bluuebunny/crossref_metadata_2025 huggingface dataset:
Chlorogenic Acid Inhibits Lipid Deposition by Regulating the Enterohepatic FXR‐FGF15 Pathway
Authors: Ye Xiaolin , Li Jing , Gao Zhe , Wang Dongwei , Wang Hongyu , Wu Jie
Published: February 2022

Aim. Chlorogenic acid (CGA) is a natural polyphenolic compound found in human dietary products. Previous studies have confirmed that CGA has many biological activities, such as regulating glucose and lipid metabolism and improving insulin resistance. However, its underlying mechanisms of action remains unclear. Here, we demonstrate the protective effects and molecular mechanisms of action of CGA in reducing weight gain and hyperlipidemia in mice fed with a high‐fat diet (HFD). Methods and Results. C57BL/6 mice were fed with normal chow or HFD; half of the mice in each group received CGA treatment by oral gavage for 16 weeks. CGA treatment was found to significantly inhibit HFD‐induced weight gain and hyperlipidemia and increased energy expenditure by promoting the expression of genes involved in thermogenesis and mitochondrial biogenesis. Furthermore, CGA was shown to inhibit the enterohepatic farnesoid X receptor (FXR) fibroblast growth factor 15 (FGF15) pathway and changes serum bile acid (BA) pool, thereby contributing to the increased expression of cholesterol 7 α‐hydroxylase (CYP7A1). Conclusions. CGA increases the metabolic elimination of cholesterol by inhibiting the enterohepatic FXR/FGF15 pathway.
Advances in Key Drug Target Identification and New Drug Development for Tuberculosis
Authors: Mi Jie , Gong Wenping , Wu Xueqiong
Published: February 2022

Tuberculosis (TB) is a severe infectious disease worldwide. The increasing emergence of drug‐resistant Mycobacterium tuberculosis (Mtb) has markedly hampered TB control. Therefore, there is an urgent need to develop new anti‐TB drugs to treat drug‐resistant TB and shorten the standard therapy. The discovery of targets of drug action will lay a theoretical foundation for new drug development. With the development of molecular biology and the success of Mtb genome sequencing, great progress has been made in the discovery of new targets and their relevant inhibitors. In this review, we summarized 45 important drug targets and 15 new drugs that are currently being tested in clinical stages and several prospective molecules that are still at the level of preclinical studies. A comprehensive understanding of the drug targets of Mtb can provide extensive insights into the development of safer and more efficient drugs and may contribute new ideas for TB control and treatment.
Study on the Equivalence of Penetration Overloading for Projectile-Borne Components in Nonproportional Penetrators
Authors: Yan Amin , Pi Aiguo , Yang He , Huang Fenglei , Wang Xiaofeng
Published: February 2022

The reliability assessment of the projectile-borne components in a high-speed penetrator is an important issue in the penetration field. In this study, a scaling model embedded with a deceleration measurement device was used to investigate the overloading situation due to the high cost of the prototype test. The projectile could be scaled, while the deceleration measurement device needs to maintain full scale. Thus, a nonproportional scaling design is proposed to represent the rigid-body deceleration of the prototype projectile. This study, considering the mass of the deceleration measurement device, lays out the design criteria of the scaling model and carries out rigid-body deceleration similarity verification tests of the prototype and the scaling model. In addition, the rigid-body deceleration similarity was examined through model predictions and numerical simulation. These results show that the rigid-body deceleration of the nonproportional scaling model is generally in agreement with that of the prototype for penetrating the semi-infinite concrete target. The deviations of rigid-body deceleration magnitude and duration are 6.76% and −12.1%, respectively. This makes it reasonable and feasible to investigate the overloading situation of prototype projectile through a nonproportional scaling model.
Mandibular Body Reconstruction Utilizing a Three-Dimensional Custom-Made Porous Titanium Plate: A Four-Year Follow-Up Clinical Report
Authors: Ardila Carlos-Martín , Hernández-Arenas Yuritza , Álvarez-Martínez Efraín
Published: February 2022

A clinical case of a 42-year-old woman patient, who had a mandibular reconstruction utilizing a three-dimensional (3D) custom-made porous titanium plate dental restoration, is presented. She showed a recurrence of a unicystic ameloblastoma involving the left hemimandible. The patient declined to be managed by a bone-free flap. A mandibular resection in the healthy areas was provided, followed by reconstruction utilizing a 3D custom-made porous titanium plate dental restoration with a hybrid dental prosthesis. The 3D rehabilitation was created considering slim tomodensitometric sections. The cutting guides and custom-created 3D plate were fabricated employing medical software via computer-aided design and fabricating with locations planned for healing abutments. The patient was contented with the rehabilitation, and the condition continued stable at the four-year follow-up.
Degree-Based Topological Indices and QSPR Analysis of Antituberculosis Drugs
Authors: Adnan Mr. , Bokhary Syed Ahtsham Ul Haq , Abbas Ghulam , Iqbal Tanveer
Published: February 2022

A topological index of graph

G

is a numerical quantity which describes its topology. If it is applied to molecular structure of a chemical compounds, then it reflects the theoretical properties of the chemical compounds. In this paper, well-known degree-based topological indices are applied on chemical structures of antituberculosis drugs. Chemical structure is considered as graph, where elements are taken as vertices and bounds between them are taken as edges. Furthermore, QSPR analysis of the said topological indices are discussed, and it is shown that these topological indices are highly correlated with the physical properties of antituberculosis drugs. This theocratical analysis may help the chemist and people working in pharmaceutical industry to predict properties of antituberculosis drugs without experimenting.
Morphological and Anatomical Characterization of Ecotype Needles of Cedrus atlantica in Morocco
Authors: El Bakkali Nezha , Amraoui Mohammed Bendriss
Published: February 2022

Atlas cedar (Cedrus atlantica (Endl.) G. Manetti ex Carrière) is an endemic species in the mountains of North Africa that is attracting international interest in its use in the reforestation of degraded ecosystems. This study aims to investigate and evaluate the morphoanatomical characteristics of needles of four cedar populations localized in the Middle and High Atlas Mountains. Descriptive statistics, analysis of variance (ANOVA), descriptive power, scatter-plot of the discrimination function, scatter-plot of discrimination, and dendrogram of the closest Euclidean distances were made on traits. The results of the linear model of ANOVA nested as population and tree within population suggest the differences statistically significant for the traits measured at a different level. Among these traits, the length of the needle, the width of a vascular bundle including endodermis, and thickness of the wall of hypodermis cell revealed the highest discriminating characters among populations of C. atlantica from the Middle and High Atlas and between the populations of the Middle Atlas. The agglomeration of populations over short Euclidean distances also showed a higher level of differentiation between two ecotypes of C. atlantica not very geographically distant in the Atlas Mountains of Morocco. The ecotype belonging to Aït Oufella and Aït Ayach confers this species a place of choice in the projects of revalorization of the Mediterranean populations, especially in semiarid areas.
Concurrent Primary Follicular Lymphoma and a Mature Cystic Teratoma of the Ovary: A Case Report and Review of Literature
Authors: Hutspardol Sakara , Li Yi , Dube Valerie , Delabie Jan
Published: February 2022

Primary lymphoma concurrent with teratoma of the ovary is exceedingly rare. Based on our review of the literature, there are only 8 case reports describing concurrent primary diffuse large B-cell lymphoma and teratoma. Here, we report the first case of primary follicular lymphoma concurrent with mature ovarian cystic teratoma, which, to our knowledge, has not been described in the literature.
Optimization of Accounting Information System for Enterprises in Smart City by Intelligent Sensor under the Internet of Things
Authors: Li Xiaoguang
Published: February 2022

In order to realize the continuous optimization of the enterprise financial accounting information system of the smart city, from the perspective of intelligent sensor technology, firstly, this paper understands the use feelings of the enterprise financial accounting-related personnel about the information system in the smart city based on the relevant theories of intelligent sensor, smart city, and accounting information. Secondly, the Internet of things technology and intelligent sensing technology are applied to the optimization of enterprise financial accounting information system. Finally, the corresponding opinions and suggestions are put forward from the perspectives of government, employees, and enterprises. The results show that about 40%∼60% of enterprise financial accountants believe that data integration and sharing, data governance, and data operation management systems need to be continuously optimized and upgraded. Applying the Internet of things technology and intelligent sensing technology to the optimization of enterprise financial accounting information system, it is found that it can not only improve the accuracy of financial data processing, but also receive the required results efficiently and in real time. It is more important to apply intelligent sensing technology to enterprise financial information system. After comparison, it is found that the net profit of the enterprise increased from 112.69 million yuan to 3329.33 million yuan. The owner’s equity of the enterprise increased from 2045.68 million yuan to 11177.34 million yuan. The cash flow of the enterprise increased from 1056.91 million yuan to 6892.56 million yuan. Therefore, this paper studies how to optimize the enterprise financial accounting information system based on the intelligent sensor of the Internet of things in the smart city, which has great reference significance for the management of enterprise financial operation.
Research on the Hierarchical Teaching Method of University English Based on Artificial Intelligence Wireless Network
Authors: Zhang Qian , Ji Zeyu
Published: February 2022

University English is one of the basic core courses for all university students. The course involves many difficult concepts and grammatical structures, so it is difficult to most students. The starting point in any teaching program is to determine whether teaching is needed to specify what that teaching should accomplish. So the students’ need is of vital importance to the success of university English teaching. Traditional university English teaching does not take into account students’ individual learning abilities and feedback, which would cause students to not grasp enough the key knowledge, and then make students lose their interest in English. The development of artificial intelligence technology is becoming more and more mature, especially in the application of English teaching, which promotes the reform, development, and modernization of English teaching. Hence, in this paper, we propose a hierarchical teaching method for the university English teaching platform and employ artificial intelligence to find the needs of university students and know about the mastering knowledge of students. Initially, the dataset is preprocessed using normalization, and then, the feature extraction is performed using principal component analysis (PCA). For classification of the data, we employ the

K

-means clustering algorithm. To enhance the evaluation system, the whale optimization algorithm (WOA) is used. The performance of the proposed system is analyzed, and it is shown that the average score of students who used the proposed platform to learn university English is far higher than those students who did not use the platform. Hence, the platform can improve students’ autonomous learning and English abilities.
The Origin of Abnormal Beta Oscillations in the Parkinsonian Corticobasal Ganglia Circuits
Authors: Asadi Atefeh , Madadi Asl Mojtaba , Vahabie Abdol-Hossein , Valizadeh Alireza
Published: February 2022

Parkinson’s disease (PD) is a neurodegenerative brain disorder associated with motor and nonmotor symptoms. Exaggerated beta band (15–30 Hz) neuronal oscillations are widely observed in corticobasal ganglia (BG) circuits during parkinsonism. Abnormal beta oscillations have been linked to motor symptoms of PD, but their exact relationship is poorly understood. Nevertheless, reduction of beta oscillations can induce therapeutic effects in PD patients. While it is widely believed that the external globus pallidus (GPe) and subthalamic nucleus (STN) are jointly responsible for abnormal rhythmogenesis in the parkinsonian BG, the role of other cortico-BG circuits cannot be ignored. To shed light on the origin of abnormal beta oscillations in PD, here we review changes of neuronal activity observed in experimental PD models and discuss how the cortex and different BG nuclei cooperate to generate and stabilize abnormal beta oscillations during parkinsonism. This may provide further insights into the complex relationship between abnormal beta oscillations and motor dysfunction in PD, which is crucial for potential target-specific therapeutic interventions in PD patients.
Design and Implementation of Optimum LSD Coded Signal Processing Algorithm in the Multiple-Antenna System for the 5G Wireless Technology
Authors: Pateriya Priyanka , Singhai Rakesh , Shukla Piyush
Published: February 2022

The 5G system requires an optimum coding technique to achieve the high diversity gain, low bit error rate (BER), and low detection complexity. Various coding techniques were developed in recent times for improving the diversity performance of the MIMO systems. Space-time-coding (STC) is used to fulfill the requirement of handling large data flow in the 5G wireless communications. It is highly required to optimize the orthogonal nature of STC. The paper proposed a novel design of the optimum linearly scalable dispersion code (O-LSDC). In this paper, an optimum coefficient-based O-LSDC is designed based on the elementary matrix operations, unitary matrix normalization technique, and coefficient mapping strategy. Mapped coefficients are linearly solved for optimum value estimation. To find the optimum solution of the LSDC codes, five cases of LSDC are defined based on the scaling coefficients and then performance is evaluated against the BER vs. SNR. Evaluating the simulation results in terms of error probabilities for the five different orthonormal LSDC, this work simulates the system for multiple antennas using the Rayleigh fading MIMO system model. Also, evaluating the impact of the proposed LSDC over the BER performance for the varied number of Monte Carlo iterations, then the performance graph is plotted for multiple-antennas system. The proposed O-LSDC under Rayleigh fading channel using the M-PSK modulation enhances the performance of the 5G and beyond communication system in terms of BER and SNR.
A Threat Intelligence Analysis Method Based on Feature Weighting and BERT-BiGRU for Industrial Internet of Things
Authors: Yan Jingchen , Du Zhe , Li Jifang , Yang Shiduo , Li Jinghao , Li Jianbin
Published: February 2022

The combination of 5G technology and the industrial Internet of things (IIoT) makes it possible to realize the interconnection of all things. Still, it also increases the risk of attacks such as large-scale DDoS attacks and IP spoofing attacks. Threat intelligence is a collection of information causing potential and nonpotential harm to the industrial Internet. Extracting network security entities and their relationships from threat intelligence text and constructing structured threat intelligence information are particularly important for IIoT security protection. However, threat intelligence is mostly text reports, which means the value information needs to be extracted manually by security analysts, and it is highly dependent on personnel experience. Therefore, this study proposes an IIoT threat intelligence analysis method based on feature weighting and BERT-BiGRU. In this method, BERT-BiGRU is used to classify attack behavior and attack strategy. Then, the attack behavior is weighted to make the classified result more accurate according to the relationship between attack strategy and attack behavior in ATT&CK for ICS knowledge. Finally, the possibility of attack and the harm degree of attack are calculated to form the threat value of the attack. The security analysts can judge the emergency response sequence by the threat value to improve the accuracy and efficiency of emergency response. The results indicate that the proposed method in this study is more accurate than the other standard methods and is more suitable for the unstructured threat intelligence analysis of IIoT.
Security-Level Improvement of IoT-Based Systems Using Biometric Features
Authors: Moradi Masoud , Moradkhani Masoud , Tavakoli Mohammad Bagher
Published: February 2022

The Internet of Things (IoT) is reported as a main research topic in the current decade. It will be possible to connect smart devices to each other using IoT, a platform such as the Internet. However, the expansion and intrusion of such a large network raises some new security issues and risks related to the disclosure of user confidential information where these devices are subject to hacker threats and intrusions. Traditional security systems were password based. In this paper, after reviewing the actions taken in this regard, the improvement level of biometric security compared with traditional password-based methods will be proven in section three using the Markov model. By considering the results of the evaluation, the probability of occurrence of security problems is decreased by 90.71% by applying biometric features. Then, multi-layer security architecture with biometric features and coding systems is suggested to increase security. In the first layer, the fingerprint recognition algorithm is dependent on the module, and the U.are.U 5100 module provides more security than others. In the second layer, the Hash mechanism of the MD5 algorithm is, on average, 63.21% more efficient. By determining the properties of the first two architectural layers and ultimately for the IoT application layer, empirical methods and hardware platforms for the Internet of things are used. Concerning the simulation results, the suggested mechanism enhances the system security by 120.38% on average, which is 106.23, 110.45, and 144.46% of relative improvement compared with IoT sensors, controller layer mechanisms, and application layer mechanisms, respectively.
Digital Financial Inclusion, Spatial Spillover, and Household Consumption: Evidence from China
Authors: Li Yao , Long Haiming , Ouyang Jiajun
Published: February 2022

Financial development is often considered one of the main drivers promoting household consumption. As a form of financial development, whether digital financial inclusion can promote household consumption has been a concern for researchers and policymakers. Considering geographical connectivity characteristics, we examine the effects of digital financial inclusion on household consumption by applying spatial econometric models and using data from 31 provinces in China from 2013 to 2018. The impact of digital financial inclusion is further disaggregated into direct, indirect, and total impacts. The results show that if digital financial inclusion is improved by 1%, household consumption will correspondingly increase by 0.2207%. The spatial spillover effect on neighboring areas is negative: a 1% increase in the level of digital financial inclusion of nearby provinces leads to a 0.1289% decrease in household consumption in the local province. For policymakers, it is necessary to balance the development of digital financial inclusion and view different areas as a whole when making policies to promote consumption. Further analysis based on subsamples finds that the effect of digital financial inclusion on household consumption is more considerable for rural households than for urban households.
Observation and Analysis of the Postoperative Analgesic Effect of Subanaesthetic Dose of Ketamine in Kashin–Beck Disease Patients after Total Knee Arthroplasty
Authors: Xie Huijin , Zhu Gaobo , Zhu Changmou , Wang Wei
Published: February 2022

With the transformation of modern medical models, the medical needs of patients have changed from treatment to safe, comfortable, and painless treatment. Therefore, it is clinically important to find an ideal analgesia model to reduce the pain after total knee arthroplasty and minimize the impact of surgical trauma on the body pressure. This article aims to study the effects of lower limb nerve block combined with local infiltration analgesia of the joint cavity on the hemodynamics and postoperative analgesia effects of knee joint replacement in elderly patients by comparing the effects of the subanaesthetic dose of ketamine on the hemodynamics and postoperative analgesia effect of knee joint replacement in elderly patients’ intraoperative analgesia program. This article proposes that 90 patients requiring unilateral total knee replacement were randomly divided into 3 groups, with 30 patients in each group, age 65–85 years, average age 75 years, ASA I ∼ II grade, and body mass index 13.89 ∼ 37.26. Use a multifunctional monitor to monitor the patient’s continuous blood pressure (SBP/DBP) and mean arterial pressure (MAP), heart rate (HR), electrocardiogram (ECG), intraoperative pulse oxygen saturation (SpO2), and end-tidal carbon dioxide (PETCO2). The following are monitored: record the heart rate (HR), systolic blood pressure (SBP), and diastolic blood pressure before induction of anesthesia (T0), before the upper tourniquet (T1), and after the upper tourniquet (T2), before tourniquet withdrawal (T3), and after tourniquet withdrawal (T4), mean arterial pressure (MAP). The three groups of patients had different degrees of itching, vomiting, nausea, and other adverse reactions. The experimental results in this article show that, in elderly patients with epidural anesthesia, the use of propofol and dexmedetomidine to maintain the patient’s BIS value between 60 and 70 can meet the depth of sedation required for surgery without important surgical operation knowledge.
Can Artificial Intelligence Be Applied to Diagnose Intracerebral Hemorrhage under the Background of the Fourth Industrial Revolution? A Novel Systemic Review and Meta-Analysis
Authors: Zhao Kai , Zhao Qing , Zhou Ping , Liu Bin , Zhang Qiang , Yang Mingfei
Published: February 2022

Aim. We intended to provide the clinical evidence that artificial intelligence (AI) could be used to assist doctors in the diagnosis of intracerebral hemorrhage (ICH). Methods. Studies published in 2021 were identified after the literature search of PubMed, Embase, and Cochrane. Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) was used to perform the quality assessment of studies. Data extraction of diagnosis effect included accuracy (ACC), sensitivity (SEN), specificity (SPE), positive predictive value (PPV), negative predictive value (NPV), area under curve (AUC), and Dice scores (Dices). The pooled effect with its 95% confidence interval (95%CI) was calculated by the random effects model. I-Square (I2) was used to test heterogeneity. To check the stability of the overall results, sensitivity analysis was conducted by recalculating the pooled effect of the remaining studies after omitting the study with the highest quality or the random effects model was switched to the fixed effects model. Funnel plot was used to evaluate publication bias. To reduce heterogeneity, recalculating the pooled effect of the remaining studies after omitting the study with the lowest quality or perform subgroup analysis. Results. Twenty-five diagnostic tests of ICH via AI and doctors with overall high quality were included. Pooled ACC, SEN, SPE, PPV, NPV, AUC, and Dices were 0.88 (0.83∼0.93), 0.85 (0.81∼0.89), 0.90 (0.88∼0.92), 0.80 (0.75∼0.85), 0.93 (0.91∼0.95), 0.84 (0.80∼0.89), and 0.90 (0.85∼0.95), respectively. There was no publication bias. All of results were stable as revealed by sensitivity analysis and were accordant as outcomes via subgroups analysis. Conclusion. Under the background of the fourth industrial revolution, AI might be an effective and efficient tool to assist doctors in the clinical diagnosis of ICH.
Altered White Matter Integrity in Patients with Retinal Vein Occlusion: A Diffusion Tensor Imaging and Tract-Based Spatial Statistics Study
Authors: Zhang Mou-Xin , Chen Min-Jie , Tang Li-Ying , Yu Chen-Yu , Xu Yu-Ling , Xu San-Hua , Ying Ping , Kang Min , Zhang Li-Juan , Shao Yi
Published: February 2022

Background. To investigate microstructural alterations of white matter in retinal vein occlusion (RVO) patients by tract-based spatial statistics (TBSS) and diffusion tensor imaging (DTI). Material/Methods. DTI was performed on 14 RVO patients and 14 normal controls (HCs). We measured and recorded fractional anisotropy (FA) and radial diffusivity (RD) of white matter fibers and classified them through the receiver operating characteristic (ROC) curve and correlation analysis, respectively. Results. The mean FA value of white matter in RVO patients is lower than the HCs, and the mean RD value in RVO patients increased, especially in the bilateral posterior thalamic, bilateral sagittal stratum, body of corpus callosum, cingulum, and fornix. The ROC curve of different brain regions showed high accuracy. Moreover, the mean FA and RD values were significantly correlated with visual and psychological disorders. Conclusion. TBSS could be regarded as an important method to reveal the alterations of white matter in RVO patients, indicating the underlying neurological mechanism of the RVO.
Respiratory Disorders Related to e-Waste Exposure among Workers in the Informal Sector in a Sub-Saharan African City: An Exposed Nonexposed Study
Authors: Wachinou Ablo Prudence , Kêdoté Nonvignon Marius , Padonou Geraud , Adè Serge , Darboux Joaquin , Tohi Mirlène , Fiogbé Arnauld , Fobil Julius , Agodokpessi Gildas
Published: February 2022

Introduction. Exposure to electrical and electronic equipment waste (e-waste) has become a growing health concern. The objective of this study was to measure the effect of exposure to e-waste on respiratory symptoms and on lung function parameters in workers involved in informal recycling activities in Cotonou city, Benin. Methods. This was a cross-sectional study, in which exposed e-waste workers in Cotonou city were randomly selected. A matching nonexposed group based on age and sex was recruited from the general population. Respiratory symptoms were investigated using a questionnaire adapted from the British Medical Research Council’s standardized respiratory questionnaire. Participants underwent lung function test using a portable spirometer (MIR SPIROBANK). Data were analyzed with STATA version 15 software. Results. The overall prevalence of respiratory symptoms in e-waste workers was statistically higher in the exposed group (33.1% vs. 21.6%;

p
=
0.027

). Chest tightness (11.8% vs. 2.1%;

p
=
0.003

) and breathlessness (6.8% vs. 1.4%;

p
=
0.018

) were the most reported symptoms by e-waste workers. Lung function testing showed a higher proportion of disorders among e-waste workers (25.0% vs. 14.9%,

p
=
0.029

), with a higher proportion of probable restrictive (10.8% vs. 2.7,

p
=
0.005

) and mixed (4.1% vs. 0%,

p
=
0.013

) ventilatory disorders. Handling or working with e-waste was found associated with a significant reduction in forced expiratory volume in one second (FEV1) by 0.4 L (95% CI: 0.3-0.6) and forced vital capacity (FVC) by 0.75 L (95% CI: 0.6-0.9) after adjustment for age, BMI, smoking habits, asthma history, and daily income. Conclusion. Work involving e-waste is associated with a higher prevalence of respiratory symptoms and with an increased risk of FEV1 and FVC decline, as well as of lung function impairment, particularly of restrictive disorders. Further studies to better clarify this association are needed. Awareness on this major public health threat should be raised in other sub-Saharan and Asian urban areas.
Post-Psychotic Depression: An Updated Review of the Term and Clinical Implications
Authors: Guerrero-Jiménez Margarita , Carrillo de Albornoz Calahorro Carmen Maura , Girela-Serrano Braulio , Bodoano Sánchez Isabel , Gutiérrez-Rojas Luis
Published: February 2022

Background: Post-psychotic depression (PPD) is an important and frequent clinical phenomenon featuring controversial complexity in its nosological and aetiopathogenic cataloguing. Objectives: The main objective of this research was to review the published literature on PPD. The second objective was to indicate its clinical importance, either comorbid or as an entity of its own. To answer these questions, a historical review of the term is made and a search about the clinical, evolutionary, predisposal, and prognostic variables that characterize the PPD. Methods: The international recommendations were followed according to the Preferred Items for Reporting of Systematic Reviews and Meta-Analyses (PRISMA). The databases used were Web of Science and PubMed, with the deadline for the inclusion of articles in November 2019. The MeSH used were the following: “post” AND “psych *” AND “psich” AND “depr.” Results: The search resulted in 64 articles. Only 19 of these met the pre-specified inclusion criteria and were finally included in the review. One article found that reading this literature was added due to its relevance. Despite its high prevalence (around 30%), there is little research about the term PPD. Nevertheless, results show data to improve the description of the syndrome, revealing differential characteristics from other depressive symptoms in chronic psychosis due to its clinical implications. Conclusions: Coinciding with the latest classification manuals that do not include the term, there appears to be an abandonment of its use despite its high prevalence. Data suggest that PPD is a nosological entity different from a secondary effect to antipsychotics, the negative symptoms of psychosis, and other clinical disorders that combine psychotic and depressive symptoms such as bipolar disorder, schizoaffective disorder, or depression with psychotic symptoms. PPD also has differential characteristics concerning further depressive symptoms, especially important clinical implications such as higher suicide risk and poorer quality of life.
Barrett’s Oesophagus: Today’s Mistake and Tomorrow’s Wisdom in Screening and Prevention
Authors: Tan W. Keith , di Pietro Massimiliano
Published: February 2022

Background: Oesophageal adenocarcinoma (OAC) is a lethal cancer with an overall 5-year survival of <20%. Given the presence of a pre-invasive disease stage, also known as Barrett’s oesophagus (BO), and the availability of minimally invasive treatments for BO-related neoplasia, it is thought that early detection is the best strategy to improve patient outcomes. Clinical guidelines recommend endoscopic screening in patients with symptoms of acid reflux and additional risk factors. This strategy is flawed by the cost and invasiveness of endoscopy as well as by the fact that a significant proportion of OAC patients deny a history of reflux symptoms. Summary: New research on the use of epidemiologic and clinical data has allowed the creation of risk-prediction algorithms to identify the population at risk. In addition, newer less-invasive devices such as transnasal endoscopy, Cytosponge, volumetric laser endomicroscopy, and volatile organic compounds are emerging as promising options to allow screening in the primary care setting. Finally, there is an opportunity to intervene at the pre-invasive stage with pharmacological strategies to reduce the risk burden. Key Messages: In this review, we provide a critical appraisal of the different screening approaches and chemopreventive strategies and a guide to readers on how to implement research evidence in clinical practice.
Population-Based Analysis of Sex-Dependent Risk Factors for Mortality in Thoracic Surgery for Lung Cancer
Authors: Baum Philip , Eichhorn Martin E. , Diers Johannes , Wiegering Armin , Klotz Laura V. , Winter Hauke
Published: February 2022

Objective: Sex is an important predictor for lung cancer survival and a favorable prognostic indicator for women compared to men. Specific surgery-related sex differences of patients with lung cancer remain unclear. The aim of this study is to analyze sex-specific differences after lung cancer resections to identify factors for an unfavorable prognosis. Methods: This is a retrospective analysis of a German nationwide discharge register of every adult inpatient undergoing pulmonary resection for lung cancer from 2014 until 2017. DRG data and OPS procedures were analyzed with the help of the Federal Statistical Office using remote controlled data. A multivariable regression model was established in a stepwise process to evaluate the effect of sex on inpatient mortality. Results: A total of 38,806 patients underwent surgical resection for lung cancer between January 2014 and December 2017 in Germany. Women were significantly younger at admission than men (mean 64.7 years [SD 10.1] vs. 66.6 years [SD 9.5]; p < 0.0001). They had fewer unreferred admissions (risk ratio 0.83 [0.77, 0.90], p < 0.0001) and were significantly less likely to have recorded comorbidities. Raw in-hospital mortality was 1.8% for women and 4.1% for men. In the multivariable analysis of in-hospital mortality, the likelihood of death for women compared to men was 21% reduced (OR 0.79 [CI: 0.66, 0.93, p = 0.005]). The risk of postoperative complications such as ventilation >48 h, ARDS, tracheotomy, or pneumonia was significantly lower for women. Conclusions: Women undergoing lung cancer surgery were younger and had less comorbidities than men in Germany. Female sex was associated with lower mortality and less postoperative complications.
Programmed Cell Death Protein 1 Blockade Elicits Ongoing Remission in 2 Cases of Refractory Epstein-Barr Virus-Associated Metastatic Gastric Carcinoma
Authors: Masetti Michael , Lindinger Martin , Lorenzen Sylvie
Published: February 2022

Introduction: Over the last decade, immunotherapy has revolutionized oncological treatment of malignancies across all entities including gastric cancer (GC). The programmed cell death protein 1 (PD-1) inhibitor pembrolizumab has demonstrated durable responses and survival benefit in distinct patient subgroups with advanced GC (aGC). In 2017, pembrolizumab monotherapy was approved by the US Food and Drug Administration (FDA) for the treatment of refractory metastatic GC over-expressing programmed death ligand 1 (PD-L1), as well as for refractory advanced tumors with deficient DNA mismatch repair/microsatellite instability (dMMR/MSI) or high tumor mutational burden (TMB). However, several biomarker unselected studies have reported only limited single-agent immunotherapeutic efficacy. Thus, the identification of predictive biomarkers to select patient subgroups that are most eligible for immunotherapy is of particular importance. A growing number of studies consider Epstein-Barr virus (EBV)-associated GC (EBVaGC) as a molecularly distinct and immunogenic subtype which might be particularly sensitive to immune-checkpoint inhibition. Case Report: Here, we present 2 cases of heavily pretreated patients with refractory, metastatic EBVaGC, who experienced a significant and sustained response to monotherapy with the PD-1 checkpoint inhibitor pembrolizumab. Conclusion: Comprehensive genetic testing for predictive biomarkers (e.g., PD-L1, MSI/dMMR, tTMB, EBV) to identify patient subgroups most eligible for immunotherapy is of particular importance in aGC, especially in patients that are refractory to conventional chemotherapy.
Induction motor efficiency maximizing based on torque per power index
Authors: Abbas Najimaldin M. , Mustafa Mohammed Obaid , Shakor Ali M.
Published: February 2022

In this paper, efficiency maximization of induction motor variable frequency speed regulation system based on torque per power (TPP) index is proposed. The detail of the mathematical model of the induction motor considering the iron loss and the rotor field orientation, the relationship between the motor torque loss power ratio and the motor speed and slip frequency presented. The functional relationship between the torque loss power ratio and the motor speed and slip is derived, and the derivative is obtained to find the optimal slip frequency corresponding to the maximum value. The simulation model and experimental platform of the control system were built in Matlab/Simulink to verify the effectiveness of the method. The result approved the torque loss power ratio takes the maximum value, the high energy efficiency operation with the minimum power loss of the motor control system is realized.
Analysis of active islanding detection techniques for grid-connected inverters systems
Authors: Ikken Naima , Tariba Nour-Eddine , Bouknadel Abdelhadi , Haddou Ahmed , Omari Hafsa El , Omari Hamid El
Published: February 2022

An island is a section of the electrical grid that contains producing assets and loads that are separated from the main grid and powered by these generators, such as solar systems, with voltage and frequency maintained at nominal levels. It's worth noting that the concept of islanding is linked to time. When the inverter detects an isolated grid activity for a particular period of time, the inverter is compelled to decouple from the general grid, according to the criteria that dictate the working principle of a photovoltaic (PV) systemThis paper presents research and comparisons of the main islanding detection techniques for single-phase systems based on various structures, as well as a comparison of the improvement of the traditional islanding detection method using three different methods (active frequency drift (AFD), slip mode phase shift (SMS) and Sandia frequency shift (SFS)). Under normal and abnormal operating conditions, a comparison of these three examined improvements was made. Additionally, physical security information management (PSIM) software simulation results are generated to test the performance and effectiveness of the effective technique plan.
New lambda tuning approach of single input fuzzy logic using gradient descent algorithm and particle swarm optimization
Authors: Zohedi Fauzal Naim , Aras Mohd Shahrieel Mohd , Kasdirin Hyreil Anuar , Nordin Nurdiana Binti
Published: February 2022

Underwater remotely operated vehicle (ROV) is important in underwater industries as well as for safety purposes. It can dive deeper than humans and can replace humans in a hazardous underwater environment. ROV depth control is difficult due to the hydrodynamic of the ROV itself and the underwater environment. Overshoot in the depth control may cause damage to the ROV and its investigated location. This paper presenting a new tuning approach of single input fuzzy logic controller (SIFLC) with gradient descent algorithm (GDA) and particle swarm optimization (PSO) implementation for ROV depth control. The ROV was modeled using system identification to simulate the depth system. Proportional integral derivative (PID) controller was applied to the model as a basic controller. SIFLC was then implemented in three tuning approaches which are heuristic, GDA, and PSO. The output transient was simulated using MATLAB Simulink and the percent overshoot (OS), time rise (Tr), and settling time (Ts) of the systems without and with controllers were compared and analyzed. The result shows that SIFLC GDA output has the best transient result at 0.1021% (OS), 0.7992s (Tr), and 0.9790s (Ts).
Efficacy of chili plant diseases classification using deep learning: a preliminary study
Authors: Rozlan Suhana , Hanafi Marsyita
Published: February 2022

Plant disease classification using deep learning techniques is a popular research area due to the numerous opportunities for introducing advance and robust classifiers. Nevertheless, classifying chilli plant diseases accurately from images under uncontrolled environment and various imaging conditions remains unsolved due to the lack of chilli disease image datasets. In this study, the efficacy of three high-performance deep learning algorithms, namely VGG16, InceptionV3, and EfficientNetB0, in classifying three types of chilli leaves diseases, namely upward curling, mosaic/mottling, and the bacterial spot, is demonstrated. These methods are popularly used for other plant disease classifications due to their effectiveness. The experiments were performed on the 3,000 chilli plant disease images collected from three different field environments in Selangor, Malaysia. The images were captured with a complex background and various illuminations, angles, and distances to reflect the real-life scenarios. The complexity of the collected images was created based on the taxonomic information of chilli leaves diseases and the unavailability of chilli disease images under various imaging conditions in the publicly available plant disease databases. Experimented using appropriate specifications, the models demonstrated outstanding performance with more than 95% accuracy with the highest accuracy of 98.83% by InceptionV3.
Automated sleep apnea classification based on statistical and spectral analysis of electrocardiogram signals
Authors: Kumari Lavu Venkata Rajani , Lohitha Anumolu , Kavya Atluri , Tarakeswar Nallamothu
Published: February 2022

Well-being sleep is a significant segment for maintaining mental comparably as genuine flourishing. More than six-hour recordings are required to distinguish sleep apnea, which are extremely long duration recordings. It's difficult for a human to deduce the problem from electrocardiogram (ECG) readings. As a result, automated PC-based assessment is expected to detect abnormalities as early as possible. An automated framework for the classification of obstructive sleep apnea (OSA) can moreover be distinguished from the ECG Signals. From the Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) polysomnographic informational collection, 18 subjects have been considered as data signals. The signal is segmented into 30 seconds and features are extracted by using the discrete wavelet transform (DWT). DWT of seven-level decomposition is applied on the segmented signal by using the wavelet 'sym3'. 12 features were extracted from each level and all of them are used to categorize the five types of sleep apnea. Random forest, k-nearest neighbor (KNN), and support vector machine (SVM) are used for classification of apnea. The random forest (RF) classifier outperformed the others with an average of accuracy (Acc) of 98.53% according to the study's findings. The experimental results show the developed model outperforms the state of art algorithms in the literature.
Automatic construction of generic stop words list for hausa text
Authors: Bichi Abdulkadir Abubakar , Samsudin Ruhaidah , Hassan Rohayanti
Published: February 2022

Stop-words are words having the highest frequencies in a document without any significant information. They are characterized by having common relations within a cluster. They are the noise of the text that are evenly distributed over a document. Removal of stop words improve the performance and accuracy of information retrieval algorithms and machine learning at large. It saves the storage space by reducing the vector space dimension, and helps in effective documents indexing. This research generated a list of Hausa stop words automatically using aggregated method by combining frequency and statistics methods. The experiments are conducted using a primarily collected Hausa corpus consisting of 841 Hausa news articles of size 646862 words and finally a list of distinct 81 Hausa stop words is generated.
Efficient electrocardiogram signal compression algorithm using dual encoding technique
Authors: Rijab Khalida Shaaban , Hussien Mohammed Abdul Redha
Published: February 2022

In medical practices, the storage space of electrocardiogram (ECG) records is a major concern. These records can contain hours of recording, necessitating a large amount of storage space. This problem is commonly addressed by compressing the ECG signal. The proposed work deal with the ECG signal compression method for ECG signals using discrete wavelet transform (DWT). The DWT appeared as powerful tools to compact signals and shows a signal in another time-frequency representation. It is very appropriate in the elimination & removal of redundancy. The ECG signals are decomposed using DWT. After that, the coefficients that result from DWT are threshold depending on the energy packing efficiency (EPE) of the signal. The compression is achieved by the quantization and dual encoding techniques (run-length encoding & Huffman encoding). The dual encoding technique compresses data significantly. The result of the proposed method shows better performance with compression ratios and good quality reconstructed signals. For example, the compression ratio (CR)=20.6, 10.7 and 11.1 with percent root mean square difference (PRD)=1%, 0.9% and 1% for using different DWT (Haar, db2 and FK4) Respectively.
Frequency recommendation for long term evolution network implementation using simple multi attribute rating technique
Authors: Angelia Putri , Munadi Rendy , Adriansyah Nachwan Mufti
Published: February 2022

The increasing demand for telecommunication services causes data traffic density. Therefore, in this research, the long-term evolution (LTE) network expansion was carried out using a choice of frequency bands of 700 MHz, 2100 MHz, and 2300 MHz. The analysis was carried out from the technical and economic aspects. Frequency band recommendations were obtained using the simple multi-attribute rating technique (SMART) method. This research was conducted using a case study of Semarang City. Based on the simulation results, the average of reference signal receive power (RSRP) values for frequency 700 MHz and 2300 MHz is in the very good range, while the frequency of 2100 MHz is in the good range. The signal to interference noise ratio (SINR) values for the three frequencies are in the normal category and the throughput values are in the very good category. The techno-economic calculations of the three frequencies, namely the value of internal rate of return (IRR), net present value (NPV), and payback period are included in the business category that is feasible to do. Based on the ranking results, the 700 MHz frequency is the most superior, both in terms of technical and economic aspects.
Free-space optical channel performance under atmospheric losses using orthogonal frequency division multiplexing
Authors: Mani Vinoth Kumar , Kumar Vinod
Published: February 2022

Free space optics (FSO) is a fast-growing technology that outperforms fiber optics in communication network infrastructure without spectrum licensing. The goal of this work is to evaluate the performance of the FSO communication system using direct detection 4-quadrature amplitude modulation (4-QAM) and 4-phase shift keying (4-PSK) with orthogonal frequency division multiplexing (OFDM) scheme. Simulating a direct detection OFDM-FSO system and comparing constellation diagrams, electrical power, and optical power have been used to conduct the analysis. The model is validated using a constellation diagram of received signals for various FSO channel ranges and weather conditions. According to simulation results, the OFDM-FSO architecture combined with the 4-QAM modulation technique produces the most efficient output with the least amount of power consumption for data rates up to 10 Gb/s and FSO channel ranges of up to
 3 km for clear air, 1.7 km, and 1.3 km for thin and thick fog, and 0.7 km for heavy fog. This investigation can enhance the current fiber optic network's structure connected with the FSO system to provide last-mile connectivity in 5G modules.