Miracle-dz/UniFAR-FTUs huggingface dataset:
Hybrid prediction method of solar power using different computational intelligence algorithms

Computational Intelligence (CI) holds the key to the development of smart grid to overcome the challenges of planning and optimization through accurate prediction of Renewable Energy Sources (RES). This paper presents an architectural framework for the construction of hybrid intelligent predictor for solar power. This research investigates the applicability of heterogeneous regression algorithms for 6 hour ahead solar power availability forecasting using historical data from Rockhampton, Australia. Data is collected across six years with hourly resolution from 2005 to 2010. We observe that the hybrid prediction method is suitable for a reliable smart grid energy management. Prediction reliability of the proposed hybrid prediction method is carried out in terms of prediction error performance based on statistical and graphical methods. The experimental results show that the proposed hybrid method achieved acceptable prediction accuracy. These potential model could be apply as a local predictor for any proposed hybrid method in the real life application for six hour in advance prediction to ensure constant solar power supply in the smart grid operation.
A WCET-oriented static branch prediction scheme for real time systems

Branch prediction mechanisms are becoming commonplace within current generation processors. Dynamic branch predictors, albeit able to predict branches quite accurately in average, are becoming increasingly complex. Thus, determining their worst-case behavior, which is highly recommended for real-time applications, is getting increasingly difficult and error-prone, and may even be soon impossible for the most complex branch predictors. In contrast, static branch predictors are inherently predictable, to the detriment of a lower prediction accuracy. In this paper, we propose a WCET-oriented static branch prediction scheme. Unlike related work on compiler-directed static branch prediction, our scheme does not address program average-case performance (i.e. average-case branch misprediction rate) but addresses worst-case program performance instead (i.e. branch mispredictions which impact programs WCET estimates). Experimental results on a PowerPC 7451 architecture show that the estimated WCET can be decreased by up to 21 % (with an average improvement of 15%) as compared with the method where all branches are conservatively considered mispredicted. Our scheme, although applicable to any processor with support for static branch prediction, is specially suited to processors with complex dynamic predictors, for which safe and tight WCET estimate methods do not exist.
CHARACTERISATION OF HEALING AGENTS FOR SELF-HEALING CEMENTITIOUS SYSTEMS

Recent developments in self-healing technology inspired by natural biological materials have the potential to dramatically improve the performance and durability of cementitious materials. These self-healing cementitious materials comprise artificial flow networks embedded within the cementitious matrix that upon damage release healing agents that are transported via capillary flow to macro-cracked and microcracked regions. However, the mechanisms of capillary flow in cementitious materials and the interactions between varying viscosity and surface tension are not well understood and there are few reported studies to date that have attempted to measure or simulate these for cementitious materials. This paper considers the flow characteristics of healing agents in macro-cracks formed as a result of material damage occurring during the early life of a structure and whose presence contributes to the deterioration processes that reduce the longevity of reinforced concrete structures. The ability to predict the capillary flow of healing agents within discrete cracks will further the development of efficient self-healing cementitious materials which will in turn deliver economic, environmental and social benefits, such as reduced maintenance and repair costs and reduced use of natural resources. This paper presents the results from an experimental investigation into the Hagen-Poiseuille (H-P) flow characteristics of one autonomic (adhesive based) and one autogenic (pozzolanic based) healing agent. Particular attention is given to the timeviscosity and time-surface tension relationships of the healing agents when in contact with mortar. Additional benchmark experiments are currently being undertaken for the capillary flow of the two healing agents between glass plates and concrete plates of varying compressive strength. These studies provide data to validate a numerical model developed by the research group, in which terms are added to allow for stickslip behaviour and frictional dissipation at the meniscus wall boundary. The initial results from these validations are promising and confirm the validity of the theoretical approach adopted.
User profiling vs. accuracy in recommender system user experience

A Recommender System (RS) filters a large amount of information to identify the items that are likely to be more interesting and attractive to a user. Recommendations are inferred on the basis of different user profile characteristics, in most cases including explicit ratings on a sample of suggested elements. RS research highlights that profile length, i. e. , the number of collected ratings, is positively correlated to the accuracy of recommendations, which is considered an important quality factor for RSs. Still, gathering ratings adds a burden on the user, which may negatively affect the UX. A design tension seems to exist, induced by two conflicting requirements -- to raise accuracy by increasing the profile length, and to make the profiling process smooth for the user by limiting the number of ratings. The paper presents a wide empirical study (1080 users involved) which explores this issue. Our work attempts to identify which of the two contrasting forces influenced by profile length -- recommendations accuracy and burden of the rating process - has stronger effects on the perceived quality of the UX with a RS.
Significance of the heating rate on the physical properties of carbonized maple wood

Abstract Effects of the heating rate on the physical properties of carbonized wood were investigated by comparing the dimensional shrinkage, electrical resistivity, Young's modulus, and the evolution of turbostratic crystallites in maple hardwood samples carbonized at 600°C, 800°C, and 1000°C under heating regimes of 3°C h-1 and 60°C h-1. Important carbonized wood properties that developed at high temperature and high heating rates could also be produced at slow heating rates and lower temperatures. Furthermore, slow heating rates promoted the formation and growth of graphene sheets in turbostratic crystallites, which had a significant influence on the electrical resistivity and Young's modulus of the carbonized wood. The results indicate that the graphene sheets of turbostratic crystallites formed during wood carbonization were arranged parallel to the axial direction of wood cells and at an angle to the circumference of wood cells in the cross-sectional plane. With regard to the production of carbon products, a decrease in the heating rate may be beneficial for char properties and the prevention of crack production during manufacture of large monolithic carbon specimens from wood and wood-based materials.
Coupled ER to Golgi Transport Reconstituted with Purified Cytosolic Proteins

A cell-free vesicle fusion assay that reproduces a subreaction in transport of pro-α-factor from the ER to the Golgi complex has been used to fractionate yeast cytosol. Purified Sec18p, Uso1p, and LMA1 in the presence of ATP and GTP satisfies the requirement for cytosol in fusion of ER-derived vesicles with Golgi membranes. Although these purified factors are sufficient for vesicle docking and fusion, overall ER to Golgi transport in yeast semi-intact cells depends on COPII proteins (components of a membrane coat that drive vesicle budding from the ER). Thus, membrane fusion is coupled to vesicle formation in ER to Golgi transport even in the presence of saturating levels of purified fusion factors. Manipulation of the semi-intact cell assay is used to distinguish freely diffusible ER- derived vesicles containing pro-α-factor from docked vesicles and from fused vesicles. Uso1p mediates vesicle docking and produces a dilution resistant intermediate. Sec18p and LMA1 are not required for the docking phase, but are required for efficient fusion of ER- derived vesicles with the Golgi complex. Surprisingly, elevated levels of Sec23p complex (a subunit of the COPII coat) prevent vesicle fusion in a reversible manner, but do not interfere with vesicle docking. Ordering experiments using the dilution resistant intermediate and reversible Sec23p complex inhibition indicate Sec18p action is required before LMA1 function.
Biomolecular Network Simulator: software for stochastic simulation of cellular biological processes

We developed a software package called Biomolecular Network Simulator (BNS) to model and simulate complex biomolecular reaction networks. The software uses the Gillespie stochastic simulation algorithm for generating Monte Carlo trajectories that describe the evolution of a system of biochemical reactions. This software uses a combination of MATLAB and C-coded functions and is parallelized with the MatlabMPI library to run on multiprocessor architectures. Simulations on HPC can be run either in the interactive or in the batch mode. The graphical user interface of BNS allows users to easily set parameters for the model and simulations. Furthermore, BNS contains a comprehensive set of tools for post-simulation analysis of the results.
Analysis of shopping behavior based on surveillance system

Closed Circuit Television systems in shopping malls could be used to monitor the shopping behavior of people. From the tracked path, features can be extracted such as the relation with the shopping area, the orientation of the head, speed of walking and direction, pauses which are supposed to be related to the interest of the shopper. Once the interest has been detected the next step is to assess the shopper's positive or negative appreciation to the focused products by analyzing the (non-verbal) behavior of the shopper. Ultimately the system goal is to assess the opportunities for selling, by detecting if a customer needs support. In this paper we present our methodology towards developing such a system consisting of participating observation, designing shopping behavioral models, assessing the associated features and analyzing the underlying technology. In order to validate our observations we made recordings in our shop lab. Next we describe the used tracking technology and the results from experiments.
A Neural Computational Model of Incentive Salience

Incentive salience is a motivational property with ‘magnet-like’ qualities. When attributed to reward-predicting stimuli (cues), incentive salience triggers a pulse of ‘wanting’ and an individual is pulled toward the cues and reward. A key computational question is how incentive salience is generated during a cue re-encounter, which combines both learning and the state of limbic brain mechanisms. Learning processes, such as temporal-difference models, provide one way for stimuli to acquire cached predictive values of rewards. However, empirical data show that subsequent incentive values are also modulated on the fly by dynamic fluctuation in physiological states, altering cached values in ways requiring additional motivation mechanisms. Dynamic modulation of incentive salience for a Pavlovian conditioned stimulus (CS or cue) occurs during certain states, without necessarily requiring (re)learning about the cue. In some cases, dynamic modulation of cue value occurs during states that are quite novel, never having been experienced before, and even prior to experience of the associated unconditioned reward in the new state. Such cases can include novel drug-induced mesolimbic activation and addictive incentive-sensitization, as well as natural appetite states such as salt appetite. Dynamic enhancement specifically raises the incentive salience of an appropriate CS, without necessarily changing that of other CSs. Here we suggest a new computational model that modulates incentive salience by integrating changing physiological states with prior learning. We support the model with behavioral and neurobiological data from empirical tests that demonstrate dynamic elevations in cue-triggered motivation (involving natural salt appetite, and drug-induced intoxication and sensitization). Our data call for a dynamic model of incentive salience, such as presented here. Computational models can adequately capture fluctuations in cue-triggered ‘wanting’ only by incorporating modulation of previously learned values by natural appetite and addiction-related states.
ISOLATION BARRIERS BETWEEN PETUNIA AXILLARIS AND PETUNIA INTEGRIFOLIA (SOLANACEAE)

The isolation barriers restricting gene flow between populations or species are of crucial interest for understanding how biological species arise and how they are maintained. Few studies have examined the entire range of possible isolation barriers from geographic isolation to next generation hybrid viability. Here, we present a detailed analysis of isolation barriers between two flowering plant species of the genus Petunia (Solanaceae). Petunia integrifolia and P. axillaris feature divergent pollination syndromes but can produce fertile hybrids when crossed in the laboratory. Both Petunia species are primarily isolated in space but appear not to hybridize in sympatry. Our experiments demonstrate that pollinator isolation is very high but not strong enough to explain the absence of hybrids in nature. However, pollinator isolation in conjunction with male gametic isolation (i.e., pollen–pistil interaction) can explain the lack of natural hybridization, while postzygotic isolation barriers are low or nonexistent. Our study supports the notion that reproductive isolation in flowering plants is mainly caused by pre‐ rather than postzygotic isolation mechanisms.
Creating a shared understanding of testing culture on a social coding site

Many software development projects struggle with creating and communicating a testing culture that is appropriate for the project's needs. This may degrade software quality by leaving defects undiscovered. Previous research suggests that social coding sites such as GitHub provide a collaborative environment with a high degree of social transparency. This makes developers' actions and interactions more visible and traceable. We conducted interviews with 33 active users of GitHub to investigate how the increased transparency found on GitHub influences developers' testing behaviors. Subsequently, we validated our findings with an online questionnaire that was answered by 569 members of GitHub. We found several strategies that software developers and managers can use to positively influence the testing behavior in their projects. However, project owners on GitHub may not be aware of them. We report on the challenges and risks caused by this and suggest guidelines for promoting a sustainable testing culture in software development projects.
Kras as a key oncogene and therapeutic target in pancreatic cancer

Pancreatic cancer is one of the deadliest human malignancies and little progress has been achieved in its treatment over the past decades. Advances in our understanding of the biology of this disease provide new potential opportunities for treatment. Pancreatic cancer is preceded by precursor lesions, the most common of which are known as Pancreatic Intraepithelial Neoplasia (PanIN). PanIN lesions, which are the focus of this review, have a high incidence of Kras mutations, and Kras mutations are a hallmark of the late-stage disease. We now know from genetically engineered mouse models that oncogenic Kras is not only driving the formation of pancreatic cancer precursor lesions, but it is also required for their progression, and for the maintenance of invasive and metastatic disease. Thus, an enormous effort is being placed in generating Kras inhibitors for clinical use. Additionally, alternative approaches, including understanding the role of Kras effector pathways at different stages of the disease progression, are being devised to target Kras effector pathways therapeutically. In particular, efforts have focused on the MAPK pathway and the PI3K pathway, for which inhibitors are widely available. Finally, recent studies have highlighted the need for oncogenic Kras to establish feedback mechanisms that maintain its levels of activity; the latter might constitute alternative ways to target Kras in pancreatic cancer. Here, we will review recent basic research and discuss potential therapeutic applications.
SPO: Structure Preserving Oversampling for Imbalanced Time Series Classification

This paper presents a novel structure preserving over sampling (SPO) technique for classifying imbalanced time series data. SPO generates synthetic minority samples based on multivariate Gaussian distribution by estimating the covariance structure of the minority class and regularizing the unreliable eigen spectrum. By preserving the main covariance structure and intelligently creating protective variances in the trivial eigen feature dimensions, the synthetic samples expand effectively into the void area in the data space without being too closely tied with existing minority-class samples. Extensive experiments based on several public time series datasets demonstrate that our proposed SPO in conjunction with support vector machines can achieve better performances than existing over sampling methods and state-of-the-art methods in time series classification.
Rating Performance and Agency Incentives of Structured Finance Transactions

The mismatch between credit ratings o fstructured finance transactions and their true risks has been a source of the Global Financial Crisis which manifested in criticism of models and techniques applied by credit rating agencies (CRA). This paper provides an empirical study which assesses the historical performance of credit ratings for structured finance transactions and finds that CRAs do not include all factors explaining securitization impairment risk. In addition, CRA ratings for selected asset categories underestimate risk in origination years when the fee revenue is high.
Surface and Adhesive Properties of Low-Density Polyethylene after Radiation Cross-Linking

Radiation cross-linking gives inexpensive commodity plastics and technical plastics the mechanical, thermal, and chemical properties of high-performance plastic. This upgrading of the plastics enables them to be used in conditions which they would not be able to with stand otherwise. The irradiation cross-linking of thermoplastic materials via electron beam or cobalt 60 (gammy rays) is performed separately, after processing. Generally, ionizing radiation includes accelerated electrons, gamma rays and X-rays. Radiation processing with an electron beam offers several distinct advantages when compared with other radiation sources, particularly γ-rays and x-rays. The process is very fast, clean and can be controlled with much precision. There is no permanent radioactivity since the machine can be switched off. In contrast to γ-rays and x-rays, the electron beam can steered relatively easily, thus allowing irradiation of a variety of physical shapes. The energy-rich beta rays trigger chemical reactions in the plastics which results in networking of molecules (comparable to the vulcanization of rubbers which has been in industrial use for so long). The energy from the rays is absorbed by the material and cleavage of chemical bonds takes place. This releases free radicals which in next phase from desired molecular bonds. This article describes the effect of radiation cross-linking on the surface and adhesive properties of low-density polyethylene.
Oil palm phenolics as a bioactive ingredient in promoting cardiovascular health.

Some plant-based bioactives are known to possess multiple health benefits, and polyphenols represent the largest group of these. The presence of multifunctional (antioxidant, anti-lipid peroxidative and metal chelating) properties within the same molecule enables polyphenols to confer pleiotropism, akin to several therapeutic agents. With such emerging positive scientific evidence, novel polyphenols are actively being pursued by the food and supplement industries as a natural, safe and cost-effective means of delivering health benefits to consumers. Several naturally occurring polyphenol compounds (e.g. tea, grape, wine) have been shown to afford cardiovascular protection through their actions on the vasculature. The palm oil industry is a global provider of several natural antioxidants. Palm carotenes rich in -carotenes, and palm vitamin E enriched in tocotrienols reside in the fruit mesocarp, and are recovered from extracted crude palm oil. In addition, a novel water-soluble antioxidant complex enriched in polyphenols (oil palm phenolics; OPP) has been isolated from the large aqueous biomass generated during the milling process. In the present study we evaluated the potential cardiovascular outcomes of OPP via a series of in vitro and in vivo studies following both acute administration and long-term feeding in rats. OPP dose-dependently relaxed isolated blood vessel preparations, and lowered blood pressure (BP) in the nitric oxide deficient model of hypertension as well as in the spontaneously hypertensive rat following acute administration. OPP afforded protection against cardiac arrhythmia following induction of myocardial ischemia by coronary artery ligation in a whole animal model of sudden cardiac death. The results thus implicate OPP as a potential bioactive ingredient effective in promoting cardiovascular health.
Design proposal for reducing actuator redundancy in intrinsically compliant manipulators

Variable Stiffness Actuators (VSA) allow for simultaneous position and stiffness control of a joint by the use of two actuators, therefore they are used in the design of intrinsically compliant manipulators. Generally, for a manipulator with n joints n VSAs are used, resulting in 2n actuators. In this work, we propose the design of a two-link intrinsically compliant manipulator using only three actuators (instead than four): one Series Elastic Actuator (SEA) in a mono-articular configuration, and a VSA based on two antagonistic actuators in biarticular (actuators producing simultaneous torque about both joints) configuration. The proposed actuation structure reduces the amount of actuators, while increasing the isotropy of the end effector force (in all the workspace), and end effector stiffness isotropy when the arm extends. Therefore the proposed structure based on monoarticular SEA and biarticular VSA is suitable for light and compliant manipulation, as for example robotic hands, arms and legs.
HICCUPS: health information collaborative collection using privacy and security

A recent national survey suggests that the HIPAA privacy rule has not only failed to preserve patient privacy adequately, but also has had a negative impact on clinical research. Our work suggests that researchers revisit the possibilities of homomorphic encryption and apply the techniques to secure aggregation of medical telemetry. A primary goal is to maintain the privacy of individual patient records while also allowing clinical researchers to have flexible access to aggregated information. We discuss the preliminary design of HICCUPS, a distributed system that uses homomorphic encryption to allow only the caregivers to have unrestricted access to patients' records and at the same time enable researchers to compute statistical values and aggregation functions across different patients and caregivers. In the context of processing medical telemetry, we advocate expressibility of aggregation functions more than fast computation as a primary metric of system quality.