Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effects of Soil Type, Particle Size, Temperature, and Moisture on Reproduction of Belonolaimus longicaudatus.

Effects of soil type, particle size, temperature, and moisture on the reproduction of Belonolaimus longicaudatus were investigated under greenhouse conditions. Nematode increases occurred only in soils with a minimum of 80% sand and a maximum of 10% clay. Optimum soil particle size for reproduction of the Tarboro, N.C. and Tifton, Ga. populations of the nematode was near that of 120-370 mum (65-mesh) silica sand. Reproduction was greatest at 25-30 C. Some reproduction by the Tifton, Ga. population occurred at 35 C, whereas the Tarboro, N.C. population declined, as compared to the initial inoculum. Both populations reproduced slightly at 20 C. Nematode reproduction was greater at a moisture level of 7% than at a high of 30% or a low of 2%. Reproduction occurred at the high moisture level only when the nutrient solution was aerated.
2016 Ieee International Conference on Big Data (big Data) Urban Human Mobility Data Mining: an Overview

—Understanding urban human mobility is crucial for epidemic control, urban planning, traffic forecasting systems and, more recently, various mobile and network applications. Nowadays, a variety of urban human mobility data have been gathered and published. Pervasive GPS data can be collected by mobile phones. A mobile operator can track people's movement in cities based on their cellular network location. This urban human mobility data contains rich knowledge about locations and can help in addressing many urban challenges such as traffic congestion or air pollution problems. In this article, we survey recent literature on urban human mobility from a data mining view: from the data collection and cleaning, to the mobility models and the applications. First, we summarize recent public urban human mobility data sets and how to clean and preprocess such data. Second, we describe recent urban human mobility models and predictors, e.g., the deep learning predictor, for predicting urban human mobility. Third, we describe how to evaluate the models and predictors. We conclude by considering how applications can utilize the mobility models and predictive tools for addressing city challenges.
M 2 M Traffic and Models

Different from the traditional human-type communications (HTC) for which 3G wireless networks are currently designed and optimized for, machine-type communication MTC (or Machine to Machine (M2M) communications) is seen as a form of data communication, among devices and/or from devices to a set of servers, that do not necessarily require human interaction [1]. Such MTC is also about collecting and distributing the meaningful data efficiently, often in real time, managing connected devices, providing back-end connectivity anywhere and anytime and consequently enabling creation of the so-called Internet of Things (IoT). At the present time, the most interesting applications from the commercial point of view are related to intelligent transport, smart meters (automatic electricity, water and gas meters reading) and tracking and tracing in general. However, the M2M application space is vast and includes security, health monitoring, remote management and control, distributed/mobile computing, gaming, industrial wireless automation, and ambient assisted living.
Extending the sRNAome of Apple by Next-Generation Sequencing

The global importance of apple as a fruit crop necessitates investigations into molecular aspects of the processes that influence fruit quality and yield, including plant development, fruit ripening and disease resistance. In order to study and understand biological processes it is essential to recognise the range of molecules, which influence these processes. Small non-coding RNAs are regulatory agents involved in diverse plant activities, ranging from development to stress response. The occurrence of these molecules in apple leaves was studied by means of next-generation sequencing. 85 novel microRNA (miRNA) gene loci were predicted and characterized along with known miRNA loci. Both cis- and trans-natural antisense transcript pairs were identified. Although the trans-overlapping regions were enriched in small RNA (sRNA) production, cis-overlaps did not seem to agree. More than 150 phased regions were also identified, and for a small subset of these, potential miRNAs that could initiate phasing, were revealed. Repeat-associated siRNAs, which are generated from repetitive genomic regions such as transposons, were also analysed. For this group almost all available repeat sequences, associated with the apple genome and present in Repbase, were found to produce siRNAs. Results from this study extend our current knowledge on apple sRNAs and their precursors significantly. A rich molecular resource has been created and is available to the research community to serve as a baseline for future studies.
UBH 3: an anthropomorphic hand with simplified endo-skeletal structure and soft continuous fingerpads

The paper describes work in progress at the University of Bologna concerning the design of a new anthropomorphic robot hand. The hand is based on the modular assembly of articulated fingers that adopt an original configuration of their structure, made with rigid links connected by elastic hinges that are coaxially crossed by flexible tendons. This innovative design is suitable to host distributed sensory equipment and continuous compliant cover, allowing a high level of anthropomorphism together with great structural simplification, reliability enhancement and cost reduction. Furthermore, the proposed solution is very flexible, as it can be adapted to many different hand configurations and is not dependent on a particular type of actuation, being compatible with future availability of any kind of artificial muscles.
CAHIER DU LAMSADE 303 Mars 2011 Exponential approximation schemata for some network design problems

We study approximation of some well-known network design problems such as traveling salesman problem (for both minimization and maximization versions) and min steiner tree, by moderately exponential algorithms. The general goal of the issue of moderately exponential approximation is to catch-up on polynomial inapproximability, by providing algorithms achieving, with worst-case running times importantly smaller than those needed for exact computation, approximation ratios unachievable in polynomial time.
Wind turbine generators: Conventional and emerging technologies

This paper discusses the currently used generator systems in wind energy conversion systems and some of the newer concepts with their technical features. The Brushless doubly fed induction generator, Brushless doubly fed reluctance generator and the Switched reluctance generator are viable alternatives for wind power applications. This paper also highlights the hybrid wind generator solutions which is an emerging trend in hybrid renewable energy solutions. Using the appropriate control techniques, these generator technologies unlike the conventional wind turbine generator can produce constant wind power irrespective of the changes in velocity of wind speed. This has tremendous application in Africa as the installed capacity increases and the need to provide remote communities with electricity remains paramount. The merits and demerits of the various technologies are uniquely grouped in a novel way to aid decision making based on available resources.
Housing prices, stock prices and the US economy

ABSTRACT This paper studies the relationship between housing prices, stock prices, interest rates and aggregate output in the US using monthly data from 1993 to 2014. Evidence from causality tests and a variance decomposition procedure suggest that stock prices have a much larger effect on aggregate output in the US economy than do either housing prices or interest rates. Instead, the wealth effect created by changes in stock prices has a relatively large impact on US aggregate output. Separate estimations and variance decompositions for the sample periods 1993–2001, 2002–2008 and 2009–2014 show that the impact of housing prices relative to stock prices has been waning over time.
An Energy Efficient Chain-Based Clustering Routing Protocol for Wireless Sensor Networks

Wireless sensor network consisting of a large number of sensors is effective for gathering data in a variety of environments. Since the sensors operate on battery of limited power, it is a challenging task to design an efficient routing scheme which can minimize the delay while offering high energy efficiency and long network lifetime. In this paper we propose a new routing protocol and data gathering scheme in which the sensor nodes form chains in each cluster. The cluster and chain construction occur only once, and the cluster-head rotates locally inside the cluster without re-clustering. Simulation results show that the proposed routing scheme significantly reduces energy consumption and increases the lifetime of sensor network compared to other hierarchical routing schemes such as Low-Energy Adaptive Clustering Hierarchy (LEACH) and Power-Efficient Gathering in Sensor Information System (PEGASIS).
Link Prediction and Denoising in Netowrks

Link Prediction and Denoising in Netowrks by Yun-Jhong Wu Co-Chairs: Professor Elizaveta Levina and Professor Ji Zhu Network data represent connections between units of interests, but are often noisy and/or include missing values. This thesis focuses on denoising network data via inferring underlying network structure from an observed noisy realization. The observed network data can be viewed as a single random realization of an unobserved latent structure, and our general approach to estimating this latent structure is based factorizing it into a product of interpretable components, with structural assumptions on the components determined by the nature of the problem. We first study the problem of predicting links when edge features are available, or node features that can be converted into edge features. We propose a regression-type model to combine information from network structure and edge features. We show that estimating parameters in this model is straightforward and the estimator enjoys excellent theoretical performance guarantees. Another direction we study is predicting links in time-stamped dynamic networks. A common approach to modeling networks observed over time is aggregating the networks to a few snapshots, which reduces computational complexity, but also loses information. We address this limitation through a dynamic network model based on tensor factorization, which simultaneously captures time trends and the graph structure of dynamic networks without aggregating over time. We develop an efficient algorithm to fit this model and demonstrate the method performs well numerically. The last contribution of this thesis is link prediction for ego-networks. Ego-networks are constructed by recording all friends of a particular user, or several users, which is widely used in survey-based social data collection. There are many methods for filling in missing data in a matrix when entries are missing independently at random, but here it is more appropriate to assume that whole rows of the matrix are missing (corresponding to users), whereas other rows are observed completely. We develop an approach to estimate missing links in this scenario via subspace estimation, exploiting potential low-rank structure common in networks. We obtain theoretical bounds on the estimator’s performance and demonstrate it significantly outperforms many widely used benchmarks in both simulated and real networks.
The " Pure Contagion " Effect between SHIBOR and Multinational Benchmark Interest Rates

DOI: 10.21276/sjet.2017. 5.10. 5 Abstract: By the Crisis contagion canonical model put forward by Pesaran & Pick, this paper verified whether there is a pure contagion effect between the SHIBOR and the benchmark interest rates of several representative countries, and measured the scale of the effect. Finally, it is found that, the benchmark interest rates of developed countries except Japan have positive pure contagion effects on SHIBOR in varying degrees, while the SHIBOR has no significant pure contagion to the benchmark interest rates in developed countries except Japan; different from the empirical results of developed countries, the benchmark interest rate of BRICs member states has negative pure contagion effects of varying degrees to SHIBOR, but the SHIBOR has a more negative pure contagion effects on the benchmark interest rate of BRICs member states.
Understanding the Experiences of Anxiety in Community Dwelling Older Adults—Understanding Anxiety in Older Adults

Objectives: Anxiety is commonly reported as being experienced by older adult patients. However most of the theories on anxiety in older adults are developed from clinical measures rather than open-ended questionnaires. Consequently, little is known about the day to day experiences of anxiety in the lives of older adults, and the functional impairment that may result. Method: Community dwelling older adults (n = 135) were administered an open-ended questionnaire eliciting their experiences of anxiety using a cognitive behavioural framework. Directed content analysis was applied to discover the shared experiences of anxiety in older adults. Results: Although 64% of older adults reported avoidance behaviour that appeared anxiety driven, they generally denied experiencing anxiety themselves. Thought content and processes were idiosyncratic however commonalities were thinking positively (34%), problem solving (31%), rumination (31%) and difficulty concentrating (19%). A broad range of physical symptoms including those that may relate to medical conditions and depression were reported as resulting from anxiety, most commonly headaches (26%) and gastrointestinal disturbances (26%). Conclusion: Anxiety driven behaviours were common and appeared to negatively impact their quality of life through avoidance behaviours. Older adults may benefit from education to destigmatise the experiences of anxiety and improve reporting of functional impairment due to anxiety.
Keywords: cardiovascular outcomes, eicosapentaenoic acid, fibric acids, niacin, omega-3 fatty acids, triglycerides Abbreviations AACE = American Association of Clinical Endocrinologists; ACCORD = Action to Control Cardiovascular Risk in Diabetes; AIM-HIGH = Atherothrombosis Intervention in Metabolic

© 2016 AACE ENDOCRINE PRACTICE Rapid Electronic Article in Press Rapid Electronic Articles in Press are preprinted manuscripts that have been reviewed and accepted for publication, but have yet to be edited, typeset and finalized. This version of the manuscript will be replaced with the final, published version after it has been published in the print edition of the journal. The final, published version may differ from this proof. DOI:10.4158/EP161445.RA © 2016 AACE
Modelling a Hybrid Energy-Efficient Architecture for Parallel Disk Systems

In the past decade parallel disk systems have been highly scalable and able to alleviate the problem of disk I/O bottleneck, thereby being widely used to support a wide range of dataintensive applications. Optimizing energy consumption in parallel disk systems has strong impacts on the cost of backup power-generation and cooling equipment, because a significant fraction of the operation cost of data centres is due to energy consumption and cooling. Although flash memory is very energyefficient compared to disk drives, flash memory is expensive. Thus, it is not a cost-effective way to make use of large flash memory to build energy-efficient parallel disk systems. To address this problem, in this paper we proposed a hybrid disk architecture or HYBUD that integrates a non-volatile flash memory with buffer disks to build cost-effective and energyefficient parallel disk systems. While the most popular data sets are cached in flash memory, the second most popular data sets are cached in buffer disks. HYBUD is energy efficient because flash memory and buffer disks can serve a majority of incoming disk requests, thereby keeping data disks in low-power state for longer period times. Furthermore, HYBUD is cost-effective, since a huge amount of popular data can be cached in buffer disks in addition to the flash memory. Experimental results demonstratively show that compared with two existing non-hybrid architectures, HYBUD provides significant energy savings for parallel disk
Reduced platelet cytochrome c oxidase activity in Alzheimer's disease

We evaluated a simplified method for preparation and analysis of platelet cytochrome c oxidase activity in Alzheimer's disease (AD) and control patients. Mean cytochrome c oxidase activity in controls (n = 17) was 0.233 sec−1/mg whereas mean cytochrome c oxidase activity in Alzheimer patients (n = 19) was 0.193 sec−1/mg, p=0.033. Complex III (ubiquinol:cytochrome c oxidoreductase), complex II (succinic dehydrogenase), and citrate synthase were all assayed as internal controls and were not significantly different in controls and Alzheimer patients. There is a relatively specific loss of platelet cytochrome c oxidase activity in Alzheimer disease patients.
Chronic Renal Disease : Orthomolecular Ramifications

Introduction Increasingly, human kidneys are under assault from environmental toxins as well as an array of diseases that place them at risk of ultimately failing. Eleven percent of American adults now show evidence of chronic kidney disease, with over 400,000 afflicted with end-stage kidney disease. Over a third of those cases are caused by diabetes, and the remainder by high blood pressure and other conditions, including genetic ones. Diabetes is epidemic, spurred in part by changing eating patterns and obesity. It currently kills more people than AIDS. The epidemic will worsen. The World Health Organization and the International Diabetes Foundation have predicted that by the year 2030, more than twice as many people worldwide will suffer from this devastating disease as now do.
volumechange and strength characteristics of normal and high-strength mortars: effect of aggregate type and water-binder ratio

Abstract This study investigated the impact of aggregate type on the volumechanges including drying shrinkage, autogenous shrinkage, and swelling for mortars made with different w/b ratios. The main properties including compressive and flexural strengths were also studied. For this purpose, three groups of mixes were prepared: two of them were prepared with 0.2 and 0.3 w/b ratios which were classified as high-strength mortars, and for comparison, a one group of normal-strength mortars was prepared with a 0.5 w/c ratio. Each group consisted of three mixes made with natural sand (NS), limestone aggregate (LA), or recycled concrete aggregate (RCA). Within each group, the LA mixes generally showed the lowest drying shrinkage and autogenous shrinkage regardless of the w/b ratio, while the greatest ones were observed for RCA mortars. The results also indicated that the group of mixes of the 0.2 w/b ratio gave the highest autogenous shrinkage.
Novel Regulation of Cortical Acetylcholine Release and Cognitive Behavior

Page 2 2 DEDICATION I wholeheartedly dedicate this work to my husband, David, my parents, and the rest of my family for their continued care, love, and encouragement throughout my life. ACKNOWLEDGEMENTS First and foremost, I would like to express my gratitude towards Dr. Bruno for his guidance, mentorship, and inspiration. For the past year, I have had the privilege of working in his laboratory and learning about the neuropsychopharmacology of schizophrenia. He has served as an excellent role model of perseverance and dedication, and the opportunities that I have experienced will last throughout my lifetime. The knowledge and lessons that I have gained through his mentorship will be invaluable as I further my education. I would like to thank the College of Biological Sciences, Department of Microbiology for its financial contribution to my undergraduate education through the Anne H. Baumhofer Scholarship. In addition, I would also like to thank the college for specifically funding my undergraduate research through the Dean's Undergraduate Research Fund. My gratitude to The College of Social and Behavioral Sciences for contributing to this research project through a grant awarded in the 2007 scholarship competition. Additionally, I would like to thank the College of the Arts and Sciences for contributing to my undergraduate education through the ASC Undergraduate Research Scholarship Competition in the fall of 2007. I would also like to express my gratitude to all the members of the lab for their help and collaboration with so many different aspects of my project: Department of Microbiology, and my honors advisor, Joanna Spanos, through the College of Arts and Sciences Honors Department, for their guidance throughout my undergraduate education. Finally, I would like to thank Dr. Randy Nelson of the Psychology Department and Dr. T.V. Rajanbabu of the Chemistry Department for donating their time and serving as committee members for my thesis defense.
Classification of Displacive Transformations : What is a Martensitic Transformation ?

The displacive transformation classification proposed at ICOMAT 79 [1] is reviewed in light of recent progress in mechanistic understanding. Issues considered include distinctions between shuffle transformation vs. self-accommodating shear, dilatation vs. shear-dominant transformation, and nucleated vs. continuous transformation.
Using inheritance in a metadata based approach to data quality assessment

Currently available data quality tools provide development environments that significantly decrease the effort in dealing with common data problems, such as those related with attribute domain validation, syntax checking, or value matching against a reference master data repository. On the contrary, more complex and specific data quality functionalities, whose requirements usually derive from application domain business rules, have to be developed from scratch, usually leading to high costs of development and maintenance. This paper introduces the concept of inheritance in a metadata-driven approach to simplified data quality rule management. The approach is based on the belief that even complex data quality rules very often adhere to recurring patterns that can be encoded and encapsulated as reusable, abstract templates. The approach is supported by a metamodel developed on top of OMG's Common Warehouse Metamodel, herein extended with the ability to derive new rule patterns from existing ones, through inheritance. The inheritance metamodel is presented in UML and its application is illustrated with a running example.