High level cognitive information processing in neural networks

Two related research efforts were addressed: (1) high-level connectionist cognitive modeling; and (2) local neural circuit modeling. The goals of the first effort were to develop connectionist models of high-level cognitive processes such as problem solving or natural language understanding, and to understand the computational requirements of such models. The goals of the second effort were to develop biologically-realistic model of local neural circuits, and to understand the computational behavior of such models. In keeping with the nature of NASA's Innovative Research Program, all the work conducted under the grant was highly innovative. For instance, the following ideas, all summarized, are contributions to the study of connectionist/neural networks: (1) the temporal-winner-take-all, relative-position encoding, and pattern-similarity association techniques; (2) the importation of logical combinators into connection; (3) the use of analogy-based reasoning as a bridge across the gap between the traditional symbolic paradigm and the connectionist paradigm; and (4) the application of connectionism to the domain of belief representation/reasoning. The work on local neural circuit modeling also departs significantly from the work of related researchers. In particular, its concentration on low-level neural phenomena that could support high-level cognitive processing is unusual within the area of biological local circuit modeling, and also serves to expand the horizons of the artificial neural net field

Spatial Database For Intersections

Deciding which intersections in the state of Kentucky warrant safety improvements requires a comprehensive inventory with information on every intersection in the public roadway network. The Kentucky Transportation Cabinet (KYTC) had previously catalogued only those intersections where state-maintained roadways met. However, this inventory did not account for intersections between state- and locally-maintained routes, nor was it designed to accommodate regular updates. As such, the Kentucky Transportation Center (KTC) at the University of Kentucky developed a methodology to create and maintain a full inventory of every intersection in the state. The database contains precise location information as well as several safety and operational attributes for each point of an intersection. By replicating the topology factors used in the Highway Safety Manual (HSM), the research team categorized every intersection type, and developed. Safety Performance Functions (SPF) for each intersection type. The SPFs were used to rank each intersection. It is anticipated that this project’s deliverables will be used to increase KYTC’s ability to effectively allocate funds to maintain and improve intersection safety. Making the database available to expert users will allow continuous improvements. In the future, AADT data and traffic control information could be included

Kentucky Traffic Collision Facts 2019

KENTUCKY’S TRAFFIC COLLISION FACTS report is based on collision reports submitted to the Kentucky State Police Records Branch. As required by Kentucky Revised Statutes 189.635: “Every law enforcement agency whose officers investigate a vehicle accident of which a report must be made...shall file a report of the accident...within ten days after investigation of the accident upon forms supplied by the bureau.” The stated purpose of this requirement is to utilize data on traffic collisions for such purposes as will improve the traffic safety program in the Commonwealth

Analysis of Traffic Crash Data in Kentucky 2015-2019

Executive Summary and Introduction This report documents an analysis of traffic crash data in Kentucky. A primary objective of this study was to determine average crash statistics for Kentucky highways. Where used, rates were calculated for various types of highways and for counties and cities. Difference criteria were used for exposure. Average and critical numbers, SPFs, and rates of crashes were calculated for various types of highways in rural and urban areas. These use crashes identified on highways where Annual Average Daily Traffic (AADT) volumes were available. The data in this report may be used to help identify problem areas. The other primary objective of this study was to provide data that can be used in the preparation of the problem identification portion of Kentucky’s Annual Highway Safety Plan (HSP). Crash statistics were analyzed and a summary of results and recommendations in several problem identification areas is presented. These general areas include; alcohol involvement, occupant protection, speed, teenage drivers, pedestrians, bicycles, motorcycles, trucks, and vehicle defects. Other areas included in the analysis for which specific recommendations were not made include, school bus crashes and train crashes. The crash data are stored in the Collision Report Analysis for Safer Highways (CRASH) database. This database is updated daily so the number of crashes in a given calendar year will continue to change for a substantial time after the end of that year. KTC captures an extract annually for analysis. Annual reports have previously been prepared since 1978 dealing with the calculation of statewide traffic crash rates for Kentucky and preparation of the problem identification portion of Kentucky’s Annual Highway Safety Plan. Traffic crash data for a five-year period were used in the preparation of this report. Kentucky has a systematic procedure to identify locations that have had abnormal rates or numbers of traffic crashes. However, before that procedure may be utilized, average crash rates and numbers must be determined for appropriate highway categories and for rural and urban areas. A primary objective of this study was to determine average traffic crash statistics for Kentucky. Those statistics may then be used in the high-crash location identification program to identify locations that should be investigated to determine whether changes should be made. A highway safety program is prepared each year for Kentucky in order to comply with Section 402, Title 23 of the United States Code. This program includes the identification, programming, budgeting, and evaluation of safety projects with the objective of reducing the number and severity of traffic crashes. The second major objective of this report is to provide data that may be included as the problem identification portion of Kentucky’s Annual Highway Safety Plan. Results from this report are used to provide benchmark data for that process

GRP94 (gp96) and GRP94 N-Terminal Geldanamycin Binding Domain Elicit Tissue Nonrestricted Tumor Suppression

In chemical carcinogenesis models, GRP94 (gp96) elicits tumor-specific protective immunity. The tumor specificity of this response is thought to reflect immune responses to GRP94-bound peptide antigens, the cohort of which uniquely identifies the GRP94 tissue of origin. In this study, we examined the apparent tissue restriction of GRP94-elicited protective immunity in a 4T1 mammary carcinoma model. We report that the vaccination of BALB/c mice with irradiated fibroblasts expressing a secretory form of GRP94 markedly suppressed 4T1 tumor growth and metastasis. In addition, vaccination with irradiated cells secreting the GRP94 NH2-terminal geldanamycin-binding domain (NTD), a region lacking canonical peptide-binding motifs, yielded a similar suppression of tumor growth and metastatic progression. Conditioned media from cultures of GRP94 or GRP94 NTD-secreting fibroblasts elicited the up-regulation of major histocompatibility complex class II and CD86 in dendritic cell cultures, consistent with a natural adjuvant function for GRP94 and the GRP94 NTD. Based on these findings, we propose that GRP94-elicited tumor suppression can occur independent of the GRP94 tissue of origin and suggest a primary role for GRP4 natural adjuvant function in antitumor immune responses

Precision delivery of RAS-inhibiting siRNA to KRAS driven cancer via peptide-based nanoparticles

Over 95% of pancreatic adenocarcinomas (PDACs), as well as a large fraction of other tumor types, such as colorectal adenocarcinoma, are driven by KRAS activation. However, no direct RAS inhibitors exist for cancer therapy. Furthermore, the delivery of therapeutic agents of any kind to PDAC in particular has been hindered by the extensive desmoplasia and resultant drug delivery challenges that accompanies these tumors. Small interfering RNA (siRNA) is a promising modality for anti-neoplastic therapy due to its precision and wide range of potential therapeutic targets. Unfortunately, siRNA therapy is limited by low serum half-life, vulnerability to intracellular digestion, and transient therapeutic effect. We assessed the ability of a peptide based, oligonucleotide condensing, endosomolytic nanoparticle (NP) system to deliver siRNA to KRAS-driven cancers. We show that this peptide-based NP is avidly taken up by cancer cell

Braveheart, a Long Noncoding RNA Required for Cardiovascular Lineage Commitment

Long noncoding RNAs (lncRNAs) are often expressed in a development-specific manner, yet little is known about their roles in lineage commitment. Here, we identified Braveheart (Bvht), a heart-associated lncRNA in mouse. Using multiple embryonic stem cell (ESC) differentiation strategies, we show that Bvht is required for progression of nascent mesoderm toward a cardiac fate. We find that Bvht is necessary for activation of a core cardiovascular gene network and functions upstream of mesoderm posterior 1 (MesP1), a master regulator of a common multipotent cardiovascular progenitor. We also show that Bvht interacts with SUZ12, a component of polycomb-repressive complex 2 (PRC2), during cardiomyocyte differentiation, suggesting that Bvht mediates epigenetic regulation of cardiac commitment. Finally, we demonstrate a role for Bvht in maintaining cardiac fate in neonatal cardiomyocytes. Together, our work provides evidence for a long noncoding RNA with critical roles in the establishment of the cardiovascular lineage during mammalian development.Damon Runyon Cancer Research Foundation (DRG 2032-09)Damon Runyon Cancer Research Foundation (DFS 04-12)European Molecular Biology Organization (Long-term Fellowship)National Heart, Lung, and Blood Institute. Bench to Bassinet Program (U01HL098179)National Heart, Lung, and Blood Institute. Bench to Bassinet Program (U01HL098188)Smith Family FoundationPew Charitable Trusts. Program in the Biomedical Science

BOSC 2019, the 20th annual Bioinformatics Open Source Conference.

The Bioinformatics Open Source Conference is a volunteer-organized meeting that covers open source software development and open science in bioinformatics. Launched in 2000, BOSC has been held every year since. BOSC 2019, the 20th annual BOSC, took place as one of the Communities of Special Interest (COSIs) at the Intelligent Systems for Molecular Biology meeting (ISMB/ECCB 2019). The two-day meeting included a total of 46 talks and 55 posters, as well as eight Birds of a Feather interest groups. The keynote speaker was University of Cape Town professor Dr. Nicola Mulder, who spoke on "Building infrastructure for responsible open science in Africa". Immediately after BOSC 2019, about 50 people participated in the two-day CollaborationFest (CoFest for short), an open and free community-driven event at which participants work together to contribute to bioinformatics software, documentation, training materials, and use cases