Miracle-dz/UniFAR-FTUs huggingface dataset:
PREPARATION AND CHARACTERIZATION OF SOLID DISPERSION FAMOTIDINE – MANNITOL BY CO-GRINDING METHOD

ABSTRACT Objective: This study aims to prepare and characterize solid dispersion of famotidine using mannitol to enhance the solubility and dissolution rate. Methods: Solid dispersions were prepared by co-grinding method in 9 formulas. The ratio of famotidine and mannitol was varied (1:1, 1:2, 2:1 w/w), and each ratio was milled at three different times (30, 60, and 90 minutes). The physical mixture was also prepared as comparison at ratio 1:1 w/w. Solid dispersions were characterized by X-ray diffraction analysis, Fourier transform infrared (FTIR) spectroscopy, differential scanning calorimetry (DSC) analysis, scanning electron microscopy (SEM), particle size analysis, solubility, and dissolution rate study. The assay of famotidine was done using a UV spectrophotometer. Results: The highest solubility of famotidine in solid dispersion was obtained in F2 (ratio 1:2 and grinding time 30 minutes). The solubility of intact famotidine, physical mixture, and solid dispersion F2 was 1.630±0.027, 2.757±0.096, and 3.272±0.076 mg/ml, respectively. X-ray diffractogram of solid dispersion F2 showed a decrease in the peak intensity of famotidine. Thermogram of DSC showed a decrease of famotidine melting point for both physical mixture and solid dispersion. Photomicrograph of SEM indicated the changes in morphology solid dispersion compared to intact substances. FTIR analysis showed no chemical interaction between famotidine and mannitol. The particle size analysis showed a reduction in the particle size of the solid dispersion. The dissolution result after 60 minutes was 85.029%, 86.166%, 92.057% for intact famotidine, physical mixture, and solid dispersion F2, respectively. Conclusion: Solid dispersion increased solubility and dissolution rate. Keywords: Solid dispersion, Famotidine, Mannitol, Co-grinding, Solubility.
CÍLE MOLEKULÁRNĚGENETICKÉ ANALÝZY ZÁVISLOSTI NA ALKOHOLU

Zavislost na alkoholu je multifaktorialni chronicke recidivujici onemocněni, u ktereho nenachazime jasne, dominantni etiologicke faktory, spise velke množstvi faktorů genetických i psychosocialnich, ktere zvysuji riziko zavislosti. Molekularni genetika zavislosti na alkoholu je tedy velmi komplexni a suma znalosti se stale dynamicky rozviji. Zavislost na alkoholu je spojena se změnami genů pro glutamatergni, GABAergni, dopaminove, serotoninove, cholinergni, adrenergni, opioidni, kanabinoidni mechanismy, genů proteinů regulujicich stresovou odpověď organismu, genů enzymů metabolizujicich alkohol. Tyto změny se na klinicke urovni manifestuji poruchami systemu odměny, motivacnich, hedonických a emocnich systemů, inhibicnich a excitacnich procesů. Ukazuje se tež, že specificka geneticka nachylnost je v pozadi i odvykaciho stavu a jeho zavažných komplikaci.
High-Input Impedance Voltage-Mode Multifunction Filter

This paper proposes a high-input impedance voltage-mode (VM) multifunction biquad filter which employs three current-feedback amplifiers (CFAs), three resistors, and two grounded capacitors. The proposed VM multifunction biquad filter has single-input and triple-output and can realize non-inverting low-pass (NLP), inverting band-pass (IBP), and non-inverting band-stop (NBS) voltage responses at the same time without increasing component selection. The proposed VM multifunction biquad filter enjoys the orthogonal tunability of angular frequency and quality factor and also provides the advantage of using only two grounded capacitors, high-input impedance and low active/passive sensitivity. The performance of the proposed VM multifunction biquad filter is verified through its hardware implementation and OrCAD PSpice simulation based on AD844-type CFAs. The circuit analysis, sensitivity analysis, and NLP, IBP, and NBS voltage responses are also shown in this paper. The paper presents a method to effectively reduce the active and passive components, maintain good circuit performance, and reduce circuit costs.
Randomized, Comparative Study of Full- and Half-Dose Fluorescein Angiography

Purpose: This study determines whether fluorescein angiography (FA) with a 250-mg dose of fluorescein (half dose) is equal in quality to the standard 500-mg dose of fluorescein (full dose) when using digital ultra-widefield (UWF) technology. Methods: In a randomized, prospective study using a UWF imaging system, FAs performed with half dose were compared with angiograms performed with full dose. Imaging studies were reviewed by 4 reviewers based on 6 characteristics: dye transit, macrovasculature, macula detail, microvasculature, leakage, and overall quality. The scores for macrovasculature, macula detail, microvasculature, and overall quality were converted to a fuzzy rating score to confirm results. Results: Seventy-nine FAs from 67 patients were reviewed for this study, including 12 patients who had both half-dose and full-dose FAs. Of all the factors studied, only microvasculature received a significantly different score between full dose and half dose that was confirmed by the fuzzy rating scale (3.79 vs 3.53; P = .04). Among those eyes that received both full and half dose, there was no significant difference in any of the 6 factors. Conclusions: In a UWF imaging system, aside from looking at fine microvascular abnormalities, the 250-mg dose of fluorescein provided similar results to a 500-mg dose. The images were not significantly different in overall quality.
Significant Improvement of Passivation Performance by Two-Step Preparation of Amorphous Silicon Passivation Layers in Silicon Heterojunction Solar Cells*

The key feature of amorphous/crystalline silicon heterojunction solar cells is extremely low surface recombination, which is related to superior passivation on the crystalline silicon wafer surface using thin hydrogenated amorphous silicon (a-Si:H) layers, leading to a high open-circuit voltage. In this work, a two-step method of a-Si:H passivation is introduced, showing excellent interface passivation quality, and the highest effective minority carrier lifetime exceeds 450 μs. By applying a buffer layer deposited through pure silane plasma, the risk of film epitaxial growth and plasma damage caused by hydrogen diluted silane plasma is effectively reduced. Based on this, excellent passivation is realized through the following hydrogen diluted silane plasma process with the application of high density hydrogen. In this process, hydrogen diffuses to a-Si/c-Si interface, saturating residual dangling bonds which are not passivated by the buffer layer. Employing this two-step method, a heterojunction solar cell with an area of 239 cm2 is prepared, yielding to open-circuit voltage up to 735 mV and total-area efficiency up to 22.4%.
Vegetation cover and plant diversity on cold climate green roofs

Both vegetation abundance and community composition play important roles in functions of green roofs (e.g. stormwater retention, habitat provision, aesthetic appearance). However, green roofs’ vegetation, and hence their functions, can change significantly over time. More understanding of these changes is required, particularly in cold climates. Therefore, this study investigated vascular plant covers and species compositions on 41 roof sections located in Sweden’s subarctic and continental climate zones. For the roof sections with a known originally intended vascular plant composition (n = 32), on average 24 ± 9% of the intended species were detected in surveys, and unintended species accounted for 69 ± 3% of the species found. However, most colonizing species formed sparse cover on the roofs. Thus, they may make less contributions to green roofs’ potential functionalities related to vegetation density (e.g. social perception, effectiveness in stormwater management and thermal performance) than the intended vegetation. The intended species dominated plant cover (93 ± 3%) and Sedum acre (58 ± 36% cover) was the most commonly detected species and as found in previous studies, substrate depth was positively related to both plant cover and species richness. Contrary to a hypothesis, the roofs’ vascular plant cover was not related to species richness but was significantly and negatively correlated with moss cover. The results highlight the importance of substrate depth for both plant abundance and species diversity and show that even in a cold climate, colonizing unintended species can strongly contribute to green roofs’ species richness.
Machine Learning for On-the-Fly Reliability-Aware Cell Library Characterization

Aging-induced degradation imposes a major challenge to the designer when estimating timing guardbands. This problem increases as traditional worst-case corners bring over-pessimism to designers, exacerbating competitive and close-to-the-edge designs. In this work, we present an accurate machine learning approach for aging-aware cell library characterization, enabling the designer to evaluate their circuit under the impact of precisely selected degradation. Unlike state of the art, we bring cell library characterization to the designer, empowering their capability in exploring the impact of aging while protecting confidential information from the foundry at the same time. Furthermore, the fast inference of cell libraries makes it feasible, for the first time, to examine aging-induced variability analysis in a Monte-Carlo fashion. Finally, we show that the designer is able to select a less pessimistic timing guardband by choosing adequate delta threshold voltage (<inline-formula> <tex-math notation="LaTeX">$\Delta {V_{th}} $ </tex-math></inline-formula>) for their design and their needs. Our machine learning approach reaches an <inline-formula> <tex-math notation="LaTeX">$R^{2}$ </tex-math></inline-formula> score of <inline-formula> <tex-math notation="LaTeX">$>99\%$ </tex-math></inline-formula> for almost all data stored in the cell library. Only timing constraints show slightly less accuracy with an <inline-formula> <tex-math notation="LaTeX">$R^{2}$ </tex-math></inline-formula> score around 95%. When using ML-characterized libraries in static timing analysis, we achieve errors smaller than <inline-formula> <tex-math notation="LaTeX">$\pm 0.5\%$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$\pm 0.1\%$ </tex-math></inline-formula> for path delay and dynamic power, respectively. Errors in leakage power are negligible and even smaller by orders of magnitude. Our machine learning implementation for standard cell library characterization is publicly available. Download: <uri>https://opensource.mlcad. org</uri>
Cardiac Stimulation in the Third Millennium: Where Do We Head from Here?

Over the years, pacemakers have evolved from a life-saving tool to prevent asystole to a device to treat heart rhythm disorders and heart failure, aiming at improving both cardiac function and clinical outcomes. Cardiac stimulation nowadays aims to correct the electrophysiologic roots of mechanical inefficiency in different structural heart diseases. This has led to awareness of the concealed risks of customary cardiac pacing that can inadvertently cause atrioventricular and inter-/intra-ventricular dyssynchrony, and has promoted the development of new pacing modalities and the use of stimulation sites different from the right atrial appendage and the right ventricular apex. The perspective of truly physiologic pacing is the leading concept of the continued research in the past 30 years, which has made cardiac stimulation procedure more sophisticated and challenging. In this article, we analyze the emerging evidence in favor of the available strategies to achieve an individualized physiologic setting in bradycardia pacing.
Genetic and Biochemical Predictors of Neonatal Bronchopulmonary Dysplasia

Abstract Bronchopulmonary dysplasia (BPD) is a common complication of prematurity with a multifactorial etiology, influenced by both genetic susceptibility and environmental factors on the immature lung. Fibroblast growth factor receptor-3 and -4 (FGFR-3 and FGFR-4) are abundantly expressed in both the epithelium and mesenchyme in the developing mammalian lung. FGFR-4 may play a role in developing BPD as it is associated with airway inflammation and remodeling; studies showed a link between BPD and a polymorphism in the FGFR-4 gene. The aim of this study was to study the significance of FGFR-4 in developing BPD and to investigate the correlation between its serum level and its genetic polymorphism in relation to development of BPD in preterms. This case–control study was performed on 80 preterm neonates (<32 weeks) divided into two groups: group I included 50 preterms with respiratory distress syndrome (RDS) who developed BPD and group II included 30 preterms with RDS only. The mean serum level of FGFR-4 was significantly lower in group I than in group II (p-value < 0.05). There was no significant correlation between the serum levels of FGFR-4 and the degree of severity of BPD. Allele variation in the FGFR-4 gene was similar in both groups. The serum level of FGFR-4 was significantly lower in preterms with BPD, although the gene polymorphism was not significantly different in the studied groups.
Geodesic projection of the von Mises–Fisher distribution for projection pursuit of directional data

We investigate geodesic projections of von Mises–Fisher (vMF) distributed directional data. The vMF distribution for random directions on the (p−1)-dimensional unit hypersphere Sp−1 ⊂ Rp plays the role of multivariate normal distribution in directional statistics. For one-dimensional circle S1, the vMF distribution is called von Mises (vM) distribution. Projections onto geodesics are one of main ingredients of modeling and exploring directional data. We show that the projection of vMF distributed random directions onto any geodesic is approximately vM-distributed, albeit not exactly the same. In particular, the distribution of the geodesic-projected score is an infinite scale mixture of vM distributions. Approximations by vM distributions are given along various asymptotic scenarios including large and small concentrations (κ → ∞, κ → 0), high-dimensions (p → ∞), and two important cases of double-asymptotics (p, κ → ∞, κ/p → c or κ/ √ p → λ), to support our claim: geodesic projections of the vMF are approximately vM. As one of potential applications of the result, we contemplate a projection pursuit exploration of high-dimensional directional data. We show that in a high dimensional model almost all geodesic-projections of directional data are nearly vM, thus measures of non-vM-ness are a viable candidate for projection index. MSC2020 subject classifications: Primary 62H11; secondary 62E20, 62R30.
Grand Challenges in Radar Signal Processing

Signal processing for radar systems is a vast and fascinating discipline that covers numerous techniques and touches on many application areas. The history of radar began more than one hundred years ago, in 1904, when ChristianHülsmeyer demonstrated the first experimental radar in Cologne, Germany (Griffiths et al., 2019). The banks of the River Rhine at Cologne’s Hohenzollern Bridge were the scene of this important invention. Later, in 1920, GuglielmoMarconi also observed in his experiments radio detection of targets, but it was not untilWorldWar II that the dynamic development of radar emerged. It has since then evolved into an indispensable all-weather, long-range sensor. Military and security applications have always been the main drivers of radar development. However, more recently, radar has become a key technology for civilian applications including air, maritime, and ground traffic control, in addition to urban sensing and indoor monitoring. Radar not only affects our present time worldwide, but also shapes our future. According to its acronymRAdio Detection And Ranging, the classical radar mission is to detect and locate objects (Skolnik, 2002). With the advent of coherent pulse radar, velocity measurements have become possible by exploiting the Doppler effect (Chen and Ling, 2001). In contrast to camera images and many other sensors, radar is able to provide quantitative data on range and speed. Today specialized radars measure range as well as azimuth and elevation angles, enabling target detection and localization. Through Synthetic Aperture Radar (SAR), Inverse SAR (ISAR), or Interferometric SAR (InSAR), a 3D image of an object can be obtained (Melvin and Scheer, 2012; Richards, 2014). In recent years, passive radar systems have been gaining considerable and increasing attention for both target detection and ground imaging (Lombardo and Colone, 2012; Blasone et al., 2020). Applications of radar techniques span from ocean current monitoring to Earth digital elevation mapping, from automotive to biomedicine, from industrial monitoring in IoT scenarios to through the wall imaging (Amin, 2010), from the detection of vital signs and discerning the activities of daily living (Amin, 2017) to UAVmonitoring (see Theodoridis and Chellappa (2013) and Theodoridis and Chellappa (2017) for a broad overview of many radar signal processing techniques and applications). There are also many key radar applications in agriculture, forestry, soil moisture monitoring, geology, geomorphology and hydrology, oceanography, land use, land cover mapping, and archeology. Radar has a long history, and judging from the growing applications of active sensing, it has an illustrious and bright future. Future radar systems should effectively support a massive variety of applications with novel hardware solutions and innovative signal processing techniques. Several grand challenges inherent to future radar systems are outlined in the following.
The Effect of Family-Centered Educational Supportive Intervention on Parental Stress of Premature Infants Hospitalized in the NICU

Background: Premature birth and infant hospitalization in the neonatal intensive care unit (NICU) is stressful for parents; therefore, training and supporting couples with the aim of reducing stress are very important. Objectives: The present study aimed at investigating the effect of family-centered educational, supportive intervention on parental stress of premature infants hospitalized in the NICU. Methods: This quasi-experimental study was performed on the eligible parents of 80 premature infants admitted to the NICU ward of Ali-ibn Abitaleb Hospital in Zahedan, in two groups of 40 intervention and control. Samples were selected by convenience sampling and randomly divided into two groups. The intervention group received five sessions of a family-centered educational support program in five days, with an average of 60 minutes per session, and the control group received only routine training and care. Data were collected using the Parental Stress scale (PSS) questionnaire with approved validity and reliability before and after the end of educational interventions at discharge from the hospital. Data were analyzed by SPSS, version 22 using paired t-test, independent t-test, and chi-square. Results: Mean of parental stress scores of mothers and fathers of premature infants was not significantly different in the intervention and control groups before family-centered educational-supportive intervention (P > 0.05), but after the intervention, the mean of parental stress scores of parents in the intervention group was significantly lower than the control group (P = 0.001). Conclusions: Family-centered educational supportive intervention has a positive and significant effect on reducing stress in parents of preterm infants admitted to NICU. Therefore, training and support of parents during the hospitalization of their infants is recommended.
Physics and chemical activation to produce activated carbon from empty palm oil bunches waste

This research was conducted by laboratory-scale trials to make activated carbon from empty oil palm bunches. Empty bunches were palm oil processing industrial waste. This research was an effort to optimize waste management. Empty palm oil bunches were studied to become carbon active. Activated carbon is needed to meet the needs of the food industry and non-food industries. This research aimed to determine the appropriate method, optimal operating condition, and get the specification of standard carbon active. Making activated carbon was carried out by multiple activations; chemical and physical. The feed carbonation process was conducted at 400° C for 4 hours with N2 gas flow. After the charcoal is formed, chemical activation is carried out using an H3PO4 activator with a concentration of 9-15% wt. Physical activity was conducted by heating the activated carbon method in 700°C for an hour. The result of the study showed that multiple activations produced activated carbon, and the quality filled the standard. H3PO4 concentration of 13% was the most appropriate concentration to provide activated carbon with the best quality. The best quality activated carbon, which has produced of this research has complied with Indonesian National Standards 06-3730-1995 with parameters: 3% moisture content, 3.92% ash content, 0.7% volatile matter, 95.38% bonded carbon, iodine number 945.47 mg / g, and surface area of 272.9 m2/g.
Clustering of Association Rules for Big Datasets using Hadoop MapReduce

Mining association rules is essential in the discovery of knowledge hidden in datasets. There are many efficient association rule mining algorithms. However, they may suffer from generating large number of rules when applied to big datasets. Large number of rules makes knowledge discovery a daunting task because too many rules are difficult to understand, interpret or visualize. To reduce the number of discovered rules, researchers proposed approaches, such as rules pruning, summarizing, or clustering. For the flourishing field of big data and Internet-of-Things (IoT), more effective solutions are crucial to cope with the rapid evolution of data. In this paper, we are proposing a novel parallel association rule clustering approach which is based on Hadoop MapReduce. We ran many experiments to study the performance of the proposed approach, and promising results have been demonstrated, e.g. the lowest scaleup was 77%.
Detection and Location of Aged Cable Segment in Underground Power Distribution System Using Deep Learning Approach

Aged cable segments in underground power distribution systems will gradually develop into severe faults. The location of aged cable segment is essential for ensuring system reliability and reducing maintenance cost, but is rarely studied by the existing research. In this article, a novel aged cable segment detection and location method based on wide frequency range transfer function (TF) measurement and deep learning approaches is proposed to fill the gap. The relationship between the measured TF and cable ageing parameters is analyzed, and two models with combined sparse autoencoder and convolutional neural network are trained to estimate the aging location and severity. A transfer learning approach is further developed to improve the model performance for various online situations. Experiments are conducted which prove the effectiveness and generalization ability of the proposed method. Compared with existing approaches, the proposed method shows better performance under different ageing situations, even smooth ageing scenarios.