Hydrographic and Impairment Statistics (HIS) is a National Park Service (NPS) Water Resources Division (WRD) project established to track certain goals created in response to the Government Performance and Results Act of 1993 (GPRA). One water resources management goal established by the Department of the Interior under GRPA requires NPS to track the percent of its managed surface waters that are meeting Clean Water Act (CWA) water quality standards. This goal requires an accurate inventory that spatially quantifies the surface water hydrography that each bureau manages and a procedure to determine and track which waterbodies are or are not meeting water quality standards as outlined by Section 303(d) of the CWA. This project helps meet this DOI GRPA goal by inventorying and monitoring in a geographic information system for the NPS: (1) CWA 303(d) quality impaired waters and causes; and (2) hydrographic statistics based on the United States Geological Survey (USGS) National Hydrography Dataset (NHD). Hydrographic and 303(d) impairment statistics were evaluated based on a combination of 1:24,000 (NHD) and finer scale data (frequently provided by state GIS layers).

This study seeks to examine important components of our nation's sex offender tracking and monitoring systems, with a focus on risk assessment and sexual recidivism (measured by re-arrest). Data were collected from 1,789 adult sex offenders in the following states. Florida: 500 cases Minnesota: 500 cases New Jersey: 291 cases South Carolina: 498 cases The data file contains another 551 cases from the state of Massachusetts. However, due to how and when those cases were identified they were not included in the Principal Investigator's focus and analysis. There are also another 151 cases where a study participant's state is missing. Total there are 2,491 cases and 1,947 variables.

The ADAM spoken corpus is a collection of 450 spoken dialogues: they are both human-human (200 dialogues) and human-machine (250 dialogues). All the dialogues are recordings and transcriptions of telephone conversations in the semantic domain of tourism and railway transportation. The format of the audio files is the standard format for telephone signal data recommended by the SPEECHDAT3 project directions. Each dialogue is annotated at five levels of linguistic information: prosody, morphosyntax, syntax, semantics and pragmatics. For each level a corresponding annotation scheme has been defined that provides annotation instructions, examples and criteria. The result of each annotation is an XML file that encodes the content of a dialogue with respect to a particular level according to the annotation scheme of that level. The human-human dialogues are simulated telephone conversations between two experimental subjects, playing the roles of a travel agent and of a caller, respectively. The human-machine dialogues were collected on the field: they are interactions between callers and the automatic telephone information service of the Italian railway company, recorded during an experimental phase of that service. Each dialogue in the ADAM corpus is represented by an orthographic transcription (physically an XML file), which in turn is linked to an audio file containing the corresponding recording. In addition, the transcription of each dialogue is associated to five XML annotation files, according to five different levels or layers of linguistic information, namely prosody, morphosyntax, syntax, semantics and pragmatics.

The objective of the Autism Biomarkers Consortium for Clinical Trials (ABC-CT) is to evaluate a set of lab-based behavioral video tracking (VT), electroencephalography (EEG), and eye tracking (ET) measures for use in clinical trials with children with autism spectrum disorder (ASD). Within the larger organizational structure of the ABC-CT, the Data Acquisition and Analytic Core (DAAC) oversees the standardization of VT, EEG, and ET data acquisition, data processing, and data analysis. This includes designing and documenting data acquisition and analytic protocols and manuals; facilitating site training in acquisition; data acquisition quality control (QC); derivation and validation of dependent variables (DVs); and analytic deliverables including preparation of data for submission to the National Database for Autism Research (NDAR). To oversee consistent application of scientific standards and methodological rigor for data acquisition, processing, and analytics, we developed standard operating procedures that reflect the logistical needs of multi-site research, and the need for well-articulated, transparent processes that can be implemented in future clinical trials. This report details the methodology of the ABC-CT related to acquisition and QC in our Feasibility and Main Study phases. Based on our acquisition metrics from a preplanned interim analysis, we report high levels of acquisition success utilizing VT, EEG, and ET experiments in a relatively large sample of children with ASD and typical development (TD), with data acquired across multiple sites and use of a manualized training and acquisition protocol.

This is a non-randomized, open label, two-cohort, multi-institutional study to evaluate the use of diarrheal management tools intended to facilitate timely intervention and treatment modifications due to afatinib treatment-related diarrhea in patients with EGFR mutations-positive adenocarcinoma of the lung. Patients in Cohort 1 will follow diarrhea management. Patients in Cohort 2 will receive prophylactic loperamide starting the fist day of afatinib treatment.

Database of authoritative health information about diseases, conditions, and wellness issues that offers reliable, up-to-date health information for free. It contains the latest treatments, information on drugs and supplements, the meanings of words, and medical videos and illustrations. Links to the latest topic or disease specific medical research or clinical trials are also offered. * MedlinePlus pages contain carefully selected links to Web resources with health information on over 900 topics. ** The MedlinePlus health topic pages include links to current news on the topic and related information. You can also find preformulated searches of the MEDLINE/PubMed database, which allow you to find references to latest health professional articles on your topic. * The A.D.A.M. medical encyclopedia brings health consumers an extensive library of medical images and videos, as well as over 4,000 articles about diseases, tests, symptoms, injuries, and surgeries. * The Merriam-Webster medical dictionary allows you to look up definitions and spellings of medical words. * Drug and supplement information is available from the American Society of Health-System Pharmacists (ASHP) via AHFS Consumer Medication Information, and Natural Medicines Comprehensive Database Consumer Version. ** AHFS Consumer Medication Information provides extensive information about more than 1,000 brand name and generic prescription and over-the-counter drugs, including side effects, precautions and storage for each drug. ** Natural Medicines Comprehensive Database Consumer Version is an evidence-based collection of information on alternative treatments. MedlinePlus has 100 monographs on herbs and supplements. * Interactive tutorials from the Patient Education Institute explain over 165 procedures and conditions in easy-to-read language. An XML File for the MedlinePlus Health Topics is available, http://www.nlm.nih.gov/medlineplus/xmldescription.html. The ontology is available through Bioportal, http://bioportal.bioontology.org/ontologies/MEDLINEPLUS

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Means and standard errors of GLAS and airborne LiDAR variables used in sapsucker models.

Improving translation quality and efficiency is one of the key challenges in the field of Natural Language Processing (NLP). This study proposes an enhanced model based on Bidirectional Encoder Representations from Transformers (BERT), combined with a dependency self-attention mechanism, to automatically detect and correct textual errors in the translation process. The model aims to strengthen the understanding of sentence structure, thereby improving both the accuracy and efficiency of error correction. The research uses the Conference on Natural Language Learning (CoNLL)-2014 dataset as an experimental benchmark, which contains a rich collection of grammatical error samples and is a standard resource in linguistic research. During model training, the Adam optimization algorithm is employed, and the model’s performance is enhanced by introducing a customized dependency self-attention mechanism for parameter optimization. To validate the model’s effectiveness, the performance of the baseline model and the improved model is compared using multiple evaluation metrics, including accuracy, recall, F1 score, edit distance, Bilingual Evaluation Understudy (BLEU) score, and average processing time. The results show that the proposed model significantly outperforms the baseline model in terms of accuracy (improving from 0.78 to 0.85), recall (improving from 0.81 to 0.87), and F1 score (improving from 0.79 to 0.86). The average edit distance decreases from 3.2 to 2.5, the BLEU score increases from 0.65 to 0.72, and the average processing time is reduced from 2.3 seconds to 1.8 seconds. This study provides an innovative approach for intelligent text correction tasks, expands the application scenarios of the BERT model, and offers significant support for the practical implementation of NLP technologies. The findings not only highlight the advantages of the improved model but also offer new ideas and directions for future related research.

Summary of group means, standard deviations, t-statistics, and P-values.

BackgroundHealthcare practitioners rely on research based on solid evidence for their clinical decisions, ensuring the provision of safe and effective patient care. The use of reporting guidelines and the registration of clinical trials enhance the reliability and credibility of research findings by promoting transparency and minimizing potential biases. However, it remains uncertain to what extent leading immunology and allergy journals have embraced these tools. This study aims to evaluate how commonly reporting guidelines and clinical trial registration are required and endorsed within leading immunology and allergy journals.MethodsWe identified the top 100 journals in the subcategory of “Immunology and Allergy” using the Scopus CiteScore tool for the year 2021. We thoroughly reviewed the “Instructions for Authors” section of each journal, focusing on indications related to specific reporting guidelines as outlined by the Enhancing the Quality and Transparency of Health Research (EQUATOR) Network, as well as the practice of clinical trial registration. Our documentation categorized statements as “Not Mentioned,” “Recommended,” “Not Accepted,” or “Required.” The category “Not Accepted” specifically indicated that the journal explicitly did not accept the study designs associated with certain reporting guidelines, rather than implying bias against these guidelines. ensure equitable evaluation, we communicated with each journal to confirm the types of articles they accepted.ResultsAmong the 100 journals assessed, the CONSORT guideline emerged as the most frequently cited, with 60 journals recommending adherence and 13 requiring it. Conversely, the QUOROM guideline was the least commonly cited, with merely two journals recommending its adherence and none requiring it. Nineteen journals did not reference a single reporting guideline. Remarkably, clinical trial registration was required by 42 journals and recommended by 34.ConclusionThis study reveals variation in the adoption of reporting guidelines and clinical trial registration in immunology and allergy journals. While some journals strongly advocate for or require these practices, others do not emphasize them at all. This inconsistency affects research rigor and reproducibility, highlighting the need for stricter enforcement. Editors should encourage these practices to enhance transparency and minimize biases.

Baseline characteristics of the analysis cohort, mean (standard deviation) displayed unless otherwise stated.

• p < .05 (two-tailed)** p < .01 (two-tailed)*** p < .001 (two-tailed)Means, standard deviations, and inter-correlations of predictor and outcome variables.