bluuebunny/crossref_metadata_2025_split huggingface dataset:
A general framework for analysing the mortality experience of a large portfolio of lives: with an application to the UK universities superannuation scheme
Authors: Cairns Andrew J. G. , Blake David , Dowd Kevin , Coughlan Guy D. , Jones Owen , Rowney Jeffrey 
Published: April 2022

AbstractWe propose a general framework that can be used to analyse the mortality experience of a large portfolio of lives. The objective of the framework is to provide a firm evidence base to support the setting of future mortality assumptions for the portfolio as a whole or subgroup-by-subgroup. The framework is developed in tandem with an analysis of the mortality of pensioners in the Universities Superannuation Scheme (USS), the largest funded pension scheme in the UK and one with a highly educated and very homogeneous membership. The USS experience was compared with English mortality subdivided into deprivation deciles using the Index of Multiple Deprivation (IMD). USS was found to have significantly lower mortality rates than even IMD-10 (the least deprived of the English deciles), but with similar mortality improvement rates to that decile over the period 2005–2016. Higher pensions were found to predict lower mortality, but only weakly so, and only for persons who retired on the first day of a month (mostly from active service). We found that other potential covariates derived from an individual’s post/zip code (geographical region and the IMD associated with their local area) typically had no explanatory power. This lack of dependence is an important conclusion of the USS-specific analysis and contrasts with others that consider the mortality of more heterogeneous scheme memberships. Although the key findings are likely to be particular to USS, we argue that our analytical framework will be useful for other large pension schemes and life annuity providers.
Predictive model for bacterial co-infection in patients hospitalized for COVID-19: a multicenter observational cohort study
Authors: Giannella Maddalena , Rinaldi Matteo , Tesini Giulia , Gallo Mena , Cipriani Veronica , Vatamanu Oana , Campoli Caterina , Toschi Alice , Ferraro Giuseppe , Horna Clara Solera , Bartoletti Michele , Ambretti Simone , Violante Francesco , Viale Pierluigi , Curti Stefania 
Published: April 2022

Abstract
Objective
The aim of our study was to build a predictive model able to stratify the risk of bacterial co-infection at hospitalization in patients with COVID-19.

Methods
Multicenter observational study of adult patients hospitalized from February to December 2020 with confirmed COVID-19 diagnosis. Endpoint was microbiologically documented bacterial co-infection diagnosed within 72 h from hospitalization. The cohort was randomly split into derivation and validation cohort. To investigate risk factors for co-infection univariable and multivariable logistic regression analyses were performed. Predictive risk score was obtained assigning a point value corresponding to β-coefficients to the variables in the multivariable model. ROC analysis in the validation cohort was used to estimate prediction accuracy.

Results
Overall, 1733 patients were analyzed: 61.4% males, median age 69 years (IQR 57–80), median Charlson 3 (IQR 2–6). Co-infection was diagnosed in 110 (6.3%) patients. Empirical antibiotics were started in 64.2 and 59.5% of patients with and without co-infection (p = 0.35). At multivariable analysis in the derivation cohort: WBC ≥ 7.7/mm3, PCT ≥ 0.2 ng/mL, and Charlson index ≥ 5 were risk factors for bacterial co-infection. A point was assigned to each variable obtaining a predictive score ranging from 0 to 5. In the validation cohort, ROC analysis showed AUC of 0.83 (95%CI 0.75–0.90). The optimal cut-point was ≥2 with sensitivity 70.0%, specificity 75.9%, positive predictive value 16.0% and negative predictive value 97.5%. According to individual risk score, patients were classified at low (point 0), intermediate (point 1), and high risk (point ≥ 2). CURB-65 ≥ 2 was further proposed to identify patients at intermediate risk who would benefit from early antibiotic coverage.

Conclusions
Our score may be useful in stratifying bacterial co-infection risk in COVID-19 hospitalized patients, optimizing diagnostic testing and antibiotic use.
Thermal shock of subsurface material with plastic flow during scuffing
Authors: Zhang Chuanwei , Zhai Han , Sun Dong , Zheng Dezhi , Zhao Xiaoli , Gu Le , Wang Liqin 
Published: April 2022

AbstractThe thermal shock of subsurface material with shear instability and severe plastic flow during scuffing was investigated. The scuffing damage of M50 steel was tested using a high-speed rolling—sliding contact test rig, and the transient temperature during scuffing was calculated using the Fourier transform method considering the effects of both frictional heat and plastic work. The results show that a thermal shock with a rapid rise and subsequent rapid decrease in the contact temperature is generated in the subsurface layers. The frictional power intensity generates a high temperature rise, leading to the austenitization of the subsurface material. Consequently, the plastic flow is generated in the subsurface layer under the high shear stress, and the resulting plastic strain energy generates a further temperature increase. Subsequently, a rapid decrease in the contact temperature quenches the material, resulting in clear shear slip bands and retained austenite in the subsurface layers of the M50 steel.
Prävalenz von Muskel-Skelett-Erkrankungen in der Zahnmedizin
Authors: Holzgreve F. , Weis T. , Grams I. , Germann U. , Wanke E. M. 
Published: April 2022

ZusammenfassungDie traditionellen Behandlungspositionen der Zahnärzt/innen hinter, neben und vor dem/r Patienten/in führen zur asymmetrischen Neigung und Verdrehung des Kopfes sowie des Rumpfes. Die Folge können Fehlhaltungen sein, die Muskel-Skelett-Erkrankungen verursachen. Das erklärt wahrscheinlich die hohe Prävalenz bei Zahnärzt/innen und zahnmedizinischen Fachangestellten. Daher werden in dieser Übersicht mögliche Ursachen und Konsequenzen der Prävalenz sowie ergonomische Maßnahmen für diese Berufsgruppen aufgeführt. Zudem erläutern wir ergonomische Empfehlungen für die Sitzhaltung von Zahnärzt/innen auf Basis der vorhandenen Literatur.
Modeling stochastic service time for complex on-demand food delivery
Authors: Zheng Jie , Wang Ling , Wang Shengyao , Chen Jing-fang , Wang Xing , Duan Haining , Liang Yile , Ding Xuetao 
Published: April 2022

AbstractUncertainty is everywhere in the food delivery process, which significantly influences decision-making for complex on-demand food delivery problems, affecting delivery efficiency and customer satisfaction. Especially, the service time is an indispensable part of the delivery process impacted by various uncertain factors. Due to the simplicity and high accuracy requirement, we model the uncertain service time as a Gaussian mixture model (GMM). In detail, we transform the distribution estimation problem into a clustering problem by determining the probability of each data belonging to each component (each cluster as well). A hybrid estimation of distribution algorithm is proposed to intelligently solve the clustering problem with the criterion to optimize quality and simplicity simultaneously. First, to optimize the simplicity, problem-specific encoding and decoding methods are designed. Second, to generate initial solutions with good clustering results, a Chinese restaurant process-based initialization mechanism is presented. Third, a weighted-learning mechanism is proposed to effectively guide the update of the probability model. Fourth, a local intensification based on maximum likelihood is used to exploit better solutions. The effect of critical parameters on the performances of the proposed algorithm is investigated by the Taguchi design of the experimental method. To demonstrate the effectiveness of the proposed algorithm, we carry out extensive offline experiments on real-world historical data. Besides, we employ the GMMs obtained by our algorithm in a real-world on-demand food delivery platform, Meituan, to assist decision-making for order dispatching. The results of rigorous online A/B tests verify the practical value of introducing the uncertainty model into the real-life application.
New extension of ordinal priority approach for multiple attribute decision-making problems: design and analysis
Authors: Abdel-Basset Mohamed , Mohamed Mai , Abdel-monem Ahmed , Elfattah Mohamed Abd 
Published: April 2022

AbstractThe selection and assessment process of appropriate robots became a more complex and complicated task due to various available alternatives and conflicting attributes which must take into consideration. Also, uncertainty which exists usually in the selection process is an unavoidable component that needs to be thoughtfully measured and traditional multi-attribute decision-making approaches failed to deal precisely with it. Since almost all decisions originate from subjective ordinal preferences, handling uncertainty using linguistic variables is also not enough. Thus, the objective of the current study is to present a new extended ordinal priority approach in the neutrosophic environment for the first time to select an appropriate robot. Since neutrosophic is one of the most effective and accommodating tools for handling uncertainty, thus, this method goes to transform linguistic information into triangular neutrosophic numbers using a new presented scale. This scale was used to determine the importance degree of attributes and alternatives regarding experts' opinions. Also, the score function of the triangular neutrosophic number is used for prioritizing attributes and alternatives. The experts in our proposed method have the same degree of importance, since each expert is a person with special skills and knowledge representing mastery of a particular subject. To measure the applicability and efficiency of the proposed approach, an experimental case study has been established for the robot selection problem of a new pharmaceutical city in Egypt for the first time. The source of data in this case study is experts, interviews, and questionnaires. Also, sensitivity and comparative analysis are further made for verifying the power of the proposed approach. The outcome of this study shows that the suggested approach for robot selection is quite helpful and has a great performance under uncertainty over classical and fuzzy ordinal priority approaches. Also, the suggested approach is less consumption of time and simpler than the fuzzy ordinal priority approach. Therefore, we recommend firms and governments to apply it for increasing product quality, hence the profitability of manufacturing industries and decrease needless costs.
A New Dimensionality-Unbiased Score for Efficient and Effective Outlying Aspect Mining
Authors: Samariya Durgesh , Ma Jiangang 
Published: April 2022

AbstractThe main aim of the outlying aspect mining algorithm is to automatically detect the subspace(s) (a.k.a. aspect(s)), where a given data point is dramatically different than the rest of the data in each of those subspace(s) (aspect(s)). To rank the subspaces for a given data point, a scoring measure is required to compute the outlying degree of the given data in each subspace. In this paper, we introduce a new measure to compute outlying degree, called Simple Isolation score using Nearest Neighbor Ensemble (SiNNE), which not only detects the outliers but also provides an explanation on why the selected point is an outlier. SiNNE is a dimensionally unbias measure in its raw form, which means the scores produced by SiNNE are compared directly with subspaces having different dimensions. Thus, it does not require any normalization to make the score unbiased. Our experimental results on synthetic and publicly available real-world datasets revealed that (i) SiNNE produces better or at least the same results as existing scores. (ii) It improves the run time of the existing outlying aspect mining algorithm based on beam search by at least two orders of magnitude. SiNNE allows the existing outlying aspect mining algorithm to run in datasets with hundreds of thousands of instances and thousands of dimensions which was not possible before.
Skill of the Saudi-KAU CGCM in Forecasting ENSO and its Comparison with NMME and C3S Models
Authors: Almazroui Mansour , Ehsan Muhammad Azhar , Tippett Michael K. , Ismail Muhammad , Islam M. Nazrul , Camargo Suzana J. , Abid Muhammad Adnan , O’Brien Enda , Kamil Shahzad , Robertson Andrew W. , Singh Bohar , Hussein Mahmoud , Omar Vale Mohamed , Yousef Ahmed Elsayed 
Published: April 2022

AbstractThis paper assesses the skill of the Saudi-King Abdulaziz University coupled ocean–atmosphere Global Climate Model, namely Saudi-KAU CGCM, in forecasting the El Niño-Southern Oscillation (ENSO)-related sea surface temperature. The model performance is evaluated based on a reforecast of 38 years from 1982 to 2019, with 20 ensemble members of 12-month integrations. The analysis is executed on ensemble mean data separately for boreal winter (December to February: DJF), spring (March to May: MAM), summer (June to August: JJA), and autumn (September to November: SON) seasons. It is found that the Saudi-KAU model mimics the observed climatological pattern and variability of the SST in the tropical Pacific region. A cold bias of about 0.5–1.0 °C is noted in the ENSO region during all seasons at 1-month lead times. A statistically significant positive correlation coefficient is observed for the predicted SST anomalies in the tropical Pacific Ocean that lasts out to 6 months. Across varying times of the year and lead times, the model shows higher skill for autumn and winter target seasons than for spring or summer ones. The skill of the Saudi-KAU model in predicting Niño 3.4 index is comparable to that of state-of-the-art models available in the Copernicus Climate Change Service (C3S) and North American Multi-Model Ensemble (NMME) projects. The ENSO skill demonstrated in this study is potentially useful for regional climate services providing early warning for precipitation and temperature variations on sub-seasonal to seasonal time scales.
Inter-Firm Inventor Collaboration and Path-Breaking Innovation: Evidence From Inventor Teams Post-Merger
Authors: Li Kai , Wang Jin 
Published: April 2022

AbstractUsing a large and novel data set over the period of 1976 to 2019 tracking inventors’ career paths following mergers and acquisitions, we show that collaboration between acquirer and target inventors post-merger is associated with more path-breaking patents than those filed by either acquirer or target inventor-only teams. We further show that such collaboration is more important in improving acquirers’ innovation capabilities than hiring target inventors and knowledge spillovers. Finally, we show that recombining tacit knowledge embodied in the human capital of acquirer and target inventors is likely the mechanism. We conclude that inter-firm inventor collaboration is one key means for achieving synergies.
The contribution of Antarctic moss peat to the understanding of global peatland processes
Authors: Fenton James H.C. 
Published: April 2022

AbstractThe moss banks of the Maritime Antarctic composed of one or both of the mosses Chorisodontium aciphyllum and Polytrichum strictum form peat banks up to 3.4 m thick and 5500 years of age. They represent perhaps the simplest peat-forming systems in the world, so studying their dynamics can help in the understanding of peatland dynamics generally, particularly those of temperate blanket peat. They can provide insights into how the balance of growth, decomposition and compaction of peat results in peat formation, how downhill creep can be the cause of both vertical edges and the creation of patterned bogs and how erosion of peat can be a natural process.
On the discovery and interpretation of overcounting in Orkhon Inscriptions
Authors: He Chuansheng 
Published: April 2022

AbstractThe discovery of overcounting in Orkhon Inscriptions has been an important contribution by historical comparative linguistics during the nineteenth century. However, the initial interpretation of overcounted numerals in Orkhon Inscriptions by Thomsen and Radloff was not correct, resulting in serious difficulties in reconstructing old Turkic history. It was Bang and Marquart who worked out the true semantics of overcounted numerals. This article aims to present a historical overview on the discovery and interpretation of overcounted numerals in Orkhon Inscriptions. Considering that Bang and Marquart did not explicitly spell out their evidence for reaching the true semantics of these numerals, this article presents a series of arguments proving the existence of overcounting in Old Turkic based on language per se, historical facts, logical reasoning, and bilingual translation.
Evaluating the Age Distribution of Exposed Crust in the Acasta Gneiss Complex Using Detrital Zircons in Pleistocene Eskers
Authors: Bilak Grayson S. , Niemetz Kaylyn , Reimink Jesse R. , Reyes Alberto V. , Chacko Thomas , DuFrane S. Andrew , Belosevic Michael , Ketchum John W. F. 
Published: April 2022

AbstractThe Acasta Gneiss Complex (AGC) is a ∼2,400 km2 Hadean‐Mesoarchean terrane that contains the oldest known zircon‐bearing rocks on Earth. Despite its importance for early Earth geology, only a small fraction (∼50 km2) of the AGC has been mapped in detail. We use detrital zircon grains from late Pleistocene eskers that transect the Complex to approximate the lateral extent and relative proportions of diverse‐aged ancient rock units within the vast, little‐studied parts of the AGC. The esker sediment was derived from glacially eroded bedrock and therefore zircon grains can serve as a proxy for the ages of exposed bedrock in the study area. U‐Pb dates on ∼2400 detrital zircons from coarse and fine grain‐size fractions along the esker transect yield age distributions that coincide with ages of regionally mapped AGC bedrock, the adjacent Wopmay Orogen, and granitoids of the Slave craton. Based on detrital zircon age distributions and new reconnaissance‐scale mapping, we infer that 3.37 Ga granitoids are a volumetrically significant component of the unmapped AGC. Esker zircons older than 3.7 Ga are present in most esker samples but at low abundance, which suggests that Eoarchean and Hadean rocks are a volumetrically subordinate component of the AGC. However, the data also suggest that unmapped rocks at least as old as 3.95 Ga are present toward the inferred eastern limit of the AGC, a location where Eoarchean rocks have not been recognized previously.
MiRNA-363-3p/DUSP10/JNK axis mediates chemoresistance by enhancing DNA damage repair in diffuse large B-cell lymphoma
Authors: Zhou Wenping , Xu Yuanlin , Zhang Jiuyang , Zhang Peipei , Yao Zhihua , Yan Zheng , Wang Haiying , Chu Junfeng , Yao Shuna , Zhao Shuang , Yang Shujun , Guo Yongjun , Miao Jinxin , Liu Kangdong , Chan Wing C. , Xia Qingxin , Liu Yanyan 
Published: April 2022

AbstractAnthracycline-based chemotherapy resistance represents a major challenge in diffuse large B-cell lymphoma (DLBCL). MiRNA and gene expression profiles (n = 47) were determined to uncover potential chemoresistance mechanisms and therapeutic approaches. An independent correlation between high expression of miRNA-363-3p and chemoresistance was observed and validated in a larger cohort (n = 106). MiRNA-363-3p was shown to reduce doxorubicin-induced apoptosis and tumor shrinkage in in vitro and in vivo experiments by ectopic expression and CRISPR/Cas9-mediated knockout in DLBCL cell lines. DNA methylation was found to participate in transcriptional regulation of miRNA-363-3p. Further investigation revealed that dual specificity phosphatase 10 (DUSP10) is a target of miRNA-363-3p and its suppression promotes the phosphorylation of c-Jun N-terminal kinase (JNK). The miRNA-363-3p/DUSP10/JNK axis was predominantly associated with negative regulation of homologous recombination (HR) and DNA repair pathways. Ectopic expression of miRNA-363-3p more effectively repaired doxorubicin-induced double-strand break (DSB) while enhancing non-homologous end joining repair and reducing HR repair. Targeting JNK and poly (ADP-ribose) polymerase 1 significantly inhibited doxorubicin-induced DSB repair, increased doxorubicin-induced cell apoptosis and tumor shrinkage, and improved the survival of tumor-bearing mice. In conclusion, the miRNA-363-3p/DUSP10/JNK axis is a novel chemoresistance mechanism in DLBCL that may be reversed by targeted therapy.
A nanotheranostic agent based on Nd3+-doped YVO4 with blood-brain-barrier permeability for NIR-II fluorescence imaging/magnetic resonance imaging and boosted sonodynamic therapy of orthotopic glioma
Authors: Lv Zhijia , Jin Longhai , Cao Yue , Zhang Hao , Xue Dongzhi , Yin Na , Zhang Tianqi , Wang Yinghui , Liu Jianhua , Liu Xiaogang , Zhang Hongjie 
Published: April 2022

AbstractThe specific diagnosis and treatment of gliomas is a primary challenge in clinic due to their high invasiveness and blood-brain barrier (BBB) obstruction. It is highly desirable to find a multifunctional agent with good BBB penetration for precise theranostics. Herein, we design and construct a core-shell structured nanotheranostic agent (YVO4:Nd3+-HMME@MnO2-LF, marked as YHM) with YVO4:Nd3+particles as the core and MnO2nanosheets as the shell. Sonosensitizer hematoporphyrinmonomethyl ether (HMME) and lactoferrin (LF) were further loaded and modified on the surface, giving it a good ability to cross the BBB, near-infrared fluorescence imaging in the second window (NIR-II)/magnetic resonance imaging (MRI) bimodality, and highly efficient sonodynamic therapy (SDT) of orthotopic gliomas. The YVO4:Nd3+(25%) core exhibited good NIR-II fluorescence properties, enabling YHM to act as promising probes for NIR-II fluorescence imaging of vessels and orthotopic gliomas. MnO2shell can not only provide O2in the tumor microenvironments (TME) to significantly improve the healing efficacy of SDT, but also release Mn2+ions to achieve T1-weight MRI in situ. Non-invasive SDT can effectively restrain tumor growth. This work not only demonstrates that multifunctional YHM is promising for diagnosis and treatment of orthotopic glioma, but also provides insights into exploring the theranostic agents based on rare earth-doped yttrium vanadate nanoparticles.
Self-frequency-conversion nanowire lasers
Authors: Yi Ruixuan , Zhang Xutao , Li Chen , Zhao Bijun , Wang Jing , Li Zhiwen , Gan Xuetao , Li Li , Li Ziyuan , Zhang Fanlu , Fang Liang , Wang Naiyin , Chen Pingping , Lu Wei , Fu Lan , Zhao Jianlin , Tan Hark Hoe , Jagadish Chennupati 
Published: April 2022

AbstractSemiconductor nanowires (NWs) could simultaneously provide gain medium and optical cavity for performing nanoscale lasers with easy integration, ultracompact footprint, and low energy consumption. Here, we report III–V semiconductor NW lasers can also be used for self-frequency conversion to extend their output wavelengths, as a result of their non-centrosymmetric crystal structure and strongly localized optical field in the NWs. From a GaAs/In0.16Ga0.84As core/shell NW lasing at 1016 nm, an extra visible laser output at 508 nm is obtained via the process of second-harmonic generation, as confirmed by the far-field polarization dependence measurements and numerical modeling. From another NW laser with a larger diameter which supports multiple fundamental lasing wavelengths, multiple self-frequency-conversion lasing modes are observed due to second-harmonic generation and sum-frequency generation. The demonstrated self-frequency conversion of NW lasers opens an avenue for extending the working wavelengths of nanoscale lasers, even to the deep ultraviolet and THz range.