Miracle-dz/UniFAR-FTUs huggingface dataset:
Learned Micro-Doppler Representations for Targets Classification Based on Spectrogram Images

This paper proposes a new approach for classifying ground moving targets captured by pulsed Doppler radar. Radar echo signals express the Doppler effect that moving targets produce. A learned feature representation extracted from spectrogram images using a transfer learning paradigm is proposed. A discrimination power analysis that derives highly discriminative features used to train a robust classifier was conducted. The extensive experiments performed on the public RadEch dataset show that the proposed method produces a significant boost in performance when compared to other state-of-the-art methods.
Triple-order Optimization for Performance Enhancement of Piezoelectric MEMS Resonator

Quality factor (Q) is an extremely important parameter for the practical applications of micro-electromechanical systems (MEMS) resonators. Single optimization is difficult to achieve the high-performance MEMS resonators. This paper reports a strategy of triple-order optimization for high-performance piezoelectric MEMS resonator by resonant body parallel connection, suspended frame structure and phononic crystals (PnC). Firstly, according to the Butterworth Van Dyke (BVD) equivalent circuit model, the topologies structure of resonator was comprehensively studied and the three resonant bodies parallel connection was proposed to lower the motional impedances, while the anchor loss will rise due to the number of tethers increased. Secondly, the suspended frame structure was utilized to reduce the number of tethers in parallel-type resonators to suppress the anchor loss. Thirdly, the PnC structure was proposed to further realize high-Q by preventing the leakage of acoustic energy from resonant body to substrate via tethers. Finally, the Q of the proposed resonator was obtained by using finite-element-analysis (FEA) simulation, which revealed a 3.3fold enhancement (i.e. Qu = 9318.0) compared with the conventional resonator (i.e. Qu= 2799.6). In the meantime, the motional resistance and insert loss have also been significantly optimized.
Development of a Neural Network-Based Control System for the DLR-HIT II Robot Hand Using Leap Motion

In this paper, a neural network (NN) based adaptive controller has been successfully developed for the teleoperation of a DLR-HIT II robot hand using Leap Motion sensor. To achieve this, the coordinate positions of the human hand fingers are captured by a Leap Motion sensor. Moreover, inverse kinematics is used to transform the Cartesian position data of the fingertips into corresponding joint angles of all the five fingers, which are then directly sent to teleoperate the DLR-HIT II hand via User Datagram Protocol (UDP). In addition, a NN-based control system programmed by the MATLAB Simulink function has been investigated to enhance the overall control performance by compensating the dynamic uncertainties existing in the teleoperation system. The stability of the control system has been proved mathematically using Lyapunov stability equations. A series of experiments have been conducted to test the performance of the proposed control technique, which has been proved to be an effective teleoperation strategy for the DLR-HIT II robot hand.
An efficient platform for generating somatic point mutations with germline transmission in the zebrafish by CRISPR / Cas 9-mediated gene editing

Homology-directed recombination (HDR)–mediated genome editing is a powerful approach for both basic functional study and disease modeling. Although some studies have reported HDR-mediated precise editing in nonrodent models, the efficiency of establishing pure mutant animal lines that carry specific amino acid substitutions remains low. Furthermore, because the efficiency of nonhomologous end joining (NHEJ)induced insertion and deletion (indel) mutations is normally much higher than that of HDR-induced point mutations, it is often difficult to identify the latter in the background of indel mutations. Using zebrafish as the model organism and Y box– binding protein 1 (Ybx1/ybx1) as the model molecule, we have established an efficient platform for precise CRISPR/Cas9-mediated gene editing in somatic cells, yielding an efficiency of up to 74% embryos. Moreover, we established a procedure for screening germline transmission of point mutations out of indel mutations even when germline transmission efficiency was low (<2%). To further improve germline transmission of HDR-induced point mutations, we optimized several key factors that may affect HDR efficiency, including the type of DNA donor, suppression of NHEJ, stimulation of HDR pathways, and use of Cas9 protein instead of mRNA. The optimized combination of these factors significantly increased the efficiency of germline transmission of point mutation up to 25%. In summary, we have developed an efficient procedure for creating point mutations and differentiating mutant individuals from those carrying knockouts of entire genes.
Heart Disease Detection by Using Machine Learning Algorithms and a Real-Time Cardiovascular Health Monitoring System

Cardiovascular diseases are the most common cause of death worldwide over the last few decades in the developed as well as underdeveloped and developing countries. Early detection of cardiac diseases and continuous supervision of clinicians can reduce the mortality rate. However, accurate detection of heart diseases in all cases and consultation of a patient for 24 hours by a doctor is not available since it requires more sapience, time and expertise. In this study, a tentative design of a cloud-based heart disease prediction system had been proposed to detect impending heart disease using Machine learning techniques. For the accurate detection of the heart disease, an efficient machine learning technique should be used which had been derived from a distinctive analysis among several machine learning algorithms in a Java Based Open Access Data Mining Platform, WEKA. The proposed algorithm was validated using two widely used open-access database, where 10-fold cross-validation is applied in order to analyze the performance of heart disease detection. An accuracy level of 97.53% accuracy was found from the SVM algorithm along with sensitivity and specificity of 97.50% and 94.94%respectively. Moreover, to monitor the heart disease patient round-the-clock by his/her caretaker/doctor, a real-time patient monitoring system was developed and presented using Arduino, capable of sensing some real-time parameters such as body temperature, blood pressure, humidity, heartbeat. The developed system can transmit the recorded data to a central server which are updated every 10 seconds. As a result, the doctors can visualize the patient’s real-time sensor data by using the application and start live video streaming if instant medication is required. Another important feature of the proposed system was that as soon as any real-time parameter of the patient exceeds the threshold, the prescribed doctor is notified at once through GSM technology.
Structural Basis for Reversible Phosphorolysis and Hydrolysis Reactions of 2O-- Glucosylglycerol Phosphorylase *

Kouki K. Touhara (東原幸起), Takanori Nihira (仁平高則), Motomitsu Kitaoka (北岡本光), Hiroyuki Nakai (中井博之), and Shinya Fushinobu (伏信進矢) From the Department of Biotechnology, University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo 113-8657, the Faculty of Agriculture, Niigata University, Niigata 950-2181, and the National Food Research Institute, National Agriculture and Food Research Organization, Tsukuba, Ibaraki 305-8642, Japan
Structural Analysis of the Catalytic Mechanism and Substrate Specificity of Anabaena Alkaline Invertase InvA Reveals a Novel Glucosidase*

Invertases catalyze the hydrolysis of sucrose to glucose and fructose, thereby playing a key role in primary metabolism and plant development. According to the optimum pH, invertases are classified into acid invertases (Ac-Invs) and alkaline/neutral invertases (A/N-Invs), which share no sequence homology. Compared with Ac-Invs that have been extensively studied, the structure and catalytic mechanism of A/N-Invs remain unknown. Here we report the crystal structures of Anabaena alkaline invertase InvA, which was proposed to be the ancestor of modern plant A/N-Invs. These structures are the first in the GH100 family. InvA exists as a hexamer in both crystal and solution. Each subunit consists of an (α/α)6 barrel core structure in addition to an insertion of three helices. A couple of structures in complex with the substrate or products enabled us to assign the subsites −1 and +1 specifically binding glucose and fructose, respectively. Structural comparison combined with enzymatic assays indicated that Asp-188 and Glu-414 are putative catalytic residues. Further analysis of the substrate binding pocket demonstrated that InvA possesses a stringent substrate specificity toward the α1,2-glycosidic bond of sucrose. Together, we suggest that InvA and homologs represent a novel family of glucosidases.
Cyclic AMP Inhibits the Activity and Promotes the Acetylation of Acetyl-CoA Synthetase through Competitive Binding to the ATP / AMP Pocket *

Xiaobiao Han (韩小彪), Liqiang Shen (申立强), Qijun Wang (王启军) , Xufeng Cen (岑旭峰), Jin Wang (王金), Meng Wu (吴萌)**, Peng Li (李鹏), Wei Zhao (赵维), Yu Zhang (张余), and Guoping Zhao (赵国屏) From the Key Laboratory of Synthetic Biology, Institute of Plant Physiology and Ecology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200032, China, the Key Laboratory of Synthetic Biology, Chinese Academy of Sciences Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200032, China, the Department of Medical Microbiology and Parasitology, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China, the **Shanghai Institute of Biochemistry and Cell Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China, the State Key Lab of Genetic Engineering & Institutes of Biomedical Sciences, Department of Microbiology and Microbial Engineering, School of Life Sciences, Fudan University, Shanghai 200433, China, the Shanghai-MOST Key Laboratory of Disease and Health Genomics, Chinese National Human Genome Center at Shanghai, Shanghai 201203, China, the Department of Microbiology and Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, New Territories, Hong Kong SAR, China, and the University of Chinese Academy of Sciences, Beijing 100049, China
Alkaline Response of a Halotolerant Alkaliphilic Halomonas Strain and Functional Diversity of Its Na+(K+)/H+ Antiporters*

Halomonas sp. Y2 is a halotolerant alkaliphilic strain from Na+-rich pulp mill wastewater with high alkalinity (pH >11.0). Transcriptome analysis of this isolate revealed this strain may use various transport systems for pH homeostasis. In particular, the genes encoding four putative Na+/H+ antiporters were differentially expressed upon acidic or alkaline conditions. Further evidence, from heterologous expression and mutant studies, suggested that Halomonas sp. Y2 employs its Na+/H+ antiporters in a labor division way to deal with saline and alkaline environments. Ha-NhaD2 displayed robust Na+(Li+) resistance and high transport activities in Escherichia coli; a ΔHa-nhaD2 mutant exhibited growth inhibition at high Na+(Li+) concentrations at pH values of 6.2, 8.0, and 10.0, suggesting its physiological role in osmotic homeostasis. In contrast, Ha-NhaD1 showed much weaker activities in ion exporting and pH homeostasis. Ha-Mrp displayed a combination of properties similar to those of Mrp transporters from some Bacillus alkaliphiles and neutrophiles. This conferred obvious Na+(Li+, K+) resistance in E. coli-deficient strains, as those ion transport spectra of some neutrophil Mrp antiporters. Conversely, similar to the Bacillus alkaliphiles, Ha-Mrp showed central roles in the pH homeostasis of Halomonas sp. Y2. An Ha-mrp-disrupted mutant was seriously inhibited by high concentrations of Na+(Li+, K+) but only under alkaline conditions. Ha-NhaP was determined to be a K+/H+ antiporter and shown to confer strong K+ resistance both at acidic and alkaline stresses.
Using Generative Adversarial Nets to Reduce Fingerprint Collection for Indoor Localization

WiFi positioning is currently the more mainstream indoor positioning method, and fingerprint database construction is crucial to WiFi-based localization systems. However, this approach requires enough fingerprint data for a single point. In this paper, we convert channel state information (CSI) data into amplitude feature maps to construct initial fingerprint library and then extend the fingerprint database using the proposed improved deep convolutional generative adversarial nets (IDCGAN) model. Finally, the amplitude feature maps are trained by the CNN to locate. Based on the extended fingerprint database, the accuracy of indoor localization systems can be improved with reduced human effort.
Number : Title : Purification , Characterization , Mode of Action and Enhanced Production of Salivaricin mmaye 1 , a Novel Bacteriocin from Lactobacillus salivarius

Background Emergence of antibiotic resistance among pathogenic and food spoilage bacteria such as Staphylococcus aureus, Micrococcus luteus, Streptococcus pyogenes, Streptococcus sanguinis, Streptococcus mutans, Bacillus cereus and Listeria monocytogenes triggered the search for alternative antimicrobials. An investigation aimed at purifying, characterizing, elucidating the mode of action and enhancing the production of salivaricin from Lactobacillus salivarius of human gut origin was conducted. Results Salivaricin mmaye1 is a novel bacteriocin purified from Lactobacillus salivarius isolated from human feces. It is potent at micromolar concentrations and has a molecular weight of 1221.074 Da as determined by MALDI-TOF mass spectrometry. It has a broad spectrum of antibacterial activity. Salivaricin mmaye1 possesses high thermal and chemical stability and displayed moderate pH stability. The proteinaceous nature of salivaricin mmaye1 was revealed by the complete loss of activity after treatment with pepsin, trypsin, α-chymotrypsin, protease and proteinase. Salivaricin mmaye1 is cell-wall associated and adsorption-desorption of the bacteriocin from the cell wall of the producer via pH modification proved successful. It exhibited a bactericidal mode of action mediated by pore formation. Its biosynthesis is regulated by a quorum sensing mechanism. Enhanced production of salivaricin mmaye1 was achieved in a newly developed growth medium. Conclusions Salivaricin mmaye1 is a novel, cell-wall associated, broad-spectrum, highly potent bacteriocin with a bactericidal mode of action exerted through pore formation. It is thermally and chemically stable and possesses moderate pH stability. Its synthesis is regulated via quorum sensing. Its production was enhanced in a newly developed growth medium. These findings pave the way for future evaluation for the medical and food applications using salivaricin mmaye1. Suggested Reviewers: John Tagg Ph.D Professor, Microbiology, University of Otago john.tagg@otago.ac. nz His expertise in the research of bacteriocins and publications on the subject is valuable. Sudesh Kumar Pillai Ph.D Professor, University of Science Malaysia ksudesh@usm.my Expertise on lactic acid bacteria and his wide publications Jeremy Burton Ph.D Assistant Professor, Department of Microbiology & Immunology, Western University , Western University, London, Ontario, Canada Jeremy.Burton@lawsonresearch.com Expertise on bacteriocins Paul Ross paul.ross@teagasc.ie Published work and expertise on bacteriocins George N. Bennett Bennett Professor, Biochemistry & Cell Biology, Rice University gbennett@rice.edu For his expertise in Microbial Biotechnology and he is a member of the Journal's Board of Editors.
Developing a Neural Machine Translation system for Irish

In this paper we develop a neural machine translation (NMT) system for translating from English into Irish and vice versa. We evaluate the performance of NMT on the resource-poor English-Irish (EN–GA) language pair, show that we can achieve good translation quality in comparison to previously reported systems, and outperform Google Translate TM with several BLEU points on a domain-specific test set related to the legal domain. We show that back-translation of monolingual data closely related to the domain of the test set can further increase the model’s performance. Finally, we present a lightweight method for filtering synthetic sentence pairs obtained via back-translation using a tool for misalignment detection. We show that our approach results in a slightly higher BLEU score while requiring less training data.
Novel Framework for Browser Compatibility Testing of a Web Application using Selenium

With a wide range of web browsers available, end users can use a variety of web browsers to access a web application. It is now become essential to review and compare website functionality and styles on multiple browser platforms. For different browsers requests may be handled and processed in a different manner based on the user agents received from the client browser. So just testing on a single browser may cause the application functionality to behave differently or incorrectly on another browser. You need to make sure that your web application works fine across multiple browsers. Compatibility testing is a non-functional testing in which the application is verified to run on different browsers, various resolution, various operating systems, etc. But testing across multiple browsers can become very time consuming and costly. In this paper, our focus will be on cross-browser testing which simply means to test a web application in multiple browsers, and making sure that it works consistently and as intended and does compromise in quality or features. The aim of this paper is to create a prototype framework for browser compatibility testing. It deals with automation testing for a web application on different web browsers using Selenium WebDriver. It briefly describes the tools and frameworks used for automation testing along with the advantages and disadvantages of automated testing with the focus on testing user interfaces of web-based applications to achieve high quality software.
Chapter 2 Food Webs and Graphs

The study of food webs has occurred over the last 50 years, generally by ecologists working in natural habitats with specific relatively narrow interests in mind. At the outset, a few mathematicians became interested in the graph-theoretic properties of food webs and their corresponding competition graphs; however, linkages between ecologists’, mathematicians’, and conservationists’ interests and results were few and far between. This chapter introduces food webs and various corresponding graphs and parameters to those interested in important research areas that link mathematics and ecology. A basic background on foodwebs and graphs is provided, with exercises to further illustrate the concepts. Each section has exercises which reinforce the newly introduced concepts. These exercises, sometimes open-ended, together with additional references to preliminary work may be used as springboards to numerous research questions presented in the chapter. Research questions accessible to biology and mathematics students of all levels, with references to previous work, are provided. We should note that all specific research questions are, at least in part, open questions, thus providing ample opportunities for student involvement with actual research. The citations accompanying each research question give more background and starting points for exploration. The main goals for this chapter are to provide the necessary background that will allow the reader to:
The Reader's Feeling and Text-based Emotions: The Relationship between Subjective Self-reports, Lexical Ratings, and Sentiment

In this study, we examined how precisely a sentiment analysis and a word list-based lexical analysis predict the emotional valence (as positive or negative emotional states) of 63 emotional short stories. Both the sentiment analysis and the word listbased analysis predicted subjective valence, which however was predicted even more precisely when both analysis methods were combined. These results can, for example, contribute to the development of new technology-based teaching designs, in that positive or negative emotions in the texts or online-contributions of students can be assessed in automated form and transferred into instructional measures. Such instructional actions can, for example, be hints, learning support or feedback adapted to the students’ emo-
Exploring the Implications of Artificial Intelligence in Various Aspects of Scholarly Peer Review

This doctoral work aims to explore the possible avenues in academic peer review where Artificial Intelligence (AI) could have a positive impact. Present day peer review is suffering from many shortcomings, foremost being that it is a very time-delayed process. We identify three potential factors: Novelty, Scope and Quality which are central to the theme of scholarly communication process and seek to investigate various techniques encompassing Natural Language Processing, Information Extraction and Retrieval, Data Mining, Bibliographic Analysis, etc. to address those. The objective is to develop an AI assisted decision support system for the editors, reviewers as well as the authors to get preliminary meta information about a prospective manuscript which may aid in decision making and hence speed-up the overall process. The project is challenging, vast and incorporates several features which closely resembles human behavior to identify quality and appropriate manuscripts. Initial set of experiments on curated and scholarly data show promising results. We are sure that there more issues to address, many scope of improvements which would eventually lead us one step closer to this ambitious vision: to cut through the clutter of bad literature and accelerate scientific discovery and eventually bring AI more close to the academic peer review system.
METHOD TO MIMIC ENVIRONMENT SHAPES AND COLORS USING FRACTAL THEORY

This paper presents a scientific solution for generating shapes and colors to mimic the environment. The replication model for the shapes and colors from the nature presented in this paper is based on using intelligent software programming solutions that are able to identify colors, shapes and their distribution from a set of digital images. The achieved replication model covers a broader range of spatial frequencies, which offers the advantage of using the same pattern for multiple observation ranges. The pattern and spatial frequencies of the shapes are generated so as to provide an accurate mimic for a defined range.
A 3 D Polarized Reversed Monte Carlo Radiative Transfer Model for mm and sub-mm Passive Remote Sensing in Cloudy Atmospheres

This paper introduces a 3D polarized radiative transfer model that has been developed to assess the influence of cirrus clouds on radiances measured by the EOS-MLS instrument. EOS-MLS is on the Aura satellite, which is due for launch in June 2004. The radiative transfer model uses a reversed Monte Carlo algorithm and has been incorporated in the ARTS 1.1. x software package. The model will be used to study aspects of the scattering problem that are not considered in the existing operational EOS-MLS cloudy-sky forward model, including the influence of non-spherical, oriented hydrometeors and 3D inhomogeneous cloud structure. This paper presents the radiative transfer algorithm and example model results, which demonstrate significant 3D and polarization effects. Although the development of this model was motivated by the EOS-MLS mission, it is also directly applicable to ground-based and downlooking geometries.