Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of Surfactant‐Assisted Wettability Alteration on Immiscible Displacement: A Microfluidic Study

Drainage displacement at unfavorable viscosity ratios is often encountered in oil recovery, CO2 sequestration, and NAPL remediation, which significantly limits recovery of fluids from porous media. Surfactants have been extensively used as wettability modifiers to improve hydrocarbon recovery from rock matrix by imbibition. But little attention has been paid to the effect of surfactant‐assisted wettability alteration on displacement in non‐fractured porous media. In this study, we investigate surfactant‐assisted immiscible displacement in NAPL‐wet microfluidic chips. We find that the change of advancing contact angle by surfactant is velocity dependent. A stable displacement can be achieved at low velocity when wettability‐altering surfactant solution is used as injection fluid. In comparison, fingering occurs at all capillary numbers for water injection, resulting in low NAPL recovery. The generation of NAPL ganglion during waterflooding is significantly different from that during wettability‐altering surfactant flooding. The generation of NAPL ganglion during wettability‐altering surfactant flooding is related to velocity and saturation due to the wettability alteration and interfacial tension reduction. In contrast, the production of NAPL ganglion during waterflooding is only saturation dependent. NAPL ganglia generated during wettability‐altering surfactant flooding are primarily within the pore‐size range and can be easily recovered in subsequent recovery processes. To the best of our knowledge, this study reveals for the first time the pore‐scale mechanism of surfactant‐assisted wettability on the immiscible displacement, which is important for highly efficient NAPL remediation.
Anonymization Techniques for Privacy Preservation in Social Networks: A Review

Any data that user creates or owns is known as the user's data (For example: Name, USN, Phone number, address, email Id). As the number of users in social networks are increasing day by day the data generated by the user's is also increasing. Network providers will publish the data to others for analysis with hope that mining will provide additional functionality to their users or produce useful results that they can share with others. The analysis of social networks is used in modern sociology, geography, economics and information science as well as in various fields. Publicizing the original data of social networks for analysis raises issues of confidentiality, the adversary can search for documented threats such as identity theft, digital harassment and personalized spam. The published data may contain some sensitive information of individuals which must not be disclosed for this reason social network data must be anonymized before it is published. To do the data in nominate the anonymization technique should be applied, to preserve the privacy of data in the social network in a manner that preserves the privacy of the user whose records are being published while maintaining the published dataset rich enough to allow for the exploration of data. In order to address the issue of privacy protection, we first describe the concept of k-anonymity and illustrate different approaches for its enforcement. We then discuss how the privacy requirements characterized by k-anonymity can be violated in data mining and introduce possible approaches to ensure the satisfaction of k-anonymity in data mining also several attacks on dataset are discussed.
The application of ensemble precipitation forecasts to reservoir operation

Although inflow forecasts are useful information that can be used for improving reservoir operation efficiency, uncertainty is still a challenge for getting sound operation results. Ensemble precipitation forecasts can take uncertainties under consideration, so they have been a research topic for improving reservoir operations. In this paper, a rainfall–runoff model, combined of a multiple linear regression model (for non-flood seasons) and the Xinanjiang model (for flood seasons), for inflow forecasts and a stochastic dynamic programming model for reservoir operations are developed in order to effectively use the ensemble precipitation forecast. To explore the best way for using the ensemble precipitation forecast, two post-processing techniques, i.e., ensemble forecast averaging (EFA) and interval value (IV), are tested. The ensemble precipitation forecast from the European Centre for Medium-Range Weather Forecasts (ECMWF) was chosen due to its high accuracy, and the Huanren reservoir, located in China, was used to test the newly developed models. The results show that, compared with the traditional rule curve, hydropower generation increases by 4.86% and 4.55%, respectively, when EFA and IV are used, which indicates that the use of ensemble forecasts facilitates considerable improvements in operating performance.
OBTENÇÃO DA MISTURA CASCA DE UVACONCENTRADO PROTÉICO DE SORO DE LEITE EM PÓ POR ATOMIZAÇÃO EM SPRAY DRYER: INFLUÊNCIA DAS CONDIÇÕES DE PROCESSO NO RENDIMENTO E QUALIDADE DO PRODUTO

RESUMO – O resíduo agroindustrial da uva Isabel (Vitis labrusca) ou o bagaço da uva é um descarte da indústria de vinhos e sucos de uva, todavia apresenta grande quantidade de compostos fenólicos. As antocianinas são pigmentos de plantas com alta atividade antioxidante que conferem a coloração avermelhada das cascas e polpa da uva. Entretanto, são sensíveis a luz, calor e presença de oxigênio, entre outros. A secagem por spray dryer (microencapsulação) é indicada para produtos termo-sensíveis, uma vez que a rápida formação do pó a temperaturas moderadas garante uma alta retenção do aroma, da cor e dos nutrientes. Este trabalho teve por objetivo a produção de um material particulado a partir do processo de microencapsulação da polpa de casca de uva-concentrado protéico do soro do leite, analisando-se a influência das condições operacionais e concentração de adjuvante no rendimento do processo e qualidade do produto.
A Simple and Computationally-Efficient SHE Technique Utilizing the Same Notch Angles for the Entire Modulation Range

This paper proposes a novel and computationally efficient selective harmonic elimination (SHE) technique which eliminates the predefined lower order harmonics (till 19th order) from the phase voltage while controlling its fundamental. In conventional SHE schemes, the notch angles need to be computed online for each frequency in order to eliminate the harmonics and control the fundamental value. This involves intensive online computations and the convergence to the correct notch angles is not guaranteed, resulting in incorrect fundamental and/or presence of lower order harmonics. In contrast to this, a SHE technique, that uses the same pre-computed notch angles for all modulation indices, is proposed in this paper, thereby significantly reducing the computational burden. Here, the control of fundamental voltage at different frequencies is ensured by the concept of phase shifting of two identical notched waveforms. This ensures precise control of fundamental voltage while completely eliminating the pre-defined lower order harmonics. Moreover, the proposed scheme exhibits linear control till 0.582 times the DC-link voltage compared to 0.577 times the DC-link voltage in case of space vector PWM. The proposed method is validated experimentally on an induction motor drive system.
Measuring the effects of tourists’ relative willingness to spend and third-degree price discrimination on inbound tourism expenditure differentials

Tourism expenditures are determined by a set of antecedents that reflect tourists’ willingness and ability to spend, and de facto incremental monetary outlays at which willingness and ability is transformed into total expenditures. Based on the neoclassical theoretical argument of utility-constrained expenditure minimization, we extend the current literature by applying a sustainability-based segmentation criterion, namely, the Legatum Prosperity IndexTM to the decomposition of a total expenditure differential into tourists’ relative willingness to spend and an upper bound of third-degree price discrimination, using mean-level and conditional quantile estimates. Our results indicate that understanding the price–quantity composition of international inbound tourism expenditure differentials assists agents in the tourism industry in their quest for profit maximization.
Wind Farm Area Shape Optimization Using Newly Developed Multi-Objective Evolutionary Algorithms

In recent years, wind farm layout optimization (WFLO) has been extendedly developed to address the minimization of turbine wake effects in a wind farm. Considering that increasing the degrees of freedom in the decision space can lead to more efficient solutions in an optimization problem, in this work the WFLO problem that grants total freedom to the wind farm area shape is addressed for the first time. We apply multi-objective optimization with the power output (PO) and the electricity cable length (CL) as objective functions in Horns Rev I (Denmark) via 13 different genetic algorithms: a traditionally used algorithm, a newly developed algorithm, and 11 hybridizations resulted from the two. Turbine wakes and their interactions in the wind farm are computed through the in-house Gaussian wake model. Results show that several of the new algorithms outperform NSGA-II. Length-unconstrained layouts provide up to 5.9% PO improvements against the baseline. When limited to 20 km long, the obtained layouts provide up to 2.4% PO increase and 62% CL decrease. These improvements are respectively 10 and 3 times bigger than previous results obtained with the fixed area. When deriving a localized utility function, the cost of energy is reduced up to 2.7% against the baseline.
Doping titanium dioxide with copper, nitrogen, or sulphur : physico-chemical properties and their photo-catalytic activity towards emerging pollutants.

vi Acknowledgements . vii Dedication . ix List of Abbreviations . xvii List of Tables . xviii List of Figures . xx List of Equations . xxvii List of Schemes . xxviii Chapter
Cogging Torque Dynamic Reduction Based on Harmonic Torque Counteract

This article presents a method to reduce cogging torque in permanent magnet (PM) machines from dynamic control based on harmonic torque counteract (HTC). We find the possibility of dynamic cancellation of cogging torque and harmonic torque by studying their generation mechanism and period characteristics, and further study the current harmonic injection scheme for cogging torque reduction. Further, two case studies of an integer slot PM machine and a fractional slot PM machine based on finite element analysis well validate the proposed method. Among them, the cogging torque of a 6-slot/2-pole PM synchronous machine is weakened from 932.0 to 56.2 mN.m, with a weakening ratio of 94.0%, and the cogging torque of the other with 6-slot/4-pole is weakened from 1.23 N.m to 44.21 mN.m, with a weakening ratio of 96.4%. The theory of this article can be extended to PM machines with other different pole/slot combinations and topologies.
Characterization of flavour and volatile compounds of fermented squid using electronic nose and HPMS in combination with GC-MS

ABSTRACT The present study investigated the flavour characteristics and key volatile components of fermented squid (Dosidicus gigas) as well as their formation mechanism by three different starter cultures of lactic acid bacteria (LAB) and natural squid. The sensory assessment, volatile compounds, as well as the amino acids of the mixed fermented squid were detected using pickled brine as samples of fermented squid. A total 88 types of volatile compounds were found in four samples by 0–72 h of fermentation. After fermentation by LAB, the volatile compounds of squid showed that the fermented squid with different started cultures differed mainly in terms of numbers of alcohols, ketones, and esters. Furthermore, the amounts of volatile compounds among three starter cultures were also obviously different. Gas Chromatography-Mass Spectrometer (GC-MS) analysis indicated that the mixed fermentation process contained relatively higher (+)-limonene (11.71%) (lemon scent) and 3-hydroxy-2-butanone (5.72%) (creamy taste). These compounds were not detected in the control group. The main flavour compounds of nonanal and 2, 4-decadienal were gradually reduced. Meanwhile, 2, 3-butanedione, 2-heptanone, 2-pentylfuran, and nonanoic acid are the key flavour components. The total principal component is 94.01%, which were clarified by electronic nose in combination with principal components analysis. After mixed fermentation by LAB, the total amino acid (TAA) content reached 85.36 g/100 g, which was almost twice the amount of the control, especially in aspartate, glutamate, and threonine. Our results indicated that LAB has obvious effects on deodorization and flavour promotion during the fermentation of squid. This study provided an important basis for the further development and utilization of squid.
Modeling of Moisture Content of Subgrade Materials in High-Speed Railway Using a Deep Learning Method

Moisture content of subgrade materials is an essential factor affecting frost heave deformation of high-speed railway subgrade in a seasonally frozen region. Modeling and predicting moisture transport play an important role in analyzing the subgrade thermal and hydraulic conditions in cold regions. In this study, a long short-term memory (LSTM) model was proposed based on subgrade material moisture in two sections during one winter and spring cycle from 2015 to 2016. The reliability of the model was verified by comparing the monitoring data with the model results. The results demonstrate that the LSTM model can be effectively used to forecast the dynamic characteristics of the moisture of subgrade materials. The data of simulated moisture content of subgrade materials have a root mean square error ranging from 0.17 to 0.47 in the training phase and from 0.20 to 10.5 in the testing phase. The proposed model provides a novel method for long-term moisture prediction in subgrade materials of high-speed railways in cold regions.
A Method of Defect Depth Recognition in Active Infrared Thermography Based on GRU Networks

Active infrared thermography (AIRT) is a significant defect detection and evaluation method in the field of non-destructive testing, on account of the fact that it promptly provides visual information and that the results could be used for quantitative research of defects. At present, the quantitative evaluation of defects is an urgent problem to be solved in this field. In this work, a defect depth recognition method based on gated recurrent unit (GRU) networks is proposed to solve the problem of insufficient accuracy in defect depth recognition. AIRT is applied to obtain the raw thermal sequences of the surface temperature field distribution of the defect specimen. Before training the GRU model, principal component analysis (PCA) is used to reduce the dimension and to eliminate the correlation of the raw datasets. Then, the GRU model is employed to automatically recognize the depth of the defect. The defect depth recognition performance of the proposed method is evaluated through an experiment on polymethyl methacrylate (PMMA) with flat bottom holes. The results indicate that the PCA-processed datasets outperform the raw temperature datasets in model learning when assessing defect depth characteristics. A comparison with the BP network shows that the proposed method has better performance in defect depth recognition.
Properties of cyanobacterial UV-absorbing pigments suggest their evolution was driven by optimizing photon dissipation rather than photoprotection

An ancient repertoire of UV absorbing pigments which survive today in the phylogenetically oldest extant photosynthetic organisms the cyanobacteria point to a direction in evolutionary adaptation of the pigments and their associated biota from largely UVC absorbing pigments in the Archean to pigments covering ever more of the longer wavelength UV and visible in the Phanerozoic.Such a scenario implies selection of photon dissipation rather than photoprotection over the evolutionary history of life.This is consistent with the thermodynamic dissipation theory of the origin and evolution of life which suggests that the most important hallmark of biological evolution has been the covering of Earths surface with organic pigment molecules and water to absorb and dissipate ever more completely the prevailing surface solar spectrum.In this article we compare a set of photophysical photochemical biosynthetic and other germane properties of the two dominant classes of cyanobacterial UV absorbing pigments the mycosporine like amino acids MAAs and scytonemins.Pigment wavelengths of maximum absorption correspond with the time dependence of the prevailing Earth surface solar spectrum and we proffer this as evidence for the selection of photon dissipation rather than photoprotection over the history of life on Earth.
A Secure Model to Protect Healthcare IoT System from Version Number and Rank Attack

Recently the entire world is witnessing a pandemic outbreak of COVID-19. Resultantly, the healthcare sector battles the challenges like inadequacy of staff members, feeble patient monitoring services, etc. IoT technology provides complete digitization. However, this healthcare IoT falls prey to various attacks and security threats. The main cause of the attacks is the IoT communication and routing protocols. Routing protocol for low power lossy network (RPL) provides the potent routing mechanism in the 6LoWPAN network. However, RPL is an unsecured protocol; hence providing security to IPV6-RPL connected devices is a challenging task. This paper modeled the rules for RPL protocol signatures like ETX, beacon interval, and energy consumption in a novel attack detection system. The simulation results proved that the proposed system detects the conventional as well as RPL specific attacks precisely version number and rank attacks in healthcare IoT systems with higher accuracy and detection rate.
Particle Number Emissions of Gasoline, Compressed Natural Gas (CNG) and Liquefied Petroleum Gas (LPG) Fueled Vehicles at Different Ambient Temperatures

Compressed natural gas (CNG) and liquefied petroleum gas (LPG) are included in the group of promoted transport fuel alternatives for traditional fossil fuels in Europe. Both CNG and LPG fueled vehicles are believed to have low particle number and mass emissions. Here, we studied the solid particle number (SPN) emissions >4 nm, >10 nm and >23 nm of bi-fuel vehicles applying CNG, LPG and gasoline fuels in laboratory at 23 °C and sub-zero (−7 °C) ambient temperature conditions. The SPN23 emissions in CNG or LPG operation modality at 23 °C were below the regulated SPN23 limit of diesel and gasoline direct injection vehicles 1/km. Nevertheless, the limit was exceeded at sub-zero temperatures, when sub-23 nm particles were included, or when gasoline was used as a fuel. The key message of this study is that gas-fueled vehicles produced particles mainly <23 nm and the current methodology might not be appropriate. However, only in a few cases absolute SPN >10 nm emission levels exceeded 6 ×1011 1/km when >23 nm levels were below 6 ×1011 1/km. Setting a limit of 1 ×1011 1/km for >10 nm particles would also limit most of the >4 nm SPN levels below 6 ×1011 1/km.
Development and verification of the programming resilience scale for university students

Learning programming challenges students who encounter difficulties such as resolving syntax and format errors. These challenges require students to invoke resilience to overcome programming problems and keep trying. In response, this study developed the programming resilience scale for university students (PRSUS). The snowball-sampling method was used to collect the data of science and engineering undergraduates, and the participants were divided into two groups (n1 = 316, n2 = 358) for an exploratory and a confirmatory factor analysis, respectively. For the PRSUS, 3 items were retained for each of 4 dimensions, namely: persistence, perceived value, difficulty cognition, and incremental belief. The reliability and validity indexes indicate the scale is reliable for measuring programming resilience. Moreover, the results showed that most undergraduates had a high level of programming resilience, and they could judge their level correctly in comparison to their peers. The study also found that, although no significant difference was found among the grade or age groups, the programming resilience of the male students was significantly better than that of the female students. The PRSUS is expected to help researchers and teachers to identify students who have difficulties learning programming and to provide early interventions to students. Implications for practice or policy: Students can use the PRSUS to test if they have a high level of programming resilience and improve their programming resilience in a targeted way. Educators can use the PRSUS to identify students who find it difficult to finish programming learning or to judge whether their teaching can make students more willing to overcome programming difficulties.
Not diverse enough? Displacement, diversity discourse, and commercial gentrification in Santa Ana, California, a majority-Mexican city

This research investigates how diversity discourse unfolds as part of commercial gentrification when public and private growth actors call for increased diversity in a city that is majority Latinx in the United States. My argument is twofold: first, commercial gentrification is itself a racialised project to manage diversity; second, the discourse around diversity foments spatial strategies used by both state and private actors that dislocate immigrant communities and economies. This in-depth case study using Santa Ana, California, provides a more nuanced understanding of the relationship between diversity and commercial gentrification in a majority Mexican immigrant city. The research finds that, as diversity discourse promotes liberal colourblind practices within a majority Latinx city, it also contributes to distributing resources along racial lines. Diversity discourse presented a liberal and inclusive form of gentrification while also providing a justification for the displacement of immigrant-serving businesses by positioning them as exclusionary or backward. The dislocation or erasure of immigrant-serving businesses occurred through spatial strategies backed by the state to make new property available in the downtown commercial area. Removal was not only physical but also occurred through assimilation, wherein businesses ‘adapted’ to survive. Planning and development actors in this case failed to recognise the value of cultural and economic community networks while also diverting attention and resources away from immigrant-serving businesses. The case provides unique insight into the multiplicity of economic and political interests in a Latinx-majority place.
Fuzzy Prediction Intervals Using Credibility Distributions

We present a new forecasting scheme based on the credibility distribution of fuzzy events. This approach allows us to build prediction intervals using the first differences of the time series data. Additionally, the credibility expected value enables us to estimate the k-step-ahead pointwise forecasts. We analyze the coverage of the prediction intervals and the accuracy of pointwise forecasts using different credibility approaches based on the upper differences. The comparative results were obtained working with yearly time series from the M4 Competition. The performance and computational cost of our proposal, compared with automatic forecasting procedures, are presented.