bluuebunny/crossref_metadata_2025 huggingface dataset:
Association between the Angle of the Left Subclavian Artery and Procedural Time for Percutaneous Coronary Intervention in Patients with Acute Coronary Syndrome
Authors: Miyagawa Masatsugu , Fukamachi Daisuke , Fukumoto Katsunori , Monden Masaki , Takahashi Kurara , Migita Shohei , Mizobuchi Saki , Tanaka Yudai , Ogaku Akihito , Koyama Yutaka , Fujito Hidesato , Arai Riku , Takei Norio , Kojima Keisuke , Iida Korehito , Murata Nobuhiro , Okumura Yasuo
Published: November 2022

Background. The effect of left subclavian artery tortuosity during percutaneous coronary intervention (PCI) in patients with acute coronary syndrome (ACS) remains unclear. Methods. Of 245 ACS patients (from November 2019 and May 2021), 79 who underwent PCI via a left radial approach (LRA) were included. We measured the angle of the left subclavian artery in the coronal view on CT imaging as an indicator of the tortuosity and investigated the association between that angle and the clinical variables and procedural time. Results. Patients with a left subclavian artery angle of a median of <70 degrees (severe tortuosity) were older (75.4 ± 11.7 vs. 62.9 ± 12.3 years,

P
<
0.001

) and had a higher prevalence of female sex (42.1% vs. 14.6%,

P
=
0.007

), hypertension (94.7% vs. 75.6%,

P
=
0.02

), and subclavian artery calcification (73.7% vs. 34.2%,

P
<
0.001

) than those with that ≥70 degrees. The left subclavian artery angle correlated negatively with the sheath cannulation to the first balloon time (ρ = −0.51,

P
<
0.001

) and total procedural time (ρ = −0.32,

P
=
0.004

). A multiple linear regression analysis revealed that the natural log transformation of the sheath insertion to first balloon time was associated with a subclavian artery angle of <70 degrees (β = 0.45,

P
<
0.001

). Conclusion. Our study showed that lower left subclavian artery angles as a marker of the tortuosity via the LRA were strongly associated with a longer sheath insertion to balloon time and subsequent entire procedure time during the PCI.
Fault Diagnosis and Prediction of Continuous Industrial Processes Based on Hidden Markov Model-Bayesian Network Hybrid Model
Authors: Yasenjiang Jiarula , Xu Chenxing , Zhang Shengpeng , Zhang Xin
Published: November 2022

Hidden Markov models (HMMs) have been recently used for fault detection and prediction in continuous industrial processes; however, the expected maximum (EM) algorithm in the HMM has local optimality problems and cannot accurately find the fault root cause variables in complex industrial processes with high-dimensional data and strong variable coupling. To alleviate this problem, a hidden Markov model-Bayesian network (HMM-BN) hybrid model is proposed to alleviate the local optimum problem in the EM algorithm and diagnose the fault root cause variable. Firstly, the model introduces expert empirical knowledge for constructing BN to accurately diagnose the fault root cause variable. Then, the EM algorithm is improved by sequential and parallel learning to alleviate the initial sensitivity and local optimum problems. Finally, the log-likelihood estimates (LL) calculated by the improved hidden Markov model provide empirical evidence for the BN and give fault detection, prediction, and root cause variable detection results based on information about the similar increasing and decreasing patterns of LL for the training data and the online data. Combining the Tennessee Eastman (TE) process and the continuously stirred tank reactor (CSTR) process, the feasibility and effectiveness of the model are verified. The results show that the model can not only find the fault in time but also find the cause of the fault accurately.
Space-Distributed Traffic-Enhanced LSTM-Based Machine Learning Model for COVID-19 Incidence Forecasting
Authors: Muñoz-Organero Mario
Published: November 2022

The COVID-19 virus continues to generate waves of infections around the world. With major areas in developing countries still lagging behind in vaccination campaigns, the risk of new variants that can cause re-infections worldwide makes the monitoring and forecasting of the evolution of the virus a high priority. Having accurate models able to forecast the incidence of the spread of the virus provides help to policymakers and health professionals in managing the scarce resources in an optimal way. In this paper, a new machine learning model is proposed to forecast the spread of the virus one-week ahead in a geographic area which combines mobility and COVID-19 incidence data. The area is divided into zones or districts according to the location of the COVID-19 measuring points. A traffic-driven mobility estimate among adjacent districts is proposed to capture the spatial spread of the virus. Traffic-driven mobility in adjacent districts will be used together with COVID-19 incidence data to feed a new deep learning LSTM-based model which will extract patterns from mobility-modulated COVID-19 incidence spatiotemporal data in order to optimize one-week ahead estimations. The model is trained and validated with open data available for the city of Madrid (Spain) for 3 different validation scenarios. A baseline model based on previous literature able to extract temporal patterns in COVID-19 incidence time series is also trained with the same dataset. The results show that the proposed model, based on the combination of traffic and COVID-19 incidence data, is able to outperform the baseline model in all the validation scenarios.
Data Transmission in Backscatter IoT Networks for Smart City Applications
Authors: Kim Dae-Young , Park Jihoon , Kim Seokhoon
Published: November 2022

Backscatter communication is a battery-less data transmission method for massive IoT devices. These backscatter devices receive an incident signal from an RF-source gateway to harvest energy. These devices can be operated to transmit data after harvesting energy. This technology is widely applied to smart city applications. In general, IoT devices in the smart city applications have insufficient resources. They use narrowband communication to transmit small sizes of data. Thus, a simple channel access approach should be considered for data transmission. In addition, network scalability is also important in the backscatter network for smart city applications. According to energy harvesting and data generation, devices participating in data transmission can change frequently. Providing the network scalability by the changing devices can improve the transmission efficiency in the backscatter network. Therefore, we propose a novel media access scheme for the backscatter network in the smart city applications. The proposed scheme is designed by the contention-based approach to support the network scalability. It controls backscattering signal for energy harvesting and distributes contention in multiple access. It allows additional data transmission in backscattering period for harvesting energy to provide fairness of devices. For performance evaluation, extensive computer simulations are carried out and the proposed method is compared to TDMA that is a typical media access scheme in the backscatter network.
Health Detection System for Sports Dancers during Training Based on an Image Processing Technology
Authors: Zhang Lu
Published: November 2022

Dance sport is a competition of athletes for qualities such as speed, strength, endurance, flexibility, and coordination, requiring a high level of overall physical fitness. As China’s sports fever continues to heat up, especially among students, the active nature of young people can lead to overenthusiasm for sports, dance, and other sports, which can lead to various physical discomforts during sports. Especially in the current sports habits of students, there is a great hidden danger of sports injuries. It is mainly due to excessive exercise, irregular exercise methods, and incomplete sports protective equipment. On this basis, this study proposes a model to further assess the health status of individuals and groups from the rate of energy consumption during exercise by building a real-time motion detection system. The development of sports health assessment systems, including the application of imaging techniques, is also analyzed. The experimental results in this article show that when the error threshold is set to 10%, the accuracy of the model is 85%, and the obtained results are ideal.
Construction of Digital Economy Trade Security Evaluation System Based on Computational Intelligence
Authors: Zhu Yuqin , Wang Fengling
Published: November 2022

The upgrading of the digital economy (DE) is crucial to building an intelligent society. The rapid development of computational intelligence in recent years has also brought vitality to the development of the DE. However, with the deepening of international trade, the issue of trade security has become more and more prominent. Therefore, this study aimed to construct a DE trade security evaluation system. For computational intelligence, this study proposes a support vector machine based on improved particle swarm optimization. Such an algorithm can play a key role in the construction of an evaluation system. It is built for the evaluation system. This study selects five indicators of market competitiveness, trade control, trade dependence, market concentration, and trade legal system evaluation. The experimental results of this study prove that the evaluation system proposed in this study is effective. In its test for some countries in the world, the UK trade security index was the highest at 0.582, while China was relatively low at 0.492.
Thermal Decomposition, Ignition Process and Combustion Behavior of Nitrate Ester Plasticized Polyether Propellant at 0.1–3.0 MPa
Authors: Tu Chengyin , Feng Yaya , Ling Zhigang , Chen Xiong , Zhou Changsheng , Li Yingkun , Li Weixuan , Cai Wenxiang
Published: November 2022

Nitrate ester plasticized polyether (NEPE) propellant is widely used in solid rocket motors, having both good mechanical properties and high specific impulse. However, its ignition and combustion process are complex and need to be better understood. In this study, a high-pressure sealed combustion chamber was constructed, a thermogravimetry-differential scanning calorimetry was used to investigate the thermal decomposition process, and a high-speed camera was used to capture the ignition process and combustion behavior of the propellant. The results showed that the thermal decomposition process of this propellant could be divided into two stages. The first stage (50–350°C) was the major mass loss stage and exhibited typical features of BTTN, RDX, and AP decomposition. The second stage (350–500°C) was mainly accompanied by decomposition of the remaining components as well as slight oxidation of aluminum particles. The ignition process of NEPE propellant was divided into four stages, including the inert heating period stage, thermal decomposition stage, initial flame stage, and stable combustion stage. After the propellant absorbed heat, the propellant started to pyrolyze and gasify to generate flammable gas. When the temperature of the propellant surface reached the flammable gas ignition point, an initial flame was generated on the surface, which spread rapidly, covering the surface. The ignition delay time of the propellant was measured by a signal acquisition system, and a mathematical model was then established for the ignition delay time. The results showed that the ignition delay time decreased with increased laser heat flux and ambient pressure. Finally, the Vielle burning rate empirical formula was used to fit the burning rate data for the propellant. The resulting good fit was consistent with experimental measurements and showed that the formula was valid for predicting the NEPE propellant burning rate under 0.1–3.0 MPa nitrogen.
Insights into Optimal Schemes of Radial Network Arch Pedestrian Bridge
Authors: Belevičius Rimantas , Rusakevičius Dainius , Valentinavičius Saulius
Published: November 2022

The main objective of the article is to find the optimal ranges of the cardinal topological, shape, and dimensional parameters that fully describe the constructional scheme of pedestrian radial network arch bridges of moderate spans. This task is solved by formulating the global optimization problem and seeking the minimum mass of the whole bridge structure. An optimal bridge scheme was obtained by tuning a large set of interdependent design parameters of diverse character: the topological parameters–the type of hanger arrangement, and the number of hangers; the shape parameters–hanger spread and central section angles, the alteration of these angles, and the arch rise; and the sizing parameters–all cross‐sectional dimensions of structural members. Mathematically, this is a constrained mixed‐integer global optimization problem solved by a stochastic evolutionary algorithm. Plane light‐deck bridges of typical moderate 30, 45, 60, 75, and 90 m spans were optimized. Decisive design parameters and their rational ranges for all spans were revealed. In addition, the effects of some simplifications of the general bridge scheme were shown: using the constant spread and central section angles; imposing certain values on the ratio arch rise/bridge span; bounding the hanger diameters to a given value; and so on. Obtained results clearly indicate that the design recommendations for the lightweight network arch bridges should differ from the recommendations for similar automotive and railway bridges. Our findings are: the optimal ratio of arch rise to the bridge span is 0.20–0.30, the number of hangers is >40 even for the shortest spans, the spread angle between hangers is 30°–40°, and the girder mass amounts to ∼30% of the total bridge mass, while the mass of hangers amounts up to 20% and increases when imposing constraints on the minimal radius at the expense of diminishing arch mass.
Prevention of Malaria in Pregnancy: What Do the Pregnant Women of Nigeria Know and Do about It?
Authors: Kalu Stephen , Cleenewerck Laurent , Gulma Kabiru AbuBakar , Bhalla Devender
Published: November 2022

Objective. We assessed knowledge, attitude, and practice regarding two malaria prevention measures (long-lasting impregnated mosquito nets, LLINs, and intermittent preventative therapy with sulphadoxine-pyrimethamine (IPTp-SP)) among pregnant women in Nigeria. Methods. Pregnant women selected from among the four communities of Nnewi were interviewed by using a semistructured, interviewer-administered questionnaire on the respondents’ demography, knowledge of the cause, consequences, and malaria prevention methods. Also, a total of 48 focused group discussions, 24 key informant interviews, and 24 in-depth interviews were held among women leaders, village heads, pregnant women, community health workers, husbands of pregnant wives, and drug and insecticide-treated net sellers. Results. A total of 384 women (88.0% third trimester, 90.0% literate, and 41.1% primigravidae) participated. About 80.0% suffered from malaria during their current pregnancy. The majority was aware of the cause of malaria, local name of malaria, mode of transmission, risk of malaria among pregnant women, etc. However, their knowledge and attitude were inadequate regarding the symptomatology and complications of malaria in pregnancy, benefits of sleeping under the net or taking chemoprophylactic doses, or the concurrent use of both. About 80.0% had LLINs, yet only 41.5% slept under it the previous night. Only 31.0% had IPTp-SP doses under direct observation. Only 35.9% had a good understanding of IPTp-SP during pregnancy. Conclusion. Our work presents important practice gaps associated with the prevention of malaria during pregnancy. The pregnant women seemed to be aware of the basic concepts related to malaria but that does not translate into adequate attitude and practice necessary for malaria reduction.
Vanillic Acid Inhibited the Induced Glycation Using In Vitro and In Vivo Models
Authors: Alhadid Amani , Bustanji Yasser , Harb Amani , Al-Hiari Yusuf , Abdalla Shtaywy
Published: November 2022

Background. Glycation is implicated in the pathophysiology of many diseases, including diabetes, cancer, neurodegenerative diseases, and aging. Several natural and synthetic compounds were investigated for their antiglycation activity. We evaluated the antiglycation effect of vanillic acid (VA) using in vitro and in vivo experimental models. Methods. In vitro, bovine serum albumin (BSA) (50 mg/ml) was incubated with glucose (50 mM) with or without VA at 1.0–100 mM for 1 week at 37°C, and then, excitation/emission fluorescence was measured at 370/440 nm to determine glycation inhibition. The cytoprotective effect of VA was evaluated using RAW 264.7 cells incubated with or without VA at 7.8–500 μM along with 100–400 μM of methylglyoxal for 48 hours, and cell viability was determined using the MTT assay. Aminoguanidine (AMG) was used as a positive control in both in vitro and cell culture experiments. In vivo, 52 streptozotocin-induced diabetic rats were randomly assigned to 4 groups and treated with 0, 1.5, 4.5, or 15 mg/kg VA for four weeks. Serum fructosamine and blood glycosylated hemoglobin (HbA1c) were then measured, and advanced glycation end-products (AGEs) were detected in the kidneys and the skin of deboned tails using an immunohistochemistry assay. Results. VA caused a concentration-dependent effect against BSA glycation (IC50 of 45.53 mM vs. 5.09 mM for AMG). VA enhanced cell viability at all concentrations of VA and methylglyoxal. VA did not affect serum fructosamine or blood HbA1c levels, although it markedly decreased AGEs in the kidney in a dose-dependent manner and decreased AGEs in the skin of deboned tail tissues. Conclusion. VA had significant antiglycation activity at cellular and long-term glycation.
Biomechanical Sensing Systems for Cardiac Activity Monitoring
Authors: Owida Hamza Abu
Published: November 2022

Cardiovascular disease is consistently ranked high among the causes of death on a global scale. Monitoring of cardiovascular signs throughout the course of a long period of time and in real time is necessary in order to discover anomalies and begin early intervention at the appropriate time. To this purpose, a significant amount of interest among researchers has been directed toward the creation of flexible sensors that may be worn or implanted and are capable of constant, immediate observation of a variety of main physiological indicators. The real-time readings of the heart and arteries’ pressure fluctuations can be reflected directly by mechanical sensors, which are one of the many types of sensors. Potential benefits of mechanical sensors include excellent accuracy and considerable versatility. Capacitive, piezoresistive, piezoelectric, and triboelectric principles are the foundations of the four types of mechanical sensors that are discussed in this article as recent developments for the purpose of monitoring the cardiovascular system. The biomechanical systems that are present in the cardiovascular system are then detailed, along with their monitoring, and this includes blood and endocardial pressure, pulse wave, and heart rhythm. In conclusion, we examine the usefulness of the use of continuous health monitoring for the treatment of vascular disease and highlight the difficulties associated with its translation into clinical practice.
Constraints on Diagenetic Fluid Source and Genesis in Tight Dolostone Reservoir of Submember Ma55 of Ordovician Majiagou Formation in Northwestern Ordos Basin, China: Evidence from Petrology and Geochemistry
Authors: Li Baiqiang , Wu Zhenzhen , Zhou Taofa , Chen Bin , Wang Qicong , Zhang Xiaoli
Published: November 2022

Diagenetic fluids is one of the most important reservoir modifiers, their differences can result in various petrography, storage capacity, and geochemical characteristics, so clarifying the diagenetic fluids is vital for understanding dolostone origin. Dolomitization is an important genetic type of dolostone reservoir, the fluid properties differ in different dolomitization, which may lead to reservoir storage capacity changes. Therefore, the identification of dolomitization fluid properties is critical for deeply understanding of dolomitization process and predicting storage capacity. Two types of dolostone are developed in submember Ma55 of Majiagou Formation in northwestern Ordos Basin, with obviously different petrological characteristics and reservoir properties. On the basis of petrological studies such as core and casting thin section observation and cathodoluminescence analysis, the diagenetic fluid properties of these two dolostone are characterized by geochemical analytical methods such as major and trace element tests. The results show that Type-1 dolostone is mainly composed of micritic dolomite, showing micritic structure and algae-rich lamina structure, and accompanied by evaporite minerals and moldic pores. This type of dolostone has a various Mn content, weak to medium cathodoluminescence intensity, high contents of TiO2, Al2O3, K2O+Na2O, Li, and U, and lower content of TFe2O3. The type-2 dolostone is composed of fine-grained dolomite with obvious residual texture of primary limestone, clear brim, and cloudy center structure, accompanied by the existence of intergranular pores. Most of this kind of dolostone have medium-strong cathodoluminescence, higher TFe2O3 content and lower TiO2, Al2O3, K2O+Na2O, Li, and U contents. Moreover, both the two types of dolostone have similar Fe/Ca and Mn/Ca ratios, and a low and concentrated CaO content, whose composition is similar to that of stoichiometric dolomite. The comprehensive analysis shows that the diagenetic fluid of Type-1 dolostone is mainly a high salinity fluid existed in plaster and calcareous sediments in a near surface environment with low temperature. The diagenetic fluid of Type-2 dolostone may be a high salinity brine formed by evaporation and concentration of seawater with normal salinity. The research results will provide a significant theoretical basis for the evaluation of dolostone reservoir quality and the prediction of favorable areas of reservoir distribution.
Artificial Intelligence Based Study Association between p53 Gene Polymorphism and Endometriosis: A Systematic Review and Meta-analysis
Authors: Ma Xia , Jin Xiaoxiao , Shao Xiujuan , Hu Wanjing , Jin Haihong , Wang Yiqun
Published: November 2022

Background. The P53 gene is critical to the onset and progression of cancers. Currently, relevant study findings indicate that the p53 gene may have a strong association with the risk of endometriosis, but these findings have not been united. To gather more statistically meaningful clinical data, we used meta-analysis to examine the relationship between the rs1042522 single nucleotide polymorphism of the tumor suppressor gene p53 and the incidence of endometriosis. Methods. Through a comprehensive literature survey of PubMed, MEDLINE, EMBASE, Springer, and Web of Science literature databases, we obtained a clinical control case study on the relationship between p53 gene polymorphism and the prevalence of female endometriosis and finally traced the relevant references included. The quality of the literature included in this study was evaluated, and Revman5.3 was used to complete the meta-analysis. Results. This research includes eight publications. The total number of cases in the study group was 1551, whereas the total number of cases in the control group was 1440. The findings of the sensitivity analyses of each omitted piece of the literature revealed no significant difference. The results of the meta-analysis showed that there were significant differences in the GG gene frequency (OR = 0.56, 95%CI (0.38, 0.92),

P

 = 0.003), allele G (OR = 2.46, 95%CI (1.41,4.29),

P

 = 0.002), and allele C (OR = 0.62, 95%CI (0.46, 0.84),

P

 = 0.002) between the study group and the control group (

P

< 0.01), but there was no significant difference in the GC gene frequency (OR = 1.17, 95%CI (1.01,1.36),

P

 = 0.03), and the CC gene frequency (OR = 1.25, 95%CI (0.85,1.82),

P

 = 0.26) (

P

> 0.01). Conclusion. Our study results show that there is a significant correlation between the single nucleotide of the p53 gene and the incidence rate of female endometriosis, in which the decrease of the GG gene frequency and the increase of allele C are likely to increase the risk of such diseases.
Therapeutic and Neuroprotective Effects of Bushen Jianpi Decoction on a Rotenone-Induced Rat Model of Parkinson’s Disease
Authors: Liang Wei , Yao Lulu , Chen Jiahao , Chen Zhiying , Wu Xiling , Huang Xiaobo
Published: November 2022

Parkinson’s disease (PD) is an age-related neurodegenerative disorder characterized by the loss of dopaminergic neurons in the substantia nigra (SN) pars compacta. Dopamine (DA) replacement therapy is one of the most effective drug treatments for PD; however, long-term levodopa treatment can lead to various side effects that negatively impact the quality of life of patients. Therefore, finding safe and effective alternative drugs to treat PD is of clinical importance. The Bushen-Jianpi decoction (BSJPD) was derived from classic traditional Chinese medicine and has been shown to be effective in the treatment of PD. This study explored the effects and mechanisms of action of BSJPD in PD. In our study, rats were randomly divided into six groups: the vehicle group, rotenone (ROT) + Saline group, ROT + low-dose BSJPD group, ROT + high-dose BSJPD group, ROT + Madopar group, and ROT + low-dose BSJPD + Madopar group. Treatment was administered to the rats once a day for 28 days, and behavioral tests were assessed. Tyrosine hydroxylase (TH), catechol-O-methyltransferase (COMT), monoamine oxidase B (MAO-B), dopa decarboxylase (DDC), alpha-synuclein (α-syn), and heme oxygenase-1 (HO-1) levels were detected. Our results show that BSJPD increases the body weight of rats, improves their motor coordination, reverses decreasing TH levels in the SN, and increases the expression level of DDC and HO-1 in the striatum (ST), but it fails to affect TH levels in the ST in the PD model. In addition, BSJPD reduced the expression of MAO-B in the ST in the PD model, but it did not have a significant effect on COMT. Rather, COMT in the plasma and liver increased in the low-dose BSJPD treatment group. Upregulation of α-syn in the PD model was also observed, but BSJPD has shown no obvious effect to clear it. Our results suggest that BSJPD exhibits a therapeutic effect on PD and may play a neuroprotective role by regulating HO-1 expression and participating in the metabolic process of DA.
Can Well‐Being, Positive Affect, or Contact with the Elderly Be Potential Predictors of Attitudes towards Older People? A Study on the Polish Population
Authors: Marta Podhorecka , Jakub Husejko , Anna Pyszora , Kornelia Kędziora-Kornatowska , Agnieszka Woźniewicz
Published: November 2022

Objectives. The age discrimination, i.e., ageism, is still a current social problem. Therefore, it is justified to conduct studies increasing the knowledge about this phenomenon. The aim of our research was to determine whether the type of personality, manifested mood, and well‐being can influence the attitudes towards the elderly. Material and Methods. During the research, we collected information from 923 participants and we used the following tools: demographic questionnaire, Kogan’s Attitudes Toward Old People Scale, Euthymia Scale, WHO‐5 Well‐Being Index, and the author’s questionnaire on contacts with an elderly person. Results. We used R 4.0.2 to analyse the data. In our current model study, we did not observe statistically significant relationships between the WHO‐5 or ES scores and the KOAP score. Conclusions. The conducted study did not show any correlation between mood, sense of well‐being, or contact with the elderly and attitude towards the elderly. The results of our study may become the basis for further research to find the relationship between the mood and well‐being shown in attitudes towards the elderly. Perhaps, however, the assumption should also be made that there is no such relationship.
Transcriptional Antagonism by CDK8 Inhibition Improves Therapeutic Efficacy of MEK Inhibitors
Authors: Malone Clare F. , Kim Minjee , Alexe Gabriela , Engel Kathleen , Forman Alexandra B. , Robichaud Amanda , Conway Amy Saur , Goodale Amy , Meyer Ashleigh , Khalid Delan , Thayakumar Allen , Hatcher John M. , Gray Nathanael S. , Piccioni Federica , Stegmaier Kimberly
Published: November 2022

Aberrant RAS/MAPK signaling is a common driver of oncogenesis that can be therapeutically targeted with clinically approved MEK inhibitors. Disease progression on single-agent MEK inhibitors is common, however, and combination therapies are typically required to achieve significant clinical benefit in advanced cancers. Here we focused on identifying MEK inhibitor-based combination therapies in neuroblastoma with mutations that activate the RAS/MAPK signaling pathway, which are rare at diagnosis but frequent in relapsed neuroblastoma. A genome-scale CRISPR-Cas9 functional genomic screen was deployed to identify genes that when knocked out sensitize RAS-mutant neuroblastoma to MEK inhibition. Loss of either CCNC or CDK8, two members of the mediator kinase module, sensitized neuroblastoma to MEK inhibition. Furthermore, small-molecule kinase inhibitors of CDK8 improved response to MEK inhibitors in vitro and in vivo in RAS-mutant neuroblastoma and other adult solid tumors. Transcriptional profiling revealed that loss of CDK8 or CCNC antagonized the transcriptional signature induced by MEK inhibition. When combined, loss of CDK8 or CCNC prevented the compensatory upregulation of progrowth gene expression induced by MEK inhibition. These findings propose a new therapeutic combination for RAS-mutant neuroblastoma and may have clinical relevance for other RAS-driven malignancies.

Significance:

Transcriptional adaptation to MEK inhibition is mediated by CDK8 and can be blocked by the addition of CDK8 inhibitors to improve response to MEK inhibitors in RAS-mutant neuroblastoma, a clinically challenging disease.
Targeted Metabolomic Profiling of Plasma Samples in Gastric Cancer by Liquid Chromatography-Mass Spectrometry
Authors: Matsumoto Taisuke , Fukuzawa Masakatsu , Itoi Takao , Sugimoto Masahiro , Aizawa Yumi , Sunamura Makoto , Kawai Takashi , Nemoto Daiki , Shinohara Hirokazu , Muramatsu Takahiro , Suzuki Yuka , Kagawa Yasuyuki , Suguro Maya , Uchida Kumiko , Koyama Yohei , Madarame Akira , Morise Takashi , Yamaguchi Hayato , Sugimoto Akihiko , Yamauchi Yoshiya , Kono Shin , Naito Sakiko
Published: November 2022

Introduction: As the high mortality rate of gastric cancer (GC) is due to delayed diagnosis, early detection is vital for improved patient outcomes. Metabolic deregulation plays an important role in GC. Although various metabolite-level biomarkers for early detection have been assessed, there is still no unified early detection method. We conducted a plasma metabolome study to assess metabolites that may distinguish GC samples from non-GC samples. Methods: Blood samples were collected from 72 GC patients and 29 control participants (non-GC group) at the Tokyo Medical University Hospital between March 2020 and November 2020. Hydrophilic metabolites were identified and quantified using liquid chromatography-time-of-flight mass spectrometry. Differences in metabolite concentrations between the GC and non-GC groups were evaluated using the Mann-Whitney test. The discrimination ability of each metabolite was evaluated by the area under the receiver operating characteristic curve. A radial basis function (RBF) kernel-based support vector machine (SVM) model was developed to assess the discrimination ability of multiple metabolites. The selection of variables used for the SVM utilized a step-wise regression method. Results: Of the 96 quantified metabolites, 8 were significantly different between the GC and non-GC groups. Of these, N1-acetylspermine, succinate, and histidine were used in the RBF-SVM model to discriminate GC samples from non-GC samples. The area under the curve (AUC) of the RBF-SVM model was higher (0.915; 95% CI: 0.865–0.965, p < 0.0001), indicating good performance of the RBF-SVM model. The application of this RBF-SVM to the validation dataset resulted from the AUC of the RBF-SVM model was (0.885; 95% CI: 0.797–0.973, p < 0.0001), indicating the good performance of the RBF-SVM model. The sensitivity of the RBF-SVM model was better (69.0%) than those of the common tumor markers carcinoembryonic antigen (CEA) (10.5%) and carbohydrate antigen 19-9 (CA19-9) (2.86%). The RBF-SVM showed a low correlation with CEA and CA19-9, indicating its independence. Conclusion: We analyzed plasma metabolomics, and a combination of the quantified metabolites showed high sensitivity for the detection of GC. The independence of the RBF-SVM from tumor markers suggested that their complementary use would be helpful for GC screening.
A Case of Nephrotic Syndrome with Bilateral Serous Retinal Detachment and Shallow Anterior Chamber Associated with Ciliary Body Edema
Authors: Takai Yasuyuki , Sakuma Toshiro , Mashimo Keitaro , Inoue Kenji , Ebihara Nobuyuki
Published: November 2022

Nephrotic syndrome is a disease that causes fluid retention in the body due to loss of protein in the blood, which can lead to serous retinal detachment (SRD) in the macula. We report a case of severe SRD in both eyes and angle closure due to ciliary body edema caused by nephrotic syndrome. A 57-year-old man was admitted to the Department of Nephrology in our hospital for a thorough examination of his generalized edema. He was diagnosed with nephrotic syndrome but proved to be refractory to steroid treatment. Due to distortion symptoms in both eyes on the 30th day of hospitalization, the patient was referred to our department. Best-corrected visual acuity (BCVA) was 0.8 in the right eye and 1.0 in the left eye. Slit lamp examination and anterior segmental optical coherence tomography (OCT) showed shallow anterior chambers in both eyes. Fundus and macular OCT demonstrated severe SRD in the posterior pole of both eyes. After observing the presence of hypoalbuminemia, we considered the possibility of SRD and angle closure due to ciliary edema that resulted from the leaks associated with the nephrotic syndrome. Thereafter, ocular findings improved in conjunction with systemic symptom improvements associated with ultrafiltration and low-density lipoprotein apheresis. On the 60th day of hospitalization, his BCVA improved to 1.2 in both eyes, SRD disappeared, and the anterior chamber depth normalized. This case demonstrates the importance of recognizing SRD and angle closure associated with ciliary body edema as complications linked with nephrotic syndrome.
Two Electrocardiographic Aberrations Important for All Caring for Patients to Know about
Authors: Madias John E.
Published: November 2022

Two electrocardiographic (ECG) aberrations encountered daily in ECG interpretation/overreading, which appear to be either unknown or ignored, by all caring for patients, are described herein: the 1st is the transient increase in the amplitude of QRS complexes in the right precordial ECG leads, leading to the erroneous diagnosis of left ventricular hypertrophy, often encountered in patients with episodes of supraventricular tachycardia, rapid sinus tachycardia, and atrial fibrillation; the 2nd is the spurious ST-segment elevations in lateral and/or inferior ECG leads in patients with right bundle branch block, interpreted by the automated ECG diagnostic algorithms as due to “acute myocardial infarction,” “ischemic injury,” “pericarditis,” and “early repolarization,” in the absence of such pathologies or electrophysiological explanations.
Human ear print recognition based on fusion of difference theoretic texture and gradient direction pattern features
Authors: Thabt Saleh Kawther , Ali Mustafa Raniah , Salman Chyad Haitham
Published: November 2022

Human ear recognition can be defined as a branch of biometrics that uses images of the ears to identify people. This paper provides a new ear print recognition approach depending on the combination of gradient direction pattern (GDP2) and difference theoretic texture features (DTTF) features. The region of interest (ROI), the gray scale of the ear print was cut off, noise removal by the median filter, histogram equalization, and local normalization (LN) are the first steps in this approach. After the image has been processed, it is used as input for the fusion of GDP2 and DTTF for extracting the features of ear print images. Lastly, the Gaussian distribution (GD) was utilized to compute the distance among fusion feature vectors (FV) for ear print images for recognizing ear print images for people using a set of images that had been trained and tested. The unconstrained ear recognition challenge (UERC) database, which comprises 330 subjects for ear print images, provides the approach that was suggested by employing ear print databases. Furthermore, experimental results on images from a benchmark dataset reveal that statistical-rely super-resolution methods outperform other algorithms in ear recognition accuracy, which was around 93.70% in this case.
Research on secure workload execution scheme in heterogeneous cloud environment
Authors: Pasha Fairoz , Natarajan Jayapandian
Published: November 2022

The increasing demand for the hardware, software and infrastructure is playing a big role in the information technology domain towards the need of customer’s specific requirements. Cloud computing is a major backbone for providing such services over the internet. It includes the services such as applications, storage, network, scalability, sharing, virtualization, confidentiality, security, authentication, and integrity. A large number of data intensive workflow applications uses heterogeneous cloud environment for communication and computation operation. An intruder/attacker will utilize these environments for their benefit by flooding malicious links, unwanted information and others. In cloud environment, detecting a malicious device/packet during workflow execution is a critical and challenging task. The various workflow method with security, service level agreement (SLA) and quality of service (QoS) have been modelled in recent time; However, these models are not efficient in detecting malicious users and maintaining high level of QoS or workflow applications. This article focus is on addressing research future direction, issues and challenges of work in meeting secure and efficient workflow execution model for heterogeneous cloud environment.
Healthcare scenario: a new task scheduling algorithm in cloud computing environment
Authors: Bansal Nidhi , Kumar Singh Ajay
Published: November 2022

Makespan and cost are the major factors in the current scenario and they generally upgrade the results to optimize the upcoming task processing by implementing the scheduling within the specified cloud platform. A new proposed agenda is being considered for a health care system to make the world healthier. The paper is designed to identify prior work as a health evaluator for the end user and act accordingly. It also satisfies the end user by providing demanded results and can establish trust between the system and the customer within a global era. By analyzing the COVID-pandemic situation in the digital world, things should be implemented in conjunction with healthcare and technology to serve things better. The proposed algorithm works on priority basis by analyzing the current patient condition and then implemented in CloudSim Toolkit. As per the results, the proposed steps are performing 50-70% better in terms of makespan and cost. Notable optimization has been accomplished by the proposed healthcare evaluator.
Improving WSNs execution using energy-efficient clustering algorithms with consumed energy and lifetime maximization
Authors: Sameer Jabbar Mohanad , Saeed Issa Samer , Hussein Ali Adnan
Published: November 2022

Wireless sensor networks (WSNs) has a major designing feature representing by energy. Specifically, the sensor nodes have limited battery energy and are deployed remote from base station (BS); therefore, the actual enhancement dealing with energy turns into the Clustering routing protocols fundamentals which concerned in network lifetime improvement. Though, unexpected and energy insensible of the clusters head (CH) selection is not the best of WSN for greatly lowering lifetime network. A presentation article of an WSNs incoming routing approach using a mix of the fuzzy approach besides hybrid energy-efficient distributing (HEED) algorithm for increasing the lifetime and node’s energy. The FLH-P proposal algorithm is split into two parts. The stable election protocol HEED approach is used to arrange WSNs into clusters. Then, using a combination of fuzzy inference and the low energy adaptive clustering hierarchy (LEACH) algorithm, metrics like residual energy, minimal hops, with node traffic counts are taken into account. A comparison of FLH-P proposal algorithm with LEACH algorithm, fuzzy approach, and HEED utilizing identical guiding standards was used for demonstrating the performance of the suggested technique from where corresponding consumed energy as well as lifetime maximization. The suggested routing strategy considerably increases the network lifetime and transmitted packet throughput, according to simulation findings.
Web-based autism screening using facial images and convolutional neural network
Authors: Ikermane Mohamed , El Mouatasim Abdelkrim
Published: November 2022

Developmental disabilities such as autism spectrum disorder (ASD) affect a person’s ability to interact socially, and communicate effectively and also cause behavioral issues. Children with ASD cannot be cured but they might benefit from early intervention to enhance their cognitive abilities, favorite their growth , and affect their lives and families in a positive way. Multiple standard ASD screening tools are used such as the autism diagnostic observational schedule (ADOS) and the autism diagnostic interview (ADI), which are known to be lengthy and challenging without specialist training to administrate and score. The process of ASD assessment can be time-consuming and costly, and the growing number of autistic cases worldwide indicates an urgent need for a quick, simple, and dependable self-administered autism screening tool that may be used if a child displays some of the common signs of autism, and to ensure whether or not he should seek professional full ASD diagnosis. According to a number of studies, ASD individuals exhibit facial phenotypes that are distinct from those of normally developing children. Furthermore, convolutional neural networks (CNN) have mostly found utility in image classification applications due to their high classification accuracy. Using facial images, a dense convolutional network (Densenet) model, and cloud-based advantages, in this paper we proposed a practical, fast, and easy-to-use ASD online screening approach. Easily available through the internet via the link “https://asd-detector.herokuapp.com/”, our suggested web-based screening instrument may be a practical and trustworthy tool for practitioners in their ASD diagnostic procedures with a 98 percent testing dataset classification accuracy.
Underwater image copyright protection using robust watermarking technique
Authors: Talib Gaata Methaq , Dhiaa Al-Hassani Mustafa
Published: November 2022

It became possible to send and reformat underwater images for copyright theft due to the rapid advancement of computer networks and image forgery tools. Acquiring underwater images is dangerous and requires much efforts, expensive imaging equipment, and professional photographers. Therefore, there is an urgent need to develop copyright protection methods to ensure that property rights are not lost. This paper presents a robust watermarking technique that ensures proof of ownership for underwater images, preventing unauthorized individuals from claiming ownership. The suggested watermarking technique's main contribution depends on using the Hough transform in order to find appropriate regions to hide the watermark information within the underwater images. The Hough transform is useful for identifying areas of difficult texture that can be used as a host for watermark information with minimal distortion. Also, the Twofish algorithm has been used to encrypt the watermark information before being hidden in the underwater image. The performance of the suggested watermarking technique is tested by two metrics: quality and robustness. The results show that the suggested method works because of the quality of the images that were made after the watermark was added and because it could withstand the attacks on it.
Blockchain for baccalaureate examination sheets protection in Iraq
Authors: A. Nahi Hayder , M. Hashim Saeed , J. Kreem Dhurgham
Published: November 2022

Due to their unique qualities, including data integrity, security, decentralization, and dependability, blockchain technologies have drawn a lot of interest from both academia and business. In order to effectively handle the adoption problems of blockchain technologies, it is important to identify what influences their use and adoption. In order to protect the exam sheet (as image format) for the baccalaureate examination in Iraq. This paper article sought to construct a private blockcahin powered by a variety of algorithms, After that, with this concern about privacy and fear of private information leaking, and in order to ensure that that image will only be seen by the specific person you want, the technology is full of many encryption features that achieve this end, we encrypt the image before sending it as a transaction in the Blockchain network. Also, we obtained speed smart contact verifications compared with traditional systems due to the proposed system is private and has simple complexity.
Perturb and observe maximum power point tracking approach for microgrid linked photovoltaic system
Authors: Rout Kshirod Kumar , Mishra Debani Prasad , Mishra Sivkumar , Patra Suman , Salkuti Surender Reddy
Published: November 2022

This paper develops a maximum power point tracking (MPPT) approach for a microgrid-linked solar photovoltaic (PV) system based on the concept of a perturb and observe (P&O) approach. It is an iterative algorithm that requires a starting point to trace the maximum power point tracking. This study proposes the P&O MPPT algorithm for a 3-ɸ grid-connected PV system. In this work, the PV system is modeled as a DC grid-connected PV system, and the MPPT algorithm is applied to that model. An MPPT application is used in this proposal to amplify the effectiveness of the PV array in face of any unsteady climatic circumstances. Hence, the highest energy could be secured out of the solar PV array and interfaced with the grid. The voltage source converter will empower defining of boundaries and greatest degrees of force from sunlight-based chargers in an efficient way. A few outcomes like the current, voltage and result power for each different mix have been noted.
Design of current controlled instrumental amplifier by using complementary metallic oxide semiconductor technology
Authors: Hasan Ghanim Thiab , Ali Kamil Jadu , Mutlaq Ali Hlal
Published: November 2022

In this paper, a complementary metal oxide semiconductor (CMOS) instrumental amplifier was designed and implemented in order to provide the possibility of controlling the current and voltage gain. The proposed instrumentation amplifier consists of three conveyors with active resistor. The parasitic resistance value (Rx) was reduced with a large bandwidth level in addition to achieving a high common mode rejection ratio (CMRR). Simulation was performed by using 0.35μm CMOS technology by using the advanced design system (ADS) software. The results obtained prove that the proposed circuit has a good efficiency with higher degree of CMRR in comparison with other amplifiers designed and implemented in other similar works.