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In 2014, the Pathology and Laboratory Quality Center for Evidence-Based Guidelines ('The Center') of the College of American Pathologists (CAP) published a clinical practice guideline that created recommendations for analytic [...], * Context.--In 2014, the College of American Pathologists developed an evidence-based guideline to address analytic validation of immunohistochemical assays. Fourteen recommendations were offered. Per the National Academy of Medicine standards for developing trustworthy guidelines, guidelines should be updated when new evidence suggests modifications. Objective.--To assess evidence published since the release of the original guideline and develop updated evidence-based recommendations. Design.--The College of American Pathologists convened an expert panel to perform a systematic review of the literature and update the original guideline recommendations using the Grading of Recommendations Assessment, Development and Evaluation approach. Results.--Two strong recommendations, 1 conditional recommendation, and 12 good practice statements are offered in this updated guideline. They address analytic validation or verification of predictive and nonpredictive assays, and recommended revalidation procedures following changes in assay conditions. Conclusions.--While many of the original guideline statements remain similar, new recommendations address analytic validation of assays with distinct scoring systems, such as programmed death receptor-1 and analytic verification of US Food and Drug Administration approved/ cleared assays; more specific guidance is offered for validating immunohistochemistry performed on cytology specimens. (Arch Pathol Lab Med. 2024;148:e111-e153; doi: 10.5858/arpa.2023-0483-CP

Integration of electronic monitoring on commercial bottom long-line vessels has been successfully conducted through several pilot studies in the U.S. Gulf of Mexico reef fish fishery. Collaborative work conducted from 2016 through 2021 by the Mote Marine Laboratory Center for Fisheries Electronic Monitoring at Mote (CFEMM) and 13 volunteer eastern Gulf fishing vessels resulted in observations of 82,936 individual fish from 131 unique species or species groups from 306 trips covering 2,822 sea days of fishing effort. The fishing area covered 114,268 [km.sup.2] with capture depths ranging from 35 m to 360 m. The most predominantly caught species were red grouper, Epinephelus morio (65%); red snapper, Lutjanus campechanus (9%); and yellowedge grouper, Epinephelus flavolimbatus (5%). Of these species, 48%, 23%, and 2%, were discarded, respectively. Important bycatch species included blueline tilefish, Caulolatilus microps; scamp, Mycteroperca phenax; and gag grouper, Mycteroperca microlepis. Notably, sea turtle and sea bird interactions were minimal. Discards included undersized and depredated reef fish, along with a variety of shark species. Statistically significant spatial clusters of high catch per unit of effort (CPUE) hotspots, low CPUE cold spots, and random distributions are presented spatially joined to 10.0 min grids for primary targeted and bycatch species, grouped shark bycatch, and specifically for sandbar sharks, Carcharhinus plumbeus, a species that is prohibited from harvest, except under a NMFS research permit. This project demonstrates that electronic monitoring is an effective method for collecting catch and bycatch data from the commercial eastern Gulf of Mexico reeffish fishery. Increasing trip coverage and providing additional EM-derived data that complements observer reports would contribute to enriching the data available for supporting stock assessments and promoting sustainable fishing practices., Introduction The U.S. Gulf of Mexico (hereafter referred to as 'Gulf') commercial reef fish fishery involves more than 800 federally permitted vessels (Stephen (1)) using primarily bottom longline (BLL) and [...]

Electronic monitoring (EM) systems have been developed to facilitate fisheries data collection in many industrialized fleets but remain less common onboard smaller vessels. This work tested the performance of small-vessel EM systems to meet the reporting objectives in the California deep-set buoy gear (DSBG) fishery for swordfish, Xiphias gladius. Two EM service providers were contracted to develop monitoring platforms, which included both 1- and 2-camera systems. Initial testing was performed onboard a research vessel to identify functional configurations and refine data collection procedures prior to commercial testing. Commercial trials were performed onboard four vessels during the 2020-21 fishing seasons, resulting in 126 electronically monitored set days. Fishery performance metrics from EM records were compared between service providers, fishing logbooks, and records from NOAA-certified observers. Catch comparisons yielded full agreement (100%) for both target (109/109) and incidental catch (9/9) between the 2-camera EM system and logbook records. The 1-camera system yielded 88% agreement (52/59) for target catch and 14% (1/7) for incidental catch. Unquantified catch events occurred outside the 1-camera field of view onboard larger vessels with independent hauling and catch-processing areas. Collectively, this study demonstrates that EM can be used to accurately document fishery catch statistics in the developing commercial DSBG fishery., Introduction Fishery monitoring and observation provide the basis for which accurate catch statistics can be generated, allowing managers to document and respond to fishery performance trends over time (Gilman et [...]

A fundamental function performed by a sensory network is the retrieval of data gathered collectively by sensor nodes. The metrics that measure the efficiency of this data collection process are time and energy. In this paper, we study via simple discrete mathematical models, the statistics of the data collection time in sensory networks. Specifically, we analyze the average minimum delay in collecting randomly located/distributed sensors data for networks of various topologies when the number of nodes becomes large. Furthermore, we analyze the impact of various parameters such as size of packet, transmission range, and channel erasure probability on the optimal time performance. Our analysis applies to directional antenna systems as well as omnidirectional ones. This paper focuses on directional antenna systems and briefly presents results on omnidirectional antenna systems. Finally, a simple comparative analysis shows the respective advantages of the two systems. Index Terms--Broadcasting, data collection, delay, directional antenna, sensor networks.

The American Community Survey (ACS) is a continuous measurement survey program designed to replace the census long form sample. While the census sample provides detailed socioeconomic data once a decade, the ACS will provide these data annually using a questionnaire that largely mirrors the census long form. This paper examines operational data in Bronx County, one of 36 ACS test counties, and finds the ACS superior to the census on two important measures of data quality. First, applying the minimal data requirement for inclusion of a long form in the census sample, ACS questionnaires were significantly more likely than the long forms to meet this threshold. Second, the level of nonresponse to items on the ACS was often one-half the census level. The ACS and census have sharply divergent goals and operational methods that affect data quality. The primary objective of the census is a population count for reapportionment and redistricting; collecting long form information is a secondary goal. In contrast, the primary objective of the ACS is to estimate the characteristics of an area based on answers to all items on the survey. Operationally, the census follows up every nonresponding household, using a pool of minimally trained, temporary workers. In comparison, the ACS follows up only one-in-three nonresponding households, using a permanent cadre of professional interviewers. This results in superior nonresponse follow-up in the ACS, with lower levels of non-sampling error, even in more difficult-to-enumerate high poverty areas of the Bronx. The ACS is to be fully implemented in July 2004, pending Congressional funding. With detailed socioeconomic data available annually from the ACS, the 2010 census would then be able to focus primarily on a population headcount. The paper concludes by discussing operational aspects of the ACS that must be improved, including increasing its visibility, for the survey to he accepted as an integral part of the nation's data collection system.

Byline: Qinbao Song, Martin Shepperd Intelligent data analysis techniques are useful for better exploring real-world data sets. However, the real-world data sets always are accompanied by missing data that is one major factor affecting data quality. At the same time, good intelligent data exploration requires quality data. Fortunately, Missing Data Imputation Techniques (MDITs) can be used to improve data quality. However, no one method MDIT can be used in all conditions, each method has its own context. In this paper, we introduce the MDITs to the KDD and machine learning communities by presenting the basic idea and highlighting the advantages and limitations of each method.

Den-site visitation and radiotelemetry is used primarily to collect data, for studying denning behavior of American black beer, by researchers. Rarely documented behaviors associated with den exits and estimated cub ages at den emergence are observed.

TPL-KATS-concept map, a software tool was developed to examine the organization of mental representations through the use of a computer. This software was originally developed as a data collection tool for psychological studies, but can be a valuable resource in training, interface design, and education as well.

It is crucial that procedural consistency should be maintained for proper data analysis throughout the wildlife project. Continuity in data collection is critical for long-term studies, so the observers must collect the same types of data using the same units and notations.