bluuebunny/crossref_metadata_2025_split huggingface dataset:
An evaluation of online Edcraft gamified learning (EGL) to understand motivation and intention of recycling among youth
Authors: Cheng Kin Meng , Koo Ah Choo , Nasir Junita Shariza Binti Mohd , Wong Shen Yuong 
Published: December 2022

AbstractRecycling is a process carried out by various organizations and individuals to enhance the environment’s long-term sustainability. Some youth think that recycling is a monotonous action as it may seem inconvenient, less aware of the environmental issues and more time-consuming than they think and rather go for video games. Therefore, this study investigates the relationship between motivation and recycling intention in gamified learning among youth. To address the research aim, this study uses gamification as a motivational driver for a game-like learning experience to improve recycling intentions among youth. Self-determination theory (SDT) and the theory of Planned Behavior (TPB) will be this study's main motivational and behavioral theories. (n = 124) high schools and college students were invited to take part in an online gamified recycling activity, Edcraft Gamified Learning (EGL), consisting of two levels of gamified unused plastic-crafting recycling activities. After the activity, the participants will answer a post-event questionnaire and the data collected were analyzed. The result shows that controlled motivation (CM) and autonomous motivation (AM) positively influenced youth attitudes and social norms. Besides, attitude is the only psychosocial determinant that positively influences the recycling intention of the youth. Gamification only moderates positively between attitude and recycling intention. This study has clearly shown the effectiveness of gamified learning activity towards recycling intention directly and as a component that moderates the relationship between attitude and recycling intention, which shows a favorable evaluation towards recycling intention with gamified learning involved. Moreover, the findings showed that not all relationships are positive in a gamified learning environment, and it gives a good view on the weakness and strengths with the guideline of SDT and TPB.
scATAC-Seq reveals heterogeneity associated with spermatogonial differentiation in cultured male germline stem cells
Authors: Suen Hoi Ching , Luk Alfred Chun Shui , Liao Jinyue 
Published: December 2022

AbstractSpermatogonial stem cells are the most primitive spermatogonia in testis, which can self-renew to maintain the stem cell pool or differentiate to give rise to germ cells including haploid spermatids. All-trans-retinoic acid (RA), a bioactive metabolite of vitamin A, plays a fundamental role in initiating spermatogonial differentiation. In this study, single-cell ATAC-seq (scATAC-seq) was used to obtain genome-wide chromatin maps of cultured germline stem cells (GSCs) that were in control and RA-induced differentiation states. We showed that different subsets of GSCs can be distinguished based on chromatin accessibility of self-renewal and differentiation signature genes. Importantly, both progenitors and a subset of stem cells are able to respond to RA and give rise to differentiating cell subsets with distinct chromatin accessibility profiles. In this study, we identified regulatory regions that undergo chromatin remodeling and are associated with the retinoic signaling pathway. Moreover, we reconstructed the differentiation trajectory and identified novel transcription factor candidates enriched in different spermatogonia subsets. Collectively, our work provides a valuable resource for understanding the heterogeneity associated with differentiation and RA response in GSCs.
Paraoxonase-2 contributes to promoting lipid metabolism and mitochondrial function via autophagy activation
Authors: Shin Gu-Choul , Lee Hyeong Min , Kim Nayeon , Yoo Sang-Ku , Park Hyung Soon , Choi Leo Sungwong , Kim Kwang Pyo , Lee Ah-Ra , Seo Sang-Uk , Kim Kyun-Hwan 
Published: December 2022

AbstractNon-alcoholic fatty liver disease (NAFLD) is an increasingly prevalent immuno-metabolic disease that can progress to hepatic cirrhosis and cancer. NAFLD pathogenesis is extremely complex and is characterized by oxidative stress, impaired mitochondrial function and lipid metabolism, and cellular inflammation. Thus, in-depth research on its underlying mechanisms and subsequent investigation into a potential drug target that has overarching effects on these features will help in the discovery of effective treatments for NAFLD. Our study examines the role of endogenous paraoxonase-2 (PON2), a membrane protein with reported antioxidant activity, in an in vitro cell model of NAFLD. We found that the hepatic loss of PON2 activity aggravated steatosis and oxidative stress under lipotoxic conditions, and our transcriptome analysis revealed that the loss of PON2 disrupts the activation of numerous functional pathways closely related to NAFLD pathogenesis, including mitochondrial respiratory capacity, lipid metabolism, and hepatic fibrosis and inflammation. We found that PON2 promoted the activation of the autophagy pathway, specifically the mitophagy cargo sequestration, which could potentially aid PON2 in alleviating oxidative stress, mitochondrial dysfunction, lipid accumulation, and inflammation. These results provide a mechanistic foundation for the prospect of PON2 as a drug target, leading to the development of novel therapeutics for NAFLD.
A two-phase model of collective memory decay with a dynamical switching point
Authors: Igarashi Naoki , Okada Yukihiko , Sayama Hiroki , Sano Yukie 
Published: December 2022

AbstractPublic memories of significant events shared within societies and groups have been conceptualized and studied as collective memory since the 1920s. Thanks to the recent advancement in digitization of public-domain knowledge and online user behaviors, collective memory has now become a subject of rigorous quantitative investigation using large-scale empirical data. Earlier studies, however, typically considered only one dynamical process applied to data obtained in just one specific event category. Here we propose a two-phase mathematical model of collective memory decay that combines exponential and power-law phases, which represent fast (linear) and slow (nonlinear) decay dynamics, respectively. We applied the proposed model to the Wikipedia page view data for articles on significant events in five categories: earthquakes, deaths of notable persons, aviation accidents, mass murder incidents, and terrorist attacks. Results showed that the proposed two-phase model compared favorably with other existing models of collective memory decay in most of the event categories. The estimated model parameters were found to be similar across all the event categories. The proposed model also allowed for detection of a dynamical switching point when the dominant decay dynamics exhibit a phase shift from exponential to power-law. Such decay phase shifts typically occurred about 10 to 11 days after the peak in all of the five event categories.
Comparative proteoinformatics revealed the essentials of SDS impact on HaCaT keratinocytes
Authors: Shkrigunov Timur , Kisrieva Yulia , Samenkova Natalia , Larina Olesya , Zgoda Victor , Rusanov Alexander , Romashin Daniil , Luzgina Natalia , Karuzina Irina , Lisitsa Andrey , Petushkova Natalia 
Published: December 2022

AbstractThere is no direct evidence supporting that SDS is a carcinogen, so to investigate this fact, we used HaCaT keratinocytes as a model of human epidermal cells. To reveal the candidate proteins and/or pathways characterizing the SDS impact on HaCaT, we proposed comparative proteoinformatics pipeline. For protein extraction, the performance of two sample preparation protocols was assessed: 0.2% SDS-based solubilization combined with the 1DE-gel concentration (Protocol 1) and osmotic shock (Protocol 2). As a result, in SDS-exposed HaCaT cells, Protocol 1 revealed 54 differentially expressed proteins (DEPs) involved in the disease of cellular proliferation (DOID:14566), whereas Protocol 2 found 45 DEPs of the same disease ID. The ‘skin cancer’ term was a single significant COSMIC term for Protocol 1 DEPs, including those involved in double-strand break repair pathway (BIR, GO:0000727). Considerable upregulation of BIR-associated proteins MCM3, MCM6, and MCM7 was detected. The eightfold increase in MCM6 level was verified by reverse transcription qPCR. Thus, Protocol 1 demonstrated high effectiveness in terms of the total number and sensitivity of MS identifications in HaCaT cell line proteomic analysis. The utility of Protocol 1 was confirmed by the revealed upregulation of cancer-associated MCM6 in HaCaT keratinocytes induced by non-toxic concentration of SDS. Data are available via ProteomeXchange with identifier PXD035202.
Discrimination between possible sarcopenia and metabolic syndrome using the arterial pulse spectrum and machine-learning analysis
Authors: Wu Li-Wei , OuYoung Te , Chiu Yu-Chih , Hsieh Ho-Feng , Hsiu Hsin 
Published: December 2022

AbstractSarcopenia is defined as decreased skeletal muscle mass and function, and is an important cause of frailty in the elderly, also being associated with vascular lesions and poor microcirculation. The present study aimed to combine noninvasive pulse measurements, frequency-domain analysis, and machine learning (ML) analysis (1) to determine the effects on the pulse waveform induced by sarcopenia and (2) to develop discriminating models for patients with possible sarcopenia. Radial blood pressure waveform (BPW) signals were measured noninvasively for 1 min in 133 subjects who visited Tri-Service General Hospital for geriatric health checkups. They were assigned to a robust group and a possible-sarcopenia group that combined dynapenia, presarcopenia, and sarcopenia. Two classification methods were used: ML analysis and a self-developed scoring system that used 40 harmonic pulse indices as features: amplitude proportions and their coefficients of variation, and phase angles and their standard deviations. Significant differences were found in several spectral indices of the BPW between possible-sarcopenia and robust subjects. Threefold cross-validation results indicated excellent discrimination performance, with AUC equaling 0.77 when using LDA and 0.83 when using our scoring system. The present noninvasive and easy-to-use measurement and analysis method for detecting sarcopenia-induced changes in the arterial pulse transmission condition could aid the discrimination of possible sarcopenia.
One-year-later spontaneous EEG features predict visual exploratory human phenotypes
Authors: Celli Miriam , Mazzonetto Ilaria , Zangrossi Andrea , Bertoldo Alessandra , Cona Giorgia , Corbetta Maurizio 
Published: December 2022

AbstractDuring visual exploration, eye movements are controlled by multiple stimulus- and goal-driven factors. We recently showed that the dynamics of eye movements –how/when the eye move– during natural scenes’ free viewing were similar across individuals and identified two viewing styles: static and dynamic, characterized respectively by longer or shorter fixations. Interestingly, these styles could be revealed at rest, in the absence of any visual stimulus. This result supports a role of intrinsic activity in eye movement dynamics. Here we hypothesize that these two viewing styles correspond to different spontaneous patterns of brain activity. One year after the behavioural experiments, static and dynamic viewers were called back to the lab to record high density EEG activity during eyes open and eyes closed. Static viewers show higher cortical inhibition, slower individual alpha frequency peak, and longer memory of alpha oscillations. The opposite holds for dynamic viewers. We conclude that some properties of spontaneous activity predict exploratory eye movement dynamics during free viewing.
3D magnetic imaging using electron vortex beam microscopy
Authors: Barrows Frank , Petford-Long Amanda K. , Phatak Charudatta 
Published: December 2022

AbstractElectron vortex beams are free-electron waves that carry orbital angular momentum. There has been growing theoretical and experimental interest in the use of electron vortex beams as a tool for the investigation of magnetic materials. However, due to the complex wavefront of the propagating waves, a deeper understanding of the interaction of electron vortex beams and the magnetic sample is needed. Here we calculate the magnetic phase shift that an electron vortex beam obtains upon transmitting through a magnetic sample. We show that this magnetic phase shift is influenced by the out-of-plane magnetization, which is a unique characteristic of incident electron vortex beams and is proportional to their orbital angular momentum. Finally, we develop a phase retrieval methodology to retrieve the out-of-plane component of magnetization. Based on our theory, we discuss suitable experimental conditions that would enable this imaging capability for magnetic materials and further extend to non-magnetic chiral materials.
Structural mass spectrometry approaches to understand multidrug efflux systems
Authors: Russell Lewis Benjamin , Lawrence Ryan , Hammerschmid Dietmar , Reading Eamonn 
Published: December 2022

AbstractMultidrug efflux pumps are ubiquitous across both eukaryotes and prokaryotes, and have major implications in antimicrobial and multidrug resistance. They reside within cellular membranes and have proven difficult to study owing to their hydrophobic character and relationship with their compositionally complex lipid environment. Advances in structural mass spectrometry (MS) techniques have made it possible to study these systems to elucidate critical information on their structure–function relationships. For example, MS techniques can report on protein structural dynamics, stoichiometry, connectivity, solvent accessibility, and binding interactions with ligands, lipids, and other proteins. This information proving powerful when used in conjunction with complementary structural biology methods and molecular dynamics (MD) simulations. In the present review, aimed at those not experts in MS techniques, we report on the current uses of MS in studying multidrug efflux systems, practical considerations to consider, and the future direction of the field. In the first section, we highlight the importance of studying multidrug efflux proteins, and introduce a range of different MS techniques and explain what information they yield. In the second section, we review recent studies that have utilised MS techniques to study and characterise a range of different multidrug efflux systems.
Denitrosation of Aryl-N-nitrosamines by a Transnitrosation Strategy Using Ethanethiol and p-Toluenesulfonic Acid under Mild Reaction Conditions
Authors: Kandasamy Jeyakumar , Kanaujiya Vimlesh Kumar , Tiwari Varsha , Baranwal Siddharth , Srivastava Vandana 
Published: December 2022

AbstractA convenient and practical route is reported for the denitrosation of aryl-N-nitrosamines under mild reaction conditions using ethanethiol and PTSA. The reactions proceeds at room temperature and the amines are obtained in good to excellent yields. Many functional groups that are susceptible to reduction were stable during the denitrosation. A broad substrate scope and easy operations are salient features of this method.
Physics-informed sparse identification of bistable structures
Authors: Liu Qinghua , Zhao Zhenyang , Zhang Ying , Wang Jie , Cao Junyi 
Published: December 2022

Abstract
The design of bistable structures is a hot topic in the last decade due to its wide application in smart actuators, energy harvesters, flexible robotics, etc. The characterization of the nonlinear restoring force of bistable structures plays a significant role in modeling and enhancing dynamic performance. However, the traditional nonparametric identification methods may have insufficient accuracy or even be invalid because of numerical differentiation procedures and static fitting. Besides, the modern data-driven sparse regression identification methods rely highly on the assumed nonlinear basis functions and lack interpretability. In this paper, a physics-informed sparse identification method is proposed for the nonlinear restoring force identification of bistable structures. The function of the nonlinear restoring force is physically informed by the derived equation of the Hilbert transform and parameter fitting. Furthermore, sparse identification is conducted based on the free vibration responses of the bistable vibrator. The numerical studies verify the effectiveness of the proposed algorithm under the noise level of 30 dB. Experimental measurement is conducted on a magnetic coupled bistable beam to perform the model identification. It has been demonstrated that the reconstructed dynamic response and nonlinear restoring force both keep in good agreement with the measured ones.
ITER relevant multi-emissive sheaths at normal magnetic field inclination
Authors: Tolias P. , Komm M. , Ratynskaia S. , Podolnik A. 
Published: December 2022

Abstract
Reliable modeling of macroscopic melt motion induced by fast transients requires the accurate and computationally efficient description of the emitted current density that escapes to the pre-sheath. The ITER sheaths that surround hot tungsten surfaces during edge-localized modes are characterized by important contributions from secondary electron emission and electron backscattering as well as by the coupling between thermionic emission and field electron emission. Under the guidance of systematic particle-in-cell simulations that incorporate a comprehensive analytical electron emission model, a highly accurate semi-empirical treatment of the escaping electron current has been achieved.
Prediction of Future NBA Games’ Point Difference: A Statistical Modeling Approach
Authors: Han Ruize , Shi Shunying , Hu Tianrui , Tao Sijian 
Published: December 2022

Abstract
Nowadays, the popularity of the NBA along with the penetration of gambling ideas is rising all around the world. More and more fans prefer to bet on sports gambling. People want to predict the final score difference for each individual game. In addition, there are many either superficial or underlying factors that will affect the game’s result. The central claim of this article is to establish a reliable model that could predict each game’s result by extracting and analyzing previous games’ outcomes. The major analysis is done by modeling and exploratory data analysis, and is composed of several graphical methods. For the modeling part, ideally the model could predict the games’ score differences by analyzing previous dozens of games’ data sets. The database consists of four seasons 2013-2017 on Goldsheet website to explore more analysis. Then step by step checking and demonstrating to prove the feasibility and precision of the model. The model will collect and analyze the data information, like teams, rebounds, assists, turnovers, three points, free throws, blocks, and injury data. Considering the transfer between teams and other changes, the model will predict the future game result in each season independently by using each team’s previous game result in that season. This article indicates the idea of linear regression model to find the best fit by comparing the correlation strength of each variable, which include the home-field advantage, teams’ technical statistics, and injury data, to the result of a game. The model final outcomes implies that the game’s result has the most correlation with the home-field advantage and player injury; however, team’s basic technical statistics, included the rebounds, blocks, turnovers, free throws, three points, and assists, have low correlation coefficient with the result to demonstrate that they are not significant to a game’s result.
Fluxion Form Comparison between Newton Fluid and Bingham Fluid based on Three-Dimensional Numerical Simulation With Examples of Blood in Aorta and Water
Authors: Hu Tianmu 
Published: December 2022

Abstract
The rheological properties of blood is one of the most important parameter to make an influence on human health. And the numerical simulation is a popular methodology to conduct research towards the fluxion form of blood. In this dissertation, this paper uses Ansys Aim to computationally analyze the vessels based on the theory of Computational Fluid Dynamics (CFD for short). Two kinds of fluid, namely the Newton fluid, water, and the non-Newton fluid, blood, are taken into consideration. And the model of the blood’s non-Newton fluid is set as the Bingham model. Two fluids’ distributions of velocity and absolute stress are given, and the comparison of their fluxion form is done. The simulated results reveal that the biggest velocity in Bingham model is 18.07% bigger than that in Newton model, and the max difference of stress in Bingham model is 139% bigger than that in the water model. The results stated above pave the way for the subsequent research.
Finding Minimum Production Time and Optimal Procedure for a Project When Step Times are Given by Constructive Real Numbers
Authors: Li Yijia , Shan Peiyuan , Xu Tiancheng , Zhang Shenyao , Zou Tiancheng 
Published: December 2022

Abstract
In the production process, some jobs can only be done sequentially, while others can be done synchronously. Given the time needed to complete each job, an oriented graph with a source vertex and a sink vertex can be generated. Each route starting from the source vertex and ending at the sink vertex represents a way of completing the project. It is possible to find the minimum production time and the optimal production path when time for each job is given by a rational number. However, this paper proves that there does not exist a computer program that can always generate the minimum time and optimal path when the time needed for each job is a constructive real number.
A Simple Proof of Bieberbach Conjecture
Authors: Yao Wenqing 
Published: December 2022

Abstract
The famous Riemann mapping theorem, which was established in 1851, states that every proper subdomain of the complex plane that is simply connected (without “holes”) is the image of the unit disk under a univalent analytic mapping f(z). This is the most significant characteristic of univalent analytic functions. The domain D, the image point f(0) in D, and the restriction that f’(0) be a positive real integer each independently define the mapping function f(z). One naturally asks how geometric aspects of the image domain f(D) represent analytic properties of f when considering univalent analytic functions as “Riemann mappings”. This is the perspective of geometric function theory, whose primary issue was solved by de Branges’ proof. The Bieberbach conjecture (hereinafter referred to as “BC”) is essentially a claim on the extreme nature of the Koebe function. Therefore, a key subject in this article is to make an explanation of the Koebe function and intepret why it is the best contender to be “largest” in the sense of the conjecture. Also, a detailed but easy understanding noval proof is given for this conjecture.