Miracle-dz/UniFAR-FTUs huggingface dataset:
Minimally supervised dependency-based methods for natural language processing

This work investigates minimally-supervised methods for solving NLP tasks, without requiring explicit annotation or training data. Our motivation is to create systems that require substantially reduced effort from domain and/or NLP experts, compared to annotating a corresponding dataset, and also offer easier domain adaptation and better generalisation properties. We apply these principles to four separate language processing tasks and analyse their performance compared to supervised alternatives. First, we investigate the task of detecting the scope of speculative language, and develop a system that applies manually-defined rules over dependency graphs. Next, we experiment with distributional similarity measures for detecting and generating hyponyms, and describe a new measure that achieves the highest performance on hyponym generation. We also extend the distributional hypothesis to larger structures and propose the task of detecting entailment relations between dependency graph fragments of various types and sizes. Our system achieves relatively high accuracy by combining distributional and lexical similarity scores. Finally, we describe a self-learning framework for improving the accuracy of an unlexicalised parser, by calculating relation probabilities using its own dependency output. The method requires only a large in-domain text corpus and can therefore be easily applied to different domains and genres. While fully supervised approaches generally achieve the highest results, our experiments found minimally supervised methods to be remarkably competitive. By moving away from explicit supervision, we aim to better understand the underlying patterns in the data, and to create systems that are not tied to any specific domains, tasks or resources.
A New Nasopharyngeal Dynamic Reference Frame Improves Accuracy in Navigated Skull Base Targets

Objective. We questioned whether the position of the dynamic reference frame (DRF) influences the application accuracy in electromagnetically navigated cranial procedures. A carrier for an electromagnetic DRF was developed, which could be fixed at the posterior edge of the vomer near the center of the head. This nasopharyngeal DRF was compared with a standard DRF fixed to the surface of the forehead. Methods. Image coordinates and real-world coordinates were co-registered and the total target error (TTE) was measured in the frontal and the lateral skull base of formalin fixed human head. At each anatomical site, 10 targets served for TTE determinations and 5 different fiducial combinations were used for registration. Results. With the nasopharyngeal DRF, lower TTE values (2.8 ± 1.4 mm; mean ± SD) were observed when compared with the forehead DRF (3.7 ± 2.8 mm; P = .004). TTEs of both anatomical sites investigated were significantly lower when using the nasopharyngeal DRF (frontal skull base 3.4 vs 2.1 mm, P = .005 and lateral skull base 3.9 vs 3.5 mm, P = .013) than with the standard forehead mounted one. Conclusion. Positioning the DRF in the center of the head significantly improved the application accuracy of targets in the skull base with electromagnetic navigation by 25%.
An Analysis of Forced and Internal Variability in a Warmer Climate in CCSM3

AbstractChanges in the mean state and the modes of internal variability due to increases in greenhouse gas (GHG) and aerosol concentrations were investigated by comparing a suite of long-term integrations of A1B runs and the corresponding control runs with a constant level of GHG and aerosol concentrations in the Community Climate System Model, version 3 (CCSM3). The evolution of signal- [defined as the standard deviation (STDV) of ensemble mean anomalies] to-noise (defined as STDV of departures of individual members from their corresponding ensemble means) ratio (SNR) is examined. It is shown that SNR is sensitive to the amplitude of external forcing, and the sensitivity is variable and geographical location dependent. The time evolution of the SNR is largely due to the changes in the mean while little influence on the internal variability is found. Surface air temperature (TS) and geopotential height at 200 hPa (H200) responses are largely linear with an increase in GHG and aerosol concentrations and ca.
Treponema pallidum receptor binding proteins interact with fibronectin

Analysis of plasma proteins avidly bound to T. pallidum surfaces revealed the ability of T. pallidum to acquire numerous host macromolecules. No acquisition was evident by the avirulent spirochete, T. phagedenis biotype Reiter. Western blotting technology using hyperimmune antifibronectin serum as a probe revealed the ability of virulent treponemes to avidly bind fibronectin from a complex medium such as plasma. The specificity of the tiplike adherence of motile T. pallidum to fibronectin-coated glass surfaces and to fibronectin on HEp- 2 cells was reinforced by the observation that pretreatment of coverslips or cell monolayers with monospecific antiserum against fibronectin substantially reduced T. pallidum attachment. The stoichiometric binding of T. pallidum to fibronectin-coated coverslips and the inability of unlabeled or 35S-radiolabeled treponemes to interact with glass surfaces treated with other plasma proteins further established the specific nature of the interaction between virulent T. pallidum and fibronectin. The avid association between three outer envelope proteins of T. pallidum and fibronectin was also demonstrated. These treponemal surface proteins have been previously identified as putative receptor-binding proteins responsible for T. pallidum parasitism of host cells. The data suggest that surface fibronectin mediates tip-oriented attachment of T. pallidum to host cells via a receptor-ligand mechanism of recognition.
Community Detection and Analysis in PPI Network

Community detection problem has been studied for years, but no agreement on the common definition of community has been reached till now. One topology may be of different types, unipartite or bipartite/multipartite. The previous literatures mostly proposed only one type of community. As the definition of community is understood differently, the grouping results are always applicable to some specified networks. If the definition changes, the grouping result will no longer be ``good''. This paper proposes an energy model to find communities in a PPI network and a hierarchical method to analyze relationship of vertices inside community. First, by analyzing the definition of community, energy model is proposed based on the characteristics of the PPI network types which are unipartite, bipartite or mixed type with both unipartite and bipartite. Second, energy model is used to find overlapping communities in PPI networks. Third, by finding the important vertices and the hierarchical levels inside a community. The experiment results show that the energy model is applicable to unipartite, bipartite or mixed PPI networks. Although the understanding of communities and the community results are different by using different community detection methods, the hierarchial method get the same level result based on different community results for a network. Hierarchical method inside community solves the limitation problem, makes community detection more accurately and universally. Furthermore, Finding local important vertices can control the spread of information of the whole network efficiently.
Low-Rank Embedding for Robust Image Feature Extraction

Robustness to noises, outliers, and corruptions is an important issue in linear dimensionality reduction. Since the sample-specific corruptions and outliers exist, the class-special structure or the local geometric structure is destroyed, and thus, many existing methods, including the popular manifold learning- based linear dimensionality methods, fail to achieve good performance in recognition tasks. In this paper, we focus on the unsupervised robust linear dimensionality reduction on corrupted data by introducing the robust low-rank representation (LRR). Thus, a robust linear dimensionality reduction technique termed low-rank embedding (LRE) is proposed in this paper, which provides a robust image representation to uncover the potential relationship among the images to reduce the negative influence from the occlusion and corruption so as to enhance the algorithm’s robustness in image feature extraction. LRE searches the optimal LRR and optimal subspace simultaneously. The model of LRE can be solved by alternatively iterating the argument Lagrangian multiplier method and the eigendecomposition. The theoretical analysis, including convergence analysis and computational complexity, of the algorithms is presented. Experiments on some well-known databases with different corruptions show that LRE is superior to the previous methods of feature extraction, and therefore, it indicates the robustness of the proposed method. The code of this paper can be downloaded from http://www.scholat. com/laizhihui.
Environmental aspects of new embedded power modules with 500 W and 50 kW

Embedding technology enables miniaturisation of electric and electronic components together with improved reliability and thermal stability in harsh environment. This work investigates in form of single case studies the environmental performance from cradle-to-gate of two new designed and fabricated power modules for electric vehicle application with the method of the Sustainable Process Index (SPI) or “ecological footprint”. The SPI results for a 500 W power module demonstrator for e-bikes is 461 m2.a/sample and for a 50 kW power module demonstrator for automotive application 18817 m2.a/sample. The life cycle impact assessments show, that the wafer manufacturing has the largest impact followed by the silver sinter paste, FR4 material and copper in case of the 500 W Demonstrator, and by the silver sinter paste in case of the 50 kW Demonstrator, respectively. These first results show, that there is further research needed to generate more precise life cycle inventory data for wafer fabrication, FR4 material manufacturing, and the fabrication of metallization sinter pastes including nano-particles.
Uncertainty Propagation in Long-Term Structured Regression on Evolving Networks

In long-term forecasting it is important to estimate the confidence of predictions, as they are often affected by errors that are accumulated over the prediction horizon. To address this problem, an effective novel iterative method is developed for Gaussian structured learning models in this study for propagating uncertainty in temporal graphs by modeling noisy inputs. The proposed method is applied for three long-term (up to 8 years ahead) structured regression problems on real-world evolving networks from the health and climate domains. The obtained empirical results and use case analysis provide evidence that the new approach allows better uncertainty propagation as compared to published alternatives.
Rural cadastral surveying with the global positioning system

Abstract Cadastral surveys have traditionally been performed using the well established techniques of traversing and radiation. The equipment used to accomplish these surveys has evolved from optical theodolites and steel bands, to total station and data recorder technology. With the recent advances in satellite technology, space based positioning systems are now capable of replacing conventional survey methods for many survey applications. This paper presents the results of a rural cadastral survey performed using the Global Positioning System (GPS). The survey was also performed using conventional total station techniques. A comparison of the results obtained reveals positional differences of one to four centimetres between the two data collection techniques.
icrofluidic doublets in aqueous samples generated by microfabricated hermal probes

This paper describes an investigation of microfluidic actuation of doublet patterns in samples of water on blank substrates, using singular and arrayed microfabricated thermal probes. A doublet is a twodimensional flow pattern consisting of adjacent, opposing vortices with linear streamlines between them. In this work, each probe consists of a polyimide thin film cantilever with a metal heater near the tip which generates a temperature gradient up to 1 ◦C/ m along its length. The probes are 360 m long, 42–120 m wide, and 3.5 m thick, and the tips are typically <1 mm away from the liquid surface. The velocity of the
Nonlinear oscillations for cyclic movements in variable impedance actuated robotic arms

Biologically inspired Variable Impedance Actuators (VIA) offer the capability to execute cyclic and/or explosive multi degree of freedom (DoF) motions efficiently by storing elastic energy. This paper studies the preconditions which allow to induce robust cyclic motions for strongly nonlinear, underactuated multi DoF robotic arms. By experimental observations of human motor control, a simple control law is deduced. This controller achieves intrinsic oscillatory motions by switching the motor position triggered by a joint torque threshold. Using the derived controller, the periodic behavior of the robotic arm is analyzed in simulations. It is found that a modal analysis of the linearized system at the equilibrium point allows to qualitatively predict the periodic behavior of this type of strongly nonlinear systems. The central statement of this paper is that cyclic motions can be induced easily in VIA systems, if the eigenfrequencies and modal damping values of the linearized system are well separated. Validation is given by simulation and experiments, where a human controls a simulated robotic arm, and the developed regulator controls a robotic arm in simulation and experiments.
Imaging chromatin nanostructure with binding-activated localization microscopy based on DNA structure fluctuations

Abstract Advanced light microscopy is an important tool for nanostructure analysis of chromatin. In this report we present a general concept for Single Molecule localization Microscopy (SMLM) super-resolved imaging of DNA-binding dyes based on modifying the properties of DNA and the dye. By careful adjustment of the chemical environment leading to local, reversible DNA melting and hybridization control over the fluorescence signal of the DNA-binding dye molecules can be introduced. We postulate a transient binding as the basis for our variation of binding-activated localization microscopy (BALM). We demonstrate that several intercalating and minor-groove binding DNA dyes can be used to register (optically isolate) only a few DNA-binding dye signals at a time. To highlight this DNA structure fluctuation-assisted BALM (fBALM), we applied it to measure, for the first time, nanoscale differences in nuclear architecture in model ischemia with an anticipated structural resolution of approximately 50 nm. Our data suggest that this approach may open an avenue for the enhanced microscopic analysis of chromatin nano-architecture and hence the microscopic analysis of nuclear structure aberrations occurring in various pathological conditions. It may also become possible to analyse nuclear nanostructure differences in different cell types, stages of development or environmental stress conditions.
maxAlike: maximum likelihood-based sequence reconstruction with application to improved primer design for unknown sequences

Motivation: The task of reconstructing a genomic sequence from a particular species is gaining more and more importance in the light of the rapid development of high-throughput sequencing technologies and their limitations. Applications include not only compensation for missing data in unsequenced genomic regions and the design of oligonucleotide primers for target genes in species with lacking sequence information but also the preparation of customized queries for homology searches. Results: We introduce the maxAlike algorithm, which reconstructs a genomic sequence for a specific taxon based on sequence homologs in other species. The input is a multiple sequence alignment and a phylogenetic tree that also contains the target species. For this target species, the algorithm computes nucleotide probabilities at each sequence position. Consensus sequences are then reconstructed based on a certain confidence level. For 37 out of 44 target species in a test dataset, we obtain a significant increase of the reconstruction accuracy compared to both the consensus sequence from the alignment and the sequence of the nearest phylogenetic neighbor. When considering only nucleotides above a confidence limit, maxAlike is significantly better (up to 10%) in all 44 species. The improved sequence reconstruction also leads to an increase of the quality of PCR primer design for yet unsequenced genes: the differences between the expected Tm and real Tm of the primer-template duplex can be reduced by ~26% compared with other reconstruction approaches. We also show that the prediction accuracy is robust to common distortions of the input trees. The prediction accuracy drops by only 1% on average across all species for 77% of trees derived from random genomic loci in a test dataset. Availability: maxAlike is available for download and web server at: http://rth.dk/resources/maxAlike. Contact: gorodkin@rth.dk Supplementary information: Supplementary data are available at Bioinformatics online.
3D Displays in Cars: Exploring the User Performance for a Stereoscopic Instrument Cluster

In this paper, we investigate user performance for stereoscopic automotive user interfaces (UI). Our work is motivated by the fact that stereoscopic displays are about to find their way into cars. Such a safety-critical application area creates an inherent need to understand how the use of stereoscopic 3D visualizations impacts user performance. We conducted a comprehensive study with 56 participants to investigate the impact of a 3D instrument cluster (IC) on primary and secondary task performance. We investigated different visualizations (2D and 3D) and complexities (low vs. high amount of details) of the IC as well as two 3D display technologies (shutter vs. autostereoscopy). As secondary tasks the participants judged spatial relations between UI elements (expected events) and reacted on pop-up instructions (unexpected events) in the IC. The results show that stereoscopy increases accuracy for expected events, decreases task completion times for unexpected tasks, and increases the attractiveness of the interface. Furthermore, we found a significant influence of the used technology, indicating that secondary task performance improves for shutter displays.
Webly-Supervised Learning of Multimodal Video Detectors

Given any complicated or specialized video content search query, e.g. ”Batkid (a kid in batman costume)” or ”destroyed buildings”, existing methods require manually labeled data to build detectors for searching. We present a demonstration of an artificial intelligence application, Webly-labeled Learning (WELL) that enables learning of ad-hoc concept detectors over unlimited Internet videos without any manual an-notations. A considerable number of videos on the web are associated with rich but noisy contextual information, such as the title, which provides a type of weak annotations or la-bels of the video content. To leverage this information, our system employs state-of-the-art webly-supervised learning(WELL) (Liang et al. ). WELL considers multi-modal information including deep learning visual, audio and speech features, to automatically learn accurate video detectors based on the user query. The learned detectors from a large number of web videos allow users to search relevant videos over their personal video archives, not requiring any textual metadata,but as convenient as searching on Youtube.
SITUACIÓN Y DISTRIBUCIÓN DE LAS NUTRIAS EN MÉXICO,CON ÉNFASIS EN Lontra longicaudis annectens MAJOR, 1897

Resumen: En Mexico existen tres especies de nutrias: dos de rio y una marina. La nutria marina o "viejo de mar" Enhydra lutris nereis (Merriam, 1904), ha sido considerada extinta, aunque hay indicios de su presencia en Baja California. En Mexico existen dos subespecies de la nutria de rio del norte: Lontra canadensis sonorae (Rhoads, 1898) en el noroeste, y Lontra canadensis lataxina (Cuvier, 1823),en el noreste. La situacion de esta especie es desconocida. Por ultimo, la nutria de rio neotropical, Lontra longicaudis annectens (Major, 1897), se encuentra distribuida en casi todos los grandes rios de las planicies costeras, arroyos, lagos, presas y lagunas costeras. Esta especie se adapta a una variedad de habitats, desde las regiones aridas con bosque espinoso y matorral, hasta los bosques tropicales perennifolios y subcaducifolios, y desde el nivel del mar con bosque tropical caducifolio, hasta 1,700m en el bosque mesofilo de montana. La poblacion de la nutria de rio neotropical esta declinando en Mexico por una serie de factores generados por el ser humano: desechos industriales y urbanos, envenenamiento de los rios, el uso de pequenas cantidades de TNT para la pesca de subsistencia familiar, la apertura de nuevas areas para la agricultura y el sistema agricola de roza, tumba y quema de los bosques tropicales. Los arroyos y rios de las sierras tropicales con cauces perennes que aun poseen la vegetacion de galeria original y una marcada epoca de lluvias, son los habitats mas estables. En funcion de lo cual son las zonas propuestas para la conservacion de las nutrias de rio. Abstract: There are two species ofriver and one species ofsea olters in Mexico. The sea olter or "viejo de mar" Enhydra lutris nereis (Merriam, 1904), has been considered extinct, ven though there are signs that a few survive in Baja California. In norhtern Mexico there are two subspecies of the river olter Lontra canadensis. L. canadensis sonorae (Rhoads, 1898) is found in northwestern Mexico, and L. canadensis lataxina (Cuvier, 1823) is found in northeastern Mexico. The conservation status of this species is unknown. Finally, the southern river olter Lontra longicaudis annectens (Major, 1897) is distributed along most rivers ofthe tropicallowlands, small rivers, lakes, damns and estuaries. This species adapts to a variety of habitats, from the arid regions with spiny bushes and scrub, to the tropical rain forests, from the sea level in the tropical dry forests up to 1,700m in cIoud forcsts.In Mexico, the population of the southern river otters is declining due to human activities: industrial and urban waste, river poisoning, the use of small amounts of TNT for fishing for familiar subsistence, the opening of new areas for agriculture and the cutting and burning oftropical forests. AlIthe localities with the original vegetation, perennial rivers and a well marked rainy season, are the more stable habitats. Based on this, these areas are proposed for the river otter's conservation. Palabras clave: distribucion, conservacion, nutrias, Lontra, Enhydra , Mexico
Geology and geochemistry of an Archean mafic dike complex in the Chan Formation: basis for a revised plate-tectonic model of the Yellowknife greenstone belt

An Archean mafic dike complex in the Chan Formation at the base of the mafic volcanic section of the Yellowknife greenstone belt consists of multiple metagabbro dikes and sills separated by screens of pillowed mafic volcanic rocks, which are cut by a younger postvolcanic metadiabase dike swarm. Field relationships and geochemical characteristics are compatible with a comagmatic origin for the metagabbro and metavolcanic rocks that were fed through and deposited on an older, rift-related, supracrustal sequence of the Dwyer Group. The synvolcanic metagabbro dikes have extended the strike length of the volcanic section by at least 100%. The mafic rocks of the Chan Formation are geochemically similar to mid-ocean ridge basalt, possibly with a minor subduction-zone component. Preliminary eNd values for metagabbroic rocks are consistent with the derivation of magmas predominantly from a normal, depleted-mantle source. The Chan Formation is interpreted to have formed in a marginal basin-like setting, adjacent to.