Placenta praevia: Preach and perception

Placenta praevia is a known obstetric condition that causes complications to mother and fetus. This study was done to evaluate the knowledge of placenta praevia amongst the obstetric patients. A cross sectional study was carried out in Hospital Ipoh, Perak among 323 antenatal and postnatal patients. Socio-demographic parameters (ie age, race, parity, occupation, educational level) and history of placenta praevia were studied in relation to level of knowledge and attitude towards placenta praevia. Twenty (6.2%) from 323 women had current or past history of placenta praevia. Three had history of placenta praevia while 17 had current placenta praevia with prevalence of 5.3%. The mean score of knowledge achieved by patients was 11.8 which indicated overall poor knowledge. Occupation, level of education and history of placenta praevia were found to have a relationship with level of knowledge regarding placenta praevia in all obstetric patients. There was a significant relationship between attitude of patients with current and history of placenta praevia to level of knowledge regarding placenta praevia. (p=0.037, <0.05). In conclusion, the knowledge and attitude towards placenta praevia among obstetric patients in Hospital Ipoh was better in those who had higher education status, white-collar occupation and currently pregnant with placenta praevi

Character-level Chinese-English Translation through ASCII Encoding

Character-level Neural Machine Translation (NMT) models have recently achieved impressive results on many language pairs. They mainly do well for Indo-European language pairs, where the languages share the same writing system. However, for translating between Chinese and English, the gap between the two different writing systems poses a major challenge because of a lack of systematic correspondence between the individual linguistic units. In this paper, we enable character-level NMT for Chinese, by breaking down Chinese characters into linguistic units similar to that of Indo-European languages. We use the Wubi encoding scheme, which preserves the original shape and semantic information of the characters, while also being reversible. We show promising results from training Wubi-based models on the character- and subword-level with recurrent as well as convolutional models.Comment: 7 pages, 3 figures, 3rd Conference on Machine Translation (WMT18), 201

Multi-scale characterisation of the 3D microstructure of a thermally-shocked bulk metallic glass matrix composite

Bulk metallic glass matrix composites (BMGMCs) are a new class of metal alloys which have significantly increased ductility and impact toughness, resulting from the ductile crystalline phases distributed uniformly within the amorphous matrix. However, the 3D structures and their morphologies of such composite at nano and micrometre scale have never been reported before. We have used high density electric currents to thermally shock a Zr-Ti based BMGMC to different temperatures, and used X-ray microtomography, FIB-SEM nanotomography and neutron diffraction to reveal the morphologies, compositions, volume fractions and thermal stabilities of the nano and microstructures. Understanding of these is essential for optimizing the design of BMGMCs and developing viable manufacturing methods

Towards the AlexNet Moment for Homomorphic Encryption: HCNN, theFirst Homomorphic CNN on Encrypted Data with GPUs

Deep Learning as a Service (DLaaS) stands as a promising solution for cloud-based inference applications. In this setting, the cloud has a pre-learned model whereas the user has samples on which she wants to run the model. The biggest concern with DLaaS is user privacy if the input samples are sensitive data. We provide here an efficient privacy-preserving system by employing high-end technologies such as Fully Homomorphic Encryption (FHE), Convolutional Neural Networks (CNNs) and Graphics Processing Units (GPUs). FHE, with its widely-known feature of computing on encrypted data, empowers a wide range of privacy-concerned applications. This comes at high cost as it requires enormous computing power. In this paper, we show how to accelerate the performance of running CNNs on encrypted data with GPUs. We evaluated two CNNs to classify homomorphically the MNIST and CIFAR-10 datasets. Our solution achieved a sufficient security level (> 80 bit) and reasonable classification accuracy (99%) and (77.55%) for MNIST and CIFAR-10, respectively. In terms of latency, we could classify an image in 5.16 seconds and 304.43 seconds for MNIST and CIFAR-10, respectively. Our system can also classify a batch of images (> 8,000) without extra overhead

A REVIEW OF CINNAMON AS A POTENT ANTICANCER DRUG

ABSTRACTCinnamon is one of the most popular and oldest spices. Several recent studies have found that cinnamon also has anticancer activity. The present workhas reported the antineoplastic potential of the spice cinnamon in cancer. Collectively, these data suggest that cinnamon could be proposed as a potentanticancer drug. The bibliographic investigation was carried out during January 2004-December 2014 by analyzing journals and peer-reviewedpapers from the last decades. Peer-reviewed articles were indexed by Scopus, PubMed, and Google scholar. Only relevant studies published in Englishwere considered. There were 24 articles that reported the cytotoxic activity of cinnamon on all culture cell lines. About 8 species of Cinnamomum havebeen isolated with their active compounds for cancer cell lines. Based on the reviews of those articles, we conclude that cinnamon has the potentialto be further developed as an anticancer agent. In further development, however, not only the research for investigating the anticancer activities, butalso research for investigating the safety of cinnamon to the normal cell need to be performed.Keywords: Review, Cinnamon, Anticancer, Cinnamomum species, Cell lines

GAS CHROMATOGRAPH-MASS SPECTROMETER ANALYSIS AND ACUTE ORAL TOXICITY OF CINNAMOMUM BURMANNII., NESS EX BL. ESSENTIAL OIL

ABSTRACTObjective: Cinnamomum burmannii Nees Ex Bl. essential oil has cytotoxic effect on a lot of cancer cell lines. An investigation was carried out to analyzethe possible chemical components from C. burmannii essential oil and evaluate its acute toxicity, before an effective formulation of C. burmanniiessential oil as anticancer drugs.Methods: This study was analyzed chemical components from C. burmannii essential oil by gas chromatograph-mass spectrometer (GC-MS) andevaluated the acute oral toxicities of C. burmannii essential oil in strain Balb/C mice. Results: This analysis revealed that C. burmannii essential oil contains the active compound cinnamaldehyde (71.814%), trans-cinnamyl acetate(11.09%), coumarin (3.41%), and cineol (1.77%). Acute oral toxicity of C. burmannii essential oil with lethal dose 50 3679.11 mg/kg BW.Conclusion: C. burmannii essential oil contains the active compound cinnamaldehyde, trans-cinnamyl acetate, coumarin and cineol. Acute oral toxicityconclusively indicates C. burmannii essential oil includes category 5 practically non-toxic.Keywords: Gas chromatograph-mass spectrometer, Cinnamomum burmannii, Essential oil, Acute toxicity

Achieving GWAS with Homomorphic Encryption

One way of investigating how genes affect human traits would be with a genome-wide association study (GWAS). Genetic markers, known as single-nucleotide polymorphism (SNP), are used in GWAS. This raises privacy and security concerns as these genetic markers can be used to identify individuals uniquely. This problem is further exacerbated by a large number of SNPs needed, which produce reliable results at a higher risk of compromising the privacy of participants. We describe a method using homomorphic encryption (HE) to perform GWAS in a secure and private setting. This work is based on a proposed algorithm. Our solution mainly involves homomorphically encrypted matrix operations and suitable approximations that adapts the semi-parallel GWAS algorithm for HE. We leverage the complex space of the CKKS encryption scheme to increase the number of SNPs that can be packed within a ciphertext. We have also developed a cache module that manages ciphertexts, reducing the memory footprint. We have implemented our solution over two HE open source libraries, HEAAN and SEAL. Our best implementation took $24.70$ minutes for a dataset with $245$ samples, over $4$ covariates and $10643$ SNPs. We demonstrate that it is possible to achieve GWAS with homomorphic encryption with suitable approximations

In situ synchrotron x-ray study of ultrasound cavitation and its effect on solidification microstructures

Considerable progress has been made in studying the mechanism and effectiveness of using ultrasound waves to manipulate the solidification microstructures of metallic alloys. However, uncertainties remain in both the underlying physics of how microstructures evolve under ultrasonic waves, and the best technological approach to control the final microstructures and properties. We used the ultrafast synchrotron X-ray phase contrast imaging facility housed at the Advanced Photon Source, Argonne National Laboratory, US to study in situ the highly transient and dynamic interactions between the liquid metal and ultrasonic waves/bubbles. The dynamics of ultrasonic bubbles in liquid metal and their interactions with the solidifying phases in a transparent alloy were captured in situ. The experiments were complemented by the simulations of the acoustic pressure field, the pulsing of the bubbles, and the associated forces acting onto the solidifying dendrites. The study provides more quantitative understanding on how ultrasonic waves/bubbles influence the growth of dendritic grains and promote the grain multiplication effect for grain refinement