bluuebunny/crossref_metadata_2025_split huggingface dataset:
What dominates the seasonal predictable signals of the East Asian summer monsoon rainfall in addition to the decaying/developing El Niño–Southern Oscillation and spring Arctic Oscillation?
Authors: Ying Kairan , Jiang Dabang , Zheng Xiaogu , Frederiksen Carsten S. , Peng Jing , Zhao Tianbao , Zhong Linhao 
Published: May 2022

Abstract
Improvement in the seasonal forecasting of East Asian summer monsoon rainfall (EASMR) remains a great challenge, as it is influenced by varied and complex impacts from (1) external forcings and slowly varying internal variabilities, which are potentially predictable, and (2) internal dynamics on intraseasonal time scales, which is basically unpredictable beyond a season. In this work, a (co-)variance decomposition method is applied to identify the leading potentially predictable (slow) patterns of the EASMR [the seasonal mean rainfall in the region (100°E–140°E, 5°N–50°N) in June–July–August] during 1979–2019 by separating the unpredictable noise (intraseasonal). We focus on the most critical predictable sources that are additional to the decaying (DC) El Niño–Southern Oscillation (ENSO), developing (DV) ENSO, and spring Arctic Oscillation (AO) – the three most important and well-recognized predictors for EASMR. We find that (1) the indices that represent the EASMR predictability related to the DC ENSO, spring AO and DV ENSO are the preceding November to March Niño 1+2 sea surface temperature (SST), the April–May AO, and the May Niño 4 SST, respectively; (2) the dominant additional predictable EASMR signals that are linearly independent of the DC ENSO, spring AO and DV ENSO have apparent relationships with the interannual variability of the SST in the western North Pacific, tropical and southern Atlantic, southern Indian, and Arctic oceans during boreal springtime, as well as the linear trend; and (3) by applying a principal component regression scheme to evaluate the EASMR predictability arising from DC/DV ENSO–AO and these additional predictors, the cross-validated fraction variance skill of the total seasonal mean EASMR is 11% (8%–land; 13%–ocean) for the former, and 15% (15%–land; 15%–ocean) for the latter, with a total of 26% that comprises more than 80% of the potential predictability of the EASMR. The considerable skill stemming from the predictors additional to DC/DV ENSO–AO indicates that they are worthy of attention in the seasonal forecasting of EASMR, especially for terrestrial areas.
Differential angiogenic induction impacts nasal polyp tissue growth
Authors: de Góes Hallyson André Nascimento , Amaral Jônatas Bussador do , Almeida Joyce dos Anjos , Voegels Richard Louis , Cruz Leandro Ticlia de la , Thamboo Andrew , Gomes Lígia Ferreira , Pezato Rogério 
Published: May 2022

Abstract
Background: In chronic rhinosinusitis with nasal polyps, inflammatory edema drives tissue remodeling favoring anomalous growth of the nasal mucosa, but a proangiogenic contribution of nasal polyp in support of tissue growth is still controversial. The chorioallantoic membrane of chicken embryo model was employed to address the potentiality of nasal tissue fragments to modulate angiogenesis.Methods: Fifty-seven fertilized eggs were implanted with polyp or healthy nasal mucosa tissue or were kept as non-implanted controls. The embryos' size, length, and development stage, and chorioallantoic membrane vasculature morphology were evaluated after 48h. Quantitative computer vision techniques applied to digital chorioallantoic membrane images automatically calculated the branching index as the ratio between the areas of the convex polygon surrounding the vascular tree and the vessels’ area. Results: Mucosal, but not polyp tissue implants, hampered embryo development and induced underdeveloped chorioallantoic membranes with anastomosed, interrupted, and regressive vessels. Vessels’ areas and branching indexes were higher among the chorioallantoic membranes with polyp implants and controls than among those with healthy mucosa implants. Discuss: This study demonstrated for the first time a differential angiogenic induction from nasal polyp tissue supporting tissue growth when compared with healthy nasal mucosa.Conclusion: Nasal polyp presents differential angiogenic induction that impacts tissue growth.
Pediatric Patient with Penetrating Brain Injury by a Pickaxe: Case Report and Literature Review
Authors: Mansilla Raíssa , Pinguelo Paulo Henrique Reigota , Pilon Bárbara Contarato , Amaral Luís Gustavo Duarte , Martins Fernando Jorge Monteiro , Silva Geraldo Luiz Paraguassu Correia da 
Published: May 2022

Abstract
Head trauma due to falls is often seen in children; however, penetrating brain injury (PBI), the most life-threatening condition of traumatic brain injury (TBI), is exceedingly rare. Herein, we report and discuss the challenges encountered in the surgical and postoperative management of a 13-year-old child patient with PBI by a pickaxe who was admitted to Glasgow Coma Scale (GCS) 3 and who not only survived but also achieved a good Glasgow Outcome Scale (GOS) after one year of postoperative follow-up. To our knowledge, this is the first case of pickaxe-induced brain injury on the American continent and the youngest survivor of this trauma reported in the literature.
Zn-(BDC) and Zn-(BDC)-NH 2 MOFs: Novel Photocatalysts for Desulfurization of Dibenzothiophene from Fuels
Authors: Mohammadzadeh Dawud , Hosseini Seyed Ali 
Published: May 2022

Abstract
The paper reports the development of nanostructures of organic-metallic frameworks (MOFs) in the form of Zn(BDC) and Zn(BDC)-NH2 as potent macroporous photocatalysts for desulfurization of aromatic hydrocarbons (dibenzothiophene) in fuels. The reason for placing amine groups in the Zn-MOF photocatalytic structure was that it increased the interaction between MOF and sulfur compounds. The experiments were designed out by the Box-Behnken method of response surface methodology (RSM) and the process was modelled and optimized. Three independent parameters i.e. concentration of dibenzothiophene, the amount of photocatalyst and light emission time were considered in the experimental design. The interactions between the parameters were also investigated by 2D contour and 3D plots. The optimum removal of DBT (50.40%) resulted under a fuel model containing 50 ppm DBT, desulfurized by 0.060 g of Zn-MOF-NH2 photocatalyst under visible lamp light for 180 min. The predicted response (DBT removal%) by the RSM model was 50.68%. The amine-modified Zn-MOF exhibited a greater activity in the elimination of DBT due to its active amine groups. The mechanism of photocatalytic desulfurization of DBT over Zn-MOF-NH2 was proposed. The physical-chemical properties of the MOF samples were further recognized by Fourier Transform Infrared (FTIR), X-ray diffraction (XRD), Brunauer-Emmett-Teller (BET), Field-Emission Scanning Electron Microscopy (FESEM) and Uv-Vis diffuse reflectance spectroscopy (UV-Vis DRS). This study showed that Zn-MOF can be an effective photocatalyst for desulfurization under the visible light of a fuel model.
Self-reduction assisted MXene/Silver composite Tencel cellulose-based fabric with electrothermal conversion and NIR photothermal actuation
Authors: Li Han , Pan Yinuo , Du Zhaoqun 
Published: May 2022

Abstract
Smart e-textiles, which are capable of wireless transmission, signal conversion and energy transduction, have the capability to provide added values and be more versatile. However, there are still many challenges in fabricating a flexible and durable smart fabric with high-level multifunctional integration. Herein, a novel two-dimensional material, Ti3C2Tx MXene, and zero-dimensional material, silver nanoparticles (AgNPs) were coupled to fabricate a smart Tencel fabric with electrical and light versatility. By self-reduction reaction, silver nitrate can be reduced to AgNPs because the existence of reductant, MXene, enabling flexible conductive points and paths for fabric. Benefiting from excellent hydrophilicity and rich terminals of MXene, the interface bonding force was enough to get a uniform fabric. Because of the enhanced electrical conductivity of MXene/AgNPs, the MXene/silver nanoparticles (MS) Tencel fabric exhibited excellent electrothermal property (57.1℃ at 30s heating time under 6.0 V voltage) as well as thermal sensing performance, and can serve as an element of array heating devices. In addition, the MS fabric also has photothermal (maximal bending angle was 149° at 31s) capability due to the conversion of near-infrared (NIR) light by MXene, enabling photothermal actuator resulting from thermal expansion of encapsulated Ecoflex layer. With thermal and NIR sensitive capabilities, the MS Tencel fabric performed thermal sensation and has the potential in thermal sensitive robots.
Stochastic simulation of seawater intrusion in Longkou area, China
Authors: Fan Yue , Wu Qinghua , Cui Haodong , Lu Wenxi , Ren Wanli 
Published: May 2022

Abstract
Seawater intrusion is a common groundwater pollution problem, which has a great impact on ecological environment and economic development. In this paper, a numerical simulation model of variable density groundwater was constructed to simulate and predict the future seawater intrusion in Longkou city, Shandong Province of China. The influence of the sensitive parameter uncertainty of the model on the simulation results was evaluated by using the Monte Carlo method. In order to reduce the computational load from repeatedly calling the simulation model, the surrogate model was established by using the Support Vector Regression (SVR) method. The research results indicate that the SVR surrogate model can fit the input-output relationship of the simulation model with high accuracy. The seawater intrusion in the Longkou area will gradually aggravate at a slow rate, and the area of seawater intrusion is estimated to be 67.45 to 77.07 km2 after 30 years with 80% confidence.
Validating ORR and PFS as surrogate endpoints in phase II and III clinical trials for NSCLC patients: difference exists in the strength of surrogacy in various trial settings
Authors: Hua Tiantian , Gao Yuan , Zhang Ruyang , Wei Yongyue , Chen Feng 
Published: May 2022

Abstract
ObjectiveThis study aims to systematically validate the performance of surrogate endpoints in phase II and III clinical trials for NSCLC patients under various trial settings.MethodsA literature search retrieved all registered phase II and III trials of NSCLC patients in which OS, with at least one of ORR and PFS, were reported. Associations between surrogate and true endpoints were assessed on two levels. On the arm level, three pairs of correlations, i.e., ORR vs. median OS, ORR vs. median PFS, and median PFS vs. median OS, were analysed using Spearman's rho. On the trial level, similarly, three pairs of correlations, i.e., ΔORR vs. HR of OS, ΔORR vs. HR of PFS, and HR of PFS vs. HR of OS, were analysed using Spearman's rho and weighted linear regression model respectively. Finally, sensitivity analyses were performed to explore surrogacy under various trial settings.ResultsAt arm level, three pairs of correlations are all high (Spearman's rho= 0.700, 0.831, 0.755, respectively). At trial level, there is a low correlation between ΔORR and HR of OS, a high correlation between ΔORR and HR of PFS and a moderate correlation between HR of PFS and HR of OS (Spearman's rho=0.462, 0.764, 0.584, respectively). In the sensitivity analysis, we find correlations between surrogate and true endpoints vary by different trial settings. It is noteworthy that the strength of surrogacy of these intermediate endpoints in targeted therapy is greater than that in immunotherapy.ConclusionWe suggest that in phase II and III trials of targeted therapy and immunotherapy for NSCLC patients: 1) ORR lacks validity for the surrogacy of OS, excluding in first-line therapy, and 2) ORR may be an appropriate surrogate endpoint for PFS, and 3) PFS may be considered a modest surrogacy for OS, with better performance in first-line therapy trials.
Sleep-controlling neurons are sensitive and vulnerable to multiple forms of α-synuclein: implications for the early appearance of sleeping disorders in α-synucleinopathies
Authors: Santos Altair B Dos , Skaanning Line K , Thaneskwaran Siggania , Mikkelsen Eyd , Romero-Leguizamon Cesar R , Skamris Thomas , Kristensen Morten P , Langkilde Annette E , Kohlmeier Kristi A. 
Published: May 2022

Abstract
Parkinson’s disease, Multiple System Atrophy, and Lewy Body Dementia are incurable diseases called α-synucleinopathies as they are mechanistically linked to the protein, α-synuclein (α-syn). α-syn exists in different structural forms which have been linked to clinical disease distinctions. However, sleeping disorders (SDs) are common in the prodromal phase of all three α-synucleinopathies, which suggests that sleep-controlling neurons are affected by multiple forms of α-syn. To determine whether a structure-independent neuronal impact of α-syn exists, we compared and contrasted the cellular effect of three different α-syn forms on neurotransmitter-defined cells of two sleep-controlling nuclei located in the brainstem: the Laterodorsal Tegmental nucleus and the Pedunculopontine Tegmental nucleus. We utilized size exclusion chromatography, fluorescence spectroscopy, circular dichroism spectroscopy and transmission electron microscopy to precisely characterize ​​timepoints in the α-syn aggregation process with three different dominating forms of this protein (monomeric, oligomeric and fibril) and we conducted an in-depth investigation of the underlying neuronal mechanism behind cellular effects of the different forms of the protein using electrophysiology, multiple-cell calcium imaging, single-cell calcium imaging and live-location tracking with fluorescently-tagged α-syn. Interestingly, α-syn altered membrane currents, enhanced firing, increased intracellular calcium and facilitated cell death in a structure-independent manner in sleep-controlling nuclei, and postsynaptic actions involved a G-protein-mediated mechanism. These data are novel as the sleep-controlling nuclei are the first brain regions reported to be affected by α-syn in a structure-independent manner. These regions may represent highly important targets for future neuroprotective therapy to modify or delay disease progression in α-synucleinopathies.
Deep learning based clinical target volumes contouring and model adaptation for prostate cancer: easy and efficient application
Authors: Wen Feng , Chen Zhebin , Wang Xin , Dou Meng , Yang Jialuo , Xu Yupeng , Yao Yu , Shen Yali 
Published: May 2022

Abstract
Background: Radiotherapy has been crucial in the treatment of prostate cancer. However, manual segmentation is labor intensive and highly variable among radiation oncologists, especially for lymph node volumes. Hence, in this study, a deep learning based automated contouring model is constructed with style adaptation algorithm for clinical target volumes (CTVs) of intact and postoperative prostate cancer. Methods: Computed tomography (CT) data sets for 197 prostate cancer patients, treated by one senior physician with more than 15 years of radiation work experience, during the period of November 2012 to January 2020 were selected, retrospectively. Of these patients, 167 cases were used for the training set and 30 for the test set. Two auto-delineation models were built for radical radiotherapy and postoperative radiotherapy of prostate cancer, including CTV1 for pelvic lymph nodes and CTV2 for prostate tumors or prostate tumor beds. In addition, delineation quality and processing time of the artificial intelligence (AI) algorithm were compared with those of a junior oncologist with 3 years of working experience. To further explore the number of patients required for the style adaptation model, to achieve another senior oncologist’s counting style, cases of the style transfer mode were gradually increased, adding ten patients to the training model each time. Results: No significant differences were found for the volumetric dice (VD) coefficients of the two models, CTV1 and CTV2, among DeeplabV3+, Unet++, and 3D U-net (p > 0.05). In the radical radiotherapy model, the VD coefficient of CTV1 calculated by AI, was higher than that of the one delineated by the junior physician (0.85 vs. 0.82, p = 0.018), while the VD coefficients of CTV2 counted by the junior physician and AI were the same (0.84 vs. 0.84, p = 0.958); In the postoperative radiotherapy model, the quantitative parameter of CTV1 and CTV2, counted by AI, was better than that of the junior physician (VD, 0.86 vs 0.83 for CTV1, p = 0.041; 0.79 vs 0.73 for CTV2, p = 0.003, respectively). The median delineation time for AI was 0.23 min in the postoperative model and 0.26 min in the radical model, which were significantly shorter than those of the physician (50.40 min and 45.43 min, respectively, p < 0.001). The correction time of the senior physician for AI was much shorter compared with that of the junior physician in both models (p < 0.001). For style adaptation from one physician to another, approximately 20 cases were required to construct a personal style based on the basic delineation model. Conclusion: Using deep active learning and attention mechanism, a highly consistent and time-saving contouring model was built for CTVs of prostate cancer. It was possible to train the style adaptation mode from one physician’s style to that of another with limited patient samples.
Low-complexity Hybrid Interference Cancellation for Sparse Code Multiple Access
Authors: GHANI Bilal , launay frederic , POUSSET Yannis , PERRINE Clency , CANCES Jean Pierre 
Published: May 2022

Abstract
Sparse code multiple access (SCMA) is one of Non Orthogonal Multiple Access (NOMA) candidate for 5G mobile communications. Multiple overlapped blocks of SCMA code are transmitted per frequency layer which compels the receiver to cancel unwanted SCMA code blocks. Thanks to the sparsity of SCMA, Message Passing Algorithm (MPA) achieves near-optimal performance. Nevertheless process is time-consuming and has a high degree of complexity even if Max-Log algorithm is used. In this paper we propose a Hybrid Interference Cancellation with Log Domain MPA algorithm (HIC-MPA) which uses either hard interference cancellation or soft interference cancellation following by a LDPC decoder. The choice of interference cancellation decoder depends on a threshold value based on power measurements. Results show a significant reduction in terms of complexity as compared to the traditional MPA process for the same values of Bit Error Rate (BER).
Transformer Based on Channel-Spatial Attention for Accurate Classification of Scenes in Remote Sensing Image
Authors: Guo Jingxia , Jia Nan , Zhang Mingxu , Zhang Ru , Li Minhui 
Published: May 2022

Abstract
Recently, the scenes in large datasets of high-resolution remote sensing (HRRS) have been classified using methods based on convolution neural networks (CNNs). These methods are well-suited for spatial feature extraction and can classify images with relatively high accuracy. However, CNNs do not adequately learn the long-distance dependencies between images and features in image processing, but this is necessary for processing HRRS images because the semantic content of the scenes in these images is closely related to their spatial relationship. CNNs also have limitations in solving problems with large intra-class differences and high inter-class similarity. In response to these challenges, in this study we combine the channel-spatial attention (CSA) mechanism with the Vision Transformer method to propose an effective HRRS image scene classification framework using Channel-Spatial Attention Transformers (CSAT). The model extracts the channel and spatial features of HRRS images using CSA and the Multi-Head Self-Attention (MHSA) mechanism in the transformer module. The experimental results show that the CSAT network exhibits superior scene classification performance compared to a selection of state-of-the-art (SOTA) methods.
Optic radiation atrophy in Lewy body disease with visual hallucination on phase difference enhanced magnetic resonance images
Authors: Miyata Mari , Kakeda Shingo , Yoneda Tetsuya , Ide Satoru , Okada Kazumasa , Adachi Hiroaki , Korogi Yukunori 
Published: May 2022

Abstract
Visual hallucinations (VH) occur commonly in Lewy body disease (LBD), including Parkinson’s disease (PD), PD with dementia, and dementia with Lewy bodies. We aimed to use phase difference enhanced imaging (PADRE) to assess structural abnormalities of optic radiation (OR) in patients with Lewy body disease (LBD) concomitant with VH. Firstly, two radiologists reviewed the OR appearances in healthy subjects (HS) on PADRE. Next, based on the OR abnormalities, two reviewers assessed the PADRE images from 18 HS and 38 and 110 patients with LBD, with and without VH, respectively, in a blinded manner. Finally, all patients with LBD without VH were eventually followed up for at least 5 years after magnetic resonance imaging to determine the appearance of VH. The radiologists identified three layers, namely external sagittal stratum, internal sagittal stratum, and tapetum, in OR on the PADRE in HS. Moreover, they were able to consensually define the OR as abnormal when the layers were obscured and the disappearance of the cranial side. The sensitivity/specificity of abnormal OR for each case was 68%/81% (LBD with VH vs. LBD without VH). Furthermore, VH appeared in 12 of the 21 (57%) patients with LBD and abnormal OR during the follow-up period. However, no patients without abnormal OR reported VH. Patients with LBD and VH demonstrated the abnormal OR. This in turn might be a useful marker to distinguish the patients with VH from those without VH and HS. Moreover, it might facilitate predicting the appearance of VH in the following 5 years.
Association of Helicobacter pylori infection with survival outcomes in advanced gastric cancer patients treated with immune checkpoint inhibitors
Authors: Che Hebin , Xiong Qi , Ma Jinxia , Chen Shixue , Wu Huan , Xu Hongli , Hou Baicun 
Published: May 2022

Abstract
Background Accumulating evidence has revealed that the gut microbiota influences the effectiveness of immune checkpoint inhibitors (ICIs) in cancer patients. As a part of the human microbiome, Helicobacter pylori (H. pylori) was reported to be associated with reduced effectiveness of anti-PD1 immunotherapy in patients with non-small-cell lung cancer (NSCLC). Gastric cancer is more closely related to H. pylori, so we conducted a retrospective analysis to verify whether the association of H. pylori and effectiveness is applicable to advanced gastric cancer (AGC) patients. Material and methods AGC patients who had evidence of H. pylori and received anti-PD-1 antibodies were enrolled in the study. The differences in the disease control rate (DCR), overall survival (OS) and progression-free survival (PFS) between the H. pylori-positive group and the negative group were compared. Results A total of 77 patients were included in this study; 34 patients were H. pylori positive, and the prevalence of H. pylori infection was 44.2%. Compared with the H. pylori-negative group, patients in the H. pylori-positive group had a higher risk of nonclinical response to anti-PD-1 antibody, with an OR of 2.91 (95% CI: 1.13-7.50). Patients in the H. pylori-negative group had a longer OS and PFS than those in the positive group, with an estimated median OS of 17.5 months vs. 6.2 months (HR = 2.85, 95% CI: 1.70-4.78; P = 0.021) and a median PFS of 8.4 months vs. 2.7 months (HR=3.11, 95% CI: 1.96-5.07, P=0.008). Multivariate analysis indicated that H. pylori infection was independently associated with PFS (HR=1.90, 95% CI: 1.10-3.30; P=0.022). Conclusion Our study unveils for the first time that H. pylori infection is associated with the outcome of immunotherapy for AGC patients. Multicenter, large sample and prospective clinical studies are needed to verify the association.