Miracle-dz/UniFAR-FTUs huggingface dataset:
A Multiscale Symbolic Dynamic Entropy Analysis of Traﬃc Flow

The complexity analysis of traffic flow is important for understanding the property of traffic system. Being good at analyzing the regularity and complexity, multiscale SamEn has attracted much attention and many methods have been proposed for complexity analysis of traffic flow. However, there may exist discontinuity of the calculated entropy value which makes the regularity of the traffic system difficult to understand. The phenomenon occurs due to an inappropriate selection of the parameter r in the multiscale SamEn. Moreover, it is diﬃcult to select an appropriate r for the accurate evaluation of the complexity, which limits the application of multiscale entropy for traffic flow analysis. To solve this problem, a new entropy-based method, multiscale symbolic dynamic entropy, for evaluating the traﬃc system is proposed here. To verify the eﬀectiveness of the proposed method, traﬃc data collected from stations in diﬀerent cities are preprocessed by the proposed method. Both results of two cases show that the weekend patterns and weekday patterns are eﬀectively distinguished using the proposed method, respectively. Speciﬁcally, compared with the traditional methods including multiscale SamEn and the multiscale modiﬁed SamEn, the complexity of the corresponding traﬃc system can be better evaluated without considering the selection of r, which demonstrates the eﬀectiveness of the proposed method.
Compounding a High-Permittivity Thermoplastic Material and Its Applicability in Manufacturing of Microwave Photonic Crystals

Additive Manufacturing (AM) techniques allow the production of complex geometries unattainable through other traditional technologies. This advantage lends itself well to rapidly iterating and improving upon the design of microwave photonic crystals, which are structures with intricate, repeating features. The issue tackled by this work involves compounding a high-permittivity material that can be used to produce 3D microwave photonic structures using polymer extrusion-based AM techniques. This material was acrylonitrile butadiene styrene (ABS)-based and used barium titanate (BaTiO3) ceramic as the high-permittivity component of the composite and involved the use of a surfactant and a plasticizer to facilitate processing. Initial small amounts of the material were compounded using an internal batch mixer and studied using polymer thermal analysis techniques, such as thermogravimetric analysis, rheometry, and differential scanning calorimetry to determine the proper processing conditions. The production of the material was then scaled up using a twin-screw extruder system, producing homogeneous pellets. Finally, the thermoplastic composite was used with a screw-based, material extrusion additive manufacturing technique to produce a slab for measuring the relative permittivity of the material, as well as a preliminary 3D photonic crystal. The real part of the permittivity was measured to be 12.85 (loss tangent = 0.046) in the range of 10 to 12 GHz, representing the highest permittivity ever demonstrated for a thermoplastic AM composite at microwave frequencies.
Piloting an Evidence-Based Assessment Protocol for Incarcerated Adolescents

ABSTRACT Although evidence-based assessment is considered an essential component of evidence-based practice, few adolescents have access to evidence-based assessment. Despite experiencing high rates of mental health disorders, incarcerated justice-involved adolescents are rarely able to access evidence-based psychiatric care. In this article, we discuss the components of an evidence-based assessment protocol designed and piloted with incarcerated adolescents involved in Rhode Island’s juvenile justice system. In particular, we describe the components of our evidence-based protocol, ways in which evidence-based assessment may need to be modified when working with this population, and discuss policy and clinical implications relevant to increasing access to evidence-based assessment among incarcerated adolescents.
Blockchain as IoT Economy Enabler: A Review of Architectural Aspects

In the IoT-based economy, a large number of subjects (companies, public bodies, or private citizens) are willing to buy data or services offered by subjects that provide, operate, or host IoT devices. To support economic transactions in this setting, and to pave the way for the implementation of decentralized algorithmic governance powered by smart contracts, the adoption of the blockchain has been proposed both in scientific literature and in actual projects. The blockchain technology promises a decentralized payment system independent of (and possibly cheaper than) conventional electronic payment systems. However, there are a number of aspects that need to be considered for an effective IoT–blockchain integration. In this review paper, we start from a number of real IoT projects and applications that (may) take advantage of blockchain technology to support economic transactions. We provide a reasoned review of several architectural choices in light of typical requirements of those applications and discuss their impact on transaction throughput, latency, costs, limits on ecosystem growth, and so on. We also provide a survey of additional financial tools that a blockchain can potentially bring to an IoT ecosystem, with their architectural impact. In the end, we observe that there are very few examples of IoT projects that fully exploit the potential of the blockchain. We conclude with a discussion of open problems and future research directions to make blockchain adoption easier and more effective for supporting an IoT economy.
Introducción al análisis de sobrevida

Las primeras aplicaciones de este análisis estudiaron el tiempo desde el inicio de un tratamiento hasta la muerte, de ahí el nombre de sobrevida. Posteriormente, su aplicación se extendió a otras situaciones de interés clínico (tiempo a la reinternación, al abandono del tratamiento, al retorno laboral luego de una cirugía, etc.), por lo que una denominación más adecuada es la de análisis de tiempo al evento. Los objetivos del análisis de sobrevida son: a) estimar e interpretar la sobrevida, b) comparar la sobrevida entre distintos grupos y c) evaluar la relación de distintas variables explicativas con la sobrevida.
A Single Bout of Ultra-Endurance Exercise Reveals Early Signs of Muscle Aging in Master Athletes

Middle-aged and master endurance athletes exhibit similar physical performance and long-term muscle adaptation to aerobic exercise. Nevertheless, we hypothesized that the short-term plasticity of the skeletal muscle might be distinctly altered for master athletes when they are challenged by a single bout of prolonged moderate-intensity exercise. Six middle-aged (37Y) and five older (50Y) master highly-trained athletes performed a 24-h treadmill run (24TR). Vastus lateralis muscle biopsies were collected before and after the run and assessed for proteomics, fiber morphometry, intramyocellular lipid droplets (LD), mitochondrial oxidative activity, extracellular matrix (ECM), and micro-vascularisation. Before 24TR, muscle fiber type morphometry, intramyocellular LD, oxidative activity, ECM and micro-vascularisation were similar between master and middle-aged runners. For 37Y runners, 24TR was associated with ECM thickening, increased capillary-to-fiber interface, and an 89% depletion of LD in type-I fibers. In contrast, for 50Y runners, 24TR did not alter ECM and capillarization and poorly depleted LDs. Moreover, an impaired succinate dehydrogenase activity and functional class scoring of proteomes suggested reduced oxidative phosphorylation post-24TR exclusively in 50Y muscle. Collectively, our data support that middle-aged and master endurance athletes exhibit distinct transient plasticity in response to a single bout of ultra-endurance exercise, which may constitute early signs of muscle aging for master athletes.
Crystallization kinetics and thermodynamics of an Ag–In–Sb–Te phase change material using complementary in situ microscopic techniques

The crystallization of an amorphous Ag–In–Sb–Te (AIST) phase change material (PCM) is studied using multiple in situ imaging techniques to directly quantify crystal growth rates over a broad range of temperatures. The measurable growth rates span from ≈ 10–9 to ≈ 20 m/s. Recent results using dynamic transmission electron microscopy (TEM), a photoemission TEM technique, and TEM with sub-framed imaging are reported here and placed into the context of previous growth rate measurements on AIST. Dynamic TEM experiments show a maximum observed crystal growth rate for as-deposited films to be > 20 m/s. It is shown that crystal growth above the glass transition can be imaged in a TEM through use of subframing and a high-frame-rate direct electron detection camera. Challenges associated with the determination of temperature during in situ TEM experiments are described. Preliminary nanocalorimetry results demonstrate the feasibility of collecting thermodynamic data for crystallization of PCMs with simultaneous TEM imaging.
Vanadium and Manganese Carbonyls as Precursors in Electron-Induced and Thermal Deposition Processes

The material composition and electrical properties of nanostructures obtained from focused electron beam-induced deposition (FEBID) using manganese and vanadium carbonyl precursors have been investigated. The composition of the FEBID deposits has been compared with thin films derived by the thermal decomposition of the same precursors in chemical vapor deposition (CVD). FEBID of V(CO)6 gives access to a material with a V/C ratio of 0.63–0.86, while in CVD a lower carbon content with V/C ratios of 1.1–1.3 is obtained. Microstructural characterization reveals for V-based materials derived from both deposition techniques crystallites of a cubic phase that can be associated with VC1−xOx. In addition, the electrical transport measurements of direct-write VC1−xOx show moderate resistivity values of 0.8–1.2 × 103 µΩ·cm, a negligible influence of contact resistances and signatures of a granular metal in the temperature-dependent conductivity. Mn-based deposits obtained from Mn2(CO)10 contain ~40 at% Mn for FEBID and a slightly higher metal percentage for CVD. Exclusively insulating material has been observed in FEBID deposits as deduced from electrical conductivity measurements. In addition, strong tendencies for postgrowth oxidation have to be considered.
CONTINUITY: CONnectivity Tool with INtegration of sUbcortical regions, regIstration and visualization of TractographY

In this work, we present CONTINUITY, a novel, open-source interactive computation and visualization tool for brain connectome data. The connectome processing pipeline performs surface based processing as the main mode of operation. The automated processing includes structural-to-diffusion image co-registration, surface reconstruction for subcortical structures, as well as fiber tractography. The tool supports 3 different probabilistic methods of tractography offered by the tractography frameworks in FSL, MRtrix and DIPY. All methods employ brain and subcortical surfaces as seeds to initialize the tractography algorithms. CONTINUITY implements a friendly Graphical User Interface (GUI) to make the workflow accessible for nontechnical users. Additionally, it offers the possibility to visualize the results of the brain connectome in several interactive plot types such as a hierarchical edge bundling circle plot and over 2D/3D brain templates. This visualization tool can also be applied to connectome matrices computed with other tools and pipelines.
Joint Antenna and Device Scheduling in Full-Duplex MIMO Wireless-Powered Communication Networks

In this article, we study a joint antenna and Internet of Things device (ID) scheduling problem in the full-duplex (FD) multiple-input–multiple-output (MIMO) wireless-powered communication network (WPCN) over time-varying fading channels. We first formulate an optimization problem to maximize the average sum rate of IDs while satisfying their minimum average data rate requirements by jointly scheduling ID selection for uplink data transmission, antenna switching, and beamforming. To deal with the problem, we propose a scheduling algorithm based on Lagrangian duality and the stochastic optimization theory. The proposed scheduling algorithm necessitates solving per-time-slot problems, each of which aims at maximizing the weighted sum of the selected ID’s uplink data rate and the nonselected IDs’ harvested power from the downlink by jointly optimizing ID selection, antenna switching between uplink and downlink, and beamforming at that time slot. To solve the per-time-slot problem, we develop a joint ID selection, antenna switching, and beamforming (Joint-IAB) algorithm based on the block coordinate descent (BCD) and successive convex approximation (SCA) methods. Through simulation, we demonstrate that our scheduling algorithm with the proposed Joint-IAB algorithm provides better performance than the other scheduling algorithms while well satisfying the given minimum average data rate requirements of IDs.
Leptin Receptor Deficiency Results in Hyperphagia and Increased Fatty Acid Mobilization during Fasting in Rainbow Trout (Oncorhynchus mykiss)

Leptin is a pleiotropic hormone known for regulating appetite and metabolism. To characterize the role of leptin signaling in rainbow trout, we used CRISPR/Cas9 genome editing to disrupt the leptin receptor (LepR) genes, lepra1 and lepra2. We compared wildtype (WT) and mutant fish that were either fed to satiation or feed deprived for six weeks. The LepR mutants exhibited a hyperphagic phenotype, which led to heavier body weight, faster specific growth rate, increased viscero- and hepatosomatic indices, and greater condition factor. Muscle glycogen, plasma leptin, and leptin transcripts (lepa1) were also elevated in fed LepR mutant fish. Expression levels of several hypothalamic genes involved in feed regulation were analyzed (agrp, npy, orexin, cart-1, cart-2, pomc-a1, pomc-b). No differences were detected between fed WT and mutants except for pomc-b (proopiomelanocortin-b), where levels were 7.5-fold higher in LepR fed mutants, suggesting that pomc-b expression is regulated by leptin signaling. Fatty acid (FA) content did not statistically differ in muscle of fed mutant fish compared to WT. However, fasted mutants exhibited significantly lower muscle FA concentrations, suggesting that LepR mutants exhibit increased FA mobilization during fasting. These data demonstrate a key role for leptin signaling in lipid and energy mobilization in a teleost fish.
Novel Application of Multiscale Cross-Approximate Entropy for Assessing Early Changes in the Complexity between Systolic Blood Pressure and ECG R-R Intervals in Diabetic Rats

Cardiac autonomic neuropathy (CAN) is a common complication of diabetes mellitus, and can be assessed using heart rate variability (HRV) and the correlations between systolic blood pressure (SBP) and ECG R-R intervals (RRIs), namely baroreflex sensitivity (BRS). In this study, we propose a novel parameter for the nonlinear association between SBP and RRIs based on multiscale cross-approximate entropy (MS-CXApEn). Sixteen male adult Wistar Kyoto rats were equally divided into two groups: streptozotocin-induced diabetes and age-matched controls. RRIs and SBP were acquired in control rats and the diabetic rats at the onset of hyperglycemia and insulin-treated euglycemia to determine HRV by the ratio of low-frequency to high-frequency power (LF/HF) and Poincaré plot as SSR (SD1/SD2), BRS, and MS-CXApEn. SSR and BRS were not significantly different among the three groups. The LF/HF was significantly higher in the hyperglycemic diabetics than those in the controls and euglycemic diabetic rats. MS-CXApEn was higher in the diabetic hyperglycemic rats than the control rats from scales 2 to 10, and approached the values of controls in diabetic euglycemic rats at scales 9 and 10. Conclusions: We propose MS-CXApEn as a novel parameter to quantify the dynamic nonlinear interactions between SBP and RRIs that reveals more apparent changes in early diabetic rats. Furthermore, changes in this parameter were related to correction of hyperglycemia and could be useful for detecting and assessing CAN in early diabetes.
Ex vivo sensing of primordial follicles in ovarian tissues by spectral-domain optical coherence tomography

Minimally invasive visualization of follicles in the ovaries of adolescent and young adult (AYA) patients with cancer is a promising technique for maintaining fertility by cryopreserving follicle-rich ovarian tissues. Optical coherence tomography (OCT) using near-infrared light, which is less invasive to the follicles, is a promising imaging technique for quantifying follicle density before cryopreservation. A spectral-domain OCT system equipped with a superluminescent diode with a central wavelength of 1300 nm was applied to visualize primordial follicles with a diameter of about 20 μm, which are often found at depths of 100–1000 μm in ovarian tissue. We used a 20x immersion objective to improve lateral image resolution and reduce ghost images due to surface reflections. OCT images of 30 μm diameter glass beads mimicking primordial follicles embedded in a polyacrylamide gel containing scattering particles were visualized at the depth required for imaging the ovaries. Ovarian tissues of 3-day-old and 12-day-old mice were fixed between an originally designed hydrophobic silicone plate and a cover glass. The distribution of primordial follicles and the structure of mature follicles were visualized in ovaries of 3-day-old and 12-day-old mice, respectively. These results indicate that near-infrared OCT at a central wavelength of 1300 nm with an extended depth of light penetration can effectively visualize the structure of follicles and quantify their density at depths where follicles are abundant in ovarian tissues. Further improvements in spatial resolution and image processing are expected to accelerate the contribution to reproductive medicine in the future.
A Three-Dimensional Finite Element Analysis Model of SAW Torque Sensor with Multilayer Structure

A three-dimensional finite element analysis model of surface acoustic wave (SAW) torque sensor based on multilayer structure is proposed in this paper. Compared with the traditional saw torque sensor with quartz as piezoelectric substrate, the SAW torque sensor with multilayer structure has the advantages of fast propagation speed and high characteristic frequency. It is a very promising torque sensor, but there is very little related research. In order to successfully develop the sensor, it is essential to understand the propagation characteristics and torque sensing mode of SAW in multilayer structure. Therefore, in this study, we first established a multi-layered finite element analysis model of SAW device based on IDT/128° Y-X lithium niobate/diamond/Si (100). Then, the effects of different film thicknesses on the characteristic frequency, electromechanical coupling coefficient, s parameter, and mechanical quality factor of SAW device without changing the wavelength are analyzed. Then, based on the finite element analysis, a three-dimensional research model of a new SAW torque sensor suitable for small diameter torsion bar (d = 10 mm) is established, and the relationship between saw device deformation and torque under the condition of small torque (±40 Nm) is tested. The shape variable is introduced into the finite element analysis model of multi-layer SAW device. Finally, the relationship between saw torque sensor with multi-layer structure and torque is established by using the deformation relationship, which shows the perfect curve of sensor performance.
Modernising Orodispersible Film Characterisation to Improve Palatability and Acceptability Using a Toolbox of Techniques

Orodispersible films (ODFs) have been widely used in paediatric, geriatric and dysphagic patients due to ease of administration and precise and flexible dose adjustments. ODF fabrication has seen significant advancements with the move towards more technologically advanced production methods. The acceptability of ODFs is dependent upon film composition and process of formation, which affects disintegration, taste, texture and mouthfeel. There is currently a lack of testing to accurately assess ODFs for these important acceptability sensory perceptions. This study produced four ODFs formed of polyvinyl alcohol and sodium carboxymethylcellulose using 3D printing. These were assessed using three in vitro methods: Petri dish and oral cavity model (OCM) methods for disintegration and bio-tribology for disintegration and oral perception. Increasing polymer molecular weight (MW) exponentially increased disintegration time in the Petri dish and OCM methods. Higher MW films adhered to the OCM upper palate. Bio-tribology analysis showed that films of higher MW disintegrated quickest and had lower coefficient of friction, perhaps demonstrating good oral perception but also stickiness, with higher viscosity. These techniques, part of a toolbox, may enable formulators to design, test and reformulate ODFs that both disintegrate rapidly and may be better perceived when consumed, improving overall treatment acceptability.
An Exploration Study of Multi-stage Conversational Passage Retrieval: Paraphrase Query Expansion and Multi-view Point-wise Ranking

In this paper, we report our methods and experiments for the TREC Conversational Assistance Track (CAsT) 2021. In this work, We aim to improve the conversational information seeking system by reforming the modules in the existing multi-stage conversational search pipeline. In the first-stage document retrieval, we proposed the Paraphrase Query Ex-pansion (PQE), which is adapted to the less-training-data scenario like CAsT. As for the second-stage re-ranking, we adopt the T5 point-wise ranking model with multi-view learning framework (monoT5M) to avoid the underlying overfitting problems. To further elucidate the effectiveness of our proposed methods, we also report the ablation studies of our proposed modules.
Improving the Accuracy-Robustness Trade-Off for Dual-Domain Adversarial Training

While Adversarial Training remains the standard in improving robustness to adversarial attack, it often sacriﬁces accuracy on natural (clean) samples to a signiﬁcant extent. Dual-domain training, optimizing on both clean and adversarial objectives, can help realize a better trade-off between clean accuracy and robustness. In this paper, we develop methods to improve dual-domain training for large adversarial perturbations and complex datasets. We ﬁrst demonstrate that existing meth-ods suffer from poor performance in this setting, due to a poor training procedure and overﬁtting to a particular attack. Then, we develop novel meth-ods to address these issues. First, we show that adding KLD regularization to the dual training objective mitigates this overﬁtting and achieves a better trade-off, on CIFAR-10 and a 10-class subset of ImageNet. Then, inspired by domain adaptation, we develop a new normalization technique, Dual Batch Normalization, to further improve accuracy. Combining these two strategies, our model sets a new state of the art in trade-off performance for dual-domain adversarial training.