Miracle-dz/UniFAR-FTUs huggingface dataset:
Generation of Fixed-position Foci with Generalized Fibonacci Class Zone Plate

In this paper the generalized Fibonacci class zone plates with varying structural parameters are proposed to generate the fixed-position foci. Unlike the generalized Fibonacci and modified Thue-Morse zone plates, the proposed zone plate can generate more subsidiary foci and the construction method is applicable to many kinds of bi-focal zone plates. The construction method of the proposed zone plate is illustrated and the focusing property of the proposed zone plate has been verified with simulations. The Fibonacci, Thue-Morse, mbonacci and precious mean sequences are the common bi-focal sequences. It was proved in the simulation that the position of one of the foci of a generalized Fibonacci class zone plate based on the common bi-focal sequence can be kept constant when the structural parameters change and the generalized Fibonacci class zone plates based on the common bi-focal sequences can generate more subsidiary foci along the optic axis, and the position of one of two main foci can be kept constant for two different generalized Fibonacci class zone plates based on the arbitraryorder common bi-focal sequences. The proposed zone plates can be applied to trap particles at the designated plane and generate a clearer image at the described position along the optic axis.
Extraction of Significant lexical Associations to Classify the Essential Perspectives for Text Summarization

In this paper, a text summarization algorithm is proposed based on classifying the essential perspectives in texts. The algorithm is concerned with extracting significant lexical associations as the features for classification. Experimental results show that these features are enough to classify a number of pre-defined perspectives with a high frequency. In order to determine the related perspective, flow of consecutive sentences was shown to be most necessary.
Design of Vehicle Detection System based on Magnetic Sensor

In order to solve the problems of traditional vehicle detection technology, such as complicated installation and wiring, maintenance difficulties and high cost, the thesis design a vehicle detection system based on geomagnetic sensor that can detect the vehicles speed and implement traffic flow statistic. The system consists of vehicle detection nodes, the master node, and upper computer, the vehicle detection nodes mainly uses STM8L SCM with the geomagnetic sensor and the 433MHz wireless transceiver module. Test results show that the system possesses small size, low cost and high performance, and can actually be applied to outdoor parking spaces detection.
J ul 2 01 8 Probability measure-valued polynomial diffusions

We introduce a class of probability measure-valued diffusions, coined polynomial, of which the well-known Fleming–Viot process is a particular example. The defining property of finite dimensional polynomial processes considered by Cuchiero et al. (2012); Filipović and Larsson (2016) is transferred to this infinite dimensional setting. This leads to a representation of conditional marginal moments via a finite dimensional linear PDE, whose spatial dimension corresponds to the degree of the moment. As a result, the tractability of finite dimensional polynomial processes are preserved in this setting. We also obtain a representation of the corresponding extended generators, and prove well-posedness of the associated martingale problems. In particular, uniqueness is obtained from the duality relationship with the PDEs mentioned above.
The macro-determinants of private equity investment : a European comparison ∗

A strong private equity market is a cornerstone for commercialization and innovation in modern economies. However, substantial differences exist in the relative amounts raised and invested in private equity across European countries. We investigate the macro-determinants of private equity investment in Europe, focusing on the comparison between CEE and Western European countries. Our estimations are based on a data set running from 2001 to 2008 and covers 14 Western European and three CEE countries. Applying robust estimation techniques we identify a ’robust’ set of determinants of private equity activity in both regions. We find similarities as well as differences in the driving forces of private equity investments in Western European and CEE countries. Our results suggest that commercial bank lending, equity market capitalization, unit labour costs and corporate tax rates are significant determinants of private equity activity. JEL classification: C23, C52, E22, G24
Evaluation of SERS Nanoparticles to Detect Bacillus cereus and Bacillus thuringiensis

Bacillus cereus, Bacillus anthracis, Bacillus mycoides, Bacillus pseudomycoides, Bacillus thuringiensis, and Bacillus weihenstephanensis are six Bacillus species that have been identified as agents of foodborne illness (Ankolekar et al., 2009). B. cereus is a gram positive, spore-forming, and facultative anaerobic bacterium found in soil, contaminated irrigation water, fresh raw vegetables, and cooked rice (Organji et al., 2015). Infection due to B. cereus may result in diarrheal and emetic syndromes, depending on the degree of expression of the enterotoxin gene (Li et al., 2016). B. thuringiensis is a spore-forming bacterium and is closely related to B. cereus. Unlike B. cereus, B. thuringiensis has parasporal crystal bodies that are encoded by the cry genes (Vilas-Bôas et al., 2007). Worldwide outbreaks of foodborne illness due to B. cereus have been associated with the consumption of raw produce, including beans, cress, and mustard bean sprouts (Burnett and Beuchat, 2001). In particular, perishable agricultural products subject to short time frames for distribution and consumption can be contaminated with pathogenic Bacillus species, resulting in potential foodborne illness for consumers. Although outbreaks in the United States are considered underreported, approximately 1% of bacterial outbreaks in the United States in 2015 were confirmed to be caused by Evaluation of SERS Nanoparticles to Detect Bacillus cereus and Bacillus thuringiensis
Topic Modeling and Network Visualization to Explore Patient Experiences

—Online support groups and health-related social networking sites can be powerful ways for patients to connect with each other and seek ways to improve their health. This content can also help clinicians and scientists understand patient experience and unmet needs. However, it can be difficult to navigate and make sense of the large volume of content. This paper proposes and demonstrates techniques that may be used to visualize topics in online health discussions. Topic modeling in conjunction with network visualization can effectively provide overviews and segmenting data. Decisions made during this process affect how content is represented and therefore, interpreted. We present a case study of a lightweight approach to model health discussion content from PatientsLikeMe using open source tools. Implications of differing representations, possibilities for extending this approach, and potential use scenarios are discussed.
USED BY FARMERS IN SOUTH-EASTERN POLAND

The aim of the study was to evaluate the use of agri-environment schemes in the years 2004-2006 and 2007-2013 by farmers south-eastern Poland. In this region are more implemented these packages sciences, which are less onerous. Most of the agri-environmental programs implemented by farmers, puts great emphasis on the conservation and preservation of the rural landscape. Agri-environmental program increased environmental awareness among farmers who implement it and helps to inhibit the development of intensive agriculture. Simplification of the documentation related to the agri-environmental program, may affect the increase in the number of new farmers willing to implement these programs. In south-eastern region of Poland, the natural packages are realized more willingly, and receiving payments is the main incentive that convinces farmers to join agri-environment program. Implementing the agri-environmental program on farms in this region of Poland contributed both to improvement of water quality, reduction of soil erosion on a farm, and on the other hand to reduction of the livestock population. Increased employment of agri-environment advisor, especially botanists and ornithologists, would facilitate farmer participation in environmental programs.
Study The Effect of Thiadiazole and Thiazine Derivatives as Antiatherogenic and Antioxidant Agents in Induced Hyperlipidemic Mice

This study conducted to examine the effect of two newly synthesized compounds[3-(5-(ethylthio)-1,3,4-thiadiazol-2-yl)-2,3dihydro-2-(3-nitrophenyl)benzo[1-3-e] thiazin-4-one (compound I) and 5(4-dimethyl amino) benzylidene amino)-1,3,4-thiadiazole-2thiol(compound II)] as antiatherogenic and antioxidant agents, In vivo study. The study was carried out on sixty male Wister mice aged seven to eight weeks their weight ranged(180-200 g). The mice were grouped as: group(1)(G1): control group (20 mice). Group(2)(G2):consisted of 40 mice in which the mice were daily administered cholesterol (25mg/kg/day) in coconut oil 6% and creamy cheese for 28 days. Lipid profile (total cholesterol (Tch), triglyceride (TG), high density lipoprotein cholesterol (HDL-c), low density lipoprotein cholesterol (LDL-c) and very low density lipoprotein cholesterol VLDL-c), was measured for 12 of mice chosen randomely from G2 to assure hyperlipidemia. Then group2 (G2) subdivided into two groups: group (2.A): (14 mice) which the mice were daily treated with (10 -4 )M of compound (I)via drinking water for 20 days. Group(2.B):(14 mice) which the mice were daily treated with (10 -5 )M of compound II via drinking water for 20 days. Lipid profile, catalase, total oxidative status (TOS), total antioxdant status (TAS) , and atherogenic index of plasma (AIP) were determined in all studied groups. The results showed significant Study The Effect of Thiadiazole and Thiazine Derivatives as Antiatherogenic and Antioxidant Agents in Induced Hyperlipidemic Mice. Tamara A. Alubaidi 12 12 1122 2 elevation in levels of Tch, TG, LDL and VLDL, while there are significant reduction in HDL-c levels in G2 comparing to G1. After orally administration of compounds I and II from the mice, the results revealed that the levels of Tch, TG, LDL and VLDL were reduced while the levels of HDL-c was elevated. Catalase activity showed significant decrease in G2 when compared with G1. Also, a significant elevation was found in AIP, TOS and TAS in G2 when comparing to G1. Also, significant elevation was noticed in catalase activity after administration of compounds I and II, in addition to reduction in levels of AIP, TOS, and TAS. The conclusion could be drawn from this study that compounds I and II could be considered as antiatherogenic and antioxidant agents.
Localization using Pre-existing Satellite Imagery

We present a method for localization of Unmanned Aerial Vehicles (UAVs) which is meant to replace an onboard GPS system in the event of a noisy or unreliable GPS signal. Our method requires only a downward-facing monocular RGB camera on the UAV, and pre-existing satellite imagery of the flight location to which the UAV imagery is compared and aligned. To overcome differences in the image capturing conditions between the satellite and UAV, such as seasonal and perspective changes, we propose the use of Convolutional Neural Network (CNN) representations trained on readily available satellite data. To increase localization accuracy, we also develop an optimization which jointly minimizes the error between adjacent UAV frames as well as the satellite map. We demonstrate how our method improves on recent systems from literature by achieving greater performance in flight environments with very few landmarks. For a GPS-denied flight at 0.2km altitude, over a flight distance of 0.85km, we achieve average localization error of less than 8 meters. We make our source code and datasets available to encourage further work on this emerging topic.
The abundance and size of giant sea anemones at different depths in the waters of Teluk Tamiang village, south Kalimantan, Indonesia

The depth of waters has a close correlation with intensity of sunlight and waters’ temperature. The deeper the waters from the surface, the less light intensity be received. As a result, temperature also decreases at the deeper layer. This certainly gives effect on the abundance and the body size of giant sea anemones. The purpose of this study is to find out the relationship of the depth of waters to the distribution of abundance and body size of the giant sea anemones in the waters of Teluk Tamiang village, south Kalimantan, Indonesia. Study sites were divided into five stations: three stations in the western part of the waters and two stations in the eastern part of the waters of Teluk Tamiang. Each station was subdivided into three depths: 0-2 m, > 2-4 m, and > 4-6 m. Data of relative abundance and body size of giant sea anemones at different depths were analyzed using Kruskal Wallis test. Distribution of abundance and body size of giant sea anemones based on depths was analyzed using Correspondence Analysis. The results showed that there were three species of giant sea anemones found, namely Stichodactyla gigantea, Entacmaea quadricolor and Heteractis crispa. The abundance and body size of S. gigantea were higher than those of E. quadricolor and H. crispa. However, the distribution of abundance and body size anemones had no significant difference among the depths of waters.
Technological capability and industry catch-up in new digital sectors : The evidence from China ’ s digital games industry

How do latecomers compete with incumbents in emerging digital industries and what innovative capabilities they build to succeed? The convergence of digital technologies across different disciplines has accelerated technological change. Yet existing catch-up literature is not sufficient to explain how latecomers from emerging economies with lagging digital technologies have caught up. Drawing on the case study of China's digital games industry, we derive a model of capability development, which is related to the conditions of the establishment of latecomers’ capability, the relationship with the institutional settings in which they are embedded, and the successful catch-up strategy. Our research provides three contributions. We reveal that digital emerging industries create opportunities for the alternative capability development of these latecomers to gradually catch up with advanced incumbents; we show that how latecomers in emerging countries transfer prior sector experiences and skills to compensate for their disadvantaged initial conditions and leverage the cross-industry alliance strategy for successful market entry; and we identify the role of institutions in the development of new digital industries.
Nonlinear mean-reversion in the real exchange rate: evidence from a panel of OECD countries

We examine the presence of mean-reversion in the real exchange rates of a panel of 20 OECD using the standard Dickey-Fuller test and smooth transition autoregression (STAR) framework. Our results provide strong support for the long run empirical validity of the purchasing power parity in most all major industrial countries. Our findings attribute the nonlinear stationarity of the real exchange rates to certain nonlinearities in the short run adjustment paths of these rates. Such nonlinearities in the adjustment process may arise by more aggressive market reaction and government intervention when its departure from equilibrium is more drastic.
The cellular pipelined algorithm architecture for 1 D diffusion simulation using residue number system

This paper is oriented to the cellular pipelined algorithm architecture for the 1D diffusion simulation. The finite difference representation of 1D diffusion is written in terms of the residue number system. The cellular pipelined algorithm architectures for the main operations with a minimum period are developed. The parallel Substitution Algorithm is used for the algorithm design and modeling. The time complexity of the algorithm presented is obtained.
A Brief Account of Iterative Big Data Clustering Algorithms

-Today, maximum of the organizations have to deal with big quantities of records, that is hastily growing. In order to address these explosively growing amounts of information, one has so that it will extract, examine, and process information time to time. Clustering has for this reason been identified keeping in view this example and it is considered as an essential device used to analyze huge statistics. Technological progress, specifically inside the regions of finance and enterprise informatics, poses a big task for big scale records clustering. To deal with this issue, researchers have provided you with parallel clustering algorithms that are primarily based on parallel programming fashions. MapReduce is one of the most typically used frameworks used for this motive and it has received high consciousness thanks to its flexibility, fault tolerance and programming ease. However, the overall performance has trouble for iterative packages. This paper gives an in depth evaluation of iterative frameworks which could help MapReduce for overcoming boundaries for iterative algorithms.
SOLVENT-FREE BILAYER LIPID DOME DEVICE FOR CHANNEL PROTEIN RECORDINGS

This paper describes a device that enables to form solvent-free bilayer lipid membranes for electrical ion-channel recordings. We designed arrayed apertures surrounded by SU8 fences on an Al-coated polymer film for the matrix of the bilayer. An electrospray method allows a solvent-free, dried lipid coating at Al-exposed surface of the film, and domeshaped bilayer membranes are formed by electroformation/gentle-hydration method. The SU8 fence plays a role positioning the membrane on top of the aperture, allowing electrical monitoring across the membrane. Since avoiding the drawback of the organic solvent, we believe that this system will be very useful for channel protein study.
Phylogenetic analysis of ovine herpes virus-2 ( OHV-2 ) in malignant catarrhal fever infected cattle in Al-Qadisiyah governorate of Iraq

Ovine herpesvirus-2 is a member of the gammaherpesviruses of the herpeseviridae, which is the etiologic agent of malignant catarrhal fever (MCF), a significant fatal disease of cattle. MCF disease was diagnosed in native Iraqi cattle of AlQadisiyah governorate of Iraq, during the period from April 2014 and August 2016. Twenty-three blood samples were collected from clinically suspected cattle. The presence of the virus in samples was ascertained based on clinical pictures, postmortem examination and molecular assays. Pansystemic involvement included respiratory, digestive, urinary, nervous systems and ocular lesions were described. A molecular analysis based on a tegument protein gene by specific semi-nestedPCR, DNA sequence and multiple alignments of all PCR products confirmed the Ovine herpesvirus-2 (OHV-2) infection, and revealed a single and double nucleotide deletion, insertion and substitutions. Some of these mutations were non-silent, resulting in changes at the predicted amino acids level into viral tegument protein. The phylogenetic analysis showed the disease was caused by two genovariants of OHV-2 including at one cluster and were related to other sequences from others countries was analyzed. MCF is sporadically occurring in cattle in Iraq, the head and eye form is more pronounced form. It has been concluded that study is provides valuable information about the genetic variation among the OHV-2 genotypes in Iraqi cattle. Based on sequence and phylogenetic analysis of tegument protein gene, this paper elucidated genetic relationship between identified Iraqi OHV-2 with other strains detected in other geographical regions. These results provide new information on the epidemiological and genetically of OHV-2 in Iraq. Keyword: MCF, Iraq, Ovine herpesvirus-2, genovariants, Al-Qadisiyah governorate, Iraq Available online at http://www.vetmedmosul. com سبرهلا سوريفل يروطتلا ليلحتلا (OHV-2) ىمحلاب ةباصملا راقبلأا يف يف ةثيبخلا ةيلازلزلا
Environmental Values and Behaviours of Adventure Tourism Operators : The case of the Tsitsikamma , South Africa

Adventure tourism is one of the fastest growing sectors of the tourism industry. As a unique form of nature-based tourism, in that it involves active engagement with nature, the relationship between the adventure tourism industry and the environment has yet to be adequately explored. The vital role of the environment in adventure tourism has been mentioned throughout literature, but the environmental perspectives of adventure tourism operators are largely unknown. This study examines the attitudes and practices of adventure tourism operators through data collected from five companies in the Tsitsikamma, South Africa, a hot-spot for adventure tourism in a unique environment. It first demonstrates the wide spectrum of initiatives taken by different adventure tourism companies that operate within this unique and fragile environment. The results also show that this group of adventure guides do have some sense of environmental awareness, though environmental values were, generally, relatively low when compared with other similar studies. However, this group of adventure guides do demonstrate a number of behaviours taken to minimize the environmental impact of these activities.
Comparison of Data from the North Georgia Lightning Mapping Array and the GOES-16 Geostationary Lightning Mapper

The North Georgia Lightning Mapping Array (NGLMA) is an array of sensors deployed by the Severe Storms Research Center (SSRC) at the Georgia Tech Research Institute. Centered on the metropolitan Atlanta area in north Georgia, the NGLMA uses 12 ground-based sensing stations to detect total lightning. In this paper, we will compare total lighting data collected in north Georgia by the NGLMA to the data detected by the GOES-16 Geostationary Lightning Mapper (GLM) over this same area for two cases in July and September of 2017. Results indicate that the GLM data is offset to the east by 0.05 to 0.1 degrees in longitude (5-9 km), with no significant latitudinal offsets
Quantum Recommendation Systems ( FULL VERSION )

A recommendation system uses the past purchases or ratings of n products by a group of m users, in order to provide personalized recommendations to individual users. The information is modeled as an m×n preference matrix which is assumed to have a good rank-k approximation, for a small constant k. In this work, we present a quantum algorithm for recommendation systems that has running time O(poly(k)polylog(mn)). All known classical algorithms for recommendation systems that work through reconstructing an approximation of the preference matrix run in time polynomial in the matrix dimension. Our algorithm provides good recommendations by sampling efficiently from an approximation of the preference matrix, without reconstructing the entire matrix. For this, we design an efficient quantum procedure to project a given vector onto the row space of a given matrix. This is the first algorithm for recommendation systems that runs in time polylogarithmic in the dimensions of the matrix and provides an example of a quantum machine learning algorithm for a real world application.