Use Of Data Sources Research Articles

A cross-sectional study of data linkage and artificial intelligence practices across European countries

Abstract Background The availability of different data sources is increasing with the possibility to link them with each other. However, linked administrative data can be complex to use and may require advanced expertise and skills in statistical analysis. The main objectives of this study were to describe the use of data linkage and artificial intelligence (AI) in routine public health activities and the constraints to linking different data sources. Methods A cross-sectional survey was performed across European countries to explore the current practices applied by national institutes of public health, health information and statistics for innovative use of data sources (i.e., the use of data linkage and/or AI). Results In Europe, the use of data linkage and AI at national institutes of public health, health information and statistics varies. The use data linkage in routine by applying a deterministic method or a combination of two types of linkages (i.e., deterministic & probabilistic) for public health surveillance and research purposes is common in majority of European countries. The use of AI to estimate health indicators is not frequent among these institutes. The complex data regulation laws, lack of human resources, skills and problems with data governance, were reported by European countries as main constraints to routine data linkage for public health surveillance and research. Conclusions Our study showed that the majority of European countries have integrated data linkage in their routine public health activities but only a few use AI. A sustainable national health information system allowing to link different data sources are essential to contribute to public health research. Moreover, it supports evidence-informed health policy making processes with an overview of various aspects affecting population health and may contribute to European pandemic preparedness.

Data Sources for use in a Healthcare Interoperability Resources (HL7-FHIR) Platform. A Decision Guide for Clinicians and Data Scientists in Public ICUs

Data Sources for use in a Healthcare Interoperability Resources (HL7-FHIR) Platform. A Decision Guide for Clinicians and Data Scientists in Public ICUs

Effects of purple cabbage anthocyanin extract on the gluten characteristics and the gluten network evolution of high-gluten dough.

Anthocyanins are polyphenolic pigments that have hypoglycemic, antioxidation, anti-aging, and other effects. Research has shown that polyphenols can optimize the processing of dough and improve the texture and nutritional characteristics of dough products. The formation of gluten networks is decisive for the quality of flour products. The effects of purple cabbage anthocyanin (PCA) extract on the structure, microscopic morphology, and network formation of gluten protein were studied, and the types of cross-linking between PCA and gluten protein are discussed. The results show that PCA extract increased the free sulfhydryl (SH) group content and the free amino group of gluten proteins, stimulated an increase in the β-sheet ratio and the decrease of α-helix ratio, and increased the gluten index significantly (P < 0.05). The PCA extract also induced gluten protein aggregation, increased the height of protein molecular chains, and stimulated the formation of gluten networks. When PCA extract concentrations were 4 g kg-1 and 8 g kg-1, the gluten network was more homogeneous, continuous, and dense. Appropriate anthocyanins have a positive effect on the properties of gluten and promote the formation of gluten networks. Excessive anthocyanins destroy gluten protein interaction and harm gluten cross-linking. This study may provide a useful source of data for the production of functional flour products rich in anthocyanins. © 2024 Society of Chemical Industry.

Faiz Kararının Duygusal Açıklaması: Türkiye’de Twitter Analizi

Emotions are pervasive in Economics. The spillover effect of Central Bank's interest decision is a crucial topic not only to economies but also to individuals. Twitter is a useful source of data for social and economic research as data provides public available and accessible easily. The study aims to determine the emotions with longitudinal research by analyzing tweets about the interest decision of the Central Bank in Turkiye. Within the study emotions expressed by tweets about interest rate decision are analyzed using Plutchik’s Wheel of Emotions. The 2873 tweets about the interest decision cut on 29 November 2022 were examined by the Maxqda qualitative data analysis program. According to findings, the emotion of "anger" is mostly concentrated under the heading of interest rate decision. Also the analysis indicated that majority of tweets emphasized inflation and foreign exchange among macroeconomic variables and reducing interest indicates negative effects on economy especially by means of inflation. The study contains the classification of emotions regarding interest rate decision and provides evidence that economic decisions affect emotions and they are not independent from each other. Also study aims to provide comprehensive data for researchers who want to use Twitter with economics and emotions together.

A feasibility study to explore the use of real‐time caregiver reports for people living with dementia at home to label multi‐modal sensor data

AbstractBackgroundMulti‐modal sensor systems, consisting of sensors throughout the home, are able to collect data on the person living with dementia’s (PlwD’s) activities. However, caregivers may have challenges interpreting the data, leading to a lack of actionable information. It’s important to get real‐time reports from caregivers to label the sensor data to build relevant machine learning algorithms; yet, this has not been done with PlwD. The aim of this feasibility study was to explore if the use of a multi‐modal sensor system in conjunction with real‐time caregiver reports can provide valuable insights into the daily lives of PlwD.MethodWe developed the MAISON (Multimodal AI‐based Sensor platform for Older Individuals) system and deployed it into the homes of dyads (PlwD and their family caregiver) for 8‐weeks. MAISON includes: a smartphone, a smartwatch to continuously collect heart rate, step, and accelerometer data to infer walking, and running, as well as a smart mattress that can collect sleep time and quality. A digital diary was added to the MAISON system that automatically sends the caregiver 2‐3 pre‐set questions every day about their loved one. Caregivers could also report any significant occurrences throughout the day, as they see fit, through the app.ResultTwo dyads were recruited to date. Only about 15% of data was missing from the sensor system by the end of the study. Caregivers were providing their reports with high adherence. The caregivers’ reports were used to label the sensor data successfully, and upon analysis, we found that caregivers’ reports were reflected in the sensor data and the labels derived from their reports were accurate. Results indicate this study methodology is an innovative approach to utilize the family caregiver’s reports.ConclusionThis is the first longitudinal study to demonstrate the feasibility of a multi‐modal sensor system used by caregivers and PwlD. Findings show that caregivers' reports can be useful sources of data for labeling sensor data. The conjunction of caregiver reports and sensor data will provide valuable information to build accurate machine learning models about behaviors of PlwD which is a foundational step to support dyads at home using technology.

Analisis Strategi Pemasaran Produk Tabungan IB Hijrah Haji Muda pada Generasi Milenial di Bank Muamalat Cabang Stabat

The purpose of this study is to find out the marketing strategy of young IB Hijrah Hajj savings for the millennial generation at Bank Muamalat Stabat Branch. The use of data sources in this study is primary and secondary data. The data analysis technique is using SWOT analysis. This analysis places situations and conditions as input factors, then grouped according to their respective contributions described Internal Factors Analysis Summary. Analysis of external factors EFAS. The results showed that the marketing strategy of the IB Hijrah Haji Muda Savings product carried out by Bank Muamalat Stabat Branch was in a very favorable situation for the company because it had opportunities and strengths so that it could take advantage of existing opportunities. The strategy that must be applied in this condition is to support an aggressive growth policy (growth oriented strategy).

Annual incidence and fatality rates of notifiable infectious diseases in southeast China from 1950 to 2022 and relationship to socioeconomic development.

Over the past 70 years, China has advanced significantly in the prevention and treatment of infectious diseases while simultaneously undergoing a socioeconomic transformation, making it a useful source of data for analysing relationships between public health policy and the control of infectious diseases. We collected data on the incidence of notifiable infectious diseases and associated fatalities in Jiangsu province in southeast China from the Provincial Center for Disease Control and Prevention, Provincial Institute of Parasitic Diseases, and the Nationwide Notifiable Infectious Diseases Reporting Information System. We compared data from different historical periods using descriptive statistical methods, joinpoint regression, and correlation analysis. During 1950-2022, 75 754 008 cases of 46 notifiable infectious diseases were reported in Jiangsu, with an average annual incidence was 1679.49 per 100 000 population and a fatality rate of 1.82 per 1000 persons. The incidence of classes A-B decreased (average annual percent change (AAPC) = -2.1) during the entire study period, while the incidence of class C increased (AAPC = 10.8) after 2004. The incidence of intestinal diseases (AAPC = -4.4) and vector-borne and zoonotic diseases (AAPC = -8.1) decreased rapidly, while the incidence of sexually transmitted and blood-borne diseases (AAPC = 1.8) increased. The number of medical and health institutions and the per capita gross domestic product correlated negatively with the annual incidence of diseases in classes A-B, but not with fatality rates. Although the annual incidence of many severe infectious diseases has decreased in Jiangsu since 1950, the incidence of sexually transmitted and blood-borne diseases increased. Socioeconomic growth and sustainable investment in health systems are associated with better control of infectious diseases.

Estimation of mobility and population in Spain during different phases of the COVID-19 pandemic from mobile phone data

This work aims to find out the effectiveness of sources based on Big Data like mobile phone records to analyze mobility flows and changes in the population of Spain in different scenarios during the period of the pandemic caused by the COVID-19 virus. To this end, we have used mobile phone data provided by the National Institute of Statistics from four days corresponding to different phases of the pandemic. Origin–Destination matrices and population estimation calculations at the spatial level of population cells have been elaborated. The results show different patterns that correspond to the phenomena that have occurred, as the decrease of the population during the periods associated with the confinement measures. The consistency of findings with the reality and the generally good correlation with the population census data indicate that mobile phone records are a useful source of data for the elaboration of demographic and mobility studies during pandemics.

Examining Pediatric Resident Electronic Health Records Use During Prerounding: Mixed Methods Observational Study

Electronic health records (EHRs) play a substantial role in modern health care, especially during prerounding, when residents gather patient information to inform daily care decisions of the care team. The effective use of the EHR system is crucial for efficient and frustration-free prerounding. Ideally, the system should be designed to support efficient user interactions by presenting data effectively and providing easy navigation between different pages. Additionally, training on the system should aim to make user interactions more efficient by familiarizing the users with best practices that minimize interaction time while using the full potential of the system's capabilities. However, formal training on EHR systems often falls short of providing residents with all the necessary EHR-related skills, leading to the adoption of inefficient practices and the underuse of the system's full range of capabilities. This study aims to examine the efficiency of EHR use during prerounding among pediatric residents, assess the effect of experience level on EHR use, and identify areas for improvement in EHR design and training. A mixed methods approach was used, involving a self-reported survey and video analysis of prerounding practices of the entire population of pediatric residents from a large teaching hospital in the South Atlantic Region. The residents were stratified by experience level by postgraduate year. Data were collected on the number of pages accessed, duration of prerounding, task completion rates, and effective use of data sources. Observational and qualitative data complemented the quantitative analysis. Our study followed the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) reporting guidelines, ensuring completeness and transparency of reporting. Of the 30 pediatric residents, 20 were included in the analyses; of these, 16 (80%) missed at least 1 step during prerounding. Although more experienced residents on average omitted fewer steps, 4 (57%) of the 7 most experienced residents still omitted at least 1 step. On average, residents took 6.5 minutes to round each patient and accessed 21 pages within the EHR during prerounding; no statistically significant differences were observed between experience levels for prerounding times (P=.48) or number of pages accessed (P=.92). The use of aggregated data pages within the EHR system neither seem to improve prerounding times nor decrease the number of pages accessed. The findings suggest that EHR design should be improved to better support user needs, and hospitals should adopt more effective training programs to familiarize residents with the system's capabilities. We recommend implementing prerounding checklists and providing ongoing EHR training programs for health care practitioners. Despite the generalizability of limitations of our study in terms of sample size and specialization, it offers valuable insights for future research to investigate the impact of EHR use on patient outcomes and satisfaction, as well as identify factors that contribute to efficient and effective EHR usage.

Determination of antimicrobial use in commercial poultry farms in Plateau and Oyo States, Nigeria

BackgroundIndiscriminate use of antimicrobials for the prevention and treatment of bacterial infection in animals is a common practice in Nigeria as in other developing countries. These antimicrobials are purchased over the counter without restrictions and often administered in form of medicated feedstuffs. In Nigeria, like most developing countries, antimicrobial prescription data are not routinely collected or reported at the farm level, instead import data are used in reporting antimicrobial consumption. Farmers can be useful sources of data on the use of antimicrobial agents by class, animal species, production type and age. The objective of the study was to determine the knowledge, attitude and practices of poultry farmers on antimicrobial resistance and to generate data on antimicrobial use (AMU) in poultry farms in Plateau and Oyo states in accordance with the guidelines of the World Organization for Animal Health (WOAH).MethodsA questionnaire used by the Food and Agriculture Organization (FAO) of the United Nations in Ghana was adopted and modified to collect data on the knowledge, attitude and practices of farmers on AMR and AMU and to collect AMU data from selected poultry farms. A focus group discussion (FGD) was conducted in Plateau state with poultry farmers and representatives from the state veterinary services, using a checklist. The aim of the FGD was to have an idea on antimicrobial use among poultry farmers and to generate additional questions that might be added to the questionnaire. Stratified random sampling technique was used to select 50 farms from Plateau and Oyo states, using the list of registered poultry farms in the two states as sampling frame.ResultsNinety eight percent (98%) of farmers gave antibiotics as prophylactic treatment to day old chicks. There were 47 different products used in the two states within the study period. We observed that five classes of antibiotics (Tetracyclines, Penicillins, Aminoglycosides, Polypeptides and Fluoroquinolone) were used in the two states. A total of 351 kg of active ingredients from seven different classes, namely: tetracyclines, penicillins, aminoglycosides, polypeptide, fluoroquinolones, amphenicol and macrolides were recorded from the two states. Some products contained cocktail of antibiotics, having up to six different classes with very high concentration of active ingredients which are not in the list of registered antimicrobials reported to WOAH.ConclusionThe concept used for this survey proved that the approach can be applied for AMU surveillance in the animal health sector. It also provided insight on farmers’ knowledge and practices with regards to the use of antimicrobials which is missing in the national import data. The need for “stronger” antibiotics was identified as one of the drivers of antibiotic resistance.

A super-ensemble approach to map land cover types with high resolution over data-sparse African savanna landscapes

Accurate and timely land cover products are critical inputs for landscape planning, and provide key information for biodiversity conservation and food security. However, poor mapping quality and low resolution are considerable issues in existing land cover maps over the African savanna, where land use is complex and changing rapidly, and necessary ground-truth data are sparse and hard to obtain. To overcome this problem, to make optimal use of existing maps, and to minimize manual training data collection, we developed a three-stage ensemble method to make land cover maps. In the first stage, we extracted the consensus of multiple existing land cover products to generate fragmented pixel-wise training labels. In the second stage, we translated pixel-wise training labels to image-wise labels using Random Forest (RF) as a “gap-filling model”, with temporal features extracted from Sentinel-1 time series, raw bands, and vegetation indices derived from PlanetScope basemaps. These image-wise labels were scored and edited by humans and the quality information was used in the next stage. For stage three, we trained a U-Net network based upon these image-wise labels, using Sentinel-1 time series and raw bands of PlanetScope basemaps as image features. Using the information on label quality, a quality-weighted loss function was used in the network to reduce the impact of noise in the training labels. Using Northern Tanzania as a case study, the results demonstrate that ensembles of existing land cover maps provide a useful source of data for developing improved land cover maps over hard-to-classify, data-sparse landscapes. The Random Forest “gap-filling model” had an overall accuracy of 80.26% on our independent test dataset with 7 classes. The final U-Net model had an overall accuracy of 83.57%. This approach can be readily applied to other regions and extents (e.g., regional, global) and other data sources (e.g., Sentinel-2).

Wood and bark structure in Buddleja: anatomical background of stem morphology.

Bark (all tissues outside of the vascular cambium) has been extensively studied in recent years, especially its anatomy and physiology. Macromorphological bark characters can be important taxonomically for many plant groups, including the genus Buddleja (Scrophulariaceae). However, the relationship between macroscopic bark appearance and its microscopic structure remains obscure, hampering the use and interpretation of bark traits in plant taxonomy and phylogenetics as well as in other fields of botany. We studied micro- and macrostructure of bark in the species of Buddleja representing wide taxonomic and geographic diversity to identify general relationships between bark anatomy and morphology. We also examined Buddleja xylem and discussed the importance of anatomical traits for understanding the relationships between clades in this genus. The smooth bark surface in sect. Gomphostigma and the outgroup (Freylinia spp.) relates to the small number of periderms of superficial origin and limited sclerification. This allows for the retention of visible lenticels. In the rest of Buddleja, bark sloughs off and division of labour is present: collapsed phloem undergoes sclerification and acts as a protective layer, while thin-walled phellem forms the separation layers. A similar pattern is found in some groups (e.g. Lonicera), but in others (e.g. Vitis and the species of Eucalyptus with stringy bark), the pattern is inversed. Wood and bark anatomy supports a sister relationship between the southern African section Gomphostigma and the rest of Buddleja but is taxonomically uninformative among remaining clades. Limited development of periderms and sclerification allows for the retention of a smooth bark surface and conspicuous lenticels. Sloughing off of bark requires division of labour into a lignified protective layer and a thin-walled separation layer. These two functions are never served by a single tissue but are rather divided between phloem and periderm. How more subtle features (e.g. size and shape of fissures) are determined requires further study. Simultaneously, bark anatomy could be a useful source of data to complement molecular phylogenetic studies in a total evidence approach for systematics.

Application of artificial intelligence and machine learning for BIM: review

Quality control is very important aspect in Building Information Modelling (BIM) workflows. Whatever stage of the lifecycle it is important to get and to follow building indicators. The BIM it is very data consuming field and analysis of these data require advance numerical tools from image processing to big data analysis. Artificial intelligent (AI) and machine learning (ML) had proven their efficiency to deal with automate processes and extract useful sources of data in different industries. In addition to the indicators tracking, AI and ML can make a good prediction about when and where to provide maintenance and/or quality control. In this article, a review of the AI and ML application in BIM will be presented. Further suggestions and challenges will be also discussed. The aim is to provide knowledge on the needs nowadays into building and landscaping domain, and to give a wide understanding on how those technics would impact industries and future studies.

ОЦЕНКА РЕАКЦИИ ПЕРИФЕРИЧЕСКОЙ ГЕМОДИНАМИКИ НА ВОЗДЕЙСТВИЕ ПЕРЕГРУЗОК НАПРАВЛЕНИЯ «ГОЛОВА – НОГИ» (+Gz) НА ЦЕНТРИФУГЕ КОРОТКОГО РАДИУСА МЕТОДОМ ДОПЛЕРФЛОУМЕТРИИ

We investigated peripheral arterial blood flow during exposure to the head-to-legs g-loads (+Gz) on a short-arm centrifuge (SAC). Purpose was to use some objective monitoring instruments for testing the hypothesis that the hemodynamic reaction to +Gz would be analogous to the reactions observed in the tilt test and/or the lower body negative pressure (LBNP) test. Six normal male subjects participated in 6 SAC runs with alternating interval g-loads of +1.27 Gz and +2.7 Gz. Blood flow in the femoral (FA) and medial cerebral (MCA) arteries was recorded continuously before, during and after runs with the use of Doppler flowmetry (Kardiomed device). It was found that +Gz centrifugation produced typical anti-gravity changes in hemodynamics, i.e. an increase in FA resistance and decrease in MCR resistance. In comparison to the records at rest, FA blood flow decreased 60 %; MCA blood flow changed insignificantly - no more than 10 % down. It was borne out that +Gz centrifugation has same effects as the Earth's gravity in standing humans, produces orthostatic blood pressure in the lower part of the body, and initiates the totality of anti-gravity hemodynamic reactions. Doppler recording was a quite useful source of data about the blood flow reaction to +Gz centrifugation.

Evaluating the accuracy of gridded water resources reanalysis and evapotranspiration products for assessing water security in poorly gauged basins

Abstract. Achieving water security in poorly gauged basins is critically hindered by a lack of in situ river discharge data to assess past, current, and future evolution of water resources. To overcome this challenge, there has been a shift toward the use of freely available satellite and reanalysis data products. However, due to inherent bias and uncertainty, these secondary sources require careful evaluation to ascertain their performance before being applied in poorly gauged basins. The objectives of this study were to evaluate river discharge and evapotranspiration estimates from eight gridded water resources reanalysis (WRR), six satellite-based evapotranspiration (ET) products, and ET estimates derived from complimentary relationship (CR–ET) across eight river basins located in Central–West Africa. Results highlight strengths and weaknesses of the different WRR in simulating discharge dynamics and ET across the basins. Likewise, satellite-based products also show some strength and weaknesses in simulating monthly ET. Our results further revealed that the performance of the different models in simulating river discharge and evapotranspiration is strongly influenced by model structure, input data, and spatial resolution. Considering all hydrological model evaluation criteria, FLDAS-Noah, Lisflood, AWRAL, and Terra were among the best performing WRR products while for ET estimates, FLDAS-Noah, Terra, GLEAM3.5a and 3.5b, and PMLV2 outperformed the rest of the products. Given the plethora of WRR and ET products available, it is imperative to evaluate their performance in representative gauged basins to identify products that can be applied in each region. However, the choice of a particular product will depend on the application and user requirements. Taking this together, results from this study suggest that gridded WRR and ET products are a useful source of data for assessing water security in poorly gauged basins.

An inventory of European data sources to support pharmacoepidemiologic research on neurodevelopmental outcomes in children following medication exposure in pregnancy: A contribution from the ConcePTION project.

Studies on medication safety in pregnancy are increasingly focusing on child neurodevelopmental outcomes. Establishing neurodevelopmental safety is complex due to the range of neurodevelopmental outcomes and the length of follow-up needed for accurate assessment. The aim of this study was to provide an inventory of European data sources for use in pharmacoepidemiologic studies investigating neurodevelopment following maternal medication exposure. The EUROmediSAFE inventory of data sources in Europe for evaluating perinatal and long-term childhood risks associated with in-utero exposure to medication was updated by contacting colleagues across 31 European countries, literature review and internet searches. Included data sources must record at least one neurodevelopmental outcome and maternal medication use in pregnancy must be available, either in the data source itself or through linkage with another data source. Information on the domain of neurodevelopment, measure/scale used and the approach to measurement were recorded for each data source. Ninety data sources were identified across 14 countries. The majority (63.3%) were created for health surveillance and research with the remaining serving administrative purposes (21.1% healthcare databases,15.6% other administrative databases). Five domains of neurodevelopment were identified-infant development (36 data sources,13 countries), child behaviour (27 data sources, 10 countries), cognition (29 data sources, 12 countries), educational achievement (20 data sources, 7 countries), and diagnostic codes for neurodevelopmental disorders (42 data sources, 11 countries). Thirty-nine data sources, in 12 countries, had information on more than one domain of neurodevelopment. This inventory is invaluable to future studies planning to investigate the neurodevelopmental impact of medication exposures during pregnancy. Caution must be used when combining varied approaches to neurodevelopment outcome measurement, the age of children in the data source, and the sensitivity and specificity of the outcome measure selected should be borne in mind.

Preferences, Substitutes, and Complements: Mapping the Relationship between Data Sources within Teachers’ Instructional Practice

ABSTRACT The extent to which teachers collect, interpret, and use information from multiple data sources is a key distinction between novice and expert data users. Understanding and exploring this dimension of teachers’ instructional decision making requires a shift in contemporary perspectives toward the interconnectedness of data sources within teachers’ practice of data use. In the present study, I develop and apply a conceptual framework for mapping the structure of connections between data sources within and across instructional practices. Findings indicate teachers typically use two to six data sources in the context of a given instructional practice, with considerable variation in the relationship between those data sources across instructional practices. Toward this end, the present study advances a typology for classifying teachers’ preference for, substitution between, and complementary use of data sources. Findings have implications for preservice teacher preparation, in-service teacher professional learning, and research perspectives on data use in education.

Paediatric acute care cardiology collaborative data registry validation.

The Pediatric Acute Care Cardiology Collaborative (PAC3) was established to improve acute care cardiology outcomes through the development of an accurate and well-validated clinical registry. We report the validation results of the initial PAC3 registry audits and describe a novel regional audit format developed to accommodate a rapidly expanding membership facilitate collaborative learning and allow for necessary modification due to the COVID-19 pandemic. Six hospitals were audited using a regional audit format and three hospitals were subsequently audited virtually. Critical and challenging-to-collect data elements were audited among at least 40 randomly selected cases. Discrepancies were categorised as either major or minor depending on their relative importance to patient outcomes and clinical care. Results were tabulated and reported. We audited 386 encounters and 27,086 individual data fields across 9 hospitals. The aggregate overall accuracy rate was 99.27% and the aggregate major discrepancy rate was 0.51%. The overall accuracy rate ranged from 98.77% to 99.59%, and the major discrepancy rate ranged from 0.26% to 0.88% across the cohort. No appreciable difference was seen between audit formats. Both the regional and virtual audit methods were viewed favourably by participants. A low data discrepancy rate was found demonstrating that the PAC3 registry is a highly accurate data source for use in quality improvement, benchmarking, and research. Regional audits and virtual audits were both successfully implemented.

Ecomorphology of the tarsometatarsus of waterfowl (Anseriformes) based on geometric morphometrics and its application to fossils.

Anseriformes is a diverse group of birds that comprises screamers, the Magpie Goose, and swans ducks and geese, with a relatively rich fossil record. Waterfowl live in close relation to water bodies, but show a diversity of locomotory habits, being typically categorized as walkers, dabblers, and divers. Owing to its functional significance and high preservation potential, the tarsometatarsus has been considered to be a "key" element upon which to base ecomorphological inferences in fossil waterfowl. For instance, based on features of the tarsometatarsus the Miocene flightless duck Cayaoa bruneti and the Oligocene-Miocene large waterfowl Paranyroca have been inferred as divers. Herein, we use a geometric morphometric approach and comparative methods to assess the phylogenetic and ecomorphological signals in the shape and size of waterfowl tarsometatarsi in relation to their locomotory habits. We also apply phylogenetic flexible discriminant analysis (pFDA) to test the inferred diving habits in the extinct waterfowl Cayaoa and Paranyroca. Extant waterfowl species are largely distributed according to their locomotory habit along the main axis of variation in the shape space, a pattern mirrored by the phylogenetic generalized least squares model, which shows that a third of the shape variation is significantly explained by the habit. The pFDA reclassifies correctly almost all extant species and classified with high posterior probabilities the fossil Cayaoa and Paranyroca as a diver and as a dabbler, respectively. Our quantitative multivariate approach confirms the tarsometatarsus as a useful source of data upon which reliably assesses locomotory habits of fossil waterfowl.

Development and Validation of the Skimmed Milk Pellet Extraction Protocol for SARS-CoV-2 Wastewater Surveillance.

Wastewater surveillance for SARS-CoV-2 may serve as a useful source of data for public health departments as the virus is shed in the stool of infected individuals. However, for wastewater data to be actionable, wastewater must be collected, concentrated, and analyzed in a timely manner. This manuscript presents modifications on a skimmed milk concentration protocol to reduce processing time, increase the number of samples that can be processed at once, and enable use in resource-limited settings. Wastewater seeded with Human coronavirus OC43 (OC43) was concentrated using a skimmed milk flocculation protocol, and then pellets were directly extracted with the QIAamp Viral RNA Mini kit. This protocol has a higher average effective volume assayed (6.35 mL) than skimmed milk concentration methods, with and without Vertrel XF™, which involve resuspension of the pellets in PBS extraction prior to nucleic acid extraction (1.28 mL, 1.44 mL, respectively). OC43 was selected as a recovery control organism because both it and SARS-CoV-2 are enveloped respiratory viruses that primarily infect humans resulting in respiratory symptoms. The OC43 percent recovery for the direct extraction protocol (3.4%) is comparable to that of skimmed milk concentration with and without Vertrel XF™ extraction (4.0%, 2.6%, respectively). When comparing SARS-CoV-2 detection using McNemar’s chi-square test, the pellet extraction method is not statistically different from skimmed milk concentration, with and without Vertrel XF™ extraction. This suggests that the method performs equally as well as existing methods. Added benefits include reduced time spent per sample and the ability to process more samples at a single time. Direct extraction of skimmed milk pellets is a viable method for quick turnaround of wastewater data for public health interventions.Supplementary InformationThe online version contains supplementary material available at 10.1007/s12560-022-09512-5.