bluuebunny/crossref_metadata_2025_split huggingface dataset:
Association between opioid therapy trajectories and potential opioid‐related adverse health events
Authors: Hayes Corey J. , Koonce Ruston M. , Gressler Laura Elisabeth , Hu Bo , Williams James Silas , Martin Bradley C. 
Published: June 2022

AbstractPurposeWe identified associations between membership in seven group‐based trajectories based on supply of filled opioid prescriptions and potential opioid‐related adverse health events over a 720‐day window.MethodsWe identified two veteran cohorts with chronic non‐cancer pain who initiated treatment with long‐term opioid therapy between 2008 and 2015, excluding those with prior substance use disorder (n = 373 941) or non‐SUD, opioid‐related adverse outcome (n = 405 631) diagnoses. Outcomes of interest included opioid use disorder, non‐opioid drug use disorder, and alcohol use disorder for the first cohort; or accidents resulting in wounds or injuries, self‐inflicted injuries, opioid‐related accidents and overdoses, alcohol and non‐opioid drug‐related accidents and overdoses, and violence‐related injuries for the second cohort. Using a cross‐sectional design, Veterans were followed until the specific outcome of interest was diagnosed, they died, the study ended, or they were lost to follow up. Accelerated failure time models were estimated for each outcome.ResultsMembership in persistent moderate days covered and persistent modest days covered trajectories was associated with decreased risk of opioid use disorder (Moderate: θ = 0.59, 95%CI:0.54, 0.64; Modest: θ = 0.54, 95%CI:0.50, 0.59) and opioid overdose (Moderate: θ = 0.67,95%CI: 0.57, 0.79; Modest: θ = 0.72, 95%CI:0.61, 0.85) versus higher‐utilizing persistent users. Rapid discontinuation was associated with decreased risk of opioid use disorder (θ = 0.86, 95% CI:0.77, 0.95) and opioid overdose (θ = 0.54, 95%CI:0.41, 0.71), but increased risk of alcohol use disorder (θ = 1.07, 95%CI:1.00, 1.15) and other substance use disorders. Delayed discontinuation or delayed reduction was associated with increased risk for most opioid related adverse health events.ConclusionPersistent use trajectories with low levels of opioid utilization were associated with lower risks of potential opioid‐related adverse health events.
A dataset resource for clinically associated phosphosites in hepatocellular carcinoma
Authors: Meng Qian , Wang Yuqiu , Lu Dayun , Song Nixue , Zhou Hu , Zhu Hongwen 
Published: June 2022

AbstractPhosphorylation is one of the most common post‐translational modifications (PTMs) and is closely related to protein activity and function, playing a critical role during cancer development. Quantitative phosphoproteomic strategies have been widely used to study the underlying mechanisms of cancer progression or drug resistance. In this report, we analyzed the association of phosphosite levels originated from our previously reported proteogenomic study in hepatocellular carcinoma (HCC) with clinical parameters, including prognosis, recurrence, and Tumor–Node–Metastasis (TNM) stages. By using both the log‐rank test and univariate Cox proportional hazards regression analysis, we found that the abundance levels of 1712 phosphosites were associated with prognosis and those of 393 phosphosites associated with recurrence. Besides, 692 phosphosites had different abundance levels among TNM stages (I, II, III+IV) by Analysis of Variance (ANOVA) test. Gene ontology (GO) biological process and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using proteins with these statistically significant phosphosites. In conclusion, we provided a dataset resource for clinically associated phosphosites in HCC, which may be beneficial to liver cancer related basic research.
Patient‐specific synthetic magnetic resonance imaging generation from cone beam computed tomography for image guidance in liver stereotactic body radiation therapy
Authors: Zhang Zeyu , Jiang Zhuoran , Zhong Hualiang , Lu Ke , Yin Fang‐Fang , Ren Lei 
Published: June 2022

AbstractObjectiveDespite its prevalence, cone beam computed tomography (CBCT) has poor soft‐tissue contrast, making it challenging to localize liver tumors. We propose a patient‐specific deep learning model to generate synthetic magnetic resonance imaging (MRI) from CBCT to improve tumor localization.MethodsA key innovation is using patient‐specific CBCT‐MRI image pairs to train a deep learning model to generate synthetic MRI from CBCT. Specifically, patient planning CT was deformably registered to prior MRI, and then used to simulate CBCT with simulated projections and Feldkamp, Davis, and Kress reconstruction. These CBCT‐MRI images were augmented using translations and rotations to generate enough patient‐specific training data. A U‐Net‐based deep learning model was developed and trained to generate synthetic MRI from CBCT in the liver, and then tested on a different CBCT dataset. Synthetic MRIs were quantitatively evaluated against ground‐truth MRI.ResultsThe synthetic MRI demonstrated superb soft‐tissue contrast with clear tumor visualization. On average, the synthetic MRI achieved 28.01, 0.025, and 0.929 for peak signal‐to‐noise ratio, mean square error, and structural similarity index, respectively, outperforming CBCT images. The model performance was consistent across all three patients tested.ConclusionOur study demonstrated the feasibility of a patient‐specific model to generate synthetic MRI from CBCT for liver tumor localization, opening up a potential to democratize MRI guidance in clinics with conventional LINACs.
Stratosphere–troposphere coupling enhances subseasonal predictability of Northern Eurasian cold spells
Authors: Statnaia Irina , Karpechko Alexey , Kämäräinen Matti , Järvinen Heikki 
Published: June 2022

AbstractHere we explore the stratospheric influence on the predictability of Eurasian cold‐spell events using the European Centre for Medium‐Range Weather Forecasts (ECMWF) ensemble hindcasts obtained from the Subseasonal‐to‐Seasonal (S2S) archive. To isolate the stratospheric influence, we subsampled two groups of hindcasts according to the strength of the stratospheric polar vortex preceding the cold spells at the surface. The predicted probability of cold spells, defined as the lowest 10th percentile of weekly mean temperature anomalies over northern Eurasia (10° W–130° E and 50° N–65° N), is systematically higher, by 0.05–0.2, at lags 7–24 days in the forecasts initialized during the weak stratospheric vortex compared to the strong stratospheric vortex group, extending the predictability of cold spells by 3–5 days. Our results suggest that, in the case of the weak polar vortex, stratosphere–troposphere coupling favors the negative Northern Annular Mode (NAM) regime and the cold‐air outbreaks in Eurasia. As a consequence, the long stratospheric predictability extends the predictability of the cold spells. On the other hand, when the polar vortex is strong, the stratospheric anomalies do not favor the observed negative NAM regime, which thus results from the internal tropospheric processes only. In this case the predictability of cold‐air spells is limited. Furthermore, we show that the extended predictability of cold spells arising from the stratosphere–troposphere coupling is captured by a simple statistical model, suggesting that governing large‐scale dynamics behave effectively linearly over some limited periods. Quantified contribution of the stratosphere–troposphere coupling to the enhanced skill of the extended‐range cold‐spell forecasts documented in our paper may prove useful in the development of forecasting tools.
Theoretical investigations on the properties of graphene supported metal (Al, Zn, Fe) catalysts and the reaction mechanism of catalyzing water to hydrogen peroxide
Authors: Wan Xu‐Jiang , Wu Yang , Mao Dan , Qin Qiao‐Qiao , Liu Xiang‐Yang , Li Lai‐Cai 
Published: June 2022

AbstractIn this paper, density functional theory (DFT) was used to study the reaction mechanism of the production of hydrogen peroxide from oxygen and water catalyzed by graphene supported metal (Al, Zn, and Fe) catalysts. By comparing the supported stability of metal at different sites on graphene surface, the optimal support sites are determined and then a stable catalyst model is selected. Two different reaction paths for the synthesis of hydrogen peroxide and a competitive reaction path for the generation of hydrogen are discussed, the microscopic reaction mechanism of the synthesis of hydrogen peroxide catalyzed by water and oxygen is investigated in detail. The stable structures of reactants, intermediates, and products in each path are optimized. By comparing the activation energies of different reaction paths, the optimal reaction paths are obtained, and the possibility of side reaction products is predicted. At the same time, the electron density, band structure, and density of states characteristics of these graphene supported metal catalysts are studied. The correlation between the physical properties of the three catalysts and their catalytic performances is analyzed. It is predicted that Al, Zn, and Fe catalysts supported by graphene may have the ability to directly generate hydrogen peroxide in industrial wastewater treatment.
Safe reward‐based deep reinforcement learning control for an electro‐hydraulic servo system
Authors: Wu Minling , Liu Lijun , Yu Zhen , Li Weizhou 
Published: June 2022

AbstractIn this article, a safe deep reinforcement learning (DRL) control method based on a safe reward shaping method is proposed and applied to the constrained control for an electro‐hydraulic servo system (EHSS). The proposed control method improves the safety of the constrained control for a nonlinear system with the minimal intervention to the optimization of the performance objective, while the convergence speed of the DRL process has accelerated. By introducing control barrier functions (CBFs) to the reward shaping, a CBF‐based potential difference term is designed to shape the safe reward, which not only provides the safe guidance for the DRL process by encoding the safety constraints of the nonlinear system, but also considers effects of the complex safety transformation on the convergence process in the DRL. Then the safe reward‐based DRL control method is presented to learn the optimal safety policy of position tracking for the EHSS with position error constraints by planning and optimizing the safety together with the performance objective. Theoretical analysis is given to demonstrate that the proposed control method with the safe reward can achieve the optimal safety performance for the constrained control system. Experimental results of the constrained control for the EHSS with system uncertainties and perturbations are also exhibited, to show that the proposed control method converges fast and performs safer and better than the conventional control methods.
Spermine‐Responsive Intracellular Self‐Aggregation of Gold Nanocages for Enhanced Chemotherapy and Photothermal Therapy of Breast Cancer
Authors: Xie Beibei , Zhao Huichao , Shui Mingju , Ding Yuan‐Fu , Sun Chen , Wang Ziyi , Gao Cheng , Chen Guosong , Wang Ruibing 
Published: June 2022

AbstractImproving the precise accumulation and retention of nanomedicines in tumor cells is one of the keys to effective therapy of tumors. Herein, supramolecular peptides capped Au nanocages (AuNCs) that may self‐aggregate into micron‐sized clusters intracellularly in response to spermine (SPM), leading to specific accumulation and retention of AuNCs in SPM‐overexpressed tumor cells, are developed. In this design, polydopamine (PDA) is in situ coated on the surface of AuNCs with doxorubicin (DOX) encapsulated. A small peptide, Phe‐Phe‐Val‐Leu‐Lys (FFVLK), is conjugated with PDA via esterification, and cucurbit[7]uril (CB[7]) is threaded onto the N‐terminal Phe via host‐guest interactions. Once the supramolecular peptide (CB[7]‐FFVLK) capped AuNCs are internalized in SPM‐overexpressed breast cancer cells, CB[7] can be competitively removed from FFVLK by SPM, due to the much higher binding affinity between CB[7] and SPM than that between CB[7] and Phe, leading to exposure of free FFVLK, which can subsequently self‐assemble and induce the aggregation of AuNCs to micron‐sized clusters, resulting in the significantly enhanced accumulation and retention of DOX‐loaded AuNCs in tumor cells. Under NIR laser irradiation, the enhanced photothermal conversion of AuNCs aggregates, together with photothermia‐induced release of DOX leads to synergistic photothermal therapy and chemotherapy against breast cancer.
An Efficient Electron Donor for Conjugated Microporous Polymer Photocatalysts with High Photocatalytic Hydrogen Evolution Activity
Authors: Han Changzhi , Xiang Sihui , Ge Mantang , Xie Peixuan , Zhang Chong , Jiang Jia‐Xing 
Published: June 2022

AbstractConjugated microporous polymers (CMPs) with donor‐acceptor (D‐A) molecular structure show high photocatalytic activity for hydrogen evolution due to the efficient light‐induced electron/hole separation, which is mostly determined by the nature of electron donor and acceptor units. Therefore, the selection of electron donor and acceptor holds the key point to construct high performance polymer photocatalysts. Herein, two dibenzo[b,d]thiophene‐S,S‐dioxide (BTDO) containing CMP photocatalysts using tetraphenylethylene (TPE) or dibenzo[g,p]chrysene (DBC) as the electron donor to investigate the influence of the geometry of electron donor on the photocatalytic activity are design and synthesized. Compared with the twisted TPE donor, DBC has a planar molecular structure with extended π‐conjugation, which promotes the charges transmission and light‐induced electron/hole separation. As a result, the polymer DBC‐BTDO produced from DBC donor shows a remarkable photocatalytic hydrogen evolution rate (HER) of 104.86 mmol h‐1 g‐1 under full arc light (λ > 300 nm), which is much higher than that of the polymer TPE‐BTDO (1.80 mmol h‐1 g‐1), demonstrating that DBC can be an efficient electron donor for constructing D‐A polymer photocatalysts with high photocatalytic activity for hydrogen evolution.
A High Potential Polyanion Cathode Material for Rechargeable Mg‐Ion Batteries
Authors: Li Cuicui , Lin Lu , Wu Wanlong , Sun Xiaoqi 
Published: June 2022

AbstractThe development of Mg‐ion batteries is hindered by the lack of cathode materials that allow facile and reversible Mg2+ intercalation at high potential. Herein, the authors present a polyanion cathode material of K2(VO)2(HPO4)2(C2O4)⋅4.5H2O (KVPCH) for Mg‐ion batteries. The inductive effect of polyanions ensures the high redox potential of the vanadium centers. In addition, the material contains structural water located between the layers. It helps with Mg2+ desolvation at the electrode–electrolyte interface and facilitates its diffusion in the structure, as confirmed by experimental analysis and theoretical calculations. Thanks to those factors, the KVPCH electrode presents excellent Mg storage capability at room temperature. It delivers 121 mAh g–1 capacity at 1C with a high average discharge potential of 0.16 V versus Ag/Ag+ (3.2 V vs Mg/Mg2+). A capacity retention of 87% is realized after 1500 cycles at 5C. A rocking‐chair Mg‐ion full cell is also demonstrated with the KVPCH cathode and a MoOx anode, which achieves 46 mAh g–1 capacity (based on the total active material mass of two electrodes). This work would bring effective paths for the design of cathode materials for Mg‐ion batteries.
Potential Applications of Nickel‐Based Metal‐Organic Frameworks and their Derivatives
Authors: Helal Aasif , Shaheen Shah Syed , Usman Muhammad , Khan Mohd Yusuf , Aziz Md. Abdul , Mizanur Rahman Mohammad 
Published: June 2022

AbstractMetal‐Organic Frameworks (MOFs), a novel class of porous extended crystalline structures, are favored in different fields of heterogeneous catalysis, CO2separation and conversion, and energy storage (supercapacitors) due to their convenience of synthesis, structural tailor‐ability, tunable pore size, high porosity, large specific surface area, devisable structures, and adjustable compositions. Nickel (Ni) is a ubiquitous element extensively applied in various fields of catalysis and energy storage due to its low cost, high abundance, thermal and chemical stability, and environmentally benign nature. Ni‐based MOFs and their derivatives provide us with the opportunity to modify different properties of the Ni center to improve their potential as heterogeneous catalysts or energy storage materials. The recent achievements of Ni−MOFs and their derivatives as catalysts, membrane materials for CO2separation and conversion, electrode materials and their respective performance have been discussed in this review.
The interplay between students' motivational profiles and science learning
Authors: Kubsch Marcus , Fortus David , Neumann Knut , Nordine Jeffrey , Krajcik Joseph 
Published: June 2022

AbstractStudents' motivation plays an important role in successful science learning. However, motivation is a complex construct. Theories of motivation suggests that students' motivation must be conceptualized as a motivational system with numerous components that interact in complex ways and influence metacognitive processes such as self‐evaluation. This complexity is further increased because students' motivation and success in science learning influence each other as they develop over time. It is challenging to study the co‐development of motivation and learning due to these complex interactions which can vary widely across individuals. Recently, person‐centered approaches that capture students' motivational profiles, that is, the multiplicity of motivational factors as they co‐occur in students, have been successfully used in educational psychology to better understand the complex interplay between the co‐development of students' motivation and learning. We employed a person‐centered approach to study how the motivational profiles, constructed from goal‐orientation, self‐efficacy, and engagement data of N = 401 middle school students developed over the course of a 10‐week energy unit and how that development was related to students' learning. We identified four characteristic motivational profiles with varying temporal stability and found that students' learning over the course of the unit was best characterized by considering the type of students' motivational profiles and the transitions that occurred between them. We discuss implications for the design and implementation of interventions and future research into the complex interplay between motivation and learning.
Frame Accuracy of Combined EPN Weekly Coordinate Solutions
Authors: Kotsakis Christopher , Chatzinikos Miltiadis 
Published: June 2022

AbstractThe scope of this paper is to perform an internal quality assessment, at frame parameter level, on the combined EPN weekly coordinate solutions. Specifically, the weekly SINEX solution files from the EPN Analysis Combination Centre are analyzed in order to infer the internal accuracy of the origin, orientation and scale of the respective epoch solutions. Our investigation covers almost the entire operational period of EPN starting from 1999 up to present time, and it uses both the routine and re-processed (repro2) series of combined weekly solutions. Through the results of this study we are able to assess the impact of various changes or updates that have been applied into the routine GNSS data processing and combination strategies on the quality of the estimated EPN weekly frames.
An Entrepreneurial Process for Exploiting Vulnerable People’s Labor
Authors: Shepherd Dean A. , Parida Vinit , Wincent Joakim 
Published: June 2022

AbstractIn this chapter—“An Entrepreneurial Process for Exploiting Vulnerable People’s Labor”—we take an even bigger step toward the dark side of entrepreneurial action in response to chronic adversity. In this chapter, we take the perspective of victims to explore a destructive entrepreneurial process that involves multiple actors—namely, that of exploiting vulnerable women and girls for human trafficking. We focus on the destructive entrepreneurial practices used to exploit vulnerable individuals for their labor to explain how entrepreneurs (as actors within the human-trafficking system) methodically target impoverished women and girls and transform their autonomous objections into unquestioned compliance. We show that through the entrepreneurial practices of (1) deceptive recruiting of the vulnerable, (2) entrapping through isolation, (3) extinguishing alternatives by building barriers, and (4) converting the exploited into exploiters, these entrepreneurs diminish and eventually eliminate vulnerable workers’ autonomy. In doing so, we shed light on the illegal entrepreneurial process of exploiting vulnerable individuals’ labor and ruining their lives by eliminating their free will.
Designing Online Learning Environments to Support Problem-Based Learning
Authors: Ge Xun , Huang Kun 
Published: June 2022

AbstractProblem-based learning (PBL) represents an instructional approach through which learning is gained by investigating, negotiating, and resolving meaningful problems. PBL can be challenging to implement, and the online learning ecology adds another layer of challenges as it demands effective interactions between pedagogy and technology. To inform the design of online learning environments to support PBL, this chapter presents a practical pedagogical framework to support four key aspects of PBL implementation: (1) preparation and planning, (2) design and development, (3) implementation and facilitation, and (4) assessment. Strategies, tools, and examples were drawn from the literature to address each aspect.
Effectivity of Semi-positive Line Bundles
Authors: Anella F. , Huybrechts D. 
Published: June 2022

AbstractWe review work by Campana–Oguiso–Peternell (J Differ Geom 85(3):397–424, 2010) and Verbitsky (Geom Funct Anal 19(5):1481–1493, 2010) showing that a semi-positive line bundle on a hyperkähler manifold admits at least one non-trivial section. This is modest but tangible evidence towards the SYZ conjecture for hyperkähler manifolds.