Miracle-dz/UniFAR-FTUs huggingface dataset:
Implementation of a Sequence-to-Sequence Stacked Sparse Long Short-Term Memory Autoencoder for Anomaly Detection on Multivariate Timeseries Data of Industrial Blower Ball Bearing Units

The advent of Industry 4.0 introduced new ways for businesses to evolve by implementing maintenance policies leading to advancements in terms of productivity, efficiency, and financial performance. In line with the growing emphasis on sustainability, industries implement predictive techniques based on Artificial Intelligence for the purpose of mitigating machine and equipment failures by predicting anomalies during their production process. In this work, a new dataset that was made publicly available, collected from an industrial blower, is presented, analyzed and modeled using a Sequence-to-Sequence Stacked Sparse Long Short-Term Memory Autoencoder. Specifically the right and left mounted ball bearing units were measured during several months of normal operational condition as well as during an encumbered operational state. An anomaly detection model was developed for the purpose of analyzing the operational behavior of the two bearing units. A stacked sparse Long Short-Term Memory Autoencoder was successfully trained on the data obtained from the left unit under normal operating conditions, learning the underlying patterns and statistical connections of the data. The model was evaluated by means of the Mean Squared Error using data from the unit’s encumbered state, as well as using data collected from the right unit. The model performed satisfactorily throughout its evaluation on all collected datasets. Also, the model proved its capability for generalization along with adaptability on assessing the behavior of equipment similar to the one it was trained on.
Quantitative evaluation method for liver fibrosis based on multi-Rayleigh model with estimation of number of tissue components in ultrasound B-mode image

The development of a quantitative diagnostic method for liver fibrosis using an ultrasound B-mode image is highly required. In our previous study, a multi-Rayleigh model was proposed to express a probability distribution of echo envelope amplitude from a fibrotic liver. Using the multi-Rayleigh model, a structure of fibrotic tissue can be quantitatively estimated. In this study, a method of estimating the number of tissue components was proposed to improve the accuracy of estimating a fibrotic tissue structure. Using threshold processing for a squared Mahalanobis distance of moments, which is a statistical property of echo envelope amplitude, the number of tissue components could be quantitatively estimated. The results of evaluation of clinical ultrasound B-mode images using the multi-Rayleigh model with estimation of the number of tissue components well reflected the tissue structural changes caused by liver fibrosis. It was concluded that our proposed method of estimating the number of tissue components improves the accuracy of liver fibrosis evaluation based on the multi-Rayleigh model.
Vortex Lattices in Superconducting Niobium and Skyrmion Lattices in Chiral MnSi: An Investigation by Neutron Scattering

We use small angle neutron scattering as a versatile tool for the investigation of two different kinds of complex magnetic order: We examine the static and dynamic properties of the vortex lattice (VL) of the conventional superconducting model system niobium and we prove that a skyrmion lattice exists in the A-phase of the weak itinerant heli-magnet MnSi. Both the VL in niobium and the skyrmion lattice in MnSi can be regarded as a macroscopic lattice, formed by topological entities with particle-like properties, emerging from continuous fields.
The 3Rs in Experimental Liver Disease

Simple Summary This article provides a review of recent studies that explore the application of the 3Rs in experimental animal models of liver disease, comparing different models for a correct search for replacement, refinement, and reduction methods. However, the limitations of each of the replacement techniques are identified, which highlights that although the use of animal models is still necessary, their number can be reduced and adjusted to the scientific question of interest, always taking into account their welfare and using alternative techniques to answer more specific questions. Abstract Patients with cirrhosis present multiple physiological and immunological alterations that play a very important role in the development of clinically relevant secondary complications to the disease. Experimentation in animal models is essential to understand the pathogenesis of human diseases and, considering the high prevalence of liver disease worldwide, to understand the pathophysiology of disease progression and the molecular pathways involved, due to the complexity of the liver as an organ and its relationship with the rest of the organism. However, today there is a growing awareness about the sensitivity and suffering of animals, causing opposition to animal research among a minority in society and some scientists, but also about the attention to the welfare of laboratory animals since this has been built into regulations in most nations that conduct animal research. In 1959, Russell and Burch published the book “The Principles of Humane Experimental Technique”, proposing that in those experiments where animals were necessary, everything possible should be done to try to replace them with non-sentient alternatives, to reduce to a minimum their number, and to refine experiments that are essential so that they caused the least amount of pain and distress. In this review, a comprehensive summary of the most widely used techniques to replace, reduce, and refine in experimental liver research is offered, to assess the advantages and weaknesses of available experimental liver disease models for researchers who are planning to perform animal studies in the near future.
Graph Homomorphisms and Vector Colorings

A graph vertex coloring is an assignment of labels, which are referred to as colors, such that no two adjacent vertices receive the same color. The vertex coloring problem is NP-Complete [8], and so no polynomial time algorithm is believed to exist. The notion of a graph vector coloring was introduced as an efficiently computable relaxation to the graph vertex coloring problem [7]. In [6], the authors examined the highly symmetric class of 1-walk regular graphs, characterizing when such graphs admit unique vector colorings. We present this characterization, as well as several important consequences discussed in [5, 6]. By appealing to this characterization, several important families of graphs, including Kneser graphs, Quantum Kneser graphs, and Hamming graphs, are shown to be uniquely vector colorable. Next, a relationship between locally injective vector colorings and cores is examined, providing a sufficient condition for a graph to be a core. As an immediate corollary, Kneser graphs, Quantum Kneser graphs, and Hamming graphs are shown to be cores. We conclude by presenting a characterization for the existence of a graph homomorphism between Kneser graphs having the same vector chromatic number. The necessary condition easily generalizes to Quantum Kneser graphs, simply by replacing combinatorial expressions with their quantum analogues.
Cell-Free UAV Networks With Wireless Fronthaul: Analysis and Optimization

The use of uncrewed aerial vehicles (UAVs) in cell-free networks is poised to unleash a number of new opportunities to further improve wireless networks. However, cell-free UAV networks present major challenges related to the wireless nature of access and fronthaul links. This manuscript studies the uplink of cell-free systems where users connect to UAVs, the latter devices forwarding the information to a processing point through imperfect wireless fronthaul links. Three multiple access alternatives are considered for the fronthaul, namely frequency division multiples access, spatial division multiple access, and combinations thereof. Deterministic equivalent expressions for the spectral efficiency under these fronthaul schemes and minimum mean-square error reception are derived. Then, the optimization subproblems of (a) the 3D deployment of the UAVs, (b) the user transmit powers, and (c) the UAV transmit powers, are investigated. The joint optimization of these subproblems yields superior performance, with the 3D deployment being the main source of improvement.
Wavelength dependent terahertz wave modulation based on preformed air plasma

Terahertz wave generation from laser induced air plasma is widely used due to its high electric field and broad frequency bandwidth. For further understanding of the mechanism of the terahertz wave generation in laser-induced plasma as well as the terahertz modulator base on pre-formed air plasma, the generation of terahertz radiation using an effective wavelength scaling mechanism is examined when two-color laser fields are mixed in pre-formed plasma created by synchronized 800nm laser pulse. In our experiment, the effect of preformed plasma is investigated using an orthogonal pumping geometry. With a preformed plasma, both the modulation depth of terahertz radiation energy and the change of terahertz radiation polarization increases with increasing excitation laser wavelength. We found that the terahertz modulation depth and terahertz polarization changes increase as a function of the energy of the 800nm-prepulse. Some possible reasons are discussed. We attribute the terahertz polarization rotation to additional relative phase of the two-color fields introduced by the preformed air plasma. This provides a practical way to control the polarization and energy of terahertz pulses for potential applications.
Emotions as emergent properties

In recent decades, affective scientists have begun using concepts and tools from dynamical systems theory (DST) to characterise emotional processes. This article considers how the concept of emergence might be used to develop this approach. Emotions are explicated as ‘emergent products’ that diachronically constrain the operations of their parts in virtue of feedback loops (a classical feature of nonlinear dynamical systems). The explication is shown to be broadly consistent with what is sometimes called ‘pattern’ emergence. Casting emotions as emergent patterns is shown to shed light on a major conceptual and empirical challenge emotion theorists have faced over the past century: identifying and measuring the presence of emotional episodes (Lindquist et al., 2012; Hollenstein & Lanteigne, 2014), dubbed here the ‘boundary problem’ (following Colombetti, 2014). In particular, the explication suggests seeing the emotional ‘signatures’ thought to accompany emotional episodes as fragile and context-bound: likely to hold under a relevant class of interventions (Woodward, 2005), but not without exception beyond that class. This in turn may suggest a need to significantly revise the statistical methods currently used to measure the presence of emotional ‘signatures’. The casting of emotions as emergent patterns also functions as a further case study supporting the value of ‘pattern emergence’ (Winning & Bechtel, 2019) as a powerful vehicle for characterising the objects of investigation — compound and context-sensitive — ubiquitous in the biological sciences.
A comprehensive meta-analysis reveals the key variables and scope of seed defense priming

Background When encountered with pathogens or herbivores, the activation of plant defense results in a penalty in plant fitness. Even though plant priming has the potential of enhancing resistance without fitness cost, hurdles such as mode of application of the priming agent or even detrimental effects in plant fitness have yet to be overcome. Here, we review and propose seed defense priming as an efficient and reliable approach for pathogen protection and pest management. Methods Gathering all available experimental data to date, we evaluated the magnitude of the effect depending on plant host, antagonist class, arthropod feeding guild and type of priming agent, as well as the influence of parameter selection in measuring seed defense priming effect on plant and antagonist performance. Results Seed defense priming enhances plant resistance while hindering antagonist performance and without a penalty in plant fitness. Specifically, it has a positive effect on crops and cereals, while negatively affecting fungi, bacteria and arthropods. Plant natural compounds and biological isolates have a stronger influence in plant and antagonist performance than synthetic chemicals and volatiles. Discussion This is the first meta-analysis conducted evaluating the effect of seed defense priming against biotic stresses studying both plant and pest/pathogen performance. Here, we proved its efficacy in enhancing both, plant resistance and plant fitness, and its wide range of application. In addition, we offered insight into the selection of the most suitable priming agent and directed the focus of interest for novel research.
A Digital Music-Based Mindfulness Intervention for Black Americans With Elevated Race-Based Anxiety: A Multiple-Baseline Pilot Study

Background Race-based anxiety is a substantial health issue for the Black community. Although mindfulness interventions have demonstrated efficacy for alleviating anxiety, three central barriers prevent Black Americans from accessing existing mindfulness treatments: high costs, excessive time commitments, and limited cultural relevance. There is a need for novel mindfulness interventions for the Black community that can overcome these barriers. Objective The goal of this web-based study was to examine the preliminary efficacy, feasibility, and acceptability of a novel digital music-based mindfulness intervention for middle-to-low-income Black Americans with elevated race-based anxiety. Methods This study used a nonconcurrent multiple-baseline design (n=5). The intervention featured contributions from Lama Rod Owens (a world-renowned meditation teacher and LA Times best-selling author) and Terry Edmonds (the former chief speechwriter for President Bill Clinton). We examined the effect of the intervention on state anxiety and assessed its feasibility and acceptability using quantitative and qualitative measures. Results Results revealed that administration of the intervention led to significant decreases in state anxiety (Tau-U range –0.75 to –0.38; P values<.001). Virtually all feasibility and acceptability metrics were high (ie, the average likelihood of recommending the intervention was 98 out of 100). Conclusions This study offers preliminary evidence that a digital music-based mindfulness intervention can decrease race-based anxiety in Black Americans. Future research is needed to replicate these results, test whether the intervention can elicit lasting changes in anxiety, assess mechanisms of change, and explore the efficacy of the intervention in real-world contexts.
A global stability analysis of a thin-airfoil wake

In this paper we review the problem of the wake-flow s tability for a thin airfoil by using both a locally plane-wave analysis, based on a WKBJ app roximation, and a global numerical stability analysis. The core of the instability is further l ocalized by performing a structural sensitivity analysis of the linearized Navier-Stokes operator as outli ned in [7]. In particular the sensitivity of the eigenvalue to a spatially-localized feedback from velo city to force is evaluated by using the product of the direct and adjoint global mode. It is shown, us ing a plane wave analysis, that the flow at the trailing edge is absolutely unstable for any Reyno lds number for values of the parameter m corresponding to separation of the base flow. The analysis fu rther shows that the base flow at the trailing edge is not absolutely unstable as the value of m tends to zero. The global eigenvalue analysis shows that the frequency and growth rate are very si milar to what is found with the local plane wave analysis at the trailing edge. Finally, the struc tural sensitivity analysis indicates that the wavemaker is situated just downstream of the trailing edge.
Recent advances in the application of MXenes for neural tissue engineering and regeneration

Transition metal carbides and nitrides (MXenes) are crystal nanomaterials with a number of surface functional groups such as fluorine, hydroxyl, and oxygen, which can be used as carriers for proteins and drugs. MXenes have excellent biocompatibility, electrical conductivity, surface hydrophilicity, mechanical properties and easy surface modification. However, at present, the stability of most MXenes needs to be improved, and more synthesis methods need to be explored. MXenes are good substrates for nerve cell regeneration and nerve reconstruction, which have broad application prospects in the repair of nervous system injury. Regarding the application of MXenes in neuroscience, mainly at the cellular level, the long-term in vivo biosafety and effects also need to be further explored. This review focuses on the progress of using MXenes in nerve regeneration over the last few years; discussing preparation of MXenes and their biocompatibility with different cells as well as the regulation by MXenes of nerve cell regeneration in two-dimensional and three-dimensional environments in vitro. MXenes have great potential in regulating the proliferation, differentiation, and maturation of nerve cells and in promoting regeneration and recovery after nerve injury. In addition, this review also presents the main challenges during optimization processes, such as the preparation of stable MXenes and long-term in vivo biosafety, and further discusses future directions in neural tissue engineering.
Application of H2 -based Sliding Mode Control for an Active Magnetic Bearing System

In this paper, application of Sliding Mode Control (SMC) technique for an Active Magnetic Bearing (AMB) system with varying rotor speed is considered. The gyroscopic effect and mass imbalance inherited in the system is proportional to rotor speed in which this nonlinearity effect causes high system instability as the rotor speed increases. Transformation of the AMB dynamic model into regular system shows that these gyroscopic effect and imbalance lie in the mismatched part of the system. A H2-based sliding surface is designed which bound the mismatched parts. The solution of the surface parameter is obtained using Linear Matrix Inequality (LMI). The performance of the controller applied to the AMB model is demonstrated through simulation works under various system conditions. Keywords—Active Magnetic Bearing (AMB), Sliding Mode Control (SMC), Linear Matrix Inequality (LMI), mismatched uncertainty and imbalance.
Primal and dual approaches to adjustable robust optimization

Robust optimization has become an important paradigm to deal with optimization under uncertainty. Adjustable robust optimization is an extension that deals with multistage problems. This thesis starts with a short but comprehensive introduction to adjustable robust optimization. Then the two approaches developed in this thesis are explained in detail: a primal and a dual approach. In the dual approach various duality aspects of adjustable robust optimization models are exploited which lead to new model formulations. Although these formulations are equivalent to the original models, they have a different structure which allows us to solve problems more efficiently. It even opens up the possibility to solve a type of nonlinear adjustable robust optimization models that were deemed intractable before. In the primal approach the so-called decision rules, that are used to find solutions to adjustable robust models, are improved by lifting the uncertainty set. Crucially, these richer decision rules require only little additional computational effort. Next, it is shown that there can be multiple optimal solutions for adjustable robust optimization models. Lastly, an extension to existing adjustable robust models is given in which the information used in decision rules is still inexact. Throughout the thesis the benefits of all approaches are illustrated with numerical experiments.
GSK3β Inhibition Ameliorates Atherosclerotic Calcification

Endothelial-mesenchymal transition (EndMT) drives endothelium to contribute to atherosclerotic calcification. In a previous study, we showed that glycogen synthase kinase-3β (GSK3β) inhibition induced β-catenin and reduced mothers against DPP homolog 1 (SMAD1) in order to redirect osteoblast-like cells towards endothelial lineage, thereby reducing vascular calcification in Matrix Gla Protein (Mgp) deficiency and diabetic Ins2Akita/wt mice. Here, we report that GSK3β inhibition or endothelial-specific deletion of GSK3β reduces atherosclerotic calcification. We also find that alterations in β-catenin and SMAD1 induced by GSK3β inhibition in the aortas of Apoe−/− mice are similar to Mgp−/− mice. Together, our results suggest that GSK3β inhibition reduces vascular calcification in atherosclerotic lesions through a similar mechanism to that in Mgp−/− mice.
Watching the emergence of a Fano resonance in doubly excited helium

We report on the experimental observation of the buildup of the 2s2p Fano resonance in helium in the time domain, which has been under theoretical investigation for more than a decade. The emergence of the absorption line is temporally resolved by interrupting the natural decay of the excited state via saturated strong-field ionization at a variable time delay. We compare the experimental data with full ab-initio simulations to validate the time-gating by strong-field ionization and thereby confirm the recently developed theory for the formation of Fano line-profiles.
Wide-Angle Beam Scanning Phased Array Antennas: A Review

Phased array antennas (PAAs) with flexible and agile wide-angle beam scanning (WABS) abilities have drawn rapidly increasing attentions in recent years. They have found significant applications in beyond fifth-generation (B5G) and sixth-generation (6G) wireless communications, satellite communications, sensing, etc., for their outstanding capability to achieve wide spatial coverage, enable critical frequency reuse, and improve the system capacity. In this review, we aim to investigate and discuss several challenges that hinder WABS for conventional PAAs, including the strong mutual coupling, narrow beamwidth of the element antenna, etc. We then review and summarize a variety of innovative techniques to overcome these challenges. Subsequently, we discuss and analyze potential research gaps of WABS PAAs for future emerging applications. This timely review fulfills the demand of a thorough and detailed investigation on WABS technologies for PAAs and provides detailed introduction and guidance for interested researchers and engineers.
Current Sensor Integration Issues with Wide-Bandgap Power Converters

Precise current sensing is essential for several power electronics’ protection, control, and reliability mechanisms. Even so, WBG power converters will likely struggle to develop a single current-sensing scheme to measure various types of currents due to the limited space and size of these devices, the required high sensing speed, and the high electromagnetic interference (EMI) emissions they cause. Analysis of existing current sensors was conducted in such terms with the objective of understanding the challenges associated with their integration into WBG power converters. Since each of these requirements has different design tradeoffs, it is challenging to consider one specific method of current sensing to be perfect for all situations; thus, the possibility of developing novel methods to improve the performance of these single-scheme current sensors is further explored.