Miracle-dz/UniFAR-FTUs huggingface dataset:
Repeatability, reproducibility and consistency of horse shape data and its association with linearly described conformation traits in Franches-Montagnes stallions

Linear description (LD) of conformation traits was introduced in horse breeding to minimise subjectivity in scoring. However, recent studies have shown that LD traits show essentially the same problems as traditionally scored traits, such as data converging around the mean value with very small standard deviations. To improve the assessment of conformation traits of horses, we investigated the application of the recently described horse shape space model based upon 403 digitised photographs of 243 Franches-Montagnes (FM) stallions and extracted joint angles based on specific landmark triplets. Repeatability, reproducibility and consistency of the resulting shape data and joint angles were assessed with Procrustes ANOVA (Rep) and intra-class correlation coefficients (ICC). Furthermore, we developed a subjective score to classify the posture of the horses on each photograph. We derived relative warp scores (PCs) based upon the digitised photos conducting a principal component analysis (PCA). The PCs of the shapes and joint angles were compared to the posture scores and to the linear description data using linear mixed effect models including significant posture scores as random factors. The digitisation process was highly repeatable and reproducible for the shape (Rep = 0.72–0.99, ICC = 0.99). The consistency of the shape was limited by the age and posture (p < 0.05). The angle measurements were highly repeatable within one digitiser. Between digitisers, we found a higher variability of ICC values (ICC = 0.054–0.92), indicating digitising error in specific landmarks (e.g. shoulder point). The posture scores were highly repeatable (Fleiss’ kappa = 0.713–0.857). We identified significant associations (p(X2) < 0.05) with traits describing the withers height, shoulder length and incline, overall leg conformation, walk and trot step length. The horse shape data and angles provide additional information to explore the morphology of horses and therefore can be applied to improve the knowledge of the genetic architecture of LD traits.
The Brief Case: The Unexpected Souvenir

aDepartment of Medicine, Division of Infectious Diseases, Mayo Clinic, Phoenix, Arizona, USA bDepartment of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA cDepartment of Internal Medicine, Mayo Clinic, Phoenix, Arizona, USA dDepartment of Medicine, Division of Hematology and Oncology, Mayo Clinic, Phoenix, Arizona, USA eDepartment of Laboratory Medicine and Pathology, Mayo Clinic, Phoenix, Arizona, USA
Retinal Ganglion Cell Axon Sorting at the Optic Chiasm Requires Dystroglycan

In the developing visual system, retinal ganglion cell (RGC) axons project from the retina to several distal retinorecipient regions in the brain. Several molecules have been implicated in guiding RGC axons in vivo, but the role of extracellular matrix molecules in this process remains poorly understood. Dystroglycan is a laminin-binding transmembrane protein important for formation and maintenance of the extracellular matrix and basement membranes and has previously been implicated in axon guidance in the developing spinal cord. Using two genetic models of functional dystroglycan loss, we show that dystroglycan is necessary for correct sorting of contralateral and ipsilateral RGC axons at the optic chiasm. Missorted axons still target retinorecipient brain regions and persist in adult mice, even after axon pruning is complete. Our results highlight the importance of the extracellular matrix for axon sorting at an intermediate choice point in the developing visual circuit. Summary Statement Abnormal retinal ganglion cell axon sorting in the optic chiasm in the absence of functional dystroglycan results in profound defects in retinorecipient innervation.
Google n-gram viewer does not include arabic corpus! towards n-gram viewer for arabic corpus

Google N-gram viewer is one of those newly published Google services. Google archived or digitized a large number of books in different languages. Google populated the corpora from over 5 million books published up to 2008. This Google service allows users to enter queries of words. The tool then charts time-based data that show the frequency of usage of query words. Although Arabic is one of the top spoken language in the world, Arabic language is not included as one of the corpora indexed by the Google n-gram viewer. This research work discusses the development of large Arabic corpus and indexing it using N-grams to be included in Google N-gram viewer. A showcase is presented to build a dataset to initiate the process of digitizing the Arabic content and prepare it to be incorporated in Google N-gram viewer. One of the major goals of including Arabic content in Google N-gram is to enrich Arabic public content, which has been very limited in comparison with the number of people who speak Arabic. We believe that adopting Arabic language by Google N-gram viewer can significantly benefit researchers in different fields related to Arabic language and social sciences.
Interaction of Copper Toxicity and Oxidative Stress in Campylobacter jejuni

Copper is a required micronutrient for most aerobic organisms, but it is universally toxic at elevated levels. These organisms use homeostatic mechanisms that allow for cells to acquire enough of the element to sustain metabolic requirements while ensuring that lethal levels cannot build up in the cell. Campylobacter jejuni is an important foodborne pathogen that typically makes its way into the food chain through contaminated poultry. C. jejuni has a metabolic requirement for copper and encodes a copper detoxification system. In the course of studying this system, we have learned that it is important for avian colonization. We have also gained insight into how copper exerts its toxic effects in C. jejuni by promoting oxidative stress. ABSTRACT Copper is both a required micronutrient and a source of toxicity in most organisms, including Campylobacter jejuni. Two proteins expressed in C. jejuni (termed CopA and CueO) have been shown to be a copper transporter and multicopper oxidase, respectively. We have isolated strains with mutations in these genes, and here we report that they were more susceptible to both the addition of copper in the growth media and to induced oxidative stress. Both mutant strains were defective in colonization of an avian host, and copper in the feed exacerbated the colonization deficiency. Overexpression of a cytoplasmic peptide derived from the normally periplasmic copper-binding region of CueO also caused copper intolerance compared to nonexpressing strains or strains expressing the non-copper-binding versions of the peptide. Taken together, the results indicate that copper toxicity in C. jejuni is due to a failure to effectively sequester cytoplasmic copper, resulting in an increase in copper-mediated oxidative damage. IMPORTANCE Copper is a required micronutrient for most aerobic organisms, but it is universally toxic at elevated levels. These organisms use homeostatic mechanisms that allow for cells to acquire enough of the element to sustain metabolic requirements while ensuring that lethal levels cannot build up in the cell. Campylobacter jejuni is an important foodborne pathogen that typically makes its way into the food chain through contaminated poultry. C. jejuni has a metabolic requirement for copper and encodes a copper detoxification system. In the course of studying this system, we have learned that it is important for avian colonization. We have also gained insight into how copper exerts its toxic effects in C. jejuni by promoting oxidative stress.
A Novel Model Based on Square Root Elastic Net and Artificial Neural Network for Forecasting Global Solar Radiation

In recent years, solar energy has attracted a great deal of attentions from scientific researchers because it is a clean and renewable form of energy. To make good use of solar energy, an effective way to forecast solar radiation is essential to guarantee the reliability of grid-connected photovoltaic installations. Although an artificial neural network (ANN) is of great importance, irrelevant variables are utilized which results in complex model and intractable computation cost. To remove these irrelevant variables, the combination of variable selection methods and ANN are applied. However, how to select the regularization parameters in these techniques is challenging. This paper successfully investigates a square root elastic net- (SREN-) based approach to tackle this challenge and selects all the important variables. An Elman neural network (ENN) is constructed with the important variables selected by SREN as inputs. Based on meteorological data, SRENENN has been developed for 1-year period in Xinjiang area of China. The present model delivers superior relationship between the estimated and measure values.
Proceedings of the 4 th Workshop on Making Sense of Microposts ( # Microposts 2014 ) Big things come in small packages

According to the Computational Social Science Society of the Americas (CSSSA), computational social science is “The science that investigates social phenomena through the medium of computing and related advanced information processing technologies”. Positioned between the computer and social sciences, this new and emerging interdisciplinary field is fuelled by at least the following two developments: (i) availability of data: With the web, a huge volume of social data is now available which enables the study of traces of social interactions on new scales. (ii) increasing quantification of social theories: With recent advances in the social sciences, social theories become increasingly formal and/or mathematical and thus amenable to quantification. Taken together, these two developments give rise to a whole range of new and interesting problems on the intersection between computer and social sciences. While a multitude of social data is available on the World Wide Web, microblogs are of particular interest due to their real-time nature, their rich social fabric and their presumed on/offline coupling. In this talk, I am going to talk about the potentials and the challenges of doing computational social science based on data obtained from microblogs such as Twitter. In particular, I want to present previous work by my group and others to identify research avenues where progress has already been made or where progress is on the horizon, and contrast these with what I feel are open research challenges in this emerging field. Work that demonstrates the potential of microblogs for computational social science includes for example [1], where we have operationalized a number of theoretical constructs from sociology to characterize the nature of online conversational practices of political parties on Twitter. In another work, we have studied the ways in which users’ fields of expertise can be inferred from microblog data [4]. Work that demonstrates the pitfalls and challenges of doing computational social science with microblog data include for example [5] where we have studied a network of bots who are competing against each other in attacking users on Twitter. In subsequent work, we have found that such attacks have the potential to impact the social graph of Twitter [3], i.e. the network of who follows whom respectively who replies to whom. In other work, [2] have shown that there is a stark difference between the demographics of Twitter and the general population of the US, finding that Twitter users significantly over-represent densely populated regions and are predominantly male. I will argue that these and other factors need to be considered when we aim to unlock the full potential of microblog data for computational social science
Nano-rectenna powered body-centric nano-networks in the terahertz band

A wireless body-centric nano-network consists of various nano-sized sensors with the purpose of healthcare application. One of the main challenges in the network is caused by the very limited power that can be stored in nano-batteries in comparison with the power required to drive the device for communications. Recently, novel rectifying antennas (rectennas) based on carbon nanotubes (CNTs), metal and graphene have been proposed. At the same time, research on simultaneous wireless information and power transfer (SWIPT) schemes has progressed apace. Body-centric nano-networks can overcome their energy bottleneck using these mechanisms. In this Letter, a nano-rectenna energy harvesting model is developed. The energy harvesting is realised by a nano-antenna and an ultra-high-speed rectifying diode combined as a nano-rectenna. This device can be used to power nanosensors using part of the terahertz (THz) information signal without any other system external energy source. The broadband properties of nano-rectennas enable them to generate direct current (DC) electricity from inputs with THz to optical frequencies. The authors calculate the output power generated by the nano-rectenna and compare this with the power required for nanosensors to communicate in the THz band. The calculation and analysis suggest that the nano-rectenna can be a viable approach to provide power for nanosensors in body-centric nano-networks.
Integrin β1 activity is required for cardiovascular formation in zebrafish

Integrins are transmembrane molecules that facilitate cell‐to‐cell and cell‐to‐extracellular matrix (ECM) interactions. Integrin molecules are heterodimers that consist of α‐ and β‐subunits. The integrin β1 gene is widely expressed in vivo and is the major β molecule in many tissues; however, tissue‐specific roles of integrin β1 are still elusive. In this study, we investigated integrin β1 function in endothelial cells of zebrafish. An integrin β1b mutant zebrafish exhibited morphological abnormalities in blood vessel formation, cephalic hemorrhage and a decreased responsiveness to tactile stimulation during development. To determine the role of integrin β1b in vascular formation, we developed a Gal4/UAS‐mediated conditional inactivation of integrin β1 by expressing the cytoplasmic region of integrin β1 that acts as a dominant‐negative (DN) isoform. Expression of integrin β1 DN in endothelial cells induced blood vessel abnormalities as in integrin β1b mutants. These results show that endothelial cells require integrin activity for the formation and/or maintenance of blood vessels in zebrafish. Furthermore, our time‐lapse recording visualized the breakpoint of cephalic vessels and the hemorrhage onset. Taken together, our tissue‐specific inactivation of integrin β1 in zebrafish is powerful tools for functional analysis of integrin β1 in developing tissues.
Resource Allocation Game on Social Networks: Best Response Dynamics and Convergence

The decisions that human beings make to allocate time has significant bearing on economic output and to the sustenance of social networks. The time allocation problem motivates our formal analysis of the resource allocation game, where agents on a social network, who have asymmetric, private interaction preferences, make decisions on how to allocate time, a bounded endowment, over their neighbors. Unlike the well-known opinion formation game on a social network, our game appears not to be a potential game, and the Best-Response dynamics is non-differentiable making the analysis of Best-Response dynamics non-trivial. In our game, we consider two types of player behavior, namely optimistic or pessimistic, based on how they use their time endowment over their neighbors. To analyze Best-Response dynamics, we circumvent the problem of the game not being a potential game, through the lens of a novel two-level potential function approach. We show that the Best-Response dynamics converges point-wise to a Nash Equilibrium when players are all: optimistic; pessimistic; a mix of both types. Finally, we show that the Nash Equilibrium set is non-convex but connected, and Price of Anarchy is unbounded while Price of Stability is one. Extensive simulations over a stylized grid reveals that the distribution of quality of the convergence points is unimodal-we conjecture that presence of unimodality is tied to the connectedness of Nash Equilibrium.
Mapping and Sequencing of a Significant Quantitative Trait Locus Affecting Resistance to Koi Herpesvirus in Common Carp

Cyprinids are the most highly produced group of fishes globally, with common carp being one of the most valuable species of the group. Koi herpesvirus (KHV) infections can result in high levels of mortality, causing major economic losses, and is listed as a notifiable disease by the World Organization for Animal Health. Selective breeding for host resistance has the potential to reduce morbidity and losses due to KHV. Therefore, improving knowledge about host resistance and methods of incorporating genomic data into breeding for resistance may contribute to a decrease in economic losses in carp farming. In the current study, a population of 1,425 carp juveniles, originating from a factorial cross between 40 sires and 20 dams was challenged with KHV. Mortalities and survivors were recorded and sampled for genotyping by sequencing using Restriction Site-Associated DNA sequencing (RADseq). Genome-wide association analyses were performed to investigate the genetic architecture of resistance to KHV. A genome-wide significant QTL affecting resistance to KHV was identified on linkage group 44, explaining approximately 7% of the additive genetic variance. Pooled whole genome resequencing of a subset of resistant (n = 60) and susceptible animals (n = 60) was performed to characterize QTL regions, including identification of putative candidate genes and functional annotation of associated polymorphisms. The TRIM25 gene was identified as a promising positional and functional candidate within the QTL region of LG 44, and a putative premature stop mutation in this gene was discovered.
Persistent Stochastic Non-Interference

In this paper, we study an information flow security property for systems specified as terms of a quantitative Markovian process algebra, namely the Performance Evaluation Process Algebra (PEPA). We propose a quantitative extension of the Non-Interference property used to secure systems from the functional point view by assuming that the observers are able to measure also the timing properties of the system, e.g., the response time of certain actions or its throughput. We introduce the notion of Persistent Stochastic Non-Interference (PSNI) based on the idea that every state reachable by a process satisfies a basic Stochastic Non-Interference (SNI) property. The structural operational semantics of PEPA allows us to give two characterizations of PSNI: one based on a bisimulation-like equivalence relation inducing a lumping on the underlying Markov chain, and another one based on unwinding conditions which demand properties of individual actions. These two different characterizations naturally lead to efficient methods for the verification and construction of secure systems. A decision algorithm for PSNI is presented and an application of PSNI to a queueing system is discussed.
The Complexity and Simulation of Revenue Sharing Negotiation Based on Construction Stakeholders

This paper focuses on the complexity characteristics of a stakeholder’s revenue sharing for time compression in construction projects, such as adopting a life cycle perspective, the preferences of stakeholders, and the adaptability behaviors in the negotiation process. We build an agent-based model on revenue sharing negotiation. Considering that the agents who are in a weak position not only care about their own benefits but also compare their benefits to others, we design an experimental scenario where a contractor has fairness preference based on China’s reality. According to different sympathy and envy coefficients, we can divide the inequity aversion preference into three typical types, and we research how a contractor’s different types of inequity aversion preferences impact revenue sharing coefficient of agreements, results of successful negotiations, and efficiency in negotiations. Results are as follows: it is advantageous for a contractor to maintain a modest inequity aversion for their own earnings and the degree of sympathy preference in inequity aversion has an important impact on the time to reach consensus while the degree of jealousy preference has no obvious effect. If contractors’ sympathy preference is maintained within a moderate range, it will achieve a higher success rate of negotiations in the negotiation process; the success rate of negotiation is affected largely by the agents’ sympathy preference, though it is also influenced by the jealousy preference, but it is not very sensitive.
Characterization of an NLRP1 Inflammasome from Zebrafish Reveals a Unique Sequential Activation Mechanism Underlying Inflammatory Caspases in Ancient Vertebrates

NLRP1 inflammasome is one of the best-characterized inflammasomes in humans and other mammals. However, the existence of this inflammasome in nonmammalian species remains poorly understood. In this study, we report the molecular and functional identification of an NLRP1 homolog, Danio rerio NLRP1 (DrNLRP1) from a zebrafish (D. rerio) model. This DrNLRP1 possesses similar structural architecture to mammalian NLRP1s. It can trigger the formation of a classical inflammasome for the activation of zebrafish inflammatory caspases (D. rerio Caspase [DrCaspase]–A and DrCaspase-B) and maturation of D. rerio IL-1β in a D. rerio ASC (DrASC)–dependent manner. In this process, DrNLRP1 promotes the aggregation of DrASC into a filament with DrASCCARD core and DrASCPYD cluster. The assembly of DrNLRP1 inflammasome depends on the CARD–CARD homotypic interaction between DrNLRP1 and DrASCCARD core, and PYD–PYD interaction between DrCaspase-A/B and DrASCPYD cluster. The FIIND domain in DrNLRP1 is necessary for inflammasome assembly. To understand the mechanism of how the two DrCaspases are coordinated in DrNLRP1 inflammasome, we propose a two-step sequential activation model. In this model, the recruitment and activation of DrCaspase-A/B in the inflammasome is shown in an alternate manner, with a preference for DrCaspase-A followed by a subsequent selection for DrCaspase-B. By using morpholino oligonucleotide–based knockdown assays, the DrNLRP1 inflammasome was verified to play important functional roles in antibacterial innate immunity in vivo. These observations demonstrate that the NLRP1 inflammasome originated as early as in teleost fish. This finding not only gives insights into the evolutionary history of inflammasomes but also provides a favorable animal model for the study of NLRP1 inflammasome-mediated immunology and diseases.