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The Politics of Cultural Renewal in Germany, 1830-1880.
No full textThough often regarded as a bastion of cultural self-confidence during the early and middle decades of the nineteenth century, the so-called Land der Dichter und Denker (‘land of poets and thinkers’) was in reality marked by profound insecurity and self-doubt—not limited to its latecomer status as a political power. The sense of unquestioned cultural supremacy that had defined the age of Beethoven, Goethe, and Hegel began to dissipate with their deaths in the late 1820s and early 1830s. Between 1830 and 1880, with a few notable exceptions such as Wagner, Nietzsche, Brahms, and Heine, few cultural figures matched the stature of their predecessors, as later generations never ceased to point out. No one felt this perceived decline more acutely than the German writers, artists, and thinkers who lived through it. Yet this period was not characterised by resignation alone. Alongside cultural despair came fits of manic, palingenetic optimism—anticipations of profound political transformation that would break them out of the trap into which they had fallen. This thesis examines the origins and development of this phenomenon through two such events: the revolutions of 1848–1849 and the unification of Germany in 1871. By analysing the intellectual and cultural responses to these events, this study sheds light on the ways in which German thinkers grappled with questions of identity, decline, and regeneration in an era of uncertainty and transformation
Conservation evidence is biased but can support decision‐making for prevalent and severe threats in tetrapods
No full textAbstract
Tackling the global decline in biodiversity requires effective conservation actions to manage ongoing threats. Evidence from the success of past interventions can help identify effective actions. Such evidence‐based conservation is facilitated by searchable resources that synthesize knowledge across taxa and conditions. The existing evidence base has known taxonomic and geographic gaps, but how the diversity and prevalence of threats affecting biodiversity is represented remains unclear.
We assessed the availability of evidence to address conservation threats, testing whether more evidence exists for actions tackling threats that affect more species (taxonomic prevalence) and from locations where threats are more likely (spatial prevalence). We focused on amphibians, reptiles, birds and mammals, groups with published conservation evidence synopses and completed IUCN Red List assessments listing threats.
Overall, there were more studies testing conservation actions directed at more common threats (high taxonomic prevalence). Actions tackling threats linked to agriculture and exploitation of natural resources, which affect the largest number of species (34.9% and 31.0% of 35128 species, respectively), had more evidence (20.6% and 18.5% of 3662 studies, respectively). However, actions for some threats were understudied (e.g. energy production and mining), while some had more evidence than expected (e.g. invasive species). Actions targeting more prevalent threats were not identified as more effective or better understood.
More studies tested conservation actions in areas where species were more likely to be impacted by threats (high spatial prevalence). However, only limited or no evidence was available for some highly impacted areas. For example, none of the 253 studies of actions addressing the impact of agriculture on birds were located in Africa, a region where 12% of the land is classed as high agriculture impact.
Synthesis and applications: Despite taxonomic and spatial biases, substantial conservation evidence is available to support decision‐making by practitioners, particularly for the most prevalent and severe threats. Given the current biodiversity crisis, it is critical that this information is more widely used and that coordination among academic and practitioner partners is encouraged to evaluate current evidence and fill gaps, for example, regarding energy production and mining. A reliable and transferable evidence base is essential to effectively tackle the biodiversity crisis.
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Methodological advancements in dialect identification tasks: perception, representation and social meaning in South East England
No full textThis study presents a dialect identification task in which 191 listeners drew on a digital map around the area(s) they thought 99 speakers were from and provided evaluative responses based on speech excerpts. This study is the first to demonstrate the importance of uniting five strands of investigation in dialect identification tasks: (1) listeners’ accuracy compared to chance; (2) listener-group and speaker-group accuracy; (3) precision; (4) misidentifications; (5) the relationship between attitudes and patterns of (mis)identification. This approach provides detailed insights into non-specialists’ perceptual representation of linguistic variation, comprising the first perceptual dialectology study in South East England. Results show that rather than identifying regional linguistic features, listeners were closely attuned to variation by class and ethnicity which predicted how they geographically assigned speakers. In addition, the method provides insights into perceptual processes, including the important role of social meaning in the perception and representation of dialects
Ensuring inclusion is central to critical care research design
No full textFamily members of people who have been admitted to critical care are known to experience
long-term adverse outcomes [1]. These can include mental health problems such as
posttraumatic stress, anxiety, and depression [2]. This has rightly drawn considerable
attention, with at least 59 randomised controlled trials (RCTs) delivering interventions to
support family members published in recent years [3]. Despite this, synthesised evidence in
relation to how outcomes in this cohort might be improved, remains inconclusive [4]
Health-related quality-of-life instruments for Alzheimer's disease and mixed dementia.
No full textBACKGROUND: Over the last 20 years, a number of instruments developed for the assessment of health-related quality of life (HRQL) in dementia have been introduced. The aim of this review is to synthesize evidence from published reviews on HRQL measures in dementia and any new literature in order to identify dementia specific HRQL instruments, the domains they measure, and their operationalization. METHODS: An electronic search of PsycINFO and PubMed was conducted, from inception to December 2011 using a combination of key words that included quality of life and dementia. RESULTS: Fifteen dementia-specific HRQL instruments were identified. Instruments varied depending on their country of development/validation, dementia severity, data collection method, operationalization of HRQL in dementia, psychometric properties, and the scoring. The most common domains assessed include mood, self-esteem, social interaction, and enjoyment of activities. CONCLUSIONS: A number of HRQL instruments for dementia are available. The suitability of the scales for different contexts is discussed. Many studies do not specifically set out to measure dementia-specific HRQL but do include related items. Determining how best to operationalize the many HRQL domains will be helpful for mapping measures of HRQL in such studies maximizing the value of existing resources
A modeling framework for detecting and leveraging node-level information in Bayesian network inference
No full textBayesian graphical models are powerful tools to infer complex relationships in high dimension, yet are often fraught with computational and statistical challenges. If exploited in a principled way, the increasing information collected alongside the data of primary interest constitutes an opportunity to mitigate these difficulties by guiding the detection of dependence structures. For instance, gene network inference may be informed by the use of publicly available summary statistics on the regulation of genes by genetic variants. Here we present a novel Gaussian graphical modeling framework to identify and leverage information on the centrality of nodes in conditional independence graphs. Specifically, we consider a fully joint hierarchical model to simultaneously infer (i) sparse precision matrices and (ii) the relevance of node-level information for uncovering the sought-after network structure. We encode such information as candidate auxiliary variables using a spike-and-slab submodel on the propensity of nodes to be hubs, which allows hypothesis-free selection and interpretation of a sparse subset of relevant variables. As efficient exploration of large posterior spaces is needed for real-world applications, we develop a variational expectation conditional maximization algorithm that scales inference to hundreds of samples, nodes and auxiliary variables. We illustrate and exploit the advantages of our approach in simulations and in a gene network study which identifies hub genes involved in biological pathways relevant to immune-mediated diseases
New parameters of power: On LLM-based manipulation and control and the spectre of strategic AI
No full textLarge language models (LLMs) can reproduce a wide variety of rhetorical styles and generate text that expresses a broad spectrum of sentiments. This capacity, now available at low cost, makes them powerful tools for manipulation and control. We draw attention to this phenomenon as an instance of a broader restructuring of computational infrastructures that introduce novel mechanisms for power. In this paper we consider four types of power made possible by the rapid and largely unregulated adoption of LLMs. These include the power to: (a) pollute and uniformize information environments, (b) persuade users via conversational interfaces (e.g., via ‘AI personas’), (c) create novel computational models of human agents (e.g., ‘silicon subjects’) and (d) create novel computational models of human agent populations (e.g., ‘silicon societies’). We draw attention to Meta's ‘Cicero’ model as a proof of concept for how such techniques can be used to produce controllable and steerable strategic dialogue models. We draw these strands together to argue that coordinated use of such techniques make LLM-based systems powerful instruments for the exertion, modulation, and projection of power. We situate these novel expressions of power in relation to ambitions to establish a new generative foundation for computing.</jats:p
Water security and hydrosocial resilience in the Peruvian Andes: Remote sensing and cultural governance in the Razuhuillca watershed
No full textDroughts and water-related conflicts in the Andean mountain regions of South America have intensified in recent decades, yet limited understanding of the interaction between hydrological dynamics and culturally embedded governance systems has constrained effective water-security strategies. This study addresses this gap by integrating remote-sensing indicators (NDWI, SAVI, NBR) with ethnographic and institutional data to analyze hydrosocial resilience in the Razuhuillca watershed (Huanta Province, Peruvian Andes) between 2016 and 2025. Multitemporal Sentinel-2 analysis reveals a structural decoupling between surface moisture and vegetation vigor, characterized by increasing NDWI and declining SAVI values (r = 0.411, p < 0.001), indicating a condition of humid degradation under climatic neutrality. Cross-correlation analysis identifies a three-month lag between precipitation and vegetation response, evidencing hydrological memory and slow-release watershed dynamics. Ethnographic evidence shows that local communities interpret these changes through cosmological frameworks that conceive water and mountains as living beings endowed with memory and moral agency. Ritual offerings, rain-calling burnings, purification ceremonies, and communal patrols function as hybrid infrastructures of regulation and repair, translating ecological stress into collective action. The 2020 water-poisoning crisis, which caused widespread trout mortality and a temporary suspension of urban water supply, served as a real-world stress test of this governance system, revealing resilience as containment rather than full ecological recovery. By explicitly combining Earth observation with situated knowledge, this study demonstrates the novelty of operationalizing hydrosocial resilience through remote sensing, and contributes to Sustainable Development Goals 6 (Clean Water and Sanitation) and 13 (Climate Action) by advocating governance frameworks that integrate technical monitoring with cultural and moral dimensions in Andean and other highland watersheds
Multi-Functional OCT Enables Longitudinal Study of Retinal Changes in a VLDLR Knockout Mouse Model.
No full textWe present a multi-functional optical coherence tomography (OCT) imaging approach to study retinal changes in the very-low-density-lipoprotein-receptor (VLDLR) knockout mouse model with a threefold contrast. In the retinas of VLDLR knockout mice spontaneous retinal-chorodoidal neovascularizations form, having an appearance similar to choroidal and retinal neovascularizations (CNV and RNV) in neovascular age-related macular degeneration (AMD) or retinal angiomatous proliferation (RAP). For this longitudinal study, the mice were imaged every 4 to 6 weeks starting with an age of 4 weeks and following up to the age of 11 months. Significant retinal changes were identified by the multi-functional imaging approach offering a threefold contrast: reflectivity, polarization sensitivity (PS) and motion contrast based OCT angiography (OCTA). By use of this intrinsic contrast, the long-term development of neovascularizations was studied and associated processes, such as the migration of melanin pigments or retinal-choroidal anastomosis, were assessed in vivo. Furthermore, the in vivo imaging results were validated with histological sections at the endpoint of the experiment. Multi-functional OCT proves as a powerful tool for longitudinal retinal studies in preclinical research of ophthalmic diseases. Intrinsic contrast offered by the functional extensions of OCT might help to describe regulative processes in genetic animal models and potentially deepen the understanding of the pathogenesis of retinal diseases such as wet AMD
A model for drug transport across two membranes of Gram-negative bacteria by an MFS tripartite assembly.
No full textTransport of proteins and small molecules across cellular membrane is crucial for bacterial interaction with the environment and survival against antibiotics. In Gram-negative bacteria that possess two layers of membranes, specialized macromolecular machines are required to transport substrates across the cell envelope, often via an indirect stepwise process. The major facilitator superfamily (MFS)-type tripartite efflux pumps use proton electrochemical gradient to extrude drugs in diverse bacterial species, but the architecture of the assembly and structural mechanisms remain elusive. A representative MFS-type tripartite efflux pump, EmrAB-TolC, mediates resistance to multiple antimicrobial drugs through proton-coupled EmrB, a member of the DHA2 transporter family. Here, we report the high-resolution (3.13 Å) structure of the EmrAB-TolC pump, revealing a distinct, asymmetric architecture emerging from the assembly of TolC:EmrA:EmrB with a ratio of 3:6:1 and contacts that are essential for the pump assembly. Key residues involved in drug transport are identified and corroborated by mutagenesis and antibiotic sensitivity assays. The structural and functional data support a model for one-step drug transport by the MFS pump across the entire envelope of Gram-negative bacteria