Filling Rate Research Articles

Mechanical Behavior and Crack Evolution of Goaf Surrounding Rock with Different Roof-Contacted Filling Rates.

The goaf formed by mining is filled and treated, which greatly improves the safety and stability of the surrounding rock. During the filling process, the roof-contacted filling rates (RCFR) of goaf were closely related to the stability control of the surrounding rock. The influence of the roof-contacted filling rate on the mechanical characteristics and crack propagation of the goaf surrounding rock (GSR) has been studied. Biaxial compression experiments and numerical simulation experiments were conducted on samples under different operating conditions. The results were as follows: (1) The peak stress, peak strain, and elastic modulus of the GSR are closely related to the RCFR and the goaf size; they increase with the increase of the RCFR, and decrease with the increase of the goaf size; (2) In the initial loading stage, a small number of cracks are generated, and the acoustic emission ringing count increases slowly. The mid-loading stage is the crack initiation and rapid expansion, and the cumulative ring count curve shows a "stepwise" growth. In the later loading stage, cracks continue to propagate and form macroscopic fractures, but the number of rings significantly decreases; (3) Shear cracks are prone to occur in the rock part of the GSR; tensile cracks are prone to occur in the backfill; and the crack propagation speed in the rock is faster than in the backfill. Stress concentration is the direct cause of GSR failure. The maximum concentrated stress of rock mass and backfill is 1~2.5 times and 0.17~0.7 times of the peak stress of the GSR, respectively.

Measurement Strategies for The Joint Commission Health Care Disparities Standard: Defining Hospital-Based Requirements—Part 1

Measurement Strategies for The Joint Commission Health Care Disparities Standard: Defining Hospital-Based Requirements—Part 1

Controller therapy attenuates asthma exacerbations associated with prior severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in children

Controller therapy attenuates asthma exacerbations associated with prior severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in children

Fill‐rate service level constrained distribution network design

AbstractThe design of distribution networks that simultaneously consider location and inventory decisions seeks to balance costs and product availability. The most commonly observed measure of product availability in practical settings is the fill‐rate service level. However, the optimal design of a distribution network that considers the fill rate to control shortages of fast‐moving consumer goods (FMCG) is considered intractable and has only been addressed by heuristic methods. This paper addresses the optimal design of a distribution network for FMCG able to provide high fill‐rate service level under a continuous review policy. Considering the exact formulation for the provided fill rate, we formulated a joint location–inventory model with fill‐rate service level constraints as a convex mixed integer nonlinear problem for which a novel decomposition‐based outer approximation algorithm is proposed. Numerical experiments have shown that our solution approach provides good‐quality solutions that are on average 0.15% and, at worst, 2.2% from the optimal solution.

An adaptive product changeover policy for a capacitated two-product supply chain in a non-stationary demand environment

ABSTRACT The present paper investigates the effectiveness, in terms of fill rate, of a new adaptive production control policy for a two-product, two-echelon (i.e. factory and retailer) supply chain subject to a non-stationary customer demand. To model the capacity constraints more realistically, the factory node consists of an unbuffered production line subject to failures, and non-negligible changeover times. To cope with the disruptive events, we propose a new production control strategy named Adaptive Hedging Corridor Policy. A simulation model based on discrete-time difference equations is developed, and a two-step experimental campaign is conducted to compare the proposed control policy with two well-known alternatives proposed in the literature. The analysis of the results demonstrates the effectiveness of the new adaptive strategy in maximising the fill rate of supply chains subject to a non-stationary demand.

Development of natural language processing (NLP) models for extracting key features from unstructured notes to create real-world data (RWD) assets for clinical research at scale.

6607 Background: RWD derived from Electronic Health Records (EHR) has detailed clinical information about patient journeys that can assist in clinical research, trial design, safety assessments etc. However, much of the vital information is locked away in unstructured clinical texts and needs to be converted to structured format to be useful for downstream applications. We demonstrate how this can be achieved at scale with a high degree of accuracy through NLP. Methods: NLP models were developed to extract data for 11 clinical variables from unstructured notes of ~98k lung cancer patients and merged with the structured data into a common data model (Table). These models were a combination of domain knowledge, rule-based models, machine learning models, and deep learning models. The increase in fill rate per variable over structured data only was used to quantify the improvement by NLP. The accuracy of the models was assessed against a manually curated dataset comprising of 752 patients. Results: The NLP models significantly improved the fill rate of key clinical variables and were able to extract the information from clinical notes with high accuracy (Table). For some variables such as NSCLC/SCLC status, surgery, tumor grade and histology, all or most of the data was extracted via NLP. Metastatic status via NLP included distant metastasis, locally advanced disease and no metastasis whereas in the structured data, only data for distant metastasis was present. In the case of Performance Status (PS), even though a significant number of patients had at least 1 PS recorded in the structured data, NLP significantly increased longitudinal capture, thus increasing the density of this variable per patient. Conclusions: NLP models can be developed and used to enrich structured RWD data by extracting information from unstructured documents thus significantly improving the utility of this data for downstream applications. Given the high accuracy of these models and the scale at which they can be run, this can be a good alternative to human curation or can augment human curation enabling the creation of very large-scale datasets for clinical research. [Table: see text]

On fairness and efficiency in nonprofit operations: Dynamic resource allocations

We study a sequential resource allocation problem balancing fairness and efficiency for nonprofit operations. (Un)fairness is measured by the expected maximum demand shortfall among all communities, and (in)efficiency is measured by the expected remaining resources after allocation. We characterize the optimal allocation policy as a two‐threshold policy in which the optimal allocation quantities are spoon‐shaped in terms of the current maximum demand shortfall. We further show that the thresholds and optimal allocation quantity for each community are nondecreasing in resource levels, realized demand from the current community, and weight of the efficiency objective. Based on these results, we propose a simple heuristic policy and numerically show that it performs well and generates fair allocations in a stochastic majorization order. The numerical results show that adding a small weight to the fairness objective significantly improves the system's fairness at a small efficiency cost. Moreover, the optimal initial capacity level is increasing (decreasing) in demand variance if the efficiency weight is small (large). Our theoretical analysis can be extended to the fill rate–based fairness metric.

PCR2 The Magnitude of the Association between Insulin Adherence Based on Prescription Fill Rate Measures and Glycemic Control: A Systematic Review and Meta-Analysis

Despite studies measuring association of insulin adherence and glycemic control in type 2 diabetes mellitus (T2DM), the magnitude and significance of association remains unclear. This study aims to summarize evidence on the association between insulin adherence and glycemic control in adults with T2DM.

Sensitivity Analysis of Al0.3Ga0.7N/GaN Dielectric Modulated MOSHEMT Biosensor

Emerging and newly proposed devices integrate various materials at different scales (from nano to submicron), which reveals sensor response. Prefab simulation is in great demand to elucidate fundamental biosensor phenomena that are based on transistors. Numerous HEMT-based biosensors have been developed, however, MOSHEMT deserves to be further investigated. The sensitivity analysis with neutral and charged biomolecules is thus carried out in this research using a single gate high-κ dielectric MOSHEMT through Technology Computer Aided Design simulation. The device performance is evaluated through the shift (sensing action) of device parameters like Two-Dimensional Electron Gas, on-current, transconductance, drain current and output conductance due to the immobilization of biomolecules in the cavity created under the gate. For the neutral biomolecule (), the fluctuation in on-current, transconductance, drain current, and output conductance is determined to be 330.3 μA μm−1, 102.0 μS μm−1, 319.0 μA μm−1, and 534.9 μS μm−1, respectively. Positively charged biomolecules were more sensitive to the device than negatively charged ones. Analysis is done on the response to the fill rates of the biomolecules in the cavity. For the vertical, horizontal, and tapered profiles, the transconductance sensitivities are 0.65, 0.17, and 0.32 and the drain current sensitivities are 0.25, 0.16, and 0.27 at the lowest fill (25%). In light of this, the AlGaN/GaN dielectric modulated MOSHEMT assures that the device can be used in sensitive intelligent biomedical applications.

Stochastic joint replenishment problem under a fill rate constraint with controllable lead times and shared cost allocation

In a family of items under coordinated inventory replenishments, some products may be replenished at the same time, which in turn implies that some lead time components and costs may be shared among them. This paper investigates this aspect in the context of the joint replenishment problem under the class of cyclic policies, assuming random demands and controllable lead times, and imposing a fill rate constraint for each item.

The knock-on effects of COVID-19 pandemic on the supply and availability of generic medicines in Ethiopia: mixed methods study

BackgroundCOVID-19 pandemic posed a major impact on the availability and affordability of essential medicines. This study aimed to assess the knock-on effects of the COVID-19 pandemic on the supply availability of non-communicable chronic disease (NCD) medicines and paracetamol products in Ethiopia.MethodsA mixed methods study was conducted to assess the supply and availability of twenty-four NCD drugs and four paracetamol products listed on the national essential medicines list for hospitals. Data were collected from twenty-six hospitals located in seven zones of Oromia region in the southwestern part of Ethiopia. We extracted data on drug availability, cost and stock out for these drugs between May 2019 and December 2020. The quantitative data were entered into Microsoft Excel and exported to statistical package software for social science (SPSS) version 22 (IBM Corporation, Armonk, NY, USA) software for analysis.ResultsThe overall mean availability of selected basket medicines was 63.4% (range 16.7% to 80.3%) during the pre-COVID-19 time. It was 46.3% (range 2.8% to 88.7) during the pandemic. There was a relative increase in the availability of two paracetamol products [paracetamol 500 mg tablet (67.5% versus 88.7%) and suppository (74.5% versus 88%)] during the pandemic. The average monthly orders fill rates for the selected products range from 43 to 85%. Pre-COVID-19, the average order fill rate was greater or equal to 70%. However, immediately after the COVID-19 case notification, the percentage of order(s) filled correctly in items and quantities began decreasing. Political instability, shortage of trained human resources, currency inflation, and limited drug financing were considered as the major challenges to medicine supply.ConclusionThe overall stock out situation in the study area has worsened during COVID-19 compared to pre-COVID-19 time. None of the surveyed chronic disease basket medicines met the ideal availability benchmark of 80% in health facilities. However, availability of paracetamol 500 mg tablet surprisingly improved during the pandemic. A range of policy frameworks and options targeting inevitable outbreaks should exist to enable governments to ensure that medicines for chronic diseases are consistently available and affordable.

A lower canal fill rate and unreestablished vertical femoral offset may increase the risk of the postoperative periprosthetic fractures after cementless bipolar hemiarthroplasty for femoral neck fractures in elderly patients.

Periprosthetic fractures (PPFs) is one of the major causes of failure of hip arthroplasty with cementless stem; however, studies on the incidence and risk factors of PPFs after cementless hemiarthroplasty for femoral neck fractures (FNFs) are lacking. This retrospective study included patients who underwent cementless bipolar hemiarthroplasty for displaced intracapsular FNFs. The demographic data were reviewed, Dorr classification was used to describe morphology of the femur, radiological parameters were measured including stem-shaft angle, canal fill ratio (CFR), canal flare index (CFI), morphologic cortical index (MCI), canal calcar ratio (CCR), and vertical and horizontal femoral offset. The sample comprised 10 men and 46 women (affected hip: left, 38; right, 18). The mean patient age was 82.82±10.61 (range, 69-93) years, and the mean hemiarthroplasty to PPFs time was 26.28±14.04 (range, 6.54-47.77) months. Seven (12.28%) patients had PPFs. A significant relationship was found between the incidence of PPF and CFR (p = 0.012), patients had a significantly smaller femoral stem CFR (0.76%±0.11%) than controls (0.85%±0.09%). The PPFs group had a significant shorter and unreestablished vertical femoral offset (p = 0.048). A smaller femoral stem CFR associated with a potentially unacceptably high PPFs risk in uncemented hemiarthroplasty for displaced FNFs may result from mismatched prosthesis and bone dimensions in the elderly population, especially when accompanied by a poorly reestablished vertical femoral offset. With increasing evidence of the benefits of cemented fixation, a cemented stem for the treatment of displaced intracapsular FNFs is recommended for such a elderly frail population.

Usage of 3D printing technology in centrifugal pumps and material selection

The fused deposition modeling (FDM) technique which is one of the 3D printing technologies was used to produce a centrifugal pump impeller. The fabrication and investigation of the impeller were preferred because of its complex geometry and the difficulties encountered in its production. The most commonly used ABS, HIPS, PLA, and carbon fiber filaments were preferred to compare and determine the most suitable material for the production of the impellers. Firstly, mechanical test specimens from four different materials were printed in the 3D printer according to standards. Then the tensile tests and quasi-static punch shear tests (QS-PST) were applied to determine the mechanical properties of the 3D printed parts. Also, the mechanical tests were repeated to some specimen with the different fillings to define the optimum fill rates. Secondly, the impellers were fabricated from four materials by using the 3D printer in determined fill rates. Then, these impellers were mounted in the actual pump system, and pump performance tests were performed. In the pump performance tests, the head, pump efficiency, and electric power parameters were measured against the flow rate for each impeller. Finally, the mechanical properties and pump performance of the impellers compared with the GG25 cast iron impeller which is produced by traditional technique. As a result, PLA was selected as the most appropriate material for the production of the impellers. Furthermore, PLA showed superior performance compared to others when price, production time, and product weight parameters were considered.

Receipt of Medications for Chronic Disease During the First 2 Years of the COVID-19 Pandemic Among Enrollees in Fee-for-Service Medicare

During the first 2 years of the COVID-19 pandemic, inpatient and ambulatory care declined dramatically. Little is known about prescription drug receipt during this period, particularly for populations with chronic illness and with high risk of adverse COVID-19 outcomes and decreased access to care. To investigate whether receipt of medications was maintained during the first 2 years of the COVID-19 pandemic among older people with chronic diseases, particularly Asian, Black, and Hispanic populations and people with dementia, who faced pandemic-related care disruptions. This cohort study used a 100% sample of US Medicare fee-for-service administrative data from 2019 to 2021 for community-dwelling beneficiaries aged 65 years or older. Population-based prescription fill rates were compared for 2020 and 2021 vs 2019. Data were analyzed from July 2022 to March 2023. The COVID-19 pandemic. Age- and sex-adjusted monthly prescription fill rates were calculated for 5 groups of medications commonly prescribed for chronic disease : angiotensin-converting enzyme inhibitors and angiotensin receptor blockers, 3-hydroxy-3-methylglutaryl coenzyme A (HMG CoA) reductase inhibitors (statins), oral diabetes medications, asthma and chronic obstructive pulmonary disease medications, and antidepressants. Measurements were stratified by race and ethnicity group and dementia diagnosis. Secondary analyses measured changes in the proportion of prescriptions dispensed as a 90-day or greater supply. Overall, the mean monthly cohort included 18 113 000 beneficiaries (mean [SD] age, 74.5 [7.4] years; 10 520 000 females [58.1%]; 587 000 Asian [3.2%], 1 069 000 Black [5.9%], 905 000 Hispanic [5.0%], and 14 929 000 White [82.4%]); 1 970 000 individuals (10.9%) were diagnosed with dementia. Across 5 drug classifications, mean fill rates increased by 2.07% (95% CI, 2.01% to 2.12%) in 2020 and decreased by 2.61% (95% CI, -2.67% to -2.56%) in 2021 compared with 2019. Fill rates decreased by less than the mean overall decrease for Black enrollees (-1.42%; 95% CI, -1.64% to -1.20%) and Asian enrollees (-1.05%; 95% CI, -1.36% to -0.77%) and people diagnosed with dementia (-0.38%; 95% CI, -0.54% to -0.23%). The proportion of fills dispensed as 90-day or greater supplies increased during the pandemic for all groups, with an increase per 100 fills of 3.98 fills (95% CI, 3.94 to 4.03 fills) overall. This study found that, in contrast to in-person health services, receipt of medications for chronic conditions was relatively stable in the first 2 years of the COVID-19 pandemic overall, across racial and ethnic groups, and for community-dwelling patients with dementia. This finding of stability may hold lessons for other outpatient services during the next pandemic.

An Exploration of Journals Requested by Health Sciences Libraries Through DOCLINE Interlibrary Loan During the Early COVID-19 Pandemic

COVID-19 challenged information exchange globally, including interlibrary loan (ILL). This project explored DOCLINE ILL borrowing data from 15 academic, hospital, and association health sciences libraries before and during the pandemic to understand gaps in ILL coverage. We reviewed aggregate filled and unfilled borrowing data from March to August in 2019 and 2020. We compared these time periods to each other and to system-wide fill rates. We normalized journal titles, added journal price and language, calculated descriptive statistics and odds ratios, and conducted 2-proportion z-tests of differences. In our sample of 14,891 requests, the odds of requests being unfilled were 2.7 times higher in 2020 than in 2019. While the proportion of non-English language content requested did not change, a significantly higher proportion went unfilled in 2020. The rate of unfilled requests for older items also rose significantly between 2019 and 2020. Our findings support the conclusion that the COVID-19 pandemic significantly influenced ILL article request fulfillment in health sciences libraries. Libraries should consider collection development strategies to increase the accessibility of articles held only in print, and those with specialized print collections may want to prioritize digitization of older materials. Future research on the availability, utility, and expense of the materials more likely to remain unfilled should inform publisher backfile prioritization as well as consortial and individual library collection development practices.

Taming the Long Tail: The Gambler’s Fallacy in Intermittent Demand Management

Problem definition: “Long tail” products with intermittent demand often tie up valuable warehouse space and capital investment for many companies. Furthermore, the paucity of demand data poses additional challenges for model estimation and performance evaluation. Traditional inventory solutions are not designed for products with intermittent demand. In this paper, we propose a new framework to optimize the choice of “replenishment timing” and “replenishment quantity” for managing the inventory metrics of long tail products, when evaluated over a finite horizon. Methodology/results: Our analysis is motivated by a recent interesting observation that the gambler’s fallacy phenomenon actually holds in a finite number of coin tosses. We use this phenomenon to analyze the inventory problem for intermittent demand to demonstrate that classical inventory models using KPIs such as fill rate, average cost per cycle, or average cost per unit, etc., must necessarily “bias” the underlying demand distribution to account for the finite horizon effect. We provide the exact closed-form expressions of the biased distribution to account for this effect in performance evaluation. The results show that the choice of replenishment timing and replenishment quantity is essential to superior performance on several key inventory metrics. Managerial implications: For long tail products, the belief that it is less likely for another demand to arrive shortly after a preceding one (the gambler’s fallacy), turns out to be true when performance is tabulated over a finite horizon, even if demands across time are independent. So it pays to delay the replenishment of depleted stocks to save on holding cost and warehouse space. Managers can optimize the replenishment timing, besides choosing the replenishment quantity, to optimize the performance metrics of several classes of inventory problems. This is especially useful for companies managing a large number of long tail products. Funding: This work was supported in part by the National Natural Science Foundation of China [Grant 72192832] and the 2019 Academic Research Fund Tier 3 of the Ministry of Education-Singapore [Grant MOE-2019-T3-1-010]. Supplemental Material: The e-companion is available at https://doi.org/10.1287/msom.2023.1217 .

The 2022 and 2023 Emergency Medicine Residency Match: A Cautionary Tale.

Introduction The emergency medicine (EM) match has undergone significant shifts in 2022 and 2023. While variation in specialty fill rates is expected over time, EM programs noted a significant increase in open positions starting in 2022. Utilizing National Resident Matching Program (NRMP) data over a 10-year period, we identified significant deviations in the emergency medicine match. Methods Shewhart control charts were used to plot the match results over time. A 10-year sample was used to establish the baseline value. From this value, the upper and lower control limits were established. Residency program expansion, decreasing applicant numbers, and changing applicant types were evaluated to detect any non-random changes to the process. Results While the number of EM PGY-1 positions added over time was within the expected range, both the number of unmatched positions and the change in the number of total US MD applicants were outside of this range and are considered to be "out of control." Conclusion It is not yet clear which contributing causes may underlie this sudden change. Several potential etiologies exist, including mismatches in supply and demand for positions, changes in perceptions of the specialty, the effects of COVID-19, and changing workforce needs. Historically similar experiences affecting other specialties, including anesthesia and radiation oncology, are analyzed. Potential solutions for returning to the necessary and usual success of the emergency medicine specialty match are explored.

Comparative evaluation of three commercially available markerless depth sensors for close-range use in surgical simulation

PurposeMinimally invasive surgeries have restricted surgical ports, demanding a high skill level from the surgeon. Surgical simulation potentially reduces this steep learning curve and additionally provides quantitative feedback. Markerless depth sensors show great promise for quantification, but most such sensors are not designed for accurate reconstruction of complex anatomical forms in close-range.MethodsThis work compares three commercially available depth sensors, namely the Intel D405, D415, and the Stereolabs Zed-Mini in the range of 12–20 cm, for use in surgical simulation. Three environments are designed that closely mimic surgical simulation, comprising planar surfaces, rigid objects, and mitral valve models of silicone and realistic porcine tissue. The cameras are evaluated on Z-accuracy, temporal noise, fill rate, checker distance, point cloud comparisons, and visual inspection of surgical scenes, across several camera settings.ResultsThe Intel cameras show sub-mm accuracy in most static environments. The D415 fails in reconstructing valve models, while the Zed-Mini provides lesser temporal noise and higher fill rate. The D405 could reconstruct anatomical structures like the mitral valve leaflet and a ring prosthesis, but performs poorly for reflective surfaces like surgical tools and thin structures like sutures.ConclusionIf a high temporal resolution is needed and lower spatial resolution is acceptable, the Zed-Mini is the best choice, whereas the Intel D405 is the most suited for close-range applications. The D405 shows potential for applications like deformable registration of surfaces, but is not yet suitable for applications like real-time tool tracking or surgical skill assessment.

Fatigue database of additively manufactured alloys

Fatigue is a process of mechanical degradation that is usually assessed based on empirical rules and experimental data obtained from standardized tests. Fatigue data of engineering materials are commonly reported in S-N (the stress-life relation), ε-N (the strain-life relation), and da/dN-ΔK (the relation between the fatigue crack growth rate and the stress intensity factor range) data. Fatigue and static mechanical properties of additively manufactured (AM) alloys, as well as the types of materials, parameters of AM, processing, and testing are collected from thousands of scientific articles till the end of 2022 using natural language processing, machine learning, and computer vision techniques. The results show that the performance of AM alloys could reach that of conventional alloys although data dispersion and system deviation are present. The database (FatigueData-AM2022) is formatted in compact structures, hosted in an open repository, and analyzed to show their patterns and statistics. The quality of data collected from the literature is measured by defining rating scores for datasets reported in individual studies and through the fill rates of data entries across all the datasets. The database also serves as a high-quality training set for data processing using machine learning models. The procedures of data extraction and analysis are outlined and the tools are publicly released. A unified language of fatigue data is suggested to regulate data reporting for the fatigue performance of materials to facilitate data sharing and the development of open science.

Lipid-Lowering Therapy Utilization and Dosage Among Patients with Acute Coronary Syndrome Events: A Retrospective Cohort from 12 Community Hospitals.

Clinical practice guidelines recommend initiating a high-intensity LLT and continued monitoring of low-density lipoprotein cholesterol (LDL-C) following acute coronary syndrome (ACS). We used real-world data to describe LLT utilization after discharge and 1-year adherence. The reduction in LDL-C was also evaluated. Data were extracted from electronic health records (EHRs) from 12 hospitals in a large community healthcare system in midwestern United States between 2013 and 2019. Data on eligible patients recently discharged with an ACS event were linked to pharmacy claims data to describe LLT fill rates and 1-year post-discharge adherence. Adherence was reported as the proportion of days covered ≥80%. Of the 10,589 eligible patients, 49% filled a high-intensity statin at discharge and only 36% were adherent at 1 year. The mean (SD) age was 66.1±13.3, 39.3% were females, 58.8% were Caucasian, and 53.0% had Medicare. There was a clear trend for greater fill rates at discharge among patients with higher LDL-C values than those with lower values (p<0.01). Key predictors of high-intensity (versus medium-intensity) LLT use within 21 days after an ACS event included ACS type (odds ratio [OR] 0.59; 95% confidence interval [CI] 0.52-0.67 for NSTEMI versus STEMI), age group (OR: 0.59; 95% CI: 0.48-0.72 for >75 years versus <65years), and statin use before index ACS event (OR: 1.56; 95% CI: 1.23-1.88). This real-world study found that despite recommendations in clinical practice guidelines, high-intensity LLT fill rates at discharge and 1-year adherence to LLT remain suboptimal. Clinical characteristics, including ACS type and LDL-C values, were strong predictors of filling and adherence to guideline-recommended therapy. Age, sex, and race/ethnicity disparities were observed in discharge fill rates and 1-year adherence. These results highlight the need for continued efforts at the patient and provider levels to improve LLT adherence among ACS patients.