bluuebunny/crossref_metadata_2025 huggingface dataset:
Psychology and Indigenous People
Authors: González Roberto , Carvacho Héctor , Jiménez-Moya Gloria
Published: July 2021

Whether there are common features inherent to the psychology of Indigenous peoples around the globe has been the subject of much debate. We argue that Indigenous peoples share the experience of colonization and its social and psychological consequences. We develop this argument across four sections: ( a) the global history of colonization and social inequalities; ( b) aspects concerning identity and group processes, including the intergenerational transmission of shared values, the connection with nature, and the promotion of social change; ( c) prejudice and discrimination toward Indigenous peoples and the role of psychological processes to improve relations between Indigenous and non-Indigenous peoples; and ( d) the impact of historical trauma and colonialism on dimensions including cognition, mental health, and the well-being of Indigenous peoples as well as the basis for successful interventions that integrate Indigenous knowledge. Finally, we address future challenges for research on these topics.
Financial Development and Carbon Emissions: Analyzing the Role of Financial Risk, Renewable Energy Electricity, and Human Capital for China
Authors: Guo Yiping
Published: July 2021

This study introduces the role of financial risk index and renewable energy electricity output along with financial development and human capital as new determinants of carbon emissions and uses updated time-series data from 1988–2018 for China, employing novel econometric approaches, i.e., Narayan and Popp unit root test with structural breaks, Maki cointegration, and frequency domain causality test for long, short, and medium run causality. The empirical outcome shows that improvement in human capital index and rising shares of renewable energy in electricity output help to limit carbon emissions. In contrast, gross domestic product, financial risk index, and structural break of 2001 increase carbon emissions. Moreover, structural break year of 2008 and financial development index reduces carbon emissions. The negative association between financial development and carbon emissions supports the positive school of thoughts of financial development which promotes sustainable environment. This study recommends promotion of quality human capital and green financial development along with increasing the shares of renewable energy in electricity for achieving China 2030 climate targets of reducing pollution.
Adoption of Snake Variable Model-Based Method in Segmentation and Quantitative Calculation of Cardiac Ultrasound Medical Images
Authors: Huang Xing , Zhu Haozhi , Wang Jiexin
Published: July 2021

This paper intends to explore the effect of the enhanced snake variable model in the segmentation of cardiac ultrasound images and its adoption in quantitative measurement of cardiac cavity. First, the basic principles of the traditional snake model and the gradient vector flow (GVF) snake model are explained. Then, an ellipsoid model is constructed to obtain the initial contour of the heart based on the three-dimensional volume of cardiac ultrasound image, and a discretized triangular mesh model is generated. Finally, the vortical gradient vector flow (VGVF) external force field is introduced and combined with the greedy algorithm to process the deformation of the initial ellipsoid contour of the heart. The segmentation effect is quantitatively evaluated regarding the area overlap rate (AOR) and the mean contour distance (MCD). The results show that the VGVF snake model can segment the deep recessed area of the “U-shaped map” in contrast to the traditional snake model and the GVF snake model. After being applied to ultrasonic image segmentation, the VGVF snake model obtains the segmentation result that is close to the doctor’s manual segmentation result, and the average AOR and MCD are 97.4% and 3.2, respectively. The quantitative evaluation of the cardiac cavity is carried out based on the segmentation results, and the measurement of the volume change of the left ventricle within a cardiac cycle is realized. To sum up, VGVF snake model is superior to the traditional snake and GVF snake models in terms of ultrasonic image segmentation, which realizes the three-dimensional segmentation and quantitative calculation of the cardiac cavity.
[Retracted] Utilization of Artificial Neural Network in Predicting the Total Organic Carbon in Devonian Shale Using the Conventional Well Logs and the Spectral Gamma Ray
Authors: Siddig Osama , Abdulhamid Mahmoud Ahmed , Elkatatny Salaheldin , Soupios Pantelis
Published: July 2021

Due to high oil and gas production and consumption, unconventional reservoirs attracted significant interest. Total organic carbon (TOC) is a significant measure of the quality of unconventional resources. Conventionally, TOC is measured experimentally; however, continuous information about TOC is hard to obtain due to the samples’ limitations, while the developed empirical correlations for TOC were found to have modest accuracy when applied in different datasets. In this paper, data from Devonian Duvernay shale were used to develop an optimized empirical correlation to predict TOC based on an artificial neural network (ANN). Three wells’ datasets were used to build and validate the model containing over 1250 data points, and each data point includes values for TOC, density, porosity, resistivity, gamma ray and sonic transient time, and spectral gamma ray. The three datasets were used separately for training, testing, and validation. The results of the developed correlation were compared with three available models. A sensitivity and optimization test was performed to reach the best model in terms of average absolute percentage error (AAPE) and correlation coefficient (R) between the actual and predicted TOC. The new correlation yielded an excellent match with the actual TOC values with R values above 0.93 and AAPE values lower than 14%. In the validation dataset, the correlation outperformed the other empirical correlations and resulted in less than 10% AAPE, in comparison with over 20% AAPE in other models. These results imply the applicability of this correlation; therefore, all the correlation’s parameters are reported to allow its use on different datasets.
An English Learning System Based on Mobile Edge Computing Constructs a Wireless Distance Teaching Environment
Authors: Wang Lingtuo , Xu Zhiqiang
Published: July 2021

The development of information technology and the progress of the educational information process provide technical support for the construction of a distance learning environment for learning English. Online teaching mode is a new thing for people, and it is more and more accepted by people familiar with it. We summarize and analyze the texts of short messages generated by students’ online learning, so as to fully understand students, make effective adjustments to the classroom, guide teachers’ teaching practices, optimize the classroom, and improve students’ learning, practical, and innovative abilities, in order to study the effect of online teaching on improving the ability and skills of learning English efficiently. This paper builds wireless distance teaching based on the English learning system of mobile edge computing and uses the method of case analysis and literature analysis to collect data from the database. A model was built based on online teaching, and a large number of relevant documents were read and analyzed through the literature survey method. The results of the study show that online teaching can effectively improve students’ oral and reading abilities. Students’ oral and reading abilities are about 30% higher than traditional teaching methods, and the awareness of cooperation among students has also increased by 80% compared to before, which solves the problem of popularization and improvement. The contradiction and the resolution of polarization and the transformation of underachievers, so that students’ personalities can be brought into full play and development, and college education will be on the track of quality education. This shows that the wireless long-distance teaching environment constructed by the English learning system based on mobile edge computing can play an excellent role in improving English ability.
Offline Pashto Characters Dataset for OCR Systems
Authors: Khan Sulaiman , Khan Habib Ullah , Nazir Shah
Published: July 2021

In computer vision and artificial intelligence, text recognition and analysis based on images play a key role in the text retrieving process. Enabling a machine learning technique to recognize handwritten characters of a specific language requires a standard dataset. Acceptable handwritten character datasets are available in many languages including English, Arabic, and many more. However, the lack of datasets for handwritten Pashto characters hinders the application of a suitable machine learning algorithm for recognizing useful insights. In order to address this issue, this study presents the first handwritten Pashto characters image dataset (HPCID) for the scientific research work. This dataset consists of fourteen thousand, seven hundred, and eighty-four samples—336 samples for each of the 44 characters in the Pashto character dataset. Such samples of handwritten characters are collected on an A4-sized paper from different students of Pashto Department in University of Peshawar, Khyber Pakhtunkhwa, Pakistan. On total, 336 students and faculty members contributed in developing the proposed database accumulation phase. This dataset contains multisize, multifont, and multistyle characters and of varying structures.
Robust Distribution-Free Hybrid Exponentially Weighted Moving Average Schemes Based on Simple Random Sampling and Ranked Set Sampling Techniques
Authors: Malela-Majika Jean-Claude , Shongwe Sandile C. , Aslam Muhammad , Abbasi Saddam A.
Published: July 2021

This paper proposes new nonparametric hybrid exponentially weighted moving average (HEWMA) control charts based on simple random sampling (SRS) and ranked set sampling (RSS) techniques using the Wilcoxon rank-sum

W

statistic. The in-control robustness and out-of-control (OOC) performances are thoroughly investigated using extensive simulations. The HEWMA

W

chart is shown to be superior to the basic exponentially weighted moving average (EWMA) and double EWMA

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charts in many cases under normal and nonnormal distributions. Moreover, the OOC sensitivities of the new HEWMA

W

-type control charts are further improved by using supplementary 2-of-2 and 2-of-3 standard and improved runs-rules approaches. It is found that the proposed HEWMA

W

-type charts with runs-rules perform better than the basic HEWMA

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SRS and RSS charts. Real-life data based on the impurity of iron ore are used to illustrate the design and implementation of the new control charts.
The Effect of First-Year Seminar Classroom Design on Social Integration and Retention of STEM First-Time, Full-Time College Freshmen
Authors: Leary Miriam , Tylka Alexander , Corsi Victoria , Bryner Randy
Published: July 2021

Classroom design is related to student satisfaction and learning, but its effect on student retention is unknown. This exploratory study compared the impact of classroom design on social integration and retention among STEM first-time, full-time college freshmen in a first-year seminar course by comparing classroom sizes (large (LL) vs. small (SL) lecture), classroom formats (lecture (SL) vs. flipped classroom (FC)), and classroom student composition of students at risk of attrition based on low math placement scores (combined low math (CLM) vs. separated low math (SLM)). To capture social integration of freshman after their first semester, students completed a survey for course credit. Retention rates of freshman returning to the university for their second year were included. Almost all students in all classrooms had made friends in college; most had made friends with peers in the course and were spending time with them outside of class. Compared with LL students, SL reported lower satisfaction with their overall social life. More FC students were satisfied with their social life, and fewer found making friends to be harder than expected. These findings showed even greater disparities between groups for at-risk students. SLM students exhibited lower social integration than CLM students. The CLM flipped classroom retained the highest percentage of students at the university into the second year. Findings from the present study suggest that integrating at-risk students into a first-year seminar flipped classroom that matches student composition of the major benefits social integration and retention into the second year, for all students as well as those with low math scores.
Diagnosis of the Misaligned Faults of the Vertical Test Instrument of High‐Precision Industrial Robot Reducer
Authors: Yu Zhen , Zhang Yuan
Published: July 2021

High‐precision reducer is the core component of industrial robots. In order to achieve the comprehensive performance testing of precision reducers, an instrument with a vertical layout and a cylindrical structure is designed. As a rotating machine, the inevitable coupling misalignment of the instrument can lead to vibration faults which lead to errors in the test. So it is pretty necessary to diagnose and monitor the coupling misalignment while the instrument is working. The causes of the coupling misaligned fault of the instrument and the relationship between the misalignment fault and torque ripple are analyzed in this paper. A method of using the torque transducer in the measurement chain of the instrument to diagnose the coupling misalignment is proposed in this paper. Many experiments have been done to test the capability of detecting the coupling misalignment using this method. Experimental results show that the amplitude of torque ripple of the shaft is linearly related to the coupling misalignment and is quadratically related to the rotation speed of the shaft when the misalignment exists in the shaft. The combination of components at the rotation frequency (fr) and the additional components can be used to diagnose faults due to coupling misalignment.
Grape Seed Proanthocyanidins Inhibit Migration and Invasion of Bladder Cancer Cells by Reversing EMT through Suppression of TGF‐β Signaling Pathway
Authors: Yang Ninggang , Gao Jing , Hou Ruizhen , Xu Xiaoli , Yang Ningqiang , Huang Shuangsheng
Published: July 2021

Bladder cancer (BC) is the most common cancer of the urinary system. Despite advances in diagnosis and therapy, the prognosis is still poor because of recurrence and metastasis. Epithelial‐mesenchymal transition (EMT) is considered to play an important role in the invasion and metastasis of BC. Grape seed proanthocyanidins (GSPs) exhibit chemopreventive and chemotherapeutic activities against several types of cancer. However, their effects and underlying mechanisms on the invasive potential of BC remain unclear. In this study, we found that GSPs inhibited migration, invasion, and MMP‐2/‐9 secretion of both T24 and 5637 bladder cancer cells at noncytotoxic concentrations. We also discovered that 5637 cells were more suitable than T24 cells for the EMT study. Further study showed that GSPs inhibited EMT by reversing the TGF‐β‐induced morphological change and upregulation of mesenchymal markers N‐cadherin, vimentin, and Slug as well as downregulation of epithelial markers E‐cadherin and ZO‐1 in 5637 cells. GSPs also inhibited TGF‐β‐induced phosphorylation of Smad2/3, Akt, Erk, and p38 in 5637 cells without affecting the expression of total Smad2/3, Akt, Erk, and p38. Taken together, the results of the present study demonstrate that GSPs effectively inhibit the migration and invasion of BC cells by reversing EMT through suppression of the TGF‐β signaling pathway, which indicates that GSPs could be developed as a potential chemopreventive and therapeutic agent against bladder cancer.
Research on Classification Method of Network Resources Based on Modified SVM Algorithm
Authors: Zhang Hao , Hu Jingchao , Zhang Yaodong
Published: July 2021

According to the traditional classification method of network capital resources, there are some problems such as low efficiency, low recall rate, and low precision rate of information. Therefore, this paper proposes a new classification method of network capital resources based on SVM algorithm. Firstly, the original sample data are analyzed by principal component analysis to realize the design of resource classification process. Then, the dimension reduction of network resources data is realized by word segmentation and denoising. Thirdly, the reduced sample data are trained by the SVM classifier, and the best parameters of the reduced data are obtained by the grid search method. Lastly, the search range of SVM classifier parameters based on the original sample data is reset, so as to quickly obtain the best SVM classifier parameters of the original sample data and realize the classification. The experimental results show that this method can improve the recall and precision of network resource information and shorten the classification time of network resources.
Forecasting Time‐Series Energy Data in Buildings Using an Additive Artificial Intelligence Model for Improving Energy Efficiency
Authors: Truong Ngoc-Son , Ngo Ngoc-Tri , Pham Anh-Duc
Published: July 2021

Building energy efficiency is important because buildings consume a significant energy amount. The study proposed additive artificial neural networks (AANNs) for predicting energy use in residential buildings. A dataset in hourly resolution was used to evaluate the AANNs model, which was collected from a residential building with a solar photovoltaic system. The proposed AANNs model achieved good predictive accuracy with 14.04% in mean absolute percentage error (MAPE) and 111.98 Watt‐hour in the mean absolute error (MAE). Compared to the support vector regression (SVR), the AANNs model can significantly improve the accuracy which was 103.75% in MAPE. Compared to the ANNs model, accuracy improvement percentage by the AANNs model was 4.6% in MAPE. The AANNs model was the most effective forecasting model among the investigated models in predicting energy consumption, which provides building managers with a useful tool to improve energy efficiency in buildings.
Advanced Abdominal Pregnancy (AAP) after 20 Weeks of Gestation in Japan: A Retrospective Review
Authors: Hoshino Tatsuji , Mori Tatsuo , Fujii Yu , Yoshioka Shinya
Published: July 2021

Background. An advanced abdominal pregnancy (AAP) rarely continues to a live birth, but sometimes, a live birth may occur. In developed countries, women with AAP who have not been diagnosed preoperatively are expected to be diagnosed quickly, and the pregnant woman and the fetus will be saved. After careful examination of the past cases, we sought to derive what is the best diagnosis and treatment choice in the current medical environment. Materials and Methods. We retrospectively studied AAP cases in Japan. We examined diagnosis of AAP before fetal delivery and placental treatment at the time of delivery. AAP was well documented in 10 cases. We contacted the AAP authors, who reported 10 AAP cases in Japan, directly to confirm any unclear points. Results. Two cases were diagnosed with AAP before laparotomy, one was diagnosed after IUFD, and seven were diagnosed at the time of laparotomy. The two most recent cases were diagnosed with AAP preoperatively by ultrasound and MRI. Six cases were described for preoperative diagnosis. There were two cases of placenta previa, one of a bicornuate uterus, one of breech presentation, one of a combination of uterine cervical fibroids and placenta previa, and one of a combination of presentation and placental abnormality with uterine fibroids. In five cases, the placenta was removed at the time of laparotomy. Simultaneous removal of the placenta during laparotomy could not be performed because of intra-amniotic infection with a macerated fetus in an IUFD case. Among eight cases, excluding 20-week and 21-week gestation with no expectation of viable newborns, there were one male and seven female fetuses. The birth weight ranged from 1765 to 3520 g, with a median birth weight of 2241 g. Combined malformations were described in six of the seven live births. Clubfoot, torticollis, joint contracture, and bone deformity were transient because intrauterine compression quickly improved. Conclusion. In recent cases, AAP has been diagnosed by MRI and ultrasound. MRI should be performed if abdominal pregnancy is suspected. Postoperative infections may occur if the placenta is not removed at the time of delivery. We recommend placental resection with the help of an anesthesiologist, a gynecologist, a urologist, and a surgeon in the current medical environment.
Established Digital Model of Fruit Body Growth of Agrocybe cylindracea Based on Network Programming
Authors: Wang Long , Li Lingli , Zhou Qingping
Published: July 2021

Agricultural information technology is an emerging technology based on the cross-fertilization of information technology and agricultural science, which has caused the rapid development of digital agriculture and smart agriculture. Crop growth models, as one of their core components, can dynamically simulate the crop growth and development process and its relationship with climate factors, soil properties, and management techniques, thus effectively overcoming the strong spatial and temporal limitations in traditional agricultural production management research and providing quantitative tools for early warning and effect assessment of crop productivity prediction under different conditions. This study focuses on the general technical approach, the latest research progress, and future development thinking developed by the authors in the construction and application of the tea mushroom growth model. Based on the fitting method of the data model curve of the Internet laboratory, this study is proposed to use network programming technology to digitally fit the growth curve of cap diameter and stalk diameter of the fruiting body in the process of Agrocybe cylindracea growth. The fitting system adopted the development mode of PHP + MYSQL and took the MYSQL database as the core, which made the curve fitting of the final experimental data fast, convenient, and more intelligent. This study laid a preliminary foundation for the effective establishment and improvement of laboratory Agrocybe cylindracea, fruiting body growth data statistics and analysis, and graphical output network sharing.
The Accuracy of Visceral Adiposity Index for the Screening of Metabolic Syndrome: A Systematic Review and Meta-Analysis
Authors: Bijari Moniba , Jangjoo Sara , Emami Nima , Raji Sara , Mottaghi Mahdi , Moallem Roya , Jangjoo Ali , Saberi Amin
Published: July 2021

Background and Aims. Visceral adiposity index (VAI) is a novel marker of fat distribution and function which incorporates both anthropometric and laboratory measures. Recently, several studies have suggested VAI as a screening tool for metabolic syndrome (MetS). Here, we aimed to consolidate the results of these studies by performing a systematic review and meta-analysis. Methods and Results. We searched PubMed and EMBASE online databases for eligible studies that investigated the association of VAI and MetS. After reviewing 294 records, we included 33 eligible papers with a sum of 20516 MetS and 53242 healthy participants. The risk of bias in the included studies was assessed, and the relevant data was extracted. All included studies reported a significant association between VAI and MetS screening, but were highly heterogeneous in their reported effects. We pooled the diagnostic test accuracy metrics of VAI for MetS screening and showed that it has a moderate-to-high accuracy with an area under the summary receiver operating characteristics curve of 0.847, a pooled sensitivity of 78%, and a pooled specificity of 79%. Besides, we pooled the difference in means of VAI between patients with MetS and healthy controls, revealing that VAI was 2.15 units higher in MetS patients. Conclusions. VAI is an accurate, low-cost, and widely available screening marker for MetS. However, further studies are needed to evaluate its applicability in clinical practice, determine an optimal cut-off, and identify populations that would benefit the most from it.
English Grammar Error Detection Using Recurrent Neural Networks
Authors: He Zhenhui
Published: July 2021

Automatic marking of English compositions is a rapidly developing field in recent years. It has gradually replaced teachers’ manual reading and become an important tool to relieve the teaching burden. The existing literature shows that the error of verb consistency and the error of verb tense are the two types of grammatical errors with the highest error rate in English composition. Hence, the detection results of verb errors can reflect the practicability and effectiveness of an automatic reading system. This paper proposes an English verb’s grammar error detection algorithm based on the cyclic neural network. Since LSTM can effectively retain the valid information in the context during training, this paper decided to use LSTM to model the labeled training corpus. At the same time, how to convert the text information in English compositions into numerical values for subsequent calculation is also an important step in automatic reading. Most mainstream tools use the word bag model, i.e., each word is encoded according to the order of each word in the dictionary. Although this encoding method is simple and easy to use, it not only causes the vector to lose the sequence information of the text but also is prone to dimensional disaster. Therefore, word embedding model is adopted in this paper to encode the text, and the text information is sequentially mapped to a low-dimensional vector space. In this way, the position information of the text is not lost, and the dimensional disaster is avoided. The proposed work collects some corpus samples and compares the proposed algorithm with Jouku and Bingguo. The verification results show the superiority of the proposed algorithm in verb error detection.
Diagnosis and Treatment Effect of Convolutional Neural Network-Based Magnetic Resonance Image Features on Severe Stroke and Mental State
Authors: Han Lihong , Liu Li , Hao Yankun , Zhang Lan
Published: July 2021

The purpose of this paper is to explore the impact of magnetic resonance imaging (MRI) image features based on convolutional neural network (CNN) algorithm and conditional random field on the diagnosis and mental state of patients with severe stroke. 208 patients with severe stroke who all received MRI examination were recruited as the research objects. According to cerebral small vascular disease (CSVD) score, the patients were divided into CSVD 0∼4 groups. The patients who completed the three-month follow-up were classified into cognitive impairment group (124 cases) and the noncognitive impairment group (84 cases) according to the cut-off point of the Montreal cognitive assessment (MOCA) scale score of 26. A novel image segmentation algorithm was proposed based on U-shaped fully CNN (U-Net) and conditional random field, which was compared with the fully CNN (FCN) algorithm and U-Net algorithm, and was applied to the MRI segmentation training of patients with severe stroke. It was found that the average symmetric surface distance (ASSD) (3.13 ± 1.35), Hoffman distance (HD) (28.71 ± 9.05), Dice coefficient (0.78 ± 1.35), accuracy (0.74 ± 0.11), and sensitivity (0.85 ± 0.13) of the proposed algorithm were superior to those of FCN algorithm and U-Net algorithm. There were significant differences in the MOCA scores among the five groups of patients from CSVD 0 to CSVD 4 in the three time periods (0, 1, and 3 months) (

P
<
0.05

). Differences in cerebral microhemorrhage (CMB), perivascular space (PVS), and number of cavities, Fazekas, and total CSVD scores between the two groups were significant (

P
<
0.05

). Multivariate regression found that the number of PVS, white matter hyperintensity (WMH) Fazekas, and total CSVD score were independent factors of cognitive impairment. In short, MRI images based on deep learning image segmentation algorithm had good application value for clinical diagnosis and treatment of stroke and can effectively improve the detection effect of brain domain characteristics and psychological state of patients after stroke.
Development of a Human Intestinal Organoid Model for In Vitro Studies on Gut Inflammation and Fibrosis
Authors: Kandilogiannakis Leonidas , Filidou Eirini , Drygiannakis Ioannis , Tarapatzi Gesthimani , Didaskalou Stylianos , Koffa Maria , Arvanitidis Konstantinos , Bamias Giorgos , Valatas Vassilis , Paspaliaris Vasilis , Kolios George
Published: July 2021

Inflammatory Bowel Diseases (IBDs) are characterized by chronic intestinal inflammation and fibrosis, the latter being the predominant denominator for long-term complications. Epithelial and mesenchymal 2D cultures are highly utilized in vitro models for the preclinical evaluation of anti-inflammatory and antifibrotic therapies. More recently, human intestinal organoids (HIOs), a new 3D in vitro model derived from pluripotent stem cells, have the advantage to closely resemble the architecture of the intestinal mucosa. However, the appropriate timing for the study of inflammatory and fibrotic responses, during HIO development, has not been adequately investigated. We developed HIOs from the human embryonic stem cell line, H1, and examined the expression of mesenchymal markers during their maturation process. We also investigated the effect of inflammatory stimuli on the expression of fibrotic and immunological mediators. Serial evaluation of the expression of mesenchymal and extracellular matrix (ECM) markers revealed that HIOs have an adequately developed mesenchymal component, which gradually declines through culture passages. Specifically, CD90, collagen type I, collagen type III, and fibronectin were highly expressed in early passages but gradually diminished in late passages. The proinflammatory cytokines IL-1α and TNF-α induced the mRNA expression of fibronectin, collagen types I and III, tissue factor (TF), and alpha-smooth muscle actin (α-SMA) primarily in early passages. Similarly, HIOs elicited strong mRNA and protein mesenchymal (CXCL10) and epithelial (CXCL1, CCL2, CXCL8, and CCL20) chemokine responses in early but not late passages. In contrast, the epithelial tight junction components, CLDN1 and JAMA, responded to inflammatory stimulation independently of the culture passage. Our findings indicate that this HIO model contains a functional mesenchymal component, during early passages, and underline the significance of the mesenchymal cells’ fitness in inflammatory and fibrotic responses. Therefore, we propose that this model is suitable for the study of epithelial-mesenchymal interactions in early passages when the mesenchymal component is active.
Randomized Phase II Study of Axitinib versus Observation in Patients with Recurred or Metastatic Adenoid Cystic Carcinoma
Authors: Kang Eun Joo , Ahn Myung-Ju , Ock Chan-Young , Lee Keun-Wook , Kwon Jung Hye , Yang Yaewon , Choi Yoon Hee , Kim Min Kyoung , Ji Jun Ho , Yun Tak , Nam Byung-Ho , Kim Sung-Bae , Keam Bhumsuk
Published: July 2021

Purpose:

The role of chemotherapy in adenoid cystic carcinoma (ACC) is controversial because ACC is usually stable without chemotherapy and the lack of randomized trials. Here, we conducted the first randomized trial to evaluate the efficacy of axitinib as compared with observation in ACC.

Patients and Methods:

In this multicenter, prospective phase II trial, we enrolled patients with recurrent or metastatic ACC whose cancer had progressed within the past 9 months. Patients were randomly assigned to either axitinib (5 mg twice daily) or observation at a 1:1 ratio. Crossover from observation to axitinib was permitted after progression. The primary endpoint was a 6-month progression-free survival (PFS) rate. The secondary endpoints included objective response rate (ORR), overall survival (OS), PFS, duration of response, and adverse events.

Results:

Sixty patients were allocated to the axitinib or observation group, with response evaluation conducted in 54 patients. With a median follow-up of 25.4 months, the 6-month PFS rate was 73.0% with axitinib and 23.0% with observation. Median PFS was longer in the axitinib arm (10.8 months vs. 2.8 months, P < 0.001). The ORR of axitinib was 0.0%, but the disease control rate was 100.0% with axitinib and 51.9% with observation. Median OS was not reached with axitinib, but was 27.2 months with observation (P = 0.226). The most frequently reported adverse events for axitinib were oral mucositis and fatigue.

Conclusions:

In this first randomized trial in patients with ACC, axitinib significantly increased the 6-month PFS rate as compared with observation. (ClinicalTrials.gov number, NCT02859012)
A Biparatopic Antibody–Drug Conjugate to Treat MET-Expressing Cancers, Including Those that Are Unresponsive to MET Pathway Blockade
Authors: DaSilva John O. , Yang Katie , Surriga Oliver , Nittoli Thomas , Kunz Arthur , Franklin Matthew C. , Delfino Frank J. , Mao Shu , Zhao Feng , Giurleo Jason T. , Kelly Marcus P. , Makonnen Sosina , Hickey Carlos , Krueger Pamela , Foster Randi , Chen Zhaoyuan , Retter Marc W. , Slim Rabih , Young Tara M. , Olson William C. , Thurston Gavin , Daly Christopher
Published: July 2021

Lung cancers harboring mesenchymal-to-epithelial transition factor (MET) genetic alterations, such as exon 14 skipping mutations or high-level gene amplification, respond well to MET-selective tyrosine kinase inhibitors (TKI). However, these agents benefit a relatively small group of patients (4%–5% of lung cancers), and acquired resistance limits response durability. An antibody–drug conjugate (ADC) targeting MET might enable effective treatment of MET-overexpressing tumors (approximately 25% of lung cancers) that do not respond to MET targeted therapies. Using a protease-cleavable linker, we conjugated a biparatopic METxMET antibody to a maytansinoid payload to generate a MET ADC (METxMET-M114). METxMET-M114 promotes substantial and durable tumor regression in xenografts with moderate to high MET expression, including models that exhibit innate or acquired resistance to MET blockers. Positron emission tomography (PET) studies show that tumor uptake of radiolabeled METxMET antibody correlates with MET expression levels and METxMET-M114 efficacy. In a cynomolgus monkey toxicology study, METxMET-M114 was well tolerated at a dose that provides circulating drug concentrations that are sufficient for maximal antitumor activity in mouse models. Our findings suggest that METxMET-M114, which takes advantage of the unique trafficking properties of our METxMET antibody, is a promising candidate for the treatment of MET-overexpressing tumors, with the potential to address some of the limitations faced by the MET function blockers currently in clinical use.
SLC7A11 Is a Superior Determinant of APR-246 (Eprenetapopt) Response thanTP53Mutation Status
Authors: Fujihara Kenji M. , Corrales Benitez Mariana , Cabalag Carlos S. , Zhang Bonnie Z. , Ko Hyun S. , Liu David S. , Simpson Kaylene J. , Haupt Ygal , Lipton Lara , Haupt Sue , Phillips Wayne A. , Clemons Nicholas J.
Published: July 2021

APR-246 (eprenetapopt) is in clinical development with a focus on hematologic malignancies and is promoted as a mutant-p53 reactivation therapy. Currently, the detection of at least one TP53 mutation is an inclusion criterion for patient selection into most APR-246 clinical trials. Preliminary results from our phase Ib/II clinical trial investigating APR-246 combined with doublet chemotherapy [cisplatin and 5-fluorouracil (5-FU)] in metastatic esophageal cancer, together with previous preclinical studies, indicate that TP53 mutation status alone may not be a sufficient biomarker for APR-246 response. This study aims to identify a robust biomarker for response to APR-246. Correlation analysis of the PRIMA-1 activity (lead compound to APR-246) with mutational status, gene expression, protein expression, and metabolite abundance across over 700 cancer cell lines (CCL) was performed. Functional validation and a boutique siRNA screen of over 850 redox-related genes were also conducted. TP53 mutation status was not consistently predictive of response to APR-246. The expression of SLC7A11, the cystine/glutamate transporter, was identified as a superior determinant of response to APR-246. Genetic regulators of SLC7A11, including ATF4, MDM2, wild-type p53, and c-Myc, were confirmed to also regulate cancer-cell sensitivity to APR-246. In conclusion, SLC7A11 expression is a broadly applicable determinant of sensitivity to APR-246 across cancer and should be utilized as the key predictive biomarker to stratify patients for future clinical investigation of APR-246.
Sarcopenia Is Associated with Mortality in Adults: A Systematic Review and Meta-Analysis
Authors: Xu Jane , Wan Ching S. , Ktoris Kiriakos , Reijnierse Esmee M. , Maier Andrea B.
Published: July 2021

Background: Sarcopenia can predispose individuals to falls, fractures, hospitalization, and mortality. The prevalence of sarcopenia depends on the population studied and the definition used for the diagnosis. Objective: This systematic review and meta-analysis aimed to investigate the association between sarcopenia and mortality and if it is dependent on the population and sarcopenia definition. Methods: A systematic search was conducted in MEDLINE, EMBASE, and Cochrane from 1 January 2010 to 6 April 2020 for articles relating to sarcopenia and mortality. Articles were included if they met the following criteria – cohorts with a mean or median age ≥18 years and either of the following sarcopenia definitions: Asian Working Group for Sarcopenia (AWGS and AWGS2019), European Working Group on Sarcopenia in Older People (EWGSOP and EWGSOP2), Foundation for the National Institutes of Health (FNIH), International Working Group for Sarcopenia (IWGS), or Sarcopenia Definition and Outcomes Consortium (SDOC). Hazard ratios (HR) and odds ratios (OR) were pooled separately in meta-analyses using a random-effects model, stratified by population (community-dwelling adults, outpatients, inpatients, and nursing home residents). Subgroup analyses were performed for sarcopenia definition and follow-up period. Results: Out of 3,025 articles, 57 articles were included in the systematic review and 56 in the meta-analysis (42,108 participants, mean age of 49.4 ± 11.7 to 86.6 ± 1.0 years, 40.3% females). Overall, sarcopenia was associated with a significantly higher risk of mortality (HR: 2.00 [95% CI: 1.71, 2.34]; OR: 2.35 [95% CI: 1.64, 3.37]), which was independent of population, sarcopenia definition, and follow-up period in subgroup analyses. Conclusions: Sarcopenia is associated with a significantly higher risk of mortality, independent of population and sarcopenia definition, which highlights the need for screening and early diagnosis in all populations.
Specialty Choice among Final-Year Medical Students at Taif University
Authors: Mahfouz Mohammad Eid M. , Althobaiti Ziyad F. , Alosaimi Saud G. , Alghamdi Yasser A. , Alharthi Hattan E. , Althobaiti Abdulaziz M. , Altowairqi Faisal K.
Published: July 2021

Introduction: In Saudi Arabia (SA), the most important issue for senior students during their modules and hospital training is choosing a medical specialty. Because many factors influence this process, the primary goal of this study was to determine participants’ preferred specialty, location, and other influencing factors. Materials and Methods: This cross-sectional study involved 6th-year students from the medical schools in Taif city, SA, conducted from November 2020 to June 2021. Baseline characteristics, specialties of interest, place, and psychological aspects of their interests were all evaluated via a self-reported questionnaire. Results: One hundred forty of 200 surveyed students responded (70% response rate). About 44.3% were females, and 55.7% were male, with a mean grade point average of 3.5/4.0 and were all from Taif University. Nearly 86.4% were interested in SA’s local training programs, and the most preferred hospital for residency program was the Ministry of Health (37.1%), while the most preferred region inside SA was the western region (61.4%). The preferred medical specialties were family medicine followed by ENT, yet 2% were undecided about their future specialty. The most common factor that influenced the students to choose the location for training was quality of training (41.4%), followed by the cooperation of the hospital staff with new trainees (30%). Conclusion: The majority of medical interns preferred to complete their residency or postgraduate studies in SA, according to the findings of the study. Family medicine and ENT were the most common specialties, regardless of gender. Students’ career decisions are influenced by several factors. Future research that can help create a more accurate career-counseling model and improve successful career-counseling strategies will need to address these factors.
Evolution of Evidence-Based Medicine in Stroke
Authors: Hankey Graeme J.
Published: July 2021

The introduction and evolution of evidence-based stroke medicine has realized major advances in our knowledge about stroke, methods of medical research, and patient outcomes that continue to complement traditional individual patient care. It is humbling to recall the state of knowledge and scientific endeavour of our forebears who were unaware of what we know now and yet pursued the highest standards for evaluating and delivering effective stroke care. The science of stroke medicine has evolved from pathophysiological theory to empirical testing. Progress has been steady, despite inevitable disappointments and cul-de-sacs, and has occasionally been punctuated by sensational breakthroughs, such as the advent of reperfusion therapies guided by imaging.
Hardware implementation and performance evaluation of microcontroller-based 7-level inverter using POD-SPWM technique
Authors: Chadli Hajar , Chadli Sara , Boutouba Mohamed , Saber Mohammed , Tahani Abdelwahed
Published: July 2021

Renewable energy sources are considered as inexhaustible sources for the very long-term, as they come from natural processes that are constantly replenished. However, there are a number of challenges facing renewable energy technology adoption, like the grid connecting problems. One of the main challenges relates to the grid connecting problem is the power quality issues for power converter, such as harmonics, voltage stability, and frequency fluctuation. Hence, the inverter remains the first element to be built because of its undeniable advantages in alternative continuous conversion. However, it has some disadvantages such as high component count and complex control method. This paper presents the design and implementation of a new 7-level inverter architecture with only six switches. This architecture requires fewer components compared to other 7-level inverter topologies therefore, the overall cost, control technique complexity, and conduction losses are highly reduced. A digital phase opposition disposition sinusoidal pulse width modulation (POD-SPWM) strategy using the Arduino is adopted to improve the performance of the proposed multilevel inverter (MLI) which leads to further reduction in total harmonic sistortion (THD). In this paper, the proposed inverter is tested using Proteus software and Matlab Simulink. Finally, a laboratory setup of the proposed inverter was built to validate its workability by the experimental results.
Future smart grid communication-deployment of IoT: opportunities and challenges
Authors: Soni Payal , Subhashini J.
Published: July 2021

India’s electrical power system grid also known as the power grid is serving us from a very long time. In this duration, there were no major developments or changes reported in the power grid system. Electrical power consumer demand is increasing drastically and the present grid system is not able to fulfil these emerging requirements. To fulfil the requirements of future power load, we need a modified system which has to be reliable, secure, intelligent and efficient. By converting the power grid into the smart grid will be a promising solution for adopting the above properties. Communication Infrastructure is a major part of the smart grid. The end-user can reduce their expenditure on electricity demand by using smart home appliance, to keep away from the rush hours and also make use of the renewable energy instead from utility, is a great example of deployment of internet of things (IoT) in grid communication. In this paper, we have provided a survey of different communication technology, applications, benefits and challenges in communication infrastructure, spatially IoT.
Towards using UAV for improving 5G cellular communication systems
Authors: Sayed Kotb Mohamed El , Anis Wagdy R. , Abd-Elhafez Ahmed A.
Published: July 2021

Unmanned aerial vehicles (UAVs) have sparked a lot of interest in the wireless networking community as an emerging subject in aerial robotics. The UAV environment can be used to improve UAV communications in various ways. These smart devices cater for a broad variety of wireless technologies and applications because of UAV's inherent features related to versatile mobility in 3D space, autonomous operations as well as intelligent positioning. This study will investigate the convergence synergies between 5G/B5G mobile systems and UAV technologies, with the UAV being integrated into current cellular networks as a modern aerial user equipment (UE). In this integration, UAVs play the function of cellular flying customers, and are hence referred to as cellularly linked UAVs (a.k.a. UAVUE, drone-UE, 5G-connected drone, or aerial user). The major goal of this research is to provide a thorough analysis of the integration task, as well as major technical breakthroughs from 5G/B5G and current work in prototyping architecture and field trials that support cell-based UAVs. This study examines recent 3GPP standards advances as well as socio-economic challenges that must be addressed before this promising technology can be properly implemented. There are already some accessible issues clearing the way for potential study opportunities.
An improvement to hybrid beamforming precoding scheme for mmWave massive MIMO systems based on channel matrix
Authors: Amirifar Zahra , Abouei Jamshid
Published: July 2021

The massive multiple-input multiple-output (MIMO) technology has been applied innew generation wireless systems due to growing demand for reliability and high datarate. Hybrid beamforming architectures in both receiver and transmitter, includinganalog and digital precoders, play a significant role in 5G communication networksand have recently attracted a lot of attention. In this paper, we propose a simple andeffective beamforming precoder approach for mmWave massive MIMO systems. Wefirst solve an optimization problem by a simplification subject, and in the second step,we use the covariance channel matrixfCk=Cov(Hk)andBk=HkHHkinstead of chan-nel matrixHk. Simulation results verify that the proposed scheme can enjoy a highersum rate and energy efficiency than previous methods such as spatially sparse method,analog method, and conventional hybrid method even with inaccurate Channel StateInformation (CSI). Percentage difference of the achievable rate ofCk=Cov(Hk)andBk=HkHHkschemes compared to conventional methods are 2.51% and 48.94%, re-spectively.