BACKGROUND: The vertical jump can be analyzed based on the flight time achieved by the individual. This measurement can be obtained using a force platform or a three-dimensional infrared camera system, but such equipment is expensive and requires training for data collection and processing. Thus, this study aimed to evaluate the accuracy and reliability of using a smartphone and the Kinovea software compared with a force platform as a method of vertical jump analysis.
METHODS: For this purpose, two independent evaluators analyzed videos of bipodal and unipodal vertical jumps by counting the variables among participants. The participants performed three consecutive jumps in bipodal and unipodal conditions with the dominant and non-dominant legs.
RESULTS: The intra-rater analysis for bipodal jumps was found to have excellent reproducibility (ICC = 0.903 to 0.934), whereas for unipodal jumps, the reproducibility was moderate to excellent (ICC = 0.713 to 0.902). The inter-rater analysis showed that for bipodal jumps, the reproducibility is substantial to excellent (ICC = 0.823 to 0.926), while for unipodal jumps, it is moderate (ICC = 0.554 to 0.702).
CONCLUSIONS: Therefore, it can be concluded that the vertical jump evaluation can be performed using the smartphone-Kinovea system. However, the same evaluator should carry out the evaluation to maintain reliable indices.

When evaluating the impact of environmental exposures on human health, study designs often include a series of repeated measurements. The goal is to determine whether populations have different trajectories of the environmental exposure over time. Power analyses for longitudinal mixed models require multiple inputs, including clinically significant differences, standard deviations, and correlations of measurements. Further, methods for power analyses of longitudinal mixed models are complex and often challenging for the non-statistician. We discuss methods for extracting clinically relevant inputs from literature, and explain how to conduct a power analysis that appropriately accounts for longitudinal repeated measures. Finally, we provide careful recommendations for describing complex power analyses in a concise and clear manner.
For longitudinal studies of health outcomes from environmental exposures, we show how to [1] conduct a power analysis that aligns with the planned mixed model data analysis, [2] gather the inputs required for the power analysis, and [3] conduct repeated measures power analysis with a highly-cited, validated, free, point-and-click, web-based, open source software platform which was developed specifically for scientists.
As an example, we describe the power analysis for a proposed study of repeated measures of per- and polyfluoroalkyl substances (PFAS) in human blood. We show how to align data analysis and power analysis plan to account for within-participant correlation across repeated measures. We illustrate how to perform a literature review to find inputs for the power analysis. We emphasize the need to examine the sensitivity of the power values by considering standard deviations and differences in means that are smaller and larger than the speculated, literature-based values. Finally, we provide an example power calculation and a summary checklist for describing power and sample size analysis.
This paper provides a detailed roadmap for conducting and describing power analyses for longitudinal studies of environmental exposures. It provides a template and checklist for those seeking to write power analyses for grant applications.

UNASSIGNED: Considering the need for daily activity analysis of older adults, development of easy-to-use, free electroencephalogram (EEG) analysis tools are desired in order to decrease barriers to accessing this technology and increase the entry of a wide range of new researchers.
UNASSIGNED: We describe a newly developed tool set for EEG analysis, enabling import, average, waveform display and iso-potential scalp topographies, utilizing the programming language Perl.
UNASSIGNED: The basic processing, including average, display waveforms, and isopotential scalp topography was implemented in the current system. The validation was examined by making difference waveforms between the results using the current analysis system and a commercial software.Comparison with Existing Method(s): The current software tool set consists of free software. The scripts are easily editable by any user and there are no black boxes.
UNASSIGNED: The currently reported procedures provide an easy-to-begin, flexible, readable, easy-to-modify basic tool set for EEG analysis and is expected to recruit new EEG researchers.

The purpose of this technical note is to illustrate a simple and economical preoperative method for preshaping a reconstructive titanium plate in a fibula free flap (FFF) by using 3D printing of a virtually reconstructed mandible haptic model. The whole process consisted in creating a 3D model of the patient\'s mandible based on a CT-scan using a combination of free software (3Dslicer and ITK-snap), and simulating the surgical osteotomies and reconstruction, and print it as a guide for bending a reconstruction titanium plate. Reconstruction is performed using virtual cubes (1 to 3 cubes, according the number of FFF osteotomies). This virtual lab work is performed using 3D Builder® (Microsoft, Redmond) software. This technique allows obtaining an optimal plate application on the bony fragments. It facilitates reconstructive surgery with good functional (putting the patient back in an optimal dental occlusion based on the native maxilla) and aesthetic results. This technical note presents a simple and economical preoperative fabrication of a reconstructive plate through freeware and a low-cost 3D printer accessible to all surgeons.

The cross-sectional geometry (CSG) of long bone diaphyses is used in bioanthropology to evaluate their resistance to biomechanical constraints and to infer life-history-related patterns such as mobility, activity specialization or intensity, sexual dimorphism, body mass and proportions. First limited by technical analytical constraints to the analysis of one or two cross sections per bone, it has evolved into the analysis of cross sections of the full length of the diaphyseal part of long bones. More recently, researchers have developed analytical tools to map the cortical thickness of entire diaphyses to evaluate locomotor signatures. However, none of these analytical tools are easy to use for scientists who are not familiar with computer programming, and some statistical procedures-such as mapping the correlation coefficients of the diaphyseal thickness with various parameters have yet to be made available. Therefore, we developed an automated and open-source application that renders those analyses (both CSG and cortical thickness) in a semiautomated and user friendly manner. This application, called \"Diaphysator\", is associated with another free software (\"Extractor\", presented in Dupej et al. (2017). American Journal of Physical Anthropology, 164, 868-876). Diaphysator can be used as an online application (https://diaphysator.shinyapps.io/maps) or as a package for R statistical software. Along with the mean maps of cortical thickness and mean CSG parameter graphs, the users can evaluate the correlations and partial correlations of both CSG parameters at every cross section along the diaphyseal length, and cortical thickness data points of the entire diaphysis, with any factor such as age, sex, stature, and body mass.

Mass spectrometry (MS) is one of the most effective techniques for high-throughput, high-resolution characterization of glycan structures. Although many software applications have been developed over the last decades for the interpretation of MS data of glycan structures, only a few are capable of dealing with the large data sets produced by glycomics analysis. Furthermore, these applications utilize databases that can lead to redundant glycan annotations and do not support post-processing of the data within the software or by third party applications. To address the needs, we present GRITS Toolbox, a freely-available, platform-independent software application capable of storing and processing glycomics MS data along with associated metadata. GRITS Toolbox automatically annotates MS data using an integrated glycan identification module that references manually curated databases of mammalian glycans (provided with the software) or any user-defined databases. Extensive display routines are provided to post-process the data and refine the automated annotation using expert knowledge of the user. The software also allows side by side comparison of annotations from different MS runs or samples and exporting of annotations into Excel format.

Intermittent-flow respirometry is widely used to measure oxygen uptake rates and subsequently estimate aerobic metabolic rates of aquatic animals. However, the lack of a standard quality-control software to detect technical problems represents a potential impediment to comparisons across studies in the field of evolutionary and conservation physiology. Here, we introduce \'FishResp\', a versatile R package and its graphical implementation for quality-control and filtering of raw respirometry data. Our goal is to provide a straightforward, cross-platform and free software to help improve the quality and comparability of metabolic rate estimates for reducing methodological fragmentation in the field of aquatic respirometry. FishResp accepts data from various respirometry systems, allows users to detect potential mechanical problems which can occur during oxygen uptake measurements (e.g. chamber leaking, poor water circulation), and offers six options to correct raw data for microbial oxygen consumption. The software performs filtering of raw data based on user criteria, and produces accurate and unbiased estimates of absolute and mass-specific metabolic rates. Using data from three-spined sticklebacks (Gasterosteus aculeatus) and Trinidadian guppies (Poecilia reticulata), we demonstrate the virtues of FishResp, highlighting the importance of detecting mechanical problems and correcting measurements for background respiration.

Mathematical models developed in predictive microbiology are nowadays an essential tool for food scientists and researchers. However, advanced knowledge of scientific programming and mathematical modelling are often required in order to use them, especially in cases of modelling of dynamic and/or non-linear processes. This may be an obstacle for food scientists without such skills. Scientific software can help making these tools more accessible for scientists lacking a deep mathematical or computing background. Recently, the R package bioinactivation was published, including functions (model fitting and predictions) for modelling microbial inactivation under isothermal or dynamic conditions. It was uploaded to the Comprehensive R Archive Network (CRAN), but users need basic R programming knowledge in order to use it. Therefore, it was accompanied by Bioinactivation SE, a user-friendly web application including selected functions in the software for users without a programming background. In this work, a new web application, Bioinactivation FE, is presented. It is an extension of Bioinactivation SE which includes an interface to every function in the bioinactivation package: model fitting of isothermal and non-isothermal experiments, and generation of survivor curves and prediction intervals. Moreover, it includes several improvements in the user interface based on the users\' feedback. The capabilities of the software are demonstrated through two case studies using data published in the scientific literature. In the first case study, the response of Escherichia coli to isothermal and non-isothermal treatments is compared, illustrating the presence of an induced thermal resistance. In the second, the effect of nanoemulsified d-limonene on the thermal resistance of Salmonella Senftenberg is quantified.

The use of the MRI-navigation system ensures accurate targeting of TMS. This, in turn, results in TMS motor mapping becoming a routinely used procedure in neuroscience and neurosurgery. However, currently, there is no standardized methodology for assessment of TMS motor-mapping results. Therefore, we developed TMSmap-free standalone graphical interface software for the quantitative analysis of the TMS motor mapping results (http://tmsmap.ru/). In addition to the estimation of standard parameters (such as the size of cortical muscle representation and the center of gravity location), it allows estimation of the volume of cortical representations, excitability profile of the cortical surface map, and the overlap between cortical representations. The input data for the software includes the coordinates of the coil position (or electric field maximum) and the corresponding response in each stimulation point. TMSmap has been developed for versatile assessment and comparison of TMS maps relating to different experimental interventions including, but not limited to longitudinal, pharmacological and clinical studies (e.g., stroke recovery). To illustrate the use of TMSmap we provide examples of the actual TMS motor-mapping analysis of two healthy subjects and one chronic stroke patient.

Most pathological pain conditions in patients and rodent pain models result in marked alterations in mechanosensation and the gold standard way to measure this is by use of von Frey fibers. These graded monofilaments are used to gauge the level of stimulus-evoked sensitivity present in the affected dermal region. One of the most popular methods used to determine von Frey thresholds is the up-down testing paradigm introduced by Dixon for patients in 1980 and by Chapman and colleagues for rodents in 1994. Although the up-down method is very accurate, leading to its widespread use, defining the 50% threshold from primary data is complex and requires a relatively time-consuming analysis step. We developed a computer program, the Up-Down Reader (UDReader), that can locate and recognize handwritten von Frey assessments from a scanned PDF document and translate these measurements into 50% pain thresholds. Automating the process of obtaining the 50% threshold values negates the need for reference tables or Microsoft Excel formulae and eliminates the chance of a manual calculation error. Our simple and straightforward method is designed to save research time while improving data collection accuracy and is freely available at https://sourceforge.net/projects/updownreader/ or in supplementary files attached to this manuscript.