The tidyverse : manipulating and visualising large datasets

Manipulating and visualising large datasets using tidyverse: a demonstration, using an example from the Ethiopian drought in 2015-16, of the power of Tidyverse, to clean and manipulate data, and produce striking, clear, reproducible and high impact visualisations using the dplyr and ggplot2 packages

ceylon: An R package for plotting the maps of Sri Lanka

The rapid evolution in the fields of computer science, data science, and artificial intelligence has significantly transformed the utilisation of data for decision-making. Data visualisation plays a critical role in any work that involves data. Visualising data on maps is frequently encountered in many fields. Visualising data on maps not only transforms raw data into visually comprehensible representations but also converts complex spatial information into simple, understandable form. Locating the data files necessary for map creation can be a challenging task. Establishing a centralised repository can alleviate the challenging task of finding shape files, allowing users to efficiently discover geographic data. The ceylon R package is designed to make simple feature data related to Sri Lanka's administrative boundaries and rivers and streams accessible for a diverse range of R users. With straightforward functionalities, this package allows users to quickly plot and explore administrative boundaries and rivers and streams in Sri Lanka.Comment:

Evaluation of radiodensity and dimensional stability of polymeric materials used for oral stents during external beam radiotherapy of head and neck carcinomas.

Purpose Intraoral stents protect the healthy tissues from ionizing radiation during external beam radiotherapy reducing mucositis, hyposalivation and osteoradionecrosis. This study investigated the radiodensity and dimensional stability of polymeric materials for suitability in construction of intraoral stents and aimed to provide clinical guidelines. Methods Specimens were fabricated using 4 material types namely, resin composite (ProTemp-PRO), polymethylmethacrylate (PMMA) (Enamel Temp Plus-ETP, Palapress-PAL, TAB 2000-TAB), polycaprolactone (Orfit-ORF) and silicone (Adisil-ADI, Lab Putty-LAB, Memosil2-MEM, Optosil-OPT, President Plus-PRE, Siolaplast A-SIA). They were randomly assigned to measure their radiodensity in Hounsfield Units (HU) (12x12x11mm3) (Nradiodensity = 66; n = 6) using a computer tomograph (CBCT, Toshiba Aquillon LB scanner) at baseline and after 6 weeks. The scanning protocol was applied with and without single energy metal artifact reduction (SEMAR) scans using a slice thickness of 1 and 5 mm. The same materials have been tested for their dimensional stability (µm3) at baseline, 1, 6, 12, 24 h, 3 and 6 weeks (14 × 4 × 2 mm3) (Ndimension = 55; n = 5 per material) using stereolithography (STL) files generated by a lab scanner (L2i, Imetric4D, Courgenay, Switzerland) and analyzed using a matching software (Geomagic ControlX 2020, 3D Systems). Data were analyzed using a paired t-test (alpha = 0.05). Results Radiodensity values (HU) were significantly affected by the material classification (p < 0.05). Polycaprolactone (43.6) presented significantly lower HU values followed by PMMA (91.3-414.9) than those of silicone materials (292.8-874.5). In terms of dimensional stability (µm3), PMMA materials (Δ:1.53-2.68) and resin composite (Δ:2.89) were significantly more dimensionally stable compared to those of silicone materials (Δ:13.64-6.63) and polycaprolactone (Δ:-0.76) and (p < 0.05). Conclusion For fabricating intraoral stents, when reduced radiodensity values are required polycaprolactone could be recommended as it fulfils the requirements for reduced radiodensity and dimensional stability. Among all silicone materials, OPT and MEM can be recommended based on the low HU and dimensional stability

Infer: An R Package for Tidyverse-Friendly Statistical Inference

infer implements an expressive grammar to perform statistical inference that adheres to the tidyverse design framework (Wickham et al., 2019). Rather than providing methods for specific statistical tests, this package consolidates the principles that are shared among common hypothesis tests and confidence intervals into a set of four main verbs (functions), supplemented with many utilities to visualize and extract value from their outputs

Effects of Human-Animal Interactions on Affect and Cognition

Human-animal interaction has clear positive effects on people’s affect and stress. But less is known about how animal interactions influence cognition. We draw parallels between animal interactions and exposure to natural environments, a research area that shows clear improvements in cognitive performance. The aim of this study is to investigate whether interacting with animals similarly enhances cognitive performance, specifically executive functioning. To test this, we conducted two experiments in which we had participants self-report their affect and complete a series of cognitive tasks (long-term memory, attentional control, and working memory) before and after either a brief interaction with a dog or a control activity. We found that interacting with a dog improved positive affect and decreased negative affect (in one of the two experiments), stress, and anxiety compared to the control condition. However, we did not find effects of animal interaction on long-term memory, attentional control, or working memory. Thus, we replicated existing findings providing evidence that interacting with animals can improve affect, but we did not find similar improvements in cognitive performance. These results suggest that either our interaction was not of sufficient dose or timed appropriately to elicit effects on cognition or the mechanisms underlying effects of human-animal interaction on cognition differ from effects generated by other cognition-enhancing interventions such as exposure to nature. Future research should continue to increase knowledge of the connection between nature exposure and human-animal interaction studies to build our understanding of cognition in response to animal interactions

Automated cleansing and harmonization of international trade data

Large volumes of data are becoming increasingly available and can be very valuable for the analysis of different phenomena. These data can originate from multiple sources and be recorded in diverse formats, requiring preliminary scrutiny in order to be further used in scientific analyses. This first crucial phase of filtering and cleansing data is usually a cumbersome and time-consuming task, but automated routines can be developed to help researchers. A routine created with the R language is here presented, to screen, harmonize and aggregate international trade data, representing the trade flows between countries for specific products, in a timeframe that covers monthly flows for at least 15 years for most countries. The R script implementing these routines is provided, being easily adapted to other datasets with similar issues. • A step-by-step procedure for cleansing and harmonizing international trade data, using R programming language, is presented • Automated routines are very effective in obtaining robust and filtered data inputs to integrate in scientific models • Spatial and temporal patterns of worldwide trade relations can be explored to enhance our understanding of various associated phenomenainfo:eu-repo/semantics/publishedVersio

Vegetation Response to Grazing Pressure in the Puna Flat, NW Argentina

Puna grasslands are located at a high‐altitude flat plateau in the Northwest of Argentina. It is an arid territory (100 to 300 mm rainfall/year) at 3,000 to 4,000 m a.s.l. The vegetation is scarce, where Andean pastoralist communities produce meat and wool, specialized in llama (Lama glama) and sheep‐breeding, although they do breed multi‐species herds that may also include goats and cattle. There are erosion processes in the Puna, where shepherds and their animals could be synergetic factors with natural very hard climatic conditions. In this work we assess the effect of ovine and lama grazing on the plant communities in the Puna grasslands. Considering that stockyards are used in a very complex way along the year, having differences between those used in winter or in summer, or used for many months or only one month, etc. we built up a Grazing Pressure Index taking in account all these factors in each sampling point. We sampled 28 paired transects (14 in sites with high grazing pressure, and 14 in sites with low grazing pressure) in 2 different ecological sites (grassy grassland and shrubby steppe). Focusing our work on the community functionality, we analysed Plant Functional Types (PTF) measuring their cover, richness and diversity. Our results do not show significant differences on PFT cover, richness or diversity between sites at different grazing pressures. It could be the result of a low grazing pressure or a long grazing pressure history that had configured the TFP associations

TEMPERATURE AND PRECIPITATION REGIME IMPACT ON SPRING BARLEY (HORDEUM VULGARE) GROWTH IN PRIEKUĻI CASE

In Latvia, the effects of drought and extreme temperatures on spring barley have so far been little studied due to the availability of data and the fact that meteorological conditions are only one of the multi-influencing factors that affect the agricultural sector.Barley usually flowers before or at the same time as ear emergence. During the flowering period high ambient temperatures are critical for yield formation. If the air temperature during flowering is above 22℃ the flowers of spring barley become sterile. From 2004 - 2022, a significant and positive correlation (R = 0,57) was observed between the average maximum daily temperature from sowing to ear emergence and the number of empty flowers in the main spike. A significant negative correlation (R = 0,55) was observed between plant height and the sum of precipitation from sowing to ear emergence and spike length and the sum of precipitation from ear emergence to maturity (R = −0,54), drought also negatively affects tillering rate and number of productive stems per plant.The combination of all the above-mentioned conditions significantly impacts the yield of barley. The following and relevant findings are very important for the agricultural sector, especially in the context of climate change.