bluuebunny/crossref_metadata_2025_split huggingface dataset:
Technology‐enhanced learning in higher education: How to enhance student engagement through blended learning
Authors: Serrano Dolores R. , Dea‐Ayuela Maria Auxiliadora , Gonzalez‐Burgos Elena , Serrano‐Gil Alfonso , Lalatsa Aikaterini 
Published: April 2019

AbstractBlended learning has risen in popularity in the last two decades as it has been shown to be an effective approach for accommodating an increasingly diverse student population in higher education and enriching the learning environment by incorporating online teaching resources. Blending significant elements of the learning environment such as face‐to‐face, online and self‐paced learning leads to better student experiences and outcomes and more efficient teaching and course management practices if combined appropriately. Hence, an appropriate systematic and dynamic approach of blended learning design is crucial for a positive outcome, starting with planning for integrating blended elements into a course and creating blended activities and implementing them. Evaluating their effectiveness and knowing in which environments they work better and improving the blended activities designed from both the student’s and instructor’s perspective are critical for the next delivery of the course. This article aims to increase awareness of higher education educators about how traditional face‐to‐face learning can be transformed into blended courses so as to develop student engagement with both in‐class and online approaches, whilst being time effective for the instructor.
Hegel's real habits
Authors: Novakovic Andreja 
Published: April 2019

AbstractHegel frequently identifies ethical life with a “second nature.” This strategy has puzzled those who assume that second nature represents a deficient appearance of ethical life, one that needs to be overcome, supplemented, or constantly challenged. I argue that Hegel identifies ethical life with a second nature because he thinks that a social order only becomes a candidate for ethical life, if it provides a context conducive to the development of what I call “real habits.” First, I show that a criterion for a real habit can be found in Hegel's Anthropology, namely, that of liberation. Next, I explain how the state, as Hegel analyzes it in the Philosophy of Right, provides such an environment by enabling trust toward and within it. I then consider two literary examples of contexts that fail to be similarly supportive—Coates' Between the World and Me and Atwood's Handmaid's Tale—concluding with reasons for thinking that real habits are an integral part of ethical life.
Elevated CO2 alters the structure of the bacterial community assimilating plant‐derived carbon in the rhizosphere of soya bean
Authors: Wang Y. H. , Yu Z. H. , Li Y. S. , Wang G. H. , Tang C. , Liu X. B. , Liu J. J. , Xie Z. H. , Jin J. 
Published: April 2019

SummaryElevated CO2 (eCO2) increases rhizodeposits, which in turn alters the soil microbial community. However, it is not really known how the microbial community metabolizes plant‐derived carbon (C) in the rhizosphere under eCO2, especially in agricultural soils. This study used a 13CO2 labelling technique combined with DNA‐stable isotope probing (SIP) to fractionate the 13C‐DNA and 12C‐DNA from the rhizosphere of soya bean plants (Glycine max (L.) Merr. cv. Suinong 14) grown for 54 days under ambient CO2 (aCO2) (390 ppm) or eCO2 (550 ppm). The DNA fractions were then subjected to Illumina Miseq sequencing. The results showed that eCO2 decreased the richness and diversity of the 13C‐assimilating bacterial community compared to aCO2 (p < 0.05). Elevated CO2 decreased the abundances of genera, including Pseudarthrobacter, Gaiellales_uncultured, Microlunatus, Gemmatimonas, Gemmatimonadaceae_uncultured, Ramlibacter, Massilia, Luteimonas, Acidobacteriaceae_uncultured, Bryobacter and Candidatus_Solibacter. These genera were probably fast‐growing bacteria and sensitive to labile C. In contrast, eCO2 stimulated the growth of genera Novosphingobium, Acidimicrobiales_uncultured, Bacillus, Flavisolibacter and Schlesneria, which were able to assimilate complex C compounds. Moreover, the increased population of Novosphingobium under eCO2 might have accelerated electron flow from the oxidation of organic C. Correspondingly, eCO2 did not affect the concentration of the dissolved organic C but increased the plant‐derived 13C in the rhizosphere. These results indicated that an eCO2‐induced increase in non‐labile C in rhizodeposits contributed to the increase in population size of a number of the plant‐C‐metabolizing genera that might become the mechanism for the turnover of fresh C in the rhizosphere, modifying the soil C cycle under eCO2 environments.
Effect of reduction of aggregate size on the priming effect in a Mollisol under different soil managements
Authors: You M. , Han X. , Chen X. , Yan J. , Li N. , Zou W. , Lu X. , Li Y. , Horwath W. R. 
Published: April 2019

SummaryThe priming effect (PE) is influenced by the amount and quality of soil organic carbon (SOC) held in different soil aggregates sizes. We examined the PE in Mollisols managed for >30 years as a grassland, farmland and bare fallow with 51, 32 and 27 g of SOC kg−1 soil, respectively, in a 60‐day incubation. Grassland soil contained 75% of aggregates in the macro size fractions >0.25 mm compared to <32% in farmland and bare fallow. Farmland and bare fallow soils contained proportionately more micro size fractions. The effect of aggregate size on the PE was assessed by comparing soils with intact aggregates to those where macroaggregates were reduced to microaggregate size fractions. In the grassland soil, cumulative CO2 mineralization increased by 20% in the reduced aggregate‐size treatment with no effect on farmland or bare fallow soils. Substrate additions to examine the PE included 13C‐glucose and 13C‐alanine (0.4 g C kg−1 dry soil), and inorganic N (2 mg N kg−1 dry soil). The PE was in the order glucose > alanine > (NH4)2SO4 and was most intense at day 3 of the incubation. Aggregate‐size reduction did not affect the PE within soil management treatments regardless of substrate addition. Most of the CO2 produced was derived from SOC rather than substrate addition and peaked at day 3. There was an interaction between microbial biomass C and dissolved organic C on the PE in the grassland soil only. The results suggested that the PE is an intrinsic characteristic of soils that are more affected by available C than the SOC in different aggregate fractions.Highlights
The priming effect from added C substrates was examined in relation to aggregate size.
Reducing macroaggregates to <0.25 mm increased CO2 production in a grassland but not agricultural Mollisol.
The positive priming effect was proportionately reduced in soil dominated by macroaggregates.
The priming effect is an intrinsic characteristic affected by C additions and less so by aggregate protected C.
Flight initiation distance and escape behavior in the black redstart (Phoenicurus ochruros)
Authors: Kalb Nadine , Anger Fabian , Randler Christoph 
Published: April 2019

AbstractThere are many anti‐predatory escape strategies in animals. A well‐established method to assess escape behavior is the flight initiation distance (FID), which is the distance between prey and predator at which an animal flees. Previous studies in various species throughout the animal kingdom have shown that group size, urbanization, and distance to refuge and body mass affect FID. In most species, FID increases if body mass, group size or distance to refuge decreases. However, how age and sexual dimorphism affect FID is rather unknown. Here, we assess the escape behavior and FID of the black redstart (Phoenicurus ochruros), a small turdid passerine. When approached by a human, males initiated flights later, that is allowing a closer approach than females. Males of this species are more conspicuous, and therefore, may exhibit aposematism to deter potential predators or are less fearful than females. Additionally, juveniles fled at shorter distances and fled to lower heights than adults. Lastly, concerning escape strategy, black redstarts, unless other passerine birds, fled less often into cover, but rather onto open or elevated spots. Black redstarts are especially prone to predation by ambushing predators that might hide in cover. Hence, this species most likely has a higher chance of escaping by fleeing to an open spot rather than to a potentially risky cover.
A model to predict the survivability of cancer comorbidity through ensemble learning approach
Authors: Naghizadeh Majid , Habibi Narges 
Published: April 2019

AbstractCancer is one of the most common death causes worldwide. Breast and genital cancers in women and prostate cancer in men constitute three of the most common cancers. Detection and prevention of these types of cancers are critical objectives. Recent findings indicate that some patients suffer from cancer comorbidity. The probability of survival among patients with comorbid condition is lower than those with only one type of cancer. The importance of concomitant chronic illnesses during cancer treatment through the SEER data is assessed through many machine‐learning approaches. In order to improve the accuracy of prediction of survival rates in patients with cancer and comorbidity of cancers, the gradient boosting ensemble method is adopted for feature selection and modelling. This proposed method increases the accuracy rate and reduces the error rate, and exhibits a significant predictive improvement of survival rates in comorbid cancer compared with the previous proposed models.
Predicting repayment of borrows in peer‐to‐peer social lending with deep dense convolutional network
Authors: Kim Ji‐Yoon , Cho Sung‐Bae 
Published: April 2019

AbstractIn peer‐to‐peer lending, it is important to predict the repayment of the borrower to reduce the lender's financial loss. However, it is difficult to design a powerful feature extractor for predicting the repayment as user and transaction data continue to increase. Convolutional neural networks automatically extract useful features from big data, but they use only high‐level features; hence, it is difficult to capture a variety of representations. In this study, we propose a deep dense convolutional network for repayment prediction in social lending, which maintains the borrower's semantic information and obtains a good representation by automatically extracting important low‐ and high‐level features simultaneously. We predict the repayment of the borrower by learning discriminative features depending on the loan status. Experimental results on the Lending Club dataset show that our model is more effective than other methods. A fivefold cross‐validation is performed to run the experiments.
Investigating the effects of loading, mechanical properties and layers geometry on fatigue life of asphalt pavements
Authors: Ziari Hassan , Aliha Mohammad Reza Mohammad , Mojaradi Barat , Jebalbarezi Sarbijan Majid 
Published: April 2019

AbstractIn this paper, fatigue life, crack growth trajectory, and stress intensity factors of top‐down and bottom‐up cracks have been investigated in a multilayered asphalt pavement using numerical method. Finite element models, Paris law, and maximum tangential stress criteria were used to determine the effects of vehicle position, thickness, and stiffness of layers on fatigue life of pavements. The results show that the minimum fatigue life of pavements with top‐down crack occurs when the wheels are symmetrically located relative to the crack plane. On the other side, in pavements with bottom‐up crack, it occurs when the front tire located on top of the crack. Moreover, the result reveals that the top‐down crack grows slower than bottom‐up crack. Also, the surface layer's stiffness has the most effect on fatigue life of pavement.
Effects of acrylonitrile content and hydrogenation on fatigue behaviour of HNBR
Authors: Narynbek Ulu K. , Huneau B. , Verron E. , Béranger A. S. , Heuillet P. 
Published: April 2019

AbstractThe influence of acrylonitrile (ACN) content and hydrogenation on the fatigue properties of HNBR is investigated. HNBR blends consist of different quantities of acrylonitrile (24, 36, and 44 wt%) and per cent hydrogenation (91%, 96%, and 99%), and a composite of two blends of HNBR with 24 and 44 wt% ACN for an average of 36 wt% . A comprehensive experimental campaign is carried out with fatigue life and crack propagation testing at 120°C. Afterwards, fatigue damage is analysed thanks to both optical and scanning electron microscopy. The results of the three experimental approaches demonstrate that HNBR with median ACN content (36 wt%) and median hydrogenation (96%) has the best fatigue resistance. In general, the fatigue resistance decreases in the following order: for ACN—36 to 44 to 24 wt%, and for hydrogenation—96% to 99% to 91%. The composite blend also has lower fatigue resistance than a regular HNBR blend.
Mouse knockout of guanylyl cyclase C: Recognition memory deficits in the absence of activity changes
Authors: Mann Elizabeth A. , Sugimoto Chiho , Williams Michael T. , Vorhees Charles V. 
Published: April 2019

AbstractGuanylyl cyclase C (GC‐C) is found in brain regions where dopamine is expressed. We characterized a mouse in which GC‐C was knocked out (KO) that was reported to be a model of attention deficit hyperactivity disorder (ADHD). We re‐examined this model and controlled for litter effects, used 16 to 23 mice per genotype per sex and assessed an array of behavioral and neurochemical outcomes. GC‐C KO mice showed no phenotypic differences from wild‐type mice on most behavioral tests, or on striatal or hippocampal monoamines, and notably no evidence of an ADHD‐like phenotype. KO mice were impaired on novel object recognition, had decreased tactile startle but not acoustic startle, and females had increased latency on cued training trials in the Morris water maze, but not hidden platform spatial learning trials. Open‐field activity showed small differences in females but not males. The data indicate that the GC‐C KO mouse with proper controls and sample sizes has a moderate cognitive and startle phenotype but has no ADHD‐like phenotype.
Characteristics of pathogens and mortality predictors of older Chinese patients with nosocomial urinary tract infections
Authors: Hu Wenxue , Xie Shaoling , Yu Feng , Hao Wenke 
Published: April 2019

AimThe aim of the present study was to investigate predominant pathogens and predictors of 28‐day mortality of older Chinese patients with nosocomial urinary tract infections (NUTI).MethodsWe retrospectively studied 1122 older patients (aged ≥60 years) with culture‐positive NUTI in Guangdong General Hospital, Guangzhou, China, from January 2009 to December 2014. The clinical features, microbial distributions and outcomes of these patients were recorded and compared between survival and death patients. Multivariate logistic regression was carried out to identify independent predictors of 28‐day mortality.ResultsThe present results showed the all‐cause mortality was 8.3%, and NUTI mortality was 1.43%. The proportions of Candida albicans (P = 0.004), Acinetobacter baumannii (P = 0.045) and Candida tropicalis (P < 0.001) in the death group were significantly higher than those in the survival group. Multivariate analysis showed two novel risk factors for mortality of older patients with NUTI, which were higher Charlson Comorbidity Index (odds ratio [OR] 1.205, 95% confidence interval (CI) 1.088–1.334] and lower level of serum prealbumin (OR 0.995, 95% CI 0.990–0.999). Furthermore, previous use of antibiotics (OR 1.984, 95% CI 1.106–3.559), inappropriate antimicrobial therapy (OR 1.883, 95% CI 1.144–3.098), intensive care unit stay (OR 4.082, 95% CI 2.469–6.749) and higher concentration of serum C‐reactive protein (OR 1.005, 95% CI 1.001–1.010) were independent prognostic factors for 28‐day mortality in older patients with NUTI.ConclusionsNUTI is associated with a high 28‐day in‐hospital mortality rate in older patients. We should evaluate the comorbidity, nutritional status, inflammatory markers, department staying and drug sensitivity test, and choose systematic therapy strategies for these older patients with NUTI. Geriatr Gerontol Int 2019; 19: 541–546.
Five‐year incidence of common comorbidities, such as hypertension, dyslipidemia, diabetes mellitus, cardiovascular disease, cerebrovascular disease and cancer, in older Japanese patients with rheumatoid arthritis
Authors: Mochizuki Takeshi , Ikari Katsunori , Yano Koichiro , Okazaki Ken 
Published: April 2019

AimTo estimate the 5‐year incidence of common comorbidities, including lifestyle‐associated diseases, in older Japanese patients with rheumatoid arthritis (RA).MethodsWe enrolled 129 consecutive patients with RA aged ≥65 years in this study. We examined all patients for the presence of hypertension, dyslipidemia, diabetes mellitus, cardiovascular disease, cerebrovascular disease and cancer at baseline (in 2013) and 5 years later (in 2018) using clinical records, self‐reported questionnaires, interviews and medication records.ResultsAt baseline, hypertension was prevalent in 37.2% of the patients, dyslipidemia in 18.6%, diabetes mellitus in 9.3%, cardiovascular disease in 14.7%, cerebrovascular disease in 10.1% and cancer in 10.1%. Furthermore, the change of prevalence after 5 years from baseline of hypertension, dyslipidemia, diabetes mellitus, cardiovascular disease, cerebrovascular disease and cancer was 4.6%, 3.9%, 0.8%, 4.7%, 2.3% and 1.5%, respectively. The factors associated at baseline and/or after 5 years of hypertension, dyslipidemia, diabetes mellitus, cardiovascular disease and cancer included disease duration and body mass index, body mass index and anti‐cyclic citrullinated peptide antibody, corticosteroid use, body mass index, and male and disease duration, respectively.ConclusionsThe Japanese population is aging and so is the population of patients with RA. In older patients with RA, hypertension and cardiovascular disease should be particularly considered. Therefore, although the therapeutic agents for RA have improved, a better understanding of the comorbidities in older patients with RA should impact the treatment of RA. Geriatr Gerontol Int 2019; 19: 577–581.
Dermatological diseases in the geriatric age group: Retrospective analysis of 7092 patients
Authors: Yaldiz Mahizer 
Published: April 2019

AimThe aim of the present study was to retrospectively investigate the dermatological diseases seen in geriatric patients, and their distribution according to age, sex and season, making a significant contribution to the few previous prevalence studies.MethodsData from 7092 geriatric patients examined at our dermatology clinic from 1 January to 31 December 2017 were retrospectively analyzed. The data were analyzed according to age, sex and seasons.ResultsThe seven most frequently occurring diseases were eczematous dermatitis, fungal infections, pruritus, precancerous and malignant neoplasm, xerosis cutis, benign neoplasms, and papulosquamous diseases, respectively. In the youngest group, the most frequent disease was eczematous dermatitis, whereas in the older group it was precancerous and malignant neoplasms. The most common disease for both men and women was eczematous dermatitis. Eczematous dermatitis, pruritus, xerosis cutis, rash and general drug eruptions, and papulosquamous diseases were most frequent in the winter, but less in the summer (P < 0.01). Fungal diseases were frequent in the spring and summer (P < 0.01). Pigmentation disorders were frequent in the summer (P < 0.01).ConclusionsThe present study, which is the largest prevalence study in the literature with 7092 geriatric patients, will raise awareness regarding the pattern and nature of dermatological diseases in geriatric patients. Geriatr Gerontol Int 2019; 19: 582–585.
Recent Insights in Migraine With Aura: A Narrative Review of Advanced Neuroimaging
Authors: Russo Antonio , Silvestro Marcello , Tessitore Alessandro , Tedeschi Gioacchino 
Published: April 2019

IntroductionMigraine is a complex neurological disorder characterized by severe headaches associated with a plethora of sensory hypersensitivity and neurovegetative symptoms. In about one‐third of the cases, a set of fully reversible focal neurological symptoms, the aura, accompanies the headache. In the last decades, advanced neuroimaging investigations allowed identification of structural, microstructural, and functional abnormalities characterizing the brain of patients with migraine with aura (MwA). However, mechanisms underlying the aura phenomena are still a matter of debate.AimsThis article reviews the most significant findings from advanced neuroimaging studies in patients with MwA both to provide a unifying physiopathological model of the aura phenomena and to clarify the potential impact of advanced neuroimaging investigation in the clinical field.MethodsA comprehensive review of PubMed citations was conducted by entering the key words “magnetic resonance imaging” combined with “migraine” AND “aura.” Other key words included “grey matter” OR “white matter,” “structural” OR “functional.” The only restriction was to English‐language publications. The abstracts of all articles published between 1997 and 2018 meeting these criteria were reviewed, and the full texts were examined for relevance to the topic.ConclusionAlthough several advanced neuroimaging studies have been conducted to investigate the neural correlates of aura phenomena, they have failed in identifying underlying pathophysiological mechanisms in their entirety. Nevertheless, functional and structural neuroimaging findings concerning the extrastriate visual cortex are characterized by a high level of reproducibility, so much so that they could be applied, in a not so far future, as diagnostic, prognostic, or therapeutic biomarkers for MwA.
Impact factors that modulate gastric cancer risk in Helicobacter pylori‐infected rodent models
Authors: Peng Chao , Li Nian‐Shuang , Hu Yi , Lu Nong‐Hua 
Published: April 2019

AbstractGastric cancer causes a large social and economic burden to humans. Helicobacter pylori (H pylori) infection is a major risk factor for distal gastric cancer. Detailed elucidation of H pylori pathogenesis is significant for the prevention and treatment of gastric cancer. Animal models of H pylori‐induced gastric cancer have provided an invaluable resource to help elucidate the mechanisms of H pylori‐induced carcinogenesis as well as the interaction between host and the bacterium. Rodent models are commonly used to study H pylori infection because H pylori‐induced pathological processes in the stomachs of rodents are similar to those in the stomachs of humans. The risk of gastric cancer in H pylori‐infected animal models is greatly dependent on host factors, bacterial determinants, environmental factors, and microbiota. However, the related mechanisms and the effects of the interactions among these impact factors on gastric carcinogenesis remain unclear. In this review, we summarize the impact factors mediating gastric cancer risk when establishing H pylori‐infected animal models. Clarifying these factors and their potential interactions will provide insights to construct animal models of gastric cancer and investigate the in‐depth mechanisms of H pylori pathogenesis, which might contribute to the management of H pylori‐associated gastric diseases.