bluuebunny/crossref_metadata_2025_split huggingface dataset:
Popularization of Science in Colleges and Universities in the New Network Media Environment Based on Artificial Intelligence
Authors: Sheng Lin 
Published: March 2023

Abstract
By introducing new network media and artificial intelligence technology into the field of science popularization in colleges and universities, this research strives to solve the practical problems of science popularization websites that are large but not distinctive in the current era, and tries to improve the social impact and economic benefits of such science popularization platforms, so as to promote platform innovation and break away from the stereotyped system design form. Through the establishment of a science popularization system for colleges and universities, the mainstream content management can be achieved, and the differentiation management between the main station and the sub station can be completed. The platform design is implemented by Java EE technology, carrying multi-functional module components, completing the componentized configuration of the system, which can be developed sustainably and has good security. The university science popularization system can operate stably in most environments, and the security management measures are strict. It can take multiple means to effectively protect the security of information, and it is simple and easy to implement. It can be seen from the design of simulation experiment that this promotion system, through the design of hybrid recommendation strategy, can_ UserCF and SBBRM_ Based on the advantages of Doc2Vec algorithm, the accuracy and coverage of system recommendations are improved, making it more universal. And the hybrid recommendation results can be compared with the main recall model to prove the efficiency of the system. This paper introduces artificial intelligence technology into the field of science popularization in colleges and universities, so as to realize the system design and improvement based on the new network media environment.
An empirical analysis of dynamic network model of international trade by using enterprise sample simulation and improved ANN algorithm
Authors: Liu Ruiqian , Chen Xiaofei 
Published: March 2023

Abstract
With the support of enterprise intelligence system, an intelligent modeling method based on synthesizing various data sources and complex metabolic networks is adopted to provide technical support for the practical application of complex large-scale dynamic models. Academic research on international trade networks relies to a large extent on network models based on macro-national data and static analysis of international trade patterns, which are usually based on charts for trade flows and economic globalization. In this paper, we analyze the complex dynamic meta-network model of international trade based on improved neural network algorithm. Because BP neural networks run through the best neural network model that is constantly adjusted according to weighted values, the adjustment of neural network value is reduced, which may be an effective means to improve the efficiency of intrusion testing applications. The simulation results show that the model has good explanatory power. The internationalization of enterprise market as the main body of international business activities affects the establishment and development of a national or regional international trade network. Therefore, there is a need to study international trade networks using data at the micro level. This paper suggests an interdisciplinary approach to the study of international trade networks and a micro-level study of international trade networks. The model based on complex meta-network dynamic model elements, introduce the dynamic network representation, use temporary labels to define the network boundary characteristics.
Internet financial forecasting and digital economy development by using machine learning algorithm in the New Consumption Environment
Authors: Huang Peng 
Published: March 2023

Abstract
DPDK (Data Plane Development Kit) provides an effective solution for the rapid processing of general multi-core processor platforms. Research based on DPDK on a general-purpose multi-core processor platform can use CPU cache to improve packet forwarding and processor core performance, as well as network function virtualization performance. In the parallel development of finance and network, people find that complex financial problems can be well solved through big data network. The rapidly changing financial market is affected by economic and political factors, and the generation of financial data is also highly uncertain. However, financial forecast analysis and forecast modeling are of great significance. As a whole, this trend could help inform policy; from a meso level, it can be insightful The changes in financial data are conducive to the planning of business strategies for enterprises and gaining market competitive advantages; from a micro level, individual investors will pay attention to historical data changes and the development of industries or companies before making investment decisions in order to obtain benefits. Internet technology can strengthen the accuracy of financial forecasting, so as to effectively avoid risks, but also can promote the development of digital economy, reduce labor costs, improve the breadth and depth of financial services in digital economy.
Campus IoT system and students’ Employment Education Innovation based on mobile edge computing
Authors: Xie Tian 
Published: March 2023

Abstract
With the rapid development of Internet of things, more and more computing intensive applications are running on the Internet of things terminals. These computing intensive applications usually need strong computing power. It requires high energy consumption to process these applications locally through Internet of things terminals. At the same time, the computing capacity and battery capacity of the Internet of things terminals are limited. To solve this problem, computing tasks can be transferred from single Internet (IOT) terminals to cloud computing with powerful computing functions. However, cloud computing has inherent limitations. That is, the distance from user terminal to remote cloud center server is very long, and the application delay time is too long. Mobile edge computing, as a new computing technology, is introduced to the network edge, which provides computing services that can generate enough capacity by obtaining a large number of free computing capacity and scattered storage space on the edge. This is a task that is used in mobile terminal or Internet of things terminal to perform computationally intensive and wait time important tasks. Unlike traditional cloud computing, mobile edge computing can be extended to wireless access points. This paper uses mobile edge computing Internet of things technology to study campus system innovation and student employment education. The high quality employment guidance education for college students is not only an important way to promote the external output of talents, but also an important link to realize the connection between universities and enterprises, and also an important means for universities to provide services to the society.
Factors influencing visual acuity in patients with active polypoidal choroidal vasculopathy and imaging parameters changes
Authors: Xia Fan , Hua Rui , Xing Peiyu , Zhang Hao , Niu Tongtong 
Published: March 2023

Abstract
We performed a retrospective, observational study for 51 eyes of 51 treatment-naive patients with polypoidal choroidal vasculopathy (PCV), whose lesion ranged within the 6x6mm scope of optical coherence tomography angiography (OCTA). Patients were divided into two groups based on the pattern of branching vascular network (BVN) on OCTA: ill-defined group and well-defined group. BVN morphology was not related to baseline best-corrected visual acuity (BCVA). But the improvement of BCVA had a significant positive relationship with the pattern of BVN on OCTA (r = 0.306, p = 0.031). The BCVA in the ill-defined BVN group (-0.18 [interquartile range: -0.40 to 0.00]) was significantly improved after anti-vascular endothelial growth factor (VEGF) injections, compared with that (0.00 [interquartile range: -0.18 to 0.00]) in the well-defined group (z = 2.143, p = 0.032). Multiple logistic regression analysis showed that male sex, smaller number of injections, and presence of polypoidal lesions on OCTA images at baseline predicted a poor prognosis of polypoidal lesions on OCTA images after anti-VEGF therapy (all p < 0.05). Finally, BCVA at baseline and the number of injections were protective factors for BCVA after anti- VEGF therapy (all p < 0.05). In contrast, history of hypertension and macular edema at baseline were risk factors for BCVA after anti-VEGF injections (all p < 0.05).
Giant electromechanical response from defective non-ferroelectric epitaxial BaTiO3 integrated on Si (100)
Authors: Vura Sandeep , Parate Shubham , Pal Subhajit , Khandelwal Upanya , Rai Rajeev , Molleti Sri Harsha , Kumar Vishnu , Ventrapragada Rama , Patil Girish , Jain Mudit , Mallya Ambresh , Ahmadi Majid , Kooi Bart , Avasthi Sushobhan , Ranjan Rajeev , Raghavan Srinivasan , Chandorkar Saurabh , Nukala Pavan 
Published: March 2023

Abstract
Lead-free, silicon compatible materials showing large electromechanical responses comparable to, or better than conventional relaxor ferroelectrics, are desirable for various nanoelectromechanical devices and applications. Defect-engineered electrostriction has recently been gaining popularity to obtain enhanced electromechanical responses at sub 100 Hz frequencies. Here, we report record values of electrostrictive strain coefficients (M31) at frequencies as large as 5 kHz (1.04×10− 14 m2/V2 at 1 kHz, and 3.87×10− 15 m2/V2 at 5 kHz) using A-site and oxygen-deficient barium titanate thin-films, epitaxially integrated onto Si. The effect is robust and retained even after cycling the devices > 5000 times. Our perovskite films are non-ferroelectric, exhibit a different symmetry compared to stoichiometric BaTiO3 and are characterized by twin boundaries and nano polar-like regions. We show that the dielectric relaxation arising from the defect-induced features correlates very well with the observed giant electrostrictive response. These films show large coefficient of thermal expansion (2.36 ⋅ 10− 5/K), which along with the giant M31 implies a considerable increase in the lattice anharmonicity induced by the defects. Our work provides a crucial step forward towards formulating guidelines to engineer large electromechanical responses even at higher frequencies in lead-free thin films.
The impact of dyslipidemia on lumbar intervertebral disc degeneration and vertebral endplate modic changes: a cross-sectional study of 1035 citizens in China
Authors: Yuan Liang , Huang Zhengqi , Han Weitao , Chang Ruiming , Sun Bo , Zhu Mingxi , Li Chenjing , Yan Jiansen , Liu Bin , Yin Haidong , Ye Wei 
Published: March 2023

Abstract
Background: Intervertebral disc degeneration (IDD) and vertebral endplate Modic changes (MCs) are common lumbar degenerative phenotypes related to low back pain (LBP). Dyslipidemia has been linked to LBP but its associations with IDD and MCs have not been fully elucidated. The present study aimed to address the possible link between dyslipidemia, IDD and MCs in the Chinese population.
Methods: 1035 citizens were enrolled in the study. The levels of serum total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C) and triglycerides (TG) were collected. IDD was evaluated based on the Pfirrmann grading system and subjects with an average grade ≥3 were defined as having degeneration. MCs were classified into typical types 1, 2 and 3. Covariables, including age, sex, BMI and fasting plasma glucose, were included for the adjustment of the logistic analyses.
Results: The degeneration group included 446 subjects while the nondegeneration group included 589 subjects. The degeneration group had significant higher levels of TC and LDL-C (p<0.001) whereas TG and HDL-C were not significant different between the two groups. TC and LDL-C concentrations were significantly positively correlated with average IDD grades (p<0.001). Multivariate logistic regression revealed that high TC (≥6.2 mmol/L, adjusted OR=1.775, 95% CI=1.209-2.606) and high LDL-C (≥4.1 mmol/L, adjusted OR=1.818, 95% CI=1.123-2.943) were independent risk factors for IDD. Type 1 MC presented in 84 (8.12%) subjects, type 2 MC presented in 244 (23.57%) subjects, type 3 MC presented in 27 (2.61%) subjects and no MC was observed in the remaining 680 (65.70%) subjects. The type 2 MC group demonstrated a higher level of TC, but the association between serum lipids and MCs could not be confirmed in further multivariate logistic regression.
Conclusions: High TC (≥6.2 mmol/L) and LDL-C (≥4.1 mmol/L) concentrations were recognized as independent risk factors for IDD for citizens in China. However, the epidemiological association between dyslipidemia and MCs could not be determined. The biomolecular effect of excess serum cholesterol may play a vital role in the development of IDD. Hypolipidemic treatment, especially when targeting cholesterol, may provide new opportunities in the management of lumbar disc degenerative diseases.
SASH3 is an unfavorable prognostic immune biomarker in patients with acute myeloid leukemia(AML).
Authors: Qiu Zhengqi , Wang Lin , Jia Xueyuan , Yang Yanru 
Published: March 2023

Abstract
Background:
Acute myeloid leukemia(AML) is a malignant clonal disease. As the most common type of leukaemia, it is characterised by poor treatment outcomes and a poor prognosis in both the paediatric and adult populations. Improving anti-tumour responses through immunomodulators is a promising strategy or a new avenue for AML treatment.
Methods:
Using publicly available data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx), we examined the association between SAM And SH3 Domain Containing 3(SASH3) and AML. Wilcoxon signed-rank test and logistic regression were used to analyze the relationship between clinical pathologic features and SASH3. Cox regression and Kaplan-Meier methods were used to determine the clinical characteristics associated with overall survival in patients with AML. Then the relationship between immune infiltration and SASH3 was also analyzed. The research finding was validated by data from the Gene Expression Omnibus (GEO) database.
Results:
Compared to normal patients, SASH3 expression in AML patients was significantly higher (p = 3.05e-34) and strongly associated with survival. In addition, SASH3 expression was significantly correlated with survival outcome (p = 5.3E-03) and cytogenetic risk (p = 3E-04) in AML. SASH3 expression was correlated with the expression of the genes HCK, SYK, FYN, ITGB2, PIK3CD, FGR, PIK3R5, VAV1, LCP2, and GRB2. Our study suggests that SASH3 expression is strongly associated with AML development and survival outcomes as well as multiple cancer-related genes and pathways, such as the HCK(Hematopoietic cell kinase) and regulation of small GTPase-mediated signal transduction.
Conclusion:
Our study revealed that SASH3 expression is closely associated with AML development and survival outcome, as well as multiple cancer-related genes and pathways, thus highlighting SASH3 as a potential therapeutic marker of AML.
Angelman Syndrome causing UBE3A ligase displays predominantly synaptic ubiquitination activity in the mouse brain
Authors: Mayor Ugo , Alduntzin Unai , Lectez Benoit , Presa Natalia , Osinalde Nerea , Fernandez Marta , Elu Nagore , Ramirez Juanma , Garcia-Barcena Cristina , Aloria Kerman , Frick Andreas , Peñagarikano Olga 
Published: March 2023

Abstract
Angelman Syndrome (AS) is a neurodevelopmental disorder with complex symptomatology caused by the loss of maternal allele expression of one single gene in the brain, the ubiquitin E3 ligase UBE3A. The underlying genetic basis of AS, and the phenotypes observed in both humans and in animal models of AS, have previously been extensively described. However, the molecular mechanisms regulated by UBE3A ubiquitination in the brain remain highly elusive. Previous studies have reported a number of proteins whose abundance or activity are altered in AS models, implicating various signalling pathways in the physiopathology of AS. However, the identified pathways could well be altered further downstream of UBE3A ubiquitination events. We provide the first proteomic report of UBE3A-mediated ubiquitination events in a mammalian brain. For this we have combined the bioUb mouse model with a new mouse strain moderately increasing UBE3A levels. Several proteins known to be involved in the trafficking and maintenance of neurotransmitter receptors as well as proteins relaying the signals of these synaptic receptors are shown here to be ubiquitinated by UBE3A. The identified proteins have roles in higher mental function, long term potentiation, seizures and neurodevelopmental disorders, being involved in the BDNF, RAS/ERK and TSC/mTOR signalling pathways. A reduced ubiquitination of these proteins is expected when UBE3A levels are lower, so their identification could be key to opening novel therapeutic strategies for treating Angelman Syndrome. Further work will be required to characterize how UBE3A timely orchestrates each of these multiple regulatory events in different neuronal subtypes within the human brain.
Molecular reframing of fibroblasts during resolution of arthritis
Authors: Ramming Andreas , Rauber Simon , Mohammadian Hashem , Schmidkonz Christian , Atzinger Armin , Soare Alina , Treutlein Christoph , Kemble Samuel , Mahony Christopher , Geisthoff Manuel , Angeli Mario , Raimondo Maria , Xu Cong , Yang Kai-Ting , Lu Le , Labinsky Hannah , Saad Mina , Gwellem Charles , Kampylafka Eleni , Knitza Johannes , Distler Jörg , Hanlon Megan , Fearon Ursula , Veale Douglas , Roemer Frank , Bäuerle Tobias , Maric Hans , Maschauer Simone , Buckley Christopher , Croft Adam , Kuwert Torsten , Prante Olaf , Cañete Juan , Schett Georg 
Published: March 2023

Abstract
Fibroblasts are key orchestrators of inflammation. Little is known whether these cells change phenotype during resolution of inflammation. We adopted a method to visualise fibroblast activation during inflammation in humans in vivo, which is based on a fibroblast activation protein (FAP) tracer detected by positron emission tomography (PET). While tracer accumulation was high in active arthritis, it decreased significantly after TNF- and IL-17A inhibition. Biopsy-based scRNA-seq analyses in experimental arthritis demonstrated that FAP signal reduction reflected a phenotypic switch from pro-inflammatory MMP3+/IL6+ fibroblasts (high FAP internalisation) to pro-resolving CD200+DKK3+ fibroblasts (low FAP internalisation). Spatial transcriptomics of human joints revealed that pro-resolving niches of CD200+DKK3+ fibroblasts clustered with innate lymphoid cells (ILC)2, whereas MMP3+/IL6+ fibroblasts were co-localised with inflammatory immune cells. CD200+DKK3+ fibroblasts stabilised the ILC2 phenotype and induced resolution of arthritis via CD200/CD200R1 pathway. Taken together, these data suggest a dynamic molecular regulation of the mesenchymal compartment during resolution of inflammation.
Association of Suicidal Status, Inflammation Markers and Resting State Functional Connectivity in Patients with Major Depressive Disorder
Authors: Olié Emilie , CLAIN Guillaume , Malestroit Manon , FIEDOS Dimitri , COGNASSE Fabrice , DEVERDUN Jérémy , Bars Emmanuelle Le , Courtet Philippe 
Published: March 2023

Abstract
Suicidal ideation and attempt might have distinct neural underpinnings. Identifying the neural substrates of suicide behaviors might help to reduce suicide rates. This study wanted to identify i) neural markers of suicide attempt using resting-state functional magnetic resonance imaging (rs-fMRI), and ii) associations between rs-fMRI metrics, suicidal phenotype and peripheral blood inflammation markers. We measured inflammation markers [C-reactive protein (CRP), interleukin (IL)-1b, IL-2, IL-6, TNF-a) and rs-fMRI metrics in 20 healthy controls (HCs) and 42 patients with unipolar depression [n=21 suicide attempters (SAs) in the last 8 days and n=21 affective controls (ACs) without lifetime history of suicide]. Amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo) and Voxel-Mirrored Homotopic Connectivity (VMHC) were estimated in prefrontal cortex, anterior cingulate cortex and insula. Participants were mainly women (66.7% of HCs, 71.4% of ACs and 85% of SAs; age range 40 to 48 years). CRP (but not IL) concentration was higher in SAs than ACs and HCs. ALFF values were decreased in the pars opercularis of the inferior frontal gyrus in SAs vs. ACs and HCs, even after controlling for suicidal ideation intensity and CRP level. Suicidal ideation intensity was negatively correlated with all rs-fMRI metrics (except ReHo of left side) of this region in SAs and ACs. Inflammation markers were not correlated with the rs-fMRI metrics. Resting-state dysfunctional connectivity in regions involved in language and cognitive control is associated with suicide intensity and attempts, but not with inflammation markers.
Enhancing reliability of particulate matter sensing by multivariate Tobit model using weather and air quality data
Authors: Won Wan-Sik , Noh Jinhong , Oh Rosy , Lee Woojoo , Lee Jong-Won , Park Edward , Su Pei-Chen , Yoon Yong-Jin 
Published: March 2023

Abstract
Low-cost particulate matter (PM) sensors have been widely used following recent sensor-technology advancements; however, inherent limitations of low-cost monitors (LCMs), which operate based on light scattering without an air-conditioning function, still restrict their applicability. We propose a regional calibration of LCMs using a multivariate Tobit model with historical weather and air quality data to improve the accuracy of ambient air monitoring, which is highly dependent on meteorological conditions, local climate, and regional PM properties. Weather observations and PM2.5 (fine inhalable particles with diameters ≤ 2.5 µm) concentrations from two regions in Korea, Incheon and Jeju, and one in Singapore were used as training data to build a visibility-based calibration model. To validate the model, field measurements were conducted by an LCM in Jeju and Singapore, where R2 and the error after applying the model in Jeju improved (from 0.85 to 0.88) and reduced by 44% (from 8.4 to 4.7 µg m-3), respectively. The results demonstrated that regional calibration involving air temperature, relative humidity, and other local climate parameters can efficiently correct bias of the sensor. Our findings suggest that the proposed post-processing using the Tobit model with regional weather and air quality data enhances the applicability of LCMs.