Miracle-dz/UniFAR-FTUs huggingface dataset:
Evolutionary impact assessment: accounting for evolutionary consequences of fishing in an ecosystem approach to fisheries management

Managing fisheries resources to maintain healthy ecosystems is one of the main goals of the ecosystem approach to fisheries (EAF). While a number of international treaties call for the implementation of EAF, there are still gaps in the underlying methodology. One aspect that has received substantial scientific attention recently is fisheries-induced evolution (FIE). Increasing evidence indicates that intensive fishing has the potential to exert strong directional selection on life-history traits, behaviour, physiology, and morphology of exploited fish. Of particular concern is that reversing evolutionary responses to fishing can be much more difficult than reversing demographic or phenotypically plastic responses. Furthermore, like climate change, multiple agents cause FIE, with effects accumulating over time. Consequently, FIE may alter the utility derived from fish stocks, which in turn can modify the monetary value living aquatic resources provide to society. Quantifying and predicting the evolutionary effects of fishing is therefore important for both ecological and economic reasons. An important reason this is not happening is the lack of an appropriate assessment framework. We therefore describe the evolutionary impact assessment (EvoIA) as a structured approach for assessing the evolutionary consequences of fishing and evaluating the predicted evolutionary outcomes of alternative management options. EvoIA can contribute to EAF by clarifying how evolution may alter stock properties and ecological relations, support the precautionary approach to fisheries management by addressing a previously overlooked source of uncertainty and risk, and thus contribute to sustainable fisheries.
Isolation and Characterization of CD 34 + Blast-Derived Exosomes in Acute Myeloid Leukemia

Exosomes are membrane-bound vesicles found in all biological fluids. AML patients’ plasma collected at diagnosis contains elevated exosome levels relative to normal donor (ND) plasma. The molecular profile of AML exosomes changes in the course of therapy and may serve as a measure of disease progression or response to therapy. However, plasma contains a mix of exosomes derived from various cell types. To be able to utilize blast-derived exosomes as biomarkers for AML, we have developed an immunoaffinity-based capture method utilizing magnetic microbeads coated with anti-CD34 antibody (Ab). This Ab is specific for CD34, a unique marker of AML blasts. The capture procedure was developed using CD34+ exosomes derived from Kasumi-1 AML cell culture supernatants. The capture capacity of CD34microbeads was shown to linearly correlate with the input exosomes. A 10 uL aliquot of CD34 microbeads was able to capture all of CD34+ exosomes present in 100–1,000 uL of AML plasma. The levels of immunocaptured CD34+ exosomes correlated with the percentages of CD34+ blasts in the AML patients’ peripheral blood. The immunocaptured exosomes had a typical cup-shaped morphology by transmission electron microscopy, and their molecular cargo was similar to that of parental blasts. These exosomes were biologically-active. Upon co-incubation with natural killer (NK) cells, captured blast-derived exosomes down-regulated surface NKG2D expression, while non-captured exosomes reduced expression levels of NKp46. Our data provide a proof-ofprinciple that blast-derived exosomes can be quantitatively recovered from AML patients’ plasma, their molecular profile recapitulates that of autologous blasts and they retain the ability to mediate immune suppression. These data suggest that immunocaptured blast-derived exosomes might be useful in diagnosis and/or prognosis of AML in the future. Citation: Hong CS, Muller L, Boyiadzis M, Whiteside TL (2014) Isolation and Characterization of CD34+ Blast-Derived Exosomes in Acute Myeloid Leukemia. PLoS ONE 9(8): e103310. doi:10.1371/journal.pone. 0103310 Editor: Zhuang Zuo, UT MD Anderson Cancer Center, United States of America Received April 30, 2014; Accepted June 30, 2014; Published August 5, 2014 Copyright: 2014 Hong et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability: The authors confirm that all data underlying the findings are fully available without restriction. All relevant data are within the paper. Funding: National Institutes of Health, USA grants PO1-CA109688 and R01-CA168628 to TLW (www.nih.gov). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors have declared that no competing interests exist. * Email: whitesidetl@upmc.edu
University of Huddersfield Repository A cognitive architecture-based model of graph comprehension

I present a model of expert comprehension performance for 2 × 2 “interaction” graphs typically used to present data from two-way factorial research designs. Developed using the ACT- R cognitive architecture, the model simulates the cognitive and perceptual operations involved in interpreting interaction graphs and provides a detailed characterisation of the information extracted from the diagram, the prior knowledge re- quired to interpret interaction graphs, and the knowledge generated during the comprehension process. The model produces a scan path of attention ﬁxations and a symbolic description of the interpretation which can be compared to human eye movement and verbal protocol data respectively, provides an account of the strategic processes that control comprehension, and makes explicit what underlies the differences between expert and novice performance.
Neuroimaging, a new tool for investigating the effects of early diet on cognitive and brain development

Nutrition is crucial to the initial development of the central nervous system (CNS), and then to its maintenance, because both depend on dietary intake to supply the elements required to develop and fuel the system. Diet in early life is often seen in the context of “programming” where a stimulus occurring during a vulnerable period can have long-lasting or even lifetime effects on some aspect of the organism's structure or function. Nutrition was first shown to be a programming stimulus for growth, and then for cognitive behavior, in animal studies that were able to employ methods that allowed the demonstration of neural effects of early nutrition. Such research raised the question of whether nutrition could also programme cognition/brain structure in humans. Initial studies of cognitive effects were observational, usually conducted in developing countries where the presence of confounding factors made it difficult to interpret the role of nutrition in the cognitive deficits that were seen. Attributing causality to nutrition required randomized controlled trials (RCTs) and these, often in developed countries, started to appear around 30 years ago. Most demonstrated convincingly that early nutrition could affect subsequent cognition. Until the advent of neuroimaging techniques that allowed in vivo examination of the brain, however, we could determine very little about the neural effects of early diet in humans. The combination of well-designed trials with neuroimaging tools means that we are now able to pose and answer questions that would have seemed impossible only recently. This review discusses various neuroimaging methods that are suitable for use in nutrition studies, while pointing out some of the limitations that they may have. The existing literature is small, but examples of studies that have used these methods are presented. Finally, some considerations that have arisen from previous studies, as well as suggestions for future research, are discussed.
A Protein Isolate from Moringa oleifera Leaves Has Hypoglycemic and Antioxidant Effects in Alloxan-Induced Diabetic Mice

Moringa oleifera has been used in traditional medicine to treat diabetes. However, few studies have been conducted to relate its antidiabetic properties to proteins. In this study, a leaf protein isolate was obtained from M. oleifera leaves, named Mo-LPI, and the hypoglycemic and antioxidant effects on alloxan-induced diabetic mice were assessed. Mo-LPI was obtained by aqueous extraction, ammonium sulphate precipitation and dialysis. The electrophoresis profile and proteolytic hydrolysis confirmed its protein nature. Mo-LPI showed hemagglutinating activity, cross-reaction with anti-insulin antibodies and precipitation after zinc addition. Single-dose intraperitoneal (i.p.) administration of Mo-LPI (500 mg/kg·bw) reduced the blood glucose level (reductions of 34.3%, 60.9% and 66.4% after 1, 3 and 5 h, respectively). The effect of Mo-LPI was also evidenced in the repeated dose test with a 56.2% reduction in the blood glucose level on the 7th day after i.p. administration. Mo-LPI did not stimulate insulin secretion in diabetic mice. Mo-LPI was also effective in reducing the oxidative stress in diabetic mice by a decrease in malondialdehyde level and increase in catalase activity. Mo-LPI (2500 mg/kg·bw) did not cause acute toxicity to mice. Mo-LPI is a promising alternative or complementary agent to treat diabetes.
Traffic engineering framework with machine learning based meta-layer in software-defined networks

Software-defined networks is an emerging architecture that separates the control plane and data plane. This paradigm enables flexible network resource allocations for traffic engineering, which aims to gain better network capacity and improved delay and loss performance. As we know, many heuristic algorithms have been developed to solve the dynamic routing problem. Whereas they lead to a high computational time cost, which results in a crucial problem whether such a heuristic approach to this NP-complete problem is of any use in practice. This paper proposes a framework with supervised machine learning based meta-layer to solve the dynamic routing problem in real time. We construct multiple machine learning modules in meta-layer, whose training set is consist of heuristic algorithm's input and its corresponding output. We show that after training process, the meta-layer will give heuristic-like results directly and independently, substituting for the time-consuming heuristic algorithm. We demonstrate, by analysis and simulation, our framework effectively enhance the network performance. Finally, the meta-layer architecture is quite universal and can be extended in numerous ways to accommodate a variety of traffic engineering scenarios in the network.
Bridging Music via Sound Effects

The prevalence of digital technologies allows people to easily create and share their own media contents, but sometimes we do not have handy tools to manipulate the media we want to create. For example, while creating personal films, a user may separately find the music segment that matches each part of the video, and then concatenate the segments to create the soundtrack that matches the visual contents along the timeline. However, one may lose the temporal coherence between consecutive music segments if the user just choose music segments that best match parts of the video contents. In this study, we focus on how to smoothly connect not-so-coherent music clips and make the transition natural and pleasant to hear. In particular, we improve the temporal smoothness by bar alignment and dual tempo adjustment. To further fit in with the transition between clips, we incorporate "sound effect insertion" which is a commonly used technique in popular song composition/remixing. In order to provide pleasant listening experience and systematically analyze the effectiveness of the proposed music bridging method, we have conducted specifically designed experiments to collect subjective opinions and reduce the cognitive loads of the participants. The experimental results indicate that with proper arrangement for creating smooth transition via tempo adjustment and sound effect insertion, the listening experience can be largely enhanced.
The Ides Framework: A Case Study In Development Of A Parallel Discrete-event Simulation System

This tutorial describes considerations in the design and development of the IDES parallel simulation system. IDES is a Java-based parallel/distributed simulation system designed to support the study of complex large-scale enterprise systems. Using the IDES system as an example, the authors discuss how anticipated model and system constraints molded the design decisions with respect to modeling, synchronization, and communication strategies.
Data Hiding & Visual Cryptography : A Review

In this paper, We emphasize on how to improve capacity of image carrier by hiding text data using combine approach of visual cryptography with data hiding technique. And to fulfill this requirement, the proposed system highlights a novel approach of an Optimize Multiple Bits Replacement Scheme with Multi-Layer Multi-Shares Visual Cryptography for Data Hiding. The proposed system hides textual data in a image carrier and achieve its encryption/decryption after going through visual cryptography. The overall effort of the proposed scheme is the achievement of encrypting/extracting multiple secret images and reference images from sharing images at different scale levels. The main aim of the proposed model is to improve security, reliability and efficiency of secret message by the combine use of data hiding and visual cryptography method. KeywordsVisual Cryptography, Data Hiding, Multi-layer Multi-Shares, Data Security, Optimize
Integrating Distributional Lexical Contrast into Word Embeddings for Antonym-Synonym Distinction

We propose a novel vector representation that integrates lexical contrast into distributional vectors and strengthens the most salient features for determining degrees of word similarity. The improved vectors significantly outperform standard models and distinguish antonyms from synonyms with an average precision of 0.66-0.76 across word classes (adjectives, nouns, verbs). Moreover, we integrate the lexical contrast vectors into the objective function of a skip-gram model. The novel embedding outperforms state-of-the-art models on predicting word similarities in SimLex-999, and on distinguishing antonyms from synonyms.
A Possible Effect of Electromagnetic Radiation from Mobile Phone Base Stations on the Number of Breeding House Sparrows (Passer domesticus)

A possible effect of long-term exposure to low-intensity electromagnetic radiation from mobile phone (GSM) base stations on the number of House Sparrows during the breeding season was studied in six residential districts in Belgium. We sampled 150 point locations within the 6 areas to examine small-scale geographic variation in the number of House Sparrow males and the strength of electromagnetic radiation from base stations. Spatial variation in the number of House Sparrow males was negatively and highly significantly related to the strength of electric fields from both the 900 and 1800 MHz downlink frequency bands and from the sum of these bands (Chi2-tests and AIC-criteria, P < 0.001). This negative relationship was highly similar within each of the six study areas, despite differences among areas in both the number of birds and radiation levels. Thus, our data show that fewer House Sparrow males were seen at locations with relatively high electric field strength values of GSM base stations and therefore support the notion that long-term exposure to higher levels of radiation negatively affects the abundance or behavior of House Sparrows in the wild.
A New Nonlinear Model of Contact Normal Force

This paper presents a new nonlinear model of the normal force that arises during compliant contact between two spheres, or between a sphere and a flat plate. It differs from a well-known existing model by only a single term. The advantage of the new model is that it accurately predicts the measured values of the coefficient of restitution between spheres and plates of various materials, whereas other models do not.
Collaborative Annotation of Videos Relying on Weak Consistency

This work discusses a distributed interactive video system that supports video annotation using simultaneous hyperlinking by multiple users. The users mark and annotate objects within the video with links to other media such as text, images, websites, or other videos. Annotations are visualized on the client user interface as an overlay close to the objects. Our system is intuitive to use; for example, it contains automatic object-tracking functionality that correctly positions the annotations, even when the form or location of an object changes. Thus, our first contribution discusses the adaptive object-tracking algorithm used for this repositioning. It shows improved precision and reliability in comparison to nonadaptive algorithms. A second key issue is to keep the system responsive when the number of concurrent annotators increases. Thus, we rely on the concept of eventual consistency between different network entities. While this weak form of consistency allows temporary inconsistencies, it ensures that a consistent state can be reached. Thus, the second contribution is the design and evaluation of our distributed interactive video system, which relies on the weak consistency paradigm.
Occipito-cervical meningioma in pregnancy

Meningiomas are tumors that are believed to be derived from the cells and vascular elements of the meninges, and grow intracranially or in the vertebral canal. They are most common in women. The growth of meningiomas is stimulated by female sex hormones and thus may progress more rapidly in pregnant women and in women with breast cancer. The patient was a pregnant 39-year old woman (G4P3A0) of 8 months gestation. The clinical symptoms and signs were progressive upper motor neuron quadriparesis, diminished sensory functions from the level of C2 downwards, and loss of bladder and rectal control. Brain and cervical computed tomography (CT) scans done 2 months before admission showed no abnormalities. Induced delivery was terminated by forceps extraction, resulting in a baby of 2,100 g with Apgar score 7/9. After delivery, postcontrast magnetic resonance imaging (MRI) showed a large contrast-enhancing tumor mass of intradural-extramedullary location in the right occipito-cervical region. The tumor had a meningeal tail, extended into the right posterior fossa and caudally to the level of C3, with compression of the spinal cord. The patient underwent a nontotal resection to remove a tumor that microscopically had the features of a meningioma.
UWB localization on indoor MIMO channels

The paper focuses on the joint use of a UWB system along with antenna arrays for localization purposes of mobile terminals in an indoor MIMO environment. The proposed localization method estimates the direction of arrival (DoA) by evaluating the delays of the received UWB signals impinging on the antenna array. Correlation processing in the time domain of the UWB impulse wavefronts yields precise temporal resolution which provide a fine estimation of DOAs if it is combined with an uniform linear antenna array and as a DS-TH (direct sequence-time hopping) UWB signals is used, an unique independent code identifies each users, therefore the desired user direction can be evaluated. In the simulated system each transmitter emits the same signal through indoor channels and each UWB signal replica is affected by AWGN noise, so slightly different signals are obtained from each channel, which is the perfect situation for using a MIMO implementation. Therefore, a 2/spl times/2 and a 2/spl times/3 UWB-MIIMO systems are analyzed to evaluate the angle error rate for different E/sub b//N/sub 0/ values.
Towards understanding of classes versus data types in conceptual modeling and UML

Traditional conceptual modeling and UML take different vague, ambiguous, and apparently incompatible approaches to making a distinction between two different entity types - classes and data types. In this paper, an in-depth theoretical study of these ambiguities and discrepancies is given and a new semantic interpretation is proposed for consolidation. The interpretation is founded on the premise that populations of the two kinds of entity types are defined in two substantially different ways: by intensional (for data types) and extensional (for classes) definitions. The notion of a generative relationship set is introduced to explain the role of specific relationship types that are used to define populations of structured data types by cross-combinations of populations of the related entity types. Finally, some important semantic consequences are described through the proposed interpretation: value-based vs. object-based semantics, associations vs. attributes, and identity vs. identification. The given interpretation is based on runtime semantics and allows for fully unambiguous discrimination of the related concepts, yet it fits into intuitive understanding and common practical usage of these concepts.
Mapping Student Days: Collaborative Ethnography and the Student Experience

Research on students’ educational experiences demonstrates the importance of a holistic understanding of the complexity of students’ lives to developing library programs, services, and resources that effectively address undergraduate needs. The “A Day in the Life” (ADITL) project investigated a typical day for over 200 students at eight diverse institutions in the US. Examining the local and individual expressions of student taskscapes – the ensemble of interrelated social activities across time and space – placed each student’s relationship to their library in a larger description of their academic and personal lives. By exploring the whole student experience, this multi-site ethnographic study mapped out a more complete, complex, and diverse cartography of college students’ lives and the library’s place in it.
A framework for security on NoC technologies

Multiple heterogeneous processor cores, memory cores and application specific IP cores integrated in a communication network, also known as networks on chips (NoCs), will handle a large number of applications including security. Although NoCs offer more resistance to bus probing attacks, power/EM attacks and network snooping attacks are relevant. For the first time, a framework for security on NoC at both the network level (or transport layer) and at the core level (or application layer) is proposed. At the network level, each IP core has a security wrapper and a key-keeper core is included in the NoC, protecting encrypted private and public keys. Using this framework, unencrypted keys are prevented from leaving the cores and NoC. This is crucial to prevent untrusted software on or off the NoC from gaining access to keys. At the core level (application layer) the security framework is illustrated with software modification for resistance against power attacks with extremely low overheads in energy. With the emergence of secure IP cores in the market and nanometer technologies, a security framework for designing NoCs is crucial for supporting future wireless Internet enabled devices.
Comparison of Human and Machine Word Recognition

We present a study which is concerned with word recognition rates for heavily degraded documents. We compare human with machine reading capabilities in a series of experiments, which explores the interaction of word/non-word recognition, word frequency and legality of nonwords with degradation level. We also study the influence of character segmentation, and compare human performance with that of our artificial neural network model for reading. We found that the proposed computer model uses word context as efficiently as humans, but performs slightly worse on the pure character recognition task.