bluuebunny/crossref_metadata_2025 huggingface dataset:
Reduced lung function and health-related quality of life after treatment for pulmonary tuberculosis in Gambian children: a cross-sectional comparative study
Authors: Nkereuwem Esin , Agbla Schadrac , Sallahdeen Azeezat , Owolabi Olumuyiwa , Sillah Abdou K , Genekah Monica , Tunkara Abdoulie , Kandeh Sheriff , Jawara Maryama , Saidy Lamin , Bush Andrew , Togun Toyin , Kampmann Beate
Published: September 2022

Background

Post-tuberculosis (post-TB) lung disease is an under-recognised consequence of pulmonary tuberculosis (pTB). We aimed to estimate the prevalence of residual lung function impairment and reduced health-related quality of life (HRQoL) in children after pTB treatment completion.

Methods

We conducted a cross-sectional comparative study of children aged less than 15 years at TB diagnosis who had completed treatment for pTB at least 6 months previously with a comparator group of age-matched children without a history of pTB. Symptoms, spirometry and HRQoL measured with PedsQL scale were collected. Variables associated with lung function impairment were identified through logistic regression models.

Results

We enrolled 68 post-TB cases (median age 8.9 (IQR 7.2–11.2) years) and 91 children in the comparison group (11.5 (8.0–13.7) years). Spirometry from 52 (76.5%) post-TB cases and 89 (94.5%) of the comparison group met the quality criteria for acceptability and repeatability. Lung function impairment was present in 20/52 (38.5%) post-TB cases and 15/86 (17.4%) in the comparison group, p=0.009. Previous pTB and a history of chronic cough were significantly associated with the presence of lung function impairment (p=0.047 and 0.006 respectively). Forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC) and FEV1/FVCz-scores were significantly lower in the post-TB cases compared with the comparison group (p= <0.001, 0.014 and <0.001, respectively). The distribution of the self-reported physical health score, and parent-reported physical, emotional, psychological, social and total HRQoL scores were significantly lower in the post-TB cases compared with the comparison group.

Conclusions

Previous TB in children is associated with significantly impaired lung function and HRQoL.
Beyond borders: cystic fibrosis survival between Australia, Canada, France and New Zealand
Authors: Coriati Adèle , Ma Xiayi , Sykes Jenna , Stanojevic Sanja , Ruseckaite Rasa , Lemonnier Lydie , Dehillotte Clémence , Tate Jan , Byrnes Catherine Ann , Bell Scott C , Burgel Pierre Regis , Stephenson Anne L
Published: September 2022

Background

Life expectancy for people with cystic fibrosis (CF) varies considerably both within and between countries. The objective of this study was to compare survival among countries with single-payer healthcare systems while accounting for markers of disease severity.

Methods

This cohort study used data from established national CF registries in Australia, Canada, France and New Zealand from 2015 to 2019. Median age of survival for each of the four countries was estimated using the Kaplan-Meier method. A Cox proportional hazards model was used to compare risk of death between Canada, France and Australia after adjusting for prognostic factors. Due to low number of deaths, New Zealand was not included in final adjusted models.

Results

Between 2015 and 2019, a total of 14 842 people (3537 Australia, 4434 Canada, 6411 France and 460 New Zealand) were included. The median age of survival was highest in France 65.9 years (95% CI: 59.8 to 76.0) versus 53.3 years (95% CI: 48.9 to 59.8) for Australia, 55.4 years (95% CI: 51.3 to 59.2) for Canada and 54.8 years (95% CI: 40.7 to not available) for New Zealand. After adjusting for individual-level factors, the risk of death was significantly higher in Canada (HR 1.85, 95% CI: 1.48 to 2.32; p<0.001) and Australia (HR 2.08, 95% CI: 1.64 to 2.64; p<0.001) versus France.

Interpretation

We observed significantly higher survival in France compared with countries with single-payer healthcare systems. The median age of survival in France exceeded 60 years of age despite having the highest proportion of underweight patients which may be due to differences in availability of transplant.
Spatial dependency and independency of nitrogen in lowbush blueberry commercial fields
Authors: Pelletier Anthony J. , Lafond Jean , Paré Maxime C.
Published: September 2022

Rhizomes of wild lowbush blueberry ( Vaccinium angustifolium Aiton) extend horizontally, creating spatial dependency when fertilization trials are performed. Knowing this spatial dependency would help researchers to better design field studies. Here, we used labelled nitrogen (N) fertilizer (15N-(NH4)2SO4) to measure N translocation among blueberry stems for one old (56 year) and one younger (15 year) commercial field. Leaf 15N concentrations at the tip-dieback stage were used to monitor N acquisition. No difference between sites suggests no field age effect on N translocation. Spatial dependency and independency were reached for distances of ≤0.75 and ≥1.75 m from the fertilizer application point, respectively.
EpIC: novel Monte Carlo generator for exclusive processes
Authors: Aschenauer E. C. , Batozskaya V. , Fazio S. , Gates K. , Moutarde H. , Sokhan D. , Spiesberger H. , Sznajder P. , Tezgin K.
Published: September 2022

We present the EpIC Monte Carlo event generator for exclusive processes based on generalised parton distributions. EpIC utilises the PARTONS framework, which provides a flexible software architecture and a variety of modelling options for the partonic description of the nucleon. The generator offers a comprehensive set of features, including simulation of a variety of exclusive processes and radiative corrections. It may be used both in the analysis of experimental data, as well as for impact studies, especially for the future electron-ion colliders.
Spatiotemporal jumps as particular solutions in geodesic trajectories with the Gödel metric on an extended manifold
Authors: Bellini Mauricio
Published: September 2022

Using the Gödel metric, we obtain some relevant solutions compatible with spatiotemporal jumps for the geodesic equations, by using an extension of General Relativity with nonzero boundary terms, which are described on an extended manifold generated by the connections $$\delta \Gamma ^{\mu }_{\alpha \beta } = b\,U^{\mu }\,g_{\alpha \beta }$$

δ

Γ

α
β

μ

=
b

U
μ

g

α
β

. These terms are given by a flow of velocities with components $$U^{\nu }$$

U
ν

: $$3\,b^2\,\nabla _{\nu }U^{\nu }=g^{\alpha \beta }\, \delta R_{\alpha \beta } = \lambda \left[ s\left( x^{\alpha }\right) \right] \,g^{\alpha \beta }\, \delta g_{\alpha \beta }$$

3

b
2

∇
ν

U
ν

=

g

α
β

δ

R

α
β

=
λ

s

x
α

g

α
β

δ

g

α
β

in the varied Einstein–Hilbert action. The solutions are valid for an arbitrary equation of state with ordinary matter: $$\Omega =P/(c^2\,\rho ) = \frac{\left( \frac{\omega }{c}\right) ^2-\lambda (s)}{\left( \frac{\omega }{c}\right) ^{2}+\lambda (s)}$$

Ω
=
P
/

(

c
2

ρ
)

=

ω
c

2

-
λ

(
s
)

ω
c

2

+
λ

(
s
)

.
Constraining extra dimensions using observations of black hole quasi-normal modes
Authors: Mishra Akash K. , Ghosh Abhirup , Chakraborty Sumanta
Published: September 2022

The presence of extra dimensions generically modify the spacetime geometry of a rotating black hole, by adding an additional hair, besides the mass M and the angular momentum J, known as the ‘tidal charge’ parameter, $$\beta $$
β
. In a braneworld scenario with one extra spatial dimension, the extra dimension is expected to manifest itself through – (a) negative values of $$\beta $$
β
, and (b) modified gravitational perturbations. This in turn would affect the quasi-normal modes of rotating black holes. We numerically solve the perturbed gravitational field equations using the continued fractions method and determine the quasi-normal mode spectra for the braneworld black hole. We find that increasingly negative values of $$\beta $$
β
correspond to a diminishing imaginary part of the quasi-normal mode, or equivalently, an increasing damping time. Using the publicly available data of the properties of the remnant black hole in the gravitational wave signal GW150914, we check for consistency between the predicted values (for a given $$\beta $$
β
) of the frequency and damping time of the least-damped $$\ell =2,m=2$$

ℓ
=
2
,
m
=
2

quasi-normal mode and measurements of these quantities using other independent techniques. We find that it is highly unlikely for the tidal charge, $$\beta \lesssim -0.05$$

β
≲
-
0.05

, providing a conservative limit on the tidal charge parameter. Implications and future directions are discussed.
Technical Efficiency in Production of Major Food Grains in Punjab, Pakistan
Authors: SALAM ABDUL , HAMEED ABDUL
Published: September 2022

Based on the 2016–2017 farm survey data, this study examines technical efficiency in the production of wheat, rice, and maize in Punjab province in Pakistan. Technical efficiency, under varying returns to scale, in wheat farming averaged 0.65; in rice, it averaged 0.74, and in the case of maize, it was 0.92. A great majority of the sample farmers were estimated to be operating under increasing returns to scale. Estimations of scale inefficiency in wheat cultivation hovered around 18%; in rice, it ranged from 16% to 21%, and in maize, it varied from 7% to 17%. These estimates are indicative of the scope and the potential for increasing technical and scale efficiencies in the production of all food grains, albeit to varying degrees for different crops.
Component Connectivity of Alternating Group Networks and Godan Graphs
Authors: Zhang Hong , Zhou Shuming , Zhang Qifan
Published: September 2022

Connectivity is an important index to evaluate the reliability and fault tolerance of a graph. As a natural extension of the connectivity of graphs, the [Formula: see text]-component connectivity of a graph [Formula: see text], denoted by [Formula: see text], is the minimum number of vertices whose removal from [Formula: see text] results in a disconnected graph with at least [Formula: see text] components. It is a scientific issue to determine the exact values of [Formula: see text] for distinguishing the fault tolerability of networks. However, [Formula: see text]-component connectivity of many well-known interconnection networks has not been explored even for small [Formula: see text]. For the [Formula: see text]-dimensional alternating group networks [Formula: see text] and [Formula: see text]-dimensional godan graphs [Formula: see text], we show that [Formula: see text] for [Formula: see text], and [Formula: see text] for [Formula: see text] and [Formula: see text].
Witnessing entanglement between two two-level atoms moving inside a leaky cavity under classical control
Authors: Taghipour J. , Mojaveri B. , Dehghani A.
Published: September 2022

Based on the quantum memory-assisted entropic uncertainty relation (QMA-EUR), we investigate the Markovian and non-Markovian dynamics of entanglement witness in a two-atom system that asymmetrically are coupled to a leaky cavity with two-photon relaxation. The atoms are two-level systems, they move inside the cavity and interact with a classical driving laser field. We discuss in detail the effects of the translational movement of the atoms, classical driving field and atom-cavity coupling on the protection of entanglement witness. Our results show that with a regular increase in the intensity of the classical driving field, the entanglement region witnessed by lower bound of QMA-EUR increases and the time of entanglement witness gets longer. In the Markovian regime, we find that quantum entanglement between the moving atoms can be witnessed for a longer time by increasing the velocity of the atoms. However, in the non-Markovian regime, higher speeds are required to witness entanglement over long time intervals. In addition, we conclude that the entanglement region witnessed by the lower bound of QMA-EUR can be protected in both the symmetrical and asymmetrical atom-cavity coupling regimes. In the asymmetrical regime, a better protection can be achieved when the memory atom is coupled to the cavity field stronger than the other atom.
Revenue-Optimal Deterministic Auctions for Multiple Buyers with Ordinal Preferences over Fixed-Price Items
Authors: Ma Will
Published: September 2022

In this article, we introduce a Bayesian revenue-maximizing mechanism design model where the items have fixed, exogenously given prices. Buyers are unit-demand and have an ordinal ranking over purchasing either one of these items at its given price or purchasing nothing. This model arises naturally from the assortment optimization problem, in that the single-buyer optimization problem over deterministic mechanisms reduces to deciding on an assortment of items to “show.” We study its multi-buyer generalization in the simplest setting of single-winner auctions or, more broadly, any service-constrained environment. Our main result is that if the buyer rankings are drawn independently from Markov chain choice models, then the optimal mechanism is computationally tractable, and structurally a virtual welfare maximizer. We also show that for ranking distributions not induced by Markov chains, the optimal mechanism may not be a virtual welfare maximizer. Finally, we apply our virtual valuation notion for Markov chains, in conjunction with existing prophet inequalities, to improve algorithmic guarantees for online assortment problems.
Redundant Label Learning via Subspace Representation and Global Disambiguation
Authors: Lyu Gengyu , Feng Songhe , Liu Wei , Liu Shuoyan , Lang Congyan
Published: September 2022

Redundant Label Learning (RLL) aims at inducing a robust model from training data, where each example is associated with a set of candidate labels, among which some of them are incorrect. Most existing approaches deal with such problem by disambiguating the candidate labels first and then inducing the predictive model from the disambiguated data. However, these approaches only focus on disambiguation for each instance’ candidate label set, while the global label context tends to be ignored. Meanwhile, these approaches usually induce the objective model by directly utilizing the original feature information, which may lead to the model overfitting due to high-dimensional redundant features. To tackle the above issues, we propose a novel feature

S
ubspac
E

R
epresentation

and label

G
lobal Disambiguat
IO
n

(
SERGIO
) approach, which improves the generalization ability of the learning system from the perspective of both feature space and label space. Specifically, we project the original high-dimensional feature space into a low-dimensional subspace, where the projection matrix is regularized with an orthogonality constraint to make the subspace more compact. Meanwhile, we introduce a label confidence matrix and constrain it with ℓ
1
-norm and trace-norm regularization simultaneously, which are utilized to explore global label correlations and further well in accordance with the nature of single-label classification and multi-label classification problem, respectively. Extensive experiments on both single-label and multi-label RLL datasets demonstrate that our proposed method achieves competitive performance against state-of-the-art approaches.
Crash Consistency
Authors: Alagappan Ram
Published: September 2022

Keeping data safe in the presence of crashes is a fundamental problem in storage systems. Although the high-level ideas for crash consistency are relatively well understood, realizing them in practice is surprisingly complex and full of challenges. The systems research community is actively working on solving this challenge, and the papers examined here offer three solutions.
A Bayesian Approach for Characterizing and Mitigating Gate and Measurement Errors
Authors: Zheng Muqing , Li Ang , Terlaky Tamás , Yang Xiu
Published: September 2022

Various noise models have been developed in quantum computing study to describe the propagation and effect of the noise that is caused by imperfect implementation of hardware. Identifying parameters such as gate and readout error rates is critical to these models. We use a Bayesian inference approach to identify posterior distributions of these parameters such that they can be characterized more elaborately. By characterizing the device errors in this way, we can further improve the accuracy of quantum error mitigation. Experiments conducted on IBM’s quantum computing devices suggest that our approach provides better error mitigation performance than existing techniques used by the vendor. Also, our approach outperforms the standard Bayesian inference method in some scenarios.
ThermoSecure: Investigating the Effectiveness of AI-Driven Thermal Attacks on Commonly Used Computer Keyboards
Authors: Alotaibi Norah , Williamson John , Khamis Mohamed
Published: September 2022

Thermal cameras can reveal heat traces on user interfaces, such as keyboards. This can be exploited maliciously to infer sensitive input, such as passwords. While previous work considered thermal attacks that rely on visual inspection of simple image processing techniques, we show that attackers can perform more effective artificial intelligence (AI)–driven attacks. We demonstrate this by presenting the development of ThermoSecure and its evaluation in two user studies (N = 21, N = 16), which reveal novel insights about thermal attacks. We detail the implementation of ThermoSecure and make a dataset of 1,500 thermal images of keyboards with heat traces resulting from input publicly available. Our first study shows that ThermoSecure successfully attacks 6-symbol, 8-symbol, 12-symbol, and 16-symbol passwords with an average accuracy of 92%, 80%, 71%, and 55% respectively, and even higher accuracy when thermal images are taken within 30 seconds. We found that typing behavior significantly impacts vulnerability to thermal attacks: hunt-and-peck typists are more vulnerable than fast typists (92% vs. 83% thermal attack success. respectively, if performed within 30 seconds). The second study showed that keycap material has a statistically significant effect on the effectiveness of thermal attacks: ABS keycaps retain the thermal trace of user presses for a longer period of time, making them more vulnerable to thermal attacks, with a 52% average attack accuracy compared with 14% for keyboards with PBT keycaps. Finally, we discuss how systems can leverage our results to protect from thermal attacks and present 7 mitigation approaches that are based on our results and previous work.
Review—Interleukins Profiling for Biosensing Applications: Possibilities and the Future of Disease Detection
Authors: Shekhar Shashank , Yadav Amit K. , Khosla Ajit , Solanki Pratima R.
Published: September 2022

Interleukins (ILs) are a major subclass of cytokines acting as molecular messengers playing role in immune system responses via a cascade of signaling pathways. Belonging to the cytokine family, the ILs play a crucial role in the theranostics of various diseases. Their abnormal expression leads to the development of various diseases such as cancer, neurodegenerative diseases, allergies, asthma, autoimmune diseases, and other physiological abnormalities. This paves the path of exploring the ILs for the development of sensitive and efficient biosensors and promoting them for clinical testing in a wide array of diseases. Further, detecting the level of ILs is very important for their early diagnosis and their progression within the body, and simultaneously their possible immunotherapeutic approaches. To achieve this goal, multidisciplinary scientific approaches involving immunology, electrochemistry, nanotechnology, photometry, etc. are already being put into action. The advancements in nanoscience and nanotechnology are aiding the development of highly sensitive biosensors for ILs detection. This review focuses on giving a detailed description of all the presently discovered ILs and their role in various diseases. Simultaneously, it also discusses the various electrochemical biosensors that can be employed for the detection of ILs in body fluids. Moreover, the role of nanomaterials in electrochemical biosensing is also discussed in this review.
Real-Time Multisignal Detection and Identification in Known and Unknown HF Channels: A Deep Learning Method
Authors: Lin Huang , Dai Xuchu
Published: September 2022

The high-frequency (HF) signal detection and identification plays an import role in HF communications, and it is challenging since the HF environment randomly varies. Due to the success of deep learning (DL) methods in the fields of computer vision and natural language processing, some researchers adopt DL-based object detection methods to detect and identify signals in wideband spectrograms and achieve the good performance. However, the existing DL-based methods are not suitable for real-time HF signal detection, and their performance will be significantly degraded when these methods are applied to an unknown HF environment. In this paper, we design a novel multiresolution signal detection and identification network for real-time HF signal detection and identification and propose a domain adaptation method to adapt the network to unknown environments. The experimental results show that the running speed and accuracy of our designed network are superior to ones of the existing DL-based networks in different HF environments, and the proposed domain adaptation method can achieve obvious performance improvement in unknown environments.
[Retracted] Evaluation of the Effectiveness of a Combination of Chinese Herbal Fumigation Sitz‐Bath and Red Ointment in Managing Postoperative Wound Healing and Pain Control in Anal Fistula Patients
Authors: He Li , Yang ZhiLing , Xu Jin , Wang QingMing
Published: September 2022

Objective. To explore the efficacy of Chinese herbal fumigation and sitz‐bath combined with red ointment in the treatment of postoperative wound healing and pain control in anal fistula patients. Methods. A total of 118 anal fistula patients were selected as the study population, randomly divided into two groups, i.e., the research group (n = 60) and the control group (n = 60). The control group was treated with red ointment therapy for postoperative wound healing and pain while the research group was treated with a combination of ointment and traditional Chinese medicine fumigation sitz‐bath, Postoperative wound healing, pain control, and safety evaluation were compared between the two groups. Results. The total effective rate in the research group was 96.67%, which was significantly higher than that in the control group (93.10%), and the difference was statistically significant (P < 0.05). The VAS scores and postoperative wound healing times in the research group were significantly lower than those in the control group. The difference was statistically significant (P < 0.05). A day after postoperative treatment, there was no significant difference (P > 0.05) in TNF‐α and IL‐6 levels between the two study groups; however, from day 3 to day 14 the levels were statistically different. TNF‐α and IL‐6 levels in research group were significantly lower than those in the control group. The difference was statistically significant (P < 0.05). The incidence of postoperative complications in the research group at 6.67% was statistically significant (P < 0.05), significantly lower than 13.79% in the control group. Conclusion. Postoperative intervention with Chinese herbal fumigation and sitz‐bath combined with red ointment can effectively reduce the wound healing duration and lower the degree of pain experienced by anal fistula patients, thereby improving their quality of life.
Boosting Transmission System Flexibility in Network-Constrained Unit Commitment by Incorporating Distributed Series Reactors
Authors: Mortezayi Reza , Rabiee Abbas , Abdali Ali
Published: September 2022

In the recent decade, renewable energy sources (RES) such as wind and photovoltaic (PV) power generations gained more attention. However, despite their proven role in the reduction of operating costs of the network, their integration has some serious challenges such as the inherent uncertainties and the energy balance at the power grid. Some options to face these challenges, as well as to enhance the network’s flexibility, are demand response (DR), distributed FACTS (D-FACTS) devices, and energy storage systems (ESS). This paper focuses on the solution of the unit commitment (UC) problem in such a way that in addition to increasing the transmission network’s flexibility, the operation cost of the network decreases. To do this, distributed series reactors (DSRs) are employed as promising D-FACTS devices to enhance the transmission network’s flexibility. The uncertainty of RES is handled by the scenario-based stochastic programming technique. A mixed-integer linear programming (MILP) approach is developed, with a guaranteed global optimal solution, by developing a convex model for power flow in the presence of DSRs. The proposed UC model is implemented on the IEEE RTS 24-bus system, and the obtained results in different cases show the ability of the abovementioned flexibilities to reduce the operation cost of the network.
Study on Properties of Epoxy Composites Modified by Functional Graphite Oxide and Polyurethane
Authors: Kang Yansong , Feng Zenghui , Jiang Xinhua , Liu Lanxuan , Tao Jiafa , Huang Xiwang , Wang Weiwei , Xiao Xiangding
Published: September 2022

To improve the performance of the epoxy resin, isophorone diisocyanate (IPDI)‐modified graphene oxide (GO) nanosheets were used, and the modified graphene oxide (iGO) was grafted with epoxy resin using polyurethane (PU) chain segments as a bridge to prepare epoxy composites. The iGO was characterized by Fourier transform infrared spectroscopy (FT‐IR), X‐ray photoelectron spectroscopy (XPS), X‐ray diffraction analysis (XRD), and transmission electron microscopy (TEM), and the results showed that IPDI increased the layer spacing of iGO from 0.79 nm to 1.06 nm by grafting with hydroxyl and carboxyl groups on the surface of GO nanosheets, which improved the degree of exfoliation of iGO. Tensile testing, dynamic thermomechanical analysis (DMA), and scanning electron microscopy (SEM) were used to figure out the thermomechanical properties of the modified epoxy composites. The results show that the tensile strength and elongation at break of the as‐prepared 0.5% iGO‐PU/EP composites are 0.2 and 6.3 times higher than those of pure EP, respectively, and that the glass transition temperature was raised by about 2°C, with a significant increase in crosslinking.
Stability Analysis of the Dual Half-Bridge Series Resonant Inverter-Fed Induction Cooking Load Based on Floquet Theory
Authors: Aljafari Belqasem , Vishnuram Pradeep , Alagarsamy Sureshkumar , Haes Alhelou Hassan
Published: September 2022

Induction heating (IH) applications aided power electronic control and becomes most attractive in recent years. Power control plays a vital role in any IH applications in which the stability of the converter is still a research hot spot due to variable frequency operation. In the proposed work, the stability of the converter is carried out based on the Floquet theory for dual-frequency half-bridge series inverter-fed multiload IH system. The dynamic behaviour of the converter is analyzed by developing a small-signal model of the converter. The system with a dynamic closed-loop controller results in poles and zeros lying outside the unit circle, which has poor closed-loop stability and up-down glitches in the frequency response plot. Hence, a proportional-integral (PI) compensator is used to mitigate the said issue, which results in a better response when compared with the open system and works satisfactorily. However, the system becomes unstable when the frequency is varied and the system also possesses a poor time domain response. Hence, the values of the controller gain are optimized with the Floquet theory, which is based on the Eigenvalues of the time domain model. For the optimized gains, the system possesses better stability for the variations in the switching frequency (20 kHz to 24 kHz), and also, the frequency response of the system is better with minimum time domain specifications. The performance of the system is simulated in MATLAB, and the response is noted for various switching frequencies in open loop, with a PI compensator, and with an optimized PI compensator. The output power is varied from 500 W to 18 W at load 1 and 250 W to 9 W at load 2. It is noted from the output response that the rise time is 0.0085 s, the peak time is 0.0001 s, and the peak overshoot is 0.1% with minimum steady-state error. Furthermore, the IH system is validated using a PIC16F877A microcontroller with the optimized PI controller, and the thermal image is recorded using a FLIR thermal imager.
A Novel Ensemble-Based Technique for the Preemptive Diagnosis of Rheumatoid Arthritis Disease in the Eastern Province of Saudi Arabia Using Clinical Data
Authors: Olatunji Sunday O. , Alansari Aisha , Alkhorasani Heba , Alsubaii Meelaf , Sakloua Rasha , Alzahrani Reem , Alsaleem Yasmeen , Almutairi Mona , Alhamad Nada , Alyami Albandari , Alshobbar Zainab , Alassaf Reem , Farooqui Mehwash , Ahmed Mohammed Imran Basheer
Published: September 2022

Rheumatoid arthritis (RA) is a chronic inflammatory disease caused by numerous genetic and environmental factors leading to musculoskeletal system pain. RA may damage other tissues and organs, causing complications that severely reduce patients’ quality of life. According to the World Health Organization (WHO), over 1.71 billion individuals worldwide had musculoskeletal problems in 2021. Rheumatologists face challenges in the early detection of RA since its symptoms are similar to other illnesses, and there is no definitive test to diagnose the disease. Accordingly, it is preferable to profit from the power of computational intelligence techniques that can identify hidden patterns to diagnose RA early. Although multiple studies were conducted to diagnose RA early, they showed unsatisfactory performance, with the highest accuracy of 87.5% using imaging data. Yet, imaging data requires diagnostic tools that are challenging to collect and examine and are more costly. Recent studies indicated that neither a blood test nor a physical finding could early confirm the diagnosis. Therefore, this study proposes a novel ensemble technique for the preemptive prediction of RA and investigates the possibility of diagnosing the disease using clinical data before the symptoms appear. Two datasets were obtained from King Fahad University Hospital (KFUH), Dammam, Saudi Arabia, including 446 patients, with 251 positive cases of RA and 195 negative cases of RA. Two experiments were conducted where the former was developed without upsampling the dataset, and the latter was carried out using an upsampled dataset. Multiple machine learning (ML) algorithms were utilized to assemble the novel voting ensemble, including support vector machine (SVM), logistic regression (LR), and adaptive boosting (Adaboost). The results indicated that clinical laboratory tests fed to the proposed voting ensemble technique could accurately diagnose RA preemptively with an accuracy, recall, and precision of 94.03%, 96.00%, and 93.51%, respectively, with 30 clinical features when utilizing the original data and sequential forward feature selection (SFFS) technique. It is concluded that deploying the proposed model in local hospitals can contribute to introducing a method that aids medical specialists in preemptively diagnosing RA and stopping or delaying the course using clinical laboratory tests.
Fetal Fibronectin as a Predictor of Preterm Delivery: A Nigerian Cohort Study
Authors: Ikeoha Cyril C. , Anikwe Chidebe C. , Umeononihu Osita S. , Okorochukwu Bartholomew C. , Mamah Johnbosco E. , Eleje George U. , Ezeama Chukwuemeka O. , Nwokoye Basil I. , Okoroafor Chigozie F. , Ugwoke Ikechukwu S.
Published: September 2022

Background. Fetal fibronectin is a useful biomarker in the diagnosis and management of preterm labour. Objectives. To evaluate the relationship between cervical fetal fibronectin and preterm delivery and the association between cervical fetal fibronectin level and gestational age at delivery. Materials and Methods. A prospective cohort study was performed in a tertiary hospital in Nigeria, involving equal number of pregnant women with (96) and without (96) preterm labour. Fetal fibronectin assay was done using solid‐phase immunogold assay. The data were analysed using IBM SPSS version 24. Descriptive and inferential statistical analyses were done. The level of significance was p‐value <0.05. Results. Less than half (47.9%) of the women in the study group had preterm delivery while 13.09% of the women in the control group delivered preterm. Fetal fibronectin test had a sensitivity, specificity, positive predictive value and negative predictive value of 78%, 86.5%, 71.9%, and 89.0%, respectively, a positive likelihood ratio and negative likelihood ratio of 5.76(95% CI, 3.67 – 9.64) and 0.26(95% CI, 0.16 – 0.41), respectively. Conclusion. The findings in our study value of fetal fibronectin in predicting preterm delivery. Its use will support less intervention for patients with negative results.
Study on the Influencing Factors of Osteoarthritis in Southern China
Authors: Lu Danqing , Ding Xiaomin , Lu Wenqing
Published: September 2022

Background. Osteoarthritis (OA) is a common chronic disease with numerous and interacting influencing factors, and current inadequate patient perceptions and behaviors in access to care contribute to the difficulties in the diagnosis, treatment, and management of osteoarthritis. Objective. The purpose of this study was to investigate the influencing factors of osteoarthritis (OA) in a southern Chinese population and to provide a scientific basis for the prevention and treatment of OA. Methods. A 1 : 2 matched case-control study was used to select 160 patients with OA from three hospitals in southern China as a case group. Three hundred and twenty cases of the same sex and similar age (within 

±

 2 years) were selected as the control group, and relevant data were collected for univariate and multivariate conditional logistic regression analysis. Results. There were no significant differences between the two groups of participants in terms of age, sex, and education (

P
>
0.05

). Logistic regression statistical analysis showed that genetic factors (OR = 4.52, 95% CI = 1.56–7.83), body mass index (OR = 2.57, 95% CI = 1.16–5.84), alcohol consumption (OR = 3.81, 95% CI = 1.53–5.87), and a history of external joint limb injury (OR = 3.37, 95% CI = 1.67–5.24) would increase the risk of OA. In contrast, eating more fresh vegetables (OR = 0.08, 95% CI = 0.03–0.31), more fresh fruits (OR = 0.34, 95% CI = 0.12–0.96), more soy products (OR = 0.11, 95% CI = 0.04–0.45), and exposure to sunlight (OR = 0.31, 95% CI = 0.14–0.71) would reduce the OA risk of OA. Conclusion. Obesity, alcohol consumption, and a history of joint trauma all increase the risk of OA in a southern Chinese population, whereas a diet rich in fresh vegetables, fresh fruit, soy products, and sun exposure would reduce the risk of OA. In the future, we should focus on improving patients’ awareness of medical care and developing their self-management skills, improving GPs’ treatment skills, improving negative attitudes of both doctors and patients, and promoting positive patient care.
Finite Groups with the Same Order and the Same Number of Elements of Maximal Order as the Projective Special Linear Group L2(q)
Authors: Zhang Qingliang
Published: September 2022

Assume that G is a finite group. It is widely known that |G| and the number of elements of maximal order in G have something to do with the structure of G. This subject is related to Thompson’s conjecture. In the present paper, we give a complete classification of the groups with the same order and the same number of elements of maximal order as L2(q), where q = 7, 17.
CTGF Promotes the Osteoblast Differentiation of Human Periodontal Ligament Stem Cells by Positively Regulating BMP2/Smad Signal Transduction
Authors: Yan Shuyun , Zhang Meng , Yang Guimei , Sun Yumei , Ai Dongmei
Published: September 2022

Objective. This work is aimed at revealing the role and the molecular mechanism of connective tissue growth factor 2 (CTGF) in the osteoblast differentiation of periodontal ligament stem cells (PDLSCs). Methods. The osteogenic differentiation of PDLSCs was induced by osteogenic induction medium (OM), and the expression level of osteogenic related proteins ALP, RUNX2, OCN, and CTGF was estimated using quantitative real‐time polymerase chain reaction (qRT‐PCR) and Western blotting analysis. We constructed cell lines with CTGF overexpression or knockdown to verify the role of CTGF in the osteoblast differentiation of PDLSCs. Alkaline phosphatase (ALP) staining was introduced to measure the osteoblasts activity, and alizarin red S (ARS) staining was employed to test matrix mineralization. The interaction between CTGF and bone morphogenetic protein‐2 (BMP‐2) was determined by endogenous coimmunoprecipitation (Co‐IP). Results. The expression level of CTGF was increased during the osteogenic induction of PDLSCs. Additionally, CTGF overexpression effectively maintained the stemness and facilitated the osteoblast differentiation in PDLSCs, and CTGF knockdown exerted opposite effects. Moreover, at molecular mechanism, CTGF increased the activity of BMP‐2/Smad signaling pathway. Conclusion. This investigation verified that CTGF promotes the osteoblast differentiation in PDLSCs at least partly by activating BMP‐2/Smad cascade signal.
Application of Art in Computer Graphic Design
Authors: Wang Weiwei
Published: September 2022

Studying painting, drawing, sculpting, and graphic design are all included in an art and design degree. Basic design ideas, colour theory, critical analysis, and creative approaches are taught to students majoring in art and design. One of the key elements that determine the calibre of art and design is colour matching. Modern art design makes extensive use of computer technology. To create high-quality art pieces, designers must thoroughly research computer colour matching. This paper is based on a knowledge of the colour matching of the art design. This paper uses computer technology to successfully select the hue and colour quantity rate of a mathematical framework. At the same time, it should select the style of colour matching style, background hue, and colour quantity. It is proposed to employ cyan, magenta, yellow, key (CMYK), hue-saturation-brightness (HSB), red, green, and blue (RGB), and other modes to get the approximate hue sum, which can serve as a useful benchmark for the modernization of art design. The experimental results demonstrate that the two groups of colour matching selected for this paper have high colour difference accuracy, but the formula accuracy provided by the weight factor for colour difference is superior to that provided by other weight factors whether it is the formula accuracy provided by computer colour matching or the accuracy of actual art images.
PRR15 Is a Novel Diagnostic and Prognostic Biomarker in Papillary Thyroid Cancer and Modulates the Tumor Microenvironment
Authors: Wang Lingli , Deng Xiaoqing , Chen Yi , Zhao Yixia , Li Zhirong
Published: September 2022

Papillary thyroid cancer (PTC), accounting for more than 80 percent of all cases of thyroid cancer, is a form of a cancerous tumor that has a very favorable prognosis. However, patients diagnosed with PTC who are already in an advanced state have a dismal outlook. This study aimed to establish the diagnostic relevance of PRR15 expression in PTC patients as well as its levels in PTC samples and its connection with immune infiltrates. The TCGA and GEO datasets were combed through to obtain information on PTC patients. The “Limma” program was used to screen for differentially expressed mRNAs (DEMs), and the results were displayed using volcano plots and heat maps. The Wilcoxon test was used to examine the level of PRR15 expression in PTC patients in comparison with that of normal tissues. To study the connection between the immune infiltration level and PRR15 expression in PTC, the single-sample sequence set enrichment analysis (ssGSEA) from the R package was utilized. The expression of PRR15 was analyzed with RT-PCR in PTC cells and normal cells. In order to evaluate the diagnostic significance of PRR15 expression, ROC assays were carried out. Experiments using CCK-8 were carried out to investigate the impact that PRR15 knockdown could have on the proliferation of PTC cells. In this study, 17 overlapped DEMs between PTC specimens and normal specimens were identified, including MPPED2, IPCEF1, SLC4A4, PKHD1L1, DIO1, CRABP1, TPO, TFF3, SPX, TCEAL2, ZCCHC12, SYTL5, PRR15, CHI3L1, SERPINA1, GABRB2, and CITED1. Our attention focused on PRR15 which was highly expressed in PTC specimens as compared with nontumor specimens. PRR15 had an AUC value of 0.926 (95% CI 0.902–0.950) for PTC based on TCGA datasets. Pan-cancer assays suggested PRR15 as an oncogenic gene in many types of tumors. Moreover, we found that PRR15 expression was positively correlated with eosinophils, NK cells, NK CD56bright cells, IDC, macrophages, DC, mast cells, and Th1 cells. Further investigations with CCK-8 demonstrated that inhibiting PRR15 resulted in a decrease in the proliferation of PTC cells. Overall, PRR15 was confirmed to be a biomarker for PTC patients and a predictor of response to immunotherapy.
[Retracted] Music Teaching Management and Music Culture Communication Environment Based on Ergonomics
Authors: Dong Rui
Published: September 2022

Music education has a relationship that is mutually restraining and interdependent. The necessity of spreading music culture offers music education social relevance and existential value in the history of music culture’s growth, and the method of spreading music culture—music education—injects strength and life into the development of music culture. Music pedagogy is constrained by the evolution of music culture as a whole. In terms of music pedagogy, traditional culture and their peculiarities or qualities will have an impact on the creation of the curriculum content system, which is also the main topic of music teaching management. By using anthropometry, physiological and psychological measurement, etc. with the human body as the main body, ergonomics is the study of the reasonable coordination between the structure and function of the human body, psychology, mechanics, and music teaching methods in order to satisfy people’s physical and mental activities and achieve the best use efficiency. The focus should be on comfort, great performance, safety, and health. In order to create a model for evaluating the quality of music instruction, a back propagation neural network (BPNN) is optimised in this paper using an adaptive mutation genetic algorithm. According to the research, our approach outperforms the BPNN model optimised using conventional evolutionary algorithm by 20.21%. The convergence pace is 80.11% faster than the convergence speed of a conventional genetic algorithm. The comparative result demonstrates that the BPNN teaching quality evaluation model with genetic algorithm optimization based on adaptive mutation can produce a more logical scientific evaluation result for the quality of music instruction.
Therapeutic Effect of Gypenosides on Antioxidant Stress Injury in Orbital Fibroblasts of Graves’ Orbitopathy
Authors: Ma Chao , Li Haoyu , Liu Wei , Lu Shuwen , Li Xian , Chen Jinyuan , Li Kaijun , Wang Wenzhan
Published: September 2022

Purpose. To examine the impact of gypenosides (Gyps) on oxidative stress damage of orbital fibroblasts (OFs) from Graves’ ophthalmopathy (GO) patients. Methods. The relationship between Gyps and GO oxidative stress was understood by bioinformatics analysis. Orbital connective tissues of GO and non-GO patients were obtained for primary OF culture. The proliferation level of OFs was measured by Cell Counting Kit-8 method, and the appropriate intervention concentration of Gyps and H2O2 was obtained. The expression of apoptosis-related protein mRNA was analyzed by RT-qPCR technique. ROS and SOD test suites were employed to detect the oxidative stress level in OFs. Flow cytometry apoptosis detection, TUNEL detection, and lactate dehydrogenase detection were used to analyze the level of apoptosis. Western blotting detection was utilized to examine the regulatory pathway of oxidative stress, apoptosis, and autophagy-related proteins. The changes of cell morphology, autophagosome, and autophagy lysosome were observed by transmission electron microscope. Results. The suitable intervention concentration of Gyps is 100 μg/mL, and the suitable intervention concentration of high concentration H2O2 is 350 μM. In comparison with the blank control group, the H2O2 intervention group enhanced the expression of apoptosis-related mRNA, the expression of ROS and SOD, the apoptosis rate, the expression of autophagy activation-related protein and Nrf2/ERK/HO-1 protein, and the number of autophagosomes and autophagy lysosomes. Compared with H2O2 intervention group, the expression of apoptosis-related mRNA decreased, ROS expression decreased, SOD expression increased, apoptosis rate decreased, autophagy activation-related protein expression decreased, Nrf2/ERK/HO-1 protein expression increased, and the quantity of autophagosomes and autophagy lysosomes decreased in H2O2 + Gyps intervention group. Conclusion. Gyps can decrease the oxidative stress level of OFs generated by H2O2, reduce cell autophagy, and reduce apoptosis. Gyps may regulate the oxidative stress response of OFs in GO patients via the Nrf2/ERK/HO-1 signaling pathway.
Blockchain-Based Electronic Medical Records System with Smart Contract and Consensus Algorithm in Cloud Environment
Authors: Dwivedi Sanjeev Kumar , Amin Ruhul , Lazarus Jegatha Deborah , Pandi Vijayakumar
Published: September 2022

The blockchain is a peer-to-peer distributed ledger technology that works on the precept of “write-once-read-only.” In a blockchain, pieces of information are arranged in the form of blocks, and these blocks are linked together using the hash value of previous blocks. The blocks in a blockchain mechanism are appended only, which means that once information is stored in a block and it cannot be changed; no one tampers the block’s content. The traditional electronic medical records (EMRs) based system stores the patients’ information in a local database or server, which provides centralization of information, and traditional EMRs are more centric on the health providers. So, security and sharing of patients’ information are difficult tasks in the traditional EMR system. The blockchain mechanism has the potential to resolve these existing problems. Due to the appended-only-ledger principle and decentralization of blocks between the network participants, blockchain technology is suited to the EMR system. In this article, first, we discuss all the existing EMR systems and discuss their drawbacks. Keeping all the drawbacks in our mind, we propose a blockchain-based medical record system that utilizes clouding technology for storage purposes. Furthermore, we have designed a smart contract and consensus algorithm for our proposed EMR. Our system only uses a permissioned blockchain model so that only verified and authenticated users can generate their data and participate in the data-sharing system.