bluuebunny/crossref_metadata_2025_split huggingface dataset:
A novel fast robust optimization algorithm for intensity‐modulated proton therapy with minimum monitor unit constraint
Authors: Fan Qingkun , Zhao Lewei , Li Xiaoqiang , Hu Jie , Lu Xiliang , Yang Zhijian , Zhang Sheng , Yang Kunyu , Ding Xuanfeng , Liu Gang , Dai Shuyang 
Published: July 2024

AbstractBackgroundIntensity‐modulated proton therapy (IMPT) optimizes spot intensities and position, providing better conformability. However, the successful application of IMPT is dependent upon addressing the challenges posed by range and setup uncertainties. In order to address the uncertainties in IMPT, robust optimization is essential.PurposeThis study aims to develop a novel fast algorithm for robust optimization of IMPT with minimum monitor unit (MU) constraint.Methods and MaterialsThe study formulates a robust optimization problem and proposes a novel, fast algorithm based on the alternating direction method of multipliers (ADMM) framework. This algorithm enables distributed computation and parallel processing. Ten clinical cases were used as test scenarios to evaluate the performance of the proposed approach. The robust optimization method (RBO‐NEW) was compared with plans that only consider nominal optimization using CTV (NMO‐CTV) without handling uncertainties and PTV (NMO‐PTV) to handle the uncertainties, as well as with conventional robust‐optimized plans (RBO‐CONV). Dosimetric metrics, including D95, homogeneity index, and Dmean, were used to evaluate the dose distribution quality. The area under the root‐mean‐square dose (RMSD)–volume histogram curves (AUC) and dose–volume histogram (DVH) bands were used to evaluate the robustness of the treatment plan. Optimization time cost was also assessed to measure computational efficiency.ResultsThe results demonstrated that the RBO plans exhibited better plan quality and robustness than the NMO plans, with RBO‐NEW showing superior computational efficiency and plan quality compared to RBO‐CONV. Specifically, statistical analysis results indicated that RBO‐NEW was able to reduce the computational time from to s () and reduce the mean organ‐at‐risk (OAR) dose from % of the prescription dose to % of the prescription dose () compared to RBO‐CONV.ConclusionThis study introduces a novel fast robust optimization algorithm for IMPT treatment planning with minimum MU constraint. Such an algorithm is not only able to enhance the plan's robustness and computational efficiency without compromising OAR sparing but also able to improve treatment plan quality and reliability.
Data‐driven inventory control involving fixed setup costs and discrete censored demand
Authors: Katehakis Michael N. , Teymourian Ehsan , Yang Jian 
Published: July 2024

AbstractWe investigate a data‐driven dynamic inventory control problem involving fixed setup costs and lost sales. Random demand arrivals stem from a demand distribution that is only known to come out of a vast ambiguity set. Lost sales and demand ambiguity would together complicate the problem through censoring, namely, the inability of the firm to observe the lost portion of the demand data. Our main policy idea advocates periodically ordering up to high levels for learning purposes and, in intervening periods, cleverly exploiting the information gained in learning periods. By regret, we mean the price paid for ambiguity in long‐run average performances. When demand has a finite support, we can accomplish a regret bound in the order of which almost matches a known lower bound as long as inventory costs are genuinely convex. Major policy adjustments are warranted for the more complex case involving an unbounded demand support. The resulting regret could range between and depending on the nature of moment‐related bounds that help characterize the degree of ambiguity. These are improvable to when distributions are light‐tailed. Our simulation demonstrates the merits of various policy ideas.
Increasing driver flexibility through personalized menus and incentives in ridesharing and crowdsourced delivery platforms
Authors: Horner Hannah , Pazour Jennifer , Mitchell John E. 
Published: July 2024

AbstractThis article formulates and solves a stochastic optimization model to investigate the impact of crowdsourced platforms (e.g., ridesharing, on‐demand delivery, volunteer food rescue, and carpooling) offering small, personalized menus of requests and incentive offers for drivers to choose from. To circumvent nonlinear variable relationships, we exploit model structure to formulate the program as a stochastic linear integer program. The proposed solution approach models stochastic responses as a sample of variable and fixed scenarios, and to counterbalance solution overfitting, uses a participation ratio parameter. The problem is also decomposed and iterated among two separate subproblems, one which optimizes menus, and another, which optimizes incentives. Computational experiments, based on a ride sharing application using occasional drivers demonstrate the importance of using multiple scenarios to capture stochastic driver behavior. Our method provides robust performance even when discrepancies between predicted and observed driver behaviors exist. Computational results show that offering menus and personalized incentives can significantly increase match rates and platform profit compared to recommending a single request to each driver. Further, compared to the menu‐only model, the average driver income is increased, and more customer requests are matched. By strategically using personalized incentives to prioritize promising matches and to increase drivers' willingness to accept requests, our approach benefits both drivers and customers. Higher incentives are offered when drivers are more likely to accept, while fewer incentives and menu slots are reserved for driver‐request pairs less likely to be accepted.
Memory‐efficient compression of 𝒟ℋ2‐matrices for high‐frequency Helmholtz problems
Authors: Börm Steffen , Henningsen Janne 
Published: July 2024

AbstractDirectional interpolation is a fast and efficient compression technique for high‐frequency Helmholtz boundary integral equations, but requires a very large amount of storage in its original form. Algebraic recompression can significantly reduce the storage requirements and speed up the solution process accordingly. During the recompression process, weight matrices are required to correctly measure the influence of different basis vectors on the final result, and for highly accurate approximations, these weight matrices require more storage than the final compressed matrix. We present a compression method for the weight matrices and demonstrate that it introduces only a controllable error to the overall approximation. Numerical experiments show that the new method leads to a significant reduction in storage requirements.
Stabilized time‐series moving morphable components method for topology optimization
Authors: Hu Xueyan , Li Zonghao , Bao Ronghao , Chen Weiqiu 
Published: July 2024

AbstractThe moving morphable components (MMC) method has been widely used for topology optimization due to its ability to provide an explicit description of topology. However, the MMC method may encounter the instability issue during iteration. Specifically, the iteration history is highly sensitive to parameters of the optimizer, that is, the move limits in the method of moving asymptotes (MMA). Additionally, the final topology obtained from the MMC method usually depends on the initial values. To address these issues and improve the stability of the MMC method in practical applications, this article introduces two strategies. The first strategy is based on the time‐series MMC (TSMMC) method, which proposes a unified description of curved components. However, the use of control‐points‐based design variables may introduce instability into the iteration process due to the strong locality associated with these variables. To mitigate this, global design variables have been incorporated into the formulation. Numerical examples demonstrate that this mixed formulation, combining global and local design variables, can enhance stability significantly. To further enhance stability, the second strategy involves using the trust region‐based moving asymptotes (TRMA) method as the optimizer instead of MMA. The TRMA method incorporates an accuracy control mechanism, resulting in stable and fast convergence behavior, as demonstrated in the numerical examples.
Estimating intralimb proportions for commingled remains
Authors: Cao Doudou , Crema Enrico R. , Pomeroy Emma 
Published: July 2024

AbstractIntralimb proportions provide insights into growth, development, populations history, and adaptation across human groups. However, the conventional approach of calculating brachial and crural indices for individual skeletons and comparing assemblages using sample means is not feasible in commingled remains. This study aims to assess the reliability of an “aggregate method” based on the ratio of sample means of limb bone lengths as an alternative to conventionally calculated indices. We examined the correlation between the aggregate and conventional indices using data from ≥124 worldwide groups (≥2000 adults). The impact of sample size, commingling degree, and within‐group variation on the correspondence between conventional and aggregate indices was further evaluated using simulated datasets. Reliability was measured using the absolute differences between the aggregate and “true” population mean indices and the proportion of simulations producing large errors (>0.02, the average within‐group variation among observed populations). Strong correlations are observed between the aggregate and conventional indices across groups in the empirical dataset. Simulation analyses indicates that larger samples improve prediction reliability, while increased commingling and within‐group variation reduce accuracy. The aggregate method is robust when upper limb samples contain >30 bones (lower limb >50), with more than half of the bones representing proximal and distal elements from the same individuals, and the standard deviation in the index is smaller than 0.02. With sufficient sample sizes, the “aggregate method” is a reliable alternative for estimating average intralimb proportions in commingled and poorly preserved skeletal assemblages, enhancing the research potential of such collections.
Video Otoscopy as a Novel Teaching and Remote Otolaryngology Consultation Tool at an Academic Medical Center
Authors: Winchester Arianna , Chow Michael , Chiang William , Rickert Scott 
Published: July 2024

AbstractObjectiveAssess the use of video otoscopy (VO) as a tool for teaching Emergency Department (ED) residents and remote Otolaryngology consultation.Study DesignSurvey and retrospective chart review.SettingTertiary care center.MethodsEmergency Medicine resident physicians completed an otologic skill self‐assessment and pathology followed by an interactive training on VO and postintervention assessment after 9 months of use. Outcomes compared change in pre‐ to posttraining scores. ED consultations using VO during this time period were reviewed to detect differences between the presumed diagnosis/treatment based only on phone consultation and VO image compared to the final diagnosis/treatment after in‐person Otolaryngology consultation.ResultsForty‐six (63.1%) ED residents participated. Diagnostic accuracy improved by 20.7% overall. The most improved diagnoses were of a normal ear canal (+75%), tympanosclerosis (+58.4%), and ear canal foreign body (+57.1%); most challenging were external auditory canal cyst (−13.6%), hemotympanum (−11.3%), and cerumen (−1.9%). Cholesteatoma did not improve because all responses were incorrect; neither did tympanic membrane perforation because all were correct. Confidence in the otologic exam and anatomy also increased (P < .01). Thirteen consults used VO and 3 (23.1%) had a change in diagnosis/treatment after in‐person Otolaryngology evaluation.ConclusionTraining on the use of VO significantly improves the confidence and diagnostic skills of ED providers for many pathologies. This application suggests the efficacy of an otologic e‐consultation model.
ChatGPT Responses to Frequently Asked Questions on Ménière's Disease: A Comparison to Clinical Practice Guideline Answers
Authors: Ho Rebecca A. , Shaari Ariana L. , Cowan Paul T. , Yan Kenneth 
Published: July 2024

AbstractObjectiveEvaluate the quality of responses from Chat Generative Pre‐Trained Transformer (ChatGPT) models compared to the answers for “Frequently Asked Questions” (FAQs) from the American Academy of Otolaryngology–Head and Neck Surgery (AAO‐HNS) Clinical Practice Guidelines (CPG) for Ménière's disease (MD).Study DesignComparative analysis.SettingThe AAO‐HNS CPG for MD includes FAQs that clinicians can give to patients for MD‐related questions. The ability of ChatGPT to properly educate patients regarding MD is unknown.MethodsChatGPT‐3.5 and 4.0 were each prompted with 16 questions from the MD FAQs. Each response was rated in terms of (1) comprehensiveness, (2) extensiveness, (3) presence of misleading information, and (4) quality of resources. Readability was assessed using Flesch‐Kincaid Grade Level (FKGL) and Flesch Reading Ease Score (FRES).ResultsChatGPT‐3.5 was comprehensive in 5 responses whereas ChatGPT‐4.0 was comprehensive in 9 (31.3% vs 56.3%, P = .2852). ChatGPT‐3.5 and 4.0 were extensive in all responses (P = 1.0000). ChatGPT‐3.5 was misleading in 5 responses whereas ChatGPT‐4.0 was misleading in 3 (31.3% vs 18.75%, P = .6851). ChatGPT‐3.5 had quality resources in 10 responses whereas ChatGPT‐4.0 had quality resources in 16 (62.5% vs 100%, P = .0177). AAO‐HNS CPG FRES (62.4 ± 16.6) demonstrated an appropriate readability score of at least 60, while both ChatGPT‐3.5 (39.1 ± 7.3) and 4.0 (42.8 ± 8.5) failed to meet this standard. All platforms had FKGL means that exceeded the recommended level of 6 or lower.ConclusionWhile ChatGPT‐4.0 had significantly better resource reporting, both models have room for improvement in being more comprehensive, more readable, and less misleading for patients.
Parameter estimation of epoxy resin cure kinetics by dynamicsDSCdata
Authors: Puhurcuoğlu Nihal , Arman Yusuf 
Published: July 2024

AbstractThis study focused on determining the curing kinetic parameters of amine‐epoxy resin by performing dynamic DSC tests. The Kissinger and Crane equations were used to determine the activation energy, the pre‐exponential factor, and the reaction order as kinetic parameters for curing. The Ozawa equation was also used to determine the activation energy that changes at different levels of cure during the reaction. The average activation energy obtained by the Ozawa method was compared with the Kissinger activation energy. In addition, the T‐β extrapolation method was used to determine the optimum curing temperature. The kinetic parameters obtained from the Kissinger and Crane equations were used in the nth‐order kinetic model to predict the degree of cure at a given time and temperature. The linear regression fitting method was used in Minitab software to determine the curing parameters. The results were evaluated based on the fitting parameters. This study provides a theoretical basis for the curing mechanisms of epoxy matrix fiber composites used in the manufacture of wind turbine blades.
Global, regional, and national burden of thalassemia during 1990‐2019: A systematic analysis of the Global Burden of Disease Study 2019
Authors: Wang Rui , Ma Xiao‐Hong , Qin Ze‐Zhen , Hu Xin‐Xuan , Mo Zhi‐Yang , Zhao Ya‐Ye , Zheng Ping , Lu Qiao‐Shan , Li Qiao , Tang Xian‐Yan 
Published: July 2024

AbstractIntroductionThalassemia represents a significant public health challenge globally. However, the global burden of thalassemia and the disparities associated with it remain poorly understood. Our study aims to uncover the long‐term spatial and temporal trends in thalassemia at global, regional, and national levels, analyze the impacts of age, time periods, and birth cohorts, and pinpoint the global disparities in thalassemia burden.MethodsWe extracted data on the thalassemia burden from the Global Burden of Disease Study (GBD) 2019. We employed a joinpoint regression model to assess temporal trends in thalassemia burden and an age‐period‐cohort model to evaluate the effects of age, period, and cohort on thalassemia mortality.ResultsFrom 1990 to 2019, the number of thalassemia incident cases, prevalent cases, mortality cases, and disability‐adjusted life years (DALYs) decreased by 20.9%, 3.1%, 38.6%, and 43.1%, respectively. Age‐standardized rates of incidence, prevalence, mortality, and DALY declined across regions with high, high‐middle, middle, and low‐middle sociodemographic index (SDI), yet remained the highest in regions with low SDI and low‐middle SDI as well as in Southeast Asia, peaking among children under five years of age. The global prevalence rate was higher in males than in females. The global mortality rate showed a consistent decrease with increasing age.ConclusionThe global burden of thalassemia has significantly declined, yet notable disparities exist in terms of gender, age groups, periods, birth cohorts, SDI regions, and GBD regions. Systemic interventions that include early screening, genetic counseling, premarital health examinations, and prenatal diagnosis should be prioritized in regions with low, and low‐middle SDI, particularly in Southeast Asia. Future population‐based studies should focus specifically on thalassemia subtypes and transfusion requirements, and national registries should enhance data capture through newborn screening.
Co‐reinforcing sustainable graphenes from thermoset/thermoplastic wastes for enhanced polypropylene matrix composites in automotive engineering
Authors: Yahyapour Ramisa , Baskan‐Bayrak Havva , Yagcı Yavuz Emre , Saner Okan Burcu 
Published: July 2024

AbstractTalc is widely used in the automotive industry as a primary reinforcement in part manufacturing. However, its relatively high density, low impact strength, and difficulty in recycling pose challenges. The present study investigates the utilization of graphene grown on talc derived from waste polypropylene (PP) and graphene nanoplatelet obtained from waste tires by recycling and upcycling processes to be used as reinforcing agents in thermoplastic processing by keeping mechanical integrity and part performance properties the same compared to the part used in serial production. The whole value chain was examined by developing compound formulation, scaling up with a high shear mixer, and injection molding of the selected exterior part of the glass front grill with its part performance tests with the real‐case thermal and structural finite element analysis. Regarding the mechanical performance analysis, the developed compound formulation having 9 wt% micron scale talc with graphene nanoparticles and hybrid additive yielded substantial enhancements of 32% and 22% in flexural and tensile strength, respectively, in the homopolymer polypropylene (HomoPP) matrix by achieving 10% weight reduction. With a systematic life cycle assessment study, CO2 reduction was provided by 55% for the selected part by replacing virgin HomoPP with mechanically recycled waste PP originally unknown.
Registration of ‘Denali’ white kidney bean
Authors: Gomez Francisco E. , Kelly James D. , Wright Evan M. , Awale Halima E. , Bales Scott 
Published: July 2024

Abstract‘Denali’ (Reg. no. CV‐360, PI 705152) white kidney bean (Phaseolus vulgaris L.), developed by Michigan State University AgBioResearch, was released in 2022 as a midseason, disease‐resistant, bush bean cultivar with uniform dry down. Denali was developed with the pedigree breeding method to the F4 generation followed by pure line selection for disease, agronomic, and quality traits. In 8 years of field trials across Michigan, Denali yielded 3500 kg ha−1, flowered in 37 d, and matured in 97days on average. Plants averaged 46 cm in height, with a lodging resistance score of 1.3 and seed size of 62 g 100 seed−1. Denali combines high yield potential with midseason maturity in a white kidney seed type. Denali outyielded ‘Beluga’ by 13% years and matured 5 days earlier. It is well adapted to the irrigated production systems on coarse‐textured soils where kidney beans are typically grown in Michigan and the Upper Midwest. Denali is resistant to Bean common mosaic virus and exhibits significantly higher levels of tolerance to root rot than ‘ND Whitetail’. Tolerance to common bacterial blight and white mold exhibited by Denali is comparable with ND Whitetail, ‘Yeti’, and ‘Snowdon’. Denali is susceptible to anthracnose. Seed size of Denali (0.62 g) is slightly smaller than Snowdon (0.69 g) and equivalent to seed produced by other white kidney bean cultivars. Seed of Denali meets industry standards for packaging and canning quality in the white kidney bean seed class.
Antimycotic effects of the plasma gun on the yeast Candida glabrata tested on various surfaces
Authors: Trebulová Kristína , Orel Inna , Pouvesle Jean‐Michel , Robert Eric , Rouillard Amaury , Stancampiano Augusto , Hrudka Jan , Menčík Přemysl , Kozáková Zdenka , Měšťánková Zuzana , Kužmová Darina , Paličková Ivana , Čížek Alois , Krčma František 
Published: July 2024

AbstractThis work focuses on the antimycotic effects of the plasma gun as a potential tool for the treatment of superficial infections. Candida glabrata was chosen as a model microorganism. The preliminary tests have been done on the agar plates to establish the basic plasma parameters. To render this research more appropriate to the real application, more complex inoculation substrates, pork skin and 3D‐printed models of the dog ear canal have been used. The results of this work confirm the high efficiency of cold plasma in the inhibition of yeasts on different surfaces and will lead to further experiments.
Dielectric barrier discharge plasma catalysis for diesel particulate matter oxidation: Optimization and synergistic differences in transition metal catalysts
Authors: Ren Baoyong , Wang Wei , Wu Zuliang , Li Jing , Gao Erhao , Zhu Jiali , Yao Shuiliang 
Published: July 2024

AbstractNonthermal plasma (NTP) enhanced catalytic oxidation of diesel particulate matter (DPM) is promising for applications. The synergistic effects of transition metal oxides (MOx, M = Mn, Cu, Ce, Fe, Co, Ti) and dielectric barrier discharge (DBD) plasma on DPM oxidation were investigated, and Fe2O3 showed the best synergistic effect. Cobalt‐doped iron oxide (Co–FeOx) displaying a spinel structure showed the best performance among M–FeOx (M = Co, Ce, Cu, Zn, Mn). The main intermediate product generated during the catalytic oxidation of DPM is monodentate carbonate. Under DBD plasma, a strong oxidizing intermediate ferrate (FeO42−) mainly produced at 100–200°C can promote the low‐temperature oxidation of DPM.
Time‐sharing synergy of NOx mode and O3 mode air discharges for efficient and pollution‐free disinfection
Authors: Wang Zifeng , Wang Luge , Zhang Pengfei , Liu Dingxin , Feng Yue , Yue Qiuyi , He Yujie , Xu Shenghang , Wang Xiangyu , Pei Dandan , Zhang Jishen , Guo Li , Rong Mingzhe 
Published: July 2024

AbstractAs an alternative disinfection technology, air plasma is limited to achieve wider application due to its restricted disinfection level and hazardous by‐products including O3 and NOx. In this work, a time‐sharing synergy strategy is proposed, where NO and NO2 are first generated by a dielectric barrier discharge reactor in NOx mode, and then the discharge is switched into O3 mode by increasing flowrate, thus producing large amounts of high‐valence NOx for efficient disinfection in sealed space. The disinfection effect of time‐sharing synergy is about 2 logs higher than using single O3 or NOx mode with the same discharge power. The concentration of high‐valence NOx is highly correlated with disinfection effect. Finally, all disinfection ingredients are removed after 2‐min gas‐washing and heating.