Miracle-dz/UniFAR-FTUs huggingface dataset:
Fate of a new silicone‐based oil‐treating agent and its effects on marine microbial communities

A new silicone‐based agent was developed to treat and recover oil slicks and various floating oily residues that are often observed in marinas and harbors. As part of its ecotoxicologic assessment, the fate of the treating agent alone or combined with crude oil, and the effects on natural microbial communities were studied in estuarine mesocosms (3.5 m3) over a 9‐week period. The ability of the in situ formed silicone layer to trap an oil slick at the water surface was highlighted by a significative reduction in the volatilization, natural dispersion, and sedimentation of the treated oil. The treatment favored the dissolution of light aromatic hydrocarbons such as methyl‐naphthalenes but these compounds were rapidly biodegraded in the water column. The agent alone, as well as the treated or untreated oil, had no effect on the biomass and photosynthetic ability of the phytoplankton community entrapped in the mesocosms. A significant stimulation of oil‐degrading bacteria was noted in mesocosms containing treated and untreated oil slicks. On the basis of these results, we conclude that the use of a silicone‐based treating agent could be an effective countermeasure to an oil spill, with neither deleterious effects to natural microbial communities nor to long‐term biodegradation of the unrecovered oil residues.
A reliable iterative method for Cauchy problems

In the present paper, the new iterative method proposed by Daftardar-Gejji and Jafari (NIM or DJM) [V. Daftardar-Gejji, H. Jafari, An iterative method for solving non linear functional equations, J. Math. Anal. Appl. 316 (2006) 753-763] is used to solve the Cauchy problems. In this iterative method the solution is obtained in the series form that converge to the exact solution with easily computed components. The results demonstrate that the method has many merits such as being derivative-free, overcome the difficulty arising in calculating calculating Adomian polynomials to handle the nonlinear terms in Adomian Decomposition Method (ADM). It does not require to calculate Lagrange multiplier in Variational Iteration Method (VIM) and no needs to construct a homotopy and solve the corresponding algebraic equations in Homotopy Perturbation Method (HPM) and can be easily comprehended with only a basic knowledge of Calculus. The results show that the present method is very effective, simple and provide the analytic solutions. The software used for the calculations in this study was MATHEMATICA r 8.0. Keywords : New iterative method; Cauchy problems; Inviscid Burger’s equation; transport equation
Unilateral exophthalmos in a horse – Diagnosis, management and outcome

Summary A 19-year-old Arabian mare was presented in the equine clinic with a history of a slowly progressing exophthalmos during six months without impairment of her general condition and vision. Using ophthalmoscopy and ultrasonography there were no morphologic changes of the bulbus. A retrobulbar mass of soft tissue density deformed the bulbus and pushed it out of the orbital cavity. The dimensions of the neoplastic growth were exactly determined using magnetic resonance imaging. The retrobulbar mass was surgically removed via dorsal orbitotomy and a melanoma was diagnosed histologically. No complications arose afterwards. The visus could be preserved. The upper eyelid still showed a partial ptosis six months after surgery.
Parameterizing and operationalizing zooplankton population dynamic and trophic interaction models

Institute of Marine Research, Austevoll Research Station, Storebo 5392, Norway*Corresponding author: tel: 1-418-775-0676; fax: 1-418-775-0546; e-mail: stephane.plourde@dfo-mpo.gc. caPlourde,S. ,andBrowman,H.I. 2014.Parameterizingandoperationalizingzooplanktonpopulationdynamicandtrophicinteractionmodels. – ICESJournal of Marine Science, 71: 234–235.Received12 November 2013; accepted14 November 2013.
Do pollen carryover and pollinator constancy mitigate effects of competition for pollination

Pollinator constancy and pollen carryover are both thought to mitigate competitive effects that result when shared pollinators cause loss of pollen to heterospecific flowers. I present analytical and simulation models to investigate how pollinator constancy and pollen carryover interact with each other and with the relationship between pollen receipt and seed set to determine pollination success in competitive environments. With inconstant pollinators, increased pollen carryover reduces variance in pollen receipt without affecting average pollen receipt. Consequently, for flowers requiring at least a threshold quantity of pollen for success, rare flowers with inconstant pollinators benefit from reduced carryover, especially for high pollen receipt thresholds, whereas common flowers benefit from increased carryover, especially for low receipt thresholds. Pollinator constancy is predicted to increase pollen receipt, especially if pollen carryover rates are low. As a result, increased pollinator constancy reduces the range of pollen receipt thresholds for which carryover is beneficial. Similarly, for flowers whose pollination success is a convex function of pollen receipt, carryover is expected to increase fecundity if pollinators are inconstant, but with even a low degree of pollinator constancy, carryover reduces fecundity. These results predict that rare plants with many ovules per flower benefit from dispersing aggregations of pollen, especially if their pollinators exhibit constancy, whereas plants with inconstant pollinators and low thresholds of pollen receipt benefit from pollen grains dispersing individually to increase the number of flowers reached by the pollen.
Compactação de biomassa vegetal visando à produção de biocombustíveis sólidos

O objetivo do presente trabalho foi avaliar briquetes produzidos a partir de casca de cafe, serragem de eucalipto e residuos da colheita do milho, e a influencia do tempo apos a compactacao em algumas propriedades dos briquetes. Apos a biomassa ser previamente seca em estufa, os briquetes foram produzidos em uma briquetadeira laboratorial, a temperatura de 120±5oC e pressao de 15 MPa. Determinaram-se a densidade a granel e o poder calorifico das biomassas in natura. Apos a compactacao, avaliou-se a influencia do tempo sobre a umidade, a expansao volumetrica e a densidade aparente dos briquetes. A partir dos resultados obtidos, pode-se observar que a casca de cafe moida apresentou o maior valor medio para densidade a granel. Estatisticamente, as biomassas analisadas apresentaram o mesmo poder calorifico superior. O efeito do tempo apos a compactacao da biomassa foi significativo para a umidade em base seca e densidade aparente para todos os briquetes produzidos. Os briquetes produzidos a partir dos residuos da colheita do milho apresentaram acentuada expansao volumetrica. Quanto a resistencia a tracao por compressao diametral, os briquetes de casca de cafe apresentaram o maior valor. Os resultados encontrados reforcam a potencialidade de utilizacao energetica dos briquetes oriundos da compactacao da casca de cafe. doi: 10.4336/2011.pfb. 31.68. 273
Incorporating Institutional Theory of Corporate Image Towards Customer Loyalty of Islamic banks

The importance of corporate image in any organization is undisputable including those of Islamic banks. Many studies on corporate image have been using metaphorical expression in various contexts. The objective of this paper, apparently, is to examine corporate image in Islamic banks based on the institutional theory which incorporates performative image, institutional image, organizational legitimacy and support. Corporate Character Scale was utilized to determine performative image of Islamic banks, while interviews were conducted to identify institutional image. A survey was then employed to study the relationships of corporate image (performative and institutional) on customer loyalty. Findings indicate that institutional image has an impact on performative image, and both of these images influence organizational legitimacy. Surprisingly, attitudinal loyalty does not have an impact on behavioural loyalty. The implication of the study in relation to corporate image is further discussed.
Genetic variation and the performance of a mass‐reared parasitoid, Trichogramma pretiosum (Hymenoptera: Trichogrammatidae), in laboratory trials

During mass rearing, adaptation of biological control agents to the rearing environment is a potential problem. Using the parasitoid wasp Trichogramma pretiosum, the performance of 26 highly inbred lines, five composite ‘populations’ (created from the inbred lines) and one insectary‐reared population was compared using fertility life tables. Of the composite populations, three were created with maximal and identical genetic variation as a mixture of all 26 inbred lines, but these were then reared for a different number of generations (2, 6 or 17) before their performance was measured. The remaining two composite populations were created based on the performance of the individual inbred lines: one was a combination of two inbred lines with a high intrinsic rate of natural increase (rm), ‘high rm’; and the other was a combination of two lines with a ‘low rm’. High and low rm populations were reared for two generations prior to testing. Parameters measured were fertility, longevity and sex ratio. We found no difference between the maximally variable population reared for two generations and the ‘high rm’ population (rm = 0.285 and 0.282, respectively). ‘Low rm’ was the population with the lower performance (rm = 0.255). Genetically variable population reared for two generations for 48 h produced significantly more offspring than the populations reared for 6 and 17 generations. Hybrid population derived from the high‐rm lines did significantly better than that derived from the low‐rm lines. Low‐performance populations become more male based than high performance at 48 h. The potential benefits to improve population's performance using inbred lines for mass rearing are discussed.
Classification and Identification of rice grains using Neural Network

: An Agricultural industry is too oldest and most widespread industry in the world. Classification and quality evaluation of rice grains is a challenge since manual classification that are being usedin this industry which may not be objective or efficient. All important decisions about variety of rice grain are based on the different features of rice grain. An automated system is introduced which can be used for rice grain type identification and classification where digital imaging is recognized as an efficient technique to extract the features from rice grains in a non-contact manner. Images are acquired for rice using camera. Image Pre-processing techniques, Segmentations, Feature extractionare the checks that are performed on the acquired image. The morphological features are extracted from the image are given to Neural Network Pattern Recognition Tool. This effort has been proposed to categorize and identify the specified rice sample based on its morphological features.
Bose Einstein 1 and Bose Einstein 2 Model for Optimal Query Expansion

: Queries are generally short, vague and contains fewer information about the documents. Therefore retrieval of relevant documents from short query is a tedious task. Another issue in Information Retrieval (IR) is problem of term mismatch. Thus degrades the performance of any retrieval system . A number of methods have been developed in order to enhance the performance of IR system. One of these methods is query expansion. Query Expansion is used to reduce problem of word mismatch. The proposed method uses two query expansion model Bo1 and Bo2 based on pseudo relevance feedback and tries to find the optimum number of document and term for which the system perform better. The proposed model ascertains that retrieval system performs better when expansion documents and terms are 8 and 15 respectively.
Genetically distinct Dutch-domesticated Clarias gariepinus used in aquaculture in southern Africa

Clarias gariepinus, a catfish species widely distributed in Africa including South Africa, is naturally absent from the Western Cape and the coastal Eastern Cape provinces. Because of its potential as an aquaculture species it has been widely used in aquaculture ventures in South Africa, specifically a stock known as Dutch catfish, a domesticated strain developed in the Netherlands. Mitochondrial DNA markers indicate that this stock is genetically distinct from the natural populations of C. gariepinus in South Africa. It could potentially pose a threat to South Africa's natural biodiversity if these fish were to escape from aquaculture farms, or was deliberately introduced into inland waters.
Scalable Filtering Approaches for Recommendation Systems in E-Commerce

: Various contents are provided through the internet. Especially the contents of e-Commerce such as music, movies, and books are indispensable for modern life style. However, it is not easy to find favorite contents among huge amounts of contents in terms of user's preference. An effective approach to solve such the problem is to develop "Recommender System. " The Recommender System of Amazon site selects and recommends the contents to meet user's preference automatically using various data stored in database. There is need to filter, prioritize and efficiently deliver relevant information in order to alleviate the problem of information overload, which has created a potential problem to many Internet users. Recommender systems solve this problem by searching through large volume of dynamically generated information to provide users with personalized content and services. The essential technique in the Recommender System is information filtering. Among the various types of information filtering that have been proposed, the techniques fall into two categories: content-based filtering and collaborative filtering. Recommender system is a kind of web intelligence technique to make daily information filtering for people. Clustering techniques can be applied to the user-based collaborative filtering framework to solve the cold start problem. This paper covers different techniques which are used in recommendation system and also proposes a system for hybrid recommendation system. Recommendation based on hybrid collaborative filtering i.e. using few techniques of collaborative filtering approach. This paper explores the different characteristics and potentials of different prediction techniques in recommendation systems in order to serve as a compass for research and practice in the field of recommendation systems.
Active Learning of Conditional Mean Embeddings via Bayesian Optimisation

We consider the problem of sequentially optimising the conditional expectation of an objec-tive function, with both the conditional distribution and the objective function assumed to be ﬁxed but unknown. Assuming that the ob-jective function belongs to a reproducing kernel Hilbert space (RKHS), we provide a novel upper conﬁdence bound (UCB) based algo-rithm CME-UCB via estimation of the conditional mean embeddings (CME), and derive its regret bound. Along the way, we derive novel approximation guarantees for the CME estimates. Finally, experiments are carried out in a synthetic example and in a likelihood-free inference application that highlight the useful insights of the proposed method.
Communication Protocols of an Industrial Internet of Things Environment: A Comparative Study

Most industrial and SCADA-like (supervisory control and data acquisition) systems use proprietary communication protocols, and hence interoperability is not fulfilled. However, the MODBUS TCP is an open de facto standard, and is used for some automation and telecontrol systems. It is based on a polling mechanism and follows the synchronous request–response pattern, as opposed to the asynchronous publish–subscribe pattern. In this study, polling-based and event-based protocols are investigated to realize an open and interoperable Industrial Internet of Things (IIoT) environment. Many Internet of Things (IoT) protocols are introduced and compared, and the message queuing telemetry transport (MQTT) is chosen as the event-based, publish–subscribe protocol. The study shows that MODBUS defines an optimized message structure in the application layer, which is dedicated to industrial applications. In addition, it shows that an event-oriented IoT protocol complements the MODBUS TCP but cannot replace it. Therefore, two scenarios are proposed to build the IIoT environment. The first scenario is to consider the MODBUS TCP as an IoT protocol, and build the environment using the MODBUS TCP on a standalone basis. The second scenario is to use MQTT in conjunction with the MODBUS TCP. The first scenario is efficient and complies with most industrial applications where the request–response pattern is needed only. If the publish–subscribe pattern is needed, the MQTT in the second scenario complements the MODBUS TCP and eliminates the need for a gateway; however, MQTT lacks interoperability. To maintain a homogeneous message structure for the entire environment, industrial data are organized using the structure of MODBUS messages, formatted in the UTF-8, and then transferred in the payload of an MQTT publish message. The open and interoperable environment can be used for Internet SCADA, Internet-based monitoring, and industrial control systems.
Review on microwave generation using backward wave oscillator

One of the most established vacuum electronic high power source- VED sources of radiation(at higher orders of power and frequency) [11],[12] is the backward wave oscillator (BWO) . A BWO is a VED that is used to generate microwaves up to very high frequency range and high power while keeping the device very compact . By adjusting the beam voltage, in [21], it is shown that , it tunes fully and rapidly over a very wide band ( around 50 percent) of frequencies. Its frequency is relatively independent of load impedance and it can be designed to be exceptionally stable in frequency. BWO are such VEDS whose size is of an inch also exist. So, compactness and its capability to be operational at broadband frequency sets it high on list of energy sources when one talks about microwave generation, especially high power accompanied at high frequency with compactness. This paper gives a detailed study on various stages that BWO has witnessed in high power microwave generation, from the time it evolved.
Comparison of Multilevel Wavelet Packet Entropy using Various Entropy Measurement for Lung Sound Classification

Wavelet Entropy (WE) is one of the entropy measurement methods by means of the discrete wavelet transform (DWT) subband. Some of the developments of WE are wavelet packet entropy (WPE), wavelet time entropy. WPE has several variations such as the Shannon entropy calculation on each subband of WPD that produces 2N entropy or WPE, which yields an entropy value. One of the WPE improvements is multilevel wavelet packet entropy (MWPE), which yields entropy value as much as N decomposition level. In a previous research, MWPE was calculated using Shannon method; hence, in this research MWPE calculation was done using Renyi and Tsallis method. The results showed that MWPE using Shannon calculation could yield the highest accuracy of 97.98% for N = 4 decomposition level. On the other hand, MWPE using Renyi entropy yielded the highest accuracy of 93.94% and the one using Tsallis entropy yielded 57.58% accuracy. Here, the test was performed on five lung sound data classes using multilayer perceptron as the classifier.
AR phone way-finding using imagery and navigation for indoor environments

Augmented Reality (AR) is newly considered in indoor navigation field nowadays, to provide more intuitive and convenient navigation function so as to improve user experience. This report will discuss about how to improve usability and convenience of an existing indoor navigation software created by Zhang (2019), by solving drawbacks of its re-localization function. A QR Code based technique has been designed and implemented, which can recognize QR Codes in a photograph and gain location as well as orientation information to guarantee that the navigation functions work properly and automatically. Based on this technique, a new version of the AR indoor navigation software has been complied, and evaluated with its time/accuracy performance. Also, a heuristic evaluation focused on user interface design has been carried out for the software.
A Survey of Algal Epiphytes from Vallisneria americana Michx. (Hydrocharitaceae) in the Lower St. Johns River, Florida

Abstract Epiphytic algae may be responsible for a significant amount of primary productivity in aquatic ecosystems, but also reduce available light, compete for nutrients, and increase drag on their living substrates. A survey of the epiphytic algal community of the submersed aquatic macrophyte Vallisneria americana Michx. (Hydrocharitaceae) in the lower St. Johns River, FLwas conducted over a 17-month period. A total of 122 infrageneric taxa were collected at four sites along a 93-km stretch of the river, yielding 32 diatoms (Bacillariophyta), 42 green algae (Chlorophyta), 45 blue-green algae (Cyanobacteria), 2 euglenoids (Euglenophyta), and 1 dinoflagellate (Pyrrophyta) taxa identified over the study period. However, only diatoms and cyanobacteria were seen at all sampling dates, and only a Cocconeis sp. was identified at all sites on all dates. This study provides baseline survey data of the epiphytic algal community in order to assess future anthropogenic effects.
Reflection methods for user-friendly submodular optimization

Recently, it has become evident that submodularity naturally captures widely occurring concepts in machine learning, signal processing and computer vision. Consequently, there is need for efficient optimization procedures for submodular functions, especially for minimization problems. While general submodular minimization is challenging, we propose a new method that exploits existing decomposability of submodular functions. In contrast to previous approaches, our method is neither approximate, nor impractical, nor does it need any cumbersome parameter tuning. Moreover, it is easy to implement and parallelize. A key component of our method is a formulation of the discrete submodular minimization problem as a continuous best approximation problem that is solved through a sequence of reflections, and its solution can be easily thresholded to obtain an optimal discrete solution. This method solves both the continuous and discrete formulations of the problem, and therefore has applications in learning, inference, and reconstruction. In our experiments, we illustrate the benefits of our method on two image segmentation tasks.