Miracle-dz/UniFAR-FTUs huggingface dataset:
An oxygen isotope test for the origin of Archean mantle roots

The origin of the peridotites that form cratonic mantle roots is a central issue in understanding the history and survival of Earth’s oldest continents. A long-standing hypothesis holds that the unusual bulk compositions of some cratonic peridotites stem from their origin as subducted oceanic serpentinite, dehydrated during subduction to form rigid buoyant keels (Schulze, 1986; Canil and Lee, 2009). We present oxygen isotope data from 93 mantle peridotites from five different Archean cratons to evaluate their possible origin as serpentinites. Cratonic mantle peridotite shows remarkably uniform δ18O values, identical to modern MORB-source mantle, that do not vary with bulk rock Si-enrichment or Ca-depletion. These data clearly conflict with any model for cratonic lithosphere that invokes serpentinite as a protolith for cratonic peridotite, and place additional constraints on cratonic mantle origins. We posit that the uniform δ18O was produced by sub-arc and/or MOR depletion processes and that the Si-enriched nature of some samples is unlikely to be related to slab melt infiltration. Instead, we suggest a peridotitic source of Si-enrichment, derived from ascending mantle melts, or a water-fluxed depleted mantle. These variably Si-enriched, cratonic mantle protoliths were then collisionally compressed into the thick cratonic roots that have protected Earth’s oldest continental crust for over 2.5 Gyr.
Conserving Biogeography: Habitat Loss and Vicariant Patterns in Endemic Squamates of the Cerrado Hotspot

Little is known about the threat levels and impacts of habitat loss over the Cerrado Squamate fauna. The region is under severe habitat loss due to mechanized agriculture, accelerated by changes in the Brazilian National Forest Code. The Squamate fauna of the Cerrado is rich in endemics and is intrinsically associated with its surrounding microhabitats, which make up a mosaic of phitophysiognomies throughout the region. Herein we evaluate current conservation status of Squamate biogeographic patterns in the Brazilian Cerrado, the single savanna among global biodiversity hotspots. To do so, we first updated point locality data on 49 endemic Squamates pertaining to seven non-random clusters of species ranges in the Cerrado. Each cluster was assumed to be representative of different biogeographic regions, holding its own set of species, herein mapped according to their extent of occurrence (EOO). We then contrasted these data in four different scenarios, according to the presence or absence of habitat loss and the presence or absence of the current protected area (PA) cover. We searched for non-random patterns of habitat loss and PA coverage among these biogeographic regions throughout the Cerrado. Finally, with the species EOO as biodiversity layers, we used Zonation to discuss contemporary PA distribution, as well as to highlight current priority areas for conservation within the Cerrado. We ran Zonation under all four conservation scenarios mentioned above. We observed that habitat loss and PA coverage significantly differed between biogeographic regions. The southernmost biogeographic region is the least protected and the most impacted, with priority areas highly scattered in small, disjunct fragments. The northernmost biogeographic region (Tocantins-Serra Geral) is the most protected and least impacted, showing extensive priority areas in all Zonation scenarios. Therefore, current and past deforestation trends are severely threatening biogeographic patterns in the Cerrado. Moreover, PA distribution is spatially biased, and does not represent biogeographic divisions of the Cerrado. Consequently, we show that biogeographic patterns and processes are being erased at an accelerated pace, reinforcing the urgent need to create new reserves and to avoid the loss of the last remaining fragments of once continuous biogeographic regions. These actions are fundamental and urgent for conserving biogeographic and evolutionary information in this highly imperiled savanna hotspot.
Using motion planning to map protein folding landscapes and analyze folding kinetics of known native structures

We present a novel approach for studying the kinetics of protein folding. The framework has evolved from robotics motion planning techniques called probabilistic roadmap methods (prms) that have been applied in many diverse fields with great success. In our previous work, we used a Prm-based technique to study protein folding pathways of several small proteins and obtained encouraging results. In this paper, we describe how our motion planning framework can be used to study protein folding kinetics. In particular, we present a refined version of our Prm-based framework and describe how it can be used to produce potential energy landscapes, free energy landscapes, and many folding pathways all from a single roadmap which is computed in a few hours on a desktop PC. Results are presented for 14 proteins. Our ability to produce large sets of unrelated folding pathways may potentially provide crucial insight into some aspects of folding kinetics, such as proteins that exhibit both two-state and three-state kinetics, that are not captured by other theoretical techniques.
Tree Pruning for New Search Techniques in Computer Games

This paper proposes a new mechanism for pruning a search game tree in computer chess. The algorithm stores and then reuses chains or sequences of moves, built up fromprevious searches. These move sequences have a built-in forward-pruning mechanism that can radically reduce the search space. A typical search process might retrieve a move from a Transposition Table, where the decision of what move to retrieve would be based on the position itself. This algorithm stores move sequences based on what previous sequences were better, or caused cutoffs. The sequence is then returned based on the current move only. This is therefore position independent and could also be useful in games with imperfect information or uncertainty, where the whole situation is not known at any one time. Over a small set of tests, the algorithm was shown to clearly out perform Transposition Tables, both in terms of search reduction and game-play results. Finally, a completely new search process will be suggested for computer chess or games in general.
Research of classification intersection hierarchical granularity algorithm based on concept lattice

Both of the lattice structure of the concept lattice and hierarchical models of the quotient space can be used to layering, and can be obtained figures under certain conditions. Because of the close links between the above, this paper uses the basic method of the lattice structure, upgrades the direct intersection concept at first, then makes up the additional points for this layer, and searches the equivalence classes with the quotient attribute functions, ensures the integrity of the domain in each layer. On this basis, a new algorithm is proposed which integrates hierarchical models and lattice structures to achieve the layering of classification intersecting situation. Example shows the method feasible.
Eosinophilic Granulomatosis with Polyangiitis: An Overview

Eosinophilic granulomatosis with polyangiitis (EGPA) is a multisystemic disorder, belonging to the small vessel anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis, defined as an eosinophil-rich and necrotizing granulomatous inflammation often involving the respiratory tract, and necrotizing vasculitis predominantly affecting small to medium-sized vessels, associated with asthma and eosinophilia. EGPA pathogenesis is not well known: HLA-DRB1*04 and *07, HLA-DRB4 and IL10.2 haplotype of the IL-10 promoter gene are the most studied genetic determinants. Among the acquired pathogenetic factors, the exposure to different allergens, infections, vaccinations, drugs, and silica exposure have been involved. Eosinophils are the most characteristic cells in EGPA and different studies have demonstrated their role as effector and immunoregulatory cells. EGPA is considered as a disease with a prevalent activation of the Th-2 cellular-mediated inflammatory response and also humoral immunity plays an important role. A link between B and T inflammatory responses may explain different disease features. EGPA typically develops into three sequential phases: the allergic phase, distinguished by the occurrence of asthma, allergic rhinitis, and sinusitis, the eosinophilic phase, in which the main pathological finding is the eosinophilic organ infiltrations (e.g., lungs, heart, and gastrointestinal system), and the vasculitic phase, characterized by purpura, peripheral neuropathy, and constitutional symptoms. ANCA (especially pANCA anti-myeloperoxidase) are present in 40–60% of the patients. An elevation of IgG4 is frequently found. Corticosteroids and cyclophosphamide are classically used for remission induction, while azathioprine and methotrexate are the therapeutic options for remission maintenance. B-cell depletion with rituximab has shown promising results for remission induction.
Handling missing data in software effort prediction with naive Bayes and EM algorithm

Background: Missing data, which usually appears in software effort datasets, is becoming an important problem in software effort prediction. Aims: In this paper, we adapt naïve Bayes and EM (Expectation Maximization) for software effort prediction, and develop two embedded strategies: missing data toleration and missing data imputation, to handle the missing data in software effort datasets. Method: The missing data toleration strategy ignores missing values in software effort datasets while missing data imputation strategy uses observed values to impute missing values. Results: Experiments on ISBSG and CSBSG datasets demonstrate that: 1)both proposed strategies outperform BPNN with classic imputation techniques as MI and MINI. Meanwhile, the imputation strategy outperforms toleration strategy in most cases and has produced the highest accuracy as 75.15%; 2) the unlabeled projects used in training prediction model has significantly improved the performances of effort prediction of naïve Bayes and EM with both strategies, especially when the size of training data to the size of unlabeled data is at a relatively optimal level; 3) each class of software effort data exactly corresponds to a Gaussian component for both ISBSG and CSBSG datasets. Conclusion: Although initial experiments on ISBSG data set demonstrate some promising aspects of the proposed strategies, we cannot draw that they can be generalized to be applied in all the other software effort datasets.
Dynamic content web applications: Crash, failover, and recovery analysis

This work assesses how crashes and recoveries affect the performance of a replicated dynamic content web application. RobustStore is the result of retrofitting TPC-W's on-line bookstore with Treplica, a middleware for building dependable applications. Implementations of Paxos and Fast Paxos are at the core of Treplica's efficient and programmer-friendly support for replication and recovery. The TPC-W benchmark, augmented with faultloads and dependability measures, is used to evaluate the behaviour of RobustStore. Experiments apply faultloads that cause sequential and concurrent replica crashes. RobustStore's performance drops by less than 13% during the recovery from two simultaneous replica crashes. When subject to an identical faultload and a shopping workload, a five-replicas RobustStore maintains an accuracy of 99.999%. Our results display not only good performance, total autonomy and uninterrupted availability, they also show that it is simple to develop efficient recovery-oriented applications using Treplica.
PDB_TM: selection and membrane localization of transmembrane proteins in the protein data bank

PDB_TM is a database for transmembrane proteins with known structures. It aims to collect all transmembrane proteins that are deposited in the protein structure database (PDB) and to determine their membrane-spanning regions. These assignments are based on the TMDET algorithm, which uses only structural information to locate the most likely position of the lipid bilayer and to distinguish between transmembrane and globular proteins. This algorithm was applied to all PDB entries and the results were collected in the PDB_TM database. By using TMDET algorithm, the PDB_TM database can be automatically updated every week, keeping it synchronized with the latest PDB updates. The PDB_TM database is available at http://www.enzim. hu/PDB_TM.
Cost Prediction Maps for Global Illumination

There is a growing demand from the media industry, including computer games, virtual reality and simulation, for increasing realism in real-time for their computer generated images. Despite considerable advances in processing power and graphics hardware, increasing scene complexity means that it is still not possible to achieve high fidelity computer graphics in a reasonable, let alone real, time on a single computer. Cost prediction is a technique which acquires knowledge of computational complexity within the rendering pipeline as the computation progresses and then uses this to best allocate the available resources to achieve the highest perceptual quality of an image in a time constrained system. In this paper we describe a method of acquiring computational cost complexity knowledge within a high fidelity graphics environment. This cost map may be used in combination with other perceptually derived maps to control a selective renderer in order to achieve the best perceptual quality results for a user specified frame-rate.
Clustering via Content-Augmented Stochastic Blockmodels

Much of the data being created on the web contains interactions between users and items. Stochastic blockmodels, and other methods for community detection and clustering of bipartite graphs, can infer latent user communities and latent item clusters from this interaction data. These methods, however, typically ignore the items' contents and the information they provide about item clusters, despite the tendency of items in the same latent cluster to share commonalities in content. We introduce content-augmented stochastic blockmodels (CASB), which use item content together with user-item interaction data to enhance the user communities and item clusters learned. Comparisons to several state-of-the-art benchmark methods, on datasets arising from scientists interacting with scientific articles, show that content-augmented stochastic blockmodels provide highly accurate clusters with respect to metrics representative of the underlying community structure.
The relationships of plasma adiponectin with a favorable lipid profile, decreased inflammation, and less ectopic fat accumulation depend on adiposity.

BACKGROUND The metabolic effects of adiponectin, including insulin sensitivity, seem to become stronger with increasing adiposity. Adiposity may also affect the relationship of adiponectin concentrations with serum lipid profile; markers of inflammation, atherosclerosis, and endothelial function; and ectopic fat accumulation. METHODS We measured plasma adiponectin concentrations, serum lipids, and serum markers of inflammation, atherosclerosis, and endothelial function in 242 Caucasians without type 2 diabetes. We also measured visceral adipose tissue with magnetic resonance tomography and liver and intramyocellular fat with (1)H magnetic resonance spectroscopy. RESULTS We divided the study participants into 2 groups: lean [mean (SE) total body fat, 26% (0.6%); n = 119] and obese [36% (0.6%); n = 123]. In the obese group, plasma adiponectin concentrations showed a strong positive association with concentrations of HDL cholesterol (P <0.0001) and negative associations with LDL cholesterol, triglycerides, high-sensitivity C-reactive protein, interleukin 6, apolipoprotein B(100), soluble E-selectin, soluble vascular cellular adhesion molecule 1, plasminogen activator inhibitor 1, leukocyte count, and liver and intramyocellular fat (all P <0.03). In the lean group, adiponectin showed a less strong association with HDL cholesterol (P = 0.005) and liver fat (P = 0.03) and no significant associations with the other variables (all P >0.10). High visceral adipose tissue was a strong predictor of low adiponectin concentrations, particularly in the obese group, and attenuated many of the significant relationships. CONCLUSIONS High adiponectin plasma concentrations are associated with favorable lipid profiles, decreased subclinical inflammation, decreased markers of atherosclerosis and endothelial function, and low ectopic fat accumulation, particularly in obese persons. Adiponectin may also have a concentration-related effect on the relationship between visceral adipose tissue and these metabolic characteristics, especially in obese persons.
Long-Term Intergenerational Persistence of Human Capital: An Empirical Analysis of Four Generations

Most previous studies of intergenerational transmission of human capital are restricted to two generations: how parents influence their children. In this study, we use a Swedish data set that links individual measures of lifetime earnings for three generations and data on educational attainment for four generations. We find that estimates obtained from data on two generations severely underestimate long-run intergenerational persistence in both labor earnings and educational attainments. Long-run social mobility is hence much lower than previously thought. We attribute this additional persistence to “dynastic human capital” — the influence on human capital of more distant family members than parents.
Energy-Aware Resource Allocation in Multi-mode Automotive Applications with Hard Real-Time Constraints

This paper presents an energy aware resource allocation approach that benefits from modal nature of hard real-time systems under consideration. The modal nature of considered applications made it possible to decrease the number of active cores consuming high power in certain modes or to switch into core states with lower power consumption, which lead to considerable energy savings while still not violating any of timing constraints. For the considered automotive use case, the number of required cores has been decreased by up to 75% in a particular mode and relatively low amount of data is to be migrated during the mode change. The trade-off between the amount of data to be migrated and energy dissipation in the subsequent state is also analysed.
Protection of spermatogenesis in mice against gamma ray induced damage by Hippophae rhamnoides

The radioprotective action of a preparation from Hippophae rhamnoides berries RH‐3, already reported to render >80% survival against whole body 10 Gy gamma irradiation, was further investigated with respect to the testicular system. RH‐3 was administered to mice 30 min before gamma irradiation (5 and 10 Gy) and histological parameters such as testis weight, sperm count, frequency of abnormal sperm, repopulation index, stem cell survival index and seminiferous tubular diameter were assessed on the 35th day. RH‐3 administration partially countered radiation induced reduction in testis weight, sperm count, repopulation index and stem cell survival index (p < 0.01). The increase in the frequency of abnormal sperm (15.17 ± 1.046%) caused by irradiation (5 Gy) was counteracted by pre‐irradiation treatment with RH‐3, which significantly decreased the level of abnormal spermatozoa to 7.99 ± 0.918% (p < 0.001), i.e. 52% abnormalities in comparison with 5 Gy irradiated group. RH‐3 treatment alone did not elicit any toxic or adverse effect on the process of spermatogenesis. The present study suggests that RH‐3 treatment protected spermatogenesis by enhancing the spermatogonial proliferation, enhancing the stem cell survival and reducing sperm abnormalities. The presence of polyphenolic flavonoids and tannins in the extract and the radical scavenging activity might be responsible for the radioprotective action of RH‐3.
Analysis of Head Gesture and Prosody Patterns for Prosody-Driven Head-Gesture Animation

We propose a new two-stage framework for joint analysis of head gesture and speech prosody patterns of a speaker towards automatic realistic synthesis of head gestures from speech prosody. In the first stage analysis, we perform hidden Markov model (HMM) based unsupervised temporal segmentation of head gesture and speech prosody features separately to determine elementary head gesture and speech prosody patterns, respectively, for a particular speaker. In the second stage, joint analysis of correlations between these elementary head gesture and prosody patterns is performed using Multi-Stream HMMs to determine an audio-visual mapping model. The resulting audio-visual mapping model is then employed to synthesize natural head gestures from arbitrary input test speech given a head model for the speaker. In the synthesis stage, the audio-visual mapping model is used to predict a sequence of gesture patterns from the prosody pattern sequence computed for the input test speech. The Euler angles associated with each gesture pattern are then applied to animate the speaker head model. Objective and subjective evaluations indicate that the proposed synthesis by analysis scheme provides natural looking head gestures for the speaker with any input test speech, as well as in ``prosody transplant" and ``gesture transplant" scenarios.
ATRIPPI: An Atom-residue Preference Scoring Function for Protein-protein Interactions

We present an ATRIPPI model for analyzing protein-protein interactions. This model is a 167-atom-type and residue-specific interaction preferences with distance bins derived from 641 co-crystallized protein-protein interfaces. The ATRIPPI model is able to yield physical meanings of hydrogen bonding, disulfide bonding, electrostatic interactions, van der Waals and aromatic-aromatic interactions. We applied this model to identify the native states and near-native complex structures on 17 bound and 17 unbound complexes from thousands of decoy structures. On average, 77.5% structures (155 structures) of top rank 200 structures are closed to the native structure. These results suggest that the ATRIPPI model is able to keep the advantages of both atom-atom and residue-residue interactions and is a potential knowledge-based scoring function for protein-protein docking methods. We believe that our model is robust and provides biological meanings to support protein-protein interactions.
An unsupervised color image segmentation algorithm for face detection applications

This paper presents an unsupervised color segmentation technique to divide skin detected pixels into a set of homogeneous regions which can be used in face detection applications or any other application which may require color segmentation. The algorithm is carried out in a two stage processing, where the chrominance and luminance information are used consecutively. For each stage a novel algorithm which combines pixel and region based color segmentation techniques is used. The algorithm has proven to be effective under a large number of test images.