Miracle-dz/UniFAR-FTUs huggingface dataset:
Fabrication of Micro-Structured Polymer by Micro Injection Molding Based on Precise Micro-Ground Mold Core

Precise micro-grinding machining was proposed to fabricate regular and controllable micro-grooved array structures on the surface of mold cores to realize the mass production and manufacturing of micro-structured polymer components by micro injection molding in this paper. First, the 3D topographies and section profiles of micro-ground mold cores and micro-formed polymers with different micro-structure parameters were presented. Then, the surface roughness of mold cores and polymers were compared. Next, the relationships between machining accuracy of mold core ground by micro-grinding and filling rates of micro-structured polymer formed by micro injection molding were investigated. Finally, the influences of micro injection molding parameters on the filling rate of micro-structures polymer were investigated. It is shown that the micro-structured polymer can be effectively and rapidly fabricated using the proposed method. The experimental results indicate the highest form accuracy of the micro-grooved mold core and the filling rate of micro-structured polymer can reach to 4.05 µm and 99.30%, respectively. It is found that the filling rate of the micro-structured polymer roughly increased with increasing machining accuracy of the mold core. The injection pressure had the greatest influence on the filling rate of the injection formed polymer, while the melt temperature had the least influence.
The graph topology for linear plants with applications to nonlinear robust stabilization

The graph topology is defined for the set of finite-dimensional linear time-varying plants that are internally stabilizable by output feedback. This follows some earlier results of M. Vidyasagar et al. (1982) on time-invariant systems. Feedback connections of linear time-varying plants and general nonlinear time-varying controllers are considered, and it is shown that the graph topology is the weakest topology in which feedback stabilization is a robust property. Using this result, necessary and sufficient conditions for robust stabilizability of families of linear time-varying plants with parametric uncertainty are derived. >
Conditionals, supposition, and euthyphro

Penultimate draft. The final version is to appear in Inquiry in a symposium on Williamson's Suppose and Tell : please cite the final version if possible. Abstract Williamson proposes that a "suppositional procedure" is a central heuristic we use to evaluate the truth of conditionals, though he also argues that this method often leads us astray. An alternative approach to the link between supposition and conditionals is to claim that we are guided by our antecedent conditional judgements in our supposing, and in particular in our determining which things follow from an initial supposition. This alternative explanation of the close link between conditionals and supposition is developed and compared to Williamson's proposal. Suppose and Tell is a rich book, full of provocative arguments, and it leads the charge in revitalising a material-conditional account of indicative conditionals, as well as a strict-conditional account of counterfactual conditionals. It does so in tandem with a powerful error-theory: any rejection of an indicative conditional with a false antecedent, for example, is an error, and it is an error even though our primary heuristic that guides our acceptance and rejection of conditionals often tells us to reject those indicatives. 1 It comes during an explosion of important and exciting work on conditionals, and it will shape the questions philosophers ask about conditionals, the sources of evidence they will feel compelled to take notice of, and the sense of the philosophical landscape writers on conditionals will share.
TSLP and HMGB1: Inflammatory Targets and Potential Biomarkers for Precision Medicine in Asthma and COPD

The airway epithelium, through pattern recognition receptors expressed transmembrane or intracellularly, acts as a first line of defense for the lungs against many environmental triggers. It is involved in the release of alarmin cytokines, which are important mediators of inflammation, with receptors widely expressed in structural cells as well as innate and adaptive immune cells. Knowledge of the role of epithelial cells in orchestrating the immune response and mediating the clearance of invading pathogens and dead/damaged cells to facilitate resolution of inflammation is necessary to understand how, in many chronic lung diseases, there is a persistent inflammatory response that becomes the basis of underlying pathogenesis. This review will focus on the role of pulmonary epithelial cells and of airway epithelial cell alarmins, in particular thymic stromal lymphopoietin (TSLP) and high mobility group box 1 (HMGB1), as key mediators in driving the inflammation of chronic lung diseases, such as asthma and chronic obstructive pulmonary disease (COPD), evaluating the similarities and differences. Moreover, emerging concepts regarding the therapeutic role of molecules that act on airway epithelial cell alarmins will be explored for a precision medicine approach in the context of pulmonary diseases, thus allowing the use of these molecules as possible predictive biomarkers of clinical and biological response.
Application of Laser Velocimetry for Characterization of Confined Swirling Flow

A two-component LDV was used in a cold flow dump combustor model to obtain detailed mean and turbulence data for both swirling and nonswirling inlet flows. Large samples were collected to resolve the second and third-order products of turbulent fluctuations with good accuracy. Particle interarrival time weighting was used to remove velocity bias from the data. The swirling flows, with and without vortex breakdown, exhibited significantly different mean flow and turbulent field behavior. A numerical scheme with the k–e closure model was used to predict the flow fields. Comparison of the numerical and experimental results showed that the k–e turbulence model is inadequate in representing the complex turbulent structure of confined swirling flows.
An Intervention on Anxiety Symptoms in Moderate Alzheimer’s Disease through Virtual Reality: A Feasibility Study and Lessons Learned

(1) Background: Although cognitive impairment is considered the core deficit of dementia, anxiety disorders also have a negative influence on the social and daily life of the affected population. We have explored the exposure of relaxing scenarios in immersive Virtual Reality (iVR) as an intervention strategy for people with moderate Alzheimer’s disease. (2) Methods: Three participants were recruited from a day center to participate in a five-week study, which included a Pre- and Post-evaluation with the Montreal Cognitive Assessment (MoCA), Neuropsychiatric Inventory-Questionnaire (NPI-Q), Clinical Dementia Rating Scale (CDR), Global Deterioration Scale (GDS), Hamilton Anxiety Rating Scale (HARS), State-Trait Anxiety Inventory (STAI), and the anxiety subdomain of the Neuropsychiatric Inventory (NPI). Participants’ heart rate, oxygen saturation, arterial pressure, and respiratory rate were also monitored during intervention sessions. Three virtual scenarios from Nature Treks VR were used as the intervention over three weeks (a total of nine sessions). (3) Results: Post-intervention anxiety assessment showed a light reduction in psychological anxiety in the HARS questionnaire. A light reduction in heart rate was also observed during the exposure to iVR. (4) Discussion: The use of virtual scenarios was a satisfactory experience for all the participants. Preliminary data point to a relaxing effect of iVR scenarios and a potential reduction in psychological anxiety, but further research is required to confirm the efficacy of the intervention.
First-Principles Study of Structural and Electronic Properties of Monolayer PtX2 and Janus PtXY (X, Y = S, Se, and Te) via Strain Engineering

In this work, the structural parameters and electronic properties of PtX2 and Janus PtXY (X, Y = S, Se, and Te) are studied based on the density functional theory. The phonon spectra and the Born criteria of the elastic constant of these six monolayers confirm their stability. All PtX2 and Janus PtXY monolayers show an outstanding stretchability with Young’s modulus ranging from 61.023 to 82.124 N/m, about one-fifth that of graphene and half that of MoS2, suggesting highly flexible materials. Our first-principles calculations reveal that the pristine PtX2 and their Janus counterparts are indirect semiconductors with their band gap ranging from 0.760 to 1.810 eV at the Perdew–Burke–Ernzerhof level (1.128–2.580 eV at the Heyd–Scuseria–Ernzerhof level). By applying biaxial compressive and tensile strain, the electronic properties of all PtX2 and Janus PtXY monolayers are widely tunable. Under small compressive strain, PtX2 and Janus PtXY structures remain indirect semiconductors. PtTe2, PtSeTe, and PtSTe monolayers undergo a semiconducting to metallic transition when the strain reaches −6, −8, and −10%, respectively. Interestingly, there is a transition from the indirect semiconductor to a quasi-direct one for all PtX2 and Janus PtXY monolayers when the tensile strain is applied.
Modeling of Microscale Gas Flows in Transition Regime Part I: Flow over Backward Facing Steps

Design of thermal management solutions for future nanoscale electronics or photonics devices will require knowledge of flow and transport through micron-scale ducts. This article concentrates on a typical flow process, namely flow over a backward-facing step with pressure boundary conditions at inlet and exit. Discrete simulation Monte Carlo (DSMC) is used as the simulation tool. An IP method is used to separate the macroscopic velocity from the molecular velocity, thus reducing statistical noise as typical in DSMC calculation of low-speed flows. Simulation is conducted for Re of 0.03 to 0.64, Ma of 0.013 to 0.083, and Kn of 0.24 to 4.81. For these parameter values no recirculating region is observed, and the high heat flux associated with reattachment is also absent.
Modeling the CO2 Sequestration Convection Problem Using the Lattice Boltzmann Method

This paper presents an investigation of the density-driven problem that rises during the CO2 sequestration into saline aquifer. The lattice Boltzmann method (LBM) is implemented in a way to solve this mixing problem (the brine problem along with the solute transport). The CO2-brine interface was located at the top of the considered domain. Different Rayleigh numbers were used in order to investigate this problem. When Rayleigh number is low, we got steady-state concentration contours describing a Rayleigh-Benard type of convection. Moreover, when the Rayleigh number was selected to be big enough, we observe that the system is less stable and a convective fingering is initiated. This instability is caused by a higher density difference between the brine and the sequestrated CO2. Note here that the turbulence is not taken into account in the study. After the onset this convective instability, the brine with a high CO2 concentration migrates down into the porous medium. This study is based on a statistical LBM theory without assuming periodicity in any directions and without considering any type of disturbances in order to turnon the instability behavior.
Spatial Index Structures for Modern Storage Devices: A Survey

To optimize the processing of spatial queries, there is an increasing interest in combining spatial index structures with modern storage devices like flash-based Solid State Drives, PCM, and 3D Xpoint. These devices have several advantages compared to classical Hard Disk Drives, such as lower power consumption, and faster reads and writes. However, modern storage devices have changed the paradigm of data management because of their intrinsic characteristics, such as asymmetric read and write costs. Intending to exploit the benefits of modern storage devices, the development of spatial index structures for these devices has been an emerging research topic with recent and constant advances in the literature. This includes the adaptation of existing spatial index structures like the R-tree, or even the design of innovative structures. In this article, we present a comprehensive survey that highlights the key ideas, compares the main characteristics, and discusses the advantages and disadvantages of spatial index structures for modern storage devices. Further, we study how experimental evaluations have been conducted to empirically compare these structures. Finally, we discuss challenges and identify potential future trends when indexing spatial data in this era of modern storage devices.
Exosomal LncRNAs in Gastrointestinal Cancer: Biological Functions and Emerging Clinical Applications

Simple Summary Exosomes are nanosized vesicles secreted by living cells and exist in biological fluids. Exosomes contain various bioactive molecules, including proteins, nucleic acids, and lipids, which can reflect the pathophysiological state of donor cells. In recent years, long non-coding RNAs (lncRNAs) in exosomes have attracted wide attention in cancer research. Exosomal lncRNAs play important roles in gastrointestinal cancer progression. Blood samples-derived exosomal lncRNAs also exhibit great potential to serve as important indicators of liquid biopsy, thus providing a novel diagnosis strategy for gastrointestinal cancer. In addition, exosomes-mediated several lncRNAs delivery can exert anti-tumor effects. The aim of this review article is to summarize the recent work conducted in this field and evaluate the opportunities and challenges in utilizing exosomal lncRNAs for the diagnostic and therapeutic purposes of gastrointestinal cancer in the clinical setting. Abstract Due to the lack of specific and effective biomarkers and therapeutic targets, the early diagnosis and treatment of gastrointestinal cancer remain unsatisfactory. As a type of nanosized vesicles derived from living cells, exosomes mediate cell-to-cell communication by transporting bioactive molecules, thus participating in the regulation of many pathophysiological processes. Recent evidence has revealed that several long non-coding RNAs (lncRNAs) are enriched in exosomes. Exosomes-mediated lncRNAs delivery is critically involved in various aspects of gastrointestinal cancer progression, such as tumor proliferation, metastasis, angiogenesis, stemness, immune microenvironment, and drug resistance. Exosomal lncRNAs represent promising candidates to act as the diagnosis biomarkers and anti-tumor targets. This review introduces the major characteristics of exosomes and lncRNAs and describes the biological functions of exosomal lncRNAs in gastrointestinal cancer development. The preclinical studies on using exosomal lncRNAs to monitor and treat gastrointestinal cancer are also discussed, and the opportunities and challenges for translating them into clinical practice are evaluated.
On the linear span of the projections in certain simple C*-algebras

In this paper we show that if a C*-algebra A admits a certain 3 × 3 matrix decomposition, then every commutator in A can be written as a linear combination of at most 84 projections in A. In certain C*-algebras, this is sufficient to allow us to show that every element is a linear combination of a fixed finite number of projections from the algebra.
Role of Uric Acid in Vascular Remodeling: Cytoskeleton Changes and Migration in VSMCs

The mechanisms by which hyperuricemia induces vascular dysfunction and contributes to cardiovascular disease are still debated. Phenotypic transition is a property of vascular smooth muscle cells (VSMCs) involved in organ damage. The aim of this study was to investigate the effects of uric acid (UA) on changes in the VSMC cytoskeleton, cell migration and the signals involved in these processes. MOVAS, a mouse VSMC line, was incubated with 6, 9 and 12 mg/dL of UA, angiotensin receptor blockers (ARBs), proteasome and MEK-inhibitors. Migration property was assessed in a micro-chemotaxis chamber and by phalloidin staining. Changes in cytoskeleton proteins (Smoothelin B (SMTB), alpha-Smooth Muscle Actin (αSMA), Smooth Muscle 22 Alpha (SM22α)), Atrogin-1 and MAPK activation were determined by Western blot, immunostaining and quantitative reverse transcription PCR. UA exposition modified SMT, αSMA and SM22α levels (p < 0.05) and significantly upregulated Atrogin-1 and MAPK activation. UA-treated VSMCs showed an increased migratory rate as compared to control cells (p < 0.001) and a re-arrangement of F-actin. Probenecid, proteasome inhibition and ARBs prevented the development of dysfunctional VSMC. This study shows, for the first time, that UA-induced cytoskeleton changes determine an increase in VSMC migratory rate, suggesting UA as a key player in vascular remodeling.
Effect of Pre-Storage CO2 Treatment and Modified Atmosphere Packaging on Sweet Pepper Chilling Injury

The effect of 10% CO2 pre-storage treatment for 12, 24, and 48 h alongside modified atmosphere packaging (MAP) on chilling injury was determined in this study. This study found significant interactions between chilling injuries and cell membrane damage indicators. The results show that chilling injuries can be somewhat reduced by the use of CO2 treatment for sweet peppers. It was noticed that the fruit’s respiration rate increased as the treatment duration increased immediately after the treatments, while the resultant did not affect the ethylene production rate, electrolyte leakage, or malondialdehyde. Similarly, after cold storage and on the final day, no really significant differences were shown in all those parameters except for the weight loss rate, chilling injury, calyx browning, and firmness, which were at the poorest state in the control group. Of all the treatments in this study, MAP appeared to be the best treatment, and preference may be given to the 24 h treatment of pretreated fruits. Weight loss, firmness, calyx browning, and chilling injury were maintained best in MAP due to the presence of CO2 and high humidity.
Diffusion and reaction caused by point catalysts

A generalized parabolic partial differential equation is studied with systems of impulse functions as the coefficients of the nonlinear term (varying medium). The latter are interpreted as moving point catalysts in a reaction-diffusion system. The existence of a unique solution in an appropriate space of continuous functions is established (initial value problem). The particular case where catalysts are given by the weighted atoms of a stable random measure and migrate according to one-dimensional stable stochastic processes is discussed in detail. Solutions to this nonlinear equation are constructed in a random medium that are homogeneous (in distribution) and ergodic with respect to the spatial shift.
Markov chain Monte Carlo Estimation of Classical and Dynamic Switching and Mixture Models

Bayesian estimation of a very general model class, where the distribution of the observations depends on a latent process taking values in a discrete state space, is discussed in this article. This model class covers finite mixture modeling, Markov switching autoregressive modeling, and dynamic linear models with switching. The consequences the unidentifiability of this type of model has on Markov chain Monte Carlo (MCMC) estimation are explicitly dealt with. Joint Bayesian estimation of all latent variables, model parameters, and parameters that determine the probability law of the latent process is carried out by a new MCMC method called permutation sampling. The permutation sampler first samples from the unconstrained posterior–which often can be done in a convenient multimove manner–and then applies a permutation of the current labeling of the states of the latent process. In a first run, the random permutation sampler used selected the permutation randomly. The MCMC output of the random permutation sampler is explored to find suitable identifiability constraints. In a second run, the permutation sampler was used to sample from the constrained posterior by imposing identifiablity constraints. This time a suitable permutation is applied if the identifiability constraint is violated. For illustration, two detailed case studies are presented, namely finite mixture modeling of fetal lamb data and Markov switching autoregressive modeling of the U.S. quarterly real gross national product data.
Mountain Tree Species Mapping Using Sentinel-2, PlanetScope, and Airborne HySpex Hyperspectral Imagery

Europe’s mountain forests, which are naturally valuable areas due to their high biodiversity and well-preserved natural characteristics, are experiencing major alterations, so an important component of monitoring is obtaining up-to-date information concerning species composition, extent, and location. An important aspect of mapping tree stands is the selection of remote sensing data that vary in temporal, spectral, and spatial resolution, as well as in open and commercial access. For the Tatra Mountains area, which is a unique alpine ecosystem in central Europe, we classified 13 woody species by iterative machine learning methods using random forest (RF) and support vector machine (SVM) algorithms of more than 1000 polygons collected in the field. For this task, we used free Sentinel-2 multitemporal satellite data (10 m pixel size, 12 spectral bands, and 21 acquisition dates), commercial PlanetScope data (3 m pixel size, 8 spectral bands, and 3 acquisitions dates), and airborne HySpex hyperspectral data (2 m pixel size, 430 spectral bands, and a single acquisition) with fusion of the data of topographic derivatives based on Shuttle Radar Topography Mission (SRTM) and airborne laser scanning (ALS) data. The iterative classification method achieved the highest F1score with HySpex (0.95 RF; 0.92 SVM) imagery, but the multitemporal Sentinel-2 data cube, which consisted of 21 scenes, offered comparable results (0.93 RF; 0.89 SVM). The three images of the high-resolution PlanetScope produced slightly less accurate results (0.89 RF; 0.87 SVM).
A Prospect to Ameliorate Affective Symptoms and to Enhance Cognition in Long COVID Using Auricular Transcutaneous Vagus Nerve Stimulation

Long COVID, the postviral disorder caused by COVID-19, is expected to become one of the leading causes of disability in Europe. The cognitive consequences of long COVID have been described as “brain fog” and characterized by anxiety and depression, and by cognitive deficits. Long COVID is assumed to be a complex condition arising from multiple causes, including persistent brainstem dysfunction and disrupted vagal signaling. We recommend the potential application of auricular transcutaneous vagus nerve stimulation (atVNS) as an ADD-ON instrument to compensate for the cognitive decline and to ameliorate affective symptoms caused by long COVID. This technique enhances vagal signaling by directly activating the nuclei in the brainstem, which are hypoactive in long COVID to enhance mood and to promote attention, memory, and cognitive control—factors affected by long COVID. Considering that atVNS is a non-pharmacological intervention, its ADD-ON to standard pharmaceutical agents will be useful for non-responders, making of this method a suitable tool. Given that atVNS can be employed as an ecological momentary intervention (EMI), we outline the translational advantages of atVNS in the context of accelerating the cognitive and affective recovery from long COVID.