Miracle-dz/UniFAR-FTUs huggingface dataset:
Economic insecurity, individual behavior and social policy

This paper is an attempt to return the discussion on social insurance and protection to its economic foundations. The paper uses a framework proposed by Ehrlich and Becker (1972) in the economics of insurance literature to first clarify the concepts and then take a comprehensive approach to insurance and protection. The approach starts with the choice problem of a representative individual facing risk, who chooses optimal levels of market insurance, self-insurance and self-protection. Market insurance and self-insurance transfer incomes between good states and bad (without changing the probabilities) while self-protection lowers the probability of the bad state (without affecting any transfers across states). Prices and costs are crucial in determining the optimal allocation. The paper illustrates the usefulness of the framework by considering the example of unemployment insurance (as market insurance), precautionary saving (as self-insurance) and investments in human capital (as self-protection). Government action is warranted from an efficiency point of view only if markets for some instruments are missing, or if there are distortions that prevent individuals from achieving their optimal insurance and protection levels.
Population genetics of Scirtothrips perseae: tracing the origin of a recently introduced exotic pest of Californian avocado orchards, using mitochondrial and microsatellite DNA markers

The Californian avocado industry has recently been impacted by the establishment of three exotic arthropod pests that are native to Mexico and Central America. Establishment of all three pests is thought to have resulted from illegal movement of host plants (avocado) into California. To identify likely sources and routes of entry of such pest invasions, we examined the population genetics of the most recent invader, avocado thrips [Scirtothrips perseae Nakahara (Thysanoptera: Thripidae)], using mitochondrial DNA (mtDNA) and microsatellite markers. The mtDNA sequences revealed three geographically distinct and divergent lineages, of which the mtDNA haplotypes of Californian individuals were most closely related to populations in the center of the pest's native range. Analysis of allele frequencies at four microsatellite loci added resolution, indicating Coatepec Harinas, Mexico, as the most likely source of the Californian population. Statistically, we did not detect any bottleneck in population size associated with the invasion of California. However, estimates of the effective population size of the invading population suggest that a severe bottleneck occurred, indicating that the quantity of host‐plant material entering California was small. Our findings implicate Coatepec Harinas, a large avocado germplasm and breeding center, as the most likely source of the introduced Californian population of S. perseae and as a likely source of previous and future avocado pest introductions. Efforts to identify natural enemies of S. perseae for biological control should focus on Coatepec Harinas and immediate surrounds. Moreover, identification of the source of invasive pests enables the establishment and enforcement of plant quarantine and free‐trade protocols.
A distributed advanced analytical trust model for VANETs

In this paper we propose a trust model based on a Markov chain in order to formalize the trust metric variation and its stability in the context of Vehicular Ad hoc Networks (VANETs). The proposed model takes into account not only the dynamic trust metric variation according to the vehicles behaviors, but also the constraints related to the monitoring process. In our model each vehicle can act as monitor and update the trust metric of its neighbors according to their behavior in the network. In addition, our model can be customized through different parameters like the trust interval and the number of transitions needed to reach the highest trust level. This flexibility enables to adapt the model according to the application context. The performance evaluation of the proposed model is presented with different parameters and two types of disruptive vehicles are taken into account: malicious and selfish. The obtained results show the resistance, the robustness and the incentive of the proposed model against the fluctuations of the vehicles behaviors.
Characteristics of the nuclear (18S, 5.8S, 28S and 5S) and mitochondrial (12S and 16S) rRNA genes of Apis mellifera (Insecta: Hymenoptera): structure, organization, and retrotransposable elements

As an accompanying manuscript to the release of the honey bee genome, we report the entire sequence of the nuclear (18S, 5.8S, 28S and 5S) and mitochondrial (12S and 16S) ribosomal RNA (rRNA)‐encoding gene sequences (rDNA) and related internally and externally transcribed spacer regions of Apis mellifera (Insecta: Hymenoptera: Apocrita). Additionally, we predict secondary structures for the mature rRNA molecules based on comparative sequence analyses with other arthropod taxa and reference to recently published crystal structures of the ribosome. In general, the structures of honey bee rRNAs are in agreement with previously predicted rRNA models from other arthropods in core regions of the rRNA, with little additional expansion in non‐conserved regions. Our multiple sequence alignments are made available on several public databases and provide a preliminary establishment of a global structural model of all rRNAs from the insects. Additionally, we provide conserved stretches of sequences flanking the rDNA cistrons that comprise the externally transcribed spacer regions (ETS) and part of the intergenic spacer region (IGS), including several repetitive motifs. Finally, we report the occurrence of retrotransposition in the nuclear large subunit rDNA, as R2 elements are present in the usual insertion points found in other arthropods. Interestingly, functional R1 elements usually present in the genomes of insects were not detected in the honey bee rRNA genes. The reverse transcriptase products of the R2 elements are deduced from their putative open reading frames and structurally aligned with those from another hymenopteran insect, the jewel wasp Nasonia (Pteromalidae). Stretches of conserved amino acids shared between Apis and Nasonia are illustrated and serve as potential sites for primer design, as target amplicons within these R2 elements may serve as novel phylogenetic markers for Hymenoptera. Given the impending completion of the sequencing of the Nasonia genome, we expect our report eventually to shed light on the evolution of the hymenopteran genome within higher insects, particularly regarding the relative maintenance of conserved rDNA genes, related variable spacer regions and retrotransposable elements.
The Promise of Kickstarter: Extents to Which Social Networks Enable Alternate Avenues of Economic Viability for Independent Musicians Through Crowdfunding

Since its inception in 2009, Kickstarter, a crowdsourced funding site, has been a platform for independent creative projects to get funding, ostensibly providing alternate routes of economic viability outside of a traditional framework of creative production and distribution. Kickstarter comes onto the scene after the proliferation of online social networking sites, through which bridging social capital ties are more easily maintained. This article investigates the ways in which independent musicians have used Kickstarter in conjunction with pre-existing social networks to fund their album and sustain themselves and their artistic endeavors economically while also exploring how social networks provide ways for these “Kickstarter campaigns” to reach potential backers (funders). Through three online surveys targeting musicians, their backers, and general Kickstarter backers, yielding a total of 61 respondents, this article finds that pre-existing personal social networks and relations are imperative to the successful funding of Kickstarter campaigns.
Your morning cuppa and the language of disability: a study of usage of metaphors and attitudes in telugu news reporting

Language is an important arbiter of meaning: it builds our understanding of the world and shapes our beliefs. What we know and what we believe about a particular phenomenon has a lot to do with the specific words used to describe and discuss it. Framing disability language in the vernacular media is a matter of contentious debate. Much abuse and harassment of disabled persons occurs as a matter of ―hate reporting‖ in journalism, which is as offensive as an abusive act or expression. The ―objective reporting‖ of journalism has been redirected and hijacked by the ―dominant meaning‖ of elite media in congruence with their ideology. The impact of journalism on framing language related to disability in the news media often negatively impacts the lives of people with disabilities. Ableist language frames are also responsible for creating, modifying and even changing societal and individual attitudes. The most commonly found Ableist vocabulary, often used metaphorically, such as „going blind‟, „turning a deaf ear‟, and so on in print media, lends meanings of deficit and worthlessness to disability. Such usage gives us ample evidence of conceptualizations and beliefs that inform the contemporary understanding of disability. Early insights from frame analysis of Telugu regional print media have prompted closer attention to the language of disability that filters audience perspectives about human differences. This paper investigates the dynamics of disability terminology in Telugu newspapers and focuses in the inadvertent and habitual usage of stigmatizing terminology in media, which allows us to identify the realities of a life of difference physical, cognitive or cultural.
L1 bounds in normal approximation

The zero bias distribution W of W, defined though the characterizing equation EWf(W) = 2 Ef 0 (W ) for all smooth functions f, exists for all W with mean zero and finite variance 2 . For W and W defined on the same probability space, the L 1 distance between F, the distribution function of W with EW = 0 and Var(W) = 1, and the cumulative standard normal has the simple upper bound ||F ||1 2E|W W|. This inequality is used to provide explicit L 1 bounds with moderate-sized constants for independent sums, projections of cone measure on the sphere S(‘ p), simple random sampling and combinatorial central limit theorems.
Deep Learning for Drug Target Prediction

An important computational tool in drug design is target prediction where either for a given chemical structure the interacting biomolecules (e.g. proteins) must be identified. Chemical structures interact with different biomolecules if they have similar 3D structure. Thus, the outputs of the prediction are highly interdependent from each other. Furthermore, we have partially labelled molecules since not all training molecules are measured of being active on each biomolecule. The Merck Kaggle challenge on chemical compound activity was won by Hinton’s group with deep networks. This indicates the high potential of deep learning in drug design and attracted the attention of big pharma. However, the unrealistically small scale of the Kaggle dataset does not allow to assess the value of deep learning in drug target prediction if applied to in-house data of pharmaceutical companies. Even a publicly available drug activity data base like ChEMBL is magnitudes larger than the Kaggle dataset. ChEMBL has 13 M compound descriptors, 1.3 M compounds, and 5 k drug targets, compared to the Kaggle dataset with 11 k descriptors, 164 k compounds, and 15 drug targets. On the ChEMBL database, we compared the performance of deep learning to seven target prediction methods, including two commercial predictors, three predictors deployed by pharma, and machine learning methods that we could scale to this dataset. Deep learning outperformed all other methods with respect to the area under ROC curve and was significantly better than all commercial products. Deep learning surpassed the threshold to make virtual compound screening possible and has the potential to become a standard tool in industrial drug design.
Binary ant colony algorithm with Balanced search bias

Binary ant colony algorithm has good performance in the function optimization problem. However, the drawbacks that easy to fall into the local optimization stll exist. Through the analysis of “best-so-far” pheromone update rule, we get the lower probability bound under this update rule. Then binary ant colony algorithm with Balanced search bias is proposed. Experiment results have shown that the improved algorithm has good globe search ability and need small iterate times.
Resting state functional connectivity differences between behavioral variant frontotemporal dementia and Alzheimer's disease

Introduction: Alzheimer's disease (AD) and behavioral variant frontotemporal dementia (bvFTD) are the most common types of early-onset dementia. Early differentiation between both types of dementia may be challenging due to heterogeneity and overlap of symptoms. Here, we apply resting state functional magnetic resonance imaging (fMRI) to study functional brain connectivity differences between AD and bvFTD. Methods: We used resting state fMRI data of 31 AD patients, 25 bvFTD patients, and 29 controls from two centers specialized in dementia. We studied functional connectivity throughout the entire brain, applying two different analysis techniques, studying network-to-region and region-to-region connectivity. A general linear model approach was used to study group differences, while controlling for physiological noise, age, gender, study center, and regional gray matter volume. Results: Given gray matter differences, we observed decreased network-to-region connectivity in bvFTD between (a) lateral visual cortical network and lateral occipital and cuneal cortex, and (b) auditory system network and angular gyrus. In AD, we found decreased network-to-region connectivity between the dorsal visual stream network and lateral occipital and parietal opercular cortex. Region-to-region connectivity was decreased in bvFTD between superior temporal gyrus and cuneal, supracalcarine, intracalcarine cortex, and lingual gyrus. Conclusion: We showed that the pathophysiology of functional brain connectivity is different between AD and bvFTD. Our findings support the hypothesis that resting state fMRI shows disease-specific functional connectivity differences and is useful to elucidate the pathophysiology of AD and bvFTD. However, the group differences in functional connectivity are less abundant than has been shown in previous studies.
Evaluation of a WENO method in implicit Large Eddy Simulation of circular cylinder flow

Implicit LES results of a cylinder flow with high order numerical methods in a coarse and a refined grid were compared. The weighted essentially non-oscillatory (WENO) scheme is employed for convective flux while central differencing schemes are used for viscous terms. Several modifications were made to the high order accuracy scheme. Results show that the high order accurate schemes adopted in this paper is feasible and efficient.
The development of online trust among construction teams in Finland

SUMMARY: Construction is a complex process involving many different stakeholders. It is important that information among these stakeholders flows smoothly. A crucial aspect of the success of a project depends on the effective sharing of knowledge among the different people. Trust is important for knowledge transfer especially for online applications. There are different types of trust that have implications for knowledge sharing among the construction teams. This paper describes the importance of trust that we have identified during knowledge sharing among four construction projects in Finland. It begins with identification of the needs of online technology among construction teams. It is followed by a brief review of the different types of online trust. Section Three describes the case study methodology. In Section Four the implications of the online trust among construction teams are then discussed. Section Five concludes with suggestions for promoting trust among construction teams for knowledge sharing.
A Distance Function-Based Multi-Objective Evolutionary Algorithm

A multi-objective evolutionary algorithm (MOEA) approach is presented in this paper. The algorithm (DFBMOEA) aims to improve convergence of Paretobased MOEAs to the true Pareto optimal set/Pareto front and remove decision maker interaction from the process. A novel distance function is used as a fitness function for MOEA. A range equalisation function and a reference vector are utilised to eliminate the prior knowledge required from decision makers. A 0 & 1 knapsack problem [27] was tested to demonstrate the performance of our approach compared to two leading MOEAs: Non-dominated Sorting Genetic Algorithm II (NSGA II) and Strength Pareto EA II (SPEA II). The results show that our approach produced a set of effective Pareto optimal solutions that are comparable to the two leading MOEA s.
Dart: A Fast Heuristic Algebraic Reconstruction Algorithm for Discrete Tomography

Discrete tomography (DT) is concerned with the tomographic reconstruction of images that consist of only a small number of gray levels. DT reconstruction problems are usually underdetermined. Therefore, incorporation of heuristic rules to guide the reconstruction algorithm towards an optimal as well as intuitive solution would be valuable. In this paper, we introduce DART: a new, heuristic DT algorithm that is based on an iterative algebraic reconstruction method. Starting from a continuous reconstruction, a discrete image is reconstructed by consistent updating of border pixels. Using simulation experiments, it is shown that the DART algorithm is capable of computing high quality reconstructions from substantially fewer projections than required for conventional continuous tomography.
Group Communication for Real-time Continuous Media

In distributed applications, a group of multiple application processes have to send and receive multimedia messages by using the high-speed network. The multimedia message at the application level is decomposed into multiple smaller packets which are transmitted in the network. The multimedia applications may not mind if some packets are lost and in what order packets from di erent processes are received. The application process is required to receive more packets than the minimum receipt ratio " required by the application. In addition, the messages have to be delivered to the destinations in the predetermined time units in the real time applications. The communication system delivers the messages to the destinations in the group so as to satisfy the receipt ratio " and the deadline . The protocol is based on the fully distributed control scheme, i.e. no master controller.
Synchronization of Chaotic Systems by Using Limited Nussbaum Gain Method

In this study, we propose a novel kind of limited Nussbaum gain method to solve the unknown control direction problem of chaotic systems. It is necessary to consider the unknown control direction situation when chaos synchronization is used for secure communication. Also it is very useful to design a small gain with a Nussbaum method if the Nussbaum gain method is used in a real engineering system. The smaller a gain is designed, the safer and more stable a Nussbaum gain method is used. According to the above principles, a limited gain Nussbaum method is used to solve the uncertainties of chaotic system, such as unknown parameters, unknown nonlinear functions and unknown input or control directions. At last, detailed numerical simulation is done to testify the rightness and effectiveness of the proposed method.
Study on the Inaccuracies of Air Velocity Measured by Pitots with Different Outer Diameter in a Air Duct

The inaccuracies for air velocity measured by Pitots with different diameter have been demonstrated by several experiments. It is defined that the measurement ranges of air velocity by Pitots with different outer diameter. Experiments show that: measurements by Pitot are larger than the true values. The measurement error of air velocity will be smaller if using the Pitot with a smaller outer diameter. The simplified function of correction coefficient and ratio of diameters is deduced by theoretical analysis. The maximum error of correction coefficients is 0.94%, which gained by the simplified function expression is compared with experimental data.
Special issue on interactive question answering: Introduction

Abstract In this introduction, we present our overview of interactive question answering (IQA). We contextualize IQA in the wider field of question answering, and establish connections to research in Information Retrieval and Dialogue Systems. We highlight the development of QA as a field, and identify challenges in the present research paradigm for which IQA is a potential solution. Finally, we present an overview of papers in this special issue, drawing connections between these and the challenges they address.
Bubbling and frothing liquids

We present a discrete particle based method capable of creating very realistic animations of bubbles in fluids. It allows for the generation (nucleation) of bubbles from gas dissolved in the fluid, the motion of the discrete bubbles including bubble collisions and drag interactions with the liquid which could be undergoing complex free surface motion, the formation and motion of coupled foams and the final dissipation of bubbles. This allows comprehensive simulations of dynamic bubble behavior. The underlying fluid simulation is based on the mesh-free Smoothed Particle Hydrodynamics method. Each particle representing the liquid contains an amount of dissolved gas. Gas is transferred from the continuum fluid model to the discrete bubble model at nucleation sites on the surface of solid bodies. The rate of gas transport to the nucleation sites controls the rate of bubble generation, producing very natural time variations in bubble numbers. Rising bubbles also grow by gathering more gas from the surrounding liquid as they move. This model contains significant bubble scale physics and allows, in principle, the capturing of many important processes that cannot be directly modeled by traditional methods. The method is used here to realistically animate the pouring of a glass of beer, starting with a stream of fresh beer entering the glass, the formation of a dense cloud of bubbles, which rise to create a good head as the beer reaches the top of the glass.
Adaptive Control of Dual-Arm Space Robot System in Joint Space

In this paper, the coordinated control of the base's attitude and its arm's joints of dual-arm space robot system is studied. Firstly, in order to overcome the difficulty that the dynamic equations of dual-arm space robot system can not be linearly parameterized, the system is modeled as under-actuated robot system. And then with the augmentation approach, we demonstrate that the dynamic equations of the system can be linearly dependent on inertial parameters. Based on the results, an adaptive control scheme of dual-arm space robot system for coordinated motion between the base's attitude and the arm's joints is developed. The asymptotic stability of the control scheme is proved with Lyapunov method. A planar dual-arm space robot system with two objects is simulated to verify the proposed control scheme
Almost-tight hardness of directed congestion minimization

Given a set of demands in a directed graph, the <i>directed congestion minimization</i> problem is to route every demand with the objective of minimizing the heaviest load over all edges. We show that for any constant ϵ > 0, there is no Ω(log<sup>1−ϵ</sup> <i>M</i>)-approximation algorithm on networks of size <i>M</i> unless <i>NP</i> ⊆ <i>ZPTIME</i>(<i>n</i><sup>polylog <i>n</i></sup>). This bound is almost tight given the <i>O</i>(log <i>M</i>/log log <i>M</i>)-approximation via randomized rounding due to Raghavan and Thompson.