bluuebunny/crossref_metadata_2025 huggingface dataset:
Reporting quality for abstracts of randomised trials on child and adolescent depression prevention: a meta-epidemiological study on adherence to CONSORT for abstracts
Authors: Wiehn Jascha , Nonte Johanna , Prugger Christof
Published: August 2022

Objectives

This study aimed to investigate adherence to Consolidated Standards of Reporting Trials (CONSORT) for abstracts in reports of randomised trials on child and adolescent depression prevention. Secondary objective was to examine factors associated with overall reporting quality.

Design

Meta-epidemiological study.

Data sources

We searched MEDLINE, EMBASE, PsycINFO, PsycArticles and CENTRAL.

Eligibility criteria

Trials were eligible if the sample consisted of children and adolescents under 18 years with or without an increased risk for depression or subthreshold depression. We included reports published from 1 January 2003 to 8 August 2020 on randomised controlled trials (RCTs) and cluster randomised trials (CRTs) assessing universal, selective and indicated interventions aiming to prevent the onset of depression or reducing depressive symptoms.

Data extraction and synthesis

As the primary outcome measure, we assessed for each trial abstract whether information recommended by CONSORT was adequately reported, inadequately reported or not reported. Moreover, we calculated a summative score of overall reporting quality and analysed associations with trial and journal characteristics.

Results

We identified 169 eligible studies, 103 (61%) RCTs and 66 (39%) CRTs. Adequate reporting varied considerably across CONSORT items: while 9 out of 10 abstracts adequately reported the study objective, no abstract adequately provided information on blinding. Important adverse events or side effects were only adequately reported in one out of 169 abstracts. Summative scores for the abstracts’ overall reporting quality ranged from 17% to 83%, with a median of 40%. Scores were associated with the number of authors, abstract word count, journal impact factor, year of publication and abstract structure.

Conclusions

Reporting quality for abstracts of trials on child and adolescent depression prevention is suboptimal. To help health professionals make informed judgements, efforts for improving adherence to reporting guidelines for abstracts are needed.
Ice cleat distribution programmes and ice cleat use among older adults: repeated cross-sectional evidence from 63 municipal interventions in Sweden
Authors: Holmberg Robin , Gustavsson Johanna , Svensson Mikael , Bonander Carl
Published: August 2022

Introduction

Ice cleats may help prevent ice-related falls in places with icy roads, but there is limited evidence about the association between ice cleat distribution and ice cleat use. Our study examined the association between Swedish municipal distribution programmes and ice cleat use among older adults (65+ years).

Methods

We combined data on municipal ice cleat distribution programmes (n=63) with repeated cross-sectional self-reports of ice cleat use in Sweden from 2007, 2010, 2014 and 2018. Respondents (n=63 234) were classified as exposed if they lived in a municipality with a programme, belonged to an eligible age group and responded after distribution (n=2507). Dose-response was assessed using distributed ice cleat pairs per capita (mean: 0.38). Linear probability models were used to estimate probability differences in ice cleat use between exposed and unexposed respondents, adjusting for age, sex, country of birth, education, survey wave and municipality. Ineligible age groups living in programme municipalities, who should be unaffected by ice cleat distribution, were used for bias assessment.

Results

Exposure to ice cleat distribution programmes was associated with 7.5 percentage points (95% CI 4.2 to 10.9) higher self-reported ice cleat use after confounding adjustment. The association was larger in municipalities that distributed one pair of ice cleats per capita (17.3 percentage points (95% CI 11.2 to 23.4)). No association was found among the ineligible age groups (−2.3 (95% CI −5.5 to 1.0)).

Conclusion

Distributing ice cleats to older adults may help increase their use of ice cleats in settings with icy road conditions.
Pleural plaques and risk of lung cancer in workers formerly occupationally exposed to asbestos: extension of follow-up
Authors: Gallet Justine , Laurent François , Paris Christophe , Clin Bénédicte , Gislard Antoine , Thaon Isabelle , Chammings Soizick , Gramond Celine , Ogier Guy , Ferretti Gilbert , Andujar Pascal , Brochard Patrick , Delva Fleur , Pairon Jean-Claude , Lacourt Aude
Published: August 2022

Background

Occupational asbestos exposure is associated with pleural plaques (PP), a benign disease often seen as a marker of past exposure to asbestos and lung cancer. The association between these two diseases has not been formally proved, the aim of this study was to evaluate this association in the asbestos-related disease cohort (ARDCO) cohort.

Methods

ARDCO is a French multicentric cohort including workers formerly occupationally exposed to asbestos from 2003 to 2005. CT scan was performed to diagnose PP with double reading and lung cancer (incidence and mortality) was followed through health insurance data and death certificates. Cox models were used to estimate the association between PP and lung cancer adjusting for occupational asbestos exposure (represented by cumulative exposure index, time since first exposure and time since last exposure) and smoking status.

Results

A total of 176 cases (of 5050 subjects) and 88 deaths (of 4938 subjects) of lung cancer were recorded. Smoking status was identified as an effect modifier. Lung cancer incidence and mortality were significantly associated with PP only in non-smokers, respectively, HR=3.13 (95% CI 1.04 to 9.35) and HR=16.83 (95% CI 1.87 to 151.24) after adjustment for age, occupational asbestos exposure and smoking status.

Conclusions

ARDCO study was the first to study this association considering equal asbestos exposure, and more specifically, our study is the first to test smoking as an effect modifier, so comparison with scientific literature is difficult. Our results seem to consolidate the hypothesis that PP may be an independent risk factor for lung cancer but they must be interpreted with caution.
Unveiling hidden physics at the LHC
Authors: Fischer Oliver , Mellado Bruce , Antusch Stefan , Bagnaschi Emanuele , Banerjee Shankha , Beck Geoff , Belfatto Benedetta , Bellis Matthew , Berezhiani Zurab , Blanke Monika , Capdevila Bernat , Cheung Kingman , Crivellin Andreas , Desai Nishita , Dev Bhupal , Godbole Rohini , Han Tao , Harris Philip , Hoferichter Martin , Kirk Matthew , Kulkarni Suchita , Lange Clemens , Lassila-Perini Kati , Liu Zhen , Mahmoudi Farvah , Manzari Claudio Andrea , Marzocca David , Mukhopadhyaya Biswarup , Pich Antonio , Ruan Xifeng , Schnell Luc , Thaler Jesse , Westhoff Susanne
Published: August 2022

The field of particle physics is at the crossroads. The discovery of a Higgs-like boson completed the Standard Model (SM), but the lacking observation of convincing resonances Beyond the SM (BSM) offers no guidance for the future of particle physics. On the other hand, the motivation for New Physics has not diminished and is, in fact, reinforced by several striking anomalous results in many experiments. Here we summarise the status of the most significant anomalies, including the most recent results for the flavour anomalies, the multi-lepton anomalies at the LHC, the Higgs-like excess at around 96 GeV, and anomalies in neutrino physics, astrophysics, cosmology, and cosmic rays. While the LHC promises up to 4 $$\hbox {ab}^{-1}$$

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1

of integrated luminosity and far-reaching physics programmes to unveil BSM physics, we consider the possibility that the latter could be tested with present data, but that systemic shortcomings of the experiments and their search strategies may preclude their discovery for several reasons, including: final states consisting in soft particles only, associated production processes, QCD-like final states, close-by SM resonances, and SUSY scenarios where no missing energy is produced. New search strategies could help to unveil the hidden BSM signatures, devised by making use of the CERN open data as a new testing ground. We discuss the CERN open data with its policies, challenges, and potential usefulness for the community. We showcase the example of the CMS collaboration, which is the only collaboration regularly releasing some of its data. We find it important to stress that individuals using public data for their own research does not imply competition with experimental efforts, but rather provides unique opportunities to give guidance for further BSM searches by the collaborations. Wide access to open data is paramount to fully exploit the LHCs potential.
A new perspective on quantum field theory revealing possible existence of another kind of fermions forming dark matter
Authors: Pavšič Matej
Published: July 2022

Quantum fields are considered as generators of infinite-dimensional Clifford algebra [Formula: see text], which can be either orthogonal (in the case of fermions) or symplectic (in the case of bosons). A generic quantum state can be expressed as a superposition of the basis elements of [Formula: see text], with the superposition coefficients being multiparticle complex-valued wavefunctions. The basis elements, that are products of the generators of [Formula: see text] in the Witt basis, act as creation and annihilation operators. They create positive and negative energy states that include the bare and the Dirac vacuum as special cases. It is shown that the nonvanishing electric charge arises from an extra dimension or from doubling the number of creation and annihilation operators, which brings an extra imaginary unit [Formula: see text] into the description. A further extension is to consider [Formula: see text] as one of the quaternionic imaginary units and consider a generic state as having values in the quaternionic algebra or, equivalently, in the complexified two-dimensional Clifford algebra, [Formula: see text]. It contains two distinct fundamental representations of [Formula: see text], one associated with the weak isospin doublet [Formula: see text] and the other one with the doublet of new leptons, denoted by [Formula: see text], that together with the new quarks [Formula: see text] can be identified with dark matter.
HOW APPLICABLE ARE DIGITAL MATURITY MODELS TO SMEs?: A CONCEPTUAL FRAMEWORK AND EMPIRICAL VALIDATION APPROACH
Authors: WILLIAMS CHRISTOPHER A. , SCHALLMO DANIEL , SCORNAVACCA EUSEBIO
Published: July 2022

The aim of this paper is to investigate the current landscape of digital maturity models for small- and medium-sized enterprises (SMEs) and the capabilities embedded in the models using a semi-systematic literature review and semi-structured interviews. Based on current knowledge, our research provides insights into the gaps in maturity model research for SMEs. Our primary findings show that digital maturity modelling, particular for SMEs, is currently a significant topic across several industries but remains limited by the lack of procedural properties and suitable SME-specific capabilities. This is supported by our literature review and initial interview findings. The paper offers a conceptual framework including defined criteria and essential properties. Furthermore, the paper outlines a transparency approach to empirical validation to increase the rigor of future maturity model research.
SCALE-UPS AND INTELLECTUAL PROPERTY RIGHTS: THE ROLE OF TECHNOLOGICAL AND COMMERCIALISATION CAPABILITIES IN FIRM GROWTH
Authors: SEIP MARCEL , VAN DER HEIJDEN ANNE , BAX MARLEEN
Published: July 2022

This paper studies the role of technological and commercialisation capabilities within scale-ups. Scale-ups are firms which manage to achieve an annual growth rate of at least 20% over a period of at least three years and with at least 10 employees in the beginning of the period. Based on evidence from IPR literature, we use patent filings to signal capabilities related to technological innovation and trademark filings to signal the downstream capabilities connected with the commercialisation of new products and services. By comparing the IPR flings of the top 250 scale-ups with other scale-ups and non-scale-up firms, this paper provides evidence that commercialisation capabilities contribute more to the growth of these firms than technological capabilities. Scale-ups tend to file trademarks already at a young age indicating that these capabilities are already present when these firms start off whereas patents are filed later on.
Safe Assets at Financial Globalization
Authors: Hung Ly Dai
Published: July 2022

The paper explores the impact of safe assets on the economic growth on the financial globalization context. The method employs both cross-section and panel data regression on a data sample of 148 economies, both advanced and developing ones, over the 1990–2019 period. The robustness analysis is carried out by controlling for different sub-sampling data, including advanced economies compared with emerging and developing economies, and 3 consecutive 10-year periods from 1990 to 2019. The empirical evidence establishes an inverted-U-shaped dependence pattern of economic growth on the assets safety, measured by the sovereign debts rating. The economic growth is first increasing then decreasing on the assets safety, with the turning point being the value at 12.0 of sovereign debts rating. Thus, the assets safety only exerts a positive impact on the economic growth for the low safety level.
A LINKAGE BETWEEN THE FINANCIAL AND THE REAL ECONOMY
Authors: REY SEBASTIÁN A.
Published: July 2022

The aim of this paper is to present a linkage between the real economy (micro and macro) and the financial economy. This relationship is obtained from the non-arbitrage valuation of equities framework. The paper also investigates if this theoretical relationship is actually observed. For this purpose, it proposes and tests an empirical model for excess returns that includes the linkage as a crucial element. The actual observation of the linkage could be of special importance for the financial economics discipline, since it presents several features that are not usually seen in other asset pricing or macro-finance models: (a) the relationship is explicit and does not depend on the estimation of free parameters; (b) it is derived under arbitrage free arguments and does not introduce subjective concepts as utility function or risk aversion; and (c) it explains the observed level of equity risk premium without entering in contradiction with its theoretical foundations. The conclusions of the performed tests are in favor of the concepts provided by the framework, meaning that further research could offer an alternative understanding of the behavior of financial markets and their connection with the real economy.
Palaeomagnetic evidence for the age of the Stornoway Formation
Authors: Storetvedt K. M. , Steel R. J.
Published: August 2022

Synopsis

A palaeomagnetic study of material from the lowermost and most fine-grained layers of the Stornoway sediments suggests a late Permian-Triassic age for this formation. This supports recent suggestions that the Stornoway Formation may be an onshore representative of the many deep Mesozoic basins recently discovered in surrounding coastal waters.
Pseudocapacitive Charge Storage in Electrochromic Transition-Metal Oxide Thin Films
Authors: Dong Dongmei , Benhaddouch Tinsley Elizabeth , Metler Christopher Lloyd , Marcial John , Zhao Yaoli , Venkadesh Vagheeswari , Thundat Thomas , Bhansali Shekhar
Published: August 2022

Electrochromic pseudocapacitive transition-metal oxide materials, such as tungsten oxide, which combine fast response, high energy density, and optical effects, can play a significant role as energy storage materials. Here we investigate the electrochemical kinetics of thin films of tungsten oxide, which turn transparent to sky-blue color in the lithiated state due to the reduction of W6+ to W5+. We investigated the charge density, charge transfer, ion diffusion, and interfacial behavior upon Li+ insertion/de-insertion in WO3. The electrochromic thin film’s pseudocapacitive and electrical double layer mechanism was differentiated based on the power-law. Faradaic diffusion-controlled process dominates over the surface capacitive behavior at scan rates below 40 mV s−1. These films exhibit an areal charge density of around 100 mC cm−2 and a capacitance of 80 mF cm−2, superior to most comparable electrochromic materials and supercapacitors. This work combines electrochromics and energy storage properties and provides a fundamental understanding of pseudocapacitive and electrochromic mechanisms in WO3.
A Ceramic Rich Quaternary Composite Solid-State Electrolyte for Solid-State Lithium Metal Batteries
Authors: Al-Salih Hilal , Cui Mengyang , Yim Chae-Ho , Sadighi Zoya , Yan Shuo , Karkar Zouina , Goward Gillian R. , Baranova Elena A. , Abu-Lebdeh Yaser
Published: August 2022

Solid-state lithium metal batteries are one of the most promising candidates to take over the traditional liquid-based lithium ion batteries as they not only allow us to circumvent safety issues but also boost energy density far over the current limits imposed by the present chemistries. We have recently demonstrated that the combination of highly conductive inorganic solid electrolyte (ISE), Li0.33La0.55TiO3 (LLTO), with the mechanically durable solid polymer electrolyte (SPE), polyethylene oxide: Lithium bis(trifluoromethanesulfonyl)imide (PEO:LiTFSI), alongside a solid plasticizer, Succinonitrile, has proved to be successful in making highly performing polymer-rich (70% polymer) quaternary composite solid electrolytes (CSEs) that evade both the brittleness of ceramics and the poor conductivity of polymers. Herein, we extend the work to ceramic rich quaternary CSEs (70% ceramic). Ceramic-rich films were fabricated using tape casting technique and have reasonable ionic conductivity of 1.5 × 10−4 S cm−1 at 55 °C, decent mechanical properties and displays impressive endurance in Li ∣∣ Li symmetrical cells (> 800 h). Solid-state coin-type cells assembled with composite cathode show satisfactory cycling performance at 0.05 C and 55 °C reaching specific discharge capacity of 160.6 mAh g−1, maintaining high Coulombic efficiency (> 95%) and high capacity retention of 90.3% after 30 cycles.
BattPhase—A Convergent, Non-Oscillatory, Efficient Algorithm and Code for Predicting Shape Changes in Lithium Metal Batteries Using Phase-Field Models: Part I. Secondary Current Distribution
Authors: Jang Taejin , Mishra Lubhani , Roberts Scott A. , Planden Brady , Subramaniam Akshay , Uppaluri Maitri , Linder David , Gururajan Mogadalai P. , Zhang Ji-Guang , Subramanian Venkat R.
Published: August 2022

Electrochemical models at different scales and varying levels of complexity have been used in the literature to study the evolution of the anode surface in lithium metal batteries. This includes continuum, mesoscale (phase-field approaches), and multiscale models. Thermodynamics-based equations have been used to study phase changes in lithium batteries using phase-field approaches. However, grid convergence studies and the effect of additional parameters needed to simulate these models are not well-documented in the literature. In this paper, using a motivating example of a moving boundary model in one- and two-dimensions, we show how one can formulate phase-field models, implement algorithms for the same and analyze the results. An open-access code with no restrictions is provided as well. The article concludes with some thoughts on the computational efficiency of phase-field models for simulating dendritic growth.
Communication—Sustainable Starfish-Derived N-Doped Porous Carbon for High-Performance Electric Double Layer Capacitors
Authors: Hong Tae Hwa , Lee Yoon Hak , Jang Hyeonji , Lee Jung Tae
Published: August 2022

Electric double layer capacitors can be used in broad applications, including portable electronics, high power tools, and transportation. However, such systems require more sustainable materials and a boosting of their electrochemical performance. In this study, starfish, as an unusable destroyer of marine ecosystems, are transformed into functional nitrogen-doped carbon materials with high porosity toward high-performance EDLC electrodes. The synthesized starfish-derived carbon exhibits a surface area of up to 3122 m2 g−1, a specific capacitance of up to 295.7 F g−1 at a current density of 0.5 A g−1, and capacitance retention of 81.5% upon an increase in current density from 0.5 to 10 A g−1.
Preparation of 3D Printing PLGA Scaffold with BMP‐9 and P‐15 Peptide Hydrogel and Its Application in the Treatment of Bone Defects in Rabbits
Authors: Wang Xiaomei , Chen Wanjun , Chen Zhe , Li Yixiu , Wu Kai , Song Yulin
Published: July 2022

Objective. To prepare a three‐dimensional (3D) printing polylactic acid glycolic acid (PLGA) scaffold with bone morphogenetic protein‐9 (BMP‐9) and P‐15 peptide hydrogel and evaluate its application in treating bone defects in rabbits. Methods. 3D printing PLGA scaffolds were formed and scanned by electron microscopy. Their X‐ray diffraction (XRD), in vitro degradation, and compressive strength were characterized. BMP‐9 and P‐15 hydrogels were prepared. Flow cytometry was used to detect apoptosis, and an electron microscope was used to evaluate cell adhesion to scaffolds. Alkaline phosphatase (ALP), type 1 collagen (Col‐I), osteocalcin (OCN), runt‐related transcription factor 2 (RUNX2), and osterix (SP7) were detected by western blotting. MicroCT was used to detect new bone formation, and bone tissue‐related protein expressions were determined in the rabbit model with bone defects. Results. The 3D printing scaffolds were cylindrical, and the inner diameter of the scaffolds was about 1 mm. The bread peak with wide distribution showed that the 3D printing only involved a physical change, which did not change the properties of the materials. The degradation rate of scaffolds was 9.38%, which met the requirements of properties of biological scaffolds. The water absorption of the support was about 9.09%, and the compressive strength was 15.83 N/mm2. In the coculture of bone marrow mesenchymal stem cells (BMSCs) with scaffolds, the 2% polypeptide hydrogel showed the most obvious activity in promoting the differentiation of BMSCs. Flow cytometry showed that the 0% and 2% groups did not cause obvious apoptosis compared with the control group. Scaffolds with 2% and 4% polypeptide promoted the expression of ALP, COL‐1, OCN, RUNX2, and Sp7 in BMSCs. In vivo experiments showed that the expression of ALP, COL‐1, OCN, RUNX2, and Sp7 protein in the 2% polypeptide scaffold group increased significantly compared with the model group. MicroCT detection demonstrated that the 2% polypeptide scaffold had good bone repair ability. Conclusion. The PLGA scaffolds combined with BMP‐9 and P‐15 peptide hydrogels had good biological and mechanical properties and could repair bone defects in rabbits.
[Retracted] Big Data Analysis of Manufacturing and Preclinical Studies of Nanodrug‐Targeted Delivery Systems: A Literature Review
Authors: Cao Qiang , Li Xiaochen , Zhang Qi , Zhou Kexuan , Yu Ying , He Zixu , Xiang Zhibiao , Qiang Yi , Qi Wei
Published: July 2022

Objective. Nanodelivery is a modern technology involving improved delivery methods and drug formulations. The current development and initial applications of nanocarriers are pointing to new directions in the current development of nanomedicine. Researchers are increasingly applying nanodelivery to the delivery of therapeutic or diagnostic agents. This article discusses the preparation and application of nanocomplexes and nanoparticles, as well as their potential future value in clinical research. Through a review and analysis, it is hoped that this will serve as a guide for the future development of various nanodelivery technologies and help researchers learn more about these technologies. Materials and Methods. A literature search was conducted using the keywords “Nano drug delivery” or “Nanomedical materials” or “Nano”. A literature search was conducted in three major databases, PubMed, Web of Science, and Google Scholar, using the keywords such as “Nano drug delivery”, “Nanomedical materials”, or “Nanobubble drug delivery”. The initial search was screened by title and abstract. In the full‐text review, the titles or abstracts were reviewed according to the selection criteria based on the inclusion criteria. The risk of bias and study quality was assessed according to the Cochrane guidelines, and possible biases such as selection bias and good selection bias were included in the review. Results. A total of 297 studies were included in this study, of which 219 were excluded based on the screening criteria, resulting in the inclusion of 78 studies, the majority of which were original studies and clinical trials, and a small number of which provided design and route of administration analysis of nanomaterial particles and effect fluorograms and were studied in more depth. This paper summarises and reviews the views and directions of the included articles. The main directions include cyclodextrin‐based or grafted cyclodextrin nanomaterials, nanobubbles, and stimuli‐sensitive and temperature‐sensitive nanodelivery systems. Conclusion. The use of innovative, targeted drug delivery systems is effective in cancer drug delivery by summarising the previous studies. However, nanodelivery systems’ risks and therapeutic effects need to be evaluated before clinical application. Future research in the field of targeted drug delivery nanosystems should focus on the development of nanocarriers with high in vivo delivery capacity, good synergy with therapeutic agents, and milder short‐term and long‐term toxicological effects and conduct comprehensive preclinical trials on nanodrug delivery systems with high potential for clinical application as soon as possible, to find nanodrug delivery systems suitable for clinical use and put them into the clinical application as soon as possible.
Water Quality Prediction Based on SSA-MIC-SMBO-ESN
Authors: Kang Yan , Song Jinling , Lin Zhuo , Huang Liming , Zhai Xiaoang , Feng Haipeng
Published: August 2022

Water pollution threatens the safety of human production and life. To quickly respond to water pollution, it is important for water management staff to predict water quality changes in advance. Drawing on the temporality of water quality data, the leaky integrator echo state network (ESN) was introduced to construct the water quality prediction models for dissolved oxygen (DO), permanganate index (CODMn), and total phosphorus (TP), respectively. First, the missing values were filled by the linear trend method of adjacent points, and the outliers were detected and corrected by the Z-score method and the linear trend method. Second, the singular spectrum analysis (SSA) was performed to denoise the original monitoring data, such that the predicted data catch up with the real data, and the model accuracy is not affected by the hidden noise in the data. Third, the correlation between water quality indices was measured by the maximum information coefficient (MIC), and the strongly correlated indices were imported to the prediction model. Finally, according to these strong correlation indicators, the water quality prediction models based on multiple features were constructed, respectively, using the offline and online learning algorithms of the ESN. The hyperparameters of the models were optimized through the sequential model-based optimization (SMBO). Experimental results show that the proposed water quality prediction models, namely, SSA-MIC-SMBO-Offline ESN and SSA-MIC-SMBO-Online ESN, predicted DO, CODMn, and TP accurately, providing suitable tools for practical applications.
Optimization and Analysis of Intelligent Accounting Information System Based on Deep Learning Model
Authors: Feng Suzhen , Zhong Ran
Published: July 2022

Accounting information often accounts for more than 70% of an enterprise’s financial report information. Accounting information is an important reference for an enterprise to make major decisions, and it is also the fundamental guarantee for an enterprise to remain invincible under the increasingly fierce business competition. With the vigorous development of enterprise informatization, traditional accounting information processing methods can no longer meet the needs of the information age. Therefore, an excellent enterprise must have a complete set of intelligent accounting information systems. How to extract the information we want from the dazzling accounting information data is a hot topic in the current financial industry. On the basis of analyzing the significance of establishing an information system, this paper creates an intelligent recognition model, which solves the shortcomings of traditional methods such as large calculation errors, time-consuming, and labor-intensive. The research results of the article show that (1) the standardized coefficients of the four influencing factors of CSR, ROE, CEO, and SCALE are relatively large, indicating that these four influencing factors have a significant impact on the development of corporate accounting and you can pay attention to these four aspects. (2) To test the performance of the article model, the experiments are compared with other models. The results show that the model proposed in this paper has the highest running success rate on the two test sets, with a success rate of more than 98%, indicating that the model in this paper has certain advantages in accounting information processing. (3) In the page response time experiment, the financial module has the shortest response time, the number of tests is 60 times, the average response time is 0.5 s, and the success rate can reach 100%. It can reach 0.8 s, and the success rate can be kept above 98%, indicating that the system can work normally. In the system operation stability test, the number of test cases designed for the financial module is 70, the number of executed test cases is 70, and the execution rate can reach 100%. This means that the system can work properly and will not fail during operation.
CO2 Electroreduction in Organic Aprotic Solvents: A Mini Review
Authors: Kuntyi Оrest , Zozulya Galyna , Shepida Mariana
Published: July 2022

An annual increase of CO2 concentrations in the atmosphere causes global environmental problems, addressed by systematic research to develop effective technologies for capturing and utilizing carbon dioxide. Electrochemical catalytic reduction is one of the effective directions of CO2 conversion into valuable chemicals and fuels. The electrochemical conversion of CO2 at catalytically active electrodes in aqueous solutions is the most studied. However, the problems of low selectivity for target products and hydrogen evolution are unresolved. Literature sources on CO2 reduction at catalytically active cathodes in nonaqueous mediums, particularly in organic aprotic solvents, are analyzed in this article. Two directions of cathodic reduction of CO2 are considered—nonaqueous organic aprotic solvents and organic aprotic solvents containing water. The current interpretation of the cathodic conversion mechanism of carbon (IV) oxide into CO and organic products and the main factors influencing the rate of CO2 reduction, Faradaic efficiency of conversion products, and the ratio of direct cathodic reduction of CO2 are given. The influence of the nature of organic aprotic solvent is analyzed, including the topography of the catalytically active cathode, values of cathode potential, and temperature. Emphasis is placed on the role of water impurities in reducing CO2 electroreduction overpotentials and the formation of new CO2 conversion products, including formate and H2.
Association of GAB2 with Quality of Life and Negative Emotions in Patients with Gastric Cancer after Postoperative Comprehensive Care
Authors: Zhuang Juping , Yu Jiejie , Yang Yanchu
Published: July 2022

GRB2-associated binding protein 2 (GAB2), a highly conserved scaffold protein, is abnormally expressed and activated in patients with gastric cancer (GC). However, the genetic diversity of GAB2 in GC and its association with the clinical manifestations of patients are still unclear. Here, we explored the polymorphism of GAB2 rs2373115 in GC and its association with quality of life (QOL) and negative emotions of patients with GC after postoperative comprehensive care. A case-control study showed that the frequency of the GG genotype of GAB2 rs2373115 in the GC patients was higher than that in the healthy people, while the frequency of the TT + TG genotype was lower than that in the healthy people. Obvious distinctions were observed in the histological grade and TNM staging between the GG genotype and TT + TG genotype. In addition, SAS and SDS scores in the patients with GG genotype were higher than those in patients with TT + TG genotype, while the emotional function, cognitive function, dyspnea, fatigue, sleep disorder, and overall QOL in patients with GG genotype were lower than those in patients with TT + TG genotype. These results showed that GAB2 rs2373115 polymorphism was related to QOL and negative emotions in patients with GC after postoperative comprehensive care.
Evaluation of Cultural Value Validity of Digital Media Art Based on Locally Weighted Fitting Algorithm
Authors: Wu Yuelin , Li Donghong , Feng Fan
Published: July 2022

Digital media art differs from other forms of existence in the intersection of digital technology and art, and this new form of existence contains its unique value. Digital media art education crosses the disciplines of art, computer science, and technology and builds a new perspective that can encompass the academic discourse of literature and science, transcending the opposition between scientific and humanistic cultures and creating a broader knowledge structure and a new view of values and resources. In this paper, we use image quality evaluation based on local Gaussian weighted fusion and image collocation for restoration of precious cultural relics and images to realize their cultural values, in view of the current problems such as damage caused by a large number of precious paintings due to improper preservation and other problems.
Microglia Involves in the Immune Inflammatory Response of Poststroke Depression: A Review of Evidence
Authors: Xia Weili , Xu Yong , Gong Yuandong , Cheng Xiaojing , Yu Tiangui , Yu Gongchang
Published: August 2022

Poststroke depression (PSD) does not exist before and occurs after the stroke. PSD can appear shortly after the onset of stroke or be observed in the weeks and months after the acute or subacute phase of stroke. The pathogenesis of PSD is unclear, resulting in poor treatment effects. With research advancement, immunoactive cells in the central nervous system, particularly microglia, play a role in the occurrence and development of PSD. Microglia affects the homeostasis of the central nervous system through various factors, leading to the occurrence of depression. The research progress of microglia in PSD has been summarized to review the evidence regarding the pathogenesis and treatment target of PSD in the future.
X-Ray Small Target Security Inspection Based on TB-YOLOv5
Authors: Wang Muchen , Zhu Yueming , Liu Yongkang , Deng Huiping
Published: August 2022

Security inspection is extremely important for the safety of public places. In this research, we are trying to propose a novel algorithm and investigated theoretically in the X-ray dataset, which can optimize the relative low detection accuracy and the latent omission detection of smaller objects when using You Only Look Once version 5 (YOLOv5). For one side, the transform detection network is selected to be added at the bottom layer of backbone structure to avoid the loss of useful information during sequential calculation. On another side, we attempt to adjust the existing PANet structural elements of the model, including their connections and other related parameters to improve the detection performance. We integrate an efficient BiFPN with the CA mechanism, which can enhance feature extraction, and named it attention-BiFPN. Experimental consequences demonstrate that the detection accuracy of the proposed model, which we name “TB-YOLOv5,” has obvious advantages in check performance compared with the mainstream one-stage object detection models. Meanwhile, compared with YOLOv5, the data results display an improvement of up to 14.9%, and the average precision at 0.5 IOU even reached 23.4% higher in the region of small object detection. Our purpose was to explore the potential of changing a popular detection algorithm such as YOLO to address specific tasks and provide insights on how specialized adjustments can influence the detection of small objects. Our work can supply an effective method of enhancing the performance of X-ray security inspection and show promising potential for deep learning in related fields.
Machine Learning to Assess Relatedness: The Advantage of Using Firm‐Level Data
Authors: Albora Giambattista , Zaccaria Andrea
Published: July 2022

The relatedness between a country or a firm and a product is a measure of the feasibility of that economic activity. As such, it is a driver for investments at a private and institutional level. Traditionally, relatedness is measured using networks derived by country‐level co‐occurrences of product pairs, that is counting how many countries export both. In this work, we compare networks and machine learning algorithms trained not only on country‐level data, but also on firms, which is something not much studied due to the low availability of firm‐level data. We quantitatively compare the different measures of relatedness, by using them to forecast the exports at the country and firm level, assuming that more related products have a higher likelihood to be exported in the future. Our results show that relatedness is scale dependent: the best assessments are obtained by using machine learning on the same typology of data one wants to predict. Moreover, we found that while relatedness measures based on country data are not suitable for firms, firm‐level data are very informative also for the development of countries. In this sense, models built on firm data provide a better assessment of relatedness. We also discuss the effect of using parameter optimization and community detection algorithms to identify clusters of related companies and products, finding that a partition into a higher number of blocks decreases the computational time while maintaining a prediction performance well above the network‐based benchmarks.
Analysis of China’s Regional Economic Competitiveness, Regionalization, and Spatial Aggregation Characteristics Based on Density Clustering Algorithm
Authors: He Jinglin , Liu Rixing
Published: August 2022

Regional development disparities, especially in developing countries, have traditionally been one of the central issues of empirical research in regional economics. However, this rapid change is accompanied by profound changes in the spatial distribution of economic activities in China, the formation of regional economic “blocks,” the widening of regional disparities, and the geographical concentration of economic growth efficiency are important issues highlighted in this change. Therefore, it is important to explore the spatial clustering characteristics and patterns of regional economic growth to provide a scientific basis for relevant government departments to formulate reasonable regional development strategies and promote the balanced and stable development of economic growth. Clustering analysis is an important research topic in the field of data mining, which is used to discover unknown object classes in large-scale data sets. This paper proposes a density-clustering algorithm based on the regional economic competitiveness of China and analyzes its spatial aggregation characteristics. From the perspective of spatial structure theory, economic development is a dynamic process, and to optimize the spatial pattern of China’s regional economic development and improve the efficiency of economic interaction between regions, it is necessary to fully exploit the diffusion and trickle-down effects of important growth poles in the region to the surrounding areas. The experimental results show that the error rate of KSNN is very small, and the error rate of K-means and PSO has increased to a certain extent. Therefore, it can be obtained that the density-clustering algorithm based on the regional economic competitiveness zoning method in China can find out the correct clustering results without the given clustering individual cases. Thus, it is important to grasp the current situation of regional economic agglomeration and reveal the driving factors of agglomeration formation to promote the coordinated development of regional economy and guide the spatial layout of economic development.
Long Noncoding RNA HLA Complex Group 18 Improves the Cell Proliferation of Myocardial Fibroblasts by Regulating the Hsa-microRNA-133a/Epidermal Growth Factor Receptor Axis
Authors: Shi Huoshun , Sun Lebo , Zheng Dawei , Xu Guodong , Shao Guofeng
Published: July 2022

Hsa-microRNA (has-miR)-133a inactivates the extracellular signal-regulated kinase 1/2 (ERK1/2) pathway and suppresses the cell proliferation of myocardial fibroblasts by downregulation of the epidermal growth factor receptor (EGFR) expression. Bioinformatics analysis exhibits extended noncoding RNA HLA complex group 18 (lncRNA-HCG18) binds to hsa-miR-133a. The purpose of the current experiment is to explore whether lncRNA-HCG18 adsorbed hsa-miR-133a through sponging, resulting in decreased inhibition of hsa-miR-133a on EGFR and ultimately promoting the proliferation of myocardial fibroblasts. To verify and study the correlation and mechanism between lncRNA-HCG18, hsa-miR-133a, and their target genes. Firstly, after overexpression/silencing of lncRNA-HCG18 in myocardial fibroblasts, the level of hsa-miR-133a expression was evaluated by quantitative reverse transcription-polymerase chain reaction (RT-qPCR), and the EGFR, ERK1/2, and p-ERK1/2 expression levels were assessed by Western blotting to confirm that upregulation of EGFR and p-ERK1/2 protein levels by overexpression of lncRNA-HCG18, siRNA lncRNA-HCG18 (siHCG18) reduced the EGFR and p-ERK1/2 protein levels. Then, the luciferase reporter gene system was used to verify that lncRNA-HCG18 regulated EGFR expression by inhibiting the function of the hsa-miR-133a regulatory target gene. Then, a RAP assay was used to confirm that lncRNA-HCG18 interacted with hsa-miR-133a. Finally, the analysis of CCK-8 results indicated that the cell proliferation of myocardial fibroblasts was significantly reduced by siHCG18 while reversed by overexpression of lncRNA-HCG18. Thus, lncRNA-HCG18 inhibited cell viability of cardiac fibroblasts via the hsa-miR-133a/EGFR axis, which was regarded as a regulator of cell proliferation of cardiac fibroblasts in cardiovascular diseases.
Gait Recognition Based on the Plantar Pressure Data of Ice and Snow Athletes
Authors: Wu Fengyu , Li Xingyang , Zhao Wenyan , Ning Bowen
Published: July 2022

The study of plantar pressure has become a research consensus in the field of biomechanics. The purpose of this paper is to study some lower limb movements in the daily activities of ice and snow athletes to obtain relevant data so as to carry out gait recognition analysis research. This paper selects the average foot pressure, forefoot foot pressure, front and rear foot pressure, foot pressure, toe pressure, 2–5 toe pressure, standing with eyes closed, x- and y-axes speed, foot length, foot width, and other actions of ice and snow athletes. Therefore, correlation analysis, work analysis, and curve fitting analysis were carried out on the joint motion in a single gait cycle. The collection and application of foot pressure and foot posture information are also analyzed. According to the plantar structure, the sole is divided into four parts. The maximum pressure point and coordinates of each part, the pressure center point, the ratio of the width and height of the sole of the foot, and so on are extracted as the haptic features of the gait. The experimental data shows that it can be seen that if the plantar area is divided in advance and the weight of each area is marked, whether standing, walking, or standing with one leg closed eyes can achieve better recognition results, and the accuracy rate is all more than 90 percent. The average recognition accuracy rate using the method of dividing four regions is only about 80%, and the accuracy rate of recognition using the method of dividing eight regions is 82%. It can be seen that the features extracted by the FCM model proposed in this paper contain more information of the plantar pressure image, and the accuracy rate is higher in the classification and recognition.
Numerical Simulation of Smoke Control in Underground Space
Authors: Yao Hao-wei , Li You-xin , Lv Ke-feng , Zhang Jin-guang , Lv Zhong-bin , Wang Dong , Zhan Zhen-yu , Wei Xiao-ge , Song Huai-tao , Qin Heng-jie
Published: July 2022

As the underground space is relatively closed compared to other buildings, the space is hardly connected to the outside world through entrances and exits, which makes it difficult to ventilate and exchange heat with the outside. In this case, it is easy to cause a large number of casualties when a fire breaks out. When the fire happens smoke will be discharged merely by the mechanical exhaust, and air system should work simultaneously to replenish the oxygen inside. By setting four-group models, the paper analyzes the strategies for smoke extraction and air makeup in the underground construction. The paper points out that when the fire happens in a smoke bay, the neighborhood smoke extraction fan should be opened and the air makeup system should not be located at the top to disturb the smoke layer. By comparing and analyzing the performance of the smoke extraction and air conditioning system, the casualties caused by the high temperature toxic smoke from the fire can be reduced as far as possible.
A Protocol-Independent Botnet Detection Method Using Flow Similarity
Authors: Liang Jianbing , Zhao Shuang , Chen Shuhui
Published: July 2022

The detection of botnets has always been a hot spot in the field of network security. However, there are still many challenges in botnet detection. Most of the current botnet detection approaches, such as machine learning and blacklists, cannot discover evolving botnet variants. These methods are usually only valid for specific botnet protocols which are not general. Even they may be difficult to deal with encrypted botnet traffic. In this paper, we design a protocol-independent botnet detection method for these challenges. Our detection method takes advantage of the group characteristic of the botnet, which is the inherent characteristics of the botnet. We use the sequence of packet length as the characteristic of a flow. Then, we calculate the similarity between these sequences to detect botnets. Our method has an excellent generality, which is not affected by encrypted traffic and the protocols of the botnet. Experiments on a challenging dataset ISCX show that the proposed method can effectively detect botnets with a high average detection rate and low false alarm, which significantly outperforms the state-of-the-art methods. Therefore, the proposed detection method is robust and has a wide range of adaptability in detecting botnets.