Miracle-dz/UniFAR-FTUs huggingface dataset:
Correlations between type-indicator fish species and lake productivity in German lowland lakes

Morphotypes for 67 lakes in the German lowlands were derived, based on maximum depth and mixis type. A threshold of 11 m maximum depth was identified to be the best level to discriminate shallow from deep lake morphotypes. The fish communities in these two morphotypes were significantly different. Indicator species analyses based on fish biomasses found vendace Coregonus albula in deep lakes and ruffe Gymnocephalus cernuus ,b reamAbramis brama, white bream Abramis bjoerkna, roach Rutilus rutilus, pikeperch Sander lucioperca and small perch Perca fluviatilis in shallow lakes to be the most representative species of their communities. Lake productivity was closely related to biomass and in part abundance of the type-indicator species, with vendace declining with increasing chlorophyll a concentration in the deep lakes, whereas biomass of pikeperch, bream, white bream and ruffe increased and biomass of small perch decreased with increasing chlorophyll a. These results indicate that assessment of ecological integrity of lakes by their fish fauna is generally possible, if lakes are initially separated according to a depth-related morphotype before the assessment, and if eutrophication is considered to be the main anthropogenic degradation. # 2006 The Fisheries Society of the British Isles
The Proposed Implementation of RFID based Attendance System

Recent trends in Information and Communication Technology (ICT) embrace several smartphone applications in a variety of educational and industrial domains in the last several years. This research focuses to solve one of the promising problems of an educational domain to take attendance smartly using the Radio Frequency Identification (RFID) system. Current attendance system in King Abdul-Aziz University (KAU) Saudi Arabia is partly solving the attendance problem. There are several problems in the existing attendance systems such as time-consuming, the chance of mistakes, truancy issues, no contact with parent/guardian and not efficient because of roll call as taking manual attendance. The proposed RFID based attendance system will provide robust, secure and automatic attendance. The proposed system will use modern technology and support to institutions and parents to deal with most of the problems of existing attendance systems. There are several other benefits of RFID based system such as web-based and mobile interfaces, daily absent report, an automatic SMS alert to parent/guardian, reduce administrative work, improve the ratio of attendance, economical and highly efficient. The case study method will be used as a research design. The proposed system is developed and tested in KAU Saudi Arabia. The proposed system will have both web and mobile interfaces. The web interface will need the Internet to access the proposed system and the mobile interface will use the Android platform for the testing scenarios. The user will access the system to generate customized reports to review the status of students for a particular course. It is anticipated that the proposed system will significantly improve students’ monitoring mechanisms hence enabling both parents and teachers in making appropriate decisions.
MLMN: AN EFFICIENT FRAMEWORK FOR MULTI-LAYER MODEL FOR NOVELTY DETECTION IN DATA MINING

Data Classification is one of the boons to the mining process which eventually eases the process of machine learning. But it is always a doubt about the data that is being used for the classification process. As in Supervised, semi-supervised and unsupervised learning styles the selected data for the classification is always having a chance of missing unknown and new data from the data pool this adversely affects the quality of the mining process. So the process of extraction of unknown and new data from the huge data pool for classification process is very important and it is known as novelty detection. So this research of MLMN provides an ideal way to detect the novelty data that is been using in the further classification process. This research mainly focuses on the multiple layers like 1) Pattern identification, 2) Density Classification, 3) Distance identification and 4) Learning models for the efficient process of novelty detection.
THE MIGRATION OF DATA FROM A RELATIONAL DATABASE (RDB) TO AN OBJECT RELATIONAL (ORDB) DATABASE

The present article deals with the passage of migrating data from a relational database to an object relational database, by developing methods of selection and insertion which is based on optimizing the extraction of information in a predefined data model, which deals with the transition from relational to object relational, which fits to any situation processing . The migration handles the majority of the object concept including inheritance. The transition of migration is done in an automatic way, without the interference of the human factor, a prototype is already created that proves the effectiveness of this approach.
QURAN ONTOLOGY: REVIEW ON RECENT DEVELOPMENT AND OPEN RESEARCH ISSUES

Quran is the holy book of Muslims that contains the commandment of words of Allah. Quran provides instructions and guidance to humankind in achieving happiness in life in the world and the hereafter. As a holy book, Quran contains rich knowledge and scientific facts. However, humans have difficulty in understanding the Quran content. It is caused by the fact that the meaning of the searched message content depends on the interpretation. Ontology able to store the knowledge representation of Holy Quran. This paper studies recent ontology on Holy Quran research. We investigate the current trends and technology being applied. This investigation cover on several aspects, such as outcomes of previous studies, language which used on ontology development, coverage area of Quran ontology, datasets, tools to perform ontology development ontology population techniques, approaches used to integrate the knowledge of Quran and other resources into ontology, ontology testing techniques, and limitations on previous research. This review has identified four major issues involved in Quran ontology, i.e. availability of Quran ontology in various translation, ontology resources, automated process of Meronymy relationship extraction, and Instances Classification. The review of existing studies will allow future researchers to have a broad and useful background knowledge on primary and essential aspects of this research field.
THERMAL CONDUCTIVITY AND DIFFUSIVITY OF NATURAL GRAPHITE SHEET

The in–plane and through–plane thermal conductivity and diffusivity of natural graphite sheet (NGS) at densities ranging from 0.5 g cm−1 to 1.7 g cm−1 are measured using the transient plane source method. In the in–plane direction, the thermal conductivity and diffusivity are high in the range from 100 Wm−1K−1 to 350 Wm−1K−1 and from 230 mm2s−1 to 270 mm2s−1, respectively, and they increase with density. In the through–plane direction, the thermal conductivity and diffusivity are low in the range from 5 Wm−1K−1 to 2 Wm−1K−1 and from 12 mm2s−1 to 1.5 mm2s−1, respectively, and they decrease with density. The in–plane properties are independent of the compression pressure but the through–plane properties increase with pressure especially at higher densities. The sheet-to-sheet thermal contact resistance of stacked NGS is found to be negligible.
IN VITRO STUDIES ON BIOACCESSIBILE HEAVY METALS IN RICE

The tendency to accumulate in biological systems makes heavy metals a significant health hazard. Rice consumption is one major pathway of heavy metal bioaccumulation in human, because of its ability to absorb toxic element from soil and water more effectively than any other crops. Studies related to toxic elements in rice have attracted a great concern worldwide involving paddy field and marketed rice samples. However nowadays the fractions of metals are eventually absorbed into the systemic circulation i.e. bioavailability (in vivo studies) are gaining greater attention. A total of ten rice samples were collected randomly from the market, cooked and analysed for total heavy metal content. The cooked rice samples were subjected to in vitro digestion to find out the bioaccessible metal concentration using AAS. Based on the inherent and bioaccessible metal content total hazard quotient was worked out. In vitro digestion results indicated that bioaccessible Pb ranged between 0.07 to 0.76 mg kg and the per cent of bioaccessibility was between 1.57 to 11.28. The bioaccessible Ni content was between 1.19 to 2.53mg kg in digested extract and the percentage ranges from 11.63 to 32.86. There were no earlier studies on the bioaccessibility of Ni in rice. Bioaccessible Cd and Cr was 0.14 to 1.12 mg kg 0.96 to 4.21 mg kg in digested extract respectively. The inherent metal content was above the permissible limit in most cases, the bioaccessibility of the analysed metals were independent of their total content. The total hazard quotient data analysis showed, there was no evident risk heavy metals consumed through rice.
A scalable approach to control diverse behaviors for physically simulated characters

Human characters with a broad range of natural looking and physically realistic behaviors will enable the construction of compelling interactive experiences. In this paper, we develop a technique for learning controllers for a large set of heterogeneous behaviors. By dividing a reference library of motion into clusters of like motions, we are able to construct experts, learned controllers that can reproduce a simulated version of the motions in that cluster. These experts are then combined via a second learning phase, into a general controller with the capability to reproduce any motion in the reference library. We demonstrate the power of this approach by learning the motions produced by a motion graph constructed from eight hours of motion capture data and containing a diverse set of behaviors such as dancing (ballroom and breakdancing), Karate moves, gesturing, walking, and running.
The Elephant in the Chamber? Incorporating Tweets about Trump into Congressional Ideal Point Estimates

Political science has traditionally measured legislator preferences using roll-call voting behavior, but we consider the possibility that legislative votes might fail to adequately capture attitudes toward President Donald Trump. We estimate Congressional ideal points using an alternative expression of preferences: tweeting. Sampling from a population of all tweets authored by members of the U.S. House and Senate related to Donald Trump from November 2016 to February 2018, we incorporate the frequency, timing, and content of these tweets into representations of legislator ideology using a neural net approach. We construct a model in which legislator attitudes towards Trump are represented as vector embeddings, and Donald Trump himself is represented as a vector that is constructed using a neural network from the text of his daily tweets. In our model, the interaction between legislator embeddings and Trump embeddings produces predictions of both the number of times legislators tweet about Donald Trump and the sentiment of tweets about Donald Trump. We assess the quality of our learned representations for legislators by comparing to the canonical DW-NOMINATE representations as well as votes on Trumpendorsed legislation.
Adaptive visualization of 3D meshes using localized triangular strips

:- 3D meshes are the principal representation of 3D objects. They are very powerful in manipulation and easy to visualize. However, they often require a huge amount of data for storage and/or transmission. In this paper, we present an effective technique to stream triangular meshes using enhanced mesh stripificatio algorithm. In fact, stripificatio algorithms are used to speed up the rendering of geometric models because they reduce the number of vertices sent to the graphics pipeline by exploiting the fact that adjacent triangles share an edge. This enables to use our technique to adaptively visualize the 3D models during their transmission. The firs step of the proposed technique is based on storing 3D objects as a set of strips. This encodes the geometry and the connectivity of the input model in a robust fashion. The stripificatio algorithm achieves compression ratios above 61 : 1 over ASCII encoded formats. Second, the strips are directly sent to the rendering pipeline in accordance with the viewpoint direction resulting in faster transmission and rendering of complex graphical objects. Binary space partitioning, kd-trees, is used to enhance our stripificatio algorithm. Some examples are given to demonstrate the effectiveness of our technique.
Generating passive systems from recursively defined polynomials

In single-input single-output linear time-invariant systems, and in particular in filter modelling and design, some properties of the system (such as shaped frequency responses) are achieved by using polynomials of particular types for the design of the system transfer function. In this paper it is shown that single-input single-output linear time-invariant systems having as transfer function the ratio between two successive polynomials recursively defined have particular properties. In particular, if the ratio between successive polynomials of either Fibonacci or Lucas type is considered, loss-less systems are achieved, while starting from Jacobsthal or Morgan-Voyce polynomials relaxation systems are defined. Furthermore, it is also shown that transfer functions obtained by considering either the ratio between a Fibonacci polynomial of order n and a Lucas polynomial of order n or between a Fibonacci polynomial of order n and a Lucas polynomial of order n− 1 multiplied by the complex variable s are also loss-less.
Benefits for the standardization of Mission Planning Services from Advanced Planning Experiences

The ambitious goal of the Spacecraft Monitoring & Control (SM&C) Working Group of the Consultative Committee for Space Data Systems (CCSDS) is to define a set of standardized, interoperable mission operation (MO) services, which allow rapid and efficient construction of co-operating space systems. Such services will have to be general enough to cope with the various needs of existing and future missions, but at the same specified enough to be practically usable. This paper presents some ideas to deal with this difficult task drawn from existing architectures and interfaces used in AI advanced software systems for planning and scheduling.
Swarm Optimization Based Gravitational Search Approach for Channel Assignment in MCMR Wireless Mesh Network

Wireless Mesh Networks offers cost-efficient and higher network efficiency by utilizing multiple channels multiple radio(MCMR) nodes. Also addition, the amalgamation of multiple radio nodes and multiple hops mesh framework tends to overcome the limitation of single radio networks like the ability to achieve the rising accessible system bandwidth. In spite of these benefits, certain MCMR wireless mesh networks still suffer from performance issues like network connectivity, network throughput degradation whenever network size increases. Thus, an effective channel assignment (CA) approach could minimize the number of interference co-channels and enhance the throughput of the network. Thus, a hybridized form of gravitational search approach and particle swarm optimization is presented in this paper to resolve the issue of CA. The velocity and position updates of PSO are merged with the GSA operations to obtain the best channel with good connectivity. This approach maximizes the capability of exploration and exploitation for global and local searches using PSO and GSA operations. The goal of this methodology is the minimization of a number of interfering links and the maximization of network connectivity and throughput. The experimental results for this approach are carried out using NS2 and compared with previously suggested heuristic optimization algorithms such as Learning Automated and Genetic Algorithm Approach, Improved Gravitational Search Approach and Dynamic particle swarm optimization Approach. The simulation outcome showed a better performance of the suggested methodology compared to existing methodologies.
SELECTION OF FACTORS AFFECTING WOMEN'S LOYALTY IN BUYING GOODS IN INDONESIAN E-MARKETPLACES USING THE PROFILE MACHINE METHOD

The use of social media in the field of online marketing has been used by female consumers. In its use found uncomfortable transactions even though vendors have provided good features to reduce risk. This study investigates web site factors that affect consumer loyalty online shopping through social media namely Buyer Loyalty (Business View, Market Service View, Third Party B2B EM Performance, Transaction View, and Infrastructure View) and its attributes Trust (Quality of information, Customer loyalty, Volume trading, Product promotion, Reduction of transaction costs, Consumer characteristics (Free Shipping Costs, Trust in Marketing Makers), Firms characteristics (Functionality and value-added, Reputation, Privacy), Brand Recognition (Likability, Customer satisfaction, Attitude towards online shopping), Quality of Service (Transaction security, Use of the website, Reliability of the website). This study uses an IT-based platform for data collection and collects data from female consumers using the profile machine method. Data analysis by grouping female consumers using online shopping websites based on the attributes they like.
Price Leadership between Spot and Futures Markets I. Introduction Understanding the influence of one market on the other and role of each market segment in price discovery is the central question in market microstructure design and of utmost

The introduction of derivatives segment from the early 2000s onwards has led both to interactions between the spot and futures markets, and to an interest by regulators in controlling any possible harmful influences of this new trading segment. The Individual Stock Futures (ISF) segment is of phenomenal success on Indian bourses and NSE is consistently ranked number one in world ISF segment, even in the absence of strong stock lending mechanism. It is expected that the futures prices can reflect additional information, over and above that already reflected in the spot price, given the leverage benefits and so can serve as a leading indicator for the spot price. So far, no study looks at the ISF contribution to the spot segment and this study attempts to fill that gap. The traditional approach of analyzing the inter-linkages between spot and futures market concentrates on examining causality dynamics in returns and volatilities and do not address the ‘extent’ of price discovery either in spot or futures market. We follow the Information shares approach as suggested in Hasbrouck (1995, 2002) which takes into account the variability of the innovations in each market’s price. We consider intra-day data (one-minute and five-minute) of 46 NSE Nifty constituent stocks spot and futures segment during Jan 2004 to March 2007. We find that the spot and futures prices are co integrated and mutually adjusting. Building on Information Share approach of Hasbrouck, the price discovery share of futures segment is about 36% compared to that of spot segment is 64%. It is expected that futures market contribute more towards price discovery given huge trading volumes and they carry the natural advantage of cost-effectiveness in terms of leverage benefit. However, the empirical result (or the fact) is spot market leadership in price discovery and this fact is reconciled by probing the clientele of futures market and is consistent with very active participation of retail traders in futures segment. 1 Senior Researcher (CAF), Indian School of Business, Hyderabad 2 Faculty, IBS Hyderabad
Low water transport in fractal microstructure of tropical soils: application to chlordecone pesticide trapping

Abstract Chlordecone, a toxic organochlorine insecticide, is a major long term source of pollution of soils and water resources in West Indies. Allophanic soils have been strongly polluted and we show that the clay microstructure should be an important physicochemical characteristic limiting the transfer of the pesticide in water. We demonstrate the fractal structure of the allophane clay, at the nanoscale and show that it exist a correlation between the allophane fractal structure and the poor pesticides transfer from allophanic clay to water. We propose that the fractal features and associated poor low transport properties could explain why allophane clay is able to retain pesticides. Comparatively, these allophanic clays could be highly polluted but less contaminant for water resources and diffusion in environment.
Typology for ICT Adoption of EU Environmental Policies

- Information and Communication Technologies (ICT) have the potential to promote sustainable development as the growth in ICT is associated with environmental planning, research, conservation and planning. The aim of the paper is to create a typology for ICT adoption of EU environmental policies. The level of dependence on ICT solution and the level of complexity of the used ICT solutions by the established environmental policies are examined. The EU environmental policies are classified in three homogenous groups with similar ICT characteristics using K-Means cluster analysis. Regarding the classification according to the criteria, most EU environmental policies demonstrate high rate of ICT adoption and it constitutes a first and very important step for the transition to the new digital era, which is promoted by the European Union.
Five tortricines from Malaysia and New Caledonia (Lepidoptera: Tortricidae)

Five tortricines from Malaysia and New Caledonia (Lepidoptera: Tortricidae) Aoupinieta gen. n. and Homalernis mankoboi sp. n. , H. jeriau sp. n. , Peraglyphis silvana sp. n. , Aoupinieta hollowayi sp. n. , A. novaecaledoniae sp. n. are described as new. Arotrophora crustata Meyrick is transferred to Peraglyphis Common. Peraglyphis is new to the Oriental region.
Proteomic Approach to Discover Potential Biomarkers for Heart Failure

Heart failure is a clinical syndrome that develops due to abnormality in the cardiac structure or mechanical function leading to failure of the heart to deliver oxygen at a rate proportionate with the requirements of the metabolizing tissues. Despite advancement in primary prevention and therapy, it had continued to record poor prognosis and more complications leading to high rate of mortality. Recent advances in proteomic technologies permit the evaluation of systemic changes in protein expression in response to intrinsic or extrinsic perturbations to the biologic system. Proteomics is a potential tool for the discovery and application of novel biomarkers in diagnosis of the inception and progression of cardiovascular diseases (CVDs) which might then affect prevention and therapy. Shotgun proteomic approach was utilized to identify and compare the proteins in the tissue samples of a 3 month old glucokinase knockout mouse in early stage heart failure with a normal control mouse tissue sample. Bioinformatics analysis was performed using the MASCOT MS/MS ions search to identify, characterize and quantify. A total of 156 cardiac proteins were found in the normal control mouse tissue sample while 163 cardiac proteins were found in the diseased mouse tissue sample. 104 common cardiac proteins were identified in both mouse tissue samples. 35 cardiac proteins out of the common cardiac proteins were differentially expressed in the diseased mouse tissue sample and 49 unique cardiac proteins were also found in the diseased mouse tissue sample. 6 cardiac proteins (ATP Synthase mitochondrial OS, Cytochrome C somatic OS, Myoglobin OS, Myosin-6 OS, Isocitrate dehydrogenase (NADP) mitochondrial OS and Histone H4 OS with high exponentially modified protein abundance index (emPAI) from the differentially expressed and unique cardiac proteins were selected as potential discovered biomarkers. The selected proteins play an important role in cellular stress response, mitochondrial dysfunction and myocardial cell death.