Miracle-dz/UniFAR-FTUs huggingface dataset:
Tree convolution for probability distributions
with unbounded support

We develop the complex-analytic viewpoint on the tree convolutions studied by the second author and Weihua Liu in"An operad of non-commutative independences defined by trees"(Dissertationes Mathematicae, 2020, doi:10.4064/dm797-6-2020), which generalize the free, boolean, monotone, and orthogonal convolutions. In particular, for each rooted subtree $\mathcal{T}$ of the $N$-regular tree (with vertices labeled by alternating strings), we define the convolution $\boxplus_{\mathcal{T}}(\mu_1,\dots,\mu_N)$ for arbitrary probability measures $\mu_1$, . , $\mu_N$ on $\mathbb{R}$ using a certain fixed-point equation for the Cauchy transforms. The convolution operations respect the operad structure of the tree operad from doi:10.4064/dm797-6-2020. We prove a general limit theorem for iterated $\mathcal{T}$-free convolution similar to Bercovici and Pata's results in the free case in"Stable laws and domains of attraction in free probability"(Annals of Mathematics, 1999, doi:10.2307/121080), and we deduce limit theorems for measures in the domain of attraction of each of the classical stable laws.
Nonuniform Radiation Modeling of a Corrugated Plate Photocatalytic Reactor

Corrugated plate photocatalytic reactors provide a promising photoreactor design due to its potential in enhancing energy efficiency. A detailed model of such reactors is needed for engineering applications and process design. The model for the light absorption in a corrugated plate reactor using a nonuniform radiation source is developed based on first principles. The local area-specific rate of energy absorption (LASREA) distribution on the corrugated plates is examined via simulation. The effect of the design parameters on LASREA is investigated. The results from this research provide feasible basis for design and optimization of corrugated plate photoreactors. © 2005 American Institute of Chemical Engineers AIChE J, 2005
Keep the Gradients Flowing: Using Gradient Flow to Study Sparse Network Optimization

Training sparse networks to converge to the same performance as dense neural architectures has proven to be elusive. Recent work suggests that initialization is the key. However, while this direction of research has had some success, focusing on initialization alone appears to be inadequate. In this paper, we take a broader view of training sparse networks and consider the role of regularization, optimization, and architecture choices on sparse models. We propose a simple experimental framework, Same Capacity Sparse vs Dense Comparison (SC-SDC), that allows for a fair comparison of sparse and dense networks. Furthermore, we propose a new measure of gradient flow, Effective Gradient Flow (EGF), that better correlates to performance in sparse networks. Using top-line metrics, SC-SDC and EGF, we show that default choices of optimizers, activation functions and regularizers used for dense networks can disadvantage sparse networks. Based upon these findings, we show that gradient flow in sparse networks can be improved by reconsidering aspects of the architecture design and the training regime. Our work suggests that initialization is only one piece of the puzzle and taking a wider view of tailoring optimization to sparse networks yields promising results.
Aura-Net: Robust Segmentation Of Phase-Contrast Microscopy Images with Few Annotations

We present AURA-net, a convolutional neural network (CNN) for the segmentation of phase-contrast microscopy images. AURA-net uses transfer learning to accelerate training and Attention mechanisms to help the network focus on relevant image features. In this way, it can be trained efficiently with a very limited amount of annotations. Our network can thus be used to automate the segmentation of datasets that are generally considered too small for deep learning techniques. AURA-net also uses a loss inspired by active contours that is well-adapted to the specificity of phase-contrast images, further improving performance. We show that AURA-net outperforms state-of-the-art alternatives in several small (less than 100 images) datasets.
Identification over the Gaussian Channel in the Presence of Feedback

We analyze message identification via Gaussian channels with noiseless feedback, which is part of the Post Shannon theory. The consideration of communication systems beyond Shannon's approach is useful in order to increase the efficiency of information transmission for certain applications. If the noise variance is positive, we propose a coding scheme that generates infinite common randomness between the sender and the receiver. We show that any identification rate via the Gaussian channel with noiseless feedback can be achieved. The remarkable result is that this applies to both rate definitions $\frac{1}{n}\log M$ (as defined by Shannon for transmission) and $\frac{1}{n}\ \log \log\ M$ — (as defined by Ahlswede and Dueck for identification). We can even show that our result holds regardless of the selected scaling for the rate. A detailed version with all proofs, explanations and more discussions can be found in [1].
Quantum process inference for a single-qubit Maxwell demon

While quantum measurement theories are built around density matrices and observables, the laws of thermodynamics are based on processes such as are used in heat engines and refrigerators. The study of quantum thermodynamics fuses these two distinct paradigms. In this article, we highlight the usage of quantum process matrices as a unified language for describing thermodynamic processes in the quantum regime. We experimentally demonstrate this in the context of a quantum Maxwell’s demon, where two major quantities are commonly investigated; the average work extraction 〈W 〉 and the efficacy γ which measures how efficiently the feedback operation uses the obtained information. Using the tool of quantum process matrices, we develop the optimal feedback protocols for these two quantities and experimentally investigate them in a superconducting circuit QED setup.
Nondegenerate Abnormality, Controllability, and Gap Phenomena in Optimal Control with State Constraints

In optimal control theory, infimum gap means that there is a gap between the infimum values of a given minimum problem and an extended problem, obtained by enlarging the set of original solutions and controls. The gap phenomenon is somewhat"dual"to the problem of the controllability of the original control system to an extended solution. In this paper we present sufficient conditions for the absence of an infimum gap and for controllability for a wide class of optimal control problems subject to endpoint and state constraints. These conditions are based on a nondegenerate version of the nonsmooth constrained maximum principle, expressed in terms of subdifferentials. In particular, under some new constraint qualification conditions, we prove that: (i) if an extended minimizer is a nondegenerate normal extremal, then no gap shows up; (ii) given an extended solution verifying the constraints, either it is a nondegenerate abnormal extremal, or the original system is controllable to it. An application to the impulsive extension of a free end-time, non-convex optimization problem with control-polynomial dynamics illustrates the results.
Subdimensional Expansion for Multi-Objective Multi-Agent Path Finding

Conventional multi-agent path planners typically determine a path that optimizes a single objective, such as path length. Many applications, however, may require multiple objectives, say time-to-completion and fuel use, to be simultaneously optimized in the planning process. Often, these criteria may not be directly compared and sometimes lie in competition with each other. Simply applying standard multi-objective search algorithms to multi-agent path finding may prove to be inefficient because the size of the space of possible solutions, i.e., the Pareto-optimal set, can grow exponentially with the number of agents. This letter presents an approach that bypasses this so-called curse of dimensionality by leveraging our prior multi-agent work with a framework called subdimensional expansion. One example of subdimensional expansion, when applied to A<inline-formula><tex-math notation="LaTeX">$^*$</tex-math></inline-formula>, is called M<inline-formula><tex-math notation="LaTeX">$^*$</tex-math></inline-formula> and M<inline-formula><tex-math notation="LaTeX">$^*$</tex-math></inline-formula> was limited to a single objective function. We combine principles of dominance and subdimensional expansion to create a new algorithm, named multi-objective M<inline-formula><tex-math notation="LaTeX">$^*$</tex-math></inline-formula> (MOM<inline-formula><tex-math notation="LaTeX">$^*$</tex-math></inline-formula>), which dynamically couples agents for planning only when those agents have to “interact” with each other. MOM<inline-formula><tex-math notation="LaTeX">$^*$</tex-math></inline-formula> computes the complete Pareto-optimal set for multiple agents efficiently and naturally trades off sub-optimal approximations of the Pareto-optimal set and computational efficiency. Our approach is able to find the complete Pareto-optimal set for problem instances with hundreds of solutions which the standard multi-objective A<inline-formula><tex-math notation="LaTeX">$^*$</tex-math></inline-formula> algorithms could not find within a bounded time.
Orientation Convolutional Networks for Image Recognition

Deep Convolutional Neural Networks (DCNNs) are capable of obtaining powerful image representations, which have attracted great attentions in image recognition. However, they are limited in modeling orientation transformation by the internal mechanism. In this paper, we develop Orientation Convolution Networks (OCNs) for image recognition based on the proposed Landmark Gabor Filters (LGFs) that the robustness of the learned representation against changed of orientation can be enhanced. By modulating the convolutional filter with LGFs, OCNs can be compatible with any existing deep learning networks. LGFs act as a Gabor filter bank achieved by selecting $ p $ $ \left( \ll n\right) $ representative Gabor filters as andmarks and express the original Gabor filters as sparse linear combinations of these landmarks. Specifically, based on a matrix factorization framework, a flexible integration for the local and the global structure of original Gabor filters by sparsity and low-rank constraints is utilized. With the propogation of the low-rank structure, the corresponding sparsity for representation of original Gabor filter bank can be significantly promoted. Experimental results over several benchmarks demonstrate that our method is less sensitive to the orientation and produce higher performance both in accuracy and cost, compared with the existing state-of-art methods. Besides, our OCNs have few parameters to learn and can significantly reduce the complexity of training network.
Effects of maternal vitamin D3 on quality and water distribution in pork of offspring pigs during frozen storage

Vitamin D3 is an important regulator of adipogenesis, and it is correlated with fat accumulation. It was found that maternal vitamin D3 status influenced adipocyte commitment and differentiation of musculus longissimus dorsi in piglets via changing adipogenic genes expression (Guo et al., 2020a). Meanwhile, maternal vitamin D3 affected intramuscular fat (IMF) content and meat quality of offspring pigs by regulating fatty acid synthesis and hormone sensitive lipase mRNA expression (Guo et al., 2020b). In addition, vitamin D also has important direct effects on skeletal muscle (Abrams et al., 2018), and improving maternal vitamin D3 status can promote prenatal skeletal muscle development in offspring pigs by regulating the expression of muscle transcription factors (Zhou et al., 2016). These results suggested that maternal vitamin D3 concentrations affected meat quality attributes and eating quality of offspring pigs. It was previously found that fat accumulation, especially the suitable amount of IMF could significantly improve the taste of meat, palatability, juiciness, tenderness, flavour and, finally, the meat quality (Hunt et al., 2014; Bauer et al., 2016). The eating quality of pork is usually affected ABSTRACT. In total, 27 sows (41st day of pregnancy) were divided into three groups: LD, ND and HD, and fed 200, 800 and 3200 IU of vitamin D3/kg basal diet, respectively. All their offspring pigs were fed the same vitamin D3 replete diet. On day 150, 18 offspring (sex balance, 6 offspring per maternal diet group) were weighed and slaughtered to investigate effects of maternal vitamin D3 status on quality and water distribution in pork during frozen storage. It was shown that in longissimus dorsi muscles from all groups L*, b* values, thawing loss, cooking loss, T21 and T22 relaxation times increased with frozen storage (P < 0.05), whereas a* value and shear force decreased with frozen storage (P < 0.05). In addition, in comparison with HD group, meat from LD group had higher L* and b* values, thawing loss, shear force, and T22 relaxation times (P < 0.05). Whereas cooking loss and T21 relaxation times of longissimus dorsi muscles in offspring born in HD group were lower (P < 0.05) than that in those born in ND and LD groups, while a* values of meat from LD group were lower (P < 0.05) than that from ND and HD groups during frozen storage. It was indicated that maternal vitamin D3 status influenced meat colour, thawing loss, cooking loss, shear force and water distribution of longissimus dorsi muscles in offspring, and maternal vitamin D3 supplementation could decrease quality deterioration of muscles, and prolong meat quality during frozen storage. Received: 28 September 2020 Revised: 20 November 2020 Accepted: 9 December 2020
Elevated concentrations of cholesterol and low-density lipoprotein (LDL) in human blood serum due to using milk predominant long chain fatty acids (C14:0-C18:0) causes

Elevated concentrations of cholesterol and low-density lipoprotein (LDL) in human blood serum due to using milk predominant long chain fatty acids (C14:0-C18:0) causes the higher risk of cardio-vascular diseases (Mansbridge et al. 1997). Increasing the ratio of unsaturated to saturated fatty acid along with conjugated linoleic acid (CLA) common and useful isomers (C18:2 cis-9, trans-11 and trans-10, cis-12) in dairy milk fat was well-studied (Aydin, 2005; Troegeler-Meynadier and Enjalbert, 2005). Based on previous studies, CLA had some positive effects such as reduction in body fat deposition, type II diabetes prevalence, atherosclerosis, while improving bone mineralization and immune system along with anti-carcinogenic properties (Belury, 2002). In order to improve unsaturated fatty acid (FA) content of milk fat, some oilseeds were fed to ruminants. Researches indicated high linoleic acid content of safflower seed (Carthamus tinctorius) which can be fed to ruminants (Alizadeh et al. 2010). In an experiment, adding 6% of diet dry matter (DM) safflower oil raised cis-9, trans11 CLA content of milk (Bell et al. 2006). safflower seed have some phenolic glycosides (2-hydroxy-arctiin and matairesinol monoglucoside) as antinutritional factor and it can be altered dry matter intake (DMI) in ruminant (Kim et al. 2006) but Nagatsu (2004) reprted that its amount in safflower is reduced by breeding for improving seed yield. No negative effects were determined on milk production, DMI H. Paya and A. Taghizadeh
Aripiprazole Use in Children and Adolescents

n November 15, 2002, the newest of the atypical antipsychotics, aripiprazole, was approved by the by the Food and Drug Administration (FDA) for the treatment of schizophrenia. It has subsequently been approved for use in the treatment of bipolar mania as well. This agent has been shown to be similar in efficacy to traditional antipsychotics as well as other atypical antipsychotics, but offers an improved adverse effect profile. There is growing interest in the use of aripiprazole in children with schizophrenia, schizoaffective disorder, and conduct disorders.
Use of Discourse Marker ‘so’ in the Malaysian ESL Job Interviews

The discourse marker ‘so’ has been identified as being typically high in spoken discourse, but previous studies have been focusing on its use in the oral production of native speakers. This paper explores the use of ‘so’, concentrating on job interview speech in the Malaysian English as a Second Language (ESL) context. It aims to explicate the multifunctional uses of ‘so’ in a self-developed corpus made up of 16 actual job interviews conducted in English, comprising job interviews in two different organizations in Malaysia. In the corpus, ‘so’ is identified as the tenth most frequent word, which also makes it the most-used discourse marker in the job interview speech. The results suggest that ‘so’ in the corpus serves five main functions, namely 1) to introduce summary; 2) to continue previous speaker’s topic; 3) to mark sequential relations; 4) to hold the floor; and 5) to introduce elaboration to justify a prior statement. Interestingly, when ‘so’ is used in turn-initials, it points to a specific function which is 6) to introduce new information. However, it was also found that the high frequency of ‘so’ in the corpus is associated with ‘pseudo-bridging’ whereby ‘so’ is simply used to 7) add new information and making speech seem coherent. The study implies that the teaching of discourse markers in speech, specifically the use of ‘so’ should focus more on the pragmatic functions than on semantic meanings per se, to avoid the inappropriate or overuse of this particular linguistic element.
Search for Gravitational Waves from the Coalescence of Subsolar Mass and Eccentric Compact Binaries

We present a search for gravitational waves from subsolar mass compact-binary mergers that allows for nonnegligible orbital eccentricity. Subsolar mass black holes are a signature of primordial origin black holes, which may be a component of dark matter. To produce binary coalescences, primordial black holes may form close binaries either in the early universe or more recently through dynamical interactions. A signature of dynamical formation would be the observation of noncircularized orbits. We search for black hole mergers where the primary mass is 0.1–7M ⊙ and the secondary mass is 0.1–1M ⊙. We allow for eccentricity up to ∼0.3 at a dominant-mode gravitational-wave frequency of 10 Hz for binaries with component masses >0.5M ⊙. We find no convincing candidates in the public LIGO data from 2015–2017. The two most promising candidates have a false alarm rate of 1 per 3 and 4 yr, respectively, which combined is only a ∼2. 4σ deviation from the expected Poisson rate. Given the marginal statistical significance, we place upper limits on the rate of subsolar mass mergers under the assumption of a null observation and compare how these limits may inform the possible dark matter contribution.
The effect of Covid-19 on intraregional tourism of Gulf Cooperation Council countries

© 2021 International Journal of Tourism and Hospitality. This is an open access article under the CC BY license (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. Abstract Little information is known about the impact of pandemic/epidemic on a tourist’s choice of destination. To fulfill this gap, Conservation of Resources Theory and Fear Appeal Theory are used. The current study aims to get first-hand information regarding people’s perception of tourism services, perception of susceptibility, perception of travel risk, and self-efficacy on travel following Covid-19 pandemic. Besides, revealing the impacts of visitors’ gender and nationality on all these dimensions. Drawing on a sample of 1,112 valid questionnaires from the Gulf Cooperation Council (GCC) countries, which had a domestic or international travel experience, was utilized to collect the data throughout an online survey. The data were analyzed using factor analyses, mean comparison, standard deviation, Mann-Whitney Test & Kruskal-Wallis Test to check the aim and validity of the study. The findings revealed that Covid-19 pandemic influences GCC potential tourists significantly in many ways. Finally, this paper provided some practical implications for reopening the tourism and hospitality business after the Covid-19.
Reinforcement Learning Based Temporal Logic Control with Soft Constraints Using Limit-deterministic Generalized Büchi Automata

—This paper studies the control synthesis of motion planning subject to uncertainties. The uncertainties are considered in robot motion and environment properties, giving rise to the probabilistic labeled Markov decision process (PL-MDP). A model-free reinforcement learning (RL) is developed to generate a ﬁnite-memory control policy to satisfy high-level tasks expressed in linear temporal logic (LTL) formulas. One of the novelties is to translate LTL into a limit deterministic generalized Büchi automaton (LDGBA) and develop a corresponding embedded LDGBA (E-LDGBA) by incorporating a tracking-frontier function to overcome the issue of sparse accepting rewards, resulting in improved learning performance without increasing computational complexity. Due to potentially conﬂicting tasks, a relaxed product MDP is developed to allow the agent to revise its motion plan without strictly following the desired LTL constraints if the speciﬁed tasks can only be partially fulﬁlled. An expected return composed of violation rewards and accepting rewards is developed. The designed violation function quantiﬁes the differences between the revised and the desired motion planning, while the accepting rewards are proposed to enforce the satisfaction of the acceptance condition of the relaxed product MDP. Rigorous analysis shows that any RL algorithm that optimizes the expected return is guaranteed to ﬁnd policies that, in decreasing order, can 1) satisfy the acceptance condition of relaxed product MDP and 2) reduce the violation cost over long-term behaviors. Also, we validate the control synthesis approach via simulation and experimental results.