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In recent years, United States federal funding agencies, including the National Institutes of Health (NIH) and the National Science Foundation (NSF), have implemented public access policies to make research supported by funding from these federal agencies freely available to the public. Enforcement is primarily through annual and final reports submitted to these funding agencies, where all peer-reviewed publications must be registered through the appropriate mechanism as required by the specific federal funding agency. Unreported and/or incorrectly reported papers can result in delayed acceptance of annual and final reports and even funding delays for current and new research grants. So, it's important to make sure every peer-reviewed publication is reported properly and in a timely manner. For large collaborative research efforts, the tracking and proper registration of peer-reviewed publications along with generation of accurate annual and final reports can create a large administrative burden. With large collaborative teams, it is easy for these administrative tasks to be overlooked, forgotten, or lost in the shuffle. In order to help with this reporting burden, we have developed the Academic Tracker software package, implemented in the Python 3 programming language and supporting Linux, Windows, and Mac operating systems. Academic Tracker helps with publication tracking and reporting by comprehensively searching major peer-reviewed publication tracking web portals, including PubMed, Crossref, ORCID, and Google Scholar, given a list of authors. Academic Tracker provides highly customizable reporting templates so information about the resulting publications is easily transformed into appropriate formats for tracking and reporting purposes. The source code and extensive documentation is hosted on GitHub (https://moseleybioinformaticslab.github.io/academic%5ftracker/) and is also available on the Python Package Index (https://pypi.org/project/academic%5ftracker) for easy installation. [ABSTRACT FROM AUTHOR]

The article presents a study which examined the role of primary somatosensory cortex in touch-induced mechanical and heat analgesia. Topics discussed include effect of reafferent signals from self-generated whisking on facial nociception, the activation of somatosensory barrel cortex (S1B) by noxious stimuli, and analysis of the effect of whisking on activity of individual S1B L2/3 neurons in response to noxious stimuli.

The risk of significant Kirkendall voiding within the intermetallic bond between a conventional solder joint and an electroplated Cu pad is relatively low and directly related to the presence of certain impurities in the latter. However, while the Cu–Sn reaction has been thoroughly studied so far, there is very limited understanding of the impact of space confinement on the Cu/solder interface dynamics. While no voiding has been found in micro joints on high-purity Cu, the propensity for voiding in the Cu3Sn is higher in such joints than in Ball Grid Array scale (macro) joints for a given quality of electroplated Cu. Systematic trends are also somewhat different. In general, the intermetallic compound growth rate varies with interactions between solder volume to pad area ratio, solder composition, pad finish, initial assembly process parameters, subsequent heat treatments, and specifics of the further thermomechanical history. Notably, when the solder is thin enough, the Cu3Sn growth rate is much higher than for thicker configurations and this is what leads to a substantial increase of the risk of severe voiding in micro joints. A mechanistic understanding leads to strategies for electroplating of Cu with low voiding propensity for use in micro solder joints. [ABSTRACT FROM AUTHOR]