Miracle-dz/UniFAR-FTUs huggingface dataset:
Escaping Deleterious Immune Response in Their Hosts: Lessons from Trypanosomatids

The Trypanosomatidae family includes the genera Trypanosoma and Leishmania, protozoan parasites displaying complex digenetic life cycles requiring a vertebrate host and an insect vector. Trypanosoma brucei gambiense, Trypanosoma cruzi, and Leishmania spp. are important human pathogens causing human African trypanosomiasis (HAT or sleeping sickness), Chagas’ disease, and various clinical forms of Leishmaniasis, respectively. They are transmitted to humans by tsetse flies, triatomine bugs, or sandflies, and affect millions of people worldwide. In humans, extracellular African trypanosomes (T. brucei) evade the hosts’ immune defenses, allowing their transmission to the next host, via the tsetse vector. By contrast, T. cruzi and Leishmania sp. have developed a complex intracellular lifestyle, also preventing several mechanisms to circumvent the host’s immune response. This review seeks to set out the immune evasion strategies developed by the different trypanosomatids resulting from parasite–host interactions and will focus on: clinical and epidemiological importance of diseases; life cycles: parasites–hosts–vectors; innate immunity: key steps for trypanosomatids in invading hosts; deregulation of antigen-presenting cells; disruption of efficient specific immunity; and the immune responses used for parasite proliferation.
Localization of Pronuclei of Human Zygotes using Texture Features from Multiple Focal Planes

We propose a technique for recovering the position and depth of pronuclei of human zygotes, from z-stacks acquired using Hoffman Modulation Contrast microscopy. We use Local Binary Pattern features for describing local texture, and integrate information from multiple neighboring areas of the stack, including those where the object to be detected would appear defocused; interestingly, such defocused areas provide very discriminative information for detection. We also show how the directional characteristics of the apparent lighting in HMC images, which is often considered an hindrance for automated processing, provides important information which is lost when using rotationally-invariant texture features. Experimental results confirm the effectiveness of our approach, which allows one to derive new 3D measurements for improved scoring of zygotes during In Vitro Fertilization.
Experiments with a robotic computer: Body, affect and cognition interactions

We present RoCo, the first robotic computer designed with the ability to move its monitor in subtly expressive ways that respond to and encourage its user's own postural movement. We use RoCo in a novel user study to explore whether a computer's “posture” can influence its user's subsequent posture, and if the interaction of the user's body state with their affective state during a task leads to improved task measures such as persistence in problem solving. We believe this is possible in light of new theories that link physical posture and its influence on affect and cognition. Initial results with 71 subjects support the hypothesis that RoCo's posture not only manipulates the user's posture, but also is associated with hypothesized posture-affect interactions. Specifically, we found effects on increased persistence on a subsequent cognitive task, and effects on perceived level of comfort.
Journal of Economic Behavior & Organization Trust, Trustworthiness and Social Networks: Playing a Trust Game When Networks Are Formed in the Lab

This paper investigates the impact of network formation on trust and trustworthiness. We run a laboratory experiment where, in sequence, networks are generated endogenously within an anonymous group and subjects play a trust game. The experimental design includes two main treatments and a baseline: in the baseline subjects play a trust game with no networks being formed, in treatment NT the network building phase precedes the trust game, and in treatment TN the network game is played at the end. This allows us to identify the two main factors through which networks impact on trust and trustworthi-ness: information accrued to subjects through social interaction (when this occurs first) and reputation (when it follows). We find that in NT, the overall level of trust is lower but offers are directed to more trustworthy recipients. A common past history matters in determining whom to trust (information value of networks). In TN, continuation play enforces higher levels of trust and trustworthiness (reputation and enforced reciprocity). Profits that subjects make in the trust game are higher in the presence of social interaction, and significantly so when network formation informs the decision of whom to trust.
MapReduce with Deltas

The MapReduce programming model is extended conservatively to deal with deltas for input data such that recurrent MapReduce computations can be more efficient for the case of input data that changes only slightly over time. That is, the extended model enables more frequent re-execution of MapReduce computations and thereby more up-to-date results in practical applications. Deltas can also be pushed through pipelines of MapReduce computations. The achievable speedup is analyzed and found to be highly predictable. The approach has been implemented in Hadoop, and a code distribution is available online. The correctness of the extended programming model relies on a simple
Industry Risk and Debt Contracting ∗

This paper shows that industry risk is priced in debt contracts by utilizing proprietary forward-looking industry risk rating scores from IBISWorld Inc. Overall industry risk includes three categories: growth risk, sensitivity risk and structural risk, all measured at the six-digit NAICS level. Our results, obtained using industry fixed-effect regressions and controlling for firm-level measures of credit risk, suggest loans issued to firms in riskier industries have higher spreads, smaller loan amounts, and shorter maturities. We further find that while growth risk and sensitivity risk generally represent higher risk to lenders, structural risk, which reflects competition, can be beneficial to lenders.
Disparity between dorsal and ventral networks in patients with obsessive-compulsive disorder: evidence revealed by graph theoretical analysis based on cortical thickness from MRI

As one of the most widely accepted neuroanatomical models on obsessive-compulsive disorder (OCD), it has been hypothesized that imbalance between an excitatory direct (ventral) pathway and an inhibitory indirect (dorsal) pathway in cortico-striato-thalamic circuit underlies the emergence of OCD. Here we examine the structural network in drug-free patients with OCD in terms of graph theoretical measures for the first time. We used a measure called efficiency which quantifies how a node transfers information efficiently. To construct brain networks, cortical thickness was automatically estimated using T1-weighted magnetic resonance imaging. We found that the network of the OCD patients was as efficient as that of healthy controls so that the both networks were in the small-world regime. More importantly, however, disparity between the dorsal and the ventral networks in the OCD patients was found in terms of graph theoretical measures, suggesting a positive evidence to the imbalance theory on the underlying pathophysiology of OCD.
Predicted Willingness of Irish Farmers to Adopt GM Technology

In this article, we use a probit model to assess the factors that will influence the decision of Irish farmers to adopt genetically modified (GM) technology should they be given a choice in the near future of selecting between GM and non-GM varieties of crops. The results from the probit model indicate that among the likely early adopters of GM technology in Ireland are farmers with large farm acreage who are specialist crop farmers and who have formal agricultural education together with access to high-quality soils. Contrary to expectations and theory, the farmer’s age was insignificant in the final specification of the model. Neither tenure nor profitability had any influence in determining the likelihood of adoption once farm size was accounted for, indicating that farm size may dominate other farm-level characteristics.
TimeML Events Recognition and Classification: Learning CRF Models with Semantic Roles

This paper analyzes the contribution of semantic roles to TimeML event recognition and classification. For that purpose, an approach using conditional random fields with a variety of morphosyntactic features plus semantic roles features is developed and evaluated. Our system achieves an F1 of 81.4% in recognition and a 64.2% in classification. We demonstrate that the application of semantic roles improves the performance of the presented system, especially for nominal events.
High-velocity regions in planetary nebulae

The internal velocity fields of planetary nebulae are studied with a resolution of 5 km s −1 . W e analyse deep echelle spectra from three nebulae in the Galactic bulge, the Sagittarius Dwarf and the Small Magellanic Cloud (SMC). No effects of metallicity are seen, except possibly a slower onset of the fast wind from the central star. Robust evidence is found for the existence of a highvelocity shock at the inner edges of the nebulae. Such a shock is predicted in hydrodynamical models but had not previously been observed. The shock gas is accelerated by the fast wind from the central star. A similar shock at the outer edges traces the expansion of the ionized shell into the ambient asymptotic giant branch (AGB) wind. Evidence for localized regions of high velocity is also found from lines of intermediate excitation, for two of the nebulae. We explore several possible interpretations: (i) an embedded shock at intermediate radii, as predicted by hydrodynamic models at the position of the outer edge of the swept-up inner shell; (ii) deviations from spherical symmetry, where in some directions the intermediate-excitation lines extend into the region of the outer shock; (iii) an intermediate swept-up shell, as seen in some Galactic planetary nebulae. The remaining nebula, with a low-mass Wolf‐Rayet central star ([WC] star), shows strong turbulence. This may trace a superposition of many embedded shock-lets. We suggest a relation to the time-variable [WC] wind, giving a planetary nebula subjected to a multitude of sound waves.
Deriving a Domain Specific Test Collection from a Query Log

Cultural heritage, and other special domains, pose a particular problem for information retrieval: evaluation requires a dedicated test collection that takes the particular documents and information requests into account, but building such a test collection requires substantial human effort. This paper investigates methods of generating a document retrieval test collection from a search engine’s transaction log, based on submitted queries and user-click data. We test our methods on a museum’s search log file, and compare the quality of the generated test collections against a collection with manually generated and judged known-item topics. Our main findings are the following. First, the test collection derived from a transaction log corresponds well to the actual search experience of real users. Second, the ranking of systems based on the derived judgments corresponds well to the ranking based on the manual topics. Third, deriving pseudo-relevance judgments from a transaction log file is an attractive option in domains where dedicated test collections are not readily available.
On consistent migration of flows in SDNs

We study consistent migration of flows, with special focus on software defined networks. Given a current and a desired network flow configuration, we give the first polynomial-time algorithm to decide if a congestion-free migration is possible. However, if all flows must be integer or are unsplittable, this is NP-hard to decide. A similar problem is providing increased bandwidth to an application, while keeping all other flows in the network, but possibly migrating them consistently to other paths. We show that the maximum increase can be approximated arbitrarily well in polynomial time. Current methods as RSVP-TE consider unsplittable flows and remove flows of lesser importance in order to increase bandwidth for an application: We prove that deciding what flows need to be removed is an NP-hard optimization problem with no PTAS possible unless P = NP.
Evolutionary Dynamics of GLD-1–mRNA Complexes in Caenorhabditis Nematodes

Given the large number of RNA-binding proteins and regulatory RNAs within genomes, posttranscriptional regulation may be an underappreciated aspect of cis-regulatory evolution. Here, we focus on nematode germ cells, which are known to rely heavily upon translational control to regulate meiosis and gametogenesis. GLD-1 belongs to the STAR-domain family of RNA-binding proteins, conserved throughout eukaryotes, and functions in Caenorhabditis elegans as a germline-specific translational repressor. A phylogenetic analysis across opisthokonts shows that GLD-1 is most closely related to Drosophila How and deuterostome Quaking, both implicated in alternative splicing. We identify messenger RNAs associated with C. briggsae GLD-1 on a genome-wide scale and provide evidence that many participate in aspects of germline development. By comparing our results with published C. elegans GLD-1 targets, we detect nearly 100 that are conserved between the two species. We also detected several hundred Cbr-GLD-1 targets whose homologs have not been reported to be associated with C. elegans GLD-1 in either of two independent studies. Low expression in C. elegans may explain the failure to detect most of them, but a highly expressed subset are strong candidates for Cbr-GLD-1-specific targets. We examine GLD-1-binding motifs among targets conserved in C. elegans and C. briggsae and find that most, but not all, display evidence of shared ancestral binding sites. Our work illustrates both the conservative and the dynamic character of evolution at the posttranslational level of gene regulation, even between congeners.
Time to pregnancy and semen parameters: a cross-sectional study among fertile couples from four European cities.

BACKGROUND In fertile populations, little is known about the association between semen parameters and time to pregnancy (TTP). METHODS Pregnant women from Copenhagen, Edinburgh, Paris and Turku who conceived without medical intervention were asked for their TTP (942 couples), and their partners provided a semen sample. The proportion of morphologically normal sperm and the multiple anomalies index (MAI, ratio of the total number of anomalies to the number of abnormal sperm) were centrally estimated. We estimated rate ratios for the occurrence of a pregnancy by a discrete survival model, adjusted for sexual activity and female factors affecting fecundity. RESULTS Increasing sperm concentration influenced TTP up to 55 x 10(6)/ml. The proportion of morphologically normal sperm influenced TTP up to 39% according to David's criteria, and this association held among the subjects with a sperm concentration >55 x 10(6)/ml. For strict criteria, the threshold value was 19% normal sperm. An increase of 0.5 in MAI was associated with an adjusted rate ratio for the occurrence of a pregnancy of 0.68 (95% confidence interval: 0.54-0.85). CONCLUSIONS These results highlight the importance of sperm morphology parameters and indicate that the effect of proportion of normal sperm on TTP may be independent of sperm concentration.
Toll-like receptors as developmental tools that regulate neurogenesis during development: an update

Neurogenesis, the process of generating new neurons in the brain, fascinates researchers for its promise to affect multiple cognitive and functional processes in both health and disease. Many cellular pathways are involved in the regulation of neurogenesis, a complexity exemplified by the extensive regulation of this process during brain development. Toll-like receptors (TLRs), hallmarks of innate immunity, are increasingly implemented in various central nervous system plasticity-related processes including neurogenesis. As TLRs are involved in neurodegenerative disorders, understanding the involvement of TLRs in neurogenesis may hold keys for future therapeutic interventions. Herein, we describe the current knowledge on the involvement of TLRs in neurogenesis and neuronal plasticity and point to current knowledge gaps in the field.
Quality control for UMTS-AMR speech channels

In UMTS speech transmissions, the Adaptive Multi-Rate (AMR) speech codec is employed to allow for a dynamic assignment of data rates to individual users. The control of AMR modes is based on quality measurements of the transmission channel and aims at the maximization of speech quality by selecting the mode which is best suited to the current interference situation. In contrast to GSM, a reduction of AMR modes also leads to an increased cell capacity in UMTS. In this paper, a decentralized method for AMR mode switching is presented which is based on individual softbit measurements at the Viterbi channel decoder and optimizes the speech quality for a wide range of channel conditions. This method was developed by optimizing the AMR mode switching thresholds with respect to PESQ speech quality scores. The second part of the paper describes a new instrumental non-intrusive method for speech quality measurement by the evaluation of UMTS transmission parameters for application to UMTS-AMR speech transmissions. High correlations with the reference PESQ scores were observed.
Perceptual image compression for data transmission on the battlefield

This paper treats the compression of Synthetic Aperture Radar (SAR) imagery. SAR images are difficult to compress, relative to natural images, because SAR contains an inherent high frequency speckle. Today's state-of-the-art coders are designed to work with natural images, which have a lower frequency content. Thus, their performance on SAR is under par. In this paper we given an overview performance report on the popular compressions techniques, and investigate three approaches to improve the quality of SAR compression at low- bit rates. First, we look at the design of optimal quantizers which we obtain by training on SAR data. Second, we explore the use of perceptual properties of the human visual system to improve subjective coding quality. Third, we consider the use of a model that separates the SAR image into structural and textural components. The paper concludes with a subjective evaluation of the algorithms based on the CCIR recommendation for the assessment of picture quality.
On coalition formation with sparse synergies

We consider coalition formation problems for agents with an underlying synergistic graph, where edges between agents represent some vital synergistic link, such as communication, trust, or physical constraints. A coalition is infeasible if its members do not form a connected subgraph, meaning parts of the coalition are isolated from others. Current state-of-the-art coalition formation algorithms are not designed for problems over synergistic graphs. They assume that all coalitions are feasible and so involve redundant computation when this is not the case. Accordingly, we propose algorithms, namely D-SlyCE and DyCE, to enumerate all feasible coalitions in a distributed fashion and find the optimal feasible coalition structure respectively. When evaluated on a variety of synergistic graphs, D-SlyCE is up to 660 times faster while DyCE is up to 7 x 104 times faster than the state-of-the-art algorithms. For particular classes of graphs, D-SlyCE is the first to enumerate valid coalition values for up to 50 agents and DyCE is the first algorithm to find the optimal coalition structure for up to 30 agents in minutes as opposed to months for previous algorithms.
Ontogenetic patterns of limb loading, in vivo bone strains and growth in the goat radius

SUMMARY As tetrapods increase in size and weight through ontogeny, the limb skeleton must grow to accommodate the increases in body weight and the resulting locomotor forces placed upon the limbs. No study to date, however, has examined how morphological changes in the limb skeleton during growth reflect ontogenetic patterns of limb loading and the resulting stresses and strains produced in the limbs. The goal of this study was to relate forelimb loads to in vivo bone strains in the radius of the domestic goat (Capra hircus) across a range of gaits and speeds through ontogeny while observing how the growth patterns of the bone relate to the mechanics of the limb. In vivo bone strains in the radius were recorded from two groups of juvenile goats (4 kg, 6 weeks and 9 kg, 15 weeks) and compared with previously reported strain data for the radius of adult goats. Ontogenetic strain patterns were examined in relation to peak forelimb ground reaction forces, ontogenetic scaling patterns of cross-sectional geometry and bone curvature, and percentage mineral ash content. Peak principal longitudinal tensile strains on the cranial surface and compressive strains on the caudal surface of the radius increased during ontogeny but maintained a uniform distribution, resulting in the radius being loaded primarily in bending through ontogeny. The increase in strain occurred despite uniform loading (relative to body weight) of the forelimb through ontogeny. Instead, the increase in bone strain resulted from strong negative growth allometry of the cross-sectional area (∝M0.53) and medio-lateral and cranio-caudal second moments of area (IML∝M1.03, ICC∝M0.84) of the radius and only a small increase (+2.8%) in mineral ash content. Even though bone strains increased with growth and age, strains in the younger goats were small enough to suggest that they maintain safety factors at least comparable with adults when moving at similar absolute speeds. Increased variability of loading in juvenile animals may also favor the more robust dimensions of the radius, and possibly other limb bones, early in growth.
Randomized approximations of operators and their spectral decomposition for diffusion based embeddings of heterogeneous data

Modern sensing platforms acquire heterogeneous data collected from multiple sensing modalities. We are then faced with the challenge of fusing the already collected heterogeneous data for effective use in such applications as data classification, segmentation, or target detection. Data fusion is a non-trivial problem and many existing approaches are either highly dependent on the types of data or fuse the information post classification. When the data is high dimensional and possesses a large number of data points (pixels), such as is the case for Hyperspectral Satellite Imagery, it can be burdensome on even the most efficient algorithms. Previous techniques of data integration have relied harmonic analysis methods to fuse data and produce low dimensional representations of large heterogeneous datasets. These techniques construct data-driven operators whose spectral decomposition creates a representation of the data. The bottlenecks of this approach are in the construction of the operator and its spectral decomposition, which may require a significant computational cost. Thus, we introduce randomized approximations at the most computationally intensive steps to significantly reduce the computational cost with minimal loss of fidelity, thus enabling the practical use of these highly sophisticated and geometrically reliable methods.