can change neutrino spectra through accumulation of a large number of scatterings. In deterministic methods employed for neutrino transport in CCSN simulations, we normally cannot afford to deploy a large enough number of energy bins needed to resolve this small energy exchange, and subgrid techniques are employed one way or another. In this paper, we study quantitatively with the Monte Carlo (MC) method how well such a treatment performs. We first investigate the effects of nucleon recoils on the neutrino spectra and confirm that the average energy is reduced by ∼15% for heavy-lepton neutrinos and much smaller amounts for other types of neutrinos in a typical postbounce situation. It is also observed that the nucleon scattering dominates the electron scattering in the thermalization of neutrino spectra in all flavors. We then study possible artifacts that the coarse energy grid may produce in the deterministic methods. In order to mimic the latter calculation, we redistribute MC particles in each energy bin after a certain interval in a couple of ways and study how the results are affected, depending on the energy resolution. We also discuss the possible implications of our results for the deterministic methods.
Creep Motion of Elastic Interfaces Driven in a Disordered Landscape

The thermally activated creep motion of an elastic interface weakly driven on a disordered landscape is one of the best examples of glassy universal dynamics. Its understanding has evolved over the past 30 years thanks to a fruitful interplay among elegant scaling arguments, sophisticated analytical calculations, efficient optimization algorithms, and creative experiments. In this article, starting from the pioneer arguments, we review the main theoretical and experimental results that lead to the current physical picture of the creep regime. In particular, we discuss recent works unveiling the collective nature of such ultraslow motion in terms of elementary activated events. We show that these events control the mean velocity of the interface and cluster into “creep avalanches” statistically similar to the deterministic avalanches observed at the depinning critical threshold. The associated spatiotemporal patterns of activated events have been recently observed in experiments with magnetic domain walls. The emergent physical picture is expected to be relevant for a large family of disordered systems presenting thermally activated dynamics.
Degenerate doping in β-Ga2O3 single crystals through Hf-doping

n-type conductivity of β-Ga2O3 grown from the melt is typically achieved using Sn and Si. In this paper, we experimentally and computationally investigate Hf doping of β-Ga2O3 single crystals using UV–vis-NIR absorption and Hall effect measurements and hybrid functional calculations. Unintentionally-doped and Hf-doped samples with a nominal concentration of 0.5at% were grown from the melt using vertical gradient freeze and Czochralski method in mixed Ar + O2 atmosphere. We demonstrate Hf dopants, predicted to incorporate on the octahedral GaII site as a shallow donor, achieve degenerate doping in β-Ga2O3 with a measured electron concentration ∼2 × 1019 cm−3, mobility 80–65 cm2 V−1 s−1, and resistivity down to 5 mΩ cm in our samples. The concentration of Hf was measured to be 1.3 × 1019 atoms cm−3 using glow discharge mass spectroscopy on doped samples, confirming Hf to be the cause of n-type conductivity (electron concentration ∼2 × 1019 cm−3).
Pequi oil microencapsulation by complex coacervation using gelatin-cashew gum

New functional foods and beverages can be developed using bioactive compounds present in pequi oil. Complex coacervation is an encapsulation method used for preserving bioactive molecules, especially those that are hydrophobic or sensitive to high temperatures. The objective of this work was to produce and characterize pequi oil microparticles using cashew gum/gelatin matrix (CG/GE) through complex coacervation. Gum Arabic (GA) was also studied in comparison with CG. The coacervation process was performed without pequi oil to determine the ideal proportions of the matrix components, followed by the embedding of the oil inthe microparticles for evaluation. Satisfactory microparticles were produced at pH 4.5 in the weight ratios of CG/GE = 2:1 and GA/GE = 1:3. Pequi oil release was greater in acidic pH, especially at pH 2 for the CG/GE matrix. The encapsulation efficiency for CG/GE and GA/GE was 72.53% (±4.80) and 82.77% (±6.09), respectively . The results showed that the CG/GE combination seemed very promising as anencapsulation matrix, especially for food applications involving pH values higher than 3.
Effects of Gender, Effort, and Spatial Visualization Abilities in an Engineering Graphics Class

The objective of this study is to understand the interaction between gender, spatial visualization ability, effort, and course outcomes in an engineering graphics course. Within engineering, spatial visualization ability is essential to many applications, beginning with engineering graphics. Engineering graphics courses are commonly introductory-level classes in engineering programs, creating challenges for women, who on average score lower on tests of spatial visualization ability. Improved understanding of gender differences in engineering graphics classes could therefore help identify pedagogical areas to support women and increase their retention in engineering programs. Although a gender gap exists in spatial ability and performance in engineering graphics classes, female students still achieve positive course outcomes. We hypothesize that: 1) female students put more effort into engineering graphics courses; and 2) that this greater effort (measured as time spent on homework, homework scores, quiz scores and attendance) by female students reduces the gender gap in course and exam grades. By analyzing scores on homework, quizzes, exams, and attendance in addition to total course score, we can better assess differences between students and quantify the relative importance of different factors like effort and ability on student performance. We present data from three semesters of a freshman-level engineering graphics course at a large research university and analyze differences in spatial visualization ability and course outcomes of male students (n=232) and female students (n=76). Female students scored lower on spatial visualization tests and course exams but had higher performance in less time-restricted, effortrelated outcomes, such as attendance and homework scores, compared to male students. However, on average, female students had lower overall course grades. After accounting for the spatial ability gender gap by comparing students in groups of similar visualization ability, we found that female students with high spatial visualization abilities tended to have better performance on less time-restricted, effort-related outcomes and took more time on homework, but still had lower exam and course scores than their male counterparts. It appears that the gender gap in performance may not be explained fully by spatial visualization, but could be related to gender differences in testing. Better understanding of the differences between male and female students of similar visualization ability could help educators identify opportunities to leverage these differences in developing pedagogical strategies to support women in introductory engineering graphics courses and further engineering pursuits.
Reconfigurable Intelligent Surface-Assisted Space Shift Keying

The concept of reconfigurable intelligent surface (RIS)-assisted transmission, where phases of reflected signals are adjusted in an effective arrangement, has been recently put forward as a promising solution for 6G and beyond networks. Considering this and the undeniable potential of index modulation (IM) techniques, an RIS-based space shift keying (SSK) scheme is proposed in this letter to maintain all inherent advantages of both RISs and SSK. Specifically, a mathematical framework is presented by using a maximum likelihood (ML) detector for the calculation of the average bit error rate (ABER). Extensive computer simulation results are provided to assess the potential of the proposed RIS-based SSK system and to verify the theoretical derivations. The obtained results indicate that the proposed scheme enables highly reliable transmission with unconventionally high energy efficiency, however with the added cost of increased receiver complexity.