Miracle-dz/UniFAR-FTUs huggingface dataset:
Tiotropium bromide exerts anti-inflammatory effects during resistive breathing, an experimental model of severe airway obstruction

Introduction Resistive breathing (RB), a hallmark of obstructive airway diseases, is characterized by strenuous contractions of the inspiratory muscles that impose increased mechanical stress on the lung. RB is shown to induce pulmonary inflammation in previous healthy animals. Tiotropium bromide, an anticholinergic bronchodilator, is also shown to exert anti-inflammatory effects. The effect of tiotropium on RB-induced pulmonary inflammation is unknown. Methods Adult rats were anesthetized, tracheostomized and breathed spontaneously through a two-way non-rebreathing valve. Resistances were connected to the inspiratory and/or expiratory port, to produce inspiratory resistive breathing (IRB) of 40% or 50% Pi/Pi,max (40% and 50% IRB), expiratory resistive breathing (ERB) of 60% Pe/Pe,max (60% ERB) or combined resistive breathing (CRB) of both 40% Pi/Pi,max and 60% Pe/Pe,max (40%/60% CRB). Tiotropium aerosol was inhaled prior to RB. After 6 h of RB, mechanical parameters of the respiratory system were measured and bronchoalveolar lavage (BAL) was performed. IL-1β and IL-6 protein levels were measured in lung tissue. Lung injury was estimated histologically. Results In all, 40% and 50% IRB increased macrophage and neutrophil counts in BAL and raised IL-1β and IL-6 lung levels, tissue elasticity, BAL total protein levels and lung injury score. Tiotropium attenuated BAL neutrophil number, IL-1β, IL-6 levels and lung injury score increase at both 40% and 50% IRB. The increase in macrophage count and protein in BAL was only reversed at 40% IRB, while tissue elasticity was not affected. In all, 60% ERB raised BAL neutrophil count and total protein and reduced macrophage count. IL-1β and IL-6 levels and lung injury score were increased. Tiotropium attenuated these alterations, except for the decrease in macrophage count and the increase in total protein level. In all, 40%/60% CRB increased macrophage and neutrophil count in BAL, IL-1β and IL-6 levels, tissue elasticity, total protein in BAL and histological injury score. Tiotropium attenuated the aforementioned alterations. Conclusion Tiotropium inhalation attenuates RB-induced pulmonary inflammation.
Robust Adaptive Optimization Algorithm for Stability Control of Electric Patrol Survey UAV

In this paper, a mathematical model of flight pattern and flight attitude is established and analyzed. The flight pattern of the power patrol flight is analyzed. Based on the original linear quadratic optimal control algorithm, the motion and optimal control model of the unmanned aerial vehicle (UAV) patrol process is established to meet the unmanned aerial vehicle (UAV) inspection constraints, then a linear quadratic optimization Control based optimal control algorithm is proposed. In this paper, four-rotor aircraft as an example for simulation research, different motion models with different optimization control, and add different interference signals and the corresponding filter algorithm for antijamming performance testing. The simulation results show that the UAV can obtain good control effect by the linear quadratic optimal control, and its stability and anti - jamming performance can be improved obviously.
Error estimates for higher-order finite volume schemes for convection–diffusion problems

Abstract It is still an open problem to prove a priori error estimates for finite volume schemes of higher order MUSCL type, including limiters, on unstructured meshes, which show some improvement compared to first order schemes. In this paper we use these higher order schemes for the discretization of convection dominated elliptic problems in a convex bounded domain Ω in ℝ2 and we can prove such kind of an a priori error estimate. In the part of the estimate, which refers to the discretization of the convective term, we gain h1/2. Although the original problem is linear, the numerical problem becomes nonlinear, due to MUSCL type reconstruction/limiter technique.
Smart Integrated Optical Rotation Sensor Incorporating a Fly-by-Wire Control System

In this work, a first prototype smart optical rotary sensor is demonstrated for fly-by-wire applications to detect cockpit inceptors or flight control surface movement. A rotary encoder, optical setup, electronic circuits, and a microcontroller, with built-in analog-to-digital converters, are packed into a single housing with dimensions of 80 mm × 80 mm × 50 mm to propose a smart sensor. To simulate cockpit inceptors or flight control surface displacement, an actuator is rotated by a computer-controlled driver and the output voltages are sent to the computer using a universal serial bus. Signal processing is done in two steps: software filtering followed by optical powers extraction from the measured digitized voltages. Experimental results show that the sensor has the sensitivity of 17.5 mW · W–1/° and an accuracy of 0.5% over the full range of 180°. Moreover, we test the sensor's reliability by examining the sensor response while varying the input power of the light source and we demonstrate that the sensor is highly reliable, a vital requirement for avionic applications. The sensor not only meets the requirements for avionic applications but it is also smart which leads to less maintenance, less electromagnetic interference (EMI) (instead of ∼100 twisted wire pairs, four buses are used which are more EMI resistant), and significant weight reduction.
Fungicidal Potency and Mechanisms of θ-Defensins against Multidrug-Resistant Candida Species

ABSTRACT Systemic candidiasis is a growing health care concern that is becoming even more challenging due to the growing frequency of infections caused by multidrug-resistant (MDR) Candida species. Thus, there is an urgent need for new therapeutic approaches to candidiasis, including strategies bioinspired by insights into natural host defense against fungal pathogens. The antifungal properties of θ-defensins, macrocyclic peptides expressed in tissues of Old World monkeys, were investigated against a panel of drug-sensitive and drug-resistant clinical isolates of Candida albicans and non-albicans Candida species. Rhesus θ-defensin 1 (RTD-1), the prototype θ-defensin, was rapidly and potently fungicidal against drug-sensitive and MDR C. albicans strains. Fungal killing occurred by cell permeabilization that was temporally correlated with ATP release and intracellular accumulation of reactive oxygen species (ROS). Killing by RTD-1 was compared with that by histatin 5 (Hst 5), an extensively characterized anticandidal peptide expressed in human saliva. RTD-1 killed C. albicans much more rapidly and at a >200-fold lower concentration than that of Hst 5. Unlike Hst 5, the anticandidal activity of RTD-1 was independent of mitochondrial ATP production. Moreover, RTD-1 was completely resistant to Candida proteases for 2 h under conditions that rapidly and completely degraded Hst 5. MICs and minimum fungicidal concentrations (MFCs) of 14 natural θ-defensins isoforms against drug-resistant C. albicans isolates identified peptides that are more active than amphotericin B and/or caspofungin against fluconazole-resistant organisms, including MDR Candida auris. These results point to the potential of macrocyclic θ-defensins as structural templates for the design of antifungal therapeutics.
Image‐domain shading correction for cone‐beam CT without prior patient information

In the era of high‐precision radiotherapy, cone‐beam CT (CBCT) is frequently utilized for on‐board treatment guidance. However, CBCT images usually contain severe shading artifacts due to strong photon scatter from illumination of a large volume and non‐optimized patient‐specific data measurements, limiting the full clinical applications of CBCT. Many algorithms have been proposed to alleviate this problem by data correction on projections. Sophisticated methods have also been designed when prior patient information is available. Nevertheless, a standard, efficient, and effective approach with large applicability remains elusive for current clinical practice. In this work, we develop a novel algorithm for shading correction directly on CBCT images. Distinct from other image‐domain correction methods, our approach does not rely on prior patient information or prior assumption of patient data. In CBCT, projection errors (mostly from scatter and non‐ideal usage of bowtie filter) result in dominant low‐frequency shading artifacts in image domain. In circular scan geometry, these artifacts often show global or local radial patterns. Hence, the raw CBCT images are first preprocessed into the polar coordinate system. Median filtering and polynomial fitting are applied on the transformed image to estimate the low‐frequency shading artifacts (referred to as the bias field) angle‐by‐angle and slice‐by‐slice. The low‐pass filtering process is done firstly along the angular direction and then the radial direction to preserve image contrast. The estimated bias field is then converted back to the Cartesian coordinate system, followed by 3D low‐pass filtering to eliminate possible high‐frequency components. The shading‐corrected image is finally obtained as the uncorrected volume divided by the bias field. The proposed algorithm was evaluated on CBCT images of a pelvis patient and a head patient. Mean CT number values and spatial non‐uniformity on the reconstructed images were used as image quality metrics. Within selected regions of interest, the average CT number error was reduced from around 300 HU to 42 and 38 HU, and the spatial nonuniformity error was reduced from above 17.5% to 2.1% and 1.7% for the pelvis and the head patients, respectively. As our method suppresses only low‐frequency shading artifacts, patient anatomy and contrast were retained in the corrected images for both cases. Our shading correction algorithm on CBCT images offers several advantages. It has a high efficiency, since it is deterministic and directly operates on the reconstructed images. It requires no prior information or assumptions, which not only achieves the merits of CBCT‐based treatment monitoring by retaining the patient anatomy, but also facilitates its clinical use as an efficient image‐correction solution. PACS number(s): 87.57. C‐, 87.57. cp, 87.57. Q‐
Discriminatively Local Hashing for Preserving Semantic Manifold

Learning to hash, owing to its compact compression and economical computation, is becoming more and more crucial in data embedding, storage, indexing and computing for various intelligent tasks such as semantic computing and search engines. However, numerous existing hashing methods are schemed in the normal Euclidean space with the assumption that Lp metric represents the semantic similarities which usually is not the case in practical scenarios. With respect to such observation, we propose a novel learning paradigm for hashing, called Discriminatively Local Hashing for Preserving Semantic Manifold (DLH for short), in a more general Manifold space. More specifically, appropriate nearest neighbors are firstly selected for Graph semantics with Euclidean metric in order to preserving semantic manifold; then supervised labels are further leveraged to distinguish which are real neighbors in the previous selected ones for fine-tuning the semantic embedding. Compared with some completing baselines on several public datasets, our proposed method DLH performs much better or at least comparable.
Heat transfer enhancement in nano-fluids suspensions : thermal wave effects and hyperbolic heat conduction.

The spectacular heat transfer enhancement revealed experimentally in nanofluids suspensions is being investigated theoretically at the macro-scale level aiming at explaining the possible mechanisms that lead to such impressive experimental results. In particular, the possibility that thermal wave effects via hyperbolic heat conduction could have been the source of the excessively improved effective thermal conductivity of the suspension is shown to provide a viable explanation although the investigation of alternative possibilities is needed prior to reaching an ultimate conclusion.
Nanoporous metals: a new class of nanostructured energy materials

Dealloyed nanoporous metals(NPMs) represent a new class of functional materials with unique structural properties such as high surface area,low density,high permeability,high electrical and thermal conductivity,and tunable structural features,which make them very attractive for important applications including catalysis,separation,and energy and environmental technologies.This article tends to provide an overview of the recent advances in this area,regarding their preparation,structure and interfacial properties.In particular,we will address their great potential as next generation electrode materials for new energy technologies.
Gender differences in anxiety and depression among the caregivers of patients with dementia

Background: Providing care to dementia patients itself poses risk of distress in bio-psychosocial paradigm. It is important to assess the mental health status and attend to the needs of caregivers. The present investigation focuses on gender differences related to anxiety and depression in caregivers of dementia patients. Methods: This cross-sectional study was carried out in an out-patient setting in the Dementia clinic of a tertiary care hospital. Sixty caregivers of consescutive dementia patients receiving outpatient care were assessed using the Hospital Anxiety and Depression Scale (HADS). Descriptive analysis was done to find in between group differences for the male and female caregivers and Pearson’s correlation coefficient was calculated to find the association between the number of family members with chronic illness and the scores on HADS. Results: Male and female care- givers differed significantly on the HADS—Total, Anxiety and Depression subscale scores with female care givers having significantly higher scores. There was a significant correlation between the number of family members with chronic illness and HADS-Anxiety subscale scores in female caregivers. Conclusion: It is crucial to screen caregivers, especially females, of patients with dementia for presence of anxiety and depression. This approach will help timely identification and proper management of these individuals. It is important to promote measures to soften the impact that the patient has on the caregiver, and that, at the same time, improves the quality of life of the patient.
A Uniform Control Strategy for the Interlinking Converter in Hierarchical Controlled Hybrid AC/DC Microgrids

This paper presents a uniform control strategy for the bidirectional ac/dc interlinking converter (BIC) in hierarchical controlled hybrid microgrid. The uniform control strategy unifies different control structures for multifunctional BIC in terms of power management, ac and dc voltage support. With the unified control structure, various triggering mechanisms for BIC mode-switch are not compulsory in response to the relevant scenario changes in the power network. Therefore, the negative consequences, such as unsmooth transition and system collapse due to the inaccurate or slower mode switch, can be avoided. Moreover, the uniform control strategy is also applicable for the hierarchical controlled hybrid microgrid, whose control architecture is typically comprised of the centralized and decentralized levels. This enables the communication fault ride-through capability and the impact from the communication failures can thus be mitigated. To sum up the above two features, the proposed control strategy is able to provide a smooth operation for the BIC without control mode switch in the event of unintentional scenario changes in power or communication network. To verify the validity of the proposed uniform control strategy, the controller hardware-in-the-loop experimental results have been provided in this paper.
Towards Single Pin Scan for Extremely Low Pin Count Test

Design-for-Testability (DFT) techniques for test cost reduction of digital circuits rely on efficient deployment of scan test through smart DUT (device under test) partitions, matching of scan test I/O needs to the DUT needs for increased scan data throughput, and optimal test pattern generation methods. The test cost is further reduced by testing multiple devices in parallel using the same set of ATE resources. As a result, the number of scan pins available in a DUT for test application is reduced. The need for managing different DUT partitions and ensuring that the scan I/O interface matches with the DUT requirements further aggravates the need for scan test pins. In this paper, a generic methodology for reduced pin count scan test is presented. Specific solutions are described for internal generation of all scan mode control signals, e.g. scan enable, clock control, X-mask control, switching between slow speed shift clock and high speed capture clock, etc., across one or more DUT partitions. It is shown how this method can ultimately lead to a single pin scan test solution. These methods have been implemented in cost sensitive SOC designs and, as a result, the scan test time has been reduced by 2x - 3x over what has been achieved using other aggressive test cost reduction methods for scan compression. These methods are also independent of the specific scan compression solution used.
Comparative study of different image reconstruction methods

Image reconstruction process in computed tomog-raphy(CT) uses set of x-ray projection data to reconstruct images. This paper presents comparative study of different image reconstruction methods. Analytical reconstruction projection is defined as line integral form, by using Fourier transform, Fourier slice theorem and inverse Fourier transform of an image to be reconstructed. Algebraic reconstruction technique of iterative reconstruction projection is defined in terms of system of linear equation. Many analytical and iterative methods are available. In this paper FBP analytical method and different iterative methods (kaczmarz, randomize kaczmarz, L1 and L2norm) are used to reconstruct the image. Reconstructed image quality is compared on the basis of MSE(mean square error), MAE(mean absolute error), SNR(signal to noise ratio), PSNR(peak signal to noise ratio). Experimental result shows that when number of rays increases till the matrix LU factorization is possible by computer system, then image quality is improved and FBP method is better than all other methods. Computation time is also increases when number of rays increase, FBP methods is computationally efficient.
Atomic force microscopy as applied to materials with anisotropic nanostructure

Creation of new nanostructured materials is impossible without serious study of their internal structure at the nanoscale level (when it is necessary to consider the effects associated with the features of the molecular structure of substance, even though the material can still be considered as a continuous medium). Atomic force microscopy (AFM) is one of the most promising tools for such studies. Its main advantage over traditional electron microscopy is that the atomic force microscope allows obtaining information not only on the topology of the internal structure of the material, but also on its local physical properties (which may dier significantly from the macroscopic
Drain-Voltage Balance and Phase-Shifted PWM Control Schemes for High-Efficiency Parallel-String Dimmable LED Drivers

An LED driver consisting of dimmable current balancing circuits (CBCs) and a boost converter with drain voltage balance (DVB) and phase-shifted pulsewidth modulation (PSPWM) control schemes is presented. To reduce the power loss on conventional linear current regulators, CBCs are employed. The DVB control scheme is proposed to maintain a desired constant voltage across the CBCs, so as to increase current balance and achieve high efficiency of the CBCs. Thus, the bus voltage of the boost converter is adaptively regulated based on the DVB control. The PSPWM control scheme can alleviate the variation of the bus current provided by the boost converter. As a result, the transient ripple of the bus voltage can be reduced when the light-emitting diode (LED) strings are turned on and off. Furthermore, the utilization of DVB control is increased when the PWM dimming duty cycle becomes lower. The experimental results demonstrate that the minimum voltage among the CBCs is always kept at the lowest constant level while maintaining the required current passing through the LED strings. The efficiency of the CBCs is kept almost the same for different LED currents and is over 95%. Thus, a high-efficient parallel-string dimmable LED driver with simple circuitry can be achieved.
Modeling and Analysis of One-Tier Ultradense Multiuser Networks

Most research on stochastic geometry has uniformly treated all users in cellular networks. In reality, the performance of a user depends strongly on the distances from a user to the tagged base station and other interfering base stations. Meanwhile, the throughput of a network is decided by the number of base stations and the number of users that can be served in the cell. This paper aims to investigate the achievable performance of users located at different positions in the Voronoi cell. First, we proposed a near formula of distribution of distances from users to their tagged base stations. Then, we deduce the coverage probabilities and ergodic rates of different users in the cell when the network is fully loaded or partially loaded. Finally, we proposed a novel definition of network throughput to respond to the networks’ throughput in real time. We compare all our derivations to the Monte Carlo simulation. The numerical results are very close to the simulation results.
NANOPARTICLES AS DRUG DELIVERY SYSTEMS

Nanoparticles as a drug delivery system has a several advantages over a conventional multi dose therapy much review effort in developing a nano particle as a drug delivery system has been focused on controlled release and sustained release dose forms. The various approaches are available for achieving the nano particle as a drug delivery system. One of the most effective approaches is nano particles of the drug. Nano particles are solid colloidal particles ranging in size from 10-1000nm in which the active principle is dissolved and diffused. Nano particles were prepared by Amphiphilic macro molecule, Cross linking, Emulsion polymerization, Interfacial polymerization, Denaturation of natural macromolecules in an oil emulsion, Chemical dehydration, Solvent evaporation, Solvent deposition, Nanoparticle formation by desolvation of macromolecules and co-accervation. The choice of technique mainly depends upon nature of polymer used, the drug and intended use. By the use of nano particles several drugs has been developed for efficacy, to reduce side effects and drug toxicity, increased therapeutic index and bioavailability for prolonging and controlled release.
Sparse Principal Component Analysis via Variable Projection

Sparse principal component analysis (SPCA) has emerged as a powerful technique for data analysis, providing improved interpretation of low-rank structures by identifying localized spatial structures in the data and disambiguating between distinct time scales. We demonstrate a robust and scalable SPCA algorithm by formulating it as a value-function optimization problem. This viewpoint leads to a flexible and computationally efficient algorithm. It can further leverage randomized methods from linear algebra to extend the approach to the large-scale (big data) setting. Our proposed innovation also allows for a robust SPCA formulation which can obtain meaningful sparse components in spite of grossly corrupted input data. The proposed algorithms are demonstrated using both synthetic and real world data, showing exceptional computational efficiency and diagnostic performance.