Miracle-dz/UniFAR-FTUs huggingface dataset:
MSS: Investigating the Effectiveness of Domain Combinations and Topic Features for Word Sense Disambiguation

We participated in the SemEval-2010 Japanese Word Sense Disambiguation (WSD) task (Task 16) and focused on the following: (1) investigating domain differences, (2) incorporating topic features, and (3) predicting new unknown senses. We experimented with Support Vector Machines (SVM) and Maximum Entropy (MEM) classifiers. We achieved 80.1% accuracy in our experiments.
Learning Translation Invariant Kernels for Classification

Appropriate selection of the kernel function, which implicitly defines the feature space of an algorithm, has a crucial role in the success of kernel methods. In this paper, we consider the problem of optimizing a kernel function over the class of translation invariant kernels for the task of binary classification. The learning capacity of this class is invariant with respect to rotation and scaling of the features and it encompasses the set of radial kernels. We show that how translation invariant kernel functions can be embedded in a nested set of sub-classes and consider the kernel learning problem over one of these sub-classes. This allows the choice of an appropriate sub-class based on the problem at hand. We use the criterion proposed by Lanckriet et al. (2004) to obtain a functional formulation for the problem. It will be proven that the optimal kernel is a finite mixture of cosine functions. The kernel learning problem is then formulated as a semi-infinite programming (SIP) problem which is solved by a sequence of quadratically constrained quadratic programming (QCQP) sub-problems. Using the fact that the cosine kernel is of rank two, we propose a formulation of a QCQP sub-problem which does not require the kernel matrices to be loaded into memory, making the method applicable to large-scale problems. We also address the issue of including other classes of kernels, such as individual kernels and isotropic Gaussian kernels, in the learning process. Another interesting feature of the proposed method is that the optimal classifier has an expansion in terms of the number of cosine kernels, instead of support vectors, leading to a remarkable speedup at run-time. As a by-product, we also generalize the kernel trick to complex-valued kernel functions. Our experiments on artificial and real-world benchmark data sets, including the USPS and the MNIST digit recognition data sets, show the usefulness of the proposed method.
Multi-agent intrusion detection system in industrial network using ant colony clustering approach and unsupervised feature extraction

Industrial control systems have been globally connected to the open computer networks for decentralized management and control purposes. Most of these networked control systems that are not designed with security protection can be vulnerable to network attacks nowadays, so there is a growing demand of efficient and scalable intrusion detection systems (IDS) in the network infrastructure of industrial plants. In this paper, we present a multi-agent IDS architecture that is designed for decentralized intrusion detection and prevention control in large switched networks. An efficient and biologically inspired learning model is proposed for anomaly intrusion detection in the multi-agent IDS. The proposed model called ant colony clustering model (ACCM) improves the existing ant-based clustering approach in searching for near-optimal clustering heuristically, in which meta-heuristics engages the optimization principles in swarm intelligence. In order to alleviate the curse of dimensionality, four unsupervised feature extraction algorithms are applied and evaluated on their effectiveness to enhance the clustering solution. The experimental results on KDD-Cup99 IDS benchmark data demonstrate that applying ACCM with one of the feature extraction algorithms is effective to detect known or unseen intrusion attacks with high detection rate and recognize normal network traffic with low false positive rate
Work-related stress factors and problem drinking with special reference to measures of drinking.

Colell et al. examined the associations between drinking patterns and measures of work-related stress factors with data on 13,005 working individuals. Exposure to a noxious working environment and severe lack of social support were significantly associated with heavy drinking in men. In addition, precariousness was also associated with binge drinking in men. The authors concluded that alcohol abuse in male workers should be considered as manifestations of work-related stress. I have a concern regarding the self-administered questionnaire on alcohol consumption and problem drinking used in this study. Colell et al. quoted a reference on the quantification of alcohol use. As surveys for alcohol use tend to underestimate the amount of alcohol consumed, Colell et al. quoted a reference that both sporadic and heavy drinkers tend to accurately report the actual amount of alcohol consumed. Stockwell et al. recommended that both recent and longer-term drinking patterns should be included in surveys on alcohol consumption and problem drinking. The alcohol use disorders identification test (AUDIT) includes both recent recall and drinking patterns in the past one year. Although there is no comparative study of the validity of measures of alcohol use between AUDIT and the measures used by Colell et al., AUDIT is considered as the “gold standard” questionnaire for alcohol abuse developed by the World Health Organization. Justification for the use of the AUDIT in alcohol abuse research has been reviewed, and theAUDIT has less reporting bias for alcohol use. I also reported the validity of the AUDIT for Japanese workers.
Does Parental Unemployment Cause Right-Wing Extremism?

Recent years have witnessed a rise in right-wing extremism among German youth and young adults. This paper investigates the extent to which the experience of parental unemployment during childhood affects young people's far right-wing attitudes and xenophobia. Estimates from three German data sets show a positive relationship between growing up with unemployed parents and right-wing extremism, with xenophobia in particular. This paper uses stark differences in unemployment levels between East and West Germany, both before and after reunification, to investigate a causal relationship. Instrumental variables estimates suggest strong and significant effects of parental unemployment on right-wing extremism. Various panel estimates also point to a positive relationship. The results are consistent with classical theories of economic interest and voting behaviour which predict that persons who develop feelings of economic insecurity are more susceptible to right-wing extremism and anti-foreign sentiments.
Plasmodium berghei Δp52&p36 Parasites Develop Independent of a Parasitophorous Vacuole Membrane in Huh-7 Liver Cells

The proteins P52 and P36 are expressed in the sporozoite stage of the murine malaria parasite Plasmodium berghei. Δp52&p36 sporozoites lacking expression of both proteins are severely compromised in their capability to develop into liver stage parasites and abort development soon after invasion; presumably due to the absence of a parasitophorous vacuole membrane (PVM). However, a small proportion of P. berghei Δp52&p36 parasites is capable to fully mature in hepatocytes causing breakthrough blood stage infections. We have studied the maturation of replicating Δp52&p36 parasites in cultured Huh-7 hepatocytes. Approximately 50% of Δp52&p36 parasites developed inside the nucleus of the hepatocyte but did not complete maturation and failed to produce merosomes. In contrast cytosolic Δp52&p36 parasites were able to fully mature and produced infectious merozoites. These Δp52&p36 parasites developed into mature schizonts in the absence of an apparent parasitophorous vacuole membrane as shown by immunofluorescence and electron microscopy. Merozoites derived from these maturing Δp52&p36 liver stages were infectious for C57BL/6 mice.
Three New Pierce's Disease Pathogenicity Effectors Identified Using Xylella fastidiosa Biocontrol Strain EB92-1

Xylella fastidiosa (X. fastidiosa) infects a wide range of plant hosts and causes economically serious diseases, including Pierce's Disease (PD) of grapevines. X. fastidiosa biocontrol strain EB92-1 was isolated from elderberry and is infectious and persistent in grapevines but causes only very slight symptoms under ideal conditions. The draft genome of EB92-1 revealed that it appeared to be missing genes encoding 10 potential PD pathogenicity effectors found in Temecula1. Subsequent PCR and sequencing analyses confirmed that EB92-1 was missing the following predicted effectors found in Temecula1: two type II secreted enzymes, including a lipase (LipA; PD1703) and a serine protease (PD0956); two identical genes encoding proteins similar to Zonula occludens toxins (Zot; PD0915 and PD0928), and at least one relatively short, hemagglutinin-like protein (PD0986). Leaves of tobacco and citrus inoculated with cell-free, crude protein extracts of E. coli BL21(DE3) overexpressing PD1703 exhibited a hypersensitive response (HR) in less than 24 hours. When cloned into shuttle vector pBBR1MCS-5, PD1703 conferred strong secreted lipase activity to Xanthomonas citri, E. coli and X. fastidiosa EB92-1 in plate assays. EB92-1/PD1703 transformants also showed significantly increased disease symptoms on grapevines, characteristic of PD. Genes predicted to encode PD0928 (Zot) and a PD0986 (hemagglutinin) were also cloned into pBBR1MCS-5 and moved into EB92-1; both transformants also showed significantly increased symptoms on V. vinifera vines, characteristic of PD. Together, these results reveal that PD effectors include at least a lipase, two Zot-like toxins and a possibly redundant hemagglutinin, none of which are necessary for parasitic survival of X. fastidiosa populations in grapevines or elderberry.
Cultural values of Chinese tertiary students and the implications for first-year engagement

This study identifies the cultural values of Chinese tertiary education students and applies these findings in a discussion of the implications for first-year student engagement for this subgroup. Survey results revealed strong collectiveness and conservation needs and a marked rejection of self-enhancement. The results were compared with previous data over a 19 year period and it was found that the values held by Chinese tertiary students had not changed despite rapid socio-economical change within China during the same time frame. As such, values provide a strong platform from which to develop first-year engagement strategies for this group. Broadly speaking, engagement activities directed towards Chinese students that facilitate in-group relations and that recognise and reward the combined efforts of group members are likely to be more effective than those that focus upon the individual. Engagement activities that provide consistency, clear expectations and role clarity are more likely to encourage participation rather than those that emphasise change or surprise. Engagement activities that promote self-enhancement potentials are likely to be met with resistance, whereas those that promote transformation beyond self interests are likely to invoke motivation.
2 Background 2 . 1 Overview of

The concepts of smart cities and smart communities have started to become a reality in this age of the Internet of Things (IoT). In the midst of this IoT revolution, recently, low power wide area networking (LPWAN) technologies[1, 2, 3, 4] have become very popular, as they are an excellent fit to the IoT data traffic that are generated and consumed by many smart cities applications. For instance, if we think of city-scale IoT applications like smart metering, environment monitoring, road traffic monitoring, facility management, smart parking, street lighting, vehicle tracking, waste management, precision agriculture, and home automation, we observe that the basic communication requirements in these applications include a long radio range (i.e. several hundred meters of range), low power (i.e. an extended battery-life of several months or years), and low bandwidth (i.e. a data rate of few kbps). Thus, low power WANs are being considered as the enablers of city-scale IoT. Among different choices of low power WANs, we study one of the most popular technologies of today, which is called the LoRa WAN [2]. LoRa has so far been mainly adopted by the European countries, although recently, over 100 cities in the USA have begun to deploy city-wide LoRa networks [5]. LoRa has an advertised radio range of up to 9 miles (in line-of-sight), a data rate of up to 50kbps, and a battery life of around 10 years. Though LoRa is considered for outdoor applications, its properties can also be leveraged for indoor scenarios. As LoRa operates in the sub-GHz band, it obtains more penetration ability making it more resilient to noise and multipath. This property makes LoRa a better choice for indoor localization. Recently for localizing in large facilities (e.g. multistory buildings, large warehouse), multiple access points or beacons need to be installed due to the short range of traditional RF signals e.g. WiFi, Bluetooth Low Energy (BLE). However, due to the long range of LoRa, fewer number of access points or node can perform similar operations. In this paper, we study the performance and prospect of LoRa in indoor localization. We observed that LoRa is more stable than WiFi and BLE and is more resilient to environment change. We achieved mean error of 1.19m and 1.72m with unprocessed RSSI value in line of sight and non-line of sight respectively.
A projection approach to equality constrained iterative linear quadratic optimal control

This paper presents a state and state-input constrained variant of the discrete-time iterative Linear Quadratic Regulator (iLQR) algorithm, with linear time-complexity in the number of time steps. The approach is based on a projection of the control input onto the nullspace of the linearized constraints. We derive a fully constraint-compliant feedforward-feedback control update rule, for which we can solve efficiently with Riccati-style difference equations. We assume that the relative degree of all constraints in the discrete-time system model is equal to one, which often holds for robotics problems employing rigid-body dynamic models. Simulation examples, including a 6 DoF robotic arm, are given to validate and illustrate the performance of the method.
Electron-phonon interactions and related physical properties of metals from linear-response theory.

Spectral distribution functions of electron-phonon interaction ${\mathrm{\ensuremath{\alpha}}}^{2}$F(\ensuremath{\omega}) obtained by ab initio linear-response calculations are used to describe various superconducting and transport properties in a number of elemental metals such as Al, Cu, Mo, Nb, Pb, Pd, Ta, and V. Their lattice dynamics and self-consistently screened electron-phonon coupling are evaluated within local density functional theory and using a linear-muffin-tin-orbital basis set. We compare our theoretical ${\mathrm{\ensuremath{\alpha}}}^{2}$F(\ensuremath{\omega}) with those deduced from the tunneling measurements and find a close agreement between them. Temperature-dependent electrical and thermal resistivities as well as transport constants ${\ensuremath{\lambda}}_{\mathrm{tr}}$ also agree well with the experimental data. The values of ${\ensuremath{\lambda}}_{\mathrm{tr}}$ are close to the electron-phonon coupling parameter \ensuremath{\lambda}. For the latter a very good agreement with specific-heat measurements was found without any paramagnon contribution, except in Pd. We conclude that our method provides the description of electron-phonon interactions in tested materials with an accuracy of 10%. \textcopyright{} 1996 The American Physical Society.
Asymptotic Error-Correcting Performance of Joint Source-Channel Schemes based on Arithmetic Coding

In joint source-channel (JSC) schemes based on arithmetic coding (AC), additional redundancy may be introduced in order to reduce transmission errors. The purpose of this work is to provide analytical tools to predict and evaluate the effectiveness of that redundancy. Integer binary AC is modeled by a reduced-state automaton in order to obtain a bit-clock trellis of the AC. Considering AC as a trellis code, distance spectra are then derived. In particular, an algorithm to compute the free distance of an arithmetic code is proposed. The obtained code properties allow to compute upper bounds on both bit error and symbol error probabilities and thus provide an objective criterion to analyze the behavior of JSCAC schemes when used on noisy channels
Modifying Effects of the HFE Polymorphisms on the Association between Lead Burden and Cognitive Decline

Background As iron and lead promote oxidative damage, and hemochromatosis (HFE) gene polymorphisms increase body iron burden, HFE variant alleles may modify the lead burden and cognitive decline relationship. Objective Our goal was to assess the modifying effects of HFE variants on the lead burden and cognitive decline relation in older adults. Methods We measured tibia and patella lead using K-X-ray fluorescence (1991–1999) among participants of the Normative Aging Study, a longitudinal study of community-dwelling men from greater Boston. We assessed cognitive function with the Mini-Mental State Examination (MMSE) twice (1993–1998 and 1995–2000) and genotyped participants for HFE polymorphisms. We estimated the adjusted mean differences in lead-associated annual cognitive decline across HFE genotype groups (n = 358). Results Higher tibia lead was associated with steeper cognitive decline among participants with at least one HFE variant allele compared with men with only wild-type alleles (p interaction = 0.03), such that a 15 μg/g increase in tibia lead was associated with a 0.2 point annual decrement in MMSE score among HFE variant allele carriers. This difference in scores among men with at least one variant allele was comparable to the difference in baseline MMSE scores that we observed among men who were 4 years apart in age. Moreover, the deleterious association between tibia lead and cognitive decline appeared progressively worse in participants with increasingly more copies of HFE variant alleles (p-trend = 0.008). Results for patella lead were similar. Conclusion Our findings suggest that HFE polymorphisms greatly enhance susceptibility to lead-related cognitive impairment in a pattern consistent with allelelic dose.
On global stability of financial networks

The recent financial crisis have generated renewed interests in fragilities of global financial networks among economists and regulatory authorities. In particular, a potential vulnerability of the financial networks is the "financial contagion" process in which insolvencies of individual entities propagate through the "web of dependencies" to affect the entire system. In this paper, we formalize an extension of a financial network model originally proposed by Nier et al. for scenarios such as the OTC derivatives market, define a suitable global stability measure for this model, and perform a comprehensive empirical evaluation of this stability measure over more than 700,000 combinations of networks types and parameter combinations. Based on our evaluations, we discover many interesting implications of our evaluations of this stability measure, and derive topological properties and parameters combinations that may be used to flag the network as a possible fragile network. An interactive software FIN-STAB for computing the stability is available from the website this http URL
Surface Reconstruction from Unorganized Point Data with Quadrics

We present a reverse engineering method for constructing a surface approximation scheme whose input is a set of unorganized noisy points in space and whose output is a set of quadric patches. The local surface properties, necessary for the subsequent segmentation, are estimated directly from the data using a simple and efficient data structure—the neighborhood graph. Our segmentation scheme, based on principal curvatures, constructs initial point subsets, which may be enlarged or further subdivided based on associated approximation error estimates obtained through approximation of the initial segments by quadric surfaces. Our method is highly efficient and produces a high‐quality piecewise quadric surface approximation of engineering objects, which we demonstrate for several simple and complex example data sets.
Penerapan Social Network Analysis dalam Penentuan Centrality Studi Kasus Social Network Twitter

The twitter provides a kind of relation between users in specific form. When someone follow others, it doesn’t mean that she/he know well about them. We have defined a friend relationship between users in twitter as connection following and follower between two users. Based on this definition we develop a system to get friends and also friends of friends relation from a specific user. We use twitter API to get following and follower list and then construct a graph that represent a social network between those users. From this graph, we analyse the centrality using SNA (Social Network Analysis) method, i.e. closeness and betweeness. We propose to use these methods in order to find out who is the most influence user in the his/her social network to spread out the tweet or information. With this system, user can know about their social network based on their friend list on twitter. Kata Kunci : Social Network Analysis, Betweenness Centrality, Closeness Centrality
Digital analysis of choroidal neovascularisation in consecutive fluorescein angiograms for use in longitudinal clinical trials

Background/aims: To document the natural history and to assess the efficacy of interventional therapies in neovascular age related macular degeneration (AMD), an accurate and reproducible method is required for analysis of consecutive fluorescence angiograms. The development and evaluation of an image analysis software for this purpose is described here. It allows for the quantitative analysis of changes in CNV and/or leakage area over time. Methods: In digitised angiograms, a mouse driven arrow was used to delineate the CNV border. The ratio of the CNV area to the square of the distance between two vessels was automatically calculated by pixel count to compensate for variation in image sizes at different examination times. These results were directly transferred and stored in a database. To assess reproducibility, CNV areas in 20 patients with occult and 20 patients with classic CNV were determined independently by two readers. Results: There was only marginal variability between observers with this method: the mean deviation was 0.01 pixels for classic CNV (95% CI −0.17 to +0.15, SD 0.35) and 0.55 pixels for occult CNV (95% CI −1.06 to −0.04, SD 1.14). Conclusions: This practical PC based method allows for quantification of angiographic features such as CNV size in early frames and area of leakage in late frames. Limitations include non-readily defined borders in angiograms of poor image quality or indistinct borders of the hyperfluorescent areas of interest. The software is applicable to future clinical trials where the analysis of neovascular complex changes is required, for example, following therapeutic intervention.