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Starch has been a convenient, economically important polymer with substantial applications in the food and processing industry. However, native starches present restricted applications, which hinder their industrial usage. Therefore, modification of starch is carried out to augment the positive characteristics and eliminate the limitations of the native starches. Modifications of starch can result in generating novel polymers with numerous functional and value-added properties that suit the needs of the industry. Here, we summarize the possible starch modifications in planta and outside the plant system (physical, chemical, and enzymatic) and their corresponding applications. In addition, this review will highlight the implications of each starch property adjustment.
The objective of the present paper is to explore the potentials and challenges inherent in con- ceptualizations of global citizenship education (GCE) in the context of foreign language edu- cation. Specifically, we argue for a critical approach to GCE that emphasizes the significance of language as symbolic power by drawing on the concepts of critical literacy (e.g., Freire 1983; Janks 2014) and symbolic competence (Kramsch 2006; 2011; 2021). To illustrate the necessity of such a critical approach to GCE, we critically analyze teaching materials designed for the English language classroom as provided by the curriculum framework (KMK/ BMZ 2016). The analysis reveals how reliance on dominant Western liberal and neoliberal epistemologies, norms, and discourses might inadvertently reinforce the very inequalities that GCE actually seeks to address. By foregrounding the relationship between language, symbolic power, and GCE, we further redesign these teaching materials and incorporate pedagogical and methodological principles which are in line with a critical literacy and symbolic competence.
The study explores differences between three user types in the top tweets about the 2015 “refugee crisis” in Germany and presents the results of a quantitative content analysis. All tweets with the keyword “Flüchtlinge” posted for a monthlong period following September 13, 2015, the day Germany decided to implement border controls, were collected (N = 763,752). The top 2,495 tweets according to number of retweets were selected for analysis. Differences between news media, public and private actor tweets in topics, tweet characteristics such as tone and opinion expression, links, and specific sentiments toward refugees were analyzed. We found strong differences between the tweets. Public actor tweets were the main source of positive sentiment toward refugees and the main information source on refugee support. News media tweets mostly reflected traditional journalistic norms of impartiality and objectivity, whereas private actor tweets were more diverse in sentiments toward refugees.
Creativity is a crucial part of policy capacity in governments. Existing studies on creative behavior in the public sector assess employees' openness to new ideas and creative solutions, and they confirm the relevance of organizational and individual determinants for pro-creativity attitudes. Yet we lack systemic evidence on the explicit level of work-related creativity among policy officials in government organizations. At the same time, novel technologies and particularly social networking services change the working environment of policy officials radically, alter organizational features, and may also yield crucial individual effects. Our study analyses “policy creativity” of policy officials in three European governments. We demonstrate the importance of organizational and individual features, including the stress triggered by using social networking services. Our study captures officials' creativity explicitly and adds to debates on creativity and innovation in the public sector as well as the micro-level foundations of the digital transformation in the public sector.
This meta-analysis synthesizes 332 effect sizes of various methods to enhance creativity. We clustered all studies into 12 methods to identify the most effective creativity enhancement methods. We found that, on average, creativity can be enhanced, Hedges’ g = 0.53, 95% CI [0.44, 0.61], with 70.09% of the participants in the enhancement conditions being more creative than the average person in the control conditions. Complex training courses, meditation, and cultural exposure were the most effective (gs = 0.66) while the use of cognitive manipulation drugs was the least and also noneffective, g = 0.10. The type of training material was also important. For instance, figural methods were more effective in enhancing creativity, and enhancing converging thinking was more effective than enhancing divergent thinking. Study effect sizes varied considerably across all studies and for many subgroup analyses, suggesting that researchers can plausibly expect to find reversed effects occasionally. We found no evidence of publication bias. We discuss theoretical implications and suggest future directions for best practices in enhancing creativity. (PsycInfo Database Record (c) 2023 APA, all rights reserved)
Design thinking is a well-established practical and educational approach to fostering high-level creativity and innovation, which has been refined since the 1950s with the participation of experts like Joy Paul Guilford and Abraham Maslow. Through real-world projects, trainees learn to optimize their creative outcomes by developing and practicing creative cognition and metacognition. This paper provides a holistic perspective on creativity, enabling the formulation of a comprehensive theoretical framework of creative metacognition. It focuses on the design thinking approach to creativity and explores the role of metacognition in four areas of creativity expertise: Products, Processes, People, and Places. The analysis includes task-outcome relationships (product metacognition), the monitoring of strategy effectiveness (process metacognition), an understanding of individual or group strengths and weaknesses (people metacognition), and an examination of the mutual impact between environments and creativity (place metacognition). It also reviews measures taken in design thinking education, including a distribution of cognition and metacognition, to support students in their development of creative mastery. On these grounds, we propose extended methods for measuring creative metacognition with the goal of enhancing comprehensive assessments of the phenomenon. Proposed methodological advancements include accuracy sub-scales, experimental tasks where examinees explore problem and solution spaces, combinations of naturalistic observations with capability testing, as well as physiological assessments as indirect measures of creative metacognition.
A review of all research papers published in the European Sociological Review in 2016 and 2017 (N = 118) shows that only a minority of papers clearly define the parameter of interest and provide sufficient reasoning for the selected control variables of the statistical analysis. Thus, the vast majority of papers does not reach minimal standards for the selection of control variables. Consequently, a majority of papers interpret biased coefficients, or statistics without proper sociological meaning. We postulate that authors and reviewers should be more careful about control variable selection. We propose graphical causal models in the form of directed acyclic graphs as an example for a parsimonious and powerful means to that end.
Background:
Contamination detection is a important step that should be carefully considered in early stages when designing and performing microbiome studies to avoid biased outcomes. Detecting and removing true contaminants is challenging, especially in low-biomass samples or in studies lacking proper controls. Interactive visualizations and analysis platforms are crucial to better guide this step, to help to identify and detect noisy patterns that could potentially be contamination. Additionally, external evidence, like aggregation of several contamination detection methods and the use of common contaminants reported in the literature, could help to discover and mitigate contamination.
Results:
We propose GRIMER, a tool that performs automated analyses and generates a portable and interactive dashboard integrating annotation, taxonomy, and metadata. It unifies several sources of evidence to help detect contamination. GRIMER is independent of quantification methods and directly analyzes contingency tables to create an interactive and offline report. Reports can be created in seconds and are accessible for nonspecialists, providing an intuitive set of charts to explore data distribution among observations and samples and its connections with external sources. Further, we compiled and used an extensive list of possible external contaminant taxa and common contaminants with 210 genera and 627 species reported in 22 published articles.
Conclusion:
GRIMER enables visual data exploration and analysis, supporting contamination detection in microbiome studies. The tool and data presented are open source and available at https://gitlab.com/dacs-hpi/grimer.
In recent experimental work, arguments for or against Condition C reconstruction in A'-movement have been based on low/high availability of coreference in sentences with and without A'-movement. We argue that this reasoning is problematic: It involves arbitrary thresholds, and the results are potentially confounded by the different surface orders of the compared structures and non-syntactic factors. We present three experiments with designs that do not require defining thresholds of 'low' or 'high' coreference values. Instead, we focus on grammatical contrasts (wh-movement vs. relativization, subject vs. object wh-movement) and aim to identify and reduce confounds. The results show that reconstruction for A'-movement of DPs is not very robust in German, contra previous findings. Our results are compatible with the view that the surface order and non-syntactic factors (e.g. plausibility, referential accessibility of an R-expression) heavily influence coreference possibilities. Thus, the data argue against a theory that includes both reconstruction and a hard Condition C constraint. There is a residual contrast between sentences with subject/object movement, which is compatible with an account without reconstruction (and an additional non-syntactic factor) or an account with reconstruction (and a soft Condition C constraint).
Competence development must change at all didactic levels to meet the new requirements triggered by digitization. Unlike classic learning theories and the resulting popular approaches (e.g., sender-receiver model), future-oriented vocational training must include new learning theory impulses in the discussion about competence acquisition. On the one hand, these impulses are often very well elaborated on the theoretical side, but the transfer into innovative learning environments - such as learning factories - is often still missing. On the other hand, actual learning factory (design) approaches often concentrate primarily on the technical side. Subject-oriented learning theory enables the design of competence development-oriented vocational training projectsin learning factories in which persons can obtain relevant competencies for digitization. At the same time, such learning theory approaches assume a potentially infinite number of learning interests and reasons. Following this, competence development is always located in an institutional or organizational context. The paper conceptionally answers how this theoryimmanent challenge is synthesizable with the reality of organizationally competence development requirements.
Thermal energy from concentrating solar thermal technologies (CST) may contribute to decarbonizing applications from heating and cooling, desalination, and power generation to commodities such as aluminium, hydrogen, ammonia or sustainable aviation fuels (SAF). So far, successful commercial-scale CST projects are restricted to solar industrial process heat (SIPH) and concentrating solar power (CSP) generation and, at least for the latter, depend on support from public policies that have been stagnating for years. As they are technologically similar, spillovers between SIPH or CSP and other emerging CST could accelerate commercialization across use cases while maximizing the impact of scarce support. Here, we review the technical potential for cross-fertilization between different CST applications and the ability of the current policy regime to enable this potential. Using working temperature as the key variable, we identify different clusters of current and emerging CST technologies. Low-temperature CST (<400℃) applications for heating, cooling and desalination already profit from the significant progress made in line-focussing CSP over the last 15 years. A newly emerging cluster of high temperature CST (>600℃) for solar chemistry and high-grade process heat has significant leverage for spillovers with point-focussing solar tower third-generation CSP currently under development. For these spillovers to happen, however, CSP policy designs would need to prioritize innovation for high working temperature and encourage modular plant design, by adequately remunerating hybridized plants with heat and power in and outputs that include energy sources beyond CST solar fields. This would enable synergies across applications and scales by incentivizing compatibility of modular CST components in multiple sectors and use cases.
Its properties make copper one of the world’s most important functional metals. Numerous megatrends are increasing the demand for copper. This requires the prospection and exploration of new deposits, as well as the monitoring of copper quality in the various production steps. A promising technique to perform these tasks is Laser Induced Breakdown Spectroscopy (LIBS). Its unique feature, among others, is the ability to measure on site without sample collection and preparation. In this work, copper-bearing minerals from two different deposits are studied. The first set of field samples come from a volcanogenic massive sulfide (VMS) deposit, the second part from a stratiform sedimentary copper (SSC) deposit. Different approaches are used to analyze the data. First, univariate regression (UVR) is used. However, due to the strong influence of matrix effects, this is not suitable for the quantitative analysis of copper grades. Second, the multivariate method of partial least squares regression (PLSR) is used, which is more suitable for quantification. In addition, the effects of the surrounding matrices on the LIBS data are characterized by principal component analysis (PCA), alternative regression methods to PLSR are tested and the PLSR calibration is validated using field samples.
Background
The aggregation of a series of N-of-1 trials presents an innovative and efficient study design, as an alternative to traditional randomized clinical trials. Challenges for the statistical analysis arise when there is carry-over or complex dependencies of the treatment effect of interest.
Methods
In this study, we evaluate and compare methods for the analysis of aggregated N-of-1 trials in different scenarios with carry-over and complex dependencies of treatment effects on covariates. For this, we simulate data of a series of N-of-1 trials for Chronic Nonspecific Low Back Pain based on assumed causal relationships parameterized by directed acyclic graphs. In addition to existing statistical methods such as regression models, Bayesian Networks, and G-estimation, we introduce a carry-over adjusted parametric model (COAPM).
Results
The results show that all evaluated existing models have a good performance when there is no carry-over and no treatment dependence. When there is carry-over, COAPM yields unbiased and more efficient estimates while all other methods show some bias in the estimation. When there is known treatment dependence, all approaches that are capable to model it yield unbiased estimates. Finally, the efficiency of all methods decreases slightly when there are missing values, and the bias in the estimates can also increase.
Conclusions
This study presents a systematic evaluation of existing and novel approaches for the statistical analysis of a series of N-of-1 trials. We derive practical recommendations which methods may be best in which scenarios.
Local laws on urban policy, i.e., ordinances directly affect our daily life in various ways (health, business etc.), yet in practice, for many citizens they remain impervious and complex. This article focuses on an approach to make urban policy more accessible and comprehensible to the general public and to government officials, while also addressing pertinent social media postings. Due to the intricacies of the natural language, ranging from complex legalese in ordinances to informal lingo in tweets, it is practical to harness human judgment here. To this end, we mine ordinances and tweets via reasoning based on commonsense knowledge so as to better account for pragmatics and semantics in the text. Ours is pioneering work in ordinance mining, and thus there is no prior labeled training data available for learning. This gap is filled by commonsense knowledge, a prudent choice in situations involving a lack of adequate training data. The ordinance mining can be beneficial to the public in fathoming policies and to officials in assessing policy effectiveness based on public reactions. This work contributes to smart governance, leveraging transparency in governing processes via public involvement. We focus significantly on ordinances contributing to smart cities, hence an important goal is to assess how well an urban region heads towards a smart city as per its policies mapping with smart city characteristics, and the corresponding public satisfaction.
Interest rates are central determinants of saving and investment decisions. Costly financial intermediation distorts these price signals by creating a spread between deposit and loan rates. This study investigates how bank spreads affect climate policy in its ambition to redirect capital. We identify various channels through which interest spreads affect carbon emissions in a dynamic general equilibrium model. Interest rate spreads increase abatement costs due to the higher relative price for capital-intensive carbon-free energy, but they also tend to reduce emissions due to lower overall economic growth. For the global average interest rate spread of 5.1 percentage points, global warming increases by 0.2°C compared to the frictionless economy. For a given temperature target to be achieved, interest rate spreads necessitate substantially higher carbon taxes. When spreads arise from imperfect competition in the intermediation sector, the associated welfare costs can be reduced by clean energy subsidies or even eliminated by economy-wide investment subsidies.
This paper applies Monster Theory to the use of Greek mythology in three creator-owned comic series by female writers: InSEXts (2016 – 2017) by American comic writer Marguerite Bennett and Indonesian artist working in America Ariela Kristantina as well as Eros/Psyche (2021) and Porcelain (2021) by Maria Llovet, a comic writer and artist from Barcelona. In the first volume of InSEXts, set in Victorian London, there are allusions to the Furies and Pandora, linked with the discourse of the repression of women. In the second volume, set in the late nineteenth century Paris art world, the representation of classical subjects in art becomes a means to repress women, and a goddess with a Gorgon-like appearance takes revenge on the male repressors. In Eros/Psyche the story of Eros and Psyche and broken statues forms the backdrop and context for a tale of love and deception at a girls’ school, and in Porcelain a girl is faced with a choice of paths towards Eros or Thanatos, like Herakles at the crossroads choosing between the paths of virtue and vice. With reference to Cohen’s seven theses of Monster Culture I examine how Bennett and Lovett subvert the idea of the monster and the hero.
Charitable giving
(2023)
We investigate how different levels of information influence the allocation decisions of donors who are entitled to freely distribute a fixed monetary endowment between themselves and a charitable organization in both giving and taking frames. Participants donate significantly higher amounts, when the decision is described as taking rather than giving. This framing effect becomes smaller if more information about the charity is provided.
Challenges and proposals for introducing digital certificates in higher education infrastructures
(2023)
Questions about the recognition of MOOCs within and outside higher education were already being raised in the early 2010s. Today, recognition decisions are still made more or less on a case-by-case basis. However, digital certification approaches are now emerging that could automate recognition processes. The technical development of the required machinereadable documents and infrastructures is already well advanced in some cases. The DigiCerts consortium has developed a solution based on a collective blockchain. There are ongoing and open discussions regarding the particular technology, but the institutional implementation of digital certificates raises further questions. A number of workshops have been held at the Institute for Interactive Systems at Technische Hochschule Lübeck, which have identified the need for new responsibilities for issuing certificates. It has also become clear that all members of higher education institutions need to develop skills in the use of digital certificates.