bluuebunny/crossref_metadata_2025_split huggingface dataset:
The freedom we mean: A causal independence account of creativity and academic freedom
Authors: Kronfeldner Maria 
Published: June 2021

AbstractAcademic freedom has often been defended in a progressivist manner: without academic freedom, creativity would be in peril, and with it the advancement of knowledge, i.e. the epistemic progress in science. In this paper, I want to critically discuss the limits of such a progressivist defense of academic freedom, also known under the label ‘argument from truth.’ The critique is offered, however, with a constructive goal in mind, namely to offer an alternative account that connects creativity and academic freedom in a way that goes beyond mere reference to epistemic progress and involves reference to the freedom to think independently as the freedom we mean when we point to creativityandwhen we point to academic freedom. The resulting causal independence account is not only epistemologically stronger than a progressivist account, it also allows to counter the curbing of academic freedom in the name of progress. The latter becomes key, for instance, when authoritarian political regimes limit or negate academic freedom with reference to an epistemic progress suitably defined for that regime.
Intergenerational Upward (Im)mobility and Political Support of Public Education Spending
Authors: Di Gioacchino Debora , Sabani Laura , Usai Stefano 
Published: June 2021

AbstractThis paper provides a simple model of hierarchical education to study the political determination of public education spending and its allocation between different tiers of education. The model integrates private education decisions by allowing parents, who are differentiated according to income and human capital, to top up public expenditures with private transfers. We identify four groups of households with conflicting preferences over the the size of the public education budget and its allocation. In equilibrium, public education budget, private expenditures and expenditure allocation among different tiers of education, depend on which group of households is in power and on country-specific features such as income inequality and intergenerational persistence in education. By running a cluster analysis on 32 OECD countries, we seek to establish if distinctive ‘education regimes’, akin to those identified in the theoretical analysis, could be discerned. Our main finding is that a high intergenerational persistence in education might foster the establishment of education regimes in which the size and the allocation of the public budget among different tiers of education prevent a stable and significant increase of the population graduation rate, thus plunging the country in a ‘low education’ trap.
MLatom 2: An Integrative Platform for Atomistic Machine Learning
Authors: Dral Pavlo O. , Ge Fuchun , Xue Bao-Xin , Hou Yi-Fan , Pinheiro Max , Huang Jianxing , Barbatti Mario 
Published: June 2021

AbstractAtomistic machine learning (AML) simulations are used in chemistry at an ever-increasing pace. A large number of AML models has been developed, but their implementations are scattered among different packages, each with its own conventions for input and output. Thus, here we give an overview of our MLatom 2 software package, which provides an integrative platform for a wide variety of AML simulations by implementing from scratch and interfacing existing software for a range of state-of-the-art models. These include kernel method-based model types such as KREG (native implementation), sGDML, and GAP-SOAP as well as neural-network-based model types such as ANI, DeepPot-SE, and PhysNet. The theoretical foundations behind these methods are overviewed too. The modular structure of MLatom allows for easy extension to more AML model types. MLatom 2 also has many other capabilities useful for AML simulations, such as the support of custom descriptors, farthest-point and structure-based sampling, hyperparameter optimization, model evaluation, and automatic learning curve generation. It can also be used for such multi-step tasks as Δ-learning, self-correction approaches, and absorption spectrum simulation within the machine-learning nuclear-ensemble approach. Several of these MLatom 2 capabilities are showcased in application examples.
Zur (Fach‑)Spezifität von Unterrichtsqualität im Fach Sport
Authors: Richartz Alfred , Kohake Kathrin 
Published: June 2021

ZusammenfassungIn der empirischen Unterrichtsforschung wird Unterrichtqualität anhand von Merkmalen beurteilt, die sich auf die Wirksamkeit von Unterricht beziehen. Auch der Sportunterricht wird zunehmend unter der Perspektive der Unterrichtsqualität analysiert. Dabei spielen generische Qualitätsdimensionen wie Klassen- und Zeitmanagement und sozio-emotionale Unterstützung der Schüler*innen eine wesentliche Rolle. Fachtypische Lerngelegenheiten des Sportunterrichts weisen Überschneidungsbereiche jedoch auch maßgebliche Unterschiede zu anderen Fächern auf: Schüler*innen sollen einerseits fachspezifisches Wissen und Können erwerben, um ihre Teilnahme an der Sport- und Bewegungskultur zu fördern. Andererseits sollen Schüler*innen aber wie in anderen Fächern Zusammenhänge verstehen und kritische Bewertungen vornehmen, um ihr Sporttreiben selbstbestimmt und verantwortlich zu gestalten. Die Qualität der Lernunterstützung im Sport muss sich daher auf drei Bereiche beziehen: auf motorisches Lernen, auf spieltaktisches Lernen und auf verständnis- und bewertungsbezogenes Lernen. Der Beitrag zeigt, dass generische Qualitätsmerkmale ergänzt werden sollten um Merkmale effektiver Unterstützung in den beiden sportspezifischen Lernfeldern. Hierzu zählen eine für das Bewegungslernen geeignete Aufmerksamkeitslenkung, spezifische Feedbacktechniken, sinnvolle didaktische Reduktion sowie ausreichende Lernzeit für die beim motorischen und taktischen Lernen erforderlichen Prozeduralisierungsprozesse.
From the past to the future: what we learn from China’s 2020 Census
Authors: Zheng Zhenzhen 
Published: June 2021

AbstractThe population of China has entered an era of low fertility and aging, with a slower growth rate in the last decade. This commentary briefly reviews demographic changes in China in the last seven decades with some important years of change in mortality, fertility and urbanization, and discusses future trends according to the information provided by the 2020 Census. China has experienced “compressed” population change, and population aging will continue to advance, meanwhile the size of the population is expected to reach its peak in the near future. To prepare proper response to the challenges proactively, institutional change which adapts to population changes is necessary.
A COMPARISON OF VARIOUS ANALYTIC CHOICE PRINCIPLES
Authors: D’AURIAC PAUL-ELLIOT ANGLÈS , KIHARA TAKAYUKI 
Published: June 2021

AbstractWe investigate computability theoretic and descriptive set theoretic contents of various kinds of analytic choice principles by performing a detailed analysis of the Medvedev lattice of
$\Sigma ^1_1$
-closed sets. Among others, we solve an open problem on the Weihrauch degree of the parallelization of the
$\Sigma ^1_1$
-choice principle on the integers. Harrington’s unpublished result on a jump hierarchy along a pseudo-well-ordering plays a key role in solving this problem.
Are Policy Analogies Persuasive? The Household Budget Analogy and Public Support for Austerity
Authors: Barnes Lucy , Hicks Timothy 
Published: June 2021

AbstractPublic opinion on complex policy questions is shaped by the ways in which elites simplify the issues. Given the prevalence of metaphor and analogy as tools for cognitive problem solving, the deployment of analogies is often proposed as a tool for this kind of influence. For instance, a prominent explanation for the acceptance of austerity is that voters understand government deficits through an analogy to household borrowing. Indeed, there are theoretical reasons to think the household finance analogy represents a most likely case for the causal influence of analogical reasoning on policy preferences. This article examines this best-case scenario using original survey data from the United Kingdom. It reports observational and experimental analyses that find no evidence of causation running from the household analogy to preferences over the government budget. Rather, endorsement of the analogy is invoked ex post to justify support for fiscal consolidation.
Cultivating Self-Control in FinTech: Evidence from a Field Experiment on Online Consumer Borrowing
Authors: Bu Di , Hanspal Tobin , Liao Yin , Liu Yong 
Published: June 2021

AbstractWe report the results of a longitudinal intervention with students across 5 universities in China designed to reduce online consumer debt. We allocate participants to either a financial literacy treatment group, a self-control treatment group, or a zero-touch control group. Our self-control training intervention features detailed tracking of spending and borrowing, budgeting, and introspection about consumption choices. This intervention reduces online borrowing and delinquency charges, mainly driven by a reduction in entertainment-related spending and borrowing. In contrast, financial literacy interventions improve test scores but only marginally affect borrowing. Our results suggest that cultivating self-regulation and budgeting skills can improve borrowing behavior on e-commerce platforms.
Mechanism of leaf rust resistance in wheat wild relatives, Triticum monococcum L. and T. boeoticum L.
Authors: Riar Amandeep K. , Chhuneja Parveen , Keller Beat , Singh Kuldeep 
Published: June 2021

AbstractTriticum monococcum L. and T. boeoticum L., diploid wild relatives of bread wheat (T. aestivum L.), possess resistance to leaf rust (also known as brown rust) caused by Puccinia triticina Eriks. Haustorium formation-based resistance mechanisms (i.e. pre-haustorial and post-haustorial resistance) to leaf rust have been studied and reported in various T. monococcum accessions. In the present study, the mechanism of leaf rust resistance in T. monococcum and T. boeoticum accessions was studied using confocal laser scanning microscopy. Components of resistance studied at a histological level against leaf rust pathotypes, a Mexican pathotype (TCB/TD) and a Swiss pathotype (97512-19), indicated different types of resistance mechanism operative in the two accessions. The resistance in T. monococcum ranged from pre-haustorial resistance against 97512-19 to post-haustorial resistance against TCB/TD. The response in T. boeoticum was post-haustorial with necrosis against the two pathotypes. Pre-haustorial resistance observed in T. monococcum could serve as a potential source of durable rust resistance in wheat breeding.
THE DEVELOPMENT AND EVALUATION OF THE STIGMA OF ILLEGALITY AND MARGINALIZATION OF LATINXS (SIML) SCALE
Authors: Santos Carlos E. , Cadenas Germán A. , Menjívar Cecilia , Cisneros Jesús 
Published: June 2021

AbstractDrawing on two online studies among predominantly U.S.-born and lawful permanent resident Latinxs, we developed a self-report scale intended to capture how discrimination related to perceived legal status, as well as perceptions of racial/ethnic marginalization of Latinxs in U.S. society, are experienced among a wide swath of the Latinx population. We also explore how these processes may be associated with psychological distress in this population. In line with the immigration scholarship that has identified a spillover effect of immigration enforcement and the racialization of legal status beyond the undocumented population, our exploratory factor analysis results from Study I (N= 355 Latinxs) collected in fall of 2013 revealed four factors among our study population:Fear of Deportation, Marginalization of Latinxs in U.S. Society, Marginalization Due to Perceived Illegality,andFear Due to Perceived Illegality.Results from a confirmatory factor analysis from a separate study conducted in spring of 2016 (Study II;N= 295 Latinxs) provided evidence in support of the structure identified in Study I. Results also revealed evidence of the association between theStigma of Illegality and Marginalization of Latinxs(SIML) subscales and psychological distress, measured as anxiety and depression. Implications of these findings are discussed.
Potato injury risk and weed control from reduced rates of PPO-inhibiting herbicides
Authors: Colquhoun Jed B. , Heider Daniel J. , Rittmeyer Richard A. 
Published: June 2021

AbstractThe ability to use the protoporphyrinogen oxidase (PPO)-inhibiting herbicides fomesafen, flumioxazin, and sulfentrazone in potato is limited regionally or by soil texture, largely because of crop injury noted in research in the 1990s. With that in mind, we evaluated whether reducing the herbicide rates could maintain weed control while providing more consistent crop safety. Studies were conducted on a silt loam and a coarse-textured loamy sand soil. Soil texture played a greater than anticipated role in PPO-inhibitor herbicide injury risk as it relates to high-precipitation events. For example, in 2020 at the silt loam location, there were five precipitation events across the season that exceeded 2.5 cm, including one 6 d after treatment (DAT), and a seasonal total precipitation that was over 10 cm greater than the previous year. Despite excessive moisture and initial potato injury as high as 27% where flumioxazin was applied at the high rate with S-metolachlor, by 29 DAT injury was less than 10% in all treatments, and marketable tuber yield was similar among treatments. In contrast, in 2020 at the loamy sand location, there were four precipitation events across the season that exceeded 2.5 cm, and potato injury was as much as 60%. In 2020 the high amount of injury from flumioxazin was hypothesized to be caused by precipitation before herbicide application and not after, suggesting a need for more research in this area. This work documents the fine line between yield reduction presumably caused by reduced weed control and yield reduction assumed to be related to herbicide injury. This delineation between adequate weed control and consistent crop safety may differ by soil texture and environmental conditions, supporting the notion that custom-tailored weed management may become more necessary as high-precipitation events become more common in upper midwestern U.S. agricultural systems.
POST control of Italian ryegrass in hazelnut orchards
Authors: Moretti Marcelo L. 
Published: June 2021

AbstractItalian ryegrass has become a problematic weed in hazelnut orchards of Oregon because of the presence of herbicide-resistant populations. Resistant and multiple-resistant Italian ryegrass populations are now the predominant biotypes in Oregon; there is no information on which herbicides effectively control Italian ryegrass in hazelnut orchards. Six field studies were conducted in commercial orchards to evaluate Italian ryegrass control with POST herbicides. Treatments included flazasulfuron, glufosinate, glyphosate, paraquat, rimsulfuron, and sethoxydim applied alone or in selected mixtures during early spring when plants were in the vegetative stage. Treatment efficacy was dependent on the experimental site. The observed range of weed control 28 d after treatment was 13% to 76% for glyphosate, 1% to 72% for paraquat, 58% to 88% for glufosinate, 16% to 97% for flazasulfuron, 8% to 94% for rimsulfuron, and 25% to 91% for sethoxydim. Herbicides in mixtures improved control of Italian ryegrass compared to single active ingredients based on contrast analysis. Herbicides in mixture increased control by 27% compared to glyphosate, 18% to rimsulfuron, 15% to flazasulfuron, 19% to sethoxydim, and 12% compared to glufosinate when averaged across all sites, but mixture did not always improve reduction of ground coverage or of biomass. This complex site-specific response highlights the importance of record-keeping for efficient herbicide use. Glufosinate is an effective option to manage Italian ryegrass. However, the glufosinate-resistant biotypes documented in Oregon may jeopardize this practice. Nonchemical weed control options are needed for sustainable weed management in hazelnuts.
Potential Mechanisms Responsible for Spatial Variability in Intensity and Thickness of Oxygen Minimum Zone in the Bay of Bengal
Authors: Udaya Bhaskar T. V. S. , Sarma V. V. S. S. , Pavan Kumar J. 
Published: June 2021

AbstractSpatial variability in boundaries and thickness of oxygen minimum zone (OMZ) is derived based on measured dissolved oxygen data obtained from sensors on board biogeochemical (BGC) Argo floats between 2013 and 2019 in the Bay of Bengal (BoB). Upper and lower boundaries of the OMZ varied from 60 to 200 m and 100 to 800 m respectively with the thickness of 80–650 m in the BoB. Relatively thicker OMZ is noticed in the northern than southern BoB associated with stratification. The oxygen concentrations in the OMZ in the NW was low (<1.5 μM) than NE BoB (2.5 μM) indicating that thick and intense OMZ occurs in the NW region associating with stratification and high primary production. Significant decrease in particle‐back‐scatter signal was observed toward offshore from shelf indicating organic matter from the shelf sediments may be supporting bacterial carbon demand in the OMZ. The particle backscatter signal peaked in the OMZ region with a higher signal in the north than southern BoB and it is consistent with the low oxygen concentration in the former indicating that organic matter from shelf sediments may be supporting carbon needs in the OMZ. In addition to this, the occurrence of eddies significantly controls the intensity of the OMZ in the BoB through mixing at the upper boundary of OMZ. Therefore, this study suggests that spatial variations in intensity of OMZ in the BoB are governed by stratification, primary and export productions, organic matter decomposition, and eddy‐driven mixing.
Personalized machine learning of depressed mood using wearables
Authors: Shah Rutvik V. , Grennan Gillian , Zafar-Khan Mariam , Alim Fahad , Dey Sujit , Ramanathan Dhakshin , Mishra Jyoti 
Published: June 2021

AbstractDepression is a multifaceted illness with large interindividual variability in clinical response to treatment. In the era of digital medicine and precision therapeutics, new personalized treatment approaches are warranted for depression. Here, we use a combination of longitudinal ecological momentary assessments of depression, neurocognitive sampling synchronized with electroencephalography, and lifestyle data from wearables to generate individualized predictions of depressed mood over a 1-month time period. This study, thus, develops a systematic pipeline for N-of-1 personalized modeling of depression using multiple modalities of data. In the models, we integrate seven types of supervised machine learning (ML) approaches for each individual, including ensemble learning and regression-based methods. All models were verified using fourfold nested cross-validation. The best-fit as benchmarked by the lowest mean absolute percentage error, was obtained by a different type of ML model for each individual, demonstrating that there is no one-size-fits-all strategy. The voting regressor, which is a composite strategy across ML models, was best performing on-average across subjects. However, the individually selected best-fit models still showed significantly less error than the voting regressor performance across subjects. For each individual’s best-fit personalized model, we further extracted top-feature predictors using Shapley statistics. Shapley values revealed distinct feature determinants of depression over time for each person ranging from co-morbid anxiety, to physical exercise, diet, momentary stress and breathing performance, sleep times, and neurocognition. In future, these personalized features can serve as targets for a personalized ML-guided, multimodal treatment strategy for depression.
Gene expression studies in Depression development and treatment: an overview of the underlying molecular mechanisms and biological processes to identify biomarkers
Authors: Mariani Nicole , Cattane Nadia , Pariante Carmine , Cattaneo Annamaria 
Published: June 2021

AbstractA combination of different risk factors, such as genetic, environmental and psychological factors, together with immune system, stress response, brain neuroplasticity and the regulation of neurotransmitters, is thought to lead to the development of major depressive disorder (MDD). A growing number of studies have tried to investigate the underlying mechanisms of MDD by analysing the expression levels of genes involved in such biological processes. These studies have shown that MDD is not just a brain disorder, but also a body disorder, and this is mainly due to the interplay between the periphery and the Central Nervous System (CNS). To this purpose, most of the studies conducted so far have mainly dedicated to the analysis of the gene expression levels using postmortem brain tissue as well as peripheral blood samples of MDD patients. In this paper, we reviewed the current literature on candidate gene expression alterations and the few existing transcriptomics studies in MDD focusing on inflammation, neuroplasticity, neurotransmitters and stress-related genes. Moreover, we focused our attention on studies, which have investigated mRNA levels as biomarkers to predict therapy outcomes. This is important as many patients do not respond to antidepressant medication or could experience adverse side effects, leading to the interruption of treatment. Unfortunately, the right choice of antidepressant for each individual still remains largely a matter of taking an educated guess.
A carbazole compound, 9-ethyl-9H-carbazole-3-carbaldehyde, plays an antitumor function through reactivation of the p53 pathway in human melanoma cells
Authors: Wen Jie , Chen Wenqian , Zhao Baoxiang , Xu Qiuping , Liu Chang , Zhang Qun , Xie Zhiwei , Yan Yonggan , Guo Jing , Huang Jun , Miao Junying , Wu Xunwei 
Published: June 2021

Abstractp53, the major tumor suppressor, is frequently mutated in many cancers, and up to 84% of human melanomas harbor wild-type p53, which is considered to be an ideal target for melanoma therapy. Here, we evaluated the antitumor activity of a carbazole derivative, 9-ethyl-9H-carbazole-3-carbaldehyde (ECCA), on melanoma cells. ECCA had a selectively strong inhibitory activity against the growth of BRAF-mutated and BRAF-wild-type melanoma cells but had little effect on normal human primary melanocytes. ECCA inhibited melanoma cell growth by increasing cell apoptosis, which was associated with the upregulation of caspase activities and was significantly abrogated by the addition of a caspase inhibitor. In vivo assays confirmed that ECCA suppressed melanoma growth by enhancing cell apoptosis and reducing cell proliferation, and importantly ECCA did not have any evident toxic effects on normal tissues. RNA-Seq analysis identified several pathways related to cell apoptosis that were affected by ECCA, notably, activation of the p53 signaling pathway. Biochemical assays demonstrated that ECCA enhanced the phosphorylation of p53 at Ser15 in melanoma cells harboring wild-type p53, and importantly, the knockdown or deletion of p53 in those cells counteracted the ECCA-induced apoptosis, as well as senescence. Further investigations revealed that ECCA enhanced the phosphorylation of p38-MAPK and c-Jun N-terminal kinase (JNK), and treatment with either a p38-MAPK or a JNK inhibitor rescued the cell growth inhibition elicited by ECCA, which depended on the expression of the p53 gene. Finally, the combination of ECCA with a BRAF inhibitor significantly enhanced the growth inhibition of melanoma cells. In summary, our study demonstrates that the carbazole derivative, ECCA, induces melanoma cell apoptosis and senescence through the activation of p53 to significantly and selectively suppress the growth of melanoma cells without affecting normal human melanocytes, suggesting its potential to develop a new drug for melanoma therapy.