bluuebunny/crossref_metadata_2025 huggingface dataset:
Modelling STEMI service delivery: a proof of concept study
Authors: Cole Justin , Beare Richard , Phan Thanh , Srikanth Velandai , Stub Dion , Smith Karen , Murdoch Karen , Layland Jamie
Published: December 2021

Background

Access to individual percutaneous coronary intervention (PCI) centres has traditionally been determined by historical referral patterns along arbitrarily defined geographic boundaries. We set out to produce predictive models of ST-elevation myocardial infarction (STEMI) demand and time-efficient access to PCI centres.

Methods

Travel times from random addresses to PCI centres in Melbourne, Australia, were estimated using Google map application programming interface (API). Departures at 08:15 and 17:15 were compared with 23:00 to determine the effect of peak hour traffic congestion. Real-world ambulance travel times were compared with estimated travel times using Google map developer software. STEMI incidence per postcode was estimated by merging STEMI incidence per age group data with age group per postcode census data. PCI centre network configuration changes were assessed for their effect on hospital STEMI loading, catchment size, travel times and the number of STEMI cases within 30 min of a PCI centre.

Results

Nearly 10% of STEMI cases travelled more than 30 min to a PCI centre, increasing to 20% by modelling the removal of large outer metropolitan PCI centres (p<0.05). A model of 7 PCI centres compared favourably to the current existing network of 11 PCI centres (p=0.18 (afternoon), p=0.5 (morning and night)). The intraclass correlation between estimated travel times and ambulance travel times was 0.82, p<0.001.

Conclusion

This paper provides a framework to integrate prehospital environmental variables, existing or altered healthcare resources and health statistics to objectively model STEMI demand and consequent access to PCI. Our methodology can be modified to incorporate other inputs to compute optimum healthcare efficiencies.
Efficacy of biological therapies and small molecules in moderate to severe ulcerative colitis: systematic review and network meta-analysis
Authors: Burr Nicholas E , Gracie David J , Black Christopher J , Ford Alexander C
Published: December 2021

Objective

Biological therapies and small molecules continue to be evaluated in moderate to severely active ulcerative colitis, but are often studied in placebo-controlled trials, meaning their relative efficacy and safety is unknown. We examined this in a network meta-analysis.

Design

We searched the literature to October 2021 to identify eligible trials. We judged efficacy using clinical remission, endoscopic improvement, or clinical response, and according to previous exposure or non-exposure to antitumour necrosis factor (TNF)-α therapy. We also assessed safety. We used a random effects model and reported data as pooled relative risks (RRs) with 95% CIs. Interventions were ranked according to their P-score.

Results

We identified 28 trials (12 504 patients). Based on failure to achieve clinical remission, upadacitinib 45 mg once daily ranked first versus placebo (RR 0.73; 95% CI 0.68 to 0.80, P-score 0.98), with infliximab 5 mg/kg and 10 mg/kg second and third, respectively. Upadacitinib ranked first for clinical remission in both patients naïve to anti-TNF-α drugs (RR 0.69; 95% CI 0.61 to 0.78, P-score 0.99) and previously exposed (RR 0.78; 95% CI 0.72 to 0.85, P-score 0.99). Upadacitinib was superior to almost all other drugs in these analyses. Based on failure to achieve endoscopic improvement infliximab 10 mg/kg ranked first (RR 0.61; 95% CI 0.51 to 0.72, P-score 0.97), with upadacitinib 45 mg once daily, second, and infliximab 5 mg/kg third. Upadacitinib was more likely to lead to adverse events, but serious adverse events were no more frequent, and withdrawals due to adverse events were significantly lower than with placebo. Infections were significantly more likely with tofacitinib than placebo (RR 1.41; 95% CI 1.03 to 1.91).

Conclusion

In a network meta-analysis, upadacitinib 45 mg once daily ranked first for clinical remission in all patients, patients naïve to anti-TNF-α drugs and patients previously exposed. Infliximab 10 mg/kg ranked first for endoscopic improvement. Most drugs were safe and well tolerated.
Aortic stenosis in chronic kidney disease: challenges in diagnosis and treatment
Authors: Gupta Jessica I , Gualano Sarah K , Bhave Nicole
Published: December 2021

Chronic kidney disease (CKD) is becoming increasingly common and is associated with development and rapid progression of aortic stenosis (AS). Patients with AS and CKD have higher mortality rates than those with AS of similar severity and normal kidney function. The diagnosis of severe AS in patients with CKD is often challenging due to alterations in haemodynamics and heart structure, and integration of data from multiple imaging modalities may be required. When indicated, the definitive treatment for severe AS is aortic valve replacement. Patients with CKD are candidates for bioprosthetic valve replacement (surgical or transcatheter aortic valve implantation) or mechanical valve replacement. However, for patients with CKD, lifetime management is complex, as patients with CKD have a higher competing risk of bioprosthetic structural valve deterioration, bleeding in the setting of systemic anticoagulation and mortality related to CKD itself. The involvement of a heart-kidney multidisciplinary team in the care of patients with CKD and severe AS is ideal to navigate the complexities of diagnosis and management decisions.
Impaired social cognition and fine dexterity in patients with Cowden syndrome associated with germlinePTENvariants
Authors: Desjardins Clément , Caux Frédéric , Degos Bertrand , Benzohra Djallel , De Liège Astrid , Bohelay Gérôme , Longy Michel , Béreaux Chloé , Garcin Béatrice
Published: December 2021

Purpose

Cowden syndrome (CS) is an autosomal dominant disease related to germlinePTENvariants and is characterised by multiple hamartomas, increased risk of cancers and frequent brain alteration. Since the behaviour of patients with CS sometimes appears to be inappropriate, we analysed their neuropsychological functioning.

Methods

This monocentric study was conducted between July 2018 and February 2020. A standardised neuropsychological assessment, including an evaluation of social cognition, executive functions, language and dexterity, as well as a cerebral MRI were systematically proposed to all patients with CS. Moreover,PTENvariants were identified.

Results

Fifteen patients from 13 families were included, with six non-sense (40%), three missense (20%), five frameshift (33.3%) and one splice site (6.6%) variant types. Twelve patients (80%) had altered social cognition: 10 patients had an abnormal modified Faux-Pas score and 5 had Ekman’s facial emotions recognition impairment. Nearly all patients (93%) had impaired dexterity. Cerebral MRI showed various cerebellar anomalies in seven patients (46.7%).

Conclusion

Altered social cognition and impaired fine dexterity are frequently associated with CS. Further studies are needed to confirm these results and to determine whether dexterity impairment is due to the effect of germlinePTENvariants in the cerebellum.
Tax incidence of electronic nicotine delivery systems (ENDS) in the USA
Authors: Shang Ce , Ma Shaoying , Lindblom Eric N
Published: December 2021

Background

A growing number of states or jurisdictions in the USA have imposed excise taxes on electronic nicotine delivery systems (ENDS). However, there is no consensus on how best to tax ENDS.

Objectives

We specifically compare the tax incidence or burden for ENDS and cigarettes and analyse how ENDS tax incidence is associated with the choices of tax bases and rates.

Methods

We calculate ENDS excise tax incidence as the percentage of retail prices for each state or jurisdiction. Next, we use ordinary least squares to evaluate how tax incidence is associated with the choices of tax bases (eg, a specific tax base vs a value or ad valorem tax base) and rates and how these associations are moderated by product types.

Results

ENDS and cigarette tax incidence is similar at the state level. Nonetheless, when federal cigarette taxes are considered, the cigarette tax incidence is higher than the tax incidence on closed-system ENDS. The proportion of states that impose value taxes is higher for open systems (65.4%) than for closed systems (46.2%). A value tax base is associated with a 7 percentage point lower tax incidence compared with a specific tax base. Product type further moderates the association between tax base and incidence.

Conclusion

Tax incidence can be used to measure the strength of ENDS tax policies and how they are compared with cigarette taxes. Policymakers who aim to prevent youth from using ENDS may consider a value tax base to raise the tax incidence of closed systems—the product type preferred by young people.
Testing the $$R_{D^{(*)}}$$ anomaly at the LHeC
Authors: Azuelos Georges , Fischer Oliver , Jana Sudip
Published: December 2021

B-Physics anomalies have recently raised renewed interest in leptoquarks, predicted in several theoretical frameworks. Under simplifying but conservative assumptions, we show that the current limits from LHC searches together with the requirement to explain the observed value for $$R_{D^{(*)}}$$

R

D

(

∗
)

constrain the $$R_2$$

R
2

leptoquark mass to be in the range of $$800 \le m_{R_2} \le 1000$$

800
≤

m

R
2

≤
1000

 GeV. We study the search for $$R_2$$

R
2

at the LHeC via its resonance in the $$b\tau $$

b
τ

final state by performing a cut-and-count analysis of the signal and the dominant Standard Model backgrounds. We find that the LHeC has an excellent discovery potential for the $$R_2$$

R
2

leptoquark even for couplings to the first generation as small as $${\mathcal {O}}(10^{-2})$$

O
(

10

-
2

)

.
Higgs inflation and its extensions and the further refining dS swampland conjecture
Authors: Liu Yang
Published: December 2021

On the one hand, Andriot and Roupec (Fortsch Phys, 1800105, 2019) proposed an alternative refined de Sitter conjecture, which gives a natural condition on a combination of the first and second derivatives of the scalar potential (Andriot and Roupec 2019). On the other hand, in our previous article (Liu in Eur Phys J Plus 136:901, 2021) , we have found that Palatini Higgs inflation model is in strong tension with the refined de Sitter swampland conjecture (Liu 2021). Therefore, following our previous research, in this article we examine if Higgs inflation model and its two variations: Palatini Higgs inflation and Higgs-Dilaton model (Rubio in Front Astron Space Sci, 10.3389/fspas.2018.00050, 2019) can satisfy the “further refining de Sitter swampland conjecture” or not. Based on observational data (Ade et al., Phys Rev Lett 121:221301, 2018; Akrami et al., Planck 2018 results. X. Constraints on inflation, arXiv:1807.06211 [astro-ph.CO], 2018; Aghanim et al., Planck 2018 results: VI. Cosmological parameters, arXiv:1807.06209 [astro-ph.CO], 2018), we find that these three inflationary models can always satisfy this new swampland conjecture if only we adjust the relevant parameters a, $$b = 1-a$$

b
=
1
-
a

and q. Therefore, if the “further refining de Sitter swampland conjecture” does indeed hold, then the three inflationary models might all be in “landscape”.
Utilization of continental transforms in break-up: observations, models, and a potential link to magmatism
Authors: Lundin E. R. , Doré A. G. , Naliboff J. , Van Wijk J.
Published: December 2021

Reactivation of continental transform faults (hereafter transforms) is identified herein as a significant factor in continental break-up, based on a global review of divergent margins and numerical modelling. Divergent margins that have reactivated transforms are characterized by linear and abrupt terminations of thick continental crust. Transforms represent some of the largest structures on Earth, and these megastructures represent major lithospheric weaknesses and are therefore prone to reactivation upon changes in the stress field, which typically occur during plate break-up. The blunt termination of the margins is consistent with observations of very limited pre-break-up lithospheric thinning of such margins. This mode of break-up appears to occur abruptly, and contrasts notably with highly tapered and slowly extended divergent margins. Magma leakage along transforms is well-known worldwide where divergence occurs across such features. This leakage may evolve to dyke injections, further reducing the plate strength. We observe that many of the blunt margins we attribute to transform reactivation have been prone to above-normal magmatism and are marked by seaward-dipping reflectors underlain by high-velocity lower crustal intrusions. The magmatism may be directly related to the separation of abruptly terminated margins, whereby the large resulting lateral thermal gradients trigger edge-driven convection and melt addition.
Mapping the complexity of transform margins
Authors: Markwick Paul J. , Paton Douglas A. , Mortimer Estelle J.
Published: December 2021

Transform margins are a function of the pre-existing crustal architecture (pre-transform) and the interplay of syn- and post-transform geodynamic processes. We use a suite of geospatial databases to investigate four transform margins: East Africa (Davie Deformational Zone, DDZ), Equatorial Africa, and the South African and Falkland (Malvinas) margins (Agulhas–Falkland Fracture Zone, AFFZ). The East African margin is the most complex of the four. This is a consequence of Late Jurassic–Early Cretaceous transform motion affecting highly heterogeneous crust, and post-transform deformation that varies along the margin. Equatorial Africa most closely adheres to traditional definitions of ‘transform margins’, but actually comprises two principal transform systems – the Romanche and St Pauls, dictated by the pre-transform distribution of mobile belts and West African craton. All four margins are spatially associated with volcanism, and each exhibits narrow uplifts associated with transpression or transtension. But the causal relationship of these features with transform processes differ. Volcanism along the East African margin is pre- and post-transform. Syn-transform volcanism on the AFFZ is spatially limited, with the AFFZ possibly acting as a conduit for magmatism rather than as a causal driver. Transform margins are varied and complex and require an understanding of pre-, syn- and post-transform geodynamics.
A Large-scale Empirical Analysis of Ransomware Activities in Bitcoin
Authors: Wang Kai , Pang Jun , Chen Dingjie , Zhao Yu , Huang Dapeng , Chen Chen , Han Weili
Published: December 2021

Exploiting the anonymous mechanism of Bitcoin, ransomware activities demanding ransom in bitcoins have become rampant in recent years. Several existing studies quantify the impact of ransomware activities, mostly focusing on the amount of ransom. However, victims’ reactions in Bitcoin that can well reflect the impact of ransomware activities are somehow largely neglected. Besides, existing studies track ransom transfers at the Bitcoin address level, making it difficult for them to uncover the patterns of ransom transfers from a macro perspective beyond Bitcoin addresses.

In this article, we conduct a large-scale analysis of ransom payments, ransom transfers, and victim migrations in Bitcoin from 2012 to 2021. First, we develop a fine-grained address clustering method to cluster Bitcoin addresses into users, which enables us to identify more addresses controlled by ransomware criminals. Second, motivated by the fact that Bitcoin activities and their participants already formed stable industries, such as
Darknet
and
Miner
, we train a multi-label classification model to identify the industry identifiers of users. Third, we identify ransom payment transactions and then quantify the amount of ransom and the number of victims in 63 ransomware activities. Finally, after we analyze the trajectories of ransom transferred across different industries and track victims’ migrations across industries, we find out that to obscure the purposes of their transfer trajectories, most ransomware criminals (e.g., operators of Locky and Wannacry) prefer to spread ransom into multiple industries instead of utilizing the services of Bitcoin mixers. Compared with other industries,
Investment
is highly resilient to ransomware activities in the sense that the number of users in
Investment
remains relatively stable. Moreover, we also observe that a few victims become active in the
Darknet
after paying ransom. Our findings in this work can help authorities deeply understand ransomware activities in Bitcoin. While our study focuses on ransomware, our methods are potentially applicable to other cybercriminal activities that have similarly adopted bitcoins as their payments.
The Complexity and Expressive Power of Limit Datalog
Authors: Kaminski Mark , Kostylev Egor V. , Grau Bernardo Cuenca , Motik Boris , Horrocks Ian
Published: December 2021

Motivated by applications in declarative data analysis, in this article, we study
Datalog
Z
—an extension of Datalog with stratified negation and arithmetic functions over integers. This language is known to be undecidable, so we present the fragment of
limit
Datalog
Z
programs, which is powerful enough to naturally capture many important data analysis tasks. In limit
Datalog
Z
, all intensional predicates with a numeric argument are
limit
predicates that keep maximal or minimal bounds on numeric values. We show that reasoning in limit
Datalog
Z
is decidable if a
linearity
condition restricting the use of multiplication is satisfied. In particular, limit-linear
Datalog
Z
is complete for Δ
2
EXP
and captures Δ
2
P
over ordered datasets in the sense of descriptive complexity. We also provide a comprehensive study of several fragments of limit-linear
Datalog
Z
. We show that semi-positive limit-linear programs (i.e., programs where negation is allowed only in front of extensional atoms) capture coNP over ordered datasets; furthermore, reasoning becomes coNEXP-complete in combined and coNP-complete in data complexity, where the lower bounds hold already for negation-free programs. In order to satisfy the requirements of data-intensive applications, we also propose an additional stability requirement, which causes the complexity of reasoning to drop to EXP in combined and to P in data complexity, thus obtaining the same bounds as for usual Datalog. Finally, we compare our formalisms with the languages underpinning existing Datalog-based approaches for data analysis and show that core fragments of these languages can be encoded as limit programs; this allows us to transfer decidability and complexity upper bounds from limit programs to other formalisms. Therefore, our article provides a unified logical framework for declarative data analysis which can be used as a basis for understanding the impact on expressive power and computational complexity of the key constructs available in existing languages.
A Survey on Aspect-Based Sentiment Classification
Authors: Brauwers Gianni , Frasincar Flavius
Published: December 2021

With the constantly growing number of reviews and other sentiment-bearing texts on the Web, the demand for automatic sentiment analysis algorithms continues to expand. Aspect-based sentiment classification (ABSC) allows for the automatic extraction of highly fine-grained sentiment information from text documents or sentences. In this survey, the rapidly evolving state of the research on ABSC is reviewed. A novel taxonomy is proposed that categorizes the ABSC models into three major categories: knowledge-based, machine learning, and hybrid models. This taxonomy is accompanied with summarizing overviews of the reported model performances, and both technical and intuitive explanations of the various ABSC models. State-of-the-art ABSC models are discussed, such as models based on the transformer model, and hybrid deep learning models that incorporate knowledge bases. Additionally, various techniques for representing the model inputs and evaluating the model outputs are reviewed. Furthermore, trends in the research on ABSC are identified and a discussion is provided on the ways in which the field of ABSC can be advanced in the future.
FOXO1 Is a Critical Switch Molecule for Autophagy and Apoptosis of Sow Endometrial Epithelial Cells Caused by Oxidative Stress
Authors: Lu Jiayin , Huang Jiaqiang , Zhao Shisu , Xu Wenjiao , Chen Yaoxing , Li Yuanyuan , Wang Zixu , Dong Yanjun , You Renrong , Cao Jing , Dong Yulan
Published: December 2021

Oxidative stress (OS) is involved in various reproductive diseases and can induce autophagy and apoptosis, which determine the different fates of cells. However, the sequence and the switch mechanism between autophagy and apoptosis are unclear. Here, we reported that chronic restraint stress (CRS) induced OS (decreased T‐AOC, T‐SOD, CAT and GSH‐Px and increased MDA) and then disturbed the endocrine environment of sows during early pregnancy, including the hypothalamic‐pituitary‐ovarian (HPO) and the hypothalamic‐pituitary‐adrenal (HPA) axes. Meanwhile, after CRS, the KEAP1/NRF2 pathway was inhibited and attenuated the antioxidative ability to cause OS of the endometrium. The norepinephrine (NE) triggered β2‐AR to activate the FOXO1/NF‐κB pathway, which induced endometrial inflammation. CRS induced the caspase‐dependent apoptosis pathway and caused MAP1LC3‐II accumulation, SQSTM1/p62 degradation, and autophagosome formation to initiate autophagy. Furthermore, in vitro, a cellular OS model was established by adding hydrogen peroxide into cells. Low OS maintained the viability of endometrial epithelial cells by triggering autophagy, while high OS induced cell death by initiating caspase‐dependent apoptosis. Autophagy preceded the occurrence of apoptosis, which depended on the subcellular localization of FOXO1. In the low OS group, FOXO1 was exported from the nucleus to be modified into Ac‐FOXO1 and bound to ATG7 in the cytoplasm, which promoted autophagy to protect cells. In the high OS group, FOXO1 located in the nucleus to promote transcription of proapoptotic proteins and then induce apoptosis. Here, FOXO1, as a redox sensor switch, regulated the transformation of cell autophagy and apoptosis. In summary, the posttranslational modification of FOXO1 may become the target of OS treatment.
Effectiveness of Contralaterally Controlled Functional Electrical Stimulation versus Neuromuscular Electrical Stimulation on Upper Limb Motor Functional Recovery in Subacute Stroke Patients: A Randomized Controlled Trial
Authors: Huang Songhua , Liu Peile , Chen Yinglun , Gao Beiyao , Li Yingying , Chen Chan , Bai Yulong
Published: December 2021

Purpose. To compare the effectiveness of contralaterally controlled functional electrical stimulation (CCFES) versus neuromuscular electrical stimulation (NMES) on motor recovery of the upper limb in subacute stroke patients. Materials and Methods. Fifty patients within six months poststroke were randomly assigned to the CCFES group (

n
=
25

) and the NMES group (

n
=
25

). Both groups underwent routine rehabilitation plus 20-minute stimulation on wrist extensors per day, five days a week, for 3 weeks. Fugl-Meyer Assessment of upper extremity (FMA-UE), action research arm test (ARAT), Barthel Index (BI), and surface electromyography (sEMG) were assessed at baseline and end of intervention. Results. After a 3-week intervention, FMA-UE and BI increased in both groups (

p
<
0.05

). ARAT increased significantly only in the CCFES group (

p
<
0.05

). The changes of FMA-UE, ARAT, and BI in the CCFES group were not greater than those in the NMES group. The improvement in sEMG response of extensor carpi radialis by CCFES was greater than that by NMES (

p
=
0.026

). The cocontraction ratio (CCR) of flexor carpi radialis did not decrease in both groups. Conclusions. CCFES improved upper limb motor function, but did not show better treatment effect than NMES. CCFES significantly enhanced the sEMG response of paretic extensor carpi radialis compared with NMES, but did not decrease the cocontraction of antagonist.
The Complex Dynamics of Sharing Platform Competition Game
Authors: Xiao Jianli
Published: December 2021

With the rapid development of Internet technologies and online sharing platforms, sharing economy has become a major trend in economy. The entry of sharing economy leads to profound impacts on incumbent industry. We build a dynamic sharing platform competition model with which agents are bounded rational, and consumer side is heterogeneous. Then, we present the fixed points and the stability conditions of the bifurcation of the dynamic model. We simulate the adjustment speed of sharing platform, sharing platform price, and costs of traditional firm effects on system stability, and we present stable area, bifurcation diagram, the largest Lyapunov exponent, and strange attractor of different parameters, and we give a feedback control method at last. Our main results are as follows: (1) when adjustment speed of sharing platform increases, the system becomes bifurcation, and finally, the system goes into a chaotic state; when the system is stable, price of traditional firm and fee decision of sharing platform are constant. (2) When price of sharing platform increases, sharing platform is more stable while traditional firm is more vulnerable. Suppose the system is in the stable state; when sharing platform price increases, traditional firm price increases, while sharing platform fees decreases. (3) When traditional firm cost is small, the system would be more stable. When the system is stable, with traditional firm cost increasing, traditional firm price increases quicker than sharing platform consumer fee, while sharing platform seller fee decreases. (4) Feedback control can alleviate the chaotic state of system. With feedback control parameter increases, the system becomes more stable.
Penetration of Silver Diamine Fluoride in Deep Carious Lesions of Human Permanent Teeth: An In Vitro Study
Authors: Manuschai Jutharat , Talungchit Supitcha , Naorungroj Supawadee
Published: December 2021

Background. When silver diamine fluoride (SDF) is used in conjunction with conservative caries removal in deep carious lesions, the distribution depth of silver is critical for safety and effectiveness. Objective. The purpose of this study is to determine the effect of selected caries removal on silver penetration when 38% SDF is applied to deep carious lesions in permanent teeth. Methods. Extracted permanent teeth with caries extending to the inner third of the dentin were used (N = 18). The periphery of the carious lesion was completely removed to the dentinoenamel junction (DEJ). In group A (n = 9), no further removal of carious tissue was performed, leaving necrotic dentin inner to the DEJ, whereas in group B (n = 9) superficial necrotic dentin was completely removed until leathery, slightly moist, reasonably soft dentin remained. SDF was applied for 3 minutes in both groups. Microcomputer tomography (micro-CT) and field emission scanning electron microscopy coupled with energy-dispersive X-ray spectroscopy (FESEM-EDS) were used to measure mineral density and silver distribution. The silver penetration depth/lesion depth (PD/LD) ratio was calculated for each sample. The Mann–Whitney U test was used to compare differences between the two groups. Results. The micro-CT analysis showed that the PD/LD ratios of group B (1.07–2.29) were marginally greater than those of group A (1.00–1.31). However, a statistically significant difference was not observed (

p

value = 0.5078). When stratified by remaining dentin thickness (RDT), the PD/LD ratios of group B were still greater than those of group A only when RDT was >500 µm. The FESEM-EDS analysis indicated that silver particles precipitated throughout the entire thickness of the carious lesions. Conclusion. Applying SDF on a deep carious lesion and leaving the necrotic dentin pulpally did not affect silver penetration. However, the extent to which silver penetrates the remaining dentin beneath the lesions is dependent on the amount and characteristics of that dentin.
Inverse Family of Numerical Methods for Approximating All Simple and Roots with Multiplicity of Nonlinear Polynomial Equations with Engineering Applications
Authors: Shams Mudassir , Rafiq Naila , Kausar Nasreen , Ahmed Shams Forruque , Mir Nazir Ahmad , Chandra Saha Suvash
Published: December 2021

A new inverse family of the iterative method is interrogated in the present article for simultaneously estimating all distinct and multiple roots of nonlinear polynomial equations. Convergence analysis proves that the order of convergence of the newly constructed family of methods is two. The computer algebra systems CAS-Mathematica is used to determine the lower bound of convergence order, which justifies the local convergence of the newly developed method. Some nonlinear models from physics, chemistry, and engineering sciences are considered to demonstrate the performance and efficiency of the newly constructed family of inverse simultaneous methods in comparison to classical methods in the literature. The computational time in seconds and residual error graph of the inverse simultaneous methods are also presented to elaborate their convergence behavior.
A Pregnancy Case of Primary Mediastinal Large B Cell Lymphoma with Superior Vena Cava Syndrome
Authors: Brownhalls Lauren , Gillett Ann , Whately Yasmin , Tanaka Keisuke
Published: December 2021

Primary mediastinal large B cell lymphoma (PMLBCL) is a subtype of non-Hodgkin’s lymphoma which presents rarely in pregnancy. It is an aggressive tumour that is associated with symptoms of superior vena cava (SVC) compression and airway compromise such as dyspnoea, facial and arm swelling, cough, or chest pain. Timely diagnosis is imperative to optimising patient outcomes and reducing both maternal and fetal morbidity and mortality. We report a case of a 33-year-old woman diagnosed with PMLBCL who presented at 33-week gestation with SVC obstruction to 1 mm in diameter. After multidisciplinary team discussion regarding maternal and fetal implications of management options, we proceeded to a caesarean section and initiated chemotherapy postdelivery. Lower segment caesarean section was uncomplicated, and she underwent a cycle of R-CHOEP followed by 5 cycles of DA-EPOCH. Eighteen months since the completion of the chemotherapy, the disease remained in remission.
Exploration of the Potential Mechanisms of Wumei Pill for the Treatment of Ulcerative Colitis by Network Pharmacology
Authors: Huang Jinke , Zheng Yijun , Ma Jinxin , Ma Jing , Lu Mengxiong , Ma Xiangxue , Wang Fengyun , Tang Xudong
Published: December 2021

Background. Wumei pill (WMP) has a long history of colitis treatment in China, but the protective mechanisms have not been elucidated. To uncover the potential mechanisms of WMP against ulcerative colitis (UC), the network pharmacology approach was utilized in this study. Methods. Public databases were utilized to identify the potential targets of WMP and genes related to UC. Based on the identified overlapping common targets, drug-ingredient-target gene network, Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, and protein-protein interaction (PPI) analysis were conducted. Molecular docking was carried out to verify the selected key active ingredients and core targets. Results. 129 active ingredients and 622 target genes were obtained. The drug-ingredient-target gene network revealed 52 active ingredients of WMP acting on 73 targets related to UC. GO analysis revealed that biological processes were mainly associated with oxidative stress, such as, reactive oxygen species metabolic processes, response to oxidative stress, cellular response to oxidative stress, response to reactive oxygen species, and regulation of reactive oxygen species metabolic processes. KEGG analysis revealed that the immune- and inflammation-related pathways, tumor-related signaling pathways, and microbial infection-related signaling pathways were the most significant. PPI network identified 13 core target genes. The molecular docking results indicated the formation of stable bonds between the active ingredients and core target genes. Conclusions. The approach of network pharmacology reveals the key ingredients, potential core targets, and biological process of WMP in the treatment of UC. The mechanisms of action of WMP involve anti-inflammation, antioxidation, and modulation of immunity, which provides evidence for the therapeutic role of WMP in UC.
Trends in Incidence and Survival of Patients with Pancreatic Neuroendocrine Neoplasm, 1987–2016
Authors: Wang Jingxuan , Liu Jianhua , He Chao , Sun Tiantian , Yan Yan , Che Gang , Li Xuemin , Sun Huanhuan , Ma Haiqing
Published: December 2021

Background. Pancreatic neuroendocrine neoplasm (pNEN), with the lowest 5-year survival rates in neuroendocrine tumors (NETs), exerts great threat to human health. Because large-scale population research aimed at pNEN is rare, we aimed to explore the tendencies and differences of changes in incidences and survival rates of pNEN in each decade from 1987 to 2016 and evaluate the impacts of age, sex, race, socioeconomic status (SES), and grade. Methods. Data on pNEN cases from 1987 to 2016 were extracted from the Surveillance, Epidemiology, and End Results Program (SEER) database. Kaplan–Meier, Cox proportional hazards regression analyses, and relative survival rates (RSRs) were used to identify risk factors for pNEN. Results. The incidence and survival duration of pNEN increase every decade due to medical developments. The disparities of long-term survival in different age, sex, and grade groups expanded over time while that in race and SES groups narrowed. Older age and higher grade are independent risk factors for poorer survival. Females have lower incidence and longer survival than males. Prognosis of Black patients and poor (medium and high poverty) patients improved. Conclusions. This study depicted changes in incidence and survival rates of pNEN over the past three decades and evaluated potential risk factors related to pNEN, benefiting future prediction of vulnerable and clinical options.
Analysis of Digital Long Jump Take‐off Wearable Sensor Monitoring System
Authors: Wang Baosen , Zong Bobo , Wang Hongwei , Han Bo
Published: December 2021

The wearable sensor monitoring system builds a long jump take‐off recognition network model based on different digital feature extraction methods (one‐dimensional digital feature extraction method, two‐dimensional digital feature extraction method, and feature extraction method combining one‐dimensional digitization and recursion). Experimental verification and analysis are performed on the processed sample data, and the identification effects, advantages, and disadvantages of the four methods are obtained. First, the sensor behavior movement collection software is designed based on the Android system, and the collection time and frequency are specified at the same time. In addition, for the problem of multisensor behavior recognition, an effective result fusion method is proposed. In a multisensor behavior recognition system, constructing a parallel processing architecture is conducive to improving the rate of behavior recognition. To maintain or increase the rate of behavior recognition, the result fusion method plays a vital role. Finally, this paper analyzes the process of multitask behavior recognition and constructs a residual model that can effectively integrate multitask results and fully mine data information. The experimental results show that, for the monitoring of exercise volume, we use step count statistics to extract feature values that can distinguish activity types based on human motion characteristics. This paper proposes a sample autonomous learning method to find the optimal sample training set and avoid occurrence of overfitting problems. In the recognition of 11 types of long jump take‐offs, the average accuracy rate reached 98.7%. The average replacement method is used to count the number of steps, which provides a data reference for the user’s daily exercise volume.
Estimation of Arc Welding Pressure Pipeline Weld Peaking Parameters Based on Data Prediction
Authors: Liao Pu , Liu Guixiong , Yang Ningxiang
Published: December 2021

Peaking parameter is the key content in the regular inspection of the pressure pipeline. Solving the problem of the peaking measurement method defined by a standard cannot be applied to a situation in which there exists a weld surface with reinforcement and misalignment. In this paper, a peaking estimation method based on data prediction was proposed to estimate the contour information of the base metal at the weld joint using the contour point set data of the base metal part of the weld. Herein, the longitudinal weld peaking estimation method based on a piecewise logistic regression (PLR) and the girth weld peaking estimation method based on a piecewise Bayesian linear regression (PBLR) were studied, and the midpoint of the two symmetrical points of the base metal on either side of the weld was used as a reference for calculating the peaking. Finally, we collected the surface profile data of longitudinal weld pressure pipes with diameters of 155 mm, 255 mm, 550 mm, and 600 mm and the surface profile data of girth weld pressure pipes with diameters of 120 mm, 130 mm, 140 mm, and 170 mm. This weld seam data used the data estimation method proposed in this article and traditional long short-term memory and fitting methods. The results showed that the proposed data prediction method could accurately predict the position of the base metal, and the theoretical mean absolute error of the peaking estimation based on the PBLR and PLR could attain 0.06 mm and 0.07 mm, respectively, which meets the parameter measurement requirements of related verification fields.
TSN Switch Queue Length Prediction Based on an Improved LSTM Network
Authors: Wang Xin , Shang Zhijun , Xia Changqing , Cui Shijie , Shao Shuai
Published: December 2021

With the high‐speed development of network technology, time‐sensitive networks (TSNs) are experiencing a phase of significant traffic growth. At the same time, they have to ensure that highly critical time‐sensitive information can be transmitted in a timely and accurate manner. In the future, TSNs will have to further improve network throughput to meet the increasing traffic demand based on the guaranteed transmission delay. Therefore, an efficient route scheduling scheme is necessary to achieve network load balance and improve network throughput. A time‐sensitive software‐defined network (TSSDN) can address the highly distributed industrial Internet network infrastructure, which cannot be accomplished by traditional industrial communication technologies, and it can achieve distributed intelligent dynamic route scheduling of the network through global network monitoring. The prerequisite for intelligent dynamic scheduling is that the queue length of future switches can be accurately predicted so that dynamic route planning for flow can be performed based on the prediction results. To address the queue length prediction problem, we propose a TSN switch queue length prediction model based on the TSSDN architecture. The prediction process has three steps: network topology dimension reduction, feature selection, and training prediction. The principal component analysis (PCA) algorithm is used to reduce the dimensionality of the network topology to eliminate unnecessary redundancy and overlap of relevant information. Feature selection requires comprehensive consideration of the influencing factors that affect the switch queue length, such as time and network topology. The training prediction is performed with the help of our enhanced long short‐term memory (LSTM) network. The input‐output structure of the network is changed based on the extracted features to improve the prediction accuracy, thus predicting the network congestion caused by bursty traffic. Finally, the results of the simulation demonstrate that our proposed TSN switch queue length prediction model based on the improved LSTM network algorithm doubles the prediction accuracy compared to the original model because it considers more influencing factors as features in the neural network for training and learning.
The Effect of Sandblasting on Bond Strength of Soft Liners to Denture Base Resins: A Systematic Review and Meta-Analysis of In Vitro Studies
Authors: Hamedirad Fahimeh , Alikhasi Marzieh , Hasanzade Mahya
Published: December 2021

Objectives. This study aimed to evaluate the effect of sandblasting on the bond strength of denture base resin to soft liners. Materials and Methods. This report follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. PubMed, Embase, Cochrane, Scopus, and OpenGrey databases were searched for in vitro studies that compared sandblasting with no treatment in terms of the tensile, shear, and peel bond strength of resilient lining materials (acrylic-based or silicone-based) to polymethyl methacrylate denture base resin. Based on the outcome, the analysis was carried out in three groups of tensile, shear, and peel bond strength. Subgroup analysis was done for the effect of size of particles on sandblasting, blasting pressure, and type of soft liner whenever possible. Heterogeneity was evaluated among the studies, and meta-analysis was performed with random effect models (p<.05). Results. After screening, 16 articles met the inclusion criteria for meta-analyses. No treatment showed significantly higher tensile (p<0.001) or peel (p=0.04) bond strength, although shear bond strength of sandblasted resin was significantly better (p=0.008). Results of subgroup analyses of particle size favored the control group in 50 µ Al2O3 particle size (p<0.001). In analyses of blasting pressure, the control group had significantly better tensile bond strength than specimens with blasting pressure ≤1 bar (p<0.001) while specimens with blasting pressure beyond 1 bar showed significantly more tensile strength than control group (p=0.03). In silicon-based liners, groups without any surface treatment had significantly higher tensile bond strength (p<0.001). Conclusion. According to the in vitro studies, sandblasting would not lead to significant increase in bond strength of soft liner to the denture base resin.
Use of mNUTRIC-Score for Nutrition Risk Assessment and Prognosis Prediction in Critically Ill Patients with COVID-19: A Retrospective Observational Study
Authors: Yanowsky-Escatell Francisco G. , Ontiveros-Galindo Areli L. , Arellano-Arteaga Kevin J. , Román-Pintos Luis M. , Andrade-Castellanos Carlos A. , Hernández-Corona Diana M. , González-Heredia Tonatiuh , Villegas-Rivera Geannyne
Published: December 2021

Introduction. Nutritional risk is highly prevalent in patients with COVID-19. Relevant data on nutritional assessment in the critically ill population are scarce. This study was conducted to evaluate the modified Nutrition Risk in the Critically Ill (mNUTRIC)-Score as a mortality risk factor in mechanically ventilated patients with COVID-19. Methods. We conducted this retrospective observational study in critically ill patients with COVID-19. Patients’ characteristics and clinical information were obtained from electronic medical records. The nutritional risk for each patient was assessed at the time of mechanical ventilation using the mNUTRIC-Score. The major outcome was 28-day mortality. Results. Ninety-eight patients were analyzed (mean age, 57.22 ± 13.66 years, 68.4% male); 46.9% of critically ill COVID-19 patients were categorized as being at high nutrition risk (mNUTRIC-Score of ≥5). A multivariate logistic regression model indicated that high nutritional risk has higher 28-day hospital mortality (OR = 4.206, 95% CI: 1.147–15.425,

p
=
0.030

). A multivariate Cox regression analysis showed that high-risk mNUTRIC-Score had a significantly increased full-length mortality risk during hospitalization (OR = 1.991, 95% CI: 1.219–3.252,

p
=
0.006

). Conclusion. The mNUTRIC-Score is an independent mortality risk factor during hospitalization in critically ill COVID-19 patients.
The Effects of Omega-3 Supplementation on Resting Metabolic Rate: A Systematic Review and Meta-Analysis of Clinical Trials
Authors: Yarizadeh Habib , Hassani Bahar , Nosratabadi Saeed , Baharlooi Hussein , Asadi Sara , Bagherian Seyed Ahmad , Islam Shariful , Djafarian Kurosh , Mirzaei Khadijeh
Published: December 2021

Background. It is uncertain if omega-3 polyunsaturated fatty acids are associated with increase in resting metabolic rate (RMR) in adults. Objective. The aim of the present study was to evaluate the overall effects of omega-3 on RMR. Methods. Both PubMed and Scopus libraries were searched up to April 2021. Study quality was assessed using the Jadad scale. Random- and fixed-effects models were utilized in order to obtain pooled estimates of omega-3 supplementation impacts on RMR, using weight mean difference (WMD). Results. Seven studies including a total of 245 participants were included. There was significantly higher FFM-adjusted RMR in the intervention group than the control group (WMD: 26.666 kcal/kg/day, 95% CI: 9.010 to 44.322,

p
=
0.003

). Study quality showed that four of seven included studies were of high quality. However, there was no significant difference in results in the subgroup analysis according to the quality of studies. Subgroup analyses revealed significant changes for sex (for women: WMD = 151.793 kcal/day, 95% CI = 62.249 to 241.337,

p
=
0.001

) and BMI (for BMI > 25: WMD = 82.208 kcal/day, 95% CI = 0.937 to 163.480,

p
=
0.047

). Influence analysis indicated no outlier among inclusions. Conclusion. The current study depicted that omega-3 polyunsaturated acids can significantly increase RMR in adults. However, further assessments of omega-3 supplementation therapy are critical to monitor its long-term outcomes and potential clinical application.
Designing an Optimum and Reduced Order Filter for Efficient ECG QRS Peak Detection and Classification of Arrhythmia Data
Authors: Amhia Hemant , Wadhwani A. K.
Published: December 2021

Electrocardiogram (ECG) is commonly used biological signals that show an important role in cardiac analysis. The interpretation and acquisition of QRS complex are significant measures of ECG data dispensation. The R wave has a vital character in the analysis of cardiac rhythm irregularities as well as in the determination of heart rate variability (HRV). This manuscript is proposed to design a new artificial-intelligence-based approach of QRS peak detection and classification of the ECG data. The design of reduced order IIR filter is proposed for the low pass smoothening of the ECG signal data. The min-max optimization is used for optimizing the filter coefficient to design the reduced order filter. In this research paper, elimination of baseline wondering and the power line interferences from the ECG signal is of main attention. The result presented that the accuracy is increased by around 13% over the basic Pan–Tompkins method and around 8% over the existing FIR-filter-based classification rules.
Reliability Estimation for the Remained Stress-Strength Model under the Generalized Exponential Lifetime Distribution
Authors: Saber Mohammad Mehdi , Mohie El-Din Marwa M. , Yousof Haitham M.
Published: December 2021

A stress-strength reliability model compares the strength and stresses on a certain system; it is used not only primarily in reliability engineering and quality control but also in economics, psychology, and medicine. In this paper, a novel extension of stress-strength models is presented. The mew model is applied under the generalized exponential distribution. The maximum likelihood estimator, asymptotic distribution, and Bayesian estimation are obtained. A comprehensive simulation study along with real data analysis is performed for illustrating the importance of the new stress-strength model.