History File Research Articles

Long-Term Trajectories of Postoperative Recovery in Younger and Older Veterans

Major surgery sometimes involves long recovery or even permanent institutionalization. Little is known about long-term trajectories of postoperative recovery, as surgical registries are limited to 30-day outcomes and care can occur across various institutions. To characterize long-term postoperative recovery trajectories. This retrospective cohort study used Veterans Affairs (VA) Surgical Quality Improvement Program data (2016 through 2019) linked to the Residential History File, combining data from the VA, Medicare/Medicaid, and other sources to capture most health care utilization by days. Patients were divided into younger (younger than 65 years) or older (65 years or older) subgroups, as Medicare eligibility is age dependent. Latent-class, group-based trajectory models were developed for each group. These data were analyzed from February 2023 through August 2024. Surgical care in VA hospitals. Days elsewhere than home (DEH) were counted in 30-day periods for 275 days presurgery and 365 days postsurgery. A 5-trajectory solution was optimal and visually similar for both age groups (cases: 179 879 younger [mean age (SD) 51.2 (10.8) years; most were male [154 542 (83.0%)] and 198 803 older [mean (SD) age, 72.2 (6.0) years; 187 996 were male (97.6%)]). Most cases were in trajectories 1 and 2 (T1 and T2). T1 cases returned home within 30 days (younger, 74.0%; older, 54.2%), while T2 described delayed recovery within 30 to 60 days (younger, 21.6%; older, 35.5%). Trajectory 3 (T3) and trajectory 4 (T4) were similar for the first 30 days postsurgery, but subsequently separated with T3 representing protracted recovery of 6 months or longer (younger, 2.7%; older, 3.8%) and T4 indicating long-term loss of independence (younger, 1.3%; older, 5.2%). Few (trajectory 5) were chronically dependent, with 20 to 30 DEH per month before and after surgery (younger, 0.4%; older, 1.3%). In this study, trajectory models demonstrated clinically meaningful differences in postoperative recovery that should inform surgical decision-making. Registries should include longer-term outcomes to enable future research to distinguish patients prone to long-term loss of independence vs protracted, but meaningful recovery.

Climate Change and Building Renovation: The Impact of Historical, Current, and Future Climatic Files on a School in Central Italy

Climate change significantly affects the operating environment of buildings. These changes impact both energy efficiency and occupants’ comfort and remain crucial even in building restoration, where design decisions typically rely on historical data, yet performance depends on anticipated future scenarios. The present work evaluates the impact of different climate datasets on dynamic energy simulations for an educational building in Central Italy, focusing on estimating heating demands across historical, current, and future climatic scenarios. The assessment considers both the building’s current state and potential energy-efficient retrofits. Initially, various meteorological datasets, including measured and model-generated data, are selected to predict key weather parameters. The analysis reveals the potential and limitations of regional climate models (RCMs) in estimating these variables, with the MM5 dataset emerging as the most reliable. Subsequently, the energy performance of the reference building and its vulnerability to climate change are assessed. Our results show significant differences in energy demand based on construction periods, with the oldest section consuming 29% to 54% more energy monthly than the newer sections. Moreover, using non-representative climatic files can lead to prediction errors of up to 199%. Finally, the building’s energy behaviour is analysed under future climate conditions by generating typical meteorological years (TMYs) for 2030, 2050, and 2070. This analysis evaluates the energy requirements for both existing and retrofitted building configurations. The findings confirm that retrofit interventions with high-performance insulation and upgraded windows significantly enhance the building’s energy efficiency and resilience to future climate conditions, leading to annual energy savings of 50% to 57%.

Navigating financial risk: Unlocking the power of modeling and risk quantification in episode-based payment models.

28 Background: The Centers for Medicare and Medicaid Innovation’s (CMMI) Enhancing Oncology Model (EOM) is a voluntary value-based care (VBC) model that requires physician group practices (PGPs) to assume financial risk and performance accountability for episodes of care related to seven common cancers. However, PGPs often lack the means to assess the financial impact and risks associated with these alternative payment models. To address this, we employed Monte Carlo Simulations (MCS) to calculate the likelihood of outcomes and associated risks. This information can assist PGPs in making informed decisions about assuming risk and participating in the EOM. Methods: Using historical episode files from 2019 to 2022 for 23 PGPs in The US Oncology Network, along with the EOM Price Prediction Model provided by CMMI, we calculated the predicted baseline price and savings per episode. We then determined the average savings for each PGP per time-period and utilized the MCS technique to simulate savings and risk, under each EOM risk arrangement. We shared the simulation results with the PGPs to support their decision-making process and participation. Results: Despite having enough episodes per time-period (ranging from 105 to 6100) for the 23 PGPs, the limited number of time-based populations (only 6) based on case mix and patient volume made traditional probability assessments inadequate. To overcome this, we utilized MCS with 5000 simulations per PGP, assuming a normal distribution based on population characteristics. By assessing the savings outcomes of each simulation, we developed probability distributions and confidence intervals to determine the likelihood of generating shared savings, recoupment, or landing in the neutral zone within the EOM. Factors such as episode counts, baseline price, and risk arrangement had the greatest impact on the range of outcomes. We shared the MCS results with all 23 PGPs, highlighting the limitations of the original data and facilitating their decision-making process. Ultimately, 12 PGPs chose to assume risk based on the probability of financial outcomes with the model, and to select the appropriate risk arrangement in the EOM. Conclusions: Compared to the status quo measures of central dispersion, MCS yields a wide range of expected financial outcomes per PGP. MCS is a robust technique for quantifying outcome probabilities in VBC models despite low data volumes but relies on the representativeness and quality of the original data. Conducting sensitivity analysis with MCS to assess the impact of individual assumptions or data inputs on outcome probabilities is an area for further exploration.

CURL Extensions – Weaving a Unique Property Reference Number into Address Histories in the Scottish Community Health Index

The Community Health Index (CHI) is the patient registration system for the National Health Service (NHS) in Scotland, covering the entire population. CHI has long been used as a population Indexing Spine to facilitate health-based data linkage for both operational and research purposes in Scotland. Changes in patient’s residential address since 2000 have been captured in a CHI Address History File. Addresses in CHI are recorded in unstructured free-text format, so property-based analyses and linkage is problematic. In August 2020, 90% of CHI addresses for currently registered patients, and people who had died that year, were seeded with a Unique Property Reference Number (UPRN). This product, called CHI-UPRN Residential Linkage (CURL), enabled NHS Scotland to harness important information on the patient population (5.8 million) and their place of residence, facilitating several data products related to COVID-19. The current project is extending CURL to UPRN-seed the 31 million address histories of everyone registered with a family doctor in Scotland since January 2000. The project, due for completion in Summer 2024, will look at alternative address-matching algorithms with the aim of achieving a 95% UPRN-match rate across the longitudinal CURL file. Quality assurance exercises help us to understand the precision and sensitivity of matching across time and geography. Analysis of how the longitudinal file is constructed across the person and property-level indices permits a deeper understanding of the capabilities and limitations of the CURL product when used to deliver innovative analyses or modelling that link people and places over time.

Major Customers and the Speed of Leverage Adjustments

Purpose: This study investigates how major customers influence the speed of adjustment (SOA) in a firm's capital structure, specifically examining the effects of governmental versus non-governmental major customers.Study design/methodology/approach: The study employs Blundell and Bond’s (1998) GMM model to estimate SOA. Robustness methods include fixed effects, two-stage least squares (2SLS), propensity score matching (PSM), and the augmented doubly censored Tobit (DPF estimator).Sample and data: The sample consists of 186,240 firm-year observations from Compustat North America annual files and Compustat historical segment files, spanning 1978 to 2013. Firms in the utility and financial sectors are excluded.Results: Findings indicate that major customers significantly influence SOA by reducing market uncertainty through certifications. Firms with major customers have a higher SOA, with governmental customers exhibiting an even higher SOA than non-governmental ones. Results are consistent across various models and settings.Originality/value: This study uniquely identifies major customers as critical determinants of SOA, highlighting the heterogeneities in firms' SOA. It stresses the importance of considering customer type in financial strategies, differentiating between governmental and non-governmental impacts. These findings offer valuable insights for scholars, policymakers, and practitioners.Research limitations/implications: Focusing on publicly listed U.S. firms limits generalization. Future research should extend the analysis to other regions and recent periods. The findings provide insights for supplier firms in strategizing financial decisions and managing relationships with major customers. We emphasize the significant role of major customers in financial strategies, advocating for more detailed disclosure policies in the U.S. and globally to enhance transparency and market efficiency.

Enhanced Feature-driven Multi-objective Learning for Optimal Cloud Resource Allocation

In cloud networks, especially those with distributed computing setups and data centers, one of the biggest obstacles is allocating resources. This is the key area, and this must be balanced between optimizing system performance on one side and affordability, stability (reliance) of operation, and energy efficiency. The importance of improving resource allocation methodologies in these complex cloud computing systems is recognized, and therefore this paper comes with an appropriate title--“Enhanced Feature-Driven Multi-Objective Learning for Optimal Cloud Resource Allocation” (OCRA), which integrates together both the latest machine learning techniques as well as traditional concepts from research into cloud computing. OCRA capably analyzes historical files on CPU, memory, disk and network usage. In addition to neatly assimilating large data sets such as that was the compliance rate with past SLAs or workload frequencies over certain time periods and resource allocations; even their patterns of service requests are an important piece of information for many busy people’s lives today the adaptive mechanism is one of the defining traits of the model. It can accurately anticipate changes in resource demand and immediately adjust supply, fully able to respond rapidly when fluctuations arise suddenly or unexpectedly. Multi-Objective Random Forests are at the very core of OCRA. Each tree for decision making is specially designed to meet a particular performance objective in mind. Combining these trees into a Random Forest ensemble increases not only the model's predictive accuracy but also its stability. Pareto optimization is wisely used to maintain a balance among performance indicators, without an excessive focus on one effect alone. OCRA is proven empirically through experimental studies where key performance indicators such as Resource Utilization Rate and Quality of Service (QoS) Adherence Rate are taken into account. OCRA is both energy-efficient, an important attribute in today's environmentally conscious world, and does not sacrifice performance. As far as speed, flexibility and overall efficiency are concerned, OCRA has always been superior to the other cloud resources allocation programs of its own day. While it's still not quite ready for users who don't have a firm background in computer science or programming skills (ocra is plotted on 0-x), with sufficient memory and dominant minutes turn into mechanical equipment without configuration services.

Historical child sexual abuse cases reported to the police by Indigenous adults in a northern Canadian territory: an exploration of factors affecting the likelihood of charges and convictions

ABSTRACT The current research examined historical child sexual abuse files from a northern Canadian police force, looking at factors pertaining to the offence, the complainant and the suspect, in an area with a large Indigenous population. The dataset analysed represented all reported cases (N = 229) of historical child sexual abuse by Indigenous complainants in the database of the participating force from 2005 to 2019. Analysis of all cases showed charges were more likely in cases with multiple complainants, female complainants and complainants 11–14 years old at the time of the abuse. For cases where charges were laid (n = 135), convictions were slightly more likely in cases with less serious offences. For trial cases (n = 75), multiple complainants, the relationship of suspect to complainant, age of suspect and age difference between complainant and suspect were significantly associated with trial outcome. Ethnicity of suspects showed no relationship to charges or convictions. PRACTICE IMPACT STATEMENT This research demonstrates the importance of support for all victims of historical child sexual abuse when navigating the difficult process of disclosing abuse and engaging the criminal justice process. In particular, Indigenous men may need increased access to victim services, given the finding that they are less likely to see charges and convictions at trial for their cases. Continued public education encouraging reporting of child sexual abuse, even for victims of historical crimes, is needed as cases with long delays between offence and report are just as likely to result in charges and convictions as cases with less delay.

CMD + V for chemistry: Image to chemical structure conversion directly done in the clipboard

AbstractWe present Clipboard‐to‐SMILES Converter (C2SC), a macOS application that directly converts molecular structures from the clipboard. The app focuses on seamlessly converting screenshots of molecules into a desired molecular representation. It supports a wide range of molecular representations, such as SMILES, SELFIES, InChI's, IUPAC names, RDKit Mol's, and CAS numbers, allowing effortless conversion between these formats within the clipboard. C2SC automatically saves converted molecules to a local history file and displays the last 10 entries for quick access. Additionally, it incorporates several SMILES operations, including canonicalization, augmentation, as well price‐searching molecules on chemical vendors for the cost‐effective purchasing option. Beyond the one‐click conversion from clipboard to molecular structures, the app offers continuous monitoring of the clipboard which automatically converts any supported representations or images detected into SMILES. The convenient interface, directly in the status bar, as well as availability as macOS application, makes C2SC useful for a broad community not requiring any programming expertise. Most conversions are performed locally, notably the image‐to‐SMILES conversion, with internet access only necessary for specific tasks like price lookups. In summary, C2SC provides a user‐friendly and efficient solution for converting molecular structures directly from the clipboard, offering seamless conversions between comprehensive chemical representations and can be directly downloaded from https://github.com/O-Schilter/Clipboard-to-SMILES-Converter.

Research on the Dilemma and Countermeasure of Cadre Personnel File Management

Personnel file management, as an effective means of cadre management, involves various links such as file collection and sorting, file review, file search and borrowing, file transfer, etc. In order to give full play to its important role in cadre and talent work, this paper briefly summarizes the current situation and development history of cadre and personnel files, and identifies the existing problems and causes of current archive management. The improvement measures are put forward.

History File of the Theater “Scala” in Bălți City During the Years 1934-1977

The article proposes new information about the history of the “Scala” Theater in the city of Bălți. The following aspects are elucidated: to what extent the “Scala” theater in the city of Bălți managed to justify the expectations of the local administration and the general public; what was the contribution of this institution in the cultural affirmation of the city of Bălți in the various periods that marked its existence for about four decades of activity, from the year of its inauguration – 1934, until the moment of the demolition of the last pillar of the edifice – 1977; how present is the image of the “Scala” theater in the cultural memory of the city today. On the stage of the “Scala” Theater, leading personalities of Romanian art played, such as: “Maria Filotti (actress), George Enescu, Constantin Tănase, Maria Tănase, Vasile Popovici, Gică Petrescu.

Racial Disparities in Breast Cancer Treatments and Adverse Events in the SEER-Medicare Data.

Despite lower incidence rates, African American (AA) patients have shorter survival from breast cancer (BC) than white (W) patients. Multiple factors contribute to decreased survival, including screening disparities, later presentation, and access to care. Disparities in adverse events (AEs) may contribute to delayed or incomplete treatment, earlier recurrence, and shortened survival. Here, we analyzed the SEER-Medicare dataset, which captures claims from a variety of venues, in order to determine whether the cancer care venues affect treatment and associated adverse events. We investigated a study population whose claims are included in the Outpatient files, consisting of hospital and healthcare facility venues, and a study population from the National Claims History (NCH) files, consisting of claims from physicians, office practices, and other non-institutional providers. We demonstrated statistically and substantively significant venue-specific differences in treatment rates, drugs administered, and AEs from treatments between AA and W patients. We showed that AA patients in the NCH dataset received lower rates of treatment, but patients in the Outpatient dataset received higher rates of treatment than W patients. The rates of recorded AEs per treatment were higher in the NCH setting than in the Outpatient setting in all patients. AEs were consistently higher in AA patients than in W patients. AA patients had higher comorbidity indices and were younger than W patients, but these variables did not appear to play roles in the AE differences. The frequency of specific anticancer drugs administered in cancer- and venue-specific circumstances and their associated AEs varied between AA and W patients. The higher AE rates were due to slightly higher frequencies in the administration of drugs with higher associated AE rates in AA patients than in W patients. Our investigations demonstrate significant differences in treatment rates and associated AEs between AA and W patients with BC, depending on the venues of care, likely contributing to differences in outcomes.

Multiscale modeling to optimize thermal performance design for urban social housing: A case study

Climate change impacts the entire planet, and its effects are particularly evident in urban areas. Northern cities in Brazil experience a hot and humid climate, which poses a challenge to achieving high levels of thermal performance in housing developments. This challenge is amplified by the fact that most residents do not have access to air conditioning systems, making it difficult to mitigate the heat. Current technologies have the potential to confront this critical situation by diagnosing thermal performance and implementing optimized strategies for modeling multiple climatic scales, including the city, neighborhood, and indoor environment. Therefore, this study aims to fill a research gap by utilizing simulations to predict and optimize the thermal performance of naturally ventilated social housing in hot and humid equatorial climates, while considering the effects of climate change. Adaptive modeling principles were applied, fostering synergy among the meso, local, and microclimatic scales through a unidirectional simulation. The results revealed that the region experiencing the highest real estate growth has witnessed a significant increase in temperature over the years. The comparison between historical and future climate files confirmed predictions of climate change in a pessimistic scenario, particularly regarding temperature and relative humidity indicators. When climate files adjusted for future climate conditions were used, it was discovered that passive building design strategies had a stronger impact on the microclimate compared to heat island mitigation strategies. This impact led to better building thermal performance. However, at the building scale, thermal performance is highly influenced by climate change and could be reduced by up to 11% (in 2020) and 39% (in 2050).

Is alveolar osteitis more prevalent since COVID-19? A cross-sectional study

Objectives: The aim of the study was to analyze the association between post-extraction alveolar osteitis and coronavirus disease 2019 (COVID-19) in a single center. Material and Methods: A monocentric cross-sectional study was carried out at NSVK Sri Venkateshwara Dental College and Hospital located in Bannerughatta, Bengaluru in the Department of Oral and Maxillofacial Surgery from January 2021 to August 2022. The study sample comprised 50 participants; an extraction of one or more teeth was performed on women and men between the age group of 15–83 years and returned with complication of alveolar osteitis. Demographic details such as age, gender, medical history, personal habits, COVID-19 immunization history, history of COVID-19, and its complications were acquired from the patient’s case history files throughout the study and recorded. Descriptive statistics were used to analyze the collected data. Chi-square test was used to check for association between the groups. Results: Females (62%) were majority of the study participants with an average age of 40 years. Of the patients reported to the hospital, 46% were COVID-positive, 38% were smokers, 48% consumed alcohol, and 80% presented with some underlying systemic condition. A statistically significant association was seen between history of COVID-19 positive patients and systemic condition with P = 0.014 (P ≤ 0.05). Conclusion: Patients with systemic conditions were more prone to dry socket; however, personal habits such as smoking, alcohol, and use of tobacco showed no direct relationship. According to study, previous history of COVID-19 infection did not have significant effects in regards to alveolar osteitis. Thus, more research on recovered COVID-19 patients should be done to understand the etiology of dry socket.

Good-Bye I/B/E/S (or Not?)

ABSTRACT In October 2018, I/B/E/S claimed to have anonymized the identifications (IDs) of 88 brokers and their analysts in its Detail History Files. This paper examines to what extent the change affects the post-2018 Detail History File. The main findings are as follows. First, there is no evidence of a large-scale ID anonymization for the annual and quarterly EPS forecasts for U.S. firms. Second, the anonymization predominantly affects the forecasts of non-U.S. firms. A significant percentage of forecasts for non-U.S. firms have been anonymized since January 2017 (at least one year earlier than what was claimed). Third, there is no evidence of a large-scale ID reshuffling of forecasts between the 2015 and 2021 Detail History Files. Last, because the anonymization has very little effect on the Recommendations Detail File, I am able to offer detailed steps to reverse engineer the anonymized analyst IDs in the Unadjusted Detail History File. JEL Classifications: G00; M41.

Modeling unrelated blood stem cell donor recruitment using simulated registrant cohorts: Assessment of human leukocyte antigen matching across ethnicity groups.

Human leukocyte antigen (HLA)-matched unrelated donors are not available for some patients considered for allogeneic hematopoietic cell transplantation, particularly among certain ethnic groups. Simulated recruitment modeling can inform efforts to find new matches for more patients. Simulated recruits were generated by assigning a pair of donor HLA haplotypes from historical data files and matched against HLA data of patient searches in the Canadian Blood Services Stem Cell Registry. Recruitment cohorts reflected the proportion of five specific ethnic groups in the 2016 Canadian census data. Novel 8/8 HLA matches between simulated recruits and patients increased linearly with larger recruitment cohorts. The proportion of novel 8/8 HLA matches from Caucasian, Hispanic, and Native American/First Nations recruits was equal to or greater than their relative proportion in the recruited cohort (match to: recruit ratio (MRR) ≥ 1). In contrast, African American and Asian & Pacific Islander recruits represented a smaller proportion of novel matches relative to their percentage of the recruited cohort (MRR <1). The proportion of novel 7/8 HLA-matches from each ethnic group was approximately the same as their proportion in the recruited cohort (MRR ~ 1) and high rates of 7/8 HLA-matching already exist within the Canadian Blood Services registry for all ethnic groups. Continued large recruitment cohorts are needed to add new 8/8 HLA matches to registry inventories. Likelihoods of novel HLA matches varied across ethnic groups, reflecting varied HLA haplotype frequencies across groups. Simulated cohort modeling can inform recruitment strategies that will generate new donor options for patients.

Degradation reduces greenhouse gas emissions while weakening ecosystem carbon sequestration of Moso bamboo forests

Moso bamboo (Phyllostachys heterocycla cv. Pubescens) is well known for its high capacity to sequester atmospheric carbon, which has a unique role to play in combating global warming. Many Moso bamboo forests are gradually degrading due to rising labor costs and falling prices for bamboo timber. However, the mechanisms of carbon sequestration of Moso bamboo forest ecosystems in response to degradation are unclear. In this study, a space-for-time substitution approach was used to select Moso bamboo forest plots with the same origin and similar stand types, but different years of degradation, and four degradation sequences, continuous management (CK), 2 years of degradation (D-I), 6 years of degradation (D-II) and 10 years of degradation (D-III). A total of 16 survey sample plots were established based on the local management history files. After a 12-month monitoring, the response characteristics of soil greenhouse gases (GHG) emissions, vegetation, and soil organic carbon sequestration in different degradation sequences were evaluated to reveal the differences in the ecosystem carbon sequestration. The results indicated that under D-I, D-II, and D-III, the global warming potential (GWP) of soil GHG emissions decreased by 10.84 %, 17.75 %, and 31.02 %, while soil organic carbon (SOC) sequestration increased by 2.82 %, 18.11 %, and 4.68 %, and vegetation carbon sequestration decreased by 17.30 %, 33.49 %, and 44.76 %, respectively. In conclusion, compared to CK, the ecosystem carbon sequestration was reduced by 13.79 %, 22.42 %, and 30.31 %, respectively. This suggests that degradation reduces soil GHG emissions but weakens the ecosystem carbon sequestration capability. Therefore, in the background of global warming and the strategic goal of carbon neutrality, restorative management of degraded Moso bamboo forests is critically needed to improve the carbon sequestration potential of the ecosystem.

Impact of climate change on the life cycle greenhouse gas emissions of cross-laminated timber and reinforced concrete buildings in China

With the urgency of addressing climate change, cross-laminated timber (CLT) has become a sustainable material to substitute reinforced concrete (RC) in building applications. There is a growing number of studies on the life cycle assessment of CLT buildings worldwide, mainly based on historical weather files. This study integrates climate change on life cycle greenhouse gas emissions (LCGHGE) in CLT and RC buildings in five climate zones, including the product and construction (P&C), operational and End-of-Life (EoL) stages. The CCWorldWeatherGen tool is used to generate future weather data (i.e., the 2020s, 2050s and 2080s) for the A2 emissions scenario. The simulation results show heating demands will decline significantly and cooling demands will rise in all cases. By the 2080s, global warming will result in an average LCGHGE of 33.09% and 38.90% higher than the baseline scenario for RC and CLT buildings, respectively. Strategies to reduce space cooling demand and decarbonize electricity will become increasingly important in the future. The average LCGHGE of CLT buildings is 27.53%, 26.22%, 24.67% and 22.19% lower than those of RC alternatives in the baseline, the 2020s, 2050s and 2080s, respectively. The study demonstrates that the lower greenhouse gas (GHG) emissions and the greater benefits from EoL from CLT buildings outweigh the operational GHG savings benefits from the thermal mass of RC buildings, even when climate impact is taken into account. Therefore, CLT buildings are a feasible way to reduce GHG emissions from buildings in China.

The Vatic Weather File Generator (VWFG v1.0.0)

To combat climate change caused by cities, it is necessary to perform urban physics modeling to assess mitigation solutions suitable for future climates. A challenge is availability of reliable future weather files for investigation of future climate scenarios. This research aims to develop the Vatic Weather File Generator (VWFG) using the statistical downscaling approach to fill this gap. VWFG is novel by using a history of weather files over multiple years to downscale future climate model data utilizing (1) quantile–quantile bias corrections, (2) record matching by the Finkelstein–Schafer method, and (3) shifting–stretching corrections. This implementation of VWFG uses the CanRCM4 climate model (1980–2100) and the ERA5 reanalysis data product as weather files (1980–2020) for two Representative Concentration Pathway (RCP) scenarios. VWFG outputs are consistent with findings in other studies. Further, to investigate the performance of VWFG for a case in Toronto, Canada, the Vertical City Weather Generator (VCWG) is forced by VWFG to predict the building sensible heating and cooling energy demands for a two-story single-family residential house. It is found that the building sensible heating demand is reduced over time (∼ 15%–30% for RCP 4.5–8.5 W m−2) and the building sensible cooling demand is increased over time (∼ 20%–50% for RCP 4.5–8.5 W m−2). The amount of change is greater for RCP 8.5 than RCP 4.5 W m−2. VWFG is a simple, practical, and widely applicable tool for urban physics simulations of future climates, particularly in cases where reliable forcing data is lacking otherwise.

Research on the implementation and practice of the CCAMLR System of Inspection

Abstract The CCAMLR System of Inspection has been in place for more than 30 years, but its implementation and impact have yet to be summarised and analysed. The purpose of the research is to clarify the legal basis, analyse the implementation and make suggestions for further improvements. By analysing the CAMLR Convention and historical files, the System of Inspection has been further improved and many details have been added based on some international fisheries agreements and domestic laws regulating fisheries. Article XXIV of the CAMLR Convention, various Conservation Measures and documents form the legal basis of the System of Inspection. The System is divided into two types, namely At-sea inspection and Port inspection. Combined with the annual reports of CCAMLR meetings over the past 30 years, the System has become relatively complete as a “Compliance Monitoring Mechanism” under the CCAMLR Compliance Evaluation Procedure with other monitoring, control and surveillance (MCS) tools. However, inspection data have not been stable over the years. Since 2017, the increase in catches has not led to an increase in the number of inspections in the annual reports. In addition, At-sea inspections do not cover all Subareas of the Convention. At present, the objects of inspection have been extended to Non-Member vessels, so that it should also be sanctioned through various mechanisms. In addition, the System of Inspection is different from the Compliance Evaluation Procedure and the relationship between the two needs to be confirmed in practice. Due to the change in inspection methods, the lack of inspection data and the increase in other MCS tools, At-sea inspection does not cover all Subareas of the Convention. The System of Inspection is constantly being practised and improved. The study calls on Members to continue to carry out inspections and to improve the System in order to achieve the conservation and rational use of fishery resources.

DISCHARGE LOCATIONS AFTER HOSPITALIZATIONS INVOLVING OPIOID USE DISORDER AMONG MEDICARE ENROLLEES

Abstract Hospitalizations involving opioid use disorder (OUD) are increasing in the Medicare population. Rising OUD-related acute care use emphasizes the need to understand where post-acute care is provided and opportunities to facilitate OUD treatment in those settings. We conducted a retrospective cohort study using 2016-2018 Medicare Provider Analysis and Review (MedPAR) files linked to enrollment data and the Residential History File (RHF) for 100% of Medicare fee-for-service beneficiaries aged ≥18 years. We used diagnostic codes for opioid dependence or “abuse” to identify OUD from MedPAR data. The RHF identified hospital discharge locations. Our analysis included 459,763 OUD-related hospitalizations. Overall, individuals &amp;lt; 65 years (60.3%), female (53.7%), or Medicare-Medicaid dually enrolled (59.1%) were the majority. The mean (standard deviation) length of stay was 5.5 (6.6) days and 31.3% of OUD-related hospitalizations required intensive care use. Seventy percent of patients with OUD-related hospitalizations were discharged home, 15.8% to skilled nursing facilities (SNFs), 9.6% to non-SNF institutional facilities, 2.5% home with home health services, and 1.8% died in-hospital. Within 30 days of hospital discharge, the range for 30-day all-cause readmissions was 27.7% (home) to 47.5% (non-SNF institutional setting). The 30-day all-cause mortality ranged from 3.1% (home without health) to 6.4% (non-SNF institutional settings). Given that over one-quarter of OUD-related hospitalizations resulted in discharge to locations other than home and that many institutional post-acute care settings cannot obtain OUD medications, modifying Drug Enforcement Administration regulations and expanding access to OUD medications for aging adults in post-acute and long-term care settings must be a near-term policy focus.