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Rainfall is associated with divorce in the socially monogamous Seychelles warbler
No full text1. Divorce—terminating a pair bond whilst both members are alive—is a mating strategy observed in many socially monogamous species often linked to poor reproductive success. As environmental factors directly affect individual condition and reproductive performance, they can indirectly influence divorce. Given current climate change, understanding how environmental fluctuations affect partnership stability has important implications, including for conservation. Yet, the relationship between the environment and divorce remains largely unstudied.
2. We examined the influence of temporal environmental variability on the prevalence of within- and between-season divorce and the possible underlying mechanisms in a socially monogamous passerine.
3. Analysing 16 years of data from a longitudinal dataset, we investigated the relationship between rainfall and divorce in the Seychelles warbler (Acrocephalus sechellensis). First, we performed climate window analyses to identify the temporal windows of rainfall that best predict reproductive success and divorce. Then, we tested the effects of these temporal windows of rainfall on reproductive success and divorce and the influence of reproductive success on divorce whilst controlling for covariates.
4. Annual divorce rates varied from 1% to 16%. The probability of divorce was significantly associated with the quadratic effect of 7 months of total rainfall before and during the breeding season, with divorce increasing in years with low and high rainfall. This quadratic relationship was driven by a heavy rainfall event in 1997, as excluding 1997 from our analyses left a significant negative linear relationship between rainfall and divorce. Although the same temporal window of rainfall predicting divorce significantly influenced reproductive success, we found no significant correlation between reproductive success and divorce.
5. Our findings suggest that rainfall impacts divorce. Given that this effect is likely not directly mediated by reproductive success, we discuss other possible drivers. Although the 1997 super El Niño event shows how heavy rainfall may affect socially monogamous partnerships, more data are required to estimate the robustness of this effect. By adding to the growing body of literature showing that environmental conditions influence the stability of socially monogamous partnerships, we provide novel insights that may also be important for conservation efforts in times of climate change
Theta Transcranial Alternating Current Stimulation Is Not Effective in Improving Working Memory Performance
Get PDFThere is an extensive body of research showing a significant relationship between frontal midline theta activity in the 4- to 8-Hz range and working memory (WM) performance. Transcranial alternating current stimulation (tACS) is recognized for inducing lasting changes in brain oscillatory activity. Across two experiments, we tested whether WM could be improved through tACS of dorsomedial pFC and ACC, by affecting executive control networks associated with frontal midline theta. In Experiment 1, after either a 20-min verum or sham stimulation applied to Fpz–CPz at 1 mA and 6 Hz, 31 participants performed WM tasks, while EEG was recorded. The tasks required participants to either mentally manipulate memory items or retain them in memory as they were originally presented. No significant effects were observed in behavioral performance, and we found no change in theta activity during rest and task after stimulation. However, alpha activity during retention or manipulation of information in WM was less strongly enhanced during the delay period after verum stimulation as compared with sham. In Experiment 2 (n = 25), tACS was administered during the task in two separate sessions. Here, we changed the order of the stimulation blocks: A 25-min task block was either accompanied first by sham stimulation and then by verum stimulation, or vice versa. Again, we found no improvements in WM through either tACS after-effects or online stimulation. Taken together, our results demonstrate that theta frequency tACS applied at the midline is not an effective method for enhancing WM
Divergences and convergences across European musical preferences: how taste varies within and between countries
Get PDFWhen investigating relational structures in culture, research in Europe has often either mapped the relationship between cultural tastes in a particular context, or mapped differences in cultural tastes (measured consistently) in different countries, without assessing how these differences can vary across them. Indeed, the idea of national homology (namely that the structures of cultural capital would be fairly similar in nations across Europe) has never been really tested, probably due to a lack of cross-national research on cultural preferences. Using data from the EUCROSS survey that took place in Denmark, Germany, Italy, Romania, Spain and the UK (2012–2013, n = 6016), we first use multiple correspondence analysis to estimate the relationships between a set of items on musical tastes. We then extend this through the use of class-specific analysis, to investigate how these relationships vary in each of the six countries. Finally, we analyse the relationships between the underlying dimensions of music tastes and different components of cosmopolitanism, compared with key demographic variables. We show that the musical field significantly varies across the nations represented in the survey, demonstrating that musical preferences remain largely anchored in national contexts. Cultural preferences are shaped by historical and social dynamics specific to each country, with significant variations in the symbolic value and demographic associations of music genres
Gaps in our understanding of ice-nucleating particle sources exposed by global simulation of the UK Earth System Model
No full textChanges in the availability of a subset of aerosol known as ice-nucleating particles (INPs) can substantially alter cloud microphysical and radiative properties. Despite very large spatial and temporal variability in INP properties, many climate models do not currently represent the link between (i) the global distribution of aerosols and INPs and (ii) primary ice production in clouds. Here we use the UK Earth System Model to simulate the global distribution of dust, marine-sourced, and black carbon INPs suitable for immersion-mode freezing of liquid cloud droplets over an annual cycle. The model captures the overall spatial and temporal distribution of measured INP concentrations, which is strongly influenced by the world's major mineral dust source regions. A negative bias in simulated versus measured INP concentrations at higher freezing temperatures points to incorrectly defined INP properties or a missing source of INPs. We find that the ability of the model to reproduce measured INP concentrations is greatly improved by representing dust as a mixture of mineralogical and organic ice-nucleating components, as present in many soils. To improve the agreement further, we define an optimized hypothetical parameterization of dust INP activity (ns(T)) as a function of temperature with a logarithmic slope of −0.175 K⁻¹, which is much shallower than existing parameterizations (e.g. −0.35 K⁻¹ for the K-feldspar data of Harrison et al., 2019). The results point to a globally important role for an organic component associated with mineral dust
Prospective piperacillin lymphocyte transformation testing in patients with cystic fibrosis receiving regular and desensitization courses of piperacillin-tazobactam
No full textBackground
Piperacillin-tazobactam is used in patients with cystic fibrosis to treat recurrent respiratory infections. Exposure is associated with a high frequency of non-immediate hypersensitivity.
Objective
To assess the applicability of the lymphocyte transformation test (LTT) for the diagnosis of piperacillin hypersensitivity and the influence of desensitization on piperacillin-specific T-cell responses.
Methods
Study-arm one was an analysis of LTT responses from 58 naïve/baseline tolerant patients with samples collected over a three-year interventional phase. In study-arm two, seventeen hypersensitive patients were recruited and LTTs were conducted before and post-desensitization. Clinical hypersensitivity reactions in both arms were monitored over an eight-year observational period.
Results
Fifty-eight patients in study arm one received 611 (range, 2-40; mean±SD, 10.5±8.1) piperacillin-tazobactam courses during the interventional phase, of which 11 developed hypersensitivity. The patients that remained tolerant received 236 piperacillin-tazobactam courses in the observational period, of which 9 developed hypersensitivity. Ten/eleven interventional phase hypersensitive patients had a positive LTT, while one remained negative. 136 negative LTTs were recorded with 39 tolerant patients, while eight patients recorded a positive LTT, with 4 developing hypersensitivity during the observational period. Ten LTT positive patients in study arm two underwent piperacillin-tazobactam desensitization, with seven tolerating the drug. The strength of the LTT decreased during desensitization and negative results were recorded for a minimum of 14-days. During follow-up, eight patients tolerated 62 piperacillin-tazobactam courses through desensitization.
Conclusions
LTT is a sensitive marker of drug sensitisation that could be used to inform future patient management. Desensitization is associated with attenuation of the piperacillin-specific T-cell response
RuvBL1/2 reduce toxic dipeptide repeat protein burden in multiple models of C9orf72-ALS/FTD
Get PDFA G4C2 hexanucleotide repeat expansion in C9orf72 is the most common cause of amyotrophic lateral sclerosis and frontotemporal dementia (C9ALS/FTD). Bidirectional transcription and subsequent repeat-associated non-AUG (RAN) translation of sense and antisense transcripts leads to the formation of five dipeptide repeat (DPR) proteins. These DPRs are toxic in a wide range of cell and animal models. Therefore, decreasing RAN-DPRs may be of therapeutic benefit in the context of C9ALS/FTD. In this study, we found that C9ALS/FTD patients have reduced expression of the AAA+ family members RuvBL1 and RuvBL2, which have both been implicated in aggregate clearance. We report that overexpression of RuvBL1, but to a greater extent RuvBL2, reduced C9orf72-associated DPRs in a range of in vitro systems including cell lines, primary neurons from the C9-500 transgenic mouse model, and patient-derived iPSC motor neurons. In vivo, we further demonstrated that RuvBL2 overexpression and consequent DPR reduction in our Drosophila model was sufficient to rescue a number of DPR-related motor phenotypes. Thus, modulating RuvBL levels to reduce DPRs may be of therapeutic potential in C9ALS/FTD
(Re)Examining the research-practice interface:International perspectives, multiple methods, persistent challenges, and novel directions
Get PDFIn applied linguistics, the interface between research and practice (broadly construed to include but not be limited to additional language teachers, teacher educators, policymakers, materials designers, test developers, etc.) has gained increasing attention in recent years (e.g., Sato & Loewen, 2022a). Recent calls (e.g., Sato, 2023) have urged applied linguists to both prioritize research which can INFORM and BE INFORMED BY practice as well as to focus research efforts on theorizing and empirically investigating the research-practice link ITSELF. In response to these calls, this colloquium brought together an international team of fourteen applied linguists to offer a state-of-the-art perspective on the research-practice relationship in applied linguistics. Collectively, this team presented findings and outcomes of recent empirical and practitioner initiatives in a wide range of educational contexts. The six presentations in the colloquium highlighted nuanced interfaces between research and practice via diverse collaborations, research methods, and empirical findings. Furthermore, collectively, they offered a more comprehensive portrayal of the current state of the research-pedagogy relationship in our field as well as clear indications for important next steps for applied linguists of all disciplinary traditions and contexts to further improve this relationship going forward
Computational fluid dynamics and shape analysis enhance aneurysm rupture risk stratification
Get PDFPurpose
Accurately quantifying the rupture risk of unruptured intracranial aneurysms (UIAs) is crucial for guiding treatment decisions and remains an unmet clinical challenge. Computational Flow Dynamics and morphological measurements have been shown to differ between ruptured and unruptured aneurysms. It is not clear if these provide any additional information above routinely available clinical observations or not. Therefore, this study investigates whether incorporating image-derived features into the established PHASES score can improve the classification of aneurysm rupture status.
Methods
A cross-sectional dataset of 170 patients (78 with ruptured aneurysm) was used. Computational fluid dynamics (CFD) and shape analysis were performed on patients’ images to extract additional features. These derived features were combined with PHASES variables to develop five ridge constrained logistic regression models for classifying the aneurysm rupture status. Correlation analysis and principal component analysis were employed for image-derived feature reduction. The dataset was split into training and validation subsets, and a ten-fold cross validation strategy with grid search optimisation and bootstrap resampling was adopted for determining the models’ coefficients. Models’ performances were evaluated using the area under the receiver operating characteristic curve (AUC).
Results
The logistic regression model based solely on PHASES achieved AUC of 0.63. All models incorporating derived features from CFD and shape analysis demonstrated improved performance, reaching an AUC of 0.71. Non-sphericity index (shape variable) and maximum oscillatory shear index (CFD variable) were the strongest predictors of a ruptured status.
Conclusion
This study demonstrates the benefits of integrating image-based fluid dynamics and shape analysis with clinical data for improving the classification accuracy of aneurysm rupture status. Further evaluation using longitudinal data is needed to assess the potential for clinical integration
Neural ordinary differential equations for predicting the temporal dynamics of a ZnO solid electrolyte FET
Get PDFEfficient storage and processing are essential for temporal data processing applications to make informed decisions, especially when handling large volumes of real-time data. Physical reservoir computing provides effective solutions to this problem, making them ideal for edge systems. These devices typically necessitate compact models for device-circuit co-design. Alternatively, machine learning (ML) can quickly predict the behaviour of novel materials/devices without explicitly defining any material properties and device physics. However, previously reported ML device models are limited by their fixed hidden layer depth, which restricts their adaptability to predict varying temporal dynamics of a complex system. Here, we propose a novel approach that utilizes a continuous-time model based on neural ordinary differential equations to predict the temporal dynamic behaviour of a charge-based device, a solid electrolyte FET, whose gate current characteristics show a unique negative differential resistance that leads to steep switching beyond the Boltzmann limit. Our model, trained on a minimal experimental dataset successfully captures device transient and steady state behaviour for previously unseen examples of excitatory postsynaptic current when subject to an input of variable pulse width lasting 20–240 milliseconds with a high accuracy of 0.06 (root mean squared error). Additionally, our model predicts device dynamics in ∼5 seconds, with 60% reduced error over a conventional physics-based model, which takes nearly an hour on an equivalent computer. Moreover, the model can predict the variability of device characteristics from device to device by a simple change in frequency of applied signal, making it a useful tool in the design of neuromorphic systems such as reservoir computing. Using the model, we demonstrate a reservoir computing system which achieves the lowest error rate of 0.2% in the task of classification of spoken digits
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