Increasing the Size of a Piece of Popcorn

Popcorn is an extremely popular snack food in the world today. Thermodynamics can be used to analyze how popcorn is produced. By treating the popping mechanism of the corn as a thermodynamic expansion, a method of increasing the volume or size of a kernel of popcorn can be studied. By lowering the pressure surrounding the unpopped kernel, one can use a thermodynamic argument to show that the expanded volume of the kernel when it pops must increase. In this project, a variety of experiments are run to test the validity of this theory. The results show that there is a significant increase in the average kernel size when the pressure of the surroundings is reduced.Comment: Latex document, 14 pages, 4 figures, 1 page of table

Variational Approach to Hard Sphere Segregation Under Gravity

It is demonstrated that the minimization of the free energy functional for hard spheres and hard disks yields the result that excited granular materials under gravity segregate not only in the widely known "Brazil nut" fashion, i.e. with the larger particles rising to the top, but also in reverse "Brazil nut" fashion. Specifically, the local density approximation is used to investigate the crossover between the two types of segregation occurring in the liquid state, and the results are found to agree qualitatively with previously published results of simulation and of a simple model based on condensation.Comment: 10 pages, 3 figure

Analysis of local extinction of a n-heptane spray flame using large-eddy simulation with tabulated chemistry

This work is focused on the study of flame stabilization and local extinction of a spray flame in an atmospheric non-swirled test rig referred to as the CORIA Rouen Spray Burner. This burner shows a double reaction front structure, with an outer laminar diffusion flame and an inner wrinkled partially-premixed flame undertaking local extinction. This unsteady phenomenon is investigated here using large-eddy simulations with a tabulated chemistry method based on steady and unsteady diffusion flamelets with heat loss. A validation of the numerical simulations is conducted first for the carrier and dispersed phase and good agreement with the experimental data is found for mean and fluctuating quantities. The present results were able to predict relevant parameters of the flame like the lift-off length and flame shape. Numerical results evidence some intermittency on the OH concentration with the presence of high values of formaldehyde indicating the existence of localized extinction in the leading edge of the flame. A detailed analysis showed the impact of droplets on the reacting layer and the existence of rich pockets quenching the flame front. Further downstream, it was shown that when the scalar dissipation rate reaches high values near the reaction zone, the flame front becomes thinner and wrinkled until it eventually quenches. The numerical results evidence that the applied tabulated chemistry method is capable of capturing the local extinction and re-ignition events occurring in the inner layer.This work was partially funded by the Spanish Ministerio de Econom´ıa y Competitividad within the frame of the CHEST (TRA2017-89139-C2-1-R) project. BSC also acknowledges the funding from the CoEC project through the European Union’s Horizon 2020 research and innovation programme under grant agreement No 952181. Authors acknowledge the computer resources at Marenostrum and the technical support provided by Barcelona Supercomputing Center (BSC) (IM-2019-3-0025, IM-2020-1-0017, IM-2020-2-0026). Authors also thank the access to the CRSB database kindly provided by Prof. B. Renou.Peer ReviewedPostprint (author's final draft

Aprender fazendo: formação de multiplicadores comunitários com uso de tecnologias da Embrapa.

Esta sistematização teve como intenção, entre outros aspectos, servir como um registro de um modelo diferenciado de abordagem em um segmento de público não usual da Embrapa. Deve servir como balizamento para a Unidade da Embrapa Amazônia Oriental no tocante às atividades de TT e pode ser utilizada, também, por parceiros institucionais, por exemplo: Empresa de Assistência Técnica e Extensão Rural (Emater) e sistema de Assessoria Técnica, Social e Ambiental à Reforma Agrária (Ates); universidades, Serviço Brasileiro de Apoio às Micro e Pequenas Empresas (Sebrae), além dos atores envolvidos.bitstream/item/176438/1/COLECAO-SISTEMATIZACAO-EXPERIENCIAS-vol-6.pd

Optimal Resource Allocation with Delay Guarantees for Network Slicing in Disaggregated RAN

In this article, we propose a novel formulation for the resource allocation problem of a sliced and disaggregated Radio Access Network (RAN) and its transport network. Our proposal assures an end-to-end delay bound for the Ultra-Reliable and Low-Latency Communication (URLLC) use case while jointly considering the number of admitted users, the transmission rate allocation per slice, the functional split of RAN nodes and the routing paths in the transport network. We use deterministic network calculus theory to calculate delay along the transport network connecting disaggregated RANs deploying network functions at the Radio Unit (RU), Distributed Unit (DU), and Central Unit (CU) nodes. The maximum end-to-end delay is a constraint in the optimization-based formulation that aims to maximize Mobile Network Operator (MNO) profit, considering a cash flow analysis to model revenue and operational costs using data from one of the world's leading MNOs. The optimization model leverages a Flexible Functional Split (FFS) approach to provide a new degree of freedom to the resource allocation strategy. Simulation results reveal that, due to its non-linear nature, there is no trivial solution to the proposed optimization problem formulation. Our proposal guarantees a maximum delay for URLLC services while satisfying minimal bandwidth requirements for enhanced Mobile BroadBand (eMBB) services and maximizing the MNO's profit.Comment: 21 pages, 10 figures. For the associated GitHub repository, see https://github.com/LABORA-INF-UFG/paper-FGKCJ-202

A Survey on Long-Range Wide-Area Network Technology Optimizations

Long-Range Wide-Area Network (LoRaWAN) enables flexible long-range service communications with low power consumption which is suitable for many IoT applications. The densification of LoRaWAN, which is needed to meet a wide range of IoT networking requirements, poses further challenges. For instance, the deployment of gateways and IoT devices are widely deployed in urban areas, which leads to interference caused by concurrent transmissions on the same channel. In this context, it is crucial to understand aspects such as the coexistence of IoT devices and applications, resource allocation, Media Access Control (MAC) layer, network planning, and mobility support, that directly affect LoRaWAN’s performance.We present a systematic review of state-of-the-art works for LoRaWAN optimization solutions for IoT networking operations. We focus on five aspects that directly affect the performance of LoRaWAN. These specific aspects are directly associated with the challenges of densification of LoRaWAN. Based on the literature analysis, we present a taxonomy covering five aspects related to LoRaWAN optimizations for efficient IoT networks. Finally, we identify key research challenges and open issues in LoRaWAN optimizations for IoT networking operations that must be further studied in the future

Medieval and early modern diets in the Polack region of Belarus: A stable isotope perspective

In western and north-western Europe there has been a growing focus on exploring how major economic, political, and social changes during the Medieval period impacted the lived experience of different populations and sectors of society. Stable isotope analysis has proven particularly powerful in this regard, providing direct insights into the long-term diets of individuals and communities. Despite experiencing similarly dramatic social reconfigurations and changes, eastern Europe has, however, received far less attention in this regard. The territory of Belarus has, especially, so far remained a relative blank spot on the bioarchaeological map of Europe, though cities such as Polack emerged rapidly as key nodes within a growing economic and religious network. To gain direct insight into the diets of inhabitants of the Polack region of Belarus in the 11-18th centuries, we applied stable carbon and nitrogen isotope analysis to bone and dentine collagen from human (n = 143) and animal (n = 105) individuals from the city of Polack and surrounding rural sites. Results indicate a diet based on C3 terrestrial resources, which did not differ between sexes and showed limited variation over time. Contrary to expectations, it appears that animal products were commonly consumed by rural dwellers, but no significant reliance on fish resources or millet consumption is found. In contrast to examples from western Europe, we argue that the diets in the city and the surrounding villages remained broadly similar for the majority of the population, and similar to commoners analysed in Poland and Lithuania, perhaps suggestive of slightly different economic changes operating in this part of the Medieval world

Comparison of computed tomography image features extracted by radiomics, self-supervised learning and end-to-end deep learning for outcome prediction of oropharyngeal cancer

Background and purpose: To compare the prediction performance of image features of computed tomography (CT) images extracted by radiomics, self-supervised learning and end-to-end deep learning for local control (LC), regional control (RC), locoregional control (LRC), distant metastasis-free survival (DMFS), tumor-specific survival (TSS), overall survival (OS) and disease-free survival (DFS) of oropharyngeal squamous cell carcinoma (OPSCC) patients after (chemo)radiotherapy.Methods and materials: The OPC-Radiomics dataset was used for model development and independent internal testing and the UMCG-OPC set for external testing. Image features were extracted from the Gross Tumor Volume contours of the primary tumor (GTVt) regions in CT scans when using radiomics or a self-supervised learning-based method (autoencoder). Clinical and combined (radiomics, autoencoder or end-to-end) models were built using multivariable Cox proportional-hazard analysis with clinical features only and both clinical and image features for LC, RC, LRC, DMFS, TSS, OS and DFS prediction, respectively.Results: In the internal test set, combined autoencoder models performed better than clinical models and combined radiomics models for LC, RC, LRC, DMFS, TSS and DFS prediction (largest improvements in C-index: 0.91 vs. 0.76 in RC and 0.74 vs. 0.60 in DMFS). In the external test set, combined radiomics models performed better than clinical and combined autoencoder models for all endpoints (largest improvements in LC, 0.82 vs. 0.71). Furthermore, combined models performed better in risk stratification than clinical models and showed good calibration for most endpoints.Conclusions: Image features extracted using self-supervised learning showed best internal prediction performance while radiomics features have better external generalizability.</p