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This book is for teenage girls to read. Refreshingly frank and engaging first person stories, highly notable mentors, and stunning photography.

Hitlers Weg an die Macht ist oft beschrieben worden.Kaum beachtet wurde jedoch bisher, dass er sich dabei in starkem Maße an Mussolini orientierte.Der faschistische Diktator war sein großes Vorbild.Auf ihn ließ er auch nichts kommen, als er selbst die Macht erlangt hatte und der \"Duce\" von ihm abhängig geworden war.

We Fishis the tale of a father and son's shared dialogue in poetry and in prose, memoir and reflection, as they delight in their time spent fishing while considering the universal challenge of raising good children. Their story and their lesson have the power to teach today's young African American men about friendship, family, and trust; and the potential to save a generation from the dangers of the modern world and from themselves.

This cross-sectional study tests a conceptual financial socialization process model, specifying four-levels that connect anticipatory socialization during adolescence to young adults' current financial learning, to their financial attitudes, and to their financial behavior. A total of 2,098 first-year college students (61.9% females) participated in the survey, representing a diverse ethnic group (32.6% minority participation: Hispanic 14.9%, Asian/Asian American 9%, Black 3.4%, Native American 1.8% and other 3.5%). Structural equation modeling indicated that parents, work, and high school financial education during adolescence predicted young adults' current financial learning, attitude and behavior, with the role played by parents substantially greater than the role played by work experience and high school financial education combined. Data also supported the proposed hierarchical financial socialization four-level model, indicating that early financial socialization is related to financial learning, which in turn is related to financial attitudes and subsequently to financial behavior. The study presents a discussion of how the theories of consumer socialization and planned behavior were combined effectively to depict the financial development of young adults. Several practical implications are also provided for parents, educators and students.

Pre-training by language modeling has become a popular and successful approach to NLP tasks, but we have yet to understand exactly what linguistic capacities these pre-training processes confer upon models. In this paper we introduce a suite of diagnostics drawn from human language experiments, which allow us to ask targeted questions about information used by language models for generating predictions in context. As a case study, we apply these diagnostics to the popular BERT model, finding that it can generally distinguish good from bad completions involving shared category or role reversal, albeit with less sensitivity than humans, and it robustly retrieves noun hypernyms, but it struggles with challenging inference and role-based event prediction— and, in particular, it shows clear insensitivity to the contextual impacts of negation.

While there is ample research on the barriers and enablers for implementing circular economy (CE) in large companies and developed economies, scant research exists concerning the factors impacting CE implementation in small and medium enterprises (SMEs) in emerging economies. To address this gap, our research seeks to determine the internal and external barriers SMEs face when implementing CE initiatives in emerging economies and identify how they can leverage CE implementation through bottom-up approaches. We present a multiple-case study of five SMEs in Mexico. Our findings suggest that the lack of regional enabling conditions and unsuitability between the CE business strategy and the context can further exacerbate implementation barriers. In this sense, we found that in our study’s unsuccessful case, the company failed to align its business to the particularities of the markets where it operated. Contrary, successful initiatives adopted strategies that incorporated contextual attributes in their business models, such as available infrastructure, current regulations, or consumer characteristics. Our results provide lessons from both failing and successful CE initiatives implemented by SMEs in an emerging economy. This work intends to help practitioners, policymakers, and researchers to create the required enabling conditions to accelerate the transition toward a CE in these regions.

Global issues such as environmental problems and food security are currently of concern to all of us. Circular bioeconomy is a promising approach towards resolving these global issues. The production of bioenergy and biomaterials can sustain the energy–environment nexus as well as substitute the devoid of petroleum as the production feedstock, thereby contributing to a cleaner and low carbon environment. In addition, assimilation of waste into bioprocesses for the production of useful products and metabolites lead towards a sustainable circular bioeconomy. This review aims to highlight the waste biorefinery as a sustainable bio-based circular economy, and, therefore, promoting a greener environment. Several case studies on the bioprocesses utilising waste for biopolymers and bio-lipids production as well as bioprocesses incorporated with wastewater treatment are well discussed. The strategy of waste biorefinery integrated with circular bioeconomy in the perspectives of unravelling the global issues can help to tackle carbon management and greenhouse gas emissions. A waste biorefinery–circular bioeconomy strategy represents a low carbon economy by reducing greenhouse gases footprint, and holds great prospects for a sustainable and greener world.

“Nudge”-style interventions are often deemed successful if they generate large behavior change at low cost, but they are rarely subjected to full social welfare evaluations. We combine a field experiment with a simple theoretical framework to evaluate the welfare effects of one especially policy-relevant intervention, home energy social comparison reports. In our sample, the reports increase social welfare, although traditional evaluation approaches overstate gains because they ignore significant costs incurred by nudge recipients. Overall, home energy report welfare gains might be overstated by $620 million. We develop a prediction algorithm for optimal targeting; this approach would double the welfare gains.

Disturbance events can happen at a temporal scale much faster than wildland fire fuel data updates. When used as input for wildland fire behavior models, outdated fuel datasets can contribute to misleading forecasts, which have implications for operational firefighting, mitigation, and wildland fire research. Remote sensing and machine learning methods can provide a solution for on-demand fuel estimation. Here, we show a proof of concept using C-band synthetic aperture radar and multispectral imagery, land cover classes, and tree mortality surveys to train a random forest classifier to estimate wildland fire fuel data in the East Troublesome Fire (Colorado) domain. The algorithm classified over 80% of the test dataset correctly, and the resulting wildland fire fuel data was used to simulate the East Troublesome Fire using the coupled atmosphere—wildland fire behavior model, WRF-Fire. The simulation using the modified fuel inputs, where 43% of original fuels are replaced with fuels representing dead trees, improved the burn area forecast by 38%. This study demonstrates the need for up-to-date fuel maps available in real time to provide accurate prediction of wildland fire spread, and outlines the methodology based on high-resolution satellite observations and machine learning that can accomplish this task.