Appropriateness of Outpatient Antibiotic Use in Seniors across Two Canadian Provinces

Antimicrobials are among the most prescribed medications in Canada, with over 90% of antibiotics prescribed in outpatient settings. Seniors prescribed antimicrobials are particularly vulnerable to adverse drug events and antimicrobial resistance. The extent of inappropriate antibiotic prescribing in outpatient Canadian medical practice, and the potential long-term trends in this practice, are unknown. This study is the first in Canada to examine prescribing quality across two large-scale provincial healthcare systems to compare both quantity and quality of outpatient antibiotic use in seniors. Population-based analyses using administrative health databases were conducted in British Columbia (BC) and Ontario (ON), and all outpatient, oral antimicrobials dispensed to seniors (≥65 years) from 1 January 2000 to 31 December 2018 were identified. Antimicrobials were linked to an indication using a 3-tiered hierarchy. Tier 1 indications, which always require antibiotics, were given priority, followed by Tier 2 indications that sometimes require antibiotics, then Tier 3, which never require antibiotics. Prescription rates were calculated per 1000 population, and trends were examined overall, by drug class, and by patient demographics. Prescribing remained steady in both provinces, with 11,166,401 prescriptions dispensed overall in BC, and 27,656,014 overall in ON. BC prescribed at slightly elevated rates (range: 790 to 930 per 1000 residents), in comparison to ON (range: 745 to 785 per 1000 residents), throughout the study period. For both provinces, a Tier 3 diagnosis was the most common reason for antibiotic use, accounting for 50% of all indication-associated antibiotic prescribing. Although Tier 3 indications remained the most prescribed-for diagnoses throughout the study period, a declining trend over time is encouraging, with much room for improvement remaining. Elevated prescribing to seniors continues across Canadian outpatient settings, and prescribing quality is of high concern, with 50% of all antimicrobials prescribed inappropriately for common infections that do not require antimicrobials.

Comparison of Diesel Tractor Emissions in Korea

Due to the shortage of agricultural labor forces and rapid aging of farmers, the utilization of tractors is becoming popular and essential in Korea. Tractors can be classified into two types, a walking tractor called as a power tiller and a riding tractor. In this study, agricultural tractors including walking and riding types were categorized into 4 levels by rated output power. And diesel emission inventory of tractors was established and analyzed using 2011 and 2019 survey data in Korea. Emission inventory including CO, NOx, SOx, TSP(PM10), PM2.5, VOCs and NH3 were established using Tier 3 methodology. The total amount of emission using agricultural tractors was decreased about 13% from 2011 to 2019. The number of walking tractors were decreased by about 19% in 8 years, on the other hand that of riding tractors were increased by about 12%. However, the emission reduction is about 48% for walking tractors and the emission increment is about 5% for riding tractors. Thus, the total emission from agricultural tractors was decreased by about 16% in those periods. It is due to the decrease of 21% and 15% in the hours of use of walking and riding tractors, respectively, in 2019. Walking tractors mainly emit air pollutants from spraying and transporting. Riding tractors mainly 61% of total air pollutants emits from soil preparation and transporting operations. Geographic information system (GIS) was used to spatially assign air pollutants variables into 17 provinces and metropolitan cities in Korea. High emission generating regions and changes of emissions during 8 years were clearly seen in GIS analysis. High air pollutant emitting regions are mainly located in the western and southern regions of Korea, which have plenty of arable areas compared to other regions in Korea.

Country-specific emission factor for developing a tier 3 system of Indonesia’s seagrass carbon inventory

Climate action regarding carbon inventory requires baseline assessment, data regarding annual changes, and evaluation of reductions in carbon emissions. However, many studies of seagrass ecosystems have focused only on carbon stock and sequestration, neglecting the importance of the carbon emission factor. It is known that emission factors for land-use change, including those in seagrass ecosystems, can be derived from biomass and sediment carbon stock. Since currently Indonesia only has data for biomass carbon stock, we propose the measurement of province-based emission factors. This study combines the available carbon stock data reported in national or international publications and conducts a meta-analysis to obtain emission factor values. The results show that the biomass standing carbon stock of Indonesia’s seagrass meadows ranges from 0.30 tC/ha (i.e., Special Region of Yogyakarta) to 16.51 tC/ha (i.e., Gorontalo province), while emission factor ranges from 0.012 tC/ha/yr to 0.661 tC/ha/yr (equal to 0.05 t CO2/ha/yr to 2.42 t CO2/ha/yr). These findings will be beneficial for developing Tier 3 carbon inventory since they allow country-specific emission factor for the seagrass ecosystem to be measured.

Multitiered Systems of Supports, Response to Intervention, and Positive Behavioral Interventions and Supports

This chapter covers the Response to Intervention framework, Positive Behavioral Interventions and Supports, and multitiered systems of supports (MTSS). The Response to Intervention framework is a central step in implementing a successful MTSS framework. MTSS delivers school-based supports across three tiers: tier 1 (universal), tier 2 (targeted), and tier 3 (individualized). The MTSS framework is a resource that enables schools to use data not only to identify students at risk for poor learning outcomes but also to monitor student progress and deliver evidence-based interventions. The chapter provides examples of ways social workers can maximize the utility of these models and school teams to improve student outcomes.

Validation analysis of EMDB entries

The Electron Microscopy Data Bank (EMDB) is the central archive of the electron cryo-microscopy (cryo-EM) community for storing and disseminating volume maps and tomograms. With input from the community, EMDB has developed new resources for validation of cryo-EM structures, focussing on the quality of the volume data alone and that of the fit of any models, themselves archived in the Protein Data Bank (PDB), to the volume data. Based on recommendations from community experts, the validation resources are developed in a three-tiered system. Tier 1 covers an extensive and evolving set of validation metrics, including tried and tested as well as more experimental ones, which are calculated for all EMDB entries and presented in the Validation Analysis (VA) web resource. This system is particularly useful for cryo-EM experts, both to validate individual structures and to assess the utility of new validation metrics. Tier 2 comprises a subset of the validation metrics covered by the VA resource that have been subjected to extensive testing and are considered to be useful for specialists as well as non-specialists. These metrics are presented on the entry-specific web pages for the entire archive on the EMDB website. As more experience is gained with the metrics included in the VA resource, it is expected that consensus will emerge in the community regarding a subset that is suitable for inclusion in the tier 2 system. Tier 3, finally, consists of the validation reports and servers that are produced by the Worldwide Protein Data Bank (wwPDB) Consortium. Successful metrics from tier 2 will be proposed for inclusion in the wwPDB validation pipeline and reports. We describe the details of the new resource, with an emphasis on the tier 1 system. The output of all three tiers is publicly available, either through the EMDB website (tiers 1 and 2) or through the wwPDB ftp sites (tier 3), although the content of all three will evolve over time (fastest for tier 1 and slowest for tier 3). It is our hope that these validation resources will help the cryo-EM community to get a better understanding of the quality, and the best ways to assess the quality of cryo-EM structures in EMDB and PDB.

What makes seep carbonates ignore self-sealing and grow vertically: the role of burrowing decapod crustaceans

The mechanisms that govern the vertical growth of seep carbonates were deciphered by studying the sedimentary architecture of a 15 m thick, 8 m wide column of limestone encased in deep-water marl in the middle Callovian interval of the Terres Noires Formation in the SE France Basin. The limestone body, also called “pseudobioherm”, records intense bioturbation, with predominant traces of the Thalassinoides/Spongeliomorpha suite, excavated by decapod crustaceans. Bioturbation was organized in four tiers. The uppermost tier, tier 1, corresponds to shallow homogenization of rather soft sediment. Tier 2 corresponds to pervasive burrows dominated by large Thalassinoides that were later passively filled by pellets. Both homogenized micrite and burrow-filling pellets are depleted in 13C in the range from −5 ‰ to −10 ‰. Tier 3 is characterized by small Thalassinoides that have walls locally bored by Trypanites; the latter represent tier 4. The diagenetic cements filling the tier-3 Thalassinoides are arranged in two phases. The first cement generation constitutes a continuous rim that coats the burrow wall and has consistent δ13C values of approximately −8 ‰ to −12 ‰, indicative of bicarbonate originating from the anaerobic oxidation of methane. In contrast, the second cement generation is dominated by saddle dolomite precipitated at temperatures >80 ∘C, at a time when the pseudobioherm was deeply buried. The fact that the tubes remained open until deep burial means that vertical fluid communication was possible over the whole vertical extent of the pseudobioherm up to the seafloor during its active development. Therefore, vertical growth was fostered by this open burrow network, providing a high density of localized conduits through the zone of carbonate precipitation, in particular across the sulfate–methane transition zone. Burrows prevented self-sealing from blocking upward methane migration and laterally deflecting fluid flow. One key aspect is the geometric complexity of the burrows with numerous subhorizontal segments that could trap sediment shed from above and, hence, prevent their passive fill.

Identifying opportunities for improving the organ supply through race-stratified data

Organ procurement in the US has received attention from government officials and policymakers the last two years, culminating in CMS releasing an updated Final Rule related to organ donation this year. This regulatory change revises how organ procurement organizations (OPOs), the federal contractors tasked with managing deceased donation, are evaluated and certified/de-certified. We used 2019 data and the CMS methodology to calculate race-stratified donation data among racial/ethnic minorities across the 57 OPOs. We found that the variability in donation rates across the 57 OPOs are greater among minority populations than non-Hispanic white potential donors. Among Tier 3 OPOs, there are: a) some with low donation rates across all racial/ethnic groups; b) some with low donation rates among only certain groups, and c) some where donation rates are lowest among non-Hispanic white patients. Among low-performing OPOs, these race/ethnicity-stratified data show that under-performance in certain areas is not due to the population demographics, and identifies areas for targeted interventions to increase donation and avoid decertification

Simultaneous Monitoring of the Middle Cerebral and Basilar Arteries to Detect Right-to-Left Shunts Using Transcranial Doppler by Agitated Saline Administration

Transcranial Doppler (TCD) is an easy, non-invasive, and real-time monitoring device for detecting right-to-left shunts (RLS). Nonetheless, it has limited benefits in patients with poor temporal windows. Therefore, we aimed to investigate whether the basilar artery (BA) window was as effective as the middle cerebral artery (MCA) in detecting RLS during TCD monitoring. Overall, we enrolled 344 patients with stroke, transient ischemic attack, headache, or dizziness. MCA and BA were monitored using a modified headset. To investigate the feasibility of the suboccipital window in detecting RLS, we instituted an evaluation tool with three tiers to evaluate microembolic signals (MESs) during TCD monitoring. Tier 1: TCD monitoring of the MCA (bilaterally) in the resting state, tier 2: TCD monitoring of the MCA (bilaterally) while performing the Valsalva maneuver, and tier 3: TCD monitoring of the index MCA and BA while performing the Valsalva maneuver. In tiers 2 and 3, a high agreement rate of 0.8076 and 0.8068 (p<0.001), respectively, on the weighted kappa index, and a high intra-class correlation coefficient of 0.9822 and 0.9860 (p<0.001), respectively, were observed on detecting MESs. Our data suggests that the BA window is as effective as the MCA window for detecting RLS on TCD.

CLASSIFYING COMPONENT FUNCTION IN PRODUCT ASSEMBLIES WITH GRAPH NEURAL NETWORKS

Function is defined as the ensemble of tasks that enable the product to complete the designed purpose. Functional tools, such as functional modeling, offer decision guidance in the early phase of product design where explicit design decisions are yet to be made. Function-based design data is often sparse and grounded in individual interpretation. As such, function-based design tools can benefit from automatic function classification to increase data fidelity and provide function representation models that enable function-based intelligent design agents. Function- based design data is commonly stored in manually generated design repositories. These design repositories are a collection of expert knowledge and interpretations of function in product design bounded by function-flow and component taxonomies. In this work, we represent a structured taxonomy-based design repository as assembly-flow graphs, then leverage a graph neural network (GNN) model to perform automatic function classification. We support automated function classification by learn- ing from repository data to establish the ground truth of component function assignment. Experimental results show that our GNN model achieves a micro-average F1-score of 0.832 for tier 1 (broad), 0.756 for tier 2, and 0.783 for tier 3 (specific) functions. Given the imbalance of data features, the results are encouraging. Our efforts in this paper can be a starting point for more sophisticated applications in knowledge-based CAD systems, and Design-for-X consideration in function-based design.