Miracle-dz/UniFAR-FTUs huggingface dataset:
The anti-cancer activity and potential clinical application of rice bran extracts and fermentation products

Rice bran is the main by-product of rice processing and contains approximately 64% of the nutrients in rice. Its various nutrient elements include rice bran proteins, oil, oryzanol, vitamins, polysaccharides, etc. The use of fermented technology can increase the content of bioactive peptides, promote the absorption efficiency, and further improve the functionality and added value of rice bran. In recent years, the nutritional value and function of the extracts and fermented products of rice bran have been emphatically studied. Rice bran extracts and fermentation products serve a critical role in the anti-inflammatory reaction, reducing the plasma lipid effect and increasing anti-cancer activity. Moreover, few review studies have been reported on the anti-cancer activity and potential mechanism of action of rice bran extract and its fermentation products. In this review, we focused on the anti-cancer function, mechanisms, and potential clinical usage of rice bran extracts and fermentation products in the adjuvant therapy of cancer patients.
Microwave Enhanced Knoevenagel Condensation of Ethyl Cyanoacetate with Aldehydes

Abstract The reaction rate of Knoevenagel condensation can be dramatically enhanced by irradiating the reaction mixture containing ethyl cyanoacetate, an aldehyde, P2O5, piperidine, and chlorobenzene with a commercial microwave oven. A number of Knoevenagel condensation products were prepared in good yields in very short reaction times (2-15min) under the microwave irradiation.
Insight : interactive machine learning for complex graphics selection

Modern vector graphics editors support the creation of a wonderful variety of complex designs and artwork. Users produce highly realistic illustrations, stylized representational art, even nuanced data visualizations. In light of these complex graphics, selections, representations of sets of objects that users want to manipulate, become more complex as well. Direct manipulation tools that artists and designers find accessible and useful for editing graphics such as logos and icons do not have the same applicability in these more complex cases. Given that selection is the first step for nearly all editing in graphics, it is important to enable artists and designers to express these complex selections. This thesis explores the use of interactive machine learning techniques to improve direct selection interfaces. To investigate this approach, I created Insight, an interactive machine learning selection tool for making a relevant class of complex selections: visually similar objects. To make a selection, users iteratively provide examples of selection objects by clicking on them in the graphic. Insight infers a selection from the examples at each step, allowing users to quickly understand results of actions and reactively shape the complex selection. The interaction resembles the direct manipulation interactions artists and designers have found accessible, while helping express complex selections by inferring many parameter changes from simple actions. I evaluated Insight in a user study of digital designers and artists, finding that Insight enabled users to effectively and easily make complex selections not supported by state-of-the-art vector graphics editors. My results contribute to existing work by both indicating a useful approach for providing complex representation access to artists and designers, and showing a new application for interactive machine learning. Thesis Supervisor: Dr. Mitchel Resnick Title: LEGO Papert Professor of Learning Research
Overview on vision-based 3D reconstruction

As an developing technology,vision-based 3D reconstruction still got limitations in many aspects.Overviewed the main methods and relative study status of vision-based 3D reconstruction,and analyzed the advantages and disadvantages of these methods,hope to get a general understanding of this field and future indicate the study orientations in the future.
Benefits and Challenges of the Adoption of Cloud Computing in Business

The loss of business and downturn of economics almost occur every day. Thus technology is needed in every organization. Cloud computing has played a major role in solving the inefficiencies problem in organizations and increase the growth of business thus help the organizations to stay competitive. It is required to improve and automate the traditional ways of doing business. Cloud computing has been considered as an innovative way to improve business. Overall, cloud computing enables the organizations to manage their business efficiently. Unnecessary procedural, administrative, hardware and software costs in organizations expenses are avoided using cloud computing. Although cloud computing can provide advantages but it does not mean that there are no drawbacks. Security has become the major concern in cloud and cloud attacks too. Business organizations need to be alert against the attacks to their cloud storage. Benefits and drawbacks of cloud computing in business will be explored in this paper. Some solutions also provided in this paper to overcome the drawbacks. The method has been used is secondary research, that is collecting data from published journal papers and conference papers.
Concurrency Control of Transactions in Embedded Real-time Databases

Besides protecting database consistency, the objects of concurrency control mechanisms in embedded real-time databases should take transactions’ timing constraints and reducing the overheads resolving data conflicts into consideration. In the paper, a modified high priority abort protocol ACA-HPA-CA for embedded real-time transactions is discussed, including its formal description, lock compatible matrix, lock table structure and locking operations algorithms. The suggested protocol can avoid the “circle abort” and “useless abort” and has been applied successfully to an embedded real-time main memory database system ARTs-EDB developed by ourselves.
Synthesis and Characterization of Imidazole Derivatives and Catalysis Using Chemical Pharmaceutical Compounds

--- This review is an updated and expanded version of imidazole represent an important class of heterocycles, which contains two hetero (nitrogen) atoms and two double bonds. There are so many compounds which contain Imidazole ring and exhibit different types of pharmacological and biological activities such as antimicrobial, antitumor, antiepileptic, and antihistaminic, anti oxidative, anti-inflammatory, anti diarrhoeal, analgesic, which has caused an excessive use of drugs.
THE OUTER SHOCK OF THE OXYGEN-RICH SUPERNOVA REMNANT G292.0+1.8: EVIDENCE FOR THE INTERACTION WITH THE STELLAR WINDS FROM ITS MASSIVE PROGENITOR

We study the outer-shock structure of the oxygen-rich supernova remnant G292.0+1.8 using a deep observation with the Chandra X-ray Observatory. We measure radial variations of the electron temperature and emission measure that we identify as the outer shock propagating into a medium with a radially decreasing density profile. The inferred ambient density structure is consistent with models for the circumstellar wind of a massive progenitor star rather than for a uniform interstellar medium. The estimated wind density (nH = 0.1–0.3 cm−3) at the current outer radius (∼ 7.7 pc) of the remnant is consistent with a slow wind from a red supergiant (RSG) star. The total mass of the wind is estimated to be ∼15–40 M☉ (depending on the estimated density range), assuming that the wind extended down to near the surface of the progenitor. The overall kinematics of G292.0+1.8 are consistent with the remnant expanding through the RSG wind.
Research of object tracking based on CamShift algorithm

Considering the actual application of indoor mobile robot on object tracking,an improved algorithm of CamShift tracking combined with SIFT matching is proposed in this paper.By using CamShift algorithm to track the moving object,and in the meanwhile extracting and matching feature points for part of the object based on SIFT algorithm,the 2D coordinates of each matching conjugate points are acquired.With these coordinates,the object's location based on parallax principle is obtained.The experimental results show that this algorithm can track the moving target well in the scene with simple background,and the error is among the acceptable range.
A Compact Triangular Slot Array Multiband Antenna for Wireless Applications

A novel compact triangular slot array multi-broadband planar antenna is proposed for mobile handsets in the paper. The antenna has an inverted triangle structure radiator with fourteen units triangular slot array and coplanar waveguide (CPW) feed structure. The antenna can cover more than ten mobile applications in three broad-bands with -10dB bandwidth of 69.57% (0.613-1.267GH) for UHF (606-806MHz), GSM900 (880-960MHz), LTE44 (703-803MHz), CDMA2000 (825-880,885-960MHz), 30.17% (1.97-2.67GHz) for DCS1800 (1710-1880MHz),TD-SCDMA (1880-2025MHz,2300-2400MHz), WCDMA (1920-2170MHz,1755-1880MHz), LTE33-41 (1900-2690MHz), Bluetooth, GPS, COMPASS, GLONSS, GALILEO, WLAN (802.11b/g/n:2.4-2.48GHz), and 31.17%(4.17-5.71GHz) for WLAN (802.11a/n:5.15-5.35GHz) wireless applications. The antenna is fabricated on a 1.6 mm-thick FR4 substrate with dielectric constant of 4.4, and the size is 60*55mm2. The good agreement between the measurement results and the simulation validates the proposed design approach and meets the requirements for various wireless applications.
"Social" Science Gateways to e-Infrastructures

Notwithstanding the existence of a large and highly-performant computing infrastructure, and the effort made to improve the quality of these e-Infrastructures, the user base has remained quite small relative to the potential number of users. On the other hand Social Networks (SNs) have become extremely popular, thanks in large part to their intuitive and easy-to-use interfaces. Recognising the potential to improve the overall usability of e-Infrastructures, recently, a significant effort has been made to develop e-Collaboration environments allowing scientists to access remote computing facilities, referred as “Science Gateways” (SG).
Learning from sequential data for anomaly detection

Anomaly detection has been used in a wide range of real world problems and has received significant attention in a number of research fields over the last decades. Anomaly detection attempts to identify events, activities, or observations which are measurably different than an expected behavior or pattern present in a dataset. This thesis focuses on a specific set of techniques targeting the detection of anomalous behavior in a discrete, symbolic, and sequential dataset. Since profiling complex sequential data is still an open problem in anomaly detection, and given that the rate of production of sequential data in fields ranging from finance to homeland security is exploding, there is a pressing need to develop effective detection algorithms that can handle patterns in sequential information flows. In this thesis, we address context-aware multi-class anomaly detection as applied to discrete sequences and develop a context learning approach using an unsupervised learning paradigm. We begin the anomaly detection process by applying our approach to differentiate normal behavior classes (contexts) before attempting to model normal behavior. This approach leads to stronger learning on each class by taking advantage of the power of advanced models to identify normal behavior of the sequence classes. We evaluate our discrete sequence-based anomaly detection framework using two illustrative applications: 1) System call intrusion detection and 2) Crowd anomaly
Design a Slot-Less Linear Actuator for Food Processing Application

This paper is about design of slot-less linear oscillatory actuator for food processing application. Linear actuator is a device that produces linear motion without using any mechanical. People are still using traditional or conventional compression method by pressing hand in the moulding device to process the traditional cookies such as samperit and tart. However, this method is no longer practical as it requires a lot of energy and longer time to press the dough which will affect the productivity. The main objective of this research is to design slotless linear actuator for food processing based on desired application. So, a power moulding device embedded with slot-less linear actuator is proposed and simulated using Ansys Maxwell software. In Ansys Maxwell, the analysis of the coil sizing has been carried out in details. The variable parameters that include in this project are number of coil, number of turns, height of coil and gap between coils. As a result, the best model of slot-less linear actuator is chosen based on the required specifications and thrust characteristic. This new device can help to overcome or solve the weaknesses of the conventional compression method. In conclusion, this research provides overview and guidelines of linear actuator for food processing.
Software-Defined Network (SDN) Problem Statement and Use Cases for Data Center Applications

Software Defined Network (SDN) is an overlay architecture that presents the underlying transport network to the applications and services for monitoring, and provisioning at abstraction level. In this memo, we outline some of the problems, and present an architecture outline. We will present a few applications to validate the problems and the architecture framework.
3D reconstruction of medical image based on VTK

A 3D reconstruction system is developed with VTK and MC algorithm.Since rendering or storage cost of object is proportional to the number of triangles in mesh,too complex and detailed model will cause system overloaded in storage, transmission,computing and real-time rendering of mesh.Merging vertexes can reduce the number of triangles in mesh.
A Survey of Cable-Suspended Parallel Robots and their Applications in Architecture and Construction

Serial, aerial and solid-linked parallel robots are unable to handle large payloads in building-scale workspaces for on-site applications and are thus best suited for automated fabrication in plant settings. In contrast, Cable Suspended Parallel Robots or CSPRs are able to handle large loads and traverse great distances as required on building construction sites. This paper reviews the existing literature and practice to bridge the gap between our understanding of CSPRs and their applicability to building-scale tasks such as full-scale concrete printing and building façade installation. The research identifies key activities in CSPRs fabrication workflows. Using a comparative approach, the paper investigates five CSPR variants and assesses the performance characteristics. A simple kinematic model of each CSPR is developed and implemented as a Rhino/Grasshopper script to aid in the performance assessment of each system. The paper concludes with a ranking of CSPR systems and their likely applicability to full-scale implementation on a construction site.
Research and Implementation of MD5 Brute-force Cracking Algorithm based on CUDA

CUDA( Compute Unified Device Architecture) is a popular research and application field in parallel computing. And a major challenge is how to refractor parallel program and maximize the crack speed. With the single-machine single-card and single-machine multi-card experimental environment platform built up previously,a series of parallel crypto algorithm are designed. On the other hand,the existing researches and implementions are mostly based on the single-machine single-card or single- machine multi-card mode. This paper proposes a general platform of GPU cluster for brute-force cracking,and on this platform a series of experiments are done,thus to evaluate the robustness and effectiveness in brute-force cracking of MDS algorithm. In addition,the experiments on this general platform could provide certain foundation for future design of crypto-analysis algorithm and enhancement of algorithm performance.
Research of Web log data preprocessing based on collaborative filtering

Collaborative filtering is one of the most successful applications in the field of personalized service.The Web log can provide personalized service technology with important data resource.And the validity of collaborative filtering algorithm and the quality of personalized service will be improved as long as the effective preprocessing to log data has been done.On the foundation of dealing with material log data,it gives a structure figure and a method of data preprocessing based on collaborative filtering.This method can not only provide cleaner and more regular data source but also make up the defects of former interests measurement in the aspect of user's interests measurement,which provides a more precious sustainment for collaborative filtering algorithm.
A R Adaptive Multiple Importance Sampling (ARAMIS)

ARAMIS is an R package that runs the AMIS [1] algorithm. The main features of ARAMIS are parallelization and customization. ARAMIS exploits the massively parallel structure of AMIS to improve the performance of the algorithm as it was implemented in the original paper. As a result simulation time is reduced by orders of magnitudes. As for customization, the potential of the R language is fully exploited by ARAMIS which allows the user to taylor the software to the model which results from his or her own research setting. Target and proposal kernel can be easily specied by the user. Some working examples contained in the manual explain how this can be eciently and easily done. As a consequence of the exibility and eciency of the package, even fairly complicated problems can be accommodated, e.g. sampling from an Extreme Value (EV) Copula distribution with a mixture of EV distributions as the proposal kernel. The latter is an interesting and useful example of how the user can specify some \real-world" combination of target/proposal and it is added, in the manual, to the two working examples detailed in [1].
Coh-Metrix: An automated tool for theoretical and applied natural language processing

Coh-Metrix provides indices for the characteristics of texts on multiple levels of analysis, including word characteristics, sentence characteristics, and the discourse relationships between ideas in text. Coh-Metrix was developed to provide a wide range of indices within one tool. This chapter describes Coh-Metrix and studies that have been conducted validating the Coh-Metrix indices. Coh-Metrix can be used to better understand differences between texts and to explore the extent to which linguistic and discourse features successfully distinguish between text types. Coh-Metrix can also be used to develop and improve natural language processing approaches. We also describe the Coh-Metrix Text Easability Component Scores, which provide a picture of text ease (and hence potential challenges). The Text Easability components provided by Coh-Metrix go beyond traditional readability measures by providing metrics of text characteristics on multiple levels of language and discourse. DOI: 10.4018/978-1-60960-741-8.ch011
Automated Business Rules Harvesting using Semantic Technology

We aim to present an approach that can be used for the automated identification and extraction of the business rules with the help of using semantic technology. In typical BRMS, keyword based search is used to extract required business rules from rule base. However, we aim to incorporate semantic based search for retrieving business rules according to the contextual meaning and identify context of search, location, variation of words, and synonyms. In business rules, it is defined that the constraints and rules control the behavior of the business for achieving the goal of any organization. One can apply business rules in the form of constraints, definition and operations. All the strategies and directions tell the business rules that what organization should do and how to focus on a particular business activity. In Business Management controlled all the work like saving, defining, updating, retrieving, and deleting the rules. No support available still that give us accuracy of matching of word, location, intent, variation of words, synonyms, concept matching to provide relevant search result. Limitations of simple search have some issues when result is published after a query. Most popular techniques are called stemming but it has some draw backs because it focuses on the root word not the meaning. In semantic based search, a search is improved by improving accuracy by searching according to the contextual meaning.
Word Play What Happens When People Talk

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Face Contour Extraction and Tracking Using Level Sets

In this paper, a novel method using level set technique for face contour extraction and tracking in image sequences with simple backgrounds is proposed. Firstly the motion boundary is quickly detected via interframe image difference. After appropriate thresholding and morphological operations, the possible face region is then found out according to heuristic rules in face profile projections. Using the detected possible face region rectangle as the initial evolving curve, the accurate face contour is extracted using a modified level set model. Assuming that the face is always moving in image sequences, a first order Kalman filter is then used for motion estimation. Thus the face contour can be tracked with the same level set model in the following image frames. The experimental results show the efficiency of our method.
A Proof of the Axion

We show that the de Sitter quantum breaking bound when applied to QCD exposes the necessity of the axion solution to the strong CP problem. The Peccei-Quinn mechanism emerges as a consistency requirement independent of the naturalness questions. The $\theta$-angle must be unphysical rather than simply small. All other approaches including a fine-tuning of $\theta$ lead to the existence of de Sitter vacua and are excluded by consistency.