Performance of Portland Limestone Cements: Cements Designed to Be More Sustainable That Include up to 15% Limestone Addition

In 2009, ASTM and AASHTO permitted the use of up to 5% interground limestone in ordinary portland cement (OPC) as a part of ASTM C150/AASHTO M85. When this project was initiated a new proposal was being discussed that would enable up to 15% interground limestone to be considered in ASTM C595/AASHTO M234 cement. This project was initiated to provide rapid feedback to INDOT for use in discussions regarding these specifications (this has become ASTM C595/AASHTO M240). PLC is designed to enable more sustainable construction which may significantly reduce the CO2 that is embodied in the built infrastructure while extending the life of cement quarries. The physical and chemical properties of the cementitious materials used in this study were examined. PLC is typically a finer cement (10 to 30% Blaine fineness) with a reduction in the coarse clinker particles (\u3e20µm) and an increase in fine particles which are primarily limestone. Isothermal calorimetry and chemical shrinkage results imply that these PLC materials have a similar or slight greater reaction and would be able to be used interchangeably with OPC in practice as it relates to the rate of reaction. The PLC mortars exhibited relatively similar activation energies compared to the corresponding OPCs allowing the maturity method to be used by INDOT for both the PLC and OPC systems. The mechanical properties of OPC and PLC were generally similar with the PLC typically having slightly higher early age strengths but similar 28 day strengths. No significant change in drying shrinkage or restrained shrinkage cracking was observed for the PLC when compared with OPC (Barrett et al. 2013). The PLC has similar volumes of permeable voids as the OPC. The chloride diffusion coefficients in the PLC systems may range from 0 to 30% higher than the OPCs. The PLC showed synergistic benefits when paired with fly ash. Based on the available literature and available testing results INDOT could consider PLC, as specified in accordance with ASTM C-595/AASHTO M 240, to be a suitable option for use in INDOT concrete applications

dbOGAP - An Integrated Bioinformatics Resource for Protein O-GlcNAcylation

<p>Abstract</p> <p>Background</p> <p>Protein O-GlcNAcylation (or O-GlcNAc-ylation) is an O-linked glycosylation involving the transfer of β-<it>N</it>-acetylglucosamine to the hydroxyl group of serine or threonine residues of proteins. Growing evidences suggest that protein O-GlcNAcylation is common and is analogous to phosphorylation in modulating broad ranges of biological processes. However, compared to phosphorylation, the amount of protein O-GlcNAcylation data is relatively limited and its annotation in databases is scarce. Furthermore, a bioinformatics resource for O-GlcNAcylation is lacking, and an O-GlcNAcylation site prediction tool is much needed.</p> <p>Description</p> <p>We developed a database of O-GlcNAcylated proteins and sites, dbOGAP, primarily based on literature published since O-GlcNAcylation was first described in 1984. The database currently contains ~800 proteins with experimental O-GlcNAcylation information, of which ~61% are of humans, and 172 proteins have a total of ~400 O-GlcNAcylation sites identified. The O-GlcNAcylated proteins are primarily nucleocytoplasmic, including membrane- and non-membrane bounded organelle-associated proteins. The known O-GlcNAcylated proteins exert a broad range of functions including transcriptional regulation, macromolecular complex assembly, intracellular transport, translation, and regulation of cell growth or death. The database also contains ~365 potential O-GlcNAcylated proteins inferred from known O-GlcNAcylated orthologs. Additional annotations, including other protein posttranslational modifications, biological pathways and disease information are integrated into the database. We developed an O-GlcNAcylation site prediction system, OGlcNAcScan, based on Support Vector Machine and trained using protein sequences with known O-GlcNAcylation sites from dbOGAP. The site prediction system achieved an area under ROC curve of 74.3% in five-fold cross-validation. The dbOGAP website was developed to allow for performing search and query on O-GlcNAcylated proteins and associated literature, as well as for browsing by gene names, organisms or pathways, and downloading of the database. Also available from the website, the OGlcNAcScan tool presents a list of predicted O-GlcNAcylation sites for given protein sequences.</p> <p>Conclusions</p> <p>dbOGAP is the first public bioinformatics resource to allow systematic access to the O-GlcNAcylated proteins, and related functional information and bibliography, as well as to an O-GlcNAcylation site prediction tool. The resource will facilitate research on O-GlcNAcylation and its proteomic identification.</p

Automatic Uncovering of Patient Primary Concerns in Portal Messages Using a Fusion Framework of Pretrained Language models.automatic Uncovering of Patient Primary Concerns in Portal Messages Using a Fusion Framework of Pretrained Language Models

OBJECTIVES: The surge in patient portal messages (PPMs) with increasing needs and workloads for efficient PPM triage in healthcare settings has spurred the exploration of AI-driven solutions to streamline the healthcare workflow processes, ensuring timely responses to patients to satisfy their healthcare needs. However, there has been less focus on isolating and understanding patient primary concerns in PPMs-a practice which holds the potential to yield more nuanced insights and enhances the quality of healthcare delivery and patient-centered care. MATERIALS AND METHODS: We propose a fusion framework to leverage pretrained language models (LMs) with different language advantages via a Convolution Neural Network for precise identification of patient primary concerns via multi-class classification. We examined 3 traditional machine learning models, 9 BERT-based language models, 6 fusion models, and 2 ensemble models. RESULTS: The outcomes of our experimentation underscore the superior performance achieved by BERT-based models in comparison to traditional machine learning models. Remarkably, our fusion model emerges as the top-performing solution, delivering a notably improved accuracy score of 77.67 ± 2.74% and an F1 score of 74.37 ± 3.70% in macro-average. DISCUSSION: This study highlights the feasibility and effectiveness of multi-class classification for patient primary concern detection and the proposed fusion framework for enhancing primary concern detection. CONCLUSIONS: The use of multi-class classification enhanced by a fusion of multiple pretrained LMs not only improves the accuracy and efficiency of patient primary concern identification in PPMs but also aids in managing the rising volume of PPMs in healthcare, ensuring critical patient communications are addressed promptly and accurately

Retrospective content analysis of consumer product reviews related to chronic pain

Chronic pain (CP) lasts for more than 3 months, causing prolonged physical and mental burdens to patients. According to the US Centers for Disease Control and Prevention, CP contributes to more than 500 billion US dollars yearly in direct medical cost plus the associated productivity loss. CP is complex in etiology and can occur anywhere in the body, making it difficult to treat and manage. There is a pressing need for research to better summarize the common health issues faced by consumers living with CP and their experience in accessing over-the-counter analgesics or therapeutic devices. Modern online shopping platforms offer a broad array of opportunities for the secondary use of consumer-generated data in CP research. In this study, we performed an exploratory data mining study that analyzed CP-related Amazon product reviews. Our descriptive analyses characterized the review language, the reviewed products, the representative topics, and the network of comorbidities mentioned in the reviews. The results indicated that most of the reviews were concise yet rich in terms of representing the various health issues faced by people with CP. Despite the noise in the online reviews, we see potential in leveraging the data to capture certain consumer-reported outcomes or to identify shortcomings of the available products

Examine the species and beam-energy dependence of particle spectra using Tsallis Statistics

Tsallis Statistics was used to investigate the non-Boltzmann distribution of particle spectra and their dependence on particle species and beam energy in the relativistic heavy-ion collisions at SPS and RHIC. Produced particles are assumed to acquire radial flow and be of non-extensive statistics at freeze-out. J/psi and the particles containing strangeness were examined separately to study their radial flow and freeze-out. We found that the strange hadrons approach equilibrium quickly from peripheral to central A+A collisions and they tend to decouple earlier from the system than the light hadrons but with the same final radial flow. These results provide an alternative picture of freeze-outs: a thermalized system is produced at partonic phase; the hadronic scattering at later stage is not enough to maintain the system in equilibrium and does not increase the radial flow of the copiously produced light hadrons. The J/psi in Pb+Pb collisions at SPS is consistent with early decoupling and obtains little radial flow. The J/psi spectra at RHIC are also inconsistent with the bulk flow profile.Comment: 12 pages, 4 figures, added several references and some clarifications et

A common type system for clinical natural language processing

Background: One challenge in reusing clinical data stored in electronic medical records is that these data are heterogenous. Clinical Natural Language Processing (NLP) plays an important role in transforming information in clinical text to a standard representation that is comparable and interoperable. Information may be processed and shared when a type system specifies the allowable data structures. Therefore, we aim to define a common type system for clinical NLP that enables interoperability between structured and unstructured data generated in different clinical settings. Results: We describe a common type system for clinical NLP that has an end target of deep semantics based on Clinical Element Models (CEMs), thus interoperating with structured data and accommodating diverse NLP approaches. The type system has been implemented in UIMA (Unstructured Information Management Architecture) and is fully functional in a popular open-source clinical NLP system, cTAKES (clinical Text Analysis and Knowledge Extraction System) versions 2.0 and later. Conclusions: We have created a type system that targets deep semantics, thereby allowing for NLP systems to encapsulate knowledge from text and share it alongside heterogenous clinical data sources. Rather than surface semantics that are typically the end product of NLP algorithms, CEM-based semantics explicitly build in deep clinical semantics as the point of interoperability with more structured data types

THETA-rhythm makes the world go round:dissociative effects of TMS theta versus alpha entrainment of right pTPJ on embodied perspective transformations

Being able to imagine another person's experience and perspective of the world is a crucial human ability and recent reports suggest that humans "embody" another's viewpoint by mentally rotating their own body representation into the other's orientation. Our recent Magnetoencephalography (MEG) data further confirmed this notion of embodied perspective transformations and pinpointed the right posterior temporo-parietal junction (pTPJ) as the crucial hub in a distributed network oscillating at theta frequency (3-7 Hz). In a subsequent transcranial magnetic stimulation (TMS) experiment we interfered with right pTPJ processing and observed a modulation of the embodied aspects of perspective transformations. While these results corroborated the role of right pTPJ, the notion of theta oscillations being the crucial neural code remained a correlational observation based on our MEG data. In the current study we therefore set out to confirm the importance of theta oscillations directly by means of TMS entrainment. We compared entrainment of right pTPJ at 6 Hz vs. 10 Hz and confirmed that only 6 Hz entrainment facilitated embodied perspective transformations (at 160° angular disparity) while 10 Hz slowed it down. The reverse was true at low angular disparity (60° between egocentric and target perspective) where a perspective transformation was not strictly necessary. Our results further corroborate right pTPJ involvement in embodied perspective transformations and highlight theta oscillations as a crucial neural code

Overview of BioCreative II gene normalization

Background: The goal of the gene normalization task is to link genes or gene products mentioned in the literature to biological databases. This is a key step in an accurate search of the biological literature. It is a challenging task, even for the human expert; genes are often described rather than referred to by gene symbol and, confusingly, one gene name may refer to different genes (often from different organisms). For BioCreative II, the task was to list the Entrez Gene identifiers for human genes or gene products mentioned in PubMed/MEDLINE abstracts. We selected abstracts associated with articles previously curated for human genes. We provided 281 expert-annotated abstracts containing 684 gene identifiers for training, and a blind test set of 262 documents containing 785 identifiers, with a gold standard created by expert annotators. Inter-annotator agreement was measured at over 90%. Results: Twenty groups submitted one to three runs each, for a total of 54 runs. Three systems achieved F-measures (balanced precision and recall) between 0.80 and 0.81. Combining the system outputs using simple voting schemes and classifiers obtained improved results; the best composite system achieved an F-measure of 0.92 with 10-fold cross-validation. A 'maximum recall' system based on the pooled responses of all participants gave a recall of 0.97 (with precision 0.23), identifying 763 out of 785 identifiers. Conclusion: Major advances for the BioCreative II gene normalization task include broader participation (20 versus 8 teams) and a pooled system performance comparable to human experts, at over 90% agreement. These results show promise as tools to link the literature with biological databases