Miracle-dz/UniFAR-FTUs huggingface dataset:
Techno-economic and uncertainty analyses of heat- and ultrasound-assisted extraction technologies for the production of crude anthocyanins powder from Hibiscus sabdariffa calyx

Abstract This study designed, techno-economically analyzed and compared the heat-assisted extraction (HAE)- and ultrasound-assisted extraction (UAE)-technology-based processes (HAE-tBP and UAE-tBP) for the production of crude anthocyanins powder (CAnysP) from Hibiscus sabdariffa calyx (HSC) with the assistance of SuperPro Designer software. Both the base cases and industrial setups of 600 L extractor capacities for HAE- and UAE-tBPs were analyzed and compared. When building the process flowsheets, peculiarities of the technicalities of both HAE and UAE extractors were taken into consideration. Materials and energy demands, production costs and unit production cost (UPC) of CAnysP were the parameters used for process analysis. Uncertainty and sensitivity analyses were conducted for the process with least CAnysP UPC using Monte Carlo simulations in Oracle Crystal Ball software. The HAE-tBP recorded the highest number of batches of 5278 per annum. HSC of 15.551 kg was required to produce 7.433 and 10.022 kg/batch CAnysP by 600 L extractor setup of HAE- and UAE-tBPs, respectively. The UAE-tBP achieved lower CAnysP UPC (164.28 US$/kg) compared with HAE-tBP (176.31 US$/kg) with 80.08% certainty. Out of the variables considered for sensitivity analysis of UAE-tBP UPC, ultrasound treatment time contributed the highest (+62%), while anthocyanins recovery contributed the least (+0.2%) to the variance in UPC.
Depressive and anxious symptomatology in a Lebanese sample during the COVID-19 outbreak

ABSTRACT This study explores the correlates of depressive and anxious symptomatology in a Lebanese sample during the COVID-19 outbreak. A convenience sample of 191 respondents participated in a cross-sectional survey and completed measures of fear of COVID-19, rumination about COVID-19, job insecurity, political trust, depression, and generalized anxiety. Results indicated that political trust was associated with greater wellbeing (manifested as decreased job insecurity, fear of COVID-19, depression, and anxiety). Respondents who reported no compliance with self-isolation measures reported less rumination about COVID-19 and less fear of COVID-19 than those who did. Multiple regression analyses showed that fear of, and rumination about, COVID-19 predicted depressive and anxious symptomatology while political trust was protective against depressive symptomatology only. This study provides a novel perspective on mental health in Lebanon, by focusing on its social and psychological predictors during the COVID-19 pandemic. Due to political and economic instability in Lebanon, the COVID-19 crisis may have deleterious effects on mental health in the Lebanese population. Internet-based cognitive behavioral therapy is an evidence-based and cost-effective approach to enhancing mental health during the pandemic and may be beneficial in the Lebanese context.
Power grid frequency prediction using spatiotemporal modeling

Understanding power system dynamics is essential for interarea oscillation analysis and the detection of grid instabilities. The FNET/GridEye is a GPS‐synchronized wide‐area frequency measurement network that provides an accurate picture of the normal real‐time operational condition of the power system dynamics, giving rise to new and intricate spatiotemporal patterns of power loads. We propose to model FNET/GridEye grid frequency data from the U.S. Eastern Interconnection with a spatiotemporal statistical model. We predict the frequency data at locations without observations, a critical need during disruption events where measurement data are inaccessible. Spatial information is accounted for either as neighboring measurements in the form of covariates or with a spatiotemporal correlation model captured by a latent Gaussian field. The proposed method is useful in estimating power system dynamic response from limited phasor measurements and holds promise for predicting instability that may lead to undesirable effects such as cascading outages.
Continuous Mechanical Extraction of Fibres from Linseed Flax Straw for Subsequent Geotextile Applications

Linseed flax is a multipurpose crop. It is cultivated for its seeds and particularly for its oil. The main contributors for this crop are Canada, France and Belgium. In general, straws of linseed flax are buried in the fields or burnt. However, these solutions are not good practices for the environment and from an economical point of view. In this study, straws of linseed flax (six batches in total) with different dew retting durations and harvesting techniques were studied to possibly use them for producing innovative geotextiles. Two different fibre extraction processes were investigated. A first process (A) involved horizontal breaker rollers and then a breaking card. A second one (B) consisted in using vertical breaker rollers, and an “all fibre” extraction device (fibre opener) followed by sieving. The chemical composition of fibres in parietal constituents appeared to be globally equivalent to the one of textile flax with a pectic content decreasing as a function of the dew retting duration. This contributed to an increase in the cellulose content. The fibre content was situated in a range from 29% to 33%, which corresponds to a good yield for linseed flax fibre. The level of purity can reach values of up to 90% for method A (without extra-sieving) and 96% for method B (with extra-sieving), and the length of the fibres (larger for method A than for method B) and their tensile properties make them suitable for structural geotextile yarn manufacturing.
Law Enforcement: The key to a Crime-free Society

ABSTRACT This paper intends to simulate a simple artificial society divided into two populations: criminal and non-criminal. The time evolution of the system is modeled using a set of differential equations, borrowing relevant features from the prey-predator, epidemic spread, and harvesting models. Each population can switch type upon interaction. The stability and equilibrium points of this system are examined, concluding that harvesting and interaction rates play an important role in the evolution of the system toward different stable equilibria between populations, which eventually coalesce into one. The results indicate that as long as the harvesting and conversion rates remain sufficiently small, the criminal population thrives. However, when either of the two crosses a certain value, the criminal population becomes extinct.
Influence of moisture/water absorption on mechanical and thermal properties of polyamide6/boric oxide composites

Purpose This paper aims to investigate the mechanical and thermal behavior, i.e. tensile strength, hardness, impact strength and glass transition temperatures of water-treated polyamide6/boric oxide (PA) composites. Design/methodology/approach The PA6 and PA6/boric oxide composites were exposed to an open environment and immersed in water for 15 days to analyze the effect of environmental humidity and frequent water immersion conditions on the composite’s mechanical and thermal properties. The tensile strength, elastic modulus, hardness and impact strength of materials were measured to identify the mechanical properties. The scanning electron microscopy (SEM), X-ray diffraction (XRD) and differential scanning calorimetry (DSC) characterizations were used to see the effect of humidity/water absorption on microstructure, crystallinity and glass transition temperatures. Findings The testing results revealed the loss in strength, elastic modulus and hardness, while the impact resistance was improved after exposure of materials to humidity/water. SEM images clearly show the formation of voids and XRD graphs revealed the loss in crystallinity after water immersion. The DSC plots of water immersed materials revealed the loss of glass transition temperatures up to 15°C. Originality/value The mechanical and thermal behavior of PA composites varies according to the surrounding atmosphere. Experiments were performed to investigate the influence of water treatment on the PA6/B2O3 composite’s mechanical and thermal properties. Water treatment resulted in the bonding between PA and water molecules, which generated voids in the materials. These voids generations are found the main reason for the low strength and hardness of water-treated materials.
Effects of gamma irradiation on structural, thermal and mechanical properties of polyamide-11/halloysite nanotubes nanocomposites

The effect of gamma irradiation on neat Polyamide-11 (PA11) and PA11 filled with 3 wt% of halloysite nanotubes (HNTs) was investigated at various doses up to 100 kGy in air and at room temperature. The irradiation test was conducted on sample films prepared by a twin-screw extruder in the first step then cast extrusion. The study showed the formation of a maximum of gel fraction up to 10 and 20 kGy for neat PA11 and PA11/HNTs, respectively. Furthermore, the results indicated the occurrence of crosslinking at low irradiation dose, whereas chain scission took place at higher ones. Additionally, the results revealed that the presence of HNTs limits the impacts of gamma irradiation through a barrier effect. An optimum irradiation dose was found for thermal and mechanical properties, corresponding to the dose for maximum gel formation. Moreover, experimental design was implemented to highlight the main incidences and interactions of both halloysite incorporation and radiation dose on some relevant effects of gamma irradiation.
A computational approach with residual error analysis for the fractional-order biological population model

ABSTRACT In this study, a fractional Bernstein series solution method has been submitted to solve the fractional-order biological population model with one carrying capacity. The numerical method has been implemented by an effective algorithm written on the computer algebraic system Maple 15. An error-bound analysis is performed by using a process similar to the RK45 method. An error estimation technique relating to residual function is presented. In the numerical application, the variations in the population of prey and predator with respect to time and situations of these two species relative to each other are plotted. The outputs obtained from our method are compared with the homotopy perturbation Sumudu transform method and reproducing kernel Hilbert space method. The approximate solutions gained from the Bernstein series method are consistent with those of other methods. The advantage of our method is that it requires less computational cost compared with methods involving more complex operations.
Hyperspectral imagery denoising using minimum noise fraction and VBM3D

Abstract. Hyperspectral imagery denoising is a classical problem in hyperspectral remote sensing applications. In our previous work, we combined principal component analysis with wavelet shrinkage, and good denoising results were obtained. We combine minimum noise fraction (MNF) with video block matching and 3D filtering (VBM3D), which is a powerful video denoising method. After MNF transform, we automatically select k0, the number of spectral band images as a threshold for denoising. We reduce the noise in spectral band images of MNF transformed data from k0 to the last band image and do not denoise the first k0 − 1 spectral band images. Finally, we perform an inverse MNF transform to obtain the denoised data cubes. We compare our MNF + VBM3D method with different denoising methods such as bivariate wavelet shrinkage (BivShrink), non-local means, SURELET, and block matching and 3D filtering (BM3D). Experimental results demonstrate that MNF + VBM3D achieves the best denoising results among almost all methods for three testing data cubes and with different noise levels.
Predicting patterns of persistence at a South African university: a decision tree approach

PurposeThe emerging field of educational data mining provides an opportunity to process large-scale data emerging from higher education institutions (HEIs) into reliable knowledge. The purpose of this paper is to examine factors influencing persistence amongst students enrolled in a Chemistry major at a South African university using enrolment data.Design/methodology/approachThe sample consisted of 511 students registered for a Chemistry major beginning in 2012, 2013 and 2014. Descriptive statistics in counts and percentages and classification (decision) tree methods were used in the analysis.FindingsGraduation from the Chemistry major is likely to occur after 4 years, which is regulation time plus 1 year, whilst departure mainly occurs in the first year of study. Classification tree modelling demonstrated that first year accumulated credits (FYAC), gender, financial aid status and school quintile were the factors associated with persistence. FYAC was the most critical factor.Research limitations/implicationsAlthough this study has many strengths, significantly the use of data mining methods to classify students, some limitations might affect how the results are interpreted. First, the analysis focused on a one-degree major in one institution, which leads to the suspicion that the observed results are discipline or institution-specific. Thus, the findings cannot be generalised to other contexts or disciplines. Second, with so many potential factors influencing student persistence, the analysis presented in this paper, which was limited to the covariates obtained in the institutional dataset the authors used, is by no means exhaustive. There is the possibility that some factors, which are not included in the present analysis, might have more predictive power.Originality/valueGlobally, university administrators are interested in predicting student outcomes and understanding the intricate balance between enrolment and throughput. Thus, whilst the findings from this study have an institutional focus, they resonate with other HEIs and present an alternative and highly visual way of identifying specific combinations of factors associated with persistence. The results from a classification tree model can also classify students at risk and inform the development of interventions that will support them.
Impact of entrainment-mixing and turbulent fluctuations on droplet size distributions in a cumulus cloud: An investigation using Lagrangian microphysics with a sub-grid-scale model

Entrainment-mixing and turbulent fluctuations critically impact cloud droplet size distributions (DSDs) in cumulus clouds. This problem is investigated via a new sophisticated modeling framework using the CM1 LES model and a Lagrangian cloud microphysics scheme – the “super-droplet method” (SDM) – coupled with sub-grid-scale (SGS) schemes for particle transport and supersaturation fluctuations. This modeling framework is used to simulate a cumulus congestus cloud. Average DSDs in different cloud regions show broadening from entrainment and secondary cloud droplet activation (activation above the cloud base). DSD width increases with increasing entrainment-induced dilution as expected from past work, except in the most diluted cloud regions. The new modeling framework with SGS transport and supersaturation fluctuations allows a more sophisticated treatment of secondary activation compared to previous studies. In these simulations, it contributes about 25%of the cloud droplet population and impacts DSDs in two contrastingways: narrowing in extremely diluted regions and broadening in relatively less diluted. SGS supersaturation fluctuations contribute significantly to an increase in DSD width via condensation growth and evaporation. Mixing of super-droplets from SGS velocity fluctuations also broadens DSDs. The relative dispersion (ratio of DSD dispersion and mean radius) negatively correlates with grid-scale vertical velocity in updrafts, but is positively correlated in downdrafts. The latter is from droplet activation driven by positive SGS supersaturation fluctuations in grid-mean subsaturated conditions. Finally, the sensitivity to model grid length is evaluated. The SGS schemes have greater influence as the grid length is increased, and they partially compensate for the reduced model resolution.
Indonesia Kris Representation on Virtual YouTuber “Anya Melfissa” Visual Identity

The rapidly evolving motion capture technology has made it possible to solve online identity problems with the medium of moving character design known as Virtual YouTuber. Spontaneous reaction in Livestream media can make fictional character feels real through a virtual avatar. As such, anthropomorphism representation can be used and Anya Melfissa is a Virtual Youtuber whose moe anthropomorphism of Indonesia Keris. However, the visual identity of Indonesia Kris is hard to find by most people and the problem is interesting to study using the theory of semiotics, anthropomorphism, and kris visual identity. The method used to analyze Anya Melfissa’s character design will use visual text analysis to identify its visual elements such as icon, index, and symbol. The results of the analysis show that Anya Melfissa’s character design has a kris visual identity which is at the level of thirdness in Peirce’s semiotics theory. The conclusion obtained from the kris representation in Anya Melfissa’s character design is proven to exist and requires a deeper level of understanding of Indonesian kris itself.
2D–Materials‐Based Quantum Dots: Gateway Towards Next‐Generation Optical Devices

A major focus on graphene‐based two‐dimensional (2D) materials is highlighted in recent days owing to their fascinating properties with widespread applications in electronic devices, catalysis, photonics and medicine. Here, we critically evaluate 2D materials based quantum dots (QDs) to understand the significant ways of fabrication adopted to meet their challenging demands in par with other 2D nanostructures to be in parallel with the current photonic technology with emphasis on future research scope to make use of these materials. We also discuss the different applications of 2D QDs emphasizing the realization of fluorescent probes which are in great demand to well‐establish these materials in the healthcare sector for the betterment of mankind. This study is a key priority and will bring a great impact in the advancement of simple yet challenging 2D QDs by bringing them towards the next level of applications point‐of‐view similar to that of graphene.
Information-Theoretic Limits for Steganography in Multimedia

Steganography in multimedia aims to embed secret data into an innocent multimedia cover object. The embedding introduces some distortion to the cover object and produces a corresponding stego-object. The embedding distortion is measured by a cost function that determines the probability of detection of the existence of secret embedded data. An accurate definition of the cost function and its relation to the maximum embedding rate is the keystone for the proper evaluation of a steganographic system. Additionally, the statistical distribution of multimedia sources follows the Gibbs distribution which is a complex statistical model that prohibits a thorough mathematical analysis.Previous multimedia steganographic approaches either assume a relaxed statistical distribution of multimedia sources or presume a proposition on the maximum embedding rate then try to prove the correctness of the proposition. Alternatively, this paper introduces an analytical procedure for calculating the maximum embedding rate within multimedia cover objects through a constrained optimization problem that governs the relationship between the maximum embedding rate and the probability of detection by any steganographic detector. In the optimization problem, we use the KL-divergence between the statistical distributions for the cover and the stego-objects to be our cost function as it upper limits the performance of the optimal steganographic detector. To solve the optimization problem, we establish an equivalence between the Gibbs and the correlated-multivariate-quantized-Gaussian distributions for mathematical thorough analysis. The solution to our optimization problem provides an analytical form for the maximum embedding rate in terms of the WrightOmega function. Moreover, we prove that the achieved maximum embedding rate comes in agreement with the well-known square root law (SRL) of steganography. We also establish the relationship between the achieved maximum embedding rate and the experimental results obtained from several embedding and detection steganographic techniques.
Winning, Losing, and the Quality of Democracy

Citizens who voted for a party that won the election are more satisfied with democracy than those who did not. This winner–loser gap has recently been found to vary with the quality of electoral democracy: the higher the quality of democracy, the smaller the gap. However, we do not know what drives this relationship. Is it driven by losers, winners, or both? And Why? Linking our work to the literature on motivated reasoning and macro salience and benefiting from the Comparative Study of Electoral Systems project—covering 163 elections in 51 countries between 1996 and 2018, our results show that the narrower winner–loser gap in well-established electoral democracies is not only a result of losers being more satisfied with democracy, but also of winners being less satisfied with their victory. Our findings carry important implications since a narrow winner–loser gap appears as a key feature of healthy democratic systems.
The relationship between social media context awareness and active coping during COVID-19: the mediation effect of positive reframing

Awareness of the context of social media is identified as an emerging technical capacity relating to the awareness of the social digital community in which a particular experience takes place, realizing the impact on the observer of the perceived social media context, rationalizing the process of social media information undergoing and owning trust for acting on social media. This investigation is an explorative research, analyzing data form 403 Romanian respondents in an online survey, regarding the psychological effect of the imposed social isolation, over respondent’s coping mechanisms. We used the Brief-COPE to determine efficient and inadequate ways to deal with adverse situations and the 4 items SMCA social media context awareness scale. The hypothesis is that the association between social media context awareness (SMCA) and active coping (AC) is mediated by positive reframing (PR), as a potential enhancer of active coping under prolonged social isolation periods over the general population. The standardized indirect effect found was (.11) × (.37) =. 04, supporting the mediation hypothesis, suggesting that rather than a direct causal relationship be-tween the SMCA and the AC, our mediation model proposes that SMCA influences the PF mediator variable, which in turn influences the dependent variable AC. Social media context awareness along with positive reframing as a mediator, in a stressful situation, are enhancers of an active coping mechanism.
Output Reduction over Time of Germicidal UV-C Lamps Used for Treating Agricultural Crops

ABSTRACT It is important in understanding the potential benefits of ultraviolet (UV-C) field applications for control of powdery mildew to know how long the lamps will last before replacement. We conducted a laboratory evaluation of a sample of low-pressure discharge germicidal UV-C lamps that have been used in field trials to control strawberry powdery mildew. None of the lamps tested failed to start after more than a year of operation. The degradation of UV-C output followed trends similar to those described by the manufacturer. Based on these measurement data and on the long history of this lamp technology, we predict that these lamps can continue to perform in the field after the manufacturer’s rated life of approximately 10,000 hours of continuous operation, by reducing the speed of application to deliver the prescribed UV-C dose. With protective sleeves, these low pressure discharge UV-C lamps can be expected to last for many years of service.