A review of techniques for spatial modeling in geographical, conservation and landscape genetics

Most evolutionary processes occur in a spatial context and several spatial analysis techniques have been employed in an exploratory context. However, the existence of autocorrelation can also perturb significance tests when data is analyzed using standard correlation and regression techniques on modeling genetic data as a function of explanatory variables. In this case, more complex models incorporating the effects of autocorrelation must be used. Here we review those models and compared their relative performances in a simple simulation, in which spatial patterns in allele frequencies were generated by a balance between random variation within populations and spatially-structured gene flow. Notwithstanding the somewhat idiosyncratic behavior of the techniques evaluated, it is clear that spatial autocorrelation affects Type I errors and that standard linear regression does not provide minimum variance estimators. Due to its flexibility, we stress that principal coordinate of neighbor matrices (PCNM) and related eigenvector mapping techniques seem to be the best approaches to spatial regression. In general, we hope that our review of commonly used spatial regression techniques in biology and ecology may aid population geneticists towards providing better explanations for population structures dealing with more complex regression problems throughout geographic space

Artificial Intelligence Algorithms to Diagnose Glaucoma and Detect Glaucoma Progression: Translation to Clinical Practice

Purpose: This concise review aims to explore the potential for the clinical implementation of artificial intelligence (AI) strategies for detecting glaucoma and monitoring glaucoma progression. / Methods: Nonsystematic literature review using the search combinations "Artificial Intelligence," "Deep Learning," "Machine Learning," "Neural Networks," "Bayesian Networks," "Glaucoma Diagnosis," and "Glaucoma Progression." Information on sensitivity and specificity regarding glaucoma diagnosis and progression analysis as well as methodological details were extracted. / Results: Numerous AI strategies provide promising levels of specificity and sensitivity for structural (e.g. optical coherence tomography [OCT] imaging, fundus photography) and functional (visual field [VF] testing) test modalities used for the detection of glaucoma. Area under receiver operating curve (AROC) values of > 0.90 were achieved with every modality. Combining structural and functional inputs has been shown to even more improve the diagnostic ability. Regarding glaucoma progression, AI strategies can detect progression earlier than conventional methods or potentially from one single VF test. / Conclusions: AI algorithms applied to fundus photographs for screening purposes may provide good results using a simple and widely accessible test. However, for patients who are likely to have glaucoma more sophisticated methods should be used including data from OCT and perimetry. Outputs may serve as an adjunct to assist clinical decision making, whereas also enhancing the efficiency, productivity, and quality of the delivery of glaucoma care. Patients with diagnosed glaucoma may benefit from future algorithms to evaluate their risk of progression. Challenges are yet to be overcome, including the external validity of AI strategies, a move from a "black box" toward "explainable AI," and likely regulatory hurdles. However, it is clear that AI can enhance the role of specialist clinicians and will inevitably shape the future of the delivery of glaucoma care to the next generation. / Translational Relevance: The promising levels of diagnostic accuracy reported by AI strategies across the modalities used in clinical practice for glaucoma detection can pave the way for the development of reliable models appropriate for their translation into clinical practice. Future incorporation of AI into healthcare models may help address the current limitations of access and timely management of patients with glaucoma across the world

Urinary incontinence related to perineal muscle strength in the first trimester of pregnancy: cross-sectional study

Objective To analyze pelvic floor muscle strength (PFMS), urinary continence and quality of life related to urinary incontinence (UI) of women in the first trimester of pregnancy. Method Cross-sectional study with a sample of 500 women who started prenatal care in a complementary healthcare facility in Guarulhos, state of São Paulo, from 2012 and 2013. Pelvic floor muscle strength was evaluated through perineometry. The pregnant women who presented UI answered the International Consultation on Incontinence Questionnaire-Short Form (ICIQ-SF). Results It was found that maternal age (OR=1.06; CI95% 1.02-1.11) and prior UI (OR=15.12; 95%CI 8.19-27.92) are the variables that, in tandem, best explain the occurrence of UI at the beginning of pregnancy. The mean score on the ICIQ-SF was 8.2 (SD=3.9), considered a moderate impact on quality of life. Conclusion Older pregnant women with prior UI are more likely to have UI in the first trimester of pregnancy.
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Performance and Consistency of Indicator Groups in Two Biodiversity Hotspots

In a world limited by data availability and limited funds for conservation, scientists and practitioners must use indicator groups to define spatial conservation priorities. Several studies have evaluated the effectiveness of indicator groups, but still little is known about the consistency in performance of these groups in different regions, which would allow their a priori selection.We systematically examined the effectiveness and the consistency of nine indicator groups in representing mammal species in two top-ranked Biodiversity Hotspots (BH): the Brazilian Cerrado and the Atlantic Forest. To test for group effectiveness we first found the best sets of sites able to maximize the representation of each indicator group in the BH and then calculated the average representation of different target species by the indicator groups in the BH. We considered consistent indicator groups whose representation of target species was not statistically different between BH. We called effective those groups that outperformed the target-species representation achieved by random sets of species. Effective indicator groups required the selection of less than 2% of the BH area for representing target species. Restricted-range species were the most effective indicators for the representation of all mammal diversity as well as target species. It was also the only group with high consistency.We show that several indicator groups could be applied as shortcuts for representing mammal species in the Cerrado and the Atlantic Forest to develop conservation plans, however, only restricted-range species consistently held as the most effective indicator group for such a task. This group is of particular importance in conservation planning as it captures high diversity of endemic and endangered species

Reliability analysis of moment redistribution in reinforced concrete beams

Design codes allow a limited amount of moment redistribution in continuous reinforced concrete beams and often make use of lower bound values in the procedure for estimating the moment redistribution factors. Here, based on the concept of demand and capacity rotation, and by means of Monte Carlo simulation, a probabilistic model is derived for the evaluation of moment redistribution factors. Results show that in all considered cases, the evaluated mean and nominal values of moment redistribution factor are greater than the values provided by the ACI code. On the other hand, the 5th percentile value of moment redistribution factor could be lower than those specified by the code. Although the reduction of strength limit state reliability index attributable to uncertainty in moment redistribution factors is not large, it is comparable to the reduction in reliability index resulting from increasing the ratio of live to dead load

Análise integrada de sistemas de produção de tomateiro com base em indicadores edafobiológicos.

A análise integrada de indicadores edafobiológicos ligados ao manejo do solo constitui uma ferramenta importante para estimar níveis de sustentabilidade do agroecossistema, detectando-se pontos críticos para a devida correção de manejo. Essa ferramenta foi empregada na avaliação de sistemas de produção orgânica e convencional de tomate, em cultivo protegido e a campo aberto, no estado de São Paulo. Tomaram-se como referência solos de mata nativa e/ou pastagem natural, dependendo do local de estudo. Em Serra Negra, o solo sob sistema orgânico apresentou maior capacidade de campo e teor de argila dispersa mais baixo, indicativos da estabilidade dos agregados. No sistema convencional observou-se uma elevada condutividade elétrica, evidenciando a alta disponibilidade de sais solúveis. A análise de componentes principais (ACP) permitiu concluir que há maior grau de similaridade entre o solo sob sistema orgânico e aqueles das bases referenciais, com respeito aos indicadores químicos e biológicos. Constatou-se que C org, N total, polissacarídeos, FDA (hidrólise de diacetato de fluoresceína) e atividade enzimática de desidrogenase estão positivamente relacionados com o sistema orgânico, a mata nativa e a pastagem. Em contrapartida, a saturação por bases (V%), pH, teores de Mn, Mg e Ca, bem como a razão de dispersão estão inversamente relacionadas ao manejo orgânico. Já em Araraquara, os resultados da ACP distinguiram as áreas organicamente cultivadas das matas nativas, principalmente, com base nos indicadores biológicos

Tortricid Moths Reared from the Invasive Weed Mexican Palo Verde, Parkinsonia aculeata, with Comments on their Host Specificity, Biology, Geographic Distribution, and Systematics

As part of efforts to identify native herbivores of Mexican palo verde, Parkinsonia aculeata L. (Leguminosae: Caesalpinioideae), as potential biological control agents against this invasive weed in Australia, ten species of Tortricidae (Lepidoptera) were reared from Guatemala, Mexico, Nicaragua, and Venezuela: Amorbia concavana (Zeller), Platynota rostrana (Walker), Platynota helianthes (Meyrick), Platynota stultana Walsingham (all Tortricinae: Sparganothini), Rudenia leguminana (Busck), Cochylis sp. (both Tortricinae: Cochylini), Ofatulena duodecemstriata (Walsingham), O. luminosa Heinrich, Ofatulena sp. (all Olethreutinae: Grapholitini), and Crocidosema lantana Busck (Olethreutinae: Eucosmini). Significant geographic range extensions are provided for O. duodecemstriata and R. leguminana. These are the first documented records of P. aculeata as a host plant for all but O. luminosa. The four species of Sparganothini are polyphagous; in contrast, the two Cochylini and three Grapholitini likely are specialists on Leguminosae. Ofatulena luminosa is possibly host specific on P. aculeata. Host trials with Rudenia leguminana also provide some evidence of specificity, in contrast to historical rearing records. To examine the possibility that R. leguminana is a complex of species, two data sets of molecular markers were examined: (1) a combined data set of two mitochondrial markers (a 781-basepair region of cytochrome c oxidase I (COI) and a 685-basepair region of cytochrome c oxidase II) and one nuclear marker (a 531-basepair region of the 28S domain 2); and (2) the 650-basepair “barcode” region of COI. Analyses of both data sets strongly suggest that individuals examined in this study belong to more than one species