Efficient Partial Discharge Detection in Online Gas Insulated Switchgear Monitoring: Characterization Insights

This paper focuses on investigating the detection of partial discharge (PD) in gas insulated switchgears (GIS) through the use of advanced deep learning models and signal processing methods. The aim is to effectively differentiate PD-induced noise from other noises in high-voltage environments using these sophisticated techniques. PD, often a precursor to serious faults, emits distinctive acoustic signals during its occurrence. The collaboration with Qatar General Water and Electricity Corporation (KAHRAMAA) enriches our research by providing valuable insights into real-world applications and specific considerations in GIS systems. The paper also includes a comprehensive overview of GIS systems, highlighting the complexities of their operations and the vital role of PD detection in ensuring their reliability. Furthermore, the study extensively explores various machine learning techniques, examining their effectiveness in identifying unique patterns in PD noise, thereby enabling quick and accurate detection of potential faults in the system. The paper also investigates several designs in the field of deep learning, including K-Nearest Neighbors (KNN). This model is taught to identify the distinctive features of noise caused by PD, setting it apart from other kinds of noise that are prevalent in high-voltage situations. The study also explores the useful uses of PD detection in preserving the integrity of GIS systems. It emphasizes how early detection of PD can save system failures, lower maintenance expenses, and increase equipment longevity. KAHRAMAA's real-world case studies demonstrate how successful these deep learning models are in practical environments. The paper concludes by discussing the future directions of this field of study. It raises the possibility of making model training better by utilizing bigger and more varied datasets and investigating cutting-edge deep learning methods

Effects of Prenatal Testosterone Treatment on Puberty, Reproductive Cyclicity, and Responsiveness of the Neuroendocrine Axis to Steroid Feedback Mechanisms in First-Generation Ewes: A Model for Polycystic Ovary Syndrome

Polycystic ovary syndrome is the leading cause of anovulatory infertility in women of reproductive age, characterized by anovulation, polycystic ovarian morphology, and hyperandrogenism. It is a multifactorial disease impacted by environmental, lifestyle, genetic, and epigenic influences. Obesity can increase the severity and development of PCOS phenotype. Prenatal testosterone exposure can alter the developmental trajectory to cause reprogramming of key processes that may lead to onset of PCOS in adulthood. We hypothesized that prenatal exposure to testosterone (T) excess would 1) advance time of puberty attainment and disrupt progesterone cycles; 2) reduce the responsiveness of the neuroendocrine axis to estradiol positive feedback; 3) disrupt periovulatory LH surge dynamics; and 4) reduce neuroendocrine sensitivity to progesterone negative feedback during the mid-luteal phase in first generation ewes. Our results indicate that while prenatal T treatment combined with postnatal excessive weight gain did not alter age at puberty, it exacerbated the reproductive defects seen during the first breeding season (early adulthood) and further deteriorated reproductive cyclicity in the second breeding season (adulthood). In addition, the estradiol positive feedback mechanism was impaired in both T maintenance (prenatally exposed to T excess and postnatally fed 100% of NRC requirements) and T overfed females (prenatally T treated and postnatally fed 130% of NRC requirements), through a delayed LH surge and reduced LH surge amplitude, which can have detrimental effects on ovulation and subsequent fertility. Key features of the preovulatory LH surge were altered, with no further amplification of postnatal overfeeding observed. Lastly, responsiveness to progesterone negative feedback was reduced in prenatal T maintenance fed ewes and amplified in T overfed ewes, through an observed increase of LH pulse amplitude, peak, and pulse frequency. These data herein support our previous findings that prenatal T treatment in female sheep results in neuroendocrine dysfunction and periovulatory disruptions, and that the shorter T treatment window of gestational day 60-90 is sufficient to program these effects. Moreover, postnatal overfeeding had varying effects on these neuroendocrine disruptions and provides valuable insight into the effects of obesity on PCOS pathogenesis in women

Starsky & Hutch Concordance

Possibly published in the 1980s.Also known as: Starsky & Hutch Concordance

A Journey to Healing: Women's Empowerment After Mass Killings

In the wake of Rwanda's genocide, a remarkable shift occurred in villages that experienced intense military and army violence. Women, stepping into the void left by conflict, emerged as leaders, reshaping their communities. This brief explains how female leadership spurred significant improvements in welfare, reduced violence, and influenced gender norms. These results provide a compelling case for empowering women in governance and household roles globally