bluuebunny/crossref_metadata_2025 huggingface dataset:
A Novel Strategy for Screening Active Components in Cistanche tubulosa Based on Spectrum-Effect Relationship Analysis and Network Pharmacology
Authors: Liu Xiao-Tong , Sun Dong-Mei , Yu Wen-Xin , Lin Wei-Xiong , Liu Liao-Yuan , Zeng Yu
Published: January 2023

Cistanche tubulosa (Schenk) R. Wight is a valuable herbal medicine in China. The study aimed to explore the potential mechanisms of C. tubulosa on antioxidant activity using spectrum-effect relationship and network pharmacology and the possibilities of utilizing herbal dregs. In this work, different extracts of C. tubulosa, including herbal materials, water extracts, and herbal residues, were evaluated using high-performance liquid chromatography (HPLC) technology. In addition, the antioxidant activities were estimated in vitro, including 2, 2-diphenyl-1-picrylhydrazyl; superoxide anion; and hydroxyl radical scavenging assays. The spectrum-effect relationships between the HPLC fingerprints and the biological capabilities were analyzed via partial least squares regression, bivariate correlation analysis, and redundancy analysis. Furthermore, network pharmacology was used to predict potential mechanisms of C. tubulosa in the treatment of antioxidant-related diseases. According to the results, eleven common peaks were shared by different extracts. Geniposidic acid, echinacoside, verbascoside, tubuloside A, and isoacteoside were quantified and compared among different forms of C. tubulosa. The spectrum-effect relationship study indicated that peak A6 might be the most decisive component among the three forms. Based on network pharmacology, there were 159 target genes shared by active components and antioxidant-related diseases. Targets related to antioxidant activity and relevant pathways were discussed. Our results provide a theoretical basis for recycling the herbal residues and the potential mechanisms of C. tubulosa in the treatment of antioxidant-related diseases.
Using a Hybrid Multiattribute Decision-Making Model for Evaluating the Sustainable Development Potential of Characteristic Towns and Exploring Development Planning Strategies
Authors: Lin Jing-Yang , Zhao Lai-Chun , Zheng Yu-Yi , Du Qing-Kun , Xiong Lei , Zhu Bo-Wei , Tzeng Gwo-Hshiung
Published: January 2023

In recent years, with the development of ’China’s new urbanization, the “characteristic town movement” with the development of industrial economy first has brought problems to a large number of rural settlements, such as no cultural planning, no consumption of industry, and no soul. Then, in reality, there are still a large number of rural settlements under the planning of the upper-level local government, with the goal of developing into a characteristic town in the future. Therefore, this study believes that there is an urgent need to build a framework for evaluating the construction potential of rural settlements with sustainable characteristic towns. Not only that but also a decision analysis model should be provided for real-world empirical cases. This model needs to cover the assessment of the sustainable development potential of characteristic towns as the goal and the formulation of improvement strategies. This study combines the data collection of current characteristic town development rating reports, applies data exploration technology to extract core impact elements and obtain hierarchical decision rules, integrates expert domain knowledge with DEMATEL technology, and establishes an impact network relationship diagram between core impact elements. At the same time, the representative characteristic town cases are assessed for their sustainable development potential, and the modified VIKOR technique is applied to clarify the actual problems of the empirical cases, in an attempt to determine whether the development potential and development plan of the characteristic town meet the sustainable development needs from the pre-evaluation mechanism.
The Butterfly: A Novel Minimally Invasive Transurethral Retraction Device for Benign Hypertrophy of the Prostate
Authors: Katz Ran , Ahmed Muhamad Sabih Abu , Safadi Ali , Roizman Shmuel , Zisman Amnon , Kabha Maharan , Dekel Yoram , Baniel Jack , Aharony Shachar
Published: January 2023

Introduction: The Butterfly Prostatic Retraction device is a novel transurethral implant designed to dilate the prostatic urethra and treat lower urinary tract symptoms. We assessed its safety, efficacy and impact on urinary flow, ejaculation, and quality of life. Materials and Methods: We included 64 men, treated for benign prostate hyperplasia for at least 1 year. All patients had Qmax≤ 13 mL/s and IPSS >12. Insertion of the device was performed via cystoscopy. Follow-up visits were performed at 2 weeks, 1, 3, 6, and 12 months and included uroflowmetry, IPSS, QoL, and sexual function questionnaires. Cystoscopy was performed on 3 and 12 months. Results: Patients age was 50–83 years. 28 patients completed a 1-year follow-up with an intact device. Mean Qmax improved by 2 mL/s (25%), IPSS median drop was 10 points (40%), and QoL score was 1.5 points (38%). Sexually active patients reported antegrade ejaculation. On cystoscopy, gradual coverage of the devices with urethral mucosa was observed. In 1 patient, the device was repositioned. In 19 patients, the device was removed. 12 patients returned to alpha-blocker therapy and 7 patients underwent TURP. One patient developed a bulbar urethral stricture. Conclusions: We demonstrated feasibility and good tolerability of the Butterfly device.
Angststörungen und depressive Störungen: Ein Risiko bei Augenerkrankungen?
Authors: Göbel Katja
Published: January 2023

Background: Progressive and irreversible vision loss has been shown to place a patient at risk of mental health problems such as anxiety. However, the reported prevalence of anxiety symptoms and disorders among eye disease patients vary across studies. Thus, this study aims to clarify the estimated prevalence of anxiety symptoms and disorders among ophthalmic disease patients. Methods: Relevant studies on the prevalence of anxiety symptoms and disorders among eye disease patients were collected through international databases, PubMed, Scopus, and Web of Science. A random-effects model was used to determine the pooled prevalence of anxiety symptoms and disorders among ophthalmic disease patients. Results: The 95 included studies yielded a pooled prevalence of 31.2% patients with anxiety symptoms and 19.0% with anxiety disorders among subjects with ophthalmic disease. Pediatric patients were more anxious (58.6%) than adults (29%). Anxiety symptoms were most prevalent in uveitis (53.5%), followed by dry eye disease (DED, 37.2%), retinitis pigmentosa (RP, 36.5%), diabetic retinopathy (DR, 31.3%), glaucoma (30.7%), myopia (24.7%), age-related macular degeneration (AMD, 21.6%), and cataract (21.2%) patients. Anxiety disorders were most prevalent in thyroid eye disease (TED, 28.9%), followed by glaucoma (22.2%) and DED (11.4%). When compared with healthy controls, there was a twofold increase on the prevalence of anxiety symptoms (OR = 1.912, 95% CI 1.463–2.5, p < 0.001) and anxiety disorders (OR = 2.281, 95% CI 1.168–4.454, p = 0.016). Conclusion: Anxiety symptoms and disorders are common problems associated with ophthalmic disease patients. Thus, comprehensive and appropriate treatments are necessary for treating anxiety symptoms and disorders among ophthalmic disease patients.
EPOC en jóvenes: Comorbilidades y riesgo de mortalidad
Authors: Acuña-Kaldman Moisés
Published: January 2023

Rationale and objectives: Patients with chronic obstructive pulmonary disease (COPD), usually diagnosed after the 6th decade, frequently suffer from comorbidities. Whether COPD patients 50 years or younger (Young COPD) have similar comorbidities with the same frequency and mortality impact as aged-matched controls or older COPD patients is unknown. Methods: We compared comorbidity number, prevalence and type in 3 groups of individuals with ≥ 10 pack-years of smoking: A Young (≤ 50 years) COPD group (n = 160), an age-balanced control group without airflow obstruction (n = 125), and Old (> 50 years) COPD group (n = 1860). We also compared survival between the young COPD and control subjects. Using Cox proportional model, we determined the comorbidities associated with mortality risk and generated Comorbidomes for the «Young» and «Old» COPD groups. Results: The severity distribution by GOLD spirometric stages and BODE quartiles were similar between Young and Old COPD groups. After adjusting for age, sex, and pack-years, the prevalence of subjects with at least one comorbidity was 31% for controls, 77% for the Young, and 86% for older COPD patients. Compared to controls, «Young» COPDs’ had a nine-fold increased mortality risk (p < 0.0001). «Comorbidomes» differed between Young and Old COPD groups, with tuberculosis, substance use, and bipolar disorders being distinct comorbidities associated with increased mortality risk in the Young COPD group. Conclusion: Young COPD patients carry a higher comorbidity prevalence and mortality risk compared to non-obstructed control subjects. Young COPD differed from older COPD patients by the behavioral-related comorbidities that increase their risk of premature death.
Systemische Medikamenteneinnahme und das Risiko, an feuchter AMD zu erkranken
Authors: Strauß Olaf
Published: January 2023

Purpose: To examine whether systemic medications are associated with the subsequent development of wet age-related macular degeneration (AMD). Methods: A retrospective study of 259 562 individuals based on registry data, from January 1, 2001, to December 31, 2017. End-point event was the International Classification of Diseases (ICD)-10 diagnosis for wet AMD. Association between use of systemic medication covering 85 generic drugs categorized according to Anatomical Therapeutic Chemical (ATC) codes and the incidence of wet AMD was evaluated using multivariate Poisson regression model (adjusted for age, sex, diabetes, cancer and socioeconomic group) and nested case-control design. Results: The mean length of follow-up was 9.84 years. The number of cases with wet AMD was 2947 and incidence rate was 1.15 per 1000 person-years. After adjustment, we observed an increased risk for the development of wet AMD for patients exposed to amlodipine (IRR 1.33, 95% CI 1.16–1.53), or felodipine (1.24, 95% CI 1.02–1.50). Similarly, an increased risk of wet AMD was associated with the use of bicalutamide (2.14, 95% CI 1.14–4.02), estradiol (1.20, 95% CI 1.03–1.40) and atorvastatin (1.22, 95% CI 1.05–1.43). Of note, digoxin (0.72, 95% CI 0.57–0.91), and ramipril (0.80, 95% CI 0.65–0.99) users had a lower incidence of wet AMD. Conclusions: Our findings suggest that the use of second-generation calcium channel blockers could be associated with an increased risk for wet AMD development. Of note, the incidence of wet AMD seemed to be lower in patients using ramipril and dig­oxin. More studies are needed to elucidate the associations further.
Unregelmäßige Hautpigmentierung: Welchen Einfluss haben Algenextrakte aus der Blauen Lagune?
Authors: Makrantonaki Evgenia
Published: January 2023

Introduction: Bathing in the Blue Lagoon (BL) in Iceland benefits patients with psoriasis. Accordingly, the BL water contains algae with biological activities that improve skin barrier function and affect T-cell responses relevant for psoriasis. Bathing in the BL is also becoming increasingly popular among healthy individuals and anecdotal evidence suggests positive effects on uneven skin pigmentation. Objective: The aim of the study was to address the impact of BL algae on skin pigmentation. Methods: In this work, in vitro gene expression studies in melanocytes and a noninvasive in vivo study were conducted. Results: We here report that normal human epidermal melanocytes, which had been treated with nontoxic concentrations of BL algae, show a significantly reduced expression of α melanocyte-stimulating hormone-induced expression of genes important for melanin synthesis, such as tyrosinase, tyrosinase-related protein 1, dopachrome tautomerase, melan A protein, and pre-melanosome protein. This in vitro observation prompted us to conduct a randomized, double-blind, intra-individual, comparative split-face in vivo study, in which 60 volunteers with pre-existing facial pigment spots were treated twice daily with a BL algae containing serum or a vehicle control. We found that constitutive skin pigmentation as determined by colorimetry (individual typology angle and luminescence) did not differ significantly between vehicle- and serum-treated skin sites. In marked contrast, digital photography under cross-polarized lighting and RBX technology (VISIA CR) revealed that the number of pigment spots in the serum-treated face decreased significantly compared to the vehicle-treated side. Conclusion: Thus, BL algae can affect human melanocyte function in vitro and reduce uneven facial skin pigmentation in vivo.
Central GLP-1 Resistance Induced by Severe Traumatic Brain Injury Was Associated with Persistent Hyperglycemia in Humans
Authors: Zhou Min , Du Min , Tang Rui , Liu Hai-Yan , Gao Zhi , Wang Ying , You He-Yang , Hao JI-Wei , Ji Zong-Shu , Wang Di , Zhang Qing-Hong
Published: January 2023

Introduction: Whether central glucagon-like peptide 1 (GLP-1)/GLP-1 receptor system mediated peripheral glucose homeostasis in patients with traumatic brain injury (TBI) is not clear. We aim to determine if plasma GLP-1 level could distinguish the non-survivors from the survivors during the first 14 days after TBI that could prognose 6 months mortality. Methods: Metabolic, inflammatory, and hematologic profiles were examined in 73 patients with TBI in neurological intensive care unit. Factors that discriminate non-survivors from survivors were determined by two-way ANOVA. Biomarkers associated with mortality were determined by binary logistic regression and Cox proportional hazard regression. Results: The non-survivors had higher infectious SOFA scores (p < 0.001), lower first 3 days’ body temperature (p = 0.017), greater chance of cerebral hernia (p = 0.048), and decompressive craniectomy (p = 0.001) than the survivors. Higher 14-day plasma GLP-1 (p < 0.0001), glucose (p = 0.002), and IL-6 (p = 0.005) levels, in contrast with lower insulin level at days 4–7 (p = 0.020) were found in non-survivors than in survivors. Except the survivors who had an increased 14-day platelet number (p < 0.001), the two groups did not differ in hematological profile and intestinal barrier function. Although GLP-1 correlated closely with IL-6 in both the groups, it correlated with neither insulin nor glucose in each group. GLP-1 on days 8–10 and IL-6 on days 1–3 were positively, while insulin on days 4–7 was negatively associated with mortality. Conclusion: Persistent higher GLP-1 level in non-survivors over the survivors may present more severe central resistance to endogenous GLP-1 in non-survivors, which may be associated with progressive hyperglycemia with increased mortality in TBI.
IL-37 Ameliorates Renal Fibrosis by Restoring CPT1A-Mediated Fatty Acid Oxidation in Diabetic Kidney Disease
Authors: Xiong Li , He Ting , Liu Chi , Qin Shaozong , Xiao Tangli , Xin Wang , Wang Yaqin , Ran Li , Zhang Bo , Zhao Jinghong
Published: January 2023

Introduction: Diabetic kidney disease (DKD) is a major source of chronic kidney disease and end-stage renal disease. The injury of glomerulus in DKD is the primary focus; however, proximal tubulopathy also is an indispensable factor in the progression of DKD. Interleukin-37 (IL-37), an anti-inflammatory cytokine of IL-1 family member, has been demonstrated to be associated with diabetes and its relative complications in recent years, but the effect of IL-37 on renal fibrosis in DKD is unclear. Methods: We established streptozotocin plus high fat diet-induced DKD mice model with wild type or IL-37 transgenic mice. Masson and HE staining, immunostaining, and Western blot were used to observe renal fibrosis. In addition, RNA-sequencing was applied to explore the potential mechanisms of IL-37. In vitro, treatment of human proximal tubular (HK-2) cells with 30 mmol/L high glucose or 300 ng/mL recombinant IL-37 further elucidated the possible mechanism of IL-37 inhibition of DKD renal fibrosis. Results: In this work, we first verified the decreased expression of IL-37 in kidney of DKD patient and its correlation with clinical features of renal impairment. Moreover, IL-37 expression markedly attenuated proteinuria and renal fibrosis in DKD mice. Using RNA-sequencing, we found and confirmed a novel role of IL-37 in ameliorating fatty acid oxidation (FAO) reduction of renal tubular epithelial cells both in vivo and in intro. In addition, further mechanistic studies showed that IL-37 alleviated the FAO reduction in HK-2 cells and renal fibrosis in DKD mice through upregulating carnitine palmitoyl-transferase 1A (CPT1A), an important catalyzer for FAO pathway. Conclusion: These data suggest that IL-37 attenuates renal fibrosis via regulating FAO in renal epithelial cells. Upregulation of IL-37 levels might be an effective therapeutic avenue for DKD.
High-efficiency 2.45 and 5.8 GHz dual-band rectifier design with modulated input signals and a wide input power range
Authors: El Mattar Sara , Baghdad Abdennaceur
Published: January 2023

This paper presents a new rectifier design for radio frequency (RF) energy harvesting by adopting a particular circuit topology to achieve two objectives at the same time. First, work with modulated input signal sources instead of only continuous waveform (CW) signals. Second, operate with a wide input power range using the Wilkinson power divider (WPD) and two different rectifier diodes (HSMS2852 and SMS7630) instead of using active components. According to the comparison with dual-band rectifiers presented in the literature, the designed rectifier is a high-efficiency rectifier for wide RF power input ranges. A peak of 67.041% and 49.089% was reached for 2.45 and 5.8 GHz, respectively, for CW as the input signal. An efficiency of 72.325% and 45.935% is obtained with a 16 QAM modulated input signal for the operating frequencies, respectively, 69.979% and 54.579% for 8PSK. The results obtained demonstrate that energy recovery systems can use modulated signals. Therefore, the use of a modulated signal over a CW signal may have additional benefits.
Modelling and simulation for energy management of a hybrid microgrid with droop controller
Authors: Saadaoui Khalil , Rhazi Kaoutar Senhaji , Mejdoub Youssef , Aboudou Abderraouf
Published: January 2023

The most efficient and connected alternative for increasing the use of local renewable energy sources is a hybrid microgrid, these systems face additional challenges due to the integration of power electronics, energy storage technologies and traditional power plants. The hybrid alternating current-direct current (AC-DC) microgrid that is the subject of this research uses a primary-droop control system to regulate state variables and auxiliary services, thus, it is composed of batteries, solar panels and a miniature wind turbine (PDC) and controls how each energy source in a microgrid contributes to the final product. To achieve the given objectives, this paper will create appropriate models for each part of the microgrid design and define, among them, the energy storage batteries and power electronic converters required for each level of each of these systems. Finally, the dynamic nature of the system will be critically evaluated and characterized, to distribute the load and reduce imbalances, modify the primary drop of the resulting microgrid using MATLAB simulation.
Sensitivity of solar panel energy conversion at sunrise and sunset on three weather fluctuations in equatorial climate
Authors: Satria Habib , Syah Rahmad , Silviana Nukhe Andri , Syafii Syafii
Published: January 2023

The high sunlight intensity in tropical and equatorial regions makes the potential for installing photovoltaic (PV) panels. However, the initial design of PV installations must be analyzed. Their implementation is carried out in buildings with load power for household electricity scale. For this reason, the panel reliability system could be efficient by designing the initial PV requirements using systematic measurements. Collecting data on fluctuating sunlight intensity (unpredictable weather) conditions needs the use of manual measuring tools, namely digital light meters and PV data with sensor integration. The research sample consists of three fluctuating hot weather conditions, namely hot-sunny, hot-cloudy and hot-rainy conditions. These weather conditions were taken because the climate of West Sumatra tends to shift clouds which sometimes cover the sun's rays. The peak PV output for direct current (DC) power generated during hot- sunny conditions reaches 1827.17 W, in sunny-cloudy weather it reaches around 1626.85 W and during sunny-rainy weather conditions the resulting output is 1161.81 W. From daily measurements, the results show that the efficiency of the PV system is strongly influenced by the prevailing weather climate.
Stability analysis and speed control of brushless DC motor based on self-ameliorate soft switching control methods
Authors: Rao Nagaraj , Rai Chelladka Shantharama
Published: January 2023

In recent years, electric vehicles are the large-scale spread of the transportation field has led to the emergence of brushless direct current (DC) motors (BLDCM), which are mostly utilized in electrical vehicle systems. The speed control of a BLDCM is a subsystem, consisting of torque, flux hysteresis comparators, and appropriate switching logic of an inverter. Due to the sudden load torque variation and improper switching pulse, the speed of the BLDCM is not maintained properly. In recent research, the BLDC current control method gives a better way to control the speed of the motor. Also, the rotor position information should be the need for feedback control of the power electronic converters to varying the appropriate pulse width modulation (PWM) of the inverter. The proposed optimization work controls the switching device to manage the power supply BLDCM. In this proposed self-ameliorate soft switching (SASS) system is a simple and effective way for BLDC motor current control technology, a proposed control strategy is intended to stabilize the speed of the BLDCM at different load torque conditions. The proposed SASS system method is analyzing hall-based sensor values continuously. The suggested model is simulated using the MATLAB Simulink tool, and the results reveal that the maximum steady-state error value achieved is 4.2, as well as a speedy recovery of the BLDCM's speed.
Fuzzy-proportional-integral-derivative-based controller for object tracking in mobile robots
Authors: Vuong Duc-Phuc , Nguyen Trong-Thang
Published: January 2023

This paper aims at designing and implementing an intelligent controller for the orientation control of a two-wheeled mobile robot. The controller is designed in LabVIEW and based on analyzed image parameters from cameras. The image program calculates the distance and angle from the camera to the object. The fuzzy controller will get these parameters as crisp input data and send the calculated velocity as crisp output data to the right and left wheel motor for the robot tracking the target object. The results show that the controller gives a fast response and high reliability and quickly carries out data recovery from system faults. The system also works well in the uncertainties of process variables and without mathematical modeling.
A new approach to design line start permanent magnet synchronous motors
Authors: Swierczynski Karol , Antal Maciej , Habrych Marcin , Brusilowicz Bartosz
Published: January 2023

The article describes a new approach to line start permanent magnet synchronous motors (LSPMSM) design process. This different, novel approach is based on the modification of mass-produced induction motors. The presented method facilitates and expedites the electrical motor design process. A field-circuit model of the motor has been created to expound the methodology of the process. Then, the machine's geometry was changed to apply permanent magnets. The problems and benefits associated with the use of permanent magnets were described. The created model was tested. The authors examined the operation of the LSPMSM motor in different states, such as starting, no-load, and blocked-rotor tests. Electromechanical characteristics have been plotted. The simulation results were compared with the parameters and characteristics of the induction motor. The conducted tests proved the correctness of the design process. The operational properties of the motor have been improved. Moreover, the validity of using LSPMSM motors instead of induction motors has also been demonstrated.
Research trends on microgrid systems: a bibliometric network analysis
Authors: Tambunan Handrea Bernando , Priambodo Nur Widi , Hartono Joko , Aditya Indra Ardhanayudha , Triani Meiri , Rasgianti Rasgianti
Published: January 2023

The numeral of academic publications in the microgrid system field has rapidly grown. A microgrid system is a group of interconnected distributed generation, loads, and energy storage operating as a single controllable entity. Many published articles recently focused on distributed generation, system control, system stability, power quality, architectures, and broader focus areas. This work analyzes microgrid: alternating current (AC), direct current (DC), and hybrid AC/DC microgrid systems with bibliometric network analysis through descriptive analysis, authors analysis, sources analysis, words analysis, and evolutionary path based on the Scopus database between 2010 and 2021. The finding helps find out the top authors and most impact sources, most relevant and frequently used in the research title, abstract, and keyword, graphically mapping the research evolved and identifying trend topic.
Design of the electric propulsion system for dumper trucks
Authors: Naranjo Lourido Walter , Riaño Ocampo Luis Ariel , Gallego Chipiaje Gustavo Andres , Baquero Javier Eduardo Martinez , Rodriguez Umaña Luis Alfredo
Published: January 2023

This article designs a high-efficiency electric propulsion system for industrial trucks, such as dumper trucks. This design proposes using an alternative energy storage system of green H2 hydrogen to reduce emissions. This design determines the propulsion systems' technical and power requirements, starting with each vehicle's driving and duty cycles. For this analysis, a longitudinal dynamic model is created, with which the behavior of the energy conversion chain of the propulsion system is established. The evolutionary methodology analyzes the dynamic forces of vehicle interaction to size the propulsion system's components and the storage system. Using green H2 as fuel allows an energy yield three times higher than diesel. In addition, using this green hydrogen prevents the emission of 264,172 kg of CO₂, which the dumper emits when consuming 1,000 daily gallons of diesel within its working day.
Optimal protective relaying scheme of distributed generation connected distribution network using particle swarm optimization-gravitational search algorithm technique
Authors: Bheemasenarao Arathi Pothakanahalli , Byalihal Shankaralingappa C
Published: January 2023

This paper develops particle swarm optimization integrated with gravitational search algorithm (PSO-GSA) to coordinate the relays in a distribution system with distributed generation (DG) connectivity. This algorithm combines PSO and GSA to improve the performance of the relay protection system. To prevent relay malfunctions following DG penetration, a suitable primary and backup relay is chosen. The PSO-GSA is coded using MATLAB software and tested on an IEEE 4-bus system simulated in Simulink. Results indicate that, when compared to using regular PSO and GSA procedures individually, the PSO-GSA technique reduces the operating time of the relay significantly.
Modeling of magnetic sensitivity of the metal-oxide-semiconductor field-effect transistor with double gates
Authors: Hasan Ghanim Thiab , Mutlaq Ali Hlal , Ali Kamil Jadu , Saad Mohammed Ayad
Published: January 2023

In this paper, we investigated the effect of magnetic field on the carrier transport phenomenon in metal-oxide-semiconductor field-effect transistor (MOSFET) with double gates by examining the behavior of the semiconductor under the Lorentz force and a constant magnetic field. Various behaviors within the channel have been simulated including the potential distribution, conduction and valence bands, total current density, total charge density and the magnetic field. The results obtained indicate that this modulation affects the electrical characteristics of the device such as on-state current (ION), subthreshold leakage current (IOF), threshold voltage (VTh), and the Hall voltage (VH) is induced by the magnetic field. The change in threshold voltage caused by the magnetic field has been observed to affect the switching characteristics of the device, such as speed and power loss, as well as the threshold voltage VTh and (ION/IOF) ratio. Note that it is reduced by 10-3 V. 102 for magnetic fields of ±6 and ±5.5 tesla respectively.
Simulation model of ACO, FLC and PID controller for TCP/AQM wireless networks by using MATLAB/Simulink
Authors: Awad Buraq Abdulhadi , Oudah Manal Kadhim , Enaya Yaser Ali , Shneen Salam Waley
Published: January 2023

The current work aims to develop a suitable design for control systems as part of a queue management system using the transmission control protocol/and active queue management (TCP/AQM) protocol to handle the expected congestion in the network. The research also aims to make a comparison between the different control methods, including the traditional proportional integral derivative (PID) and the expert fuzzy logic control (FLC), as well as the optimal ant colony optimization (ACO) that is used according to the performance improvement criteria to reach the best values for parameters the traditional controller (kd, ki, k p), where the addition of the performance indicator time-weighted absolute error (ITAE) was adopted. The use of this method without any other optimization algorithm that can be applied to adjust the parameters of the PID to verify the possibility of improving performance and enhance that with experience and to know the level of improvement for this particular system being the subject of the study. The results showed the superiority of the optimal ACO over both the FLC expert and the conventional PID, as well as the superiority of the FLC expert over the traditional PID.
Design and fabrication of a moving robotic glove system
Authors: Thu Ha Vo , Thanh Nguyen Thi , Ha Vo Thanh
Published: January 2023

This paper presents the research, design, and manufacture of a robotic hand to control movement with a glove. The moving glove-controlled robotic hand is based on two main parts: the hand mechanism and the control circuit. The control glove unit includes an Arduino nRF24l01 microcontroller module and five flex sensors for five fingers. These sensors are used to collect data about the curvature of each finger. Then those data will be received by the Arduino microcontroller and sent by the nRF24l01 module. The hand's microcontroller will process that information and control five servo motors so that the five fingers of the robotic hand are moved. The result of this research is to produce a robotic hand that accurately simulates the curvature of a user's finger and mimics the motion of a glove well. Moreover, the robot hand can grip objects of different sizes (from 0.1 to 1 kg) and shapes, from which this robot helps users easily manipulate objects.
Multimode system condition monitoring using sparsity reconstruction for quality control
Authors: Bougheloum Wafa , Bekaik Mounir , Gherbi Sofiane
Published: January 2023

In this paper, we introduce an improved multivariate statistical monitoring method based on the stacked sparse autoencoder (SSAE). Our contribution focuses on the choice of the SSAE model based on neural networks to solve diagnostic problems of complex systems. In order to monitor the process performance, the squared prediction error (SPE) chart is linked with nonparametric adaptive confidence bounds which arise from the kernel density estimation to minimize erroneous alerts. Then, faults are localized using two methods: contribution plots and sensor validity index (SVI). The results are obtained from experiments and real data from a drinkable water processing plant, demonstrating how the applied technique is performed. The simulation results of the SSAE model show a better ability to detect and identify sensor failures.
Software calibration for AK8963 magnetometer based on optimal ellipsoidal fitting
Authors: El fatimi Aziz , Addaim Adnane , Guennoun Zouhair
Published: January 2023

With the rapid development of mechatronics, systems in package (SiP), in particular the MPU-9250 inertial measurement Unit 9DOF (MPU-6050 6DOF and AK8963 3DOF), are becoming ubiquitous in applications for autonomous navigation purposes. Nevertheless, they suffer from some accuracy problems related to axis misalignment, disturbances, and deviation over time that make them unable to work autonomously for a long time. This paper will present a simple and practical calibration method using a least-squares based ellipsoid fitting method to calibrate and compensate for the error interference of the AK8963 sensor. Towards the end of this paper, a comparison between before and after the calibration is presented to study the software compensation effect and the stability of the magnetic sensor under study.
Semi-automatic model to colony forming units counting
Authors: Pinto-Lopera Jesus Emilio , Meneses-Cabezas Diana Carolina , Zapata-Serna Yuliana , Garces-Gomez Yeison Alberto
Published: January 2023

Colony forming units counting is a conventional process carry out in bacteriological laboratories, and it is used to follow the behavior of bacteria in different conditions. Currently exist different systems, automatic or semi-automatic, to counting colony forming units exits, but, in general, many laboratories continue using manual counting, which consumes considerable time and effort from researchers and laboratory employees. This paper presents a mathematical model carry out to segment the colony forming units and, in this way, counting them from a digital image of the sample. The method uses the color space information of some points in the image and shows good behavior for images with many or few colony forming units in the sample, according to manual counting. The results show efficiencies close to 98% with MacConkey agar.
An optimized discrete wavelet transform compression technique for image transferring over wireless multimedia sensor network
Authors: Bennani Mohamed Taj , Yaden Mohamed Faysal
Published: January 2023

Transferring images in a wireless multimedia sensor network (WMSN) knows a fast development in both research and fields of application. Nevertheless, this area of research faces many problems such as the low quality of the received images after their decompression, the limited number of reconstructed images at the base station, and the high-energy consumption used in the process of compression and decompression. In order to fix these problems, we proposed a compression method based on the classic discrete wavelet transform (DWT). Our method applies the wavelet compression technique multiple times on the same image. As a result, we found that the number of received images is higher than using the classic DWT. In addition, the quality of the received images is much higher compared to the standard DWT. Finally, the energy consumption is lower when we use our technique. Therefore, we can say that our proposed compression technique is more adapted to the WMSN environment.
Compressive speech enhancement using semi-soft thresholding and improved threshold estimation
Authors: Sahu Smriti , Rayavarapu Neela
Published: January 2023

Compressive speech enhancement is based on the compressive sensing (CS) sampling theory and utilizes the sparsity of the signal for its enhancement. To improve the performance of the discrete wavelet transform (DWT) basis-function based compressive speech enhancement algorithm, this study presents a semi-soft thresholding approach suggesting improved threshold estimation and threshold rescaling parameters. The semi-soft thresholding approach utilizes two thresholds, one threshold value is an improved universal threshold and the other is calculated based on the initial-silence-region of the signal. This study suggests that thresholding should be applied to both detail coefficients and approximation coefficients to remove noise effectively. The performances of the hard, soft, garrote and semi-soft thresholding approaches are compared based on objective quality and speech intelligibility measures. The normalized covariance measure is introduced as an effective intelligibility measure as it has a strong correlation with the intelligibility of the speech signal. A visual inspection of the output signal is used to verify the results. Experiments were conducted on the noisy speech corpus (NOIZEUS) speech database. The experimental results indicate that the proposed method of semi-soft thresholding using improved threshold estimation provides better enhancement compared to the other thresholding approaches.
Bio-inspired intelligence for minimizing losses in substrate integrated waveguide
Authors: Akkader Souad , Bouyghf Hamid , Baghdad Abdennaceur
Published: January 2023

This paper presents a study of various types of losses in substrate-integrated waveguides (SIW) using a genetic algorithm. Three main types of losses are considered and examined separately: conductor loss, dielectric loss, and radiation loss. Furthermore, the current analysis allows for a physical understanding of the loss impacts as well as the creation of design guidelines to reduce losses at 10 GHz frequency while keeping the miniaturized size of the SIW. Validation results obtained using the software Ansys HFSS, verify that the attenuation constant of the SIW can be significantly reduced to  0.4 dB/m, the Insertion loss S21 to -0.2 dB and the return loss to -38 dB if the geometric parameters are chosen properly. This study enables us to identify the source of losses in a SIW and, as a result, eliminate any type of dispersion. That demonstrates the usability of SIW technologies in the design of microwave circuits used in Internet of things applications.
Improving the error performance of offset pulse position modulation using Reed–Solomon error correction code and low-density parity
Authors: Salman Ahmed Hasan , Al-Nedawe Basman Monther , Shuja'a Mohamed Ibrahim
Published: January 2023

An innovative performance study of an offset pulse-position modulation (OPPM) scheme is presented in this work with Reed–Solomon (RS) and low-density parity-checking (LDPC). The main aim is to resolve the errors of OPPM three using an RS or LDPC as a sporadic set of forward error correction (FEC). In this regard, the separate FEC has been utilized with coding that is based on multi-level, and waveform shaping based on the trellis. To systematically conduct this research, the greatest transmission efficiency that associated with the optimum RS code rates at different fiber normalization bandwidths is evaluated. Furthermore, the transmission efficiencies, channel extension, as well as the required number of photons per pulse of OPPM before and after the integration with RS or LDPC are compared. The results indicate an enhancement of mitigating the system's bit error rate and delivering more error-free data to the receiver in the occasion of applying the optimal settings of the RS or LDPC.
Improving the reliability in bio-nanosensor modules using hardware redundancy techniques
Authors: Ghasemzadeh Rahebeh , Farazkish Razieh , Amiri Nasrin , Sahafi Amir
Published: January 2023

A nano-robot is a controlled robotic system at the nanoscale. Nowadays, nanorobotics has become of particular interest in medicine and pharmacy. The accurate diagnosis of the diseases as well as their rapid treatment will make everyone surprised and will significantly reduce the associated risks. The modeling of reliability in biosensors is studied for the first time in this paper. The use of practical hardware redundancy has turned into the most cost-effective to improve the reliability of a system. Additionally, the Markov model is used to design fault-tolerant systems in nanotechnology. The proposed method is compared with some existing methods, such as triple modular redundancy and non-fault-tolerant systems; it is shown that using this method, a larger number of faults between 3-5 can be tolerated. Using the proposed method, the number of modules can be increased to nine. However, a larger number than 9 MR is not recommended because of an increased delay and requiring more hardware. As the scale of components used in digital systems has gotten smaller, the use of hardware redundancy has become cost-effective. But there is a trade-off between the amount of used hardware and fault tolerance, which can also be investigated.
Exploring machine learning techniques for fake profile detection in online social networks
Authors: Bharti Bharti , Gill Nasib Singh , Gulia Preeti
Published: January 2023

The online social network is the largest network, more than 4 billion users use social media and with its rapid growth, the risk of maintaining the integrity of data has tremendously increased. There are several kinds of security challenges in online social networks (OSNs). Many abominable behaviors try to hack social sites and misuse the data available on these sites. Therefore, protection against such behaviors has become an essential requirement. Though there are many types of security threats in online social networks but, one of the significant threats is the fake profile. Fake profiles are created intentionally with certain motives, and such profiles may be targeted to steal or acquire sensitive information and/or spread rumors on online social networks with specific motives. Fake profiles are primarily used to steal or extract information by means of friendly interaction online and/or misusing online data available on social sites. Thus, fake profile detection in social media networks is attracting the attention of researchers. This paper aims to discuss various machine learning (ML) methods used by researchers for fake profile detection to explore the further possibility of improvising the machine learning models for speedy results.
Dysgraphia detection based on convolutional neural networks and child-robot interaction
Authors: Gouraguine Soukaina , Riad Mustapha , Qbadou Mohammed , Mansouri Khalifa
Published: January 2023

Dysgraphia is a disorder of expression with the writing of letters, words, and numbers. Dysgraphia is one of the learning disabilities attributed to the educational sector, which has a strong impact on the academic, motor, and emotional aspects of the individual. The purpose of this study is to identify dysgraphia in children by creating an engaging robot-mediated activity, to collect a new dataset of Latin digits written exclusively by children aged 6 to 12 years. An interactive scenario that explains and demonstrates the steps involved in handwriting digits is created using the verbal and non-verbal behaviors of the social humanoid robot Nao. Therefore, we have collected a dataset that contains 11,347 characters written by 174 participants with and without dysgraphia. And through the advent of deep learning technologies and their success in various fields, we have developed an approach based on these methods. The proposed approach was tested on the generated database. We performed a classification with a convolutional neural network (CNN) to identify dysgraphia in children. The results show that the performance of our model is promising, reaching an accuracy of 91%.
An optimized deep learning model for optical character recognition applications
Authors: Salih Sinan Q. , L. Khalaf Ahmed , Sami Mohsin Nuha , Fahad Jabbar Saadya
Published: January 2023

The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recognition applications; the proposed method was evaluated for performance in terms of computational accuracy, convergence analysis, and cost.
Design and analysis of a new brake-by-wire system using machine learning
Authors: Hassanein Ahmed , Dawod Nourhan , Hassan Nouran
Published: January 2023

One of the main aims of the recent research on brake-by-wire systems is to decrease mechanical components. In this paper, we propose replacing the brake pedal with a driving wheel that is fully covered by pressure braking batch sensors. The new mechanism for braking translates pressure exerted through the driver’s hands on the driving wheel to a corresponding electrical signal. A proposed design for the pressure braking batch (PBB) is made out of a mesh of conducting threads separated by a resistive sheet. To the best of our knowledge, this idea has not been raised before in other research papers. Different people have different muscle strengths and so the problem of identifying the intention of the user when pressing the PBB is tackled. For this aim, a new dataset of its kind is created by several volunteers. From each volunteer, age, gender, body mass index (BMI), and maximum pressure exerted on the driving wheel are collected. Using Weka software, the detection accuracy is calculated for a new volunteer to know the intention of his/her pressure on PBB. Among the three algorithms tried, the regression tree gives the best results in predicting the class of the pressure exerted by the volunteers.
Techniques of deep learning and image processing in plant leaf disease detection: a review
Authors: Kini Anita S. , Reddy Prema K. V. , Pai Smitha N.
Published: January 2023

Computer vision techniques are an emerging trend today. Digital image processing is gaining popularity because of the significant upsurge in the usage of digital images over the internet. Digital image processing is a practice that can help in designing sophisticated high-end machines, which can hold the ophthalmic functionality of the human eye. In agriculture, leaf examination is important for disease identification and fair warning for any deficiency within the plant. Many prominent plant species are facing extinction because of a lack of knowledge. A proper realization of computer vision techniques aid in extracting a significant amount of information from leaf image. This necessitates the requirement of an automatic leaf disease detection method to diagnose disease occurrences and severity, for timely crop management, by spraying pesticides. This study focuses on techniques of digital image processing and machine learning rendered in plant leaf disease detection, which has great potential in precision agriculture. To support this study, techniques exercised by various researchers in recent years are tabulated.