Miracle-dz/UniFAR-FTUs huggingface dataset:
Dispersion of passive tracers in the direct enstrophy cascade: Experimental observations

The paper reports a statistical analysis of the separation of pairs in the enstrophy cascade, in a two-dimensional flow. The flow is produced experimentally, using electromagnetic forcing. Two regimes of separation are found. At early times (i.e., within two integral times) the separation process is exponential, following Lin’s law [J. T. Lin, J. Atmos. Sci. 29, 394 (1972)]. In this range of time, the probability density functions (PDFs) of separations are self-similar in time, developing stretched exponential tails, and one may define a Lagrangian correlation time. Above two integral times, an algebraic regime takes place, with exponential tails for the PDFs of the separations, and self-similar Lagrangian correlation functions. The present work thus confirms the existence of two regimes, by analyzing a number of statistical quantities including the Lagrangian PDF and the temporal Lagrangian correlation functions which so far, were left undetermined for the Batchelor regime.
Aerodynamic levitation of laser-heated solids in gas jets

Solid spheres were aerodynamically levitated in gas jets and laser heated to temperatures above 2000 K. Stable levitation in a supersonic jet from a 0.081‐cm nozzle was demonstrated with 0.03–0.20 g, 0.24–0.47‐cm‐diam specimens at a height between 0.7–2.0 cm above the nozzle and ambient pressures between 1.1–18 Torr. A model of supersonic jet levitation accurately predicts height vs pressure over the full range of conditions that were investigated. The efficiency with which jet momentum is converted into levitation force decreases with the jet:specimen diameter ratio and jet Reynolds number. The rate of jet spreading with distance from the nozzle deduced from levitation experiments agrees with that measured by pitot tube traverses of the jet. Pitot tube pressure measurements also reveal a transition from laminar to turbulent supersonic jet flow at nozzle Reynolds numbers just above the maximum values at which stable levitation is observed. Laser heating reduces the jet momentum required for levitation at a given height and increases levitation stability. In experiments with subsonic jets, the required jet momentum flow rate exceeds the specimen weight by ∼2/CD, where CD is the specimen drag coefficient at its terminal free‐fall speed under the ambient conditions. Exploratory studies of laser‐heated liquid levitation are also reported.
Identification of Key Genes Induced by Different Potassium Levels Provides Insight into the Formation of Fruit Quality in Grapes

Inadequate potassium (K) availability is a common abiotic stress that limits the growth and quality of fruit trees. Few studies have investigated the physiological and molecular responses of grapes at different potassium levels. In this study, an integrated approach was developed for grapevines grown at four different potassium fertilization levels [0 (K0-CK), 150 (K150), 300 (K300), and 450 (K450) g/plant] in combination with metabolite measurements and transcript analysis. The results showed that different K levels affected the accumulation of sugars and anthocyanins in the fruit. At 78 days after bloom (DAB), the K150, K300, and K450 treatments increased soluble sugar content by 37.39%, 31.10% and 32.59%, respectively, and anthocyanin content by 49.78%, 24.10%, and 13.06%, respectively, compared to K0. Weighted gene co-expression network analysis (WGCNA) of DEGs identified a network of 11 grapevines involved. During fruit development, potassium application promoted the accumulation of anthocyanins and sugars in fruit by regulating the up-regulation of GST, AT, UFGT and SPS, HT, PK gene expressions. These results suggest that potassium deficiency inhibits anthocyanin and sugar metabolism. In addition, it promotes the up-regulation of KUP expression, which is the main cause of K accumulation in fruits. Together, our data revealed the molecular mechanism in response to different K levels during fruit quality formation and provides the scientific foundation for the improvement of fruit quality by adding K fertilizer.
Ultrasound imaging of the mouse pancreatic duct using lipid microbubbles

Research requiring the murine pancreatic duct to be imaged is often challenging due to the difficulty in selectively cannulating the pancreatic duct. We have successfully catheterized the pancreatic duct through the common bile duct in severe combined immune deficient (SCID) mice and imaged the pancreatic duct with gas filled lipid microbubbles that increase ultrasound imaging sensitivity due to exquisite scattering at the gas/liquid interface. A SCID mouse was euthanized by CO2, a midline abdominal incision made, the common bile duct cut at its midpoint, a 2 cm, 32 gauge tip catheter was inserted about 1 mm into the duct and tied with suture. The duodenum and pancreas were excised, removed in toto, embedded in agar and an infusion pump was used to instill normal saline or lipid-coated microbubbles (10 million / ml) into the duct. B-mode images before and after infusion of the duct with microbubbles imaged the entire pancreatic duct (~ 1 cm) with high contrast. The microbubbles were cavitated by high mechanical index (HMI) ultrasound for imaging to be repeated. Our technique of catheterization and using lipid microbubbles as a contrast agent may provide an effective, affordable technique of imaging the murine pancreatic duct; cavitation with HMI ultrasound would enable repeated imaging to be performed and clustering of targeted microbubbles to receptors on ductal cells would allow pathology to be localized accurately. This research was supported by the Experimental Mouse Shared Service of the AZ Cancer Center (Grant Number P30CA023074, NIH/NCI and the GI SPORE (NIH/NCI P50 CA95060).
Statistical Depth for Text Data: An Application to the Classification of Healthcare Data

This manuscript introduces a new concept of statistical depth function: the compositional D-depth. It is the first data depth developed exclusively for text data, in particular, for those data vectorized according to a frequency-based criterion, such as the tf-idf (term frequency–inverse document frequency) statistic, which results in most vector entries taking a value of zero. The proposed data depth consists of considering the inverse discrete Fourier transform of the vectorized text fragments and then applying a statistical depth for functional data, D. This depth is intended to address the problem of sparsity of numerical features resulting from the transformation of qualitative text data into quantitative data, which is a common procedure in most natural language processing frameworks. Indeed, this sparsity hinders the use of traditional statistical depths and machine learning techniques for classification purposes. In order to demonstrate the potential value of this new proposal, it is applied to a real-world case study which involves mapping Consolidated Framework for Implementation and Research (CFIR) constructs to qualitative healthcare data. It is shown that the DDG-classifier yields competitive results and outperforms all studied traditional machine learning techniques (logistic regression with LASSO regularization, artificial neural networks, decision trees, and support vector machines) when used in combination with the newly defined compositional D-depth.
Deep Multitask Learning by Stacked Long Short-Term Memory for Predicting Personalized Blood Glucose Concentration

The adverse glycemic events triggered by the inaccurate insulin infusion in Type I diabetes (T1D) can lead to fatal complications. Predicting blood glucose concentration (BGC) based on clinical health records is critical for control algorithms in the artificial pancreas (AP) and aiding in medical decision support. This paper presents a novel deep learning (DL) model incorporating multitask learning (MTL) for personalized blood glucose prediction. The network architecture consists of shared and clustered hidden layers. Two layers of stacked long short-term memory (LSTM) form the shared hidden layers that learn generalized features from all subjects. The clustered hidden layers comprise two dense layers adapting to the gender-specific variability in the data. Finally, the subject-specific dense layers offer additional fine-tuning to personalized glucose dynamics resulting in an accurate BGC prediction at the output. OhioT1DM clinical dataset is used for the training and performance evaluation of the proposed model. A detailed analytical and clinical assessment have been performed using root mean square (RMSE), mean absolute error (MAE), and Clarke error grid analysis (EGA), respectively, which demonstrates the robustness and reliability of the proposed method. Consistently leading performance has been achieved for 30- (RMSE = 16.06 <inline-formula><tex-math notation="LaTeX">$\pm$</tex-math></inline-formula> 2.74, MAE = 10.64 <inline-formula><tex-math notation="LaTeX">$\pm$</tex-math></inline-formula> 1.35), 60- (RMSE = 30.89 <inline-formula><tex-math notation="LaTeX">$\pm$</tex-math></inline-formula> 4.31, MAE = 22.07 <inline-formula><tex-math notation="LaTeX">$\pm$</tex-math></inline-formula> 2.96), 90- (RMSE = 40.51 <inline-formula><tex-math notation="LaTeX">$\pm$</tex-math></inline-formula> 5.16, MAE = 30.16 <inline-formula><tex-math notation="LaTeX">$\pm$</tex-math></inline-formula> 4.10), and 120-minute (RMSE = 47.39 <inline-formula><tex-math notation="LaTeX">$\pm$</tex-math></inline-formula> 5.62, MAE = 36.36 <inline-formula><tex-math notation="LaTeX">$\pm$</tex-math></inline-formula> 4.54) prediction horizon (PH). In addition, the EGA analysis confirms the clinical feasibility by maintaining more than 94% BGC predictions in the clinically safe zone for up to 120-minute PH. Moreover, the improvement is established by benchmarking against the state-of-the-art statistical, machine learning (ML), and deep learning (DL) methods.
Modeling Irradiation-Induced Degradation for 4H-SiC Power MOSFETs

In this article, we proposed a comprehensive model for predicting the degradation of SiC MOSFETs after gamma-ray irradiation. It is experimentally founded that SiC MOSFETs exhibit different degradation behaviors under gate bias (i.e., <inline-formula> <tex-math notation="LaTeX">${V}_{\text {GS}} =15$ </tex-math></inline-formula> V and <inline-formula> <tex-math notation="LaTeX">${V}_{\text {DS}} $ </tex-math></inline-formula> = 0 V) and drain bias (i.e., <inline-formula> <tex-math notation="LaTeX">${V}_{\text {GS}} $ </tex-math></inline-formula> = 0 V and <inline-formula> <tex-math notation="LaTeX">${V}_{\text {DS}} =400$ </tex-math></inline-formula> V) in terms of threshold voltage (<inline-formula> <tex-math notation="LaTeX">${V}_{\text {TH}}$ </tex-math></inline-formula>) and ON-resistance (<inline-formula> <tex-math notation="LaTeX">${R}_{\text {ds}, \text{ON}}$ </tex-math></inline-formula>). TCAD simulation shows that gate bias causes a high electric field in gate oxide above the MOS channel region, while drain bias generates relatively lower electric field in gate oxide around near-channel region. The differences in electric field under gate bias and drain bias lead to different hole yields and charge accumulation in gate oxide, which is the underlying physical mechanism for their different degradation behaviors. <inline-formula> <tex-math notation="LaTeX">${V}_{\text {TH}}$ </tex-math></inline-formula> is chosen as the parameter to quantify the accumulated charges in gate oxide and further predict irradiation-induced degradation. The relationship between the variation of threshold voltage (<inline-formula> <tex-math notation="LaTeX">${\Delta} {V}_{\text {TH}}$ </tex-math></inline-formula>) and the total ionizing doses (TIDs) under both gate and drain bias is formulated and validated. Comparison among measured data, TCAD simulation, and model prediction shows that the maximum prediction error is lower than 0.08 V, which proves the rationale and accuracy of the proposed degradation model. In addition, the two submodels for gate bias and drain bias are unified as one according to the time dependence effect (TDE) for TID irradiation. The proposed model could be useful to predict the degradation and/or lifetime of SiC MOSFETs in irradiation environments.
Study of carbon pellet ablation in ECR-heated W7-AS plasmas

The ablation of carbon pellets injected into ECR-heated plasmas of Wendelstein 7-AS (W7-AS) has been investigated using a photographic technique with the aim of studying features of the ablation process in stellarator plasmas. The ablation rate profiles were measured assuming a proportionality of the C II radiation and the ablation rate. This assumption was confirmed experimentally and by simulations performed by a quasi-three-dimensional code. The fraction of continuum radiation, which is detected together with the C II line radiation (when using the light filters with finite spectral width), did not affect these measurements.No significant drifts of pellet clouds in the toroidal, poloidal and radial directions were observed in the C II line (723 nm) emission. From fast electron temperature measurements (Δt = 10 µs) using ECE diagnostics, no indications of a pre-cooling wave were found.A difference between the ablation rates for discharges with low and high plasma density, which lies beyond the error bars, was observed. A specific zone of enhanced ablation was detected at the plasma periphery at high density. The appearance of such ablation enhancement, points to the existence of an additional local heat flux. However, the mechanism that could explain the enhanced ablation phenomena at high plasma densities remains unclear.
High–Performance Biscrolled Ni–Fe Yarn Battery with Outer Buffer Layer

The increasing demand for portable and wearable electronics has promoted the development of safe and flexible yarn–based batteries with outstanding electrochemical properties. However, achieving superior energy storage performance with a high active material (AM) load and long cycle life with this device format remains a challenge. In this study, a stable and rechargeable high–performance aqueous Ni–Fe yarn battery was constructed via biscrolling to embed AMs within helical carbon nanotube (CNT) yarn corridors. Owing to the high load of charge storage nanoparticles (NPs; above 97 wt%) and the outer neat CNT layer, the buffered biscrolled Ni–Fe yarn battery demonstrates excellent linear capacity (0.053 mAh/cm) and cycling stability (60.1% retention after 300 charge/discharge cycles) in an aqueous electrolyte. Moreover, our flexible yarn battery exhibits maximum energy/power densities of 422 mWh/cm3 and 7535 mW/cm3 based on the total volume of the cathode and anode, respectively, which exceed those reported for many flexible Ni–Fe batteries. Thus, biscrolled Ni–Fe yarn batteries are promising candidates for next–generation conformal energy solutions.
Support Vector Machine Parameters Optimization for 500 kV Long OHTL Fault Diagnosis

Faults can seriously damage high-voltage (HV) power systems, particularly if they occur on the long overhead transmission line (OHTL) that connects the nuclear power plant (NPP) to the electrical grid. Finding OHTL problems quickly and accurately is essential for the economy, safety, and dependability of the HV power systems. It is essential to pinpoint the problematic phase to avoid unneeded power outages. Thus, one of the most crucial research challenges is now how to identify, classify, and locate OHTL faults. In this study, transient current with high frequency oscillations that arise immediately after a defect at the sending end is investigated in a single-circuit, single-side fed Egyptian 500-kV HV long OHTL. Asymmetric and symmetric faults and locations are also represented in the Alternative Transients Program-Electro Magnetic Transients Program (ATP/EMTP) simulation model under varying fault resistance and inception angles. The proposed solution in this paper is an Optimized Support Vector Machine (OSVM), whose characteristics are optimized via a mutant particle swarm optimization (MPSO) method to detect 500 kV long OHTL faults. The localizer model is also built for practical applications, including power system noise contaminating fault signals. The findings prove that the suggested approach locates the fault in 0.012 seconds from the start of the event, with a 0.0098 percent average percentage error, and without being impacted by differences in fault distance, fault resistance, noise, or fault inception angle. Additionally, the optimised classifier reaches a 99.85% accuracy rate, enhancing line system dependability and advancing nuclear system development.
VORTICITY BALANCE AND TIME SCALES OF A TWO-DIMENSIONAL AIRFOIL IN AN UNSTEADY FREE STREAM

In unsteady aerodynamic research, there exists a long list of operational variables due to the complexity of the flow. For engineering design purposes, parametric study is the conventional approach. In this investigation, an alternative approach is used. It is demonstrated here that the physical insights of the intricate unsteady aerodynamic flow can be understood from a simple fundamental vorticity balance concept. The test configuration is a stationary two‐dimensional NACA 0012 airfoil placed at the static stall angle of 12° in an unsteady free stream. A local circulation measurement technique is introduced to survey the evolving vorticity field on the airfoil. The information about the vorticity convection and the surface vorticity flux over the wing provides a basic understanding regarding the variation of the unsteady lift.
Parenteral-Mucosal prime-boost with a TB subunit vaccine enhances early lung T cells against aerosol M. tuberculosis infection with transient improved protection.

T cell mediated immunity is critical to control M.tuberculosis (Mtb) infection and tuberculosis (TB) disease. However, Mtb actively delays the adaptive T cell response after initial infection. Thus, a cornerstone of TB vaccine development is to overcome this delay and recruit T cells for direct contact with infected lung phagocytes to control early bacterial growth. Given parenterally, the H56:CAF01 subunit vaccine results in an early CD4 T cell response in Mtb-infected lungs and significant reduction in CFU. Here, we investigate mucosal prime-boost delivery of H56:CAF01 to elicit a lung-localized/homing memory T cell population for further accelerated lung T cell recruitment and Mtb control. CB6F1 mice vaccinated with H56 (Ag85B-ESAT6-Rv2660) adjuvanted with CAF01 (Th1/Th17-skewing liposomes) either 3× s.c. , or 2× s.c. + i.n. boost(s) were rested to memory phase and then challenged with aerosol Mtb. Tissue-localized Mtb-specific T cells were enumerated by flow cytometry, and bacterial CFU determined. In vivo intravascular staining identified lung-localized from vasculature-localized T cells. Prime-boost with H56 resulted in a 10-fold increase in recruited/expanded Mtb-specific T cells in the lung parenchyma early after Mtb challenge over s.c. -only vaccination and a reduction in lung CFU at peak infection. However, no CFU difference was observed the chronic stage. Inhibition of S1P1 did not enhance the early protective effect, suggesting against local Trm as driving protection. Overall, the limited increased protection despite significant lung T cell enhancement suggests a constrained ability of vaccine T cells to control early Mtb replication.
Hybrid optimization algorithm for optimal designing of microstrip patch antenna

Microstrip Patch Antennas (MPAs) are generally renowned for their adaptability regarding feasible geometries, which makes them appropriate for numerous diverse conditions. The suitability to integrate and the trivial structure with microwave incorporated circuits was said to be the major advantage among several advantages. MPA poses constricted bandwidth; thus it has a complication while tuning. In addition, MPAs are renowned for their reduced gain. As a result, there is a necessity to raise the gain and bandwidth of MPA. This work intends to put forward a novel approach that gets a non‐linear objective for assisting the modeling of solution spaces for antenna constraints. Thus, “Salp Swarm based Shark Smell Optimization (SS‐SSO) that hybrids the concepts of Salp Swarm Algorithm (SSA) and Shark Smell Optimization (SSO)” is developed that tuned the constraints of MPA. The implication of the developed approach is to boost the antenna gain by optimal electing of dielectric value, patch length, substrate width, and thickness of MPA.
An Adaptive Servomechanism for a Class of Infinite-Dimensional Systems

A universal adaptive controller is constructed that achieves asymptotic tracking of a given class of reference signals and asymptotic rejection of a prescribed set of disturbance signals for a class of multivariable infinite-dimensional systems that are stabilizable by high-gain output feedback. The controller does not require an explicit identification of the system parameters or the injection of a probing signal. In contrast to most of the work in universal adaptive control, this paper is based on an input-output approach and the results do not require a state-space representation of the plant. The abstract input-output results are applied to retarded systems and integrodifferential systems.
Histopathological presence of dermal elements in resected margins of neural structures obtained from initial repair surgery for myelomeningocele

Background: Development of dermoid or epidermoid cysts in myelomeningocele (MMC) sites is generally thought to occur in a delayed fashion due to implantation of dermal elements during initial repair surgery. Another theory is that dermal and dermoid elements may already be present within dysplastic neural structures at birth. Methods: We experienced histopathological presence of dermal elements in resected tissues at initial repair surgery in four out of 18 cases with MMC who required resection of parts or margins of the neural structures to perform cord untethering. Since one of these cases has already been reported, we describe the clinicopathological findings for the remaining three cases. Results: In Case1, cryptic dermoid elements were discovered in the terminal filum-like structure (FT-LS) caudal to the open neural placode (NP). The FT-LS had histopathological characteristics similar to the retained medullary cord. In Case 2, dermoid elements were discovered in the caudal margin of the dysplastic conus medullaris. In Case 3, a thin squamous epithelial layer overlapped the rostral margin of the NP where the NP was located near the skin. Case 1 developed an epidermoid cyst at 1 year and 2 months of age, which was totally resected. Conclusion: Prenatally existing cryptic dermoid elements in the caudal portion of neural structures and remnants of dermal elements overlapping the rostral margin of the NP are associated with delayed occurrence of dermoid/ epidermoid cysts. Postoperative histopathological investigation of the resected specimens is recommended. Once dermal elements are revealed, repeated imaging examination and additional surgery should be considered.