Miracle-dz/UniFAR-FTUs huggingface dataset:
A spectral survey of an ultra-hot Jupiter

Context. KELT-9 b exemplifies a newly emerging class of short-period gaseous exoplanets that tend to orbit hot, early type stars – termed ultra-hot Jupiters. The severe stellar irradiation heats their atmospheres to temperatures of ~4000 K, similar to temperatures of photospheres of dwarf stars. Due to the absence of aerosols and complex molecular chemistry at such temperatures, these planets offer the potential of detailed chemical characterization through transit and day-side spectroscopy. Detailed studies of their chemical inventories may provide crucial constraints on their formation process(es) and evolution history. Aims. We aim to search the optical transmission spectrum of KELT-9 b for absorption lines by metals using the cross-correlation technique. Methods. We analysed two transit observations obtained with the HARPS-N spectrograph. We used an isothermal equilibrium chemistry model to predict the transmission spectrum for each of the neutral and singly ionized atoms with atomic numbers between three and 78. Of these, we identified the elements that are expected to have spectral lines in the visible wavelength range and used those as cross-correlation templates. Results. We detect (>5σ) absorption by Na I, Cr II, Sc II and Y II, and confirm previous detections of Mg I, Fe I, Fe II, and Ti II. In addition, we find evidence of Ca I, Cr I, Co I, and Sr II that will require further observations to verify. The detected absorption lines are significantly deeper than predicted by our model, suggesting that the material is transported to higher altitudes where the density is enhanced compared to a hydrostatic profile, and that the material is part of an extended or outflowing envelope. There appears to be no significant blue-shift of the absorption spectrum due to a net day-to-night side wind. In particular, the strong Fe II feature is shifted by 0.18 ± 0.27 km s−1, consistent with zero. Using the orbital velocity of the planet we derive revised masses and radii of the star and the planet: M* = 1.978 ± 0.023 M⊙, R* = 2.178 ± 0.011 R⊙, mp = 2.44 ± 0.70 MJ and Rp = 1.783 ± 0.009 RJ.
Mixing set and bag semantics

The conservativity theorem for nested relational calculus implies that query expressions can freely use nesting and unnesting, yet as long as the query result type is a flat relation, these capabilities do not lead to an increase in expressiveness over flat relational queries. Moreover, Wong showed how such queries can be translated to SQL via a constructive rewriting algorithm. While this result holds for queries over either set or multiset semantics, to the best of our knowledge, the questions of conservativity and ormalization have not been studied for queries that mix set and bag collections, or provide duplicate-elimination operations such as SQL's SELECT DISTINCT. In this paper we formalize the problem, and present partial progress: specifically, we introduce a calculus with both set and multiset collection types, along with natural mappings from sets to bags and vice versa, present a set of valid rewrite rules for normalizing such queries, and give an inductive characterization of a set of queries whose normal forms can be translated to SQL. We also consider examples that do not appear straightforward to translate to SQL, illustrating that the relative expressiveness of flat and nested queries with mixed set and multiset semantics remains an open question.
Representation Learning for Attributed Multiplex Heterogeneous Network

Network embedding (or graph embedding) has been widely used in many real-world applications. However, existing methods mainly focus on networks with single-typed nodes/edges and cannot scale well to handle large networks. Many real-world networks consist of billions of nodes and edges of multiple types, and each node is associated with different attributes. In this paper, we formalize the problem of embedding learning for the Attributed Multiplex Heterogeneous Network and propose a unified framework to address this problem. The framework supports both transductive and inductive learning. We also give the theoretical analysis of the proposed framework, showing its connection with previous works and proving its better expressiveness. We conduct systematical evaluations for the proposed framework on four different genres of challenging datasets: Amazon, YouTube, Twitter, and Alibaba. Experimental results demonstrate that with the learned embeddings from the proposed framework, we can achieve statistically significant improvements (e.g., 5.99-28.23% lift by F1 scores; p<<0.01, t-test) over previous state-of-the-art methods for link prediction. The framework has also been successfully deployed on the recommendation system of a worldwide leading e-commerce company, Alibaba Group. Results of the offline A/B tests on product recommendation further confirm the effectiveness and efficiency of the framework in practice.
Operator approach to complexity: Excited states

We evaluate the complexity of the free scalar field by the operator approach in which the transformation matrix between the second quantization operators of reference state and target state is regarded as the quantum gate. We first examine the system in which the reference state is two non-interacting oscillators with same frequency $\omega_0$ while the target state is two interacting oscillators with frequency $\tilde \omega_1$ and $\tilde \omega_2$. We calculate the geodesic length on the associated group manifold of gate matrix and reproduce the known value of ground-state complexity. Next, we study the complexity in the excited states. Although the gate matrix is very large we can transform it to a diagonal matrix and obtain the associated complexity. We explicitly calculate the complexity in several excited states and prove that the square of geodesic length in the general state $|{\rm n,m}\rangle$ is $D_{\rm (n,m)}^2={\rm (n+1)}\left(\ln {\sqrt{\tilde \omega_1\over \omega_0}}\,\right)^2 +{\rm (m+1)}\left(\ln {\sqrt{\tilde \omega_2\over \omega_0}}\,\right)^2$. The results are extended to the N couple harmonic oscillators which correspond to the lattice version of free scalar field.
Continuous‐time mean–variance portfolio selection: A reinforcement learning framework

We approach the continuous‐time mean–variance portfolio selection with reinforcement learning (RL). The problem is to achieve the best trade‐off between exploration and exploitation, and is formulated as an entropy‐regularized, relaxed stochastic control problem. We prove that the optimal feedback policy for this problem must be Gaussian, with time‐decaying variance. We then prove a policy improvement theorem, based on which we devise an implementable RL algorithm. We find that our algorithm and its variant outperform both traditional and deep neural network based algorithms in our simulation and empirical studies.
Predicting Affect Classification in Mental Status Examination Using Machine Learning Face Action Recognition System: A Pilot Study in Schizophrenia Patients

Classifying patients’ affect is a pivotal part of the mental status examination. However, this common practice is often widely inconsistent between raters. Recent advances in the field of Facial Action Recognition (FAR) have enabled the development of tools that can act to identify facial expressions from videos. In this study, we aimed to explore the potential of using machine learning techniques on FAR features extracted from videotaped semi-structured psychiatric interviews of 25 male schizophrenia inpatients (mean age 41.2 years, STD = 11.4). Five senior psychiatrists rated patients’ affect based on the videos. Then, a novel computer vision algorithm and a machine learning method were used to predict affect classification based on each psychiatrist affect rating. The algorithm is shown to have a significant predictive power for each of the human raters. We also found that the eyes facial area contributed the most to the psychiatrists’ evaluation of the patients’ affect. This study serves as a proof-of-concept for the potential of using the machine learning FAR system as a clinician-supporting tool, in an attempt to improve the consistency and reliability of mental status examination.
DUSP8 Regulates Cardiac Ventricular Remodeling by Altering ERK1/2 Signaling.

RATIONALE Mitogen-activated protein kinase (MAPK) signaling regulates the growth response of the adult myocardium in response to increased cardiac workload or pathological insults. The dual-specificity phosphatases (DUSPs) are critical effectors, which dephosphorylate the MAPKs to control the basal tone, amplitude, and duration of MAPK signaling. OBJECTIVE To examine DUSP8 as a regulator of MAPK signaling in the heart and its impact on ventricular and cardiac myocyte growth dynamics. METHODS AND RESULTS Dusp8 gene-deleted mice and transgenic mice with inducible expression of DUSP8 in the heart were used here to investigate how this MAPK-phosphatase might regulate intracellular signaling and cardiac growth dynamics in vivo. Dusp8 gene-deleted mice were mildly hypercontractile at baseline with a cardiac phenotype of concentric ventricular remodeling, which protected them from progressing towards heart failure in 2 surgery-induced disease models. Cardiac-specific overexpression of DUSP8 produced spontaneous eccentric remodeling and ventricular dilation with heart failure. At the cellular level, adult cardiac myocytes from Dusp8 gene-deleted mice were thicker and shorter, whereas DUSP8 overexpression promoted cardiac myocyte lengthening with a loss of thickness. Mechanistically, activation of extracellular signal-regulated kinases 1/2 were selectively increased in Dusp8 gene-deleted hearts at baseline and following acute pathological stress stimulation, whereas p38 MAPK and c-Jun N-terminal kinases were mostly unaffected. CONCLUSIONS These results indicate that DUSP8 controls basal and acute stress-induced extracellular signal-regulated kinases 1/2 signaling in adult cardiac myocytes that then alters the length-width growth dynamics of individual cardiac myocytes, which further alters contractility, ventricular remodeling, and disease susceptibility.
Enrichment of omega-3 fatty acids in suckling pigs by maternal dietary fish oil supplementation.

This study was designed to determine whether substituting menhaden fish oil (FO) for lard (LA) in a practical sow diet was a suitable method for enriching newborn pigs with omega-3 polyunsaturated fatty acids (n-3 PUFA). On d 107 of gestation, 18 crossbred sows were randomly allotted to one of three experimental diets, in which FO was substituted for LA at 0, 3.5, and 7% of the diet. On d 1, 7, 14, and 21 after farrowing samples of milk and serum from the sows and pig serum were collected for fatty acid analysis. The content of n-3 PUFA in the serum of sows fed FO increased six-fold over that in serum of LA-fed sows P < . 0001). Feeding FO decreased the levels of arachidonic acid in maternal serum by approximately 50% (P < .0001). Similar changes were reflected in the fatty acid profiles of sow's milk. Pig serum n-3 PUFA levels were elevated over 5- and 10-fold within 24 h of birth in those litters born to sows fed 3.5 and 7% fish oil, respectively. Eicosapentaenoic acid levels in pig serum increased linearly (P < .01) during the first 2 wk postnatally in pigs suckling FO-feds sows and accounted for as much as 12% of the total fatty acids present on d 21. In conclusion, we have demonstrated that feeding FO to sows during late gestation and lactation enriches the newborn pig with n-3 PUFA.
Noise-induced synchronization and anti-resonance in excitable systems; Implications for information processing in Parkinson's Disease and Deep Brain Stimulation.

We study the statistical physics of a surprising phenomenon arising in large networks of excitable elements in response to noise: while at low noise, solutions remain in the vicinity of the resting state and large-noise solutions show asynchronous activity, the network displays orderly, perfectly synchronized periodic responses at intermediate level of noise. We show that this phenomenon is fundamentally stochastic and collective in nature. Indeed, for noise and coupling within specific ranges, an asymmetry in the transition rates between a resting and an excited regime progressively builds up, leading to an increase in the fraction of excited neurons eventually triggering a chain reaction associated with a macroscopic synchronized excursion and a collective return to rest where this process starts afresh, thus yielding the observed periodic synchronized oscillations. We further uncover a novel anti-resonance phenomenon: noise-induced synchronized oscillations disappear when the system is driven by periodic stimulation with frequency within a specific range. In that anti-resonance regime, the system is optimal for measures of information capacity. This observation provides a new hypothesis accounting for the efficiency of Deep Brain Stimulation therapies in Parkinson's disease, a neurodegenerative disease characterized by an increased synchronization of brain motor circuits. We further discuss the universality of these phenomena in the class of stochastic networks of excitable elements with confining coupling, and illustrate this universality by analyzing various classical models of neuronal networks. Altogether, these results uncover some universal mechanisms supporting a regularizing impact of noise in excitable systems, reveal a novel anti-resonance phenomenon in these systems, and propose a new hypothesis for the efficiency of high-frequency stimulation in Parkinson's disease.
Patients’, Carers’, and the Public’s Perspectives on Electroconvulsive Therapy

Aims and Method: The aim of this study was to present patients’, carers’, and the public’s perspectives on electroconvulsive therapy (ECT) through a narrative review of the literature. Results: People’s perspectives on ECT are often negative due to media and Internet portrayal. Perspectives are influenced by risks, short-term side effects, and the most commonly reported longer-term side effect: memory loss. However, many patients do not report memory loss. Most people who experience ECT and their carers report a positive perspective. In the future, people’s perspectives may become more positive with higher service delivery standards and a more balanced, well-informed view of modern ECT presented by the media. However, ECT has risks and side effects, and negative and critical perspectives on the use and effects of ECT will persist. Clinical Implications: Perspectives on ECT are important because of the impact on stigma, patient treatment choice, patient consent, and provision of and referral for ECT.
Expected Density of Cooperative Bacteria in a 2D Quorum Sensing Based Molecular Communication System

The exchange of small molecular signals within microbial populations is generally referred to as quorum sensing (QS). QS is ubiquitous in nature and enables microorganisms to respond to fluctuations in living environments by working together. In this study, a QS- based molecular communication system within a microbial population in a two-dimensional (2D) environment is analytically modeled. Microorganisms are randomly distributed on a 2D circle where each one releases molecules at random times. The number of molecules observed at each randomly-distributed bacterium is first derived by characterizing the diffusion and degradation of molecules within the population. Using the derived result and some approximation, the expected density of cooperative bacteria is derived. Our model captures the basic features of QS. The analytical results for noisy signal propagation agree with simulation results where the Brownian motion of molecules is simulated by a particle- based method. Therefore, we anticipate that our model can be used to predict the density of cooperators in a variety of QS-coordinated activities, e.g., biofilm formation and antibiotic resistance.
Spectral density estimation using P-spline priors

This article proposes a Bayesian approach to estimating the spectral density of a stationary time series using a prior based on a mixture of P-spline distributions. Our proposal is motivated by the B-spline Dirichlet process prior of Edwards et al. (2018a) in combination with Whittle's likelihood and aims at reducing the high computational complexity of its posterior computations. The strength of the B-spline Dirichlet process prior over the Bernstein-Dirichlet process prior of Choudhuri et al. (2004) lies in its ability to estimate spectral densities with sharp peaks and abrupt changes due to the flexibility of B-splines with variable number and location of knots. Here, we suggest to use P-splines of Eilers and Marx (1996) that combine a B-spline basis with a discrete penalty on the basis coefficients. We demonstrate in a simulation study and two real case studies that this approach retains the flexibility of the B-splines, achieves the same ability to accurately estimate peaks due to a new data-driven knot allocation scheme but significantly reduces the computational costs.
Fine-grained Access Control and Revocation for Sharing Data on Clouds

With the current rapid increase of cloud computing, enterprises outsource their sensitive data for sharing in a cloud. The key problems of this approach include establishing access control for the encrypted data, and revoking the access rights from users when they are no longer authorized to access the encrypted data on cloud servers. This paper aims to solve these problems. Firstly, based on the attribute encryption and the dual encryption system, we propose a concrete access control scheme constructed over the composite order bilinear groups, and we prove its security under the standard model. Then, we propose a fully fine-grained revocation scheme under the direct revocation model, so as to efficiently revoke access rights from users on cloud servers.
IVO: Inverse Velocity Obstacles for Real Time Navigation

In this paper, we present IVO: Inverse Velocity Obstacles an egocentric framework that improves the real time implementation. The proposed method stems from the concept of velocity obstacle and can be applied for both single agent and multi-agent system. It focuses on computing collision free maneuvers without any knowledge or assumption on the pose and the velocity of the robot. This is primarily achieved by reformulating the velocity obstacle to adapt to an ego-centric framework. This is a significant step towards improving real time implementations of collision avoidance in dynamic environments as there is no dependency on state estimation techniques to infer the robot pose and velocity. We evaluate IVO for both single agent and multi-agent in different scenarios and show it's efficacy over the existing formulations. We also show the real time scalability of the proposed methodology.
Atorvastatin attenuates sympathetic hyperinnervation together with the augmentation of M2 macrophages in rats postmyocardial infarction.

OBJECTIVES Inflammation after myocardial infarction (MI) causes cardiac nerve sprouting and consequent ventricular arrhythmias (VAs). Macrophages, as major immune cells, are involved in the entire inflammation response process and serve as a link between inflammation and sympathetic hyperinnervation by regulating nerve growth factor (NGF) expression. Accumulating evidence shows that statins possess antiarrhythmogenic properties, and the aim of this study was to explore the mechanism by which atorvastatin ameliorates cardiac sympathetic nerve sprouting via regulating macrophage polarization. METHODS Rat models of MI were created by ligating the left coronary artery. MI-operated rats received either atorvastatin or phosphate-buffered saline for 7 days. Immunohistochemical analyses and immunofluorescence staining were used to analyze macrophage infiltration after MI and to detect the distribution and density of growth-associated protein-43 (GAP-43) and tyrosine hydroxylase (TH) in nerve fibers in peri-infarct zones after MI. The polarity of the macrophages that were obtained from the rat peritoneal cavity was examined via flow cytometry. The protein levels of NGF were detected via Western blot analysis, and the concentrations of NGF in the supernatants were determined via enzyme-linked immunosorbent assay. The mRNA levels of NGF, inducible nitric oxide synthase (iNOS), Arginase-1 (Arg1), interleukin-1β (IL-1β), and tumor necrosis factor-α (TNF-α) were examined by quantitative real-time polymerase chain reaction. The association between VAs and MI was evaluated using programmed electrophysiological stimulation. RESULTS Macrophages were successfully induced to the M1 (classically activated) and M2 (alternatively activated) phenotypes by stimulation with lipopolysaccharide and interferon-γ (LPS + IFN-γ) and interleukin-4 (IL-4), respectively. Atorvastatin markedly downregulated IL-1β, TNF-α, iNOS, and NGF and upregulated Arg1, shifting the macrophage phenotype from M1 to M2. Moreover, atorvastatin significantly reduced TH levels and the density of GAP-43-positive nerve fibers and decreased inducible VAs. CONCLUSION Atorvastatin effectively ameliorated cardiac sympathetic nerve remodeling and prevented VAs after MI by significantly downregulating the expression of NGF, IL-1β, and TNF-α via together with the augmentation of M2 macrophage.
Early Intervention in Low Birth Weight Premature Infants: Results at 18 Years of Age for the Infant Health and Development Program

OBJECTIVE. To assess whether improvements in cognitive and behavioral development seen in preschool educational programs persist, we compared those in a multisite randomized trial of such a program over the first 3 years of life (INT) to those with follow-up only (FUO) at 18 months of age. METHODS. This was a prospective follow-up of the Infant Health and Development Program at 8 sites heterogeneous for sociodemographic characteristics. Originally 985 children were randomized to the INT (n = 377) or FUO (n = 608) groups within 2 birth weight strata: heavier low birth weight (HLBW; 2001–2499 g) and lighter low birth weight (LLBW; ≤2000 g). Primary outcome measures were the Peabody Picture Vocabulary Test (PPVT-III), reading and mathematics subscales of the Woodcock-Johnson Tests of Achievement, youth self-report on the Total Behavior Problem Index, and high-risk behaviors on the Youth Risk Behavior Surveillance System (YRBSS). Secondary outcomes included Weschler full-scale IQ, caregiver report on the Total Behavior Problem Index, and caregiver and youth self-reported physical health using the Medical Outcome Study measure. Assessors were masked as to study status. RESULTS. We assessed 636 youths at 18 years (64.6% of the 985, 72% of whom had not died or refused at prior assessments). After adjusting for cohort attrition, differences favoring the INT group were seen on the Woodcock-Johnson Tests of Achievement in math (5.1 points), YRBSS (−0.7 points), and the PPVT-III (3.8 points) in the HLBW youth. In the LLBW youth, the Woodcock-Johnson Tests of Achievement in reading was higher in the FUO than INT group (4.2). CONCLUSIONS. The findings in the HLBW INT group provide support for preschool education to make long-term changes in a diverse group of children who are at developmental risk. The lack of observable benefit in the LLBW group raises questions about the biological and educational factors that foster or inhibit sustained effects of early educational intervention.