Miracle-dz/UniFAR-FTUs huggingface dataset:
American Exceptionalism: Population Trends and Flight Initiation Distances in Birds from Three Continents

Background All organisms may be affected by humans' increasing impact on Earth, but there are many potential drivers of population trends and the relative importance of each remains largely unknown. The causes of spatial patterns in population trends and their relationship with animal responses to human proximity are even less known. Methodology/Principal Finding We investigated the relationship between population trends of 193 species of bird in North America, Australia and Europe and flight initiation distance (FID); the distance at which birds take flight when approached by a human. While there is an expected negative relationship between population trend and FID in Australia and Europe, we found the inverse relationship for North American birds; thus FID cannot be used as a universal predictor of vulnerability of birds. However, the analysis of the joint explanatory ability of multiple drivers (farmland breeding habitat, pole-most breeding latitude, migratory habit, FID) effects on population status replicated previously reported strong effects of farmland breeding habitat (an effect apparently driven mostly by European birds), as well as strong effects of FID, body size, migratory habit and continent. Farmland birds are generally declining. Conclusions/Significance Flight initiation distance is related to population trends in a way that differs among continents opening new research possibilities concerning the causes of geographic differences in patterns of anti-predator behavior.
Spontaneous expression of mirror self-recognition in monkeys after learning precise visual-proprioceptive association for mirror images

Significance Self-awareness is a higher intelligence that can be revealed by mirror self-recognition (MSR) in humans. Testing MSR has become the main approach to examining the existence of self-recognition in animals, and only a few species have passed the test. However, it remains controversial whether failing the MSR test is a result of the lack of an animal’s self-recognition ability or the inadequacy of the mirror test. We found that MSR spontaneously appeared in rhesus monkeys after training for precise visual-proprioceptive association for mirror images. Thus, bodily self-consciousness may be a cognitive ability present in many more species than previously thought, and could be revealed by MSR when the animal acquired visual-proprioceptive association for the images in the mirror. Mirror self-recognition (MSR) is generally considered to be an intrinsic cognitive ability found only in humans and a few species of great apes. Rhesus monkeys do not spontaneously show MSR, but they have the ability to use a mirror as an instrument to find hidden objects. The mechanism underlying the transition from simple mirror use to MSR remains unclear. Here we show that rhesus monkeys could show MSR after learning precise visual-proprioceptive association for mirror images. We trained head-fixed monkeys on a chair in front of a mirror to touch with spatiotemporal precision a laser pointer light spot on an adjacent board that could only be seen in the mirror. After several weeks of training, when the same laser pointer light was projected to the monkey's face, a location not used in training, all three trained monkeys successfully touched the face area marked by the light spot in front of a mirror. All trained monkeys passed the standard face mark test for MSR both on the monkey chair and in their home cage. Importantly, distinct from untrained control monkeys, the trained monkeys showed typical mirror-induced self-directed behaviors in their home cage, such as using the mirror to explore normally unseen body parts. Thus, bodily self-consciousness may be a cognitive ability present in many more species than previously thought, and acquisition of precise visual-proprioceptive association for the images in the mirror is critical for revealing the MSR ability of the animal.
Disability in adults with arthrogryposis is severe, partly invisible, and varies by genotype

Objective To understand the disability of adults with arthrogryposis multiplex congenita (AMC), a rare disease spectrum characterized by at least 2 joint contractures at birth in different body areas. Methods This is a retrospective analysis of data for unselected persons with AMC referred to the French center for adults with AMC from 2010 to 2016. All underwent a pluriprofessional systematic and comprehensive investigation of deficits, activity limitation, and participation restriction according to the International Classification of Functioning, Disability and Health and genetic analysis when indicated. Participants were divided by amyoplasia and other AMC types. Results Mean (SD) age of the 43 participants (27 female) was 33.2 (13.4) years; 28 had amyoplasia and 15 other types of AMC. Beyond joint stiffness, deformities, and muscle weakness, the well-known core symptoms that we quantified and for which first-line treatment involved technical aids, other less visible disorders that could contribute to severe participation restriction were particularly pain and psychological problems including anxiety, fatigue, difficulty in sexual life, altered self-esteem, and feelings of solitude. Severe respiratory disorders were infrequent and were linked to PIEZO2 mutations. Gait disorders were not due to respiratory impairment but to skeletal problems and were always associated with amyoplasia when severe. Functional independence was worse but respiratory and swallowing capacities were better with amyoplasia than other AMC types. Conclusion This study describes disability patterns of a cohort of adults with AMC by genotype. The disability of adults with AMC is influenced by genotype, with important invisible disability.
Xenopus Piwi proteins interact with a broad proportion of the oocyte transcriptome

Piwi proteins utilize small RNAs (piRNAs) to recognize target transcripts such as transposable elements (TE). However, extensive piRNA sequence diversity also suggests that Piwi/piRNA complexes interact with many transcripts beyond TEs. To determine Piwi target RNAs, we used ribonucleoprotein-immunoprecipitation (RIP) and cross-linking and immunoprecipitation (CLIP) to identify thousands of transcripts associated with the Piwi proteins XIWI and XILI (Piwi-protein-associated transcripts, PATs) from early stage oocytes of X. laevis and X. tropicalis. Most PATs associate with both XIWI and XILI and include transcripts of developmentally important proteins in oogenesis and embryogenesis. Only a minor fraction of PATs in both frog species displayed near perfect matches to piRNAs. Since predicting imperfect pairing between all piRNAs and target RNAs remains intractable, we instead determined that PAT read counts correlate well with the lengths and expression levels of transcripts, features that have also been observed for oocyte mRNAs associated with Drosophila Piwi proteins. We used an in vitro assay with exogenous RNA to confirm that XIWI associates with RNAs in a length- and concentration-dependent manner. In this assay, noncoding transcripts with many perfectly matched antisense piRNAs were unstable, whereas coding transcripts with matching piRNAs were stable, consistent with emerging evidence that Piwi proteins both promote the turnover of TEs and other RNAs, and may also regulate mRNA localization and translation. Our study suggests that Piwi proteins play multiple roles in germ cells and establishes a tractable vertebrate system to study the role of Piwi proteins in transcript regulation.
Set-based label propagation of face images

Graph-based Semi-Supervised Learning (SSL) has proven to be an effective tool for label propagation, however, its accuracy is highly dependent on how to form the data weight matrix, in which each element is obtained as the similarity between every pair of data points. Inspired by the success of set-based recognition methods, a novel approach is brought up to incorporate the set-to-set matching as well as single-to-single matching when building up the weight matrix. Canonical Correlation Analysis (CCA), which measures the principal angles between two manifolds, is adopted to compute the set similarity. Moreover, Local Binary Pattern, an effective texture descriptor, is investigated as a data representation to further improve the label propagation performance. The proposed approach is evaluated on two public face image data sets, and shown to significantly outperform the standard SSL methods in terms of accuracy.
Anomalies in Network Bridges Involved in Bile Acid Metabolism Predict Outcomes of Colorectal Cancer Patients

Biomarkers prognostic for colorectal cancer (CRC) would be highly desirable in clinical practice. Proteins that regulate bile acid (BA) homeostasis, by linking metabolic sensors and metabolic enzymes, also called bridge proteins, may be reliable prognostic biomarkers for CRC. Based on a devised metric, “bridgeness,” we identified bridge proteins involved in the regulation of BA homeostasis and identified their prognostic potentials. The expression patterns of these bridge proteins could distinguish between normal and diseased tissues, suggesting that these proteins are associated with CRC pathogenesis. Using a supervised classification system, we found that these bridge proteins were reproducibly prognostic, with high prognostic ability compared to other known markers.
Comparison of the Transcriptome between Two Cotton Lines of Different Fiber Color and Quality

To understand the mechanism of fiber development and pigmentation formation, the mRNAs of two cotton lines were sequenced: line Z128 (light brown fiber) was a selected mutant from line Z263 (dark brown fiber). The primary walls of the fiber cell in both Z263 and Z128 contain pigments; more pigments were laid in the lumen of the fiber cell in Z263 compared with that in Z128. However, Z263 contained less cellulose than Z128. A total of 71,895 unigenes were generated: 13,278 (20.26%) unigenes were defined as differentially expressed genes (DEGs) by comparing the library of Z128 with that of Z263; 5,345 (8.16%) unigenes were up-regulated and 7,933 (12.10%) unigenes were down-regulated. qRT-PCR and comparative transcriptional analysis demonstrated that the pigmentation formation in brown cotton fiber was possibly the consequence of an interaction between oxidized tannins and glycosylated anthocyanins. Furthermore, our results showed the pigmentation related genes not only regulated the fiber color but also influenced the fiber quality at the fiber elongation stage (10 DPA). The highly expressed flavonoid gene in the fiber elongation stage could be related to the fiber quality. DEGs analyses also revealed that transcript levels of some fiber development genes (Ca2+/CaM, reactive oxygen, ethylene and sucrose phosphate synthase) varied dramatically between these two cotton lines.
Examining the Prey Mass of Terrestrial and Aquatic Carnivorous Mammals: Minimum, Maximum and Range

Predator-prey body mass relationships are a vital part of food webs across ecosystems and provide key information for predicting the susceptibility of carnivore populations to extinction. Despite this, there has been limited research on the minimum and maximum prey size of mammalian carnivores. Without information on large-scale patterns of prey mass, we limit our understanding of predation pressure, trophic cascades and susceptibility of carnivores to decreasing prey populations. The majority of studies that examine predator-prey body mass relationships focus on either a single or a subset of mammalian species, which limits the strength of our models as well as their broader application. We examine the relationship between predator body mass and the minimum, maximum and range of their prey's body mass across 108 mammalian carnivores, from weasels to baleen whales (Carnivora and Cetacea). We test whether mammals show a positive relationship between prey and predator body mass, as in reptiles and birds, as well as examine how environment (aquatic and terrestrial) and phylogenetic relatedness play a role in this relationship. We found that phylogenetic relatedness is a strong driver of predator-prey mass patterns in carnivorous mammals and accounts for a higher proportion of variance compared with the biological drivers of body mass and environment. We show a positive predator-prey body mass pattern for terrestrial mammals as found in reptiles and birds, but no relationship for aquatic mammals. Our results will benefit our understanding of trophic interactions, the susceptibility of carnivores to population declines and the role of carnivores within ecosystems.
Genome-Wide Mutagenesis of Dengue Virus Reveals Plasticity of the NS1 Protein and Enables Generation of Infectious Tagged Reporter Viruses

ABSTRACT Dengue virus (DENV) is a major global pathogen that causes significant morbidity and mortality in tropical and subtropical areas worldwide. An improved understanding of the regions within the DENV genome and its encoded proteins that are required for the virus replication cycle will expedite the development of urgently required therapeutics and vaccines. We subjected an infectious DENV genome to unbiased insertional mutagenesis and used next-generation sequencing to identify sites that tolerate 15-nucleotide insertions during the virus replication cycle in hepatic cell culture. This revealed that the regions within capsid, NS1, and the 3′ untranslated region were the most tolerant of insertions. In contrast, prM- and NS2A-encoding regions were largely intolerant of insertions. Notably, the multifunctional NS1 protein readily tolerated insertions in regions within the Wing, connector, and β-ladder domains with minimal effects on viral RNA replication and infectious virus production. Using this information, we generated infectious reporter viruses, including a variant encoding the APEX2 electron microscopy tag in NS1 that uniquely enabled high-resolution imaging of its localization to the surface and interior of viral replication vesicles. In addition, we generated a tagged virus bearing an mScarlet fluorescent protein insertion in NS1 that, despite an impact on fitness, enabled live cell imaging of NS1 localization and traffic in infected cells. Overall, this genome-wide profile of DENV genome flexibility may be further dissected and exploited in reporter virus generation and antiviral strategies. IMPORTANCE Regions of genetic flexibility in viral genomes can be exploited in the generation of reporter virus tools and should arguably be avoided in antiviral drug and vaccine design. Here, we subjected the DENV genome to high-throughput insertional mutagenesis to identify regions of genetic flexibility and enable tagged reporter virus generation. In particular, the viral NS1 protein displayed remarkable tolerance of small insertions. This genetic flexibility enabled generation of several novel NS1-tagged reporter viruses, including an APEX2-tagged virus that we used in high-resolution imaging of NS1 localization in infected cells by electron microscopy. For the first time, this analysis revealed the localization of NS1 within viral replication factories known as “vesicle packets” (VPs), in addition to its acknowledged localization to the luminal surface of these VPs. Together, this genetic profile of DENV may be further refined and exploited in the identification of antiviral targets and the generation of reporter virus tools.
Deep learning with word embeddings improves biomedical named entity recognition

Motivation: Text mining has become an important tool for biomedical research. The most fundamental text‐mining task is the recognition of biomedical named entities (NER), such as genes, chemicals and diseases. Current NER methods rely on pre‐defined features which try to capture the specific surface properties of entity types, properties of the typical local context, background knowledge, and linguistic information. State‐of‐the‐art tools are entity‐specific, as dictionaries and empirically optimal feature sets differ between entity types, which makes their development costly. Furthermore, features are often optimized for a specific gold standard corpus, which makes extrapolation of quality measures difficult. Results: We show that a completely generic method based on deep learning and statistical word embeddings [called long short‐term memory network‐conditional random field (LSTM‐CRF)] outperforms state‐of‐the‐art entity‐specific NER tools, and often by a large margin. To this end, we compared the performance of LSTM‐CRF on 33 data sets covering five different entity classes with that of best‐of‐class NER tools and an entity‐agnostic CRF implementation. On average, F1‐score of LSTM‐CRF is 5% above that of the baselines, mostly due to a sharp increase in recall. Availability and implementation: The source code for LSTM‐CRF is available at https://github.com/glample/tagger and the links to the corpora are available at https://corposaurus.github. io/corpora/. Contact: habibima@informatik.hu‐berlin.de
Mobile user interfaces for efficient verification of holograms

Paper documents such as passports, visas and banknotes are frequently checked by inspection of security elements. In particular, view-dependent elements such as holograms are interesting, but the expertise of individuals performing the task varies greatly. Augmented Reality systems can provide all relevant information on standard mobile devices. Hologram verification still takes long and causes considerable load for the user. We aim to address this drawback by first presenting a work flow for recording and automatic matching of hologram patches. Several user interfaces for hologram verification are presented, aiming to noticeably reduce verification time. We evaluate the most promising interfaces in a user study with prototype applications running on off-the-shelf hardware. Our results indicate that there is a significant difference in capture time between interfaces but that users do not prefer the fastest interface.
A robust method to extract the rotational part of deformations

We present a novel algorithm to extract the rotational part of an arbitrary 3 X 3 matrix. This problem lies at the core of two popular simulation methods in computer graphics, the co-rotational Finite Element Method and Shape Matching techniques. In contrast to the traditional method based on polar decomposition, degenerate configurations and inversions are handled robustly and do not have to be treated in a special way. In addition, our method can be implemented with only a few lines of code without branches which makes it particularly well suited for GPU-based applications. We demonstrate the robustness, coherence and efficiency of our method by comparing it to stabilized polar decomposition in several simulation scenarios.
Multi-agent based internet search

In this paper, we present a multi-agent system for searching the internet. The search for interesting documents on the internet is becoming more and more difficult. The main problem is not that we do not have the needed information to build or use knowledge, the problem is that we have too much information, mostly irrelevant. A proof of this is that inference engines are largely outperformed by the expansion of the internet and the results of queries are often of very poor quality. To improve the search process, intelligent individual agents were developed. We believe that multi-agent systems can give more accurate results than the individual agents because in a multi-agent system, agents can be specialised in different tasks and can share information. We implemented such an approach using an open multi-agent system containing personal assistants, library agents, filter agents, and search agents. In this paper, we study the models of internet multi-agent systems and propose an architecture to do intelligent web search. The application is based on an AUML protocol (slightly extended) to allow interoperability and yields more accurate results than standard search engines.
Expecting the best and being prepared for the worst: structure, profiles, and 2‐year temporal stability of dispositional optimism in women with breast cancer

Dispositional optimism is viewed as a key personality resource for resiliency and has been linked to adjustment among women with breast cancer. The aim was to examine (a) the psychometric proprieties of Life Orientation Test‐Revised (LOT‐R), (b) the potential independence and co‐occurrence of positive and negative dimensions of future outcome expectancies, (c) the longitudinal invariance of LOT‐R and the temporal stability of dispositional optimism over 2 years following surgery, and (d) the predictive impact of optimism and pessimism on emotional distress among women with breast cancer.
USING AN EFFICIENT ARTIFICIAL BEE COLONY ALGORITHM FOR PROTEIN STRUCTURE PREDICTION ON LATTICE MODELS

The well-known artificial bee colony (ABC) algorithm is one of the most recently introduced swarm-based algorithms. The ABC system combines both local and global search methods in an attempt to balance exploration and exploitation processes, and hopefully, it can be successfully applied to solve real-world problems. In the past, the Science Magazine named the protein folding problem (PFP) as one of the 125 biggest unsolved problems in science. The PFP addresses the question of how the amino acid sequence (AAS) of a specific protein dictates its structure. In the study, we present a modified ABC (MABC) algorithm for the PFP with both 2D and 3D HP models. We demonstrate that our algorithm can be applied successfully to the protein folding problem based on the hydrophobic-polar lattice model. The simulation results show that the modified artificial bee colony algorithm can successfully be applied to the protein folding problem.
Multi-Chip Dataflow Architecture for Massive Scale Biophysically Accurate Neuron Simulation

State-of-the-art neuron simulators are capable of simulating at most few tens/hundreds of neurons in real-time due to the exponential growth in the communication costs with the number of simulated neurons. In this paper, we present a novel, reconfigurable, multi-chip system architecture based on localized communication, which effectively reduces the communication cost to a linear growth. The system is very flexible and it allows to tune, at run-time, various parameters, e.g. the intracellular concentration of chemical compounds, the interconnection scheme between the neurons. Experimental results indicate that the proposed system architecture allows the simulation of up to few thousands biophysically accurate neurons over multiple chips.
Endogenous Technology Adoption and Medical Costs

Despite the claim that technology has been one of the most important drivers of healthcare spending growth over the past decades, technology variables are rarely introduced explicitly in cost equations. Furthermore, technology is often considered exogenous. Using 1996-2007 panel data on Swiss geographical areas, we assessed the impact of technology availability on per capita healthcare spending covered by basic health insurance whilst controlling for the endogeneity of health technology availability variables. Our results suggest that medical research, patent intensity and the density of employees working in the medical device industry are influential factors for the adoption of technology and can be used as instruments for technology availability variables in the cost equation. These results are similar to previous findings: CT and PET scanner adoption is associated with increased healthcare spending, whilst increased availability of percutaneous transluminal coronary angioplasty facilities is associated with reductions in per capita spending. However, our results suggest that the magnitude of these relationships is much greater in absolute value than that suggested by previous studies that did not control for the possible endogeneity of the availability of technologies. Copyright © 2016 John Wiley & Sons, Ltd.