bluuebunny/crossref_metadata_2025_split huggingface dataset:
γ‐Valerolactone/H2O‐ Derived Facile Preparation of Lignin‐Based AgNPs to Full Utilization of Lignocellulosic Biomass
Authors: Li Shengren , Xue Yuyuan , Hao Baolin , Yang Taowei , Zhang Yan , Shen Qi 
Published: June 2022

AbstractLignin‐based functional material has become an important way to realize the high‐value utilization of lignin. However, the unstable performance limited its practical application, resulting from the inherent heterogeneity and uncertain extraction process of lignin. Here, a coupling process of the preparation of lignin‐based silver nanoparticles (AgNPs) and carbohydrate refining was presented to realize the facile and stable preparation of AgNPs from lignocellulose, of which γ‐Valerolactone (GVL)/H2O was used both as the extraction solvent of lignin and the catalyst for AgNPs synthesis in Ag2O/lignin system. The reaction rules and behaviors of AgNPs were systematically studied. Meanwhile, the separation rate of hemicellulose could exceed 90 % and a high‐purity cellulose of 95.12 % was obtained. The enzymatic hydrolysis efficiency of residual cellulose from corncob was close to 71 %. The reliability of different biomass sources was also verified. This work provided a potential solution for improving the economic benefits of lignocellulose refining.
Dual Proton Conducting Channels Constructed by Acid‐Base Double‐Shell Carbon Nanotubes to Boost the Proton Conductivity of SPEEK
Authors: Yang Mengjie , Rong Jianxin , Xia Minglong , Wang Shuo , Feng Yi , Ding Huili 
Published: June 2022

AbstractSulfonated poly(ether ether ketone) (SPEEK) has been widely investigated as a substitution of commercial Nafion as proton exchange membranes (PEMs). However, the disadvantages such as shrinkage of proton transfer channels at high temperature and low humidity conditions cannot be neglected. In this manuscript, the carboxyl and imidazole double‐shelled carbon nanotubes(CNTs−C@N) was incorporated into the SPEEK matrix to fabricate composite PEM (denoted as SPEEK/CNTs−C@N−Y, Y is the percentage composition of CNTs−C@N), serving as one‐dimensional fillers. SPEEK/CNTs−C@N‐1.0 composite membrane performed a higher horizontal proton conductivity (0.302 S/cm) under 80 °C and 100 % relative humidity (RH) compared with original SPEEK membrane 0.181 S/cm. The high proton conductivity could be mainly attributed to the dual proton conducting channel formed by two types of acid‐base pairs, which immensely promote the Grotthuss mechanism. Therefore, SPEEK/CNTs−C@N composite membranes are expected to develop PEMs with high proton conductivity at high temperature and low humidity.
Bismuth, a Previously Less‐studied Element, Is Bursting into New Hotspots
Authors: Xin Yanmei , Wang Zhuo , Yao Congfei , Shen Haocheng , Miao Yuqing 
Published: June 2022

AbstractBismuth (Bi) is a particular element with many distinctive properties such as low toxicity or nontoxicity, high specific gravity, photoluminescence, photoelectronic and photovoltaic effects, strong oxidation ability, water insolubility, etc. These distinctive properties help to boost various applications of Bi. The recent decades have witnessed a dramatic increase in the application research of Bi‐based materials, especially on photocatalysis. This paper begins with an introduction to the history of Bi, followed by a summary of its distinctive properties, and then provides a comprehensive overview of its applications in photocatalysis, sensing, medicine, and diagnosis and treatments, with a particular focus on near‐infrared photocatalysis, flexible wearable sensor, in vivo detection and therapeutics. Finally, the main challenges and development prospects of the Bi‐based materials are introduced. With the development trends of Bi research discussed, this paper is aimed at improving the knowledge of Bi and arising the research interest of Bi in the hope of extending the applications of Bi.
Interface Engineering to Boost Thermal Safety of Microsized Silicon Anodes in Lithium‐Ion Batteries
Authors: Liu Qing , Meng Tao , Yu Le , Guo Songtao , Hu Yunhuan , Liu Zhifang , Hu Xianluo 
Published: June 2022

AbstractBattery safety is vital to the application of lithium‐ion batteries (LIBs), especially for high energy density cells applied in electric vehicles. As an anode material with high theoretical capacity and natural abundance, Si has received extensive attention for LIBs. However, it suffers from severe electrode pulverization during cycling due to large volume changes and an unstable solid electrolyte interphase (SEI), resulting in accelerated capacity fading and even safety hazards. Therefore, safe and long‐term cycling of Si‐based anodes, especially under high‐temperature cycling, is highly challenging for state‐of‐the‐art high‐energy LIBs. The thermal behavior of SEI is crucial for a high safety battery as the decomposition of SEI is the first step in thermal runaway. Here, highly reversible and thermotolerant microsized Si anodes for safe LIBs are demonstrated. Comprehensive electrochemical/mechanical/thermochemical behaviors of the SEI are systematically investigated. The rational design of robust SEI endows the Si‐based cells with long‐term durability at elevated temperatures and superior thermal safety. This work paves the way for designing industrial‐scale, low‐cost, microsized Si anodes with applications in next‐generation LIBs with high energy densities and high safety.
The role of satisfaction in labor diaspora dynamics: An analysis of BREXIT effects
Authors: Elo Maria , Silva Susana C. , Vlačić Božidar 
Published: June 2022

AbstractIn diaspora research, people's international mobility is often understood as a response to pull‐push forces on an economic macro‐level or as part of diasporic waves. However, labor diaspora formations are also influenced by micro‐level (i.e., individual perceptions) drivers related to work per se, such as satisfaction. This explorative qualitative study takes a novel angle and focuses on the role of Portuguese nurses’ satisfaction with the evaluation of the Brexit scenario and its effects on this labor diaspora's mobility and stability. The findings illustrate that satisfaction, although affected by uncertainty, mainly relates to perceived working conditions and legislation and the possibilities to communicate with locals and other diasporans. This paper provides suggestions for future research and contributes to the development of theory on staying and human stickiness, explaining the dynamics of exit and entry in (re‐)migration decision making.
Superior results of return to sport after double-bundle versus single-bundle anterior cruciate ligament reconstruction in young active patients
Authors: Qin Liang , You Hongbo , Qi Jun , Ren Ye , Cheng Peng , Liang Shuang , Wang Jiang 
Published: June 2022

Abstract
Purpose
To compare return to sport and clinical results in young active patients who underwent anatomic single-bundle (SB) versus double-bundle (DB) anterior cruciate ligament reconstruction (ACLR).

Methods
Young active patients undergoing SB or DB ACLR from 2017 to 2019 at our institution were retrospectively reviewed. The primary outcome measures were the rate and time to return to sports, with secondary measures including the Lachman test, pivot shift test, Lysholm scores, International Knee Documentation Committee (IKDC) scores and graft rupture.

Results
The study included a total of 90 patients (DB group, 42; SB group, 48), with a mean follow-up of 27.1 ± 6.1 months. Young active patients who underwent DB ACLR had a higher rate of return to pivoting sports than those who underwent SB ACLR (HR = 2.4; 95% confidence interval [CI]: 1.4, 4.1; p = 0.013). The DB group returned to pivoting sports at a mean ± SD of 11.0 ± 2.9 months compared with 12.7 ± 2.7 months in the SB group (p = 0.01). There was one traumatic failure in the SB group and one contralateral ACL rupture in the DB group. There was no significant difference in the rate and time to return to running, Lachman test, pivot-shift test, Lysholm or IKDC scores in either group.

Conclusion
Both anatomical SB and DB techniques achieved satisfactory clinical outcomes. DB techniques led to superior performance of return to pivoting sports but nonsignificant differences in time and rate of return to running, passive stability measurement, subjective knee function outcome and graft rupture rate in both groups at the 2-year follow-up. The DB ACLR should be considered a viable option to treat young patients with high activity demands.

Level of evidence
III.
An effective restriction theorem via wall-crossing and Mercat’s conjecture
Authors: Feyzbakhsh Soheyla 
Published: June 2022

AbstractWe prove an effective restriction theorem for stable vector bundlesEon a smooth projective variety:$$E|_D$$E|Dis (semi)stable for all irreducible divisors$$D \in |kH|$$D∈|kH|for allkgreater than an explicit constant. As an application, we show that Mercat’s conjecture in any rank greater than 2 fails for curves lying on K3 surfaces. Our technique is to use wall-crossing with respect to (weak) Bridgeland stability conditions which we also use to reprove Camere’s result on slope stability of the tangent bundle of$${\mathbb {P}}^n$$Pnrestricted to a K3 surface.
Bedingungen einer neuen ökologischen Industriepolitik
Authors: Praetorius Barbara , Dierker Wolfgang 
Published: June 2022

ZusammenfassungZur Erreichung der globalen Klimaziele ist eine drastische Emissionsminderung in allen Sektoren wie Energiewirtschaft, Gebäude, Verkehr und Landwirtschaft notwendig. Zudem spielt die Industrie hierbei eine zentrale Rolle. Neben der Emissionsminderung in der eigenen Produktion hat die Industrie die Aufgabe, klimaneutrale Produkte und emissionsfreie Produktionsverfahren hervorzubringen. Mit Hilfe einer neuen ökologischen Industriepolitik soll die Umgestaltung der Wirtschaft hin zur Klimaneutralität gelingen.
Multiple kernel-based anchor graph coupled low-rank tensor learning for incomplete multi-view clustering
Authors: Wang Senhong , Cao Jiangzhong , Lei Fangyuan , Jiang Jianjian , Dai Qingyun , Ling Bingo Wing-Kuen 
Published: June 2022

AbstractIncomplete Multi-View Clustering (IMVC) attempts to give an optimal clustering solution for incomplete multi-view data that suffer from missing instances in certain views. However, most existing IMVC methods still have various drawbacks in practical applications, such as arbitrary incomplete scenarios cannot be handled; the computational cost is relatively high; most valuable nonlinear relations among samples are often ignored; complementary information among views is not sufficiently exploited. To address the above issues, in this paper, we present a novel and flexible unified graph learning framework, called Multiple Kernel-based Anchor Graph coupled low-rank Tensor learning for Incomplete Multi-View Clustering (MKAGT_IMVC), whose goal is to adaptively learn the optimal unified similarity matrix from all incomplete views. Specifically, according to the characteristics of incomplete multi-view data, MKAGT_IMVC innovatively improves an anchor selection strategy. Then, a novel cross-view anchor graph fusion mechanism is introduced to construct multiple fused complete anchor graphs, which captures more the intra-view and inter-view nonlinear relations. Moreover, a graph learning model combining low-rank tensor constraint and consensus graph constraint is developed, where all fused complete anchor graphs are regarded as prior knowledge to initialize this model. Extensive experiments conducted on eight incomplete multi-view datasets clearly show that our method delivers superior performance relative to some state-of-the-art methods in terms of clustering ability and time-consuming.
Statistical Analysis in the German National Cohort (NAKO) – Specific Aspects and General Recommendations
Authors: Kuss Oliver , Becher Heiko , Wienke Andreas , Ittermann Till , Ostrzinski Stefan , Schipf Sabine , Schmidt Carsten O , Leitzmann Michael , Pischon Tobias , Krist Lilian , Roll Stephanie , Sand Matthias , Pohlabeln Hermann , Rach Stefan , Jöckel Karl-Heinz , Stang Andreas , Mueller Ulrich A , Werdecker Andrea , Westerman Ronny , Greiser Karin H , Michels Karin B 
Published: June 2022

AbstractThe German National Cohort (NAKO) is an ongoing, prospective multicenter cohort study, which started recruitment in 2014 and includes more than 205,000 women and men aged 19–74 years. The study data will be available to the global research community for analyses. Although the ultimate decision about the analytic methods will be made by the respective investigator, in this paper we provide the basis for a harmonized approach to the statistical analyses in the NAKO. We discuss specific aspects of the study (e.g., data collection, weighting to account for the sampling design), but also give general recommendations which may apply to other large cohort studies as well.
Informing environmental health and risk priorities through local outreach and extension
Authors: Grieger Khara , Cummings Christopher L. 
Published: June 2022

AbstractOur society is currently facing an unprecedented number of environmental and societal challenges. Stakeholder and community engagement can help identify priority issues and needs at local levels. One approach to engage stakeholders and communities in the contexts of environmental, health, and societal challenges is to leverage outreach and extension programs. Within this context, and to help identify priority issues to focus subsequent research and extension programs in North Carolina (NC), a survey was conducted with extension agents to identify priority issues as they relate to environmental health and risks and related needs. Based on responses from 66 study participants that represented half of the 100 NC counties, we found that Water pollution, Flooding, Natural resources management, and Engaging stakeholders were top priority issues across all environmental health and risk topics. Participants also identified that practices of Engaging stakeholders as well as Assessing, Managing, and Communicating risks were increasingly important. Participants indicated they needed a moderate-to-significant amount of guidance across a range of areas related to assessing, managing, communicating, and making decisions regarding environmental health and risk topics, as well as engaging with local communities. Outcomes from this work can not only help inform subsequent research and outreach efforts at local scales, but this work demonstrates a simple, low-cost approach to elicit perspectives and priorities can be leveraged in other states and regions with established stakeholder and community outreach programs more broadly.
Multiple Treatment Modeling for Target Marketing Campaigns: A Large-Scale Benchmark Study
Authors: Gubela Robin M. , Lessmann Stefan , Stöcker Björn 
Published: June 2022

AbstractMachine learning and artificial intelligence (ML/AI) promise higher degrees of personalization and enhanced efficiency in marketing communication. The paper focuses on causal ML/AI models for campaign targeting. Such models estimate the change in customer behavior due to a marketing action known as the individual treatment effect (ITE) or uplift. ITE estimates capture the value of a marketing action when applied to a specific customer and facilitate effective and efficient targeting. We consolidate uplift models for multiple treatments and continuous outcomes and perform a benchmarking study to demonstrate their potential to target promotional monetary campaigns. In this use case, the new models facilitate selecting the optimal discount amount to offer to a customer. Large-scale analysis based on eight marketing data sets from leading B2C retailers confirms the significant gains in the campaign return on marketing when using the new models compared to relevant model benchmarks and conventional marketing practices.
Complications and Healthcare Consumption of Pregnant Women with a Migrant Background: Could There be an Association with Psychological Distress?
Authors: Heller Hanna M. , de Vries Annemijn V. R. , Hoogendoorn Adriaan W. , Scheele Fedde , Kop Willem J. , de Groot Christianne J. M. , Honig Adriaan , Broekman Birit F. P. 
Published: June 2022

Abstract
Objective
Previous studies reported less prenatal healthcare consumption and more perinatal complications in women with a migrant background. Hence, we investigated in a country with free healthcare access whether women with a migrant background differed with respect to pregnancy complications, healthcare consumption and in terms of associations with psychological distress in comparison to native Dutch.

Methods
We included 324 native Dutch and 303 women with a migrant background, who visited two hospitals in Amsterdam for antenatal care between 2014 and 2015. Participants completed the Edinburgh Postnatal Depression Scale, the Hospital Depression and Anxiety Scale, and sociodemographic questions. Complications and healthcare consumption during pregnancy were extracted from medical records. Regression analyses were used with adjustment for covariates.

Results
Except for gestational diabetes [adjusted OR = 3.09; 95% CI = (1.51, 6.32)], no differences were found between groups in perinatal complications [OR = 1.15; 95% CI = (0.80, 1.64)], nor in healthcare consumption [OR = 0.87; 95% CI = (0.63, 1.19)].
Women with a migrant background reported more depressive symptoms [Cohen’s d = 0.25; 95% CI = (0.10, 0.41)], even after adjustment for socio-economic factors. Psychological distress was associated with more hospital admissions during pregnancy. When experiencing depressive symptoms, women with a migrant background had an increased risk to be admitted [OR = 1.11; 95% CI = (1.01, 1.21)].

Conclusions for Practice
This cohort study found no differences in pregnancy-related complications, except for diabetes, nor different healthcare consumption, in women with a migrant background versus native Dutch, in a country with free health care access. However, women with a migrant background experienced more depressive symptoms, and when depressed their risk for hospital admission increased. Additional research is warranted to improve healthcare for this population.
Detection of two poleroviruses infecting garlic (Allium sativum) in Australia
Authors: Nurulita Sari , Geering Andrew D. W. , Crew Kathleen S. , Harper Stephen M. , Thomas John E. 
Published: June 2022

AbstractTwo near complete polerovirus genomes were assembled using high throughput sequencing (HTS) data from two separate samples of garlic cultivar ‘Glenlarge’ grown in Gatton, Queensland, Australia. Whole genome sequence comparisons showed that one contig shared 96.7% nucleotide identity with phasey bean mild yellows virus (MT966032.1) and the other, 99.8% nucleotide identity with turnip yellows virus (MT586581.1). Phylogenetic analyses further revealed that the isolates fell within the PBMYV group 2 and TuYV group 2 clades, respectively. This is the first report of these poleroviruses infecting garlic.
The role of eating disorders features, psychopathology, and defense mechanisms in the comprehension of orthorexic tendencies
Authors: Costanzo Giulia , Marchetti Daniela , Manna Giovanna , Verrocchio Maria Cristina , Falgares Giorgio 
Published: June 2022

Abstract
Purpose
Recent studies pointed out the importance to distinguish orthorexia nervosa (ON) from non-problematic forms of interest with healthy eating. This distinction needs to be further explored since it may favor a better comprehension of the relationship between orthorexic behaviors and psychopathology and lead to an improved understanding of the psychological processes implicated in ON. Therefore, the aim of the current study was to investigate the associations between ON and the core features of eating disorders (EDs), psychopathological symptoms and defense mechanisms, by differentiating three groups of individuals: an ON symptoms group, a healthy-eating control group, and a normal-eating control group.

Methods
College students (n = 270, Mage = 21.57, SD = 2.16) were recruited from Palermo’s University, in the south of Italy, and were assigned to three groups: 52 in the ON symptoms group, 157 in the healthy-eating control group and 61 in the normal-eating control group. Participants completed four questionnaires assessing ON (EHQ-21), eating psychopathology (EDI-3), psychopathological symptoms (BSI) and defense mechanisms (DSQ-40).

Results
Compared to the control groups, the ON symptoms group reported greater EDs’ features, higher psychopathological symptoms and greater employment of different neurotic and immature defense mechanisms. No differences were found between groups with regard to obsessive–compulsive symptoms.

Conclusion
Our findings support the notion that ON behaviors should be carefully distinguished from non-problematic forms of interest with healthy eating. Indeed, results suggest that ON individuals are characterized by similar clinical features and defensive functioning as those observed in traditional EDs, indicating the importance of deepening our understanding of the relationship between these conditions.

Level of evidence
Level V, descriptive cross-sectional study.
AttenSy-SNER: software knowledge entity extraction with syntactic features and semantic augmentation information
Authors: Tang Mingjing , Li Tong , Gao Wei , Xia Yu 
Published: June 2022

AbstractSoftware knowledge community contains a large scale of software knowledge entity information, complex structure and rich semantic correlations. It is significant to recognize and extract software knowledge entity from software knowledge community, as it has great impact on entity-centric tasks such as software knowledge graph construction, software document generation and expert recommendation. Since the texts of the software knowledge community are unstructured by user-generated texts, it is difficult to apply the traditional entity extraction method in the domain of the software knowledge community due to the problems of entity variation, entity sparsity, entity ambiguity, out-of-vocabulary (OOV) words and the lack of annotated data sets. This paper proposes a novel software knowledge entity extraction model, named AttenSy-SNER, which integrates syntactic features and semantic augmentation information, to extract fine-grained software knowledge entities from unstructured user-generated content. The input representation layer utilizes Bidirectional Encoder Representations from Transformers (BERT) model to extract the feature representation of the input sequence. The contextual coding layer leverages the Bidirectional Long Short-Term Memory (BiLSTM) network and Graph Convolutional Network (GCN) for contextual information and syntactic dependency information, and a semantic augmentation strategy based on attention mechanism is introduced to enrich the semantic feature representation of sequences as well. The tag decoding layer leverages Conditional Random Fields (CRF) to solve the dependency between the output tags and obtain the global optimal label sequence. The results of model comparison experiments show that the proposed model has better performance than the benchmark model in software engineering domain.