A prolog implementation of pattern search to optimize software quality assurance

Quality Assurance (QA) is a critical factor in the development of successful software systems. Through the use of various QA tools, project managers can ensure that a desired level of performance and reliability is built into the system. However, these tools are not without cost. Project managers must weight all QA costs and benefits for each development environment before weigh all QA costs and benefits for each development environment before establishing an allocation strategy. The development of a system dynamics model has provided project managers with an automated tool that accurately replicates a project's dynamic behavior. This model can be used to determine the optimal quality assurance distribution pattern over a given project's life cycle. The objective of this thesis was to enhance a prototype expert system module that interacts with the system dynamics model for determining QA effort allocation schemes. The new module uses a pattern search algorithm to derive an optimal distribution scheme from a given set of project parameters. This system not only resolves all limitations discovered in the prototype model but also achieved significant reductions in total project cost.http://archive.org/details/aprologimplement1094530680Lieutenant, United Sstates NavyApproved for public release; distribution is unlimited.Approved for public release; distribution is unlimited

Exploring the Training and Practice Experiences of Male School Counselors

Males are underrepresented as school counselors and may experience stigma associated with being viewed as less masculine, sexual deviants, or unqualified. Despite these aspects, research has shown benefits for school stakeholders based in the diverse perspectives male school counselors can provide. The purpose of this phenomenological qualitative research study was to understand the lived experiences of 25 male school counselors from across the United States. Based on the thematic analysis findings, we will discuss specific implications and recommendations for male school counselor training, supervision, and practice

Guiding the design of well-powered Hi-C experiments to detect differential loops

Motivation: Three-dimensional chromatin structure plays an important role in gene regulation by connecting regulatory regions and gene promoters. The ability to detect the formation and loss of these loops in various cell types and conditions provides valuable information on the mechanisms driving these cell states and is critical for understanding long-range gene regulation. Hi-C is a powerful technique for characterizing 3D chromatin structure; however, Hi-C can quickly become costly and labor-intensive, and proper planning is required to ensure efficient use of time and resources while maintaining experimental rigor and well-powered results. Results: To facilitate better planning and interpretation of human Hi-C experiments, we conducted a detailed evaluation of statistical power using publicly available Hi-C datasets, paying particular attention to the impact of loop size on Hi-C contacts and fold change compression. In addition, we have developed Hi-C Poweraid, a publicly hosted web application to investigate these findings. For experiments involving well-replicated cell lines, we recommend a total sequencing depth of at least 6 billion contacts per condition, split between at least two replicates to achieve the power to detect differences in the majority of loops. For experiments with higher variation, more replicates and deeper sequencing depths are required. Values for specific cases can be determined by using Hi-C Poweraid. This tool simplifies Hi-C power calculations, allowing for more efficient use of time and resources and more accurate interpretation of experimental results. Availability and implementation: Hi-C Poweraid is available as an R Shiny application deployed at http://phanstiel-lab.med.unc.edu/poweraid/, with code available at https://github.com/sarmapar/poweraid

Enhancement of fast scan cyclic voltammetry detection of dopamine with tryptophanmodified electrodes

Fast scan cyclic voltammetry (FSCV) allows for real -time analysis of phasic neurotransmitter levels. Tryptophan (TRP) is an aromatic amino acid responsible for facilitating electron transfer kinetics in oxidoreductase enzymes. Previous work with TRP-modified electrodes showed increased sensitivity for cyclic voltammetry detection of dopamine (DA) when used with slower scan rates (0.05 V/s). Here, we outline an in vitro proof of concept for TRP-modified electrodes in FSCV detection of DA, and decreased sensitivity for ascorbic acid (AA). TRP-modified electrodes had a limit of detection (LOD) for DA of 2.480 ± 0.343 nM compared to 8.348 ± 0.405 nM for an uncoated electrode. Selectivity for DA/ascorbic acid (AA) was 1.107 ± 0.3643 for uncoated and 15.57 ± 4.184 for TRP-modified electrodes. Additionally, these TRP-modified electrodes demonstrated reproducibility when exposed to extended cycling. TRP-modified electrodes will provide an effective modification to increase sensitivity for DA

E-Liquid Autofluorescence can be used as a Marker of Vaping Deposition and Third-Hand Vape Exposure

In the past 5 years, e-cigarette use has been increasing rapidly, particularly in youth and young adults. Due to the novelty of e-cigarettes (e-cigs) and e-cigarette liquids (e-liquids), research on their chemo-physical properties is still in its infancy. Here, we describe a previously unknown and potentially useful property of e-liquids, namely their autofluorescence. We performed an emission scan at 9 excitation wavelengths common to fluorescent microscopy and found (i) that autofluorescence differs widely between e-liquids, (ii) that e-liquids are most fluorescent in the UV range (between 350 and 405 nm) and (iii) fluorescence intensity wanes as the emission wavelength increases. Furthermore, we used the autofluorescence of e-liquids as a marker for tracking e-cig aerosol deposition in the laboratory. Using linear regression analysis, we were able to quantify the deposition of a "vaped" e-liquid onto hard surfaces. Using this technique, we found that every 70 mL puff of an e-cigarette deposited 0.019% e-liquid (v/v) in a controlled environment. Finally, we vaped a surface in the laboratory and used our method to detect e-cig aerosol third-hand exposure. In conclusion, our data suggest that e-cigarette autofluorescence can be used as a marker of e-cigarette deposition

Hot Training Conditions Inhibit Adequate Ad Libitum Recovery Fluid Intake of Runners

International Journal of Exercise Science 12(6): 1322-1333, 2019. This study examined voluntary fluid intake, hydration descriptors, and sweat loss estimation accuracy following runs in wet bulb globe temperatures of 18 (TEMP) and 26 ºC (HOT). Twelve male runners completed 1-h runs at 65% of VO2 max with access to water during runs and a variety of beverages for the following 24-h. Urine specific gravity (USG), body mass, fluid intake, and urine output were assessed at 12 and 24-h. Runners lost 1.355 ± 0.263 and 1.943 ± 0.485 L during TEMP and HOT, respectively. Sweat loss volume was underestimated by approximately one-third during both conditions. Cumulative fluid intake from start until 1-h post-run was greater in HOT, but not at 12-h (2.202±0.600 vs 2.265±0.673 L) or 24-h (3.602±0.807 vs 3.742±1.205 L). Runners replaced a lower percentage of sweat losses and displayed higher USG (p \u3c 0.001) for HOT (119±34%; 1.027±0.004) versus TEMP (166±51%; 1.018±0.004) at 12-h while exhibiting repeatable rehydration patterns within runners (ICC = 0.89) between trials. Absolute body mass was unable to differentiate the substantial differences in fluid replacement percentage. Seven runners replace

The Geometric Osteotomy: Joint Preservation in Juxta-Articular Surface Bone Neoplasms

Purpose. To present the oncologic and functional results of a consecutive series of patients treated by geometric osteotomy and allograft reconstruction for juxta-articular surface bone neoplasms

Bedtoolsr: An R package for genomic data analysis and manipulation.

The sequencing of the human genome and subsequent advances in DNA sequencing technology have created a need for computational tools to analyze and manipulate genomic data sets. The bedtools software suite and the R programming language have emerged as indispensable tools for this purpose but have lacked integration. Here we describe bedtoolsr, an R package that provides simple and intuitive access to all bedtools functions from within the R programming environment. We provide several usability enhancements, support compatibility with past and future versions of bedtools, and include unit tests to ensure stability. bedtoolsr provides a user-focused, harmonious integration of the bedtools software suite with the R programming language that should be of great use to the genomics community

Measuring Thermal Profiles in High Explosives using Neural Networks

We present a new method for calculating the temperature profile in high explosive (HE) material using a Convolutional Neural Network (CNN). To train/test the CNN, we have developed a hybrid experiment/simulation method for collecting acoustic and temperature data. We experimentally heat cylindrical containers of HE material until detonation/deflagration, where we continuously measure the acoustic bursts through the HE using multiple acoustic transducers lined around the exterior container circumference. However, measuring the temperature profile in the HE in experiment would require inserting a high number of thermal probes, which would disrupt the heating process. Thus, we use two thermal probes, one at the HE center and one at the wall. We then use finite element simulation of the heating process to calculate the temperature distribution, and correct the simulated temperatures based on the experimental center and wall temperatures. We calculate temperature errors on the order of 15{\deg}C, which is approximately 12% of the range of temperatures in the experiment. We also investigate how the algorithm accuracy is affected by the number of acoustic receivers used to collect each measurement and the resolution of the temperature prediction. This work provides a means of assessing the safety status of HE material, which cannot be achieved using existing temperature measurement methods. Additionally, it has implications for range of other applications where internal temperature profile measurements would provide critical information. These applications include detecting chemical reactions, observing thermodynamic processes like combustion, monitoring metal or plastic casting, determining the energy density in thermal storage capsules, and identifying abnormal battery operation