Miracle-dz/UniFAR-FTUs huggingface dataset:
Anti-Cancer Activity of Silver Nanoparticle Synthesized from Stem Extract of ocimum Kilimandscharicum Against Hep-G 2 , Liver Cancer Cell Line

Silver nanoparticle synthesis was performed with ethanol stem extract of Ocimum kilimandscharicum in the present investigation. It was identified as silver nanopartcle based on the characteristic excitation peak at 410nm and with different morphology and size, which was visualized clearly in Scanning Electron Microcope. EDAX analysis reveals that, the synthesized nanomaterial was corresponding to silver only. The zeta potential studies reveal that, the synthesized nanoparticle was highly stable and are positive in charge. The cytotoxicity against Hep G2, liver cancer cell line reveals an excellent IC50 value of 49μg/mL. Thus, the present study recommend the silver nanoparticle for the effective control of liver cancer cell line and further study would be initiated cell nanoparticle interaction and its associated pathways for apoptosis.
Enzymatic production of cellulose nanofibers from oil palm empty fruit bunch (EFB) with crude cellulase of Trichoderma sp.

Oil palm empty fruit bunch (EFB) biomass was used as a source for isolation of cellulose nanofibers (CNF) using enzymatic method. Non-cellulosic component were removed from biomass by delignification process using inoculum of Marasmius sp. Nanocellulose production began with cryocrushing pre-treatment, enzyme addition, and post-treatment with sonication. In enzyme addition, crushed EFB suspended in sodium-citrate buffer and various percentage of crude cellulase enzyme from Trichoderma sp. which is 50%, 100%, and 200% (v/w), followed by incubation in various period which is 2, 3, and 4 days. Particle size analyzer, Scanning electron microscopy and Fourier-transmmission infrared spectroscopy were used to determine the properties of CNF. Maximum CNF size distribution of 2, 3, and 4 days incubation period was 30.717 and 70 nm, respectively (50% (v/w)); 94.75 and 635 nm, respectively (100% (v/w)); 837.51 and 433 nm, respectively (200% (v/w)). Almost 100% yield achieved from variation of 50% (v/w) enzyme and 2 days incubation period. FTIR spectroscopy analysis showed that some impurities in nanocellulose. SEM analysis showed that fibril nanocellulose, with larger size than PSA, mainly because aggregation of nanocellulose.
Water treatment method and a water treatment system

The present invention can provide a high water recovery and treatment system that the water treatment method comprising salt water regeneration. The water treatment system of the present invention comprises: a first desalination unit, which comprises a Ca ion, SO4 ions and carbonate ions are separated into treated water of Ca ion, and carbonate ion concentrated water SO4 ions is treated with concentrated water; crystallization unit , which is disposed on the downstream side of the first portion of desalination, and having a gypsum crystallization from the first crystallization tank was concentrated water (21) and the first crystallization vessel (21) a seed supply portion supplying gypsum seed (22); a first pH measuring section (543), which was measured for the pH of the first concentrate in the first crystallization vessel (21); and a control unit (24), the pH measured by the first portion (543) measured by the pH scale in preventing calcium scale inhibitor is a case where the function to reduce the pH range, the control unit supply amount of the gypsum seed crystal is lowered by the first pH measuring section (543 ) measured by the pH than at high pH range, the control unit supply amount of the gypsum seed crystal increases.
Microwave-Assisted Rapid Exfoliation of Graphite into Graphene by Using Ammonium Bicarbonate as the Intercalation Agent

Making full use of the unique properties of graphene has required a new route for its scalable production. Here we demonstrate a green and fast approach for preparing high-quality few-layer graphene sheets (GS) based on a microwave irradiation method. This method takes advantage of solvent-free microwaves directly and violently exfoliates pristine graphite into GS by using ammonium bicarbonate (NH4HCO3) as a peeling media. In the microwave heating process, the decomposition of NH4HCO3 into H2O steam, CO2, and NH3 can generate strong pressure that exceeds the van der Waals force between the sheet layers of graphite, achieving effective peeling off of the sheets to very large graphene with fewer defects.
A Dominating Set-Based Sleep Scheduling in Energy Harvesting WBANs

Energy Harvesting Wireless Body Area Networks (EH-WBANs) where sensor nodes can harvest energy from their ambient environment are of great potential for low-power medical monitoring systems. The availability of energy in EH-WBANs, however, is challenged by uncertainty of harvested energy sources and limited charging efficiency, and thus the energy saving is still of great importance. To improve energy efficiency, this paper studies the sleep scheduling problem in EH-WBANs, which is of fundamental importance for network lifetime and connectivity while being not systematically addressed. Technically, this problem is proved to be NP-Complete, and thus needs non-trivial efforts to deal with. To that end, we present a series of approximation algorithms with proven performance from perspective of constructing minimum dominating set (DS), where energy saving and energy harvesting techniques are combined to prolong the network lifetime while guaranteeing real-time requirement of EH-WBANs. Specifically, we first propose a centralized algorithm that can construct DS with minimum size and discover the maximum number of DSs. We then design two distributed algorithms independent of prior global knowledge to improve network scalability, namely EEU and Improved EEU respectively. Theoretical analysis and extensive simulations are conducted to confirm the superiority of the proposed sleep scheduling algorithms.
Evidence of Absence of Tidal Features in the Outskirts of Ultra Diffuse Galaxies in the Coma Cluster

We study the presence of tidal features associated with ultra diffuse galaxies (UDGs) in galaxy clusters. Specifically, we stack deep Subaru images of UDGs in the Coma cluster to determine whether they show position angle twists at large radii. Selecting galaxies with central surface brightness magarcsec−2 and projected half-light radius , we identify 287 UDGs in the Yagi et al. catalog of low surface brightness Coma objects. The UDGs have apparent spheroidal shapes with median Sérsic index and median axis ratio . The images are processed by masking all background objects and rotating to align the major axis before stacking them in bins of properties such as axis ratio, angle of major axis with respect to the cluster center, and separation from cluster center. Our image stacks reach further than 7 kpc (≳4re). Analysis of the isophotes of the stacks reveals that the ellipticity remains constant up to the last measured point, which means that the individual galaxies have a non-varying position angle and axis ratio and show no evidence for tidal disruption out to . We demonstrate this explicitly by comparing our stacks with stacks of model UDGs with and without tidal features in their outskirts. We infer that the average tidal radius of the Coma UDGs is >7 kpc and estimate that the average dark matter fraction within the tidal radius of the UDGs inhabiting the innermost 0.5 Mpc of Coma is >99%.
A Statistical Approach for Predicting Thermal Diffusivity Profiles in Fusion Plasmas as a Transport Model

A statistical approach is proposed to predict thermal diffusivity profiles as a transport “model” in fusion plasmas. It can provide regression expressions for the ion and electron heat diffusivities (χi and χe), separately, to construct their radial profiles. An approach that this letter is proposing outstrips the conventional scaling laws for the global confinement time (τE) since it also deals with profiles (temperature, density, heating depositions etc.). This approach has become possible with the analysis database accumulated by the extensive application of the integrated transport analysis suite to experiment data. In this letter, TASK3D-a [M. Yokoyama et al., Plasma Fusion Res. 9, 3402017 (2014)] analysis database for high-ion-temperature (high-Ti) plasmas [H. Takahashi et al., Nucl. Fusion 53, 073034 (2013)] in the LHD (Large Helical Device) [O. Kaneko et al., Nucl. Fusion 53, 104015 (2013)] is used as an example to describe an approach.
Designing a Robust and Accurate Model for Consumer-Centric Short-Term Load Forecasting in Microgrid Environment

The consumer’s short-term load forecasting plays an essential role in microgrid energy distribution. However, the load forecasting at consumer level is more challenging than at substation level due to high volatility and uncertainty in energy consumption. In literature, many machine learning-based forecasting models have been explored. However, there is a need of developing a robust and accurate model to handle highly inconsistent energy consumption. In this article, we propose a robust and accurate model for consumer’s short-term load forecasting, which uses feasible techniques such as random forest, support vector regressor, and long short-term memory as base predictors to handle varying traits of energy consumption. For the final decision-making on forecasting result of these predictors, it assigns weights to each predictor dynamically as per the forecasting efficacy. The proposed model is tested on different consumer’s varying traits of energy consumption. The experimental results show that the proposed model achieves forecasting error reduction by 3.46 and 2.53 in terms of average RMSE and MAE, respectively, in comparison with the existing models. It is robust and accurate even in presence of highly volatile and uncertain load patterns, and thus, it can better fit for microgrid energy management.
Determination and uncertainty analysis of inorganic arsenic in rice by UHPLC-ICPMS

The present study arose from the need of to determine inorganic arsenic (iAs) at low levels in rice. Ultra-high performance liquid chromatography coupled with inductively coupled plasma mass spectrometry (UHPLC-ICPMS) using Kinetic Energy Discrimination (KED) mode to eliminate spectral interferences was used for analysis of iAs. Sample preparation involves extraction of inorganic arsenic (sum of As3+ and As5+) with water by heating at 90 °C for 5 min in water bath. Separation is accomplished with a reversed-phase ion pack column using a gradient chromatographic method followed by ICPMS analysis within 5 min. The method was validated in accordance with Commission Regulation (EU) No 836/2011 and performance characteristics were verified. Acceptable values were obtained for specificity, repeatability (HorRatr < 0.6), within-lab reproducibility (HorRatR < 0.3) with recovery 80-90%, limit of quantification (0.02 mg/kg), fitness-for-purpose and trueness (using CRM); thus, the method can be considered for oﬃcial control purposes.
A coupled system of ordinary and partial differential equations modeling the swelling of mitochondria

Mitochondrial swelling has huge impact to multicellular organisms since it triggers apoptosis, the programmed cell death. In this thesis we present a new mathematical approach to model this phenomenon. As a novelty it includes spatial effects, which are of great importance for the in vivo process. Our model considers three mitochondrial subpopulations varying in the degree of swelling. The evolution of these groups is dependent on the present calcium concentration and is described by a system of ODEs, whereas the calcium propagation is modeled by a reaction-diffusion equation taking into account spatial effects. Here we study both the case of non-degenerate and degenerate diffusion and analyze the derived model with respect to existence and long-time behavior of solutions.
OCTA-BAND METAMATERIAL INSPIRED MULTIBAND MONOPOLE ANTENNA FOR WIRELESS APPLICATION

In this paper, a Rectangular Monopole Antenna (RMPA) with offset microstrip feed is presented. The structure is fabricated on an FR4 substrate with a dimension of 28×32×1.6 mm3. The proposed structure achieves multiband operation by engraving 2 Complementary Split Ring Resonators (CSRRs) and a C-Shaped slot. Also, 2 Split Ring Resonators (SRRs) are printed on the adjacent sides of the radiating element. The parametric analysis is used to determine the optimum position of the feed and other critical parameters. The proposed structure operates at 2.25 GHz, 3.86 GHz, 4.60 GHz, 5.64 GHz, 5.86 GHz, 6.94 GHz, 7.48 GHz, and 9.47 GHz. The permeability of the SRR and permittivity of the CSRR are extracted and presented. The proposed antenna is fabricated and measured. The measured results of S11, radiation pattern, and gain are on par with the simulated results. The proposed antenna’s simulated surface current and efficiency are also presented to validate the performance. Simple structure, stable radiation pattern, multiband operation, reasonable gain, and efficiency are the significant features of the proposed RMPA.
A New Feature Selection-Aided Observer for Sensor Fault Diagnosis of an Industrial Gas Turbine

In complex systems, observers play a vital role in fault diagnosis and performance monitoring. Hence, the accuracy of these observers is very important. In this paper, an alternative solution to improve the observer accuracy is investigated. For this purpose, a feature selection-aided observer is proposed. This observer utilizes a feature-selection scheme that augments the sensor data with its time-domain features to observe the system. A decision tree algorithm selects the features needed for the observer, which act as soft sensors. In this scheme, a sliding mode observer is integrated with the decision tree method to select features for attaining more information from sensors (extracting two outputs from each sensor) which causes to increase the number of the observer equations. To implement this method, an augmented model for providing the statistical information is defined. To assess the performance of the introduced algorithm, an industrial twin shaft gas turbine is considered. In this model, the big data of the SGT 600 gas turbine is broken down into numerous data sets with a predefined sample time, then the subspace algorithm (N4SID) is utilized to obtain a state-space model by mean and variance of the inputs and outputs. Moreover, the algorithm is used to detect and diagnose sensors fault with a novel decision logic. Simulation results illustrate that the proposed observer is accurate and reliable for monitoring performance and diagnosing faults and failures.
Study on Spatial Distribution Characteristics of Industrial Pollution Sources in 2008

With the continuous development of China’s economy, the problems of pollutant emissions and environmental governance are gradually emerging. Based on the monthly data of man-made emission sources in Asia from the 2008 East Asia MIX emission inventory, this study analyzed the temporal and spatial distribution characteristics of air pollutants including PM2.5 , PM10 , CO, CO2 , NOx, OC, etc., and explored the difference and variation law of material concentration distribution between designated special regions, as well as the possible impact of various atmospheric systems on them. Firstly, in most areas of China, the distribution of pollutants has obvious temporal and spatial differences, and the overall trend of pollutant concentration is higher in the north than in the south. The results show that the monthly variation trend of pollutants in India is significantly correlated with that in China. However, compared with the monthly trend in northern China, it is not particularly obvious.
Effects of Hydration/Dehydration on Interfacial Polymer Fraction and Dynamics in Nanocomposites Based on Metal–Oxides and Physically Adsorbed Polymer

Effects of hydration on the interfacial dynamics of polydimethylsiloxane (PDMS) adsorbed on silica and titania nanoparticles in the form of aggregates of different specific surface area (SBET, 25–342 m2/g) were studied employing equilibrium water sorption/desorption isotherms (ESI/EDI) and broad-band dielectric spectroscopy (BDS). ESI revealed a systematic increase of the water content, h, of initial oxides (varying up to 60 wt %) with increasing SBET, whereas changes in h in nanocomposites (PNCs) are very weak (0.1–0.3 wt %) and practically independent from SBET. BDS allowed for the detection of an increase in the interfacial polymer fraction with hydration, accompanied by a significant enhancement of dynamics and cooperativity of the corresponding segmental relaxation in the interfacial layer (αint relaxation), changes being reversible as recorded by hydration and subsequent dehydration of the samples. At the same time, bulk PDMS dynamics in PNCs (α relaxation) was not significantly affected. Effects of.
LEARNING SOFT ROBOT AND SOFT ACTUATOR DYNAMICS USING DEEP NEURAL NETWORK

Inspired by living organisms and being the forefront of robotics evolution, the research in soft robotics has been growing exponentially. Due to the flexibility of these robots that is made from soft materials such as silicone or even a fabric allows them to manoeuvre on secluded environments through crevice openings which bring many advantages comparing to the rigidcomponent robots which proves much more delicate interaction with humans and environments. In this paper, modelling of the soft robot using finite element modelling will be discussed in conjunction with deep neural network for the bending and control of the end effector.
Posthumous trading patterns affecting artwork prices

This study aims to identify factors contributing to price fluctuations in artworks after an artist’s death. With access to information on seller characteristics from a historical dataset of all art auctions that took place in London between 1741 and 1913, we investigate how trading patterns and network effects at auctions affect art sales prices. Following an artist’s death, we capture dynamic effects in sales patterns and find that prices decline by 7%. We attribute this decline on the confluence of non-strategic and strategic effects, first on a frequent lack of access to professional consultation and secondly on changes in trading patterns of art dealers posthumously. Our results highlight the long-term influence of those factors on high valued art.
Ecological Momentary Assessment and mHealth Interventions Among Men Who Have Sex With Men: Scoping Review

Background Ecological momentary assessment (EMA) is a research design that allows for the measurement of nearly instantaneous experiences within the participant’s natural environment. Using EMA can help improve recall bias, ecological validity, and patient engagement while enhancing personalization and the ubiquity of interventions. People that can benefit from the use of EMA are men who have sex with men (MSM). Previous EMA studies have been successful in capturing patterns of depression, anxiety, substance use, and risky sexual behavior. These findings are directly relevant to MSM, who have high rates of each of these psychological and behavioral outcomes. Although there is a driving force behind the growing literature surrounding EMAs among MSM, no synthesizing reviews yet exist. Objective The aims of this study were to (1) synthesize the literature across fields on how EMA methods have been used among MSM, (2) better understand the feasibility and acceptability of EMA interventions among MSM, and (3) inform designs for future research studies on best evidence-based practices for EMA interventions. Methods Based on 4 library databases, we conducted a scoping review of EMAs used within interventions among MSM. The eligibility criteria included peer-reviewed studies conducted in the United States and the use of EMA methodology in an intervention for MSM. Modeling after the Centers for Disease Control and Prevention’s Compendium of Evidence-Based Interventions as the framework, we applied a typology that used 8 distinct review criteria, for example, sample size, design of the intervention, random assignment, design of the follow-up investigation, rate of retention, and rate of engagement. Results Our results (k=15, N=952) indicated a range of sample sizes; the smallest sample size was 12, while the largest sample size was 120. Of the 15 studies, 7 (47%) focused on outcomes related to substance use or outcomes related to psychological experiences. Of the 15 studies, 5 (33%) implemented an EMA intervention across 30 days. Of the 15 studies, 2 studies (13%) used random assignment, and 2 studies (13%) had quasi-experimental designs. Of the 15 studies, 10 studies (67%) reported acceptable retention rates greater than 70%. The outcomes that had event-contingent prompts (ie, prompts after engaging in substance use) were not as effective in engaging participants, with overall engagement rates as low as 37%. Conclusions Our systematic scoping review indicates strong evidence that the EMA methodology is both feasible and acceptable at high rates among MSM, especially, when examining psychological and behavioral outcomes such as negative or positive affect, risky sexual behavior, or substance use. Further research on optimal designs of EMA interventions for MSM is warranted.
The mediation relationship between life satisfaction and subjective vitality fear of COVID-19 and problematic internet use (tur)

Objective: This aim is to examine the mediating role of life satisfaction and rotating vitality in the relationship between fear of COVID-19 and problematic internet use in adolescents. Method: The participants in Turkey to 532 adolescents (304 females, 228 males) are formed. In the study COVID-19 Fear Scale, Life Satisfaction Scale, Subjective Vitality Scale, and Problematic Internet Use Scale were used. Due to the COVID-19 outbreak, education was not held in schools, so data were collected online. For this, scales were sent to the participants through online data collection prepared via Google Forms. Results: Relationships between adolescents' fear of experiencing coronavirus and their life satisfaction, fitness, and problematic internet use were determined by Pearson correlation analysis. It is seen that the problematic internet use has a positive relationship with the fear of COVID-19, a negative relationship with life satisfaction and other vitality, and low follow-up. It is observed that there is a low level, negatively significant relationship between COVID-19 and life satisfaction and vitality. Regression analysis examined the mediating relationship between life satisfaction and age's fear of COVID-19 and internet use. The research was performed by Hayes (2009) to test the mediating effect. The process was carried out in the macro mirror. In this method, 5000 resampling method was chosen. Discussion: Their results mediate the relationship between life satisfaction and health fear of COVID-19 and problematic internet use.
Assessment of the biological effect of Cu nanoparticles impregnated in polyethylene medical devices combined with the effect of LED radiation of the red and violet spectra on the ability of microorganisms to form biofilms and on daily biofilms

For many years scientists around the world have been looking for an alternative to antibiotics due to rapidly growing level of resistance to them. LED light of various spectra and metal nanoparticles are considered as a promising alternative to antibiotics. In this work, we determined the complex effect of copper nanoparticles impregnated in high-pressure polyethylene and non-woven material with the effect of red and violet LED radiation on the ability of microorganisms to form biofilms and on already formed daily biofilms.