Miracle-dz/UniFAR-FTUs huggingface dataset:
Kinetics of carbon dioxide, methane and hydrolysis in co-digestion of food and vegetable wastes

Kinetic models which can express the behaviors of hydrolysis and biogas generation more precisely than the conventional models were developed. The developed models were evaluated based on the experimental data of six batch reactors. Anaerobic digestion test was co-digestion of food and vegetable waste with inoculating horse dung by 15% of the total wet weight, at the temperature of 37oC. For hydrolysis, the modified model was developed from an original first-order kinetic model. The modified first-order kinetic model was proved to be better than the original one with the hydrolysis rate constant in the range of 0.22-0.34/day and hydrolyzable rate of 0.80 to 0.84. Kinetics of carbon dioxide and methane were developed from a current potential model. The comparison between experimental data and modeling values had the high correlation of determination (0.9918-0.9998) and low root mean square errors (0.08-4.51) indicating the feasibility of the developed model. In which, the evolution of methane showed the rate constant in the range of 0.031-0.039/day. The carbon dioxide from fermentation accounted for 12-44% of the total observed carbon dioxide. Thus, separation of fermentation and methanogenesis by various reactors may reduce the price of methane enrichment significantly. There was a lag time between methanogenesis and fermentation in reactors (λ = 7-11 days). Also, the biogas yield was in the range of 431.6-596.9 Nml/g-VS with the CH4 concentration of 56.2-67.5%. The best methane yield (393.7 Nml/g-VS) was in a reactor with food waste to the vegetable waste ratio by 1.8:1 (wet basis) and C/N ratio by 25.4.
FinFET Inverter Designs: Behavior and Challenges of Process Variability

Abstract— Technology scaling alongside the increasing process variability impact in modern technology nodes are themain reasons to control deviations over metrics in IC nanome-ter designs. Schmitt Triggers are traditionally used for noise immunity enhancement, and have been recently applied to mitigate radiation effects and process variability impact. The main contribution of this work is to trace the relationship between transistor sizing, supply voltage, and process variability to get a low energy consumption circuit while still keeping low levels of deviations due to the impact of process-induced variability. It is shown that a cost-benefit analysis can highlight sets of sizing and supply voltage where it can provide a 37.51% decrease in energy consumption while only increasing its sensibility by 7.42%. Furthermore, it is presented that the dependence of supply voltage and sensibility to process variability is not directly related, with slight decreases in the supply volt-ages bringing better results. Overall, the traditional CMOS inverter is still the fastest and most energy-efficient circuit, although, when comparing noise immunity characteristics, the 6-Transistor Schmitt Trigger presents higher noise margins, slopes, gains, and hysteresis ratios. The improvements,although, may increase propagation times, energy consumption, and area.
Influence of individual versus collaborative peer assessment on score accuracy and learning outcomes in higher education: an empirical study

Abstract Maximising the accuracy and learning of self and peer assessment activities in higher education requires instructors to make several design decisions, including whether the assessment process should be individual or collaborative, and, if collaborative, determining the number of members of each peer assessment team. In order to support this decision, a quasi-experiment was carried out in which 82 first-year students used three peer assessment modalities. A total of 1574 assessments were obtained. The accuracy of both the students’ self-assessment and their peer assessment was measured. Results show that students’ self-assessment significantly improved when groups of three were used, provided that those with the 20% poorest performances were excluded from the analysis. This suggests that collaborative peer assessment improves learning. Peer assessment scores were more accurate than self-assessment, regardless of the modality, and the accuracy improved with the number of assessments received. Instructors need to consider the trade-off between students’ improved understanding, which favours peer assessment using groups of three, and a higher number of assessments, which, under time constraints, favours individual peer assessment.
Factors associated with grain feeding in dairy farms located in the central-western region of Paraná State, Brazil

This study aimed to investigate factors associated with grain feeding and determine the typology of dairy farms that use high-grain diets. Twenty-two farm operators were interviewed in three municipalities located in the central-western region of Paraná state, Brazil. Information on reproductive and nutritional management practices, sociodemographic characteristics, and farm performance was collected. Data were analyzed using exploratory factor analysis, hierarchical cluster analysis, and multiple linear regression. Three factors (F1, F2, and F3) were extracted, which together explained 82.61% of the total variance. F1 comprised diet quality, technology, and breeding composition. F2 comprised labor and size. F3 comprised feed quality and schooling. Farms were classified into four groups and compared in terms of factor scores and performance parameters. Group 1 had the highest mean score on F1 (0.715), group 4 on F2 (1.642), and group 2 on F3 (1.116). Groups 4 and 1 had the highest milk productivity (2043.50 and 399.52 L day−1, respectively) and labor efficiency (418.16 and 148.63 L worker−1 day−1, respectively). Group 4 also had the highest mean number of cows per worker (25.52 cows worker−1). Regression analysis revealed that diet quality, technology, and breeding composition (F1) explained the variance in cow productivity. Labor and size, (F2) explained the variance in number of cows per worker. Daily productivity and labor efficiency were explained by both F1 and F2. Feed quality and farm operator’s level of schooling did not explain the variation in any of the variables. We found that roughage quality, breeding technology, and herd breed composition are the major factors associated with grain feeding. Farmers who feed cows high-quality roughage throughout the year and invest in genetic improvement and selective breeding strategies are more likely to adopt high-grain feeding and have high milk productivity.
Polyethylene/Clay/Graphite Nanocomposites as Potential Materials for Preparation of Reinforced Conductive Natural Gas Transfer Pipes

A series of high-density polyethylene/Cloisite 20A/graphite nanocomposites were prepared via melt blending for the production of polymeric pipes for natural gas transfer. The microstructural, mechanical, thermal, electrical and barrier properties of prepared nanocomposites were investigated. An intercalated morphology was observed for prepared nanocomposites. Improved mechanical properties e.g. over 148 % increase in Young’s modulus were observed by incorporating the nanoparticles into the polyethylene matrix. The thermal analysis showed that the melting point of polyethylene was slightly increased by incorporating both fillers, i.e. Cloisite 20A and graphite in it, and the crystallinity was depended on the type of filler. The results showed that the MFI values decreased by incorporating the fillers into the polyethylene matrix and further decreases were observed by increasing the contents of the filler. It was also found that a considerable amount of electrical conductivity is created in graphite loaded nanocomposites. The natural gas permeability investigations revealed of more than 51 % decrease in the permeability by incorporating 5 wt. % of Cloisite 20A to the polyethylene. It was concluded that the prepared nanocomposites due to their enhanced mechanical, thermal and barrier properties along with the conductive nature are excellent materials to be used in the production of polymeric pipes in natural gas distribution and transportation networks.
Begging for Crime? The Effect of State Laws Restricting Access to Temporary Assistance for Needy Families on Unsuccessful Completion of Parole

Transitioning from prison to the community can pose significant hardships as returning individuals seek to support themselves while searching for work and housing. Temporary Assistance for Needy Families (TANF) is one potential service that can help ease this transition, however, in numerous states TANF is not available to many former offenders. We conduct a fixed effects analysis on laws banning TANF assistance and state rates of unsuccessful parole completion between 1994 and 2016. We find that states that imposed restrictions on TANF saw an increase in state rates of unsuccessful parole completion. Furthermore, we find no significant difference between full bans and partial bans of TANF, indicating that even partial bans may undermine efforts to successfully reintegrate former offenders.
Classifying lymphoma and tuberculosis case reports using machine learning algorithms

Available literature reports several lymphoma cases misdiagnosed as tuberculosis, especially in countries with a heavy TB burden. This frequent misdiagnosis is due to the fact that the two diseases can present with similar symptoms. The present study therefore aims to analyse and explore TB as well as lymphoma case reports using Natural Language Processing tools and evaluate the use of machine learning to differentiate between the two diseases. As a starting point in the study, case reports were collected for each disease using web scraping. Natural language processing tools and text clustering were then used to explore the created dataset. Finally, six machine learning algorithms were trained and tested on the collected data, which contained 765 lymphoma and 546 tuberculosis case reports. Each method was evaluated using various performance metrics. The results indicated that the multi-layer perceptron model achieved the best accuracy (93.1%), recall (91.9%) and precision score (93.7%), thus outperforming other algorithms in terms of correctly classifying the different case reports.
Implementation of software for data processing of X-ray optical measurements for the analysis of structural parameters

The development of semiconductor nanoelectronic technology requires the use of new approaches to metrological control of critically important stages of device structure formation. The development and use of complex measurement methods based on various physical principles allowing one to obtain exhaustive information about the features of real structures, including the existence of hidden and unaccounted layers in transition areas, are of special interest. This paper presents the idea of implementing a complex approach to X-ray optical studies for a two-wavelength measurement scheme, including the methods of relative X-ray reflectometry, refractometry and diffuse X-ray scattering, and its application to the analysis of dimensional parameters of thin-film structures. The study was carried out with the help of a software package for analysing TiN diffusion-barrier layers. A comparison of the results obtained with the results of one-wavelength methods shows the high efficiency of the implemented approach for performing various tasks of metrological control of nanoelectronic devices.
The relationship between attitudes toward the teaching profession, occupational resilience belief, and extra-role behavior: A moderated mediation model

This study aims to examine the direct and indirect relationships between pre-service teachers’ attitudes toward the teaching profession, their occupational resilience beliefs, and their tendency to engage in extra-role behaviors within the framework of structural equation modeling. A relational survey model was used to design this quantitative investigation. The sample comprises 430 pre-service teachers who enrolled at four different programs at a state university in Turkey. The study used the attitudes toward teaching profession scale, the occupational resilience beliefs scale for pre-service teachers, and the extra-role behaviors scale (teacher form) as data collection tools. The researchers created hypothesis models examining the mediating and moderated mediating role of the occupational resilience belief in the effect that attitudes toward the teaching profession have on extra-role behaviors and tested these models within the framework of structural equation modeling. As a result of the study, it was found that the relationship strength between the attitudes toward the teaching profession, the occupational resilience belief, and extra-role behaviors was moderate. The study determined that occupational resilience belief plays a mediating role in the effect of pre-service teachers’ attitudes toward the teaching profession on extra-role behaviors. According to the results of the moderated mediation analysis, the influence of this indirect effect on extra-role behaviors varies according to the type of program studied, even though it does not differ significantly according to the class level of the pre-service teachers. This indirect effect is provided at the best level for pre-service teachers in the mathematics education program. However, the study concluded that the indirect effect influence significantly weakened in the Turkish education program. Moderated mediation model
Can Machines Learn Capital Structure Dynamics?

Yes, they can! Machine learning models that exploit big data identify leverage determinants and predict optimal leverage better than classical methods both in the cross-section and time-series. Using a large sample of U.S. firms from 1972 to 2018, we apply random forests, gradient boosting machines, neural networks, and generalized additive models to predict target leverage and analyze the contributing factors. Machine learning models that allow for nonlinearities and complex interactions boost the out-of-sample R-squared from 36% to 56% over linear methods such as LASSO. The superior predictive performance occurs every year of the out-of-sample period at the aggregate level as well as subsamples such as firms undergoing a major capital restructuring. The best performing model (random forests) selects market-to-book, industry median leverage, cash & equivalents, Z-Score, profitability, stock returns, and firm size as robust and reliable predictors of market leverage. Improved target measurement through machine learning implies smaller deviations from optimal leverage, and the speed of adjustment increases by 10%-34% relative to LASSO, lending stronger support to the dynamic trade-off theory. Machine learning depicts uncertainty, investment, and cash flow considerations as the most important drivers of the adjustment process.
Effect of engine size, speed, and dilution method on thermal stratification of premixed homogeneous charge compression–ignition engines: A large eddy simulation study

High heat release rates limit the operating range of homogeneous charge compression–ignition engines to low and medium loads. Thermal stratification has been shown to stagger autoignition, lower heat release rates, and extend the operating range of homogeneous charge compression–ignition engines. However, the dependence of naturally occurring thermal stratification on the engine size, speed, and internal residual dilution is not fully understood. A three-dimensional computational fluid dynamics model with large eddy simulations and detailed chemical kinetics was developed using CONVERGE. This model was used to simulate two different engines: (1) a light-duty 2.0 GM Ecotec Engine modified for homogeneous charge compression–ignition combustion in one of the cylinders and (2) a medium-duty Cummins B-series engine modified for homogeneous charge compression–ignition combustion in one of the cylinders. For the light-duty engine, five consecutive modeled cycles were compared with experimental data from 300 consecutive cycles using residual gas dilution at 2000 r/min. For the medium-duty engine, five consecutive modeled cycles were compared with experimental data from 100 consecutive cycles using air dilution with intake heating at 1200 r/min. In the light-duty engine, it was found that incomplete mixing between fresh charge and residual gas increased thermal stratification early in the compression stroke for residual dilution compared to air dilution. Residual stratification at the onset of ignition was small and not directly coupled with thermal stratification. Heat losses to the walls were the dominant source of thermal stratification at the onset of ignition. The reduced oxygen concentration due to residual dilution, increased the temperature requirement for autoignition, which increased heat transfer losses and increased the thermal stratification around top dead center. The thermal stratification before ignition reduced when the engine speed increased because of the lower heat transfer losses. The light-duty engine was found to have larger portion of the fuel energy lost to heat transfer than the medium-duty engine, which resulted in larger thermal stratification before ignition.
Synthesis of a chromium terephthalate metal organic framework and use as nanoporous adsorbent for removal of diazinon organophosphorus insecticide from aqueous media

Abstract MIL-101(Cr), as a chromium terephthalate metal organic framework (MOF), is synthesized hydrothermally and used for removal of diazinon from aqueous media. Different methods such as FT-IR, FE-SEM, TGA, XRD and BET analysis were applied for characterization of prepared MIL-101(Cr). The results revealed that MIL-101(Cr) has octahedral structure, 96% crystallinity, thermal stability up to 550 °C and about 2600 m2/g BET surface area with microporous structure. Adsorption experiments were designed by Design expert software and the effect of parameters such as pH (2–10), temperature (25–61 ), contact time (5–85 minutes) and adsorbent dosage (0.1–0.9 g/L) was investigated. Adsorption process was optimized by response surface methodology (RSM) and the optimum conditions of adsorption process was achieved in pH 6.5, temperature 25 °C, contact time 64 minutes and adsorbent dosage 0.74g/L which is lead to 96% removal of diazinon. In order to investigate the reusability and life time of MIL-101(Cr), the adsorbent is used in five successive cycles for adsorption of diazinon in fresh samples and good results are obtained. Langmuir and Freundlich isotherm models were deliberated by adsorption equilibrium data and Langmuir model show better conformity (R2 = 0.985) with the experimental results. Kinetic study was carried out using pseudo first order, pseudo second order and intraparticle diffusion kinetic models. Experimental data were better fitted to the pseudo second order with a correlation coefficient of 0.997 which signified that the experimental outcome of the adsorption of diazinon was a chemical adsorption. GRAPHICAL ABSTRACT
The compatibility performance of fuel system elastomers with two dioxolane molecules as blends with diesel

The compatibility of 17 elastomers with two dioxolane molecules was assessed by volume change and hardness measurements. Each molecule was blended with diesel in concentrations of 0, 10, 20 and 30 wt. %. The elastomers included two fluorocarbons, six acrylonitrile butadiene rubbers (NBRs), and one each of fluorosilicone, chloroprene rubber (CR), polyurethane, styrene butadiene rubber (SBR), hydrogenated NBR (HNBR), a blend of NBR and PVC (OZO), epichlorohydrin/ ethylene oxide (ECO), ethylene propylene diene monomer (EPDM), and silicone. Specimens of each elastomer were immersed in the test fuels for a period of 4 weeks and measured for property change. Afterwards they were dried at 60°C for 20 h and remeasured. The results showed that the dioxolanes were suitable with many of the elastomers and that the performances were essentially the same for both molecules. The dioxolanes were found to either have negligible impact beyond neat diesel or they produced a small increase in swell. This minimal impact is attributed to the fact that the solubility parameters (especially those associated with polarity and hydrogen bonding) of the dioxolanes are similar to those of diesel. As a result, little change in solubility and hence swell occurred when dioxolane was added to the diesel.
Colletotrichum Species Related To “Nam Dork Mai See Tong” Mango In Central Thailand And Risk Detection of Carbendazim-Resistant Strains

Nam Dork Mai See Tong mango is a deluxe commercial fruit in Thailand, however anthracnose disease becoming a major problem affecting market-driven. Fungicide treatment is the main component in the mango anthracnose management, notwithstanding the appearance of fungal-resistance has been become a factor of fungicide limition and can affect to increasingly higher costs. Thirty-two isolates of the Colletotrichum species complex were obtained from anthracnose-diseased mango cv. Nam Dork Mai See Tong in 3 provinces of Thailand. Fungal identification based on morphological and molecular markers was investigated. All isolates were divided into 3 species: C. asianum , C. gloeosporioides and C. siamense . Pathogenicity tests revealed that all 3 species caused symptoms on artificially unwounded mango fruits and leaves. Only C. gloeosporioides have previously been reported on mango, while C. asianum and C. siamense were first reports associated with mango in Thailand. The responsiveness of Colletotrichum isolates to carbendazim was evaluated using an MIC assay. Nine isolates of C. asianum were highly resistant, while 5 and 8 isolates of C. gloeosporioides were resistant (R) and highly resistant (HR), respectively. Moreover, all isolates of C. siamense were HR. Mutations were detected by PCR of a partial sequence of the β-tubulin gene. The sequence of β-tubulin gene in HR strains showed a single nucleotide transversion of adenine to cytosine, resulting in a substitution at codon 198. However, R strains were found to have only an amino acid change at codon 200. Additionally, PCR-RFLP was applied as a rapid technique to detect carbendazim resistance. The results demonstrated that only the Bsh 1236I restriction enzyme generated two bands (200 and 300 bp) in the highly resistant strain, but these bands were absent in the sensitive (S) and R strains. Hence, PCR-RFLP technique showed the potential to specifically detect benzimidazole fungicide resistance in 3 species of Colletotrichum. Moreover, this technique is accessible and feasible for laboratory assessment
The importance of thermal dissociation in CO2 microwave discharges investigated by power pulsing and rotational Raman scattering

The input power of a CO2 microwave plasma is modulated at kHz rate in scans of duty cycle at constant average power to investigate gas heating dynamics and its relation to dissociation efficiency. Rotational temperature profiles obtained from rotational Raman scattering reveal peak temperatures of up to 3000 K , while the edge temperature remains cold (500 K ). During the plasma ‘OFF’-period, the gas cools down convectively, but remains overall too hot to allow for strong overpopulation of vibrational modes (2200 K in the core). Fast optical imaging monitors plasma volume variations and shows that power density scales with peak power. As dissociation scales with observed peak rotational temperature, it is concluded that thermal processes dominate. A simple 0D model is constructed which explains how higher power density favors dissociation over radial energy transport. Thermal decomposition is reviewed in relation to quenching oxygen radicals with vibrationally excited CO2, to reflect on earlier reported record efficiencies of 90%.