Miracle-dz/UniFAR-FTUs huggingface dataset:
Nanoscale Structure of Langmuir–Blodgett Film of Bent-Core Molecules

Bent-core mesogens (BCMs) are a class of thermotropic liquid crystals featuring several unconventional properties. However, the interpretation and technological exploitation of their unique behavior have been hampered by the difficulty of controlling their anchoring at surfaces. To tackle this issue, we report the nanoscale structural characterization of BCM films prepared using the Langmuir–Blodgett technique. Even though BCMs are quite different from typical amphiphilic molecules, we demonstrate that stable molecular films form over water, which can then be transferred onto silicon substrates. The combination of Brewster angle microscopy, atomic force microscopy, and X-ray reflectivity measurements shows that the molecules, once transferred onto a solid substrate, form a bilayer structure with a bottom layer of flat molecules and an upper layer of upright molecules. These results suggest that Langmuir–Blodgett films of BCMs can provide a useful means to control the alignment of this class of liquid crystals.
Real-Time Monitoring of Critical Quality Attributes during High-Shear Wet Granulation Process by Near-Infrared Spectroscopy Effect of Water Addition and Stirring Speed on Pharmaceutical Properties of the Granules

To produce high-quality pharmaceuticals, a real-time monitoring method for the high-shear wet granulation process (HSWG) was developed based on near-infrared spectroscopy (NIRS). Samples consisting of lactose, potato starch, and hydroxypropyl cellulose were prepared using HSWG with varying amounts of purified water (80, 90, and 100 mL) and impeller speed (200, 400, and 600 rpm), which produces granules of different characteristics. Twelve batches of samples were used for the calibration and nine batches were used for validation. After drying, the median particle size (D50), tapped density (TD), and Hauser ratio (HR) were measured. The best calibration models to predict moisture content (MC), D50, TD, and HR were determined based on pretreated NIR spectra using partial least squares regression analysis (PLSR). The temporal changes in the pharmaceutical properties under different amounts of water added and stirring speed were monitored in real time using NIRS/PLSR. Because the most important critical quality attribute (CQA) in the process was MC, granule characteristics such as D50, TD, and HR were analyzed with respect to MC. They might be used as robust and simple monitoring methods based on MC to evaluate the pharmaceutical properties of HSWG granules.
Uniform Model and Analysis of PWM DC–DC Converter for Discontinuous Conduction Mode

ABSTRACT In this paper, a modified small signal state space average model is proposed to analyze the pulse width modulated converter operating in discontinuous conduction mode (DCM). It is based on a unique correction matrix (Mc) and new duty ratio constrain which is derived on the basic properties of inductor current. A 12 volt, 5 watt power supply based on Cuk converter is designed to demonstrate this proposed methodology. Transfer functions (input-to-output and control-to-output) of this power supply are calculated theoretically with the help of proposed modelling procedure. Bode plots of those transfer function are achieved using MATLAB toolboxes. To validate the proposed model, a simulation is also performed in MATLAB and frequency response is captured at run time using linearization technique. Bode plots from proposed model are very much in line with simulation results and offer improved predictions for high frequency dynamics of converter operating in DCM. The validity of presented work is reconfirmed by experimental set-up. The presented work is also compared with conventional small signal modelling on the basis of frequency analysis.
Challenges and Advantages of Zinc Bromide Flow Batteries in Power System Applications

This paper studies the challenges and advantages of Zinc Bromide Flow batteries for power system applications. To this end, the outcomes of several experiments are evaluated and summarized here. Some experiments dove into the weaknesses of Zinc Bromide flow batteries and solutions to those issues, while others went over the feasibility and cost effectiveness of implementing a Zinc Bromide storage solution for power grid applications. As seen from these experiments, the weaknesses of Zinc Bromide batteries are few and they do not prevent the technology from being a highly promising energy storage solution.
Exposure to Air Pollution from Road Traffic and Incidence of Respiratory Diseases in the City of Meknes, Morocco

For monitoring spatio-temporal variations of nitrogen dioxide (NO2) content, passive diffusive samplers have been deployed in 14 near-road and residential sites for 14 days. In parallel with the winter campaign to measure the NO2 tracer, road traffic counting sessions were carried out on the city’s main roads. The coupling of the results of the measurement campaigns and the counting sessions under Arcgis 9.3 made it possible to determine the areas most affected by automobile pollution and to carry out a high spatial resolution mapping of the pollutant prospected. The results of this study show that atmospheric NO2 concentrations reach maximum values in the city center and decrease towards its periphery. The analysis of the epidemiological situation of the principal diseases related to air pollution in the city of Meknes during the study period (2010–2014) showed that among subjects aged five years and older, acute respiratory diseases occurred more in women than men. The most affected age group was between 15 and 49 years, while asthma attacks were noted mainly among women aged 50 years and older. Acute respiratory illness and asthma attacks were prevalent in the winter and fall. Among children under five years of age, the age group most affected by pneumonia was those under 11 months. Our integrative approach combined spatialized GIS-based health indicators of these diseases, the location of stationary and mobile sources of air pollution, and measured NO2 levels. This combination has made it possible to detect that residents in areas with heavy road traffic are likely to be more affected than those in areas near industrial activity. The habitat type also contributes significantly to the development and exacerbation of the pathologies studied, especially in the districts of the old Medina.
A Two-Step Fuzzy MCDM Method for Implementation of Sustainable Precision Manufacturing: Evidence from China

Despite that products of precision manufacturing are widely used in many fields involving the national economy, precision manufacturing processes are more unfriendly to the environment, resources and social development than general manufacturing. Hence, the implementation of sustainable precision manufacturing (SPM) is of great strategic significance. There is no literature identifying and ranking the drivers of implementation of SPM and the impact on sustainability owing to the application of advanced manufacturing technologies in SPM has not been explored. To resolve these problems, drivers of SPM are identified based on combined support of prior studies and six groups of experts consisting of 71 individuals from six precision manufacturing enterprises. The drivers are calculated and ranked by a two-step fuzzy MCDM method which integrated the fuzzy AHP (fuzzy analytic hierarchy process) and fuzzy TOPSIS (fuzzy technique for order of preference by similarity to ideal solution) algorithms. The evaluation of drivers is based on the basic principles of sustainable development (environmental criterion, social criterion and economic criterion). The paper concludes that technological innovation, government support and current legislation are the most critical drivers during SPM implementation. Additionally, the result of sensitivity verification of the proposed method conducted proves the robustness and correctness of the algorithm and results.
Construction of a Prediction Model for College Students' Psychological Disorders Based on Decision Systems and Improved Neural Networks

Modeling and prediction of psychological disorders is a hot topic in current research. Neural networks are very important factors in improving the accuracy and precision ratios of the models which are developed for the prediction of the psychological disorders. An upgraded neural network prediction model of psychological diseases was suggested in order to attain an optimum prediction effect of psychological disorders. First, it analyzes the current progress in predicting the psychological barrier, finds the current limitations of various psychological barrier forecast model, collects the historical data of psychological barriers, and introduces the chaos algorithm of mental disorder history data preprocessing, psychological barriers to better mining change characteristic, and then, after pretreatment using neural network to the psychological barriers to learning history data, introduce the grain subgroup algorithm to improve the problems existing in the neural network, establish a prediction model of the optimal psychological barriers, and finally, through the contrast test and other psychological obstacle prediction model, the results depict enhanced neural network psychological barrier prediction accuracy of more than 95%, compared with the contrast model. Precision is improved by more than 5%. At the same time, the psychological barrier modeling time is shorter, improving the psychological barriers to predict. The efficiency has a higher practical application value.
HOW RELIGIOSITY, KNOWLEDGE, AND CHARACTERISTICS OF MUZAKKI AFFECT ZAKAT COMPLIANCE

Several things affect the achievement of targets, such as internal and external factors of the zakat management organization. The level of compliance with paying zakat is one of the external factors that can affect the receipt of zakat. So, this research will examine indicators that affect the level of compliance to pay zakat in Indonesia, using religiosity, knowledge, and characteristics of muzakki. The approach in this research is a quantitative approach with probit regression. This research collects 200 respondents as samples from Muslim-majority areas, such as East Java, Yogyakarta, Central Java, and South Sulawesi. It is hoped that this research will find indicators that can influence the level of muzakki compliance in paying zakat. The probit regression results, of all the variables used, there are two significant variables, namely religiosity and knowledge. Meanwhile, demographic variables such as age, income, education, marital status, and gender are insignificant because some people who pay zakat are not based on whether they have reached nishab. They always set aside 2.5% of their income for zakat after payday. The statement reinforces other evidence that people who pay zakat in Indonesia are more driven by factors of faith and trust. Theoretically, this study offers a new research model to explain muzakki compliance in paying zakat. Empirically, this research contributes to zakat managers' focus programs on increasing religiosity and knowledge of muzakki.
Identification of Collision Mechanism at Seismogenic Fault Interface Using Finite Element Analysis Involving Plate Bending Applications Using Ant Colony Optimization

Abstract Understanding space-time correlation in equilibrium matrix when force of collision involving earthquake stress strain interaction. The proposed study shows that non-linear dynamics of earthquake behaviour simulated with ant colony optimization in short timescale deformation by analysis of the stiffness matrix and the stress strain interaction process of the rock pattern. An improved ant colony optimization combined with local search is proposed for solving this complex optimization problem of finding trigger zones for earthquake occurrences. The disturbances at trigger basins for any system cause the collapse of a subsystem leading to stress evolution and slip due to strain nucleation. The stress strain network based on redistribution of stress accumulation are discretized into four states of low stress and strain and a finite element model is established to identify vertices for the stress-strain component and edges for global coupling effects have been constructed for dynamic monitoring of stress and strain behaviour at triggering zones. In this paper, an efficient algorithm is developed for the formation of null basis of triangular and rectangular plate bending finite element models, corresponding to highly sparse flexibility matrices. Triggering basins serve as harbingers of large earthquake where stress-strain interactions have been analyzed by the quasi-static mechanics of seismic precursory stress-strain propagation in the crustal lithosphere. The simulation framework shows that with time, spatial triggering points as stress varies from one point to another to identify the external influences for the body forces and the surface forces for geodynamic frameworks.
Hybrid Treatment of Tannery Effluent by Natural Coagulants for Vegetative Seed Germination

Treatment of the tannery wastewater by mixing the effluents in desired ratio, with natural coagulants prepared by using natural elements and small quantity of chemicals is a cost-effective method. Here, indigenous naturalcoagulant named chitosan extracted from shrimp-shell and Morinaga Oleifera seed as a bio-absorbent was used. To the best of knowledge, this comprehensive hybrid method not been investigated yet for tannery effluent treatment. Chitosan can also be used in water processing engineering as a part of a filtration process. Chitosan causes the fine sediment particles to bind together and is subsequently removed with the sediment during sand filtration. The Chitosan and Morinaga seeds extraction works on wastewater treatment in an excellent way. The reduction of BOD, COD, Salinity proves the effectively of these prepared coagulants from natural elements. Resultant coagulant treated wastewater significantly reduced the pollutants were 97% TDS, 46% COD, 10% Salinity and 43% BOD respectively and removal proves the effectivity of these prepared coagulants. Moreover, it will help on the designing a low-cost chemical free treatment technology of the tannery effluent as for attracting the tannery-owner to set up a treatment plant. At the same time, the effect of the treated water to the vegetative seed germination and growth was also examined. That can be identified the impact of application of the treated wastewater for irrigation. Journal of Engineering Science 13(1), 2022, 73-79
Synthesis of Cobalt Ferrite Nanoparticles Using Microemulsion Method: Structure, Morphology, and Magnetic Properties

Cobalt ferrite nanoparticles were prepared by the microemulsion method. Different values of pH of the microemulsion were maintained to find out the optimum pH to prepare cobalt ferrite nanoparticles. Prepared nanoparticles were characterized using X-ray Powder Diffraction (XRD), Vibrating Sample Magnetometer (VSM), and Scanning Electron Microscope (SEM). Rietveld refinement was used to analyze the crystal structure of the prepared cobalt ferrite nanoparticles. The crystallite size of prepared nanoparticles has been found from XRD in the range of 13.79 nm to 30.40 nm. The saturation magnetization, remanent magnetization, and coercivity have been found to be 12.05 emu/g, 0.77 emu/g, and 118.912 Oe respectively from VSM measurements. Journal of Engineering Science 13(1), 2022, 81-87
Comparison of conventional sensor with single mode optical fiber sensor for monitoring of partial discharge in oil insulation

High-voltage transformer is the most critical and expensive component in a power system network in order to ensure the stability of the system. Partial discharge (PD) is small electrical sparks present in an insulator as result of the electrical breakdown of a gas (for example air) contained within a void or in a highly nonuniform electric field. Partial discharge (PD) phenomenon is one of the reasons that happen in high voltage appliances and lead to failure of power transformer, leading to expensive repair and power outage. An acoustic emission (AE) phenomenon also happens near the discharge zone that is used to detect (PD). Partial discharge detection is a technique widely used for high voltage equipment insulation condition monitoring and assessment. Many researchers have used acoustic emissions (AE) at the vicinity of the discharge zones to detect PD. This project compares the sensitivity of single mode fiber optical sensor with capacitive sensor. The fiber optical sensor (FOS) and capacitive sensor were immersed in an oil tank fitted with two steel electrodes which were connected to different values of high voltage source. The data obtained by both sensors were then analyzed in time and frequency domain, and compared by peak analysis that suggest that single mode optical fiber was able to act as acoustic sensor with large wide band of signals. These experimental results are interesting which also suggest that both sensors have peculiar characteristics for the detection of AE and could be used as per the PD detection requirements.
Statistical Modeling of Data Breach Risks: Time to Identification and Notification

It is very challenging to predict the cost of a cyber incident owing to the complex nature of cyber risk. However, it is inevitable for insurance companies who offer cyber insurance policies. The time to identifying an incident and the time to noticing the affected individuals are two important components in determining the cost of a cyber incident. In this work, we initialize the study on those two metrics via statistical modeling approaches. Particularly, we propose a novel approach to imputing the missing data, and further develop a dependence model to capture the complex pattern exhibited by those two metrics. The empirical study shows that the proposed approach has a satisfactory predictive performance and is superior to other commonly used models.
Marine Actinomycetes Associated with Stony Corals: A Potential Hotspot for Specialized Metabolites

Microbial secondary metabolites are an important source of antibiotics currently available for combating drug-resistant pathogens. These important secondary metabolites are produced by various microorganisms, including Actinobacteria. Actinobacteria have a colossal genome with a wide array of genes that code for several bioactive metabolites and enzymes. Numerous studies have reported the isolation and screening of millions of strains of actinomycetes from various habitats for specialized metabolites worldwide. Looking at the extent of the importance of actinomycetes in various fields, corals are highlighted as a potential hotspot for untapped secondary metabolites and new bioactive metabolites. Unfortunately, knowledge about the diversity, distribution and biochemistry of marine actinomycetes compared to hard corals is limited. In this review, we aim to summarize the recent knowledge on the isolation, diversity, distribution and discovery of natural compounds from marine actinomycetes associated with hard corals. A total of 11 new species of actinomycetes, representing nine different families of actinomycetes, were recovered from hard corals during the period from 2007 to 2022. In addition, this study examined a total of 13 new compounds produced by five genera of actinomycetes reported from 2017 to 2022 with antibacterial, antifungal and cytotoxic activities. Coral-derived actinomycetes have different mechanisms of action against their competitors.
Research on the Simulation Model of Continuous Fiber-Reinforced Composites Printing Track

The rapid development of additive manufacturing technology (AM) is revolutionizing the traditional continuous fiber-reinforced polymer (CFRP) manufacturing process. The combination of FDM technology and CFRP technology gave birth to continuous fiber reinforced thermoplastic composites (CFRTPC) 3D printing technology. Parts with complex structure and excellent performance can be fabricated by this technology. However, the current research on CFRTPC printing mainly focuses on printing equipment, materials, and the improvement of mechanical properties. In this paper, the CFRTPC 3D printing track errors are investigated during the printing process, and it is found that the polytetrafluoroetylene (PTFE) tube in the nozzle of the printer head is often blocked. Through detailed analysis, a line-following mathematical model reflecting the deviations of the CFRTPC printing track is established. According to the characteristics of the fiber and its track during actual laying, a modified line-following model, without the minimum curvature point, is further proposed. Based on this model, the actual printing track for the theoretical path is simulated, the process tests are carried out on the printing track at different corner angles, and the relevant rules between the parameters of the model and different corner angles are obtained. The mathematical model is verified by experiments, and the clogging problem of the printer head caused by the fiber track error is solved, which provides theoretical support for the rational design of the fiber track in CFRTPC printing.
Prenatal Exposure to Locally Emitted Air Pollutants Is Associated with Birth Weight: An Administrative Cohort Study from Southern Sweden

While prenatal exposure to ambient air pollution has been shown to be associated with reduced birth weight, there is substantial heterogeneity across studies, and few epidemiological studies have utilized source-specific exposure data. The aim of the present study was, therefore, to investigate the associations between local, source-specific exposure to fine particulate matter (PM2.5) during pregnancy and birth weight. An administrative cohort comprising 40,245 singleton births from 2000 to 2009 in Scania, Sweden, was combined with data on relevant covariates. Investigated sources of PM2.5 included all local sources together as well as tailpipe exhaust, vehicle wear-and-tear, and small-scale residential heating separately. The relationships between these exposures, represented as interquartile range (IQR) increases, and birth weight (continuous) and low birth weight (LBW; <2500 g) were analyzed in crude and adjusted models. Each local PM2.5 source investigated was associated with reduced birth weight; average decreases varied by source (12–34 g). Only small-scale residential heating was clearly associated with LBW (adjusted odds ratio: 1.14 (95% confidence interval: 1.04–1.26) per IQR increase). These results add to existing evidence that prenatal exposure to ambient air pollution disrupts fetal growth and suggest that PM2.5 from both vehicles and small-scale residential heating may reduce birth weight.