Notes

Microsecond hydrodynamic relationships inside lustrous colloidal dispersions probed in the Western european XFEL.
Relatively few studies have considered the impact of the COVID-19 pandemic on intimate partner violence (IPV) advocates or the agencies where they work. In this study, based on United States IPV advocates' experiences working with survivors during the COVID-19 pandemic, we conducted interviews to explore 1) personal challenges and resilience working as IPV advocates during the COVID-19 pandemic; 2) how agencies adapted to the pandemic to support IPV survivors and advocates; and 3) specific needs and challenges of culturally-specific agencies. We conducted semi-structured interviews with 53 IPV advocates from June to November 2020. Participants were included if they worked directly with survivors, identified as an IPV advocate, worked at a US-based agency, and spoke and understood English. We created a sampling matrix to ensure adequate representation from IPV advocates serving survivors from communities which have been marginalized. Interviews were conducted through a virtual platform by a trained member of the research team. We used an inductive thematic analysis approach, with weekly coding meetings to resolve discrepancies in coding. Five themes emerged from the data 1) IPV advocates described how working as an IPV advocate during the COVID-19 pandemic impacted them personally; 2) agencies developed new methods of addressing IPV advocates' needs; 3) agencies developed new solutions to address pandemic-related client needs; 4) transitioning advocacy work to virtual formats created challenges but also opportunities and; 5) pandemic limitations and impacts compounded pre-pandemic challenges for culturally specific agencies. IPV advocates are frontline workers who have played essential roles in adjusting services to meet survivor needs during the COVID-19 pandemic while simultaneously coping with pandemic impacts on themselves and their agencies. Developing inter-agency collaborations and promoting advocates' safety and wellbeing during future public health crises will help support IPV survivors.This article disentangles and explores some commonly made assumptions about egalitarian state-socialist ideologies. Based on the conceptual framework of the multiprinciple approach of justice, it presents the results of an in-depth analysis of (e)valuation patterns of distributive justice in Cuban state-socialism. The analysis mainly focuses on ideational conceptions of distributive justice (just rewards), but it also accounts for distribution outcomes and resulting (in)equalities (actual rewards). The results of the comparative case study of the Cuban framework of institutions and political leaders' views in two periods of time, the early 1960s and the 2010s, point to (e)valuation patterns that are generally labelled as egalitarian, such as the allocation rules of outcome equality and (non-functional) needs. However, contrary to common assumptions about egalitarian state-socialist ideologies, the results also point to several other patterns, including equity rules as well as functional and productivist allocation rules. I argue that many of these (e)valuation patterns, in their connection to the discursive storyline of the Cuban economic battle, are indeed compatible with egalitarian state-socialist ideology.Learning from texts has been widely adopted throughout industry and science. While state-of-the-art neural language models have shown very promising results for text classification, they are expensive to (pre-)train, require large amounts of data and tuning of hundreds of millions or more parameters. This paper explores how automatically evolved text representations can serve as a basis for explainable, low-resource branch of models with competitive performance that are subject to automated hyperparameter tuning. We present autoBOT (automatic Bags-Of-Tokens), an autoML approach suitable for low resource learning scenarios, where both the hardware and the amount of data required for training are limited. The proposed approach consists of an evolutionary algorithm that jointly optimizes various sparse representations of a given text (including word, subword, POS tag, keyword-based, knowledge graph-based and relational features) and two types of document embeddings (non-sparse representations). The key idea of autoBOT is that, instead of evolving at the learner level, evolution is conducted at the representation level. The proposed method offers competitive classification performance on fourteen real-world classification tasks when compared against a competitive autoML approach that evolves ensemble models, as well as state-of-the-art neural language models such as BERT and RoBERTa. Moreover, the approach is explainable, as the importance of the parts of the input space is part of the final solution yielded by the proposed optimization procedure, offering potential for meta-transfer learning.
Despite their fundamental role in determining many important properties of materials, detailed momentum-dependent information on the strength of electron-phonon and phonon-phonon coupling across the entire Brillouin zone has remained elusive. Ultrafast electron diffuse scattering (UEDS) is a recently developed technique that is making a significant contribution to these questions. Here, we describe both the UEDS methodology and the information content of ultrafast, photoinduced changes in phonon-diffuse scattering from single-crystal materials. We present results obtained from Ni, WSe
, and TiSe
, materials that are characterized by a complex interplay between electronic (charge, spin) and lattice degrees of freedom. We demonstrate the power of this technique by unraveling carrier-phonon and phonon-phonon interactions in both momentum and time and following nonequilibrium phonon dynamics in detail on ultrafast time scales. By combining
calculations with ultrafast diffuse electron scattering, insights into electronic and magnetic dynamics that impact UEDS indirectly can also be obtained.

To realize the full gamut of functions that are envisaged for electronic textiles (e-textiles) a range of semiconducting, conducting and electrochemically active materials are needed. This article will discuss how metals, conducting polymers, carbon nanotubes, and two-dimensional (2D) materials, including graphene and MXenes, can be used in concert to create e-textile materials, from fibers and yarns to patterned fabrics. Many of the most promising architectures utilize several classes of materials (e.g., elastic fibers composed of a conducting material and a stretchable polymer, or textile devices constructed with conducting polymers or 2D materials and metal electrodes). click here While an increasing number of materials and devices display a promising degree of wash and wear resistance, sustainability aspects of e-textiles will require greater attention.
Depression and anxiety are highly prevalent and comorbid in adolescents, and this co-occurrence leads to worse prognosis and additional difficulties. The relationship between depression and anxiety must be delineated to, in turn, reduce and prevent the comorbidity, however our knowledge is still limited. We used network analysis to investigate bridge symptoms; symptoms that connect individual depression and anxiety symptoms and thus can help explain the comorbidity. We also examined the role of relevant risk and protective factors in explaining these symptom-level associations between these disorders. We analyzed data from the Avon Longitudinal Study of Children and Parents (n = 3670). Depression and anxiety symptoms, peer victimization, bullying, peer relational problems, prosocial behavior, and parental monitoring were assessed at a single time point around age 13 years. Stressful life events (SLEs) were assessed at age 11 years. We identified the most prominent bridge symptoms among depression ("feeling unhappy", "feeling lonely") and anxiety symptoms ("worrying about past", "worrying about future"). Peer relational difficulties and SLEs were strongly associated with several depression and anxiety symptoms, such that these two risk factors created a link between individual depression and anxiety symptoms. Prosocial behavior had several negative associations with symptoms of both disorders, suggesting it can be an important protective factor.
The online version contains supplementary material available at 10.1007/s10862-021-09880-5.
The online version contains supplementary material available at 10.1007/s10862-021-09880-5.During the COVID-19 pandemic, an increasing reliance on digital technology to carry out social, entertainment, work and school activities increased, which may have affected the ways in which parents mediated their children's digital technology use. Given the prominent role that digital technology will have in the future, it is important to investigate parent and child characteristics which impacted parental mediation of children's digital technology use. Therefore, the present study aimed at analysing the frequency of parental mediation strategies (i.e. active and restrictive) during lockdown, their determinants, and how the two strategies affected children's digital skills and time spent online. Data were collected from 461 parent and 461 child participants. Results showed that almost half of parents (46%) practiced parental mediation with the same frequency, while the 42.6% applied it more often. Active mediation was predicted by parental worries about online risks, while restrictive mediation was predicted by time spent online by children, parental worries about online risks, parental negative attitudes towards digital technology and parents' digital skills. Children developed more digital skills when their parents applied higher levels of both active and restrictive mediation, and they spent the lowest amount of time online when their parents employed higher levels of restrictive and lower levels of active mediation. Practical implications for families and children's wellbeing are discussed.This paper presents an overall educational philosophy of working with students underprepared for college-level work, which we term "a pedagogy of preparation." We consider how instructors scaffolded instruction to foster college readiness in students who were now able to enroll in college-level work regardless of academic preparation after state-level legislation (SB 1720) that dramatically altered the delivery of developmental education in the Florida College System (FCS). We also consider how collaboration increased among campus personnel after the legislation to foster college readiness in students underprepared for college-level work.The faculty sabbatical leave has been present in many institutions of higher education since its inception at Harvard University in 1880 but is relatively underexamined in the literature related to the outcomes not only to the institution but also to the faculty member. This study included interviews with 12 faculty members at one research university in the U.S. to better understand their perceptions of their sabbatical experiences in relation to the model of faculty professional growth. Findings underscored that faculty were agentic in their learning, the professional relationships they sought out to do this learning, as well as the commitments they made in this learning and growth, including that of their own work-life balance.
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