Miracle-dz/UniFAR-FTUs huggingface dataset:
Spreading rumours without the network

In this paper we tackle the following question: is it possible to predict the characteristics of the evolution of an epidemic process in a social network on the basis of the degree distribution alone? We answer this question affirmatively for several diffusion processes-- Push-Pull, Broadcast and SIR-- by showing that it is possible to predict with good accuracy their average evolution. We do this by developing a space efficient predictor that makes it possible to handle very large networks with very limited computational resources. Our experiments show that the prediction is surprisingly good for many instances of real-world networks. The class of real-world networks for which this happens can be characterized in terms of their neighbourhood function, which turns out to be similar to that of random networks. Finally, we analyse real instances of rumour spreading in Twitter and observe that our model describes qualitatively well their evolution.
Speculative Trading and Stock Returns

Using data from Chinese stock markets, we examine the effect of speculative trading on stock returns. We develop a volume-related variable, abnormal turnover ratio (ATR), by isolating speculative trading from liquidity and other components in trading volume. After a group of tests verifying that ATR indeed represents speculative trading, we show that ATR negatively predicts future stock returns. The average monthly return spread between the top and bottom ATR deciles is −1.87%, suggesting a highly significant negative ATR premium. The return predictability of ATR survives after controlling for common risk factors and event-driven information shocks. These findings indicate that speculative trading affects asset prices.
REPRESENTATIONS OF IN NUMBER THEORY: FINITUDE VERSUS PARITY

We present a new method for expressing Chaitin's random real, , through Diophantine equations. Where Chaitin's method causes a particular quantity to express the bits of by fluctuating between finite and infinite values, in our method this quantity is always finite and the bits of are expressed in its fluctuations between odd and even values, allowing for some interesting developments. We then use exponential Diophantine equations to simplify this result and finally show how both methods can also be used to create polynomials which express the bits of in the number of positive values they assume.
The spin of accreting stars: dependence on magnetic coupling to the disc

We formulate a general, steady-state model for the torque on a magnetized star from a surrounding accretion disc. For the first time, we include the opening of dipolar magnetic-field lines due to the differential rotation between the star and disc, so the magnetic topology then depends on the strength of the magnetic coupling to the disc. This coupling is determined by the effective slip rate of magnetic-field lines that penetrate the diffusive disc. Stronger coupling (i.e. lower slip rate) leads to a more open topology and thus to a weaker magnetic torque on the star from the disc. In the expected strong coupling regime, we find that the spin-down torque on the star is more than an order of magnitude smaller than calculated by previous models. We also use our general approach to examine the equilibrium ('disc-locked') state, in which the net torque on the star is zero. In this state, we show that the stellar spin rate is roughly an order of magnitude faster than predicted by previous models. This challenges the idea that slowly-rotating, accreting protostars are disc locked. Furthermore, when the field is sufficiently open (e.g. for mass accretion rates ≥5 x 10 -9 M ○. yr -1 , for typical accreting protostars), the star will receive no magnetic spin-down torque from the disc at all. We therefore conclude that protostars must experience a spin-down torque from a source that has not yet been considered in the star-disc torque models - possibly from a stellar wind along the open field lines.
Validation and Verification of Use Cases and Class Models

The description of the functional, behavioral, and structural system essentials form central components of any serious requirements specification. In the UML, for example, functional requirements are expressed by use cases, their behavior modeled by e.g. activity graphs, and structural requirements are captured by class models. Unfortunately, any software development method dealing with different models faces difficulties ensuring consistency of the specifications and completeness with respect to each other. To overcome these deficiencies, we refine activity graphs to meet the needs of a suitable modeling element for use case behavior. The refinement in particular supports the proper coupling of activity graphs and the class model. Granularity and semantics of the approach allow for a seamless, traceable transition of use cases to domain classes and for the verification of the domain class model against the use case model. The validation of the use case model and parts of the domain class model is supported as well.
Norges Teknisk-naturvitenskapelige Universitet Local Solutions to High Frequency 2d Scattering Problems Local Solutions to High Frequency 2d Scattering Problems

preprint numerics no. 5/2008 norwegian university of science and technology trondheim, norway We consider the solution of high-frequency scattering problems in two dimensions , modelled by an integral equation on the boundary of the scattering object. We devise a numerical method to obtain solutions on only parts of the boundary with little computational effort. The method incorporates asymp-totic properties of the solution and can therefore attain particularly good results for high frequencies. Potential uses of such partial solutions for non-convex objects and multiple scattering configurations are presented and a brief error analysis is included. We show that in the simplest implementation of the method the integral equation reduces to an ordinary differential equation.
LLVM-CHiMPS : Compilation Environment for FPGAs Using LLVM Compiler Infrastructure and CHiMPS Computational Model

CHiMPS (Compiling High level language to Massively Pipelined System) system, developed by Xilinx is gaining popularity due to its convenient computational model and architecture for field programmable gate array computing. The CHiMPS system utilizes CHiMPS target language as an intermediate representation to bridge between the high level language and the data flow architecture generated from it. However, currently the CHiMPS frontend does not provide many commonly used optimizations and has some use restrictions. In this paper we present an alternative compiler environment based on low level virtual machine compiler environment extended to generate CHiMPS target language code for the CHiMPS architecture. Our implementation provides good support for global optimizations and analysis and overcomes many limitations of the original Xilinx CHiMPS compiler. Simulation results from codes based on this approach show to outperform those obtained with the original CHiMPS compiler.
Stress modulates the use of spatial versus stimulus-response learning strategies in humans.

Animal studies provided evidence that stress modulates multiple memory systems, favoring caudate nucleus-based "habit" memory over hippocampus-based "cognitive" memory. However, effects of stress on learning strategy and memory consolidation were not differentiated. We specifically address the effects of psychosocial stress on the applied learning strategy in humans. We designed a spatial learning task that allowed differentiating spatial from stimulus-response learning strategies during acquisition. In 13 subsequent trials, participants (88 male and female students) had to locate a "win" card out of four placed at a fixed location in a 3D model of a room. Relocating one cue in the last trial allowed inferring the applied learning strategy. Half of them participated first in the "Trier Social Stress Test. " Salivary cortisol and heart rate measurements were taken. Stressed participants used a stimulus-response strategy significantly more often than controls. Subsequent verbal report revealed that spatial learners had a more complete awareness of response options than stimulus-response learners. Importantly, learning performance was not affected by stress. Taken together, stress prior to learning facilitated simple stimulus-response learning strategies in humans-at the expense of a more cognitive learning strategy. Depending on the context, we consider this as an adaptive response.
Smoothing methods for mathematical programs with equilibrium constraints

In the recent optimization world, mathematical programs with equilibrium constraints (MPECs) have been receiving much attention and there have been proposed a number of methods for solving MPECs. We provide a brief review of the recent achievements in the MPEC field and, as further applications of MPECs, we also mention the developments of the stochastic mathematical programs with equilibrium constraints (SMPECs).
Vulnerability to Covariate and Idiosyncratic Shocks and Safety Net Targeting of Rural Households with an Application to Rural Tanzania By

This paper develops a measure or rural household vulnerability, based on the risk of consumption falling below a poverty line, which combines existing approaches to estimating idiosyncratic risks with an approach to measuring covariate risk arising from crop production. The methodology is applied to rural households in Tanzania, using household surveys in a relatively wealthy and a relatively poorer region. The results suggest that covariate risk faced by rural households that arises from crop production is substantial, but quite different in the two regions. Consumption is estimated to depend significantly on crop income, and the variability of that induces considerable overall consumption risk. Covariate risk is found to constitute smaller shares of total consumption risk in the wealthier region. The share of covariate risk in total household consumption risk is found to be similar among poor and non-poor. Vulnerability is quite different in the two regions, with rural households in the poorer region exhibiting considerably higher vulnerability. It is found that non-poor households are quite vulnerable and that there is a considerable degree of hard core poverty. It is demonstrated that observable indicators can be identified to discriminate vulnerable from non-vulnerable households
Local-Memory-Based Integrity Checking for Embedded Systems

The Limited Local Memory (LLM) machine architecture is proposed to improve the security on a multi-core processor with a small trusted computing base (TCB). It uses one privileged core's local memory for executing detection tools to monitor the state of a target OS running on other cores, depending on isolation of the privileged core to ensure the reliability of the detection tools. It has some characteristics fitting embedded systems, such as causing little overhead, a small TCB and requiring minimal modification on the target OS. However, in current research, the LLM architecture was only emulated in QEMU, a virtual machine monitor, and assumed a limited and somehow big space of the local memory that may rarely be equipped on embedded processors. In this paper, we apply this method to a real embedded platform with a LLM-similar hardware configuration, but equipped with a much smaller local memory. Firstly, we propose design details to apply our system to a local memory with such a small size. Then we evaluate the influence that this method would cause to the detection tools and present some hardware recommendations to make the LLM architecture more applicable on real processors. Our research can illustrate the efficiency of the LLM architecture and generalize the application of it for embedded systems by reducing the size requirement on the local memory.
EFFECT OF A ROAD SAFETY EDUCATION INTERVENTION ON ROAD SAFETY KNOWLEDGE OF UNIVERSITY DRIVERS IN IBADAN, NIGERIA

Background: It is essential for drivers employed in the formal sector to have good knowledge of road safety in order to safeguard their lives and those of the staff they are employed to drive. The study was conducted to determine the effect of a road safety education intervention on road safety knowledge of drivers employed in the University of Ibadan, Nigeria. Method: A quasi-experimental study of 98 intervention and 78 control drivers selected using a cluster sampling technique was conducted. The intervention comprised a two-day training on road safety and first aid. The drivers' knowledge of road safety was measured at baseline, immediately and 4-months post-intervention. Aggregate scores of road safety knowledge were computed giving minimum and maximum obtainable scores of 0 and 16 respectively. Change in mean scores over the three measurement periods was assessed using Repeated Measures Analysis of Variance (ANOVA). Independent t-test was used to compare the scores between intervention and control drivers at each of the assessment periods. Twenty-nine drivers did not complete the study (attrition rate = 16.5%). Results: At baseline, mean road safety knowledge scores for the intervention and control drivers were 12.7±2.2 and 12.9± 2.3 (p = 0.510) respectively. Immediately and four months post intervention, the scores of the intervention drivers were 13.8±1.9 and 12.8±1.6; while scores for the controls were 13.3±2.0 and 13.2±1.8. Repeated measures ANOVA revealed that the increase in knowledge over the three assessment periods was not statistically significant. Conclusion: The intervention resulted in an initial increase in road safety knowledge of the intervention drivers. However, this was not sustained to the forth month post-intervention. This finding suggests periodic refresher trainings to sustain the knowledge acquired.
Design and implementation of a decentralized message bus for microservices

A new software architecture, known as microservices, becomes rapidly popular recently. Microservices could help developers cope well with the problems of software complexity and demands on an adaptive development process that needs to respond to changes quickly. In this architecture, a single monolithic large application would be divided into small multiple isolated services. They are separately deployed and communicated to other services via remote calls. This architectural style allows any changes on one service not affecting the others. However, if services directly make remote calls, it would create interdependencies and tight couplings between them. To remove such problem, this paper proposes a decentralized message bus to use as a communication tool between services. Our message bus provides a framework for services to collaborate. It divides into four main components, public API, message bus, messaging and service discovery. The API uses the HTTP and RESTful style of communication. We use decentralized service discovery to avoid a single point of failure of the system. The messaging uses a simple TCP connection with only a header and body in its message. We also define three necessary communication messages for the services, viz. request/response, notification and publish/subscribe. The proposed framework is implemented and tested with a real-world scenario. It works correctly without any problem. Also, to realize how it could be scaled, we run the system continuously with incremental services and traffics. From the observation on the resource consumption of CPU, memory and network I/O, we found that the network consumption grows linearly while the CPU and memory usages have little change in consumption.
Bootstrapped Authorship Attribution in Compression Space Notebook for PAN at CLEF2012

From a machine learning standpoint, the PAN 2012 Lab contest had one major challenge. In all authorship attribution tasks, the number of training documents was extremely low. We extended our previous work, in which com- pression distances to randomly selected prototype documents from the training corpus were used as feature representation. A supervised multi-class classifier was learned in the resulting feature space using the remaining documents. In- spired by the bootstrapped resampling method, we now drew document samples from the few source documents in order to obtain sufficient prototypes and sam- ples to learn a supervised classifier. Using internal validation, we tuned the size of the document samples, compression method, distance measure, classification method, and decision threshold (open-class tasks) for optimal F1 score. With this scheme we submitted for the closed-class and open-class author identification tasks. In the overall results for these tasks we achieved a shared fourth ranking, based on the reported average recall of the 11 teams.
Protection against DDoS Attacks Based on Traffic Level Measurements

— A method for protecting an Internet server against a bandwidth-consuming DDoS attack is proposed and analyzed. Incoming traffic is monitored continuously and " dangerous " traffic intensity rises are detected. Such an event activates a traffic filtering rule which pushes down the incoming aggregate traffic to an acceptable level by discarding excess packets according to the measured relative traffic levels of active sources. Compared to other studies, our method has a structurally stronger base: legitimate traffic to the server is not necessarily hindered because of the attack or the traffic suppression. The method is supported by an analysis and a simulation as well.
Evaluation of zinc and magnesium bioavailability from pea (Pisum sativum, L.) sprouts. Effect of illumination and different germination periods

Summary The effect of sprouting pea seeds (Pisum sativum, L) for 2, 4 and 6 days, with and without light, on the content of zinc (Zn) and magnesium (Mg) and their nutritive utilisation by growing rats was studied. Soaking of pea seeds prior to germination caused a 49% reduction in Zn content followed by minor losses during germination. The content of Mg decreased by 6% as a result of the soaking process, and by 20–28% during germination. Sprouting for 2 and 4 days improved the bioavailability of Zn and Mg from pea seeds (from 32.2 to 88.6–108.0 μg retained Zn per day, and from 1.64 to 2.97–4.79 mg retained Mg per day in raw and sprouted pea flour diets, respectively), outweighing the reductions in Zn and Mg content because of seed soaking. The presence or absence of light during the germination process did not affect the results. We conclude that sprouting of peas for 4 days was the most effective treatment to improve the bioavailability of Zn and Mg in pea seeds.
Decision Trees-Aided Active Power Reduction of a Virtual Power Plant for Power System Over-Frequency Mitigation

The incorporation of distributed generation (DG) under the virtual power plant (VPP) paradigm allows the coherent central control, and the coordinated market integration of several and widely dispersed electric power sources. That way, VPPs can participate in frequency control by regulating in a coordinated manner their output power for the sake of system stability. This study analyzes a decision tree (DT)-based methodology that dispatches a requested reduction of active power within a VPP (among the sources it consists of), so as to support the mitigation of over-frequency. The presented control con-cept finds its application concerning grid support in case of over-frequency, and is also meant as a response to related reports and studies asking for the increased contribution of DG to overcome such phenomena.
A closed-form solution for human finger positioning

In this paper we describe a novel technique for solving the inverse kinematics problem for human fingers. We derive a closed-form solution that places the fingertips precisely in the desired location by allowing minor deviations in the rotations of the Proximal Interphalangeal and Distal Interphalangeal joints compared to the fixed ratio that is known to exist between them. The obvious advantage is that with our approach there is no need to iterate until the distance between the fingertips and the desired locations is small enough. We show that this method is reliable and exact while showing minimal differences to the finger poses generated by the original closed-form solution. In our experiments we found the positions of the intermediate joints of the finger to deviate only around 1.5 mm in the worst case from those resulting from a numerical approximation of the original closed-form solution. On average the deviation is less than 0.5 millimeter.
Association between serum 25-hydroxyvitamin d levels, bone geometry, and bone mineral density in healthy older adults.

PURPOSE The association between serum 25-hydroxyvitamin D values and cortical/trabecular bone parameters in older adults has been incompletely explored. This study was designed to investigate the relationship between serum 25-hydroxyvitamin D levels and bone parameters for the tibia and radius using peripheral quantitative computed tomography in free-living healthy older adults. METHODS The study involved 134 older adults attending a twice-weekly low-intensity fitness program. In addition to clinical history and serum parameters, we assessed fat-free mass using dual-energy X-ray absorptiometry, total bone and cortical bone cross-sectional areas, and trabecular and cortical bone mineral density for the tibia and radius by peripheral quantitative computed tomography. RESULTS After applying multivariate linear regression models, adjusting for sex, age, body mass index, fat mass and fat-free mass, and creatinine, the association between 25-hydroxyvitamin D and bone parameters was significant for total bone and cortical bone cross-sectional areas in the radius (partial R (2) = 0.05 and 0.09, respectively) and for trabecular bone mineral density and cortical bone cross-sectional area in the tibia (partial R (2) = 0.11 and 0.02, respectively). CONCLUSION These findings support the idea that serum 25-hydroxyvitamin D levels and bone parameters are linked in older adults. Longitudinal studies are needed to establish whether vitamin D levels over time are associated with changes in these parameters.
Appearance-based gaze tracking with spectral clustering and semi-supervised Gaussian process regression

Two of the challenges in appearance-based gaze tracking are: 1) prediction accuracy, 2) the efficiency of calibration process, which can be considered as the collection and analysis phase of labelled and unlabelled eye data. In this paper, we introduce an appearance-based gaze tracking model with a rapid calibration. First we propose to concatenate local eye appearance Center-Symmetric Local Binary Pattern(CS-LBP) descriptor for each subregion of eye image to form an eye appearance feature vector. The spectral clustering is then introduced to get the supervision information of eye manifolds on-line. Finally, taking advantage of eye manifold structure, a sparse semi-supervised Gaussian Process Regression(GPR) method is applied to estimate the subject's gaze coordinates. Experimental results demonstrate that our system with an efficient and accurate 5-points calibration not only can reduce the run-time cost but also can lead to a better accuracy result of 0.9°.