Miracle-dz/UniFAR-FTUs huggingface dataset:
Classification Via Recurrent Convolutional Neural Networks

The state-of-the-art methods used for sentiment classification are primarily based on statistical machine learning, and their performance strongly depends on the quality of the extracted features. The extracted features are often derived from the output of pre-existing natural language processing (NLP) systems, which leads to the propagation of errors in the existing tools and hinders the performance of these systems. In contrast to traditional methods, this paper introduces a recurrent convolutional neural network for text classification that works independently of and without human-designed features. The model applies a recurrent structure to capture as much contextual information as far as possible when learning word representations, which may introduce considerably less noise compared to traditional window-based neural networks. In addition, we also employ a max-pooling layer that automatically judges which words play key roles in sentiment classification to capture the key components in texts. We also conduct experiments on movie review datasets. These experimental results show that the proposed method outperforms current state-of-theart methods.
SOUTHWESTERN ATLANTIC OCEAN

The Río de la Plata estuary (RdlP) and adjacent continental shelf exhibit complex hydrological processes as a result of a highly variable fluvial discharge and associated terrigenous supply, which are primarily controlled by regional climatic forcing in interaction with the oceanographic system. Previous hydrological studies indicate that Little Ice Age and Medieval Climate Anomaly resulted in increased/decreased river runoff due to an enhanced/weakened precipitation regime. This study aims to analyze the cyclicity in the runoffrelated continental supply and the associated climatic oscillation behind it over the past 1,000 cal yr BP. To achieve this, we used a 10-m-long sediment core retrieved from the RdlP mud depocenter, which exhibits an extremely high and fairly constant linear sedimentation rate of 1.1 cm yr-1. We performed continuous 1-cm XRF element intensity scans and performed time series analysis on Fe/K, Ti/Al, Fe/Ca, Ti/Ca and Si/Al ratios, considered as regional proxies for inferring fluvial supply. The most significant cyclicities occur at 215, 192, 115, 100, 49, 47, 37, 35, and 2.5-8 yrs recurrence times. The long-term cyclicity is persistent throughout the whole record for all ratios, and it is probably related to solar forcing, i.e., the 200 yr Vries/Suess cycle, which determines the activity of the South American Monsoon System activity. The shorter climate-related cyclicities (˂100 yr) are probably related to the Atlantic Multidecadal Oscillation, the Pacific Decadal Oscillation and the El Niño Southern Oscillation climatic modes, and were registered only for Ti/Al, Fe/K and Si/Al ratios. We further identified an intensification of such shorter climate-related cyclicities over the past 500 yr BP. This study provides new evidence that both tropical Pacific and Atlantic SSTs and solar forcing are the main drivers of changes in rainfall over Southeastern South America on interannual to decadal, multidecadal and centennial scales, and thus modulates the RdlP river discharge.
Deposited in DRO : 04 January 2019 Version of attached

Citation for published item: Schorsch, Michael and Kramer, Manuela and Goss, Tatjana and Eisenhut, Marion and Robinson, Nigel and Osman, Deenah and Wilde, Annegret and Sadaf, Shamaila and Br uckler, Hendrik and Walder, Lorenz and Scheibe, Renate and Hase, Toshiharu and Hanke, Guy T. (2018) 'A unique ferredoxin acts as a player in the low-iron response of photosynthetic organisms. ', Proceedings of the National Academy of Sciences of the United States of America. , 115 (51). E12111-E12120.
DISSERTATION / DOCTORAL THESIS

Alternaria spp. are ubiquitous molds that are able to produce toxic secondary metabolites which may contaminate food globally. One of those is the mycotoxin altertoxin II (ATX-II), a genotoxic and mutagenic compound. In recent years, different flavonoids that can co-occur with mycotoxins in food were demonstrated to temper toxic effects of molds, mostly through their anti-oxidant properties. Thus, in this study, we assessed the influence of the berry anthocyanidin delphinidin on the toxicity of ATX-II in HT-29 colon carcinoma cells. We performed coupled SRB/WST-1 cytotoxicity assays which revealed only weak antagonistic interactions, and single-cell gel electrophoresis (“comet”) assays, where we observed a potent protective effect of delphinidin on the DNA-damaging properties of ATX-II. Furthermore, we investigated the mechanism for this interaction. In the DCF assay delphinidin was found to reduce intracellular oxidative stress levels, which might contribute partly to the latter protection. However, LC-MS experiments showed that a co-incubation of the mycotoxin with either delphinidin or its potential degradation product phloroglucinol aldehyde significantly decreased ATX-II concentrations in aqueous solutions, indicating that a direct chemical reaction of ATX-II with these components is likely responsible for the observed loss of toxicity. Our results provide evidence that delphinidin – and possibly other anthocyanins and polyphenols as well – might play a role in the protection of the gut from Alternariainduced genotoxicity.
Nationaal Lucht-en Ruimtevaartlaboratorium National Aerospace Laboratory NLR NLR-TP-2006-693 Bayesian tracking of two possible unresolved maneuvering targets

The paper studies the problem of maintaining tracks of two targets that may maneuver in and out formation flight, whereas the sensor and measurement extraction chain produces false and possibly unresolved or missing measurements. If the possibility of unresolved measurements is not modelled than it is quite likely that either the two tracks coalesce or that one of the two tracks diverges on false measurements. In literature a robust measurement resolution model has been incorporated within an IMM/MHT track maintenance setting. A straightforward incorporation of the same model within an IMM and PDAlike hypothesis merging approach suffers from track coalescence. In order to improve this situation, the paper develops a track-coalescence avoiding hypotheses merging version for the two target problem considered. Through Monte Carlo simulations, the novel filters are compared to applying hypotheses merging approaches that ignore the possibility of unresolved measurements or trackcoalescence.
On the complementarities of design and product innovation within firms

This paper aims at contributing to the literature on design innovation looking at the importance of potential complementarities between the design function and product innovation activities. We argue that design should not be seen simply as an input in the innovation production function of firms. Instead, we conceptualise design and product innovation as complementary processes whose interplay may lead to simultaneous increasing returns through synergistic linkages across different dimensions of knowledge creation. We test the presence of mutually reinforcing effects between design and product innovation applying conditional mixed-process (CMP) regression on a longitudinal dataset of over 3,000 manufacturing firms in Spain for the period 2007-2016. Our findings empirically confirm that design and product innovation are not independent processes, pointing to significant complementarities between their dynamics through synergistic linkages within firms’ innovation activities. Results are shown to be fully robust to GMM estimation.
Exaeskalarako sare-interkonexioen diseinurako helburu-aniztasuneko optimizazioa Designing an Exascale Interconnect using Multi-objective Optimization

Exascale performance will be delivered by systems composed of millions of interconnected computing cores. The way these computing elements are connected with each other (network topology) has a strong impact on many performance characteristics. In this work we propose a multi-objective optimizationbased framework to explore possible network topologies to be implemented in the EU-funded ExaNeSt project. The modular design of this system’s interconnect provides great flexibility to design topologies optimized for specific performance targets such as communications locality, fault tolerance or energy-consumption. The generation procedure of the topologies is formulated as a three-objective optimization problem (minimizing some topological characteristics) where solutions are searched using evolutionary techniques. The analysis of the results, carried out using simulation, shows that the topologies meet the required performance objectives. In addition, a comparison with a well-known topology reveals that the generated solutions can provide better topological characteristics and also higher throughput in almost all evaluated scenarios. KEYwORDS: Exascale performance, multi-objective optimization, evolutionary techniques, simulation.
3rd INTERNATIONAL CONFERENCE ON LIFELONG EDUCATION AND LEADERSHIP FOR ALL

This paper is part of a broader international research project, which includes eight case studies carried out in public schools in Portugal and in Chile. It is a comparative study, which aims to understand the way teachers describe formal and informal opportunities for collaboration in their schools and its effect in terms of practical knowledge; to identify the enablers and inhibitors that influence professional collaborative learning at school; to understand the role of teacher evaluation and student academic schools view their own professional development. In this case study, a public school, located in the north of Portugal, with sixty years of history, was selected. The participants in the study are teachers from different disciplinary areas and teaching departments. The school includes elementary and secondary school level, with regular and professional study programmes. Data collection is based on semi-structured interviews to the school director and to eight teachers, mainly coordinators of teaching departments. Results based on findings from teachers point out the importance of collaborative work, but they also recognize that schools need a reorgan opportunities are also seen as fundamental for professional development and to improve student outcomes. Conclusions and implications for teacher collaboration and professional development will be discussed in the paper.
Innovation and Performance of Companies with a Legacy of Risk Capital Funding A Swedish Perspective

The purpose of this paper is to investigate how R&D investments affect public companies that was backed by risk capital in their early stage. In our research, we investigate whether firms with prior risk capital involvement can better manage investments in R&D and if this effect is observable on a business performance level. The sample contains 280 companies that were listed on the Swedish stock exchange between year 2000-2015. Even though a lot of research has been devoted both to the area of firm innovativeness and to the area of risk capital investor’s performance, not much effort has been aimed in combining these two areas of interest. This study will therefore contribute to an additional perspective, combining the fields of innovation and finance. The indicators that was chosen in order to measure business performance are stock price and profitability which allows us to shape a broader view of the subject. The identified problem of this thesis was addressed using a quantitative method where general least squares was applied in order to estimate the effect. The findings indicate that innovation intensity have a positive impact on firm performance in terms of stock price for firms previously funded by risk capital. Nonetheless, this is not true regarding the impact on profitability, where the results instead point to a negative effect of R&D spending in previously risk capital backed firms. This result stress the importance of how business performance is measured, as the effect of R&D give different outcome of stock price compared to profitability.
2 nd Global Conference on Artificial Intelligence Invariant Projections in Games

Identification of implicit structures in dynamic systems is a fundamental problem in Artificial Intelligence. In this paper, we focus on General Game Playing where games are modeled as finite state machines. We define a new property of game states called invariant projections which strongly corresponds to humans’ intuition of game boards and may be applied in General Game Playing to support powerful heuristics, and to automate the design of game visualizations. We prove that the computation of invariant projections is Π2 -complete in the size of the game description. We also show that invariant projections form a lattice, and the lattice ordering may be used to reduce the time to compute invariant projections potentially by a factor that is exponential in the schema size of game states. To enable competitive general game players to efficiently identify boards, we propose a sound (but incomplete) heuristic for computing invariant projections and evaluate its performance.
Title YARS 2 : A Federated Repository for Querying GraphStructured Data from the Web

We present the architecture of an end-to-end semantic search engine that uses a graph data model to enable interactive query answering over structured and interlinked data collected from many disparate sources on the Web. In particular, we study distributed indexing methods for graph-structured data and parallel query evaluation methods on a cluster of computers. We evaluate the system on a dataset with 430 million statements collected from the Web, and provide scale-up experiments on 7 billion synthetically generated statements.
さRI “ K WORTH TAKINGざ-ENTREPRENEURIAL BEHAVIOR WHEN FACED WITH RISK AND UNCERTAINTY : A LAB EXPERIMENT

3rd year, Exp. final date January 2016, gz.ino@cbs.dk Are entrepreneurial-oriented individuals different from others in their propensities to take risk and uncertainty? Entrepreneurial-oriented individuals are defined as individuals that show entrepreneurial intentions ? the cognitive state that precedes the decision to form a new venture. Cognitive theory suggests differences in risk taking due to individual characteristics. However, entrepreneurship theory did not provide empirical support for such differences. Using data from a laboratory experiment with simple money games, we observe how individuals from two different groups (entrepreneurial-oriented, non-entrepreneurial-oriented) react to different degrees of risk and uncertainty when real monetary incentives are involved in each decision. The analysis reveals significant differences between entrepreneurial and non-entrepreneurial-oriented individuals in their decision making. In particular, entrepreneurial-oriented individuals appear to be more sensitive towards a ? house money effect? (increased risk seeking in the presence of a prior gain) and less sensitive towards a ? risk propensity effect? (reduced risk avoidance in the presence of increasing degrees of risk). These results have fundamental implications for the understanding of cognitive factors guiding entrepreneurial decision-making.
Source Participation Behavior-A Review and Introduction of a Participation Lifecycle Model

Open Source has proven its impact on business and puzzled researchers. However, little is known about participation behavior or limited to participants traits or participation rationales. We review existing research and propose a coherent participation lifecycle model. The framework illustrates the stages a volunteer progresses through from pre-contribution steps, for instance community selection, to initial participation, e.g. community joining, to sustained participation. The model guides researchers in an end-to-end participation lifecycle framework, highlights certain influences and socialization impact, and creates consensus in research. We also draw the attention to further research areas and propose a research agenda in regards to open source participation behavior.
Made TOROKOFF Between the Learning and the Non-learning Organisation : Some Evidence from the Estonian Public and Private Sectors 1

nagement consultant in own company ALO OÜ. Centre for Entrepreneurship, Faculty of Economics and Business Administration, University of Tartu, Estonia. Address: Narva Rd. 4-B104, EE51009 Tartu, Estonia. Tel. : +372~737 6362. Fax: +372~737 6363. E-mail: Tonis.Mets@mtk.ut.ee. Made TOROKOFF – PhD student, research fellow, Centre for Entrepreneurship at University of Tartu, a trainer and consultant at Development Company Invicta. Centre for Entrepreneurship, Faculty of Economics and Business Administration, University of Tartu, Estonia. Address: Narva Rd. 4-B104, EE51009 Tartu, Estonia. Tel. : +372~737 6362. Fax: +372~737 6363. E-mail: made.torokoff@ut.ee. ISSN 1392-1142 ORGANIZACIJŲ VADYBA: SISTEMINIAI TYRIMAI: 2007.43
SPECPATCH: Human-In-The-Loop Adversarial Audio Spectrogram Patch Attack on Speech Recognition

In this paper, we propose SpecPatch, a human-in-the loop adversarial audio attack on automated speech recognition (ASR) systems. Existing audio adversarial attacker assumes that the users cannot notice the adversarial audios, and hence allows the successful delivery of the crafted adversarial examples or perturbations. However, in a practical attack scenario, the users of intelligent voice-controlled systems (e.g., smartwatches, smart speakers, smartphones) have constant vigilance for suspicious voice, especially when they are delivering their voice commands. Once the user is alerted by a suspicious audio, they intend to correct the falsely-recognized commands by interrupting the adversarial audios and giving more powerful voice commands to overshadow the malicious voice. This makes the existing attacks ineffective in the typical scenario when the user's interaction and the delivery of adversarial audio coincide. To truly enable the imperceptible and robust adversarial attack and handle the possible arrival of user interruption, we design SpecPatch, a practical voice attack that uses a sub-second audio patch signal to deliver an attack command and utilize periodical noises to break down the communication between the user and ASR systems. We analyze the CTC (Connectionist Temporal Classification) loss forwarding and backwarding process and exploit the weakness of CTC to achieve our attack goal. Compared with the existing attacks, we extend the attack impact length (i.e., the length of attack target command) by 287%. Furthermore, we show that our attack achieves 100% success rate in both over-the-line and over-the-air scenarios amid user intervention.
Sigstore: Software Signing for Everybody

Software supply chain compromises are on the rise. From the effects of XCodeGhost to SolarWinds, hackers have identified that targeting weak points in the supply chain allows them to compromise high-value targets such as U.S. government agencies and corporate targets such as Google and Microsoft. Software signing, a promising mitigation for many of these attacks, has seen limited adoption in open-source and enterprise ecosystems. In this paper, we propose Sigstore, a system to provide widespread software signing capabilities. To do so, we designed the system to provide baseline artifact signing capabilities that minimize the adoption barrier for developers. To this end, Sigstore leverages three distinct mechanisms: First, it uses a protocol similar to ACME to authenticate developers through OIDC, tying signatures to existing and widely-used identities. Second, it enables developers to use ephemeral keys to sign their artifacts, reducing the inconvenience and risk of key management. Finally, Sigstore enables user authentication by means of artifact and identity logs, bringing transparency to software signatures. Sigstore is quickly becoming a critical piece of Internet infrastructure with more than 2.2M signatures over critical software such as Kubernetes and Distroless.
Poster: MUSTARD - Adaptive Behavioral Analysis for Ransomware Detection

Behavioural analysis based on filesystem operations is one of the most promising approaches for the detection of ransomware. Nonetheless, tracking all the operations on all the files for all the processes can introduce a significant overhead on the monitored system. We present MUSTARD, a solution to dynamically adapt the degree of monitoring for each process based on their behaviour to achieve a reduction of monitoring resources for the benign processes.
Secure in-packet Bloom Filter forwarding on the NetFPGA

In-packet Bloom filters allow one to forward source-routed packets with minimal forwarding tables, the Bloom filter encoding the identities of the links the packet needs to be forwarded over. If the link identities are made content dependent, e.g. by computing the next-hop candidate link identifiers by applying a cryptographic function over some information carried in the packet header, the Bloom filters differ pseudo-randomly from packet-to-packet, making the forwarding fabric resistant towards unauthorised traffic. In this paper, we describe our early implementation and testing of an in-packet Bloom filters forwarding node that implements cryptographically computed link identifiers. We have tested two different cryptographic techniques for the link-identity computation and thereby for making the forwarding decision. The algorithms have been implemented and tested on the Stanford NetFPGA. The performance and eifficiency of the algorithms is also briefly discussed.
Portable Driver Monitoring System using Matlab

:Various investigations show that driver’s drowsiness is one of the main causes of road accidents. The development of technologies for preventing drowsiness at the time is a major challenge in the field of accident avoidance. The advance in computing technology has provided the means for building intelligent vehicle systems. The purpose of this study is to detect the drowsiness in driver’s to prevent the accidents and to improve the safety on the highways. A system aiming at detecting driver drowsiness or fatigue on the basis of video analysis is presenting. A real time face detection is implemented to locate driver’s face region. A method of detecting drowsiness in drivers is developed by using a camera that points directly towards the face and capture for the video. As a detection method the system uses image processing technology to analyze the images of the driver’s face taken with a video camera. The captured video is done; it is converted into number of frames of images and monitoring of the face region and eyes in order to detect drowsiness. The system is able monitoring eyes and determines whether the eyes are in an open or shows signs of drowsiness. This detection system avoids a noncontact technique for judging various levels of alertness and facilities early detection of a decline in alertness during driving.
Shape Optimization of MicroChannel Heat Sink for MicroElectronic Cooling

A numerical investigation of 3-D fluid flow and heat transfer in a rectangular micro-channel has been carried out using water as a cooling fluid in a silicon substrate. Navier–Stokes and energy equations for laminar flow and conjugate heat transfer are solved using a finite volume solver. Solutions are first carefully validated with available analytical and experimental results; the shape of the micro-channel is then optimized using surrogate methods. Ratios of the width of the micro-channel to the depth and the width of the fin to the depth are selected as design variables. Design points are selected through a four-level full factorial design. A single objective function thermal resistance, formulated using pumping power as a constraint, is optimized. Mass flow rate is adjusted by the constant pumping power constraint. Response surface approximation, Kriging, and radial basis neural network methods are applied to construct surrogates and the optimum point is searched by sequential quadratic programming.