bluuebunny/crossref_metadata_2025_split huggingface dataset:
Securing Interviews as an Underrepresented Applicant Post-USMLE Pass/Fail: A National Survey of Competitive Residency Directors
Authors: Kindler Rebecca , Kahn Julia , Uddin Anaz , Petersen Kristina H. 
Published: October 2023

Abstract
Background In January 2022, the United States Medical Licensing Examination (USMLE) changed Step-1 score reporting to pass/fail.Objective To report selection criteria important to residency program directors (PDs) and whether they believe pass/fail scoring will impact underrepresented in medicine (URM), international (IMG), or osteopathic (OG) residency applicants.Methods A Qualtrics survey was sent between August, 2022 – January, 2023 to 1,141 US PDs from specialties with traditionally low match rates: dermatology, ophthalmology, otolaryngology, orthopedic surgery, neurosurgery, interventional radiology, diagnostic radiology, radiation oncology, thoracic surgery, vascular surgery, plastic surgery, and urology. Contact information was obtained from AMA, FRIEDA, or program websites.Results We received 433 responses (38%). When asked to anticipate the difficulty student groups will face matching into their specialty, PDs reported: for URM, 24.0% increased, 46.0% unchanged, and 30.0% decreased, OG, 49.19% increased, 44.58% unchanged, and 6.23% decreased; for IMG, 56.35% increased, 39.72% unchanged, and 3.93% decreased. When asked to rank the most important selection factors, the top two responses were Step-2 CK score and away rotation participation at their site.Conclusion PDs overwhelmingly believed match difficulty would either increase or remain unchanged for OG (93.77%) and IMG (96.07%). In contrast, 76.0% reported difficulty for URM students would either decrease or remain unchanged. Paradoxically, PDs ranked Step-2 CK score and away rotation participation as the most important selection factors. Although the intention may be to dismantle barriers for URM applicants, enhanced emphasis on Step 2CK and away rotations place additional socioeconomic and standardized exam barriers.
Assessing the role of natural kelp forests in modifying seawater chemistry
Authors: Strain Elisabeth MA , Swearer Stephen E , Ambler India , Morris Rebecca L , Nickols Kerry J 
Published: October 2023

Abstract

Climate change is causing widespread impacts on seawater pH through ocean acidification (OA). Kelp forests, in some locations can buffer the effects of OA through photosynthesis. However, the factors influencing this variation remain poorly understood. To address this gap, we conducted a literature review and field deployments of pH and dissolved oxygen (DO) loggers within four habitats: intact kelp forest, moderate kelp cover, sparse kelp cover and barrens at one site in Port Phillip Bay, a wind-wave dominated coastal embayment in Victoria, Australia. Additionally, a wave logger was placed directly in front of the intact kelp forest and barrens habitats. Most studies reported that kelp increased seawater pH and DO during the day, compared to controls without kelp. This effect was more pronounced in densely populated forests, particularly in shallow, sheltered conditions. Our field study was broadly consistent with these observations, with intact kelp habitat having higher seawater pH than habitats with less kelp or barrens and higher seawater DO compared to barrens, particularly in the afternoon and during calmer wave conditions. Although kelp forests can provide local refuges to biota from OA, the benefits are variable through time and may be reduced by declines in kelp density and increased wave exposure.
The impact of antibiotic prophylaxis with cefazolin, and ceftizoxime along with aminoglycosides on postoperative complications, hospitalization, and returning to normal life for percutaneous nephrolithotomy, A prospective cross-sectional study
Authors: Falahatkar Siavash , Mokhtari Gholamreza , Kazemnejhad-Leili Ehsan , Abed-Kamalchi Milad , Kazemi Samira , Sheikhi Fatemeh , Jafari Alireza 
Published: October 2023

Abstract
Objective
This study investigated the efficacy of first-generation cephalosporin (cefazolin) and third-generation cephalosporin (ceftizoxime) as prophylactic antibiotics in patients undergoing PCNL surgery. The study also examined the incidence of postoperative complications, hospitalization duration, and return to normal life.
Methods
This prospective cross-sectional study included patients (≥ 20 years) who underwent PCNL surgery at RAZI, GOLSAR, and PARS Hospitals from January 01, 2013, to December 31, 2022. Patients were divided into two groups and received 1mg/kg of either first-generation (cefazolin) or third-generation (ceftizoxime) intravenously, 30 minutes before the surgery. The incidence of postoperative complications, hospitalization duration, and return to normal life were compared based on the type of prophylactic antibiotic. Risk factors were evaluated using chi-squared tests followed by multivariate logistic regression analysis.
Results
The ceftizoxime group showed significantly lower rates of general complications (13.0% vs 31.4%) and postoperative fever (2.8% vs 15.0%) compared to the cefazolin group. The ceftizoxime group also had a significantly shorter total hospitalization duration (1.31 ± 1.18 days) compared to the cefazolin group (4.03 ± 1.57 days) (p = 0.000). Additionally, the ceftizoxime group had a significantly shorter duration for return to normal life (5.97 ± 3.37 days) compared to the cefazolin group (8.15 ± 2.93 days) (p = 0.001).
Conclusion
The third-generation prophylactic cephalosporin (ceftizoxime) was superior to the first-generation (cefazolin) in reducing postoperative fever rates, hospitalization duration, and time to return to normal life for patients.
The effect of several mineral formulations on controlling strawberry blossom blight due to Botrytis cinerea
Authors: Shemshaki Naghme Save , Sharifi Kasra , Khodaparast Seyed Akbar , Mamani Leila , Mousanejad Sedigheh 
Published: October 2023

Abstract
Gray mold is one of the most important strawberry diseases worldwide. Today, minerals play a significant role in controlling plant diseases. The antimicrobial effects of salt solutions have been widely documented in researches describing their effectiveness in managing various plant diseases. The study aimed to evaluate the impact of mineral compounds on controlling strawberry blossom blight caused by Botrytis cinerea. Ten mineral compounds were used to evaluate the controlling effect on the disease-causing fungus in vitro with five doses. Six mineral compounds that include aluminum chloride, aluminum sulfate, sodium metabisulfite, sodium selenite, borax, and potassium sulfate were chosen based on inhibition of mycelial growth compared to the control, mycelium deformation, and lack of conidiation, for formulations based on EC, based on two oils of flax seeds and castor. The number of infected and healthy flowers were recorded to evaluate the controlling effect of mineral compound formulations on strawberry blossom blight under greenhouse conditions. The formulations efficiency were between 48% − 80%. The best formulation after signum® was aluminum chloride based on castor oil at two parts per thousand.
Effects of sitting-style Baduanjin on older adults with heart failure: Study Protocol for a Randomized Controlled Trial
Authors: wu min , jin xiao , jiang minghong , Li Ran , Song Hongli , li Mingwei 
Published: October 2023

Abstract
Importance:
Heart failure (HF) is a complex disease, mainly caused by structural or functional changes such as ventricular filling or cardiac ejection, leading to clinical symptoms and signs and seriously affecting patients' quality of life. Guideline-directed medical therapy can significantly alleviate patients' symptoms and reduce mortality and hospitalization rate. Exercise can improve cardiopulmonary function, and all major guidelines unanimously recommend exercise-centered cardiac rehabilitation. However, unscientific exercise increases myocardial oxygen consumption and aggravates symptoms in patients with HF. Therefore, choosing appropriate exercise to improve patients' exercise tolerance and quality of life has become a research hotspot. Sitting Baduanjin, a traditional Chinese exercise method that combines movement with rest, is easy to understand, highly recognized by society, and can be widely promoted. Moreover, some studies have indicated that sitting Baduanjin can ameliorate cardiopulmonary function and improve patients' quality of life. Therefore, studying the influence of sitting Baduanjin on senile HF is significant.
Methods and analysis:
This single-blind randomized controlled trial is designed to demonstrate that regular sedentary exercise and guided medication can significantly improve the quality of life of patients with HF. In this trial, 136 eligible patients will be randomly assigned to the Baduanjin and control groups in a ratio of 1:1. The Baduanjin group will practice sitting Baduanjin at home (45 min each time, three times a week) along with routine treatment, while the control group will only receive basic routine treatment. The primary outcome is the Minnesota HF questionnaire. Secondary outcomes include N-terminal proB-type natriuretic peptide (NT-proBNP), left ventricular end-diastolic diameter (LVEDD), left ventricular ejection fraction (LVEF), and left ventricular end-systolic diameter (LVESD). Researchers blinded to treatment allocation will analyze the data.
Conclusion
This study will provide strong evidence to establish regular sitting-style Baduanjin exercise effectiveness in significantly improving the quality of life of patients with HF.
Clinical registration:
We have registered with the China Clinical Trials Registration Center on November 18, 2022, the registration number is ChiCTR2200065921.
Automated Phase-Type Distribution Fitting via Expectation-Maximization
Authors: Mialaret Marco , Pereira Paulo , Barreto Antônio Sá , Pinheiro Thiago , Maciel Paulo 
Published: October 2023

Abstract

In numerous practical domains such as reliability and performance engineering, finance, healthcare, and supply chain management, a common and formidable challenge revolves around the accurate modeling of intricate time-based data and event durations. The inherent complexities inherent to real-world systems often render the effective application of conventional statistical distributions a formidable task. Phase-type (PH) distributions emerge as a remarkably adaptable class of distributions ideally suited for modeling scenarios like failure times or response times, thanks to their Markovian representation. These distributions find utility in both analytical and simulation-driven approaches for system evaluation , and they are frequently employed to approximate empirical datasets. This paper introduces an approach that leverages user-friendly tools, graphical adjustment features, and integration with existing tools to streamline the process of fitting PH distributions to empirical data. Simplifying this procedure empowers domain experts to more accurately model complex systems, resulting in enhanced decision-making, more efficient resource allocation, improved reliability assessments, and optimized system performance across an extensive spectrum of practical domains where the analysis of time-based data remains pivotal. Furthermore, this study presents a method for the automated determination of parameters within a fitted Hyper-Erlang distribution. This method utilizes the Bayesian Information Criterion (BIC) within a Bayesian optimization framework integrated into an Expectation-Maximization (EM) algorithm. Consequently , it enables the derivation of the probability density function (pdf) for a given dataset through a combination of Hyper-Erlang distributions. Subsequently, this pdf serves as a critical tool for the assessment of system performance.
Design and synthesis of Berberine loaded Nano- hydroxyapatite/Gelatin Scaffold for bone cancer treatment
Authors: Khajavi Sajjad , Bahraminasab Marjan , Arab Samaneh , Talebi Athar , Kokhaei Parviz , Abdoos Hassan 
Published: October 2023

Abstract
The treatment of osteosarcoma, as the most destructive bone cancer, is allied with many challenges. One of the new tissue engineering approaches is the use of a local drug delivery system implanted after surgery. This system can be a scaffold mimicking the natural tissue extracellular matrix, loaded with drugs. Therefore, the purpose of this study was to construct different berberine-loaded nano-hydroxyapatite/gelatin scaffolds, and to investigate their effects on osteosarcoma cancer cells. The scaffolds after fabrication were analyzed for physicochemical properties using XRD, EDS, FTIR, and FE-SEM. The drug loading and release, and the biocompatibility (MTT and LDH) were also evaluated. Moreover, apoptosis, viability, colony formation, and scratch tests were conducted on cancer cells. The scaffolds exhibited a porosity of 66.64% with pore sizes of 10–70 micrometers. The results showed that the released berberine had a cytotoxic effect on cancer cells (cell death of ⁓38–80% based on LDH, and cell proliferation < 56% and < 21% in terms of early and late exposure based on MTT). The apoptosis results revealed a remarkable increase in the percentage of apoptotic MG63 cells after treatment with berberine-loaded scaffolds in a dose-dependent manner. All scaffolds with berberine were able to significantly prevent colony formation and cell migration (only 9.7–15.7% closure).
Heptadecagonal Fuzzy Number and its Distinctive Representation, Ranking, Defuzzification Technique and Application in Fuzzy Linear Programming Problem
Authors: Bala Vipin , Kumar Jitender , Kadyan M. S. 
Published: October 2023

Abstract
In this study, distinct categories of linear and nonlinear heptadecagonal fuzzy numbers with symmetry and asymmetry and their graphical representation are proposed. The membership functions and alpha-cuts for different types of heptadecagonal fuzzy numbers are also explained. Linear and nonlinear heptadecagonal fuzzy numbers with symmetry and asymmetry serve as powerful tools for simplifying the comprehension of vagueness data across different problems. By using the alpha-cut, the arithmetic operations on linear heptadecagonal fuzzy number with symmetry are addressed. A ranking method based on the centroid formula is used to rank two heptadecagonal fuzzy numbers and the alpha-cut method is applied to compute the defuzzification for linear heptadecagonal fuzzy number with symmetry. A numerical example for the fuzzy linear programming problem has been presented to illustrate the proposed methodology.
Cervical Cancer Prediction through Different Screening Methods using Machine Learning based on the strong features CNN-SVM network.
Authors: Karimi Sepideh , Razavi Firozeh , Soheili Mehdi 
Published: October 2023

Abstract
As you know, the uterus is part of the reproductive system of women and is. When normal cells in the cervix turn into abnormal cells and gradually grow abnormally out of control, they become cervical cancer (cervical cancer).The aim is to compare the several initiatives to better accuracy, the foresight for the cancer to develop from various western dominated methods by using the engine to identify the strong features of the coast's network CNN-SVM. It is the integration The abstract features extracted from the hidden layer LeNet-5 are combined with strong features after dimension reduction, then the combined features are entered into the SVM classifier for classification. Finally, they are classified by SVM, KNN, ANN, DROPUT, and by voting method they are we also compared. The results showed that the strong feature of the CNN-SVM model can be used in cell classification for early cervical cancer screening. In the conclusion obtained, as well as using functions to improve performance, such as logistic regression, with Acc, Sn, Sp 93.6, 00, 00 relatively, only performed more than in the part and well, and it could have performed more than for improvement.
Des-q: a Quantum Algorithm to Construct and Efficiently Retrain Decision Trees for Regression and Binary Classification
Authors: Kumar Niraj , Yalovetzky Romina , Li Changhao , Minnsen Pierre , Pistoia Marco 
Published: October 2023

Abstract

Decision trees are widely used in machine learning for their simplicity in construction and interpretability. However, as data sizes grow, traditional methods for constructing and retraining decision trees become increasingly slow, scaling polynomially with the number of training examples. We introduce a novel quantum algorithm, Des-q, for constructing and retraining decision trees in regression and binary classification. Assuming the data stream produces small increments of new training examples, Des-q significantly reduces the tree retraining time, achieving poly-logarithmic time complexity in the number of examples, even accounting for the time needed to load the new examples into quantum-accessible memory. Our approach involves building a decision tree algorithm to perform k-piecewise linear tree splits at each internal node. These splits simultaneously generate multiple hyperplanes, dividing the feature space into k distinct regions. To determine the k suitable anchor points for these splits, we develop an efficient quantum-supervised clustering method, building upon the q-means algorithm by Kerenidis et al. Des-q first efficiently estimates each feature weight using a novel quantum technique to estimate the Pearson correlation. Subsequently, we employ weighted distance estimation to cluster the training examples in k disjoint regions based on nearest-neighbor matching and then proceed to expand the tree using the same procedure. We benchmark the performance of the simulated version of our algorithm against the state-of-the-art classical decision tree on multiple data sets with numerical features. Further, we showcase that the proposed algorithm exhibits similar performance to the state-of-the-art decision tree while significantly speeding up the periodic tree retraining.
Factors influencing prosthesis selection and variation: a survey of orthopaedic surgeons in Australia.
Authors: Allen Michelle J , Brain David , Crawford Ross , Senanayake Sameera , Harris Ian A , Elliott Lana , Hinchcliff Reece , McCreanor Victoria , McPhail Steven M 
Published: October 2023

Abstract
Background: There is increasing demand for knee and hip arthroplasties, with considerable health system cost implications. Despite much of the surgical costs relating to the particular prosthesis used, little is known about which factors are most influential for surgeon decision-making, nor is it clear what level of variation may be warranted for clinical reasons.
Materials and Methods: A three-stage study was conducted to address the dual objectives of: a) identify factors influencing prosthesis selection for total hip arthroplasty (THA) and total knee arthroplasty (TKA); and b) develop a working definition for what could be considered unwarranted variation in THA and TKA implant selection. A questionnaire was developed and piloted with input from orthopaedic surgeons. This cross-sectional survey was conducted with orthopaedic surgeons across Australia, followed by an expert panel to finalise the working definition.
Results: Revision rates, familiarity with implant, and implant quality, were factors considered a priority when choosing a prosthesis, whilst other factors including cost, were reported to have limited influence. Technological advancement and revision rates were influential for past changes of prosthesis, and strong clinical evidence for future changes. Consensus was reached on a working definition of unwarranted variation that focused on implants with revision rates of 20% or higher compared to published benchmarks. Use of multiple cost thresholds was recommended for defining both narrow and broad definitions of unwarranted variation.
Conclusion: Findings from this study provide valuable insights into the decision-making process for prosthesis selection, as well as what surgeons believe might constitute unwarranted variation. This information can be used to progress our understanding of the magnitude and impact of this variation through use of the suggested unwarranted variation definitions, as well as inform strategies to address unwarranted variation in prosthesis selection.
Level of evidence: Non-randomised cross-sectional survey – Level 3.
Trial registration: Not applicable.
Characterizing Patient Phenotypes and Emerging Trends in Application of Spatial Analysis in Individual-Level Health Data
Authors: Mollalo Abolfazl , Hamidi Bashir , Lenert Leslie , Alekseyenko Alexander V. 
Published: October 2023

Abstract
Objectives: Health information systems (HIS) commonly contain patient addresses that provide valuable data for geocoding and spatial analysis, enabling more comprehensive descriptions of individual patients in biomedical studies. Despite the widespread adoption of HIS, no systematic review has examined the extent to which spatial analysis is used in characterizing patient phenotypes.
Materials and Methods: We systematically evaluated English-language peer-reviewed articles from PubMed/MEDLINE, Scopus, Web of Science, and Google Scholar databases from inception to August 20, 2023, without imposing constraints on time, geography, or specific health domains.
Results: Only 62 articles met the eligibility criteria. These articles utilized diverse spatial methods, with a predominant focus on clustering techniques, while spatiotemporal analysis (frequentist and Bayesian) and modeling were relatively underexplored. Geographically, the use was limited, involving only nine countries, with over 80% of studies conducted in the United States. Moreover, a noteworthy surge (82.3%) in publications was observed post-2017. The publications investigated various clinical areas, including infectious disease, endocrinology, and cardiology, using phenotypes defined over a range of data domains, such as demographics, diagnoses, and visit. The primary health outcomes investigated were asthma, hypertension, and diabetes. Notably, patient phenotypes involving genomics, imaging, and notes were rarely utilized.
Discussion and Conclusion: This review underscores the growing interest in spatial analysis of HIS-derived data and highlights knowledge gaps in clinical health, phenotype domains, geospatial distribution, and spatial methodologies. Additionally, this review proposes guidelines for harnessing the potential of spatial analysis to enhance the context of individual patients for future biomedical research.