Islanding Detection Techniques for Synchronous Distributed Generation

The issue of unintentional islanding detection of grid connected synchronous distributed generation (SDG) remains the most challenging task faced by the distributed generation (DG) industry as SDG is highly capable of prolonging an island. This paper gives an insight of anti-islanding detection techniques mainly applied for SDG. Different techniques conclude that it is challenging to point out a generic method for a distinct purpose as the application of particular practice depends on nature of the end use and system dependent elements. Also, the setup and operational cost affect the selection of anti-islanding technique to achieve minimal compromising between cost and system quality. A test bench is created in the MATLAB/Simulink® to demonstrate the results of a 33 kV system. The results are highly satisfactory and they are according to the current practices

Anti-Androgenic Therapies Targeting the Luminal Androgen Receptor of a Typical Triple-Negative Breast Cancer

Triple-negative tumors are progressively delineating their existence over the extended spectrum of breast cancers, marked by intricate molecular heterogeneity, a low overall survival rate, and an unexplored therapeutic approach. Although the basal subtype transcends the group and contributes approximately 80% to triple-negative breast cancer (TNBC) cases, the exceptionally appearing mesenchymal and luminal androgen receptor (LAR) subtypes portray an unfathomable clinical course. LAR with a distinct generic profile frequently metastasizes to regional lymph nodes and bones. This subtype is minimally affected by chemotherapy and shows the lowest pathologic complete response. The androgen receptor is the only sex steroid receptor that plays a cardinal role in the progression of breast cancers and is typically overexpressed in LAR. The partial AR antagonist bicalutamide and the next-generation AR inhibitor enzalutamide are being assessed in standard protocols for the mitigation of TNBC. There arises an inevitable need to probe into the strategies that could neutralize these androgen receptors and alleviate the trajectory of concerning cancer. This paper thus focuses on reviewing literature that provides insights into the anti-androgenic elements against LAR typical TNBC that could pave the way for clinical advancements in this dynamic sphere of oncology

Anti-Androgenic Therapies Targeting the Luminal Androgen Receptor of a Typical Triple-Negative Breast Cancer

Triple-negative tumors are progressively delineating their existence over the extended spectrum of breast cancers, marked by intricate molecular heterogeneity, a low overall survival rate, and an unexplored therapeutic approach. Although the basal subtype transcends the group and contributes approximately 80% to triple-negative breast cancer (TNBC) cases, the exceptionally appearing mesenchymal and luminal androgen receptor (LAR) subtypes portray an unfathomable clinical course. LAR with a distinct generic profile frequently metastasizes to regional lymph nodes and bones. This subtype is minimally affected by chemotherapy and shows the lowest pathologic complete response. The androgen receptor is the only sex steroid receptor that plays a cardinal role in the progression of breast cancers and is typically overexpressed in LAR. The partial AR antagonist bicalutamide and the next-generation AR inhibitor enzalutamide are being assessed in standard protocols for the mitigation of TNBC. There arises an inevitable need to probe into the strategies that could neutralize these androgen receptors and alleviate the trajectory of concerning cancer. This paper thus focuses on reviewing literature that provides insights into the anti-androgenic elements against LAR typical TNBC that could pave the way for clinical advancements in this dynamic sphere of oncology

Qualitative survey on artificial intelligence integrated blockchain approach for 6G and beyond

Abstract Utilizing the 0.1 to 10 THz spectrum in the next-generation wireless communication networks holds potential for futuristic applications. However, managing resources to accommodate numerous devices raises privacy and security concerns. Further, technology proliferation entwines devices, infrastructure complexity, and resources. Indeed, the transition from 5G (fifth-generation) to 6G (sixth-generation) signifies a progression towards high-speed data rates, minimal latency, and seamless integration of artificial intelligence, enabling ground-breaking applications and services. However, it complicates network management, privacy, resource allocation, and data processing. Notably, integrating Blockchain Technology (BCT) and Machine Learning (ML) is a promising solution, enhancing security, decentralization, trust in ML decisions, and efficient data sharing. This survey thoroughly reviews the integrated ML and BCT, showcasing their collaborative enhancement of network security, decentralization, trust in ML decisions, immutability, and efficient model sharing. Furthermore, we also delve into various distinctive topics, such as BCT-enabled spectrum refarming, rate splitting multiple access, 6G radar-based communication, reconfigurable intelligent surfaces, visible light communication, and integrated sensing and communication. Moreover, it also explores the integration of ML and BCT in novel 6G communication technologies, including molecular, holographic, and semantic communication. Finally, critical open issues, challenges, solutions, and futuristic scope are identified for forthcoming researchers