Miracle-dz/UniFAR-FTUs huggingface dataset:
Weighted parametric systems: Modelling and architecture

Modern systems' design usually lies in multiple components which are connected via their interfaces. Synchronous applications, like IoT, require parametric systems, i.e., systems that aim to operate independently of the number of their components. A key feature in modelling of parametric systems is the architecture specification that defines the underlying topology and provides coordination rules. On the other hand, to achieve optimized requirements and performance there is need for describing parametric architectures and parametric behavior in a quantitative setting. In this paper we study the quantitative modelling and architecture specification of component-based parametric systems. We introduce a weighted extended first-order interaction logic as a specification language for weighted parametric architectures. We also introduce weighted parametric models defined by composed transition systems whose interactions are expressed by formulas of our weighted logic. Equivalence of weighted extended first-order interaction logic formulas is decidable in the class of computable fields. We show that our weighted logic can efficiently describe several software architectures with quantitative characteristics.
Inhibition and rapid recovery of Ca2+ current during Ca2+ release from sarcoplasmic reticulum in guinea pig ventricular myocytes.

We have investigated the modulation of the L-type Ca2+ channel by Ca2+ released from the sarcoplasmic reticulum (SR) in single guinea pig ventricular myocytes under whole-cell voltage clamp. [Ca2+]i was monitored by fura 2. By use of impermeant monovalent cations in intracellular and extracellular solutions, the current through Na+ channels, K+ channels, nonspecific cation channels, and the Na+-Ca2+ exchanger was effectively blocked. By altering the amount of Ca2+ loading of the SR, the time course of the Ca2+ current (ICa) could be studied during various amplitudes of Ca2+ release. In the presence of a large Ca2+ release, fast inhibition of ICa occurred, whereas on relaxation of [Ca2+]i, fast recovery was observed. The time course of this transient inhibition of ICa reflected the time course of [Ca2+]i. However, the inhibition seen in the first 50 ms, ie, the time of net Ca2+ release from the SR, exceeded the inhibition observed later during the pulse, suggesting the existence of a higher [Ca2+] near the channel during this time. Transient inhibition of ICa during Ca2+ release was observed to a similar degree at all potentials. It could still be observed in the presence of intracellular ATP-gamma-S and of cAMP. Therefore, we conclude that the modulation of ICa by Ca2+ release from the SR is not related to dephosphorylation. It could be related to a reduction in the driving force and to a direct inhibition of the channel by [Ca2+]i. The observation that the degree of inhibition does not depend on membrane potential suggests that the Ca2+ binding site for this modulation is located outside the pore. (ABSTRACT TRUNCATED AT 250 WORDS)
New approaches to expand hematopoietic stem and progenitor cells

Introduction: Hematopoietic stem cells (HSCs) are defined by their capacity to self-renew and to differentiate into all blood cell lineages, and are currently the foundation of HSC transplantation therapy. A variety of methods have recently been explored to find a way to expand hematopoietic stem and progenitor cells (HSCs/PCs) ex vivo in order to improve the efficiency and outcome of HSC transplantation. Areas covered: Recent studies of HSCs/PCs have led to the development of new ways to detect and purify HSCs/PCs and have also revealed several intrinsic and extrinsic factors that control the molecular signals fundamental to self-renewal and differentiation of HSCs. These findings have provided new approaches for expanding HSCs/PCs ex vivo utilizing protein factors and small-molecule compounds (SMCs) and have also demonstrated promising outcomes in clinical trials. Expert opinion: Although further technical innovation is still needed, elucidation of the whole picture of signaling pathways critical to HSCs/PCs and manipulation of such pathways by SMCs could establish efficient, cost-effective, riskless and robust methods for ex vivo expansion of HSCs/PCs. With these efforts, more sophisticated HSC transplantation would be possible in the near future.
Realization of 
PT
-symmetric and 
PT
-symmetry-broken states in static optical-lattice potentials

R. Labouvie et al. [Phys. Rev. Lett. 116, 235302 (2016)] have described an experiment with a weakly interacting Bose-Einstein condensate trapped in a one-dimensional optical lattice with localized loss created by a focused electron beam. We show that by setting suitable initial currents between neighboring sites it is possible to create $\mathcal{PT}$-symmetric quasi-stationary and $\mathcal{PT}$-symmetry broken decaying states in an embedded two-mode subsystem. This subsystem exhibits gain provided by the coupling to the reservoir sites and localized loss due to the electron beam, and shows the same dynamics as a non-Hermitian two-mode system with symmetric real and antisymmetric imaginary time-independent potentials, except for a proportionality factor in the chemical potential. We also show that there are three other equivalent scenarios, and that the presence of a localized loss term significantly reduces the size of the condensate required for the realization.
Trust and Community Treatment Orders

There are conflicting views about the benefits of community treatment orders (CTOs) for people with mental illness. While there is a significant literature on the coercive nature of CTOs, there is less on the impact that CTOs have upon trust. A recovery-oriented approach requires a trusting therapeutic relationship and the coercion inherent in the CTO process may make it difficult for trust to be built, nurtured, and sustained between workers and patients. Our aim was therefore to examine the role of trust within the CTO experience for mental health workers and patients on CTOs. Methods: We conducted a thematic discourse analysis of 8 in-depth interviews with people who were currently on a CTO and 10 interviews with multi-disciplinary mental health workers in Adelaide, Australia (total N = 18 interviews). The interviews were coded and analyzed with the assistance of a patient representative. The findings reveal the challenges and opportunities for trust within the coercive relationship of a CTO. Findings: We found that patients have diverse experiences of CTOs and that trust or mistrust played an import role in whether or not they found the CTO beneficial.
Nurses’ Job Satisfaction, Organizational Commitment, and Career Intent

ObjectiveThe objective of this survey was to define the characteristics of the nursing work force of a mixed urban/rural region of New York state and to determine the nurses’ level of job satisfaction and commitment to the work setting. BackgroundRecent investigations suggest nurses are highly dissatisfied with the demands of the healthcare environment and are expressing increased likelihood of leaving the work setting. These factors, in combination with the increasing age of the current nursing work force, are contributing to serious concerns about the future of patient care. MethodsA random sample survey was mailed to registered nurses in the Finger Lakes Region of New York State in June 2000. Items in the questionnaire addressed nurse characteristics, reasons for leaving or staying with an employing agency, one- and five-year career intent, and level of job satisfaction and organizational commitment. ResultsForty-six percent of the nurses returned completed questionnaires. Within this sample, most of the nurses were older, European American, and female. Personal and organizational characteristics contributed to differences in levels of job satisfaction, organizational commitment, and 1- and 5-year intent. In addition, many of the most satisfied and committed nurses reported their intent to leave nursing within the next 5 years. ConclusionsFindings of this investigation suggest the organizational environment, educational preparation, and personal characteristics of currently employed registered nurses affect their current job satisfaction, organizational commitment, and plans for continuing as a nurse.
Guiding Theorem Proving by Recurrent Neural Networks

We describe two theorem proving tasks -- premise selection and internal guidance -- for which machine learning has been recently used with some success. We argue that the existing methods however do not correspond to the way how humans approach these tasks. In particular, the existing methods so far lack the notion of a state that is updated each time a choice in the reasoning process is made. To address that, we propose an analogy with tasks such as machine translation, where stateful architectures such as recurrent neural networks have been recently very successful. Then we develop and publish a series of sequence-to-sequence data sets that correspond to the theorem proving tasks using several encodings, and provide the first experimental evaluation of the performance of recurrent neural networks on such tasks.
Trajectory Optimization on Manifolds: A Theoretically-Guaranteed Embedded Sequential Convex Programming Approach

Sequential Convex Programming (SCP) has recently gained popularity as a tool for trajectory optimization due to its sound theoretical properties and practical performance. Yet, most SCP-based methods for trajectory optimization are restricted to Euclidean settings, which precludes their application to problem instances where one must reason about manifold-type constraints (that is, constraints, such as loop closure, which restrict the motion of a system to a subset of the ambient space). The aim of this paper is to fill this gap by extending SCP-based trajectory optimization methods to a manifold setting. The key insight is to leverage geometric embeddings to lift a manifold-constrained trajectory optimization problem into an equivalent problem defined over a space enjoying a Euclidean structure. This insight allows one to extend existing SCP methods to a manifold setting in a fairly natural way. In particular, we present a SCP algorithm for manifold problems with refined theoretical guarantees that resemble those derived for the Euclidean setting, and demonstrate its practical performance via numerical experiments.
More applications of the d-neighbor equivalence: acyclicity and connectivity constraints

In this paper, we design a framework to obtain efficient algorithms for several problems with a global constraint (acyclicity or connectivity) such as Connected Dominating Set, Node Weighted Steiner Tree, Maximum Induced Tree, Longest Induced Path, and Feedback Vertex Set. We design a meta-algorithm that solves all these problems and whose running time is upper bounded by $2^{O(k)}\cdot n^{O(1)}$, $2^{O(k \log(k))}\cdot n^{O(1)}$, $2^{O(k^2)}\cdot n^{O(1)}$ and $n^{O(k)}$ where $k$ is respectively the clique-width, $\mathbb{Q}$-rank-width, rank-width and maximum induced matching width of a given decomposition. Our meta-algorithm simplifies and unifies the known algorithms for each of the parameters and its running time matches asymptotically also the running times of the best known algorithms for basic NP-hard problems such as Vertex Cover and Dominating Set. Our framework is based on the $d$-neighbor equivalence defined in [Bui-Xuan, Telle and Vatshelle, TCS 2013]. The results we obtain highlight the importance of this equivalence relation on the algorithmic applications of width measures. We also prove that our framework could be useful for $W[1]$-hard problems parameterized by clique-width such as Max Cut and Maximum Minimal Cut. For these latter problems, we obtain $n^{O(k)}$, $n^{O(k)}$ and $n^{2^{O(k)}}$ time algorithms where $k$ is respectively the clique-width, the $\mathbb{Q}$-rank-width and the rank-width of the input graph.
Physics-informed transfer path analysis with parameter estimation using Gaussian processes

Gaussian processes regression is applied to augment experimental data of transfer-path analysis (TPA) by known information about the underlying physical properties of the system under investigation. The approach can be used as an alternative to model updating and is also applicable if no detailed simulation model of the system exists. For vibro-acoustic systems at least three features are known. Firstly, observable quantities fulfill a wave equation or a Helmholtz-like equation in the frequency domain. Secondly, the relation between pressure/stress and displacement/velocity/acceleration are known via constitutive relations involving mass density and elastic constants of the material. The latter also determine the propagation speed of waves. Thirdly, the geometry of the system is often known up to a certain accuracy. Here it is demonstrated that taking into account this information can potentially enhance TPA results and quantify their uncertainties at the same time. In particular this is the case for noisy measurement data and if material parameters and source distributions are (partly) unknown. Due to the probabilistic nature of the procedure unknown parameters can be estimated, making the method also applicable to material characterization as an inverse problem.
Mono- and dual-targeting triplebodies activate natural killer cells and have anti-tumor activity in vitro and in vivo against chronic lymphocytic leukemia

ABSTRACT Chronic lymphocytic leukemia (CLL) is the most common form of leukemia that affects B lymphocytes in adults. Natural killer (NK) cells in CLL patients are intrinsically potent but display poor in situ effector functions. NKG2D is an activating receptor found on NK and CD8+ T cells and plays a role in immunosurveillance of CLL. In this study, we developed mono- and dual-targeting triplebodies utilizing a natural ligand for human NKG2D receptor (ULBP2) to retarget NK cells against tumor cells. Triplebodies in both formats showed better ability to induce NK-cell-dependent killing of target cells compared to bispecific counterparts. A mono-targeting triplebody ULBP2-aCD19-aCD19 successfully triggered NK cell effector functions against CLL cell line MEC1 and primary tumor cells in allogenic and autologous settings. Additionally, a dual-targeting triplebody ULBP2-aCD19-aCD33 specific for two distinct tumor-associated antigens was developed to target antigen loss variants, such as mixed lineage leukemia (MLL). Of note, this triplebody exhibited cytotoxic activity against CD19/CD33 double positive cells and retained its binding features even in the absence of one of the tumor antigens. Further, ULBP2-aCD19-aCD19 showed significant in vivo activity in immune-deficient (NSG) mouse model transplanted with CLL cell line as target cells and human immune cells as an effector population providing a proof-of-principle for this therapeutic concept.
The distinction problem for metaplectic case

We use the theta lifts between [Formula: see text] and [Formula: see text] to study the distinction problems for the pair [Formula: see text] where [Formula: see text] is a quadratic field extension over a nonarchimedean local field [Formula: see text] of characteristic zero and [Formula: see text] is a quaternion algebra. With a similar strategy, we give a conjectural formula for the multiplicity of distinction problem related to the pair [Formula: see text]
Stumbling Reactions in Partial Gravity – Neuromechanics of Compensatory Postural Responses and Inter-Limb Coordination During Perturbation of Human Stance

Spontaneous changes in gravity play a significant role in interplanetary space missions. To preserve the astronauts’ capability to execute mission-critical tasks and reduce the risk of injury in transit and on planetary surfaces, a comprehensive understanding of the neuromuscular control of postural responses after balance deterioration in hypo- or hyper-gravity conditions is essential. Therefore, this study aimed to evaluate the effect of acute gravitational variation on postural adjustments in response to perturbations. Gravitational changes were induced using parabolic flight. Postural set was manipulated by randomly providing unilateral left, bilateral or split perturbations which require balance corrections to restore postural stability. In six subjects, postural reactions were recorded after anterior and posterior surface perturbations for progressively increased gravitational conditions spanning from 0.25 to 1.75 g. Ankle and knee joint kinematics and electromyograms (EMG) of eight leg muscles were recorded prior (PRE) and after perturbation onset. Muscle activation onset latencies and amplitudes in the short-, medium-, and long-latency responses (SLR, MLR, LLR) were assessed. Results demonstrate an increased muscle activity (p < 0.05) and co-contraction in the lower extremities (p < 0.05) prior to perturbation in hypo- and hyper-gravity. After perturbation, reduced muscle onset latencies (p < 0.05) and increased muscle activations in the MLR and LLR (p < 0.05), concomitant with an increased co-contraction in the SLR, were manifested with a progressive rise in gravity. Ankle and knee joint deflections remained unaffected, whereas angular velocities increased (p < 0.05) with increasing gravitation. Effects were more pronounced in bi- compared to unilateral or split perturbations (p < 0.05). Neuro-mechanical adaptations to gravity were more distinct and muscle onset latencies were shorter in the displaced compared to the non-displaced leg. In conclusion, the timing and magnitude of postural reflexes involved in stabilization of bipedal stance are gravity-dependent. The approximately linear relationship between gravity and impulse-directed EMG amplitudes or muscle onset latencies after perturbation indicates that the central nervous system correctly predicts the level of gravity. Moreover, it accurately governs contractions in the antigravity musculature to counterbalance the gravitational pull and to regain upright posture after its disturbance. Importantly, unilateral perturbations evoked fast reflex responses in the synergistic muscles of the non-displaced contralateral leg suggesting a synchronized inter-limb coordination mediated by spinal circuitries.
Heterojunction-Free GaN Nanochannel FinFETs With High Performance

Heavily doped GaN nanochannel fin-shaped field-effect transistors (FinFETs) without heterojunction have been fabricated and characterized for the first time. Simplified pragmatical technology for GaN epitaxial growth and FinFET process was used to achieve nanodevices with a channel width from 40 to 100 nm and a gate length of 1 μm. They exhibit excellent on-state performance, such as maximum drain current of 670 mA/mm and maximum transconductance of 168 mS/mm. Record off-state performance was measured: extremely low leakage current of ~ 10-11 mA and source-drain breakdown voltage of ~280 V. The subthreshold slope of 68 mV/decade is close to the theoretical limit (60 mV/decade, so far achieved only in SOI MOSFETs) and leads to very high Ion/Ioff ratio of 108 - 109. The proposed heterojunction-free nanochannel GaN FinFET is a very promising candidate not only for high-performance and high-speed integrated circuits but also for high-power applications.
Combining Experience Replay with Exploration by Random Network Distillation

Our work is a simple extension of the paper "Exploration by Random Network Distillation"[1]. More in detail, we show how to efficiently combine Intrinsic Rewards with Experience Replay in order to achieve more efficient and robust exploration (with respect to PPO/RND) and consequently better results in terms of agent performances and sample efficiency. We are able to do it by using a new technique named Prioritized Oversampled Experience Replay (POER), that has been built upon the definition of what is the important experience useful to replay. Finally, we evaluate our technique on the famous Atari game Montezuma’s Revenge and some other hard exploration Atari games.
Label Mapping Neural Networks with Response Consolidation for Class Incremental Learning

Class incremental learning refers to a special multi-class classification task, in which the number of classes is not fixed but is increasing with the continual arrival of new data. Existing researches mainly focused on solving catastrophic forgetting problem in class incremental learning. To this end, however, these models still require the old classes cached in the auxiliary data structure or models, which is inefficient in space or time. In this paper, it is the first time to discuss the difficulty without support of old classes in class incremental learning, which is called as softmax suppression problem. To address these challenges, we develop a new model named Label Mapping with Response Consolidation (LMRC), which need not access the old classes anymore. We propose the Label Mapping algorithm combined with the multi-head neural network for mitigating the softmax suppression problem, and propose the Response Consolidation method to overcome the catastrophic forgetting problem. Experimental results on the benchmark datasets show that our proposed method achieves much better performance compared to the related methods in different scenarios.
Impact of Disease‐Modifying Therapies on Brain and Spinal Cord Atrophy in Multiple Sclerosis

Brain and spinal cord atrophy occur early in the course of multiple sclerosis (MS) and continue throughout this lifelong illness, resulting in substantial parenchymal tissue loss at later disease stages. Treatments that slow or prevent atrophy may reduce disability progression in the long term. Disease‐modifying agents (DMAs) such as interferon [. beta]‐1b (IFN[.beta]‐1b), IFN[. beta]‐1a, and glatiramer acetate inhibit inflammatory events believed to initiate and perpetuate the disease process. DMAs have been shown to inhibit aspects of MS related to brain inflammation such as relapses and gadolinium‐enhanced lesions. Because brain inflammation has been linked to irreversible brain tissue injury, DMAs should be effective in reducing the rate of brain atrophy progression. Weekly IFN[. beta]‐1a (Avonex or Rebif) has been shown to slow the rate of brain atrophy; a large study of a frequent injection regimen with IFN[. beta]‐1a (Rebif) showed continued atrophy progression despite IFN[. beta]‐1a at a rate similar to placebo‐treated patients. It is not clear why weekly treatment regimens with lower total doses of IFN[. beta]‐1a would show beneficial effects on brain atrophy compared with frequent injections with larger weekly doses. This article reviews results of clinical trials that have examined the effects of DMAs on brain and spinal cord atrophy in patients with MS. Some of these agents have demonstrated positive effects in well‐controlled studies, suggesting that anti‐inflammatory therapy can delay or prevent the emergence of irreversible central nervous system pathology.
A Comparative Review of Microservices and Monolithic Architectures

Microservices' architecture is getting attention in the academic community and the industry, and mostly is compared with monolithic architecture. Plenty of the results of these research papers contradict each other regarding the performance of these architectures. Therefore, these two architectures are compared in this paper, and some specific configurations of microservices' applications are evaluated as well in the term of service discovery. Monolithic architecture in concurrency testing showed better performance in throughput by 6% when compared to microservices architecture. The load testing scenario did not present significant difference between the two architectures. Furthermore, a third test comparing microservices applications built with different service discovery technologies such as Consul and Eureka showed that applications with Consul presented better results in terms of throughput.