Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of L-methionine on growth performance, carcass quality, feather traits, and small intestinal morphology of Pekin ducks compared with conventional DL-methionine

The research studied the effects ofl-methionine (l-Met) on growth performance, carcass quality, feather traits, and small intestinal morphology of Pekin ducks compared with conventionaldl-methionine (dl-Met). A total of 1080, 1-day-old male Pekin ducks were randomly allotted to 9 groups with 6 replicate pens of 20 birds each. During the starter phase (1 to 14 d), ducks were fed a basal diet (Met, 0.30%) or that supplemented with dl-Met or l-Met at 0.05, 0.10, 0.15, or 0.20% of feed. During the grower phase (15 to 35 d), ducks were fed a basal diet (Met, 0.24%) or that supplemented with dl- Met or l-Met at 0.04, 0.08, 0.12, or 0.16% of feed. Compared with ducks fed the basal diet, supplementation with either dl- Met or l-Met increased the body weight (BW) of ducks at days 14 and 35, increased average daily gain (ADG) and average daily feed intake (ADFI), decreased F:G at the starter phase, and increased ADG over the whole 35-d period (P < 0.05). The efficacy of l-Met compared to dl- Met was 140.1% for 14-d BW, 137.6% for ADG and 121.0% for F:G for days 1 to 14. Ducks fed diets supplemented with l-Met had greater proportion of leg muscle, higher than in ducks provided with dl- Met (P < 0.05). The breast muscle proportion was enhanced with dl- Met rather than l- Met supplementation (P < 0.01). The back feathers score and fourth primary wing feather length were increased with dl- Met or l-Met supplementation (P < 0.01), and there was increased efficacy of l-Met relative to dl- Met for back feathers score (153.1%). Dietary dl- Met or l- Met supplementation increased villus height of ileal mucosa of ducks at days 14 and 35 (P < 0.01). Overall, dietary l-Met or dl- Met supplementation affected the growth performance of ducks during the starter phase, and improved the feather traits and small intestinal morphology. The efficacy of l-Met to dl- Met ranged from 120 to 140% for growth performance of young ducks (1 to 14 d) and was 153% for the feather traits of ducks (35 d).
The Physiology of Intrapartum Fetal Compromise at Term.

Uterine contractions in labor result in a 60% reduction in uteroplacental perfusion, causing transient fetal and placental hypoxia. A healthy term fetus with a normally developed placenta is able to accommodate this transient hypoxia by activation of the peripheral chemoreflex, resulting in a reduction in oxygen consumption and a centralisation of oxygenated blood to critical organs, namely the heart, brain and adrenals. Providing there is adequate time for placental and fetal re-perfusion between contractions, these fetuses will be able to withstand prolonged periods of intermittent hypoxia and avoid severe hypoxic injury. However, there exists a cohort of fetuses where abnormal placental development in the first half of pregnancy results in failure of endovascular invasion of the spiral arteries by the cytotrophoblastic cells and inadequate placental angiogenesis. This produces a high-resistance, low flow circulation predisposing to hypo-perfusion, hypoxia, re-perfusion injury and oxidative stress within the placenta. Furthermore, this renders the placenta susceptible to fluctuations and reduction in uteroplacental perfusion in response to external compression and stimuli (as occurs in labor), further reducing fetal capillary perfusion, placing the fetus at risk of inadequate gas/nutrient exchange. This placental dysfunction predisposes the fetus to intrapartum fetal compromise. In the absence of a rare catastrophic event, intrapartum fetal compromise occurs as a gradual process when there is an inability of the fetal heart to respond to the peripheral chemoreflex to maintain cardiac output. This may arise as a consequence of placental dysfunction reducing pre-labor myocardial glycogen stores necessary for anaerobic metabolism or due to an inadequate placental perfusion between contractions to restore fetal oxygen and nutrient exchange. If the hypoxic insult is severe enough and long enough, profound multi-organ injury and even death may occur. This review provides a detailed synopsis of the events that can result in placental dysfunction, how this may predispose to intrapartum fetal hypoxia and what protective mechanisms are in place to avoid hypoxic injury.
Facial image registration

Face alignment is an important step in a typical automatic face recognition system.This thesis addresses the alignment of faces for face recognition applicationin video surveillance context. The main challenging factors of this research includethe low quality of images (e.g., low resolution, motion blur, and noise), uncontrolledillumination conditions, pose variations, expression changes, and occlusions. In orderto deal with these problems, we propose several face alignment methods using differentstrategies. The _rst part of our work is a three-stage method for facial pointlocalization which can be used for correcting mis-alignment errors. While existingalgorithms mostly rely on a priori knowledge of facial structure and on a trainingphase, our approach works in an online mode without requirements of pre-de_nedconstraints on feature distributions. The proposed method works well on images underexpression and lighting variations. The key contributions of this thesis are aboutjoint image alignment algorithms where a set of images is simultaneously alignedwithout a biased template selection. We respectively propose two unsupervised jointalignment algorithms : \Lucas-Kanade entropy congealing" (LKC) and \gradient correlationcongealing" (GCC). In LKC, an image ensemble is aligned by minimizing asum-of-entropy function de_ned over all images. GCC uses gradient correlation coef-_cient as similarity measure. The proposed algorithms perform well on images underdi_erent conditions. To further improve the robustness to mis-alignments and thecomputational speed, we apply a multi-resolution framework to joint face alignmentalgorithms. Moreover, our work is not limited in the face alignment stage. Since facealignment and face acquisition are interrelated, we develop an adaptive appearanceface tracking method with alignment feedbacks. This closed-loop framework showsits robustness to large variations in target's state, and it signi_cantly decreases themis-alignment errors in tracked faces.
Clinical Predictors of Laryngeal Preservation Rate in Stage III-IV Laryngeal Cancer and Hypopharyngeal Cancer Patients Treated with Organ Preservation

Purpose: To determine factors affecting laryngeal preservation rate in laryngeal and hypopharyngeal cancer patients treated with organ preservation. Material and Methods: Retrospective study examining stage III to IV laryngeal and hypopharyngeal cancer patients who have been treated with organ preservation. Conventional radiation must be applied in all patients with minimum dose of 45 Gray. Weekly or triweekly chemotherapy can be adding during radiation. Salvage surgery should be considered in residual disease or local recurrence. Kaplan-Meier was used for survival analysis and, Log rank test and Cox proportional hazard test were used for uni and multivariate analysis. Results: From January 2010 to October 2014, there were 69 patients treated with laryngeal preservation and 53 patients received radiation dose 61-70 Gray. After completing radiation, we found that 44 patients have no residual tumor within 6 months and 33 patients can preserve their functional larynx later with complete response (median follow up 6 mo, range 0-46.3 mo). The 1-year, 2-year and 3-year laryngeal preservation rate was 49%, 36 % and 32 % respectively. On univariate analysis, lower nodal stage (p = 0.008), stage III disease (p = 0.046), tumor volume <10 ml (p = 0.005), no true vocal cord involvement (p = 0.016), dose 61-70 Gray (p < 0.001) and no interruption of treatment (p = 0.017) have better laryngeal preservation rates. ECOG performance status 2, higher nodal stage, stage IV, presence of true vocal cord involvement, upper airway obstruction before/during radiation and radiation dose below 61-70 Gray had an effect on worse overall survival when evaluated with univariate analysis statistical significance. Conclusion: For factors that affected laryngeal preservation in our study were nodal stage, group stage, tumor volume, true vocal cord involvement, radiation dose and treatment break time more than one week with statistical significance.
Fog Computing Applications: Taxonomy and Requirements

Fog computing was designed to support the specific needs of latency-critical applications such as augmented reality, and IoT applications which produce massive volumes of data that are impractical to send to faraway cloud data centers for analysis. However this also created new opportunities for a wider range of applications which in turn impose their own requirements on future fog computing platforms. This article presents a study of a representative set of 30 fog computing applications and the requirements that a general-purpose fog computing platform should support.
Broadband spectroscopy of astrophysical ice analogues

Context. Reliable, directly measured optical properties of astrophysical ice analogues in the infrared and terahertz (THz) range are missing from the literature. These parameters are of great importance to model the dust continuum radiative transfer in dense and cold regions, where thick ice mantles are present, and are necessary for the interpretation of future observations planned in the far-infrared region. Aims. Coherent THz radiation allows for direct measurement of the complex dielectric function (refractive index) of astrophysically relevant ice species in the THz range. Methods. We recorded the time-domain waveforms and the frequency-domain spectra of reference samples of CO ice, deposited at a temperature of 28.5 K and annealed to 33 K at different thicknesses. We developed a new algorithm to reconstruct the real and imaginary parts of the refractive index from the time-domain THz data. Results. The complex refractive index in the wavelength range 1 mm–150 μm (0.3–2.0 THz) was determined for the studied ice samples, and this index was compared with available data found in the literature. Conclusions. The developed algorithm of reconstructing the real and imaginary parts of the refractive index from the time-domain THz data enables us, for the first time, to determine the optical properties of astrophysical ice analogues without using the Kramers–Kronig relations. The obtained data provide a benchmark to interpret the observational data from current ground-based facilities as well as future space telescope missions, and we used these data to estimate the opacities of the dust grains in presence of CO ice mantles.
Sequential Learning of Active Subspaces

ABSTRACT In recent years, active subspace methods (ASMs) have become a popular means of performing subspace sensitivity analysis on black-box functions. Naively applied, however, ASMs require gradient evaluations of the target function. In the event of noisy, expensive, or stochastic simulators, evaluating gradients via finite differencing may be infeasible. In such cases, often a surrogate model is employed, on which finite differencing is performed. When the surrogate model is a Gaussian process (GP), we show that the ASM estimator is available in closed form, rendering the finite-difference approximation unnecessary. We use our closed-form solution to develop acquisition functions focused on sequential learning tailored to sensitivity analysis on top of ASMs. We also show that the traditional ASM estimator may be viewed as a method of moments estimator for a certain class of GPs. We demonstrate how uncertainty on GP hyperparameters may be propagated to uncertainty on the sensitivity analysis, allowing model-based confidence intervals on the active subspace. Our methodological developments are illustrated on several examples. Supplementary files for this article are available online.
Notes on Computational Hardness of Hypothesis Testing: Predictions using the Low-Degree Likelihood Ratio

These notes survey and explore an emerging method, which we call the low-degree method, for predicting and understanding statistical-versus-computational tradeoffs in high-dimensional inference problems. In short, the method posits that a certain quantity -- the second moment of the low-degree likelihood ratio -- gives insight into how much computational time is required to solve a given hypothesis testing problem, which can in turn be used to predict the computational hardness of a variety of statistical inference tasks. While this method originated in the study of the sum-of-squares (SoS) hierarchy of convex programs, we present a self-contained introduction that does not require knowledge of SoS. In addition to showing how to carry out predictions using the method, we include a discussion investigating both rigorous and conjectural consequences of these predictions. These notes include some new results, simplified proofs, and refined conjectures. For instance, we point out a formal connection between spectral methods and the low-degree likelihood ratio, and we give a sharp low-degree lower bound against subexponential-time algorithms for tensor PCA.
Time Reversal Symmetry Breaking in the Fe-Chalcogenide Superconductors

The interplay of topology and superconductivity has been studied in the FeTe1-xSex family of Fe-based superconductors using high resolution laser-based photoemission. At the superconducting transition a gap is observed to open at the Dirac point in a topological surface state. The associated mass acquisition points to time reversal symmetry breaking associated with the formation of ferromagnetism in the surface layer. Such a coupling of two phases, triplet and singlet spin states, has previously been predicted in 2D superconductors, as at a surface, in the presence of spin-orbit coupling. The presence of intrinsic ferromagnetism combined with strong spin-orbit coupling provides an ideal platform for the Quantum Anomalous Hall effect.
A Novel Approach for Robust Multi Human Action Detection and Recognition based on 3-Dimentional Convolutional Neural Networks

In recent years, various attempts have been proposed to explore the use of spatial and temporal information for human action recognition using convolutional neural networks (CNNs). However, only a small number of methods are available for the recognition of many human actions performed by more than one person in the same surveillance video. This paper proposes a novel technique for multiple human action recognition using a new architecture based on 3Dimdenisional deep learning with application to video surveillance systems. The first stage of the model uses a new representation of the data by extracting the sequence of each person acting in the scene. An analysis of each sequence to detect the corresponding actions is also proposed. KTH, Weizmann and UCF-ARG datasets were used for training, new datasets were also constructed which include a number of persons having multiple actions were used for testing the proposed algorithm. The results of this work revealed that the proposed method provides more accurate multi human action recognition achieving 98%. Other videos were used for the evaluation including datasets (UCF101, Hollywood2, HDMB51, and YouTube) without any preprocessing and the results obtained suggest that our proposed method clearly improves the performances when compared to state-of-the-art methods.
Combinatorial protein–protein interactions on a polymerizing scaffold

Significance Scaffold proteins play an important role in the control and evolution of cellular signaling processes by brokering interactions among docking proteins. In recent years it has become apparent that many scaffolds can form oligomers. We explore theoretically the combinatorial impact of scaffold polymerization on promoting interactions. It is well known that increasing scaffold abundance first expands opportunities for ligand interaction but then collapses them as ligands become separated on different scaffold instances. The polymerizing system stands out by significantly heightening interaction possibilities in the promoting phase and considerably mitigating their collapse. While the qualitative behavior of the system is robust, parameter changes—achievable through the very processes the system mediates—can considerably sculpt its quantitative behavior. Scaffold proteins organize cellular processes by bringing signaling molecules into interaction, sometimes by forming large signalosomes. Several of these scaffolds are known to polymerize. Their assemblies should therefore not be understood as stoichiometric aggregates, but as combinatorial ensembles. We analyze the combinatorial interaction of ligands loaded on polymeric scaffolds, in both a continuum and discrete setting, and compare it with multivalent scaffolds with fixed number of binding sites. The quantity of interest is the abundance of ligand interaction possibilities—the catalytic potential Q—in a configurational mixture. Upon increasing scaffold abundance, scaffolding systems are known to first increase opportunities for ligand interaction and then to shut them down as ligands become isolated on distinct scaffolds. The polymerizing system stands out in that the dependency of Q on protomer concentration switches from being dominated by a first order to a second order term within a range determined by the polymerization affinity. This behavior boosts Q beyond that of any multivalent scaffold system. In addition, the subsequent drop-off is considerably mitigated in that Q decreases with half the power in protomer concentration than for any multivalent scaffold. We explain this behavior in terms of how the concentration profile of the polymer-length distribution adjusts to changes in protomer concentration and affinity. The discrete case turns out to be similar, but the behavior can be exaggerated at small protomer numbers because of a maximal polymer size, analogous to finite-size effects in bond percolation on a lattice.
Local Stabilization of an Unstable Parabolic Equation via Saturated Controls

We derive a saturated feedback control, which locally stabilizes a linear reaction-diffusion equation. In contrast to most other works on this topic, we do not assume the Lyapunov stability of the uncontrolled system and consider general unstable systems. Using Lyapunov methods, we provide estimates for the region of attraction for the closed-loop system, given in terms of linear and bilinear matrix inequalities. We show that our results can be used with distributed as well as scalar boundary control, and with different types of saturations. The efficiency of the proposed method is demonstrated by means of numerical simulations.
Inertial migration of bidisperse suspensions flowing in microchannels: effect of particle diameters ratio

Up to date, inertial migration of particles in microflows has demonstrated a great potential for a wide range of applications. In particular, this phenomenon is used to achieve particle separation or sorting in a suspension. Recent works reported that the focusing mode of particles can be modified in a polydisperse suspension. Nevertheless, the impact of the particle sizes in a mixture on their inertial migration has been rarely studied up to now. Thus, we have investigated in this work the influence of bidispersity on the lateral migration of the particles towards equilibrium positions and on their longitudinal ordering into trains. Different changes in the particles behavior were observed when the ratio between the particle sizes (dp1/dp2) varied from 1.64 to 4.58.
Two-hidden-layer Feedforward Neural Networks are Universal Approximators: A Constructive Approach

It is well known that Artificial Neural Networks are universal approximators. The classical result proves that, given a continuous function on a compact set on an n-dimensional space, then there exists a one-hidden-layer feedforward network which approximates the function. Such result proves the existence, but it does not provide a method for finding it. In this paper, a constructive approach to the proof of this property is given for the case of two-hidden-layer feedforward networks. This approach is based on an approximation of continuous functions by simplicial maps. Once a triangulation of the space is given, a concrete architecture and set of weights can be obtained. The quality of the approximation depends on the refinement of the covering of the space by simplicial complexes.
Achievable multiplicity partitions in the inverse eigenvalue problem of a graph

Abstract Associated to a graph G is a set 𝒮(G) of all real-valued symmetric matrices whose off-diagonal entries are nonzero precisely when the corresponding vertices of the graph are adjacent, and the diagonal entries are free to be chosen. If G has n vertices, then the multiplicities of the eigenvalues of any matrix in 𝒮 (G) partition n; this is called a multiplicity partition. We study graphs for which a multiplicity partition with only two integers is possible. The graphs G for which there is a matrix in 𝒮 (G) with partitions [n − 2, 2] have been characterized. We find families of graphs G for which there is a matrix in 𝒮 (G) with multiplicity partition [n − k, k] for k ≥ 2. We focus on generalizations of the complete multipartite graphs. We provide some methods to construct families of graphs with given multiplicity partitions starting from smaller such graphs. We also give constructions for graphs with matrix in 𝒮 (G) with multiplicity partition [n − k, k] to show the complexities of characterizing these graphs.