bluuebunny/crossref_metadata_2025_split huggingface dataset:
The teaching concept chem⁝LEVEL – promoting technical language on the basis of the Johnstone triangle
Authors: Haas Jan‐Bernd , Marohn Annette 
Published: June 2022

AbstractChemisches Wissen kann nach Johnstone in drei Ebenen eingeordnet werden: die makroskopische, submikroskopische und repräsentative Ebene. Chemiker:innen können ohne Probleme innerhalb dieser Ebenen kommunizieren, Lernenden fällt dieses jedoch schwer. Eine sprachliche Vermischung der Ebenen kann Verständnisschwierigkeiten und fachlich nicht anschlussfähige Vorstellungen fördern. Das Unterrichtskonzept „chem⁝LEVEL – Fachsprache fördern auf Basis des Johnstone‐Dreiecks“ verfolgt das Ziel, die Ebenen transparent im Unterricht darzustellen und eine ebenenspezifische Fachsprache zu fördern. Dazu wurde eine schülergerechte Visualisierung des Johnstone‐Dreiecks entwickelt und eine digitale Lernumgebung zum Thema galvanische Zellen gestaltet.
Understanding principles of empirical science – a further development of the teaching concept choice2reflect
Authors: Kralisch Christopher , Marohn Annette 
Published: June 2022

AbstractDas fünfphasige Unterrichtskonzept choice2reflect ermöglicht es Schülerinnen und Schülern, auf der Basis von Wissenschaftskriterien rationale, sachlich begründete Entscheidungen in gesellschaftlich kontrovers diskutierten Themen (z. B. Nahrungsergänzungsmittel oder Homöopathie) zu treffen. Der Beitrag beschreibt den iterativen, in drei Mesozyklen verlaufenden Prozess der Weiterentwicklung von choice2reflect im Rahmen des Design‐based‐Research‐Ansatzes. Innerhalb des ersten Mesozyklus werden Unterrichtsmaterialien zu Wissenschaftskriterien entwickelt und erprobt. Das Ziel des zweiten Mesozyklus besteht in der Erweiterung der Unterrichtskonzeption auf die Kontroverse Nahrungsergänzungsmittel. Im dritten Mesozyklus wird ein Prüfschema zur Bewertung von Kontroversen entwickelt und erprobt.
Supporting self‐directed learning in chemistry education with digital learning environments
Authors: Buchholz Jana , Jesgarz Melina , Schneeweiß Niklas , Sieve Bernhard 
Published: June 2022

AbstractIm Distanzunterricht mussten die Lernenden in hohem Maß selbstgesteuert und eigenständig lernen [1]. Diese Form des Lernens lässt sich durch digitale Lernumgebungen unterstützen und bietet nicht nur Potenziale im Homeschooling, sondern generell für den digital gestützten Chemieunterricht [2–5]. Doch was muss bei der Erstellung digitaler Lernumgebungen beachtet werden, damit die Lernenden optimal in ihrem Lernprozess unterstützt werden? Anhand von empirischen Ergebnissen leiten wir Gestaltungsempfehlungen für digitale Lernumgebungen ab und zeigen beispielhaft Realisationsmöglichkeiten für den Chemieunterricht auf.
Hydrogen storage in metal hydride – a perspective on energy storage implemented experimentally and digitally for schools
Authors: Rubner Isabel 
Published: June 2022

AbstractDie Energieversorgung ist eine der zentralen Herausforderungen der aktuellen und auch zukünftigen Generationen und ist als ein Ziel der Agenda 2030 in den Sustainable Development Goals formuliert. Nutzt man regenerative Energien zur Elektrolyse von Wasser, so kann der dabei gewonnene (grüne) Wasserstoff einen enormen und sauberen Beitrag zur Energieversorgung leisten. Die Speicherung des Wasserstoffs ist problematisch und die Speicherung in Form von Metallhydriden stellt hierbei eine zukunftsträchtige Perspektive dar. Diese Speichertechnologie gibt es bereits auch für den didaktischen Bereich und wird im sogenannten Hydrostik genutzt. Der Hydrostik ist ideal für den schulpraktischen Bereich geeignet, da er im Format einer klassischen Batterie, flexibel transportierbar und lagerfähig ist. Bei Raumwechsel an Schule bzw. Hochschule oder auch bei Vortragsreisen kann somit die Wasserstoffquelle problemlos mitgeführt werden. Dies stellt eine Brücke von einer innovativen Technologie mit Anwendungsfeldern im schulischen Einsatz dar. In diesem Artikel wird die Funktionsweise der Wasserstoffspeicherung im Hydrostik verdeutlicht und einige klassische Schulexperimente mit dem Hydrostik vorgestellt. Ferner werden thermodynamische Aspekte beleuchtet. Die Visualisierung der Prozesse wird durch verschiedene digitale Komponenten (Animationen, AR etc.) unterstützt.
Testing new concepts in university teacher training for the acquisition of digital competencies according to DiKoLAN – development and investigation of the effectiveness of a teaching‐learning module in the field of simulation and modelling
Authors: Müller Lukas , Thoms Lars‐Jochen , Möhrke Philipp , Henne Anna , Huwer Johannes 
Published: June 2022

AbstractDer Orientierungsrahmen DiKoLAN beschreibt digitale Basiskompetenzen für das Lehramt in den Naturwissenschaften. Eine Lehrveranstaltung des Lehrstuhls für Fachdidaktik der Naturwissenschaften an der Universität Konstanz widmet sich gezielt dem Aufbau der in DiKoLAN genannten Kompetenzen. In diesem Artikel werden die Konzeption, die Umsetzung und die Evaluation eines Lehr‐Lernmoduls im Bereich Simulation und Modellierung beschrieben. Die Evaluation des Moduls hat Wissensfelder mit Entwicklungspotenzial bei den Studierenden offengelegt, die Stärken einer strukturellen Orientierung an DiKoLAN aufgezeigt und Ansätze zur Optimierung zukünftiger Lehrveranstaltungen zur Förderung digitaler Kompetenzen im Bereich Simulation und Modellierung gegeben.
LPLB: An approach for the design of a lightweight convolutional neural network
Authors: Saleem Tausifa Jan , Chishti Mohammad Ahsan 
Published: June 2022

SUMMARYConvolutional neural network (CNN) is one of the widely used deep neural network architecture for data analytics in the Internet of Things (IoT). However, due to its severe resource requirements, deploying CNN on resource‐constrained edge devices is quite challenging. Moreover, IoT services demand fast data analytics in order to be useful in their context. Hence, ensuring the deployment of CNN models on IoT edge devices is crucial. To this purpose, this article proposes a framework LPLB (less parameters and less bits) for the design of a lightweight CNN with reduced number of parameters and lesser storage requirements while preserving the model accuracy. LPLB consists of three steps: CNN training, iterative parameter drop and post‐training quantization. The performance of LPLB is evaluated on three datasets: German traffic sign recognition dataset, Kaggle hand gesture recognition dataset, and CIFAR‐10 dataset. Experiments conducted in the study reveal that the proposed framework is able to reduce the number of parameters by 11× in case of German traffic sign recognition dataset, 12.5× in case of Kaggle hand gesture recognition dataset, and 14× in case of CIFAR‐10 dataset. Moreover, the storage requirements are reduced by 44.42× in case of German traffic sign recognition dataset, 50× in case of Kaggle hand gesture recognition dataset, and 56.7× in case of CIFAR‐10 dataset. This is achieved without a significant drop in the accuracy. The accuracy drop in case of German traffic sign recognition dataset is 0.215%, 0.18% in case of Kaggle hand gesture recognition dataset, and 0.148% in case of CIFAR‐10 dataset. The proposed framework is generic and can be used for the design of lightweight CNN models corresponding to other use‐cases as well. This will make real‐time classification/recognition possible in delay‐sensitive applications like self‐driving cars, advanced driver assistance systems, health monitoring, elderly posture recognition and so forth.
Inflammatory bowel disease and periodontitis: A retrospective chart analysis
Authors: Abrol Nazia , Compton Sharon M. , Graf Daniel , Parashar Pallavi , Heo Giseon , Gibson Monica P. 
Published: June 2022

AbstractObjectivesThis study examined the variation in prevalence of periodontitis among different sexes, age groups, smoking status, and oral hygiene adherence in patients affected by either Crohn's disease (CD) or ulcerative colitis (UC).Materials & MethodsThis study was a retrospective chart analysis that collected data from the School of Dentistry's Oral Health Clinic at the University of Alberta, Edmonton, Canada. Patients' electronic health records between the years of 2013 and 2019 were analyzed. Multiple keywords such as IBD, CD, UC, and periodontal disease with various spelling combinations were used for searching and gathering pertinent data, which was then further assessed. After applying the inclusion and exclusion criteria, a total of 80 patient charts were included. These patient charts were thoroughly screened to gather information such as age, sex, smoking status, and a variety of periodontal parameters. Collected data were analyzed using SPSS software by using Pearson's χ2, Pearson's correlation, and Mann–Whitney U‐test.ResultsIBD had an impact on the severity of periodontitis in patients between the ages of 50 and 64 years with higher odds ratio (OR). Biological sex or history of smoking in IBD patients did not have higher odds of developing periodontitis. Plaque score derived from this retrospective study was used to estimate the patient's oral hygiene status and showed no impact. Also, prevalence of periodontitis did not differ between UC and CD. We anticipated some of these findings because of the retrospective nature of the study.ConclusionsWithin the limitation of the retrospective study, IBD patients in the 50–64 age group years showed a higher odds ratio for a greater prevalence of periodontitis. Thus, a closer periodontal recall and evaluation in these patients is recommended for early diagnosis and preventive care. It is advised that periodontists work closely with gastroenterologists to maintain periodontal health in IBD‐affected individuals.
A general deep learning model for bird detection in high‐resolution airborne imagery
Authors: Weinstein Ben G. , Garner Lindsey , Saccomanno Vienna R. , Steinkraus Ashley , Ortega Andrew , Brush Kristen , Yenni Glenda , McKellar Ann E. , Converse Rowan , Lippitt Christopher D. , Wegmann Alex , Holmes Nick D. , Edney Alice J. , Hart Tom , Jessopp Mark J. , Clarke Rohan H. , Marchowski Dominik , Senyondo Henry , Dotson Ryan , White Ethan P. , Frederick Peter , Ernest S. K. Morgan 
Published: June 2022

AbstractAdvances in artificial intelligence for computer vision hold great promise for increasing the scales at which ecological systems can be studied. The distribution and behavior of individuals is central to ecology, and computer vision using deep neural networks can learn to detect individual objects in imagery. However, developing supervised models for ecological monitoring is challenging because it requires large amounts of human‐labeled training data, requires advanced technical expertise and computational infrastructure, and is prone to overfitting. This limits application across space and time. One solution is developing generalized models that can be applied across species and ecosystems. Using over 250,000 annotations from 13 projects from around the world, we develop a general bird detection model that achieves over 65% recall and 50% precision on novel aerial data without any local training despite differences in species, habitat, and imaging methodology. Fine‐tuning this model with only 1000 local annotations increases these values to an average of 84% recall and 69% precision by building on the general features learned from other data sources. Retraining from the general model improves local predictions even when moderately large annotation sets are available and makes model training faster and more stable. Our results demonstrate that general models for detecting broad classes of organisms using airborne imagery are achievable. These models can reduce the effort, expertise, and computational resources necessary for automating the detection of individual organisms across large scales, helping to transform the scale of data collection in ecology and the questions that can be addressed.
Evolutionary and ecological insights from vital staining of bivalve oocytes: A Red Queen at the sweepstakes?
Authors: Beninger Peter G. , Chérel Daphné , Le Pennec Gaël , Shumway Sandra E. 
Published: June 2022

AbstractTo determine the proportion of inviable oocytes that are spawned along with normal oocytes in marine bivalves, we turned to a time‐honored technique not previously used on invertebrate oocytes: the neutral red vital stain. Despite the difficulty in obtaining induced spawns from field‐collected Cerastoderma edule (L), the results and insights from this simple procedure to answer a simple question were unexpected and far‐reaching. Mean proportions of inviable oocytes in the spawns of cockle C. edule ranged from 35% to 85%, with the vast majority represented by atresic (autolyzing) oocytes. These levels are in agreement with previous quantitative histological observations of prespawning atresia in both C. edule and the Manila clam Tapes philippinarum. Such elevated prefertilization inviability mirrors the known high level of postfertilization inviability in bivalves. Together, these high levels of inviability may account for much of the early mortality in the type III survivorship curves typical of marine bivalves. The combination of high fecundity and high oocyte inviability suggests a Red Queen‐type reproductive dilemma in these species. In addition, the great degree of interindividual variation observed in oocyte inviability suggests that cockles, and perhaps other intertidal bivalves, present a Sweepstakes Reproductive Strategy, in which highly variable individual fecundity confronts a highly variable environment. The neutral red technique promises to be a useful tool for investigating prespawning inviability in other marine taxa, as well as for aquaculture, conservation, restocking, ecophysiology, and environmental monitoring.
Nutrient resorption responses of plant life forms to nitrogen addition in temperate shrublands
Authors: Zhang Jianhua , Tang Zhiyao , Wang Wenting , Zhang Hufang , Liu Yong , Xin Yanhua , Zhao Lijuan , Li He 
Published: June 2022

AbstractAtmospheric nitrogen (N) deposition has significantly altered nutrient availability in most terrestrial ecosystems, which may affect plant nutrient resorption and hence change nutrient cycling and community composition. Although studies on the effects of changed soil nutrients on leaf nutrient resorption have been extensively reported in forests and grasslands, much less known about how plants in temperate shrublands respond to nitrogen deposition across the world. A 4‐year N addition experiment in Vitex negundo and Spiraea trilobata shrublands was conducted to investigate the potential impacts of N deposition on nutrient resorption in two life forms. The green and senesced leaf N ([N]g and [N]s) and phosphorus ([P]g and [P]s) concentrations were measured in four shrubs and two graminoids to calculate N (NRE) and P (PRE) resorption efficiency. We found markedly lower NRE and PRE in shrubs than in graminoids, implying that shrubs probably have a higher capability of acquiring nutrients from soil, whereas graminoids rely on acquiring more nutrients via resorption. N addition increased the [N]g, [N]s, and N:P ratios ([N:P]) and decreased the [P]g of shrubs and all species, whereas it only increased [N]s but had negligible effects on the [N]g, [P]g, and [N:P] of graminoids. The [P]s, NRE, and PRE did not change in either life form or all species combined after N fertilization. Our results suggest that shrubs increase N uptake but do not alter internal N cycling (i.e., nutrient resorption), whereas graminoids do not change N acquisition strategies, in response to increased N supply from the soil. Continuous N addition exacerbated the P limitation of the shrub plants. Both shrubs and graminoids were more likely to adopt nearly complete utilization of P from the soil and senesced leaves under P deficiency, leading to a noneffect of N addition on leaf PRE. Our findings also suggest that the [N]g and [P]g responses to N addition are life‐form specific, implying that N addition may affect ecosystem carbon (C) and nutrient cycles by altering the dominance values of the two life forms and community composition.
Health status and the Great Recession. Evidence from electronic health records
Authors: Belotti Federico , Kopinska Joanna , Palma Alessandro , Piano Mortari Andrea 
Published: June 2022

AbstractWe investigate the impact of the Great Recession in Italy on the incidence of chronic diseases using new individual longitudinal data from Electronic Health Records. We exploit the exogenous shock in the economic conditions occurred in 2008 to estimate heterogeneous effects of an unprecedented rise in local unemployment rates in an individual fixed‐effects model. Our results document that harsh economic downturns have a negative long‐lasting effect on cardiovascular disease and a temporary effect on depression. This effect is heterogeneous across gender, increases with age and is stronger right before the retirement age. An important policy recommendation emerging from this study is that prolonged economic downturns constitute an additional external risk for individual health and not a temporary benefit.
G‐Quartets, 4‐Way Junctions and Triple Helices but Not DNA Duplexes: Planarization of Twisted Push–Pull Flipper Probes by Surface Recognition Rather Than Physical Compression
Authors: Sakai Naomi , Assies Lea , Matile Stefan 
Published: June 2022

AbstractPlanarizable push–pull flipper probes have been introduced to image order and tension of membranes in living cells. In this report, we show that fluorescent flippers can also be planarized by chemical interactions on DNA architectures rather than by physical forces in biomembranes. Compared to fluorescence in water, the planarization on parallel cMyc G‐quartets is characterized by a 100 nm red shift of the excitation maximum and a strong increase in fluorescence intensity. A coinciding 100 nm red shift of the emission maximum compared to planarized flippers in ordered membranes reveals that planarization occurs on the water‐accessible surface rather than within the G‐quartets. Less relevant for physical compression in the ground state in hydrophobic membranes, this functional relevance of flipper solvatochromism in the excited state, reflected by red shifts in emission rather than excitation, is unprecedented and introduces attractive dual sensing perspectives. With decreasing efficiency, flippers are also planarized by antiparallel hTel22 G‐quartets, 4‐way junctions and triple helices, while the aromatic surface of B‐DNA duplexes is too small for strong enough π stacking. These remarkably consistent results expand the understanding of planarizable push–pull flipper probes and enable applications in new directions.
Dense and shuffle attention U‐Net for automatic skin lesion segmentation
Authors: Zhang Guanzhong , Wang Shengsheng 
Published: June 2022

AbstractThe segmentation of skin lesions is a critical step in the detection of skin cancer. However, it is also difficult because of unclear boundaries, various size and shape of skin lesions, the appearance of interference objects and different backgrounds in dermoscopic images. This study presents proposed multiple attention‐based methods based on U‐net architecture. At first, dense attention gates (DAG) are proposed to obtain the focus area of the feature map by capturing information through extern feature maps. Then, to extend the capability of capturing feature relationships of the DAG module. We introduced The shuffle attention module which can fuse two self‐attention modules in a lightweight yet effective way. According to the experiments conducted on International Skin Imaging Collaboration (ISIC) 2017 and PH2 datasets, the proposed model can generate satisfactory segmentation results and great capability in practical computer‐aided diagnosis systems.
Medication adherence and health beliefs among South Asian immigrants with diabetes in the United States: A qualitative study
Authors: Jamil Amna , Jonkman Lauren J. , Miller Michelle , Jennings Luke , Connor Sharon E. 
Published: June 2022

AbstractIntroductionPeople of South Asian descent carry a high burden of cardiovascular disease (CVD) and type 2 diabetes mellitus (DM2) both globally and in the United States. Although retrospective cohort studies indicate decreased medication adherence among South Asian immigrants, data exploring contributing factors are limited.ObjectivesTo explore how cultural perspectives of South Asian immigrants in the U.S. impact adherence to medications for DM2 and CVD.MethodsThis qualitative research study recruited South Asian immigrants in the U.S. with CVD and/or DM2. Semi‐structured interviews were conducted utilizing the conceptual frameworks of the Patient Explanatory Model and HOPE questions. A modified version of the Voils DOSE‐Nonadherence measure was administered to all participants. Interviews were transcribed, coded, and analyzed through an iterative process to develop overarching themes.ResultsTwelve individuals participated: half were female, with an average age of 63 (range 49‐75), and the majority emigrated from Pakistan. The average extent of nonadherence score on the modified version of the Voils DOSE‐Nonadherence measure was 1.36 (range 1‐2.33). Five overarching themes were identified: (1) Numerical results motivated health change; (2) Open communication improved medication adherence; (3) Self‐management and autonomy valued; (4) Religious/spiritual beliefs may strengthen medication adherence; and (5) Complementary and alternative medicines (CAM) augment Western medicines.ConclusionProviders may engage in various culturally‐based strategies to optimize medication adherence in South Asian immigrants. Resources should be allocated toward facilitating disease state education, encouraging self‐monitoring, and providing training for providers on CAM. Providers should engage the patient‐family dyad and cultivate collaborative relationships with patients. Providers should be aware that patients desire autonomy in making health care decisions, and those with higher health literacy and health care providers in their social network may be more likely to self‐titrate medications.
Performance evaluation of a laboratory‐developed light‐initiated chemiluminescence assay for quantification of egg white‐specific IgE
Authors: Tan Xin , Zhang Bei , Zheng Lisheng , Shi Hongbin , Liu Dandan , Sun Yuanmin , Li Xue , Li Huiqiang 
Published: June 2022

AbstractBackgroundSpecific IgE (sIgE) testing has become one of the most important tools for diagnosing IgE‐mediated food allergy. Enzyme‐linked immunosorbent assay (ELISA) and dot‐enzyme‐linked immunosorbent assay (Dot‐ELISA) have been used to measure sIgE in clinical widely. Light‐initiated chemiluminescence assay (LICA) is a new method for measuring allergen‐sIgE. We aimed to establish a LICA method for quantitative detection of egg white‐sIgE and evaluate its performances.MethodsThe best chemibeads coupling method in detecting egg white‐sIgE was selected, and a LICA method for quantitative detection of egg white‐sIgE was established. The precision study was performed according to Clinical and Laboratory Standards Institute (CLSI) EP5‐A2. Detection capability which contains limit of blank (LoB), limit of detection (LoD), and limit of quantitation (LoQ) was evaluated according to National Health Commission of the People's Republic of China (NHC) WS/T 514–2017. Linear range was evaluated according to CLSI EP6‐A. All data were analyzed using SPSS software.ResultsPrecision contains repeatability and intermediate precision. The CV of repeatability ranged from 2.72% to 7.29%, and the CV of intermediate precision ranged from 4.93% to 8.64%. The LoB, LoD, and LoQ of the assay were 0.000 kUA/L, 0.053 kUA/L, and 0.076 kUA/L. The assay linear range was 0.076–34.125 kUA/L (r = 0.9979 ≥ 0.9900).ConclusionThis laboratory‐developed LICA method can detect egg white‐sIgE, and performance meets clinical requirements. This method shows rapid turnaround cycles and high sensitivity. It can be used as an alternative method for clinical detection of egg white‐sIgE.