bluuebunny/crossref_metadata_2025_split huggingface dataset:
Order recognition by Schubert polynomials generated by optical near-field statistics via nanometre-scale photochromism
Authors: Uchiyama Kazuharu , Nakajima Sota , Suzui Hirotsugu , Chauvet Nicolas , Saigo Hayato , Horisaki Ryoichi , Uchida Kingo , Naruse Makoto , Hori Hirokazu 
Published: November 2022

AbstractIrregular spatial distribution of photon transmission through a photochromic crystal photoisomerized by a local optical near-field excitation was previously reported, which manifested complex branching processes via the interplay of material deformation and near-field photon transfer therein. Furthermore, by combining such naturally constructed complex photon transmission with a simple photon detection protocol, Schubert polynomials, the foundation of versatile permutation operations in mathematics, have been generated. In this study, we demonstrated an order recognition algorithm inspired by Schubert calculus using optical near-field statistics via nanometre-scale photochromism. More specifically, by utilizing Schubert polynomials generated via optical near-field patterns, we showed that the order of slot machines with initially unknown reward probability was successfully recognized. We emphasized that, unlike conventional algorithms, the proposed principle does not estimate the reward probabilities but exploits the inversion relations contained in the Schubert polynomials. To quantitatively evaluate the impact of Schubert polynomials generated from an optical near-field pattern, order recognition performances were compared with uniformly distributed and spatially strongly skewed probability distributions, where the optical near-field pattern outperformed the others. We found that the number of singularities contained in Schubert polynomials and that of the given problem or considered environment exhibited a clear correspondence, indicating that superior order recognition is attained when the singularity of the given situations is presupposed. This study paves way for physical computing through the interplay of complex natural processes and mathematical insights gained by Schubert calculus.
A low-frequency multiple-band sound insulator without blocking ventilation along a pipe
Authors: Zhou Zi-jian , Ao Wei , Fan Li , Zhang Shu-yi , Cheng Li-ping , Xu Xiao-dong , Zhao Jin-yu , Zhang Hui 
Published: November 2022

AbstractIt is challenging to insulate sound transmission in low frequency-bands without blocking the air flow in a pipe. In this work, a small and light membrane-based cubic sound insulator is created to block acoustic waves in multiple low frequency-bands from 200 to 800 Hz in pipes. Due to distinct vibration modes of the membrane-type faces of the insulator and co-action of acoustic waves transmitting along different paths, large sound attenuation is achieved in multiple frequency-bands, and the maximum transmission loss reaches 25 dB. Furthermore, because the sound insulator with a deep subwavelength size is smaller than the cross-sectional area of the pipe, it does not block ventilation along the pipe.
Bifocal flat lens with different imaging characteristics for a dual-sensor imaging system
Authors: Zhou Yin , Kuang Feng-Lin , Li Rui , Li Lei 
Published: November 2022

AbstractWide field of view (FOV) images and magnified images can be taken simultaneously by dual-sensor imaging systems. Here, we propose an approach for creating a bifocal flat lens with different imaging characteristics of its two foci, which makes dual-sensor imaging systems more integrated and miniaturized. That is, two special parts of two different conventional ZP are extracted and then combine the two elements in a specific way. So that there are two foci with different characteristics along the optical axis, one is long focus with higher resolution, the other is short focus with long depth of focus (DOF). Under the proposed approach, a thin and light bifocal diffractive lens (BDL) with thickness of 0.6 μm is developed. The long and short focal lengths of the BDL are ~ 81 mm and ~ 27 mm, respectively, with a diameter of 6 mm. We experimentally demonstrate that the long focus of the BDL is capable of taking high-resolution magnified images, and its resolution is up to 21.90″. The short focus is able to take wide FOV with long DOF images, and two objects spread 2880 mm apart can be imaged clearly. The experiment results demonstrate that all of these metrics are better than those of a conventional refractive lens.
Correlation between brain functional connectivity and neurocognitive function in patients with left frontal glioma
Authors: Ueda Masaya , Usami Kiyohide , Yamao Yukihiro , Yamawaki Rie , Umaba Chinatsu , Liang Nan , Nankaku Manabu , Mineharu Yohei , Honda Masayuki , Hitomi Takefumi , Ikeguchi Ryosuke , Ikeda Akio , Miyamoto Susumu , Matsuda Shuichi , Arakawa Yoshiki 
Published: November 2022

AbstractThe association between neurocognitive function (NCF) impairment and brain cortical functional connectivity in glioma patients remains unclear. The correlations between brain oscillatory activity or functional connectivity and NCF measured by the Wechsler Adult Intelligence Scale full-scale intelligence quotient scores (WAIS FSIQ), the Wechsler Memory Scale-revised general memory scores (WMS-R GM), and the Western aphasia battery aphasia quotient scores (WAB AQ) were evaluated in 18 patients with left frontal glioma using resting-state electroencephalography (EEG). Current source density (CSD) and lagged phase synchronization (LPS) were analyzed using exact low-resolution electromagnetic tomography (eLORETA). Although 2 and 2 patients scored in the borderline range of WAIS FSIQ and WMS-R GM, respectively, the mean WAIS FSIQ, WMS-R GM, and WAB AQ values of all patients were within normal limits, and none had aphasia. In the correlation analysis, lower WMS-R GM was associated with a higher LPS value between the right anterior prefrontal cortex and the left superior parietal lobule in the beta1 band (13–20 Hz, R = − 0.802, P = 0.012). These findings suggest that LPS evaluated by scalp EEG is associated with memory function in patients with left frontal glioma and mild NCF disorders.
Two independent variants of epidermal growth factor receptor associated with risk of glioma in a Korean population
Authors: Baek In Ki , Cheong Hyun Sub , Namgoong Seok , Kim Jeong-Hyun , Kang Seok-Gu , Yoon Seon-Jin , Kim Se Hoon , Chang Jong Hee , Kim Lyoung Hyo , Shin Hyoung Doo 
Published: November 2022

AbstractGliomas are the most common primary tumors in the brain and spinal cord. In previous GWASs, SNPs in epidermal growth factor receptor (EGFR) have been reported as risk loci for gliomas. However, EGFR variants associated with gliomas in the Korean population remain unstudied. This study explored the association of EGFR SNPs with the risk of glioma. We genotyped 13 EGFR exon SNPs in a case–control study that included 324 Korean patients diagnosed with glioma and 480 population-based controls. Statistical analyses of the association between EGFR SNPs and glioma risk were conducted using logistic regression. Both stepwise analysis and conditional logistic analysis were performed to identify independent associations among genotyped variants. We confirmed that two SNPs (rs2227983, rs1050171) were significantly associated with glioma (rs2227983: odds ratio = 1.42, Pcorr = 0.009; rs1050171: odds ratio = 1.68, Pcorr = 0.005). Additionally, the stepwise analysis and conditional logistic analysis indicated that both SNPs created variants with independent genetic effects. This study is the first to show evidence that functional variants of EGFR, namely, rs2227983 (K521R) and rs1050171 (Q787Q), are associated with an increased risk of glioma in the Korean population. Future work should confirm the functional association between EGFR variants and glioma.
Predictive model for the preoperative assessment and prognostic modeling of lymph node metastasis in endometrial cancer
Authors: Asami Yuka , Hiranuma Kengo , Takayanagi Daisuke , Matsuda Maiko , Shimada Yoko , Kato Mayumi Kobayashi , Kuno Ikumi , Murakami Naoya , Komatsu Masaaki , Hamamoto Ryuji , Kohno Takashi , Sekizawa Akihiko , Matsumoto Koji , Kato Tomoyasu , Yoshida Hiroshi , Shiraishi Kouya 
Published: November 2022

AbstractLymph node metastasis (LNM) is a well-established prognostic factor in endometrial cancer (EC). We aimed to construct a model that predicts LNM and prognosis using preoperative factors such as myometrial invasion (MI), enlarged lymph nodes (LNs), histological grade determined by endometrial biopsy, and serum cancer antigen 125 (CA125) level using two independent cohorts consisting of 254 EC patients. The area under the receiver operating characteristic curve (AUC) of the constructed model was 0.80 regardless of the machine learning techniques. Enlarged LNs and higher serum CA125 levels were more significant in patients with low-grade EC (LGEC) and LNM than in patients without LNM, whereas deep MI and higher CA125 levels were more significant in patients with high-grade EC (HGEC) and LNM than in patients without LNM. The predictive performance of LNM in the HGEC group was higher than that in the LGEC group (AUC = 0.84 and 0.75, respectively). Patients in the group without postoperative pathological LNM and positive LNM prediction had significantly worse relapse-free and overall survival than patients with negative LNM prediction (log-rank test, P < 0.01). This study showed that preoperative clinicopathological factors can predict LNM with high precision and detect patients with poor prognoses. Furthermore, clinicopathological factors associated with LNM were different between HGEC and LGEC patients.
The vaccination rift effect provides evidence that source vaccination status determines the rejection of calls to get vaccinated
Authors: Thürmer J. Lukas , McCrea Sean M. 
Published: November 2022

AbstractCOVID vaccination protects individuals and helps end the pandemic, but a sizable minority in Western countries rejects the vaccine. Vaccination status should serve as a group membership, critical communication between groups undermines trust, and we accordingly suggest that calls to get vaccinated by vaccinated sources lead to defensive rejection instead of desired behavior change. We term this the vaccination rift effect. A unique collaboration with national print, online and TV news media yielded a large (N = 1170), age-representative sample of Austrian citizens for our fully randomized experiment. Participants exhibited the vaccination rift: They ascribed less constructive motives, d = 0.28, 95% CI [0.17; 0.40], experienced more threat, d = − 0.30, 95% CI [− 0.42; − 0.19], and ascribed worse personality characteristics to vaccinated (vs. unvaccinated) commenters, d = 0.17, 95% CI [0.06; 0.29]. Constructiveness consistently predicted behavioral measures of counterarguing and vaccination planning (indirect effects B = 0.033, SE = 0.013 and B = − 0.056, SE = 0.014). The vaccination rift was substantially stronger among the critical group of unvaccinated participants, ds = |0.39–0.52|, than among those fully vaccinated, ds = |0.08–0.17|. We discuss how to apply these psychological mechanics of the vaccination rift to public campaigns.
Antibody-dependent cellular cytotoxicity-null effector developed using mammalian and plant GlycoDelete platform
Authors: Kang Cho Eun , Lee Seungeun , Ahn Taeyoung , Seo Dong Hye , Ko Byoung Joon , Jung Minkyu , Lee Jinu , Kim Joo Young , Kim Woo Taek 
Published: November 2022

AbstractCancer therapy using immune checkpoint inhibitor antibodies has markedly shifted the paradigm of cancer treatment. However, methods completely eliminating the effector function of these signal-regulating antibodies is urgently required. The heterogeneity of glycan chains in antibodies limits their use as therapeutic agents due to their variability; thus, the development of uniform glycan chains is necessary. Here, we subjected the anti-programmed cell death protein (PD)-1 antibody nivolumab, a representative immune checkpoint inhibitor, to GlycoDelete (GD) engineering to remove the antibody-dependent cellular cytotoxicity (ADCC) of the antibody, leaving only one glycan in the Fc. Glyco-engineered CHO cells were prepared by overexpressing endo-β-N-acetyl-glucosaminidase (Endo T) in CHO cells, in which N-acetyl-glucosaminyl-transferase I was knocked out using Cas9. GD IgG1 nivolumab and GD IgG4 nivolumab were produced using GD CHO cells, and glycan removal was confirmed using mass spectrometry. Target binding and PD-1 inhibition was not altered; however, ADCC decreased. Furthermore, the IgG4 form, determined to be the most suitable form of GD nivolumab, was produced in a plant GD system. The plant GD nivolumab also reduced ADCC without affecting PD-1 inhibitory function. Thus, CHO and plant GD platforms can be used to improve signal-regulating antibodies by reducing their effector function.
Pre-transplant platelet-to- lymphocyte ratio predicts outcome after allogeneic hematopoietic stem cell transplantation
Authors: Woelfinger P. , Hauptrock B. , Kriege O. , List A. , Schmitt T. , Kuchen R. , Theobald M. , Wagner-Drouet E. M. 
Published: November 2022

AbstractFor many patients with hematological malignancies such as acute leukemia or myelodysplastic syndrome allogeneic hematopoietic stem cell transplantation (allogeneic HSCT) is the only curative treatment option. Despite the curative potential of this treatment many patients experience relapse of their underlying disease or die due to multiple complications e.g. infections. Risk scores could help to assess the individual prognosis and guide patients and treating physicians to choose between different treatment options. Parameters reflecting the inflammatory status, such as neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), and platelet-to-lymphocyte ratio (PLR), have been demonstrated to be associated with prognosis and treatment complications in patients with various cancers. In this study, we evaluate pre-HSCT NLR, MLR and PLR as predictive markers in patients undergoing allogeneic HSCT. We demonstrate that a high (> 133) PLR level is associated with better clinical outcome. Patients with high pre-HSCT PLR show a significant better overall survival (p = 0.001), less relapses (p = 0.016), lower non-relapse-mortality (p = 0.022), less transfusions of red blood cells, platelets and fresh frozen plasma (p = 0.000), fewer episodes of fever (p = 0.002), considerably less different antibiotics (p = 0.005), fewer intensive care unit treatment (p = 0.017) and a lower in-hospital mortality (p = 0.024). Pre-HSCT PLR is easy to calculate by daily routine and could help to predict patient outcome after allogeneic HSCT.
Significance of Brinkman and Stokes system conjuncture in human knee joint
Authors: Al-Atawi Nawal Odah , Hasnain Shahid , Saqib Muhammad , Mashat Daoud S. 
Published: November 2022

AbstractStokes’s equation in the fluid domain and Brinkman’s equation in the porous media are combined in the current study which is designated by the Stokes-Brinkman coupling. The current paper gives a theoretical analysis of the Stokes-Brinkman coupling. It has been shown that such a model is a good match for the knee joint. A flow model has been investigated in order to get a better understanding of the convective diffusion of the viscous flow along the articular surfaces between the joints. The Beavers and Joseph slip conditions which are a specific boundary condition for the synovial fluid are used to solve the governing system of partial differential equations for the synovial fluid and the results are provided here. We develop formulas for the interfacial velocity for both flow through special slip condition and analyse the link between the slip parameters $$\alpha $$
α
and $$\beta $$
β
. Thus, the damping force due to the porous medium naturally when we non-dimensionalize, some parameter which are controlling the structure like, $$\beta $$
β
and $$\alpha $$
α
. Through the development of an analytical solution and numerical simulation (using the finite volume approach) it is hoped that the mechanisms of nutritional transport into the synovial joint will be better understood. According to the data the average concentration has a negative connection with both the axial distance and the duration spent in the experiment. Many graphs have been utilized to gain understanding into the problem’s various characteristics including velocity and concentration, among others. Hyaluronate (HA) is considered to be present in porous cartilage surfaces and the viscosity of synovial fluid fluctuates in response to the amount of HA present.
Competition between electrostatic interactions and halogen bonding in the protein–ligand system: structural and thermodynamic studies of 5,6-dibromobenzotriazole-hCK2α complexes
Authors: Winiewska-Szajewska Maria , Czapinska Honorata , Kaus-Drobek Magdalena , Fricke Anna , Mieczkowska Kinga , Dadlez Michał , Bochtler Matthias , Poznański Jarosław 
Published: November 2022

AbstractCK2 is a member of the CMGC group of eukaryotic protein kinases and a cancer drug target. It can be efficiently inhibited by halogenated benzotriazoles and benzimidazoles. Depending on the scaffold, substitution pattern, and pH, these compounds are either neutral or anionic. Their binding poses are dictated by a hydrophobic effect (desolvation) and a tug of war between a salt bridge/hydrogen bond (to K68) and halogen bonding (to E114 and V116 backbone oxygens). Here, we test the idea that binding poses might be controllable by pH for ligands with near-neutral pKa, using the conditionally anionic 5,6-DBBt and constitutively anionic TBBt as our models. We characterize the binding by low-volume Differential Scanning Fluorimetry (nanoDSF), Isothermal Calorimetry (ITC), Hydrogen/Deuterium eXchange (HDX), and X-ray crystallography (MX). The data indicate that the ligand pose away from the hinge dominates for the entire tested pH range (5.5–8.5). The insensitivity of the binding mode to pH is attributed to the perturbation of ligand pKa upon binding that keeps it anionic in the ligand binding pocket at all tested pH values. However, a minor population of the ligand, detectable only by HDX, shifts towards the hinge in acidic conditions. Our findings demonstrate that electrostatic (ionic) interactions predominate over halogen bonding.
Investigation of the compaction process of electrical machines magnetic circuits and its detrimental effect on magnetic performances
Authors: Helbling Hugo , Van Gorp Adrien , Benabou Abdelkader , Coorevits Thierry , Tounzi Abdelmounaïm , Boughanmi Walid , Laloy Daniel 
Published: November 2022

AbstractThe manufacturing processes of electrical machines may lead to significant degradation of the magnetic properties of their magnetic core (stator, rotor) performances and, as a consequence, to a decrease of their energy efficiency. While the effects of some processes (cutting, welding …) are widely discussed in the literature, this is not the case with the compaction process although it is systematically used to maintain the assembly of electrical steel sheets that compose the magnetic circuits. In addition to the conventional one, a specific compaction process exists for high-power electrical machines. After an introduction, the paper firstly deals with the two studied processes (conventional, specific). Then, an experimental mock-up to study the impact of the two configurations on the magnetic properties (iron losses, normal magnetization curve) is presented. This mock-up is the first, in the literature, that allows to study the effect of a controlled compaction mechanical stress on magnetic properties. Obtained results in both configurations highlight a magneto-mechanical effect that is not reported in the literature where these effects are commonly considered following in-plane mechanical stresses. This paper presents a magneto-mechanical model, taking into account the compaction stress effect, as well as a modelling protocol to model the effect of 3D mechanical stress on magnetic properties, which has never been done in the literature.
Predictive model of spatial scale of forest fire driving factors: a case study of Yunnan Province, China
Authors: Li Wenhui , Xu Quanli , Yi Junhua , Liu Jing 
Published: November 2022

AbstractForest fires are among the major natural disasters that destroy the balance of forest ecosystems. The construction of a forest fire prediction model to investigate the driving mechanism of fire drivers on forest fires can help reveal the mechanism of forest fire occurrence and its risk, and thus contribute to the prevention and control of forest fires. However, previous studies on the mechanisms of forest fire drivers have not considered the effect of differences in spatial scale of action of forest fire drivers on the predicted effect. Therefore, the present study proposes a spatial prediction model of forest fires that considers the spatial scale effect of forest fire drivers to predict forest fire risk. First, based on historical forest fire data and geographic environmental data in the Yunnan Province, geographically weighted logistic regression (GWLR) was used to determine the forest fire drivers and to estimate the probability of forest fire occurrence at locations where fire observations are absent. Then, multi-scale geographically weighted regression (MGWR) was used to explore the spatial scales of action of different drivers on forest fires. The results show that meteorological factors such as relative humidity, air temperature, air pressure, sunshine hours, daily precipitation, wind speed, topographic factors such as elevation, slope, and aspect, anthropogenic factors such as population density and road network, as well as vegetation type, were significantly correlated with forest fires; thus, they are identified as important factors influencing occurrence of forest fires in the Yunnan Province. The MGWR model regression results show that the role of different forest fire drivers on forest fire occurrence has spatial scale differences. The spatial scale of drivers such as altitude, aspect, wind speed, temperature, slope, and distance from the road to the fire point was larger and their spatial influence was relatively stable, with spatial heterogeneity having less influence on the model evaluation results. The spatial scale of drivers such as relative humidity, sunshine, air pressure, precipitation, population density, and vegetation type were smaller, and spatial heterogeneity had a more obvious influence on the model evaluation results. This study provides a reference for selecting drivers and evaluating their spatial scale effects to construct predictive regional forest fire models.