Interactions between competition and predation shape early growth and survival of two Neotropical hylid tadpoles [poster]

Background/Question/Methods Recent literature reviews reveal that competition typically has stronger effects on growth than the presence of predators, while predation has larger effects on survival. Further, past studies show that predators typically lessen the negative effect of competition on growth and also make interspecific competition beneficial for the survival of focal species. We examine the independent and combined effects of competition and predation for survival and growth of the tadpoles of two co-occurring Neotropical hylid frogs (Agalychnis callidryas and Dendropsophus ebraccatus). Our experiment crossed tadpole species composition (single and mixed at single total density) with the presence or absence of a free-roaming predator (Anax sp. dragonfly larva) using a 3x2 factorial design. Six replicates were conducted in 300 L mesocosms at the Smithsonian Tropical Research Center, Gamboa, Panama. Results/Conclusions Dragonfly larvae were effective predators of both species, but had larger effects on A. callidryas survival. A. callidryas grew faster in the presence of D. ebraccatus, suggesting it is a more effective competitor. A. callidryas reduced D. ebraccatus growth in the absence of dragonflies; however, this effect disappeared when predators were present. Though our results are largely consistent with similar previous studies, one interesting difference did emerge. Not only did predation have larger effects on survival than competition, but predator presence resulted in a much larger reduction in tadpole growth than competition – even though predation increased per capita resource levels. This can be attributed to either changes in feeding behavior or metabolic costs of alteration of phenotypically plastic traits. Thus, in our study, predator effects dominated survival and growth and highlight the importance of top-down effects, as well as costs associated with phenotypic plasticity, in shaping interactions between these species

Five-level cascade asymmetric multilevel converter

A five-level cascaded asymmetric multilevel converter is analysed and designed. This topologysynthesises five voltage levels with a reduced number of components when compared to the most common symmetric topologies. It allows getting more voltage levels with less switching states. Its behaviour is similar to a hybrid converter with the advantage of working with only one DC bus. It does not present the usual drawbacks of symmetrical topologies. The cascaded asymmetric converter, presented here, appears as a very attractive alternative among the five-level converters with no voltage balancing problem. The performance of the proposed topology is evaluated with Pspice simulations in different applications.Fil: Gonzalez, Sergio Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; Argentina. Universidad Nacional de La Plata. Facultad de Ingeniería; ArgentinaFil: Valla, Maria Ines. Universidad Nacional de La Plata. Facultad de Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; ArgentinaFil: Christiansen, C. F.. Universidad Nacional de La Plata. Facultad de Ingeniería; Argentin

Population distribution models: species distributions are better modeled using biologically relevant data partitions

<p>Abstract</p> <p>Background</p> <p>Predicting the geographic distribution of widespread species through modeling is problematic for several reasons including high rates of omission errors. One potential source of error for modeling widespread species is that subspecies and/or races of species are frequently pooled for analyses, which may mask biologically relevant spatial variation within the distribution of a single widespread species. We contrast a presence-only maximum entropy model for the widely distributed oldfield mouse (<it>Peromyscus polionotus</it>) that includes all available presence locations for this species, with two composite maximum entropy models. The composite models either subdivided the total species distribution into four geographic quadrants or by fifteen subspecies to capture spatially relevant variation in <it>P. polionotus </it>distributions.</p> <p>Results</p> <p>Despite high Area Under the ROC Curve (AUC) values for all models, the composite species distribution model of <it>P. polionotus </it>generated from individual subspecies models represented the known distribution of the species much better than did the models produced by partitioning data into geographic quadrants or modeling the whole species as a single unit.</p> <p>Conclusions</p> <p>Because the AUC values failed to describe the differences in the predictability of the three modeling strategies, we suggest using omission curves in addition to AUC values to assess model performance. Dividing the data of a widespread species into biologically relevant partitions greatly increased the performance of our distribution model; therefore, this approach may prove to be quite practical and informative for a wide range of modeling applications.</p

Physically-sound simulation of low-velocity impact on fiber reinforced laminates

A high-fidelity virtual tool for the numerical simulation of low-velocity impact damage in unidirectional composite laminates is proposed. A continuum material model for the simulation of intraply damage phenomena is implemented in a numerical scheme as a user subroutine of the commercially available Abaqus finite element package. Delaminations are simulated using of cohesive surfaces. The use of structured meshes, aligned with fiber directions allows the physically-sound simulation of matrix cracks parallel to fiber directions, and their interaction with the development of delaminations. The implementation of element erosion criteria and the application of intraply and interlaminar friction allow for the simulation of fiber splits and their entanglement, which in turn results in permanent indentation in the impacted laminate. It is shown that this simulation strategy gives sound results for impact energies bellow and above the Barely Visible Impact Damage threshold, up to laminate perforation condition

Organic Dairy Sheep Production Management

Organic production systems are based on natural processes, the use of local feed resources, and the maintenance of biodiversity in all senses. Several studies have noted the positive effects of organic sheep milk production systems on animal welfare, animal health, product quality, and environmental impact. On the other hand, it has been reported that dairy sheep organic farms show lower milk yields and increase the susceptibility to environmental impacts compared with conventional farms. The standards that regulate feeding management in organic systems are one of the most critical factors that influence milk production performance. Lower milk production is also associated with poor ability to adapt specialized dairy breeds to organic management, low genetic potential for milk production in native and local breeds, and elevated dependence on environmental conditions. However, the aim of organic dairy production is not to reach maximum dairy productivity but rather to integrate animal and crop production and to develop a symbiotic relationship between recyclable and renewable resources; furthermore, organic production positively affects the employment rate and quality of life in rural communities. Organic dairy sheep production is one means of improving the balance between society’s demand for food and the ecological impact of the agro-alimentary industry

Random insights into the complexity of two-dimensional tensor network calculations

Projected entangled pair states (PEPS) offer memory-efficient representations of some quantum many-body states that obey an entanglement area law, and are the basis for classical simulations of ground states in two-dimensional (2d) condensed matter systems. However, rigorous results show that exactly computing observables from a 2d PEPS state is generically a computationally hard problem. Yet approximation schemes for computing properties of 2d PEPS are regularly used, and empirically seen to succeed, for a large subclass of (not too entangled) condensed matter ground states. Adopting the philosophy of random matrix theory, in this work we analyze the complexity of approximately contracting a 2d random PEPS by exploiting an analytic mapping to an effective replicated statistical mechanics model that permits a controlled analysis at large bond dimension. Through this statistical-mechanics lens, we argue that: i) although approximately sampling wave-function amplitudes of random PEPS faces a computational-complexity phase transition above a critical bond dimension, ii) one can generically efficiently estimate the norm and correlation functions for any finite bond dimension. These results are supported numerically for various bond-dimension regimes. It is an important open question whether the above results for random PEPS apply more generally also to PEPS representing physically relevant ground state

Production, Processing, Commercialization and Analysis of Costumer Preferences of Sheep Cheese in Chile

The constant increase in the demand for dairy products and their derivatives has generated a higher consumption of dairy products (113.5 t/year). Chile has not been the exception; in 2017, it presented an average per capita consumption of 11.1 kg of cheese, making it the largest consumer in Latin America, followed by Argentina (7.5 kg) and Uruguay (5 kg). Although Chile does not have a strong tradition of consuming sheep’s milk cheese compared with other (European) countries, in recent years, there have been changes in the demands and expectations of cheese consumers, who demand higher quality and a wider range of varieties, thus establishing the potential for further products to enter the market. The global cheese industry has taken charge of these trends through the phenomenon of granting a premium value to certain products, adding new ingredients and flavors, producing limited editions of certain products, favoring traditional recipes and craft methods, and highlighting specific localities of origin. Given a greater appreciation for and popularity of locally produced cheeses and value-added products, particularly those with the highly valued “Designation of Origin” label, this would offer a potential for expansion in the Chilean market

Anomaly Detection in Small-Scale Industrial and Household Appliances

Anomaly detection is concerned with identifying rare events/ observations that differ substantially from the majority of the data. It is considered an important task in the energy sector to enable the identification of non-standard device conditions. The use of anomaly detection techniques in small-scale residential and industrial settings can provide useful insights about device health, maintenance requirements, and downtime, which in turn can lead to lower operating costs. There are numerous approaches for detecting anomalies in a range of application scenarios such as prescriptive appliance maintenance. This work reports on anomaly detection using a data set of fridge power consumption that operates on a near zero energy building scenario. We implement a variety of machine and deep learning algorithms and evaluate performances using multiple metrics. In the light of the present state of the art, the contribution of this work is the development of a inference pipeline that incorporates numerous methodologies and algorithms capable of producing high accuracy results for detecting appliance failures

Post-COVID-19 Symptoms and Heart Disease: Incidence, Prognostic Factors, Outcomes and Vaccination: Results from a Multi-Center International Prospective Registry (HOPE 2)

COVID-19; Heart disease; PersistentCOVID 19; Malaltia cardíaca; PersistentCOVID-19; Enfermedad cardíaca; PersistenteBackground: Heart disease is linked to worse acute outcomes after coronavirus disease 2019 (COVID-19), although long-term outcomes and prognostic factor data are lacking. We aim to characterize the outcomes and the impact of underlying heart diseases after surviving COVID-19 hospitalization. Methods: We conducted an analysis of the prospective registry HOPE-2 (Health Outcome Predictive Evaluation for COVID-19-2, NCT04778020). We selected patients discharged alive and considered the primary end-point all-cause mortality during follow-up. As secondary main end-points, we included any readmission or any post-COVID-19 symptom. Clinical features and follow-up events are compared between those with and without cardiovascular disease. Factors with p < 0.05 in the univariate analysis were entered into the multivariate analysis to determine independent prognostic factors. Results: HOPE-2 closed on 31 December 2021, with 9299 patients hospitalized with COVID-19, and 1805 died during this acute phase. Finally, 7014 patients with heart disease data were included in the present analysis, from 56 centers in 8 countries. Heart disease (+) patients were older (73 vs. 58 years old), more frequently male (63 vs. 56%), had more comorbidities than their counterparts, and suffered more frequently from post-COVID-19 complications and higher mortality (OR heart disease: 2.63, 95% CI: 1.81–3.84). Vaccination was found to be an independent protector factor (HR all-cause death: 0.09; 95% CI: 0.04–0.19). Conclusions: After surviving the acute phase, patients with underlying heart disease continue to present a more complex clinical profile and worse outcomes including increased mortality. The COVID-19 vaccine could benefit survival in patients with heart disease during follow-up.Non-conditioned grant (Fundación Interhospitalaria para la Investigación cardiovascular, FIC. Madrid, Spain). This nonprofit institution had no role in the study design; collection, analysis, or interpretation of data; in the writing of the report; nor in the decision to submit the paper for publication