bluuebunny/crossref_metadata_2025_split huggingface dataset:
Citizen science in the social sciences and humanities: the power of interdisciplinarity
Authors: Tauginienė Loreta , Butkevičienė Eglė , Vohland Katrin , Heinisch Barbara , Daskolia Maria , Suškevičs Monika , Portela Manuel , Balázs Bálint , Prūse Baiba 
Published: May 2020

AbstractCitizen science evolved through multiple disciplinary manifestations into a new field of study and a participatory method of enquiry. While most citizen science projects take place within problem-focused natural sciences, social sciences and humanities help understanding the human dimension and open a broad methodological spectrum for enriching scientific research with new approaches and for boosting public participation. In this paper, we use a meta-synthesis approach to explore how citizen science is practised in the so far less addressed social sciences and humanities by focusing on the role of the citizens, the goals and approaches of the projects, the tasks in which citizens are engaged and their gains across projects of diverse disciplinary background. Our findings indicate that social sciences are gaining more acknowledgment within interdisciplinary citizen science projects by addressing ‘wicked’ problems of human behaviour and agency, while humanities are in quest of a better-defined locus in citizen science. We conclude that social sciences and humanities still face considerable barriers to infiltrate citizen science; the payoffs are substantial and already rewarding for several subfields in social sciences and humanities.
Design to prediction tools for banana maturity based on image processing
Authors: Sandra  , Prayogi I Y , Damayanti R , Djoyowasito G 
Published: May 2020

AbstractImage processing is a method to process image become information consisted of phisycal condition of product. Image processing applications in agriculture are currently developing very rapidly, especially for the prediction of fruit quality and maturity. The purpose of this study is to design a tool to predict the maturity of bananas. The type of banana used in this study isbarlinbanana (Musa paradisiaca. L) with maturity levels 1, 3, 5 and 7. While the image processing characteristics use data R, G and B which are captured by the TCS3200 sensor. From a number of experiments, a distinguishing factor is obtained for the RGB value for each level of maturity, maturity 1 with the value of G> B; maturity 3 with Value R> G, Value (R-G) <9 and G Value ⩾ 142; maturity 5 with a value of R> G, a value of 9 ⩽ (R-G) and a value of G ⩾ 142; maturity 7 with a value of R> G and a value of 142 ⩾ G. The results of the prediction of the banana maturity using this tool for maturity 1 accuracy prediction 100%, maturity 3 accuracy predictions 80%, maturity 5n accuracy prediction 100% and maturity 7 accuracy predictions 60%.
Effect of brewing time and duration of listening to Mozart’s symphony on emotions and sensory perception of Wonosari green tea
Authors: Fibrianto K , Izza A , Caharanis P D G , Hasyati N , Wulandari E S 
Published: May 2020

Abstract
Mind and body relaxation can be stimulated by consuming tea and enjoying music. While green tea contains L-theanin which stimulate relaxation, music in general may change moods and emotions. This current study aims to determine the effect of listening to Mozart’s symphony number 6.K.43 at fundamental tone F music on emotion and sensory perception when consuming green tea. Three brewing durations (1, 3 and 5 minutes), 3 levels of listening time to the music (1, 3, and 5 minutes) with 4 different treatment techniques. There were 14 trained panellists involved in the study and they were asked to assess 15 sensory attributes including taste, flavour and mouth-feel of Wonosari green tea on Spectrum method. In general it can be concluded that the music mostly enhance the intensity of sensory attributes (p-value<0.05). It is also important to note that positive emotions improved when respondents listening to Mozart’s regardless the duration of listening.
Beetroot (Beta vulgaris L. var. rubra L.) flour proportion and oven temperature affect the physicochemical characteristics of beetroot cookies
Authors: Aulia F , Sunarharum W B 
Published: May 2020

Abstract
Red beetroot (Beta vulgaris L. var. rubra L.) is one of the agricultural commodities that is very beneficial for human health, one of the benefits is to facilitate the transport of nutrients throughout the body and maintain the number of red blood cells. However, the utilization of red beetroot commodities is still limited, especially in Indonesia. For this reason, innovation is required in the manufacture of red beetroot derivative products. This study aims to know the effect of beetroot flour proportion and oven temperature on the physicochemical characteristics of beetroot cookies. This study was conducted by using Factorial Randomized Block Design consisting of two treatment factors, i.e. proportion of beet flour (10%, 15%, and 20%) and oven temperature (160°C, 170°C, and 180°C) in three replicates. Statistical analysis was performed using Minitab 17. Best treatment was selected by Multiple Attribute method. The results showed that the factor of increasing the proportion of beetroot powder and oven temperature had a significant effect on lightness, redness, yellowness, hardness, fracturability, moisture content, and crude fiber of the cookies. The interaction between the two factors of beetroot powder proportion and oven temperature was significantly (α=0.05) affecting the brightness, redness, and yellowness, and crude fiber, but did not significantly affect hardness, fracturability, and moisture content. Best treatment was the cookies made of 15% proportion of beetroot and 180°C of oven temperature that contains potassium of 476.16 mg / kg, magnesium of 2045.76 mg / kg, and phosphorus (P) of 2801.6 mg / kg.
Investigation of several surfactant use strategies to improve the hydrolysis of glucan in newspaper
Authors: Vaurs L-P , Heaven S , Banks Charles 
Published: May 2020

Abstract
Newspaper represent a large quantity of a relatively cheap and available source of lignocellulose. Newspaper could enzymatically be hydrolysed into fermentable sugars for further bioethanol or biochemical production. Low glucan conversions (20-50%) have been generally found in literature, thus this led to the investigations of multiple pre-treatments to improve sugars release. Surfactants such as sodium dodecyl sulphate (SDS), Tween 80 and polyethylene glycol represent a relatively low-cost pre-treatment to improve newspaper hydrolysability. Several surfactants use strategies were tested using the 3 products mentioned earlier. A simple mass, cost and energy model was developed to determine the optimum surfactant pre-treatment. SDS wash using 0.5% SDS based on total solids (TS) gave the most promising results: it released 82 kg of the cheapest produced sugars (0.7£ kg-1 sugar).
Biosurfactants production using glucose and molasses as carbon sources by Azotobacter vinelandii and soil washing application in hydrocarbon-contaminated soil
Authors: Devianto L A , Latunussa C E L , Helmy Q , Kardena E 
Published: May 2020

Abstract
The purpose of this research was to understand the influence of carbon source variation in the biosurfactant production by Azotobacter vinelandii as well as its potential application on remediation of hydrocarbon-contaminated soil by soil washing. The growth microorganism, biosurfactant quantity in exopolysaccharide and fatty acid fraction were examined. The quality of biosurfactant was analysed by emulsification index. The results show that biggest production was occurred at the 48th hour with μmax1 = 0.416/hour, μmax2 = 0.093/hour and Ks1 = 6.55 g/L, Ks2 = 4.69 g/L for glucose and molasses substrate respectively. Biosurfactant product of Azotobacter vinelandii in glucose 1.5%, 2%, 2.5%, and 3% showed emulsification index as much as 100%. While, emulsification index of the biosurfactant produced with molasses reached 100% within 1%, 1.5%, and 2% molasse concentration. These results showed that molasses has potential utilization as carbon source in biosurfactant production. In soil washing application, Biosurfactant and Tween 80 were used as emulsifier to removed Total Petroleum Hydrocarbons (TPH) by contacting in conical flask at rotary shaker. The results showed that highest removal achieved by using biosurfactant up to 48.89% which occurred at 100 rpm for 40 minutes.
A study of the effect of calcium chloride (CaCl2) and pH on the flocculation ability of Saccharomyces cerevisiae (NCYC 1195)
Authors: Pienasthika M , Brahmanti A A , Purwatiningrum I , Wardani A K 
Published: May 2020

Abstract
The best fermentation ability of yeast-forming flock species is highly desirable in the bioethanol production process. Saccharomyces cerevisiae NCYC 1195 is known to have the ability to form flock which is influenced by the concentration of calcium chloride (CaCl2) and pH. This is because calcium ions can form bonds with mannose on the surface of the cell wall of S. cerevisiae, while the degree of acidity will affect the charges of specific protein on the cell wall. The ability of flocculation will precipitate S. cerevisiae cells so that they will not be mixed with fermentation medium. Thus, the separation process of cell and fermentation media can be done quickly and efficiently, without expensive centrifugation step. The aim of this study was to determine the effect of CaCl2 concentration and pH that used to determine the ability and stability of the flock of S. cerevisiae. Three concentration of CaCl2 (10-5, 10-7, 10-9 M) were used as well as three variations of pH (4,5,6). Culture was incubated at 30°C with 100 rpm agitation and analysed for flocculation ability every 4 hours during 24 hours. The stability of the flock was analysed every 24 hours during 30 days. The highest flock formation ability (73.15%) was obtained with the concentration of CaCl2 concentration 10-9 M and pH 5.
Experimental study of the effect of phase mismatch on a CW-pumped cascaded quadratic nonlinear frequency comb
Authors: Ulvila Ville , Vainio Markku 
Published: May 2020

Abstract
Optical frequency comb generation by continuous-wave-pumped cascaded quadratic nonlinearities (CQN) appears a promising alternative to well-established modelocked lasers, especially if access to the mid-infrared spectral region is needed. We report an experimental investigation of spectral properties of a CQN frequency comb, which is based on second-harmonic generation (SHG) and is pumped internally by a continuous-wave optical parametric oscillator. Our study focuses on SHG phase mismatch, which has drawn little attention in the previously reported CQN frequency comb research. The main observation of our study is that it is possible to improve spectral purity of the CQN frequency comb by adjusting the phase mismatch. In addition to the CQN process that generates a frequency comb in the near-infrared region, our experimental setup involves several other nonlinear processes. These processes lead to a composite comb, which extends from visible to mid-infrared.
An Avatar-Led Intervention Promotes Smoking Cessation in Young Adults: A Pilot Randomized Clinical Trial
Authors: Karekla Maria , Savvides Stella Nicoleta , Gloster Andrew 
Published: May 2020

AbstractBackgroundSmoking remains a global concern, especially for young adults. There is a dearth of smoking cessation programs for this population, who seldom seek help or are motivated to quit.PurposeThis pilot study assessed the effectiveness of a digital avatar-led Acceptance and Commitment Therapy (ACT) smoking cessation program (Flexiquit) for young adult smokers at all levels of motivation to quit.MethodsSmokers with no particular interest in quitting smoking (65.45% reported being in pre-contemplation or contemplation stages of change) were recruited from three universities (105 smoking ≥ 1 cigarette per day during the past 30 days, 68 females). Those who completed questionnaires online (N = 84; M = 22.44 years, SD = 2.61, range 18–28 years old) were randomized to either a six-session avatar-led intervention (Flexiquit; N = 49) or a wait-list control (N = 35). Primary outcomes included cessation status (7-day point prevalence) and number of cigarettes smoked per day; secondary outcomes were nicotine dependence, intention-to-quit smoking and self-efficacy, assessed at pre- and post-intervention, and only for Flexiquit at 6-month follow-up.ResultsIn intention-to-treat analysis more participants (OR = 3.10, 95% CI = 0.92–10.41) in the treatment group (28.57%) versus the control group (11.43%) reported quitting smoking; however, the difference was not statistically significant (p = .067). There were statistically significant decreases in average number of cigarettes, nicotine dependence and increases in self-efficacy, and intention-to-quit smoking compared to controls. Treatment gains in the Flexiquit group were maintained through the 6-month follow-up.ConclusionsAn avatar-led digitized smoking cessation intervention based on ACT could increase the odds of quitting smoking. Findings suggest that a digitized program designed to engage young adults in smoking cessation may result in quitting smoking and has a high applicability potential especially among the hard-to-reach population of young adults.QuestionCan an avatar-led digitized Acceptance and Commitment Therapy (ACT) smoking cessation intervention result in quitting smoking and increasing intention to quit among young smokers at various levels of motivation to quit, compared to a wait-list control group?FindingsIn this pilot randomized clinical trial that included 84 smokers, 28.57% in the treatment condition versus 11.43% in the wait-list control group were abstinent at post (intention-to-treat [ITT] analysis). An avatar-led digitized ACT smoking cessation intervention results in high quitting smoking rates and has a high applicability potential especially among the hard-to-reach population of young adult smokers.
Orchid conservation: from theory to practice
Authors: Phillips Ryan D , Reiter Noushka , Peakall Rod 
Published: May 2020

AbstractBackgroundGiven the exceptional diversity of orchids (26 000+ species), improving strategies for the conservation of orchids will benefit a vast number of taxa. Furthermore, with rapidly increasing numbers of endangered orchids and low success rates in orchid conservation translocation programmes worldwide, it is evident that our progress in understanding the biology of orchids is not yet translating into widespread effective conservation.ScopeWe highlight unusual aspects of the reproductive biology of orchids that can have important consequences for conservation programmes, such as specialization of pollination systems, low fruit set but high seed production, and the potential for long-distance seed dispersal. Further, we discuss the importance of their reliance on mycorrhizal fungi for germination, including quantifying the incidence of specialized versus generalized mycorrhizal associations in orchids. In light of leading conservation theory and the biology of orchids, we provide recommendations for improving population management and translocation programmes.ConclusionsMajor gains in orchid conservation can be achieved by incorporating knowledge of ecological interactions, for both generalist and specialist species. For example, habitat management can be tailored to maintain pollinator populations and conservation translocation sites selected based on confirmed availability of pollinators. Similarly, use of efficacious mycorrhizal fungi in propagation will increase the value of ex situ collections and likely increase the success of conservation translocations. Given the low genetic differentiation between populations of many orchids, experimental genetic mixing is an option to increase fitness of small populations, although caution is needed where cytotypes or floral ecotypes are present. Combining demographic data and field experiments will provide knowledge to enhance management and translocation success. Finally, high per-fruit fecundity means that orchids offer powerful but overlooked opportunities to propagate plants for experiments aimed at improving conservation outcomes. Given the predictions of ongoing environmental change, experimental approaches also offer effective ways to build more resilient populations.
QDeep: distance-based protein model quality estimation by residue-level ensemble error classifications using stacked deep residual neural networks
Authors: Shuvo Md Hossain , Bhattacharya Sutanu , Bhattacharya Debswapna 
Published: May 2020

Abstract

Motivation
Protein model quality estimation, in many ways, informs protein structure prediction. Despite their tight coupling, existing model quality estimation methods do not leverage inter-residue distance information or the latest technological breakthrough in deep learning that has recently revolutionized protein structure prediction.

Results
We present a new distance-based single-model quality estimation method called QDeep by harnessing the power of stacked deep residual neural networks (ResNets). Our method first employs stacked deep ResNets to perform residue-level ensemble error classifications at multiple predefined error thresholds, and then combines the predictions from the individual error classifiers for estimating the quality of a protein structural model. Experimental results show that our method consistently outperforms existing state-of-the-art methods including ProQ2, ProQ3, ProQ3D, ProQ4, 3DCNN, MESHI, and VoroMQA in multiple independent test datasets across a wide-range of accuracy measures; and that predicted distance information significantly contributes to the improved performance of QDeep.

Availability and implementation
https://github.com/Bhattacharya-Lab/QDeep.

Supplementary information
Supplementary data are available at Bioinformatics online.
Phylogenetic double placement of mixed samples
Authors: Balaban Metin , Mirarab Siavash 
Published: May 2020

Abstract

Motivation
Consider a simple computational problem. The inputs are (i) the set of mixed reads generated from a sample that combines two organisms and (ii) separate sets of reads for several reference genomes of known origins. The goal is to find the two organisms that constitute the mixed sample. When constituents are absent from the reference set, we seek to phylogenetically position them with respect to the underlying tree of the reference species. This simple yet fundamental problem (which we call phylogenetic double-placement) has enjoyed surprisingly little attention in the literature. As genome skimming (low-pass sequencing of genomes at low coverage, precluding assembly) becomes more prevalent, this problem finds wide-ranging applications in areas as varied as biodiversity research, food production and provenance, and evolutionary reconstruction.

Results
We introduce a model that relates distances between a mixed sample and reference species to the distances between constituents and reference species. Our model is based on Jaccard indices computed between each sample represented as k-mer sets. The model, built on several assumptions and approximations, allows us to formalize the phylogenetic double-placement problem as a non-convex optimization problem that decomposes mixture distances and performs phylogenetic placement simultaneously. Using a variety of techniques, we are able to solve this optimization problem numerically. We test the resulting method, called MIxed Sample Analysis tool (MISA), on a varied set of simulated and biological datasets. Despite all the assumptions used, the method performs remarkably well in practice.

Availability and implementation
The software and data are available at https://github.com/balabanmetin/misa and https://github.com/balabanmetin/misa-data.

Supplementary information
Supplementary data are available at Bioinformatics online.
Fully interpretable deep learning model of transcriptional control
Authors: Liu Yi , Barr Kenneth , Reinitz John 
Published: May 2020

Abstract

Motivation
The universal expressibility assumption of Deep Neural Networks (DNNs) is the key motivation behind recent worksin the systems biology community to employDNNs to solve important problems in functional genomics and moleculargenetics. Typically, such investigations have taken a ‘black box’ approach in which the internal structure of themodel used is set purely by machine learning considerations with little consideration of representing the internalstructure of the biological system by the mathematical structure of the DNN. DNNs have not yet been applied to thedetailed modeling of transcriptional control in which mRNA production is controlled by the binding of specific transcriptionfactors to DNA, in part because such models are in part formulated in terms of specific chemical equationsthat appear different in form from those used in neural networks.

Results
In this paper, we give an example of a DNN whichcan model the detailed control of transcription in a precise and predictive manner. Its internal structure is fully interpretableand is faithful to underlying chemistry of transcription factor binding to DNA. We derive our DNN from asystems biology model that was not previously recognized as having a DNN structure. Although we apply our DNNto data from the early embryo of the fruit fly Drosophila, this system serves as a test bed for analysis of much larger datasets obtained by systems biology studies on a genomic scale. .

Availability and implementation
The implementation and data for the models used in this paper are in a zip file in the supplementary material.

Supplementary information
Supplementary data are available at Bioinformatics online.
Rapid Analysis of Four Amphetamines in Urine by Self-Made Pipette-Tip Solid-Phase Extraction Followed by GC-MS/MS
Authors: Shi Jia-Wei , Zhou Jing-Feng , He Xiong , Zhang Yun 
Published: May 2020

Abstract
A simple and rapid pipette-tip solid-phase extraction (PT-SPE) procedure with derivatization prior to gas chromatography triple quadrupole mass spectrometry analysis is developed for the simultaneous determination of amphetamine (AMP), methamphetamine (MA), 3,4-methylenedioxyamphetamine (MDA) and 3,4-methylenedioxymethamphetamine (MDMA) in urine samples. The PT-SPE procedure using self-made sorbent could extract drugs within 6 min from 100-μL urine samples, requiring low solvent-consumption (&lt;2.0 mL). Besides, the self-made pipette tip could be reused at least five times. Under optimized conditions, the recoveries of four amphetamines at spiked levels (low, medium and high) ranged from 87.7 to 110.4%, with relative standard deviations &lt; 9.5%. The limit of detections and limit of quantifications for AMP, MA, MDA and MDMA were in the range of 2.52–8.25 ng⋅mL−1 and 8.4–27.5 ng⋅mL−1, respectively. Validation results show that the proposed method is suitable for the quantitation of amphetamines and has been successfully applied in the urine samples of suspected drug abusers.