Miracle-dz/UniFAR-FTUs huggingface dataset:
Sharing Knowledge: A Guide to Effective Science Communication

Human knowledge is growing faster today than at any time in history - far outracing our ability to share it. The gap between those with access to knowledge and those without has implications for future global stability. At the national level, the effectiveness of knowledge sharing influences the rate at which countries grow and achieve sustainability. Sharing Knowledge is a guide for scientific managers, researchers, communicators and policy makers on practical, low-cost ways to add value to science by assisting its adoption or commercialisation. It is also a valuable text for the teaching of public awareness of science and science communication at tertiary level.
Forcefree Control with Independent Compensation for Articulated Robot Arms and Its Applications

In this paper, the forcefree control with independent compensation is described. The forcefree control with independent compensation, in which inertia, friction and gravity torque are compensated independently, can realize flexible motion of robot arms. The forcefree control with independent compensation is compared with other force control methods such as compliance control. Various applications of the forcefree control with independent compensation are also explained.
Predicting and Preventing Child Maltreatment: A Bio-Cognitive Transactional Approach

In this chapter, I consider the pathology-amplifying transactional processes that involve (1) adults who interpret caregiving challenges as threats, and who respond to such threats with " defensive " reactions, and (2) children who are exceptionally reactive to their social environment. Within this dyadic combination, the responses shown by one member foster increased stress and maladaptive coping responses in the other member (see Fig. 1). This process reflects a bio-cognitive transactional system that may serve to foster mal-or mistreatment within parent-child relationships – and may even lead to perpetuation of such interactions across generations (e. We also consider the utility of intervention processes early in life that may prevent or attenuate the mistreatment or maltreatment of young children that often follows from combined parent and child risk features. A transactional approach can be employed not only to explain or predict child maltreatment, but also as a conceptual framework for remediation.
Small Molecule-Induced Allosteric Activation of the Vibrio cholerae RTX Cysteine Protease Domain

Vibrio cholerae RTX (repeats in toxin) is an actin-disrupting toxin that is autoprocessed by an internal cysteine protease domain (CPD). The RTX CPD is efficiently activated by the eukaryote-specific small molecule inositol hexakisphosphate (InsP6), and we present the 2.1 angstrom structure of the RTX CPD in complex with InsP6. InsP6 binds to a conserved basic cleft that is distant from the protease active site. Biochemical and kinetic analyses of CPD mutants indicate that InsP6 binding induces an allosteric switch that leads to the autoprocessing and intracellular release of toxin-effector domains.
Flattened Data in Convolutional Neural Networks: Using Malware Detection as Case Study

Convolutional Neural Networks (CNNs) are very powerful variants of multilayer perceptron models inspired by human's brain neural system to reveal local, spatial correlation in a series of data. While CNNs are popularly used for image recognition nowadays, it is also possible to apply CNNs in other areas, for example, detection of malicious software. In this paper, we show how CNNs may be used to improve the classification of malicious software due to the high-level feature abstraction and equal-variance property against noises. Taking advantages of convolution kernels, CNNs are naturally born for pattern recognition on images only. For this application, we introduce a new transformation technique which converts a series of event logs into flattened data with two-dimensional features so that CNNs can be trained to detect malicious behaviors effectively. With the combination property and the proposed flattened input format, CNN can perform a k-skip-n-gram dimensionality reduction which learns more flexible and complex patterns comparing to the traditional solutions. Our preliminary results show that our latest CNNs-based malware detection engine reaches 93.012% prediction accuracy and 12.9% FNR under 32,000 samples of a training set. To our knowledge, this is the first paper discussing the application and effectiveness of CNNs on malware detection.
COMPLEX INTERACTIONS OF OCTOPAMINE AND TYRAMINE ORCHESTRATE SUGAR RESPONSIVENESS AND STARVATION RESISTANCE IN DROSOPHILA

18 Introduction . 19 Methods . 20 Fly stocks and culture . 20 Starvation procedure . 20 Survival experiments . 20 Sugar response test . 21 PER assay validation . 22 Carbohydrate measurement . 22 Electrophysiological recording . 22 Statistics . 23 Results . 24 tßh nM18 mutants respond less to sucrose . 24 Physiological response to starvation is weaker in tßh nM18 compared to wild type flies . 25 Acute tßh induction rescues the sugar response phenotype . 27 Sensitivity of taste receptor neurons is lower in tßh nM18 mutants . 28 Differential outcome of OA/TA-receptor manipulations on survival and sugar responsiveness . 29
Housing Demand in Italy: A Microeconometric Analysis

This paper estimates tenure choice and housing demand equations in Italy, using cross-section data from the Bank of Italy 1991 Survey. The data include information on housing characteristics that is used to calculate hedonic price indexes for the Italian housing market. Empirical literature in this field is extended by using the hedonic price approach in order to take into account the problem of rent control and rationing in the rental sector. Then, the results on price and income elasticities are found to be similar to those reported in previous housing studies for the USA, the UK and Sweden.
ARE THE KINEMATICS OF DLAs IN AGREEMENT WITH THEIR ARISING IN THE GAS DISKS OF GALAXIES?

We demonstrate in this paper that the velocity widths of the neutral gas in damped Lyα (DLA) systems are inconsistent with these systems originating in gas disks of galaxies, similar to those seen in the local universe. We examine the gas kinematics of local galaxies using the high-quality H i 21 cm data from the H i Nearby Galaxies Survey and make a comparison with the velocity profiles measured in the low-ionization metal lines observed in DLAs at high redshifts. The median velocity width of z = 0 H i gas above the DLA column density limit of NH i = 2 × 1020 cm−2 is approximately 30 km s−1, whereas the typical value in DLAs is a factor of 2 higher. We argue that the gas kinematics at higher redshifts are increasingly influenced by gas that is not participating in ordered rotation in cold disks, but is more likely associated with tidal gas related to galaxy interactions or processes such as superwinds and outflows. An analysis of the H i in the local interacting starburst galaxy M 82 shows that the velocity widths in this galaxy are indeed similar to what is seen in DLAs.
Improved Circuit Model of Photovoltaic Array

A circuit based model of photovoltaic array (PV) suitable for simulation studies of solar power systems is proposed in this paper. The proposed model is realised using Power System Block Set under MATLAB/SIMULINK, however, it can be constructed using standard simulation software such as PSPICE. The proposed circuit model has several advantages: simple, reliable, allows simulation of basic cells, group of cells, or mismatched panels that work under different operating conditions. The obtained results of both uniform and mismatched PVs prove the validity of the proposed model to simulate the non-linear behaviour of photovoltaic array not only to understand the operation of PV systems but also to design a proper maximum power point tracker to extract the maximum possible power from the photovoltaic array.
Large Sample Theory for an Estimatorof the Mean of a Counting Processwith Panel Count

We study an estimator of the mean function of a counting process based on \panel count" data which has been proposed by Sun and Kalbbeisch (1995). The setting for \panel count data" is one in which n independent subjects, each with a counting process with common mean function, are observed at several possibly diierent times during a study. Following a model proposed by Schick and Yu (1997), we allow the number of observation times, and the observation times themselves, to be random variables. Our goal is to estimate the mean function of the counting process. We show that the estimator of the mean function proposed by Sun and Kalbbeisch (1995) can be viewed as a pseudo-maximum likelihood estimator when a non-homogeneous Poisson process model is assumed for the counting process. We then show that the estimator of Sun and Kalbbeisch (1995) is consistent, and derive the pointwise asymptotic distribution for the estimator.
Eulerian Smoke Simulation on the GPU MSc Computer Animation and Visual Effects Master Thesis

The realistic simulation of smoke motion has always been a popular demand in the visual effects industry. However, systems that implemented this fluid behavior have been predominately non-interactive, high-quality offline rendering systems. The purpose of this thesis has been to provide an efficient and interactive tool for the realistic simulation of smoke. A fast and efficient method for real-time Eulerian smoke simulation on the GPU is presented. The implemented application uses an OpenCL gas solver, along with a real-time iso-surface extraction method for the rendering of the fluid.
Plug-and-Play Model Predictive Control for Load Shaping and Voltage Control in Smart Grids

This paper presents a predictive controller for handling plug-and-play charging requests of flexible loads in a distribution system. Two types of flexible loads are defined: 1) deferrable loads that have a fixed power profile but can be deferred in time and 2) shapeable loads that have flexible power profiles but fixed energy requests, such as plug-in electric vehicles. The proposed method uses a hierarchical control scheme based on a model predictive control formulation for minimizing the global system cost. The first stage computes a reachable reference that trades off deviation from the nominal voltage with the required generation control. The second stage uses a price-based objective to aggregate flexible loads and provide load shaping services, while satisfying system constraints and users’ preferences at all times. It is shown that the proposed controller is recursively feasible under specific conditions, i.e., the flexible load demands are satisfied and bus voltages remain within the desired limits. Finally, the proposed scheme is illustrated on a 55 bus radial distribution network.
SIOPRED performance in a Forecasting Blind Competition

In this paper we present the results obtained by applying our automatic forecasting support system, named SIOPRED, over a data set of time series in a Forecasting Blind Competition. In order to apply our procedure for providing point forecasts it has been necessary to develop an interactive strategy for the choice of the suitable length of the seasonal cycle and the seasonality form for a generalized exponential smoothing method, which have been obtained using SIOPRED. For the choice of those essential characteristics of forecasting methods, also a certain multi-objective formulation which minimizes several measures of fitting is used. Once these specifications are established, the model parameters (i.e. initial conditions and smoothing parameters) are also selected by using SIOPRED, which applies non-linear optimization and Soft Computing techniques without intervention by the forecaster in a completely automated way. Finally, our interactive proposal uses a multi-objective approach for selecting the data pattern.
A scheduling algorithm for shared sensor and actuator networks

Shared Sensor and Actuator Networks (SSAN) represents a new design trend of Wireless Sensor Network (WSNs) that allows the system infrastructure to be shared among multiple applications submitted by different users instead of the original application-specific network design. In this context, we propose a task scheduling algorithm that well utilizes the characteristics of applications with common tasks to improve the system energy efficiency, so as to extend the most concerned performance metric system lifetime. Our proposal is validated by both computer simulations and real sensor nodes tests.
Accessing and activating social capital resources in Buffalo's public high schools

The contents of this paper were presented by the author in June 2006 at the University of Cambridge’s 3rd Annual Postgraduate Symposium in Education. The paper summarises and presents conclusions from a dissertation completed shortly thereafter. The paper first examines the distribution of social capital both across and within a representative sample of six public high schools in Buffalo, New York, an industrial city that has suffered massive urban decline and is characterised by high rates of social dislocation. Though SPSS analyses indicate social capital’s positive relationship to academic achievement, individual levels of social capital are shown to be mediated most prominently by socio-economic status and, the higher a student’s household income, the greater their social capital resources tend to be. While quantitative analysis suggests that some actors are constrained in their access to social capital (based especially on socio-economic status) as a result of structural forces, it does not conclude that they are controlled by them. Many disadvantaged students make use of social capital resources and achieve ‘against the odds’. Qualitative techniques explore the processes behind Buffalo students’ access to, and activation of, social capital resources. These processes are revealed to vary according to students’ school and social contexts.
Agricultural Growth in India: Examining the Post-Green Revolution Transition

India has enjoyed rapid economic growth over the past forty years, GDP per capita (PPP$) accelerating from less than 1% in the 1970s to over 5.8% in the 2000s. As incomes have risen, consumer demand has shifted from staple grains toward higher valued foods, such as horticultural and livestock products. Indian farmers appear to be meeting these new growth opportunities. But as production shifts, questions are being raised about agriculture’s ability to meet the basic food needs of India’s 1.24 billion citizens. Central to these questions has been the waning impact of cereal grain technologies typified by the Green Revolution. Our purpose is to examine the productivity growth implications of farmers’ decisions to diversify production and to assess new sources of growth in Indian agriculture. In doing so, we construct new production and productivity accounts and evaluate total factor productivity (TFP) growth, from 1980 to 2008, at the national, regional, and state levels. Results suggest renewed growth in aggregate TFP growth despite a slowdown in cereal grain yield growth. TFP growth appears to have shifted to the Indian South and West, led by growth in horticultural and livestock products.
Online Search Interface for the Sejong Korean-Japanese Bilingual Corpus and Auto-interpolation of Phrase Alignment

A user-friendly interface to search bilingual resources is of great help to NLP developers as well as pure-linguists. Using bilingual resources is difficult for linguists who are unfamiliar with computation, which hampers capabilities of bilingual resources. NLP developers sometimes need a kind of workbench to check their resources. The online interface this paper introduces can satisfy these needs. In order to implement the interface, this research deals with how to align Korean and Japanese phrases and interpolates them into the original bilingual corpus in an automatic way.
The SRAMO Techique for Analysis and Reuse of Requirements in Multi-agent Application Engineering

The increasing interest on the multi-agent software development paradigm turns necessary the elaboration of appropriate techniques and methodologies. A Multiagent Application Engineering process is characterized by the construction of applications based on agent-oriented reusable software artifacts. This paper presents SRAMO, an ontology-driven technique for requirement analysis of multi-agent applications by reusing domain models representing common and variable requirements of a family of multi-agent applications in a domain. The requirements of a particular application are represented in models obtained through the instantiation of the ONTORMAS ontology that expresses the knowledge of the MAAEM methodology for Multi-agent Application Engineering, MAAEM integrates SRAMO and techniques for design and implementation of a specific application in a domain family. Part of a case study employing SRAMO for modeling RecomTour, a multi-agent application for recommendation of touristic packages through Web usage mining and collaborative filtering is also
Effect of Sodium Sulfite, Sodium Dodecyl Sulfate, and Urea on the Molecular Interactions and Properties of Whey Protein Isolate-Based Films

Whey protein coatings and cast films are promising for use as food packaging materials. Ongoing research is endeavoring to reduce their permeability. The intention of this study was to evaluate the effect of the reactive additives sodium sulfite, sodium dodecyl sulfate (SDS), and urea on the oxygen barrier, water vapor barrier, and protein solubility of whey protein cast films. The concentration of the reactive additives was 1 to 20 wt. -%. Dried whey protein cast films were used as substrate materials. The water vapor transmission rate, the oxygen permeability, and the protein solubility were measured. Effective diffusion coefficients and effective sorption coefficients were calculated from the results of the water vapor sorption experiments. The presence of sodium sulfite resulted in an increased number of hydrophobic interactions and hydrogen bonds and a slightly decreased number of disulfide bonds. The oxygen permeability decreased from 68 to 46 cm3 (STP/standard temperature and pressure) 100 μm (m2 d bar)−1 for 1 wt. -% SDS in the whey protein cast film. The water vapor transmission rate decreased from 165 to 44 g 100 μm (m2 d)−1 measured at 50 to 0% r. h. for 20 wt. -% SDS in the whey protein cast film. The reduction in the water vapor transmission rate correlated with the lower effective diffusion coefficient.
Investigating multisensory spatial cognition through the phenomenon of extinction

The study of pathologic behavioral phenomena following damage to the central nervous system has substantially contributed to our understanding of the normal organization of cognitive brain functions. The investigation of clinical extinction in neurological patients, for example, revealed that events occurring in the immediate proximity to the body (i.e. in near peripersonal space) undergo a high degree of multisensory processing. Indeed, visual–tactile extinction is most severe near a given body part: tactile stimuli on the contralesional hand are more severely extinguished by visual stimuli presented near, as compared to far, from the ipsilesional hand. Here, extinction-based evidence will first be reported to illustrate the peculiar nature of multisensory processing occurring in pericorporeal space. Second, the plastic features of such processing following tool-use will be presented. Our findings in patients with visual–tactile extinction show that the use of a tool as an extension of reachable space may dynamically modulate the multisensory processing of farther, non-reachable sectors of space. Finally, a normal model of the clinical phenomenon of tactile extinction is proposed and demonstrated. We show that, despite accurate and comparable perception of single stimulation to the right or left hand, somatosensory performance is lower when reporting double simultaneous stimuli in neurologically healthy participants, thus replicating the typical extinction patient’s behavior. This intrinsic limitation of the somatosensory perceptual system was exploited to further investigate multisensory interactions between proprioceptive–kinesthetic and tactile inputs in normal subjects. In this respect, we demonstrate that experiencing the functional property of a tool may selectively modulate the tactile extinction-like phenomenon in healthy subjects. These findings, in addition to validating the normal model of tactile extinction, may open new perspectives for investigating the pervasive aspects of multisensory processing in humans and their neurophysiological bases.
Collaborative Multi-Level Embedding Learning from Reviews for Rating Prediction

We investigate the problem of personalized review-based rating prediction which aims at predicting users' ratings for items that they have not evaluated by using their historical reviews and ratings. Most of existing methods solve this problem by integrating topic model and latent factor model to learn interpretable user and items factors. However, these methods cannot utilize word local context information of reviews. Moreover, it simply restricts user and item representations equivalent to their review representations, which may bring some irrelevant information in review text and harm the accuracy of rating prediction. In this paper, we propose a novel Collaborative Multi-Level Embedding (CMLE) model to address these limitations. The main technical contribution of CMLE is to integrate word embedding model with standard matrix factorization model through a projection level. This allows CMLE to inherit the ability of capturing word local context information from word embedding model and relax the strict equivalence requirement by projecting review embedding to user and item embeddings. A joint optimization problem is formulated and solved through an efficient stochastic gradient ascent algorithm. Empirical evaluations on real datasets show CMLE outperforms several competitive methods and can solve the two limitations well.
A Clock Skew Replication Attack Detection Approach Utilizing the Resolution of System Time

The clock skew, or the physical ticking rate difference between two digital clocks, has been revealed to have potential on serving as the device fingerprint for identification/authentication purpose. However, it remains as an open issue to detect clock skew replication behavior, which is realized by sending altered timestamps. In this study, it is confirmed that an attacker may fake any target skew with the error being no more than 1ppm in local network environments. Besides, it is also observed that the value of fake timestamps are affected by the time resolution of the attacker's system clock. When the resolution is 1 ms or lower, a relatively large jump between consecutive offsets happens regularly, and the scale of each jump is theoretically the very time resolution of the attacker's system clock. This characteristic is thus adopted to develop a filtering method such that the receiver is able to detect fake timestamps. When the periodical jumps are detected, the filter module abandons these jumps to recover the original clock skew. Experimental results on 15.6 ms and 1 ms time resolutions show that the developed method is effective to detect skew replication attacks, and the errors of the recovered clock skews are no more than 1ppm from the real skews of the attackers.