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In the tropics generally, natural vegetation is being destroyed rapidly and often replaced with export crops such as oil palm and soybeans. To mitigate the effects of the Sixth Mass Extinction event that we have caused and are experiencing now, the following will be necessary a stable (and almost certainly lower) human population, sustainable levels of consumption, and social justice that empowers the less wealthy people and nations of the world, where the vast majority of us live, will be necessary.We have been field observers of tropical insects on four continents and, since 1978, intense observers of caterpillars, their parasites, and their associates in the 1,260 km2 of dry, cloud, and rain forests of Área de Conservación Guanacaste (ACG) in northwestern Costa Rica. ACG's natural ecosystem restoration began with its national park designation in 1971. check details As human biomonitors, or "insectometers," we see that ACG's insect species richness and density have gradually declined since the late 1970s, and more intensely since about 2005. The overarching perturbation is climate change. It has caused increasing ambient temperatures for all ecosystems; more erratic seasonal cues; reduced, erratic, and asynchronous rainfall; heated air masses sliding up the volcanoes and burning off the cloud forest; and dwindling biodiversity in all ACG terrestrial ecosystems. What then is the next step as climate change descends on ACG's many small-scale successes in sustainable biodevelopment? Be kind to the survivors by stimulating and facilitating their owner societies to value them as legitimate members of a green sustainable nation. Encourage national bioliteracy, BioAlfa.Most animal species on Earth are insects, and recent reports suggest that their abundance is in drastic decline. Although these reports come from a wide range of insect taxa and regions, the evidence to assess the extent of the phenomenon is sparse. Insect populations are challenging to study, and most monitoring methods are labor intensive and inefficient. Advances in computer vision and deep learning provide potential new solutions to this global challenge. Cameras and other sensors can effectively, continuously, and noninvasively perform entomological observations throughout diurnal and seasonal cycles. The physical appearance of specimens can also be captured by automated imaging in the laboratory. When trained on these data, deep learning models can provide estimates of insect abundance, biomass, and diversity. Further, deep learning models can quantify variation in phenotypic traits, behavior, and interactions. Here, we connect recent developments in deep learning and computer vision to the urgent demand for more cost-efficient monitoring of insects and other invertebrates. We present examples of sensor-based monitoring of insects. We show how deep learning tools can be applied to exceptionally large datasets to derive ecological information and discuss the challenges that lie ahead for the implementation of such solutions in entomology. We identify four focal areas, which will facilitate this transformation 1) validation of image-based taxonomic identification; 2) generation of sufficient training data; 3) development of public, curated reference databases; and 4) solutions to integrate deep learning and molecular tools.Insects have diversified through more than 450 million y of Earth's changeable climate, yet rapidly shifting patterns of temperature and precipitation now pose novel challenges as they combine with decades of other anthropogenic stressors including the conversion and degradation of land. Here, we consider how insects are responding to recent climate change while summarizing the literature on long-term monitoring of insect populations in the context of climatic fluctuations. Results to date suggest that climate change impacts on insects have the potential to be considerable, even when compared with changes in land use. The importance of climate is illustrated with a case study from the butterflies of Northern California, where we find that population declines have been severe in high-elevation areas removed from the most immediate effects of habitat loss. These results shed light on the complexity of montane-adapted insects responding to changing abiotic conditions. We also consider methodological issues that would improve syntheses of results across long-term insect datasets and highlight directions for future empirical work.

Patient acceptance of implantable cardioverter defibrillators (ICDs) is one of the factors influencing clinical outcomes. This study aimed to develop a Japanese version of the Florida Patient Acceptance Survey (FPAS; a measure of acceptance of ICDs), examine its reliability and validity, and test instrument reliability and ability to generate valid data in a new population.

122 outpatients with ICD, cardiac resynchronization therapy defibrillator (CRTD) completed the FPAS, the 12-Item Short-Form Health Survey developed for the Medical Outcomes Study, and the Hospital Anxiety and Depression Scale.

Confirmatory and exploratory factor data analyses yielded a three-factor model with nine items. This version of the FPAS had high internal consistency, both for the single factor scale and all other subscales; Cronbach's

Resident assessments are analyzed by multidimensional scaling.

We analyzed observer-based real care and support time in four facilities with 209 residents during two working days; resident, organizational data and pairs of residents were assessed by registered and assistant nurses regarding the dissimilarity of resident pairs. Registered- and assistant nurses dissimilarity assessments are compared to criteriabased nursing management assessment.

The fits of management criteria matrices as external restrictions are higher in registered nurses' than in assistant nurses' assessments. These differences disappear with low staffing.

The influence of qualification levels on assessment is affected by staffing. Low complexity of Assistant Nurses assessments is connected to higher nursing care and support time in groups of demanding residents.

The influence of qualification levels on assessment is affected by staffing. Low complexity of Assistant Nurses assessments is connected to higher nursing care and support time in groups of demanding residents.

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