Miracle-dz/UniFAR-FTUs huggingface dataset:
Enhancement of Hydrogen Sensing Performance of a Pd Nanoparticle/Pd Film/GaOx/GaN-Based Metal–Oxide– Semiconductor Diode

A new Pd nanoparticle (NP)/Pd film/GaO<sub><italic>x</italic></sub>/GaN-based metal–oxide–semiconductor diode hydrogen sensor is fabricated and studied. In this paper, appropriate photochemical drop coating and an H<sub>2</sub>O<sub>2</sub> surface treatment were used to form Pd NPs and a GaO<sub><italic>x</italic></sub> dielectric layer. The Pd NPs increased the surface area/volume ratio, and the presence of GaO<sub><italic>x</italic></sub> layer led to the effective dissociation of hydrogen molecules. The improved hydrogen sensing properties include a very high sensing response of <inline-formula> <tex-math notation="LaTeX">$1.24 \times 10^{{7}}$ </tex-math></inline-formula> (in 1% H<sub>2</sub>/air gas at 300 K) and an extremely low detection level (<inline-formula> <tex-math notation="LaTeX">${\le} 1$ </tex-math></inline-formula> ppm H<sub>2</sub>/air). Furthermore, based on a kinetic adsorption analysis, the activation energy was only 13.1 <inline-formula> <tex-math notation="LaTeX">$\text {KJ}\cdot \text {mol}^{-{1}}$ </tex-math></inline-formula> that is beneficial for hydrogen sensing. The proposed device is therefore promising for high-performance hydrogen sensing applications.
Research on Keyword Extraction of Word2vec Model in Chinese Corpus

With the rise of neural networks in recent years, Word2vec, a tool based on neural networks, has been widely used. Word2vec, as a new technology for natural language processing, whose appearance has made word expression in computers a major breakthrough. At the same time, more and more people are keen on sports news because of the development of national fitness exercise in our country. However, the existence of professional jargon in the news makes it obscure to ordinary readers. In this paper, Word2vec was applied to sports news, and was used to explore Chinese corpus and keyword extraction. The experimental results show that Word2vec can match related words in descending order of similarity so that readers can understand the news better.
Design of A Circular Microstrip Patch Antenna with Single Band Notch Characteristic for UWB Applications

A circular microstrip patch antenna with a single band notch characteristic is proposed using one U slot on radiating patch is discussed and presented in this paper. Ground plane is modified with truncated ground at top corners. Microstrip fed is used along with modified ground plane. This circular ultra wideband antenna may be used for frequency range from 2.3086 to 12.0056 GHz with single band notching range from 3.2457 to 3.1029 GHz. This ultra wideband antenna may be used for applications in C band from 4 to 8 GHz, upper S band from 2 to 4 GHz, X band from 8 to 12 GHz, ITU uplink satellite communication band from 8.1to 8.4 GHz, RFID from 6.6 to 7.1 GHz, WLAN from 5.2 to 5.8 while rejecting 3.5/5.5 GHz WiMAX band. Interference with WiMAX system can be minimized by choosing single band rejection design. Truncated ground plane enhance the proposed antenna bandwidth. VSWR is well below 2 for total performing frequency range except for the single band rejection.
Impact of Effective Assessment towards Students' Motivation in Computer Programming Course

Motivation is essential for successful engagement in learning. This factor is especially important in courses that are considered difficult and require high cognitive engagement. The focus of this work is computer programming education among engineering students. In previous studies, motivation to learn appeared to be a common issue in computer programming courses. In regards to motivation issues, the assessments in the course is considered as important as the other aspects of learning environment. This work presents a qualitative study on undergraduate engineering students' motivation towards learning programming in the perspective of improving the assessment methods. The assessment-centred aspect from How People Learn framework and three motivational components: expectancy, value and affective are used as the theoretical lens of this study. The methods used in this study are observations and interviews while the data was analyzed using thematic analysis method. The findings suggest that the students struggled with their perceived value towards computer programming and were lack of excitement during learning. Hence, several suggestions were mapped from the findings as meaningful teaching guide for the instructors in the future. Keywords- computer programming; assessment-centred; motivation to learn
Piecewise Linear Approximation for Extraction of JFET Resistance in SiC MOSFET

This paper proposes an accurate modeling method to inspect the resistance of JFET region in a silicon carbide (SiC) MOSFET in which piecewise linear approximation of doping profile of the p-well is utilized to simplify the calculation process. With depletion width and scatter width both considered, the newly developed model could obtain the JFET resistance more accurately than the conventional models reported. Sentaurus TCAD simulations and experimental studies are performed to verify the accuracy of the proposed model method. Additional nitrogen implantations for the JFET region are also included to further demonstrate the accuracy of the model. The developed model could help analyze the percent of JFET resistance in the total device on-state resistance, thus providing a guideline for the optimization of SiC MOSFETs.
Statistical Evaluation of Drug Safety Data

There has been growing awareness of the importance of the statistical evaluation of drug safety data both in the premarketing and postmarketing settings. Careful and comprehensive approaches are warranted in safety evaluation. This paper offers a high-level review of some key issues and emerging statistical methodological developments. Specifically, the following topics are discussed: prospective program-level safety planning, evaluation, and reporting; the impact of adverse event grouping on statistical analysis; the applications of Bayesian methods in safety signal detection; meta-analysis for analyzing safety data; and safety graphics. Aspects related to benefit-risk assessments are also covered.
Antibody-dependent cellular cytotoxicity in HIV infection

&NA; Interactions between the Fc segment of IgG and its receptors (Fc&ggr;Rs) found on cells such as natural killer cells, monocytes, macrophages and neutrophils can potentially mediate antiviral effects in the setting of HIV and related infections. We review the potential role of Fc&ggr;R interactions in HIV, SIV and SHIV infections, with an emphasis on antibody-dependent cellular cytotoxicity (ADCC). Notably, these viruses employ various strategies, including CD4 down-regulation and BST-2/tetherin antagonism to limit the effect of ADCC. Although correlative data suggest that ADCC participates in both protection and control of established infection, there is little direct evidence in support of either role. Direct evidence does, however, implicate an Fc&ggr;R-dependent function in augmenting the beneficial in vivo activity of neutralizing antibodies.
A New Model of High Speed 7T SRAM Cell

The progression of minimizing the size of the device and enlarging the density of the chip by using millions of transistors has become a firm challenge for researcher. The complex design has affected not only the power consumption but also the time delay. Considering all the facts this research proposed a new 7T SRAM memory cell with better read performance and large static noise margin by regulating drain induces barrier lowering (DIBL) effect. Liner Technology Spice and Cadence virtuoso simulation in standard 90nm CMOS technology provides the results obtained in this proposal.
Texture synthesis for SAR image simulation

SAR image simulation is important for a number of tasks in the design of SAR dedicated systems. We propose here a SAR texture simulation tool. Based on a statistical description of the local reflectivity and elevation of a surface, this tool generates seamless texture mapping patterns. The associated SAR texture renderer can provide several levels of realism, from flat 2-D texture mapping to 3-D unperfectly conducting surfaces back-scattering model, going through normal dithered Lambert law. The back-scattering model simulates polarizing, overlaying and shadowing effects, but not the multiple reflections. Using the range-buffer technique, the synthetic texture patterns are mapped on 3-D objects.
Bayesian regularized neural network decision tree ensemble model for genomic data classification

ABSTRACT Machine learning techniques have been widely applied to solve the classification problem of highly dimensional and complex data in the field of bioinformatics. Among them, Bayesian regularized neural network (BRNN) became one of the popular choices due to its robustness and ability to avoid over fitting. On the other hand, Bayesian approach applied to neural network training offers computational burden and increases its time complexity. This restricts the use of BRNN in an on-line machine learning system. In this article, a Bayesian regularized neural network decision Tree (BrNdT) ensemble model, is proposed to combat high computational time complexity of a classifier model. The key idea behind the proposed ensemble methodology is to weigh and combine several individual classifiers and apply majority voting decision scheme to obtain an efficient classifier which outperforms each one of them. The simulation results show that the proposed method achieves a significant reduction in time complexity and maintains high accuracy over other conventional techniques.
Mixed lineage kinase-4 promotes gastric carcinoma tumorigenesis through suppression of the c-Jun N-terminal kinase signaling pathway

Mixed lineage kinase-4 (MLK-4) is an important member of the mixed-lineage family of kinases that regulates the extracellular signal-regulated kinases and c-Jun N-terminal kinase (JNK) signaling pathways. The functions and mechanisms of MLK-4 in cancer initiation and progression have not been well understood. The present study investigated the expression, function and regulatory mechanism of MLK-4 in gastric carcinoma cells. Biochemical data indicated that normal MLK-4 was downregulated, which exerted dominant negative effects on gastric carcinoma cell viability, migration and invasion. The experimental data demonstrated that MLK-4 supplement abrogated activity of these mutants and induced inhibitory effects on gastric carcinoma cell viabilty, migration and invasion in vitro and in vivo. In addition, to determine the regulatory mechanism of MLK-4, its signaling pathway was assessed in gastric carcinoma cancer cells by regulating MLK-4. The present observations indicated that restoring MLK-4 activity by supplemental MLK-4 reduced gastric carcinoma cell colony formation in vitro and suppressed tumor viability, migration and invasion in vivo. The results of the present study indicated that MLK-4 may be a potential protein for targeting gastric carcinoma by suppressing kinases, which may lead to reduction of JNK signaling and enhance therapeutic efficacy in gastric carcinoma.
A Combinational LDA-Based Topic Model for User Interest Inference of Energy Efficient IPTV Service in Smart Building

Internet multimedia computing and service is becoming one of the main contributors to global energy consumption in smart building for the coming decades. In particular, Internet protocol television (IPTV) has been regarded as an important source for the Internet multimedia computing and service in our daily lives. With the development of IPTV user interest inference for network resource allocation and energy efficient design, the quality of experience (QoE) has been considered as one of the most prominent evaluation indicators for IPTV service. However, due to the explosive increase of TV programs and user’s mixed interests, how to quickly infer user interest and thus effectively allocate IPTV network resources are still a challenging and urgent problem. Moreover, with the increasing amount of user data, the requirement of real-time processing is more important than before. To handle these issues, we first put forward a new indicator called watching ratio to calculate the proportion of program’s time watched by user, which could measure user’s subjective watching QoE from objective perspective. Then, considering both the users’ current interests and their prospective interests, we propose a combinational latent Dirichlet allocation (cLDA) model and design the associated batch-based Gibbs sampling algorithm for user interest inference. Furthermore, considering the real-time processing demand in applications, we also design an online-based inference algorithm for the proposed cLDA (online-cLDA) model. Experimental results show that the proposed models and algorithms can improve the accuracy of user interest inference which can be beneficial to IPTV resource allocation in an energy efficient design.
HPV vaccination acceptability among men who have sex with men in Urumqi, China

ABSTRACT Background: Human papillomavirus (HPV) infection is common among men who have sex with men (MSM), especially among Human Immunodeficiency Virus (HIV)-infected MSM. The prevalence of HPV among MSM, accounts for the higher incidence of HPV-related cancer observed in this population. It is well known that targeted HPV vaccination is an effective way to prevent HPV infection; an intervention which could be beneficial for a high-risk group such as MSM. The current study aimed to assess the attitudes towards and acceptability of the HPV vaccine among MSM in in Urumqi, China. Methods: A total of 253 HIV-uninfected and 205 HIV-infected MSM (in Urumqi, China participated in the current cross-sectional study. Information on HPV-related knowledge, willingness to be vaccinated as well as demographic data were collected through a self-administered survey. A logistic regression model was applied to determine the predictors of HPV vaccine acceptability among the population. Results: The survey results indicated that only 218 (47.6%) of MSM questioned were aware of the term HPV, nevertheless, once awareness was established the prevalence of acceptability of free HPV vaccine was recorded at 96.7% of the total MSM sample. However, HIV-uninfected and HIV-infected MSM demonstrated significantly different attitudes in regard to their acceptability of free HPV vaccination (94.9% vs. 99.0%, p < 0.001) as well as their willingness to pay for the HPV vaccination (64.8% vs. 80.5%, p < 0.001), with the HIV-infected group being significantly more receptive towards HPV immunization. A multivariate logistic regression analysis indicated that local residency, employment status, hepatitis B vaccination status, previous awareness of HPV and HIV status were independent predictors of the participants’ willingness to pay for HPV vaccination. Conclusions: Participants in the current study demonstrated poor knowledge of HPV but the majority of MSM were willing to accept HPV vaccine after consultation; with HIV-infected MSM displaying higher acceptability towards a potential HPV vaccination than HIV-uninfected MSM. MSM who were previously aware of HPV were more likely to be willing to pay for HPV vaccine.
Learning Outcomes-Oriented Feedback-Response Pedagogy in Computer System Course

Higher education should focus on learning outcomes, which means teaching design should be student-centered instead of teacher- or course-centered. Effective feedback and response between teachers and student enhance performance and achievement for learners as well as educators. The classic questionnaires are always not effective and timely enough. According to the requirements of talent engineer training, a learning outcomes-oriented feedback-response pedagogy is applied in computer system course, which is an important core major course and basic engineer training course. Multiple kinds of feedback are scheduled at appropriate times and multiform responses are prompt to do assessment and improvement of learning outcomes. Inspiring changes in our course and from students indicate that the pedagogy is effective and meet the need of engineering talents training.
ELiRF-UPV en TASS 2018: Categorización Emocional de Noticias(ELiRF-UPV at TASS 2018: Emotional Categorization of News Articles)

This paper describes the participation of the ELiRF research group of the Universitat Politècnica de València at TASS2018 Workshop which is a satellite event of the XXXIV edition of the International Conference of the Spanish Society for Natural Language Processing. We describe the approaches used for “Good Or Bad News? Emotional categorization of news articles” task, the results obtained and a discussion of these results. Our participation has focused primarily on exploring different approaches of Deep Learning and we have achieved competitive results in the addressed task.
Prenatal diagnosis of fetal multiple hemivertebrae: the importance of 3D ultrasound assessment

Abstract We herein present a case of fetal multiple hemivertebrae detected at antenatal sonography. The use of the 3 D technology supported by a new contrast enhancement rendering algorithm (Crystal Vue) has allowed the accurate prenatal classification of the defect, confirmed at follow up, that would have been difficult to define by 2 D only.
Binding Performance of Human Intravenous Immunoglobulin and 20(S)-7-Ethylcamptothecin

A previous study showed that intravenous immunoglobulin (IVIG) could preserve higher levels of biologically active lactone moieties of topotecan, 7-ethyl-10-hydroxycamptothecin (SN-38) and 10-hydroxycamptothecin at physiological pH 7.40. As one of camptothecin analogues (CPTs), the interaction of 7-ethylcamptothecin and IVIG was studied in vitro in this study. It was shown that the main binding mode of IVIG to 7-ethylcamptothecin was hydrophobic interaction and hydrogen bonding, which is a non-specific and spontaneous interaction. The hydrophobic antigen-binding cavity of IgG would enwrap the drug into a host-guest inclusion complex and prevent hydrolysis of the encapsulated drug, while the drug is adjacent to the chromophores of IgG and may exchange energy with chromophores and quench the fluorescence of the protein. Also, the typical β-sheet structure of IVIG unfolded partially after binding to 7-ethylcamptothecin. Additionally, the binding properties of IVIG and six CPTs with different substituents at A-ring and/or B-ring including camptothecin, topotecan, irinotecan, 10-hydroxycamptothecin, 7-ethylcamptothecin and SN-38 were collected together and compared each other. Synergizing with anti-cancer drugs, IVIG could be used as a transporter protein for 7-ethylcamptothecin and other CPTs, allowing clinicians to devise new treatment protocols for patients.
On Considering Saturation and Cross-Coupling Effects for Copper Loss Minimization on Highly Anisotropic Synchronous Machines

In this paper, the influence of saturation and cross-coupling effects on the copper loss minimization for synchronous machines with strong saliencies, especially the permanent-magnet-assisted synchronous reluctance machines and reluctance synchronous machines are analyzed. It is shown that state-of-the-art methods for saturation consideration through the absolute inductances fail for these machines. A novel method for maximum torque per ampere estimation, which includes the consideration of these effects through the use of differential inductances, is proposed and its effectiveness is shown through finite-element analysis and experiments.
Relation Extraction Based on Deep Learning

Extracting entities and their relations is to detect entity mentions and recognize the semantic relation between them. Most of traditional methods are feature-based and treat this task as a pipeline of two separated tasks, i.e., named entity recognition and relation classification. Due to deep neural network models can learn effective entities and relations features from the given sentences without complicated manual feature engineering. Deep learning methods have been viewed as one of the major driving force in the recent development of natural language processing. We will briefly review the previous works on deep learning and give a brief overview of recent progresses on relation extraction. We implement the models based on deep neural networks both in pipeline methods and joint methods and come to conclusion about the comparison.
Firefly Algorithm for the RBF Network Design

The paper focuses on using the firefly algorithm for designing the radial-basis neural networks. The firefly algorithm belongs to a family of the global optimization tools. The firefly algorithm is a nature-inspired and one of the most powerful algorithms for solving the NP-hard optimization problems. In the paper the firefly algorithm is used as a tool for designing of the RBF network, including estimation of its output weights and transfer function parameters. The details of the implementation are discussed. Computational experiment has been carried-out with a view to investigate effectiveness of the discussed implementation. Experiment results have confirmed usefulness of the proposed approach. Conclusions include suggestions for future research.
String Transduction with Target Language Models and Insertion Handling

Many character-level tasks can be framed as sequence-to-sequence transduction, where the target is a word from a natural language. We show that leveraging target language models derived from unannotated target corpora, combined with a precise alignment of the training data, yields state-of-the art results on cognate projection, inflection generation, and phoneme-to-grapheme conversion.
Microarray Camera Image Super-Resolution with Neural Network and Fusion of V-System

With the rapid development of artificial intelligence technology, more and more intelligent devices are beginning to be manufactured. At the same time, the demand of the image resolution is getting higher. Super-resolution of the image has become a research hotspot in the field of artificial intelligence. The same time, convolution neural networks have been successful in many fields of computer vision, including image super-resolution. Single image super-resolution has received a lot of attention and made good progress recently. However, there are few neural network models for multi-image super-resolution. Array images are a completely new experience and application for super-resolution. In this paper, we use the microarray camera (3*3) to get nine pictures in the same scene and use nine images to realize multiple images super-resolution. A super-resolution model combining software with hardware is proposed. The structure of image registration, V- system image fusion and convolution operation are constructed. The super-resolution model can extract the feature of the target image more efficiently, and the array camera has the characteristic of trading space for the time change. The model can be more accurate and efficient than single image super-resolution. In the PSNR and SSIM indexes, 1.01dB and 0.03 are increased respectively. We use ISO12233 camera resolution chart to detect the experimental pictures. In the experimental results, the resolution of the algorithm is the best.