Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimizing the NeQuick Topside Scale Height Parameters Through COSMIC/FORMOSAT-3 Radio Occultation Data

In this study, the NeQuick topside scale height empirical parameters <inline-formula> <tex-math notation="LaTeX">$H_{0}$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">$g$ </tex-math></inline-formula>, and <inline-formula> <tex-math notation="LaTeX">$r$ </tex-math></inline-formula> are globally retrieved, for the first time, exploiting a selected dataset of about 1.8M COSMIC/FORMOSAT-3 radio occultation topside electron density profiles. Corresponding spatial, diurnal, seasonal, as well as solar and magnetic activity median trends are studied and discussed. The results of this study could be considered as a baseline for the implementation of an improved NeQuick topside formulation. Indeed, applications relying on single-frequency Global Navigation Satellite System (GNSS) signals would benefit from an ameliorated characterization of the topside ionosphere because empirical ionospheric models, like NeQuick, are used to mitigate the detrimental effect that the ionosphere–plasmasphere system has on GNSS signals.
Octyl 6-O-hexanoyl-β-D-glucopyranosides: Synthesis, PASS, antibacterial, in silico ADMET, and DFT studies

An analytical procedure for the analysis of carotenoids in marine sediments rich in organic matter has been developed. Analysis of these compounds is difficult; the application of methods used by other authors required optimization for the samples studied here. The analytical procedure involved multiple ultrasound-assisted extraction with acetone followed by liquid-liquid extraction (acetone extract:benzene:water - 15:1:10 v/v/v) and HPLC analysis. The influence of column temperature on pigment separation and the quantification method were investigated – a temperature of 5 °C was selected for the Lichrospher 100 RP-18e column. The pigments in the sediment extract were quantified using a method based on HPLC analysis (at 450 nm) and spectrophotometric measurements (at 450 nm), and extinction coefficients were determined for standard solutions at this wavelength. It is very important to use the value of the extinction coefficient appropriate to the wavelength at which the detection of carotenoids was carried out.
The Modified Sadik Decomposition Method to Solve a System of Nonlinear Fractional Volterra Integro-Differential Equations of Convolution type

In this work, an incorporated form of Sadik transform and Adomian decomposition method which is called the Sadik decomposition method is presented. The method is applied to solve a system of nonlinear fractional Volterra integro-differential equations in the convolution form. To avoid collecting the noise terms that lead the method to fail for seeking the solution, the proposed method is modified by selecting a suitable initial solution. The obtained results are expressed in the explicit form of a power series with easily computable terms. In addition, illustrative examples are shown to demonstrate the effectiveness of the method.
Meteorological conditions during the MOSAiC expedition

This article sets the near-surface meteorological conditions during the Multidisciplinary drifting Observatory for the Study of Arctic Climate expedition in the context of the interannual variability and extremes within the past 4 decades. Hourly ERA5 reanalysis data for the Polarstern trajectory for 1979–2020 are analyzed. The conditions were relatively normal given that they were mostly within the interquartile range of the preceding 4 decades. Nevertheless, some anomalous and even record-breaking conditions did occur, particularly during synoptic events. Extreme cases of warm, moist air transported from the northern North Atlantic or northwestern Siberia into the Arctic were identified from late fall until early spring. Daily temperature and total column water vapor were classified as being among the top-ranking warmest/wettest days or even record-breaking based on the full record. Associated with this, the longwave radiative fluxes at the surface were extremely anomalous for these winter cases. The winter and spring period was characterized by more frequent storm events and median cyclone intensity ranking in the top 25th percentile of the full record. During summer, near melting point conditions were more than a month longer than usual, and the July and August 2020 mean conditions were the all-time warmest and wettest. These record conditions near the Polarstern were embedded in large positive temperature and moisture anomalies over the whole central Arctic. In contrast, unusually cold conditions occurred during the beginning of November 2019 and in early March 2020, related to the Arctic Oscillation. In March, this was linked with anomalously strong and persistent northerly winds associated with frequent cyclone occurrence to the southeast of the Polarstern.
Collective Influence Maximization in Mobile Social Networks

The omnipresence of information cascading process in mobile social networking applications makes the identification of a small set $S$S of influential users, which is widely believed to trigger the information outbreak, always an crucial issue in various applications such as the mobile advertising and viral marketing. Formulated as Influence maximization (IM) in 2003, this NP-hard problem has received a multitude of studies with diverse angles. However, these works often unable to provide reliable solutions, due to the loss of an exact metric for evaluating users’ contributions on information cascading in the state-of-the-art sampling based IM schemes. In this paper, we evaluate users in IM based on the collective influence (CI), a metric on the structural features of the users in network graph that reflects the contributions of the users’ neighborhoods on shaping collective dynamics of the users over the whole network. For conducting the influencer identification under probabilistic diffusion model based on the CI, we specify a quantified structural feature of the most influential users from the scope of diffusion over the whole network, and reveal that the structural influence power (CI value) of each user is a weighted cumulation of the diffusion probabilities from neighbors within certain hops. Utilizing CI, we design a novel algorithm which identifies the influencers via iteratively choosing the users with top CI values. Moreover, we point out that directly computing CI values requires to traverse the network which is originally represented by a high-dimensional matrix, and leads to huge complexity of influencer identification. To improve scalability, we further trade precision for efficiency by incorporating network embedding, a dimensionality reduction technology for networks, into algorithm design, and propose a minor variant, where CI is jointly recapitulated by low-dimensional user representations and user degrees. The superiority of our algorithms is empirically validated over 8 datasets, with an increment in influence size up to 50 percent and a comparable or even less running time comparing with existing baselines.
Evaluation of serum adropin and irisin levels and its association with anthropometric obesity indices and biochemical parameters in Type 2 diabetic patients

BACKGROUND/AIM: The newly described proteins adropin and irisin are a highly conserved polypeptide that plays essential roles in metabolic and energy homeostasis, insulin resistance, and fat browning. The aim of this study is to evaluate the circulating levels of serum adropin and irisin in type 2 diabetes mellitus (T2DM) patients and also to elucidate possible relationships between serum adropin and irisin levels with anthropometric obesity indices and biochemical parameters. SUBJECTS AND METHODS: Single-center prospective observational study included 90 T2DM patients referred to the diabetes outpatient clinic. Height, weight, and waist circumference (WC) were measured. Body mass index (BMI) and waist to height ratio (WHtR) were calculated. Fasting blood glucose, glycosylated hemoglobin, serum lipids, creatinine, urea, and blood urea nitrogen were evaluated. Estimated glomerular filtration rate (GFR) was calculated, serum adropin and irisin were evaluated. RESULTS: The results showed a significant positive correlation between adropin and irisin in females but not in males (r = 0.311; P = 0.042). In males’ group, serum adropin levels showed significant negative correlation with serum glucose (–0.423, P = < 0.05), HbA1C (–0.364, P = < 0.05), and GFR (–0.355, P = < 0.05). In contrast, creatinine was showed a significant positive correlation with adropin in males (0.381, P = < 0.05). In females’ group, adropin showed a significant negative correlation with weight (–0.371, P = < 0.05), BMI (–0.349, P = < 0.05), WC (–0.402, P = < 0.01), and WHtR (–0.398, P = < 0.01). Contrary, in males’ group, serum irisin levels showed significant positive correlation with weight (0.338, P = < 0.05), BMI (0.332, P = < 0.05), WC (0.409, P = < 0.01), and WHtR (0.432, P = < 0.01). CONCLUSION: This study demonstrated that, in T2DM patients, circulating serum adrpoin correlated negatively with anthropometric obesity indices of obesity in females, while serum irisin was positively correlated with anthropometric obesity indices of obesity in males.
Reversed Structure Based PI-Lead Controller Antiwindup Design and Self-Commissioning Strategy for Servo Drive Systems

Nowadays, the dual closed loop proportional-integral-lead (PI-Lead) controller is widely used, especially for the servo systems where high performance is required for motion control, like lithography machines and vehicle-used Lidars. Considering complex industrial applications and working conditions, more comprehensive and systematic research about the structure and potential problem of the PI-Lead controller is necessary for enhancing its performance and robustness. In this article, the failure mechanism of the classic antiwindup methods in the PI-Lead controller is analyzed. By adjusting the location of control blocks, a novel reversed structure based PI-Lead controller is proposed as a complement to the traditional antiwindup methods for effective operation and to make the system stable under severe impact disturbances. Then, a self-commissioning strategy is designed based on a fast root mean square error (FRMSE) index and without additional manual tuning factors. Compared with classic indicators, the proposed FRMSE index can achieve faster instability detection and accelerate the tuning process to protect the equipment.
Orthopyroxene–magnetite symplectite in olivine gabbros from the lower crustal Oman Ophiolite: Oman Drilling Project, Hole GT2A

Oxidation states within the planetary interior are intrinsically linked with the broad scale tectonism; however, it is di ﬃ cult to estimate the actual oxidation conditions. Orthopyroxene – magnetite symplectite formed by olivine oxidation may provide a signi ﬁ cant clue into such oxidation events. Here we report detailed mineralogical and petrological synthesis of such orthopyroxene – magnetite symplectites from olivine gabbros of Oman Ophiolite (Hole GT2A, ICDP Oman Drilling Project). In order to understand how oxidation a ﬀ ects di ﬀ erent olivine compositions, we employed a phase equilibria approach and computed several temperature – composition dia-grams at a ﬁ xed pressure (1 kbar). Our experiments predict the coexistence of olivine with Fo 75 – 76 and Fo 71 with the orthopyroxene (En 79 and En 76 ), respectively, which is remarkably similar to the mineral chemistry obtained from the Oman lower crustal gabbros. From the magnetite content, we also infer that the symplectite formation may have taken place over a range of temperatures (600 – 1000 °C) via subsolidus olivine oxidation and/or melt (oxidizing) – olivine interaction. The latter is more probable, considering the partial occurrence of orthopyroxene and clinopyroxene rim adjacent to
A Multimodal Data Fusion Technique for Heartbeat Detection in Wearable IoT Sensors

The accurate detection of heartbeats is of paramount importance in the current healthcare scenario as they act as an indicator for various underlying cardiac conditions and provides an indication of cardiorespiratory fitness. The article presents a novel multimodal data fusion technique using the discrete wavelet transform (DWT) and an application for fusing electrocardiogram (ECG), and photoplethysmogram (PPG) signals to improve beat detection accuracy in ambulatory monitoring using Internet of Things (IoT) sensors. The characteristics of interest from the input signals are first isolated in the wavelet domain and then combined to form a fused feature signal using a weighted average. The weights used are derived from a signal quality index calculation algorithm, suitable for periodic/quasiperiodic signals of different wave morphologies. The peak detection process to identify the heartbeat locations is carried out on the final fused signal. The research evaluates the algorithm performance when different types of noises at varying amplitudes corrupt the ECG and PPG signal inputs, affecting the signal-to-noise ratios (SNRs). The algorithm consistently exhibited a sensitivity of 99.69%, positive predictive value (PPV) of 99.64%, mean beat-to-beat interval relative error of 0.01, and an error spread (corresponding to 90th percentile of relative errors) of 0.02 in the −30 to 50 dB SNR range for all noise scenarios considered. The proposed algorithm exhibits improved detection sensitivities and PPVs under ambulatory conditions compared to state-of-the-art beat detection algorithms and can be used to accurately detect heartbeats where single-channel monitoring tends to fail in IoT devices.
Edge Manipulation Approaches for K-Core Minimization: Metrics and Analytics

In social networks, dense relationships among users contribute to stable communities. Breakdowns of critical connections may cause users to leave the group. A popular model to measure the cohesiveness of a network is <inline-formula><tex-math notation="LaTeX">$k$</tex-math><alternatives><mml:math><mml:mi>k</mml:mi></mml:math><inline-graphic xlink:href="wang-ieq1-3085570.gif"/></alternatives></inline-formula>-core or coreness. To identify important connections, in this paper, we propose and investigate the problem of <inline-formula><tex-math notation="LaTeX">$k$</tex-math><alternatives><mml:math><mml:mi>k</mml:mi></mml:math><inline-graphic xlink:href="wang-ieq2-3085570.gif"/></alternatives></inline-formula>-core minimization problem under three different metrics. Specifically, given a graph <inline-formula><tex-math notation="LaTeX">$G$</tex-math><alternatives><mml:math><mml:mi>G</mml:mi></mml:math><inline-graphic xlink:href="wang-ieq3-3085570.gif"/></alternatives></inline-formula> and a budget <inline-formula><tex-math notation="LaTeX">$b$</tex-math><alternatives><mml:math><mml:mi>b</mml:mi></mml:math><inline-graphic xlink:href="wang-ieq4-3085570.gif"/></alternatives></inline-formula>, we aim to retrieve a set <inline-formula><tex-math notation="LaTeX">$B$</tex-math><alternatives><mml:math><mml:mi>B</mml:mi></mml:math><inline-graphic xlink:href="wang-ieq5-3085570.gif"/></alternatives></inline-formula> of <inline-formula><tex-math notation="LaTeX">$b$</tex-math><alternatives><mml:math><mml:mi>b</mml:mi></mml:math><inline-graphic xlink:href="wang-ieq6-3085570.gif"/></alternatives></inline-formula> edges for deletion purpose, which can minimize i) the number of nodes in the collapsed <inline-formula><tex-math notation="LaTeX">$k$</tex-math><alternatives><mml:math><mml:mi>k</mml:mi></mml:math><inline-graphic xlink:href="wang-ieq7-3085570.gif"/></alternatives></inline-formula>-core (KNM), ii) the number of edges in the collapsed <inline-formula><tex-math notation="LaTeX">$k$</tex-math><alternatives><mml:math><mml:mi>k</mml:mi></mml:math><inline-graphic xlink:href="wang-ieq8-3085570.gif"/></alternatives></inline-formula>-core (KEM), and iii) the overall coreness decreased in the target node set <inline-formula><tex-math notation="LaTeX">$P$</tex-math><alternatives><mml:math><mml:mi>P</mml:mi></mml:math><inline-graphic xlink:href="wang-ieq9-3085570.gif"/></alternatives></inline-formula> (KCM). We first formally define the problems and prove that the three problems are all NP-hard. Then, a baseline greedy searching framework is developed. To scale for large graphs, optimized algorithms are developed by integrating novel pruning strategies and group-based structures. Finally, comprehensive experiments on 6 real social networks are conducted to demonstrate the efficiency and effectiveness of our proposed models and methods.
Smart Healthcare: RL-Based Task Offloading Scheme for Edge-Enable Sensor Networks

With the wide application of Internet-of-Medical-Things (IoMTs) or sensor nodes which equipped with sensors. These networked sensors are used to gather enormous data from different smart healthcare applications, and this collected data process for making appropriate decisions. Edge computing is an efficient platform that provides computational resources to collect sensor data. In the meantime, intelligent and accurate resource management by Artificial Intelligence (AI) has become the center of attention, especially in healthcare systems. With the help of AI, IoMT based healthcare devices will remarkably enhance the computational speed and range. But the challenging issue in these energy-hungry, short battery life, and delay intolerant portable devices is inappropriate and inefficient classical trends of fair resource allotment. Thus, this paper proposes Computation Offloading using Reinforcement Learning (CORL) scheme to minimize latency and energy consumption. We first formulate the problem as a combined latency and energy cost minimization problem, satisfying the lack of limited battery capacity and service latency deadline constraints. Moreover, proposed algorithm search optimal available resources node to offload task towards the trade-off between energy and latency. The experimental results show the benefits of the proposed scheme in terms of saving energy, minimizing latency, and maximum utilization of node resources in edge-enabled sensor networks. We are using an iFogSim simulator to validate the proposed scheme under realistic assumptions.
Surface and Antibacterial Properties of Titanium Dioxide Nanoparticles Synthesized in Plasma Discharge under Ultrasonic Cavitation

In this work, it is shown that intensive treatment of dispersed systems with ultrasound is an effective method for enhancing the interaction of particles and polymer with the subsequent formation of adsorption layers of high thickness and strength. This makes possible to obtain highly stable dispersed systems with a modified surface of the solid phase. The studies proved the important role of intensive ultrasonic action for controlling the properties of the nanoparticles surface in heterophase systems. It is shown that an increase in the activity of the surface of nanoparticles as a result of ultrasonic treatment is of great importance for the study of their antibacterial activity: after ultrasonic activation, nanoparticles are more active in interaction with cell membranes.
Antioxidant and Anticancer activities of yeast grown on commercial media

The use of Synthetic antioxidants is being widely restricted because of their reported toxic and carcinogenic effects. Thus, now there is considerable interest being focused towards finding antioxidants from natural sources with any unlikely effects. There is also considerable evidence which indicates lower risk of Cancer in yeast extracts and the used commercial media. The present study was conducted to determine antioxidant activity of yeast extracts grown on four different commercial media using DPPH, total phenolic content, total antioxidant activity and TBARS and to study the anticancer activity of yeast extracts on the mentioned media against human hepato carcinoma cell line (HEPG-2) using the MTT assay, Cell Cycle Analysis and mRNA Expression of Cell Apoptosis-related Gene. The yeast extract of corn meal was found to have more antioxidant activity than other commercial media. The antioxidant potential was then correlated with the total phenol content. The yeast extract of corn meal showed maximum anticancer activity against HEPG-2 as compared to that of other used media. Overall, the results achieved in this study are promising and indicate that yeast fermentation on corn meal medium is better than other used media to get on antioxidant and anticancer activities. © 2017 International Formulae Group. All rights reserved. Keywords: Yeast, commercial media, Antioxidant, Anticancer activity
Propolis natural reduction extraction process method

The invention relates to a propolis extraction process method, in particular to a propolis natural reduction extraction process method. The propolis natural reduction extraction process method is characterized by comprising the following steps of: performing low-temperature treatment on crude propolis at the temperature of -18 DEG C; grinding the crude propolis into 50 meshes at a low temperature; removing visible metal by using a high-efficiency metal detector; dissolving the crude propolis into water according to the weight ratio of the crude propolis to the water of 1:2 at the temperature of 60 DEG C for 30 minutes; standing for 24 hours; filtering 80-mesh mixture; performing freeze drying to obtain water extraction propolis powder for later use; dissolving the crude propolis into absolute ethanol according to the weight ratio of the crude propolis to the absolute ethanol of 1:4; allowing the mixture to pass through a colloid mill; dissolving the mixture by using a sol tank at the temperature of 40 DEG C for 2 hours; standing for 24 hours; filtering 200-mesh mixture; performing vacuum concentration and freeze grinding to obtain alcohol extraction propolis powder for later use; drying undissolved substances in the water extraction propolis powder and the alcohol extraction propolis powder under reduced pressure for 1 hour; mixing the undissolved substances and oil according to the ratio of the undissolved substances to the oil of 1:10 to dissolve; heating the mixture to 60 DEG C; dissolving for 1 hour; and filtering 100-mesh mixture to obtain oil soluble propolis. The propolis natural reduction extraction process method has the advantages of simple extraction method, simpleness and convenience in operation, capacity of maintaining nutritious ingredients, time saving and simple program.
The Effect of Empathy in Responses to Persuasive Health Communication Campaign Contents

The purpose of this study is to examine the effect of sympathetic reactions to public service advertisement video messages produced for health campaigns. To this end, based on the empathy response scale proposed by Campbell & Babrow (2004), the empathy response to the images of nine health campaigns with themes of smoking cessation, tuberculosis, and suicide triggered fear of health risks and health behaviors (information seeking, preventive actions). As a result of the analysis, among the factors of empathy reaction, the reality of the message creative, the match of emotions, and the identification of the characters in the video each played a role in raising fear, and it is rather fear that logically understanding the situation that causes health problems through the health campaign video It was found that it played a role in reducing health information seeking behavior. On the other hand, it was found that the higher the degree of interest, such as sympathy for the characters in the video, among the factors of the sympathetic response to the health campaign, the higher the intention of preventive action to reduce the health risk.