Development of a datalogger with open source hardware and software for the study of desert animals

The territory of the province of San Juan is composed by 80 percent by mountains. Its climate is quasi desert. It is in this place, where a group of researchers from the San Juan National University, is dedicated to the study of amphibians. To accomplish this task a device that can record data is necessary. These data are some environmental variables and the sound that these animals produce at certain temporal points. Generically to this device type is denominated data logger. This article describes the process of developing a datalogger of technical characteristics that have been specified by biologist researchers. It is a device built with open source hardware and software. The capture and data processing is done with the Arduino platform. The human computer interface is developed using the Android platform. That is, the management of datalogger is carried out by a mobile device, tablet or Smartphone based on Android.VIII Workshop Innovación en Sistemas de Software (WISS).Red de Universidades con Carreras en Informática (RedUNCI

Development of a datalogger with open source hardware and software for the study of desert animals

The territory of the province of San Juan is composed by 80 percent by mountains. Its climate is quasi desert. It is in this place, where a group of researchers from the San Juan National University, is dedicated to the study of amphibians. To accomplish this task a device that can record data is necessary. These data are some environmental variables and the sound that these animals produce at certain temporal points. Generically to this device type is denominated data logger. This article describes the process of developing a datalogger of technical characteristics that have been specified by biologist researchers. It is a device built with open source hardware and software. The capture and data processing is done with the Arduino platform. The human computer interface is developed using the Android platform. That is, the management of datalogger is carried out by a mobile device, tablet or Smartphone based on Android.VIII Workshop Innovación en Sistemas de Software (WISS).Red de Universidades con Carreras en Informática (RedUNCI

Effect of Tuned Parameters on a LSA MCQ Answering Model

This paper presents the current state of a work in progress, whose objective is to better understand the effects of factors that significantly influence the performance of Latent Semantic Analysis (LSA). A difficult task, which consists in answering (French) biology Multiple Choice Questions, is used to test the semantic properties of the truncated singular space and to study the relative influence of main parameters. A dedicated software has been designed to fine tune the LSA semantic space for the Multiple Choice Questions task. With optimal parameters, the performances of our simple model are quite surprisingly equal or superior to those of 7th and 8th grades students. This indicates that semantic spaces were quite good despite their low dimensions and the small sizes of training data sets. Besides, we present an original entropy global weighting of answers' terms of each question of the Multiple Choice Questions which was necessary to achieve the model's success.Comment: 9 page

Vast TVB parameter space exploration: A Modular Framework for Accelerating the Multi-Scale Simulation of Human Brain Dynamics

Global neural dynamics emerge from multi-scale brain structures, with neurons communicating through synapses to form transiently communicating networks. Network activity arises from intercellular communication that depends on the structure of connectome tracts and local connection, intracellular signalling cascades, and the extracellular molecular milieu that regulate cellular properties. Multi-scale models of brain function have begun to directly link the emergence of global brain dynamics in conscious and unconscious brain states to microscopic changes at the level of cells. In particular, AdEx mean-field models representing statistical properties of local populations of neurons have been connected following human tractography data to represent multi-scale neural phenomena in simulations using The Virtual Brain (TVB). While mean-field models can be run on personal computers for short simulations, or in parallel on high-performance computing (HPC) architectures for longer simulations and parameter scans, the computational burden remains high and vast areas of the parameter space remain unexplored. In this work, we report that our TVB-HPC framework, a modular set of methods used here to implement the TVB-AdEx model for GPU and analyze emergent dynamics, notably accelerates simulations and substantially reduces computational resource requirements. The framework preserves the stability and robustness of the TVB-AdEx model, thus facilitating finer resolution exploration of vast parameter spaces as well as longer simulations previously near impossible to perform. Given that simulation and analysis toolkits are made public as open-source packages, our framework serves as a template onto which other models can be easily scripted and personalized datasets can be used for studies of inter-individual variability of parameters related to functional brain dynamics.Comment: 21 pages, 9 figure

Gut bacteria responding to dietary change encode sialidases that exhibit preference for red meat-associated carbohydrates.

Dietary habits have been associated with alterations of the human gut resident microorganisms contributing to obesity, diabetes and cancer1. In Western diets, red meat is a frequently eaten food2, but long-term consumption has been associated with increased risk of disease3,4. Red meat is enriched in N-glycolylneuraminic acid (Neu5Gc) that cannot be synthesized by humans5. However, consumption can cause Neu5Gc incorporation into cell surface glycans6, especially in carcinomas4,7. As a consequence, an inflammatory response is triggered when Neu5Gc-containing glycans encounter circulating anti-Neu5Gc antibodies8,9. Although bacteria can use free sialic acids as a nutrient source10-12, it is currently unknown if gut microorganisms contribute to releasing Neu5Gc from food. We found that a Neu5Gc-rich diet induces changes in the gut microbiota, with Bacteroidales and Clostridiales responding the most. Genome assembling of mouse and human shotgun metagenomic sequencing identified bacterial sialidases with previously unobserved substrate preference for Neu5Gc-containing glycans. X-ray crystallography revealed key amino acids potentially contributing to substrate preference. Additionally, we verified that mouse and human sialidases were able to release Neu5Gc from red meat. The release of Neu5Gc from red meat using bacterial sialidases could reduce the risk of inflammatory diseases associated with red meat consumption, including colorectal cancer4 and atherosclerosis13

Experimental Study based on the Implementation of a Regulatory Framework for the Improvement of Cyber Resilience in SMEs

Currently, applying regulations oriented to cybersecurity, cyber resilience is relevant to face the high rates of cyberattacks, which have caused an interruption in the operational processes of organizations, generating an economic loss, and affecting the continuity of their business processes on the web. In this scenario, small and medium-sized enterprises (SMEs) are the most affected due to their weak technological infrastructure. Given this, this experimental study was developed to implement a regulatory framework for the improvement of cyber resilience; the criteria anticipate, resist, recover and evolve presented significant statistical values of improvement after the application of the experiment. This research contributes to counteract the refusal to use information technologies for business development; Improvement actions were carried out to face threats and computer vulnerabilities to which organizations are exposed when carrying out operations in cyberspace

Development of a datalogger with open source hardware and software for the study of desert animals

The territory of the province of San Juan is composed by 80 percent by mountains. Its climate is quasi desert. It is in this place, where a group of researchers from the San Juan National University, is dedicated to the study of amphibians. To accomplish this task a device that can record data is necessary. These data are some environmental variables and the sound that these animals produce at certain temporal points. Generically to this device type is denominated data logger. This article describes the process of developing a datalogger of technical characteristics that have been specified by biologist researchers. It is a device built with open source hardware and software. The capture and data processing is done with the Arduino platform. The human computer interface is developed using the Android platform. That is, the management of datalogger is carried out by a mobile device, tablet or Smartphone based on Android.VIII Workshop Innovación en Sistemas de Software (WISS).Red de Universidades con Carreras en Informática (RedUNCI

INCLUDING INDIGENOUS AND LOCAL KNOWLEDGE IN THE WORK OF THE INTERGOVERNMENTAL SCIENCE-POLICY PLATFORM ON BIODIVERSITY AND ECOSYSTEM SERVICES (IPBES) GLOBAL ASSESSMENT : Outcomes and lessons for the future

This chapter makes a strong case for greater inclusion of Indigenous and Local Knowledge (ILK) in global environmental policy fora and in science-policy interfaces. The chapter specifically looks at the IPBES Global Assessment which has developed one of the first global-scale mechanisms for operationalizing ILK in sustainability decision-making. The types of knowledges that have been successfully integrated into this assessment include ways in which ILK can help (1) to assess ecosystem change and associated human vulnerability; (2) to inform the achievement of global goals like the Sustainable Development Goals and Aichi Targets; and (3) to inform policy-relevant options for decision-makers. It is argued that other global initiatives seeking to engage ILK in their endeavours can learn from the ILK approach of the IPBES Global Assessment.Peer reviewe

Impact of SARS-CoV-2 Pandemic and Strategies for Resumption of Activities During the Second Wave of the Pandemic : A Report From Eight Paediatric Hospitals From the ECHO Network

The Severe Acute Respiratory Syndrome CoronaVirus type 2 (SARS-CoV-2) pandemic impacted the organization of paediatric hospitals. This study aimed to evaluate the preparedness for the pandemic among a European network of children's hospitals and to explore the strategies to restart health care services. A cross-sectional, web-based survey was distributed in May 2020 to the 13 children's tertiary care hospitals belonging to the European Children's Hospitals Organisation. Responses were obtained from eight hospitals (62%). Significant reductions were observed in accesses to the emergency departments (41.7%), outpatient visits (35.7%), intensive and non-intensive care unit inpatient admissions (16.4 and 13%, respectively) between February 1 and April 30, 2020 as compared with the same period of 2019. Overall, 93 children with SARS CoV-2 infection were admitted to inpatient wards. All the hospitals created SARS-CoV-2 preparedness plans for the diagnosis and management of infected patients. Routine activities were re-scheduled. Four hospitals shared their own staff with adult units, two designated bed spaces for adults and only one admitted adults to inpatient wards. The three main components for the resumption of clinical activities were testing, source control, and reorganization of spaces and flows. Telemedicine and telehealth services were used before the SARS-CoV-2 pandemic by three hospitals and by all the hospitals during it. Conclusion: The present study provides a perspective on preparedness to SARS-CoV-2 pandemic among eight large European children's hospitals, on the impact of the pandemic on the hospital activities and on the strategies adopted to restart clinical activities.Peer reviewe

Increased risk of type I errors in cluster randomised trials with small or medium numbers of clusters: a review, reanalysis,and simulation study

Background: Cluster randomised trials (CRTs) are commonly analysed using mixed-effects models or generalised estimating equations (GEEs). However, these analyses do not always perform well with the small number of clusters typical of most CRTs. They can lead to increased risk of a type I error (finding a statistically significant treatment effect when it does not exist) if appropriate corrections are not used. Methods: We conducted a small simulation study to evaluate the impact of using small-sample corrections for mixed-effects models or GEEs in CRTs with a small number of clusters. We then reanalysed data from TRIGGER, a CRT with six clusters, to determine the effect of using an inappropriate analysis method in practice. Finally, we reviewed 100 CRTs previously identified by a search on PubMed in order to assess whether trials were using appropriate methods of analysis. Trials were classified as at risk of an increased type I error rate if they did not report using an analysis method which accounted for clustering, or if they had fewer than 40 clusters and performed an individual-level analysis without reporting the use of an appropriate small-sample correction. Results: Our simulation study found that using mixed-effects models or GEEs without an appropriate correction led to inflated type I error rates, even for as many as 70 clusters. Conversely, using small-sample corrections provided correct type I error rates across all scenarios. Reanalysis of the TRIGGER trial found that inappropriate methods of analysis gave much smaller P values (P ≤ 0.01) than appropriate methods (P = 0.04–0.15). In our review, of the 99 trials that reported the number of clusters, 64 (65 %) were at risk of an increased type I error rate; 14 trials did not report using an analysis method which accounted for clustering, and 50 trials with fewer than 40 clusters performed an individual-level analysis without reporting the use of an appropriate correction. Conclusions: CRTs with a small or medium number of clusters are at risk of an inflated type I error rate unless appropriate analysis methods are used. Investigators should consider using small-sample corrections with mixed-effects models or GEEs to ensure valid results. Abbreviations: CRT, Cluster randomised trial; CI, Confidence interval; GEE, Generalised estimating equations; TRIGGER, Trial in Gastrointestinal Transfusio