A Novel Study on Bipolar High Voltage Direct Current Transmission Lines Protection Schemes

In long dc transmission lines identification of fault is important for transferring a large amount of power. In bipolar Line commutated converter transmission lines are subjected to harsh weather condition so accurate and rapid clearance of fault is essential. A comparative study of the bipolar system with both converters healthy and one converter tripped is studied. Most of the research paper has focussed on transmission line faults in bipolar mode but none of them had focussed when HVDC system works in monopolar mode after the fault. In the proposed scheme the voltage signals are extracted from both poles of the rectifier ends and are processed to identify the faults in transmission lines.The Artificial neural network is utilised in detecting the fault in both bipolar and monopolar system. Since it can identify the relationship between input and output data to detect the fault pattern it can be utilised under all conditions. Moreover, benefits of the proposed method are its accuracy, no requirement of the communication system as it acquires data from one end and has a reach setting of 99%

Xanthogranulomatous pyelonephritis in a child: A rare entity

Xanthogranulomatous pyelonephritis (XGP) is chronic pyelonephritis uncommonly described in adults and is rare in children. It ischaracterized by the replacement of renal parenchymal tissue by lipomatous cells making it nonfunctional and may be mistaken forpyonephrosis, cystic or solid tumor, and the most commonly, Wilms tumor. It often presents as abdominal mass in children and morecommonly involves left kidney. Imaging by computed tomography (CT) scan is characteristic, and histology is diagnostic. We arereporting a case of a child who presented with prolonged febrile illness and documented urinary tract infection with nephrolithiasiswithout any abdominal lump and received antibiotics for multiple times without any improvement. Ultrasonography was suggestiveof pyonephrosis and multiple abscesses. However, on CT scan, was diagnosed as XGP of the right kidney which was confirmed onhistology. After documenting, no function in affected kidney with other being normal, unilateral nephrectomy was done resultingin rapid symptomatic improvement

A novel primary and backup relaying scheme considering internal and external faults in HVDC transmission lines

Discrimination of different DC faults near a converter end of a DC section consisting of a filter, a smoothing reactor, and a transmission line is not an easy task. The faults occurring in the AC section can be easily distinguished, but the internal and near-side external faults in the DC section are very similar, and the relay may cause false tripping. This work proposes a method to distinguish external and internal faults occurring in the DC section. The inputs are the voltage signals at the start of the transmission line and the end of the converter filter. The difference in voltage signals is calculated and given to an intelligent controller to detect and discriminate the faults. The intelligent controller is designed using machine learning (ML) and deep learning (DL) techniques for fault detection. The long short-term memory (LSTM-) based relay gives better results than other ML methods. The proposed method can distinguish internal from external faults with 100% accuracy. Another advantage is that a primary relay is suggested that detects faults quickly within a fraction of milliseconds. Nevertheless, another advantage is that a backup relay has been designed in case the primary relay cannot operate. Results show that the LSTM-based protection scheme provides higher sensitivity and reliability under different operation modes than the conventional traveling wave-based relay

Identification of priority health conditions for field-based screening in urban slums in Bangalore, India

BACKGROUND: Urban slums are characterised by unique challenging living conditions, which increase their inhabitants' vulnerability to specific health conditions. The identification and prioritization of the key health issues occurring in these settings is essential for the development of programmes that aim to enhance the health of local slum communities effectively. As such, the present study sought to identify and prioritise the key health issues occurring in urban slums, with a focus on the perceptions of health professionals and community workers, in the rapidly growing city of Bangalore, India. METHODS: The study followed a two-phased mixed methods design. During Phase I of the study, a total of 60 health conditions belonging to four major categories: - 1) non-communicable diseases; 2) infectious diseases; 3) maternal and women's reproductive health; and 4) child health - were identified through a systematic literature review and semi-structured interviews conducted with health professionals and other relevant stakeholders with experience working with urban slum communities in Bangalore. In Phase II, the health issues were prioritised based on four criteria through a consensus workshop conducted in Bangalore. RESULTS: The top health issues prioritized during the workshop were: diabetes and hypertension (non-communicable diseases category), dengue fever (infectious diseases category), malnutrition and anaemia (child health, and maternal and women's reproductive health categories). Diarrhoea was also selected as a top priority in children. These health issues were in line with national and international reports that listed them as top causes of mortality and major contributors to the burden of diseases in India. CONCLUSIONS: The results of this study will be used to inform the development of technologies and the design of interventions to improve the health outcomes of local communities. Identification of priority health issues in the slums of other regions of India, and in other low and lower middle-income countries, is recommended

HER2-enriched subtype and novel molecular subgroups drive aromatase inhibitor resistance and an increased risk of relapse in early ER+/HER2+ breast cancer

BACKGROUND: Oestrogen receptor positive/ human epidermal growth factor receptor positive (ER+/HER2+) breast cancers (BCs) are less responsive to endocrine therapy than ER+/HER2- tumours. Mechanisms underpinning the differential behaviour of ER+HER2+ tumours are poorly characterised. Our aim was to identify biomarkers of response to 2 weeks’ presurgical AI treatment in ER+/HER2+ BCs. METHODS: All available ER+/HER2+ BC baseline tumours (n=342) in the POETIC trial were gene expression profiled using BC360™ (NanoString) covering intrinsic subtypes and 46 key biological signatures. Early response to AI was assessed by changes in Ki67 expression and residual Ki67 at 2 weeks (Ki672wk). Time-To-Recurrence (TTR) was estimated using Kaplan-Meier methods and Cox models adjusted for standard clinicopathological variables. New molecular subgroups (MS) were identified using consensus clustering. FINDINGS: HER2-enriched (HER2-E) subtype BCs (44.7% of the total) showed poorer Ki67 response and higher Ki672wk (p<0.0001) than non-HER2-E BCs. High expression of ERBB2 expression, homologous recombination deficiency (HRD) and TP53 mutational score were associated with poor response and immune-related signatures with High Ki672wk. Five new MS that were associated with differential response to AI were identified. HER2-E had significantly poorer TTR compared to Luminal BCs (HR 2.55, 95% CI 1.14–5.69; p=0.0222). The new MS were independent predictors of TTR, adding significant value beyond intrinsic subtypes. INTERPRETATION: Our results show HER2-E as a standardised biomarker associated with poor response to AI and worse outcome in ER+/HER2+. HRD, TP53 mutational score and immune-tumour tolerance are predictive biomarkers for poor response to AI. Lastly, novel MS identify additional non-HER2-E tumours not responding to AI with an increased risk of relapse

Antibacterial and Antibiofilm Properties of Medicinal Plant Extracts against Multi Drug Resistant Staphylococcus Species and Non Fermenter Bacteria

Antimicrobial resistance to the pathogenic microorganism has been characterized as a public health emergency both in the community and in hospitals. That is why; we need to find alternatives, which could be used as antibacterial agents. Therefore aim of this study is to determine the antibacterial and antibiofilm properties of 4 plant extracts Clove (Syzygium aromaticum), Tea (Camellia sinensis), Garlic (Allium sativum), coriander (Coriandrum sativum).Antibacterial properties of plant extracts at different concentrations (50, 25, 12.5, 6.25 mg/mL) were tested against Multi Drug Resistance biofilm producing Staphylococcus aureus, Pseudomonas aeruginosa, Acinetobacter baumannii, Staphylococcus epidermidis and Staphylococcus saprophyticus using the agar well diffusion method.Minimum Bactericidal Concentration (MBC) and antibiofilm properties of the plant extracts were determined using the tube dilution method and modified crystal violet assay, respectively. Total of 180 clinical isolates were screened for their MDR Pattern. Out of these, 72 were MDR isolates. These MDR isolates were categorized into weak, moderate and strong biofilm producers. Fourteen, Forty nine and nine were weak, moderate and strong biofilm producers, respectively. Out of the 4 plant extracts, Syzygium aromaticum and Camellia sinensis were found to be more effective with maximum zone of inhibition (20 – 25 mm), MBC 6.25 mg/ml and biofilm reduction of more than 50% compared to Allium sativum and Coriandrum sativum. All medicinal plant extracts were effective at different concentrations against the biofilm producing MDR isolates but Syzygium aromaticum and Camellia sinensis showed maximum antibacterial and antibiofilm activity