Real-time standard scan plane detection and localisation in fetal ultrasound using fully convolutional neural networks

Fetal mid-pregnancy scans are typically carried out according to fixed protocols. Accurate detection of abnormalities and correct biometric measurements hinge on the correct acquisition of clearly defined standard scan planes. Locating these standard planes requires a high level of expertise. However, there is a worldwide shortage of expert sonographers. In this paper, we consider a fully automated system based on convolutional neural networks which can detect twelve standard scan planes as defined by the UK fetal abnormality screening programme. The network design allows real-time inference and can be naturally extended to provide an approximate localisation of the fetal anatomy in the image. Such a framework can be used to automate or assist with scan plane selection, or for the retrospective retrieval of scan planes from recorded videos. The method is evaluated on a large database of 1003 volunteer mid-pregnancy scans. We show that standard planes acquired in a clinical scenario are robustly detected with a precision and recall of 69 % and 80 %, which is superior to the current state-of-the-art. Furthermore, we show that it can retrospectively retrieve correct scan planes with an accuracy of 71 % for cardiac views and 81 % for non-cardiac views

Solving The Problem of Adaptive E-Learning By Using Social Networks

This paper propose an enhanced E-Learning Social Network Exploiting Approach focused around chart model and clustering algorithm, which can consequently gathering dispersed e-learners with comparative premiums and make fitting suggestions, which can at last upgrade the collective learning among comparable e-learners. Through closeness revelation, trust weights overhaul and potential companions change, the algorithm actualized a programmed adjusted trust association with progressively upgraded fulfillments. Keywords: Relations, Adaptive E-Learning, Clustering , Social Network , E-learning ,  and Collaborative Learnin

Profile of serious adverse drug events in a tertiary care hospital of South India - a five years experience

Background: Adverse drug event (ADE) is said to be serious, when it is life-threatening, leads to hospitalization, disability, congenital anomaly, death or requires intervention to prevent permanent impairment or damage. The present study aimed to determine the pattern, causality, preventability of serious ADEs.Methods: This retrospective study was carried out to profile serious ADEs reported from Bangalore Medical College and Research Institute to Adverse Drug Reaction (ADR) Monitoring Centre, under Pharmacovigilance Programme of India from 2012 to 2016. Patient demographics, clinical and drug data, details of the ADE, onset time, causal drug details, outcome and severity were collected as per CDSCO form. Causality was assessed by WHO-ADR probability scale, preventability by modified Schumock and Thornton scale.Results: A total of 809 ADEs were reported, of which 50 (6.18%) were serious in nature. Male preponderance (74%) was observed, with 42% among patients aged 20-40 years. 56% of serious ADEs were reported from department of Dermatology. Steven Johnson Syndrome (SJS) (20%) contributed for most of the ADEs. Antiepileptics caused maximum number of serious ADEs (32%). 76% of the ADEs were found to be ‘probable’ and 4% were definitely preventable. 56% of them was life threatening and 86% required intensive interventions. 16% patients experienced serious ADEs during hospital stay.Conclusions: Serious ADEs constituted 6.18% of all ADEs reported. SJS was commonly seen with antimicrobials and hepatotoxicity with ATT. Antiepileptics and ATT contributed for majority of them. This study highlights the importance of monitoring and timely management of serious ADEs to commonly prescribed medications

Recent advances in human respiratory epithelium models for drug discovery

The respiratory epithelium is intimately associated with the pathophysiologies of highly infectious viral contagions and chronic illnesses such as chronic obstructive pulmonary disorder, presently the third leading cause of death worldwide with a projected economic burden of £1.7 trillion by 2030. Preclinical studies of respiratory physiology have almost exclusively utilised non-humanised animal models, alongside reductionistic cell line-based models, and primary epithelial cell models cultured at an air-liquid interface (ALI). Despite their utility, these model systems have been limited by their poor correlation to the human condition. This has undermined the ability to identify novel therapeutics, evidenced by a 15% chance of success for medicinal respiratory compounds entering clinical trials in 2018. Consequently, preclinical studies require new translational efficacy models to address the problem of respiratory drug attrition. This review describes the utility of the current in vivo (rodent), ex vivo (isolated perfused lungs and precision cut lung slices), two-dimensional in vitro cell-line (A549, BEAS-2B, Calu-3) and three-dimensional in vitro ALI (gold-standard and co-culture) and organoid respiratory epithelium models. The limitations to the application of these model systems in drug discovery research are discussed, in addition to perspectives of the future innovations required to facilitate the next generation of human-relevant respiratory models

(±)-4,12,15,18,26-Penta­hydroxy-13,17-dioxahepta­cyclo­[14.10.0.03,14.04,12.06,11.018,26.019,24]hexa­cosa-1,3(14),6(11),7,9,15,19,21,23-nona­ene-5,25-dione monohydrate

The title compound, C24H14O9·H2O, displays a cup-shaped form. The water mol­ecule is disordered over two set of sites with an occupancy ratio of 0.78:0.22. The mol­ecule of the compound has four stereocenters and corresponds to the SSRR/RRSS diastereoisomer. In the mol­ecule, the maximum dihedral angle between the planar benzene rings is 80.40 (4)°. The H atoms of the hy­droxy groups are engaged in hydrogen bonding, forming infinite chains parallel to the a axis. These chains are inter­linked through water mol­ecules, resulting in the formation of a two-dimensional network parallel to the (001) plane. Futhermore C—H⋯O, C—H⋯π and slipped π–π inter­actions result in the formation of a three-dimensional network

Open Social Learning Network

This paper considers the affordances of social networking theories and tools to build new and effective e-learning practices. We argue that “connectivism” (social networking applied to learning and knowledge contexts) can lead to a reconceptualization of learning in which formal and non-formal learning can be integrated as to build a potentially lifelong learning activities to be experienced in “personal learning environments”. In order to provide a guide in the design, development and improvement both of personal learning environments and in the related learning activities we provide a knowledge flow model called Open Social Learning Network (OSLN) —a hybrid of the LMS and the personal learning environment (PLE)—is proposed as an alternative learning technology environment with the potential to leverage the affordances of the Web to improve learning dramatically and  highlighting the stages of learning and the related enabling conditions. The derived model is applied in a possible scenario of formal learning in order to show how the learning process can be designed according to the presented theory. Keywords: Open Social Learning Network OSLN, Learning Theory, Connectivism, Networked Learnin, Collaboration Technologies, Collaborative Learning and Relationship Classification.

1-(2-Oxoindolin-3-yl­idene)-4-[2-(tri­fluoro­meth­yl)phen­yl]thio­semicarbazide

In the title compound, C16H11F3N4OS, the dihedral angle between the aromatic ring systems is 69.15 (10)°. Intra­molecular N—H⋯N and N—H⋯O hydrogen bonds generate S(5) and S(6) rings, respectively. A short N—H⋯F contact also occurs. In the crystal, inversion dimers linked by pairs of N—H⋯O hydrogen bonds generate R 2 2(8) loops. The dimers are linked by N—H⋯F hydrogen bonds, forming polymeric chains propagating in [100]. π–π inter­actions also exist between the centroids of the benzene rings of the 2-oxoindoline group at a distance of 3.543 (3) Å and a short C=O⋯π contact occurs. Two F atoms of the trifluoro­methyl group are disordered over two sets of sites in a 0.517 (8):0.483 (8) ratio

N′-[(E)-(4-Bromo-2-thienyl)methyl­ene]isonicotinohydrazide

In title compound, C11H8BrN3OS, the dihedral angle between the two aromatic rings is 27.61 (14)° and the Br atom is disordered over two sites with an occupancy ratio of 0.804 (2):0.196 (2). In the crystal, the mol­ecules are linked by N—H⋯O, C—H⋯O and C—H⋯N inter­actions, resulting in chains

(Z)-4-Hexyl-1-(5-nitro-2-oxo-2,3-dihydro-1H-indol-3-yl­idene)thio­semicarbazide

In the title compound, C15H19N5O3S, intra­molecular N—H⋯O, N—H⋯N and C—H⋯S inter­actions occur and the three terminal C atoms of the hexyl group are disordered over two sites with an occupancy ratio of 0.664 (12):0.336 (12). In the crystal, inversion dimers linked by pairs of N—H⋯O hydrogen bonds occur and C—H⋯O bonds link the dimers into chains. A short C=O⋯π contact is also present

N′-[(E)-4-Hydr­oxy-3-methoxy­benzyl­idene]pyridine-4-carbohydrazide

In the title compound, C14H13N3O3, the two six-membered rings are oriented at a dihedral angle of 15.17 (11)° and an intra­molecular O—H⋯O hydrogen bond occurs. In the crystal, mol­ecules inter­act by way of N—H⋯O, O—H⋯N and C—H⋯O hydrogen bonds, thereby generating S(5) chain and R 2 1(7) ring motifs