Miracle-dz/UniFAR-FTUs huggingface dataset:
Self-compacting concrete (SCC) behaviour incorporating limestone fines as cement and sand replacement

Abstract Owing to their high intrinsic properties, limestone fines (LF) seems to be a good replacement material of cement and/or sand, elaborating thus a new concrete without affecting its performances and properties. The present work aims at using, however, this natural material as an alternative cement or sand replacement, and investigating its influence on self-compacting concrete (SCC) properties at fresh and hardened states. Achieving this, several parameters have been examined, in terms of compressive strength, water permeability, chloride-ion penetration, gas permeability, water porosity and sorptivity. A total of 11 SCC mixes samples have been produced in two series, each one with different rate substitution (0%, 5%, 10%, 15%, 20% and 25%) of sand and cement. Our experimental data revealed the incorporation of LF up to 20% in SCC as partial replacement of sand and cement at fresh state, led to appreciable properties results. Nevertheless, at hardened state, at 15% for sand replacement an increase in compressive strength and a decrease in the water and chloride-ion diffusion, while an increase in the gas diffusion has been registered. And for cement replacement at 5%, an improvement in compressive strength and chloride ions diffusion was noted, whereas the water permeability and the gas diffusion decreased at 15% of LF substitution, where these results are widely discussed and explained in this paper.
Engagement at entry to an early intervention service for first episode psychosis: an exploratory study of young people and caregivers

ABSTRACT Early intervention services play a crucial role in providing treatment for young people experiencing a first episode psychosis. However, on average, 30 per cent of young people disengage from treatment, which may result in untreated symptoms, difficulty returning to school or work and relationship breakdowns. This qualitative study aimed to understand the help-seeking experiences and initial engagement with an early intervention service. Semi-structured interviews were conducted with nine young people and five caregivers, focussing on engagement in the first eight weeks of treatment. Themes were identified using thematic analysis. Key findings were that participants entered the early intervention service after a time of intense distress and confusion. This was related to symptoms, difficulties working or studying, and initial experiences of help-seeking and treatment. Commonly there was relief on meeting a caring person who would be their support going forward. However, trust was influenced by previous positive and negative experiences. Establishing a therapeutic relationship and building trust are dynamic and relational concepts, and as such, they warrant reflection by all key stakeholders. Awareness and understanding of these concepts may guide changes to individual practice and service development.
Robust Analog Function Computation via Wireless Multiple-Access Channels

Wireless sensor network applications often involve the computation of pre-defined functions of the measurements such as for example the arithmetic mean or maximum value. Standard approaches to this problem separate communication from computation: digitized sensor readings are transmitted interference-free to a fusion center that reconstructs each sensor reading and subsequently computes the sought function value. Such separation-based computation schemes are generally highly inefficient as a complete reconstruction of individual sensor readings at the fusion center is not necessary to compute a function of them. In particular, if the mathematical structure of the channel is suitably matched (in some sense) to the function of interest, then channel collisions induced by concurrent transmissions of different nodes can be beneficially exploited for computation purposes. This paper proposes an analog computation scheme that allows for an efficient estimate of linear and nonlinear functions over the wireless multiple-access channel. A match between the channel and the function being evaluated is thereby achieved via some pre-processing on the sensor readings and post-processing on the superimposed signals observed by the fusion center. After analyzing the estimation error for two function examples, simulations are presented to show the potential for huge performance gains over time- and code-division multiple-access based computation schemes.
Magnetoencephalographic Mapping of Interictal Spike Propagation: A Technical and Clinical Report

SUMMARY: Distinguishing propagated epileptic activity from primary epileptic foci is of critical importance in presurgical evaluation of patients with medically intractable focal epilepsy. We studied an 11-year-old patient with complex partial epilepsy by using simultaneous magnetoencephalography (MEG) and electroencephalography (EEG). In EEG, bilateral interictal discharges appeared synchronous, whereas MEG source analysis suggested propagation of spikes from the right to the left frontal lobe.
A Distributed Instrument for Performance Analysis of Real-Time Ethernet Networks

Ethernet technology is widely used in real-time industrial automation. Thanks to real-time Ethernet (RTE) protocols, defined in IEC61784-2 standard, new top-performance automation solutions can be created. Such systems may have communication cycle time down to tens of mus and cycle jitter less than 1 mus, making network testing and debugging very critical. Existing network and protocol analyzers can perform detailed local analysis, but characterization of high-performance RTE systems requires measurement of transmission delays and these instruments cannot be adequately synchronized among them to realize a distributed measurement network. This paper introduces a new low-cost distributed measurement instrument to measure timing characteristics of RTE nodes (end-to-end delays, synchronization, etc.). The proposed instrument has multiple FPGA-based probes that allow for simultaneous/synchronized logging on different place of the target RTE network. A PC-based "monitor station" stores all the data, ready for further elaboration. Architecture details are discussed, a prototype has been realized, and some experimental results are presented. For instance, synchronization accuracy between probes is below 100 ns.
Cocaine and amphetamine-like psychostimulants: neurocircuitry and glutamate neuroplasticity

Although the pharmacology of amphetamine-like psychostimulants at dopamine transporters is well understood, addiction to this class of drugs has proven difficult to deal with. The reason for this disconnection is that while the molecular mechanism of amphetamine action is critical to reinforce drug use, it is only the first step in a sequence of widespread neuroplastic events in brain circuitry. This review outlines the affect of psychostimulants on mesocorticolimbic dopamine projections that mediate their reinforcing effect, and how this action ultimately leads to enduring pathological neuroplasticity in glutamatergic projections from the prefrontal cortex to the nucleus accumbens. Molecular neuroadaptations induced by psychostimulant abuse are described in glutamate neurotransmission, and from this information potential pharmacotherapeutic targets are identified, based upon reversing or countermanding psychostimulant-induced neuroplasticity.
Effects of Wheat Naturally Contaminated with Fusarium Mycotoxins on Growth Performance and Selected Health Indices of Red Tilapia (Oreochromis niloticus × O. mossambicus)

An 8-week feeding trial was conducted to examine effects of wheat naturally contaminated with Fusarium mycotoxins (deoxynivalenol, DON 41 mg·kg−1) on growth performance and selected health indices of red tilapia (Oreochromis niloticus × O. mossambicus; initial weight = 4.3 g/fish). Five experimental diets were formulated by replacement of clean wheat with naturally contaminated wheat resulting in graded levels of DON and zearalenone (ZEN) (Diet 1 0.07/0.01, Diet 2 0.31/0.09, Diet 3 0.50/0.21, Diet 4 0.92/0.37 and Diet 5 1.15/0.98 mg·kg−1). Groups of 50 fish were randomly allocated into each of 20 aquaria and fed to near-satiety for eight weeks. Growth rate, feed intake and feed efficiency of fish fed the experimental diets decreased linearly with increasing levels of Fusarium mycotoxins (p < 0.05). Although growth depression was associated with feeding diets naturally contaminated with Fusarium mycotoxins, especially DON, no biochemical and histopathological parameters measured in blood and liver appeared affected by Fusarium mycotoxin concentrations of diets (p > 0.05). Though there was no clear evidence of overt DON toxicity to red tilapia, it is recommended that feed ingredients should be screened for Fusarium mycotoxin contamination to ensure optimal growth performance.
ANTIOXIDANT ENZYMES AND ALDEHYDE RELEASING CAPACITY OF RICE CULTIVARS (ORYZA SATIVA L.) AS DETERMINANTS OF ANAEROBIC SEEDLING ESTABLISHMENT CAPACITY

Summary. The activities of antioxidant enzymes and levels of antioxidants involved in oxygen detoxification were studied in seedlings of three indica rice (Oryza sativa L.) cultivars, namely Panikekoa and T 1471 that show good capacity for anaerobic seedling establishment (tolerant reaction) and IR 42 which has a poor anaerobic seedling establishment capacity (susceptible reaction). The activities of the antioxidant enzymes tested decreased under submergence. The activity of glutathione reductase (GR, EC 1.6.4.2) was found to be more sensitive compared to the other enzymes. On the other hand, the activity of superoxide dismutase (SOD, EC 1.15.1.9) was comparatively stable. After 5 days of submergence tolerant cultivars maintained almost 3-fold higher glutathione reductase activity than the susceptible cultivar. During submergence the tolerant cultivars showed comparatively less ascorbic acid oxidase (AAO, EC 1.10.3.3) activity and had greater ascorbic acid content. The activities of superoxide dismutase, catalase (CAT, EC 1.11.1.6), peroxidase (POX, EC 1.11.1.7), ascorbic acid peroxidase (APX, EC 1.11.1.11) and polyphenol oxidase (PPO, EC 1.14.18.1) were also higher in tolerant cultivars during submergence compared to the susceptible cultivar. Submergence was found to induce aldehyde releasing capacity in rice seedlings which was more apparent in the susceptible cultivar.
Dynamic Premotor-to-Parietal Interactions during Spatial Imagery

The neurobiological processes underlying mental imagery are a matter of debate and controversy among neuroscientists, cognitive psychologists, philosophers, and biologists. Recent neuroimaging studies demonstrated that the execution of mental imagery activates large frontoparietal and occipitotemporal networks in the human brain. These previous imaging studies, however, neglected the crucial interplay within and across the widely distributed cortical networks of activated brain regions. Here, we combined time-resolved event-related functional magnetic resonance imaging with analyses of interactions between brain regions (functional and effective brain connectivity) to unravel the premotor–parietal dynamics underlying spatial imagery. Participants had to sequentially construct and spatially transform a mental visual object based on either verbal or visual instructions. By concurrently accounting for the full spatiotemporal pattern of brain activity and network connectivity, we functionally segregated an early from a late premotor–parietal imagery network. Moreover, we revealed that the modality-specific information upcoming from sensory brain regions is first sent to the premotor cortex and then to the medial-dorsal parietal cortex, i.e., top-down from the motor to the perceptual pole during spatial imagery. Importantly, we demonstrate that the premotor cortex serves as the central relay station, projecting to parietal cortex at two functionally distinct stages during spatial imagery. Our approach enabled us to disentangle the multicomponential cognitive construct of mental imagery into its different cognitive subelements. We discuss and explicitly assign these mental subprocesses to each of the revealed effective brain connectivity networks and present an integrative neurobiological model of spatial imagery.
The Open University ’ s repository of research publications and other research outputs Semantic sentiment analysis of twitter

Sentiment analysis over Twitter offer organisations a fast and effective way to monitor the publics’ feelings towards their brand, business, directors, etc. A wide range of features and methods for training sentiment classifiers for Twitter datasets have been researched in recent years with varying results. In this paper, we introduce a novel approach of adding semantics as additional features into the training set for sentiment analysis. For each extracted entity (e.g. iPhone) from tweets, we add its semantic concept (e.g. “Apple product”) as an additional feature, and measure the correlation of the representative concept with negative/positive sentiment. We apply this approach to predict sentiment for three different Twitter datasets. Our results show an average increase of F harmonic accuracy score for identifying both negative and positive sentiment of around 6.5% and 4.8% over the baselines of unigrams and part-of-speech features respectively. We also compare against an approach based on sentiment-bearing topic analysis, and find that semantic features produce better Recall and F score when classifying negative sentiment, and better Precision with lower Recall and F score in positive sentiment classification.
The Optimal Distribution-Free Sample Complexity of Distribution-Dependent Learning

This work establishes a new upper bound on the worst-case number of labeled samples sufficient for PAC learning in the realizable case, if the learning algorithm is allowed dependence on the data distribution, or an additional pool of unlabeled samples. The bound matches known lower bounds up to constant factors. This resolves a long-standing open problem on the sample complexity of distribution-dependent PAC learning. We also discuss potential avenues for extension to distribution-independent learning. The technique and analysis build on a recent breakthrough by Hans Simon.
Application of positive matrix factorization in estimating aerosol secondary organic carbon in Hong Kong and insights into the formation mechanisms

Secondary organic carbon (SOC) is often a significant portion of organic carbon (OC) in ambient particulate matter (PM). The levels and seasonal patterns of SOC in Hong Kong were examined using more than 2000 PM 10 measurements made over a 4.5-year period (1998? 2002) in a network of ten air quality monitoring stations. The positive matrix factorization (PMF) model was used to analyze this large data set for source identification and apportioning. SOC was subsequently estimated to be the sum of OC present in the secondary sources, i.e., secondary sulfate, secondary nitrate, and secondary organic aerosol. The annual average SOC as estimated by the PMF method was 4.25 µg C/m 3 while the summer average was 1.66 µg C/m 3 and the winter average was 7.05 µg C/m 3 . In comparison, the method that uses EC as a tracer for primary carbonaceous aerosol sources to derive SOC overestimated SOC by 70? 212% for the summer samples and by 4? 43% for the winter samples. The overestimation by the EC tracer method resulted from the inability of obtaining a single OC/EC ratio that represented a mixture of primary sources varying in time and space. We found that SOC and secondary sulfate had synchronous seasonal variation and were correlated in individual seasons, suggesting common factors that control their formation. Considering the well-established fact that both gas phase oxidation and in-cloud processing are important formation pathways for sulfate, the synchronicity of SOC and sulfate suggests that in-cloud pathways are also important for SOC formation. Additionally, the presence of SOC was found to be enhanced more than that of secondary sulfate in the winter. We postulate this to be a combined result of favorable partitioning of semivolatile SOC species in the particle phase and more abundant SOC precursors in the winter.
Towards a Theory of Social Adaptation to Climate Change in Africa

Little work has been done to integrate behaviour change theories into climate change communication and adaptation research. This study proposes an integrated model of Social Adaptation to Climate Change with a framework to predict climate adaptation behaviour through a chain of relationships starting with media impact on climate knowledge, knowledge impact on human cognition and human cognition on climate adaptation behaviour. The study analyses a survey of literate youth in tertiary institutions within the Tamale Metropolitan Assembly of Ghana to answer key research questions such as a) how does the youth understand and react to climate change? b) Is media coverage significantly related to public knowledge of climate change? c) Is climate knowledge significantly related to human cognition on climate change? and d) is human cognition significantly associated with climate adaptation behaviour? The key findings of the study are that; a) climate knowledge is generally high among the educated youth within the study area; b) media has no significant impact on climate knowledge; c) climate knowledge is significantly associated with human cognition and; d) human cognition is significantly related to climate adaptation behaviour. These findings provide evidence to support the theoretical frame of this study and bring fresh perspectives to the field of climate research. The main conclusion of this investigation is that understanding and predicting climate adaptation behaviour can be enhanced through integration of hitherto fragmented areas of research namely media coverage of climate change, public knowledge of climate change and behaviour change theories. This has the added advantage of allowing for attention to be given to the human aspects of the climate adaptation initiatives.
A Model of Adaptation in Collaborative Multi-Agent Systems

Adaptation is an essential requirement for autonomous agent systems functioning in uncertain dynamic environments. Adaptation allows agents to change their behavior in order to improve the overall sys tem performance. We describe a general mechanism for adaptation in multi-agent systems in which agents modify their behavior in response to changes in the environment or actions of other agents. The agents estimate the global state of the system from local observations and adjust their actions accordingly. We derive a mathematical model that describes the collective behavior of such adaptive systems. The model, consisting of coupled rate equations, governs how the collective behavior changes in time. We apply the model to study collaboration in a group of mobile robots. The system we study is an adaptive version of the collaborative stick pulling in a group of robots examined in detail in earlier works (Ijspeert, Martinoli, Billard, & Gambardela, 2001; Lerman, Galstyan, Martinoli, & Ijspeert, 2001). In adaptive stick pulling, robots estimate the number of robots and sticks in the system and adjust their individual behavior so as to improve collective performance. We solve the mathematical model and show that adaptation improves collective performance for all parameter values.
Finding Topic-specific Strings in Text Categorization and Opinion Mining Contexts

— In this paper, we present a new probabilistic method for automatically extracting topic-specific strings in a text categorization context. The advantage of this method is twofold. First, it allows us to automatically point out the expressions characterizing a specific topic category for a potential knowledge modelling. Second, it contributes to improve categorization results by providing to the classifier text spans which are more relevant than isolated words. The novelty of our approach relies thus not only on the method used for topic-specific strings extraction but also on the adaptation of the traditional cosine similarity measure for text categorization. We choose for the evaluation to tackle two different challenging corpora: movie reviews of Internet users, and manual transcriptions of call center conversations. On these two tasks, we observed a gain in the categorization results (between 1 and 8%).
Fish Production in Streams With and Without Natural Broan Trout Populations

Brown trout (Salmo trutta) have been introduced into the waterways throughout the United States, including Pennsylvania, since the 1800’s. They may have limited interactions with native fish species in regions where they do not reproduce successfully, but where they do concerns have arisen regarding the impact they have on native species. Are brown trout having a negative effect on the native fish? If so, could they be outcompeting the natives to the point of localized extirpation? This project compared fish communities, densities, biomass and production in two similar stretches of stream in the White Clay Creek, one known to hold brown trout (the East Branch) and the other without (the Middle Branch). Fish in each branch were collected in June and October 2009 using backpack electrofishing equipment to determine species composition and abundance, population densities and community diversity. Fish were aged using scales and further examination revealed biomass and production of the species present. The fish communities within the branches were stable between June and October ( Jaccards index = 0.75 for both branches), but differed between branches ( Jaccards index = 0.64 in June and 0.58 in October). The stream without brown trout showed much lower density, biomass, and production of most species, which went counter to our hypothesis that fish would show lower levels of these factors in the presence of brown trout. Only the common shiner and longnose dace showed effects in each of these categories while favoring the branch without brown trout over the branch with brown trout. Although the results do show a possible negative correlation between these species and the brown trout, our study design did not allow us to rule out other factors. Also, the fewer number of fish in the Middle Branch as compared to the East Branch leads us to believe that something may be wreaking havoc with the natural balance of this section (e.g. land-use changes, environmental stressors or climatic factors). Continued research regarding brown trout interactions on the East Branch and stream quality of the Middle Branch is highly recommended. Disciplines Environmental Sciences | Physical Sciences and Mathematics Comments Presented to the Faculties of the University of Pennsylvania in Partial Fulfillment of the Requirements for the Degree of Master of Environmental Studies 2010. This thesis or dissertation is available at ScholarlyCommons: http://repository.upenn. edu/mes_capstones/36 FISH PRODUCTION IN STREAMS WITH AND WITHOUT NATURAL BROWN TROUT POPULATIONS Scott Weisinger August 2010 Primary Reader: Dr. William Eldridge Advisor/Secondary Reader: Dr. Sarah A. Willig