65 research outputs found
A cooperative of their own: Gender implications on renewable energy cooperatives in Germany
No full textRenewable energy cooperatives are crucial for local communities to initiate energy transition. With a mixed-methodological approach, this paper analyses the participation of women in renewable energy cooperatives in Germany and reveals the socio-cultural barriers. This study presents an intersectional analysis that integrates gender with other socio-cultural categories and identities within the social context of cooperatives. This study presents the results from a sex ratio analysis of energy cooperatives (N=388), online interviews (N=161), and semi-structured interviews (N=9). Results show that a lack of awareness of opportunities, financial resources, and time for volunteer-based workload and the lack of recognition of social inequalities in the cooperatives hinder women from actively taking part in leadership roles. This study concludes by discussing how contribution to localised renewable energy production reflects differently on genders. It also provides suggestions such as mentorship and diversity programs that would allow more women to take management roles and encourage a more inclusive and fair transition for all.European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie action grant agreement No 813837 MISTRAL Project
A critical comparison of approaches to resource name management within the IEC common information model
No full textCopyright @ 2012 IEEEElectricity network resources are frequently identified within different power systems by inhomogeneous names and identities due to the legacy of their administration by different utility business domains. The IEC 61970 Common Information Model (CIM) enables network modeling to reflect the reality of multiple names for unique network resources. However this issue presents a serious challenge to the integrity of a shared CIM repository that has the task of maintaining a resource manifest, linking network resources to master identities, when unique network resources may have multiple names and identities derived from different power system models and other power system applications. The current approach, using CIM 15, is to manage multiple resource names within a singular CIM namespace utilizing the CIM “IdentifiedObject” and “Name” classes. We compare this approach to one using additional namespaces relating to different power systems, similar to the practice used in CIM extensions, in order to more clearly identify the genealogy of a network resource, provide faster model import times and a simpler means of supporting the relationship between multiple resource names and identities and a master resource identity.This study is supported by the UK National Grid and Brunel University
Decoding violence against women: analysing harassment in middle eastern literature with machine learning and sentiment analysis
No full textAbstract The rising prevalence of harassment in Middle Eastern countries is mirrored in literary works from the region. However, extracting data from these texts to understand the typology and frequency of the cases poses a significant challenge due to human cognitive limitations and potential biases. Thus, this study aims to use natural language processing (NLP) approaches to propose a machine learning framework for text mining of sexual harassment content in literary texts. The data source for this study consists of twelve Middle Eastern novels. The proposed framework involves the classification of physical and non-physical types of sexual harassment using a machine-learning model. Lexicon-based sentiment and emotion detection are applied to sentences containing instances of sexual harassment for data labelling and analysis. Finally, a long short-term memory-gated recurrent unit (LSTM-GRU) deep learning model is built to classify the sentiment characteristics that induce sexual harassment. The proposed model achieved an accuracy of 75.8% while outperforming five other algorithms. Additionally, a sentiment classification with three labels—negative, positive, and neutral—was developed using an LSTM-GRU RNN deep learning model. The accuracy of this model was 84.5%. Most statements, even those involving physical sexual harassment, which had greater levels of sexual harassment, had negative sentiments, according to lexicon-based sentiment analysis. This study contributes to the field of text mining by providing a novel approach to identifying instances of sexual harassment in literature in English from the Middle East. The use of machine learning models and sentiment analysis techniques allows for more accurate identification and classification of different types of sexual harassment. Furthermore, this study sheds light on the prevalence of sexual harassment in Middle Eastern countries and highlights the need for further research and action to address this issue
Emotions Toward Sustainable Innovations: A Matter of Value Congruence
No full textPublic resistance to sustainable innovations is oftentimes accompanied by strong negative emotions. Therefore, it is essential to better understand the underlying factors of emotions toward sustainable innovations to facilitate their successful implementation. Based on the Value-Innovation-Congruence model of Emotional responses (VICE model), we argue that positive and negative emotions toward innovations reflect whether innovations are congruent or incongruent with (i.e., support or threaten) people's core values. We tested our reasoning in two experimental studies (N = 114 and N = 246), by asking participants to evaluate innovations whose characteristics were either congruent or incongruent with egoistic values (study 1) or with biospheric values (study 1 and study 2). In line with the VICE model, we found overall that the more an innovation was perceived to have characteristics congruent with these values, and biospheric values in particular, the stronger positive and the weaker negative emotions they experienced toward the innovation, especially the more strongly people endorsed these values. Emotions, in turn, were related with acceptability of innovations. Our findings highlight that emotions toward innovations can have a systematic basis in people's values that can be addressed to ensure responsible decision-making on sustainable innovations
Adapting to Dynamic User Preferences in Recommendation Systems via Deep Reinforcement Learning
No full textRecommender Systems play a significant part in filtering and efficiently prioritizing relevant information to alleviate the information overload problem and maximize user engagement. Traditional recommender systems employ a static approach towards learning the user's preferences, relying on logged previous interactions with the system, disregarding the sequential nature of the recommendation task and consequently, the user preference shifts occurring across interactions. In this study, we formulate the recommendation task as a slate Markov Decision Process (slate-MDP) and leverage deep reinforcement learning (DRL) to learn recommendation policies through sequential interactions and maximize user engagement over extended horizons in non-stationary environments. We construct the simulated environment with various degrees of preferential dynamics and benchmark two DRL-based algorithms: FullSlateQ, a non-decomposed full slate Q-learning based on a DQN agent, and SlateQ, which implements DQN using slate decomposition. Our findings suggest that SlateQ outperforms by 10.57% FullSlateQ in non-stationary environments and that with a moderate discount factor, the algorithms behave myopically and fail to make an appropriate tradeoff to maximize long-term user engagement.CSE3000 Research ProjectComputer Science and Engineerin
The monograph “Toxocariasis – Current Issue of the Medical and Sanitary Services”, the author Gheorghe Placinta
No full textDepartment of Infectious Diseases, Nicolae Testemitsanu State University of Medicine and Pharmacy Chisinau, the Republic of Moldov
LA HISTORIA DE PANTEA EN CUATRO ROMANCES DE JUAN DE LA CUEVA
No full textPanthea’s tale in four ballads of Juan de la Cueva. In this paper the author analyzes the celebrate Panthea and Abradates’ tale and the literary treatment in the passing from its original literary context –Xenophon’s Cyropaedia - into the new furnished by the paraphrase of Juan de la Cueva in four ballads of his first Coro febeoPanthea’s tale in four ballads of Juan de la Cueva. In this paper the author analyzes the celebrate Panthea and Abradates’ tale and the literary treatment in the passing from its original literary context –Xenophon’s Cyropaedia - into the new furnished by the paraphrase of Juan de la Cueva in four ballads of his first Coro febeo
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Sachbericht zum Verwendungsnachweis
No full textGlobal H2-Upscaling untersuchte, welche Maßnahmen für ein upscaling ausländischer EE-basierter Wasserstoff-Produktionskerne notwendig sind, sodass sie i) einen relevanten Beitrag zur deutschen H2-Versorgung leisten und ii) gleichzeitig die energie- und
entwicklungspolitischen Ziele der Gastländer berücksichtigen. Dabei wurden in mehreren Aspekten methodische Neuerungen im Vergleich zu den zu Beginn des Vorhabens vor allem verbreiteten Potentialanalysen eingeführt: Im Gegensatz dazu wurde auf bereits vorhandene oder zumindest in der Planung befindliche Produktionskerne fokussiert. Da dies typischerweise Demonstrationsvorhaben sind, wäre ein Upscaling um das 100-fache oder 1000-fache anzustreben, um relevante Beiträge für Deutschland leisten zu können. Für die konkreten Fälle wurden Analysen notwendiger Maßnahmen mit Blick auf EE-Ausbau, Infrastrukturausbau, lokalen Bedarfen an EE, Wasserressourcen und Flächen sowie evtl. Änderungsbedarfen in der nationalen Regulierung etc. in konkreten Länderkontexten untersucht und ein weiterer Schwerpunkt auf Akzeptanz- und Legitimationsaspekte gelegt. Daher wurden neben Analysen in Deutschland auch Vor-Ort-Studien durchgeführt, um die notwendigen Bedingungen mit den jeweiligen kulturellen und lokalen Gegebenheiten tatsächlich anhand vielfältiger Stakeholder*inneninterviews erfassen zu können. Die Gesellschaft für Internationale Zusammenarbeit (GIZ, vertreten durch den PtX Hub) unterstützte die notwendigen Analysen im Unterauftrag - auch mit Personal vor Ort. Weitere Ziele bestanden in der Untersuchung der Konsequenzen für die globalen H2- und PtX-Märkte, die sowohl durch den Import als auch durch die Nachfrage anderer Weltregionen entstehen, sowie die daraus erwachsenen geopolitischen Effekte. Schließlich wurde untersucht, wie Deutschland zur Hochskalierung der Produktionskerne beitragen kann. Die Ergebnisse dieser Analysen wurden und werden in vielfältiger Form veröffentlicht
Clinical Dental Care Epidemiology, Prevalence, Symptoms and Routes of Transmission of Coronavirus Disease 19: A Systematic Review of Literature and Meta-Analysis
No full textObjective: To evaluate the epidemiological evidence, symptoms, and transmission routes of Coronavirus Disease 19 for clinical dental care. Material and Methods: PubMed, Embase, ISI, Scopus, Medicine have been used to search for articles until October 2020. Therefore, EndNote X9 was used to manage electronic resources. A 95% confidence interval (CI) effect size, random effect model, and the REML method were evaluated. Forty-one articles were found. In the first step of selecting studies, 40 studies were selected to review the abstracts. Finally, six studies were selected. Results: The effect size of symptoms of COVID-19 was fever: 92% (ES = 0.92, 95% CI 0.79-1.06), cough: 73% (ES = 0.73, 95% CI 0.59-0.88), headache: 8% (ES = 0.8, 95% CI 0.06-0.22), myalgia 13% (ES = 0.13, 95% CI 0.01-0.27) and nasal congestion 22% (ES = 0.22, 95% CI 0.06-0.39). The following recommendations are appropriate during COVID-19 for dental emergency management: personal protective equipment and hand cleanliness practices, personal protective equipment (PPE), preprocedural mouth rinse, single-use (disposable), cone-beam computed tomography (CBCT) and periapical (PA) radiography, Rubber dam, sodium hypochlorite for root canal irrigation, disinfect inanimate surfaces, ultrasonic scaling instruments and airborne infection isolation. Conclusion: Fever should be used as the first sign in the diagnosis; dentists should measure the fever of all patients at the time of arrival and before any procedure and then ask about other symptoms
Obchodní válka mezi USA a Čínou: Účinky čínských odvetných cel na obchod se sójou
No full textV létě 2018 začala Trumpova administrativa uvalovat cla na čínský vývoz, což dále podnítilo odvetu ze strany Číny, která následně rozpoutala obchodní válku mezi dvěma největšími ekonomikami světa. Eskalovaný obchodní konflikt mezi Spojenými státy a Čínou v průběhu roku 2018 také přitáhl velkou pozornost osob, které jsou přímo zapojeny do obchodování s Čínou a jsou na tomto trhu vysoce závislé. Narušené obchodní vztahy mezi oběma ekonomikami byly obzvláště zničující pro americké zemědělství, zejména pro sójové boby, protože Čína byla největším obchodním partnerem Spojených států z touto komoditou za posledních deset let. Cílem bakalářské práce je tedy identifikovat dopady obchodní války mezi USA a Čínou na obchod se sójovými boby. K prozkoumání účinků použije autor kvantitativní metody zkoumání pomocí analýzy sekundárních kvantitativních údajů. Vzhledem k silné geografické koncentraci obchodu se sójovými boby by velké poruchy způsobené obchodní válkou mohly z dlouhodobého hlediska snížit obchodní podíl Spojených států na celosvětovém trhu se sójovými boby a vyústit v to, že se Brazílie stane předním dodavatelem sójových bobů do Číny, což následně rozšíří její tržní podíl v Číně. Práce začíná zkoumáním původu obchodního napětí mezi Spojenými státy a Čínou. Pak zkoumá zvyšování cel mezi zeměmi a zaměřuje se na zemědělství. Dále analyzuje změny v obchodu se sójou po zavedení odvetných čínských cel. Nakonec přezkoumává obchodní dohodu první fáze podepsanou Čínou a Spojenými státy.In summer 2018, the Trump administration began imposing tariffs on Chinese exports, further prompting retaliation from China, which consequently sparked the trade war between the world’s two largest economies. Escalated trade conflict between the United States and China over the course of 2018 has also drawn a great deal of attention of those directly involved in trading with China and highly dependent on this market. Disrupted trade relationship between the two economies was particularly devastating for U.S. agriculture, especially soybeans, since China has been the largest export market for this commodity for the past decade. Accordingly, the aim of the thesis is to identify the effects of the U.S.-China trade war on trade in soybeans. In order to explore the effects, the author will utilize quantitative methods of investigation by analyzing secondary quantitative data. Given the strong geographic concentration of soybean trade, the major disruptions caused by the trade war might, in the long term, reduce the trade share of the United States in the global soybean market and result in Brazil becoming the leading supplier of soybeans to China, consequently expanding its market share in China. The thesis starts by investigating the origins of trade tensions between the United States and China. Then it examines tariff escalation between the countries, focusing on agriculture. Next, it analyzes changes in soybean trade following Chinese retaliatory tariffs. Finally, it reviews the Phase One trade deal
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