bluuebunny/crossref_metadata_2025_split huggingface dataset:
Application of Polyaniline for Li‐Ion Batteries, Lithium–Sulfur Batteries, and Supercapacitors
Authors: Luo Yani , Guo Ruisong , Li Tingting , Li Fuyun , Liu Zhichao , Zheng Mei , Wang Baoyu , Yang Zhiwei , Luo Honglin , Wan Yizao 
Published: October 2018

AbstractConducting polyaniline (PANI) exhibits interesting properties, such as high conductivity, reversible convertibility between redox states, and advantageous structural feature. It therefore receives ever‐increasing attention for various applications. This Minireview evaluates recent studies on application of PANI for Li‐ion batteries (LIBs), Li–S batteries (LSBs) and supercapacitors (SCPs). The flexible PANI is crucial for cyclability, especially for buffering the volumetric changes of electrode materials, in addition to enhancing the electron/ion transport. Furthermore, PANI can be directly used as an electroactive component in electrode materials for LIBs or SCPs and can be widely applied in LSBs due to its physically and chemically strong affinity for S and polysulfides. The evaluation of studies herein reveals significant improvements of electrochemical performance by physical/chemical modification and incorporation of PANI.
Molten‐Salt‐Assisted Synthesis of Hierarchical Porous MnO@Biocarbon Composites as Promising Electrode Materials for Supercapacitors and Lithium‐Ion Batteries
Authors: Zhang Hai , Zhang Ze , Luo Ji‐Di , Qi Xing‐Tao , Yu Ji , Cai Jian‐Xin , Yang Zhen‐Yu 
Published: October 2018

AbstractBiomass‐derived carbon composites (e.g., metal oxide/biocarbon) have been used as promising electrode materials for energy storage devices owing to their natural abundance and simple preparation process. However, low loading content/inhomogeneous distribution of metal oxides and inefficient cracking of biocarbon (BC) are intractable obstacles that impede the efficient utilization of biomass. In this work, hierarchical porous MnO/BC composites were prepared by a facile molten‐salt‐assisted strategy based on the superior salt‐water absorption ability of agaric. The addition of NaCl induces a liquid reaction medium by formation of a molten salt mixture at high temperature to effectively realize the activation and cracking of the bulk carbon, and it also acts as a recyclable sacrificial template to form mesopores and macropores in the as‐prepared hierarchical porous MnO/BC composites. The highly porous and uniform BC framework effectively enhances ion diffusion and electron‐transfer ability, serves as a protective layer to prevent fracturing and agglomeration of MnO, and thus enables superior rate performance and cycling stability of the MnO/BC composite for both supercapacitor electrodes (94 % capacity retention at 20 mA cm−2 after 5000 cycles) and lithium‐ion battery anodes (783 mA h g−1 after 1000 cycles). Notably, considering the simple and low‐cost preparation process, this work opens a promising avenue for the large‐scale production of advanced metal oxide/BC hybrid electrode materials for electrochemical energy storage.
Development of Betaine‐Based Sustainable Catalysts for Green Conversion of Carbohydrates and Biomass into 5‐Hydroxymethylfurfural
Authors: Feng Yunchao , Li Mengzhu , Gao Zhebang , Zhang Xin , Zeng Xianhai , Sun Yong , Tang Xing , Lei Tingzhou , Lin Lu 
Published: October 2018

AbstractRenewable and sustainable betaine‐based catalysts (BX) derived from the betaine sugar industry or ChCl were developed for the production of 5‐hydroxymethylfurfural (HMF) from various carbohydrates. The HMF yields in the BX‐based media reached up to 88 %, 66 %, 37 % and 53 %, for the conversion of fructose, glucose, cellulose, and lignocellulosic biomass, respectively. In addition, choline‐O‐sulfate was synthesized and demonstrated to be an efficient catalyst for the conversion of fructose to HMF. From the perspective of green and sustainable chemistry, this work demonstrates benefits not only in the preparation of sustainable catalysts but also the green production of HMF from biomass.
Soil drivers of local‐scale tree growth in a lowland tropical forest
Authors: Zemunik Graham , Davies Stuart J. , Turner Benjamin L. 
Published: October 2018

AbstractSoil nutrients influence the distribution of tree species in lowland tropical forests, but their effect on productivity, especially at local scales, remains unclear. We used tree census, canopy occupancy, and soil data from the Barro Colorado Island (BCI; Panama) 50‐ha forest dynamics plot to investigate the influence of soil nutrients and potential toxins on aboveground tree productivity. Growth was calculated as the increase in diameter of 150,000 individual stems ≥1 cm diameter at breast height, representing 207 species. The effects of soil variables and other strong predictors of growth (e.g., light) were estimated using hierarchical, linear, mixed‐effects models. Growth was weakly positively associated with phosphorus (P), particularly for understory tree species that are typically considered to be limited by light. In contrast, growth was strongly negatively related to manganese (Mn) and aluminum (Al), although the latter effect was confounded by strong correlations between Al and other soil variables. The negative response to increasing Mn (and Al) suggests a toxicity effect due to solubilization and uptake of amorphous pools of metal oxides in the soil. These results show that P limits tropical tree growth at local scale on BCI, but that toxic metals represent an even greater constraint on productivity.
Studying safe storage time of orange peel (Citrus reticulata) using high‐throughput sequencing and conventional pure culture
Authors: Wang Fu , Chen Lin , Liu Sujuan , Li Fengqing , Zhang Xin , Chen Hongping , Liu Youping 
Published: October 2018

AbstractAspergillus is a fungal genus widely studied all over the world because some species are known allergens and opportunistic human pathogens. The dynamic growth of Aspergillus is a prerequisite for establishing safe storage time of orange peel. In this paper, high‐throughput sequencing technique was used for the first time to analyze the diversity and structure of fungi in the same batch of samples at different periods of time, and 20 batches of fresh orange peel and 56 batches of dried peel were verified. Results shown that the orange peel gradually began to grow Aspergillus fungal after storing for 240 days, and the abundance became maximum at 270 days and then decreased. These results suggest the safe storage time should be from January to August. And orange peel should be dried in August to prevent rapid propagation or metabolic toxicity production of Aspergillus fungi.
Abnormal phasic activity in saliency network, motor areas, and basal ganglia in Parkinson's disease during rhythm perception
Authors: Vikene Kjetil , Skeie Geir‐Olve , Specht Karsten 
Published: October 2018

AbstractBehavioral studies indicate that persons with Parkinson's disease have complexity dependent problems with the discrimination of auditory rhythms. Furthermore, neuroimaging studies show that rhythm processing activates many brain areas that overlap with areas affected by Parkinson's disease (PD). This study sought to investigate the neural correlates of rhythm processing in PD and healthy controls, with a particular focus on rhythmic complexity. We further aimed to investigate differences in brain activation during initial phases of rhythm processing. Functional magnetic resonance imaging was used to scan 15 persons with Parkinson's disease and 15 healthy controls while they listened to musical rhythms with two different levels of complexity. Rhythmic complexity had no significant effect on brain activations, but patients and controls showed differences in areas related to temporal auditory processing, notably bilateral planum temporale and inferior parietal lobule. We found indications of a particular sequential or phasic activation pattern of brain activity, where activity in caudate nucleus in the basal ganglia was time‐displaced by activation in the saliency network—comprised of anterior cingulate cortex and bilateral anterior insula—and cortical and subcortical motor areas, during the initial phases of listening to rhythms. We relate our findings to core PD pathology, and discuss the overall, rhythm processing related hyperactivity in PD as a possible dysfunction in specific basal ganglia mechanisms, and the phasic activation pattern in PD as a reflection of a lack of preparatory activation of task‐relevant brain networks for rhythm processing in PD.
Research on and Development of Inquiry‐Type Chemistry Laboratories in Israel
Authors: Hofstein Avi , Dkeidek Iyad , Katchevitch Dvora , Nahum Tami Levy , Kipnis Mira , Navon Oshrit , Shore Relly , Taitelbaum Dorit , Mamlok‐Naaman Rachel 
Published: October 2018

AbstractOver a period of more than 60 years, the chemistry laboratory has been extensively and comprehensively researched and hundreds of research papers, reviews, and doctoral dissertations have been published, investigating the laboratory as a unique learning environment. However, there were challenges and pedagogical questions regarding its educational effectiveness and benefits for teaching and learning chemistry. At the beginning of the 21st century there was a call to rethink (and research) the goals for learning chemistry in the laboratory. This is especially applicable in an era in which we are trying to enhance the goal of teaching “chemistry for all students” and/or for the benefit of what is fondly called “future citizens”. Working for more than 15 years with colleagues and students, we researched the potential of establishing an inquiry‐type chemistry laboratory for developing high‐order learning skills, namely, skills for the future or skills for life, including metacognitive and argumentative skills, and the ability of students to ask relevant questions resulting from an inquiry‐type chemistry laboratory.
Replication of the Interaction of PRKG1 and Trauma Exposure on Alcohol Misuse in an Independent African American Sample
Authors: Hawn Sage E. , Sheerin Christina M. , Webb Bradley T. , Peterson Roseann E. , Do Elizabeth K. , Dick Danielle , Kendler Kenneth S. , Bacanu Silviu‐Alin , Amstadter Ananda B. 
Published: October 2018

AbstractIn the present study, we sought to replicate recent findings of Polimanti et al. (2017), who conducted a genome‐wide gene‐by‐environment interaction study (GEWIS) and identified a gene‐by‐trauma interaction that predicts alcohol misuse among African Americans. Consistent with the findings published by Polimanti and colleagues, results of the current study demonstrated an interaction effect, b = 0.41, of trauma exposure and rs1729578 in the intron of PRKG1 on alcohol misuse in a subsample of ancestral African Americans. The minor allele (rs1729578*C) was positively associated with increased alcohol use disorder symptoms in trauma‐exposed subjects and negatively associated in non‐trauma‐exposed subjects. This effect, however, was only significant for one out of three alcohol outcome measures we investigated, suggesting the interaction may be most salient when predicting higher severity of alcohol misuse. Additionally, the effect did not remain significant after we accounted for testing the effect on three different outcome variables. Also in line with the original study, the gene‐by‐environment effect was not demonstrated among the ancestral European subsample. The findings suggest this gene variant may increase an individual's susceptibility to environmental influences, both adverse and supportive.
Climate impacts on soil erosion and muddy flooding at 1.5 versus 2°C warming
Authors: Mullan Donal , Matthews Tom , Vandaele Karel , Barr Iestyn D. , Swindles Graeme T. , Meneely John , Boardman John , Murphy Conor 
Published: October 2018

AbstractFollowing the 2015 ‘Paris Agreement’ that seeks to contain global mean temperature increase (GMTI) to well below 2°C and more ambitiously within 1.5°C, recent studies have begun assessing the response of various sectors to these levels of warming. Most studies have so far concentrated on temperature‐sensitive sectors. Given the links between a warmer atmosphere and rainfall intensity, there is also a need to examine impact sectors driven primarily by changing rainfall characteristics. One example is soil erosion and muddy flooding from agricultural land, which damages the natural and built environment. Using a case‐study hillslope in eastern Belgium—an area particularly impacted by muddy floods—this study examines (a) whether soil erosion and muddy flooding will increase in the future; and (b) whether containing GMTI to 1.5°C would help limit the problem versus 2°C. The Water Erosion Prediction Project model was used to simulate muddy flooding for the present‐day and under a range of future scenarios derived from climate models that correspond to 1.5 and 2°C GMTI. The main findings reveal no statistically significant differences between muddy flooding at 1.5 and 2°C GMTI. Limiting GMTI to 1.5°C therefore does not appear to make much difference to soil erosion and muddy flooding, because the timing of changing rainfall intensity does not always follow clear patterns with increased warming. Regardless of the magnitude of future warming, an earlier and longer muddy flooding season is projected—highlighting that mitigation measures should be continually adapted to remain resilient to climate change.
Impact of Comonomer Chemistry on Phase Behavior of Polymerizable Lyotropic Ionic Liquid Crystals: A Pre‐ and Post‐Polymerization Study
Authors: Goujon Nicolas , Dumée Ludovic F. , Byrne Nolene , Bryant Gary , Forsyth Maria 
Published: October 2018

AbstractThe design and characterization of polymerizable lyotropic ionic liquid crystals with an intact alkyl chain bilayer are described. The bilayer is left intact to enable further inclusion of peptide‐based channels to mimic biological protein membranes for potential separation applications. Impact of comonomer concentration and chemistry on the mesophase formed pre‐ and post‐polymerization is characterized. An optimum comonomer concentration of 20 wt% is found for the poly(ethylene glycol) diacrylate (PEGDA) system, before full disruption of the discontinuous cubic phase occurs. Little impact on the discontinuous cubic phase is observed by varying comonomer chemistry from PEGDA to either poly(ethylene glycol) dimethacrylate or 2‐hydroxyethyl acrylate, with exception of variation in the thermal stability of the resulting mesophase. Surprisingly, the use of 2‐hydroxyethyl methacrylate as comonomer results in formation of the 2D hexagonal phase, which is of interest for the design of biological protein membranes. Unfortunately, mesostructure retention is not observed in any systems studied. A sequence of structural changes, modeled as a change from a spherical micelle to a cylindrical micelle, and to finally a lamellar architecture, is rather observed using in situ small‐angle X‐ray scattering polymerization measurements, suggesting a reduction of the headgroup area, likely caused by cross‐linking of the acrylate moiety.
An extended technique for order preference by similarity to ideal solution group decision‐making method with linguistic interval‐valued intuitionistic fuzzy information
Authors: Garg Harish , Kumar Kamal 
Published: October 2018

AbstractLinguistic intuitionistic fuzzy set (LIFS) is an efficient theory to represent the data in form of membership degrees in a qualitative rather than the quantitative aspects. But in sometimes, it is preferable by the decision‐maker to give their preferences in terms of interval numbers rather than real numbers. To address this, the present manuscript extends the theory of LIFS to linguistic interval‐valued intuitionistic fuzzy set (LIVIFS) by expressing the degrees of membership and non‐membership by the interval‐valued linguistic terms. Under this environment, some measures of distances have been proposed to measuring the uncertainties in the data. The characteristics and their desirable relations have also been stated. Further, based on these measures, an extended technique for order preference by similarity to ideal solution method has been presented under the LIVIFS environment by different pairs of decision‐makers and their corresponding priority levels. The study has been validated through a numerical example.
Telemedicine vs Office Visits in a Movement Disorders Clinic: Comparative Satisfaction of Physicians and Patients
Authors: Hanson Ryan E. , Truesdell Marisa , Stebbins Glenn T. , Weathers Allison L. , Goetz Christopher G. 
Published: October 2018

AbstractObjectiveTo compare patient and physician satisfaction between home‐based telemedicine visits and office visits for follow‐up care within a movement disorders program.MethodsPatients were offered telemedicine visits as follow‐up care. After telemedicine visits, a questionnaire of items along a 10‐point Likert Scale (10 = most satisfied) assessed patient and overall physician satisfaction, comparing the experience to past in‐office visits.ResultsPatients and physicians were highly satisfied with the telemedicine experience, both groups having median endorsement scores of 9.25 and 10.0, respectively (response range 6–10), and furthermore, favoring future telemedicine visits when feasible. Although some assessments could not be performed (postural stability, rigidity), physicians likewise favored having future telemedicine visits (median score 10, range 5.0–10).ConclusionsThis direct comparison of patient satisfaction with telemedicine visits to previously experienced office visits strongly supports telemedicine care, with patients highlighting convenience, time, and expense. Despite some limitations with telemedicine, physicians expressed highly rated quality‐of‐service provided.
Habitual exercisers versus sedentary subjects with Parkinson's Disease: Multimodal PET and fMRI study
Authors: Sacheli Matthew A. , Murray Danielle K. , Vafai Nasim , Cherkasova Mariya V. , Dinelle Katie , Shahinfard Elham , Neilson Nicole , McKenzie Jessamyn , Schulzer Michael , Appel‐Cresswell Silke , McKeown Martin J. , Sossi Vesna , Jon Stoessl A. 
Published: October 2018

ABSTRACTBackgroundThe benefits of exercise in PD have been linked to enhanced dopamine (DA) transmission in the striatum.ObjectiveTo examine differences in DA release, reward signaling, and clinical features between habitual exercisers and sedentary subjects with PD.MethodsEight habitual exercisers and 9 sedentary subjects completed [11C]raclopride PET scans before and after stationary cycling to determine exercise‐induced release of endogenous DA in the dorsal striatum. Additionally, functional MRI assessed ventral striatum activation during reward anticipation. All participants completed motor (UPDRS III; finger tapping; and timed‐up‐and‐go) and nonmotor (Beck Depression Inventory; Starkstein Apathy Scale) assessments.Results[11C]Raclopride analysis before and after stationary cycling demonstrated greater DA release in the caudate nuclei of habitual exercisers compared to sedentary subjects (P < 0.05). Habitual exercisers revealed greater activation of ventral striatum during the functional MRI reward task (P < 0.05) and lower apathy (P < 0.05) and bradykinesia (P < 0.05) scores versus sedentary subjects.ConclusionsHabitual exercise is associated with preservation of motor and nonmotor function, possibly mediated by increased DA release. This study formulates a foundation for prospective, randomized controlled studies. © 2018 International Parkinson and Movement Disorder Society
Automatic tumor segmentation in breast ultrasound images using a dilated fully convolutional network combined with an active contour model
Authors: Hu Yuzhou , Guo Yi , Wang Yuanyuan , Yu Jinhua , Li Jiawei , Zhou Shichong , Chang Cai 
Published: October 2018

PurposeDue to the low contrast, blurry boundaries, and large amount of shadows in breast ultrasound (BUS) images, automatic tumor segmentation remains a challenging task. Deep learning provides a solution to this problem, since it can effectively extract representative features from lesions and the background in BUS images.MethodsA novel automatic tumor segmentation method is proposed by combining a dilated fully convolutional network (DFCN) with a phase‐based active contour (PBAC) model. The DFCN is an improved fully convolutional neural network with dilated convolution in deeper layers, fewer parameters, and batch normalization techniques; and has a large receptive field that can separate tumors from background. The predictions made by the DFCN are relatively rough due to blurry boundaries and variations in tumor sizes; thus, the PBAC model, which adds both region‐based and phase‐based energy functions, is applied to further improve segmentation results. The DFCN model is trained and tested in dataset 1 which contains 570 BUS images from 89 patients. In dataset 2, a 10‐fold support vector machine (SVM) classifier is employed to verify the diagnostic ability using 460 features extracted from the segmentation results of the proposed method.ResultsAdvantages of the present method were compared with three state‐of‐the‐art networks; the FCN‐8s, U‐net, and dilated residual network (DRN). Experimental results from 170 BUS images show that the proposed method had a Dice Similarity coefficient of 88.97 ± 10.01%, a Hausdorff distance (HD) of 35.54 ± 29.70 pixels, and a mean absolute deviation (MAD) of 7.67 ± 6.67 pixels, which showed the best segmentation performance. In dataset 2, the area under curve (AUC) of the 10‐fold SVM classifier was 0.795 which is similar to the classification using the manual segmentation results.ConclusionsThe proposed automatic method may be sufficiently accurate, robust, and efficient for medical ultrasound applications.
User identification via neural network based language models
Authors: Phan Tien D. , Zincir‐Heywood Nur 
Published: October 2018

SummaryIdentifying compromised accounts on online social networks that are used for phishing attacks or sending spam messages is still one of the most challenging problems of cyber security. In this research, the authors explore an artificial neural network‐based language model to differentiate the writing styles of different users on short text messages. In doing so, the aim is to be able to identify compromised user accounts. The results obtained indicate that one can learn the language model on one dataset and can generalize it to different datasets to identify users with high accuracy and low false alarm rates without any modification to the language model.