Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Replacing Groundnut Cake with Moringa oleifera Leaf Meal in the Diets of Grower Rabbits

Seventy two (72) grower rabbits were used to assess the replacement of groundnut cake with Moringa oleifera leaf meal in the diets of grower rabbits and determining its effect on growth; nitrogen digestibility and the economics of rabbit production. There were six (6) dietary treatments with Moringa oleifera leaf meal replacing groundnut cake at 0, 20, 40, 60, 80 and 100%; each treatment was replicated three times with four rabbits per replicate in a completely randomize blocked design (CRBD). Proximate analysis of Moringa oleifera leaves on air-cured basis showed that the leaves contained Dry Matter 93.4, Crude Protein 24.8, Crude Fibre 11.1, Ether Extract 2.1, Ash 8.7 and Nitrogen Free Extract 53.5%; with a Metabolizable Energy of 3 316.52 Kcal/kg. Results showed that the final body weight, body weight gain, feed intake and feed to gain ratio showed significant difference ( P 0.05). The study revealed that Moringa oleifera leaf is rich in nutrient and can be used to replace 60% of Groundnut cake in the diets of grower rabbits.
Understanding Change : Perceived Impacts of Educational and Information Technology ( E & IT ) on Teaching and Learning

Change in education is hard and complex since crucial factors, mostly hindering ones, emerge during implementation. Current literature shows that this has been proved to be true throughout the implementation of Educational and information technology (E&IT) in education in every parts of the world. For the practitioners, undersdanding change is the first step and critical point to move forward. In this study, science teacher educators’ and prospective science teachers’ understanding of E&IT and its usefullness in taeching and learning science were explored by using multiple methods in the case selected. This study includes three secondary preservice science teacher education programmes – i.e. Physics, Chemistry and Biology. The student teachers (STs) from these three programmes are expected to teach their specialist subject in secondary schools – i.e. 15-17 age groupafter their graduation. Results showed that there were some patterns in understanding the use of E&IT in science education among the participants. E&IT was perceived as information sources, presentation tools, facilitator and a medium to change current styles of teaching and learning science. The results were derieved from the participants’ actual practice and their perceptual understanding of the use of E&IT in science education.
Statistical Methods in Topological Data Analysis for Complex, High-Dimensional Data

The utilization of statistical methods an their applications within the new field of study known as Topological Data Analysis has has tremendous potential for broadening our exploration and understanding of complex, high-dimensional data spaces. This paper provides an introductory overview of the mathematical underpinnings of Topological Data Analysis, the workflow to convert samples of data to topological summary statistics, and some of the statistical methods developed for performing inference on these topological summary statistics. The intention of this non-technical overview is to motivate statisticians who are interested in learning more about the subject.
NEUTRON FLUX CHARACTERISATION OF IRRADIATION FACILITIES IN RTP

The Malaysian’s PUSPATI TRIGA Reactor (RTP) achieved its initial criticality on June 28, 1982. The reactor is designed to effectively implement various fields of basic nuclear research, manpower training, and production of radioisotopes. Several past activities on neutronics modelling development and validation of the RTP were carried out using Monte Carlo Code MCNP. In this work, the developed model was used to characterise in-core and beam-ports irradiation facilities of the reactor. The thermal and fast neutron flux distributions in these facilities were determined using MCNP mesh tally method. It was found that the flux as well as its spectral characteristics depended very much on the position of the irradiation facility in the reactor core or in the beam-ports. The maximum neutron flux was found to be in the Central Thimble facility with 1.98E13 nv of thermal neutron. The thermal-to-total flux ratio varies significantly from 0.41 for the in-core facility, 0.58 in the reflector and up to 0.88 in the beam-ports.
COMBAT: a new bitmap index coding algorithm for big data

Bitmap indexing has been widely used in various applications due to its speed in bitwise operations. However, it can consume large amounts of memory. To solve this problem, various bitmap coding algorithms have been proposed. In this paper, we present COMbining Binary And Ternary encoding (COMBAT), a new bitmap index coding algorithm. Typical algorithms derived from Word Aligned Hybrid (WAH) are COMPressed Adaptive indeX (COMPAX) and Compressed “n” Composable Integer Set (CONCISE), which can combine either two or three continuous words after WAH encoding. COMBAT combines both mechanisms and results in more compact bitmap indexes. Moreover, querying time of COMBAT can be faster than that of COMPAX and CONCISE, since bitmap indexes are smaller and it would take less time to load them into memory. To prove the advantages of COMBAT, we extend a theoretical analysis model proposed by our group, which is composed of the analysis of various possible bitmap indexes. Some experimental results based on real data are also provided, which show COMBAT's storage and speed superiority. Our results demonstrate the advantages of COMBAT and codeword statistics are provided to solidify the proof.
Observation-based solar and wind power capacity factors and power densities

Power density is the rate of energy generation per unit of land surface area occupied by an energy system. The power density of low-carbon energy sources will play an important role in mediating the environmental consequences of energy system decarbonization as the world transitions away from high power-density fossil fuels. All else equal, lower power densities mean larger land and environmental footprints. The power density of solar and wind power remain surprisingly uncertain: estimates of realizable generation rates per unit area for wind and solar power span 0.3–47 We m−2 and 10–120 We m−2 respectively. We refine this range using US data from 1990–2016. We estimate wind power density from primary data, and solar power density from primary plant-level data and prior datasets on capacity density. The mean power density of 411 onshore wind power plants in 2016 was 0.50 We m−2. Wind plants with the largest areas have the lowest power densities. Wind power capacity factors are increasing, but that increase is associated with a decrease in capacity densities, so power densities are stable or declining. If wind power expands away from the best locations and the areas of wind power plants keep increasing, it seems likely that wind’s power density will decrease as total wind generation increases. The mean 2016 power density of 1150 solar power plants was 5.4 We m−2. Solar capacity factors and (likely) power densities are increasing with time driven, in part, by improved panel efficiencies. Wind power has a 10-fold lower power density than solar, but wind power installations directly occupy much less of the land within their boundaries. The environmental and social consequences of these divergent land occupancy patterns need further study.
Theory of Mergeability: Safely Merging Two Versions of a Document

As technology becomes more readily available to the public, individuals increasingly have access to multiple machines (e.g., home desktop, office workstation, portable laptop, etc.) frequently moving from one machine to another while working on a particular task. As a result, maintaining and synchronizing different versions of documents on multiple machines is becoming an important problem. In this paper, we propose a theoretical framework to deal with this problem by first introducing reasonable definitions of when two simultaneous changes to the same document can be considered “safely mergeable. ” We then propose new and efficient algorithms to guarantee that only “safely mergeable changes” are made to the document and prove the correctness of the proposed algorithms. Finally, we evaluate the performance of our algorithms by investigating their storage and computational costs using real data.
Comparison of Leadership Levels of Students at the Faculty of Sport Sciences and Other Faculties

Leadership has a great significance in creating high performance and building team loyalty in sport. The purpose of this study is to compare the leadership levels of students studying at the Faculty of Sports Sciences and other faculties. In addition, leadership qualities were examined in terms of the variables of gender and place of stay. A total of 200 students studying at the Faculty of Sports Sciences (n=100; age 21.75±1.99 years) and other faculties (n=100 age; 20.49±1.52 years) participated in this study voluntarily. “Leadership Orientations Questionnaire” developed by Bolman and Deal [1] and adapted into Turkish by Dereli [2] to assess the leadership qualities of students was used as data collection tool. In the sub-dimensions of structural, transformational and charismatic leadership, the scores of faculty of sport sciences students were found to be significantly higher than the scores of the students in other faculties (p<0.01). The average scores of men were found to be higher than those of women in the sub-dimensions of transformational and charismatic leadership (p<0.05). It was concluded that the students studying at the Faculty of Sport Sciences had higher leadership qualities, with men having better leadership qualities.
Gamma-Poisson Dynamic Matrix Factorization Embedded with Metadata Influence

A conjugate Gamma-Poisson model for Dynamic Matrix Factorization incorporated with metadata influence (mGDMF for short) is proposed to effectively and efficiently model massive, sparse and dynamic data in recommendations. Modeling recommendation problems with a massive number of ratings and very sparse or even no ratings on some users/items in a dynamic setting is very demanding and poses critical challenges to well-studied matrix factorization models due to the large-scale, sparse and dynamic nature of the data. Our proposed mGDMF tackles these challenges by introducing three strategies: (1) constructing a stable Gamma-Markov chain model that smoothly drifts over time by combining both static and dynamic latent features of data; (2) incorporating the user/item metadata into the model to tackle sparse ratings; and (3) undertaking stochastic variational inference to efficiently handle massive data. mGDMF is conjugate, dynamic and scalable. Experiments show that mGDMF significantly (both effectively and efficiently) outperforms the state-of-the-art static and dynamic models on large, sparse and dynamic data.
Retrieval of the optical depth and vertical distribution of particulate scatterers in the atmosphere using O 2 A- and B-band SCIAMACHY observations over Kanpur: a case study

Abstract. Due to the well-defined vertical profile of O2 in the atmosphere, the strong A-band (757–774 nm) has long been used to estimate vertical distributions of aerosol/cloud from space. We extend this approach to include part of the O2 B-band (684–688 nm) as well. SCIAMACHY onboard ENVISAT is the first instrument to provide spectral data at moderate resolution (0.2–1.5 nm) in the UV/VIS/NIR including both the O2 A- and B-bands. Using SCIAMACHY specifications, we make combined use of these bands in an optimal estimation algorithm. Theoretical studies show that our algorithm is applicable both over bright and dark surfaces for the retrieval of a lognormal approximation of the vertical profile of particulate matter, in addition to its optical thickness. Synthetic studies and information content analyses prove that such a combined use provides additional information on the vertical distribution of atmospheric scatterers, attributable to differences in the absorption strengths of the two bands and their underlying surface albedos. Due to the high computational cost of the retrieval, we restrict application to real data to a case study over Kanpur through the year 2003. Comparison with AERONET data shows a commonly observed seasonal pattern of haziness, manifesting a correlation coefficient of r = 0.92 for non-monsoon monthly mean AOTs. The retrieved particulate optical thickness is found to be anti-correlated with the relative contrast of the Lambertian equivalent reflectivity (LER) at 682 nm and 755 nm by a coefficient of 0.788, confirming the hypothesis made in Sanghavi et al. (2010). Our case study demonstrates a stable physics-based retrieval of particulate matter using only SCIAMACHY data. The feasibility of our approach is enhanced by the information provided by measurements around the O2 B-band in addition to the A-band. Nonetheless, operational application to SCIAMACHY data remains challenged by radiometric uncertainties, yielding simultaneous retrieval of particle microphysical parameters impracticable and leading to over-reliance on climatological data. Addressing these issues in future instruments similar to SCIAMACHY, coupled with computational resources and speed-up of the current line-by-line radiative transfer calculations, can allow our approach to be extended to the global scale, particularly as it is not limited to dark surfaces.
Determinants of Students Utilisation of Computer Information Retrieval System in Academic Libraries: Evidence from Ghana

A number of educational institutions and libraries have established computerized information retrieval systems (CIRS) to help students to easily identify resources for their academic pursuit. The study investigates and retests the Unified Theory of Adoption and Use of Technology as a model for explaining technology (UTAUT) use among library users in the University of Ghana (UG). A questionnaire with 31 items based on the UTAUT study of (Venkatesh et al. 2003) and analysed on a 7 point Likert Scale was distributed to students using the Balme Library – University of Ghana. The results reveal that many students judge their ability to use the computer information retrieval system to accomplish the specified task as poor due to nonfamiliarity with the system. It is noted that a lot of students also doubt the ability of the system to provide the required responses they are looking for. This may be due to misconceptions from previous experiences or information gained from other people who have not been successful in using the information retrieval system. The study recommends that the Library incorporates the basic skills of interacting with the CIRS in its orientation programme to give students an acceptable perception of the CIRS.
Prediction of surface roughness when end milling Ti6Al4V alloy using adaptive neurofuzzy inference system

Surface roughness is considered as the quality index of themachine parts. Many diverse techniques have been applied in modelling metal cutting processes. Previous studies have revealed that artificial intelligence techniques are novel soft computing methods which fit the solution of nonlinear and complex problems like metal cutting processes. The present study used adaptive neurofuzzy inference system for the purpose of predicting the surface roughness when end milling Ti6Al4V alloy with coated (PVD) and uncoated cutting tools under dry cutting conditions. Real experimental results have been used for training and testing of ANFIS models, and the best model was selected based on minimum root mean square error. A generalized bell-shaped function has been adopted as a membership function for the modelling process, and its numbers were changed from 2 to 5. The findings provided evidence of the capability of ANFIS in modelling surface roughness in end milling process and obtainment of good matching between experimental and predicted results.
Collegiality and performativity in a competitive academic culture

Collegiality is one of the most symbolically significant concepts of higher education and continues to be widely espoused as a core value by members of the academic profession. However, the highly competitive and performative nature of modern higher education means that the conventional values and behaviours associated with collegiality, such as mentoring and consensual decision-making, are coming under increasing pressure. The paper reports on a questionnaire survey of academics within a Faculty of a leading research university in Hong Kong designed to understand perceptions of structural, cultural and behavioural collegiality. These perceptions vary considerably by academic rank and gender with power vested in a mainly male professorial oligarchy. Collegiality appears to be most weakly formed as a behavioural norm and, linked to this finding, the study further indicates how ventriloquizing the values of collegiality has become a performative riff in academic life which, in practice, is increasingly characterised by isolation and individualised competition.
Derivation of rainfall thresholds for pluvial flood risk warning in urbanised areas

• Development of an operational tool for pluvial flooding warning in an urban area based on off-line rainfall thresholds derived by coupling a rainfall–runoff modelling and a hydraulic routing • Inundation criteria has been considered instead of the usual flooding flow in order to assess threshold rainfall in urban areas • The proposed methodology includes the diversity of rainfall threshold in urbanized areas
Adaptive Neuro-Sliding Mode Control of PUMA 560 Robot Manipulator

: The classical sliding mode control (SMC) is a robust control scheme widely used for dealing with nonlinear systems uncertainties and disturbances. However, the conventional SMC major drawback in real applications is the chattering phenomenon problem, which involves extremely high control activity due to the switched con-trol input. To overcome this handicap, a pratical design method that combines an adaptive neural network and sliding mode control principles is proposed in this paper. The controller design is divided into two phases. First, the chattering phenomenon is removed by replacing the sign function included in the switched control by a continuous smooth function; basing on Lyapounov stability theorem. Then, an adaptive linear neural network, that has the role of online estimate the equivalent control in the neighborhood of the sliding manifold, is developed when the controlled plant is poorly modeled. Simulation results show clearly the satisfactory chattering free tracking performance of proposed controller when it is applied for the joints angular positions control of a 6-DOF PUMA 560 robot arm.
Microbial degradation of isosaccharinic acid under conditions representative for the far field of radioactive waste disposal facilities

Abstract It is UK Government policy to dispose of higher activity radioactive waste through geological disposal into an engineered deep underground geological disposal facility (GDF; DECC, 2014). Those wastes include low-level (LLW) and intermediate-level (ILW) radioactive wastes that are very heterogeneous, containing a range of inorganic and organic materials, the latter including cellulosic items. After closure of the GDF, eventual resaturation with groundwater is expected, resulting in the development of a hyperalkaline environment due to the proposed use of a cementitious backfill. Under these high-pH conditions, cellulose is unstable and will be degraded chemically, forming a range of water-soluble, low molecular weight compounds, of which the most abundant is isosaccharinic acid (ISA). As ISA is known to form stable soluble complexes with a range of radionuclides, thereby increasing the chance of radionuclide transport, the impact of microbial metabolism on this organic substrate was investigated to help determine the role of microorganisms in moderating the transport of radionuclides from a cementitious GDF. Anaerobic biodegradation of ISA has been studied recently in high-pH cementitious ILW systems, but less work has been done under anaerobic conditions at circumneutral conditions, more representative of the geosphere surrounding a GDF. Here we report the fate of ISA in circumneutral microcosms poised under aerobic and anaerobic conditions; the latter with nitrate, Fe(III) or sulfate added as electron acceptors. Data are presented confirming the metabolism of ISA under these conditions, including the direct oxidation of ISA under aerobic and nitrate-reducing conditions and the fermentation of ISA to acetate, propionate and butyrate prior to utilization of these acids during Fe(III) and sulfate reduction. The microbial communities associated with these processes were characterized using 16S rRNA gene pyrosequencing. Methane production was also quantified in these experiments, and the added electron acceptors were shown to play a significant role in minimizing methanogenesis from ISA and its breakdown products.
A Multimodal Attention Mechanism for Autonomous Mobile Robotics

Whatever the mission of an autonomous mobile robot is, attention is a helpful cognitive capability when dealing with real world environments. In this paper we present a novel control architecture which enables an integrated and efficient filtering of multiple modality sensory information. The concept of context is introduced as the set of criteria that determines what sensory information is relevant to the current mission. The proposed attention mechanism uses these contexts as a mean to adaptively select the constrained cognitive focus of the robot within the vast multimodal sensory space available. This approach for artificial attention is tested in the domain of autonomous mapping.
Help for the "Fourth-Grade Slump"--SRQ2R Plus Instruction in Text Structure or Main Idea.

Elementary school students’ ability to comprehend and study expository material begins to be a major concern primarily in the fourth grade. Chall’s (1983) characterization of this period as the “fourth grade slump” (p. 67) remains a valid observation, because teachers still report that while children continue to show ability to read narrative material during this period they are unable to completely read and understand their content area textbooks.
Efficient Audit Service Outsourcing for Data Integrity in Clouds

Cloud-based outsourced storage relieves the client’s burden for storage management and maintenance by providing a comparably low-cost, scalable, locationindependent platform. However, the fact that clients no longer have physical possession of data indicates that they are facing a potentially formidable risk for missing or corrupted data. To avoid the security risks, audit services are critical to ensure the integrity and availability of outsourced data and to achieve digital forensics and credibility on cloud computing. Provable data possession (PDP), which is a cryptographic technique for verifying the integrity of data without retrieving it at an untrusted server, can be used to realize audit services. In this paper, profiting from the interactive zero-knowledge proof system, we address the construction of an interactive PDP protocol to prevent the fraudulence of prover (soundness property) and the leakage of verified data (zeroknowledge property). We prove that our construction holds these properties based on the computation Diffie– Hellman assumption and the rewindable black-box knowledge extractor. We also propose an efficient mechanism with respect to probabilistic queries and periodic verification to reduce the audit costs per verification and implement abnormal detection timely. In addition, we present an efficient method for selecting an optimal parameter value to minimize computational overheads of cloud audit services. Our experimental results demonstrate the effectiveness of our approach.