bluuebunny/crossref_metadata_2025_split huggingface dataset:
Impact of the training loss in deep learning–based CT reconstruction of bone microarchitecture
Authors: Leuliet Théo , Maxim Voichiţa , Peyrin Françoise , Sixou Bruno 
Published: February 2022

AbstractPurposeComputed tomography (CT) is a technique of choice to image bone structure at different scales. Methods to enhance the quality of degraded reconstructions obtained from low‐dose CT data have shown impressive results recently, especially in the realm of supervised deep learning. As the choice of the loss function affects the reconstruction quality, it is necessary to focus on the way neural networks evaluate the correspondence between predicted and target images during the training stage. This is even more true in the case of bone microarchitecture imaging at high spatial resolution where both the quantitative analysis of bone mineral density (BMD) and bone microstructure is essential for assessing diseases such as osteoporosis. Our aim is thus to evaluate the quality of reconstruction on key metrics for diagnosis depending on the loss function that has been used for training the neural network.MethodsWe compare and analyze volumes that are reconstructed with neural networks trained with pixelwise, structural, and adversarial loss functions or with a combination of them. We perform realistic simulations of various low‐dose acquisitions of bone microarchitecture. Our comparative study is performed with metrics that have an interest regarding the diagnosis of bone diseases. We therefore focus on bone‐specific metrics such as bone volume and the total volume (BV and TV), resolution, connectivity assessed with the Euler number, and quantitative analysis of BMD to evaluate the quality of reconstruction obtained with networks trained with the different loss functions.ResultsWe find that using norm as the pixelwise loss is the best choice compared to or no pixelwise loss since it improves resolution without deteriorating other metrics. Visual Geometry Group (VGG) perceptual loss, especially when combined with an adversarial loss, allows to better retrieve topological and morphological parameters of bone microarchitecture compared to Structural SIMilarity (SSIM) index. This however leads to a decreased resolution performance. The adversarial loss enhances the reconstruction performance in terms of BMD distribution accuracy.ConclusionsIn order to retrieve the quantitative and structural characteristics of bone microarchitecture that are essential for postreconstruction diagnosis, our results suggest to use norm as part of the loss function. Then, trade‐offs should be made depending on the application: VGG perceptual loss improves accuracy in terms of connectivity at the cost of a deteriorated resolution, and adversarial losses help better retrieve BMD distribution while significantly increasing the training time.
Management of Spinal Muscular Atrophy in the Adult Population
Authors: Rad Nassim , Cai Haibi , Weiss Michael D. 
Published: February 2022

AbstractSpinal muscular atrophy (SMA) is a group of neurodegenerative disorders resulting from the loss of spinal motor neurons. 95% of patients share a pathogenic mechanism of loss of survival motor neuron (SMN) 1 protein expression due to homozygous deletions or other mutations of theSMN1gene, with the different phenotypes influenced by variable copy numbers of theSMN2gene. Advances in supportive care, disease modifying treatment and novel gene therapies have led to an increase in the prevalence of SMA, with a third of SMA patients now represented by adults. Despite the growing number of adult patients, consensus on the management of SMA has focused primarily on the pediatric population. As the disease burden is vastly different in adult SMA, an approach to treatment must be tailored to their unique needs. This review will focus on the management of the adult SMA patient as they age and will discuss proper transition of care from a pediatric to adult center, including the need for continued monitoring for osteoporosis, scoliosis, malnutrition, and declining mobility and functioning. As in the pediatric population, multidisciplinary care remains the best approach to the management of adult SMA. Novel and emerging therapies such as nusinersen and risdiplam provide hope for these patients, though these medications are of uncertain efficacy in this population and require additional study.
Validation of myasthenia gravis diagnosis in the older Medicare population
Authors: Lee Ikjae , Schold Jesse D. , Hehir Michael K. , Claytor Benjamin , Silvestri Nicholas , Li Yuebing 
Published: February 2022

AbstractIntroduction/AimsAdministrative health data has been increasingly used to study the epidemiology of myasthenia gravis (MG) but a case ascertainment algorithm is lacking. We aimed to develop a valid algorithm for identifying MG patients in the older population with Medicare coverage.MethodsLocal older patients (age ≥65) who received healthcare at the Cleveland Clinic and possessed Medicare coverage in 2014 and 2015 were selected. Potential MG patients were identified by using a combination of ICD9 or ICD10 codes for MG and MG‐related text‐word search. Diagnosis was categorized as “definite MG”, “possible MG” or “non‐MG” after review of clinical summaries by 5 neuromuscular specialists. Performances of various algorithms were tested by use of the definite MG cohort as a reference standard, and calculation of sensitivity, specificity, and predictive values.ResultsA total of 118 988 local older patients with Medicare coverage were identified. Usage of MG ICD codes and text‐word search resulted in 125 patients with definite and 67 with possible MG. A total of 45 algorithms involving ICD usage, medication prescription, and specialty visit were tested. The best performing algorithm was identified as 2 office visits using MG ICD codes separated by at least 4 weeks or 1 hospital discharge and 1 office visit each using MG ICD codes separated by at least 4 weeks within the two‐year period, resulting in a sensitivity and positive predictive value of 80% for identifying definite MG patients.DiscussionAlgorithms using ICD codes can reliably identify patients with MG with a high degree of accuracy.
Truck and drone routing problem with synchronization on arcs
Authors: Li Hongqi , Chen Jun , Wang Feilong , Zhao Yibin 
Published: February 2022

AbstractTruck–drone technology that enables drones to launch from or land on a moving truck without the need for the truck to stop is the focus of this study. We define the truck and drone routing problem with synchronization on arcs (TDRP‐SA). The TDRP‐SA is characterized by synchronization on arcs, time windows, classified customers, direct delivery, multiple trucks, and multiple drones carried by each truck. The TDRP‐SA involves synchronization on arcs to permit trucks to dispatch and retrieve drones at suitable moving‐LRLs (drone launch/retrieval locations) on arcs of truck routes. A moving‐LRL is essentially a drone launch/retrieval location with a moving truck, and the drone launch/retrieval operations do not need special parking for the trucks. We develop a mixed integer nonlinear programming model to address the TDRP‐SA. We propose a mathematical analysis method to locate moving‐LRLs and to estimate the drone's arrival time at the customers. We develop boundary models through introducing linear piecewise functions to locate moving‐LRLs. We provide an adaptive large neighborhood search (ALNS) heuristic. Through computational experiments, the effectiveness of the boundary models, the TDRP‐SA model and ALNS‐based heuristic are evaluated.
Path Integral Molecular Dynamics of Liquid Water in a Mean‐Field Particle Reservoir
Authors: Evangelakis Antonios , Panahian Jand Sara , Delle Site Luigi 
Published: February 2022

AbstractWe present a simulation scheme for path integral simulation of molecular liquids where a small open region is embedded in a large reservoir of non interacting point‐particles. The scheme is based on the latest development of the adaptive resolution technique AdResS and allows for the space‐dependent change of molecular resolution from a path integral representation with 120 degrees of freedom to a point particle that does not interact with other molecules and vice versa. The method is applied to liquid water and implies a sizable gain regarding the request of computational resources compared to full path integral simulations. Given the role of water as universal solvent with a specific hydrogen bonding network, the path integral treatment of water molecules is important to describe the quantum effects of hydrogen atoms’ delocalization in space on the hydrogen bonding network. The method presented here implies feasible computational efforts compared to full path integral simulations of liquid water which, on large scales, are often prohibitive.
Formal Total Synthesis of Salvinorin A
Authors: Halang Marc , Maier Martin E. 
Published: February 2022

AbstractThe generation of the quaternary stereocenter at the C9 position of salvinorin A precursors by the Claisen rearrangement was investigated. The required allyl alcohol was prepared from a Wieland‐Miescher ketone using a known γ‐hydroxylation, reduction of the enone double bond, cyanohydrin formation, and elimination, yielding an unsaturated nitrile. A two‐step reduction led to the required allyl alcohol. The subsequent Johnson‐Claisen rearrangement provided a mixture of two diastereomeric 1,4‐unsaturated esters in a ratio of around 2.6 : 1. The major isomer could be converted to a key intermediate of the Hagiwara synthesis of salvinorin A.
Cellular context determines DNA methylation profiles in SWI/SNF‐deficient cancers of the gynecologic tract
Authors: Kommoss Felix KF , Tessier‐Cloutier Basile , Witkowski Leora , Forgo Erna , Koelsche Christian , Köbel Martin , Foulkes William D , Lee Cheng‐Han , Kolin David L , von Deimling Andreas , Howitt Brooke E 
Published: February 2022

AbstractSWI/SNF (SWItch/Sucrose Non‐Fermentable) complex deficiency has been reported in a wide variety of cancers and is often associated with an undifferentiated phenotype. In the gynecologic tract SWI/SNF‐deficient cancers are diagnostically challenging and little is known about their cellular origins. Here we show that undifferentiated endometrial carcinoma (UDEC), SMARCA4‐deficient uterine sarcoma (SDUS), and ovarian small cell carcinoma, hypercalcemic type (SCCOHT) harbor distinct DNA methylation signatures despite shared morphology and SWI/SNF inactivation. Our results indicate that the cellular context is an important determinant of the epigenetic landscape, even in the setting of core SWI/SNF deficiency, and therefore methylation profiling may represent a useful diagnostic tool in undifferentiated, SWI/SNF‐deficient cancers. Furthermore, applying copy number analyses and group‐wise differential methylation analyses including endometrioid endometrial carcinomas and extracranial malignant rhabdoid tumors, we uncover analogous molecular features in SDUS and SCCOHT in contrast to UDEC. These results suggest that SDUS and SCCOHT represent chromosomally stable SWI/SNF‐deficient cancers of the gynecologic tract, which are within the broader spectrum of malignant rhabdoid tumors. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.
Synchronously improved thermal conductivity and mechanical property for polybenzimidazole composites by building the ternary hybrid nanofillers networks
Authors: Mo Rui , Zhu Liuliu , Wu Xinfeng , Guo Wenyao , Min Yulin , Fan Jinchen 
Published: February 2022

AbstractA unique and highly efficient means to ameliorate the thermal conductivities (TCs) of polymers towards the polymer‐based thermal management materials is by introducing high‐thermal conductivity nanofillers to prepare polymer composites. However, in order to obtain high TC, the large content of a single filler often brings serious dispersibility problems which greatly affect the improvement of the TC. Meantime, in a polymeric matrix, it is difficult for a single nanofiller itself to form the heat conduction path. Herein, in order to overcome the above‐mentioned problems, we introduced highly thermal conductive nanofillers like two‐dimensional (2D) functionalized boron nitride nanoflakes (f‐BNNS), MXene (Ti3C2Tx), and one‐dimensional (1D) silver nanowires (AgNWs) into the polybenzimidazole (PBI) matrix together. It is found that the introduction of high‐aspect‐ratio AgNWs could not only improve the dispersion of nanofillers under high‐loading amounts but also facilitate the formation of heat conduction path with thermally conductive f‐BNNS and Ti3C2Tx. When the total loading amount of MXene, f‐BNNS, and AgNWs was 50.5 wt% (MXene: 25 wt%, f‐BNNS: 25 wt%, AgNWs: 0.5 wt%), the yield and ultimate tensile strengths of the f‐BNNS/MXene/AgNWs/PBI‐50/0.5 composite film reached ~204.8 and ~ 203.6 MPa, respectively. Meantime, the in‐plane and through‐plane TCs of f‐BNNS/MXene/AgNWs/PBI‐50/0.5 composite film also could reach ~31.97 and ~ 2.25 W·m−1 K−1 with increases of ~52.2% and ~ 80% in comparison with those of f‐BNNS/MXene/PBI composites, respectively, having the same contents of f‐BNNS and MXene.
Modeling of the piezoresistive behavior of carbon nanotube/polymer composites during stress relaxation
Authors: Shim Wonbo , Jeon Seung‐Yeol , Yu Woong‐Ryeol 
Published: February 2022

AbstractThe resistance change of carbon nanotube (CNT)/polymer composites during stress relaxation depended strongly on the CNT concentration and aspect ratio. At low concentration, the resistance of the composites increased regardless of aspect ratio of CNTs as relaxation progressed, while the relaxation modulus accordingly decreased. This trend changed with CNT concentration. To investigate the mechanism, a new resistor model was developed based on the number of contacts between CNTs within tunneling distance of each other. Simulations revealed that when the number of contacts between CNTs is insufficient to form multiple conducting pathways, the increased tunneling resistance has more influence on the overall resistance, leading to the increased resistance. Finally, the proposed resistor model was used to qualitatively explain the resistance change of the composites at different CNT concentration and aspect ratios during tensile test, demonstrating its validity.
Validation of diagnostic coding for interstitial lung diseases in an electronic health record system in Hong Kong
Authors: Ye Yisha , Hubbard Richard , Li Gloria Hoi‐Yee , Ho Shun Cheong , Sing Chor Wing , Cheung Ching Lung , Lam David Chi Leung 
Published: February 2022

AbstractObjectiveLarge electronic medical record (EMR) databases can facilitate epidemiology research into uncommon diseases such as interstitial lung disease (ILD). Given the rarity and diagnostic difficulty of ILD, the validity of the coding in EMR requires clarification. We aimed to assess the validity of International Classification of Diseases, 9th Revision (ICD‐9) code algorithms for identifying ILD in the territory‐wide electronic medical health record system of Clinical Data Analysis and Reporting System (CDARS) in Hong Kong.MethodPatients who visited the Queen Mary Hospital in 2005–2018 with ILD were identified using the following ICD‐9 codes: post‐inflammatory pulmonary fibrosis (PPF; ICD‐9: 515), idiopathic fibrosing alveolitis (IFA; ICD‐9: 516.3), connective tissue disease‐associated interstitial lung disease (CTD‐ILD; ICD‐9: 517.2, 517.8, 714.81), sarcoidosis (ICD‐9: 135) and extrinsic allergic alveolitis (EAA; ICD‐9: 495). A random selection was conducted in cases with diagnostic code of PPF and IFA, where a relative higher case number was identified. All the cases of CTD‐ILD, sarcoidosis and EAA were included in validation for relatively small case number.ResultsTwo hundred and sixty nine cases were validated using medical record review by a respiratory specialist. The overall positive predictive value (PPV) was 79% (95% CI, 74%–84%). In subgroup analysis, true positive case numbers of PPF, IFA, CTD‐ILD, sarcoidosis and EAA were 74/100 (74%), 95/100 (95%), 11/15 (73%), 27/32 (84%) and 6/22 (27%), respectively.ConclusionsThis was the first ICD‐9 coding validation for ILD in Hong Kong CDARS. Our study demonstrated that using ICD‐9 algorithms 515, 516.3, 517.2, 517.8, 714.81 and 135 enhanced identifications of ILDs with PPV that was reliable to support utility of CDARS database for further clinical research on ILDs. The validity is particularly high with 516.3.
Anomalous Optically Induced Nonvolatile Magnetization Effect in Mn3O4 Superparamagnetic Nanoparticles
Authors: Zhang Yin , Yao Kangkang , Li Jianing , Cao Kaiyan , Wang Fang , Tian Fanghua , Zhou Chao , Song Xiaoping , Yang Sen 
Published: February 2022

AbstractCompared to the normal memory effect observed in interacting magnetic nanoparticles, here, an anomalous photo‐induced magnetization in Mn3O4 superparamagnetic nanoparticles is reported. When the nanoparticles are frozen below blocking temperature, the incident light can create a “melting” of the frozen spins on Mn3O4, leading to a nonvolatile memory effect in magnetization. In addition, the photo‐induced magnetization will change to another on/off response as the temperature rise above blocking temperature. Most interestingly, it is found that the immediate change of magnetization when removing off the light is closely related to the phase transition of Mn3O4. The nonvolatile magnetization effect triggered by the significant photo‐magnetism coupling is promising for searching next‐generation optical‐based devices.
Searching for a mechanistic description of pairwise epistasis in protein systems
Authors: Barnes Jonathan E. , Miller Craig R. , Ytreberg Frederick Marty 
Published: February 2022

AbstractWhen two or more amino acid mutations occur in protein systems, they can interact in a nonadditive fashion termed epistasis. One way to quantify epistasis between mutation pairs in protein systems is by using free energy differences: ϵ = ΔΔG1,2 − (ΔΔG1 + ΔΔG2) where ΔΔG refers to the change in the Gibbs free energy, subscripts 1 and 2 refer to single mutations in arbitrary order and 1,2 refers to the double mutant. In this study, we explore possible biophysical mechanisms that drive pairwise epistasis in both protein–protein binding affinity and protein folding stability. Using the largest available datasets containing experimental protein structures and free energy data, we derived statistical models for both binding and folding epistasis (ϵ) with similar explanatory power (R2) of .299 and .258, respectively. These models contain terms and interactions that are consistent with intuition. For example, increasing the Cartesian separation between mutation sites leads to a decrease in observed epistasis for both folding and binding. Our results provide insight into factors that contribute to pairwise epistasis in protein systems and their importance in explaining epistasis. However, the low explanatory power indicates that more study is needed to fully understand this phenomenon.
Some tools to predict failure probability on products recently launched on the market: A mobile phone case study
Authors: Laos José Arturo Montoya , Jiménez‐Hernández José del Carmen 
Published: February 2022

AbstractPrediction about the failure probability of a product or system is essential in reliability engineering, where a decision‐making process is carried out on a regular basis. This paper proposes a novel index, that allows to predict the failure rate on products recently launched into the market; its calculation is based on sales information and failure reports. Maximum likelihood method is used to derive a mathematical expression for this index, and prediction intervals are obtained throughout a bootstrap approach. A good performance regarding the mean square error and coverage probability is observed in the simulation study included here. Monthly sales data and mobile phone failure reports, provided by the company in charge of the warranty policy process, were used to illustrate our proposal that emerged from an academic‐industry collaboration.
Temperature‐dependent electronic properties for 4f states in cerium mononitride
Authors: Li Ru‐song , Zhou Xiao‐hua , Xie Zheng , Kong Ling‐yun , Wang Deng‐wu , Wang Yang 
Published: February 2022

AbstractIn order to elucidate the temperature‐dependent occupancy number of Ce 4f electrons and valence state of Ce ions in cerium mononitride (CeN), we perform an ab initio calculation by using a many‐body scheme combing density functional theory with dynamical mean field theory, taking into account the spin‐orbit coupling (SOC) interaction and on‐site Coulomb repulsion between Ce 4f electrons. Results demonstrate that Ce 4f j = 5/2 and j = 7/2 manifolds undergo insulating‐metallic transition with increasing of temperature. Ce 4f‐conduction electrons hybridization, f‐f correlation, SOC interaction and final state effects yield a complicated spectrum function in CeN. Ce 4f atomic configuration transition and hybridization might be responsible for the temperature‐dependent occupancy number of Ce 4f electrons and the mixed‐valence state in CeN. A fact that localization of Ce 4f electrons, that is, 4f1 configuration or Ce3+ valence, increases with increasing of temperature could account for the experimentally observed lattice constant versus temperature data. Finally, the so‐called quasiparticle band structure is also discussed for comparison with experimental angle‐resolved photoemission spectrum.
The Quantum Condition Space
Authors: Hu Zixuan , Kais Sabre 
Published: February 2022

AbstractThe fundamental properties of quantum physics are exploited to evaluate event probabilities with projection measurements. Next, to study what events can be specified by quantum methods, the concept of the condition space is introduced, which is found to be the dual space of the classical outcome space of bit strings. Like the classical outcome space generates the quantum state space, the condition space generates the quantum condition space being the central idea of this work. The quantum condition space permits the existence of entangled conditions having no classical equivalent. In addition, the quantum condition space is related to the quantum state space by a Fourier transform guaranteed by the Pontryagin duality, and therefore an entropic uncertainty principle can be defined. The quantum condition space offers a novel perspective of understanding quantum states with the duality picture. Furthermore, the quantum conditions have physical meanings and realizations of their own and thus may be studied for purposes beyond the original motivation of characterizing events for probability evaluation. Finally, the relation between the condition space and quantum circuits provides insights into how quantum states are collectively modified by quantum gates, which may lead to deeper understanding of the complexity of quantum circuits.