Spatially-explicit and spectral soil carbon modeling in Florida.

Profound shifts have occurred over the last three centuries in which human actions have become the main driver to global environmental change. In this new epoch, the Anthropocene, human-driven changes such as population growth, climate and land use change, are pushing the Earth system well outside its normal operating range causing severe and abrupt environmental change. In this context, we present research highlights from Florida (150,000 km2) showing how anthropogenic-induced changes have had major impacts on carbon dynamics in soils, including (i) modeling of carbon and nutrient dynamics and soil carbon sequestration impacted by climate and land use change; (ii) geospatial assessment of soil carbon stocks and pools, and (iii) spectral-based soil carbon modeling. Our research is embedded in the STEP-AWBH modeling concept which explicitly incorporates Human forcings and time-dependent evolution of Atmospheric, Water, and Biotic factors into the modeling process. Spatially-explicit soil carbon observations were fused with ancillary environmental data and various statistical and geostatistical methods were used to upscale soil carbon across the region. Our results suggest that soil hydrologic and taxonomic, biotic (vegetation and land use), and climatic properties show complex interactions explaining the variation of soil carbon within this heterogeneous subtropical landscape

The Terrestrial Carbon (Terra C) Information System to facilitate carbon synthesis across heterogeneous landscapes.

There are urgent needs to better synthesize knowledge and data across large regions and time periods to address global climate change, conduct soil/terrestrial carbon accounting, model carbon dynamics, assess carbon sequestration, and develop strategies for mitigation and adaptation. To address these needs we developed the Terrestrial Carbon (TerraC) Information System dedicated to advance soil/terrestrial carbon science. TerraC offers user-friendly tools to upload, store, manage, query, analyze, and download lab and field data characterizing carbon in soils, plants/biomass, atmosphere, water, and whole ecosystems. The purpose of TerraC is three-fold to: (i) advance carbon science through sharing of carbon and ancillary environmental data; (ii) facilitate environmental synthesis; and (iii) enhance collaboration among students, faculty, scientists, and extension specialists through shared resources. Data and metadata stored in TerraC can be shared privately among selected users (groups) or publicly with any user. We integrated various spatially-explicit soil carbon and ancillary environmental data collected in Florida representing different time periods, and conducted a synthesis analysis on soil carbon that will be presented as a case study. Detailed information about TerraC and data sharing options are available at: http://TerraC.ifas.ufl.edu

Electromechanical analysis of an adaptive piezoelectric energy harvester controlled by two segmented electrodes with shunt circuit networks

This paper presents an adaptive power harvester using a shunted piezoelectric control system with segmented electrodes. This technique has spurred new capability for widening the three simultaneous resonance frequency peaks using only a single piezoelectric laminated beam where normally previous works only provide a single peak for the resonance at the first mode. The benefit of the proposed techniques is that it provides effective and robust broadband power generation for application in self-powered wireless sensor devices. The smart structure beam with proof mass offset is considered to have simultaneous combination between vibration-based power harvesting and shunt circuit control-based electrode segments. As a result, the system spurs new development of the two mathematical methods using electromechanical closed-boundary value techniques and Ritz method-based weak-form analytical approach. The two methods have been used for comparison giving accurate results. For different electrode lengths using certain parametric tuning and harvesting circuit systems, the technique enables the prediction of the power harvesting that can be further proved to identify the performance of the system using the effect of varying circuit parameters so as to visualize the frequency and time waveform responses

Effect of shunted piezoelectric control for tuning piezoelectric power harvesting system responses – Analytical techniques

This paper presents new analytical modelling of shunt circuit control responses for tuning electromechanical piezoelectric vibration power harvesting structures with proof mass offset. For this combination, the dynamic closed-form boundary value equations reduced from strong form variational principles were developed using the extended Hamiltonian principle to formulate the new coupled orthonormalised electromechanical power harvesting equations showing combinations of the mechanical system (dynamical behaviour of piezoelectric structure), electromechanical system (electrical piezoelectric response) and electrical system (tuning and harvesting circuits). The reduced equations can be further formulated to give the complete forms of new electromechanical multi-mode FRFs and time waveform of the standard AC-DC circuit interface. The proposed technique can demonstrate self-adaptive harvesting response capabilities for tuning the frequency band and the power amplitude of the harvesting devices. The self-adaptive tuning strategies are demonstrated by modelling the shunt circuit behaviour of the piezoelectric control layer in order to optimise the harvesting piezoelectric layer during operation under input base excitation. In such situations, with proper tuning parameters the system performance can be substantially improved. Moreover, the validation of the closed-form technique is also provided by developing the Ritz method-based weak form analytical approach giving similar results. Finally, the parametric analytical studies have been explored to identify direct and relevant contributions for vibration power harvesting behaviours

Climate change : strategies for mitigation and adaptation

The sustainability of life on Earth is under increasing threat due to humaninduced climate change. This perilous change in the Earth's climate is caused by increases in carbon dioxide and other greenhouse gases in the atmosphere, primarily due to emissions associated with burning fossil fuels. Over the next two to three decades, the effects of climate change, such as heatwaves, wildfires, droughts, storms, and floods, are expected to worsen, posing greater risks to human health and global stability. These trends call for the implementation of mitigation and adaptation strategies. Pollution and environmental degradation exacerbate existing problems and make people and nature more susceptible to the effects of climate change. In this review, we examine the current state of global climate change from different perspectives. We summarize evidence of climate change in Earth’s spheres, discuss emission pathways and drivers of climate change, and analyze the impact of climate change on environmental and human health. We also explore strategies for climate change mitigation and adaptation and highlight key challenges for reversing and adapting to global climate change

A Text Mining Pipeline Using Active and Deep Learning Aimed at Curating Information in Computational Neuroscience

The curation of neuroscience entities is crucial to ongoing efforts in neuroinformatics and computational neuroscience, such as those being deployed in the context of continuing large-scale brain modelling projects. However, manually sifting through thousands of articles for new information about modelled entities is a painstaking and low-reward task. Text mining can be used to help a curator extract relevant information from this literature in a systematic way. We propose the application of text mining methods for the neuroscience literature. Specifically, two computational neuroscientists annotated a corpus of entities pertinent to neuroscience using active learning techniques to enable swift, targeted annotation. We then trained machine learning models to recognise the entities that have been identified. The entities covered are Neuron Types, Brain Regions, Experimental Values, Units, Ion Currents, Channels, and Conductances and Model organisms. We tested a traditional rule-based approach, a conditional random field and a model using deep learning named entity recognition, finding that the deep learning model was superior. Our final results show that we can detect a range of named entities of interest to the neuroscientist with a macro average precision, recall and F1 score of 0.866, 0.817 and 0.837 respectively. The contributions of this work are as follows: 1) We provide a set of Named Entity Recognition (NER) tools that are capable of detecting neuroscience entities with performance above or similar to prior work. 2) We propose a methodology for training NER tools for neuroscience that requires very little training data to get strong performance. This can be adapted for any sub-domain within neuroscience. 3) We provide a small corpus with annotations for multiple entity types, as well as annotation guidelines to help others reproduce our experiments

Final results from the PERUSE study of first-line pertuzumab plus trastuzumab plus a taxane for HER2-positive locally recurrent or metastatic breast cancer, with a multivariable approach to guide prognostication

Background: The phase III CLinical Evaluation Of Pertuzumab And TRAstuzumab (CLEOPATRA) trial established the combination of pertuzumab, trastuzumab and docetaxel as standard first-line therapy for human epidermal growth factor receptor 2 (HER2)-positive locally recurrent/metastatic breast cancer (LR/mBC). The multicentre single-arm PERtUzumab global SafEty (PERUSE) study assessed the safety and efficacy of pertuzumab and trastuzumab combined with investigator-selected taxane in this setting. Patients and methods: Eligible patients with inoperable HER2-positive LR/mBC and no prior systemic therapy for LR/mBC (except endocrine therapy) received docetaxel, paclitaxel or nab-paclitaxel with trastuzumab and pertuzumab until disease progression or unacceptable toxicity. The primary endpoint was safety. Secondary endpoints included progression-free survival (PFS) and overall survival (OS). Prespecified subgroup analyses included subgroups according to taxane, hormone receptor (HR) status and prior trastuzumab. Exploratory univariable analyses identified potential prognostic factors; those that remained significant in multivariable analysis were used to analyse PFS and OS in subgroups with all, some or none of these factors. Results: Of 1436 treated patients, 588 (41%) initially received paclitaxel and 918 (64%) had HR-positive disease. The most common grade 653 adverse events were neutropenia (10%, mainly with docetaxel) and diarrhoea (8%). At the final analysis (median follow-up: 5.7 years), median PFS was 20.7 [95% confidence interval (CI) 18.9-23.1] months overall and was similar irrespective of HR status or taxane. Median OS was 65.3 (95% CI 60.9-70.9) months overall. OS was similar regardless of taxane backbone but was more favourable in patients with HR-positive than HR-negative LR/mBC. In exploratory analyses, trastuzumab-pretreated patients with visceral disease had the shortest median PFS (13.1 months) and OS (46.3 months). Conclusions: Mature results from PERUSE show a safety and efficacy profile consistent with results from CLEOPATRA and median OS exceeding 5 years. Results suggest that paclitaxel is a valid alternative to docetaxel as backbone chemotherapy. Exploratory analyses suggest risk factors that could guide future trial design

Diminishing benefits of urban living for children and adolescents’ growth and development

Optimal growth and development in childhood and adolescence is crucial for lifelong health and well-being1–6. Here we used data from 2,325 population-based studies, with measurements of height and weight from 71 million participants, to report the height and body-mass index (BMI) of children and adolescents aged 5–19 years on the basis of rural and urban place of residence in 200 countries and territories from 1990 to 2020. In 1990, children and adolescents residing in cities were taller than their rural counterparts in all but a few high-income countries. By 2020, the urban height advantage became smaller in most countries, and in many high-income western countries it reversed into a small urban-based disadvantage. The exception was for boys in most countries in sub-Saharan Africa and in some countries in Oceania, south Asia and the region of central Asia, Middle East and north Africa. In these countries, successive cohorts of boys from rural places either did not gain height or possibly became shorter, and hence fell further behind their urban peers. The difference between the age-standardized mean BMI of children in urban and rural areas was <1.1 kg m–2 in the vast majority of countries. Within this small range, BMI increased slightly more in cities than in rural areas, except in south Asia, sub-Saharan Africa and some countries in central and eastern Europe. Our results show that in much of the world, the growth and developmental advantages of living in cities have diminished in the twenty-first century, whereas in much of sub-Saharan Africa they have amplified