bluuebunny/crossref_metadata_2025_split huggingface dataset:
Assessment of influences of posterior rotation of the tibial condyles on the Insall-Salvati ratio
Authors: Nagamine Ryuji , Kawasaki Makoto , Kim Kang-Il , Sakai Akinori , Suguro Toru 
Published: December 2022

AbstractThe positional relationship between patellar and femoral articular surfaces may vary according to the degree of posterior rotation of the tibial condyle, which may influence the patellar configuration. We hypothesized that the configuration of the patella has a rhomboid transformation similar to that of the tibial condyle. This cohort study included 313 patients with knee pain who underwent lateral-view knee digital radiography. The length of the long axis, short axis of the patella, and patellar tendon length of the patellofemoral joint were measured. The patella axis ratio (length of long/short axis) as patellar configuration and Insall-Salvati ratio were calculated. Correlations between the configuration of the tibial condyle and the three length parameters and the Insall-Salvati ratio were assessed. Posterior rotation and the rhomboid transformation of the tibial condyle were positively correlated with the length of the long axis of the patella and negatively correlated with the Insall-Salvati ratio. The more the tibial articular surface shifted posteriorly due to posterior rotation and rhomboid transformation of the tibial condyle, the longer the long axis of the patella was, and the smaller the Insall-Salvati ratio was. The long axis of the patella became longer due to rhomboid transformation, similar to the tibial condyle.
Periportal steatosis in mice affects distinct parameters of pericentral drug metabolism
Authors: Albadry Mohamed , Höpfl Sebastian , Ehteshamzad Nadia , König Matthias , Böttcher Michael , Neumann Jasna , Lupp Amelie , Dirsch Olaf , Radde Nicole , Christ Bruno , Christ Madlen , Schwen Lars Ole , Laue Hendrik , Klopfleisch Robert , Dahmen Uta 
Published: December 2022

AbstractLittle is known about the impact of morphological disorders in distinct zones on metabolic zonation. It was described recently that periportal fibrosis did affect the expression of CYP proteins, a set of pericentrally located drug-metabolizing enzymes. Here, we investigated whether periportal steatosis might have a similar effect. Periportal steatosis was induced in C57BL6/J mice by feeding a high-fat diet with low methionine/choline content for either two or four weeks. Steatosis severity was quantified using image analysis. Triglycerides and CYP activity were quantified in photometric or fluorometric assay. The distribution of CYP3A4, CYP1A2, CYP2D6, and CYP2E1 was visualized by immunohistochemistry. Pharmacokinetic parameters of test drugs were determined after injecting a drug cocktail (caffeine, codeine, and midazolam). The dietary model resulted in moderate to severe mixed steatosis confined to periportal and midzonal areas. Periportal steatosis did not affect the zonal distribution of CYP expression but the activity of selected CYPs was associated with steatosis severity. Caffeine elimination was accelerated by microvesicular steatosis, whereas midazolam elimination was delayed in macrovesicular steatosis. In summary, periportal steatosis affected parameters of pericentrally located drug metabolism. This observation calls for further investigations of the highly complex interrelationship between steatosis and drug metabolism and underlying signaling mechanisms.
A viscoelastic–viscoplastic constitutive model for polymer bonded explosives under low impact loading
Authors: Xiao Youcai , Wang Zeyu , Wang Ruisheng , Zhang Xiaowei , Fan Chenyang , Wei Zhifang , Sun Yi 
Published: December 2022

AbstractViscoplastic work is very important to explosive ignition under impact loading. At present, a large number of constitutive models only consider the viscoelastic and damage behavior of explosives, ignoring the plastic effect under low impact loading. A new viscoelastic–viscoplastic (VE–VP) model was developed and studied to describe the dynamic mechanical behaviors of polymer-bonded explosives (PBXs). The total strain was assumed to be the sum of the viscoelastic (VE) and viscoplastic (VP) components. A generalized Maxwell model was used to determine the VE responses. A VP model was developed by using the classical J2 rate-dependent model with isotropic hardening. Viscoplastic flow was considered in hyperbolic sinusoidal form. The explicit algorithms of VE model were proposed and assessed by using two different integration methods. The accuracy and efficiency of these two methods are similar at high strain rates. The coupled algorithms of VE–VP model were developed by referring to the classical elasto-viscoplasticity (EVP) provided and using the expression of incremental relaxation modulus. The proposed model was implemented in the ABAQUS using a user-subroutine (VUMAT) to predict the response behaviors of PBX 9501 under low impact loading. Several numerical simulations illustrated the computational efficiency and the accuracy of the proposed methods. The model predictions were compared with experimental data, and reasonable agreement was obtained.
Structural optimization and hydraulic performance analysis of bionic pit flow channels based on a genetic algorithm
Authors: Xu Tianyu , Su Yanru , Su Zhouming , Zhi Shuteng , Zheng Ennan 
Published: December 2022

AbstractOrthogonal experiments have mostly been used in the structural optimization of drip irrigation emitter flow channels. To further improve the efficiency of the optimal design, this study used a genetic algorithm to optimize the structure of the bionic pit flow channel. Based on the structural similarity and performance optimization of the torus-margo bordered pit structure, the constitutive equation of the flow channel unit was constructed. The selection, crossover and mutation operators were set by the genetic algorithm, and the objective function value was calculated. The design variables and known variables that met the requirements were put into the computational domain model, and the pit flow channel structure was simulated and optimized. The results showed that there were large low-velocity regions at the junctions and corners of the pit flow channel units at a working pressure of 50 kPa, and no complete low-velocity vortices were observed, indicating that the flow channels had good anti-clogging performance. The distribution of flow velocity on the same cross-section was quite different, which made the flow layers collide and mix, which intensified the loss of energy, indicating that it had a good energy dissipation effect. The multivariate linear regression analysis showed that the four variables of tooth stagger value (j), flow channel angle (θ), tooth spacing (l) and inner and outer boundary spacing (h) had a decreasing degree of influence on the flow index (x). The flow index (x) was negatively correlated with the tooth stagger value (j), flow channel angle (θ) and tooth spacing (l), and positively correlated with the inner and outer boundary spacing (h). The test results of physical samples showed that the average error between the simulation results and the real values was 3.4%, indicating that the accuracy was high, which can provide a basis for the structural optimization design of related pit drip irrigation emitters.
Direct imaging of intracellular RNA, DNA, and liquid–liquid phase separated membraneless organelles with Raman microspectroscopy
Authors: Samuel Ashok Zachariah , Sugiyama Kaori , Ando Masahiro , Takeyama Haruko 
Published: December 2022

AbstractMethodologies for direct intracellular imaging of RNA and DNA are necessary for the advancement of bioimaging. Here we show direct label-free imaging of RNA and DNA in single cells by isolating their accurate Raman spectra. Raman images of DNA from interphase cells show intact nucleus, while those from mitotic cells reveal condensed chromosome. The condensed chromosome images are accurate enough to assign the stage of mitotic cell division (e.g., metaphase). Raman spectral features indicate B-DNA double helical conformational form in all the cell lines investigated here. The Raman images of RNAs, on the other hand, reveal liquid-liquid phase separated (LLPS) membraneless organelles in interphase cells, which disappears during mitosis. Further, the Raman spectrum of proteins from the intracellular LLPS organelles indicates slight enrichment of amyloid-like secondary structural features. Vibrational imaging of intracellular DNA and RNA simultaneously would open myriad of opportunities for examining functional biochemical aspects of cells and organelles.
Exploring robust architectures for deep artificial neural networks
Authors: Waqas Asim , Farooq Hamza , Bouaynaya Nidhal C. , Rasool Ghulam 
Published: December 2022

AbstractThe architectures of deep artificial neural networks (DANNs) are routinely studied to improve their predictive performance. However, the relationship between the architecture of a DANN and its robustness to noise and adversarial attacks is less explored, especially in computer vision applications. Here we investigate the relationship between the robustness of DANNs in a vision task and their underlying graph architectures or structures. First we explored the design space of architectures of DANNs using graph-theoretic robustness measures and transformed the graphs to DANN architectures using various image classification tasks. Then we explored the relationship between the robustness of trained DANNs against noise and adversarial attacks and their underlying architectures. We show that robustness performance of DANNs can be quantified before training using graph structural properties such as topological entropy and Olivier-Ricci curvature, with the greatest reliability for complex tasks and large DANNs. Our results can also be applied for tasks other than computer vision such as natural language processing and recommender systems.
CAT: Learning to collaborate channel and spatial attention from multi‐information fusion
Authors: Wu Zizhang , Wang Man , Sun Weiwei , Li Yuchen , Xu Tianhao , Wang Fan , Huang Keke 
Published: December 2022

AbstractChannel and spatial attention mechanisms have proven to provide an evident performance boost of deep convolution neural networks. Most existing methods focus on one or run them parallel (series), neglecting the collaboration between the two attentions. In order to better establish the feature interaction between the two types of attentions, a plug‐and‐play attention module is proposed, which is termed as ‘CAT’—activating the Collaboration between spatial and channel Attentions based on learned Traits. Specifically, traits are represented as trainable coefficients (i.e. colla‐factors) to adaptively combine contributions of different attention modules to fit different image hierarchies and tasks better. Moreover, the global entropy pooling is proposed apart from global average pooling and global maximum pooling (GMP) operators, which is an effective component in suppressing noise signals by measuring the information disorder of feature maps. A three‐way pooling operation is introduced into attention modules and the adaptive mechanism is applied to fuse their outcomes. Extensive experiments on MS COCO, Pascal‐VOC, Cifar‐100, and ImageNet show that our CAT outperforms the existing state‐of‐the‐art attention mechanisms in object detection, instance segmentation, and image classification. The model and code will be released soon.
Optimal semi‐dynamic traffic and power flow assignment of coupled transportation and power distribution systems for electric vehicles
Authors: Zhao Qiang , Wei Zhenfan , Liu Hui , Han Yinghua , Wang Jinkuan 
Published: December 2022

AbstractAs the most promising alternative to internal combustion engines (ICEs), electric vehicles (EVs) have an excellent development outlook. The charging route scheduling of EVs can simultaneously affect traffic congestion in the transportation network (TN) and power flow distribution in the power distribution network (PDN). The research on TN and PDN coupling networks based on the static traffic flow model is relatively mature; however, it ignores that the traffic flow will spread across periods in a short scheduling period. In this paper, a semi‐dynamic traffic flow model is proposed to represent the dynamic propagation characteristics of EVs and ICEs flow. Furthermore, the cost of carbon emission and system operation are combined as the overall goal of system optimisation. Since the model has become a more complex non‐linear model, this paper proposes to combine the heuristic sequential boundary tightening and binary expansion method to linearise the model. The study compared four cases and found that a 20% penetration rate of EVs can reduce carbon emissions by 4.2% while reducing the system's total cost by 10%. Moreover, the impact of network congestion on the spatiotemporal distribution of traffic flow and power flow in the coupled network is alleviated.
Usability of a gamified antibiotic resistance awareness mobile application: A qualitative evaluation
Authors: Mohamad Ummul Hanan , Abdul Hakim Intan Nadiah , Ali‐Akbari Mahdi 
Published: December 2022

AbstractAntibiotic resistance has been one of the global health threats, yet the awareness of this issue remained low. Hence, an antibiotic resistance awareness app (Stop and End the Drastic Antibiotic Resistance [SEDAR]) was developed to improve public awareness of this issue. To identify the usability problems and improve the app's design before its deployment to the real user, a study on usability must be conducted. The purpose of this paper is to reveal the findings from the usability evaluation of the SEDAR app and present the necessary critical revisions made to improve the usability further. This study adopted guerrilla testing, observation, and retrospective probing methods to evaluate the usability of the SEDAR app. In total, eight participants were involved in this study. Based on the qualitative data, the SEDAR app has good usability. The participants found that it is easy to use, and the navigation within the app is straightforward. The information on antibiotics and antibiotic resistance conveyed through the app is easy to understand due to laymen's terms instead of using scientific terms. A substantial revision suggested by a few participants to further improve the SEDAR app was to add another language selection, the Malay language, to help local users with difficulties understanding English. The SEDAR app has acceptable usability. It is sufficient for users to learn more about antibiotics and antibiotic resistance as the app is easy to use and straightforward. The preliminary data suggested that SEDAR can potentially increase public awareness of antibiotics and antibiotic resistance.
A dagging‐based deep learning framework for transmission line flexibility assessment
Authors: Morteza Azita , Sadipour Masod , Fard Reza Saadati , Taheri Saman , Ahmadi Amirhossein 
Published: December 2022

AbstractUncertainty in renewable energy generation, energy consumption, and electricity prices, as well as transmission congestion, pose a number of problems in modern power grids, necessitating stability on the supply, grid, and demand sides. Grid‐side stability can be achieved by dynamic line rating (DLR) forecasting, which reliably predicts the overall current carrying potential of overhead transmission lines. Long short‐term memory proved beneficiary in this field, owing to its ability to learn highly variable and uncertain data. To empower this network to tackle the non‐stationary nature of meteorological parameters, a novel machine learning (ML) architecture based on Dagging technique is proposed and tested on the data collected from a 400 kV overhead transmission line. Simulation results corroborate that the proposed Dagging‐based stacked LSTM can successfully handle the non‐stationary issue and outperform the decomposition‐based technique, as the state‐of‐the‐art algorithm, for various forecasting horizons. The results confirm the generalizability of models with an application in forecasting DLR over the line without utilizing additional sensors and communication networks. Moreover, the proposed model is compared to several ML architectures, including support vector machines (SVM), random forest (RF), and multi‐layer perceptron (MLP) in a comprehensive benchmark study. The introduced algorithm outperforms MLP by 3.4%, RF by 9.4%, and SVM by 6.7% in terms of average prediction accuracy.
The contribution of low‐head pumped hydro storage to grid stability in future power systems
Authors: Qudaih Mohammed , Engel Bernd , Truijen Daan P. K. , De Kooning Jeroen D. M. , Stockman Kurt , Hoffstaedt Justus , Jarquin‐Laguna Antonio , Ruiz Ruben Ansorena , Goseberg Nils , de Vilder Lucas , Bricker Jeremy D. , Joseph Melvin , Zangeneh Mehrdad , Terheiden Kristina 
Published: December 2022

AbstractThe pan‐European power grid is experiencing an increasing penetration of Variable Renewable Energy (VRE). The fluctuating and non‐dispatchable nature of VRE hinders them in providing the Ancillary Service (AS) needed for the reliability and stability of the grid. Therefore, Energy Storage Systems (ESS) are needed along the VRE. Among the different ESS, a particularly viable and reliable option is Pumped Hydro Storage (PHS), given its cost‐effective implementation and considerable lifespan, in comparison to other technologies. Traditional PHS plants with Francis turbines operate at a high head difference. However, not all regions have the necessary topology to make these plants cost‐effective and efficient. Therefore, the ALPHEUS project will introduce low‐head PHS for regions with a relatively flat topography. In this paper, a grid‐forming controlled converter coupled with low‐head PHS that can contribute to the grid stability is introduced, emphasising its ability to provide different AS, especially frequency control, through the provision of fast Frequency Containment Reserve (fFCR) as well as synthetic system inertia. This paper is an extended version of the paper “The Contribution of Low‐head Pumped Hydro Storage to a successful Energy Transition”, which was presented at the 19th Wind Integration Workshop 2020.
Das Netzwerk Universitätsmedizin: Der Transfer von
Erkenntnissen aus der Forschung in die Patient*innenbehandlung am
Beispiel von COVID-19
Authors: Heyder Ralf 
Published: December 2022

ZusammenfassungEin wichtiges Instrument zur Verbreitung neuer Erkenntnisse aus der Forschung in
der Patient*innenbehandlung sind Leitlinien. Sie sollen eine
möglichst optimale evidenzbasierte Versorgung unterstützen.
Für den Umgang mit einer neuen Erkrankung wie COVID-19, für die
es initial keine etablierte Versorgungspraxis gab, war die schnelle Erarbeitung
aktueller Leitlinien essentiell. Angesichts intensiver weltweiter Forschung
entstand in kurzer Zeit sehr viel neues Wissen. Gleichzeitig mussten akut sehr
viele Patient*innen behandelt werden. Die Fülle neuer
Erkenntnisse musste somit in einer Zeit sehr schnell in die Praxis transferiert
werden, in der medizinisches Personal durch den hohen Versorgungsbedarf ohnehin
schon sehr stark belastet war. Zudem ist die Erstellung von Leitlinien
zeitintensiv und aufwändig. Daher hat das Netzwerk
Universitätsmedizin (NUM), ein Forschungsverbund von 36 deutschen
Universitätsklinika, im Projekt CEOsys Ansätze entwickelt, um
den Transfer neuer Erkenntnisse aus der COVID-19-Forschung in die
Patient*innenbehandlung erheblich zu beschleunigen. Die dafür
erforderlichen Plattformen müssen nun verstetigt werden, um die Pandemic
Preparedness in Deutschland dauerhaft zu verbessern.
Corona-Pandemie: Ökonomische Aspekte des Impfschutzes und der
Impfpriorisierung im Herbst 2022
Authors: Ulrich Volker , Cassel Dieter 
Published: December 2022

ZusammenfassungDer Beitrag geht der Frage nach, ob das Gesundheitswesen besser als bisher durch
den dritten Pandemieherbst und den folgenden Winter kommen könnte und
welche Maßnahmen dazu ergriffen werden müssten. Wie kann seine
Resilienz und Nachhaltigkeit zum Wohle der Bevölkerung gestärkt
werden?
Diagnostic Utility of Spinal Ultrasounds in Neonates
Authors: Gajagowni Saivaroon , Altes Talissa , Vachharajani Akshaya J. 
Published: December 2022

Objective Ultrasound (US) is a common imaging modality used to evaluate spinal anomalies in newborns. However, many indications for the use of spinal US are associated with low diagnostic yield. The purpose of this study is to evaluate the indications and the diagnostic utility of spinal USs performed in newborns at our institution. We also review patient presentations for caudal regression syndrome (CRS) that was identified from the USs performed.
Study Design This study is a retrospective review of spinal USs performed between January 1, 2006, and December 31, 2021, in newborns at a single institution. Indications for each US and any associated abnormalities were noted. Infants with abnormal USs showing CRS are described with their long-term medical outcomes.
Results A total of 592 USs were performed during the specified time period of which 72 (12%) were abnormal. The presence of a sacral dimple was the most common indication for performing a spinal US, although only 14 (4%) were identified as abnormal. Of these 14, 6 (43%) were further evaluated by spinal magnetic resonance imaging (MRI) at the recommendations of a pediatric radiologist and of these, only 2 (14%) had abnormal MRI findings. The two newborns with abnormal MRI findings had mothers with diabetes mellitus in their pregnancies. Of note, one additional newborn had abnormalities on spinal US that was never confirmed on MRI due to being lost to follow-up. Among the other indications, anorectal anomalies (odds ratio [OR], 7.55; 95% confidence interval [CI], 3.01–18.91), spinal mass (OR, 17.99; 95% CI, 7.86–41.2), and meningocele were most associated with abnormal findings.
Conclusion Overall, spinal US has a low diagnostic yield. Sacral dimple was the most common indication for performing a spinal US but had a low yield with few long-term sequelae. Anorectal anomalies had a strong association with abnormal US findings.
Key Points
Racial and Ethnic Disparities among Pregnancies with Chronic Hypertension and Adverse Outcomes
Authors: Fishel Bartal Michal , Chen Han-Yang , Amro Farah , Mendez-Figueroa Hector , Wagner Stephen M. , Sibai Baha M. , Chauhan Suneet P. 
Published: December 2022

Objective We aimed to ascertain whether the risk of adverse pregnancy outcomes in the United States among individuals with chronic hypertension differed by maternal race and ethnicity and to assess the temporal trend.
Study Design Population-based retrospective study using the U.S. Vital Statistics datasets evaluated pregnancies with chronic hypertension, singleton live births that delivered at 24 to 41 weeks. The coprimary outcomes were a composite maternal adverse outcome (preeclampsia, primary cesarean delivery, intensive care unit admission, blood transfusion, uterine rupture, or unplanned hysterectomy) and a composite neonatal adverse outcome (preterm birth, small for gestational age, Apgar's score <5 at 5 minutes, assisted ventilation> 6 hours, seizure, or death). Multivariable Poisson regression models were used to estimate adjusted relative risks (aRRs) and 95% confidence intervals (CIs).
Results Between 2014 and 2019, the rate of chronic hypertension in pregnancy increased from 1.6 to 2.2%. After multivariable adjustment, an increased risk for the composite maternal adverse outcome was found in Black (aRR = 1.10, 95% CI = 1.09–1.11), Hispanic (aRR = 1.04, 95% CI = 1.02–1.05), and Asian/Pacific Islander (aRR = 1.07, 95% CI = 1.05–1.10), compared with White individuals. Compared with White individuals, the risk of the composite neonatal adverse outcome was higher in Black (aRR = 1.39, 95% CI = 1.37–1.41), Hispanic (aRR = 1.15, 95% CI = 1.13–1.16), Asian/Pacific Islander (aRR = 1.34, 95% CI = 1.31–1.37), and American Indian (aRR = 1.12, 95% CI = 1.07–1.17). The racial and ethnic disparity remained unchanged during the study period.
Conclusion We found a racial and ethnic disparity with maternal and neonatal adverse outcomes in pregnancies with chronic hypertension that remained unchanged throughout the study period.
Key Points