bluuebunny/crossref_metadata_2025 huggingface dataset:
Deep Learning-Based Data Augmentation and Model Fusion for Automatic Arrhythmia Identification and Classification Algorithms
Authors: Ma Shuai , Cui Jianfeng , Xiao Weidong , Liu Lijuan
Published: August 2022

Automated ECG-based arrhythmia detection is critical for early cardiac disease prevention and diagnosis. Recently, deep learning algorithms have been widely applied for arrhythmia detection with great success. However, the lack of labeled ECG data and low classification accuracy can have a significant impact on the overall effectiveness of a classification algorithm. In order to better apply deep learning methods to arrhythmia classification, in this study, feature extraction and classification strategy based on generative adversarial network data augmentation and model fusion are proposed to address these problems. First, the arrhythmia sparse data is augmented by generative adversarial networks. Then, aiming at the identification of different types of arrhythmias in long-term ECG, a spatial information fusion model based on ResNet and a temporal information fusion model based on BiLSTM are proposed. The model effectively fuses the location information of the nearest neighbors through the local feature extraction part of the generated ECG feature map and obtains the correlation of the global features by autonomous learning in multiple spaces through the BiLSTM network in the part of the global feature extraction. In addition, an attention mechanism is introduced to enhance the features of arrhythmia-type signal segments, and this mechanism can effectively focus on the extraction of key information to form a feature vector for final classification. Finally, it is validated by the enhanced MIT-BIH arrhythmia database. The experimental results demonstrate that the proposed classification technique enhances arrhythmia diagnostic accuracy by 99.4%, and the algorithm has high recognition performance and clinical value.
Battery Electric Bus Selection Based on Entropy Weight Method and Road Operation Test: Using Nanjing Bus Company as an Example
Authors: He Zhixia
Published: August 2022

Before putting battery electric buses into actual daily operations, the selection of buses is of great importance to the bus companies and the improvement of energy efficiency. Based on multi-dimension big data provided by the Nanjing Bus Company and by adopting the entropy weight method and road operation test, this paper presented an objective method for the selection of battery electric bus. Each of these four enterprises, BYD, Kaiwo, Yinlong, and Jiankang which were commonly seen in the Chinese market, provided two types of battery electric buses. Four different routes were selected for the road test and collected over 50 days of daily operation test data. In order to reflect all aspects of the vehicle performance, eight indexes which had been considered and designed comprehensively were classified into three categories: reliability, economy, and security. Together with the road operation data, an evaluation system based on the bus’s daily operation performance was established through the entropy weight method. Assessing results showed that battery electric bus with better performance usually had a total evaluation score over 0.69. Generally, electric buses with high scores on one route also had higher scores on all the other routes, such as brand D. But, on unimpeded routes, results may differ, for example, in route 134 W, 10-meter buses of brand B ranked first. In contrast to earlier studies, the selection result obtained by this method was more objective and intuitional, which was also consistent with the actual scenario. The selection process indicates that this method is highly practical and can be easily carried out. Therefore, we can assume that the proposed method can evaluate the actual operation state of battery electric buses and provides a new selection way.
Effects of Rhythmic Gymnastics on Joint Attention and Emotional Problems of Autistic Children: A Preliminary Investigation
Authors: Duan Guanting , Han Qing , Yao Mingyan , Li Ran
Published: August 2022

The adaptive rhythmic gymnastics (ARG) course has been specially designed for children with autism spectrum disorders (ASD). The purpose of this study is to discover the influence of the course on the joint attention and emotional problems of ASD children. This study adopted A-B-A cross-subject multibaseline design in a single case research design. The joint attention behaviour of two 6-year-old ASD children was examined. The experiment process was recorded and coded, and the results were analysed. The results illustrated the following: (1) ARG is effective in promoting the development of joint attention in ASD children, but it has a better effect on increasing responding joint attention, and (2) to a certain extent, ARG can boost the classroom participation of ASD children and improve their emotional problems.
Correlation Between Platelet-Lymphocyte Ratio and Neutrophil-Lymphocyte Ratio in Patients with Uterine Leiomyoma: A Cross-Sectional Study
Authors: Duan Yanan , Peng Yiqing , Shi Xiuling , Zhao Ying , Liu Kunyan , Zhou Runsheng , Peng Cunxu
Published: August 2022

The inflammatory reaction has been proven to be a key factor in the pathogenesis of uterine leiomyoma. The platelet-lymphocyte ratio (PLR) and the neutrophil-lymphocyte ratio (NLR) are inexpensive and reliable inflammatory biomarkers. However, evidence of the relationship between PLR and NLR in patients with uterine leiomyoma is limited. This study aimed to explore the relationship between PLR and NLR in patients with incident uterine leiomyoma. This cross-sectional study included 763 patients with uterine leiomyoma who were first diagnosed in our hospital between January 2016 and December 2016. Patient characteristics were collected for univariate analysis, smooth curve fitting, and multivariate piecewise linear regression. Overall, 722 patients with an average age of 40.16 ± 5.99 years were included. The average PLR was 161.22 ± 65.33. Univariate analysis revealed a significant positive correlation between PLR and NLR (

P
<
0.0001

). In addition, the non-linear relationship between the PLR and NLR was tested using smooth curve fitting after adjusting for potential confounding factors. The multivariate piecewise linear regression model showed that there was a significant positive correlation between PLR and NLR in both PLR <226.45 (β 0.01, 95% CI: 0.01, 0.01;

P
<
0.0001

) and >226.45 (β 0.00, 95% CI: 0.00, 0.00;

P
=
0.0026

). In conclusion, PLR and NLR are positively correlated in patients with uterine leiomyoma. This result clarifies the promoting role of inflammation in the occurrence of uterine leiomyoma.
Adhesive Bond Integrity of Experimental Zinc Oxide Nanoparticles Incorporated Dentin Adhesive: An SEM, EDX, μTBS, and Rheometric Analysis
Authors: Alfaawaz Yasser F. , Alamri Renad , Almohsen Fatimah , Shabab Sana , Alhamdan Mai M. , Al Ahdal Khold , Farooq Imran , Vohra Fahim , Abduljabbar Tariq
Published: August 2022

Objective. Our study is aimed at preparing an experimental adhesive (EA) and assessing the influence of adding 5-10 wt.% concentrations of zinc oxide (ZnO) nanoparticles on the adhesive’s mechanical properties. Methods. Field emission scanning electron microscopy (FESEM) and energy dispersive X-ray (EDX) spectroscopy were employed to investigate the morphology and elemental distribution of the filler nanoparticles. To examine the adhesive properties, microtensile bond strength (μTBS) testing, an investigation of the rheological properties, degree of conversion (DC), and analysis of the interface between the adhesive and dentin were carried out. Results. The SEM micrographs of ZnO nanoparticles demonstrated spherical agglomerates. The EDX plotting confirmed the incidence of Zn and oxygen (O) in the ZnO nanoparticles. The highest μTBS was observed for nonthermocycled (NTC) 5 wt.% ZnO group (

32.11
±
3.60

 MPa), followed by the NTC-10 wt.% ZnO group (

30.04
±
3.24

 MPa). Most of the failures observed were adhesive in nature. A gradual reduction in the viscosity was observed at higher angular frequencies, and the addition of 5 and 10 wt.% ZnO to the composition of the EA lowered its viscosity. The 5 wt.% ZnO group demonstrated suitable dentin interaction by showing the formation of resin tags, while for the 10 wt.% ZnO group, compromised resin tag formation was detected. DC was significantly higher in the 0% ZnO (EA) group. Conclusion. The reinforcement of the EA with 5 and 10 wt.% concentrations of ZnO nanoparticles produced an improvement in the adhesive’s μTBS. However, a reduced viscosity was observed for both nanoparticle-reinforced adhesives, and a negotiated dentin interaction was seen for 10 wt.% ZnO adhesive group. Further research exploring the influence of more filler concentrations on diverse adhesive properties is recommended.
An Enhanced Dynamic Nonlinear Polynomial Integrity-Based QHCP-ABE Framework for Big Data Privacy and Security
Authors: Singamaneni Kranthi Kumar , Juneja Abhinav , Abd-Elnaby Mohammed , Gulati Kamal , Kotecha Ketan , Kumar A. P. Senthil
Published: August 2022

Topics such as computational sources and cloud-based transmission and security of big data have turned out to be a major new domain of exploration due to the exponential evolution of cloud-based data and grid facilities. Various categories of cloud services have been utilized more and more widely across a variety of fields like military, army systems, medical databases, and more, in order to manage data storage and resource calculations. Attribute-based encipherment (ABE) is one of the more efficient algorithms that leads to better consignment and safety of information located within such cloud-based storage amenities. Many outmoded ABE practices are useful for smaller datasets to produce fixed-size cryptograms with restricted computational properties, in which their characteristics are measured as evidence and stagnant standards used to generate the key, encipherment, and decipherment means alike. To surmount the existing problems with such limited methods, in this work, a dynamic nonlinear poly randomized quantum hash system is applied to enhance the safety of cloud-based information. In the proposed work, users’ attributes are guaranteed with the help of a dynamic nonlinear poly randomized equation to initialize the chaotic key, encipherment, and decipherment. In this standard, structured and unstructured big data from clinical datasets are utilized as inputs. Real-time simulated outcomes demonstrate that the stated standard has superior exactness, achieving over 90% accuracy with respect to bit change and over 95% accuracy with respect to dynamic key generation, encipherment time, and decipherment time compared to existing models from the field and literature. Experimental results are demonstrated that the proposed cloud security standard has a good efficiency in terms of key generation, encoding, and decoding process than the conventional methods in a cloud computing environment.
Deep Neural Network-Based Novel Mathematical Model for 3D Brain Tumor Segmentation
Authors: Ladkat Ajay S. , Bangare Sunil L. , Jagota Vishal , Sanober Sumaya , Beram Shehab Mohamed , Rane Kantilal , Singh Bhupesh Kumar
Published: August 2022

The use of multimodal magnetic resonance imaging (MRI) to autonomously segment brain tumors and subregions is critical for accurate and consistent tumor measurement, which can help with detection, care planning, and evaluation. This research is a contribution to the neuroscience research. In the present work, we provide a completely automated brain tumor segmentation method based on a mathematical model and deep neural networks (DNNs). Each slice of the 3D picture is enhanced by the suggested mathematical model, which is then sent through the 3D attention U-Net to provide a tumor segmented output. The study includes a detailed mathematical model for tumor pixel enhancement as well as a 3D attention U-Net to appropriately separate the pixels. On the BraTS 2019 dataset, the suggested system is tested and verified. This proposed work will definitely help for the treatment of the brain tumor patient. The pixel level accuracy for tumor pixel segmentation is 98.90%. The suggested system architecture's outcomes are compared to those of current system designs. This study also examines the suggested system architecture's time complexity on various processing units with neuroscience approach.
Unexplained Hematocrit Increase after Therapeutic Phlebotomy in a Patient with Marked Erythrocytosis
Authors: Machhi Rushad , Cunningham Ashley M. , Hennrick Kenneth , Schaser Karen A. , Williams Eliot C. , Rose William Nicholas
Published: August 2022

We report a patient with hereditary erythrocytosis who underwent a therapeutic phlebotomy and had a post-phlebotomy hematocrit that was higher than the pre-phlebotomy hematocrit. We could not discern a reason for this hematocrit increase after phlebotomy. Instead of performing another phlebotomy, we performed an automated red cell depletion via an apheresis instrument. This procedure is essentially a red cell exchange, but 5% albumin is used as the replacement fluid instead of red blood cells. The patient’s hematocrit decreased from 80% to 39% after three consecutive daily red cell depletion procedures. We share our experience to report the unusual finding of a patient’s hematocrit that increased with phlebotomy and to raise awareness of the red cell depletion procedure.
A Village Reconstruction Model Using Particle Swarm Optimization Algorithm
Authors: Zhang Huiyi , Chen Fang , Sun Qiang , Feng Ye
Published: August 2022

In bygone days, the way to deal with traditional villages in developing new cities in China was often to overturn them and replace the original environment with the built-up urban environment, causing constructive destruction to the traditions and cultures. According to the new village transformation requirements, the planning and construction of villages must be shaped with their own cultural and humanistic characteristics of the habitat requirements. It does not favor demolishing large constructions by implementing a different environment. A traditional village is an essential spatial framework to retain the “mark” of the local characteristics of the new city. It can be an essential element in shaping the individual characteristics of the village by realizing the diversity of spatial forms and regional cultural connotations of the new village. Therefore, this paper proposes a new village transformation model based on traditional villages’ social, economic, and spatial patterns, combined with a new particle swarm optimization (PSO) algorithm named multi-objective particle swarm optimization (MOPSO). The model transforms the village based on the required optimum resource allocation with the global solution. The experiment shows that the proposed model suits village renovation and modernization. The work is a step toward the advancements and betterment of rural development.
Schisandrin A from Schisandra chinensis Attenuates Ferroptosis and NLRP3 Inflammasome-Mediated Pyroptosis in Diabetic Nephropathy through Mitochondrial Damage by AdipoR1 Ubiquitination
Authors: Wang Xiaohu , Li Qin , Sui Bangzhi , Xu Maodi , Pu Zhichen , Qiu Teng
Published: August 2022

Schisandra chinensis, as a Chinese functional food, is rich in unsaturated fatty acids, minerals, vitamins, and proteins. Hence, this study was intended to elucidate the effects and biological mechanism of Schisandrin A from Schisandra chinensis in DN. C57BL/6 mice were fed with a high-fat diet and then injected with streptozotocin (STZ). Human renal glomerular endothelial cells were stimulated with 20 mmol/L d-glucose for DN model. Schisandrin A presented acute kidney injury in mice of DN. Schisandrin A reduced oxidative stress and inflammation in model of DN. Schisandrin A reduced high glucose-induced ferroptosis and reactive oxygen species (ROS-)-mediated pyroptosis by mitochondrial damage in model of DN. Schisandrin A directly targeted AdipoR1 protein and reduced LPS+ATP-induced AdipoR1 ubiquitination in vitro model. Schisandrin A activated AdipoR1/AMPK signaling pathway and suppressed TXNIP/NLRP3 signaling pathway in vivo and in vitro model of DN. Conclusively, our study revealed that Schisandrin A from Schisandra chinensis attenuates ferroptosis and NLRP3 inflammasome-mediated pyroptosis in DN by AdipoR1/AMPK-ROS/mitochondrial damage. Schisandrin A is a possible therapeutic option for DN or other diabetes.
Prediction Model for Driver Reaction Time Based on PSO-BP Neural Network Model
Authors: Wang Dan , Hong Liang , Zhang Ce , Bai Yajie , Bi Zhen Zhen , Lin Yier
Published: August 2022

A critical element of accident reconstruction technology is the driver reaction time, which is also a key aspect of evaluating driver takeover time in autonomous driving. There are various factors affecting driver reaction time, including driver psychological factors, nondriving tasks, external environment, and other reasons. It is necessary to record and predict the driver reaction time to support the takeover time in the degraded takeover study because this paper is designed to conduct a degraded takeover study in the human-machine codriving stage with safety of the intended functionality. Therefore, a model based on PSO-BP neural network algorithm to predict driver reaction time is developed. A wavelet transform algorithm is used to denoise the signal first in order to improve the convergence speed and prediction accuracy of the model. Meanwhile, the BP neural network prediction model based on the PSO is established to optimize the weights and thresholds of the BP neural network to achieve the prediction of the driver reaction time. A total of six main feature parameters of driver’s HRV in the time and frequency domains were selected as input indicators and substituted into the input signal of PSO-BP neural network model for training and testing. The prediction results obtained from the PSO-BP neural network model were compared with that of the BP neural network prediction, and it demonstrated that the prediction results obtained in this paper have smaller error values, verifying the reasonableness and validity of the model.
Effect of Perioperative Comprehensive Nursing Intervention on the Rehabilitation Effect of Radiofrequency Ablation for Patients with Hypertrophic Obstructive Cardiomyopathy
Authors: Xiang Xiaoping , Chen Yanru , Dai Lijun
Published: August 2022

Objective. The aim of the study was to determine standardized perioperative nursing for radiofrequency ablation of hypertrophic obstructive cardiomyopathy under the guidance of intracardiac ultrasound, which can improve the quality of nursing. Methods. From January 2020 to November 2021, 40 patients with hypertrophic obstructive cardiomyopathy who underwent radiofrequency ablation under the guidance of intracardiac ultrasound in our hospital were selected. Patients were grouped according to their use of standardized perioperative nursing. Patients from both cohorts were compared for negative emotions, depression, and anxiety at the baseline and at month 2. Results. In general, there were no differences between the two groups (P > 0.05). At admission, the Self‐rating Depression Scale (SDS) and Self‐rating Anxiety Scale (SAS) scores of these two groups showed no differences (P > 0.05). Following nursing, the scores of the two groups dropped significantly, with the control group scoring much lower than the experimental group. Among the experimental group, the satisfaction rate was 100.00%, whereas the control group had an 85.00% satisfaction rate (P < 0.05). Following nursing, the scores of the two groups dropped significantly, with the control group scoring much lower than the experimental group. Conclusions. To sum up, perioperative comprehensive nursing intervention during surgical treatment can quickly alleviate patients’ clinical symptoms, reduce complications, damage to patients’ body, reduce patients’ pain, relieve patients’ anxiety and depression, and improve overall sleep quality and clinical nursing satisfaction.
Container Performance and Vulnerability Management for Container Security Using Docker Engine
Authors: Alyas Tahir , Ali Sikandar , Khan Habib Ullah , Samad Ali , Alissa Khalid , Saleem Muhammad Asif
Published: August 2022

Containers have evolved to support microservice architecture as a low-cost alternative to virtual machines. Containers are increasingly prevalent in the virtualization landscape because of better working; containers can bear considerably less overhead than the conventional hypervisor-based component virtual machines. However, containers directly communicate with the host kernel, and attackers can co-locate containers in the host system quicker than virtual machines. This causes significant security issues in container technology. The security hardening system is currently targeted at implementing universal access management regulations that make it difficult to assess the required procedure for accessing containers. Security mechanisms include an explicit awareness of the purpose and actions of the container and entail manual interaction and configuration. A user-friendly container protection scheme implemented an access policy to comply with its anticipated and legitimate application performance. In this study, container technology constraints have been overcome by proposing a unique Docker-sec mechanism. Docker-sec uses four mechanisms; the original collection has been improved during container runtime by additional rules that constrain the capacity of the container, further representing the applications in practice, file system, processes, network isolation, and vulnerability scanning of Docker images over different workload. Different vulnerabilities have been scanned with a CVE severity level. Results showed that inter-container communication with the system is more secure containers from zero vulnerabilities with an overhead of 3.45%.
Proliferation, Metastasis, and Radiosensitivity of Nasopharyngeal Carcinoma Cells in the Expression and Effect of Kiwifruit Extract through the Regulation of miR-205-5p
Authors: Chen Qiuqiu , Pan Min , Lu Yusong , Wei Feifei , Chen Chunqiao , Huang Hui
Published: August 2022

Background. Radix Actinidiae extract (RAE) has been shown to inhibit cancer in many studies, but its potential mechanism in nasopharyngeal cancer (NPC) progression remains unclear. Methods. NPC cells (SUNE1) were treated with different doses of RAE. For transfection, SUNE1 cells were transfected with the microRNA (miR)-205-5p inhibitor (anti-miR-205-5p) or mimic followed by treatment with 200 μg/mL RAE for 24 h. The MTT assay and colony formation assay were used to detect cell proliferation and radiosensitivity. The transwell assay was used to detect cell migration and invasion. The expression of miR-205-5p was detected by quantitative real-time PCR. The protein expression levels of matrix metalloproteinase-2 (MMP2) and matrix metalloproteinase-9 (MMP9) were detected by western blot analysis. Results. RAE inhibited NPC cell proliferation, migration, and invasion, while it enhanced radiosensitivity (

P
<
0.05

). Also, RAE treatment decreased miR-205-5p expression, as well as MMP2 and MMP9 protein levels (

P
<
0.05

). Anti-miR-205-5p transfection enhanced the effects of RAE on NPC cell proliferation, migration, invasion, and radiosensitivity (

P
<
0.05

), while miR-205-5p mimic transfection had an opposite effect (

P
<
0.05

). Conclusion. RAE might decrease miR-205-5p, thereby it inhibited NPC cell proliferation and metastasis and enhanced radiosensitivity.
Impact of Healthcare on Stock Market Volatility and Its Predictive Solution Using Improved Neural Network
Authors: Rouf Nusrat , Bashir Malik Majid , Sharma Sparsh , Ra In-Ho , Singh Saurabh , Meena Abhishek
Published: August 2022

The unprecedented Corona Virus Disease (COVID-19) pandemic has put the world in peril and shifted global landscape in unanticipated ways. The SARSCoV2 virus, which caused the COVID-19 outbreak, first appeared in Wuhan, Hubei Province, China, in December 2019 and quickly spread around the world. This pandemic is not only a global health crisis, but it has caused the major global economic depression. As soon as the virus spread, stock market prices plummeted and volatility increased. Predicting the market during this outbreak has been of substantial importance and is the primary motivation to carry out this work. Given the nonlinearity and dynamic nature of stock data, the prediction of stock market is a challenging task. The machine learning models have proven to be a good choice for the development of effective and efficient prediction systems. In recent years, the application of hyperparameter optimization techniques for the development of highly accurate models has increased significantly. In this study, a customized neural network model is proposed and the power of hyperparameter optimization in modelling stock index prices is explored. A novel dataset is generated using nine standard technical indicators and COVID-19 data. In addition, the primary focus is on the importance of selection of optimal features and their preprocessing. The utilization of multiple feature ranking techniques combined with extensive hyperparameter optimization procedures is comprehensive for the prediction of stock index prices. Moreover, the model is evaluated by comparing it with other models, and results indicate that the proposed model outperforms other models. Given the detailed design methodology, preprocessing, exploratory feature analysis, and hyperparameter optimization procedures, this work gives a significant contribution to stock analysis research community during this pandemic.
Research on Lateral and Longitudinal Coordinated Control of Distributed Driven Driverless Formula Racing Car under High-Speed Tracking Conditions
Authors: Bai Yunlong , Li Gang , Jin Hongyao , Li Ning
Published: August 2022

Aiming at the problem that it is difficult to ensure the trajectory tracking accuracy and driving stability of the distributed driven driverless formula racing car under high-speed tracking conditions, a lateral and longitudinal coordinated control strategy is proposed. Based on the adaptive model predictive control theory, the lateral motion controller is designed, and the prediction time domain of the controller is changed in real time according to the change of vehicle speed. Based on the sliding mode variable structure control theory, a longitudinal motion controller is designed to accurately track the desired vehicle speed. Considering the coupling between the lateral and longitudinal controls, the lateral controller inputs the longitudinal speed and displacement of the vehicle, using the feedback mechanism to update the prediction model in real time, the longitudinal controller takes the front wheel angle as the input, the driving torque is redistributed through the differential drive control, and the lateral and longitudinal coordinated control is carried out to improve the trajectory tracking accuracy and driving stability. The typical working conditions are selected for co-simulation test verification. The results show that the lateral and longitudinal coordinated control strategy can effectively improve the vehicle trajectory tracking control accuracy and driving stability.
Effects of Commercial Antioxidants on Aging Resistances of Asphalt Binders
Authors: An Xijie , Gao Ying , Dong Zizhen , Guo Qinglin , Li Lili , Li Yancang
Published: August 2022

Asphalt aging has a direct influence on the durability of asphalt mixture. In order to improve thermal oxidizing aging resistance of asphalt, the commercial antioxidants including Irganox 1010 and Irgafos 168 were selected to modify base asphalt and SBR asphalt. The basic properties of modified asphalt before and after the rolling thin film oven test (RTFOT) are evaluated by penetration, softening point, ductility, and viscosity. The Fourier transform infrared spectroscopy (FTIR) test was applied to determine the antiaging mechanism of modified and unmodified asphalt. According to the test result, Irganox 1010 not only reduces the aging degree of asphalt but also has little adverse effect on other properties. Irgafos 168 with a content of 1% improves the low temperature ductility of asphalt and improves the antiaging performance of asphalt significantly. After RTFOT, the content of oxygen-containing functional groups (carbonyl group and sulfoxide group) declines significantly in antioxidation modified asphalt, and Irganox 1010 and Irgafos 168 inhibit oxidizing reaction in the aging procedure. This study can provide a useful reference for improving the aging property of asphalt in highway construction.
Epigenetic Application of ATAC-Seq Based on Tn5 Transposase Purification Technology
Authors: Li Wangchun , Tim Wu U , Cheng Yu , Huang Yanhao , Mao Lipeng , Sun Menghan , Qiu Congling , Zhou Lin , Gao Lijuan
Published: August 2022

Background. Assays of transposase accessible chromatin sequencing (ATAC-seq) is an efficient assay to investigate chromatin accessibility, which depends on the activity of a robust Tn5 transposase to fragment the genome while cutting in the sequencing adapters. Methods. We propose reliable approaches for purifying hyperactive Tn5 transposase by chitin magnetic bead sorting. Double-stranded DNA of J76 cells and 293T cells were digested and subjected to tagmentation as test samples with Tn5 transposase, and libraries were established and sequenced. Sequencing data was then analyzed for peak calling, GO enrichment, and motif analysis. Results. We report a set of rapid, efficient, and low-cost methods for ATAC-seq library construction and data analysis, through large-scale and rapid sequencing. These methods can provide a reference for the study of epigenetic regulation of gene expression.
Antioxidant, Antidiabetic, and Antihypertension Inhibitory Potentials of Phenolic Rich Medicinal Plants
Authors: Hassan Amir , Khan Mohmand Numan Zada , Ullah Himayat , Hussain Abrar
Published: August 2022

Veronica (Plantaginaceae) and Schoenoplectus have a unique chemotaxonomic and phytochemical importance and are widely utilized in Turkish and Traditional Chinese Herbal Medicine (TCM) for treating tonics, influenza, diuretics, expectorants, restoratives, and respiratory diseases, and both are very useful in treating infectious and metabolic disorders as well. This study evaluates two medicinal plant species, Veronica biloba and Schoenoplectus triqueter (L.) Palla; extraction was performed through Soxhlet and maceration methods as well as determination of free and bound phenolics. Evaluated biological screening of (extracts and phenolics) angiotensin-I converting enzyme (ACE), Type-II diabetes (α-glucosidase and α-amylase), and antioxidants potential was performed using modified assays. The angiotensin-I converting enzyme (ACE) 50% inhibition potential in Veronica biloba was found at IC50 = 210.68 μg/mL and in Schoenoplectus triqueter (L.) Palla at IC50 = 229.40 µg/mL, respectively. Meanwhile Type-II diabetes with α-amylase 50% inhibition shown by bound phenolics of Veronica biloba at IC50 = 219.66 µg/mL and its water extract at IC50 = 110.09 µg/mL possesses higher potential, and α-glucosidase potential by free phenolics was found to be active at IC50 = 469.56 µg/mL, while water and ethyl acetate extracts showed higher potential, IC50 = 78.65 µg/mL and IC50 = 97.03 µg/mL, than the standard acarbose, recorded lower. In case of amylase, α-glucosidase showed IC50 = 88.73 μg/mL. Our results showed that both plants possess a direct relationship with the increase in the concentration of extracts and inhibited very strongly angiotensin-I converting enzyme (ACE) and Type-II diabetes (α-glucosidase and α-amylase). The properties of enzyme hindrance may be associated with phenolic compounds and rich phenolic plant antioxidant potential provides a route to the elucidation of natural antihypertension and antidiabetes.
Investigate the Mechanical Properties of Soybean Oil Reinforced with ATH‐Filled Polyester‐Based Hybrid Nanocomposites
Authors: Kaatubi K. M. , Meenakshi Reddy R. , Gnanasundar J. , Ramesh Birla , Rajendran Rajasekar , Joseph Manuel D. , Mohammed Sridar. W. , Asiful H. Sundar , Anbese Endalkachew Mergia
Published: August 2022

A mixed microbiologically composite made from natural Linum usitatissimum fibers with nano‐reinforced organic plastics can improve properties while being environmentally friendly. The inclusion of aluminium tris hydroxide particles into an organic polymer enables it to maintain stiffness without sacrificing durability, even while improving barriers and material characteristics. A study of numerous composite samples verified this complementary effect, with combinations including 10 percent EMS and 2.6 wt.% ATH retaining the resin’s stiffness, stress to breakage, and mechanical properties while improving durability. Mechanical tests such as tensile and impact strength were discovered using the conventional ASTM test plan. Best‐practice designs which maximize constituent interactions are thus attainable, and the research findings serve as the basis for discovering this balance, thereby broadening the spectrum of microbiologically polymer nanocomposites. The cracked surfaces of the nanomaterials, and the amount of dispersion of an ATH filler, were examined using a scanning electron microscope.
CD248 Regulates Wnt Signaling in Pericytes to Promote Angiogenesis and Tumor Growth in Lung Cancer
Authors: Hong Chia-Lun , Yu I-Shing , Pai Chen-Hsueh , Chen Jin-Shing , Hsieh Min-Shu , Wu Hua-Lin , Lin Shu-Wha , Huang Hsiang-Po
Published: August 2022

The tumor microenvironment plays a central role in cancer initiation and progression. CD248 is expressed in tumor-associated stromal cells, particularly fibroblasts and pericytes. Exploring the function of CD248 has the potential to provide biological insights into tumor-supportive stroma and potential therapeutic targets. Here, we investigated the role of stromal CD248 in lung cancer. In orthotopic lung cancer transplantation models, tumor volume, density of vessels and pericytes, and functionality of tumor vessels were all lower in mice lacking Cd248 (Cd248LacZ/LacZ) compared with Cd248 wild-type or haploinsufficient mice. Two angiogenic factors, OPN and SERPINE1, were decreased in Cd248LacZ/LacZ pericytes, and supplementation with both factors rescued their proliferation and endothelial cell tube formation–promoting ability. Mechanistically, Wnt/β-catenin signaling induced Opn and Serpine1 expression and was suppressed in Cd248LacZ/LacZ pericytes. CD248 interacted with Wnt pathway repressors IGFBP4 and LGALS3BP, leading to increased Wnt/β-catenin signaling. Correspondingly, administration of a β-catenin inhibitor in Cd248+/LacZ mice mimicked the effect of Cd248 loss and blocked the growth of transplanted lung tumor cells that were resistant to this inhibitor in vitro. In addition, CD248+ pericytes coexpressed OPN and SERPINE1 and correlated with increased tumor size in human lung cancer. Additionally, high expression of CD248, OPN, and SERPINE1 was associated with poor survival in lung cancer patients. In summary, CD248 derepresses Wnt signaling and upregulates OPN and SERPINE1 in pericytes, resulting in enhanced angiogenesis and lung cancer growth. This novel axis of CD248–Wnt signaling–angiogenic factors in pericytes provides a potential target for lung cancer therapy.

Significance:

These findings demonstrate that CD248 maintains pericyte function in lung cancer through the Wnt signaling pathway and present CD248 as a potential therapeutic target.
NCOA4-Mediated Ferritinophagy Is a Pancreatic Cancer Dependency via Maintenance of Iron Bioavailability for Iron–Sulfur Cluster Proteins
Authors: Santana-Codina Naiara , del Rey Maria Quiles , Kapner Kevin S. , Zhang Huan , Gikandi Ajami , Malcolm Callum , Poupault Clara , Kuljanin Miljan , John Kristen M. , Biancur Douglas E. , Chen Brandon , Das Nupur K. , Lowder Kristen E. , Hennessey Connor J. , Huang Wesley , Yang Annan , Shah Yatrik M. , Nowak Jonathan A. , Aguirre Andrew J. , Mancias Joseph D.
Published: August 2022

Pancreatic ductal adenocarcinomas (PDAC) depend on autophagy for survival; however, the metabolic substrates that autophagy provides to drive PDAC progression are unclear. Ferritin, the cellular iron storage complex, is targeted for lysosomal degradation (ferritinophagy) by the selective autophagy adaptor NCOA4, resulting in release of iron for cellular utilization. Using patient-derived and murine models of PDAC, we demonstrate that ferritinophagy is upregulated in PDAC to sustain iron availability, thereby promoting tumor progression. Quantitative proteomics reveals that ferritinophagy fuels iron–sulfur cluster protein synthesis to support mitochondrial homeostasis. Targeting NCOA4 leads to tumor growth delay and prolonged survival but with the development of compensatory iron acquisition pathways. Finally, enhanced ferritinophagy accelerates PDAC tumorigenesis, and an elevated ferritinophagy expression signature predicts for poor prognosis in patients with PDAC. Together, our data reveal that the maintenance of iron homeostasis is a critical function of PDAC autophagy, and we define NCOA4-mediated ferritinophagy as a therapeutic target in PDAC.

Significance:

Autophagy and iron metabolism are metabolic dependencies in PDAC. However, targeted therapies for these pathways are lacking. We identify NCOA4-mediated selective autophagy of ferritin (“ferritinophagy”) as upregulated in PDAC. Ferritinophagy supports PDAC iron metabolism and thereby tumor progression and represents a new therapeutic target in PDAC.

See related commentary by Jain and Amaravadi, p. 2023.

See related article by Ravichandran et al., p. 2198.

This article is highlighted in the In This Issue feature, p. 2007
Open High School Program during Pandemic an Assessment: Basis for Program Enhancement
Authors: Timula Janette M.
Published: August 2022

Education plays a significant part in moulding the future of our young generation of learners and leaders, and recognized as a basic human right. It is an essential requirement for a person’s well-being. Education is an absolute right of every individual which will enable him/her to become a productive citizen, globally competitive and can make the difference to every individual’s quality of life. Schools faced unprecedented challenges to ensuring sustainable education during the novel coronavirus COVID-19 pandemic. As school closures due to COVID-19 separate students from structured routines and educational supports, the number of disengaged students may continue to grow. Accordingly, this quantitative study reported that the Rizal High School in Pasig City, Philippines continuously adopted Open High School Program to meet with the disengaged students in the new normal. The subjects of the study were the twenty randomly selected teachers of Rizal High School during the School Year 2020-2021. It was found out that summary of the assessment on the open high school program based on goals and objectives has a general weighted mean of 3.75 interpreted as strongly agree, implies that the goals and objectives of the Open High School Program were well planned, organized and clearly defined. Such that, the methods of teaching had a general weighted mean of 3.46 "Strongly Agree." Further, there was an issue in the open high school program learners that needs to be addressed.
Qualifications and Competencies of Guidance Teachers as Correlates with their Performance: Basis for a Proposed Enrichment Program
Authors: Recede Reynald Alfred A. , Ignacio Nadia C. , Paz- Muñoz Felisa , Pekas Monette G.
Published: August 2022

The study aimed to determine the qualifications and competencies of guidance teachers in correlation with their performance for the school year 2018 – 2019. The status of the qualifications of the guidance teachers was determined in terms of educational attainment, level of seminars and trainings attended pertinent to guidance related work and length of service as a guidance teacher.  The respondents of the study were 15 school heads, 37 guidance teachers and 1,001 teachers. The study utilized the descriptive evaluative method. Data were collected through the use of researcher – adapted questionnaire checklist.  The results showed that there is no significant correlation between the qualifications of the guidance teachers and their competencies as perceived by the three groups of respondents. The results showed that there are no significant correlations between the qualifications of the guidance teachers and their performance. In consideration of the correlation that exists, the administrators and the teachers perceived that the guidance teachers’ qualifications are positively correlated with the performance. The results showed that there is a low correlation between the competencies of guidance teachers and their performance but considered to be not significant. In consideration of the administrators and teachers, the correlation is positive while for the guidance teachers themselves, the correlation is negative.
Computer Based Learning and Laboratory Based Learning in Electric Circuits: A Literature Review
Authors: Aballe Kathy Sheen , Tabago Roe Francis , De Juan Earl John , Suganob Aida Lou , Cardaño Milkay Mae , Pederiso Angeline , Mercado Justine C.
Published: August 2022

Computer based learning and laboratory-based learning are widely used nowadays mainly for teaching and learning of both teacher and students especially in teaching electrical circuits. This paper aims to review computer-based learning and laboratory-based learning, specifically other forms of CBL and LBL and how these methods are integrated in teaching and learning electrical circuits, and its advantages and disadvantages. In conducting this literature review, the researchers adapted the PRISMA method in which various journal articles are screened through different stages. Criterion was imposed to guide the researchers in the inclusion and exclusion process. It was found out that there are other forms of computer-based learning (CBL) such as the Java-based virtual laboratory and Grid computing laboratory. Also, integrating computer-based learning and laboratory-based learning would build a workable environment that helped in motivating students in exploring electrical circuits. There are various advantages of computer-based learning such as time saving and easy access to laboratory manuals. On the other hand, advantages of laboratory-based learning include the positive impact of interaction, group discussion, and collaboration that was delimited by the computer-based learning.
Generate, Annotate, and Learn: NLP with Synthetic Text
Authors: He Xuanli , Nassar Islam , Kiros Jamie , Haffari Gholamreza , Norouzi Mohammad
Published: August 2022

This paper studies the use of language models as a source of synthetic unlabeled text for NLP. We formulate a general framework called “generate, annotate, and learn (GAL)” to take advantage of synthetic text within knowledge distillation, self-training, and few-shot learning applications. To generate high-quality task-specific text, we either fine-tune LMs on inputs from the task of interest, or prompt large LMs with few examples. We use the best available classifier to annotate synthetic text with soft pseudo labels for knowledge distillation and self-training, and use LMs to obtain hard labels for few-shot learning. We train new supervised models on the combination of labeled and pseudo-labeled data, which results in significant gains across several applications. We investigate key components of GAL and present theoretical and empirical arguments against the use of class-conditional LMs to generate synthetic labeled text instead of unlabeled text. GAL achieves new state-of-the-art knowledge distillation results for 6-layer transformers on the GLUE leaderboard.
Saturated Transformers are Constant-Depth Threshold Circuits
Authors: Merrill William , Sabharwal Ashish , Smith Noah A.
Published: August 2022

Transformers have become a standard neural network architecture for many NLP problems, motivating theoretical analysis of their power in terms of formal languages. Recent work has shown that transformers with hard attention are quite limited in power (Hahn, 2020), as they can be simulated by constant-depth AND/OR circuits (Hao et al., 2022). However, hard attention is a strong assumption, which may complicate the relevance of these results in practice. In this work, we analyze the circuit complexity of transformers with saturated attention: a generalization of hard attention that more closely captures the attention patterns learnable in practical transformers. We first show that saturated transformers transcend the known limitations of hard-attention transformers. We then prove saturated transformers with floating-point values can be simulated by constant-depth threshold circuits, giving the class TC0 as an upper bound on the formal languages they recognize.
Die Theodizee in Maximos von Tyros’ 41. Rede
Authors: Krämer Benedikt
Published: August 2022

The present paper inquires into Maximus of Tyre’s theodicy (Or. 41). Contemporary scholarship tends to disclaim the philosophical significance of Maximus’ speeches due to their opulent rhetoric and popularising style. Oratio 41—Maximus’ speech on the problem of evil—might be suited to counteract such tendencies. The paper first analyses the different aspects of Maximus’ theodicy within its Stoic-Middle Platonic milieu, then demonstrates, how Maximus always takes into account the main purpose of his orations—encouraging his adolescent listeners to choose philosophy as a way of life.
Economic Integration via Novel Investment Agreements: CAI’s Focus on Market Access vis-à-vis the Current Bilateral Investment Treaties Between China and European Union Member States
Authors: Vaccaro-Incisa G. Matteo , Giemza Wojciech
Published: August 2022

The EU-China Comprehensive Agreement on Investment (CAI) features limited substantive ‘traditional’ guarantees for foreign investors but contains original liberalization commitments that go beyond the otherwise common ‘admission’ promise, or the less common ‘establishment’ commitment, to regulate ‘market access’ – a unicorn in the field. By focusing on this aspect, the analysis makes reference to a) the current legal and policy framework of both EU and China, b) their respective international investment agreement (IIA) policies, and c) the bilateral investment treaties between China and EU member States. The CAI reveals a sui generis character as, in addition to its novel focus, it consolidates the EU tendency to drawing from other fields, including trade law, environmental law, labour law, sustainable development, and public international law. Considering CAI’s departure from established models, and its specific scope and context, the agreement may not contribute significantly to the development of the design and evolution of substantive rights afforded to foreign investors in IIAs.
The CAI and Sustainable Development
Authors: Dagbanja Dominic Npoanlari
Published: August 2022

Sustainable investment is underpinned by principles that emphasise an investment’s contribution to sustainable development. Among the constituent elements of sustainable investment under the Comprehensive Agreement on Investment (CAI) is corporate social responsibility (CSR). I appraise CSR provisions as to whether they make investment work for sustainable development. The provisions on CRS are founded on internationally recognised norms on sustainable development and responsible business practices as overarching principles and demonstrate EU-China leadership to harmonise and converge rules on investment protection and norms on sustainable development. This has long term systemic implications for both EU-China future international economic relations and for the global investment treaty regime. However, the sustainable development provisions exemplified by those on CRS create voluntary responsibilities. They are, therefore, unlikely to result in the attainment of the objective of sustainable investment. To infuse substantive content to these provisions and make them practically relevant, I propose that aspects of the norms on sustainable development and responsible business practices need to be incorporated into CAI and made legally binding and enforceable.