Miracle-dz/UniFAR-FTUs huggingface dataset:
Introducing Gaussian covariance graph models in genome-wide prediction

Several statistical models used in genome-wide prediction assume independence of marker allele substitution effects, but it is known that these effects might be correlated. In statistics, graphical models have been identified as a useful tool for covariance estimation in high dimensional problems and it is an area that has recently experienced a great expansion. In Gaussian covariance graph models (GCovGM), the joint distribution of a set of random variables is assumed to be Gaussian and the pattern of zeros of the covariance matrix is encoded in terms of an undirected graph G. In this study, methods adapting the theory of GCovGM to genome-wide prediction were developed (Bayes GCov, Bayes GCov-KR and Bayes GCov-H). In simulated and real datasets, improvements in correlation between phenotypes and predicted breeding values and accuracies of predicted breeding values were found. Our models account for correlation of marker effects and permit to accommodate general structures as opposed to models proposed in previous studies which consider spatial correlation only. In addition, they allow incorporation of biological information in the prediction process through its use when constructing graph G, and their extension to the multiallelic loci case is straightforward.
Learning Translations from Comparable Corpora

This thesis examines the possibility of using comparable corporato augment statistical models of translation. Treating comparable corporaas marginal samples from an aligned bilingual joint distribution, the estimation of tr anslation models from a combination of bilingual parallel and comparable corporais seen as a variation of the labelled-unlabelled problem [Seeger, 2000b]. Results on synthetic data confirm that successful re-estima tion within the EM framework [Dempster et al., 1977] is highly-dependent on the bala nce between complete and incomplete data [Nigam, 2001]. Here we show that the util ity of re-estimation with additional incomplete data is highly-dependent on the accuracy of initial parameters estimated from the complete data alone. We propose a method for constraining the re-estimation proc edure in relation to the degree of comparabilitybetween marginal samples. This is seen to result in better conditional models when the assumption of comparabilit y is valid. Finally, we consider how more complex marginal models could be used to fu r her constrain the re-estimation of the conditional.
Effective switch memory management in OpenFlow networks

OpenFlow networks require installation of flow rules in a limited capacity switch memory (Ternary Content Addressable Memory or TCAMs, in particular) from a logically centralized controller. A controller can manage the switch memory in an OpenFlow network through events that are generated by the switch at discrete time intervals. Recent studies have shown that data centers can have up to 10,000 network flows per second per server rack today. Increasing the TCAM size to accommodate these large number of flow rules is not a viable solution since TCAM is costly and power hungry. Current OpenFlow controllers handle this issue by installing flow rules with a default idle timeout after which the switch automatically evicts the rule from its TCAM. This results in inefficient usage of switch memory for short lived flows when the timeout is too high and in increased controller workload for frequent flows when the timeout is too low. In this context, we present SmartTime - an OpenFlow controller system that combines an adaptive timeout heuristic to compute efficient idle timeouts with proactive eviction of flow rules, which results in effective utilization of TCAM space while ensuring that TCAM misses (or controller load) does not increase. To the best of our knowledge, SmartTime is the first real implementation of an intelligent flow management strategy in an OpenFlow controller that can be deployed in current OpenFlow networks. In our experiments using multiple real data center packet traces and cache sizes, SmartTime adaptive policy consistently outperformed the best performing static idle timeout policy or random eviction policy by up to 58% in terms of total cost.
Dynamics of Japanese Encephalitis Virus Transmission among Pigs in Northwest Bangladesh and the Potential Impact of Pig Vaccination

Background Japanese encephalitis (JE) virus infection can cause severe disease in humans, resulting in death or permanent neurologic deficits among survivors. Studies indicate that the incidence of JE is high in northwestern Bangladesh. Pigs are amplifying hosts for JE virus (JEV) and a potentially important source of virus in the environment. The objectives of this study were to describe the transmission dynamics of JEV among pigs in northwestern Bangladesh and estimate the potential impact of vaccination to reduce incidence among pigs. Methodology/Principal Findings We conducted a comprehensive census of pigs in three JE endemic districts and tested a sample of them for evidence of previous JEV infection. We built a compartmental model to describe JEV transmission dynamics in this region and to estimate the potential impact of pig vaccination. We identified 11,364 pigs in the study area. Previous JEV infection was identified in 30% of pigs with no spatial differences in the proportion of pigs that were seropositive across the study area. We estimated that JEV infects 20% of susceptible pigs each year and the basic reproductive number among pigs was 1.2. The model suggest that vaccinating 50% of pigs each year resulted in an estimated 82% reduction in annual incidence in pigs. Conclusions/Significance The widespread distribution of historic JEV infection in pigs suggests they may play an important role in virus transmission in this area. Future studies are required to understand the contribution of pig infections to JE risk in humans and the potential impact of pig vaccination on human disease.
Security Analysis of Mobile Two-Factor Authentication Schemes

Two-factor authentication (2FA) schemes aim at strengthening the security of login password-based authentication by deploying secondary authentication tokens. In this context, mobile 2FA schemes require no additional hardware (e.g., a smartcard) to store and handle the secondary authentication token, and hence are considered as a reasonable trade-off between security, usability and costs. They are widely used in online banking and increasingly deployed by Internet service providers. In this article, we investigate 2FA implementations of several well-known Internet service providers such as Google, Dropbox, Twitter and Facebook. We identify various weaknesses that allow an attacker to easily bypass 2FA, even when the secondary authentication token is not under attacker's control. We then go a step further and present a more general attack against mobile 2FA schemes. Our attack relies on a cross-platform infection that subverts control over both end points (PC and a mobile device) involved in the authentication protocol. We apply this attack in practice and successfully circumvent diverse schemes: SMS-based TAN solutions of four large banks, one instance of a visual TAN scheme, 2FA login verification systems of Google, Dropbox, Twitter and Facebook accounts, and the Google Authenticator app currently used by 32 third-party service providers. Finally, we cluster and analyze hundreds of real-world malicious Android apps that target mobile 2FA schemes and show that banking Trojans already deploy mobile counterparts that steal 2FA credentials like TANs.
A Cost/Benefit Approach to Performance Analysis

Most performance engineering approaches focus on understanding the use of runtime resources. However such approaches do not quantify the value being provided in return for the consumption of these resources. Without such a measure it is not possible to compare the efficiency of these components (that is whether the runtime cost is reasonable given the benefit being provided). We have created an empirical approach that measures the value being provided by a code path in terms of the visible data it generates for the rest of the application. Combining this with traditional performance cost data, creates an efficiency measure for every code path in the application. We have evaluated our approach using the DaCapo benchmark suite, demonstrating our analysis allows us to quantify the efficiency of the code in each benchmark and find real optimisation opportunities, providing improvements of up to 36% in our case studies.
Applicability of multiparty computation schemes for Wireless Sensor Networks

Wireless Sensor Networks pose special requirements to the deployed security algorithms, due to their unique properties: a single sensor node has great restrictions in terms of computing power, available memory and available energy. It is nevertheless desirable for the messages exchanged over the air interface to be secure against eavesdropping and forging. Since a single sensor node can be captured and removed very easily and almost undetectable, cryptographic schemes that do not rely on a single master secret present in every node, like those based on, for example, multiparty computations, seem to be a promising alternative in this setting. We are currently investigating the applicability of a modified implementation of the Gennaro-Rabin-Rabin multiparty multiplication protocol for sensor networks, with a special focus on the number of messages that have to be exchanged and the additional load put on every node by this protocol. This paper gives a short overview of our work and lists some preliminary results.
GENETIC AND PHENOTYPIC TRENDS IN MILK PRODUCTION TRAITS OF ANGLO NUBIAN GOATS FROM SELECTED FARMS IN THE PHILIPPINES

Using 570 lactation records from 172 Anglo Nubian goats produced from 21 sires and 161 dams and kidding from 2000 to 2016, heritability estimates based on dam-daughter regression were 0.52 ±0.22, 0.71 ±0.22, and 0.29 ±0.22 for total milk yield (TMY), daily milk yield (DMY), and number of lactations or parity (NLact), respectively. Heritability estimates for lactation length (LL), age at first kidding (AFK) and kidding interval (KI) were close to zero or had large standard errors. Repeatability estimates were 0.46 ±0.04 and 0.47 ±0.04 for TMY and DMY, respectively. Significant genetic correlations (P<0.01) were found between TMY and LL (r=0.72), TMY and DMY (r=0.95), TMY and NLact (r=0.97), and DMY and NLact (r=0.90). Significant phenotypic correlations (P<0.01) were found between TMY and LL (r=0.59), TMY and DMY (r=0.80), TMY and NLact (r=0.51), TMY and AFK (r=-0.36), DMY and NLact (r=0.61), DMY and AFK (r=-0.39), and NLact and AFK (r=-0.33). Comparison of genetic (doe’s estimated transmitting ability) and phenotypic trends from 1996 to 2012 showed environmental effects (doe’s year and month of birth and/or parity) comprising 52.56%, 75.83%, 13.77% and 52.13% of the average phenotypic values for TMY, LL, DMY and NLact, respectively.
How political are national identities? A comparison of the United States, the United Kingdom, and Germany in the 2010s

Research demonstrates the multi-dimensional nature of American identity arguing that the normative content of American identity relates to political ideologies in the United States, but the sense of belonging to the nation does not. This paper replicates that analysis and extends it to the German and British cases. Exploratory structural equation modeling attests to cross-cultural validity of measures of the sense of belonging and norms of uncritical loyalty and engagement for positive change. In the 2010s, we find partisanship and ideology in all three nations explains levels of belonging and the two content dimensions. Interestingly, those identifying with major parties of the left and right in all three countries have a higher sense of belonging and uncritical loyalty than their moderate counterparts. The relationship between partisanship, ideology, and national identity seems to wax and wane over time, presumably because elite political discourse linking party or ideology to identity varies from one political moment to the next.
Genetic Basis of Resistance to Cry1Ac and Cry2Aa in Heliothis virescens (Lepidoptera: Noctuidae)

Abstract The development of pest resistance to transgenic crop plants producing insecticidal toxins from Bacillus thuringiensis Berliner (Bt) poses a major threat to their sustainable use in agriculture. “Pyramiding” two toxins with different modes of actions in the same plant is now being used to delay the evolution of resistance in the insects, but this strategy could fail if a single gene in a pest confers resistance to both toxins. The CP73 strain of the cotton pest Heliothis virescens (F.) is resistant to both Cry1Ac and Cry2Aa toxins from Bt. We explored the genetic basis of resistance in this strain with a backcross, split-family design. The gene with the largest effect on Cry1Ac resistance in CP73 (BtR-5) maps to linkage group 10 of H. virescens and thus differs from the previously described linkage group 9 BtR-4 resistance found in the YHD2 strain, involving mutation of the gene encoding a 12-domain cadherin-like binding target of the Cry1A toxins. Neither BtR-4 nor BtR-5 seems to confer significant resistance to Cry2Aa. A majority of the linkage groups studied in one backcross family made a small positive contribution to resistance for both toxins. Thus, the Cry2Aa resistance in CP73 is not caused by either of the two major Cry1Ac resistance-conferring genes but instead probably has a quantitative genetic basis.
Verifying Constant-Time Implementations

The first two authors were funded by Project “TEC4Growth - Pervasive Intelligence, Enhancers and Proofs of Concept with Industrial Impact/NORTE-01-0145-FEDER-000020”, which is fi- nanced by the North Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, and through the European Regional Development Fund (ERDF). The third and fourth authors were supported by projects S2013/ICE2731 N-GREENS Software-CM and ONR Grants N000141210914 (AutoCrypt) and N000141512750 (SynCrypt). The fourth author was also supported by FP7 Marie Cure Actions-COFUND 291803 (Amarout II). We thank Peter Schwabe for providing us with a collection of negative examples. We thank Hovav Shacham, Craig Costello and Patrick Longa for helpful observations on our verification results. TEC4Growth - Pervasive Intelligence, Enhancers and Proofs of Concept with Industrial Impact/NORTE-01-0145-FEDER-000020
High-rate space-time block codes with fast maximum-likelihood decoding

Orthogonal space-time block codes (OSTBCs) represent an attractive choice of space-time coding scheme because of their simple maximum-likelihood (ML) decoding and full diversity property. However, the code orthogonality property limits their achievable transmission rate. In this paper, new high-rate block codes are proposed that are referred to as orthogonal structure based STBCs. To obtain these codes, the proposed design adds extra-symbols to the OSTBC matrix using different reasonable strategies. Because of the internal OSTBC structure of the proposed designs, the ML decoder can be implemented in a fast way. Simulations validate an improved performance-to-complexity tradeoff of the proposed codes as compared to several other popular choices of space-time codes.
Parallel Sparse Coding for Seafloor Image Analysis

Sparse coding has been a popular learning model in machine learning eld. However, due to the complexity of the learning model, the high computational cost has seriously hindered its application. Toward this purpose, this paper presents a parallel sparse coding method to improve the performance by exploiting the power of acceleration technologies such as Intel MIC and GPU. We use both parallel programming modes, i.e., the Native model and the Ooad model, to parallelize the sparse coding on MIC based computer cluster. Extensive experimental results on the AUV data of the southeast coast of Tasmania have shown that sparse coding can be accelerated signicantly on MIC and GPU. When using the same number of threads, the Native model and the Ooad model achieve very close performance for sparse coding. In addition, Native model demonstrates better performance scalability than the Ooad model. On the other side, parallel implementation on GPU shows the best performance.
Learning in Stochastic Games and Markov Decision Processes

In their standard formulations, stochastic games and Markov decision processes assume a rational opponent or a stationary environment. Online learning algorithms can adapt to arbitrary opponents and non-stationary environments, but do not incorporate the dynamic structure of stochastic games or Markov decision processes. We survey recent approaches that apply online learning to dynamic environments where the assumptions of rationality and stationarity are invalid. The emphasis is on the connections and differences between different approaches arising from different modeling assumptions and performance baselines.
How do API documentation and static typing affect API usability?

When developers use Application Programming Interfaces (APIs), they often rely on documentation to assist their tasks. In previous studies, we reported evidence indicating that static type systems acted as a form of implicit documentation, benefiting developer productivity. Such implicit documentation is easier to maintain, given it is enforced by the compiler, but previous experiments tested users without any explicit documentation. In this paper, we report on a controlled experiment and an exploratory study comparing the impact of using documentation and a static or dynamic type system on a development task. Results of our study both confirm previous findings and show that the benefits of static typing are strengthened with explicit documentation, but that this was not as strongly felt with dynamically typed languages.
Designing maps for the colour-vision impaired

To design maps that are readable by the colour-vision impaired but are also appealing to those with normal colour vision successfully, cartographers need to know how the colour-vision impaired person perceives colour and which colour combinations become confused. In this article, we concentrate on red-green colour confusion, which is by far the most common form of colour-impaired vision, and suggest how maps can be designed to consider this user group. We also introduce Color Oracle (see http://colororacle.cartography.ch), a free application that allows the designer to see colours on the monitor as people with colour-impaired vision see them. Figure 1 The visible spectrum as perceived by the normal viewer (top) and by those with red-green vision impairment
Process for preparing an adsorbent material in the absence of binder comprising a hydrothermal treatment step and process for extracting lithium from saline solutions using said material

The invention relates to a process for preparing a crystalline solid material of formula LiCl.2Al(OH)3.nH2O with n being between 0.01 and 10, said process comprising at least the following steps: a) a step of mixing, in an aqueous medium, at least one source of alumina and at least one source of lithium in order to obtain a suspension, b) a step of filtering the suspension obtained in step a) in order to obtain a paste, c) a step of drying the paste obtained at the end of step b), d) a step of shaping said dried paste, directly after the drying step c) in order to obtain a shaped solid material, said shaping step d) being carried out in the absence of binder, and e) the drying of the shaped solid material obtained, f) a step of hydrothermal treatment in order to obtain the shaped crystalline solid material of formula LiCl.2Al(OH)3.nH2O. The invention also relates to a solid material obtained according to this process and to a process for extracting lithium from saline solutions using the material thus prepared.
Efﬁcient, Context-Sensitive Dynamic Analysis via Calling Context Up trees

State-of-the-art dynamic bug detectors such as data race and memory leak detectors report program locations that are likely causes of bugs. However, static program location is not enough for developers to understand the behavior of increasingly complex and concurrent software. Dynamic calling context provides additional information, but it is expensive to record calling context frequently, e.g., at every read and write. Context-sensitive dynamic analyses can build and maintain a calling context tree to track calling context, but in order to reuse existing nodes, CCT-based approaches require an expensive lookup. This paper introduces the calling context uptree (CCU), a new data structure in which each node points “up” to its parent instead of “down” to its children. A CCU-based approach adds low time overhead because it can allocate new nodes quickly, but it adds high space overhead because it cannot reuse existing nodes. However, tracing-based garbage collection (GC) collects unused CCU nodes naturally and efficiently. To reduce space used by the remaining nodes, we present an efficient algorithm that piggybacks on GC to merge redundant nodes lazily. We implement our CCU-based approach in a high-performance Java virtual machine and integrate it with memory leak and data race detectors so they can report context-sensitive sites that cause bugs. We show that despite allocating instead of reusing nodes, our CCU-based approach adds low overhead to these clients and keeps space overhead low by relying on GC and performing lazy merging. The CCU can thus provide low-overhead context sensitivity to a variety of dynamic analyses that report bug causes.
GeoVIBE : A Visual Interface to Geographic Digital Library

This paper explores the possibilities of visualizing document similarities and differences in both spatial and topical domains. Building on previous studies of geographical information retrieval and textual information retrieval (IR) systems, we report on the development of an information browsing tool, GeoVIBE. The system consists of two types of browsing windows, GeoView and VibeView, that work in coordination for visual navigation in the document space. GeoView imposes a geographical order to the document space based on the idea of hypermaps where "icons" and "footprints" may be embedded in maps as the clickable hotspots linking to relevant documents. VibeView is a visual presentation of document similarity space defined by multiple reference points. By smooth integration of two browsing strategies, GeoVIBE enables users to search information using geographic clues as well as conceptual clues. Document relevance may be judged visually by inspecting spatial arrangement and relations of documents in a map view and the similarities among documents defined on a vector space model. Some future research are identified as critical to enable GeoVIBE as a powerful information searching environment.
Adaptive real-time video-tracking for arbitrary objects

In this paper, we present a visual object tracker for mobile systems that is able to specialize to individual objects during tracking. The core of our method is a novel observation model and the way it is automatically adapted to a changing object and background appearance over time. The model is integrated into the well known Condensation algorithm (SIR filter) for statistical inference, and it consists of a boosted ensemble of simple threshold classifiers built upon center-surround Haar-like features, which the filter continuously updates based on the images perceived. We present optimizations and reasonable approximations to limit the computational costs. Thus, the final algorithms are capable of processing video input at real-time. To experimentally investigate the gain of adapting the observation model we compare two different approaches with a non-adapting version of our observation model: maintaining a single observation model for all particles, and maintaining individual observation models for each particle. In addition, experiments were conducted to compare system performances between the proposed algorithms and two other state of the art Condensation based tracking approaches.