1,944 research outputs found
Portfolio of Compositions: Developing a personal compositional approach based on attributes of spoken language
This compositional portfolio comprises eight original works presented in musical scores. The works were written between October 2013 and April 2017 during the course of my PhD research. The compositions featured are for a variety of combinations of voices and solo instrument up to full orchestra. Audio recordings of performances are included for all except the final orchestral work. In these compositions, I introduce a new compositional idea, declaiming, which I have been developing and which is explained in this commentary. This idea is used to determine the formal structure of these pieces. Unique approaches to using this compositional idea are described in this commentary, regarding individual works
Characterization of anti-leukemia components from Indigo naturalis using comprehensive two-dimensional K562/cell membrane chromatography and in silico target identification.
Traditional Chinese Medicine (TCM) has been developed for thousands of years and has formed an integrated theoretical system based on a large amount of clinical practice. However, essential ingredients in TCM herbs have not been fully identified, and their precise mechanisms and targets are not elucidated. In this study, a new strategy combining comprehensive two-dimensional K562/cell membrane chromatographic system and in silico target identification was established to characterize active components from Indigo naturalis, a famous TCM herb that has been widely used for the treatment of leukemia in China, and their targets. Three active components, indirubin, tryptanthrin and isorhamnetin, were successfully characterized and their anti-leukemia effects were validated by cell viability and cell apoptosis assays. Isorhamnetin, with undefined cancer related targets, was selected for in silico target identification. Proto-oncogene tyrosine-protein kinase (Src) was identified as its membrane target and the dissociation constant (Kd) between Src and isorhamnetin was 3.81 μM. Furthermore, anti-leukemia effects of isorhamnetin were mediated by Src through inducing G2/M cell cycle arrest. The results demonstrated that the integrated strategy could efficiently characterize active components in TCM and their targets, which may bring a new light for a better understanding of the complex mechanism of herbal medicines
2,6-Dibromo-4-(2-hydroxyethyl)phenol
The title compound, C8H8Br2O2, crystallized with two independent molecules (A and B) in the asymmetric unit. They differ in the conformation of the 2-hydroxyethyl chain with the C—C—C—O torsion angle being −68.0 (12)° in molecule A and 172.2 (9)° in molecule B. In the crystal, the A molecules are linked via pairs of O—H⋯O hydrogen bonds, forming inversion dimers, while the B molecules are linked via an O—H⋯O hydrogen bond, forming a polymeric chain propagating in [010]. In addition, there are O—H⋯O and O—H⋯Br hydrogen bonds, and Br⋯Br [3.599 (2) Å] and π–π interactions [centroid–centroid distances = 3.581 (6) and 3.931 (6) Å], leading to the formation of a two-dimensional network parallel to (001)
Complex Power System for Lithium Batteries and Lead-Acid Batteries
This paper discusses about the power system, and focus on complex power system applications on the public transportation. The objective of this research is to improve power system to achieve green energy applications. Energy depletion is a global problem for people who live on the Earth and we have to face this problem. So before energy depletion occurs, we should develop more energy alternatives. In this paper, we go through two experimental verification of complex power systems. The first part is to establish a platform for static electricity complex experiments. In the second part, using vehicle test platform for dynamic test. Finally, by creating a motor drive mode simulate actual conditions to enhance the accuracy of the experimental results. According to the results we can know the power system after being modified can improve overall system performance
THE RELATIONSHIP BETWEEN DIABETES MELLITUS AND TUBERCULOSIS IN REVIEW OF PREVALENCE, DIAGNOSTICS AND PREVENTION
Tuberculosis (TB) is a bacterial infection caused by M. tuberculosis, also known as Mycobacterium Tuberculosis. There is a bidirectional relationship between TB and diabetes, and they both impact the presentation of each other. Diabetes is being increasingly recognized as a risk factor for TB. The expected rise in diabetes cases in developing countries having the brunt of tuberculosis would increase the influence of diabetes on TB in the coming future. The impact and relationship between TB and diabetes will vary across different regions of the world depending on the incidence and prevalence of each condition. Patient education is so important in understanding the disease nature (both TB and diabetes), duration of treatment, side effects of drugs, and complications of disease as well as the promotion of healthy lifestyle choices. The objective of this review is to determine the prevalence, diagnostic and prevention strategy between diabetes mellitus and tuberculosis. The selected studies were identified using Pub Med database. The identified studies define lifestyle as important risk factor that may worsen the progression of the disease. This article also discussed about the prevalence of tuberculosis-diabetes mellitus over a span of 8 years.
Peer Review History:
Received 13 August 2019; Revised 24 August; Accepted 6 September, Available online 15 September 2019
Academic Editor: Prof. Dr. Gorkem Dulger, Duzce University, Turkey, [email protected]
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Received file: Reviewer's Comments:
Average Peer review marks at initial stage: 5/10
Average Peer review marks at publication stage: 8/10
Reviewer(s) detail:
Dr. Nuray Arı, Ankara University, Turkiye, [email protected]
Noha El Baghdady, MTI University, Cairo, Egypt, [email protected]
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Integrated analysis of the structure and function of bacterial community in water and shrimp intestine microbes reveals their interaction
Shrimp is closely associated with different microbial populations of the gut and the environment, particularly of the
water. Despite significant microbiome research in shrimp, a direct relationship between the shrimp's gut microbiota and the
habitat environment remains unclear. The bacterial profiles of the shrimp intestine and its aqueous environment were compared
by compiling data from earlier research to characterize the dynamic interaction between shrimp and habitat. According to the
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water bacteria, including nitrate reduction, methylotrophy, methanol oxidation, intracellular parasites, human infectious
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function, revealing new information on shrimp and water ecology. Although the relative abundances in the bacterial composition
were different in shrimp intestine, water and sediment, the bacterial communities were almost similar, indicating the close
interaction between host and the environment in microbiome. Notably, the significant distribution of disease-related pathogens
including Vibrio and Flavobacterium in shrimp intestine and habitat water provided valuable information for disease prediction
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Use of estradiol promotes tendon bone healing in rabbit model underwent anterior cruciate ligament reconstruction
Enhancing Cross-task Black-Box Transferability of Adversarial Examples with Dispersion Reduction
Neural networks are known to be vulnerable to carefully crafted adversarial
examples, and these malicious samples often transfer, i.e., they remain
adversarial even against other models. Although great efforts have been delved
into the transferability across models, surprisingly, less attention has been
paid to the cross-task transferability, which represents the real-world
cybercriminal's situation, where an ensemble of different defense/detection
mechanisms need to be evaded all at once. In this paper, we investigate the
transferability of adversarial examples across a wide range of real-world
computer vision tasks, including image classification, object detection,
semantic segmentation, explicit content detection, and text detection. Our
proposed attack minimizes the ``dispersion'' of the internal feature map, which
overcomes existing attacks' limitation of requiring task-specific loss
functions and/or probing a target model. We conduct evaluation on open source
detection and segmentation models as well as four different computer vision
tasks provided by Google Cloud Vision (GCV) APIs, to show how our approach
outperforms existing attacks by degrading performance of multiple CV tasks by a
large margin with only modest perturbations linf=16.Comment: arXiv admin note: substantial text overlap with arXiv:1905.0333
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