Miracle-dz/UniFAR-FTUs huggingface dataset:
Only falls and horses: accidents and injuries in racehorse training.

BACKGROUND The horseracing training industry has largely been ignored in terms of active occupational health research. AIMS To provide baseline statistics on the specific nature and type of accidents that occurred in English horseracing stables during 2008. METHODS All 716 training yards/stables registered with the British Horseracing Authority were contacted in April/May 2009 to complete the Racing Injury Accident Statistical Survey. The survey asked respondents to detail all recorded accidents and injuries during 2008. RESULTS Two hundred and fifty-six yards (36%) provided usable responses. The proportion of different-sized yards was highly comparable with the sizes of yards in the national population. Employees per yard ranged from 1 to 121 (mean = 9 ± 14), with a total of 2293 employees (30% of the total 7558 UK yard staff). At the point of survey, participating yards housed between 0 and 243 horses (mean = 6 ± 32), with 6420 horses covered in this survey. One hundred and thirty yards (51%) reported no accidents. Of the remaining 126 yards, 665 accidents were reported, ranging from 1 to 58 accidents per establishment, equalling 5 accidents per yard (± 7) or 3 accidents per yard for the entire sample. There was a mean of 53 horse-related accidents per month, and 96% were horse-related. Medical treatment was required for 50% of accidents. CONCLUSIONS This representative sample covers the broad range of hazards, accidents and injuries in this difficult-to-access but unique industry. Recommendations for the management of accidents are made.
Nios II Processor-Based Self-Adaptive QRS Detection System

For our project, we designed and implemented a cardiac arrhythmia electrocardiogram (ECG) monitoring system that can adaptively modify and change the components of its processing chain to carry out the best treatment on electrocardiogram signals. We investigated and provided a solution to a fundamental problem in the area of biomedical signal processing: accurate QRS complex detection for varying environmental and patient conditions. We implemented the ECG monitoring system in an Altera® Cyclone® II FPGA.
A SPICE model of flexible transition metal dichalcogenide field-effect transistors

This paper presents the first SPICE model of the transition metal dichalcogenide (TMD) field-effect transistor (FET), which is a promising candidate for flexible electronics. The model supports different transistor design parameters such as width, length, oxide thickness, and various channel materials (MoS2, WSe2, etc.), as well as the applied strain, which enables the evaluation of transistor- and circuit-level behavior under process variation and different levels of bending. We performed SPICE simulations on digital logic gates to explore the design space of both MoS2- and WSe2-based transistors, and to evaluate the projected performance of these circuits under applied strain. Our simulations show that WSe2 circuits outperform MoS2 and Si-based CMOS in terms of energy-delay product (EDP) by up to 1 order of magnitude, depending on applications. Finally, we investigate TMDFET's behavior under process variation.
CLUSTERING IN AIRBORNE LASER SCANNING RAW DATA FOR SEGMENTATION OF SINGLE TREES

In recent years airborne laser scanning has been proven to be a helpful tool for remote sensing forestry applications. As laser scanning systems now provide very high point density (> 10 points/m2), we pursue the approach of deriving geometric parameters on a single-tree basis. We explore the potential of delineating single trees from laser scanner raw data (x,y,ztriples) through cluster analysis and validate this approach with a dataset of about 2000 georeferenced trees. The dataset includes tree height and crown diameter and was gathered on a long term forest monitoring site by the Swiss Federal Institute for Forest, Snow and Landscape Research (WSL). A robust linear regression of field data tree heights with LIDAR derived tree heights leads to a slope of 0.91 and an offset of 0.71 m, with a RMS of 0.6 m. The accuracy of the laser scanner is evaluated through 6 reference targets, being 3x3 m2 in size and horizontally plain. Internal offsets were found to be less than 0.25 m, the standard deviation of the points on the targets was about 0.06 m.
Scalable top-k spatial keyword search

In this big data era, huge amounts of spatial documents have been generated everyday through various location based services. Top-k spatial keyword search is an important approach to exploring useful information from a spatial database. It retrieves k documents based on a ranking function that takes into account both textual relevance (similarity between the query and document keywords) and spatial relevance (distance between the query and document locations). Various hybrid indexes have been proposed in recent years which mainly combine the R-tree and the inverted index so that spatial pruning and textual pruning can be executed simultaneously. However, the rapid growth in data volume poses significant challenges to existing methods in terms of the index maintenance cost and query processing time. In this paper, we propose a scalable integrated inverted index, named I3, which adopts the Quadtree structure to hierarchically partition the data space into cells. The basic unit of I3 is the keyword cell, which captures the spatial locality of a keyword. Moreover, we design a new storage mechanism for efficient retrieval of keyword cell and preserve additional summary information to facilitate pruning. Experiments conducted on real spatial datasets (Twitter and Wikipedia) demonstrate the superiority of I3 over existing schemes such as IR-tree and S2I in various aspects: it incurs shorter construction time to build the index, it has lower index storage cost, it is order of magnitude faster in updates, and it is highly scalable and answers top-k spatial keyword queries efficiently.
Antiepileptic and Antidepressive Polypharmacy in Patients with Multiple Sclerosis

Objective. Patients with multiple sclerosis (MS) are often suffering from neuropathic pain. Antiepileptic drugs (AEDs) and tricyclic antidepressants (TCAs) are commonly used and are susceptible to be involved in drug interactions. The aim of this retrospective study was to investigate the prevalence of use of antiepileptic and antidepressive drugs in MS patients and to discuss the theoretical potential for interactions. Methods. Review of the medical records from all patients treated at a dedicated MS rehabilitation centre in Norway between 2009 and 2012. Results. In total 1090 patients attended a rehabilitation stay during the study period. Of these, 342 (31%; 249 females) with mean age of 53 (±10) years and EDSS 4.8 (±1.7) used at least one AED (gabapentin 12.7%, pregabalin 7.7%, clonazepam 7.8%, and carbamazepine 2.6%) or amitriptyline (9.7%). Polypharmacy was widespread (mean 5.4 drugs) with 60% using additional CNS-active drugs with a propensity to be involved in interactions. Age, gender, and EDSS scores did not differ significantly between those using and not using AED/amitriptyline. Conclusion. One-third of MS patients attending a rehabilitation stay receive AED/amitriptyline treatment. The high prevalence of polypharmacy and use of CNS-active drugs calls for awareness of especially pharmacodynamic interactions and possible excessive adverse effects.
Faces and bases: Boolean intervals

We consider redundant analogues of the f- and h-vectors of simplicial complexes and present bases of R^{m+1} related to these ``long'' f- and h-vectors describing the face systems from 2^{1,. ,m}; we list the corresponding change of basis matrices. The representations of the long f- and h-vectors of a face system with respect to various bases are expressed based on partitions of the system into Boolean intervals.
Bringing Pictorial Space to Life: computer techniques for the analysis of paintings

This paper explores the use of computer graphics and computer vision techniques in the history of art. The focus is on analysing the geometry of perspective paintings to learn about the perspectival skills of artists and explore the evolution of linear perspective in history. Algorithms for a systematic analysis of the twoand three-dimensional geometry of paintings are drawn from the work on “single-view reconstruction” and applied to interpreting works of art from the Italian Renaissance and later periods. Since a perspectival painting is not a photograph of an actual subject but an artificial construction subject to imaginative manipulation and inadvertent inaccuracies, the internal consistency of its geometry must be assessed before carrying out any geometric analysis. Some simple techniques to analyse the consistency and perspectival accuracy of the geometry of a painting are discussed. Moreover, this work presents new algorithms for generating new views of a painted scene or portions of it, analysing shapes and proportions of objects, filling in occluded areas, performing a complete threedimensional reconstruction of a painting and a rigorous analysis of possible reconstruction ambiguities. The validity of the techniques described here is demonstrated on a number of historical paintings and frescoes. Whenever possible, the computer-generated results are compared to those obtained by art historians through careful manual analysis. This research represents a further attempt to build a constructive dialogue between two very different disciplines: computer science and history of art. Despite their fundamental differences, science and art can learn and be enriched by each other’s procedures. A longer and more detailed version of this paper may be found in [5].
Anatomy of the Enigmatic Reptile Elachistosuchus huenei Janensch, 1949 (Reptilia: Diapsida) from the Upper Triassic of Germany and Its Relevance for the Origin of Sauria

The holotype and only known specimen of the enigmatic small reptile Elachistosuchus huenei Janensch, 1949 from the Upper Triassic (Norian) Arnstadt Formation of Saxony-Anhalt (Germany) is redescribed using μCT scans of the material. This re-examination revealed new information on the morphology of this taxon, including previously unknown parts of the skeleton such as the palate, braincase, and shoulder girdle. Elachistosuchus is diagnosed especially by the presence of the posterolateral process of the frontal, the extension of the maxillary tooth row to the posterior margin of the orbit, the free posterior process of the jugal, and the notched anterior margin of the interclavicle. Phylogenetic analyses using two recently published character-taxon matrices recovered conflicting results for the phylogenetic position of Elachistosuchus–either as an archosauromorph, as a lepidosauromorph or as a more basal, non-saurian diapsid. These different placements highlight the need of a thorough revision of critical taxa and new character sets used for inferring neodiapsid relationships.
Rule Based System for Enhancing Recall for Feature Mining from Short Sentences in Customer Review Documents

This paper discovers rules for enhancing the recall values of sentences containing opinions from customer review documents. It does so by mining the features and opinion from different blogs, news site, and review sites. With the advent of numerous web sites which are posting online reviews and opinion there has been exponential growth of user generated contents. Since almost all the contents are stored in unstructured or semi-structured format, mining of features and opinions from it has become a challenging task. The paper extracts features and thereby opinions sentences using semantic and linguistic analysis of text documents. The polarity of the extracted opinions is established using numeric score values obtained through Senti- WordNet. The system shows that normal rules discovered earlier are not sufficient to improve recall values as some of the opinions does not contain sentences which are linguistically correct but they express the main idea what the writer wants to convey about his opinion on a particular product. Our experiment uses a method which first identifies short sentences and then uses rules which can be applied on those sentences so that the recall values are enhanced. The paper also applies rules on sentences which are linguistically and syntactically incorrect. The efficacy of the system is established through experimentation over customer reviews on four different models of digital camera, and iPhone. Keywords-Opinion mining; Opinion analysis; Sentiment Analysis; Text mining; Rules generation; Natural language processing.
UbiBeam++: Augmenting Interactive Projection with Head-Mounted Displays

Interactive tabletops or projections became widely utilized in schools, museum exhibitions or conference rooms to teach and illustrate dynamic artifacts or support talks. In such scenarios, all observers, such as pupils and teachers, will perceive the same information even if they hold different positions and could benefit from an adapted and personalized view. We developed the UbiBeam++ mixed reality software toolkit to enable augmentation of an interactive projection surface using optical see-through glasses. Our toolkit supports simultaneous presentation of private, shared, and public content. Private and shared content is registered in space and presented through a head-mounted display, while public content is presented by a projector. Our toolkit simplifies the development of interactive projections with different visualization levels. In a preliminary study, participants understood the concept of personalized information space and appreciated the presentation of additional information. Looking forward, our toolkit supports the development and the exploration of various scenarios not only limited to teaching, presentations or games.
Testing Intrusion detection systems: a critique of the 1998 and 1999 DARPA intrusion detection system evaluations as performed by Lincoln Laboratory

In 1998 and again in 1999, the Lincoln Laboratory of MIT conducted a comparative evaluation of intrusion detection systems (IDSs) developed under DARPA funding. While this evaluation represents a significant and monumental undertaking, there are a number of issues associated with its design and execution that remain unsettled. Some methodologies used in the evaluation are questionable and may have biased its results. One problem is that the evaluators have published relatively little concerning some of the more critical aspects of their work, such as validation of their test data. The appropriateness of the evaluation techniques used needs further investigation. The purpose of this article is to attempt to identify the shortcomings of the Lincoln Lab effort in the hope that future efforts of this kind will be placed on a sounder footing. Some of the problems that the article points out might well be resolved if the evaluators were to publish a detailed description of their procedures and the rationale that led to their adoption, but other problems would clearly remain. /par>
Classification of Attitude Words for Opinion Mining

This work details appraisal extraction from attitude expressions. Here, by attitude expressions, we refer to those single words that convey the evaluation of sentiments or emotional states, about human behaviors, objects, processes or people, according to the Appraisal Theory of language. The attitude words can be classified into affect, judgment, and appreciation; either positive or negative. Extraction of the attitude words has a significant range of applications from opinion extraction and summarization, up to temporal opinion analysis. To determine the attitude, we use two machine learning techniques; namely, Support Vector Machines and Random Forest. These algorithms classify a given word starting from a vector that represents the information from the context where the words tend to occur. On the other hand, we can observe the context of the words relying on a corpus of sentences from user generated contents, such as reviews, editorials and other online texts.
Exploiting Semantic Proximity for Information Retrieval

In this paper, we propose a method which exploits the semantic proximity of words in unrestricted natural language text to retrieve relevant documents. In order to facilitate this functionality, the system represents the documents and the query in the form of semantically relatable sets (SRS), which are a group of entities demanding semantic relations when the semantic representation of the sentence is ultimately produced. We also devise a method to augment the SRSs to further boost the performance. WordNet is used to deal with different forms of divergence between the query and the documents. In a series of experiments on TREC data, our semantic proximity based retrieval technique yields high precision with improved mean-average-precision in comparison to conventional retrieval techniques.
Word sense disambiguation using machine-readable dictionaries

Most approaches to full-text information retrieval currently index documents based on the words they contain, and retrieve them based on the word’s frequency of occurrence. This can cause many irrelevant documents to be retrieved because words are often ambiguous. We propose an approach in which documents are indexed by word aenaea, and in which these senses are taken from a machine-readable dictionary. We review some of the work on machine-readable dictionaries and the approaches that have been taken to word sense disambiguation. We then discuss our own approach to the problem based on the use of multiple sources of evidence. We conclude with the results of some experiments that indicate the degree to which lexical ambiguity is a factor in current systems.
How Does Institutional Change Coincide with Changes in the Quality of Life? An Exemplary Case Study

This paper provides a framework to assess correlations between the change of institutional functions (political centralization, plurality, rule of law, security of property, economic liberty, measured by 12 indicators) and improvements in human development (income, education, health) and violence limitations (conflict-related death tolls) to separate effective from ineffective institutional change. We apply this framework to a low-end institutional environment and provide a century case study of today’s Democratic Republic of the Congo (DRC). Major results are threefold: first, we provide a thick description of institutional development in the Congo in a colonial and post-colonial and hence long-run setting; secondly, we identify periods of institutional change with distinctly different degrees of effectiveness; and thirdly, we are able to provide qualitative information on the questions of perspective (we follow a non-elitist approach), institutional connections, and timing of effects. Finally we propose extension of the framework, especially with respect to in-depth studies of critical transition periods, and its application to comparative case studies.
Monitoring Editor

Perturbation of neddylation-dependent NF-κB responses in the intestinal epithelium drives apoptosis and inhibits resolution of mucosal inflammation ABSTRACT Recent work has revealed a central role for neddylation (the conjugation of a Nedd8 moiety to Cullin proteins) in the fine-tuning of the NF-κB response (via Cullin-1). In the present study, we investigated the contribution of Cullin-1 neddylation and NF-κB signaling to mucosal inflammatory responses in vitro and in vivo. Initial in vitro studies using cultured intestinal epithelial cells revealed that the neddylation inhibitor MLN4924 prominently induces the deneddylation of Cullin-1. Parallel Western blot, luciferase reporter, and gene target assays identified MLN4924 as a potent inhibitor of intestinal epithelial NF-κB. Subsequent studies revealed that MLN4924 potently induces epithelial apoptosis but only in the presence of additional inflammatory stimuli. In vivo administration of MLN4924 (3 mg/kg per day) in a TNBS-induced colitis model significantly accentuated disease severity. Indeed, MLN4924 resulted in worsened clinical scores and increased mortality early in the inflamma-tory response. Histologic analysis of the colon revealed that neddylation inhibition results in increased tissue damage and significantly increased mucosal apoptosis as determined by TUNEL and cleaved caspase-3 staining, which was particularly prominent within the epitheli-um. Extensions of these studies revealed that ongoing inflammation is associated with significant loss of deneddylase-1 (SENP8) expression. These studies reveal that intact Cullin-1 neddylation is central to resolution of acute inflammation. the addition of a neural precursor expressed, developmentally down-regulated (Nedd8) moiety to proteins (Bruning et al., 2011)—has recently gained significant attention in a variety of diseases. Neddylation is involved in the regulation of two key transcription factors, facilitating activation of nuclear factor κB (NF-κB; Amir et al., 2002; Ehren-traut et al., 2013) and inhibition of hypoxia-inducible factor (HIF) during inflammatory processes (Cernada et al., 2011; Curtis et al., 2015). Their respective regulation relies on the intricate interplay between NF-κB and HIF, their regulator proteins, IκB, and von Hippel–Lindau protein and a group of scaffolding proteins called Cullin proteins (Pan et al., 2004; Merlet et al., 2009). The ability of these Cullin proteins to mark their target proteins for ubiquitin-dependent proteasomal degradation relies on their neddylation status (Pan et al., 2004). These authors contributed equally to this work. The authors declare no financial interests in any of the work presented here. Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License
Voltage sag characterization with Matlab/Simulink

This paper describes a methodology for voltage sag characterization using Matlab/Simulink. It includes fault simulations for voltage sag magnitude calculation using Simulink, based on the SimPowerSystems toolbox, and also considering protection-systems modeling for sag duration calculation. Other sag characteristics, such as phase-angle jump and shape, are described and simulated.
SON conflict resolution using reinforcement learning with state aggregation

In future generation networks one of the main focuses is on automating the network optimization. This is done through so called Self Organizing Network (SON) functions. A SON instance is a realization of a SON function that governs one or several cells. Several independent SON instances of one or multiple SON functions are likely to generate conflicts. This raises the need for a SON COordinator (SONCO) meant to solve these conflicts. In this paper we consider that each SON function has one SON instance on every cell and we present the design of a SONCO function for coordinating all these instances. The SONCO solves the conflicts that appear on the update requests arbitrating (i.e. accepting/denying the requests) so that it minimizes a predefined regret. This regret takes into account the weights associated to the SON functions that rank their importance according to the operator policies. We solve the problem in a Reinforcement Learning (RL) framework as it offers the possibility to improve the decisions based on past experiences. We employ a state-aggregation technique to make the state space of our solution scale linearly with the number of cells. We provide a study case for two SON functions: Mobility Load Balancing (MLB) tuning the Cell Individual Offset(CIO) and Mobility Robustness Optimization (MRO) tuning the CIO together with the handover hysteresis. The proposed SONCO function solves the conflicts on the CIO update requests. Numerical results show how the proposed SONCO is able to favor either MLB or MRO requests according to their associated weights.