bluuebunny/crossref_metadata_2025 huggingface dataset:
Activation by NarL at the Escherichia coli ogt promoter
Authors: Ruanto Patcharawarin , Chismon David L. , Hothersall Joanne , Godfrey Rita E. , Lee David J. , Busby Stephen J. W. , Browning Douglas F.
Published: July 2020

The Escherichia coli NarX/NarL two-component response-regulator system regulates gene expression in response to nitrate ions and the NarL protein is a global transcription factor, which activates transcript initiation at many target promoters. One such target, the E. coli ogt promoter, which controls the expression of an O6-alkylguanine-DNA-alkyltransferase, is dependent on NarL binding to two DNA targets centred at positions −44.5 and −77.5 upstream from the transcript start. Here, we describe ogt promoter derivatives that can be activated solely by NarL binding either at position −44.5 or position −77.5. We show that NarL can also activate the ogt promoter when located at position −67.5. We present data to argue that NarL-dependent activation of transcript initiation at the ogt promoter results from a direct interaction between NarL and a determinant in the C-terminal domain of the RNA polymerase α subunit. Footprinting experiments show that, at the −44.5 promoter, NarL and the C-terminal domain of the RNA polymerase α subunit bind to opposite faces of promoter DNA, suggesting an unusual mechanism of transcription activation. Our work suggests new organisations for activator-dependent transcription at promoters and future applications for biotechnology.
Cultural Competence and Self-Efficacy After Study Abroad Experiences
Authors: de Diego-Lázaro Beatriz , Winn Kevin , Restrepo María Adelaida
Published: July 2020

Purpose

Cultural competence is crucial for the successful provision of speech, language, and hearing services. The purpose of this study was to assess and describe gains in cultural awareness, cultural competence, and self-efficacy after service-learning study abroad experiences and to examine whether gains in these areas are related to higher clinical skills ratings in speech-language pathology and audiology students.

Method

Sixteen speech-language pathology and audiology students participated in two international study abroad experiences (Nicaragua and Malawi). Students completed a survey on cultural awareness, competence, and self-efficacy beliefs and journal entries before, during, and after their trips. In addition, the supervisors assessed the clinical skills of the students by the end of the trip. The researchers applied a mixed-methods approach to analyze data from the survey, clinical ratings, and journals.

Results

Students showed significant increases in cultural awareness, competence, and self-efficacy. Gains in self-efficacy and cultural awareness were highly correlated with students' clinical ratings in cultural competence as judged by their supervisors. Two main themes were identified from the journal entries: continuing community involvement and growth in cultural self-efficacy.

Conclusion

Service-learning study abroad experiences help students develop cultural awareness and competence skills and increase their self-efficacy beliefs. Using a mixed-methods approach can help identify strengths and weaknesses in the training of speech-language pathology and audiology students with regard to cultural competence.

Supplemental Material

https://doi.org/10.23641/asha.12642647
Komplikationen nach pleuralem getunnelten Dauerkatheter bei symptomatischen rezidivierenden benignen und malignen Pleuraergüssen
Authors: Langner S. , Koschel D. , Kleymann J. , Tausche K. , Karl S. , Frenzen F. , Heberling M. , Schulte-Hubbert B. , Halank M. , Kolditz M.
Published: July 2020

Einleitung Die Implantation eines pleuralen getunnelten Dauerkatheters (indwelling pleural catheter = IPC) stellt bei symptomatischen rezidivierenden benignen und malignen Pleuraergüssen (BPE und MPE) neben einer Pleurodese eine weitere etablierte Therapiemethode dar.

Zur Sicherheit des IPC, insbesondere zu Pneumothorax und Katheterinfektionen, existierten wenige Studien.

Ziel unserer Untersuchung war, die Komplikationshäufigkeit nach IPC-Anlage und deren prädiktive Faktoren bei Patienten mit BPE vs. MPE zu ermitteln.

Methoden Retrospektive Analyse aller IPC-Implantationen im Bereich Pneumologie am Universitätsklinikum Dresden im Zeitraum von 2015 – 2018.

Ergebnisse Bei 86 Patienten (je 43 m/f; Alter 66,9 ± 13,3 Jahre) wurde bei symptomatischem BPE und MPE ein IPC implantiert. Ein BPE bzw. MPE bestand bei 12,8 % (11/86) bzw. 87,2 % (75/86) der Erkrankten.

Als Sofortkomplikation nach IPC-Anlage war bei 43/86 (50 %) Patienten ein meist kleiner, asymptomatischer Pneumothorax nachweisbar. 34/43 (79 %) Patienten bedurften diesbezüglich keiner spezifischen Therapie. Bei 9/43 war ein IPC-Sog im Median über 3 Tage erforderlich. 8/43 Patienten wiesen einen großen Pneumothorax mit partieller/kompletter Regredienz im Median nach 2 Tagen auf.

Bei 15,1 % (13/86) der Gesamtgruppe und 36,4 % (4/11) der BPE vs. 12 % (9/75) der MPE kam es im Median nach 87 (BPE/MPE 116/87) Tagen zu einer Katheterinfektion. Diese war bei BPE (p = 0,035), großem Pneumothorax (4/8 Patienten; p = 0,015) und längerer Katheterverweildauer (124 ± 112 vs. 71 ± 112 Tage; p = 0,07) häufiger.

Schlussfolgerung Kleine Pneumothoraces sind häufig nach IPC-Implantation, bedürfen aber meist keiner spezifischen Therapie. Bei 15,1 % aller Patienten war im Median nach 87 Tagen eine Katheterinfektion nachweisbar. Diese trat häufiger bei BPE, längerer Katheterverweildauer und großen Pneumothoraces auf.
Bauhinia Protease Inhibitors Attenuate Gastric Ulcer by Blocking Neutrophil Enzymes
Authors: Valois Mayara Vioto , de Oliveira Cleide , Lapa Antonio José , Souccar Caden , Oliva Maria Luiza Vilela
Published: July 2020

Proteases play a pivotal role in many signaling pathways; inhibitors of well-established proteases have shown a substantial therapeutic success. This study aimed to examine the in vivo effects of 3 protease inhibitors isolated from Bauhinia species: i) Bauhinia mollis elastase inhibitor, which blocks human neutrophil elastase (Kiapp 2.8 nM) and cathepsin G (Kiapp 1.0 nM) activities; ii) Bauhinia mollis trypsin inhibitor, a trypsin inhibitor (Kiapp 5.0 nM); and iii) Bauhinia bauhinioides cruzipain inhibitor, which inhibits elastase (Kiapp 2.6 nM), cathepsin G (Kiapp 160.0 nM), and the cysteine proteases cathepsin L (Kiapp 0.2 nM). Bauhinia bauhinioides cruzipain inhibitor, Bauhinia mollis elastase inhibitor, and Bauhinia mollis trypsin inhibitor were isolated using acetone and ammonium sulfate fractionations, DEAE-Sephadex, trypsin-Sepharose, and Resource-Q chromatographies. Mice and rats were treated intraperitoneally with 1 dose of inhibitor; gastric mucosal lesions were induced by cold-restraint stress. Oral pretreatment of mice with Bauhinia mollis elastase inhibitor or Bauhinia mollis trypsin inhibitor (1 – 10 mg/kg) did not show anti-ulcer effect, while Bauhinia bauhinioides cruzipain inhibitor (0.1 – 1.0 mg/kg) produced a similar reduction of the index of mucosal damage at all effective doses (30 to 33% < control). In rats at doses lower than those used in mice, Bauhinia mollis elastase inhibitor and Bauhinia bauhinioides cruzipain inhibitor reduced the index of mucosal damage by 66% and 54% of controls, respectively. The results indicate a protective effect against gastric mucosal lesions associated with elastase inhibition but not inhibition of trypsin activities. Moreover, the lack of Bauhinia mollis elastase inhibitor efficacy observed in mice may possibly be related to the reported structural differences of elastase in mice and rats.
Correlation between Age and Surgical Approach for Thoracic and Lumbar Hemivertebra
Authors: Nikova Alexandrina , Chatzipaulou Varvara , Malkots Belkis , Mustafa Reichan Molla , Valsamidou Christina , Birbilis Theodosis
Published: July 2020

Objective Hemivertebra (HV) is a congenital defect of the formation of the spinal vertebra, which can result in scoliosis or kyphosis along with the related symptomatology of spine deformity. More often than not, it is linked to other abnormalities and requires attention. Its management is surgical and it is of great importance for the physician to choose the right approach at the right time, due to its deteriorative prognosis.

Methods Due to the interest of the subject, the authors investigated the world literature between 1990 and 2018 and found 45 articles, reporting thoracic, thoracolumbar, and lumbar HV in children and its postsurgical outcome, aiming to show whether the approaches are equal in terms of the final outcome.

Results The chosen surgical method depends much on the level of the pathology. Despite this fact, after analyzing the included data, we found that the surgical techniques are unequal with regard to the purpose of achieving improvement. Age, caudal and cranial curves, segmental kyphosis, and scoliosis are factors playing a major role in this.

Conclusion If not treated, HV leads to deterioration and dysfunction. The most optimal result, however, is achieved only when the surgical approach is applied according to age and rest of the accompanying factors, which should be considered in future management planning.
Evaluation of Rise in Pulp Chamber Temperature after Activation with Different Curing Lights on Bleached Teeth–An In Vitro Study
Authors: Bansal Aditya , Kumar Yogesh , Jindal Neetu , Aggarwal Renu , Jain Somya
Published: July 2020

Introduction The aim of the study was to evaluate rise in pulp chamber temperature after activation with different curing lights on bleached teeth in an in vitro study. The present study is an in vitro study with a sample size of 100. A total of 100 human extracted maxillary central and lateral incisors were collected and then randomly assigned into one control group and four experimental groups (n = 20).

Material and Methods As many as 100 freshly extracted noncarious human maxillary central and lateral incisor teeth were used in this study. The access opening of all 100 samples were done to facilitate access to the pulp chambers for measuring the temperature. The samples were embedded into the additional silicone model, and uniform distance of 5 mm from tooth surface was taken for gel activation using different curing lights (LED, QTH, plasma arc, diode laser). The temperature inside the pulp chamber was measured using digital infrared thermometer. Infrared light of infrared thermometer was put on pulp chamber before the bleaching gel application (T0) 1 minute after bleaching gel application (T1). Later, there was changing of color of bleaching gel from dark red into green color when activated with different curing lights (T2).

Statistical Analysis The temperature data obtained were analyzed statistically by one-way ANOVA and posthoc Tukey’s tests. Significance level was set at 5% for all analyses.

Results The mean and standard deviation (SD) values of rise in pulp chamber temperature after activation with different light sources were Group II (LED) 0.5 ± 0.466, Group III (QTH) 0.775 ± 0.229, Group IV (plasma arc) 1.26 ± 0.690, and Group V (diode laser) 1.355 ± 0.452.

Conclusion Compared with other light-curing units, LED group induced lowest rise in pulp chamber temperature. Whereas, bleaching without light activation does not induce rise in pulp chamber temperature.
Effect of hydride vapor phase epitaxy growth conditions on the degree of atomic ordering in GaInP
Authors: Schulte Kevin L. , Diercks David R. , Roberts Dennice M. , Dippo Patricia C. , Packard Corinne E. , Simon John , Ptak Aaron J.
Published: July 2020

We report a systematic study of CuPt-type ordering in hydride vapor phase epitaxy (HVPE)-grown Ga0.5In0.5P. Selected-area electron diffraction reveals ordering in samples grown on (001) GaAs substrates offcut toward (11¯1)B. The ordering is single-variant, occurring only on (11¯1)B planes and not on (1¯11)B. Quantitative analysis of the order parameter by high-resolution x-ray diffraction (HRXRD) indicates that ordering increases with deposition temperature in samples grown at 600–700 °C with a constant gas-phase V/III ratio ∼3. Ordering increases with V/III ratio in the range of 1.3–6.7 at a constant deposition temperature of 650 °C. Photoluminescence measurements correlate the order parameter with Ga0.5In0.5P bandgap contraction, though the contraction is larger than expected based on the magnitude of order parameters measured by HRXRD. A possible reason for this discrepancy is that the photoluminescence emission occurs in the lower bandgap ordered domains, which are small and evenly dispersed throughout the material. We also show that the degree of ordering decreases with growth rate, disappearing at ∼60 μm/h. The HVPE-grown material exhibits a generally weaker ordering than organometallic vapor phase epitaxy (OMVPE)-grown material, likely due to the moderate V/III ratios employed, in contrast to the V/III ratios in the 100s typical of OMVPE. However, the tendency for ordering to increase with V/III ratio suggests that the same dimer-induced stress mechanism used to explain the occurrence of ordering in OMVPE-grown material also applies to HVPE. The tendencies for ordering to increase with deposition temperature and decrease with growth rate show that kinetics limit the degree of ordering, also in agreement with OMVPE trends.
Electrospinning and emerging healthcare and medicine possibilities
Authors: Liu Ziqian , Ramakrishna Seeram , Liu Xiaoling
Published: July 2020

Electrospinning forms fibers from either an electrically charged polymer solution or polymer melt. Over the past decades, it has become a simple and versatile method for nanofiber production. Hence, it has been explored in many different applications. Commonly used electrospinning assembles fibers from polymer solutions in various solvents, known as solution electrospinning, while melt and near-field electrospinning techniques enhance the versatility of electrospinning. Adaption of additive manufacturing strategy to electrospinning permits precise fiber deposition and predefining pattern construction. This manuscript critically presents the potential of electrospun nanofibers in healthcare applications. Research community drew impetus from the similarity of electrospun nanofibers to the morphology and mechanical properties of fibrous extracellular matrices (ECM) of natural human tissues. Electrospun nanofibrous scaffolds act as ECM analogs for specific tissue cells, stem cells, and tumor cells to realize tissue regeneration, stem cell differentiation, and in vitro tumor model construction. The large surface-to-volume ratio of electrospun nanofibers offers a considerable number of bioactive agents binding sites, which makes it a promising candidate for a number of biomedical applications. The applications of electrospinning in regenerative medicine, tissue engineering, controlled drug delivery, biosensors, and cancer diagnosis are elaborated. Electrospun nanofiber incorporations in medical device coating, in vitro 3D cancer model, and filtration membrane are also discussed.
Low pressure gas electron diffraction: An experimental setup and case studies
Authors: Vishnevskiy Yury V. , Blomeyer Sebastian , Reuter Christian G.
Published: July 2020

Principles of low pressure gas electron diffraction are introduced. An experimental setup has been constructed for measuring the electron diffraction patterns of gaseous samples at pressures below 10−3 mbar. Test measurements have been performed for benzoic acid at T = 287 K corresponding to a vapor pressure of the substance P = 2 × 10−4 mbar, for iodoform CHI3 at T = 288 K (P = 4 × 10−4 mbar), and for carbon tetraiodide CI4 at T = 290 K (P = 1 × 10−4 mbar). Due to the low experimental temperature, thermal decomposition of CI4 has been prevented, which was unavoidable in previous classical measurements at higher temperatures. From the obtained data, the molecular structures have been successfully refined. The most important semi-empirical equilibrium molecular parameters are re(Car–Car)av = 1.387(5) Å in benzoic acid, re(C–I) = 2.123(3) Å in iodoform, and re(C–I) = 2.133(7) Å in carbon tetraiodide. The determined parameters showed consistency with the theoretically predicted values. A critical comparison with the results of the earlier investigations has also been done.
Physical limits of flight performance in the heaviest soaring bird
Authors: Williams H. J. , Shepard E. L. C. , Holton Mark D. , Alarcón P. A. E. , Wilson R. P. , Lambertucci S. A.
Published: July 2020

Significance

Flapping flight is extremely costly for large birds, yet little is known about the conditions that force them to flap. We attached custom-made “flight recorders” to Andean condors, the world’s heaviest soaring birds, documenting every single wingbeat and when and how individuals gained altitude. Remarkably, condors flapped for only 1% of their flight time, specifically during takeoff and when close to the ground. This is particularly striking as the birds were immature. Thus, our results demonstrate that even inexperienced birds can cover vast distances over land without flapping. Overall, this can help explain how extinct birds with twice the wingspan of condors could have flown.
Multiple origins of green coloration in frogs mediated by a novel biliverdin-binding serpin
Authors: Taboada Carlos , Brunetti Andrés E. , Lyra Mariana L. , Fitak Robert R. , Faigón Soverna Ana , Ron Santiago R. , Lagorio María G. , Haddad Célio F. B. , Lopes Norberto P. , Johnsen Sönke , Faivovich Julián , Chemes Lucía B. , Bari Sara E.
Published: July 2020

Significance

Green coloration of vertebrates is normally attributed to pigments and structural components inside skin chromatophores cells. However, these components do not account for the vivid blue-green colors of hundreds of species of frogs with sparse chromatophores. Our study shows that green coloration originates in proteins of the serpin superfamily that bind the pigment biliverdin, modulating its absorbance properties. Using a South American treefrog, we demonstrated that these serpins have a clear ecological role in modulating the reflectance properties and rendering animals cryptic in the foliage even in the near-infrared portion of the spectrum. These findings open up exciting research perspectives both in biochemistry and evolution of serpins, as well as in the study of extracellular protein-mediated coloration in vertebrates.
Deceleration of Metastable Li+ Beam by Combining Electrostatic Lens and Ion Trap Technique
Authors: Chen Shao-Long , Zhou Peng-Peng , Liang Shi-Yong , Sun Wei , Sun Huan-Yao , Huang Yao , Guan Hua , Gao Ke-Lin
Published: July 2020

Ion deceleration has played a critical role in ion-related research when the ions are produced in the form of a high-energy beam. We present a deceleration method combining electrostatic lens and ion trap technique, which can effectively decelerate ions to energy below the trapping potential of a typical ion trap. The experiments were performed on metastable 1s2s
3
S
1 Li+ ions, and demonstrated that the kinetic energy could easily be reduced from ∼450 eV to a few eV, with the latter being confirmed using the Doppler-shifted fluorescence spectra.
Determining two coefficients in diffuse optical tomography with incomplete and noisy Cauchy data
Authors: Tam Quyen Tran Nhan
Published: July 2020

In this paper we investigate the non-linear and ill-posed inverse problem of simultaneously identifying the conductivity and the reaction in diffuse optical tomography with noisy measurement data available on an accessible part of the boundary. We propose an energy functional method and the total variational regularization combining with the quadratic stabilizing term to formulate the identification problem to a PDE constrained optimization problem. We show the stability of the proposed regularization method and the convergence of the finite element regularized solutions to the identification in the L

s
-norm for all s ∈ [0, ∞) and in the sense of the Bregman distance with respect to the total variation semi-norm. To illustrate the theoretical results, a numerical case study is presented which supports our analytical findings.
Design and Development of Traffic Evacuation Software Based on Micro Simulation
Authors: Duan Bingyu , Wang Ziyang , Chen Xudong
Published: July 2020

In order to better evacuate residents in the case of regional disasters and ensure the safety of the lives and properties of regional residents, we designed and developed traffic evacuation simulation software under various disasters based on microscopic simulation. The system adopts C / S architecture, MVC design mode, and has the functions of road network simulation, intersection simulation, vehicle operation simulation and signal control simulation. It is loaded through the simulation program, compares different evacuation schemes, optimizes the setting of space division, path division, signal Phase and signal phase. Provide reference basis for the relevant departments to evacuate residents.
Study of Reasons for Pitting Corrosion Occurred on Flange Made of 1Cr18Ni9Ti Stainless Steel
Authors: Sun Gang , Li Xiaolin , Du Jun , Luo Jia , Wang Tairan
Published: July 2020

When pickling the stainless steel flange made of 1Cr18Ni9Ti after welding process, rough pits were observed on the surface of the part. An investigation of occurrence mechanism and chemical composition of these pits has been carried out, which involved scanning electron microscope (SEM) and Energy Dispersive Spectroscopy (EDS). It was found that the flange suffering local corrosion called pitting corrosion during the pickling process, for the reason of that cavities occurred between the outer sleeve nut and the weld joint area blocked the movement of cations, mostly Fe3+ and Cr3+. These cations hydrolyzed to H+ absorbing Cl− outside the cavity in the pickling acid causing corrosion on the part surface. Adjusting purity of pickling acid and shafting the part during pickling process can obviously reduce the potential of occurrence of pitting corrosion.
Generating Adversarial Examples for Static PE Malware Detector Based on Deep Reinforcement Learning
Authors: Chen Jun , Jiang Jingfei , Li Rongchun , Dou Yong
Published: July 2020

Machine learning technology has been applied in filed of malware detection; it can improve efficiency of malware detection to deal with more and more increasing malware variants. However, malware detection model based on machine learning also has weakness which can be cheated by adversarial examples. Researching on method of generating adversarial examples could be benefit to exposing vulnerability of malware detection model and designing better malware detector. In this paper, we propose a reinforcement learning environment named gym-malware-mini based on gym-malware through which we generate adversarial examples using DQN and A2C deep reinforcement learning algorithm. As a result, DQN agent learned better policy of generating adversarial examples in gym-malware-mini, Success rate is increased by 18% compared with gym-malware. Success rate of DQN agent and A2C agent is increased by 20% and 15% compared with random agent in gym-malware-mini environment.
Improved Gradient Projection Algorithm for Deblurred Image Application
Authors: Yan Haixia , Liu Yanjun
Published: July 2020

For the purpose of reducing the noise of deblurred image, an improved Gradient Projection method by sparse coding Reconstruction (GPSR) algorithm is proposed. Different with the traditional Gradient Projection method for sparse reconstruction code (GPSR) method, the obvious distinctions between the original image and deblurred image are projected onto dimensional projection image value. Thus the picture noise are deleted. The classical Gradient Sparse Projection computing method, searching direction changes time by time. Now we propose the new method by running with fix step. The constraints of searching method is guarantee. We prove the new computing method in theory, and at the same time, we running the method by classical picture. We compare the running results of classic method and the fix step hunt method (FXHM), the running results of two methods are shown in the article, the performance of fix step hunt method (FXHM) is higher than the classic method as possible as it can.
Research on Optimization of Tourism Route Based on Genetic Algorithm
Authors: Chen Yafeng , Zheng Xiaoyang , Fang Ziming , Yu Yue , Kuang Zhongjie , Huang Yiting
Published: July 2020

This paper aims at the tourist route planning of 47 scenic spots faced by tourists when traveling in Chongqing. The route distance and transportation cost of tourists during travel are taken into account and the optimal planning of tourist routes are recommended to meet their personal needs. First, the coordinates of longitude and latitude of each attraction and the transportation costs between the attractions are collected. Second, the distance target and transportation cost target are combined into a combined target by using the weighting coefficient method. Finally, the optimal solution of the combined target was solved by the genetic algorithm. The result obtained is that when only the cost is considered, the distance of 47 attractions is 2257.76 kilometers and the transportation cost is 2866.2 yuan. While only the distance is analyzed, the above two values are 1426.68 kilometers and 4931.18 yuan, respectively.
Application of Ibeacon in Indoor Positioning and Navigation
Authors: Ye Nuanqiang , Luo Jinman , Zhao Shanlong , Yan Jing
Published: July 2020

In recent years, with the development of new energy vehicles, the demand for indoor charging is increasing. In the construction and application development of large indoor parking lot, users’ demand for location-based service is more urgent. At this point the indoor positioning technology appears to be very important. At present, indoor mainstream technologies include UWB, RFID, ZigBee, ultrasonic, inertial navigation, optical positioning, iBeacon, Wi-fi and geomagnetic, etc. Compared with other technologies, iBeacon technology has the advantages of low power consumption and strong compatibility. IBeacon positioning technology helps users find idle charging piles more quickly and conveniently. This paper will briefly introduce the application of iBeacon in indoor positioning and navigation and related algorithms.
Human Detection Based on Improved Mask R-CNN
Authors: Wang Yuejuan , Wu Ji , Li Heting
Published: July 2020

Human detection has been widely concerned by academic and industrial circles. The gradual maturity of deep learning framework further improves the accuracy and speed of detection. However, the relatively mature human detection methods cannot get accurate detection results because of the complex background, shooting angle and many limitations of human behaviour. Aiming at solving the problems of human detection in complex scenes, a novel human detection algorithm based on the improved mask R-CNN framework is proposed by implementing the leading research results of object detection through deep learning. The algorithm combines ResNet and FPN to extract the features of the image, and then takes advantage of RoIAlign and fine-grained Slic to proofread the pixels. In the experiments that compared with the original mask R-CNN algorithm on the same data set was carried out to verify the effectiveness of the proposed algorithm. The mAP and AR value of the improved mask R-CNN algorithm is greater than that of the mask R-CNN algorithm when the IoU is 0.5-0.95, showing that the improved mask R-CNN framework was able to detect human from video better.
Effective Data Generation for E-banking Transactions Using Cycle-Consistent Adversarial Networks
Authors: Wang Xiaoguo , Zhao Han
Published: July 2020

In the anti-fraud research, the small amount of fraudulent transactions leads to extremely class imbalanced data. This problem becomes a bottleneck of fraud detection. In this paper, we apply the Cycle-Consistent Adversarial Networks (CycleGAN) to generate data for the minority class. Based on real e-banking transaction data, generators and discriminators are designed to generate synthetic data that meets the characteristics of e-banking transactions. Synthetic samples and real samples are mixed into the training of fraud detection model, and multiple metrics are used to verify the effect. Experimental results show that the synthetic data generated by CycleGAN can effectively improve the performance of the fraud detection model.
A Simplified Design of Automatic Energy Consumption Measuring Platform for Embedded Systems
Authors: Wu Huanjie , Chen Chun , Weng Kai
Published: July 2020

In this paper, a simplified design of automatic energy consumption measuring platform for embedded systems is proposed. A straightforward device named USB-TTL replaces the intermediate device in the original design and becomes the link between the host computer and the target board. The simplification makes the design of host computer software simpler and the whole platform more reliable. It also eliminates the need to design software for the intermediate device. In general, it has features similar to the original design. A series of test sets are also designed to verify its capabilities and accuracy. Compared to the original design, the simplified one has almost consistent accuracy, is easier to deploy, and requires less wiring and devices.
An Approach to Decrease Interference among Modalities in Emotion Detection
Authors: Dai Yu , Weng Jiancheng , Liu Yi , Liu Jian , Chang Boyu
Published: July 2020

Emotion detection of video clips through multimodal information helps in a number of applications, including view mining, recommending system, public opinion and public sentiment monitoring. Current multimodal fusion techniques are applied to identify relevant information among modalities, which can introduce the interference of different modalities when detecting the emotion in the video. In this paper, we introduce a method which uses Q-Learning algorithm in attention-based network for decreasing interference among different emotion modalities. Experimental results prove that our method can improve the performance of basic attention-based network when detecting the emotion in the video.
A Quantitative Investment Model Based on Random Forest and Sentiment Analysis
Authors: Chen Mingqin , Zhang Zhenhua , Shen Jiawen , Deng Zhijian , He Jiaxing , Huang Shiting
Published: July 2020

In recent years, under the influence of economic globalization and anti-globalization, the stock market has experienced great fluctuations in China. Quantitative investment has attracted a lot of attention because of its characteristics of maintaining stable returns. Existing research is unilaterally based on quantitative data or qualitative data for analysis to construct a quantitative investment model. This paper considers both quantitative and qualitative data to construct a more comprehensive model than that in the past. Based on the optimized database, we present a combinational model named RF-SA, which is composed of random forest and sentiment analysis model. First of all, this paper uses the SBS algorithm to select the characteristics of stock transaction historical data, optimizes the prediction database, reduces data redundancy, and improves the accuracy of the model. Secondly, we analyze the characteristics of the Chinese stock market and study the advantages and disadvantages of many data mining algorithms, and select random forest model, the most suitable model, to build the first step of stock selection model. Then, through the analysis of public opinion, the confidence index of the stockholders is calculated; on this basis, the results of the RF model and the confidence index are combined to make a second choice for the stock, and the quantitative investment portfolio is obtained, and excess returns can be obtained. The results of empirical data show that, the RF-SA model obtains a higher rate of return than the investment model of the Shanghai Stock Index.
Towards End-to-End Face Recognition Method through Spatial Transformer
Authors: Wu Yanfang , Lu Xiaobo , Qin Chen
Published: July 2020

Face recognition technology is widely applied in daily life, but in most methods, similarity or affine transformation is employed to align face images according to five facial landmarks. The face alignment module is implemented independently, thus it’s difficult in end-to-end training. In this paper, the main purpose is to design a towards end-to-end trainable face recognition method based on indoor scenes. Due to that spatial transformer can implement any parametrizable transformation, we joint it with recognition network, making end-to-end training possible. Simultaneously, any prior knowledge on facial landmarks isn’t required. The model jointly with spatial transformer can achieve 0.3% higher accuracy than similarity transformation. Most downsampling methods ignore the sampling theorem, making convolutional networks not shift-invariant. We replace max-pooling by MaxBlurPool in spatial transformer network, and the accuracy is improved by 0.25%.
Design of Multifunctional Handheld Terminal for EOD Robot
Authors: Sun Tiancheng , Tan Yingzi
Published: July 2020

This paper designs a multifunctional handheld terminal for the explosive ordnance disposal robot (EOD robot), which can not only be used for one-to-one remote control of robots, but also be used as a remote monitoring platform for multiple robots. The hardware part of the terminal is based on the four-core processor Exynos4412, including power management, video decoding, data storage, network communication and other functional modules. The software part takes embedded Linux as the operating system platform, including human-computer interaction, network communication and data decoding modules. The system uses multithreading technology and draws the 3d model of the robot through OpenGL. The test results show that the terminal system is stable and reliable, and can meet the application requirements.
Research on Financial Aid Model of Colleges and Universities Based on Artificial Neural Network
Authors: Zhou Jun , Yang Mei , Wang Fang , Wang Chao
Published: July 2020

There are some problems in the recognition of financial aid objects in Colleges and Universities, such as being interfered by human factors and weak in quantification. The existing relevant research is mainly about policies, systems and measures, while the application of artificial intelligence in precise financial aid in colleges and universities needs further research. And the new generation of AI technology in deep learning can automatically extract data characteristics, and it can be used in the accurate identification of poor students, with the advantages of having no need for human intervention. This model designs and optimizes the precise identification model of university funding objects based on artificial intelligence technology, and achieves a satisfactory recognition rate, which explores a new technical way to improve the equity of education funding and its efficiency exploration.
A Method for Converting Inclusion Measure to Entropy of Interval Type-2 Fuzzy Sets
Authors: Zheng Gao , Wang Jing
Published: July 2020

In order to model imprecise information better, more and more scholars use type-2 fuzzy sets, among which interval type-2 fuzzy sets have practical application value, the reasons lie in that their secondary grades are all 1 and there are some fast algorithms for their operations. Inclusion measure and entropy are considered as two basilic parameters in fuzzy set theory because of their versatility, and those of interval type-2 fuzzy sets have become research hotspots nowadays. This paper mainly studies the relationship between the inclusion measure and entropy of interval type-2 fuzzy sets presented by Zheng et al., proposes and proves a transformation theorem that the former can be converted to the latter within the constraints of their axiomatic definitions. The result offers a reference for the theoretical research and practical application in the future.
The Improved Equilibrium Optimization Algorithm with Averaged Candidates
Authors: Gao Zhengming , Zhao Juan , Tian Xuejun
Published: July 2020

In this paper, we proposed the improvement of the newly raised equilibrium optimization (EO) algorithm by hybridizing the grey wolf optimization (GWO) algorithm. Simulation experiments were carried out and results showed that the hybrid EO algorithm with averaged candidates would perform better than the original one. Considering the better results and the smooth convergence curve on different types of benchmark functions, we recommend to withdraw the concept of equilibrium pool in the construction of the EO algorithm henceforth, and keep the guiding equation relevant to the averaged concentration of four best candidates instead.
Development of a Vision Guided Robot for Grafting Watermelon Based on Hole Insertion Method
Authors: Liu Kai , Jiang Kai , Mu Yanqiu
Published: July 2020

The grafting success rate of existing grafting robots will be significantly affected by individual differences in seedling’s shape. To circumvent this problem, a vision guided robot consisting of a Denso manipulator, a scion cutting unit, a rootstock holding unit, a Cognex machine vision system, a control system, and an end effector was developed. The robot autonomously performed its grafting task using a machine vision to locate the punching target point and the tip of scion hypocotyl, and then control system regulated the manipulator to punch a hole on the rootstock stem and accurately insert the watermelon scion into the hole. The function experiment showed that the punching angle of pin used by robot was 60° and the maximum inserting speed should not exceed 25 mm/s. Grafting experiment results showed that For the seedlings with individual differences in seedling’s shape, the success rate of present grafting robot(95.6%) is higher than that (83%) of a early grafting robot (2JC-600B). It is obvious that vision guidance reduce the negative effect of individual differences in seedling’s shape on grafting success rate.
Transmission Line Wire Following System Based on Unmanned Aerial Vehicle 3D Lidar
Authors: Zhang Ying , Liao Ruchao , Wang Yong , Liao Jiandong , Yuan Xinxing , Kang Taizhong
Published: July 2020

UAV(Unmanned aerial vehicle) wire checking is an efficient and scientific solution of transmission line operations. Aiming at the existing technology, this paper put forward a kind of based on 3D laser radar and ROS (Robot Operating System) of the UAV wire follow System. In the process of power transmission line inspection of wire, the system capture the wire by 3D laser radar mounted on the UAV and calculate the space distance between UAV and the wire and angle of this distance in 3D laser radar coordinate axis, control drone aircraft by PID(Proportion Integration Differentiation) algorithm in the attitude of UAV and inspection speed by the ROS on the onboard computer system platform for real-time wire following and automatic inspection task. Field experiments show that the system can effectively improve the efficiency and safety of wire inspection, and is conducive to the automation, safety and informatization of transmission line inspection process.
Block H-matrices and Spectrum of Block Matrices
Authors: Gao Huishuang , Han Guichun , Sun Yanhong , Sun Fei , Ren Yuan
Published: July 2020

In this paper, we obtain a set of practical criteria of block H-matrices. At the same time, a range of eigenvalues is given for a kind of nonsingular block H-matrix.
An Attention-Based LSTM Model for Stock Price Trend Prediction Using Limit Order Books
Authors: Li Yunhao , Li Liuliu , Zhao Xudong , Ma Tianyi , Zou Ying , Chen Ming
Published: July 2020

Stock price trend prediction has been a hot issue in the financial field, which has been paid much attention by both academia and industry. It is a challenging task due to the non-stationary and high volatility of the stock prices. Traditional methods for predicting stock price trends are mostly based on the historical OHLC (i.e., open, high, low, and close prices) data. However, it eliminates most of the trading information. To address this problem, in this paper, another type of stock price data, i.e., limit order books (LOBs), is used. For better exploring the relationship of the LOBs and stock price trend, inspired by the successful application of deep learning-based methods, an attention-based LSTM model is applied. The trend of stock price can be predicted by using the LOBs data of the previous day. By using the real stock price data of the China stock market, the effectiveness of the proposed model is validated by experimental results.
Study on the Positioning Scheme of Charging Pile Based on Ibeacon
Authors: Luo Jinman , Fen Youjun , Liu Piao , Ye Ruijing
Published: July 2020

With its advantages of low power consumption, anti-interference and low cost, ibeacon can not only provide users with positioning services, but also well adapt to the market. Therefore, this paper mainly studies and discusses the positioning scheme based on the ibeacon charging pile. According to the RSSI value, the distance between the bluetooth base station and the undetermined position node is derived, and the weighted triangulation algorithm is used to locate the undetermined position node. Finally, the a-star algorithm is used to quickly plan the shortest path.
Research on Ways to Improve College Students’ Sense of Acquiring Ideological and Political Courses under the Background of Artificial Intelligence
Authors: Duan Yuanpeng , Wu Shuting
Published: July 2020

Under the background of artificial intelligence, to promote the reform and innovation of college students’ ideological and political theory courses (hereafter this text will be abbreviated as “ideological and political courses”) and enhance their sense of acquisition of ideological and political courses. Survey and interview techniques were used to conduct a survey of “the current situation of college students’ ideological and political course acquisition”with nearly 300 college students as survey samples. College students’ perceived acquisition of ideological and political courses has some problems, such as unsatisfactory attendance, less active participation in ideological and political courses, and poor quality of homework after ideological and political courses. The hidden acquisition of ideological and political courses for college students has some issues that college students’ knowledge of the communist party of China is not deep enough, and their will to learn ideological and political courses is not firm enough. There are some main problems in college students’ awareness of ideological and political course practice, such as the small number of times they participate in the teaching practice of ideological and political theory course and the low degree of combining ideological and political theory with practical activities. Under the background of artificial intelligence, the way to improve college students’ acquisition of ideological and political courses is: The unique teaching technology and teaching resources of artificial intelligence are used to assist in the design of integrated ideological and political courses, the establishment of teaching information resources for ideological and political courses, and the optimization of the teaching process of ideological and political courses.
The Course Reform of the Modern Control Theory and Method Based on the Unmanned Aerial Vehicle
Authors: Lei Xusheng , Ma Jun
Published: July 2020

Focusing on the problems of the low efficiency and poor practical ability in the course of the modern control theory and method, the unmanned aerial vehicle is introduced in the class room teaching of the modern control theory and method. Using the engineering practice as the entry point, the unmanned aerial vehicle has been involved into the course system construction, head and tail teaching, homework, and examination process. Therefore, abstract theories and formulas are closely combined with concrete engineering practice. The learning interest and enthusiasm of elective students are motivated, and the ability to analyze and solve problems are improved. Five years of teaching practice results show that the reform of teaching methods has achieved good results.
Robust and Accelerated Frequency-Tuned Salient Object Detection via Color Quantization
Authors: Huang Zhe , Guo Baolong , Wang Geng , Li Cheng , Wei Zhifei
Published: July 2020

Frequency-tuned (FT) saliency detector has been widely used in various image processing and computer vision applications. However, removing high frequency noise and textures by a Difference of Gaussians (DoG) filter is still time-consuming, which hinders real-time execution of FT. In this paper, an improved algorithm is proposed to tackle the obstacles to performance improvement. It exploits color quantization within natural images and substitute Gaussian filtering process. Experimental results demonstrate that the proposed method runs up to about two times as fast as FT while resulting in almost the same saliency map.
Application Research of Virtual Reality Technology in Design
Authors: Fan Hongbin , Jiang Weisheng
Published: July 2020

With the improvement of people’s living standards, virtual reality technology has been applied to different industries, its own interactive feature, real-time feature and scene feature, which make it widely used in the field of architecture. This paper applies virtual reality technology to interior design, users can experience immersive-artistic conception in the virtual scene. We introduce the concept of virtual reality, and analyze the relationship between virtual reality technology and interior design; we study several main technologies of virtual reality, which include VRML modeling for installing interior virtual scene, using X3D technology for scene expansion of virtual interior design, Web technology is used to share virtual scenes. In the process of interior design, we put VRML technology into realizing the initialization of virtual scene, then adopt X3D technology to simulate the virtual scene, and proofread the generated virtual scene based on VRML technology, in order to realize online experience of the virtual scene, we display the effect of virtual interior design in the web environment, so that users can interact with the virtual interior design scene. By a large number of experiments, we prove that X3D technology can be used for displaying the virtual scene space in many dimensions, and the virtual environment has good maintainability; with the help of online-virtual reality technology, users can modify the scene of interior design, move the objects of scene, so that users can optimize the design of space according to their own wishes.
Allometric Growth Patterns of Fine Scale Fish Larvae and Its Ecological Significance
Authors: Yang Guiqiang , Wang Zhanquan , He Jie , Li Wentong , Yuan Ding
Published: July 2020

Ecological experiment was conducted to study the allometric growth of fine scale fish yolk-sac larvae and its significance in adaptation in early life stage. The results indicated organs such as feeding, breathing and swimming of larvae in the yolk sac stage are rapidly differentiated, and all key organs are allomorphic. In all parts of the body, the head length, tail fin length and body height are growing at a positive allometric speed, the trunk is growing at a slow speed; in the head organs, the rostrum length, eye diameter and head length are growing at a positive allometric speed; in the swimming organs, tail fin length is positive allometric growth; yolk sac length, yolk sac width and yolk sac height are positive allometric growth consumption. The fast development of feeding, breathing, swimming and other organs in yolk-sac larvae of fine scale fish, increases larval survival ability at the early stage in the shortest possible time, and there were important ecological significance to adapt the complex and changing external environment.