bluuebunny/crossref_metadata_2025 huggingface dataset:
Interleukin (IL) 16: a candidate urinary biomarker for proliferative lupus nephritis
Authors: Häyry Aliisa , Faustini Francesca , Zickert Agneta , Larsson Anders , Niewold Timothy B , Svenungsson Elisabet , Oke Vilija , Gunnarsson Iva
Published: September 2022

Objective

Lupus nephritis (LN) is a severe manifestation of systemic lupus erythematosus (SLE). The pathogenesis is incompletely understood and diagnostic biomarkers are scarce. We investigated interleukin (IL) 16 as a potential biomarker for LN in a well-characterised cohort of patients with SLE.

Methods

We measured urinary (u-) and plasma (p-) levels of IL-16 in predefined patient groups using ELISA: LN (n=84), active non-renal SLE (n=63), inactive non-renal SLE (n=73) and matched population controls (n=48). The LN group included patients with recent biopsy-confirmed proliferative (PLN, n=47), mesangioproliferative (MES, n=11) and membranous (MLN, n=26) LN. Renal expression of IL-16 was investigated by immunohistochemistry. Associations between IL-16 measurements and clinical parameters and the diagnostic value for LN were explored.

Results

p-IL-16 was detected in all investigated cases and high p-IL-16 levels were observed in patients with active SLE. u-IL-16 was detected (dt-u-IL-16) in 47.6% of patients with LN, while only up to 17.8% had dt-u-IL-16 in other groups. In the LN group, 68% of patients with PLN had dt-u-IL-16, while the proportions in the MLN and MES groups were lower (11.5% and 45.5%, respectively). The highest u-IL-16 levels were detected in the PLN group. In the regression model, u-IL-16 levels differentiated PLN from other LN patient subgroups (area under the curve 0.775–0.896, p<0.0001). dt-u-IL-16 had superior specificity but slightly lower sensitivity than elevated anti-double-stranded DNA and low complement C3 or C4 in diagnosing PLN. A high proportion of LN kidney infiltrating cells expressed IL-16.

Conclusions

We demonstrate that detectable u-IL-16 can differentiate patients with PLN from those with less severe LN subtypes and active non-renal SLE. Our findings suggest that u-IL-16 could be used as a screening tool at suspicion of severe LN. Furthermore, the high IL-16 levels in plasma, urine and kidney tissue imply that IL-16 could be explored as a therapeutic target in SLE.
Valvular disease burden in the modern era of percutaneous and surgical interventions: the UK Biobank
Authors: Tung Monica , Nah Gregory , Tang Janet , Marcus Greg , Delling Francesca N
Published: September 2022

Background

The burden of valvular heart disease (VHD) has increased significantly among ageing populations, yet remains poorly understood in the present-day context of percutaneous and surgical interventions.

Objective

To define the incidence, clinical correlates and associated mortality of VHD in the UK Biobank cohort.

Methods

We interrogated data collected in the UK Biobank between 1 January 2000 and 30 June 2020. VHD incidence was determined using International Classification of Disease-10 codes for aortic stenosis (AS), aortic regurgitation (AR), mitral stenosis, mitral regurgitation (MR) and mitral valve prolapse. We calculated HRs for incident VHD and all-cause mortality. Clinical correlates of VHD included demographics, coronary artery disease, heart failure and atrial fibrillation. Surgical and percutaneous interventions for mitral and aortic VHD were considered time-dependent variables.

Results

Among 486 187 participants, the incidence of any VHD was 16 per 10 000 person-years, with highest rates for MR (8.2), AS (7.2) and AR (5.0). Age, heart failure, coronary artery disease and atrial fibrillation were significantly associated with all types of VHD. In our adjusted model, aortic and mitral VHD had an increased risk of all-cause death compared with no VHD (HR 1.62, 95% CI 1.44 to 1.82, p<0.001 and HR 1.25, 95% CI 1.09 to 1.44, p=0.002 for aortic and mitral VHD, respectively).

Conclusion

VHD continues to constitute a significant public health burden, with MR and AS being the most common. Age and cardiac comorbidities remain strong risk factors for VHD. In the modern era of percutaneous and surgical interventions, mortality associated with VHD remains high.
How do multiple long-term conditions impact on the cost-of-illness in early rheumatoid arthritis?
Authors: Hsieh Ping-Hsuan , Geue Claudia , Wu Olivia , McIntosh Emma , Siebert Stefan
Published: September 2022

Objective

Multiple long-term conditions (MLTCs) are prevalent in rheumatoid arthritis (RA) and associated with worse outcomes and greater economic burden. However, little is known about the impact of MLTCs on the cost-of-illness (COI) in early RA, including direct and indirect costs. The objective of this study was to quantify this impact on COI.

Methods

The Scottish Early Rheumatoid Arthritis study is a national cohort of adults with new-onset RA. Direct costs were estimated applying relevant unit costs to health resource utilisation; indirect costs were measured by productivity loss due to health conditions. Two-part models were used, adjusting for age, gender, baseline functional disability and health-related quality of life. The Charlson Comorbidity Index score was calculated using ICD-10 diagnoses. Individuals were defined as ‘RA alone’, ‘RA plus LTC’ and ‘RA plus MLTCs’ according to the number of coexisting LTCs.

Results

Data were available for 818 participants. Average annualised direct costs incurred by people with early RA plus MLTCs (£4444; 95% CI £3100 to £6371) were twice as, and almost five times higher than, those with a single LTC (£2184; 95% CI £1596 to £2997) and those without LTC (£919; 95% CI £694 to £1218), respectively. Indirect costs incurred by RA plus MLTCs (£842; 95% CI £377to £1521) were 3.1 times higher than RA alone (£530; 95% CI £273to £854). The relative proportion of direct costs increased with LTC category, ranging from 77.2% to 84.1%. In addition to increased costs with LTCs, costs also increased with age and were higher for men regardless of LTC category.

Conclusions

MLTCs impact on COI early in the course of RA. The presence of LTCs is associated with significant increases in both direct and indirect costs among people with early RA.
Prolonged COVID-19 symptom duration in people with systemic autoimmune rheumatic diseases: results from the COVID-19 Global Rheumatology Alliance Vaccine Survey
Authors: DiIorio Michael , Kennedy Kevin , Liew Jean W , Putman Michael S , Sirotich Emily , Sattui Sebastian E , Foster Gary , Harrison Carly , Larché Maggie J , Levine Mitchell , Moni Tarin T , Thabane Lehana , Bhana Suleman , Costello Wendy , Grainger Rebecca , Machado Pedro M , Robinson Philip C , Sufka Paul , Wallace Zachary S , Yazdany Jinoos , Gore-Massy Monique , Howard Richard A , Kodhek More A , Lalonde Nadine , Tomasella Laura-Ann , Wallace John , Akpabio Akpabio , Alpízar-Rodríguez Deshiré , Beesley Richard P , Berenbaum Francis , Bulina Inita , Chock Eugenia Yupei , Conway Richard , Duarte-García Alí , Duff Eimear , Gheita Tamer A , Graef Elizabeth R , Hsieh Evelyn , El Kibbi Lina , Liew David FL , Lo Chieh , Nudel Michal , Singh Aman Dev , Singh Jasvinder A , Singh Namrata , Ugarte-Gil Manuel F , Hausmann Jonathan S , Simard Julia F , Sparks Jeffrey A
Published: September 2022

Objective

We investigated prolonged COVID-19 symptom duration, defined as lasting 28 days or longer, among people with systemic autoimmune rheumatic diseases (SARDs).

Methods

We analysed data from the COVID-19 Global Rheumatology Alliance Vaccine Survey (2 April 2021–15 October 2021) to identify people with SARDs reporting test-confirmed COVID-19. Participants reported COVID-19 severity and symptom duration, sociodemographics and clinical characteristics. We reported the proportion experiencing prolonged symptom duration and investigated associations with baseline characteristics using logistic regression.

Results

We identified 441 respondents with SARDs and COVID-19 (mean age 48.2 years, 83.7% female, 39.5% rheumatoid arthritis). The median COVID-19 symptom duration was 15 days (IQR 7, 25). Overall, 107 (24.2%) respondents had prolonged symptom duration (≥28 days); 42/429 (9.8%) reported symptoms lasting ≥90 days. Factors associated with higher odds of prolonged symptom duration included: hospitalisation for COVID-19 vs not hospitalised and mild acute symptoms (age-adjusted OR (aOR) 6.49, 95% CI 3.03 to 14.1), comorbidity count (aOR 1.11 per comorbidity, 95% CI 1.02 to 1.21) and osteoarthritis (aOR 2.11, 95% CI 1.01 to 4.27). COVID-19 onset in 2021 vs June 2020 or earlier was associated with lower odds of prolonged symptom duration (aOR 0.42, 95% CI 0.21 to 0.81).

Conclusion

Most people with SARDs had complete symptom resolution by day 15 after COVID-19 onset. However, about 1 in 4 experienced COVID-19 symptom duration 28 days or longer; 1 in 10 experienced symptoms 90 days or longer. Future studies are needed to investigate the possible relationships between immunomodulating medications, SARD type/flare, vaccine doses and novel viral variants with prolonged COVID-19 symptoms and other postacute sequelae of COVID-19 among people with SARDs.
Risk stratification in symptomatic intracranial atherosclerotic disease with conventional vascular risk factors and cerebral haemodynamics
Authors: Tian Xuan , Fang Hui , Lan Linfang , Ip Hing Lung , Abrigo Jill , Liu Haipeng , Zheng Lina , Fan Florence S Y , Ma Sze Ho , Ip Bonaventure , Song Bo , Xu Yuming , Li Jingwei , Zhang Bing , Xu Yun , Soo Yannie O Y , Mok Vincent , Wong Ka Sing , Leung Thomas W , Leng Xinyi
Published: September 2022

Background and purpose

Symptomatic intracranial atherosclerotic stenosis (sICAS) is associated with a considerable risk of recurrent stroke despite contemporarily optimal medical treatment. Severity of luminal stenosis in sICAS and its haemodynamic significance quantified with computational fluid dynamics (CFD) models were associated with the risk of stroke recurrence. We aimed to develop and compare stroke risk prediction nomograms in sICAS, based on vascular risk factors and these metrics.

Methods

Patients with 50%–99% sICAS confirmed in CT angiography (CTA) were enrolled. Conventional vascular risk factors were collected. Severity of luminal stenosis in sICAS was dichotomised as moderate (50%–69%) and severe (70%–99%). Translesional pressure ratio (PR) and wall shear stress ratio (WSSR) were quantified via CTA-based CFD modelling; the haemodynamic status of sICAS was classified as normal (normal PR&WSSR), intermediate (otherwise) and abnormal (abnormal PR&WSSR). All patients received guideline-recommended medical treatment. We developed and compared performance of nomograms composed of these variables and independent predictors identified in multivariate logistic regression, in predicting the primary outcome, recurrent ischaemic stroke in the same territory (SIT) within 1 year.

Results

Among 245 sICAS patients, 20 (8.2%) had SIT. The D2H2A nomogram, incorporating diabetes, dyslipidaemia, haemodynamic status of sICAS, hypertension and age ≥50 years, showed good calibration (P for Hosmer-Lemeshow test=0.560) and discrimination (C-statistic 0.73, 95% CI 0.60 to 0.85). It also had better performance in risk reclassification and provided larger net benefits in decision curve analysis, compared with nomograms composed of conventional vascular risk factors only, and plus the severity of luminal stenosis in sICAS. Sensitivity analysis in patients with anterior-circulation sICAS showed similar results.

Conclusions

The D2H2A nomogram, incorporating conventional vascular risk factors and the haemodynamic significance of sICAS as assessed in CFD models, could be a useful tool to stratify sICAS patients for the risk of recurrent stroke under contemporarily optimal medical treatment.
Direct measurement of the ionization quenching factor of nuclear recoils in germanium in the keV energy range
Authors: Bonhomme A. , Bonet H. , Buck C. , Hakenmüller J. , Heusser G. , Hugle T. , Lindner M. , Maneschg W. , Nolte R. , Rink T. , Pirovano E. , Strecker H.
Published: September 2022

This article reports the measurement of the ionization quenching factor in germanium for nuclear recoil energies in the keV range. Precise knowledge of this factor in this energy range is highly relevant for coherent elastic neutrino-nucleus scattering and low mass dark matter searches with germanium-based detectors. Nuclear recoils were produced in a thin high-purity germanium target with a very low energy threshold via irradiation using monoenergetic neutron beams. The energy dependence of the ionization quenching factor was directly measured via kinematically constrained coincidences with surrounding liquid scintillator based neutron detectors. The systematic uncertainties of the measurements are discussed in detail. With measured quenching factors between 0.16 and 0.23 in the 0.4 keV$$_{nr}$$

nr

 to 6.3 keV$$_{nr}$$

nr

 energy range, the data are compatible with the Lindhard theory with a parameter k of 0.162 $$\pm \,0.004$$

±

0.004

(stat + sys).
Almost all 2-bridge knots are curly
Authors: Ernst C. , Gover S.
Published: September 2022

A spiral knot or link diagram (introduced in [C. Adams, R. Hudson, Rachel, R. Morrison, W. George, L. Starkston, S. Taylor and O. Turanova, The spiral index of knots, Math. Proc. Cambridge Philos. Soc. 149(2) (2010) 297–315]) is an oriented knot or link diagram where, when traversing through the planar diagram, the curvature does not change sign. An oriented knot or link type is called curly if it admits a spiral diagram with fewer maxima than the braid index of that knot or link type. We prove that all 2-bridge knots and links with a braid index greater than three are curly. We also show that many alternating oriented Montesinos links are curly.
CEO Overconfidence and CSR Engagement
Authors: Chen Roger C. Y. , Hung Shih-Wei , Wei Yu-Chen
Published: September 2022

This study explored the impact of CEO overconfidence on corporate social responsibility (CSR). We found that overconfident CEOs do not like to engage in CSR actives. Moreover, a firm with better CSR performance and overconfident CEOs could increase the probability of agency problems. This implied that overconfident CEO is engaged in CSR based on self-interest motivation to reduce operating performance of the firm.
Unique Luminescence Properties in Zn2+-Doped CsPbBr3 Perovskite Nanocrystals
Authors: Yao Zhenyang , Yin Yali , Xia Yu , Chen Haitao
Published: September 2022

All-inorganic halide perovskite (CsPbX3) is a photoelectric material with great potential. However, the Pb element in CsPbX3 is toxic, which affects the further use of these materials. The toxicity problem can be solved by adding Zn ions into CsPbBr3. In this work, Zn-doped cesium lead bromide perovskites (CsPbBr3) nanocrystals (NCs) were synthesized by thermal injection method, and their optical properties were also studied. When Zn was introduced into CsPbBr3, its exciton emission summit shifts slightly. By changing the concentration of Zn[Formula: see text], the size and optical properties of Zn:CsPbBr3 NCs can be controlled. We also study the decay lifetime of its emission peak, and the results showed that Zn:CsPbBr3 had a longer PL decay lifetime than undoped CsPbBr3. This indicated that the incorporation of CsPbBr3 into Zn[Formula: see text] had a good application prospect in the optical field.
Monitoring ground movement at Volcán de Colima, Mexico, using Sentinel-1 data and SqueeSAR
®
Authors: Mason P. J. , Bischoff C. A. , Hughes G. , Petrone C. M. , Varley N. R. , Nicholas G. , Ferretti A.
Published: September 2022

Volcán de Colima is a highly active stratovolcano in western Mexico, which presents a significant hazard to over 300 000 people who live within
c.
40 km of the volcano. Because of its persistent activity, the volcano is actively monitored and researched, and understanding the patterns of behaviour is vital to accurate hazard assessment. Sentinel-1 synthetic aperture radar (SAR) images from ascending and descending orbits allow 1D and 2D ground motions to be retrieved using multi-interferogram techniques. SqueeSAR
®
's unique processing allows a better characterization of subtle ground movements in remote, rural mountainous areas compared with many other multi-interferogram techniques. A dataset of 147 SAR scenes (2017–19) has been processed to show patterns of lava subsidence (<150 mm of downward vertical deformation over 2 years), as well as volcano deflation and apparent westward lateral movement. These data indicate that viscous andesitic lava flows may remain mobile for years following eruption and emplacement, and that the entire volcanic edifice is subsiding. Despite the apparent quiescence, volcanic edifices can remain highly dynamic after the termination of explosive or effusive activity. We interpret that the western flank of Volcán de Colima may become steeper with time and may be of long-term concern for hazard assessment activities.

Thematic collection:
This article is part of the Remote sensing for site investigations on Earth and other planets collection available at:
https://www.lyellcollection.org/topic/collections/remote-sensing-for-site-investigations-on-earth-and-other-planets
The Impacts of Digital Literacy on Citizen Civic Engagement—Evidence from China
Authors: Li Yunrong , Li Gang
Published: September 2022

The use of information and communication technologies and the internet is becoming more and more important in people's lives. The ability to make use of these technologies turns out to be a new kind of literacy–digital literacy. Besides, engaging in civic life is a basic citizen right. As a form of civic engagement, political participation is largely shaped by the use of internet and online communities. We expect that digital literacy offers people capabilities to speak out their viewpoints in online spaces. Using data from China collected in 2017, we investigate empirically the relationship between digital literacy and individual online political participation. We measure online political participation as online rights protection for oneself and for others. Estimation results show a positive and significant effect of digital literacy on online political participation. For those who care about news and those who believe that the government workers pay attention to the public's thoughts online, the impact of digital literacy is larger than that for the general population. We propose that lack of digital literacy is a barrier for people to participate in online political activities in China. We also suggest policies for promoting digital literacy.
Striatal Syntaxin 1A Is Associated with Development of Tourette Syndrome in an Iminodipropionitrile-Induced Animal Model
Authors: Yang Liu , Wang Xueming , Liu Xiumei , Chen Xin
Published: September 2022

Tourette syndrome (TS) is a neurodevelopmental movement disorder characterized by multiple motor and vocal tics. In this study, we used a TS rat model induced by 3,3

′

-iminodipropionitrile (IDPN) and aimed to investigate the expression change of Syntaxin 1A (STX1A). Rats in the control group received intraperitoneal injection of normal saline, and TS rats were injected with IDPN (150 mg/kg/day). After 7 days of treatment, the stereotypic behaviors were assessed. Next, rats were sacrificed; brains were removed for RNA extraction and Western blotting analysis and fixed in 4% paraformaldehyde for immunofluorescence analysis. After 7 days of IDPN administration, stereotypic behaviors were successfully induced. The IDPN group exhibited more counts in biting, putting forepaws around mouth, licking, head twitching, shaking claws, body raising, and episodic utterance. The striatal STX1A mRNA, protein, and STX1A expression in striatal dopaminergic neurons were investigated. As expected, the total STX1A mRNA and protein levels were decreased in the TS model rats. In the striatal dopaminergic neurons, the IDPN group showed a slightly decreased STX1A/TH double positive area, but no statistical significance was found. Additionally, we assessed the expression of some genes closely related to STX1A, such as SNAP25, SY, and gephyrin, and no differences were found between the two groups. Together, reduced STX1A expression is associated with IDPN-induced TS development. Our findings suggested that decreased striatal STX1A expression is associated with the development of TS in the IDPN-induced rat model.
LASSO Model Better Predicted the Prognosis of DLBCL than Random Forest Model: A Retrospective Multicenter Analysis of HHLWG
Authors: Shen Ziyuan , Zhang Shuo , Jiao Yaxue , Shi Yuye , Zhang Hao , Wang Fei , Wang Ling , Zhu Taigang , Miao Yuqing , Sang Wei , Cai Guoqi , Huaihai Lymphoma Working Group
Published: September 2022

Background. Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous non-Hodgkin’s lymphoma with great clinical challenge. Machine learning (ML) has attracted substantial attention in diagnosis, prognosis, and treatment of diseases. This study is aimed at exploring the prognostic factors of DLBCL by ML. Methods. In total, 1211 DLBCL patients were retrieved from Huaihai Lymphoma Working Group (HHLWG). The least absolute shrinkage and selection operator (LASSO) and random forest algorithm were used to identify prognostic factors for the overall survival (OS) rate of DLBCL among twenty-five variables. Receiver operating characteristic (ROC) curve and decision curve analysis (DCA) were utilized to compare the predictive performance and clinical effectiveness of the two models, respectively. Results. The median follow-up time was 43.4 months, and the 5-year OS was 58.5%. The LASSO model achieved an Area under the curve (AUC) of 75.8% for the prognosis of DLBCL, which was higher than that of the random forest model (AUC: 71.6%). DCA analysis also revealed that the LASSO model could augment net benefits and exhibited a wider range of threshold probabilities by risk stratification than the random forest model. In addition, multivariable analysis demonstrated that age, white blood cell count, hemoglobin, central nervous system involvement, gender, and Ann Arbor stage were independent prognostic factors for DLBCL. The LASSO model showed better discrimination of outcomes compared with the IPI and NCCN-IPI models and identified three groups of patients: low risk, high-intermediate risk, and high risk. Conclusions. The prognostic model of DLBCL based on the LASSO regression was more accurate than the random forest, IPI, and NCCN-IPI models.
DNMT1 Gene Expression in Patients with Helicobacter pylori Infection
Authors: Ahmadi Hedayati Manouchehr , Ahmadi Amjad , Khatooni Zahed
Published: September 2022

DNMT1, as a critical enzyme affecting epigenetics through methylation of DNA cytosine-rich sequences, regulates gene expression. Exterior factors including long-term infections, in this study Helicobacter pylori infection, could change host cells’ epigenetics by affecting DNMT1 gene expression. This study investigated the statistical correlation between H. pylori virulence genes and DNMT1 gene expression in gastric antral epithelial cells of gastric adenocarcinoma and gastritis patients. In a case-control study, 50 and 53 gastritis and gastric adenocarcinoma antral biopsies, including 23 and 21 patients with H. pylori infection, respectively, were collected from hospitals in the west of Iran. Having extracted total RNA from gastric biopsy samples, cDNA was synthesized and virulence genes of H. pylori were detected by using the PCR method. Relative real-time RT PCR was used to detect ΔΔCt fold changes of the DNMT1 gene expression in divided groups of patients based on H. pylori infection and clinical manifestations. The results showed that along with increasing patients’ age, the DNMT1 gene expression will increase in gastric antral epithelial cells of gastric cancer patients (

P
≤
0.05

). On the other hand, the biopsy samples with infection of H. pylori cagA, cagY, and cagE genotypes revealed a direct correlation along with increased DNMT1 gene expression. This study revealed the correlations of H. pylori cag pathogenicity island genes with increased DNMT1 gene expression.
Construction Schedule Management System for Large-Scale Construction Projects Based on Multisensor Network
Authors: Meng Fanmin , Yu Shaozhi , Xue Jianying
Published: September 2022

As an important task of construction project management, construction schedule management is related to the realization of project period, cost, quality, and other objectives. However, in actual construction, problems such as difficulties in plan implementation and management are often encountered, and schedule delays often occur. Moreover, with the increase in the scale and complexity of modern buildings, the management of construction schedules has brought about larger issues and higher requirements have been put forward for the management level of the construction schedule. The traditional timetable management and scheduling is not highly relevant to the project entity. There is no entity change, the project information loss is serious, the tracking and control of the construction timetable is not in place, there is fine management, and the construction timetable management cannot meet the needs of modern construction. In order to ensure the smooth implementation of projects and objectives, it is urgent to explore new management ideas and methods to promote the smooth progress of construction process management. BIM technology has the advantages of visibility, simulation, adjustment, optimization, and advanced data integration, which helps to make up for the shortcomings of previous schedule management and improve the level of construction schedule management. Based on the research situation of large-scale construction project monitoring system and the analysis of information fusion technology, this paper proposes a large-scale construction project monitoring system scheme based on multisensor network information fusion. Through the investigation of the monitoring content, the composition of the multisensor network is determined. This paper is applicable to large-scale construction projects. Through the research and design of hardware modules, software modules, and fusion algorithms, the data acquisition, transmission, calculation, and display functions of the monitoring system based on multisensor network information fusion are realized, which can effectively monitor the entire process of large-scale construction projects.
FBXW7 Reduces the Cancer Stem Cell-Like Properties of Hepatocellular Carcinoma by Regulating the Ubiquitination and Degradation of ACTL6A
Authors: Wang Xing , Li Ying , Li Yongning , Liu Peng , Liu Songbai , Pan Yaozhen
Published: September 2022

Cancer stem cells (CSCs) comprise a subset of tumor cells that can initiate tumorigenesis and promote tumor advance. A previous study showed that the expression of FBXW7 in hepatocellular carcinoma (HCC) clinical samples was lower than that in the adjacent nontumor tissues and was negatively correlated with the invasion and migration of HCC cells. However, the biological characteristics and the underlying molecular mechanisms of FBXW7 in HCC stemness are yet to be elucidated. In present study, we found that FBXW7 participates in the self-renewal, tumorigenicity, sorafenib therapy, and stem cell-like properties of HCC cells in vivo and in vitro. The upregulation of FBXW7 inhibited the stemness and reduced the tumorigenicity and drug resistance of HCC cells. Mechanistically, proteins binding to FBXW7 were identified by coimmunoprecipitation and protein colocalization assays. We confirmed ACTL6A as a novel downstream target for FBXW7. The in vivo ubiquitination assay showed that FBXW7 repressed HCC malignancy by regulating the oncogenic activity of ACTL6A in a ubiquitin-dependent manner. Furthermore, we found that ACTL6A overexpression inversed the self-renewal abilities and tumorigenic abilities depressed by overexpressing FBXW7. The current findings suggested that FBXW7 reduces the stemness of HCC cells by targeting and degrading ACTL6A and provides a novel target for the diagnosis and treatment of HCC.
Computer Information Processing System Based on RFID Internet-of-Things Encryption Technology
Authors: Yuan Chunyan
Published: September 2022

With the increasing development of information science and technology and the vigorous use and promotion of new technologies, profound changes have taken place in all aspects of our daily life. With this huge change, the IoT industry was born. And it analyzes and processes the large amount of data generated between them, and finally, it helps the development of the economy. The RFID system studied in this paper is the radio frequency identification system, which is an automatic signal identification system. The relationship between the RFID system and the Internet of Things is that the former will obtain a large amount of Internet of Things information data by identifying the Internet of Things. However, it is difficult to guarantee the analysis and processing of data and the security of data in the RFID system. This paper aims to study the effective processing and security guarantee of a large amount of data obtained by the RFID system after processing the identification of the Internet of Things. It is expected to overcome the problems of conventional related art. This paper proposes the encryption technology for the Internet of Things RFID system, as well as the corresponding algorithm, and establishes a processing system for information data. The experimental results of this paper show that the cryptographic mechanism run by the algorithm PECC has better security performance compared with other cryptographic mechanisms, and its computational complexity can be reduced by 28.35%.
Automatic Aesthetics Evaluation of Robotic Dance Poses Based on Hierarchical Processing Network
Authors: Peng Hua , Ren Hui , Wang Ziyang , Hu Huosheng , Li Jing , Feng Sheng , Zhao Liping , Hu Keli
Published: September 2022

Vision plays an important role in the aesthetic cognition of human beings. When creating dance choreography, human dancers, who always observe their own dance poses in a mirror, understand the aesthetics of those poses and aim to improve their dancing performance. In order to develop artificial intelligence, a robot should establish a similar mechanism to imitate the above human dance behaviour. Inspired by this, this paper designs a way for a robot to visually perceive its own dance poses and constructs a novel dataset of dance poses based on real NAO robots. On this basis, this paper proposes a hierarchical processing network-based approach to automatic aesthetics evaluation of robotic dance poses. The hierarchical processing network first extracts the primary visual features by using three parallel CNNs, then uses a synthesis CNN to achieve high-level association and comprehensive processing on the basis of multi-modal feature fusion, and finally makes an automatic aesthetics decision. Notably, the design of this hierarchical processing network is inspired by the research findings in neuroaesthetics. Experimental results show that our approach can achieve a high correct ratio of aesthetic evaluation at 82.3%, which is superior to the existing methods.
Predicting the Physician’s Specialty Using a Medical Prescription Database
Authors: Akhlaghi Mahboube , Tabesh Hamed , Mahaki Behzad , Malekpour Mohammad-Reza , Ghasemi Erfan , Mansourian Marjan
Published: September 2022

Purpose. The present study is aimed at predicting the physician’s specialty based on the most frequent two medications prescribed simultaneously. The results of this study could be utilized in the imputation of the missing data in similar databases. Patients and Methods. The research is done through the KAy-means for MIxed LArge datasets (KAMILA) clustering and random forest (RF) model. The data used in the study were retrieved from outpatients’ prescriptions in the second populous province of Iran (Khorasan Razavi) from April 2015 to March 2017. Results. The main findings of the study represent the importance of each combination in predicting the specialty. The final results showed that the combination of amoxicillin-metronidazole has the highest importance in making an accurate prediction. The findings are provided in a user-friendly R-shiny web application, which can be applied to any medical prescription database. Conclusion. Nowadays, a huge amount of data is produced in the field of medical prescriptions, which a significant section of that is missing in the specialty. Thus, imputing the missing variables can lead to valuable results for planning a medication with higher quality, improving healthcare quality, and decreasing expenses.
Based on Improved Artificial Neural Network Sewage Monitoring Alarm System Method
Authors: Chen Liping , Zhao Ruichuan , Wu Wenzheng
Published: September 2022

Sewage discharge has become a key issue affecting the quality of the water environment, and how to effectively monitor and manage sewage discharge behavior has become a key factor to avoid water pollution and improve water quality. However, the current domestic sewage discharge monitoring system is not perfect, resulting in the lack of effective monitoring of enterprise sewage discharge by regulatory authorities, which provides an opportunity for enterprises to steal discharge. In the background of sewage treatment plant, the comprehensive design of sewage monitoring and alarm system is carried out based on the idea of physical information fusion. The design adopts a four-layer information physical architecture, which is divided into four parts: perception communication, fusion processing, push, and execution. In the fusion treatment part, the neural network intelligent algorithm is used to predict the dissolved oxygen, and the oxygen delivery is adjusted according to the predicted value to achieve accurate aeration and optimize the effluent quality. The push and execution parts adopt multiparameter monitoring to realize the smooth operation of equipment and ensure the system security. A new optimal control strategy of dissolved oxygen based on neural network is proposed. Through a large number of experiments and historical data, the intake index and dissolved oxygen value of the aeration tank under the condition of optimal outlet water are obtained as samples. According to the sample training, the BP neural network optimized by particle swarm optimization algorithm is adopted to achieve accurate prediction of dissolved oxygen under different inlet water conditions. The smooth operation of sewage treatment equipment is accomplished by the lower machine and the upper machine. In sewage treatment, each process section collects the equipment status in strict accordance with the order of sewage monitoring facilities. Then the communication network between the upper computer and the lower computer and the sensor is designed. The lower machine adopts PLC as the core, programming PLC through STEP7, and uses PID algorithm to control dissolved oxygen. The PC is developed in C language, so as to realize user login, real-time data display, over-limit fault alarm, report query, user management, etc. The PC integrates MATLAB neural network on the platform to predict dissolved oxygen through mixed programming quantity. The sewage alarm system based on improved artificial neural network is sensitive and has excellent performance. It provides a new idea for intelligent sewage detection and real-time monitoring.
Macroscopic Mechanical Properties and Microscopic Bonding Mechanisms of Glass Fiber-Modified Loess
Authors: Li Le , Ye Wanjun , Bai Yang , Wu Yuntao
Published: September 2022

Focusing on the performance improvement of glass fiber-modified loess, a series of laboratory tests were carried out, and the macroscopic mechanical properties of glass fiber-modified loess were studied by conventional triaxial shear tests. With the help of scanning electron microscopy (SEM), the pores and cracks image analysis system (PCAS) and nuclear magnetic resonance (NMR) tests, the microscopic properties of the improved loess were studied qualitatively and quantitatively from three aspects: mode of structural contact, pore morphological characteristics and pore structure arrangement characteristics. Finally, the interface zone bond-slip model was used to analyze the internal mechanism of glass fiber and loess interface zone slip. The macroscopic test results show with the same glass fiber length, the shear strength, cohesion and internal friction angle of the modified loess all increased first and then decreased with increasing incorporation of glass fibers. And the optimal ratio of glass fibers is 0.6%. Under the same fiber ratio, the shear strength and cohesion of the improved loess continued to increase with increasing fiber length. The optimal fiber length used in the project was 9 mm. Qualitative analysis of the SEM images show that with the increase in the glass fiber incorporation ratio, the fiber increasingly sutures the cracks in the soil and tightens the soil at both ends of the cracks. Quantitative analysis shows that the proportion of pore area is the largest at the 0.8% mixing ratio, followed by the 0% mixing ratio, and the smallest at the 0.6% mixing ratio. It can be seen from the NMR test results that the T2 spectral distribution curve under the fiber ratios of 0.2%–0.6% is shifted to the left compared with the ratios of 0% and 0.8%. The peak-top signal intensity of the main spectrum peak when the fiber ratio is 0.6% is the weakest.
Fractional-Order Ebola-Malaria Coinfection Model with a Focus on Detection and Treatment Rate
Authors: Zhang Lingling , Addai Emmanuel , Ackora-Prah Joseph , Arthur Yarhands Dissou , Asamoah Joshua Kiddy K.
Published: September 2022

Coinfection of Ebola virus and malaria is widespread, particularly in impoverished areas where malaria is already ubiquitous. Epidemics of Ebola virus disease arise on a sporadic basis in African nations with a high malaria burden. An observational study discovered that patients in Sierra Leone’s Ebola treatment centers were routinely infected with malaria parasites, increasing the risk of death. In this paper, we study Ebola-malaria coinfections under the generalized Mittag-Leffler kernel fractional derivative. The Banach fixed point theorem and the Krasnoselskii type are used to analyse the model’s existence and uniqueness. We discuss the model stability using the Hyers-Ulam functional analysis. The numerical scheme for the Ebola-malaria coinfections using Lagrange interpolation is presented. The numerical trajectories show that the prevalence of Ebola-malaria coinfections ranged from low to moderate depending on memory. This means that controlling the disease requires adequate knowledge of the past history of the dynamics of both malaria and Ebola. The graphical dynamics of the detection rate indicate that a variation in the detection rate only affects the following compartments: individuals that are latently infected with the Ebola, Ebola virus afflicted people who went unnoticed, individuals who have been infected with the Ebola virus and have been diagnosed with the disease, and persons undergoing Ebola virus therapy.
Procurement Volume Prediction of Cross-Border E-Commerce Platform Based on BP-NN
Authors: Jiang Yaping
Published: September 2022

For logistics management, predictive analysis has never been more crucial than it is now, thanks to the vast number of deal data generated every second by electronic commerce. In an effort to enhance customer service and supply control, e-commerce businesses are progressively utilizing machine learning technologies to enhance projections. The back-propagation neural network (BP-NN) model is used to develop a C-A-BP forecasting model that considers commodity sales characteristics and the data series’ trend. In order to predict each cluster, a C-BP-NN model is first created, adding sales information as influencing elements into the C-BP-NN model. An A-BP-NN model is used in combination with the ARIMA that is employed for the linear component. These two forecasting models are merged to provide the final results. By comparing the results of the ARIMA, BP-NN, A-BP-NN, and C-BP-NN using the information provided by Jollychic’s cross-border platform, the A-C-BPNN was shown to be the best.
Toward a New Nodal Pricing Policy of the Brazilian Transmission System Considering Multiple Hydrological Scenarios
Authors: Dornellas Carlos R. R. , Leite da Silva Armando M. , Costa João G. C. , Machado Jr Zulmar S. , Marcato André L. M. , Mello João C. O.
Published: September 2022

This paper presents a new method for allocating transmission system costs in hydro prevailing energy markets. The proposed approach is based on nodal pricing, and it considers multiple hydrological scenarios obtained from optimized energy models. These models are much closer to the operational reality of hydro dominant systems and more adequate to the transmission operation planning. The nodal pricing strategy comprises two steps to recover the total costs of the transmission system. The first one calculates the charges corresponding to the utilized network capacity, estimated at a specified operating condition, and it brings the locational signal to the tariff. In the second step, the charges related to the transmission capacity available but not used in the system are assessed by a postage stamp. This latter step accomplishes the task of recovering the total transmission charges and defining the final tariff for specific operating dispatching. On the other hand, the optimized energy models, based on stochastic dual dynamic programming, are used to minimize the operating costs while penalizing possible energy spillages. These models create monthly sequences of hydrothermal coordinated generating scenarios and dispatching conditions, which are used by the nodal pricing strategy to produce the generation/load charges and tariffs and the corresponding statistics. The proposed method, combining the nodal pricing strategy and the optimized energy model, is applied to a Brazilian network configuration and the results are fully discussed. Moreover, probabilistic analyses are also performed to describe the annual costs of transmission of thermoelectric and hydroelectric plants and industrial electrointensive consumers installed in different areas of the network.
Intelligent Analysis Strategy of Pragmatic Failure in Cross-Cultural Communication Based on Convolution Neural Network
Authors: Dai Hang , Zhao Tianyu
Published: September 2022

The study of pragmatic failure in cross-cultural communication is a subject of great theoretical significance and practical value in contemporary linguistic research. This paper takes pragmatic failures in cross-cultural communication as the research object, and tries to make the discussion systematic, theoretical, and scientific. With this feature, the complexity of the convolutional network will be greatly reduced. In the convolution layer, the convolution operation can make the features of the initial speech more obvious, and it can also have certain effect on the noise reduction of speech. It is of great theoretical and practical significance to use convolutional neural network to study the intelligent analysis strategies of pragmatic failure in cross-cultural communication. In this paper, the intelligent analysis strategy of pragmatic failure in cross-cultural communication based on deep convolution neural network is taken as the research object, and an optimized end-to-end deep convolution neural network model is proposed. Experimental results show that the overall recognition rate of this algorithm is improved by 59.8%. Especially, the efficiency of obtaining results is basically maintained at 61.8%. The intelligent analysis strategy of pragmatic failure in cross-cultural communication based on convolutional neural network reduces redundant calculation and shortens training time to some extent, and this algorithm can better reflect the advantages of accelerating network convergence compared with simple network.
Optimized Design of Polyethylene Fiber-Engineered Cementitious Composite Mix Ratio Based on the Analytic Hierarchy Process
Authors: Han Fengxia , Liu Qing , Guo Xin , Niu Yanfeng
Published: September 2022

Finding a method to optimize the design of the polyethylene fiber-engineered cementitious composite (PE-ECC) mix proportion is an urgent endeavor. The analytic hierarchy process (AHP) is an efficient decision-making tool for complicated problems with multiple variables and uncertainties. In this study, initial cracking strength, ultimate tensile strength, tensile displacement, and test age, as influencing factors of the PE-ECC optimum mix design were considered. The weightings of the factors were quantified through the AHP method according to the tensile test results of 14 groups of specimens with different mix proportions. The water to binder ratios (0.25, 0.27, 0.29, 0.31), the mineral admixtures (30%, 40%, 50%, and 60%), and the PE ratio (2%) were the three main test parameters for the factors of the PE-ECC tensile properties. The weight of each influence factor was calculated by constructing a matrix, which confirmed that the judgment matrix satisfies the consistency test. The optimum mixture ratio of 30% fly ash and 0.27 water-binder ratio were obtained. The results demonstrate the applicability and rationality of the AHP theory. The findings from this study can be used as a guideline for the optimized design of PE-ECC mix proportions.
Efficacy Analysis of Combining Sintilimab with Neoadjuvant Chemotherapy in Treating Middle and Advanced Rectal Cancer Based on Big Data
Authors: Wang Yifei , Fei Jiandong , Zheng Yanan , Li Ping , Ren Xiaodong , An Yongzhu
Published: September 2022

Objective. To analyze the efficacy of combining sintilimab with neoadjuvant chemotherapy in treating middle and advanced rectal cancer based on big data. Methods. According to the inclusion and exclusion criteria, 43 patients with middle and advanced rectal cancer, who were treated with sintilimab and neoadjuvant chemotherapy in General Surgery of the hospitals of Zhangjiakou city from January 2020 to January 2022, were selected for the retrospective study. The patients’ short-term efficacy was scientifically evaluated, and the factors affecting efficacy and the correlation were analyzed. Results. Among the 43 enrolled patients, 30 of them had regional lymphatic metastasis but none had distant metastasis; most patients were at Broders II and TNM III, and all of them had adenocarcinoma; the total response rate was 69.77% (30 cases), with no grade IV and V adverse reactions; the patients were divided into the effective group and the ineffective group after treatment based on the evaluation results of short-term efficacy, and analysis of the relevant factors exposed in both groups revealed significant differences in age, tumor size, CEA, NLR value, PLR value, TNM stage, and presence of combined lymphatic metastasis between the two groups (

P
<
0.05

); univariate analysis showed that tumor size, CEA, TNM stage, and combined lymphatic metastasis were the independent risk factors affecting the efficacy in patients with middle to advanced rectal cancer (

P
<
0.05

); and through the Spearman correlation analysis of the above independent risk factors, it was further confirmed that tumor size, CEA, TNM stage, and combined lymphatic metastasis were negatively correlative with the efficacy of combining sintilimab with neoadjuvant chemotherapy in treating middle to advanced rectal cancer (

P
<
0.05

). Conclusion. Combining sintilimab with neoadjuvant chemotherapy has good efficacy and safety profile, which is conducive to subsequent surgery; in contrast, larger tumor diameter, higher CEA level, higher TNM stage, and more serious lymphatic metastasis are all independent risk factors affecting treatment sensitivity and can lead to poor efficacy.