Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison Between Less Invasive Surfactant Administration (LISA) and Intubation-Surfactant-Extubation (InSurE) in Preterm Infants with Respiratory Distress Syndrome: A Retrospective Study

Background: Bronchopulmonary dysplasia (BPD) is an important morbidity caused by neonatal lung injury due to mechanical ventilator use. Respiratory distress syndrome (RDS) is leading cause of mechanical ventilation in preterm infants. Surfactant was administrated through the endotracheal tube for management of RDS, which compels invasive mechanical ventilation. Recently, Intubation-SURfactant administration-Extubation (INSURE) and Less-invasive surfactant administration (LISA) have been introduced to avoid invasive mechanical ventilation. This study aimed to compare the effectiveness of LISA and INSURE.Methods: This single-center, retrospective study enrolled 47 newborns admitted to the neonatal intensive care unit (NICU) of the Wonju Severance Christian’s Hospital between January 1, 2017 and August 31, 2019, above a gestational age of 25 weeks, and required surfactant. The patient were divided into the LISA group and the INSURE group, and compared capillary gas analysis, oxygen saturation index (OSI), and morbidities.Results: The LISA group and the INSURE group included 34 and 13 newborns respectively. Demographic feature and OSI showed no significant differences between two groups. In the LISA group, pCO2 decreased over 1 hour(57.49±9.43mmHg), 2 hours(53.07±9.25mmHg, p=0.04) and 6 hours (46.50±8.53mmHg, p=0.01). pCO2 of the INSURE group decreased steeper within 2 hours (49.55±8.96mmHg to 39.56±6.20mmHg) in the INSURE group, however, the trend was not significant (p = 0.06). There were no significant differences in morbidities. Discussion: LISA and INSURE showed no significant differences in OSI and morbidities. Although LISA decreases pCO2 more slowly than INSURE, the difference is not statistical significant. LISA and INSURE are equally effective modalities for surfactant administration.
Esterification of high acidity vegetable oil catalyzed by tin-based catalysts with different sulfate contents: contribution of homogeneous catalysis

Abstract Biodiesel production costs can be significantly reduced by using nonrefined feedstock. Sulfated solid catalysts have been proposed for producing biodiesel from acid oils by esterification reactions. Nevertheless, leaching of sulfate species to the reaction medium may occur, but often it is not considered. In this article, a commercial tin sulfate (SnSO4) was used as a catalyst for the esterification of a feedstock with high content of free fatty acid in order to assess the contribution of the homogeneous catalysis in different situations. SnSO4 was calcined at different temperatures (300, 400, 500 and 700 °C) and converted into SnO2 after calcination at temperatures higher than 300 °C. Homogeneous catalysis seems possible to occur with all of the catalysts, but it was clearly observed for the uncalcined catalyst (SnSO4) and for that calcined at 300 °C (SnSO4(300)). For these catalysts, an important leaching of the sulfate species was confirmed. Higher conversions were obtained with the uncalcined SnSO4. Reactions at the same conditions using sulfuric acid as catalyst at concentrations of 0.1% were performed and confirmed conversions higher than 80%. Heterogeneous catalysis plays a significant role only with the catalyst that present the highest specific surface areas and acidity (SnSO4(400)). As some small amount of sulfate species is retained in the structure or surface of the calcined catalysts (even after calcination at 700 °C), we cannot exclude the possibility that these species are also leached during reaction. Thus, a possible contamination of biodiesel through the use of sulfated catalysts cannot be ruled out.
Studying the Effect of Bengali Folk Music on Human Autonomic Nervous System Through Multi-Fractal Detrended Fluctuation Analysis of HRV Signals

Music therapy is a frequently used tool to treat cardiac and neurological diseases. It has been proven that music impacts human body as well as mind. The reason behind such impact of music on humans is because of the release of a chemical agent inside the brain known as dopamine also known as the happy hormone. Autonomic Nervous System (ANS) is reactive to the chemical stimuli which comprises of sympathetic and parasympathetic nerves. In this paper, we present the effect of Bengali folk music on ANS. The signals were taken while the subject is listening to music and also during normal resting condition. In time series analysis, multifractal detrended fluctuation analysis (MF-DFA) is used for determining the statistical self-affinity and highly chaotic behavior of a signal. Multifractal detrended fluctuation analysis is used as a quantifying parameter to detect the effect of Bengali folk music on ANS. Our experimental result shows a satisfactory result in this context.
Analysis of Blockchain-Based Storage Systems

Increasing storage needs has driven cloud storage to become a prevalent choice to store data for both business and personal use. Cloud service providers, such as Google, offer advantages over storing personal hard drives; however, customers lose privacy and require trust in the provider to act honestly with their data. This thesis explores an alternative to cloud storage using Blockchain technology. I focus on Sia, a blockchain-based storage platform that allows users to rent storage from other users. In this study, I evaluate the security, performance and costs between the Sia and traditional cloud storage. I assessed security based on five categories: encryption, data access, durability, redundancy and availability. The performance and costs were evaluated through various storage tests using Sia and Google Drive. The results revealed Sia to have higher availability and less data access (more privacy). Google Drive displayed faster upload times, while Sia displayed faster download times. Additionally, the final cost of using Sia was comparable to cloud providers; however, was more than double of what was expected due to data redundancy costs. Further testing is needed to fully understand the complex costs structure of a blockchain-based storage platform.
Interactive Automation Of COVID-19 Classification Through X-Ray Images Using Machine Learning

Machine learning had given many benefits to the humankind by implementing technology on the daily human lives. To add, when the pandemic COVID-19 hits Earth globally in early 2020, mankind is challenged with the sudden emergence of the virus that costed many lives. With the virus spreading fast, it has become a challenge towards medical experts to keep their environment clean from the virus. Scientists and medical experts raced to find a cure and plausible methods to avoid the virus from spreading, ranging from lockdowns to standard operating procedures on daily routines. Studies have also shown that geographical factors in the rural area becomes a great challenge to experts on providing medical attention towards the community that had been infected in the rural areas. Fortunately, with the help of advanced current technology, scientists and medical experts are able to counter these problems. In this study, an experimental model with an accuracy of 87% is used, and the application to a web server is used via Python and Flask. The accuracy is achieved by adjusting batch sizes and implementing image augmentation using Keras’ ImageDataGenerator feature. Therefore, this project focuses on utilizing machine learning to classify COVID-19 patients through X-ray images on a web server, which could further improve the accessibility for humanity to seek for medical attention.
Novel, rosin‐based, hydrophobically modified cationic polyacrylamide for kaolin suspension flocculation

A novel, hydrophobically modified cationic polyacrylamide (HMPAM) was synthesized via the copolymerization of acrylamide, diallyl dimethyl ammonium chloride (DMDAAC), and diallylmethyl dehydroabietic acid propyl ester ammonium bromide. Optimum conditions for preparing HMPAM were such that the amount of initiator was 0.075 wt % of the total monomer mass, the monomer concentration was 20 wt %, and the amount of DMDAAC was 18 mol % of the total monomer molar mass. HMPAM was characterized with an UV–visible spectrometer, H-NMR, Ubbelohde viscometer, rotational viscometer, and rotational rheometer. HMPAM solutions exhibited strong hydrophobic associations, and the critical association concentration of the HMPAM aqueous solution was about 0.7 wt %; the HMPAM solutions also showed salt thickening and shear resistance. The surface morphologies of the freeze-dried HMPAM samples (1 wt %) were also observed via scanning electron microscopy. Compared with unmodified cationic polyacrylamide, Synthesis of HMPAM-0.5 exhibited a stronger flocculation capacity, and the optimal transmittance of the supernatants was above 95%. HMPAM-0.5 showed significant flocculation performances for 3–4 and 3–5 wt % kaolin suspensions at 40 and 50 mg/L, respectively. Moreover, the flocculation performance was enhanced with the addition of NaCl and CaCl2. VC 2018 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2018, 135, 46637.
Espectroscopia Raman na medição de óleos lubrificantes automotivos

A espectroscopia Raman utiliza a tecnica do espalhamento da luz de modo a identificar as frequencias vibracionais dos compostos e obter uma vasta quantidade de informacoes, fazer comparacoes e criar metodologias novas com rapidez e de forma nao invasiva. O oleo lubrificante automotivo tem grande importância para o funcionamento do motor, porem apresenta diferencas entre a composicao de oleos novos e usados. Neste trabalho foi verificada as diferencas espectrais entre oleos novos e usados com a tecnica Raman e analise multidimensional PCA como ferramenta adicional, visando determinar as diferencas em funcao do tempo de uso. Foi constatado que o espectro Raman fornece informacoes relevantes para analise de oleos novos, porem apresenta limitacoes para a analise de oleos usados. Palavras-chave: Espectroscopia Raman, oleo lubrificante automotivo, PCA.
Dual-Modal Imaging-Guided Theranostic Nanocarriers Based on 2-Methoxyestradiol and Indocyanine Green

The effect of a chemotherapeutic drug is always limited by insufficient drug dose and drug toxicity. However, when tumor cells are exposed to the maximum concentration of a chemotherapeutic drug, the best effect can be achieved. Here we developed a strategy (graphic summary) to enhance the therapeutic and diagnostic capabilities of known chemotherapeutics. We used a dual-mode near-infrared (NIR) fluorescence/photoacoustic imaging technology to actively guide the photothermal therapeutic agent indocyanine green (ICG) and a chemotherapeutic drug 2-methoxyestradiol (2-ME) loaded into thermosensitive liposomes (TSLs), on the surfaces of which was grafted the tumor-targeting peptide cRGDyk, (cRGDyk-2-ME@ICG-TSL) to the tumor target. Drug release studies have shown that TSL has a satisfactory performance for targeting and releasing 2-ME under the high temperature conditions induced by NIR laser irradiation. In vitro studies confirmed that cRGDyk-2-ME@ICG-TSLs can effectively induce drug accumulation and cytotoxicity in B16-F10 melanoma cells under near-infrared laser irradiation using cRGDyk peptide and temperature-sensitive dual targeting. Twenty-four hours after the intravenous injection of cRGDyk-2-ME@ICG-TSLs into melanoma tumor-bearing mice, dual-mode NIR fluorescence/photoacoustic imaging could accurately identify tumors and normal tissues. In addition, the combination of cRGDyk-2-ME@ICG-TSLs and NIR radiation suppressed tumor growth in nude mice bearing tumors and was associated with a lower risk of side effects on normal organs. Our results indicate that TSLs can increase the therapeutic index of chemotherapeutic drugs and is suitable as a drug delivery system for diagnostic and tumor treatment tools guided by dual-mode imaging.
Combustion Derived SrTiO3: Synthesis, Characterization and Evaluation of Electrochemical Behavior Towards Quantification of Hg(II) Ions

In this work, we are reporting the synthesis of porous SrTiO3 nanoparticles by using solution combustion route employing strontium nitrate and titanium-peroxo complex as oxidizer. The results of physico-analytical techniques revealed that SrTiO3 have a relatively small particle size, good dispersibility and diminished agglomeration. Powder X-ray diffraction pattern shows cubic perovskite structure (space group Pm3m) and the morphology was observed using a scanning electron microscope. The band gap of 3.24 eV was calculated using the diffuse reflectance spectrum. The surface area (~26.51 m2/g) of SrTiO3 was measured by BET method. SrTiO3 nanoparticles show violet-blue-green photoluminescence emission spectrum at room temperature. The photocatalytic degradation was carried out to investigate the photocatalytic activity of SrTiO3 under UV-light and evaluated for the electrochemical quantification of Hg(II) ions in aqueous solution using differential pulse anodic stripping voltammetry. The results reveal that SrTiO3 nanoparticles show better quantification result for Hg(II) ions.
Contact Tracing Proximity Data Exchange and Consolidation with App Design

A contact tracing system collects, stores, and processes proximity data to identify the contacts and the cases for an infection. A subject is a case when the subject is infected with specific symptoms or signs. A subject is a contact if the subject is likely infected but not having any infection specific symptoms or signs yet. Most of the currently deployed contact tracing solutions are built with Bluetooth LE in smartphones. Some solutions offer wearable alternative. The Bluetooth LE in smartphone is used in exchanging proximity data (PD) records with other smartphones within Bluetooth LE range. The exchanged records are consolidated to compute proximity distance and proximity duration for each subject in the data when needed. These two computed values are then used to identify contacts and cases as per the guidelines issued by the concerned healthcare authority. A poorly designed exchange and consolidation procedure could lead to loss of information, unreliable contact tracing system, and resource issues. The objective of this paper is to identify the design alternatives for data consolidation and evaluate the design options enabled by these alternatives. The design of a contact tracing App is proposed to estimate the volume of proximity data and complete these evaluations.
A Mössbauer-based XANES calibration for hydrous basalt glasses reveals radiation-induced oxidation of Fe

Abstract Oxygen fugacity (fo2) exerts first-order control on the geochemical evolution of planetary interiors, and the Fe3+/ΣFe ratios of silicate glasses provide a useful proxy for fO2. Fe K-edge micro-X-ray absorption near-edge structure (XANES) spectroscopy allows researchers to micro-analytically determine the Fe3+/ΣFe ratios of silicate glasses with high precision. In this study we characterize hydrous and anhydrous basalt glass standards with Mössbauer and XANES spectroscopy and show that synchrotron radiation causes progressive changes to the XANES spectra of hydrous glasses as a function of radiation dose (here defined as total photons delivered per square micrometer), water concentration, and initial Fe3+/ΣFe ratio. We report experiments from eight different radiation dose conditions and show that Fe in hydrous silicate glasses can undergo rapid oxidation upon exposure to radiation. The rate and degree of oxidation correlates with radiation dose and the product of water concentration and ferrous/ferric iron oxide ratio on a molar basis (Φ = XHO0.5·XFeO/XFeO1.5). For example, a basalt glass with 4.9 wt% dissolved H2O and Fe3+/ΣFe = 0.19 from its Mössbauer spectrum may appear to have Fe3+/ΣFe ≥ 0.35 when analyzed over several minutes at a nominal flux density of ~2 × 109 photons/s/μm2. This radiation-induced increase in Fe3+/ΣFe ratio would lead to overestimation of fO2 by about two orders of magnitude, with dramatic consequences for the interpretation of geological processes. The sample area exposed to radiation shows measureable hydrogen loss, consistent with radiation-induced breaking of O–H bonds, associated H migration and loss, and oxidation of Fe2+. This mechanism is consistent with the observation that anhydrous glasses show no damage under any beam conditions. Cryogenic cooling does not mitigate, but rather accelerates, iron oxidation. The effects of beam damage appear to persist indefinitely. We detect beam damage at the lowest photon flux densities tested (3 × 106 photons/s/ μm2); however, at flux densities ≤6 × 107 photons/s/µm2, the hydrous glass calibration curve defined by the centroid (derived from XANES spectra) and Fe3+/SFe ratios (derived from Mössbauer spectra) is indistinguishable from the anhydrous calibration curve within the accuracy achievable with Mössbauer spectroscopy. Thus, published Fe3+/ΣFe ratios from hydrous glasses measured at low photon flux densities are likely to be accurate within measurement uncertainty with respect to what would have been measured by Mössbauer spectroscopy. These new results demonstrate that to obtain accurate Fe3+/ΣFe ratios from hydrous, mafic, silicate glasses, it is first necessary to carefully monitor changes in the XANES spectra as a function of incident dose (e.g., fixed-energy scan). Defocusing and attenuating the beam may prevent significant oxidation of Fe in mafic water-bearing glasses.
Data Acquisition Strategy and Developments at MAX IV

The experimental capabilities at the MAX IV synchrotron consists of 17 beamlines at full capacity. Each beamline puts different requirements on the control system in terms of data acquisition, high performance, data volume, pre-processing needs, and fast experiment feedback and online visualization. Therefore, high demands are put on the data management systems, and the reliability and performance of these systems has a big impact on the overall success of the facility. At MAX IV we have started the DataStaMP (Data Storage and Management Project) with the aim of providing a unified and reliable solution for all data sources in our facility. This work presents the control system aspects of the project. It is initially aimed at providing data management solution for a selected number of detectors and beamlines. It is developed in a modular and scalable architecture and combines several programming languages and frameworks. All the software runs in a dedicated cluster and communicates with the experimental stations through high performance networks, using gRPC to talk to the control system and ZMQ for retrieving the data stream.
Application of hybrid material, modified sericite and pine needle extract, for blue-green algae removal in the lake

The present study assessed the efficient removal of nutrients and Chlorophyll-a (Chl-a) by using methyl esterified sericite (MES) and pine needle extracts (PNE), a low cost and abundant green hybrid material from nature. For this purpose, the optimal conditions were investigated, such as the pH, temperature, MES and PNE ratio, and MES-PNE dose. In addition, a Microcystis aeruginosa control using MES-PNE was also analyzed with various inhibition models. The removal of the nutrient and Chl-a onto MES-PNE was optimized for over 95% removal as follows: 22.5 for the MES-PNE ratio, 7-8 pH and a 22-25°C temperature. In this respect, approximately 1.52-2.20 g/L of MES-PNE was required to remove each 1 g of dry weight/L of Chl-a. Total phosphorus (TP) has a greater influence on the increase in Chl-a than total nitrogen (TN) according to the correlation between TN, TP and Chl-a. Moreover, the Luong model was the best model for fitting the biodegradation kinetics data from Chl-a on MES-PNE from lake water. The novel hybrid material MES-PNE was very effective at removing TN, TP and Chl-a from the lake and can be applied in the field.
Stereo to five-channels bombyx sonobuoys: from four years cetacean monitoring to real-time whale-ship anti-collision system

The BOMBYX stereo sono buoy is a non expensive device that can derive azimuth and radial velocities with acoustic pressure. This information enables computation of azimuths of low-frequency and high acoustic sources from a compact sensor array. The standard approach for estimating azimuth from these antenna could be by conventional beamforming, but it is computationally expensive, and vulnerable to directional noise contamination for weak signals. We recall here the alternative multiplicative processing scheme that computes the ? active intensity? of an acoustic signal to obtain the dominant directionality of a noise field as a function of time and frequency. This information is conveniently displayed as an ? azigram,? which is analogous to a spectrogram, but uses color to indicate azimuth instead of intensity. Data from Bombyx over 4 years demonstrate this approach. We illustrate how azigrams improves detectability of low signal-to- noise ratio signals and may also enhance the detection and potential classification of signals embedded in directional noise fields.
R ANKING C OST : O NE -S TAGE C IRCUIT R OUTING BY D IRECTLY O PTIMIZING G LOBAL O BJECTIVE F UNC - TION

Circuit routing has been a historically challenging problem in designing electronic systems such as very large-scale integration (VLSI) and printed circuit boards (PCBs). The main challenge is that connecting a large number of electronic components under specific design rules and constraints involves a very large search space, which is proved to be NP-complete. Early solutions are typically designed with hard-coded heuristics, which suffer from problems of non-optimal solutions and lack of flexibility for new design needs. Although a few learning-based methods have been proposed recently, their methods are cumbersome and hard to extend to large-scale applications. In this work, we propose a new algorithm for circuit routing, named as Ranking Cost (RC), which innovatively combines searchbased methods (i.e., A* algorithm) and learning-based methods (i.e., Evolution Strategies) to form an efficient and trainable router under a proper parameterization. Different from two-stage routing methods ( i.e., first global routing and then detailed routing), our method involves an one-stage procedure that directly optimizes the global objective function, thus it can be easy to adapt to new routing rules and constraints. In our method, we introduce a new set of variables called cost maps, which can help the A* router to find out proper paths to achieve the global objective. We also train a ranking parameter, which can produce the ranking order and further improve the performance of our method. Our algorithm is trained in an end-to-end manner and does not use any artificial data or human demonstration. In the experiments, we compare with the sequential A* algorithm and a canonical reinforcement learning approach, and results show that our method outperforms these baselines with higher connectivity rates and better scalability. Our ablation study shows that our trained cost maps can capture the global information and guide the routing result to approach global optima.