Miracle-dz/UniFAR-FTUs huggingface dataset:
Tolerance and accumulation of lead by fenugreek

In the present study, the response of fenugreek (Trigonella foenumgraceum L.) along with remediation potential was tested against lead (Pb). A pot trial was set up in order to evaluate remediation efficiency of T. foenumgraceum. Growth parameters and remediation potential of fenugreek against different concentrations of Pb was compared. Different physical parameters were studied. Biochemical parameters like chlorophyll content, soluble protein, total soluble sugar and proline were analyzed. The results showed that fenugreek accumulated Pb and translocated it in the harvestable parts of the plants. Metal accumulation increased consistently with increasing concentration of Pb in the treatments. Dry matter yield of plant increased with decreasing Pb concentration in the treatment. In conclusion, fenugreek can be used for remediation of Pb contaminated soil.
Lipid profile and quality of meat from finishing pig supplemented with minerals

Pork represents the largest source of animal protein consumed globally and the demand for this product grows each day (United States Department of Agriculture, 2018). However, consumers have become more demanding in relation to the quality of the pork and the inherent health benefits it can provide. To meet this demand, nutritional strategies applied during the animals’ production, arise as a tool to improve the meat quality characteristics, as well as to reduce the fat content, making it leaner and with a lipid profile better suited for consumption as recommended by the World Health Drganization (Food and Agriculture Drganization of United Nations, 2010).
Optical layer survivability: single service-class case

This paper considers capacity provisioning for service and restoration in a WDM optical network which provides lightpaths to higher layer networks. We develop a framework for jointly assigning wavelengths to service and restoration paths for all failures. For various types of path-based and link-based restoration methods, the problem is reduced to a vertex coloring problem in a single graph. Using this framework, we present routing and wavelength assignment algorithms for service and restoration with varying capacity/restoration time tradeoffs, and evaluate their performance through simulations. We also evaluate the difference in wavelength requirement under on-line incremental traffic and off-line traffic based on the properties of the conflict graph.
Medical Diagnosis Algorithm Based on Tongue Image on Mobile Device

inter-class variance method to binarize the original tongue image, and then use the mathematical morphology method to modify Abstract In traditional Chinese medical (TCM) science, tongue images can be observed for medical diagnosis; however, the tongue diagnosis of TCM is influenced by the subjective factors of doctors, and the diagnosis results vary from person to person. Quantitative TCM tongue diagnosis can improve the accuracy of diagnosis and increase the application value. In this paper, digital image processing and pattern recognition technologies are employed on mobile device to classify tongue images collected in different health states. First, through grayscale integral projection processing, the trough is found to localize the tongue body. Then the tongue body image is transferred from RGB color space to HSV color space, and the average H and S values are considered as the color features. Finally, the diagnosis results are obtained according to the relationship between the color characteristics and physical symptoms.
Epileptic Seizure Data Classification Using RBAs and Linear SVM

The objective of this paper is to make a distinction between EEG data of normal and epileptic subjects. Methods: The dataset is taken from 20-30 years healthy male/female subjects from EEG lab of Dept. of Neurology, Dr. RML Institute of Medical Sciences, Lucknow (India). The feature extraction has been done using the Hilbert Huang Transform (HHT) method. The experimental EEG signals have been decomposed till 5th level of Intrinsic Mode Function (IMF) followed by calculation of high order statistical values of each IMF. Relief algorithm (RBAs) is used for feature selection and classification is performed using Linear Support Vector Machine (Linear SVM). This paper gives an independent approach of classifying Epileptic EEG data with reduced computational cost and high accuracy. Our classification result shows sensitivity, specificity, selectiv­ity and accuracy of 96.4%, 79.16%, 84.3% and 88.5% respectively. The proposed method has been analyzed to be very effective in accurate classification of epileptic EEG data with high sensitivity.
Learning a deep l ∞ encoder for hashing

We investigate the l∞-constrained representation which demonstrates robustness to quantization errors, utilizing the tool of deep learning. Based on the Alternating Direction Method of Multipliers (ADMM), we formulate the original convex minimization problem as a feed-forward neural network, named Deep l∞ Encoder, by introducing the novel Bounded Linear Unit (BLU) neuron and modeling the Lagrange multipliers as network biases. Such a structural prior acts as an effective network regularization, and facilitates the model initialization. We then investigate the effective use of the proposed model in the application of hashing, by coupling the proposed encoders under a supervised pairwise loss, to develop a Deep Siamese l∞ Network, which can be optimized from end to end. Extensive experiments demonstrate the impressive performances of the proposed model. We also provide an in-depth analysis of its behaviors against the competitors.
Comparison of relift Luo converters for LED lighting purpose

This paper discusses the incorporation of relift Luo converters for vehicles’ front lighting purpose. As the technology is improved, there is an immediate need to improvise the efficiency and attractiveness of front lighting systems of the next generation automobiles. Therefore, the use of Light Emitting Diode (LED) lighting systems is highly recommended to facelift the luminance and its efficiency rather than conventional ways. In this work, we compared two relift Luo converters to choose a suitable topology for the above-mentioned application. All the modern equipment relies on power conditioning system to improve the efficiency and longevity of the system. Hence, it is required to analyze dc-dc converter topologies and its performance. Simulation of the relift circuits is carried out in Psim and the theoretical results are validated.
SVM- ased Audio Classification for Content- ased Multimedia Retrieval

Audio classification is very important in multimedia retrieval such as audio indexing, analysis and content-based video retrieval. In this paper, we have proposed a clip-based support vector machine (SVM) approach to classify audio signals into six classes, which are pure speech, music, silence, environmental sound, speech with music and speech with environmental sound. The classification results are then used to partition a video into homogeneous audio segments, which is used to analyze and retrieve its higher-level content. The experimental results show that the proposed system not only improves classification accuracy, but also performs better than the other classification systems using the decision tree (DT), K Nearest Neighbor (K-NN) and Neural Network (NN).
Cloud Computing: Technical Challenges and CloudSim Functionalities

The rapid development in internet era is continuous; big organizations and individuals are finding the means that can reduce their cost of communication, storage and computing. One of these, Cloud computing is an emerging technology that can deliver reliable, secure, fault-tolerant, sustainable, and scalable services. Cloud computing present's software, infrastructure, or platform as services (SaaS, IaaS, and PaaS). For example, instead of storing software applications and data locally on a personal computer, the software applications and data are stored on remote servers and accessed through a connection to the internet. The services offered by Cloud Computing over the Internet are rapidly changing the way we use computers. Companies that have built large data centers to offer these services include Microsoft, Amazon, Google, and Yahoo. In these days, More than 70 percent of 1000 companies will pay for some cloud computing service, and more than 20 percent of them will pay for cloud computing infrastructure. In this paper, we will discuss all aspects of cloud computing like concepts, definition, types, characteristics, benefits, and identify the top technical and non- technical challenges of cloud computing also focusing on CloudSim and its functionality in this field.
Anillin Stabilizes Membrane-cytoskeleton Interactions During Drosophila Male Germ Cell Cytokinesis

The scaffolding protein anillin plays a crucial role during cytokinesis – the physical separation of daughter cells following chromosome segregation. Anillin binds filamentous F-actin, nonmuscle myosin II and septins, and in cell culture models has been shown to restrict actomyosin contractility to the cleavage furrow. Whether anillin also serves this function during the incomplete cytokinesis that occurs in developing germ cells has remained unclear. Localization of anillin to several actin-rich structures in developing male germ cells also suggests potential roles for anillin outside of cytokinesis. In this study, I demonstrate that anillin is required for cytokinesis in dividing Drosophila spermatocytes. In addition, spermatid individualization is defective in anillin-depleted cells, although similarities to another cytokinesis mutant, four wheel drive, suggest this may be a secondary effect of failed cytokinesis. Anillin, septins and myosin II stably associate with the cleavage furrow in wild-type dividing spermatocytes. Anillin is necessary for recruitment of septins to the cleavage furrow, and for maintenance of Rho, F-actin and myosin II at the equator in late stages of cytokinesis. Membrane trafficking appears unaffected in anillin-depleted cells, although, unexpectedly, ectopic expression of one membrane trafficking marker, DE-cadherin-GFP, suppresses the cytokinesis defect. DE-cadherin-GFP recruits β-catenin (armadillo) and α-catenin to the cleavage furrow and stabilizes F-actin at the iii equator. Taken together, my results suggest that the anillin-septin and cadherin-catenin complexes can serve as alternative means to promote tight physical coupling of F-actin and myosin II to the cleavage furrow and successful completion of cytokinesis.
Applying Eye Tracking in Virtual Construction Environments to Improve Cognitive Data Collection and Human-Computer Interaction of Site Hazard Identification

– In the Architecture, Engineering and Construction (AEC) field, eye tracking technology is being applied more frequently in cognitive research such as hazard identification. These studies typically use eye tracking in a diagnostic way and pay less attention to the application of virtual environment. However, in virtual environment, eye tracking not only can enhance the study of the cognitive process but also improves the human-computer interaction. Therefore, this paper elaborates on how we use eye tracking devices to track 3D objects in virtual environments diagnostically and interactively. First, we analyze the existing research gaps of using eye tracking in the construction industry. Then, we follow 3D object identification, diagnostic mode and interactive mode to develop a methodology by HTC VIVE device with Pupil Labs HTC Vive Binocular Add-on based on the research gaps. Finally, an example experiment is provided to demonstrate studying hazard identification using eye tracking in construction safety. For analyzing the eye movement data from the participants, we offer the number of confirmations, the scan path and the 3D heatmap of objects in both static and dynamic construction site scenes. This paper provides an approach of applying eye tracking to gather more data in virtual environment for the future cognitive studies and explores the possibility to improve human-computer interaction using eye tracking in the construction industry.
How to Build a Web Scraper for Social Media

In recent years, the act of scraping websites for information has become increasingly relevant. However, along with this increase in interest, the internet has also grown substantially and advances and improvements to websites over the years have in fact made it more difficult to scrape. One key reason for this is that scrapers simply account for a significant portion of the traffic to many websites, and so developers often implement antiscraping measures along with the Robots Exclusion Protocol (robots.txt) to try to stymie this traffic. The popular use of dynamically loaded content – content which loads after user interaction – poses another problem for scrapers. In this paper, we have researched what kinds of issues commonly occur when scraping and crawling websites – more specifically when scraping social media – and how to solve them. In order to understand these issues better and to test solutions, a literature review was performed and design and creation methods were used to develop a prototype scraper using the frameworks Scrapy and Selenium. We found that automating interaction with dynamic elements worked best to solve the problem of dynamically loaded content. We also theorize that having an artificial random delay when scraping and randomizing intervals between each visit to a website would counteract some of the anti-scraping measures. Another, smaller aspect of our research was the legality and ethicality of scraping. Further thoughts and comments on potential solutions to other issues have also been included.
A customized precision format based on mantissa segmentation for accelerating sparse linear algebra

In this work, we pursue the idea of radically decoupling the floating point format used for arithmetic operations from the format used to store the data in memory. We complement this idea with a customized precision memory format derived by splitting the mantissa (significand) of standard IEEE formats into segments, such that values can be accessed faster if lower accuracy is acceptable. Combined with precision‐aware algorithms that dynamically adapt the data access accuracy to the numerical requirements, the customized precision memory format can render attractive runtime savings without impacting the memory footprint of the data or the accuracy of the final result. In an experimental analysis using the adaptive precision Jacobi method on diagonalizable test problems, we assess the benefits of the mantissa‐segmenting customized precision format on recent multi‐ and manycore architectures.
Activated Carbon Prepared from Rose Branch using H3PO4- hydrothermal Carbonization and Activation and its Apllication for Supercapacitors

Charcoals of rose branch were prepared by the three different carbonization treatments: phosphoric acid hydrothermal method, traditional hydrothermal method and pyrolysis. Then these charcoals were activated under the same conditions to obtain activated carbons. It is found phosphoric acid plays two major roles: (1) improving the specific surface area and the pore volume of the charcoals; (2) increasing the reactivity of the charcoals, making charcoals easier to be activated. Electrodes using activated carbons from different carbonization methods were prepared, and electrochemical measurements were performed with a three-electrode cell using 1 M Na 2 SO 4 as the electrolyte. Activated carbons prepared by conventional hydrothermal carbonization showed the lowest capacitance (137 F / g, at 0.2 A / g) and capacity retention (72.79%, at 2 A / g); while activated carbon prepared by phosphoric acid hydrothermal carbonization showed the highest specific capacitance (178 F / g, at 0.2 A / g) and capacity retention (91.01%, at 2 A / g).
Dynamic average modelling of renewable generation sources for real time simulation

The increase in microgrids and smart grid research comprising renewable generation sources with advanced grid control functionalities is driving the need for sophisticated simulation and hardware in the loop (HIL) test facilities using digital real time simulators (DRTS). Unlike traditional off line simulation tools, DRTS provides fast, continuous real time operation as well as hardware interfaces to test the operation of physical control, protection and power devices before they are installed in the smart/micro grid application. The available computation resources of the DRTS to achieve fast, continuous real time operation impose a limitation on the size and level of detail of the power system model for the simulation and HIL application. Reduced dynamic models that represent the power system and control dynamics with sufficient accuracy provide an acceptable trade-off between the required computation resources and size of the power system model for large simulation applications. This paper discusses the dynamic average modelling of renewable energy generation sources for real time simulation applications.
Recent advances in technologies for the removal of volatile methylsiloxanes: A case in biogas purification process

Abstract Volatile methylsiloxanes (VMS) exist as trace impurities in biogas and hamper the effective utilization of biogas. Various technologies, including adsorption, absorption, membrane separation and biological degradation, are used for the removal of VMS in biogas purification process. This work aims to summarize the recent advances of these technologies. Their advantages/disadvantages and factors that affect the removal efficiency of VMS are analyzed and discussed. Particular attention is paid to adsorption for its highest purification efficiency among the current VMS control technologies. Decrease of the adsorbed capacity under high humidity atmosphere and incomplete desorption are unavoidable conundrums at the present stage. The origination and influenced pathways of these issues are elaborated. Finally, research directions of these technologies for a further development are suggested to fulfill a high VMS removal efficiency and deep understanding of mechanisms.
Development of Decision-Making Support Systems to Design Chemical Process Equipment for Batch Production

It is impossible to create new and modernize the existing batch process production without the development of modern process equipment based on innovative technological processes. In this case, the decision-making system is a multi-level hierarchical system of interconnected local processes, which should be provided with information of various kinds, storing and processing the results of solving local problems, forming project documentation necessary for the manufacture of process equipment with minimal human participation, etc. To perform such functions, a decision support system (DSS) should be created, which accelerates decision-making processes, eliminates errors in the transfer of information between local design decision-making tasks, formalizes knowledge of the subject area, processes and stores them, reduces the number of design and technological enterprise services. The existing DSSs used in the development of process equipment have fundamental shortcomings, the main of which is the lack of decision-making capability using the knowledge of the subject area, which in practice is compensated by an increase in the number of design departments of enterprises. The scientific problem of creating a DSS is to develop a methodology based on information models of objects, assumptions, a large number of restrictions, principles, methods, algorithms, modern forms of information representation and processing, the application of which will increase the efficiency of the development process of devices (reducing development time, increasing productivity developer labor and reducing their number).
Sustainable Closed-Loop Supply Chaing Network Design

i ACKNOWLEDGEMENTS . ii DEDICATION . iii TABLE OF CONTENTS . iv LIST OF TABLES . viii LIST OF FIGURES . x CHAPTER ONE: INTRODUCTION . 1 1.1. Motivation and scope . 1 1.2. Supply Chain Management and Networks . 3 1.2. 1. Forward logistics . 4 1.2. 2. Reverse logistics . 4 1.2. 3. Closed-Loop logistics . 4 1.2. 4. Supply Chain Network Design . 5 1.2. 5. Sustainable supply chain network design . 5 1.3. Thesis Objectives and Outlines . 6 CHAPTER TWO: LITERATURE REVIEW . 9 2.
Design of a broadband high-efficiency Doherty power amplifier for 5G communication systems

In this paper, a novel load modulation network structure is proposed by connecting a shunt λ / 2 micro-strip line at the combiner of traditional DPA. And it can achieve wideband impedance transformation for the carrier power ampli ﬁ er. In this way, the performance of the DPA is improved in both bandwidth and back-o ﬀ point e ﬃ ciency. A broadband high-e ﬃ ciency Doherty power ampli ﬁ er (DPA) is designed and fabricated for 5G mobile communication. Measurement results show that the saturated output power of the DPA is above 43dBm in the range of 3.1 to 3.7GHz, and the saturated drain e ﬃ ciency is between 65% and 73.1%. Additionally, drain e ﬃ ciency of the 8dB power back-o ﬀ is above 40%. And better than − 45.6dBc adjacent leak power ratio (ACLR) can be achieved with Digital Pre-Distortion (DPD) under 10MHz LTE signal testing at 3.3GHz.
Current Ripple Simulation in DC Traction Voltage System of an Electric Bus: 2

Current ripple can cause a lot of problems as it spreads in the DC-side of the TVS of electric and electric hybrid vehicles. Fully knowing the properties of the TVS can be used to build a simulation model to determine the spreading of current ripple beforehand, which in turn is useful for calculating component placement, optimal filter sizes, and component lifetime. Being the second in line of an ongoing chain of thesis projects at Volvo buses, this master thesis proposes methods of measurement, simulation model adjustments, and usage of the finished model. Using an LCR meter, the impedance of several components was measured and modeled in LTSpice based on curve fitted parameters. Comparing the simulated properties to current and voltage levels measured in real vehicles, the accuracy of the models of different buses is presented and validated. (Less)
Links in science : linking network and bibliometric analyses in the study of research performance

The research described in this thesis aims to establish the use of detailed collaboration and citation analysis combined with other forms of bibliometric analysis as a tool enabling a better understanding of the organization of scientific communities and the way knowledge is spread inside scientific communities. In the study of collaboration networks the main goal is to identify existing research groups, potential research groups, and patterns of collaboration. The analysis of citations networks through specific measures and metrics, on the other hand, makes it possible to identify main lines of research through the years. Thus, such analyses improve our understanding of the growth and decline of fields, including phenomena such as paradigm shifts and emerging research themes. Network measures and metrics also allow for the identification of important nodes (e.g., journals, articles) embedded in the citation network.