Improved Energy Conversion Process With Coupling Induction Motors And Invastigate Unbalanced Operation With Definition Of The Voltage Unbalance

This paper assesses Voltage unbalance study as one of power quality issues which is especially effected distribution voltages and is noteworthy. however it is possible that voltage in level of producing and transmission be balanced but this voltages in level of distribution can go out of balance and be unbalanced which is because of unbalanced systems, unequal impedances and lack of appropriate and balanced distribution of one phase loads in distribution systems occurs. In this thesis operation of steady state machine conjunction (Induction motor) under unbalanced voltage will be evaluated. Induction motors in small sizes attach as coupled and will be used instead of big sized induction motors, which is proper for improved electromagnetic systems and more efficient energy conversion mechanism in both symmetric and asymmetric states. Two coupled induction motors can have the same or different rates mechanically. This thesis will analyze coupled machinery using symmetric elements and MATLAB software. Definition of unbalance voltage is used by CVUF factor (complex voltage unbalance factor). Induction motors coupling with DC motors (direct current) is analyzed and coupling effect in electromagnetic torque in all system is studied and comparing of unbalanced voltage on standalone and coupled machines is demonstrateed. The purpose of such comparing is finding the best states in balanced and unbalanced working, also this thesis evaluates the effect of induction motors connection as coupling in energy conversion process

5G NR-V2X: Towards Connected and Cooperative Autonomous Driving

This paper is concerned with the key features and fundamental technology components for 5G New Radio (NR) for genuine realization of connected and cooperative autonomous driving. We discuss the major functionalities of physical layer, Sidelink features and its resource allocation, architecture flexibility, security and privacy mechanisms, and precise positioning techniques with an evolution path from existing cellular vehicle-to-everything (V2X) technology towards NR-V2X. Moreover, we envisage and highlight the potential of machine learning for further enhancement of various NR-V2X services. Lastly, we show how 5G NR can be configured to support advanced V2X use cases in autonomous driving

Low-Level Laser Irradiation Modulated Viability of Normal and Tumor Human Lymphocytes In Vitro

Introduction: Laser radiation is a promising strategy against various malignancies. Recent studies have shown that the application of low-power laser therapy (LPLT) at different doses and exposure times could modulate the growth dynamic of tumor cells. Based on the type of laser, LPLT could potentially trigger cell proliferation, differentiation, and apoptosis in different cell lines.Methods: In this study, MTT assay was used to monitor the effect of low and high laser intensities on the viability of normal and cancer lymphocytes. The protein levels of Ki-67 (a proliferation marker) and Caspase-3 (an apoptosis factor) were measured in human peripheral mononuclear cells (PBMCs) and the B-lymphoblastic cell line (Nalm-6) using flow cytometry after being-exposed to 630-nm LPLT at low (2, 4, 6, and 10 J/cm2) and high (15, 30, 60, and 120 J/cm2) energy densities in a continuous mode for 48 and 72 hours.Results: By using higher energy densities, 60 and 120 J/cm2, a significant decrease was shown in the viability of Nalm-6 cells, which reached 6.6 and 10.1% after 48 hours compared to the control cells (P < 0.05). Notably, Cell exposure to doses 30, 60, and 120 J/cm2 yielded 7.5, 12.9, and 21.6 cell viability reduction after 72 hours. The collected data showed that the high-intensity parameters of LPLT (15 to 120 J/cm2) promoted significant apoptotic changes in the exposed cells coincided with the activation of Caspase-3 compared to the none-treated control cells (P < 0.05). The data further showed the stimulation of the Ki-67 factor both in primary PBMCs and the lymphoblastic cell line treated with LPLT at energy densities of 4 and 6 J/cm2 (P < 0.05), indicating enhanced cell proliferation. Similar to Nalm-6 cells, primary PBMCs showed apoptosis after 48 hours of being exposed to doses 60, and 120 J/cm2, indicated by increased Caspase-3 levels (P < 0.05). As expected, the Nalm-6 cells were resistant to cytotoxic effects of laser irradiation in the first 48 hours (P > 0.05) compared to normal PBMCs. The exposure of Nalm-6 cells to low-intensity laser intensities increased a proliferation rate compared to the PBMCs treated with the same doses.Conclusion: We showed the potency of LPLT in the induction of apoptosis and proliferation in human primary PBMCs and Nalm-6 cells in a dose and time-dependent manner after 72 hours.

5G NR-V2X: Toward Connected and Cooperative Autonomous Driving

5G New Radio (NR) is touted as a pivotal enabling technology for the genuine realization of connected and cooperative autonomous driving. Despite numerous research efforts in recent years, a systematic overview on the role of 5G NR in future connected autonomous communication networks is missing. To fill this gap and to spark more future research, this article introduces the technology components of 5G NR and discusses the evolution from existing cellular vehicle-to-everything (V2X) technology toward NR-V2X. We primarily focus on the key features and functionalities of the physical layer, sidelink communication and its resource allocation, architecture flexibility, security and privacy mechanisms, and precise positioning techniques. Moreover, we envisage and highlight the potential of machine learning for further performance enhancement in NR-V2X services. Lastly, we show how 5G NR can be configured to support advanced V2X use cases

5G NR-V2X: Toward Connected and Cooperative Autonomous Driving

5G New Radio (NR) is touted as a pivotal enabling technology for the genuine realization of connected and cooperative autonomous driving. Despite numerous research efforts in recent years, a systematic overview on the role of 5G NR in future connected autonomous communication networks is missing. To fill this gap and to spark more future research, this article introduces the technology components of 5G NR and discusses the evolution from existing cellular vehicle-to-everything (V2X) technology toward NR-V2X. We primarily focus on the key features and functionalities of the physical layer, sidelink communication and its resource allocation, architecture flexibility, security and privacy mechanisms, and precise positioning techniques. Moreover, we envisage and highlight the potential of machine learning for further performance enhancement in NR-V2X services. Lastly, we show how 5G NR can be configured to support advanced V2X use cases

Recent Advances in Machine Learning for Network Automation in the O-RAN

© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/The evolution of network technologies has witnessed a paradigm shift toward open and intelligent networks, with the Open Radio Access Network (O-RAN) architecture emerging as a promising solution. O-RAN introduces disaggregation and virtualization, enabling network operators to deploy multi-vendor and interoperable solutions. However, managing and automating the complex O-RAN ecosystem presents numerous challenges. To address this, machine learning (ML) techniques have gained considerable attention in recent years, offering promising avenues for network automation in O-RAN. This paper presents a comprehensive survey of the current research efforts on network automation using ML in O-RAN. We begin by providing an overview of the O-RAN architecture and its key components, highlighting the need for automation. Subsequently, we delve into O-RAN support for ML techniques. The survey then explores challenges in network automation using ML within the O-RAN environment, followed by the existing research studies discussing application of ML algorithms and frameworks for network automation in O-RAN. The survey further discusses the research opportunities by identifying important aspects where ML techniques can benefit.Peer reviewe

Tracking of chloramphenicol, erythromycin, and sulfamethoxazole antibiotic-resistant bacteria from untreated wastewater effluents to receiving river

Background: The aim of this study was to investigate the frequency and type of bacteria resistant to chloramphenicol (CHL), erythromycin (E), and sulfamethoxazole (SXT) antibiotics from untreated wastewater effluents to receiving river. Methods: In total, 32 samples were taken from eight sites located in the raw wastewater to the downstream of the receiving Ghotor river in Khoy city. Resistant microorganisms were studied through modified HPC method and CLSI standards. Different and specific colonies were selected and re-cultured in R2A culture medium and enough colonies were used for DNA extraction. Bacterial 16sr RNA target gene was amplified and sequenced. Pseudomonas sp., Comamonas sp., and Thiobacillus sp. were predominant bacterial species identified in water samples. Also, antibiotic-resistant genes (ARGs) including sul1, ermB, and cmlA1 were tracked by PCR. Results: The average total number of antibiotic-resistant bacteria (ARB) increased in the downstream (2.4×102 to 2.6×104 CFU/100 mL). The comparison of the results related to the river’s upstream and downstream also indicated a significant difference between ARB and ARGs contents (P<0.05). The average number of bacteria resistant to SXT, E, and CHL antibiotics was obtained to be 2.3×104, 2.3×104, and 3.4×104 CFU/mL, respectively. Finally, the evaluation of water revealed that only the aeration lagoon was able to decline the number of CHL-resistant bacteria (88.9%) while this process increased the number of SXT- (51%) and E- (16%) resistant bacteria. The lowest and highest percentages of the identified genes were related to ermB (12.5%) and sul1 (81.25%), respectively. Conclusion: According to the results, wastewaters play an important role in releasing ARB and their antibiotic resistance genes to downstream of Ghotor rivers in Khoy city. Keywords: Heterotrophic bacteria, Sulfamethoxazole, Chloramphenicol, Erythromycin, Polymerase chain reaction, Wastewater, River