Miracle-dz/UniFAR-FTUs huggingface dataset:
Density functional theory insight into metal ions and vacancies for improved performance in storage devices

Metal ions and oxygen vacancies (Vo) in resistive switching (RS) material play a crucial role in nonvolatile low power consuming memory devices. Performed first principle calculations investigate the impact of Cu dopant as well as collective effect of Cu + Vo on cubic ATiO3 (A = Ba, Be and Mg). Utilization of GGA + U for including coulombic effect with nonlocal exchange and exchange correlation functional has made the results more accurate. Structural properties, defect states formation in the bandgap region, and formation energy have been studied. Orbital contributions of each atom in valance band and conduction band region have been determined to explore the influence of Cu doping and Cu + Vo on electronic properties of optimized ATiO3. Among the studied materials, BeTiCuO3 + Vo is found to have least oxygen vacancy formation energy (EOVFE) and highest conductivity. The clustering of Vo around the dopant is noted, which leads to the formation of conducting filaments (CFs). These CFs play pivotal role in switching mechanism for low potential RRAM and allied devices.
REACTIVE POWER COMPENSATION BASED OPTIMIZATION OF MICRO-SCALE STAND-ALONE PHOTOVOLTAIC SYSTEMS

Inductive loads demand reactive power that does not turn into useful energy from the energy source, adversely affects system components, and releases excessive thermal energy. The control of the power factor (cos φ) decreases the negative effect of reactive power in the system by performing reactive power compensation (RPC). In this study, RPC is applied to a Photovoltaic (PV) system to increase the overall system. The designed system's main components' mathematical modeling and performance simulations are made using MATLAB codes and Simulink modellings. Simulation-based performance data were compared with the data obtained from the experimental setup. As a result of the study, the system's current-carrying capacity (CCC) is increased, a reduction in thermal energy is obtained; therefore, the system performance is optimized.
Optical properties of porcine oral mucosa at application of iodine preparation based on glycerol

The use of diffuse reflection spectroscopy made it possible to determine the optical properties of the mucous membrane of the oral cavity of a pig. The binary diffusion coefficient of iodine in Lugol's composition (aqueous solution of iodine (0.01 w/w), potassium iodide (0.02 w/w) and glycerol (0.94 w/w)) was determined for the first time ex vivo in the lining of the alveolar gingiva pigs: (8.86±0.75)·10–7 cm2/s. For the first time, the binary diffusion coefficient of glycerol was determined in the composition of Lugol (an aqueous solution of iodine (0.01 w/w), potassium iodide (0.02 w/w), and glycerol (0.94 w/w)) ex vivo in the lining of the alveolar gingiva pigs: (6.44±0.62)·10-7 cm2/s. It was revealed that after complete staining of the gingiva with a dye, radiation does not pass into the biological tissue from 200-600 nm, which includes the areas of iodine absorption peaks, and starting from 650-800 nm, the effect of optical clearing is observed with an efficiency of up to 120%.
A method for constructing a global motion path and planning a route for a self-driving vehicle

The article presents methods for constructing an unmanned vehicle (UV) motion path in an environment with obstacles to solve the problem of finding a path for a non-holonomic vehicle in an environment with obstacles. A combined approach is described and individual components are considered that allow solving the problem of planning a path for a non-holonomic vehicle. The practical use example of the combined approach for solving the problem of planning the UV path is given.
Mobile Edge Computing Based Video Surveillance System Using Special Hardware and Virtualization Technology

As technology evolution, the solution for society security system is a hot research topic. Video surveillance is an important guarantee for society security. To meet various application scenarios, quick end-to-end (E2E) response is the key of video surveillance system. Mobile edge computing (MEC) could reduce E2E delivery delay by processing data nearby the data source. This paper introduces a MEC based solution that uses special hardware, graphics processing units (GPU), to accelerate graphic data processing. Taking the limited resource of edge scenario into consideration, virtualization technology is used to share computing resource on demand. The solution also proposes deployment policy basing on functional component’s requirement. Finally, this paper verifies the solution and puts forward recommendations.
DESAIN PASSIVE COOLING MENGGUNAKAN PERFORATED ALUMINUM PLATE PADA FOTOVOLTAIK MONOKRISTALLIN

The conversion of solar energy into electrical energy using Photovoltaic monocrystalline modules is an alternative power plant that is pollution-free and environmentally friendly. Indonesia is a subtropical area that is rich in sunlight, which is the main raw material for PV. The energy conversion process in PV is strongly influenced by an increase in temperature that exceeds the threshold, which will cause a decrease in PV efficiency. Increasing the efficiency of PV has been done by many researchers from various countries, previous studies mostly used force convection or active cooling methods by adding cooling fans, spray water, heat sinks that require additional energy, problems that arise are how to improve photovoltaic efficiency without adding any extra energies? In this research, increasing the efficiency of PV using the free convection or passive cooling method, designing a perforated aluminum plate that is installed next to the bottom of the PV panel by designing holes 15mm in diameter and 20 mm apart. The idea of this research is something new and has a contribution to science, so it is very necessary to do this research in developing new and renewable technologies.
The Views of the Public on Making Decisions about over the Counter Medications and Their Attitudes towards Evidence of Effectiveness

Aim: This study aimed to determine the public views on making decisions about over the counter drugs and their attitudes towards evidence of their effectiveness. Methodology: The present study includes gathering data from the public using a survey that was adapted from a previous study. This survey was translated from English to Arabic language and was converted to an online form using Google Forms and then the link was sent to be completed by the public. Results: The survey was completed by 102 respondents. Most of the respondents agreed that the most important factors that influence their purchases of medications were the safety of the product (73.53%) and the efficacy of the drug (71.57). Most of the respondents agreed that the main methods of determining the effectiveness of the medication included the previous using of the drug (76.5%) and the physician recommendation to use it by a (75.5%). Only about 49.02% of them agreed that the majority of non-prescription medicines are supported by scientific evidence from drug trials to prove they are effective. Original Research Article Ahmed et al.; JPRI, 33(9): 5-12, 2021; Article no.JPRI. 65764 6 Conclusion: This study highlighted positive views and attitudes toward the use of OTC drugs. It is important to increase the awareness of the public about how to use these drugs wisely. Community pharmacists should play a crucial role in optimizing medication use and in patients counseling.
Correlation between carbohydrate content, protein, and fat with compatibility of durian seed grafting (durio zibethinus. Murr)

Durian nurseries can be done using generative and vegetative material sources. Both sources of propagation have their respective weaknesses and strengths. To get quality seeds requires a combination of two sources of propagation material that has each of the advantages that can complement each other. The process of merging can be through grafting. The grafting method in durian nurseries can use side grafting and shoot grafting methods. The purpose of this study was to determine differences in levels of protein, carbohydrates, fats, and phytohormones from various sources and storage time of the stem. This study was compiled based on factorial designs in the Randomized Group Design (RCBD). The first factor is the source of the stem (S), which consists of 3 sources, namely the primary branch (S1), secondary branch (S2), tertiary branch (S3). The second factor is the length of storage of the stem (T) which consists of 4 levels of storage time of the scion namely: 0 days (T0), 2 days (T1), 4 days (T2) and 6 days (T3). It was concluded that the carbohydrate content of the sciots gave the highest positive contribution to the increase in the number of shoots followed by the number of leaves, percentage of living grafts, leaf area, leaf area ratio, root canopy ratio, shoot length, and stem diameter. The protein content cannot contribute to the growth of grafted seeds even has a tendency to inhibit growth. The fat content in the scion does not contribute to the growth of plant variables.
Evolution of atomic structure and electronic transport properties in n-type Bi2Te3 films via Bi2 planar defects

Bi2Te3 films always exhibit n-type transport characteristics even under the Bi-rich condition, which, however, was not clarified clearly. Herein, by virtue of advanced techniques such as scanning tunneling microscopy, angle-resolved photoelectron spectroscopy, scanning transmission electron microscopy, and x-ray photoelectron spectroscopy, we are able to identify the structural evolution on the atomic scale for Bi-rich Bi2Te3 films. The excess of Bi content will lead to the formation of p-type BiTe antisite defects; however, there is a doping limit for the excess of Bi to form BiTe antisites. Beyond this limit, the excess of Bi will form the n-type Bi2 planar defects in the van der Waals gap, the excellent electron donors, which can enhance the electron density by over one order of magnitude and up to the 1021 cm−3 range for Bi-rich Bi2Te3 films. Benefiting from the remarkable increase in the electron density and the suppression of carrier intrinsic excitations, Bi2Te3 films with Bi2 planar defects possess a much improved thermoelectric power factor, with a maximum value of 1.4 mW m−1 K−2 at 450 K, showing about 130% enhancement compared to that of the film without Bi2 intercalations. The discovery opens a new avenue to improve the thermoelectric properties of Bi2Te3 films utilizing the Bi2 planar defects.
Remote Sensing of Narrowing Barrier Islands along the Coast of Pakistan over Past 30 Years

Barrier islands (BIs) are the first line of defense against the sea/wave actions in coastal areas, and assessing their stability is crucial in the context of effective coastal planning. Therefore, this study evaluates the spatial–temporal shoreline changes of the BIs in Pakistan over the past three decades (1989–2018). Satellite data from Landsat missions are used to delineate the shorelines of 19 BIs in Pakistan. After delineating the shorelines from satellite observations, two well-known statistical methods (i.e., end point rate (EPR) and linear regression rate (LRR)) are used to capture the localized changes in the BIs. The results ascertain that nearly all of the BIs have experienced noteworthy erosion during the past three decades. While the mean erosion over all the BIs during the study period is estimated to be >6 m/y, significant spatial heterogeneities among the individual BIs exist. The interdecadal comparison indicates that the highest mean erosion of the BIs occurred during the period 1989–1999 (13.03 ± 0.62 m/y), which gradually reduced over the preceding decades (i.e., 7.76 ± 0.62 m/y during the period 1999–2009 and 3.8 ± 0.7 m/y during the period 2009–2018). Nevertheless, ~65% of the total BIs experienced high erosion (>2 m/y), ~15% experienced moderate (<2 m/y), and ~20% experienced low erosion (<1 m/y) during the period 1989-2018. This situation implies that while ~65% of these BIs need immediate interventions from the concerned authorities, the 15% BIs with moderate erosion might experience high erosion in the wake of rising sea levels and decreasing sediment influx in the near future without proper measures. This depletion of the BIs might not only affect Pakistan but also have regional consequences due to their various services.
Atomic Structure of the Initial Nucleation Layer in Hexagonal Perovskite BaRuO3 Thin Films

Hexagonal perovskites are an attractive family of materials due to their various polymorphs and rich structure–property relationships. BaRuO3 (BRO) is a prototypical hexagonal perovskite, in which the electromagnetic properties are significantly modified depending on its lattice structure. Whereas thin‐film synthesis would allow the study of the diverse properties of hexagonal perovskites by epitaxially stabilizing various metastable polymorphs, the epitaxial growth of hexagonal perovskites, especially at the initial growth stage, is yet to be addressed. In this study, it is shown that an intriguing nucleation behavior takes place during the initial stabilization of a hexagonal 9R BRO thin film deposited on a (111) SrTiO3 (STO) substrate. It is found that a nanoscale strained layer composed of different RuO6 octahedral stacking is initially formed at the interface followed by a relaxed single crystal 9R BRO thin film. Within the interface layer, hexagonal BRO is nucleated on the (111) STO substrate by both face‐ and corner‐sharing octahedra. More interestingly, it is found that boundaries between differently stacked nucleation layers (heterostructural boundaries) facilitate strain relaxation, in addition to the formation of conventional misfit dislocations evolved from homostructural boundaries. The observations reveal an important underlying mechanism to understand the thin‐film epitaxy and strain accommodation in hexagonal perovskites.
Glycans in scaffold design in tissue reconstruction

Development of an artificial tissue by tissue engineering is witnessed to be one of the long lasting clarified solutions for the damaged tissue function restoration. To accomplish this, a scaffold is designed as a cell carrier in which the extracellular matrix (ECM) performs a prominent task of controlling the inoculated cell’s destiny. ECM composition, topography and mechanical properties lead to different types of interactions between cells and ECM components that trigger an assortment of cellular reactions via diverse sensing mechanisms and downstream signaling pathways. The polysaccharides in the form of proteoglycans and glycoproteins yield better outcomes when included in the designed matrices. Glycosaminoglycan (GAG) chains present on proteoglycans show a wide range of operations such as sequestering of critical effector morphogens which encourage proficient nutrient contribution toward the growing stem cells for their development and endurance. In this review we discuss how the glycosylation aspects are of considerable importance in everyday housekeeping functions of a cell especially when placed in a controlled environment under ideal growth conditions. Hydrogels made from these GAG chains have been used extensively as a resorbable material that mimics the natural ECM functions for an efficient control over cell attachment, permeability, viability, proliferation, and differentiation processes. Also the incorporation of non-mammalian polysaccharides can elicit specific receptor responses which authorize the creation of numerous vigorous frameworks while prolonging the low cost and immunogenicity of the substance.
An Energy-Efficient Edge Computing Framework for Decentralized Sensing in WSN-Assisted IoT

This paper addresses the problem of decentralized sensor selection in an energy-constrained wireless sensor network-based Internet-of-Things, for monitoring a spatio-temporally varying process. To do so, an adaptive edge computing framework and its variants are proposed which distributedly optimize a critical trade-off between sensing quality and remaining energy of the sensor nodes (SNs). Unlike the existing distributed sensing approaches, the proposed one aims to maintain energy balance among the SNs. The original sensor selection problem is decoupled into multiple sub-problems, each solvable at an edge node elected as head of a coverage region containing a set of SNs. The sub-problem in each coverage region is adapted to variations of the underlying process. In each region, the process is estimated using PCA-SBL (principal component analysis-sparse Bayesian learning) on noisy signal measured by the respective active SNs. Further, to correctly adapt to the process and estimate the signal, a novel logic is designed that indicates requirement of network retraining in the next measurement cycle. The results from extensive simulation studies illustrate improved energy efficiency and network energy balance of the proposed framework over the existing closest competitive centralized and decentralized approaches. The proposed framework is tested on synthetic as well as real data-sets of a sensor network.
Machine learning models to predict red blood cell transfusion in patients undergoing mitral valve surgery

Background Red blood cell (RBC) transfusion therapy has been widely used in surgery, and has yielded excellent treatment outcomes. However, in some instances, the demand for RBC transfusion is assessed by doctors based on their experience. In this study, we use machine learning models to predict the need for RBC transfusion during mitral valve surgery to guide the surgeon’s assessment of the patient’s need for intraoperative blood transfusion. Methods We retrospectively reviewed 698 cases of isolated mitral valve surgery with and without combined tricuspid valve operation. Seventy percent of the database was used as the training set and the remainder as the testing set for 13 machine learning algorithms to build a model to predict the need for intraoperative RBC transfusion. According to the characteristic value of model mining, we analyzed the risk-related factors to determine the main effects of variables influencing the outcome. Results A total of 166 patients of the cases considered had undergone intraoperative RBC transfusion (24.52%). Of the 13 machine learning algorithms, CatBoost delivered the best performance, with an AUC of 0.888 (95% CI: 0.845–0.909) in testing set. Further analysis using the CatBoost model revealed that hematocrit (<37.81%), age (>64 y), body weight (<59.92 kg), body mass index (BMI) (<22.56 kg/m2), hemoglobin (<122.6 g/L), type of surgery (median thoracotomy surgery), height (<160.61 cm), platelet (>194.12×109/L), RBC (<4.08×1012/L), and gender (female) were the main risk-related factors for RBC transfusion. A total of 204 patients were tested, 177 of whom were predicted accurately (86.8%). Conclusions Machine learning models can be used to accurately predict the outcomes of RBC transfusion, and should be used to guide surgeons in clinical practice.
Machine learning techniques for real-time UV-Vis spectral analysis to monitor dissolved nutrients in surface water

Ultraviolet-visible (UV-Vis) spectroscopy is a well-established technique for real-time analyzing contaminants in finished drinking water and wastewater. However, it has struggled in surface water because surface water such as river water has more complex chemical compositions than drinking water and lower concentrations of nutrient contaminants such as nitrate. Previous spectrophotometric analysis using absorbance peak at UV region to estimate nitrate in drinking water performs poorly in surface water because of interference from suspended particles and dissolved organic carbon which absorb light along similar wavelengths. To overcome these challenges, the paper develops a machine learning approach to utilize the entire spectral wavelengths for accurate estimation of low concentration of dissolved nutrients from surface water background. The spectral training data used in this research are obtained by analyzing water samples collected from the US-Canada bi-nationally regulated Detroit River during agricultural seasons using A.U. G. Signals' dual channel spectrophotometer system. Confirmatory concentrations of dissolved nitrate in these samples are validated by laboratory analysis. Several commonly used supervised learning techniques including linear regression, support vector machine (SVM), and deep learning using convolutional neural network (CNN) and long short-term memory (LSTM) network are studied and compared in this work. The results conclude that the SVM with linear kernel, CNN with linear activation function, and LSTM network are the best regression models, which are able to achieve a cross validation root-mean-squared-error (RMSE) less than 0.17 ppm. The results demonstrate effectiveness of the machine learning approach and feasibility of real-time UV-Vis spectral analysis to monitor dissolved nutrient levels in the surface watersheds.
Yb-doped yttrium aluminum perovskite for radiation balanced laser application

Radiation balanced laser (RBL) can be realized by managing the cooling process via the anti-Stokes photoluminescence (PL), the small-signal gain, and the heating processes including the Stokes shifts and the multi-phonon relaxation. Yttrium aluminum perovskite (YAP) shows lower phonon energy than yttrium aluminum garnet (YAG) which the radiation balanced laser was demonstrated. According to the single-frequency phonon model, the low maximum phonon energy of YAP makes the multi-phonon relaxation probability of Yb-doped YAP [(Yb:Y)AP] smaller than Yb-doped YAG [(Yb:Y)AG]. The low multi-phonon relaxation probability of YAP suggests that (Yb:Y)AP is suitable material for RBL. In this work, we evaluated the PL characteristics and estimated the ideal laser cooling efficiency and the small-signal gain of the (Yb:Y)AP (Yb0.1Y0.9AlO3) ceramics fabricated by a solid-state reaction method. We used McCumber’s relationship and referred to the literatures to derive the absorption and the small-signal gain spectra. The fluorescence re-absorption is observed in the PL spectra of (Yb:Y)AP ceramics with a thickness of ~2 mm, whereas the re-absorption is not observed in (Yb:Y)AG(Yb 0.3Y2.7Al5O12). This result indicates the strong absorbance of (Yb:Y)AP. The obtained ideal laser cooling efficiencies of (Yb:Y)AP and (Yb:Y)AG at 300 K were 1.4 and 1.8%, respectively. On the other hand, the maximum small-signal gain of 0.27 cm−1 in (Yb:Y)AP is 3.5 times larger than that of 0.078 cm−1 in (Yb:Y)AG. The large smallsignal gain of (Yb:Y)AP arises from its strong absorbance and intrinsic energy structure.
Alternative Hydrogen Peroxide Sources for Peroxyoxalate “Glowstick” Chemiluminescence Demonstrations

Simple protocols have been devised for peroxyoxalate chemiluminescence demonstrations that use urea–hydrogen peroxide or sodium percarbonate as oxidants in place of aqueous solutions of hydrogen peroxide. The procedures described are compatible with well-known peroxyoxalates and fluorescers and have been found to be convenient for use for outreach activities in venues with limited laboratory facilities.