bluuebunny/crossref_metadata_2025 huggingface dataset:
Management of patellar tendinopathy: a systematic review and network meta-analysis of randomised studies
Authors: Challoumas Dimitris , Pedret Carles , Biddle Mairiosa , Ng Nigel Yong Boon , Kirwan Paul , Cooper Blair , Nicholas Patrick , Wilson Scott , Clifford Chris , Millar Neal L
Published: November 2021

Objectives

We performed a systematic review and network meta-analysis (NMA) of randomised controlled trials (RCTs) to provide insights into the effectiveness of available treatment modalities in patellar tendinopathy(PT).

Methods

Several databases were searched in May 2021 for RCTs assessing the effectiveness of any intervention compared with any other intervention, placebo or no treatment for pain and/or function in PT. The risk of bias and strength of evidence were assessed with the Cochrane Collaboration and GRADE (Grading of Recommendations, Assessment, Development and Evaluations)/GRADE-NMA tools.

Results

A total of 37 RCTs were eligible that assessed 33 different interventions and their combinations, most represented by single studies. Based on pairwise meta-analyses of two RCTs, extracorporeal shockwave therapy (ESWT) does not appear to be superior to sham ESWT (eccentric exercise in both groups) for short-term pain (mean differences (MD) +0.1, 95% CI (−0.8 to 1), p=0.84) or function (MD −1.8, 95% CI (–8 to 4.4), p=0.57). Based on a pairwise meta-analysis of three RCTs, isometric exercise appears as effective as isotonic exercise for immediate postintervention pain relief (MD −1.03, 95% CI (−2.6 to 0.5), p=0.19). Our NMA showed that topical glyceryl trinitrate (GTN) and hyaluronic acid injection, both combined with eccentric exercise and moderate, slow resistance exercise had the highest probability of being the most effective interventions (low/very low strength of evidence).

Conclusions

Promising interventions with inadequate evidence, such as topical GTN, hyaluronic acid injections and isometric and slow resistance exercise, should be further investigated through high-quality RCTs. Meanwhile, eccentric loading with or without adjuncts should remain the first-line treatment for all individuals with patellar tendinopathy.
Integrated analysis reveals prognostic value of HLA-I LOH in triple-negative breast cancer
Authors: Zhou Yi-Fan , Xiao Yi , Jin Xi , Di Gen-Hong , Jiang Yi-Zhou , Shao Zhi-Ming
Published: November 2021

Background

Triple-negative breast cancers (TNBCs), especially those non-immune-inflamed tumors, have a poor prognosis and limited therapies. Human leukocyte antigen (HLA)-I not only contributes to antitumor immune response and the phenotype of the tumor microenvironment, but also is a negative predictor of outcomes after immunotherapy. However, the importance of HLA functional status in TNBCs remains poorly understood.

Methods

Using the largest original multiomics datasets on TNBCs, we systematically characterized the HLA-Ⅰ status of TNBCs from the perspective of HLA-Ⅰ homogeneity and loss of heterozygosity (LOH). The prognostic significance of HLA-I status was measured. To explain the potential mechanism of prognostic value in HLA-Ⅰ status, the mutational signature, copy number alteration, neoantigen and intratumoral heterogeneity were measured. Furthermore, the correlation between HLA-Ⅰ functional status and the tumor immune microenvironment was analyzed.

Results

LOH and homogeneity in HLA-I accounted for 18% and 21% of TNBCs, respectively. HLA-I LOH instead of HLA-I homogeneity was an independent prognostic biomarker in TNBCs. In particular, for patients with non-immune-inflamed tumors, HLA-I LOH indicated a worse prognosis than HLA-I non-LOH. Furthermore, integrated genomic and transcriptomic analysis showed that HLA-I LOH was accompanied by upregulated scores of mutational signature 3 and homologous recombination deficiency scores, which implied the failure of DNA double-strand break repair. Moreover, HLA-I LOH had higher mutation and neoantigen loads and more subclones than HLA-I non-LOH. These results indicated that although HLA-I LOH tumors with failure of DNA double-strand break repair were prone to produce neoantigens, their limited capacity for antigen presentation finally contributed to poor immune selection pressure.

Conclusion

Our study illustrates the genomic landscape of HLA-I functional status and stresses the prognostic significance of HLA-I LOH in TNBCs. For “cold” tumors in TNBCs, HLA-I LOH indicated a worse prognosis than HLA-I non-LOH.
Comprehensive epithelial tubo-ovarian cancer risk prediction model incorporating genetic and epidemiological risk factors
Authors: Lee Andrew , Yang Xin , Tyrer Jonathan , Gentry-Maharaj Aleksandra , Ryan Andy , Mavaddat Nasim , Cunningham Alex P , Carver Tim , Archer Stephanie , Leslie Goska , Kalsi Jatinder , Gaba Faiza , Manchanda Ranjit , Gayther Simon , Ramus Susan J , Walter Fiona M , Tischkowitz Marc , Jacobs Ian , Menon Usha , Easton Douglas F , Pharoah Paul , Antoniou Antonis C
Published: November 2021

Background

Epithelial tubo-ovarian cancer (EOC) has high mortality partly due to late diagnosis. Prevention is available but may be associated with adverse effects. A multifactorial risk model based on known genetic and epidemiological risk factors (RFs) for EOC can help identify women at higher risk who could benefit from targeted screening and prevention.

Methods

We developed a multifactorial EOC risk model for women of European ancestry incorporating the effects of pathogenic variants (PVs) in BRCA1, BRCA2, RAD51C, RAD51D and BRIP1, a Polygenic Risk Score (PRS) of arbitrary size, the effects of RFs and explicit family history (FH) using a synthetic model approach. The PRS, PV and RFs were assumed to act multiplicatively.

Results

Based on a currently available PRS for EOC that explains 5% of the EOC polygenic variance, the estimated lifetime risks under the multifactorial model in the general population vary from 0.5% to 4.6% for the first to 99th percentiles of the EOC risk distribution. The corresponding range for women with an affected first-degree relative is 1.9%–10.3%. Based on the combined risk distribution, 33% of RAD51D PV carriers are expected to have a lifetime EOC risk of less than 10%. RFs provided the widest distribution, followed by the PRS. In an independent partial model validation, absolute and relative 5-year risks were well calibrated in quintiles of predicted risk.

Conclusion

This multifactorial risk model can facilitate stratification, in particular among women with FH of cancer and/or moderate-risk and high-risk PVs. The model is available via the CanRisk Tool (www.canrisk.org).
Two-year efficacy and safety of erenumab in participants with episodic migraine and 2–4 prior preventive treatment failures: results from the LIBERTY study
Authors: Ferrari Michel Dominique , Reuter Uwe , Goadsby Peter J , Paiva da Silva Lima Gabriel , Mondal Subhayan , Wen Shihua , Tenenbaum Nadia , Pandhi Shaloo , Lanteri-Minet Michel , Stites Tracy
Published: November 2021

Objective

To evaluate individual and group long-term efficacy and safety of erenumab in individuals with episodic migraine (EM) for whom 2–4 prior preventatives had failed.

Methods

Participants completing the 12-week double-blind treatment phase (DBTP) of the LIBERTY study could continue into an open-label extension phase (OLEP) receiving erenumab 140 mg monthly for up to 3 years. Main outcomes assessed at week 112 were: ≥50%, ≥75% and 100% reduction in monthly migraine days (MMD) as group responder rate and individual responder rates, MMD change from baseline, safety and tolerability.

Results

Overall 240/246 (97.6%) entered the OLEP (118 continuing erenumab, 122 switching from placebo). In total 181/240 (75.4%) reached 112 weeks, 24.6% discontinued, mainly due to lack of efficacy (44.0%), participant decision (37.0%) and adverse events (AEs; 12.0%). The ≥50% responder rate was 57.2% (99/173) at 112 weeks. Of ≥50% responders at the end of the DBTP, 36/52 (69.2%) remained responders at ≥50% and 22/52 (42.3%) at >80% of visits. Of the non-responders at the end of the DBTP, 60/185 (32.4%) converted to ≥50% responders in at least half the visits and 24/185 (13.0%) converted to ≥50% responders in >80% of visits. Change from baseline at 112 weeks in mean (SD) MMD was −4.2 (5.0) days. Common AEs (≥10%) were nasopharyngitis, influenza and back pain.

Conclusions

Efficacy was sustained over 112 weeks in individuals with difficult-to-treat EM for whom 2–4 prior migraine preventives had failed. Erenumab treatment was safe and well tolerated, in-line with previous studies.

Trial registration number

NCT03096834
Variations in cigarette brand characteristics: can consumers tell the difference?
Authors: Pennings Jeroen L A , Ferris Wayne Geoffrey , Klerx Walther N M , Pauwels Charlotte G G M , Talhout Reinskje
Published: November 2021

Objectives

Sensory experience is an important determinant of smoking initiation, brand choice and harm perception, but little is known about how cigarette design shapes sensory experience. This study reports which variations in tobacco blend and design characteristics available on the market are likely to be perceived as different by consumers.

Methods

Truth Tobacco Industry Documents was reviewed for studies showing noticeable sensory differences resulting from variations in tobacco blend and design characteristics. These differences were compared with tobacco product data as available in the Dutch section of the European Common Entry Gate (EU-CEG) system on 30 April 2020.

Results

Industry documents identified discrimination thresholds for ventilation, pressure drop, tobacco weight, filter length, and tar and nicotine levels in smoke while evidence for other design characteristics was less conclusive. In the 103 different cigarette varieties in the EU-CEG database, five main types of cigarettes could be identified by principal component analysis, differing in (combinations of) design characteristics. The most significant differences between brand varieties were tar, nicotine and carbon monoxide emissions and associated parameters filter ventilation, filter length, cigarette length and tobacco weight.

Conclusions

While some clusters of brand varieties provided a noticeably different product for consumers, in many cases design differences within these clusters did not exceed the expected discrimination threshold. This indicates that many products on the market are not discernibly different for consumers, and that proliferation of brand varieties has a non-sensory purpose, such as marketing. Policy makers should consider limiting available brand varieties and regulating design characteristics to reduce product appeal.
Exception from informed consent trials: social-media-based community consultation campaigns are representative of target communities
Authors: Farley Paige , Stephens Shannon W , Crowley Brandon , Collins Sean P , Wong Monica D , Panas Ashley B , Dennis Bradley M , Richmond Neal , Inaba Kenji , Brown Karen N , Holcomb John B , Jansen Jan O
Published: November 2021

Background

‘Community consultation’ (CC) is a key step when conducting Exception From Informed Consent research. Social-media-based CC has been shown to reach more people than traditional methods, but it is unclear whether those reached are representative of the community as a whole.

Methods

This is a retrospective analysis of the CC performed in preparation for the PHOXSTAT trial. Social media advertisement campaigns were conducted in the catchment areas of the three participating trauma centers and evaluated by examining Facebook user statistics. We compared these data to georeferenced population data obtained from the U.S. Census Bureau. We examined variations in the proportion of each age group reached, by gender.

Results

Our social media advertisements reached a total of 332 081 individuals in Los Angeles, Birmingham, and Nashville. Although there were differences in the proportion of individuals reached within each age group and gender groups, compared with the population in each area, these were small (within 5%). In Birmingham, participants 55 to 64 years old, 25 to 34 years old, and females 18 to 24 years old were slightly over-represented (a larger proportion of individuals in this age group were reached by the social media campaign, compared with the population resident in this area). In contrast, in Nashville, female participants 45 to 64 years old, and males 25 to 64 years old were over-represented. In Los Angeles, females 45 to 64 years old, and males 25 to 64 years and over were over-represented.

Discussion

In conclusion, this study demonstrates that social media CC campaigns can be used to reach a sample of the community broadly representative of the population as a whole, in terms of age and gender. This finding is helpful to IRBs and investigators, as it lends further support to the use of social media to conduct CC. Further work is needed to analyze how representative community samples are in terms of other characteristics, such as race, ethnicity, and socioeconomic status.

Level III evidence

Economic & Value-based Evaluations.
Non-Fickian diffusion in viscous aerosol particles
Authors: Preston Thomas C.
Published: November 2021

Slow condensed phase diffusion in organic aerosol particles can impede many chemical and physical processes associated with atmospheric aerosol (e.g., gas-particle equilibrium partitioning). The characteristic times associated with these high viscosity particles are typically modelled using a concentration-dependent diffusivity within a purely Fickian framework. In that model, the medium in which diffusion is taking place is treated as being inviscid as far as mass transport is concerned. In this report, we investigate the validity of assuming that the viscosity is equal to zero by using a transport model that includes viscous pressure gradients. It is found that the effect of viscosity is negligible for particles with radii that are larger than 100 nm, but below that radius, it can delay water uptake and loss by orders of magnitude for physically realistic viscosities. However, if the Stokes–Einstein relation is obeyed, then viscosity can be ignored, even for nanosized particles. In addition to numerical calculations, a dimensionless Deborah number is defined that indicates the significance of Fickian diffusion compared with the rheological response during water transport.
On Penrose’s theory of objective gravitationally induced wave function reduction
Authors: Gallego Torromé Ricardo
Published: November 2021

In this paper, the formal structure of Penrose’s gravitationally induced reduction of the wave function mechanism is analyzed. It is shown that pushing Penrose’s argument forward leads to the interpretation of quantum coherence in microscopic systems as an observable signature violation of general covariance. We discuss potential avenues to avoid this conclusion, among them emergent quantum mechanics and super-determinism.
EFFECTS OF CLIMATE CHANGE ON ELECTRICITY CONSUMPTION: A DECOMPOSITION OF INDUSTRIAL, RESIDENTIAL, AGRICULTURAL, AND COMMERCIAL SECTORS
Authors: KIM HYUN-GYU
Published: November 2021

This study explores the impacts of temperature changes on electricity consumption in South Korea. In particular, the study estimates the impacts by separating them into the residential, commercial, industrial, and agricultural sectors. The study found that temperature changes affect the electricity consumption of all four sectors. However, the size and shape of impacts vary depending on the sector. While the commercial and industrial electricity consumption increase both in hot and cold temperatures, residential consumption increases only in hot temperatures. The agricultural sector shows that its consumption responds to cold temperatures more significantly than hot temperatures. These results suggest that the sectoral variations should be considered when predicting future electricity consumption. With an assumption of 2°C average temperature increases, the electricity consumption of residential, commercial, industrial, and agricultural sectors is projected to increase by 6%, 8%, 1%, and 4% in the summer season (July to September), respectively. In the spatial analysis, the annual consumption of residential and commercial sectors is projected to increase in most counties while the agricultural sector shows the opposite result. With 2°C and 5°C average temperature increases, the study found that total electricity consumption in August would increase by 4.1% (1.5[Formula: see text]TWh) and 11.3% (4.1[Formula: see text]TWh). This would create additional costs of $0.17 billion and $0.45 billion with an assumption that the average marginal cost of electricity in South Korea was 11 cents per kWh.
Small-scale field evaluation of geochemical blending of waste rock to mitigate acid rock drainage potential
Authors: Day Stephen J.
Published: November 2021

Blending of potentially acid generating (PAG) waste rock with non-PAG waste rock to create a rock mixture which performs as non-PAG is a possible approach to permanent prevention of acid rock drainage (ARD) for PAG waste rock. In 2012, a field weathering study using 300 kg samples was implemented at Teck Coal's Quintette Project located in northeastern British Columbia, Canada to test the prevention of acid generation in the PAG waste rock by dissolved carbonate leached from overlying non-PAG waste rock and direct neutralization of acidic water from PAG waste rock by contact with non-PAG waste rock.

After eight years of monitoring the experiments, the layered non-PAG on PAG barrels provided proof-of-concept that as the thickness of the PAG layer increases relative to the thickness of the non-PAG layers, acidic waters are more likely to be produced. The PAG on non-PAG layering has resulted in non-acidic water and no indications of metal leaching despite accelerated oxidation in the PAG layer shown by sulfate loadings. The study has demonstrated that the scale of heterogeneity of PAG and non-PAG materials is a critical consideration for providing certainty that rock blends designed to be non-PAG will perform as non-PAG in perpetuity. This is contrary to the standard paradigm in which an excess of acid-consuming minerals is often considered sufficient alone to ensure ARD is not produced.
Synergic Deep Learning for Smart Health Diagnosis of COVID-19 for Connected Living and Smart Cities
Authors: Shankar K. , Perumal Eswaran , Elhoseny Mohamed , Taher Fatma , Gupta B. B. , El-Latif Ahmed A. Abd
Published: November 2021

COVID-19 pandemic has led to a significant loss of global deaths, economical status, and so on. To prevent and control COVID-19, a range of smart, complex, spatially heterogeneous, control solutions, and strategies have been conducted. Earlier classification of 2019 novel coronavirus disease (COVID-19) is needed to cure and control the disease. It results in a requirement of secondary diagnosis models, since no precise automated toolkits exist. The latest finding attained using radiological imaging techniques highlighted that the images hold noticeable details regarding the COVID-19 virus. The application of recent artificial intelligence (AI) and deep learning (DL) approaches integrated to radiological images finds useful to accurately detect the disease. This article introduces a new synergic deep learning (SDL)-based smart health diagnosis of COVID-19 using Chest X-Ray Images. The SDL makes use of dual deep convolutional neural networks (DCNNs) and involves a mutual learning process from one another. Particularly, the representation of images learned by both DCNNs is provided as the input of a synergic network, which has a fully connected structure and predicts whether the pair of input images come under the identical class. Besides, the proposed SDL model involves a fuzzy bilateral filtering (FBF) model to pre-process the input image. The integration of FBL and SDL resulted in the effective classification of COVID-19. To investigate the classifier outcome of the SDL model, a detailed set of simulations takes place and ensures the effective performance of the FBF-SDL model over the compared methods.
Labeling Privacy Protection SVM Using Privileged Information for COVID-19 Diagnosis
Authors: Ni Tongguang , Zhu Jiaqun , Qu Jia , Xue Jing
Published: November 2021

Edge/fog computing works at the local area network level or devices connected to the sensor or the gateway close to the sensor. These nodes are located in different degrees of proximity to the user, while the data processing and storage are distributed among multiple nodes. In healthcare applications in the Internet of things, when data is transmitted through insecure channels, its privacy and security are the main issues. In recent years, learning from label proportion methods, represented by inverse calibration (InvCal) method, have tried to predict the class label based on class label proportions in certain groups. For privacy protection, the class label of the sample is often sensitive and invisible. As a compromise, only the proportion of class labels in certain groups can be used in these methods. However, due to their weak labeling scheme, their classification performance is often unsatisfactory. In this article, a labeling privacy protection support vector machine using privileged information, called LPP-SVM-PI, is proposed to promote the accuracy of the classifier in infectious disease diagnosis. Based on the framework of the InvCal method, besides using the proportion information of the class label, the idea of learning using privileged information is also introduced to capture the additional information of groups. The slack variables in LPP-SVM-PI are represented as correcting function and projected into the correcting space so that the hidden information of training samples in groups is captured by relaxing the constraints of the classification model. The solution of LPP-SVM-PI can be transformed into a classic quadratic programming problem. The experimental dataset is collected from the Coronavirus disease 2019 (COVID-19) transcription polymerase chain reaction at Hospital Israelita Albert Einstein in Brazil. In the experiment, LPP-SVM-PI is efficiently applied for COVID-19 diagnosis.
An Unsupervised Aspect-Aware Recommendation Model with Explanation Text Generation
Authors: Sun Peijie , Wu Le , Zhang Kun , Su Yu , Wang Meng
Published: November 2021

Review based recommendation utilizes both users’ rating records and the associated reviews for recommendation. Recently, with the rapid demand for explanations of recommendation results, reviews are used to train the encoder–decoder models for explanation text generation. As most of the reviews are general text without detailed evaluation, some researchers leveraged auxiliary information of users or items to enrich the generated explanation text. Nevertheless, the auxiliary data is not available in most scenarios and may suffer from data privacy problems. In this article, we argue that the reviews contain abundant semantic information to express the users’ feelings for various aspects of items, while these information are not fully explored in current explanation text generation task. To this end, we study how to generate more fine-grained explanation text in review based recommendation without any auxiliary data. Though the idea is simple, it is non-trivial since the aspect is hidden and unlabeled. Besides, it is also very challenging to inject aspect information for generating explanation text with noisy review input. To solve these challenges, we first leverage an advanced unsupervised neural aspect extraction model to learn the aspect-aware representation of each review sentence. Thus, users and items can be represented in the aspect space based on their historical associated reviews. After that, we detail how to better predict ratings and generate explanation text with the user and item representations in the aspect space. We further dynamically assign review sentences which contain larger proportion of aspect words with larger weights to control the text generation process, and jointly optimize rating prediction accuracy and explanation text generation quality with a multi-task learning framework. Finally, extensive experimental results on three real-world datasets demonstrate the superiority of our proposed model for both recommendation accuracy and explainability.
Combining Graph Convolutional Neural Networks and Label Propagation
Authors: Wang Hongwei , Leskovec Jure
Published: November 2021

Label Propagation Algorithm (LPA) and Graph Convolutional Neural Networks (GCN) are both message passing algorithms on graphs. Both solve the task of node classification, but LPA propagates node label information across the edges of the graph, while GCN propagates and transforms node feature information. However, while conceptually similar, theoretical relationship between LPA and GCN has not yet been systematically investigated. Moreover, it is unclear how LPA and GCN can be combined under a unified framework to improve the performance. Here we study the relationship between LPA and GCN in terms of
feature/label influence
, in which we characterize how much the initial feature/label of one node influences the final feature/label of another node in GCN/LPA. Based on our theoretical analysis, we propose an end-to-end model that combines GCN and LPA. In our unified model, edge weights are learnable, and the LPA serves as regularization to assist the GCN in learning proper edge weights that lead to improved performance. Our model can also be seen as learning the weights of edges based on node labels, which is more direct and efficient than existing feature-based attention models or topology-based diffusion models. In a number of experiments for semi-supervised node classification and knowledge-graph-aware recommendation, our model shows superiority over state-of-the-art baselines.
Therapeutic Potential of In Vitro–Derived Oocytes for the Restoration and Treatment of Female Fertility
Authors: Picton Helen M.
Published: November 2021

Considerable progress has been made with the development of culture systems for the in vitro growth and maturation (IVGM) of oocytes from the earliest-staged primordial follicles and from the more advanced secondary follicles in rodents, ruminants, nonhuman primates, and humans. Successful oocyte production in vitro depends on the development of a dynamic culture strategy that replicates the follicular microenvironment required for oocyte activation and to support oocyte growth and maturation in vivo while enabling the coordinated and timely acquisition of oocyte developmental competence. Significant heterogeneity exists between the culture protocols used for different stages of follicle development and for different species. To date, the fertile potential of IVGM oocytes derived from primordial follicles has been realized only in mice. Although many technical challenges remain, significant advances have been made, and there is an increasing consensus that complete IVGM will require a dynamic, multiphase culture approach. The production of healthy offspring from in vitro–produced oocytes in a secondary large animal species is a vital next step before IVGM can be tested for therapeutic use in humans.
Accelerated Battery Lifetime Simulations Using Adaptive Inter-Cycle Extrapolation Algorithm
Authors: Sulzer Valentin , Mohtat Peyman , Pannala Sravan , Siegel Jason B. , Stefanopoulou Anna G.
Published: November 2021

We propose algorithms to speed up physics-based battery lifetime simulations by one to two orders of magnitude compared to the state-of-the-art. First, we propose a reformulation of the Single Particle Model with side reactions to remove algebraic equations and hence reduce stiffness, with 3x speed-up in simulation time (intra-cycle reformulation). Second, we introduce an algorithm that makes use of the difference between the “fast” timescale of battery cycling and the “slow” timescale of battery degradation by adaptively selecting and simulating representative cycles, skipping other cycles, and hence requires fewer cycle simulations to simulate the entire lifetime (adaptive inter-cycle extrapolation). This algorithm is demonstrated with a specific degradation mechanism but can be applied to various models of aging phenomena. In the particular case study considered, simulations of the entire lifetime are performed in under 5 s. This opens the possibility for much faster and more accurate model development, testing, and comparison with experimental data.
Evaluation of Mechanical Properties of Sisal and Bamboo Fibres Reinforced with Polymer Matrix Composites Prepared by Compression Moulding Process
Authors: Mohan S. Krishna , Ganesan Arul Thayammal , Ramarao M. , Mangrulkar Amol L. , Rajesh S. , Al Obaid Sami , Alfarraj Saleh , Sivakumar S. , Ganesan Manikandan
Published: November 2021

Today’s modern, dynamic world would be impossible to imagine without the concept of composite material advancement. Various studies are being conducted in this area in order to reach the desired level. In terms of compatibility, natural fibre reinforced polymer‐based composites and synthetic fibre composites are very similar. Because they are lightweight, nontoxic, and nonabrasive, they are very popular with consumers. They are also readily available and affordable. Composite materials made from natural fibre have superior mechanical properties compared to those made from synthetic fibre. As part of this research, an epoxy‐based composite with bamboo and sisal fibre reinforcement is examined. Reinforced with epoxy resin, bamboo fibre and sisal fibre are used to make composite materials. The effect of adding bamboo fibre and sisal fibre in various weight percentages on the mechanical behaviour of composites is investigated.
Field Localization and Density Cavitation in Low-Beta Plasmas
Authors: Rinawa Motilal , Chauhan Prashant , Kumar Sintu , Singh Manoj Kumar , Singh Hari Kumar , Sharma Amit , Sharma R. P.
Published: November 2021

In the present paper, filamentous structure formation, associated turbulent spectrum, and density cavity formation phenomena have been investigated for low-β plasma <mml:math xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mnf="http://cambridge.org/core/manifest" xmlns:cup="http://contentservices.cambridge.org" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:m="http://cambridge.org/core/metadata" xmlns:core="http://cambridge.org/core" xmlns:c="http://cambridge.org/core/content" id="M2">β≪me/mi applicable to the auroral region. A set of dimensionless equations governing the dynamics of three dimensionally propagating inertial Alfvén wave (3D-IAW) and perpendicularly propagating magnetosonic wave (PMSW) has been developed. Ponderomotive force due to 3D-IAW has been included in the dynamics of the PMSW. Numerical simulation has been performed to study the nonlinear coupling of these two waves. From the obtained results, we found that the field intensity localization takes place which may further lead to the additional dissipation/turbulence process for particle heating and acceleration in space plasma. The associated turbulent spectrum is obtained with scaling nearly k−4.28 at smaller scales (in the dissipation range). Relevance of the obtained results with the observations reported by various spacecrafts such as Hawkeye and Heos 2 has been discussed. Also, density fluctuations (depletion) of ∼0.10 n0 are calculated, which are consistent with the FAST spacecraft observation reported.
Silica/OCP Affects the Viability of Osteoblasts through ROS-Induced Autophagy
Authors: Gong Jianghao , Fu Shangjun , Zhou Zhenghao
Published: November 2021

Objective. To explore the effects of silicone gel nanoparticles modified with octacalcium phosphate on the surface (silica/OCP) polymer drugs on the proliferation of osteoblasts and autophagy. Method. Silica/OCP was prepared in vitro, and the quality of the sample preparation was tested through characterization experiments. The osteoblast cell line (hFOB1.19) was treated with silica/OCP, autophagy inhibitor (3-methyladenine (3-MA)), and silica/OCP+3-MA, respectively. The proliferation of hFOB1.19 cells was detected through the methylthiazolyldiphenyl-tetrazolium bromide (MTT) kit. Flow cytometry was used to detect the cell apoptosis. The change in protein beclin1 and P62 expression in hFOB1.19 cells was observed in Western blot. An ROS detection kit was used to detect the content of reactive oxygen species in hFOB1.19 cells. Results. Silica/OCP was a sphere with a particle size of 50 nm to 130 nm and had an OCP phase in electron projection microscopy and X-ray diffraction techniques. The results indicated that OCP successfully modified silica and the material was successfully prepared. An MTT kit and flow cytometry test showed that the cell viability of the cells treated with silica/OCP increased significantly (

P
<
0.05

), and the intracellular apoptosis phenomenon was significantly decreased (

P
<
0.05

) compared to the control group. Moreover, the inhibition of cell viability and promotion of apoptosis caused by the autophagy inhibitor 3-MA can be rescued. Western blotting demonstrated that the protein level of beclin1 in osteoblasts reached the highest after six hours of treatment with silica/OCP, and the protein level of p62, the substrate protein of autophagy, reached the lowest. At the same time, treatment of cells with the autophagy inhibitor 3-MA and silica/OCP+3-MA found that the protein levels of beclin1 and p62 in the silica/OCP+3-MA group were adjusted back compared to the 3-MA group. After adding the autophagy inhibitor, the reactive oxygen content in the cell was significantly increased (

P
<
0.05

) in the silica/OCP group. In the presence of intracellular reactive oxygen inhibitors catalase and silica/OCP, the cell viability of osteoblasts was significantly lower than that of the silica/OCP group but significantly higher than that of the silica/OCP+3-MA group. The apoptosis level of the silica/OCP+catalase group was also significantly lower than that of the silica/OCP+3-MA group (

P
<
0.05

) but was significantly higher than that of the silica/OCP group (

P
<
0.05

). Conclusion. Silica/OCP nanoparticles can upregulate the level of autophagy in osteoblasts and promote the proliferation of osteoblasts.
Influencing User’s Behavior Concerning Android Privacy Policy: An Overview
Authors: Di Ming , Nazir Shah , Deng Fucheng
Published: November 2021

The wide-ranging implementation of Android applications used in various devices, from smartphones to intelligent television, has made it thought-provoking for developers. The permission granting mechanism is one of the defects imposed by the developers. Such assessing of defects does not allow the user to comprehend the implication of privacy for granting permission. Mobile applications are speedily easily reachable to typical users of mobile. Despite possible applications for improving the affordability, availability, and effectiveness of delivering various services, it handles sensitive data and information. Such data and information carry considerable security and privacy risks. Users are usually unaware of how the data can be managed and used. Reusable resources are available in the form of third-party libraries, which are broadly active in android apps. It provides a diversity of functions that deliver privacy and security concerns. Host applications and third-party libraries are run in the same process and share similar permissions. The current study has presented an overview of the existing approaches, methods, and tools used for influencing user behavior concerning android privacy policy. Various prominent libraries were searched, and their search results were analyzed briefly. The search results were presented in diverse perspectives for showing the details of the work done in the area. This will help researchers to offer new solutions in the area of the research.
Analyzing Parametric Sensitivity on the Cyclic Behavior of Steel Shear Walls
Authors: Seyed Kolbadi Seyed Mohamad , Hassani Nemat , Seyed-Kolbadi Seyed Mahdi , Mirtaheri Masoud
Published: November 2021

As a destructive phenomenon in most parts of the world, earthquake has threatened the safety of structures and the lives of its inhabitants and is considered as the main problem in the seismic vulnerability of buildings. Steel shear walls are regarded as one of the newest structural systems resistant to lateral load in steel structures. The present study aimed to investigate the impact of effective parameters on cyclic behavior by numerically modeling a steel shear wall and comparing it with laboratory results. The results indicated the significant contribution of the thickness of steel shear sheet so that when the thickness changes to 25%, the final response of the structure increased by approximately 20% and decreased by 15%.
Fast Independent Component Analysis Algorithm-Based Functional Magnetic Resonance Imaging in the Diagnosis of Changes in Brain Functional Areas of Cerebral Infarction
Authors: Du Naiyi , Zhang Zhao , Xiao Yao , Jiang Lijie
Published: November 2021

The aim of this study was to analyze the application value of functional magnetic resonance imaging (FMRI) optimized by the fast independent component correlation algorithm (ICA algorithm) in the diagnosis of brain functional areas in patients with lumbar disc herniation (LDH). An optimized fast ICA algorithm was established based on the ICA algorithm. 50 patients with cerebral infarction were selected as the research objects, and 30 healthy people were selected as the control group. The 50 patients from the observation group were examined by fMRI based on Fast ICA algorithm, while the control group was tested by fMRI based on the routine ICA algorithm. The performances of the two algorithms, the analysis results of the two groups of brain functional areas, cerebral blood flow (CBF), resting state functional connectivity (rsFC), behavioral data, and image data correlation of patients were compared. The results showed that the sensitivity, specificity, and accuracy of Fast ICA algorithm were 97.83%, 89.52%, and 96.27%, respectively, which in the experimental group were greatly better than the control group (88.73%, 72.19%, and 89.72%), showing statistically significant differences (

P
<
0.05

). The maximum Dice coefficient of FAST ICA algorithm was 0.967, and FAST ICA algorithm was better obviously than the traditional ICA algorithm (

P
<
0.05

). The cerebral blood flow of the healthy superior frontal gyrus (SFG) and healthy superior marginal gyrus (SMG) of the observation group with good motor function recovery were 1.02 ± 0.22 and 1.53 ± 0.61, respectively; both indicators showed an increasing trend, and those in the experimental group were much higher in contrast to the control group, showing statistically obvious differences (

P
<
0.05

). Besides, the detection results of cerebral blood flow (CBF) in the healthy SFG and healthy SMG were negatively correlated with the results of connection test B. In summary, the fMRI based on the Fast ICA algorithm showed a good diagnostic effect in the changes of brain functional areas in patients with cerebral infarction. The experimental results showed that the cerebral blood flow in the brain area was related to motor or cognitive function. The results of this study provided a reliable reference for the examination and diagnosis of brain functional areas in patients with cerebral infarction.
The Image Analysis of the Visual Sensor and the Effect of Vitamin E Supplementation on Football Players’ Free Radicals and Their Physical Strength Supplement
Authors: Zhao Wei
Published: November 2021

With the help of image analysis technology of visual sensors, the research discusses the supplementation of vitamin E on free radicals and physical strength of football players after intensive exercise. The free radical supplementation and physical strength supplementation of athletes after strenuous exercise by taking a proper amount of vitamin E were studied and discussed. The effects of vitamin E on free radical metabolism, serum antioxidant level, and antioxidant enzyme activity and serum lipid peroxide metabolism after acute exercise can be generalized. 40 football players were recruited from the sports department of a physical education college in our province and randomly divided into the experimental group and the control group. The experimental group was divided into the T1 group and the T2 group, and the control group was also divided into the C1 group and the C2 group accordingly, with 10 players in each group. After the football league, the C1 and T1 groups will perform maximal aerobic exercise, and the C2 and T2 groups will perform intermittent anaerobic exercise. Serum malondialdehyde (MDA), total antioxidant capacity (T‐AOC), glutathione peroxidase (GSH‐PX), and superoxide dismutase (SOD) were determined. The comparison between the control group taking placebo and the experimental group taking vitamin E for a period of time shows that the average values of MDA are 3.25 ± 0.31 (nm/ml) and 4.20 ± 0.78 (nm/ml), respectively. After taking vitamin E, the antioxidant level of the experimental group was significantly higher than that of the control group, serum antioxidant enzyme activity decreased, serum lipid peroxidation products decreased significantly, and more free radicals were generated immediately after aerobic exercise. Vitamin E can significantly reduce the generation of free radicals during football players’ intermittent anaerobic exercise and improve the body’s antioxidant capacity.
[Retracted] Study on the Efficacy and Safety of Ambroxol Combined with Methylprednisolone in Patients with Acute Lung Injury
Authors: Su Weiwei , Dong Qinglian , Jiao Fangfang
Published: November 2021

Background. There is no better treatment method towards paraquat‐induced acute lung injury (ALI) at present. Ambroxol combined with methylprednisolone exhibits a significant improvement effect on ALI treatment, whereas their mechanism in ALI is still unclear. Methods. 64 patients with ALI caused by paraquat poisoning brought to our hospital from January 2015 to January 2018 were selected. They were separated into a combined treatment group (CTG) and a routine treatment group (RTG) on the basis of different treatment methods. The survival of patients was observed after 7 days of treatment. Arterial blood gas, oxygen partial pressure (PaO2), partial pressure of carbon dioxide (PaCO2), oxygenation index (PaO2/FiO2), patient’s spontaneous respiratory rate (RR), tidal volume (VT), and positive end‐expiratory pressure (PEEP) were observed before and after treatment for 7 days. Interleukin 6 (IL‐6) and tumor necrosis factor α (TNF‐α) were analyzed. The differences of indexes between the dead patients and the survivors were observed, and the potential predictive value of death was analyzed. Results. After treatment, the indexes of patients were significantly improved in both groups compared with those before therapy. Further comparison showed that the improvement of PaO2, PaCO2, and PaO2/FiO2 in CTG was obviously higher than that in RTG (p < 0.05). The improvement of RR, PEEP, and VT in CTG was obviously higher than that in RTG (p < 0.05). The decreased degree of IL‐6 and TNF‐α in CTG was higher than that in RTG (p < 0.05). The 7‐day mortality rate of 64 patients was 39.06%, and there was no obvious difference in the 7‐day survival rate in both groups (p = 0.649). IL‐6 and TNF‐α were expected to be potential prediction indexes of paraquat‐induced ALI. Conclusion. Ambroxol combined with methylprednisolone significantly improved the oxygen partial pressure and oxygenation index of patients with paraquat‐induced ALI and inhibited the inflammatory response of patients.
Mining Temporal Association Rules with Temporal Soft Sets
Authors: Liu Xiaoyan , Feng Feng , Wang Qian , Yager Ronald R. , Fujita Hamido , Alcantud José Carlos R.
Published: November 2021

Traditional association rule extraction may run into some difficulties due to ignoring the temporal aspect of the collected data. Particularly, it happens in many cases that some item sets are frequent during specific time periods, although they are not frequent in the whole data set. In this study, we make an effort to enhance conventional rule mining by introducing temporal soft sets. We define temporal granulation mappings to induce granular structures for temporal transaction data. Using this notion, we define temporal soft sets and their

Q

-clip soft sets to establish a novel framework for mining temporal association rules. A number of useful characterizations and results are obtained, including a necessary and sufficient condition for fast identification of strong temporal association rules. By combining temporal soft sets with NegNodeset-based frequent item set mining techniques, we develop the negFIN-based soft temporal association rule mining (negFIN-STARM) method to extract strong temporal association rules. Numerical experiments are conducted on commonly used data sets to show the feasibility of our approach. Moreover, comparative analysis demonstrates that the newly proposed method achieves higher execution efficiency than three well-known approaches in the literature.
The Ontology‐Based Approach Supporting Holistic Energy‐Tunnel Design considering Cost, Heat Flux, and System Feasibility
Authors: Meng Kun , Cui Chunyi , Zhang Cheng , Liu Hailong
Published: November 2021

As an emerging geothermal structure, the energy tunnel has been an important part of geothermal engineering. However, the conventional methods for designing energy tunnels mostly rely on complex numerical models. Furthermore, a macrolevel multidomain collaborative design method to consider multiple areas and design indicators is unavailable. This study combined ontology and semantic Web rule language to establish the domain knowledge of energy tunnels which is an enrichment of the conventional ground source heat pump domain knowledge and develop a comprehensive decision‐making tool named OntoETS for the design of energy‐tunnel systems. The tool can promote the optimal design scheme with an optimal combination of multiple indexes through an analysis of the economy, heat flux, and system feasibility of the energy‐tunnel system from a macroperspective by combining multiple domains. Furthermore, a case study was conducted to demonstrate the effectiveness and practicability of the developed holistic decision‐making system.
Association between Neutrophilic Granulocyte Percentage and Diabetes Mellitus in Cushing’s Syndrome Patients: A Cross-Sectional Study
Authors: Wang Baomin , Yang Yumei , Yuan Haoyue , Li Xiaomu
Published: November 2021

Background. Glucose metabolism is frequently impaired in patients with Cushing’s syndrome (CS) due to chronic exposure to excess glucocorticoids. Inflammation plays an essential role in the pathophysiology of diabetes mellitus (DM). The present study aimed to investigate the potential associations of inflammatory blood cell parameters, including white blood cell (WBC) count, neutrophil count, neutrophilic granulocyte percentage (NEUT%), lymphocyte count (LYM), and lymphocyte proportion (LYM%), with diabetes mellitus in Cushing's syndrome patients. Materials and Methods. The cross-sectional study was conducted in Zhongshan Hospital of Fudan University, China. A total of 150 patients with Cushing’s syndrome were retrospectively screened from 2017 to 2019. The demographic data, clinical data, and blood samples (lipids, adrenal, glucose, and inflammatory blood cell parameters) were recorded. Statistical analyses were carried out by using the SPSS software package, version 13.0. Results. In this study, the prevalence of diabetes mellitus was 38.7% in patients with Cushing’s syndrome. Patients with DM had higher WBC, neutrophil, NEUT% levels than patients without DM (p<0.05). As the NEUT% increased, a stepwise increase in glucose and glycated hemoglobin (HbA1c) level was observed. In addition, in the multivariate logistic regression, NEUT% was a significant independent risk factor for DM, regardless of gender, age, body mass index (BMI), and triglyceride and 12 midnight cortisol (12 MN cortisol) level (OR = 2.542, 95% CI 1.337–4.835,p<0.001). Conclusions. In conclusion, elevated NEUT% level was linked to diabetes in patients with Cushing’s syndrome. The neutrophilic granulocyte percentage may be referred to as a new predictor for diabetes in Cushing’s syndrome patients.