bluuebunny/crossref_metadata_2025 huggingface dataset:
Nicotine Ingestion Reduces Heart Rate Variability in Young Healthy Adults
Authors: Guo Qian-nan , Wang Jing , Liu Hong-yan , Wu Dong , Liao Shi-xiu
Published: January 2022

Around the whole world, smoking is considered harmful to human health, such as increasing the risk of cardiovascular disease (CVD, such as coronary heart disease and stroke) and lung cancer. The purpose of this study was to explore whether nicotine, the main component of tobacco, has adverse effects on heart rate variability (HRV) in adolescents, so as to remind adolescents not to smoke and not to take pleasure in abusing nicotine. In this study, 40 male and 40 female young healthy nonsmoking subjects were selected to analyze the changes of HRV after taking 4 mg nicotine orally. We found that nicotine reduced HRV in young healthy male and female subjects, and there was no gender difference in this effect (P > 0.05). In conclusion, smoking is harmful to the cardiac system of young people, especially when nicotine content ≥4 mg dosage.
Application of Nanomaterial in Hydrogels Related to Wound Healing
Authors: Liu Yangyang , Song Shurui , Liu Shuangyong , Zhu Xiaoyan , Wang Peige
Published: January 2022

Traditional dressings used for wound repair, such as gauze, have shortcomings; for example, they cannot provide a suitable microenvironment for wound recovery. Therefore, it is necessary to find a better dressing to overcome shortcomings. Hydrogel provides a suitable wet environment, has good biocompatibility, and has a strong swelling rate to absorb exudate. Nanomaterial in hydrogels has been used to improve their performance and overcome the shortcomings of current hydrogel dressings. Hydrogel dressing can also be loaded with nanodrug particles to exert a better therapeutic effect than conventional drugs and to make the dressing more practical. This article reviews the application of nanotechnology in hydrogels related to wound healing and discusses the application prospects of nanohydrogels. After searching for hydrogel articles related to wound healing, we found that nanomaterial can not only enhance the mechanical strength, antibacterial properties, and adhesion of hydrogels but also achieve sustained drug release. From the perspective of clinical application, these characteristics are significant for wound healing. The combination of nanomaterial and hydrogel is an ideal dressing with broad application prospects for wound healing in the future.
Dietary Determinants of Dental Caries Prevalence and Experience in Saudi Schoolchildren: Frequency versus Quantity
Authors: Al-Zahrani Abdulkarim , Al-Qahtani Mohammed , Al-Barti Mohammed , Bakhurji Eman A.
Published: January 2022

Background. Sugar-added diet has been associated with increased risk of developing dental caries. Objective. To investigate the dietary determinants of caries prevalence and experience based on the frequency versus the quantity of consumption among Saudi schoolchildren. Methods. This is a cross-sectional study that invited 12- to 15-year-old intermediate school students (N = 3000) in four cities in the Eastern Province of Saudi Arabia. Data collection comprised a pretested questionnaire and clinical examination. Caries was diagnosed based on the World Health Organization (WHO) criteria and was recorded as a decayed, missing, filled tooth (DMFT). The questionnaire included questions regarding the consumption of different quantities and frequencies of multiple sugar-containing food items. Multiple logistic and linear regression models were used to assess the influence of sugar-containing food on the dental caries experience (DMFT) and prevalence of decayed teeth. SPSS version 20.0 was used to analyze the data at 5% significance level. Results. Of 3000 invited students, 2262 participated with a participation rate of 75.4%. Our study found that the frequency of soft drink consumption was significantly associated with increased caries prevalence (adjusted OR = 1.33, 95% CI 1.07–1.65) and experience (adjusted B = 0.46, 95% CI 0.16–0.76). The frequency of consumption of fruit juice was statistically significantly associated with increased caries experience (adjusted B = 0.48, 95% CI 0.16–0.79). The interaction terms between the frequency and the quantity of consumption of energy drinks, soft drinks, and sweetened milk were statistically significantly related to caries experience and prevalence. Conclusion. Although the frequency of consumption of sugar-containing drinks was more associated with caries experience and prevalence, the interaction between frequency and quantity was highly related to the prevalence and experience of dental caries.
Clinical Analysis of Single and Double Sacroiliac Screws in the Treatment of Tile C1 Pelvic Fracture
Authors: Deng Hong-Li , Li Dong-Yang , Cong Yu-Xuan , Zhang Bin-Fei , Lei Jin-Lai , Wang Hu , Wang Peng-Fei , Zhuang Yan
Published: January 2022

We investigated the difference between fixation of single and double sacroiliac screws in the treatment of Tile C1 pelvic fractures. The data of 54 patients with Tile C1 pelvic fractures who were admitted to the trauma center of the Red Society Hospital Affiliated to Xi’an Jiaotong University between August 2016 and August 2020 were retrospectively analyzed. All patients with posterior pelvic ring injuries underwent fixation with sacroiliac screws assisted by a percutaneous robotic navigation system. The operative time, amount of intraoperative blood loss, and postoperative follow‐up time between the two groups (single sacroiliac and double sacroiliac screw groups) were compared. The Matta and Majeed scores at the last follow‐up were compared between the groups to evaluate fracture reduction and functional recovery. Forty‐nine patients were followed up for 17.2 (±4.5) months and 16.2 (±3.4) months in the single and double sacroiliac screw groups, respectively. All patients had excellent fracture reduction immediately after surgery, according to the Matta score. All fractures healed without complications. There was no statistically significant difference in preoperative general information, amount intraoperative blood loss, intraoperative anterior ring fixation method, and postoperative follow‐up time between the two groups (P > 0.05). The operative time of the single sacroiliac screw group was shorter than that of the double sacroiliac screw group (P < 0.05). At the last follow‐up, the Matta score of the double sacroiliac screw group was significantly better than that of the single sacroiliac screw group (P < 0.05), and there was no statistically significant difference in the Majeed functional scores (P > 0.05). For Tile C1 pelvic fractures, double sacroiliac screw fixation of posterior ring injuries can provide a more stable treatment with no statistically significant difference in functional recovery.
Study on the Mechanism of Compound Kidney-Invigorating Granule for Osteoporosis based on Network Pharmacology and Experimental Verification
Authors: Lv Hao , Wang Jiuxiang , Zhu Yujun , Jiang Ting
Published: January 2022

Background. This study used a combination of network pharmacology and experimental confirmation to clarify the mechanism of the compound kidney-invigorating granule (CKG) in treating osteoporosis (OP). Methods. The main bioactive compounds and corresponding targets of CKG were collected and screened via the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), Yet another Traditional Chinese Medicine (YaTCM), and UniProt databases. Disease targets of OP were summarized in GeneCards and the Comparative Toxicogenomics Database (CTD). Targets of CKG for OP were obtained by Venn diagram. The protein-protein interaction (PPI) network was constructed by the STRING database and then screened for hub genes through Cytoscape 3.7.2 software. The Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment were analyzed and visualized by R software. Then, CB-Dock was used for molecular docking verification. Finally, we confirmed the antiosteoporosis effect of CKG through animal and cell experiments. Results. A total of 250 putative targets were obtained from 65 bioactive compounds in CKG. Among them, 140 targets were related to OP. Topological analysis of the PPI network yielded 23 hub genes. Enrichment analysis showed the targets of CKG in treating OP might concentrate on the MAPK signaling pathway, the TNF signaling pathway, the PI3K-Akt signaling pathway, etc. The results of molecular docking showed the bioactive components in CKG had good binding ability with the key targets. The experimental results showed that CKG-medicated serum had a promoting effect on proliferating hBMSCs, increasing the expression of AKT, PI3K, ERK1, and IkB in cells and decreasing the expression of IKK in cells. Conclusion. CKG has a complex of multicomponent, multitarget, and multipathway. This study lays the theoretical foundation for further in vitro and in vivo experimental studies and further expands the clinical applications of CKG.
Scutellariae Radix and Citri Reticulatae Pericarpium Mixture Regulate PPARγ/RXR Signaling in Reflux Esophagitis
Authors: Lee Jin A. , Shin Mi-Rae , Park Hae-Jin , Roh Seong-Soo
Published: January 2022

Objective. Gastroesophageal reflux disease (GERD) is a gastrointestinal disorder in which stomach contents reflux into the esophagus, causing complications such as mucosal damage. GERD is a very common disease and is on the rise worldwide. The aim of this study was to assess the impact of a Scutellariae Radix and Citri Reticulatae Pericarpium mixture (SC) on esophageal mucosal injury in rats with chronic acid reflux esophagitis (CARE). Methods. After inducing reflux esophagitis through surgery, the group was separated and the drug was administered for 2 weeks: normal rats (Normal, n = 8), CARE-induced rats were treated with distilled water (Control, n = 8), CARE-induced rats were treated with vitamin E 30 mg/kg body weight (VitE, n = 8), CARE-induced rats were treated with SC 100 mg/kg body weight (SC100, n = 8), and CARE-induced rats were treated with SC 200 mg/kg body weight (SC200, n = 8). Results. SC treatment significantly reduced the degree of esophageal mucosal damage, significantly reduced levels of MDA and MPO, and inhibited the activation of the NF-κB inflammatory pathway by activating the PPARγ/RXR pathway. In addition, SC treatment significantly regulated the expression of arachidonic acid-related proteins (COX-1, COX-2, and PGE2) and modulated the MMP/TIMP proteins in reflux esophagitis. Conclusion. Consequently, SC improved the damage to the esophageal mucosa. Also, the anti-inflammatory effects of the SC suggested the inhibition of NF-κB pathway through the activation of the PPARγ/RXR pathway, thereby reducing the expression of inflammation-related cytokines.
Encryption Management of Accounting Data Based on DES Algorithm of Wireless Sensor Network
Authors: Lu Zixin
Published: January 2022

The emergence of wireless sensor networks connects the physical world with the information world and changes the way humans interact with nature. With the rapid development of modern information technology, accounting information systems (AIS) have emerged at the historic moment. Under the information environment, accounting data exists in paper or paperless form. The use of information technology not only brings convenient and efficient services to enterprises but also has a huge impact on the internal control of the enterprise. Because the network is open and unstable, the system is vulnerable to illegal intrusion and viruses. Based on the above background, the research content of this article is to use DES algorithm to encrypt accounting data. DES (Data Encryption Standard) encryption algorithm is a symmetric password encryption method. It has the advantages of fast encryption speed, simple and practical algorithm, and consideration of both security and efficiency requirements. This paper discusses the application of DES encryption technology to accounting data processing. To achieve data security management goals. Therefore, this paper proposes a DES algorithm based on the logistic chaotic system. Through experimental simulation, the results show that the chaotic discrete model has initial value sensitivity and iterative nonrepetition. The resulting key space is independent and random. In the application, you can perform random key input according to the performance of software and hardware, which is flexible; there is only one “1186828” in the initial DES algorithm encryption process, but each set of plain text in the improved DES algorithm corresponds to a corresponding set of keys and independence. The test results show that they are maintained between 5 and 6.6. It is proved that using the initial value sensitivity of the logistic system and using the initial value as the key can realize the secure management of accounting data on the premise of ensuring efficiency.
Evaluation of the Effects of Processing Technique on Chemical Components in Raphani Semen by HPLC and UPLC-Q-TOF-MS
Authors: Gao Sijia , Wang Jirui , Cheng Lei , Fan Yuxin , Qin Weihan , Wang Yunhong , Guo Yanlei , Zhang Xiaomei , Yang Yong
Published: January 2022

In this study, the effects of different processing techniques on the chemical components of Raphani Semen (RS) were evaluated. An established high-performance liquid chromatography (HPLC) method was adopted for the simultaneous determination of glucoraphanin, sinapine thiocyanate, raphanin, and erucic acid in the fried products of Raphani Semen to evaluate the chemical changes during frying processing as well as optimize the best frying technology of Raphani Semen. Then, the chemical components in the fried Raphani Semen were identified by ultrahigh-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS). A total of 54 compounds in processed Raphani Semen were identified by UPLC-Q-TOF-MS. The results showed that the content of glucoraphanin and sinapine thiocyanate was the highest in the fried products at 130°C for 10 min, and the effect of “Enzyme Killing and Glycosides Preserving” was the best. Therefore, this condition was chosen as the best frying technology of Raphani Semen. This study provided a more scientific basis for evaluation of the quality of Raphani Semen fried products and optimization of the frying technology of Raphani Semen.
Hemodynamic Analysis of Pipeline Embolization Device Stent for Treatment of Giant Intracranial Aneurysm under Unsupervised Learning Algorithm
Authors: Gao Haibin , You Wei , Lv Jian , Li Youxiang
Published: January 2022

To treat large intracranial aneurysms, pipeline embolization device (PED) stent with unsupervised learning algorithms was utilized. Unsupervised learning model algorithm was used to screen aneurysm health big data, find aneurysm blood flow and PED stent positioning characteristic parameters, and guide PED stent treatment of intracranial aneurysms. The research objects were 100 patients with intracranial large aneurysm admitted to X Hospital of X Province from June 2020 to June 2021, who were enrolled into two groups. One group used the prototype transfer generative adversarial network (PTGAN) model to measure mean blood flow and mean vascular pressure and guide the placement of PED stents (PTGAN group). The other group did not use the model to place PED (control group). The PTGAN model can learn feature information from horizontal and vertical directions, with smooth edges and prominent features, which can effectively extract the main morphological and texture features of aneurysms. Compared with the convolutional neural network (CNN) model, the accuracy of the PTGAN model increased by 8.449% (87.452%–79.003%), and the precision increased by 8.347% (91.23%–82.883%). The recall rate increased by 7.011% (87.231%–80.22%), and the F1 score increased by 8.09% (89.73%–81.64%). After the adoption of the PTGAN model, the average blood flow inside the aneurysm body was 0.22 (m/s). After the adoption of the CNN model, the average blood flow inside the aneurysm body was 0.21 (m/s), and the difference was 0.01 (m/s), which was considerable (

p
<
0.05

). Through this research, it was found that the PTGAN model was better than the CNN model in terms of accuracy, precision, recall, and F1 score values. The PTGAN model was better than the CNN model in detecting the average blood flow rate and average blood pressure after treatment, and the blood flowed smoothly. Postoperative complications and postoperative relief were also better than those of the control group. In summary, based on the unsupervised learning algorithm, the PED stent had a good adoption effect in the treatment of intracranial aneurysms and was suitable for subsequent treatment.
Exploring the Mechanism of Edaravone for Oxidative Stress in Rats with Cerebral Infarction Based on Quantitative Proteomics Technology
Authors: Wang Guozuo , Zeng Xiaomei , Gong Shengqiang , Wang Shanshan , Ge Anqi , Liu Wenlong , Ge Jinwen , He Qi
Published: January 2022

Objective. To explore the mechanism of edaravone in the treatment of oxidative stress in rats with cerebral infarction based on quantitative proteomics technology. Method. The modified Zea Longa intracavitary suture blocking method was utilized to make rat CI model. After modeling, the rat was intragastrically given edaravone for 7 days, once a day. After the 7-day intervention, the total proteins of serum were extracted. After proteomics analysis, the differentially expressed proteins are analyzed by bioinformatics. Then chemoinformatics methods were used to explore the biomolecular network of edaravone intervention in CI. Result. The neurological scores and pathological changes of rats were improved after the intervention of edaravone. Proteomics analysis showed that in the model/sham operation group, 90 proteins in comparison group were upregulated, and 26 proteins were downregulated. In the edaravone/model group, 21 proteins were upregulated, and 41 proteins were downregulated. Bioinformatics analysis and chemoinformatics analysis also show that edaravone is related to platelet activation and aggregation, oxidative stress, intercellular adhesion, glycolysis and gluconeogenesis, iron metabolism, hypoxia, inflammatory chemokines, their mediated signal transduction, and so on. Conclusion. The therapeutic mechanism of edaravone in the treatment of CI may involve platelet activation and aggregation, oxidative stress, intercellular adhesion, glycolysis and gluconeogenesis, iron metabolism, hypoxia, and so on. This study revealed the serum protein profile of edaravone in the treatment of cerebral infarction rats through serum TMT proteomics and discovered the relevant mechanism of edaravone regulating iron metabolism in cerebral infarction, which provides new ideas for the study of edaravone intervention in cerebral infarction and also provides reference information for future research on the mechanism of edaravone intervention in iron metabolism-related diseases.
Social Media Analytics for Pharmacovigilance of Antiepileptic Drugs
Authors: Yahya Anwar Ali , Asiri Yousef , Alyami Ibrahim
Published: January 2022

Epilepsy is a common neurological disorder worldwide and antiepileptic drug (AED) therapy is the cornerstone of its treatment. It has a laudable aim of achieving seizure freedom with minimal, if any, adverse drug reactions (ADRs). Too often, AED treatment is a long-lasting journey, in which ADRs have a crucial role in its administration. Therefore, from a pharmacovigilance perspective, detecting the ADRs of AEDs is a task of utmost importance. Typically, this task is accomplished by analyzing relevant data from spontaneous reporting systems. Despite their wide adoption for pharmacovigilance activities, the passiveness and high underreporting ratio associated with spontaneous reporting systems have encouraged the consideration of other data sources such as electronic health databases and pharmaceutical databases. Social media is the most recent alternative data source with many promising potentials to overcome the shortcomings of traditional data sources. Although in the literature some attempts have investigated the validity and utility of social media for ADR detection of different groups of drugs, none of them was dedicated to the ADRs of AEDs. Hence, this paper presents a novel investigation of the validity and utility of social media as an alternative data source for the detection of AED ADRs. To this end, a dataset of consumer reviews from two online health communities has been collected. The dataset is preprocessed; the unigram, bigram, and trigram are generated; and the ADRs of each AED are extracted with the aid of consumer health vocabulary and ADR lexicon. Three widely used measures, namely, proportional reporting ratio, reporting odds ratio, and information component, are used to measure the association between each ADR and AED. The resulting list of signaled ADRs for each AED is validated against a widely used ADR database, called Side Effect Resource, in terms of the precision of ADR detection. The validation results indicate the validity of online health community data for the detection of AED ADRs. Furthermore, the lists of signaled AED ADRs are analyzed to answer questions related to the common ADRs of AEDs and the similarities between AEDs in terms of their signaled ADRs. The consistency of the drawn answers with the existing pharmaceutical knowledge suggests the utility of the data from online health communities for AED-related knowledge discovery tasks.
A Weighted Statistical Network Modeling Approach to Product Competition Analysis
Authors: Cui Yaxin , Ahmed Faez , Sha Zhenghui , Wang Lijun , Fu Yan , Contractor Noshir , Chen Wei
Published: January 2022

Statistical network models have been used to study the competition among different products and how product attributes influence customer decisions. However, in existing research using network‐based approaches, product competition has been viewed as binary (i.e., whether a relationship exists or not), while in reality, the competition strength may vary among products. In this paper, we model the strength of the product competition by employing a statistical network model, with an emphasis on how product attributes affect which products are considered together and which products are ultimately purchased by customers. We first demonstrate how customers’ considerations and choices can be aggregated as weighted networks. Then, we propose a weighted network modeling approach by extending the valued exponential random graph model to investigate the effects of product features and network structures on product competition relations. The approach that consists of model construction, interpretation, and validation is presented in a step‐by‐step procedure. Our findings suggest that the weighted network model outperforms commonly used binary network baselines in predicting product competition as well as market share. Also, traditionally when using binary network models to study product competitions and depending on the cutoff values chosen to binarize a network, the resulting estimated customer preferences can be inconsistent. Such inconsistency in interpreting customer preferences is a downside of binary network models but can be well addressed by the proposed weighted network model. Lastly, this paper is the first attempt to study customers’ purchase preferences (i.e., aggregated choice decisions) and car competition (i.e., customers’ co‐consideration decisions) together using weighted directed networks.
On the Safe‐Haven Ability of Bitcoin, Gold, and Commodities for International Stock Markets: Evidence from Spillover Index Analysis
Authors: Wang Qian , Wei Yu , Wang Yao , Liu Yuntong
Published: January 2022

Stock market is susceptible to various external shocks for its tight dependence on economic fundamentals, financial speculation, and fragile emotions in massive traders, making it a very risky market for investors. In this paper, we aim to identify whether commonly recognized safe‐haven assets, that is, bitcoin, gold, and commodities, can provide investors with effective hedging utility in international stock markets, especially during periods of extreme market turbulence. By using the spillover index method based on the TVP‐VAR model, we find that firstly, bitcoin, gold, and commodities can only offer weak hedging effects on stock markets. Furthermore, their abilities to act as a safe haven are ranked as: commodities > gold > bitcoin. Secondly, in general, we have observed the increasing hedging ability of these safe‐haven assets in times of extreme market turmoil. Thirdly, among international stock and safe‐haven asset markets, the world and the developed stock markets act as the net spillover transmitters, while bitcoin, gold, and commodities are the net recipients. Lastly, the total spillover effects are time‐varying and increase significantly after the outbreak of extreme events.
An Ensembled Spatial Enhancement Method for Image Enhancement in Healthcare
Authors: Siddiqi Muhammad Hameed , Alsirhani Amjad
Published: January 2022

Most medical images are low in contrast because adequate details that may prove vital decisions are not visible to the naked eye. Also, due to the low-contrast nature of the image, it is not easily segmented because there is no significant change between the pixel values, which makes the gradient very small Hence, the contour cannot converge on the edges of the object. In this work, we have proposed an ensembled spatial method for image enhancement. In this ensembled approach, we first employed the Laplacian filter, which highlights the areas of fast intensity variation. This filter can determine the sufficient details of an image. The Laplacian filter will also improve those features having shrill disjointedness. Then, the gradient of the image has been determined, which utilizes the surrounding pixels for the weighted convolution operation for noise diminishing. However, in the gradient filter, there is one negative integer in the weighting. The intensity value of the middle pixel might be deducted from the surrounding pixels, to enlarge the difference between the head-to-head pixels for calculating the gradients. This is one of the reasons due to which the gradient filter is not entirely optimistic, which may be calculated in eight directions. Therefore, the averaging filter has been utilized, which is an effective filter for image enhancement. This approach does not rely on the values that are completely diverse from distinctive values in the surrounding due to which it recollects the details of the image. The proposed approach significantly showed the best performance on various images collected in dynamic environments.
A Lightweight Authentication Scheme Based on Consortium Blockchain for Cross-Domain IoT
Authors: Zhang Yujian , Luo Yuhao , Chen Xing , Tong Fei , Xu Yuwei , Tao Jun , Cheng Guang
Published: January 2022

Internet of Things (IoT) has been ubiquitous in both industrial and living areas, but also known for its weak security. Being as the first defense line against various cyberattacks, authentication is even more critical to IoT applications. Moreover, there has been a growing demand for cross-domain collaboration, leading to an increasing need for cross-domain authentication. Recently, certificate-based authentication schemes have been extensively studied. However, many of these schemes are not efficient in computation, storage, and communication, which are highly required in IoT. In this paper, we propose a lightweight authentication scheme based on consortium blockchain and design a cryptocurrency-like digital token to build trust. Furthermore, trust lifecycle management is performed by manipulating the amount of tokens. The comprehensive analysis and evaluation demonstrate that the proposed scheme is resistant to various common attacks and more efficient than competitor schemes in terms of storage, communication, and authentication cost.
[Retracted] Construction and Empirical Study of Learner Portrait in Online General Education Course
Authors: Zhang Zongbiao
Published: January 2022

The problems of high course selection rate, low completion rate, and insufficient pertinence of learning support services in online general education courses are the focus of current general education researchers. Based on 3P (presage, process, and product) learning theory, we put forward a “three‐stage, four‐level” framework for learners’ portrait process of online general education course, including three learning stages of “presage process product” and four levels of “portrait goal, data collection, label analysis, and portrait service.” Then, taking the learners of the online general education course of Zhejiang Shuren College as an example, we make a case analysis based on the portrait framework, evaluate the learning effect from different stages, and put forward targeted teaching strategies and measures. Research results show that the proposed framework can reflect the characteristics of online learning experience, online learning investment, and online learning results of high‐risk learners and can provide data support for the design of online learning support services and optimizing learning effects.
BRAF Mutations: The Discovery of Allele- and Lineage-Specific Differences
Authors: Hanrahan Aphrothiti J. , Solit David B.
Published: January 2022

Cancer treatment is increasingly guided by molecular analyses designed to identify clinically actionable genomic alterations in individual patients. The discovery of BRAF mutations in human cancer, and the subsequent development and FDA authorization of selective BRAF inhibitors highlight the potential clinical impact and current limitations of precision oncology paradigms. In 2002, Brose and colleagues reported that the distribution of BRAF mutations differed in melanoma and lung cancer and that not all BRAF mutations were functionally equivalent. Here, we discuss this landmark paper, which foreshadowed subsequent research elucidating how biochemical differences among mutant alleles within the same gene and lineage-specific differences among cancer types impact drug sensitivity. Such translational studies provided a road map for the development of novel RAF inhibitors and rational combination strategies that promise greater clinical activity and/or more favorable toxicity profiles.

See related article by Brose and colleagues, Cancer Res 2002;62:6997–7000
Engineering Principles for Synthetic Biology Circuits in Cancer Immunotherapy
Authors: Shih Ryan M. , Chen Yvonne Y.
Published: January 2022

Recent advances in biomolecular engineering have led to novel cancer immunotherapies with sophisticated programmed functions, including chimeric antigen receptor (CAR) T cells that bind tumor-associated antigens (TAA) to direct coordinated immune responses. Extensive engineering efforts have been made to program not only CAR specificity, but also downstream pathways that activate molecular responses. Collectively, these efforts can be conceptualized as an immunotherapy circuit: TAAs bind the CAR as input signals; intracellular signaling cascades process the binding interactions into transcriptional and translational events; and those events program effector output functions. More simply, this sequence may be abstracted as input, processing, and output. In this review, we discuss the increasingly complex scene of synthetic-biology solutions in cancer immunotherapy and summarize recent work within the framework of immunotherapy circuits. In doing so, a toolbox of basic modular circuits may be established as a foundation upon which sophisticated solutions can be constructed to meet more complex problems.

See related article on p. 5.
Frequency response analysis under faults in weak power systems
Authors: Arcia Marino Godoy , Sanchez Zaid Garcia , Hernandez Herrera Hernan , Cueto Cruz José Antonio Gonzalez , Silva Ortega Jorge Iván , Sánchez Gustavo Crespo
Published: January 2022

The renewable energy sources (RESs) projects are solutions with environmental benefits that are changing the traditional power system operation and concept. Transient stability analysis has opened new research trends to guarantee a secure operation high penetration. Problems such as frequency fluctuations, decoupling between generator angular speed, network frequency fluctuation and kinetic energy storing absence are the main non-conventional RESs penetration in power systems. This paper analyzes short-circuit influence on frequency response, focusing on weak distribution networks and isolated, to demonstrate relevance in frequency stability. A study case considered a generation outage and a load input to analyze frequency response. The paper compares frequency response during a generation outage with a short-circuit occurrence. In addition, modular value and angle generator terminal voltage affectation by electric arc and network ratio R⁄X, failure type influence in power delivered behavior, considering fault location, arc resistance and load. The arc resistance is defined as an added resistance that appears during failure and influences voltage modulus and angle value results showing that intermittent non-conventional RES participation can lead to frequency fluctuations. Results showed that arc resistance, type of failure, location and loadability determine the influence of frequency response factors in weak power systems.
A new high speed charge and high efficiency Li-Ion battery charger interface using pulse control technique
Authors: El Alaoui Mustapha , El Khadiri Karim , El Alami Rachid , Tahiri Ahmed , Lakhssassi Ahmed , Qjidaa Hassan
Published: January 2022

A new Li-Ion battery charger interface (BCI) using pulse control (PC) technique is designed and analyzed in this paper. Thanks to the use of PC technique, the main standards of the Li-Ion battery charger, i.e. fast charge, small surface area and high efficiency, are achieved. The proposed charger achieves full charge in forty-one minutes passing by the constant current (CC) charging mode which also included the start-up and the constant voltage mode (CV) charging mode. It designed, simulated and layouted which occupies a small size area 0.1 mm2 by using Taiwan Semiconductor Manufacturing Company 180 nm complementary metal oxide semi-conductor technology (TSMC 180 nm CMOS) technology in Cadence Virtuoso software. The battery voltage VBAT varies between 2.9 V to 4.35 V and the maximum battery current IBAT is 2.1 A in CC charging mode, according to a maximum input voltage VIN equal 5 V. The maximum charging efficiency reaches 98%.
Reliability improvement and loss reduction in radial distribution system with network reconfiguration algorithms using loss sensitivity factor
Authors: Devi Parasa Sushma , Kumar Dasari Ravi , Chakravarthula Kiran
Published: January 2022

Studies on load flow in electrical distribution system have always been an area of interest for research from the previous few years. Various approaches and techniques are brought into light for load flow studies within the system and simulation tools are being used to work out on varied characteristics of system. This study concentrates on these approaches and the improvements made to the already existing techniques considering time and the algorithms complexity. Also, the paper explains the network reconfiguration (NR) techniques considered in reconfiguring radial distribution network (RDN) to reduce power losses in distribution system and delivers an approach to how various network reconfiguration techniques support loss reduction and improvement of reliability in the electrical distribution network.
Input-output linearization of DC-DC converter with discrete sliding mode fuzzy control strategy
Authors: Karthikeyan Viji , Tiwari Anil Kumar , Vedi Agalya , Devaraju Buvana
Published: January 2022

The major thrust of the paper is on designing a fuzzy logic approach has been combined with a well-known robust technique discrete sliding mode control (DSMC) to develop a new strategy for discrete sliding mode fuzzy control (DSMFC) in direct current (DC-DC) converter. Proposed scheme requires human expertise in the design of the rule base and is inherently stable. It also overcomes the limitation of DSMC, which requires bounds of uncertainty to be known for development of a DSMC control law. The scheme is also applicable to higher order systems unlike model following fuzzy control, where formation of rule base becomes difficult with rise in number of error and error derivative inputs. In this paper the linearization of input-output performance is carried out by the DSMFC algorithm for boost converter. The DSMFC strategy minimizes the chattering problem faced by the DSMC. The simulated performance of a discrete sliding mode fuzzy controller is studied and the results are investigated.
High-performance FPGA implementation of the secure hash algorithm 3 for single and multi-message processing
Authors: Assad Fatimazahraa , Fettach Mohamed , El Otmani Fadwa , Tragha Abderrahim
Published: January 2022

The secure hash function has become the default choice for information security, especially in applications that require data storing or manipulation. Consequently, optimized implementations of these functions in terms of Throughput or Area are in high demand. In this work we propose a new conception of the secure hash algorithm 3 (SHA-3), which aim to increase the performance of this function by using pipelining, four types of pipelining are proposed two, three, four, and six pipelining stages. This approach allows us to design data paths of SHA-3 with higher Throughput and higher clock frequencies. The design reaches a maximum Throughput of 102.98 Gbps on Virtex 5 and 115.124 Gbps on Virtex 6 in the case of the 6 stages, for 512 bits output length. Although the utilization of the resource increase with the increase of the number of the cores used in each one of the cases. The proposed designs are coded in very high-speed integrated circuits program (VHSIC) hardware description language (VHDL) and implemented in Xilinx Virtex-5 and Virtex-6 A field-programmable gate array (FPGA) devices and compared to existing FPGA implementations.
Method of optimization of the fundamental matrix by technique speeded up robust features application of different stress images
Authors: Chater Ahmed , Benradi Hicham , Lasfar Abdelali
Published: January 2022

The purpose of determining the fundamental matrix (F) is to define the epipolar geometry and to relate two 2D images of the same scene or video series to find the 3D scenes. The problem we address in this work is the estimation of the localization error and the processing time. We start by comparing the following feature extraction techniques: Harris, features from accelerated segment test (FAST), scale invariant feature transform (SIFT) and speed-up robust features (SURF) with respect to the number of detected points and correct matches by different changes in images. Then, we merged the best chosen by the objective function, which groups the descriptors by different regions in order to calculate ‘F’. Then, we applied the standardized eight-point algorithm which also automatically eliminates the outliers to find the optimal solution ‘F’. The test of our optimization approach is applied on the real images with different scene variations. Our simulation results provided good results in terms of accuracy and the computation time of ‘F’ does not exceed 900 ms, as well as the projection error of maximum 1 pixel, regardless of the modification.
An effective method for clustering-based web service recommendation
Authors: Cuong Nguyen Ha Huy , Khiet Bui Thanh , Nguyen Van Loi , Nguyen Thanh Thuy
Published: January 2022

Normally web services are classified by the quality of services; however, the term quality is not absolute and defined relatively. The quality of web services is measured or derived using various parameters like reliability, scalability, flexibility, and availability. The limitation of the methods employing these parameters is that sometimes they are producing similar web services in recommendation lists. To address this research problem, the novel improved clustering-based web service recommendation method is proposed in this paper. This approach is mainly dealing with producing diversity in the results of web service recommendations. In this method, functional interest, quality of service (QoS) preference, and diversity features are combined to produce a unique recommendation list of web services to end-users. To produce the unique recommendation results, we propose a varied web service classification order that is clustering-based on web services’ functional relevance such as non-useful pertinence, recorded client intrigue importance, and potential client intrigue significance. Additionally, to further improve the performance of this approach, we designed web service graph construction, an algorithm of various widths clustering. This approach serves to enhance the exceptional quality, that is, the accuracy of web service recommendation outcomes. The performance of this method was implemented and evaluated against existing systems for precision, and f-score performance metrics, using the research datasets.
Flight-schedule using Dijkstra's algorithm with comparison of routes findings
Authors: Salem Israa Ezzat , Mijwil Maad M. , Abdulqader Alaa Wagih , Ismaeel Marwa M.
Published: January 2022

The Dijkstra algorithm, also termed the shortest-route algorithm, is a model that is categorized within the search algorithms. Its purpose is to discover the shortest-route, from the beginning node (origin node) to any node on the tracks, and is applied to both directional and undirected graphs. However, all edges must have non-negative values. The problem of organizing inter-city flights is one of the most important challenges facing airplanes and how to transport passengers and commercial goods between large cities in less time and at a lower cost. In this paper, the authors implement the Dijkstra algorithm to solve this complex problem and also to update it to see the shortest-route from the origin node (city) to the destination node (other cities) in less time and cost for flights using simulation environment. Such as, when graph nodes describe cities and edge route costs represent driving distances between cities that are linked with the direct road. The experimental results show the ability of the simulation to locate the most cost-effective route in the shortest possible time (seconds), as the test achieved 95% to find the suitable route for flights in the shortest possible time and whatever the number of cities on the tracks application.
Medium access control protocol design for wireless communications and networks review
Authors: Jaber Zaid Hashim , Kadhim Dheyaa Jasim , Al-Araji Ahmed Sabah
Published: January 2022

Medium access control (MAC) protocol design plays a crucial role to increase the performance of wireless communications and networks. The channel access mechanism is provided by MAC layer to share the medium by multiple stations. Different types of wireless networks have different design requirements such as throughput, delay, power consumption, fairness, reliability, and network density, therefore, MAC protocol for these networks must satisfy their requirements. In this work, we proposed two multiplexing methods for modern wireless networks: Massive multiple-input-multiple-output (MIMO) and power domain non-orthogonal multiple access (PD-NOMA). The first research method namely Massive MIMO uses a massive number of antenna elements to improve both spectral efficiency and energy efficiency. On the other hand, the second research method (PD-NOMA) allows multiple non-orthogonal signals to share the same orthogonal resources by allocating different power level for each station. PD-NOMA has a better spectral efficiency over the orthogonal multiple access methods. A review of previous works regarding the MAC design for different wireless networks is classified based on different categories. The main contribution of this research work is to show the importance of the MAC design with added optimal functionalities to improve the spectral and energy efficiencies of the wireless networks.
Quality of experience aware network selection model for service provisioning in heterogeneous network
Authors: Gadde Nagaraja , Jakkali Basavaraj , Halasinanagenahalli Siddamallaih Ramesh Babu , Gowrishankar Gowrishankar
Published: January 2022

Heterogeneous wireless networks (HWNs) are capable of integrating the different radio access technologies that make it possible to connect mobile users based on the performance parameters. Further quality of service (QoS) is one of the major topics for HWNs, moreover existing radio access technology (RAT) methodology are designed to provide network QoS criteria. However, limited work has been carried out for the RAT selection mechanism considering user QoS preference and existing models are developed based on the multi-mode terminal under a given minimal density network. For overcoming research issues this paper present quality of experience (QoE) RAT (QOE-RAT) selection methodology, incorporating both network performance criteria and user preference considering multiple call and multi-mode HWNs environment. First, this paper presents fuzzy preference aware weight (FPAW) and multi-mode terminal preference aware TOPSIS (MMTPA-TOPSIS) for choosing the best RAT for gaining multi-services. Experiment outcomes show the QOE-RAT selection method achieves much superior packet transmission outcomes when compared with state-of-art Rat selection methodologies.
Crop leaf disease detection and classification using machine learning and deep learning algorithms by visual symptoms: a review
Authors: Vasavi Pallepati , Punitha Arumugam , Narayana Rao T. Venkat
Published: January 2022

A Quick and precise crop leaf disease detection is important to increasing agricultural yield in a sustainable manner. We present a comprehensive overview of recent research in the field of crop leaf disease prediction using image processing (IP), machine learning (ML) and deep learning (DL) techniques in this paper. Using these techniques, crop leaf disease prediction made it possible to get notable accuracies. This article presents a survey of research papers that presented the various methodologies, analyzes them in terms of the dataset, number of images, number of classes, algorithms used, convolutional neural networks (CNN) models employed, and overall performance achieved. Then, suggestions are prepared on the most appropriate algorithms to deploy in standard, mobile/embedded systems, Drones, Robots and unmanned aerial vehicles (UAV). We discussed the performance measures used and listed some of the limitations and future works that requires to be focus on, to extend real time automated crop leaf disease detection system.
Using deep learning to detecting abnormal behavior in internet of things
Authors: Al-Shabi Mohammed , Abuhamdah Anmar
Published: January 2022

The development of the internet of things (IoT) has increased exponentially, creating a rapid pace of changes and enabling it to become more and more embedded in daily life. This is often achieved through integration: IoT is being integrated into billions of intelligent objects, commonly labeled “things,” from which the service collects various forms of data regarding both these “things” themselves as well as their environment. While IoT and IoT-powered decices can provide invaluable services in various fields, unauthorized access and inadvertent modification are potential issues of tremendous concern. In this paper, we present a process for resolving such IoT issues using adapted long short-term memory (LSTM) recurrent neural networks (RNN). With this method, we utilize specialized deep learning (DL) methods to detect abnormal and/or suspect behavior in IoT systems. LSTM RNNs are adopted in order to construct a high-accuracy model capable of detecting suspicious behavior based on a dataset of IoT sensors readings. The model is evaluated using the Intel Labs dataset as a test domain, performing four different tests, and using three criteria: F1, Accuracy, and time. The results obtained here demonstrate that the LSTM RNN model we create is capable of detecting abnormal behavior in IoT systems with high accuracy.