Pass Rate Research Articles

Dosimetric effects of small field size, dose grid size, and variable split-arc methods on gamma pass rates in radiation therapy.

This study investigates the influence of calculation accuracy in peripheral low-dose regions on the gamma pass rate (GPR), utilizing the Acuros XB (AXB) algorithm and ArcCHECK™ measurement. The effects of varying small field sizes, dose grid sizes, and split-arc techniques on GPR were analyzed. Various small field sizes were employed. Thirty-two single-arc plans with dose grid sizes of 2mm and 1mm and prescribed doses of 2, 5, 10, and 20Gy were calculated using the AXB algorithm. In total, 128 GPR plans were examined. These plans were categorized into three sub-fields (3SF), four sub-fields (4SF), and six sub-fields (6SF). The GPR results deteriorated with smaller target sizes and a 2mm dose grid size in a single arc. A similar degradation in GPR was observed with smaller target sizes and a 1mm dose grid size. However, the 1mm dose grid size generally resulted in better GPR compared with the 2mm dose grid size for the same target sizes. The GPR improved with finer split angles and a 2mm dose grid size in the split-arc method. However, no statistically significant improvement was observed with finer split angles and a 1mm dose grid size. This study demonstrates that coarser dose grid sizes result in lower GPRs in peripheral low-dose regions as calculated by AXB with ArcCHECK™ measurement. To enhance GPR, employing split-arc methods and finer dose grid sizes could be beneficial.

Impact of integrating smartphones in the teaching and learning of Mathematics in Mberengwa district, Zimbabwe

Worldwide, the utility of smartphones in the teaching and learning of Mathematics has been greatly recognized and taken advantage of. This is mainly because of the precisions this technology can bring in the classroom. This study investigated the impact of integrating smart phones in the teaching and learning of Mathematics at secondary schools in Chegato Cluster in Mberengwa district, Zimbabwe. It also examined strategies that can be used to enhance the use of smartphones in these schools. The study used a mixed method approach where both qualitative and quantitative data was gathered and was used to answer the formulated research questions. Ten parents, 10 Mathematics teachers, 4 school heads and 40 learners participated in the study. The study found that the introduction of the competence-based curriculum by the ministry of Education in Zimbabwe, which is in solidarity with Education 5.0 calls for the use of smart phones in the teaching and learning of Mathematics which ensures that several modern skills are being acquired by learners in Chegato secondary schools. Learners in Chegato Cluster benefit by using smartphones to store soft copies of various Mathematics textbooks which are often scarce in hard-copy form. Students also benefit from Mathematical applications that are installed in their smartphones. Teachers use smartphones as media in the classroom to enhance learner-understanding of the concepts. Again, in Chegato, the use of smartphones has exposed learners to various Mathematical technological skills that help in the learning of Mathematics and has the potential of improving the pass rate. School heads and teachers acknowledged that the availability of smartphones in the schools has greatly assisted “O” level Mathematics learners to accomplish their tasks.Strategies that can be used to enhance the use of smartphones in secondary schools include the use of individualised student passwords which are controlled and monitored by the school administrators to ensure that the activities of each learner on the Internet can be tracked and any attempts by students to visit undesirable sites are detected. Also, the use of software applications, such as Mikrotik Hotspot Blocker, can be used to block students from accessing unsavoury Internet sites. The study concluded that though challenges such as lack of technological resources and some educators’ negative attitudes towards the use of smart phones affect Chegato Cluster, most participants found it helpful to use smartphones in the classroom because the gadget expose learners to new and better ways of dealing with Mathematical concepts. The study finally calls for all the involved parties in the cluster and beyond to actively take up their responsibilities facilitating the use of smartphones for the benefits of the students.

LEVEL OF ACADEMIC PERFORMANCE OF STUDENTS IN SECONDARY SCHOOLS OF ALEBTONG DISTRICT. A CROSS-SECTIONAL STUDY.

Background In Uganda, there is an overall concern over the generally poor academic performance of students learning in government-aided schools. The study aims to assess the level of academic performance of students in secondary schools of Alebtong District. Methodology A descriptive cross-sectional study was conducted and quantitative data collected from 115 respondents was obtained. Results The level of academic performance of students in secondary schools of Alebtong District was relatively low. The mean response of 2.6 suggested that students' performance in standardized exams, particularly UCE and UACE, is not very high. A mean response of 2.2 indicated that the pass rate of students in Alebtong District was not very high and only 25% of students obtained a second-grade result. The mean response was 1.8 indicating that a high percentage of students in lower secondary do not obtain a first-grade result. A mean response of 2.8 indicated that there might be some challenges regarding dropout rates and student retention in secondary schools. The mean response was 3.2 indicating that students in Alebtong District generally experience a relatively smooth transition and progression through their secondary education. Conclusion Generally, schools in Alebtong District have not yet archived their desired potential with the majority of the students unable to score a minimum of second-grade result. There is still a need for greater improvement in the level of academic performance of students in secondary schools in Alebtong District Recommendation Strategies should be implemented to enhance students' performance in standardized exams, increase the pass rate, improve grade distribution, reduce dropout rates, and ensure the smooth transition and completion of secondary education. Encouraging students' active involvement in extra-curricular activities could also be explored as a potential avenue for supporting academic excellence.

Homogenization Path Based on 250 mm × 280 mm Bloom under Mixed Light and Heavy Presses: Simulation and Industrial Studies

This study proposed a new method for homogenizing continuous casting blooms based on solidification simulation calculations and industrial tests. The text describes a theoretical analysis of the solidification route of a cast billet of high-carbon alloy steel (B300A) under different process conditions. It summarizes the changing law of different under-pressure process parameters and under-pressure efficiency. The text also presents a solution to the seriousness of center shrinkage defects in the continuous casting of a large square billet of high-carbon alloy steel with the synergistic control technology of mixed light and heavy mixing under pressure. The study indicates that the center carbon segregation index of a high carbon steel continuous casting billet is 1.05, with a carbon extreme difference of not more than 0.08% and a proportion of 98.4%. Additionally, the center shrinkage is not more than a 0.5 level with a proportion of 99.5%. Meanwhile, the internal quality of cast billets has been improved, allowing for the rolling of large-size bars with a low consolidation ratio. The pass rate for internal ultrasonic flaw detection using the GB/T4162A grade is now higher than 99.95%, significantly reducing process costs and improving production efficiency for continuous casting and rolling.

Learning pains: system design, management, and lessons learned using electronic patient reported outcomes in the QUEST study of chronic post-amputation pain

BackgroundStudying pain clinically can be challenging. Typically, studies use paper diaries and measure pain from baseline and some pre-specified study endpoints. Both can lead to inaccuracies if studying on-demand device use. The QUEST study evaluating the safety and effectiveness of the investigational Altius device for treating chronic post-amputation pain (PAP) became, to our knowledge, the first longitudinal study to capture and validate repeated measurements using electronic patient-reported outcomes (ePRO).MethodsThe system was designed to capture pain episodes, device use, pain medication use and prosthetic use in “real-time.” Subjects received an electronic diary (eDiary) during screening and were required to demonstrate compliant reporting, and requisite pain levels to progress towards device implantation. Data were collected and merged with Altius session data and study visit data for 3 Month Primary Endpoint analysis. Compliance data across Device Treatment and End-of-Day Reports were also collected.ResultseDiary Eligibility pass rate during screening was 82% (410/497 subjects). Subjects generated 1,773,356 datapoints and 197,952 reports throughout QUEST. A total of 14,337 device uses were captured during Randomized Testing, with 77.0% and 82.7% compliant Device-use Reports and End-of-Day Reports captured, respectively. QUEST results are presented elsewhere (clinicaltrials.gov Identifier NCT 00221934).ConclusionsNeuros and partner vendors developed a unique system to capture accurate, “real-time” pain and treatment data from subjects with chronic PAP, despite health and technical-related challenges. This system provided a robust data set not yet seen in chronic pain literature and could provide a framework for better understanding chronic pain.Clinical Trial Information ClinicalTrials.gov ID NCT02221934, Registration Date: 2014–08-15.

Enhancing online dose distribution reconstruction in radiotherapy through sparse sampled rotating fiber arrays and deep learning

A optical fiber array dosimeter based on radiation-induced luminescence can be used in two-dimensional dose distribution measurements. However, using rotating fiber arrays introduces challenges in terms of online monitoring and variations in detector performance due to the long data acquisition time. This study aims to propose and demonstrate a novel method for online fast reconstruction of two-dimensional dose distributions in radiation therapy using projection data obtained from sparsely sampled rotating fiber arrays. The projection data were processed in both the projection and image domains to achieve restoration and noise reduction by deep learning techniques. The performance of the proposed method was evaluated using simulation data obtained by Monte Carlo toolkit Geant4 and experimental data obtained from a medical accelerator. Results showed that the method can successfully reconstruct dose distribution through sparse sampling and reduce the measurement time to one-sixth of the original. The peak signal-to-noise ratio, root mean square error, and structural similarity index were 23.72, 2.68, and 0.95, respectively. Additionally, the 3%/3 mm gamma pass rate reached 98.4% under specific irradiation conditions with a dose of at least 10% of the maximum dose. The integration of sparse sampling techniques, rotating fiber arrays, and deep learning techniques offers new possibilities for the fast and efficient reconstruction of two-dimensional dose distributions, ensuring high-quality radiotherapy outcomes.

Residency program factors affecting ACVS board examination pass rates from 2017 to 2021: A survey of ACVS small animal surgery residency programs.

To identify small animal surgery (SAS) residency program factors associated with board examination pass rates for the American College of Veterinary Surgeons (ACVS) board certification examinations. Online survey. Program directors of ACVS-registered SAS residency programs. An online survey was distributed to eligible 2021 ACVS SAS residency program directors. Respondents provided program information and Phase I and Phase II board examination pass rate data from 2017 to 2021. Programs were grouped based on overall combined board examination pass rates as "excellent" (≥90%) versus "adequate" (<90%). Data were analyzed using recursive partitioning. Responses from 36 ACVS SAS residency programs (18 private practice [PP], 18 academic programs [AP]) were included. Pass rates were considered "excellent" for 17/36 programs (11/17 AP, 6/17 PP). The strongest indicator of "excellent" programs was most mentors participating in rounds >75% of the time. Of those, the second indicator of "excellent" programs was a soft tissue caseload of <7 surgeries/resident/week. If the soft tissue caseload was >7 surgeries/resident/week, a high orthopedic caseload (>9 surgeries/resident/week) was indicative of "excellent" programs. If most mentors were not participating in rounds >75% of the time, APs were more likely to be "excellent." SAS APs may have higher ACVS board examination pass rates. Mentor involvement, caseload, and residency practice type may influence board examination pass rates. ACVS SAS residency programs' board examination pass rates may improve by optimizing mentor involvement and caseload regardless of practice type.

Research on Bearing Surface Scratch Detection Based on Improved YOLOV5

Bearings are crucial components of machinery and equipment, and it is essential to inspect them thoroughly to ensure a high pass rate. Currently, bearing scratch detection is primarily carried out manually, which cannot meet industrial demands. This study presents research on the detection of bearing surface scratches. An improved YOLOV5 network, named YOLOV5-CDG, is proposed for detecting bearing surface defects using scratch images as targets. The YOLOV5-CDG model is based on the YOLOV5 network model with the addition of a Coordinate Attention (CA) mechanism module, fusion of Deformable Convolutional Networks (DCNs), and a combination with the GhostNet lightweight network. To achieve bearing surface scratch detection, a machine vision-based bearing surface scratch sensor system is established, and a self-made bearing surface scratch dataset is produced as the basis. The scratch detection final Average Precision (AP) value is 97%, which is 3.4% higher than that of YOLOV5. Additionally, the model has an accuracy of 99.46% for detecting defective and qualified products. The average detection time per image is 263.4 ms on the CPU device and 12.2 ms on the GPU device, demonstrating excellent performance in terms of both speed and accuracy. Furthermore, this study analyzes and compares the detection results of various models, demonstrating that the proposed method satisfies the requirements for detecting scratches on bearing surfaces in industrial settings.

Effectiveness of a virtual reality trainer for retention of tourniquet application skills for hemorrhage control among emergency medicine residents.

With a rise in mass casualty incidents, training in hemorrhage control using tourniquets has been championed as a basic-and lifesaving-procedure for bystanders and medical professionals alike. The current standard for training is in-person (IP) courses, which can be limited based on instructor availability. Virtual reality (VR) has demonstrated the potential to improve the accuracy of certain medical tasks but has not yet been developed for hemorrhage control. The objective of this study was to evaluate the efficacy of a VR hemorrhage trainer in learner retention of tourniquet application when compared to traditional IP instructor teaching among a cohort of emergency medicine residents practicing in a Level I trauma center. This was a prospective, observational study of 53 emergency medicine residents at an inner-city program. Participants were randomly assigned to either the control or the VR group. On Day 0, all residents underwent a training session (IP vs. VR) for the proper, stepwise application of a tourniquet, as defined by the American College of Trauma Surgeons. Each participant was then assessed on the application of a tourniquet by a blinded instructor using the National Registry Hemorrhage Control Skills Lab rubric. After 3 months, each resident was reevaluated on the same rubric, with subsequent data analysis on successful tourniquet placement (measured as under 90 s) and time to completion. Of the 53 participants, the IP training group had an initial pass rate of 97% (28/29) compared to 92% (22/24) in the VR group (p = 0.58). On retention testing, the IP training group had a pass rate of 95% (20/21) compared to 90% (18/20) in the VR group (p = 0.62). Stratifying the success of tourniquet placement by level of resident training did not demonstrate any statistically significant differences. In this pilot study of emergency medicine residents, we found no significant differences in successful hemorrhage control by tourniquet placement between those trained with VR compared to a traditional IP course among emergency medicine residents. While more studies with greater power are needed, the results suggest that VR may be a useful adjunct to traditional IP medical training.

Variation in Oral Board Examination Accommodations Among Specialties

Board certification can have broad implications for candidates' career trajectories, and prior research has found sociodemographic disparities in pass rates. Barriers in the format and administration of the oral board examinations may disproportionately affect certain candidates. To characterize oral certifying examination policies and practices of the 16 Accreditation Council for Graduate Medical Education (ACGME)-accredited specialties that require oral examinations. This cross-sectional study was conducted from March 1 to April 15, 2023, using data on oral examination practices and policies (examination format, dates, and setting; lactation accommodations; and accommodations for military deployment, family emergency, or medical leave) as well as the gender composition of the specialties' boards of directors obtained from websites, telephone calls and email correspondence with certifying specialists. The percentages of female residents and residents of racial and ethnic backgrounds who are historically underrepresented in medicine (URM) in each specialty as of December 31, 2021, were obtained from the Graduate Medical Education 2021 to 2022 report. For each specialty, accommodation scores were measured by a modified objective scoring system (score range: 1-13, with higher scores indicating more accommodations). Poisson regression was used to assess the association between accommodation score and the diversity of residents in that specialty, as measured by the percentages of female and URM residents. Linear regression was used to assess whether gender diversity of a specialty's board of directors was associated with accommodation scores. Included in the analysis were 16 specialties with a total of 46 027 residents (26 533 males [57.6%]) and 233 members of boards of directors (152 males [65.2%]). The mean (SD) total accommodation score was 8.28 (3.79), and the median (IQR) score was 9.25 (5.00-12.00). No association was found between test accommodation score and the percentage of female or URM residents. However, for each 1-point increase in the test accommodation score, the relative risk that a resident was female was 1.05 (95% CI, 0.96-1.16), and the relative risk that an individual was a URM resident was 1.04 (95% CI, 1.00-1.07). An association was found between the percentage of female board members and the accommodation score: for each 10% increase in the percentage of board members who were female, the accommodation score increased by 1.20 points (95% CI, 0.23-2.16 points; P = .03). This cross-sectional study found considerable variability in oral board examination accommodations among ACGME-accredited specialties, highlighting opportunities for improvement and standardization. Promoting diversity in leadership bodies may lead to greater accommodations for examinees in extenuating circumstances.

A connecting rod assembly deformation cognition method based on quality characteristics probability network

As the core component of marine diesel engines, the connecting rod quality directly affects the reliability and life of diesel engines. However, the deformation problem of the connecting rod assembly process, which caused the low pass rate of one-time assembly, has not been well solved. The deformation of connecting rod assembly is difficult to analyze by mechanism because it is influenced by many quality characteristics with complex and cross-process correlations. To address this issue, this paper proposes a connecting rod assembly deformation cognition method based on the quality characteristics probability network. Firstly, a quality characteristics probabilistic network model for the connecting rod assembly process is established. Secondly, based on the quality characteristics probability network model and the complexity of cross-process correlation, the K-shell entropy weight model is used to identify the key quality characteristics and construct their correlation model. Then, to deal with the uncertainty of the influence degree between quality characteristics, a Bayesian network is used to establish an influence analysis model of key quality characteristics and analyze their influence relationship from qualitative and quantitative perspectives. Finally, the simulation and actual assembly data of marine diesel engine connecting rod assembly process are used to train and verify the cognition method. The results show that the method can effectively analyze the relationship between the connecting rod assembly process quality characteristics and predict the connecting rod deformation degree. The proposed method can comprehensively consider the influence of multiple processes and quality characteristics, improve the accuracy of analysis and prediction of connecting rod deformation, and can be used to guide the dynamic adjustment of the connecting rod assembly process to increase the pass rate of one-time. Moreover, the proposed method can also provide a reference for other multi-process and multi-factor problem analyses.

Error detection for radiotherapy planning validation based on deep learning networks.

Quality assurance (QA) of patient-specific treatment plans for intensity-modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT) necessitates prior validation. However, the standard methodology exhibits deficiencies and lacks sensitivity in the analysis of positional dose distribution data, leading to difficulties in accurately identifying reasons for plan verification failure. This issue complicates and impedes the efficiency of QA tasks. The primary aim of this research is to utilize deep learning algorithms for the extraction of 3D dose distribution maps and the creation of a predictive model for error classification across multiple machine models, treatment methodologies, and tumor locations. We devised five categories of validation plans (normal, gantry error, collimator error, couch error, and dose error), conforming to tolerance limits of different accuracy levels and employing 3D dose distribution data from a sample of 94 tumor patients. A CNN model was then constructed to predict the diverse error types, with predictions compared against the gamma pass rate (GPR) standard employing distinct thresholds (3%, 3mm; 3%, 2mm; 2%, 2mm) to evaluate the model's performance. Furthermore, we appraised the model's robustness by assessing its functionality across diverse accelerators. The accuracy, precision, recall, and F1 scores of CNN model performance were 0.907, 0.925, 0.907, and 0.908, respectively. Meanwhile, the performance on another device is 0.900, 0.918, 0.900, and 0.898. In addition, compared to the GPR method, the CNN model achieved better results in predicting different types of errors. When juxtaposed with the GPR methodology, the CNN model exhibits superior predictive capability for classification in the validation of the radiation therapy plan on different devices. By using this model, the plan validation failures can be detected more rapidly and efficiently, minimizing the time required for QA tasks and serving as a valuable adjunct to overcome the constraints of the GPR method.

The Relationship between Cognitive Factors and Noncognitive Factors, Including Grit, and NBCOT® Exam Performance

This retrospective study examined the predictive ability of cognitive and non-cognitive factors, including grit, on first attempt pass rate on the National Board for Certification in Occupational Therapy exam. A convenience sample of 226 graduates from six cohorts of one occupational therapy program was used. Binary logistic regression revealed that grit was not a significant predictor. Program grade point average and verbal and quantitative Graduate Record Examination scores were independent predictors of passing on the first attempt. These findings can be used to identify at-risk students who could benefit from support to increase student success on the licensure exam.

Commissioning of a novel PET-Linac for biology-guided radiotherapy (BgRT).

Biology-guided radiotherapy (BgRT) is a novel radiotherapy delivery technique that utilizes the tumor itself to guide dynamic delivery of treatment dose to the tumor. The RefleXion X1 system is the first radiotherapy system developed to deliver SCINTIX® BgRT. The X1 is characterized by its split arc design, employing two 90-degree positron emission tomography (PET) arcs to guide therapeutic radiation beams in real time, currently cleared by FDA to treat bone and lung tumors. This study aims to comprehensively evaluate the capabilities of the SCINTIX radiotherapy delivery system by evaluating its sensitivity to changes in PET contrast, its adaptability in the context of patient motion, and its performance across a spectrum of prescription doses. A series of experimental scenarios, both static and dynamic, were designed to assess the SCINTIX BgRT system's performance, including an end-to-end test. These experiments involved a range of factors, including changes in PET contrast, motion, and prescription doses. Measurements were performed using a custom-made ArcCHECK insert which included a 2.2cm spherical target and a c-shape structure that can be filled with a PET tracer with varying concentrations. Sinusoidal and cosine4 motion patterns, simulating patient breathing, was used to test the SCINTIX system's ability to deliver BgRT during motion-induced challenges. Each experiment was evaluated against specific metrics, including Activity Concentration (AC), Normalized Target Signal (NTS), and Biology Tracking Zone (BTZ) bounded dose-volume histogram (bDVH) pass rates. The accuracy of the delivered BgRT doses on ArcCHECK and EBT-XD film were evaluated using gamma 3%/2mm and 3%/3mm analysis. In static scenarios, the X1 system consistently demonstrated precision and robustness in SCINTIX dose delivery. The end-to-end delivery to the spherical target yielded good results, with AC and NTS values surpassing the critical thresholds of 5 kBq/mL and 2, respectively. Furthermore, bDVH analysis consistently confirmed 100% pass rates. These results were reaffirmed in scenarios involving changes in PET contrast, emphasizing the system's ability to adapt to varying PET avidities. Gamma analysis with 3%/2mm (10% dose threshold) criteria consistently achieved pass rates>91.5% for the static tests. In dynamic SCINTIX delivery scenarios, the X1 system exhibited adaptability under conditions of motion. Sinusoidal and cosine4 motion patterns resulted in 3%/3mm gamma pass rates>87%. Moreover, the comparison with gated stereotactic body radiotherapy (SBRT) delivery on a conventional c-arm Linac resulted in 93.9% gamma pass rates and used as comparison to evaluate the interplay effect. The 1cm step shift tests showed low overall gamma pass rates of 60.3% in ArcCHECK measurements, while the doses in the PTV agreed with the plan with 99.9% for 3%/3mm measured with film. The comprehensive evaluation of the X1 radiotherapy delivery system for SCINTIX BgRT demonstrated good agreement for the static tests. The system consistently achieved critical metrics and delivered the BgRT doses per plan. The motion tests demonstrated its ability to co-localize the dose where the PET signal is and deliver acceptable BgRT dose distributions.

Characterization of a novel pulse normalization technology for beam scanning of small fields without a reference chamber.

A novel pulse normalization technology enabling the acquisition of low noise beam data without the use of a physical reference chamber has recently been commercially released. The purpose of this study was to characterize the use of this technology for beam scanning of small fields required in the commissioning of a stereotactic radiotherapy program. Three detectors (Edge diode, microDiamond, PinPoint) were used to acquire beam data under three conditions: with a reference chamber, with pulse normalization and no reference chamber (PN), and without pulse normalization and no reference chamber (nPN). Percent depth dose (PDD) scans were acquired for 0.5, 1.0, 2.0, and 3.0 cm2 field sizes and profiles were acquired at 1.4, 10, and 30cm depths using continuous scanning. The coefficient of variation (CoV) was calculated for all beam data to compare signal-to-noise and gamma comparisons (1%, 1mm) were calculated of the PN and nPN scans compared to the reference data. Average 95th percentile CoV values were similar for all detectors across conditions, with PN data being comparable to reference data and minor increases observed for nPN data. Mean gamma pass rates for PN PDD scans exceeded 98% for all detectors. Profile gamma pass rates were 100% for all detectors at 1.4 and 10cm depth. At 30cm depth, profiles acquired with the PinPoint and microDiamond detectors had lower mean gamma pass rates than the Edge, at 95% and 95.7%, respectively. A novel pulse normalization technology was demonstrated to be effective for acquiring beam profiles and PDDs for small fields without the use of a physical reference chamber. Limitations in how the method is implemented led to some errors in data acquired using lower sensitivity detectors. When used with a diode, pulse normalization produced equivalent scans to those acquired with a reference chamber.

Academic program enhancement supporting the success of undergraduate nursing students and graduates

Nursing program administrators, faculty, academic success coaches, and remediation specialists have implemented many interventions in support of baccalaureate nursing students' retention and graduates' NCLEX-RN® first-time pass rates. A private university's undergraduate nursing program's team incorporated additional evidence-based interventions aimed improving students' achievement of benchmarks following a 3-year decline in NCLEX-RN pass rates. Interventions expanded the prelicensure academic program's activities using a continuous quality improvement approach. A simulation center was constructed and a director was hired. A consultant also facilitated faculty engagement in curricular revisions. A new position, coordinator tutor/remediation specialist, was filled and the academic success coach launched interventions that complemented an initial and subsequent strategies for success initiative. New interventions were trialed and evaluated and became integral to students' and graduates' success. The academic success coach's commitment to students' achievements promoted their engagement in interventions. Pass rates increased and were sustained. Examples of interventions, supported by evidence, are presented in tables for review. A logic model depicts components of the program plan and its interventions as augmented by prospective strategies and remediation interventions. Continuous quality improvement processes will continue. Students and graduates have commented positively on the benefits of the assorted, success-promoting interventions.

An Assessment of the Active Learning Worksheets in an Undergraduate Human Anatomy and Physiology Course

Anatomy &amp; Physiology I is a demanding gateway science course for community college students. It is particularly challenging for underrepresented Hispanic students who must navigate course content, language barriers, and work-related time constraints. This paper introduces a new active learning strategy to promote meaningful learning and conceptual understanding of Anatomy &amp; Physiology, enhancing students' academic success. The teaching strategy incorporates enhanced lecture presentations and discussions. It also includes periodic pauses for students to engage in active learning activities aligned with learning outcomes. These activities spark student interest and provide immediate feedback on their understanding of challenging topics. The study indicates that the pass rate, mainly grades of C+ and above (a requirement in all nursing courses), was consistently higher for active learning participants than those who attended traditional lectures. This evidence suggests that an active learning environment boosts academic performance among our ethnically diverse students.

Lateral response artifact correction method using image stitching technique in radiochromic film dosimetry.

Lateral response artifact (LRA) is caused by the interaction between film and flatbed scanner in the direction perpendicular to the scanning direction. This can significantly affect the accuracy of patient-specific quality assurance (QA) in cases involving large irradiation fields. We hypothesized that by utilizing the central area of the flatbed scanner, where the magnitude of LRA is relatively small, the LRA could be mitigated effectively. This study proposes a practical solution using the image-stitching technique to correct LRA for patient-specific QA involving large irradiation fields. Gafchromic™ EBT4 film and Epson Expression ES-G11000 flatbed scanner were used in this study. The image-stitching algorithm requires a spot between adjacent images to combine them. The film was scanned at three locations on a flatbed scanner, and these images were combined using the image-stitching technique. The combined film dose was then calculated and compared with the treatment planning system (TPS)-calculated dose using gamma analysis (3%/2mm). Our proposed LRA correction was applied to several films exposed to 18 × 18 cm2 open fields at doses of 200, 400, and 600 cGy, as well as to four clinical Volumetric Modulated Arc Therapy (VMAT) treatment plans involving large fields. For doses of 200, 400, and 600 cGy, the gamma analysis values with and without LRA corrections were 95.7%versus 67.8%, 95.5%versus 66.2%, and 91.8%versus 35.9%, respectively. For the clinical VMAT treatment plan, the average pass rate±standard deviation in gamma analysis was 94.1%±0.4% with LRA corrections and 72.5%±1.5% without LRA corrections. The effectiveness of our proposed LRA correction using the image-stitching technique was demonstrated to significantly improve the accuracy of patient-specific QA for VMAT treatment plans involving large irradiation fields.

Dose averaged linear energy transfer optimization for large sacral chordomas in carbon ion therapy.

Carbon ion beams are well accepted as densely ionizing radiation with a high linear energy transfer (LET). However, the current clinical practice does not fully exploit the highest possible dose-averaged LET (LETd) and, consequently, the biological potential in the target. This aspect becomes worse in larger tumors for which inferior clinical outcomes and corresponding lower LETd wasreported. The vicinity to critical organs in general and the inferior overall survival reported for larger sacral chordomas treated with carbon ion radiotherapy (CIRT), makes the treatment of such tumors challenging. In this work it was aimed to increase the LETd in large volume tumors while maintaining the relative biological effectiveness (RBE)-weighted dose, utilizing the LETd optimization functions of a commercial treatment planning system (TPS). Ten reference sequential boost carbon ion treatment plans, designed to mimic clinical plans for large sacral chordoma tumors, were generated. High dose clinical target volumes (CTV-HD) larger than were considered as large targets. The total RBE-weighted median dose prescription with the local effect model (LEM) was in 16 fractions (nine to low dose and seven to high dose planning target volume). No LETd optimization was performed in the reference plans, while LETd optimized plans used the minimum LETd (Lmin) optimization function in RayStation2023B. Three different Lmin values were investigated and specified for the seven boost fractions: , and . To compare the LETd optimized against reference plans, LETd and RBE-weighted dose based goals similar to and less strict than clinical ones were specified for the target. The goals for the organs at risk (OAR) remained unchanged. Robustness evaluation was studied for eight scenarios ( range uncertainty and setup uncertainty along the main three axes). The optimization method with resulted in an optimal LETd distribution with an average increase of (and ) in the CTV-HD by ( ) (and ( )), without significant difference in the RBE-weighted dose. By allowing over- and under-dosage in the target, the (and ) can be increased by ( ) (and ( )), using the optimization parameters . The pass rate for the OAR goals in the LETd optimized plans was in the same level as the reference plans. LETd optimization lead to less robust plans compared to referenceplans. Compared to conventionally optimized treatment plans, the LETd in the target was increased while maintaining the RBE-weighted dose using TPS LETd optimization functionalities. Regularly assessing RBE-weighted dose robustness and acquiring more in-room images remain crucial and inevitable aspects duringtreatment.

Correlation Between Residency Program Characteristics and American Board of Obstetrics and Gynecology Certifying Examination Passage Rates [ID 2683567

INTRODUCTION: The correlation between obstetrics and gynecology residency program size and type with certifying examination passage rates is not previously reported. Our objective was to evaluate the relationship between residency program size and type with American Board of Obstetrics and Gynecology (ABOG) certifying examination (CE) pass rates. METHODS: This is a cross-sectional study of ABOG specialty CE passage rates from 2020 to 2022. The CE passage rates were obtained from the ABOG website and stratified by program size (small 3–4, medium 5–7, large &gt;8 residents per class) and type (community-based; community-based, university-affiliated; and university-based). Military-based programs were excluded, as were programs of unknown size. Passage rates were compared among groups using chi-squared test. RESULTS: During the study period, 3,766 candidates sat for the CE. Small programs accounted for 730 candidates (19.4%), 1,805 (47.9%) candidates from medium programs, and 1,231 candidates (32.7%) from large programs. Passage rates were higher among medium and large programs versus small programs (small [604/730; 82.7%], medium [1,656/1,805, 91.7%], and large [1,149/1,231; 93.3%]; P&lt;.001). Passage rates among community-based candidates (299/347; 86.2% pass rate) and community-based university-affiliated candidates (962/1,100; 87.5% pass rate) were lower versus university-based candidates (2,148/2,319; 92.6% pass rate; P&lt;.0001). CONCLUSION: During the study period, university-based programs and medium or large programs had higher CE passage rates. There are a number of limiting factors to the interpretation of the results such as academic differences upon entry to residency, resources available at each program, and amount of dedicated study time. A causal effect of program size and type cannot be assumed.