Miracle-dz/UniFAR-FTUs huggingface dataset:
Synchronization of Coupled Dynamical Systems: Tolerance to Weak Connectivity and Arbitrarily Bounded Time-Varying Delays

We study synchronization of coupled linear systems over networks with weak connectivity and nonuniform time-varying delays. We focus on the case where the internal dynamics are time-varying but nonexpansive (stable dynamics with a quadratic Lyapunov function). Both uniformly jointly connected and infinitely jointly connected communication topologies are considered. A new concept of quadratic synchronization is introduced. We first show that global asymptotic quadratic synchronization can be achieved over directed networks with uniform joint connectivity and arbitrarily bounded delays. We then study the case of infinitely jointly connected communication topology. In particular, for the undirected communication topologies, it turns out that the existence of a uniform time interval for the jointly connected communication topology is not necessary and quadratic synchronization can be achieved when the time-varying nonuniform delays are arbitrarily bounded. Simulation results are provided to validate the theoretical results.
The genetic component of preeclampsia: A whole-exome sequencing study

Preeclampsia is a major cause of maternal and perinatal deaths. The aetiology of preeclampsia is largely unknown but a polygenetic component is assumed. To explore this hypothesis, we performed an in-depth whole-exome sequencing study in women with (cases, N = 50) and without (controls, N = 50) preeclampsia. The women were identified in an unselected cohort of 2,545 pregnant women based on data from the Danish National Patient Registry and the Medical Birth Registry. Matching DNA was obtained from a biobank containing excess blood from routine antenatal care visits. Novogene performed the whole-exome sequencing blinded to preeclampsia status. Variants for comparison between cases and controls were filtered in the Ingenuity Variant Analysis software. We applied two different strategies; a disease association panel approach, which included variants in single genes associated with established clinical risk factors for preeclampsia, and a gene panel approach, which included biological pathways harbouring genes previously reported to be associated with preeclampsia. Variant variability was compared in cases and controls at the level of biological processes, signalling pathways, and in single genes. Regardless of the applied strategy and the level of variability examined, we consistently found positive correlations between variant numbers in cases and controls (all R2s>0.88). Contrary to what was expected, cases carried fewer variants in biological processes and signalling pathways than controls (all p-values ≤0.02). In conclusion, our findings challenge the hypothesis of a polygenetic aetiology for preeclampsia with a common network of susceptibility genes. The greater genetic diversity among controls may suggest a protective role of genetic diversity against the development of preeclampsia.
Exploring Possible Relations Between Optical Variability Time Scales and Broad Emission Line Shapes in AGN

Here we investigate the connection of broad emission line shapes and continuum light curve variability time scales of type-1 Active Galactic Nuclei (AGN). We developed a new model to describe optical broad emission lines as an accretion disk model of a line profile with additional ring emission. We connect ring radii with orbital time scales derived from optical light curves, and using Kepler's third law, we calculate mass of central supermassive black hole (SMBH). The obtained results for central black hole masses are in a good agreement with {other methods. This indicates that the variability time scales of AGN may not be stochastic, but rather connected to the orbital time scales which depend on the central SMBH mass.
Regularization and Computation with high-dimensional spike-and-slab posterior distributions

We consider the Bayesian analysis of a high-dimensional statistical model with a spike-and-slab prior, and we study the forward-backward envelop of the posterior distribution -- denoted $\check\Pi_{\gamma}$ for some regularization parameter $\gamma>0$. Viewing $\check\Pi_\gamma$ as a pseudo-posterior distribution, we work out a set of sufficient conditions under which it contracts towards the true value of the parameter as $\gamma\downarrow 0$, and $p$ (the dimension of the parameter space) diverges to $\infty$. In linear regression models the contraction rate matches the contraction rate of the true posterior distribution. We also study a practical Markov Chain Monte Carlo (MCMC) algorithm to sample from $\check\Pi_{\gamma}$. In the particular case of the linear regression model, and focusing on models with high signal-to-noise ratios, we show that the mixing time of the MCMC algorithm depends crucially on the coherence of the design matrix, and on the initialization of the Markov chain. In the most favorable cases, we show that the computational complexity of the algorithm scales with the dimension $p$ as $O(pe^{s_\star^2})$, where $s_\star$ is the number of non-zeros components of the true parameter. We provide some simulation results to illustrate the theory. Our simulation results also suggest that the proposed algorithm (as well as a version of the Gibbs sampler of Narisetti and He (2014)) mix poorly when poorly initialized, or if the design matrix has high coherence.
Cognitive Strategies and Physical Activity in Older Adults: A Discriminant Analysis

Background Although a number of studies have examined sociodemographic, psychosocial, and environmental determinants of the level of physical activity (PA) for older people, little attention has been paid to the predictive power of cognitive strategies for independently living older adults. However, cognitive strategies have recently been considered to be critical in the management of day-to-day living. Methods Data were collected from 243 men and women aged 55 years and older living in France using face-to-face interviews between 2011 and 2013. Results A stepwise discriminant analysis selected five predictor variables (age, perceived health status, barriers' self-efficacy, internal memory, and attentional control strategies) of the level of PA. The function showed that the rate of correct prediction was 73% for the level of PA. The calculated discriminant function based on the five predictor variables is useful for detecting individuals at high risk of lapses once engaged in regular PA. Conclusions This study highlighted the need to consider cognitive functions as a determinant of the level of PA and, more specifically, those cognitive functions related to executive functions (internal memory and attentional control), to facilitate the maintenance of regular PA. These results are discussed in relation to successful aging.
Berberine Regulates Treg/Th17 Balance to Treat Ulcerative Colitis Through Modulating the Gut Microbiota in the Colon

Berberine (BBR), an alkaloid isolated from Rhizoma Coptidis, Cortex Phellode, and Berberis, has been widely used in the treatment of ulcerative colitis (UC). However, the mechanism of BBR on UC is unknown. In this study, we investigated the activities of T regulatory cell (Treg) and T helper 17 cell (Th17) in a dextran sulfate sodium (DSS)-induced UC mouse model after BBR administration. We also investigated the changes of gut microbiota composition using 16S rRNA analysis. We also examined whether BBR could regulate the Treg/Th17 balance by modifying gut microbiota. The mechanism was further confirmed by depleting gut microbiota through a combination of antibiotic treatment and fecal transplantations. Results showed that BBR treatment could improve the Treg/Th17 balance in the DSS-induced UC model. BBR also reduced diversity of the gut microbiota and interfered with the relative abundance of Desulfovibrio, Eubacterium, and Bacteroides. Moreover, BBR treatment did not influence the Treg/Th17 balance after the depletion of gut microbiota. Our results also revealed that fecal transplantation from BBR-treated mice could relieve UC and regulate the Treg/Th17 balance. In conclusion, our study provides evidence that BBR prevents UC by modifying gut microbiota and regulating the balance of Treg/Th17.
Conquering Generals: an NP-Hard Proof of Useful Work

Proof of Work systems are used in cryptocurrencies to obtain consensus in distributed peer-to-peer systems that share no trust. Miners of cryptocurrency compete by engaging in the Proof of Work to solve a cryptographic challenge. The first to successfully provide a solution to the challenge wins by minting new currency. The process of mining also simultaneously prevents double-spending through the creation of an append-only distributed database known as the blockchain. The most widely adopted Proof of Work is the Hashcash scheme and the most widely deployed miners are ASIC-based. Despite the popularity of Hashcash, two issues are commonly identified its use. Firstly, the high energy consumption of the scheme is perceived as wasteful because the solutions found provide no useful output, and secondly, the computational complexity class of the scheme is not formally known. Based on these deficiencies, we propose a novel Proof of Work system which achieves the following goals: - to provide a fiscally incentivized platform for algorithm research that aims to optimize an NP-Hard computational problem. This provides indirect insight into the P Versus NP Clay Institute Millennium problem, thus providing useful output. - to construct a challenge within a known hard computational complexity class. - to ensure the Proof of Work created is inclusive of ASIC hardware. Our proposal is a hybrid Proof of Work system that initially uses the Hashcash scheme and which subsequently constructs an instance of the NP-Hard Travelling Salesman Problem. We build on the ambitions of others to develop Proofs of Useful Work. We differentiate our paper from related work as the first to consider the current capital investment into ASIC hardware, thus including them in our proposal.
Meta Transfer Learning for Facial Emotion Recognition

The use of deep learning techniques for automatic facial expression recognition has recently attracted great interest but developed models are still unable to generalize well due to the lack of large emotion datasets for deep learning. To overcome this problem, in this paper, we propose utilizing a novel transfer learning approach relying on PathNet and investigate how knowledge can be accumulated within a given dataset and how the knowledge captured from one emotion dataset can be transferred into another in order to improve the overall performance. To evaluate the robustness of our system, we have conducted various sets of experiments on two emotion datasets: SAVEE and eNTERFACE. The experimental results demonstrate that our proposed system leads to improvement in performance of emotion recognition and performs significantly better than the recent state-of-the-art schemes adopting fine-tuning/pre-trained approaches.
Infant Exposure to Metals through Consumption of Formula Feeding in Mekelle, Ethiopia

This study aimed at determination of heavy metals (cadmium, lead, and zinc) in milk-based infant formulas collected from Mekelle, Ethiopia, and their associated health risks to the infants through consumption of these products. The infant feeding samples were dry-ashed in a muffle furnace followed by digestion in nitric acid and the resulting solutions were analyzed by flame atomic absorption spectrophotometer. Cadmium was not detected in the samples while the levels of lead and zinc ranged from not detected value to 0.103 mg/kg and from 27.888 to 71.553 mg/kg, respectively. The estimated daily intake values and the health risk indices of both metals were below their respective safety limits and the threshold of 1, respectively. These findings show low infant health risk of these metals through consumption of these products. Nevertheless, regular monitoring of infant formula for toxic metals is required since infants are potentially more susceptible to metals.
Task-dependent modulation of spinal and transcortical stretch reflexes linked to motor learning rate

It is generally believed that task-dependent control of body configuration (‘posture’) is achieved by adjusting voluntary motor activity and transcortical ‘long-latency’ reflexes. Spinal monosynaptic circuits are thought not to be engaged in such task-level control. Similarly, being in a state of motor learning has been strongly associated only with an upregulation of feedback responses at transcortical latencies and beyond. In two separate experiments, the current study examined the task-dependent modulation of stretch reflexes by perturbing the hand of human subjects while they were waiting for a ‘Go’ signal to move at the different stages of a classic kinematic learning task (visuomotor rotation). Although the subjects had to resist all haptic perturbations equally, the study leveraged that task-dependent feedback controllers may already be ’loaded’ at the movement anticipation stage. In addition to an upregulation of short- and long-latency reflex gains during early exposure to the visual distortion, I found a relative inhibition of reflex responses in the ‘washout’ stage (sensory realignment state). For more distal muscles (brachioradialis), this inhibition also extended to the monosynaptic reflex response (‘R1’). These R1 gains reflected individual motor learning performance in the visuomotor task. The results demonstrate that the system’s ‘control policy’ in visuomotor adaptation can also include inhibition of proprioceptive reflexes, and that aspects of this policy can affect monosynaptic spinal circuits. The latter finding suggests a novel form of state-related control, probably realized by independent control of fusimotor neurons, through which segmental circuits can tune to higher-level features of a sensorimotor task. Additional Information Conflict of interest The author declares no conflict of interest. Author contributions M.D. devised, designed and implemented the project, analyzed the data and wrote the manuscript. The author approves the final version of the manuscript and is fully accountable for all aspects of the work. The experiments were performed at the Department of Integrative Medical Biology, Umeå University, Sweden. Funding This work was financially supported through grants awarded to M.D. by the Kempe Foundation, the local Foundation for Medical Research (“Insamlingsstiftelsen”) and the Swedish Research Council (project 2016-02237).
Theoretical and Methodological Context of (Post)-Modern Econometrics and Competing Philosophical Discourses for Policy Prescription

Abstract This research article was championed as a way of providing discourses pertaining to the concept of “Critical Realism (CR)” approach, which is amongst many other forms of competing postmodern philosophical concepts for the engagement of dialogical discourses in the area of established econometric methodologies for effective policy prescription in the economic science discipline. On the whole, there is no doubt surrounding the value of empirical endeavours in econometrics to address real world economic problems, but equally so, the heavy weighted use and reliance on mathematical contents as a way of justifying its scientific base seemed to be losing traction on the intended focus of economics when it comes to confronting real world problems in the domain of social interaction. In this vein, the construction of mixed methods discourse(s), which favour that of CR philosophy is hereby suggested in this article as a way forward in confronting with issues raised by critics of mainstream economics and other professionals in the postmodern era.
Breaking-down the Ontology Alignment Task with a Lexical Index and Neural Embeddings

Large ontologies still pose serious challenges to state-of-the-art ontology alignment systems. In the paper we present an approach that combines a lexical index, a neural embedding model and locality modules to effectively divide an input ontology matching task into smaller and more tractable matching (sub)tasks. We have conducted a comprehensive evaluation using the datasets of the Ontology Alignment Evaluation Initiative. The results are encouraging and suggest that the proposed methods are adequate in practice and can be integrated within the workflow of state-of-the-art systems.
Complementary and Alternative Medicine for Diabetes Diabetes Canada Clinical Practice Guidelines Expert Committee

• Anywhere from 25% to 57% of people with diabetes report using complementary or alternative medicine. • Some natural health products have shown a lowering of A1C by ≥0.5% in trials lasting at least 3 months in adults with type 2 diabetes, but most are single, small trials that require further large-scale evaluations before they can be recommended for widespread use in diabetes. • A few more commonly used natural health products for diabetes have been studied in larger randomized controlled trials and/or meta-analyses refuting the popular belief of benefit of these compounds. • Health-care providers should always ask about the use of complementary and alternative medicine as some may result in unexpected side effects and/or interactions with traditional pharmacotherapies.
Exploring the boundaries of quantum mechanics: advances in satellite quantum communications

Recent interest in quantum communications has stimulated great technological progress in satellite quantum technologies. These advances have rendered the aforesaid technologies mature enough to support the realization of experiments that test the foundations of quantum theory at unprecedented scales and in the unexplored space environment. Such experiments, in fact, could explore the boundaries of quantum theory and may provide new insights to investigate phenomena where gravity affects quantum objects. Here, we review recent results in satellite quantum communications and discuss possible phenomena that could be observable with current technologies. Furthermore, stressing the fact that space represents an incredible resource to realize new experiments aimed at highlighting some physical effects, we challenge the community to propose new experiments that unveil the interplay between quantum mechanics and gravity that could be realizable in the near future. This article is part of a discussion meeting issue ‘Foundations of quantum mechanics and their impact on contemporary society’.
A Graph Database for a Virtualized Network Infrastructure

Modern communication networks are large, dynamic, complex, and increasingly use virtualized network infrastructure. To deploy, maintain, and troubleshoot such networks, it is essential to understand how network elements - such as servers, switches, virtual machines, and virtual network functions - are connected to one another, and to be able to discover communication paths between them. For network maintenance applications such as troubleshooting and service quality management, it is also essential to understand how connections change over time, and be able to pose time-travel queries to retrieve information about past network states. With the industry-wide move to Software Defined Networks and Virtualized Network Functions (VNFs) [26][24], maintaining these inventory and topology databases becomes a critical issue. In this paper, we explore the database requirements for the management and troubleshooting of network services using VNF and SDN technologies. This work was initiated in the context of Open source ECOMP, which has been now merged into ONAP [24], the new industry-standard for managing network automation. We develop a graph-based layered network model with layers representing increasing levels of specificity, from VNFs to physical hardware. We then describe the kinds of queries required for activities such as operations management and troubleshooting. These considerations have led us to develop Nepal, a model-driven graph database system to represent and reason over network service topology and data flows within the network. Nepal has several features making it particularly applicable for querying inventory: Nepal has a strongly-typed but flexible schema to support model-driven networking; it makes graph paths a first-class object in its query system; it has sophisticated support for in-the-past queries; and it works as a layer over one or more underlying databases. We demonstrate the capabilities of Nepal by examples, discuss its model-driven query capabilities, and implementation details on Gremlin and Postgres. We illustrate how path queries can simplify the extraction of information from a dynamic inventory of a multi-layer network and can be used for troubleshooting.
Advanced 2-µm solid-state laser for wind and CO 2 lidar applications

Significant advancements in the 2-micron laser development have been made recently. Solid-state 2-micron laser is a key subsystem for a coherent Doppler lidar that measures the horizontal and vertical wind velocities with high precision and resolution. The same laser, after a few modifications, can also be used in a Diffrencial Absorption Lidar (DIAL) system for measuring atmospheric CO 2 concentration profiles. The world record 2-micron laser energy is demonstrated with an oscillator and two amplifiers system. It generates more than one joule per pulse energy with excellent beam quality. Based on the successful demonstration of a fully conductive cooled oscillator by using heat pipe technology, an improved fully conductively cooled 2-micron amplifier was designed, manufactured and integrated. It virtually eliminates the running coolant to increase the overall system efficiency and reliability. In addition to technology development and demonstration, a compact and engineering hardened 2-micron laser is under development. It is capable of producing 250 mJ at 10 Hz by an oscillator and one amplifier. This compact laser is expected to be integrated to a lidar system and take field measurements. The recent achievements push forward the readiness of such a laser system for space lidar applications. This paper will review the developments of the state-of-the-art solid-state 2-micron laser.
Finding Substitutable Binary Code for Reverse Engineering by Synthesizing Adapters

Independently developed codebases typically contain many segments of code that perform the same or closely related operations. Being able to detect these related segments is helpful to applications such as reverse engineering. In this paper, we tackle the problem of determining whether two segments of binary code perform the same operation by asking whether one segment can be substituted by the other. A key insight behind our approach is that because these segments often have different interfaces, some glue code (an adapter) will be needed to perform the substitution. Here we present an algorithm that searches for substitutable code segments by attempting to synthesize an adapter between them. We implement our technique using concrete adapter enumeration and binary symbolic execution to explore the relation between size of adapter search space and total search time. Then, using more than 61,000 fragments of binary code extracted from a ARM image built for the iPod Nano 2g device and functions from the VLC media player, we evaluate our adapter synthesis implementation on more than one million synthesis tasks. Our tool finds dozens of instances of VLC functions in the firmware image. These results confirm that instances of adaptably substitutable binary functions exist in real-world code, and suggest that adapter synthesis has promising reverse engineering applications.