Miracle-dz/UniFAR-FTUs huggingface dataset:
Anaphoric Connectives and Long-Distance Discourse Relations in Czech

This paper is a linguistic as well as technical survey for the development of a shallow discourse parser for Czech. It focuses on long-distance discourse relations signalled by (mostly) anaphoric discourse connectives. Proceeding from the division of connectives on “structural” and “anaphoric” according to their (in)ability to accept distant (non-adjacent) text segments as their left-sided arguments, and taking into account results of related analyses on English data in the framework of the Penn Discourse Treebank, we analyze a large amount of language data in Czech. We benefit from the multilayer manual annotation of various language aspects from morphology to discourse, coreference and bridging relations in the Prague Dependency Treebank 3.0. We describe the linguistic parameters of long-distance discourse relations in Czechin connection with their anchoring connective, and suggest possible ways of their detection. Our empirical research also outlines some theoretical consequences for the underlying assumptions in discourse analysis and parsing, e.g. the risk of relying too much on different (language-specific? ) part-of-speech categorizations of connectives or the different perspectives in shallow and global discourse analyses (the minimality principle vs. higher text structure).
A Note on Agenda Restrictions in Multi-issue Bargaining by

We study the effects of a between-cake discount factor in the agenda selection problem faced by a multi-issue committee. The presence of an interval of time between bargaining stages is a reasonable and realistic assumption. We show that this assumption simplifies the agenda selection problem strongly. In particular, the equilibrium multiplicity obtained in In and Serrano (2002) does not hold: a unique SPE can be established among the sequential bargaining procedures. JEL Classification: C72, C73, C78
Making Dressing Easier: Smart Clothes to Help With Putting Clothes on Correctly

Dressing is an Activity of Daily Living (ADL) that can be difficult to do for individuals living with cognitive disorders and can, therefore, negatively impact their quality of life. Our research focuses on the development of an assistive robot and smart clothing system to aid a user with this ADL. In this paper, we present our autonomous Clothing Perception System that uniquely incorporates smart sensors into clothing in order to perceive if a person has worn the clothes correctly. Four different dressing states can be identified: correctly worn; partially worn; backwards; or inverted (inside out). Our novel system uses a combination of capacitive sensors, contact switches, an infrared LED and an RGB-D sensor to determine the dressing state. The multi-modal sensing system was integrated into a collared shirt and tested to verify its performance.Results with different individuals putting on the shirt showed that the system was able to perceive the four distinct dressing states for all of them.
Classification of fine particles from construction and demolition waste through image analysis

Construction and demolition waste (CDW) has become one of the most important environmental problems in large and medium-sized cities around the world. The classification and segregation of CDW particles constitute the main difficulties for their recycling. The present paper proposes a methodology for classification of fine particles from CDW. It uses size, shape and texture parameters to discriminate between CDW particles from mortar, ceramic and concrete in a typical supervised classification procedure. The total success rate reached was 73.96% and the success rates for mortar and ceramic were greater than 80%. The main limitation was the recognition of the concrete particles; the best result obtained for its success rate was 56.30%. Keywords—construction and demolition waste, shape, texture, supervised classification, scanning electron microscopy
! Degree Project Level : Bachelor ’ s A Content Analysis of the Features of Online Discourse on Japanese Twitter

This research was conducted in order to study and analyze the online discourse in Japanese. It is a Twitter-specific study on the Japanese linguistic features of computer-mediated communication. A total of 887 tweets from 30 Japanese celebrities between ages 19-31 were divided by age, gender, degree of formality and genre, and a content analysis was conducted on them to compare the use of orthographic and lexical features by using previous studies by Nishimura (2003) and Miyake (2007) as a framework. The results show that Twitter was most commonly used for replies to other Twitter users, to maintain social media presence and for self-promotion. Tweets were most commonly sent via iPhone, written in informal style. The findings also offer further proof on how strongly the graphic signs are part of online communication, and confirm that many technology-inspired slang words and abbreviations are created for different media platforms.
A New PID Controller Design with Constraints on Relative Delay Margin for First-Order Plus Dead-Time Systems

The maximum sensitivity function as the conventional robustness index is often used to test the robustness and cannot be used to tune the controller parameters directly. To reduce analytical difficulties in dealing with the maximum sensitivity function and improve the control performance of the proportional-integral-derivative controller, the relative delay margin as a good alternative is proposed to offer a simple robust analysis for the proportional-integral-derivative controller and the first-order plus dead-time systems. The relationship between the parameters of the proportional-integral-derivative controller and the new pair, e.g., the phase margin and the corresponding gain crossover frequency, is derived. Based on this work, the stability regions of the proportional-integral-derivative controller parameters, the proportional gain and the integral gain with a given derivative gain, are obtained in a simple way. The tuning of the proportional-integral-derivative controller with constraints on the relative delay margin is simplified into an optimal disturbance rejection problem and the tuning procedure is summarized. For convenience, the recommended parameters are also offered. Simulation results demonstrate that the proposed methodology has better tracking and disturbance rejection performance than other comparative design methodologies of the proportional-integral/proportional-integral-derivative controller. For example, the integrated absolute errors of the proposed proportional-integral-derivative controller for the tracking performance and disturbance rejection performance are less than 91.3% and 91.7% of the integrated absolute errors of other comparative controllers in Example 3, respectively. The proposed methodology shows great potential in industrial applications. Besides, the proposed method can be applied to the design of the proportional-integral-derivative controller with filtered derivative which is recommended for practical applications to weaken the adverse influence of the high-frequency measurement noise.
Feature Selection for CBR in Imitation of RoboCup Agents : A Comparative Study

We present a comparison of two methods for selecting the features employed in the representation of cases for a case-based reasoning approach to imitation of agents in the RoboCup simulation platform. Feature Selection methods are compared empirically in terms of the imitation performance, the size of the resulting feature set, and execution time. Differences and their implications are discussed.
Sexual and reproductive health and rights : reflections on the Millennium Development Goals

Considerable progress has been made in expanding access to health services through strong political leadership and development of policies, guidelines and legislation. However, South Africans still face challenges and obstacles in accessing comprehensive treatment, prevention and care for sexually transmitted infections (STIs) including HIV, sexual and reproductive health (SRH), family planning and contraception, pregnancy, delivery, psychosocial support and counselling. Major challenges lie in ensuring that guidelines are implemented, that standard protocols are followed and that health-care worker performance is improved and monitored. In order to fulfil the rights of all South Africans to equal access to health care and life-saving prevention and treatment programmes, evidence-based interventions, the provision of comprehensive and holistic care, optimal therapeutic care and SRH services need to be strengthened. The strengthening of SRH services also entails integrating reproductive health with other services and providing guidelines for implementation.
A Depression-Based Index to Represent Topographic Control in Urban Pluvial Flooding

Extensive studies have highlighted the roles of rainfall, impervious surfaces, and drainage systems in urban pluvial flooding, whereas topographic control has received limited attention. This study proposes a depression-based index, the Topographic Control Index (TCI), to quantify the function of topography in urban pluvial flooding. The TCI of a depression is derived within its catchment, multiplying the catchment area with the slope, then dividing by the ponding volume of the depression. A case study is demonstrated in Guangzhou, China, using a 0.5 m-resolution Digital Elevation Model (DEM) acquired using Light Detection and Ranging (LiDAR) technology. The results show that the TCI map matches well with flooding records, while the Topographic Wetness Index (TWI) cannot map the frequently flooded areas. The impact of DEM resolution on topographic representation and the stability of TCI values are further investigated. The original 0.5 m-resolution DEM is set as a baseline, and is resampled at resolutions 1, 2, 5, and 10 m. A 1 m resolution has the smallest TCI deviation from those of 0.5 m resolution, and gives the optimal results in terms of striking a balance between computational efficiency and precision of representation. Moreover, the uncertainty in TCI values is likely to increase for small depressions.
An Analysis of Trust in Smart Home Devices

In recent times, smart home devices like Amazon Echo and Google Home have reached mainstream popularity. These devices are intrinsically intrusive, being able to access user’s personal information. There are growing concerns about indiscriminate data collection and invasion of user privacy in smart home devices. Improper trust assumptions and security controls can lead to unauthorized access of the devices, which can have severe consequences (i.e. safety risks). In this paper, we analysed the behaviour of smart home devices with respect to trust relationships. We set up a smart home environment to evaluate how trust is built and managed. Then, we performed a number of interaction tests with diﬀerent types of users (i.e. owner, guests). As a result, we were able to assess the eﬀectiveness of the provided security controls and identify some relevant security issues. To address them, we deﬁned a trust model and proposed a solution based on it for securing smart home devices.
Document Clustering using various External Knowledge sources

The problem of document clustering is to arrange a set of documents into groups such that documents within a group are related to each other. Document clustering has been studied extensively because of the huge increase in the amount of digital text content online and also due to its wide applicability in areas such as web mining, information retrieval, etc. Typical document clustering algorithms have issues like handling high dimensionality, scalability, building an efficient hierarchy, good clustering accuracy, etc. In this thesis, we present a framework for document clustering that addresses all the above issues. The framework is a fusion of two broach approaches. The first approach consists of a topic-based document clustering algorithm, and in the second approach we provide methods to enhance the clustering produced using various external knowledge sources like Wikipedia and Social Content. Next, we provide a specific implementation of the first approach of our framework using the concept of frequent itemsets. We define a frequent itemset based hierarchical document clustering algorithm that handles the high dimensionality of the documents by considering only important words which represent topics. A frequent itemset is a set of words that occurs frequently together in a set of documents. Using frequent itemsets also takes care of the scalability of the algorithm as we consider only the important (topic-indicating) words. We explain the drawbacks of the previous approaches and propose improvements to them in our approach to obtain a clustering. Next, we provide methods to process these clusters in order to construct a compact hierarchy of clusters. We also give meaningful labels to the clusters using Wikipedia to allow a user to easily browse through the clusters.
ntitumor activity and toxicity of volatile oil from the leaves of nnona leptopetala onalisa

Annona leptopetala (R.E.Fr.) H. Rainer, Annonaceae, is used in folk medicine like antitumor and antiinflammatory. The aim of this study was to determine chemical composition, toxicity and antitumor activity of A. leptopetala leaves volatile oil. Fresh leaves were hydrodistilled and then the volatile oil chemical composition was assessed by gas chromatography and mass spectrometry. Toxicity was assessed using haemolysis, micronucleus and acute toxicity protocols. Antitumor effects were determined in vitro and in vivo, using sulforhodamine B assay and sarcoma 180 murine tumor model, respectively. Spathulenol was the major component identified (12.56%). The volatile oil showed in vitro antitumor activity mainly in leukemia cell line (K-562), with Total growth inhibit (TGI) (concentration producing TGI) of 0.64 g/ml. In other hand, the volatile oil <250 g/ml did not inhibit HaCat non-tumor cell line growth. The concentration that produced 50% haemolysis was 372.8 g/ml. The 50% lethal dose in mice was approximately phatulenol 447.2 mg/kg intraperitoneally. Sarcoma 180 tumor growth inhibition rates were 59.29% and 58.77% at 100 and 150 mg/kg intraperitoneally, respectively. The volatile oil presented moderate gastrointestinal toxicity and no genotoxicity was observed at 350 mg/kg. Thus, the volatile oil shows antitumor activity with moderate toxicity. © 2018 Sociedade Brasileira de Farmacognosia. Published by Elsevier Editora Ltda. This is an open he CC access article under t
Are There Productivity Spillovers from Southern MNCs in the Swiss Service / Construction Industry ?

Although developing and emerging market firms (southern MNCs) are increasingly engaged in outward FDI in European advanced economies, we have an incomplete and inconsistent understanding of whether, and under what conditions, this investment may benefit the local economy. Our paper addresses this issue by examining whether local firms may benefit from the entry and the presence of southern MNCs in services/construction industry. We argue that analyzing spillovers from southern MNCs needs to distinguish these effects according to how they take place as well as the technological characteristics of local knowledge receivers. Using firms-level data from Switzerland, we found that local firms need to upgrade their human capital to take benefit from the entry and presence of southern MNCs in their industry; otherwise the presence of southern MNCs reduces the productivity of local services/construction firms in Switzerland. No benefit is found from competition effects. Moreover, interactions between different technological capacities of local firms and the ways they benefit from spillovers from southern MNCs provide differences in spillover results.
Towers of Saliency: A Reinforcement Learning Visualization Using Immersive Environments

Deep reinforcement learning (DRL) has had many successes on complex tasks, but is typically considered a black box. Opening this black box would enable better understanding and trust of the model which can be helpful for researchers and end users to better interact with the learner. In this paper, we propose a new visualization to better analyze DRL agents and present a case study using the Pommerman benchmark domain. This visualization combines two previously proven methods for improving human understanding of systems: saliency mapping and immersive visualization.
Double-Hard Debias: Tailoring Word Embeddings for Gender Bias Mitigation

Word embeddings derived from human-generated corpora inherit strong gender bias which can be further amplified by downstream models. Some commonly adopted debiasing approaches, including the seminal Hard Debias algorithm, apply post-processing procedures that project pre-trained word embeddings into a subspace orthogonal to an inferred gender subspace. We discover that semantic-agnostic corpus regularities such as word frequency captured by the word embeddings negatively impact the performance of these algorithms. We propose a simple but effective technique, Double Hard Debias, which purifies the word embeddings against such corpus regularities prior to inferring and removing the gender subspace. Experiments on three bias mitigation benchmarks show that our approach preserves the distributional semantics of the pre-trained word embeddings while reducing gender bias to a significantly larger degree than prior approaches.
Unification and Matching in Separable Theories ⋆

We study unification and matching in equational theories based on semirings, which include Kleene algebra and extensions with different forms of concurrency, constraint semirings, and synchronous actions algebra. Generally the unification problems are undecidable in this setting, but different undecidability proofs are required. On the other hand, the matching problems are decidable and a general pattern can be drawn. This pattern is developed into a matching algorithm, relying on a new way of combining non-disjoint theories, which we call stratification, and on a relaxation of the finite variant property, which we call separability. Consequently, we believe that our algorithm and the notions that we introduce have an importance i) beyond theories based on semirings; ii) for other problems related to unification and matching.
30TH INTERNATIONAL COSMIC RAY CONFERENCE Draco Observation with the MAGIC Telescope

The nearby dwarf spheroidal galaxy Draco with its high mass t o light ratio is a promising target for indirect dark matter (DM) searches. It is located at a distance of about 82 kpc, at the edge of the Milky Way. The dwarf galaxy is enclosed by a DM halo where t h DM particle may annihilate and produce an observable gamma-ray flux. Among the different DM particle candidates is the neutralin o, the lightest supersymmetric (SUSY) particle, very favored. Looking at the high energetic photon chan nel, neutralino annihilation produces mainly a continuous spectrum with a characteristic cut-off at the n eutralino mass. Accelerator experiments provide a lower mass limit of 45 GeV, thus the cut-off is expected to be between 45 GeV and several TeV. The MAGIC telescope at the Canary Islands has the lowest ener gy th eshold of all ground based very high energy gamma-ray observatories and is therefore best s uited to search for these signals.
Microtiming in the rhythmic structure of Candombe drumming patterns ∗

The analysis of micro–rhythmic aspects of music has experienced an important development in recent years. Microtiming involves small–scale temporal deviations of events in the musical surface with respect to an underlying isochronous metrical grid. These deviations can take the form of tempo variations like rubato; in other cases they rather consist of the time–shifting of events with respect to the steady beats of a constant tempo (e.g. notes inégales in Baroque or “swing” eighth–notes in Jazz). It has been recently argued that in some cases microtiming could be better understood by considering non–isochronous beat subdivisions. This paper presents the results of measuring and analysing the micro–rhythmical properties of the drumming patterns in Uruguayan Candombe. Candombe rhythm results from the interaction of the patterns of three drums of different size and pitch, and its metric structure—a cycle of four beats and sixteen pulses—shares many traits with other musics of the Afro–Atlantic world. The analysis of several recordings by renowned players reveals the systematic and consistent use of micro–temporal deviations in the patterns of Candombe, demonstrating that microtiming is a structural component of its rhythm.
Translational Profiling of Platinum-Based Chemotherapeutics

The platinum family of chemotherapeutics (including cisplatin, carboplatin, and oxaliplatin) are among the most widely prescribed drugs in modern oncology. They are especially common in the treatment of prostate cancer, which is currently the most diagnosed cancer among American males. Despite the ubiquity and extensive study into their chemistry and biology, the exact mechanism by which these drugs are cytotoxic to cancerous cells remains largely unknown. While much is known about their apoptotic effects on healthy cells, this is insufficient to explain their broadly effective anti-tumor activity, given the high frequency of apoptosis-deficient mutants found in most cancers. What studies have been conducted regarding the mechanisms of toxicity in cancerous cells have primarily relied on transcriptional profiling (microarray) technology, which is poorly suited to toxicity studies because of the wide array of posttranscriptional regulation that genes and proteins are known to be subject to. In order to guide rational design of new chemotherapeutics that augment both the positive anti-tumor and the negative side effects of existing platinum drugs, large volumes of translationally-based proteomic data are necessary. In this proposal, we utilize a novel procedure that is capable of selectively labelling and isolating newly synthesized proteins after a given time. Such temporal control allows for untargeted identification of only those proteins whose synthesis is augmented in response to platinum-family drugs, and the ease of the technique allows for its simultaneous application to a variety of treatment groups. By coupling this isolation technique with high precision mass spectrometry, we will generate a unique translational heat map showing the relative changes in protein levels in both healthy and cancerous cells exposed to cisplatin, carboplatin, and oxaliplatin. Subsequent analysis of the Worldwide Protein Data Bank will identify genes associated with these proteins, and will allow for the application of high quality sorting and enrichment algorithms such as Gene Ontology and Gene Set Enrichment. These methods will allow us to construct interactome maps that show the relation of the identified genes to known cellular processes. By dividing these maps into subnetworks using the Ingenuity software and assigning each subnetwork a score corresponding to the extent to which it was perturbed each drug, we will elucidate the molecular mechanism of cytotoxicity for each drug in both healthy and cancerous cells. This work will improve human health by providing novel strategies for increasing the efficiency and decreasing the side effects of both existing and subsequently developed chemotherapeutics. Tiffany Chen & Brandon Russell Page 1 of 10
THE GENERATION OF SIRNAAMIRNA EXPRESSIONVECTORS

(51) Int. Cl. CI2P 19/34 (2006.01) C12N 15/10 (2006.01) CI2N IS/II (2006.01) CI2N 5/66 (2006.01) CI2N 5/64 (2006.01) (52) U.S. Cl. CPC . C12N 15/111 (2013.01); C12N2310/111 (2013.01); C12N 2330/30 (2013.01): CI2N 15/10 (2013.01); C12N 23 10/53 (2013.01); CI2N 15/66 (2013.01); C12N 15/64 (2013.01); CI2N 2310/14 (2013.01) USPC . 435/91.1