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Abstract Alpine grassland vegetation supports globally important biodiversity and ecosystems that are increasingly threatened by climate warming and other environmental changes. Trait-based approaches can support understanding of vegetation responses to global change drivers and consequences for ecosystem functioning. In six sites along a 1314 m elevational gradient in Puna grasslands in the Peruvian Andes, we collected datasets on vascular plant composition, plant functional traits, biomass, ecosystem fluxes, and climate data over three years. The data were collected in the wet and dry season and from plots with different fire histories. We selected traits associated with plant resource use, growth, and life history strategies (leaf area, leaf dry/wet mass, leaf thickness, specific leaf area, leaf dry matter content, leaf C, N, P content, C and N isotopes). The trait dataset contains 3,665 plant records from 145 taxa, 54,036 trait measurements (increasing the trait data coverage of the regional flora by 420%) covering 14 traits and 121 plant taxa (ca. 40% of which have no previous publicly available trait data) across 33 families.

With a focus on the challenges of today and tomorrow in the critical medical humanities the role of history is often overlooked. Yet history and medicine are closely intertwined. Right now, with the surfacing of knotty problems such as changing demographics, chronic pain, loneliness and Long Covid – and the consequent necessity to change directions and policies – history seems more urgent than ever. However, historians of medicine have sometimes been reticent to play a role in medicine and policymaking. The recent and welcome development of the critical medical humanities has intervened in medicine in important ways, but often without clear engagement with the history of medicine. In this letter, we make a renewed case for coherence and collaboration between history of medicine, medicine, and medical humanities, emphasising the continuity and links between all three. The skills and focus of the historian of medicine bring crucial historical context to the table, enabling better understanding of medical collecting, new imaginative futures, profound critiques of key medical concepts, and understandings of the body through time. By emphasising what historians can do for medicine and medical humanities, we call for building historical work into how medicine, illness and health are understood now and in the future. We suggest three potential roles for historians: keepers of memories, conversation partners, and futurist thinkers.

Abstract The Arctic is warming at a rate four times the global average, while also being exposed to other global environmental changes, resulting in widespread vegetation and ecosystem change. Integrating functional trait-based approaches with multi-level vegetation, ecosystem, and landscape data enables a holistic understanding of the drivers and consequences of these changes. In two High Arctic study systems near Longyearbyen, Svalbard, a 20-year ITEX warming experiment and elevational gradients with and without nutrient input from nesting seabirds, we collected data on vegetation composition and structure, plant functional traits, ecosystem fluxes, multispectral remote sensing, and microclimate. The dataset contains 1,962 plant records and 16,160 trait measurements from 34 vascular plant taxa, for 9 of which these are the first published trait data. By integrating these comprehensive data, we bridge knowledge gaps and expand trait data coverage, including on intraspecific trait variation. These data can offer insights into ecosystem functioning and provide baselines to assess climate and environmental change impacts. Such knowledge is crucial for effective conservation and management in these vulnerable regions.

The International Tundra Experiment (ITEX) was established to understand how environmental change impacts Arctic and alpine ecosystems. The success of the ITEX network has allowed for several important across-site syntheses, and for some ITEX sites enough data have now been collected to perform within-site syntheses on the effects of environmental change across ecological scales. In this study, we analyze climate data and synthesize three decades of research on the ecological effects of environmental change at the ITEX site at Finse, southern Norway. We found a modest warming rate of +0.36 °C per decade and minor effects on growing season length. Maximum winter snow depth was highest in winters with a positive North Atlantic Oscillation. Our synthesis included 80 ecological studies from Finse, biased towards primary producers with few studies on ecological processes. Species distributions depended on microtopography and microclimate. Experimental warming had contrasting effects on abundance and traits of individual species and only modest effects at the community level above and below ground. In contrast, nutrient addition experiments caused strong responses in primary producer and arthropod communities. This within-site synthesis enabled us to conclude how different environmental changes (experimental and ambient warming, nutrient addition, and environmental gradients) impact across ecological scales, which is challenging to achieve with across-site approaches.

Background. Weight loss and lifestyle interventions are the mainstay of treatment in pediatric NAFLD. There are gaps in the literature on the objective improvement in BMI to meaningfully impact NAFLD in children. Aim. To determine the decrease in BMI associated with a significant decline in ALT and other metabolic parameters. Methods. Retrospective chart review of pediatric patients with the diagnosis of NAFLD. Data were collected at the baseline and 6 and 12 months. A linear regression model was used to assess the percent change in BMI predictive of change in ALT and other metabolic parameters. Results. 281 charts were included. 71% of patients who had up to a 2.5% loss in BMI at 6 months had a decrease in ALT of up to 10 U/L compared to 43% patients who did not have a decrease in BMI up to 2.5% loss at the same time period (P=0.01). The linear regression model showed that 6-month and 12-month percent changes in BMI are predictive of 6-month and 12-month ALT changes (P=0.01 and 0.02), respectively. ALT normalization was achieved on 12% of patients with a ≥2.5% decrease in BMI at 6 months compared to 1% of patients that had no decrease of ≥2.5% decrease in BMI at 6 months (P=0.01). The mean BMI Z-score decline was 0.18 (P=0.001) in the group with a ≥2.5% decrease in BMI at 6 months. Conclusions. BMI loss of up to 2.5% and the mean BMI Z-score 0.18 are associated with a significant decrease in ALT of up to 10 U/L. BMI percent change at 6 months and 12 months is predictive of changes in ALT. These results should help guide providers in clinical practice set objective goals for the management of children with NAFLD resulting from obesity.

Purpose To evaluate the validity of spot urine assay methods in estimating the 24-h urinary sodium, potassium and sodium-to-potassium ratio during three different sodium diets. Materials and methods Twelve healthy volunteers were asked to adhere to 3 dietary sodium targets (3.3–5.0g/day,5.0 g/day) for three consecutive weeks and to measure salt excretion daily in spot urine samples using a self-monitoring device. On day 7 of each week, 24-h urine was collected to compare measured with estimated 24-h salt excretion (by the Kawasaki, Tanaka and INTERSALT equations). Results Correlation coefficients relating measured and estimated 24-h sodium excretion were low and not significant for Kawasaki and INTERSALT and moderate for the Tanaka equation (τ 0.56–0.64,p

Foundation species provide habitat and modify the availability of resources to other species. In nature, multiple foundation species may occur in mixture, but little is known on how their interactions shape the community assembly of associated species. Lichens provide both structural habitat and resources to a variety of associated organisms and thereby serve as foundation species. In this study, we use mat-forming lichens and their associated micro-arthropods as a miniature ecosystem to study potential synergies between foundation species diversity and the abundance and functional diversity of higher trophic levels. We created lichen patches with monocultures and mixtures of up to four species, and extracted Collembola (identified to species level), Oribatida, Mesostigmata, Pseudoscorpiones, and Araneae with Tullgren apparatuses after 106 days of incubation within a natural lichen mat. We found that different lichen species supported different arthropod abundances. For 19 out of a total of 55 lichen mixtures and arthropod groups, we found non-additive, synergistic effects on arthropod abundance, although the specific lichen mixture causing synergistic effects differed with arthropod group. In addition, synergistic effects on arthropod abundance were more common for arthropod groups at lower trophic levels. The functional diversity of lichen mixtures explained patterns in Collembola abundance, but in the opposite direction than hypothesized because synergistic responses were more frequent in functionally similar lichen mixtures. Finally, we found few effects of lichen mixture identity or diversity on the functional diversity of Collembola communities. When applied to large-scale ecosystems, our results suggest that understanding interactions between coexisting foundation species and identifying those species that drive synergistic effects of foundation species on consumer biota, is likely to be of importance to biodiversity conservation and restoration efforts.

Abstract Our basic beliefs about reality can be impossible to prove and yet we can feel a strong intuitive conviction about them, as exemplified by insights that imbue an idea with immediate certainty. Here we presented participants with worldview beliefs such as “people’s core qualities are fixed” and simultaneously elicited an aha moment. In the first experiment (N = 3000, which included a direct replication), participants rated worldview beliefs as truer when they solved anagrams and also experienced aha moments. A second experiment (N = 1564) showed that the worldview statement and the aha moment must be perceived simultaneously for this ‘insight misattribution’ effect to occur. These results demonstrate that artificially induced aha moments can make worldview beliefs seem truer, possibly because humans partially rely on feelings of insight to appraise an idea’s veracity. Feelings of insight are therefore not epiphenomenal and should be investigated for their effects on decisions, beliefs, and delusions.

ABSTRACT: Listeriosis is an infectious disease caused by bacteria of the genus Listeria, the neurological form being more common in ruminants. There are many reports of listeriosis in small ruminants in the region that includes Brazil, Argentina and Uruguay. However, these diagnoses were mainly based on histological lesions in the central nervous system (CNS) without the isolation and characterization of the involved Listeria strains. The aim of this study was to report sheep and goats listeriosis cases from 2016 to 2021 in northwestern Uruguay. The diagnosis was made according to lesions observed at histopathology, plus Listeria isolation in CNS, identifying it at specie and serotype level. Nine animals (n=9) of three outbreaks and five sporadic cases of listeriosis were studied. Sheep was the species with more cases in relation to goats, and adults were the category most affected. Cases occurred in spring and less frequently in winter. All presented neurological clinical signs and the lesions in the CNS were consistent with suppurative meningoencephalitis and micro-abscesses in the brainstem. In eight of nine CNS samples, Listeria strains were isolated (seven L. monocytogenes and one L. innocua). All the L. monocytogenes isolates carried the inlA gene; serotyping showed that four strains belonged to serotype 1/2b, two isolates belonged to serotype 4b, and one to serotype 1/2a. Considering that listeriosis is a common disease in this region and the fact that isolates are scarcely recovered from small ruminants, it would be important to emphasize the need for Listeria isolation to better characterize the strains that affect animals. Not only to improve knowledge about the epidemiology of disease but also with the objective of developing serotype specific vaccines for animal use.

Electronic health records (EHRs) contain valuable data for reuse in science, quality evaluations, and clinical decision support. Because routinely obtained laboratory data are abundantly present, often numeric, generated by certified laboratories, and stored in a structured way, one may assume that they are immediately fit for (re)use in research. However, behind each test result lies an extensive context of choices and considerations, made by both humans and machines, that introduces hidden patterns in the data. If they are unaware, researchers reusing routine laboratory data may eventually draw incorrect conclusions. In this paper, after discussing health care system characteristics on both the macro and micro level, we introduce the reader to hidden aspects of generating structured routine laboratory data in 4 steps (ordering, preanalysis, analysis, and postanalysis) and explain how each of these steps may interfere with the reuse of routine laboratory data. As researchers reusing these data, we underline the importance of domain knowledge of the health care professional, laboratory specialist, data manager, and patient to turn routine laboratory data into meaningful data sets to help obtain relevant insights that create value for clinical care.

Abstract Quantifying lymphocyte vacuolization in peripheral blood smears (PBSs) serves as a measure for disease severity in CLN3 disease—a lysosomal storage disorder of childhood‐onset. However, thus far quantification methods are based on labor‐intensive manual assessment of PBSs. As machine learning techniques like convolutional neural networks (CNNs) have been deployed quite successfully in detecting pathological features in PBSs, we explored whether these techniques could be utilized to automate quantification of lymphocyte vacuolization. Here, we present and validate a deep learning pipeline that automates quantification of lymphocyte vacuolization. By using two CNNs in succession, trained for cytoplasm‐segmentation and vacuolization‐detection, respectively, we obtained an excellent correlation with manual quantification of lymphocyte vacuolization (r = 0.98, n = 40). These results show that CNNs can be utilized to automate the otherwise cumbersome task of manually quantifying lymphocyte vacuolization, thereby aiding prompt clinical decisions in relation to CLN3 disease, and potentially beyond.

Mapping the spatial and temporal dynamics of species distributions is necessary for biodiversity conservation land-use planning decisions. Recent advances in remote sensing and machine learning have allowed for high-resolution species distribution modeling that can inform landscape-level decision-making. Here we compare the performance of three popular Sentinel-2 (10-m) land cover maps, including dynamic world (DW), European land cover (ELC10), and world cover (WC), in predicting wild bee species richness over southern Norway. The proportion of grassland habitat within 250 m (derived from the land cover maps), along with temperature and distance to sandy soils, were used as predictors in both Bayesian regularized neural network and random forest models. Models using grassland habitat from DW performed best (RMSE = 2.8 ± 0.03; average ± standard deviation across models), followed by ELC10 (RMSE = 2.85 ± 0.03) and WC (RMSE = 2.87 ± 0.02). All satellite-derived maps outperformed a manually mapped Norwegian land cover dataset called AR5 (RMSE = 3.02 ± 0.02). When validating the model predictions of bee species richness against citizen science data on solitary bee occurrences using generalized linear models, we found that ELC10 performed best (AIC = 2278 ± 4), followed by WC (AIC = 2367 ± 3), and DW (AIC = 2376 ± 3). While the differences in RMSE we observed between models were small, they may be significant when such models are used to prioritize grassland patches within a landscape for conservation subsidies or management policies. Partial dependencies in our models showed that increasing the proportion of grassland habitat is positively associated with wild bee species richness, thereby justifying bee conservation schemes that aim to enhance semi-natural grassland habitat. Our results confirm the utility of satellite-derived land cover maps in supporting high-resolution species distribution modeling and suggest there is scope to monitor changes in species distributions over time given the dense time series provided by products such as DW.

The coronavirus disease 2019 (COVID-19) pandemic mandated rapid, flexible solutions to meet the anticipated surge in both patient acuity and volume. This paper describes one institution’s emergency department (ED) innovation at the center of the COVID-19 crisis, including the creation of a temporary ED–intensive care unit (ICU) and development of interdisciplinary COVID-19–specific care delivery models to care for critically ill patients. Mount Sinai Hospital, an urban quaternary academic medical center, had an existing five-bed resuscitation area insufficiently rescue due to its size and lack of negative pressure rooms. Within 1 week, the ED-based observation unit, which has four negative pressure rooms, was quickly converted into a COVID-19–specific unit, split between a 14-bed stepdown unit and a 13-bed ED-ICU unit. An increase in staffing for physicians, physician assistants, nurses, respiratory therapists, and medical technicians, as well as training in critical care protocols and procedures, was needed to ensure appropriate patient care. The transition of the ED to a COVID-19–specific unit with the inclusion of a temporary expanded ED-ICU at the beginning of the COVID-19 pandemic was a proactive solution to the growing challenges of surging patients, complexity, and extended boarding of critically ill patients in the ED. This pandemic underscores the importance of ED design innovation with flexible spacing, interdisciplinary collaborations on structure and services, and NP ventilation systems which will remain important moving forward.

ObjectiveSummarize evidence for use of advanced MRI techniques as monitoring biomarkers in the clinic, and highlight the latest bench-to-bedside developments.MethodsExperts in advanced MRI techniques applied to high-grade glioma treatment response assessment convened through a European framework. Current evidence regarding the potential for monitoring biomarkers in adult high-grade glioma is reviewed, and individual modalities of perfusion, permeability, and microstructure imaging are discussed (in Part 1 of two). In Part 2, we discuss modalities related to metabolism and/or chemical composition, appraise the clinic readiness of the individual modalities, and consider post-processing methodologies involving the combination of MRI approaches (multiparametric imaging) or machine learning (radiomics).ResultsHigh-grade glioma vasculature exhibits increased perfusion, blood volume, and permeability compared with normal brain tissue. Measures of cerebral blood volume derived from dynamic susceptibility contrast-enhanced MRI have consistently provided information about brain tumor growth and response to treatment; it is the most clinically validated advanced technique. Clinical studies have proven the potential of dynamic contrast-enhanced MRI for distinguishing post-treatment related effects from recurrence, but the optimal acquisition protocol, mode of analysis, parameter of highest diagnostic value, and optimal cut-off points remain to be established. Arterial spin labeling techniques do not require the injection of a contrast agent, and repeated measurements of cerebral blood flow can be performed. The absence of potential gadolinium deposition effects allows widespread use in pediatric patients and those with impaired renal function. More data are necessary to establish clinical validity as monitoring biomarkers. Diffusion-weighted imaging, apparent diffusion coefficient analysis, diffusion tensor or kurtosis imaging, intravoxel incoherent motion, and other microstructural modeling approaches also allow treatment response assessment; more robust data are required to validate these alone or when applied to post-processing methodologies.ConclusionConsiderable progress has been made in the development of these monitoring biomarkers. Many techniques are in their infancy, whereas others have generated a larger body of evidence for clinical application.

ObjectiveTo summarize evidence for use of advanced MRI techniques as monitoring biomarkers in the clinic, and to highlight the latest bench-to-bedside developments.MethodsThe current evidence regarding the potential for monitoring biomarkers was reviewed and individual modalities of metabolism and/or chemical composition imaging discussed. Perfusion, permeability, and microstructure imaging were similarly analyzed in Part 1 of this two-part review article and are valuable reading as background to this article. We appraise the clinic readiness of all the individual modalities and consider methodologies involving machine learning (radiomics) and the combination of MRI approaches (multiparametric imaging).ResultsThe biochemical composition of high-grade gliomas is markedly different from healthy brain tissue. Magnetic resonance spectroscopy allows the simultaneous acquisition of an array of metabolic alterations, with choline-based ratios appearing to be consistently discriminatory in treatment response assessment, although challenges remain despite this being a mature technique. Promising directions relate to ultra-high field strengths, 2-hydroxyglutarate analysis, and the use of non-proton nuclei. Labile protons on endogenous proteins can be selectively targeted with chemical exchange saturation transfer to give high resolution images. The body of evidence for clinical application of amide proton transfer imaging has been building for a decade, but more evidence is required to confirm chemical exchange saturation transfer use as a monitoring biomarker. Multiparametric methodologies, including the incorporation of nuclear medicine techniques, combine probes measuring different tumor properties. Although potentially synergistic, the limitations of each individual modality also can be compounded, particularly in the absence of standardization. Machine learning requires large datasets with high-quality annotation; there is currently low-level evidence for monitoring biomarker clinical application.ConclusionAdvanced MRI techniques show huge promise in treatment response assessment. The clinical readiness analysis highlights that most monitoring biomarkers require standardized international consensus guidelines, with more facilitation regarding technique implementation and reporting in the clinic.

Voluntary movements include a predictive control of the sensory-motor consequences of executed or observed actions. The motor system predicts further steps of actions relying on its pure observation. This study seeks to disclose the interference of an implicit motor prediction effect during actions reconstruction. Videos of human actions directed to objects were presented to volunteers. Subsequently, they combined four static frames of those videos randomly arranged on the screen. Such combination could be chronological (from the beginning to the end of the action) or reverse (from the end to the beginning of the action). The observed actions were also biological (human movement) or non-biological (movement of objects). The grasping began with the actor's hand in a resting position over a table (Experiment I), or with his hand in contact with the object (Experiment II). In the first experiment, participants presented lower accuracy in the biological condition rearranging in chronological order. In the second experiment, however, the accuracy was lower in reverse order. The interpretation of such results is that the implicit predictive mechanisms interfered in the rearrangement of the frames. As an example: the expected movement after a grasping action whose outcome is capping a bottle would be the withdrawal of the hand. Therefore, combining frames of a recent seen action, volunteers present less accuracy if the first frame to be placed is counterintuitive.

Early recognition of sepsis is essential for improving outcomes and preventing complications such as organ failure, depression, and neurocognitive impairment. The emergency department (ED) plays a key role in the early identification of sepsis, but clinicians lack diagnostic tools. Potentially, biomarkers could be helpful in assisting clinicians in the ED, but no marker has yet been successfully implemented in daily practice with good clinical performance. Pancreatic stone protein (PSP) is a promising biomarker in the context of sepsis, but little is known about the diagnostic performance of PSP in the ED. We prospectively investigated the diagnostic value of PSP in such a population for patients suspected of infection. PSP was compared with currently used biomarkers, including white blood cell count (WBC) and C-reactive protein (CRP). Of the 156 patients included in this study, 74 (47.4%) were diagnosed with uncomplicated infection and 26 (16.7%) patients with sepsis, while 56 (35.9%) eventually had no infection. PSP was significantly higher for sepsis patients compared to patients with no sepsis. In multivariate regression, PSP was a significant predictor for sepsis, with an area under the curve (AUC) of 0.69. Positive and negative predictive values for this model were 100% and 84.4%, respectively. Altogether, these findings show that PSP, measured at the ED of a tertiary hospital, is associated with sepsis but lacks the diagnostic performance to be used as single marker.

The energy efficiency and flight endurance of small unmanned aerial vehicles (SUAVs) can be improved through the implementation of autonomous soaring strategies. Biologically inspired flight techniques such as dynamic and thermal soaring offer significant energy savings through the exploitation of naturally occurring wind phenomena for thrustless flight. Recent interest in the application of artificial intelligence algorithms for autonomous soaring has been motivated by the pursuit of instilling generalized behavior in control systems, centered around the use of neural networks. However, the topology of such networks is usually predetermined, restricting the search space of potential solutions, while often resulting in complex neural networks that can pose implementation challenges for the limited hardware onboard small-scale autonomous vehicles. In exploring a novel method of generating neurocontrollers, this paper presents a neural network-based soaring strategy to extend flight times and advance the potential operational capability of SUAVs. In this study, the Neuroevolution of Augmenting Topologies (NEAT) algorithm is used to train efficient and effective neurocontrollers that can control a simulated aircraft along sustained dynamic and thermal soaring trajectories. The proposed approach evolves interpretable neural networks in a way that preserves simplicity while maximizing performance without requiring extensive training datasets. As a result, the combined trajectory planning and aircraft control strategy is suitable for real-time implementation on SUAV platforms.

Next to their essential roles in plant growth and development, phytohormones play a central role in plant immunity against pathogens. In this study we studied the previously reported antagonism between the plant-pathogenic oomycete Pythium arrhenomanes and the root-knot nematode Meloidogyne graminicola, two root pathogens that co-occur in aerobic rice fields. In this manuscript, we investigated if the antagonism is related to imbalances in plant hormone levels, which could be involved in activation of plant defense. Hormone measurements and gene expression analyses showed that the jasmonate (JA) pathway is induced early upon P. arrhenomanes infection. Exogenous application of methyl-jasmonate (MeJA) on the plant confirmed that JA is needed for basal defense against both P. arrhenomanes and M. graminicola in rice. Whereas M. graminicola suppresses root JA levels to increase host susceptibility, Pythium inoculation boosts JA in a manner that prohibits JA repression by the nematode in double-inoculated plants. Exogenous MeJA supply phenocopied the defense-inducing capacity of Pythium against the root-knot nematode, whereas the antagonism was weakened in JA-insensitive mutants. Transcriptome analysis confirmed upregulation of JA biosynthesis and signaling genes upon P. arrhenomanes infection, and additionally revealed induction of genes involved in biosynthesis of diterpenoid phytoalexins, consistent with strong activation of the gene encoding the JA-inducible transcriptional regulator DITERPENOID PHYTOALEXIN FACTOR. Altogether, the here-reported data indicate an important role for JA-induced defense mechanisms in this antagonistic interaction. Next to that, our results provide evidence for induced expression of genes encoding ERF83, and related PR proteins, as well as auxin depletion in P. arrhenomanes infected rice roots, which potentially further contribute to the reduced nematode susceptibility seen in double-infected plants.

The Arctic is warming twice as fast as the rest of the planet, leading to rapid changes in species composition and plant functional trait variation. Landscape-level maps of vegetation composition and trait distributions are required to expand spatially-limited plot studies, overcome sampling biases associated with the most accessible research areas, and create baselines from which to monitor environmental change. Unmanned aerial vehicles (UAVs) have emerged as a low-cost method to generate high-resolution imagery and bridge the gap between fine-scale field studies and lower resolution satellite analyses. Here we used field spectroscopy data (400–2500 nm) and UAV multispectral imagery to test spectral methods of species identification and plant water and chemistry retrieval near Longyearbyen, Svalbard. Using the field spectroscopy data and Random Forest analysis, we were able to distinguish eight common High Arctic plant tundra species with 74% accuracy. Using partial least squares regression (PLSR), we were able to predict corresponding water, nitrogen, phosphorus and C:N values ( r ^2 = 0.61–0.88, RMSEmean = 12%–64%). We developed analogous models using UAV imagery (five bands: Blue, Green, Red, Red Edge and Near-Infrared) and scaled up the results across a 450 m long nutrient gradient located underneath a seabird colony. At the UAV level, we were able to map three plant functional groups (mosses, graminoids and dwarf shrubs) at 72% accuracy and generate maps of plant chemistry. Our maps show a clear marine-derived fertility gradient, mediated by geomorphology. We used the UAV results to explore two methods of upscaling plant water content to the wider landscape using Sentinel-2A imagery. Our results are pertinent for high resolution, low-cost mapping of the Arctic.

Earthquake environmental effects (EEEs) were compiled for the earthquakes of 1626, 1759, 1819, and 1904 in the Fennoscandian Peninsula, northern Europe. The principal source of information was the contemporary newspaper press. Macroseismic questionnaires collected in 1759 and 1904 were also consulted. We prepared maps showing newly discovered EEEs together with previously known EEEs and analyzed their spatial distribution. We assigned intensities based on the 2007 Environmental Seismic Intensity (ESI) scale to 27 selected localities and compared them to intensities assigned based on the 1998 European Macroseismic Scale. While the overall agreement between the scales is good, intensities may remain uncertain due to the sparsity of written documentation. The collected data sets are most probably incomplete but still show that EEEs are not unprecedented cases in the target region. The findings include landslides and rockfalls as well as cascade effects with a risk potential and widespread water movements up to long distances. The winter earthquake of 1759 cracked ice over a large area. This investigation demonstrates that the ESI scale also has practical importance for regions with infrequent EEEs.

Arguably, it is not possible to study insight moments during problem solving without being able to accurately detect when they occur (Bowden and Jung-Beeman, 2007). Despite over a century of research on the insight moment, there is surprisingly little consensus on the best way to measure them in real-time experiments. There have also been no attempts to evaluate whether the different ways of measuring insight converge. Indeed, if it turns out that the popular measures of insight diverge, then this may indicate that researchers who have used one method may have been measuring a different phenomenon to those who have used another method. We compare the strengths and weaknesses of the two most commonly cited ways of measuring insight: The feelings-of-warmth measure adapted from Metcalfe and Wiebe (1987), and the self-report measure adapted from Bowden and Jung-Beeman (2007). We find little empirical agreement between the two measures, and conclude that the self-report measure of Aha! is superior both methodologically and theoretically, and provides a better representation of what is commonly regarded as insight. We go on to describe and recommend a novel visceral measure of insight using a dynamometer as described in Creswell et al. (2016).

Without clinical guideline on the optimal timing for primary total hip replacement (THR), patients often receive the operation with delay. Delaying THR may negatively affect long-term health-related quality of life, but its economic effects are unclear. We evaluated the costs and health benefits of timely primary THR for functionally independent adult patients with end-stage osteoarthritis (OA) compared to non-surgical therapy followed by THR after progression to functional dependence (delayed THR), and non-surgical therapy alone (Medical Therapy), from a German Social Health Insurance (SHI) perspective. Data from hip arthroplasty registers and a systematic review of the published literature were used to populate a tunnel-state modified Markov lifetime model of OA treatment in Germany. A 5% annual discount rate was applied to costs (2013 prices) and health outcomes (Quality Adjusted Life Years, QALY). The expected future average cost of timely THR, delayed THR and medical therapy in women at age 55 were €27,474, €27,083 and €28,263, and QALYs were 20.7, 16.7, and 10.3, respectively. QALY differences were entirely due to health-related quality of life differences. The discounted cost per QALY gained by timely over delayed (median delay of 11 years) THR was €1270 and €1338 in women treated at age 55 and age 65, respectively, and slightly higher than this for men. Timely THR is cost-effective, generating large quality of life benefits for patients at low additional cost to the SHI. With declining healthcare budgets, research is needed to identify the characteristics of those able to benefit the most from timely THR.

El propósito de este trabajo es el de describir el proceso de desarrollo de una forma de organización de la producción que, teniendo como núcleo al obraje maderero-yerbatero y al aserradero-fábrica de tanino, tuvo lugar durante las últimas décadas del siglo XIX y la primera mitad del siglo XX en el nordeste Argentino. La denominación de enclave que le adjudicamos a estos núcleos de actividad posee un significado espacial y socio-económico ya que se caracterizaron por establecer una suerte de aislamiento físico o clausura espacial. Estos enclaves se explayaron espacialmente en un área recientemente apropiada a las comunidades indígenas configurando un dominio territorial al cual le fueron otorgando cierta configuración que fue cambiando al alterarse las condiciones en que se desenvolvía la forma de organización de la producción que le dio origen.

Este artigo apresenta o desenvolvimento de um modelo de predição de séries temporais financeiras com o uso da Rede Neural Artificial TLFN Distribuída (Time Lagged FeedForward Network - Rede Neural Alimentada para frente Atrasada no Tempo), treinada com o algoritmo backpropagation temporal e com o pré-processamento dos sinais de entrada realizado com as Transformadas Wavelets Discretas. A metodologia demonstra como a análise de multirresolução feita com o algoritmo piramidal de Mallat colaborou para o aumento da capacidade de generalização da rede neural, otimizando as previsões feitas pelo modelo implementado. Com a finalidade de demonstrar a eficácia desta metodologia, foi realizado um estudo de caso envolvendo a séries histórica de cotações das cotas, negociadas no mercado secundário, do Fundo de Investimento Imobiliário Almirante Barroso.

This investigation focuses on two historical earthquakes that occurred in the border region between Finland and Russian North in December 1758. They were close together in time and their magnitudes are among the largest observed in the region. We thoroughly searched for contemporary Russian and Scandinavian documentation on earthquake activity in several libraries in Moscow, Helsinki, Stockholm and Copenhagen. We found two primary reports, one from the Russian North and the other from Finland. The context and content of the reports indicate that they are independent and related to the dates of December 17 and December 31, 1758. The first occurrence was reportedly observed in Kandalaksha, Knyazhnaya Guba, Kovda, Chernaya reka and krest Vzista, and the second in Inari, Utsjoki, and Karasjok. We compiled macroseismic maps for both earthquakes and sets of possible parametric solutions that fit the sparse information available. We identified two types of uncertainty in epicenter and magnitude determination: one that stems from the ambiguity of intensity assessment at localities and the other from the spatial distribution of the data points. If no single solution is the best, we propose that all possible solutions be included in earthquake catalogs.

El gastrópodo Nodilittorina peruviana es un habitante común de la zona intermareal rocosa de la costa norte y centro de Chile. Las poblaciones de esta especie se caracterizan por presentar distribuciones agregadas. Por medio de mediciones de terreno y ensayos de laboratorio se evaluó la influencia de la agregación sobre las habilidades de termorregulación y conservación de agua, en individuos pertenecientes a dos localidades de la costa de Chile que presentan distintos regímenes termales (Taltal 25º 25' S; 70º 29' W y Las Cruces 33º 35' S; 71º 38' W). Los resultados indican que la influencia de la agregación sobre las habilidades termorregulatorias es dependiente de las condiciones locales. A pesar de que los individuos de ambas localidades presentaron puntos de tolerancia térmica similares, los caracoles de Taltal mostraron tasas de pérdidas de agua menores. El tamaño de las agregaciones se relacionó en forma negativa con la tasa de pérdida de agua de los individuos de ambas localidades. En el caso de Taltal se observó un límite de tolerancia menor que en Las Cruces y una relación positiva entre tamaño de la agregación y temperatura grupal. Los resultados demuestran que las condiciones ambientales locales puede ser determinante para la efectividad de los mecanismos de termorregulación.The gastropod Nodilittorina peruviana inhabit rocky intertidal of the north and center Chile. Populations of this species exhibits aggregated distributions. Through field and lab records we studied the effect of spatial distribution of snails on their thermoregulatory and water conservation efficiencies. We studied individuals from two localities of the Chilean coast with different climatic conditions (Taltal 25° 25 ` S; 70° 29 ` W and Las Cruces 33° 35 ` S; 71° 38 ` W). Results indicate that the influence of spatial distribution thermoregulatory efficiency is dependent of the local conditions. Although individuals from both localities presented similar thermal tolerances, snails from Taltal showed lower rates of water loss. Aggregations size were negatively related with the rate of water loss in individuals from both localities. Only, individuals from Taltal decreased their limit of thermal tolerance, and exhibited a positive relationship between aggregation size and the temperature of the group. Results demonstrated that the local environmental conditions are determinate thermoregulatory strategies.

Despite funding constraints for treatment programmes in Africa, the costs and economic consequences of routine laboratory monitoring for efficacy and toxicity of antiretroviral therapy (ART) have rarely been evaluated.Cost-effectiveness analysis was conducted in the DART trial (ISRCTN13968779). Adults in Uganda/Zimbabwe starting ART were randomised to clinically-driven monitoring (CDM) or laboratory and clinical monitoring (LCM); individual patient data on healthcare resource utilisation and outcomes were valued with primary economic costs and utilities. Total costs of first/second-line ART, routine 12-weekly CD4 and biochemistry/haematology tests, additional diagnostic investigations, clinic visits, concomitant medications and hospitalisations were considered from the public healthcare sector perspective. A Markov model was used to extrapolate costs and benefits 20 years beyond the trial.3316 (1660LCM;1656CDM) symptomatic, immunosuppressed ART-naive adults (median (IQR) age 37 (32,42); CD4 86 (31,139) cells/mm(3)) were followed for median 4.9 years. LCM had a mean 0.112 year (41 days) survival benefit at an additional mean cost of $765 [95%CI:685,845], translating into an adjusted incremental cost of $7386 [3277,dominated] per life-year gained and $7793 [4442,39179] per quality-adjusted life year gained. Routine toxicity tests were prominent cost-drivers and had no benefit. With 12-weekly CD4 monitoring from year 2 on ART, low-cost second-line ART, but without toxicity monitoring, CD4 test costs need to fall below $3.78 to become cost-effective (

This study discusses the scope of historical earthquake analysis in low-seismicity regions. Examples of non-damaging earthquake reports are given from the Eastern Baltic (Fennoscandian) Shield in north-eastern Europe from the 16th to the 19th centuries. The information available for past earthquakes in the region is typically sparse and cannot be increased through a careful search of the archives. This study applies recommended rigorous methodologies of historical seismology developed using ample data to these sparse reports from the Eastern Baltic Shield. Attention is paid to the context of the reporting, the identity and role of the authors, the circumstances of the reporting, and the opportunity to verify the available information by collating the sources. We evaluate the reliability of oral earthquake recollections and develop criteria for cases when a historical earthquake is attested to by a single source. We propose parametric earthquake scenarios as a way to deal with sparse macroseismic reports and as an improvement to existing databases.

The spliceosome, a sophisticated molecular machine involved in the removal of intervening sequences from the coding sections of eukaryotic genes, appeared and subsequently evolved rapidly during the early stages of eukaryotic evolution. The last eukaryotic common ancestor (LECA) had both complex spliceosomal machinery and some spliceosomal introns, yet little is known about the early stages of evolution of the spliceosomal apparatus. The Sm/Lsm family of proteins has been suggested as one of the earliest components of the emerging spliceosome and hence provides a first in-depth glimpse into the evolving spliceosomal apparatus. An analysis of 335 Sm and Sm-like genes from 80 species across all three kingdoms of life reveals two significant observations. First, the eukaryotic Sm/Lsm family underwent two rapid waves of duplication with subsequent divergence resulting in 14 distinct genes. Each wave resulted in a more sophisticated spliceosome, reflecting a possible jump in the complexity of the evolving eukaryotic cell. Second, an unusually high degree of conservation in intron positions is observed within individual orthologous Sm/Lsm genes and between some of the Sm/Lsm paralogs. This suggests that functional spliceosomal introns existed before the emergence of the complete Sm/Lsm family of proteins; hence, spliceosomal machinery with considerably fewer components than today's spliceosome was already functional.

Teachers all over the world are now facing the challenges of the 21st century education as they face the 21st century learners. To cope up with the demands of the 21st century education, teachers, most especially teachers in the Colleges of Education, need to possess the 21st century characteristics. This study was conducted to assess the extent of the acquisition of the different 21st century characteristics of an educator among the faculty members of the College of Education of Bulacan State University and eventually proposed an enhancement program for the teachers. The respondents of the study were the thirty-one faculty members with teaching load during the short term classes of academic year 2015-2016. Questionnaire was the principal instrument used in this study to measure extent of acquisition of the 21st century characteristics of an educator. Quantitative method of research was employed and frequency, percentage and weighted mean were the statistics used in the study. The result of the study indicates that the respondents acquired the different 21st century characteristics of an educator to the large extent. In the light of the foregoing results, conclusions and recommendations were suggested: the school as envisioned being a recognized leader of excellence in instruction the suggested enhancement/intervention program for the faculty members may be adapted to address the needs of the 21st century education; as the teachers continue to develop their potentials and skills in line with the needs of the 21st century education the school administrators also need to update themselves; and full supports from the administrators are needed most especially in the development and construction of different needed 21st century education laboratories.