bluuebunny/crossref_metadata_2025_split huggingface dataset:
Oral cancer incidence rate is associated with access to dental care: City and statewide analyses
Authors: Scussiatto Henrique Ochoa , Kim Seunghee , Kolak Marynia A. , Nocon Cheryl C. , Pinto Jayant M. , Bhayani Mihir K. 
Published: May 2024

AbstractIntroductionAccess to dental care may affect diagnosis of oral squamous cell carcinoma (OSCC). We tested whether the incidence rate of OSCC is higher in regions with less dental care access in the city of Chicago and state of Illinois.Study DesignEcological cohort.SettingPopulation, outpatients, and inpatients.MethodsWe extracted 5‐year averages of the state‐wide county‐level and city‐level OSCC incidence rates from 2015 to 2019 from the Illinois Department of Public Health. Dental care access information was also collected for each county for the same period, as well as the percentage of people that had ≥1 visit to a dentist in the previous year in Chicago. Multivariate Poisson regression was used to investigate the relationship between county‐level access to dental care (and city‐level dentist visits) and OSCC incidence rate, controlling for confounders, with additional flexible semiparametric models for confirmatory sensitivity analysis.ResultsIn Illinois, higher 5‐year incidence rate of OSCC was significantly associated with low access to dental care by county (IRR = 0.96, 95% CI 0.91, 0.98). Southern/southwestern counties had higher incidence rates of OSCC (15.5%–28.4%) and the lowest rates of dental care access (47.5%–69.2%) compared to northern counties (10.3%–15% and 55.4%–80.6%, respectively). In Chicago, people with more dentist visits had a reduced chance of being diagnosed with OSCC (IRR = 0.97, 95% CI 0.91, 0.99), consistent with state‐wide analyses.ConclusionOSCC incidence rate is closely associated with poor local dental healthcare access in a major state and urban city. Increasing dental access could improve cancer outcomes via improved oral health and earlier detection.
Doppler Ultrasound and Resistive Indices in the Diagnosis of Ureteropelvic Junction Obstruction in the Pediatric Population
Authors: Meyers Mariana L. , Walker Jonathan , Sevick Carter , Beltran Gemma G. , Vemulakonda Vijaya M. 
Published: May 2024

ObjectivesMercapto acetyl tri‐glycine renogram (MAG3) scan has been the gold standard assessment of pediatric ureteropelvic junction obstruction (UPJO) but requires intravenous access and radiation exposure. While Doppler ultrasound measurements of resistive indices (RI) of the arcuate arteries have been proposed as an alternative assessment of obstruction, they have not been widely adopted in the pediatric population. We hypothesized that RI of the main renal artery (RA) is more strongly correlated with MAG3 findings than arcuate RI.MethodsPediatric patients with unilateral Society for Fetal Urology grade 3–4 hydronephrosis undergoing concomitant RUS and MAG3 were recruited. Doppler ultrasound peak systolic velocity (PSV); RI of bilateral RA at the origin, middle, and hilum; and RI of the superior, middle, and lower pole arcuate arteries were obtained. MAG3 differential renal function (DRF) and T½ were recorded. Differences in RI measurements (DRI) between the affected and normal kidney were calculated and compared with DRF and T½.Results31 patients (median 4.6‐month‐old) were enrolled. Only RA RI at the origin differed between affected and normal kidneys (p < .001). DRI RA at the origin showed weak evidence for an association with MAG3 DRF < 40% (p .07). DRI was not associated with T½ > 20 minutes.ConclusionThere was weak evidence for an association between RA DRI at the origin and DRF but not with T½. These findings suggest that RA DRI may provide additional data in the evaluation of patients with UPJO to tailor the use of MAG3 and associated risk of radiation exposure to those patients most at risk for concomitant renal function impairment.
Hydrogel‐based and spheroid‐based autologous chondrocyte implantation of the knee show similar 2‐year functional outcomes: An analysis based on the German Cartilage Registry (KnorpelRegister DGOU)
Authors: Bumberger Alexander , Niemeyer Philipp , Angele Peter , Wright Emily K. , Faber Svea O. 
Published: May 2024

AbstractPurposeTo compare short‐term patient‐reported outcomes (PRO) of two contemporary matrix‐associated autologous chondrocyte implantation (M‐ACI) products for the treatment of large articular cartilage defects of the knee.MethodsA retrospective, registry‐based, matched‐pair analysis was performed, comparing PRO of patients undergoing isolated M‐ACI with either Spherox™, a spheroid‐based ACI (Sb‐ACI), or NOVOCART™ Inject, a hydrogel‐based ACI product (Hb‐ACI), for a focal full‐thickness cartilage defect of the knee ≥4 cm2. Matching parameters included age, sex, body mass index, defect size, defect localization, symptom duration and previous surgeries. The Knee Injury and Osteoarthritis Outcome Score (KOOS) and the International Knee Documentation Committee (IKDC) score were obtained up to the 24‐month follow‐up. The total KOOS response rate and percentage of patients attaining a substantial clinical benefit (SCB) in KOOS subscores were calculated.ResultsA total of 45 patients per group were matched. The response rate after 24 months was not significantly different between the groups (Sb‐ACI 64.4% vs. Hb‐ACI 82.2%, p = 0.057). The number of patients with a SCB at 24 months was not significantly different in any KOOS subscore, despite significantly higher improvement of the total KOOS (14.8 ± 16.2 vs. 21.5 ± 15.4, p = 0.047) and KOOS pain in the Hb‐ACI group (12.2 ± 18.6 vs. 20.6 ± 19.1, p = 0.037). The IKDC score in the Hb‐ACI group was significantly higher at the 12‐ and 24‐month follow‐up (60.7 ± 20.2 vs. 70.9 ± 18.0, p = 0.013).ConclusionThe response rate and number of patients achieving an SCB were not significantly different between patients treated with Sb‐ACI or Hb‐ACI. Both procedures can achieve favourable 2‐year PRO. Hb‐ACI was associated with better PRO between 1 and 2 years postoperatively; however, the clinical relevance of this benefit is yet to be proven.Level of EvidenceIII, Retrospective comparative study.
Semi‐Supervised Learning Leveraging Denoising Diffusion Probabilistic Models for the Characterization of Nanophotonic Devices
Authors: Kim Junhyeong , Neseli Berkay , Yoon Jinhyeong , Kim Jae‐Yong , Hong Seokjin , Park Hyo‐Hoon , Kurt Hamza 
Published: May 2024

AbstractAlbeit the recent successful demonstrations of nanophotonic device designs leveraging data‐driven supervised learning methods, several challenges still remain. One of the primary constraints of these methods is their computational cost because they require a massive amount of highly time‐consuming full‐wave electromagnetic simulations. In this study, semi‐supervised learning methods are implemented to avoid this issue. Photonic crystal waveguide devices, which offer interesting light‐matter interactions such as the slow‐light effect and the filtering effect, are employed to validate the methodologies. To utilize unlabeled data within this framework, a novel deep generative model, the denoising diffusion probabilistic model is introduced. Next, a pseudo‐labeling process is introduced to assign synthetic labels to the unlabeled data. The performance of a semi‐supervised learning method is compared with a supervised learning scheme, demonstrating that the performance of the neural network can be enhanced without additional numerical calculations. This method holds extensive potential to elevate the efficiency of designing and characterizing future nanophotonic devices.
Multispectral Polarization States Generation with a Single Metasurface
Authors: Yue Zengqi , Sipahi Tarik , Ahmed Hammad , Ansari Muhammad Afnan , Wang Guanchao , Hou Guanting , Chen Xianzhong , Yang Xibin 
Published: May 2024

AbstractPolarization state generation plays an important role in optics and are applied in many fields. Multispectral polarization manipulation can increase information capacity. To meet the requirement of miniaturization and integration, it is desirable to generate multispectral polarization states with a compact optical device. a metasurface device is proposed and experimentally demonstrated, which can simultaneously realize wavelength separation and polarization generation. A geometric metasurface is used to realize the phase and wavelength multiplexing. Six polarization states with different wavelengths are generated. Customized polarization states with predesigned wavelength information can add extra degrees of freedom for carrying information, opening a new window for portable polarization optics where low‐cost and miniaturized systems are in high demand.
MarR family proteins sense sulfane sulfur in bacteria
Authors: Xuan Guanhua , Xun Luying , Xia Yongzhen 
Published: May 2024

AbstractMembers of the multiple antibiotic resistance regulator (MarR) protein family are ubiquitous in bacteria and play critical roles in regulating cellular metabolism and antibiotic resistance. MarR family proteins function as repressors, and their interactions with modulators induce the expression of controlled genes. The previously characterized modulators are insufficient to explain the activities of certain MarR family proteins. However, recently, several MarR family proteins have been reported to sense sulfane sulfur, including zero‐valent sulfur, persulfide (R‐SSH), and polysulfide (R‐SnH, n ≥ 2). Sulfane sulfur is a common cellular component in bacteria whose levels vary during bacterial growth. The changing levels of sulfane sulfur affect the expression of many MarR‐controlled genes. Sulfane sulfur reacts with the cysteine thiols of MarR family proteins, causing the formation of protein thiol persulfide, disulfide bonds, and other modifications. Several MarR family proteins that respond to reactive oxygen species (ROS) also sense sulfane sulfur, as both sulfane sulfur and ROS induce the formation of disulfide bonds. This review focused on MarR family proteins that sense sulfane sulfur. However, the sensing mechanisms reviewed here may also apply to other proteins that detect sulfane sulfur, which is emerging as a modulator of gene regulation.
Low‐profile frequency selective surface with quasi‐elliptical bandpass response using antenna‐filter‐antenna approach
Authors: Bai Ruxue , Chen Jianzhong , Wu Lihua , Xu Kai‐Da 
Published: May 2024

AbstractAn antenna‐filter‐antenna (AFA) based frequency selective surface (FSS) with excellent spatial filtering performance is proposed. This FSS design incorporates two back‐to‐back microstrip patch antennas, which not only ensures a high roll‐off rate at the passband edge and excellent flatness within the passband, but also achieves an ultra‐low profile. Significantly, the upper and lower band edges demonstrate a substantial drop from −3 to −10 dB within the 0.006 and 0.02 GHz ranges, respectively, resulting in a sharp roll‐off skirt. Furthermore, the frequency of radiation null can be controlled by manipulating the length of the quarter‐wavelength open‐ended stub, thereby possessing exceptional out‐of‐band suppression. A prototype of the proposed FSS with low profile is fabricated and measured. The simulations and measurements of the AFA‐based FSS show that a quasi‐elliptical bandpass filtering response with superior performance is achieved.
Analysis of natural vibration of truncated conical shells partially filled with fluid
Authors: Bochkarev Sergey A. , Lekomtsev Sergey V. 
Published: May 2024

AbstractIn this paper, we study the vibrational behavior of shells in the form of truncated cones containing an ideal compressible fluid. The sloshing effect on the free surface of the fluid is neglected. The dynamic behavior of the elastic structure is investigated based on the classical shell theory, the constitutive relations of which represent a system of ordinary differential equations written for new unknowns. Small fluid vibrations are described in terms of acoustic approximation using the wave equation for hydrodynamic pressure written in spherical coordinates. Its transformation into the system of ordinary differential equations is carried out by applying the generalized differential quadrature method. The formulated boundary value problem is solved by Godunov's orthogonal sweep method. Natural frequencies of shell vibrations are calculated using the stepwise procedure and the Muller method. The accuracy and reliability of the obtained results are estimated by making a comparison with the known numerical and analytical solutions. The dependencies of the lowest frequency on the fluid level and cone angle of shells under different combinations of boundary conditions (simply supported, rigidly clamped, and cantilevered shells) have been studied comprehensively. For conical straight and inverted shells, a numerical analysis has been performed to estimate the possibility of finding configurations at which the lowest natural frequencies exceed the corresponding values of the equivalent cylindrical shell.
Optimal error estimates of a decoupled finite element scheme for the unsteady inductionless MHD equations
Authors: Zhang Xiaodi , Dong Shitian 
Published: May 2024

AbstractThis article focuses on a new and optimal error analysis of a decoupled finite element scheme for the inductionless magnetohydrodynamic (MHD) equations. The method uses the classical inf‐sup stable Mini/Taylor‐Hood (Mini/TH) finite element pairs to appropriate the velocity and pressure, and Raviart–Thomas (RT) face element to discretize the current density spatially, and the semi‐implicit Euler scheme with an additional stabilized term and some delicate implicit–explicit handling for the coupling terms temporally. The method enjoys some impressive features that it is linear, decoupled, unconditional energy stable and charge‐conservative. Due to the errors from the explicit handing of the coupling terms and the existence of the artificial stabilized term, and the contamination of the lower‐order RT face discretization in the error analysis, the existing theoretical results are not unconditional and optimal. By utilizing the anti‐symmetric structure of the coupling terms and the existence of the extra dissipative term, and the negative‐norm estimate for the mixed Poisson projection, we establish the unconditional and optimal error estimates for all the variables. Numerical tests are presented to illustrate our theoretical findings.
C5 Pentacle Structures: A Localization‐Delocalization Matrices Approach
Authors: Pilmé Julien , Spezia Riccardo 
Published: May 2024

AbstractThis article explores the possible presence of a pentacle valence bond structure in C
cyclic molecules. At this end, we have used quantum chemistry tools to elucidate the possible arrangement and the nature of chemical bonds within linear, cyclic, and three‐dimensional structures only formed by five carbon atoms. While the linear structure is clearly the most stable one, local minima were obtained for both bi‐ and three‐dimensional structures. Using the localization‐delocalization matrices approach, we characterize both the minimum linear structure and the cyclic ones. Interestingly, the linear structure is a combination of ionic and covalent bonds, albeit the four distances are almost identical, when using Density Functional Theory. For cyclic C
, the pentacle bonding arrangement emerges as a significant Lewis structure, indicative of an unusual formal configuration characterized by five intersecting C−C bonds. Our calculations show that this pentacle arrangement in cyclic C
scheme is also present in the more known cyclo‐pentadienyl molecule.
Effect of cutting flute geometry of orthodontic miniscrew on cortical bone microdamage and primary stability using a human bone analog
Authors: Wijarn Sansanee , Uezono Masayoshi , Takakuda Kazuo , Ogasawara Takeshi , Techalertpaisarn Paiboon , Moriyama Keiji 
Published: May 2024

AbstractBackgroundAlthough orthodontic miniscrews were developed to provide reliable anchorage against orthodontic traction forces, they have pervasive low stability problems. Cutting flute geometry of the screw is considered to be a key factor; however, it has not been fully investigated. Therefore, the objective of our study is to evaluate the effect of cutting flute geometry on cortical bone microdamage.Materials and methodsHuman bone analogs, 1.0 mm thick, were prepared alongside custom‐made Ti6Al4V screws. These screws, with no flutes or modified flute geometries, came in lengths of 1.2, 2.4, and 5.0 mm, each with rake angles of 0° and 20°. Each screw was inserted into a bone sample and removed while measuring the maximum insertion torque (MIT) and the maximum removal torque (MRT). The bone microdamage was evaluated using cross‐sectional surface images of human bone analogs.ResultsMRT was significantly different in all pairwise comparisons among the three flute‐length groups in each rake angle, and the 5.0‐mm‐length groups demonstrated the lowest values. Similar tendencies were found in MIT and the bone microdamage, although significant differences were not observed in all the pairwise comparisons in the flute‐length groups in each rake angle. Interestingly, the two rake angle groups in each flute‐length exhibited significant differences in MIT and the bone microdamage, but not in MRT.ConclusionFrom our investigation using custom‐made screws and human bone analog, cortical bone microdamage is affected by both flute geometries, whereas primary stability is affected by only the flute length.
Why does mobile payment promote purchases? Revisiting the pain of paying, and understanding the implicit pleasure via selective attention
Authors: Ma Qingguo , Tan Yulin , He Yijin , Cheng Lu , Wang Manlin 
Published: May 2024

AbstractThe past years have witnessed a phenomenal growth of the mobile payment market, but how mobile payment affects purchase behavior receives less attention from academics. Recent studies suggested that lower pain of paying may not fully clarify the relationship between mobile payment and increased purchases (i.e., mobile payment effect). The current research first introduced price level in Study 1 and demonstrated that the pain of paying served as an underlying mechanism only in the high‐price condition rather than the low‐price condition. As such, Study 2 was conducted in a low‐price context to address the uncovered mechanisms. We propose a new concept of “pleasure of payment” that is defined as an implicit and consumption‐related hedonic response based on the cue theory of consumption. By tracking spontaneous attention to positive attributes (i.e., benefits) of products, Study 2 demonstrated this implicit pleasure as a psychological mechanism for the mobile payment effect when the pain of paying was not at play. These findings have important implications for mobile payment in research and practice by identifying price level as a boundary condition for the role of pain of paying and understanding the positive downstream consequences of mobile payment usage on consumer psychology.
Characterizing diseases using genetic and clinical variables: A data analytics approach
Authors: Gollapalli Madhuri , Anand Harsh , Srinivasan Satish Mahadevan 
Published: May 2024

AbstractPredictive analytics is crucial in precision medicine for personalized patient care. To aid in precision medicine, this study identifies a subset of genetic and clinical variables that can serve as predictors for classifying diseased tissues/disease types. To achieve this, experiments were performed on diseased tissues obtained from the L1000 dataset to assess differences in the functionality and predictive capabilities of genetic and clinical variables. In this study, the k‐means technique was used for clustering the diseased tissue types, and the multinomial logistic regression (MLR) technique was applied for classifying the diseased tissue types. Dimensionality reduction techniques including principal component analysis and Boruta are used extensively to reduce the dimensionality of genetic and clinical variables. The results showed that landmark genes performed slightly better in clustering diseased tissue types compared to any random set of 978 non‐landmark genes, and the difference is statistically significant. Furthermore, it was evident that both clinical and genetic variables were important in predicting the diseased tissue types. The top three clinical predictors for predicting diseased tissue types were identified as morphology, gender, and age of diagnosis. Additionally, this study explored the possibility of using the latent representations of the clusters of landmark and non‐landmark genes as predictors for an MLR classifier. The classification models built using MLR revealed that landmark genes can serve as a subset of genetic variables and/or as a proxy for clinical variables. This study concludes that combining predictive analytics with dimensionality reduction effectively identifies key predictors in precision medicine, enhancing diagnostic accuracy.
Business environment and adoption of AI: Navigation for internationalization by new ventures in emerging markets
Authors: Moharrak Moayad , Nguyen Nguyen Phong , Mogaji Emmanuel 
Published: May 2024

AbstractThis study explores the intersection of international business and artificial intelligence (AI), focusing on how new ventures navigate environmental challenges for international expansion within Africa's transportation sector. Despite a wealth of literature on AI in developed countries, a notable gap exists in the understanding of the challenges emerging economies face in implementing AI practices, particularly in the context of Africa‐to‐Africa internationalization. The current study delved into the transformative potential of AI, identifying institutional voids as opportunities for innovation on the continent. Employing the Technology Organization and Environment framework, the study investigated the adoption of AI technology in the African business environment. Qualitative data gathered through interviews with transport tech startup founders across Africa provided insights into technological innovation, institutional dynamics, and market peculiarities. The founders recognized hurdles such as data scarcity, human resource constraints, and regulatory obstacles amid institutional voids. The study underscores the importance of understanding expectations, balancing possibilities and realities, and fostering collaboration. It offers valuable insights into the complexities faced by and opportunities for new ventures leveraging AI in internationalization, with practical implications for strategic AI implementation, policy development, market expansion, technology solutions, and cross‐border transportation within Africa's unique business landscape.