bluuebunny/crossref_metadata_2025 huggingface dataset:
Association of macular OCT and OCTA parameters with visual acuity in glaucoma
Authors: Wu Jo-Hsuan , Moghimi Sasan , Nishida Takashi , Mohammadzadeh Vahid , Kamalipour Alireza , Zangwill Linda M , Weinreb Robert N
Published: September 2022

Background/aims

To investigate the association of macular optical coherence tomography (OCT)/OCT angiography (OCTA) parameters with visual acuity (VA) in glaucoma.

Methods

144 pseudophakic primary open-angle glaucoma eyes were included. Foveal (fVD), parafoveal (pf), perifoveal (perifVD) and whole-image vessel densities (wiVD) of superficial and deep layers, and their corresponding ganglion cell complex (GCC) thicknesses were obtained from OCTA 6×6 mm2macula scans. Foveal avascular zone (FAZ) area, FAZ circumference and foveal density-300 (FD300) were measured. Correlation between OCT/OCTA parameters and Logarithm of the Minimum Angle of Resolution VA (logMAR VA) in early and moderate-advanced glaucoma was evaluated with age and Signal Strength Index-adjusted mixed models. Area under receiver operating characteristic (AUC) was used to evaluate discriminative power of OCT/OCTA for decreased VA (<20/25).

Results

In early glaucoma (80 eyes), no parameter correlated with VA. In moderate-advanced glaucoma (64 eyes), greater FAZ area (β=0.228) and circumference (β=0.063) correlated with worse VA (p<0.05), but not FD300. fThinner sectoral and global GCC was associated with worse VA (β=0.002–0.003, p<0.05), except for inferior hemifield perifGCC and wiGCC. For VD, lower superior hemifield superficial perifVD and wiVD (β=0.007–0.008) and deep fVD (β=0.004) correlated with worse VA (p<0.05). OCT/OCTA parameters showed modest ability to discriminate decreased VA, with the superior hemifield performing better than the inferior hemifield. In early glaucoma, GCC and VD showed similar discrimination (AUC=0.67–0.77). In moderate-advanced glaucoma, fGCC and pfGCC yielded higher AUC (0.75–0.81) than VD (AUC=0.63–0.72).

Conclusions

Some macular OCT/OCTA parameters were associated with VA in moderate-advanced, but not early glaucoma. These structural parameters may help identify glaucoma patients with impaired vision and reduced quality of life.

Trial registration number

NCT00221897.
A search for relevant contextual factors in intervention studies: a stepwise approach with online information
Authors: Van der Elst Michael , Schoenmakers Birgitte , Dierckx Eva , De Donder Liesbeth , De Roeck Ellen , Duppen Daan , Fret Bram , Schols Jos M G A , Kempen Gertrudis I J M , De Lepeleire Jan
Published: September 2022

Objective

The aim of the present study is to describe a stepwise approach to study which contextual factors might moderate the effect of healthcare interventions and to test feasibility of this approach within the D-SCOPE project.

Design

Exploratory case study.

Setting

In the D-SCOPE project, a complex intervention by means of home visits was set up to improve access to tailored care in three municipalities (Ghent, Knokke-Heist and Tienen).

Methods

One designed and tested an approach including five steps: (1) a theoretical/conceptual discussion of relevant contextual factor domains was held; (2) a search was done to find appropriate web-based public datasets which covered these topics with standardised information; (3) a list of all identified contextual factors was made (inventory); (4) to reduce the long list of contextual factors, a concise list of most relevant contextual factors was developed based on the opinion of two independent reviewers and (5) a nominal grouping technique (NGT) was applied.

Results

Three public web-based datasets were found resulting in an inventory of 157 contextual factors. After the selection by two independent reviewers, 41 contextual factors were left over and presented in a NGT which selected 10 contextual factors. The NGT included seven researchers, all familiar with the D-SCOPE intervention, with various educational backgrounds and expertise and lasted approximately 1 hour.

Conclusion

The present study shows that a five-step approach is feasible to determine relevant contextual factors that might affect the results of an intervention study. Such information may be used to correct for in the statistical analyses and for interpretation of the outcomes of intervention studies.

NCT03168204
Retained radial catheters associated with variant radial anatomy in neurointerventional procedures
Authors: Catapano Joshua S , Winkler Ethan A , Srinivasan Visish M , Dishion Evan L , Rutledge Caleb , Baranoski Jacob F , Cole Tyler S , Rudy Robert F , Rumalla Kavelin , Zomaya Martin P , Jadhav Ashutosh P , Ducruet Andrew F , Albuquerque Felipe C
Published: September 2022

Background

Transradial artery access (TRA) for neurointerventional procedures is gaining widespread acceptance. However, complications that were previously rare may arise as TRA procedures increase. Here we report a series of retained catheter cases with a literature review.

Methods

All patients who underwent a neurointerventional procedure during a 23-month period at a single institution were retrospectively reviewed for a retained catheter in TRA cases. In cases of retained catheters, imaging was reviewed for anatomical variances in the radial artery, and clinical and demographic case details were analyzed.

Results

A total of 1386 nondiagnostic neurointerventional procedures were performed during the study period, 631 (46%) initially via TRA. The 631 TRA cases were performed for aneurysm embolization (n=221, 35%), mechanical thrombectomy (n=116, 18%), carotid stent/angioplasty (n=40, 6%), arteriovenous malformation embolization (n=38, 6%), and other reasons (n=216, 34%). Thirty-nine (6%) TRA procedures crossed over to femoral access, most commonly because the artery of interest could not be catheterized (26/39, 67%). A retained catheter was identified in five cases (1%), and one (0.2%) patient had an entrapped catheter that was recovered. All six patients with a retained or entrapped catheter had aberrant radial anatomy.

Conclusion

Retained catheters for neurointerventional procedures performed via TRA are rare. However, this complication may be associated with variant radial anatomy. With the increased use of TRA for neurointerventional procedures, awareness of anatomical abnormalities that may lead to a retained catheter is necessary. We propose a simple protocol to avoid catheter entrapment, including in emergent situations such as TRA for stroke thrombectomy.
A descriptive study of venous pressures and gradients while awake and both pre- and post-stent under anesthesia in patients with idiopathic intracranial hypertension
Authors: Fargen Kyle M , Wolfe Stacey Q , Traunero Justin R , Iyer Ankitha M , Kittel Carol
Published: September 2022

Background

This study aims to explore factors that affect venous sinus pressures and associated gradients while awake and under general anesthesia (GA) both before and after venous sinus stenting (VSS) in patients with idiopathic intracranial hypertension (IIH).

Methods

A retrospective analysis was performed examining pressures and gradients in patients with IIH having undergone awake venography followed by VSS under GA.

Results

174 patients were included. Compared with awake, GA superior sagittal sinus (SSS) pressures were 2.6 mmHg lower (p=0.01) resulting in a total cranial gradient reduction of 2.5 mmHg (p=0.002). The transverse-sigmoid gradient, the most commonly stented segment, did not differ under the two conditions (p=0.30). Regression analyses demonstrated that body mass index, gender, blood pressure, and end-tidal carbon dioxide content significantly affected venous pressures (all p<0.05). After stenting, mean total cranial gradients decreased by 13.2 mmHg while skull base gradients increased by 0.8 mmHg. Stenting resulted in an 84% mean reduction in the target gradient and a mean decrease in SSS pressures by 78% of the target gradient. When cardiopulmonary and anesthetic factors were optimized, GA had a limited effect on the target gradient in most patients (p=0.88).

Conclusions

This study is the largest series to date to report on cerebral venous pressure measurements and gradients recorded while awake and under GA both before and after VSS for IIH. In a well-controlled cardiorespiratory and anesthetic setting, GA venography may provide information that is not substantially inequivalent to that obtained while awake.
Exercise as airway clearance therapy (ExACT) in cystic fibrosis: a UK-based e-Delphi survey of patients, caregivers and health professionals
Authors: Saynor Zoe Louise , Cunningham Steve , Morrison Lisa , Main Eleanor , Vogiatzis Ioannis , Reid Simon , Urquhart Donald
Published: September 2022

Replacing traditional airway clearance therapy (tACT) with exercise (ExACT) in people with cystic fibrosis (pwCF) is a top research priority. A UK-based e-Delphi consensus was performed to inform the type(s), duration and intensity of ExACT. The expert panel comprised CF physiotherapists, doctors, pwCF and parents/partners. Exercise ACT was considered to be aerobic activity, of at least 20 min duration and intense enough to elicit deep breathing. Consensus was reached that assessment breaths, coughs and huffs should accompany exercise to remove loose secretions, with support for trials to investigate ExACT versus tACT during times of stable disease but not pulmonary exacerbations.
Three matrix factorizations from the steps of elimination
Authors: Strang Gilbert , Drucker Daniel
Published: September 2022

Every real [Formula: see text] matrix [Formula: see text] can be factored in three ways that arise from the steps of elimination: a lower triangular/upper triangular factorization [Formula: see text], a column-row factorization [Formula: see text], and a triple factorization [Formula: see text]. The column-row factorization provides both a constructive proof that the row rank [Formula: see text] of [Formula: see text] equals the column rank, and a formula for the pseudoinverse [Formula: see text] not based on the singular value decomposition. In the triple factorization, [Formula: see text] and [Formula: see text] contain the first [Formula: see text] independent columns of [Formula: see text] and the first [Formula: see text] independent rows of [Formula: see text]; [Formula: see text] is the invertible submatrix of [Formula: see text] where [Formula: see text] meets [Formula: see text]. An alternative to the traditional elimination method, using slide steps in place of the usual swap steps, identifies the first [Formula: see text] independent rows of [Formula: see text].
A Study on Affine Transformations and a Novel Universal Prediction Theory
Authors: Liu G. R.
Published: September 2022

Artificial neural networks (NNs) with various architectures are widely used for practical problems, including multilayer perceptron (MLP), the Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), among others. The TrumpetNets and TubeNets were also recently proposed for creating two-way deepnets for both forward and inverse problems. All these studies have demonstrated the power of NNs, but the theoretical foundation needs a more thorough study. This paper first conducts an intensive study on affine transformations and its role as a prediction function. This reveals a data-to-parameter (or [Formula: see text]) encoding mechanism and its uniqueness with proof. Then, effects of the architecture and the roles of nonlinear activation functions wrapping the affine transformations are investigated. The effects of stacking of affine transformations and chaining of the wrapped affine transformations in an NN are examined, leading finally to a novel Universal Prediction Theory (UPT).
The Hybrid Element-Free Galerkin Method for 3D Helmholtz Equations
Authors: Cheng Heng , Zhang Jiao , Xing Zebin
Published: September 2022

In this study, the hybrid element-free Galerkin (HEFG) method is studied to solve the 3D Helmholtz equations. The idea of the dimension splitting method (DSM) is introduced into the improved element-free Galerkin (IEFG) method, thus a sequence of 2D forms can be obtained by splitting the problem domain of 3D Helmholtz equation, each 2D form can be discretized by using the IEFG method, thus the corresponding 2D discretized equations can be obtained, and these equations can be coupled by employing the finite difference method (FDM) in the dimension splitting direction, thus final formulae of numerical solution for 3D Helmholtz equation can be obtained. In Sec. 4, the relative errors and the convergence are analyzed, respectively, and the numerical results show that the calculation resources can be saved greatly without losing the computational accuracy when using the HEFG method.
Laplace transform-type multipliers for Kontorovich–Lebedev transform
Authors: Mandal U. K. , Dziri Moncef , Prasad Akhilesh
Published: September 2022

In this paper, we investigate Poison kernel associated with Kontorovich–Lebedev transform. We significantly simplify the integral yielding a tractable form which is more useful for explicit calculation. We establish also that Kontorovich–Lebedev multipliers of Laplace transform type are bounded from [Formula: see text] into it self when [Formula: see text] and from [Formula: see text] into [Formula: see text] provided that [Formula: see text] is in the Muckenhoupt class [Formula: see text] on [Formula: see text]. At the end, an integral representation of the operator [Formula: see text] is obtained and its boundedness has been discussed in Lebesgue space.
Primitive idempotents in a semisimple ring
Authors: Singh Inderjit , Kumar Pankaj , Sangwan Monika
Published: September 2022

Let [Formula: see text] be distinct primes, [Formula: see text] odd. Let [Formula: see text], where [Formula: see text] be an integer. In this paper, it is observed that the explicit expressions of primitive idempotents from [Formula: see text] are sufficient to compute the explicit expressions of primitive idempotent in semisimple ring [Formula: see text]. It is also shown that the results obtained in [A. Sahni and P. T. Sehgal, Minimal cyclic codes of length [Formula: see text], Finite Fields Appl. 18(5) (2012) 1017–1036; P. Kumar and S. K. Arora, [Formula: see text]-mapping and primitive idempotents in semisimple ring [Formula: see text], Comm. Algebra 41(10) (2013) 3679–3694] are simple corollaries to the results obtained in the paper.
Study on matrix transformation of complex uncertain sequences via uncertain measure
Authors: Das Birojit , Tripathy Binod Chañdra , G̃ranados Carlos
Published: September 2022

In this paper, we initiate the concept of matrix transformation through uncertain measure of a complex uncertain sequence. We establish a necessary and sufficient condition under which an infinite matrix transforms a convergent sequence into another. As an application of this notion, we prove the well-known Silverman–Toeplitz theorem and Kojima–Schur theorem in an uncertainty space.
A Novel Autoencoder Deep Architecture for Detecting the Outlier in Heterogeneous Data Sets
Authors: Uttarkabat Satarupa , Sharma Abhaya , Patra Bidyut Kumar
Published: September 2022

Neighborhood-based unsupervised approaches like LDOF, LOF and symmetric neighborhood (INFLO) have proven effective over decades. These techniques principally utilize the information of either the [Formula: see text]-nearest neighbor or the reverse [Formula: see text]-nearest neighbors to detect the outlierness of each object in a data set. However, these methodologies fail to detect genuine outliers in heterogeneous data sets located between two dense clusters, between dense and sparse clusters or the scattered data sets. In addition, LOF treats a normal point of a sparse cluster as an outlier if the sparse cluster is close to a dense cluster. This paper proposes a novel autoencoder deep learning architecture to overcome the limitations of the aforementioned techniques. In the proposed approach, we identify the potential outliers intelligently from a given data set and mark them to generate training samples for the autoencoder. These marked points are not included in the training samples. Finally, the trained autoencoder is used to compute the outlierness of each data point in the whole data set (training samples + marked points). Experimental results with synthetic and real-world data sets show that the proposed model outperforms these widely applied techniques along with state-of-the-art works.
Spatial Attendance Spillover in Football Leagues
Authors: Jang Hayley , Shin Yongcheol
Published: September 2022

We analyse the spatial attendance spillover applying spatial panel-data models with the Italian Football League data from 2001/2002 to 2016/2017. Our Quasi-Maximum Likelihood empirical results suggest that no significant spatial interaction was evident in earlier seasons (2001–2013), but modest spatial spillover was in play from 2013 to 2016. In addition, cross-quality spillover exists only locally in the same cities. We use numerical simulations to examine the potential impact of such spillover on attendance distribution and then competitive balance; spillover implies an interaction between the two exclusive markets that are the principal sources of competitive imbalance. Our numerical simulations suggest that spatial spillover may create attendance variations across member teams. The final outcome depends on the spillover sign, the network structure, and the market size distribution. Combining the empirical results with numerical simulations, we find that a recent, slightly positive spillover may modestly reduce attendance disparity.
Cell therapy attenuates endothelial dysfunction in hypertensive rats with heart failure and preserved ejection fraction
Authors: de Couto Geoffrey , Mesquita Thassio , Wu Xiaokang , Rajewski Alex , Huang Feng , Akhmerov Akbarshakh , Na Na , Wu Di , Wang Yizhou , Li Liang , Tran My , Kilfoil Peter , Cingolani Eugenio , Marbán Eduardo
Published: September 2022

We tested the concept that inflammation of endothelial cells is a major pathogenic factor in HFpEF. CDCs are heart-derived cell products with verified anti-inflammatory therapeutic properties. Infusion of CDCs reduced oxidative stress, restored eNOS abundance, lowered monocyte levels, and rescued the expression of multiple disease-associated genes, thereby restoring vascular reactivity. The salutary effects of CDCs support the hypothesis that inflammation of endothelial cells is a proximate driver of HFpEF.
Widespread intracoronary allogeneic cardiosphere-derived cell therapy with and without cyclosporine in reperfused myocardial infarction
Authors: Techiryan George , Weil Brian R. , Young Rebeccah F. , Canty John M.
Published: September 2022

In a three-way blinded, randomized design, we determined whether allogeneic CDCs administered at reperfusion improved myocardial function and whether intravenous cyclosporine enhanced their efficacy. In contrast to prior studies using oral cyclosporine, CDCs with or without intravenous cyclosporine had no effect on function or infarct size. This indicates that CDCs may be most efficacious for treating chronic LV dysfunction where cyclosporine can be initiated at least 72 h before cell therapy.
Identifying Glucose Metabolism Status in Nondiabetic Japanese Adults Using Machine Learning Model with Simple Questionnaire
Authors: Uchida Tomoki , Kanamori Takeshi , Teramoto Takanori , Nonaka Yuji , Tanaka Hiroki , Nakamura Satoshi , Murayama Norihito
Published: September 2022

We aimed to identify the glucose metabolism statuses of nondiabetic Japanese adults using a machine learning model with a questionnaire. In this cross-sectional study, Japanese adults (aged 20–64 years) from Tokyo and surrounding areas were recruited. Participants underwent an oral glucose tolerance test (OGTT) and completed a questionnaire regarding lifestyle and physical characteristics. They were classified into four glycometabolic categories based on the OGTT results: category 1: best glucose metabolism, category 2: low insulin sensitivity, category 3: low insulin secretion, and category 4: combined characteristics of categories 2 and 3. A total of 977 individuals were included; the ratios of participants in categories 1, 2, 3, and 4 were 46%, 21%, 14%, and 19%, respectively. Machine learning models (decision tree, support vector machine, random forest, and XGBoost) were developed for identifying the glycometabolic category using questionnaire responses. Then, the top 10 most important variables in the random forest model were selected, and another random forest model was developed using these variables. Its areas under the receiver operating characteristic curve (AUCs) to classify category 1 and the others, category 2 and the others, category 3 and the others, and category 4 and the others were 0.68 (95% confidence intervals: 0.62–0.75), 0.66 (0.58–0.73), 0.61 (0.51–0.70), and 0.70 (0.62–0.77). For external validation of the model, the same dataset of 452 Japanese adults in Hokkaido was obtained. The AUCs to classify categories 1, 2, 3, and 4 and the others were 0.66 (0.61–0.71), 0.57 (0.51–0.62), 0.60 (0.50–0.69), and 0.64 (0.57–0.71). In conclusion, our model could identify the glucose metabolism status using only 10 factors of lifestyle and physical characteristics. This model may help the larger general population without diabetes to understand their glucose metabolism status and encourage lifestyle improvement to prevent diabetes.
[Retracted] Application of Artificial Neural Network Algorithm in Facial Biological Image Information Scanning and Recognition
Authors: Zhang Zexin , Hu Ruimin , Hu Wenyi
Published: September 2022

In order to solve the problem that the accuracy of face recognition is not good due to the influence of jitter and environmental factors in the mobile shooting environment, this paper proposes the application of an artificial neural network algorithm in the information scanning and recognition of face biological images. The spatial neighborhood information is integrated into the amplitude detection of multipose face images, and the dynamic corner features of multipose face images are extracted. The structural texture information of multipose face images is compared to a global moving RGB three‐dimensional bit plane random field, and the multipose face images are detected and fused. At different scales, appropriate feature registration functions are selected to describe the feature points of multipose face images. The parallax analysis of target pixels and key feature detection of multipose face images are carried out. Image stabilization and automatic recognition are realized by combining artificial neural network learning and feature registration methods. The experimental results show that the experiment is designed with MATLAB, the frame frequency of dynamic face image acquisition is 1200 kHz, the number of collected samples of the multipose face image is 2000, the training sample set is 200, the noise coefficient = 0.24, the number of multipose face image blocks is 120, and the structural similarity is 0.12. It is found that the output signal‐to‐noise ratio of multipose face image recognition using the method in this paper is high. Conclusion. This method has good performance in feature point registration and high recognition accuracy for multipose face image recognition.
Interactive Design of Business English Learning Resources Based on EDIPT Multimodal Model
Authors: Yang Xiaomei , Qi Shi
Published: September 2022

Aiming at the problem that online video learning resources of business English are scattered and the learners are inefficient in acquiring learning resources, this paper designed a business English learning system based on the EDIPT model. In addition, aiming at the problem of multifeature fusion between low-level features and high-level semantic features in video scenes, this paper proposes a multi-modal video scene segmentation algorithm based on a deep network. By minimizing the square sum of distances in the time period, the shots are clustered, and finally, the semantic scene is obtained. The experimental results show that the algorithm has good performance in classification accuracy and can effectively segment video scenes, which is helpful for users to improve their comprehensive business English skills.
Analysis of Management Innovation of State-Owned Enterprises in the Context of Artificial Intelligence and Market-Oriented Economic Fluctuations
Authors: Wang Yanwen , Sun Lu
Published: September 2022

At this stage, with the development of society, China’s modernization level has also been greatly improved. Under the background of artificial intelligence and the impact of economic globalization, China’s external economic environment is changing with each passing day. Chinese enterprises are looking for new development ways to maintain their own development vitality under the condition of artificial intelligence. State-owned enterprises are controlled by the central or local governments. On this basis, this paper mainly discusses the innovative methods of state-owned enterprise management under the background of artificial intelligence, so as to provide reference for the innovation of state-owned enterprise management.
A Deep Learning-Based Assisted Teaching System for Oral English
Authors: Li Haibo , Liu Xue
Published: September 2022

The progress of global economic integration has forced English learners to have an urgent need to improve their oral English. College students’ oral English ability is currently the worst of the four abilities of listening, speaking, reading, and writing. The main reasons are internal and external. The internal reason is that the pronunciation characteristics of Chinese students are different from those of English. The external cause is that the practice environment and tools of oral English are not ideal, which affects the improvement of learners’ oral English. This study proposes using a deep learning algorithm (DLA) English in the evaluation of oral English quality to improve learners’ oral English level. The quality of oral English can be comprehensively evaluated in terms of pitch, speed of sound, and rhythm. The standard of pronunciation is the foundation of oral English and is the most critical factor. In many DLAs, the input unit of DNN at a certain moment and its upper and lower moment input units have no relationship and are independent of each other, and the timing dependencies of adjacent units are not fully considered. The results are generally not very good on speech recognition tasks. This study proposes a time-delay neural network (TDNN) and a long short-term memory (LSTM) network to calculate the posterior probability of the model state to model context-dependent features in order to solve this problem. The fusion model TDNN-LSTM is applied in the English spoken pronunciation recognition task. To compare the accuracy of oral English pronunciation, several classic DLAs are introduced. The experimental results show that the method described in this study has a number of advantages. Although the performance improvement of this method in terms of recognition accuracy is not large, a certain degree of improvement is also very important for the oral English teaching assistant system.
[Retracted] An Evaluation Model for the Influence Factors of Interest in Literature Courses Based on Data Analysis and Association Rules in a Small‐Sample Environment
Authors: Zhao Yiqian
Published: September 2022

The primary tools for developing pupils’ creativity, capacity for verbal expression, and spiritual growth are literary reading and writing. Literature is a sort of art that elicits feelings and expresses the author’s comprehension and outlook on social life via the use of language. Reading and writing literary works helps students develop their aesthetic sensibilities and capacity to create compelling images, as well as their spirituality and wisdom. This study suggests a data mining‐based optimal design approach for analyzing association rules of influencing aspects of interest in literary courses. To increase the frequency and accuracy of data mining, association rules are used to obtain the association mapping relationship between data sets of influencing factors of interest in literature courses. Rough set theory is then used to distinguish between the feature sets of data sets in the same subspace and different subspaces. To identify the most prevalent factor that affects the interest of the curriculum’s literary components and then to conduct simulation testing and analysis. The proposed arithmetic has a particular accuracy, which is 8.25% greater than the conventional arithmetic, according to simulation findings. This outcome demonstrates in full how the enhanced arithmetic decreases the amount of records in the scanning database by grouping and compressing the database, hence lowering the scanning time and pruning before the connection process of Liu arithmetic. Classical literary works are without a doubt the most valuable resources to feed, edify, forge, and grow the spirit, soul, and personality of contemporary individuals throughout history and in all nations. Education through literature develops one’s character, spirit, emotions, and aesthetic sense. The importance of reaffirming the significant place of literature education in contemporary national basic education cannot be overstated.
Preparation of Alumina Nanoparticles and Coating with Polyvinylpyrrolidone to Treat Cadmium Contamination of Water
Authors: Fayyadh Shaymaa Mohammed , Abed Foud Nihad , Awsaj Emaad Muhamme , Mohammed Samar S. , Mohamad Abdulsattar Abdullah Hamad , Abdulridha M. Mahdi , Alshehri Sameer , Tadele Gashaw , Enbeyle Wegayehu
Published: September 2022

Alumina nanoparticles were prepared by sol-gel method, where the obtained nanosize was 35 nm, and the nanomaterial was coated with PVP polymer, where the nanomaterial was dispersed by ultrasonic waves for half an hour, and then, the polymer was added, and under high magnetic stirring for 24 hours, it was dried at a temperature of 60°C for 24 hours. Cadmium salt solutions were prepared with different concentrations of 10, 30, and 60 ppm, and the nanomaterial was immersed in the prepared solutions at different times of 10, 30, and 60 minutes, and the measurement was done by an atomic absorption device. By means of the electronic scanner, a difference appeared in the nanosize, and this indicates that the packaging has completely occurred.
Trends of and Factors Associated with Maternal Near-Miss in Selected Hospitals in North Shewa Zone, Central Ethiopia
Authors: Gebremariam Tesfay Brhane , Demie Takele Gezahegn , Derseh Behailu Tariku , Mruts Kalayu Brhane
Published: September 2022

Maternal near-miss (MNM) refers to a woman who nearly died but survived a complication that occurred during pregnancy, childbirth, or within 42 days of termination of pregnancy. Studies in Ethiopia showed an inconsistent proportion of MNM across time and in different setups. This study is aimed at assessing the magnitude, trends, and correlates of MNM at three selected hospitals in North Shewa Zone, Central Ethiopia. A hospital-based cross-sectional study was conducted among 905 mothers who gave birth from 2012 to 2017 in three hospitals using the WHO criteria for MNM. Medical records of the study subjects were selected using a systematic sampling technique. Data were retrieved using a pretested data extraction tool. Association between MNM and independent variables was assessed by using a binary logistic regression model. An odds ratio with a 95% confidence interval (CI) andpvalue of <0.05 were used to declare the level of significance. Of the 905 medical records reviewed, the prevalence of MNM was 14.3% (95%CI=11.9−16.6) and similar over the last six years (2012-2017). The magnitude of life-threatening pregnancy complications was found to be 12.7%; severe preeclampsia (31%) and postpartum hemorrhage (26%) account for the highest proportion. Admission at a higher level of obstetric care like referral hospital (AOR=4.85; 95% CI: 1.82-12.94) and general hospital (AOR=3.76; 95% CI: 1.37-10.33), not using partograph for labor monitoring (AOR=1.89; 95% CI: 1.17-3.04), history of abortion (AOR=2.52; 95% CI: 1.18-5.37), and any other pregnancy complications (AOR=6.91; 95% CI: 3.89-12.28) were factors significantly associated with higher MNM. Even though lower than the national figure, the proportion of MNM in the study area was very high, and there were no significant changes over the last six consecutive years. Giving special emphasis to women with prior history of pregnancy complications, hypertensive disorders of pregnancy, and obstetric hemorrhage with strict and quick management protocols and the use of partograph for labor monitoring are recommended to reduce the burden of severe maternal outcomes in the study area and Ethiopia.
[Retracted] Analysis of the Effect of Classroom Reform of English Literature on the Theme of Environmental Protection in Universities Based on Artificial Intelligence Technology
Authors: Li Xuefeng
Published: September 2022

Under the current theme of environmental protection, the effect of English literature classroom teaching reform cannot be analyzed qualitatively. Based on BP neural network, we present an analytical model of the impact of College English Literature Classroom Teaching Reform on environmental protection based on artificial intelligence technology. We analyze the teaching reform of English literature classrooms with the theme of environmental protection under artificial intelligence technology and explore the concept of “intelligent education” and the construction path of university English ecological teaching mode. Based on the in‐depth excavation of teaching information, this paper analyzes the impact of college English literature classroom reform on the theme of environmental protection. Combined with BP neural network, a scientific analytic hierarchy process index system model is established, and the weight relationship of various reform influencing factors is given relatively objectively. The scores of the model based on the BP neural network under the six effect analysis indicators of teaching attitude, teaching tools, reform plan, reform teaching content, classroom organization, and reform rationality are 90.97, 86.3, 80.4, 95.7, 84.8, and 87.4, respectively. The results show that this model has a good ability for analysis and evaluation, which also provides some new ideas and entry points for the reform of the current English classroom teaching model. This study has a certain contribution to the breakthrough of college English teaching goals.
[Retracted] Public Art and Space Environment Design Using Genetic Algorithm‐Guided 3D Virtual Reconstruction
Authors: Luo Man
Published: September 2022

Public art plays a crucial role in influencing the development of the urban space environment by embodying the spiritual outlook and cultural heritage of a city. The research status and development trend of contemporary public art and space environment design are introduced in this article. In this essay, the relationship between public art and the environment of public spaces is examined in terms of type, status quo, and impact. The requirements of the virtual process are then thoroughly examined through the practical application of various collaborative software based on the actual needs of 3D virtual reconstruction. In parallel, a genetic algorithm‐based optimization design scheme for the space environment is proposed. Numerous experiments are conducted to confirm the viability of this method. The efficiency of this algorithm, according to experiments, is very high, reaching 94.87 percent. The scores of the residents are also good as a result of this article’s design. This demonstrates the validity of this approach. The study of public art and urban space environment design is expected to contribute positively to the growth of the city.
Design and Implementation of Print Advertisement Based on Computer Image Interactive Virtualization
Authors: Liu Huabai
Published: September 2022

This study aimed to further enhance and enrich users’ visual experience, provide users with a more infectious image sense, and further promote the development of multidimensional, virtualized, and interactive graphic advertising design applications. This study presents a design idea of print advertisement based on computer image interactive virtual technology. Based on the in-depth analysis of the multidimensional expression of plane image interactive virtualization, this idea carries out interactive virtual design with the help of interactive virtual image segmentation algorithm and plane advertising image element optimization technology. Through the test of image interactive edge extraction function on MATLAB platform, the simulation results show that the edge width of single side extraction results with different gray levels of the same width and different widths of the same gray level are 9 pixels, the gray values are 5a0, 110, and 200, respectively, and the edge width corresponds to 3, 9, and 15 pixels, respectively. The results show that the system can effectively enhance the image definition and obtain better print advertising design effect.
Analysis of Graphic Language Expression in Visual Communication Design
Authors: Xu Haixia , Shi LiLi
Published: September 2022

With the continuous development of society, only relying on words can no longer satisfy the mutual communication between people and countries. In the background of the data era, graphics language also meets more opportunities and challenges, so it is of great significance to transform data into the graphics language. This paper mainly designs a set of a data-based intelligent system. Through the research of multi-dimensional data visualization, firstly, the high-dimensional data is processed to reduce the dimension, so as to get the lower dimensional data, and then the low-dimensional data is transformed into a more intuitive type of graphic markers, so that users can understand the high-dimensional data more intuitively. The research results show that the system can provide users with the most appropriate label type and save users more time and energy. Data visualization has different experiences for different users, so it is a very important challenge to make users feel that pivoting is as effective as possible.
Formation Mechanism of Microbial Diversity in Artificial Intelligence Devices due to Intermediate Disturbance by Low-Dose UV Radiation for Complementary Medicine
Authors: Ye Junjie , Yang Yang , Wang Juanyi , Han Jingyu , Zhang Lihong , Gong Tianrun , Zhang Yi , Xing Xiaodong , Dong Chen
Published: September 2022

The development of artificial intelligence devices in the complementary medicine field is rapid and the surface microbial diversity pollution was found with periodic low-dose ultraviolet radiation (LDUVR). Since artificial intelligence devices do not have enough different types of substrates for microbial communities, it is unclear how the great microbial diversity can emerge and persist, as this clearly defies the competitive exclusion principle of ecology. In this study, the 5 most common genera in the artificial intelligence devices, Escherichia, Pseudomonas, Streptococcus, Staphylococcus and Aeromonas have been sampled without and with periodic LDUVR, respectively. A new hypothesis was put up to clarify the construction and maintenance process of high microbiological diversity in artificial intelligence devices by comparing and evaluating the variations between the dynamic response characteristics of their relative abundances in the two scenarios as follows: the periodic LDUVR can be regarded as an adverse factor with intermediate disturbance, causing stronger microbial stochastic growth responses (SGR) which would inevitably give rise to stronger random variation of the other important processes tightly correlated with SGR, such as intra- and interspecific competition process, and substrates production and consumption process, which could effectively diminish the auto- and cross-correlation of stochastic processes of microbial populations, alleviating the intra- and inter-specific competitions. In artificial intelligence devices with LDUVR, these crucial succession processes can propel the microbial communities to generate and sustain a high species diversity. Finally, thorough Monte Carlo simulations were used to thoroughly confirm the idea. This research can build the theoretical groundwork, offer fresh viewpoints, and suggest potential microbial prevention strategies for the succession of microbial communities in LDUVR.
[Retracted] Astragalus membranaceus and Salvia miltiorrhiza Ameliorate Hypertensive Renal Damage through lncRNA‐mRNA Coexpression Network
Authors: Zhou Le , Han Cong , Liu Yao , Cui Tao , Shen Zhen , Li Xiang-yu , Jiang Yue-hua , Li Wei
Published: September 2022

lncRNAs and mRNA are closely associated with hypertensive renal damage, and Astragalus membranaceus and Salvia miltiorrhiza (AS) have a therapeutic effect; however, the mechanism of AS to ameliorate hypertensive renal damage through the co‐expression network of lncRNA‐mRNA was unclear. In this study, we investigated the role of AS regulated the coexpression network of lncRNA‐mRNA in improving hypertensive renal damage. Sixteen 24‐week old spontaneous hypertensive rats (SHRs) were randomly divided into model group (M) and drug intervention group (AS, 5.9 g/kg), 8 Wistar Kyoto rats (WKY) of the same age as normal group (N). The treatment of rats was 4 weeks. Detecting the change of blood pressure, renal pathology and renal function related indicators, and lncRNA and mRNA sequencing and joint analysis was performed on the kidney. AS reduced blood pressure; decreased urine NAG, urine mALB, serum CysC, and IL‐6; and improved renal pathology compared with group M. Simultaneously, AS reversed the disordered expression of 178 differential expression (DE) mRNAs and 237 DE‐lncRNAs in SHRs, and their joint analysis showed that 13 DE‐mRNAs and 32 DE‐lncRNAs were coexpressed. Further analysis of 13 coexpressed DE‐mRNAs showed negative regulation of blood pressure and fatty acid beta‐oxidation was highly enriched in GO pathways, PPAR signaling pathway was highly enriched in KEGG pathways, and the verification related to these pathways was also highly consistent with the sequence. AS can alleviate hypertensive renal damage through the coexpression network of lncRNA‐mRNA, of which coexpressed 13 DE‐mRNAs and 32 DE‐lncRNAs were the important targets, and the pathway negative regulation of blood pressure, fatty acid beta‐oxidation, and PPAR signaling pathway play a major regulatory role.
KL-FGF23-VD Axis in Improving Late-Onset Alzheimer’s Disease by Modulating IKK/NF-κB Signal Pathway
Authors: Cai Yingying , Hu Jiali , He Mingjie
Published: September 2022

Aim of the Study. Late-onset Alzheimer’s disease (LOAD) is recognized as a degeneration disorder in patients’ central nervous system over 65 years old who will experience memory decline and cognitive impairment, causing great harm to the health of the elderly. To investigate the role of KL-FGF23-VD axis in LOAD and its molecular mechanism, we designed experiments from two dimensions of cells and animals. Materials and Methods. LOAD rats and Aβ microglia were constructed by using Aβ1-40 and IBO mixture. The effect of KL-FGF23-VD axis on LOAD was investigated by transfecting overexpressing and interfering with KL gene adenovirus, and IKK-16 was added to Aβ microglia to explore the effect of KL-FGF23-VD axis on regulation of IKK/NF-κB signaling pathway. Results. The results showed that, in KL-OE group, FGF23 was decreased in the hippocampus of LOAD rats compared with control and KL-si, and the trend was opposite in the KL-si group. The KL-FGF23-VD axis can alleviate inflammatory response, reduce the deposition of Aβ, and inhibit activation of the NF-κB pathway and neuron apoptosis in brain tissue of LOAD rats. In Aβ microglia, the expression of KL-FGF23-VD axis was consistent with animal experiments. The KL-FGF23-VD axis can inhibit the expression of Aβ microglia inflammatory factors and the activation of microglia and NF-κB pathway. Meanwhile, IKK expression was decreased in KL-OE group compared with KL-si and Control. In the IKK-16 addition group, the ability of KL-FGF23-VD axis to inhibit the activation of microglia and NF-κB pathway was enhanced. Conclusions. These findings suggest a potential role of the KL-FGF23-VD axis in AD treatment by regulating the IKK/NF-κB pathway.
[Retracted] Occupational Health Development and Safety Management of Enterprise Employees Based on the Perspective of Sustainable Environment
Authors: Chen Qilong , Li Hongliang , Pan Xiao
Published: September 2022

In recent years, the economy of enterprises has developed rapidly. Most enterprises focus on economic interests and ignore the occupational health of employees, resulting in an increase in the occupational morbidity rate of employees. Occupational insecurity of corporate employees will reduce the work efficiency of employees. In turn, it will affect the economic development of the enterprise. Paying attention to the occupational health and safety development of corporate employees is a necessary measure for corporate economic development. The main reasons that endanger the occupational health of employees are the unreasonable discharge of pollutants and the substandard treatment of pollutants. The sustainable environmental strategy of enterprise development can well control the risk factors that endanger the occupation of enterprise employees, and it is conducive to the health and safety development of enterprise employees and enterprises. This paper studied the impact of sustainable environmental factors on the occupational health and safety development of enterprise employees through the fuzzy analytic hierarchy process and analyzed the impact on the occupation of enterprise employees according to the larger influencing factors. The experimental results showed that heavy metal wastewater, dust, hydrogen sulfide gas, and high‐temperature radiation are the four most weighted impact indicators. Different concentrations of these four indicators are tested; when the concentration value of these impact indicators is low, it has little impact on the occupational safety and development of enterprise employees. However, when the concentration increases, the occupational safety and development of enterprise employees are seriously reduced. When the safety is the lowest, it is only 20%, and the development is only 23%. Carrying out sustainable environmental development can reduce the discharge of industrial waste; hence, while protecting the environment, the occupational health and safety and development potential of employees can be improved.