Miracle-dz/UniFAR-FTUs huggingface dataset:
Anticandidal Effects of Thymoquinone: Mode of Action Determined by Transmission Electron Microscopy (TEM)

Thymoquinone (TQ) is one of the bioactive constituents of black cumin seed (Nigella sativa L.) oil. It is well known that this natural volatile quinone has remarkable antimicrobial effects, especially against Candida species. Consequently, in this present study TQ was evaluated for its anticandidal effects against 14 different pathogenic Candida strains by using the in vitro, partly modified, microdilution CLSI M27-A2 method. After TQ treatment at the minimum inhibitory concentration (MIC), ultra-thin sections of C. albicans cells were thoroughly evaluated by transmission electron microscopy (TEM). The mode of action of TQ on different Candida cells was elaborated, where their disintegration and disorganization with amorphous nucleus were observed microscopically.
A Multi-layered Annotation Scheme and Computational Model for Co-Learning Semantic and Prosodic Structures of Chinese Discourse

This paper presents a novel annotation scheme of Chinese discourse structures to model the complex interactions among grammar, semantics and phonology. The scheme mainly contains three layers, i.e., grammatical, semantic and prosodic layers. Within each layer, the representations of dependency relations, rhetorical structure, information structure, topic chain, prosodic boundaries and stress distributions are specified. Based on the scheme, a large scale corpus of transcribed speech data is constructed and annotated. We further propose a machine learning methodology to learn from the annotated corpus a computational representation of the internal structure of each layer and the interactions across different layers. Specifically, we employ the Recursive Neural Network (RNN) to model the fine-grained structure in natural language information, through learning a distributed representation of the structural units. The proposed annotation scheme and machine learning methodology to expected to underpin more effective and intelligent speech engineering and understanding technologies of the future.
X-Parameter Characterization of LDMOS Devices for Broadband Doherty High-Power Amplifier Design

We present a novel design approach of high-power broadband Doherty amplifier (DPA) by the X-parameters. It is based on the nonlinear vector network analysis of the 3-port circuit composed of the main and peak power devices, connected to the input network. The technique permits the analysis of the best termination for both the peak and main devices, mutually interacting by the input network, and development of the broadband output networks which optimizes the mutual devices load modulation. The three-port nonlinear vector characterization method was applied to the analysis of a broadband DPA designs based on a pair of Silicon Laterally Diffused MOSFETs (LDMOS) with optimized peak power and efficiency in the 700 MHz to 960 MHz bandwidth. The DPA performance exhibited a peak power of 54.2 dBm at center frequency with a peak drain efficiency up to 71.5%. and a drain efficiency in excess of 68 % within 8-dB back-off at center frequency band.
Activation of the mammalian target of rapamycin signaling pathway underlies a novel inhibitory role of ring finger protein 182 in ventricular remodeling after myocardial ischemia‐reperfusion injury

Myocardial ischemia‐reperfusion injury (MIRI) is a major cause of cardiovascular disease, leading to mortality and disability associated with coronary occlusion worldwide. A correlation of mammalian target of rapamycin (mTOR)/nuclear factor‐kappa B (NF‐κB) signaling pathway has been observed with brain damage resulting from myocardial ischemia. Therefore, by establishing MIRI rat model, this study aimed to explore whether ring finger protein 182 (RNF182) regulates the mTOR signaling pathway affecting MIRI. Initially, MIRI rat model was successfully established, followed by either treatment of shRNF182 or phosphoesterase (PITE) (inhibitor of the mTOR signaling pathway). Then, the serum levels of superoxide dismutase (SOD), glutathione peroxidase (GSH‐Px) and malondialdehyde (MDA), left ventricular ejection fraction (LVEF), left ventricular fractional shortening (LVFS), left ventricular systolic pressure (LVSP), and left ventricular end‐diastolic pressure (LVEDP) were determined, followed by detection of myocardial infarct sizes and myocardial cell apoptosis. Moreover, the levels of related genes/proteins were determined to further determine the mechanisms of RNF182 in MIRI. First, RNF182 was upregulated in MIRI. Another key observation of this study was that rats with shRNF182 presented with downregulated SOD, GSH‐Px, and MDA in serum, accompanied by decreased levels of LVEF, LVFS, LVSP, and LVEDP. In addition, both reduced myocardial infarct sizes and apoptosis of myocardial cells were observed after silencing RNF182. Furthermore, silencing of the RNF182 was observed to downregulate Bcl 2–associated X and cysteine proteinase 3 but upregulate mTOR, ribosome protein subunit 6 kinase 1, eukaryotic elongation factor 2, and B‐cell lymphoma‐2. Importantly, the effects of RNF182 silencing were reversed after PITE treatment. In conclusion, our study demonstrates that RNF182 silencing can prevent ventricular remodeling in rats after MIRI by activating the mTOR signaling pathway.
Moving Breast Cancer Therapy up a Notch

Breast cancer is the second most common malignancy, worldwide. Treatment decisions are based on tumor stage, histological subtype, and receptor expression and include combinations of surgery, radiotherapy, and systemic treatment. These, together with earlier diagnosis, have resulted in increased survival. However, initial treatment efficacy cannot be guaranteed upfront, and these treatments may come with (long-term) serious adverse effects, negatively affecting a patient's quality of life. Gene expression-based tests can accurately estimate the risk of recurrence in early stage breast cancers. Disease recurrence correlates with treatment resistance, creating a major need to resensitize tumors to treatment. Notch signaling is frequently deregulated in cancer and is involved in treatment resistance. Preclinical research has already identified many combinatory therapeutic options where Notch involvement enhances the effectiveness of radiotherapy, chemotherapy or targeted therapies for breast cancer. However, the benefit of targeting Notch has remained clinically inconclusive. In this review, we summarize the current knowledge on targeting the Notch pathway to enhance current treatments for breast cancer and to combat treatment resistance. Furthermore, we propose mechanisms to further exploit Notch-based therapeutics in the treatment of breast cancer.
Psychometric properties of the Chinese-version Stroke and Aphasia Quality of Life Scale 39-generic version (SAQOL-39g)

ABSTRACT Background and purpose: Aphasia is a common outcome of stroke affecting one-third of the post-stroke population in China. While the quality of life (QOL) may be affected, care is often inadequately guided due to lack of validated measure for Chinese population with stroke-induced aphasia. This study aimed to develop a Chinese-version of the Stroke and Aphasia Quality of Life-39 generic version (SAQOL-39g) and evaluate its feasibility, reliability, and validity in Chinese patients with stroke-induced aphasia. Methods: The process of translation and adaptation suggested by WHO was used to develop the Chinese-version of SAQOL-39. We evaluated the feasibility, reliability, and validity of the scale in 84 aphasia patients and their proxies by assessing the internal consistency of the test items, test–retest consistency, and the structural validity of data. Results: The self-report and the proxy-report form were completed within 21.4 and 13.3 min on average, respectively. Physical, communication, and psychological subdomains were extracted as three common factors. The Cronbach’s alpha coefficients of overall domain and subdomains for both forms ranged from 0.879 to 0.950, indicating high internal consistency. The intraclass correlation coefficients ranged from 0.804 to 0.987 for overall domain and subdomains of the forms. No significant difference was found between two forms. Conclusions: The Chinese-version SAQOL-39g has excellent reliability, validity, and feasibility for measuring the QOL of Chinese post-stroke aphasia patients. The consistency between self-report and proxy-report forms was good, implying that the proxy-report form can be used to assess the QOL of post-stroke aphasia patients.
Empirical study of software process improvement in Malaysian small and medium enterprises: The human aspects

Software Process Improvement (SPI) aims to achieve quality software products in software companies. Ignoring human factors can cause several types of damage in the software development process. Because, Software development is not a purely technical task, but rather it is a relationship between technical and human factors that interact with each other constantly. Currently, Small Medium Enterprises' (SMEs) software development companies in Malaysia still struggle to implement SPI successfully. Therefore, the main objective of this study is to investigate the empirical evidence based on the human factor perspective for helping Malaysian SMEs' software development companies to implement SPI strategies. A questionnaire‐based survey method was used for gathering information from 79 practitioners. The results indicate that 9 factors (employee awareness, leadership involvement, employee involvement, customer involvement, senior management support, staff experience, staff learning, staff skills, and client support) are considered important for implementing SPI in Malaysian SME software development companies. The involvement of both leadership and employees, and getting support from management are the most important human factors that should be considered during the design process of SPI strategies.
Analysis and Improvements on Current Pothole Detection Techniques

India recorded at least 4,80,652 accidents in 2016, leading to 1,50,785 deaths which were caused by speeding, overtaking, drunk driving, speed breakers and potholes. Potholes are not just structural failure in a road surface, here in India these days is a major cause of road side causalities. A constant detection and repair in proper time can not only result in ensure road surface quality but can also save many lives. The proposal describes one such road maintenance system which uses Basic Ultrasonic Sensors, Raspberry Pi and A Mobile Phone with Internet Capabilities which are connected to an Internet-of-Things platform over the Internet. In addition to providing a generic Internet-of-Things based platform, the proposed solution brings objective real time data about the state of the roads in a particular region which can be sent to the local authorities to take further actions upon.
Smart Car Systems: A need in smart city

Vehicles were invented to save the time and efforts of humans, but the same vehicles proved to be fatal as count went on increasing. Thus it is mandatory to resolve these issues of accidents caused by vehicles and create a smart system which is user friendly which aims to provide data such as temperature, humidity, directions, journey travelled etc to users, to facilitate communication between two vehicles so as to prevent unusual braking caused by two vehicles in proximity thus preventing accidents. The use of NFC (Near Field Connect) will smartly help the user to follow the laws by default thus creating a robust traffic regulatory system. Also the use of two independent server of regulatory system as well as the user server will maintain the user privacy of the data.
An Effective Enhancement and Segmentation of Coronary Arteries in 2D Angiograms

Vessel enhancement in two-dimensional angiogram images is an essential pre-requisite step towards the isolation of coronary arteries. Hessian-based filters are the most commonly used vessel enhancement filters; however, these filters are more sensitive to noise and suppress the bifurcation regions. Suppression of bifurcation regions results in disconnected vessels. In this study, we present a technique that enhances the arteries of the heart in 2D angiograms and also refines the noisy vesselness obtained through Frangi’s method by using guided filter which produces more enhanced image that can be used as an effective pre-processing step for binarization of the Frangi vessel response having less discontinuities and joint suppression. The proposed approach makes use of the guided filter which smooths the edges, and at the same time preserves the edges as well for the enhancement of vessels. Following this filter, an Adaptive thresholding is applied to segment the coronary arteries from the angiogram. The proposed method has been tested on real angiography images and the efficiency of the method has been shown qualitatively as well as quantitatively.
Identification of Twitter User Credibility Using Machine Learning

Twitter offers social media platform in the form of microblog in which becomes social judgment and updates. The popularity of Twitter shows that there is growth in quantity of information. Not all user posted content can be trusted. This can be a serious impact on users who are using Twitter as a source of information and decision making. Users of Twitter are expected to be independently able to obtain credible information from those who are credible in their expertise field. This research measurement model of user credibility in delivering information based on topic areas of competence and proposed method with machine learning. The features consist of visible feature and tweet activity. Education becomes a feature that affects user identification. The result shows that algorithm of Neural Network using parameter learning rate of 0.35 and momentum of 0.2 resulted in a good performance with an accuracy of 77.46%.
Translation, cultural adaptation, validation, and reliability study of the Quick-EBP-VIK instrument: Chinese version.

RATIONALE, AIMS, AND OBJECTIVES Valid and reliable instruments for measuring are needed. To add knowledge to the subject of tools of evidence-based practice (EBP) evaluation in mainland China, the present study aims to translate the Quick-EBP-VIK into Chinese, which is an instrument for the assessment of nurses' value, knowledge, and implementation of EBP, and to evaluate the metric characteristics of the Chinese version. METHODS In this methodological study, a total sample of 402 nurses from mainland China was applied. Construct validity was evaluated by using factor analysis and further supported through known-group validity. A panel of experts examined the content validity. Internal consistency was determined using composite reliability and Cronbach alpha. The intraclass correlation coefficient (ICC) was calculated to assess test-retest reliability. RESULTS The exploratory factor analysis revealed a three-factor structure model same to the original instrument. The confirmatory factor analysis showed a good fit model with a comparative fit index of 0.957 and a root mean square error of approximation of 0.065. Significant differences were found in the item means of the tool between nurses who received EBP training and those who had not, which supported the known-group validity. The Cronbach alpha and composite reliability for the three subscales were all higher than 0.70. The ICC ranged from 0.569 to 0.928 for the three subscales and from 0.494 to 0.903 for the items included in the instrument. CONCLUSION The Chinese version of the Quick-EBP-VIK has evidence of acceptable reliability and validity and can be used to measure value, knowledge, and implementation of EBP for Chinese nurses.
Agile practices for global software development vendors in the development of green and sustainable software

Over the last decade, the use of agile methods has grown dramatically for software development. Agile methods guarantee to accelerate the delivery of remarkable software with increased user satisfaction and reduced cost. However, in recent years, due to emergence of green software engineering, software developers are compelled to focus more on green and sustainable aspects of software. Global software engineering aims to design, develop, and use a software with limited energy and computing resources. Recently, software engineers in global software development (GSD) have adapted agile methods for quick, interactive, and environment‐friendly software development. However, there is a lack of specific practices to be followed by GSD vendors in the development of green and sustainable software.
An Edge Computing Framework for Real-Time Monitoring in Smart Grid

Due to the ever-growing demands in modern cities, unreliable and inefficient power transportation becomes one critical issue in nowadays power grid. This makes power grid monitoring one of the key modules in power grid system and play an important role in preventing severe safety accidents. However, the traditional manual inspection cannot efficiently achieve this goal due to its low efficiency and high cost. Smart grid as a new generation of the power grid, sheds new light to construct an intelligent, reliable and efficient power grid with advanced information technology. In smart grid, automated monitoring can be realized by applying advanced deep learning algorithms on powerful cloud computing platform together with such IoT (Internet of Things) devices as smart cameras. The performance of cloud monitoring, however, can still be unsatisfactory since a large amount of data transmission over the Internet will lead to high delay and low frame rate. In this paper, we note that the edge computing paradigm can well complement the cloud and significantly reduce the delay to improve the overall performance. To this end, we propose an edge computing framework for real-time monitoring, which moves the computation away from the centralized cloud to the near-device edge servers. To maximize the benefits, we formulate a scheduling problem to further optimize the framework and propose an efficient heuristic algorithm based on the simulated annealing strategy. Both real-world experiments and simulation results show that our framework can increase the monitoring frame rate up to 10 times and reduce the detection delay up to 85% comparing to the cloud monitoring solution.
Cathode: the Key Factor in Vacuum Breakdown

The objective of this paper is to prove that the cathode is the key factor in vacuum breakdown. Three identical groups (I, II and III) of electrodes were prepared. Each group contained two pairs of plane-plane copper electrodes, pair A and B. In each group, the two pairs of electrodes were firstly applied the conditioning process of impulse voltage. Afterward, pair C was arranged by a combination of cathode of pair A and B, pair A cathode- pair B cathode. Pair D was arranged by a combination of anode of pair A and B, pair A anode- pair B anode. The arrangement was under the vacuum condition without exposure of air condition. Surface-analysis of the electrode surfaces were done before and after the vacuum breakdown test for pair A and B by X-ray photoelectron spectroscopy (XPS). The breakdown test and surface analysis were repeated to new combined electrode pairs, pair C and D, again to check the breakdown characteristic of the two new pairs of electrodes. All the three group results showed that after the conditioning saturation, no XPS result difference existed among pair A, B C and D. The breakdown electric fields of pair B and C (sharing the same cathode) were nearly the same, suggesting the cathode influence the breakdown electric field. The breakdown electric field of pair D was obvious higher than that of pair A. The only difference between pair A and D is the cathode. The results may provide a further understanding about the factor of the anode and cathode in the vacuum breakdown test.
Diabetic macular edema: Evidence-based management

Diabetic macular edema (DME) is the most common cause of vision loss in patients with diabetic retinopathy with an increasing prevalence tied to the global epidemic in type 2 diabetes mellitus. Its pathophysiology starts with decreased retinal oxygen tension that manifests as retinal capillary hyperpermeability and increased intravascular pressure mediated by vascular endothelial growth factor (VEGF) upregulation and retinal vascular autoregulation, respectively. Spectral domain optical coherence tomography (SD-OCT) is the cornerstone of clinical assessment of DME. The foundation of treatment is metabolic control of hyperglycemia and blood pressure. Specific ophthalmic treatments include intravitreal anti-VEGF drug injections, intravitreal corticosteroid injections, focal laser photocoagulation, and vitrectomy, but a substantial fraction of eyes respond incompletely to all of these modalities resulting in visual loss and disordered retinal structure and vasculature visible on SD-OCT and OCT angiography. Efforts to close the gap between the results of interventions within randomized clinical trials and in real-world contexts, and to reduce the cost of care increasingly occupy innovation in the social organization of ophthalmic care of DME. Pharmacologic research is exploring other biochemical pathways involved in retinal vascular homeostasis that may provide new points of intervention effective in those cases unresponsive to current treatments.
NVCL: Exploiting NVRAM in Cache-Line Granularity Differential Logging

Emerging byte-addressable non-volatile memory is considered an alternative storage device for persistence guarantee with high performance. In this work, we design NVCL (NVRAM Cache-Line Granularity Logging) and develop it in Redis. The proposed NVCL exploits the cache-line flush granularity of NVRAM to maintain the write-ahead differential log and is able to flush non-continuous dirty cache lines to guarantee persistence. NVCL effectively reduces the size of persistent logs by only flushing updated data in every memory page. We measured the performance on an Intel machine with a 16 GiB non-volatile dual in-line memory module (NVDIMM). Our performance study shows that NVCL can save up to 127× NVRAM writes and shows 84% speedup comparing to Redis append-only-file logging mechanism. NVCL also reduces up to 50% NVRAM writes and achieves 15% speedup over state-of-the-art logging mechanism NVWAL.