bluuebunny/crossref_metadata_2025 huggingface dataset:
Efficiency of acid digestion procedures for geochemical analysis of tungsten mining wastes
Authors: Han Zhengdong , Edraki Mansour , Nguyen Ai Duc , Mostert Marietjie
Published: June 2021

There is an increasing global demand for tungsten, which is a critical element used in various industries. There are millions of tons of current and legacy mineral processing tungsten tailings worldwide that can potentially contaminate the environment and pose human health risks. These tailings could also become valuable resources if we thoroughly characterize their geochemical composition. In this study, an innovative method was developed to achieve the complete digestion of tungsten tailings. We tested three different digestion methods (hotplate digestion, bomb digestion and ColdBlock
TM
digestion) and compared the results. Additionally, an alkali fusion for major element analysis was applied and tested. The results showed that alkali fusion is the best method for major element analysis, while bomb digestion is best for tungsten and trace element analysis, although volatile chlorite loss was also observed. The hot plate digestion method was not recommended, owing to poor recovery of trace elements compared to the bomb digestion method. The quicker and safer ColdBlock
TM
digestion method can be used for bismuth, molybdenum, and several rare-earth element analyses, as indicated by their recovery being close to that from the bomb digestion method.
Regulation of Bacterial Ribonucleases
Authors: Deutscher Murray P.
Published: June 2021

Ribonucleases (RNases) are essential for almost every aspect of RNA metabolism. However, despite their important metabolic roles, RNases can also be destructive enzymes. As a consequence, cells must carefully regulate the amount, the activity, and the localization of RNases to avoid the inappropriate degradation of essential RNA molecules. In addition, bacterial cells often must adjust RNase levels as environmental situations demand, also requiring careful regulation of these critical enzymes. As the need for strict control of RNases has become more evident, multiple mechanisms for this regulation have been identified and studied, and these are described in this review. The major conclusion that emerges is that no common regulatory mechanism applies to all RNases, or even to a family of RNases; rather, a wide variety of processes have evolved that act on these enzymes, and in some cases, multiple regulatory mechanisms can even act on a single RNase.
Use of statistical methods for the interpretation of measurement results of Peruvian wines with MOS E-noses
Authors: Paredes-Doig Ana Lucía , Doig-Camino Elizabeth , Sun-Kou Rosario , Picasso Gino , La Rosa-Toro Adolfo
Published: June 2021

With the sensors made in the laboratory, two electronic noses were built. One of them, of platinum doped tin oxides and the other of palladium. The sensing of the wines was monitored with the LabVIEW software and the statistical methods were applied with the XLSTAT software. It was observed that for the nose of platinum sensor a difference in the groups of commercial and unknown wines was shown. This difference is attributed to the brand or origin of the wines. While the nose of palladium sensors allowed to distinguish the strains because it locked the Borgoña wines in a different conglomerate. This could be observed with the PCA, cluster and Factorial methods, complementing the three methods the statistical information.
Mirtazapine reduces susceptibility to hypocapnic central sleep apnea in males with sleep-disordered breathing: a pilot study
Authors: Prowting Joel , Maresh Scott , Vaughan Sarah , Kruppe Elizabeth , Alsabri Bander , Badr M. Safwan , Sankari Abdulghani
Published: June 2021

To our knowledge, this research study is novel as it is the first study in humans assessing the effect of mirtazapine on CO2 reserve and chemosensitivity in individuals with severe sleep-disordered breathing. This is also the first study to determine the potential therapeutic effects of mirtazapine on sleep parameters in individuals with a spinal cord injury.
Influence of wide-pulse neuromuscular electrical stimulation frequency and superimposed tendon vibration on occurrence and magnitude of extra torque
Authors: Espeit Loïc , Rozand Vianney , Millet Guillaume Y. , Gondin Julien , Maffiuletti Nicola A. , Lapole Thomas
Published: June 2021

This study is the first to assess the effect of stimulation frequency and superimposed tendon vibration on extra torque characteristics generated by wide-pulse neuromuscular electrical stimulation. The percentage of subjects showing extra torque (i.e., considered as responders) was similar for low-frequency and high-frequency wide-pulse neuromuscular electrical stimulation. In the responders, the extra torque was greater for high-frequency than for low-frequency wide-pulse neuromuscular electrical stimulation. The superimposition of tendon vibration had no effect on extra torque occurrence or magnitude.
Rapid Maxillary Expansion and Nocturnal Enuresis in Children and Adolescents: A Systematic Review of Controlled Clinical Trials
Authors: Khalaf Khaled , Mansour Dina , Sawalha Zain , Habrawi Sima
Published: June 2021

Objectives. To evaluate the effectiveness of rapid palatal expansion in the treatment of nocturnal enuresis among 6–18-year-old children and adolescents. Methods. Comprehensive searches were carried out in 6 electronic databases (EBSCO, ProQuest, Clinical Key, Science Direct, SCOPUS, and OVID) and supplemented by additional manual searches in 4 orthodontic journals until June 2020. Randomized controlled clinical trials (RCTs) and controlled clinical trials (CCTs) of children and adolescents aged 6–18 years old of both genders who underwent rapid palatal expansion and were considered unresponsive to previous conventional nocturnal enuresis treatment were included in this review. Risk of bias of individual trials was assessed using the Risk of Bias in Non-randomized Studies of Interventions (ROBINS-I) assessment tool for CCTs and the revised Cochrane Risk-of-Bias tool for RCTs (RoB 2). Results. Four studies met all inclusion criteria and were finally included in this systematic review, of which one was an RCT and three were CCTs. Reduction in nocturnal enuresis frequency was reported in all included studies with varying rates and methods of reporting, but most studies reported a statistically significant reduction in the number of wet nights per week. The average range of becoming completely dry 1 year after treatment with an RME was 0%–60%. Also, there was a statistically significant correlation between an improvement in bedwetting and an increase in nasal volume after the use of RME. Conclusion. A rapid palatal expansion device may be considered as an alternative treatment option of the nocturnal enuresis condition with guarded prognosis when other treatment modalities have failed.
Data Clustering Improves Siamese Neural Networks Classification of Parkinson’s Disease
Authors: Shalaby Mohamed , Belal Nahla A. , Omar Yasser
Published: June 2021

Parkinson’s disease (PD) is a clinical neurodegenerative disease having symptoms like tremor, rigidity, and postural disability. According to Harvard, about 60,000 of American citizens are diagnosed with PD yearly, with more than 10 million people infected worldwide. An estimate of 4% of the people have PD before they reach the age 50; however, the incident increases with age. Diagnosis of PD relies on the expertise of the physician and depends on several established clinical criteria. This makes the diagnosis subjective and inefficient. Hence, continuous efforts are being made to enhance the diagnosis of PD using deep learning approaches that rely on experienced neurologists. Siamese neural networks mainly work on two different input vectors and are used in comparison of output vectors. Moreover, clustering a dataset before applying classification enhances the distribution of similar samples among groups. In addition, applying the Siamese network can overcome the limitation of samples per class in the dataset by guiding the network to learn differences between samples rather than focusing on learning specific classes. In this paper, a Siamese neural network is applied to diagnose PD. Siamese networks predict the sample class by estimating how similar a sample is to other samples. The idea behind this work is clustering the dataset before training the network, as different pairs that belong to the same cluster are candidates to be mistaken by the network and assumed to be matched pairs. To overcome this problem, the dataset is first clustered, and then the architecture feeds the network to pairs of the same cluster. The proposed framework is concerned with comparing the performance when using clustered against unclustered data. The proposed framework outperforms the conventional framework without clustering. The accuracy achieved for classifying unclustered PD patients reached 76.75%, while it reached 84.02% for clustered data, outperforming the same technique on unclustered data. The significance of this study is in the enhanced performance achieved due to the clustering of data, which shows a promising framework to enhance the diagnostic capability of computer‐aided disease diagnostic tools.
Artificial Intelligence and Neural Network-Based Shooting Accuracy Prediction Analysis in Basketball
Authors: Li Hongfei , Zhang Maolin
Published: June 2021

In order to improve the accuracy of shooting in basketball. A shooting accuracy prediction method based on the convergent improved resource allocating network (CIRAN) online radial basis function neural network (RBFNN) is proposed, and the RBFNN learning algorithm is improved. Through the collection of shooting motion images, feature point extraction, and edge contour feature extraction, the shooting motion trajectory is obtained. Using the online neural network based on the CIRAN learning algorithm to predict the accuracy of shooting, this method analyzes the radial basis function (RBF) network. Based on the RBF analysis, the number of network layers and the number of hidden layer neurons are adjusted and optimized. In order to improve the prediction accuracy of shooting in basketball, a method based on. Through the analysis, it can be known that the accuracy of both the traditional RBFNN and the CIRAN-based online neural network for the prediction of shooting accuracy is above 70%. The prediction accuracy of the online neural network for shooting is higher than that of the traditional one. This is mainly because the online update function of the learning algorithm can better adjust the corresponding structure with the development of the game and has a better generalization ability. In addition, because the CIRAN learning algorithm introduces the hidden layer neuron deletion strategy, its network structure is simpler than that of the traditional one, the number of hidden layer neurons is less, and the running time required is less, which can better meet the real-time requirements and provide a more scientific method for basketball training.
Metabolite Characteristics in Tongue Coating from Damp Phlegm Pattern in Patients with Gastric Precancerous Lesion
Authors: Xu Yifeng , Zhang Renling , Morris Robert , Cheng Feng , Wang Yiqin , Zhu Zhujing , Hao Yiming
Published: June 2021

Objective. In this study, we analyzed the metabolite profile of the tongue coating of patients having gastric precancerous lesion (GPL) with damp phlegm pattern and proposed a mechanism of pathological transition. Methods. The changes in tongue-coating metabolites in patients with GPL damp phlegm pattern were analyzed using GC-TOF-MS and UHPLC-QE-MS metabolomics methods. Results. When compared with 20 patients who did not exhibit a nondamp phlegm pattern, 12 metabolites were highly expressed and 10 metabolites were under expressed in 40 cases of damp phlegm pattern, of which involved 9 metabolic pathways. Compared with 15 healthy people, 134 metabolites were upregulated and 3 metabolites were downregulated in 40 cases exhibiting a damp phlegm pattern, of which involved 17 metabolic pathways. The patients with damp phlegm pattern were compared with nondamp phlegm pattern patients and healthy people, the main differential metabolites were primarily lipids and lipid-like molecules, and the main differential metabolic pathways were related to glycerophospholipid metabolism. In the glycerophospholipid metabolism, the metabolites with changes were phosphatidylethanolamine and lysoPC(18 : 1 (9z)). Among them, phosphatidylethanolamine exists in the synthesis stage of glycerophospholipid metabolism.Conclusions. Abnormal expression of lipids and lipid-like molecules, as the major metabolic change, was involved in the formation of GPL patients with damp phlegm pattern.
Histopathological and Biochemical Assessment of Neuroprotective Effects of Sodium Valproate and Lutein on the Pilocarpine Albino Rat Model of Epilepsy
Authors: Al-Rafiah Aziza Rashed , Mehdar Khlood Mohammed
Published: June 2021

Epilepsy is one of the most frequent neurological disorders characterized by an enduring predisposition to generate epileptic seizures. Oxidative stress is believed to directly participate in the pathways of neurodegenerations leading to epilepsy. Approximately, one-third of the epileptic patients who suffer from seizures do not receive effective medical treatment. Sodium valproate (SVP) is a commonly used antiepileptic drug (AED); however, it has toxic effects. Lutein (L), a carotenoid, has potent antioxidant and anti-inflammatory properties. The aim of this study was to determine the neuroprotective effect of sodium valproate (SVP) and lutein (L) in a rat model of pilocarpine- (PLC-) induced epilepsy. To achieve this aim, fifty rats were randomly divided into five groups. Group I: control, group II: received PLC (400 mg/kg intraperitoneally), group III: received PLC + SVP (500 mg/kg orally), group IV: received PLC + SVP + L (100 mg/kg orally), and group V: received (PLC + L). Racine Scale (RC) and latency period to onset seizure were calculated. After eight weeks, the hippocampus rotarod performance and histological investigations were performed. Oxidative stress was investigated in hippocampal homogenates. Results revealed that SVP and L, given alone or in combination, reduced the RC significantly, a significant delay in latency to PLC-kindling onset, and improved rotarod performance of rats compared with the PLC group. Moreover, L was associated with a reduction of oxidative stress in hippocampal homogenate, a significant decrease in serum tumor necrosis factor-alpha (TNF-α) level, and inhibition of cerebral injury and displayed antiepileptic properties in the PLC-induced epileptic rat model. Data obtained from the current research elucidated the prominent neuroprotective, antioxidant, and anti-inflammatory activities of lutein in this model. In conclusion, lutein cotreatment with AEDs is likely to be a promising strategy to improve treatment efficacy in patients suffering from epilepsy.
The Antibacterial and Antioxidant Roles of Buckwheat Honey (BH) in Liquid Preservation of Boar Semen
Authors: Lan Qun , Xie Yingyu , Pan Jiahua , Chen Qiaohui , Xiao Tianfang , Fang Shaoming
Published: June 2021

In the present study, we hypothesized that buckwheat honey (BH) should be regarded as a potential alternative to antibacterial and antioxidant agent in liquid storage of boar semen. To this end, boar semen was firstly studied for in vitro dose tolerability to BH by measuring sperm progressive motility. The optimum progressive motility of boar spermatozoa was observed in extender with 0.5% and 0.6% BH addition. Afterward, sperm quality parameters, bacterial profile and composition, total antioxidant (T‐AOC), catalase (CAT), superoxide dismutase (SOD), and malondialdehyde (MDA) levels of control, BH supplementation, antibiotics supplementation, and incorporated supplementation were compared during liquid storage period, to further investigate antibacterial and antioxidant properties of BH. The results showed that BH supplementation significantly improved sperm motility, acrosome integrity, plasma membrane integrity, inhibited opportunistic bacterial growth, and altered microbial compositions at the end of preservation. Additionally, T‐AOC, SOD, and CAT levels were significantly higher in the BH supplementation group than those in the control and antibiotic supplementation group, whereas MDA level exhibited opposite change pattern. Importantly, BH addition to the extender was able to exert a synergistic effect in combination of antibiotic use. Our findings suggested that the appropriate concentrations (0.5% and 0.6%) of BH were added to the extender could act antibacterial and antioxidant roles in liquid preservation of boar semen.
Phenological Differences, Genetic Diversity, and Population Structure of Genotypes Obtained from Seeds of Kaman-1 Walnut Cultivar
Authors: Sütyemez Mehmet , Bükücü Şakir Burak , Keleş Özlem , Özcan Akide , Yıldırım Esra , Boyacı Selma
Published: June 2021

Walnut (Juglans regia L.) is a diploid (2n = 32), deciduous, monoecious, and generally open-pollinated tree with nuts of high nutrient content. In this study, the phenological differences, genetic diversity, and population structure of Kaman-1 and its 79 progenies obtained by open pollination were characterized by ISSR primers and some important phenological traits. As a result of the phenological observations, it was determined that the progenies differ significantly from Kaman-1. Besides, using ISSR primers, walnut genotypes were found to have genetic similarities ranging from 0.52 to 0.99. UPGMA cluster analysis showed that accessions from 2 different groups were classified, and population structure analysis confirmed this finding. Based on the results, a significant variation both phenologically and genetically was found within the walnut accessions. Also, this study confirmed that the progenies obtained from the Kaman-1 walnut cultivar have a quite wide variation and that ISSR primers and phenological traits are an important tool in determining genetic diversity.
Predicting Poor Outcome of COVID-19 Patients on the Day of Admission with the COVID-19 Score
Authors: Tseng Luke , Hittesdorf Erin , Berman Mitchell F. , Jordan Desmond A. , Yoh Nina , Elisman Katerina , Eiseman Katherine A. , Miao Yuqi , Wang Shuang , Wagener Gebhard
Published: June 2021

Background. COVID-19 may result in multiorgan failure and death. Early detection of patients at risk may allow triage and more intense monitoring. The aim of this study was to develop a simple, objective admission score, based on laboratory tests, that identifies patients who are likely going to deteriorate. Methods. This is a retrospective cohort study of all COVID-19 patients admitted to a tertiary academic medical center in New York City during the COVID-19 crisis in spring 2020. The primary combined endpoint included intubation, stage 3 acute kidney injury (AKI), or death. Laboratory tests available on admission in at least 70% of patients (and age) were included for univariate analysis. Tests that were statistically or clinically significant were then included in a multivariate binary logistic regression model using stepwise exclusion. 70% of all patients were used to train the model, and 30% were used as an internal validation cohort. The aim of this study was to develop and validate a model for COVID-19 severity based on biomarkers. Results. Out of 2545 patients, 833 (32.7%) experienced the primary endpoint. 53 laboratory tests were analyzed, and of these, 47 tests (and age) were significantly different between patients with and without the endpoint. The final multivariate model included age, albumin, creatinine, C-reactive protein, and lactate dehydrogenase. The area under the ROC curve was 0.850 (CI [95%]: 0.813, 0.889), with a sensitivity of 0.800 and specificity of 0.761. The probability of experiencing the primary endpoint can be calculated as

p
=

e

−
2.4475
+
0.02492
age
−
0.6503
albumin
+
0.81926
creat
+
0.00388
CRP
+
0.00143
LDH

/

1
+

e

−
2.4475
+
 
0.02492
age
−
0.6503
albumin
+
0.81926
creat
+
0.00388
CRP
+
0.00143
LDH

. Conclusions. Our study demonstrated that poor outcome in COVID-19 patients can be predicted with good sensitivity and specificity using a few laboratory tests. This is useful for identifying patients at risk during admission.
Research on Evaluation and Improvement Policy of Higher Education Development Based on TOPSIS‐Synthetic Control Method
Authors: Zhang Huan-Ming , Ma Rui-Qi , Deng Meng-Xiang , Liu Xian-Bei
Published: June 2021

This article aims at the evaluation and improvement of the development of higher education. First of all, according to the theory and hypothesis, the comprehensive evaluation index system of higher education development level is established. The TOPSIS and the combination weighting method based on goal programming are used to measure the scores of higher education development levels of 19 major countries in the world in the recent 20 years, and the horizontal and vertical comparative analysis is carried out. Then, according to the practical feasibility, Turkey is selected as the target country to propose a higher education development and improvement policy by 2030, and the causal effect of our proposed policy is estimated using the synthetic control method. This study can provide a reference for other countries in the world to improve their higher education level.
Interleukin 10 Plays an Important Role in Neonatal Rats with Hypoxic-Ischemia Associated with B-Cell Lymphoma 2 and Endoplasmic Reticulum Protein 29
Authors: Bai Xue , Xiong Liu-Lin , Fang Chang-Le , Zhou Hao-Li , Xue Lu-Lu , Hu Yue , Xia Qing-Jie , Liu Jia , Zhang Jun-Yan , Wang Ting-Hua , Yang Si-Jin
Published: June 2021

Interleukin 10 (IL-10) is a synthetic inhibitor of human cytokines with immunomodulatory and anti-inflammatory effects. This study was designed to investigate the expression variation of IL-10 in the multiple sites including cortex, hippocampus, and lung tissues of neonatal hypoxic-ischemic (HI) rats and explore the crucial role of IL-10 in alleviating HI brain damage. In this study, neonatal Sprague-Dawley rats were subjected to the right common carotid artery ligation, followed by 2 h of hypoxia. The expression of IL-10 in the cortex, hippocampus, and lung tissues was measured with immunohistochemistry, real-time quantitative polymerase chain reaction (RT-qPCR), and western blot (WB). Immunofluorescence double staining was performed to observe the localization of IL-10 in neurons and astrocytes. Moreover, not-targeting and targeting IL-10 siRNA lentivirus vectors were injected into the rats of the negative control (NC) and IL-10 group, respectively, and the mRNA levels of B-cell lymphoma 2 (Bcl-2) and endoplasmic reticulum protein 29 (ERp29) were detected by RT-qPCR following IL-10 silence. The results demonstrated that the IL-10 expression was markedly increased after HI and IL-10 were colocalized with neurons and astrocytes which were badly injured by HI insult. In addition, Bcl-2 and ERp29 were remarkably decreased following IL-10 mRNA interference compared with the NC group. Our findings revealed that IL-10 exerted its antiapoptotic and neuroprotective effects by regulating the expression of Bcl-2 and ERp29, indicating that IL-10 may be a promising molecule target for HIE treatment.
Conformal Super-Biderivations on Lie Conformal Superalgebras
Authors: Huang Zhongxian
Published: June 2021

In this paper, the conformal super-biderivations of two classes of Lie conformal superalgebras are studied. By proving some general results on conformal super-biderivations, we determine the conformal super-biderivations of the loop super-Virasoro Lie conformal superalgebra and Neveu–Schwarz Lie conformal superalgebra. Especially, any conformal super-biderivation of the Neveu–Schwarz Lie conformal superalgebra is inner.
One-Shot M-Array Pattern Based on Coded Structured Light for Three-Dimensional Object Reconstruction
Authors: Jia Xiaojun , Liu Zihao
Published: June 2021

Pattern encoding and decoding are two challenging problems in a three-dimensional (3D) reconstruction system using coded structured light (CSL). In this paper, a one-shot pattern is designed as an M-array with eight embedded geometric shapes, in which each 2 × 2 subwindow appears only once. A robust pattern decoding method for reconstructing objects from a one-shot pattern is then proposed. The decoding approach relies on the robust pattern element tracking algorithm (PETA) and generic features of pattern elements to segment and cluster the projected structured light pattern from a single captured image. A deep convolution neural network (DCNN) and chain sequence features are used to accurately classify pattern elements and key points (KPs), respectively. Meanwhile, a training dataset is established, which contains many pattern elements with various blur levels and distortions. Experimental results show that the proposed approach can be used to reconstruct 3D objects.
Research on Diagnostic Information of Smart Medical Care Based on Big Data
Authors: Xu Zhihai , Shi Donglin , Tu Zhiwei
Published: June 2021

The medical field has gradually become intelligent, and information and the research of intelligent medical diagnosis information have received extensive attention in the medical field. In response to this situation, this paper proposes a Hadoop-based medical big data processing system. The system first realized the ETL module based on Sqoop and the transmission function of unstructured data and then realized the distributed storage management function based on HDFS. Finally, a MapReduce algorithm with variable key values is proposed in the data statistical analysis module. Through simulation experiments on the system modules and each algorithm, the results show that because the traditional nondistributed big data acquisition module transmits the same scale of data, it consumes more than 3200 s and the transmission time exceeds 3000 s. The time consumption of smart medical care under the 6G protocol is 150 s, the transmission time is 146 s, and the time is reduced to 1/10 of the original. The research of intelligent medical diagnosis information based on big data has good rationality and feasibility.
Modeling Clinical Responses to Targeted Therapies by Patient-Derived Organoids of Advanced Lung Adenocarcinoma
Authors: Kim Seok-Young , Kim Sang-Min , Lim Sumin , Lee Ji Yeon , Choi Su-Jin , Yang San-Duk , Yun Mi Ran , Kim Chang Gon , Gu Seo Rin , Park Chaewon , Park A-Young , Lim Sun Min , Heo Seong Gu , Kim HyunKi , Cho Byoung Chul
Published: June 2021

Purpose:

Patient-derived organoids (PDO) of lung cancer has been recently introduced, reflecting the genomic landscape of lung cancer. However, clinical relevance of advanced lung adenocarcinoma organoids remains unknown. Here, we examined the ability of PDOs to predict clinical responses to targeted therapies in individual patients and to identify effective anticancer therapies for novel molecular targets.

Experimental Design:

Eighty-four organoids were established from patients with advanced lung adenocarcinoma. Formalin-fixed, paraffin-embedded tumor specimens from corresponding patients were analyzed by whole-exome sequencing (n = 12). Organoids were analyzed by whole-exome sequencing (n = 61) and RNA sequencing (n = 55). Responses to mono or combination targeted therapies were examined in organoids and organoid-derived xenografts.

Results:

PDOs largely retained somatic alterations including driver mutations of matching patient tumors. PDOs were able to recapitulate progression-free survival and objective responses of patients with non–small cell lung cancer receiving clinically approved tyrosine kinase inhibitors. PDOs recapitulated activity of therapeutic strategies under clinical investigation. YUO-071 harboring an EGFR exon 19 deletion and a BRAF G464A mutation and the matching patient responded to dabrafenib/trametinib combination therapy. YUO-004 and YUO-050 harboring an EGFR L747P mutation was sensitive to afatinib, consistent with the response in the matching patient of YUO-050. Furthermore, we utilized organoids to identify effective therapies for novel molecular targets by demonstrating the efficacy of poziotinib against ERBB2 exon 20 insertions and pralsetinib against RET fusions.

Conclusions:

We demonstrated translational relevance of PDOs in advanced lung adenocarcinoma. PDOs are an important diagnostic tool, which can assist clinical decision making and accelerate development of therapeutic strategies.
Pioglitazone Enhances β-Arrestin2 Signaling and Ameliorates Insulin Resistance in Classical Insulin Target Tissues
Authors: El-Fayoumi Shaimaa , Mansour Rehab , Mahmoud Amr , Fahmy Ahmed , Ibrahim Islam
Published: June 2021

Introduction: Pioglitazone is a thiazolidinedione oral antidiabetic agent. This study aimed to investigate the effects of pioglitazone as insulin sensitizer on β-arrestin2 signaling in classical insulin target tissues. Methods: Experiments involved three groups of mice; the first one involved mice fed standard chow diet for 16 weeks; the second one involved mice fed high-fructose, high-fat diet (HFrHFD) for 16 weeks; and the third one involved mice fed HFrHFD for 16 weeks and received pioglitazone (30 mg/kg/day, orally) in the last four weeks of feeding HFrHFD. Results: The results showed significant improvement in the insulin sensitivity of pioglitazone-treated mice as manifested by significant reduction in the insulin resistance index. This improvement in insulin sensitivity was associated with significant increases in the β-arrestin2 levels in the adipose tissue, liver, and skeletal muscle. Moreover, pioglitazone significantly increased β-arrestin2 signaling in all the examined tissues as estimated from significant increases in phosphatidylinositol 4,5 bisphosphate and phosphorylation of Akt at serine 473 and significant decrease in diacylglycerol level. Conclusion: To the best of our knowledge, our work reports a new mechanism of action for pioglitazone through which it can enhance the insulin sensitivity. Pioglitazone increases β-arrestin2 signaling in the adipose tissue, liver, and skeletal muscle of HFrHFD-fed mice.
Hair Follicle Melanogenesis Reflected in Hair Pigmentation as a Developmental Factor in Alopecia Areata
Authors: Juhasz Margit , Conic Rosalynn R.Z. , Atanaskova Mesinkovska Natasha
Published: June 2021

The mechanism of alopecia areata (AA) is not well-elucidated, and hair follicle melanogenesis pathways are implicated as possible sources for autoantigens. After a retrospective medical record review at a single tertiary medical center, the hair color of 112 AA patients were identified and compared to a control group of 104 androgenetic alopecia patients. There were no statistically significant differences in the natural hair color prevalence between the 2 groups (p = 0.164), and hair color was not a predictor of the alopecia type. Our results suggest hair pigmentation, determined by the eumelanin-to-pheomelanin ratio, is not a positive risk factor for AA development. We hope that our study will encourage multiple large-scale, collaborative, retrospective medical reviews to determine if our results are reproducible in diverse patient populations.
A comparative study of deep learning based language representation learning models
Authors: Boukabous Mohammed , Azizi Mostafa
Published: June 2021

Deep learning (DL) approaches use various processing layers to learn hierarchical representations of data. Recently, many methods and designs of natural language processing (NLP) models have shown significant development, especially in text mining and analysis. For learning vector-space representations of text, there are famous models like Word2vec, GloVe, and fastText. In fact, NLP took a big step forward when BERT and recently GTP-3 came out. In this paper, we highlight the most important language representation learning models in NLP and provide an insight of their evolution. We also summarize, compare and contrast these different models on sentiment analysis, and thus discuss their main strengths and limitations. Our obtained results show that BERT is the best language representation learning model.
ArSL-CNN a convolutional neural network for Arabic sign language gesture recognition
Authors: Alani Ali A. , Cosma Georgina
Published: June 2021

Sign language (SL) is a visual language means of communication for people who are Deaf or have hearing impairments. In Arabic-speaking countries, there are many Arabic sign languages (ArSL) and these use the same alphabets. This study proposes ArSL-CNN, a deep learning model that is based on a convolutional neural network (CNN) for translating Arabic SL (ArSL). Experiments were performed using a large ArSL dataset (ArSL2018) that contains 54049 images of 32 sign language gestures, collected from forty participants. The results of the first experiments with the ArSL-CNN model returned a train and test accuracy of 98.80% and 96.59%, respectively. The results also revealed the impact of imbalanced data on model accuracy. For the second set of experiments, various re-sampling methods were applied to the dataset. Results revealed that applying the synthetic minority oversampling technique (SMOTE) improved the overall test accuracy from 96.59% to 97.29%, yielding a statistically signicant improvement in test accuracy (p=0.016,  α<0=05). The proposed ArSL-CNN model can be trained on a variety of Arabic sign languages and reduce the communication barriers encountered by Deaf communities in Arabic-speaking countries.
Algorithm for extracting product feature from e-commerce comment
Authors: Kaewphet Chanida , Wisitpongpun Nawaporn
Published: June 2021

Reviews of e-commerce play an important role in online purchasing decisions. Consumers are likely to read reviews and comments on products from other consumers. In addition to those opinions that reflect consumers' trust in products, it also provides each product's distinctive properties. Today, there are many online reviews, resulting in enormous comments and suggestions. However, as fully reading reviews is quite difficult, this article presents 3 algorithms for automatic extraction of product features hidden in e-commerce reviews: a traditional frequency-based product feature extraction (F-PFE), syntax analyzer system (SAS), and the hybrid approach called the frequency and syntax-based product feature extraction (FaS-PFE). The proposed algorithms were tested against 4 different types of products: shampoo, skincare, mobile phone, and tablet, using reviews from amazon.com. Based on the product review used in this study, it was found that the SAS can help improve the performance in terms of precision by 15% when compared with the traditional F-PEE approach. When considering both the word frequency and syntax, FaS-PFE clearly outperforms the other two approaches with 94.00% precision and 95.13% recall.
On active anti-islanding techniques: survey
Authors: Elshrief Yasser Ahmed , Abd-Elhaleem Sameh , Abo Zalam Belal , D. Asham Amin
Published: June 2021

The phenomenon of feeding loads from any distributed generators (DGs) with a total disconnection of utility grid at the point of common coupling is called Islanding. The DGs are usually independently controlled. Hence, when the islanding problem occurs, the electric utility loses the control and supervision over that section of the power grid. Furthermore, prolonged islanding can prevent reconnection to the power grid and may cause damage due to voltage and frequency excursions. Therefore, the islanding detection, which is also called anti-islanding (AI), is one of the most critical aspects of the integration of DG sources into the power grid. In this paper, a comprehensive survey on the local AI techniques is illustrated, especially active type which is used for improving the performance regarding the size of the non-detection zone and detection speed. Extensive comparisons are provided to demonstrate the effectiveness of each technique.
A smart wearable device based on internet of things for the safety of children in online transportation
Authors: Tunggadewi Elsyea Adia , Agustin Eva Inaiyah , Yunardi Riky Tri
Published: June 2021

The world needs to pay attention to children who often become victims of violence and cannot escape social problems. Various safety devices that are commonly known as smart wearable devices have been created, but they still have many shortcomings. Thus, in this research a safety device that can be held by children is designed and is equipped with a button that can be pressed, then it will automatically send the location and photo of the scene to the parent's cellphone via the telegram application. It uses the Raspberry Pi Zero W controller, the GNSS HMC5983 SAW LNA GPS Module to determine the location, and the 5MP Raspberry Pi Zero Camera Module to capture the incident. Based on the results, the average time needed to share locations is 0.91 seconds, and the average time needed to capture is 11.57 seconds, if the device and receiving cellphone use the same network. Additionally, the average time needed to share locations is 0.96 seconds, and the average time needed to capture is 12.09 seconds, if the device and receiving cellphone use a different network. Both conditions have 97.5% location accuracy rate and 100% photo accuracy rate.
Design of gas concentration measurement and monitoring system for biogas power plant
Authors: Iswanto Iswanto , Ma’arif Alfian , Kebenaran Bilah , Megantoro Prisma
Published: June 2021

Biogas is a gas obtained from the breakdown of organic matter (such as animal waste, human waste, and plants) by methanogenic bacteria in an oxygen-free (anaerobic) state. The biogas produced mainly consists of 50-70% methane, 30-40% carbon dioxide, and other gases in small amounts. The gas produced has a different composition depending on the type of animal that produces it. It is challenging to obtain biogas concentration data because the monitoring equipment is currently minimal. Therefore, this research discusses how to make a monitoring system for biogas reactors. Sensors are installed in the digester tank and storage tank. The installed sensors are the MQ-4 sensor to detect methane gas (CH4), MG-811 sensor to detect carbon dioxide (CO2) gas, MQ-136 sensor to detect sulfide acid gas (H2S), and Thermocouple Type-K to detect temperature. The sensor will send a signal to the control unit in Arduino Mega 2560, then processed and displayed on the liquid crystal display (LCD). The sensor calculation results' accuracy is not much different from the reference based on the sensor readings. The sensor deviation standard is below 5.0, indicating that the sensor is in precision. The sensor's linearity of MQ-4 is 0.7%, the MG-811 is 0.17%, the MQ-136 is 0.29%, and the Type-K Thermocouple is 1.19%. The installed sensor can be used to monitor gas concentration and temperature in a biogas reactor.
Development of an IoT-based water and power monitoring system for residential building
Authors: Santos Leah , Bautista John Carlo , Estanque Matt William , Paloa Christian John , Villaran Ana Beatrice
Published: June 2021

This study provides information between tenants and landlords on the use of the Internet of Things for power and water monitoring systems. It is one way to make reading meters and water meters easier to access using the available internet connection. The developed application using the android studio software is installed on a smartphone/tablet and verified to fully working on android versions from 4.1 (jellybean) to android 9.0 (pie). Tests were carried out in a household where the prototype was installed in a residential apartment. The data collected was monitored in the application and viewed by tenants and landlords. The results from the mean comparison of the power and volume readings measured by the wattmeter and water meter claim that the readings from the conventional meters and designed prototype have no significant difference using the Mann-Whitney U test. Evaluations were conducted showing that the device and the developed application using IoT is reliable, accurate, functional and user-friendly to use by tenants and landlords.
Android-based capacitor discharging calculator application
Authors: Kartika Wisnu , Loniza Erika , Safitri Meilia
Published: June 2021

Nowadays, many people using smartphone to connet to her colleague. The electronic device using capacitor and transistor. The electronic device’s size recently become smaller. The capacitor can be used to the most important function that is used to store the energy and on the DC system is used to decrease the ripple from AC source. This research purpose build an apps which can calculate the charge remaining inside the capacitor. The method is using RC time constant. This research work well and can work functionally. 
Isolated Arabic handwritten words recognition using EHD and HOG methods
Authors: Mohammed Mamoun Jassim , Tariq Suphian Mohammed , Ayad Hayder
Published: June 2021

Handwriting recognition is a growing field of study in computer vision, artificial intelligence and pattern recognition technology aimed to recognizing texts and handwritings of hefty amount of produced official documents and paper works by institutes or governments. Using computer to distinguish and make these documents accessible and approachable is the goal of these efforts. Moreover, recognition of text has accomplished practically a major progress in many domains such as security sector and e-government structure and more. A system for recognition text’s handwriting was presented here relied on edge histogram descriptor (EHD), histogram of orientated gradients (HOG) features extraction and support vector machine (SVM) as a classifier is proposed in this paper. HOG and EHD give an optimal features of the Arabic hand-written text by extracting the directional properties of the text. Besides that, SVM is a most common machine learning classifier that obtaining an essential classification results within various kernel functions. The experimental evaluation is carried out for Arabic handwritten images from IESK-ArDB database using HOG, EHD features and proposed work provides 85% recognition rate.
K-means method for clustering learning classes
Authors: D. Indriyanti A. , R. Prehanto D. , Z. Vitadiar T.
Published: June 2021

Learning class is a collection of several students in an educational institution. Every beginning of the school year the educational institution conducts a grouping class test. However, sometimes class grouping is not in accordance with the ability of students. For this reason, a system is needed to be able to see the ability of students according to the desired parameters. Determination of the weight of test scores is done using the K-Means method as a grouping method. Iteration or repetition process in the K-Means method is very important because the weight value is still very possible to change. Therefore, the repetition process is carried out to produce a value that does not change and is used to determine the ability level of students. The results of the class grouping test scores affect the ability of students. Application of K-Means method is used in building an information system grouping student admissions in an educational institution. Acceptance of students will be grouped into 3 groups of learning classes. The results of testing the system that applies K-Means method and based on data on the admission of prospective students from educational institutions have very high accuracy with an error rate of 0.074. 
A robust watermark algorithm for copyright protection by using 5-level DWT and two logos
Authors: Rishek Hoshi Alaa , Zainal Nasharuddin , Ismail Mahamod , T. Rahem Abd Al-Razak , Muhsin Wadi Salim
Published: June 2021

Recent growth and development of internet and multimedia technologies have made it significant to upload data; however, in this situation, the protection of intellectual property rights has become a critical issue. Digital media, including videos, audios, and images are readily distributed, reproduced, and manipulated over these networks that will be lost copyright. Also, the development of various data manipulation tools like PDF converter and Photoshop Editor has resulted in digital data copyright issues. So, a digital watermarking technique has emerged as an efficient technique of protecting intellectual property rights by providing digital data copyright authentication and protection. In this technique, a watermarked document was integrated into electronic data to prevent unauthorized access. In this paper, A robust watermark algorithm based on a 5-level DWT and Two Log was proposed to enhance the copyright protection of images in unsecured media. Our lab results validate that our algorithm scheme is robust and forceful against several sets of attacks, and high quality watermarked image was achieved, where the algorithm was assessed by computation of many evaluation metrics such as PSNR, SNR, MAE, and RMSE.
Performance comparison of channel coding schemes for 5G massive machine type communications
Authors: Belhadj Salima , Lakhdar Abdelmounaim Moulay , Bendjillali Ridha Ilyas
Published: June 2021

Channel coding for the fifth generation (5G) mobile communication is currently facing new challenges as it needs to uphold diverse emerging applications and scenarios. Massive machine-type communication (mMTC) constitute one of the main usage scenarios in 5G systems, which promise to provide low data rate services to a large number of low power and low complexity devices. Research on efficient coding schemes for such use case is still ongoing and no decision has been made yet. Therefore, This paper compares the performance of different coding schemes, namely: tail-biting convolutional code (TBCC), low density parity check codes (LDPC), Turbo code and Polar codes, in order to select the appropriate channel coding technique for 5G-mMTC scenario. The considered codes are evaluated in terms of bit error rate (BER) and block error rate (BLER) for short information block lengths (K ≤ 256). We further investigate their Algorithmic complexity in terms of the number of basic operations. The Simulation results indicate that polar code with CRC-aided successive cancelation list decoder has better performance compared with other coding schemes for 5G-mMTC scenario.
Dual-band bandpass filter based on two U-shaped defected microstrip structure
Authors: Mabrok Mussa , Zakaria Zahriladha , Masrukin Yully , Sutikno Tole
Published: June 2021

This paper presents design of dual-band bandpass filter by integrating conventional quarter-wavelength short circuit stubs bandpass filter with U-shaped defected microstrip structure notch filter. Based on the parametric analysis, it is found that high attenuation level can be achieved by using two U-shaped defected microstrip structure separated by specific distance. The designed circuit simulated using advanced design system and fabricated based on Roger 4350B. The simulation results are in good agreement with measured results. The designed filter covered two pass bands centered at 2.51 GHz and 3.59 GHz with 3-dB fractional bandwidth of 15.94% and 15.86%, respectively, return losses better than 15 dB, and insertion losses better than 1 dB. The designed device can be used for wireless communication applications such as WLAN and WiMAX.
Cloud computing based e-government in Iraq using partial least square algorithm
Authors: Salah Hashim Hayder , Amin Al-Sul Zainab
Published: June 2021

The electronic government (e-government) worldwide is slowly progressing. The e-government progress in developing countries, such as Iraq, is slower compared with those of regional countries. Prior research suggested deploying cloud based E-government (CBEG). However, most studies are either review or conceptual. This study aims to examine the CBEG in Iraq and identify the criteria that are required for utilizing this technology. A total of 279 academic staff working in the IT department in Iraqi universities have participated in this study. The findings using matrix and the algorithm of partial least square presented ten criteria. After using the average variance extracted technique, the criteria reduced to seven. Further analysis using smart partial least square was conducted, and this resulted in five important criteria namely, reliability of the service followed by availability, security, trust, and technological competence. Decision makers have to increase the competence of the staff and enhance the CBEG services.