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Operations on high-dimensional, fixed-width vectors can be used to distribute information from several vectors over a single vector of the same width. For example, a set of key-value pairs can be encoded into a single vector with multiplication and addition of the corresponding key and value vectors: the keys are bound to their values with component-wise multiplication, and the key-value pairs are combined into a single superposition vector with component-wise addition. The superposition vector is, thus, a memory which can then be queried for the value of any of the keys, but the result of the query is approximate. The exact vector is retrieved from a codebook (a.k.a. item memory), which contains vectors defined in the system. To perform these operations, the item memory vectors and the superposition vector must be the same width. Increasing the capacity of the memory requires increasing the width of the superposition and item memory vectors. In this article, we demonstrate that in a regime where many (e.g., 1,000 or more) key-value pairs are stored, an associative memory which maps key vectors to value vectors requires less memory and less computing to obtain the same reliability of storage as a superposition vector. These advantages are obtained because the number of storage locations in an associate memory can be increased without increasing the width of the vectors in the item memory. An associative memory would not replace a superposition vector as a medium of storage, but could augment it, because data recalled from an associative memory could be used in algorithms that use a superposition vector. This would be analogous to how human working memory (which stores about seven items) uses information recalled from long-term memory (which is much larger than the working memory). We demonstrate the advantages of an associative memory experimentally using the storage of large finite-state automata, which could model the storage and recall of state-dependent behavior by brains., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Teeters, Kleyko, Kanerva and Olshausen.)

The Neurodata Without Borders (abbreviation NWB) format is a current technology for storing neurophysiology data along with the associated metadata. Data stored in the format is organized into separate HDF5 files, each file usually storing the data associated with a single recording session. While the NWB format provides a structured method for storing data, so far there have not been tools which enable searching a collection of NWB files in order to find data of interest for a particular purpose. We describe here three tools to enable searching NWB files. The tools have different features making each of them most useful for a particular task. The first tool, called the NWB Query Engine, is written in Java. It allows searching the complete content of NWB files. It was designed for the first version of NWB (NWB 1) and supports most (but not all) features of the most recent version (NWB 2). For some searches, it is the fastest tool. The second tool, called "search_nwb" is written in Python and also allow searching the complete contents of NWB files. It works with both NWB 1 and NWB 2, as does the third tool. The third tool, called "nwbindexer" enables searching a collection of NWB files using a two-step process. In the first step, a utility is run which creates an SQLite database containing the metadata in a collection of NWB files. This database is then searched in the second step, using another utility. Once the index is built, this two-step processes allows faster searches than are done by the other tools, but does not enable as complete of searches. All three tools use a simple query language which was developed for this project. Software integrating the three tools into a web-interface is provided which enables searching NWB files by submitting a web form., (Copyright © 2020 Ježek, Teeters and Sommer.)

The Neurodata Without Borders (NWB) initiative promotes data standardization in neuroscience to increase research reproducibility and opportunities. In the first NWB pilot project, neurophysiologists and software developers produced a common data format for recordings and metadata of cellular electrophysiology and optical imaging experiments. The format specification, application programming interfaces, and sample datasets have been released., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Objective: To examine the factors impacting postgraduate year 1 (PGY1) residents' self-perceived readiness for residency., Methods: A total of 1801 residents who matched in American Society of Health-System Pharmacists (ASHP)-accredited PGY1 programs were e-mailed individualized invitations to take an online survey. The survey collected self-ratings of readiness for residency training competencies including time management and organization, foundational knowledge, clinical practice, project management, and communication., Key Findings: Data from 556 completed surveys were analyzed. Residents agreed they were ready to perform activities requiring time management and organization (median = 4, mean = 4.08), foundational knowledge (median = 4, mean = 3.83), clinical practice (median = 4, mean = 3.67), and communication (median = 4, mean = 4.05). Residents who completed at least 1 academic advance pharmacy practice experience (APPE), 5 clinical APPEs, or held a bachelors degree felt more confident than their counterparts in regard to project management (P < .001, <.001, and .01, respectively)., Conclusion: PGY1 residents generally felt prepared for time management and organization, foundational knowledge, and communication residency training competencies. This was significant for those who completed 1 or more academic APPEs, 5 or more clinical rotations, or a bachelors degree. Study results may assist pharmacy schools in preparing students for residency training, prospective resident applicants in becoming more competitive candidates for residency programs, and residency program directors in resident selection., (© The Author(s) 2014.)

Purpose: The results of a survey to identify personnel time, funding, and other resources used to support existing postgraduate year 1 (PGY1) pharmacy residencies and to determine potential residency program expansion are reported., Methods: An electronic survey was distributed to PGY1 residency program directors (RPDs). Respondents were asked to provide demographic information and to characterize resources used to support their training programs., Results: The survey response rate was 62%, representing 493 respondents. About 21% indicated their formal job descriptions identified them as a PGY1 RPD, and 8% replied that time expectations to perform the residency functions were specified. Up to 69% of respondents estimated that the time spent performing residency functions was 5-16 hours weekly. Other personnel who facilitated pharmacy residency logistics included administrative assistants, coordinators, and pharmacists, devoting approximately 1-8 hours weekly to the residency program. Half of respondents indicated their PGY1 programs received funding through the Centers for Medicare and Medicaid Services (CMS) pass-through reimbursement; 30% were not eligible, 11% had not considered such reimbursement due to the amount of work required, and 9% did not know if their sites received such funding., Conclusion: A survey of PGY1 RPDs collected a wide range of information about the resources used to support their programs and about future plans. Almost half of respondents anticipated expanding their PGY1 residency program capacity, and responses made it clear that adequate documentation was important for programs applying for CMS pass-through reimbursement and facing an audit.

An internal chart review of warfarin patients revealed a 44 percent complication rate resulting in higher treatment costs, and identified patient noncompliance, access to monitoring, and insufficient patient education as contributing factors. A warfarin usage guideline was created to assist physicians with warfarin management and subsequently the Anticoagulation Center (ACC) was established. To date over 950 patients have been managed through the ACC with therapeutic international normalized ratios an average of 82 percent of the time. Fewer bleeds and treatment failures have occurred in the ACC group, and a patient satisfaction survey revealed that ACC patients were very satisfied with their care more often than non-ACC patients.

Background: This article describes how the Pharmacy and Therapeutics Committee at Lutheran General Hospital (Park Ridge, IL) formed a continuous quality improvement (CQI) team and used statistical process control (SPC) tools to assess efforts to reduce medication errors., Methods: The team worked with the nursing quality council to develop an intravenous (IV) training module for nurses that effectively decreased the average number of errors per month. The article illustrates the effective use of a run chart, a Pareto chart, and two types of control charts (p-charts and np-charts) to identify an opportunity for improvement, develop an improvement strategy, and measure the effectiveness of the intervention., Conclusion: Lessons learned from this case include the following: 1) Although run charts can be used as a preliminary step to determine whether a process has common-cause or special-cause variation, p-charts or np-charts are more precise tools for identifying special causes and for measuring the impact of interventions; 2) Pareto charts are useful for focusing on the areas of a process that will have the greatest impact in achieving the desired results; 3) When p-charts show little variation in control limits from month to month, the np-chart is an appropriate and more user-friendly alternative; and 4) In addition to validating the overall effectiveness of the intervention, the np-chart also helped to identify where the intervention failed.

Teeters and Arbib presented a model of the anuran retina which qualitatively accounts for the characteristic response properties used to distinguish ganglion cell type in anurans. In this paper we test the model's ability to reproduce quantitatively tabulated data on the dependency on stimulus shape and size, with a new implementation of the model in the neural simulation language NSL. Data of Ewert and Hock relating toad R2, R3, and R4 ganglion cell responses to moving worm, antiworm, and square-shaped stimuli of various edge lengths are used to test stimulus shape and size dependency. A close match to the data can be achieved by tuning some of the model parameters while still retaining the characteristic responses to the typical stimulus types. We stress here the importance of a populational approach to the models. We place more emphasis on the variation of response properties in a population of neurons of the same class, rather than questing for the neuron of a given type. As an example of the populational approach we offer a model for the respiratory R3 response following researchers who argue that a subclass of R3 neurons are activated by stationary boundaries owing to the anuran's self induced respiratory eye movement.

A model is presented which accounts for many characteristic response properties used to classify anuran ganglion cell types while being consistent with data concerning interneurons. In the model color is ignored and input stimuli are assumed to be only black and white at high contrast. We show that accurate ganglion cell responses are obtained even with simplified receptors and horizontal cells: Receptors are modeled as responding with a step change, while horizontal cells respond only to global changes in intensity brought about by full field illumination changes. A hyperpolarizing and depolarizing bipolar cell are generated by subtracting local receptor and horizontal potentials. Two transient amacrine cells (On and Off) are generated using a high-pass filter like mechanism with a thresholded output which responds to positive going changes in the corresponding bipolar cell potentials. The model shows how a selective combination of bipolar and amacrine channels can account for many of the response properties used to classify the anuran ganglion cell types (class-0 through 4) and makes several experimental predictions.