Life-History Traits of Three Syntopic Species of the South American Redbelly Toads (Anura: Bufonidae: Melanophryniscus) from the Atlantic Forest of Argentina

Amphibians from Atlantic Forests of South America are one of the most threatened vertebrates of the world, mainly due to the habitat loss and infectious diseases. With the goal to improve the knowledge of the lifehistory traits of the amphibian that inhabit these regions, and thus, to aid conservation and management-decision making, our main goals were to describe the reproductive activity pattern and analyze the interspecific variation in body size and the reproductive traits of three species of redbelly toads (Melanophryniscus) of the Atlantic Forest of Argentina. We also analyzed age structure, whether Sexual Size Dimorphism (SSD) exists, and if this dimorphismcould be explained by proximate mechanisms such as differences in growth patterns. The Melanophryniscus we studied bred during two or three consecutive days, in several explosive events that occurred between April 2009 and October 2012. These events were determined by a trade-off between the air and water temperature, and the level of the water bodies. We observed spatial segregation among the three species we studied when they reproduced synchronously and in sympatry and with the presence of multiple clutches. We found inter-specific differences inbody size. We recorded male-biased sex ratio and SSD in all three species of Melanophryniscus studied. We also found significant interspecific differences in age-related parameters following the differences in body size. Species were not sexually dimorphic by age. We also did not find covariation between body size and reproductive traits. These new insights allow us to predict the responses of Melanphryniscus we studied to the impact of the destruction of their habitat and global warming.Fil: Marangoni, Federico. Universidad Nacional del Nordeste. Facultad de Ciencias Exactas, Naturales y Agrimensura. Departamento de Biología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste; ArgentinaFil: Baldo, Juan Diego. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Universidad Nacional de Misiones. Instituto de Biología Subtropical; Argentin

An analysis of Universal Differential Equations for data-driven discovery of Ordinary Differential Equations

In the last decade, the scientific community has devolved its attention to the deployment of data-driven approaches in scientific research to provide accurate and reliable analysis of a plethora of phenomena. Most notably, Physics-informed Neural Networks and, more recently, Universal Differential Equations (UDEs) proved to be effective both in system integration and identification. However, there is a lack of an in-depth analysis of the proposed techniques. In this work, we make a contribution by testing the UDE framework in the context of Ordinary Differential Equations (ODEs) discovery. In our analysis, performed on two case studies, we highlight some of the issues arising when combining data-driven approaches and numerical solvers, and we investigate the importance of the data collection process. We believe that our analysis represents a significant contribution in investigating the capabilities and limitations of Physics-informed Machine Learning frameworks

Injective Domain Knowledge in Neural Networks for Transprecision Computing

Machine Learning (ML) models are very effective in many learning tasks, due to the capability to extract meaningful information from large data sets. Nevertheless, there are learning problems that cannot be easily solved relying on pure data, e.g. scarce data or very complex functions to be approximated. Fortunately, in many contexts domain knowledge is explicitly available and can be used to train better ML models. This paper studies the improvements that can be obtained by integrating prior knowledge when dealing with a non-trivial learning task, namely precision tuning of transprecision computing applications. The domain information is injected in the ML models in different ways: I) additional features, II) ad-hoc graph-based network topology, III) regularization schemes. The results clearly show that ML models exploiting problem-specific information outperform the purely data-driven ones, with an average accuracy improvement around 38%

An Analysis of Regularized Approaches for Constrained Machine Learning

open4noopenLombardi, Michele; Baldo, Federico; Borghesi, Andrea; Milano, MichelaLombardi, Michele; Baldo, Federico; Borghesi, Andrea; Milano, Michel

Miracle: the multi-interface cross-layer extension of ns2

We present Miracle, a novel framework which extends ns2 to facilitate the simulation and the design of beyond 4G networks. Miracle enhances ns2 by providing an efficient and embedded engine for handling cross-layer messages and, at the same time, enabling the coexistence of multiple modules within each layer of the protocol stack. We also present a novel framework developed as an extension of Miracle called Miracle PHY and MAC. This framework facilitates the development of more realistic Channel, PHY and MAC modules, considering features currently lacking in most state-of-the-art simulators, while at the same time giving a strong emphasis on code modularity, interoperability and reusability. Finally, we provide an overview of the wireless technologies implemented in Miracle, discussing in particular the models for the IEEE 802.11, UMTS and WiMAX standards and for Underwater Acoustic Networks. We observe that, thanks to Miracle and its extensions, it is possible to carefully simulate complex network architectures at all the OSI layers, from the physical reception model to standard applications and system management schemes. This allows to have a comprehensive view of all the interactions among network components, which play an important role in many research areas, such as cognitive networking and cross-layer design

Clinical Use of a 180-Day Implantable Glucose Monitoring System in Dogs with Diabetes Mellitus: A Case Series

Simple Summary A novel continuous glucose monitoring system (CGMS) equipped with a long-term sensor has recently been developed for humans with diabetes mellitus. The sensor is inserted under the skin and continuously measures the glucose in the interstitial fluid over a period of up to 180 days. The aim of this study was to describe, for the first time, the clinical use of this novel CGMS in three diabetic dogs (DD). The insertion and use of the device were straightforward and well tolerated by the dogs. Some device-related issues, such as sensor dislocation and trouble with daily calibrations, were reported. A good correlation between the glucose values measured by this CGMS and those obtained with a flash glucose monitoring system and a portable-blood glucose meter, previously validated for use in DD, was found (rs = 0.85 and rs = 0.81, respectively). The functional life of the sensor was 180 days in two of the three dogs, and the use of the device provided high satisfaction to the owners. This innovative device might be considered a future alternative for continuous glucose monitoring in dogs with diabetes mellitus. The novel Eversense XL continuous glucose monitoring system (Senseonics, Inc., Germantown, Maryland) has recently been developed for monitoring diabetes in humans. The sensor is fully implanted and has a functional life of up to 180 days. The present study describes the use of Eversense XL in three diabetic dogs (DD) with good glycemic control managed by motivated owners. The insertion and use of the device were straightforward and well tolerated by the dogs. During the wearing period, some device-related drawbacks, such as sensor dislocation and daily calibrations, were reported. A good correlation between the glucose values measured by the Eversense XL and those obtained with two commercially available devices, previously validated for use in DD, was found (r(s) = 0.85 and r(s) = 0.81, respectively). The life of the sensor was 180 days in two of the DD and provided high satisfaction. This innovative device might be considered a future alternative for home glucose monitoring in DD

Urinary cortisol-creatinine ratio in dogs with hypoadrenocorticism

Background Basal serum cortisol (BSC) >= 2 mu g/dL (>55 nmol/L) has high sensitivity but low specificity for hypoadrenocorticism (HA). Objective To determine whether the urinary corticoid:creatinine ratio (UCCR) can be used to differentiate dogs with HA from healthy dogs and those with diseases mimicking HA (DMHA). Animals Nineteen healthy dogs, 18 dogs with DMHA, and 10 dogs with HA. Methods Retrospective study. The UCCR was determined on urine samples from healthy dogs, dogs with DMHA, and dogs with HA. The diagnostic performance of the UCCR was assessed based on receiver operating characteristics (ROC) curves, calculating the area under the ROC curve. Results The UCCR was significantly lower in dogs with HA (0.65 x 10(-6); range, 0.33-1.22 x 10(-6)) as compared to healthy dogs (3.38 x 10(-6); range, 1.11-17.32 x 10(-6)) and those with DMHA (10.28 x 10(-6); range, 2.46-78.65 x 10(-6)) (P < .0001). There was no overlap between dogs with HA and dogs with DMHA. In contrast, 1 healthy dog had a UCCR value in the range of dogs with HA. The area under the ROC curve was 0.99. A UCCR cut-off value of <1.4 yielded 100% sensitivity and 97.3% specificity in diagnosing HA. Conclusions and Clinical Importance The UCCR seems to be a valuable and reliable screening test for HA in dogs. The greatest advantage of this test is the need for only a single urine sample

Prevalence of Asymptomatic SARS-CoV-2 Infection in the General Population of the Veneto Region: Results of a Screening Campaign with Third-Generation Rapid Antigen Tests in the Pre-Vaccine Era

The aim of our study was to ascertain the prevalence of SARS-CoV-2 infection in the general population during a period of moderate risk, just before Italy started to implement its vaccination campaign. A third-generation antigenic nasal swab sample was collected by a healthcare provider, and all individuals testing positive subsequently had a nasopharyngeal swab for molecular testing; the result was used to calculate the positive predictive value. The population consisted of 4467 asymptomatic adults with a mean age of 46.8 +/- 16.00 years. The 62.2% tested for the first time, while 37.8% had previously undergone a mean 2.2 tests for SARS-CoV-2. With 77 of our overall sample reporting they had previously tested positive for COVID-19 and 14 found positive on our screening test, the overall estimated prevalence of the infection was 0.31%. Nine of the 14 cases were confirmed on molecular testing with a PPV of 64.3%. The mean age of the individuals testing positive was 38.1 +/- 17.4. Based on the timing of symptom onset, six of the above cases were classified as false negatives, and the adjusted estimated prevalence was 0.34%. Describing levels of infection in a general population seems to be very difficult to achieve, and the universal screening proved hugely expensive particularly in a low-prevalence situation. Anyway, it is only thanks to mass screening efforts that epidemiological data have been collected. This would support the idea that routine screening may have an impact on mitigating the spread of the virus in higher-risk environments, where people come into contact more frequently, as in the workplace