Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficiency of lipid accumulating Actinomycetes isolated from soil for biodiesel production: Comparative study with microalgae

ABSTRACT Due to the global warming and the increase of toxic gases emitted from the fossil fuels and the increase of energy demand, it is necessary to look for alternative sources for biodiesel. In this work, fifty bacterial species were isolated from soil samples and the isolated bacteria were tested for their ability of lipid production. The most potent lipid producer was identified as Streptomyces coelicolor A3-NC:003888.3 using the 16S rDNA partial sequencing technique. The lipid production process was performed in a bench scale for pure S. coelicolor, Chlorella vulgaris (as a standard biodiesel producer) and mixed algal bacterial culture as a comparative study. The results indicated that 93% wt of fatty acids of Streptomyces was converted to the corresponding fatty acid methyl esters (biodiesel). After transesterification of the produced lipids, the obtained oil was characterized according to American Society for Testing and Materials (ASTM) standards. The density of bacterial biodiesel was 0.866 and that of algal biodiesel was 0.797; also the specific gravity was 0.866 and 0.784 for bacterial and algal biodiesel, respectively, giving more lubricant characters for bacterial biodiesel. The gross heating value of bacterial biodiesel (43426 Kj/Kg) was higher than that of algal biodiesel (41896 Kj/Kg), dependently, the cetane number of bacterial biodiesel (38) was little lower than that of algal biodiesel (43).
Leveraging multi-model season-ahead streamflow forecasts to
trigger advanced flood preparedness

Abstract. Disaster planning has historically allocated minimal effort and finances toward advanced preparedness, however evidence supports reduced vulnerability to flood events, saving lives and money, through appropriate early actions. Among other requirements, effective early action systems necessitate the availability of high-quality forecasts to inform decision making. In this study, we evaluate the ability of statistical and physically based season-ahead prediction models to appropriately trigger flood early preparedness actions based on a 75 % or greater probability of surpassing the 80th percentile of historical seasonal streamflow for the flood-prone Marañón River and Piura River in Peru. The statistical prediction model, developed in this work, leverages the asymmetric relationship between seasonal streamflow and the ENSO phenomenon. Additionally, a multi-model (least squares combination) is also evaluated against current operational practices. The statistical and multi-model predictions demonstrate superior performance compared to the physically based model for the Marañón River by correctly triggering preparedness actions in all four historical occasions. For the Piura River, the statistical model proves superior to all other approaches, and even achieves an 86 % hit rate when the required threshold exceedance probability is reduced to 50 %, with only one false alarm. Continued efforts should focus on applying this season-ahead prediction framework to additional flood-prone locations where early actions may be warranted and current forecast capacity is limited.
Model-Agnostic Meta-Learning With Optimal Alternative Scaling Value and Its Application to Industrial Soft Sensing

In soft sensing, relationship variation of process variables and quality indicators may cause the model trained from the training datasets unsuitable for the prediction on the testing datasets. As the model-agnostic meta-learning can utilize the supporting datasets to strengthen the prediction performance of the query samples, it can maintain reliable prediction performance in relationship variation. However, the traditional model-agnostic meta-learning contains inconsistencies between the parameters evaluated in the training stage and those adapted in the predicting stage. The phenomenon is inferred as the dilemma of getting valuable evaluated parameters related to the initial parameters and accurate parameters representing the parameters adapted in the predicting stage. In this article, we propose the stage-related adaption block to use the model-agnostic meta-learning modularly. Finally, the model-agnostic meta-learning method based on the optimal alternative scaling value is proposed and verified in a numerical example and an industrial application.
Framing Effects and Group Differences in Public Opinion about Prison Pell Grants

ABSTRACT After years of gridlock on the issue, a bipartisan group of members of Congress struck a deal in 2020 to restore eligibility for inmates to access Pell Grants. Evidence indicates that college education programs in prison reduce recidivism and, consequently, state corrections expenditures, but legislators in prior decades feared that voters would resent government subsidy of college classes for criminals. To assess the contemporary politics of the issue, we analyze data from a framing experiment embedded in the 2016 Cooperative Congressional Election Study. We find that Americans, on average, neither support nor oppose the proposal to restore inmates’ Pell Grant eligibility; however, exposure to arguments about the proposal’s benefits to inmates in particular and American society more broadly both increased subjects’ support. We further explore how this framing effect varies across political partisanship and racial resentment. We find that both frames elicited a positive response from subjects, especially among Democrats and subjects with low or moderate racial resentment.
Children’s Interactions in Ability-based Groups in a Primary Classroom

The article reports data from an aspect of the study which aimed to study the nature of children’s interactions and their perceptions of ability-based groups in a primary classroom in England. Previous studies on ability-based group have mainly used quantitative research designs to study children’s interactions and appeared to award less opportunities to children to talk about their experiences of working in ability-based groups. This study has used qualitative ethnographic research design to study children’s interactions and their perceptions of working in ability-based groups. Children’s interactions were studied using participant observations and debriefing activities were used to elicit children’s perspectives on their recorded interactions. Furthermore, informal conversational interviews were also used to hear children’s perspectives on their experiences of working in ability-based groups. The article only focuses on data related to children’s interactions, which revealed that children appeared to be cooperative, non-cooperative and competitive towards their peers in ability-based groups. We noted that children interpreted the group structure and learning task distinctively when deciding whether or not to work with others in groups. In some cases, children exhibited gender-biased attitudes while interacting with their peers. Children showed cooperative attitudes towards same-sex peers and non-cooperative attitudes towards other-sex peers. The findings highlight the importance of fully understanding children’s contexts and their dynamic influences on children’s interactions during their routinely organised ability-based group work. These also highlight the importance of listening to children’s perspectives while studying their interactions in ability groups in the mainstream primary classrooms.
The Maimai M8 experimental catchment database: Forty years of process‐based research on steep, wet hillslopes

Global Institute for Water Security, University of Saskatchewan, Saskatoon, Saskatchewan, Canada School of Geosciences, University of Birmingham, Birmingham, UK Dept of Earth, Ocean & Atmospheric Sciences, University of British Columbia, Vancouver, British Columbia, Canada Landcare Research, Lincoln, New Zealand Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, Switzerland Centre for Hydrology, University of Saskatchewan, Canmore, Alberta, Canada School of Geographical Sciences, University of Bristol, Bristol, UK Cabot Institute, University of Bristol, Bristol, UK Hetch Hetchy Power, San Francisco, California, USA Division of Earth and Ocean Sciences, Nicolas School of the Environment, Duke University, Durham, North Carolina, USA GNS Science, Lower Hutt, New Zealand Department of Civil Engineering, Univeristy of Calgary, Calgary, Alberta, Canada Disaster Prevention Research Institute, Kyoto University, Kyoto, Japan Department of Geography, University of Zurich, Zurich, Switzerland Dept of Biological and Ecological Engineering, Oregon State University, Corvallis, Oregon, USA Faculty of Environment & Natural Resources, University of Freiburg, Freiburg, Germany Faculty of Engineering, University of Bristol, Bristol, UK
Deciphering temperature, pressure and oxygen-activity conditions of chlorite formation

Abstract The advantages and limits of empirical, semi-empirical and thermodynamic methods devoted to the estimation of chlorite-formation temperature are discussed briefly. The results of semi- empirical and thermodynamic approaches with different assumptions regarding the redox state of iron in chlorite are compared for a large set of natural data covering a range of pressure conditions from a few hundred bars to 18 kbar and temperature from 100 to 500°C. The T-XFe3+ evolution estimated using the thermodynamic approach of Vidal et al. (2005) shows a systematic increase in XFe3+ with decreasing temperature, which is compatible with the decrease in a02 buffered by magnetite- or hematite-chlorite equilibrium. This trend as well as the observed increase in vacancies in chlorite with decreasing temperature is interpreted as the incorporation of Fe3+-Sudoite. The standard-state properties of this end- member have been derived to reproduce the observed T-aO2-XFe3+ evolutions. It can be used to estimate T-aO2-XFe3 values with a Chl-Qtz-H2O multi-equilibrium approach. When combining our results with those of other studies published recently, it appears that thermodynamic approaches and mapping techniques developed for metamorphic rocks can be used to discuss the conditions of formation of very low-grade rocks where kinetics is much more sluggish than in metamorphic rocks. This requires use of appropriate analytical tools and techniques with a spatial resolution of a few hundred nanometres.
Tropical African wildfire aerosols trigger teleconnections over mid-to-high latitudes of Northern Hemisphere in January

This study investigates the impacts of African wildfire aerosols (primary organic carbon, black carbon and sulfate) on the Northern Hemispheric in January. We found that wildfire aerosols emitted from equatorial Africa result in two mid-to-high latitudes atmospheric Rossby wave trains. One is from subtropical Atlantic propagating northeastward across Europe to Siberia, and the other one propagates eastward from Middle East across Asia to Pacific Northwest. The maximum positive geopotential height anomaly locates in Europe, concurrent with a greater-than-2 K land surface warming. These Rossby wave trains are excited by the atmospheric heating that caused by the wildfire aerosols in equatorial Africa and propagate into extratropics with the help of the westerly jet. Based on the diabatic heat budget analysis, the Rossby wave source is primarily from the solar absorption of black carbon of African wildfire. The present study emphasizes that wildfire aerosols, especial the absorbing aerosols, would have profound climate effects on remote regions and thus need more attentions.
Optimum degradation test plan under model mis-specification for Wiener and gamma processes

Abstract Degradation tests have been used for the purpose of assessing reliability information. In this paper, we consider a degradation test design problem under a statistical model mis-specification scenario. The Wiener and gamma processes are considered in this research. A gamma process is suitable for describing degradation paths that exhibit monotone behavior. However, if one fits a Wiener process model to the data, the resulting statistical inferences may be affected. Tsai, Tseng, and Balakrishnan studied the effect on the estimated mean time to failure. However, the experimental design problem was not discussed. A lack of the explicit functional form of the estimation variances makes it difficult to find degradation plans that can improve test efficiency. In this paper, functional forms of optimal degradation test plans are proposed under model mis-specification. Furthermore, a weighted ratio objective function considering the prior probability of the true model is used to find robust test plans for practical use. The results from a numerical example show that, by using an appropriate degradation test plan, the estimation variance can be reduced, and the test efficiency can be improved. A simulation study is conducted to investigate the performance of the parameter estimates when the sample size is small.
At the molecular resolution with MINFLUX?

MINFLUX is purported as the next revolutionary fluorescence microscopy technique claiming a spatial resolution in the range of 1–3 nm in fixed and living cells. Though the claim of molecular resolution is attractive, I am concerned whether true 1 nm resolution has been attained. Here, I compare the performance with other super-resolution methods focusing particularly on spatial resolution claims, subjective filtering of localizations, detection versus labelling efficiency and the possible limitations when imaging biological samples containing densely labelled structures. I hope the analysis and evaluation parameters presented here are not only useful for future research directions for single-molecule techniques but also microscope users, developers and core facility managers when deciding on an investment for the next ‘state-of-the-art’ instrument. This article is part of the Theo Murphy meeting issue ‘Super-resolution structured illumination microscopy (part 2)’.
Solar‐powered switched reluctance motor‐driven water pumping system with battery support

Funding information Department of Science and Technology (DST), Govt. of India, Grant/Award Number: RP02979; Improvement of Science and Technology, Grant/Award Number: RP03195G Abstract This work deals with the development of an efficient and reliable solar photovoltaic-fed water pump with a battery energy storage (BES). This system ensures a continuous and rated supply of water in all working conditions. A new control logic for BES is developed, which significantly improves the overall response of the system. The support of the battery as a backup source is obtained through a bidirectional DC-DC converter. Both the charging/discharging control and maximum power tracking of the solar panel are achieved through this bidirectional converter, whereas the voltage asymmetry compensation across split capacitors at DC link and motor drive controls are supervised by switched reluctance motor converter. The performance of the present scheme is examined through both simulated and experimental responses and is found adequate under all operational scenarios.
Shape memory crosslinked polyurethanes containing thermoreversible Diels-Alder couplings

Crosslinked polyurethanes (PUs) containing irreversible (allophanate) and reversible Diels-Alder chemical bonds were synthesized using various diisocyanates (methylene diphenyl diisocyanate MDI, 1,6-hexamethylenediisocyanate HDI) and poly(ɛ-caprolactone) ((PCL) with different molecular weights (Mn = 10 kg/mol, 25 kg/mol, 50 kg/mol) as diol component. The melting/crystallization of PCL and the reversible DA bonds acted as temperature-activated switches for shape memory performances, while allophanate network provided the permanent crosslinks for these PUs. The reversible DA bonds were obtained by the reaction of diisocyanate-ended prepolymers with furfurylamine (FA) followed by the addition of bismaleimide (BMI). The permanent crosslinks between the linear chains containing DA bonds were achieved using additional amounts of diisocyanates (MDI or HDI). The above reaction path was supported by infrared spectroscopic results and swelling experiments. Tensile mechanical and shape memory properties in tension of the PUs were determined and discussed as a function of composition and crosslink densities deduced from swelling and dynamic mechanical analysis. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016, 133, 44145.
Direct chemical inhibition responsible for displacement of a native herbivore by an invasive congener

The mechanisms causing native displacement by invasive species are challenging to identify. We used survey data to demonstrate a local extinction of a native gastropod ( Pomacea paludosa ) from a Florida wetland coincident with invasion of a non-native gastropod ( P. maculata ). We then examined the potential for P. maculata to displace P. paludosa . We used two field experiments to examine effects of densities and heterospecific interactions on juvenile growth in situ and we used lab and mesocosm experiments to explore chemically-mediated interactions between the species. Field experiments produced variable results; evidence for reduced P. paludosa growth in the presence of P. maculata was found under higher nutrient conditions with fast snail growth rates, but growth inhibition disappeared under oligotrophic conditions. Resource reduction could not be demonstrated in the field. Juvenile P. paludosa did not avoid mucus of P. maculata and did not reduce feeding in response to cues. Nevertheless, exposure to mucus and waterborne cues of P. maculata reduced P. paludosa growth by 53% relative to conspecific cue exposure. In mesocosms juvenile P. paludosa growth was significantly negatively correlated with adult P. maculata waterborne cues and was particularly affected at exposures ≥60% (~0.6 · m -2 ). Combined mucus and waterborne cues appeared to further reduce growth at low exposure (20%). We documented the first apparent local extinction of P. paludosa by P. maculata. We found no evidence for competition, but the results collectively pointed to direct chemical inhibition of growth that could be important at field scales, even at low densities.
Deep Fusion Feature Extraction for Caries Detection on Dental Panoramic Radiographs

Caries is the most well-known disease and relates to the oral health of billions of people around the world. Despite the importance and necessity of a well-designed detection method, studies in caries detection are still limited and show a restriction in performance. In this paper, we proposed a computer-aided diagnosis (CAD) method to detect caries among normal patients using dental radiographs. The proposed method mainly consists of two processes: feature extraction and classification. In the feature extraction phase, the chosen 2D tooth image was employed to extract deep activated features using a deep pre-trained model and geometric features using mathematic formulas. Both feature sets were then combined, called fusion feature, to complement each other defects. Then, the optimal fusion feature set was fed into well-known classification models such as support vector machine (SVM), k-nearest neighbor (KNN), decision tree (DT), Naïve Bayes (NB), and random forest (RF) to determine the best classification model that fit the fusion features set and perform the most preeminent result. The results show 91.70%, 90.43%, and 92.67% for accuracy, sensitivity, and specificity, respectively. The proposed method has outperformed the previous state-of-the-art and shows promising results when none of the measured factors is less than 90%; therefore, the method is promising for dentists and capable of wide-scale implementation caries detection in hospitals.
An Efficient and Accurate Real Time Facial Expression Detection Using CNN

Real Facial expression acknowledgment (RTFER) has become a functioning examination zone that finds a ton of utilizations in territories like human-PC interfaces, human feeling investigation, mental investigation, clinical conclusion and so on Mainstream strategies utilized for this intention depend on math and appearance. Profound convolutional neural networks (CNN) have appeared to beat customary strategies in different visual acknowledgment errands including Facial Expression Recognition. Despite the fact that endeavours are made to improve the exactness of RTFER frameworks utilizing CNN, for functional applications existing strategies probably won't be adequate. This examination incorporates a conventional audit of RTFER frameworks utilizing CNN and their qualities and restrictions which assist us with comprehension and improve the RTFER frameworks further.
State-of-the-Practice Review on the Use of Flocculants for Construction Stormwater Management in the United States

Construction stormwater practices have a vital role in protecting downstream water bodies from runoff that is typically characterized with large amounts of sediment and suspended solids. Most sediment control practices lack the capability to capture fine-sized soil particles that are responsible for causing elevated turbidity. Flocculation is a form of chemical treatment that uses flocculant particles as a binding bridge to form larger particles to enhance the gravitational settling process. The use of flocculants provides promising results for removing fine particles and treating construction stormwater. This study provides a comprehensive review of flocculants and their applications in construction stormwater treatment in the U.S. The study presents a literature review and results of a state-of-the-practice survey distributed to state departments of transportation. Results from 37 participating state agencies and data from specifications and design manuals for non-participating agencies were compiled to develop a comprehensive understanding of current uses and perceptions. Results indicated that 39% of state agencies currently use flocculants on construction sites. Within that, 54% of the state agencies rely on manufacturer guidance for dosage and application rates and only 23% require monitoring residual flocculant in downstream receiving waters. The potential risk of polluting downstream water bodies because of overdosage of flocculants related to inadequate application rates and techniques is the main concern of the state departments of transportation on flocculant usage. Understanding the perspective of the state agencies on flocculants will provide an insight into future research agendas for extending the use of flocculants in construction stormwater management.
Numerical simulation of lithium‐ion battery performance considering electrode microstructure

A spatially resolved three‐dimensional microscale model of a lithium‐ion battery half‐cell is developed and applied to periodic electrode microstructures made up of spherical particles following a bidisperse particle size distribution. The geometries of the periodic unit cells are derived from discrete element simulations using periodic boundary conditions. Three different particle arrangements, which consist of two layered structures and one mixed particle array, as well as three different compression rates, are considered. In the study, the cathode is assumed to consist of LiMn2O4 as active material. Layered particle arrangements comprising the particle fraction of the smaller particle size in the region close to the separator are found to be beneficial especially for high‐rate applications. According to the simulation results, the high‐rate capability is reduced upon compression of the electrode microstructures. Copyright © 2015 John Wiley & Sons, Ltd.