Miracle-dz/UniFAR-FTUs huggingface dataset:
Chalcogenide of type I-V-VI₂ for thermoelectric applications

Here, we report on a series of samples with nominal compositions AgBiSe2-xSx (with x= 0 to 2) belonging to the class of ternary chalcogenides of type I-V-VI₂. The structural and thermal analysis result shows a complete solid solution without miscibility gap and phase transitions for all compositions. We have succeeded in obtaining single phase compounds, of both hexagonal and cubic phase, and the high temperature XRD study showed the rhombohedral phase too for selected compositions (x=1 to 2 in AgBiSexS2-x). The DSC results confirmed the presence of the phase transitions for all compositions, with a shift of the temperature of transition as a function of the sulfur/selenium fraction. The high pressure XRD investigation of the compound AgBiSe₂ showed a pressure induced phase transition from hexagonal-to-rhombohedral-to-cubic phase. In this respect, chemical pressure with 30% Sb on the Bi site has been successfully applied to stabilize the cubic phase for all compositions. Nb doping in the Sb-substituted samples does not show any change in the phase behavior at RT in comparison with the undoped samples. The influence of doping on transport properties was analyzed. The negative value of S for all compositions indicates n-type semiconducting behavior over the range (50-300K). Further, the results not only shows very low value of κ but the ∣S∣ and ρ value also decreases for each composition from Nb fraction 0.02 to 0.04. This gives us the opportunity to optimize the power factor in order to improve the ZT value. At last, collaborative study with Chinese team showed that ZT of 1.3 at 890 K can be achieved for AgPbmSnSe2+m (m = 50).
Fault Diagnostic Methodologies for Utility-Scale Photovoltaic Power Plants: A State of the Art Review

The worldwide electricity supply network has recently experienced a huge rate of solar photovoltaic penetration. Grid-connected photovoltaic (PV) systems range from smaller custom built-in arrays to larger utility power plants. When the size and share of PV systems in the energy mix increases, the operational complexity and reliability of grid stability also increase. The growing concern about PV plants compared to traditional power plants is the dispersed existence of PV plants with millions of generators (PV panels) spread over kilometers, which increases the possibility of faults occurring and associated risk. As a result, a robust fault diagnosis and mitigation framework remain a key component of PV plants. Various fault monitoring and diagnostic systems are currently being used, defined by calculation of electrical parameters, extracted electrical parameters, artificial intelligence, and thermography. This article explores existing PV fault diagnostic systems in a detailed way and addresses their possible merits and demerits.
Mapping Susceptibility to Debris Flows Triggered by Tropical Storms: A Case Study of the San Vicente Volcano Area (El Salvador, CA)

In this study, an inventory of storm-triggered debris flows performed in the area of the San Vicente volcano (El Salvador, CA) was used to calibrate predictive models and prepare a landslide susceptibility map. The storm event struck the area in November 2009 as the result of the simultaneous action of low-pressure system 96E and Hurricane Ida. Multivariate Adaptive Regression Splines (MARS) was employed to model the relationships between a set of environmental variables and the locations of the debris flows. Validation of the models was performed by splitting 100 random samples of event and non-event 10 m pixels into training and test subsets. The validation results revealed an excellent (area under the receiver operating characteristic (ROC) curve (AUC) = 0.80) and stable (AUC std. dev. = 0.01) ability of MARS to predict the locations of the debris flows which occurred in the study area. However, when using the Youden’s index as probability threshold to discriminate between pixels predicted as positives and negatives, MARS exhibits a moderate ability to identify stable cells (specificity = 0.66). The final debris flow susceptibility map, which was prepared by averaging for each pixel the score of the 100 MARS repetitions, shows where future debris flows are more likely to occur, and thus may help in mitigating the risk associated with these landslides.
Experimental and Theoretical Infrared Spectroscopic Study on Hydrated Nafion Membrane

A collaborative experimental and theoretical study on the dependence of the infrared (IR) spectrum of hydrated Nafion electrolyte membrane on the hydration number is investigated in great detail. Experimental time-resolved attenuated total reflection Fourier transform IR spectroscopic results show that Nafion membrane has a unique IR peak intensity dependence on the hydration number. Calculated IR spectra indicate that this unique IR peak intensity dependence is correctly reproduced not for the singly hydrated Nafion but for the doubly hydrated Nafion. This result strongly supports the relay mechanism of the proton conductance, in which protonated water clusters are relayed by the side chains through the doubly hydrated sulfonic acid groups under low-humidity conditions.
BaTiO3 incorporation effect on the dielectric properties of polymer from aqueous emulsion: An enhanced dispersion technique

An economic and environment friendly process was adapted to synthesize new dielectric composite materials. Using ethylene vinyl acetate (EVA)/vinyl ester of versatic acid (VeoVa) terpolymer as an aqueous emulsion provides a homogenous dispersion of BaTiO3 (BT) particles, due to the high viscosity and polarity of the vinyl resin (VR). Composites films were obtained from these dispersions by water evaporation. The evolution of the dielectric properties as a function of the BaTiO3 content, was correctly fitted by a Maxwell-Garnett model. This fitting of the experimental curve shows a good dispersion of filler in the vinyl resin and the particles separation by a layer of resin as expected for the preparation method used in this study. The VR/BT composites show good synergy between the dielectric properties of the different phases of the composites due to the formation of macrodipoles and to the strong interactions between polar EVA/VeoVa groups and the BaTiO3 particles surface. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016, 133, 44333.
Machine Learning Approach to Predictive Maintenance in Manufacturing Industry - A Comparative Study

Predictive maintenance is the way to improve asset management in every manufacturing industry. While handling advance costlier machinery in the industry, the predictive maintenance knowledge will be essential to protect the machinery before gets degradation performance. Recently, the emergence of business in manufacturing industry deals with good systems, regular intervals maintenance process, predictive maintenance (PdM), machine learning (ML) approaches are extensively applied for handling the health standing of business instrumentation. Now the digital transformation towards I4.0, data techniques, processed management and communication networks; it’s doable to gather huge amounts of operational and processes conditions information generated type many items of kit and harvest information for creating an automatic fault detection and diagnosing with the aim to attenuate period of time and increase utilization rate of the parts and increase their remaining helpful lives. The predictive maintenance is inevitable for property good producing in I40. This paper aims to provide a comprehensive review of the recent advancements of metric capacity unit techniques wide applied to PdM for good producing in I4.0 by classifying the analysis consistent with metric capacity unit algorithms, ML class, machinery and instrumentation used device employed in information acquisition, classification of knowledge size and kind, and highlight the key contributions of the researchers and so offers pointers and foundation for additional analysis. In this research paper we constructed a Random Forest model to predict the failure of the various machine in manufacturing industry. It compares the prediction result with Decision Tree (DT) algorithm and proves its superiority in accuracy and precision.
Dynamic analysis and oscillation elimination of brushless doubly fed wind power generation system during symmetrical voltage dips

In the dynamics of grid-connected operation of brushless doubly-fed generators, grid voltage dips can cause the extreme imbalance between the voltage and the back electromo-tive forces in power winding. When these imbalances are combined with the inﬂuence of the inertia link composed of converter and generator, a serious over-current and current oscillation forms in power winding and control winding. This paper gives a process analysis and proposes an improved control to the system during the low voltage ride through event. According to the mathematical model of the generators, the correlation between the power winding and control winding currents is established and then a fully equivalent simpliﬁed model is obtained accordingly. When the voltage suddenly drops to zero, the analytic expressions of power winding and control winding are calculated in the complex frequency domain and the inﬂuence factors of overshoot and oscillations are analyzed. The conventional control method relies on limited PI regulation that cannot eliminate the oscillations completely. It is found that after adjusting a proportional coefﬁcient and eliminating the integral link of the control winding current controller, the order of the control system reduces. Therefore, the generation system can quickly recover to a steady state without oscillations. Finally, the analysis and improvement
Quantifying energy consumptioneandogreenhouse gass emissions of construction projects: A case study of Semarang -Bawen road project

Roads have significant impacts on the environment, economy and society, and the choice of pavement thus has broad implications. All phases of road development, from construction to operations, consume a vast amount of resources and produce waste and emissions. This study aims to examine energy consumption and greenhouse gas (GHG) emissions of a road construction project using Life Cycle Assessment (LCA) approach. Semarang-Bawen section road project was used as a case study, which uses Asphalt Concrete-Wearing Course (AC-WC) and Asphalt Concrete-Binder Course (AC-BC) layers for flexible pavement, and concrete slabs for rigid pavement. The methods used to estimate energy consumption and GHG emissions refers to the Intergovernmental Panel on Climate Change (IPCC) procedure, i.e. the Energy Use and GHG Emissions for Pavement Construction, and Fuel Conversion Method. The results show energy consumption of the project for the flexible and rigid pavements are 1193.79 GJ and 952.056 GJ, respectively. This indicates that the flexible pavement contributes to CO2 emissions greater than the rigid one. The flexible pavement has a total emission of 89257.96 kgCO2/km, while the rigid pavement is of 70464.53 kgCO2/km. Based on these results it can be concluded that rigid pavement is considered more environmentally friendly than flexible pavement.
Effect of functionalization of multiwalled carbon nanotubes with aminated poly(ether sulfone) on thermal and mechanical properties of poly(ether ether ketone) nanocomposites

Multiwalled carbon nanotubes (MWCNTs) were functionalized with aminated poly(ether sulfone) (PES) through the amidation reaction. Characterizations by Fourier transform infrared spectroscopy and X-ray diffraction corroborated the success of grafting reaction. Raman spectra reveal that no further damage occurred after the anchoring of PES to the carboxylated MWCNTs. Transmission electron microscopy shows that PES functionalization resulted in better dispersion of MWCNTs than acid oxidation. Poly(ether ether ketone) (PEEK)/MWCNTs functionalized with PES (PES-MWCNTs) nanocomposites were fabricated by solution-mixing and compression-molding techniques. Thermogravimetric analysis indicates that PES-MWCNTs/PEEK nanocomposites have the highest degradation temperature and thermal stability. Furthermore, noticeable increases in the crystallization and melting temperature as well as in the degree of crystallinity were found from differential scanning calorimetry thermograms, attributed to the strong heterogeneous nucleating role of PES-MWCNTs. Tensile test presents that the attachment of PES to the surface of MWCNTs exceptionally improved the tensile strength and Young’s modulus, and obtained moderate elongation at break. Impact toughness test and dynamic mechanical analysis show that the addition of PES-MWCNTs greatly enhanced the toughness and storage modulus of PEEK, respectively. These results are attributed to improved dispersion of PES-MWCNTs and strong interfacial adhesion to matrix, which is evidenced by scanning electron microscopy.
Assessment of Prediction Models of Confirmed, Recovered and Deceased cases due to COVID-19

Pandemic relates to a situation where any disease starts spreading geographically and affects a entire country or the whole world. So when an epidemic becomes pandemic, it really a question of our survival. COVID -19 has become a pandemic as we all know and needs real and underneath research on that. The procession of death is uncountable still now. It can cause significant economic, social, and political disruption. So it’s very necessary to know the impact of it on originating venue so that we can analyze its potential and rate of spreads. So to do this we have applied here some Machine learning algorithm and concepts of regression for prediction. In this present work we have made prediction model of confirmed cases, Recovered and death cases using K-Nearest Neighbour regressor and Gradient Boosting Regressor. The model performance is very good in predicting all the cases. The R squared value is very near to 1.
Epidemiology, pathogens  distribution, antibiotic susceptibility and the risk factors for mortality of patients with central nervous system infections: a retrospective study from 2012 to 2019 in a teaching hospital in China

Background: Central nervous system (CNS) infections are relatively rare but associated with high mortality worldwide. Empirical antimicrobial therapy is crucial for the prognosis of patients with CNS infections, which should be based on the knowledge of pathogens distribution and antibiotic sensitivities. China is a vast country, and the pathogens distribution varies nationwide. The aim of this study is to investigate the features of pathogens in patients with CNS infections in north China and we tried to evaluate the risk factors for mortality.Methods: We retrospectively analyzed the patients with positive cerebrospinal fluid (CSF) culture in a teaching hospital between January 2012 and December 2019. The following information were collected: demographic characteristics, laboratory data, causative organisms and antimicrobial susceptibility results. Univariate analysis and binary logistic regression analysis were performed to identify the risk factors for mortality.Results: In this eight-year retrospective study, a total of 72 patients were diagnosed with CNS infections and 86 isolates were identified. Among all the microorganisms detected, Gram-positive strains consisted of 59.3%, Gram-negative bacteria of 30.2% and fungi of 10.5%. The predominant Gram-positive isolate was coagulase-negative staphylococci. Acinetobacter baumannii, Escherichia coli and Klebsiella were the common Gram-negative strains. Compared to 2012-2015 years, the proportion of Gram-negative bacteria increased markedly during 2016-2019 years. Vancomycin, teicoplanin and linezolid were still 100% sensitive to Gram-positive bacteria. For the multidrug-resistant Gram-negative bacteria, only tigecycline was the 100% sensitive antibiotics. The mortality of the 72 patients was 30.6%. In the multivariate analysis, age >50 years, combined pulmonary infection and CSF glucose < normal value were associated with poor prognosis. Conclusions: CNS infections cause high mortality worldwide. Although Gram-positive bacteria are still the primary pathogen of CNS infections, Gram-negative bacteria had increased in recent years and should be considered in the choice of empirical antibiotic treatment. Special attention should be given to older patients and those combined pulmonary infection and with low CSF glucose level.
Anthropogenic Impact on Beach Heterogeneity within a Littoral Cell (Northern Tuscany, Italy)

In this paper the evolution of the Northern Tuscany littoral cell is documented through a detailed analysis of the increasing anthropogenic pressure since the beginning of the 20th century. This sector of the Tuscany coast has been experiencing strong erosion effects that resulted in the loss of large volumes of sandy beaches. The anthropogenic impact on natural processes have been intensified by the construction of two ports in the early decades of the 20th century. Competent authorities reacted by building hard protection structures that tried to fix the position of the shoreline but offset the erosion drive downdrift. Therefore, in the last 20 years a regional Plan was undertaken to gradually replace the hard defense schemes with a softer approach, which involved a massive use of sediment redistribution activities. Many nourishments have been done ever since, using both sand and gravel. All these hard and soft protection operations have been archived in a geodatabase, and visualized in maps that clearly show the progressive change from hard to soft defense. This database may improve the approach to any future analysis of the littoral cell both in terms of research and management, while providing a practical example that may be easily replicated elsewhere.
Stability Indicating RP-HPLC Method for In-Vitro Analysis of 5-Flurouracil

5-Flurouracil (FU), {5-fluoropyrimidines-2, 4(1H, 3H)-dione} is an anticancer drug that competitively inhibits thymidylate synthatase, an enzyme required for DNA synthesis that leads to programmed cell death of proliferating cells. It is used as topical cream for squamous cell carcinoma but a little information is available for its active drug targeting. Our attempt is to generate a validated stability indicating RP-HPLC method for the quantitation of 5-FU for active targeting to squamous cell carcinoma. In our study, RP-HPLC system used was (SHIMADZU (AT vp), Japan) and comprised of UV detector (SCL-10A vp), a pump system (LC-10 AT vp), and an injector. The separation was achieved on C18 LiChrospher®100 (250 x 4.6 mm, 5 μm) and elution was monitored gradiently with mobile phase consisting of HPLC water at a flow rate of 1ml/min. The injection volume was 20 μL previously filtered through 0. 45μ membrane filter and elute was analyzed at the set wavelength of 269 nm. The proposed method was validated for various parameters such as specificity, linearity, precision, accuracy, and robustness. The calibration plot drawn was found to be linear over the concentration range of 1–10μg/mL and within the acceptable range (R2 = 0.999). The developed method was found to be simple, precise, and accurate and can be reproduced with LOD and LOQ of 0.007108 and 0. 021539μg/mL respectively. The degradation study at variable temperatures such as 0°C; 8°C, 25°C, 37°C and pH 1.2, 3.2, 4.2, 6.8 and 7.4 after storage for 24 h suggested that 5-FU was stable at aforementioned temperatures and pH. It further signifies that the method is suitable for in-process quality control analysis of new composition of 5-FU due to good accuracy and high degree of precision.
Analysis and optimization of a 12/14 double‐stator flux‐switching machine using low cost magnet

Flux ‐ switching permanent magnet (FSPM) machine attracted a great deal of attention for industrial applications owing to its high efficiency and high torque/power densities. However, on the downside, it suffers from high cost of rare ‐ earth permanent magnets (REPMs). Although employing ferrite magnets remarkably reduces the cost of material, ferrite magnet lower energy product will negatively affect the electromagnetic performance of this machine. As a solution, the double ‐ stator flux ‐ switching permanent magnet (DSFSPM) machine has been presented in this paper to improve the electromagnetic performance of a conventional ferrite based FSPM counterpart. In this regard, a new analytical approach followed by a brief discussion of the influence of rotor pole number on the electromagnetic performance of two DSFSPM machines with 10 ‐ and 14 ‐ pole rotors are studied. It is shown that 12/14 DSFSPM machine with ferrite magnets generates almost 30% more developed torque than the other with 10 ‐ pole rotor. Then, a comprehensive comparison on the electromagnetic performances of a 12/14 DSFSPM machine with ferrite magnets, and two 12/14 FSPM machines with REPMs and ferrite magnets are investigated by finite element method. Besides, a cost study highlights the monetary beneficial of the proposed 12/14 DSFSPM machine for the competitive EVs market. Furthermore, a laboratory scale 12/14 DSFSPM machine is designed based on analytical approach, optimized by Taguchi optimization method, and experimentally tested to validate both analytical and FEM results.
Temperature characteristics of Gate all around nanowire channel Si-TFET

This paper study the impact of working temperature on the electrical characteristics of gate all around nanowire channel Si-TFET and examines the effect of working temperature on threshold voltage, transcondactance (gm), ION/IOFF ratio, drain induced barrier lowering (DIBL), and sub-threshold swing (SS). The (Silvaco) simulation tool has been used to investigate the working temperature on the Si-TFET characteristics. The temperature range in this study is from -25 to 150°C. The results indicate that the TFET must work in electronic circuits with the lower temperature as possible to get better performances. Furthermore, the TFET has good performances as a temperature nanosensor with diode connection mode under ON conditions.
“I’m a Teacher.” –Preschool Teachers’ Perception of Professional Self

Preschool education requires articulate, reflective and highly qualified teachers. However, within the teaching field, it is claimed that preschool teachers have the lowest perception of their own professional status. Determining the preschool teachers’ professional standing is problematic and begins with preschool teachers’ sense of professionals self. Using a mixed methods research methodology, the study garnered quantitative as well as personal insights into preschool teachers’ perception of professional self. The findings showed that the preschool teachers have an emerging perception of professionalism. The study also highlighted the importance in providing opportunities as well as space for teamwork within supportive professional communities. To further enhance professional learning, the study findings also highlighted the role of supportive mentors. Teacher education and professional development programs, together with statutory and professional institutions have to take the lead to improve the profession. Importantly, the preschool community must continue to develop leaders in a landscape that is evolving quickly.