Miracle-dz/UniFAR-FTUs huggingface dataset:
Photodynamic Therapy in the Extracellular Matrix of Mouse Lungs: Preliminary Results of an Alternative Tissue Sterilization Process

Lung transplantation is one of the most difficult and delicate procedures among organ transplants. For the success of the procedure and survival of the new organ, the sterilization step for acellular lungs prior to recellularization is important to ensure that they are free of any risk of transmitting infections from the donor to the recipient subject. However, there are no available information concerning the lung mechanical parameters after sterilizing photodynamic therapy. The aim of this study was to evaluate the extracellular matrix (ECM) and lung mechanical parameters of decellularized lungs undergoing sterilizing photodynamic therapy (PDT). Besides, we also analyzed the lung after controlled infection with C. albicans in order to evaluate the effectiveness of PDT. The lung mechanical evaluation parameters, resistance ( ) and elastance ( ), exhibited no significant differences between groups. In addition, there were no PDT-induced changes in lung properties, with maintenance of the viscoelastic behavior of the lung scaffold after 1 h exposure to PDT. The ECM components remained virtually unchanged in the acellular lungs of both groups. We also showed that there was a reduction in fungal infection population after 45 minutes of PDT. However, more studies should be performed to establish and verify the effectiveness of PDT as a possible means for sterilizing lung scaffolds. This manuscript was presented as a master thesis of Nadua Apostolico at the postgraduate program in rehabilitation sciences, University Nove de Julho—UNINOVE.
Inclusive Language MOOCs

This article discusses the application of MOOCs for refugees and migrants in order to help these groups of people develop the language competences and transverse skills which they require to improve their level of social inclusion and possibilities in the labour market, and/or access higher education in the country in which they find themselves or plan to go. Specifically, this research focuses on the way in which Language MOOCs (or LMOOCs [Martín-Monje, Barcena, 2014]) deploy on mobile devices [Read, Barcena 2015] can effectively and advantageously be used by displaced people. The study reported here outlines the design of two LMOOCs of Spanish for immediate needs, based on a previous needs analysis, developed by the ATLAS research group in collaboration with NGOs and refugee support associations in Spain.
Research on an Improved Sliding Mode Sensorless Six-Phase PMSM Control Strategy Based on ESO

The six-phase motor control system has low torque ripple, low harmonic content, and high reliability; therefore, it is suitable for electric vehicles, aerospace, and other applications requiring high power output and reliability. This study presents a superior sensorless control system for a six-phase permanent magnet synchronous motor (PMSM). The mathematical model of a PMSM in a stationary coordinate system is presented. The information of motor speed and position is obtained by using a sliding mode observer (SMO). As torque ripple and harmonic components affect the back electromotive force (BEMF) estimated value through the traditional SMO, the function of the frequency-variable tracker of the stator current (FVTSC) is used instead of the traditional switching function. By improving the SMO method, the BEMF is estimated independently, and its precision is maintained under startup or variable-speed states. In order to improve the estimation accuracy and resistance ability of the observer, the rotor position error was taken as the disturbance term, and the third-order extended state observer (ESO) was constructed to estimate the rotational speed and rotor position through the motor mechanical motion equation. Finally, the effectiveness of the method is verified by simulation and experiment results. The proposed control strategy can effectively improve the dynamic and static performance of PMSM.
Structural and Magnetic Properties of Potassium-Doped 2,3-DiMethylnaphthalene

The development of potential magnetic materials in metal-doped polycyclic aromatic hydrocarbons has been a research hotspot in recent years. Here we have successfully synthesized stable potassium-doped 2,3-dimethylnaphthalene samples. The combination of first-principles calculations and XRD results identifies that doping of potassium into 2,3-dimethylnaphthalene forms a monoclinic structure with a molar ratio of 1:2 between potassium and molecule. The red shifts in the Raman spectra indicate that potassium 4s electrons are transferred to the organic molecules. The magnetic measurements show that the doped materials exhibit a temperature-independent magnetization in the temperature region of 1.8–300 K, which is consistent with the Pauli paramagnetic behavior. This is distinct from the diamagnetism of pristine material. Compared to the previous focus on benzene ring structure, our study of aromatic hydrocarbon derivatives of benzene ring opens a new route for the development of this field.
Experimental Production of Composite Fiber for Additive Production Technology

In recent years, additive production technology has spread to almost all manufacturing areas. In most cases, a fiber is used as an input material in the 3D printing process, the required properties of which are mainly its strength and durability. With the ongoing development of the 3D printing techniques, the need to develop fibers that do not pose a burden to the environment comes to the fore. This paper points out the possibilities of producing fibers intended for additive production. The paper describes the fiber production on FilaFab PRO EX350 device used for producing fibers for the 3D printing technology. The aim of the paper is to describe the production of fibers and to compare commonly available fibers with the experimentally made ones. To run the tests, a clear fiber and a composite fiber with carbon powder filler were produced. The mechanical properties achieved by these experimentally produced fibers were compared in tensile tests with commonly available fibers purchased from sellers of 3D printing materials.
Oil market volatility: comparison of COVID-19 crisis with the SARS outbreak of 2002 and the global financial crisis of 2008

Abstract During the recent COVID-19 outbreak, the crude oil market experienced enormous price fluctuations. A large number of researchers contended the volatility observed in oil market as unprecedented and it was immediately attributed to the pandemic owing to its globally devastating nature. Whether or not this attribution is justified, is the major question we have raised in this paper. We perform the comparative analysis of the volatility spasms of oil market during the COVID-19 pandemic (COVID-19), the Global financial crisis of 2008 (GFC) and the SARS outbreak of 2002–2004 (SARS). Preliminary investigation is conducted using two proxies of market sentiment which are oil price returns and oil price spread. For further investigations we apply symmetric GARCH (1,1) and the asymmetric GJR-GARCH (1,1) models. Our results based on skewness and kurtosis, indicate an extremely high degree of fat tail risk implying COVID-19 crisis as low probability yet high severity event a.k. a. black swan event. Our results further confirm the presence of volatility clustering (GARCH effect) along with the highest degree of asymmetry during COVID-19. These facts collectively make COVID-19 crisis more uncertain and pessimistic compared to the GFC and SARS.
How does the onset time of El Niño events affect tropical cyclone genesis and intensity over the western North Pacific?

Previous studies have shown that the equatorial Pacific Ocean warming can be separated into spring (April~June; SP) and summer (July~October; SU) modes based on the onset time of El Niño events. Different onset times are caused by different atmospheric and oceanic conditions, which, in turn, should influence tropical cyclone (TC) activity. While the location of TC formation in the western North Pacific (WNP) shifts significantly eastward and equatorward in the SP type relative to climatology (1951–2017), only an eastward shift occurs in the SU type. Only intense TCs (category 1 + 2 + 3 and 4 + 5) have an obvious eastward and equatorward shift in the SP type, with no such shift in any TC category in the SU type. The number of category 4 + 5 TCs in the SP type increases significantly, but fewer category 1 + 2 + 3 TCs in the SU type. In the SP type, TCs are generally stronger, with more in category 4 + 5, and longer life spans occurring across all categories. However, no obvious change in TC intensity can be identified except for category 1 + 2 + 3 in the SU type. The eastward and equatorward shift of the mean genesis position in the developing phases of SP can be attributed to a southeastward shift of favourable atmospheric and oceanic conditions, which include weaker zonal vertical wind shear, stronger relative vorticity, higher mid‐level relative humidity, and enhanced upper‐ocean temperature (5–100 m). All these conditions are mainly related to the onset time of the westerly anomalies near the central equatorial Pacific. These results suggest that the onset time of El Niño events could serve as a good forecasting indicator for TC genesis position and intensity over the WNP.
Constrained optimised flexible power control for grid‐connected converters under unbalanced faults

This paper presents a constrained multi-objective optimisation scheme for a grid-connected voltage source converter operating under unbalanced voltage conditions in a three-phase three-wire system. The scheme is aimed at evaluating the converter reference currents required to supply all the power generated by the connected source to the grid, whilst simultaneously suppressing oscillations of both real and reactive powers. The trade-off between these two conﬂicting requirements is achieved by setting a single cost function with variable weightings. Two constraints are set to restrict the converter instantaneous phase current and maintain low DC-bus voltage percentage ripple. A genetic algorithm is applied to search for the optimal solution. Simulation results are presented and conﬁrm the effectiveness of the proposed method.
Isolation of Volatiles Compounds in Banana by HS-SPME: Optimization for the Whole Fruit and Pulp

The best conditions for the isolation of banana volatiles by headspace solid phase microextraction (HS-SPME) were determined for the intact whole fruit (with peel) and for the pulp only. Optimization of isolation conditions was carried out using a Central Composite Rotational Design based on Response Surface Methodology with two factors: time needed to reach equilibrium in the headspace and the fiber exposure time. Samples were analyzed by GC-MS. The criteria were higher number of peaks and greater total area of the chromatogram. The best conditions for isolating volatiles from the headspace of whole fruits were 140 min headspace equilibrium and 120 min fiber exposure, while for the banana pulp the best conditions were 15 and 60 min for equilibrium and exposure times, respectively. The results suggest that the whole fruit and pulp have very similar qualitative volatile profile in ripe banana.
Simulation and deep learning on point clouds for robot grasping

Purpose In this work, the authors aim to provide a set of convenient methods for generating training data, and then develop a deep learning method based on point clouds to estimate the pose of target for robot grasping. Design/methodology/approach This work presents a deep learning method PointSimGrasp on point clouds for robot grasping. In PointSimGrasp, a point cloud emulator is introduced to generate training data and a pose estimation algorithm, which, based on deep learning, is designed. After trained with the emulation data set, the pose estimation algorithm could estimate the pose of target. Findings In experiment part, an experimental platform is built, which contains a six-axis industrial robot, a binocular structured-light sensor and a base platform with adjustable inclination. A data set that contains three subsets is set up on the experimental platform. After trained with the emulation data set, the PointSimGrasp is tested on the experimental data set, and an average translation error of about 2–3 mm and an average rotation error of about 2–5 degrees are obtained. Originality/value The contributions are as follows: first, a deep learning method on point clouds is proposed to estimate 6D pose of target; second, a convenient training method for pose estimation algorithm is presented and a point cloud emulator is introduced to generate training data; finally, an experimental platform is built, and the PointSimGrasp is tested on the platform.
Are tissue samples obtained via remote biopsy useful for fatty acid-based diet analyses in a free-ranging carnivore?

Fundamental knowledge on free-ranging animals has been obtained through capture-based studies; however, these may be logistically intensive, financially expensive, and potentially inconsistent with local cultural values. Genetic mark–recapture using remote tissue sampling has emerged as a less invasive alternative to capture-based population surveys but provides fewer opportunities to collect samples and measurements for broader ecological studies. We compared lipid content, fatty acid (FA) composition, and diet estimates from adipose tissue of polar bears (Ursus maritimus) obtained from two collection methods: remote biopsies (n = 138) sampled from helicopters and hunter-collected tissue (n = 499) from bears harvested in Davis Strait and Gulf of Boothia, Nunavut, 2010 – 2018. Lipid content of adipose tissue was lower in remote biopsies than harvest samples likely because remote biopsies removed only the outermost layer of subcutaneous tissue, rather than the more metabolically dynamic innermost tissue obtained from harvest samples. In contrast, FA composition was similar between the two collection methods with relatively small proportional differences in individual FAs. For diet estimates in Davis Strait, collection method was not a predictor of prey contribution to diet. In Gulf of Boothia, collection method was a predictor for some prey types, but the differences were relatively minor; the rank order of prey types was similar (e.g., ringed seal; Pusa hispida was consistently the primary prey in diets) and prey proportions differed by < 6% between the collection methods. Results from both methods showed that diets varied by geographic area, season, year, age class, and sex. Our study demonstrates that adipose tissue from remote biopsy provides reliable estimates of polar bear diet based on FA analysis and can be used to monitor underlying ecological changes in Arctic marine food webs.
COVID-19 Blues: A Big Data Analysis

The purpose of this study was to analyze big data related to the “ Corona Blues ” to explore major issues and meanings. The data were collected using web crawling from January through August, 2020, and analyzed using semantic network analysis. The results indicated that the top keywords related to Corona Blues were depression, overcoming, prolongation, mind, and anxiety. Topic modeling indicated that the main topics were psychological difficulties, mental health services, youth support, overcoming the corona virus, and medical interest. Additionally, the top N-gram keywords in positive data were depression-overcoming, and emotional guard-overcoming. On the other hand, the top N-gram keywords in negative data were depression-helplessness, and anxiety-helplessness. Big data analysis reveals the need for continuity of care and psychological support for Corona Blues. Implications for counseling intervention and recommendations for further research are provided.
Model-based Pre-processing in Protein Mass Spectrometry

Model-Based Pre-processing in Protein Mass Spectrometry. (December 2009) John C. Wagaman, B.S., Millersville University; M.S., University of Central Florida Co–Chairs of Advisory Committee: Dr. Jianhua Huang Dr. Webster West The discovery of proteomic information through the use of mass spectrometry (MS) has been an active area of research in the diagnosis and prognosis of many types of cancer. This process involves feature selection through peak detection but is often complicated by many forms of non-biological bias. The need to extract biologically relevant peak information from MS data has resulted in the development of statistical techniques to aid in spectra pre-processing. Baseline estimation and normalization are important pre-processing steps because the subsequent quantification of peak heights depends on this baseline estimate. This dissertation introduces a mixture model to estimate the baseline and peak heights simultaneously through the expectation-maximization (EM) algorithm and a penalized likelihood approach. Our model-based pre-processing performs well in the presence of raw, unnormalized data, with few subjective inputs. We also propose a model-based normalization solution for use in subsequent classification procedures, where misclassification results compare favorably with existing methods of normalization. The performance of our pre-processing method is evaluated using popular matrix-assisted laser desorption and ionization (MALDI) and surface-enhanced laser desorption and ionization (SELDI) data sets as well as through simulation.
Unsaturated Hydraulic Conductivity Variation of Expansive Yazoo Clay with Wet-Dry Cycles

Expansive soils are subjected to shrink-swell behavior with moisture variation in Mississippi, United States. With successive moisture and temperature variations over the seasons, the hydraulic conductivity of expansive soil is subjected to change because of the development of shrinkage cracks, which can be as large as as 1.2 cm wide and 1.5 m deep in the field, affecting the vertical hydraulic conductivity (Kv), whereas the horizontal hydraulic conductivity (Kh) remains fairly constant. The current study intends to investigate the hydraulic conductivity of highly expansive Yazoo clay at different wet-dry cycles. To observe the changes in the hydraulic conductivity with different wet-dry cycles in the laboratory, an instantaneous profile method to measure the permeability was utilized. Compacted Yazoo clay samples at different initial moisture content instrumented with moisture sensors at different depths to monitor changes in the moisture content were investigated. The samples were subjected to one, two, and three numbers (1N, 2N, and 3N) of wetting and drying cycles. For the drying process, testing chambers are kept in a controlled high-temperature booth of about 37°C simulating high summer temperatures in Mississippi. After the end of the wet-dry cycles, the test is performed to investigate the changes in the hydraulic conductivity of soil with the presence of shrinkage cracks. The hydraulic conductivity of highly plastic clay is very low at a fully compacted state and was observed to be (1.0×10-8 cm/s) at the 1N wetting phase. However, with an increment in the wet-dry cycles, the Kv of Yazoo clay increases (3.70×10-4 cm/s) after the sample is exposed to three wet-dry cycles. Even though the changes in the Kv of highly plastic clay define the infiltration behavior, which mostly controls the slope failure and pavement distress, consideration of the climatic loads is ignored in the design phase of the highway embankment and levees. By inclusion of the climatic variation, and evaluating the performance, the design life and resilience of the structures can be significantly increased
ULTRASOUND, INTERFERENCE CURRENT, AND EXERCISE FOR RECURRENT KNEE PAIN DUE TO OSTEOARTHRITIS

Introduction:- To study the effectiveness of ultrasound, interference current, and exercise in recurrent knee pain due to osteoarthritis and to find the optimal frequency, intensity, and duration of exercise. Materials and methods:- Twelve outpatients (age 67.16 Â± 7.89 years) with recurrent knee pain due to osteoarthritis were followed for one month. They were treated with interference current, ultrasound, and exercise for two weeks. All patients were instructed to perform the exercises as often as possible, for as long as possible, and as intensively as possible at home for one month. The pain was reported on a visual analog scale daily for two weeks and after one month. In the beginning, in the middle, and at the end of the month were recorded knee mobility, the periarticular muscle strength, frequency, intensity, and duration of the exercises. Results:- During the two-week course the pain was decreasing every following day (P>0.05). Over the weekend the pain increased (P<0.05). After two weeks and after one month improved the pain (P<0.05), knee mobility (P>0.05), and muscle strength (P>0.05). There was a significant correlation and regression between pain and exercise frequency (P<0.05). If the exercise frequency is greater than five times a day, the pain regressively tends to zero (P>0.05). There was no correlation between pain and exercise intensity (P>0.05) and between pain and exercise duration (P>0.05). Discussion:- The pain decrease during the week and its increase during the weekend show that interference current, ultrasound, and exercise have a short-term analgesic effect. Improving all parameters after two weeks and after one month shows that exercise has a long-term effect. Frequent, short, and low-intensity exercise is recommended due to the correlation with regression between pain and exercise frequency, in the absence of a correlation between pain and intensity or duration of exercise. The recommended frequency of exercise is five times a day, as at this frequency the pain tends to disappear. Conclusion:- The combination of ultrasound, interference current, and exercise is effective in recurrent knee pain due to osteoarthritis. Short and low-intensity exercises with a frequency of more than five times a day are optimal.
A Dissolution Kinetic Study of Disperse Dye in Supercritical Carbon Dioxide to Design an Efficient Supercritical Dyeing Process

The dissolution behavior of dye in supercritical carbon dioxide influences the overall mass transfer that controls a supercritical dyeing process. Increasing the dissolution rate of the dye leads to shortening of the dyeing process time and can improve the efficiency of the process. Controlling the properties of the carbon dioxide flow is a good method to improve the dissolution rate of dyes. In this study, a dissolution kinetic model was designed by quantitatively analyzing and formulating the dissolution phenomenon of dyes using an in situ UV/Vis spectrometer. Through this model, the dissolution rate was compared by varying the geometric shape of the column containing the dye and the flow rate of carbon dioxide. Moreover, the correlation equation between the Reynolds number and Sherwood number was obtained through mass transfer coefficients derived under various conditions. In order to verify the utility of this equation, it was applied to a scaled-up device and the precise result could be predicted. This study can be useful in the design of dyeing processes and make-up equipment.